The study shows that FASTag reduces toll-plaza idling, fuel wastage, and congestion, cutting particulate matter and GHG emissions by nearly 7% nationwide. The upcoming GPS-based tolling system could further reduce emissions by ~4%. Highest reductions were observed in Uttar Pradesh (17%), Rajasthan (15%), and Madhya Pradesh (12%), highlighting the role of smart transport policies in advancing India’s Net-Zero goals.
This study develops a comprehensive high-resolution (0.1° × 0.1°) methane emission dataset for India for 2023, integrating 25 anthropogenic and natural sources through a country-specific bottom-up framework. The inventory helps close key data gaps and provides a strong scientific basis for climate modeling, methane mitigation, and sustainable development.
This study is the first-of-its-kind national study which examines the link between PM2.5 emissions and eye diseases across India using high-resolution emission data and hospital records from 720 districts (2019–2020). Results show a significant association between PM2.5 emissions and ophthalmic cases, with 32.6 million eye-related hospital visits, nearly 80% from rural areas. Eye disease risk was 4 times higher in exposed rural populations, highlighting the need for targeted clean-air and public health action.
This study developed a high-resolution (~0.4 km × 0.4 km) emission inventory for Delhi covering eight major pollutants to improve source-based air pollution control strategies. For 2020, annual emissions of PM2.5 and PM10 were estimated at 123.8 and 243.6 Gg yr⁻¹, respectively. Decadal analysis (2010–2020) showed the highest growth from the transport sector, with major increases in NOx (91%), BC (57%), and OC (34%), highlighting priority areas for targeted mitigation.
This study presents the first-of-its-kind ultra-fine (~400 m x 400 m) surface emission and its sources over megacity Mumbai for the most recent year, 2020 (i.e., April 2019-March 2020), that includes the maximum number (17 Nos. of major and minor sources) responsible for discharging eight kinds of pollutants, namely PM2.5, PM10, CO, NOx, SO₂, VOC, BC, and OC. Developed emission dataset identified most polluting hotspots across the megacity for mitigation actions under NCAP.
This study presents a district-level India inventory of Mercury (Hg) emissions for 2019 using IPCC methodology and country-specific emission factors. Total Hg emissions were estimated at 459.4 t/yr, led by thermal power plants (186.5 t/yr), followed by non-ferrous metal production and captive power plants. The study found that 233 million people living near major industrial zones may be exposed, providing key evidence for future emission control and health-risk planning.
This study estimates India’s livestock-sector Methane (CH₄) emissions at 12.74 Tg yr⁻¹ for 2019, including 11.63 Tg yr⁻¹ from enteric fermentation and 1.11 Tg yr⁻¹ from manure management. A district-level spatial inventory identified major emission hotspots, showing how livestock population patterns strongly influence rural methane emissions and can support targeted mitigation policies.
This study develops a comprehensive gridded (0.1° × 0.1°) Ammonia (NH₃) emission inventory for India, covering 24 sources. Total NH₃ emissions were estimated at 10.54 Tg/yr in 2022, dominated by synthetic fertilizer use (~47%) and livestock (~34%). The dataset identifies national hotspots and provides a valuable tool for atmospheric modeling and pollution-control policies.
These intensive studies have precisely decoded the emissions of air pollutants for the five megacities and the first smart city of India that are published in reputable international peer-reviewed journals. The developed high-resolution emission dataset has the potential to be a useful scientific resource for policymakers as well as for the goals of the “National Clean Air Programme” (NCAP). The dataset would undoubtedly strengthen the city-specific mitigation strategy and air quality modeling, along with the health impact assessment.
Link to the published articles:-
Delhi- https://lnkd.in/gu-J3ZWR
Mumbai - https://lnkd.in/giBkdKwy
Bengaluru - https://lnkd.in/dWimkdf8
Kolkata - https://lnkd.in/dh59GvXK
Bhubaneswar - https://lnkd.in/gEtSwqJV