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

机译：上海市能源消费和碳排放的空间格局及政策建议

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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 CO 2 emissions by energy type, by usage type, and by facilities. Finally, we use a spatial grid to represent the energy consumption and CO 2 emissions. The grid shows CO 2 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 CO 2 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.
机译：本研究通过自下而上的方法构建了上海1 km×1 km的能源消耗和碳排放空间网格。首先，我们通过GIS定位上海的所有能耗地点。其次，我们按能源类型，使用类型和设施来计算能耗和相关的CO 2排放量。最后，我们使用空间网格来表示能耗和CO 2排放量。网格显示，上海的CO 2排放在空间上与能源类型和消费量高度相关。该研究还发现，上海的高能耗和高碳排放地区表现出显着的空间聚集性。在7209个空间能耗单元中，排在前十位的排放网格占上海CO 2排放总量的52.8％;前20个网格占64.5％，前50个网格占76.5％。最关键的排放源是燃煤发电厂和钢铁厂。最重要的线路排放源是延安路和内环高架桥。占未来增长最快的地区排放源是商业和民用天然气。在进行了空间分析之后，本文提出了节约上海能源消耗和减少碳排放的政策建议和解决方案。

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