Assessing the impact of short-term ozone exposure on excess deaths from cardiovascular disease: a multi-pollutant model in Nanjing, China's Yangtze River Delta.

Background: Ozone pollution is associated with cardiovascular disease mortality, and there is a high correlation between different pollutants. This study aimed to assess the association between ozone and cardiovascular disease deaths and the resulting disease burden in Nanjing, China. Methods: A total of 151,609 deaths from cardiovascular disease were included in Nanjing, China from 2013 to 2021. Daily data on meteorological and air pollution were collected to apply a generalized additional model with multiple pollutants to perform exposure-response analyses, stratification analysis, and evaluation of excess deaths using various standards. Results: In the multi-pollutant model, an increase of 10 µg/m3 in O3 was significantly associated with a 0.81% (95%CI: 0.49, 1.12%) increase in cardiovascular disease deaths in lag05. The correlation weakened in both the single-pollutant model and two-pollutant models, but remained more pronounced in females, the older group, and during warm seasons. From 2013 to 2021, the number of excess deaths attributed to ozone exposure in cardiovascular disease continued to rise with an increase in ozone concentration in Nanjing. If the ozone concentration were to be reduced to the WHO standard and the minimum level, the number of deaths would decrease by 1,736 and 10,882, respectively. Conclusion: The risk of death and excess deaths from cardiovascular disease due to ozone exposure increases with higher ozone concentration. Reducing ozone concentration to meet WHO standards or lower can provide greater cardiovascular disease health benefits.

Source-Specific Air Pollution and Loss of Independence in Older Adults Across the US.

Importance: Air pollution is a recognized risk factor associated with chronic diseases, including respiratory and cardiovascular conditions, which can lead to physical and cognitive impairments in later life. Although these losses of function, individually or in combination, reduce individuals' likelihood of living independently, little is known about the association of air pollution with this critical outcome. Objective: To investigate associations between air pollution and loss of independence in later life. Design, Setting, and Participants: This cohort study was conducted as part of the Environmental Predictors Of Cognitive Health and Aging study and used 1998 to 2016 data from the Health and Retirement Study. Participants included respondents from this nationally representative, population-based cohort who were older than 50 years and had not previously reported a loss of independence. Analyses were performed from August 31 to October 15, 2023. Exposures: Mean 10-year pollutant concentrations (particulate matter less than 2.5 µm in diameter [PM2.5] or ranging from 2.5 µm to 10 µm in diameter [PM10-2.5], nitrogen dioxide [NO2], and ozone [O3]) were estimated at respondent addresses using spatiotemporal models along with PM2.5 levels from 9 emission sources. Main Outcomes and Measures: Loss of independence was defined as newly receiving care for at least 1 activity of daily living or instrumental activity of daily living due to health and memory problems or moving to a nursing home. Associations were estimated with generalized estimating equation regression adjusting for potential confounders. Results: Among 25 314 respondents older than 50 years (mean [SD] baseline age, 61.1 [9.4] years; 11 208 male [44.3%]), 9985 individuals (39.4%) experienced lost independence during a mean (SD) follow-up of 10.2 (5.5) years. Higher exposure levels of mean concentration were associated with increased risks of lost independence for total PM2.5 levels (risk ratio [RR] per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.10), PM2.5 levels from road traffic (RR per 1-IQR of 10-year mean, 1.09; 95% CI, 1.03-1.16) and nonroad traffic (RR per 1-IQR of 10-year mean, 1.13; 95% CI, 1.03-1.24), and NO2 levels (RR per 1-IQR of 10-year mean, 1.05; 95% CI, 1.01-1.08). Compared with other sources, traffic-generated pollutants were most consistently and robustly associated with loss of independence; only road traffic-related PM2.5 levels remained associated with increased risk after adjustment for PM2.5 from other sources (RR per 1-IQR increase in 10-year mean concentration, 1.10; 95% CI, 1.00-1.21). Other pollutant-outcome associations were null, except for O3 levels, which were associated with lower risks of lost independence (RR per 1-IQR increase in 10-year mean concentration, 0.94; 95% CI, 0.92-0.97). Conclusions and Relevance: This study found that long-term exposure to air pollution was associated with the need for help for lost independence in later life, with especially large and consistent increases in risk for pollution generated by traffic-related sources. These findings suggest that controlling air pollution could be associated with diversion or delay of the need for care and prolonged ability to live independently.

