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Lab-Scale Model to Evaluate Odor and Gas Concentrations Emitted by Deep Bedded Pack Manure
Published on: July 19, 2018
A High-Resolution (30-m by 30-m) Gridded Dataset of Livestock Manure and Food Waste Generation in Ontario, Canada
Ushnik Mukherjee1, Jake Debruyn2, Juliane Mai3
1Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada. u3mukher@uwaterloo.ca.
Abstract:
Spatially explicit data on organic waste generation is limited, constraining efforts to reduce pollution and to plan for nutrient recovery and renewable energy infrastructure. We address this gap by providing a gridded, high-resolution (30-m by 30-m) dataset of livestock manure and food waste generation rates, along with associated nitrogen (N) and phosphorus (P) content, across Ontario, Canada for 2021. Manure estimates are derived from census livestock counts disaggregated to individual barns identified using aerial imagery. Food waste is estimated using population and employment data and sector-specific generation coefficients. By allocating livestock to geolocated barns and downscaling food waste to built-up areas, the dataset reveals local hotspots that are obscured in coarser administrative data. We find that 71% of manure is concentrated in just 25% of the producing area, with intensities exceeding 4,700 kg/ha/yr. Food waste shows similar clustering, with nearly 60% generated in 5.8% of the area. These spatial insights support precision siting of waste-to-resource infrastructure, enabling more effective pollution reduction and circular resource recovery.
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