基于卫星数据识别臭氧生成高值区的方法及其应用

卓俊玲; 朱珊娴; 隆重; 徐炜达; 王宇萌; 李怀瑞

doi:10.12153/j.issn.1674-991X.20220377

基于卫星数据识别臭氧生成高值区的方法及其应用

doi: 10.12153/j.issn.1674-991X.20220377

1.
生态环境部环境工程评估中心
2.
北京英视睿达科技股份有限公司

基金项目: 生态环境部生态环境执法局立项课题“生态环境执法监察”（2111102）

详细信息

作者简介:
卓俊玲（1973—），女，高级工程师，主要从事生态环境执法研究，zhuojl@acee.gov.cn

中图分类号: X51
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- 文章访问数: 314
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-22
- 网络出版日期: 2022-11-25

A satellite-based method and application for identifying high ozone production area

1.
Environmental Engineering Assessment Center, Ministry of Ecology and Environment
2.
Beijing Insights Value Technology Co., Ltd.

摘要

摘要:
近年来，我国臭氧污染问题逐步显现。为持续推动京津冀及周边、汾渭平原等重点区域环境质量改善，生态环境部实施了“千里眼”计划，构建了大气污染网格化监管体系。2020年，针对夏季臭氧污染问题，开展了臭氧生成高值区识别研究，向重点区域生态环境部门、监督帮扶现场工作组推送环境异常信息，为打赢蓝天保卫战提供了重要支撑。利用哨兵-5卫星数据，结合企业清单、用电数据、历史污染源检查问题等数据，通过RFM模型综合挖掘识别臭氧生成高值区。结果表明：京津冀和汾渭平原的大多数城市地区和工业集聚区属于VOCs控制区或VOCs-NO_x共同控制区；该方法推送的臭氧生成高值区问题率为65.3%，高出整体问题率21.5个百分点；高值区内企业发现问题率为27.1%，高出非高值区3.7个百分点，提升了2020年夏季臭氧污染防治监督帮扶的工作成效。高值区问题率、高值区内企业问题率和推送次数有关，实践结果表明，经过重复推送，高值区内企业问题率呈先升后降的规律，企业问题率拐点时间与企业整改完成周期有关。该方法对于以包装印刷、工业涂装为主导的产业集群，应用效果较好。
- 臭氧防治 /
- 精准管控 /
- 卫星数据 /
- HCHO/NO₂ /
- 臭氧生成高值区
Abstract:
Over recent years, ozone pollution has become a prominent issue in China. To perpetuate the improvement of environmental quality in Beijing-Tianjin-Hebei (BTH) Region and its surrounding areas and Fen-Wei Plain, the Ministry of Ecology and Environment launched the Thousand Miles Eye Program to build a grid-based air pollution monitoring system. In 2020, to address the ozone pollution problem during the summer months, a study was conducted to identify high ozone production area and pushed anomaly environmental information to the environmental authorities in key regions and the onsite inspection and assistance teams, thus providing important support for winning the blue sky defense war. Based on the data from Sentinel-5P satellite, and combined with the enterprise data inventories, electricity consumption data, pollution source inspection records, and so on, high ozone production areas were identified and located through the RFM model. The findings of the study showed that most urban areas and industrial clusters in the BTH region and Fen-Wei Plain were located within VOC-control areas or VOC-NO_x-cooperative control areas. The problem rate of high ozone production areas pushed by the method was 65.3%, 21.5 percentage points higher than the overall problem rate. The problem rate among enterprises in high ozone production areas was 27.1%, 3.7 percentage points higher than those in non-high ozone production areas. This methodology improved the efficacy of inspection and assistance in ozone pollution inspection and control during the summer of 2020. The problem rate of high ozone production areas and the problem rate of enterprises in high ozone production areas were correlated with the times of push notifications of high ozone production areas; and the practice results showed that after repeated pushes of such notifications, the rate of problematic enterprises in high ozone production areas showed a pattern of rising first before falling, and the inflection point of the problem rate of enterprises was correlational to their cycle of rectification. This methodology proves more effective with industrial clusters dominated by packaging printing and industrial painting businesses.
- ozone pollution reduction /
- precise control /
- satellite data /
- HCHO/NO₂ ratio /
- high ozone production area

