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汾渭平原空气质量及气象要素对其日变化和年际变化的影响

秦卓凡 廖宏 陈磊 朱佳 钱静

秦卓凡, 廖宏, 陈磊, 等. 2021. 汾渭平原空气质量及气象要素对其日变化和年际变化的影响[J]. 大气科学, 45(6): 1−19 doi: 10.3878/j.issn.1006-9895.2101.20240
引用本文: 秦卓凡, 廖宏, 陈磊, 等. 2021. 汾渭平原空气质量及气象要素对其日变化和年际变化的影响[J]. 大气科学, 45(6): 1−19 doi: 10.3878/j.issn.1006-9895.2101.20240
QIN Zhuofan, LIAO Hong, CHEN Lei, et al. 2021. Fenwei Plain Air Quality and the Dominant Meteorological Parameters for Its Daily and Interannual Variations [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(6): 1−19 doi: 10.3878/j.issn.1006-9895.2101.20240
Citation: QIN Zhuofan, LIAO Hong, CHEN Lei, et al. 2021. Fenwei Plain Air Quality and the Dominant Meteorological Parameters for Its Daily and Interannual Variations [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(6): 1−19 doi: 10.3878/j.issn.1006-9895.2101.20240

汾渭平原空气质量及气象要素对其日变化和年际变化的影响

doi: 10.3878/j.issn.1006-9895.2101.20240
基金项目: 国家自然科学基金项目91744311、42021004
详细信息
    作者简介:

    秦卓凡,女,1997年出生,硕士研究生,主要从事大气气溶胶与气候变化等领域的研究。E-mail: qinzhuofan@nuist.edu.cn

    通讯作者:

    廖宏,E-mail: hongliao@nuist.edu.cn

  • 中图分类号: P402

Fenwei Plain Air Quality and the Dominant Meteorological Parameters for Its Daily and Interannual Variations

Funds: National Natural Science Foundation of China (Grants 91744311, 42021004)
  • 摘要: 汾渭平原因其封闭的地形条件以及煤炭为主的能源结构,大气污染问题一直存在,并于2018年被列入大气污染防控的重点区域。文章利用2015年以来PM10、PM2.5、SO2、NO2、CO、O3质量浓度的观测数据和空气质量指数(Air Quality Index,简称AQI),分析了汾渭平原AQI及大气污染物质量浓度的时空分布特征;使用多元线性回归模型研究了气象条件对冬季PM2.5和夏季O3浓度日最大8 h滑动平均值(MDA8_O3)日变化和年际变化的影响。研究发现,汾渭平原的空气质量在2015~2017年间逐年变差,在2018~2019年有所好转,污染较重的城市为西安、渭南、咸阳、临汾、运城、三门峡、洛阳,集中在汾河平原与渭河平原交界处。汾渭平原的首要大气污染物多为PM2.5、PM10或O3,三者占比之和约90%。重污染时期主要集中在天气条件不利及污染物排放量大的冬季供暖期,但夏季O3浓度的升高趋势使得汾渭平原夏季污染情况越来越严重。影响汾渭平原冬季PM2.5浓度和夏季MDA8_O3日变化最主要的气象要素都是2 m高度气温(简称T2M),相对贡献分别是45.5%、35.3%,都表现为正相关;第二主要的气象要素都是2 m相对湿度(简称RH2M),相对贡献分别是41.5%(正相关)、25.4%(负相关)。影响汾渭平原冬季PM2.5浓度年际变化最主要的2个气象要素是T2M和RH2M,其相对贡献分别为43.6%、31.9%,且都呈正相关,2015~2019年汾渭平原冬季气象条件的变化会导致PM2.5浓度上升,部分削弱了人为减排导致的下降趋势(−8.3 μg m−3 a−1)。影响汾渭平原夏季MDA8_O3年际变化最主要的2个气象要素是T2M(正相关)和850 hPa风速(WS850,负相关),其相对贡献分别为71.7%、16.3%。2015~2019年汾渭平原夏季气象条件的变化导致O3污染呈上升趋势(1.2 μg m−3 a−1),但O3污染的总上升趋势(8.7 μg m−3 a−1)中,人为排放变化的贡献更大(7.5 μg m−3 a−1)。本研究表明,汾渭平原大气污染形势严峻,其颗粒物污染问题尚未解决,还面临着新的臭氧污染的挑战,汾渭平原内的11个地级市分属陕西、山西、河南三省管辖,三省交界处又是重污染区域,所以需要三省联合防治防控,协同改善汾渭平原的空气质量。
  • 图  1  汾渭平原地形及城市分布。陕西省、山西省、河南省的城市分别用●、☆、△表示

