留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于企业用电数据的大气污染防治工作研究进展

陈建华 李政 刘翰青 高健 杨艳 竹双

陈建华,李政,刘翰青,等.基于企业用电数据的大气污染防治工作研究进展[J].环境工程技术学报,2023,13(2):510-516 doi: 10.12153/j.issn.1674-991X.20220272
引用本文: 陈建华,李政,刘翰青,等.基于企业用电数据的大气污染防治工作研究进展[J].环境工程技术学报,2023,13(2):510-516 doi: 10.12153/j.issn.1674-991X.20220272
CHEN J H,LI Z,LIU H Q,et al.Research progress of air pollution prevention and control based on enterprise electricity consumption data[J].Journal of Environmental Engineering Technology,2023,13(2):510-516 doi: 10.12153/j.issn.1674-991X.20220272
Citation: CHEN J H,LI Z,LIU H Q,et al.Research progress of air pollution prevention and control based on enterprise electricity consumption data[J].Journal of Environmental Engineering Technology,2023,13(2):510-516 doi: 10.12153/j.issn.1674-991X.20220272

基于企业用电数据的大气污染防治工作研究进展

doi: 10.12153/j.issn.1674-991X.20220272
基金项目: 国家重点研发计划项目(2022YFC3703400) ;潍坊市大气污染成因与治理“一市一策”跟踪研究项目
详细信息
    作者简介:

    陈建华(1970—),女,研究员,博士,主要从事大气环境化学研究,chenjh@craes.org.cn

    通讯作者:

    李政(1996—),男,硕士研究生,主要从事大气科学研究,lizheng2061@163.com

  • 中图分类号: X51

Research progress of air pollution prevention and control based on enterprise electricity consumption data

  • 摘要:

    当前,我国处于“十四五”的关键发展时期,对于污染防治工作提出了“精准治污、科学治污、依法治污”的新要求。电力能源是企业的战略资源和核心生产要素,企业用电数据能够反映企业的经济运行、产业运转情况,具有非常大的数据挖掘价值,在大气污染防治领域的应用前景广阔。综述了目前国内外基于企业用电数据的企业污染排放模型构建、“散乱污”与“偷排漏排”企业识别监管、特别管控期间污染排放监管与评估及精细化大气污染源排放清单构建等方面的研究现状。结果表明:运用企业用电数据,能够实现对企业(尤其是小、微企业)污染物排放的精准监管,一定程度上弥补了环保监管在这方面的不足,极大提高了工作效率。总结了电力大数据在大气污染防治应用中需要注意的问题,并对后续电力数据在大气污染防治领域的深层次应用提出了建议。

     

  • [1] ZHANG Q, ZHENG Y X, TONG D, et al. Drivers of improved PM 2.5 air quality in China from 2013 to 2017[J]. PNAS,2019,116(49):24463-24469. doi: 10.1073/pnas.1907956116
    [2] ZHENG B, TONG D, LI M, et al. Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions[J]. Atmospheric Chemistry and Physics,2018,18(19):14095-14111. doi: 10.5194/acp-18-14095-2018
    [3] 雷宇, 严刚.关于“十四五”大气环境管理重点的思考[J]. 中国环境管理,2020,12(4):35-39. doi: 10.16868/j.cnki.1674-6252.2020.04.035

    LEI Y, YAN G. Thoughts on the key issues regarding atmospheric environment management in the 14th Five-Year Plan[J]. Chinese Journal of Environmental Management,2020,12(4):35-39. doi: 10.16868/j.cnki.1674-6252.2020.04.035
    [4] 孙金龙, 黄润秋.以习近平生态文明思想为指引 推动生态文明建设实现新进步[J]. 环境保护,2021,49(15):8-10.

