TY - JOUR
T1 - Development of decision support framework for optimizing resource recovery from a household-scale integrated agri-aquaculture system in the Mekong Delta, Vietnam
AU - Thu Thao, Nguyen Thi
AU - LeThanh, Son
AU - Schnitzer, Hans
AU - Thang, Nguyen Viet
AU - Hai, Le Thanh
N1 - Funding Information:
This research is funded by Vietnam National University - Ho Chi Minh City ( VNU-HCM ) under grant number NCM-2020-24-01. The authors would like to thank to the Department of Natural Resources and Environment in the provinces in Mekong delta for assistance during site investigation and data collection, and ASEAN-European Academic University network (ASEA-UNINET) for collaboration with IPPE, TU Graz, Austria, to implement this study. Special thanks to Mr. Mark Looney (Environmental Source Samplers, Inc., Wilmington, NC, mark@essknowsair.com ) for your elaborative language editing on our manuscript.
Funding Information:
There is a research gap on an optimization approach for economic and environmental performance of resource recovery solutions for the IFS. Economic optimization modelling was used to evaluate the energy and nutrient recovery performance of agroforestry residue treatment (Raviv et al., 2018), organic waste composting performance (Bekchanov and Mirzabaev, 2018). Recycling organic waste into compost decreased costs of both total waste management and chemical fertilizer use (Bekchanov and Mirzabaev, 2018). The economic and environmental optimization of a large-scale integrated system using 1000 cow dung as fertilizer for crops revealed a significant reduction in environmental impact but also a 14 percent decrease in profits (Taifouris and Martin, 2021). The research gap has highlighted the necessity of economic and environmental optimization approach for resource recovery solutions based on biowastes in a household-scale IFS. It raises further research questions: (i) What types of resource recovery (or biowaste treatment) solutions are appropriate for a small-scale integrated system? (ii) Which combination of these solutions could generate post-treatment products gaining economic profits for this system? (iii) How to optimize economic and environmental efficiency for these solutions when applied to small-scale (household size) farming systems? and (iv) Which guide can be used to assist the implementation process of optimizing the economic and environmental performance of resource recovery solutions for this system? This work aims to fulfill this gap by proposing a decision support framework for optimizing resource recovery options for a household scale IFS that does not require a large investment while reducing GHG emission. The framework involves economic assessment based on the FarmDESIGN model (Timler et al., 2020) and LCA at cradle-to-gate stages to optimize resource recovery performance. It includes the sequential steps for optimizing processes that follow the well-known “continuous improvement” PDCA (Plan - Do - Check - Act) cycle (Jiang et al., 2021). The cycle steps are the same as those in the FarmDESIGN model, which was developed specifically for an agricultural system. A resource recovery process for agricultural waste operates as a system, so the FarmDESIGN model's steps can be used for project planning of the resource recovery process.This research proposed a decision support framework for optimizing resource recovery efficiency on energy and nutrient products recovered from biowaste treatment of a household-scale IFS system. The economic and environmental performance of resource recovery solutions in this system was maximized for reconfiguring the system by combining concept of “continuous improvement” with LCA. Folowing the steps of this framework, the economic performance of the resource recovery facility installations was evaluated using the IFS system's input data. The data based on the household's income limits, such as farm size and budget, as well as adequate biowaste supplies obtained from animals and plants, in conjunction with payback time and operation costs, would create constraints for optimization algorithms for economic problems of treatment options. Composting, vermicomposting, AD, pyrolysis, and pelleting were chosen as appropriate processes to recover energy and nutrients from agricultural waste for the case study. The optimization results show that the most feasible scenarios were a combination of composting, vermicomposting, pelleting, and AD. Pyrolysis could be used as an energy recovery technique if the products have a high predicted market price. Scenarios in which manure is divided evenly between AD and composting reduce GHG emissions more effectively than scenarios in which manure is only placed in the anaerobic tank. Depending on the input data sources, this framework can be applied to other cases with different types of biowastes. It may be of interest to not only integrated farm managers but decision-makers involved in agricultural waste management.This research is funded by Vietnam National University - Ho Chi Minh City (VNU-HCM) under grant number NCM-2020-24-01. The authors would like to thank to the Department of Natural Resources and Environment in the provinces in Mekong delta for assistance during site investigation and data collection, and ASEAN-European Academic University network (ASEA-UNINET) for collaboration with IPPE, TU Graz, Austria, to implement this study. Special thanks to Mr. Mark Looney (Environmental Source Samplers, Inc. Wilmington, NC, mark@essknowsair.com) for your elaborative language editing on our manuscript.
Publisher Copyright:
© 2022
PY - 2022/12/15
Y1 - 2022/12/15
N2 - Various biodegradable wastes derived from an integrated farming system require appropriate waste treatment solutions to maximize their resource recovery efficiency regarding environmental and economic benefits. This study aims to develop a decision support framework for optimizing resource recovery performance of biowaste treatment solutions in the integrated system. The “continuous improvement” concept of the FarmDESIGN model is adopted in conjunction with a Life Cycle Assessment tool. The combination of these two tools provides a comprehensive approach to the optimization algorithms for solving economic problems and emission reduction potential assessment in technology options of biowaste treatment for the integrated farming system. A case study was used for this purpose, with data from a household-scale integrated agri-aquaculture system in Vietnam's Mekong Delta. The results of the optimization calculations revealed that decisions on resource recovery solutions based on system data would identify a set of alternative system configurations. A good farm configuration including solutions of composting, vermicomposting, pelleting, and anaerobic digestion would be appropriate for an agri-aquaculture system larger than 2 ha in size, yielding the highest profits of up to 1900 USD while emitting the least amount of greenhouse gas. This study provides the implementation process of optimizing resource recovery performance, which may be of interest not only to integrated farm managers, but also decision-makers involved in agricultural waste management.
AB - Various biodegradable wastes derived from an integrated farming system require appropriate waste treatment solutions to maximize their resource recovery efficiency regarding environmental and economic benefits. This study aims to develop a decision support framework for optimizing resource recovery performance of biowaste treatment solutions in the integrated system. The “continuous improvement” concept of the FarmDESIGN model is adopted in conjunction with a Life Cycle Assessment tool. The combination of these two tools provides a comprehensive approach to the optimization algorithms for solving economic problems and emission reduction potential assessment in technology options of biowaste treatment for the integrated farming system. A case study was used for this purpose, with data from a household-scale integrated agri-aquaculture system in Vietnam's Mekong Delta. The results of the optimization calculations revealed that decisions on resource recovery solutions based on system data would identify a set of alternative system configurations. A good farm configuration including solutions of composting, vermicomposting, pelleting, and anaerobic digestion would be appropriate for an agri-aquaculture system larger than 2 ha in size, yielding the highest profits of up to 1900 USD while emitting the least amount of greenhouse gas. This study provides the implementation process of optimizing resource recovery performance, which may be of interest not only to integrated farm managers, but also decision-makers involved in agricultural waste management.
KW - Bio-resource recovery
KW - Decision support framework
KW - FarmDESIGN
KW - Integrated AAS
KW - Life cycle assessment
UR - http://www.scopus.com/inward/record.url?scp=85140766644&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2022.134643
DO - 10.1016/j.jclepro.2022.134643
M3 - Article
AN - SCOPUS:85140766644
VL - 379
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
SN - 0959-6526
M1 - 134643
ER -