    Figure  1.  Topography and distribution of cities in the Fenwei Plain. Cities in Shaanxi, Shanxi, and Henan Provinces are represented by ●, ☆, and △, respectively

    图  2  2015~2019年汾渭平原空气质量指数(AQI)分级占比的逐年变化

    Figure  2.  Yearly changes in the percentages of AQI (Air Quality Index) classes in the Fenwei Plain from 2015 to 2019

    图  3  2015~2019年汾渭平原11市污染天(AQI>100)频率的季节变化及空间分布

    Figure  3.  Seasonal variations and spatial distributions of the frequency of polluted days (AQI>100) in 11 cities in the Fenwei Plain from 2015 to 2019

    图  4  2015~2019年汾渭平原污染天(AQI>100)频率月变化(11市平均)

    Figure  4.  Monthly variations in the frequency of polluted days (AQI>100) in the Fenwei Plain (average of 11 cities) from 2015 to 2019

    图  5  2015~2019年汾渭平原首要污染物物种占比的逐年变化

    Figure  5.  Yearly changes in the percentages of primary pollutants in the Fenwei Plain from 2015 to 2019

    图  6  2001~2019年汾渭平原PM10质量浓度年均值变化

    Figure  6.  Changes in the annual mean concentrations of PM10 in the Fenwei Plain from 2001 to 2019

    图  7  2015~2019年(a、e)PM10、(b、f)PM2.5、(c、g)粗颗粒物(即PM10减PM2.5)的质量浓度和(d、h)PM2.5占PM10的比重在11个城市及汾渭平原(11市平均)的逐年变化(左列)和11市平均值的月变化(右列)

    Figure  7.  Yearly changes (left column) in the concentration of (a, e) PM10, (b, f) PM2.5, (c, g) coarse particulate matter (i.e., PM10 minus PM2.5), and (d, h) the proportion of PM2.5 in PM10 in 11 cities and the Fenwei Plain (average for 11 cities) from 2015 to 2019, and the corresponding monthly changes in the average values for the 11 cities (right column)

    图  8  2015~2019年汾渭平原MDA8_O3(O3质量浓度的日最大8 h滑动平均值)月均值变化

    Figure  8.  Monthly variations in MDA8_O3 (maximum daily 8-hour average of O3 concentration) in the Fenwei Plain from 2015 to 2019

    图  9  2015~2019年汾渭平原11市夏季MDA8_O3时空分布

    Figure  9.  Spatial distributions of summertime MDA8_O3 in 11 cities in the Fenwei Plain from 2015 to 2019

    图  10  2015~2019年(a、d)SO2、(b、e)NO2、(c、f)CO的质量浓度年均值在11个城市及汾渭平原(11市平均)的逐年变化(左列)以及各污染物浓度11市平均值的逐月变化(右列)

    Figure  10.  Yearly variations (left column) in the annual mean concentrations of (a, d) SO2, (b, e) NO2, and (c, f) CO in the Fenwei Plain from 2015 to 2019 in 11 cities and in the Fenwei Plain (average of 11 cities), monthly variations (right column) in the concentrations averaged over the Fenwei Plain (11 cities) for 2015–2019

