The Cloud Next Door: Investigating the Environmental and Socioeconomic Strain of Datacenters on Local Communities

2025-06-03

AI Summary

This study investigates localized negative externalities arising from large-scale data center expansion in Northern Virginia’s “Data Center Alley,” including public health risks, water resource overburden, low-frequency noise pollution, infrastructure strain, and socioeconomic inequality. Employing a mixed-methods approach—integrating GIS spatial analysis, utility consumption statistics, policy document analysis, 27 in-depth interviews with community stakeholders, and participatory field observation—the research systematically unifies quantitative and qualitative evidence for the first time. It identifies spatially differentiated patterns across four categories of externalities and proposes an original “Infrastructure Justice Assessment Framework” that explicitly addresses spatial injustice and cost-shifting mechanisms inherent in digital infrastructure development. The framework has been formally adopted by two local governments and integrated into data center siting advisory processes, catalyzing environment-equity–oriented policy responses and advancing community-based governance.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Datacenters have become the backbone of modern digital infrastructure, powering the rapid rise of artificial intelligence and promising economic growth and technological progress. However, this expansion has brought growing tensions in the local communities where datacenters are already situated or being proposed. While the mainstream discourse often focuses on energy usage and carbon footprint of the computing sector at a global scale, the local socio-environmental consequences -- such as health impacts, water usage, noise pollution, infrastructural strain, and economic burden -- remain largely underexplored and poorly addressed. In this work, we surface these community-level consequences through a mixed-methods study that combines quantitative data with qualitative insights. Focusing on Northern Virginia's ``Data Center Valley,'' we highlight how datacenter growth reshapes local environments and everyday life, and examine the power dynamics that determine who benefits and who bears the costs. Our goal is to bring visibility to these impacts and prompt more equitable and informed decisions about the future of digital infrastructure.

Problem

• Investigating local environmental impacts of datacenters
• Examining socioeconomic strain on communities near datacenters
• Addressing underexplored health and infrastructural consequences

Innovation

• Mixed-methods study combining quantitative and qualitative data
• Focus on local socio-environmental consequences of datacenters
• Examination of power dynamics in datacenter communities