| 河南省2014-2020年PM2.5浓度时空分布特征及气象成因分析 |
| Spatial and Temporal Characteristics and Correlation Analysis of Meteorological Factors on PM2.5 Concentration in Henan Province from 2014 to 2020 |
| 投稿时间：2021-09-22 修订日期：2022-01-11 |
| DOI：10.19316/j.issn.1002-6002.2023.01.09 |
| 中文关键词: PM2.5 河南省 时空分布 空间自相关分析 气象因子 |
| 英文关键词:PM2.5 Henan Province temporal and spatial distribution spatial autocorrelation analysis meteorological factors |
| 基金项目:国家自然科学基金青年项目(42105071);河南省大气污染综合防治与生态安全重点实验室开放基金项目(No.PAP202101);中国气象局开封市气象防灾减灾重点实验室应用技术研究基金项目(No.BQK202103)第一 |
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| 通讯作者:韩艳* 河南大学地理与环境学院, 河南 开封 475004 |
| 摘要点击次数: 1817 |
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| 中文摘要: |
| 利用2014-2020年河南省18个地级城市空气质量监测资料和气象数据,运用空间自相关分析、ArcGIS制图及相关性分析等方法,从时空分布特征上揭示河南省PM2.5污染特征,并分析其气象成因。结果表明:河南省2014-2020年PM2.5年均浓度为40~100 μg/m3,总体呈递减趋势。PM2.5浓度季节分布特征为冬季＞秋季=春季＞夏季。河南省2019年和2020年PM2.5污染空间分布存在显著自相关,污染程度严重的地区主要是中部和东北部地区。冷热点分析发现,热点城市为濮阳、安阳、济源、郑州、新乡、焦作、鹤壁,冷点城市为信阳、驻马店、周口。PM2.5在年尺度上与气压、气温、相对湿度、风向、风速、能见度显著相关,其中,与气温相关性最高,相关系数为-0.424。当相对湿度处于90%以下时,PM2.5浓度与相对湿度呈正相关;而在相对湿度超过90%之后,PM2.5浓度下降至70 μg/m3。风速超过6 m/s后,其对PM2.5浓度的影响显著降低。能见度与PM2.5浓度呈负相关,其中,新乡、平顶山、郑州对应的相关系数分别为-0.616、-0.586、-0.564,表明这3个城市的能见度状况受PM2.5浓度影响较大。 |
| 英文摘要: |
| Using the air quality monitoring data and meteorological data of 18 prefecture-level cities in Henan Province from 2014 to 2020,spatial autocorrelation analysis,ArcGIS mapping and correlation analysis were applied to reveal the PM2.5 pollution characteristics of Henan Province in terms of spatial and temporal distribution characteristics,and analyze its meteorological causes.The results showed that the annual average PM2.5 concentrations in Henan Province from 2014 to 2020 ranged from 40 to 100 μg/m3,with an overall decreasing trend,and the seasonal distribution of PM2.5 concentrations was characterized as winter > autumn = spring > summer.There was a significant autocorrelation between the annual average PM2.5 pollution spatial distribution in Henan Province in 2019 and 2020,and the areas with serious pollution levels were mainly in the central and northeastern regions.By cold and hot spot analysis,the hot spot cities were Puyang,Anyang,Jiyuan,Zhengzhou,Xinxiang,Jiaozuo,and Hebi,and the cold spot cities were Xinyang,Zhumadian,and Zhoukou.PM2.5 was significantly correlated with air pressure,air temperature,relative humidity,wind direction,wind speed,and visibility on an annual scale,where the highest correlation with PM2.5 was air temperature with a correlation coefficient of -0.424.When relative humidity was below 90%,the PM2.5 concentration was positively correlated with relative humidity.The effect of wind speed on PM2.5 concentration decreases significantly after wind speed exceeds 6 m/s.The effect of wind speed on PM2.5 concentration decreases significantly after the relative humidity exceeds 90%.Visibility was negatively correlated with PM2.5 pollution,and the correlation coefficients were -0.616,-0.586,and -0.564 for Xinxiang,Pingdingshan,and Zhengzhou,respectively,indicating that the visibility conditions in these three cities were deeply influenced by PM2.5 concentrations. |
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