Waste to Land (W2L): A novel tool to show and predict the spatial effect of applying biosolids on the environment. (November 2020)

• Record Type: Journal Article
• Authors: Gonzalez-Ollauri, Alejandro; Thomson, Craig S.; Mickovski, Slobodan B.
• Is Part Of: Agricultural systems. Volume 185(2020)
• Publication Date: 2020-11
• Subjects: Agriculture -- Biosolids -- Modelling -- Spatial analysis -- Stakeholder engagement -- Multi-criteria analysis; Agricultural systems -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; 338.16
• DOI: 10.1016/j.agsy.2020.102934
• Languages: English
• ISSNs: 0308-521X

Abstract

Abstract: There is a complex relationship between land-use, the environment, food production and quality. Regulatory and non-regulatory interventions, such as application of biosolids to agricultural land, are often undertaken at a field- or farm- level and the aggregated effects across farms and regions are difficult to understand, predict, and communicate to others both spatially and temporally. The aim of this paper was to introduce Waste to Land (W2L). W2L is a novel, holistic tool that combines spatial data analysis methods, multi-criteria analysis, and numerical models to detect areas for optimum biosolids application and to predict the spatial effect of applying biosolids to land. A robust framework was developed first to chart the effects of applied biosolids on the environment and, potentially, on the human food chain. Selecting cadmium as a prototype contaminant, a conceptual model was designed as the basis to define the workflow for the tool. Using the open-source, statistical language R and freely available data, the operation and outputs from the tool were demonstrated at a national scale in Scotland, UK. The results provided fresh intelligence on the ability of the Scottish Landbank to receive biosolids and on the spatial effect of landspreading biosolids, to facilitate the exchange of information between stakeholders, and to enable decision-making in a context of spreading biosolids on farmland. Highlights: A novel tool to predict the spatial effect of applying biosolids to land is proposed The tool combines spatial data analysis, multi-criteria analysis, and numerical models in R The tool's feasibility and potential was verified through stakeholder engagement The tool will allow gaining new knowledge, enhancing communication among stakeholders, and aiding the decision-making process