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Article

Spatial Configuration of Energy Consumption and Carbon Emissions of Shanghai, and Our Policy Suggestions

by 1,†, 2,*,†, 1,*,† and 3
1
Fudan University Energy Research Center, School of Social Development and Public Policy, Fudan University, Shanghai 200433, China
2
Shanghai Academy of Fine Arts, Shanghai University, Shanghai 200444, China
3
School of Architecture, Tsinghua University, Beijing 100084, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Brian Deal
Sustainability 2017, 9(1), 104; https://doi.org/10.3390/su9010104
Received: 30 November 2016 / Revised: 28 December 2016 / Accepted: 4 January 2017 / Published: 12 January 2017
(This article belongs to the Special Issue Urban Sustainability and Planning Support Systems)
This research constructs a 1 km × 1 km Shanghai energy consumption and carbon emission spatial grid through a bottom-up approach. First, we locate all energy consumption locations in Shanghai via GIS. Second, we calculate energy consumption and associated CO2 emissions by energy type, by usage type, and by facilities. Finally, we use a spatial grid to represent the energy consumption and CO2 emissions. The grid shows CO2 emissions in Shanghai are highly spatially correlated with energy types and volumes of consumption. This research also finds out that high energy consumption and carbon emission locations in Shanghai display significant spatial aggregation. In 7209 spatial energy consumption cells, the top 10 grids of emissions account for 52.8% of total CO2 emissions in Shanghai; the top 20 grids account for 64.5% and the top 50 grids account for 76.5%. The most critical point emission sources are coal-fired power plants and iron and steel plants. The most important line emission sources are the Yan’an Road and Inner Ring viaducts. The area emission sources that account for the most future-projected growth are commercial and residential natural gas. After this spatial analysis, this paper makes policy suggestions and solutions to conserve energy consumption and mitigate carbon emissions in Shanghai. View Full-Text
Keywords: energy; carbon emissions; spatial grid; Shanghai; policy decision support systems energy; carbon emissions; spatial grid; Shanghai; policy decision support systems
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MDPI and ACS Style

Pan, K.; Li, Y.; Zhu, H.; Dang, A. Spatial Configuration of Energy Consumption and Carbon Emissions of Shanghai, and Our Policy Suggestions. Sustainability 2017, 9, 104. https://doi.org/10.3390/su9010104

AMA Style

Pan K, Li Y, Zhu H, Dang A. Spatial Configuration of Energy Consumption and Carbon Emissions of Shanghai, and Our Policy Suggestions. Sustainability. 2017; 9(1):104. https://doi.org/10.3390/su9010104

Chicago/Turabian Style

Pan, Kexi, Yongfu Li, Hanxiong Zhu, and Anrong Dang. 2017. "Spatial Configuration of Energy Consumption and Carbon Emissions of Shanghai, and Our Policy Suggestions" Sustainability 9, no. 1: 104. https://doi.org/10.3390/su9010104

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