山东省环境空气中PM<sub>2.5</sub>与O<sub>3</sub>的复合污染特征与时空变化趋势

张淼; 丁椿; 孟赫; 高健; 李彦; 王桂霞; 林晶晶; 许杨

doi:10.13198/j.issn.1001-6929.2022.11.02

山东省环境空气中PM_2.5与O₃的复合污染特征与时空变化趋势

doi: 10.13198/j.issn.1001-6929.2022.11.02

张淼^1,,
丁椿²,
孟赫³,
高健⁴,
李彦¹,
王桂霞¹,
林晶晶¹,
许杨^1, ,

1.
山东省生态环境监测中心，山东济南　250101
2.
中科三清科技有限公司，北京　100029
3.
山东省青岛生态环境监测中心，山东青岛　266003
4.
中国环境科学研究院，北京　100012

基金项目: 山东省自然科学基金重大基础研究项目(No.ZR2020ZD21)；山东省自然科学基金面上项目(No.ZR2021MD013)

详细信息

作者简介:
张淼（1979-），男，山东烟台人，高级工程师，硕士，主要从事环境空气质量预报与监测研究，zhangmiao@shandong.cn

通讯作者:
许杨(1968-)，男，山东济南人，研究员，主要从事生态环境监测研究，xuyang8659@163.com

中图分类号: X131.1
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出版历程
- 收稿日期: 2022-08-30
- 修回日期: 2022-10-12

Characteristics and Spatiotemporal Variation of PM_2.5 and O₃ in Shandong Province

1.
Shandong Provincial Eco-Environment Monitoring Center, Jinan 250101, China
2.
Clear Science & Technology Co., Ltd., Beijing 100029, China
3.
Qingdao Eco-Environment Monitoring Center of Shandong Province, Qingdao 266003, China
4.
Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Funds: Shandong Provincial Natural Science Foundation, China (No.ZR2020ZD21, ZR2021MD013)

