Ambient Air Quality Standards Research Articles

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.

Bottom-up assessment of air quality management strategies in Vijayawada, India: Emissions inventory, atmospheric capacity, and policy scenarios

A bottom-up approach evaluates air quality management strategies in Vijayawada, India, a rapidly urbanizing city facing declining air quality. Detailed emission inventories and dispersion modeling assess pollutant concentrations (PM10, PM2.5, SO2, NOx) under various policy scenarios for 2025 and 2030. Business-as-usual (BAU) scenarios reveal the inadequacy of current regulations for PM, SO2, and NOx control. While BS-VI standards effectively reduced NOx emissions from vehicles, overall trends indicate a diminishing atmospheric capacity to assimilate pollutants. Alternative scenarios (ALTs) incorporating sector-specific controls project emission reductions (12–15 % PM10, 19–24 % PM2.5, 24–48 % SO2, 19–32 % NOx) and are expected to maintain pollutant levels below national ambient air quality standards. This integrated approach offers valuable insights for policymakers to develop sustainable air quality strategies aligned with SDGs. The study emphasises the need to consider potential trade-offs between environmental benefits and resource demands, such as increased electricity demand for electric vehicles (SDG 7) and land use competition from urban greening (SDG 11). This study aids in identifying strategies that maximise environmental benefits while minimising trade-offs, fostering sustainable urban development. The research's novelty lies in its integration of scenario-based analysis with atmospheric capacity evaluation, providing a robust framework for air quality management in rapidly urbanising regions.

Spatio-temporal distribution and source contributions of the ambient pollutants in Lucknow city, India.

Clean air is imperative to the survival of all life forms on the planet. However, recent times have witnessed enormous escalation in urban pollution levels. It is therefore, incumbent upon us to decipher measures to deal with it. In perspective, the present study was carried out to assess PM10 and PM2.5 loading, metallic constituents, gaseous pollutants, source contributions, health impact and noise level of nine-locations, grouped as residential, commercial, and industrial in Lucknow city for 2019-21. Mean concentrations during pre-monsoon for PM10, PM2.5, SO2 and NO2 were: 138.2 ± 35.2, 69.1 ± 13.6, 8.5 ± 3.3 and 32.3 ± 7.4µg/m3, respectively, whereas post-monsoon concentrations were 143.0 ± 33.3, 74.6 ± 14.5, 12.5 ± 2.1, and 35.5 ± 6.3µg/m3, respectively. Exceedance percentage of pre-monsoon PM10 over National Ambient Air Quality Standards (NAAQS) was 38.2% while that for post-monsoon was 43.0%; whereas corresponding values for PM2.5 were 15.2% and 24.3%. Post-monsoon season showed higher particulate loading owing to wintertime inversion and high humidity conditions. Order of elements associated with PM2.5 is Co < Cd < Cr < Ni < V < Be < Mo < Mn < Ti < Cu < Pb < Se < Sr < Li < B < As < Ba < Mg < Al < Zn < Ca < Fe < K < Na and that with PM10 is Co < Cd < Ni < Cr < V < Ti < Be < Mo < Cu < Pb < Se < Sr < Li < B < As < Mn < Ba < Mg < Al < Fe < Zn < K < Na < Ca. WHO AIRQ + ascertained 1654, 144 and 1100 attributable cases per 0.1 million of population to PM10 exposure in 2019-21. Source apportionment was carried out using USEPA-PMF and resolved 6 sources with highest percent contributions including road dust re-entrainment, biomass burning and vehicular emission. It is observed that residents of Lucknow city regularly face exposure to particulate pollutants and associated constituents making it imperative to develop pollution abetment strategies.

