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Air pollution is a rapidly growing major health concern around the world. Atmospheric particulate matter that has a diameter of less than 2.5 µm (PM2.5) refers to an air pollutant composed of particles and chemical compounds that originate from various sources. While epidemiological studies have established the association between PM2.5 exposure and cardiovascular diseases, the precise cellular and molecular mechanisms by which PM2.5 promotes cardiovascular complications are yet to be fully elucidated. In this review, we summarize the various sources of PM2.5, its components, and the concentrations of ambient PM2.5 in various settings. We discuss the experimental findings to date that evaluate the potential adverse effects of PM2.5 on cardiovascular homeostasis and function, and the possible therapeutic options that may alleviate PM2.5-driven cardiovascular damage.

Black Americans in Louisiana are disproportionately dying from COVID-19, and environmental disparities may be contributing to this injustice. While Black communities in Louisiana's industrialized r...

Atmospheric aerosols are one of the main pollutants which are harmful to human health and environment. Atmospheric aerosols emitted from different sources are of different sizes and depending upon the size of the aerosol particle, it deposits in different parts of the body and cause varying health problems. Fine Particulate (PM2.5) is associated with more severe health consequences than coarse particulate (PM10) which might be short-term acute symptoms like coughing, shortness of breath, wheezing, respiratory diseases, to more serious problems like asthma, Chronic Obstructive Pulmonary Disease (COPD), bronchitis, pneumonia and long-term chronic irritation and inflammation of the respiratory tract, which may eventually result in lung cancer. Inhalation of ultrafine particles (

Highlights • A risk-benefit analysis was performed to estimate the optimal outdoor moderate physical activity (MPA) duration under varying particulate matter (PM2.5) concentrations. • An inverse nonlinear relationship was identified between optimal MPA duration and background PM2.5 concentration levels. • The relationship between optimal MPA duration and background PM2.5 concentration levels was stronger when exercising at a location closer to a source of air pollution. • Compared to the general adult population, adults aged 60 years and older had substantially steeper curves. • The health benefit of outdoor MPA by far outweighs the health risk of PM2.5 pollution for the global average urban background concentration., Objective Outdoor physical activity (PA) brings important health benefits, but exposure to polluted air increases health risks. This study aimed to quantify the tradeoff of PA under fine particulate matter (PM2.5) air pollution by estimating the optimal PA duration under various pollution levels. Methods A risk-benefit analysis was performed to estimate the optimal outdoor moderate PA (MPA) duration under varying PM2.5 concentrations. Results An inverse nonlinear relationship was identified between optimal MPA duration and background PM2.5 concentration levels. When background PM2.5 concentration increased to 186 µg/m3, the optimal outdoor MPA duration decreased to 2.5 h/week, the minimum level recommended by current PA guidelines. When background PM2.5 concentration further increased to 235 µg/m3, the optimal outdoor MPA duration decreased to 1 h/week. The relationship between optimal MPA duration and background PM2.5 concentration levels was stronger when exercising at a location closer to a source of air pollution. Compared to the general adult population, adults aged 60 years and older had substantially steeper curves—the optimal outdoor MPA duration decreased to 2.5 h/week when background PM2.5 concentration reached 45 µg/m3. Conclusion The health benefit of outdoor MPA by far outweighs the health risk of PM2.5 pollution for the global average urban background concentration (22 μg/m3). This modeling study examined a single type of air pollutant and suffered from measurement errors and estimation uncertainties. Future research should examine other air pollutants and indoor PA, incorporate short- and mid-term health effects of MPA and air pollution into the risk-benefit analysis, and provide estimates specific for high-risk subgroups., Graphical Abstract Image, graphical abstract

