Low Levels Of Air Pollution Research Articles

Оцінка якості атмосферного повітря Житомира за показниками ушкодженості пилку Spiraea x vanhouttei

An assessment of the state of Spiraea x vanhouttei pollen in the green areas of Zhytomyr under the influence of various factors of urbotechnogenic origin was carried out. A species of perennial plants of the shrub layer was selected for bioindicative studies. The generative part of these plant species is exposed to the main components of air pollution for a long time, as is the human respiratory system. Assessment of the state of atmospheric air in the surface layer is important for determining potential consequences for the ecosystem and assessing the risk to public health. Atmospheric air pollution by emissions of pollutants from industrial enterprises and motor vehicles is one of the main environmental problems of Zhytomyr and the region. Although in general, according to the data of the CGO named after B. Sreznevskyi, Zhytomyr belongs to the cities with a low level of atmospheric air pollution. It occupies the 23rd position among other cities of Ukraine. The article describes the characteristics of the main components of air pollution and their sources. To monitor the state of the gametophyte S. x vanhouttei, 6 locations were selected in different districts of the city, which differ in terms of anthropogenic load and the presence of green spaces. The sensitivity of pollen was studied by qualitative (fertility) and quantitative indicators. In most of the studied territories, plants have retained a high reproductive potential. A significant loss (by 2.1–2.25 times) of pollen fertility was noted only in plants in the territory with increased influence of emissions from mobile sources. The depressive effect of exogenous factors is more evidenced by the variability of morphometric characteristics. In particular, the production of morphologically diverse pollen grains and the reduction of their average size. In particular, the production of a larger share of morphologically diverse pollen grains and a decrease in their average size was noted. This is also due mainly to the impact of emissions from motor vehicles, as this is the area where the city’s largest transport hubs are located – the railway station and the central bus station. Thus, the conclusions of the Central Geophysical Observatory named after B. Sreznevsky regarding the dominant influence of mobile sources in the total amount of pollutants in the urban ecosystem of Zhytomyr. The established manifestations of the sensitivity of S. vanhouttei pollen to a complex of exogenous factors of the growing environment confirm the prospects of its use as a medium-resistant species for bioindicative assessment of the state of the environment.

Prenatal exposure to particulates and anthropometry through 9 years of age in a birth cohort.

Previous research observed links between prenatal air pollution and risk of childhood obesity but the timing of the exposure is understudied. We examined prenatal particulate matter (PM10, PM2.5) exposure and child anthropometry. Children's body mass index z-scores (zBMI) at 0-3 (N = 4370) and 7-9 (n = 1191) years were derived from reported anthropometry at paediatric visits. We ran linear mixed models for six windows, adjusting for maternal, child, and neighbourhood factors. PM10 exposure across pregnancy and at multiple windows was associated with higher zBMI in both early and middle childhood. For instance, one interquartile range increase in PM10 exposure during the first 2 weeks of pregnancy was associated with higher zBMI at 0-3 (0.05, 95% CI: 0.01, 0.10) and 7-9 (0.14, 95% CI: 0.02, 0.23). PM2.5 exposure during the final 2 weeks of gestation was associated with higher zBMI at 7-9 years (B: 0.12, 95% CI: 0.04, 0.22). Even at low levels of air pollution, prenatal PM10 exposure was associated with higher zBMI in childhood.

An explainable AI framework for spatiotemporal risk factor analysis in public health: a case study of cardiovascular mortality in South Korea

