Research on characteristics and influencing factors of road dust emission in a southern city in China.

One of the primary causes of urban atmospheric particulate matter, which is harmful to human health in addition to affecting air quality and atmospheric visibility, is road dust. This study used online monitoring equipment to examine the characteristics of road dust emissions, the effects of temperature, humidity, and wind speed on road dust, as well as the correlation between road and high-space particulate matter concentrations. A section of a real road in Jinhua City, South China, was chosen for the study. The findings demonstrate that the concentration of road dust particles has a very clear bimodal single-valley distribution throughout the day, peaking between 8:00 and 11:00 and 19:00 and 21:00 and troughing between 14:00 and 16:00. Throughout the year, there is a noticeable seasonal change in the concentration of road dust particles, with the highest concentration in the winter and the lowest in the summer. Simultaneously, it has been discovered that temperature and wind speed have the most effects on particle concentration. The concentration of road dust particles reduces with increasing temperature and wind speed. The particle concentrations of road particles and those from urban environmental monitoring stations have a strong correlation, although the trend in the former is not entirely consistent, and the changes in the former occur approximately 1 h after the changes in the latter.

Fine Particulate Matter and Osteoporosis: Evidence, Mechanisms, and Emerging Perspectives.

Air pollution, particularly fine particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5), has been recognized for its adverse effects on multiple organs beyond the lungs. Among these, the bone began to garner significant attention. This review covers epidemiological, animal and cell studies on PM2.5 exposure and bone health as well as studies on PM2.5-induced diseases with skeletal complications. Emerging evidence from epidemiological studies indicates a positive association between PM2.5 exposure and the incidence of osteoporosis and fractures, along with a negative association with bone mineral density. Experimental studies have demonstrated that PM2.5 can disrupt the metabolic balance between osteoclasts and osteoblasts through inflammatory responses, oxidative stress, and endocrine disruption, thereby triggering bone loss and osteoporosis. Additionally, this review proposes a secondary mechanism by which PM2.5 may impair bone homeostasis via pathological alterations in other organs, offering new perspectives on the complex interactions between environmental pollutants and bone health. In conclusion, this contemporary review underscores the often-overlooked risk factors of PM2.5 in terms of its adverse effects on bone and elucidates the mechanisms of both primary and secondary toxicity. Further attention should be given to exploring the molecular mechanisms of PM2.5-induced bone impairment and developing effective intervention strategies. With global climate change, increasing ozone pollution, emerging pollutants, and multifactorial exposure to environmental factors, these issues are likely to become of greater concern in the near future.

Landscape Fire Air Pollution as a Mediator in Drought and Childhood Stunting Pathway in Low- and Middle-Income Countries.

Drought induces dry hazards, including wildfire, and increased air pollution from wildfire may be a mechanism by which drought increases health risks. We examined whether the drought-wildfire pathway increases the risk of childhood stunting. We analyzed all geocoded children under five across 44 low- and middle-income countries (LMICs). We first conducted mixed-effect regressions to examine the three pairwise associations between standardized precipitation evapotranspiration index (SPEI), fire-sourced PM2.5, and childhood stunting. We then employed a causal mediation analysis to determine whether compounding drought-wildfire (cascading or co-occurring) events significantly impact the drought-stunting pathway. We found that each 1-unit decrease in SPEI exposure was associated with a 2.16% [95% confidence interval (CI): 0.79, 3.49%] increase in stunting risk and 0.57 (95% CI 0.55, 0.59%) µg/m3 increase in fire-sourced PM2.5. Additionally, each 1 µg/m3 increase in 24 month average fire-sourced PM2.5 was associated with an increased risk of 2.46% (95% CI: 2.16, 2.76%) in stunting. Drought-mediated fires accounted for 26.7% (95% CI: 14.5, 36.6%) of the linkage between SPEI and stunting. Our study revealed fire-sourced PM2.5 is a mediator in the drought-stunting pathway in LMICs. To protect child health under increasing drought conditions, personal interventions against wildfire should be considered to enhance climate resilience.

OSGIN1 regulates PM2.5-induced fibrosis via mediating autophagy in an in vitro model of COPD.

