Particulate matter (PM) has been linked to numerous adverse health effects in humans, with exposure being a significant factor in cardiovascular diseases and increased rates of mortality and morbidity. This study analyzed the concentrations of PM1, PM2.5, and PM10 during a dust storm in Western India in January and February, primarily affecting Ahmedabad, Pune, and Mumbai. Under typical atmospheric conditions, the monthly average inhaled concentrations of PM1, PM2.5, and PM10 in Ahmedabad were 30, 65, and 117 µg/m3, respectively. In comparison, Mumbai recorded 41, 80, and 143 µg/m3, while Pune reported 62 and 100 µg/m3 for PM2.5 and PM10. During the dust storm, however, these levels rose sharply: Ahmedabad reached 72, 154, and 269 µg/m3, Mumbai escalated to 136, 310, and 544 µg/m3, and Pune increased to 150 and 251 µg/m3. The findings highlight the substantial elevation in PM exposure associated with dust storm events, underscoring their potential implications for air quality and public health in urban regions of Western IndiaThe study employed the Multiple-Path Particle Dosimetry (MPPD) model to deepen the analysis to evaluate age-specific particle deposition in the three cities. Coarse particles (PM10) predominantly settled in the head and tracheobronchial regions, whereas finer particles (PM2.5 and PM1) were mainly deposited in the pulmonary areas. PM2.5 deposition was observed to be highest in children, followed by the elderly and adults. A detailed lobar analysis indicated that the left lower lobes experienced the highest deposition, followed by the right and middle lobes. PM2.5 emerged as the dominant particle size fraction deposited across all lobes for individuals of all age groups, including infants, children, and adults. The findings underscore the critical role of PMs in lung deposition and their relevance in assessing health risks, such as oxidative stress and toxicity from particle accumulation.

On-road transport is a major contributor to the country's air pollution profile. Envisioned reaching Net-Zero by 2070 and curbing air pollution, Government of India's initiative to adopt FASTag (Fast and Secure Transmission of Highway Tags) technology is revolutionary in the toll collection system in transport ecosystem. This is the first-ever national-level study to investigate the impact of FASTag policy on mitigating vehicular emissions near toll plazas across India. The emission reduction is assessed and estimated using the Intergovernmental Panel on Climate Change (IPCC) defined bottom-up approach for 2025. The estimated emissions findings highlight that there is a significant reduction varying up to similar to 7% for PM2.5, PM10, CO, NOx, VOC, SO2, BC, OC and CO2 emissions due to the FASTag as compared to traditional toll collection system, where the highest reduction comes from the regions like Indo-Gangetic plain, Western and South-Eastern India. With the implementation of advanced Global Positioning System (GPS) based toll collection systems in the forthcoming year, it will further reduce emissions by another similar to 4%. Heavy commercial vehicles (HCVs) are the largest contributor to emissions and are likely to contribute the largest portion to the reduction of pollutants. This research sensitises the role of policy-induced advanced sustainable transport technology to achieve Net-Zero.

Methane (CH4) is a predominant climate-forcing agent and has become a focal point of global climate discussions, owing to its significant contribution to atmospheric warming. The ambiguity surrounding the relative contributions of various natural and anthropogenic sources, coupled with associated uncertainties, poses significant challenges to assessing methane emissions in developing nations like India. To address these challenges and better understand the methane-emitting sources, this study presents a comprehensive high-resolution gridded (0.1 degrees & times; 0.1 degrees) inventory of CH4 emission by including 25 distinct anthropogenic and natural sources in India for 2023 by adopting the IPCC bottom-up approach. The estimated CH4 over India is 37.79 Tg yr-1, which will redefine the contribution of various sources. The agriculture sector contributed similar to 50% followed by wetlands (22.8 %), fossil fuel (8.9 %) and waste management (8.4 %). This study reports the first-ever comprehensive emissions from natural sources like wetlands and termites. The Indo-Gangetic Plain (IGP) and coastal states show elevated emissions with Uttar Pradesh contributing the highest (10.8 %) followed by Gujarat (9.4 %), and Maharashtra (8.6 %). However, surprisingly cities exhibit lower CH4 as compared to other semi-urban/rural regions. This developed dataset can be a valuable input to optimize the climate study by filling the data gap, enabling policymakers to formulate various mitigation measures. The emission dataset can be accessed through the Zenodo repository 10.5281/zenodo.14089138 (Sahu, 2024).