Bottom-Up Assessment of Air Quality Management Strategies in Vijayawada, India: Emissions Inventory, Atmospheric Capacity, and Policy Scenarios

A bottom-up approach evaluates air quality management strategies in Vijayawada, India, a rapidly urbanizing city facing declining air quality. Detailed emission inventories and dispersion modeling assess pollutant concentrations (PM10, PM2.5, SO2, NOx) under various policy scenarios for 2025 and 2030. Business-as-usual (BAU) scenarios reveal the inadequacy of current regulations for PM, SO2, and NOx control. While BS-VI standards effectively reduced NOx emissions from vehicles, overall trends indicate a diminishing atmospheric capacity to assimilate pollutants. Alternative scenarios (ALTs) incorporating sector-specific controls project emission reductions (12-15% PM10, 19-24% PM2.5, 24-48% SO2, 19-32% NOx) and are expected to maintain pollutant levels below national ambient air quality standards. This integrated approach offers valuable insights for policymakers to develop sustainable air quality strategies aligned with SDGs. The study emphasises the need to consider potential trade-offs between environmental benefits and resource demands, such as increased electricity demand for electric vehicles (SDG 7) and land use competition from urban greening (SDG 11). This study aids in identifying strategies that maximise environmental benefits while minimising trade-offs, fostering sustainable urban development. The research's novelty lies in its integration of scenario-based analysis with atmospheric capacity evaluation, providing a robust framework for air quality management in rapidly urbanising regions.

Insight Study of Trace Elements in PM2.5 During Nine Years in Delhi, India: Seasonal Variation, Source Apportionment, and Health Risks Assessment.

This study investigated the concentrations, seasonal variations, sources, and human health risks associated with exposure to heavy elements (As, Al, Pb, Cr, Mn, Cu, Zn, and Ni) of PM2.5 at an urban location of Delhi (28° 38' N, 77° 10' E; 218m amsl), India, from January 2013 to December 2021. The average mass concentration of PM2.5 throughout the study period was estimated as 127 ± 77µgm-3, which is exceeding the National Ambient Air Quality Standards (NAAQS) limit (annual: 40µgm-3; 24h: 60µgm-3). The seasonal mass concentrations of PM2.5 exhibited at the order of post-monsoon (192 ± 110 µgm-3) > winter (158 ± 70 µgm-3) > summer (92 ± 44 µgm-3) and> monsoon (67 ± 32 µgm-3). The heavy elements, Al (1.19µgm-3), Zn (0.49µgm-3), Pb (0.43µgm-3), Cr (0.21µgm-3), Cu (0.21µgm-3), Mn (0.07µgm-3), and Ni (0.14µgm-3) exhibited varying concentrations in PM2.5, with the highest levels observed in the post-monsoon season, followed by winter, summer, and monsoon seasons. Six primary sources throughout the study period, contributing to PM2.5 were identified by positive matrix factorization (PMF), such as dust (paved/crustal/soil dust: 29.9%), vehicular emissions (17.2%), biomass burning (15.4%), combustion (14%), industrial emissions (14.2%), and Br-rich sources (9.2%). Health risk assessments, including hazard quotient(HQ), hazard index(HI), and carcinogenic risk(CR), were computed based on heavy elements concentrations in PM2.5. Elevated HQvalues for Cr and Mn linked with adverse health impacts in both adults and children. High carcinogenic risk values were observed for Cr in both adults and children during the winter and post-monsoon seasons, as well as in adults during the summer and monsoon seasons. The combined HIvalue exceeding one suggests appreciable non-carcinogenic risks associated with the examined elements. The findings of this study provide valuable insights into the behaviour and risk mitigation of heavy elements in PM2.5, contributing to the understanding of air quality and public health in the urban environment of Delhi.

Model misspecification, measurement error, and apparent supralinearity in the concentration-response relationship between PM2.5 and mortality.

A growing number of studies have produced results that suggest the shape of the concentration-response (C-R) relationship between PM2.5 exposure and mortality is "supralinear" such that incremental risk is higher at the lowest exposure levels than at the highest exposure levels. If the C-R function is in fact supralinear, then there may be significant health benefits associated with reductions in PM2.5 below the current US National Ambient Air Quality Standards (NAAQS), as each incremental tightening of the PM2.5 NAAQS would be expected to produce ever-greater reductions in mortality risk. In this paper we undertake a series of tests with simulated cohort data to examine whether there are alternative explanations for apparent supralinearity in PM2.5 C-R functions. Our results show that a linear C-R function for PM2.5 can falsely appear to be supralinear in a statistical estimation process for a variety of reasons, such as spatial variation in the composition of total PM2.5 mass, the presence of confounders that are correlated with PM2.5 exposure, and some types of measurement error in estimates of PM2.5 exposure. To the best of our knowledge, this is the first simulation-based study to examine alternative explanations for apparent supralinearity in C-R functions.

