Integrating multi-stage climate and health risks using multi-source data in the Delhi Mumbai industrial corridor | |
| Author | Kanchan, Arun |
| Call Number | AIT Diss. no.UI-25-02 |
| Subject(s) | Air quality--India--Mumbai Climatic changes--Health aspects--India--Mumbai Climatic changes--Environmental aspects--India--Mumbai Industrialization--Risk assessment--India--Mumbai |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Urban Innovation and Sustainability |
| Publisher | Asian Institute of Technology |
| Abstract | Urban corridor development faces significant climate and health risks, particularly within India’s Delhi-Mumbai Industrial Corridor (DMIC) — a USD 100 billion infrastructure initiative spanning six states. Despite existing policies, three critical knowledge gaps persist: (1) lack of climate data integration in urban planning, (2) fragmented environmental monitoring across agencies, and (3) inadequate risk communication with vulnerable communities. This study assesses multi-stage climate and health risks by integrating multi-source data, generating insights for enhancing industrial growth and sustainable development across 19 industrial areas, 147 districts, and 26 smart cities in DMIC.A multi-scale approach integrates geospatial analysis, environmental monitoring, and statistical modeling. At the regional scale, MODIS satellite data (2001–2021) is used to evaluate land use and land surface temperature trends, validated through Mann-Kendall tests and Sen’s Slope calculations. CHIRPS precipitation data identifies shifts in rainfall patterns, while TerrSet’s Cellular Automata-Markov Chain model projects future climate scenarios (2030, 2050, 2100). Surat Smart City serves as a case study at the city level, where low-cost air quality sensors capture pollution variations at a neighborhood scale. These sensor readings undergo statistical validation against regulatory-grade monitors to assess the nexus between climate, pollution, and health risk. This study identifies significant warming trends across DMIC zones, with projected land surface temperature (LST) increases of up to 3–4°C by 2100 in urban expansion corridors, compounded by industrial heat retention effects. Land-use changes indicate over 700% growth in built-up areas in some districts, intensifying the urban heat island effect. Air quality analysis reveals persistent PM₂.₅ exceedances linked to rising respiratory and cardiovascular disease risks, particularly among vulnerable populations. Integrating multi-source data, namely LST, air quality metrics, land-use changes, and public health indicators, into a unified PCA–AHC framework enabled the classification of environmental risk zones and resolved multicollinearity across datasets. This approach captured 71.4–82.1% cumulative variance, achieving sharper differentiation of risk profiles compared to standalone methods. The findings underscore the urgency of climate-resilient planning and targeted health interventions, providing decision-makers with actionable spatial insights to mitigate intersecting climate and health risks while supporting sustainable industrial growth in the DMIC’s rapidly transforming landscape. |
| Year | 2025 |
| Type | Dissertation |
| School | School of Environment, Resources, and Development |
| Department | Department of Development and Sustainability (DDS) |
| Academic Program/FoS | Urban Innovation and Sustainability (UIS) |
| Chairperson(s) | Vilas Nitivattananon |
| Examination Committee(s) | Tripathi, Nitin Kumar;Ekbordin Winijkul |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2025 |