Impacts of SO2 taxations and renewable energy development on CO2, NOx and SO2 emissions in Jing-Jin-Ji region

Both air pollutant and carbon emissions are serious problems in China, particularly the economic and pollution intensive urban agglomerations. Therefore, this paper selected the most severely polluted Jing-Jin-Ji region (Beijing, Tianjin and Hebei urban clusters) to study the potential of mitigating both carbon and air pollutant emission. The Computable General Equilibrium (CGE) model was applied and six scenarios were constructed by considering policies of environmental tax and renewable energy. Business-as-usual (BaU) scenario assumed no tax and fixed renewable energy to 2002 level, whereas other scenarios assumed that intensified renewable energy (RE) and tax on sulfur dioxide (SO2) (TAXI and TAX2) were implemented either alone or combined. The results indicated that both RE and SO2 tax could contribute to regional low-carbon development and air pollutant reduction, and the reduction is about 10-40% depending on scenarios. However, Renewable energy is always more effective in reducing CO2 and air pollutant emissions than TAXI but less effective than TAX2 for Hebei. From the sectoral perspective, power sector would exhibit both the largest emissions and reduction potentials in all three Cities, accounting for about 21%, 31% and 28% of total CO2 emissions respectively for Beijing,,Tianjin and Hebei, in 2020. Considering different policies, it is more effective for Hebei to apply renewable energy to reduce its power sector emissions in the long term, and tax policy is more effective for emission reduction from other sectors in Tianjin. Further analysis on the economic impact of mitigation policy revealed that Tianjin and Beijing would suffer relatively greater negative impacts than Hebei in terms of loss in total GDP, while developing renewable energy could help to reduce such negative impacts. It is suggested that the policymakers need to take into accounts the regional economic situation and natural resource potential when they formulate low-carbon policies. (C) 2017 Elsevier Ltd. All rights reserved.