昆明城区大气污染物时空分布特征

郭丽辉; 尹惠敏; 颜翔; 徐小峰; 黄晓

doi:10.12153/j.issn.1674-991X.20210208

昆明城区大气污染物时空分布特征

doi: 10.12153/j.issn.1674-991X.20210208

昆明市生态环境监测站

详细信息

作者简介:
郭丽辉（1972—），女，高级工程师，主要从事大气自动监测和污染控制研究工作，1552758600@qq.com

中图分类号: X513
计量
- 文章访问数: 391
- HTML全文浏览量: 221
- PDF下载量: 74
- 被引次数: 0
出版历程
- 收稿日期: 2021-05-25

Temporal and spatial distribution characteristics of atmospheric pollutants in urban area of Kunming City

Ecological and Environmental Monitoring Station in Kunming

摘要

摘要:
利用2013—2020年昆明城区国控点监测数据，分析大气污染物时空分布特征。结果表明：2013—2020年昆明城区O₃年均浓度总体呈上升趋势，其余污染物年均浓度呈下降趋势，O₃增幅为4.1%，SO₂降幅为67.9%，其余污染物降幅为35.0%~55.0%。超过GB 3095—2012《环境空气质量标准》一级以上标准的首要污染物天数占比显示，O₃已经代替PM_2.5成为昆明市最主要的大气污染物；O₃浓度春季最高，夏季次之，秋季最低；PM₁₀和PM_2.5浓度春、冬季高，夏季最低；SO₂、NO₂、CO浓度冬季最高，夏季最低，但SO₂和NO₂四季变化幅度较其他污染物小。春、夏季的O₃，冬、春季的PM_2.5是昆明市大气污染的防治的重点。O₃浓度日变化呈单峰型分布，CO、NO₂、PM₁₀、PM_2.5浓度呈双峰型分布，但PM₁₀、PM_2.5浓度峰谷变化不明显；NO₂、CO、PM_2.5、PM₁₀浓度峰值出现在早高峰时段，O₃浓度峰值出现在14:00—15:00，SO₂浓度上午高于下午。大气污染物浓度分布具有明显的空间差异性，SO₂、PM_2.5、NO₂、PM₁₀、CO浓度城区西部高于东部，分别高出54.5%、20.0%、17.9%、14.6%和2.4%，O₃浓度则相反，城区东部高于西部，高出9.0%；SO₂、NO₂、O₃浓度东部、西部差异呈逐年减小趋势，不排除上风向安宁工业园区污染传输影响变弱的可能性。
- 大气污染物 /
- 时空分布 /
- 变化趋势 /
- 昆明城区
Abstract:
Based on the monitoring data of national control monitoring stations in the urban area of Kunming in 2013-2020, the temporal and spatial distribution features of atmospheric pollutants were analyzed. The results showed that during the period of 2013-2020, the annually-averaged concentration of O₃ in the urban area of Kunming generally showed an upward trend, and the annually-averaged concentrations of other pollutants showed a downward trend. The annually-averaged concentration of O₃ increased by 4.1%, while that of SO₂ dropped by 67.9% and other pollutants dropped by 35.0%-55.0%. The proportion of days of primary pollutants exceeding Level 1 or above the standard of Ambient Air Quality Standards (GB 3095—2012 ) indicated that O₃ instead of PM_2.5 had become the primary atmospheric pollutant in Kunming. The highest concentration of O₃ appeared in spring, followed by summer, and the lowest in autumn, the concentrations of PM₁₀ and PM_2.5 were generally high in spring and winter but low in autumn, and as for SO₂, NO₂ and CO, the highest concentrations appeared in winter and lowest in summer. But the variation ranges in four seasons of SO₂ and NO₂ were smaller than that of other pollutants. O₃ in spring and summer and PM_2.5 in spring and winter were the key points of air pollutants control in Kunming. The daily variation of O₃ presented single peak distribution, CO, NO₂, PM₁₀ and PM_2.5 presented double peaks distribution, but the variation of peak-valley of PM₁₀ and PM_2.5 concentrations were not distinct. The peaks of NO₂, PM_2.5, PM₁₀ and CO were identical to morning rush hours, the peak of O₃ usually appeared during 14:00-15:00, and the concentration of SO₂ was higher in the morning than in the afternoon. As for spatial distribution patterns, remarkable distinctions existed for different pollutants. The concentrations of SO₂, PM_2.5, NO₂, PM₁₀ and CO of western stations were 54.5%, 20.0%, 17.9%, 14.6% and 2.4%, respectively higher than those of eastern stations. On the contrary, O₃ concentrations in eastern stations were 9.0% higher than that of western stations. The difference of SO₂, NO₂ and O₃ concentrations between eastern and western stations had narrowed down year by year, and this might be caused by the weakening of the impact of pollution transmission from Anning Industrial Park.
- atmospheric pollutant /
- temporal and spatial distribution /
- variation trend /
- urban area of Kunming

