This is the first multi-city study in India that examines the association between short-term exposure to PM2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution. The study found a 1.4% higher daily mortality, with a 10 µg/m³ increase in 2-day moving average of PM2·5. Causal instrumental variable analysis representing the effect of locally generated air pollution, showed a stronger association with daily mortality (3·6% [2·1–5·0]) than the overall estimate. Two times higher risk of death per 10 µg/m³ increase was observed, when restricting the analyses to observations below the Indian air quality standard (2·7% [1·7–3·6]). Using the integrated exposure–response curve, 7·2% (4·2%–10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines.

Bont et al., 2024
Lancet Planet Health

This study investigates the representation of summer monsoon precipitation and associated extremes over the Indo-Gangetic Plains (IGP) using high-resolution regional climate models (RCMs) under the CORDEX-CORE framework. The analysis reveals that eastern parts of the IGP receive higher precipitation compared to the western parts, primarily driven by the direction of the monsoon low-level flow. The RCMs effectively capture extreme rainfall events, which are closely linked to moisture transport and trough activity. The study underscores the significance of RCMs in accurately assessing local-scale climate variability, which is critical for the agriculture-dependent regions of the IGP.

Pant et al., 2024
Climate Dynamics

This study analyses future changes in heat waves across India using regional climate models from the CORDEX-SA dataset under RCP 4.5 and RCP 8.5 scenarios, revealing that heat wave frequency will increase significantly, overshadowing intensity. A four-to-seven-fold rise in heat wave frequency is projected under RCP 4.5, while RCP 8.5 predicts a five-to-ten-fold increase. Central, South-central, and North-western India are identified as future heat wave hotspots, with substantial increases in heat stress anticipated over coastal regions, posing critical risks to health, agriculture, and infrastructure.

Singh et al., 2023
iScience

This study evaluated the performance of 12 Global Circulation Models from the CMIP6 experiment with IMD observed data sets to reproduce the extreme rainfall events as well as project the changes in frequency and intensity of the hydro climate extremes in future and found that under low emission scenarios (SSP1-2.6), the frequency of extreme rainfall is going to increase over the western ghat and northeast IRBs, while an increase in heavy rainfall intensity (14.3%) noticed under SSP2-4.5 in the upper Ganga and Indus basin. Also, approximately 4%–10% of the heavy rainfall is projected to increase over the western part of IRBs during the Near (2021–2040) and Mid (2041–2060) future.

Chaubey et al., 2023
Earth's Future

The study identifies three prominent heat wave (HW) prone regions i.e., Northwestern, Central and South-Central India, and found a Spatio-temporal shift in the occurrence of HW events with a significantly increasing trend, highest being in West Madhya Pradesh (0.80 events/year), while a significantly decreasing trend was observed over eastern region i.e., Gangetic West Bengal (-0.13events/year). Severe Heat wave (SHW) events showed a southward expansion and a spatial surge during the decades of 2001-2010 and 2010-2016. Additionally, correlation between HW/SHW events and observed mortality reveals that the eastern coastal states i.e., Odisha and Andhra Pradesh show a significant positive correlation of 0.62 and 0.73 respectively.

Singh et al., 2021
International Journal of Climatology

The evidence of effect of multiple air pollutants e.g., aerosols (black carbon, BC; PM2.5 and PM10) and trace gases (NO2, SO2 and O3) on all-cause premature mortality was established over central Indo-Gangetic Plain (IGP). Statistically significant impact of BC aerosols (4.95%), followed by NO2 (2.38%) and PM2.5 (1.06%) on mortality was noted, particularly for elderly and children. Individual effects of air pollutants increased in presence of other pollutants. The distributed lag nonlinear model showed significant lag effect of pollutants up to 5 days. The exposure-response curves for individual air pollutants were mostly linear.

Singh et al., 2021
Atmospheric Environment

Aerosol climatology during typical haze dominating period was explored using several EOS products from 2010 - 2020. Comparatively high aerosol loading with dominance of fine and UV-absorbing aerosol are noted across the Indo-Gangetic plain (AOD:0.58; UVAI:0.74) against weak UV-absorbing fine aerosols over Southeast Asia (AOD:0.26; UVAI:0.07). Urban hotspots across IGP (except Dhaka) denote a spatially consistent minor increasing trend in AOD (0.2-1.8x10-2year-1) while increase in UVAI is more prominent over upper IGP. Smoke aerosols are more UV-absorbing across South Asia compared to Southeast Asia. At upper atmosphere (>4km) dust aerosols clearly dominate across the IGP. Smoke & urban aerosols are abundant over SEA.

Banerjee et al., 2021
JGR-Atmosphere

Increasing trend of DTR (0.038_C/decade) during 1951–2016, and a decreasing trend (−0.02_C/decade) during the recent period (1991–2016) across the different agro-climatic zones (ACZs) of India. Increasing trend was noted for Tmax (0.078_C/decade, significant), Tmin (0.049_C/decade) during 1951–2016 and Srad (0.10 MJ/m2/day/decade) during 1984–2016. Decreasing trend in DTR was accounted for much increase in Tmin (0.210_C/decade) during 1991–2016. There were also interesting spatial differences found with the ACZs in the north-west, parts of Gangetic plain, north-east, and central India exhibiting negative DTR trends.

