Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 C target could avoid ~118,000 and ~614,000 PM2.5 attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393–$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries.
China, with a heavy dependence on coal power, has announced a clear goal of carbon neutrality by 2060. Electrification of final energy use and high penetration of renewable energy are essential to achieve this. The resulting growth of intermittent renewables and changes in demand curve profiles require greater flexibility in the power system for real-time balancing – greater ability of generators and consumers to ramp up and down. However, the plan and market system with regulated prices makes this challenging. We discuss the options to improve flexibility, including 1) increasing supply-side flexibility, through retrofitting existing power plants to boost their responsiveness; 2) promoting flexibility from power grids, through building an efficient power grid with inter-provincial and inter-regional transmission capacity to balance spatial mismatch, given that China has a vast territory; 3) encouraging demand flexibility, through demand-response measures to enable demand shifting over time and space to address fluctuations in renewable energy generation; and 4) providing flexibility from energy storage. We consider policies to achieve this, in particular, power market reforms to unlock the flexibility potential of these sources. Regulated electricity prices and lack of auxiliary services markets are major obstacles and we discuss how markets in other countries provide lessons in providing incentives for a more flexible system.
China forecasts that a 14-fold increase in photovoltaic installations is needed to meet 2060 carbon-neutrality targets. In light of the fact that air pollution impairs photovoltaic performance, pollution control could reduce the installation requirement, but research has not yet taken into account the coeval impact of unfavorable meteorological conditions, which also impair performance. Here, we employ a coupled model to determine the impact of air-pollution control policies on China’s photovoltaic power output in the presence of varying meteorological conditions between 1995 and 2019. We find that the benefits of air-pollution control introduced in 2004 were only partially offset by unfavorable meteorological conditions (primarily in Central and South China) and resulted in solar-power performance improvement of 0.9%/decade from 2008 onward. Further analysis shows that solar-power output in 2020 was 1.7% higher thanks to air-pollution control and that more stringent air-quality targets could reduce the demand for photovoltaic installed capacity needed to meet the 2060 carbon-neutrality target.
The rapidly falling costs of renewable energy has made them the focus of efforts in making a low-carbon transition. However, when cheap large-scale energy storage is not available, the variability of renewables implies that fossil-based technologies have to ramp up-and-down frequently to provide flexibility for matching electricity demand and supply. Here we provide a study on the indirect cost of renewable energy due to thermal efficiency loss of coal plants with such ramping requirements. Using monthly panel data for China, we show that higher renewable share is associated with fewer operating hours of coal-fired units (COHOUR). We use an instrumental variable depending on natural river flows to identify the causal effect of reduced COHOURs in raising the heat rate of coal-fired units. Specifically, a 1 percentage point increase in the share of renewables leads to a 6.4 h reduction per month, and a reduction of one COHOUR results in a 0.09 gce/kWh increase of gross heat rate (+0.03%). We estimate that the thermal efficiency loss indicates 4.77 billion US dollars of indirect cost of renewables in 2019, or 9.44 billion if we include the social cost of carbon emissions. These results indicate that we should consider the indirect impacts of renewables on total coal use and the importance of increasing flexibility of the system.
As the world’s largest CO2 emitter, China’s ability to decarbonize its energy system strongly affects the prospect of achieving the 1.5 °C limit in global, average surface-temperature rise. Understanding technically feasible, cost-competitive, and grid-compatible solar photovoltaic (PV) power potentials spatiotemporally is critical for China’s future energy pathway. This study develops an integrated model to evaluate the spatiotemporal evolution of the technology-economic-grid PV potentials in China during 2020 to 2060 under the assumption of continued cost degression in line with the trends of the past decade. The model considers the spatialized technical constraints, up-to-date economic parameters, and dynamic hourly interactions with the power grid. In contrast to the PV production of 0.26 PWh in 2020, results suggest that China’s technical potential will increase from 99.2 PWh in 2020 to 146.1 PWh in 2060 along with technical advances, and the national average power price could decrease from 4.9 to 0.4 US cents/kWh during the same period. About 78.6% (79.7 PWh) of China’s technical potential will realize price parity to coal-fired power in 2021, with price parity achieved nationwide by 2023. The cost advantage of solar PV allows for coupling with storage to generate cost-competitive and grid-compatible electricity. The combined systems potentially could supply 7.2 PWh of grid-compatible electricity in 2060 to meet 43.2% of the country’s electricity demand at a price below 2.5 US cents/kWh. The findings highlight a crucial energy transition point, not only for China but for other countries, at which combined solar power and storage systems become a cheaper alternative to coal-fired electricity and a more grid-compatible option.