    图  11  2015~2019年冬季(DJF)气象要素T2M(2 m高度气温,第一行)、RH2M(2 m高度相对湿度,第二行)在汾渭平原的空间分布:冬季平均值(左列);在PM2.5重污染天(HPD)期间的均值(中间列);在PM2.5重污染天均值减去冬季平均值得到的差值(右列),黑点表示在该格点上的差值通过了0.05显著性水平的t检验,下同

    Figure  11.  Spatial distributions of T2M (2-meter-height air temperature, first line) and RH2M (2-meter-height relative humidity, second line) in the Fenwei Plain in the winter (DJF) of 2015–2019: Winter average (left column); average over the PM2.5 heavily polluted days (middle column); differences of meteorological parameters in heavily polluted days (HPD) relative to the winter average (right column), the black dots indicate that the difference on this grid pass the 0.05 significance level for t test, the same below

    图  12  2015~2019年夏季(JJA)气象要素T2M(第一行)、RH2M(第二行)、SWGDN(地表入射短波通量,第三行)在汾渭平原的空间分布:夏季平均值(左列);在O3重污染天(HPD)期间的均值(中间列);在O3重污染天均值减去夏季平均值得到的差值(右列)

    Figure  12.  Spatial distributions of T2M (first line), RH2M (second line), and SWGDN (surface incoming shortwave flux, third line) in the Fenwei Plain in the summer (JJA) of 2015–2019: Summer average (right column); average over the O3 heavily polluted days (middle column); differences of meteorological parameters in heavily polluted days (HPD) relative to the summer average (right column)

    图  13  2015~2019年冬季(a)PM2.5浓度以及(b)主要的气象要素T2M、RH2M、WS850在汾渭平原的年际变化(由异常季均值表示)。将观测异常分解为由气象驱动的异常(由多元线性回归模型得到,用MLR表示)和剩余异常(由观测异常减MLR计算得出,用Δ表示),详见2.6节

    Figure  13.  Interannual variations in (a) PM2.5 concentrations and (b) key meteorological parameters (T2M, RH2M, WS850) in the Fenwei Plain in winter from 2015 to 2019, represented by seasonal mean anomalies. The observational anomalies are decomposed into meteorologically driven anomalies (obtained from Multiple Linear Regression, represented in MLR), and residual anomalies (calculated from observational anomalies minus MLR, represented in Δ); see 2.6 for details

    图  14  2015~2019年夏季(a)MAD8_O3以及(b)主要的气象要素T2M、WS850、CLDTOT(total cloud area fraction)在汾渭平原的年际变化(由异常季均值表示)。将观测异常分解为由气象驱动的异常(由多元线性回归模型得到,用MLR表示)和剩余异常(由观测异常减MLR计算得出,用Δ表示),详见2.6。

    Figure  14.  Interannual variations in (a) MAD8_O3 and (b) key meteorological parameters (T2M, WS850, CLDTOT) in the Fenwei Plain in summer from 2015 to 2019, represented by seasonal mean anomalies. The observational anomalies are decomposed into meteorologically driven anomalies (obtained from Multiple Linear Regression, represented in MLR), and residual anomalies (calculated from observational anomalies minus MLR, represented in Δ); see 2.6 for details.

    表  1  空气质量指数的分级

    Table  1.   Classification of Air Quality Index

    空气质量指数空气质量指数级别空气质量指数类别
    0~50一级
    51~100二级
    101~150三级轻度污染
    151~200四级中度污染
    201~300五级重度污染
    >300六级严重污染
    下载: 导出CSV

    表  2  API、AQI及其分别对应的PM10浓度限值

    Table  2.   API, AQI and their respective PM10 concentration limits

    APIAPI对应的PM10
    浓度/μg m−3
    AQIAQI对应的PM10
    浓度/μg m−3
    0 0 0 0
    50 50 50 50
    100150100150
    150250
    200350200350
    300420300420
    400500400500
    500600500600
    下载: 导出CSV