Abstrct A composite Air Health Index (AHI) is helpful for separately emphasizing the health risks of multiple stimuli and communicating the overall risks of an adverse atmospheric environment to the public. We aimed to establish a new AHI by integrating daily mortality risks due to air pollution with those due to non-optimum temperature in China. Based on the exposure-response (E-R) coefficients obtained from time-series models, the new AHI was constructed as the sum of excess mortality risk associated with air pollutants and non-optimum temperature in 272 Chinese cities from 2013 to 2015. We examined the association between the “total AHI” (based on total mortality) and total mortality, and further compared the ability of the “total AHI” to predict specific cardiopulmonary mortality with that of “specific AHIs” (based on specific mortalities). On average, air pollution and non-optimum temperature were associated with 28.23% of daily excess mortality, of which 23.47% was associated with non-optimum temperature while the remainder was associated with fine particulate matter (PM2.5) (1.12%), NO2 (2.29%,), and O3 (2.29%). The new AHI uses a 10-point scale and shows an average across all 272 cities of 6 points. The E-R curve for AHI and mortality is approximately linear, without any thresholds. Each one unit increase in “total AHI” is associated with a 0.84% increase in all-cause mortality and 1.01%, 0.98%, 1.02%, 1.66%, and 1.71% increases in cardiovascular disease, coronary heart disease, stroke, respiratory diseases, and chronic obstructive pulmonary disease mortality, respectively. Cause-specific mortality risk estimates using the “total AHI” are similar to those predicted by “specific AHIs”. In conclusion, the “total AHI” proposed herein could be a promising tool for communicating health risks related to exposure to the ambient environment to the public.

Background We investigated the change of coronary atherosclerosis with long-term exposure to fine particulate matter of aerodynamic diameter Methods Subjects undergoing serial CCTAs between January 2007 and December 2017 (n = 3,127) were analyzed. Each individual's cumulative amount of PM2.5 exposure between the two CCTAs was evaluated by Kriging interpolation and zonal analysis, considering the time interval between the two CCTAs. The main outcome was progression of coronary artery calcium (CAC) with additional semiquantitative analysis on the changes in the severity and composition of atherosclerotic plaques. Results The CAC scores increased by 30.8 Agatston units per-year under a median PM2.5 concentration 24.9μg/m3 and tended to increase with the cumulative amount of PM2.5 exposure (r = 0.321, p Conclusions Cumulative exposure to air pollution is associated with the progression of diffuse coronary calcification, the importance of which may be more significant than other traditional cardiovascular risk factors. Further investigations into the causality between PM2.5 and coronary atherosclerosis are warranted to improve global cardiovascular health.

tabira has in its territory the largest complex of opencast mining in the world, located close to residential areas of the city. The air quality monitoring network installed in the city is the main source of particulate matter (PM) emission data. However, these air quality stations only cover the areas near the mines and do not measure fine particulate matter (PM2.5). Thus, a first field campaign was carried out to characterize PM in the city and to compare high volume data from air quality stations with the dichotomous air sampler data. Results of trajectories’ cluster analysis showed a long-range transport of aerosols during the sampling days from northeast (84% of the trajectories), east-southeast (12%), and south-southwest (3%) directions. Regarding the meteorological conditions during the sampling days, negative correlations were seen between coarse particulate matter (PM10) from mostly air quality stations and all meteorological parameters (but temperature). Results of the X-ray fluorescence and principal component analyses showed that the main trace elements in the coarse (PM2.5-10) and fine modes (PM2.5) are iron and sulfur, associated with emissions from mining activities, air mass transport from regional iron and steelmaking industry activities, vehicle emissions, local and regional biomass burning, and natural biogenic emissions. This work is the first assessment of source apportionment done in the city. Comparisons with other studies, for some large metropolitan areas, showed that Itabira has comparable contributions of sulfur, iron and elements such as copper, selenium, chromium, nickel, vanadium and lead.

Atmospheric transport of fine particulate matter (PM2.5), 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 PM2.5 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 PM2.5-related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality.

Fine particulate matter (PM2.5) pollution can cause serious public health problems worldwide. A novel geographically and temporally weighted neural network constrained by global training (GC-GTWNN) is proposed in this article for the remote sensing estimation of surface PM2.5. The global neural network (NN) is trained to learn the overall effect of the influencing variables on surface PM2.5, and the local geographically and temporally weighted NN (GTWNN) addresses the spatiotemporal heterogeneity of the relationship between PM2.5 and the influencing variables. Specifically, a global NN is trained with all samples collected from the entire study domain and period. Then, initialized with the global NN, the GTWNN models are built for each location and time and fine-tuned via spatiotemporally localized samples. Meanwhile, the geographically weighted loss function is designed for GTWNN. The proposed GC-GTWNN modeling is tested with a case study across China, which integrates satellite aerosol optical depth, surface PM2.5 measurements, and auxiliary variables. Cross-validation results indicate that a remarkable improvement is observed from the global NN to GC-GTWNN modeling (R² value increasing from 0.49 to 0.80), and GC-GTWNN modeling also notably outperforms the conventionally popular PM2.5 estimation models.