Mall et al., 2021
International Journal of Climatology

It is the first study to evaluate performance of eight CORDEX-SA regional climate models for simulating heat waves over India. In the present study, Regional Climate Models (RCMs) namely, CCAM and RegCM, from Coordinated Regional Climate Downscaling Experiments (CORDEX) for South Asia (SA) are evaluated for simulating heat waves (March–June) over India in comparison with observations from India Meteorological Department (IMD). LMDZ4 and GFDL-ESM2M were found to be best-performing models in significantly reproducing the heat wave frequency and spatial variability in closer proximity with observations over India amongst all models after bias correction. The study suggests a way forward to assess RCMs performance in extreme weather analysis in future projections.

Singh et al., 2021
Atmospheric Research

As soil erosion is an integral element for sustainable agricultural and environmental development, this study aims to investigate the impact of rainfall and land use/land cover changes in the current and future scenarios (1981 – 2040) to further deduce the soil erosion losses using the state-of-the-art Revised Universal Soil Loss Equation (RUSLE), Cellular Automata Markov Chain (CA-Markov) and machine learning models. In total seven CMIP5 model projections viz Ensemble mean, MRI-CGCM3, INMCM4, canESM2, MPI-ESM-LR, GFDL-ESM2M and GFDL-CM3 of rainfall were used in model development and comparison. As a result, we have generated an integrated framework for the prediction of soil erosion rates over Mahi River Basin.

Maurya et al., 2021
Journal of Hydrology

Smoke injection height varied considerably during rice (October-November: 0.71±0.65km) and wheat (April-may: 2.34±1.34km) residue burning period with a significant positive correlation with prevailing boundary layer. Besides, despite travelling efficiently to free troposphere, major proportion of smoke AOD (50-80%) continue to remain close to the surface (less than 3km).

Vinjamuri et al., 2020
Environmental Pollution

Impact of climate change on sugarcane crop was assessed using the CANEGRO-Sugarcane model in diverse agro-climatic zones of the Uttar Pradesh. The results showed that Stalk Fresh Mass is projected to increase by 3–39% (rainfed) and 7–47% (irrigated) in 2040–2060 relative to 1971–2000. Similarly, Sucrose Mass is projected to decrease by 9–69% (rainfed) and 6–37% (irrigated). The findings suggest the development of efficient water use, heat-tolerant cane variety and improved farm management strategies in the near future to assist the sugar industry and to adapt to the changing climate in northern India.

Sonkar et al., 2020
Sugar Tech

A comprehensive evaluation of multi-satellite satellite precipitation products are undertaken against ground-measured Indian Meteorological Department (IMD) precipitation data to estimate and forecast the meteorological drought in the Bundelkhand region of Central India. The high-resolution CHIRPS data showed the closest agreement with the IMD precipitation and well captured the drought characteristics. The Standardized Precipitation Index (SPI) identified seven major droughts events during the period of 1981 to 2016. The forecasting result showed a reasonably good agreement with the observed datasets with the one-month lead time.

Pandey et al., 2020
Geocarto International

Conclusive evidence of the negative impact of rising temperature on wheat yield was reported for India. The impact was inconsistent spatially. One degree increase in mean temperature resulted a 7% decrease in wheat yield over India which varied disproportionally across the wheat growing zones within a range of -9% (peninsular zone, PZ) to 4% (northern hills zone, NHZ).

Sonkar et al., 2019
Environmental Pollution

Increase in daily mean temperature was strongly associated with excess mortality in Varanasi, both during summer (5.61%) and winter (1.50%). Daily mortality was found to be increased by 12% due to heat wave. The study is first to present the increase in mortality with decrease in diurnal temperature variation. Increase in mortality was high during summer compared to winter. Similarly, risk ratio was high due to heat wave compared to cold spell.

Singh et al., 2019
Science of the Total Environment

We assessed the existing status and scope of DRR including CCA in development projects across South Asia, so that an effective and achievable deliberation may be made to regional policymakers. The project inventory was diverse in nature with respect to location, scale, sectoral focus, and strategic importance. Bangladesh, India, and Bhutan were found to be proactive in implementing DRR- and CCA-related projects. Meta-analysis suggests an urgent need for an individual and collaborative convergence of processes for DRR and CCA through policies, plans, strategies, and programs.

Mall et al., 2019
International Journal of Disaster Risk Science

This work aims to explore the biasness in the RegCM climate model outputs for diverse agro climatic zones of Uttar Pradesh, India emphasizing on wheat and rice yields with and without bias corrected data for the baseline period of 1971–2000. Bias correction approach showed good agreement for the annual and seasonal maximum and minimum temperatures. The CERES-Wheat and CERES-Rice models embedded in DSSAT (Decision Support System for Agro-technology Transfer) were used to quantify the biasness in the simulated potential, irrigated, and rainfed wheat and rice yield. The RCM-simulated wheat and rice yield were high while the bias-corrected yield has shown good agreement with the observed yield.

Mall et al., 2018
Climatic Change