Particulate Matter (PM) pollution is a prime component of air pollution and poses a substantial risk to human health, including the eye. This work envisioned to show the impact of PM2·5 pollution on the Ophthalmic disease prevalence in India. This national-level observational-based cross-sectional retrospective study included the hospital-reported ophthalmic outpatients in 2019-20. The sector-wise high-resolution (0·1° × 0·1°) PM2·5 emission data along with the annual average PM2·5 concentration data for 2019 from NASA is adopted for the risk factor analysis. Nearly 32·6 million footfalls are recorded in various hospitals due to ophthalmic morbidity in 2019, out of which surprisingly ~ 80% of cases are registered in rural India. Half of the total ophthalmic disease burden comes from the top 100 districts out of the total 720 districts in India. The inferential analyses depicted a statistically significant positive correlation (r = 0·54, 95% CI 0·48 - 0·59, P < 0·001) between the PM2·5 emission and ophthalmic outpatients. The risk of eye disease in the exposed rural population is 4 times higher than the unexposed population 4·19 (4·19 - 4·2). The PM2·5 emission from household cooking activity shows a greater correlation (r2 = 0·28, 95% CI 0·22 - 0·35, P < 0·001) with the occurrence of ophthalmic cases in India followed by incense stick and mosquito coil burning (r2 = 0·28 (0·22 - 0·34)), and transportation (r2 = 0·24 (0·18 - 0·29)). The meteorological parameters like temperature and humidity show very little association and precipitation shows a negative correlation with the number of ophthalmic outpatients in India. This study suggests that surface emission data could be a potential tool to link prevailing diseases in India.

Particulate chloride (pCl) is a significant constituent of atmospheric particulate matter, playing a critical role as a key precursor to secondary aerosols via nocturnal heterogeneous reactions. While coarse pCl typically prevails along the coastal belt, however, the growing presence of fine pCl in the interior regions is an emerging air quality concern. Anthropogenic sources driving these emissions remain poorly characterised, particularly in India, where existing global inventories lack resolution and specificity. This study presents the first high-resolution (0.1° × 0.1°) national anthropogenic emission inventory of pCl across India for 2023, identifying 42 discrete sources. Total pCl emissions are estimated at 245.6 Gg/yr, of which biomass burning contributes ~68 % and waste burning ~21 %. Emission hotspots are concentrated in the northern and southern Indo-Gangetic Plain and the Northeastern states, with over 60 % of total emissions originating from just 8 % of the country's area. Despite an estimated uncertainty of ±71 %, this comprehensive dataset offers critical insights for chemical transport modelling and policy formulation, enabling targeted mitigation strategies and advancing understanding of pCl dynamics at the national level.

The impact of air pollution mitigation policies needs to be studied by evaluating long-term trends of lead pollutant to determine air quality index, the particulate matter (PM). A decade of SAFAR (System of Air quality and weather Forecasting And Research) observations revealed that the trend of particulate matter (PM) with size < 2.5 µm (PM2.5) and size < 10 µm (PM10), respectively, in a highly polluted global city, Delhi, shows a reduction of − 3.12 ± 0.52 µg/m3/year (− 4.68 ± 0.84 µg/m3/year) or overall, 28.8