摘要

摘要: 山东省PM_2.5-O₃复合污染特征突出，空间差异性明显，本文基于2016—2020年国控和省控环境空气自动监测站监测数据以及同期各气象代表站气象监测数据，分析PM_2.5和O₃时空分布的变化特征，初步探究其与气象因子及前体物的关系. 结果表明：①2016—2020年山东省空气质量逐步改善，优良天数比例上升了7.1%，重污染天数比例下降了3.5%. 除O₃年评价值上升9.6%以外，SO₂、PM₁₀、PM_2.5、CO和NO₂的浓度均下降，降幅依次为61.3%、29.8%、28.6%、26.3%和11.4%. 各市PM_2.5年评价值均下降(范围为18.4%~34.9%)；除德州市外，其他15市O₃年评价值均上升，滨州市的升幅(30.8%)最大. 1月PM_2.5平均浓度最高，呈现先下降后上升的年变化趋势，6月O₃平均浓度最高，且逐年上升. ②山东省PM_2.5和O₃均呈现内陆地区高于沿海地区的分布特征，PM_2.5浓度在西部内陆地区较高，O₃浓度在中北部内陆地区较高，PM_2.5-O₃复合污染特征在中西部地区较明显. 统计期间共计出现PM_2.5-O₃复合污染日224 d，分布在2—11月，出现天数逐年减少. ③为探究PM_2.5-O₃复合污染的影响因素及气象特征，进行相关性分析及气象因子阈值筛查，结果表明，PM_2.5日均浓度和O₃_8 h (臭氧日最大8小时滑动平均值)与其主要前体物和气象因子均呈现相反的相关关系，且对不同因子的响应有一定区域性差异. 当气温为14.9~24.1 ℃、相对湿度为55.5%~75.1%、风速为0.6~2.9 m/s、气压为992.8~1 018.8 hPa时PM_2.5-O₃复合污染易于发生，该条件下大部分城市的气温、相对湿度和气压平均值介于PM_2.5和O₃污染单独发生时的对应因子平均值，但平均风速小于PM_2.5和O₃污染单独发生的平均风速. 研究显示，“十三五”期间山东省PM_2.5浓度波动下降，O₃浓度波动上升，二者的协同关系日趋明显，气象因素对PM_2.5和O₃的生成和累积有一定影响.
- PM_2.5和O₃ /
- 污染特征 /
- 时空分布 /
- 气象因子 /
- 山东省
Abstract: The composite characteristics of PM_2.5-O₃ in Shandong Province were relatively prominent and also showed obvious spatial differences. To study characteristics of co-pollution of surface O₃ and PM_2.5 in Shandong province, the spatial distribution of the PM_2.5 and O₃ concentration was analyzed, and the relationship between O₃ and PM_2.5, meteorological parameters and their precursors was explored based on the monitoring data of national and provincial ambient air quality monitoring sites and meteorological sites from 2016 to 2020. The results indicated that: (1) During 2016-2020, the air quality in Shandong Province improved gradually, the number of days with excellent and good air quality increased by 7.1%, and heavily polluted days decreased by 3.5%. Except for the 90th percentile of the maximum daily 8-hour average of the O₃ concentration (O_{3 MDA8}^90th), which increased by 9.6%, the concentration of SO₂, PM₁₀, PM_2.5, CO and NO₂ decreased by 61.3%, 29.8%, 28.6%, 26.3% and 11.4%, respectively. The annual average PM_2.5 values of all cities in Shandong Province decreased by 18.4% to 34.9%. The O_{3 MDA8}^90th increased in all the cities except for Dezhou City. The largest increasing ratio of O_{3 MDA8}^90th was 30.8% in Binzhou City. The highest average PM_2.5 concentration occurred in January, while the highest average O₃ concentration occurred in June. The PM_2.5 concentration in January decreased and then increased from 2016 to 2020, while the O₃ concentration in June increased from 2016 to 2020. (2) The PM_2.5 and O₃ concentration in inland cities was higher than those in coastal cities. PM_2.5 concentration in the western inland area was higher, and O₃ concentration in central and northern inland area was higher. The synergistic pollution characteristics of PM_2.5 and O₃ were obvious in the central and western Shandong Province. During the whole study period, there were 224 days of the synergistic pollution of PM_2.5 and O₃, which mainly occurred from February to November. The number of PM_2.5 and O₃ synergistic pollution days decreased year by year. (3) The correlations between PM_2.5 or O₃ concentration and meteorological factors, and the thresholds of meteorological factors during PM_2.5, O₃ or PM_2.5-O₃ composite pollutant days were also studied. The results showed that the daily average PM_2.5 and O₃_8 h concentrations had negative correlations with their precursors and meteorological parameters. Moreover, there were spatial differences in the correlations between PM_2.5 and O₃, their precursors and meteorological parameters. The statistical results showed that PM_2.5-O₃ complex pollution was favorable to occur when the atmospheric temperature, relative humidity, wind speed, and atmospheric pressure were 14.9-24.1 °C, 55.5%-75.1%, 0.6-2.9 m/s, and 992.8-1018.8 hPa, respectively. In most cities of Shandong Province, the average values of atmospheric temperature, relative humidity and atmospheric pressure during the synergistic pollution of PM_2.5 and O₃ were between those during the PM_2.5 pollution and those during the O₃ pollution. But the average wind speed during the synergistic pollution of PM_2.5 and O₃ was lower than those during the PM_2.5 pollution and during the O₃ pollution. In summary, the study showed that the PM_2.5 concentration decreased overall, while O₃ concentration increased, and the synergistic changes of PM_2.5 and O₃ became more obvious during the ‘13th Five-Year Plan’ period. Meteorological factors played a role in the formation and accumulation of PM_2.5 and O₃.
- PM_2.5 and O₃ /
- pollution characteristics /
- temporal and spatial distribution /
- meteorological factors /
- Shandong Province

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图 1 山东省国控和省控环境空气监测点分布

Figure 1. Location of national and provincial ambient air quality monitoring sites in Shandong Province

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图 2 2016—2020年山东省PM_2.5及O₃_8 h污染等级占比

Figure 2. Proportions of levels of PM_2.5 and O₃ pollution in Shandong Province from 2016 to 2020

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图 3 2016—2020年山东省PM_2.5及O₃年评价值的空间分布

Figure 3. Spatial distribution of the annual average concentrations of PM_2.5 and O₃ in Shandong Province

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图 4 2016—2020年山东省各市PM_2.5和O₃年评价值

Figure 4. Annual average concentrations of PM_2.5 and O₃ in each city of Shandong Province from 2016 to 2020

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图 5 2016—2020年山东省O₃、PM_2.5、气温和相对湿度的月变化

Figure 5. Monthly variations of O₃ , the PM_2.5 concentrations, atmospheric temperature and relative humidity in Shandong Province from 2016 to 2020

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图 6 2016—2020年东营市O₃_8 h超标下O₃_8 h和PM_2.5浓度的散点图

Figure 6. Scatter plot of O₃_8 h and PM_2.5 under O₃_8 h exceeding standard in Dongying City from 2016 to 2020

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图 7 山东省各市PM_2.5-O₃复合污染日、O₃超标日和PM_2.5超标日的平均气温

Figure 7. Average temperature in the days of the synergistic pollution of PM_2.5 and O₃, the PM_2.5 pollution and the O₃ pollution in each city of Shandong Province

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图 8 山东省各市PM_2.5-O₃复合污染日、O₃超标日和PM_2.5超标日的平均相对湿度

Figure 8. Average relative humidity in the days of the synergistic pollution of PM_2.5 and O₃, the PM_2.5 pollution and the O₃ pollution in each city of Shandong Province

