Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data

Association of long-term exposure to PM2.5 and its chemical components with the reduced quality of sleep

Poor sleep quality is a widespread concern. While the influence of particle exposure on sleep disturbances has received considerable attention, research exploring other dimensions of sleep quality and the chemical components of the particles remains limited. We employed a marginal structural model to explore the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality. The odds ratio (95 % CI) for poor sleep quality was 1.335 (1.292-1.378), 1.097 (1.080-1.113), 1.137 (1.100-1.174), 1.197 (1.156-1.240), and 1.124 (1.107-1.140) per IQR increase in the concentration of PM2.5, SO42-, NO3-, NH4+, and BC, respectively. The score (and 95 % CI) of sleep latency, use of sleep medication, habitual sleep efficiency, subjective sleep quality, and daytime dysfunction were affected by PM2.5, with an increase of 0.059 (0.050-0.069), 0.054 (0.049-0.059), 0.011 (0.008-0.014), 0.011 (0.005-0.018), and 0.026 (0.018-0.034) per IQR increase in PM2.5 concentrations, respectively. This study supports the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality.

Short-term exposure to ambient fine particulate matter constituents and myocardial infarction mortality

Short-term ambient fine particulate matter (PM2.5) exposure has been related to an increased risk of myocardial infarction (MI) death, but which PM2.5 constituents are associated with MI death and to what extent remain unclear. We aimed to explore the associations of short-term exposure to PM2.5 constituents with MI death and evaluate excess mortality. We conducted a time-stratified case-crossover study on 237,492 MI decedents in Jiangsu province, China during 2015-2021. Utilizing a validated PM2.5 constituents grid dataset at 1 km spatial resolution, we estimated black carbon (BC), organic carbon (OC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) exposure by extracting daily concentrations grounding on the home address of each subject. We employed conditional logistic regression models to evaluate the exposure-response relationship between PM2.5 constituents and MI death. Overall, per interquartile range (IQR) increase of BC (lag 06-day; IQR: 1.75 μg/m3) and SO42- (lag 04-day; IQR: 5.06 μg/m3) exposures were significantly associated with a 3.91% and 2.94% increase in odds of MI death, respectively, and no significant departure from linearity was identified in the exposure-response curves for BC and SO42-. If BC and SO42- exposures were reduced to theoretical minimal risk exposure concentration (0.89 μg/m3 and 1.51 μg/m3), an estimate of 4.55% and 4.80% MI deaths would be avoided, respectively. We did not find robust associations of OC, NO3-, NH4+, and Cl- exposures with MI death. Individuals aged ≥80 years were more vulnerable to PM2.5 constituent exposures in MI death (p for difference <0.05). In conclusion, short-term exposure to PM2.5-bound BC and SO42- was significantly associated with increased odds of MI death and resulted in extensive excess mortality, notably in older adults. Our findings emphasized the necessity of reducing toxic PM2.5 constituent exposures to prevent deaths from MI and warranted further studies on the relative contribution of specific constituents.

Ambient PM2.5 Chemical Composition and Cardiovascular Disease Hospitalizations in China

Little is known about the impacts of specific chemical components on cardiovascular hospitalizations. We examined the relationships of PM2.5 chemical composition and daily hospitalizations for cardiovascular disease in 184 Chinese cities. Acute PM2.5 chemical composition exposures were linked to higher cardiovascular disease hospitalizations on the same day and the percentage change of cardiovascular admission was the highest at 1.76% (95% CI, 1.36-2.16%) per interquartile range increase in BC, followed by 1.07% (0.72-1.43%) for SO42-, 1.04% (0.63-1.46%) for NH4+, 0.99% (0.55-1.43%) for NO3-, 0.83% (0.50-1.17%) for OM, and 0.80% (0.34%-1.26%) for Cl-. Similar findings were observed for all cause-specific major cardiovascular diseases, except for heart rhythm disturbances. Short-term exposures to PM2.5 chemical composition were related to higher admissions and showed diverse impacts on major cardiovascular diseases.

Increased mortality risk from airborne exposure to polycyclic aromatic hydrocarbons

BACKGROUND

The potential health effects of airborne polycyclic aromatic hydrocarbons (PAHs) among general population remained extensively unstudied. This study sought to investigate the association of short-term exposure to low-level total and 7 carcinogenic PAHs with mortality risk.

METHODS

We conducted an individual-level time-stratified case-crossover study in Jiangsu province of eastern China, by investigating over 2 million death cases during 2016-2019. Daily concentrations of total PAH and its 7 carcinogenic species including benzo[a]anthracene (BaA), benzo[a]pyrene (BaP), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), chrysene (Chr), dibenz[a,h]anthracene (DahA), and indeno[1,2,3-cd]pyrene (IcdP), predicted by well-validated spatiotemporal models, were assigned to death cases according to their residential addresses. We estimated mortality risk associated with short-term exposure to increase of an interquartile range (IQR) for aforementioned PAHs using conditional logistic regression.

