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Meng Gao, Gufran Beig, Shaojie Song, Hongliang Zhang, Jianlin Hu, Qi Ying, Fengchao Liang, Yang Liu, Haikun Wang, Xiao Lu, Tong Zhu, Gregory Carmichael, Chris P. Nielsen, and Michael B. McElroy. 2018. “The Impact of Power Generation Emissions on Ambient PM2.5 Pollution and Human Health in China and India.” Environment International, 121, Part 1, Pp. 250-259. Publisher's VersionAbstract

Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM≤2.5 micrometers in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.

 

yu_hang_zheng_jian_zhao_.jpg

Hang Yu

Fellow, Harvard-China Project
Ph.D. Student, School of Economics, Peking University
Pierce Hall G2B, 29 Oxford St., Cambridge, MA
yuhang_econ@pku.edu.cn
Jing

Commentary: Can Unlucky Number 4 Be Lucky Too? How the Chinese Superstition About “4” Made Possible a Study on the Health Effects of Air Pollution in Beijing

August 14, 2018

It is rarely possible to conduct controlled experiments in the social sciences owing to the vast number of variables that, in a “real-world” setting, can almost never be manipulated to create the ideal experimental conditions. However, there are occasionally instances when the unintended effects of certain policies create circumstances that are like an experiment, called a natural experiment. When the combination of a vehicle restriction policy in Beijing and the Chinese superstition about the...

Read more about Commentary: Can Unlucky Number 4 Be Lucky Too? How the Chinese Superstition About “4” Made Possible a Study on the Health Effects of Air Pollution in Beijing
Govinda R. Timilsina, Jing Cao, and Mun S. Ho. 2018. “Carbon Tax for Achieving China's NDC: Simulations of Some Design Features Using a CGE Model.” Climate Change Economics, 9, 3. Publisher's VersionAbstract
China has set a goal of reducing its CO2 intensity of GDP by 60–65% from the 2005 level in 2030 as its nationally determined contribution (NDC) under the Paris Climate Change Agreement. While the government is considering series of market and nonmarket measures to achieve its target, this study assesses the economic consequences if the target were to meet through a market mechanism, carbon tax. We used a dynamic computable general equilibrium model of China for the analysis. The study shows that the level of carbon tax to achieve the NDC target would be different depending on its design features. An increasing carbon tax that starts at a small rate in 2015 and rises to a level to meet the NDC target in 2030 would cause smaller GDP loss than the carbon tax with a constant rate would do. The GDP loss due to the carbon tax would be smaller when the tax revenue is utilized to cut existing distortionary taxes than when it is transferred to households as a lump-sum rebate.
Xinyu Chen, Jiajun Lv, Michael B. McElroy, Xingning Han, Chris Nielsen, and Jinyu Wen. 2018. “Power system capacity expansion under higher penetration of renewables considering flexibility constraints and low carbon policies.” IEEE Transactions on Power Systems. Publisher's VersionAbstract
Deploying high penetration of variable renewables represents a critical pathway for deep decarbonizing the power sector. The conflict between their temporal variability and limited system flexibility has been largely ignored currently at planning stage. Here we present a novel capacity expansion model optimizing investment decisions and full-year, hourly power balances simultaneously, with considerations of storage technologies and policy constraints, such as carbon tax and renewable portfolio standards (RPS). Based on a computational efficient modeling formulation, all flexibility constrains (ramping, reserve, minimum output, minimal online/offline time) for the 8760-hour duration are incorporated. The proposed model is applied to the northwestern grid of China to examine the optimal composition and distribution of power investments with a wide range of renewable targets. Results indicate that the cost can increase moderately towards 45% of RPS, when properly designing the generation portfolio: prioritizing wind investments, distributing renewable investments more evenly and deploying more flexible mid-size coal and gas units. Reaching higher penetrations of renewables is expensive and the reductions of storage costs are critically important for an affordable low-carbon future. RPS or carbon taxes to reach a same target of emission reduction in China will result in similar overall costs but different generation mixes.
EV in China

Financial Times Cites Recent China Project Study Exploring Environmental Implications of Electric Vehicle Charging in China

May 23, 2018

A Financial Times article examining the sometimes-ambiguous environmental benefits of electric vehicles in China, whose energy market has yet to fully transition out of being fossil fuel-dominated, cites the findings of a China Project study... Read more about Financial Times Cites Recent China Project Study Exploring Environmental Implications of Electric Vehicle Charging in China

China Project Spring 2018 Newsletter

China Project Spring 2018 Newsletter

May 22, 2018

This spring the Harvard-China Project continued its investigations of the “China 2030/2050” theme sponsored by the Harvard Global Institute (HGI). Our community explored a number of pressing issues, including a Nature Energy paper on the environmental implications of electric vehicle charging in China. The research, which offers a strategy for reducing CO2 emissions and improving air quality with electric vehicles in Beijing, was authored by a Harvard-Tsinghua...

Read more about China Project Spring 2018 Newsletter

Commentary: Does the path to a low-carbon future run through a global grid?

May 21, 2018

satelliteBy Jonathan Mingle

Imagine flipping a switch and lighting your home with hydropower from southern Brazil, solar power from the Sahara Desert, or wind power from the High Arctic. If Liu Zhenya’s plan comes to fruition, sourcing clean energy from the farthest reaches of the globe could become just that routine for billions of electricity users by 2050.... Read more about Commentary: Does the path to a low-carbon future run through a global grid?

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The Harvard-China Project receives major support from the Harvard Global Institute on the theme of 'China 2030/2050: Energy and Environmental Challenges for the Future.'

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