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Brakes, tyres and road deposits have become important contributors to the overall particle emissions of vehicles globally, with constituents in these wear particles considered to be harmful to human health (PM 10 and PM 2.5 ). Previous research has documented mass/size distributions, physical and chemical characteristics, emission factors and long-term implications and environmental occurrences. The complex path these pollutants take from their origins to the environment, however, is not fully understood. This is partly owing to the breadth of spatio-temporal scales involved in the advection-diffusion processes (nanometers to meters, microseconds to minutes). These short timescale particle transport mechanisms impact human exposure, such as pedestrians and cyclists, and initiate the long-term interaction of these pollutants with other environmental compartments. Here, we present an analysis for urban driving conditions to highlight the opportunities to reveal these complex pathways and formulate opinions that aim to stimulate future enquiry. We describe important vehicular areas and exposure scenarios where efforts should focus. Future interdisciplinary research into these particle transport mechanisms must be prioritised as it can provide the foundation for developing urgently needed pollution control strategies, transport infrastructure layouts and transport policies that mitigate, or possibly eliminate pollution exposure risks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Copyright of Biomédica: Revista del Instituto Nacional de Salud is the property of Instituto Nacional de Salud of Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The utilization of solid fuels remains a significant contributor to air pollution, with well-documented adverse health consequences. In rural regions, the prevalence of solid fuel use for heating and cooking plays a pivotal role in shaping local air quality. This study focuses on evaluating personal exposure to gaseous pollutants originating from restaurants situated in Karunya Nagar, Coimbatore, Tamil Nadu, India. The study design considers establishments that use distinct energy sources, with a particular emphasis on those employing wood and liquefied petroleum gas. We measure the concentration of various pollutants, including particulate matter (PM1, PM2.5, PM10), carbon dioxide, formaldehyde, and total volatile organic carbon, utilizing advanced sensor technology. The levels of these pollutants are influenced by various factors, such as ventilation, chimney placement, stove type, fuel selection, time of exposure, frequency of exposure, and toxicity. Notably, our findings reveal that restaurants using wood as a cooking fuel tend to release higher quantities of gaseous pollutants compared to those employing liquefied petroleum gas. In addition to quantitative measurements, we employ comprehensive chemical characterization techniques, including scanning electron microscopy, X-ray diffraction analysis, energy dispersive X-ray analysis, and Fourier transform infrared spectroscopy, to delineate the morphology, chemical composition, and other essential properties of the emitted particulate matter. Our study sheds light on the potential health repercussions faced by rural residents who heavily rely on solid domestic fuels. The insights derived from this research not only contribute to the reduction of air pollution exposure but also facilitate the development of exposure assessment models for forthcoming epidemiological investigations. This aligns with the broader objectives of Sustainable Development Goals and seeks to enhance the well-being of women in rural Southern India. [ABSTRACT FROM AUTHOR]

Background: Evidence on the relationship between air pollution and allergic sensitisation in childhood is inconsistent, and this relationship has not been investigated in the context of smoke events that are predicted to increase with climate change. Thus, we aimed to evaluate associations between exposure in two early life periods to severe levels of particulate matter with an aerodynamic diameter < 2.5 μm (PM2.5) from a mine fire, background PM2.5, and allergic sensitisation later in childhood. Methods: We measured specific immunoglobulin E (IgE) levels for seven common aeroallergens as well as total IgE levels in a cohort of children who had been exposed to the Hazelwood coal mine fire, either in utero or during their first two years of life, in a regional area of Australia where ambient levels of PM2.5 are generally low. We estimated personal exposure to fire-specific emissions of PM2.5 based on a high-resolution meteorological and pollutant dispersion model and detailed reported movements of pregnant mothers and young children during the fire. We also estimated the usual background exposure to PM2.5 at the residential address at birth using a national satellite-based land-use regression model. Associations between both sources of PM2.5 and sensitisation to dust, cat, fungi, and grass seven years after the fire were estimated with logistic regression, while associations with total IgE levels were estimated with linear regression. Results: No association was found between the levels of exposure at either developmental stage to fire-related PM2.5 and allergic sensitisation seven years after the event. However, levels of background exposure were positively associated with sensitisation to dust (OR = 1.90, 95%CI = 1.12,3.21 per 1 μg/m3). Conclusions: Chronic but low exposure to PM2.5 in early life could be more strongly associated with allergic sensitisation in childhood than time-limited high exposure levels, such as the ones experienced during landscape fires. [ABSTRACT FROM AUTHOR]

Environmental epidemiology studies require accurate estimations of exposure intensities to air pollution. The process from air pollutant emission to individual exposure is however complex and nonlinear, which poses significant modeling challenges. This study aims to develop an exposure assessment model that can strike a balance between accuracy, complexity, and usability. In this regard, neural networks offer one possible approach. This study employed a custom-designed pruned feed-forward neural network (pruned-FNN) approach to calculate the air pollution exposure index based on emission time and rates, terrain factors, meteorological conditions, and proximity measurements. The model's performance was evaluated by cross-validating the estimated exposure indexes with ground-based monitoring records. The pruned FNN can predict pollution exposure indexes (PEIs) that are highly and stably correlated with the monitored air pollutant concentrations (Spearman's rank correlation coefficients for tenfold cross-validation (mean ± standard deviation: 0.906 ± 0.028) and for random cross-validation (0.913 ± 0.024)). The predicted values are also close to the ground truth in most cases (95.5% of the predicted PEIs have relative errors smaller than 10%) when the training datasets are sufficiently large and well-covered. The pruned-FNN method can make accurate exposure estimations using a flexible number of variables and less extensive data in a less money/time-consuming manner. Compared to other exposure assessment models, the pruned FNN is an appropriate and effective approach for exposure assessment that covers a large geographic area over a long period of time. [ABSTRACT FROM AUTHOR]

