Average Particulate Matter Concentrations Research Articles

Multiple dietary patterns and the association between long-term air pollution exposure with type 2 diabetes risk: Findings from UK Biobank cohort study

BackgroundEvidence of modifying effect of various dietary patterns (DPs) on risk of type 2 diabetes (T2D) induced by long-term exposure to air pollution (AP) is still rather lacking, which therefore we aimed to explore in this study. MethodsWe included 78,230 UK Biobank participants aged 40–70 years with at least 2 typical 24-hour dietary assessments and without baseline diabetes. The annual average concentration of particulate matter with diameter micrometers ≤2.5 (PM2.5) and ≤10 (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOX) estimated by land use regression model was the alternative proxy of long-term AP exposure. Three well-known prior DPs such as Mediterranean diet (MED), dietary approaches to stop hypertension diet (DASH), and empirical dietary inflammatory pattern (EDIP), as well as three posterior DPs derived by the rank reduced regression model were used to capture participants’ dietary habits. Cox regression models were used to estimate AP-T2D and DP-T2D associations. Modifying effect of DPs on AP-T2D association was assessed using stratified analysis and heterogeneity test. ResultsDuring a median follow-up 12.19 years, 1,693 participants developed T2D. PM2.5, PM10, NO2, and NOX significantly increased the T2D risk (P <0.05), with hazard ratio (HR) and 95% confidence interval (95% CI) for per interquartile range increase being 1.09 (1.02,1.15), 1.04 (1.00, 1.09), 1.11 (1.04, 1.18), and 1.08 (1.03, 1.14), respectively. Comparing high with low adherence, healthy DPs were associated with a 14–41% lower T2D risk. Participants with high adherence to MED, DASH, and anti-EDIP, alongside the posterior anti-oxidative dietary pattern (AODP) had attenuated and statistically non-significant NO2-T2D and NOX-T2D associations (Pmodify <0.05). ConclusionsMultiple forms of healthy DPs help reduce the T2D risk associated with long-term exposure to NO2 and NOX. Our findings indicate that adherence to healthy DPs is a feasible T2D prevention strategy for people long-term suffering from NO2 and NOX pollution.

Pregnancy exposure to PM2.5 from wildland fire smoke and preterm birth in California

BackgroundWildfires in the Western United States are a growing and significant source of air pollution that is eroding decades of progress in air pollution reduction. The effects on preterm birth during critical periods of pregnancy are unknown. MethodsWe assessed associations between prenatal exposure to wildland fire smoke and risk of preterm birth (gestational age < 37 weeks). We assigned smoke exposure to geocoded residence at birth for all live singleton births in California conceived 2007–2018, using weekly average concentrations of particulate matter ≤ 2.5 µm (PM2.5) attributable to wildland fires from United States Environmental Protection Agency’s Community Multiscale Air Quality Model. Logistic regression yielded odds ratio (OR) for preterm birth in relation to increases in average exposure across the whole pregnancy, each trimester, and each week of pregnancy. Models adjusted for season, age, education, race/ethnicity, medical insurance, and smoking of the birthing parent. ResultsFor the 5,155,026 births, higher wildland fire PM2.5 exposure averaged across pregnancy, or any trimester, was associated with higher odds of preterm birth. The OR for an increase of 1 µg/m3 of average wildland fire PM2.5 during pregnancy was 1.013 (95 % CI:1.008,1.017). Wildland fire PM2.5 during most weeks of pregnancy was associated with higher odds. Strongest estimates were observed in weeks in the second and third trimesters. A 10 µg/m3 increase in average wildland fire PM2·5 in gestational week 23 was associated with OR = 1.034; 95 % CI: 1.019, 1.049 for preterm birth. ConclusionsPreterm birth is sensitive to wildland fire PM2.5; therefore, we must reduce exposure during pregnancy.

