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Air pollution is known to be one of the major risk factors for premature morbidity and mortality globally, which are preventable. Therefore, the public is informed about air pollution through the Air Quality Index (AQI). The AQI represents integrated data of selected pollutants and produces a combined overall index for specific locations and time. The AQI algorithm generates a range of numbers and categories of colors that indicate likely health risks from air pollutants and the public's actions to minimize the risks. However, it lacks emerging evidence on chemical toxicity or composition. Hence, policymakers may also consider addinga toxicity matrix of fine particles to refine the algorithm, such as oxidative potential. Further, the risk is commonly communicated in numbers and not in color as dictated by the AQI. The AQI values and categories vary significantly between countries for the same pollution concentration, leading to confusion. Hence, we recommend developing a universal AQI (UAQI) with a consistent relationship between colors, concentrations, and toxicity to communicate air pollution risks to the public. Further, communication media should be encouraged to use universal color-coding rather than AQI values, i.e., numbers. Therefore, a global policy framework for regulatory authorities and policymakers is needed to communicate air pollution risk information consistently and to minimize public health exposure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Near real-time monitoring of major air pollutants, i.e., particulate matter (PM 10 , PM 2.5 , PM 1 ), trace gases (O 3 , CO, NO, NO 2 , NO x , NH 3 , CO 2 , SO 2 ) and Volatile Organic Compounds (VOCs: benzene, ethylbenzene, m-, p-xylene, o-xylene and toluene) along with climatological parameters was done in eight-cities field campaigns during the rabi (wheat) crop residue burning period in the northwest of Indo-Gangetic Plain (IGP) region. The phase-wise monitoring was done at eight locations representing rural, semi-urban and urban backgrounds. During the whole campaign, the semi-urban site (Sirsa) observed the highest average concentration of PM 10 (226 ± 111 μg m -3 ) and PM 2.5 (91 ± 67 μg m -3 ). The urban site (Chandigarh) reported the minimum concentrations of all the three size fractions of particulate matter with PM 10 as 89 ± 54 μg m -3 , PM 2.5 as 42 ± 22 μg m -3 and PM 1 as 20 ± 13 μg m -3 where the monitoring was done in the early phase of the campaign. The highest VOC concentration was recorded at the semi-urban (Sirsa) site, whereas the lowest was at a rural location (Fatehgarh Sahib). NH 3 concentration was observed highest in rural sites (31.7 ± 29.8 ppbv), which can be due to the application of fertilizers in agricultural activities. Visible Infrared Imaging Radiometer Suite (VIIRS) based fire and thermal anomalies, along with HYSPLIT back trajectory analysis, show that major air masses over monitoring sites (22 %-70 %) were from the rabi crop residue burning regions. The characteristic ratios and Principal component analysis (PCA) results show that diverse sources, i.e., emissions from crop residue burning, solid biomass fuels, vehicles and industries, majorly degrade the regional air quality. This multi-city study observed that semi-urban regions have the most compromised air quality during the rabi crop residue burning and need attention to address the air quality issues in the IGP region., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R 2 = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R 2 = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Air pollution has emerged as a leading global health risk in recent decades, where its health impacts are primarily focused on urban areas. In India, semi-urban and rural areas are also emerging as air pollution hotspots. As these regions are out of focus, the current study monitored air pollution (PM 2.5 ) at a rural district of Punjab in North India and attempted to study the associated health impacts. Hospital data of outpatient department (OPD), inpatient department (IPD) and all-cause mortality was correlated with change in PM 2.5 concentrations. PM 2.5 concentrations showed seasonal variations having relatively higher concentrations during post-monsoon and winter seasons. This rise in air pollution (annual average 92 µg/m 3 ) was found to be mainly due to crop residue burning, including local meteorology. In comparison, hospital data shows that hospital visits and admissions were higher during monsoon. This shows that hospital admissions could not be directly linked to air pollution in rural areas as other factors such as short days during winters and self-medication, socio-economic factors and dependency on local unauthorised traditional healers may influence. The application of the AirQ + model for short-term health effects reveals that out of 2582 total deaths, preventable deaths ranging from 246 (WHO guidelines value - 10 µg/m 3 ) to 159 (Indian NAAQS - 40 µg/m 3 ) could be ascribed to air pollution exposure and specifically PM 2.5 . However, these deaths are avoidable by developing strategies to minimise air pollution in rural areas. Hence, a comprehensive approach is needed to plan air pollution reduction strategies, including urban, semi-urban and rural areas., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The COVID-19 lockdown resulted in improved air quality in many cities across the world. With the objective of what could be the new learning from the COVID-19 pandemic and subsequent lockdowns for better air quality and human health, a critical synthesis of the available evidence concerning air pollution reduction, the population at risk and natural versus anthropogenic emissions was conducted. Can the new societal norms adopted during pandemics, such as the use of face cover, awareness regarding respiratory hand hygiene, and physical distancing, help