China, the largest global CO2 emitter, recently announced ambitious targets for carbon neutrality by 2060. Its technical and economic feasibility is unclear given severe renewable integration barriers. Here, we developed a cross-sector, high-resolution assessment model to quantify optimal energy structures on provincial bases for different years. Hourly power system simulations for all provinces for a full year are incorporated on the basis of comprehensive grid data to quantify the renewable balancing costs. Results indicate that the conventional strategy of employing local wind, solar, and storage to realize 80% renewable penetration by 2050 would incur a formidable decarbonization cost of $27/ton despite lower levelized costs for renewables. Coordinated deployment of renewables, ultra-high-voltage transmissions, storages, Power-to-gas and slow-charging electric vehicles can reduce this carbon abatement cost to as low as $−25/ton. Were remaining emissions removed by carbon capture and sequestration technologies, achieving carbon neutrality could be not only feasible but also cost-competitive post 2050.
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.
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.
This paper provides retrospective firm-level evidence on the effectiveness of China’s carbon market pilots in reducing emissions in the electricity sector. We show that the carbon emission trading system (ETS) has no effect on changing coal efficiency of regulated coal- fired power plants. Although we find a significant reduction in coal consumption associated with ETS participation, this reduction was achieved by reducing electricity production. The output contraction in the treated plants is not due to their optimizing behavior but is likely driven by government decisions, because the impacts of emission permits on marginal costs are small relative to the controlled electricity prices and the reduction is associated with financial losses. In addition, we find no evidence of carbon leakage to other provinces, but a significant increase in the production of non-coal-fired power plants in the ETS regions.
To evaluate the improved emission estimates from online monitoring, we applied the Models-3/CMAQ (Community Multiscale Air Quality) system to simulate the air quality of the Yangtze River Delta (YRD) region using two emission inventories with and without incorporated data from continuous emission monitoring systems (CEMSs) at coal-fired power plants (cases 1 and 2, respectively). The normalized mean biases (NMBs) between the observed and simulated hourly concentrations of SO2, NO2, O3, and PM2.5in case 2 were−3.1 %, 56.3 %,−19.5 %, and−1.4 %, all smaller in absolute value than those in case 1 at 8.2 %, 68.9 %,−24.6 %, and 7.6 %, respectively. The results indicate that incorporation of CEMS data in the emission inventory reduced the biases between simulation and observation and could better reflect the actual sources of regional air pollution. Based on the CEMS data, the air quality changes and corresponding health impacts were quantified for different implementation levels of China's recent “ultra-low” emission policy. If the coal-fired power sector met the requirement alone (case 3), the differences in the simulated monthly SO2, NO2, O3, and PM2.5concentrations compared to those of case 2, our base case for policy comparisons, would be less than 7 % for all pollutants. The result implies a minor benefit of ultra-low emission control if implemented in the power sector alone, which is attributed to its limited contribution to the total emissions in the YRD after years of pollution control (11 %, 7 %, and 2 % of SO2, NOX, and primary particle matter (PM) in case 2, respectively). If the ultra-low emission policy was enacted at both power plants and selected industrial sources including boilers, cement, and iron and steel factories (case 4), the simulated SO2, NO2, and PM2.5concentrations compared to the base case would be 33 %–64 %, 16 %–23 %, and 6 %–22 % lower, respectively, depending on the month (January, April, July, and October 2015). Combining CMAQ and the Integrated Exposure Response (IER) model, we further estimated that 305 deaths and 8744 years of life loss (YLL) attributable to PM2.5exposure could be avoided with the implementation of the ultra-low emission policy in the power sector in the YRD region. The analogous values would be much higher, at 10 651 deaths and 316 562 YLL avoided, if both power and industrial sectors met the ultra-low emission limits. In order to improve regional airquality and to reduce human health risk effectively, coordinated control of multiple sources should be implemented, and the ultra-low emission policy should be substantially expanded to major emission sources in industries other than the power industry.