RESULTS

An IQR increase (16.9 ng/m3) in 2-day (the current and prior day) moving average of total PAH concentration was associated with risk increases of 1.90% (95% confidence interval [CI]: 1.71-2.09) in all-cause mortality, 1.90% (95% CI: 1.70-2.10) in nonaccidental mortality, 2.01% (95% CI: 1.72-2.29) in circulatory mortality, and 2.53% (95% CI: 2.03-3.02) in respiratory mortality. Risk increases of cause-specific mortality ranged between 1.42-1.90% for BaA (IQR: 1.6 ng/m3), 1.94-2.53% for BaP (IQR: 1.6 ng/m3), 2.45-3.16% for BbF (IQR: 2.8 ng/m3), 2.80-3.65% for BkF (IQR: 1.0 ng/m3), 1.36-1.77% for Chr (IQR: 1.8 ng/m3), 0.77-1.24% for DahA (IQR: 0.8 ng/m3), and 2.96-3.85% for IcdP (IQR: 1.7 ng/m3).

CONCLUSIONS

This study provided suggested evidence for heightened mortality risk in relation to short-term exposure to airborne PAHs in general population. Our findings suggest that airborne PAHs may pose a potential threat to public health, emphasizing the need of more population-based evidence to enhance the understanding of health risk under the low-dose exposure scenario.

The joint impact of PM2.5 constituents on the risk of cerebrovascular diseases hospitalization: A large community-based cohort study

Air pollution poses significant health risks to urban areas, with limited focus on the chronic association of PM2.5 and its constituents on cerebrovascular diseases (CERs), especially regarding the joint associations. This study explores the individual and joint associations between PM2.5 constituents and CER hospitalization risks through a cohort analysis of 36,271 adults in the Pearl River Delta, South China, from 2015 to 2020. Cox proportional hazards regression and quantile-based g-computation models were used to quantify the individual and joint associations of annual mean concentrations of PM2.5 constituents with hospitalization for CERs. 1151 participants were hospitalized due to CERs during the five-year follow-up period. Joint associations analyses identified that one quartile increase in co-exposure may result in hazard ratios of 1.530 (1.441-1.623), 1.840 (1.710-1.980), and 1.609 (1.491-1.737) for CERs, total, and ischemic stroke hospitalization, respectively. The adverse effect was primarily driven by organic matter and chlorine. Men, those with a history of tobacco or alcohol use or with low residential greenness, were more susceptible to CERs hospitalization following PM2.5 constituents co-exposure. Upcoming strategies should focus on monitoring and regulating PM2.5 constituents, encouraging healthy lifestyles, and enhancing urban greenery.

Dissecting the Photochemical Reactivity of Metal Ions during Atmospheric Nitrate Transformations on Photoactive Mineral Dust

Dissecting the photochemical reactivity of metal ions is a significant contribution to understanding secondary pollutant formation, as they have a role to be reckoned with atmospheric chemistry. However, their photochemical reactivity has received limited attention within the active nitrogen cycle, particularly at the gas-solid interface. In this study, we delve into the contribution of magnesium ion (Mg2+) and ferric ion (Fe3+) to nitrate decomposition on the surface of photoactive mineral dust. Under simulated sunlight irradiation, the observed NOX production rate differs by an order of magnitude in the presence of Mg2+ (6.02 × 10-10 mol s-1) and Fe3+ (2.07 × 10-11 mol s-1). The markedly decreased fluorescence lifetime induced by Mg2+ and the change in the valence of Fe3+ revealed that Mg2+ and Fe3+ significantly affect the concentration of nitrate decomposition products by distinct photochemical reactivity with photogenerated electrons. Mg2+ promotes NOX production by accelerating charge transfer, while Fe3+ hinders nitrate decomposition by engaging in a redox cyclic reaction with Fe2+ to consume photogenerated carriers continuously. Furthermore, when Fe3+ coexists with other metal ions (e.g., Mg2+, Ca2+, Na+, and K+) and surpasses a proportion of approximately 12%, the photochemical reactivity of Fe3+ tends to be dominant in depleting photogenerated electrons and suppressing nitrate decomposition. Conversely, below this threshold, the released NOX concentration increases sharply as the proportion of Fe3+ decreases. This research offers valuable insights into the role of metal ions in nitrate transformation and the generation of reactive nitrogen species, contributing to a deep understanding of atmospheric photochemical reactions.

Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities

Short-term exposure to particles with aerodynamic diameters less than 2.5 μm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.

