Sherman, Peter

2023
Xinyang Guo, Xinyu Chen, Xia Chen, Peter Sherman, Jinyu Wen, and Michael McElroy. 2023. “Grid integration feasibility and investment planning of offshore wind power under carbon-neutral transition in China.” Nature Communications, 14, 2447. Publisher's VersionAbstract
Offshore wind power, with accelerated declining levelized costs, is emerging as a critical building-block to fully decarbonize the world’s largest CO2 emitter, China. However, system integration barriers as well as system balancing costs have not been quantified yet. Here we develop a bottom-up model to test the grid accommodation capabilities and design the optimal investment plans for offshore wind power considering resource distributions, hourly power system simulations, and transmission/storage/hydrogen investments. Results indicate that grid integration barriers exist currently at the provincial level. For 2030, optimized offshore wind investment levels should be doubled compared with current government plans, and provincial allocations should be significantly improved considering both resource quality and grid conditions. For 2050, offshore wind capacity in China could reach as high as 1500 GW, prompting a paradigm shift in national transmission structure, favoring long-term storage in the energy portfolio, enabling green hydrogen production in coastal demand centers, resulting in the world’s largest wind power market.
2022
Shaojie Song, Haiyang Lin, Peter Sherman, Xi Yang, Shi Chen, Xi Lu, Tianguang Lu, Xinyu Chen, and Michael B. McElroy. 2022. “Deep decarbonization of the Indian economy: 2050 prospects for wind, solar, and green hydrogen.” iScience, 25, 6, Pp. 104399. Publisher's VersionAbstract
The paper explores options for a 2050 carbon free energy future for India. Onshore wind and solar sources are projected as the dominant primary contributions to this objective. The analysis envisages an important role for so-called green hydrogen produced by electrolysis fueled by these carbon free energy sources. This hydrogen source can be used to accommodate for the intrinsic variability of wind and solar complementing opportunities for storage of power by batteries and pumped hydro. The green source of hydrogen can be used also to supplant current industrial uses of gray hydrogen produced in the Indian context largely from natural gas with important related emissions of CO2. The paper explores further options for use of green hydrogen to lower emissions from otherwise difficult to abate sectors of both industry and transport. The analysis is applied to identify the least cost options to meet India’s zero carbon future.
Peter Sherman, Haiyang Lin, and Michael B. McElroy. 2022. “Projected global demand for air conditioning associated with extreme heat and implications for electricity grids in poorer countries.” Energy and Buildings, 268, August, Pp. 112198. Publisher's VersionAbstract

Human-induced climate change will increase surface temperatures globally over the next several decades. Climate models project that global mean surface temperature could increase by over 2˚C by 2050 relative to the preindustrial period, with even greater changes at the regional level. These temperature changes have clear and pertinent implications for extremes, and consequentially, heat-induced health issues for people living in particularly hot climates. Here, we study future projections in the demand for AC globally in the 2050s associated with extreme heat events. To do this, we employ an ensemble of CMIP6 models under high and low emissions scenarios. We find that the increasing frequency of extreme temperatures will cause a significant portion of the global population to be exposed to conditions that require cooling. This issue will be especially pervasive in poor countries such as India and Indonesia, which at present lack the AC units required to handle rapidly growing populations and increased frequencies of extreme temperatures. The electricity needed for cooling in these countries could reach as high as 75% of the current total annual electricity demand, which could place serious strain on the electricity grid infrastructure during peak cooling hours. We conclude that demand for cooling in the future will pose a significant challenge for poorer countries whose people will require AC units to handle extreme temperatures. In some countries, the grid infrastructure is insufficient at present to meet projected AC demands, and this need must be considered in future power systems planning.

2021
Shaojie Song, Haiyang Lin, Peter Sherman, Xi Yang, Chris P. Nielsen, Xinyu Chen, and Michael B. McElroy. 2021. “Production of hydrogen from offshore wind in China and cost-competitive supply to Japan.” Nature Communications, 12, 6953. Publisher's VersionAbstract
The Japanese government has announced a commitment to net-zero greenhouse gas emissions by 2050. It envisages an important role for hydrogen in the nation’s future energy economy. This paper explores the possibility that a significant source for this hydrogen could be produced by electrolysis fueled by power generated from offshore wind in China. Hydrogen could be delivered to Japan either as liquid, or bound to a chemical carrier such as toluene, or as a component of ammonia. The paper presents an analysis of factors determining the ultimate cost for this hydrogen, including expenses for production, storage, conversion, transport, and treatment at the destination. It concludes that the Chinese source could be delivered at a volume and cost consistent with Japan’s idealized future projections.
