徐州市供暖期空气污染特征及来源分析

冯春莉; 饶永才; 孟庆江; 李辉; 邓国庆; 孙瑞

doi:10.12153/j.issn.1674-991X.20220300

徐州市供暖期空气污染特征及来源分析

doi: 10.12153/j.issn.1674-991X.20220300

江苏省徐州环境监测中心

基金项目: 徐州市重点研发计划项目（社会发展KC20057）

详细信息

作者简介:
冯春莉(1988—)，女，高级工程师，硕士，主要从事大气环境监测与管理，fcljulia@163.com

中图分类号: X51
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出版历程
- 收稿日期: 2022-03-30

Characteristics and sources apportionment of air pollution during heating period in Xuzhou

Xuzhou Environmental Monitoring Center, Jiangsu Province

摘要

摘要:
徐州市大气污染物浓度近年来下降明显，但供暖期的大气污染问题依然较为严重，研究供暖期空气污染特征及污染来源对于大气污染预警和防控具有重要作用。采用地面监测、遥感卫星监测、PM_2.5组分分析、潜在源贡献因子法(PSCF)以及浓度权重轨迹分析(CWT)等方法，对徐州市2016—2020年5个供暖期的空气污染特征进行了分析，并对供暖期PM_2.5来源进行了解析。结果表明：徐州市空气质量近年来有较大好转，但供暖期污染物浓度明显高于非供暖期。供暖对PM_2.5浓度影响较大，供暖期PM_2.5浓度较供暖前后升高40%~71%。供暖期Cl⁻、NO₃ ⁻、SO₄ ²⁻和NH₄ ⁺浓度明显高于供暖前后，说明供暖期NH₄ ⁺与NO₃ ⁻、SO₄ ²⁻、Cl⁻有高度相关性。PM_2.5来源中燃煤源、工业源贡献占比供暖期分别较供暖后高出9.9%和13.9%，供暖期间的SOR、NOR明显大于非供暖期，SO₂和NO_x的二次转化效率明显升高。轨迹分析表明，供暖期影响徐州市的潜在源区主要分布在徐州市周边及河北省，PM_2.5浓度大于75 μg/m³的主要贡献区集中在山东省、河南省、安徽省北部和河北省南部。
- 供暖期 /
- PM_2.5 /
- PSCF /
- CWT /
- 源解析 /
- 贡献区
Abstract:
The concentrations of air pollutants in Xuzhou have decreased significantly in recent years. However, the problem of air pollution during the heating periods is still serious. Studying the characteristics and sources of air pollution during the heating periods plays an important role in the early warning and prevention and control of air pollution. A set of approaches, such as ground monitoring, remote sensing satellite monitoring, PM_2.5 composition analysis, potential source contribution factor method (PSCF) and concentration-weighted trajectory analysis (CWT), were comprehensively adopted. The air pollution characteristics of Xuzhou in five heating periods from 2016 to 2020 were analyzed, and the sources of PM_2.5 in the heating periods were analyzed. The results showed that the air quality in Xuzhou had significantly improved in recent years, but the concentrations of most air pollutants during the heating periods were significantly higher than that in the non-heating periods. The heating had a great impact on the concentration of PM_2.5, and during the heating periods, the concentration of PM_2.5 increased by 40%-71% compared with those before and after the heating periods. The concentrations of Cl⁻, NO₃ ⁻, SO₄ ²⁻, and NH₄ ⁺ in the heating periods were significantly higher than those before and after the heating periods, indicating that the concentration of NH₄ ⁺ had a strong correlation with NO₃ ⁻, SO₄ ²⁻ and Cl⁻ during the heating periods. The contribution of coal combustion and industrial emission to PM_2.5 during the heating periods was 9.9% and 13.9%, respectively, higher than that after the heating periods, the SOR and NOR during the heating periods were significantly higher than those in non-heating periods, and the secondary conversion efficiency of SO₂ and NO_x increased significantly. The trajectory analysis indicated that the potential source areas contributed to Xuzhou during the heating periods were mainly distributed in Hebei Province and the areas neighboring Xuzhou, and the main contributing areas with PM_2.5 concentration higher than 75 µg/m³ were from Shandong, Henan, northern Anhui, and southern Hebei.
- heating period /
- PM_2.5 /
- PSCF /
- CWT /
- source apportionment /
- contributing areas

HTML全文

图 1 2016—2020年供暖前、供暖期和供暖后污染物浓度

Figure 1. Pollutant concentrations before, during and after heating periods in 2016-2020

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图 2 2020年供暖前、供暖期和供暖后大气PM_2.5的PMF因子

Figure 2. PMF factor diagram of PM_2.5 before, during and after heating period in 2020

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图 3 2020年供暖期前、供暖期和供暖后PM_2.5来源分析结果

Figure 3. Source apportionment results before, during and after heating period in 2020

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图 4 徐州市与其周边城市供暖期PM_2.5浓度对比

Figure 4. PM_2.5 concentrations in Xuzhou Cith and its surrounding cities during heating periods

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图 5 供暖期间气象要素及颗粒物污染风玫瑰图

注：图中数字为风速，m/s。

Figure 5. Wind rose of meteorological elements and particulate pollution during heating periods

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图 6 2019年供暖期间后向轨迹

Figure 6. Backward trajectory during heating period in 2019

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图 7 2019年供暖期间潜在源区（PSCF）、贡献（CWT）分析

Figure 7. Potential source contribution factor (PSCF) and concentration-weighted trajectory (CWT) analysis of heating period in 2019

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表 1 供暖前、供暖期和供暖后PM_2.5各组分浓度占比

Table 1. Proportion of PM_2.5 component concentration before, during and after heating periods %　

时期	Cl⁻	NO₃ ⁻	SO₄ ²⁻	Na⁺	NH₄ ⁺	K⁺	Mg²⁺	Ca²⁺	EC	OM	无机元素
供暖前	3.5	36.8	13.3	0.5	16.7	1.0	0.1	0.7	2.1	20.8	4.3
供暖期	4.6	37.2	11.4	0.3	16.4	1.0	0.1	0.6	2.2	21.5	4.8
供暖后	2.9	33.7	13.0	0.7	16.1	0.9	0.2	0.9	3.3	21.4	6.9

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