High-Resolution Spatiotemporal Modeling for PM2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3-, NH4+, and SO42-) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 μg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Associations between particulate matter exposure during pregnancy and executive function of toddlers in a prospective cohort study

BACKGROUND

Exposure to particulate matter (PM) has been found to be associated with impaired cognitive function. However, limited evidence is available on the relationship between PM exposure in the prenatal period and toddler executive function (EF), and the potential influence of breastfeeding.

METHODS

The study included 1106 mother-toddler pairs recruited between 2015 and 2019. We assessed mothers' PM1, PM2.5, and PM10 prenatal exposure with a satellite-based dataset at a 1 × 1 km spatial resolution and assigned to participants based on residential addresses. Toddler EF was measured using the Behavior Rating Inventory of Executive Function for Preschoolers (BRIEF-P) questionnaire, higher BRIEF-P scores indicated poorer EF in toddlers. We determined the associations of PM exposure during pregnancy with BRIEF-P scores using multiple linear regression models.

RESULTS

In the first trimester, a 10 μg/m3 increase of PM was associated with 1.49 (95% confidence interval [CI]: 0.14-2.83; PM1), 0.68 (95% CI: 0.10-1.26; PM2.5), and 0.63 (95% CI: 0.07-1.20; PM10) elevated toddler global executive composite index scores, respectively. In the stratified analysis, a 10 μg/m3 increase in first trimester PM1 exposure was related to 0.54 (95% CI: 0.19-0.89) higher inhibition scores in toddlers who received complementary breastfeeding for less than six months and -0.15 (95% CI: 0.81-0.51) higher inhibition scores in toddlers who received complementary breastfeeding for six months or more (P for interaction: 0.046). Additionally, a 10 μg/m3 increment in first trimester PM1 exposure was related to 0.36 (95% CI: 0.13-0.59) higher emotional control scores in toddlers who received breastfeeding for less than 12 months and -0.54 (95% CI: 1.25-0.18) higher inhibition scores in toddlers who received breastfeeding for no less than 12 months (P for interaction: 0.043).

CONCLUSIONS

PM exposure during the first trimester, especially PM1, has been linked to lower toddler EF performance in toddlers; feeding with breast milk may be a potential protective measure.

Gestational Exposure to PM2.5 and Specific Constituents, Meconium Metabolites, and Neonatal Neurobehavioral Development: A Cohort Study

Exposure to fine particulate matter (PM2.5) during pregnancy has been inversely associated with neonatal neurological development. However, the associations of exposure to specific PM2.5 constituents with neonatal neurological development remain unclear. We investigated these associations and examined the mediating role of meconium metabolites in a Chinese birth cohort consisting of 294 mother-infant pairs. Our results revealed that exposure to PM2.5 and its specific constituents (i.e., organic matter, black carbon, sulfate, nitrate, and ammonium) in the second trimester, but not in the first or third trimester, was inversely associated with the total neonatal behavioral neurological assessment (NBNA) scores. The PM2.5 constituent mixture in the second trimester was also inversely associated with NBNA scores, and sulfate was identified as the largest contributor. Furthermore, meconium metabolome analysis identified four metabolites, namely, threonine, lysine, leucine, and saccharopine, that were associated with both PM2.5 constituents and NBNA scores. Threonine was identified as an important mediator, accounting for a considerable proportion (14.53-15.33%) of the observed inverse associations. Our findings suggest that maternal exposure to PM2.5 and specific constituents may adversely affect neonatal behavioral development, in which meconium metabolites may play a mediating role.

Gestational and Postpartum Exposure to PM2.5 Components and Glucose Metabolism in Chinese Women: A Prospective Cohort Study

Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6-8 weeks postpartum. Residential PM2.5 and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5 exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5 exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction = 0.003). In the quantile-based g-computation model, NO3- consistently contributed to the combined effect of PM2.5 components on gestational and postpartum FPG. This study was the first to suggest that PM2.5 components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5 components are essential to improving maternal glucose metabolism.

Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China

BACKGROUND

The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome.

METHODS AND RESULTS

A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05).

CONCLUSIONS

Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.

Long-term PM1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China

Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.

Long-term exposure to major constituents of fine particulate matter and neurodegenerative diseases: A population-based survey in the Pearl River Delta Region, China

BACKGROUND

Exposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions.

OBJECTIVES

To explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases.

METHODS

We recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer's disease (AD) and Parkinson's disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence.

RESULTS

PM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45-2.27; 1.78; 95% CI, 1.37-2.32; and 1.99; 95% CI, 1.54-2.57 for the second, third, and fourth quartiles, respectively).

CONCLUSIONS

Long-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals.

ENVIRONMENTAL IMPLICATION

PM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.

Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease and subtypes: A retrospective cohort study of the employed population of Southwest China

BACKGROUND

While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear.

