Achieving China's energy and climate policy targets in 2030 under multiple uncertainties

Abstract

The stringency of China's energy and climate targets in 2030 and the policy needed to realize these targets are full of controversy, mainly as a result of multiple future uncertainties. This study has developed a stochastic energy-economy-environment integrated model, to assess China's energy and climate targets in 2030, with a particular focus on the carbon intensity reduction, carbon emission peaking, and non-fossil energy development. The probabilities of realizing the targets are obtained, and the nexus among different targets is explored. It's argued that carbon emission management and policy-making should be implemented from the perspective of risk management, and policy makers can take corresponding policy measures based on the degree of confidence required under multiple future uncertainties. It is found that the probabilities of realizing carbon emission-peaking target and non-fossil energy target are low, with the business-as-usual efforts, and additional policies may still be needed. More specific, carbon pricing plays a major role in curbing and peaking carbon emissions, while the policy mix of ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T2 carbon pricing and non-fossil energy subsidies can peak the carbon emission with relatively low cost compared to the single carbon pricing policy. It is also found that the carbon intensity reduction target is most likely to be attained, followed by the carbon-peaking target, and then the non-fossil energy target, given the same policy efforts. This indicates that, China may not deliberately increase carbon emissions rapidly over the next decade to make the carbon emission peak as high as possible; otherwise, it may be difficult to achieve the non-fossil energy target.

Integrated policy assessment and optimisation over multiple sustainable development goals in Eastern Africa

“…Given the heterogeneous mix of policy objectives in the SSA context, and the high implicit uncertainty for policymaking caused by the wide range of possible development scenarios in the region, integrated and robust policy analysis is required for designing policies that take advantage of identified synergies between different SDGs, independent of the socioeconomic development of the region (Collste et al 2017, Doukas et al 2018, Duan et al 2018, Mainali et al 2018. In regions where the lack of access to modern energy sources and consequential high dependence on unsustainably harvested traditional biomass are major causes of GHG emissions and premature mortality, the implementation and impacts of policies such as carbon taxing are not straightforward and, instead, land policies and subsidies for cleaner energy technologies will constitute effective policy instruments for sustainable development (Mohammed et al 2015, Cameron et al 2016, Schwerhoff and Sy 2017.…”

Energy and carbon intensity: A study on the cross-country industrial shift from China to India and SE Asia

“…We therefore, hypothesize that even when looking at the same industrial sector, countries will have different energy intensity per economic output (H1). Energy intensity relies largely on the technologies used and gradually cross-country knowledge transfer progresses by either governmental schemes or multinationals active in several countries [33]. Therefore, we hypothesize that different countries' energy intensity for the same industrial sectors will converge over time (H2).…”

Measuring the Energy and Carbon Emission Efficiency of Regional Transportation Systems in China: Chance-Constrained DEA Models

“…Chinese government has been implementing many policies and measures to increase energy efficiency and reduce carbon emissions. By 2020, China intends to contract carbon dioxide (CO 2 ) emissions per unit of GDP by 18% compared with the level in 2015 [6].…”