ABSTRACT Understanding environmental disease risk factor analysis at the district level is essential for gaining valuable insights into regional disease variations, offering a broader perspective compared to individual-level studies. Recently, explainable artificial intelligence (XAI) has received increasing attention in the analysis of factors affecting public health. However, previous purely data-driven XAI-based risk factor analyses faced challenges in capturing regional effect of environmental variables, leading to confusion regarding key spatiotemporal risk factors. Therefore, this study proposes a framework that includes two complementary XAI-based risk factor analyses following two assumptions. Regionally rescaled environmental variables must account for the unequal effects on environmental factors, which are likely influenced by variations in adaptation capacity to weather conditions and differences in exposure-response relationships to air pollutants. District-level disease distribution highlights geographic disparity in sociodemographic vulnerability, whereas temporal variation in diseases by district underscores temporal environmental impacts. Based on these two hypotheses, we rescaled environmental variables using two complementary schemes: one that employs the district-level disease distribution as the target variable, and another that utilizes the temporal residual of the disease within each district. We evaluated this framework by analyzing the association between cardiovascular age-standardized mortality rate (CVD-ASMR) and various risk factors in South Korea from 2010 to 2019, using high-performing random forest and light gradient boosting models with additive Shapley explanation. Compared to previous purely data-driven XAI-based analyses, the proposed schemes achieved significantly better results in capturing regional exposure-response relationships. In two complementary schemes, the most explainable factor to districts with high CVD-ASMR was low education level related to sociodemographic vulnerability, whereas the most explainable factors to high temporal CVD-ASMR patterns were low greenness and high air pollution levels. In addition, the two complementary schemes enabled us to reasonably analyze the interaction effect of the two risk factors, i.e. temperature and air pollutants. Furthermore, high CVD-ASMR and its high temporal variation were observed in situations of high sociodemographic vulnerability with poor air quality. These findings provide insightful public health planning for sustainable cities and society by pinpointing high-risk areas and tailoring strategies to address regional environmental challenges.

Estimating the effect of annual PM2·5 exposure on mortality in India: a difference-in-differences approach.

In 2019, the Global Burden of Diseases, Injuries, and Risk Factors Study attributed 0·98 million deaths to ambient air pollution in India based on potentially inappropriate exposure-response functions from countries with low air pollution levels. Instead, using data from India, we investigated long-term exposure to PM2·5 and all-cause mortality with a causal inference method. We collected national counts of annual mortality from 2009 to 2019 from the Civil Registration System at the district level to calculate annual district-level mortality rate as our main outcome and obtained annual PM2·5 concentrations from a high-resolution spatiotemporal model. We applied an extended version of the difference-in-differences design by use of generalised additive models with quasi-Poisson distribution, including indicator variables and separate time trends for spatial administrative divisions. PM2·5 concentrations obtained at 1 km × 1 km spatial resolution across the country were used to calculate annual district-level mean PM2·5 concentrations. Similarly, we collected confounders at the district level, such as mean and SD of quarterly temperatures, gross domestic product per capita, population aged 60 years or older, clean cooking fuel usage, literacy in women, and median age. The spatial unit of analysis was administrative division. The annual median population-weighted PM2·5 was 38·9 μg/m3 (5-95th percentile 19·7-71·8 μg/m3). The full population lived in areas with PM2·5 concentrations exceeding the 5 μg/m3 annual mean recommended in the WHO guidelines, and 1·1 billion of 1·4 billion (81·9% of the total population) lived in areas above the Indian National Ambient Air Quality Standards for annual mean PM2·5 not exceeding 40 μg/m3. A 10 μg/m3 increase in annual PM2·5 concentration was associated with an 8·6% (95% CI 6·4-10·8) higher annual mortality. Based on the Indian National Ambient Air Quality Standards, a total of 3·8 million (95% CI 2·9-4·9) deaths between 2009 and 2019 were attributable to PM2·5, amounting to 5·0% (3·8-6·4) of total mortality. Based on the WHO guidelines, a total of 16·6 million (13·0-21·8) deaths were attributable to PM2·5, amounting to 24·9% (19·5-32·5) of total mortality. Our difference-in-differences approach allowed us to assess the full extent of registered deaths in the most populated country in the world, which has high levels of air pollution. We provide new evidence of increased mortality risk from long-term PM2·5, which emphasises the need for tighter regulatory standards to potentially substantially reduce mortality across India. Swedish Research Council for Sustainable Development.

