A review of urban air pollution monitoring and exposure assessment methods

The impact of urban air pollution on the environments and human health has drawn increasing concerns from researchers, policymakers and citizens. To reduce the negative health impact, it is of great importance to measure the air pollution at high spatial resolution in a timely manner. Traditionally, air pollution is measured using dedicated instruments at fixed monitoring stations, which are placed sparsely in urban areas. With the development of low-cost micro-scale sensing technology in the last decade, portable sensing devices installed on mobile campaigns have been increasingly used for air pollution monitoring, especially for traffic-related pollution monitoring. In the past, some reviews have been done about air pollution exposure models using monitoring data obtained from fixed stations, but no review about mobile sensing for air pollution has been undertaken. This article is a comprehensive review of the recent development in air pollution monitoring, including both the pollution data acquisition and the pollution assessment methods. Unlike the existing reviews on air pollution assessment, this paper not only introduces the models that researchers applied on the data collected from stationary stations, but also presents the efforts of applying these models on the mobile sensing data and discusses the future research of fusing the stationary and mobile sensing data

Air Pollution and Health: A Review of Measurement Techniques

Air pollution is one of the significant causes of loss of healthy life years due to illness originating from indoor and outdoor air pollution sources like burning of biomass, vehicular emissions, etc. In the presented study, review of various methods used to assess health risks in terms of mortality and morbidity has been described. The use of precise instruments is essential for monitoring of health determinants causing serious health effects in urban regions. Data obtained from monitoring can be fed into the mathematical models in order to get the overall impact. These models are fed with specific concentration value for specific compounds, and they provide calculated number of population at risk. The main problem in using such models is the inability to calculate health risks for every pollutant. To validate the results obtained from mathematical models surveying needs to be synergies with the results. In air pollution impact assessment studies, public perception is one of the important components which these mathematical models do not incorporate, hence we recommend integrated assessment models for such studies. Perception based surveys generate huge data set and require statistical tools like SPSS, STATA for further analysis. It is essential to carry out exposure assessment studies as well to determine the pollution source and its impact on health in a more holistic way. Knowledge of these factors will help us to take measures to reduce pollutant concentration and recommend alternative solution

Urban air pollution and health inequities: a workshop report.

Over the past three decades, an array of legislation with attendant regulations has been implemented to enhance the quality of the environment and thereby improve the public's health. Despite the many beneficial changes that have followed, there remains a disproportionately higher prevalence of harmful environmental exposures, particularly air pollution, for certain populations. These populations most often reside in urban settings, have low socioeconomic status, and include a large proportion of ethnic minorities. The disparities between racial/ethnic minority and/or low-income populations in cities and the general population in terms of environmental exposures and related health risks have prompted the "environmental justice" or "environmental equity" movement, which strives to create cleaner environments for the most polluted communities. Achieving cleaner environments will require interventions based on scientific data specific to the populations at risk; however, research in this area has been relatively limited. To assess the current scientific information on urban air pollution and its health impacts and to help set the agenda for immediate intervention and future research, the American Lung Association organized an invited workshop on Urban Air Pollution and Health Inequities held 22-24 October 1999 in Washington, DC. This report builds on literature reviews and summarizes the discussions of working groups charged with addressing key areas relevant to air pollution and health effects in urban environments. An overview was provided of the state of the science for health impacts of air pollution and technologies available for air quality monitoring and exposure assessment. The working groups then prioritized research needs to address the knowledge gaps and developed recommendations for community interventions and public policy to begin to remedy the exposure and health inequities

Environmental public health tracking of childhood asthma using California health interview survey, traffic, and outdoor air pollution data.

BackgroundDespite extensive evidence that air pollution affects childhood asthma, state-level and national-level tracking of asthma outcomes in relation to air pollution is limited.ObjectivesOur goals were to evaluate the feasibility of linking the 2001 California Health Interview Survey (CHIS), air monitoring, and traffic data; estimate associations between traffic density (TD) or outdoor air pollutant concentrations and childhood asthma morbidity; and evaluate the usefulness of such databases, linkages, and analyses to Environmental Public Health Tracking (EPHT).MethodsWe estimated TD within 500 feet of residential cross-streets of respondents and annual average pollutant concentrations based on monitoring station measurements. We used logistic regression to examine associations with reported asthma symptoms and emergency department (ED) visits/hospitalizations.ResultsAssignment of TD and air pollution exposures for cross-streets was successful for 82% of children with asthma in Los Angeles and San Diego, California, Counties. Children with asthma living in high ozone areas and areas with high concentrations of particulate matter < 10 microm in aerodynamic diameter experienced symptoms more frequently, and those living close to heavy traffic reported more ED visits/hospitalizations. The advantages of the CHIS for asthma EPHT include a large and representative sample, biennial data collection, and ascertainment of important socio-demographic and residential address information. Disadvantages are its cross-sectional design, reliance on parental reports of diagnoses and symptoms, and lack of information on some potential confounders.ConclusionsDespite limitations, the CHIS provides a useful framework for examining air pollution and childhood asthma morbidity in support of EPHT, especially because later surveys address some noted gaps. We plan to employ CHIS 2003 and 2005 data and novel exposure assessment methods to re-examine the questions raised here

Road traffic pollution monitoring and modelling tools and the UK national air quality strategy.