    SUN J L, HUANG R Q. Taking Xi Jinping's Ecological Civilization Thought as a guide to promote the construction of ecological civilization and realize new progress[J]. Environmental Protection,2021,49(15):8-10.
    [5] 孙彩萍, 刘孝富, 孙启宏, 等.美国固定源监管机制对我国排污许可证实施的借鉴[J]. 环境工程技术学报,2018,8(2):191-199. doi: 10.3969/j.issn.1674-991X.2018.02.026

    SUN C P, LIU X F, SUN Q H, et al. An inspiration to pollution permitting system implementation in China from the United States' stationary source supervisory mechanism[J]. Journal of Environmental Engineering Technology,2018,8(2):191-199. doi: 10.3969/j.issn.1674-991X.2018.02.026
    [6] 孙彩萍, 孙启宏, 王维, 等.固定源大气污染物监管技术框架及应用研究[J]. 环境工程技术学报,2019,9(6):741-747. doi: 10.12153/j.issn.1674-991X.2019.06.172

    SUN C P, SUN Q H, WANG W, et al. Technical framework and application of site-inspection and enforcement for air pollutants from stationary sources[J]. Journal of Environmental Engineering Technology,2019,9(6):741-747. doi: 10.12153/j.issn.1674-991X.2019.06.172
    [7] 赵晶晶.关于电力大数据应用于大气污染防治的思考[J]. 环境保护与循环经济,2021,41(2):101-103. doi: 10.3969/j.issn.1674-1021.2021.02.026
    [8] 雒军, 唐坚, 赵喆, 等.基于大数据的电力环保数据平台建设[J]. 电力大数据,2020,23(1):58-63.

    LUO J, TANG J, ZHAO Z, et al. Construction of power environmental protection data platform based on big data[J]. Power Systems and Big Data,2020,23(1):58-63.
    [9] CHANDIO A A, JIANG Y S, AHMAD F, et al. Investigating the long-run interaction between electricity consumption, foreign investment, and economic progress in Pakistan: evidence from VECM approach[J]. Environmental Science and Pollution Research International,2020,27(20):25664-25674. doi: 10.1007/s11356-020-08966-z
    [10] SALAHUDDIN M, ALAM K, OZTURK I, et al. The effects of electricity consumption, economic growth, financial development and foreign direct investment on CO2 emissions in Kuwait[J]. Renewable and Sustainable Energy Reviews,2018,81:2002-2010. doi: 10.1016/j.rser.2017.06.009
    [11] 邓雪晴.基于电力数据的经济发展趋势分析[J]. 中国市场,2017(32):28-29. doi: 10.13939/j.cnki.zgsc.2017.32.028
    [12] 李海.电力消费量与国房景气指数关系研究[J]. 统计与决策,2018,34(5):95-98. doi: 10.13546/j.cnki.tjyjc.2018.05.023
    [13] WANG J, TIAN Y J, JIA F, et al. Constructing the industrial prosperity index based on big data of enterprise electricity[J]. IOP Conference Series: Earth and Environmental Science,2020,571(1):012002. doi: 10.1088/1755-1315/571/1/012002
    [14] AL-MULALI U, CHE SAB C N B. Electricity consumption, CO2 emission, and economic growth in the Middle East[J]. Energy Sources, Part B: Economics, Planning, and Policy,2018,13(5):257-263. doi: 10.1080/15567249.2012.658958
    [15] ZHANG P F, CAI W Q, YAO M T, et al. Urban carbon emissions associated with electricity consumption in Beijing and the driving factors[J]. Applied Energy,2020,275:115425. doi: 10.1016/j.apenergy.2020.115425
    [16] WANG P Y, MA L F, LI X L, et al. Analysis and research on enterprise resumption of work and production based on K-means clustering[C]//2021 IEEE 6th International Conference on Big Data Analytics. Xiamen: IEEE, 2021: 169-174.
    [17] 王林信, 江元, 罗世刚, 等.基于电力大数据的企业复工复产模型研究及应用[J]. 电力大数据,2020,23(12):65-71.