Assessing the impact of coal furnace activities on air quality: A comprehensive spatial and temporal analysis

Air pollution is a critical threat to public health and environmental systems, primarily driven by industrial activities such as coal furnace operations. This study uses advanced spatial analysis techniques, including kriging and Principal Component Analysis (PCA), to assess the impact of these activities on air quality in a designated study area. The Air Quality Index (AQI) is also employed to evaluate air quality in this research. Additionally, five key variables—number of households, coal furnaces, average income, average cost, and AQI—are normalized using the MinMaxScaler for comparative analysis. Also, the results indicate that the southern and western regions of the study area have the highest pollutant concentrations, correlating with high AQI values and the density of coal furnaces and industrial activities. The PCA results show that urban areas are mainly affected by CO2 and SO2, significantly influencing the AQI, while agricultural land and other types of land (rangeland, forest, dryland, barren land) show varying dominant pollutants. Agricultural lands were found to be primarily impacted by SO2, CO2, and CO. In addition, a temporal analysis reveals a 10% annual increase in coal furnace operations from 2003 to 2024, contributing to the rise in pollution levels. The AQI optimization results also indicate a strong negative correlation between the number of coal furnaces and AQI, suggesting that reducing the number of coal furnaces can lower air pollution levels. These findings highlight the significant role of industrial emissions in worsening air quality and emphasize the need for cleaner technologies, reduced coal furnace usage, and stronger regulatory measures.

THE RELATIONSHIP BETWEEN AIR POLLUTION AND CORONARY ARTERY DISEASE: A SYSTEMATIC REVIEW

Several previous research studies have shown that air pollution has broad impacts on human health, particularly in the cardiovascular field. Exposure to air pollution entering the respiratory system can trigger inflammatory responses and increase the risk of cardiovascular diseases such as coronary artery disease. This systematic review aim to determine the relationship between air pollution and the occurrence of Coronary Artery Disease (CAD). Journal searches were conducted on five electronic databases, namely Pubmed, Science Direct, Europe PMC, Wiley Online Library, and Cochrane, following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) method. The search results get six original articles that meet the inclusion and exclusion criteria for analysis. Based on the results of the analysis shows that there is a significant relationship between air pollution in the form of gas components or particulate matter with the incidence of coronary artery disease. High levels of air pollution in an area can also increase the risk of CAD higher than areas with lower levels of air pollution.

Association between exposure to air pollution and increased ischaemic stroke incidence: a retrospective population-based cohort study (EP-PARTICLES study)

Abstract Aims Short-term effects of Polish smog, particularly benzo(alpha)pyrene [B(a)P], are unclear. We aimed to examine the association between short-term exposure to air pollution and ischaemic stroke (IS) incidence. Methods and results We conducted a retrospective population-based cohort study including an EP-PARTICLES cohort of 8 million inhabitants in the years 2011–20 (80 million person-years of observation). Individual clinical data on emergency hospitalizations due to IS (ICD-10: I63.X) was analysed. We used quasi-Poisson models to examine municipality-specific associations between air pollutants and IS, considering various covariates. We recorded 146 262 cases of IS with a dominance of females (51.8%) and people over 65 years old (77.6%). In the overall population, exposure to PM2.5, NO2, B(a)P, and SO2 increased the risk of IS onset on the day of exposure by 2.4, 1, 0.8, and 0.6%, respectively. Age and sex were modifying variables for PM2.5, NO2, and B(a)P exposure with more pronounced effects in non-elderly individuals and women (all Pinteraction < 0.001). Residents of regions with high tobacco and alcohol consumption were more sensitive to the effects of PM2.5 and SO2. The slopes of response–effect curves were non-linear and steeper at lower concentrations. Conclusion Exposure to air pollution may be associated with higher IS incidence, particularly posing a higher risk to non-elderly women. Harmful lifestyle habits might exacerbate its impact. Exposure to even low levels of air pollutants had negative effects. Registration The study was registered at ClinicalTrials.gov (NCT05198492).