OBJECTIVE

To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes.

METHODS

Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3-, SO42-, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD.

RESULTS

Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42-, NO3-, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42- (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD.

CONCLUSIONS

Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.

Effects of different sizes of ambient particulate matter and household fuel use on physical function: National cohort study in China

BACKGROUND

Impact of outdoor and household air pollution on physical function remains unelucidated. This study examined the influence of various ambient particulate sizes (PM1, PM2.5, and PM10) and household fuel usage on physical function.

METHODS

Data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011 and 2015 were utilized. The physical functional score was computed by summing scores from four tests: grip strength, gait speed, chair stand test, and balance. Multivariate linear and linear mixed-effects models were used to explore the separate and combined effects of PM1, PM2.5, PM10 and household fuel use on physical function in the cross-sectional and longitudinal analyses, respectively, and to further observe the effects of fuel cleanup on physical function in the context of air pollution exposure.

RESULTS

Both cross-sectional and longitudinal analyses revealed negative correlations between PM1 (β = -0.044; 95% CI: -0.084, -0.004), PM2.5 (β = -0.024; 95% CI: -0.046, -0.001), PM10 (β = -0.041; 95% CI: -0.054, -0.029), and physical function, with a more pronounced impact observed for fine particulate matter (PM1). Cleaner fuel use was associated with enhanced physical function compared to solid fuels (β = 0.143; 95% CI: 0.070, 0.216). The presence of air pollutants and use of solid fuels had a negative impact on physical function, while cleaner fuel usage mitigated the adverse effects of air pollutants, particularly in areas with high exposure.

CONCLUSION

This study underscores the singular and combined detrimental effects of air pollutants and solid fuel usage on physical function. Addressing fine particulate matter, specifically PM1, and prioritizing efforts to improve household fuel cleanliness in regions with elevated air pollution levels are crucial for preventing physical disability.

Short-term association of particulate matter and cardiovascular disease mortality in Shanghai, China between 2003 and 2020

Objective

Evidence regarding the effects of particulate matter (PM) pollutants on cardiovascular disease (CVD) mortality remains limited in Shanghai, China. Our objective was to thoroughly evaluate associations between PM pollutants and CVD mortality.

Methods

Daily data on CVD mortality, PM (PM10 and PM2.5) pollutants, and meteorological variables in Shanghai, China were gathered from 2003 to 2020. We utilized a time-series design with the generalized additive model to assess associations between PM pollutants and CVD mortality. Additionally, we conducted stratified analyses based on sex, age, education, and seasons using the same model.

Results

We found that PM pollutants had a significant association with CVD mortality during the study period. Specifically, there was a 0.29% (95%CI: 0.14, 0.44) increase in CVD mortality for every 10 μg/m3 rise in a 2-day average (lag01) concentration of PM10. A 0.28% (95% CI: 0.07, 0.49) increase in CVD mortality was associated with every 10 μg/m3 rise in PM2.5 concentration at lag01. Overall, the estimated effects of PM10 and PM2.5 were larger in the warm period compared with the cold period. Furthermore, males and the older adult exhibited greater susceptibility to PM10 and PM2.5 exposure, and individuals with lower education levels experienced more significant effects from PM10 and PM2.5 than those with higher education levels.

Conclusion

Our findings suggested that PM pollutants have a substantial impact on increasing CVD mortality in Shanghai, China. Moreover, the impacts of air pollution on health may be altered by factors such as season, sex, age, and educational levels.

Ambient fine particulate matter constituents and semen quality among adult men in China

Exposure to ambient fine particulate matter (PM2.5) was associated with decreased semen quality, but the relationship between PM2.5 constituents and semen quality was unclear. We recruited 27,824 adult men attending an infertility clinic in Wuhan, China, between 2014 and 2020. We used a four-dimensional spatiotemporal deep forest model to estimate concentrations of PM2.5 mass and its chemical constituents, including organic matter (OM), black carbon (BC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-). We employed linear regression models to estimate the association between PM2.5 mass and its constituents with various sperm parameters. Exposure to PM2.5 was associated with a reduction in sperm quality, with a percent change of - 5.69% (95% confidence interval [CI]: -8.53%, -2.85%) for sperm density, - 15.09% (95% CI: -22.24%, -7.94%) for sperm total count, - 1.63% (95% CI: -2.36%, -0.91%) for sperm progressive motility, and - 2.30% (95% CI: -3.04%, -1.55%) for sperm total motility. Among specific constituents, exposure to OM, BC, Cl-, or NO3- was associated with a reduction in these four semen quality parameters. The association was more pronounced among older men or individuals with lower levels of education. Our findings suggest that PM2.5 mass and each constituent were associated with decreased semen quality in adult men.

