BACKGROUND: There are a few reports on the associations between fine particulate matter (PM2.5)-bound heavy metals and lung function.
OBJECTIVE: To evaluate the associations of single and mixed PM2.5-bound heavy metals with lung function.
METHODS: This study included 316 observations of 224 Chinese adults from the Wuhan-Zhuhai cohort over two study periods, and measured participants\' personal PM2.5-bound heavy metals and lung function. Three linear mixed models, including the single constituent model, the PM2.5-adjusted constituent model, and the constituent residual model were used to evaluate the association between single metal and lung function. Mixed exposure models including Bayesian kernel machine regression (BKMR) model, weighted quantile sum (WQS) model, and Explainable Machine Learning model were used to assess the relationship between PM2.5-bound heavy metal mixtures and lung function.
RESULTS: In the single exposure analyses, significant negative associations of PM2.5-bound lead, antimony, and cadmium with peak expiratory flow (PEF) were observed. In the mixed exposure analyses, significant decreases in forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC), maximal mid-expiratory flow (MMF), and forced expiratory flow at 75% of the pulmonary volume (FEF75) were associated with the increased PM2.5-bound heavy metal mixture. The BKMR models suggested negative associations of PM2.5-bound lead and antimony with lung function. In addition, PM2.5-bound copper was positively associated with FEV1/FVC, MMF, and FEF75. The Explainable Machine Learning models suggested that FEV1/FVC, MMF, and FEF75 decreased with the elevated PM2.5-bound lead, manganese, and vanadium, and increased with the elevated PM2.5-bound copper.
CONCLUSIONS: The negative relationships were detected between PM2.5-bound heavy metal mixture and FEV1/FVC, MMF, as well as FEF75. Among the PM2.5-bound heavy metal mixture, PM2.5-bound lead, antimony, manganese, and vanadium were negatively associated with FEV1/FVC, MMF, and FEF75, while PM2.5-bound copper was positively associated with FEV1/FVC, MMF, and FEF75.

BACKGROUND: Short-term exposure to particulate matter air pollution has been associated with the exacerbations of COPD, but its association with COPD mortality was not fully elucidated. We aimed to assess the association between short-term particulate matter exposure and the risk of COPD mortality in China using individual-level data.
METHODS: We derived 2.26 million COPD deaths from a national death registry database in Chinese mainland between 2013 and 2019. Exposures to fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) were assessed by satellite-based models of a 1 × 1 km resolution and assigned to each individual based on residential address. The associations of PM2.5 and PM2.5-10 with COPD mortality were examined using a time-stratified case-crossover design and conditional logistic regressions with distributed lag models. We further conducted stratified analyses by age, sex, education level, and season.
RESULTS: Short-term exposures to both PM2.5 and PM2.5-10 were associated with increased risks of COPD mortality. These associations appeared and peaked on the concurrent day, attenuated and became nonsignificant after 5 or 7 days, respectively. The exposure-response curves were approximately linear without discernible thresholds. An interquartile range increase in PM2.5 and PM2.5-10 concentrations was associated with 4.23% (95% CI: 3.75%, 4.72%) and 2.67% (95% CI: 2.18%, 3.16%) higher risks of COPD mortality over lag 0-7 d, respectively. The associations of PM2.5 and PM2.5-10 attenuated slightly but were still significant in the mutual-adjustment models. A larger association of PM2.5-10 was observed in the warm season.
CONCLUSIONS: This individual-level, nationwide, case-crossover study suggests that short-term exposure to PM2.5 and PM2.5-10 might act as one of the environmental risk factors for COPD mortality.
BACKGROUND: This study is supported by the National Key Research and Development Program of China (2023YFC3708304 and 2022YFC3702701), the National Natural Science Foundation of China (82304090 and 82030103), the 3-year Action Plan for Strengthening the Construction of the Public Health System in Shanghai (GWVI-11.2-YQ31), and the Science and Technology Commission of Shanghai Municipality (21TQ015).