Association between long-term exposure to low ambient PM2.5 and cardiovascular hospital admissions: A UK Biobank study

IntroductionA causal link between air pollution exposure and cardiovascular events has been suggested. However fewer studies have investigated the shape of the associations at low levels of air pollution and identified the most important temporal window of exposure. Here we assessed long-term associations between particulate matter < 2.5 µm (PM2.5) at low concentrations and multiple cardiovascular endpoints using the UK Biobank cohort. MethodsUsing data on adults (aged > 40) from the UK Biobank cohort, we investigated the associations between 1-year, 3-year and 5-year time-varying averages of PM2.5 and incidence of major adverse cardiovascular events (MACE), myocardial infarction (MI), heart failure, atrial fibrillation and flutter and cardiac arrest. We also investigated outcome subtypes for MI and stroke. Events were defined as hospital inpatient admissions. We fitted Cox proportional hazard regression models applying extensive control for confounding at both individual and area level. Finally, we assessed the shape of the exposure–response functions to assess effects at low levels of exposure. ResultsWe analysed data from 377,736 study participants after exclusion of prevalent subjects. The average follow-up (2006–2021) was 12.9 years. We detected 19,353 cases of MACE, 6,562 of acute MI, 6,278 of heart failure, 1,258 for atrial fibrillation and flutter, and 16,327 for cardiac arrest. Using a 5-year exposure window, we detected positive associations (for 5 μg/m3 increase in PM2.5) for 5-point MACE of [1.12 (95 %CI: 1.00–1.26)], heart failure [1.22 (1.00–1.50)] and cardiac arrest [1.16 (1.03–1.31)]. We did not find any association with acute MI, while non-ST-elevation MI was associated with the 1-year exposure window [1.52 (1.12–2.07)]. The assessment of the shape of the exposure–response relationships suggested that risk is approximately linear for most of the outcomes. ConclusionsWe found positive associations between long-term exposure to PM2.5 and multiple cardiovascular outcomes for different exposure windows. The cardiovascular risk tends to rise even at exposure concentrations below 12–15 μg/m3, indicating high risk below UK national and international thresholds.

Associations between Changes in Exposure to Air Pollutants due to Relocation and the Incidence of 14 Major Disease Categories and All-Cause Mortality: A Natural Experiment Study.

Though observational studies have widely linked air pollution exposure to various chronic diseases, evidence comparing different exposures in the same people is limited. This study examined associations between changes in air pollution exposure due to relocation and the incidence and mortality of 14 major diseases. We included 50,522 participants enrolled in the UK Biobank from 2006 to 2010. Exposures to particulate matter with a diameter (), particulate matter with a diameter (), nitrogen oxides (), nitrogen dioxide (), and sulfur dioxide () were estimated for each participant based on their residential address and relocation experience during the follow-up. Nine exposure groups were classified based on changes in long-term exposures due to residential mobility. Incidence and mortality of 14 major diseases were identified through linkages to hospital inpatient records and death registries. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incidence and mortality of the 14 diseases of interest. During a median follow-up of 12.6 years, 29,869 participants were diagnosed with any disease of interest, and 3,144 died. Significantly increased risk of disease and all-cause mortality was observed among individuals who moved from a lower to higher air polluted area. Compared with constantly low exposure, moving from low to moderate exposure was associated with increased risk of all 14 diseases but not for all-cause mortality, with adjusted HRs (95% CIs) ranging from 1.18 (1.05, 1.33) to 1.48 (1.30, 1.69); moving from low to high areas increased risk of all 14 diseases: infections [1.37 (1.19, 1.58)], blood diseases [1.57 (1.34, 1.84)], endocrine diseases [1.77 (1.50, 2.09)], mental and behavioral disorders [1.93 (1.68, 2.21)], nervous system diseases [1.51 (1.32, 1.74)], ocular diseases [1.76 (1.56, 1.98)], ear disorders [1.58 (1.35, 1.86)], circulatory diseases [1.59 (1.42, 1.78)], respiratory diseases [1.51 (1.33, 1.72)], digestive diseases [1.74 (1.58, 1.92)], skin diseases [1.39 (1.22, 1.58)], musculoskeletal diseases [1.62 (1.45, 1.81)], genitourinary diseases [1.54 (1.36, 1.74)] and cancer [1.42 (1.24, 1.63)]. We observed similar associations for and with 14 diseases (but not with all-cause mortality); increases in and were positively associated with 14 diseases and all-cause mortality. This study supports potential associations between ambient air pollution exposure and morbidity as well as mortality. Findings also emphasize the importance of maintaining consistently low levels of air pollution to protect the public's health. https://doi.org/10.1289/EHP14367.