Private vehicles are high dominant mode of transport in Salem, India, since there is no any commuter personal exposure information on air pollution. This is the first pollutant exposure study in different private vehicles across Salem city. In this study, critical air pollutant of fine particulate matter, PM2.5, was measured. In addition, accumulation of CO2, concentration also assessed in closed vehicles. The measured vehicles were motorcycle, auto rickshaw, hatchback car, sedan car, sports utility vehicle car, and multi utility vehicle van. The four-wheeler (car and van) in-vehicle concentrations were assessed under four different ventilation conditions. Student?s t-test statistical analysis was carried out to determine the significance exposure level between the vehicles. It is observed that there is no statistically significant difference (p ? 0.05) between the vehicles of motorcycle and sedan, motorcycle and multi utility vehicle van, and auto rickshaw and sports utility vehicle for PM2.5 pollutant. A regression analysis shows a strong negative correlation between PM2.5 and CO2 concentration in an air-conditioning cars.

Air pollution is one of the major risk factors contributing to adverse public health outcomes worldwide. Fine particulate matter (PM2.5) has been repeatedly associated with increased risk of cardiovascular events, including heart attacks. Because PM2.5 is unequally distributed with elevated concentrations near high-traffic and industrial zones, PM2.5 is an environmental justice issue of major public health concern. In this study, we reviewed the relationship between PM2.5, emergency visits due to heart attacks, and environmental justice in San Diego County using data from CalEnviroScreen 3.0. Our results indicate that PM2.5, diesel PM emissions, and emergency visits due to heart attacks are weakly, but positively correlated (r=0.3, R2

We assessed the oxidative potential (OP) of both water-soluble and methanol-soluble fractions of ambient fine particulate matter (PM2.5) in the Midwestern United States. A large set of PM2.5 samples (N=241) was collected from five sites set up in different environments, i.e., urban, rural, and roadside, in Illinois, Indiana, and Missouri during May 2018–May 2019. Five acellular OP endpoints, including the consumption rate of ascorbic acid and glutathione in a surrogate lung fluid (SLF) (OPAA and OPGSH, respectively), dithiothreitol (DTT) depletion rate (OPDTT), and ⚫OH generation rate in SLF and DTT (OPOH−SLF and OPOH−DTT, respectively), were measured for all PM2.5 samples. PM2.5 mass concentrations in the Midwestern US as obtained from these samples were spatially homogeneously distributed, while most OP endpoints showed significant spatiotemporal heterogeneity. Seasonally, higher activities occurred in summer for most OP endpoints for both water- and methanol-soluble extracts. Spatially, the roadside site showed the highest activities for most OP endpoints in the water-soluble extracts, while only occasional peaks were observed at urban sites in the methanol-soluble OP. Most OP endpoints showed similar spatiotemporal trends between mass- and volume-normalized activities across different sites and seasons. Comparisons between two solvents (i.e., water and methanol) showed that methanol-soluble OP generally had higher activity levels than corresponding water-soluble OP. Site-to-site comparisons of OP showed stronger correlations for methanol-soluble OP compared to water-soluble OP, indicating a better extraction of water-insoluble redox-active compounds from various emission sources into methanol. We found a weak correlation and inconsistent slope values between PM2.5 mass and most OP endpoints. Moreover, the poor to moderate intercorrelations among different OP endpoints indicate different mechanisms of OP represented by these endpoints and thus demonstrate the rationale for analyzing multiple acellular endpoints for a better and more comprehensive assessment of OP.