in reducing disease burden in the future? The use of masks will be more socially acceptable during the high air pollution episodes in lower and middle-income countries, which could help to reduce air pollution exposure. Although post-pandemic, some air pollution reduction strategies may be affected, such as car-pooling and the use of mass transit systems for commuting to avoid exposure to airborne infections like coronavirus. However, promoting non-motorized modes of transportation such as cycling and walking within cities as currently being enabled in Europe and other countries could overshadow such losses. This demand focus on increasing walkability in a town for all ages and populations, including for a differently-abled community. The study highlighted that for better health and sustainability there. is also a need to promote other measures such as work-from-home, technological infrastructure, the extension of smart cities, and the use of information technology., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The seasonal burning of crop residue significantly affects the environment, leading to poor air quality over Indo-Gangetic Plain (IGP) in India. Hence, there have been significant efforts to minimize crop residue burning through policy, innovations, and awareness measures. However, an abrupt increase in paddy residue burning was observed over IGP during 2020. Hence, the study explores the factors leading to this sharp rise. The business as usual trends analysis revealed that paddy crop residue burning activities increased significantly (60%) in 2020 compared to the previous year. The massive increase in crop residue burning consequently seems to be linked with the COVID-19 pandemic, which affected the farmer's income, including the poor compliance by the regulatory authorities. The study also highlights the issues and prospects for sustainable crop residue management and explores the solutions to minimize crop residue burning. There are few crops in India that have guaranteed minimum sale price and are also subsidized. These provisions encourage farmers to grow those particular crops, resulting in the generation of large amounts of crop residue from these specific crops. There have been several efforts by the Indian government, including based on recent court intervention. Still, there is no respite from burning activities and the occurrence of Delhi winter smog every year. Hence, the study emphasizes a need to adopt integrated approaches having in situ eco-friendly solutions, which enhances the farmer's income and focuses on employability, capacity building, awareness generation, and in situ economically viable solutions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In India, Indo-Gangetic Plains (IGP) is becoming the hotspot of air pollution due to increasing anthropogenic activities such as rapid industrial growth, infrastructure development, transportation activities, and seasonal practice of crop residue burning. In the current study, seasonal variation in ambient air quality for 14 parameters, i.e., particulate matter (PM), trace gases, and volatile organic compounds (VOCs), along with meteorological parameters, was studied in 21 districts of the Haryana state for year 2019, situated in IGP. To analyze spatial variation of pollutants, ambient air quality data of 23 continuous ambient air quality monitoring stations were divided into three zones based on ecology and cropping pattern. All the zones showed annual mean PM 10 and PM 2.5 concentrations much higher than national ambient air quality standards. Annual mean PM 10 concentration (±standard deviation) in Zones-1, 2, and 3 was 156±86, 174±93, and 143±74 μg m -3 , whereas for PM 2.5 was 71±44, 85±54, and 78±47 μg m -3 . The results showed a considerable seasonal variation in the concentration of all pollutants. Most of the pollutants peak in the post-monsoon season, followed by winters in which crop residue burning predominates in many parts of the Haryana. PM 10 concentrations increased by 65-112% and PM 2.5 concentrations increased by 131-147% in the post-monsoon season compared to monsoons. The post-monsoon season showed the highest concentration of PM 10 , NO, and toluene (Zone-1); and PM 2.5 , NH 3 , CO, and benzene (Zone-2); whereas in winters, SO 2 (Zone-1); ethylbenzene, m,p-xylene, and xylene (Zone-2); and NO 2 and NOx (Zone-3) showed the maximum pollution levels. The O 3 concentration was highest in the pre-monsoon season (Zone-1). The satellite-based fire counts and PCA results show a significant influence of crop residue burning in the post-monsoon season and solid biomass burning in winters on Haryana's air quality. The study could help to understand seasonal variation in ambient air quality and the influence of factors such as crop residue burning in the IGP region, which could help to formulate season-specific control measures to improve regional air quality., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The emissions from agricultural activities significantly impact the air quality at local (rural) and regional scales. The study monitored the near real-time concentrations of emission from agrarian activities, i.e., particulate matter (PM 10 , PM 2.5 , PM 1 ), traces gases and VOCs, along with meteorological parameters in a rural area of Indo-Gangetic Plains (IGP). As different agricultural activities take place simultaneously in the region, sampling period was divided into three phases based on regional agricultural activities as HB (harvesting-burning) period, BTS (burning-tillage-sowing) period and PFS (pesticide-fertilizer spray) period. The highest mean concentration (± standard deviation) of particulate matter, i.e., PM 10, PM 2.5, PM 1 was observed during HB period as 151.0 ± 52.3, 94.7 ± 32.9 and 41.0 ± 16.3 μgm -3 followed by PFS as 121.7 ± 49.1, 87.8 ± 35.5 and 39.7 ± 15.7 μgm -3 and BTS period as 92.5 ± 38.8, 63.5 ± 28.4, 26.6 ± 10.9 μgm -3 respectively. The mean concentration of NO (8.4 ± 3.4 ppb), SO 2 (5.8 ± 1.2 ppb), CO (0.9 ± 0.3 ppm), O 3 (12.5 ± 3.3 ppb) was also highest during harvesting-burning period. In the burning-tillage-sowing period, the mean concentration of NO 2 (31.0 ± 2.9 ppb), benzene (2.8 ± 0.6 μgm -3 ) and o-xylene (2.1 ± 0.3 μgm -3 ) were highest. The data of crop residue burning fires showed that during HB period, around 34,683 active fires were there in the region (state of Punjab), whereas, in studied district, the number of fire counts were 635. During the HB period, around 70% of the air masses were originated within a 500 km area, whereas during the BTS and PFS period, 75% and 86% of air masses were originated from 500 km region, respectively. The ratio of PM 2.5 /PM 10 during study period ranged from 0.63 to 0.72 and was observed highest during PFS period. The current study investigated the influence of agricultural activities on air quality during post-monsoon season in a rural area of Indo-Gangetic Plains to understand the impact of these activities on air quality in the region and plan mitigation strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Sustained use and adoption of clean cooking fuels have become an important concern for developing countries due to the enormous burden of diseases attributable to household air pollution (HAP). The transition and adoption of clean household energy involve various socio-economic, behavioral, and technological barriers at different community levels. Hence, the present paper aims to scrutinize the factors, key determinants, and other interventions among rural households that limit clean cookstoves' sustained uses. The study proposes an integrated model to enhance clean cooking fuel uptake and uses based on the available evidence. The health, climate and environmental factors were identified as the key to trigger the adoption of clean cooking fuel alternatives. The model comprises the integration of components for targeted clean fuel policy interventions and promotes green recovery. The elements include Knowledge, Housing characteristics, Awareness, Interventions, Willingness to pay, Adoption, Lower emissions and Gender Equality (THE KHAIWAL model) to ascertain the intervention focus regions. Integration of model components in policy implementation will promote clean household energy to reduce emissions, leading to improve quality of life, good health, women empowerment, better air quality and climate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Air pollution affects not only the air quality in megacities but also in medium and small-sized cities due to rapid urbanization, industrialization, and other anthropogenic activities. From October 28, 2015 to November 3, 2015, the Indo-Gangetic Plains region, including Chandigarh encountered an episode of poor visibility during the daytime. The daily average PM 2.5 concentration reached 191 μg/m 3, and visibility reduced by ∼2.2 times in the Chandigarh region. PM 2.5 concentration was found around 4 times higher than a non-haze day and more than 3 times higher than National Ambient Air Quality Standards for 24 h. A significant correlation between PM 2.5 and CO (r: 0.87) during the haze period indicated similarity in their emission sources; which was attributed to the burning of solid organic matter. Further, satellite data and back-trajectory analysis of air masses showed large-scale rice stubble burning in the agricultural fields, adjoining to the city areas. The transboundary movement of air masses below 500 m and meteorological conditions played a major role in building the pollution load in the Chandigarh region. Moreover, the enhanced concentration of biomass burning tracers, i.e., organic carbon (∼3.8 times) and K + ions (2∼ times) in PM 2.5 and acetonitrile (∼2.3 times) in ambient air was observed during the haze event. The study demonstrates how regional emissions and meteorological conditions can affect the air quality in a city; which can be useful for proper planning and mitigation policies to minimize high air pollution episodes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The impact of restrictions during various phases of COVID-19 lockdown on daily mean PM 2.5 concentration in five Indian megacities (New Delhi, Chennai, Kolkata, Mumbai, and Hyderabad) was studied. The impact was studied for pre-lockdown (1st Mar-24th Mar 2020), lockdown (25th Mar-31st May 2020), and unlocking (1st Jun-31st Aug 2020) phases. The lockdown period comprises 4 lockdown phases with distinct measures, whereas the unlocking period had 3 phases. PM 2.5 concentration reduced significantly in all megacities and met the national standards during the lockdown period. The maximum reduction in PM 2.5 level was observed in Kolkata (62%), followed by Mumbai (49%), Chennai (34%), and New Delhi (26%) during the lockdown period. Comparatively, Hyderabad exhibited a smaller reduction in PM 2.5 concentration, i.e., 10%. The average PM 2.5 levels during the lockdown in the peak hour (i.e., 07:00-11:00 h) in New Delhi, Chennai, Kolkata, Mumbai, and Hyderabad decreased by 21.3%, 48.5%, 63.4%, 56.4%, and 23.8%, respectively, compared to those before lockdown period. During the unlocking period, except for Chennai, all megacities showed a reduction in average PM 2.5 levels compared to concentrations in the lockdown period, but these reductions were mainly linked with monsoon rains in India. The current study provided an opportunity to study air pollution in the absence of major anthropogenic activities and during limited activities in monsoon season having an ecological design. The study reports a new baseline of PM 2.5 , except for monsoon, and explores this knowledge to plan future air pollution reduction strategies. The study also discusses how this new learning of knowledge could strengthen air pollution control policies for better air quality and sustainability.Graphical abstract.

