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综合卫星数据分析评估新冠疫情对甲烷排放的重大影响。

Significant impact of the covid-19 pandemic on methane emissions evaluated by comprehensive statistical analysis of satellite data.

机构信息

Greenhouse Gas Metrology team, Korea Research Institute of Standard and Science (KRISS), Daejeon, 34113, South Korea.

Korea National University of Science and Technology (UST), Daejeon, 34113, South Korea.

出版信息

Sci Rep. 2024 Sep 28;14(1):22475. doi: 10.1038/s41598-024-72843-9.

Abstract

The COVID-19 pandemic has significantly influenced various aspects of society, including environmental factors such as methane emissions. This study investigates the changes in methane concentrations in Seoul, South Korea, from 2019 to 2023, using TROPOMI satellite data and rigorous statistical analyses. The normality of the sample data is first assessed using the Shapiro-Wilk (S-W) and Kolmogorov-Smirnov (K-S) tests, indicating that the data can be considered to come from a normal distribution. The S-W test demonstrated superior discriminative power (highest statistical power: 0.8668) compared to the K-S test (highest statistical power: 0.4002), confirming the validity of parametric tests for our data. The S-W test shows better discriminative power than the K-S test in terms of sensitivity to departures from normality, particularly for small sample sizes. Based on this confirmation, parametric tests such as analysis of variance (ANOVA) and post-hoc tests (Bonferroni correction, Tukey's HSD, Scheffe's method) are employed to identify significant differences in methane levels across different years. The ANOVA results show a statistically significant difference in methane concentrations across years (p-value: , F-value: 26.572). Post-hoc analyses reveal no significant difference in methane concentrations between 2019 and 2020 (p-values: Bonferroni - 0.1045, Tukey's HSD - 0.397, Scheffe's - 0.1045), and no significant difference between 2020 and 2021 (p-values: Bonferroni - 0.917, Tukey's HSD - 0.840, Scheffe's - 0.917). However, a significant increase in methane levels is observed from 2022 to 2023 (p-values: Bonferroni - 0.0001, Tukey's HSD - 0.0002, Scheffe's - 0.0001), correlating with the "new normal" policy implemented in South Korea starting in November 2021 and effectively from the beginning of 2022. This suggests that changes in industrial activities and transportation patterns due to the "new normal" have contributed to higher methane emissions. Student's t-test and Welch's t-test were used to validate the ANOVA results. Permutation tests showed no significant difference between 2019 and 2020 (test statistic: -0.0096, p-values: 0.1191 for Student's and 0.1156 for Welch's). However, a significant difference was found between 2022 and 2023 (test statistic: -0.0172, p-value: 0.0001), confirming ANOVA results that indicated increased methane levels post-pandemic. This study provides a robust quantitative assessment of the pandemic's impact on methane levels and sets a methodological statistical approach for future research in the environmental research community.

摘要

新冠疫情对社会的各个方面产生了重大影响,包括甲烷排放等环境因素。本研究使用 TROPOMI 卫星数据和严格的统计分析,调查了韩国首尔从 2019 年到 2023 年期间甲烷浓度的变化。首先使用 Shapiro-Wilk(S-W)和 Kolmogorov-Smirnov(K-S)检验评估样本数据的正态性,表明数据可以被认为来自正态分布。S-W 检验显示出比 K-S 检验更高的判别能力(最高统计能力:0.8668),证实了我们的数据可以使用参数检验。S-W 检验在灵敏度方面优于 K-S 检验,对偏离正态性的情况更为敏感,特别是对于小样本量的情况。基于这一确认,采用参数检验,如方差分析(ANOVA)和事后检验(Bonferroni 校正、Tukey 的 HSD、Scheffe 法)来识别不同年份之间甲烷水平的显著差异。ANOVA 结果显示,甲烷浓度在不同年份之间存在统计学上的显著差异(p 值: ,F 值:26.572)。事后检验分析显示,2019 年和 2020 年之间的甲烷浓度没有显著差异(p 值:Bonferroni - 0.1045,Tukey 的 HSD - 0.397,Scheffe 的 - 0.1045),2020 年和 2021 年之间也没有显著差异(p 值:Bonferroni - 0.917,Tukey 的 HSD - 0.840,Scheffe 的 - 0.917)。然而,2022 年到 2023 年期间,甲烷水平显著增加(p 值:Bonferroni - 0.0001,Tukey 的 HSD - 0.0002,Scheffe 的 - 0.0001),这与韩国从 2021 年 11 月开始实施的“新常态”政策以及从 2022 年初开始的有效实施有关。这表明,由于“新常态”,工业活动和交通模式的变化导致了更高的甲烷排放。使用学生 t 检验和 Welch 检验来验证 ANOVA 结果。置换检验显示 2019 年和 2020 年之间没有显著差异(检验统计量:-0.0096,p 值:0.1191 用于学生检验,0.1156 用于 Welch 检验)。然而,2022 年和 2023 年之间存在显著差异(检验统计量:-0.0172,p 值:0.0001),证实了 ANOVA 结果,表明大流行后甲烷水平增加。本研究为评估疫情对甲烷水平的影响提供了稳健的定量评估,并为环境研究界的未来研究设定了一种方法学统计方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d8/11438891/2890f9cbe14e/41598_2024_72843_Fig1_HTML.jpg

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