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

BackgroundParticulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. ObjectiveThis cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. MethodsPregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. ResultsAfter adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. ConclusionsThis study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Study on the Vertical Distribution and Transport of Aerosols in the Joint Observation of Satellite and Ground-Based LiDAR

The mechanism of aerosol pollution transport remains highly elusive owing to the myriad of influential factors. In this study, ground station data, satellite data, ground-based LiDAR remote sensing data, sounding data, ERA5 reanalysis and a backward trajectory model were combined to investigate the formation process and optical properties of winter aerosol pollution in Beijing and surrounding areas. The analysis of ground station data shows that compared to 2019 and 2021, the pandemic lockdown policy resulted in a decrease in the total number of pollution days and a decrease in the average concentration of particulate matter in the Beijing area in 2020. The terrain characteristics of the Beijing-Tianjin-Hebei (BTH) made it prone to northeast and southwest winds. The highest incidence of aerosol pollution in Beijing occurs in February and March during the spring and winter seasons. Analysis of a typical heavy aerosol pollution process in the Beijing area from 28 February to 5 March 2019 shows that dust and fine particulate matter contributed to the primary pollution; surface air temperature inversion and an average wind speed of less than 3 m/s were conducive to the continuous accumulation of pollutants, which was accompanied by the oxidation reaction of NO2 and O3, forming photochemical pollution. The heavy aerosol pollution was transmitted and diffused towards the southeast, gradually eliminating the pollution. Our results provide relevant research support for the prevention and control of aerosol pollution.

Exposure to ambient air pollution and metabolic dysfunction-associated fatty liver disease: Findings from over 2.7 million adults in Northwestern China

Ambient air pollutants exposures may lead to aggravated Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD). However, there is still a scarcity of empirical studies that have rigorously estimated this association, especially in regions where air pollution is severe. To fill in the literature gap, we conducted a cross-sectional study involving 2711,207 adults living in five regions of southern Xinjiang Uyghur Autonomous Region in 2021. Using a Space-Time Extra-Trees model, we assessed the four-year (2017–2020) average concentrations of particulate matter with aerodynamic diameter ≤1 µm (PM1), particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5), particulate matter with aerodynamic diameter ≤10 µm (PM10), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO), and then assigned these values to the participants. Generalized linear mixed models were employed to examine the relationships between air pollutants and the prevalence of MAFLD, with adjustment for multiple confounding factors. The odds ratios and 95% confidence intervals of MAFLD were 2.002 (1.826–2.195), 1.133 (1.108–1.157), 1.034 (1.027–1.040), 1.077 (1.023–1.134), 2.703 (2.322–3.146) and 1.033 (1.029–1.036) per 10 µg/m3 increase in the 4-year average PM1, PM2.5, PM10, O3, SO2 and CO exposures, respectively. The robustness of the findings was confirmed by a series of sensitivities. In summary, long-term exposure to ambient air pollutants was associated with increased odds of MAFLD, particularly in males and individuals with unhealthy lifestyles.

The short-term effect of ambient particulate matter on suicide death

BackgroundAir pollution can cause various respiratory and neurological diseases and continuous exposure can lead to death. Previous studies have reported that particulate matter (PM) exposure increases the risk of depression, suicidal thoughts, and suicidal death; however, the results are inconsistent and limited. This study aimed to examine the relationship between short-term PM exposure and suicide deaths, as well as investigate the short-term effects of PM on suicide death within vulnerable groups based on factors such as sex, age group, suicide-related information (note, method, and cause), psychiatric disorders, and physical diseases.MethodsData on a total of 28,670 suicide deaths from 2013 to 2017, provided by the Korea Foundation for Suicide Prevention, were analyzed. The study design employed a time-series analysis with a two-stage approach. In the first step, a generalized additive model combined with a distributed lag nonlinear model was used to estimate the short-term effect of PM exposure on suicide risk specific to each city. In the second step, the estimated results from each city were pooled through a meta-analysis to derive the overall effect. We determined the effects of single lag, cumulative lag, and moving average PM concentrations from days 0–7 before suicide.ResultsWe confirmed an association between exposure to PM10 (≤ 10 μm in diameter) and deaths due to suicide. In particular, among individuals with psychiatric disorders and those who employed non-violent suicide methods, increased exposure to PM10 was associated with a higher risk of death by suicide, with percentage changes of 5.92 (95% confidence interval [CI]: 3.95–7.92) and 11.47 (95% CI: 7.95–15.11), respectively. Furthermore, in the group with psychiatric disorders, there was an observed tendency of increasing suicide risk as PM10 levels increased up to 120 µg/m3, whereas in the group with non-violent suicide deaths, there was a pronounced trend of rapid increase in suicide risk with an increase in PM10 up to 100 µg/m3.ConclusionsThese results show an association between short-term exposure to PM and suicide. Our study adds evidence for the benefits of reducing PM in preventing diseases and improving mental health.