Fine particulate matter (PM2.5) has been identified as a significant contributing factor to the exacerbation of chronic obstructive pulmonary disease (COPD). It has been observed that PM2.5 may induce lung fibrosis in COPD, although the precise molecular mechanism behind this remains unclear. In a previous study, we demonstrated that PM2.5 upregulates OSGIN1, which in turn leads to injury in airway epithelial cells, thereby, suggesting a potential link between PM2.5 exposure and COPD. Based on this, we hypothesized that OSGIN1 plays a role in PM2.5-induced fibrosis in COPD. Human bronchial epithelial (HBE) cells were treated with cigarette smoke extract (CSE) to construct an in vitro model of COPD. Our findings revealed that PM2.5 increased fibrosis indicators and upregulated OSGIN1 in CSE-stimulated HBE cells (CSE-HBEs), and that knockdown of OSGINA reduced the expression of fibrosis indicators. Through the use of microRNA target prediction software and the Gene Expression Omnibus database, we predicted miRNAs that targeted OSGIN1 in COPD. Subsequently, real-time polymerase chain reaction and western blot analysis confirmed that PM2.5 modulated miR-654-5p to regulate OSGIN1 in CSE-HBEs. Western blot demonstrated that OSGIN1 induced autophagy, thereby exacerbating fibrosis in CSE-HBEs. In summary, our results suggest that PM2.5 upregulates OSGIN1 through miR-654-5p, leading to increased autophagy and fibrosis in CSE-HBEs.

The Worsening of Myocardial Ischemia-Reperfusion Injury in Uremic Cardiomyopathy is Further Aggravated by PM2.5 Exposure: Mitochondria Serve as the Central Focus of Pathology.

Uremic cardiomyopathy (UC) represents a complex syndrome characterized by different cardiac complications, including systolic and diastolic dysfunction, left ventricular hypertrophy, and diffuse fibrosis, potentially culminating in myocardial infarction (MI). Revascularization procedures are often necessary for MI management and can induce ischemia reperfusion injury (IR). Despite this clinical relevance, the role of fine particulate matter (PM2.5) in UC pathology and the underlying subcellular mechanisms governing this pathology remains poorly understood. Hence, we investigate the impact of PM2.5 exposure on UC susceptibility to IR injury. Using a rat model of adenine-induced chronic kidney disease (CKD), the animals were exposed to PM2.5 at 250 µg/m3 for 3 h daily over 21 days. Subsequently, hearts were isolated and subjected to 30 min of ischemia followed by 60 min of reperfusion to induce IR injury. UC hearts exposed to PM2.5 followed by IR induction (Adenine + PM_IR) exhibited significantly impaired cardiac function and increased cardiac injury (increased infarct size and apoptosis). Analysis at the subcellular level revealed reduced mitochondrial copy number, impaired mitochondrial bioenergetics, decreased expression of PGC1-α (a key regulator of mitochondrial biogenesis), and compromised mitochondrial quality control mechanisms. Additionally, increased mitochondrial oxidative stress and perturbation of the PI3K/AKT/AMPK signaling axis were evident. Our findings therefore collectively indicate that UC myocardium when exposed to PM2.5 is more vulnerable to IR-induced injury, primarily due to severe mitochondrial impairment.

Fine particulate matter potentiates Th17-cell pathogenicity in experimental autoimmune uveitis via ferroptosis.

The effect of fine particulate matter (PM2.5) on the development of uveitis remains unclear. Therefore, this study was designed to investigate the role of PM2.5 in experimental autoimmune uveitis (EAU) and its potential mechanism. Our results showed that PM2.5 could exacerbate the activity of EAU, as evidenced by severer clinical and pathological changes, correlated with elevated Th17 cells frequency and IL-17A expression. Proteomic analysis revealed ferroptosis was the most significant pathway. In vivo, the levels of Fe2+, ROS, lipid ROS, and malondialdehyde, as well as the expression of TFRC, HMOX1, FTH1, and FTL1 in CD4+ T cells were increased, while GSH/GSSG ratio and the expression of ACSL1 and GPX4 were decreased after PM2.5 exposure. In vitro, the expression of TFRC and HMOX1 were increased, while the expression FTH1, FTL1, ACSL1, and GPX4 were decreased after PM2.5 exposure. Ferrostatin-1 effectively alleviated PM2.5-induced intraocular inflammation and suppressed the frequency of Th17 cells. These results suggest that PM2.5 could aggravate intraocular inflammation and immune response in EAU mice through ferroptosis. Ferroptosis could be a potential marker for the prevention and treatment of uveitis.

