TFEB/LAMP2 contributes to PM0.2-induced autophagy-lysosome dysfunction and alpha-synuclein dysregulation in astrocytes.

Atmospheric particulate matter (PM) exacerbates the risk factor for Alzheimer's and Parkinson's diseases (PD) by promoting the alpha-synuclein (α-syn) pathology in the brain. However, the molecular mechanisms of astrocytes involvement in α-syn pathology underlying the process remain unclear. This study investigated PM with particle size <200 nm (PM0.2) exposure-induced α-syn pathology in ICR mice and primary astrocytes, then assessed the effects of mammalian target of rapamycin inhibitor (PP242) in vitro studies. We observed the α-syn pathology in the brains of exposed mice. Meanwhile, PM0.2-exposed mice also exhibited the activation of glial cell and the inhibition of autophagy. In vitro study, PM0.2 (3, 10 and 30 µg/mL) induced inflammatory response and the disorders of α-syn degradation in primary astrocytes, and lysosomal-associated membrane protein 2 (LAMP2)-mediated autophagy underlies α-syn pathology. The abnormal function of autophagy-lysosome was specifically manifested as the expression of microtubule-associated protein light chain 3 (LC3II), cathepsin B (CTSB) and lysosomal abundance increased first and then decreased, which might both be a compensatory mechanism to toxic α-syn accumulation induced by PM0.2. Moreover, with the transcription factor EB (TFEB) subcellular localization and the increase in LC3II, LAMP2, CTSB, and cathepsin D proteins were identified, leading to the restoration of the degradation of α-syn after the intervention of PP242. Our results identified that PM0.2 exposure could promote the α-syn pathological dysregulation in astrocytes, providing mechanistic insights into how PM0.2 increases the risk of developing PD and highlighting TFEB/LAMP2 as a promising therapeutic target for antagonizing PM0.2 toxicity.

An exploration of meteorological effects on PM2.5 air quality in several provinces and cities in Vietnam.

Linking meteorology and air pollutants is a key challenge. The study investigated meteorological effects on PM2.5 concentration using the advanced convergent cross mapping method, utilizing hourly PM2.5 concentration and six meteorological factors across eight provinces and cities in Vietnam. Results demonstrated that temperature (ρ = 0.30) and radiation (ρ = 0.30) produced the highest effects, followed by humidity (ρ = 0.28) and wind speed (ρ = 0.24), while pressure (ρ = 0.22) and wind direction (ρ = 0.17) produced the weakest effects on PM2.5 concentration. Comparing the ρ values showed that temperature, wind speed, and wind direction had greater impacts on PM2.5 concentration during the dry season whereas radiation had a more influence during the wet season; Southern stations experienced larger meteorological effects. Temperature, humidity, pressure, and wind direction had both positive and negative influences on PM2.5 concentration, while radiation and wind speed mostly had negative influences. During PM2.5 pollution episodes, there was more contribution of meteorological effects on PM2.5 concentration indicated by ρ values. At contaminated levels, humidity (ρ = 0.45) was the most dominant factor affecting PM2.5 concentration, followed by temperature (ρ = 0.41) and radiation (ρ = 0.40). Pollution episodes were pointed out to be more prevalent under higher humidity, higher pressure, lower temperature, lower radiation, and lower wind speed. The ρ calculation also revealed that lower temperature, lower radiation, and higher humidity greatly accelerated each other under pollution episodes, further enhancing PM2.5 concentration. The findings contributed to the literature on meteorology and air pollution interaction.

Alder expansion stimulates nitrogen oxide (NOx) emissions from southern Eurasian permafrost peatlands.