A striking feature of urban formation has been the deployment of mega-blocks, often on the order of sixteen hectares or more. On the other hand, recent urban policies give strong suggestions for smaller and finer-grained neighborhood block and grid arrangements. This paper explores the transformation of urban block structures in high-density cities beyond spatial conditions of big versus small blocks by emphasizing “place” making through the degree of spatial diversity and flexibility. Using spatial indices of urban block arrangements, road network efficiencies and gradients of transit network accessibility, the assessment on urban neighborhood block structure is applied to territories of central core, suburban and peripheral development in Beijing, Shanghai and Shenzhen at multiple spatial scales. The results show that the overall efficiency and flexibility of urban block structures becomes more a matter of a narrowing of the range of differing block sizes among the three territories and a concomitant higher potential capacity for adaptation to a broader range of development options. Beyond the Chinese context, in high-density cities across the globe, policies on place making should adopt a multi-scale spatial analysis strategy to measure the configuration of the overall urban block structure and guide the transformation of the city.
Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration–response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM2.5- and O3-related mortality was expected to decline 23% or 289 (95% confidence interval: 220–360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM2.5 exposure under the national air quality standard (35 μg/m3) and WHO guideline (10 μg/m3) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O3 (100 μg/m3). Increased health impact of O3 suggested a great significance of joint control of PM2.5 and O3 in future policy-making.
Due to spatial heterogeneity worldwide, results from studies examining the effect of residential self-selection on travel behavior vary substantially. As a result of housing reform, the unique housing allocation system in China is a prime example of a context where the self-selection effect may conflict with international knowledge. Using a sample of 3836 residents, whom are living in Transit-Oriented Development (TOD) and non-TOD neighborhoods in Shanghai, this study untangles the effects that the built environment and residential self-selection have on travel behavior, in the context of diversified housing types in urban China. Specifically, this paper employs propensity score matching (PSM) to quantitate the relative importance of the built environment itself, verses residential self-selection, in influencing travel behavior for each of the housing types. The results show that the residential self-selection effect in the four types of housing (work-unit, commodity, public, and replacement) accounts for 15.2%, 30.7%, 18.5%, and 5.9% of the total impact on vehicle kilometers traveled (VKT), respectively. These findings expand the international database of point estimates in the relative contribution of self-selection toward the impact on travel behavior across global contexts, providing a comprehensive framework for similar studies on self-selection in other parts of the world.
Hydrogen can play a key role in facilitating the transition to a future deeply decarbonized energy system and can help accommodate higher penetrations of renewables in the power system. Arguments to justify this conclusion are supported by an analysis based on real-world data from China’s Western Inner Mongolia (WIM). The economic feasibility and decarbonization potential of renewable-based hydrogen production are discussed through an integrated power-hydrogen-emission analytical framework. The framework combines a high-resolution wind resource analysis with hourly simulation for the operation of power systems and hydrogen production considering technical and economic specifications on selection of three different types of electrolyzers and two operating modes. The results indicate that using wind power to produce hydrogen could provide a cost-competitive alternative (<2 $kg-1) to WIM’s current coal-dominated hydrogen manufacturing system, contributing at the same time to important reductions in wind curtailment and CO2 emissions. The levelized cost for hydrogen production is projected to decrease in the coming decade consistent with increases in wind power capacity and decreases in capital costs for electrolyzers. Lessons learned from the study can be applied to other regions and countries to explore possibilities for larger scale economically justified and carbon saving hydrogen production with renewables.
