COVID-19疫情期间全球气温和主要大气污染物浓度变化的空间关联

doi:10.16258/j.cnki.1674-5906.2022.04.012

生态环境学报 ›› 2022, Vol. 31 ›› Issue (4): 740-749.DOI: 10.16258/j.cnki.1674-5906.2022.04.012

COVID-19疫情期间全球气温和主要大气污染物浓度变化的空间关联

易嘉慧¹^,²(), 何超³, 杨璐¹^,², 叶志祥¹^,², 田雅¹^,², 柯碧钦¹^,², 慕航¹^,², 涂佩玥⁴, 韩超然¹^,², 洪松¹^,²^,^*()

1.武汉大学资源与环境科学学院,湖北武汉 430079
2.武汉大学/地理信息系统教育部重点实验室,湖北武汉 430079
3.长江大学资源与环境学院,湖北武汉 430100
4.湖北大学资源环境学院,湖北武汉 430062

收稿日期:2021-11-29 出版日期:2022-04-18 发布日期:2022-06-22
通讯作者: *洪松（1973年生）,男,教授,博士,研究方向为环境地学。E-mail: songhongpku@126.com
作者简介:易嘉慧（1999年生）,女,硕士研究生,研究方向为环境地学。E-mail: 2020202050003@whu.edu.cn
基金资助:
国家重点研发计划项目(2017YFC0212600)

Spatial Correlation between Changes in Global Temperature and Major Air Pollutants during the COVID-19 Pandemic

YI Jiahui¹^,²(), HE Chao³, YANG Lu¹^,², YE Zhixiang¹^,², TIAN Ya¹^,², KE Biqin¹^,², MU Hang¹^,², TU Peiyue⁴, HAN Chaoran¹^,², HONG Song¹^,²^,^*()

1. School of Resources and Environmental Sciences, Wuhan University, Wuhan 430079, P. R. China
2. Key Laboratory of Geographic Information System, Ministry of Education, Wuhan 430079, P. R. China
3. College of Resources and Environment, Yangtze University, Wuhan 430100, P. R. China
4. Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, P. R. China

Received:2021-11-29 Online:2022-04-18 Published:2022-06-22

摘要/Abstract

摘要：

新冠肺炎（COVID-19）疫情期间,全球采取封锁措施给研究气温变化和空气质量变化的关联性提供了机会。基于2015—2020年全球0.1°×0.1°分辨率的气温数据和全球城市逐日主要污染物（PM_2.5、NO₂和O₃）浓度数据,利用空间分析和双变量全局空间自相关等方法,以2015—2019年的滑动平均值为基准值,对比分析了2020年COVID-19疫情期间全球气温和主要大气污染物的时空变化规律,探讨了全球9个区域两者之间的空间关联特征,为制定气候变化和污染物防控政策提供科学参考。结果表明,（1）相比2015—2019年同期基准值,2020年全球气温在COVID-19封锁期间（2020年Q₁时段）平均升高0.24 ℃;其中,中亚（1.72 ℃）、东欧和北亚地区（1.70 ℃）2020年年均气温升幅较大;南亚（-0.93 ℃）和北欧（-0.64 ℃）年均气温降幅较大。（2）相比2015—2019年基准值,2020年Q₁时段全球PM_2.5和NO₂浓度分别下降16.41%和29.73%,O₃浓度升高7.92%;南亚PM_2.5（-22.40 μg·m^-3）和NO₂（-6.42 μg·m^-3）质量浓度下降最显著。对于全球O₃质量浓度而言,欧洲显著增加,增幅为2.61 μg·m^-3,而亚洲（-0.93 μg·m^-3）和北美洲（-1.96 μg·m^-3）显著下降。（3）在COVID-19期间各污染物与气温的空间关联性由强及弱依次为O₃、NO₂和PM_2.5。从空间上看,降温区域中,南亚（0.219）和北美洲（0.159）的气温与NO₂呈显著空间正相关,各区域气温与O₃呈不显著空间关联;升温区域中,北欧（0.558）、南欧（0.406）和西欧（0.284）气温均与O₃呈显著空间正相关。疫情封锁期间,大气污染物浓度变化对气温有影响,PM_2.5和NO₂浓度大幅下降时,当地气温有下降趋势。