Spatiotemporally continuous PM2.5 dataset in the Mekong River Basin from 2015 to 2022 using a stacking model

With the potential to cause millions of deaths, PM2.5 pollution has become a global concern. In Southeast Asia, the Mekong River Basin (MRB) is experiencing heavy PM2.5 pollution and the existing PM2.5 studies in the MRB are limited in terms of accuracy and spatiotemporal coverage. To achieve high-accuracy and long-term PM2.5 monitoring of the MRB, fused aerosol optical depth (AOD) data and multi-source auxiliary data are fed into a stacking model to estimate PM2.5 concentrations. The proposed stacking model takes advantage of convolutional neural network (CNN) and Light Gradient Boosting Machine (LightGBM) models and can well represent the spatiotemporal heterogeneity of the PM2.5-AOD relationship. In the cross-validation (CV), comparison with CNN and LightGBM models shows that the stacking model can better suppress overfitting, with a higher coefficient of determination (R2) of 0.92, a lower root mean square error (RMSE) of 5.58 μg/m3, and a lower mean absolute error (MAE) of 3.44 μg/m3. For the first time, the high-accuracy PM2.5 dataset reveals spatially and temporally continuous PM2.5 pollution and variations in the MRB from 2015 to 2022. Moreover, the spatiotemporal variations of annual and monthly PM2.5 pollution are also investigated at the regional and national scales. The dataset will contribute to the analysis of the causes of PM2.5 pollution and the development of mitigation policies in the MRB.

Spatiotemporal patterns and drivers of the urban air pollution island effect for 2273 cities in China

Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban-rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM2.5 and PM10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM2.5 and PM10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control.

Modification of Food Allergy on the Associations between Early Life Exposure to Size-Specific Particulate Matter and Childhood Allergic Rhinitis

Previous studies have reported the association between particulate matter (PM) and childhood allergic rhinitis (AR). However, it is unclear whether food allergy (FA) modifies the PM-AR association. We aimed at evaluating the effect of the modification of FA on PM-AR association in preschool children. We adopted a cross-sectional study and conducted a questionnaire survey among preschool children aged 3-6 years in 7 cities in China from June 2019 to June 2020 to collect information on AR and FA. We used a combination of multilevel logistic regression and restricted cubic spline functions to quantitatively assess whether FA modifies the associations between size-specific PM exposure (1 × 1 km) and the risk of AR. The adjusted odds ratios (ORs) for AR among the children with FA as per a 10 μg/m3 increase in early life PM1, PM2.5, and PM10 were significantly higher than the corresponding ORs among the children without FA [e.g., OR: 1.58, 95% CI: (1.32, 1.90) vs 1.29, 95% CI: (1.18, 1.41), per 10 μg/m3 increase in PM1]. The interactions between FA and size-specific PM exposure and their effects on AR were statistically significant (all p-int < 0.001). FA, as an important part of the allergic disease progression, may modify the PM-AR association in preschool children.

Association of ambient air pollution and pregnancy rate among women undergoing assisted reproduction technology in Fujian, China: A retrospective cohort study

BACKGROUND

Previous studies have reported the impact of ambient air pollutants on assisted reproduction. They concentrated on highly polluted environments and individual pollutants. It is unclear whether these effects continue at lower levels and as mixed effects. We aimed to study the influence of lower pollutant concentrations on pregnancy rates and identify vulnerable populations.

METHODS

We conducted a retrospective cohort study involving 9465 patients with infertility who received treatment from a local hospital between 2015 and 2021. Daily average levels of six pollutants (PM2.5, PM10, NO2, CO, SO2, and O3) were collected from air quality monitoring stations. We employed generalized linear regression models (logistic, linear, and lasso), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) to assess the impact of pollutants on pregnancy rates. Additionally, stratified analyses were performed to identify potentially vulnerable populations.

RESULTS

Findings from the generalized linear models revealed a significant negative correlation between interquartile range increment exposure to PM2.5 (OR = 1.17, 95 % CI = 1.09-1.26), PM10 (OR = 1.18, 95 % CI = 1.11-1.26), NO2 (OR = 1.21, 95 % CI = 1.13-1.30), CO (OR = 1.02, 95 % CI = 1.00-1.03), SO2 (OR = 1.11, 95 % CI = 1.05-1.17) and pregnancy rate when considering the effects of individual pollutants. The WQS index exhibited a negative correlation with pregnancy rates and the number of oocytes retrieved (aOR = 1.20, 95 % CI = 1.08-1.34). BKMR analyses indicated an overall significant trend of decreasing pregnancy rates as pollutant concentrations increased across percentiles. Stratified analysis unveiled heightened sensitivity to pollutants among individuals aged ≥35 years.

