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OUTUBRO 2007 Seropédica

UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO INSTITUTO DE TECNOLOGIA

DEPARTAMENTO DE ENGENHARIA

Elaboração de metodologia de cálculo para neutraliz ação de emissão de carbono com plantio de seringueiras ( Hevea Brasiliensis ).

C:\mcaraujo\DEFESA DE ESTÁGIO\Relatório de defesa de estágio - FIRJAN 2007_d.doc 2

Instituições colaboradoras:

Universidade Federal Rural do Rio de Janeiro – UFRRJ / IT / DE

Serviço Brasileiro de Apoio às Micro e Pequenas Empresas - SEBRAE-RJ

Responsáveis pela elaboração da proposta:

Orientador: José Mário de Oliveira Ramos (B. Sc. Química Industrial)

Federação das Indústrias do Estado do Rio de Janeiro– FIRJAN

Co-Orientador: Marcello Ramos (B. Sc. Ciências Econômicas)

Instituto Tecnológico da Borracha – ITeB

Professor Orientador: Roberto Precci Lopes (D. Sc. Engenharia Agrícola)

Instituto de Tecnologia / Departamento de Engenharia – UFRRJ / IT / DE

Estagiário: Matheus Concolato de Araújo (Graduando Engenharia Agrícola)

Universidade Federal Rural do Rio de Janeiro – UFRRJ


SUMÁRIO

1. Apresentação 04

2. Introdução 05

2.1. O efeito estufa 05

2.2. O protocolo de kyoto 07

2.3. O mercado de carbono 09

2.4. Contexto 11

2.4.1. A heveicultura 11

2.4.2. Oportunidade de mercado 12

2.4.3. A cadeia produtiva da borracha 15

3. Justificativa 16

4. Objetivo geral 17

5. A contribuição da pequena empresa na redução dos GEE`s 18

6. Metodologia de cálculo específico para redução de emissões 19

6.1. Base teórica para cálculo do montante de CO2 equi. – inventário de emissões

19

6.1.1. Emissões indiretamente relacionadas às ações da empresa 20

6.1.2. Emissões diretamente relacionadas às ações da empresa 23

6.2. Base teórica para o cálculo da quantidade de árvores necessárias 25

7. O que se espera deste projeto 29

8. Metodologia de monitoramento 29

9. Exemplo de aplicação 30

9.1. Projeto de neutralização de emissões da III SEMEAGRI 30

10. Documentos anexos 37

11. Literatura consultada 38


1. APRESENTAÇÃO

O projeto ora apresentado visa dar subsídios técnicos, com vistas à

implantação de um programa para redução dos gases de efeito estufa (GEE`s),

por meio da neutralização do carbono emitido em eventos empresariais e

atividades desenvolvidas pelas micro e pequenas empresas do ramo da

borracha pela implantação e monitoramento do plantio de seringueiras (Hevea

Brasiliensis), no Estado do Rio de Janeiro.

A proposta se fundamenta pelo fato de que plantios de seringueira se

constituem em uma alternativa sócio-econômica e ambiental, adequada a

pequenos e médios produtores, uma vez que gera emprego e renda o ano

todo, contribui para a redução do êxodo rural e seqüestra o carbono da

atmosfera em quantidades significativas, na ordem de 90 toneladas de CO2 ou

330,3 toneladas de CO2 equivalente (CO2 equi) por planta de 15 anos de idade

(Oliveira et al, 2006), gerando créditos de carbono aos heveicultores e ao país.

Somando-se a isto, a cultura é reflorestadora e contribui para a conservação do

solo e da água, abrigo e alimentação da fauna (mamíferos, aves, insetos).

Atualmente, a área cultivada com seringueira no Brasil é de

aproximadamente 100.000 ha, mas, para o pais atingir a auto-suficiência em

borracha natural até 2030 seria necessário o plantio de 50.000 ha•ano-1. Assim,

daqui a 25 anos, o Brasil teria 1,25 milhões de hectares reflorestados com

seringueira, com ótimas repercussões ambientais, sociais e econômicas

favoráveis à nossa imagem externa e com redução do déficit na nossa balança

comercial com a implantação da borracha.

Além disto, a mitigação dos GEE`s através do plantio de seringueiras se

reveste de importância fundamental ao desenvolvimento da sociedade

moderna, uma vez que reduziria a demanda por borracha sintética que é um

insumo altamente poluente e derivado de petróleo. O que torna a seringueira

singular é sua capacidade de produzir borracha natural com características de

elasticidade, plasticidade, isolamento térmico, resistência à fricção,

impermeabilidade aos líquidos e gases, bem como isolamento elétrico,

imprescindíveis para a fabricação de pneumáticos e de uma centena de

artefatos consumidos em todo mundo com atributos técnicos e ambientais sem

comparação às borrachas sintéticas.


No âmbito regional o desenvolvimento de projetos de reflorestamento

em larga escala, além de cumprir os objetivos em relação ao efeito estufa, trás

consigo uma série de adicionalidades: geração de empregos; melhoria da

qualidade ambiental, principalmente no que diz respeito à preservação dos

recursos hídricos, do solo e da biodiversidade; viabilização do uso múltiplo do

espaço; entre outras.

Desta forma, através dos reflorestamentos é possível melhorar a

qualidade ambiental de regiões degradadas e contribuir ao mesmo tempo para

um desenvolvimento local e regional mais sustentável além do benefício global

que é a fixação do carbono.

2. INTRODUÇÃO

Entender o comportamento do clima global continua sendo um grande

desafio para cientistas e ambientalistas. A história do planeta mostra que as

alterações climáticas, quando são bruscas, podem causar a extinção de

espécies, como ocorreu há cerca de 65 milhões de anos, quando segundo

estudos científicos, um asteróide gigante teria colidido com a Terra, gerando

tanta poeira cósmica que o mundo teria ficado no escuro e a temperatura caído

bruscamente. Em conseqüência disso, as plantas não puderam crescer e

muitos animais, como os dinossauros, teriam sido extintos por falta de comida

(Junior & Barroso; 2006).

Há milênios o homem sofre os caprichos do clima, mas foi se adaptando.

As sucessivas eras glaciais fizeram o ser humano migrar e aprender a viver em

novos ambientes e desenvolver a capacidade de inovar para melhorar as

condições de vida.

Mas o progresso econômico e o crescimento populacional

impulsionaram atividades que causam alterações no meio ambiente.

Atualmente, os poluentes lançados na atmosfera pela indústria, pelos veículos

e pela agropecuária estão interferindo nos ciclos naturais do clima global.

2.1. O EFEITO ESTUFA

As previsões sobre o clima global são motivos de polêmica. Acirram-se

as negociações em acordos internacionais, marcados por interesses


econômicos e políticos. Há, contudo, um consenso no mundo científico: está

ocorrendo o aquecimento global. Segundo o Painel Intergovernamental sobre

Mudança do Clima (IPCC, sigla em inglês), que reúne cerca de mil cientistas, a

temperatura do planeta no século XX aumentou em média 0,6 ºC, sendo a

década de 1990 a mais quente de toda a história. Até 2100, a Terra poderá

esquentar até 5,8 ºC, ou seja, dez vezes mais que o aumento do século XX.

A elevação da temperatura está sendo causada pelo aumento dos gases

que formam o efeito estufa, que é um fenômeno natural. A presença de

carbono na atmosfera é essencial para garantir que a temperatura oscile dentro

dos limites necessários para a existência da vida na Terra. A energia do sol, ao

atingir a superfície do planeta, transforma-se em calor e aquece o ambiente.

Uma parte desse calor, porém é refletida e volta para o espaço. Mas o vapor

d’água, o carbono e outros gases existentes na atmosfera formam uma redoma

que bloqueia e acaba retendo parte das radiações solares refletidas pela

superfície. Sem essa camada protetora, a temperatura média do planeta seria

de 19 ºC negativos. Graças ao efeito estufa, ela é de 14 ºC positivos.

O problema é que o dióxido de carbono (CO2), o metano (CH4) e o óxido

nitroso (N2O), lançados pelo homem, estão engrossando esse “cobertor”. A

queima de petróleo, carvão e gás natural por indústrias, automóveis e usinas

termoelétricas libera grande quantidade de dióxido de carbono no ar. Soma-se

a isso a destruição das florestas, cujo carbono armazenado nas árvores escapa

para a atmosfera. Outras atividades, como a criação de gado e o cultivo de

arroz, emitem metano e óxido nitroso. Abaixo podemos observar (Figura1) o

cenário de emissões no mundo. Se as emissões continuarem a aumentar, é

quase certo que no século XXI os níveis de dióxido de carbono duplicarão em

relação à época pré-industrial. Difícil prever como isso afetaria a vida no

planeta, pois o clima global é um sistema complexo.


2.2. O PROTOCOLO DE KYOTO

O Protocolo de Kyoto, firmado em dezembro de 1997, pelas 186 partes

da Convenção-Quadro das Nações Unidas para Mudança do Clima –

CQNUMC1, foi a pedra fundamental para a conscientização dos agentes

econômicos quanto aos riscos inerentes à mudança global do clima, quando

estabeleceu (dentro do princípio de responsabilidades comuns, porém

diferenciadas) metas para a redução das emissões antrópicas de Gases do

Efeito Estufa – GEE, em média 5% abaixo dos níveis verificados em 1990, para

os países (partes) listados em seu Anexo I, ou seja, países desenvolvidos, para

o período de 2008 a 2012, convencionado como primeiro período de

compromisso.

Com o objetivo de reduzir o custo marginal da redução das emissões

das partes listadas no Anexo I, o Protocolo contempla três mecanismos de

flexibilização:

1 O texto da Convenção-Quadro das Nações Unidas para Mudança do Clima – CQNUMC, foi adotado pela ONU em 9 de maio de 1992, sendo aberta para assinatura durante a Rio 92 e posteriormente até junho de 1993. A Convenção entrou em vigor em 21 de março de 1994.

Figura 1 – Situação mundial da emissão de CO 2

Fonte: Júnior e Barroso, 2006 - Banco Mundial, Dado s de 1999.


� O Comércio de Emissões (Emissions Trading): permite que partes do

Anexo I que conseguirem reduzir suas emissões de GEE além da meta

estabelecida pelo Protocolo, podem comercializar esse excedente com

outras partes do Anexo I;

� A Implementação Conjunta (Joint Implementation): permite que partes

do Anexo I participem em projetos de redução de emissões de GEE em

outras partes do Anexo I. As reduções resultantes desses projetos

podem ser divididas entre essas partes e utilizadas para atingir suas

metas; e

� O Mecanismo de Desenvolvimento Limpo – MDL (Clean Development

Mechanism – CDM): permite que partes do Anexo I invistam em projetos

de redução de emissões ou comprem as reduções de emissões de

projetos desenvolvidos em partes não listadas no Anexo I. Essas partes

do Anexo I podem utilizar essas reduções de emissões para atingir suas

metas. Portanto, esse é o único mecanismo de flexibilização do

Protocolo que se aplica ao Brasil, que não é uma parte listada no Anexo

I. Os procedimentos desse mecanismo foram estabelecidos nos Acordos

de Marraquesh, em novembro de 2001, na Sétima Conferência das

Partes – CoP-7.

Para que o Protocolo entrasse em vigor, ficou estabelecido que seria

necessária sua ratificação, aceitação, aprovação ou adesão por: (i) pelo

menos, 55 das partes da CQNUMC e (ii) por partes, listadas no Anexo I, que

contabilizem conjuntamente, pelo menos, 55% das emissões de GEE em 1990.

Em março de 2001, o Presidente George W. Bush declarou que os

Estados Unidos, responsáveis por 36,1% das emissões de GEE em 1990,

nunca ratificariam o Protocolo, pois prejudicaria financeiramente a economia

americana, deixando, sua entrada em vigor, condicionada à ratificação de

todos os países industrializados, com exceção da Austrália que seguiu a

iniciativa americana.

Convém ressaltar, que o modelo estabelecido pelo Protocolo, de

estabelecimento de metas para as emissões, com um sistema de negociação


de emissões acoplado, foi trazido para a arena das negociações internacionais

pelos Estados Unidos.

2.3. O MERCADO DE CARBONO

Apesar dessa indiscutível indefinição, o Protocolo vêm cumprindo o

papel de mudar o paradigma da ordem econômica mundial, através da

incorporação da mudança climática na função utilidade dos agentes. As

evidências podem ser notadas nas iniciativas correntes no emergente mercado

de reduções de emissões, isto é, mercado de carbono, conforme podemos

observar na figura 2.

Atualmente, existem dois tipos de ativos sendo negociados no mercado:

� Permissões de emissão (emission allowances) alocadas num regime de

metas e negociação (cap and trade) como, por exemplo, as AAUs

(Assigned Amount Units) do Protocolo de Kyoto;

Figura 2 – Ações dese nvolvidas para redução dos GEE`s - Cenário Mundial Fonte: Campos et al ., 2004 - PricewaterhouseCoopers. Emission critical, 2004.


� Reduções de emissão baseadas em projetos (project-based emission

reductions), isto é, oriundas de atividades de projeto que reduzem as

emissões quando comparadas a emissões que aconteceriam na

ausência do projeto.

Dessa forma, pode-se segmentar o mercado conforme mostrado na figura 3.

Até o terceiro mês de 2006, com uma negociação estimada de reduções

de emissões baseadas em projetos de 79 milhões de toneladas de CO2, as

reduções classificadas como Kyoto Pre-Compliance, ou seja, para serem

utilizadas no regime de Kyoto, caso venha a vigorar, representam,

aproximadamente, 90% do volume negociado.

De uma forma geral, o mercado de carbono hoje se encontra dividido em

dois segmentos: (i) Kyoto, o qual é capitaneado pela União Européia, e (ii) Não-

Kyoto, cujo principal ator é os Estados Unidos.

Figura 3 – Segmentação do Mercado - Transações Baseadas em Projetos Fonte: Campos et al ., 2004 - Franck Lecocq, Karan Capoor, PCF plus Rese arch, World Bank. State and Trends of Carbon Market, 2006. Based on data and insights provided by Evolut ion Markets LLC, Natsource LLC, and PointCarbon.


2.4. CONTEXTO

2.4.1. A HEVEICULTURA

A produção mundial de borracha natural em 2005 foi de 8.682 mil

toneladas, para um consumo de 8.742 mil toneladas, do qual mais de 79% é

originária do Sudeste Asiático. Em 2005, o Brasil produziu somente 100 mil

toneladas, cerca de 1% da produção mundial, mesmo possuindo extensas

áreas, clima e solo, infra-estrutura, estabilidade política e mercado consumidor

favorável ao desenvolvimento dessa cultura (vide Figura 4). A seringueira é

uma planta cujo habitat natural é a região Amazônica e tem o nome científico

de Hevea brasiliensis.

Apesar de todas as condições favoráveis ao desenvolvimento da cultura

da seringueira e o Brasil ser o seu “berço”, o país importa cerca de dois terços

do consumo interno de borracha natural, principalmente dos países asiáticos.

Assim é que apesar da excelente capacidade de desenvolver a produção

interna, existem desafios a serem superados para tirar o Brasil do papel de

altamente dependente do produto importado, para voltar a sua condição

original de exportador.

2.4.2. OPORTUNIDADE DE MERCADO

O mercado de borracha natural no Brasil e no mundo é comprador desta

importante commodity. O Brasil importa dois terços do que consome (Figura 5)

e mundialmente prevê-se um déficit de 2,5 a 4 milhões de toneladas em 2030.

A reversão do quadro atual da produção mundial e a inserção do Brasil

nesse cenário competitivo constitui-se no grande desafio do país.

Figura 4 – Produção e Consumo Mundial de Borracha Natural. Fonte: Instituto Agronômico de Campinas - IAC


O custo da borracha natural produzida no Brasil é competitivo em

relação a outros países. Apesar da baixa quantidade que o Brasil produz

atualmente, o país possui capacidade de aumentar sua produção, tornando-se

futuramente exportador dessa commodity, seguindo exemplos de iniciativas

como a do Estado de São Paulo que possui 14 milhões de hectares aptos a

heveicultura e, em 2005, foi responsável por 60% da borracha produzida no

país.

Planta-se seringueira desde os Estados da região Norte até o norte e o

noroeste do Paraná. Assim é que estudos têm sido realizados visando inserir o

Estado do Rio de Janeiro entre os produtores desta importante matéria prima,

principalmente tendo em vista que se trata do segundo maior consumidor de

borracha natural do País. Na figura 6 é apresentado o mapa edafoclimático

para o cultivo da seringueira no Estado do Rio de Janeiro realizado pela

Embrapa Solos e no Quadro 1 encontram-se listados os Municípios aptos ao

cultivo da seringueira no Estado do Rio de Janeiro, segundo o Zoneamento das

áreas aptas ao cultivo da espécie, realizado pela Embrapa Solos, (Carmo et al;

2005).

Figura 5 – Produção, Importação e Consumo de Borracha Natural no Brasil. Fonte: Instituto Agronômico de Campinas - IAC


QUADRO 1. Regiões e municípios do Estado do Rio de Janeiro com melhor aptidão agrícola para o cultivo da seringueira.

CENTRO SUL FLUMINENSE

MÉDIO PARAÍBA

BAIXADAS LITORÂNEAS *

NOROESTE FLUMINENSE NORTE SERRANA

Sapucaia Barra do Piraí Silva Jardim Bom Jesus do Itabapoana São Fidélis Santa Maria

Madalena

Areal Piraí Casimiro de Abreu Varre e Sai Conceição

de Macabú Trajano de Morais

Três Rios Pinheiral Rio Bonito Porciúncula Bom Jardim

Levi Gasparian Rio Claro Cachoeira de Macacú Natividade Macuco

Paraíba do Sul Volta Redonda Laje do Muriaé Cantagalo

Pati de Alferes Barra Mansa Miracema Cordeiro

Miguel Pereira Porto Real Cambuci Duas Barras

Vassouras Resende Itaperuna Carmo Paulo de Frontin

Valença S.J. Vale Rio Preto

MU

NIC

ÍPIO

S

Mendes Rio das Flores São Sebastião do Alto

Fonte: Carmo et al., EMBRAPA-Solos, 2005.

Figura 6 – Mapa edafoclimático para o cultivo da seringueira no Estado do Rio de Janeiro. Fonte: Carmo et al; 2005.


Apesar do Brasil ser um grande produtor de borracha sintética, que é um

produto altamente poluente e derivado de petróleo, a borracha natural é uma

matéria-prima estratégica utilizada na manufatura de mais de 50.000 produtos,

que incluem materiais médico-hospitalares, calçados, pneus, material bélico e

outros, em função de características que a tornam insubstituível, como

elasticidade, flexibilidade, resistência à abrasão e a corrosão, impermeabilidade

e fácil adesão a tecidos e ao aço (Costa et al., 2000; Gonçalves et al., 2001).

Outro fator que gera grandes oportunidades é que a heveicultura (cultivo

da seringueira) é uma atividade de forte apelo sócio-econômico e ambiental, e

sua expansão trará grandes benefícios à população rural. Essa cultura é

conhecida também pela sua capacidade de geração de trabalho permanente,

bem como pelo caráter intensivo no emprego da mão-de-obra, uma vez que a

sua exploração não é mecanizada. Essa atividade reserva espaço ao trabalho

da mulher, tendo em vista que a sangria é uma prática que exige

especialização, habilidade, sensibilidade e não é associada a grande esforço

físico.

A participação da mão-de-obra no custo total é da ordem de 20% a 30 %

na fase de formação do seringal, e de 20% a 35% na fase de produção,

dependendo do sistema de sangria adotado. Como os agricultores familiares

não têm custos fixos elevados e nem encargos sociais, tornam-se mais

competitivos no mercado globalizado, e devem ser incluídos nos programas de

fomento e expansão da cultura. A heveicultura é uma boa opção para

pequenos agricultores e assentados da reforma agrária, desde que estejam

organizados em associações e cooperativas e tenham assistência técnica

especializada, ações essas inseridas na proposta deste trabalho.

Do ponto de vista do desenvolvimento econômico e social, existe um alto

potencial de geração de renda para alívio da pobreza rural, dado que cerca de

85% da produção brasileira é feita por MPEs2 rurais. Estudos do ITeB indicam

que o retorno sobre o investimento da cultura da borracha pode chegar a 31%,

gerando para uma família com uma propriedade de 3 hectares, uma renda

mensal de cerca de R$ 1,2 mil3. Podendo esta cultura ser consorciada com

2 MPEs: Médias e pequenas propriedades rurais. 3 Fonte: ITeB (Instituto Tecnológico da Borracha)


outra, essa renda pode aumentar, despertando o interesse e empenho dos

agricultores.

2.4.3. A CADEIA PRODUTIVA DA BORRACHA

A cadeia produtiva da borracha natural, como ilustrado na figura 7, é

constituída por quatro setores: 1) produção (heveicultura e extrativismo nos

seringais nativos); 2) beneficiamento (usinas); 3) indústrias (pneumáticos e

artefatos); 4) comércio e prestação de serviços; além de um agente inicial para

insumos e o consumidor final, os quais atuam em seqüência e são

interdependentes.

Consumidor final

Setor comercial e prestador de

serviços

Setor industrial

Setor de beneficiamento

Setor produtivo

InsumosConsumidor

finalConsumidor

final


serviços


serviços

Setor industrial

Setor industrial



Setor produtivo

Setor produtivo

InsumosInsumos

No Brasil, o setor produtivo conta com aproximadamente 137.000 ha

plantados, o setor de beneficiamento conta com 22 usinas de beneficiamento4

e o setor industrial conta com 8 indústrias de pneumáticos – maior consumidor

da borracha natural. Os setores de produção e beneficiamento da borracha são

considerados os mais fracos da cadeia, obtendo faturamentos anuais de R$

300 e 400 milhões, respectivamente, sendo muito menores que o das

indústrias de pneumáticos (R$ 14,2 bilhões/ano) e de artefatos (R$ 4,2

bilhões/ano). No setor produtivo, a situação é mais crítica, pois o menor

faturamento ainda é dividido com um número elevado de empresários e

empregados, levando a um resultado per capta bem menor que nos demais

setores da cadeia. Portanto, existe a necessidade de apoio governamental e

das empresas de maior porte dos setores de produção, beneficiamento e

industrialização, para incentivos à Inovação Tecnológica do setor produtivo, de

modo a superar os entraves e fortalecer a cadeia como um todo.