Cleaner air for vulnerable people – Finding better locations for essential building premises

Long-term exposure to ambient air pollution even at relatively low concentrations is associated with adverse health effects especially for children, the elderly and people with pre-existing chronic disease. Due to a variety of urban planning decisions, essential building premises attended by these vulnerable groups may be sited in locations exposed to higher levels of air pollution. Using high spatial resolution air pollution concentrations estimated by satellite-based Land Use Regression (LUR) models in Australia, we mapped and approximated the annual average concentrations of particulate matter (PM2.5) and nitrogen dioxide (NO2) at schools, child care centres, aged care facilities and hospitals across Sydney. We found that 137 (3.1 %) and 287 (6.4 %) of the total number of essential buildings assessed were exposed to annual average PM2.5 and NO2 concentrations, respectively, where: the air pollutant concentrations were greater than the median concentration of other locations in the surrounding Local Government Area (LGA), and; air pollutant levels were greater than the 90th percentile concentrations for Sydney, and; air pollution at the essential building location was at least 1 µg/m3 for PM2.5 or 2 ppb for NO2 greater than the 25th percentile concentration of other locations in the LGA. Based on these criteria, we found that many essential building premises in Sydney were in high air pollution locations and there were other meaningfully lower air pollution locations within the surrounding area. Air quality is becoming an increasingly important issue for local jurisdictions to consider as more essential amenities are required to serve denser populations in busier places exposed to more air pollution. Our study showed that high resolution maps can be used as a health-based planning tool to encourage the siting of buildings at locations better protective of health.

Individual exposure of ambient particulate matters and eosinophilic chronic rhinosinusitis with nasal Polyps: Dose-Response, mediation effects and recurrence prediction

PurposeWe evaluated the association between ambient particulate matter (PM) exposure and eosinophilic chronic rhinosinusitis with nasal polyps (CRSwNP), and predicted the CRSwNP recurrence risk using machine learning algorithms. MethodsIn total, 1,086 patients with CRSwNP were recruited from nine hospitals in China during 2014–2019. The average annual concentrations of ambient PMs before surgery were assessed using satellite-based daily concentrations of PM2.5 and PM10 for a 1 × 1-km2 area. Linear regression and logistic regression models were used to evaluate the associations of PM exposure with eosinophilia and risks of eosinophilic CRSwNPs. In addition, mediation effect analysis was used to validate the interrelationships of the aforementioned factors. Finally, machine learning algorithms were used to predict the recurrence risks of CRSwNPs. ResultsThere was a significantly increased risk of eosinophilic CRSwNPs with each 10 μg/m3 increase in PMs, with odds ratios (ORs) of 1.039 (95% confidence interval [CI] = 1.007–1.073) for PM10 and 1.058 (95% CI = 1.007– 1.112) for PM2.5. Eosinophils had a significant mediation effect, which accounted for 52% and 35% of the relationships of CRSwNP recurrence with PM10 and PM2.5, respectively. Finally, we developed a naïve Bayesian model to predict the risk of CRSwNP recurrence based on PM exposure, inflammatory data, and patients’ demographic factors. ConclusionsIncreased PM exposure is associated with an increased risk of eosinophilic CRSwNP in China. Therefore, patients with eosinophilic CRSwNP should reduce PM exposure to mitigate its harmful impacts.

Association between long-term exposure to ambient particulate matter and pulmonary function among men and women in typical areas of South and North China.

