Document Type
Article
Publication Date
3-2020
Abstract
Remote communities such as rural villages, post-disaster housing camps, and military forward operating bases are often located in remote and hostile areas with limited or no access to established infrastructure grids. Operating these communities with conventional assets requires constant resupply, which yields a significant logistical burden, creates negative environmental impacts, and increases costs. For example, a 2000-member isolated village in northern Canada relying on diesel generators required 8.6 million USD of fuel per year and emitted 8500 tons of carbon dioxide. Remote community planners can mitigate these negative impacts by selecting sustainable technologies that minimize resource consumption and emissions. However, the alternatives often come at a higher procurement cost and mobilization requirement. To assist planners with this challenging task, this paper presents the development of a novel infrastructure sustainability assessment model capable of generating optimal tradeoffs between minimizing environmental impacts and minimizing life-cycle costs over the community’s anticipated lifespan. Model performance was evaluated using a case study of a hypothetical 500-person remote military base with 864 feasible infrastructure portfolios and 48 procedural portfolios. The case study results demonstrated the model’s novel capability to assist planners in identifying optimal combinations of infrastructure alternatives that minimize negative sustainability impacts, leading to remote communities that are more self-sufficient with reduced emissions and costs.
DOI
10.3390/su12062208
Source Publication
Sustainability
Recommended Citation
Filer, J. E., Delorit, J. D., Hoisington, A. J., & Schuldt, S. J. (2020). Optimizing the Environmental and Economic Sustainability of Remote Community Infrastructure. Sustainability, 12(6), 2208. https://doi.org/10.3390/su12062208
Included in
Environmental Indicators and Impact Assessment Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons
Comments
This is an open access article published by MDPI and distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CC BY 4.0
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