Machine Learning Classification of Air Quality Monitoring Stations to Achieve Ambient NO2 Objectives Using Emission Scenarios and Chemical Transport Model

Exceeding the latest Canadian Ambient Air Quality Standards (CAAQS) for NO2 concentration in Canadian cities motivates discussions on new policies and directives. Advanced air quality modeling and machine learning clustering algorithms integrating the Weather Research Forecast (WRF) and Community Multiscale Air Quality (CMAQ) models were used to classify air quality monitoring (AQM) stations based on pollution concentration modeling results. The sensitivity of ambient NO2 to the primary anthropogenic emission sources was investigated in Alberta, Canada. Emissions from two main sources, upstream oil and gas (UOG) and transportation sources, have been identified as the reason Alberta fails to meet the newly adopted NO2 CAAQS objectives. The air quality model was validated with ground-level observation data and the atmospheric model accurately replicates spatiotemporal NO2 variations. Despite contributing 62% of Alberta’s total NOx emissions, UOG influences ambient NO2 concentrations modestly in urban areas (<10%) but significantly affects rural regions. In contrast, transportation emission sources, responsible for 23% of NOx emissions, dominate ambient NO2 levels (up to 63%) in large cities. The discrepancy of emission contribution and ground-level concentrations, obtained from the chemical transport model, was resolved using a k-prototypes clustering algorithm to propose a new approach for categorizing AQM stations which led to improving the conventional classifications. The new approach considered the sensitivity of NO2 to emission reduction scenarios and provided an improved classification to be used for emission reduction interventions. Based on the updated classification, one set of AQM stations clearly showed sensitivity to NO2 emission reduction in the transportation sector despite their lower contributions to overall emissions. These stations were categorized as population exposure stations in large cities.

An evaluation of air quality impact prediction performance undertaken as part of environmental impact assessment (EIA) in India

Effective implementation of the Environmental Impact Assessment (EIA) is recognised as a global issue, in particular the impact prediction stage, which is the ‘core’ of EIA. Consisting of four stages: impact identification, impact assessment, significance evaluation, and mitigation measures on the possible environmental repercussions of project developmental activities, the efficacy of impact prediction can define the quality of the EIA process, which will better align environmental decision-making to sustainable development. The weakness of impact prediction in EIA demands more study to enhance practice. Although this is widely explored in the context of developed countries such as the UK, it is particularly concerning in India. A specialised review package built from several sources is utilised to assess the efficacy of air quality impact prediction, based on Lee & Colley (1991). 20 EIA reports of Category A (mega-scale projects causing significant environmental impacts) are reviewed. This study's evaluation indicates that significance evaluation and mitigation actions are the weakest phases and a major concern while assessing air quality studies conducted as a part of EIA. Recommendations to improve the process include prioritising the cumulative impact assessment within the regulatory framework, enhancing capacity building, embedding public participation and instilling accountability among stakeholders, which can be adopted globally. Additional recommendations specifically for India are revising the National Ambient Air Quality Standards (NAAQS), restructuring the EIA review mechanism by EAC and improving mitigation measures by adopting GIS and remote sensing technologies.

Seasonal Variations Assessment of Air Pollutants of Communities in the Vicinity of Scrap Metal Recycling Industries in Ogijo, Shagamu South LGA, Ogun State, SW Nigeria

This manuscript presents a thorough investigation into the seasonal variations of air pollutants in communities surrounding scrap metal recycling industries in Ogijo, Shagamu South LGA, Ogun State, Nigeria utilizing advanced Gary Wolf Environmental Sensing and Particulate Counting devices. The study meticulously measures concentrations of carbon monoxide, nitrogen dioxide, sulfur dioxide, PM2.5, and PM10 during both dry and wet seasons across 20 strategic sampling locations and control. The findings reveal significant seasonal fluctuations in pollutant levels, with some concentrations exceeding Nigerian ambient air quality standards, highlighting a pressing environmental health concern. The study not only underscores the critical need for regulatory oversight and the implementation of safer metal scrapping practices but also advocates for regular environmental monitoring to mitigate the adverse impacts of such industries on local communities and the environment.

