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Published on: May 15, 2017
Governing Urban Wetlands for Decarbonization: Integrating Policy, Infrastructure, and Biogeochemistry.
Giri Raj Kattel1,2, Mengzhen Xu2
1Department of Infrastructure Engineering, The University of Melbourne, Melbourne, Parkville 3010, Australia.
Environmental Science & Technology
|July 1, 2026
Summary
Urban wetlands can mitigate climate change, but governance decisions, not just ecology, determine their greenhouse gas impact. Effective management is key to ensuring these natural systems benefit, rather than harm, climate goals.
Area of Science:
- Environmental Science
- Policy Science
- Urban Ecology
Background:
- Urban wetlands are promoted as nature-based solutions for climate mitigation.
- Greenhouse gas emissions from urban wetlands are highly variable and can be counterproductive.
- Urban hydrology, nutrient loading, and disturbance regimes are tightly managed, influencing emissions.
Purpose of the Study:
- To reframe knowledge on urban wetland carbon outcomes through a policy science lens.
- To identify controllable decision points influencing whether urban wetlands are climate assets or liabilities.
- To propose strategies for optimizing urban wetlands for climate mitigation.
Main Methods:
- Policy science lens applied to existing biogeochemical knowledge.
- Identification of governance-influenced decision points.
- Outline of four interlinked management strategies.
Main Results:
- Carbon outcomes in urban wetlands are shaped by governance decisions, not solely ecological potential.
- Controllable decision points exist in design, operation, monitoring, and institutional coordination.
- Four strategies are proposed: governance-informed design, low-carbon infrastructure operation, adaptive monitoring, and institutional alignment.
Conclusions:
- Urban wetlands can be actively managed as climate-friendly infrastructure.
- Recognizing wetlands as governable systems offers a pragmatic approach to decarbonization.
- Strategies can integrate urban wetlands into climate mitigation efforts despite real-world constraints.
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