Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales

Quantifying fire-specific smoke exposure and health impacts

Rapidly changing wildfire regimes across the Western United States have driven more frequent and severe wildfires, resulting in wide-ranging societal threats from wildfires and wildfire-generated smoke. However, common measures of fire severity focus on what is burned, disregarding the societal impacts of smoke generated from each fire. We combine satellite-derived fire scars, air parcel trajectories from individual fires, and predicted smoke PM2.5 to link source fires to resulting smoke PM2.5 and health impacts experienced by populations in the contiguous United States from April 2006 to 2020. We quantify fire-specific accumulated smoke exposure based on the cumulative population exposed to smoke PM2.5 over the duration of a fire and estimate excess asthma-related emergency department (ED) visits as a result of this exposure. We find that excess asthma visits attributable to each fire are only moderately correlated with common measures of wildfire severity, including burned area, structures destroyed, and suppression cost. Additionally, while recent California fires contributed nearly half of the country's smoke-related excess asthma ED visits during our study period, the most severe individual fire was the 2007 Bugaboo fire in the Southeast. We estimate that a majority of smoke PM2.5 comes from sources outside the local jurisdictions where the smoke is experienced, with 87% coming from fires in other counties and 60% from fires in other states. Our approach could enable broad-scale assessment of whether specific fire characteristics affect smoke toxicity or impact, inform cost-effectiveness assessments for allocation of suppression resources, and help clarify the growing transboundary nature of local air quality.

Indoor and Personal PM2.5 Samples Differ in Chemical Composition and Alter Zebrafish Behavior Based on Primary Fuel Source

Fine particulate matter (PM2.5) exposure has been linked to diverse human health impacts. Little is known about the potential heterogeneous impacts of PM2.5 generated from different indoor fuel sources and how exposure differs between personal and indoor environments. Therefore, we used PM2.5 collected by one stationary sampler in a kitchen and personal samplers (female and male participants), in homes (n = 24) in Kheri, India, that used either biomass or liquified petroleum gas (LPG) as primary fuel sources. PM2.5 samples (pooled by fuel type and monitor placement) were analyzed for oxidative potential and chemical composition, including elements and 125 organic compounds. Zebrafish (Danio rerio) embryos were acutely exposed to varying concentrations of PM2.5 and behavioral analyses were conducted. We found relatively high PM2.5 concentrations (5-15 times above World Health Organization daily exposure guidelines) and varied human health-related chemical composition based on fuel type and monitor placement (up to 15% carcinogenic polycyclic aromatic hydrocarbon composition). Altered biological responses, including changes to mortality, morphology, and behavior, were elicited by exposure to all sample types. These findings reveal that although LPG is generally ranked the least harmful compared to biomass fuels, chemical characteristics and biological impacts were still present, highlighting the need for further research in determining the safety of indoor fuel sources.

Associations of long-term particulate matter exposure with cardiometabolic diseases: A systematic review and meta-analysis

BACKGROUND

This review aimed to establish a holistic perspective of long-term PM exposure and cardiometabolic diseases, identify long-term PM-related cardiovascular and metabolic risk factors, and provide practical significance to preventative measures.

METHOD

A combination of computer and manual retrieval was used to search for keywords in PubMed (2903 records), Embase (2791 records), Web of Science (5488 records) and Cochrane Library (163 records). Finally, a total of 82 articles were considered in this meta-analysis. Stata 13.0 was accustomed to inspecting the studies' heterogeneity and calculating the combined effect value (RR) by selecting the matching models. The subgroup analysis, sensitivity analysis and publication bias tests were also performed.

RESULTS

Meta-analysis figured an association between PM and cardiometabolic diseases. PM2.5 (per 10 μg/m3 increase) boosted the risk of hypertension (RR = 1.14, 95 % CI: 1.09-1.19), coronary heart disease (CHD) (RR = 1.21, 95 % CI: 1.08-1.35), diabetes (RR = 1.16, 95 % CI: 1.11-1.21) and stroke (including ischemic stroke and hemorrhagic stroke). PM10 (per 10 μg/m3 increase) elevated the incidence of hypertension (RR = 1.11, 95 % CI: 1.07-1.16) and diabetes (RR = 1.26, 95 % CI: 1.08-1.47). PM1 (per 10 μg/m3 increase) exposure increased the risk of total dyslipidemia, yielding the RR of 1.10 (95 % CI: 1.01-1.18). Furthermore, the elderly, overweight and higher background pollutant level were potentially susceptible to related diseases.

CONCLUSION

There was a virtual connection between long-term exposure to PM and cardiometabolic diseases. PM2.5 or PM10 (per 10 μg/m3) increased the risk of hypertension, CHD, diabetes, stroke and dyslipidemia, causing cardiovascular "multimorbidity" in high-risk populations.

The influence of environment and Earnings on Prolonged existence and human fertility: A Deeper Dive into Asia's environmentally vulnerable nations

This study inspects the impact of environmental deterioration and income on longevity and fertility in Asian countries, specifically the nations that are highly vulnerable to extreme weather. The study examines the data, covering two decades from 2000 to 2019. The empirical conclusions of the panel ARDL-PMG and the CS-ARDL econometric models indicate that environmental degradation leads to a decline in birth rate and life expectancy, while a rising income has a significant influence over longevity. However, increasing per capita income alone cannot solve the problem of population crisis in climatically susceptible countries. Therefore, the sample countries must prioritize climate action and formulate climate-resilient policies to add more years to the lives of their citizens. Similarly, for increasing childbirth the sample nations need to make peace with nature. The outcomes of this study are strong enough, as both the models support each other's findings, producing similar significant outcomes.

Air pollution deaths attributable to fossil fuels: observational and modelling study

OBJECTIVES

To estimate all cause and cause specific deaths that are attributable to fossil fuel related air pollution and to assess potential health benefits from policies that replace fossil fuels with clean, renewable energy sources.

DESIGN

Observational and modelling study.

METHODS

An updated atmospheric composition model, a newly developed relative risk model, and satellite based data were used to determine exposure to ambient air pollution, estimate all cause and disease specific mortality, and attribute them to emission categories.

DATA SOURCES

Data from the global burden of disease 2019 study, observational fine particulate matter and population data from National Aeronautics and Space Administration (NASA) satellites, and atmospheric chemistry, aerosol, and relative risk modelling for 2019.

RESULTS

Globally, all cause excess deaths due to fine particulate and ozone air pollution are estimated at 8.34 million (95% confidence interval 5.63 to 11.19) deaths per year. Most (52%) of the mortality burden is related to cardiometabolic conditions, particularly ischaemic heart disease (30%). Stroke and chronic obstructive pulmonary disease both account for 16% of mortality burden. About 20% of all cause mortality is undefined, with arterial hypertension and neurodegenerative diseases possibly implicated. An estimated 5.13 million (3.63 to 6.32) excess deaths per year globally are attributable to ambient air pollution from fossil fuel use and therefore could potentially be avoided by phasing out fossil fuels. This figure corresponds to 82% of the maximum number of air pollution deaths that could be averted by controlling all anthropogenic emissions. Smaller reductions, rather than a complete phase-out, indicate that the responses are not strongly non-linear. Reductions in emission related to fossil fuels at all levels of air pollution can decrease the number of attributable deaths substantially. Estimates of avoidable excess deaths are markedly higher in this study than most previous studies for these reasons: the new relative risk model has implications for high income (largely fossil fuel intensive) countries and for low and middle income countries where the use of fossil fuels is increasing; this study accounts for all cause mortality in addition to disease specific mortality; and the large reduction in air pollution from a fossil fuel phase-out can greatly reduce exposure.

CONCLUSION

Phasing out fossil fuels is deemed to be an effective intervention to improve health and save lives as part the United Nations' goal of climate neutrality by 2050. Ambient air pollution would no longer be a leading, environmental health risk factor if the use of fossil fuels were superseded by equitable access to clean sources of renewable energy.