O fator mais importante, objeto deste projeto, é que o crescimento dos

setores de produção e de beneficiamento da borracha, está relacionado a

investimentos em novos plantios, para a expansão da área cultivada com

4 CONAB, 2006

Figura 7 – Cadeia Produtiva da Borracha. Fonte: Instituto Tecnológico da Borracha


seringueira, visando o aumento da produção nacional de borracha natural. Se a

taxa de crescimento do consumo continuar a 5% ao ano, o Brasil estará

consumindo mais de um milhão de toneladas de borracha natural por volta do

ano de 2030. Este crescimento propiciaria a esses setores, aumentarem mais

de dez vezes a sua capacidade instalada e, conseqüentemente, seu

faturamento, seu potencial de geração de 1.100.000 empregos diretos e

1.925.000 empregos indiretos, na cadeia produtiva como um todo, nos

próximos 25 anos.

3. JUSTIFICATIVA

As Mudanças Climáticas, tema em evidência atualmente, estão se

acentuando devido a constante intervenção antropogênica5 na natureza,

segundo o relatório do IPCC-(2005).

Desde o século XIX o planeta vem sofrendo com as emissões

constantes e crescentes de gases de efeito estufa, os chamados GEE’s, devido

principalmente a industrialização vivida no período pelos paises desenvolvidos

e mais recentemente pelos paises em desenvolvimento.

Desde meados do século passado, diversas ações foram criadas para

alertar os paises e congregar esforços para a resolução dos problemas que

adviriam do excesso de emissões e de acúmulo dos GEE’s na atmosfera.

A partir da assinatura do protocolo de Quioto em 1997 e sua ratificação

em fevereiro de 2005, ações mais concretas foram implementadas, tais como

os Mecanismos de Desenvolvimento Limpo (MDL) - especificamente voltados

para projetos em paises não-anexo16 -, os IC’s7 e Alocação8 - mecanismos

somente permitidos entre países anexo19.

O que temos visto, a partir de todas estas ações, é que a sociedade

constituída vem sofrendo as conseqüências deste aquecimento global,

traduzido por inúmeras catástrofes ambientais e tem se mobilizado no sentido

de participar mais ativamente do esforço de reduzir as emissões dos gases de

efeito estufa, por meio do plantio de árvores que através do processo de

5 Em sentido restrito, diz-se dos impactos no meio ambiente, gerados por ações do homem. 6 Países que não se comprometeram em cortar emissões, países em desenvolvimento. 7 Implementações conjuntas. 8 Allowances, permissões de emissões. 9 Países comprometidos com a redução de emissões, países desenvolvidos.


fotossíntese captam o CO2 da atmosfera e armazenam nos seus tecidos.

Recentemente, imbuídos de responsabilidade social, outras alternativas foram

concebidas e uma delas, especificamente, diz respeito à neutralização do

carbono emitido por atividades culturais, recreativas e de produção, pelo

carbono absorvido traduzido pelo equivalente em número de árvores plantadas.

Entretanto poucos estudos tem sido realizados com o objetivo de indicar

as espécies que realizam mais eficientemente este processo e que ao mesmo

tempo possam participar do processo produtivo com alto valor agregado. Assim

sendo, o que se observa é que por desconhecimento, os pequenos e médios

produtores ficam a margem deste esforço.

Este projeto se propõe contribuir para o maior conhecimento da cultura

da seringueira que é uma espécie altamente eficiente em absorver e estocar o

carbono da atmosfera e economicamente rentável, contribuindo assim para a

sustentabilidade.

Neste sentido, propõe-se a elaboração de uma metodologia específica

de cálculo para que se possa quantificar, através de um inventário de

emissões, a quantidade de CO2 equivalente que é liberada para atmosfera nos

diversos eventos, desenvolvimento produtos, processos e/ou serviços,

promovidos pelas micro e pequenas empresas.

Com base nesse inventário é calculada a quantidade de árvores

necessárias para capturar o montante de CO2 emitido, neutralizando-se assim

as emissões de GEE’s

4. OBJETIVO GERAL

Este projeto visa a oferecer as micro, pequenas e médias empresas

subsídios para a mitigação do efeito estufa vinculado ao desenvolvimento rural

através do plantio de árvores da espécie Hevea brasiliensis (seringueira).

Para a consecução deste objetivo o projeto propõe a concessão de um

selo “Seringueira Ambiental” (conforme modelo apresentado na Figura 8)

certificando ações, eventos, produtos, processos e serviços, promovidos pelas

empresas de uma maneira geral e pelas micro e pequenas empresas,

especificamente, que desejarem neutralizar suas emissões de gases do efeito

estufa através de plantações de seringueiras.


5. A CONTRIBUIÇÃO DA PEQUENA EMPRESA NA REDUÇÃO DOS GEE’s

Pretende-se através deste trabalho, buscar no dia-a-dia das micro e

pequenas empresas, quantificar as emissões de carbono aferidas em seus

processos de fabricação e no aumento de suas capacidades de produção.

Pelas características que possuem as micro e pequenas empresas não

tem em seus quadros departamentos de meio ambiente como verificado nas

grandes empresas e nem por isto devem passar ao largo da contribuição

mundial para a reversão do aquecimento em nosso planeta.

Havendo uma ferramenta confiável, em que se possa quantificar as

emissões em procedimentos tais como o aumento do consumo de energia

elétrica face ao aumento de produção; gastos com combustível e vale

transporte dos funcionários pelo aumento do quadro funcional; viagens a

trabalho pelos diversos meios de transporte; participação em feiras e eventos,

e compará-las para a obtenção do diferencial emitido de CO2eq, certamente

através desta ferramenta se estará propiciando ao setor a maneira adequada

de participação no freio ao aquecimento global pela contrapartida do plantio de

seringueiras nos projetos enquadrados no selo “seringueira ambiental”.

Figura 8 – Modelo de Selo de Cerificação proposto. Fonte: Instituto Tecnológico da Borracha - ITeB


6. METODOLOGIA DE CÁLCULO ESPECÍFICO PARA REDUÇÃO D E

EMISSÕES

6.1. BASE TEÓRICA PARA CÁLCULO DO MONTANTE DE CO 2 equi. –

INVENTÁRIO DE EMISSÕES

Um inventário de emissões é uma ferramenta básica para o

estabelecimento de políticas ambientais e energéticas, em especial no que se

refere a processos de combustão.

A crescente discussão sobre o aquecimento global levou o Painel

Intergovernamental de Mudanças Climáticas (IPCC) a elaborar um manual de

práticas para inventários nacionais de emissões atmosféricas causadoras de

efeito estufa. Este tem como a principal finalidade, instituir metodologias para

estimar as quantidades de gases gerados a partir do uso de energéticos,

principalmente os de origem fóssil, em todos os países que compõem a

Organização das Nações Unidas (ONU), uniformizando o conhecimento sobre

o acréscimo destes na atmosfera e seus possíveis efeitos sobre o clima

terrestre.

Tomando-se como base os projetos até então realizados no âmbito de

neutralização de carbono, foi estabelecida uma listagem de atividades

consideradas potenciais emissoras de CO2. Emissões estas divididas entre

diretas e indiretamente relacionadas às ações da empresa. De posse dessas

atividades foi elaborado um INVENTÁRIO DE EMISSÕES DE GEE`S – ANUAL

(vide anexo 1).

No cenário nacional existem atualmente os seguintes derivados de

petróleo para o setor de transporte: Gasolina, Diesel, Gás Natural Veicular,

querosene de aviação. A gasolina esta com uma adição de álcool

regulamentada em torno de 23%. Essa adição reduzirá as emissões

relacionadas a esta categoria de combustível. O álcool e o biodiesel por serem

combustíveis renováveis não são contabilizados como fontes de gases de

efeito estufa uma vez que todo o carbono emitido pela queima do combustível

foi retirado da atmosfera na plantação da cana-de-açúcar ou qualquer outro

grão, através da fotossíntese utilizando a energia solar. Diferentemente, os

combustíveis fósseis lançam para a atmosfera bilhões de toneladas de CO2


que estavam armazenadas nas jazidas de petróleo, fora da circulação

atmosférica.

Existe também um outro aspecto, os combustíveis não são totalmente

queimados. Uma pequena parte é convertida em partículas de carbono

conhecidas como “carbono grafítico” (do inglês Black Carbon) que é a “fuligem

dos carros”, que além de interferir na absorção dos raios solares na atmosfera

(influenciando as mudanças globais), causam problemas respiratórios à

população dos grandes centros urbanos.

Cada combustível utilizado possui diferentes teores de carbono e o

rendimento é inversamente proporcional à potência. A maneira como o

motorista dirige também influi muito no consumo.

O cálculo das emissões são, convencionalmente, apresentados na

unidade de massa de gás carbônico e não de carbono somente (C). Por isso é

necessária a conversão de massa de C para massa de CO2. A massa do CO2 é

cerca de 44, e a do Carbono é igual a 12, logo, o fator de conversão de C para

CO2 será igual a 44/12 = 3,6.

Massa do carbono =12 Massa do oxigênio = 16

Massa de CO2 = 12 + (2 x16); ou seja 44.

Ou seja, cada tonelada de carbono queimada é convertida em 3,6 toneladas de

CO2.

6.1.1. Emissões indiretamente relacionadas às ações da empresa

� Meios de transporte

O “Good Practice Guidance and Uncertainty Management in National

Greenhouse Inventories – Revised 1996 IPCC Guidelines for National

Greenhouse Gas” determina que “as emissões de gases de efeito estufa de

fontes móveis são melhor calculadas pela quantidade de combustível

queimado, teor de carbono e as emissões correspondentes de CO2 (método

Tier – 1 ou top-down)”.

O Cálculo das emissões de CO2 é feito para três meios de transporte

mais utilizados: Carro de passeio, ônibus e avião. Dentro do cenário nacional


de automóveis de passeio temos potências que variam de, genericamente

falando, de 1000 a 2000 cilindradas, que consomem algo em torno de 6 a 12

litros de combustível por quilometro rodado.

O cálculo das emissões por carro de passeio é como se houvesse

somente um passageiro, já os ônibus foram considerados 30 passageiros e nos

aviões, o Boing 737 (trechos São Paulo – Rio de Janeiro e São Paulo-

Salvador) com uma capacidade em torno de 150 passageiros e o Boing 777

(trecho São Paulo-Paris) com uma capacidade de 270 passageiros e com uma

taxa de ocupação média de 70% dos assentos por vôo. As estimativas foram

calculadas levando em consideração diferentes consumos durante a

decolagem, velocidade de cruzeiro e pouso para cada trecho com

especificações do modelo da aeronave (Fonseca, 2007).

O calculo anual leva em consideração a distância percorrida por dia

multiplicado por 365 dias/ano.

O cálculo para estimar a emissão realizada por uma pessoa, parte da

seguinte equação:

Automóvel: Emissões (kg de CO2) = CC x DP x DC x TC x 3,6 Ônibus: Emissões (kg de CO2) = CC x DP x DC x TC x 3,6 / NP Avião: Emissões (kg de CO2) = CC x TC x 3,6 / NP x TO Onde: CC = Consumo de combustível (L•km-1) ou massa de combustível consumida por viagem. DP = Distância percorrida (km) DC = Densidade do combustível (kg•L-1) TC = Teor de carbono no combustível (%) NP = Número de passageiros TO = Taxa de ocupação dos assentos

Para simplificar o cálculo é elaborado um fator de emissões para cada

“potência do motor/tipo de combustível” e meio de transporte. Esse fator é uma

taxa média de emissão de CO2 por pessoa por quilômetro percorrido,

denominado pkm , massa de CO2 emitida por quilômetro percorrido por pessoa.


No caso da viagem de avião, a estimativa das emissões é simplificada,

com apenas as emissões em três classes de distância percorrida. O trecho Rio

de Janeiro – São Paulo possui cerca de 500 quilômetros para ida e volta; São

Paulo – Salvador, com 1450 quilômetros para ida e volta e o trecho São Paulo -

Paris com cerca de 9400 quilômetros para ida e volta. Nesse caso, o total é

dado por viagem, por isso é preciso adaptar quaisquer outros trechos para

esses três estudos de caso. Se uma pessoa fez um outro trecho, é preciso que

se escolha um ou mais trechos estudados para que, comparativamente, possa

se calcular as emissões de um vôo. De qualquer maneira todos estes cálculos

são apenas especulativos, pois existem diversos fatores que influenciam a

estimativa. O tipo de aeronave, taxa de ocupação do avião (passageiros e

carga), direção e força do vento, dentre outros fatores.

Através do fator pkm o cálculo pode então ser feito diretamente através

do produto da distância pelo fator de emissão. Os Quadros 2, 3 e 4 apresentam

as emissões em kgCO2/pkm para carro de passeio, ônibus e avião

respectivamente.

QUADRO 2. Emissões de CO 2, por tipos de combustível e potências, para carros de passeio.

Combustível Teor C Densidade kg/L

Potência do Motor

Consumo km/L ou (L/km)

Emissões (kgCO 2 eq. /pkm)

Gasolina* 0,67 0,800 de 1,0 a 1,4 12 (0,08) 0,161

Gasolina* 0,67 0,800 de 1,5 a 2,0 10 (0,1) 0,194

Diesel 0,84 0,840 de 1,0 a 1,4 12 (0,08) 0,212

Diesel 0,84 0,840 de 1,5 a 2,0 10 (0,1) 0,254

GNV 0,75 0,750 de 1,0 a 1,4 12 (0,8) 0,169

GNV 0,75 0,750 de 1,5 a 2,0 10 (0,1) 0,203

*- Com 23% de álcool incluído.

QUADRO 3. Emissões de CO 2, por tipos de combustível e potências, para ônibus.

Combustível Teor C Densidade (kg/L)

Pass./ônibus Consumo km/L ou (L/km)

Emissões (kgCO 2 eq./pkm)

diesel 0,84 0,840 30 4 (0,25) 0,0059

Fonte: Fonseca, K. T., 2007 – Programa Florestas do Futuro.



QUADRO 4. Emissões de CO 2 para aviões.

Modelo Teor de C (%)

Densidade (kg/L)

Pass./avião Consumo km/kg ou (kg/Km)

kg CO 2

eq./pkm

Air Bus A320 0,86 0,799 150 0,19 (5,08) 0,150

Boeing 737 0,86 0,799 150 0,24 (4,14) 0,122

Boeing 777 0,86 0,799 270 0,08 (11,65) 0,191

*taxa de ocupação: 0,7%

6.1.2. Emissões diretamente relacionadas às ações d a empresa

� Consumo de energia elétrica

Para calcular as emissões relativas ao consumo energético utiliza-se o

fator de emissão (kgCO2 eq / kWh) do mix energético brasileiro desenvolvido a

partir da metodologia ACM0002 “Consolidated baseline methodology for grid-

connected electricity generation from renewable sources” (vide anexo 2),

aprovada pela UNFCCC para Projetos de Mecanismo de Desenvolvimento

Limpo (MDL) empregados no Brasil, conforme indicado no Quadro 5.

QUADRO 5. Fator de emissão para cálculo referente ao consum o de energia elétrica.

Tipo Fator de emissão

(kg CO 2 eq./kWh)

Energia elétrica em KWh 0,27

� Consumo de combustível em máquinas estacionárias e Consumo

de gás

O IPCC recomenda o uso de fatores de emissão locais para aplicação

dos cálculos, uma vez que seu manual adota fatores de emissão relativos aos

combustíveis utilizados nos Estados Unidos e nos países da Organização para

Cooperação e Desenvolvimento Econômico (OCDE). Os órgãos nacionais que

determinam os fatores a serem utilizados são o Ministério de Minas e Energia

(MME), o Ministério de Ciências e Tecnologia (MCT) e a Agência Nacional do

Petróleo (ANP).


Fonte: Martins, 2004 - The Green Initiative.


No caso da eletricidade gerada a partir dos geradores a diesel é utilizado

o valor padrão do IPCC, proposto para a metodologia AMS I.D ‘Grid connected

renewable electricity generation’ (vide anexo 3).

� Consumo de água e Produção de esgoto

Para esta análise o fator de consumo energético para o tratamento da

água do Instituto para Analise de Segurança Global (IAGS) e para o tratamento

de esgoto do Iowa Association of Municipal Utilities (IAMU), expressos em kWh

por m3, são multiplicados pelo fator de emissão de CO2eq. do mix energético

brasileiro. Para a realização das estimativas relativas aos resíduos sólidos é

utilizado o fator de emissão de GEE do IPCC Guidelines, 1996, capítulo 6 (vide

anexo 4). O quadro 6 apresenta o consumo de energia elétrica referente ao

consumo de água e ao tratamento de esgoto e o fator de emissão associado,

considerando inclusas as termoelétricas na composição da matriz energética.

QUADRO 6. Fator de emissão para cálculo referente ao consumo d e água e produção de

esgoto.

Tipo Consumo de Energia

Elétrica (kwh/m 3)

Fator de emissão

(kg CO 2 eq./kWh)

Consumo água 0,6 0,27

Volume de esgoto tratado 0,4 0,27

� Quantidade de papel utilizada

Para se estimar as emissões relativas a cada um dos itens

considerados, é utilizado o software Global Emission Model for Integrated

Systems (GEMIS 4.3) do Instituto OEKO, o qual se baseia na ferramenta de

Analise de Ciclo de Vida associada a fatores de mudanças climáticas do IPCC

para obter o fator de emissão de GEE (tCO2eq/kg) de cada material. O quadro

7 apresenta os fatores de emissão referentes a quantidade de diferentes tipos

de papel utilizados.

Fonte: Martins, 2004 - The Green Initiative.


QUADRO 7. Fator de emissão para cálculo referente ao consum o de papel.

Item Papel higiênico Papel toalha Papel p/ cartão Papel Sulfite

Fator de emissão (kg CO2 eq./kg) 0,64 0,64 1,24 0,426

6.2. BASE TEÓRICA PARA O CÁLCULO DA QUANTIDADE DE

ÁRVORES NECESSÁRIAS

A seringueira é uma cultura da família das euforbiáceas cujo produto

principal é o látex que vai dar origem à borracha natural, utilizada

primordialmente na fabricação de pneumáticos e de centenas de artefatos de

grande utilidade para a sociedade humana. Por seu caráter de cultura perene,

porte, e vida útil de mais de quarenta anos, sua madeira pode ser utilizada para

construção civil e fabricação de móveis e caixas de embalagens, tornando a

cultura mais útil, importante e lucrativa. Além desses produtos, a seringueira é

uma planta melífera que apresenta nectários nas flores e na base dos pecíolos

das folhas, e suas sementes podem ser empregadas para extração de óleo,

contribuindo para agregação de renda extra aos agricultores (Gonçalves,

2001). Essas características conferem maior valor agregado à cultura, que

estoca carbono na sua biomassa arbórea.

Assim sendo, estudos de estoques de carbono na biomassa têm

demonstrado que a seringueira é uma excelente seqüestradora do carbono

atmosférico.

Quantificação da Biomassa e dos estoques de carbono nos seringais de

cultivo.

Os estudos para a quantificação da biomassa e do carbono

estocado em seringais de cultivo são realizados por meio do método

destrutivo de árvores representativas da população e são computados o

carbono estocado na árvore inteira, o carbono estocado no solo, na

serrapilheira e na borracha seca. A biomassa seca é convertida em

carbono utilizando-se o fator 0,5, significando que 50% da biomassa seca

é composta por carbono, (Dewar e Cannel, 1992, Fearnside, 1996, Soares e

Fonte: Martins, 2004 - The Green Initiative. .


Oliveira, 2002). De acordo com Face, (1994), considera-se que uma tonelada

de carbono corresponde a 3,67 toneladas de CO2 equivalente (CO2eq.),

cuja unidade é expressa em Micrograma por hectare, (Mg.ha-1).

No mercado de negociações sobre mudança climática global, os

Certificados de Emissões Reduzidas (CERS) são contabilizados em função

do CO2eq., ou seja, ao se falar em CERS, entende-se igualmente CO2eq.

Pesquisas demonstram a eficiência da seringueira em estocar o carbono

atmosférico em quantidades equivalentes ao de uma floresta natural (Rahaman

& Sivakumaram; 1998). Segundo os autores, o total de carbono seqüestrado na

biomassa da madeira e na borracha seca produzida por um hectare de

seringueira aos 30 anos é de 135 toneladas, isto é 495 toneladas de C02

equivalente(CO2eq.).

Neste sentido, em Minas Gerais, Carmo et al.; (2006) realizaram estudos

visando à quantificação do carbono estocado na biomassa nos clones de

seringueira mais plantados na região sudeste, RRIM 600 e IAN 873, com 15 e

20 anos de idade, respectivamente, plantados na região da Zona da Mata. Os

resultados do trabalho encontram-se na Tabela 1.

Tabela 1 - Dados médios do carbono orgânico e equivalente armazenados na planta, na

serrapilheira, no solo e na borracha seca, em seringais dos clones RRIM 600 e IAN 873. (MG,

2006).

Clones Carbono orgânico Mg.ha -1 C02 eq. Mg.ha -1

RRIM 600 (15 anos) 156,5 574,4

IAN 873 (20 anos) 167,1 613,3

No entanto, o teor de carbono estocado pelas plantas depende de vários

fatores, como: espécie, propriedades físicas e fertilidade do solo,

disponibilidade de água e nutrientes, manejo da planta, etc... e no caso da

seringueira, as exigências específicas do material genético plantado também

tem que ser levado em consideração. Assim é que Pereira et al; (2004)

quantificando o carbono em seringais do clone PB 235 com 4, 6 e 15 anos de

implantação no Paraná, encontraram os seguintes resultados, Tabela 2.


Tabela 2 - Dados médios do carbono orgânico e equivalente armazenados na planta, em

seringais com 4, 6 e 15 anos de idades do clone PB 235. (PR, 2006).

Clones Carbono orgânico Mg.ha -1 C02 eq. Mg.ha -1

PB 235 (04 anos) 7 25

PB 235 (06 anos) 21 77

PB 235 (15 anos) 90 330

Ciclagem de Nutrientes.

Estes estudos permitem verificar a utilização de seringais de cultivos

como alternativa para recuperação de áreas degradadas, bem como, a

influência dos diferentes clones, IAN 873 e RRIM 600, nas características do

solo.