Exposure to fine particulate matter (PM2.5) air pollution is associated with large‐scale health consequences, but the ranges in estimates of global air pollution exposure and PM2.5‐related global premature mortality remain understudied. Using four model/observation‐based PM2.5 data sets and six Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we compare ranges in current PM2.5‐related mortality estimates based on model/observation combinations to the range of projected emissions reductions and the resulting impacts on global health from CMIP6 models. Although estimates of current mortality are sensitive to the PM2.5 data set (6.54–9.23 million/year using the central estimate from the Global Exposure Mortality Model), the projected near‐term benefits of emissions reductions for reduced mortality are much more certain. Specifically, until the middle of the century, uncertainty ranges in projected avoided deaths are less than the magnitude of ranges in present‐day mortality estimates, even when projected future changing socio‐demographic factors are considered. Under a low‐emissions scenario, avoided cumulative early deaths could reach 275 million (range: 243–351 million) by 2100, assuming no future socio‐demographic changes. Avoided cumulative deaths could reach 124 million (range: 74–246 million) if changing future socio‐demographic factors are considered. As the global population ages and becomes more sensitive to breathing polluted air, there will be an increasing need for policies that both reduce air pollution and improve public health. Plain Language Summary: Most people on Earth breathe polluted air. Breathing polluted air is associated with a variety of health problems, including early death. Despite the importance of breathing polluted air, global estimates of early death associated with breathing polluted air are often based on one observation‐based data set of global air pollution. Here we examine the ranges in estimates of global deaths from air pollution due to the choice of observation‐based data set. We find that estimates of recent global air pollution and associated deaths in recent years can vary substantially, depending on data set. We also use the latest climate model simulations to estimate how air pollution and associated deaths would change under a high‐emissions future and a low‐emissions future. We find that climate models agree that reducing fossil fuel emissions would lead to rapid, large‐scale reductions in the amount of polluted air people breathe, which leads to avoided future early deaths through at least the middle of the century. However, as the global population ages and becomes more sensitive to breathing polluted air, there will be an increasing need for policies that both reduce air pollution and improve public health. Key Points: Estimates of recent global air pollution exposure and associated premature deaths are sensitive to the choice of observation‐based data setThe benefits of reduced fossil fuel emissions for future global health remain relatively well‐constrained until late in the centuryUnder aggressive emissions reductions, avoided cumulative premature deaths could reach 124 million by 2100 [ABSTRACT FROM AUTHOR]

Little is known regarding the amount of hydrogen sulfide (H2S) emitted during refinery process under different management systems. Therefore, two refinery fields were investigated to explain their H2S emission, as they were managed using non-standardized and standardized protocols. In addition, three units of standardized refinery were investigated to correlate the amount of emitted H2S with oil quality. Both of non-standardized and standardized oil refineries emitted H2S, but the former contributed more; in fact, it was orders of magnitude higher. At non-standardized and standardized oil refineries, the highest concentration of H2S measured was 35.6 ± 2.4 and 2.6 ± 0.3 mg/m3, respectively, and the concentrations steadily declined with the distance from the refinery subunits until it was not detected at 550 and 130 m, respectively. In addition, refinery subunits: distillation tower, flare gas, and storage tank, emitted H2S, but the former was the dominant source. The crude oil quality affected H2S concentration in the air, the higher sulfur content the more H2S released. Furthermore, there was diurnal pattern of H2S concentrations, with higher H2S emitted during nighttime than the daytime. This study demonstrates that H2S emitted into atmosphere, and it most likely affects refinery workers health, surrounding area, and this can lead to further environmental consequences. [ABSTRACT FROM AUTHOR]

Average ambient concentrations of nitrogen dioxide (NO2), an important air pollutant, have declined in the United States since the enactment of the Clean Air Act. Despite evidence that NO2 disproportionately affects racial/ethnic minority groups, it remains unclear what drives the exposure disparities and how they have changed over time. Here, we provide evidence by integrating high-resolution (1 km × 1 km) ground-level NO2 estimates, sociodemographic information, and source-specific emission intensity and location for 217,740 block groups across the contiguous United States from 2000 to 2016. We show that racial/ethnic minorities are disproportionately exposed to higher levels of NO2 pollution compared with Whites across the United States and within major metropolitan areas. These inequities persisted over time and have worsened in many cases, despite a significant decrease in the national average NO2 concentration over the 17-y study period. Overall, traffic contributes the largest fraction of NO2 disparity. Contributions of other emission sources to exposure disparities vary by location. Our analyses offer insights into policies aimed at reducing air pollution exposure disparities among races/ethnicities and locations. [ABSTRACT FROM AUTHOR]

Background and objective: Studies linking early life exposure to air pollution and subsequent impaired lung health have focused on chronic, low-level exposures in urban settings. We aimed to determine whether in utero exposure to an acute, high-intensity air pollution episode impaired lung function 7-years later. Method: We conducted a prospective cohort study of children who lived in the vicinity of a coalmine fire. Respiratory function was measured using the forced oscillation technique (FOT). Z-scores for resistance at 5 Hz (R5), reactance at 5 Hz (X5) and area under the reactance curve (AX) were calculated. Two sets of analyses were conducted to address two separate questions: (1) whether mine fire exposure (a binary indicator; conceived after the mine fire vs in utero exposed) was associated with the respiratory Z-scores; (2) whether there was any dose–response relationship between fire-related PM2.5 exposure and respiratory outcomes among those exposed. Results: Acceptable lung function measurements were obtained from 79 children; 25 unexposed and 54 exposed in utero. Median (interquartile range) for daily average and peak PM2.5 for the exposed children were 4.2 (2.6 – 14.2) and 88 (52—225) µg/m3 respectively. There were no detectable differences in Z-scores between unexposed and exposed children. There were no associations between respiratory Z-scores and in utero exposure to PM2.5 (daily average or peak). Conclusion: There was no detectable effect of in utero exposure to PM2.5 from a local coalmine fire on post-natal lung function 7-years later. However, statistical power was limited. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 - March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory. Weekly variations of NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 24% at weekends in Riyadh, and high reductions are found near the city center and the areas along the highway. An average weekend reduction estimate of 30% in Madrid is found. The regions with dominant sources are located in the east of Madrid, where the residential areas and the Madrid-Barajas airport are located. Additionally, the NO2 emissions decreased by 21% in March-June 2020 compared to the same period in 2019 induced by the COVID-19 lockdowns in Riyadh. A much higher reduction (60%) is estimated for Madrid where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas and cover smaller areas during weekdays than at weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Though our analysis is limited to two cities as testing examples, the method has proved to provide reliable and consistent results. Therefore, it is expected to be suitable for other trace gases and other target regions. [ABSTRACT FROM AUTHOR]

Adverse health effects have been linked with exposure to livestock farms, likely due to airborne microbial agents. Accurate exposure assessment is crucial in epidemiological studies, however limited studies have modelled bioaerosols. This study used measured concentrations in air of livestock commensals (Escherichia coli (E. coli) and Staphylococcus species (spp.)), and antimicrobial resistance genes (tetW and mecA) at 61 residential sites in a livestock-dense region in the Netherlands. For each microbial agent, land use regression (LUR) and random forest (RF) models were developed using Geographic Information System (GIS)-derived livestock-related characteristics as predictors. The mean and standard deviation of annual average concentrations (gene copies/m3) of E. coli , Staphylococcus spp., tetW and mecA were as follows: 38.9 (±1.98), 2574 (±3.29), 20991 (±2.11), and 15.9 (±2.58). Validated through 10-fold cross-validation (CV), the models moderately explained spatial variation of all microbial agents. The best performing model per agent explained respectively 38.4%, 20.9%, 33.3% and 27.4% of the spatial variation of E. coli , Staphylococcus spp., tetW and mecA. RF models had somewhat better performance than LUR models. Livestock predictors related to poultry and pig farms dominated all models. To conclude, the models developed enable enhanced estimates of airborne livestock-related microbial exposure in future epidemiological studies. Consequently, this will provide valuable insights into the public health implications of exposure to specific microbial agents. [Display omitted] • Improving livestock exposure assessment is crucial for accurately assessing health risks. • Empirical spatial models effectively predict airborne microbial concentrations. • Random Forest models slightly outperform Land Use Regression models. • Variables related to poultry and pig farms are large contributors to the models. • Modelling residential exposure will benefit future epidemiological studies. [ABSTRACT FROM AUTHOR]

Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOX emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO2 pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO2 columns by day‐of‐the‐week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2‐m temperatures and NO2 column amounts and find that NO2 is larger on the hottest days (>32°C) as compared to warm days (26°C–32°C), which is in contrast to a general decrease in NO2 with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO2 data to annual surface‐level concentrations yields relatively strong correlation (R2 = 0.66). These new developments make TROPOMI NO2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations. Plain Language Summary: Nitrogen oxides are a group of air pollutants released after fossil fuel combustion. A constituent of nitrogen oxides, nitrogen dioxide (NO2), can be observed by satellite instruments due to its chemical properties. In this project, we average together images of NO2 pollution gathered by the Tropospheric Monitoring Instrument satellite instrument over the United States in order to better determine the spatial distribution of NO2 air pollution. We find that this newest satellite instrument can observe air pollution with unprecedented clarity, similar to how HDTV is an advancement over regular TV. For example, we quantify pollution near individual airports, shipping areas, and major interstates; previous satellite instruments were unable to quantify air pollution with this type of precision. We also average the satellite data over different intervals to better determine cycles of air pollution. We find that NO2 air pollution is 16% lower on Saturdays and 24% lower on Sundays. Additionally, we find that NO2 pollution is larger on the hottest summer days as compared to typical summer days. These developments demonstrate how this new satellite instrument can advantageous for policymakers and health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations Key Points: The high instrument sensitivity of Tropospheric Monitoring Instrument (TROPOMI) can measure NO2 pollution with unprecedented clarity compared to predecessor instrumentsWe can now quantify pollution hotspots within cities such as those related to airport/shipping operations and high traffic areasAnnual column NO2 observed by TROPOMI has good correlation (R2 = 0.66) with EPA surface observations without any surface‐to‐column conversion [ABSTRACT FROM AUTHOR]

Open municipal solid waste (MSW) combustion is a major emission source of particulate air pollution, polycyclic aromatic hydrocarbons, and more exotic hazardous organic pollutants including polychlorinated biphenyls and brominated flame retardants. However, the adverse impact of MSW combustion emission on health among the general population is unknown. Therefore, a cross-sectional study was conducted to explore the associations between potential exposure to MSW combustion-related air pollution and symptoms of adverse health effects among residents of a community adjacent to a large open landfill in Lagos, Nigeria. Using ordinal logistic regression and controlling for age, sex, and smoking, it was observed that residence for ≥ 11 years had increased odds (p < 0.05) of daily occurrence of tingling/numbness/whiteness of fingers (2.614), headaches (2.725), memory problems (2.869), tremor/cramps (2.748), and confusion (3.033) among other symptoms. These results indicate adverse health impacts of chronic exposure to MSW combustion emission. [ABSTRACT FROM AUTHOR]

The two-stage process of propensity score analysis (PSA) includes a design stage where propensity scores (PSs) are estimated and implemented to approximate a randomized experiment and an analysis stage where treatment effects are estimated conditional on the design. This article considers how uncertainty associated with the design stage impacts estimation of causal effects in the analysis stage. Such design uncertainty can derive from the fact that the PS itself is an estimated quantity, but also from other features of the design stage tied to choice of PS implementation. This article offers a procedure for obtaining the posterior distribution of causal effects after marginalizing over a distribution of design-stage outputs, lending a degree of formality to Bayesian methods for PSA that have gained attention in recent literature. Formulation of a probability distribution for the design-stage output depends on how the PS is implemented in the design stage, and propagation of uncertainty into causal estimates depends on how the treatment effect is estimated in the analysis stage. We explore these differences within a sample of commonly used PS implementations (quantile stratification, nearest-neighbor matching, caliper matching, inverse probability of treatment weighting, and doubly robust estimation) and investigate in a simulation study the impact of statistician choice in PS model and implementation on the degree of between- and within-design variability in the estimated treatment effect. The methods are then deployed in an investigation of the association between levels of fine particulate air pollution and elevated exposure to emissions from coal-fired power plants. [ABSTRACT FROM AUTHOR]

Bicycle is not only a sustainable mode of transport but also health benefits of bicycling due to increased physical activities are well cited. However, in urban agglomerations, on-road air pollution exposure to cyclists/pedestrians is a matter of concern which is understudied. This study proposes an approach to calculate the on-road air pollution exposure for drivers of different vehicles in an agent-based simulation framework. In the proposed approach, the breathing rate of different drivers, penetration rate, vehicleoccupancy and background concentration are taken into consideration. The approach is applied to a real-world scenario of Patna, India where non-motorized modes are in abundance. A comparison of total inhaled mass per trip for drivers of different vehicles is made and it is found that cyclists are most exposed user group. An analysis for various background concentrations for different days of the year shows that the contribution of the background concentration has a major effect on the air pollution exposure level. The outcome is spatially analyzed to identify the locations of most affected user groups mapped to their home locations. Further, the on-road air pollution exposure of business-as-usual scenario is compared with a policy case and it is found that a dedicated bicycle track can increase the exposure per trip to cyclists by 40%. [ABSTRACT FROM AUTHOR]

Background/aim: Industrial-scale animal feeding operations (AFOs) have adverse impacts on regional air quality. Air emissions include endotoxins and other pro-inflammatory components, and exposure may cause airway inflammation and respiratory effects in susceptible individuals residing nearby. We aimed to develop and validate metrics for estimating time-varying exposure to AFO air pollution in surrounding communities and, secondly, to determine whether exposure is associated with health effects in children with asthma.Methods: We conducted a longitudinal panel study of N = 58 children with asthma in an agricultural region of Washington State with a high density of dairy AFOs. Children were followed for up to 26 months with repeated measures of respiratory health (N = 2023 interviews; N = 3853 lung function measurements); urine was collected in a subcohort (N = 16) at six-day intervals over three months and analyzed for leukotriene E4 (LTE4), a biomarker of systemic inflammation (N = 138 measurements). We developed an approach to estimate daily exposure to AFO airborne emissions based on distance to AFOs, AFO size, and daily wind speed and direction, and validated the estimates against direct measurements of ammonia, a chemical marker of AFO emissions, measured biweekly at 18 sites across the region for 14 months. Short-term relationships between AFO pollutant exposure and outcomes were assessed using regression models accounting for within-participant correlation and several potential confounders.Results: Estimates of daily AFO air pollution correlated moderately well with outdoor ammonia measurements (N = 842; r = 0.62). Forced expiratory volume in 1 s (FEV1) as percent of predicted was 2.0% (95% CI: 0.5, 3.5) lower with each interquartile increase in previous day exposure, but no associations with asthma symptoms were observed. There was suggestive evidence that LTE4 concentrations were higher following days of elevated exposure to AFO emissions (p = 0.06).Conclusions: A simple metric of time-varying exposure to AFO emissions was correlated with daily outdoor ammonia levels. Children with asthma may be adversely affected by exposure to AFO emissions. [ABSTRACT FROM AUTHOR]

