Predicting PM2.5 levels over the north of Iraq using regression analysis and geographical information system (GIS) techniques

Geomatics, Natural Hazards & Risk

Zainab Ali Khalaf¹  Huda Jamal Jumaah²  Vahideh Saeidi³  Shattri Mansor⁴  Naonori Ueda⁵  Bahareh Kalantar⁵  Hussein Habeeb Hamed⁶ 

[1] College of Electronic Engineering, Ninevah University;Department of Environment and Pollution Engineering, Technical Engineering College - Kirkuk, Northern Technical University;Department of Mapping and Surveying, Darya Tarsim Consulting Engineers Co. Ltd;Faculty of Engineering, Department of Civil Engineering, Geospatial Information Science Research Centre (GISRC), Universiti Putra Malaysia;RIKEN Center for Advanced Intelligence Project, Goal-Oriented Technology Research Group, Disaster Resilience Science Team;Technical Engineering College - Kirkuk, Northern Technical University;

关键词: pm2.5;    pm10;    polynomial model;    meteorological parameters;    health impact;   

DOI  :  10.1080/19475705.2021.1946602

来源: DOAJ

【 摘 要 】

Particulate matter (PM2.5) concentrations are a serious human health concern and global models are the common methods for PM2.5 particle estimation disregarding the local changes and factors. In this study, a polynomial model for PM2.5 particles prediction was proposed to examine the correlations among PM2.5, PM10, and meteorological parameters. The study was carried out in the north of Iraq including two provinces; Kirkuk and Sulaymaniyah. The data gathered from different sources. Two datasets have been used, collected during July 2019 and February 2020. To test our methodology, the model was applied on a small subset of the study area (5.6 km2) inside the Kirkuk province. Datasets (observation and ground truth) were utilized to examine the model. Based on the July 2019 dataset, the mean local R2 values were estimated at 0.98 and 0.97 in the north part of Iraq, and inside the Kirkuk province (the small subset), respectively. While based on the February 2020 dataset, the mean local R2 values were estimated at 0.98 inside the Kirkuk province. High values of prediction accuracies were obtained by 82% and 96% in July and February, respectively. Moreover, our findings highlighted that the health impacts and air quality varied from moderate to unhealthy in the region.

【 授权许可】

Unknown