Study of atmospheric visibility and its influence factors in six typical cities in China
-
摘要:
采用线性相关性分析、分类变量分析等统计学方法，分析了巴彦淖尔、石家庄、廊坊、郑州、武汉、广州六市2019—2020年的PM2.5与气象观测数据，研究了PM2.5浓度与大气相对湿度对大气能见度的影响。结果表明：六市大气能见度年变化规律虽存在较大差异，但最低值均出现于每年12月—次年2月，且年变化规律基本一致；气象条件、相对湿度、PM2.5浓度对能见度的影响明显，其中相对湿度通过改变PM2.5物化性质间接影响能见度，与能见度相关程度相对较弱。PM2.5浓度与能见度的线性相关性良好，以幂函数为主；整体上，相对湿度与PM2.5浓度对大气能见度影响呈协同作用，相对湿度越大的城市对PM2.5的控制要求越高。此外，PM2.5浓度高于平台点时，大气能见度基本不随PM2.5浓度增加而继续降低，只有PM2.5浓度低于突变点时，大气能见度才会随PM2.5浓度降低而显著提升，各市能见度突变点与平台期点所对应PM2.5浓度差异较大。
Abstract:The statistical methods such as linear correlation analysis and categorical variable analysis were employed to analyze the data of particulate matter and meteorological observations in six cities (Bayannaoer, Shijiazhuang, Langfang, Zhengzhou, Wuhan, Guangzhou) from 2019 to 2020. The influences of particulate matter concentration and atmospheric relative humidity on atmospheric visibility were investigated. The results indicated that there were significant differences in the annual variation of atmospheric visibility among the six cities, but the lowest values consistently occurred from December to February of the following year, and the annual variation pattern was generally consistent. The influences of meteorological conditions, relative humidity, and particulate matter concentration on visibility were apparent, with relative humidity indirectly affecting visibility through changes in the physicochemical properties of particulate matter, but with a relatively weak correlation. There was a good linear correlation between PM2.5 concentration and visibility, mainly following a power function. Overall, relative humidity and particulate matter had a synergistic effect on visibility, and cities with higher relative humidity required stricter control of particulate matter. Additionally, the study found that when PM2.5 concentration was higher than the threshold value, visibility did not continue to decrease with increasing particulate matter, but significantly improved only when PM2.5 concentration was below the threshold value. There was a significant difference in PM2.5 concentration between the turning point and the platform period point associated with visibility in each city.
-
图 1 六市国控大气城市站点与气象站点分布
Figure 1. Distribution map of state-controlled air monitoring points and weather stations in the six cities
图 2 2019—2020年六市PM2.5浓度、PM10浓度、RH与VIS月均值变化趋势
Figure 2. Variation trends of PM2.5, PM10, RH and VIS in the six cities from 2019 to 2020
图 3 2019—2020年六市PM2.5浓度、RH与VIS的月均环比变化率
Figure 3. Monthly average month on month change rate of PM2.5, RH and VIS in the six cities from 2019 to 2020
图 4 六市在不同RH区间平均VIS趋势
Figure 4. Average visibility trends of the six cities in different RH ranges
图 5 六市VIS随PM2.5浓度及RH变化规律
Figure 5. Variation trends of VIS with PM2.5 and RH in the six cities
图 6 六市不同PM2.5浓度区间对应平均VIS变化趋势
Figure 6. Average VIS tendency chart of different CPM2.5 ranges in the six cities
图 7 六市在不同PM2.5浓度区间轻微霾与轻度霾出现频率
Figure 7. Occurrence frequencies of light haze in different PM2.5 ranges in the six cities
表 1 突变点及平台期所对应PM2.5浓度
Table 1. Concentration of PM2.5 corresponding to inflection and plateau points
RH/% 巴彦淖尔/（μg/m3） 石家庄/（μg/m3） 武汉/（μg/m3） 郑州/（μg/m3） 廊坊/（μg/m3） 突变点 平台期 突变点 平台期 突变点 平台期 突变点 平台期 突变点 平台期 ≤40 63 199 68 187 60 191 60 180 40~50 63 195 69 186 66 185 61 179 50~60 59 190 71 180 71 182 65 173 62 171 60~70 60 178 70 171 66 166 53 144 57 160 70~80 56 162 63 152 63 141 46 123 52 140 80~90 56 160 52 125 51 119 37 104 47 119 90~95 44 187 42 95 22 68 47 103 ＞95 29 81 
