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Is India Being Primed as a Dumping Ground for Data Centres?

As global resistance grows, energy- and water-hungry facilities may seek refuge where incentives are high and scrutiny is weak
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••5 mins read
Google’s Cerrillos data centre in Chile was redesigned after environmental courts mandated sustainable cooling to protect aquifers
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Data Centres, Dumping Logic, and Governance Risks

1. Dumping Beyond Trade: Expanding the Concept

Context

  • Traditionally, dumping refers to exporting goods below cost or domestic prices, distorting fair competition in international trade.
  • The article expands this idea to policy-enabled dumping, where legal imports or investments externalise costs onto the host country.
  • Dumping can occur even when imports are lawful, if state policies favour narrow commercial interests over broader public welfare.
  • This shift is significant for governance, as it reframes dumping as a regulatory and democratic accountability issue, not merely a trade violation.

When dumping is narrowly viewed as a trade offence, governments overlook deeper institutional failures that allow long-term social and environmental costs to accumulate.

2. Data as the New Oil: Digital Infrastructure Externalities

Context

  • Data is increasingly seen as a strategic economic resource, comparable to oil in its role in modern economies.
  • Like extractive industries, data-driven growth relies on heavy physical infrastructure such as data centres.
  • These facilities require large quantities of electricity, water, land, and cooling systems.
  • Assuming digital infrastructure is inherently clean risks underestimating its ecological and infrastructural footprint.

Ignoring the material basis of the digital economy leads to growth models that undermine sustainability while appearing technologically progressive.

3. Good vs Bad Data Centres: Governance-Relevant Distinction

Context

  • Data centres are not intrinsically harmful; their impact depends on siting, design, and operational choices.
  • Efficient centres align infrastructure design with local resource availability and grid capacity.
  • Inefficient centres often comply on paper but impose real-world costs due to poor planning.
  • The distinction is vital for regulators to prevent cumulative environmental stress.

Characteristics

Good Data Centres

  • Located where power supply is reliable and scalable
  • Pay for required grid upgrades
  • High server utilisation, avoiding idle capacity
  • Efficient cooling systems:
    • Optimised airflow
    • Higher inlet temperature tolerance
    • Use of ambient air or liquid cooling where feasible
  • Minimal use of potable water; reliance on recycled water
  • Continuous monitoring of energy, water, and emissions

Bad Data Centres

  • Sited in water-stressed or poorly zoned regions
  • Depend on water-intensive evaporative cooling
  • Use outdated cooling designs with high energy overheads
  • Externalise costs to households, utilities, and ecosystems

When design and location ignore local constraints, regulatory approvals translate into long-term governance failures.

4. Global Resistance to Data Centres: Comparative Experience

Context

  • In developed economies, public resistance to data centres is increasing due to environmental and social concerns.
  • Local governments face pressure to assess zoning compatibility, water use, and energy demand.
  • Transparency deficits have intensified conflicts between communities and developers.

Comparative Examples

  • Chile:
    • Google’s Cerrillos data centre faced legal challenge over aquifer stress.
    • Environmental court required climate impact assessment and alternative cooling.
  • United States:
    • North Carolina: Project withdrawn after mayor signalled unanimous rejection.
    • Minnesota: Proposal stalled due to inadequate environmental review and delayed disclosure.

As scrutiny increases in the Global North, capital may shift towards jurisdictions with lower regulatory friction.

5. India’s Data-Centre Expansion: Scale and Risks

Context

  • India is positioning itself as a major global data-centre hub, supported by policy incentives and market size.
  • Multiple forecasts indicate rapid capacity growth during the current decade.
  • This expansion coincides with significant water stress, power system constraints, and regulatory gaps.
  • The risk lies in incentive-driven growth without adequate institutional safeguards.

Key Projections

  • JLL: ~77% growth, reaching 1.8 GW by 2028
  • CRISIL: 2.3–2.5 GW by FY 2028
  • Colliers: Capacity exceeding 4.5 GW by 2030

Rapid infrastructure growth without regulatory strengthening can convert comparative advantage into systemic environmental risk.

6. Institutional Safeguards and Accountability Mechanisms

Context

  • India’s governance framework shows both weaknesses and corrective potential.
  • Oversight bodies have repeatedly flagged lapses in environmental clearance and monitoring.
  • Judicial and tribunal systems provide avenues for accountability, though often delayed.
  • Civil society engagement enhances transparency and deterrence.

Key Institutions

  • Comptroller and Auditor General (CAG)
  • Supreme Court of India
  • National Green Tribunal (NGT)
  • State governments and local authorities
  • Civil society organisations

Strong institutions raise the cost of non-compliance and prevent unchecked externalisation of development costs.

7. Governance Red Flags in Data-Centre Policy

Context

  • Certain policy and administrative signals indicate heightened dumping risk.
  • These signals often reflect systemic governance weaknesses rather than isolated issues.
  • Early identification allows preventive regulation rather than reactive litigation.

Warning Signs

  • Incentives that race to the bottom:
    • Excessive land and power subsidies
    • Accelerated or exempted clearances
  • Rapid addition of large power loads:
    • No clear rules on who pays for grid upgrades
    • Risk of household cross-subsidisation
  • Siting in water-stressed regions:
    • Absence of binding water budgets
    • Lack of contingency planning
  • Opaque processes:
    • Non-disclosure agreements with utilities
    • Hard-to-access environmental filings
    • Use of shell entities

Unchecked governance dilution locks in long-term environmental and fiscal liabilities.