Nitrogen oxides (NOx) play an important role for atmospheric chemistry and radiative forcing. However, NOx emissions from the vast northern circumpolar permafrost regions have not been studied in situ due to limitations of measurement techniques. Our goals were to validate the offline analytical technique, and based on this, to widely quantify in situ NOx emissions from peatlands in the southern Eurasian permafrost region. To this end, we conducted a comparison of online and offline flux measurements in 2018 and 2019 using the synthetic air flushing, steady-state opaque chamber method. With differences in annual average and cumulative fluxes less than 0.1 µg N m-2 h-1 and 0.01 kg N ha-1 year-1, the online and offline fluxes were in good agreement, demonstrating the feasibility of conducting offline measurements in remote regions without power supply. The flux measurements over 2 years showed obvious NOx emissions of 0.05-0.14 and 0.13-0.30 kg N ha-1 year-1 in the hollow and hummock microtopography of permafrost peatlands, respectively. The rapid expansion of alder (Alnus sibirica) in the peatlands induced by permafrost degradation significantly increased soil mineral N contents and NOx emissions depending on the age of alder (0.64-1.74 and 1.44-2.20 kg N ha-1 year-1 from the alder forests with tree ages of 1-10 years and 11-20 years, respectively). Alder expansion also intensively altered the thermal state of permafrost including the sharp increases of soil temperatures during the non-growing season from October to April and active layer thickness. This study provides the first in situ evidences of NOx emissions from the northern circumpolar permafrost regions and uncovers the well-documented expansion of alders can substantially stimulate NOx emissions and thus, significantly affect air quality, radiative forcing, and ecosystem productivity in the pristine regions.

The Joint Effects of Thunderstorms and Power Outages on Respiratory-Related Emergency Visits and Modifying and Mediating Factors of This Relationship.

BACKGROUND: While limited studies have evaluated the health impacts of thunderstorms and power outages (POs) separately, few have assessed their joint effects. We aimed to investigate the individual and joint effects of both thunderstorms and POs on respiratory diseases, to identify disparities by demographics, and to examine the modifications and mediations by meteorological factors and air pollution. METHODS: Distributed lag nonlinear models were used to examine exposures during three periods (i.e., days with both thunderstorms and POs, thunderstorms only, and POs only) in relation to emergency department visits for respiratory diseases (2005-2018) compared to controls (no thunderstorm/no PO) in New York State (NYS) while controlling for confounders. Interactions between thunderstorms and weather factors or air pollutants on health were assessed. The disparities by demographics and seasons and the mediative effects by particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) and relative humidity (RH) were also evaluated. RESULTS: Thunderstorms and POs were independently associated with total and six subtypes of respiratory diseases in NYS [highest risk ratio (RR) = 1.12; 95% confidence interval (CI): 1.08, 1.17], but the impact was stronger when they co-occurred (highest RR = 1.44; 95% CI: 1.22, 1.70), especially during grass weed, ragweed, and tree pollen seasons. The stronger thunderstorm/PO joint effects were observed on chronic obstructive pulmonary diseases, bronchitis, and asthma (lasted 0-10 d) and were higher among residents who lived in rural areas, were uninsured, were of Hispanic ethnicity, were 6-17 or over 65 years old, and during spring and summer. The number of comorbidities was significantly higher by 0.299-0.782/case. Extreme cold/heat, high RH, PM2.5, and ozone concentrations significantly modified the thunderstorm-health effect on both multiplicative and additive scales. Over 35% of the thunderstorm effects were mediated by PM2.5 and RH. CONCLUSION: Thunderstorms accompanied by POs showed the strongest respiratory effects. There were large disparities in thunderstorm-health associations by demographics. Meteorological factors and air pollution levels modified and mediated the thunderstorm-health effects. https://doi.org/10.1289/EHP13237.

Indirect Effects of PM2.5 Exposure on COVID-19 Mortality in Greater Jakarta, Indonesia: An Ecological Study.

Background: Air pollution, including PM2.5, was suggested as one of the primary contributors to COVID-19 fatalities worldwide. Jakarta, the capital city of Indonesia, was recognized as one of the ten most polluted cities globally. Additionally, the incidence of COVID-19 in Jakarta surpasses that of all other provinces in Indonesia. However, no study has investigated the correlation between PM2.5 concentration and COVID-19 fatality in Jakarta. Objective: To investigate the correlation between short-term and long-term exposure to PM2.5 and COVID-19 mortality in Greater Jakarta area. Methods: An ecological time-trend study was implemented. The data of PM2.5 ambient concentration obtained from Nafas Indonesia and the National Institute for Aeronautics and Space (LAPAN)/National Research and Innovation Agency (BRIN). The daily COVID-19 death data obtained from the City's Health Office. Findings: Our study unveiled an intriguing pattern: while short-term exposure to PM2.5 showed a negative correlation with COVID-19 mortality, suggesting it might not be the sole factor in causing fatalities, long-term exposure demonstrated a positive correlation. This suggests that COVID-19 mortality is more strongly influenced by prolonged PM2.5 exposure rather than short-term exposure alone. Specifically, our regression analysis estimate that a 50 µg/m3 increase in long-term average PM2.5 could lead to an 11.9% rise in the COVID-19 mortality rate. Conclusion: Our research, conducted in one of the most polluted areas worldwide, offers compelling evidence regarding the influence of PM2.5 exposure on COVID-19 mortality rates. It emphasizes the importance of recognizing air pollution as a critical risk factor for the severity of viral respiratory infections.