Exposure to Low-Level Air Pollution and Hyperglycemia Markers during Pregnancy: A Repeated Measure Analysis.

Epidemiologic evidence has emerged showing an association between exposure to air pollution and increased risks of gestational diabetes mellitus (GDM). This study examines the effect of low-level air pollution exposure on a subclinical biomarker of hyperglycemia (i.e., HbA1c) in pregnant people without diabetes before conception. We measured HbA1c in 577 samples repeatedly collected from 224 pregnant people in Rochester, NY, and estimated residential concentrations of PM2.5 and NO2 using high-resolution spatiotemporal models. We observed a U-shaped trajectory of HbA1c during pregnancy with average HbA1c levels of 5.13 (±0.52), 4.97 (±0.54), and 5.43 (±0.40)% in early-, mid-, and late pregnancy, respectively. After adjustment for the U-shaped trajectory and classic GDM risk factors, each interquartile range increase in 10 week NO2 concentration (8.0 ppb) was associated with 0.09% (95% CI: 0.02 to 0.16%) and 0.18% (95% CI: 0.08 to 0.28%) increases in HbA1c over the entire pregnancy and in late pregnancy, respectively. These associations remained robust among participants without GDM. Using separate distributed lag models, we identified a period between 8th and 14th gestational weeks as critical windows responsible for increased levels of HbA1c measured at 14th, 22nd, and 30th gestational weeks. Our results suggest that low-level air pollution contributes to hyperglycemia in medically low-risk pregnant people.

Long-term exposures to low concentrations of source-specific air pollution, road-traffic noise, and systemic inflammation and cardiovascular disease biomarkers

ObjectivesAir pollution and traffic noise are detrimental to cardiovascular health. However, the effects of different sources of these exposures on cardiovascular biomarkers remain unclear. We explored the associations of long-term exposure to source-specific air pollution (vehicular exhausts and residential woodsmoke) at low concentrations and road-traffic noise with systemic inflammation and cardiovascular disease biomarkers. Material and methodsModeled outdoor exposure to fine particulate matter (aerodynamic diameter ≤2.5 μm; PM2.5) from vehicular exhausts and residential woodsmoke, nitrogen dioxide (NO2) from road traffic, and road-traffic noise were linked to the home addresses of the participants (Finnish residents aged 25–74) in the FINRISK study 1997–2012. The participants were located in the cities of Helsinki, Vantaa, and the region of Turku, Finland. The outcomes were high-sensitivity C-reactive protein (CRP), a biomarker for systemic inflammation, and cardiovascular disease biomarkers N-terminal pro-B-type natriuretic peptide (NT-proBNP) and troponin I. We performed cross-sectional analyses with linear and additive models and adjusted for potential confounders. ResultsWe found no association between PM2.5 from vehicular exhausts (% CRP difference for 1 μg/m3 increase in PM2.5: −0.9, 95% confidence interval, CI: −7.2, 5.8), or from residential woodsmoke (% difference: −8.1, 95% CI: −21.7, 7.9) and CRP (N = 4147). Road-traffic noise >70 dB tended to be positively associated with CRP (% CRP difference versus noise reference category of ≤45 dB: 18.3, 95% CI: −0.5, 40.6), but the association lacked significance and robustness (N = 7142). Otherwise, we found no association between road-traffic noise and CRP, nor between NO2 from road traffic and NT-proBNP (N = 1907) or troponin I (N = 1951). ConclusionLong-term exposures to source-specific, fairly low-level air pollution from vehicular exhausts and residential woodsmoke, or road-traffic noise were not associated with systemic inflammation and cardiovascular disease biomarkers in this urban area.

The effect of low-level air pollution exposure on weight at birth

The effect of low-level air pollution exposure on weight at birth

Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: The HEI Experience and What's Next?

