Subnational implications from climate and air pollution policies in India's electricity sector.

Emissions of greenhouse gases and air pollutants in India are important contributors to climate change and health damages. This study estimates current emissions from India's electricity sector and simulates the state-level implications of climate change and air pollution policies. We find that (i) a carbon tax results in little short-term emissions reductions because there is not enough dispatchable lower emission spare capacity to substitute coal; (ii) moving toward regional dispatch markets rather than state-level dispatch decisions will not lead to emissions reductions; (iii) policies that have modest emissions effects at the national level nonetheless have disparate state-level emissions impacts; and (iv) pricing or incentive mechanisms tied to production or consumption will result in markedly different costs to states.

Should India Move toward Vehicle Electrification? Assessing Life-Cycle Greenhouse Gas and Criteria Air Pollutant Emissions of Alternative and Conventional Fuel Vehicles in India.

We perform a state-specific life-cycle assessment of greenhouse gases (GHG) (CO2eq) and sulfur dioxide (SO2) emissions in India for representative passenger vehicles (two-wheelers, three-wheelers, four-wheelers, and buses) and technologies (internal combustion engine, battery electric, hybrid electric, and plug-in hybrid electric vehicles). We find that in most states, four-wheeler battery-electric vehicles (BEVs) have higher GHG and SO2 emissions than other conventional or alternative vehicles. Electrification of those vehicle classes under present conditions would not lead to emission reductions. Electrified buses and three-wheelers are the best strategies to reduce GHG emissions in many states, but they are also the worst strategy in terms of SO2 emissions. Electrified two-wheelers have lower SO2 emissions than gasoline in one state. The Indian grid would need to decrease its carbon dioxide emissions by 38-52% and SO2 emissions by 58-97% (depending on the state) for widespread vehicle electrification for sustainability purposes to make sense. If the 2030 goals for India under the Glasgow COP are met, we find that four-wheeler BEVs still have higher GHG emissions in 18 states compared to a conventional gasoline compact four wheeler, and all states will have higher SO2 emissions for BEVs across all vehicle types compared to their conventional counterparts.

Current and Future Estimates of Marginal Emission Factors for Indian Power Generation.

Emission factors from Indian electricity remain poorly characterized, despite known spatial and temporal variability. Limited publicly available emissions and generation data at sufficient detail make it difficult to understand the consequences of emissions to climate change and air pollution, potentially missing cost-effective policy designs for the world's third largest power grid. We use reduced-form and full-form power dispatch models to quantify current (2017-2018) and future (2030-2031) marginal CO2, SO2, NOX, and PM2.5 emission factors from Indian power generation. These marginal emissions represent emissions changes due to small changes in demand. For 2017-2018, spatial variability in marginal CO2 emission factors range 3 orders of magnitude across India's states. There is limited seasonal and intraday variability with coal generation likely to meet changes in demand more than half the time in more than half of the states. Assuming the Government of India approximate 2030 targets, the median marginal CO2 emission factor across states decreases by approximately a factor of 2, but emission factors still span 3 orders of magnitude across states. Under 2030-2031 assumptions there is greater seasonal and intraday variability by up to factors of two and four, respectively. Estimates provide emission factors to evaluate interventions such as electric vehicles, increased air conditioning, and energy efficiency.

Spatial Correlation of Ultrafine Particle Number and Fine Particle Mass at Urban Scales: Implications for Health Assessment.

The epidemiological evidence for ultrafine particles (UFP; particles with diameter <100 nm) causing chronic health effects independent of fine particulate matter (PM2.5) mass is inconclusive. A prevailing view is that urban UFP and PM2.5 mass have different spatial patterns, which should allow epidemiological studies to distinguish their independent, chronic health effects. We investigate intraurban spatial correlation of PM2.5 and UFP exposures in Pittsburgh, Pennsylvania. Measurements and predictions of a land-use regression model indicate moderate spatial correlation between particle number concentrations (PNC; a proxy for UFP) and PM2.5 (R2 of 0.38 and 0.41, respectively). High-resolution (1-km) chemical transport model simulations predict stronger spatial correlation (R2 ≈ 0.8). The finding of moderate to strong spatial correlation was initially surprising because secondary aerosol contributes the vast majority of PM2.5 mass. However, intraurban spatial patterns of both PNC and PM2.5 are driven by local emissions and both pollutants largely behave as passive tracers at time scales of 1 day or less required for transport across most urban environments. Although previous research has shown little temporal correlation between PNC and PM2.5, our finding of moderate to strong spatial correlation may complicate epidemiological analyses to separate the chronic health effects of PNC from PM2.5 mass.