CO2and Air Pollutants Emissions under Different Scenarios Predicted by a Regional Energy Consumption Modeling System for Shanghai, China

被引:4
|
作者
Wang, Jing [1 ,2 ]
Zhang, Yan [1 ,2 ]
Wu, Libo [2 ,3 ]
Ma, Weichun [1 ,2 ]
Chen, Limin [1 ]
机构
[1] Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200438, Peoples R China
[2] Fudan Univ, Big Data Inst Carbon Emiss & Environm Pollut, Shanghai 200438, Peoples R China
[3] Fudan Univ, Sch Econ, Ctr Energy Econ & Strategies Studies, Shanghai 200438, Peoples R China
基金
中国国家自然科学基金;
关键词
energy-environment system; LAPs; CO2; TIMES model; Shanghai; RIVER DELTA REGION; CO2; EMISSIONS; CALIFORNIA; INVENTORY; IMPACTS;
D O I
10.3390/atmos11091006
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
About 75% energy demand and emissions all concentrate in urban areas, especially in the metropolises, placing a heavy burden on both the energy supply system and the environment system. To explore low emission pathways and provide policy recommendations for the Shanghai energy system and the environmental system to reach the carbon dioxide (CO2) peak by 2030 and attain emission reduction targets for local air pollutants (LAPs), a regional energy-environment optimization model was developed in this study, considering system costs, socio-economic development and technology. To verify the reliability of the model simulation and evaluate the model risk, a historical scenario was defined to calculate the emissions for 2004-2014, and the data were compared with the bottom-up emission inventory results. By considering four scenarios, we simulated the energy consumption and emissions in the period of 2020-2030 from the perspective of energy policies, economic measures and technology updates. We found that CO(2)emissions might exceed the amount of 250 million tons by the end of 2020 under the current policy, and carbon tax with a price of 40 CNY per ton of carbon dioxide is an imperative measure to lower carbon emissions. Under the constraints, the emissions amount of SO2, NOx, PM10, and PM(2.5)will be reduced by 95.3-180.8, 207.8-357.1, 149.4-274.5, and 59.5-119.8 Kt in 2030, respectively.
引用
收藏
页数:24
相关论文
共 50 条
  • [31] COMPARISON AND ANALYSIS OF ENERGY CONSUMPTION AND CO2 EMISSIONS OF CHINA AND ASEAN
    Lu, Wei
    Tan, Taide
    Cao, Cong
    [J]. ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2014, VOL 6A, 2015,
  • [32] Uncertainty of energy consumption and CO2 emissions in the building sector in China
    Guo, Yangyang
    Uhde, Helena
    Wen, Wen
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2023, 97
  • [33] Tourism, economic growth, energy consumption, and CO2 emissions in China
    Zhang, Jiekuan
    Zhang, Yan
    [J]. TOURISM ECONOMICS, 2021, 27 (05) : 1060 - 1080
  • [34] An estimation of energy consumption and CO2 emissions in tourism sector of China
    Pu Wu
    Peihua Shi
    [J]. Journal of Geographical Sciences, 2011, 21 : 733 - 745
  • [35] Scenario analysis of household energy consumption and CO2 emissions in China
    Ning, Yadong
    Zhang, Chunbo
    Ding, Tao
    [J]. ADVANCES IN ENERGY SCIENCE AND EQUIPMENT ENGINEERING, 2015, : 1203 - 1207
  • [36] An estimation of energy consumption and CO2 emissions in tourism sector of China
    Wu Pu
    Shi Peihua
    [J]. JOURNAL OF GEOGRAPHICAL SCIENCES, 2011, 21 (04) : 733 - 745
  • [37] The impact of household consumption on energy use and CO2 emissions in China
    Feng, Zhen-Hua
    Zou, Le-Le
    Wei, Yi-Ming
    [J]. ENERGY, 2011, 36 (01) : 656 - 670
  • [38] Projection of the Co-Reduced Emissions of CO2 and Air Pollutants from Civil Aviation in China
    Guo, Xiurui
    Ning, Chunxiao
    Shen, Yaqian
    Yao, Chang
    Chen, Dongsheng
    Cheng, Shuiyuan
    [J]. SUSTAINABILITY, 2023, 15 (09)
  • [39] Impact of globalization and energy consumption on CO2 emissions in China: Implications for energy transition
    Xie, Henglang
    Bui, Wency Kher Thinng
    [J]. FINANCE RESEARCH LETTERS, 2024, 67
  • [40] Analysis of China's oil and gas consumption under different scenarios toward 2050: An integrated modeling
    Pan, Xunzhang
    Wang, Lining
    Dai, Jiaquan
    Zhang, Qi
    Peng, Tianduo
    Chen, Wenying
    [J]. ENERGY, 2020, 195