Outdoor air pollution in India is not only an urban problem

Decoding temporal patterns and trends of PM10 pollution over Delhi: a multi-year analysis (2015-2022)

The current study delved into an extensive analysis of multi-year observations on PM10 to have trends at various time scales in Delhi, India. High-resolution ground observations from all 37 monitoring stations from 2015 to 2022 were used. This study used non-parametric generalized additive model (GAM) based smooth-trend and Theil-Sen slope estimator techniques to analyze temporal trends and variations. The long-term PM10 concentration, both in its ambient and de-seasonalized forms, exhibited a statistically significant decreasing trend. An average decrease of - 7.57 [95% confidence interval (CI) - 16.51, 0.18] µg m-3 year-1 for ambient PM10 and - 8.45 [95% CI - 11.96, - 5.58] µg m-3 year-1 for de-seasonalized PM10 mass concentration was observed. Breaking it down into seasons, we observed significant declines in PM10 concentrations during monsoon (- 10.71 µg m-3 year-1, p < 0.1) and post-monsoon (- 7.49 µg m-3 year-1, p < 0.001). On the other hand, summer and winter displayed statistically insignificant declining trends of - 5.32 µg m-3 year-1 and - 6.06 µg m-3 year-1, respectively. Remarkably, all months except March displayed declining PM10 concentrations, suggesting a gradual reduction in particle pollution across the city. Further analysis of PM10 across various wind sectors revealed a consistent decreasing trend in all wind directions. The most substantial decrease was observed from the northwest (- 10.24 µg m-3 year-1), while the minimum reduction occurred from the east (- 5.67 µg m-3 year-1). Throughout the 8-year study period, the daily average PM10 concentration remained at 228 ± 124 µg m-3, ranging from 33 to 819 µg m-3. Seasonal variations were apparent, with concentrations during winter, summer, monsoon, and post-monsoon seasons averaging 279 ± 133, 224 ± 117, 135 ± 95, and 323 ± 142 µg m-3, respectively. November had the highest and August had the lowest concentration. Weekend PM10 concentration is slightly lower than weekdays. These findings emphasize the need for more stringent government action plans.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 μg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 μg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 μg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 μg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

High loadings of carbonaceous aerosols from wood smoke in the atmosphere of Beijing from 2015 to 2017: Implications for energy transition policy

Recently, biomass has been regarded as a promising option for solid energy in China, which is promoted in the residential sector and firing power plants. We collected 200 PM2.5 samples (particulate matter with a aerodynamic diameter smaller than 2.5 μm) at multi-sites across Beijing from three individual sampling cases from 2015 to 2017. The levels of OC, OC fractions, EC, EC fractions, as well as K+ were measured. Then, we adopted the Positive Matrix Factorization 5.0 to apportion the sources of carbonaceous aerosols. The source apportionment results were compared with the estimates of source contribution using the bottom-up technical method with the latest emission inventories after the Action Plan was put into effect in 2013. Our results demonstrate that high pollution of carbonaceous aerosols originated from wood smoking based on the receptor modeling and bottom-up technical method in Beijing from 2015 to 2017. Future energy transition policy should focus on the technologies and regulations for reducing emissions from renewable biomass fuel combustion. This study highlights the importance of regulations that address emissions controls on fuels replacing coal combustion to meet the needs to mitigate air pollution from primary energy use.

Association between sea-land breeze and particulate matter in five coastal urban locations in India

Particulate matter less than 2.5 μm particle diameter (PM2.5) is the most significant environmental issue globally. PM2.5 is an integral component of air quality monitoring and management, human health, weather, climate, and epidemiological research. In this work, we investigate the seasonal variation in PM2.5 mass concentrations and the association between the sea-land breeze system and particulate matter in five coastal urban locations in India (Kolkata, Visakhapatnam, Chennai, Thiruvananthapuram, and Mumbai). The relative occurrence of high PM2.5 mass concentrations was the greatest during the winter season (December through February) while the relative occurrence of low PM2.5 mass concentrations was the greatest during the monsoon season (June through September). Amongst locations, Kolkata experiences the highest PM2.5 loading in winter while Thiruvananthapuram experiences the lowest PM2.5 loading in monsoon. Indo-Gangetic Plain (IGP) outflow onto the Bay of Bengal significantly impacts locations along the eastern coast of India with reduced impact from north (Kolkata) to south (Chennai). The sea-breeze component analysis revealed daily cycles of the sea-land breeze with varying magnitudes of the breeze between the different seasons. Overall, we found a negative association between the sea-land breeze magnitude and PM2.5 mass concentrations, implying that the weakened sea-land breeze may deteriorate air quality in coastal locations due to poor ventilation. The vertical profiles of aerosol extinction showed elevated aerosol layers within 1 km from the surface in almost all locations. The decreasing trend in the land-sea temperature contrast in coastal locations is expected to deteriorate air quality in coastal locations in the warming future. Nevertheless, critical analyses using ground-based remote sensing techniques are required for a better understanding the impact of sea-land breeze dynamics on air quality in coastal locations.

