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.

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.

Governments foster voluntary actions within households to mitigate climate change. However, the literature suggests that they may not be as effective as expected due to rebound effects. We use a dynamic economy–energy–environment computable general equilibrium (CGE) model of the Catalan economy to simulate the effect of 75 different actions on GDP and net CO2 emissions, over a 20-year period. We also examine how a carbon tax could counteract the carbon rebound effects. We find energy rebound effects ranging from 61.77% to 117.49% for voluntary energy conservation actions, depending on where the spending is redirected, with similar carbon rebound values. In our main scenarios, where energy savings are redirected to savings and all non-energy goods proportionally, the rebound is between 64.47% and 66.90%. We also find, for these scenarios, that a carbon tax of between 2.4 and 3.6 €/ton per percentage point of voluntary energy reduction would totally offset carbon rebound effects. These results suggest that voluntary actions in households need additional measures to provide the expected results in terms of energy use reduction and climate change mitigation.

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. 

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.

Reducing CH4 emissions is a major global challenge, owing to the world-wide rise in emissions and concentration of CH4 in the atmosphere, especially in the past decade. China has been the greatest contributor to global anthropogenic CH4 emissions for a long time, but current understanding towards its growing emissions is insufficient. This paper aims to link China's CH4 emissions during 2005–2012 to their socioeconomic determinants by combining input-output models with structural decomposition analysis from both the consumption and income perspectives. Results show that changes in household consumption and income were the leading drivers of the CH4 growth in China, while changes in efficiency remained the strongest factor offsetting CH4 emissions. After 2007, with the global financial crisis and economic stimulus plans, embodied emissions from exports plunged but those from capital formation increased rapidly. The enabled emissions in employee compensation increased steadily over time, whereas emissions induced from firms' net surplus decreased gradually, reflecting the reform on income distribution. In addition, at the sectoral level, consumption and capital formation respectively were the greatest drivers of embodied CH4 emission changes from agriculture and manufacturing, while employee compensation largely determined the enabled emission changes across all industrial sectors. The growth of CH4 emissions in China was profoundly affected by the macroeconomic situation and the changes of economic structure. Examining economic drivers of anthropogenic CH4emissions can help formulate comprehensive mitigation policies and actions associated with economic production, supply and consumption.