Studies comparing the effects of different sizes and concentrations of ambient particulate matter (PM) on pulmonary function in different regions and sexes remain sparse. To investigate the associations of different sizes and levels of long-term ambient PM exposure with pulmonary function among people of different sexes in typical areas of South and North China. In 2021, a total of 1,592 participants aged 20-73 years were recruited to participate in the pulmonary function test from the baseline survey of the Diverse Life-Course Cohort (DLCC) in typical areas of Guangdong Province and Hebei Province. The three-year (2018-2020) average ambient PM concentrations were assessed from the ChinaHighPM1 dataset, ChinaHighPM2.5 dataset and ChinaHighPM10 dataset. Mean differences in pulmonary function were used in multilevel models for different regions and sexes. We discovered significant associations of ambient PM exposure with reduced forced vital capacity (FVC) and increased forced expiratory volume in 1 s/forced vital capacity ratio (FEV1/FVC) among men and lower levels of FEV1 and FVC among women, such that a 5-μg/m3 concentration increase in PM1, PM2.5, and PM10 was associated with decreases in FVC of 122.1 ml (95% confidence interval (CI): 30.8, 213.4), 54.6 ml (95% CI: 15.8, 93.3) and 42.9 ml (95% CI: 12.7, 73.1) and increases in FEV1/FVC of 2.2% (95% CI: 0.6, 3.9), 1.1% (95% CI: 0.4, 1.9) and 0.9% (95% CI: 0.3, 1.5) among men and decreases in FEV1 of 51.1 ml (95% CI: 9.7, 92.4), 21.6 ml (95% CI: 4.3, 38.9) and 16.7 ml (95% CI: 3.3, 30.1) and in FVC of 77.8 ml (95% CI: 10.0, 145.6), 38.7 ml (95% CI: 9.0, 68.5) and 31.1 ml (95% CI: 8.1, 54.1) among women in Hebei Province. There was no association between ambient PM and pulmonary function in Guangdong Province. Long-term exposure to different sizes and concentrations of ambient PM were associated with FEV1 and FVC among men and women differently. The impact of ambient PM on FVC should be of greater concerned.

Association of Temperature Thresholds with Heat Illness- and Cardiorespiratory-Related Emergency Visits during Summer Months in Alaska.

Recent record-breaking hot temperatures in Alaska have raised concerns about the potential human health implications of heat exposure among this unacclimated population. We estimated cardiorespiratory morbidity associated with days above summer (June-August) heat index (HI, apparent temperature) thresholds in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) for the years 2015-2019. We implemented time-stratified case-crossover analyses of emergency department (ED) visits for International Classification of Diseases, 10th Revision codes indicative of heat illness and major cardiorespiratory diagnostic codes using data from the Alaska Health Facilities Data Reporting Program. Using conditional logistic regression models, we tested maximum hourly HI temperature thresholds between 21.1°C (70°F) and 30°C (86°F) for a single day, 2 consecutive days, and the absolute number of previous consecutive days above the threshold, adjusting for the daily average concentration of particulate matter . There were increased odds of ED visits for heat illness above a HI threshold as low as 21.1°C (70°F) [; 95% confidence interval (CI): 4.05, 47.29], and this increased risk continued for up to 4 d (; 95% CI: 1.15, 5.10). Asthma and pneumonia were the only respiratory outcomes positively associated with the HI: ED visits for both were highest the day after a heat event (Asthma: ; 95% CI: 1.00, 1.39; Pneumonia: ; 95% CI: 1.06, 1.84). There was a decreased odds of bronchitis-related ED visits when the HI was above thresholds of 21.1-28°C (70-82°F) across all lag days. We found stronger effects for ischemia and myocardial infarction (MI) than for respiratory outcomes. Multiple days of warm weather were associated with an increased risk of health impacts. For each additional preceding day above a HI of 22°C (72°F), the odds of ED visits related to ischemia increased 6% (95% CI: 1%, 12%); for each additional preceding day above a HI of 21.1°C (70°F), the odds of ED visits related to MI increased 7% (95% CI: 1%, 14%). This study demonstrates the importance of planning for extreme heat events and developing local guidance for heat warnings, even in areas with historically mild summertime climates. https://doi.org/10.1289/EHP11363.

Monitoring the Air Quality and Microclimate in a Semi-urban Area Using a Smartphone

In most developing countries, the air quality index is a relevant issue since it directly impacts human health and mobility. Commercial devices have already been used to describe the relationship between the air quality index and associated risks. But these results are not readily accessible to the general public, especially in semi-urban areas where threats of air pollution lurk with rapid urbanisation. The main idea is to use open-source wireless technologies for real-time monitoring of outdoor pollutants where free access to data on air pollution is not available. The result of the study shows the mean concentration of nitrous oxide ranges from 1.50 μg/m3 to 3.83 μg/m3 with the maximum being 6 μg/m3 and the minimum being 0 μg/m3. The average daily concentration of P.M10 ranges from 20.58 μg/m3 to 38.43 μg/m3 with a maximum 46 μg/m3 and the minimum 13 μg/m3. The average concentration of particulate matter P.M2.5 ranges from 30.04 μg/m3 to 53.39 μg/m3 with the maximum concentration being 59 μg/m3 and the minimum concentration being 2 μg/m3 in the study period. Similarly, the daily mean concentration of ozone varied between 19.87 μg/m3 and 34.75 μg/m3 with a maximum 52 μg/m3 and the minimum 5 μg/m3. The mean AQI value ranges from 34.54 to 54.30 with a maximum value of 91 and a minimum being 24. PM2.5 and PM10 showed a positive correlation (r2 = 0.998) with each other, indicating they came from the same source. Both PM2.5 and PM10 were negatively and weakly correlated with temperature and humidity. In the study, it is shown that PM10 acts as a single variable that affects the air quality index as a result of the combined effects of multiple factors.