The interplay between air pollution, built environment, and physical activity: Perceptions of children and youth in rural and urban India

The role of physical inactivity as a contributor to non-communicable disease risk in children and youth is widely recognized. Air pollution and the built environment can limit participation in physical activity and exacerbate non-communicable disease risk; however, the relationships between perceptions of air pollution, built environment, and health behaviours are not fully understood, particularly among children and youth in low and middle-income countries. Currently, there are no studies capturing how child and youth perceptions of air pollution and built environment are associated with physical activity in India, thus, this study investigated the association between perceived air pollution and built environment on moderate-to-vigorous physical activity (MVPA) levels of Indian children and youth. Online surveys captured MVPA, perception of air pollution as a problem, built environment factors, as well as relevant sociodemographic characteristics from parents and children aged 5-17 years in partnership with 41 schools across 28 urban and rural locations during the Coronavirus disease lockdowns in 2021. After adjusting for age, gender, and location, a significant association was found between the perception of air pollution as a problem and MVPA levels (β = -18.365, p < 0.001). Similarly, the perception of a high crime rate was associated with lower MVPA levels (β = -23.383, p = 0.002). Reporting the presence of zebra crossings, pedestrian signals, or attractive natural sightings were associated with higher MVPA levels; however, this association varied across sociodemographic groups. These findings emphasize the importance of addressing air pollution and improving the built environment to facilitate outdoor active living, including active transportation, among children and youth - solutions that are particularly relevant not only for preventing non-communicable disease risk but also for climate change mitigation.

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

Background

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.

Methods

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.

Findings

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 40 μg/m3.

Interpretation

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.

Funding

National Institutes of Health (NIH T-32-HL139443-3).

Exhaust particle number and composition for diesel and gasoline passenger cars under transient driving conditions: Real-world emissions down to 1.5 nm

Recent recommendations given by WHO include systematic measurements of ambient particle number concentration and black carbon (BC) concentrations. In India and several other highly polluted areas, the air quality problems are severe and the need for air quality related information is urgent. This study focuses on particle number emissions and BC emissions of passenger cars that are technologically relevant from an Indian perspective. Particle number and BC were investigated under real-world conditions for driving cycles typical for Indian urban environments. Two mobile laboratories and advanced aerosol and trace gas instrumentation were utilized. Our study shows that passenger cars without exhaust particle filtration can emit in real-world conditions large number of particles, and especially at deceleration a significant fraction of particle number can be even in 1.5-10 nm particle sizes. The mass concentration of exhaust plume particles was dominated by BC that was emitted especially at acceleration conditions. However, exhaust particles contained also organic compounds, indicating the roles of engine oil and fuel in exhaust particle formation. In general, our study was motivated by serious Indian air quality problems, by the recognized lack of emission information related to Indian traffic, and by the recent WHO air quality guidance; our results emphasize the importance of monitoring particle number concentrations and BC also in Indian urban areas and especially in traffic environments where people can be significantly exposed to fresh exhaust emissions.

PM2.5 pollution exceeding Indian standard over a semi-urban region at eastern IGP: Chemistry, meteorological impact, and long-range transport

A year-long study (January-December 2019) on the chemical characterization and meteorological impact on PM2.5 was conducted over a semi-urban station, Shyamnagar, in the easternmost part of the Indo-Gangetic Plains (IGP). PM2.5 concentrations (Mean = 81.69 ± 66.27 μgm-3; 7.10-272.74 μgm-3), the total carbonaceous aerosols (TCA) (Mean = 22.85 ± 24.95 μgm-3; 0.77-102.97 μgm-3) along with differential carbonaceous components like organic carbon (OC) (Mean = 11.28 ± 12.48 μgm-3; 0.48-53.01 μgm-3) and elemental carbon (EC) (Mean = 4.83 ± 5.28 μgm-3; 0.1-22.13 μgm-3) exhibited prominent seasonal variability with the highest concentrations during winter, followed by post-monsoon, pre-monsoon and lowest during monsoon. A similar seasonal variation was observed for the total water-soluble ionic species (Mean = 31.91 ± 20.12 μgm-3; 0.1-126.73 μgm-3). We observed that under the least favorable conditions (low ventilation coefficient), high PM2.5 pollution (exceeding Indian standard) was associated with a high increase in secondary components of PM2.5. Eastern, central and western parts of IGP, as well as Nepal, were the major long-distant source regions whereas the northern part of West Bengal and parts of Bangladesh were the major regional source region for high PM2.5 pollution over Shyamnagar. The ratios like char-EC/soot-EC, non-sea-K+/EC and non-sea-SO42-/EC strongly indicated the dominance of fossil fuel burning over biomass burning. Compared with other studies, we observed that the PM2.5 pollution over this semi-urban region was comparable (and even higher in some cases) with other parts of IGP. The high exceedance of PM2.5 over the Indian standard in Shyamnagar strongly demands an immediate initiation of systematic and regular based air pollution monitoring over semi-urban/non-urban regions in India, especially IGP, in addition to the polluted cities.