Although concentrations of ambient air pollution continue to decline in high-income regions, epidemiological studies document adverse health effects at levels below current standards in many countries. The Health Effects Institute (HEI) recently completed a comprehensive research initiative to investigate the health effects of long-term exposure to low levels of air pollution in the United States (U.S.), Canada, and Europe. We provide an overview and synthesis of the results of this initiative along with other key research, the strengths and limitations of the research, and remaining research needs. The three studies funded through the HEI initiative estimated the effects of long-term ambient exposure to fine particulate matter (PM2.5), nitrogen dioxide, ozone, and other pollutants on a broad range of health outcomes, including cause-specific mortality and cardiovascular and respiratory morbidity. To ensure high quality research and comparability across studies, HEI worked actively with the study teams and engaged independent expert panels for project oversight and review. All three studies documented positive associations between mortality and exposure to PM2.5 below the U.S. National Ambient Air Quality Standards and current and proposed European Union limit values. Furthermore, the studies observed nonthreshold linear (U.S.), or supra-linear (Canada and Europe) exposure-response functions for PM2.5 and mortality. Heterogeneity was found in both the magnitude and shape of this association within and across studies. Strengths of the studies included the large populations (7-69 million), state-of-the-art exposure assessment methods, and thorough statistical analyses that applied novel methods. Future work is needed to better understand potential sources of heterogeneity in the findings across studies and regions. Other areas of future work include the changing and evolving nature of PM components and sources, including wildfires, and the role of indoor environments. This research initiative provided important new evidence of the adverse effects of long-term exposures to low levels of air pollution at and below current standards, suggesting that further reductions could yield larger benefits than previously anticipated.

Long-term Exposure to Ambient Air Pollution and its Association with Mental Well-Being, Depression and Anxiety: A Nationally Representative Study.

Exposure to ambient air pollution may play a role in the onset of common mental disorders like depressive and anxiety disorders. The association of long-term exposure to particles smaller than 10 μm (PM10) with these diseases remains unclear. This study aimed to estimate the association of long-term exposure to PM10 with mental well-being and the frequency of probable diagnosis of common mental disorders. A nationally representative cross-sectional study was done in mainland Portugal. Long-term exposure was estimated through one-year average concentrations of PM10, calculated with data from the Portuguese Environment Agency, attributed individually considering individuals' postal codes of residence. The mental well-being and the probable diagnosis of common mental disorders were ascertained through the five-item Mental Health Inventory scale. Linear and Robust Poisson regression models were computed to estimate change percentages, prevalence ratios (PR), and their 95% confidence intervals (95% CI). The median (interquartile range) concentration of PM10 was 18.6 (15.3 - 19.3) μg/m3. The mental well-being score was 72 (56 - 84) points, on a scale from 0 to 100. A probable diagnosis of common mental disorders was found in 22.7% (95% CI: 20.0 to 25.6). Long-term exposure to PM10 was associated with a non-statistically significant decrease in the mental well-being score [for each 10 μg/m³ increment in one-year average PM10 concentrations, there was a 2% (95% CI: -8 to 4) decrease], and with a non-statistically significant increase in the common mental health frequency (PR = 1.012, 95% CI: 0.979 to 1.045). We did not find statistically significant associations between long-term exposure to PM10 and mental well-being or the frequency of probable diagnosis of common mental disorders. These results may be explained by the reduced variability in the exposure values, given the geographical distribution and functioning of the network of air quality monitoring stations. This study contributes with evidence for low levels of air pollutants, being one of the first to adjust for individual and aggregate-level variables. Moreover, to the best of our knowledge, this was the first nationally representative, population-based study conducted on the Portuguese population using real-life data. Maintaining a robust and nationwide air quality monitoring network is essential for obtaining quality exposure data.

Monitoring of atmospheric air quality in cities participating in the federal project “Clean Air” of the Far Eastern Economic Region

