School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China; State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China.
Department of Geography and Resource Management, the Chinese University of Hong Kong, Hong Kong.
Sci Total Environ. 2022 Jan 10;803:150083. doi: 10.1016/j.scitotenv.2021.150083. Epub 2021 Sep 3.
Understanding the spatio-temporal heterogeneous effects of socioeconomic and meteorological factors on CO emissions from combinations of different district heating systems with "Coal-to-Gas" transition can contribute to the development of future low-carbon energy systems that are efficient and effective. This work downscales city-level CO emissions to a 3 × 3 km gridded level in northern China during 2012 to 2018. By employing the Geographically and Temporally Weighted Regression (GTWR) model, nighttime light (NTL) data are adopted as a proxy of the level of urbanization, and the Temperature-Humidity-Wind (THW) Index is used as a proxy of meteorological factors in the downscaling model. The results show that, for more than 85% of the cities, urbanization significantly enhances the CO emissions of district heating systems, while the THW Index shows negative impacts on CO emissions. Significant spatial and temporal heterogeneity exists. The grids with the highest CO emissions from coal-fired boilers (grids with annual variation >0.59 Gg CO/year) are mainly located in nonurban areas of the two megacities Beijing and Tianjin and also in the capital cities of each province. Urbanization has larger effects on the CO emissions of natural gas-fired boilers than of coal-fired boilers and combined heat and power (CHP). The average growth rate of CO emissions of gas-fired boilers in the urban areas of the study regions was approximately 4.7 times that of nonurban areas. The spatio-temporal heterogeneous impacts of urbanization on CO emissions should therefore be considered in future discussions of clean heating policies and climate response strategies.
理解社会经济和气象因素在不同区域供热系统与“煤改气”组合的 CO 排放的时空异质效应，可以为未来高效、有效的低碳能源系统的发展做出贡献。本研究将中国北方城市层面的 CO 排放量细分为 2012 年至 2018 年的 3×3km 格网水平。通过使用地理时空加权回归（GTWR）模型，采用夜间灯光（NTL）数据作为城市化水平的代理变量，温度湿度风速（THW）指数作为气象因子的代理变量，应用于降尺度模型。结果表明，对于超过 85%的城市，城市化显著增强了区域供热系统的 CO 排放，而 THW 指数对 CO 排放表现出负面影响。存在显著的时空异质性。燃煤锅炉 CO 排放量最高的网格（年变化大于 0.59GgCO/年）主要分布在京津冀两个特大城市的非城区，以及各省的省会城市。城市化对天然气锅炉的 CO 排放影响大于燃煤锅炉和热电联产（CHP）。研究区域城区燃气锅炉 CO 排放量的平均增长率约为非城区的 4.7 倍。因此，在未来清洁供暖政策和气候应对策略的讨论中，应考虑城市化对 CO 排放的时空异质影响。