    WANG L X, JIANG Y, LUO S G, et al. Research and application of enterprise resumption model based on power big data[J]. Power Systems and Big Data,2020,23(12):65-71.
    [18] 尹积军, 潘巍巍.基于电力大数据的企业复工电力指数研究与应用[J]. 浙江电力,2021,40(2):26-32. doi: 10.19585/j.zjdl.202102005

    YIN J J, PAN W W. Research and application of resumption power index based on power big data[J]. Zhejiang Electric Power,2021,40(2):26-32. doi: 10.19585/j.zjdl.202102005
    [19] 李迪, 耿亮, 佟大力, 等.互联网与能源融合背景下电力信息通信领域的发展趋势和方向[J]. 电力信息与通信技术,2015,13(7):1-7.

    LI D, GENG L, TONG D L, et al. The new development direction of electric power information communication domain under the background of Internet and energy fusion[J]. Electric Power Information and Communication Technology,2015,13(7):1-7.
    [20] 赵雅迪, 吴钊, 李庆兵, 等.电费回收风险预测的大数据方法应用[J]. 电信科学,2019,35(2):125-133.

    ZHAO Y D, WU Z, LI Q B, et al. Application of big data method in forecasting the risk of tariff recovery[J]. Telecommunications Science,2019,35(2):125-133.
    [21] 江峰青, 张湧, 时志雄, 等. 基于高频用电数据的工业企业污染物排放监控方法: CN104571050A[P]. 2015-04-29.
    [22] 吴力波, 周阳, 陈海波, 等.基于智能电网大数据的工业企业大气污染排放特征研究[J]. 中国环境管理,2016,8(4):37-42. doi: 10.16868/j.cnki.1674-6252.2016.04.037

    WU L B, ZHOU Y, CHEN H B, et al. Emission characteristics of industrial air pollution by using smart-grid big data[J]. Chinese Journal of Environmental Management,2016,8(4):37-42. doi: 10.16868/j.cnki.1674-6252.2016.04.037
    [23] 杨文涛, 谯鹏, 刘贤赵, 等.2011—2017年中国PM2.5多尺度时空分异特征分析[J]. 环境科学,2020,41(12):5236-5244.

    YANG W T, QIAO P, LIU X Z, et al. Analysis of multi-scale spatio-temporal differentiation characteristics of PM2.5 in China from 2011 to 2017[J]. Environmental Science,2020,41(12):5236-5244.
    [24] MARCHETTI D J, PARIGI G. Energy consumption, survey data and the prediction of industrial production in Italy: a comparison and combination of different models[J]. Journal of Forecasting,2000,19(5):419-440. doi: 10.1002/1099-131X(200009)19:5<419::AID-FOR749>3.0.CO;2-J
    [25] 马春玲, 王进, 孙晨鑫, 等.电力-环保数据融合分析的企业短期排污监测预警[J]. 电子世界,2021(15):37-38.
    [26] 孙开宁, 陈真, 樊茂, 等.基于电力大数据挖掘的重点企业污染防治专项行动方案设计[J]. 供用电,2021,38(4):28-36.

    SUN K N, CHEN Z, FAN M, et al. Design of special action plan for pollution prevention and control of key enterprises based on electric power big data mining[J]. Distribution & Utilization,2021,38(4):28-36.
    [27] 李俊楠, 李会君, 于鹏飞, 等.电力与环保大数据共享在大气污染防治中的应用[J]. 华东科技(学术版),2018(6):9.
    [28] 汲国强, 李笑蓉, 丁健民, 等.基于数据挖掘的唐山地区用电量与空气质量相关性分析[J]. 电子世界,2017(1):22-24. doi: 10.3969/j.issn.1003-0522.2017.01.012
    [29] CAO J, CHENG Y, YU C. Urban air quality management in Xi'an[R]. London: SAGE Publications, 2018.
    [30] KONG T T, WANG Z, YANG H. Governance of the rural “scattered and polluted” enterprises in Tianjin[J]. E3S Web of Conferences,2018,53:04050. doi: 10.1051/e3sconf/20185304050
    [31] 智静, 乔琦, 李艳萍, 等.“散乱污”企业定义及分类管控方法框架[J]. 环境保护,2019,47(20):46-50. doi: 10.14026/j.cnki.0253-9705.2019.20.011