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图 9 山东省各市PM_2.5-O₃复合污染日、O₃超标日和PM_2.5超标日的平均气压

Figure 9. Average air pressure in the days of the synergistic pollution of PM_2.5 and O₃, the PM_2.5 pollution and the O₃ pollution in each city of Shandong Province

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图 10 山东省各市PM_2.5-O₃复合污染日、O₃超标日和PM_2.5超标日的平均风速

Figure 10. Average wind speed in the days of the synergistic pollution of PM_2.5 and O₃, the PM_2.5 pollution and the O₃ pollution in each city of Shandong Province

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表 1 2016—2020年山东省常规污染物、优良日和重污染日率、综合指数及气象要素平均值

Table 1. Annual average values of air pollutants, proportions of excellent, good and heavily polluted days, composite air quality index and meteorological parameters in Shandong Province from 2016 to 2020

年份	SO₂年评价值/(μg/m³)	NO₂年评价值/(μg/m³)	PM₁₀年评价值/(μg/m³)	PM_2.5年评价值/(μg/m³)	O₃年评价值/(μg/m³)	CO年平均值/ (mg/m³)	优良天数占比/%	重污染天数占比/%	综合指数	年均气温/℃	年均相对湿度(RH)/%
2016	31	35	114	63	157	1.9	63.0	5.9	6.29	15.1	60.4
2017	21	34	101	54	171	1.7	65.1	3.5	5.67	15.1	57.8
2018	15	33	92	47	169	1.5	68.0	3.1	5.16	15.2	61.0
2019	14	35	94	50	186	1.5	59.7	3.4	5.42	15.3	62.9
2020	12	31	80	45	172	1.4	70.1	2.4	4.84	14.7	65.5

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表 2 2016—2020年山东省各污染物作为首要污染物的天数

Table 2. The number of the days of different primary pollutants in Shandong Province from 2016 to 2020

年份	各污染物作为首要污染物的天数/d
年份	PM₁₀	O₃_8 h	PM_2.5	NO₂	SO₂
2016	103.4	94.1	132.3	1.8	0.1
2017	106.1	118.9	102.9	3.1	0
2018	103.0	133.7	84.4	4.8	0
2019	92.6	141.5	91.1	7.0	0
2020	77.4	140.2	94.5	6.9	0

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表 3 2016—2020年山东省各月累积PM_2.5-O₃复合污染日统计

Table 3. The monthly numbers of PM_2.5-O₃ co-pollution days in Shandong Province from 2016 to 2020

年份	PM_2.5-O₃复合污染日数/d
年份	1月	2月	3月	4月	5月	6月	7月	9月	10月	11月	12月	合计
2016	0	0	12	22	16	12	11	49	2	0	0	124
2017	0	0	1	10	4	19	3	4	0	0	0	41
2018	0	0	10	14	2	0	0	0	0	1	0	27
2019	0	1	0	9	1	0	1	0	3	0	0	15
2020	0	0	0	3	2	2	0	0	10	0	0	17

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表 4 山东省各市PM_2.5及O₃_8 h与其前体物和气象因素的双变量相关分析

Table 4. Bivariate correlation analysis between PM_2.5 and O₃, their precursors and meteorological factors in each city of Shandong Province

