Dataset for greenhouse gas modelling in diesel dependent communities transitioning to bioenergy
Buss, Jennifer; Mansuy, Nicolas; Laganière, Jérôme (2022), Dataset for greenhouse gas modelling in diesel dependent communities transitioning to bioenergy , Dryad, Dataset, https://doi.org/10.5061/dryad.79cnp5hxw
The data presented here are from the research article entitled “Greenhouse gas mitigation potential of replacing diesel fuel with wood-based bioenergy in an arctic Indigenous community: A pilot study in Fort McPherson, Canada”. Based on a pilot study realized in Northern Canada and life cycle assessment, we provide a set of key parameters and operational data gathered along the biomass supply chain to build a GHG mitigation scenario and compute the quantity and timing of GHG savings in the off-grid community of Fort McPherson, NWT. Given that GHG mitigation scenarios are often assessed against a relative fossil-fuel reference scenario, we are providing two categories of data; 1) data for the reference fossil fuel scenario and; 2) data along the upstream operations of biomass supply chains. Both categories contain data related to the operational processes as well as forest growth or decomposition of unused feedstock. Although the data presented are mostly derived from the boreal forest, they could help guide other communities beyond the boreal to develop a renewable bioenergy system and assess their GHG mitigation options.
Data for both scenarios were collected and curated from a community-based bioenergy project, published literature, and other GHG models and inventories. As many parameters as possible came from the local area being studied to better tailor the model to Fort McPherson’s specific conditions. A seven-step process was designed to guide users through building the biomass and fossil fuel reference scenarios, identifying the key parameters, and computing the quantity and timing of GHG savings. These steps are identified as: feedstock selection, collection and processing, transportation, conversion, computing GHG emissions, development of forest carbon dynamics, and computing forest carbon.
This file contains GHG emissions factors, forest growth parameters, and biomass decomposition parameters used in the greenhouse gas (GHG) modelling performed in Buss et al. 2022. A metadata tab in the file describes all parameters included in the data file, their sources, as well as the naming convention for scenarios. The data file includes a total of 72 scenarios.
This file contains the R code for the GHG model. The code guides users through a seven-step life cycle analyses designed to aid in the development of biomass and reference fossil fuel scenarios, and calculate the quantity and timing of GHG benefits. It also includes a description of model parameters and outputs.
This file contains a summary of a small subset of model outputs for all 72 scenarios included in the Bioenergy_Modelling_Data file. Model outputs included in this file are carbon parity times and GHG emissions at 25, 50, and 100 years.
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