Long-term Exposure to Ambient Air Pollutants and Increased Risk of Pneumonia in the UK Biobank

Short-term exposure to air pollution has been linked to pneumonia risk. However, evidence on the long-term effects of air pollution on pneumonia morbidity is scarce and inconsistent. We investigated the associations of long-term air pollutant exposure with pneumonia and explored the potential interactions with smoking. Is long-term exposure to ambient air pollution associated with the risk of pneumonia, and does smoking modify the associations? We analyzed data in 445,473 participants without pneumonia within 1 year before baseline from the UK Biobank. Annual average concentrations of particulate matter (particulate matter with a diameter< 2.5 μm [PM2.5] and particulate matter with a diameter< 10 μm [PM10]), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were estimated using land-use regression models. Cox proportional hazards models were used to assess the associations between air pollutants and pneumonia incidence. Potential interactions between air pollution and smoking were examined on both additive and multiplicative scales. The hazard ratios of pneumonia for each interquartile range increase in PM2.5, PM10, NO2, and NOx concentrations were 1.06 (95%CI, 1.04-1.08), 1.10 (95%CI, 1.08-1.12), 1.12 (95%CI, 1.10-1.15), and 1.06 (95%CI, 1.04-1.07), respectively. There were significant additive and multiplicative interactions between air pollution and smoking. Compared with individuals who had never smoked with low air pollution exposure, individuals who had ever smoked with high air pollution exposure had the highest pneumonia risk (PM2.5: hazard ratio [HR], 1.78; 95%CI, 1.67-1.90; PM10: HR, 1.94; 95%CI, 1.82-2.06; NO2: HR, 2.06; 95%CI, 1.93-2.21; NOx: HR, 1.88; 95%CI, 1.76-2.00). The associations between air pollutants and pneumonia risk persisted in participants exposed to air pollutants concentrations meeting the European Union limits. Long-term exposure to air pollutants was associated with an increased risk of pneumonia, especially in individuals who smoke.

Adverse Health Effects (Bronchitis Cases) Due to Particulate Matter Exposure: A Twenty-Year Scenario Analysis for the Greater Athens Area (Greece) Using the AirQ+ Model

It is well known that air pollution has a negative impact on human health. Research has shown an increasing trend in hospital admissions due to respiratory and heart diseases during and after consecutive days of high or even medium air pollution levels. The objective of this paper is to provide quantitative and qualitative data concerning the impact of long-term air pollution on the health of residents living in the Greater Athens Area (GAA). More accurately, the prevalence of bronchitis in children and the incidence of chronic bronchitis cases in adults due to particulate matter exposure are estimated utilizing the AirQ+ model. For this purpose, daily average concentrations of particulate matter with an aerodynamic diameter less than or equal to 10 μm (PM10) from five different locations within the GAA, covering the period 2001–2020, are used. The results show a significant correlation between PM10 concentrations and adverse health effects (R2 = 0.9). Interestingly, there were more cases of children suffering from bronchitis disease than cases of adults. In addition, it was observed that the unhealthiest areas in the GAA are the center of Athens city (mean annual PM10 concentration in 2019: 36 μgr/m3), as well as suburban areas (Lykovrissi and Marousi: mean annual PM10 concentrations in 2019 were 27 μgr/m3 and 28 μgr/m3, respectively). Finally, a decreasing trend for both PM10 concentrations and the prevalence of chronic bronchitis across the GAA was observed through the examined 20 years, which was significantly higher over the period 2010–2020.

Assessing over decadal biomass burning influence on particulate matter composition in subequatorial Amazon: literature review, remote sensing, chemical speciation and machine learning application.