Evidence on the public health relevance of exposure to livestock farm emissions is increasing. Research mostly focused on chemical air pollution, less on microbial exposure, while endotoxins are suggested relevant bacterial components in farm emissions. Acute respiratory health effects of short-term exposure to livestock-related air pollution has been shown for NH 3 and PM 10 , but has not yet been studied for endotoxin. We aimed to assess associations between lung function and short-term exposure to livestock farming emitted endotoxin in co-pollutant models with NH 3 and PM 10. In 2014/2015, spirometry was conducted in 2308 non-farming residents living in a rural area in the Netherlands. Residential exposure to livestock farming emitted endotoxin during the week prior to spirometry was estimated by dispersion modelling. The model was applied to geo-located individual barns within 10 km of each home address using provincial farm data and local hourly meteorological conditions. Regional week-average measured concentrations of NH 3 and PM 10 were obtained through monitoring stations. Lung function parameters (FEV 1 , FVC, FEV 1 /FVC, MMEF) were expressed in %-predicted value based on GLI-2012. Exposure-response analyses were performed by linear regression modelling. Week-average endotoxin exposure was negatively associated with FVC, independently from regional NH 3 and PM 10 exposure. A 1.1% decline in FVC was estimated for an increase of endotoxin exposure from 10th to 90th percentile. Stratified analyses showed a larger decline (3.2%) for participants with current asthma and/or COPD. FEV 1 was negatively associated with week-average endotoxin exposure, but less consistent after co-pollutant adjustment. FEV 1 /FVC and MMEF were not associated with week-average endotoxin exposure. Lower lung function in non-farming residents was observed in relation to short-term residential exposure to livestock farming emitted endotoxin. This study indicates the probable relevance of exposure to microbial emissions from livestock farms considering public health besides chemical air pollution, necessitating future research incorporating both. • The impact of livestock farm emissions on public health is understudied. • Our study pioneers in assessing short-term residential exposure to endotoxin. • Novel application of dispersion modelling on farms' emissions showed useful. • We found lower lung function in non-farming residents after higher exposure. • Probable health relevance of endotoxin was substantiated by co-pollutant adjustment. [ABSTRACT FROM AUTHOR]

• A 16-year update on the first UK environmental justice air quality study is given. • Emissions for private vehicles are attributed to census area of registered keeper. • Social inequalities in traffic-related pollution exposure are clearer and stronger. • Young children, adults, and households in poverty have highest levels of exposure. • A strong inverse relationship was found between poverty and emissions generation. This paper presents unique spatial analyses identifying substantial discrepancies in traffic-related emissions generation and exposure by socioeconomic and demographic groups. It demonstrates a compelling environmental and social injustice narrative with strong policy implications for the UK and beyond. In the first instance, this research presents a decadal update for England and Wales to Mitchell and Dorling's 2003 analysis of environmental justice in the UK. Using 2011 UK Government pollution and emissions data with 2011 UK Census socioeconomic and demographic data based on small area census geographies, this paper demonstrates a stronger relationship between age, poverty, road NO x emissions and exposure to NO 2 concentrations. Areas with the highest proportions of under-fives and young adults, and poorer households, have the highest concentrations of traffic-related pollution. In addition, exclusive access to UK annual vehicle safety inspection records ('MOT' tests) allowed annual private vehicle NO x emissions to be spatially attributed to registered keepers. Areal analysis against Census-based socioeconomic characteristics identified that households in the poorest areas emit the least NO x and PM, whilst the least poor areas emitted the highest, per km, vehicle emissions per household through having higher vehicle ownership, owning more diesel vehicles and driving further. In conclusion, the analysis indicates that, despite more than a decade of air quality policy, environmental injustice of air pollution exposure has worsened. New evidence regarding the responsibility for generation of road traffic emissions provides a clear focus for policy development and targeted implementation. [ABSTRACT FROM AUTHOR]

The paper simulates the spatial variations in the sources of, and exposure to, traffic-related PM10 emissions for the city of Vienna, Austria. Using an extended and calibrated MATSim micro-simulation model, we reproduce agent-level mobility patterns for a representative day. Street-level PM10 emissions, mostly from cars, are extrapolated for the entire city to estimate concentration and exposure levels at hourly intervals. We show that exposure levels exceed the recommended 50 μ g/m 3 threshold between peak travel hours at home, education, and work locations. Among different socioeconomic status (SES) groups, urban, single, 15 years and younger, and those living near the city center face high exposure levels, while car users, that cause a majority of the emissions, are relatively less exposed. Finally, we show that Shared Autonomous Electric Vehicles (SAEVs) reduce PM10 emissions, but the benefits are not homogeneously distributed across the different SES groups. [ABSTRACT FROM AUTHOR]

Abstract In 2008, Utah launched a reform of working time for which workers in treated public agencies were allowed to compress workweek from 5 to 4 days, by extending working hours from 8 to 10 per day. This paper estimates the impact of the initiative on the consumption of fuel and on the production of CO2 by public fleets. By assembling a new dataset on 43 public agencies and by adopting a difference-in-difference framework, a contraction in the consumption of fuel by 2% and a 14% decrease in the generation of CO2 was found. Highlights • Estimation of the impact of public work schedule on the consumption of fuel and on the production of CO2 by public fleets. • Analysis of a US-based program of workweek compression. • Contraction in the consumption of fuel by 2% and a 14% decrease in the generation of CO2. [ABSTRACT FROM AUTHOR]

Vehicles play an important role in modern life; however, they also generate hazards. Occupational exposed subjects are in long-term contact with harmful products, which sets these professionals in a susceptible group to air pollutant damage. The aims of this study were to quantify individual exposure to pollutant gases and chemical elements and to evaluate oxidative and genetic damage in professional motorcyclists and office workers. We recruited professional motorcyclists and office workers from Porto Alegre, Brazil, between January and December 2016. Individual exposure to air pollutants was assessed by passive monitoring. Fingernail trace elements were determined by using inductively coupled plasma mass spectrometry. Oxidative stress biomarkers were quantified spectrophotometrically, and genotoxicity was evaluated by micronuclei assay. Individual exposure to NO2 and O3, trace element content (Sb, Pt, As, Cd, V, Mn, and Co), oxidative stress factors, and genetic damage were statistically higher in professional motorcyclists (p < 0.05). Moreover, NO2 and O3 levels showed very strong positive correlation with plasmatic lipid peroxidation (p < 0.001 and r = 0.8849 and 0.8995) and strong positive correlation with micronuclei frequency (p < 0.001 and r = 0.7683 and 0.7280). Results suggest that professional motorcyclists are at high risk due to long-term air pollution exposure, which implies in the onset of several harmful effects and worsening of pre-existent diseases. [ABSTRACT FROM AUTHOR]

