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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.)

Pollen, climatic variables and air pollutants coexist in nature with the potential to interact with one another and play a crucial role in increasing allergic diseases. The current study evaluates the influence of meteorological parameters and air pollutants on the airborne pollen in an urban city, Chandigarh, situated in the Indo-Gangetic Plains. Airborne pollen monitoring was done following Spanish Aerobiological Network guidelines and dynamics of daily total pollen and six most abundant taxa were studied from June 2018 to June 2020. Among meteorological parameters, temperature and wind were the most correlated and influential parameters to airborne pollen concentration. Annual Pollen Integral (APIn) of Cannabis sativa (r = 0.52), Parthenium hysterophorus (r = 0.27), Poaceae (r = 0.32) and total pollen concentration (r = 0.30) showed a statistically significant positive correlation with temperature. In contrast, precipitation and relative humidity negatively correlated with APIn of total pollen concentration, Eucalyptus sp. and Poaceae except for Parthenium hysterophorus and Celtis occidentalis. Similar results were found with Seasonal Pollen Integral (SPIn) of total pollen concentration, six major taxa and meteorological variables. Spearman correlation performed for NOx showed a significant positive correlation among APIn and SPIn of Celtis occidentalis and insignificant among APIn and SPIn of Eucalyptus sp. and Morus alba. In contrast, except for Eucalyptus sp., PM 10 and PM 2.5 were negatively correlated among APIn and SPIn of total pollen concentration and other major taxa. Spearman's correlation of APIn and SPIn for each pollen taxon, meteorological parameters and air pollutants suggests that each taxon has a different pattern in response to all parameters. The study findings suggest that pollen response must be examined at the taxon level, not the assemblage level, having long time-series data. This will help to compute future scenarios of changing environmental factors and comprehend the relationships and trends among meteorology, air pollutants and aerobiology., 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.)

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.)

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.)

Columnar Aerosol Optical Depths (AOD) over an urban area (Chandigarh) and a rural area (Khera, Fatehgarh Sahib district) situated in the Indo-Gangetic Plains (IGP) of India were analysed to study their temporal heterogeneity in terms of interannual, seasonal and monthly variations. Over the last few decades, IGP has become one of the global hotspots of air pollution due to the increased anthropogenic activities such as traffic, industries, agricultural waste burning etc. Level-2 AODs (550 nm) were retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard NASA's Terra and Aqua satellites, for a period of 14 years (2005-2018). The climatological mean Terra-MODIS (Aqua-MODIS) AOD over the urban location was ~0.497 ± 0.238 (0.474 ± 0.228), whereas over the rural location it was 0.542 ± 0.269 (0.534 ± 0.282). Linear trend analysis estimated an increase in annual mean Terra-MODIS (Aqua-MODIS) AOD at a rate of ~0.009 (0.013) per year over the urban site; whereas over the rural location the rate of increase was ~0.003 (0.004) per year. Results show that the observed increase is ~1.49% (2.41%) of climatological mean AOD over the urban location for Terra-MODIS (Aqua-MODIS), whereas, over the rural location, it was ~0.50% (0.67%). Using the HYSPLIT trajectory model, it was concluded that, during post-monsoon, the observed high AODs can be related to massive crop residue burning in the IGP region. These AOD trends can also be used to track the regional anthropogenic air-pollution changes. An empirical relation between AOD and PM 10 was established, which can be used to estimate PM 10 over the urban and rural areas of IGP (using MODIS AODs), complementing the sparse ground-based monitoring. Further, satellite-based air pollution data can be used for baseline assessment and understanding the impact of control policies such as National Clean Air Programme and to support formulate evidence-based pollution control 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 © 2020 Elsevier B.V. All rights reserved.)

The long-term trend of air pollutants was studied in Chandigarh, located in Indo-Gangetic Plains of India. The SPM, PM 10 , NO x, and SO 2 depict site-specific variation having different anthropogenic activities. The results indicate that PM 10 levels in Chandigarh remain higher than the prescribed annual ambient air quality standards (60 μg m -3 ) of India. Seasonal Kendall test indicates a declining trend of PM 10 for the year 2003 to 2018 at an industrial and commercial site (1996-2016). There is a significant increase in NOx levels at all locations except at commercial sites. The results of the linear regression model and Theil-Sen slope show that SPM is declining at all locations, but results are not statistically significant. Interestingly, PM 10 levels at the industrial site display a significant declining trend (1.3% year -1 ). Similarly, NOx levels are increasing at all sites but having a statistically significant trend at a rural location (8.9% year -1 ) and residential site (15.2% year -1 ). Air pollutants show strong seasonal variability having a higher concentration in post-monsoon and winter season, which found to be linked with regional anthropogenic activities such as crop residue burning and use of solid biomass fuel for cooking and other purposes. Lowest PM 10 levels were observed during the monsoon and having a decline of 47.4-66.4% as compared to winter levels. Site-specific variations in air pollutants were found to be associated with air quality improvement policies such as shifting of an interstate bus terminal, ban on diesel autos, including strict implementation of air quality norms on industries. As the relative contribution of various pollution sources is still unknown, the seasonal pattern of pollutants will help in knowing the background concentration of pollutants and could help to formulate evidence-based policies to mitigate air pollution under National Clean Air Programme (NCAP)., (Copyright © 2020. Published by Elsevier B.V.)