    表  3  气象要素

    Table  3.   Meteorological parameters considered

    简写全称单位
    CLDTOT总云面积分数(total cloud area fraction)
    PBLH行星边界层高度(planetary boundary layer height)m
    PREC降水量(total precipitation)mm d−1
    SWGDN地表入射短波通量(surface incoming shortwave flux)W m−2
    T2M2米高度气温(2-meter-height air temperature)°C
    RH2M2米高度相对湿度(2-meter-height relative humidity)
    WS10M10米高度风速(10-meter-height wind speed)m s−1
    WS850850 hPa风速(wind speed at 850 hPa)m s−1
    下载: 导出CSV

    表  4  影响汾渭平原冬季PM2.5浓度日变化的主要气象要素(由MLR模型和LMG方法得到,详见2.6节)

    Table  4.   Key meteorological parameters that influence daily variations of PM2.5 concentration in the Fenwei Plain in winter (obtained from MLR model and LMG method, see 2.6 for details)

    气象要素回归系数相对贡献
    T2M7.6145.5%
    RH2M1.9541.5%
    WS850−1.6510.8%
    PREC−4.822.2%
    下载: 导出CSV

    表  5  影响汾渭平原夏季MDA8_O3日变化的主要气象要素(由MLR模型和LMG方法得到,详见2.6)

    Table  5.   Key meteorological parameters that influence the daily variation of summertime MDA8_O3 in the Fenwei Plain (obtained from MLR model and LMG method, see 2.6 for details)

    气象要素回归系数相对贡献
    T2M4.6535.3%
    RH2M−0.5025.4%
    SWGDN0.0822.0%
    WS850−3.5117.3%
    下载: 导出CSV

    表  6  影响汾渭平原2015~2019年冬季PM2.5浓度或夏季MAD8_O3年际变化的气象要素(由MLR模型和LMG方法得到,详见2.6)(空白表示冬季或夏季的MLR模型中没有该气象要素)

    Table  6.   Key meteorological parameters that influence the interannual variations of wintertime PM2.5 and summertime MAD8_O3 in the Fenwei Plain from 2015 to 2019 (obtained from MLR model and LMG method; see 2.6 for details; blank means that the meteorological parameter is not present in the MLR model in winter or summer)

    气象要素冬季PM2.5夏季MAD8_O3
    回归系数相对贡献回归系数相对贡献
    T2M6.5143.6%8.5771.7%
    RH2M1.2631.9%
    WS850−1.6611.1%−3.7216.3%
    SWGDN−0.338.5%
    PREC−10.664.9%
    CLDTOT−0.2512.0%
    下载: 导出CSV
  • [1] Aw J, Kleeman M J. 2003. Evaluating the first-order effect of intraannual temperature variability on urban air pollution [J]. J. Geophys. Res. :Atmos., 108(D12): 4365. doi: 10.1029/2002JD002688
    [2] Bi J. 2012. A review of statistical methods for determination of relative importance of correlated predictors and identification of drivers of consumer liking [J]. J. Sens. Stud., 27(2): 87−101. doi: 10.1111/j.1745-459X.2012.00370.x
    [3] Che H Z, Gui K, Xia X G, et al. 2019. Large contribution of meteorological factors to inter-decadal changes in regional aerosol optical depth [J]. Atmos. Chem. Phys., 19(16): 10497−10523. doi: 10.5194/acp-19-10497-2019
    [4] Chen L, Zhu J, Liao H, et al. 2020. Meteorological influences on PM2.5 and O3 trends and associated health burden since China's clean air actions [J]. Sci. Total Environ., 744: 140837. doi: 10.1016/j.scitotenv.2020.140837
    [5] Chen Z Y, Xie X M, Cai J, et al. 2018. Understanding meteorological influences on PM2.5 concentrations across China: A temporal and spatial perspective [J]. Atmos. Chem. Phys., 18(8): 5343−5358. doi: 10.5194/acp-18-5343-2018
    [6] Ding X, Wang X M, Gao B, et al. 2012. Tracer-based estimation of secondary organic carbon in the Pearl River Delta, South China [J]. J. Geophys. Res.: Atmos., 117(D5): D05313. doi: 10.1029/2011JD016596
    [7] Grömping U. 2006. Relative importance for linear regression in R: The package relaimpo [J]. J. Stat. Softw., 17(1): 1−27. doi: 10.18637/jss.v017.i01
    [8] 黄小刚, 邵天杰, 赵景波, 等. 2019. 汾渭平原PM2.5浓度的影响因素及空间溢出效应 [J]. 中国环境科学, 39(8): 3539−3548. doi: 10.3969/j.issn.1000-6923.2019.08.049

