Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments

Background, aim and scope  

Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 μm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore, the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions.     

某高密度街区大气颗粒物质量浓度分布特征实测研究

为研究城市高密度街区大气颗粒物浓度分布特征,2019年秋季对上海市某高密度街区道路大气颗粒物浓度、空气温度、相对湿度、地理位置、车辆与道路图像视频信息进行了同步移动在线监测,并结合街区内固定站数据和后向轨迹模拟结果,总结了影响街区大气颗粒物浓度变化的主要因素。结果表明:城市大气颗粒物背景拟合值处于较低水平时,街区内的大气颗粒物浓度变化和影响因素易被识别;机动车污染源对大气颗粒物浓度贡献大,其中大型机动车的影响明显;户外施工和道路清扫会引起大气颗粒物浓度上升,其中PM₁₀上升更明显;交通密度大的十字路口大气颗粒物浓度通常较高;城市高架的盖状结构会阻碍大气颗粒物在垂直方向上的扩散,引起局部大气颗粒物浓度上升;街区内高大浓密的乔木对近地面的大气颗粒物屏蔽效果不理想,甚至有助于颗粒物累积;早晚高峰时段大气颗粒物浓度较非高峰时段高。     

某高密度街区大气颗粒物质量浓度分布特征实测研究

为研究城市高密度街区大气颗粒物浓度分布特征,2019年秋季对上海市某高密度街区道路大气颗粒物浓度、空气温度、相对湿度、地理位置、车辆与道路图像视频信息进行了同步移动在线监测,并结合街区内固定站数据和后向轨迹模拟结果,总结了影响街区大气颗粒物浓度变化的主要因素。结果表明:城市大气颗粒物背景拟合值处于较低水平时,街区内的大气颗粒物浓度变化和影响因素易被识别;机动车污染源对大气颗粒物浓度贡献大,其中大型机动车的影响明显;户外施工和道路清扫会引起大气颗粒物浓度上升,其中PM₁₀上升更明显;交通密度大的十字路口大气颗粒物浓度通常较高;城市高架的盖状结构会阻碍大气颗粒物在垂直方向上的扩散,引起局部大气颗粒物浓度上升;街区内高大浓密的乔木对近地面的大气颗粒物屏蔽效果不理想,甚至有助于颗粒物累积;早晚高峰时段大气颗粒物浓度较非高峰时段高。     

A multi-objective assessment of an air quality monitoring network using environmental,economic, and social indicators and GIS-based models

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O₃) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs’ objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O₃ was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O₃, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O₃ monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the performance of air quality monitoring networks in urban regions.

Implications:The U.S. Environmental Protection Agency issued a directive in 2006 that air pollution agencies assess the performance of their AQMNs; as a result, we developed a GIS-based, multi-objective assessment approach that integrates environmental, economic, and social indicators, and demonstrates its use through assessing the O₃ and PM₁₀ monitoring networks in the Phoenix metropolitan area. We exhibit a method of assessing network performance and identifying areas that would benefit from new monitoring stations; also, we demonstrate the effect of adding weights to the indicators. Our study shows that using a multi-indicator approach gave detailed assessment results for the Phoenix AQMN.     

Particulate matter air pollution and respiratory impact on humans and animals

Air pollution is now fully acknowledged to be a public health problem and a social issue. Particulate matter (PM) concentration has been linked with several clinical manifestations of pulmonary and cardiovascular diseases and is associated with morbidity and mortality induced by respiratory diseases both in human and animals. Current research on airborne particle-induced health effects investigates the critical characteristics of particulate matter that determine their biological effects. Scientific evidence assessed that the size of the airborne particles and their surface area determine the potential to elicit inflammatory injury, oxidative damage, and other biological effects. Thus, the present review paper aims to summarize the current evidences and findings on the effect of air pollution on lung function in both humans and animals.     