Geographic Variations in Urban-Rural Particulate Matter (PM2.5) Concentrations in the United States, 2010-2019.

Fine particulate matter 2.5 (PM2.5) is a widely studied pollutant with substantial health impacts, yet little is known about the urban-rural differences across the United States. Trends of PM2.5 in urban and rural census tracts between 2010 and 2019 were assessed alongside sociodemographic characteristics including race/ethnicity, poverty, and age. For 2010, we identified 13,474 rural tracts and 59,065 urban tracts. In 2019, 13,462 were rural and 59,055 urban. Urban tracts had significantly higher PM2.5 concentrations than rural tracts during this period. Levels of PM2.5 were lower in rural tracts compared to urban and fell more rapidly in rural than urban. Rural tract annual means for 2010 and 2019 were 8.51 [2.24] µg/m3 and 6.41 [1.29] µg/m3, respectively. Urban tract annual means for 2010 and 2019 were 9.56 [2.04] µg/m3 and 7.51 [1.40] µg/m3, respectively. Rural and urban majority Black communities had significantly higher PM2.5 pollution levels (10.19 [1.64] µg/m3 and 9.79 [1.10] µg/m3 respectively), in 2010. In 2019, they were: 7.75 [1.1] µg/m3 and 7.09 [0.78] µg/m3, respectively. Majority Hispanic communities had higher PM2.5 levels and were the highest urban concentration among all races/ethnicities (8.01 [1.73] µg/m3), however they were not the highest rural concentration among all races/ethnicities (6.22 [1.60] µg/m3) in 2019. Associations with higher levels of PM2.5 were found with communities in the poorest quartile and with higher proportions of residents age<15 years old. These findings suggest greater protections for those disproportionately exposed to PM2.5 are needed, such as, increasing the availability of low-cost air quality monitors.

Differential impacts of ambient PM2.5 exposure on sperm quality in northern Thailand.

OBJECTIVE: This study aimed to explore the correlation between ambient particulate matter 2.5 (PM2.5) concentration and sperm quality among northern Thai men exposed to the seasonal air pollution from the agricultural burning process. METHODS: The demographic data and semen analysis of Thai men living in Chiang Mai, Thailand, who visited the infertile clinic were collected. The correlation test between the monthly amount of PM2.5 and sperm quality was carried out. RESULTS: From 2017 to 2021, 1,109 Thai men visited the Infertile Clinic. The correlation test between PM2.5 and sperm quality in years with a better climate revealed a weak positive correlation between the mean PM2.5 and percentage of progressive motile sperm and normal morphology (r=0.08, p=0.05 and r=0.1, p=0.02). However, there was a negative correlation between the mean PM2.5 and sperm concentration, progressive motility and normal sperm morphology during the years with a higher amount of ambient PM2.5, and especially PM2.5 exposure 3 months before semen collection (r=-0.12, p=0.01, r=-0.11, p=0.003, r=-0.15, p=0.004). CONCLUSIONS: Exposure to a high amount of PM2.5 air pollution negatively affects sperm quality.

Maternal exposure to ambient particulate matter on the growth of twin fetuses after in vitro fertilization.