Introduction. Air pollution over 2021 was associated with about 6.7 thousand additional deaths and almost 1.1 million additional cases of illness among the Russian population. Conducting an atmospheric air quality assessment for the subsequent selection of priority measures aimed at reducing its negative impact on public health is the main task of the Clean Air federal project. The aim of the study is to assess the management of monitoring and air quality in the cities of Komsomolsk-on-Amur, Petrovsk-Zabaykalsky, and Ussuriysk before the implementation of the federal project “Clean Air”. Materials and methods. The monitoring programs for atmospheric air quality, the results of laboratory studies for 2021 were used. The number, location of observation posts, volumes, frequency of sampling, a list of indicators, the total number of samples, the number of samples exceeding the MPC, average annual, maximum one-time concentrations of pollutants were analyzed. Results. In Komsomolsk-on-Amur, atmospheric air quality monitoring was carried out at 4 stationary and 3 route posts, Ussuriysk – 1 mobile and 1 stationary post, Petrovsk-Zabaikalsky – 1 stationary post. All studied cities are characterized by systematic excesses of hygienic standards for specific indicators. The level of air pollution in the city of Komsomolsk-on-Amur is assessed as very high, in the cities of Ussuriysk and Petrovsk-Zabaikalsky – low. Despite the low level of air pollution, these towns are characterized by systematic excesses of hygienic standards of some indicators. Limitations. The study analyzed the management of monitoring and the results of laboratory studies of atmospheric air only in the cities of Komsomolsk-on-Amur, Ussuriysk, Petrovsk-Zabaykalsky. Conclusion. The existing monitoring system in the Ussuriysk, Komsomolsk-on-Amur and Petrovsk-Zabaykalsky cities fails to allow an objective assessing of the quality of atmospheric air and its impact on public health. To objective evaluation of the impact of atmospheric air quality on the health of the population of the studied cities, measures to optimize the monitoring system were proposed.

Improved Air Quality and Asthma Incidence from School Age to Young Adulthood: A Population-based Prospective Cohort Study.

Rationale: The benefits of improved air quality on asthma remain understudied. Objectives: Our aim was to investigate associations of changes in ambient air pollution with incident asthma from school age until young adulthood in an area with mostly low air pollution levels. Methods: Participants in the BAMSE (Swedish abbreviation for Children, Allergy, Environment, Stockholm, Epidemiology) birth cohort from Stockholm without asthma before the 8-year follow-up were included (N = 2,371). We estimated the association of change in individual-level air pollutant exposure (particulate matter with an aerodynamic diameter ≤ 2.5 μm [PM2.5] and ≤ 10 μm [PM10], black carbon [BC], and nitrogen oxides [NOx]) from the first year of life to the 8-year follow-up with asthma incidence from the 8-year until the 24-year follow-up. Multipollutant trajectories were identified using the group-based multivariate trajectory model. We also used parametric G-computation to quantify the asthma incidence under different hypothetical interventions regarding air pollution levels. Results: Air pollution levels at residency decreased during the period, with median reductions of 5.6% for PM2.5, 3.1% for PM10, 5.9% for BC, and 26.8% for NOx. A total of 395 incident asthma cases were identified from the 8-year until the 24-year follow-up. The odds ratio for asthma was 0.89 (95% confidence interval [CI], 0.80-0.99) for each interquartile range reduction in PM2.5 (equal to 8.1% reduction). Associations appeared less clear for PM10, BC, and NOx. Five multipollutant trajectories were identified; the largest reduction trajectory displayed the lowest odds of asthma (odds ratio, 0.55; 95% CI, 0.31-0.98) compared with the lowest reduction trajectory. If the PM2.5 exposure had not declined up to the 8-year follow-up, the hypothetical asthma incidence was estimated to have been 10.9% higher (95% CI, 0.8-20.8%). Conclusions: A decrease in PM2.5 levels during childhood was associated with a lower risk of incident asthma from school age to young adulthood in an area with relatively low air pollution levels, suggesting broad respiratory health benefits from improved air quality.

Systemic oxidative stress levels during the course of pregnancy: Associations with exposure to air pollutants