Impact of the global economic crisis on metal levels in particulate matter (PM) at an urban area in the Cantabria Region (Northern Spain)

Air pollution by particulate matter is well linked with anthropogenic activities; the global economic crisis that broke out in the last year may be a proper indicator of this close relationship. Some economic indicators show the regional effects of the crisis on the Cantabria Region. The present work aims to evaluate the impact of the economic crisis on PM10 levels and composition at the major city of the region, Santander. Some metals linked to anthropogenic activities were measured at Santander and studied by Positive Matrix Factorization; this statistical analysis allowed to identify three main factors: urban background, industrial and molybdenum-related factor. The main results show that the temporal trend of the levels of the industrial tracers found in the present study are well agree with the evolution of the studied economic indicators; nevertheless, the urban background tracers and PM10 concentration levels are not well correlated with the studied economic indicators.     

Neural network and multiple regression models for PM10 prediction in Athens: a comparative assessment

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter <10 microm (PM10) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2-9.4%) and of episodic prediction ability (false alarm rate values lower by 7-13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.     

Environmental Appraisal-Particulate Matter,Oxides of Sulfur,and Sulfuric Acid

The role of particulate matter and oxides of sulfur in degradation of the atmospheric environment is discussed. The Federal Air Quality Criteria for these pollutants are analyzed for their conformance with the requirement of the Clean Air Act of 1967 that they reflect the latest scientific knowledge pertinent to the indication of their effects on health and welfare. Visibility reduction by suspended particulate matter is treated and the bases for the criteria issued in the documents “Air Quality Criteria for Particulate Matter” and “Air Quality Criteria for Sulfur Oxides” are examined. The reactions between particulate matter and gaseous pollutants are discussed, along with the Impact of particulate matter on modifications of weather processes. Local effects, such as precipitation, are considered. The relationship between pollution by particulate matter and cloud formation is discussed, as are persistence of fog and the observation that certain sources of particulate pollution are also sources of ice nuclei.     

Neural Network and Multiple Regression Models for PM10 Prediction in Athens: A Comparative Assessment

Abstract

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter <10 µm (PM₁₀) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2–9.4%) and of episodic prediction ability (false alarm rate values lower by 7–13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.     

Atmospheric pollution in an urban environment by tree bark biomonitoring - part II: Sr, Nd and Pb isotopic tracing

The harmful effect of manmade particles on natural processes and human health is documented by a large number of studies showing a positive correlation between particulate matter (PM) concentration and health effects. Diminution of this health risk necessitates among others the precise knowledge of the particle sources, their physical and chemical properties and their dissemination in the environment. Pb isotope ratios have been successfully used during the past decades as tracers of anthropogenic Pb disseminated in the biosphere. Here we show that tree bark biomonitoring with lead (Pb), strontium (Sr) and neodymium (Nd) isotope ratios as tracers allow a thorough analysis of the impacts of industrial and other anthropogenic emissions on the urban environment. This is the first comprehensive multi-isotope tracer study of atmospheric pollution in an urban environment allowing to identify and to integrate the different plume paths of emissions in a digital map system. This innovative approach might become an important tool for environmental management and policy-making processes dealing especially with risks and surveillance of air quality in the urban environment.     

The economic benefits of fulfilling the World Health Organization’s limits for particulates: A case study in Algeciras Bay (Spain)

Algeciras Bay is an important industrial and port zone in the south of Spain whose pollution by particulate matter surpasses the threshold levels recommended by the World Health Organization (WHO) in its 2005 Guide on Air Quality. This study analyses the mortality avoided and the economic benefit which would be derived from a reduction of the pollution of PM2.5 and PM10 to the levels recommended by the WHO in Algeciras Bay in the period 2005-2015. The analysis carried out shows that the industrial zones, such as Los Barrios and San Roque, are those which have greater levels of pollution and in which the relative risk is greater. The calculations for Algeciras Bay between 2000 and 2015 show 182 deaths which would be avoided if the particulate matter pollution were reduced to the levels recommended by the WHO. Likewise, the economic valuation which this impact has on health is carried out through two concepts: the cost of illness and the Value of Statistical Life (VSL). The result shows that the economic benefit that would come out with the cost of illness valuation is 5,329,110€ and from the VSL is 414,787,113€.