Thermodynamical framework for effective mitigation of high aerosol loading in the Indo-Gangetic Plain during winter

The Indo-Gangetic Plain (IGP) experiences severe air pollution every winter, with ammonium chloride and ammonium nitrate as the major inorganic fractions of fine aerosols. Many past attempts to tackle air pollution in the IGP were inadequate, as they targeted a subset of the primary pollutants in an environment where the majority of the particulate matter burden is secondary in nature. Here, we provide new mechanistic insight into aerosol mitigation by integrating the ISORROPIA-II thermodynamical model with high-resolution simultaneous measurements of precursor gases and aerosols. A mathematical framework is explored to investigate the complex interaction between hydrochloric acid (HCl), nitrogen oxides (NOx), ammonia (NH3), and aerosol liquid water content (ALWC). Aerosol acidity (pH) and ALWC emerge as governing factors that modulate the gas-to-particle phase partitioning and mass loading of fine aerosols. Six "sensitivity regimes" were defined, where PM1 and PM2.5 fall in the "HCl and HNO3 sensitive regime", emphasizing that HCl and HNO3 reductions would be the most effective pathway for aerosol mitigation in the IGP, which is ammonia-rich during winter. This study provides evidence that precursor abatement for aerosol mitigation should not be based on their descending mass concentrations but instead on their sensitivity to high aerosol loading.

Energy inequality and air pollution nexus in India

Energy usage, inequality, and their impacts are deeply intertwined, especially in India. Every year, cooking using biomass-based solid fuel usage causes death to tens of thousands of Indians, specifically, economically unprivileged people. Solid fuel burning has been known as one of the prominent sources of ambient PM_2.5 (particulate matter with an aerodynamic diameter of <2.5 μm) concentration in the atmosphere. Thus, limiting the PM_2.5 emission from biomass-based cooking fuel through the transition to LPG has gained priority. The government report in India indicates that nearly 8 million households became beneficiaries of the LPG connection through the PMUY scheme till 2019. The transition to clean cooking fuel may have an influence on the ambient PM_2.5 concentration. In this study, to explore the nexus between energy inequality and air pollution, we investigated the present status of clean fuel usage in India and its drivers, including the impact of such a massive transition to cleaner fuel on ambient air quality, with a specific focus on PM_2.5. The results show an improvement of 15 % in LPG usage from 2015 to 2019 in India., Yet the majority of poorer (>60 %) and poorest communities (>90 %) still use solid biomass as the cooking fuel. No significant correlation (r = 0.036; p-value ≫ 0.05) was obtained between LPG usage and ambient PM_2.5 concentration suggesting the influence of other confounding factors which might subdue the anticipated effect of the usage of clean fuel. The analysis suggests, despite the successful launching of the PMUY, the low LPG usage pattern among the poor, because of the lack of an effective subsidy policy, might jeopardize the effort to fix the standard of ambient air as per WHO.

The effect of social determinants of health on severity of microbial keratitis presentation at a tertiary eye care hospital in Southern India

Purpose

Understanding the association between social determinants of health (SDoHs) and microbial keratitis (MK) can inform underlying risk for patients and identify risk factors associated with worse disease, such as presenting visual acuity (VA) and time to initial presentation.

Methods

This was a cross-sectional study was conducted with patients presenting with MK to the cornea clinic at a tertiary care hospital in Madurai, India. Patient demographics, SDoH survey responses, geographic pollution, and clinical features at presentation were collected. Descriptive statistics, univariate analysis, multi-variable linear regression models, and Poisson regression models were utilized.

Results

There were 51 patients evaluated. The mean age was 51.2 years (SD = 13.3); 33.3% were female and 55% did not visit a vision center (VC) prior to presenting to the clinic. The median presenting logarithm of the minimum angle of resolution (logMAR) VA was 1.1 [Snellen 20/240, inter-quartile range (IQR) = 20/80 to 20/4000]. The median time to presentation was 7 days (IQR = 4.5 to 10). The average particulate matter 2.5 (PM2.5) concentration, a measure of air pollution, for the districts from which the patients traveled was 24.3 μg/m3 (SD = 1.6). Age- and sex-adjusted linear regression and Poisson regression results showed that higher levels of PM2.5 were associated with 0.28 worse presenting logMAR VA (Snellen 2.8 lines, P = 0.002). Patients who did not visit a VC had a 100% longer time to presentation compared to those who did (incidence rate ratio = 2.0, 95% confidence interval = 1.3-3.0, P = 0.001).

Conclusion

Patient SDoH and environmental exposures can impact MK presentation. Understanding SDoH is important for public health and policy implications to mitigate eye health disparities in India.