Background: Congenital malformations are considered as one of the significant causes of preterm as well as neonatal morbidity and mortality. Literature suggests the association of diverse congenital deformities with maternal exposure to air pollutants. However, the evidence is still inconclusive on the manifestation of these during pregnancy. Thus, systematic review was done on the available epidemiological studies studying the effect of air pollutants on congenital malformations. Furthermore, the meta-analysis was conducted for several combinations of air pollutants and congenital defects., Methods: Twenty six epidemiological studies were extracted from the databases and examined for association of risk of congenital defects with air pollutant concentrations. Metaanalysis was done if the risk estimates of the same anomaly and pollutant group were reported in at least three studies., Results: Each study reported a statistically significant increased risk of congenital malformation with some air pollutant, amid the several tested combinations. Our meta-analysis reported that nitrogen dioxide and PM 2.5 were associated with the risk of pulmonary valve stenosis with OR = 1.74 and OR = 1.42 respectively. The risk of developing tetralogy of Fallot (TOF) was observed to be associated with PM 2.5 with OR = 1.52 . SO 2 exposure was related to a high risk of the ventricular septal defect (VSD) with OR = 1.15 and orofacial defects (OR = 1.27)., Conclusion: It is evidenced that ambient air pollutants have some effect on congenital malformations. Standard case definitions, improved methods of exposure, and better control of confounders will improve future research in this area., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The variation in ambient air quality during COVID-19 lockdown was studied in Chandigarh, located in the Indo-Gangetic plain of India. Total 14 air pollutants, including particulate matter (PM 10 , PM 2.5 ), trace gases (NO 2 , NO, NO x , SO 2 , O 3 , NH 3 , CO) and VOC's (benzene, toluene, o-xylene, m,p-xylene, ethylbenzene) were examined along with meteorological parameters. The study duration was divided into four parts, i.e., a) 21 days of before lockdown b) 21 days of the first phase of lockdown c) 19 days of the second phase of lockdown d) 14 days of the third phase of lockdown. The results showed significant reductions during the first and second phases for all pollutants. However, concentrations increased during the third phase. The concentrations of SO 2 , O 3, and m,p-xylene kept on increasing throughout the study period, except for benzene, which continuously decreased. The percentage decrease in the concentrations during consecutive periods of lockdown were 28.8%, 23.4% and 1.1% for PM 2.5 and 36.8%, 22.8% and 2.4% for PM 10 respectively. The Principal Component Analysis (PCA) and characteristic ratios identified vehicular pollution as a primary source during different phases of lockdown. During the lockdown, residential sources showed a significant adverse impact on the air quality of the city. Regional atmospheric transfer of pollutants from coal-burning and stubble burning were identified as secondary sources of air pollution. The findings of the study offer the potential to plan air pollution reduction strategies in the extreme pollution episodes such as during crop residue burning period over Indo-Gangetic plain., Competing Interests: Declaration of competing interest Authors confirm that there’s no financial/personal interest or belief that could affect the objectivity. All authors read the paper and approved it., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Emissions from the crop residue burning adversely affect the regional and global air quality including public health. In this study, a district-wise comprehensive emission inventory of key pollutants (PM 2.5 , PM 10 , CO, CO 2 , SO 2 , NOx, N 2 O, NH 3 , CH 4 , NMVOC, EC, OC, PAH) emitted during primary crop residue burning was developed using activity data for the major agrarian states of north India for the agricultural year 2017-18. The emissions were scaled to the spatial resolution of 1 km grid to study the spatial distribution of crop residue burning activities using VIIRS Thermal anomalies datasets. An estimated 20.3 Mt and 9.6 Mt of crop residue were burned in Punjab and Haryana, resulting in an emission of 137.2 Gg and 56.9 Gg of PM 2.5 and 163.7 Gg and 72.1 of PM 10 Gg for respective states. The emissions of EC, OC, and PAHs were 8.6 Gg, 45.7 Gg, and 0.08 Gg in Punjab, whereas in Haryana emissions were 3.7 Gg, 17.7 Gg, and 0.03 Gg, respectively. The results show that rice and wheat crops were major contributor to residue burnt at the field (>90%) leading to the high load of atmospheric emissions in the IGP region. Further, CO 2 equivalent greenhouse gas emissions were 34.8 Tg and 17.3 Tg for Punjab and Haryana, respectively. Around 30000 and 8500 active fires were detected by VIIRS over the agricultural area of Punjab and Haryana during the studied year. The GIS-based bottom-up approach using gridded emission inventory shows pollutant distribution dominates over the south-western part of Punjab and north-western region of Haryana. The proximity of these regions to Delhi and transboundary movement of emissions towards Indo-Gangetic plains causes high air pollution episodes. The high-resolution inventory of various pollutants will be useful for regional air quality models to better predict and manage the hotspot of air pollution., Competing Interests: Declaration of competing interest Authors confirm that there’s no