A seringueira é uma cultura que tem o hábito caducifólio e se caracteriza

pela queda de folhas e de outros componentes da parte aérea que irão formar

a serrapilheira constituindo-se num importante mecanismo de transferência de

nutrientes da fitomassa vegetal para o solo. Segundo Andrade et al.; (2003), o

acúmulo de serrapilheira na superfície do solo é regulado pela quantidade de

material que cai da parte aérea das árvores e sua taxa de decomposição. A

compreensão da dinâmica da decomposição da serrapilheira é importante para

aferir o balanço de carbono e nutrientes em sistemas florestais e agroflorestais,

sendo assim, Kindel et al. (2006) verificaram a contribuição da queda de

material vegetal (folhiço) na matéria orgânica, carbono e macronutrientes do

solo de seringais dos clones IAN 873 e RRIM 600. Os totais aportados

encontram-se na Tabela 4. Tabela 3 - Totais de carbono orgânico e equivalente encontrados em clones de seringueira.

(MG; 2006).

Material vegetal Carbono orgânico Mg.ha -1 C02 eq. Mg.ha -1

RRIM 600 2,5 9,17

IAN 873 2,1 7,7

Carbono estocado nos solos sobre os seringais.

O solo é considerado como o maior reservatório terrestre de C, e pode

atuar como uma fonte ou um depósito de CO2 para atmosfera, dependendo do

sistema de manejo adotado (Bayer e Mielniczuk, 1999). As plantas através da

fotossíntese são o elo de ligação entre o carbono que se encontra na atmosfera


e o carbono que se encontra no solo na forma de matéria orgânica.

Dependendo das práticas agrícolas que são utilizadas o solo irá agir como um

dreno ou como uma fonte de CO2 para atmosfera (Amado, 2003). A figura 9

apresenta um esquema ilustrando o ciclo do carbono em agroecossistemas.

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CICLO DO CARBONO EM AGROECOSSISTEMAS

Dióxido de carbono na atmosfera

Drenagem

CO2, HCO3-, CO3--

CO2

CO2

CO2

CO2

FOTOSSÍNTESE

RESPIRAÇÃO DE PLANTAS

COMBUSTÃO

RESPIRAÇÃO

BACTÉRIA

FUNGOS

RAÍZES

MATÉRIA ORGÂNICA

EROSÃO

PERDAS

RESÍDUOS CULTURAIS

PREPAROZONA

(C4)

(C3)

ANIMAIS

ESTERCO

ATIVO

LENTO

PASSIVO

Emissões de CO 2 associadas ao preparo do solo.

Um dos processos-chave para a adição de carbono ao solo é a

fotossíntese, na qual o CO2 é combinado com água utilizando a energia solar

para formar carboidratos. O carbono acumulado nas plantas é ciclado no

ecossistema terrestre sendo uma parte armazenada temporariamente no solo

na forma de MO, da qual é o principal constituinte com 58% (Reicosky, 1999

citado por Amado, 2003).

As atividades de preparo podem estimular a mineralização da matéria

orgânica e a liberação de CO2 que se encontrava nos poros, reduzindo a

permanência do carbono no solo (Bruce et al.,1999; Reicosky &

Lindnstom,1993 citados por Amado, 2003). Clima, vegetação, topografia e tipo

de solo irão condicionar o tamanho do estoque de carbono que será

armazenado no solo.

Figura 9 – Esquema do Ciclo do Carbono em agroecossistemas (Re icosky ,1998 citado por Amado, 2003)..


Segundo Silva & Machado (2000), há uma maior preservação da matéria

orgânica, de um modo geral, em áreas sob vegetação natural, havendo perdas

consideráveis de carbono quando essas são convertidas em área de cultivo.

No caso de plantios de seringueiras, principalmente em áreas acidentadas, não

há revolvimento do solo com a muda plantada diretamente na cova, o que

permite a manutenção da matéria orgânica do solo.

Rios et al. (2006) conduziram um estudo com a finalidade de quantificar

o efeito do manejo na matéria orgânica e seus componentes em clones de

seringueira e verificaram que os clones de seringueira RRIM 600 e IAN 873,

estocaram 40,0 e 51,7 Mg.C.ha-1, respectivamente, causando impactos

diferenciados na acumulação de matéria orgânica.

Carbono estocado na Borracha Natural.

Para a computação do carbono estocado em plantios de seringueira tem

que ser quantificado o estocado na borracha natural seca pois segundo Esah

(1990), 90% da composição de borracha natural crua é constituída de carbono.

Assim sendo, por meio de estimativa da produção média de borracha natural

no Brasil, em torno de 1500 a 2000kg.ha-1.ano, o carbono equivalente pode ser

quantificado.

7. O QUE SE ESPERA DESTE PROJETO

Espera-se na conclusão deste projeto, obter-se a ferramenta necessária

para quantificar o carbono emitido nas micro, pequenas e médias empresas e

em eventos, e neutralizá-lo através do plantio de seringueiras, revitalizando a

heveicultura e contribuindo para a mitigação dos gases de efeito estufa,

alterando o quadro atual imposto pelas mudanças climáticas.

8. METODOLOGIA DE MONITORAMENTO

Para garantir o sucesso deste restauro florestal e, conseqüentemente, a

fixação do carbono, as mudas plantadas serão mantidas por trabalhadores e

técnicos do local contratados por um período de dois anos, fase de

estabelecimento das novas árvores.


As áreas reflorestadas serão monitoradas durante todo o período de

absorção da quantidade de CO2eq. emitido, estimado em 40 anos, através da

metodologia para projetos florestais AR-AM0001 (Revised simplified baseline

and monitoring methodologies for selected small-scale afforestation and

reforestation project activities under the clean development mechanism)

aprovada pelo conselho executivo da UNFCCC. Além disso, devido ao caráter

legal das áreas a serem reflorestadas (APPs) haverá fiscalização de órgãos

ambientais estaduais e federais, sendo o corte das árvores considerado crime

inafiançável perante a legislação ambiental brasileira.

9. EXEMPLO DE APLICAÇÃO

Para uma melhor compreensão da metodologia proposta para o cálculo

de emissões de GEE’s, quantificados em CO2 eq., apresentar-se-á um exemplo

fictício de uma situação que pode ser avaliada com este trabalho.

9.1. Projeto de neutralização de emissões da Semana Acadêmica de

Engenharia Agrícola - SEMEAGRI

O projeto de neutralização de emissões da Semana Acadêmica de

engenharia Agrícola - SEMEAGRI tem como objetivo compensar as emissões

de Gases de Efeito Estufa (GEE) decorrentes da realização do evento

tornando-o Neutro em Carbono.

As emissões de GEE atribuídas ao congresso serão absorvidas por um

reflorestamento a ser realizado na última semana do mês de outubro do ano de

2009, nas margens do Rio Guandu, município de Seropédica. Através deste

reflorestamento será possível melhorar a qualidade ambiental da área que se

apresenta degradada, contribuindo ao mesmo tempo para um desenvolvimento

local mais sustentável e para o combate às mudanças climáticas através da

fixação do carbono.

O projeto consiste de duas etapas. A primeira é a produção do Inventário

de Emissões de gases de efeito estufa (GEE) relativas à realização do referido

evento. A segunda é estimar o número de árvores a serem plantadas para

absorver da atmosfera este montante de GEE (quantificados em CO2

equivalente), tornando o evento Neutro em Carbono.


� INVENTÁRIO DE EMISSÕES DE GEE

Neste inventário, todas as emissões de GEE contabilizadas foram

expressas na forma de toneladas de dióxido de carbônico equivalente (CO2

eq.), seguindo o padrão mundial estipulado pelo Intergovernamental Pannel on

Climate Change (IPCC), órgão científico para assuntos de mudanças climáticas

da ONU. CO2 eq. é uma medida utilizada para comparar as emissões de vários

gases de efeito estufa baseado no potencial de aquecimento global de cada

um. O dióxido de carbono equivalente é o resultado da multiplicação das

toneladas emitidas do gás pelo seu potencial de aquecimento global.

Para a produção do presente Inventário foram utilizados dados

fornecidos pela Ambiente Global – Comunicação, Eventos & Sustentabilidade,

organizador do evento. Foram contabilizadas as emissões decorrentes do

transporte dos palestrantes, do consumo de energia elétrica no local do evento,

do consumo de materiais e produção de resíduos (Tabela 9.1 a 9.6).

TABELA 9.1 – Emissão total em tCO2 eq. referente ao uso de transporte aéreo.

Meio Trajeto Passageiros Distância total (Km)

Fator de Emissão (Kg CO2 eq./PKm)

Emissão Total (t CO2 eq.)

Avião Comercial

Salvador São Paulo

(CGH) 3 1.500 0,122 0,549

Avião Comercial

Brasília (BSB) São Paulo

(CGH) 5 1.734 0,191 1,656

TOTAL 2,205

TABELA 9.2 – Emissão total em tCO2eq. referente ao consumo de energia elétrica..

Fonte Consumo Evento (kWh)

Fator de Emissão (Kg CO2 eq./KWh)

Emissão Total (t CO2 eq.)

Rede (mix brasileiro) 1.700 0,27 0,459

TOTAL 0,459

TABELA 9.3 – Emissão total em tCO2eq. referente ao consumo de papel. Fonte: The Green Initiative

Fonte: The Green Initiative


Tipo Quantidade total (Kg)

Fator de Emissão (Kg CO2eq./Kg)

Emissão Total (t CO2eq.)

Papel Kraft (pastas) 31,7 0,74 0,023

Papel Higiênico 8 0,64 0,005

Papel Toalha 18 0,64 0,011

Papel cartão 15 1,24 0,018

Papel Sulfite 40,5 0,426 0,017

TOTAL 0,074

TABELA 9.4 – Emissão total em tCO2eq. referente ao consumo de água e ao tratamento do esgoto gerado.

Tipo Quant. per

capta (m3/pessoa/dia)

Participantes Consumo total (m 3)

Consumo energ. elet. (Kwh/m 3)

Consumo energ.

elet. Total (Kwh)

Fator de Emissão (Kg CO2eq./Kwh)

Emissão Total

(t CO2eq.)

Consumo de água

0,50 70 420 0,60 252 0,27 0,07

Volume de esgoto tratado (m3/hab/dia)

0,40 70 336 0,40 134

0,27 0,04

TOTAL 0,011

Para estimar as emissões relativas a cada um dos itens considerados,

foi utilizado o modelo computacional Global Emission Model for Integrated

Systems (GEMIS 4.3) do Instituto OEKO, o qual se baseia na ferramenta de

Análise de Ciclo de Vida associada a fatores de mudanças climáticas do IPCC

para obter o fator de emissão de GEE (tCO2 eq./Kg) de cada material.

TABELA 9.5 – Emissão total em tCO2 eq.

Origem das emissões Transporte Energia elétrica Materiais Resíduos

Emissão Total (t CO 2 eq.) 2,205 0,459 0,074 0,011

TOTAL 2,749





O resultado final do Inventário de Emissões de GEE foi a emissão de

2,749 tCO2 eq decorrentes da realização da Semana Acadêmica de

Engenharia Agrícola.

� CÁLCULO DO NÚMERO DE ÁRVORES

Esta é a etapa de implantação do Projeto. A partir do resultado final

obtido na primeira etapa, quantidade total de GEE emitidos em função da

realização do evento, o número de indivíduos da espécie hevea brasiliensis a

serem plantadas será calculado.

A equação utilizada para calcular do número de árvores a serem

plantadas é:

N = Et / Ff equação 1

Onde:

N – número de árvores a serem plantadas; Et – emissão total de GEE estimada na primeira etapa desta metodologia (tCO2

eq.); Ff – fator de fixação de carbono em biomassa no local de implantação do projeto (tCO2 eq./árvore).

Fator de Fixação

O Fator de Fixação utilizado neste projeto foi estimado em estudos

anteriores (Martins, 2004; Carmo et al., 2006) como segue:

Para compensar as emissões de gases de efeito estufa, estimadas na primeira

etapa do projeto, foi aplicada uma metodologia de planejamento e

quantificação de carbono em reflorestamento com hevea brasiliensis.

Foi estimada a quantidade de carbono que esse reflorestamento irá

absorver da atmosfera durante o seu crescimento. Desta maneira é possível

determinar o tamanho da área que será reflorestada para compensar as

emissões do projeto.

Um fator fundamental para o sucesso dos plantios consiste na escolha

dos clones mais apropriados a serem utilizados. Devem-se priorizar os clones

indicados à própria região do plantio, pois estes terão muito mais oportunidade

de adaptação ao ambiente.


Para esta escolha, pressupõem-se levantamentos florísticos e

fitossociológicos prévios em remanescentes florestais próximos e em

condições semelhantes ao local de implantação.

A escolha dos clones que serão utilizados no reflorestamento deste

projeto foi feita a partir de um estudo de campo onde remanescentes de

floresta de hevea foram analisados. Neste estudo foram instaladas 50 amostras

de 300m2 (50m x 6 m) e dentro de cada amostra foram classificados todos os

indivíduos com CAP (Circunferência na Altura do Peito) > 15 cm. O número

médio de indivíduos por hectare encontrado foi de 1.551.

Para estimar a quantidade de biomassa em um hectare de floresta foi

utilizado o método não destrutivo. Este método baseia-se em análise

dimensional, isto é, na relação alométrica existente entre dimensões de

diferentes partes de um mesmo organismo e na manutenção da razão relativa

de crescimento. Neste método, procura-se estabelecer uma relação entre

dados dendrométricos10 facilmente coletados em campo, tais como o diâmetro

e a altura do fuste11, medidas coletadas com árvore em pé, com os pesos dos

elementos componentes da árvore como tronco, galhos, folhas e casca. Assim

sendo, diâmetros de uma amostra de árvores são medidos e convertidos em

estimativas de peso de biomassa utilizando-se equações de regressão

alométricas. Esse tipo de equação existe para muitos tipos de florestas;

algumas são específicas para um determinado lugar, enquanto outras,

particularmente nas regiões tropicais, são mais genéricas (Alves et al., 1997;

Brown, 1996; Schroeder et al., 1997). Ainda, segundo publicação do IPCC , em

seu relatório específico sobre o tema "Land-use, land-use change and forestry",

no item 2.4.2.1.2, que descreve os métodos para estimar a biomassa de uma

árvore, cita que:

“Cortar e pesar um número suficiente de árvores para produzir equações

alométricas locais pode ser extremamente caro e consumir muito tempo, o que

pode estar além do objetivo de determinados projetos. A vantagem de se

utilizar equações genéricas é que elas são baseadas em um número grande de

10 Dendrometria é um ramo da ciência florestal que se encarrega da determinação ou estimação dos recursos florestais, quer seja da própria árvore ou do próprio povoamento. 11 O fuste, comumente chamado de tronco, tem como funções básicas à sustentação da parte aérea e à condução de seiva bruta e elaborada. É parte aérea livre de ramificações e serve de ligação entre as raízes e a copa. Pode em alguns casos acumular água e servir como estrutura de propagação vegetativa.


equações e abordam uma grande variedade de diâmetros, fatores que

aumentam a precisão das equações...”

Como citado anteriormente, nas medidas realizadas no campo foram

consideradas apenas as árvores com CAP maior ou igual a 15 cm. Assim

sendo, o número médio de indivíduos por hectare fica sempre subestimado, já

que as árvores com o diâmetro e a altura do peito inferior a este valor não

aparecem nas amostras. Para a elaboração de um projeto de seqüestro de

carbono, é preferível que a estimativa do potencial seja subestimada a super

estimada, aumentando assim a confiabilidade do projeto. A definição do CAP

mínimo está vinculada ao fato de que as equações alométricas disponíveis

perdem drasticamente a confiabilidade quando aplicadas para valores abaixo

deste limite.

Partindo destes princípios, foram utilizadas várias abordagens

combinando várias equações alométricas com diferentes grupos de dados até

a identificação da melhor alternativa, que foi a que apresentou o melhor

resultado estatístico quando comparada a realidade de campo. Na utilização

dessas equações, o valor obtido para a biomassa (Y) é dividido por mil para

obter o resultado em toneladas. O valor em toneladas é então multiplicado por

0,5 para obter as toneladas de carbono. A multiplicação por 0,5 é efetuada

porque na bibliografia disponível, em média, a matéria vegetal contém 50% de

carbono, uma vez que água é removida (MacDicken, 1997). O valor obtido é

então dividido pelo tamanho da parcela amostrada (em m2) para então obter o

valor em tC/m2. Multiplicando esse valor por 10.000 m2, obtém-se, o valor em

tC/ha.

Desta forma, a metodologia utilizada para a determinação da quantidade

de carbono no reflorestamento de mata ciliar foi:

1. Instalar um número significativo de parcelas amostrais fixas nos

remanescentes de floresta da região de estudo. As amostras foram

georreferenciadas com o auxilio de um GPS (global positioning system).

2. Dentro de cada amostra, todas as árvores com CAP maior que 15 cm

foram identificadas por clone e classe de diâmetro tendo a

circunferência na altura do peito medida.


3. A partir desses dados foi possível determinar para cada clone o número

médio de indivíduos e o CAP médio para cada espécie dentro de cada

uma das categorias de diâmetro.

Finalmente, com a utilização de uma equação alométrica desenvolvida

para a área de estudo, a quantidade de biomassa acima do solo presente no

reflorestamento foi estimada.

A Figura 10 mostra a distribuição dos valores de toneladas de carbono

em função do número de amostras encontradas entre as amostras analisadas.

É possível observar que 11% das amostras se encontram na faixa entre 20 e

40 tC/ha. Parcela similar (12%) ocorre para a faixa entre 100 e 140 tC/ha. A

grande maioria das amostras (77%) se encontra na faixa entre 40 e 100 tC/ha.

Ainda é possível observar que do total 12 amostras (31%) se encontram na

faixa entre 60 e 80 tC/ha.

Após a análise dos resultados da simulação e comparando os mesmos

com os resultados das simulações feitas com os dados obtidos em campo e

com os valores estimados de carbono em diversos ecossistemas, é possível

estimar que um hectare reflorestado com 1.600 indivíduos no município de

Seropédica, conterá em média 78 tC em biomassa acima do solo.

Figura 10 – Distribuição do número de amostras por quantidade de carbono acima do solo. Fonte: The Green Initiative


Assim sendo a remoção líquida de carbono da atmosfera na região de

estudo será de aproximadamente 80 tC/ha, o que equivale a 290 tCO2 eq. por

hectare. Esta quantidade será atingida em um período de aproximadamente 30

anos, quando a floresta atingir o estagio clímax. Considerando um número

médio de 1.600 indivíduos por hectare, o fator de f ixação utilizado para

dimensionar o reflorestamento é de 0,18 tCO 2 eq./árvore.

TABELA 9.6 – Emissão total em tCO2eq.

Total de emissões (tCO2 eq.)

Fator de fixação (tCO2 eq./árvore) Árvores Árvores (+20%)

2,749 0,18 16 20

� RESULTADOS

Por meio da metodologia de análise de fixação de carbono em biomassa e

da equação1, chegamos ao número de 16 árvores a serem plantadas.

Considerando que em um projeto de reflorestamento há uma perda normal de

mudas (de 10 a 20%) e a abordagem conservativa sempre utilizada nos

projetos, o número final de árvores a serem plantadas a fim de neutralizar as

emissões relativas à Semana Acadêmica de Engenharia Agrícola deve ser de

20 árvores.

10. Atividades realizadas durante o estágio

� Revisão de literatura na área de mudanças climáticas, neutralização de

carbono e heveicultura;

� Desenvolvimento de um website para o projeto;



� Elaboração do projeto “Implantação do selo de certificação

‘SERINGUEIRA AMBIENTAL’ como subsídio para neutralização de

emissões de Gases de Efeito Estufa com ênfase nas micro e pequenas

empresas”, aprovado pelo SEBRAE/RJ;

� Criação da arte gráfica para o selo “Seringueira Ambiental”;

� Apresentação do projeto, no stand da FIRJAN, durante a 58º Exposição

Agropecuária de Barra do Piraí/RJ;

� Visita Técnica ao seringal “Tira-Teima” – Guarapari/ES;


� Visita Técnica à Fazenda da Taquara – Barra do Piraí/RJ;

� Participação no Congresso Brasileiro de Heveicultura – Guarapari/ES;

� Representação na 8º Reunião da Câmara Setorial da Cadeia Produtiva

da Borracha Natural.


11. O saldo que o estagiário adquire

� Inserção do formando no mercado de trabalho;

� Apresentação da área de atuação profissional, orientando as

perspectivas de aprimoramento e especialização;

� Aumento da gama de conhecimento, introduzindo novos conceitos

relativos a área de estágio: Mudanças Climáticas e Heveicultura;

� Crescimento pessoal, uma vez que o estágio requer tomada de decisão,

posicionamento frente aos assuntos tratados, aplicação dos

conhecimentos adquiridos durante a graduação, entre outros.

12. DOCUMENTOS ANEXOS

� ANEXO 01 – Inventário de Emissões de GEE`S – Anual

� ANEXO 02 – Metodologia ACM0002 “Consolidated baseline

methodology for grid-connected electricity generation from

renewable sources”

� ANEXO 03 – Metodologia AMS I.D ‘Grid connected renewable

electricity generation’

� ANEXO 04 – IPCC Guidelines, 1996, capítulo 6


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Agroforestry Projects , 1997 26. MARTINS, O. S. Projetos The Green Initiative. Determinação do Potencial

do seqüestro de carbono na recuperação de matas cil iares na região de São Carlos - SP – Brasil, 2004. Disponível em: <http://www.thegreeninitiative.com>. Acesso em 26 de julho 2007

27. OLIVEIRA, D.; PEREIRA, J. DA P.; RAMOS, A. L. M.; CARAMORI, P. H.;

MARUR, C. J.; WAGNER-RIDDLE, C. & V. P.Carbono na biomassa e na respiração do solo em plantio comercial de seringue iras no Paraná. In: Antônio de Pádua Alvarenga e Ciríaca Arcângela Ferreira de Santana do Carmo, editores. Seqüestro de carbono Quantificação em seringais de cultivo e na vegetação natural. Viçosa, MG; 2006. 352p.

28. PANDEY, D. N. Carbon sequestration in agroforestry systems. Climate

Policy , v. 2, n. 4 p. 367-377, 2002. 29. PEREIRA, J. R.; RAMOS, A. L. M. Culturas intercalares e alternativas de

renda para a cultura da seringueira . In: CICLO DE PALESTRAS SOBRE A HEVEICULTURA PAULISTA, 4., Bebedouro, SP, 24-25 nov. 2004. [Palestra...]. Bebedouro, SP: secretaria de Agricultura e Abastecimento: APABOR, 2004. 18p.