Copyright of Archives of Environmental Protection is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a new approach to iteratively calculate local air pollution exposure tolls in large-scale urban settings by taking the exposure times and locations of individuals into consideration. It explicitly avoids detailed air pollution concentration calculations and is therefore characterized by little data requirements, reasonable computation times for iterative calculations, and open-source compatibility. In a first step, the paper shows how to derive time-dependent vehicle-specific exposure tolls in an agent-based model. It closes the circle from the polluting entity, to the receiving entity, to damage costs, to tolls, and back to the behavioral change of the polluting entity. In a second step, the approach is applied to a large-scale real-world scenario of the Munich metropolitan area in Germany. Changes in emission levels, exposure costs, and user benefits are calculated. These figures are compared to a flat emission toll, and to a regulatory measure (a speed reduction in the inner city), respectively. The results indicate that the flat emission toll reduces overall emissions more significantly than the exposure toll, but its exposure cost reductions are rather small. For the exposure toll, overall emissions in crease for freight traffic which implies a potential conflict between pricing schemes to optimize local emission exposure and others to abate climate change. Regarding the mitigation of exposure costs caused by urban travelers, the regulatory measure is found to be an effective strategy, but it implies losses in user benefits. [ABSTRACT FROM AUTHOR]

Objective To assess the relationship between fine particulate matter (PM2.5) concentration and ischaemic heart disease (IHD) morbidity and mortality. Methods A time-series study conducted in Beijing from 1 January 2010 to 31 December 2012. Data on 369469 IHD cases and 53247 IHD deaths were collected by the Beijing Monitoring System for Cardiovascular Diseases, which covers all hospital admissions and deaths from IHD from Beijing's population of 19.61 million. Results The mean daily PM2.5 concentration was 96.2 μg/m³ with a range from 3.9 to 493.9 μg/m³. Only 15.3% of the daily PM2.5 concentrations achieved WHO Air Quality Guidelines target (25 μg/m³) in the study period. The dose-response relationships between PM2.5 and IHD morbidity and mortality were non-linear, with a steeper dose-response function at lower concentrations and a shallower response at higher concentrations. A 10 μg/m³ increase in PM2.5 was associated with a 0.27% (95% CI 0.21 to 0.33%, p<2.00×10-16) increase in IHD morbidity and a 0.25% (95% CI 0.10 to 0.40%, p=1.15×10-3) increase in mortality on the same day. During the 3 years, there were 7703 cases and 1475 deaths advanced by PM2.5 pollution over expected rates if daily levels had not exceeded the WHO target. Conclusions PM2.5 concentration was significantly associated with IHD morbidity and mortality in Beijing. Our findings provide a rationale for the urgent need for stringent control of air pollution to reduce PM2.5 concentration. [ABSTRACT FROM AUTHOR]

Air pollution is a significant cause of cardiovascular morbidity and mortality worldwide. Although the epidemiologic association between air pollution exposures and exacerbation of cardiovascular disease (CVD) is well established, the mechanisms by which these exposures promote CVD are incompletely understood. This review provides an overview of the components of air pollution, an overview of the cardiovascular effects of air pollution exposure, and a review of the basic mechanisms that are activated by exposure to promote CVD. [ABSTRACT FROM AUTHOR]

Air pollution remains one of the major health threats around the world. Compared to adults, foetuses and infants are more vulnerable to the effects of environmental toxins. Maternal exposure to air pollution causes several adverse birth outcomes and may lead to life-long health consequences. Given that a healthy intrauterine environment is a critical factor for supporting normal foetal brain development, there is a need to understand how prenatal exposure to air pollution affects brain health and results in neurological dysfunction. This review summarised the current knowledge on the adverse effects of prenatal air pollution exposure on early life neurodevelopment and subsequent impairment of cognition and behaviour in childhood, as well as the potential of early-onset neurodegeneration. While inflammation, oxidative stress, and endoplasmic reticulum are closely involved in the physiological response, sex differences also occur. In general, males are more susceptible than females to the adverse effect of in-utero air pollution exposure. Considering the evidence provided in this review and the rising concerns of global air pollution, any efforts to reduce pollutant emission or exposure will be protective for the next generation. [Display omitted] • Prenatal exposure to air pollution impacts foetal brain development and cognition. • Males have a greater susceptibility to prenatal air pollution exposure than females. • Oxidative stress, ER stress and neuroinflammation interactions lead to abnormal brain functions. [ABSTRACT FROM AUTHOR]

Air pollution has been an increasing concern within the Kingdom of Saudi Arabia and other Middle Eastern countries. In this work the authors present an analysis of daily ozone (O3), nitrogen oxide (NOx), and particulate matter (<10 μm aerodynamic diameter; PM10) concentrations for two years (2010 and 2011) at sites in and around the coastal city of Jeddah, as well as a remote background site for comparison. Monthly and weekly variations, along with their implications and consequences, were also examined. O3within Jeddah was remarkably low, and exhibited the so-called weekend effect—elevated O3levels on the weekends, despite reduced emissions of O3precursors on those days. Weekend O3increases averaged between 12% and 14% in the city, suggesting that NOx/volatile organic compound (VOC) ratios within cities such as Jeddah may be exceptionally high. Sites upwind or far removed from Jeddah did not display this weekend effect. Based on these results, emission control strategies in and around Jeddah must carefully address NOx/VOC ratios so as to reduce O3at downwind locations without increasing it within urban locations themselves. PM10concentrations within Jeddah were elevated compared with North American cites of similar climatology, though comparable to other large cities within the Middle East.Implications:Daily concentrations of O3, PM10, and NOx in and around the city of Jeddah, Saudi Arabia, are analyzed and compared with those of other reference cities. Extremely low O3 levels, along with a significant urban weekend effect (higher weekend O3, despite reduced NOx concentrations), is apparent, along with high levels of PM10 within the city. Urban O3 in Jeddah was found to be lower than that of other comparable cities, but the strong weekend effect suggests that care must be taken to reduce downwind O3 levels without increasing them within the city itself. Further research into the emissions and chemistry contributing to the reduced O3 levels within the city is warranted. [ABSTRACT FROM AUTHOR]