Heavy metals, particularly cadmium (Cd) and lead (Pb), pose a significant environmental challenge worldwide owing to their detrimental effects on ecosystem sustainability. India, the most populous country in the world, presently faces severe contamination by heavy metals. This study identifies and quantifies the Cd and Pb emissions from the principal industrial sources at the district level across India, using the IPCC bottom-up approach for 2019. The developed emission inventory includes various industries, notably coal-based power plants, captive power plants, cement production, iron and steel manufacturing, non-ferrous metal production, municipal and biomedical waste incineration, the glass industry, and fly ash generated. Annual emissions were reported to be approximately 2,016 tonnes/year (t/yr) for Cd and 19,258 t/yr for Pb, where coal combustion across different industries emitted approximately 93 t of Cd and 927 t of Pb, with the energy sector contributing about 66% and fly ash accounting for over 80% of total emissions. Among non-ferrous metals, copper production is solely responsible for 44 t and 77 t of Cd and Pb, respectively. The research also identifies regional hotspots for Cd and Pb emissions across India, highlighting areas where targeted remediation strategies can support sustainable environmental management.

Anthropogenic greenhouse gas emissions significantly impact the middle and upper atmosphere. They cause cooling and thermal shrinking and affect the atmospheric structure. Atmospheric contraction results in changes in key atmospheric features, such as the stratopause height or the peak ionospheric electron density, and also results in reduced thermosphere density. These changes can impact, among others, the lifespan of objects in low Earth orbit, refraction of radio communication and GPS signals, and the peak altitudes of meteoroids entering the Earth's atmosphere. Given this, there is a critical need for observational capabilities to monitor the middle and upper atmosphere. Equally important is the commitment to maintaining and improving long‐term, homogeneous data collection. However, capabilities to observe the middle and upper atmosphere are decreasing rather than improving.

Ammonia (NH3) acts as a key precursor of the particulate matter, could reduce visibility, deplete stratospheric ozone, and trigger perturbation in ecosystems. Being an agrarian country with a large livestock population and uncontrolled fertilizer application, India could be accountable as a major stakeholder of global NH3 emissions. This study developed a comprehensive gridded (0.1° x 0.1°) ammonia inventory for India considering 24 types of sources. The total NH3 emission is estimated to be 10.54 Tg/yr in 2022, where synthetic fertilizer application accounts for ∼47 % followed by livestock (∼34 %). Minor unattended sectors such as biomass burning, agricultural soil, human excrement, waste disposal, etc. contribute 0.68 Tg/yr, 0.32 Tg/yr, 0.3 Tg/yr, and 0.14 Tg/yr, respectively. The overall uncertainty of the inventory ranges around ± 55 %. These emission datasets are essential for atmospheric chemistry models and could be a crucial tool for policymakers to combat ammonia pollution.

We hereby present the variability of fine particles (PM1 ≤ 1 micron) that has not yet been investigated under the influence of COVID-19-induced lockdown in three major cities of different climatic zones in India. We unfold the baseline level of PM1, a level to which the population is chronically exposed and extremely critical for epidemiologists for fixing health markers. This has been achieved using the saturation point methodology under fair weather conditions. The baseline level of PM1 for Delhi and Mumbai is found to be 13 µg m− 3 and 9 µg m− 3, respectively. The processes leading to a significantly higher decline in the level of PM1 as compared to coarser particles (PM2.5) are discussed. The varying magnitude of the declining trends in PM1 is found to be linked to the intensity of residential emissions, which vary from one city to another and was exempted during lockdown. Our findings are critical in understanding the dominant role played by different sources of PM1 in framing effective health risk management policies. The reduction in PM1 is found to be significantly higher than that of PM2.5 during a lockdown. The baseline level is found to be 13 µg m− 3 for Delhi and 9 µg m− 3 for Mumbai. The magnitude of reduction in PM1 among different metros is influenced by biofuel usage. A baseline estimate will be a critical input to epidemiologists and health policies.