    Huang X G, Shao T J, Zhao J B, et al. 2019. Influence factors and spillover effect of PM2.5 concentration on Fen-Wei Plain [J]. China Environmental Science, 39(8): 3539−3548. doi: 10.3969/j.issn.1000-6923.2019.08.049
    [9] Jacob D J, Winner D A. 2009. Effect of climate change on air quality [J]. Atmos. Environ., 43(1): 51−63. doi: 10.1016/j.atmosenv.2008.09.051
    [10] Leung D M, Tai A P K, Mickley L J, et al. 2018. Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China [J]. Atmos. Chem. Phys., 18(9): 6733−6748. doi: 10.5194/acp-18-6733-2018
    [11] Li K, Jacob D J, Liao H, et al. 2019. Anthropogenic drivers of 2013–2017 trends in summer surface ozone in China [J]. Proc. Natl. Acad. Sci. USA, 116(2): 422−427. doi: 10.1073/pnas.1812168116
    [12] 李雁宇, 李杰, 曾胜兰, 等. 2020. 2017年汾渭平原东部大气颗粒物污染特征分析 [J]. 环境科学研究, 33(1): 63−72. doi: 10.13198/j.issn.1001-6929.2019.06.16

    Li Y Y, Li J, Zeng S L, et al. 2020. Analysis of atmospheric particulates in the eastern Fenwei Plain in 2017 [J]. Research of Environmental Sciences, 33(1): 63−72. doi: 10.13198/j.issn.1001-6929.2019.06.16
    [13] Liao H, Chen W T, Seinfeld J H. 2006. Role of climate change in global predictions of future tropospheric ozone and aerosols [J]. J. Geophys. Res. :Atmos., 111(D12): D12304. doi: 10.1029/2005JD006852
    [14] 刘瑞金, 廖宏, 常文渊, 等. 2017. 基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响 [J]. 大气科学, 41(4): 739−751. doi: 10.3878/j.issn.1006-9895.1612.16218

    Liu R J, Liao H, Chang W Y, et al. 2017. Impact of climate change on aerosol concentrations in eastern China based on Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) datasets [J]. Chinese Journal of Atmospheric Sciences, 41(4): 739−751. doi: 10.3878/j.issn.1006-9895.1612.16218
    [15] Mu Q, Liao H. 2014. Simulation of the interannual variations of aerosols in China: Role of variations in meteorological parameters [J]. Atmos. Chem. Phys., 14(18): 9597−9612. doi: 10.5194/acp-14-9597-2014
    [16] Seo J, Park D S R, Kim J Y, et al. 2018. Effects of meteorology and emissions on urban air quality: A quantitative statistical approach to long-term records (1999–2016) in Seoul, South Korea [J]. Atmos. Chem. Phys., 18(21): 16121−16137. doi: 10.5194/acp-18-16121-2018
    [17] So K L, Wang T. 2003. On the local and regional influence on ground-level ozone concentrations in Hong Kong [J]. Environ. Pollut., 123(2): 307−317. doi: 10.1016/S0269-7491(02)00370-6
    [18] Tai A P K, Mickley L J, Jacob D J. 2010. Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change [J]. Atmos. Environ., 44(32): 3976−3984. doi: 10.1016/j.atmosenv.2010.06.060
    [19] 王圣, 徐静馨, 孙雪丽, 等. 2019. 汾渭平原采暖期与非采暖期大气环境质量时空变化特征研究 [J]. 环境污染与防治, 41(12): 1451−1458. doi: 10.15985/j.cnki.1001-3865.2019.12.013