BACKGROUND: While ambient air pollution has been associated with fetal growth in singletons, its correlation among twins is not well-established due to limited research in this area. METHODS: The effects of exposure to PM2.5 particulate matter and its main components during pregnancy on birth weight and the incidence of large for gestational age (LGA) were investigated in 6177 twins born after in vitro fertilization at the Center for Reproductive Medicine of Shanghai Ninth People's Hospital (Shanghai, China) between 2007 and 2021. Other birth weight-related outcomes included macrosomia, low birth weight, very low birth weight, and small for gestational age (SGA). The associations of PM2.5 exposure with birth weight outcomes were analyzed using linear mixed-effect models and random-effect logistic regression models. Distributed lag models were incorporated to estimate the time-varying associations. RESULTS: The findings revealed that an interquartile range (IQR) increase (18 µg/m3) in PM2.5 exposure over the entire pregnancy was associated with a significant increase (57.06 g, 95 % confidence interval [CI]: 30.91, 83.22) in the total birth weight of twins. The effect was more pronounced in larger fetuses (34.93 g, 95 % CI: 21.13, 48.72) compared to smaller fetuses (21.77 g, 95 % CI: 6.94, 36.60) within twin pregnancies. Additionally, an IQR increase in PM2.5 exposure over the entire pregnancy was associated with a 34 % increase in the risk of LGA (95 % CI: 11 %, 63 %). Furthermore, specific chemical components of PM2.5, such as sulfate (SO42-), exhibited effect estimates comparable to the PM2.5 total mass. CONCLUSION: Overall, the findings indicate that exposures to PM2.5 and its specific components are associated with fetal overgrowth in twins.

Association between daily circulatory emergency ambulance dispatches and short-term PM2.5 exposure in a heavily polluted area.

Emergency ambulance dispatches (EAD) have been proven to be associated with ambient particulate matter with diameter < 2.5 µm (PM2.5) concentration, but the associations of circulatory EAD remained inconclusive, especially in heavily polluted areas. In this time series conducted in Shenyang City, Northeastern China, we explored the associations between circulatory EAD and ambient PM2.5 and its constituents. Data including 113,508 circulatory EAD records, five types of PM2.5 constituents, and meteorological information spanning from 2014 to 2019 were retrieved. Using generalized additive models (GAMs), we explored the association between circulatory EAD and calculated excess risks induced by a 10 µg/m3 increase (ERR10) in PM2.5 mass and its constituents. ERR by percentage change (ERRpc) to compare among the different constituents were also calculated. Positive associations between circulatory EAD and PM2.5 mass, sulfates, organic matters, and black carbon, were found particularly at lag0 and lag0-5, with the ERR10 of 3.8% (3.2%-4.4%), 6.5% (2.2%-10.8%), 4.2% (1.7%-6.6%), and 30.2% (17.2%-43.4%) at lag0-5, respectively. Similar associations were observed for cardiovascular EAD, while cerebrovascular EAD suggested a positive association with O3 rather than PM2.5 or its constituents. Notably, PM2.5 mass exhibited the largest ERRpc for circulatory and cardiovascular EAD, followed by sulfates and black carbon. Moreover, the risks were enhanced for circulatory and cardiovascular EAD in males compared to females and during warmer seasons compared to colder seasons. Our findings contribute new evidence on PM2.5 exposure and circulatory EAD in relatively polluted areas.

Prenatal exposure to PM2.5 and its composition on child growth trajectories in the first two years: A Prospective Birth Cohort Study.

The findings on the relationship between prenatal exposure to particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) and its constituent and children's growth trajectories are inconsistent. This association's sensitive exposure time window and possible gender differences remain unclear. Our aim was to determine the association between prenatal exposure to PM2.5 and its component and children's growth trajectories by the age of two. From 2015 to 2021, 6407 mother-infant pairs were enrolled in the study. The PM2.5 include sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM), and black carbon (BC), from the ChinaHighAirPollutants (CHAP) datasets. Children were followed at birth, 1, 3, 6, 9, 12, 18, and 24 months. Population-based and individual-based methods were used to simulate child growth trajectories: slow growth, normal growth, and rapid growth. The distributed lags modeling was used to identify sensitive time windows for the effects of prenatal exposure to PM2.5 and its components on child growth. Sex-stratified analyses estimated sex differences. Median concentrations [interquartile ranges (IQRs)] were 57.46(17.3), 10.59(3.8), 14.26(4.4), 8.69(2.8), 13.05(3.4), and 2.53(0.7) µg/m3 for PM2.5, SO42-, NO3-, NH4+, OM, and BC, respectively. Compared with the normal growth trajectory group, exposure to PM2.5 was significantly associated with a higher risk of rapid growth trajectory in boys (ORs with 95% CI for the entire, first trimester, and second trimester of pregnancy, respectively: 1.016[1.006,1.025], 1.007[1.002,1.011], 1.007[1.002,1.011]). Exposure to PM2.5 was significantly associated with a higher risk of slow growth trajectory in girls (ORs with 95% CI for the entire, second trimester, and third trimester of pregnancy, respectively: 1.010 [1.001,1.018], 1.006 [1.001,1.011], 1.007 [1.002,1.012]). Prenatal PM2.5 and its composition exposure was positively associated with BMI peak in boys (ßs with 95% CI for PM2.5, SO42-, NO3-, NH4+, OM, BC: 0.004[0.000,0.007], 0.025[0.006,0.044], 0.012[0.002,0.023], 0.022[0.004,0.039], 0.016[0.001,0.031], 0.082[0.005,0.159]), and not statistically significant in girls. We observed a more pronounced BC effect in our cohort. Prenatal exposure to PM2.5 and its component, especially at 10-22 weeks of gestation, is associated with a higher risk of rapid growth in boys and a risk of slow growth in girls.