CONCLUSIONS

By comparing results obtained from diverse models, we observed that exposure to lower levels of air pollutants led to decreased pregnancy rates. Notably, PM10, NO2, SO2, and CO emerged as the four most prominent pollutants in this context. Moreover, stratified analyses highlighted that individuals aged ≥35 years exhibited heightened susceptibility to pollutants.

Ozone, Heat Wave, and Cardiovascular Disease Mortality: A Population-Based Case-Crossover Study

A case-crossover study among 511,767 cardiovascular disease (CVD) deaths in Jiangsu province, China, during 2015-2021 was conducted to assess the association of exposure to ambient ozone (O3) and heat wave with CVD mortality and explore their possible interactions. Heat wave was defined as extreme high temperature for at least two consecutive days. Grid-level heat waves were defined by multiple combinations of apparent temperature thresholds and durations. Residential O3 and heat wave exposures were assessed using grid data sets (spatial resolution: 1 km × 1 km for O3; 0.0625° × 0.0625° for heat wave). Conditional logistic regression models were applied for exposure-response analyses and evaluation of additive interactions. Under different heat wave definitions, the odds ratios (ORs) of CVD mortality associated with medium-level and high-level O3 exposures ranged from 1.029 to 1.107 compared with low-level O3, while the ORs for heat wave exposure ranged from 1.14 to 1.65. Significant synergistic effects on CVD mortality were observed for the O3 and heat wave exposures, which were generally greater with higher levels of the O3 exposure, higher temperature thresholds, and longer durations of heat wave exposure. Up to 5.8% of the CVD deaths were attributable to O3 and heat wave. Women and older adults were more vulnerable to the exposure to O3 and heat wave exposure. Exposure to both O3 and heat wave was significantly associated with an increased odds of CVD mortality, and O3 and heat wave can interact synergistically to trigger CVD deaths.

Drivers and impacts of decreasing concentrations of atmospheric volatile organic compounds (VOCs) in Beijing during 2016-2020

China has implemented various policies and measures for controlling air pollutants. However, our knowledge of the long-term trends in ambient volatile organic compounds (VOCs) after the implementation of these action plans in China remains limited. To address this, we conducted a five-year analysis (2016-2020) of VOC compositions and concentrations in Beijing. The annual VOC concentration decreased from 44.0 ± 28.8 to 26.2 ± 16.4 ppbv, with alkanes being the most prevalent group. The annual average concentrations of alkenes, alkynes, and aromatics have experienced a significant decrease of over 50 %. Seasonal variations indicated higher VOC concentrations in winter and autumn, with more significant reductions observed in winter and autumn. The impact of meteorological conditions caused variations in VOC reductions during the Chinese Spring Festival. Satellite-based measurements of formaldehyde (HCHO) columns confirmed the reduction of VOC emissions during the Coronavirus (COVID-19) lockdown. The normalized annual average VOC concentration decreased by 2.9ppbv yr-1 from 2016 to 2020, and emission reduction contributed to 58.8 % of VOC reduction from 2016 to 2020 after meteorological normalization, indicating the effectiveness of implemented control measures. Based on receptor model, vehicle emissions and industrial sources were identified as the largest contributors to VOC concentrations. Vehicle emissions, liquefied petroleum gas/natural gas (LPG/NG) use, and coal combustion were major drivers of VOC reduction. Potential source region analysis revealed that air masses transported from northwestern and southern regions significantly contributed to VOC concentrations in Beijing. The range of source regions shrunk in both northwestern and southern regions with the reduction in VOC concentrations. The annual variations of ozone formation potential indicated a significant decrease in VOC reactivities through emission control. These results could provide insights into future emission control and coordinated efforts to improve PM2.5 and ozone levels in China.

Long-term exposure to PM1 is associated with increased prevalence of metabolic diseases: evidence from a nationwide study in 123 Chinese cities