A study on aerosols in the Brazilian subequatorial Amazon region, Tangará da Serra (TS) and Alta Floresta (AF) was conducted and compared to findings in an additional site with background characteristics (Manaus, AM). TS and AF counties suffer from intense biomass burning periods in the dry season, and it accounts for high levels of particles in the atmosphere. Chemical characterization of fine and coarse particulate matter (PM) was performed to quantify water-soluble ions (WSI) and black carbon (BC). The importance of explanatory variables was assessed using three machine learning techniques. Average concentrations of PM in AF and TS were similar (PM2.0, 17±10 µg m-3 (AF) and 16±11 µg m-3 (TS) and PM10-2.0, 13±5 µg m-3 (AF) and 11±7 µg m-3 (TS)), but higher than the background site. BC and SO4 2- were the prevalent components as they represented 27%-68% of particulates chemical composition. The combination of the machine learning techniques provided a further understanding of the pathways for PM concentration variability, and the results highlighted the influence of biomass burning for key sample groups and periods. PM2.0, BC, and most WSI presented higher concentrations in the dry season, providing further support for the influence of biomass burning.

Cardiac Autonomic Impacts of Bushfire Smoke - A Prospective Panel Study.

Air pollution is associated with cardiovascular disease and mortality. Most studies have focussed on urban or traffic-related pollution, and less is known about the impacts from bushfire smoke on cardiovascular autonomic function, although it is associated with increased sudden cardiac death and mortality. We sought to investigate its instantaneous and short-term impacts on heart rate variability (HRV). Twenty-four (24)-hour Holter electrocardiography (ECG) was repeated twice (during bushfire [Phase 1] and then clean air [Phase 2]) in 32 participants from two Australian towns (Warburton and Traralgon, Victoria) surrounding planned burning areas. This was compared with 10 control participants in another town (Maffra, Victoria) with two clean air assessments during the same periods. The primary HRV parameters assessed were those assessing overall HRV (Standard Deviation of Normal-to-Normal intervals [SDNN]), long-term HRV (Standard Deviation of the Average of Normal Sinus-to-Normal Sinus intervals for each 5-minutes [SDANN]), low frequency [LF]) and short-term HRV (Root Mean Square of Successive Differences between N-N intervals [RMSSD], High Frequency [HF], LF:HF ratio). Average concentrations of particulate matter <2.5 μm in diameter (PM2.5) were measured at fixed site monitors in each location. Mean PM2.5 levels were significantly elevated during bushfire exposure in Warburton (96.5±57.7 μg/m3 vs 4.0±1.9 μg/m3, p<0.001) and Traralgon (12.6±4.9 μg/m3 vs 3.4±3.1 μg/m3, p<0.001), while it remained low in the control town, Maffra, in each phase (4.3±3.2 μg/m3 and 3.9±3.6 μg/m3, p=0.70). Although SDANN remained stable in controls, the exposed cohort showed significant worsening in SDANN during bushfire smoke exposure by 9.6±25.7ms (p=0.039). In univariable analysis, smoke exposure was significantly associated with higher ΔSDNN and ΔSDANN (p=0.03, p=0.01 exposed vs control). The association remained significant in ΔSDANN after adjusting for age, sex and cigarette smoking (p=0.02) and of borderline significance in ΔSDNN (p=0.06). Exposure to the bushfire smoke was independently associated with reduced overall and long-term HRV. Our findings suggest that imbalance in cardiac autonomic function is a key mechanism of adverse cardiovascular effects of bushfire smoke.

Airborne particulate matter in Southeast Asia: a review on variation, chemical compositions and source apportionment

