Search

Exposure to ambient air pollution may affect cognitive functioning and development in children. Unfortunately, there is little evidence available for low- and middle-income countries (LMICs), where air pollution levels are highest. We analysed the association between exposure to ambient fine particulate matter (≤2.5 μm [PM 2.5 ]) and cognitive development indicators in a cross-sectional analysis of children (aged 3–4 years) in 12 LMICs. We linked Demographic and Health Survey data, conducted between 2011 and 2018, with global estimates of PM 2.5 mass concentrations to examine annual average exposure to PM 2.5 and cognitive development (literacy-numeracy and learning domains) in children. Cognitive development was assessed using the United Nations Children's Fund's early child development indicators administered to each child's mother. We used multivariable logistic regression models, adjusted for individual- and area-level covariates, and multi-pollutant models (including nitrogen dioxide and surface-level ozone). We assessed if sex and urban/rural status modified the association of PM 2.5 with the outcome. We included 57,647 children, of whom, 9613 (13.3%) had indicators of cognitive delay. In the adjusted model, a 5 μg/m3 increase in annual all composition PM 2.5 was associated with greater odds of cognitive delay (OR = 1.17; 95% CI: 1.13, 1.22). A 5 μg/m3 increase in anthropogenic PM 2.5 was also associated with greater odds of cognitive delay (OR = 1.05; 95% CI: 1.00, 1.10). These results were robust to several sensitivity analyses, including multi-pollutant models. Interaction terms showed that urban-dwelling children had greater odds of cognitive delay than rural-dwelling children, while there was no significant difference by sex. Our findings suggest that annual average exposure to PM 2.5 in young children was associated with adverse effects on cognitive development, which may have long-term consequences for educational attainment and health. [Display omitted] • The effects of ambient PM 2.5 on early cognitive development are scarcely studied. • We examined the association of PM 2.5 and cognitive delay in low-income countries. • Ambient PM 2.5 exposure is associated with significant cognitive delay in children. • The odds of cognitive delay associated with PM 2.5 was greater in urban children. [ABSTRACT FROM AUTHOR]

Studies examining long-term effects of ambient air pollution exposure, measured as annual averages, on pulmonary tuberculosis (TB) incidence are scarce, particularly in endemic, rural settings. We performed a small-area study in Ningxia Hui Autonomous Region (NHAR), a high TB-burden area in rural China, using township-level (n = 358 non-overlapping townships) annual TB notification data (2005–2017). We aimed to determine if annual average concentrations of ambient air pollution (particulate matter <2·5 μm [PM 2·5 ], nitrogen dioxide [NO 2 ] ozone [O 3 ]) were associated with TB notification rates (as a proxy for incidence). Air pollution effects on TB notification rates at township-level were estimated as incidence rate ratios (IRR), fitted using a generalised estimating equation (GEE) adjusted for covariates (age, sex, occupation, education, ethnicity, remoteness [urban or rural], household crowding and solid fuel use). A total of 38,942 TB notifications were reported in NHAR between 2005 and 2017. The mean annual TB notification rate was 67 (standard deviation [SD]; 7) per 100,000 people. Median concentrations of PM 2·5 , NO 2 , and O 3 were 42 μg/m3 (interquartile range [IQR]; 38–48 μg/m3), 15 ppb (IQR; 12–16 ppb), and 56 ppb (IQR; 56–57 ppb), respectively. In single pollutant models, adjusted for covariates, an interquartile range (IQR) increase (10 μg/m3) in PM 2·5 was significantly associated with higher TB notification rates (IRR: 1∙35; 95% CI: 1·25–1·48). Comparable effects on notifications of TB were observed for increases in NO 2 exposure (IRR: 1·20 per IQR (4 ppb) increase; 95% CI: 1·08–1·31). Ground-level ozone was not associated with TB notification rate in any models. The observed effects were consistent over time, in multi-pollutant models, and appeared robust to additional adjustment for indicators of household crowding, solid fuel use and remoteness. More rigorous study designs are needed to understand if improving air quality has population-level benefits on TB disease incidence in endemic settings. [Display omitted] • Annual average PM 2.5 and NO 2 exposure contributed to higher TB notifications rates. • Ground-level ozone exposure was not associated with TB notification rates. • Improvements in air quality could help alleviate the burden of TB. [ABSTRACT FROM AUTHOR]

Abstract: We estimate fine particulate matter (PM2.5) concentrations daily using MODIS satellite observations of aerosol optical depth (AOD) for a major biomass burning event around Moscow during summer 2010. Evaluation of MODIS AOD with the Moscow AERONET site supports a MODIS-AOD error estimate of ±(0.05+0.2×AOD) for this event. However, since the smoke was often thick (AOD>4.0) and spatially variable, the standard MODIS algorithm incorrectly identifies some aerosol as cloud. We test relaxed cloud screening criteria that increase MODIS coverage by 21% and find excellent agreement with coincident operational retrievals (r 2 =0.994, slope=1.01) with no evidence of false aerosol detection. We relate the resultant MODIS AOD to PM2.5 using aerosol vertical profiles from the GEOS-Chem chemical transport model. Our estimates are in good agreement with PM2.5 values estimated from in-situ PM10 (r 2 =0.85, slope=1.06), and we find that the relationship between AOD and PM2.5 is insensitive to uncertainties in biomass burning emissions. The satellite-derived and in-situ values both indicate that peak daily mean concentrations of approximately 600μgm−3 occurred on August 7, 2010 in the Moscow region of the Russian Federation. We estimate that exposure to air pollution from the Moscow wildfires may have caused hundreds of excess deaths. [Copyright &y& Elsevier]

Satellite remote sensing of air quality has evolved dramatically over the last decade. Global observations are now available for a wide range of species including aerosols, tropospheric O3, tropospheric NO2, CO, HCHO, and SO2. Capabilities for satellite remote sensing of these species in the boundary layer are reviewed for current instruments, along with physical processes affecting their accuracy and precision. Applications of satellite observations are discussed for case studies of specific events, for estimates of surface concentrations, and to improve emission inventories of trace gases and aerosols. Aerosol remote sensing at visible wavelengths exhibits high sensitivity to boundary layer concentrations. Although atmospheric scattering and surface emission of thermal radiation generally reduce instrument sensitivity to trace gases near the surface, a strong boundary layer signal in NO2 arises from its large boundary layer concentrations relative to the free troposphere. Recommendations are presented including (1) additional dedicated validation activities, especially for tropospheric NO2 and HCHO; (2) improved characterization of geophysical fields that affect remote sensing of trace gases and aerosols; (3) continued development of comprehensive assimilation and inversion capabilities to relate satellite observations to emissions and surface concentrations; (4) development of satellite instruments and algorithms to achieve higher spatial resolution to resolve urban scales, facilitate validation, and reduce cloud contamination that increases remote sensing error; and (5) support for the next generate of satellite instrumentation designed for air quality applications. [Copyright &y& Elsevier]

We investigate how a recently suggested pathway for production of secondary organic aerosol (SOA) affects the consistency of simulated organic aerosol (OA) mass in a global three-dimensional model of oxidant-aerosol chemistry (GEOS-Chem) versus surface measurements from the interagency monitoring of protected visual environments (IMPROVE) network. Simulations in which isoprene oxidation products contribute to SOA formation, with a yield of 2. 0% by mass reduce a model bias versus measured OA surface mass concentrations. The resultant increase in simulated OA mass concentrations during summer of 0. 6–1. 0μgm−3 in the southeastern United States reduces the regional RMSE to 0. 88μgm−3 from 1. 26μgm−3. Spring and fall biases are also reduced, with little change in winter when isoprene emissions are negligible. [Copyright &y& Elsevier]

Trace metal distributions are of relevance to understand sources of fine particulate matter (PM 2.5), PM 2.5 -related health effects, and atmospheric chemistry. However, knowledge of trace metal distributions is lacking due to limited ground-based measurements and model simulations. This study develops a simulation of 12 trace metal concentrations (Si, Ca, Al, Fe, Ti, Mn, K, Mg, As, Cd, Ni and Pb) over continental North America for 2013 using the GEOS-Chem chemical transport model. Evaluation of modeled trace metal concentrations with observations indicates a spatial consistency within a factor of 2. The spatial distribution of trace metal concentrations reflects their primary emission sources. Crustal element (Si, Ca, Al, Fe, Ti, Mn, K) concentrations are enhanced over the central US from anthropogenic fugitive dust and over the southwestern U.S. due to natural mineral dust. Heavy metal (As, Cd, Ni and Pb) concentrations are high over the eastern U.S. from industry. K is abundant in the southeast from biomass burning. High concentrations of Mg are observed along the coast from sea spray. The spatial pattern of PM 2.5 mass is most strongly correlated with Pb, Ni, As and K due to their signature emission sources. Challenges remain in accurately simulating observed trace metal concentrations. Halving anthropogenic fugitive dust emissions in the 2011 National Air Toxic Assessment (NATA) inventory and doubling natural dust emissions in the default GEOS-Chem simulation was necessary to reduce biases in crustal element concentrations. A fivefold increase of anthropogenic emissions of As and Pb was necessary in the NATA inventory to reduce the national-scale bias versus observations by more than 80%, potentially reflecting missing sources. • A simulation of 12 trace metals over North America with a bias within twofold. • Pb, Ni, As and K are highly correlated with PM 2.5 spatially. • Long-range transport of dust dominates the crustal metal budget over North America. [ABSTRACT FROM AUTHOR]