Exposure to particulate matter (PM) from traffic can cause adverse health risks. Recent studies project an increase in non-exhaust emissions in the future despite a reduction in exhaust emissions. While there is a lot of research on exhaust emissions, the challenges remain to quantify non-exhaust emissions, especially in developing countries. In this work, an approach has been developed, and on-road vehicular non-exhaust PM emissions are estimated due to brake wear, tyre wear, road wear and resuspension, at very high resolution (100 m 2 ) over an Indian megacity Delhi. Further, the relative contribution of non-exhaust emissions to the total vehicular emission was also calculated. The total PM10 emissions in megacity Delhi were 31.5 Gg/year, which is mainly dominated by the non-exhaust sources. The non-exhaust emissions were found to be six times (86%) of the exhaust emission (14%). The highest contribution to the total vehicular PM emission comes from the cars (34%) followed by buses (23%) and heavy commercial vehicles (HCVs, 17%), which is dominated by resuspension of dust. Cars and buses contribute less to exhaust emissions and more to non-exhaust emissions. Majors roads are the largest contributors to the total emissions in Delhi. The emissions from HCVs, diesel cars along with the other diesel vehicles result in diesel vehicles contributing more than the petrol vehicles to both exhaust and non-exhaust emissions. As India target to reduce PM pollution under the national clean air program, the current study will be useful to plan a suitable intervention to mitigate air pollution and associated health impacts., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Air pollutants emissions due to the burning of crop residues could adversely affect human health, environment, and climate. Hence, a multicity campaign was conducted during crop residue burning period in Indo Gangetic Plains (IGP) to study the impact on ambient air quality. Seventeen air pollutants along with five meteorological parameters, were measured using state of the art continuous air quality monitors. The average concentration of PM 10 , PM 2.5, and PM 1 during the whole campaign were 196.7±30.6, 148.2±20, and 51.2±8.9 μgm -3 and daily average concentration were found several times higher than national ambient air quality standards for 24h. Amritsar had the highest average concentration of PM 2.5 (178.4±83.8 μgm -3 ) followed by Rohtak and Sonipat (158.4±79.8, 156.5±105.3μgm -3 ), whereas Chandigarh recorded the lowest concentration (112.3±6.9μgm -3 ). The concentration of gaseous pollutants NO, NO 2 , NO x, and SO 2 were also observed highest at Amritsar location, i.e., 6.6±2.6ppb, 6.2±0.7ppb, 12.7±3.0ppb, and 7.5±3.3ppb respectively. The highest average O 3 and CO were 22.5±19.3ppb and 1.5±1.2ppm during the campaign. The level of gaseous pollutants and Volatile organic compounds (VOCs) found to be elevated during the campaign, which can play an important role in the formation of secondary air pollutants. The correlation of meteorology and air pollutants was also studied, and O 3 shows a significant relation with temperature and UV (R=0.87 and 0.74) whereas VOCs shows a significant correlation with temperature (R=-0.21 to -0.47). Air quality data was also analyzed to identify sources of emissions using principal component analysis, and it identifies biomass burning and vehicular activities as major sources of air pollution., (Copyright © 2018. Published by Elsevier B.V.)

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 549.6μg/m 3 , 4.2ppm, 70.2% and 20°C respectively. Highest CO and PM 2.5 concentration were found in household performing cooking in indoor kitchens (CO: 9.3ppm; PM 2.5 : 696.5μg/m 3 ) followed by outdoor kitchens (CO: 5.8ppm; PM 2.5 : 539.5μg/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 5years. 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., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Noise pollution in hospitals is recognized as a serious health hazard. Considering this, the current study aimed to map the noise pollution levels and to explore the self reported non-auditory effects of noise in a tertiary medical institute. The study was conducted in an 1800-bedded tertiary hospital where 27 sites (outdoor, indoor, road side and residential areas) were monitored for exposure to noise using Sound Level Meter for 24h. A detailed noise survey was also conducted around the sampling sites using a structured questionnaire to understand the opinion of the public regarding the impact of noise on their daily lives. The equivalent sound pressure level (Leq) was found higher than the permissible limits at all the sites both during daytime and night. The maximum equivalent sound pressure level (Lmax) during the day was observed higher (>80dB) at the emergency and around the main entrance of the hospital campus. Almost all the respondents (97%) regarded traffic as the major source of noise. About three-fourths (74%) reported irritation with loud noise whereas 40% of respondents reported headache due to noise. Less than one-third of respondents (29%) reported loss of sleep due to noise and 8% reported hypertension, which could be related to the disturbance caused due to noise. Noise levels in and around the hospital was well above the permissible standards. The recent Global Burden of Disease highlights the increasing risk of non communicable diseases. The non-auditory effects studied in the current work add to the risk factors associated with non communicable diseases. Hence, there is need to address the issue of noise pollution and associated health risks specially for vulnerable population., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

There has been a significant increase in municipal solid waste (MSW) generation in India during the last few decades and its management has become a major issue because the poor waste management practices affect the health and amenity of the cities. In the present study, various physico-chemical parameters of the MSW were analyzed to characterize the waste dumped at Gazipur landfill site in Delhi, India, which shows that it contains a high fraction of degradable organic components. The decomposition of organic components produces methane, a significant contributor to global warming. Based on the waste composition, waste age and the total amount dumped, a first-order decay model (FOD) was applied to estimate the methane generation potential of the Gazipur landfill site, which yields an estimate of 15.3 Gg/year. This value accounts to about 1-3% of existing Indian landfill methane emission estimates. Based on the investigation of Gazipur landfill, we estimate Indian landfill methane emissions at 1.25 Tg/year or 1.68 Tg/year of methane generation potential. These values are within the range of existing estimates. A comparison of FOD with a recently proposed triangular model was also performed and it shows that both models can be used for the estimation of methane generation. However, the decrease of the emission after closure is more gradual in the case of the first-order model, leading to larger gas production predictions after more than 10 years of closure. The regional and global implications of national landfill methane emission are also discussed.