Driving factors behind the continuous increase of long-term PM2.5-attributable health burden in India using the high-resolution global datasets from 2001 to 2020

Air pollution is the fourth leading global risk factor, whereas in India air pollution is reported as the highest risk factor with millions of premature deaths every year. Despite implementation of several air pollution control plans, PM_2.5 levels over India have not noticeably reduced. PM_2.5-associated health burdens in India have increased significantly in past decades. A fine resolution (0·01° × 0·01°) analysis of PM_2.5-attribulable premature deaths (rather than the coarse-level analysis) may elucidate the reason for this increase and inform and effective start-of-the-art state-level and national emission control strategies. This study quantified the spatiotemporal dynamics of PM_2.5-attributable premature deaths from 2001 to 2020 and applied a decomposition analysis to dissect the contribution of various associated parameters, such as PM_2.5 concentration, population distribution and disease-specific baseline death rate. Results show significant spatiotemporal variations of PM_2.5 and associated health burden in India. During the study period, population weighted PM_2.5 value increased from 46.0 to 59.5 μg/m³ and associated non-communicable death increased around 87.6 %, from 1050 [95 % (CI): 880-1210] thousand to 1970 (95 % CI: 1658-2259) thousand. The states of Uttar Pradesh, Bihar, West Bengal, Maharashtra, Rajasthan, and Madhya Pradesh had the highest PM_2.5-attributable deaths. In these states, non-accidental deaths increased from 232.1, 112.7, 81.4, 79.1, 66.3 and 58.5 thousand in 2001 to 424.1, 226.7, 156.2, 154.5, 123.3 and 119.7 thousand in 2020. In per capita population (/10⁵ population), the highest PM_2.5-attributable deaths were observed in Delhi, Uttar Pradesh, Bihar, Haryana and Punjab. Throughout the study period, demographic changes outweighed the health burden and were responsible for ~62.8 % increase of PM_2.5-related non-accidental deaths across India, whereas the change in PM_2.5 concentration influenced only 18.7 %. The change in baseline mortality rate impacts differently for the estimation of disease-specific mortality changes. Our findings suggest more dynamic and comprehensive policies at state-specific level, especially for North India is very indispensable for the overall decrease of PM_2.5-related deaths in India.

Climatology and landscape determinants of AOD, SO2 and NO2 over Indo-Gangetic Plain

Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO₂ and SO₂, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO₂ and SO₂ over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005-2019. IGP experienced an overall increment in AOD (R² = 0.63) and SO₂ (R² = 0.67) values, with LIGP (AOD, R² = 0.8 & SO₂, R² = 0.8) experiencing the largest rate of enhancement. The levels of NO₂ (R² = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R² = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO₂ value (3.82 ± 0.98 × 10¹⁵ molecules/cm²) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO₂ (3.8 ± 1.4 × 10¹⁵ molecules/cm²) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO₂ level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO₂ and NO₂, implying no pollution abatement effect on SO₂ and NO₂ pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.

A global review of the state of the evidence of household air pollution's contribution to ambient fine particulate matter and their related health impacts

Direct exposure to household fine particulate air pollution (HAP) associated with inefficient combustion of fuels (wood, charcoal, coal, crop residues, kerosene, etc.) for cooking, space-heating, and lighting is estimated to result in 2.3 (1.6-3.1) million premature yearly deaths globally. HAP emitted indoors escapes outdoors and is a leading source of outdoor ambient fine particulate air pollution (AAP) in low- and middle-income countries, often being a larger contributor than well-recognized sources including road transport, industry, coal-fired power plants, brick kilns, and construction dust. We review published scientific studies that model the contribution of HAP to AAP at global and major sub-regional scales. We describe strengths and limitations of the current state of knowledge on HAP's contribution to AAP and the related impact on public health and provide recommendations to improve these estimates. We find that HAP is a dominant source of ambient fine particulate matter (PM2.5) globally - regardless of variations in model types, configurations, and emission inventories used - that contributes approximately 20 % of total global PM2.5 exposure. There are large regional variations: in South Asia, HAP contributes ∼ 30 % of ambient PM2.5, while in high-income North America the fraction is ∼ 7 %. The median estimate indicates that the household contribution to ambient air pollution results in a substantial premature mortality burden globally of about 0.77(0.54-1) million excess deaths, in addition to the 2.3 (1.6-3.1) million deaths from direct HAP exposure. Coordinated global action is required to avert this burden.

High-Resolution PM2.5 Emissions and Associated Health Impact Inequalities in an Indian District

Health and livelihood impacts from ambient air pollution among populations in developing countries are disproportional. These disparities are often overlooked due to a lack of information on microlevel emission data, especially in smaller cities and rural areas. The current work in an Indian district, Saharanpur, proposes the use of novel data sets to estimate microlevel emissions from air-polluting infrastructure sectors in urban and rural areas for use in pollutant transport models. Health impacts estimated based on the surface PM_2.5 concentration suggest that the rate of premature deaths is 158 (95% CI: 122-163) and 143 (95% CI: 65-151) deaths per 100 000 people in urban and rural areas, respectively. Sixty-eight percent of the 6372 (95% CI: 3321-6987) annual premature deaths occurs in rural areas. Depicting higher contribution-exposure disparities among socioeconomic groups, the study observed that compared to their contribution to air pollution, low socioeconomic status (SES) groups in the region experience 6,7, 7, and 26% more premature deaths from PM_2.5 exposure for industries, household cooking fuel burning, open waste burning, and transportation, respectively. The majority of disability-adjusted life years (DALYs) in the study domain are observed in economically weaker worker categories. Reduced income due to the loss of these life years will significantly impact these groups due to their dependence on daily wages for basic life necessities. Microlevel pollution mitigation policies with a focus on these inequalities are critical for promoting environmental equity and justice.

