Spatial distribution and regulatory countermeasures of key emission units in the national carbon market
-
摘要:
重点排放单位空间分布特征对于生态环境部门制定全国碳市场数据质量监管政策有重要意义，但目前对重点排放单位空间分布规律认识仍然有限。以行政区重点排放单位分布为研究对象，运用全局和局部空间自相关分析探讨重点排放单位的空间集聚特征，采用空间聚类方法划定不同区域，并结合社会经济发展、用电量和产业结构等探讨管控策略。结果表明：重点排放单位在华东地区和华北地区分布较为集中，在城市和县域尺度存在明显的空间正自相关，高高集聚、低低集聚均呈现连片分布，高高集聚主要分布在煤炭资源富集和经济发达地区。依据重点排放单位数量及碳排放关联因素，将全国城市划分为7个区域，区域1主要位于西北地区，区域2由山西、陕西、宁夏中东部及新疆北部、内蒙古东部的部分地区组成，区域3、4、5和6分别主要位于东北、华北、华东和西南地区，区域7主要位于中部和南部地区。对区域1、2和6本地矿区与重点排放单位的煤质参数进行比较，可快速评估碳排放数据质量；将区域3和4的本地煤炭和外来煤炭进行区分，有助于进行重点排放单位分类监管；应关注区域5和7煤炭来源对碳排放的影响。此外，应强化重点排放单位集中区域碳排放监管的基础能力培训，做好社会经济相对落后地区重点排放单位碳排放数据质量管理帮扶等。
Abstract:The spatial distribution characteristics of key emission units are of great significance to the ecological and environmental departments in formulating the supervision policies for national carbon market data quality, but the current knowledge of these characteristics is still limited. Taking the distribution of key emission units in administrative regions as the research object, and the spatial agglomeration characteristics of key emission units were explored using global and local spatial autocorrelation analysis. Various regions were identified by the spatial clustering method, and control measures were discussed in the context of socioeconomic development, electricity consumption, industrial structure, and other factors. The findings demonstrated that the distribution of key emission units was more concentrated in east and north China, with clear signs of positive spatial autocorrelation at the city and county scales. The results also demonstrated that both high high and low low agglomeration exhibited continuous distribution, with high high agglomeration mainly distributed in areas with abundant coal resources and developed economies. The cities in China were classified into seven regions based on the quantity of key emissionunits and carbon emission-related factors. Region 1 was dominated by the northwest region. Region 2 included parts of Shanxi, Shaanxi, as well as central and eastern Ningxia, northern Xinjiang, and eastern Inner Mongolia. Regions 3, 4, 5 and 6 were primarily found in northeast, north, east, and southwest China, respectively. Region 7 was mostly in the center and south of China. The accuracy of data on carbon emissions could be rapidly evaluated by comparing coal quality parameters between local mines and key emission units in Regions 1, 2 and 6. The distinction between local and imported coal in Regions 3 and 4 could help to categorize and regulate the key emission units, while Regions 5 and 7 should pay close attention to the effects of coal sources on carbon emissions. Additionally, basic capacity building for carbon emission supervision in the concentrated regions of key emission units should be enhanced, and help for carbon emission data quality management should be offered to key emission units in socioeconomically backward areas.
-
图 1 重点排放单位在省域单元的空间分布特征
Figure 1. Spatial distribution of China's key emission units at provincial level
图 2 重点排放单位在城市和县域尺度统计特征