Exposure to particulate matter (PM) has been linked to metabolic diseases. However, the effects of PM with an aerodynamic diameter ≤ 1.0 µm (PM1) on metabolic diseases remain unclear. This study is aimed at assessing the associations of PM1 with metabolic disease risk and quantifying the concentration-response (C-R) relationship of PM1 with metabolic disease risk. A national cross-sectional study was conducted, including 12,495 middle-aged and older adults in 123 Chinese cities. The two-year average concentration of PM1 was evaluated using satellite-based spatiotemporal models. Metabolic diseases, including abdominal obesity, diabetes, hypertension, dyslipidemia, and metabolic syndrome, were identified based on physical examination, blood standard biochemistry examination, and self-reported disease histories. Generalized linear models and C-R curves were used to evaluate the associations of PM1 with metabolic diseases. A total of 12,495 participants were included in this study, with a prevalence of 45.73% for abdominal obesity, 20.22% for diabetes, 42.46% for hypertension, 41.01% for dyslipidemia, and 33.78% for metabolic syndrome. The mean ± standard deviation age of participants was 58.79 ± 13.14 years. In addition to dyslipidemia, exposure to PM1 was associated with increased risks of abdominal obesity, diabetes, hypertension, and metabolic syndrome. Each 10 μg/m3 increase in PM1 concentrations was associated with 39% (odds ratio (OR) = 1.39, 95% confidence interval (CI) 1.33, 1.46) increase in abdominal obesity, 18% (OR = 1.18, 95%CI 1.12, 1.25) increase in diabetes, 11% (OR = 1.11, 95%CI 1.06, 1.16) increase in hypertension, and 25% (OR = 1.25, 95%CI 1.19, 1.31) in metabolic syndrome, respectively. C-R curves showed that the OR values of abdominal obesity, diabetes, hypertension, and metabolic syndrome were increased gradually with the increase of PM1 concentrations. Subgroup analysis indicated that exposure to PM1 was associated with increased metabolic disease risks among participants with different lifestyles and found that solid fuel users were more susceptible to PM1 than clean fuel users. This national cross-sectional study indicated that exposure to higher PM1 might increase abdominal obesity, diabetes, hypertension, and metabolic syndrome risk, and solid fuel use might accelerate the adverse effects of PM1 on metabolic syndrome risk. Further longitudinal cohort studies are warranted to establish a causal inference between PM1 exposure and metabolic disease risk.

First close insight into global daily gapless 1 km PM2.5 pollution, variability, and health impact

Here we retrieve global daily 1 km gapless PM2.5 concentrations via machine learning and big data, revealing its spatiotemporal variability at an exceptionally detailed level everywhere every day from 2017 to 2022, valuable for air quality monitoring, climate change, and public health studies. We find that 96%, 82%, and 53% of Earth's populated areas are exposed to unhealthy air for at least one day, one week, and one month in 2022, respectively. Strong disparities in exposure risks and duration are exhibited between developed and developing countries, urban and rural areas, and different parts of cities. Wave-like dramatic changes in air quality are clearly seen around the world before, during, and after the COVID-19 lockdowns, as is the mortality burden linked to fluctuating air pollution events. Encouragingly, only approximately one-third of all countries return to pre-pandemic pollution levels. Many nature-induced air pollution episodes are also revealed, such as biomass burning.

Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study

BACKGROUND

Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate trends in black carbon and PM2·5 concentrations and their attributable mortality burden across the USA.

METHODS

In this study, we derived daily concentrations of PM2·5 and its highly toxic black carbon component at a 1-km resolution in the USA from 2000 to 2020 via deep learning that integrated big data from satellites, models, and surface observations. We estimated the annual PM2·5-attributable and black carbon-attributable mortality burden at each 1-km2 grid using concentration-response functions collected from a national cohort study and a meta-analysis study, respectively. We investigated the spatiotemporal linear-regressed trends in PM2·5 and black carbon pollution and their associated premature deaths from 2000 to 2020, and the impact of wildfires on air quality and public health.

FINDINGS

Our results showed that PM2·5 and black carbon estimates are reliable, with sample-based cross-validated coefficients of determination of 0·82 and 0·80, respectively, for daily estimates (0·97 and 0·95 for monthly estimates). Both PM2·5 and black carbon in the USA showed significantly decreasing trends overall during 2000 to 2020 (22% decrease for PM2·5 and 11% decrease for black carbon), leading to a reduction of around 4200 premature deaths per year (95% CI 2960-5050). However, since 2010, the decreasing trends of fine particles and premature deaths have reversed to increase in the western USA (55% increase in PM2·5, 86% increase in black carbon, and increase of 670 premature deaths [460-810]), while remaining mostly unchanged in the eastern USA. The western USA showed large interannual fluctuations that were attributable to the increasing incidence of wildfires. Furthermore, the black carbon-to-PM2·5 mass ratio increased annually by 2·4% across the USA, mainly due to increasing wildfire emissions in the western USA and more rapid reductions of other components in the eastern USA, suggesting a potential increase in the relative toxicity of PM2·5. 100% of populated areas in the USA have experienced at least one day of PM2·5 pollution exceeding the daily air quality guideline level of 15 μg/m3 during 2000-2020, with 99% experiencing at least 7 days and 85% experiencing at least 30 days. The recent widespread wildfires have greatly increased the daily exposure risks in the western USA, and have also impacted the midwestern USA due to the long-range transport of smoke.

INTERPRETATION

Wildfires have become increasingly intensive and frequent in the western USA, resulting in a significant increase in smoke-related emissions in populated areas. This increase is likely to have contributed to a decline in air quality and an increase in attributable mortality. Reducing fire risk via effective policies besides mitigation of climate warming, such as wildfire prevention and management, forest restoration, and new revenue generation, could substantially improve air quality and public health in the coming decades.

