Recent studies show that 67% of public transport commuters in India shifted to private vehicle ownership after the initial Covid-19 crisis (during 2021-22). Around 96% of these new vehicles were internal combustion engine vehicles (ICEVs) and will be in use for at least a decade, creating around 18.8 MtCO2 emissions annually.
Our analysis infers that if all of the newly added vehicles in India (during 2021-22) were electric vehicles (EVs), around 9.5 MtCO2 of emissions could have been avoided annually.

The Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) is a national poverty alleviation programme that provides 100 days of guaranteed wage employment to rural households whose adult members demand unskilled manual work. The scheme includes more than 260 activities (called ‘works’) that are categorised into natural resource management (NRM)-based and non-NRM-based rural development works.

In this study, we combined state-of-the-art data modelling techniques (machine learning [ML] methods) and data from state-of-the-art low-cost particulate matter (PM) sensors (LCSs) to improve the accuracy of LCS-measured PM2.5 (PM with aerodynamic diameter less than 2.5 microns) mass concentrations. We collocated nine LCSs and a reference PM2.5 instrument for 9 months, covering all local seasons, in Bengaluru, India. Using the collocation data, we evaluated the performance of the LCSs and trained around 170 ML models to reduce the observed bias in the LCS-measured PM2.5.

To effectively manage air pollution, we need to measure it accurately and at high spatial resolution. However, maintaining a dense network of regulatory instruments is financially and technically burdensome for low- and middle-income countries. A hybrid approach that combines non-conventional, less expensive, short-term stationary, and mobile deployments may be a cost-effective solution. In the city of Bengaluru, India, we adopted such a hybrid measurement approach to generate high spatial resolution air pollution maps.

MGNREGS is a poverty alleviation programme implemented pan India. As an employment guarantee scheme, it successfully captures information on the number of jobs and assets created. However, assessment of the multiple climate co-benefits arising from assets created through the programme has been a blind spot. While there have been many studies that attest to the climate co-benefits of MGNREGS works, they have been limited in their geographical scope, resulting in constrained reporting of the accrued benefits.

In India, a functioning hydrogen economy is expected to bolster the energy portfolio in a sustainable way with the support of conducive policies (National Green Hydrogen Mission) from the Government.

Novel and viable alternatives are warranted to achieve the 500 GW renewable energy target for 2030. Agrivoltaics (agriPV) is one such promising technology for optimising land usage by combining agriculture with PV.

Rooftop solar is expected to play a major role in India’s 280 GW solar target for 2030. However, only ~8 GW of the 40 GW target for 2022 has been achieved so far. The residential sector accounts for less than 20% of this installed capacity, despite being offered incentives such as net metering and a 20%–40% capital subsidy.