Hyperscale Data Centres, EIA Classification and Fiscal Incentives in India: Lessons from the Visakhapatnam Projects
Abstract This paper examines the application of India’s Environmental Impact Assessment (EIA) framework to hyperscale data-centre infrastructure, with particular attention to the structural features of the EIA Notification, 2006 and the environmental context of the Visakhapatnam region. Drawing on peer-reviewed analyses of groundwater vulnerability, coastal contamination, and the evolution of the EIA regime, it situates large-scale digital facilities within an already stressed hydrological and ecological baseline. The analysis proceeds through critical legal and environmental review of project classification under Schedule item 8(a), the consequences of Category B2 treatment, and the limited institutionalisation of cumulative assessment and public consultation. Regional studies document declining groundwater levels, high contamination vulnerability, and elevated heavy-metal and microbial loads in coastal soils and waters. Scholarly evaluations of the 2006 Notification consistently identify the exemption of B2 projects from full impact studies and statutory public hearings as a persistent constraint on the depth of scrutiny. When facilities whose dominant pressures arise from continuous operational demand for power and water are placed on a pathway designed around construction-phase effects and built-up area, those limitations become the operative ones. The paper argues that classification and appraisal should follow operational intensity, that cluster-level cumulative assessment should be mandatory where parks share receptors, and that fiscal eligibility should not be independent of the depth of environmental review.
Authors
- Hamza Khan (ORCID: https://orcid.org/0009-0007-6403-7864)
Institutions
- Symbiosis International University (IN)
Publication Details
- Journal
- Research Square
- Published
- 2026-10-30
- DOI
- https://doi.org/10.21203/rs.3.rs-11015621/v1
- Primary Topic
- Environmental and Social Impact Assessments
- Type
- preprint