30. RAHAMAN, W. A. & SIVAKUNARAN, S. Studies of carbon sequestration

in rubber. In: RUBBER FORUM, Bali, Indonésia, October, 1998. [Proceedings ...] Geneve: UNCTAD/IRSC, 1998. 17 p.

31. RIOS, L. C.; CONCEIÇÃO, M.; PÉREZ, D. V. & ARAÚJO, W.S. Estoque de

carbono e caracterização de substancias húmicas em solos sob seringais cultivados e vegetação natural. In: Antônio de Pádua Alvarenga e Ciríaca Arcângela Ferreira de Santana do Carmo, editores. Seqüestro de carbono Quantificação em seringais de cultivo e na vegetação natural. Viçosa, MG; 2006. 352p.


32. SCHROEDER, J. L. et al. Utillization of cowpea crop residues to reduce

fertilizer nitrogean inputs with fall broccoli . Crop Science, Madison, v.38, p.741-749, 1997.

33. SILVA, C. A. & MACHADO P. L. O. de A. Seqüestro e emissão de

carbono em ecossistema agrícolas: estratégias para o aumento dos estoques de matéria orgânica em solos tropicais . Rio de Janeiro: Embrapa Solos, 2000. 23p (Embrapa Solos. documentos; 19).

34. SOARES, C. P. B.; OLIVEIRA, M. L. R. Equações para estimar a

quantidade de carbono na parte aérea de árvores de eucalipto em Viçosa, Minas Gerais. Revista Árvore, viçosa, v. 26, n. 5, p. 533-539, set/out, 2002.

35. TEIXEIRA, L.B.; OLIVEIRA, R. F. Biomassa vegetal e carbono orgânico

em capoeiras e agroecossistemas no Nordeste do Pará . Belém: Embrapa Amazônia Oriental, 1999. 21 p. (Boletim de Pesquisa, 6).


ANEXO 01

Inventário de Emissões de GEE`S – Anual


INTENTÁRIO DE EMISSÕES DE GEE`S - ANUAL

⇒ Emissões diretamente relacionadas às ações da empresa.

� Consumo de energia elétrica, em kWh, dos últimos 12 (doze) meses:

JAN FEV MAR ABR MAI JUN

JUL AGO SET OUT NOV DEZ

� Consumo de combustível em máquinas estacionárias (geradores etc.):

Tipo de combustível: Consumo médio mensal, em litros:

� Consumo médio mensal de gás (aquecedores, restaurantes etc.):

� - Botijões (botijas/ano) Quantidade: � - 2kg/4,8L � - 13kg/31L � - 20kg/48L � - 45kg/108L � - 90kg/216L

� - Granel / Encanado (m3/mês) � Consumo de água em quantidade média per capta mensal:

� - litros/mês Quantidade: � - m3/mês

� Produção de esgoto em quantidade média per capta mensal:

� - litros/mês Quantidade: � - m3/mês

� Quantidade de papel utilizada, em kg/mês:

Tipo de papel: Quantidade:


⇒ Emissões indiretamente relacionadas às ações da empresa. � Meios de transporte rodoviários:

Carro de Passeio:

Motor Distância percorrida (km/mês) Gasolina de 1.0 a 1.4 Gasolina de 1.5 a 2.0

Diesel de 1.0 a 1.4 Diesel de 1.5 a 2.0 GNV de 1.0 a 1.4 GNV de 1.5 a 2.0

Ônibus:

Motor Distância percorrida (km/mês) Diesel GNV

Viagens aéreas:

Trecho (de onde para onde) Situação Número de vôos/ano � - somente ida

� - ida e volta

� - somente ida � - ida e volta





ANEXO 02

Metodologia ACM0002 “Consolidated

baseline methodology for grid-connected

electricity generation from renewable

sources”

UNFCCC/CCNUCC CDM � Executive Board ACM0002 / Version 02 Sectoral Scope: 1 3 December 2004

1

Approved consolidated baseline methodology ACM0002

“Consolidated baseline methodology for

grid-connected electricity generation from renewable sources” Sources This consolidated baseline methodology is based on elements from the following proposed new methodologies:

- NM0001 rev: Vale do Rosario Bagasse Cogeneration (VRBC) project in Brazil whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Econergy International Corporation;

- NM0012-rev: Wigton Wind Farm Project in Jamaica whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Ecosecurities ltd;

- NM0023: El Gallo Hydroelectric Project, Mexico whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Prototype Carbon Fund (approved by the CDM Executive Board on 14 April 2004);

- NM0024-rev: Colombia: Jepirachi Windpower Project whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Prototype Carbon Fund;

- NM0030-rev: Haidergarh Bagasse Based Co-generation Power Project in India whose Baseline study, Monitoring and Verification Plan and Project Design Document was submitted by Haidergarh Chini Mills, a unit of Balrampur Chini Mills Limited;

- NM0036: Zafarana Wind Power Plant Project in the Arab Republic of Egypt whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Mitsubishi Securities;

- NM0043: Bayano Hydroelectric Expansion and Upgrade Project in Panama whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Econergy International Corporation;

- NM0055: Darajat Unit III Geothermal Project in Indonesia whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by URS Corporation and Amoseas Indonesia Inc.

For more information regarding the proposal and its consideration by the Executive Board please refer to http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html. Applicability This methodology is applicable to grid-connected renewable power generation project activities under the following conditions: • Applies to electricity capacity additions from:

• Run-of-river hydro power plants; hydro power projects with existing reservoirs where the volume of the reservoir is not increased.

• Wind sources; • Geothermal sources; • Solar sources; • Wave and tidal sources.


2

• This methodology is not applicable to project activities that involve switching from fossil fuels to renewable energy at the site of the project activity, since in this case the baseline may be the continued use of fossil fuels at the site;

• The geographic and system boundaries for the relevant electricity grid can be clearly identified and information on the characteristics of the grid is available; and

• Applies to grid connected electricity generation from landfill gas capture to the extent that it is combined with the approved "Consolidated baseline methodology for landfill gas project activities� (ACM0001).

This baseline methodology shall be used in conjunction with the approved monitoring methodology ACM0002 (�Consolidated monitoring methodology for grid-connected electricity generation from renewable sources�). Project activity The project activity is grid-connected electricity generation from renewable energy sources. There are a number of different sizes and sub-types of this project activity (Run-of-river hydro power plants; hydro power projects with existing reservoirs where the volume of the reservoir is not increased, wind, geothermal, solar sources, tidal, wave). Approach �Existing actual or historical emissions, as applicable� or �Emissions from a technology that represents an economically attractive course of action, taking into account barriers to investment� Additionality The additionality of the project activity shall be demonstrated and assessed using the latest version of the “Tool for the demonstration and assessment of additionality” agreed by the CDM Executive Board, which is available on the UNFCCC CDM web site1. Project Boundary 1) Project participants shall account only the following emission sources for the project activity:

• For geothermal project activities, fugitive emissions of methane and carbon dioxide from non-condensable gases contained in geothermal steam and carbon dioxide emissions from combustion of fossil fuels required to operate the geothermal power plant.

For the baseline determination, project participants shall only account CO2 emissions from electricity generation in fossil fuel fired power that is displaced due to the project activity. 2) The spatial extent of the project boundary includes the project site and all power plants connected physically to the electricity system that the CDM project power plant is connected to. For the purpose of determining the build margin (BM) and operating margin (OM) emission factor, as described below, a (regional) project electricity system is defined by the spatial extent of the power 1 Please refer to: < http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html>


3

plants that can be dispatched without significant transmission constraints. Similarly, a connected electricity system, e.g. national or international, is defined as a (regional) electricity system that is connected by transmission lines to the project electricity system and in which power plants can be dispatched without significant transmission constraints. In determining the project electricity system, project participants should justify their assumptions. Electricity transfers from connected electricity systems to the project electricity system are defined as electricity imports and electricity transfers to connected electricity systems are defined as electricity exports. For the purpose of determining the Build Margin (BM) emission factor, as described below, the spatial extent is limited to the project electricity system, except where recent or likely future additions to transmission capacity enable significant increases in imported electricity. In such cases, the transmission capacity may be considered a build margin source, with the emission factor determined as for the OM imports below. For the purpose of determining the Operating Margin (OM) emission factor, as described below, use one of the following options to determine the CO2 emission factor(s) for net electricity imports (COEFi,j,imports) from a connected electricity system within the same host country(ies):

(a) 0 tCO2/MWh, or (b) the emission factor(s) of the specific power plant(s) from which electricity is imported, if and

only if the specific plants are clearly known, or (c) the average emission rate of the exporting grid, if and only if net imports do not exceed 20% of

total generation in the project electricity system, or (d) the emission factor of the exporting grid, determined as described in steps 1,2 and 3 below, if

net imports exceed 20% of the total generation in the project electricity system. For imports from connected electricity system located in another country, the emission factor is 0 tons CO2 per MWh. Electricity exports should not be subtracted from electricity generation data used for calculating and monitoring the baseline emission rate. Baseline Which of the plausible alternatives scenarios, as listed in step 1 of the additionality text, is the most likely baseline scenario? Please provide thorough explanation to justify your choice, based on the factors (investment or other barriers) described in the additionality methodology. This methodology is applicable only if the most likely baseline scenario is electricity production from other sources feeding into the grid. The baseline scenario is the following: electricity would have otherwise been generated by the operation of grid-connected power plants and by the addition of new generation sources. For project activities that modify or retrofit an existing electricity generation facility, the guidance provided by EB08 shall be taken into account.2 2 �If a proposed CDM project activity seeks to retrofit or otherwise modify an existing facility, the baseline may refer to the characteristics (i.e. emissions) of the existing facility only to the extent that the project activity does not increase the output or lifetime of the existing facility. For any increase of output or lifetime of the facility which is due to the project activity, a different baseline shall apply." (EB08, Annex 1, http://cdm.unfccc.int/EB/Meetings/).


4

A baseline emission factor (EFy) is calculated as a combined margin (CM), consisting of the combination of operating margin (OM) and build margin (BM) factors according to the following three steps. Calculations for this combined margin must be based on data from an official source (where available)3 and made publicly available. STEP 1. Calculate the Operating Margin emission factor(s) (EFOM,y) based on one of the four following methods:

(a) Simple OM, or (b) Simple adjusted OM, or (c) Dispatch Data Analysis OM, or (d) Average OM.

Each method is described below. Dispatch data analysis should be the first methodological choice. Where this option is not selected project participants shall justify why and may use the simple OM, the simple adjusted OM or the average emission rate method taking into account the provisions outlined hereafter. The Simple OM method (a) can only be used where low-cost/must run resources4 constitute less than 50% of total grid generation in: 1) average of the five most recent years, or 2) based on long-term normals for hydroelectricity production. The average emission rate method (d) can only be used

• where low-cost/must run resources constitute more than 50% of total grid generation and detailed data to apply option (b) is not available, and

• where detailed data to apply option (c) above is unavailable.

3 Plant emission factors used for the calculation of operating and build margin emission factors should be obtained in the following priority: 1. acquired directly from the dispatch center or power producers, if available; or 2. calculated, if data on fuel type, fuel emission factor, fuel input and power output can be obtained for each

plant; if confidential data available from the relevant host Party authority are used the calculation carried out by the project participants shall be verified by the DOE and the CDM-PDD may only show the resultant carbon emission factor and the corresponding list of plants.

3. calculated, as above, but using estimates such as • default IPCC values from the IPCC 1996 Revised Guidelines and the IPCC Good Practice Guidance for

net calorific values and carbon emission factors for fuels instead of plant-specific values (note that the IPCC Good Practice Guidance includes some updates from the IPCC 1996 Revised Guidelines);

• technology provider�s name plate power plant efficiency or the anticipated energy efficiency documented in official sources (instead of calculating it from fuel consumption and power output). This is likely to be a conservative estimate, because under actual operating conditions plants usually have lower efficiencies and higher emissions than name plate performance would imply;

• conservative estimates of power plant efficiencies, based on expert judgments on the basis of the plant�s technology, size and commissioning date; or

4. calculated, for the simple OM and the average OM, using aggregated generation and fuel consumption data, in cases where more disaggregated data is not available.

4 Low operating cost and must run resources typically include hydro, geothermal, wind, low-cost biomass, nuclear and solar generation. If coal is obviously used as must-run, it should also be included in this list, i.e. excluded from the set of plants.


5

(a) Simple OM. The Simple OM emission factor (EFOM,simple,y) is calculated as the generation-weighted average emissions per electricity unit (tCO2/MWh) of all generating sources serving the system, not including low-operating cost and must-run power plants:

∑∑ ⋅

=

jyj

jiji

yji

ysimpleOM GEN

COEFF

EF,

,,

,,

,, (1)

where Fi ,j, y is the amount of fuel i (in a mass or volume unit) consumed by relevant power sources j in year(s) y, j refers to the power sources delivering electricity to the grid, not including low-operating cost and must-run power plants, and including imports5to the grid, COEFi,j y is the CO2 emission coefficient of fuel i (tCO2 / mass or volume unit of the fuel), taking into account the carbon content of the fuels used by relevant power sources j and the percent oxidation of the fuel in year(s) y, and GENj,y is the electricity (MWh) delivered to the grid by source j. The CO2 emission coefficient COEFi is obtained as

iiCOii OXIDEFNCVCOEF ⋅⋅= ,2 (2) where: NCVi is the net calorific value (energy content) per mass or volume unit of a fuel i, OXIDi is the oxidation factor of the fuel (see page 1.29 in the 1996 Revised IPCC Guidelines for default values), EFCO2,i is the CO2 emission factor per unit of energy of the fuel i. Where available, local values of NCVi and EFCO2,i should be used. If no such values are available, country-specific values (see e.g. IPCC Good Practice Guidance) are preferable to IPCC world-wide default values. The Simple OM emission factor can be calculated using either of the two following data vintages for years(s) y:

• A 3-year average, based on the most recent statistics available at the time of PDD submission, or

• The year in which project generation occurs, if EFOM,y is updated based on ex post monitoring.

(b) Simple Adjusted OM. This emission factor (EFOM,simple adjusted,y) is a variation on the previous

method, where the power sources (including imports) are separated in low-cost/must-run power sources (k) and other power sources (j):

( )∑

∑∑

∑ ⋅⋅+

⋅⋅−=

kyk

kikiyki

y

jyj

jijiyji

yyadjustedsimpleOM GEN

COEFF

GEN

COEFFEF

,

,,,,

,

,,,,

,, 1 λλ (3)

5 As described above, an import from a connected electricity system should be considered as one power source j.


6

where Fi,k,y, COEFi,k and GENk are analogous to the variables described for the simple OM method above for plants k; the years(s) y can reflect either of the two vintages noted for simple OM above, and

( )yearper hours 8760

margin on the are sourcesrun -cost/must-lowwhichforyearperhoursofNumber% =yλ (4)

where lambda (λy ) should be calculated as follows (see figure below): Step i) Plot a Load Duration Curve. Collect chronological load data (typically in MW) for each

hour of a year, and sort load data from highest to lowest MW level. Plot MW against 8760 hours in the year, in descending order.

Step ii) Organize Data by Generating Sources. Collect data for, and calculate total annual generation (in MWh) from low-cost/must-run resources (i.e. ∑k GENk,y).

Step iii) Fill Load Duration Curve. Plot a horizontal line across load duration curve such that the area under the curve (MW times hours) equals the total generation (in MWh) from low-cost/must-run resources (i.e. ∑k GENk,y).

Step iv) Determine the �Number of hours per year for which low-cost/must-run sources are on the margin�. First, locate the intersection of the horizontal line plotted in step (iii) and the load duration curve plotted in step (i). The number of hours (out of the total of 8760 hours) to the right of the intersection is the number of hours for which low-cost/must-run sources are on the margin. If the lines do not intersect, then one may conclude that low-cost/must-run sources do not appear on the margin and λy is equal to zero. Lambda (λy) is the calculated number of hours divided by 8760.


7

Figure 1: Illustration of Lambda Calculation for Simple Adjusted OM Method

0 8760Hours

MW

Step i: Draw Load Duration Curve

Step iii: Fill Curve with Low-Cost/Must-Run Generation (MWh)

Intersection Point

Step Iv: Estimate hours Low-Cost/ Must-Run on the margin

λ = X / 8760 X hours

Note: Step (ii) is not shown in the figure, it deals with organizing data by source.

(c) Dispatch Data Analysis OM. The Dispatch Data OM emission factor (EFOM,Dispatch Data,y) is

summarized as follows:

y

yOMyDataDispatchOM EG

EEF ,

,, = (5)

where EGy is the generation of the project (in MWh) in year y, and EOM.y are the emissions (tCO2) associated with the operating margin calculated as

hDDh

hyOM EFEGE ,, ⋅=∑ (6)

where EGh is the generation of the project (in MWh) in each hour h and EFDD,h is the hourly generation-weighted average emissions per electricity unit (tCO2/MWh) of the set of power plants (n) in the top 10% of grid system dispatch order during hour h:

∑∑ ⋅

=

nhn

ninihni

hDD GEN

COEFF

EF,

,,,,

, (7)


8

where F, COEF and GEN are analogous to the variables described for the simple OM method above, but calculated on an hourly basis for the set of plants (n) falling within the top 10% of the system dispatch. To determine the set of plants (n), obtain from a national dispatch center: a) the grid system dispatch order of operation for each power plant of the system; and b) the amount of power (MWh) that is dispatched from all plants in the system during each hour that the project activity is operating (GENh). At each hour h, stack each plant�s generation (GENh) using the merit order. The set of plants (n) consists of those plants at the top of the stack (i.e., having the least merit), whose combined generation (∑ GENh) comprises 10% of total generation from all plants during that hour (including imports to the extent they are dispatched).

(d) Average OM. The average Operating Margin (OM) emission factor (EFOM,average,y) is calculated as the average emission rate of all power plants, using equation (1) above, but including low-operating cost and must-run power plants. Either of the two data vintages described for the simple OM (a) may be used.

STEP 2. Calculate the Build Margin emission factor (EFBM,y) as the generation-weighted average emission factor (tCO2/MWh) of a sample of power plants m, as follows:

∑∑ ⋅

=

mym

mimiymi

yBM GEN

COEFF

EF,

,,,,

, (8)

where Fi,m,y, COEFi,m and GENm,y are analogous to the variables described for the simple OM method above for plants m. Project participants shall choose between one of the following two options: Option 1. Calculate the Build Margin emission factor EFBM,y ex ante based on the most recent information available on plants already built for sample group m at the time of PDD submission. The sample group m consists of either

• the five power plants that have been built most recently, or • the power plants capacity additions in the electricity system that comprise 20% of the system

generation (in MWh) and that have been built most recently. Project participants should use from these two options that sample group that comprises the larger annual generation. Option 2. For the first crediting period, the Build Margin emission factor EFBM,y must be updated annually ex post for the year in which actual project generation and associated emissions reductions occur. For subsequent crediting periods, EFBM,y should be calculated ex-ante, as described in option 1 above. The sample group m consists of either

• the five power plants that have been built most recently, or • the power plants capacity additions in the electricity system that comprise 20% of the system

generation (in MWh) and that have been built most recently. Project participants should use from these two options that sample group that comprises the larger annual generation. Power plant capacity additions registered as CDM project activities should be excluded from the sample group m.


9

STEP 3. Calculate the baseline emission factor EFy as the weighted average of the Operating Margin emission factor (EFOM,y) and the Build Margin emission factor (EFBM,y):

yBMBMyOMOMy EFwEFwEF ,, ⋅+⋅= (9)

where the weights wOM and wBM, by default, are 50% (i.e., wOM = wBM = 0.5), and EFOM,y and EFBM,y are calculated as described in Steps 1 and 2 above and are expressed in tCO2/MWh. Alternative weights can be used, as long as wOM + wBM = 1, and appropriate evidence justifying the alternative weights is presented. These justifying elements are to be assessed by the Executive Board.6 The weighted average applied by project participants should be fixed for a crediting period and may be revised at the renewal of the crediting period. Leakage The main emissions potentially giving rise to leakage in the context of electric sector projects are emissions arising due to activities such as power plant construction, fuel handling (extraction, processing, and transport), and land inundation (for hydroelectric projects � see applicability conditions above). Project participants do not need to consider these emission sources as leakage in applying this methodology. Project activities using this baseline methodology shall not claim any credit for the project on account of reducing these emissions below the level of the baseline scenario. Emission Reductions The project activity mainly reduces carbon dioxide through substitution of grid electricity generation with fossil fuel fired power plants by renewable electricity. The emission reduction ERy by the project activity during a given year y is the difference between baseline emissions (BEy), project emissions (PEy) and emissions due to leakage (Ly), as follows:

yyyy LPEBEER −−= (10)

where the baseline emissions (BEy in tCO2) are the product of the baseline emissions factor (EFy in tCO2/MWh) calculated in Step 3, times the electricity supplied by the project activity to the grid (EGy in MWh), as follows:

yyy EFEGBE ⋅= (11)

For most renewable energy project activities, PEy = 0. However, for geothermal project activities, project participants shall account the following emission sources7, where applicable:

• Fugitive emissions of carbon dioxide and methane due to release of non-condensable gases from produced steam; and

• Carbon dioxide emissions resulting from combustion of fossil fuels related to the operation of the geothermal power plant.

6 More analysis on other possible weightings may be necessary and this methodology could be revised based on this analysis. There might be a need to propose different weightings for different situations. 7 Fugitive carbon dioxide and methane emissions due to well testing and well bleeding are not considered as they are negligible.


10

The data to be collected are listed in the associated monitoring methodology, AM00XX. Project emissions should be calculated as follows: a) Fugitive carbon dioxide and methane emissions due to release of non-condensable gases

from the produced steam (PESy):

( ) ySCHCHMainCOMainy MGWPwwPES ,44,2, ⋅⋅+= (12) where PESy are the project emissions due to release of carbon dioxide and methane from the produced steam during the year y, wMain,CO2 and wMain,CH4 are the average mass fractions of carbon dioxide and methane in the produced steam, GWPCH4 is the global warming potential of methane and MS,y is the quantity of steam produced during the year y.

b) Carbon dioxide emissions from fossil fuel combustion (PEFFy)

ii

yiy COEFFPEFF ⋅=∑ , (13)

where PEFFy are the project emissions from combustion of fossil fuels related to the operation of the geothermal power plant in tons of CO2, Fi,y is the fuel consumption of fuel type i during the year y and COEFi is the CO2 emission factor coefficient of the fuel type i.