下载: 导出CSV
-
[1] 张强, 耿冠楠. 中国清洁空气行动对PM2.5污染的影响[J]. 中国科学(地球科学),2020,50(4):439-440. doi: 10.1360/SSTe-2020-0005ZHANG Q, GENG G N. Impact of clean air action on PM2.5 pollution in China[J]. Scientia Sinica (Terrae),2020,50(4):439-440. doi: 10.1360/SSTe-2020-0005 [2] 何镓祺, 于兴娜, 朱彬, 等. 南京冬季气溶胶消光特性及霾天气低能见度特征[J]. 中国环境科学,2016,36(6):1645-1653.HE J Q, YU X N, ZHU B, et al. Characteristics of aerosol extinction and low visibility in haze weather in winter of Nanjing[J]. China Environmental Science,2016,36(6):1645-1653. [3] 孟晓艳, 余予, 张志富, 等. 2013年1月京津冀地区强雾霾频发成因初探[J]. 环境科学与技术,2014,37(1):190-194.MENG X Y, YU Y, ZHANG Z F, et al. Preliminary study of the dense fog and haze events' formation over Beijing-Tianjin-and-Hebei region in January of 2013[J]. Environmental Science & Technology,2014,37(1):190-194. [4] 李蔼恂, 吴昊, 柳艳香, 等. 我国公路低能见度灾害风险评估与区划研究[J]. 气象,2018,44(5):676-683.LI A X, WU H, LIU Y X, et al. Risk assessment and region partition of low visibility disasters on highway in China[J]. Meteorological Monthly,2018,44(5):676-683. [5] 孙岩. 浅谈气象条件与人体健康[C]//第35届中国气象学会年会: 气候环境变化与人体健康. 北京: 中国气象学会, 2018: 160-162. [6] FU D, XIA X, DUAN M, et al. Mapping nighttime PM2.5 from VIIRS DNB using a linear mixed-effect model[J]. Atmospheric Environment,2018,178:214-222. doi: 10.1016/j.atmosenv.2018.02.001 [7] WANG X Y, ZHANG R H, YU W. The effects of PM2.5 concentrations and relative humidity on atmospheric visibility in Beijing[J]. Journal of Geophysical Research:Atmospheres,2019,124:2235-2259. doi: 10.1029/2018JD029269 [8] KOSCHMIEDER H. Theorie der horizontalen sichtweite[J]. Beitr Physik fr Atmos,1924,12:33-55. [9] STOELINGA M T, WARNER T T. Nonhydrostatic, mesobeta-scale model simulations of cloud ceiling and visibility for an east coast winter precipitation event[J]. Journal of Applied Meteorology,1999,38(4):385-404. doi: 10.1175/1520-0450(1999)038<0385:NMSMSO>2.0.CO;2 [10] 陈静, 赵春生. 大气低能见度的影响因子分析及计算方法综述[J]. 气象科技进展,2014,4(4):44-51.CHEN J, ZHAO C S. A review of inlfuence factors and calculation of atmospheric low visibility[J]. Advances in Meteorological Science and Technology,2014,4(4):44-51. [11] 彭爽, 康平, 张小玲, 等. 成都市大气颗粒物粒径分布及其对能见度的影响[J]. 环境科学学报,2020,40(12):4432-4441.PENG S, KANG P, ZHANG X L, et al. Size distribution of atmospheric particles in Chengdu and its influence on visibility[J]. Acta Scientiae Circumstantiae,2020,40(12):4432-4441. [12] CAO J J, WANG Q Y, CHOW J C, et al. Impacts of aerosol compositions on visibility impairment in Xi'an, China[J]. Atmospheric Environment,2012,59:559-566. doi: 10.1016/j.atmosenv.2012.05.036 [13] 余洋, 杨军. 南京2007年12月持续雾霾过程的大气消光特性[J]. 环境科学学报,2016,36(7):2305-2313.YU Y, YANG J. Atmospheric extinction of a persistent fog/haze event in Nanjing during December[J]. Acta Scientiae Circumstantiae,2016,36(7):2305-2313. [14] 张俊峰. 北京市典型区域大气细颗粒物来源分析及对大气能见度影响[D]. 北京: 北京工业大学, 2020. [15] 白永清, 祁海霞, 刘琳, 等. 武汉大气能见度与 PM2.5浓度及相对湿度关系的非线性分析及能见度预报[J]. 气象学报,2016,74(2):189-199.BAI Y Q, QI H X, LIU L, et al. Study on the nonlinear relationship among the visi-bility, PM2.5 concentration and relative humidity in Wuhan and the visibility prediction[J]. Acta Meteorologica Sinica,2016,74(2):189-199. [16] 李军, 王京丽, 屈坤. 相对湿度和PM2.5浓度对乌鲁木齐市冬季能见度的影响[J]. 