    Wang S, Xu J X, Sun X L, et al. 2019. Spatial-temporal variation characteristics of air pollution in Fenwei Plain during heating and non-heating seasons [J]. Environmental Pollution and Control, 41(12): 1451−1458. doi: 10.15985/j.cnki.1001-3865.2019.12.013
    [20] Wang T, Xue L K, Brimblecombe P, et al. 2017. Ozone pollution in China: A review of concentrations, meteorological influences, chemical precursors, and effects [J]. Sci. Total Environ., 575: 1582−1596. doi: 10.1016/j.scitotenv.2016.10.081
    [21] 王跃思, 李文杰, 高文康, 等. 2020. 2013–2017年中国重点区域颗粒物质量浓度和化学成分变化趋势 [J]. 中国科学:地球科学, 50(4): 1857−1871. doi: 10.1007/s11430-018-9373-1
    [22] 卫玮, 王黎娟, 靳泽辉, 等. 2018. 基于OMI数据汾渭平原大气SO2时空分布特征分析 [J]. 生态环境学报, 27(12): 2276−2283. doi: 10.16258/j.cnki.1674-5906.2018.12.013

    Wei W, Wang L J, Jin Z H, et al. 2018. The spatio-temporal distribution characteristics of atmospheric SO2 in Fenwei Plain based on OMI data [J]. Ecology and Environment Sciences, 27(12): 2276−2283. doi: 10.16258/j.cnki.1674-5906.2018.12.013
    [23] Xu L, Pierce D W, Russell L M, et al. 2015. Interannual to decadal climate variability of sea salt aerosols in the coupled climate model CESM1.0 [J]. J. Geophys. Res.: Atmos., 120(4): 1502−1519. doi: 10.1002/2014JD022888
    [24] 杨乐超, 董雪丽, 徐波. 2018. 汾渭平原雾霾时空变化特征及其溢出效应 [J]. 环境经济研究, 3(3): 75−87. doi: 10.19511/j.cnki.jee.2018.03.006

    Yang L C, Dong X L, Xu B. 2018. Spatial distribution and spillover effects of haze pollution in the Fen-Wei Plain [J]. Journal of Environmental Economics, 3(3): 75−87. doi: 10.19511/j.cnki.jee.2018.03.006
    [25] Yang Y, Liao H, Lou S J. 2016. Increase in winter haze over eastern China in recent decades: Roles of variations in meteorological parameters and anthropogenic emissions [J]. J. Geophys. Res.: Atmos., 121(21): 13050−13065. doi: 10.1002/2016JD025136
    [26] Zhai S X, Jacob D J, Wang X, et al. 2019. Fine particulate matter (PM2.5) trends in China, 2013–2018: Separating contributions from anthropogenic emissions and meteorology [J]. Atmos. Chem. Phys., 19(16): 11031−11041. doi: 10.5194/acp-19-11031-2019
    [27] 张连华, 周春艳, 厉青, 等. 2019. 2016–2018年汾渭平原对流层NO2柱浓度时空变化遥感监测 [J]. 环境生态学, 1(4): 67−73.

    Zhang L H, Zhou C Y, Li Q, et al. 2019. Remote sensing monitoring of spatiotemporal changes of tropospheric NO2 column concentration of Fen-Wei Plain in the year of 2016–2018 [J]. Environmental Ecology, 1(4): 67−73.
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  • 收稿日期:  2020-12-02
  • 录用日期:  2021-03-02
  • 网络出版日期:  2021-03-04

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