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干旱区地理 ›› 2022, Vol. 45 ›› Issue (4): 1082-1092.doi: 10.12118/j.issn.1000-6060.2021.443

• 气候与水文 • 上一篇    下一篇

2017—2019年中天山北坡城市群大气污染及污染天气类型特征

李淑婷1,2,3(),李霞1,2(),毛列尼·阿依提看1,2,钟玉婷1,2,王慧琴1,2   

  1. 1.中国气象局乌鲁木齐沙漠气象研究所,新疆 乌鲁木齐 830002
    2.中国气象局阿克达拉大气本底野外科学试验基地,新疆 乌鲁木齐 830002
    3.新疆树木年轮生态实验室,新疆 乌鲁木齐 830002
  • 收稿日期:2021-10-03 修回日期:2022-01-20 出版日期:2022-07-25 发布日期:2022-08-11
  • 通讯作者: 李霞
  • 作者简介:李淑婷(1992-),女,助理研究员,主要从事大气环境方面的研究. E-mail: lishuting@idm.cn
  • 基金资助:
    中国沙漠气象科学研究基金(Sqj2019004);中国沙漠气象科学研究基金(Sqj2017013);中央级公益性科研院所基本科研业务费专项资金项目(IDM2020001);石河子冬季重污染天气预报研判科研及业务课题;国家自然科学基金(41575011)

Characteristics of air pollution and its polluted weather types of urban agglomeration on the north slope of the middle Tianshan Mountains from 2017 to 2019

LI Shuting1,2,3(),LI Xia1,2(),Mauren AYIKAN1,2,ZHONG Yuting1,2,WANG Huiqin1,2   

  1. 1. Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, Xinjiang, China
    2. Field Scientific Experiment Base of Akdala Atmospheric Background, China Meteorological Administration, Urumqi 830002, Xinjiang, China
    3. Xinjiang Key Laboratory of Tree-Ring Ecology, Urumqi 830002, Xinjiang, China
  • Received:2021-10-03 Revised:2022-01-20 Online:2022-07-25 Published:2022-08-11
  • Contact: Xia LI

摘要:

利用2017—2019年中天山北坡城市群(乌鲁木齐市、昌吉市、石河子市、五家渠市)逐时大气污染物监测数据及气象数据,分析了大气污染物年内变化和污染天气类型特征。结果表明:(1) 中天山北坡4座城市6类大气污染物中PM2.5超标日数最多(年均94~104 d),年均浓度介于64~73 μg·m-3,且五家渠市>乌鲁木齐市>石河子市>昌吉市。采暖期PM2.5浓度在100~118 μg·m-3之间,是非采暖期的4.00~5.00倍,靠近山前地带的城市PM2.5浓度日变化大体呈现“双峰双谷型”。(2) 4座城市污染天气类型主要分为静稳型、沙尘型和特殊型,其中静稳型占86.2%~93.6%、沙尘型占5.8%~13.2%。静稳型污染天气多出现在冬季,沙尘型主要出现在春、秋季节。静稳型污染天气中Ⅴ-Ⅵ级污染级别占比45.8%~56.6%,沙尘型污染天气中Ⅴ-Ⅵ级污染级别占比14.9%~29.4%。(3) 静稳型和沙尘型污染天气下PM2.5和PM10浓度都存在显著的线性相关,前者PM10浓度是PM2.5的1.26倍,而后者达3.16倍,此倍数可以作为区分静稳型和沙尘型污染天气的判据。

关键词: 超标日, 污染物浓度, 污染天气类型, 静稳型天气, 沙尘型天气

Abstract:

The air pollution in urban agglomeration (Urumqi City, Changji City, Shihezi City, Wujiaqu City) on the north slope of the middle Tianshan Mountains, Xinjiang, china is more serious than that in several eastern urban agglomerations. However, the characteristics of air pollution and corresponding polluted synoptic weathers on the north slope of the middle Tianshan Mountains are poorly understood. Herein, the variation characteristics of air pollutants and polluted synoptic types were analyzed using the hourly air pollutant data and meteorological data of four cities on the north slope of the middle Tianshan Mountains collected from 2017 to 2019. Results showed that: (1) among the six pollutants, PM2.5 was the primary pollutant with the maximum number of days exceeding the second standard of particulate matter in China at nearly 1/3 days (94-104 days) in a whole year. The annual average concentrations of PM2.5 were ranked as follows: Wujiaqu City (73 μg·m-3) > Urumqi City (71 μg·m-3) > Shihezi City (65 μg·m-3) > Changji City (64 μg·m-3). PM2.5 concentration during the heating period was between 100 μg·m-3 and 118 μg·m-3, which was 4.00-5.00 times higher than that during the nonheating period. The diurnal variation of PM2.5 concentration almost followed “bimodal distribution” for the three cities near the mountains but showed “unimodal distribution” for Wujiaqu City. (2) The polluted weather can be divided into three types: stagnant, dusty, and special. 86.2%-93.6% of the study area belonged to stagnant pollution, whereas 5.8%-13.2% experienced dusty pollution. Stagnant pollution mostly occurred in winter, whereas dusty pollution primarily occurred in spring and autumn. Stagnant pollution level V-VI accounted for 45.8%-56.6%, and dusty pollution at the same level accounted for 14.9%-29.4%. (3) The correlation between the PM10 and PM2.5 of these two pollution types was extremely high, and the PM10 to PM2.5 ratios were 1.26 and 3.16 for stagnant and dusty pollution, respectively. These values can be used to distinguish between stagnant and dusty pollution weathers.

Key words: exceedance day, pollutant concentration, polluted weather types, stagnant weather, dusty weather