Annual global satellite-based estimates of fine particulate matter (PM2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998-2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5-3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM2.5 concentrations exceed 90 μg/m3, with local concentrations of approximately 200 μg/m3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 μg/m3/year, with decreases beginning 2-3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM2.5. The evaluation of uncertainty for agglomerated values indicates that hybrid PM2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.

BACKGROUND The health effects of fine particulate matter (PM2.5) may be worse at higher temperatures. OBJECTIVE To investigate temperature's effect on PM2.5-mortality/morbidity associations in Lima, Peru. METHODS Time-series regressions relating PM2.5 and temperature to mortality and emergency room (ER) visits during 2010-2016. Daily PM2.5 levels (assigned to 40 Lima districts) and daily maximum temperature (Lima-wide) were estimated based on ground monitors, remote sensing, and modeling. We analyzed all-cause, cardiovascular (ICD codes I00-I99), and respiratory (ICD codes J00-J99) mortality, and cardiovascular and respiratory causes for ER visits. RESULTS The average PM2.5 concentration was 20.9 µg/m3 (IQR 17.5-23.5). The mean daily maximum temperature was 23.8 °C (IQR 20.8-26.9). PM2.5's effect on all-cause, respiratory, and circulatory disease mortality was significantly (p

POSITION DU PROBLeME: Le confinement mis en place au deuxieme trimestre 2020 a entraine une amelioration de la qualite de l'air de Santiago, capitale et plus grande ville du Chili, caracterisee par de fortes concentrations en particules fines PM2,5 liees, en grande partie, au trafic routier. L'objectif etait de mettre en evidence une potentielle reduction des visites aux urgences pour infarctus du myocarde aigu (IDM) et des deces dus a une cardiopathie ischemique (CPI) attribuable a l'emission de PM2,5, en comparant les periodes equivalentes de 2019 et de 2020. MeTHODES: A Santiago, la surveillance de la qualite de l'air se fait grâce a neuf moniteurs situes dans neuf communes differentes : Cerro Navia, Cerrillos, El Bosque, Pudahuel, Independencia, La Florida, Quilicura, Santiago centre-ville et Las Condes (classees de la plus haute a la plus basse en matiere de pauvrete multidimensionnelle). La concentration moyenne quotidienne de PM2,5 a ete decrite avec des series temporelles, et les visites aux urgences pour IDM et les deces dus a une CPI ont ete analyses de facon trimestrielle pour chaque annee. Pour estimer l'impact de l'exces de PM2,5, les fractions de risque attribuables (FRA) pour les visites aux urgences pour IDM et les deces pour CPI ont ete calculees. ReSULTATS: La moyenne quotidienne des PM2,5 a diminue dans huit des neuf communes de Santiago. Cependant, la reduction n'a ete significative que dans trois communes. Les visites aux urgences pour IDM et les deces par CPI attribuables aux PM2,5 ont diminue legerement mais significativement dans ces trois communes. Les FRA dans les autres communes sont restees similaires a 2019. CONCLUSIONS: Une reduction significative de la FRA des PM2,5 pour les deces par CPI et les visites aux urgences d'IDM n'a ete observee que dans les communes avec une reduction significative de la concentration quotidienne moyenne de PM2,5 pendant la pandemie de COVID-19.

Fine particulate matter (PM2.5) mainly originates from combustion emissions. On-road transportation is considered one of the primary sources of PM2.5 emission. The relationship between on-road transportation and PM2.5 concentration varies temporally and spatially, and the estimation for this variation is important for policymaking. Here, we reveal the quantitative association of PM2.5 concentration with on-road transportation by the spatial panel Durbin model and the geographical and temporal weighted regression. We find that 6.17 billion kilometres (km) per km2 on-road transportation increase is associated with a 1-μg/m3 county-level PM2.5 concentration increase in the contiguous United States. On-road transportation marginally contributes to PM2.5, only 1.09% on average. Approximately 3605 premature deaths are attributed to PM2.5 from on-road transportation in 2010, and about a total of 50,223 premature deaths ascribe to PM2.5 taking 6.49% from 2003 to 2016. Our findings shed light on the necessity of the county-level policies considering the temporal and spatial variability of the relationship to further mitigate PM2.5 from on-road transportation.