Redox and inflammatory mechanisms linking air pollution particulate matter with cardiometabolic derangements

Air pollution is the largest environmental risk factor for disease and premature death. Among the different components that are present in polluted air, fine particulate matter below 2.5 μm in diameter (PM2.5) has been identified as the main hazardous constituent. PM2.5 mainly arises from fossil fuel combustion during power generation, industrial processes, and transportation. Exposure to PM2.5 correlates with enhanced mortality risk from cardiovascular diseases (CVD), such as myocardial infarction and stroke. Over the last decade, it has been increasingly suggested that PM2.5 affects CVD already at the stage of risk factor development. Among the multiple biological mechanisms that have been described, the interplay between oxidative stress and inflammation has been consistently highlighted as one of the main drivers of pulmonary, systemic, and cardiovascular effects of PM2.5 exposure. In this context, PM2.5 uptake by tissue-resident immune cells in the lung promotes oxidative and inflammatory mediators release that alter tissue homeostasis at remote locations. This pathway is central for PM2.5 pathogenesis and might account for the accelerated development of risk factors for CVD, including obesity and diabetes. However, transmission and end-organ mechanisms that explain PM2.5-induced impaired function in metabolic active organs are not completely understood. In this review, the main features of PM2.5 physicochemical characteristics related to PM2.5 ability to induce oxidative stress and inflammation will be presented. Hallmark and recent epidemiological and interventional studies will be summarized and discussed in the context of current air quality guidelines and legislation, knowledge gaps, and inequities. Lastly, mechanistic studies at the intersection between redox metabolism, inflammation, and function will be discussed, with focus on heart and adipose tissue alterations. By offering an integrated analysis of PM2.5-induced effects on cardiometabolic derangements, this review aims to contribute to a better understanding of the pathogenesis and potential interventions of air pollution-related CVD.

Characteristics of secondary inorganic aerosols and contributions to PM2.5 pollution based on machine learning approach in Shandong Province

Primary emissions of particulate matter and gaseous pollutants, such as SO2 and NOx have decreased in China following the implementation of a series of policies by the Chinese government to address air pollution. However, controlling secondary inorganic aerosol pollution requires attention. This study examined the characteristics of the secondary conversion of nitrate (NO3-) and sulfate (SO42-) in three coastal cities of Shandong Province, namely Binzhou (BZ), Dongying (DY), and Weifang (WF), and an inland city, Jinan (JN), during December 2021. Furthermore, the Shapley Additive Explanation (SHAP), an interpretable attribution technique, was adopted to accurately calculate the contributions of secondary formations to PM2.5. The nitrogen oxidation rate exhibited a significant dependence on the concentration of O3. High humidity facilitates sulfur oxidation. Compared to BZ, DY, and WF, the secondary conversion of NO3- and SO42- was more intense in JN. The light-gradient boosting model outperformed the random forest and extreme-gradient boosting models, achieving a mean R2 value of 0.92. PM2.5 pollution events in BZ, DY, and WF were primarily attributable to biomass burning, whereas pollution in Jinan was contributed by the secondary formation of NO3- and vehicle emissions. Machine learning and the SHAP interpretable attribution technique offer a precise analysis of the causes of air pollution, showing high potential for addressing environmental concerns.

Acute exposure to total and source-specific ambient fine particulate matter and risk of respiratory disease hospitalization in Kuwait

Many epidemiologic studies concerned with acute exposure to ambient PM2.5 have reported positive associations for respiratory disease hospitalization. However, few studies have investigated this relationship in Kuwait and extrapolating results from other regions may involve considerable uncertainty due to variations in concentration levels, particle sources and composition, and population characteristics. Local studies can provide evidence for strategies to reduce risks from episodic exposures to high levels of ambient PM2.5 and generating hypotheses for evaluating health risks from chronic exposures. Therefore, using speciated PM2.5 data from local samplers, we analyzed the impact of daily total and source-specific PM2.5 exposure on respiratory hospitalizations in Kuwait using a case-crossover design with conditional quasi-Poisson regression. Total and source-specific ambient PM2.5 were modeled using 0-5-day cumulative distributed lags. For total PM2.5, we observed a 0.16% (95% confidence interval [CI] = 0.05, 0.27%) increase in risk for respiratory hospitalization per 1 μg/m3 increase in concentration. Of the source factors assessed, dust demonstrated a statistically significant increase in risk (0.16%, 95% CI = 0.04, 0.29%), and the central estimate for regional PM2.5 was positive (0.11%) but not statistically significant (95% CI = -0.11, 0.33%). No effect was observed from traffic emissions and 'other' source factors. When hospitalizations were stratified by sex, nationality, and age, we found that female, Kuwaiti national, and adult groups had higher effect estimates. These results suggest that exposure to ambient PM2.5 is harmful in Kuwait and provide some evidence of differential toxicity and effect modification depending on the PM2.5 source and population affected.

Achieving health-oriented air pollution control requires integrating unequal toxicities of industrial particles

Protecting human health from fine particulate matter (PM) pollution is the ambitious goal of clean air actions, but current control strategies  largely ignore the role of source-specific PM toxicity. Here, we proposed health-oriented control strategies by integrating the unequal toxic potencies of the most polluting industrial PMs. Iron and steel industry (ISI)-emitted PM2.5 exhibit about one order of magnitude higher toxic potency than those of cement and power industries. Compared with the current mass-based control strategy (prioritizing implementation of ultralow emission standards in the power sector), the proposed health-oriented control strategy (priority control of the ISI sector) could generate 5.4 times higher reduction in population-weighted toxic potency-adjusted PM2.5 exposure among polluting industries in China. Furthermore, the marginal abatement cost per unit of toxic potency-adjusted mass of ISI-emitted PM2.5 is only a quarter of that of the other two sectors under ultralow emission scenarios. We highlight that a health-oriented air pollution control strategy is urgently required to achieve cost-effective reductions in particulate exposure risks.

Associations between hemoglobin levels and source-specific exposure to ambient fine particles among children aged <5 years in low- and middle-income countries

OBJECTIVE

We investigated associations between source-specific fine particulate matter (PM2.5) exposure and hemoglobin levels among children in low- and middle-income countries (LMICs).

METHOD

36,675 children aged < 5 years were collected in 11 LMICs during 2017. We associated child hemoglobin with 20 source-specific PM2.5, and calculated changes in hemoglobin that could be attributed to different PM2.5-mixture scenarios, established using real-world data from 88 Asian and African LMICs (AA-LMICs).

RESULTS

Multiple-source analysis revealed PM2.5 produced by solvents (change in hemoglobin for 1-μg/m3 increment in PM2.5: -10.34 g/L, 95% CI -14.88 to -5.91), industrial coal combustion (-0.51 g/L, 95% CI -9.25 to -0.08), road transportation (-0.50 g/L, 95% CI -6.96 to -0.29), or waste handling and disposal (-0.34 g/L, 95% CI -4.38 to -0.23) was significantly associated with a decrease in hemoglobin level. Decreases in hemoglobin attributable to the PM2.5 mixtures were co-determined by the concentrations and their source profiles. The largest PM2.5-related change in hemoglobin was -10.25 g/L (95% CI -15.54 to -5.27) for a mean exposure of 61.01 μg/m3 in India.

CONCLUSION

Association between PM2.5 and a decrease in hemoglobin was affected by variations in PM2.5 source profiles. Source-oriented interventions are warranted to protect children in LMICs from air pollution.

Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US

Importance

Emerging evidence indicates that exposure to fine particulate matter (PM2.5) air pollution may increase dementia risk in older adults. Although this evidence suggests opportunities for intervention, little is known about the relative importance of PM2.5 from different emission sources.

Objective

To examine associations of long-term exposure of total and source-specific PM2.5 with incident dementia in older adults.

Design, Setting, and Participants

The Environmental Predictors of Cognitive Health and Aging study used biennial survey data from January 1, 1998, to December 31, 2016, for participants in the Health and Retirement Study, which is a nationally representative, population-based cohort study in the US. The present cohort study included all participants older than 50 years who were without dementia at baseline and had available exposure, outcome, and demographic data between 1998 and 2016 (N = 27 857). Analyses were performed from January 31 to May 1, 2022.

Exposures

The 10-year mean total PM2.5 and PM2.5 from 9 emission sources at participant residences for each month during follow-up using spatiotemporal and chemical transport models.

Main Outcomes and Measures

The main outcome was incident dementia as classified by a validated algorithm incorporating respondent-based cognitive testing and proxy respondent reports. Adjusted hazard ratios (HRs) were estimated for incident dementia per IQR of residential PM2.5 concentrations using time-varying, weighted Cox proportional hazards regression models with adjustment for the individual- and area-level risk factors.

Results

Among 27 857 participants (mean [SD] age, 61 [10] years; 15 747 [56.5%] female), 4105 (15%) developed dementia during a mean (SD) follow-up of 10.2 [5.6] years. Higher concentrations of total PM2.5 were associated with greater rates of incident dementia (HR, 1.08 per IQR; 95% CI, 1.01-1.17). In single pollutant models, PM2.5 from all sources, except dust, were associated with increased rates of dementia, with the strongest associations for agriculture, traffic, coal combustion, and wildfires. After control for PM2.5 from all other sources and copollutants, only PM2.5 from agriculture (HR, 1.13; 95% CI, 1.01-1.27) and wildfires (HR, 1.05; 95% CI, 1.02-1.08) were robustly associated with greater rates of dementia.

Conclusion and Relevance

In this cohort study, higher residential PM2.5 levels, especially from agriculture and wildfires, were associated with higher rates of incident dementia, providing further evidence supporting PM2.5 reduction as a population-based approach to promote healthy cognitive aging. These findings also indicate that intervening on key emission sources might have value, although more research is needed to confirm these findings.