Implications: PM_2.5 has a greater concentration in industrial localities and is linked to the industrial activity. When the particulate matter pollution is reduced to the levels recommended by the WHO in an industrialised area such as Algeciras (Spain), 182 deaths which would be avoided. The result shows that the economic benefit that would come out with the cost of illness valuation is 5,329,110€ and from the value of statistical life is 414,787,113€.     

Evolution of particulate regulation in China--prospects and challenges of exposure-based control

China's urban and rural populations face very serious health risks from combustion particles. Major sources of exposure to inhalable particulates include the burning solid fuels (biomass and coal) for household cooking and heating, coal-fired industrial and residential boilers, tobacco smoking, and diesel motor vehicles. China began to address particulate pollution problems over 25 years ago and has implemented a series of progressively more aggressive policies. This paper reviews the successes and limitations of past and existing policies for particulate controls, as well as the effects of China's economic reforms and energy policies on particulate exposure and pollution management. We examine the challenge of emissions reporting, required as part of both China's pollution levy system and emerging system for "total emissions control." Finally, we discuss practical steps toward exposure-based regulation of particulates, which would take advantage of the high cost-effectiveness for lifesaving of controlling particulate exposure from household and neighborhood sources relative to that of controlling exposure from industrial sources.     

Adaptive neuro-fuzzy based modelling for prediction of air pollution daily levels in city of Zonguldak

Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters in the urban area are important due to health impact. Artificial intelligent techniques are successfully used in modelling of highly complex and non-linear phenomena. In this study, adaptive neuro-fuzzy logic method has been proposed to estimate the impact of meteorological factors on SO2 and total suspended particular matter (TSP) pollution levels over an urban area. The model forecasts satisfactorily the trends in SO2 and TSP concentration levels, with performance between 75-90% and 69-80 %, respectively.     

Long-term assessment of particulate matter using CHIMERE model

Particulate matter (PM) and aerosols have became a critical pollutant and object of several research applications, due to their increasing levels, especially in urban areas, causing air pollution problems and thus effects on human health. The main purpose of this study is to perform a first long-term air quality assessment for Portugal, regarding aerosols and PM pollution. The CHIMERE chemistry-transport model, forced by the MM5 meteorological fields, was applied over Portugal for 2001 year, with 10 km horizontal resolution, using an emission inventory obtained from a spatial top-down disaggregation of the 2001 national inventory database. The evaluation model exercise shows a model trend to overestimate particulate pollution episodes (peaks) at urban sites, especially in winter season. This could be due to an underprediction of the winter model vertical mixing and also to an overestimation of PM emissions. Simulated inorganic components (ammonium and sulfate) and secondary organic aerosols (SOA) were compared to measurements taken at Aveiro (northwest coast of Portugal). An underestimation of the three components was verified. However, the model is able to predict their seasonal variation. Nevertheless, as a first approach, and despite the complex topography and coastal location of Portugal affected by sea salt natural aerosols emissions, the results obtained show that the model reproduces the PM levels, temporal evolution, and spatial patterns. The concentration maps reveal that the areas with high PM values are covered by the air quality monitoring network.     

杭州市空气颗粒物污染特征及变化规律研究

根据2006—2010年杭州市空气颗粒物的监测数据及2002、2006、2008年空气颗粒物来源解析结果,对杭州市空气颗粒物浓度、化学组分与污染来源等特征的变化规律进行分析,以期为空气颗粒物污染控制提供决策依据。结果表明,近年来杭州市PM10浓度有所下降,但一类功能区PM10仍超出《环境空气质量标准》(GB 3095—1996)的要求(≤0.04mg/m3),杭州市空气颗粒物污染以细颗粒物为主,空气颗粒物的二次转化、机动车尾气尘等产生的二次粒子污染相对严重;煤烟尘对杭州市PM10的贡献率下降明显,城市扬尘、二次粒子和机动车尾气尘对PM10的贡献率有所增加,是杭州市PM10的主要来源。     