This paper provides an assessment of the tools required to fulfil the air quality management role now expected of local authorities within the UK. The use of a range of pollution monitoring tools in assessing air quality is discussed and illustrated with evidence from a number of previous studies of urban background and roadside pollution monitoring in Leicester. A number of approaches to pollution modelling currently available for deployment are examined. Subsequently, the modelling and monitoring tools are assessed against the requirements of Local Authorities establishing Air Quality Management Areas. Whilst the paper examines UK based policy, the study is of wider international interest

Air Pollution Exposure Assessment for Epidemiologic Studies of Pregnant Women and Children: Lessons Learned from the Centers for Children’s Environmental Health and Disease Prevention Research

The National Children’s Study is considering a wide spectrum of airborne pollutants that are hypothesized to potentially influence pregnancy outcomes, neurodevelopment, asthma, atopy, immune development, obesity, and pubertal development. In this article we summarize six applicable exposure assessment lessons learned from the Centers for Children’s Environmental Health and Disease Prevention Research that may enhance the National Children’s Study: a) Selecting individual study subjects with a wide range of pollution exposure profiles maximizes spatial-scale exposure contrasts for key pollutants of study interest. b) In studies with large sample sizes, long duration, and diverse outcomes and exposures, exposure assessment efforts should rely on modeling to provide estimates for the entire cohort, supported by subject-derived questionnaire data. c) Assessment of some exposures of interest requires individual measurements of exposures using snapshots of personal and microenvironmental exposures over short periods and/or in selected microenvironments. d) Understanding issues of spatial–temporal correlations of air pollutants, the surrogacy of specific pollutants for components of the complex mixture, and the exposure misclassification inherent in exposure estimates is critical in analysis and interpretation. e) “Usual” temporal, spatial, and physical patterns of activity can be used as modifiers of the exposure/outcome relationships. f) Biomarkers of exposure are useful for evaluation of specific exposures that have multiple routes of exposure. If these lessons are applied, the National Children’s Study offers a unique opportunity to assess the adverse effects of air pollution on interrelated health outcomes during the critical early life period

Black carbon as an additional indicator of the adverse health effects of airborne particles compared with PM10 and PM2.5.

Current air quality standards for particulate matter (PM) use the PM mass concentration [PM with aerodynamic diameters ≤ 10 μm (PM(10)) or ≤ 2.5 μm (PM(2.5))] as a metric. It has been suggested that particles from combustion sources are more relevant to human health than are particles from other sources, but the impact of policies directed at reducing PM from combustion processes is usually relatively small when effects are estimated for a reduction in the total mass concentration

Quantifying the health burden misclassification from the use of different PM2.5 exposure tier models: A case study of London

Exposure to PM2.5 has been associated with increased mortality in urban areas. Hence, reducing the uncertainty in human exposure assessments is essential for more accurate health burden estimates. Here we quantify the misclassification that occurs when using different exposure approaches to predict the mortality burden of a population using London as a case study. We develop a framework for quantifying the misclassification of the total mortality burden attributable to exposure to fine particulate matter (PM2.5) in four major microenvironments (MEs) (dwellings, aboveground transportation, London Underground (LU) and outdoors)in the Greater London Area (GLA), in 2017. We demonstrate that differences exist between five different exposure Tier-models with incrementally increasing complexity, moving from static to more dynamic approaches. BenMap-CE, the open source software developed by the U.S. Environmental Protection Agency, is used as a tool to achieve spatial distribution of the ambient concentration by interpolating the monitoring data to the unmonitored areas and ultimately estimate the change in mortality on a fine resolution. Our results showed that using the outdoor concentration as a surrogate for the total population exposure but ignoring the different exposure concentration that occurs indoors and the time spent in transit, would lead to a misclassification of 1,174 predicted mortalities in GLA. Indoor exposure to PM2.5 is the largest contributor to total population exposure, accounting for 80% of total mortality, followed by the London Underground which contributes 15%, albeit the average percentage of time spent there by Londoners is only 0.4%. We generally confirmed that increasing the complexity and incorporating important microenvironments, such as the highly polluted LU, could significantly reduce the misclassification in health burden assessments

Measurement and Modeling of Ground-Level Ozone Concentration in Catania, Italy using Biophysical Remote Sensing and GIS

This experimental study examined spatial variation of ground level ozone (O3) in the city of Catania, Italy using thirty passive samplers deployed in a 500-m grid pattern. Significant spatial variation in ground level O3 concentrations (ranging from 12.8 to 41.7 g/m3) was detected across Catania’s urban core and periphery. Biophysical measures derived from satellite imagery and built environment characteristics from GIS were evaluated as correlates of O3 concentrations. A land use regression model based on four variables (land surface temperature, building area, residential street length, and distance to the coast) explained 74% of the variance (adjusted R2) in measured O3. The results of the study suggest that biophysical remote sensing variables are worth further investigation as predictors of ground level O3 (and potentially other air pollutants) because they provide objective measurements that can be tested across multiple locations and over time