Data Scaling: Implications for Climate Action and Governance in the UK

Area of Science:

• Environmental science
• Climate governance
• Geographic information systems

Background:

• Local actors are increasingly involved in climate governance, yet national policymakers retain significant authority.
• Effective coordination between national and local climate actions is crucial but often overlooked.
• Existing research on climate governance primarily focuses on political and institutional factors, neglecting the role of data analysis methods.

Purpose of the Study:

• To investigate how data analysis methods, specifically the modifiable areal unit problem (MAUP), can affect climate governance.
• To highlight the potential consequences of MAUP on the efficacy and equity of climate actions.
• To draw attention to data scaling as a potential challenge in climate governance.

Main Methods:

• Analysis of two local-area greenhouse gas (GHG) emissions datasets in England: consumption-based and territorial emissions.
• Conceptual exploration of the modifiable areal unit problem (MAUP) in the context of climate action data.
• Examination of how data aggregation and spatial scale can influence analytical outcomes.

Main Results:

• The study identifies the potential for the modifiable areal unit problem (MAUP) to influence climate action analysis.
• Different spatial scales and data aggregation methods can lead to varied conclusions about emissions and climate action effectiveness.
• The paper highlights that data scaling issues may have implications for the efficacy and equity of climate policies.

Conclusions:

• Methods of data analysis, including data scaling, can present challenges to effective climate governance.
• Further research is needed to understand how data processing and analysis impact the assessment of non-state actors' contributions to climate action.
• Addressing data scaling issues is essential for robust and equitable climate policy development.