Optimal utilization of ecological economic resources and low-carbon economic analysis from the perspective of Public Health

Introduction

China's urbanization process continues to deepen with social development, but the optimal utilization of ecological, economic resources and Public Health (PH) problems are becoming increasingly severe.

Methods

This paper analyses the optimal use of urban resources based on PH. Here, the public space of urban settlements is selected as the research object. Firstly, the connotation and essence of the ecological economy and Low-Carbon Economy (LCE) are analyzed. Secondly, the characteristics of public space in urban settlements are studied based on PH. The public space satisfaction evaluation model in urban settlements is constructed with five first-level and 12 second-level indicators. Finally, a questionnaire is designed to analyze urban households' outdoor activities and evaluate public space in settlements.

Results

The influencing factors of residents' satisfaction with public space in settlements are obtained through regression analysis. The results show that residents' satisfaction with the public space of the settlement is mainly evaluated from three aspects: the accessibility of public space, the integrity of public space, and the pleasure of public space. The influence coefficients are 0.355, 0.346, and 0.223, respectively, indicating that the influence degree of the three principal factors decreases in turn.

Conclusion

We can optimize the utilization of urban residential public space resources from the aspects of accessibility, integrity and pleasure, so as to promote residents to go to public spaces for outdoor activities and physical exercise, which is more conducive to the public health of residents.

Air quality trends in rural India: analysis of NO2 pollution using satellite measurements

India is a country with more than 67% of its population (947 million) residing in rural areas and 33% in urban areas (472 million) as of 2020. Therefore, health of the people living in rural India is very important for its future development plans, economy and growth. Here, we analyse the rural air quality using satellite measurements of NO₂ in India, as the sources of NO₂ are well connected to the industrial and economic uplift of a nation. Our analyses for the rural regions show distinct seasonal changes with the highest value (2.0 × 10¹⁵ molecules per cm²) in winter and the lowest in monsoon (1.5 × 10¹⁵ molecules per cm²) seasons. About 41% of the total NO₂ pollution in India is from its rural sources, but 59% of the urban sources were focused in the past studies. In addition, around 45% of the rural NO₂ pollution is due to road transport, whereas more than 90% of it in urban India comes from the power sector. Our assessment shows that the NO₂ exposure in rural regions is as serious as that in urban areas, indicating the need for more effective reduction of population exposure and protection of public health. Henceforth, this study reveals that rural India is gradually getting polluted from its nearby regions as well as from the new sources within. This is a big concern for the public health of the large rural population of India.

Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020

The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM2.5, and PM10). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month’s PM2.5 and temperature (lag1) had a significant association with influenza incidence, while the previous month’s temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM2.5 lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM10 and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.

The Effect of Particulate Matter Exposure During Pregnancy on Pregnancy and Child Health Outcomes in South Asia: Protocol for an Instrumental Variable Analysis

BACKGROUND

Determining the longer-term health effects of air pollution has been difficult owing to the multitude of potential confounding variables in the relationship between air pollution and health. Air pollution in many areas of South Asia is seasonal, with large spikes in particulate matter (PM) concentration occurring in the winter months. This study exploits this seasonal variation in PM concentration through a natural experiment.

OBJECTIVE

This project aims to determine the causal effect of PM exposure during pregnancy on pregnancy and child health outcomes.

METHODS

We will use an instrumental variable (IV) design whereby the estimated month of conception is our instrument for exposure to PM with a diameter less than 2.5 μm (PM2.5) during pregnancy. We will assess the plausibility of our assumption that timing of conception is exogenous with regard to our outcomes of interest and will adjust for date of monsoon onset to control for confounding variables related to harvest timing. Our outcomes are 1) birth weight, 2) pregnancy termination resulting in miscarriage, abortion, or still birth, 3) neonatal death, 4) infant death, and 5) child death. We will use data from the Demographic and Health Surveys (DHS) conducted in relevant regions of Bangladesh, India, Nepal, and Pakistan, along with monthly gridded data on PM2.5 concentration (0.1°×0.1° spatial resolution), precipitation data (0.5°×0.5° resolution), temperature data (0.5°×0.5°), and agricultural land use data (0.1°×0.1° resolution).

RESULTS

Data access to relevant DHSs was granted on June 6, 2021 for India, Nepal, Bangladesh, August 24, 2021 for Pakistan, and June 19 2022 for the latest DHS from India.

CONCLUSIONS

If the assumptions for a causal interpretation of our instrumental variable analysis are met, this analysis will provide important causal evidence on the maternal and child health effects of PM2.5 exposure during pregnancy. This evidence is important to inform personal behavior and interventions, such as the adoption of indoor air filtration during pregnancy as well as environmental and health policy.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/35249.

