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<p>The statistical analysis discovered a significant relationship between air pollution and environmental factors and COVID-19 mortality during three seasons. Generalized Additive Model (GAM) and other statistical approaches were used to examine the non-linear relationship between COVID-19 mortality risks and PM<sub>2.5</sub> and Land Surface Temperature (LST) parameters. In the spearman correlations coefficient results, while concurrent lockdown-period PM<sub>2.5</sub> levels have showed limited correlation with COVID-19 deaths (t-statistic: -1.22, p-value: 0.24), pre-and lockdown period of PM<sub>2.5</sub> exposure from Jan-May 2020 shown a strong association ((t-statistic: -3.47, p-value: 0.0034) also pre-covid-19 baseline period (July to December-2019) little significant relationship with COVID-19 death and PM-2.5 (t-statistic: -2.20, p-value: 0.0043) suggesting that long-term pollution exposure established underlying vulnerabilities to COVID-19. The Pre–lockdown period of LST- Jan to May − 2020 strong relationship results between COVID-19 mortality and LST compared with remaining two periods are not significant results. GAM modeling confirmed significant strong associations between PM<sub>2.5</sub> and COVID-19 mortality (<i>p</i> = 0.0011; Lag-1&#xa0;day = 0.000; Lag-7&#xa0;day = 0.0000) in the pre-lockdown period of Jan to May-2020. However the PM-2.5 is not strong relationship with COVID-19 deaths during lockdown period due to decreased emission and low inconsistency in the air pollution level. However, the Lag-1&#xa0;day and 7&#xa0;day has effects strong relationship with COVID-19 mortality. During the PM-2.5 baseline period (July to Dec. 20219) is slightly weaker relationship with COVID-19 mortality as compared with Lag-1&#xa0;day and 7-day. Temperature variations during lockdown (10&#xa0;°C to 20&#xa0;°C in northern India) demonstrate the substantial influence of reduced anthropogenic activities on regional climate parameters. Land surface temperature from January-May 2020 (Pre and lockdown period) and lockdown periods have showed a significant association with COVID-19 mortality and LST in the GAM model. However, LST baseline period (July to Dec.2019) has shown weaker relationship with COVID-19 deaths. During the Lag-1&#xa0;day and Lag-7&#xa0;day shown the strong relationship with COVID-19 deaths during three periods. The seasonal temperature conditions during the initial outbreak phase were particularly influential and risky. The significant magnitude of environmental changes observed within such a short timeframe (20&#xa0;°C in temperature and 200&#xa0;µg/m³ in PM<sub>2.5</sub>) underscores the substantial influence of human activities on local environmental conditions. In this study, we have found that air pollution and LST changes contribute to COVID-19 mortalities in India. These findings provide valuable insights into the potential benefits of emission reduction strategies and highlight the importance of addressing both immediate pollution reduction and mitigating longer-term exposure impacts, particularly in regions demonstrating the most significant environmental responses to activity restrictions.</p>

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Changes in air pollution and land surface temperature relationship with COVID-19 lockdown mortalities using generalized additive model

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Chaitanya Baliram Pande,
  • Parminder Kaur,
  • Neyara Radwan,
  • Ismail Elkhrachy,
  • Subodh Chandra Pal,
  • Maytham T. Qasim,
  • Atar Singh Pipal

摘要

The statistical analysis discovered a significant relationship between air pollution and environmental factors and COVID-19 mortality during three seasons. Generalized Additive Model (GAM) and other statistical approaches were used to examine the non-linear relationship between COVID-19 mortality risks and PM2.5 and Land Surface Temperature (LST) parameters. In the spearman correlations coefficient results, while concurrent lockdown-period PM2.5 levels have showed limited correlation with COVID-19 deaths (t-statistic: -1.22, p-value: 0.24), pre-and lockdown period of PM2.5 exposure from Jan-May 2020 shown a strong association ((t-statistic: -3.47, p-value: 0.0034) also pre-covid-19 baseline period (July to December-2019) little significant relationship with COVID-19 death and PM-2.5 (t-statistic: -2.20, p-value: 0.0043) suggesting that long-term pollution exposure established underlying vulnerabilities to COVID-19. The Pre–lockdown period of LST- Jan to May − 2020 strong relationship results between COVID-19 mortality and LST compared with remaining two periods are not significant results. GAM modeling confirmed significant strong associations between PM2.5 and COVID-19 mortality (p = 0.0011; Lag-1 day = 0.000; Lag-7 day = 0.0000) in the pre-lockdown period of Jan to May-2020. However the PM-2.5 is not strong relationship with COVID-19 deaths during lockdown period due to decreased emission and low inconsistency in the air pollution level. However, the Lag-1 day and 7 day has effects strong relationship with COVID-19 mortality. During the PM-2.5 baseline period (July to Dec. 20219) is slightly weaker relationship with COVID-19 mortality as compared with Lag-1 day and 7-day. Temperature variations during lockdown (10 °C to 20 °C in northern India) demonstrate the substantial influence of reduced anthropogenic activities on regional climate parameters. Land surface temperature from January-May 2020 (Pre and lockdown period) and lockdown periods have showed a significant association with COVID-19 mortality and LST in the GAM model. However, LST baseline period (July to Dec.2019) has shown weaker relationship with COVID-19 deaths. During the Lag-1 day and Lag-7 day shown the strong relationship with COVID-19 deaths during three periods. The seasonal temperature conditions during the initial outbreak phase were particularly influential and risky. The significant magnitude of environmental changes observed within such a short timeframe (20 °C in temperature and 200 µg/m³ in PM2.5) underscores the substantial influence of human activities on local environmental conditions. In this study, we have found that air pollution and LST changes contribute to COVID-19 mortalities in India. These findings provide valuable insights into the potential benefits of emission reduction strategies and highlight the importance of addressing both immediate pollution reduction and mitigating longer-term exposure impacts, particularly in regions demonstrating the most significant environmental responses to activity restrictions.