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<p>This research explores the interconnections between land surface temperature (LST), air pollution, ecosystem services values (ESV), and land use and land cover change (LULCC) in Nova Scotia from 2019 to 2024. Using datasets on LULC, ESV, LST, aerosol optical depth (AOD), and atmospheric pollutants (NO₂, CO, O₃, SO₂, and HCHO), the study applies machine learning-based LULC classification, spatiotemporal trend analysis, emerging correlation analysis, and air quality impact (AQI) to assess environmental impacts. The results reveal a significant rise in built-up areas (+ 168.16&#xa0;km²) and a substantial reduction in vegetation (-369.5&#xa0;km²), contributing to a slight increase in ESV from $16,075.88&#xa0;million in 2019 to $16,085.9&#xa0;million in 2024. Concurrently, air quality has deteriorated, particularly with increasing levels of SO₂ (from 0.00054&#xa0;µg/m³ to 0.00065&#xa0;µg/m³) and AOD (mean of 0.9578 in 2024), alongside regional variability in other pollutants. Spatial analysis identifies a notable eastward trend in pollution and distinct pollutant-ESV relationships, particularly in southeastern zones. The study highlights intricate bivariate associations between LULC, ESV, and pollutants, underscoring the complex environmental dynamics across cities in the region. The findings emphasize the urgent need for sustainable urban planning and targeted mitigation strategies to address air pollution and climate challenges in rapidly urbanizing and relatively stable areas alike.</p>

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Decoding climatic variability and ecosystem impact: integrating satellite-derived data and geospatial techniques for holistic air quality assessment in Nova Scotia

  • 期刊论文

  • 发表日期：

    2025年9月20日

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  • Md Tanvir Miah,
  • Raiyan Raiyan,
  • Remon Ahmed Mishu,
  • Md. Rakibul Hasan,
  • Rukaya Islam,
  • Pankaj Kanti Jodder,
  • Khan Rubayet Rahaman

摘要

This research explores the interconnections between land surface temperature (LST), air pollution, ecosystem services values (ESV), and land use and land cover change (LULCC) in Nova Scotia from 2019 to 2024. Using datasets on LULC, ESV, LST, aerosol optical depth (AOD), and atmospheric pollutants (NO₂, CO, O₃, SO₂, and HCHO), the study applies machine learning-based LULC classification, spatiotemporal trend analysis, emerging correlation analysis, and air quality impact (AQI) to assess environmental impacts. The results reveal a significant rise in built-up areas (+ 168.16 km²) and a substantial reduction in vegetation (-369.5 km²), contributing to a slight increase in ESV from $16,075.88 million in 2019 to $16,085.9 million in 2024. Concurrently, air quality has deteriorated, particularly with increasing levels of SO₂ (from 0.00054 µg/m³ to 0.00065 µg/m³) and AOD (mean of 0.9578 in 2024), alongside regional variability in other pollutants. Spatial analysis identifies a notable eastward trend in pollution and distinct pollutant-ESV relationships, particularly in southeastern zones. The study highlights intricate bivariate associations between LULC, ESV, and pollutants, underscoring the complex environmental dynamics across cities in the region. The findings emphasize the urgent need for sustainable urban planning and targeted mitigation strategies to address air pollution and climate challenges in rapidly urbanizing and relatively stable areas alike.