financial/personal interest or belief that could affect the objectivity. All authors read the paper and approved it., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM 2.5 and PM 10 ) and gaseous pollutants (NO 2 , O 3 , CO, and SO 2 ) during lockdown (25 th March - 3 rd May 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM 2.5 , PM 10 , NO 2, and CO has been found in all the regions during the lockdown. SO 2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O 3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM 2.5 , PM 10, and NO 2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O 3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O 3 has increased over IGP due to less O 3 loss. The most significant reduction (∼40-60%) was found in PM 2.5 and PM 10 . The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO 2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM 2.5 , PM 10 , NO 2, and enhancement in O 3 was proportional to the population density. Delhi's air quality has improved with a significant reduction in primary pollutants, however, an increase in O 3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Many illnesses have been attributed to the exposure of solid biomass smoke but the effect on intelligence has largely been unexplored. The study aims to examine the effect of exposure to solid biomass smoke during the first 3 years of life on intelligence among 6-8-year-old children. Children aged 6-8 years were enrolled from a primary school and their houses were visited to collect data on socio-economic status and household exposure assessment. Households using LPG as cooking fuel were considered as the unexposed group. All the children were tested for their Intelligence Quotient (IQ) using Malin's Intelligence Scale for Indian Children (MISIC). The mean IQ was calculated as the average of Verbal and Performance score. Potential confounders were adjusted using multivariate general linear model. About 45% of children had average or above-average IQ while the rest had below-average IQ. The mean scores for the arithmetic component of IQ were found to be significantly lower among solid biomass fuel users as compared to LPG users after adjusting for confounders. The mean IQ of LPG users were 5.58 points higher (95% CI: 0.46-10.1) for the arithmetic component as compared to solid biomass users. Children living in the houses using solid biomass fuel for cooking have lower IQ as compared to the children living in the houses using LPG for cooking for arithmetic component even after adjusting for potential confounders., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Advances in statistical analysis in the last few decades in the area of linear models enhanced the capability of researchers to study environmental procedures. In relation to general linear models; generalized linear models (GLM) provide greater flexibility in analyzing data related to non-normal distributions. Considering this, the current review explains various applications of the generalized additive model (GAM) to link air pollution, climatic variability with adverse health outcomes. The review examines the application of GAM within the varied field, focusing on the environment and meteorological data. Further, advantages and complications of applying GAM to environmental data are also discussed. Application of GAM allowed for specification for the error pattern and found to be an appropriate fit for the data sets having non-normal distributions; this results in lower and more reliable p-values. Since most environmental data is non-normal, GAM provides a more effective analytical method than traditional linear models. This review highlights on ambient air pollutants, climate change, and health by evaluating studies related to GAM. Additionally, an insight into the application of GAM in R software is provided, which is open source software with the extensive application for any type of dataset., (Copyright © 2019. Published by Elsevier Ltd.)

Considering the mounting evidences of the effects of air pollution on health, the present study was undertaken to assess the ambient air quality status in the fast growing urban centres of Haryana state, India. The samples were collected for total suspended particulate matter (TSPM), respirable suspended particulate matter (PM(10)), sulfur dioxide (SO(2)), and oxides of nitrogen (NO(2)) during different seasons from 8 districts of Haryana during January, 1999 to September, 2000. The four types of sampling sites with different anthropogenic activities i.e. residential, sensitive, commercial and industrial were identified in each city. The ambient air concentration of TSPM and PM(10) observed was well above the prescribed standards at almost all the sites. The average ambient air concentrations of SO(2) and NO(2) were found below the permissible limits at all the centres. Comparatively higher concentration of SO(2) was observed during winter seasons, which seems to be related with the enhanced combustion of fuel for space heating and relatively stable atmospheric conditions. Air Quality Index (AQI) prepared for these cities shows that residential, sensitive and commercial areas were moderately to severely polluted which is a cause of concern for the residents of these cities. The high levels of TSPM and SO(2) especially in winter are of major health concern because of their synergistic action. The data from Hisar city reveals a significant increase in the total number of hospital visits/admissions of the patients with acute respiratory diseases during winter season when the level of air pollutants was high.