Identify Primary Air Pollution Sources of BTEX by Using Positive Matrix Factorization (PMF): A Case Study of Ho Chi Minh City, Vietnam

Ho Chi Minh City (HCMC) is one of the main socioeconomic and financial centers of Vietnam. The city also faces serious air pollution. However, the city polluted with benzene, toluene, ethylbenzene, and xylene (BTEX) has rarely been studied. We used positive matrix factorization (PMF) to analyze BTEX concentrations measured at two sampling locations to identify the main sources of BTEX in HCMC. The locations represented residential area (i.e., To Hien Thanh) and industrial area (i.e., Tan Binh Industrial Park). At the To Hien Thanh location, the average concentrations of benzene, ethylbenzene, toluene, and xylene were 6.9, 14.4, 4.9, and 12.7 µg/m3, respectively. At the Tan Binh location, the average concentrations of benzene, ethylbenzene, toluene, and xylene were 9.8, 22.6, 2.4, and 9.2 µg/m3, respectively. The results showed that PMF was a reliable model for source apportionment in HCMC. Traffic activities were the main sources of BTEX. Besides, industrial activities also contributed to BTEX emissions, especially the location near the industrial park. The majority of BTEXs at the To Hien Thanh sampling site come from traffic sources accounting for 56.2%. Activities from traffic and photochemical reactions (42.7%) and industrial sources (40.5%) were the main sources affecting BTEX emissions at the sampling site of Tan Binh Industrial Park. This study can be used as a reference for mitigation solutions to reduce the BTEX emission in HCMC.

Global Health and Climate Effects of Organic Aerosols from Different Sources

The impact of aerosols on human health and climate is well-recognized, yet many studies have only focused on total PM2.5 or changes from anthropogenic activities. This study quantifies the health and climate effects of organic aerosols (OA) from anthropogenic, biomass burning, and biogenic sources. Using two atmospheric chemistry models, CAM-chem and GEOS-Chem, our findings reveal that anthropogenic primary OA (POA) has the highest efficiency for health effects but the lowest for direct radiative effects due to spatial and temporal variations associated with population and surface albedo. The treatment of POA as nonvolatile or semivolatile also influences these efficiencies through different chemical processes. Biogenic OA shows moderate efficiency for health effects and the highest for direct radiative effects but has the lowest efficiency for indirect effects due to the reduced high cloud, caused by stabilized temperature profiles from aerosol-radiation interactions in biogenic OA-rich regions. Biomass burning OA is important for cloud radiative effect changes in remote atmospheres due to its ability to be transported further than other OAs. This study highlights the importance of not only OA characteristics such as toxicity and refractive index but also atmospheric processes such as transport and chemistry in determining health and climate impact efficiencies.

Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition

Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.

Hypertension and Stroke as Mediators of Air Pollution Exposure and Incident Dementia

Importance

Fine particulate matter air pollution (PM2.5) has been consistently associated with cardiovascular disease, which, in turn, is associated with an increased risk of dementia. As such, vascular dysfunction might be a mechanism by which PM2.5 mediates dementia risk, yet few prior epidemiological studies have examined this potential mechanism.

Objective

To investigate whether hypertension and stroke serve as mediators and modifiers of the association of PM2.5 with incident dementia.

Design, Setting, and Participants

As part of the Environmental Predictors of Cognitive Health and Aging (EPOCH) Project, this cohort study used biennial survey data collected between 1998 and 2016 from respondents of the Health and Retirement Study (HRS), a nationally representative, population-based, cohort in the US. Eligible participants were those over 50 years of age who were free of dementia at baseline and had complete exposure, mediator, outcome, and demographic data from the HRS. Data analysis was conducted from August to November 2022.

Exposures

Exposure to PM2.5, calculated for the 10 years preceding each person's baseline examination according to residential histories and spatiotemporal models.

Main Outcomes and Measures

Incident dementia was identified using a validated algorithm based on cognitive testing and informant reports. The 4-way decomposition causal mediation analysis method was used to quantify the degree to which hypertension and stroke mediated or modified the association of PM2.5 with incident dementia after adjustment for individual-level and area-level covariates.

Results

Among 27 857 participants (mean [SD] age at baseline, 61 [10] years; 15 747 female participants [56.5%]; 19 249 non-Hispanic White participants [69.1%]), 4105 (14.7%) developed dementia during the follow-up period (mean [SD], 10.2 [5.6] years). Among participants with dementia, 2204 (53.7%) had a history of hypertension at baseline and 386 (9.4%) received a diagnosis of hypertension during the follow up. A total of 378 participants (9.2%) had a history of stroke at baseline and 673 (16.4%) developed stroke over the follow-up period. The IQR of baseline PM2.5 concentrations was 10.9 to 14.9 μg/m3. In fully adjusted models, higher levels of PM2.5 (per IQR) were not associated with increased risk of incident dementia (HR, 1.04; 95% CI, 0.98 to 1.11). Although there were positive associations of prevalent stroke (HR, 1.67; 95% CI, 1.48 to 1.88) and hypertension (HR, 1.15; 95% CI, 1.08 to 1.23) with incident dementia compared with those free of stroke and hypertension during follow-up, there was no statistically significant association of PM2.5 with stroke (odds ratio per IQR increment in PM2.5, 1.08; 95%CI, 0.91 to 1.29) and no evidence of an association of PM2.5 with hypertension (odds ratio per IQR increment in PM2.5, 0.99; 95%CI, 0.92 to 1.07). Concordantly, there was no evidence that hypertension or stroke acted as mediators or modifiers of the association of PM2.5 with incident dementia. Although the nonmediated interaction between PM2.5 and hypertension accounted for 39.2% of the total excess association (95% CI, -138.5% to 216.9%), the findings were not statistically significant.

Conclusions and Relevance

These findings suggest that although hypertension may enhance the susceptibility of individuals to air pollution, hypertension and stroke do not significantly mediate or modify the association of PM2.5 with dementia, indicating the need to investigate other pathways and potential mediators of risk.

Reversal of trends in global fine particulate matter air pollution

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m3) to a peak in 2011 (38.9 μg/m3) and decreased steadily afterwards (34.7 μg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

Data-Driven Placement of PM2.5 Air Quality Sensors in the United States: An Approach to Target Urban Environmental Injustice

In the United States, citizens and policymakers heavily rely upon Environmental Protection Agency mandated regulatory networks to monitor air pollution; increasingly they also depend on low-cost sensor networks to supplement spatial gaps in regulatory monitor networks coverage. Although these regulatory and low-cost networks in tandem provide enhanced spatiotemporal coverage in urban areas, low-cost sensors are located often in higher income, predominantly White areas. Such disparity in coverage may exacerbate existing inequalities and impact the ability of different communities to respond to the threat of air pollution. Here we present a study using cost-constrained multiresolution dynamic mode decomposition (mrDMDcc) to identify the optimal and equitable placement of fine particulate matter (PM2.5) sensors in four U.S. cities with histories of racial or income segregation: St. Louis, Houston, Boston, and Buffalo. This novel approach incorporates the variation of PM2.5 on timescales ranging from 1 day to over a decade to capture air pollution variability. We also introduce a cost function into the sensor placement optimization that represents the balance between our objectives of capturing PM2.5 extremes and increasing pollution monitoring in low-income and nonwhite areas. We find that the mrDMDcc algorithm places a greater number of sensors in historically low-income and nonwhite neighborhoods with known environmental pollution problems compared to networks using PM2.5 information alone. Our work provides a roadmap for the creation of equitable sensor networks in U.S. cities and offers a guide for democratizing air pollution data through increasing spatial coverage of low-cost sensors in less privileged communities.

Multiphase Kinetic Modeling of Air Pollutant Effects on Protein Modification and Nitrotyrosine Formation in Epithelial Lining Fluid

Exposure to ambient air pollution is a major risk factor for human health. Inhalation of air pollutants can enhance the formation of reactive species in the epithelial lining fluid (ELF) of the respiratory tract and can lead to oxidative stress and oxidative damage. Here, we investigate the chemical modification of proteins by reactive species from air pollution and endogenous biological sources using an extended version of the multiphase chemical kinetic model KM-SUB-ELF 2.0 with a detailed mechanism of protein modification. Fine particulate matter (PM2.5) and nitrogen dioxide (•NO2) act synergistically and increase the formation of nitrotyrosine (Ntyr), a common biomarker of oxidative stress. Ozone (O3) is found to be a burden on the antioxidant defense system but without substantial influence on the Ntyr concentration. In simulations with low levels of air pollution, the Ntyr concentration in the ELF is consistent with the range of literature values for bronchoalveolar lavage fluid from healthy individuals. With high levels of air pollution, however, we obtain strongly elevated Ntyr concentrations. Our model analysis shows how chemical reactions of air pollutants can modify proteins and thus their functionality in the human body, elucidating a molecular pathway that may explain air pollutant effects on human health.