重庆主城区大气重污染形势的激光雷达探测与分析

2013年1月12日-26日,利用大气超级站ALS300型激光雷达对重庆主城区大气进行了连续探测,分析了重污染形势期间的大气扩散条件及大气颗粒物时空分布等探测结果。分析表明,大气层结持续稳定,扩散条件差使得大气颗粒物浓度居高不下,大气能见度持续恶化;大气重污染期间PBL高度较低,平均为320～350m;大气颗粒物污染带处于100～400m高度范围;全国范围内异常的大气环流形势和重庆主城区独特的地形、气候特征是造成持续大气重污染形势的原因。     

An economic evaluation and assessment of environmental impact of the municipal solid waste management system for Taichung City in Taiwan

Municipal solid waste management (MSWM) is an important environmental challenge and subject in urban planning. For sustainable MSWM strategies, the critical management factors to be considered include not only economic efficiency of MSW treatment but also life-cycle assessment of the environmental impact. This paper employed linear programming technique to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of a MSWM system, and investigated the correlations between the economical optimization and pollutant emissions. A case study based on real-world MSW operating parameters in Taichung City is also presented. The results showed that the costs, benefits, streams of MSW, and throughputs of incinerators and landfills will be affected if pollution emission reductions are implemented in the MSWM strategies. In addition, the quantity of particulate matter is the best pollutant indicator for the MSWM system performance of emission reduction. In particular this model will assist the decision maker in drawing up a friendly MSWM strategy for Taichung City in Taiwan. Implications: Recently, life-cycle assessments of municipal solid waste management (MSWM) strategies have been given more considerations. However, what seems to be lacking is the consideration of economic factors and environmental impacts simultaneously. This work analyzed real-world data to establish optimal MSWM strategies considering economic efficiency and the air pollutant emissions during the life cycle of the MSWM system. The results indicated that the consideration of environmental impacts will affect the costs, benefits, streams of MSW, and throughputs of incinerators and landfills. This work is relevant to public discussion and may establish useful guidelines for the MSWM policies.     

The construction and examination of social vulnerability and its effects on PM2.5 globally: combining spatial econometric modeling and geographically weighted regression

Environmental Science and Pollution Research - Fine particulate matter (PM2.5) is of widespread concern, as it poses a serious impact on economic development and human health. Although the...     

Statistical modelling of effects on health linked to indoor air pollution, based on kitchen exposure and with reference to a cross-sectional household survey conducted in Nepal

Exposure to suspended particulate matter and carbon monoxide from indoor kitchen air can have significant effects on respiratory health as demonstrated by statistical modelling. Chronic respiratory illnesses and respiratory symptoms are modelled using the techniques of principal component analysis and binary logistic regression. Estimated models are generated from a cross-sectional household survey data conducted in Nepal with 168 respondents who cook for daily meals. The models show that individuals exposed to high levels of indoor air pollution particularly associated with unprocessed solid biomass fuels along with aging, tobacco smoking and living in poorly constructed houses mainly with mud are vulnerable to respiratory disorders.     

Estimation of economic costs of particulate air pollution from road transport in China

Valuation of health effects of air pollution is becoming a critical component of the performance of cost–benefit analysis of pollution control measures, which provides a basis for setting priorities for action. Beijing has focused on control of transport emission as vehicular emissions have recently become an important source of air pollution, particularly during Olympic games and Post-games. In this paper, we conducted an estimation of health effects and economic cost caused by road transport-related air pollution using an integrated assessment approach which utilizes air quality model, engineering, epidemiology, and economics. The results show that the total economic cost of health impacts due to air pollution contributed from transport in Beijing during 2004–2008 was 272, 297, 310, 323, 298 million US$ (mean value), respectively. The economic costs of road transport accounted for 0.52, 0.57, 0.60, 0.62, and 0.58% of annual Beijing GDP from 2004 to 2008. Average cost per vehicle and per ton of PM₁₀ emission from road transport can also be estimated as 106 US $/number and 3584 US $ t^?1, respectively. These findings illustrate that the impact of road transport contributed particulate air pollution on human health could be substantial in Beijing, whether in physical and economic terms. Therefore, some control measures to reduce transport emissions could lead to considerable economic benefit.