Thus, for geothermal project activities, PEy = PESy+ PEFFy (14) Estimation of Emissions Reductions Prior to Validation Project participants should prepare as part of the PDD an estimate of likely project emission reductions for the proposed crediting period. This estimate should, in principle, employ the same methodology as selected above (i.e. OM option 1a, 1b, 1c or 1d). Where the emission factor (EFy) is determined ex-post during monitoring, project participants may use models or other tools to estimate the emission reductions prior to validation.


11

Approved consolidated monitoring methodology ACM0002

“Consolidated monitoring methodology for zero-emissions grid-connected electricity generation from renewable sources”

Sources This monitoring methodology is based on elements from the following proposed new methodologies:

- NM0001 rev: Vale do Rosario Bagasse Cogeneration (VRBC) project in Brazil whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Econergy International Corporation.

- NM0012-rev: Wigton Wind Farm Project in Jamaica whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Ecosecurities ltd

- NM0023: El Gallo Hydroelectric Project, Mexico whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Prototype Carbon Fund (approved by the CDM Executive Board on 14 April 2004);

- NM0024-rev: Colombia: Jepirachi Windpower Project whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Prototype Carbon Fund;

- NM0030-rev: Haidergarh Bagasse Based Co-generation Power Project in India whose Baseline study, Monitoring and Verification Plan and Project Design Document was submitted by Haidergarh Chini Mills, a unit of Balrampur Chini Mills Limited

- NM0036: Zafarana Wind Power Plant Project in the Arab Republic of Egypt whose Baseline study, Monitoring and Verification Plan and Project Design Document -were prepared by Mitsubishi Securities;

- NM0043: Bayano Hydroelectric Expansion and Upgrade Project in Panama whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Econergy International Corporation.

- NM0055: Darajat Unit III Geothermal Project in Indonesia whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by URS Corporation and Amoseas Indonesia Inc.

For more information regarding the proposal and its consideration by the Executive Board please refer to http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html. Applicability This monitoring methodology shall be used in conjunction with the approved baseline methodology ACM0002 (�Consolidated baseline methodology for grid-connected electricity generation from renewable sources�) and: • Applies to electricity capacity additions from:

• Run-of-river hydro power plants; hydro power projects with existing reservoirs where the volume of the reservoir is not increased;

• Wind sources; • Geothermal sources; • Solar sources; • Wave and tidal sources.

• This methodology is not applicable to project activities that involve switching from fossil fuels to renewable energy at the site of the project activity, since in this case the baseline may be the continued use of fossil fuels at the site;


12

• The geographic and system boundaries for the relevant electricity grid can be clearly identified and information on the characteristics of the grid is available; and

• Applies to grid connected electricity generation from landfill gas capture to the extent that it is combined with the approved "Consolidated baseline methodology for landfill gas project activities� (ACM0001).

Monitoring Methodology The methodology requires monitoring of the following: • Electricity generation from the proposed project activity; • Data needed to recalculate the operating margin emission factor, if needed, based on the choice of

the method to determine the operating margin (OM), consistent with �Consolidated baseline methodology for grid-connected electricity generation from renewable sources� (ACM0002);

• Data needed to recalculate the build margin emission factor, if needed, consistent with �Consolidated baseline methodology for grid-connected electricity generation from renewable sources� (ACM0002);

• For geothermal power projects, data needed to calculate fugitive carbon dioxide and methane emissions and carbon dioxide emissions from combustion of fossil fuels required to operate the geothermal power plant.

Project boundary 1) Consistent with the �Consolidated baseline methodology for grid-connected electricity generation from renewable sources� (ACM0002) the project boundary includes the following emissions sources:

• For geothermal project activities, fugitive emissions of methane and carbon dioxide from non-condensable gases contained in geothermal steam and carbon dioxide emissions from combustion of fossil fuels required to operate the geothermal power plant.

For the baseline determination, project participants shall only account CO2 emissions from electricity generation in fossil fuel fired power that is displaced due to the project activity. 2) The spatial extent of the project boundary includes the project site and all power plants connected physically to the electricity system that the CDM project power plant is connected to.

UNFCCC/CCNUCC CDM � Executive Board ACM0002/ Version 02 Sectoral Scope: 1 3 December 2004

13

Baseline Emission Parameters The 6th column indicates which monitoring elements are required depending on which method is used to determine the operating margin (OM) in step 1 of the �Consolidated baseline methodology for grid-connected electricity generation from renewable sources� (ACM0002) �Simple OM� is defined in step 1a; �Simple Adjusted OM� in 1b; �Dispatch Data OM� in 1c; and �Average OM� in step 1d. Items required for �BM� are for the Build Margin defined in step 2. Note that for the �Simple OM�, �Simple Adjusted OM� and the �Average OM� as well as the �BM, where project participants choose, consistent with �Consolidated baseline methodology for grid-connected electricity generation from renewable sources� (ACM0002), a data vintage based on ex ante monitoring, at least EGy shall be monitored, and all parameters will be required to recalculate the combined margin at any renewal of a crediting period, using steps 1-3 in the baseline methodology.

ID number

Data type

Data variable

Data unit

Measured (m)

calculated (c)

estimated (e)

For which baseline

method(s) must this element be

included

Recording frequency

Proportion of data

monitored

How will data be

archived? (electronic/

paper)

For how long is archived data kept?

Comment

1. EGy (EGh if

dispatch data OM is used)

Electricity quantity

Electricity supplied to

the grid by the project

MWh Directly measured

Simple OM Simple Adjusted OMDispatch Data OM

Average OM BM

hourly measure-ment and monthly

recording

100% electronic

During the crediting

period and two years after

Electricity supplied by the project activity to the grid. Double check by receipt of sales.

2. EFy Emission

factor

CO2 emission factor of the

grid

tCO2 /MWh c


Average OM BM

yearly 100% electronic



Calculated as a weighted sum of the OM and BM emission factors

3. EFOM,y Emission

factor

CO2 Operating

Marin emission

factor of the grid

tCO2 /MWh c


Average OM




Calculated as indicated in the relevant OM baseline method above


14

ID number

Data type

Data variable

Data unit

Measured (m)

calculated (c)

estimated (e)

For which baseline


included

Recording frequency

Proportion of data

monitored

How will data be


paper)


Comment

4. EFBM,y Emission

factor

CO2 Build Margin

emission factor of the

grid

tCO2 /MWh c BM yearly 100% electronic



Calculated as [∑i Fi,y*COEFi] / [∑m GENm,y] over recently built power plants defined in the baseline methodology

5. Fi,y Fuel

quantity

Amount of each fossil

fuel consumed by each power source / plant

Mass or

volumem


Average OM BM




Obtained from the power producers, dispatch centers or latest local statistics.

6. COEFi Emission

factor coefficient

CO2 emission coefficient of each fuel type

i

tCO2 / mass

or volume unit

m


Average OM BM




Plant or country-specific values to calculate COEF are preferred to IPCC default values.

7. GENj/k/n,,y


Electricity generation of each power

source / plant j, k or n

MWh/a m


Average OM BM




Obtained from the power producers, dispatch centers or latest local statistics.

8. Plant name

Identification of power

source / plant for the OM

Text e


Average OM

yearly 100% of set of plants electronic



Identification of plants (j, k, or n) to calculate Operating Margin emission factors


15

ID number

Data type

Data variable

Data unit

Measured (m)

calculated (c)

estimated (e)

For which baseline


included

Recording frequency

Proportion of data

monitored

How will data be


paper)


Comment

9. Plant name

Identification of power

source / plant for the BM

Text e BM yearly 100% of set of plants electronic



Identification of plants (m) to calculate Build Margin emission factors

10. λy Parameter

Fraction of time during which low-

cost/must-run sources are on

the margin

Number c Simple Adjusted OM yearly 100% electronic



Factor accounting for number of hours per year during which low-cost/must-run sources are on the margin

11. Merit order

The merit order in which power plants

are dispatched by

documented evidence

Text m Dispatch Data OM yearly 100%

paper for original

documents, else

electronic



Required to stack the plants in the dispatch data analysis.

11a. GENj/k/ll,y

IMPORTS


Electricity imports to the

project electricity

system

kWh c


Average OM BM




Obtained from the latest local statistics. If local statistics are not available, IEA statistics are used to determine imports.


16

ID number

Data type

Data variable

Data unit

Measured (m)

calculated (c)

estimated (e)

For which baseline


included

Recording frequency

Proportion of data

monitored

How will data be


paper)


Comment

11b. COEFi,j y

IMPORTS

Emission factor

coefficient

CO2 emission coefficient of fuels used in

connected electricity systems (if

imports occur)

tCO2 / mass

or volume unit

c


Average OM BM




Obtained from the latest local statistics. If local statistics are not available, IPCC default values are used to calculate.

Project emissions (for geothermal projects)

ID number Data type Data variable

Data unit

Measured (m),

calculated (c) or

estimated (e)

Recording frequency

Proportion of data to be monitored

How will the data be


paper)

For how long is archived data kept? Comment

12. MS,y Mass

quantity

Quantity of steam produced during the year

y

t m daily 100% electronic During the crediting period and two years

after See note 1

13. wMain,CO2

Mass fraction

Fraction of CO2 in produced

steam

tCO2 / t steam m every 4

months 100% electronic During the crediting period and two years

after See note 2

14. wMain,CH4

Mass fraction

Fraction of CH4 in produced

steam

tCH4 / t steam m every 4

months 100% electronic During the crediting period and two years

after See note 2


17

ID number Data type Data variable

Data unit

Measured (m),

calculated (c) or

estimated (e)

Recording frequency

Proportion of data to be monitored

How will the data be


paper)

For how long is archived data kept? Comment

15. Mt,y Mass

quantity

Quantity of steam generated

during well testing

t m daily 100% electronic During the crediting period and two years

after See note 1

16. wt,CO2

Mass fraction

Fraction of CO2 in steam during

well testing

tCO2 / t steam m as required 100% electronic

During the crediting period and two years

after See note 2

17. wt,CH4

Mass fraction

Fraction of CO2 in steam during

well testing

tCH4 / t steam m as required 100% electronic


after See note 2

18. Fi,y Fuel

quantities

Amount of fossil fuels used for the operation

of the geothermal

plant

Mass or volume m monthly 100% electronic


after

19. COEFi

Emission factors

coefficient

CO2 emission coefficients of

fossil fuels types i used for the

operation of the geothermal

plant

tCO2 / mass or volume

unit

m as required 100% electronic During the crediting period and two years

after

Plant or country-specific values to calculate COEF are preferred to IPCC default values.


18

Note 1: Flow rates 1a. Steam flow rate, power plant The steam quantity discharged from the geothermal wells should be measured with a venture flow meter (or other equipment with at least the same accuracy). Measurement of temperature and pressure upstream of the venture meter is required to define the steam properties. The calculation of steam quantities should be conducted on a continuous basis and should be based on international standards. The measurement results should be summarized transparently in regular production reports. Note 2: Non-condensable gases in geothermal steam Non-condensable gases (NCGs) in geothermal reservoirs usually consist mainly of CO2 and H2S. They also contain a small quantity of hydrocarbons, including predominantly CH4. In geothermal power projects, NCGs flow with the steam into the power plant. A small proportion of the CO2 is converted to carbonate / bicarbonate in the cooling water circuit. In addition, parts of the NCGs are reinjected into the geothermal reservoir. However, as a conservative approach, this methodology assumes that all NCGs entering the power plant are discharged to atmosphere via the cooling tower. NCG sampling should be carried out in production wells and at the steam field-power plant interface using ASTM Standard Practice E1675 for Sampling 2-Phase Geothermal Fluid for Purposes of Chemical Analysis (as applicable to sampling single phase steam only). The CO2 and CH4 sampling and analysis procedure consists of collecting NCG samples from the main steam line with glass flasks, filled with sodium hydroxide solution and additional chemicals to prevent oxidation. Hydrogen sulphide (H2S) and carbon dioxide (CO2) dissolve in the solvent while the residual compounds remain in their gaseous phase. The gas portion is then analyzed using gas chromatography to determine the content of the residuals including CH4. All alkanes concentrations are reported in terms of methane. The NCG sampling and analysis should be performed at least every three months and more frequently, if necessary.


19

Quality Control (QC) and Quality Assurance (QA) Procedures All variables, except one related to off-site transportation, used to calculate project and baseline emissions are directly measured or are publicly available official data. To ensure the quality of the data, in particular those that are measured, the data are double-checked against commercial data. The quality control and quality assurance measures planned for the Project are outlined in the following table.

Data Uncertainty Level of

Data (High/Medium/Low)

Are QA/QC procedures planned for these data? Outline explanation how QA/QC procedures are planned

1. Low Yes These data will be directly used for calculation of emission reductions. Sales record to the grid and other records are used to ensure the consistency.

Others Low Yes Default data (for emission factors) and IEA statistics (for energy data) are used to check the local data.

UNFCCC/CCNUCC CDM � Executive Board ACM0002/ Version 02 Sectoral Scope: 1 3 December2004

20

Baseline Data For default emission factors, IPCC 1996 Guidelines on GHG Inventory (The Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, IPCC) and Good Practice Guidance Report (Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories, IPCC) are to be referred not only for their default values but also for their monitoring methodology as well as uncertainty management to ensure data credibility. These documents are downloadable from http://www.ipcc-nggip.iges.or.jp/. The latter document is a new supplementary document of the former. 1996 Guidelines: Vol. 2, Module 1 (Energy) for methodology, Vol. 3, Module 1 (Energy) for application (including default values) 2000 Good Practice Guidance on GHG Inventory and Uncertainty Management Chapter 2: Energy Chapter 6: Uncertainty IEA (Yearly Statistics)

CO2 Emissions from Fuel Combustion Energy Statistics of Non-OECD Countries


ANEXO 03

Metodologia AMS I.D ‘Grid connected

renewable electricity generation’

UNFCCC/CCNUCC _______________________________________________________________________________ CDM – Executive Board I.D./Version 11 Sectoral Scope: 1

EB 31

Indicative simplified baseline and monitoring methodologies for selected small-scale CDM project activity categories

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TYPE I - RENEWABLE ENERGY PROJECTS

Note: Categories I.A, I.B and I.C involve renewable energy technologies that supply electricity, mechanical and thermal energy, respectively, to the user directly. Renewable energy technologies that supply electricity to a grid fall into category I.D.

Project participants shall take into account the general guidance to the methodologies, information on additionality, abbreviations and general guidance on leakage provided at http://cdm.unfccc.int/methodologies/SSCmethodologies/approved.html.

I.D. ‘Grid connected renewable electricity generation’

Technology/measure

1. This category comprises renewable energy generation units, such as photovoltaics, hydro, tidal/wave, wind, geothermal and renewable biomass, that supply electricity to and/or displace electricity from an electricity distribution system that is or would have been supplied by at least one fossil fuel fired generating unit.

2. If the unit added has both renewable and non-renewable components (e.g.. a wind/diesel unit), the eligibility limit of 15MW for a small-scale CDM project activity applies only to the renewable component. If the unit added co-fires fossil fuel1, the capacity of the entire unit shall not exceed the limit of 15MW.

3. Combined heat and power (co-generation) systems are not eligible under this category.

4. In the case of project activities that involve the addition of renewable energy generation units at an existing renewable power generation facility, the added capacity of the units added by the project should be lower than 15 MW and should be physically distinct2 from the existing units.

5. Project activities that seek to retrofit or modify an existing facility for renewable energy generation are included in this category. To qualify as a small scale project, the total output of the modified or retrofitted unit shall not exceed the limit of 15 MW.

Boundary

6. The project boundary encompasses the physical, geographical site of the renewable generation source.

1 Co-fired system uses both fossil and renewable fuels. 2 Physically distinct units are those that are capable of generating electricity without the operation of existing units, and that do not directly affect the mechanical, thermal, or electrical characteristics of the existing facility. For example, the addition of a steam turbine to an existing combustion turbine to create a combined cycle unit would not be considered “physically distinct”.

UNFCCC/CCNUCC _______________________________________________________________________________ CDM – Executive Board I.D./Version 11 Sectoral Scope: 1 EB 31

Indicative simplified baseline and monitoring methodologies

for selected small-scale CDM project activity categories I.D. Grid connected renewable electricity generation (cont)

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Baseline

7. In the case of landfill gas, waste gas, wastewater treatment and agro-industries projects, recovered methane emissions are eligible under a relevant type III category. If the recovered methane is used for electricity generation the baseline shall be calculated in accordance with paragraphs below. If the recovered methane is used for heat generation it is eligible under category I.C.

8. For a system where all generators use exclusively fuel oil and/or diesel fuel, the baseline is the annual kWh generated by the renewable unit times an emission coefficient for a modern diesel generating unit of the relevant capacity operating at optimal load as given in Table I.D.1.

Table I.D.1

Emission factors for diesel generator systems (in kg CO2e/kWh*) for three different levels of load factors**

Cases: Load factors [%]

Mini-grid with 24 hour service

25%

i) Mini-grid with temporary service (4-6 hr/day)

ii) Productive applications iii) Water pumps

50%

Mini-grid with storage

100% <15 kW 2.4 1.4 1.2 >=15 <35 kW 1.9 1.3 1.1 >=35 <135 kW 1.3 1.0 1.0 >=135<200 kW 0.9 0.8 0.8 > 200 kW*** 0.8 0.8 0.8

*) A conversion factor of 3.2 kg CO2 per kg of diesel has been used (following revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories) **) Figures are derived from fuel curves in the online manual of RETScreen lnternational’s PV 2000 model, downloadable from http://retscreen.net/ ***) default values

9. For all other systems, the baseline is the kWh produced by the renewable generating unit multiplied by an emission coefficient (measured in kg CO2e/kWh) calculated in a transparent and conservative manner as:

(a) A combined margin (CM), consisting of the combination of operating margin (OM) and build margin (BM) according to the procedures prescribed in the approved methodology ACM0002. Any of the four procedures to calculate the operating margin can be chosen, but the restrictions to use the Simple OM and the Average OM calculations must be considered




3/6

OR

(b) The weighted average emissions (in kg CO2e/kWh) of the current generation mix. The data of the year in which project generation occurs must be used.

Calculations must be based on data from an official source (where available)3 and made publicly

available.

10. In the case of project activities that involve the addition of renewable energy generation units at an existing renewable power generation facility, where the existing and new units share the use of common and limited renewable resources (e.g. streamflow, reservoir capacity, biomass residues), the potential for the project activity to reduce the amount of renewable resource available to, and thus electricity generation by, existing units must be considered in the determination of baseline emissions, project emissions, and/or leakage, as relevant.

For project activities that involve the addition of new generation units (e.g. turbines) at an existing facility, the increase in electricity production associated with the project (EGy in MWh/ year) should be calculated as follows:

EGy = TEy – WTEy

Where: TEy = the total electricity produced in year y by all units, existing and new project units;

WTEy = the estimated electricity that would have been produced by existing units (installed before the project activity) in year y in the absence of the project activity, where

WTEy = MAX(WTEactual,y ,WTEestimated,y)

3 Plant emission factors used for the calculation of emission factors should be obtained in the following priority:

1. Acquired directly from the dispatch center or power producers, if available; or 2. Calculated, if data on fuel type, fuel emission factor, fuel input and power output can be obtained for each plant; If confidential data available from the relevant host Party authority are used, the calculation carried out by the project participants shall be verified by the DOE and the CDM-PDD may only show the resultant carbon emission factor and the corresponding list of plants; 3. Calculated, as above, but using estimates such as: default IPCC values from the 2006 IPCC Guidelines for National GHG Inventories for net calorific values and carbon emission factors for fuels instead of plant-specific values technology provider’s name plate power plant efficiency or the anticipated energy efficiency documented in official sources (instead of calculating it from fuel consumption and power output). This is likely to be a conservative estimate, because under actual operating conditions plants usually have lower efficiencies and higher emissions than name plate performance would imply; conservative estimates of power plant efficiencies, based on expert judgments on the basis of the plant’s technology, size and commissioning date; or 4. Calculated, for the simple OM and the average OM, using aggregated generation and fuel consumption data, in cases where more disaggregated data is not available.




4/6

Where: WTEactual,y = the actual, measured electricity production of the existing units in year y; WTEestimated,y = the estimated electricity that would have been produced by the existing units under the observed availability of the renewable resource (e.g. hydrological conditions) for year y.

If the existing units shut down, are derated, or otherwise become limited in production, the project activity should not get credit for generating electricity from the same renewable resources that would have otherwise been used by the existing units (or their replacements). Therefore, the equation for WTE still holds, and the value for WTEestimated,y should continue to be estimated assuming the capacity and operating parameters same as that at the time of the start of the project activity.

If the existing units are subject to modifications or retrofits that increase production, then WTEy can be estimated using the procedures described for EGbaseline below.

11. For project activities that seek to retrofit or modify an existing facility for renewable energy generation the baseline scenario is the following:

In the absence of the CDM project activity, the existing facility would continue to provide electricity to the grid (EGbaseline, in MWh/year) at historical average levels (EGhistorical, in MWh/year), until the time at which the generation facility would be likely to be replaced or retrofitted in the absence of the CDM project activity (DATEBaselineRetrofit). From that point of time onwards, the baseline scenario is assumed to correspond to the project activity, and baseline electricity production (EGbaseline) is assumed to equal project electricity production (EGy, in MWh/year), and no emission reductions are assumed to occur.

EGbaseline = MAX(EGhistorical, EGestimated,y) until DATEBaselineRetrofit EGbaseline = EGy on/after DATEBaselineRetrofit

Baseline emissions (BEy in tCO2) are then, the product of the baseline emissions factor (EFy in tCO2/MWh) times the electricity supplied by the project activity to the grid (EGy in MWh) minus the baseline electricity supplied to the grid in the case of modified or retrofit facilities (EG baseline in MWh), as follows:

BEy = (EGy – EGbaseline ) · EFy

EGhistorical is the average of historical electricity delivered by the existing facility to the grid, spanning all data from the most recent available year (or month, week or other time period) to the time at which the facility was constructed, retrofit, or modified in a manner that significantly affected output (i.e., by 5% or more), expressed in MWh per year. A minimum of 5 years (60 months) (excluding abnormal years) of historical generation data is required in the case of hydro facilities. For other facilities, a minimum of 3 years data is required. In the case that 5 years of historical data (or three years in the case of non hydro project activities) are not available - e.g., due to recent retrofits or exceptional circumstances as described in footnote4 - a new methodology 4 Data for periods affected by unusual circumstances such as natural disasters, conflicts, and transmission constraints shall be excluded




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or methodology revision must be proposed.

