Elucidating transport dynamics and regional division of PM2.5 and O3 in China using an advanced network model.

Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.

PM2.5 regulates the progression of lung adenocarcinoma through the axis of HCG18, miR-195 and ATG14.

Relevant studies have indicated the association of HCG18 with tumour occurrence and progression. In this study, we observed that PM2.5 can enhance the growth of lung adenocarcinoma cells by modulating the expression of HCG18. Further investigations, including overexpression and knockout experiments, elucidated that HCG18 suppresses miR-195, which in turn upregulates the expression of ATG14, resulting in the upregulation of autophagy. Consequently, exposure to PM2.5 leads to elevated HCG18 expression in lung tissues, which in turn increases Atg14 expression and activates autophagy pathways through inhibition of miR-195, thereby contributing to oncogenesis.

Salidroside Ameliorates Lung Injury Induced by PM 2.5by Regulating SIRT1-PGC-1α in Mice.

Objective: This study aimed to clarify the intervention effect of salidroside (SAL) on lung injury caused by PM 2.5 in mice and illuminate the function of SIRT1-PGC-1ɑ axis. Methods: Specific pathogen-free (SPF) grade male C57BL/6 mice were randomly assigned to the following groups: control group, SAL group, PM 2.5 group, SAL+PM 2.5 group. On the first day, SAL was given by gavage, and on the second day, PM 2.5 suspension was given by intratracheal instillation. The whole experiment consist of a total of 10 cycles, lasting 20 days. At the end of treatment, blood samples and lung tissues were collected and analyzed. Observation of pathological changes in lung tissue using inverted microscopy and transmission electron microscopy. The expression of inflammatory, antioxidants, apoptosis, and SIRT1-PGC-1ɑ proteins were detected by Western blotting. Results: Exposure to PM 2.5 leads to obvious morphological and pathologica changes in the lung of mice. PM 2.5 caused a decline in levels of antioxidant-related enzymes and protein expressions of HO-1, Nrf2, SOD2, SIRT1 and PGC-1ɑ, and an increase in the protein expressions of IL-6, IL-1ß, Bax, caspase-9 and cleaved caspase-3. However, SAL reversed the aforementioned changes caused by PM 2.5 by activating the SIRT1-PGC-1α pathway. Conclusion: SAL can activate SIRT1-PGC-1ɑ to ameliorate PM 2.5-induced lung injury.

Aerosol-PM2.5 Dynamics: in-situ and satellite observations under the influence of regional crop residue burning in post-monsoon over Delhi-NCR, India.

The increasing air pollution in the urban atmosphere is adversely impacts the environment, climate and human health. The alarming degradation of air quality, atmospheric conditions, economy and human life due to air pollution needs significant in-depth studies to ascertain causes, contributions and impacts for developing and implementing an effective policy to combat these issues. This work lies in its multifaceted approach towards comprehensive understanding and mitigating severe pollution episodes in Delhi and its surrounding areas. We investigated the aerosol dynamics in the post-monsoon season (PMS) from 2019-2022 under the influence of both crop residue burning and meteorological conditions. The study involves a broad spectrum of factors, including PM2.5 concentrations, active fire events, and meteorological parameters, shedding light on previously unexplored studies. The average AOD550 (0.799) and PM2.5 concentration (140.12 µg/m³) were the highest in 2019. PM2.5 was higher from mid-October to mid-November each year, exceeding the WHO guideline of 15 µg/m³ (24 hours) by 27 to 34 times, signifying a public health emergency. A moderate to strong correlation between PM2.5 and AOD was found (r = 0.650) in 2021. The hotspot region accounts for almost 50% (2019), 47.51% (2020), 57.91% (2021) and 36.61% (2022) of the total fire events. A statistically significant negative non-linear correlation (r) was observed between wind speed (WS) and both AOD and PM2.5 concentration, influencing air quality over the region. HYSPLIT model and Windrose result show the movement of air masses predominated from the North and North-West direction during PMS. This study suggest to promotes strategies such as alternative waste management, encouraging modern agricultural practices in hot-spot regions, and enforcing strict emission norms for industries and vehicles to reducing air pollution and its detrimental effects on public health in the region and also highlights the need for future possibilities of research to attract the global attention.