Air quality health index (AQHI) based on multiple air pollutants and mortality risks in Taiwan: Construction and validation

The currently used air quality index (AQI) is not able to capture the additive effects of air pollution on health risks and reflect non-threshold concentration-response relationships, which has been criticized. We proposed the air quality health index (AQHI) based on daily air pollution-mortality associations, and compared its validity in predicting daily mortality and morbidity risks with the existing AQI. We examined the excess risk (ER) of daily elderly (≥65-year-old) mortality associated with 6 air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) in 72 townships across Taiwan from 2006 to 2014 by performing a time-series analysis using a Poisson regression model. Random effect meta-analysis was used to pool the township-specified ER for each air pollutant in the overall and seasonal scenarios. The integrated ERs for mortality were calculated and used to construct the AQHI. The association of the AQHI with daily mortality and morbidity were compared by calculating the percentage change per interquartile range (IQR) increase in the indices. The magnitude of the ER on the concentration-response curve was used to evaluate the performance of the AQHI and AQI, regarding specific health outcomes. Sensitivity analysis was conducted using coefficients from the single- and two-pollutant models. The coefficients of PM2.5, NO2, SO2, and O3 associated with mortality were included to form the overall and season-specific AQHI. An IQR increase in the overall AQHI at lag 0 was associated with 1.90%, 2.96%, and 2.68% increases in mortality, asthma, and respiratory outpatient visits, respectively. The AQHI had higher ERs for mortality and morbidity on the validity examinations than the current AQI. The AQHI, which captures the combined effects of air pollution, can serve as a health risk communication tool to the public.

Association between long-term exposure to PM2.5 constituents and electrocardiographic abnormality: A nationwide longitudinal study in China

BACKGROUND

Electrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM2.5 constituents and changes in ECG diagnoses.

METHODS

We designed a longitudinal study among participants with repeated records of ECG examination based on the China National Stroke Screening Survey 2013-2018. Logistic regressions with multiple adjustment, estimated by the generalized estimating equation to incorporate repeated measurements, were used to assess the associations between the occurrence of any physician-diagnosed ECG abnormalities and long-term exposure to PM2.5 constituents.

RESULTS

We included 61,094 participants with 132,249 visits. All five constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) were significantly associated with an increased risk of ECG abnormalities. The excess risk of ECG abnormalities per interquartile-range increase in exposure was the highest for sulfate (26%, 95% confidence interval [CI] 23-29%), followed by ammonium (22%, 19-26%), nitrate (21%, 17-24%), black carbon (16%, 13-10%) and organic matter (9%,6%-11%). We also found that atrial fibrillation patients might be susceptible to the adverse effects of PM2.5 constituents on ECG.

CONCLUSION

Differential associations between various constituents of PM2.5 and ECG abnormalities were found. The unequal toxicities for different chemical constituents of ambient particles on cardiovascular electrophysiological endpoints should be taken into consideration when considering the biological pathways linking PM2.5 and cardiovascular conditions.

Associations of ambient manganese exposure with brain gray matter thickness and white matter hyperintensities

Manganese (Mn) exposure is associated with increased risks of dementia and cerebrovascular disease. However, evidence regarding the impact of ambient Mn exposure on brain imaging markers is scarce. We aimed to investigate the association between ambient Mn exposure and brain imaging markers representing neurodegeneration and cerebrovascular lesions. We recruited a total of 936 adults (442 men and 494 women) without dementia, movement disorders, or stroke from the Republic of Korea. Ambient Mn concentrations were predicted at each participant's residential address using spatial modeling. Neurodegeneration-related brain imaging markers, such as the regional cortical thickness, were estimated using 3 T brain magnetic resonance images. White matter hyperintensity volume (an indicator of cerebrovascular lesions) was also obtained from a certain number of participants (n = 397). Linear regression analyses were conducted after adjusting for potential confounders. A log-transformed ambient Mn concentration was associated with thinner parietal (β = -0.02 mm; 95% confidence interval [CI], -0.05 to -0.01) and occipital cortices (β = -0.03 mm; 95% CI, -0.04 to -0.01) after correcting for multiple comparisons. These associations remained statistically significant in men. An increase in the ambient Mn concentration was also associated with a greater volume of deep white matter hyperintensity in men (β = 772.4 mm3, 95% CI: 36.9 to 1508.0). None of the associations were significant in women. Our findings suggest that ambient Mn exposure may induce cortical atrophy in the general adult population.

Global food loss and waste embodies unrecognized harms to air quality and biodiversity hotspots

Global food loss and waste (FLW) undermines the resilience and sustainability of food systems and is closely tied to the United Nation's Sustainable Development Goals on climate, resource use and food security. Here we reveal strong yet under-discussed interconnections between FLW and two other Sustainable Development Goals of Human Health and Life on Land via the nitrogen cycle. We find that eliminating global FLW in 2015 would have reduced anthropogenic NH3 emissions associated with food production by 11.4 Tg (16%), decreased local PM2.5 concentrations by up to 5 μg m-3 and PM2.5-related years of life lost by 1.5 million years, and mitigated nitrogen critical load exceedances in global biodiversity hotspots by up to 19%. Halving FLW in 2030 will reduce years of life lost by 0.5-0.8 million years and nitrogen deposition by 4.7-6.0 Tg N per year (4%) (range for socioeconomic pathways). Complementary to near-term NH3 mitigation potential via technological measures, our study emphasizes incentivizing FLW reduction efforts from air quality and ecosystem health perspectives.

Will "Air Eutrophication" Increase the Risk of Ecological Threat to Public Health?

Aquatic eutrophication, often with anthropogenic causes, facilitates blooms of cyanobacteria including cyanotoxin producing species, which profoundly impact aquatic ecosystems and human health. An emerging concern is that aquatic eutrophication may interact with other environmental changes and thereby lead to unexpected cascading effects on terrestrial systems. Here, we synthesize recent evidence showing the possibility that accelerating eutrophication will spill over from aquatic ecosystems to the atmosphere via "air eutrophication", a novel concept that refers to a process promoting the growth of airborne algae, some of them with the capacity to produce toxic compounds for humans and other organisms. Being catalyzed by various anthropogenic forcings─including aquatic eutrophication, climate warming, air contamination, and artificial light at night─accelerated air eutrophication may be expected in the future, posing a potentially increasing risk of threat to public health and the environment. So far knowledge of this topic is sparse, and we therefore consider air eutrophication a potentially important research field and propose an agenda of cross-discipline research. As a contribution, we have calculated a tolerable daily intake of 17 ng m-3 day-1 for the nasal intake of microcystins by humans.

Global air pollution exposure and poverty

Air pollution is one of the leading causes of health complications and mortality worldwide, especially affecting lower-income groups, who tend to be more exposed and vulnerable. This study documents the relationship between ambient air pollution exposure and poverty in 211 countries and territories. Using the World Health Organization's (WHO) 2021 revised fine particulate matter (PM2.5) thresholds, we show that globally, 7.3 billion people are directly exposed to unsafe average annual PM2.5 concentrations, 80 percent of whom live in low- and middle-income countries. Moreover, 716 million of the world's lowest income people (living on less than $1.90 per day) live in areas with unsafe levels of air pollution, especially in Sub-Saharan Africa. Air pollution levels are particularly high in lower-middle-income countries, where economies tend to rely more heavily on polluting industries and technologies. These findings are based on high-resolution air pollution and population maps with global coverage, as well as subnational poverty estimates based on harmonized household surveys.

Optimal reactive nitrogen control pathways identified for cost-effective PM2.5 mitigation in Europe

Excess reactive nitrogen (Nr), including nitrogen oxides (NO_x) and ammonia (NH₃), contributes strongly to fine particulate matter (PM_2.5) air pollution in Europe, posing challenges to public health. Designing cost-effective Nr control roadmaps for PM_2.5 mitigation requires considering both mitigation efficiencies and implementation costs. Here we identify optimal Nr control pathways for Europe by integrating emission estimations, air quality modeling, exposure-mortality modeling, Nr control experiments and cost data. We find that phasing out Nr emissions would reduce PM_2.5 by 2.3 ± 1.2 μg·m^-3 in Europe, helping many locations achieve the World Health Organization (WHO) guidelines and reducing PM_2.5-related premature deaths by almost 100 thousand in 2015. Low-ambition NH₃ controls have similar PM_2.5 mitigation efficiencies as NO_x in Eastern Europe, but are less effective in Western Europe until reductions exceed 40%. The efficiency for NH₃ controls increases at high-ambition reductions while NO_x slightly decreases. When costs are considered, strategies for both regions uniformly shift in favor of NH₃ controls, as NH₃ controls up to 50% remain 5-11 times more cost-effective than NO_x per unit PM_2.5 reduction, emphasizing the priority of NH₃ control policies for Europe.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM_2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM_2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM_2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM_2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM_2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM_2.5 (>95 μg/m³). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM_2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Spatial and sector-specific contributions of emissions to ambient air pollution and mortality in European cities: a health impact assessment

BACKGROUND

Ambient air pollution is a major risk to health and wellbeing in European cities. We aimed to estimate spatial and sector-specific contributions of emissions to ambient air pollution and evaluate the effects of source-specific reductions in pollutants on mortality in European cities to support targeted source-specific actions to address air pollution and promote population health.