EGestimated,y is the estimated electricity that would have been produced by the existing units under the observed availability of renewable resource (e.g. hydrological conditions) for year y.

All project electricity generation above baseline levels (EGbaseline) would have otherwise been generated by the operation of grid-connected power plants and by the addition of new generation sources, as reflected in the combined margin (CM) calculations described.

In order to estimate the point in time when the existing equipment would need to be replaced in the absence of the project activity (DATEBaselineRetrofit), project participants may take the following approaches into account:

(a) The typical average technical lifetime of the equipment type may be determined and documented, taking into account common practices in the sector and country, e.g. based on industry surveys, statistics, technical literature, etc.

(b) The common practices of the responsible company regarding replacement schedules may be evaluated and documented, e.g. based on historical replacement records for similar equipment.

The point in time when the existing equipment would need to be replaced in the absence of the project activity should be chosen in a conservative manner, i.e. if a range is identified, the earliest date should be chosen.

Leakage

12. If the energy generating equipment is transferred from another activity or if the existing equipment is transferred to another activity, leakage is to be considered.

Monitoring

13. Monitoring shall consist of metering the electricity generated by the renewable technology.

14. For projects where only biomass or biomass and fossil fuel are used the amount of biomass and fossil fuel input shall be monitored.

15. For projects consuming biomass a specific fuel consumption5 of each type of fuel (biomass or fossil) to be used should be specified ex-ante. The consumption of each type of fuel shall be monitored.

16. If fossil fuel is used the electricity generation metered should be adjusted to deduct electricity generation from fossil fuels using the specific fuel consumption and the quantity of fossil fuel consumed. 5 Specific fuel consumption is the fuel consumption per unit of electricity generated (e.g. tonnes of bagasse per MWh).




6/6

17. If more than one type of biomass fuel is consumed each shall be monitored separately.

18. The amount of electricity generated using biomass fuels calculated as per paragraph 16 shall be compared with the amount of electricity generated calculated using specific fuel consumption and amount of each type of biomass fuel used. The lower of the two values should be used to calculate emission reductions.


ANEXO 04

IPCC Guidelines, 1996, capítulo 6

R e v i s e d 1 9 9 6 I P C C G u i d e l i n e s f o r N a t i o n a l G r e e n h o u s e G a s I n v e n t o r i e s : R e f e r e n c e M a n u a l

C H A P T E R 6W A S T E

6 WASTE

R e v i s e d 1 9 9 6 I P C C G u i d e l i n e s f o r N a t i o n a l G r e e n h o u s e G a s I n v e n t o r i e s : R e f e r e n c e M a n u a l 6.1

6. WASTE

6 . 1 O v e r v i e wDisposal and treatment of industrial and municipal wastes can produce emissions of mostof the important greenhouse gases (GHG). Solid wastes can be disposed of throughlandfilling, recycling, incineration or waste-to-energy. This chapter will deal withemissions resulting from landfilling of solid waste, treatment of liquid wastes and wasteincineration. Greenhouse gas emissions from waste-to-energy, where waste material isused directly as fuel or converted into a fuel, should be calculated and reported under theEnergy Chapter.

The most important gas produced in this source category is methane (CH4).Approximately 5-20 per cent (IPCC, 1992) of annual global anthropogenic CH4 producedand released into the atmosphere is a by-product of the anaerobic decomposition ofwaste. Two major sources of this type of CH4 production are solid waste disposal toland and wastewater treatment. In each case, methanogenic bacteria break down organicmatter in the waste to produce CH4.

In previous editions of the IPCC Guidelines (1995), solid waste disposal sites werecharacterised as “open dumps” or “sanitary landfills,” both of which can produce CH4 ifthe waste deposited in them contains organic matter (IPCC, 1995). Open dumps weredefined as shallow, open piles, generally only loosely compacted, and with no provisionfor control of any pollutants generated, where scavenging by animals and humans canremove much of the biodegradable wastes. Sanitary landfills, in contrast, were defined assites specifically designed to receive wastes, which may manage these waste with practicessuch as compacting, use of liners, daily cover, and a final cap. Recognising that thedistinction between landfills and open dumps is not always clear, the Revised 1996 IPCCGuidelines (this chapter) instead characterises all sites at which solid waste is deposited toland as “solid waste disposal sites” (SWDSs).

In addition to CH4, solid waste disposal sites can also produce substantial amounts ofCO2 and non-methane volatile organic compounds (NMVOCs). Decomposition oforganic material derived from biomass sources (e.g., crops, forests) which are regrownon an annual basis is the primary source of CO2 released from waste. Hence, these CO2emissions are not treated as net emissions from waste in the IPCC Methodology. Ifbiomass raw materials are not being sustainably produced, the net CO2 release should becalculated and reported under the Agriculture and Land-Use Change and ForestryChapters.

The process of wastewater treatment produces NMVOCs as well as CH4 (CORINAIR,1994). These emissions are not currently addressed in the Revised Guidelines.Wastewater treatment is also a source of N2O, and a methodology for estimating N2Oemissions is included in this Chapter for human sewage. (Chapter 4 of these RevisedGuidelines addresses N2O emissions from agriculture, using a life-cycle emissionsapproach.)

Waste incineration, like all combustion, can produce CO2, CH4, CO, NOx, N2O andNMVOCs. No detailed methodologies are provided here for this source category.Instead, the section on waste incineration later in this chapter provides references tomethods available for some of the gases. For CH4 and N2O it is only possible to reportpreliminary estimates and research results at this time. Further studies are needed to

WASTE

6.2 R e v i s e d 1 9 9 6 I P C C G u i d e l i n e s f o r N a t i o n a l G r e e n h o u s e G a s I n v e n t o r i e s : R e f e r e n c e M a n u a l

give more information about GHG emissions from this source category. For additionalinformation, refer to the discussion of emissions from combustion in Chapter 1.

The sections in this chapter dealing with land disposal of solid waste and wastewatertreatment give background information on the source, describe a methodology toestimate CH4 and N2O emissions, and discuss uncertainties associated with estimatingemissions. This is consistent with the priorities under the IPCC Methodologyprogramme. National experts are encouraged to report any other relevant emissions forwhich data are available, along with documentation of methods used. This will greatlyassist in the development of more complete methods for future editions of IPCCGuidelines. For information on estimation procedures and emissions factors for otherGHGs which are currently not provided in this chapter, experts should consult extensiveexisting literature developed by other emissions inventory programmes. Some keyexamples are:

• Default Emissions Factor Handbook (CORINAIR, 1994);

• Joint Atmospheric Emission Inventory Guidebook (1st edition) (EMEP/CORINAIR,1996);

• US EPA's Compilation of Air Pollutant Emissions Factors (AP-42) (US EPA, 1995);

• Criteria Pollutant Emission Factors for the 1985 NAPAP Emissions Inventory(Stockton and Stelling, 1987);

• Air Emissions from Municipal Solid Waste Landfills - Background Information forProposed Standards and Guidelines (US EPA, 1991; Doorn and Barlaz, 1995);

• Greenhouse Gases from Wastewater Treatment: Collection and Review of CountrySpecific Data and Preliminary Emission Models (Doorn and Eklund, 1995).

6 . 2 Met h a n e E m i s s i on s f r om S o l i d W a s t eD i s p os a l S i t e s

6 . 2 . 1 I n t r o d u c t i o n

The gases produced in solid waste disposal sites, particularly CH4, can be a localenvironmental hazard if precautions are not taken to prevent uncontrolled emissions ormigration into surrounding land. Landfill gas is known to be produced both in managed“landfill” and “open dump” sites. Both are considered here as solid waste disposal sites(SWDSs). Gas can migrate from SWDSs either laterally or by venting to atmosphere,causing vegetation damage and unpleasant odours at low concentrations, while atconcentrations of 5-15 per cent in air, the gas may form explosive mixtures.

More recently, increasing attention has focused on the role of CH4 in global atmosphericchange. Methane from SWDSs contributes a significant proportion of annual global CH4emissions, although the estimation is subject to a great deal of uncertainty. Estimates ofglobal CH4 emissions from SWDSs range from less than 20 to 70 Tg/yr (Bingemer andCrutzen, 1987, US EPA, 1994), or about 5 per cent to 20 per cent of the total estimatedemissions of 375 Tg/yr (IPCC, 1996) from anthropogenic sources globally.

This section will describe the processes that result in gas generation from SWDSs andthe factors which affect the amount of CH4 produced. It will then describe twomethodologies for estimating CH4 emissions from SWDSs. One of these methods is adefault base method which all countries can use to estimate CH4 emissions from different

6 WASTE


types of SWDSs. It is recommended that countries which have adequate data alsoestimate their emissions using the second method presented. Finally, this sectiondiscusses sources of uncertainty associated with any estimates of CH4 emissions fromSWDSs, in particular the availability and quality of data required.

6 . 2 . 2 G a s G e n e r a t i o n f r o m S o l i d W a s t e D i s p o s a lS i t e s

Organic waste in SWDSs is broken down by bacterial action in a series of stages thatresult in the formation of CH4 and CO2 (termed biogas or landfill gas) and furtherbacterial biomass. In the initial phase of degradation, organic matter is broken down tosmall soluble molecules including a variety of sugars. These are broken down further tohydrogen, CO2, and a range of carboxylic acids. These acids are then converted to aceticacid which, together with hydrogen and CO2, forms the major substrate for growth ofmethanogenic bacteria.

Landfill gas consists of approximately 50 per cent CO2 and 50 per cent CH4 by volume.However, the percentage of CO2 in landfill gas may be smaller because of decompositionof substrates with a high hydrogen/oxygen ratio (e.g., fats, hemicellulose) and becausesome of the CO2 dissolves in water within the site.

SWDSs are by nature heterogeneous. Microbiological investigations into sitecharacteristics have shown that there are considerable differences between differentSWDSs and even different regions within the same SWDS (Westlake, 1990). This makesit very difficult to extrapolate from observations on single SWDSs to predictions of globalCH4 emissions. Nevertheless, a better understanding of the factors thought to mostsignificantly influence the generation of CH4 from land disposal of solid waste can reducethe uncertainty associated with emissions estimates.

6 . 2 . 3 F a c t o r s I n f l u e n c i n g M e t h a n e G e n e r a t i o ni n S o l i d W a s t e D i s p o s a l S i t e s

This section will provide a brief summary of the most significant factors affecting CH4generation.

Waste disposal practices

Waste disposal practices of concern for CH4 emissions vary in the degree of control ofthe placement of waste and management of the site. In general, waste disposal on landwill result in CH4 production if the waste contains organic matter. Managed disposal(controlled placement of waste), in particular, tends to encourage development andmaintenance of anaerobic activity.

Waste composition

The composition of waste is one of the main factors influencing both the amount and theextent of CH4 production within SWDSs. Municipal solid waste (MSW) typically containssignificant quantities of degradable organic matter. Different countries and regions areknown to have MSW with widely differing compositions.

Physical factors

Moisture content is an important physical factor influencing landfill gas production.Moisture is essential for bacterial growth and metabolism, as well as for transport ofnutrients and bacteria within the SWDS. The moisture content of a SWDS depends on

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the initial moisture content of the waste, the extent of infiltration from surface andgroundwater sources, and the amount of water produced during the decompositionprocesses.

Temperature, pH, and nutrient availability will affect the growth rate of the bacteria.Under anaerobic conditions, landfill temperatures are generally between 25-40oC. Thesetemperatures can be maintained within the SWDS regardless of the ambient surfacetemperatures. Outside of these temperatures, CH4 production is reduced. Optimal pHfor CH4 production is around neutral (pH 7.0). Important nutrients for efficient bacterialgrowth include sulphur, phosphorus, sodium and calcium. The significance of thesephysical factors to CH4 generation can be demonstrated within controlled laboratoryconditions.

6 . 2 . 4 M e t h o d o l o g i e s t o E s t i m a t e M e t h a n eE m i s s i o n s f r o m S o l i d W a s t e D i s p o s a l S i t e s

A number of methods have been used to estimate CH4 emissions from solid wastedisposal sites. These methods vary widely, not only in the assumptions that they make,but also in their complexity, and in the amount of data they require. This chapter willdeal only with those methods that can be applied to whole regions or countries. Thereare some very complex models that are concerned with movement of CH4 and othergases through individual disposal sites; however these models cannot be applied to sitepopulations and therefore will not be considered further here.

The methods described below include the theoretical gas yield methodology, of which thedefault methodology is one variation, and a first order kinetics methodology.

Theoretical gas yield methodology

This is the simplest method for calculating CH4 emissions from SWDSs. It is based on amass balance approach, and does not incorporate any time factors into the methodology.Rather, this methodology assumes that all potential CH4 is released from waste in theyear that the waste is disposed of. Although this is not what actually occurs, it gives areasonable estimate of the current year’s emissions if the amount and composition of thewaste disposed of has been relatively constant over the previous several years. If,however, there have been significant changes in the rate of waste disposal, this simplemethod will likely not provide a good estimate of current emissions.

Default methodology

The default methodology is a mass balance approach that involves estimating thedegradable organic carbon (DOC) content of the solid waste, i.e., the organic carbon thatis accessible to biochemical decomposition, and using this estimate to calculate theamount of CH4 that can be generated by the waste. This is the approach taken byBingemer and Crutzen (1987), who divided the world into four economic regions (theUnited States, Canada and Australia; other OECD countries; the Former USSR andEastern and Central Europe; developing countries), and applied different DOC values tothe waste generated within each of these regions. It is the most widely accessible, easy-to-apply methodology for calculating country-specific emissions of CH4 from SWDSs. Itrequires the least amount of data to perform the calculations, and it can be modified andrefined as the amount of data available for each country increases. This approach wasprovided as the default methodology in the IPCC Guidelines (IPCC, 1995).

The revised default methodology provided here modifies the IPCC Guidelines (IPCC, 1995)in three important ways:

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• Rather than distinguishing between “landfills” and “open dumps,” the methodologyuses a continuum of solid waste disposal sites, characterised by the degree of wastemanagement and depth.

• Default DOC values are provided for different waste streams so that countries cancalculate the DOC content of their waste rather than relying on single default values.

• Emphasising the fact that this methodology estimates CH4 generation rather thanemission, and that oxidation often occurs in the upper layers of the waste mass and insite cover material, a CH4 oxidation factor (OX) is included in the equation (currentlyequal to 0, pending the availability of further data).

The determination of annual CH4 emissions for each country or region can be calculatedfrom Equation 1:

EQUATION 1

Methane emissions (Gg/yr)=

(MSWT x MSWF x MCF x DOC x DOCF x F x 16/12 - R) x (1-OX)

where:

MSWT = total MSW generated (Gg/yr)

MSWF = fraction of MSW disposed to solid waste disposal sites

MCF = methane correction factor (fraction)

DOC = degradable organic carbon (fraction)

DOCF = fraction DOC dissimilated

F = fraction of CH4 in landfill gas (default is 0.5)

R = recovered CH4 (Gg/yr)

OX = oxidation factor (fraction - default is 0)

Total MSW (MSWT) can be calculated from Population (thousand persons) x AnnualMSW generation rate (Gg/thousand persons/yr). Per capita MSW generation rates areprovided for many countries and regions in Table 6-1. The components of MSW mayvary from country to country. These differences can play an important role in theresulting emissions estimate, as each waste stream may have a different DOC contentand hence a different CH4 generation potential. In general, countries should include thefollowing waste streams in their estimate of total MSW generated:

1. household waste;

2. yard/garden waste; and

3. commercial/market waste.

In some countries, significant quantities of organic industrial solid waste are generated.The default values in Table 6-1 should not include industrial waste or construction anddemolition material. If a significant quantity of organic industrial solid waste is generated

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and disposed of in solid waste disposal sites, this waste should be included in the MSWgeneration rates and reflected in the corresponding DOC value chosen (see below underDegradable Organic Carbon).

In countries where no organised waste collection or disposal takes place in rural areas,the population considered should include only the urban population. The default values inTable 6-1 for developing countries and countries with economies-in-transition do notinclude rural area information.

TABLE 6-1COUNTRY WASTE GENERATION, COMPOSITION, AND DISPOSAL DATA

Region/Country MSW Generation Rate(kg/cap/day)

Fraction of MSWdisposed to SWDS

Fraction ofDOC ofMSW

MSW disposalRate

(kg/cap/day)

North America 0.18-0.21

USAa 2.0 0.62 1.24

Canadab 1.81 0.75 1.35

Oceania

Australiac 1.26 1.00 0.15 1.26

New Zealandl 1.33 1.0 0.19 1.33

UK/WesternEurope/Scandinavia

0.08-0.19

UKm 1.9 0.9 0.10 1.7

Irelandb 0.85 1.00 0.85

Austriad 0.92 0.40 0.36

Belgiumb 1.10 0.43 0.47

Denmarkb 1.26 0.20 0.25

Finlandb 1.70 0.77 1.3

Franceb 1.29 0.46 0.60

Germanyb 0.99 0.66 0.65

Greeceb 0.85 0.93 0.79

Italye 0.94 0.88 0.83

Luxembourgb 1.34 0.35 0.47

Netherlandsf 1.58 0.67 0.14 1.06

Norwayb 1.40 0.75 1.05

Portugalb 0.90 0.86 0.78

Spainb 0.99 0.85 0.83

Swedenb 1.01 0.44 0.44

Switzerlandb 1.10 0.23 0.25

Eastern Europe

Polandg 0.15 0.54

Russiah 0.93 0.94 0.17 0.87

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TABLE 6-1 (CONTINUED)COUNTRY WASTE GENERATION, COMPOSITION, AND DISPOSAL DATA

Region/Country MSW Generation Rate (kg/cap/day)

Fraction of MSWdisposed to SWDS

Fraction ofDOC of MSW

MSW disposalRate

(kg/cap/day)

Asia

Japanb 1.12 0.38 0.43

Indiai 0.33 0.6 0.18 0.2

Chinaj 0.09 0.84

Indonesiaj 0.17 0.51

Central America

Guatemalaj 0.13 0.46

South America

Brazilj 0.12 1.47

Peruj 0.15 0.98

Chilej 0.18 0.59

Africa

Egyptj 0.21 0.40

Nigeriaj 0.11 0.40

South Africak 1.00

Note: The values in Table 6-1 represent the best data available to the Expert Group. Note that all values may not reflectidentical assumptions regarding MSW composition (and hence corresponding DOC values). Where updated national data areavailable corresponding to the definitions used here, they should be used for comparison instead of the values given in Table 6-1.

a US EPA, 1995

b OECD, 1995

c Tom Beer, CSIRO, 1996

d Carolin Ziegler, University of Vienna, 1996

e Domenico Gaudioso, ENEA Italy, 1995

f Hans Oonk, TNO Environment & Energy Research, The Netherlands, 1995

g Piotr Manczarski, Warsaw University, Poland, 1995

h Alexander Lifshits, Geopolis Consulting, Moscow, 1995

i A.D. Bhide, NEERI, India, 1995

j Cal Recovery Inc., California, USA - based on experience in country.

k Les Venter, Solid Waste Dept., Johannesburg, South Africa, 1995

l E. Gray, New Zealand Ministry of Environment, 1996m UK DoE, 1995

The Fraction MSW Disposed to Solid Waste Disposal Sites (MSWF) and MethaneCorrection Factor (MCF) reflect the way in which MSW is managed and the effect ofmanagement practices on CH4 generation. The methodology requires countries toprovide data or estimates of the quantity of waste that is disposed of to each of threecategories of solid waste disposal sites (Table 6-2).

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TABLE 6-2SWDS CLASSIFICATION AND METHANE CORRECTION FACTORS

Type of site Methane correction factor (MCF) default values

Managed 1.0

Unmanaged - deep (≥5m waste) 0.8

Unmanaged - shallow (<5m waste) 0.4

Default value - uncategorised SWDSs 0.6

1. Managed solid waste disposal sites. These must have controlled placement ofwaste (i.e., waste directed to specific deposition areas and a degree of control ofscavenging and a degree of control of fires) and will include at least one of thefollowing:

• cover material;

• mechanical compacting; or

• levelling of the waste.

2. Unmanaged-deep solid waste disposal sites. All SWDSs not meeting the criteriaof managed SWDSs and which have depths of greater than or equal to 5 metres.

3. Unmanaged-shallow solid waste disposal sites. All SWDSs not meeting thecriteria of managed SWDSs and which have depths of less than 5 metres.

A methane correction factor (MCF) is assigned to each of these categories, as shown inTable 6-2. The MCF reflects the lower methane-generating potential of unmanaged sites.The classification recognises that some developing countries or countries witheconomies-in-transition may have a small number of well-managed waste disposal sites,with the majority of sites less well-managed or unmanaged, often shallow and with lowermethane-generating potential. A default value is provided for countries where thequantity of waste disposed to each SWDS is not known. A country’s classification of itswaste sites into managed or unmanaged may change over a number of years as nationalwaste management policies are implemented.

Degradable Organic Carbon (DOC) content is based on the composition of waste, andcan be calculated from a weighted average of the carbon content of various componentsof the waste stream. Country/region default data for DOC, where available, arepresented in Table 6-1 (in general, these values are for wet waste). It is highlyrecommended, however, for countries where the composition of the fractions in thewaste stream are known, that these be combined with a knowledge of the carboncontent of these various fractions to produce a country-specific value for DOC. It iscritical that the DOC value corresponds to the waste generation/disposal rate on whichthe CH4 estimate is based. For example, a country that includes industrial waste in itsMSW estimate should ensure that the DOC value used reflects this component of thewaste stream.

To assist countries to calculate the DOC of waste streams, a set of default DOC valuesfor different waste types is given in Table 6-3. Note that these values are for wet (orfresh) waste.

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TABLE 6-3DEFAULT DOC VALUES FOR MAJOR WASTE STREAMS

Waste Stream Per cent DOC (by weight)

A. Paper and textiles 40

B. Garden and park waste, and other(non-food) organic putrescibles

17

C. Food waste 15

D. Wood and straw wastea 30

a excluding lignin C

Source: Bingemer and Crutzen, 1987.

Using the values in Table 6-3, the DOC content of a country’s waste could be calculatedas shown in Equation 2.