Characterization of air pollution and associated health risks in Gansu Province, China from 2015 to 2022.

Air pollution poses a major threat to both the environment and public health. The air quality index (AQI), aggregate AQI, new health risk-based air quality index (NHAQI), and NHAQI-WHO were employed to quantitatively evaluate the characterization of air pollution and the associated health risk in Gansu Province before (P-I) and after (P-II) COVID-19 pandemic. The results indicated that AQI system undervalued the comprehensive health risk impact of the six criteria pollutants compared with the other three indices. The stringent lockdown measures contributed to a considerable reduction in SO2, CO, PM2.5, NO2 and PM10; these concentrations were 43.4%, 34.6%, 21.4%, 17.4%, and 14.2% lower in P-II than P-I, respectively. But the concentration of O3 had no obvious improvement. The higher sandstorm frequency in P-II led to no significant decrease in the ERtotal and even resulted in an increase in the average ERtotal in cities located in northwestern Gansu from 0.78% in P-I to 1.0% in P-II. The cumulative distribution of NHAQI-based population-weighted exposure revealed that 24% of the total population was still exposed to light pollution in spring during P-II, while the air quality in other three seasons had significant improvements and all people were under healthy air quality level.

Association of Gaseous Ambient Air Pollution and Dementia-Related Neuroimaging Markers in the ARIC Cohort, Comparing Exposure Estimation Methods and Confounding by Study Site.

BACKGROUND: Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE: We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS: We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxides (NOx), and 8- and 24-h ozone (O3) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS: Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher NO2 and NOx and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION: Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, NOx, and NO2 and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906.

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.

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.

Ambient air pollution exposure and COVID-19 related hospitalizations in Santiago, Chile.

Morbidity and mortality from several diseases are increased on days of higher ambient air pollution. We carried out a daily time-series analysis with distributive lags to study the influence of short-term air pollution exposure on COVID-19 related hospitalization in Santiago, Chile between March 16 and August 31, 2020. Analyses were adjusted for temporal trends, ambient temperature, and relative humidity, and stratified by age and sex. 26,579 COVID-19 hospitalizations were recorded of which 24,501 were laboratory confirmed. The cumulative percent change in hospitalizations (95% confidence intervals) for an interquartile range increase in air pollutants were: 1.1 (0.2, 2.0) for carbon monoxide (CO), 0.30 (0.0, 0.50) for nitrogen dioxide (NO2), and 2.7 (1.9, 3.0) for particulate matter of diameter ≤ 2.5 microns (PM2.5). Associations with ozone (O3), particulate matter of diameter ≤ 10 microns (PM10) and sulfur dioxide (SO2) were not significant. The observed effect of PM2.5 was significantly greater for females and for those individuals ≥ 65 years old. This study provides evidence that daily increases in air pollution, especially PM2.5, result in a higher observed risk of hospitalization from COVID-19. Females and the elderly may be disproportionately affected.

Geographic sources of ozone air pollution and mortality burden in Europe.

Ground-level ozone (O3) is a harmful air pollutant formed in the atmosphere by the interaction between sunlight and precursor gases. Exposure to current O3 levels in Europe is a major source of premature mortality from air pollution. However, mitigation actions have been mainly designed and implemented at the national and regional scales, lacking a comprehensive assessment of the geographic sources of O3 pollution and its associated health impacts. Here we quantify both national and imported contributions to O3 and their related mortality burden across 813 contiguous regions in 35 European countries, representing about 530 million people. Imported O3 contributed to 88.3% of all O3-attributable deaths (intercountry range 83-100%). The greatest share of imported O3 had its origins outside the study domain (that is, hemispheric sources), which was responsible for 56.7% of total O3-attributable mortality (range 42.5-87.2%). It was concluded that achieving the air-quality guidelines set out by the World Health Organization and avoiding the health impacts of O3 require not only the implementation of national or coordinated pan-European actions but also global strategies.

Characteristics of surface ozone pollution and its correlations with meteorological factors: the case of Xiangtan.