Changes in source specific PM2.5 from 2010 to 2019 in New York and New Jersey identified by dispersion normalized PMF

Since the Clean Air Act amendments of 1970, various efforts have been made in the United States to control ambient particulate matter and improve air quality. Although substantial progress had been made by the end of the 1990s, further reductions were needed to meet the National Ambient Air Quality Standards. To assess the effectiveness of the regulations and the impacts of economic drivers, we investigated the PM2.5 source trends at 11 sites in New York and New Jersey for the 2010–2019 period. Dispersion-normalized positive matrix factorization (DN-PMF) was used to reduce the meteorological impacts on the source apportionment. The Theil-Sen nonparametric estimator and piecewise linear regression were applied to the resolved source contributions to quantify the trends. While there is a consistent overall decrease of PM2.5 at all sites, increases were observed for some specific PM sources. Secondary Sulfate increased after 2017 at most sites based on the piecewise analysis. Similarly, recent-year increases were resolved for Diesel concentrations likely due to increasing vehicle miles traveled for heavy-duty vehicles. Back trajectory analysis of the OP-Rich source identified southeastern U.S. as a likely major source area, while Biomass Burning has a mixed source from local domestic heating as well as transported from proscribed and wildfires in the southeastern U.S.

VOC source apportionment, reactivity, secondary transformations, and their prioritization using fuzzy-AHP method in a coal-mining city in India.

This study assessed the air quality status in different functional zones of Dhanbad-a coal-mining and industrial hub, based on the measurement of aromatic and halogenated volatile organic compounds (VOCs) using gas chromatography. The study encompasses source apportionment of VOCs and their chemical reactivity in terms of OH radical loss rate (LOH), ozone-forming potential (OFP), and their secondary organic aerosol forming potential (SOAp). Furthermore, prioritization of VOCs based on a fuzzy-analytical hierarchical process (F-AHP) has also been done. The results found xylene species to have the highest concentration in all three seasons across traffic-intersection and industrial zones and toluene at the institutional zone. The study identified four sources using positive matrix factorization (PMF) model, viz., mixed traffic exhaust (35%), coal combustion sources (30%), industrial (26%), and solvent usage (9%). LOH and SOAp were ~ 16 times more at the industrial and traffic-intersection zone than the institutional zone. The aromatic species contributed 97% to the OFP, and many species exhibited less contribution to the mixing ratio of VOCs but displayed a high contribution to LOH, OFP, and SOAp, suggesting the need to prefer reactivity-based strategies in addition to concentration-based strategies in the future for their regulation. The F-AHP-based priority component analysis identified 16 species out of 29 in the priority watch list (nine in tier-1, four in tier-2, and three in tier-3). The paucity of data and lack of ambient air quality standards on VOCs (except benzene) make it difficult to determine which aspect should be dealt with first and which species require more attention. Therefore, the F-AHP method used in this study could help identify the influencing parameters to be considered while devising efficient VOC management policies.

Long-term trends in British Columbia lower mainland air quality: Criteria air pollutants and VOC

ABSTRACT The lower mainland of British Columbia is a geographic region that comprises the districts of Metro Vancouver and the Lower Fraser Valley. It is situated in a complex topographical and coastal location in southwestern British Columbia. Metro Vancouver is Canada’s third largest population center. Accessing the Canadian National Air Pollution Surveillance Program (NAPS) database we calculated air pollutant statistics using the Canadian Ambient Air Quality Standards (CAAQS) averaging times, numerical forms, and numerical levels for the years 2001to 2020. Man Kendall and Sen statistical methods were used to test for the presence of trends and the slope of those trends in fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and volatile organic compound (VOC) ambient air concentrations. We did not determine a significant trend in 98th percentile of the daily 24-hr average PM2.5 concentrations. We did determine significant negative trends in the annual average of the daily 24-hr average PM2.5 concentrations at 6 of the 9 locations. Episodic, multi-day duration elevated PM2.5 concentrations related to forest fires were a significant influence on PM2.5 ambient concentrations. Annual 4th highest daily maximum 8-hr average O3 concentrations showed no trend at 14 of 18 locations, declined at 3 locations, and increased at one location. We determined statistically significant declines in peak and average NO2 and SO2 concentrations, and in time-integrated annual VOC concentrations.