Estimating the spatiotemporal distribution of PM2.5 concentrations in Tianjin during the Chinese Spring Festival: Impact of fireworks ban.

SETTING: off fireworks during the Spring Festival (SF) is a traditional practice in China. However, because of its environmental impact, the Chinese government has banned this practice completely. Existing evaluations of the effectiveness of firework prohibition policies (FPPs) lack spatiotemporal perspectives, making it difficult to comprehensively assess their effects on air quality. Consequently, this study used remote sensing technology based on aerosol optical depth and multiple variables, compared nine statistical learning methods, and selected the optimal model, transformer, to estimate daily spatiotemporal continuous PM2.5 concentration datasets for Tianjin from 2016 to 2020. The overall model accuracy reached a root mean square error of 15.30 µg/m³, a mean absolute error of 9.55 µg/m³, a mean absolute percentage error of 21.07%, and an R2 of 0.88. Subsequently, we analysed the variations in PM2.5 concentrations from three time dimensions-the entire year, winter, and SF periods-to exclude the impact of interannual variations on the experimental results. Additionally, we quantitatively estimated firework-specific PM2.5 concentrations based on time-series forecasting. The results showed that during the three years following the implementation of the FPPs, firework-specific PM2.5 concentrations decreased by 52.70%, 49.76%, and 86.90%, respectively, compared to the year before the implementation of the FPPs. Spatially, the central urban area and industrial zones are more affected by FPPs than the suburbs. However, daily variations of PM2.5 concentrations during the SF showed that high concentrations of PM2.5 produced in a short period will return to normal rapidly and will not cause lasting effects. Therefore, the management of fireworks needs to consider both environmental protection and the public's emotional attachment to traditional customs, rather than simply imposing a blanket ban on fireworks. We advocate improving firework policies in four aspects-production, sales, supervision, and control-to promote sustainable development of the ecological environment and human society.

Interleukin-9 promotes EMT-mediated PM2.5-induced pulmonary fibrosis by activating the STAT3 pathway.

This study investigated the impact of PM2.5 on promoting EMT in PM2.5-induced pulmonary fibrosis (PF) development and explored molecular mechanisms of the IL-9/STAT3/Snail/TWIST1 signaling pathway in PF owing to PM2.5. Four groups of male SD rats were formed: control (0 mg/kg.bw), low (1 mg/kg.bw), medium (5 mg/kg.bw), and high-dose (25 mg/kg.bw) PM2.5 groups. Experimental rats were subjected to PM2.5 exposure via intratracheal instillation, given once weekly for 16 weeks. 24 h after the final exposure, blood, BALF, and lung tissues were collected. Pulmonary epithelial cells underwent cultivation and exposure to varying PM2.5 concentrations with/without inhibitors for 24 h, after which total protein was extracted for relevant protein assays. The findings demonstrated that PM2.5 damaged lung tissue to different degrees and led to PF in rats. Rats subjected to PM2.5 exposure exhibited elevated concentrations of IL-9 protein in both serum and BALF, and elevated levels of IL-9 and its receptor, IL-9R, in lung tissues, compared to control counterparts. Furthermore, PM2.5-exposed groups demonstrated significantly augmented protein levels of p-STAT3, Snail, TWIST1, Vimentin, COL-I, and α-SMA, while displaying notably diminished levels of E-Cadherin compared to control group. The same findings were observed in PM2.5-treated cells. In BEAS-2B cells co-treated with Stattic (STAT3 inhibitor) and PM2.5, the opposite results occurred. Similar results were obtained for cells co-treated with IL-9-neutralizing antibody and PM2.5. Our findings suggest PM2.5 mediates PF development by promoting IL-9 expression, leading to STAT3 phosphorylation and upregulation of Snail and TWIST1 expression, triggering EMT occurrence and progression in lung epithelial cells.