Based on ozone (O3) monitoring data for Xiangtan and meteorological observation data for 2020-2022, we examined ozone pollution characteristics and the effects of meteorological factors on daily maximum 8-h average ozone (O3-8h) concentrations in Xiangtan. Thus, we observed significant increases as well as notable seasonal variations in O3-8h concentrations in Xiangtan during the period considered. The ozone and temperature change response slope (KO3-T) indicated that local emissions had no significant effect on O3-8h generation. Further, average O3-8h concentration and maximum temperature (Tmax) values showed a polynomial distribution. Specifically, at Tmax < 27 °C, it increased almost linearly with increasing temperature, and at Tmax between 27 and 37 °C, it showed an upward curvilinear trend as temperature increased, but at a much lower rate. Then, at Tmax > 37 °C, it decreased with increasing temperature. With respect to relative humidity (RH), the average O3-8h concentration primarily exceeded the standard value when RH varied in the range of 45-65%, which is the key humidity range for O3 pollution, and the inflection point for the correlation curve between O3-8h concentration and RH appeared at ~55%. Furthermore, at wind speeds (WSs) below 1.5 m∙s-1, O3-8h concentration increased rapidly, and at WSs in the 1.5-2 m∙s-1 range, it increased at a much faster rate. However, at WSs > 2 m∙s-1, it decreased slowly with increasing WS. O3-8h concentration also showed the tendency to exceed the standard value when the dominant wind directions in Xiangtan were easterly or southeasterly.

Long-term trends (compared to the pre-war period) and public health impact of surface ozone in Ukraine.

OBJECTIVE: Aim: To analyze the dynamics of ambient air pollution by surface O3 (in pre-war and wartime periods) and assess its impact on public health in order to provide proposals aimed at developing preventive programs. PATIENTS AND METHODS: Materials and Methods: Physical and chemical methods of analysis (О3 - gas analyzers APDA-370 HORIBA, meteorological sensor WS-600); health risk assessment (AirQ+); statistical data processing methods (StatSoft STATISTICA 10.0 portable, MicrosoftR Excel). RESULTS: Results: Air quality monitoring in peak season 2021 and 2022 detected exceedances of the daily maximum 8-hour ozone (O3) concentration. This resulted in a health risk for the exposed population during 70 % (174 days) and 84 % (181 days) of observations, respectively. The maximum exceedance levels were 1.7 and 2.1 times higher than the recommended limit. Estimated number of excess cases of natural and respiratory mortality in the population over 30 years due to long-term O3 exposure: 227 (95 % CI: 0; 450) and 22 (95 % CI: 0; 54), respectively. Predictive assessments of ozone (O3) air pollution's impact during wartime activities suggest an average increase of 40 % in additional deaths from non-communicable diseases. CONCLUSION: Conclusions: Obtained results can serve as a basis for development of medical and environmental measures aimed at implementing adaptation proposals for public health in conditions of global climate change and wartime.

Spatiotemporal joint analysis of PM2.5 and Ozone in California with INLA approach.

The substantial threat of concurrent air pollutants to public health is increasingly severe under climate change. To identify the common drivers and extent of spatiotemporal similarity of PM2.5 and ozone (O3), this paper proposed a log Gaussian-Gumbel Bayesian hierarchical model allowing for sharing a stochastic partial differential equation and autoregressive model of order one (SPDE-AR(1)) spatiotemporal interaction structure. The proposed model, implemented by the approach of integrated nested Laplace approximation (INLA), outperforms in terms of estimation accuracy and prediction capacity for its increased parsimony and reduced uncertainty, especially for the shared O3 sub-model. Besides the consistently significant influence of temperature (positive), extreme drought (positive), fire burnt area (positive), gross domestic product (GDP) per capita (positive), and wind speed (negative) on both PM2.5 and O3, surface pressure and precipitation demonstrate positive associations with PM2.5 and O3, respectively. While population density relates to neither. In addition, our results demonstrate similar spatiotemporal interactions between PM2.5 and O3, indicating that the spatial and temporal variations of these pollutants show relatively considerable consistency in California. Finally, with the aid of the excursion function, we see that the areas around the intersection of San Luis Obispo and Santa Barbara counties are likely to exceed the unhealthy O3 level for USG simultaneously with other areas throughout the year. Our findings provide new insights for regional and seasonal strategies in the co-control of PM2.5 and O3. Our methodology is expected to be utilized when interest lies in multiple interrelated processes in the fields of environment and epidemiology.

Health effects of air pollution on respiratory symptoms: A longitudinal study using digital health sensors.