Epidemiological and health impact studies of fine particulate matter (PM 2.5 ) have been limited in China because of the lack of spatially and temporally continuous PM 2.5 monitoring data. Satellite remote sensing of aerosol optical depth (AOD) is widely used in estimating ground-level PM 2.5 concentrations. We improved the method for estimating long-term surface PM 2.5 concentrations using satellite remote sensing and a chemical transport model, and derived PM 2.5 concentrations over China for 2006–2012. We generated a map of surface PM 2.5 concentrations at 0.1° × 0.1° over China using the nested-grid GEOS-Chem model, most recent bottom-up emission inventory, and satellite observations from the MODIS and MISR instruments. Aerosol vertical profiles from the space-based CALIOP lidar were used to adjust the climatological drivers of the bias in the simulated results, and corrections were made for incomplete sampling. We found significant spatial agreement between the satellite-derived PM 2.5 concentrations and the ground-level PM 2.5 measurements collected from literatures (r = 0.74, slope = 0.77, intercept = 11.21 μg/m 3 ). The population-weighted mean of PM 2.5 concentrations in China is 71 μg/m 3 and more than one billion people live in locations where PM 2.5 concentrations exceed the World Health Organization Air Quality Interim Target-1 of 35 μg/m 3 . The results from our work are substantially higher than previous work, especially in heavily polluted regions. The overall population-weighted mean uncertainty over China is 17.2 μg/m 3 , as estimated using ground-level AOD measurements and vertical profiles observed from CALIOP. [ABSTRACT FROM AUTHOR]

Abstract: Land use regression (LUR) models are widely employed in health studies to characterize chronic exposure to air pollution. The LUR is essentially an interpolation technique that employs the pollutant of interest as the dependent variable with proximate land use, traffic, and physical environmental variables used as independent predictors. Two major limitations with this method have not been addressed: (1) variable selection in the model building process, and (2) dealing with unbalanced repeated measures. In this paper, we address these issues with a modeling framework that implements the deletion/substitution/addition (DSA) machine learning algorithm that uses a generalized linear model to average over unbalanced temporal observations. Models were derived for fine particulate matter with aerodynamic diameter of 2.5 microns or less (PM2.5) and nitrogen dioxide (NO2) using monthly observations. We used 4119 observations at 108 sites and 15,301 observations at 138 sites for PM2.5 and NO2, respectively. We derived models with good predictive capacity (cross-validated-R 2 values were 0.65 and 0.71 for PM2.5 and NO2, respectively). By addressing these two shortcomings in current approaches to LUR modeling, we have developed a framework that minimizes arbitrary decisions during the model selection process. We have also demonstrated how to integrate temporally unbalanced data in a theoretically sound manner. These developments could have widespread applicability for future LUR modeling efforts. [Copyright &y& Elsevier]

Epidemiological studies have consistently demonstrated that exposure to fine particulate matter (PM 2.5) is associated with increased risks of mortality. To a lesser extent, a series of studies suggest that living in greener areas is associated with reduced risks of mortality. Only a handful of studies have examined the interplay between PM 2.5 , greenness, and mortality. We investigated the role of residential greenness in modifying associations between long-term exposures to PM 2.5 and non-accidental and cardiovascular mortality in a national cohort of non-immigrant Canadian adults (i.e., the 2001 Canadian Census Health and Environment Cohort). Specifically, we examined associations between satellite-derived estimates of PM 2.5 exposure and mortality across quintiles of greenness measured within 500 m of individual's place of residence during 11 years of follow-up. We adjusted our survival models for many personal and contextual measures of socioeconomic position, and residential mobility data allowed us to characterize annual changes in exposures. Our cohort included approximately 2.4 million individuals at baseline, 194,270 of whom died from non-accidental causes during follow-up. Adjustment for greenness attenuated the association between PM 2.5 and mortality (e.g., hazard ratios (HRs) and 95% confidence intervals (CIs) per interquartile range increase in PM 2.5 in models for non-accidental mortality decreased from 1.065 (95% CI: 1.056–1.075) to 1.041 (95% CI: 1.031–1.050)). The strength of observed associations between PM 2.5 and mortality decreased as greenness increased. This pattern persisted in models restricted to urban residents, in models that considered the combined oxidant capacity of ozone and nitrogen dioxide, and within neighbourhoods characterised by high or low deprivation. We found no increased risk of mortality associated with PM 2.5 among those living in the greenest areas. For example, the HR for cardiovascular mortality among individuals in the least green areas was 1.17 (95% CI: 1.12–1.23) compared to 1.01 (95% CI: 0.97–1.06) among those in the greenest areas. Studies that do not account for greenness may overstate the air pollution impacts on mortality. Residents in deprived neighbourhoods with high greenness benefitted by having more attenuated associations between PM 2.5 and mortality than those living in deprived areas with less greenness. The findings from this study extend our understanding of how living in greener areas may lead to improved health outcomes. • Exposure to air pollution had a lower impact on risk of dying in greener areas. • This pattern held in neighbourhoods characterised by high or low deprivation. • Not accounting for greenness may overstate air pollution impacts on health. • This study extends our understanding of how living in greener areas improves health. • We found no link between PM 2.5 and risk of dying among those in the greenest areas. [ABSTRACT FROM AUTHOR]

[Display omitted] • Prenatal conditions of maternal immune activation (MIA) was associated with ASD. • Exposure to PM 2.5 and its major components during pregnancy were associated with ASD. • Prenatal MIA conditions unexpectedly did not augment effects of particles on ASD. Autism Spectrum Disorder (ASD) risk is highly heritable, with potential additional non-genetic factors, such as prenatal exposure to ambient particulate matter with aerodynamic diameter < 2.5 µm (PM 2.5) and maternal immune activation (MIA) conditions. Because these exposures may share common biological effect pathways, we hypothesized that synergistic associations of prenatal air pollution and MIA-related conditions would increase ASD risk in children. This study examined interactions between MIA-related conditions and prenatal PM 2.5 or major PM 2.5 components on ASD risk. In a population-based pregnancy cohort of children born between 2001 and 2014 in Southern California, 318,751 mother–child pairs were followed through electronic medical records (EMR); 4,559 children were diagnosed with ASD before age 5. Four broad categories of MIA-related conditions were classified, including infection, hypertension, maternal asthma, and autoimmune conditions. Average exposures to PM 2.5 and four PM 2.5 components, black carbon (BC), organic matter (OM), nitrate (NO 3 –), and sulfate (SO 4 2-), were estimated at maternal residential addresses during pregnancy. We estimated the ASD risk associated with MIA-related conditions, air pollution, and their interactions, using Cox regression models to adjust for covariates. ASD risk was associated with MIA-related conditions [infection (hazard ratio 1.11; 95% confidence interval 1.05–1.18), hypertension (1.30; 1.19–1.42), maternal asthma (1.22; 1.08–1.38), autoimmune disease (1.19; 1.09–1.30)], with higher pregnancy PM 2.5 [1.07; 1.03–1.12 per interquartile (3.73 μg/m3) increase] and with all four PM 2.5 components. However, there were no interactions of each category of MIA-related conditions with PM 2.5 or its components on either multiplicative or additive scales. MIA-related conditions and pregnancy PM 2.5 were independently associations with ASD risk. There were no statistically significant interactions of MIA conditions and prenatal PM 2.5 exposure with ASD risk. [ABSTRACT FROM AUTHOR]

Measurements of black carbon at remote and high altitude locations provide an important constraint for models. Here we present six months of refractory black carbon (rBC) data collected in July–August of 2009, June–July of 2010, and April–May of 2012 using a single particle soot photometer (SP2) at the remote Whistler High Elevation Research Site in the Coast Mountains of British Columbia (50.06°N, 122.96°W, 2182 m a.m.s.l). In order to reduce regional boundary layer influences, only measurements collected during the night (2000-0800 PST) were considered. Times impacted by local biomass burning were removed from the data set, as were periods of in-cloud sampling. Back trajectories and back trajectory cluster analysis were used to classify the sampled air masses as Southern Pacific, Northern Pacific, Western Pacific/Asian, or Northern Canadian in origin. The largest rBC mass median diameter (182 nm) was seen for air masses in the Southern Pacific cluster, and the smallest (156 nm) was seen for air masses in the Western Pacific/Asian cluster. Considering all the clusters, the median mass concentration of rBC was 25.0 ± 7.6 ng/m 3 -STP. The Northern Pacific, Southern Pacific, Western Pacific/Asian, and Northern Canada clusters had median mass concentrations of 25.0 ± 7.6, 21.3 ± 6.9, 25.0 ± 7.9, and 40.6 ± 12.9 ng/m 3 -STP, respectively. We compared these measurements with simulations from the global chemical transport model GEOS-Chem. The default GEOS-Chem simulations overestimated the median rBC mass concentrations for the different clusters by a factor of 1.2–2.2. The largest difference was observed for the Northern Pacific cluster (factor of 2.2) and the smallest difference was observed for the Northern Canada cluster (factor of 1.2). A sensitivity simulation that excluded Vancouver emissions still overestimated the median rBC mass concentrations for the different clusters by a factor of 1.1–2.0. After implementation of a revised wet scavenging scheme, the simulations overestimated the median rBC mass concentrations for the different clusters by a factor of 1.0–2.0. [ABSTRACT FROM AUTHOR]

