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To reduce traffic congestion and protect the environment, license plate control (LPC) policy has beenimplemented in Beijing since 2011. In 2019, 100,000 vehicle license plates were distributed, including60,000 for electric vehicle (EV) and 40,000 for gasoline vehicle (GV). However, whether the currentlicense plate allocation is optimal from a social welfare maximization perspective remains unclear. This paper proposes a two-level Stackelberg game which portrays the interaction between vehicle applicants and the government to quantify the optimal EV license plates under the LPC policy in Beijing. The equilibrium number of EV license plates derived from the Stackelberg model is 58,800, which could increase the social welfare by 0.38%. Sensitivity analysis is conducted to illustrate the impact of important influential factors — total license plate quota, vehicle rental fee, and energy price — on EV adoption. The LPC policy under COVID-19 is also studied through a scenario analysis. If thegovernment additionally increases the total quota by 20,000, 24% could be allocated to GV and 76% to EV. One third reduction of the current vehicle rental fee could increase EV license plates by 10.5%. Interms of energy prices, when gasoline price is low, reducing electricity price could contribute to EVadoption significantly, while that effect tapers off as the gasoline price rises.

In coping with climate change, China's CO2 mitigation targets should keep in step with the achievement of the long-term goal of holding temperature increase to well below 2 °C above pre-industrial levels by the end of this century (this is referred to as the 2 °C goal). Many previous papers have highlighted the implications of different effort-sharing principles and schemes in determining national contributions to global mitigations. In this paper, China's energy transformation towards the 2 °C goal until 2100 is examined in an integrated-assessment model in light of different effort-sharing principles to understand how the application of such schemes may alter China's energy system transformation on a pathway to this long-term goal. Across scenarios, China's non-fossil energy will account for 50–70% and 85% of primary energy consumption in 2050 and 2100, respectively in the scenarios in this study. Fossil energy with carbon capture and storage technologies and non-fossil energy will dominate power generation in China over the long run. Coal will be phased out in end-use sectors and electricity use will expand regardless of the effort-sharing principles. The sensitivity analysis of long-term steady-state levels implies that the ultimate level that emissions could reach will have great influences on the energy system transformation in China.

The market penetration of electric vehicle is subject to the capacity of charging facility greatly, however the development of charging facility is influenced by the economic incentives. In this st ...