METHODS

We conducted a health impact assessment of data from 2015 for 857 European cities to estimate source contributions to annual PM_2·5 and NO₂ concentrations using the Screening for High Emission Reduction Potentials for Air quality tool. We evaluated contributions from transport, industry, energy, residential, agriculture, shipping, and aviation, other, natural, and external sources. For each city and sector, three spatial levels were considered: contributions from the same city, the rest of the country, and transboundary. Mortality effects were estimated for adult populations (ie, ≥20 years) following standard comparative risk assessment methods to calculate the annual mortality preventable on spatial and sector-specific reductions in PM_2·5 and NO₂.

FINDINGS

We observed strong variability in spatial and sectoral contributions among European cities. For PM_2·5, the main contributors to mortality were the residential (mean contribution of 22·7% [SD 10·2]) and agricultural (18·0% [7·7]) sectors, followed by industry (13·8% [6·0]), transport (13·5% [5·8]), energy (10·0% [6·4]), and shipping (5·5% [5·7]). For NO₂, the main contributor to mortality was transport (48·5% [SD 15·2]), with additional contributions from industry (15·0% [10·8]), energy (14·7% [12·9]), residential (10·3% [5·0]), and shipping (9·7% [12·7]). The mean city contribution to its own air pollution mortality was 13·5% (SD 9·9) for PM_2·5 and 34·4% (19·6) for NO₂, and contribution increased among cities of largest area (22·3% [12·2] for PM_2·5 and 52·2% [19·4] for NO₂) and among European capitals (29·9% [12·5] for PM_2·5 and 62·7% [14·7] for NO₂).

INTERPRETATION

We estimated source-specific air pollution health effects at the city level. Our results show strong variability, emphasising the need for local policies and coordinated actions that consider city-level specificities in source contributions.

FUNDING

Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making 2023-2026 Horizon Europe project.

Global PM2.5 and secondary organic aerosols (SOA) levels with sectorial contribution to anthropogenic and biogenic SOA formation

This study estimates global PM_2.5 and anthropogenic and biogenic Secondary Organic Aerosols (a-SOA and b-SOA) and sources contributing to their formation. The global landscape was divided into eleven domains (North America (NAM); South America (SAM); Europe (EUR); North Africa and Middle East (NAF); Equatorial Africa (EAF); South of Africa (SAF); Russia and Central Asia (RUS); Eastern Asia (EAS); South Asia (SAS); Southeast Asia (SEA) and Australia (AUS)) and 46 cities based on varying populations. Three inventories for global emissions were considered: Community Emissions Data System, Model of Emission of Gases and Aerosol, and Global Fire Emissions Database. WRF-Chem model coupled with atmospheric reactions and the secondary organic aerosol model was employed for estimating PM_2.5, a-SOA, and b-SOA for 2018. No city attained WHO's annual PM_2.5 guideline of 5 μg/m³. Delhi, Dhaka, and Kolkata (63-92 μg/m³) in south Asia were the most polluted, and seven cities (mostly in EUR and NAM) met the WHO target IV (10 μg/m³). The highest SOA levels (2-9 μg/m³) were in the cities of SAS and Africa, but with a low SOA contribution to PM_2.5 (3-22%). However, the low levels of SOA (1-3 μg/m³) in EUR and NAM had a higher contribution of SOA to PM_2.5 (20-33%). b-SOA were consistent with the region's vegetation and forest cover. The SOA contribution was dominated by residential emissions in all domains (except in the NAF and AUS) (maximum in SAS). The non-coal industry was the second highest contributor (except in EAF, NAF, and AUS) and EUR had the maximum contribution from agriculture and transport. Globally, residential and industry (non-coal and coal) sectors showed the maximum contribution to SOA, with a-SOA and b-SOA being nearly equal. Ridding of biomass and residential burning of solid fuel is the single most action benefiting the PM_2.5 and SOA concerns.

Tracing the sources of PM2.5-related health burden in China

Fine particulate matter (PM2.5) poses a major environmental risk to human health. We estimated PM2.5-related premature deaths in 30 Chinese provinces in 2020 using an integrated exposure response model based on monitored concentrations and obtained regional and sectoral contributions based on the atmospheric transport of the atmospheric transport contribution matrix. From the perspective of regional- and sectoral-scale effects, the results revealed that 740,140 [95% confidence interval (CI):646,538-839,968] premature deaths were related to PM2.5 in 2020, mainly in East (30%), Central (18%), and North (15%) China. Manufacturing activity was found to be the major cause of PM2.5-related premature deaths, accounting for over 50% of the deaths. From the perspective of the interregional atmospheric transport effect, although local emissions were the major source of PM2.5-related premature deaths in all regions, non-local emissions contributed approximately 30%. The overall trend in the net atmospheric transport direction was from north to south. In particular, the Guangdong, Guangxi, and Hainan provinces of South China received contributions of more than 40% from non-local provinces, mainly from the East and Central China. Combined with economic data, the regions and sectors with the highest PM2.5-related premature deaths per unit output or consumption include the manufacturing and household sectors in North and Northeast China and transportation, agriculture, and electricity in Central China. Therefore, from the perspective of the above three impacts, although the potential impact of PM2.5 pollution on health in China has decreased with the decrease in PM2.5 concentration in the past decade owing to strict air pollution control, the central and northern parts of China are still the key areas requiring air pollution control. The health impacts of air pollution associated with the rapid development of China's manufacturing industry in the post-pandemic era cannot be ignored.

Associations of air pollutant concentrations with longitudinal kidney function changes in patients with chronic kidney disease

This longitudinal cohort study investigated the associations of air pollutant exposures, including CO, NO, NO₂, NO_x, O₃, PM₁₀, PM_2.5, and SO₂, with long-term kidney function changes in patients with chronic kidney disease (CKD). We enrolled 447 CKD patients who took part in a universal hospital pre-ESRD care program during 2011-2015. The daily average air pollutant exposures and temperature were estimated for each patient, with different levels of air pollutant concentrations defined by 5-knot and restricted cubic spline function. Predicted annual estimated glomerular filtration (eGFR) slope values by one mixed model were considered as the study outcome. The average age of the study population was 77.1 ± 12.6 years, and the median annual eGFR decreased by 2.1 ml/min/1.73 m² per year from 30 ml/min/1.73 m² at baseline during a mean follow-up time of 3.4 years. The univariable and multivariable analyses revealed no significant linear and non-linear associations between 5-knot air pollutant concentrations and annual eGFR slope. In addition, the visualized spline effect plots show insignificant variation patterns in annual eGFR slope values with increased air pollutant concentrations. These results encourage more extensive studies to clarify the causal relationships and mechanisms of long-term specific air pollutant exposures and longitudinal kidney function change, especially in CKD populations.

Energy inequality and air pollution nexus in India

Energy usage, inequality, and their impacts are deeply intertwined, especially in India. Every year, cooking using biomass-based solid fuel usage causes death to tens of thousands of Indians, specifically, economically unprivileged people. Solid fuel burning has been known as one of the prominent sources of ambient PM_2.5 (particulate matter with an aerodynamic diameter of <2.5 μm) concentration in the atmosphere. Thus, limiting the PM_2.5 emission from biomass-based cooking fuel through the transition to LPG has gained priority. The government report in India indicates that nearly 8 million households became beneficiaries of the LPG connection through the PMUY scheme till 2019. The transition to clean cooking fuel may have an influence on the ambient PM_2.5 concentration. In this study, to explore the nexus between energy inequality and air pollution, we investigated the present status of clean fuel usage in India and its drivers, including the impact of such a massive transition to cleaner fuel on ambient air quality, with a specific focus on PM_2.5. The results show an improvement of 15 % in LPG usage from 2015 to 2019 in India., Yet the majority of poorer (>60 %) and poorest communities (>90 %) still use solid biomass as the cooking fuel. No significant correlation (r = 0.036; p-value ≫ 0.05) was obtained between LPG usage and ambient PM_2.5 concentration suggesting the influence of other confounding factors which might subdue the anticipated effect of the usage of clean fuel. The analysis suggests, despite the successful launching of the PMUY, the low LPG usage pattern among the poor, because of the lack of an effective subsidy policy, might jeopardize the effort to fix the standard of ambient air as per WHO.