Jonathan D'Souza, Felix Prasanna, Luna-Nefeli Valayannopoulos-Akrivou, Peter John Sherman, Elise Penn, Shaojie Song, Alexander Archibald, and Michael B McElroy. 2021. “Projected changes in seasonal and extreme summertime temperature and precipitation in India in response to COVID-19 recovery emissions scenarios.” Environmental Research Letters, 16, Pp. 114025. Publisher's VersionAbstract
Fossil fuel and aerosol emissions have played important roles on climate over the Indian subcontinent over the last century. As the world transitions toward decarbonization in the next few decades, emissions pathways could have major impacts on India's climate and people. Pathways for future emissions are highly uncertain, particularly at present as countries recover from COVID-19. This paper explores a multimodel ensemble of Earth system models leveraging potential global emissions pathways following COVID-19 and the consequences for India's summertime (June-July-August-September) climate in the near- and long-term. We investigate specifically scenarios which envisage a fossil-based recovery, a strong renewable-based recovery and a moderate scenario in between the two. We find that near-term climate changes are dominated by natural climate variability, and thus likely independent of the emissions pathway. By 2050, pathway-induced spatial patterns in the seasonally-aggregated precipitation become clearer with a drying in the fossil-based scenario and wetting in the strong renewable scenario. Additionally, extreme temperature and precipitation events in India are expected to increase in magnitude and frequency regardless of the emissions scenario, though the spatial patterns of these changes as well as the extent of the change are pathway dependent. This study provides an important discussion on the impacts of emissions recover pathways following COVID-19 on India, a nation which is likely to be particularly susceptible to climate change over the coming decades.
Peter Sherman, Shaojie Song, Xinyu Chen, and Michael B. McElroy. 2021. “Projected changes in wind power potential over China and India in high resolution climate models.” Environmental Research Letters, 16, 3, Pp. 034057. Publisher's VersionAbstract
As more countries commit to emissions reductions by midcentury to curb anthropogenic climate change, decarbonization of the electricity sector becomes a first-order task in reaching this goal. Renewables, particularly wind and solar power, will be predominant components of this transition. How availability of the wind and solar resource will change in the future in response to regional climate changes is an important and underdiscussed topic of the decarbonization process. Here, we study changes in potential for wind power in China and India, evaluating prospectively until the year 2060. To do this, we study a downscaled, high-resolution multimodel ensemble of CMIP5 models under high and low emissions scenarios. While there is some intermodel variability, we find that spatial changes are generally consistent across models, with decreases of up to 965 (a 1% change) and 186 TWh (a 2% change) in annual electricity generation potential for China and India, respectively. Compensating for the declining resource are weakened seasonal and diurnal variabilities, allowing for easier large-scale wind power integration. We conclude that while the ensemble indicates available wind resource over China and India will decline slightly in the future, there remains enormous potential for significant wind power expansion, which must play a major role in carbon neutral aspirations.
Peter Sherman, Meng Gao, Shaojie Song, Alex T. Archibald, Nathan Luke Abraham, Jean-François Lamarque, Drew Shindell, Gregory Faluvegi, and Michael B. McElroy. 2021. “Sensitivity of modeled Indian Monsoon to Chinese and Indian aerosol emissions.” Atmospheric Chemistry and Physics, 21, 5, Pp. 3593–3605. Publisher's VersionAbstract
The South Asian summer monsoon supplies over 80 % of India's precipitation. Industrialization over the past few decades has resulted in severe aerosol pollution in India. Understanding monsoonal sensitivity to aerosol emissions in general circulation models (GCMs) could improve predictability of observed future precipitation changes. The aims here are (1) to assess the role of aerosols on India's monsoon precipitation and (2) to determine the roles of local and regional emissions. For (1), we study the Precipitation Driver Response Model Intercomparison Project experiments. We find that the precipitation response to changes in black carbon is highly uncertain with a large intermodel spread due in part to model differences in simulating changes in cloud vertical profiles. Effects from sulfate are clearer; increased sulfate reduces Indian precipitation, a consistency through all of the models studied here. For (2), we study bespoke simulations, with reduced Chinese and/or Indian emissions in three GCMs. A significant increase in precipitation (up to ~ 20 %) is found only when both countries' sulfur emissions are regulated, which has been driven in large part by dynamic shifts in the location of convective regions in India. These changes have the potential to restore a portion of the precipitation losses induced by sulfate forcing over the last few decades.