PM2.5 exposure contributes to anxiety and depression-like behaviors via phenyl-containing compounds interfering with dopamine receptor.

As a global problem, fine particulate matter (PM2.5) really needs local fixes. Considering the increasing epidemiological relevance to anxiety and depression but inconsistent toxicological results, the most important question is to clarify whether and how PM2.5 causally contributes to these mental disorders and which components are the most dangerous for crucial mitigation in a particular place. In the present study, we chronically subjected male mice to a real-world PM2.5 exposure system throughout the winter heating period in a coal combustion area and revealed that PM2.5 caused anxiety and depression-like behaviors in adults such as restricted activity, diminished exploratory interest, enhanced repetitive stereotypy, and elevated acquired immobility, through behavioral tests including open field, elevated plus maze, marble-burying, and forced swimming tests. Importantly, we found that dopamine signaling was perturbed using mRNA transcriptional profile and bioinformatics analysis, with Drd1 as a potential target. Subsequently, we developed the Drd1 expression-directed multifraction isolating and nontarget identifying framework and identified a total of 209 compounds in PM2.5 organic extracts capable of reducing Drd1 expression. Furthermore, by applying hierarchical characteristic fragment analysis and molecular docking and dynamics simulation, we clarified that phenyl-containing compounds competitively bound to DRD1 and interfered with dopamine signaling, thereby contributing to mental disorders. Taken together, this work provides experimental evidence for researchers and clinicians to identify hazardous factors in PM2.5 and prevent adverse health outcomes and for local governments and municipalities to control source emissions for diminishing specific disease burdens.

Air pollution control and carbon reduction policies: Assessing effectiveness in alleviating PM2.5-associated mortality in China.

To confront the challenges posed by air pollution and climate change, China has undertaken significant initiatives to develop strategies that address both issues concurrently. However, the health benefits of these initiatives have not been clearly articulated. In this study, the dynamic changes in health impacts under air pollution and carbon reduction actions in China are evaluated by employing the latest concentration-response models and projected PM2.5 concentrations under future scenarios. From 2020 to 2060, the enforcement of clean air and climate mitigation policies is expected to increase the percentage of the population living with PM2.5 concentrations meeting the 10 µg/m3 standard by 79 %. Without the implementation of relevant mitigation measures, PM2.5-associated deaths are projected to double due to an aging population. In comparison to the 2060 reference scenario, the joint implementation of clean air and carbon neutrality measures is expected to reduce nationwide PM2.5-associated mortality by 62 %, equivalent to 2.15 (95 % CI: 1.80-2.48) million deaths. Stringent pollution controls are crucial for reducing PM2.5-associated deaths before 2030, after which carbon neutrality actions become increasingly significant from 2030 to 2060. The challenges of mitigating future PM2.5-associated deaths vary greatly across regions, showing a critical response to pollution control and carbon reduction. The research proves the effectiveness of China's future air pollution control and carbon reduction policies in mitigating PM2.5-associated deaths.

PM2.5 exposure promotes the progression of acute kidney injury by activating NLRP3-mediated macrophage inflammatory response.

AIM: We reveal the mechanism of action whereby ambient PM2.5 promotes kidney injury. METHODS: Using C57BL/6 mice, the effects of PM2.5 exposure on the acute kidney injury (AKI) were investigated, including renal function changes, expression of inflammatory cytokines, histopathological changes, as well as activation of nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain-containing 3（NLRP3）. The effects of PM2.5 on renal injury after NLRP3 inhibition were explored using NLRP3 inhibitor (MCC950) and NLRP3 knockout mice. The effects of PM2.5 on the inflammatory response of renal macrophages were investigated at the cellular level. RESULTS: PM2.5 exposure could promote kidney injury, NLRP3 activation and inflammatory response in mice. After using MCC950 and NLRP3 knockout mice, the effects of PM2.5 and the kidney injury could be inhibited. The cellular-level results also suggested that MCC950 could inhibit the effects of PM2.5. CONCLUSION: PM2.5 can promote the progression of AKI and aggravate tissue inflammation through NLRP3, which is an important environmental toxicological mechanism of PM2.5.