Conclusion

  • Data centres are critical to India’s digital and AI-driven growth strategy.
  • Their sustainability depends on regulatory quality, institutional capacity, and public accountability.
  • Transparent zoning, resource-sensitive planning, and robust enforcement can prevent data-centre growth from becoming a new form of dumping.
  • Strengthening governance frameworks ensures that digital infrastructure supports inclusive and sustainable development.

Quick Q&A

Everything you need to know

Dumping in trade traditionally refers to selling goods in another country at a price lower than in the domestic market or below production cost. While some argue that this is often a red herring—because importing countries voluntarily accept such goods under their own regulations—it can become a concern when governments prioritize the interests of certain industries over public or environmental welfare.

In the context of data centres, 'dumping' can occur when resource-intensive and poorly designed facilities are set up in countries with weaker regulatory oversight or resource constraints. These centres may consume excessive power and water, strain local infrastructure, and externalize environmental costs. India, with incentives for data-centre development and regions under water and energy stress, could potentially face such challenges if projects are poorly located or designed without proper oversight.

A data centre may be labelled inefficient on the ground due to multiple reasons:

  • It is located in an area with unreliable power supply or water scarcity, forcing reliance on expensive and unsustainable backup solutions.
  • The design does not optimise cooling, airflow, or server utilisation, leading to high energy consumption.
  • It uses outdated infrastructure or designs that ignore the local environmental context, such as evaporative cooling in arid regions.

For instance, Google's proposed Cerrillos data centre in Santiago, Chile initially faced opposition due to potential environmental impacts on local aquifers. The company had to switch to air-cooling to reduce water dependency, illustrating how inefficiencies arise when local conditions are ignored. Thus, real-world efficiency depends on careful site selection, design, and alignment with environmental and infrastructural realities, not just theoretical benchmarks.

India can mitigate risks by integrating regulatory, technical, and participatory measures:

  • Site selection: Ensure data centres are located in regions with reliable power and minimal water stress.
  • Design standards: Mandate efficient cooling, server utilisation, and use of recycled water where feasible.
  • Regulatory transparency: Require public disclosure of energy, water, and environmental impact data and enforce zoning rules that account for local infrastructure and environmental limits.
  • Community engagement: Involve local stakeholders early in planning to prevent resistance and ensure social licence to operate.

By combining incentives with stringent environmental and social safeguards, India can support AI and IT industrialisation while preventing data-centre projects from externalizing costs to local communities or ecosystems.

Community engagement ensures that large infrastructure projects align with local needs, environmental sustainability, and public interest. Data centres are capital-intensive but low on permanent employment, and can stress local resources like water and electricity. Without early consultation, communities may resist projects, leading to delays, litigation, or redesigns, as seen in North Carolina and Minnesota in the U.S., where proposals were rescinded or paused due to local opposition.

Engaging communities early helps developers understand local conditions, adjust design and resource usage, and gain trust. It also ensures accountability, reduces environmental and social risks, and encourages governments to enforce regulations more effectively. In India, this is particularly relevant given weaker zoning enforcement and varying state policies that provide incentives without adequate oversight.

Indiscriminate expansion can have significant consequences:

  • Water stress: Placing evaporative or high-consumption cooling systems in arid regions can deplete local aquifers.
  • Energy load: Large, clustered electricity demands can strain grids, necessitating expensive upgrades often borne by households.
  • Environmental degradation: Poor design can increase emissions, heat islands, and energy inefficiency.
  • Social backlash: Communities may resist projects if local needs are ignored, leading to litigation, delays, or reputational damage.

The Chilean example shows how neglecting local water conditions triggered court mandates and redesigns. Similarly, in India, unplanned data-centre clusters in stressed basins could exacerbate scarcity, reduce resilience, and erode public trust, despite being part of industrialisation strategies.

Several global cases illustrate mitigation strategies:

  • Google, Chile: Adjusted the Cerrillos project to use air-cooling instead of water-intensive methods due to local aquifer concerns.
  • North Carolina, USA: Municipal boards required developers to comply with zoning rules and environmental reviews, prompting project withdrawal when plans failed scrutiny.
  • Minnesota, USA: Residents highlighted inadequate environmental assessments, leading to pauses in approvals and stronger local scrutiny.

These examples show that transparent planning, environmental assessment, and stakeholder consultation are essential for sustainable data-centre development, lessons that India can apply proactively to avoid similar conflicts.

India can learn the following key lessons:

  • Early stakeholder engagement: Communities must be involved in planning to prevent resistance and ensure social acceptance.
  • Environmental due diligence: Assess local water and energy constraints, and adopt cooling or design strategies that minimise resource consumption.
  • Transparent regulation: Make disclosures about peak load, water usage, cooling methods, and grid impacts public to prevent externalisation of costs.
  • Zoning and infrastructure alignment: Data centres should only be sited where power, network connectivity, and land rights are secure, avoiding areas with high environmental or social stress.

By learning from the Chilean and U.S. experiences, India can encourage responsible investment in its AI and IT industrialisation strategy while preventing the establishment of inefficient or socially harmful facilities.

Attribution

Original content sources and authors

Vasudevan Mukunth
Vasudevan Mukunth
The Hindu
The Hindu
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