Understanding the impacts of street greening patterns and wind directions on the dispersion of fine particles.

Inappropriate planting patterns can increase pollutant concentrations and threaten human health. This study examined three greening patterns (trees, trees + hedges, and hedges) using the ENVI-met model to evaluate the different effects of various planting patterns on PM2.5 dispersion within an idealized 3D street canyon under three typical wind directions. Results showed that street greenbelts alter the PM2.5 concentration field within canyons, and the horizontal and vertical distribution characteristics of PM2.5 under different wind directions were significantly different. The arbor-hedge vegetation structure showed the highest total vegetation deposition amount due to larger canopy volumes while hedges have better deposition amounts per unit volume due to their proximity to emission sources. Additionally, this research selected the averaged relative difference in PM2.5 concentration (ARDC) indicator to assess the influence of different green scenarios on the dispersion of PM2.5 concentrations. Wind direction and planting patterns jointly affect the dispersion of PM2.5 in canyons, and the ARDC varied from -4.39 % to 105.36 %. Unilateral-trees on the windward side or two rows of hedges may be the optimal vegetation layout by trade-off with other services. ARDC was significantly correlated (p < 0.01) with most of the 3D green indicators. These results could provide effective suggestions for optimizing the layout of greenbelts in street canyons to improve air quality.

PM2.5 induces developmental neurotoxicity in cortical organoids.

There is mounting evidence implicating the potential neurotoxic effects of PM2.5 during brain development, as it has been observed to traverse both the placental barrier and the fetal blood-brain barrier. However, the current utilization of 2D cell culture and animal models falls short in providing an accurate representation of human brain development. Consequently, the precise mechanisms underlying PM2.5-induced developmental neurotoxicity in humans remain obscure. To address this research gap, we constructed three-dimensional (3D) cortical organoids that faithfully recapitulate the initial stages of human cerebral cortex development. Our goal is to investigate the mechanisms of PM2.5-induced neurotoxicity using 3D brain organoids that express cortical layer proteins. Our findings demonstrate that exposure to PM2.5 concentrations of 5 µg/mL and 50 µg/mL induces neuronal apoptosis and disrupts normal neural differentiation, thereby suggesting a detrimental impact on neurodevelopment. Furthermore, transcriptomic analysis revealed PM2.5 exposure induced aberrations in mitochondrial complex I functionality, which is reminiscent of Parkinson's syndrome, potentially mediated by misguided axon guidance and compromised synaptic maintenance. This study is a pioneering assessment of the neurotoxicity of PM2.5 pollution on human brain tissues based on 3D cortical organoids, and the results are of great significance in guiding the formulation of the next air pollution prevention and control policies in China to achieve the sustainable improvement of air quality and to formulate pollution abatement strategies that can maximize the benefits to public health.

Comparison of the rate of healthcare encounters for influenza from source-specific PM2.5 before and after tier 3 vehicle standards in New York state.