The Effect of Small Particulate Matter on Tourism and Related SMEs in Chiang Mai, Thailand

In northern Thailand, the problem of small particulate matter arises every year, with the primary source being agricultural-weed burning and wildfire. The tourism industry is strongly impacted and has been in the spotlight for the past few years. Thus, this study aims to investigate the effect of small particulate matter on tourism and related SMEs in Chiang Mai, Thailand. The data were collected from 286 entrepreneurs in the tourism and related SMEs sectors. The data were analyzed using data mining and association-rule techniques. The study revealed that small particulate matter has a considerable impact on customer factors, especially when the number of customers has decreased. Operational factors and product/service factors are also affected by the dust in the form of adjustments to keep the business running and the protection of the health of employees and customers. Certainly, financial factors are affected by the small particulate matter situation, both lower revenues and higher costs.

Ammonium Chloride Associated Aerosol Liquid Water Enhances Haze in Delhi, India

The interaction between water vapor and atmospheric aerosol leads to enhancement in aerosol water content, which facilitates haze development, but its concentrations, sources, and impacts remain largely unknown in polluted urban environments. Here, we show that the Indian capital, Delhi, which tops the list of polluted capital cities, also experiences the highest aerosol water yet reported worldwide. This high aerosol water promotes secondary formation of aerosols and worsens air pollution. We report that severe pollution events are commonly associated with high aerosol water which enhances light scattering and reduces visibility by 70%. Strong light scattering also suppresses the boundary layer height on winter mornings in Delhi, inhibiting dispersal of pollutants and further exacerbating morning pollution peaks. We provide evidence that ammonium chloride is the largest contributor to aerosol water in Delhi, making up 40% on average, and we highlight that regulation of chlorine-containing precursors should be considered in mitigation strategies.

Nocturnal Atmospheric Oxidative Processes in the Indo-Gangetic Plain and Their Variation During the COVID-19 Lockdowns

This study investigates selected secondary atmospheric responses to the widely reported emission change attributed to COVID-19 lockdowns in the highly polluted Indo-Gangetic Plain (IGP) using ground-based measurements of trace gases and particulate matter. We used a chemical box-model to show that production of nighttime oxidant, NO₃, was affected mainly by emission decrease (average nighttime production rates 1.2, 0.8 and 1.5 ppbv hr^-1 before, during and relaxation of lockdown restrictions, respectively), while NO₃ sinks were sensitive to both emission reduction and seasonal variations. We have also shown that the maximum potential mixing ratio of nitryl chloride, a photolytic chlorine radical source which has not been previously considered in the IGP, is as high as 5.5 ppbv at this inland site, resulting from strong nitrate radical production and a potentially large particulate chloride mass. This analysis suggests that air quality measurement campaigns and modeling explicitly consider heterogeneous nitrogen oxide and halogen chemistry.

Urban greenery for air pollution control: a meta-analysis of current practice, progress, and challenges

Most governmental initiatives in India, to leash down urban air pollution, have yielded little results till date, largely due to purely technocratic vision, which is shrouded by technological, economic, social, institutional, and political hardships. We present this reflective article on urban greenery, as a proposition to urban authorities (e.g., pollution regulators, environmental systems' managers, urban landscape planners, environmental policy makers), shift from purely technocratic way of thinking to thinking with nature, by strategic greening of urban spaces, for long-term air pollution prevention and control measures. To that end, we offer a meta-analysis of recent (post 2005) global literature using four-stage PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach. We open the narrative by briefing about main pollutant filtration mechanisms by trees, followed by cognitive aspects of species selection (e.g., deciduous vs. evergreen, air pollution tolerance index, environmental stressors). Till date, most Indian studies on urban greenery mostly but focused on physiological aspects of trees. Here, we draw attention of urban authorities to an equally compelling, but yet less explored, aspect: design criteria, with reference to two most common urban configurations, namely, street canyon and open road. With pictorial depictions, we enumerate various categories of street canyons and discuss aspect ratio (building height to street width) and various wind flow regimes (isolated roughness, wake interface, and skimming), that the urban authorities should be cognizant about to maximize pollutant removal efficiency. For open road, we discuss vegetation barriers, with special emphasis on canopy porosity/density functions. In the final sections, we reflect on a potential systems' thinking approach for on-ground implementation, comprising of revamping of urban forestry programs, research and development, community mobilization and stakeholder engagement, and strategic outreach. In addition, we emphasize on means to harness co-benefits of urban greenery, beyond mere pollutant removal, to garner support from urban residents' communities. Last but not the least, we also caution the urban authorities about the undesirable outcomes of urban greenery that will require more process-level research.

