Impact of pandemic measures on air quality and meteorological parameters during the COVID-19 spread in the Euphrates Basin, Türkiye

Özvan H., Stein A., Aslantaş P., Osei F.

Environmental monitoring and assessment, cilt.197, sa.10, ss.1147, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 197 Sayı: 10
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1007/s10661-025-14620-3
  • Dergi Adı: Environmental monitoring and assessment
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Compendex, EMBASE, Environment Index, Food Science & Technology Abstracts, Geobase, Greenfile, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1147
  • Anahtar Kelimeler: Air quality indicators, COVID-19, Euphrates Basin, MARSS model, Meteorological parameters
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

This study investigates the impact of COVID-19 pandemic measures on air quality and their relationship with meteorological parameters in the Euphrates Basin, Türkiye. It provides a basin-specific analysis of air quality trends during the pandemic, exploring the interplay between meteorological variables and air quality indicators. The analysis examines the COVID-19 rates across 15 provinces about air quality indicators PM10 and SO2 and includes weekly average temperature (Tw) and weekly total precipitation (Pw). Three periods were defined: before the pandemic (Period 1), during the pandemic (Period 2), and after the pandemic (Period 3), each spanning 77 weeks. The spatial-temporal changes in PM10 and SO2 concerning Pw and Tw were analyzed during Periods 1 and 3, while in Period 2, they were related to the COVID-19 rates. The results of this study show that the COVID-19 outbreak was more intense in large cities, while the opposite was true in small cities. Using the Multivariate Auto-Regressive State-Space (MARSS) model, we found that PM10 and SO2 significantly influenced the COVID-19 rate during the second and third waves of the pandemic, most likely due to the decreased social and urban activities during the quarantine period. Moreover, the study identified noteworthy, though statistically non-significant, associations between population density and COVID-19 transmission patterns. These preliminary findings warrant further validation through future, more granular investigations.