Air Quality and Health Impacts of Onshore Oil and Gas Flaring and Venting Activities Estimated Using Refined Satellite-Based Emissions.

Emissions from flaring and venting (FV) in oil and gas (O&G) production are difficult to quantify due to their intermittent activities and lack of adequate monitoring and reporting. Given their potentially significant contribution to total emissions from the O&G sector in the United States, we estimate emissions from FV using Visible Infrared Imaging Radiometer Suite satellite observations and state/local reported data on flared gas volume. These refined estimates are higher than those reported in the National Emission Inventory: by up to 15 times for fine particulate matter (PM2.5), two times for sulfur dioxides, and 22% higher for nitrogen oxides (NOx). Annual average contributions of FV to ozone (O3), NO2, and PM2.5 in the conterminous U.S. (CONUS) are less than 0.15%, but significant contributions of up to 60% are found in O&G fields with FV. FV contributions are higher in winter than in summer months for O3 and PM2.5; an inverse behavior is found for NO2. Nitrate aerosol contributions to PM2.5 are highest in the Denver basin whereas in the Permian and Bakken basins, sulfate and elemental carbon aerosols are the major contributors. Over four simulated months in 2016 for the entire CONUS, FV contributes 210 additional instances of exceedances to the daily maximum 8-hr average O3 and has negligible contributions to exceedance of NO2 and PM2.5, given the current form of the national ambient air quality standards. FV emissions are found to cause over $7.4 billion in health damages, 710 premature deaths, and 73,000 asthma exacerbations among children annually.

Assessment of the Ambient Air Quality of Sangli City, Maharashtra, vis-à-vis National Ambient Air Quality Standards (NAAQS)

Assessment of ambient air quality is important to formulate short-term and long-term plans to mitigate air pollution. This study attempts to present an ambient air quality assessment for Sangli City, located at 16.85° N, and 74.58° E. The assessment is done through ambient air quality data measured over three ambient air quality monitoring stations located in residential, commercial, and industrial zones of Sangli City. The data was collected from 2009 to 2017 under the National Air Quality Monitoring Program of the Central Pollution Control Board (CPCB), India. The observed concentrations of gaseous pollutants, SO2 and NOx, and respirable particulate matter are compared with the concentration levels prescribed by the National Ambient Air Quality Standards (NAAQS) in 2009. The concentration levels of particulate matter are quite on the higher side of the prescribed standards. The levels of NOx are almost approaching the prescribed values, whereas SO2 levels are well within the margin. We have also studied seasonal variations in the pollutants during the study period. In general, the air quality in Sangli City is quite undesirable during the mid-winter to mid-summer period. The study is useful for common men to increase awareness. It also forms baseline data and is useful for local and central government to design appropriate strategies to apply corrective measures, protect health, and promote environmental protection.

Causes of Summer Ozone Pollution Events in Jinan, East China: Local Photochemical Formation or Regional Transport?

Simultaneous measurements of atmospheric volatile organic compounds (VOCs), conventional gases and meteorological parameters were performed at an urban site in Jinan, East China, in June 2021 to explore the formation and evolution mechanisms of summertime ozone (O3) pollution events. O3 Episode Ⅰ, O3 Episode II, and non-O3 episodes were identified based on the China Ambient Air Quality Standards and the differences in precursor concentrations. The O3 concentrations in Episode I and Episode II were 145.4 μg/m3 and 166.4 μg/m3, respectively, which were significantly higher than that in non-O3 episode (90 μg/m3). For O3 precursors, VOCs and NOx concentrations increased by 48% and 34% in Episode I, and decreased by 21% and 27% in Episode II compared to non-O3 episode days. The analysis of the m,p-xylene to ethylbenzene ratio (X/E) and OH exposure demonstrated that the aging of the air masses in Episode II was significantly higher than the other two episodes, and the differences could not be explained by localized photochemical consumption. Therefore, we speculate that the high O3 concentrations in Episode II were driven by the regional transport of O3 and its precursors. Backward trajectory simulations indicated that the air masses during Episode II were concentrated from the south. In contrast, the combination of high precursor concentrations and favorable meteorological conditions (high temperatures and low humidity) led to an excess of O3 in Episode I. Positive matrix factorization (PMF) model results indicated that increased emissions from combustion and gasoline vehicle exhausts contributed to the elevated concentrations of VOCs in Episode I, and solvent usage may be an important contributor to O3 formation. The results of this study emphasize the importance of strengthening regional joint control of O3 and its precursors with neighboring cities, especially in the south, which is crucial for Jinan to mitigate O3 pollution.