Black carbon nanoparticles activate the crosstalk mechanism between necroptosis and macrophage extracellular traps to change macrophages fate

PM2.5 still poses a threat to public health even at very low levels. Black carbon (BC) is a key component of PM2.5. Macrophage extracellular traps (METs) are a means by which macrophages capture and destroy invading pathogens. Necroptosis is an inflammatory programmed cell death. However, there is no research on the crosstalk mechanism between necroptosis and METs after BC exposure. In our study, fluorescence labeling, fluorescent probes, qPCR, and immunofluorescence were applied. Our research found that under normal physiological conditions, when macrophages receive external stimuli (in our experiment, phorbol 12-myristate 13-acetate (PMA)), they will form METs, thus exhibiting innate immune function. However, exposure to BC can cause necroptosis in macrophages accompanied by increased levels of ROS and cytosolic calcium ions as well as altered expression of inflammatory factors and chemokines that prevent the formation of METs, and weakening innate immune function. Notably, inhibition of necroptosis restored the formation of METs, indicating that necroptosis inhibits the formation of METs. Our experiment will enrich the understanding of the mechanism of macrophage injury caused by BC exposure, provide a new direction for studying harmful atmospheric particle toxicity, and propose new therapeutic insights for diseases caused by atmospheric particulate matter. This study is the first to explore the crosstalk mechanism between necroptosis and METs after BC exposure.

Influence of spatial resolution of PM2.5 concentrations and population on health impact assessment from 2010 to 2020 in China

Ambient PM_2.5 pollution is a leading environmental health risk factor worldwide. The spatial resolution of PM_2.5 concentrations and population strongly impacts PM_2.5-related health impact estimates. However, long-term variations and regional differences in this impact have rarely been explored, particularly in China. Here, by aggregating satellite-derived PM_2.5 concentration and population datasets at 1-km resolution in China to coarser resolutions (10, 50, and 100 km), we evaluated decadal changes in the impact of resolution on health assessments at national and local scales. For the sensitivity of population-weighted mean (PWM) PM_2.5 concentrations to resolution, we found that the national PWM PM_2.5 concentration decreased with coarser resolutions; this pattern was widely observed and was more obvious in southern and central China and the Sichuan Basin. The results showed that the sensitivity of national PWM PM_2.5 concentrations to resolution continuously weakened from 2010 to 2020, likely due to a reduction in the spatial heterogeneity of PM_2.5 concentrations in regions with high sensitivity. This weakness caused a large underestimation of the long-term trend of national PWM PM_2.5 using a 100-km resolution, which was 7% lower than the trend at 1 km. Regarding the sensitivity of PM_2.5-attributable mortality to resolution, most of China exhibited a pattern in which attributable mortality decreased with coarser resolution. The sensitivity of the estimated PM_2.5-attributable mortality to resolution also weakened over time on a national scale and in most parts of China. Nevertheless, the weakness for mortality sensitivity was not as apparent as for PWM PM_2.5 sensitivity. This was likely because different drivers played distinct roles in the temporal variation of the mortality sensitivity: population aging enhanced the sensitivity, and variations in PM_2.5 concentrations and population distribution both weakened the sensitivity. However, the national attributable mortality trend at a 100-km resolution was still underestimated by 1.75% relative to the 1-km resolution.

Characterization of the short-term temporal variability of road dust chemical mixtures and meteorological profiles in a near-road urban site in British Columbia

Implications: Non-tailpipe emissions driven by springtime road dust in northern latitude communities is increasing in importance for air pollution control and improving our understanding of the health effects of chemical mixtures from particulate matter exposure. High-volume samples from a near-road site indicated that days affected by springtime road dust are substantively different from other days with respect to particulate matter mixture composition and meteorological drivers. The high load of trace elements in PM₁₀ on high road dust days has important implications for the acute toxicity of inhaled air and subsequent health effects. The complex relationships between road dust and weather identified in this study may facilitate further research on the health effects of chemical mixtures related to road dust while also highlighting potential changes in this unique form of air pollution as the climate changes.

Exploring the contributions of major emission sources to PM2.5 and attributable health burdens in China

Ambient fine particulate matter (PM_2.5) pollution is the principal environmental risk factor for health burdens in China. Identifying the sectoral contributions of pollutant emissions sources on multiple spatiotemporal scales can help in the formulation of specific strategies. In this study, we used sensitivity analysis to explore the specific contributions of seven major emission sources to ambient PM_2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM_2.5 concentrations above the Chinese Ambient Air Quality Standard of 35 μg/m³. This percentage was expected to decrease to 35% and 39% if industrial and residential emissions were fully eliminated. In densely populated and highly polluted regions, residential sources contributed about 50% of the PM_2.5 exposure in winter, while industrial sources contributed the most (29-51%) in the remaining seasons. The three major sectoral contributors to PM_2.5-related deaths were industry (247,000 cases, 35%), residential sources (219,000 cases, 31%), and natural sources (87,000, 12%). The relative contributions of the different sectors varied in the different provinces, with industrial sources making the largest contribution in Shanghai (65%), while residential sources predominated in Heilongjiang (63%), and natural sources dominated in Xinjiang (82%). The contributions of the agricultural (11%), transportation (6%), and power (3%) sources were relatively low in China, but emissions mitigation was still effective in densely populated areas. In conclusion, to effectively alleviate health burdens across China, priority should be given to controlling residential emissions in winter and industrial emissions all year round, taking additional measures to curb emissions from other sources in urban hotspots, and formulating air pollution control strategies tailored to local conditions.

Source Contributions to PM2.5-Related Mortality and Costs: Evidence for Emission Allocation and Compensation Strategies in China

The emissions from various pollution sources were not proportional to their contributions to ambient PM_2.5 concentrations and associated health burdens. That means even with the same total abatement targets, different abatement allocation strategies across emission sources can have distinct health benefits. Insufficient knowledge of various sources' contributions to health burdens in China, the country suffering substantial PM_2.5-related deaths, hindered the government from seeking optimized abatement allocation strategies. In this context, we separated the contributions of 155 emission sources (31 provinces × 5 sectors) to PM_2.5-related mortality across China in 2017 by coupling the Comprehensive Air Quality Model with Extensions (CAMx), Weather Research and Forecasting model (WRF), and health impact assessment model. We further identified the priority-control emission sources and quantified interprovincial ecological compensation volumes to alleviate inequality induced by emission allocation strategies. Results showed that PM_2.5 pollution caused 899,443 excess deaths and around 127 billion USD costs in 2017. Approximately half of the deaths and costs were attributable to emissions from sources outside the boundary of the regions where the deaths occurred. Twenty-five out of 155 emission sources that contributed to the top 60% mortality burdens and had high marginal abatement efficiencies in China shall be the priority-control emission sources. A 1 μg/m³ decrease of PM_2.5 concentration in regions where these key emission sources occur shall be compensated by 76-153 million USD in their receptor regions. Our study sheds light on the sources' contributions to mortality burdens and costs and provides scientific evidence for optimizing the emission allocation and compensation strategies in China. It also has wide implications for other countries suffering similar problems.

The association of birthweight with fine particle exposure is modifiable by source sector: Findings from a cross-sectional study of 17 low- and middle-income countries

BACKGROUND

Low birthweight attributable to fine particulate matter (PM_2.5) exposure is a global issue affecting infant health, especially in low- and middle-income countries (LMICs). However, large-population studies of multiple LMICs are lacking, and little is known about whether the source of PM_2.5 is a determinant of the toxic effect on birthweight.

OBJECTIVE

We examined the effect on birthweight of long-term exposure to PM_2.5 from different sources in LMICs.

METHODS

The birthweights of 53,449 infants born between September 16, 2017 and September 15, 2018 in 17 LMICs were collected from demographic and health surveys. Long-term exposure to PM_2.5 in 2017 produced by 20 different sources was estimated by combining chemical transport model simulations with satellite-based concentrations of total mass. Generalized linear regression models were used to investigate the associations between birthweight and each source-specific PM_2.5 exposure. A multiple-pollutant model with a ridge penalty on the coefficients of all 20-source-specific components was employed to develop a joint exposure-response function (JERF) of the PM_2.5 mixtures. The estimated JERF was then used to quantify the global burden of birthweight reduction attributable to PM_2.5 mixtures and to PM_2.5 from specific sources.