One of the major requirements of air quality management for a particular region or country is to understand the sources of emissions, particularly those from the dominant sectors. The on-road transport sector is one of the most important sources of pollutant emissions, as it is directly linked to economic growth, and the current study focuses on India, a nation that is currently experiencing very rapid development. In view of this, the present work develops an inventory of on-road vehicular emissions at 0.5° × 0.5° resolution (approx. 55 km) for a region in India, where a technologically-based dynamic emissions factor method has been used to for the last 20 years. This new inventory can not only provide improved estimates of emissions in recent years but also highlight the relative contribution of various vehicles, based on age, to the total emissions produced by the transport sector. In addition, inventories of the major air pollutants for on-road vehicles in India are developed for the base year of 2009 for the first time in this work. The total emissions from the transport sector are estimated to be 5.4 Tg/yr for NOx, 10.2 Tg for CO, 693.3 Gg/yr for PM and 5.54 Tg/yr for VOC, 240,000 kilometers of national, state and major highways in India are used to achieve a better spatial allocation of gridded on-road emissions, along with a vehicular density map in a GIS environment. The emissions data presented in this work will not only help in improving the simulated distribution of air pollutants in chemical transport models, but can also be used for air quality management in planning related mitigation strategies.

The radiative forcing of elemental carbon (EC) and organic carbon (OC) has been estimated over two urban environments in Northern India (Jabalpur [JBL] and Udaipur [UDPR]) from November 2011 till November 2012 (till September 2012 over Jabalpur). The elemental carbon concentrations reached 7.36 ± 1.99 µg m–3 over JBL and were as high as 10.78 ± 4.85 µg m–3 over UDPR, whereas the corresponding OC concentrations were much higher in different months (as high as 19.37 ± 12.6 µg m–3 over JBL and 39.71 ± 13.05 µg m–3 over UDPR). The radiative forcing for OC and EC has been estimated using an optical model along with a radiative transfer model. The surface OC radiative forcing was found to range from –2.19 ± 1.93 W m–2 to –3.083 ± 2.29 W m–2 over JBL and –1.97 ± 1.37 to –5.89 ± 2.17 W m–2 over UDPR, whereas the estimated top of the atmosphere (TOA) forcing ranged from –0.87 ± 0.49 to –1.87 ± 0.90 W m–2 over JBL and from –1.23 ± 0.31 to –3.44 ± 1.51 W m–2 over UDPR. However, the effect of EC forcing (as high as –21.75 W m–2 at the surface of and +6.3 W m–2 at TOA over JBL and –38.21 W m–2 at the surface of and +5.05 W m–2 at TOA over UDPR) was found to be more than tenfold higher than OC forcing due to its strong atmospheric absorption, in spite of much lower concentrations compared to OC.

Routine observations of surface ozone (O3) and its precursors (NO, NO2, NOx) were taken over Bengaluru, a southern megacity, India, for 4 years period between January 2015 and December 2018. The seasonal variations of O3, NO, NO2, and NOx have been analysed to understand the short-term variability of the pollutants at this site. The magnitude of O3 varied significantly by season, with maximum concentration during winter (13.07 ppbv) and minimum concentration during monsoon (9.52 ppbv). The highest concentration was observed in the post-monsoon season (17.38 ppbv) for NO, while NO2 and NOx showed the highest (41.75, 50.42 ppbv) in the winter season. The lowest concentrations of NO (5.70 ppbv), NO2 (30.43 ppbv) and NOx(36.28 ppbv) were observed in summer. An estimate was performed to determine the site's VOC-NOx sensitivity, using the TNMHC/NOX ratio as a photochemical measure. This ratio indicates that the study region is NOX responsive in all seasons. Analysis was done on the effects of meteorological factors such as temperature, water vapour, and ventilation coefficient on pollutants. Higher correlation of O3 with temperature showed the role of photochemical reactions in the formation of ozone and water vapour content leads to the removal of ozone concentration. The influence of meteorological variables on NO2 and TNMHC did not appear to be very significant. An analysis of CAMS data with real-time measurements of ozone and oxides of nitrogen showed that ozone is significantly correlated, while nitrogen oxides are not significantly correlated with CAMS data.