    ZHI J, QIAO Q, LI Y P, et al. The definition and framework of classified control management for dispersed, violative and polluted enterprises[J]. Environmental Protection,2019,47(20):46-50. doi: 10.14026/j.cnki.0253-9705.2019.20.011
    [32] 彭菲, 於方, 马国霞, 等.“2+26”城市“散乱污”企业的社会经济效益和环境治理成本评估[J]. 环境科学研究,2018,31(12):1993-1999. doi: 10.13198/j.issn.1001-6929.2018.09.19

    PENG F, YU F, MA G X, et al. Analysis of social-economic benefits and environmental pollution control costs of "dispersed, disrupted and polluted" enterprises in the "2+26" region[J]. Research of Environmental Sciences,2018,31(12):1993-1999. doi: 10.13198/j.issn.1001-6929.2018.09.19
    [33] 王桥, 厉青, 王中挺, 等.“散乱污”企业遥感动态监管技术及应用[J]. 环境科学研究,2021,34(3):511-522. doi: 10.13198/j.issn.1001-6929.2021.02.04

    WANG Q, LI Q, WANG Z T, et al. Dynamic supervision technology and application of "dispersed, disordered and polluted" enterprises based on remote sensing[J]. Research of Environmental Sciences,2021,34(3):511-522. doi: 10.13198/j.issn.1001-6929.2021.02.04
    [34] 邓勇, 李宏发, 陈吴晓, 等. 一种基于聚类特征树和离群度量化的散乱污企业研判方法: CN112800148A[P]. 2021-05-14.
    [35] 张军. 运用电力大数据倒查监管“散乱污”[N]. 中国环境报, 2019-11-20(2).
    [36] 罗勇智.“电力大数据+环保监管”助力蓝天保卫战[J]. 大众用电,2019,34(3):9-10.

    LUO Y Z. Assisting blue sky protection campaign by “power big data + environmental supervision”[J]. Popular Utilization of Electricity,2019,34(3):9-10.
    [37] 潘丽晖, 李安定, 高树炜.分表计电监管系统在污染防治中的应用与思考[J]. 环境与可持续发展,2021,46(5):151-156. doi: 10.19758/j.cnki.issn1673-288x.202105151

    PAN L H, LI A D, GAO S W. Application status and thoughts of Process Electricity Monitoring System (PEMS) in pollution prevention and control in China[J]. Environment and Sustainable Development,2021,46(5):151-156. doi: 10.19758/j.cnki.issn1673-288x.202105151
    [38] 张增凯, 路雨婷, 赵鹏宇, 等.2019年京津冀重污染天气应急响应经济损失评估[J]. 中国环境科学,2021,41(7):3399-3408. doi: 10.3969/j.issn.1000-6923.2021.07.045

    ZHANG Z K, LU Y T, ZHAO P Y, et al. The assessment of economic cost induced by emergency responses for heavy pollution weather within Jing-Jin-Ji area in 2019[J]. China Environmental Science,2021,41(7):3399-3408. doi: 10.3969/j.issn.1000-6923.2021.07.045
    [39] 姚立峰, 郝萍萍.物联网技术助力“蓝天保卫战”: 监督企业落实错峰生产及重污染天气应急响应措施[J]. 现代信息科技,2019,3(17):163-164. doi: 10.3969/j.issn.2096-4706.2019.17.060

