Examination of Air Quality Parameters in Airports with Sentinel-5P Satellite Data: A Case Study for Istanbul and Rize-Artvin Airports

Nur Yağmur

Makale detayları

Examination of Air Quality Parameters in Airports with Sentinel-5P Satellite Data: A Case Study for Istanbul and Rize-Artvin Airports

Yazarlar:

Nur Yağmur

Yayıncı:

Afyon Kocatepe University

Ana Başlıklar:

Fotogrametri ve Uzaktan Algılama

Dergi:

Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi Vol.25 Issue 3, pp.585-603

Belge Tipi:

Makale

Yayın Tarihi:

10/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001348294

pISSN:

2149-3367

Anahtar kelimeler:

Özet:

 Airports meet a significant part of the transportation needs of society. However, with the increase in urbanization, the areas suitable for the construction of new airports have decreased, and they have started to be built on rehabilitated areas or on sea-filled areas. However, it is necessary to monitor the possible damage of these structures, which are built by destroying the natural ecosystem. In this context, one of the environmental impacts to be monitored is air quality. Remote sensing enables spatio-temporal analysis since they are not point-based data sources and provide data at specific periods. In the study, changes in air quality parameters at two new airports Istanbul Airport and Rize-Artvin Airport were examined with time series analysis. Time series of five air quality parameters ultraviolet aerosol index UV, carbon monoxide CO, nitrogen dioxide NO2, ozone O3 and sulfur dioxide SO2 for the period 2018-May 2024 were obtained using the Google Earth Engine cloud platform with the Sentinel-5P satellite. In the time series analyzes examined on a parameter basis, an increasing trend was detected in UV, SO2, NO2, and O3 parameters, while a stable trend was observed in CO parameter. In line with the statistical analyses performed, positive correlations between aircraft traffic data and CO and NO2 parameters 0.48 and 0.41 with CO parameter, 0.66 and 0.73 with NO2 parameter, respectively, for airports, as well as statistically significant results were obtained.

 Airports meet a significant part of the transportation needs of society. However, with the increase in urbanization, the areas suitable for the construction of new airports have decreased, and they have started to be built on rehabilitated areas or on sea-filled areas. However, it is necessary to monitor the possible damage of these structures, which are built by destroying the natural ecosystem. In this context, one of the environmental impacts to be monitored is air quality. Remote sensing enables spatio-temporal analysis since they are not point-based data sources and provide data at specific periods. In the study, changes in air quality parameters at two new airports Istanbul Airport and Rize-Artvin Airport were examined with time series analysis. Time series of five air quality parameters ultraviolet aerosol index UV, carbon monoxide CO, nitrogen dioxide NO2, ozone O3 and sulfur dioxide SO2 for the period 2018-May 2024 were obtained using the Google Earth Engine cloud platform with the Sentinel-5P satellite. In the time series analyzes examined on a parameter basis, an increasing trend was detected in UV, SO2, NO2, and O3 parameters, while a stable trend was observed in CO parameter. In line with the statistical analyses performed, positive correlations between aircraft traffic data and CO and NO2 parameters 0.48 and 0.41 with CO parameter, 0.66 and 0.73 with NO2 parameter, respectively, for airports, as well as statistically significant results were obtained.

 Airports meet a significant part of the transportation needs of society. However, with the increase in urbanization, the areas suitable for the construction of new airports have decreased, and they have started to be built on rehabilitated areas or on sea-filled areas. However, it is necessary to monitor the possible damage of these structures, which are built by destroying the natural ecosystem. In this context, one of the environmental impacts to be monitored is air quality. Remote sensing enables spatio-temporal analysis since they are not point-based data sources and provide data at specific periods. In the study, changes in air quality parameters at two new airports Istanbul Airport and Rize-Artvin Airport were examined with time series analysis. Time series of five air quality parameters ultraviolet aerosol index UV, carbon monoxide CO, nitrogen dioxide NO2, ozone O3 and sulfur dioxide SO2 for the period 2018-May 2024 were obtained using the Google Earth Engine cloud platform with the Sentinel-5P satellite. In the time series analyzes examined on a parameter basis, an increasing trend was detected in UV, SO2, NO2, and O3 parameters, while a stable trend was observed in CO parameter. In line with the statistical analyses performed, positive correlations between aircraft traffic data and CO and NO2 parameters 0.48 and 0.41 with CO parameter, 0.66 and 0.73 with NO2 parameter, respectively, for airports, as well as statistically significant results were obtained.