Exposure to fine particulate matter (PM 2.5) is the leading environmental risk factor for mortality globally. Satellite-derived estimates of surface PM 2.5 developed from a combination of satellites, simulations, and ground monitor data are relied upon for health impact studies. The ability to develop satellite-derived PM 2.5 estimates requires the continued availability of aerosol optical depth (AOD) sources. This work examines the impact of the addition or loss of satellite AOD data sources on global PM 2.5 estimation and the impact of continuing the long-term record with AOD from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-National Polar orbiting Partnership (S-NPP) satellite after the loss of the MODIS (MODerate resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer) instruments on board the Terra and Aqua satellites. We find that the addition of VIIRS S-NPP AOD products to geophysical PM 2.5 estimates from satellites and simulations causes regional differences that correspond to differences in the VIIRS and MODIS Deep Blue AOD algorithms and sampling. Changes in long-term trends and timeseries due to the addition or loss of AOD data sources are generally within their uncertainties. Statistical fusion with ground monitor data partially corrects for changes due to sampling differences when introducing the VIIRS AOD products, but uncertainty remains over desert regions where ground monitor coverage is sparse. This work provides promise for the sustained development of global satellite-derived PM 2.5 estimates, despite discontinuities in instruments and retrieval methods. • Impact of changing satellite AOD sources on global PM 2.5 estimation is examined. • Algorithm inconsistencies and sampling cause regional differences in PM 2.5. • Changes in trends due to the discontinuity of AOD sources are within uncertainties. • Statistical fusion with ground monitors partially corrects for sampling impacts. • Global sat-derived PM 2.5 record is sustained despite AOD source discontinuities. [ABSTRACT FROM AUTHOR]

Introduction Emerging studies have implicated air pollution in the neurodegenerative processes. Less is known about the influence of air pollution, especially at the relatively low levels, on developing dementia. We conducted a population-based cohort study in Ontario, Canada, where the concentrations of pollutants are among the lowest in the world, to assess whether air pollution exposure is associated with incident dementia. Methods The study population comprised all Ontario residents who, on 1 April 2001, were 55–85 years old, Canadian-born, and free of physician-diagnosed dementia (~ 2.1 million individuals). Follow-up extended until 2013. We used population-based health administrative databases with a validated algorithm to ascertain incident diagnosis of dementia as well as prevalent cases. Using satellite observations, land-use regression model, and an optimal interpolation method, we derived long-term average exposure to fine particulate matter (≤ 2.5 μm in diameter) (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ), respectively at the subjects' historical residences based on a population-based registry. We used multilevel spatial random-effects Cox proportional hazards models, adjusting for individual and contextual factors, such as diabetes, brain injury, and neighborhood income. We conducted various sensitivity analyses, such as lagging exposure up to 10 years and considering a negative control outcome for which no (or weaker) association with air pollution is expected. Results We identified 257,816 incident cases of dementia in 2001–2013. We found a positive association between PM 2.5 and dementia incidence, with a hazard ratio (HR) of 1.04 (95% confidence interval (CI): 1.03–1.05) for every interquartile-range increase in exposure to PM 2.5 . Similarly, NO 2 was associated with increased incidence of dementia (HR = 1.10; 95% CI: 1.08–1.12). No association was found for O 3 . These associations were robust to all sensitivity analyses examined. These estimates translate to 6.1% of dementia cases (or 15,813 cases) attributable to PM 2.5 and NO 2 , based on the observed distribution of exposure relative to the lowest quartile in concentrations in this cohort. Discussion In this large cohort, exposure to air pollution, even at the relative low levels, was associated with higher dementia incidence. [ABSTRACT FROM AUTHOR]

Background There are increasing concerns regarding the role of exposure to ambient air pollution during pregnancy in the development of early childhood cancers. Objective This population based study examined whether prenatal and early life (< 1 year of age) exposures to ambient air pollutants, including nitrogen dioxide (NO 2 ) and particulate matter with aerodynamic diameters ≤ 2.5 μm (PM 2.5 ), were associated with selected common early childhood cancers in Canada. Methods 2,350,898 singleton live births occurring between 1988 and 2012 were identified in the province of Ontario, Canada. We assigned temporally varying satellite-derived estimates of PM 2.5 and land-use regression model estimates of NO 2 to maternal residences during pregnancy. Incident cases of 13 subtypes of pediatric cancers among children up to age 6 until 2013 were ascertained through administrative health data linkages. Associations of trimester-specific, overall pregnancy and first year of life exposures were evaluated using Cox proportional hazards models, adjusting for potential confounders. Results A total of 2044 childhood cancers were identified. Exposure to PM 2.5 , per interquartile range increase, over the entire pregnancy, and during the first trimester was associated with an increased risk of astrocytoma (hazard ratio (HR) per 3.9 μg/m3 = 1.38 (95% CI: 1.01, 1.88) and, HR per 4.0 μg/m 3 = 1.40 (95% CI: 1.05–1.86), respectively). We also found a positive association between first trimester NO 2 and acute lymphoblastic leukemia (ALL) (HR = 1.20 (95% CI: 1.02–1.41) per IQR (13.3 ppb)). Conclusions In this population-based study in the largest province of Canada, results suggest an association between exposure to ambient air pollution during pregnancy, especially in the first trimester and an increased risk of astrocytoma and ALL. Further studies are required to replicate the findings of this study with adjustment for important individual-level confounders. [ABSTRACT FROM AUTHOR]

Abstract: Fine particulate matter is one of the key global pollutants affecting human health. Satellite and ground-based monitoring technologies as well as chemical transport models have advanced significantly in the past 50 years, enabling improved understanding of the sources of fine particles, their chemical composition, and their effect on human and environmental health. The ability of air pollution to travel across country and geographic boundaries makes particulate matter a global problem. However, the variability in monitoring technologies and programs and poor data availability make global comparison difficult. This paper summarizes fine particle monitoring, models that integrate ground-based and satellite-based data, and communications, then recommends steps for policymakers and scientists to take to expand and improve local and global indicators of particulate matter air pollution. One of the key set of recommendations to improving global indicators is to improve data collection by basing particulate matter monitoring design and stakeholder communications on the individual country, its priorities, and its level of development, while at the same time creating global data standards for inter-country comparisons. When there are good national networks that produce consistent quality data that is shared openly, they serve as the foundation for better global understanding through data analysis, modeling, health impact studies, and communication. Additionally, new technologies and systems should be developed to expand personal air quality monitoring and participation of non-specialists in crowd-sourced data collections. Finally, support to the development and improvement of global multi-pollutant indicators of the health and economic effects of air pollution is essential to addressing improvement of air quality around the world. [Copyright &y& Elsevier]

Abstract: Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6–10% increases in respiratory and allergic health outcomes per interquartile range (3.97 μg m−3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20–64) in the national study population. Risk estimates for air pollution and respiratory/allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05). The consistency between risk estimates based on RS and regulatory monitoring as well as the associations between air pollution and health among participants living outside the catchment area for regulatory monitoring suggest that RS can provide useful estimates of long-term ambient air pollution in epidemiologic studies. This is particularly important in rural communities and other areas where monitoring and modeled air pollution data are limited or unavailable. [Copyright &y& Elsevier]

[Display omitted] • Exposure to PM 2.5 increased CVD mortality in a nationally representative cohort. • We provided one of the very few evidence on long-term CVD effects of PM 2.5 constituents. • BC, OM, NO 3 –, NH 4 + and SO 4 2− showed appreciably larger risks than PM 2.5 total mass. • Soil dust showed no cardiovascular risks. Few studies have evaluated long-term cardiovascular effects of fine particulate matter (PM 2.5) and its constituents in countries with high air pollution levels. We aimed to investigate the associations of long-term exposure to PM 2.5 and constituents with cardiovascular mortality in China. We conducted a prospective cohort study of 90,672 adults ≥ 18 years from 2010 to 2017 in 161 districts/counties across China. The residential annual-average exposure to PM 2.5 and 6 main components from 2011 to 2017 were estimated by satellite-based and chemical transport models. Associations of PM 2.5 and constituents with cardiovascular mortality were analyzed by competing-risk Cox proportional hazards regression. The average PM 2.5 exposure throughout the whole period was 46 ± 22 μg/m3. The hazard ratios of mortality (95% confidence intervals) per 10 μg/m3 increase in PM 2.5 concentrations were 1.02 (1.00, 1.05) for overall cardiovascular disease, 1.05 (1.01, 1.09) for ischemic heart disease, 1.03 (1.00, 1.06) for overall stroke, 0.99 (0.94, 1.04) for hemorrhagic stroke, and 1.11 (1.04, 1.19) for ischemic stroke. PM 2.5 constituents from fossil fuel combustion (i.e., black carbon, organic matter, nitrate, ammonium, and sulfate) showed larger hazard ratios than PM 2.5 total mass, while soil dust showed no risks. This nationwide cohort study demonstrated associations of long-term exposure to PM 2.5 and its constituents with increased risks of cardiovascular mortality in the general population of China. Our study highlighted the importance of PM 2.5 constituents from fossil fuel combustion in the long-term cardiovascular effects of PM 2.5 in China. [ABSTRACT FROM AUTHOR]