EQUATION 2

Per cent DOC (by weight) = 0.4 (A) + 0.17 (B) + 0.15 (C) + 0.30 (D)

where:

A = per cent MSW that is paper and textiles

B = per cent MSW that is garden waste, park waste or other non-foodorganic putrescibles

C = per cent MSW that is food waste

D = per cent MSW that is wood or straw

Fraction dissimilated DOC (DOCF) is the portion of DOC that is converted to landfillgas. To date, estimates of how much carbon may be dissimilated have relied on atheoretical model that varies only with the temperature in the anaerobic zone of a landfill:0.014T + 0.28, where T = temperature (Tabasaran, 1981). If one assumes that thetemperature in the anaerobic zone of a SWDS remains constant at about 35oC,regardless of ambient temperature (Bingemer and Crutzen, 1987), this method yields afigure of 0.77 dissimilated DOC. This value is currently under review.

Recovered CH4 (R) is the amount of CH4 that is captured for flaring or use. No defaultvalues are provided for the quantity of CH4 recovered, as this value is country-specific.See Section 6.2.6 below for more information.

Oxidation Factor (OX) accounts for the CH4 that is oxidised in the upper layers of thewaste mass and in cover material, where oxygen is present. Because the defaultmethodology relies on an estimate of CH4 generation, it is important to recognise theoxidation may reduce the quantity of CH4 generated that is ultimately emitted. A numberof researchers are investigating and quantifying the effects of CH4 oxidation in wastedisposal sites. However, as yet there is no internationally accepted factor that can beapplied to account for CH4 oxidation. The CH4 oxidation factor in the equation hastherefore been set equal to 0, pending the availability of new data. A better

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understanding of the factors influencing CH4 oxidation, and more accurate quantificationof it, may allow for a revised oxidation factor (or default values) in future editions of theIPCC Guidelines. It is important that the oxidation factor be applied after subtraction ofCH4 recovered, as this CH4 is generally pulled from well below the surface of the SWDS,before oxidation can occur.

It is proposed that the default methodology, based on the theoretical gas yieldmethodology developed by Bingemer and Crutzen (1987), remain as the methodologythat can be used by all countries to calculate CH4 emissions from their SWDSs. TheWorkbook provides a detailed step-by-step version of this methodology.

Theoretical first order kinetics methodologies

More complex methods for estimating CH4 emissions from SWDSs acknowledge the factthat CH4 is emitted over a long period of time rather than instantaneously. A kineticapproach therefore needs to take into account the various factors which influence therate and extent of CH4 generation and release from SWDSs. A number of countrieshave applied this or similar modelling approaches to their own situation (Aitchison et al.,1996; UK, DOE, 1993; Van Amstel et al., 1993; Environment Canada, 1992).

First Order Decay Model

A first order decay model (Equation 3) can be used to model the rate of CH4 generationover time. This approach has been used extensively to model landfill gas generation ratecurves for individual landfills. It can also be used to model gas generation for a set ofSWDSs to develop country emissions estimates or can be applied in a more general wayto entire regions.

EQUATION 3

Q = LO R (e-kc - e -kt)

where:

Q = methane generated in current year (m3/yr)

L0 = methane generation potential (m3/Mg of refuse)

R = average annual waste acceptance rate during active life (Mg/yr)

k = methane generation rate constant (1/yr)

c = time since SWDS closure (yr)

t = time since SWDS opened (yr)

Methane generation potential (Lo). The methane generation potential depends upon thecomposition of the waste. Values for Lo can vary widely, and are difficult to estimateaccurately for a particular SWDS or set of SWDSs. Lo values may range from less than100 to over 200 m3/Mg.

Quantity of waste landfilled (R). This is the average annual waste acceptance rate duringthe SWDS’s active life.

Methane generation rate constant (k). This value is based on the environment in whichthe SWDS is located. Higher k values are associated with greater moisture in the

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SWDSs and other factors discussed in Section 6.2.3 above. Values for k may range fromless than 0.005 per year to 0.4 per year (LANDTEC, 1994; US EPA 1991).

Time since SWDS closure (c). This is the length of time in years, not including the yearof closure, since the SWDS stopped accepting waste.

Time since initial refuse replacement (t). This is the length of time in years since theSWDS began to accept waste.

Countries with sufficient data on annual waste disposal to SWDSs are encouraged toapply the derivative of the first order decay model (Equation 4), to provide a comparisonto the default methodology as well as to test the feasibility of including this approach infuture inventories guidelines.

To allow for variances in annual acceptance rates, the derivative of Equation 3 withrespect to t can be used to estimate CH4 generation from waste landfilled in a single year(Rx). In this equation, the variable t is replaced with T-x, which represents the number ofyears the waste has been in the SWDS. The resulting equation thus becomes:

EQUATION 4

QT,x = k Rx LO e-k(T-x)

where:

QT,x = the amount of methane generated in the current year (T) by thewaste Rx

x = the year of waste input

Rx = the amount of waste disposed in year x (Mg)

T = current year

In order to estimate the current emissions from waste placed in all years, Equation 4 canbe solved for all values of Rx and the results summed (see Equation 5).

EQUATION 5

QT = ΣQT,x

for x = initial year to T

6 . 2 . 5 S o u r c e s o f U n c e r t a i n t y

There are two areas of uncertainty in the estimate of CH4 emissions from solid wastedisposal sites: (1) the uncertainty attributable to the method; and (2) data uncertainty.

Uncertainty attributable to the method. As discussed previously, the default methodologyassumes that waste disposal into solid waste disposal sites is relatively constant and thatthe CH4 generated by the waste is released in the same year the waste is deposited.However, if waste disposal into solid waste disposal sites is increasing over time, then the

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default method will overestimate CH4 emissions. For example, it can be shown that ifwaste disposal into solid waste disposal sites is increasing at about 2 per cent per yearover a 20- to 30-year period, then the default method will overestimate emissions byabout 20-25 per cent. This is the principal type of uncertainty attributable to the defaultmethodology itself. The amount of waste disposed of is therefore a sensitive parameterin this default methodology.

Data uncertainty. This source of uncertainty is simply the uncertainty attributable to eachof the data inputs. In the case of the default methodology, this includes the uncertainty inthe estimates for each of the factors used in Equation 1 (e.g., total MSW generated,fraction of MSW disposed to solid waste disposal sites). Although the uncertainty in anysingle one of these factors may be relatively large, if the sources of uncertainty for onefactor are not related to the uncertainty for the other factors, then the uncertainty of theoverall CH4 emissions estimate can remain relatively low. For example, if the values foreach of the factors used in Equation 1 are assumed to have an uncertainty of ± 10 percent, then the overall uncertainty in the CH4 emissions estimate will be about ± 20 percent. If the uncertainty for each factor increases by ± 20 per cent, then the overalluncertainty in the CH4 emissions estimate increases to ± 40-50 per cent.

The following key uncertainties related to the data are discussed further below:

• The quantity and composition of landfilled waste;

• The quantity of CH4 that is actually generated from the waste in the SWDS;

• The quantity of CH4 that is actually emitted to the atmosphere.

Waste quantity and composition: The quality of CH4 emissions estimates is directlyrelated to the quality and availability of the waste management data used to derive theseestimates. However, an accurate knowledge of the quantity and composition of wastesalready in place may not be available. For most countries, limitations on funds availablewill prevent extensive investigations of old and smaller sites. It is therefore more cost-effective to concentrate efforts on improving the quality of data being collected onexisting landfilling operations, including total waste quantity as well as more detailed site-specific data.

Quantity of methane generated: The degradable organic carbon (DOC) content of wasteis an essential component in all calculations of CH4 generated, and small variations in theassumed values for DOC can result in large variations in the overall estimate of CH4emissions. Different countries have widely differing MSW compositions and thereforeDOC content. Both the rate and the extent of degradation of the various wastefractions need to be taken into account where data are available. Waste managementpractices also have significant effects on CH4 generation, for example the method oflandfilling and the water management practices. Future changes in waste managementpractices may change the composition of waste to SWDSs considerably, resulting indifferent CH4 emissions levels.

Quantity of methane generated that is emitted to the atmosphere: The main uncertaintyinfluencing the quantity of CH4 emitted is the degree of oxidation that occurs as the gasdiffuses through the landfill cover material. The presence, thickness, and othercharacteristics of SWDS cover materials can play a large role in determining the quantityof CH4 ultimately emitted from a site.

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6 . 2 . 6 F l a r i n g a n d G a s R e c o v e r y S c h e m e s

Flaring and gas recovery schemes successfully reduce CH4 emissions from SWDSs. Anynational inventory of CH4 emissions from SWDSs must therefore take into account thereductions achieved by these practices.

For sites recovering CH4 for energy use, the quantity of gas utilised is generally welldocumented. Estimates of the extent of flaring are more difficult to achieve withaccuracy, and generally have to be estimated from a knowledge of the state of SWDSmanagement within the country. If data on gas flaring are not readily available for acountry, the following steps might be useful in development of this information:

1. Creation of an inventory of gas flares purchased in the country for use with landfillgas, including year purchased, estimated useful life, and flow rates.

2. Use of this inventory to estimate quantity of landfill gas flared each year.

6 . 2 . 7 C o n c l u s i o n

A default methodology is presented here that allows simple calculation of CH4 emissionsfrom SWDSs by all countries. Countries are encouraged to use more sophisticatedmethods that incorporate country-specific data, if available. In particular, countries withsufficient data are encouraged to apply the first order decay model presented in Section6.2.4 above, and compare the results to the basic default approach. If such data are notavailable, countries are encouraged to collect data for future application of a first ordermethodology. The additional information required includes: i) the CH4 generationpotential of the waste; ii) the rate at which CH4 is generated from the waste each year;iii) the year of waste input; and iv) the amount of waste disposed of to SWDSs each year.

6 . 3 Met h a n e E m i s s i on s f r om W a s t e wa t e rHa n d l i n g

6 . 3 . 1 I n t r o d u c t i o n

Methane production from wastewater handling (WWH) under anaerobic conditions isestimated to range from 30 to 40 teragrams per year (Tg/yr). This represents 8 to 11per cent of total global anthropogenic CH4 emissions estimated at 375 Tg/yr. IndustrialWWH sources are estimated to be the major contributor to WWH emissions,accounting for 26 to 40 Tg/yr. Domestic and commercial WWH is estimated to emitapproximately 2 Tg/yr (IPCC, 1995; US EPA 1994).

Wastewater can produce CH4 if it is handled anaerobically. Anaerobic methods are usedto handle wastewater from municipal sewage and from food processing and otherindustrial facilities, particularly in developing countries. In contrast, developed countriestypically use aerobic processes for municipal wastewater treatment or anaerobicprocesses in enclosed systems where CH4 is recovered and utilised.

This section provides the default methodology for estimating CH4 emissions from WWH.

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6 . 3 . 2 B a c k g r o u n d

Handling of wastewater and its residual solids by-product (sludge) under anaerobicconditions results in CH4 production. The extent of CH4 production depends primarilyon the following factors:

A) Wastewater Characteristics

The principal factor in determining the CH4 generation potential of wastewater is theamount of degradable organic material in the wastewater. Common parameters used tomeasure the organic component of the wastewater are the BOD (Biochemical OxygenDemand) and COD (Chemical Oxygen Demand). Under the same conditions,wastewater with higher COD (or BOD) concentrations will generally yield more CH4than wastewater with lower COD (or BOD) concentrations.

B) Handling Systems

Handling systems vary in the environment that they provide for CH4 production. Systemsthat provide anaerobic environments will generally produce CH4 whereas systems thatprovide aerobic environments will normally produce little or no methane.

For example, the depth of a lagoon treatment system is a critical factor in CH4production. Shallow lagoons, less than 1 metre in depth, generally provide aerobicconditions and little CH4 is likely to be produced. Lagoons deeper than about 2-3 metreswill generally provide anaerobic environments and significant methane production isexpected.

C) Temperature

With increases in temperature, the rate of CH4 production increases. This is especiallyimportant in uncontrolled systems and in warm climates. CH4 production typicallyrequires a temperature higher than 15°C. Fermentation and thus CH4 production isnegligible at temperatures below 15°C, at which point the lagoon serves principally as asedimentation tank (Gloyna, 1971). Below 15°C significant amounts of CH4 will beproduced only in instances where sedimentation and extended sludge retention occur.

Other factors that influence CH4 generation in wastewater are retention time, degree ofwastewater treatment, and other site specific characteristics.

D) BOD vs. COD

The BOD (Biochemical Oxygen Demand) concentration indicates only the amount ofcarbon that is aerobically biodegradable. The standard measurement for BOD is a 5-daytest1, denoted as BOD5. The time period used in the BOD indicates whether only easilybiodegradable materials or more resistant compounds are taken into account. COD(Chemical Oxygen Demand) measures the total material available for oxidation (bothbiodegradable and non-biodegradable). Since the BOD is an aerobic parameter, it may beless appropriate for determining the organic components in anaerobic environments.Also, both the type of wastewater and the type of bacteria present in the wastewaterinfluence the BOD concentration of the wastewater. Although BOD is the more

1 A seven day test, denoted as BOD7, is used in some countries instead of BOD5.The conversion between BOD5 and BOD7 is dependent on the characteristics of thewastewater. Experts within individual countries should be consulted to obtainappropriate conversion coefficients.

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frequently reported parameter, reported COD/BOD ratios can be used to determine theCOD if the BOD is known.2

6 . 3 . 3 M e t h o d o l o g y f o r W a s t e w a t e r H a n d l i n g

Wastewater handling systems involve processes that transfer wastewater from its sourceto a disposal site. In most developed countries, wastewater treatment systems are usedto chemically or biologically stabilise the wastewater before disposal. In many developingcountries however, wastewater receives little or no formal treatment and is simplyhandled by transporting untreated wastewater to a disposal site.

Formal wastewater treatment methods can be classified as primary, secondary, andtertiary treatment. In primary treatment, physical barriers remove larger solids from thewastewater. Remaining particulates are then allowed to settle. Secondary treatmentconsists of a combination of biological processes that promote biodegradation by micro-organisms. These may include aerobic and anaerobic stabilisation ponds, trickling filters,and activated sludge processes. Tertiary treatment processes are used to further purifythe wastewater of contaminants and pathogens. This is achieved using one or acombination of processes, including maturation/polishing ponds, advanced filtration,carbon adsorption, ion exchange, and disinfection.

Sludge is produced in both the primary and secondary stages of treatment. Sludge that isproduced in primary treatment consists of solids that are removed from the wastewater.Sludge produced in secondary treatment is a result of biological growth in the biomass, aswell as the collection of small particles (Lexmond and Zeeman, 1995). This sludge mustbe treated further before it can be safely disposed of. Methods of sludge treatmentinclude aerobic and anaerobic stabilisation (digestion), conditioning, centrifugation,composting, and drying. Anaerobic stabilisation will produce CH4.

6 . 3 . 4 W a s t e w a t e r H a n d l i n g M e t h o d s i nD e v e l o p e d a n d D e v e l o p i n g C o u n t r i e s

Wastewater handling methods differ between developed and developing countries. Themost common methods of wastewater handling in developed countries are aerobicwastewater treatment plants and lagoons (Lexmond and Zeeman, 1995). To avoid highdischarge fees, many large industrial facilities pretreat their wastewater before releasing itinto the sewage system. There is also an increasing trend towards anaerobic treatmentsystems, which can be cheaper and produce less sludge than aerobic systems.

The degree of wastewater treatment is variable in most developing countries. Mostindustrial wastewater is discharged directly into local bodies of water, and only a fewmajor industries have comprehensive in-plant treatment facilities. Less than half ofmunicipal wastewater produced is collected in a sewage system. Collected wastewater isusually discharged into unmanaged lagoons or waterways; in coastal cities it is dischargeddirectly into the ocean. In many cases, the domestic wastewater handling facilities are pit

2 Lexmond and Zeeman estimated a minimum value of the wastewater COD/BODratio to be 1.70 (Lexmond and Zeeman 1995). The COD/BOD ratio may varysignificantly depending upon the characteristics of the wastewater. This is especially truefor industrial wastewater which may include inorganic oxidisable materials. Somecountries report BOD7 (or other) values rather than BOD5 values. In this case, domesticwastewater experts should be consulted to convert the available BOD data into theBOD5 form.

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latrines. Table 6-4 presents the main wastewater handling methods in developed anddeveloping countries.

Wastewater streams

Wastewater originates from a variety of domestic and industrial sources. Domesticwastewater streams include wastewater from toilets, bathrooms, kitchens, and in somecases, urban run-off. Industry classifies sources of wastewater into different industrialsectors (Lexmond and Zeeman, 1995), for example:

• Food and Beverages

• Paper and Pulp

• Textile

• Petrochemical

• Fertiliser

• Iron and Steel

• Non-Ferrous Metals

• Miscellaneous

Assessment of CH4 production potential from industrial wastewater streams is based onthe concentration of degradable organic matter in the wastewater, the volume ofwastewater, and the propensity of the industry to treat their wastewater in anaerobiclagoons. Using these criteria, Doorn and Eklund (1995) prioritised industrial wastewatersources with high CH4 gas production potential. These are characterised as follows:

• Paper and Pulp manufacture

• Slaughterhouses

• Alcohol, Beer, Starch

• Organic Chemicals

• Others (vegetable oil production, textiles, rubber, petroleum refineries, fruits andvegetables)

Both the paper and pulp industry and the meat and poultry processing industries producelarge volumes of wastewater that contain high levels of degradable organics. Additionally,both industries utilise large facilities that often have their own wastewater handlingsystems. The meat and poultry processing facilities commonly employ anaerobic lagoonsto treat their wastewater, while the paper and pulp industry is known to use lagoons.

The non-animal food and beverage industries collectively produce considerable amountsof waste water with significant BOD levels.

6 WASTE


TABLE 6-4METHODS OF WASTEWATER HANDLING

Handling Method Exceptions to Expected CH4 Production

Mostly aerobic disposal and handlingmethods (little or no CH4 production)

Developing countries

• Open Pits/Latrines

• Aerobic shallow ponds

• River Discharge

• Pits/latrines may produce methane whentemperature and retention time arefavourable

• Aerobic shallow ponds over 3 metres deepmay produce methane

• Stagnant, oxygen-deficient rivers may allowfor anaerobic decomposition

Developed countries

• Sewer systems with aerobic treatment • Poorly designed or managed aerobictreatment systems produce methane

Mostly anaerobic disposal and handlingmethods (high CH4 production)

Developing countries

• Anaerobic deep ponds

• Sewer systems with anaerobic treatment

Developed and developing countries

• Septic Tanks

• Poorly designed or managed anaerobicsystems may allow for aeration andreduced methane production

• Frequent solids removal reduces methaneproduction

Anaerobic Methods with Methane Recovery(mainly for sludge handling)

Primarily developed countries

6 . 3 . 5 M e t h o d o l o g y f o r E s t i m a t i n g E m i s s i o n sf r o m W a s t e w a t e r H a n d l i n g

Methane emissions from wastewater handling should be calculated for two differentwastewater and resulting sludge types:

1 Domestic Wastewater.

2 Industrial Wastewater.

3 Domestic Sludge.

4 Industrial Sludge.

For each category, the method for estimating CH4 emissions from wastewater handlingrequires three basic steps:

WASTE


Step 1 - Determine the total amount of organic material in the wastewaterproduced for each wastewater handling system. The principal factor indetermining the CH4 generation potential of wastewater is the amount of degradableorganic material of the wastewater. The most common parameters used to measure thedegradable organic component (DC) of the wastewater are the BOD (BiochemicalOxygen Demand) and COD (Chemical Oxygen Demand). Data permitting, COD is therecommended parameter for estimating the DC of wastewater. The DC indicator,usually indicated in units of mass DC per unit volume (e.g., kg COD per m3 wastewater)is multiplied by the volume of the source of wastewater (e.g., industry or domestic) toestimate the total amount of organic wastewater produced.

Step 2 - Estimate emissions factors for each wastewater handling system in kgCH4 per kg DC. The emissions factors depend on the fraction of wastewater managedby each wastewater handling method, maximum CH4 producing capacity of thewastewater, and the characteristics of the wastewater handling process (principally, thedegree to which it is anaerobic).

Step 3 - Multiply the emissions factors for each wastewater handling system bythe total amount of organic material in the wastewater produced for eachsystem, and sum across the wastewater systems to estimate total CH4 emissions.

Approach for Estimating Methane Emissions from Wastewater andWastewater Sludge Handling

This approach is adapted from Doorn and Ecklund (1995) and Lexmond and Zeeman(1995).

Step 1 -Total Organic Wastewater and Sludge

The greenhouse gas (GHG) generation potential of the wastewater is driven by theorganic content of the wastewater stream and the volume of wastewater. For thecategories of wastewater types defined (domestic and industrial), the following is themethod for estimating the total organic wastewater (TOW):

Domestic

Data needed are:

1. Degradable organic component (DC) indicator in kg DC per 1000 persons per year.For domestic wastewater and sludge, BOD is the recommended DC indicator.Although COD is considered a more appropriate indicator for the organiccomponent of the waste, BOD is the more frequently reported indicator fordomestic wastewater. Consequently, the use of BOD estimates will result in moreprecise calculations than when COD is used. (Default BOD values are provided fordifferent regions in Table 6-5).

2. Country population in thousands (developing countries may choose to estimatewastewater and sludge handling emissions based only on the urban population of thecountry if wastes produced in rural areas decompose in an aerobic environment -see Table 6-4 for a list of anaerobic and aerobic handling methods).

3. Fraction of BOD removed as sludge.

Equation 6 presents the total domestic organic wastewater (TOWdom) calculation.

EQUATION 6

TOWdom = P x Ddom x (1 - DSdom)

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Equation 7 presents the total domestic organic sludge (TOSdom) calculation.

EQUATION 7

TOSdom = P x Ddom x DSdom

where:

TOWdom = total domestic/commercial organic wastewater in kg BOD/yr

TOSdom = total domestic/commercial organic sludge in kg BOD/yr

P = population in 1000 persons

Ddom = domestic/commercial degradable organic component inkg BOD/1000 persons/yr

DSdom = fraction of domestic/commercial degradable organic componentremoved as sludge

Industrial

Data needed are:

1. Degradable organic component (DC) indicator in kg DC per m3 of industrialwastewater/sludge produced per unit product. For industrial wastewater and sludgestreams COD is the appropriate DC indicator. Data on COD values should beavailable in most countries. It is recommended that country-specific information, ifavailable, be used. Default COD values are provided for different industries byregion in Table 6-6. (Although the default values in Table 6-6 are provided byregion, in most cases the default values are based on estimates for a single countrywithin each region.)