Previous studies of air pollution and respiratory disease often relied on aggregated or lagged acute respiratory disease outcome measures, such as emergency department (ED) visits or hospitalizations, which may lack temporal and spatial resolution. This study investigated the association between daily air pollution exposure and respiratory symptoms among participants with asthma and chronic obstructive pulmonary disease (COPD), using a unique dataset passively collected by digital sensors monitoring inhaled medication use. The aggregated dataset comprised 456,779 short-acting beta-agonist (SABA) puffs across 3,386 people with asthma or COPD, between 2012 and 2019, across the state of California. Each rescue use was assigned space-time air pollution values of nitrogen dioxide (NO2), fine particulate matter with diameter ≤ 2.5 µm (PM2.5) and ozone (O3), derived from highly spatially resolved air pollution surfaces generated for the state of California. Statistical analyses were conducted using linear mixed models and random forest machine learning. Results indicate that daily air pollution exposure is positively associated with an increase in daily SABA use, for individual pollutants and simultaneous exposure to multiple pollutants. The advanced linear mixed model found that a 10-ppb increase in NO2, a 10 µg m-3 increase in PM2.5, and a 30-ppb increase in O3 were respectively associated with incidence rate ratios of SABA use of 1.025 (95 % CI: 1.013-1.038), 1.054 (95 % CI: 1.041-1.068), and 1.161 (95 % CI: 1.127-1.233), equivalent to a respective 2.5 %, 5.4 % and 16 % increase in SABA puffs over the mean. The random forest machine learning approach showed similar results. This study highlights the potential of digital health sensors to provide valuable insights into the daily health impacts of environmental exposures, offering a novel approach to epidemiological research that goes beyond residential address. Further investigation is warranted to explore potential causal relationships and to inform public health strategies for respiratory disease management.

[Air Pollutant Spatiotemporal Evolution Characteristics and Effects on Human Health in Xi'an City].

Xi'an is the political, economic, and cultural center of northwest China with a developed industry. Air pollution incidents have brought great challenges to the high-quality development of the social economy. It is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations in air pollutants in the study region from 2015 to 2021. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk-based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ2.2.3 model was used to quantify health effects. The results showed that the major pollutants were PM10, PM2.5, and O3. The main pollution characteristics of the study area were terrain characteristics and the mixed pollution of anthropogenic emissions. Compared to that of AQI, AAQI and HAQI showed better classification performance for pollution levels. HAQI revealed that approximately 80 % of the population was exposed to unhealthy air throughout the year in the study region. People were most exposed to unhealthy air in winter, followed by autumn and spring, and the least in summer. The AirQ2.2.3 model quantified the total mortality proportions attributable to PM2.5, PM10, SO2, CO, NO2, and O3, which were 0.99 %, 2.04 %, 0.41 %, 1.72 %, 8.76 %, and 3.67 %, respectively. The attributable proportion of mortality of the respiratory system and cardiovascular diseases was consistent with the change rule of total mortality.

Ozone risk assessment with free-air controlled exposure (FACE) experiments: A critical revisit.

Since risk assessments of tropospheric ozone (O3) are crucial for agricultural and forestry sectors, there is a growing body for realistic assessments by a stomatal flux-based approach in Free-Air Controlled Exposure (FACE) facilities. Ozone risks are normally described as relative risks (RRs), which are calculated by assuming the biomass or yield at zero O3 dose as "reference". However, the estimation of the reference biomass or yield is challenging due to a lack of O3-clean-air treatment at the FACEs and the extrapolation without data in a low O3 range increases the bias for estimating the reference values. Here, we reviewed a current methodology for the risk assessment at FACEs and presented a simple and effective way ("modified Paoletti's approach") of defining RRs just using biomass or yield data with a range of expected impacts under the FACE conditions hypothesizing three possible scenarios based on prediction limits using 95% credible intervals (CI) (1. Best fit using the intercept as reference, 2. Optimistic scenario using a lower CI and 3. Worst scenario using an upper CI). As a result, O3-sensitive species show a relatively narrow effect range (optimistic vs. worst scenario) whereas a wide range of response may be possibly taken in resistant species. Showing a possible effect range allows for a comprehensive understanding of the potential risks and its uncertainties related to a species sensitivity to O3. As a supporting approach, we also recommend to use scientifically relevant tools (i.e., ethylenediurea treatments; mechanistic plant models) for strengthening the obtained results for the RRs against O3. Interestingly, the moderately sensitive or resistant species showed non-linear rather than linear dose-response relationships, suggesting a need for the flexible functional form for the risk assessment to properly describe the complex plant response such as hormesis, which depends on their plasticity to O3 stress.