2020
Meng Gao, Zirui Liu, Bo Zheng, Dongsheng Ji, Peter Sherman, Shaojie Song, Jinyuan Xin, Cheng Liu, Yuesi Wang, Qiang Zhang, Jia Xing, Jingkun Jiang, Zifa Wang, Gregory R. Carmichael, and Michael B. McElroy. 2020. “China's emission control strategies have suppressed unfavorable influences of climate on wintertime PM2.5 concentrations in Beijing since 2002.” Atmospheric Chemistry and Physics, 20, 3, Pp. 1497-1505. Publisher's VersionAbstract
Severe wintertime PM2.5 pollution in Beijing has been receiving increasing worldwide attention, yet the decadal variations remain relatively unexplored. Combining field measurements and model simulations, we quantified the relative influences of anthropogenic emissions and meteorological conditions on PM2.5 concentrations in Beijing over the winters of 2002–2016. Between the winters of 2011 and 2016, stringent emission control measures resulted in a 21 % decrease in mean mass concentrations of PM2.5 in Beijing, with 7 fewer haze days per winter on average. Given the overestimation of PM2.5 by the model, the effectiveness of stringent emission control measures might have been slightly overstated. With fixed emissions, meteorological conditions over the study period would have led to an increase in haze in Beijing, but the strict emission control measures have suppressed the unfavorable influences of the recent climate. The unfavorable meteorological conditions are attributed to the weakening of the East Asia winter monsoon associated particularly with an increase in pressure associated with the Aleutian Low.
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Peter Sherman, Eli Tziperman, Clara Deser, and Michael B. McElroy. 2020. “Historical and future roles of internal atmospheric variability in modulating summertime Greenland Ice Sheet melt.” Geophysical Research Letters, 47, 6, Pp. e2019GL086913. Publisher's VersionAbstract
Understanding how internal atmospheric variability affects Greenland Ice Sheet (GrIS) summertime melting would improve understanding of future sea level rise. We analyze the Community Earth System Model Large Ensemble (CESM‐LE) over 1951‐2000 and 2051‐2100. We find that internal variability dominates the forced response on short timescales (~20 years) and that the area impacted by internal variability grows in the future, connecting internal variability and climate change. Unlike prior studies, we do not assume specific patterns of internal variability to affect GrIS melting, but derive them from Maximum Covariance Analysis. We find that the North Atlantic Oscillation (NAO) is the major source of internal atmospheric variability associated with GrIS melt conditions in CESM‐LE and reanalysis, with the positive phase (NAO+) linked to widespread cooling over the ice sheet. CESM‐LE and CMIP5 project an increase in the frequency of NAO+ events, suggesting a negative feedback to the GrIS under future climate change.
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Tianguang Lu, Peter Sherman, Xinyu Chen, Shi Chen, Xi Lu, and Michael B. McElroy. 2020. “India’s potential for integrating solar and on- and offshore wind power into its energy system.” Nature Communications, 11, 4750. Publisher's VersionAbstract
This paper considers options for a future Indian power economy in which renewables, wind and solar, could meet 80% of anticipated 2040 power demand supplanting the country’s current reliance on coal. Using a cost optimization model, here we show that renewables could provide a source of power cheaper or at least competitive with what could be supplied using fossil-based alternatives. The ancillary advantage would be a significant reduction in India’s future power sector related emissions of CO2. Using a model in which prices for wind turbines and solar PV systems are assumed to continue their current decreasing trend, we conclude that an investment in renewables at a level consistent with meeting 80% of projected 2040 power demand could result in a reduction of 85% in emissions of CO2 relative to what might be expected if the power sector were to continue its current coal dominated trajectory.
Peter Sherman, Xinyu Chen, and Michael B. McElroy. 2020. “Offshore wind: an opportunity for cost-competitive decarbonization of China’s energy economy.” Science Advances, 6, 8, Pp. eaax9571. Publisher's VersionAbstract
China has reduced growth in its emissions of greenhouse gases, success attributable in part due to major investments in onshore wind. By comparison, investments in offshore wind have been minor, limited until recently largely by perceptions of cost. Assimilated meteorological data are used here to assess future offshore wind potential for China. Analysis on a provincial basis indicates that the aggregate potential wind resource is 5.4 times larger than current coastal demand for power. Recent experiences with markets both in Europe and the US suggest that potential offshore resources in China could be exploited to cost-competitively provide 1148.3 TWh of energy in a high-cost scenario, 6383.4 TWh in a low-cost option, equivalent to between 36% and 200% of the total coastal energy demand post 2020. The analysis underscores significant benefits for offshore wind for China, with prospects for major reductions greenhouse emissions with ancillary benefits for air quality.