HTML全文

图 1 昆明城区空气质量监测站点分布示意

Figure 1. Distribution of urban air quality monitoring points in Kunming

下载: 全尺寸图片幻灯片

图 2 2013—2020年昆明城区大气污染物浓度年际变化趋势

Figure 2. Interannual variation trends of atmospheric pollutants concentration in urban area of Kunming from 2013 to 2020

下载: 全尺寸图片幻灯片

图 3 2016—2020年超过一级标准的首要污染物天数占比

Figure 3. Proportion of days with primary pollutants exceeding the Level 1 standard from 2016 to 2020

下载: 全尺寸图片幻灯片

图 4 2016—2020年昆明城区大气污染物浓度季节变化

Figure 4. Seasonal variation of atmospheric pollutants concentration in urban area of Kunming from 2016 to 2020

下载: 全尺寸图片幻灯片

图 5 2018—2020年昆明城区大气污染物浓度日变化

Figure 5. Diurnal variations of atmospheric pollutants concentration in urban area of Kunming from 2018 to 2020

下载: 全尺寸图片幻灯片

图 6 昆明城区大气污染物浓度空间分布

Figure 6. Spatial distribution of atmospheric pollutants concentration in urban area of Kunming

下载: 全尺寸图片幻灯片

图 7 2016—2020年昆明城区东部、西部站点大气污染物浓度变化比较

Figure 7. Comparison of atmospheric pollutants concentration changes between eastern and western stations in urban area of Kunming from 2016 to 2020

下载: 全尺寸图片幻灯片

表 1 气象参数的季节排序

Table 1. Seasonal ordering of the values of meteorological parameters

气象参数	排序/降水量分布
月均相对湿度	夏季≈秋季>冬季>春季
月均日照时间	春季>秋季>夏季≈冬季
辐射月均值	春季>夏季>冬季>秋季
月均风速	春季>冬季>夏季≈秋季
月均温度	夏季>春季>秋季>冬季
降水量	集中在5—8月，约占全年降水量的85%

下载: 导出CSV

参考文献(19)