[Display omitted] Growing evidence has linked fine particulate matter (PM 2.5) exposure to elevated blood pressure, but the effects of PM 2.5 components are unclear, particularly in children and adolescents. Based on a cross-sectional investigation in China, we analyzed the associations between long-term exposure to PM 2.5 and its major components with elevated blood pressure in children and adolescents. A representative sample (N = 37,610) of children and adolescents with age 7–18 years was collected in seven Chinese provinces. Exposures to PM 2.5 and five of its major components, including black carbon (BC), organic matter (OM), inorganic nitrate (NO 3 −), sulfate (SO 4 2−), and soil particles (SOIL), were estimated using satellite-based spatiotemporal models. The associations between long-term exposures to PM 2.5 and its components and diastolic blood pressure (DBP), systolic blood pressure (SBP), and hypertension were investigated using mixed-effects logistic and linear regression models. Within the populations, 11.5 % were classified as hypertension. After adjusting for a variety of covariates, per interquartile range (IQR) increment in PM 2.5 mass and BC levels were significantly associated with a higher hypertension prevalence with odds ratios (ORs) of 1.56 (95% confidence interval (CI): 1.08, 2.25) for PM 2.5 and 1.19 (95% CI: 1.04, 1.35) for BC. Long-term exposures to PM 2.5 and BC have also been associated with elevated SBP and DBP. Additionally, OM and NO 3 − were significantly associated with increased SBP, while SOIL was significantly associated with increased DBP. In the subgroup analysis, the associations between long-term exposures to BC and blood pressure vary significantly by urbanicity of residential area and diet habits. Our study suggests that long-term exposure to PM 2.5 mass and specific PM 2.5 components, especially for BC, are significantly associated with elevated blood pressure and a higher hypertension prevalence in Chinese children and adolescents. [ABSTRACT FROM AUTHOR]

Abstract: Since the mid-1990s a new generation of Earth-observing satellites has been able to detect tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary emitted species can be measured by one or more of the instruments. This review article addresses the question of how well we can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U.S. air quality managers. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NO x and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic). Techniques that enhance the usefulness of current retrievals (data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc.) are discussed. Finally, we point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial (few km) and temporal (hourly) resolution. [Copyright &y& Elsevier]

Abstract: The scattering of visible light by ice crystals and dust in radiative transfer models is challenging in part due to the large amount of scattering in the forward direction. We introduce a technique that ensures numerical conservation of photons in any radiative transfer model and that quantifies the integration error associated with highly asymmetric phase functions. When applied to a successive-orders of scatter model, the technique illustrates the high accuracy obtained in numerical integration of molecular and aerosol scattering. As well, a phase function truncation and renormalization technique is applied to scattering by ice crystals with very large size parameters, between 100 and 1000, and the scaled radiative transfer equation is solved with the spherical successive-orders model, SASKTRAN. Since computations shown this work are performed in a fully spherical model atmosphere, the computed radiances are not subject to the discontinuity at the horizon that is inherent in models using a plane–parallel assumption. The methods introduced in this work are of particular interest in modeling limb radiances in the presence of thin cirrus clouds. [Copyright &y& Elsevier]

Abstract: We investigated variations in the relative sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NOx) as inferred from the ratio of the tropospheric columns of formaldehyde to nitrogen dioxide (the “Ratio”) from the Aura Ozone Monitoring Instrument (OMI). Our modeling study suggests that ozone formation decreases with reductions in VOCs at Ratios <1 and NOx at Ratios >2; both NOx and VOC reductions may decrease ozone formation for Ratios between 1 and 2. Using this criteria, the OMI data indicate that ozone formation became: 1. more sensitive to NOx over most of the United States from 2005 to 2007 because of the substantial decrease in NOx emissions, primarily from stationary sources, and the concomitant decrease in the tropospheric column of NO2, and 2. more sensitive to NOx with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. In cities with relatively low isoprene emissions (e.g., Chicago), the data clearly indicate that ozone formation became more sensitive to NOx from 2005 to 2007. In cities with relatively high isoprene emissions (e.g., Atlanta), we found that the increase in the Ratio due to decreasing NOx emissions was not obvious as this signal was convolved with variations in the Ratio associated with the temperature dependence of isoprene emissions and, consequently, the formaldehyde concentration. [Copyright &y& Elsevier]

[Display omitted] • Evidence is scarce on PM 2.5 exposure and birth outcome in African countries. • Use of Satellite-derived PM 2.5 estimates and the Demographic Health and Surveys data. • PM 2.5 exposure was significantly associated with preterm birth (8%) and low birth weight (28%) • Associations were modified by region, and maternal, infant, household characteristics. Fine particulate matter (PM 2.5) exposure has been reported to adversely affect birth outcomes, but the evidence is limited, particularly in low- and middle-income countries (LMICs). We assessed the associations between maternal PM 2.5 exposure and low birth weight (LBW) and preterm birth (PTB) in Africa. We used standard Demographic and Health Surveys (DHS) data (2005–2015) from 15 countries in Africa to conduct a cross-sectional study. The study population was composed of 131,594 births with detailed information on maternal and household variables. LBW was defined as a birth weight of < 2500 g after 37 weeks, and PTB was defined as live birth occurring before 37 weeks of gestation. Average exposure to PM 2.5 during pregnancy was estimated using satellite-based models. Multivariable logistic regression models were constructed, and analyses of data by region (Western, Eastern, Central, and Southern Africa) and data stratified by potential effect modifiers were conducted. A total of 13,214 (10%) LBW and 4,377 (3.3%) PTB cases were identified. An interquartile range (IQR) (33.9 μg/m3) increase in PM 2.5 during pregnancy was associated with increased odds of LBW and PTB, with odds ratios (ORs) of 1.28 (95% CI: 1.23, 1.34) and 1.08 (95% CI: 1.01, 1.16), respectively. Region-specific analyses revealed significant associations between PM 2.5 and LBW in all regions, and significant associations between PM 2.5 and PTB in Western and Southern Africa. Subgroup analyses revealed that the association between PM 2.5 and LBW was present in all subgroups, and stronger associations were observed in female infants, while the association between PM 2.5 and PTB was larger in subgroups of older individuals living in urban areas. This multicountry study in Africa demonstrated significant associations between maternal exposure to PM 2.5 and higher odds of LBW and PTB. Our findings may facilitate air quality control strategies that address adverse birth outcomes in LMICs. [ABSTRACT FROM AUTHOR]

[Display omitted] • Levels of ambient PM 2.5 are stable or increasing in many low and middle-income countries. • We assessed associations between childrens' long-term PM 2.5 exposure and acute respiratory infection (ARI) • We found a significant association between annual PM and ARI in the preceding two weeks. • Boys and children living in rural areas appeared to be at greater risk of adverse effects. Evidence from developed countries suggests that fine particulate matter (≤2.5 µm [PM 2.5 ]) contributes to childhood respiratory morbidity and mortality. However, few analyses have focused on resource-limited settings, where much of this burden occurs. We aimed to investigate the cross-sectional associations between annual average exposure to ambient PM 2.5 and acute respiratory infection (ARI) in children aged <5 years living in low- and middle-income countries (LMICs). We combined Demographic and Health Survey (DHS) data from 35 countries with gridded global estimates of annual PM 2.5 mass concentrations. We analysed the association between PM 2.5 and maternal-reported ARI in the two weeks preceding the survey among children aged <5 years living in 35 LMICs. We used multivariable logistic regression models that adjusted for child, maternal, household and cluster-level factors. We also fitted multi-pollutant models (adjusted for nitrogen dioxide [NO 2 ] and surface-level ozone [O 3 ]), among other sensitivity analyses. We assessed whether the associations between PM 2.5 and ARI were modified by sex, age and place of residence. The analysis comprised 573,950 children, among whom the prevalence of ARI was 22,506 (3.92%). The mean (±SD) estimated annual concentration of PM 2.5 to which children were exposed was 48.2 (±31.0) µg/m3. The 5th and 95th percentiles of PM 2.5 were 9.8 µg/m3 and 110.9 µg/m3, respectively. A 10 µg/m3 increase in PM 2.5 was associated with greater odds of having an ARI (OR: 1.06; 95% CI: 1.05–1.07). The association between PM 2.5 and ARI was robust to adjustment for NO 2 and O 3. We observed evidence of effect modification by sex, age and place of residence, suggesting greater effects of PM 2.5 on ARI in boys, in younger children, and in children living in rural areas. Annual average ambient PM 2.5 , as an indicator for long-term exposure, was associated with greater odds of maternal-reported ARI in children aged <5 years living in 35 LMICs. Longitudinal studies in LMICs are required to corroborate our cross-sectional findings, to further elucidate the extent to which lowering PM 2.5 may have a role in the global challenge of reducing ARI-related morbidity and mortality in children. [ABSTRACT FROM AUTHOR]

[Display omitted] • Analysis of long-term exposure to PM 2.5 major components and overall mortality among the elderly in the southeastern United States. • A large-scale population-based cohort study by leveraging fine-resolution PM 2.5 components data and the Medicare population. • We observed elevated all-cause mortality associated with long-term exposure to black carbon, organic matters, nitrate, and soil particles. • Better understanding of component-specific effects of PM 2.5 on all-cause mortality could inform pollution control policies on specific sources. Long-term exposure to fine particulate matter (PM 2.5) mass has been associated with adverse health effects. However, the health effects of PM 2.5 components have been less studied. There is a pressing need to better understand the relative contribution of components of PM 2.5 , which can lay the scientific basis for designing effective policies and targeted interventions. We conducted a population-based cohort study, comprising all Medicare enrollees aged 65 or older in the southeastern United States from 2000 to 2016, to explore the associations between long-term exposure to PM 2.5 major components and all-cause mortality among the elderly. Based on well-validated prediction models, we estimated ZIP code-level annual mean concentrations for five major PM 2.5 components, including black carbon (BC), nitrate (NIT), organic matter (OM), sulfate (SO 4), and soil particles. Data were analyzed using Cox proportional hazards models, adjusting for potential confounders. The cohort comprised 13,590,387 Medicare enrollees and a total of 107,191,652 person-years. In single-component models, all five major PM 2.5 components were significantly associated with elevated all-cause mortality. The hazard ratios (HR) per interquartile range (IQR) increase in exposure were 1.027 (95% CI: 1.025–1.030), 1.012 (95% CI: 1.010–1.013), 1.018 (95% CI: 1.017–1.020), 1.021 (95% CI: 1.017–1.024), and 1.004 (95% CI: 1.003–1.006) for BC, NIT, OM, SO 4 , and soil particles, respectively. While the effect estimate of soil component was statistically significant, it is much smaller than those of combustion-related components. Our study provides epidemiological evidence that long-term exposure to major PM 2.5 components is significantly associated with elevated mortality. [ABSTRACT FROM AUTHOR]