We conduct a multi-model comparison of a carbon tax policy in China to examine how different models simulate the impacts in both near-term 2020, medium-term 2030, and distant future 2050. Though Top-down computable general equilibrium(CGE) models have been applied frequently on climate or other environmental/energy policies to assess emission reduction, energy use and economy-wide general equilibrium outcomes in China, the results often vary greatly across models, making it challenging to derive policies. We compare 8 China CGE models with different characteristics to examine how they estimate the effects of a plausible range of carbon tax scenarios – low, medium and high carbon taxes.. To make them comparable we impose the same population growth, the same GDP growth path and world energy price shocks. We find that the 2030 NDC target for China are easily met in all models, but the 2060 carbon neutrality goal cannot be achieved even with our highest carbon tax rates. Through this carbon tax comparison, we find all 8 CGE models differ substantially in terms of impacts on the macroeconomy, aggregate prices, energy use and carbon reductions, as well as industry level output and price effects. We discuss the reasons for the divergent simulation results including differences in model structure, substitution parameters, baseline renewable penetration and methods of revenue recycling.
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.
Deployment of negative emission technologies needs to start immediately if we are to avoid overshooting international carbon targets, reduce negative climate impacts, and minimize costs of emission mitigation. Actions in China, given its importance for the global anthropogenic carbon budget, can be decisive. While bioenergy with carbon capture and storage (BECCS) may need years to mature, this study focuses on developing a ready-to-implement biomass intermediate pyrolysis poly-generation (BIPP) technology to produce a potentially stable form of biochar, a medium for carbon storage, and to provide a significant source of valuable biofuels, especially pyrolysis gas. Combining the experimental data with hybrid models, the results show that a BIPP system can be profitable without subsidies: its national deployment could contribute to a 68% reduction of carbon emissions per unit of GDP in 2030 compared to 2005 and could result additionally in a reduction in air pollutant emissions. With 73% of national crop residues converted to biochar and other biofuels in the near term (2020 to 2030), the cumulative greenhouse gas (GHG) reduction could reach up to 5653 Mt CO2-eq by 2050, which could contribute 9-20% of the global GHG emission reduction goal for BECCS (28-65 Gt CO2-eq in IPCC’s 1.5 °C pathway), and nearly 2633 Mt more than that projected for BECCS alone. The national BIPP development strategy is developed on a provincial scale based on a regional economic and life-cycle analysis.
With the development of deregulated retail power markets, it is possible for end users equipped with smart meters and controllers to optimize their consumption cost portfolios by choosing various pricing plans from different retail electricity companies. This paper proposes a reinforcement learning-based decision system for assisting the selection of electricity pricing plans, which can minimize the electricity payment and consumption dissatisfaction for individual smart grid end user. The decision problem is modeled as a transition probability-free Markov decision process (MDP) with improved state framework. The proposed problem is solved using a Kernel approximator-integrated batch Q-learning algorithm, where some modifications of sampling and data representation are made to improve the computational and prediction performance. The proposed algorithm can extract the hidden features behind the time-varying pricing plans from a continuous high-dimensional state space. Case studies are based on data from real-world historical pricing plans and the optimal decision policy is learned without a priori information about the market environment. Results of several experiments demonstrate that the proposed decision model can construct a precise predictive policy for individual user, effectively reducing their cost and energy consumption dissatisfaction.
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.
Policy simulation results of Computable General Equilibrium (CGE) models largely hinge on the choices of substitution elasticities among key input factors. Currently, most CGE models rely on the common elasticities estimated from aggregated data, such as the GTAP model elasticity parameters. Using firm level data, we apply the control function method to estimate CES production functions with capital, labor and energy inputs and find significant heterogeneity in substitution elasticities across different industries. Our capital-labor substitution elasticities are much lower than the GTAP values while our energy elasticities are higher. We then incorporate these estimated elasticities into a CGE model to simulate China's carbon pricing policies and compare with the results using GTAP parameters. Our less elastic K-L substitution lead to lower base case GDP growth, but our more elastic energy substitution lead to lower coal use and carbon emissions. In the carbon tax policy exercises, we find that our elasticities lead to easier reductions in coal use and carbon emissions.
The Harvard-China Project adopted an Open Access policy in September 2017. Journal articles that are already made open access by the publishers are available on our publications page as PDF attachments, while the final manuscripts of other articles published since our adoption of the policy are available in the Harvard University open-access repository, DASH, under the Harvard-China Project collection. There is usually a six-month delay after the article is published before its manuscript is uploaded to DASH.