Environmental context Airborne particulate matter (PM) is a major public health risk in Southeast Asia. The annual average concentration of fine PM (PM2.5) in the region is significantly higher than the WHO air quality guidelines, and higher PM2.5 levels were recorded during dry seasons, primarily due to biomass burning. In this paper, we provide an overview of the seasonal variations in concentrations, chemical compositions, and sources of PM in Southeast Asian countries. Abstract Airborne particulate matter (PM) in Southeast Asia is the most important air pollutant, causing millions of premature deaths. This review provides an overview of the levels, chemical compositions and sources of PM and compared these with studies from megacities in other regions. Daily average PM2.5 concentrations were lower than polluted megacities such as Delhi but substantially higher than 24-h mean air quality guideline of the WHO. Levels of PM2.5 in maritime continental Southeast Asia (Indonesia, Brunei, Malaysia, Philippines and Singapore) were lower than in mainland continental countries (Cambodia, Myanmar, Thailand, Vietnam, and Laos). PM levels are usually two times higher during dry than wet seasons. Organic carbon is a key chemical component, contributing 9–52% of PM mass. SO42−EN22044_IE1.gif, NO3−EN22044_IE2.gif, and NH4+EN22044_IE3.gif are major ions and NO3−EN22044_IE4.gif/SO42−EN22044_IE5.gif ratios were notably lower than in megacities in other regions, implying lower emissions from mobile relative to stationary sources. Source apportionment indicates biomass burning is one of the most important sources, particularly during the haze (dry) seasons, followed by road traffic emission in dense-traffic cities such as Bangkok, Kuala Lumpur and Hanoi. The secondary aerosols contribution to PM mass is usually lower than that in cities from other regions. We suggest future PM source apportionment studies in Southeast Asia to include both inorganic and organic tracers and apply both chemical mass balance and multivariate receptor models.

Assessing Air Pollution and Determining the Composition of Airborne Dust in Urbanized Areas: Granulometric Characteristics

The article focuses on the problem of atmospheric pollution in urban areas caused by particulate matter, which is a problem for most industrial cities. The work aims to assess air pollution by particulate matter PM10 and PM2.5; determine the composition of airborne dust in a zone free of any industrial activity; obtain statistical characteristics of dust distribution in the atmospheric air of urbanized areas according to granulometric characteristics. The issues of PM10 and PM2.5 presence in the atmospheric air of urban and industrial centers in major European cities were analyzed. The degree of air pollution by PM10 and PM2.5 in the autumn-winter season 2020–2021 in Chelyabinsk city was assessed by gravimetry, considering the air quality standards valid in Russia and the European Union. It was found that the average concentration of particulate matter in the air of the urbanized areas of Chelyabinsk in the six months of the autumn-winter period 2020–2021 was 83 µg/m3 and exceeded the MPC (maximum permissible concentration) 2.1 times. The average value of the concentration of fine dust fractions for six months of the study period was 67 µg/m3, exceeding the MPC by 2.7 times. The obtained results indicate that there is a big problem of pollution, therefore it is important to apply the necessary actions to restore the state of air quality standards, which do not cause health risks to the population exposed to ultrafine particulate matter.

Ambient particulate matter pollution of different sizes associated with recurrent stroke hospitalization in China: A cohort study of 1.07 million stroke patients

BackgroundTo estimate the associations between ambient particulate matter (PM) pollution of different sizes (PM1, PM2.5, and PM10) and risk of rehospitalization among stroke patients, as well as the attributable burden in China. MethodsWe built a cohort of 1,066,752 participants with an index stroke hospitalization in Sichuan, China from 2017 to 2019. Seven-day and annual average exposures to PM pollution prior to the date of the index hospitalization were linked with residential address using a bilinear interpolation approach. Cox proportional hazard models were constructed to assess the association between ambient PM and the risk of rehospitalization. The burden of stroke rehospitalization was estimated using a counterfactual approach. Results245,457 (23.0 %) participants experienced rehospitalization during a mean of 1.15 years (SD: 0.90 years) of follow-up. Seven-day average concentrations of PM were associated with increased risk of rehospitalization: the hazard ratios (HRs) per 10 μg/m3 were 1.034 (95 % confidence interval [CI]: 1.029–1.038) for PM1, 1.033 (1.031–1.036) for PM2.5, and 1.030 (1.028–1.031) for PM10; the hazard ratios were larger for annual average concentrations: 1.082 (1.074–1.090) for PM1, 1.109 (1.104–1.114) for PM2.5, and 1.103 (1.099–1.106) for PM10. The associations were stronger in participants who were female, of minority ethnicity (non-Han Chinese), who suffered from an ischemic stroke, and those admitted under normal conditions. Population attributable fractions for stroke rehospitalization ranged from 4.66 % (95 % CI: 1.69 % to 7.63 %) for the 7-day average of PM1 to 17.05 % (14.27 % to 19.83 %) for the annual average of PM10; the reducible average cost of rehospitalization per participant attributable to PM ranged from 492.09 (178.19 to 806) RMB for the 7-day average of PM1 to 1801.65 (1507.89 to 2095.41) RMB for the annual average of PM10. ConclusionsAmbient PM pollution may increase the risk of rehospitalization in stroke patients and is responsible for a significant burden of stroke rehospitalization.