Monitoring and simultaneous sampling of Particulate matter (PM10 and PM2.5) was carried out for the first time over two urban sites in Northern India (Jabalpur and Udaipur) during December 2010–November 2012 (up to August 2012 over Udaipur). The samples of PM2.5 were analyzed for elemental carbon (EC) and organic carbon (OC) using advanced DRI Thermal optical carbon Analyzer. The monthly mean PM10 values were as high as 149 ± 44 µg m−3 over Jabalpur (JBL) and 171 ± 42.2 µg m−3 over Udaipur (UDPR) . PM2.5 mass over JBL varied between 25–79 µg m−3 and over UDPR between 24–82 µg m−3. The monthly mean OC concentration varied from 12.5 ± 7.3 µg m−3 to 28.4 ± 10.7 µg m−3 over JBL and from 7.8 ± 2.9 to 39.7 ± 11.6 µg m−3 over UDPR. The variation of monthly mean EC concentration was from 3.9–10.3 µg m−3 over JBL and from 3–10.9 µg m−3 over UDPR. The contribution of TC to PM2.5 was in the range of 31–75

Measurements of mass concentrations of particulate matters (PM2.5 and PM10) and mixing ratio of carbon monoxide (CO) were made at an urban site of Udaipur (24.58°N, 73.68°E) in India from April 2010 to March 2011. Concentrations of PM2.5, PM10 and CO show strong diurnal and seasonal variations. The highest concentrations coincide with the rush traffic and lower nocturnal boundary layer depth. The lowest concentrations in the afternoon hours are attributed to the dilution caused by higher boundary layer height and reduced traffic. The levels of trace constituents during the weekend were significantly reduced compared to the weekdays of observations. The daily PM2.5, PM10 and CO varied in the large ranges of 8–111 µg/m3, 28–350 µg/m3 and 145–795 ppbv, respectively. PM2.5 and CO show strong seasonality with higher and lower values during winter and monsoon seasons, respectively, while PM10 shows highest value during the pre-monsoon season. Flow of cleaner marine air and negligible biomass burning resulted in lower values in the monsoon season. Long-rang transport and extensive biomass burning caused higher values in winter and pre-monsoon seasons. Back trajectories show seasonal shift in the long- range transport which is consistent with the seasonality of aerosols and CO. Except for the monsoon season, mass concentrations of PM2.5 and PM10 show good correlation (typically r2 > 0.5). Relations of PM2.5 and PM10 with CO varied with the season but show good correlations (r2 > 0.5) during the winter season, while poor correlation during monsoon. The correlations suggest dominance of combustion related emissions particularly during winter season. Monthly emission ratios of ΔPM2.5/ΔPM10, ΔPM2.5/ΔCO and ΔPM10/ΔCO varied in the ranges of 0.19–0.31 µg/m3/ppbv, 0.05–0.10 µg/m3/ppbv and 0.15–0.25 µg/m3/ppbv, respectively. The mass concentration of PM2.5 tends to decrease with the increasing wind speed, while PM10 increases with wind speed.

The Indian Government implemented the project "System of Air quality Forecasting And Research (SAFAR)" for the "Commonwealth Games" 2010 in Delhi. It was adopted by the Global Urban Research Meteorology and Environment of World Meteorological Organization as its pilot project. We used data from a dense network of stations built over 2500 km2 in Delhi under the SAFAR project to investigate temporal and spatial variations of fine (PM2.5) and coarse (PM10–2.5) particles, and discuss their deposition and the airborne mass fractions that were retained after a certain amount of time. The 24-hour coarse particle (PM10–2.5) means during the Games period were always above the National Ambient Air Quality Standard NAAQS (100 μg/m3) at all the sites except the airport. In still air, initial PM10–2.5 can reach below 50 μg/m3 by deposition in an hour. The 24-hour PM2.5 means reveal that they were either around or below the NAAQS (60 μg/m3) at some sport complexes, whereas they fluctuated between 60 and 80 μg/m3 at the other sites.