Human exposures to criteria and hazardous air pollutants (HAPs) in urban areas vary greatly due to temporal-spatial variations in emissions, changing meteorology, varying proximity to sources, as well as due to building, vehicle, and other environmental characteristics that influence the amounts of ambient pollutants that penetrate or infiltrate into these microenvironments. Consequently, the exposure estimates derived from central-site ambient measurements are uncertain and tend to underestimate actual exposures. The Exposure Classification Project (ECP) was conducted to measure pollutant concentrations for common urban microenvironments (MEs) for use in evaluating the results of regulatory human exposure models. Nearly 500 sets of measurements were made in three Los Angeles County communities during fall 2008, winter 2009, and summer 2009. MEs included in-vehicle, near-road, outdoor, and indoor locations accessible to the general public. Contemporaneous 1- to 15-min average personal breathing zone concentrations of carbon monoxide (CO), carbon dioxide (CO2), volatile organic compounds (VOCs), nitric oxide (NO), nitrogen oxides (NOx), particulate matter (<2.5 μm diameter; PM2.5) mass, ultrafine particle (UFP; <100 nm diameter) number, black carbon (BC), speciated HAPs (e.g., benzene, toluene, ethylbenzene, xylenes [BTEX], 1,3-butadiene), and ozone (O3) were measured continuously. In-vehicle and inside/outside measurements were made in various passenger vehicle types and in public buildings to estimate penetration or infiltration factors. A large fraction of the observed pollutant concentrations for on-road MEs, especially near diesel trucks, was unrelated to ambient measurements at nearby monitors. Comparisons of ME concentrations estimated using the median ME/ambient ratio versus regression slopes and intercepts indicate that the regression approach may be more accurate for on-road MEs. Ranges in the ME/ambient ratios among ME categories were generally greater than differences among the three communities for the same ME category, suggesting that the ME proximity factors may be more broadly applicable to urban MEs.Implications:Estimates of population exposure to air pollutants extrapolated from ambient measurements at ambient fixed site monitors or exposure surrogates are prone to uncertainty. This study measured concentrations of mobile source air toxics (MSAT) and related criteria pollutants within in-vehicle, outdoor near-road, and indoor urban MEs to provide multipollutant ME measurements that can be used to calibrate regulatory exposure models. [ABSTRACT FROM AUTHOR]

This paper evaluates the exposure of four children to carbon monoxide (CO) in two different classrooms during the time spent in school in a typical school day, using a numerical modelling approach. The study is focused on an area of 550 × 550 m² centred at a primary school of the city of Aveiro, in central Portugal, which is located close to a road with moderate traffic and has naturally ventilated rooms. Air quality data were measured in the school yard. Traffic emissions were estimated with TREM model, using traffic counts data. Simulations of CO concentrations in the study domain were performed with the computational fluid dynamics model VADIS, considering the influence of buildings and trees over the dispersion. Indoor concentrations were simulated using a mass transfer approach. Results show that the individual exposure of children is spatially dependent, as a consequence of the wind flow and air pollutant dispersion patterns. [ABSTRACT FROM AUTHOR]

Coal-fired energy generation is the backbone of India's power sector and considered a driver of its economic development. However, it is associated with detrimental environmental and health impacts in India and its fleet is currently struggling with overcapacity and inefficiency problems. One solution to address these challenges is the early retirement of some of India's coal-fired power plants. In this paper, we introduce multidimensional indices that identify plants for retirement based on comprehensive criteria that include technical and economic characteristics of plants as well as their environmental impacts. We implement an ensemble approach, where we formulate 8008 indices based on all possible combination of seven relevant parameters and rank plants accordingly. This approach facilitates a comprehensive analysis of the plants' performance on different parameters and provides a new outlook on plant retirements that differs from the common approach of retiring plants based solely on technical characteristics such as age, capacity, and heat rate. Our results show that top plants recommended for early retirement are typically 7 years older, 13% more expensive and have around 40% higher population exposure to emissions compared to an average plant in India. We estimate the potential costs saved from the retirement of the worst-performing 50 GW of generating capacity to be $21 billion resulting from shifting ownership towards a cheaper cost of capital and replacing coal by more competitive sources such as solar power. • Identify plants for early retirement based on technical, economic and environmental indicators. • Worst performing 50 GW capacity are older, more expensive to operate and have higher population exposure. • Costs saved from retiring 50 GW capacity and replacing them with solar are $21 billion. • A multidimensional approach is essential for a politically feasible phaseout of coal. [ABSTRACT FROM AUTHOR]

We have developed an integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain, to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors, which can be used to support policymaking with respect to emission control. Central for the system is a newly developed tagging method capable of calculating the contribution from a specific emission source or sector to the overall air pollution levels, taking into account the non-linear atmospheric chemistry. The main objective of this work is to identify the anthropogenic emission sources in Europe and Denmark that contribute the most to human health impacts. In this study, we applied the EVA system to Europe and Denmark, with a detailed analysis of health-related external costs from the ten major emission sectors and their relative contributions. The paper contains a thorough description of the EVA system, the main results from the assessment of the main contributors and a discussion of the most important atmospheric chemical reactions relevant for interpreting the results. The main conclusion from the analysis is that the major contributors to health-related external costs are major power production, agriculture, road traffic, and nonindustrial domestic combustion, including wood combustion. We conclude that when regulating the emissions of ammonia from the agricultural sector, both the impacts on nature and on human health should be taken into account. This study confirms that air pollution constitutes a serious problem for human health and that the related external costs are considerable. The results in this work emphasize the importance of defining the right questions in the decision-making process. The results from assessing the impacts from each emission sector depend clearly on the assumption that the other emission sectors are not changed, especially emissions changing concentrations of atmospheric OH and therefore lifetimes of other chemical species. [ABSTRACT FROM AUTHOR]

An accurate description of emissions is crucial for model simulations to reproduce and interpret observed phenomena over extended time periods. In this study, we used an approach based on activity data to develop a consistent series of spatially resolved emissions in the United States from 1990 to 2010. The state-level anthropogenic emissions of SO2, NOx, CO, NMVOC (non-methane volatile organic compounds), NH3, PM10 and PM2.5 for a total of 49 sectors were estimated based on several long-term databases containing information about activities and emission controls. Activity data for energy-related stationary sources were derived from the State Energy Data System. Corresponding emission factors reflecting implemented emission controls were calculated back from the National Emissions Inventory (NEI) for seven years (i.e., 1990, 1995, 1996, 1999, 2001, 2002 and 2005), and constrained by the AP-42 (US EPA's Compilation of Air Pollutant Emissions Factors) dataset. Activity data for mobile sources including different types of highway vehicles and non-highway equipment were obtained from highway statistics reported by the Federal Highway Administration. The trends in emission factors for highway mobile source were informed by the 2011 National Transportation Statistics. Emissions for all non-energy-related sources were either scaled by the growth ratio of activity indicators or adjusted based on the NEI trends report. Because of the strengthened control efforts, particularly for the power sector and mobile sources, emissions of all pollutants except NH3 were reduced by half over the last two decades. The emission trends developed in this study are comparable with the NEI trend report and EDGAR (Emissions Database for Global Atmospheric Research) data, but better constrained by trends in activity data. Reductions in SO2, NOx, CO and EC (speciation of PM2.5 by SMOKE, Sparse Matrix Operator Kernel Emissions) emissions agree well with the observed changes in ambient SO2, NO2, CO and EC concentrations, suggesting that the various controls on emissions implemented over the last two decades are well represented in the emission inventories developed in this study. These inventories were processed by SMOKE and are now ready to be used for regional chemistry transport model simulations over the 1990-2010 period. [ABSTRACT FROM AUTHOR]