Exploring spatiotemporal distribution characteristics of air quality and driving factors: empirical evidence of 288 cities in China.

Excellent air quality is important for China to achieve high quality economic development. The paper analyses the spatial and temporal distribution characteristics of the air quality index (AQI) in 288 Chinese cities, and further investigates the driving factors affecting air quality using the spatial Durbin model (SDM) based on the panel data of 288 Chinese cities from 2014 to 2021. The results of the study show that: (1) China's air quality level has improved in general, but there are large differences in air quality between regions; (2) China's AQI has significant spatial positive autocorrelation, and the Moran's scatter plot shows a high-high and low-low agglomeration; (3) The driving factors of air quality have different effects, and regional heterogeneity is obvious. Some developed regions in China have already crossed the inflexion point of the environmental Kuznets curve (EKC); promoting industrial upgrading and reducing pollutant emissions can significantly improve urban PM2.5 concentrations; and the "Three-Year Strategy for Conquering the Blue Sky War" policy has lowered the AQI in North China and improved PM2.5 concentrations nationwide. Based on the above findings, the paper puts forward corresponding policy recommendations.

[Pollution attributable mortality]. / Mortalité attribuable à la pollution.

POLLUTION ATTRIBUTABLE MORTALITY. Pollution is estimated to be responsible for 9 million premature deaths per year in the world. For each cause of death with a risk increased by a pollutant, the number of deaths attributable to it is computed by comparison with the number of deaths expected under a reference pollution level, which is 10 µg/m3 for ambient particulate matter pollution. Only 8% of the deaths attributable to pollution occur in high income countries, because of the large effects of water and indoor air pollution (caused by traditional cooking methods) in low and middle-income countries. In France, by this method, one estimates that 13.200 deaths a year are attributable to ambient particulate matter pollution and 1.100 to ozone. Santé publique France, which has concluded that 48.000 deaths a year were attributable to air pollution in France, overvalues the risk by a factor of nearly 4 by overestimating the risks associated with air pollution and taking a utopian reference scenario.

MORTALITÉ ATTRIBUABLE À LA POLLUTION. On estime que la pollution est responsable de 9 millions de décès prématurés par an dans le monde. Pour chaque cause de décès dont le risque est augmenté par la pollution, un nombre de décès attribuable à la pollution est calculé par comparaison avec le nombre attendu pour un niveau de pollution de référence qui est de 10 µg/m3 pour la pollution particulaire de l'air extérieur. Seulement 8 % des décès attribuables à la pollution surviennent dans les pays à revenu élevé (effets importants des pollutions de l'eau et de l'air intérieur par des modes de cuisson traditionnels dans les pays à revenus bas ou moyens). En France, par cette méthode, on estime que 13 200 décès par an sont liés à la pollution particulaire de l'air extérieur et 1 100 à l'ozone. Santé publique France, qui conclut que 48 000 décès par an sont attribuables à la pollution de l'air en France, surévalue donc le risque d'un facteur proche de 4 en surestimant l'effet de la pollution et en prenant une pollution de référence utopique.

Fine particulate matter-sudden death association modified by ventricular hypertrophy and inflammation: a case-crossover study.