Associations of Ambient Particulate Matter with Maternal Thyroid Autoimmunity and Thyroid Function in Early Pregnancy.

This prospective birth cohort study evaluated the association of exposure to PM2.5 (diameter ≤2.5 µm), PM1-2.5 (1-2.5 µm), and PM1 (≤1 µm) with maternal thyroid autoimmunity and function during early pregnancy. A total of 15,664 pregnant women were included at 6 to 13+6 gestation weeks in China from 2018 to 2020. Single-pollutant models using generalized linear models (GLMs) showed that each 10 µg/m3 increase in PM2.5 and PM1-2.5 was related with 6% (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.01, 1.12) and 15% (OR = 1.15, 95% CI: 1.08, 1.22) increases in the risk of thyroid autoimmunity, respectively. The odds of thyroid autoimmunity significantly increased with each interquartile range increase in PM2.5 and PM1-2.5 exposure (P for trend <0.001). PM1 exposure was not significantly associated with thyroid autoimmunity. GLM with natural cubic splines demonstrated that increases in PM2.5 and PM1-2.5 exposure were associated with lower maternal FT4 levels, while a negative association between PM1 and FT4 levels was found when exposure exceeded 32.13 µg/m3. Only PM2.5 exposure was positively associated with thyrotropin (TSH) levels. Our findings suggest that high PM exposure is associated with maternal thyroid disruption during the early pregnancy.

Diel variations of airborne microbes and antibiotic resistance genes in Response to urban PM2.5 chemical properties during the heating season.

Among the components of fine particulate matter (PM2.5), the contributions of airborne microorganisms and antibiotic resistance genes (ARGs) to health risks have been overlooked. Airborne microbial dynamics exhibit a unique diurnal cycle due to environmental influences. However, the specific roles of PM2.5 chemical properties resulting from fossil fuel combustion in driving circadian fluctuations in microbial populations and ARGs remain unclear. This study explored the interactions between toxic components and microbial communities during the heating period to understand the variations in ARGs. Bacterial and fungal communities showed a higher susceptibility to diel variations in PM2.5 compared to their chemical properties. Mantel tests revealed that chemical properties and microbial community interactions contribute differently to ARG variations, both directly and indirectly, during circadian fluctuations. Our findings highlight that, during the daytime, the enrichment of pathogenic microorganisms and ARGs increases the risk of PM2.5 toxicity. Conversely, during the nighttime, the utilization of water-soluble ions by the fungal community increased, leading to a significant increase in fungal biomass. Notably, Aspergillus exhibited a significant correlation with mobile genetic elements and ARGs, implying that this genus is a crucial driver of airborne ARGs. This study provides novel insights into the interplay between the chemical composition, microbial communities, and ARGs in PM, underscoring the urgent need for a comprehensive understanding of effective air pollution control strategies.

Reducing air pollution does not necessarily reduce related adults' mortality burden: Variations in 177 countries with different economic levels.

Prolonged exposure to PM2.5 is associated with increased mortality. However, reducing air pollution concentrations does not necessarily reduce the related burden of deaths. Here, we aim to estimate the variations in PM2.5-related mortality due to contributions from key factors - PM2.5 concentration, population exposure, and healthcare levels - for 177 countries from 2000 to 2018 at the 1-km grid scale according to the Global Mortality Exposure Model (GEMM) model. We find that global reductions in PM2.5-related deaths mainly come from high and upper-middle income countries, where lowered air pollutant concentration and better healthcare can offset mortality burdens caused by increasing exposed populations. Changes in population exposure to PM2.5 contribute the most (54 %) to change in global related deaths over the examined period, followed by changes in healthcare (-42 %) and pollution concentrations (4 %). The impacts vary across countries and regions within them due to other drivers, which are significantly influenced by development status. Policies aiming at reducing PM2.5 associated health risks need to account for country-specific balances of these key socioeconomic drivers.