地区	v			T			RH			P			SO₂			NO₂			CO			PM_2.5-O₃_8 h
地区	v¹⁾	v- PM_2.5	v- O_{3_}8 h	T²⁾	T- PM_2.5	T- O_{3_}8 h	RH³⁾	RH- PM_2.5	RH- O_{3_}8 h	P⁴⁾	P- PM_2.5	P- O_{3_}8 h	SO₂⁵⁾	SO₂- PM_2.5	SO₂- O_{3_}8 h	NO₂⁶⁾	NO₂- PM_2.5	NO₂- O_{3_}8 h	CO⁷⁾	CO- PM_2.5	CO- O_{3_}8 h	PM_2.5⁸⁾	O₃_8 h⁹⁾	O₃_8 h- PM_2.5
济宁市	0.9	−0.18	−0.11	16.1	−0.59	0.77	62.2	0.14	−0.27	1016.2	0.13	−0.23	15.5	0.43	−0.03	35.0	0.62	−0.39	1.5	0.85	−0.37	53.0	184.5	−0.34
临沂市	2.1	−0.17	−0.16	14.9	−0.50	0.75	64.4	0.08	−0.08	1017.4	0.41	−0.62	13.5	0.63	−0.20	36.0	0.7	−0.27	1.6	0.85	−0.20	53.0	182.5	−0.25
潍坊市	1.5	−0.33	−0.08	14.6	−0.49	0.74	61.6	0.07	−0.13	1017.3	0.36	−0.64	12.0	0.59	−0.36	34.5	0.69	−0.33	1.7	0.9	−0.36	50.5	174.0	−0.24
泰安市	1.2	−0.19	−0.07	14.7	−0.51	0.78	61.3	0.17	−0.16	1017.6	0.39	−0.68	14.5	0.51	−0.09	32.5	0.64	−0.36	1.5	0.8	−0.39	50.5	189.0	−0.30
济南市	1.5	−0.20	0.15	15.5	−0.51	0.83	54.6	0.15	−0.18	1017.2	0.38	−0.72	14.0	0.58	−0.30	38.0	0.61	−0.41	1.6	0.83	−0.38	50.5	195.0	−0.33
淄博市	1.2	−0.33	−0.08	14.4	−0.49	0.74	63.5	0.07	−0.13	1017.2	0.36	−0.64	18.5	0.59	−0.36	40.0	0.69	−0.33	1.9	0.9	−0.36	54.5	196.0	−0.24
滨州市	1.6	−0.31	−0.13	14.3	−0.41	0.77	61.5	0.15	−0.05	1017.1	0.22	−0.55	18.0	0.51	−0.17	37.5	0.64	−0.34	1.6	0.85	−0.17	50.0	197.5	−0.22
东营市	1.4	−0.29	0.02	14.7	−0.40	0.8	60.6	0.15	−0.07	1017.3	0.27	−0.68	15.0	0.47	−0.07	33.5	0.63	−0.28	1.4	0.86	−0.13	46.5	188.0	−0.19
聊城市	1.0	−0.16	−0.07	14.7	−0.56	0.8	66.4	0.24	−0.18	1017.0	0.12	−0.22	14.0	0.36	−0.07	36.5	0.58	−0.40	1.7	0.86	−0.38	56.0	188.0	−0.36
德州市	1.3	−0.19	−0.08	14.6	−0.54	0.84	61.8	0.26	−0.15	1017.0	0.39	−0.74	14.0	0.51	−0.28	31.5	0.63	−0.51	1.6	0.88	−0.43	52.5	191.5	−0.39
菏泽市	1.9	−0.19	0.04	15.9	−0.62	0.79	63.4	0.26	−0.33	1016.8	0.38	−0.54	12.5	0.31	−0.04	31.5	0.55	−0.39	1.4	0.84	−0.35	56.0	179.5	−0.40
枣庄市	1.3	−0.02	−0.07	15.8	−0.56	0.71	63.9	0.07	−0.24	1017.3	0.25	−0.31	16.5	0.41	−0.01	32.0	0.69	−0.29	1.4	0.89	−0.35	56.5	183.0	−0.29
日照市	2.2	−0.03	−0.07	14.4	−0.44	0.67	67.9	0.1	0.09	1017.3	0.34	−0.56	9.0	0.59	−0.17	33.0	0.63	−0.12	1.5	0.82	−0.24	40.5	163.0	−0.20
青岛市	2.6	−0.08	−0.22	14.1	−0.47	0.66	68.9	0.12	0.18	1017.3	0.04	−0.05	8.0	0.69	−0.34	30.5	0.68	−0.27	1.4	0.87	−0.26	35.0	146.5	−0.20
威海市	2.7	−0.26	−0.06	13.9	−0.33	0.57	62.0	0.08	−0.05	1017.2	0.21	−0.53	5.5	0.64	−0.01	18.0	0.71	−0.12	1.0	0.87	−0.11	26.0	151.0	0.03
烟台市	2.7	−0.18	−0.09	13.5	−0.34	0.67	63.0	0.08	−0.01	1017.3	0.25	−0.58	8.5	0.64	−0.22	25.5	0.71	−0.20	1.3	0.83	−0.26	33.0	155.5	−0.11
内陆地区	1.4	0.21	0.05	15.0	0.52	0.78	62.1	0.15	0.16	1017.1	0.31	0.55	14.8	0.49	0.17	34.9	0.64	0.36	1.6	0.86	0.32	52.5	187.4	0.30
沿海地区	2.6	0.14	0.11	13.9	0.4	0.64	65.4	0.1	0.05	1017.3	0.21	0.43	7.8	0.64	0.19	26.8	0.68	0.18	1.3	0.85	0.22	33.6	154.0	0.12
山东省	1.7	−0.19	−0.09	14.7	−0.49	0.74	62.9	0.14	−0.11	1017.2	0.28	−0.52	13.1	0.53	−0.17	32.8	0.65	−0.31	1.5	0.86	−0.30	47.8	179.0	−0.25
注：1)v单位为m/s；2)T单位为℃；3)RH单位为%；4)P单位为hPa；5)SO₂浓度单位为μg/m³；6)NO₂浓度单位为μg/m³；7)CO浓度单位为mg/m³；8)PM_2.5浓度单位为μg/m³；9)O₃_8 h浓度单位为μg/m³.

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