Estimates and Predictions of Methane Emissions from Wastewater in China from 2000 to 2020

被引:39
作者
Du, Mingxi [1 ]
Zhu, Qiuan [1 ,2 ]
Wang, Xiaoge [1 ]
Li, Peng [1 ]
Yang, Bin [1 ]
Chen, Huai [3 ]
Wang, Meng [1 ]
Zhou, Xiaolu [2 ]
Peng, Changhui [1 ,2 ]
机构
[1] Northwest A&F Univ, Coll Forestry, Ctr Ecol Forecasting & Global Change, Yangling, Peoples R China
[2] Univ Quebec, Inst Environm Sci, Dept Biol Sci, Montreal, PQ, Canada
[3] Chinese Acad Sci, Chengdu Inst Biol, Chengdu, Sichuan, Peoples R China
基金
加拿大自然科学与工程研究理事会; 国家重点研发计划; 中国国家自然科学基金;
关键词
climate change; methane budget; wastewater treatment; global warming; ARTIFICIAL NEURAL-NETWORK; TREATMENT PLANTS; QUANTIFICATION; OPTIMIZATION; INVENTORY;
D O I
10.1002/2017EF000673
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Methane accounts for 20% of the global warming caused by greenhouse gases, and wastewater is a major anthropogenic source of methane. Based on the Intergovernmental Panel on Climate Change greenhouse gas inventory guidelines and current research findings, we calculated the amount of methane emissions from 2000 to 2014 that originated from wastewater from different provinces in China. Methane emissions from wastewater increased from 1349.01 to 3430.03 Gg from 2000 to 2014, and the mean annual increase was 167.69 Gg. The methane emissions from industrial wastewater treated by wastewater treatment plants (E-It) accounted for the highest proportion of emissions. We also estimated the future trend of industrial wastewater methane emissions using the artificial neural network model. A comparison of the emissions for the years 2020, 2010, and 2000 showed an increasing trend in methane emissions in China and a spatial transition of industrial wastewater emissions from eastern and southern regions to central and southwestern regions and from coastal regions to inland regions. These changes were caused by changes in economics, demographics, and relevant policies.
引用
收藏
页码:252 / 263
页数:12
相关论文
共 43 条
  • [1] [Anonymous], 2015, China Daily
  • [2] [Anonymous], 2 NAT COMM CLIM CHAN
  • [3] [Anonymous], PEOPL REP CHIN NAT G
  • [4] Location optimization of wind power generation-transmission systems under uncertainty using hierarchical fuzzy DEA: A case study
    Azadeh, Ali
    Rahimi-Golkhandan, Armin
    Moghaddam, Mohsen
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 30 : 877 - 885
  • [5] [蔡博峰 Cai Bofeng], 2015, [中国人口·资源与环境, China Population Resources and Environment], V25, P118
  • [6] Greenhouse gas emissions in China 2007: Inventory and input-output analysis
    Chen, G. Q.
    Zhang, Bo
    [J]. ENERGY POLICY, 2010, 38 (10) : 6180 - 6193
  • [7] Chinese Academy of Social Sciences, 1995, REP CHIN IND
  • [8] Assessing the "Revive the Northeast" (zhenxing dongbei) Programme: Origins, Policies and Implementation
    Chung, Jae Ho
    Lai, Hongyi
    Joo, Jang-Hwan
    [J]. CHINA QUARTERLY, 2009, (197) : 108 - 125
  • [9] Measuring and explaining eco-efficiencies of wastewater treatment plants in China: An uncertainty analysis perspective
    Dong, Xin
    Zhang, Xinyi
    Zeng, Siyu
    [J]. WATER RESEARCH, 2017, 112 : 195 - 207
  • [10] Quantification of methane emissions from municipal solid waste landfills in China during the past decade
    Du, Mingxi
    Peng, Changhui
    Wang, Xiaoge
    Chen, Huai
    Wang, Meng
    Zhu, Qiuan
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 78 : 272 - 279