Landfilling is one of the most common ways of municipal solid waste disposal. Degradation of organic waste produces CH(4) and other landfill gases that significantly contribute to global warming. However, before entering the atmosphere, part of the produced CH(4) can be oxidised while passing through the landfill cover. In the present study, the oxidation rate of CH(4) was studied with various types of compost as possible landfill cover. The influence of incubation time, moisture content and temperature on the CH(4) oxidation capacity of different types of compost was examined. It was observed that the influence of moisture content and temperature on methane oxidation is time-dependent. Maximum oxidation rates were observed at moisture contents ranging from 45% to 110% (dry weight basis), while the optimum temperature ranged from 15 to 30 degrees C.

Several studies highlight the environmental and human health impacts of outdoor air pollution. However, a significant gap exists in understanding indoor air pollution in urban households. The current work aims to characterize the fan dust samples collected from households in Chandigarh, India. The five composite samples were collected from different areas, including the dining room, drawing room, bedroom, kitchen, and worship room, of different households in the same location. Samples were characterized using various analytical techniques like X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). The concentration of all the measured elements was found to be relatively lower when compared with other similar studies. Ca and Fe showed a high household fraction. XRD confirmed the high fraction of calcite and quartz particles in household dust samples. In SEM analysis, circular, irregular flakes and fibrous particles indicated coal combustion particles in the household dust. Additionally, sharp edge particles showed the enrichment of minerals in the dust samples. Health risk assessment results indicated that the hazard index values for children and adult populations were within limits for non-carcinogenic and carcinogenic health risks from three exposure pathways, revealing insignificant health risks. Besides, the microbiological examination identifies Paebacillus barcinonensis and Bacillus megaterium in dining room dust, Bacillus megaterium and Bacillus circulans in dining and drawing room dust, Lysinibacillus boronitolerans in Bedroom dust, Paenibacillus species. and Bacillus species. in worship room dust, Bacillus circulance and Bacillus megaterium in the kitchen area. Human activities were strongly found to be associated with microbial and metal existence in the dust samples. Household dust, contaminated with biological and inorganic pollutants, has the potential to pose health risks to occupants. Hence, the study briefly discusses the approaches to minimize household dust and indoor air pollutants. Therefore, improving indoor air quality should be a vital component of public health protection policies for urban and rural households. [ABSTRACT FROM AUTHOR]

PM2.5 is one of the major contributors to air pollution in India, resulting in poor air quality and human health issues. The current study explores the applicability of TTAinterfaceTrendAnalysis (an 'R' language-based Graphical User Interface package) in estimating the annual and month-wise trends in PM2.5 over five Indian megacities (New Delhi, Kolkata, Mumbai, Hyderabad, and Chennai). The package offers a one-stop solution for various statistical analyses such as data imputation, outlier detection, trend analysis, data smoothing, diagnostic tests, etc. The trends are estimated using seven (2014–2020) years of PM2.5 data. All estimated month-wise trends of PM2.5 over the study cities were found to be statistically non-significant. Annual trends (both with and without applying data smoothing techniques) were found to be statistically significant with magnitudes ranging between − 0.27 and − 5.2 µg m−3 y−1 (negative sign indicates a declining trend). Autocorrelation analysis and normality tests are also conducted using the inbuilt options of TTAinterfaceTrendAnalysis. Results obtained are thoroughly discussed and compared with those of similar contemporary studies. To our knowledge, the current study is the first to apply TTAinterfaceTrendAnalysis for quantifying long-term trends in PM2.5. The sensitivity of the trend estimates due to the inclusion of COVID-19 lockdown PM2.5 data was also examined. The net impact of lockdown on the PM2.5 long-term trend ranged between − 0.13 and 2.29 µg m−3 y−1 across the study cities. [ABSTRACT FROM AUTHOR]

Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 µg m−3 in 6–10 October to up to 500 µg m−3 on 5–9 November, which subsequently decreased to about 100 µg m−3 in 20–30 November. Two distinct plumes of PM2.5 over 500 µg m−3 are tracked from crop residue burning in Punjab to Delhi NCR on 2–3 November and 10–11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales. [ABSTRACT FROM AUTHOR]

The impact of increasing air pollution on human health and the environment is a major concern worldwide. Exposure to air pollution is one of the leading risk factors and substantially contributes to morbidity and premature mortality. This review paper aims to examine the exposure of major air pollutants (i.e., particulate matter, sulfur dioxide, oxides of nitrogen, carbon monoxide) and its association with respiratory, cardiovascular, reproductive, and genotoxic adverse health outcomes that can cause DNA damage leading to genetic mutations. The study emphasized how a better understanding of source-receptor relationships and exposure assessment methodologies can support effective air quality management planning. Hence, there is a need to augment various exposure indicators (spatial modeling, personal/area monitoring, emphasizing central/rural site measurements, etc.) to generate reliable surrogates for informed decision-making. The critical drivers of anthropogenic interference for air pollution remain urbanization, growing vehicle use, and industrialization. This requires innovative approaches, such as energy-efficient and technologically sustainable solutions to gradually replace conventional fossil fuel from primary energy mix with renewable energy. It holds the key to meet future energy challenges and minimizing air pollution emissions. Further, there is an urgent need to frame effective public policy with graded mitigation actions to reduce the adverse impact of air pollution on human health and the environment. [ABSTRACT FROM AUTHOR]

