Development of Crop.LCA, an adaptable screening life cycle assessment tool for agricultural systems: A Canadian scenario assessment
Goglio, P., Smith, W.N., Worth, D.E., Grant, B.B., Desjardins, R.L., Chen, W., Tenuta, M., McConkey, B.G., Williams, A., Burgess, P. (2018). Development of Crop.LCA, an adaptable screening life cycle assessment tool for agricultural systems: A Canadian scenario assessment. Journal of Cleaner Production, [online] 172 3770-3780. http://dx.doi.org/10.1016/j.jclepro.2017.06.175
Plain language summary
This paper described an open-source tool written in R language, named Crop.LCA, for calculating / quantifying the impacts of agricultural system on environment. LCA stands for life cycle assessment, which is a technique to assess the environmental burden associated with all stages of commodity production, from raw material extraction, manufacture, distribution to disposal or recycling. We first utilized an agroecosystem model called DNDC, i.e. DeNitrification-DeComposition, to simulate 28 year of cropping system dynamics, then used Crop.LCA to predict soil Greenhouse Gases (GHG) Emission, represented by four categories: cumulative energy demand (CED), 100-year global warming potential (GWP), eutrophication and acidification potential. For example, rotation with legumes would help in reducing energy usage, global warming potential and acidification significantly. Crop.LCA is proven to be a useful tool to assessing cropping systems for cleaner agricultural production.
There is an increasing demand for sustainable agricultural production as part of the transition towards a globally sustainable economy. To quantify impacts of agricultural systems on the environment, life cycle assessment (LCA) is ideal because of its holistic approach. Many tools have been developed to conduct LCAs in agriculture, but they are not publicly available, not open-source, and have a limited scope. Here, a new adaptable open-source tool (Crop.LCA) for carrying out LCA of cropping systems is presented and tested in an evaluation study with a scenario assessment of 4 cropping systems using an agroecosystem model (DNDC) to predict soil GHG emissions. The functional units used are hectares (ha) of land and gigajoules (GJ) of harvested energy output, and 4 impact categories were evaluated: cumulative energy demand (CED), 100-year global warming potential (GWP), eutrophication and acidification potential. DNDC was used to simulate 28 years of cropping system dynamics, and the results were used as input in Crop.LCA. Data were aggregated for each 4-year rotation and statistically analyzed. Introduction of legumes into the cropping system reduced CED by 6%, GWP by 23%, and acidification by 19% per ha. These results highlight the ability of Crop.LCA to capture cropping system characteristics in LCA, and the tool constitutes a step forward in increasing the accuracy of LCA of cropping systems as required for bio-economy system assessments. Furthermore, the tool is open-source, highly transparent and has the necessary flexibility to assess agricultural systems.