HTML全文

图 1 高值区识别技术路线

Figure 1. Technical route for high ozone production area identification

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图 2 高值区识别流程及结果示例

Figure 2. Example of high ozone production area identification process and results

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图 3 监督帮扶期间NO₂柱浓度和HCHO柱浓度分布

Figure 3. Distribution of NO₂ and HCHO column concentration during the inspection and assistance period

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图 4 不同时段O₃控制区占比

Figure 4. Percentage of ozone control areas in different periods

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图 5 HCHO/NO₂和涉VOCs企业空间分布

Figure 5. Distribution of HCHO/NO₂ ratio and enterprises involving VOCs

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图 6 京津冀和汾渭平原44个城市的HCHO/NO₂

Figure 6. HCHO/NO₂ ratio of 44 cities in BTH Region and Fen-Wei Plain

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图 7 各时间段高值区分布及检查情况统计

Figure 7. Distribution of high ozone production areas and statistics of inspection in each period

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图 8 HCHO/NO₂和问题企业分布

Figure 8. Distribution of HCHO/NO₂ ratio and problematic enterprises

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图 9 高值区推送次数及高值区企业问题率统计

Figure 9. Number of push notifications on high ozone production areas and the problem rate of enterprises in high ozone production areas

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图 10 7类行业涉VOCs的问题企业数及问题率

Figure 10. Problems number and rate of enterprises in 7 types of industries involving VOCs

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表 1 各轮次检查中发现的问题企业数量统计

Table 1. Statistics of problematic enterprises found in each round of inspection

检查轮次	高值区推送批次	整体区域			高值区
检查轮次	高值区推送批次	检查企业数	问题企业数	企业问题率/%	检查企业数	问题企业数	企业问题率/%
第1轮	1、2	8 729	3 130	35.9	771	289	37.5
第2轮	2、3	11 182	2 604	23.3	913	263	28.8
第3轮	5、6	12 325	2 473	20.1	1 375	337	24.5
第4轮	7、8	10 279	2 136	20.8	888	202	22.7
第5轮	9、10	8 555	1 773	20.7	639	152	23.8
总计		51 070	12 116	23.7	4 586	1 243	27.1

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表 2 推送4次及以上高值区的各检查轮次企业问题率

Table 2. Problem rate of enterprises in high ozone production areas pushed four times and above in each round of inspection %　

检查轮次	所有高值区	推送5次高值区	推送4次高值区
第1轮	35.9	57.1	58.2
第2轮	23.3	28.6	37.2
第3轮	20.1	50.0	30.0
第4轮	20.8	26.9	30.5
第5轮	20.7	18.8	15.9

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表 3 7类行业高值区和非高值区的企业问题率

Table 3. Problem rate of enterprises in the 7 types of industries in high- and non-high ozone production areas

行业类型	高值区				非高值区				企业问题率差值/%
行业类型	无问题企业数	问题企业数	合计	企业问题率/%	无问题企业数	问题企业数	合计	企业问题率/%	企业问题率差值/%
包装印刷	242	128	370	34.6	2 753	1 108	3 861	28.7	5.9
工业涂装	2 278	724	3 002	24.1	24 717	5 684	30 401	18.7	5.4
化工	623	316	939	33.7	6 557	3 310	9 867	33.5	0.1
加油站	32	17	49	34.7	500	247	747	33.1	1.6
石化	73	31	104	29.8	630	303	933	32.5	−2.7
油气储存					2	1	3	33.3
其他行业	95	27	122	22.1	452	220	672	32.7	−10.6
总计	3 343	1 243	4 586	27.1	35 611	10 873	46 484	23.4	3.7

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