Background: Sudden death accounts for approximately 10% of deaths among working-age adults and is associated with poor air quality. Objectives: To identify high-risk groups and potential modifiers and mediators of risk, we explored previously established associations between fine particulate matter (PM2.5) and sudden death stratified by potential risk factors. Methods: Sudden death victims in Wake County, NC, from 1 March 2013 to 28 February 2015 were identified by screening Emergency Medical Systems reports and adjudicated (n = 399). Daily PM2.5 concentrations for Wake County from the Air Quality Data Mart were linked to event and control periods. Potential modifiers included greenspace metrics, clinical conditions, left ventricular hypertrophy (LVH), and neutrophil-to-lymphocyte ratio (NLR). Using a case-crossover design, conditional logistic regression estimated the OR (95%CI) for sudden death for a 5 µg/m3 increase in PM2.5 with a 1-day lag, adjusted for temperature and humidity, across risk factor strata. Results: Individuals having LVH or an NLR above 2.5 had PM2.5 associations of greater magnitude than those without [with LVH OR: 1.90 (1.04, 3.50); NLR > 2.5: 1.25 (0.89, 1.76)]. PM2.5 was generally less impactful for individuals living in areas with higher levels of greenspace. Conclusion: LVH and inflammation may be the final step in the causal pathway whereby poor air quality and traditional risk factors trigger arrhythmia or myocardial ischemia and sudden death. The combination of statistical evidence with clinical knowledge can inform medical providers of underlying risks for their patients generally, while our findings here may help guide interventions to mitigate the incidence of sudden death.

Study on the ability of indoor plants to absorb and purify benzene pollution.

The ability of indoor plants to purify benzene pollution is the basic basis for the selection of plants for ecological remediation of indoor benzene pollution. In this study, the purification rate and the purification amount per unit leaf area of 13 test plants at three benzene concentrations were determined by indoor fumigation experiments, and the benzene absorption and purification abilityability of indoor plants were comprehensively evaluated. The results showed that (1) there was a significant correlation between benzene concentration and purification rate and purification amount per unit leaf area. (2) At the three concentrations, Spathiphyllum floribundum showed the highest purification rate and Sansevieria trifasciata var. laurentii showed the highest purification per unit leaf area. (3) The combined results showed that Sansevieria trifasciata var. laurentii, Spathiphyllum floribundum and Aloe arborescens were the strongest absorbers and purifiers, while Podocarpus nagi and Anthurium andraeanum 'Pink champin' had the weakest absorption and purification capacity. The results of this study provide a theoretical basis and reference for the selection of plants with strong capacities to adsorb and purify benzene pollution in indoor air.

Air pollution and cancer daily mortality in Hangzhou, China: an ecological research.

BACKGROUND: Long-term exposure to air pollution has been linked to cancer incidence. However, the evidence is limited regarding the effect of short-term exposure to air pollution on cancer mortality. OBJECTIVES: This study aimed to investigate associations between short-term exposure to air pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter <10 mm (PM10) and PM2.5) and cancer daily mortality. METHODS: This study used air quality, meteorological and daily cancer death data from 2014 to 2019 in Hangzhou, China. Generalised additive models (GAM) with quasi-Poisson regression were used to analyse the associations between air pollutants and cancer mortality with adjustment for confounding factors including time trends, day of week, temperature and humidity. Then, we conducted stratified analyses by sex, age, season and education. In addition, stratified analyses of age, season and education were performed within each sex to determine whether sex difference was modified by such factors. RESULTS: After adjusting for potential confounders, the GAM results indicated a statistically significant relationship between increased cancer mortality and elevated air pollution concentrations, but only in the female population. For every 10 µg/m3 rise in pollutant concentration, the increased risk of cancer death in females was 6.82% (95% CI 3.63% to 10.10%) for SO2 on lag 03, and 2.02% (95% CI 1.12% to 2.93%) for NO2 on lag 01 and 0.89% (95% CI 0.46% to 1.33%) for PM10 on lag 03 and 1.29% (95% CI 0.64% to 1.95%) for PM2.5 on lag 03. However, no statistically significant association was found among males. Moreover, the differences in effect sizes between males and females were more pronounced during the cold season, among the elderly and among subjects with low levels of education. CONCLUSIONS: Increased cancer mortality was only observed in females with rising concentrations of air pollutants. Further research is required to confirm this sex difference. Advocate for the reduction of air pollutant emissions to protect vulnerable groups.

Association between short-term exposure to ambient air pollutants and the risk of hospital visits for acute upper respiratory tract infections among adults: a time-series study in Ningbo, China.