Increased systemic oxidative stress, implicated in adverse pregnancy outcomes for both mothers and fetuses, has been associated with gestational exposure to air pollutants such as polycyclic aromatic hydrocarbons (PAHs), fine particulate matter (PM2.5), and nitrogen dioxide (NO2). However, it is unclear whether exposure to pollutants at levels below the current air quality standards can increase oxidative stress in pregnant women. In a cohort of 305 pregnant persons residing in western New York, we examined the association between exposure to PM2.5, NO2, and PAHs (measured as urinary 1-hydroxypyrene) and urinary biomarkers of oxidative stress (malondialdehyde [MDA] and 8-hydroxy-2′-deoxyguanosine [8-OHdG]) measured in each trimester. After controlling for gestational stage, maternal age, lifestyles, and socioeconomic factors, each interquartile range (IQR) increase in 1-hydroxypyrene concentration (65.8 pg/ml) was associated with a 7.73% (95%CI: 3.18%,12.3%) higher in MDA levels throughout the pregnancy and in the first and second trimester. An IQR increase in PM2.5 concentration (3.20 μg/m3) was associated with increased MDA levels in the first trimester (8.19%, 95%CI: 0.28%,16.1%), but not the 2nd (−7.99%, 95% CI: 13.8%, −2.23%) or 3rd trimester (−2.81%, 95% CI: 10.0%, 4.38%). The average cumulative PM2.5 exposures in the 3–7 days before urine collection were associated with increased 8-OHdG levels during the second trimester, with the largest difference (22.6%; 95% CI: 3.46%, 41.7%) observed in relation to a one IQR increase in PM2.5 concentration in the previous 7 days. In contrast, neither oxidative stress biomarker was associated with NO2 exposure. Observed in pregnant women exposed to low-level air pollution, these findings expanded previously reported associations between systemic oxidative stress and high-level PM2.5 and PAH concentrations. Further, the first and second trimesters may be a susceptible window during pregnancy for oxidative stress responses to air pollution exposure.

Assessing the risks associated with indoor and outdoor air quality in relation to the geographic placement of nursing home

Indoor air quality significantly impacts the well-being and health of elderly residents in nursing homes. This study was conducted to explore the connection between indoor and outdoor PM (Particulate Matter) concentrations in nursing homes and their association with the facilities' location and construction characteristics. The findings revealed that indoor PM2.5 and PM10 concentrations ranged from 0.2 to 124 μg/m3 and 2–188.4 μg/m3, respectively, which were approximately 12.67 and 1.25 times higher than their outdoor counterparts. A strong correlation (P < 0.05) was identified between indoor PM levels and various factors, including proximity to parks, passenger terminals, and gas stations, as well as building attributes such as single-glazed windows, ceramic floor coverings, and the use of radiators. The risk assessment indicated that carcinogenic risk factors were well within acceptable limits for all nursing homes. However, it's important to note that certain PM components, particularly polycyclic aromatic hydrocarbons (PAH), may have long-term adverse effects on the health of nursing home residents. Even though indoor PM levels met the standards established by the U.S. Environmental Protection Agency (USEPA) for particulate matter risk assessments, the study emphasized that even low levels of indoor air pollutants can affect the health and well-being of older adults, particularly considering the increased vulnerability associated with aging. Consequently, the study underscores the importance of nursing home location selection and the regular monitoring of particulate matter concentrations. These measures are essential for enhancing air quality within nursing homes, ultimately contributing to the improved well-being and health of their residents.

Organic Emissions of Volatile Chemical Products in Canada: Emission Inventories, Indoor-to-Outdoor Transfer, and Regional Impacts.

The contribution of volatile chemical products (VCPs) to ambient air pollution has increased following decades of regulating combustion sources. There is a research gap concerning the impact of indoor physicochemical phenomena on VCP emissions. In this work, a bottom-up speciated VCP emission inventory with indoor-outdoor resolution was developed for Canada, an industrialized country with low air pollution levels, whose major cities are among the largest urban areas in North America. VCPs were estimated to account for about 290 kilotons of gaseous organic emissions for a typical year in the 2010s, with more than 60% of emissions occurring indoors. Coatings and cleaners were the most emissive VCP categories. Oxygenated species and saturated aliphatics dominated the chemical profiles of most emissions. Less than 5% of VCP emissions were impacted by indoor physicochemical phenomena. VCP emissions were predicted to account for 0.8-3.2 s-1 of OH reactivity and 0.22-0.52 μg/m3 of secondary organic aerosol formation potential in major urban areas in Canada. Our predictions aligned with previous measurements concerning indoor and outdoor organic pollutant levels, underscoring the important air quality impacts of VCPs relative to other sources. Our results provide helpful insights for future research regarding VCP emissions, especially from indoor spaces.

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

BackgroundMental 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.MethodsThis 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.ResultsWe 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.ConclusionsThe 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.