PM2.5 Concentration Exposure over the Belt and Road Region from 2000 to 2020

Ambient fine particulate matter (PM_2.5) can cause respiratory and heart diseases, which have a great negative impact on human health. While, as a fast-developing region, the Belt and Road (B&R) has suffered serious air pollution, more detailed information has not been revealed. This study aims to investigate the evolutionary relationships between PM_2.5 air pollution and its population-weighted exposure level (PWEL) over the B&R based on satellite-derived PM_2.5 concentration and to identify the key regions for exposure control in the future. For this, the study focused on the B&R region, covering 51 countries, ranging from developed to least developed levels, extensively evaluated the different development levels of PM_2.5 concentrations during 2000–2020 by spatial-temporal trend analysis and bivariate spatial correlation, then identified the key regions with high risk under different levels of Air Quality Guidelines (AQG). Results show that the overall PM_2.5 and PWEL of PM_2.5 concentration remained stable. Developing countries presented with the heaviest PM_2.5 pollution and highest value of PWEL of PM_2.5 concentration, while least developed countries presented with the fastest increase of both PM_2.5 and PWEL of PM_2.5 concentration. Areas with a high level and rapid increase PWEL of PM_2.5 concentration were mainly located in the developing countries of India, Bangladesh, Nepal, and Pakistan, the developed country of Saudi Arabia, and least developed countries of Yemen and Myanmar. The key regions at high risk were mainly on the Indian Peninsula, Arabian Peninsula, coastal area of the Persian Gulf, northwestern China, and North China Plain. The findings of this research would be beneficial to identify the spatial distributions of PM_2.5 concentration exposure and offer suggestions for formulating policies for the prevention and control PM_2.5 air pollution at regional scale by the governments.

High resolution vehicular exhaust and non-exhaust emission analysis of urban-rural district of India

Air quality deterioration due to vehicular emissions in smaller Indian cities and rural areas remains unacknowledged, even though the situation is alarmingly similar to megacities. The resulting lack of knowledge on travel behavior and vehicle characteristics impacts accuracy of emission studies in these regions. This study uses a novel approach and appropriate primary and secondary data sets to allocate vehicular activities (vehicle population and vehicle kilometer travelled) and associated emissions at a high spatial resolution for estimation and dispersion analysis of vehicular exhaust and non-exhaust PM_2.5 emission in an Indian urban-rural landscape. The study indicates that using approaches that do not allocate vehicles kilometers travelled to areas of their expected travel results in underestimating the percent share of PM_2.5 emissions from rural roads and motorways while overestimating overall PM_2.5 emissions. Particulate matter resuspension is the dominant form of PM_2.5 emissions from the vehicular sector on all road types, constituting an even higher fraction on rural roads. Two-wheelers contribute a high fraction of PM_2.5 emissions (exhaust and non-exhaust combined), followed by heavy commercial vehicles and four-wheelers on urban roads. Light commercial vehicles, especially agricultural tractors dominate these emissions on rural roads. PM_2.5 hotspots are prevalent in urban areas, but several rural areas also experience heavy particulate matter concentrations. Thus, vehicle movement incorporation results in more accurate emission estimation, especially in an urban-rural landscape.

Mechanisms and Pathways for Coordinated Control of Fine Particulate Matter and Ozone

PURPOSE OF REVIEW

Fine particulate matter (PM_2.5) and ground-level ozone (O₃) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM_2.5 and O₃ are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM_2.5 and O₃.

RECENT FINDINGS

Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O₃ and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM_2.5; however, O₃ was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O₃ to NO _x . Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions.

SUMMARY

Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

Association between ambient air pollutants and meteorological factors with SARS-CoV-2 transmission and mortality in India: an exploratory study

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic poses a serious public health concern worldwide. Certain regions of the globe were severely affected in terms of prevalence and mortality than other. Although the cause for this pattern is not clearly understood, lessons learned from previous epidemics and emerging evidences suggest the major role of ecological factors like ambient air pollutants (AAP) and meteorological parameters in increased COVID-19 incidence. The present study aimed to understand the impact of these factors on SARS-CoV-2 transmission and their associated mortality in major cities of India.

METHODS

This study used secondary AAP, meteorological and COVID-19 data from official websites for the period January-November 2020, which were divided into Pre-lockdown (January-March 2020), Phase I (April to June 2020) and Phase II (July to November 2020) in India. After comprehensive screening, five major cities that includes 48 CPCB monitoring stations collecting daily data of ambient temperature, particulate matter PM_2.5 and ₁₀ were analysed. Spearman and Kendall's rank correlation test was performed to understand the association between SARS-CoV-2 transmission and AAP and, meteorological variables. Similarly, case fatality rate (CFR) was determined to compute the correlation between AAP and COVID-19 related morality.

RESULTS

The level of air pollutants in major cities were significantly reduced during Phase I compared to Pre-lock down and increased upon Phase II in all the cities. During the Phase II in Delhi, the strong significant positive correlation was observed between the AAP and SARS-CoV-2 transmission. However, in Bengaluru, Hyderabad, Kolkata and Mumbai AAP levels were moderate and no correlation was noticed. The relation between AT and SARS-CoV-2 transmission was inconclusive as both positive and negative correlation observed. In addition, Delhi and Kolkata showed a positive association between long-term exposure to the AAP and COVID-19 CFR.

CONCLUSION

Our findings support the hypothesis that the particulate matter upon exceeding the satisfactory level serves as an important cofactor in increasing the risk of SARS-CoV-2 transmission and related mortality. These findings would help public health experts to understand the SARS-CoV-2 transmission against ecological variables in India and provides supporting evidence to healthcare policymakers and government agencies for formulating strategies to combat the COVID-19.