Ambient fine particulate matter (PM2.5) is one of the main environmental air pollutants that is closely related to the development of lung cancer, but the mechanisms are unclear. In this study, A549 cells were exposed to ambient PM2.5 to investigate the alterations of biological behaviors, and the possible role of miR-582-3p in the effects was further explored. The findings showed that PM2.5 exposure could significantly enhance the biological behaviors of A549 cells, and promote their epithelial-mesenchymal transition (EMT) transformation, especially at relatively low doses. Over-activation of Wnt/β-catenin signaling pathway and increased expression of miR-582-3p were also found in A549 cells after PM2.5 exposure. After the knockdown of miR-582-3p in A549 cells, the effects of PM2.5 on malignant biological behavior changes, EMT, and the activation of Wnt/β-catenin signaling pathway were all significantly alleviated. Furthermore, the inhibition of Wnt/β-catenin signaling pathway also inhibited the EMT process of A549 cells, which was rescued by the overexpression of miR-582-3p. Therefore, this study showed that ambient PM2.5 can upregulate the expression of miR-582-3p, consequently activate the Wnt/β-catenin signaling pathway, and thereby enhance EMT transformation and promote the malignant biological behaviors of A549 cells. These findings provide evidence for further research into the mechanisms by which exposure to PM2.5 in the environment promotes lung cancer.

The evidence regarding the association between long-term fine particulate (PM2.5) exposure and cardiovascular disease (CVD) in developing countries is limited. This study investigated the association between long-term exposure to PM2.5 and the prevalence of CVD among middle-aged and older adults. A total of 13,484 adults ≥ 45 years of age were surveyed in China, and logistic regression models were used to examine the association between PM2.5 and the prevalence of CVD. Furthermore, stratified analyses were conducted to explore potential effect modifiers. In addition, the burden of CVD attributable to PM2.5 was estimated. The analyses revealed that PM2.5 was associated with CVD, with an adjusted odds ratio (OR) of 1.18 (95% confidence interval [CI]: 1.12, 1.26) for each 10 μg/m3 increment in ambient PM2.5. Stratified analyses found that the elderly may be a vulnerable population. It was further estimated that approximately 20.27% (95% CI: 11.86%, 29.96%) of CVD cases could be attributable to PM2.5. This nationwide study confirmed that long-term exposure to PM2.5 was associated with an increased prevalence of CVD in China.

Fine particulate matter (PM2.5) has been linked to cardiopulmonary disease and systemic effects in humans. However, few studies have investigated the particle bioreactivity in Chinese megacities during haze episodes. The objective of this study was to determine the contributions of chemical components in PM2.5 to particle bioreactivity in Chinese megacities during haze episodes. PM2.5 samples were collected in 14 megacities across China from 23 December 2013 to 16 January 2014. Average PM2.5 concentrations ranged 88.92~199.67 μg/m3. Organic carbon (OC), elemental carbon (EC), anions, and cations per unit of PM2.5 were linked to cellular bioreactivity (i.e., reactive oxygen species (ROS) as assessed by dichlorodihydrofluorescein diacetate (DCFH) and inflammation as assessed by interleukin (IL)-6 in A549 cells). The contributions of chemicals in PM2.5 to ROS and inflammation were examined by the Pearson correlation coefficient and random forests. These results indicated that OC, Ca2+, SO42−, Cl−, F−, K+, and NO3− contributed to ROS production, whereas OC, Cl−, EC, K+, F−, Na+, and Ca2+ contributed to inflammation. In conclusion, PM2.5-contained OC and acidic ions are important in regulation of oxidative stress and inflammation during haze episodes. Our findings suggest that severe haze PM2.5 events cause deterioration in air quality and may adversely affect human health.