OBJECTIVES: Acute upper respiratory tract infections (AURTIs) are prevalent in the general population. However, studies on the association of short-term exposure to air pollution with the risk of hospital visits for AURTIs in adults are limited. This study aimed to explore the short-term exposure to air pollutants among Chinese adults living in Ningbo. METHODS: Quasi-Poisson time serious regressions with distributed lag non-linear models (DLNM) were applied to explore the association between ambient air pollution and AURTIs cases. Patients ≥ 18 years who visit three hospitals, being representative for urban, urban-rural junction and rural were included in this retrospective study. RESULTS: In total, 104,441 cases with AURTIs were enrolled in hospital during 2015-2019. The main results showed that particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5), nitrogen dioxide (NO2) and nitrogen dioxide (SO2), were positively associated to hospital visits for AURTIs, except for nitrogen dioxide (O3), which was not statistically significant. The largest single-lag effect for PM2.5 at lag 8 days (RR = 1.02, 95%CI: 1.08-1.40), for NO2 at lag 13 days (RR = 1.03, 95%CI: 1.00-1.06) and for SO2 at lag 5 days (RR = 1.27, 95%CI: 1.08-1.48), respectively. In the stratified analysis, females, and young adults (18-60 years) were more vulnerable to PM2.5 and SO2 and the effect was greater in rural areas and urban-rural junction. CONCLUSIONS: Exposure to ambient air pollution was significantly associated with hospital visits for AURTIs. This study provides epidemiological evidence for policymakers to control better air quality and establish an enhanced system of air pollution alerts.

Long-term exposure to PM2.5 air pollution and mental health: a retrospective cohort study in Ireland.

BACKGROUND: Mental illness is the leading cause of years lived with disability, and the global disease burden of mental ill-health has increased substantially in the last number of decades. There is now increasing evidence that environmental conditions, and in particular poor air quality, may be associated with mental health and wellbeing. METHODS: This cross-sectional analysis uses data on mental health and wellbeing from The Irish Longitudinal Study on Ageing (TILDA), a nationally representative survey of the population aged 50+ in Ireland. Annual average PM2.5 concentrations at respondents' residential addresses over the period 1998-2014 are used to measure long-term exposure to ambient PM2.5. RESULTS: We find evidence of associations between long-term exposure to ambient PM2.5 and depression and anxiety. The measured associations are strong, and are comparable with effect sizes for variables such as sex. Effects are also evident at relatively low concentrations by international standards. However, we find no evidence of associations between long-term ambient particulate pollution and other indicators of mental health and well-being such as stress, worry and quality of life. CONCLUSIONS: The measured associations are strong, particularly considering the relatively low PM2.5 concentrations prevailing in Ireland compared to many other countries. While it is estimated that over 90 per cent of the world's population lives in areas with annual mean PM2.5 concentrations greater than 10 µg/m3, these results contribute to the increasing evidence that suggests that harmful effects can be detected at even low levels of air pollution.

Air pollution and survival in patients with malignant mesothelioma and asbestos-related lung cancer: a follow-up study of 1591 patients in South Korea.

BACKGROUND: Despite significant advancements in treatments such as surgery, radiotherapy, and chemotherapy, the survival rate for patients with asbestos-related cancers remains low. Numerous studies have provided evidence suggesting that air pollution induces oxidative stress and inflammation, affecting acute respiratory diseases, lung cancer, and overall mortality. However, because of the high case fatality rate, there is limited knowledge regarding the effects of air pollution exposures on survival following a diagnosis of asbestos-related cancers. This study aimed to determine the effect of air pollution on the survival of patients with malignant mesothelioma and asbestos-related lung cancer. METHODS: We followed up with 593 patients with malignant mesothelioma and 998 patients with lung cancer identified as asbestos victims between 2009 and 2022. Data on five air pollutants-sulfur dioxide, carbon monoxide, nitrogen dioxide, fine particulate matter with a diameter < 10 µm, and fine particulate matter with a diameter < 2.5 µm-were obtained from nationwide atmospheric monitoring stations. Cox proportional hazard models were used to estimate the association of cumulative air pollutant exposure with patient mortality, while adjusting for potential confounders. Quantile-based g-computation was used to assess the combined effect of the air pollutant mixture on mortality. RESULTS: The 1-, 3-, and 5-year survival rates for both cancer types decreased with increasing exposure to all air pollutants. The estimated hazard ratios rose significantly with a 1-standard deviation increase in each pollutant exposure level. A quartile increase in the pollutant mixture was associated with a 1.99-fold increase in the risk of malignant mesothelioma-related mortality (95% confidence interval: 1.62, 2.44). For lung cancer, a quartile increase in the pollutant mixture triggered a 1.87-fold increase in the mortality risk (95% confidence interval: 1.53, 2.30). CONCLUSION: These findings support the hypothesis that air pollution exposure after an asbestos-related cancer diagnosis can negatively affect patient survival.