 Havalimanları toplumun ulaşım ihtiyacının önemli bir kısmını karşılamaktadır. Ancak, kentleşmenin artışı ile yeni havalimanlarının inşaatı için elverişli alanlar azalmış, şehre uzak noktalarda rehabilite edilmiş alanlara veya denize dolgu alanlara inşa edilmeye başlanmıştır. Ancak doğal ekosistemin tahrip edilmesiyle inşa edilen bu yapıların, çevreye verebileceği olası zararların izlenmesi gerekmektedir. Bu bağlamda izlenmesi gereken çevresel etkilerden biri, yeni inşa edilen bu havalimanlarının etkilediği hava kalitesidir. Uzaktan algılama kaynakları, yer istasyonları gibi nokta bazlı bir veri kaynağı olmamakla birlikte belirli periyotlarda veri sağlayarak mekânsal ve zamansal analizlere olanak sağlamaktadır. Çalışma kapsamında, ülkemizde en son faaliyete açılan İstanbul Havalimanı ve Rize-Artvin Havalimanı üzerinde hava kalite parametrelerinde meydana gelen değişimler uydu kaynaklarından elde edilen aylık zaman serileri ile incelenmiştir. Sentinel-5P uydusu ile ultraviyole aerosol indeks UV, karbon monoksit CO, azot dioksit NO2, ozon O3 ve kükürt dioksit SO2 hava kalite parametrelerinin 2018-Mayıs 2024 periyodu için zaman serileri Google Earth Engine bulut platformu kullanılarak elde edilmiştir. Parametre bazında incelenen zaman serisi analizlerinde, UV, SO2, NO2 ve O3 parametrelerinde artan bir eğilim tespit edilirken, CO parametresinde stabil bir eğilim görülmüştür. Gerçekleştirilen istatistiksel analizler doğrultusunda uçak trafiği verileri ile CO ve NO2 parametreleri arasında pozitif korelasyonların havalimanları özelinde sırasıyla CO parametresi ile 0.48 ve 0.41, NO2 parametresi ile 0.66 ve 0.73 yanı sıra istatistiksel olarak anlamlı sonuçlar elde edilmiştir.

Makale detayları

Examination of Air Quality Parameters in Airports with Sentinel-5P Satellite Data: A Case Study for Istanbul and Rize-Artvin Airports

Yazarlar:

Nur Yağmur

Yayıncı:

Afyon Kocatepe University

Ana Başlıklar:

Fotogrametri ve Uzaktan Algılama

Dergi:

Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi Vol.25 Issue 3, pp.585-603

Belge Tipi:

Makale

Yayın Tarihi:

10/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001348294

pISSN:

2149-3367

Airport

Sentinel-5P

Air quality

Time series analysis

Granger-Causality test

Google Earth EngineHavalimanı

Sentinel-5P

Hava kalitesi

Zaman serisi analizi

Granger Nedensellik testi

Google Earth Engine

Sayı

Makale detayları

Yazarlar: Nur Yağmur

Yayıncı: Afyon Kocatepe University

Ana Başlıklar: Fotogrametri ve Uzaktan Algılama

Dergi: Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi Vol.25 Issue 3, pp.585-603

Belge Tipi: Makale

Yayın Tarihi: 10/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001348294

pISSN: 2149-3367

Sayı

Yazarlar:

Nur Yağmur

Yayıncı:

Afyon Kocatepe University

Ana Başlıklar:

Fotogrametri ve Uzaktan Algılama

Dergi:

Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi Vol.25 Issue 3, pp.585-603

Belge Tipi:

Makale

Yayın Tarihi:

10/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001348294

pISSN:

2149-3367