Season-wise analyses of VOCs, hydroxyl radicals and ozone formation chemistry over north-west India reveal isoprene and acetaldehyde as the most potent ozone precursors throughout the year

The north-west Indo-Gangetic Plain is the agricultural cereal-basket of India owing to its prolific wheat and rice production. Surface ozone pollution is of growing concern over it, yet no detailed year-round in-situ measurements of its most reactive precursors, particularly the volatile organic compounds (VOCs) are available from this region. Here, using the first year-long continuous measurements of 23 major VOCs, ozone, NO_x, CO and their atmospheric oxidation products from a regionally representative site in north-west India, we evaluated speciated OH reactivities (OHR), ozone formation potential (OFP) and ozone production regimes (OPR) across all seasons. The average seasonal OHR ranged from 14 s^-1 (winter) to 21.5 s^-1 (summer). We provide the first estimate of OH radical mixing ratios varying between 0.06 and 0.37 ppt in different seasons for the peak daytime hours in this region. Recycling via HO₂+NO was the most important pathway contributing to >85% of the OH production throughout the year. Contrary to satellite derived proxies and chemical transport models which predict NO_x sensitive OPR, we show it to be strongly sensitive to both VOCs and NO_x (>90% days in a year). Remarkably for densely populated regions, isoprene and acetaldehyde collectively accounted for ~30-50% of the total OFP in all seasons. Biogenic emissions of isoprene (reaching 12.9 mg/m²/h) and high acetaldehyde from anthropogenic and photochemical sources were observed for all seasons. Monitoring and control of isoprene and acetaldehyde are therefore urgently required for efforts focused on mitigating surface ozone pollution in this demographically important region of the world.

Assessment of PM10 and PM2.5 over Ghaziabad, an industrial city in the Indo-Gangetic Plain: spatio-temporal variability and associated health effects

This study examined the PM₁₀ and PM_2.5 concentration, associated mortality, and transport pathways in Ghaziabad which is an industrial city in the Indo-Gangetic Plain. To achieve this, PM (both PM₁₀ and PM_2.5) and meteorological parameters were measured from June 2018 to May 2019 at 2 locations and analyzed together with data from a 3rd location in Ghaziabad. The highest daily average PM₁₀ and PM_2.5 concentrations were ~ 1000 µg m^-3 and ~ 450 µg m^-3, respectively. At each of the three locations, the annual mean PM₁₀ concentrations were ~ 260 ± 150 µg m^-3 while the PM_2.5 concentrations were 140 ± 90 µg m^-3. Nonparametric Spearman rank correlation analysis between meteorological parameters and PM concentrations indicated that ventilation coefficient was anti-correlated with PM concentration during the post-monsoon and winter seasons (the most polluted seasons) with rank correlation values of approximately - 0.50. Multiple linear regression (MLR) revealed that the variability in local meteorological parameters account for ~ 50% variability (maximum) in PM₁₀ mass during the monsoon and PM_2.5 during the post-monsoon season. For long-range sources, cluster and concentrated weighted trajectory (CWT) analyses utilizing regional meteorology showed the impact of transported PM from sources in Arabian sea through western India in monsoon and from parts of South Asia through Northwestern IGP and neighboring cities in Uttar Pradesh in other seasons. Finally, mortality estimates show that the number of deaths attributable to ambient PM_2.5 in Ghaziabad were ~ 873 per million individuals which was ~ 70% higher than Delhi.

Urban-rural differences in the association between long-term exposure to ambient air pollution and obesity in China

INTRODUCTION

Ambient air pollution might increase the risk of obesity; however, the evidence regarding the relationship between air pollution and obesity in comparable urban and rural areas is limited. Therefore, our aim was to contrast the effect estimates of varying air pollution particulate matter on obesity between urban and rural areas.

METHODS

Four obesity indicators were evaluated in this study, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Exposure to ambient air pollution (e.g., particulate matter with aerodynamic diameters 1.0 μm [PM₁], PM_2.5, and PM₁₀) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between air pollution particulate matter and obesity. Furthermore, the effect estimates of different air pollution particulates were contrasted between urban and rural areas.

RESULTS

A total of 36,998 participants in urban areas and 31, 256 in rural areas were included. We found positive associations between long-term exposure to PM₁, PM_2.5, and PM₁₀ and obesity. Of these air pollutants, PM_2.5 had the strongest association. The results showed that the odds ratios (ORs) for general obesity were 1.8 (95% CI, 1.64 to 1.98) per interquartile range (IQR) μg/m³ increase in PM₁, 1.89 (95% CI, 1.71 to 2.1) per IQR μg/m³ increase in PM_2.5, and 1.74 (95% CI, 1.58 to 1.9) per IQR μg/m³ increase in PM₁₀. The concentrations of air pollutants were lower in rural areas, but the effects of air pollution on obesity of rural residents were higher than those of urban residents.

CONCLUSION

Long-term (3 years average) exposure to ambient air pollution was associated with an increased risk of obesity. We observed regional disparities in the effects of particulate matter exposure from air pollution on the risk of obesity, with higher effect estimates found in rural areas. Air quality interventions should be prioritized not only in urban areas but also in rural areas to reduce the risk of obesity.