FUNDING

National Aeronautics and Space Administration (NASA) Applied Science programme, NASA MODIS maintenance programme, NASA MAIA satellite mission programme, NASA GMAO core fund, National Oceanic and Atmospheric Administration (NOAA) GEO-XO project, NOAA Atmospheric Chemistry, Carbon Cycle, and Climate (AC4) programme, and NOAA Educational Partnership Program with Minority Serving Institutions.

Estimation of health risk and economic loss attributable to PM2.5 and O3 pollution in Jilin Province, China

Ambient pollutants, particularly fine particulate matter (PM2.5) and ozone (O3), pose significant risks to both public health and economic development. In recent years, PM2.5 concentration in China has decreased significantly, whereas that of O3 has increased rapidly, leading to considerable health risks. In this study, a generalized additive model was employed to establish the relationship of PM2.5 and O3 exposure with non-accidental mortality across 17 districts and counties in Jilin Province, China, over 2015-2016. The health burden and economic losses attributable to PM2.5 and O3 were assessed using high-resolution satellite and population data. According to the results, per 10 µg/m3 increase in PM2.5 and O3 concentrations related to an overall relative risk (95% confidence interval) of 1.004 (1.001-1.007) and 1.009 (1.005-1.012), respectively. In general, the spatial distribution of mortality and economic losses was uneven. Throughout the study period, a total of 23,051.274 mortalities and 27,825.015 million Chinese Yuan (CNY) in economic losses were attributed to O3 exposure, which considerably surpassing the 5,450.716 mortalities and 6,553,780 million CNY in economic losses attributed to PM2.5 exposure. The O3-related health risks and economic losses increased by 3.75% and 9.3% from 2015 to 2016, while those linked to PM2.5 decreased by 23.33% and 18.7%. Sensitivity analysis results indicated that changes in pollutant concentrations were the major factors affecting mortality rather than baseline mortality and population.

The effect of multiple factors on water-soluble inorganic ions in diesel particulate matter emissions

The water-soluble inorganic ions (WSII) in diesel particulate matter (DPM) have a significant impact on ambient air quality and human health. In this study, the 12 groups of bench tests were conducted to analyze the emission characteristics of two diesel engines, taking into account the influence of engine parameters, test cycle, fuel types, and after-treatment measures. Compared to conventional diesel, a blend of diesel with 5 % biodiesel resulted in a reduction of the WSII emission factors by 23.7-48.0 %. The emission factors of WSII decreased by 8.4 % after installing selective catalytic reduction (SCR). Dummy variable regression analysis was used to analyze the relationship between WSII and influencing factors. The emission factors of Na+, K+, and Ca2+ were mostly affected by the engine, potentially due to the use of coolants and lubricants containing metal oxides in the engine. The emission factors of NO3- were mainly affected by the test cycle. Techniques for order preference by similarity to ideal solution (TOPSIS) were used to analyze the priority of emission reduction technologies. The results indicated that SCR, biodiesel, and low-sulfur diesel could effectively reduce WSII. This study aims to explore the influence of multiple factors on WSII, providing valuable insights for future research on WSII in DPM.

Exposure to Fine Particulate Matter Constituents and Human Semen Quality Decline: A Multicenter Study

Exposure to fine particulate matter (PM < 2.5 μm in diameter [PM2.5]) may accelerate human sperm quality decline, although research on this association is limited. Our objective was to investigate the relationship between exposure to the chemical constituents of PM2.5 air pollution and decreased sperm quality and to further explore the exposure-response relationship. We conducted a multicenter population-based cohort study including 78,952 semen samples from 33,234 donors at 6 provincial human sperm banks (covering central, northern, southern, eastern, and southwestern parts of China) between 2014 and 2020. Daily exposure to PM2.5 chemical composition was estimated using a deep learning model integrating a density ground-based measure network at a 1 km resolution. Linear mixed models with subject- and center-specific intercepts were used to quantify the harmful impacts of PM2.5 constituents on semen quality and explore their exposure-response relationships. Per interquartile range (IQR) increase in PM2.5 exposure levels during spermatogenesis was significantly associated with decreased sperm concentration, progressive motility, and total motility. For PM2.5 constituents, per IQR increment in Cl- (β: -0.02, 95% CI: [-0.03, -0.00]) and NO3- (β: -0.05, 95% CI: [-0.08, -0.02]) exposure was negatively associated with sperm count, while NH4+ (β: -0.03, 95% CI: [-0.06, -0.00]) was significantly linked to decreased progressive motility. These results suggest that exposure to PM2.5 chemical constituents may adversely affect human sperm quality, highlighting the urgent need to reduce PM2.5 exposure.