2. Wastewater produced per unit product by industry in m3/tonne of product. Defaultvalues are provided in Table 6-6. (Although the default values in Table 6-6 areprovided by region, in most cases the default values are based on estimates for asingle country within each region.)

3. Total industrial output in tonnes per year.

4. Fraction of COD removed as sludge.

Equation 8 presents the total organic wastewater (TOWind) calculation for a particularindustry.

EQUATION 8

TOWind (kg COD/yr) = W x O x Dind x (1 - DSind)

WASTE


Equation 9 presents the total organic sludge (TOSind) calculation for a particular industry.

EQUATION 9

TOSind (kg COD/yr) = W x O x Dind x DSind

where:

TOWind = total industrial organic wastewater in kg COD/yr

TOSind = total industrial organic sludge in kg COD/yr

W = wastewater consumed in m3/tonne of product

O = total output by selected industry in tonnes/yr

Dind = industrial degradable organic component in kg COD/m3

wastewater

DSind = fraction of industrial degradable organic component removed assludge

Step 2 - Emissions Factors

To calculate emissions factors for each wastewater and sludge type, a weighted average ofmethane conversion factors (MCF) is calculated using estimates of wastewater managedby each wastewater handling method. The average MCF is then multiplied by themaximum methane producing capacity (Bo) of the wastewater type.

• Maximum methane producing capacity (Bo): The methane producing potential, Bo, is themaximum amount of CH4 that can be produced from a given quantity of wastewateror sludge. The CH4 producing potential varies by the composition of thewastewater/sludge and its degradability. The default (theoretical) value for Bo is 0.25kg CH4/kg BOD for wastewater and for sludge (Lexmond et al., 1995).3

• Fraction of wastewater treated by certain handling systems (WS%): These are the fractionsof wastewater treated by a specific handling system, i.e., aerobic or anaerobic.Country specific estimates for WS should be used where available. Default estimatesof WS per cent for different countries are provided in Table 6-7 to 6-9.

• Fraction of sludge treated by certain handling systems (SS%): These are the fractions ofsludge treated by a specific handling system, i.e., aerobic or anaerobic. Country-specific estimates for SS should be used where available.

• Methane conversion factor: The amount of methane that is actually emitted depends on theCH4 conversion factor. The MCF defines the portion of CH4 producing potential (Bo)that is achieved. The MCF varies between 0.0 for a completely aerobic system to 1.0for a completely anaerobic system. Countries should contact wastewater experts to

3 Bo is expressed in units of kg CH4/kg DC, where DC is the indicator of degradablecomponent of the waste (either COD or BOD). By definition, BOD is less than or equalto COD; the maximum BOD possible is, in fact, the COD. Therefore, when estimatingthe maximum CH4 producing potential from BOD or COD, the maximum potential CH4produced per unit of BOD is equivalent to the maximum potential CH4 produced perunit of COD. This value is 0.25 kg CH4/kg COD.

6 WASTE


determine MCFs. If no data are available, as a default, use 0 for aerobic systems, and1.0 for anaerobic.4

Since aerobic and anaerobic handling are the only handling systems considered, the CH4

conversion rate can be used to characterise a broad range of systems falling betweenaerobic and anaerobic handling systems.

Equation 10 presents the emission factor calculation for wastewater:

EQUATION 10

EFi = Boi x ∑ (WSix x MCFx )

where:

EFi = emission factor (kg CH4 /kg DC) for wastewater type (e.g., fertiliserindustry, domestic, etc.)

Boi = maximum methane producing capacity (kg CH4/kg DC) forwastewater type i

WSix = fraction of wastewater type i treated using wastewater handlingsystem x

MCFx = methane conversion factors of each wastewater system x

Equation 11 presents the emission factor calculation for sludge:

EQUATION 11

EFj = Boj x ∑(SSjy x MCFy)

where:

EFj = emission factor (kg CH4 /kg DC) for sludge type j (e.g., fertiliserindustry wastewater, domestic wastewater, etc.)

Boj = maximum methane producing capacity (kg CH4/kg DC) for sludge type j

SSjy = fraction of sludge type j treated using sludge handling system y

MCFy = methane conversion factors of each sludge handling system y (Seefootnote 4)

4 If sludge is disposed of in landfills then the resulting emissions are already accountedfor in the IPCC/OECD SWDS emission methodology (Section 6.2.4). If sludge isincinerated or burned as part of an energy recovery system, then the resulting emissionsshould be reported for in the Energy Chapter, classified as an industrial waste fuel. Inthese cases, to ensure that emissions are not counted twice an “MCF” of zero should beused in this methodology for sludge disposed in SWDSs or incinerated, or burned as partof an energy recovery system. In all other cases, an appropriate MCF value should beselected based on the specific characteristics of the system used to dispose of the sludge.

WASTE


Step 3 - Wastewater Emissions

To estimate total emissions from wastewater, the selected emissions factors are multipliedby the associated organic wastewater production and summed. Subtract the amount ofCH4, if any, that is recovered and thus not emitted into the atmosphere for each handlingmethod. If no data are readily available, the default assumption is that this amount is zero.Sum the results for each handling method to determine total CH4 emissions fromwastewater. In equation form, the estimate of total CH4 emissions from wastewaterhandling is as follows:

EQUATION 12

WM = Σi (TOWi x EFi - MRi)

where:

WM = total methane emissions from wastewater in kg CH4

TOWi = total organic waste for wastewater type i in kg DC/yr. For domesticstreams, the DC is BOD; for industrial streams it is the COD (Step1)

EFi = emission factor for wastewater type i in kg CH4/kg DC (Step 2)

MRi = total amount of methane recovered or flared from wastewater type iin kg CH4. If no data are available, use the default value of zero

Step 4 - Sludge Emissions

To estimate total emissions from sludge, the selected emissions factors are multiplied bythe associated organic sludge production and summed. Subtract the amount of CH4, ifany, that is recovered and thus not emitted into the atmosphere for each handlingmethod. If no data are readily available, the default assumption is that this amount is zero.Sum the results for each handling method to determine total CH4 emissions fromwastewater. In equation form, the estimate of total CH4 emissions from sludge handling isas follows:

EQUATION 13

SM = ∑j (TOSj x EFj - MRj)

where:

SM = total methane emissions from sludge in kg CH4

TOSj = total organic waste for sludge type j in kg DC/yr. For domesticstreams, the DC is BOD; for industrial streams it is COD (Step 1)

EFj = emission factor for sludge type j in kg CH4/kg DC (Step 2)

MRj = total amount of methane recovered or flared from sludge type j in kgCH4. If no data are available, the default is zero

6 WASTE


Step 5 - Total Emissions

Total emissions from wastewater and sludge can be determined by summing the results ofSteps 3 and 4. This is expressed as follows in Equation 14:

EQUATION 14

TM = WM + SM

where:

TM = total methane from wastewater and sludge handling in kg CH4

WM = total methane emissions from wastewater in kg CH4

SM = total methane emissions from sludge in kg CH4

6 . 3 . 6 U n c e r t a i n t i e s

The quality of CH4 emissions estimates for wastewater handling is directly related to thequality and availability of the waste management data used to derive these estimates.Country specific data on wastewater quantities, characteristics, and wastewatermanagement methods are very limited. The principal sources of uncertainty are describedbelow.

Organic Wastewater Quantity and Composition

Often the amount of degradable organic wastewater that is produced and the volumeshandled in the various systems is not well known. Consequently, limitations exist forquantifying the fraction of wastewater subject to specific systems.

Physical and Chemical Data

Country-specific data on wastewater characteristics are very limited. For example,reported organic component values in industrial source categories are averages fromseveral processes. Accurate and detailed data on the chemical characteristics and volumesof process wastewater streams could improve the emissions estimates.

Wastewater Handling Facility Efficiency and Output

Aerobically treated wastewater by handling plants may be subject to anaerobic conditionsdue to poorly managed and functioning facilities. This contributes to an underestimate ofemissions. Additionally, current estimates from wastewater handling lagoons are relativelyuncertain due to the limited available data. Work is on-going to develop better emissionfactors from these sources.

TABLE 6-5ESTIMATED BOD5 VALUES IN DOMESTIC WASTEWATER BY REGION

Region BOD5 Value (kg/cap/day)

BOD5 Value (kg/1000 persons/yr)

Africa 0.037 13,505

Asia, Middle East, Latin America 0.04 14,600

N. America, Europe, Former USSR, Oceania 0.05 18,250

Source: IPCC (1994)

WASTE


TABLE 6-6INDUSTRIAL WASTEWATER DATA BY REGION

Industry Type and Region WastewaterProduced

(m3/tonnes ofproduct)

COD Value(kg COD/m3

wastewater)

Country

Beverage - Distilled & IndustryGeneric - ethanol 13 m3/ m3 ethanol 40Generic - ethanol NAV 5,000 kg/ m3 ethanolSouth America NAV 22 BrazilWestern Europe NAV 4.0 - 5.0 Netherlands

Beverage - Malt & BeerGeneric 5 m3/ m3 beer 17Generic 5-9 m3/ m3 beer 2.0 - 7.0Western Europe NAV 1.0 - 1.5 Netherlands

Food - Meat & PoultryGeneric 1.4 m3/animal NAVWestern Europe NAV 2.9 NetherlandsNorth America NAV 15.0 USA

Food - FishNorth America NAV 2.5 USA

Food - CoffeeNorth America NAV 3.0 - 14.0 USA

Food - Dairy ProductsGeneric 2.8 NAVWestern Europe NAV 1.5 Netherlands

Food - Fruits & VegetablesGeneric (cannery) 26 NAVGeneric Tomato processing 26 NAVNorth America, potatoes NAV 3.0 USAWestern Europe, bean blanching NAV 5.2 NetherlandsWestern Europe, sauerkraut NAV 10.0 - 20.0 Netherlands

Food - OilsGeneric - Vegetable oil 1.6 0.3Middle East NAV 42 TurkeyAsia NAV 25 Malaysia

Food - SugarCentral America (cane) NAV 98 Mexico

Iron And SteelSouth America 0.1 NAV Brazil

Organic ChemicalsWestern Europe NAV 20- 40 Netherlands

PharmaceuticalsMiddle East NAV 1.3 Egypt

6 WASTE


TABLE 6-6 (CONTINUED)INDUSTRIAL WASTEWATER DATA BY REGION

Industry Type and Region Wastewater Produced(m3/tonnes of

product)

COD Value(kg COD/m3

wastewater)

Country

StarchGeneric, potato starch NAV 4.0 - 16Generic, wheat starch NAV 2.0 - 42Generic, corn starch NAV 10

Petroleum ProductionNorth America NAV 0.3 -0.4 USANorth America NAV 1.8 Canada

Pulp & PaperGeneric (pulp) 58 2.0 - 15North America pulp mill 140 NAV USAGeneric (paper) NAV 2.0 - 8.0North America (virgin paper) 97 1.6 USANorth America (recycled paper) 44 3.0 USAWestern Europe (paper) NAV 1.0 - 3.0 Netherlands

TextilesRayon 501 NAVGreece NAV 0.09North America, textile mills NAV 1.0 USA

Leather TanningNorth America, generic NAV 5.8 USA

Source: Doorn and Eklund (1995). For a detailed list of references for each wastewater category, see Doorn andEklund (1995). Wastewater production of COD values are not available (NAV) for every country and region.Research is ongoing to develop wastewater production and COD values for these countries and regions. Notethat these data are currently undergoing revision and updating.

TABLE 6-7DOMESTIC WASTEWATER TREATMENT EMISSIONS FACTOR DERIVATION DATA

Region Type of Treatment Fraction of WastewaterTreated

(%)

MCF (%)

AfricaKenya Lagoons 50 NAVTunisia Lagoons 20 NAVZimbabwe Activated Sludge 50 NAVOther Africa Lagoons 5 80

AsiaIndonesia not specified 1 NAVSingapore not specified 1 NAVSouth Korea not specified 1 NAVTaiwan not specified 1 NAVOther Asia not specified 5 75

Latin America And Caribbean not specified 10 80Australia And New Zealand not specified 80 70

Source: Doorn and Eklund (1995). For a detailed list of references for each region, see Doorn and Eklund (1995). Methanecorrection factor (MCF) data are not available (NAV) for some countries and regions. Research is ongoing to provide MCFestimates for these countries and regions. Note that these data are currently undergoing revision and updating.

WASTE


TABLE 6-8INDUSTRIAL WASTEWATER TREATMENT EMISSIONS FACTOR DERIVATION

Region Type ofIndustry

Type ofTreatment

Fraction of WastewaterTreated

(%)

MCF (%)

Africa

Kenya textiles Lagoons 60 NAV

Kenya coffeeproduction

Lagoons 5 NAV

Other Africa All Lagoons 10 90

Asia

Indonesia All not specified 10 NAV

Malaysia palm oil not specified 90 NAV

Singapore All not specified 10 NAV

South Korea All not specified 10 NAV

Taiwan All not specified 10 NAV

Thailand breweries activated sludge 50 NAV

Other Asia All not specified 20 90

North America

Canada All not specified 90 70

USA All not specified 90 70

Latin America & Caribbean All not specified 20 90

Australia & New Zealand All not specified 95 70

Source: Doorn and Eklund (1995). For a detailed list of references for each region, see Doorn and Eklund (1995). Methanecorrection factor (MCF) data are not available (NAV) for some countries and regions. Research is ongoing to provide MCFestimates for these countries and regions. Note that these data are currently undergoing revision and updating.

6 WASTE


TABLE 6-9UNSPECIFIED WASTEWATER TYPE EMISSIONS FACTOR DERIVATION DATA

Region Type of Treatment Fraction ofWastewater

Treated (%)

MCF (%)

AfricaSouth Africa not specified 10 NAV

AsiaAfghanistan not specified 1 NAV

Latin America And CaribbeanColombia Lagoons 3 NAVArgentina Lagoons 3 NAV

EuropeAlbania not specified 1-92 NAVAustria not specified 65 NAVBelgium not specified 85 NAVBulgaria not specified 10-100 NAVBelarus not specified 10-80 NAVCroatia not specified 57 NAVCzech Rep not specified 10-5 NAVDenmark not specified 90 NAVEstonia not specified 10-80 NAVFinland not specified 68 NAVFrance not specified 50-85 NAVGermany not specified 90 NAVHungary not specified 44 NAVIreland not specified 66 NAVItaly not specified 92 NAVLatvia not specified 10-80 NAVLithuania not specified 10-80 NAVMoldavia not specified 10-80 NAVNetherlands not specified 90 NAVNorway not specified 94 NAVPoland not specified 10-50 NAVPortugal not specified 42 NAVRomania not specified 10-46 NAVRussia not specified 10-80 NAVSerbia not specified 57 NAVSlovenia not specified 87 NAVSpain not specified 67 NAVSweden not specified 98 NAVSwitzerland not specified 88 NAVTurkey not specified 38 NAVUkraine not specified 10-80 NAVUnited Kingdom not specified 90 NAVSlovakia not specified 10-65 NAV

Source: Doorn and Eklund (1995). Methane correction factor (MCF) data are not available (NAV). Research is ongoingto provide MCF estimates for these and other wastewater treatment systems. Note that these data are currentlyundergoing revision and updating.

WASTE


6 .4 N i t rou s Ox id e f rom Hum a n SewageSince N2O emissions from human sewage are closely linked to the agricultural N cycle,the method is further discussed in the Agriculture Chapter. For a detailed description ofthe proposed methodology, the reader is referred to Section 4.5.4 (on indirect N2Oemissions from nitrogen used in agriculture).

The emissions of N2O from human sewage are calculated as follows:

EQUATION 15

N2O(S) = Protein x FracNPR x NRPEOPLE x EF6

where:

N2O(s) = N2O emissions from human sewage (kg N2O-N/yr)

Protein = annual per capita protein intake (kg/person/yr)

NRPEOPLE = number of people in country

EF6 = emissions factor (default 0.01 (0.002-0.12) kg N2O-N/kg sewage-N produced) (See Table 4-18 in Agriculture Chapter)

FracNPR = fraction of nitrogen in protein (default = 0.16 kg N/kg protein)(See Table 4-19 in Agriculture Chapter)

6 . 5 E m i s s i on s f rom W a s t e I n c i n e r a t i on

6 . 5 . 1 I n t r o d u c t i o n

Waste incineration like other types of combustion, is a source of GHG emissions. Fewdata have been compiled on the global emissions from waste incineration. Preliminaryindicators are that this source represents a small percentage of the total GHG outputfrom the waste source category.

6 . 5 . 2 E m i s s i o n s

Certainly waste incineration produces CO2, but it is difficult to identify the portion whichshould be considered net emissions. A large fraction of the carbon in waste combusted(e.g., paper, food waste) is derived from biomass raw materials which are replaced byregrowth on an annual basis. These emissions should not be considered netanthropogenic CO2 emissions in the IPCC Methodology. If the agricultural or forestrysources are not being sustainably managed, net CO2 emissions (equivalent to reductionsin biomass stocks) should be accounted for in those source categories. On the otherhand, some carbon in waste is in the form of plastics or other products based on fossilfuel. Combustion of these materials, like fossil fuel combustion, releases net CO2emissions. In estimating emissions from waste incineration, the desired approach is toseparate carbon in the incinerated waste into biomass and fossil fuel based fractions.Only the fossil based portion should be considered net carbon emissions. Any suchdetailed analysis should ensure that carbon emissions are not double counted in thetreatment of stored carbon under energy emissions. See Overview to the IPCC Guidelines.

6 WASTE


A recent Belgian analysis (Debruyn and Van Rensbergen, 1994) offers an example of avery detailed approach.

Other relevant gases released from combustion are net GHG emissions. Methaneemissions from waste incineration are highly uncertain. An expert working grouprecognised waste incineration as a source of methane production, but was not able togive global estimates or default emissions factors. Although this source is considered tobe relatively small compared to the other CH4 sources in waste, it was recognised as anarea for further research in the future (Berdowski et al., 1993).

Recent studies have also shown that N2O may be an important GHG produced fromincineration. Table 6-10 provides data from studies of several incineration plants and theN2O produced from the waste incineration (de Soete, 1993). Studies in Belgium (IPCC,1993), Japan (Tanaka et al., 1992) and Norway (Rosland, 1993) have estimated N2Oproduction from their waste incineration processes. It has also been found that theemission level depends on the nature of the waste burned. Research in Japan has notedthat while all types of incineration produce N2O, sludge incinerators produce the highestemissions rates (Tanaka et al., 1992).

Traditional air pollutants from combustion - NOx, CO, NMVOC - are characterised inexisting emissions inventory systems. The IPCC does not provide a new methodology forthese gases, but recommends that national experts use existing published methods. Somekey examples of the current literature providing methods are: Default Emission FactorHandbook (CORINAIR, 1994), as well as the US EPA's Compilation of Air PollutantEmissions Factors (AP-42) (US EPA, 1985) and Criteria Pollutant Emission Factors for the1985 NAPAP Emissions Inventory (Stockton and Stelling, 1987).

TABLE 6-10NITROUS OXIDE EMISSIONS FROM WASTE INCINERATION

N2O Emission

Nature of Waste(reference)

Facility ToC ppmva

min.ppmva

averageppmva

max.O2(%)

g N2O /tonnewaste

Municipal refuse 10 furnaces (65-300 tonnes/day) 1.2 8 18

Municipal refuse Stepgrate

Stepgrate

Fluid. bed

780-880

780-980

830-850

0.8

4

6.7

4.9

24

10.5

10

8-14

13-15

11-43

40-220

14-123

Municipal solid waste 5 stokers (20-400 tonnes/day) 3 7 12 26-270

3 Fluid. bed 5.6 9.8 17.1 97-293

rot. koln (120 tonnes/day) 10.2 11.1 12.1 35-165

Sewage-sludge 4 incin. (150-300 tonnes/day) 57 87 125

Sludge Rotary grate

Fluid. bed

Fluid. bed

Fluid. bed

Fluid. bed

750

770-812

838-854

834-844

853-887

270

135

100

45

50.7

600

292

320

145

227

580-1528

684-1508

275-886

101-307

Source: de Soete, 1993. a ppmv = parts per million by volume

WASTE


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Harries and R. Pocock (1996) ‘’ A Methodology for Updating Routinely theAnnual Estimate of Methane Emissions from Landfill Sites in the UK. ‘’ ETSU,AEA Technology, Report RYWA/18678001/R4.

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Bingemer, H.G. and P.J. Crutzen (1987), “The production of methane from solid wastes.”Journal of Geophysical Research, 92 (D2): 2181-2187.

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de Soete, G. (1993), “Nitrous oxide from combustion and industry: chemistry, emissions,and control”, pp. 324-325. Working Group Report: Methane Emissions fromBiomass Burning. In : Proceedings of an International IPCC Workshop on Methaneand Nitrous Oxide: Methods in National Emissions Inventories and Options for Control.A.R. van Amstel (ed.), RIVM Report No. 481507003, Bilthoven, The Netherlands.

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IPCC (1992), Climate Change 1992. The Supplementary Report to the IPCC ScientificAssessment. (J.T. Houghton, G.J. Jenkins and J.J. Ephraums (eds)). Published forThe Intergovernmental Panel on Climate Change (IPCC), World MeteorologicalOrganization/United Nations Environment Programme, Cambridge UniversityPress, UK.

IPCC (1993), Parts I & II: National GHG Inventories: Transparency in Estimation andReporting. Part III: Preliminary IPCC National GHG Inventories: In-Depth Review.Prepared by The Intergovernmental Panel on Climate Change (IPCC) andOrganisation for Economic Co-operation and Development, WorldMeteorological Organization/United Nations Environment Programme.

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IPCC (1995), “IPCC Guidelines for National Greenhouse Gas Inventories, 3 Volumes: Volume 1,Reporting Instructions; Volume 2, Workbook; Volume 3, Reference Manual.”Intergovernmental Panel of Climate Change.

IPCC (1996), Climate Change 1995. The Science of Climate Change. (J.T. Houghton, L.G.Meira Filho, B.A. Callander, N. Harris, A. Kattenberg and K. Maskell (eds)).Published for The Intergovernmental Panel on Climate Change (IPCC), WorldMeteorological Organization/United Nations Environment Programme,Cambridge University Press, UK.

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OECD (1995), OECD Environmental Data Compendium 1995. Organisation for EconomicCo-operation and Development.

Rosland, A. (1993), Greenhouse Gas Emissions in Norway: Inventories and Estimation Methods,pp.14. Prepared for the Norwegian Ministry of the Environment, Oslo, Norway.

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