Spatiotemporal Analysis of Air Pollution Risk Areas Using Air Quality Parameters (PM10 and SO2): The Case of Kocaeli Province

Tuğba Memişoğlu Baykal

Makale detayları

Spatiotemporal Analysis of Air Pollution Risk Areas Using Air Quality Parameters (PM10 and SO2): The Case of Kocaeli Province

Yazarlar:

Tuğba Memişoğlu Baykal

Yayıncı:

Giresun University

Ana Başlıklar:

Mühendislik

Dergi:

Karadeniz Fen Bilimleri Dergisi Vol.13 Issue 4, pp.1386-1415

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001305304

pISSN:

2564-7377

Anahtar kelimeler:

Özet:

 Air pollution is a significant environmental problem that causes adverse effects on all people and living things. Therefore, it is necessary to prevent or control it. Geographical Information System GIS based hot spot clustering analyses play an active role in taking necessary precautions by enabling the detection of risky areas where air pollution occurs. In this study, GIS-based spatial-temporal hot spot clustering analyses of the air quality parameters of Kocaeli Province were carried out to identify risky areas in terms of air pollution. In this context, PM10 and SO2 air quality parameters recorded between 2021-2022 for Kocaeli province from the National Air Quality Monitoring Network of the Ministry of Environment, Urbanization, and Climate Change were obtained as monthly average values and linked to the location. First, spatial autocorrelation analyses of the data used in the study were carried out. Whether they showed a clustering tendency or the necessary distance values for the analyses were determined. Then, hot spot analysis Getis Ord Gi, one of the classical point clustering analyses, and evolving hot spot analysis Emerging Hot Spot Analysis based on time in the analyses were carried out. The results revealed that emerging hot spot analyses provide an easier and faster analysis than classical hot spot analyses, and also it is easy to evaluate analyses based on any time interval in one go, and more air pollution hotspots are detected in different locations.

 Air pollution is a significant environmental problem that causes adverse effects on all people and living things. Therefore, it is necessary to prevent or control it. Geographical Information System GIS based hot spot clustering analyses play an active role in taking necessary precautions by enabling the detection of risky areas where air pollution occurs. In this study, GIS-based spatial-temporal hot spot clustering analyses of the air quality parameters of Kocaeli Province were carried out to identify risky areas in terms of air pollution. In this context, PM10 and SO2 air quality parameters recorded between 2021-2022 for Kocaeli province from the National Air Quality Monitoring Network of the Ministry of Environment, Urbanization, and Climate Change were obtained as monthly average values and linked to the location. First, spatial autocorrelation analyses of the data used in the study were carried out. Whether they showed a clustering tendency or the necessary distance values for the analyses were determined. Then, hot spot analysis Getis Ord Gi, one of the classical point clustering analyses, and evolving hot spot analysis Emerging Hot Spot Analysis based on time in the analyses were carried out. The results revealed that emerging hot spot analyses provide an easier and faster analysis than classical hot spot analyses, and also it is easy to evaluate analyses based on any time interval in one go, and more air pollution hotspots are detected in different locations.

 Air pollution is a significant environmental problem that causes adverse effects on all people and living things. Therefore, it is necessary to prevent or control it. Geographical Information System GIS based hot spot clustering analyses play an active role in taking necessary precautions by enabling the detection of risky areas where air pollution occurs. In this study, GIS-based spatial-temporal hot spot clustering analyses of the air quality parameters of Kocaeli Province were carried out to identify risky areas in terms of air pollution. In this context, PM10 and SO2 air quality parameters recorded between 2021-2022 for Kocaeli province from the National Air Quality Monitoring Network of the Ministry of Environment, Urbanization, and Climate Change were obtained as monthly average values and linked to the location. First, spatial autocorrelation analyses of the data used in the study were carried out. Whether they showed a clustering tendency or the necessary distance values for the analyses were determined. Then, hot spot analysis Getis Ord Gi, one of the classical point clustering analyses, and evolving hot spot analysis Emerging Hot Spot Analysis based on time in the analyses were carried out. The results revealed that emerging hot spot analyses provide an easier and faster analysis than classical hot spot analyses, and also it is easy to evaluate analyses based on any time interval in one go, and more air pollution hotspots are detected in different locations.

 Bu çalışmada, Kocaeli İlinin hava kalitesi parametrelerinin CBS tabanlı konumsal-zamansal sıcak nokta kümeleme analizleri gerçekleştirilerek hava kirliliği açısından riskli bölgeler tespit edilmiştir. Bu bağlamda, Çevre, Şehircilik ve İklim Değişikliği Bakanlığının Ulusal Hava Kalite İzleme Ağından Kocaeli iline ait 2021-2022 yılları arasında kaydedilen Partikül madde PM10 ve Kükürt dioksit SO2 hava kalitesi parametreleri aylık ortalama değerler şeklinde temin edilerek düzenlenmiştir, konumla ilişkilendirilmiştir. Çalışmada, öncelikle kullanılan verilerin mekânsal otokorelasyon analizleri yürütülerek kümeleme eğilimi gösterip göstermediği tespit edilmiştir ve analizler için gerekli mesafe değerleri belirlenmiştir. Ardından, klasik nokta kümeleme analizlerinden sıcak nokta analizi Getis Ord Gi ve analizlerde zamanı da esas alan gelişen sıcak nokta analizi Emerging Hot Spot Analizi yürütülmüştür. Sonuçlar, gelişen sıcak nokta analizlerinin, klasik sıcak nokta kümeleme analizlerine göre daha kolay ve hızlı bir analiz sağladığını, ayrıca herhangi bir zaman aralığına dayalı analizleri tek bir seferde değerlendirebilmenin kolay yönünü ve farklı konumlarda daha çok hava kirliliği sıcak noktalarının tespit edildiğini ortaya koymuştur.

Makale detayları

Spatiotemporal Analysis of Air Pollution Risk Areas Using Air Quality Parameters (PM10 and SO2): The Case of Kocaeli Province

Yazarlar:

Tuğba Memişoğlu Baykal

Yayıncı:

Giresun University

Ana Başlıklar:

Mühendislik

Dergi:

Karadeniz Fen Bilimleri Dergisi Vol.13 Issue 4, pp.1386-1415

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001305304

pISSN:

2564-7377

Air quality

PM10

SO2

GIS

Hot Spot Analysis

Emerging Hot Spot AnalysisHava kalitesi

PM10

SO2

CBS

Sıcak nokta analizi

Gelişen sıcak nokta analizi

Sayı

Makale detayları

Yazarlar: Tuğba Memişoğlu Baykal

Yayıncı: Giresun University

Ana Başlıklar: Mühendislik

Dergi: Karadeniz Fen Bilimleri Dergisi Vol.13 Issue 4, pp.1386-1415

Belge Tipi: Makale

Yayın Tarihi: 12/2023

Belge Dili: Türkçe

Document ID (Org No.): 2001305304

pISSN: 2564-7377

Sayı

Yazarlar:

Tuğba Memişoğlu Baykal

Yayıncı:

Giresun University

Ana Başlıklar:

Mühendislik

Dergi:

Karadeniz Fen Bilimleri Dergisi Vol.13 Issue 4, pp.1386-1415

Belge Tipi:

Makale

Yayın Tarihi:

12/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001305304

pISSN:

2564-7377