Association of exposure to ultraviolet radiation and warm-season ozone air pollution with incident age-related macular degeneration: A nationwide cohort study in China.

BACKGROUND: As the leading cause of blindness, age-related macular degeneration (AMD) performs an adverse impact on human health and disability. AMD have been reported to be associated with environmental factors; however, the association between ultraviolet (UV) radiation, warm-season ambient ozone pollution, and incident AMD remains unclear. METHODS: In this study, 19,707 participants without AMD at baseline were included from a nationwide longitudinal cohort in China. UV radiation and warm-season ozone exposure were evaluated through satellite-based models. Incident AMD was diagnosed via ophthalmological fundus images. Cox proportional hazard regression models were employed to explore the association of UV radiation and warm-season ozone with incident AMD, and the hazard ratios (HRs) and 95 % confidence intervals (CIs) were reported. RESULTS: During 312,935 person-month of follow-up, 3774 participants developed to AMD. High exposure to both UV radiation and warm-season ozone was associated with increasing risk of incident AMD, with HRs and 95 % CIs of 1.32 (1.23, 1.41) and 1.20 (1.11, 1.29) in two-exposure models, respectively. Moreover, negative interaction between UV radiation and warm-season ozone was identified, and it was found that exposure to high UV radiation and low ozone presented the highest hazard for AMD. Subgroup analyses showed that the UV-AMD association was stronger in southern China, while the ozone-AMD association was greater in northern China and rural areas. CONCLUSION: Our study provides the first epidemiological evidence that both UV radiation and warm-season ozone would elevate the risk of incident AMD, and the hazard of higher UV radiation may be attenuated by exposure to ozone. Strategies for decreasing AMD burden should jointly consider environmental exposures and geographic locations.

How Does Personal Hygiene Influence Indoor Air Quality?

Humans are known to be a continuous and potent indoor source of volatile organic compounds (VOCs). However, little is known about how personal hygiene, in terms of showering frequency, can influence these emissions and their impact on indoor air chemistry involving ozone. In this study, we characterized the VOC composition of the air in a controlled climate chamber (22.5 m3 with an air change rate at 3.2 h-1) occupied by four male volunteers on successive days under ozone-free (∼0 ppb) and ozone-present (37-40 ppb) conditions. The volunteers either showered the evening prior to the experiments or skipped showering for 24 and 48 h. Reduced shower frequency increased human emissions of gas-phase carboxylic acids, possibly originating from skin bacteria. With ozone present, increasing the number of no-shower days enhanced ozone-skin surface reactions, yielding higher levels of oxidation products. Wearing the same clothing over several days reduced the level of compounds generated from clothing-ozone reactions. When skin lotion was applied, the yield of the skin ozonolysis products decreased, while other compounds increased due to ozone reactions with lotion ingredients. These findings help determine the degree to which personal hygiene choices affect the indoor air composition and indoor air exposures.

In-depth analysis of ambient air pollution changes due to the COVID-19 pandemic in the Asian Monsoon region.

The COVID-19 pandemic has given a chance for researchers and policymakers all over the world to study the impact of lockdowns on air quality in each country. This review aims to investigate the impact of the restriction of activities during the lockdowns in the Asian Monsoon region on the main criteria air pollutants. The various types of lockdowns implemented in each country were based on the severity of the COVID-19 pandemic. The concentrations of major air pollutants, especially particulate matter (PM) and nitrogen dioxide (NO2), reduced significantly in all countries, especially in South Asia (India and Bangladesh), during periods of full lockdown. There were also indications of a significant reduction of sulfur dioxide (SO2) and carbon monoxide (CO). At the same time, there were indications of increasing trends in surface ozone (O3), presumably due to nonlinear chemistry associated with the reduction of oxides of nitrogens (NOX). The reduction in the concentration of air pollutants can also be seen in satellite images. The results of aerosol optical depth (AOD) values followed the PM concentrations in many cities. A significant reduction of NO2 was recorded by satellite images in almost all cities in the Asian Monsoon region. The major reductions in air pollutants were associated with reductions in mobility. Pakistan, Bangladesh, Myanmar, Vietnam, and Taiwan had comparatively positive gross domestic product growth indices in comparison to other Asian Monsoon nations during the COVID-19 pandemic. A positive outcome suggests that the economy of these nations, particularly in terms of industrial activity, persisted during the COVID-19 pandemic. Overall, the lockdowns implemented during COVID-19 suggest that air quality in the Asian Monsoon region can be improved by the reduction of emissions, especially those due to mobility as an indicator of traffic in major cities.