Background: Studies concerning welding fume-related adverse health effects in welders are hampered by the heterogeneity of workplace situations, resulting in complex and non-standardized exposure conditions. Methods: In order to carry out welding fume exposure studies under controlled and standardized conditions, the Aachen Workplace Simulation Laboratory was developed. This laboratory consists of an emission room, in which welding fume is produced, and an exposure room in which human subjects are exposed to these fumes. Both rooms are connected by a ventilation system which allows the welding fume concentration to be regulated. Particle mass concentration was measured with a TEOM microbalance and the particle number-size distribution using a Grimm SMPS device. Results: In a study, which is the subject of this paper, it has been shown that welding fume concentration can easily be regulated between 1 and about 3 mg m. The chosen concentration can be kept constant for more than 8 h. However, transport of the particles from the emission room into the exposure room leads to a change in particle size distribution, which is probably due to coagulation of the fraction of smallest particles. Conclusion: The Aachen Workplace Simulation Laboratory is suitable for controlled exposure studies with human subjects. [ABSTRACT FROM AUTHOR]

The concentration fluctuations of a dispersing hazardous gaseous pollutant in the atmospheric boundary layer, and the hazard associated with short-term concentration levels, demonstrate the necessity of estimating the magnitude of these fluctuations using predicting models. To predict and estimate the maximum expected dosage and the exposure time within which the dosage exceeds certain health limits, the knowledge of the behaviour of concentration fluctuations at the point under consideration is needed. The whole effort is based on the field experiment MUST (Biltoft, 2001) and the computational simulations have been performed with the CFD code ADREA. [ABSTRACT FROM AUTHOR]

The article reports on the use of the integrated horizontal flux (IHF) method for determining airborne emissions from agricultural fumigants. It examines factors and field study design issues for the use of the IHF method. It also presents the results of characterizing the uncertainty in the emission fitting for the IHF method. It is said that a challenge in terms of characterizing atmospheric flux as a function of time is being posed by ground-level area sources. To conduct a cost-effective research, the optimization of field study design is therefore necessary.

Context: Prolonged exposure to ambient particles is associated with premature mortality due to cardio-respiratory diseases and lung cancer. The size and composition of these particles determine their toxicity, which is aggravated by their long-term retention in the lungs. Objective: To compare the elemental profile of particles retained along the bronchial tree and lymph nodes by combining laser capture microdissection (LCM) and elemental composition analysis through energy dispersive x-ray (EDX) and scanning electron microscopy (SEM). Material and methods: Twenty-four right lung middle lobes from autopsied cases were obtained from two cities with different pollution backgrounds. Lung samples were collected from three distinct sites within the lung at the time of autopsy: peribronchial tissue, peripheral parenchyma and hilar lymph nodes. Areas of potentially increased particle deposition were microdissected using LCM and analyzed for elemental composition through EDX ''allied'' with SEM. Results: Elemental analyses of the particles retained along the bronchial tree showed two groups of distribution: peribronchiolar or lymph node deposition. The elemental profile of peribronchial areas were significantly different between the two cities and were better discriminators of past air pollution exposure. Conclusion: Our data suggest that particle uptake varies along the bronchial tree and human lung tissue retains particles indicative of regional air pollution background. [ABSTRACT FROM AUTHOR]

To simulate the atmospheric fate of air pollutants, it is first necessary to know the emission rates that describe the release of pollutants into ambient air. For benzo(a)pyrene emission data are currently only available as yearly bulk emissions while the simulation models typically require temporally resolved emissions (e.g. hourly). Because residential heating is by far the most important source for benzo(a)pyrene, we developed a method to temporally disaggregate these bulk emission data using the linear dependency of benzo(a)pyrene emission rates stemming from residential combustion on ambient temperature. The resulting time-dependent hourly emission rates have been used in a chemical transport model to simulate concentrations and deposition fluxes of benzo(a)pyrene in the year 2000. The same simulations were repeated with constant emission rates and emission rates that varied only seasonally. By comparing the modeling results of the three emission cases with monthly measurements of air concentrations, the characteristic and the benefit of our disaggregation approach is illustrated. The simulations with disaggregated emissions fitted best to the measurements. At the same time the spatial distribution as well as the yearly total deposition was notably different with each emission case even though the yearly total emissions were kept constant. [ABSTRACT FROM AUTHOR]

The concentrations of seven heavy metals (Cd, Cr, Cu, Fe, Mn, Ni, and Pb) associated with PM10 and PM2.5 at the crossroads and the background sites have been studied in Zabrze, Poland, during smog episodes. Although the background level was unusually elevated due to both high particulate emission from the industrial and municipal sources and smog favorable meteorological conditions, significant increase of the concentration of PM2.5 and PM10 as well as associated heavy metals in the roadside air compared to the urban background has been documented. The average daily difference between the roadside and corresponding urban background aerosol concentration was equal to 39.5 μg m − 3 for PM10 and 41.2 μg m − 3 for PM2.5. The highest levels of the studied metals in Zabrze appeared for iron carried by PM10 particles: 1,706 (background) and 28,557 ng m − 3 (crossroads). The lowest concentration level (in PM10) has been found for cadmium: 7 and 77 ng m − 3 in the background and crossroads site, respectively. Also the concentrations of heavy metals carried by the fine particles (PM2.5) were very high in Zabrze during the smog episodes. Concentrations of all studied metals associated with PM10 increased at the roadside compared to the background about ten times (one order) while metals contained in PM2.5 showed two to three times elevated concentrations (except Fe—five times and Cr—no increase). [ABSTRACT FROM AUTHOR]