• Limited evidence on the PM 2.5 constituents - infant mortality association in developing countries. • A multi-country cross-sectional study based on the Demographic and Health Surveys in Africa. • PM 2.5 was associated with increased infant mortality across 15 countries in Africa. • PM 2.5 carbonaceous fractions and sulfate play a major important role in infant mortality. Few studies have investigated the association between exposure to fine particulate matter (PM 2.5) and infant mortality in developing countries, especially for the health effects of specific PM 2.5 constituents. We aimed to examine the association of long-term exposure to specific PM 2.5 constituents with infant mortality in 15 African countries from 2005 to 2015. Based on the Demographic and Health Surveys (DHS) dataset, we included birth history records from 15 countries in Africa and conducted a multicountry cross-sectional study to examine the associations between specific PM 2.5 constituents and infant mortality. We estimated annual residential exposure using satellite-derived PM 2.5 for mass and a chemical transport model (GEOS-Chem) for its six constituents, including organic matter (OM), black carbon (BC), sulfate (SO 4 2−), nitrate (NO 3 −), ammonium (NH 4 +), and soil dust (DUST). Multivariable logistic regression analysis was employed by fitting single-constituent models, the constituent-PM 2.5 models, and the constituent-residual models. We also conducted stratified analyses by potential effect modifiers and examined the specific associations for each country. We found positive and significant associations between PM 2.5 total mass and most of its constituents with infant mortality. In the single-constituent model, for an IQR increase in pollutant concentrations, the odds ratio (OR) of infant mortality was 1.03 (95 %CI; 1.01, 1.06) for PM 2.5 total mass, and was 1.04 (95 %CI: 1.02, 1.06), 1.04 (95 %CI: 1.02, 1.05), 1.02 (95 %CI: 1.00, 1.03), 1.04 (1.01, 1.06) for BC, OM, SO 4 2−, and DUST, respectively. The associations of BC, OM, and SO 4 2− remained significant in the other two models. We observed larger estimates in subgroups with older maternal age, living in urban areas, using unclean cooking energy, and with access to piped water. The associations varied among countries, and by different constituents. The carbonaceous fractions and sulfate play a major important role among PM 2.5 constituents on infant mortality. Our findings have certain policy implications for implementing effective measures for targeted reduction in specific sources (fossil fuel combustion and biomass burning) of PM 2.5 constituents against the risk of infant mortality. [ABSTRACT FROM AUTHOR]

Few cohort studies explored the associations of long-term exposure to ambient fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM 2.5) and its chemical constituents with mortality risk in rural China. We conducted a 12-year prospective study of 28,793 adults in rural Deqing, China from 2006 to 2018. Annual mean PM 2.5 and its constituents, including black carbon (BC), organic carbon (OC), ammonium (NH 4 +), nitrate (NO 3 −), sulfate (SO 4 2−), and soil dust were measured at participants' addresses at enrollment from a satellite-based exposure predicting model. Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% confidence intervals (95%CIs) of long-term exposure to PM 2.5 for mortality. A total of 1960 deaths were identified during the follow-up. We found PM 2.5 , BC, OC, NH 4 +, NO 3 −, and SO 4 2− were significantly associated with an increased risk of non-accidental mortality. The HR for non-accidental mortality was 1.17 (95%CI: 1.07, 1.28) for each 10 μg/m3 increase in PM 2.5. As for constituents, the strongest association was found for BC (HR = 1.21, 95%CI: 1.11, 1.33), followed by NO 3 −, NH 4 +, SO 4 2−, and OC (HR = 1.14–1.17 per interquartile range). A non-linear relationship was found between PM 2.5 and non-accidental mortality. Similar associations were found for cardio-cerebrovascular and cancer mortality. Associations were stronger among men and ever smokers. Conclusively, we found long-term exposure to ambient PM 2.5 and its chemical constituents (especially BC and NO 3 −) increased mortality risk. Our results suggested the importance of adopting effective targeted emission control to improve air quality for health protection in rural East China. • First cohort on PM 2.5 and constituents with mortality in rural Eastern China. • Long-term exposure to PM 2.5 increases risk of non-accidental mortality. • Black carbon has the strongest association compared to other PM 2.5 constituents. • There is a non-linear relationship between PM 2.5 and non-accidental mortality. • Sex, smoking status are effect modifiers of air pollution and mortality. [ABSTRACT FROM AUTHOR]

• Air pollution has been associated with increased mortality, but more recent evidence from low-exposure regions is needed. • Exposure to PM 2.5 and NO 2 was associated with mortality after adjustment for a wide array of potential confounders. • Stronger associations were found in physically active participants, smokers, and those with lower household income. Air pollution has been associated with increased mortality. However, updated evidence from cohort studies with detailed information on various risk factors is needed, especially in regions with low air pollution levels. We investigated the associations between long-term exposure to air pollution and mortality in a prospective cohort. We studied 88,615 participants aged ≥30 years from an ongoing cohort study in Ontario, Canada from 2009 to 2017. Exposure to ambient fine particulate matter (PM 2.5) and nitrogen dioxide (NO 2) was estimated at participants' residence. Cox proportional hazard models were used to investigate the associations between air pollution and non-accidental, cardiovascular, and respiratory mortality, adjusted for a wide array of individual-level and contextual covariates. Potential effect modification by socio-demographic and behavioral factors was also examined in exploratory stratified analyses. The fully adjusted hazard ratios (HRs) per 1 µg/m3 increment in PM 2.5 were 1.037 [95% confidence interval (CI): 1.018, 1.057]¸ 1.083 (95% CI: 1.040, 1.128) and 1.109 (95% CI: 1.035, 1.187) for non-accidental, cardiovascular, and respiratory mortality, respectively. Positive associations were also found for NO 2 ; the corresponding HRs per 1 ppb increment were 1.027 (95% CI: 1.021, 1.034), 1.032 (95% CI: 1.019, 1.046) and 1.044 (95% CI: 1.020, 1.068). We found suggestive evidence of stronger associations in physically active participants, smokers, and those with lower household income. Long-term exposure to PM 2.5 and NO 2 was associated with increased risks for non-accidental, cardiovascular, and respiratory mortality, suggesting potential benefits of further improvement in air quality even in low-exposure environments. [ABSTRACT FROM AUTHOR]

• Limited evidence on the link between PM 2.5 constituents and children's weight. • Prenatal exposure to PM 2.5 constituents was associated with decreased weight in boys. • Less consistent effect of PM 2.5 constituents on girls' weight. • A lasting effect of prenatal exposure to PM 2.5 constituents on children's weight. Studies have reported that prenatal exposure to fine particulate matter (PM 2.5) might be associated with adverse birth outcomes in offspring. However, evidence with regard to the effects of prenatal exposure to PM 2.5 and, especially, its main chemical constituents on offspring's weight in childhood is limited and inconsistent. The present study aimed to examine associations of prenatal exposure to PM 2.5 total mass and its chemical constituents in each trimester with children's weight from birth to 6 years of age using data from Shanghai-Minhang Birth Cohort Study. A total of 1,084 mother-infant pairs were included with both PM 2.5 exposure data and at least one measurement of weight and height. Weight-for-Length (WLZ), BMI-for-Age (BMIz), and Weight-for-Age (WAZ) z-scores were generated according to the World Health Organization guidelines. Exposure to PM 2.5 total mass and its chemical constituents [organic carbon (OC), black carbon (BC), ammonium (NH 4 +), nitrate (NO 3 −), sulfate (SO 4 2−), and soil dust (SOIL)] during pregnancy was estimated from a satellite based modelling framework. We used multiple informant model to estimate the associations of trimester-specific PM 2.5 total mass and its specific constituents concentrations with WLZ/BMIz and WAZ of offspring at birth and 1, 4, and 6 years of age. In multiple informant model, we observed consistent patterns of associations between exposure to PM 2.5 total mass, OC, BC, NH 4 +, NO 3 −, and SO 4 2− during the 2nd and 3rd trimesters and decreased WLZ/BMIz and WAZ at 1, 4, and 6 years of age in boys. We observed associations between prenatal exposure to PM 2.5 total mass, NH 4 +, and NO 3 − during the 1st and 2nd trimesters and increased WLZ/BMIz and WAZ in girls at birth. However, there were null associations at 1 and 4 years of age and inverse associations at 6 years of age. Prenatal exposure to PM 2.5 total mass and its main chemical constituents was associated with decreased weight in boys from 1 to 6 years of age, with increased weight at birth and decreased weight at 6 years of age in girls. Our findings suggest that prenatal exposure to PM 2.5 and its chemical constituents may have a lasting effect on offspring's weight in childhood. [ABSTRACT FROM AUTHOR]

