Exhaust emissions of transit buses: Brazil and India case studies

Cooper, Erin; Arioli, Magdala; Carrigan, Aileen; Lindau, Luis Antonio

doi:10.1016/j.retrec.2014.09.059

Cited by 13 publications

(9 citation statements)

References 1 publication

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“…It should be noted that tailpipe emissions can be greatly affected by local conditions, such as elevation, road traffic, and the specific fuel blends used. The values reported for Stockholm are much lower than other studies observed in literature, such as Cooper et al (2014) were NO x and PM 10 estimations for buses using NExBTL fuel (a market name for HVO from the company Nesté) show approximately doubled values compared to Stockholm. More specifically, the NO x emissions were around 7 g/km and the PM were around 0.08 g/km in this meta-analysis (Cooper et al, 2014).…”

Section: Inner City Electrification and Air Qualitycontrasting

confidence: 63%

“…The values reported for Stockholm are much lower than other studies observed in literature, such as Cooper et al (2014) were NO x and PM 10 estimations for buses using NExBTL fuel (a market name for HVO from the company Nesté) show approximately doubled values compared to Stockholm. More specifically, the NO x emissions were around 7 g/km and the PM were around 0.08 g/km in this meta-analysis (Cooper et al, 2014). In Stockholm, there is a significant amount (approximately 30% of the fleet) of non-diesel engine buses that have lower NO x and PM 10 emissions than their diesel counterparts.…”

Section: Inner City Electrification and Air Qualitycontrasting

confidence: 63%

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Impact of bus electrification on carbon emissions: The case of Stockholm

Xylia

Leduc

Laurent

et al. 2019

Journal of Cleaner Production

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Section: Inner City Electrification and Air Qualitycontrasting

confidence: 63%

Section: Inner City Electrification and Air Qualitycontrasting

confidence: 63%

Impact of bus electrification on carbon emissions: The case of Stockholm

Xylia

Leduc

Laurent

et al. 2019

Journal of Cleaner Production

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“…The Department of Transport in the United Kingdom (UK) reported a 21% increase in vehicle traffic from 2000 to 2010 (Figure 2) [22]. The wide variety of pollutants and PM emitted from these sources is primarily composed of volatile organic compounds (VOCs), nitrogen oxides (NO x ), sulfur dioxide (SO 2 ), carbon monoxide (CO), carbon dioxide (CO 2 ), and metal particles [21,22,23].…”

Section: Classification and Sources Of Pmmentioning

confidence: 99%

“…On the other hand, particles smaller than 1 μm behave like gas molecules, thus entering into the alveoli (deposited by diffusion forces), and move further into tissue and the circulatory system [31]. Generally, as the human body cannot prevent exposure or adversely effects by PM, people may experience several health problems including CVD, respiratory health effects, diabetes, and premature death [1,23]. The WHO (2016) estimates that PM pollution contributes to about 4.2 million premature deaths each year (16% of lung cancer deaths, 26% of respiratory infection deaths, 17% of ischemic heart disease and stroke deaths, and 25% of chronic obstructive pulmonary disease deaths), ranking it as the 14th leading cause of death worldwide [32,33,34].…”

Section: Health Problems Caused By Pm Exposurementioning

confidence: 99%

Particulate Matter Exposure of Passengers at Bus Stations: A Review

Ngoc

Kim

Bui

et al. 2018

IJERPH

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This review clarifies particulate matter (PM) pollution, including its levels, the factors affecting its distribution, and its health effects on passengers waiting at bus stations. The usual factors affecting the characteristics and composition of PM include industrial emissions and meteorological factors (temperature, humidity, wind speed, rain volume) as well as bus-station-related factors such as fuel combustion in vehicles, wear of vehicle components, cigarette smoking, and vehicle flow. Several studies have proven that bus stops can accumulate high PM levels, thereby elevating passengers’ exposure to PM while waiting at bus stations, and leading to dire health outcomes such as cardiovascular disease (CVD), respiratory effects, and diabetes. In order to accurately predict PM pollution, an artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) have been developed. ANN is a data modeling method of proven effectiveness in solving complex problems in the fields of alignment, prediction, and classification, while the ANFIS model has several advantages including non-requirement of a mathematical model, simulation of human thinking, and simple interpretation of results compared with other predictive methods.

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“…Fonte: adaptado de Brasil (2013). (ARRIAGA-COLINA et al, 2004;TEIXEIRA;FELTES;SANTANA, 2008;D' AVIGNON et al, 2010;SOUZA et al, 2013;COOPER et al, 2014) Equação 1, faz-se necessário calcular essa variável através da Equação 2:…”

Section: Introductionunclassified

Estimativa das emissões veiculares na região metropolitana de Fortaleza, CE, ano-base 2010

Lopes

Policarpo

Vasconcelos

et al. 2018

Eng. Sanit. Ambient.

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RESUMO No Brasil e no mundo, o setor dos transportes de passageiros e cargas tem contribuído decisivamente para o aumento das emissões de poluentes atmosféricos, com os consequentes problemas para o meio ambiente e para a saúde humana. Assim, muitos estudos têm recorrido a metodologias e/ou ferramentas específicas para modelar e simular poluentes atmosféricos. A frota de veículos no Ceará teve um crescimento de 169% nos últimos 10 anos, mas ainda se desconhece o volume de poluentes emitidos pela frota circulante da Região Metropolitana de Fortaleza (RMF). Nesse contexto, foram estimadas as emissões veiculares de escapamento para a RMF no ano de 2010. A quantificação das emissões de monóxido de carbono (CO), hidrocarbonetos não metano (NMHC), óxidos de nitrogênio (NOx), material particulado (MP) e aldeídos (RCHO) foi realizada através da metodologia bottom-up. De modo geral, as motocicletas apresentaram emissões significativas de poluentes, sobretudo de CO, NOx e MP, devido à grande quantidade de veículos na região. Os veículos ciclo Otto representam mais de 90% das emissões totais de CO, NMHC e RCHO, enquanto os veículos ciclo Diesel emitem mais de 85% das emissões totais de NOx e MP.

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Exhaust emissions of transit buses: Brazil and India case studies

Cited by 13 publications

References 1 publication

Impact of bus electrification on carbon emissions: The case of Stockholm

Impact of bus electrification on carbon emissions: The case of Stockholm

Particulate Matter Exposure of Passengers at Bus Stations: A Review

Estimativa das emissões veiculares na região metropolitana de Fortaleza, CE, ano-base 2010

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