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1. Inequality in air pollution mortality from power generation in India

   https://doi.org/10.1088/1748-9326/aca8bb  

   Sengupta, Shayak ; Thakrar, Sumil K. ; Singh, Kirat ; Tongia, Rahul ; Hill, Jason D. ; Azevedo, Ines M. L. ; Adams, Peter J. ( December 2022 , Environmental Research Letters)

   India’s coal-heavy electricity system is the world’s third largest and a major emitter of air pollution and greenhouse gas emissions. Consequently, it remains a focus of decarbonization and air pollution control policy. Considerable heterogeneity exists between states in India in terms of electricity demand, generation fuel mix, and emissions. However, no analysis has disentangled the expected, state-level spatial differences and interactions in air pollution mortality under current and future power sector policies in India. We use a reduced-complexity air quality model to evaluate annual PM_2.5mortalities associated with electricity production and consumption in each state in India. Furthermore, we test emissions control, carbon tax, and market integration policies to understand how changes in power sector operations affect ambient PM_2.5concentrations and associated mortality. We find poorer, coal-dependent states in eastern India disproportionately face the burden of PM_2.5mortality from electricity in India by importing deaths. Wealthier, high renewable energy states in western and southern India meanwhile face a lower burden by exporting deaths. This suggests that as these states have adopted more renewable generation, they have shifted their coal generation and associated PM_2.5mortality to eastern areas. We also find widespread sulfur emissions control decreases mortality by about 50%. Likewise, increasing carbon taxes in the short term reduces annual mortality by up to 9%. Market reform where generators between states pool to meet demand reduces annual mortality by up to 8%. As India looks to increase renewable energy, implement emissions control regulations, establish a carbon trading market, and move towards further power market integration, our results provide greater spatial detail for a federally structured Indian electricity system.

    

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2. What are the best combinations of fuel-vehicle technologies to mitigate climate change and air pollution effects across the United States?

   https://doi.org/10.1088/1748-9326/ab8a85  

   Tong, Fan ; Azevedo, Inês M. L. ( July 2020 , Environmental Research Letters)

   The transportation sector is the largest contributor to CO₂emissions and a major source of criteria air pollutants in the United States. The impact of climate change and that of air pollution differ in space and time, but spatially-explicit, systematic evaluations of the effectiveness of alternative fuels and advanced vehicle technologies in mitigating both climate change and air pollution are lacking. In this work, we estimate the life cycle monetized damages due to greenhouse gas emissions and criteria air pollutant emissions for different types of passenger-moving vehicles in the United States. We find substantial spatial variability in the monetized damages for all fuel-vehicle technologies studied. None of the fuel-vehicle technologies leads simultaneously to the lowest climate change damages and the lowest air pollution damages across all U.S. counties. Instead, the fuel-vehicle technology that best mitigates climate change in one region is different from that for the best air quality (i.e. the trade-off between decarbonization and air pollution mitigation). For example, for the state of Pennsylvania, battery-electric cars lead to the lowest population-weighted-average climate change damages (a climate change damage of 0.87 cent/mile and an air pollution damage of 1.71 cent/mile). In contrast, gasoline hybrid-electric cars lead to the lowest population-weighted-average air pollution damages (a climate change damage of 0.92 cent/mile and an air pollution damage of 0.77 cent/mile). Vehicle electrification has great potential to reduce climate change damages but may increase air pollution damages substantially in regions with high shares of coal-fired power plants compared to conventional vehicles. However, clean electricity grid could help battery electric vehicles to achieve low damages in both climate change and air pollution.

    

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3. Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption

   https://doi.org/10.1038/s41560-022-01105-7  

   Powell, Siobhan ; Cezar, Gustavo Vianna ; Min, Liang ; Azevedo, Inês M. L. ; Rajagopal, Ram ( September 2022 , Nature Energy)

   Electric vehicles will contribute to emissions reductions in the United States, but their charging may challenge electricity grid operations. We present a data-driven, realistic model of charging demand that captures the diverse charging behaviours of future adopters in the US Western Interconnection. We study charging control and infrastructure build-out as critical factors shaping charging load and evaluate grid impact under rapid electric vehicle adoption with a detailed economic dispatch model of 2035 generation. We find that peak net electricity demand increases by up to 25% with forecast adoption and by 50% in a stress test with full electrification. Locally optimized controls and high home charging can strain the grid. Shifting instead to uncontrolled, daytime charging can reduce storage requirements, excess non-fossil fuel generation, ramping and emissions. Our results urge policymakers to reflect generation-level impacts in utility rates and deploy charging infrastructure that promotes a shift from home to daytime charging.

    

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4. Probabilistic projections of baseline twenty-first century CO2 emissions using a simple calibrated integrated assessment model

   https://doi.org/10.1007/s10584-021-03279-7  

   Srikrishnan, Vivek ; Guan, Yawen ; Tol, Richard S. J. ; Keller, Klaus ( February 2022 , Climatic Change)

   Probabilistic projections of baseline (with no additional mitigation policies) future carbon emissions are important for sound climate risk assessments. Deep uncertainty surrounds many drivers of projected emissions. Here, we use a simple integrated assessment model, calibrated to century-scale data and expert assessments of baseline emissions, global economic growth, and population growth, to make probabilistic projections of carbon emissions through 2100. Under a variety of assumptions about fossil fuel resource levels and decarbonization rates, our projections largely agree with several emissions projections under current policy conditions. Our global sensitivity analysis identifies several key economic drivers of uncertainty in future emissions and shows important higher-level interactions between economic and technological parameters, while population uncertainties are less important. Our analysis also projects relatively low global economic growth rates over the remainder of the century. This illustrates the importance of additional research into economic growth dynamics for climate risk assessment, especially if pledged and future climate mitigation policies are weakened or have delayed implementations. These results showcase the power of using a simple, transparent, and calibrated model. While the simple model structure has several advantages, it also creates caveats for our results which are related to important areas for further research.

    

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5. Analyzing the Impact of Decarbonizing Residential Heating on the Electric Distribution Grid

   https://doi.org/10.1145/3607114.3607119  

   Wamburu, John ; Bashir, Noman ; Irwin, David ; Shenoy, Prashant ( June 2023 , ACM SIGEnergy Energy Informatics Review)

   Heating buildings using fossil fuels such as natural gas, propane and oil makes up a significant proportion of the aggregate carbon emissions every year. Because of this, there is a strong interest in decarbonizing residential heating systems using new technologies such as electric heat pumps. In this paper, we conduct a data-driven optimization study to analyze the potential of replacing gas heating with electric heat pumps to reduce CO 2 emission in a city-wide distribution grid. We conduct an in-depth analysis of gas consumption in the city and the resulting carbon emissions. We then present a flexible multi-objective optimization (MOO) framework that optimizes carbon emission reduction while also maximizing other aspects of the energy transition such as carbon-efficiency, and minimizing energy inefficiency in buildings. Our results show that replacing gas with electric heat pumps has the potential to cut carbon emissions by up to 81%. We also show that optimizing for other aspects such as carbon-efficiency and energy inefficiency introduces tradeoffs with carbon emission reduction that must be considered during transition. Finally, we present a detailed analysis of the implication of proposed transition strategies on the household energy consumption and utility bills, electric grid upgrades, and decarbonization policies. We compute the additional energy demand from electric heat pumps at the household as well as the transformer level and discuss how our results can inform decarbonization policies at city scale. 

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