BACKGROUND: Influenza healthcare encounters in adults associated with specific sources of PM2.5 is an area of active research. OBJECTIVE: Following 2017 legislation requiring reductions in emissions from light-duty vehicles, we hypothesized a reduced rate of influenza healthcare encounters would be associated with concentrations of PM2.5 from traffic sources in the early implementation period of this regulation (2017-2019). METHODS: We used the Statewide Planning and Research Cooperative System (SPARCS) to study adult patients hospitalized (N = 5328) or treated in the emergency department (N = 18,247) for influenza in New York State. Using a modified case-crossover design, we estimated the excess rate (ER) of influenza hospitalizations and emergency department visits associated with interquartile range increases in source-specific PM2.5 concentrations (e.g., spark-ignition emissions [GAS], biomass burning [BB], diesel [DIE]) in lag day(s) 0, 0-3 and 0-6. We then evaluated whether ERs differed after Tier 3 implementation (2017-2019) compared to the period prior to implementation (2014-2016). RESULTS: Each interquartile range increase in DIE in lag days 0-6 was associated with a 21.3% increased rate of influenza hospitalization (95% CI: 6.9, 37.6) in the 2014-2016 period, and a 6.3% decreased rate (95% CI: -12.7, 0.5) in the 2017-2019 period. The GAS/influenza excess rates were larger in the 2017-2019 period than the 2014-2016 period for emergency department visits. We also observed a larger ER associated with increased BB in the 2017-2019 period compared to the 2014-2016 period. IMPACT STATEMENT: We present an accountability study on the impact of the early implementation period of the Tier 3 vehicle emission standards on the association between specific sources of PM2.5 air pollution on influenza healthcare encounters in New York State. We found that the association between gasoline emissions and influenza healthcare encounters did not lessen in magnitude between periods, possibly because the emissions standards were not yet fully implemented. The reduction in the rates of influenza healthcare encounters associated with diesel emissions may be reflective of past policies to reduce the toxicity of diesel emissions. Accountability studies can help policy makers and environmental scientists better understand the timing of pollution changes and associated health effects.

Prediction of PM2.5 concentration based on a CNN-LSTM neural network algorithm.

Fine particulate matter (PM2.5) is a major air pollutant affecting human survival, development and health. By predicting the spatial distribution concentration of PM2.5, pollutant sources can be better traced, allowing measures to protect human health to be implemented. Thus, the purpose of this study is to predict and analyze the PM2.5 concentration of stations based on the integrated deep learning of a convolutional neural network long short-term memory (CNN-LSTM) model. To solve the complexity and nonlinear characteristics of PM2.5 time series data problems, we adopted the CNN-LSTM deep learning model. We collected the PM2.5data of Qingdao in 2020 as well as meteorological factors such as temperature, wind speed and air pressure for pre-processing and characteristic analysis. Then, the CNN-LSTM deep learning model was integrated to capture the temporal and spatial features and trends in the data. The CNN layer was used to extract spatial features, while the LSTM layer was used to learn time dependencies. Through comparative experiments and model evaluation, we found that the CNN-LSTM model can achieve excellent PM2.5 prediction performance. The results show that the coefficient of determination (R2) is 0.91, and the root mean square error (RMSE) is 8.216 µg/m3. The CNN-LSTM model achieves better prediction accuracy and generalizability compared with those of the CNN and LSTM models (R2 values of 0.85 and 0.83, respectively, and RMSE values of 11.356 and 14.367, respectively). Finally, we analyzed and explained the predicted results. We also found that some meteorological factors (such as air temperature, pressure, and wind speed) have significant effects on the PM2.5 concentration at ground stations in Qingdao. In summary, by using deep learning methods, we obtained better prediction performance and revealed the association between PM2.5 concentration and meteorological factors. These findings are of great significance for improving the quality of the atmospheric environment and protecting public health.

PM2.5 constituents associated with mortality and kidney failure in childhood-onset lupus nephritis: A 19-year cohort study.

BACKGROUND: Childhood-onset lupus nephritis (cLN) is a severe form of systemic lupus erythematosus (SLE) with high morbidity and mortality. The impact of long-term exposure to fine particulate matter (PM2.5) on adverse outcomes in cLN remains unclear. METHODS: We combined a 19-years cLN cohort from seven provinces in China with high-resolution PM2.5 dataset from 2001 to 2020, investigating the association between long-term exposure to PM2.5 and its constituents (sulfate, nitrate, organic matter, black carbon, ammonium) with the risk of death and kidney failure, analyzed with multiple variables Cox models. We also evaluated the association between 3-year average PM2.5 exposure before study entry and baseline SLE disease activity index (SLEDAI) scores using linear regression models. RESULTS: Each 10 µg/m3 increase in annual average PM2.5 exposure was associated with an increased risk of death and kidney failure (HR = 1.58, 95 % CI: 1.24-2.02). Black carbon showed the strongest association (HR = 2.14, 95 % CI: 1.47-3.12). Higher 3-year average exposures to PM2.5 and its constituents were significantly associated with higher baseline SLEDAI scores. CONCLUSIONS: These findings highlight the significant role of environmental pollutants in cLN progression and emphasize the need for strategies to mitigate exposure to harmful PM2.5 constituents, particularly in vulnerable pediatric populations.