Estimation of hourly one square kilometer fine particulate matter concentration over Thailand using aerosol optical depth

In the recent years, concentration of fine particulate matter that are 2.5 microns or less in diameter (PM2.5) in Thailand has consistently exceeded the national ambient air quality standard. Currently, the measurement of PM2.5 concentration relies on air quality monitoring stations operated by the Pollution Control Department of Thailand (PCD). However, these stations are insufficient, particularly in rural areas, where agricultural open burning are major sources of pollution after harvesting period. This study aims to enhance the monitoring of PM2.5 concentration by leveraging cost-effective technologies. We propose the integration of satellite data, specifically Aerosol Optical Depth (AOD) from Multi-Angle Atmospheric Correction (MAIAC) product and Himawari-8 satellites, with the Weather Research and Forecasting Model (WRF) data, to provide supplementary data to the ground-based monitoring. Hourly 5 × 5 km2 AOD data from Himawari-8 were downscaled to a high-resolution of 1 × 1 km2, leveraging the AOD distribution pattern of the concurrent MAIAC product using eXtreme Gradient Boosting (XGBoost) model. Notably, during Thailand’s rainy season (May to August), the study observed a relative reduction in the training model’s R-square value. This phenomenon is attributed to temporal discrepancies between Himawari-8 and the MAIAC products during this period. The predictive models of PM2.5 concentrations with the identification of pertinent variables through Pearson’s correlation analysis and recursive feature elimination, driven by the robust XGBoost model. Subsequently, the downscaled AOD, wind speed, temperature, and pressure were identified as predictors for the estimation of hourly PM2.5 concentration. This comprehensive approach enabled the projection of PM2.5 levels across Thailand, encompassing over 600,000 grids at 1 × 1 km2 resolution. The developed models, thus, offer a valuable tool for robust and high-resolution PM2.5 concentration estimation, presenting significant implications for air quality monitoring and management in Thailand.

Health risk analysis of air pollutant exposure on children’s lung function in industrial area of Bandung Regency

Industrial areas are considered to have a higher risk of air pollution impact, especially for children living close to the industry, as children breathe in more air per body weight unit than adults. This study aims to analyse the risk of exposure to ambient pollutants (PM2.5, PM10, NO2, CO, SO2, and O3) in children and factors that affect lung function disorders. This study was based in the Dayeuhkolot sub-district of Bandung Regency. A cross-sectional study was conducted on school-aged children (9-12 years old) living in an industrial close to Bandung Regency. Parents or guardians were asked to complete a questionnaire on respiratory symptoms to estimate the exposure to ambient air pollutants risk. Air pollutants (PM2.5, PM10, NO2, CO, SO2, and O3) were measured using a portable Air Quality Monitoring System (AQMS), the lung function was measured by Spirometer MSA99, and non-cancer risk (HQ) was determined using the human health risk assessment model. The average results of ambient air pollutants measurement concentration are PM2.5 (45,59 ± 15,48 µg/m3), PM10 (75,56 ±25,93 µg/m3), SO2 (9,39 ± 6,27 µg/m3), CO (17,38±6,35 µg/m3), O3 (12,58 ± 3,12 µg/m3) and NO2 (15,86 ± 3,39 µg/m3). All pollutants concentrations are still below ambient air quality standards of PP NO.22/2021. With an average non-carcinogen Health Index (HI) of 0,48 ± 0,29. A lung function of total of 35 children were collected, with an average FVC: 1,59 L and FEV1.0: 1,42 L; there were 17 children with restrictive, 5 children with obstructive, and 1 combined lung disorder. The most significant factors of respiratory disorders were gender, height, respiratory complaint, and passive smoking symptoms (p &lt; 0.05).