Background Heavy fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) pollution events continue to occur frequently in developing countries. Objectives The authors conducted a case-crossover study aimed at exploring the association between heavy PM2.5 pollution events and hospital admission for cardiovascular diseases. Methods Hospital admissions for cardiovascular diseases were observed by Beijing Municipal Commission of Health and Family Planning Information Center from 2013 to 2017. Air pollution data were collected from the Beijing Municipal Environmental Monitoring Center. Distinct definitions were used to identify heavy and extremely heavy fine particulate pollution events. A conditional logistic regression model was used. The hospital admission burdens for cardiovascular disease were also estimated. Results A total of 2,202,244 hospital admissions for cardiovascular diseases and 222 days of extremely heavy PM2.5 pollution events (PM2.5 concentration ≥150 μg/m3) were observed. The ORs associated with extremely heavy PM2.5 pollution events lasting for 3 days or more for total cardiovascular disease, angina, myocardial infarction, ischemic stroke, and heart failure were 1.085 (95% CI: 1.077-1.093), 1.112 (95% CI: 1.095-1.130), 1.068 (95% CI: 1.037-1.100), 1.071 (95% CI: 1.053-1.090), and 1.060 (95% CI: 1.021-1.101), respectively. The numbers and days of cardiovascular disease hospital admission annually related to extremely heavy PM2.5 pollution events lasting for 1 day or more were 3,311 (95% CI: 2,969-3,655) and 37,020 (95% CI: 33,196-40,866), respectively. Conclusions Heavy and extremely heavy PM2.5 pollution events resulted in substantial increased hospital admission risk for cardiovascular disease. With higher PM2.5 concentration and longer duration of heavy PM2.5 pollution events, a greater risk of cardiovascular hospital admission was observed.

In China, natural ventilation is a common way of improving indoor air quality (IAQ) in college classrooms. However, until now, the effects of both manual airing strategies and architectural factors on IAQ in classrooms have not been well explored. The present work aimed to investigate the effect of manual airing strategies, such as opening doors and opening exterior or interior windows, on the concentrations of both carbon dioxide (CO2) and fine particulate matter (PM2.5) in classrooms using field measurements. Through simulation, the effects of floor level, room orientation and the height of interior windows on CO2 concentration were also analysed. The results of this study revealed that (1) simultaneously opening doors and exterior windows or opening the doors alone could effectively reduce the indoor CO2 concentration, but the same effect could not be achieved by opening interior windows only; (2) the indoor PM2.5 concentration was primarily affected by the level of outdoor PM2.5, and it may exceed the recommended limit by 33% when the outdoor pollution level is high, even with closed doors and windows; and (3) in winter, both floor level and classroom orientation exerted a significant influence on the indoor CO2 concentration, but the height of interior windows had no effect.

Due to the complications in the measurement of fine particulate matter (PM2.5), this paper proposes a method using lidar for assessing PM2.5. By calculating the aerosol optical depth (AOD) for MODIS, CALIPSO, and ground-based lidar, the corrected PM2.5 was predicted. The results showed that AOD and PM2.5 had a linear relationship. The linear correlation coefficient between ground-based lidar AOD and PM2.5 was 0.81, and the root-mean-square error (RMSE) and mean deviation (MD) were 24.43 and 18.41, respectively. The linear correlation coefficient between CALIPSO AOD and PM2.5 was 0.8, and its RMSE and MD were 42.91 and 33.25, respectively. The linear correlation between AOD and PM2.5 for VIIRS was approximately 0.7. This paper provides more possibilities for lidar observation and prediction of the environment.

Long-term exposure to ambient fine particulate matter (PM2.5) has slowly increased both the morbidity and mortality among Chinese people; becoming a leading problem for public health efforts. In this study, the exposure-response function was used to derive the spatial-temporal dynamics of disease burden attributable to PM2.5 pollution in China. It was found that the economic loss attributable to PM2.5 increased by 93% from 35 billion Chinese yuan to 536 billion Chinese yuan within the period of 16 years. Digging further, a substantiate level of regional differences was discovered with the disease burden being the most severe in East China and the least severe in Northwest China. This article can provide more insights for future air pollution control in China.