Megacity Mumbai is a non-attainment city designated under the National Clean Air Programme (NCAP) of the Government of India, where the identification of exact sources responsible for air quality issues remains unclarified. In the present work, an effort has been made to develop an ultra-fine resolution (similar to 400mt x similar to 400mt) emission inventory by including micro-level activity data for both organized and unorganized sources using a bottom-up approach for the year 2020. The estimated results unveil that 44 Gg/yr of PM2.5, 72.5 Gg/yr of PM10, 359.7 Gg/yr of CO, 175.6 Gg/yr of NOx, 132.9 Gg/yr of SO2, 223.4 Gg/yr of VOC, 13 Gg/yr of BC and 12.5 Gg/yr of OC have been deteriorating the city air. The developed inventory is most up-to-date surface emission dataset highlighting the hotspots along with the source-specific contributions. This study targets mitigation for cleaner air in the megacity; an aid to the mission of the NCAP. In addition to this, the present dataset could be an important tool for public health management and air quality studies.

The recent La-Nina phase of the El Nino Southern Oscillation (ENSO) phenomenon unusually lasted for third consecutive year, has disturbed global weather and linked to Indian monsoon. However, our understanding on the linkages of such changes to regional air quality is poor. We hereby provide a mechanism that beyond just influencing the meteorology, the interactions between the ocean and the atmosphere during the retreating phase of the La-Nin similar to a produced secondary results that significantly influenced the normal distribution of air quality over India through disturbed large-scale wind patterns. The winter of 2022-23 that coincided with retreating phase of the unprecedented triple dip La-Nin similar to a, was marred by a mysterious trend in air quality in different climatological regions of India, not observed in recent decades. The unusually worst air quality over South-Western India, whereas relatively cleaner air over the highly polluted North India, where levels of most toxic pollutant (PM2.5) deviating up to about +/- 30 % from earlier years. The dominance of higher northerly wind in the transport level forces influx and relatively slower winds near the surface, trapping pollutants in peninsular India, thereby notably increasing PM2.5 concentration. In contrast, too feeble western disturbances, and unique wind patterns with the absence of rain and clouds and faster ventilation led to a significant improvement in air quality in the North. The observed findings are validated by the chemical-transport model when forced with the climatology of the previous year. The novelty of present research is that it provides an association of air quality with climate change. We demonstrate that the modulated large-scale wind patterns linked to climatic changes may have far reaching consequences even at a local scale leading to unusual changes in the distribution of air pollutants, suggesting ever -stringent emission control actions.

Concentrations of fine particulate matter (PM2.5) that exceed air quality standards affect human health and have an impact on the earth's radiation budget. The lack of round the clock ground-based observations from a dense network of air quality stations inhibits the understanding of PM2.5's spatio-temporal variability and the assessment of its health and climate effects. Aerosol optical depth (AOD) values retrieved from satellite based instruments can be used to derive surface PM2.5 concentrations. This study integrates Moderate Resolution Imaging Spectroradiometer (MODIS) AOD retrievals and simulations from the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) to determine the ground-level PM2.5 concentrations at a 36 km resolution across India. WRF-Chem simulations provide the factor relating the AOD with the PM2.5. Satellite-derived PM2.5 mass concentrations are compared with the available ground-based observations across India for the year of 2011. The results show a correlation between the satellite-derived monthly PM2.5 estimates and the ground-based observations for 15 stations in India with coefficients of 77% and diurnal scale coefficients varying from 0.45 to 0.75. The best estimations of PM2.5 mass concentrations on a spatio-temporal scale across India address various environmental issues.