    YAO L F, HAO P P. Internet of Things technology helps “Blue Sky Defense”: supervise enterprises to implement emergency response measures for off-peak production and heavy pollution weather[J]. Modern Information Technology,2019,3(17):163-164. doi: 10.3969/j.issn.2096-4706.2019.17.060
    [40] 唐伟, 滕予非, 靳旦, 等. 基于用电数据的企业生产模式识别及转移生产预警方法: CN111522864B[P]. 2020-11-10.
    [41] 靳旦, 唐伟, 李科峰, 等. 一种基于企业用电数据的环保响应量化方法及装置: CN111524032B[P]. 2020-11-10.
    [42] 严嘉慧, 张禄, 高鑫, 等.基于聚类算法和孤立森林的企业用电画像行为分析[J]. 电子技术与软件工程,2021(7):179-180.
    [43] LI M, LIU H, GENG G N, et al. Anthropogenic emission inventories in China: a review[J]. National Science Review,2017,4(6):834-866. doi: 10.1093/nsr/nwx150
    [44] 李守秀. 济南市燃煤电厂精细化大气污染源清单的构建[D]. 济南: 山东大学, 2019.
    [45] HE M, ZHENG J Y, YIN S S, et al. Trends, temporal and spatial characteristics, and uncertainties in biomass burning emissions in the Pearl River Delta, China[J]. Atmospheric Environment,2011,45(24):4051-4059. doi: 10.1016/j.atmosenv.2011.04.016
    [46] HU X, LIU Q Z, FU Q Y, et al. A high-resolution typical pollution source emission inventory and pollution source changes during the COVID-19 lockdown in a megacity, China[J]. Environmental Science and Pollution Research International,2021,28(33):45344-45352. doi: 10.1007/s11356-020-11858-x
    [47] HUA H, JIANG S Y, SHENG H, et al. A high spatial-temporal resolution emission inventory of multi-type air pollutants for Wuxi City[J]. Journal of Cleaner Production,2019,229:278-288. doi: 10.1016/j.jclepro.2019.05.011
    [48] WANG C, YIN S S, BAI L, et al. High-resolution ammonia emission inventories with comprehensive analysis and evaluation in Henan, China, 2006-2016[J]. Atmospheric Environment,2018,193:11-23. doi: 10.1016/j.atmosenv.2018.08.063
    [49] XING J, LI S W, JIANG Y Q, et al. Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic on the North China Plain: a response modeling study[J]. Atmospheric Chemistry and Physics,2020,20(22):14347-14359. doi: 10.5194/acp-20-14347-2020
    [50] PALLAVIDINO L, PRANDI R, BERTELLO A, et al. Compilation of a road transport emission inventory for the Province of Turin: advantages and key factors of a bottom-up approach[J]. Atmospheric Pollution Research,2014,5(4):648-655. doi: 10.5094/APR.2014.074
    [51] CHEN X J, LIU Q Z, SHENG T, et al. A high temporal-spatial emission inventory and updated emission factors for coal-fired power plants in Shanghai, China[J]. Science of the Total Environment,2019,688:94-102. doi: 10.1016/j.scitotenv.2019.06.201
    [52] 伯鑫, 赵春丽, 吴铁, 等.京津冀地区钢铁行业高时空分辨率排放清单方法研究[J]. 中国环境科学,2015,35(8):2554-2560. doi: 10.3969/j.issn.1000-6923.2015.08.038

    BO X, ZHAO C L, WU T, et al. Emission inventory with high temporal and spatial resolution of steel industry in the Beijing-Tianjin-Hebei Region[J]. China Environmental Science,2015,35(8):2554-2560. doi: 10.3969/j.issn.1000-6923.2015.08.038
    [53] 胡雪, 王鑫, 刘启贞, 等.典型大气污染源动态排放清单编制方法及应用研究[J]. 中国环境监测,2020,36(5):54-62. doi: 10.19316/j.issn.1002-6002.2020.05.08

    HU X, WANG X, LIU Q Z, et al. Research on the technique and application of compiling dynamic emission inventory of typical air pollution sources[J]. Environmental Monitoring in China,2020,36(5):54-62. □ doi: 10.19316/j.issn.1002-6002.2020.05.08
  • 加载中
计量
  • 文章访问数:  284
  • HTML全文浏览量:  170
  • PDF下载量:  59
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-03-25
  • 网络出版日期:  2023-09-04

目录

    /

    返回文章
    返回