关键词: 新冠肺炎（COVID-19）, 全球, 气温, 大气污染物, 空间关联

Abstract:

During the COVID-19 pandemic, the study of the correlation between changes in temperature and air quality has received increased attention due to the global lockdown, providing scientific references for policy-making in pollutant prevention in the context of climate change. This study applied global temperature data at a 0.1°×0.1° resolution and daily concentration data of major pollutants (i.e., PM_2.5, NO₂, O₃) in global cities from 2015 to 2020, combined with spatial analysis and bivariate global spatial autocorrelation, to reveal temporal-spatial variations of global temperatures and major air pollutant concentrations during the COVID-19 pandemic. The spatial correlations between temperatures and air pollutants in nine regions worldwide were also discussed. The results showed that: (1) compared with the benchmark value from 2015 to 2019, the global temperature in 2020 increased by an average of 0.24 ℃ during the Q₁ time period of 2020, and the average temperature in Central Asia, Eastern Europe, and Northern Asia experienced significant increases over time by 1.72 ℃, 1.70 ℃, and 1.70 ℃, respectively, while the average annual temperature in Southern Asia (-0.93 ℃) and Northern Europe (-0.64 ℃) decreased significantly. (2) Compared with the benchmark value from 2015 to 2019, the concentrations of PM_2.5 and NO₂ in the Q₁ time period of 2020 decreased by 16.41% and 29.73%, respectively, while those of O₃ increased by 7.92%. Concentrations of PM_2.5 (-22.40 μg∙m^-3) and NO₂ (-6.42 μg∙m^-3) in Southern Asia decreased most significantly. In terms of global O₃ concentrations, Europe experienced the most significant increase (2.61 μg∙m^-3), while Asia (-0.93 μg∙m^-3) and Northern America (-1.96 μg∙m^-3) showed great decreases. (3) The ranking of spatial correlations of each pollutant with air temperature during COVID-19 pandemic was O₃>NO₂>PM_2.5. The temperatures in cool areas, such as Southern Asia (0.219) and Northern America (0.159), had significant positive spatial correlations with NO₂, but no significant spatial correlations with O₃. In warm areas, significant positive correlations between the temperature and O₃were found in northern Europe (0.558), southern Europe (0.406), and Western Europe (0.284). During the lockdown period in the COVID-19 pandemic, the changes of air pollutant concentrations have had complex impacts on air temperatures. The local temperature showed a decreasing trend when the concentrations of PM_2.5 and NO₂ decreased significantly.

Key words: the novel coronavirus (COVID-19), global, air temperature, air contaminant, spatial correlation.

中图分类号:

易嘉慧, 何超, 杨璐, 叶志祥, 田雅, 柯碧钦, 慕航, 涂佩玥, 韩超然, 洪松. COVID-19疫情期间全球气温和主要大气污染物浓度变化的空间关联[J]. 生态环境学报, 2022, 31(4): 740-749.

YI Jiahui, HE Chao, YANG Lu, YE Zhixiang, TIAN Ya, KE Biqin, MU Hang, TU Peiyue, HAN Chaoran, HONG Song. Spatial Correlation between Changes in Global Temperature and Major Air Pollutants during the COVID-19 Pandemic[J]. Ecology and Environment, 2022, 31(4): 740-749.

