Association of winter vegetation activity across the indo-gangetic plain with the subsequent Indian summer monsoon rainfall
by Randhir Singh, V Rakesh & A K Varma
For the period 2001–2020, the interannual variability of the normalized difference vegetation index (NDVI) is investigated in connection to Indian summer monsoon rainfall (ISMR). According to Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data, the ISMR and the vegetative activity of the Indo-Gangetic plain (IGP) in the month of January show a significant negative association. We hypothesized that the January vegetation state affects the ISMR via a delayed hydrological response, in which the wet soil moisture anomaly formed throughout the winter to accommodate the water needs of intensive farming influences the ISMR. The soil moisture anomalies developed in the winter, particularly in the root zone, persisted throughout the summer. Evaporative cooling triggered by increasing soil moisture lowers the summer surface temperature across the IGP. The weakening of monsoon circulation as a result of the reduced intensity of land-sea temperature contrast led in rainfall suppression. Further investigation shows that moisture transport has increased significantly over the past two decades as a result of increasing westerly over the Arabian Sea, promoting rainfall over India. Agriculture activities, on the other hand, have resulted in greater vegetation in India’s northwest and IGP during the last two decades, which has a detrimental impact on rainfall processes. Rainfall appears to have been trendless during the last two decades as a result of these competing influences. With a lead time of 5 months, this association between January’s vegetation and ISMR could be one of the potential predictors of seasonal rainfall variability.
Assessment of long-term spatio-temporal variability of hot extremes and associated physical mechanism over India
by Rani Devi, K. C. Gouda & Smrutishree Lenka
By exploring the multifaceted physical mechanisms underlying hot extreme events, the way for informed strategies to mitigate their impacts and enhance the nation's resilience in the wake of a changing climate can be paved. The long-term spatio-temporal variability of hot extremes analysis found an increasing trend (0.001 °C) of DMXT over whole Indian region except the eastern parts (Indo-Gangetic plains). The hot day is noted when DMXT > 40 °C, DMXT > 37 °C, DMXT > 35 °C and also DMXT is above the 90th percentile at each grid point in the plains, hilly, coastal region of India. The temperature tendency equation has been computed to identify the role of various physical processes driving the local extreme temperature changes in India. The analysis showed that the surface adiabatic warming found to be one of the prominent drivers of hot extreme events over India. The impact of El Niño-Southern Oscillation (ENSO) phases on the frequency of hot extreme days at local scale in India are quantified. The linear trend of hot days has been found increasing at a rate of 0.14/year, 0.08/year and 0.06/year in El Niño, La Niña and neutral years respectively. Similarly, the DMXT anomaly found to be 0.4 °C higher in El Niño phase as compared to La Niña phase. The results infers that the chances of hot days occurrence are increased (decreased) by 38% (16% and 8%) in El Niño (La Niña and neutral) period. The advection of hot air by westerlies into the Indian region leads to an increase in temperature. The composite elevated (dropped) geopotential height at 500 hPa showed the presence of high (low) pressure systems which leads to hot days occurrence over western, southern and central (northern, north western) India, where winds are westerlies (easterlies) in El Niño (La Niña) phase of ENSO. This reversal of wind is linked with the movement of warm sea surface temperature from western to eastern Pacific Ocean. Comprehending the dynamics of hot extremes in the India is vital for the development of strategies to mitigate the adverse impacts on various sectors, including agriculture, health, water resources, and infrastructure.
Source: https://doi.org/10.1007/s00477-024-02744-w
Assessment of Country-Specific GHG Emissions from Road Transport Sector in India
by Iranna Gogeri & Krushna Chandra Gouda
The road transport sector in India is a significant contributor to the country’s GHG emissions inventories, so it is essential to develop a comprehensive database of emission inventories to inform the design and implementation of suitable technologies and policies for appropriate mitigation measures. The development of an inventory using all available data can be useful in developing policies and technologies for reduced GHG emissions from the road sector. The paper seeks to develop an inventory of GHG emissions from the India’s road transport sector and analyse the fuel consumptions usage during the recent decade period, i.e. 2011 to 2021. In this study, IPCC guideline Tier-I and Tier-II were adopted for the emission estimation. Country-specific emission factor (EFCS) was developed based on carbon content and corresponding net calorific value (NCV) of country-specific fuel usage. The CO2eq emissions are also measured and compared with the corresponding global warming potentials (GWP). It appears that emissions of CO2 equivalent emission (CO2eq) from multiple greenhouse gases have significantly increased from 2011 to 2021. Estimation based on carbon country-specific emission factor shows nearly 165.09 Mt in 2011, increasing to about 241.20 Mt in 2021. Hence, it has been observed nearly 4.39% of reduction in CO2eq emissions using EFCS in the year 2021. Similar decreasing trends have also been observed for other gases like CH4 and N2O. The development of a comprehensive national GHG inventory for the road transport sector in India is a critical step towards achieving the country’s climate change goals and ensuring a sustainable future for generations to come.
Source: https://doi.org/10.1007/s12647-024-00738-1
Assessment of air pollution status during COVID-19 lockdown (March–May 2020) over Bangalore City in India
by K. C. Gouda, Priya Singh, Nikhilasuma P, Mahendra Benke, Reshama Kumari, Geeta Agnihotri, Kiran M Hungund, Chandrika M, Kantha Rao B, Ramesh V & Himesh S
The coronavirus disease 2019 (COVID-19), which became a global pandemic by March 2020, forced almost all countries over the world to impose the lockdown as a measure of social distancing to control the spread of infection. India also strictly implemented a countrywide lockdown, starting from 24 March to 12 May 2020. This measure resulted in the reduction of the sources of air pollution in general: industrial, commercial, and vehicular pollution in particular, with visible improvement in ambient air quality. In this study, the impact of COVID-19 lockdown on the ambient concentration of air pollutants over the city of Bangalore (India) is assessed using Continuous Ambient Air Quality Measurement (CAAQM) data from 10 monitoring stations spread across the city. The data was obtained from Central Pollution Control Board (CPCB) and Karnataka State Pollution Control Board (KSPCB). The analysis of the relative changes in the ambient concentration of six major air pollutants (NO, NO2, NOX, PM2.5, O3, and SO2) has been carried out for two periods: March–May 2020 (COVID-19 lockdown) and the corresponding period of 2019 during when there was no lockdown. The analysis revealed significant reduction in the concentration of ambient air pollutants at both daily and monthly intervals. This can be attributed to the reduction in sources of emission; vehicular traffic, industrial, and other activities. The average reduction in the concentration of NO, NO2, NOX, PM2.5, and O3 between 01 March and 12 May 2020 was found to be 63%, 48%, 48%, 18%, and 23% respectively when compared to the same period in 2019. Similarly, the comparative analysis of pollutant concentrations between pre-lockdown (01–23 March 2020) and lockdown (24 March–12 May 2020) periods has shown a huge reduction in the ambient concentration of air pollutants, 47.3% (NO), 49% (NO2), 49% (NOX), 10% (SO2), 37.7% (PM2.5), and 15.6% (O3), resulting in improved air quality over Bangalore during the COVID-19 lockdown period. It is shown that the strict lockdown resulted in a significant reduction in the pollution levels. Such lockdowns may be useful as emergency intervention strategies to control air pollution in megacities when ambient air quality deteriorates dangerously.
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