中国环境科学,2020,40(8):3322-3331.LI J, WANG J L, QU K. Impacts of relative humidity and PM2.5 concentration on atmospheric visibility during winter in Urumqi Urban Area[J]. China Environmental Science,2020,40(8):3322-3331. [17] 生态环境部. 环境空气颗粒物(PM10与PM2.5)连续自动监测系统技术要求及监测方法: HJ 653—2017[S]. 北京: 生态环境部, 2017. [18] 生态环境部. 环境空气颗粒物(PM10与PM2.5)连续自动监测系统技运行和质控技术规范: HJ 817—2018[S]. 北京: 生态环境部, 2018. [19] 中国气象局. 霾的观测和预报等级: QX/T 113—2010[S]. 北京: 气象出版社, 2010. [20] 吕建华, 彭岩波, 谢刚. 2013年济南市大气能见度与RH和PM10、PM2.5浓度的关系[J]. 气象与环境科学,2016,39(4):93-97. [21] 李英华, 姚立英, 姚青, 等. 2013—2016年天津城区大气能见度的变化特征 与影响因素[J]. 环境工程技术学报,2018,8(4):349-358.LI Y H, YAO L Y, YAO Q, et al. Analysis of variation characteristics and influencing factors of atmospheric visibility in Tianjin urban area from 2013 to 2016[J]. Journal of Environmental Engineering Technology,2018,8(4):349-358. [22] 浦静姣, 徐宏辉, 马千里. 长江三角洲背景地区大气污染对能见度的影响[J]. 中国环境科学,2017,37(12):4435-4441.PU J J, XU H H, MA Q L. Impacts of atmospheric pollution on visibility in the background area of Yangtze River Delta, China[J]. China Environmental Science,2017,37(12):4435-4441. [23] 姜江, 张国平, 高金兵. 北京大气能见度的主要影响因子[J]. 应用气象学报,2018,29(2):188-199.JIANG J, ZHANG G P, GAO J B. Main influencing factors of visibility in Beijing[J]. Journal of Applied Meteorological Science,2018,29(2):188-199. [24] 夏志勇, 吕波, 李海滨, 等. 济南市冬季大气颗粒物粒径谱分布特征[J]. 环境工程,2019,37(3):109-112.XIA Z Y, LÜ B, LI H B, et al. Size distribution characteristic of atmospheric particles during winter in Jinan[J]. Environmental Engineering,2019,37(3):109-112. [25] 樊高峰, 马浩, 张小伟, 等. 相对湿度和 PM2.5浓度对大气能见度的影响研究: 基于小时资料的多站对比分析[J]. 气象学报,2016,74(6):959-973.FAN G F, MA H, ZHANG X W, et al. Impacts of relative humidity and PM2.5 concentration on atmospheric vis-ibility: a comparative study of hourly observations of multiple stations[J]. Acta Meteorologica Sinica,2016,74(6):959-973. [26] 张浩, 石春娥, 吴必文, 等. 合肥市能见度与相对湿度、PM2.5质量浓度的定量关系[J]. 生态环境学报,2017,26(6):1001-1008.ZHANG H, SHI C E, WU B W, et al. Quantified relationships among the visibility, relative humidity and PM2.5 mass concentration in Hefei city[J]. Ecology and Environmental Sciences,2017,26(6):1001-1008. [27] 张敏, 崔振雷, 韩素芹, 等. 天津城区大气气溶胶复折射指数的反演及消光贡献分析[J]. 环境科学研究,2019,32(9):1483-1491.ZHANG M, CUI Z L, HAN S Q, et al. The retrieval of aerosol complex refractive index and the contribution rate analyses of extinction coefficient in urban Tianjin City[J]. Research of Environmental Sciences,2019,32(9):1483-1491. [28] 蒋燕, 王斌, 罗彬. PM2.5及其组分对成都大气能见度的影响分析[J]. 环境科学与技术,2017,40(增刊2):211-215.JIANG Y, WANG B, LUO B. The impact of the components of PM2.5 on visibility in Chengdu[J]. Environmental Science & Technology,2017,40(Suppl 2):211-215. [29] 王继康, 张恒德, 桂海林, 等. 能见度与PM2.5浓度关系及其分布特征[J]. 环境科学,2019,40(7):2985-2993.WANG J K, ZHANG H D, GUI H L, et al. Relationship between atmospheric visibility and PM2.5 concentrations and distributions[J]. Environmental Science,2019,40(7):2985-2993. [30] 叶兴南, 陈建民. 灰霾与颗粒物吸湿增长[J]. 自然杂志,2013,35(5):337-341.YE X N, CHEN J M. Haze and hygroscopic growth[J]. Chinese Journal of Nature,2013,35(5):337-341. [31] 许敏, 李江波, 周玉都, 等. 廊坊市雾、霾分布概况及与重污染天气共存时的风场差异[J]. 环境工程技术学报,2020,10(5):814-822.XU M, LI J B, ZHOU Y D, et al. Distribution of fog and haze in Langfang and difference of wind field when coexisting with heavy polluted weather[J]. Journal of Environmental Engineering Technology,2020,10(5):814-822. □ -
下载:
点击查看大图
计量
- 文章访问数: 102
- HTML全文浏览量: 38
- PDF下载量: 32
- 被引次数: 0