[1]	徐锟, 刘志红, 何沐全, 等.成都市夏季近地面臭氧污染气象特征[J]. 中国环境监测,2018,34(5):36-45. XU K, LIU Z H, HE M Q, et al. Meteorological characteristics of O₃ pollution near the ground in summer of Chengdu[J]. Environmental Monitoring in China,2018,34(5):36-45.
[2]	赵熠琳, 原彩红, 刘峥, 等.我国典型南方城市臭氧污染特征[J]. 中国环境监测,2017,33(4):194-200. ZHAO Y L, YUAN C H, LIU Z, et al. Analysis on the characteristics of ozone pollution in typical cities of Southern China[J]. Environmental Monitoring in China,2017,33(4):194-200.
[3]	林燕芬, 王茜, 伏晴艳, 等.上海市臭氧污染时空分布及影响因素[J]. 中国环境监测,2017,33(4):60-67. LIN Y F, WANG Q, FU Q Y, et al. Temporal-spatial characteristics and impact factors of ozone pollution in Shanghai[J]. Environmental Monitoring in China,2017,33(4):60-67.
[4]	张春辉, 刘群, 徐徐, 等.贵阳市臭氧浓度变化及与气象因子的关联性[J]. 中国环境监测,2019,35(3):82-92. ZHANG C H, LIU Q, XU X, et al. The correlation between the characteristics of ozone concentration and meteorological factors in Guiyang[J]. Environmental Monitoring in China,2019,35(3):82-92.
[5]	张智胜, 陶俊, 谢绍东, 等.成都城区PM_2.5季节污染特征及来源解析[J]. 环境科学学报,2013,33(11):2947-2952. ZHANG Z S, TAO J, XIE S D, et al. Seasonal variations and source apportionment of PM_2.5 at urban area of Chengdu[J]. Acta Scientiae Circumstantiae,2013,33(11):2947-2952.
[6]	张殷俊, 陈曦, 谢高地, 等.中国细颗粒物(PM_2.5)污染状况和空间分布[J]. 资源科学,2015,37(7):1339-1346. ZHANG Y J, CHEN X, XIE G D, et al. Pollution status and spatial distribution of PM_2.5 in China[J]. Resources Science,2015,37(7):1339-1346.
[7]	谢运兴, 唐晓, 郭宇宏, 等.新疆大气颗粒物的时空分布特征[J]. 中国环境监测,2019,35(1):26-36. XIE Y X, TANG X, GUO Y H, et al. Spatial and temporal distribution of atmospheric particulate matter in Xinjiang[J]. Environmental Monitoring in China,2019,35(1):26-36.
[8]	李名升, 任晓霞, 于洋, 等.中国大陆城市PM_2.5污染时空分布规律[J]. 中国环境科学,2016,36(3):641-650. doi: 10.3969/j.issn.1000-6923.2016.03.001 LI M S, REN X X, YU Y, et al. Spatiotemporal pattern of ground-level fine particulate matter (PM_2.5) pollution in mainland China[J]. China Environmental Science,2016,36(3):641-650. doi: 10.3969/j.issn.1000-6923.2016.03.001
[9]	王化杰, 张波, 胡昊, 等.安徽省大气污染物时空分布特征及演化规律[J]. 环境科学研究,2018,31(4):628-641. WANG H J, ZHANG B, HU H, et al. Evolution characteristics and spatial-temporal pattern of air pollutants in Anhui Province[J]. Research of Environmental Sciences,2018,31(4):628-641.
[10]	黄晓虎, 韩秀秀, 李帅东, 等.城市主要大气污染物时空分布特征及其相关性[J]. 环境科学研究,2017,30(7):1001-1011. HUANG X H, HAN X X, LI S D, et al. Spatial and temporal variations and relationships of major air pollutants in Chinese cities[J]. Research of Environmental Sciences,2017,30(7):1001-1011.
[11]	符传博, 周航.中国城市臭氧的形成机理及污染影响因素研究进展[J]. 中国环境监测,2021,37(2):33-43. FU C B, ZHOU H. Research progress on the formation mechanism and impact factors of urban ozone pollution in China[J]. Environmental Monitoring in China,2021,37(2):33-43.
[12]	程麟钧. 我国臭氧污染特征及分区管理方法研究[D]. 北京: 中国地质大学(北京), 2018.
[13]	BEDDOWS A V, KITWIROON N, WILLIAMS M L, et al. Emulation and sensitivity analysis of the community multiscale air quality model for a UK ozone pollution episode[J]. Environmental Science & Technology,2017,51(11):6229-6236.
[14]	张朝能, 王梦华, 胡振丹, 等.昆明市PM_2.5浓度时空变化特征及其与气象条件的关系[J]. 云南大学学报(自然科学版),2016,38(1):90-98. ZHANG C N, WANG M H, HU Z D, et al. Temporal and spatial distribution of PM_2.5 concentration and the correlation of PM_2.5 and meteorological factors in Kunming City[J]. Journal of Yunnan University (Natural Sciences Edition),2016,38(1):90-98.
[15]	陈燕. 昆明城市主要空气污染物污染特征及时空分布[J]. 云南环境科学, 2005, 24(增刊2): 102-105 CHEN Y. Pollution characteristics and spatial distribution of air pollutants in Kunming City[J]. Yunnan Environmental Science, 2005, 24(Suppl 2): 102-105
[16]	施择, 毕丽玫, 史建武, 等.昆明多风季节大气PM_2.5污染特征及来源分析[J]. 环境科学与技术,2014,37(12):143-147. SHI Z, BI L M, SHI J W, et al. Characterization and source identification of PM_2.5 in ambient air of Kunming in windy spring[J]. Environmental Science & Technology,2014,37(12):143-147.
[17]	ZHAO W, FAN S J, GUO H, et al. Assessing the impact of local meteorological variables on surface ozone in Hong Kong during 2000-2015 using quantile and multiple line regression models[J]. Atmospheric Environment,2016,144:182-193. doi: 10.1016/j.atmosenv.2016.08.077
[18]	单瑞娟, 吴琳, 杨宁.北京市怀柔区大气污染物浓度变化规律及与其他要素的相关性[J]. 环境工程技术学报,2021,11(4):647-656. doi: 10.12153/j.issn.1674-991X.20200205 SHAN R J, WU L, YANG N. The variation law of air pollutant concentrations and their correlations with other factors in Huairou District, Beijing City[J]. Journal of Environmental Engineering Technology,2021,11(4):647-656. doi: 10.12153/j.issn.1674-991X.20200205
[19]	郭丽辉.昆明市2016—2018年臭氧浓度变化特征[J]. 环境科学导刊,2019,38(5):55-60. GUO L H. The variation characteristics of ozone concentration in Kunming from 2016 to 2018[J]. Environmental Science Survey,2019,38(5):55-60. □