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

Abstract

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: $$2.02\times 10^{-13}$$ 2.02 × 10 - 13 , 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.

Keywords

• Methane
• COVID-19
• TROPOMI
• Statistical analysis