Association between environmental air pollution and olfactory functioning among Italian adolescents and young adults in Northern Italy

BACKGROUND AND AIM Olfaction is a critical physiological process with various functions in humans and olfactory impairments are associated with neurodegenerative disease and decreased quality of life. Olfactory receptors are in direct contact to ambient air, and thus, olfactory function is uniquely vulnerable to airborne pollutants. Here, we investigate associations between ambient air pollutant exposure and olfactory function in adolescents and young adults in the province of Brescia, Italy. METHODS This study included 207 subjects (52.7% female, 15-25 years) enrolled in the ongoing longitudinal Public Health Impact of Metals Exposure (PHIME) study. All participants completed a baseline (2008-2014) and follow-up (2017-2021) olfactory performance assessment using the &amp;#x22;Sniffin’ Sticks”, a psychophysical test to assess odor threshold, discrimination and identification. Spatial annual average concentrations of particulate matter (PM) PM10, PM2.5 and nitrogen dioxide (NO2) were estimated for the target area between 2016-2019 on a 4 x 4 km2 spatial resolution grid by means of the Chemical Transport Model ARIA Regional. We applied multivariable beta regression models to test for associations between each pollutant and olfactory functions. RESULTS All air pollution annual average values were below European air quality standards (mean +/- SD g/m3 PM2.5 = 18.4 +/- 5.1; PM10 = 21.0 +/- 5.3; NO2 = 32.1 +/- 9.8). We observed a significant negative association between NO2 and olfactory threshold score; a 14% decrement (approximately 2 score points) for each 10 unit increase in NO2 (p = 0.042), adjusting for age, sex, Sniffin’ identification baseline score, having a cold and/or allergic rhinitis, IQ and passive smoking exposure. CONCLUSIONS These results suggest increased NO2 exposure is associated with reduced olfactory function in these Italian adolescents and young adults. The identification of risk factors for olfactory functions can help prevent reduced quality of life and improve recovery. KEYWORDS Olfactory functions; air pollution; NO2; PM2.5; PM10

Wildfire Smoke Exposure During Pregnancy and Preterm Birth in California

Background/Aim Owing to climate change and fire suppression policy, wildfires in the Western United States are a significant source of air pollution that threatens to reverse decades of progress in air pollution reduction; effects of wildfires on preterm birth (PTB) are not well understood. We assessed associations between prenatal exposure to wildland fire (wildfire and prescribed fire) smoke and risk of PTB in California. Methods The population included all live singleton births in California, 2007-2015. PTB was defined as gestational age &amp;#x3c;37 weeks. We assigned wildland fire smoke exposure to geocoded maternal residence at birth with weekly average concentrations of particulate matter &amp;#x2264;2.5 microns attributable to fires from USEPA’s Community Multiscale Air Quality Model (fire PM2.5) and smoke frequencies (smoke days) from National Oceanic and Atmospheric Administration’s Hazard Mapping System. We used logistic regression to estimate odds ratios (OR) for PTB associated with exposures in the final 6 weeks of pregnancy and Cox proportional hazard models to estimate hazard ratios (HR) for PTB in relation to weekly exposures. Models adjusted for maternal age, education, race/ethnicity, season, medical insurance, and smoking. Results Our study included 3,342,267 births. A one-smoke day increase in any of the final 6 weeks of the pregnancy was associated with increased odds of PTB, ranging from OR=1.01 (95%CI:1.01-1.02) in the final week of pregnancy to OR=1.03 (95%CI:1.02-1.03) 5 weeks before birth. A 10µg/m3 increase in fire PM2.5 in the final 6 weeks was associated with ORs ~1.04 (95%CIs covered 1.02-1.06). In survival analyses, HR=1.01 (95%CI:1.01-1.02) for a one-day increase in smoke frequency and HR=1.03 (95%CI:1.02-1.04) for a 10µg/m3 increase in fire PM2.5. Conclusion Wildland fire smoke is modestly associated with PTB. Results can inform efforts to slow climate change, manage forests, and reduce wildfire smoke exposure to pregnant people. Keywords wildfire; pregnancy; preterm birth; climate; air pollution