RESULTS

The fully adjusted single-pollutant model indicated that exposure to a 10 μg/m³ increase in total PM_2.5 was significantly associated with a -6.6 g (95% CI -11.0 to -2.3) reduction in birthweight. In single- and multiple-pollutant models, significant birthweight changes were associated with exposure to PM_2.5 produced by international shipping (SHP), solvents (SLV), agricultural waste burning (GFEDagburn), road transportation (ROAD), waste handling and disposal (WST), and windblown dust (WDUST). Based on the global average exposure to PM_2.5 mixtures, the JERF showed that the overall change in birthweight could mostly be attributed to PM_2.5 produced by ROAD (-37.7 g [95% CI -49.2 to -24.4] for a global average exposure of 2.2 μg/m³), followed by WST (-27.5 g [95% CI -42.6 to -10.7] for a 1.6-μg/m³ exposure), WDUST (-19.5 g [95% CI -26.7 to -12.6] for a 8.6-μg/m³ exposure), and SHP (-19.0 g [95% CI -32.3 to -5.7] for a 0.2-μg/m³ exposure), which, with the exception of WDUST, are anthropogenic sources. The changes in birthweight varied geographically and were co-determined by the concentration as well as the source profile of the PM_2.5 mixture.

CONCLUSION

PM_2.5 exposure is associated with a reduction in birthweight, but our study shows that the magnitude of the association differs depending on the PM_2.5 source. A source-targeted emission-control strategy that considers local features is therefore critical to maximize the health benefits of air quality improvement, especially with respect to promoting maternal and child health.

Global estimates of daily ambient fine particulate matter concentrations and unequal spatiotemporal distribution of population exposure: a machine learning modelling study

BACKGROUND

Short-term exposure to ambient PM_2·5 is a leading contributor to the global burden of diseases and mortality. However, few studies have provided the global spatiotemporal variations of daily PM_2·5 concentrations over recent decades.

METHODS

In this modelling study, we implemented deep ensemble machine learning (DEML) to estimate global daily ambient PM_2·5 concentrations at 0·1° × 0·1° spatial resolution between Jan 1, 2000, and Dec 31, 2019. In the DEML framework, ground-based PM_2·5 measurements from 5446 monitoring stations in 65 countries worldwide were combined with GEOS-Chem chemical transport model simulations of PM_2·5 concentration, meteorological data, and geographical features. At the global and regional levels, we investigated annual population-weighted PM_2·5 concentrations and annual population-weighted exposed days to PM_2·5 concentrations higher than 15 μg/m³ (2021 WHO daily limit) to assess spatiotemporal exposure in 2000, 2010, and 2019. Land area and population exposures to PM_2·5 above 5 μg/m³ (2021 WHO annual limit) were also assessed for the year 2019. PM_2·5 concentrations for each calendar month were averaged across the 20-year period to investigate global seasonal patterns.

FINDINGS

Our DEML model showed good performance in capturing the global variability in ground-measured daily PM_2·5, with a cross-validation R² of 0·91 and root mean square error of 7·86 μg/m³. Globally, across 175 countries, the mean annual population-weighted PM_2·5 concentration for the period 2000-19 was estimated at 32·8 μg/m³ (SD 0·6). During the two decades, population-weighted PM_2·5 concentration and annual population-weighted exposed days (PM_2·5 >15 μg/m³) decreased in Europe and northern America, whereas exposures increased in southern Asia, Australia and New Zealand, and Latin America and the Caribbean. In 2019, only 0·18% of the global land area and 0·001% of the global population had an annual exposure to PM_2·5 at concentrations lower than 5 μg/m³, with more than 70% of days having daily PM_2·5 concentrations higher than 15 μg/m³. Distinct seasonal patterns were indicated in many regions of the world.

INTERPRETATION

The high-resolution estimates of daily PM_2·5 provide the first global view of the unequal spatiotemporal distribution of PM_2·5 exposure for a recent 20-year period, which is of value for assessing short-term and long-term health effects of PM_2·5, especially for areas where monitoring station data are not available.

FUNDING

Australian Research Council, Australian Medical Research Future Fund, and the Australian National Health and Medical Research Council.

A global review of the state of the evidence of household air pollution's contribution to ambient fine particulate matter and their related health impacts

Direct exposure to household fine particulate air pollution (HAP) associated with inefficient combustion of fuels (wood, charcoal, coal, crop residues, kerosene, etc.) for cooking, space-heating, and lighting is estimated to result in 2.3 (1.6-3.1) million premature yearly deaths globally. HAP emitted indoors escapes outdoors and is a leading source of outdoor ambient fine particulate air pollution (AAP) in low- and middle-income countries, often being a larger contributor than well-recognized sources including road transport, industry, coal-fired power plants, brick kilns, and construction dust. We review published scientific studies that model the contribution of HAP to AAP at global and major sub-regional scales. We describe strengths and limitations of the current state of knowledge on HAP's contribution to AAP and the related impact on public health and provide recommendations to improve these estimates. We find that HAP is a dominant source of ambient fine particulate matter (PM2.5) globally - regardless of variations in model types, configurations, and emission inventories used - that contributes approximately 20 % of total global PM2.5 exposure. There are large regional variations: in South Asia, HAP contributes ∼ 30 % of ambient PM2.5, while in high-income North America the fraction is ∼ 7 %. The median estimate indicates that the household contribution to ambient air pollution results in a substantial premature mortality burden globally of about 0.77(0.54-1) million excess deaths, in addition to the 2.3 (1.6-3.1) million deaths from direct HAP exposure. Coordinated global action is required to avert this burden.

Changes in PM2.5-related health burden in China's poverty and non-poverty areas during 2000-2020: A health inequality perspective

China suffers from severe PM_2.5 pollution that has resulted in a huge health burden. Such PM_2.5-related health burden has long been suspected to differ between China's poverty-stricken areas (PAs) and non-poverty-stricken areas (NPAs). Yet, evidence-based examination of this long-held belief, which is critical as a barrier of environmental injustice to advancing China's sustainability, is still missing. Here our study shows that the PM_2.5 pollution is more serious in China's NPAs than PAs-with their annual averages being respectively 54.83 μg/m³ and 43.63 μg/m³-causing higher premature mortality in the NPAs. Compared to economic inequality, China's total PM_2.5-related premature mortality was relatively evenly distributed during 2000-2015 across regions of varying levels of gross domestic product (GDP) per capita but increased slightly in 2015-2020 owing to the dramatic change in age structure. The elderly population increased by 31 %. PM_2.5-related premature deaths were more severe for populations of low socioeconomic status, and such environmental health inequalities could be amplified by population aging. Additionally, population migration from China's PAs to developed cities contributed to 638, 779, 303, 954, and 896 premature deaths in 2000, 2005, 2010, 2015, and 2020, respectively. Changes in the age structure (53 %) and PM_2.5 concentration (28 %) had the greatest impact on premature deaths, followed by changes in population (12 %) and baseline mortality (8 %). The contribution rate of changes in the age structure and PM_2.5 concentration was higher in PAs than in NPAs. Our findings provide insight into PM_2.5-related premature death and environmental inequality, and may inform more equitable clean air policies to achieve China's sustainable development goals.

On the COP26 and coal's phase-out agenda: Striking a balance among the environmental, economic, and health impacts of coal consumption

Economic and environmental policy actions are often substitutionary in their impacts, as one man's food could be another's poison. One of the critical emphases at the recent Conference of Parties 26 (COP26) is the need for coal to be phased out in the energy consumption basket of nations to achieve environmental sustainability, but this could be at the expense of the positive performance of other socio-economic fundamentals. The best bet could then be to maintain an optimal consumption level to strike a balance. Relying on this, we examine the environmental, economic, and health impacts of coal consumption in the world's highest coal-consuming countries, putting the latter's threshold level into consideration. In summary, we find that there is a trade-off between pushing for a sustainable environment through a reduction in coal consumption and achieving better growth and health status. This implies that phasing out of coal totally will have severe economic and health costs. However, based on our threshold regression model results, it is most reasonable to maintain a lower level of coal use in the overall energy mix of these countries. This will definitely yield a relatively low level of carbon, but will still assure a certain level of economic growth and health performance. As such, reducing the intensity of coal gradually and simultaneously providing a substitute that can also serve economic and health needs are encouraged.

The Effects of Trash, Residential Biofuel, and Open Biomass Burning Emissions on Local and Transported PM2.5 and Its Attributed Mortality in Africa

Long-term exposure to ambient fine particulate matter (PM2.5) is the second leading risk factor of premature death in Sub-Saharan Africa. We use GEOS-Chem to quantify the effects of (a) trash burning, (b) residential solid-fuel burning, and (c) open biomass burning (BB) (i.e., landscape fires) on ambient PM2.5 and PM2.5-attributable mortality in Africa. Using a series of sensitivity simulations, we excluded each of the three combustion sources in each of five African regions. We estimate that in 2017 emissions from these three combustion sources within Africa increased global ambient PM2.5 by 2%, leading to 203,000 (95% confidence interval: 133,000-259,000) premature mortalities yr-1 globally and 167,000 premature mortalities yr-1 in Africa. BB contributes more ambient PM2.5-related premature mortalities per year (63%) than residential solid-fuel burning (29%) and trash burning (8%). Open BB in Central Africa leads to the largest number of PM2.5-attributed mortalities inside the region, while trash burning in North Africa and residential solid-fuel burning in West Africa contribute the most regional mortalities for each source. Overall, Africa has a unique ambient air pollution profile because natural sources, such as windblown dust and BB, contribute strongly to ambient PM2.5 levels and PM2.5-related mortality. Air pollution policies may need to focus on taking preventative measures to avoid exposure to ambient PM2.5 from these less-controllable sources.