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Meng Gao, Jinhui Gao, Bin Zhu, Rajesh Kumar, Xiao Lu, Shaojie Song, Yuzhong Zhang, Beixi Jia, Peng Wang, Gufran Beig, Jianlin Hu, Qi Ying, Hongliang Zhang, Peter Sherman, and Michael B. McElroy. 2020. “Ozone pollution over China and India: seasonality and sources.” Atmospheric Chemistry and Physics, 20, 7, Pp. 4399-4414. Publisher's VersionAbstract
A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India. Observations and model results suggest that O3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O3 control strategies.
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2019
Peter Sherman, Meng Gao, Shaojie Song, Patrick Ohiomoba, Alex Archibald, and Michael B. McElroy. 2019. “The influence of dynamics and emissions changes on China’s wintertime haze.” Journal of Applied Meteorology and Climatology, 58, 7, Pp. 1603-1611. Publisher's VersionAbstract

Haze days induced by aerosol pollution in North and East China have posed a persistent and growing problem over the past few decades. These events are particularly threatening to densely-populated cities such as Beijing. While the sources of this pollution are predominantly anthropogenic, natural climate variations may also play a role in allowing for atmospheric conditions conducive to formation of severe haze episodes over populated areas. Here, an investigation is conducted into the effects of changes in global dynamics and emissions on air quality in China’s polluted regions using 35 simulations developed from the Community Earth Systems Model Large Ensemble (CESM LENS) run over the period 1920-2100. It is shown that internal variability significantly modulates aerosol optical depth (AOD) over China; it takes roughly a decade for the forced response to balance the effects from internal variability even in China’s most polluted regions. Random forest regressions are used to accurately model (R2 > 0.9) wintertime AOD using just climate oscillations, the month of the year and emissions. How different phases of each oscillation affect aerosol loading are projected using these regressions. AOD responses are identified for each oscillation, with particularly strong responses from El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). As ENSO can be projected a few months in advance and improvements in linear inverse modelling (LIM) may yield a similar predictability for the PDO, results of this study offer opportunities to improve the predictability of China’s severe wintertime haze events, and to inform policy options that could mitigate subsequent health impacts.

JAMC paper
Meng Gao, Peter Sherman, Shaojie Song, Yueyue Yu, Zhiwei Wu, and Michael B. McElroy. 2019. “Seasonal prediction of Indian wintertime aerosol pollution using the Ocean Memory Effect.” Science Advances, 5, 7. Publisher's VersionAbstract
As China makes every effort to control air pollution, India emerges as the world’s most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulated mainly by a combination of El Niño and the Antarctic Oscillation (AAO). Both El Niño sea surface temperature (SST) anomalies and AAO-induced Indian Ocean Meridional Dipole SST anomalies can persist from autumn to winter, offering prospects for a prewinter forecast of wintertime aerosol pollution over northern India. We constructed a multivariable regression model incorporating El Niño and AAO indices for autumn to predict wintertime AOD. The prediction exhibits a high degree of consistency with observation, with a correlation coefficient of 0.78 (P < 0.01). This statistical model could allow the Indian government to forecast aerosol pollution conditions in winter and accordingly improve plans for pollution control.
Science_Advances_Paper.pdf
2017
Peter Sherman, Xinyu Chen, and Michael B. McElroy. 2017. “Wind-generated electricity in China: Decreasing potential, inter-annual variability, and association with climate change.” Scientific Reports, 7. Publisher's VersionAbstract
China hosts the world’s largest market for wind-generated electricity. The financial return and carbon reduction benefits from wind power are sensitive to changing wind resources. Wind data derived from an assimilated meteorological database are used here to estimate what the wind generated electricity in China would have been on an hourly basis over the period 1979 to 2015 at a geographical resolution of approximately 50 km × 50 km. The analysis indicates a secular decrease in generating potential over this interval, with the largest declines observed for western Inner Mongolia (15 ± 7%) and the northern part of Gansu (17 ± 8%), two leading wind investment areas. The decrease is associated with long-term warming in the vicinity of the Siberian High (SH), correlated also with the observed secular increase in global average surface temperatures. The long-term trend is modulated by variability relating to the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO). A linear regression model incorporating indices for the PDO and AO, as well as the declining trend, can account for the interannual variability of wind power, suggesting that advances in long-term forecasting could be exploited to markedly improve management of future energy systems.
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