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Calculator tool for determining greenhouse gas emissions for biosolids processing and end use
Sally Brown1, Ned Beecher, Andrew Carpenter
1School of Forest Resources, University of Washington Box 352100 Seattle, Washington 98195, United States. slb@uw.edu
Environmental Science & Technology
|November 18, 2010
Summary
Municipalities can estimate greenhouse gas (GHG) emissions from biosolids management using the Biosolids Emissions Assessment Model (BEAM). Optimizing processes to reduce methane and nitrous oxide can significantly lower GHG savings.
Area of Science:
- Environmental Science
- Waste Management
- Climate Change Mitigation
Background:
- Biosolids management is a significant source of greenhouse gas (GHG) emissions.
- Municipalities require tools to accurately estimate these emissions for effective mitigation strategies.
- Existing methods for biosolids management vary widely in their environmental impact.
Purpose of the Study:
- To develop and validate a GHG calculator tool, the Biosolids Emissions Assessment Model (BEAM).
- To enable Canadian municipalities to estimate GHG emissions associated with different biosolids management pathways.
- To identify management practices with the lowest and highest GHG footprints.
Main Methods:
- The BEAM tool was developed using data from peer-reviewed literature and Canadian municipal programs.
- GHG emissions were modeled for biosolids processing, end use, and disposal.
- Emissions from nine existing Canadian biosolids management programs were estimated using the BEAM model.
Main Results:
- Combustion after dewatering resulted in the highest GHG emissions.
- Digestion followed by land application showed the lowest emissions (-26 and -23 Mg CO(2)e 100 Mg(-1) biosolids dry wt.).
- Transportation contributed minimally to overall emissions, while N(2)O from land application and processing represented key uncertainties.
Conclusions:
- The BEAM model provides a valuable tool for municipalities to assess GHG emissions from biosolids.
- Targeted biosolids use and process optimization, particularly to avoid CH(4) and N(2)O, can lead to substantial GHG reductions.
- Further research is needed to reduce uncertainties in N(2)O emission estimations.