Background: Traffic-related air pollution has been associated with adverse cardiorespiratory effects, including increased asthma prevalence. However, there has been little study of effects of traffic exposure at school on new-onset asthma. Objectives: We evaluated the relationship of new-onset asthma with traffic-related pollution near homes and schools. Methods: Parent-reported physician diagnosis of new-onset asthma (n = 120) was identified during 3 years of follow-up of a cohort of 2,497 kindergarten and first-grade children who were asthmaand wheezing-free at study entry into the Southern California Children's Health Study. We assessed traffic-related pollution exposure based on a line source dispersion model of traffic volume, distance from home and school, and local meteorology. Regional ambient ozone, nitrogen dioxide (NO2), and particulate matter were measured continuously at one central site monitor in each of 13 study communities. Hazard ratios (HRs) for new-onset asthma were scaled to the range of ambient central site pollutants and to the residential interquartile range for each traffic exposure metric. Results: Asthma risk increased with modeled traffic-related pollution exposure from roadways nearhomes [HR 1.51; 95% confidence interval (CI), 1.25-1.82] and near schools (HR 1.45; 95% CI, 1.06-1.98). Ambient NO2 measured at a central site in each community was also associated with increased risk (HR 2.18; 95% CI, 1.18-4.01). In models with both NO2 and modeled traffic exposures, there were independent associations of asthma with traffic-related pollution at school and home, whereas the estimate for NO2 was attenuated (HR 1.37; 95% CI, 0.69-2.71). Conclusions: Traffic-related pollution exposure at school and homes may both contribute to the development of asthma. [ABSTRACT FROM AUTHOR]

Background: Emerging evidence suggests that the systemic vasculature may be a target of inhaled pollutants of vehicular origin. We have identified several murine markers of vascular toxicity that appear sensitive to inhalation exposures to combustion emissions. Objective: We sought to examine the relative impact of various pollutant atmospheres and specific individual components on these markers of altered vascular transcription and lipid peroxidation. Methods: Apolipoprotein E knockout (ApoE-/-) mice were exposed to whole combustion emissions (gasoline, diesel, coal, hardwood), biogenically derived secondary organic aerosols (SOAs), or prominent combustion-source gases [nitric oxide (NO), NO2, carbon monoxide (CO)] for 6 hr/day for 7 days. Aortas were assayed for transcriptional alterations of endothelin-1 (ET-1), matrix metalloproteinase- 9 (MMP-9), tissue inhibitor of metalloproteinase-2 (TIMP-2), and heme oxygenase-1 (HO-1), along with measures of vascular lipid peroxides (LPOs) and gelatinase activity. Results: We noted transcriptional alterations with exposures to gasoline and diesel emissions. Interestingly, ET-1 and MMP-9 transcriptional effects could be recreated by exposure to CO and NO, but not NO2 or SOAs. Gelatinase activity aligned with levels of volatile hydrocarbons and also monoxide gases. Neither gases nor particles induced vascular LPO despite potent effects from whole vehicular emissions. Conclusions: In this head-to-head comparison of the effects of several pollutants and pollutant mixtures, we found an important contribution to vascular toxicity from readily bioavailable monoxide gases and possibly from volatile hydrocarbons. These data support a role for traffic-related pollutants in driving cardiopulmonary morbidity and mortality. [ABSTRACT FROM AUTHOR]

A natural emissions inventory for the continental United States and surrounding territories is needed in order to use the US Environmental Protection Agency Community Multiscale Air Quality (CMAQ) Model for simulating natural air quality. The CMAQ air modeling system (including the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions processing system) currently estimates non-methane volatile organic compound (NMVOC) emissions from biogenic sources, nitrogen oxide (NOx) emissions from soils, ammonia from animals, several types of particulate and reactive gas emissions from fires, as well as sea salt emissions. However, there are several emission categories that are not commonly treated by the standard CMAQ Model system. Most notable among these are nitrogen oxide emissions from lightning, reduced sulfur emissions from oceans, geothermal features and other continental sources, windblown dust particulate, and reactive chlorine gas emissions linked with sea salt chloride. A review of past emissions modeling work and existing global emissions data bases provides information and data necessary for preparing a more complete natural emissions data base for CMAQ applications. A model-ready natural emissions data base is developed to complement the anthropogenic emissions inventory used by the VISTAS Regional Planning Organization in its work analyzing regional haze based on the year 2002. This new data base covers a modeling domain that includes the continental United States plus large portions of Canada, Mexico and surrounding oceans. Comparing July 2002 source data reveals that natural emissions account for 16% of total gaseous sulfur (sulfur dioxide, dimethylsulfide and hydrogen sulfide), 44% of total NOx, 80% of reactive carbonaceous gases (NMVOCs and carbon monoxide), 28% of ammonia, 96% of total chlorine (hydrochloric acid, nitryl chloride and sea salt chloride), and 84% of fine particles (i.e., those smaller than 2.5 μm in size) released into the atmosphere. The seasonality and relative importance of the various natural emissions categories are described. [ABSTRACT FROM AUTHOR]

Abstract: A GIS-based moving window approach was developed as a means for generating high resolution air pollution maps over large geographic areas. The approach is demonstrated by modelling annual mean NO2 pollution for the EU-15 (excluding Sweden) at the 1km level on the basis of emissions and meteorological data. Models were developed using monitoring data from 714 background NO2 sites for 2001 and validated by comparing predicted with observed NO2 concentrations for a reserved set of 228 background sites. First the emission map (NO x ) was derived by disaggregating national emissions estimates, categorised by source, to a 1km grid, using proxies including population and road density, traffic statistics and land cover. A set of annuli was then constructed, of varying radii, and these passed over the emissions grid to derive a calibration between measured annual average concentrations at each monitoring site and distance-weighted emissions in the surrounding area, using a focalsum function. The resulting model was then used to predict concentrations at the reserved set of validation sites, and measures of performance (R 2, RMSE and fractional bias) obtained. Validation gave R 2 =0.61, RMSE=6.59 and FB=−0.01, and indicated performance equivalent to universal kriging and better than ordinary kriging and land use regression. [Copyright &y& Elsevier]

Gridded air pollutant emission inventories are prerequisites for using air quality models to assess air pollution control strategies and predict air quality. A precise gridded emission inventory will help improve the accuracy of air quality simulation. Mobile source emissions are one of the major contributors to volatile organic compound (VOC) and nitrogen oxide (NOx) pollutants, the precursors of ozone formation. However, because of the complexity of road networks and variations in traffic flows at different road types and locations, spatial allocation of emissions from mobile sources into grid cells is challenging. This paper proposes a new methodological framework, named as "the road-network-based approach," for spatially allocating regional mobile source emission inventories. The new approach utilizes the Geographic Information System (GIS)-based road network information and road-types-based traffic flow data to provide spatial surrogates for allocating Pearl River Delta (PRD) regional mobile source emission inventories. The results show that the new approach provides reasonable spatial distributions of mobile source emissions, and the distributions are in good agreement with PRD regional on-road emission line sources. Comparisons between using the populationbased and the new road-network-based approaches are made. The air quality modeling results indicate that the new approach can obviously improve model predictions with increasing accuracy in mobile source emission allocations. Means of choosing appropriate approaches for spatially allocating regional mobile source emissions are discussed. [ABSTRACT FROM AUTHOR]