Background Investigations on the potential effects of ambient fine particulate matter (PM2.5) on large for gestational age (LGA) are limited. Furthermore, no study has explored weekly-specific susceptible exposure windows for small for gestational age (SGA) and LGA. This study evaluated the associations of exposure to ambient PM2.5 over the preconception and entire-pregnancy periods with risks of SGA and LGA, as well as explored critical weekly-specific exposure windows. Methods 10 916 singleton pregnant women with 24–42 completed gestational weeks from the Project Environmental and LifEstyle FActors iN metabolic health throughout life-course Trajectories between 2014 and 2016 were included in this study. Distributed lag models (DLMs) incorporated in Cox proportional-hazards models were applied to explore the associations of maternal exposure to weekly ambient PM2.5 throughout 12 weeks before pregnancy and pregnancy periods with risks of SGA and LGA after controlling for potential confounders. Results For a 10-μg/m3 increase in maternal exposure to PM2.5, positive associations with SGA were observed during the 1st to 9th preconceptional weeks and the 1st to 2nd gestational weeks (P Conclusions Exposure to high-level ambient PM2.5 is associated with increased risks of both SGA and LGA, and the most susceptible exposure windows are the preconception and early-pregnancy periods.

Human respiratory and cardiovascular system is severely affected with the exposure of fine particulate matters, i.e., PM10 or PM2.5. It is also been observed that air quality index (AQI) is used in many countries to define the pollution level related to particulate matters. In this study, investigation based on statistical assessment was done to establish relationship between PM10 exposure in the Zabol city of Iran with the number of patients with respiratory, cardiovascular (heart), and tuberculosis diseases. The data during the period of 2015–2017 were collected using gravitational dust sampling method from Zabol treatment centers in order to establish relation with PM10 exposure. The data set was analyzed using different statically tool as well as descriptive methods for accuracy. In this study, level of air quality index variation with different environmental condition for Zabol city was also been done. It has been observed during this study that during summer the average PM10 concentration (426 μg/m3) was observed to be higher which may be attributed to suspension of particulate matter is accelerated in the presence of heat waves. It was also observed that during the study period, almost four seasons show sign of respiratory disease effect on cardiovascular disease. It is also to report that pulmonary diseases have no effect on cardiovascular diseases. It was also seen during the study that cardiovascular diseases have no influence with the seasonal variation of Zabol city. Respiratory diseases and heart diseases are closely related to the four seasons. Respiratory and heart diseases were found to be statistically significant correlations among all seasons and year. Finally, cardiovascular diseases showed no influence on the seasonal variation.

Background Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model. Methods We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM2.5) spatio-temporal predictions (2002–2012). We employed overdispersed Poisson models to investigate the relationship between daily PM2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM2.5 dataset. Results For all PM2.5 datasets, we observed positive associations between PM2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m3 increase in daily PM2.5. We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available. Conclusions Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM2.5 and CVD admissions, regardless of model choice.

Background Lighting sources have been overlooked in previous estimates of the health burden attributable to household air pollution (HAP). However, lighting sources can be an important predictor of personal exposure to HAP in countries with limited access to electricity. We modeled the health and environmental impacts of hypothetical intervention scenarios that replace kerosene-based lighting with renewable electricity in East Africa. Methods We used comparative risk assessment methods to quantify the ischemic heart disease-, stroke-, lung cancer-, chronic obstructive pulmonary disease- and lower respiratory infection-related morbidity and mortality attributable to personal fine particulate matter (PM2.5) exposure due to kerosene-based lighting for residents of East Africa in 2015. We used health and demographic data from the Global Burden of Disease; PM2.5 exposure estimates from a previous study replacing kerosene-based lighting with solar lighting; and exposure-response functions from the literature to estimate the number of deaths and DALYs that could be avoided with increased scaling-up of the lighting source intervention. We estimated avoided black carbon emissions using emission factors from published literature. Results We estimated that 6218, 10,092, 12,723 deaths and 409, 654, 814 hundred thousand DALYs could be avoided if 33%, 66%, and 100% respectively of households using kerosene-based lighting replaced it with electricity in East Africa in 2015. Including lighting fuel in estimates of deaths due to PM2.5 from household air pollution in the region would add a further 9% in addition to those from cooking with solid fuel. Full replacement of kerosene-based lighting with renewable electricity would have reduced black carbon emissions by 4.4 Gg/year or 3957 CO2eq Gg in 2015, with the largest emission reductions in Uganda and Kenya. Conclusion Kerosene-based lighting is a non-negligible source of HAP in the region and should be included in assessments of the health burden attributable to HAP.