图/表 6

图1 全球城市空气质量监测点示意图

Figure 1 Diagram of global urban air quality monitoring sites

表1 全球2015—2020年Q1、Q2时段平均气温对比分析

Table 1 Global average temperature and its changes during Q1 and Q2 from 2015 to 2020 ℃

时间	Q₁		Q₂
时间	平均气温 Average temperature	2020年相对变化值 Relative change in 2020	平均气温 Average temperature	2020年相对变化值 Relative change in 2020
2020	8.56	—	0.13	—
2019	8.56	-0.00	-0.86	0.99
2015‒2019	8.32	0.24	-0.54	0.67

图2 全球2020年Q1时段相对2015—2019年同期平均气温变化图

Figure 2 Global average temperature changes in 2020 compared to those in Q1 period of 2015 to 2019

表2 2015—2020年Q1、Q2时段各污染物（PM2.5、NO2和O3）浓度对比统计

Table 2 Concentration changes of pollutants (PM2.5, NO2 and O3) during Q1and Q3 period from 2015 to 2020 μg∙m-3

		PM_2.5			NO₂			O₃
		质量浓度 Mass concentration	2020年相对变化值 Relative change in 2020	2020年相对变化率 Relative rate of change in 2020/%	质量浓度 Mass concentration	2020年相对变化值 Relative change in 2020	2020年相对变化率 Relative rate of change in 2020/%	质量浓度 Mass concentration	2020年相对变化值 Relative change in 2020	2020年相对变化率 Relative rate of change in 2020/%
Q₁	2020	47.82			7.78			26.44
	2019	53.75	-5.93	-11.04	9.98	-2.20	-22.05	25.27	1.18	4.65
	2015‒2019	57.21	-9.39	-16.41	11.07	-3.29	-29.73	24.51	1.94	7.92
Q₂	2020	57.45			11.53			17.51
	2019	64.22	-6.77	-10.54	13.51	-1.97	-14.62	16.91	0.62	3.56
	2015‒2019	65.63	-8.18	-12.47	14.00	-2.46	-17.60	16.84	0.67	3.98

图3 2020年Q1时段全球大气污染物（PM2.5、NO2和O3）浓度变化（a）、（c）、（e）2015—2020 年逐年Q1 时段全球 PM2.5（a）、NO2（c）和 O3（e）浓度变化（黑点是实际观测值;2020 年红点是根据 2015—2019 年Q1 时段污染物浓度线性外推的结果;误差条代表不同站点平均浓度的范围）（b）、（d）、（f）2020 年相对 2015—2019 年 Q1 时段全球 PM2.5（b）、NO2（d）和 O3（f）浓度变化时空分布图

Figure 3 Changes of global atmospheric pollutant (PM2.5, NO2 and O3) concentration in Q1 of 2020 (a), (c) and (e) represents the global concentrations change of PM2.5, NO2 and O3 in respectively, in Q1 period from 2015 to 2020 (The black dots highlight the actual observation, while the red dots within 2020 indicate the linear extrapolation of pollutant concentration during Q1 period from 2015 to 2019. Here the error bar represents the range of average concentrations at different sites) (b), (d) and (f) represents that spatial and temporal distribution of global PM2.5, NO2 and O3 concentrations respectively, in Q1 during 2020, which is compared with 2015-2019.

图4 全球气温变化和各污染物浓度变化的空间关联情况区域图为各区域不同污染物的空间分布图,从左到右为PM2.5、NO2和O3。柱状图为不同污染物与气温的双变量Moran’s I值,从左到右为PM2.5、NO2和O3,其中灰色柱状图表示统计值在P=0.05水平上不显著,蓝色或橙色柱状图表示统计值在P=0.05 水平上显著

Figure 4 Spatial correlations between global temperature changes and concentration changes of various pollutants The regional map shows the spatial distribution of different pollutants in each region. PM2.5, NO2 and O3 ranks from left to right. The bar chart here displays bivarate Moran's I values of different pollutants and air temperature. The gray bar chart indicates that the statistical values are insignificant at P=0.05, while the blue or orange bar chart indicates that the statistical values are significant at P=0.05.

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COVID-19疫情期间全球气温和主要大气污染物浓度变化的空间关联

Spatial Correlation between Changes in Global Temperature and Major Air Pollutants during the COVID-19 Pandemic

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