Figure 2. Statistics on key emission units at city level and country level
表 1 重点排放单位空间聚类
Table 1. Space clustering of key emission units
区域 地区 区域1 阿拉善盟、兰州、嘉峪关、金昌、白银、武威、张掖、平凉、酒泉、西宁、海北州 、海西州、石嘴山、固原、中卫、克拉玛依、博州、巴州、阿克苏、喀什、和田、塔城、石河子、阿拉尔、图木舒克、五家渠、北屯、双河、可克达拉 区域2 太原、大同、阳泉、长治、晋城、朔州、晋中、运城、忻州、临汾、吕梁、乌海、鄂尔多斯、锡林郭勒、淮南、阜阳、铜川、宝鸡、咸阳、渭南、延安、榆林、银川、吴忠、乌鲁木齐、吐鲁番、哈密、昌吉、伊犁 区域3 北京、天津、石家庄、唐山、秦皇岛、保定、张家口、承德、衡水、呼和浩特、包头、赤峰、通辽、呼伦贝尔、巴彦淖尔、乌兰察布、兴安盟、沈阳、大连、鞍山、抚顺、本溪、丹东、锦州、营口、阜新、辽阳、盘锦、铁岭、朝阳、葫芦岛、长春、吉林、四平、辽源、通化、白山、松原、白城、延边、哈尔滨、齐齐哈尔、鸡西、鹤岗、双鸭山、大庆、伊春、佳木斯、七台河、牡丹江、黑河、绥化、大兴安岭 区域4 邯郸、邢台、沧州、廊坊、淮北、宿州、亳州、济南、济宁、泰安、德州、聊城、菏泽、郑州、洛阳、平顶山、安阳、鹤壁、新乡、焦作、濮阳、许昌、三门峡、商丘、济源 区域5 上海、南京、无锡、徐州、常州、苏州、南通、连云港、淮安、盐城、扬州、镇江、泰州、宿迁、杭州、宁波、嘉兴、湖州、舟山、蚌埠、滁州、青岛、淄博、枣庄、东营、烟台、潍坊、威海、日照、临沂、滨州 区域6 攀枝花、泸州、宜宾、六盘水、遵义、安顺、毕节、黔西南、昆明、曲靖、玉溪、昭通、普洱、临沧、红河 区域7 温州、绍兴、金华、衢州、台州、丽水、合肥、芜湖、马鞍山、铜陵、安庆、六安、池州、宣城、福州、厦门、莆田、三明、泉州、漳州、龙岩、宁德、南昌、景德镇、萍乡、九江、新余、鹰潭、赣州、吉安、宜春、抚州、上饶、开封、漯河、南阳、信阳、周口、驻马店、武汉、黄石、十堰、宜昌、襄阳、鄂州、荆门、孝感、荆州、黄冈、咸宁、潜江、长沙、株洲、湘潭、衡阳、邵阳、岳阳、常德、张家界、益阳、郴州、怀化、娄底、广州、韶关、深圳、珠海、汕头、佛山、江门、湛江、茂名、肇庆、惠州、梅州、汕尾、河源、阳江、东莞、中山、潮州、揭阳、云浮、南宁、柳州、桂林、北海、防城港、钦州、贵港、百色、贺州、河池、来宾、崇左、海口、三亚、儋州、文昌、东方、乐东、重庆、成都、自贡、德阳、绵阳、广元、遂宁、内江、乐山、南充、眉山、广安、达州、贵阳、铜仁、黔东南、黔南、文山、西安、汉中、商洛 
下载: 导出CSV
表 2 重点排放单位碳排放的关联因素统计
Table 2. Statistics on related factors of carbon emissions from key emission units
区域 重点排放
单位数量/家全社会用电量平
均值/
（万kW·h）第二产业占比
平均值/
%人均GDP平均
值/
（元/人）区域1 29 1 239 437 37 72 720 区域2 29 2 345 103 46 64 081 区域3 53 2 239 371 31 47 841 区域4 25 2 362 935 43 56 319 区域5 31 4 774 096 44 106 099 区域6 15 1 557 210 39 51 202 区域7 122 1 998 405 40 65 617
下载: 导出CSV
-
[1] 国务院新闻办公室. 中国应对气候变化的政策与行动[A/OL]. (2021-10-27)[2023-09-01]. https://www.gov.cn/zhengce/2021-10/27/content_5646697.htm. [2] LIU Z, DENG Z, HE G, et al. Challenges and opportunities for carbon neutrality in China[J]. Nature Reviews Earth & Environment,2021,3(2):141-155. [3] 谭显春, 郭雯, 樊杰, 等. 碳达峰、碳中和政策框架与技术创新政策研究[J]. 中国科学院院刊,2022,37(4):435-443.TAN X C, GUO W, FAN J, et al. Policy framework and technology innovation policy of carbon peak and carbon neutrality[J]. Bulletin of Chinese Academy of Sciences,2022,37(4):435-443. [4] 生态环境部. 碳排放权交易管理办法(试行)[A/OL]. (2021-01-05)[2022-11-01]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk02/202101/t20210105_816131.html. [5] 生态环境部. 全国碳市场建设工作会议在京召开[EB/OL]. (2021-01-05)[2022-11-01]. https://www.mee.gov.cn/ywdt/hjywnews/202207/t20220713_988569.shtml. [6] GAO T, JIN P F, SONG D, et al. Tracking the carbon footprint of China's coal-fired power system[J]. Resources, Conservation and Recycling,2022,177:105964. doi: 10.1016/j.resconrec.2021.105964 [7] 周颖, 蔡博锋, 刘兰翠, 等. 我国火电行业二氧化碳排放空间分布研究[J]. 热力发电,2011,40(10):1-3.ZHOU Y, CAI B F, LIU L C, et al. Study on spatial distribution of CO2 emission from thermal power industry of China[J]. Thermal Power Generation,2011,40(10):1-3. [8] 何迎, 邢园通, 汲奕君, 等. 我国电力行业碳排放影响因素及区域差异研究[J]. 安全与环境学报,2020,20(6):2343-2350.HE Y, XING Y T, JI Y J, et al. On influential factors and regional difference in carbon emissions from power industry at home in China[J]. Journal of Safety and Environment,2020,20(6):2343-2350. [9] 姜华, 李艳萍, 高健. 双碳背景下煤基产业绿色低碳转型之路[J]. 