Spatial and temporal characteristic of PM2.5 and influence factors in the Yellow River Basin.

The Yellow River Basin has been instrumental in advancing ecological preservation and fostering national high-quality development. However, since the advent of China's reform and opening-up policies, the basin has faced severe environmental pollution issues. This study leverages remote sensing data from 1998 to 2019. As per the "Basin Scope and Its Historical Changes" published by the Yellow River Conservancy Commission of the Ministry of Water Resources, the Yellow River Basin is categorized into upstream, midstream, and downstream regions for analysis of their spatial and temporal distribution traits using spatial autocorrelation methods. Additionally, we employed probes to study the effects of 10 factors, including mean surface temperature and air pressure, on PM2.5. The study findings reveal that (1) the annual average concentration of PM2.5 in the Yellow River Basin exhibited a fluctuating trend from 1998 to 2019, initially increasing, then decreasing, followed by another increase before ultimately declining. (2) The air quality in the Yellow River Basin is relatively poor, making it challenging for large-scale areas with low PM2.5 levels to occur. (3) The PM2.5 concentration in the Yellow River Basin exhibits distinct high and low-value concentration areas indicative of air pollution. Low-value areas are predominantly found in the sparsely populated central and southwestern plateau regions of Inner Mongolia, characterized by a better ecological environment. In contrast, high-value areas are prevalent in the inland areas of Northwest China, with poorer natural conditions, as well as densely populated zones with high energy demand and a relatively developed economy. (4) The overall population density in the Yellow River Basin, as well as in the upstream, midstream, and downstream regions, serves as a primary driving factor. (5) The primary drivers in the middle reaches and the entire Yellow River Basin remain consistent, whereas those in the upper and lower reaches have shifted. In the upstream, air pressure emerges as a primary driver of PM2.5, while in the downstream, NDVI and precipitation become the main influencing factors.

Associations between PM2.5, ambient heat exposure and congenital hydronephrosis in southeastern China.

Objectives: This research aims to analyze how exposure to fine particulate matter (PM2.5) and ambient heat during pregnancy increases the risk of congenital hydronephrosis (CH) in newborns. Methods: A case-control study was conducted to investigate the relationship between exposure to PM2.5 and ambient heat during pregnancy and the occurrence of CH in newborns. The study, which was conducted from 2015 to 2020, included 409 infants with CH as the case group and 409 infants without any abnormalities as the control group. Using spatial remote sensing technology, the exposure of each pregnant mother to PM2.5 concentration was meticulously mapped. Additionally, data on the ambient temperature of exposure for each participant were also collected. A logistics regression model was used to calculate the influence of exposure to PM2.5 and ambient heat on the occurrence of CH. Stratified analysis and interaction analysis were used to study the interaction between ambient heat exposure and PM2.5 on the occurrence of CH. Results: At the 6th week of gestation, exposure to PM2.5 may increase the risk of CH. For every 10 µg/m3 increase in PM2.5 exposure, the risk of CH increased by 2% (95%CI = 0.98, 1.05) at a p-value of >0.05, indicating that there was no significant relationship between the results. Exposure to intense heat at 6th and 7th weeks of gestation increased the risk of CH. Specifically, for every 1°C increase in heat exposure, the risk of CH in offspring increased by 21% (95%CI = 1.04, 1.41) during the 6th week and 13% during the 7th week (95%CI = 1.02, 1.24). At 5th and 6th weeks of gestation, the relative excess risk due to interaction (RERI) was greater than 0 at the 50th percentile (22.58°C), 75th percentile (27.25°C), and 90th percentile (29.13°C) of daily maximum temperature (Tmax) distribution, indicating that the risk of CH was higher when exposed to both ambient heat and PM2.5 at the same time compared to exposure to a single risk factor. Conclusion: Exposure to higher levels of PM2.5 and ambient heat during pregnancy increases the risk of CH in infants. There was a positive interaction between exposure to intense heat and high concentration of PM2.5 on the occurrence of CH.