Both poor water, sanitation, hygiene (WaSH) and household air pollution (HAP) adversely affect the health of millions of people each year around the globe and specifically in developing countries. The objective of current work is to highlight the importance of HAP in parallel to WaSH for decision making to achieve better health specially in developing countries. There are examples, where developing countries are strengthening efforts to tackle the issue of poor water and sanitation such as ‘Clean India Mission’ was recently launched by the Government of India. However, there is lack of actions to address the issue related to HAP—to extend the coverage of clean fuel, efficient stoves and ventilated kitchens to the deprived population under the ‘Clean India Mission’. Most of the rural household and urban slums in developing countries have only a single room, where people cook and sleep. This leads them to exposure to toxic HAP, which can be minimized by developing country specific indoor air quality guidelines and action framework. Hence, there should be policies to provide them not only the subsidy for clean fuel but also to build properly ventilated kitchens along with the promotion of clean toilets and water supplies. There is a need to strengthen global efforts, to jointly address the challenges associated with the risks related to WaSH and HAP in order to efficiently reduce the global burden of disease. Further, this will also help to timely attain the sustainable development goals for better health and environment. [ABSTRACT FROM AUTHOR]

The increase in number of vehicles in metropolitan cities has resulted in increase of greenhouse gas (GHG) emissions in urban environment. In this study, emission load of GHGs (CO, NO, CO) from Chandigarh road transport sector has been estimated using Vehicular Air Pollution Inventory (VAPI) model, which uses emission factors prevalent in Indian cities. Contribution of 2-wheelers (2-w), 3-wheelers (3-w), cars, buses, and heavy commercial vehicles (HCVs) to CO, NO, CO, and total GHG emissions was calculated. Potential for GHG mitigation through clean development mechanism (CDM) in transport sector of Chandigarh under two scenarios, i.e., business as usual (BAU) and best estimate scenario (BES) using VAPI model, has been explored. A major contribution of GHG load (~ 50%) in Chandigarh was from four-wheelers until 2011; however, it shows a declining trend after 2011 until 2020. The estimated GHG emission from motor vehicles in Chandigarh has increased more than two times from 1065 Gg in 2005 to 2486 Gg by 2011 and is expected to increase to 4014 Gg by 2020 under BAU scenario. Under BES scenario, 30% of private transport has been transformed to public transport; GHG load was possibly reduced by 520 Gg. An increase of 173 Gg in GHGs load is projected from additional scenario (ADS) in Chandigarh city if all the diesel buses are transformed to CNG buses by 2020. Current study also offers potential for other cities to plan better GHG reduction strategies in transport sector to reduce their climate change impacts. [ABSTRACT FROM AUTHOR]

Exposure to household air pollutants has become a leading environmental health risk in developing countries. Considering this, real-time temporal variation in fine particulate matter (PM 2.5 ) and carbon monoxide (CO) concentrations were measured in various types of rural household kitchens. Observed average concentrations of PM 2.5 , CO, percent relative humidity (%RH) and temperature (T) in five different kitchen types were 549.6 μg/m 3 , 4.2 ppm, 70.2% and 20 °C respectively. Highest CO and PM 2.5 concentration were found in household performing cooking in indoor kitchens (CO: 9.3 ppm; PM 2.5 : 696.5 μg/m 3 ) followed by outdoor kitchens (CO: 5.8 ppm; PM 2.5 : 539.5 μg/m 3 ). The concentration of PM 2.5 and CO varied according to the fuel type and highest concentration was observed in kitchens using cowdung cakes followed by agricultural residue > firewood > biogas > Liquefied Petroleum Gas (LPG). Results revealed that the pollutants concentration varied with kitchen type, fuel type and the location of kitchen. An exposure index was developed to calculate the exposure of cook, non-cook and children below 5 years. Analysis of exposure index values shows that cooks, who use solid biomass fuel (SBF) in indoor kitchen, are four times more exposed to the harmful pollutants than the cooks using clean fuel. Further, using indoor PM 2.5 concentrations, hazard quotient was calculated based on evaluation of intake concentration and toxicological risk, which also shows that SBF users have higher health risks (hazard quotient > 1) than the clean fuel (LPG) users. [ABSTRACT FROM AUTHOR]