Investigation of the relationship between air pollution and gestational diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes. METHODS: The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 µm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant. RESULTS: None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05). CONCLUSIONS: This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.

The health of pregnant women and their children can be impacted by gestational diabetes mellitus (GDM), one of the prevalent pregnancy complications. Some of studies showed that the incidence of gestational diabetes can be influenced by genetic or environmental factors. Air pollution is an environmental stimulus that may predispose pregnant women to GDM. This research explored whether air pollution could increase the risk of developing gestational diabetes. Over 6000 pregnant women in five cities of Iran participated in the study and were screened for gestational diabetes. Their exposure to the various air pollutants during the three months preceding pregnancy and total pregnancy period was measured. In this study, we found no clear association between air pollution and gestational diabetes. However, this finding needs to be interpreted cautiously since all the influential factors were not assessed.

Associations between specific volatile organic chemical exposures and cardiovascular disease risks: insights from NHANES.

Introduction: An increasing body of research has demonstrated a correlation between pollutants from the environment and the development of cardiovascular diseases (CVD). However, the impact of volatile organic chemicals (VOC) on CVD remains unknown and needs further investigation. Objectives: This study assessed whether exposure to VOC was associated with CVD in the general population. Methods: A cross-sectional analysis was conducted utilizing data from five survey cycles (2005-2006, 2011-2012, 2013-2014, 2015-2016, and 2017-2018) of the National Health and Nutrition Examination Survey (NHANES) program. We analyzed the association between urinary VOC metabolites (VOCs) and participants by multiple logistic regression models, further Bayesian Kernel Machine Regression (BKMR) models and Weighted Quantile Sum (WQS) regression were performed for mixture exposure analysis. Results: Total VOCs were found to be positively linked with CVD in multivariable-adjusted models (p for trend = 0.025), independent of established CVD risk variables, such as hypertension, diabetes, drinking and smoking, and total cholesterol levels. Compared with the reference quartile of total VOCs levels, the multivariable-adjusted odds ratios in increasing quartiles were 1.01 [95% confidence interval (CI): 0.78-1.31], 1.26 (95% CI: 1.05-1.21) and 1.75 (95% CI: 1.36-1.64) for total CVD. Similar positive associations were found when considering individual VOCs, including AAMA, CEMA, CYMA, 2HPMA, 3HPMA, IPM3 and MHBMA3 (acrolein, acrylamide, acrylonitrile, propylene oxide, isoprene, and 1,3-butadiene). In BKMR analysis, the overall effect of a mixture is significantly related to VOCs when all chemicals reach or exceed the 75th percentile. Moreover, in the WQS models, the most influential VOCs were found to be CEMA (40.30%), DHBMA (21.00%), and AMCC (19.70%). Conclusion: The results of our study indicated that VOC was all found to have a significant association with CVD when comparing results from different models. These findings hold significant potential for public health implications and offer valuable insights for future research directions.

Scaling features in high-concentrations PM2.5 evolution: the Ignored factor affecting scarlet fever incidence.