环境工程技术学报,2022,12(5):1580-1583.JIANG H, LI Y P, GAO J. The road of green and low-carbon transformation of coal-based industry under carbon peak and carbon neutrality background[J]. Journal of Environmental Engineering Technology,2022,12(5):1580-1583. [10] WANG P, LIN C K, WANG Y, et al. Location-specific co-benefits of carbon emissions reduction from coal-fired power plants in China[J]. Nature Communications,2021,12(1):1-11. doi: 10.1038/s41467-020-20314-w [11] WANG C H, CAO X Y, MAO J, et al. The changes in coal intensity of electricity generation in Chinese coal-fired power plants[J]. Energy Economics,2019,80:491-501. doi: 10.1016/j.eneco.2019.01.032 [12] 李广宇, 周长波, 李娜娜, 等. 构建完善全国碳排放权交易市场的建议[J]. 环境保护,2022,50(8):45-49.LI G Y, ZHOU C B, LI N N, et al. Suggestions on improving the national carbon emissions trading market[J]. Environmental Protection,2022,50(8):45-49. [13] 吴尚昆, 张玉韩. 中国能源资源基地分布与管理政策研究[J]. 中国工程科学,2019,21(1):81-87.WU S K, ZHANG Y H. Distribution and management policy of energy resource bases in China[J]. Engineering Science,2019,21(1):81-87. [14] 陈琳琳, 杨宇, 洪辉, 等. 中国能源工业空间分布、基地识别与演变特征[J]. 资源科学,2016,38(12):2256-2269.CHEN L L, YANG Y, HONG H, et al. Geography distribution of China's energy industry and evolution of energy industrial bases[J]. Resources Science,2016,38(12):2256-2269. [15] EGUCHI S, TAKAYABU H, LIN C. Sources of inefficient power generation by coal-fired thermal power plants in China: a metafrontier DEA decomposition approach[J]. Renewable and Sustainable Energy Reviews,2021,138:110562. doi: 10.1016/j.rser.2020.110562 [16] 孙现伟, 邓双, 朱云, 等. 我国燃煤电厂PM2.5减排潜力预测与分析[J]. 环境科学研究,2016,29(5):637-645.SUN X W, DENG S, ZHU Y, et al. PM2.5 emissions reduction potential from coal-fired power plants in China[J]. Research of Environmental Sciences,2016,29(5):637-645. [17] 王少剑, 谢紫寒, 王泽宏. 中国县域碳排放的时空演变及影响因素[J]. 地理学报,2021,76(12):3103-3118. doi: 10.11821/dlxb202112016WANG S J, XIE Z H, WANG Z H. The spatiotemporal pattern evolution and influencing factors of CO2 emissions at the County level of China[J]. Acta Geographica Sinica,2021,76(12):3103-3118. doi: 10.11821/dlxb202112016 [18] 生态环境部. 关于印发《2019—2020年全国碳排放权交易配额总量设定与分配实施方案(发电行业)》《纳入2019—2020年全国碳排放权交易配额管理的重点排放单位名单》并做好发电行业配额预分配工作的通知[A/OL]. (2020-12-30)[2023-04-01]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/202012/t20201230_815546.html. [19] 国土资源部. 全国矿产资源规划(2016—2020年)[EB/OL]. (2016-11-15)[2023-04-01]. https://mnr.gov.cn//gk/ghjh/201811/t20181101_2324927.html. [20] 国务院办公厅. 能源发展战略行动计划(2014—2020年)[EB/OL]. [2023-04-01]. https://www.gov.cn/zhengce/content/2014-11/19/content_9222.htm. [21] 陈培阳, 朱喜钢. 基于不同尺度的中国区域经济差异[J]. 地理学报,2012,67(8):1085-1097.CHEN P Y, ZHU X G. Regional inequalities in China at different scales[J]. Acta Geographica Sinica,2012,67(8):1085-1097. [22] XIE L Y, HUANG Y, QIN P. Spatial distribution of coal-fired power plants in China[J]. Environment and Development Economics,2018,23(4):495-515. doi: 10.1017/S1355770X18000098 [23] 蒋春来, 宋晓晖, 钟悦之, 等. 2010—2015年中国燃煤电厂NO x 排放特征[J]. 中国环境科学,2018,38(8):2903-2910.JIANG C L, SONG X H, ZHONG Y Z, et al. Characteristics of NO x emissions from coal-fired power plants in China from 2010 to 2015[J]. China Environmental Science,2018,38(8):2903-2910. [24] 吴家玉, 周春瑶, 徐海红, 等. 