Index-based evaluation of the relationship between bioclimatic comfort levels and air quality levels of particles and sulfur dioxide in Sanliurfa Province (Turkey)


Dogan T. R., KARAKUŞ C. B., Aksoy I. E.

AIR QUALITY ATMOSPHERE AND HEALTH, cilt.15, sa.11, ss.2103-2121, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 11
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1007/s11869-022-01267-z
  • Dergi Adı: AIR QUALITY ATMOSPHERE AND HEALTH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, BIOSIS, CAB Abstracts, Geobase, Pollution Abstracts, Veterinary Science Database
  • Sayfa Sayıları: ss.2103-2121
  • Anahtar Kelimeler: DI, AQI, Bioclimatic comfort, Air pollutant, GIS, OUTDOOR THERMAL COMFORT, PARTICULATE MATTER, URBAN AREAS, INDUSTRIALIZED AREA, HEAVY-METALS, POLLUTION, PM10, AGGLOMERATION, VARIABILITY, POLLUTANTS
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

The aim of this study is (i) to reveal the bioclimatic comfort zones depending on the Discomfort Index (DI) in Sanliurfa province with the help of geographic information system (GIS), and (ii) to determine the relationship between bioclimatic comfort levels and Air Quality Index (AQI) levels in the Sanliurfa city. For all analyzes made in the study, annual and monthly average values of meteorological (temperature, relative humidity, wind speed) and air pollutant parameters (for PM10 and SO2) between the years 2006-2021 were used. In this context, meteorological parameters, air pollutant parameters, temporal changes of DI and AQI (for PM10 and SO2) parameters were determined by Mann-Kendal (MK) trend analysis and the relationships between all these parameters were determined by Pearson correlation analysis. The most suitable (21 <= DI < 24) months in terms of bioclimatic comfort in Sanliurfa province were June and September. In the Sanliurfa city, annual and monthly average AQI(PM10) values were generally in the "good" and "moderate" class, while AQI(SO2) values were in the "good" class in all years and all months. While the annual average temperature values showed a statistically significant increase, the annual average wind speed and PM10 and AQI(PM10) values showed a statistically significant decrease. There was a negative "weak" correlation (r = - 0.028) between DI and AQI(PM10), and a positive "moderate" correlation between DI and AQI(SO2) (r = 0.449; p < 0.05). In addition, correlations between DI, PM10, and SO2 were significant at the p < 0.05 level.