Maternal PM2.5 exposure and hypospadias risk in Chinese offspring: Insights from a nationwide surveillance-based study.

Research on the association between maternal PM2.5 exposure and hypospadias risk in male offspring, particularly in highly polluted areas, has been limited and inconsistent. This study leveraged data from China's National Population-based Birth Defects Surveillance System spanning the years 2013 to 2019, and employed sophisticated machine learning models to estimate daily PM2.5 levels and other pollutants for mothers at a 1-km resolution and a 6-km buffer surrounding maternal residences. Multivariate logistic regression analyses were performed to evaluate the relationship between PM2.5 exposure and hypospadias risk. For sensitivity analyses, stratification analysis was conducted, and models for one-pollutant and two-pollutants, as well as distributed lag nonlinear models, were constructed. Of the 1194,431 boys studied, 1153 cases of hypospadias were identified. A 10 µg/m3 increase in maternal PM2.5 exposure during preconception and the first trimester was associated with an elevated risk of isolated hypospadias, with Odds Ratios (ORs) of 1.102 (95% CI: 1.023-1.188) and 1.089 (95% CI: 1.007-1.177) at the 1-km grid, and 1.122 (95% CI: 1.034-1.218) and 1.143 (95% CI: 1.048-1.246) within the 6-km buffer. Higher quartiles of PM2.5 exposure were associated with increased odds ratios compared to the lowest quartile. These findings highlight a significant association between PM2.5 exposure during the critical conception period and an elevated risk of isolated hypospadias in children, emphasizing the need for targeted interventions to reduce PM2.5 exposure among expectant mothers.

Metabolite correlation permutation after mice acute exposure to PM2.5: Holistic exploration of toxicometabolomics by network analysis.

Many environmental toxicants can cause systemic effects, such as fine particulate matter (PM2.5), which can penetrate the respiratory barrier and induce effects in multiple tissues. Although metabolomics has been used to identify biomarkers for PM2.5, its multi-tissue toxicology has not yet been explored holistically. Our objective is to explore PM2.5 induced metabolic alterations and unveil the intra-tissue responses along with inter-tissue communicational effects. In this study, following a single intratracheal instillation of multiple doses (0, 25, and 150 µg as the control, low, and high dose), non-targeted metabolomics was employed to evaluate the metabolic impact of PM2.5 across multiple tissues. PM2.5 induced tissue-specific and dose-dependent disturbances of metabolites and their pathways. The remarkable increase of both intra- and inter-tissue correlations was observed, with emphasis on the metabolism connectivity among lung, spleen, and heart; the tissues' functional specificity has marked their toxic modes. Beyond the inter-status comparison of the metabolite fold-changes, the current correlation network built on intra-status can offer additional insights into how the multiple tissues and their metabolites coordinately change in response to external stimuli such as PM2.5 exposure.

Long-term source apportionment of PM2.5 across the contiguous United States (2000-2019) using a multilinear engine model.

Identifying PM2.5 sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM2.5 from 515 EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO42-); (6) Secondary nitrate (NO3-) and (7) Sea salt (Mg, Na, Cl and SO42-). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.

Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness.

BACKGROUND: Long-term exposure to PM2.5 has been linked to increased mortality risk. However, limited studies have examined the potential modifying effect of community-level characteristics on this association, particularly in Asian contexts. This study aimed to estimate the effects of long-term exposure to PM2.5 on mortality in South Korea and to examine whether community-level deprivation, medical infrastructure, and greenness modify these associations. METHODS: We conducted a nationwide cohort study using the National Health Insurance Service-National Sample Cohort. A total of 394,701 participants aged 30 years or older in 2006 were followed until 2019. Based on modelled PM2.5 concentrations, 1 to 3-year and 5-year moving averages of PM2.5 concentrations were assigned to each participant at the district level. Time-varying Cox proportional-hazards models were used to estimate the association between PM2.5 and non-accidental, circulatory, and respiratory mortality. We further conducted stratified analysis by community-level deprivation index, medical index, and normalized difference vegetation index to represent greenness. RESULTS: PM2.5 exposure, based on 5-year moving averages, was positively associated with non-accidental (Hazard ratio, HR: 1.10, 95% Confidence Interval, CI: 1.01, 1.20, per 10 µg/m3 increase) and circulatory mortality (HR: 1.22, 95% CI: 1.01, 1.47). The 1-year moving average of PM2.5 was associated with respiratory mortality (HR: 1.33, 95% CI: 1.05, 1.67). We observed higher associations between PM2.5 and mortality in communities with higher deprivation and limited medical infrastructure. Communities with higher greenness showed lower risk for circulatory mortality but higher risk for respiratory mortality in association with PM2.5. CONCLUSIONS: Our study found mortality effects of long-term PM2.5 exposure and underlined the role of community-level factors in modifying these association. These findings highlight the importance of considering socio-environmental contexts in the design of air quality policies to reduce health disparities and enhance overall public health outcomes.