In the pursuit of carbon neutrality, China\'s 2060 targets have been largely anchored in reducing greenhouse gas emissions, with less emphasis on the consequential benefits for air quality and public health. This study pivots to this critical nexus, exploring how China\'s carbon neutrality aligns with the World Health Organization\'s air quality guidelines (WHO AQG) regarding fine particulate matter (PM2.5) exposure. Coupling a technology-rich integrated assessment model, an emission-concentration response surface model, and exposure and health assessment, we find that decarbonization reduces sulfur dioxide (SO2), nitrogen oxides (NOx), and PM2.5 emissions by more than 90%; reduces nonmethane volatile organic compounds (NMVOCs) by more than 50%; and simultaneously reduces the disparities across regions. Critically, our analysis reveals that further targeted reductions in air pollutants, notably NH3 and non-energy-related NMVOCs, could bring most Chinese cities into attainment of WHO AQG for PM2.5 5 to 10 years earlier than the pathway focused solely on carbon neutrality. Thus, the integration of air pollution control measures into carbon neutrality strategies will present a significant opportunity for China to attain health and environmental equality.

BACKGROUND: Enhanced cardiovascular health (CVH) is linked to reduced mortality risks, whereas long-term exposure to fine particulate matter (PM2.5), elevates these risks. Whether long-term exposure to PM2.5 counteracts the health benefits of high CVH is unknown. The study aims to evaluate whether the association of CVH assessed by Life\'s Essential 8 (LE8) with death was consistent between participants with different PM2.5 exposures.
METHODS: We included 134,727 participants in the field survey of China Chronic Disease and Risk Factor Surveillance which was conducted from August 2013 to June 2014. The deaths of participants were obtained by linking to the National Mortality Surveillance System (2013-2018). The environmental data is obtained by satellite inversion. The participants\' CVH scores were calculated using the LE8 method. Hazard ratio (HR) and 95% confidence intervals (95%CI) for mortality were calculated using Cox regression models.
RESULTS: A total of 2,936 all-cause deaths and 1,158 cardiovascular disease (CVD) deaths were recorded. Compared to those with low CVH, adults with high CVH demonstrated a reduced risk of all-cause mortality, irrespective of their PM2.5 exposure levels (P < 0.05, all P for interaction >0.05). Furthermore, in comparison to those with low CVH and highest PM2.5 exposure, adults with high CVH and lowest PM2.5 exposure exhibited HR of 0.18 (95%CI, 0.12-0.25) for all-cause mortality and 0.13 (95%CI, 0.08-0.22) for CVD mortality.
CONCLUSIONS: High CVH is associated with reduced all-cause mortality risk, regardless of PM2.5 exposure levels. For Chinese adults, sustaining high CVH is advisable, irrespective of their residential location.

Fine particulate matter (PM2.5) can damage airway epithelial barriers. The anion transport system plays a crucial role in airway epithelial barriers. However, the detrimental effect and mechanism of PM2.5 on the anion transport system are still unclear. In this study, airway epithelial cells and ovalbumin (OVA)-induced asthmatic mice were used. In transwell model, the adenosine triphosphate (ATP)-induced transepithelial anion short-circuit current (Isc) and airway surface liquid (ASL) significantly decreased after PM2.5 exposure. In addition, PM2.5 exposure decreased the expression levels of P2Y2R, CFTR and cytoplasmic free-calcium, but ATP can increase the expressions of these proteins. PM2.5 exposure increased the levels of Th2-related cytokines of bronchoalveolar lavage fluid, lung inflammation, collagen deposition and hyperplasisa of goblet cells. Interestingly, the administration of ATP showed an inhibitory effect on lung inflammation induced by PM2.5. Together, our study reveals that PM2.5 impairs the ATP-induced transepithelial anion Isc through downregulating P2Y2R/CFTR pathway, and this process may participate in aggravating airway hyperresponsiveness and airway inflammation. These findings may provide important insights on PM2.5-mediated airway epithelial injury.

The Tibetan Plateau, known as the \"Third Pole\", is susceptible to ground-level ozone (O3) and fine particulate matter (PM2.5) pollution due to its unique high-altitude environment. This study constructed random forest regression models using multi-source data from ground measurements and meteorological satellites to predict variations in ground-level O3 and PM2.5 concentrations and their influencing factors across seven major cities in the Tibetan Plateau over two-year periods. The models successfully reproduced O3 and PM2.5 levels with satisfactory R-squared values of 0.71 and 0.73, respectively. Results reveal combustion-related carbon monoxide (CO) and nitrogen dioxide (NO2) as the most substantial influences on O3 and PM2.5 concentrations. Solar radiation, geographical factors, and meteorological variables also played crucial roles in driving pollutant variations. Conversely, transport-related and human activity factors exhibited relatively lower significance. High O3 and PM2.5 pollution occurred during pre-monsoon and post-monsoon/winter seasons, driven by solar radiation and emissions, respectively. While CO consistently contributed across cities and seasons, key influencing factors varied locally. This study unveils the key driving forces governing air pollutant variations across the Tibetan Plateau, shedding light on complex atmospheric processes in this unique high-altitude region.