• In those with COVID-19, higher PM 2.5 associated with higher hospitalization risk. • The association was present in each wave of the pandemic. • The association was present at PM 2.5 concentrations below the national standard. • The association was higher in Black individuals and socioeconomically disadvantaged. Ecologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM 2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking. We leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM 2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM 2.5 with risk of hospitalization. There were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM 2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM 2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%–12%) increase in risk of hospitalization. The association of PM 2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure–response suggested increased risk at PM 2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM 2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001). Exposure to higher levels of PM 2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM 2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM 2.5 on risk of hospitalization in the setting of COVID-19. [ABSTRACT FROM AUTHOR]

• PM 2.5 exposure was associated with childhood asthma incidence. • Joint effects of PM 2.5 and its components have an impact on childhood asthma incidence. • Black carbon, ammonium, and nitrate appeared to play an important role. Several studies have found positive associations between outdoor fine particulate air pollution (≤2.5 μm, PM 2.5) and childhood asthma incidence. However, the impact of PM 2.5 composition on children's respiratory health remains uncertain. We examined whether joint exposure to PM 2.5 mass concentrations and its major chemical components was associated with childhood asthma development. We conducted a population-based cohort study by identifying 1,130,855 singleton live births occurring between 2006 and 2014 in the province of Ontario, Canada. Concentrations of PM 2.5 and its seven major chemical components were assigned to participants based on their postal codes using chemical transport models and remote sensing. The joint impact of outdoor PM 2.5 concentrations and its major components and childhood asthma incidence (up to age 6) were estimated using Cox proportional hazards models, allowing for potential nonlinearity. We identified 167,080 children who developed asthma before age 6. In adjusted models, outdoor PM 2.5 mass concentrations during childhood were associated with increased incidence of childhood asthma (Hazard Ratio (HR) for each 1 μg/m3 increase = 1.026, 95% CI: 1.021–1.031). We found that the joint effects of PM 2.5 and its components on childhood asthma incidence may be 24% higher than the conventional approach. Specific components/source markers such as black carbon, ammonium, and nitrate appeared to play an important role. Early life exposure to PM 2.5 and its chemical components is associated with an increased risk of asthma development in children. The heterogeneous nature of PM 2.5 should be considered in future health risk assessments. [ABSTRACT FROM AUTHOR]

It has been posited that populations being exposed to long-term air pollution are more susceptible to COVID-19. Evidence is emerging that long-term exposure to ambient PM 2.5 (particulate matter with aerodynamic diameter 2.5 μm or less) associates with higher COVID-19 mortality rates, but whether it also associates with the speed at which the disease is capable of spreading in a population is unknown. Here, we establish the association between long-term exposure to ambient PM 2.5 in the United States (US) and COVID-19 basic reproduction ratio R 0 – a dimensionless epidemic measure of the rapidity of disease spread through a population. We inferred state-level R 0 values using a state-of-the-art susceptible, exposed, infected, and recovered (SEIR) model initialized with COVID-19 epidemiological data corresponding to the period March 2–April 30. This period was characterized by a rapid surge in COVID-19 cases across the US states, implementation of strict social distancing measures, and a significant drop in outdoor air pollution. We find that an increase of 1 μg/m3 in PM 2.5 levels below current national ambient air quality standards associates with an increase of 0.25 in R 0 (95% CI: 0.048–0.447). A 10% increase in secondary inorganic composition, sulfate-nitrate-ammonium, in PM 2.5 associates with ≈10% increase in R 0 by 0.22 (95% CI: 0.083–0.352), and presence of black carbon (soot) in the ambient environment moderates this relationship. We considered several potential confounding factors in our analysis, including gaseous air pollutants and socio-economical and meteorological conditions. Our results underscore two policy implications – first, regulatory standards need to be better guided by exploring the concentration-response relationships near the lower end of the PM 2.5 air quality distribution; and second, pollution regulations need to be continually enforced for combustion emissions that largely determine secondary inorganic aerosol formation. Unlabelled Image • Long-term air pollution renders a population more susceptible to COVID-19. • Exposure to PM 2.5 associates with COVID-19 basic reproduction ratio (R 0) in the US. • R 0 and PM 2.5 association is prominent for PM 2.5 concentrations below NAAQS standard. • Secondary inorganic composition in PM 2.5 impacts R 0 significantly. • Black carbon (soot) moderates the relation between secondary inorganic composition and R 0. [ABSTRACT FROM AUTHOR]

Limited evidence is available on the associations of long-term exposure to various fine particulate matter (PM 2.5) constituents with sub-clinical outcomes of cardiovascular disease (CVD) in China. We aimed to explore the associations of PM 2.5 and its constituents with blood pressure (BP), fasting glucose, and cardiac electrophysiological (ECG) properties based on a national survey of 5852 Chinese adults, who participated in the Sub-Clinical Outcome of Polluted Air study, from July 2017 to March 2019. Annual residential exposure to PM 2.5 and its constituents of each subject was predicted by a satellite-based mode. We assessed the associations between five main constituents [organic matter (OM), black carbon (BC), sulfate (SO 4 2−), nitrate (NO 3 −), ammonium (NH 4 +)] of PM 2.5 and systolic BP (SBP), diastolic BP (DBP), fasting glucose, and ECG measurements (PR, QRS, QT, and QTc interval) using multivariable linear regression models. Long-term PM 2.5 exposure was significantly associated with increased levels of fasting glucose, DBP, and ECG measurements. An IQR increase in OM (8.2 μg/m3) showed considerably stronger associations with an elevated fasting glucose of 0.39 mmol/L (95%CI confidence interval: 0.28, 0.49) compared with other PM 2.5 constituents. Meanwhile, an IQR increase in NO 3 −, NH 4 + and OM had stronger associations with DBP and ECG parameters compared with BC and SO 4 2−. This nationwide multi-center study in China indicated that some constituents (i.e., OM, NO 3 −, and NH 4 +) might be mainly responsible for the association of PM 2.5 with sub-clinical outcomes of CVD including BP, fasting glucose, and ECG measurements. Unlabelled Image • Few studies explore the associations of PM 2.5 constituents with sub-clinical outcomes. • PM 2.5 constituents were significantly associated with sub-clinical outcomes. • Some constituents may dominate the association of PM 2.5 with sub-clinical outcomes. [ABSTRACT FROM AUTHOR]

• Long-term exposure to ambient PM 2.5 increased the risks of childhood pneumonia. • NO 3 −, NH 4 + and OM dominated the health effects of PM 2.5 on pneumonia in children. • Children in urban areas and breastfeeding < 6 months had higher risks of pneumonia. • Children aged < 5 yrs enhanced the risk of pneumonia when exposure to ambient PM 2.5. The long-term effects of ambient PM 2.5 and chemical constituents on childhood pneumonia were still unknown. A cross-sectional study was conducted in 30,315 children in the China Children, Homes, Health (CCHH) project, involving 205 preschools in six cities in China, to investigate the long-term effects of PM 2.5 constituents on lifetime-ever diagnosed pneumonia. Information on the lifetime-ever pneumonia and demographics were collected by validated questionnaires. The lifetime annual average ambient PM 2.5 , ozone and five main PM 2.5 constituents, including SO 4 2−, NO 3 −, NH 4 +, organic matter (OM) and black carbon (BC), were estimated according to preschool addresses by a combination of satellite remote sensing, chemical transport modeling and ground-based monitors. The prevalence of lifetime-ever diagnosed pneumonia was 34.5% across six cities and differed significantly among cities (p = 0.004). The two-level logistic regression models showed that the adjusted odds ratio for PM 2.5 (per 10 µg/m3) and its constituents (per 1 µg/m3)-SO 4 2−, NO 3 −, NH 4 +, and OM were 1.12 (95% CI:1.07–1.18), 1.02 (1.00–1.04), 1.06 (1.04–1.09), 1.05 (1.03–1.07) and 1.09 (1.06–1.12), respectively. Children in urban area, aged < 5 years and breastfeeding time < 6 months enhanced the risks of pneumonia. Our study provided robust results that long-term levels of ambient PM 2.5 and its constituents increased the risk of childhood pneumonia, especially NH 4 +, NO 3 − and OM. [ABSTRACT FROM AUTHOR]

• Satellite-based and chemical transport modelling products were applied in this study. • It's the first to establish the mediation model of PM 2.5 , PROM and gestational age. • PROM mediated the relationship between PM 2.5 exposure and gestational age. • Preconception exposure to PM 2.5 and components were considered in this research. The associations between maternal exposure to fine particles with aerodynamic diameter ≤ 2.5 μm (PM 2.5) and gestational age as well as premature rupture of membranes (PROM) remain unclear. Few studies have focused on preconception exposure and components of fine particles in China. A total of 1715 pregnant women were enrolled at hospitals affiliated with Nanjing Medical University from 2014 to 2015. Personal exposure to PM 2.5 was estimated from preconception to the first trimester. Gestational age and PROM were investigated to explore their associations with PM 2.5 and its components. From 12 weeks before conception to the end of the first trimester, the gestational age was reduced by 0.89 days (95% CI: −1.37, −0.40) per 10 μg/m3 increment in PM 2.5 exposure. After the exposure period was separated into two groups, PM 2.5 exposure reduced the gestational age by 0.35 days (95% CI: −0.59, −0.11) in the 12 weeks before pregnancy. With maternal exposure to PM 2.5 early in the first trimester, gestational age was reduced by 0.62 days (95% CI: −1.09, −0.14). After mediation analysis, we found that PROM mediated the association between PM 2.5 and gestational age from preconception to the first trimester. Components analysis indicated that exposure to black carbon, organic matter, and nitrate increased the risk of PROM and decreased gestational age. Exposure to PM 2.5 as well as some components of PM 2.5 before and during early pregnancy was associated with PROM and gestational age. PROM might be a potential mediator in associations between PM 2.5 as well as various components and gestational age. [ABSTRACT FROM AUTHOR]