Temporal dynamics of urban air pollutants and their correlation with associated meteorological parameters: an investigation in northern Indian cities.

This study delves into the intricate dynamics of air pollution in the rapidly expanding northern regions of India, examining the intertwined influences of agricultural burning, industrialization, and meteorological conditions. Through comprehensive analysis of key pollutants (PM2.5, PM10, NO2, SO2, CO, O3) across ten monitoring stations in Uttar Pradesh, Haryana, Delhi, and Punjab, a consistent pattern of high pollution levels emerges, particularly notable in Delhi. Varanasi leads in SO2 and O3 concentrations, while Moradabad stands out for CO levels, and Jalandhar for SO2 concentrations. The study further elucidates the regional distribution of pollutants, with Punjab receiving significant contributions from SW, SE, and NE directions, while Haryana and Delhi predominantly face air masses from SE and NE directions. Uttar Pradesh's pollution sources are primarily local, with additional inputs from various directions. Moreover, significant negative correlations (p < 0.05) between PM10, NO2, SO2, O3, and relative humidity (RH) underscore the pivotal role of meteorological factors in shaping pollutant levels. Strong positive correlations between PM2.5 and NO2 (0.71 to 0.93) suggest shared emission sources or similar atmospheric conditions in several cities. This comprehensive understanding highlights the urgent need for targeted mitigation strategies to address the multifaceted drivers of air pollution, ensuring the protection of public health and environmental sustainability across the region.

Assessing Tunisia's urban air quality using combined lichens and Sentinel-5 satellite integration.

In Tunisia, urban air pollution is becoming a bigger problem. This study used a combined strategy of biomonitoring with lichens and satellite mapping with Sentinel-5 satellite data processed in Google Earth Engine (GEE) to assess the air quality over metropolitan Tunis. Lichen diversity was surveyed across the green spaces of the Faculty of Science of Tunisia sites, revealing 15 species with a predominance of pollution-tolerant genera. The Index of Atmospheric Purity (IAP) calculated from the lichen data indicated poor air quality. Spatial patterns of pollutants sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), carbon monoxide (CO), and aerosol index across Greater Tunis were analyzed from Sentinel-5 datasets on the GEE platform. The higher values of these indices in the research area indicate that it may be impacted by industrial activity and highlight the considerable role that vehicle traffic plays in air pollution. The results of the IAP, IBL, and the combined ground-based biomonitoring and satellite mapping techniques confirm poor air quality and an environment affected by atmospheric pollutants which will enable proactive air quality management strategies to be put in place in Tunisia's rapidly expanding cities.

Assessment of ground-level ozone pollution in Türkiye according to new WHO limits.

Ground-level ozone is a secondary pollutant and is attributable to respiratory diseases and mortality. For this reason, the World Health Organization (WHO) implemented a new long-term (peak season) limit value for ozone. The previous studies related to ozone in Türkiye were spatially limited to certain locations. In this study, annual mean and peak season ozone concentrations, and limit exceedances were investigated for Türkiye for the year 2021. Moreover, ozone peak seasons were determined for the first time for 126 air quality monitoring stations. The annual mean ozone concentration was determined as 44.3 ± 19.3 µg/m3 whereas the peak season average ozone level was 68.4 ± 27.2 µg/m3. April-September period was the most frequently observed ozone peak season. Among all stations, Erzurum Palandöken was by far the most polluted station in terms of annual mean and limit exceedances of ozone. Ankara Siteler stations have the highest rank in peak season mean. 87 and 83 stations exceeded the short-term and long-term recommendations of WHO, respectively. Four hotspot regions were revealed in terms of peak season exceedance: Adana and surrounding provinces, the surroundings of Burdur and Isparta provinces, and the northeastern and northwestern parts of Türkiye. To protect public health, WHO recommendations for 8-h and peak season limits should be immediately implemented in Turkish regulations.