As an acute respiratory disease, scarlet fever has great harm to public health. Some evidence indicates that the time distribution pattern of heavy PM2.5 pollution occurrence may have an impact on health risks. This study aims to reveal the relation between scaling features in high-concentrations PM2.5 (HC-PM2.5) evolution and scarlet fever incidence (SFI). Based on the data of Hong Kong from 2012 to 2019, fractal box-counting dimension (D) is introduced to capture the scaling features of HC-PM2.5. It has been found that index D can quantify the time distribution of HC-PM2.5, and lower D values indicate more cluster distribution of HC-PM2.5. Moreover, scale-invariance in HC-PM2.5 at different time scales has been discovered, which indicates that HC-PM2.5 occurrence is not random but follows a typical power-law distribution. Next, the exposure-response relationship between SFI and scale-invariance in HC-PM2.5 is explored by Distributed lag non-linear model, in conjunction with meteorological factors. It has been discovered that scale-invariance in HC-PM2.5 has a nonlinear effect on SFI. Low and moderate D values of HC-PM2.5 are identified as risk factors for SFI at small time-scale. Moreover, relative risk shows a decreasing trend with the increase of exposure time. These results suggest that exposure to short-term clustered HC-PM2.5 makes individual more prone to SFI than exposure to long-term uniform HC-PM2.5. This means that individuals in slightly-polluted regions may face a greater risk of SFI, once the PM2.5 concentration keeps rising. In the future, it is expected that the relative risk of scarlet fever for a specific region can be estimated based on the quantitative analysis of scaling features in high-concentrations PM2.5 evolution.

Association between residential air pollution exposure and cardiovascular risk factors in adults living in northern France.

Air pollution is associated with elevated cardiovascular mortality and an increase in cardiovascular risk factors. However, the literature data on associations between air pollution and cardiovascular risk factors are contradictory. To explore the relationship between residential exposure to atmospheric pollutants and cardiovascular risk factors (lipid biomarker and blood pressure levels). We studied a sample of 2339 adult participants in the ELISABET study from the Dunkirk and Lille urban areas of France. The mean annual exposure to atmospheric pollutants (PM10, NO2 and SO2) at the home address was estimated via an air dispersion model. The associations were probed in multivariate linear regression models. The mean NO2 level was 26.05 µg/m3 in Lille and 19.96 µg/m3 in Dunkirk. The mean PM10 level was 27.02 µg/m3 in Lille and 26.53 µg/m3 in Dunkirk. We detected a significant association between exposure to air pollutants and the high-density lipoprotein (HDL) (which is a protective factor against cardiovascular diseases) level: for a 2 µg/m3 increment in PM10, the HDL level decreased by 1.72% (p = 0.0037). None of the associations with other lipid variables or with blood pressure were significant. We didn't find evidence significant associations for most of the risk factors but, long-term exposure of adults to moderate levels of ambient air pollution was associated with a decrement in HDL.

Association between PM2.5 from a coal mine fire and FeNO concentration 7.5 years later.

BACKGROUND AND AIM: There are few long-term studies of respiratory health effects of landscape fires, despite increasing frequency and intensity due to climate change. We investigated the association between exposure to coal mine fire PM2.5 and fractional exhaled nitric oxide (FeNO) concentration 7.5 years later. METHODS: Adult residents of Morwell, who were exposed to the 2014 Hazelwood mine fire over 6 weeks, and unexposed residents of Sale, participated in the Hazelwood Health Study Respiratory Stream in 2021, including measurements of FeNO concentration, a marker of eosinophilic airway inflammation. Individual exposure to coal mine fire PM2.5 was modelled and mapped to time-location diaries. The effect of exposure to PM2.5 on log-transformed FeNO in exhaled breath was investigated using multivariate linear regression models in the entire sample and stratified by potentially vulnerable subgroups. RESULTS: A total of 326 adults (mean age: 57 years) had FeNO measured. The median FeNO level (interquartile range [IQR]) was 17.5 [15.0] ppb, and individual daily exposure to coal mine fire PM2.5 was 7.2 [13.8] µg/m3. We did not identify evidence of association between coal mine fire PM2.5 exposure and FeNO in the general adult sample, nor in various potentially vulnerable subgroups. The point estimates were consistently close to zero in the total sample and subgroups. CONCLUSION: Despite previous short-term impacts on FeNO and respiratory health outcomes in the medium term, we found no evidence that PM2.5 from the Hazelwood coal mine fire was associated with any long-term impact on eosinophilic airway inflammation measured by FeNO levels.

Mortality attributable to PM2.5 from wildland fires in California from 2008 to 2018.

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Exploring the spatial effects and influencing mechanism of ozone concentration in the Yangtze River Delta urban agglomerations of China.

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.