Ambient air pollution has been associated with childhood cancer. However, little is known about the possible impact of ambient ultrafine particles (<0.1 μm) (UFPs) on childhood cancer incidence. This study aimed to evaluate the association between prenatal and childhood exposure to UFPs and development of childhood cancer. We conducted a population-based cohort study of within-city spatiotemporal variations in ambient UFPs across the City of Toronto, Canada using 653,702 singleton live births occurring between April 1, 1998 and March 31, 2017. Incident cases of 13 subtypes of paediatric cancers among children up to age 14 were ascertained using a cancer registry. Associations between ambient air pollutant concentrations and childhood cancer incidence were estimated using random-effects Cox proportional hazards models. We investigated both single- and multi-pollutant models accounting for co-exposures to PM 2.5 and NO 2. A total of 1,066 childhood cancers were identified. We found that first trimester exposure to UFPs (Hazard Ratio (HR) per 10,000/cm3 increase = 1.13, 95% CI: 1.03–1.22) was associated with overall cancer incidence diagnosed before 6 years of age after adjusting for PM 2.5 , NO 2 , and for personal and neighborhood-level covariates. Association between UFPs and overall cancer incidence exhibited a linear shape. No statistically significant associations were found for specific cancer subtypes. Ambient UFPs may represent a previously unrecognized risk factor in the aetiology of cancers in children. Our findings reinforce the importance of conducting further research on the effects of UFPs given their high prevalence of exposure in urban areas. [ABSTRACT FROM AUTHOR]

• This is a retrospective cohort study based on a national multi-center survey. 54,517 pregnant women from 55 hospitals in 24 provinces were included in the final analysis; • A combined geoscience-statistical model was applied to estimate the exposure concentration of PM 2.5 and its components; • We used a generalized mixed model to estimate the associations, and identified several components with higher risks. • We conducted the model analysis across different exposure windows and found that the second trimester is a relatively sensitive window. Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM 2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China. The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM 2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders. A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM 2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01–1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05–1.23), black carbon (aOR = 1.15; 95%CI: 1.07–1.25) and nitrate (aOR = 1.13; 95%CI: 1.02–1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM 2.5 mass and accounting for multi-collinearity. Exposure to PM 2.5 in 2nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association. [ABSTRACT FROM AUTHOR]

• We investigated the effects of PM 2.5 exposure on renal function among pregnant women. • Exposure to PM 2.5 and its chemical constituents is positively associated with urea nitrogen (UN) and uric acid (UA). • Exposure to PM 2.5 and its chemical constituents is negatively associated with estimated glomerular filtration rate (eGFR). • PM 2.5 exposure is associated with reduced renal function among pregnant women. Fine particulate matter (PM 2.5) is the most serious environmental threat worldwide. The nephrotoxicity of PM 2.5 has been demonstrated in older adults, but no study has addressed the impacts of PM 2.5 exposure on renal function in pregnant women, who are recognized to be vulnerable and susceptible to PM 2.5 exposure. To evaluate whether exposures to PM 2.5 total mass and its chemical constituents were associated with reduced renal function among pregnant women in China. We measured serum concentrations of urea nitrogen (UN), uric acid (UA) and creatinine for 10,052 pregnant women in Shanghai, China. Exposures to PM 2.5 total mass and its 5 key chemical constituents during the whole pregnancy and each trimester of pregnancy was represented by satellite-based models. Exposures to PM 2.5 total mass and its chemical constituents of organic matter (OM), black carbon (BC), nitrate (NO 3 −) and ammonium (NH 4 +) were positively associated with serum levels of UN and UA, and negatively associated with estimated glomerular filtration rate (eGFR). An interquartile rang (IQR) increase in PM 2.5 total mass, OM, BC, NO 3 – and NH 4 + exposure in third trimester was associated with 1.33 (β = -1.33, 95% CI, −1.79, −0.87), 1.67 (β = -1.67, 95% CI, −2.26, −1.07), 1.29 (β = -1.29, 95% CI,-1.89, −0.70), 1.16 (β = -1.16, 95% CI,-1.66, −0.65) and 0.76 (β = -0.76, 95% CI, −1.08, −0.44) mL/min/1.73 m2 decrease in eGFR, respectively. We concluded that exposures to PM 2.5 during pregnancy were associated with decreased renal function among pregnant women. [ABSTRACT FROM AUTHOR]

• Air pollution was associated with the incidence of diabetes, in particular NO 2. • Air pollution was also associated with cardiovascular and diabetes mortality among persons with prevalent diabetes. • The strongest associations were observed between NO 2 and diabetes mortality. • Results may suggest that traffic-related pollution has the greatest effect on outcomes of diabetes. Growing evidence implicates ambient air pollutants in the development of major chronic diseases and premature mortality. However, epidemiologic evidence linking air pollution to diabetes remains inconclusive. This study sought to determine the relationships between selected air pollutants (nitrogen dioxide [NO 2 ], fine particulate matter [PM 2.5 ], ozone [O 3 ], and oxidant capacity [Ox; the redox-weighted average of O 3 and NO 2 ]) and the incidence of diabetes, as well as the risk of cardiovascular or diabetes mortality among individuals with prevalent diabetes. We followed two cohorts, which included 4.8 million Ontario adults free of diabetes and 452,590 Ontario adults with prevalent diabetes, from 2001 to 2015. Area-level air pollution exposures were assigned to subjects' residential areas, and outcomes were ascertained using health administrative data with validated algorithms. We estimated hazard ratios for the association between each air pollutant and outcome using Cox proportional hazards models, and modelled the shape of the concentration-response relationships. Over the study period, 790,461 individuals were diagnosed with diabetes. Among those with prevalent diabetes, 26,653 died from diabetes and 64,773 died from cardiovascular diseases. For incident diabetes, each IQR increase in NO 2 had a hazard ratio of 1.04 (95% CI: 1.03–1.05). This relationship was relatively robust to all sensitivity analyses considered, and exhibited a near-linear shape. There were also positive associations between incident diabetes and PM 2.5 , O 3 , and Ox, but these estimates were somewhat sensitive to different models considered. Among those with prevalent diabetes, almost all pollutants were associated with increased diabetes and cardiovascular mortality risk. The strongest association was observed between diabetes mortality and exposure to NO 2 (HR = 1.08, 95% CI: 1.02–1.13). Selected air pollutants, especially NO 2 , were linked to an increased risk of incident diabetes, as well as risk of cardiovascular or diabetes mortality among persons with prevalent diabetes. As NO 2 is frequently used as a proxy for road traffic exposures, this result may indicate that traffic-related air pollution has the strongest effect on diabetes etiology and survival after diabetes development. [ABSTRACT FROM AUTHOR]

Twin growth discordance is one of the leading causes of perinatal mortality in twin pregnancies. Whether prenatal exposure to fine particle (PM 2.5) air pollution is associated with twin growth discordance have not been studied yet. To evaluate the associations of prenatal exposure to PM 2.5 and its chemical constituents with twin growth discordance. This study included 1917 twin pairs and their mothers drawn from a previous twin birth cohort at the Shanghai First Maternity and Infant hospital in Shanghai, China. Exposure to PM 2.5 total mass and 6 key chemical constituents during the whole pregnancy and each trimester of pregnancy was represented by satellite-based models. Maternal exposures to PM 2.5 total mass and chemical constituents of sulfate (SO 4 2−) and ammonium (NH 4 +) during the third trimester were significantly associated with increased within-pair birth weight difference and intertwin birth weight discordance. The within-pair birth weight difference increased by 30.6 g (β = 30.6, 95% CI, 4.4–56.9), 19.2 g (β = 19.2, 95% CI, 0.2–38.1) and 33.2 g (β = 33.2, 95% CI, 7.9–58.6) for an IQR increase in PM 2.5 total mass, SO 4 2− and NH 4 + exposure, respectively. While the intertwin birth weight discordance increased by 1.3% (β = 1.3, 95% CI, 0.3–2.2), 0.9% (β = 0.9, 95% CI, 0.2–1.6) and 1.4% (β = 1.4, 95% CI, 0.4–2.3) for the same exposure metrics. Moreover, higher SO 4 2− and NH 4 + exposure was also associated with increased risk of twin growth discordance in linear dose-response manners. Compared to the lowest quartile of SO 4 2− (OR = 2.51, 95% CI, 1.08–5.82) and NH 4 + (OR = 2.97, 95% CI, 1.16–7.58) exposure, the odds of twin growth discordance were doubled in highest quartile of exposure. Our results suggest that fine particle air pollution may be a risk factor for twin growth discordance. Late pregnancy seems to be a critical window for the effects of PM 2.5 exposure on fetal growth in twins. • We investigated effects of PM 2.5 and its chemical constituents exposure on fetal growth in twins. • Exposure to PM 2.5 total mass, SO 4 2- and NH 4 + is associated with increased risk of twin growth discordance. • Late pregnancy is a critical window for the effects of PM 2.5 exposure on fetal growth in twins. [ABSTRACT FROM AUTHOR]