Modelling the air quality benefits of EU climate mitigation policies using two different PM2.5-related health impact methodologies

The EU, seeking to be a global leader in the fight against climate change, is moving ahead with ambitious policies to mitigate greenhouse gases emissions. In this context, the Fit for 55 package (FF55) is a set of proposals to revise and update EU legislation, to ensure that policies are in line with the climate goals of cutting emissions by at least 55% by 2030. Whilst these policies are designed for climate purposes, they will have positive side-effects (co-benefits) on air quality. Separately, additional policies are also in place to reduce emissions of related air pollutants and to improve air quality concentrations on EU territory. In this work, through a modelling study, we analyse the benefits of these policies via the health benefits arising from the resulting reductions in yearly average PM2.5 concentrations. Results are analysed by assessing and comparing morbidity and mortality impacts as computed using both the HRAPIE (Health risks of air pollution in Europe, WHO, as implemented in the CaRBonH model) and the GBD (Global Burden of Disease, as implemented in FASST-GBD model) approaches. Even when considering the uncertainty and variability in the results obtained using the two approaches, it is clear that EU policies can bring health and economic benefit in EU, with several Billions of Euro of benefits both in terms of morbidity and mortality indicators.

Urban policy interventions to reduce traffic-related emissions and air pollution: A systematic evidence map

BACKGROUND

Urban areas are hot spots for human exposure to air pollution, which originates in large part from traffic. As the urban population continues to grow, a greater number of people risk exposure to traffic-related air pollution (TRAP) and its adverse, costly health effects. In many cities, there is a need and scope for air quality improvements through targeted policy interventions, which continue to grow including rapidly changing technologies.

OBJECTIVE

This systematic evidence map (SEM) examines and characterizes peer-reviewed evidence on urban-level policy interventions aimed at reducing traffic emissions and/or TRAP from on-road mobile sources, thus potentially reducing human exposures and adverse health effects and producing various co-benefits.

METHODS

This SEM follows a previously peer-reviewed and published protocol with minor deviations, explicitly outlined here. Articles indexed in Public Affairs Index, TRID, Medline and Embase were searched, limited to English, published between January 1, 2000, and June 1, 2020. Covidence was used to screen articles based on previously developed eligibility criteria. Data for included articles was extracted and manually documented into an Excel database. Data visualizations were created in Tableau.

RESULTS

We identified 7528 unique articles from database searches and included 376 unique articles in the final SEM. There were 58 unique policy interventions, and a total of 1,139 unique policy scenarios, comprising these interventions and different combinations thereof. The policy interventions fell under 6 overarching policy categories: 1) pricing, 2) land use, 3) infrastructure, 4) behavioral, 5) technology, and 6) management, standards, and services, with the latter being the most studied. For geographic location, 463 policy scenarios were studied in Europe, followed by 355 in Asia, 206 in North America, 57 in South America, 10 in Africa, and 7 in Australia. Alternative fuel technology was the most frequently studied intervention (271 times), followed by vehicle emission regulation (134 times). The least frequently studied interventions were vehicle ownership taxes, and studded tire regulations, studied once each. A mere 3 % of studies addressed all elements of the full-chain-traffic emissions, TRAP, exposures, and health. The evidence recorded for each unique policy scenario is hosted in an open-access, query-able Excel database, and a complementary interactive visualization tool. We showcase how users can find more about the effectiveness of the 1,139 included policy scenarios in reducing, increasing, having mixed or no effect on traffic emissions and/or TRAP.

CONCLUSION

This is the first peer-reviewed SEM to compile international evidence on urban-level policy interventions to reduce traffic emissions and/or TRAP in the context of human exposure and health effects. We also documented reported enablers, barriers, and co-benefits. The open-access Excel database and interactive visualization tool can be valuable resources for practitioners, policymakers, and researchers. Future updates to this work are recommended.

PROTOCOL REGISTRATION

Sanchez, K.A., Foster, M., Nieuwenhuijsen, M.J., May, A.D., Ramani, T., Zietsman, J. and Khreis, H., 2020. Urban policy interventions to reduce traffic emissions and traffic-related air pollution: Protocol for a systematic evidence map. Environment international, 142, p.105826.

Gene-environment interactions and their impact on human health

The molecular processes underlying human health and disease are highly complex. Often, genetic and environmental factors contribute to a given disease or phenotype in a non-additive manner, yielding a gene-environment (G × E) interaction. In this work, we broadly review current knowledge on the impact of gene-environment interactions on human health. We first explain the independent impact of genetic variation and the environment. We next detail well-established G × E interactions that impact human health involving environmental toxicants, pollution, viruses, and sex chromosome composition. We conclude with possibilities and challenges for studying G × E interactions.

Source sectors underlying PM2.5-related deaths among children under 5 years of age in 17 low- and middle-income countries

BACKGROUND

Fine particulate matter (PM_2.5) from different source sectors might differ in toxicity. However, data from large-scale studies on vulnerable children in low- and middle-income countries (LMICs) are insufficient.

OBJECTIVE

To analyze the association of under-five death (U5D) with long-term exposure to PM_2.5 from different sources.

METHOD

We evaluated demographic and health survey data for 79,995 babies born in 2017 in 16 Asian and African LMICs (AA-LMICs) and a Latin America low-income country (i.e., Haiti). Long-term exposure to PM_2.5 was assessed by a well-established product that attributed the annual concentration to 20 source sectors in 2017. The associations of survival during < 5-year periods with each source-specific concentration of PM_2.5 were analyzed by Cox regression with multiple adjustments. We derived a multiple-pollutant ridge regression model to estimate the joint exposure-response function (JERF) between U5D and PM_2.5 mixtures. To evaluate how sources affected PM_2.5 toxicity, we evaluated the number of U5Ds attributable to PM_2.5 based on the source profiles for 88 AA-LMICs.

RESULTS

According to the single-pollutant model, the risk of U5D increased by 7% (95% confidence interval [CI]: 5%, 9%) for each 10 μg/m³ increment in total PM_2.5 concentration. The model performance was lower than that of the multiple-pollutant ridge regression model. For each 10 μg/m³ increment in PM_2.5, the excess risk of U5D ranged from 6% (95% CI: 4%, 9%) in Nepal to 10% (95% CI: 6%, 14%) in Mauritania. Based on the JERF, PM_2.5 contributed to 817,647 (95% CI: 585,729, 1,050,439), i.e., 28.0% (95% CI: 20.1%, 35.8%), of all U5Ds across the 88 AA-LMICs. The PM_2.5-related U5Ds were mostly attributable to PM_2.5 produced by desert dust, followed by solid biofuel combustion and open fires.

CONCLUSION

The average toxicity of PM_2.5 varied by source profile, which should be taken into consideration when planning public health interventions. For some AA LMICs, natural sources of PM_2.5 had the most significant health effects, and should not be ignored to ensure the protection of child health.

A Source Apportionment and Emission Scenario Assessment of PM2.5- and O3-Related Health Impacts in G20 Countries

Exposure to air pollution is a leading risk factor for premature death globally; however, the complexity of its formation and the diversity of its sources can make it difficult to address. The Group of Twenty (G20) countries are a collection of the world's largest and most influential economies and are uniquely poised to take action to reduce the global health burden associated with air pollution. We present a framework capable of simultaneously identifying regional and sectoral sources of the health impacts associated with two air pollutants, fine particulate matter (PM_2.5) and ozone (O₃) in G20 countries; this framework is also used to assess the health impacts associated with emission reductions. This approach combines GEOS-Chem adjoint sensitivities, satellite-derived data, and a new framework designed to better characterize the non-linear relationship between O₃ exposures and nitrogen oxides emissions. From this approach, we estimate that a 50% reduction of land transportation emissions by 2040 would result in 251 thousand premature deaths avoided in G20 countries. These premature deaths would be attributable equally to reductions in PM_2.5 and O₃ exposure which make up 51% and 49% of the potential benefits, respectively. In our second application, we estimate that the energy generation related co-benefits associated with G20 countries staying on pace with their net-zero carbon dioxide targets would be 290 thousand premature deaths avoided in 2040; action by India (47%) would result in the most benefits of any country and a majority of these avoided deaths would be attributable to reductions in PM_2.5 exposure (68%).