BACKGROUND: Previous studies have primarily focused on the links between fine particulate matter (PM2.5) and bone health among the general population instead of PM2.5 components and the specific population. We aimed to investigate the associations between PM2.5 components and bone health among middle-aged and elderly women.
METHODS: A total of 748 middle-aged and elderly women were randomly sampled from 32 streets/villages in Hubei Province. The concentrations of ambient PM2.5 and its components were extracted across various residential areas from the Tracking Air Pollution in China (TAP) dataset. Bone mineral density measurements were obtained from dual-energy X-ray absorptiometry scans of study participants. Multivariable logistic and linear models were employed to assess the relationship between PM2.5 and its components and bone loss.
RESULTS: Per interquartile range (IQR) increase in nitrate (NO3-) and ammonium (NH4+) concentrations were associated with 1.65 [95% confidence intervals (CI): 1.13, 2.30] and 1.77 (95% CI: 1.26, 2.49) times higher odds of osteoporosis, respectively. Long-term exposure to sulfate (SO42-), NO3-, and NH4+ was negatively associated with T-scores and bone mineral density in L1-L4 lumbar vertebrae. In addition, the elderly, women who have experienced menarche after the age of 14, and postmenopausal women were more susceptible to the water-soluble inorganic salts of PM2.5.
CONCLUSIONS: The study emphasizes the need for comprehensive policies addressing air quality, with a specific focus on vulnerable populations such as middle-aged and elderly women. Public health interventions aimed at reducing ambient PM2.5 concentrations and minimizing exposure to its harmful components are crucial in mitigating the adverse impact on skeletal health and improving the overall well-being of communities.

Prenatal exposure to fine particulate matter (PM2.5) has been linked with increased neurodevelopmental disorders. However, the most detrimental component of PM2.5 and the most vulnerable exposure time windows remain undetermined, especially in areas with high PM2.5 levels. In a prospective cohort study involving 4494 mother-child dyads, we examined the associations of prenatal exposure to PM2.5 and its four main components with children\'s neurodevelopmental and behavioral problems (NBPs), separately in three pregnancy trimesters. Poisson regression and generalized additive models were used to depict the linear and nonlinear associations, respectively. Weighted quantile sum and Bayesian kernel machine regression models were applied to examine the effects of exposure to both mixed and individual components. Results showed that exposure to PM2.5 and its components throughout the three trimesters increased the risk of children\'s NBPs (Risk ratio for PM2.5: 1.16, 95 % confidence interval 1.14-1.18 per μg/m3 in the first trimester; 1.15, 1.12-1.17 in the second trimester; 1.06, 1.04-1.08 in the third trimester), with associations gradually diminishing as pregnancy progressed (P values for trends < 0.05). Among the four main components of PM2.5, exposure to SO42- posed the highest risks on children\'s NBPs, while organic matter contributed the largest proportion to the overall impacts of PM2.5 exposure. These results underscore the significance of mitigating PM2.5 exposure in pregnant women to reduce the risk of neurodevelopmental disorders in offspring. Our findings would inform risk assessment of PM2.5 exposure and facilitate the development of precision preventive strategies targeting specific components of PM2.5 in similar areas with high levels of exposure.

UNASSIGNED: Despite the adverse effects of ambient fine particulate matter (PM2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM2.5 on the relationship between PA and type 2 diabetes remains unclear.
UNASSIGNED: In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long-term PM2.5 exposure was calculated using 1-km resolution satellite-based PM2.5 estimates. PM2.5 exposure and PA\'s effect on type 2 diabetes were assessed by cohort-stratified Cox proportional hazards models, individually and in combination.
UNASSIGNED: In 488,166 person-years of follow-up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM2.5 stratification (≤65.02 µg/m3) other than in high PM2.5 stratification (>65.02 µg/m3), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66-0.85) and 1.10 (95% CI: 0.99-1.22), respectively. Similar results were observed for PA intensity. High PM2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR = 1.79, 95% CI: 1.59-2.01 for PA volume; HR = 1.82, 95% CI: 1.64-2.02 for PA intensity).
UNASSIGNED: PA could reduce type 2 diabetes risk in low-pollution areas, but high PM2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long-term polluted residents.