Long-term exposure to ambient air pollution has been linked to cardiovascular mortality, but the associations with incidence of major cardiovascular diseases are not fully understood, especially at low concentrations. We aimed to investigate the associations between exposure to fine particulate matter (PM 2.5), nitrogen dioxide (NO 2), ozone (O 3), redox-weighted average of NO 2 and O 3 (O x) and incidence of congestive heart failure (CHF) and acute myocardial infarction (AMI). Our study population included all long-term residents aged 35–85 years who lived in Ontario, Canada, from 2001 to 2015 (~5.1 million). Incidence of CHF and AMI were ascertained from validated registries. We assigned estimates of annual concentrations of pollutants to the residential postal codes of subjects for each year during follow-up. We estimated hazard ratios (HRs) and 95% CIs for each pollutant separately using Cox proportional hazards models. We examined the shape of concentration-response associations using shape-constrained health impact functions. From 2001 to 2015, there were 422,625 and 197,628 incident cases of CHF and AMI, respectively. In the fully adjusted analyses, the HRs of CHF corresponding to each interquartile range increase in exposure were 1.05 (95% CI: 1.04–1.05) for PM 2.5 , 1.02 (95% CI: 1.01–1.04) for NO 2 , 1.03 (95% CI: 1.02–1.03) for O 3 , and 1.02 (95% CI: 1.02–1.03) for O x, respectively. Similarly, exposure to PM 2.5 , O 3 , and O x were positively associated with AMI. The concentration-response relationships were different for individual pollutant and outcome combinations (e.g., for PM 2.5 the relationship was supralinear with CHF, and linear with AMI). • PM 2.5 , NO 2 , O 3 , and O x were associated to increased congestive heart failure incidence. • Exposure to PM 2.5 , O 3 , and O x was associated with acute myocardial infarction (AMI). • A near-linear concentration-response relationship was found for PM 2.5 and AMI. • Non-linear patterns were observed for other pollutant and outcome combinations. • There was some evidence of effect modification by age and income. [ABSTRACT FROM AUTHOR]

India faces one of the highest disease burdens from air pollution in the world, with an estimated 100% of the population living in areas with PM 2.5 concentrations above the World Health Organization Guideline (10 μg/m3 annual average). With development and population growth, increases in ambient air pollution are anticipated. Combined with an aging population and increasing burden of chronic diseases, ambient air pollution will remain a concern for India well into the current century. Air quality measurements make critical contributions to the identification and prioritization of sources and locations of greatest concern, benchmarking against standards and guidelines, and in the evaluation of effectiveness of actions to reduce emissions. We compare the density of India's monitoring network with that of comparator countries and find large differences. For example, given the ~200 PM 2.5 monitoring sites in operation during the 2010–2016 period, we find that India's monitor density of ~0.14 monitors/million persons (1 monitor for every 6.8 million people) is well below that of other highly populated countries such as China (1.2 monitors/million persons), the USA (3.4 monitors/million persons), Japan (0.5 monitors/million persons), Brazil (1.8) and most European countries (2–3 monitors/million persons). To address these gaps between India and monitor densities of comparator countries will require 1600–4000 monitors (1.2–3 monitors/million persons) at an estimated capital (annual operating) cost of US $212–540 ($106–270) million. Even at these densities, only relatively basic information on common air pollutants at high temporal, but limited spatial, resolution would be available. Small-scale variability in air pollution levels within urban areas would not be well-characterized, nor would there be information on chemical constituents useful for evaluating and improving simulations and forecasts, or for characterizing source contributions. As a sufficiently dense traditional network is developed over time, the potential for an integrated monitoring framework to serve as a near-term complement to a traditional network is assessed. In this design, a smaller number of traditional monitoring sites would be linked to a single advanced surface monitoring station in each of ~11 airsheds identified as a minimal number for India. These sites would combine measurement of chemical speciation of particulate matter with measurements of aerosol scatter and aerosol optical depth to link measurements with global and regional satellite-based estimates. In turn, the advanced and traditional sites could serve as calibration nodes for low-cost sensor networks designed to complement periodic mobile monitoring campaigns and/or land use regression models, to provide high spatial and temporal resolution. Such a framework could be established at a substantially reduced cost relative to that of a traditional networks, subject to specific design and complexity considerations. The same general approach may also be applicable to the many other countries with limited or no air quality monitoring and where estimates suggest air quality is a concern. • India faces extreme air pollution and related disease burden. • Monitor density in India is low relative to comparator countries. • Satellite-derived estimates, speciation and spatial monitoring can be integrated. • An integrated monitoring framework can complement a developing traditional network. [ABSTRACT FROM AUTHOR]

Cardiovascular malformations account for nearly one-third of all congenital anomalies, making these the most common type of birth defects. Little is known regarding the influence of ambient ultrafine particles (<0.1 μm) (UFPs) on their occurrence. This population-based study examined the association between prenatal exposure to UFPs and congenital heart defects (CHDs). A total of 158,743 singleton live births occurring in the City of Toronto, Canada between April 1st 2006 and March 31st 2012 were identified from a birth registry. Associations between exposure to ambient UFPs between the 2nd and 8th week post conception when the foetal heart begins to form and CHDs identified at birth were estimated using random-effects logistic regression models, adjusting for personal- and neighbourhood-level covariates. We also investigated multi-pollutant models accounting for co-exposures to PM 2.5, NO 2 and O 3. A total of 1468 CHDs were identified. In fully adjusted models, UFP exposures during weeks 2 to 8 of pregnancy were not associated with overall CHDs (Odds Ratio (OR) per interquartile (IQR) increase = 1.02, 95% CI: 0.96–1.08). When investigating subtypes of CHDs, UFP exposures were associated with ventricular septal defects (Odds Ratio (OR) per interquartile (IQR) increase = 1.13, 95% CI: 1.03–1.33), but not with atrial septal defect (Odds Ratio (OR) per interquartile (IQR) increase = 0.89, 95% CI: 0.74–1.06). This is the first study to evaluate the association between prenatal exposure to UFPs and the risk of CHDs. UFP exposures during a critical period of embryogenesis were associated with an increased risk of ventricular septal defect. • Ambient air pollution in pregnancy increases the risk of congenital heart defects. • UFP exposures were not associated with overall congenital heart defects. • UFP exposures were associated with risk of ventricular septal defect. [ABSTRACT FROM AUTHOR]

Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms have rarely been compared in terms of their predictive ability. This study compared 16 algorithms to predict annual average fine particle (PM 2.5) and nitrogen dioxide (NO 2) concentrations across Europe. The evaluated algorithms included linear stepwise regression, regularization techniques and machine learning methods. Air pollution models were developed based on the 2010 routine monitoring data from the AIRBASE dataset maintained by the European Environmental Agency (543 sites for PM 2.5 and 2399 sites for NO 2), using satellite observations, dispersion model estimates and land use variables as predictors. We compared the models by performing five-fold cross-validation (CV) and by external validation (EV) using annual average concentrations measured at 416 (PM 2.5) and 1396 sites (NO 2) from the ESCAPE study. We further assessed the correlations between predictions by each pair of algorithms at the ESCAPE sites. For PM 2.5 , the models performed similarly across algorithms with a mean CV R2 of 0.59 and a mean EV R2 of 0.53. Generalized boosted machine, random forest and bagging performed best (CV R2~0.63; EV R2 0.58–0.61), while backward stepwise linear regression, support vector regression and artificial neural network performed less well (CV R2 0.48–0.57; EV R2 0.39–0.46). Most of the PM 2.5 model predictions at ESCAPE sites were highly correlated (R2 > 0.85, with the exception of predictions from the artificial neural network). For NO 2 , the models performed even more similarly across different algorithms, with CV R2s ranging from 0.57 to 0.62, and EV R2s ranging from 0.49 to 0.51. The predicted concentrations from all algorithms at ESCAPE sites were highly correlated (R2 > 0.9). For both pollutants, biases were low for all models except the artificial neural network. Dispersion model estimates and satellite observations were two of the most important predictors for PM 2.5 models whilst dispersion model estimates and traffic variables were most important for NO 2 models in all algorithms that allow assessment of the importance of variables. Different statistical algorithms performed similarly when modelling spatial variation in annual average air pollution concentrations using a large number of training sites. • Multiple statistical algorithms with very different assumptions were compared. • Despite the difference in modeling frameworks, predictions among the models exhibit generally good agreement. • The use of an external evaluation dataset strengthens evaluation by cross-validation. [ABSTRACT FROM AUTHOR]

Atmospheric transport of fine particulate matter (PM 2.5 ), the leading environmental risk factor for public health, is estimated to exert substantial transboundary effects at present. During the past several decades, human-produced pollutant emissions have undergone drastic and regionally distinctive changes, yet it remains unclear about the resulting global transboundary health impacts. Here we show that between 1950 and 2014, global anthropogenic PM 2.5 has led to 185.7 million premature deaths cumulatively, including about 14% from transboundary pollution. Among four country groups at different affluence levels, on a basis of per capita contribution to transboundary mortality, a richer region tends to exert severer cumulative health externality, with the poorest bearing the worst net externality after contrasting import and export of pollution mortality. The temporal changes in transboundary mortality and cross-regional inequality are substantial. Effort to reduce PM 2.5 -related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality., Competing Interests: Conflict of interest The authors declare that they have no conflict of interest., (Copyright © 2021 Science China Press. Published by Elsevier B.V. All rights reserved.)