Impacts of anthropogenic emissions and meteorology on spring ozone differences in San Antonio, Texas between 2017 and 2021

San Antonio has been designated as ozone nonattainment under the current National Ambient Air Quality Standards (NAAQS). Ozone events in the city typically occur in two peaks, characterized by a pronounced spring peak followed by a late summer peak. Despite higher ozone levels, the spring peak has received less attention than the summer peak. To address this research gap, we used the Weather Research and Forecasting (WRF)-driven GEOS-Chem (WRF-GC) model to simulate San Antonio's ozone changes in the spring month of May from 2017 to 2021 and quantified the respective contributions from changes in anthropogenic emissions and meteorology. In addition to modeling, observations from the San Antonio Field Studies (SAFS), the Texas Commission on Environmental Quality (TCEQ) Continuous Ambient Monitoring Stations (CAMS), and the spaceborne TROPOspheric Monitoring Instrument (TROPOMI) are used to examine and validate changes in ozone and precursors. Results show that the simulated daytime mean surface ozone in May 2021 is 3.8 ± 0.6 ppbv lower than in May 2017, which is slightly less than the observed average differences of −5.3 ppbv at CAMS sites. The model predicted that the anthropogenic emission-induced changes contribute to a 1.4 ± 0.5 ppbv reduction in daytime ozone levels, while the meteorology-induced changes account for a 2.4 ± 0.6 ppbv reduction over 2017–2021. This suggests that meteorology plays a relatively more important role than anthropogenic emissions in explaining the spring ozone differences between the two years. We additionally identified (1) reduced NO2 and HCHO concentrations as chemical reasons, and (2) lower temperature, higher humidity, increased wind speed, and a stronger Bermuda High as meteorological reasons for lower ozone levels in 2021 compared to 2017. The quantification of the different roles of meteorology and ozone precursor concentrations helps understand the cause and variation of ozone changes in San Antonio over recent years.

New ambient air quality standards, human capital flow, and economic growth: Evidence from an environmental information disclosure policy in China

The significance of environmental quality for the movement of human capital and economic development is growing. This study utilizes the difference-in-difference (DID) approach to analyze the effects of the implementation of new ambient air quality standards (NAAQS) on economic development and investigate its underlying mechanism. The research indicates that the NAAQS promotes urban economic growth, and this impact tends to progressively intensify over time. According to the analysis of the mechanism, the NAAQS had a significant impact on the city's human capital, which in turn contributed to economic growth. The analysis of heterogeneity indicates that the NAAQS promotes economic growth primarily in the eastern region, in large and medium-sized cities, and in cities where the government pays more attention to environmental protection. This study offers a new explanation for how environmental information disclosure (EID) promotes economic growth and provides policy enlightenment for local governments on how to increase talent inflow.

Impact of ambient air pollution and socio-environmental factors on the health of children younger than 5 years in India: a population-based analysis

Ambient air pollution and household environmental factors affect child health, particularly in low-income and middle-income countries. This study aimed to investigate the association between ambient air pollution (PM2·5) levels, socio-environmental factors (including household wealth, housing quality measures, smoking status), and the occurrence of respiratory illness in Indian children. In this retrospective and observational study, we analysed data from India's National Family Health Survey (NFHS-5, 2019-2021) combined with NASA's Global Annual PM2·5 Grids database. Bivariate and multivariable generalized additive models were employed to examine associations between key social-environmental factors and respiratory illness in children younger than 5 years. We analysed data from 224,214 children younger than 5 years, representing 165,561 families from 29,757 geographic clusters. Our results showed extremely high annual PM2·5 levels throughout India (median 63·4·g/m3, IQR 41·9-81·6), with higher exposure for rural and impoverished families. In bivariate analyses, PM2·5 was significantly associated with reported respiratory illness (p<0·001). Using generalized additive models and after accounting for key social and environmental factors, a monotonic increasing and non-linear relationship was observed between PM2·5 and respiratory illness (p<0·001), with increased likelihood of illness observed even at values near and below India's National Ambient Air Quality Standards of 40μg/m3. The study highlights the significant association of social-environmental conditions with health outcomes among young children in India. Efforts specifically targeting ambient air pollution and child health during monsoon season could have significant health benefits among this population and help achieve the goal of ending preventable deaths of children younger than 5 years. National Institutes of Health (NIH T-32-HL139443-3).