Evaluation of Pm2.5 Influence on Human Lung Cancer Cells Using a Microfluidic Platform.

In this study, we developed a microfluidic device that is able to monitor cell biology under continuous PM2.5 treatment. The effects of PM2.5 on human alveolar basal epithelial cells, A549 cells, and uncovered several significant findings were investigated. The results showed that PM2.5 exposure did not lead to a notable decrease in cell viability, indicating that PM2.5 did not cause cellular injury or death. However, the study found that PM2.5 exposure increased the invasion and migration abilities of A549 cells, suggesting that PM2.5 might promote cell invasiveness. Results of RNA sequencing revealed 423 genes that displayed significant differential expression in response to PM2.5 exposure, with a particular focus on pathways associated with the generation of reactive oxygen species (ROS) and mitochondrial dysfunction. Real-time detection demonstrated an increase in ROS production in A549 cells after exposure to PM2.5. JC1 assay, which indicated a loss of mitochondrial membrane potential (ΔΨm) in A549 cells exposed to PM2.5. The disruption of mitochondrial membrane potential further supports the detrimental effects of PM2.5 on A549 cells. These findings highlight several adverse effects of PM2.5 on A549 cells, including enhanced invasion and migration capabilities, altered gene expression related to ROS pathways, increased ROS production and disruption of mitochondrial membrane potential. These findings contribute to our understanding of the potential mechanisms through which PM2.5 can impact cellular function and health.

MiR-421 mediates PM2.5-induced endothelial dysfunction via crosstalk between bronchial epithelial and endothelial cells.

OBJECTIVE: PM2.5 is closely linked to vascular endothelial injury and has emerged as a major threat to human health. Our previous research indicated that exposure to PM2.5 induced an increased release of miR-421 from the bronchial epithelium. However, the role of miR-421 in PM2.5-induced endothelial injury remains elusive. MATERIALS AND METHODS: We utilized a subacute PM2.5-exposure model in mice in vivo and an acute injury cell model in vitro to simulate PM2.5-associated endothelial injury. We also used quantitative real-time polymerase chain reaction, western blot, enzyme-linked immunosorbent assay, and immunohistochemistry to investigate the role of miR-421 in PM2.5-induced endothelial injury. RESULTS: Our findings reveal that inhibition of miR-421 attenuated PM2.5-induced endothelial injury and hypertension. Mechanistically, miR-421 inhibited the expression of angiotensin-converting enzyme 2 (ACE2) in human umbilical vein endothelial cells and upregulated the expression of the downstream molecule inducible nitric oxide synthase (iNOS), thereby exacerbating PM2.5-induced endothelial injury. CONCLUSIONS: Our results indicate that PM2.5 exposure facilitates crosstalk between bronchial epithelial and endothelial cells via miR-421/ACE2/iNOS signaling pathway, mediating endothelial damage and hypertension. MiR-421 inhibition may offer a new strategy for the prevention and treatment of PM2.5-induced vascular endothelial injury.

Examining trends and variability of PM2.5-associated organic and elemental carbon in the megacity of Beijing, China: Insight from decadal continuous in-situ hourly observations.

