Characteristics of the air pollution and the causes of heavy air pollution in winter in the northern slope of Tianshan Mountains: case study of Shihezi City
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摘要:
以天山北坡典型代表城市石河子市为例,基于地面常规污染物浓度监测、气象观测、激光雷达观测及中尺度气象模型(WRF)模拟资料,综合分析了气象条件和边界层结构变化对空气质量的影响。结果表明:以石河子市为代表的天山北坡地区空气质量季节性差异显著,PM2.5浓度在冬、夏两季相差最高达11.4倍,且冬季(12月—次年2月)大气污染发生率高达81.2%,重度及以上污染天气占59.1%。冬季污染呈连续“污染季”变化特征,在2020—2021年冬季发生的4次重污染过程中,每次重污染过程持续时间为7~27 d,间隔仅1~3 d,各过程均以PM2.5污染为主导,PM2.5峰值浓度为373~425 μg/m3,PM2.5/PM10均值为0.82。进入秋冬季后,地面连续低温、高湿的气象条件对PM2.5浓度的增长有显著促进作用,以温度<−3 ℃和65%<相对湿度<92%为主要影响条件,在该条件下边界层高度的显著降低和连续强逆温引起的近地扩散条件转差,是冬“污染季”形成的根本原因。在2021年1月16—22日重污染过程期间,地面为持续低温、高湿、微/静风状态,重污染生消仅随边界层和逆温条件改变,其中污染累积时段边界层高度较清洁时段降低近5倍,逆温强度超过1.5 ℃/(100 m),后续由逆温的减退和边界层抬升带来3 d清洁天气。
Abstract:Taking Shihezi City, a typical city on the northern slope of Tianshan Mountains, as the case, based on the ground conventional pollutant monitoring, meteorological observation, the LiDAR observation, and the mesoscale Weather Research and Forecast (WRF) model simulation results, the impact of meteorological parameters and boundary layer structure changes on the air quality in Shihezi City were comprehensively analyzed. The results showed that the seasonal differences of air quality in Shihezi City were quite significant, with the highest difference of 11.4 times of PM2.5 concentrations between winter and summer, and the occurrence rate of air pollution episodes in December to February in winter is as high as 81.2%, with 59.1% of heavy and above polluted days. In the winter of 2020-2021, four heavy pollution processes occurred, and each heavy pollution process lasted for 7-27 d, with the interval period of only 1-3 d. Each process was dominated by fine particle pollution. In total, the period of December-February could be considered as a continuous "pollution season", with the peak value of 373-425 μg/m3 of PM2.5, and the average value of 0.82 for PM2.5/PM10. After entering autumn and winter, the continuous low temperature and high humidity meteorological conditions on the ground had a significant negative effect on PM2.5 concentration, and the main influence conditions were T<−3 ℃ and 65%<RH<92%. Under these conditions, the significant declining of boundary layer height and the change of near-ground diffusion caused by continuous strong inversion were the fundamental reasons for the formation of winter "pollution season". In the heavy pollution process on January 16-22, 2021, the continuous low temperature, high humidity and breezy/still wind conditions were the dominant ground meteorological conditions, and the generation and dissipation of heavy pollution only changed with the boundary layer and inversion conditions. The boundary layer height in the pollution accumulation period decreased by nearly 5 times compared with that in the clean days, and the intensity of the inversion temperature exceeded 1.5 ℃/(100 m). Immediately after the heavy pollution episode, 3 clean days appeared following with the receding of inversion temperature and the rising of boundary layer height.
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表 1 2018—2021年石河子市和典型对比城市各污染物月均浓度最大值及其与最小值的比值
Table 1. Maximum and minimum monthly average concentration of each pollutant in Shihezi and other typical cities from 2018 to 2021
污染物 石河子 北京 郑州 成都 上海 广州 最大值/
(μg/m3)比值/倍 最大值/
(μg/m3)比值/倍 最大值/
(μg/m3)比值/倍 最大值/
(μg/m3)比值/倍 最大值/
(μg/m3)比值/倍 最大值/
(μg/m3)比值/倍 PM2.5 179.3 11.4 59.7 2.1 109 4 74 3.3 47 2.4 40.3 2.5 PM10 219 5.5 83.3 1.9 144.3 2.4 103.3 2.7 57 1.7 70 2.3 CO1) 2.8 4.2 1.8 2.2 2.1 2.7 1.4 1.6 1.2 1.6 1.3 1.7 O3-8 h2) 145.3 3 225.5 3.8 223.3 3.5 206 3.8 184.7 2.4 193 1.8 NO2 59.3 2.6 52 2.1 58.3 1.9 50.3 1.6 57 2.4 54 1.8 SO2 14 1.8 6.3 2.4 14.7 3.4 8 1.3 8.3 1.4 9.3 1.6 1)CO为最大值当月第 95百分位数浓度,单位为mg/m3; 2)O3-8 h为最大值当月每日O3浓度8小时滑动平均值的第90百分位数浓度。 表 2 2020年10月—2021年3月石河子市重污染过程前后颗粒物浓度及气象要素小时值统计
Table 2. Hourly statistics of particulate matter concentration and meteorological elements before and after heavy pollution process in Shihezi during 2020/10-2021/3
阶段 重度以上污
染出现时长/hPM2.5峰值浓
度/(μg/m3)PM2.5平均浓
度/(μg/m3)PM2.5/PM10 温度/℃ 气压/hPa RH/% 风速/(m/s) 过程前 2020年10月1日—12月3日 0 120 35.5 0.46 3.3 975.9 62.0 1.01 重污染过程 P1 2020年12月4—30日 415 373 181.3 0.80 −16.2 982.5 80.8 0.83 P2 2021年1月1—13日 173 384 186.2 0.83 −21.0 985.5 76.4 0.76 P3 2021年1月16—22日 98 411 185.1 0.83 −16.3 972.6 74.9 0.79 P4 2021年1月26日—2月9日 285 425 215.5 0.86 −13.2 977.0 82.1 0.83 总计/平均 971 425 191.1 0.82 −16.5 980.7 79.5 0.81 过程后 2021年2月23日—3月31日 11 165 45.5 0.67 −0.1 970.8 78.0 1.39 -
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