A High-Resolution (30-m by 30-m) Gridded Dataset of Livestock Manure and Food Waste Generation in Ontario, Canada (2021)

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.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2026-04-22
DOI
https://doi.org/10.1038/s41597-026-07282-4
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A High-Resolution (30-m by 30-m) Gridded Dataset of Livestock Manure and Food Waste Generation in Ontario, Canada (2021)

Ushnik Mukherjee, Jake DeBruyn, Rebecca K. Saari, Juliane Mai et al.
Scientific Data
Food Waste Reduction and Sustainability
article

A High-Resolution (30-m by 30-m) Gridded Dataset of Livestock Manure and Food Waste Generation in Ontario, Canada (2021)

Ushnik Mukherjee, Jake DeBruyn, Rebecca K. Saari, Juliane Mai, N. B. Basu
article en

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.

Scientific Data
Ministry of Agriculture, Food and Rural Affairs (CA), University of Waterloo (CA)
Environment and Climate Change Canada
Responsible consumption and production, Zero hunger
Openalex Percentile: Top 15%
Food Waste Reduction and Sustainability
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.