京津冀区域燃煤发电行业大气污染物排放时空变化特征研究[J]. 环境工程,2017,35(8):141-145.WU J Y, ZHOU C Y, XU H H, et al. Study on spatial-temporal variabilities of air pollution emissions from coal-fired power generation industry in Beijing-Tianjin-Hebei region[J]. Environmental Engineering,2017,35(8):141-145. [25] NAKAISHI T, NAGASHIMA F, KAGAWA S. Spatial autocorrelation analysis of the environmental efficiency of coal-fired power plants in China[J]. Clean Technologies and Environmental Policy,2022,24(7):2177-2192. doi: 10.1007/s10098-022-02310-4 [26] 崔建升, 屈加豹, 伯鑫, 等. 基于在线监测的2015年中国火电排放清单[J]. 中国环境科学,2018,38(6):2062-2074. doi: 10.3969/j.issn.1000-6923.2018.06.008CUI J S, QU J B, BO X, et al. High resolution power emission inventory for China based on CEMS in 2015[J]. China Environmental Science,2018,38(6):2062-2074. doi: 10.3969/j.issn.1000-6923.2018.06.008 [27] 刘靖, 单春艳, 梁晓宇. 唐山市基于GIS的PM2.5空间聚集性及分区管控[J]. 中国环境科学,2020,40(2):513-522.LIU J, SHAN C Y, LIANG X Y. Research on spatial aggregation of PM2.5 and zoning control in Tangshan based on GIS[J]. China Environmental Science,2020,40(2):513-522. [28] 中国煤炭工业协会. 2021煤炭行业发展年度报告[EB/OL]. (2022-03-30)[2023-04-01]. http://www.coalchina.org.cn. [29] 霍超. 山西煤炭资源分布特征及勘查开发布局研究[J]. 中国煤炭地质,2020,32(9):159-162.HUO C. Study on coal resources distribution features and exploration, exploitationlayout in Shanxi Province[J]. Coal Geology of China,2020,32(9):159-162. [30] 宋洪柱. 中国煤炭资源分布特征与勘查开发前景研究[D]. 北京: 中国地质大学(北京), 2013. [31] 车亮亮, 韩雪, 武春友. 中国煤炭流动格局与利用效率的空间关联分析[J]. 经济地理,2015,35(2):134-140.CHE L L, HAN X, WU C Y. The analysis of the coal flow pattern and the spatial association of coal utilization efficiency in China[J]. Economic Geography,2015,35(2):134-140. [32] 霍超, 杜金龙, 齐宽, 等. 内蒙古煤炭资源分布特征及勘查开发布局研究[J]. 中国矿业,2021,30(6):33-36.HUO C, DU J L, QI K, et al. Research on distribution characteristics and development layout of coal resources in Inner Mongolia[J]. China Mining Magazine,2021,30(6):33-36. [33] 顾娇杨. 黑龙江省煤种分布与煤变质特征[J]. 煤炭科学技术,2004,32(9):50-53. doi: 10.3969/j.issn.0253-2336.2004.09.017GU J Y. Coal distribution and coal quality features in Helongjiang Province[J]. Coal Science and Technology,2004,32(9):50-53. doi: 10.3969/j.issn.0253-2336.2004.09.017 [34] 赵媛, 郝丽莎. 江苏省电力工业空间结构优化研究[J]. 长江流域资源与环境,2006,15(3):292-297.ZHAO Y, HAO L S. Optimization of spatial structure of electric power industry in Jiangsu Province[J]. Resources and Environment in the Yangtze Basin,2006,15(3):292-297. [35] 薛文博, 许艳玲, 王金南, 等. 全国火电行业大气污染物排放对空气质量的影响[J]. 中国环境科学,2016,36(5):1281-1288.XUE W B, XU Y L, WANG J N, et al. Ambient air quality impact of emissions from thermal power industry[J]. China Environmental Science,2016,36(5):1281-1288. [36] 高卫东, 姜巍. 中国煤炭资源供应格局演变及流动路径分析[J]. 地域研究与开发,2012,31(2):9-14. doi: 10.3969/j.issn.1003-2363.2012.02.003GAO W D, JIANG W. Analysis on supply pattern evolvement and circulation path of coal resource in China[J]. Areal Research and Development,2012,31(2):9-14. □ doi: 10.3969/j.issn.1003-2363.2012.02.003 -
下载:
点击查看大图
计量
- 文章访问数: 236
- HTML全文浏览量: 154
- PDF下载量: 52
- 被引次数: 0