More than half of the world’s population lives in urban areas. It is estimated that by 2030 there will be 41 megacities and most of them will be located in developing countries. The megacities in India (Delhi, Mumbai, and Kolkata) collectively have >46 million inhabitants. Increasing population and prosperity results in rapid growth of the already large consumption of energy and other resources, which contributes to air pollution, among other problems. Megacity pollution outflow plumes contain high levels of criteria pollutants (e.g. Particulate matter, SO 2 , NO x ), greenhouse gases, ozone precursors and aerosols; which can affect the atmosphere not only on a local scale but also on regional and global scales. In the current study, emissions and concentration trends of criteria and other air pollutants (polycyclic aromatic hydrocarbons, carbon monoxide and greenhouse gases) were examined in the three Indian megacities. Further, various policies and control strategies adopted by Indian Government are also discussed to improve air quality. Decreasing trends of SO 2 was observed in all three megacities due to decrease in the sulfur content in coal and diesel. However, increasing trend for NO x was found in these megacities due to increase in number of vehicles registered and high flash point of CNG engines, which leads to higher NO x emission. In terms of SPM and PM 10 , highest emissions have been found at Kolkata, whereas highest ambient concentrations were recorded in Delhi. For Mumbai and Kolkata fluctuating trends of SPM concentrations were observed between 1991 and 1998 and stable afterwards till 2005; whereas for Delhi, fluctuating trend was observed for the entire study period. However, several steps have been taken to control air pollution in India but there is a need to focus on control of non-exhaust emissions including municipal solid waste and biomass burning in the megacities and surrounding areas. [ABSTRACT FROM AUTHOR]

Air pollution is an emerging public health concern as there are increasing evidences that the quality of air adversely affects human health due to the presence of various toxic pollutants. Linking air pollution from its source to adverse human health effects is a complicated phenomenon that requires a multidisciplinary approach for better understanding. Decision-makers need relevant, comprehensive estimates of the disease burden attributable to different risk factors. Many statistical models have become very relevant for estimating atmospheric concentrations by analysis of complex datasets to produce inferences and predictions that can lead to better management of air pollution. This paper focuses on the Indian scenario as a case study and presents the current status of air quality in India with special reference to particulate matter. The study suggest that air-quality networks need to be developed that can depict and forecast pollution levels with health advisories for public and for pollution emergencies measures. Development of statistical models, and methods for Big Data Analytics, can yield a wide array of actionable insights to facilitate policy decisions. Models may also be used to predict the cost of the air-pollution control measures as well as the benefits in terms of the control of acute and chronic diseases caused by air pollution. This study concludes that the application of statistical models and algorithms can act as an important tool to bridge the gap between science and policy. [ABSTRACT FROM AUTHOR]

Public transport in Delhi was amended by the Supreme Court of India to use Compressed Natural Gas (CNG) instead of diesel or petrol. After the implementation of CNG since April 2001, Delhi has the highest fraction of CNG-run public vehicles in the world and most of them were introduced within 20 months. In the present study, the concentrations of various criteria air pollutants (SPM, PM10, CO, SO2 and NOx) and organic pollutants such as benzene, toluene, xylene (BTX) and polycyclic aromatic hydrocarbons (PAHs) were assessed before and after the implementation of CNG. A decreasing trend was found for PAHs, SO2 and CO concentrations, while the NOx level was increased in comparison to those before the implementation of CNG. Further, SPM, PM10, and BTX concentrations showed no significant change after the implementation of CNG. However, the BTX concentration demonstrated a clear relation with the benzene content of gasoline. In addition to the impact of the introduction of CNG the daily variation in PAHs levels was also studied and the PAHs concentrations were observed to be relatively high between 10 pm to 6 am, which gives a proof of a relation with the limited day entry and movement of heavy vehicles in Delhi. [ABSTRACT FROM AUTHOR]

Abstract: People are exposed to air pollution from a range of indoor and outdoor sources. Concentrations of nitrogen dioxide (NO2), which is hazardous to health, can be significant in both types of environments. This paper reports on the measurement and analysis of indoor and outdoor NO2 concentrations and their comparison with measured personal exposure in various microenvironments during winter and summer seasons. Furthermore, the relationship between NO2 personal exposure in various microenvironments and including activities patterns were also studied. Personal, indoor microenvironments and outdoor measurements of NO2 levels were conducted using Palmes tubes for 60 subjects. The results showed significant differences in indoor and outdoor NO2 concentrations in winter but not for summer. In winter, indoor NO2 concentrations were found to be strongly correlated with personal exposure levels. NO2 concentration in houses using a gas cooker was higher in all rooms than those with an electric cooker during the winter campaign, whereas there was no significant difference noticed in summer. The average NO2 levels in kitchens with a gas cooker were twice as high as those with an electric cooker, with no significant difference in the summer period. A time-weighted average personal exposure was calculated and compared with measured personal exposures in various indoor microenvironments (e.g. front doors, bedroom, living room and kitchen); including non-smokers, passive smokers and smoker. The estimated results were closely correlated, but showed some underestimation of the measured personal exposures to NO2 concentrations. Interestingly, for our particular study higher NO2 personal exposure levels were found during summer (14.0±1.5) than winter (9.5±2.4). [Copyright &y& Elsevier]