Organic carbon (OC) and elemental carbon (EC) in fine particulate matter (PM2.5) play pivotal roles in impacting human health, air quality, and climate change dynamics. Long-term monitoring datasets of OC and EC in PM2.5 are indispensable for comprehending their temporal variations, spatial distribution, evolutionary patterns, and trends, as well as for assessing the effectiveness of clean air action plans. This study presents and scrutinizes a comprehensive 10-year hourly dataset of PM2.5-bound OC and EC in the megacity of Beijing, China, spanning from 2013 to 2022. Throughout the entire study period, the average concentrations of OC and EC were recorded at 8.8 ±â€¯8.7 and 2.5 ±â€¯3.0 µg/m3, respectively. Employing the seasonal and trend decomposition methodology, specifically the locally estimated scatter plot smoothing method combined with generalized least squares with the autoregressive moving average method, the study observed a significant decline in OC and EC concentrations, reducing by 5.8 % yr-1 and 9.9 % yr-1 at rates of 0.8 and 0.4 µg/m3 yr-1, respectively. These declining trends were consistently verified using Theil-Sen method. Notably, the winter months exhibited the most substantial declining trends, with rates of 9.3 % yr-1 for OC and 10.9 % yr-1 for EC, aligning with the positive impact of the implemented clean air action plan. Weekend spikes in OC and EC levels were attributed to factors such as traffic regulations and residential emissions. Diurnal variations showcased higher concentrations during nighttime and lower levels during daytime. Although meteorological factors demonstrated an overall positive impact with average reduction in OC and EC concentrations by 8.3 % and 8.7 %, clean air action plans including the Air Pollution Prevention and Control Action Plan (2013-2017) and the Three-Year Action Plan to Win the Blue Sky War (2018-2020) have more contributions in reducing the OC and EC concentrations with mass drop rates of 87.1 % and 89.2 % and 76.7 % and 96.7 %, respectively. Utilizing the non-parametric wind regression method, significant concentration hotspots were identified at wind speeds of ≤2 m/s, with diffuse signals recorded in the southwestern wind sectors at wind speeds of approximately 4-5 m/s. Interannual disparities in potential source regions of OC and EC were evident, with high potential source areas observed in the southern and northwestern provinces of Beijing from 2013 to 2018. In contrast, during 2019-2022, potential source areas with relatively high values of potential source contribution function were predominantly situated in the southern regions of Beijing. This analysis, grounded in observational data, provides insights into the decadal changes in the major atmospheric composition of PM2.5 and facilitates the evaluation of the efficacy of control policies, particularly relevant for developing countries.

Changes in PM2.5-related diabetes risk under the implementation of the clean air act in Shanghai.

OBJECTIVES: We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai. METHODS: A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods. RESULTS: In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 µg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders. CONCLUSION: Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.

Association between fine particulate matter and fecundability in Henan, China: A prospective cohort study.

OBJECTIVE: To investigate the relationship between ambient fine particulate matter (PM2.5) exposure and fecundability. METHODS: This study included 751,270 female residents from Henan Province who participated in the National Free Pre-conception Check-up Projects during 2015-2017. Ambient cycle-specific PM2.5 exposure was assessed at the county level for each participant using satellite-based PM2.5 concentration data at 1-km resolution. Cox proportional hazards models with time-varying exposure were used to estimate the association between fecundability and PM2.5 exposure, adjusted for potential individual risk factors. RESULTS: During the study period, 568,713 participants were pregnant, monthly mean PM2.5 concentrations varied from 25.5 to 114.0 µg/m3 across study areas. For each 10 µg/m3 increase in cycle-specific PM2.5, the hazard ratio for fecundability was 0.951 (95 % confidence interval: 0.950-0.953). The association was more pronounced in women who were older, with urban household registration, history of pregnancy, higher body mass index (BMI), hypertension, without exposure to tobacco, or whose male partners were older, with higher BMI, or hypertension. CONCLUSION: In this population-based prospective cohort, ambient cycle-specific PM2.5 exposure was associated with reduced fecundability. These findings may support the adverse implications of severe air pollution on reproductive health.