Incorporating Social System into Water-Food-Energy Nexus

Molajou, Amir; Pouladi, Parsa; Afshar, Abbas

doi:10.1007/s11269-021-02967-4

Cited by 61 publications

(34 citation statements)

References 49 publications

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“…Food waste is produced especially in the agricultural, industrial, and urban sectors of society, including by wholesalers and consumers (Seidavi et al, 2020;Molajou et al, 2021). Utilization of such wastes requires urgent research as recycling and reduction of residues can reduce pollution and improve the current situation by preparing new feed from the residues (Chen et al, 2020;Barreira et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Investigation of parameters in restaurant food waste for use as poultry rations

et al. 2022

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One way to use food industry wastes is to feed the livestock and poultry. Applying appropriate management methods for the optimal use of agricultural waste in the preparation of livestock and poultry feed increases productivity and reduces damage to agricultural and conversion industries and the use of new resources in animal and poultry feed. In this paper, in order to investigate the possibility of recycling food waste as poultry feed, the waste produced in a restaurant has been used. The parameters of fat percentage were measured using Soxhlet extractor, percentage of dry matter using the oven, percentage of protein in it using Kjeldahl method, and also the percentage of calcium and phosphorus with the standard beard. Comparing them with the usual diet used in poultry feed shows that the average values of calcium, protein, and fat content of food waste are 0.14%, 5.65%, 7.34% higher than the average diet of poultry, respectively. Also, the average amount of phosphorus and dry matter of food waste is 0.48% and 60% less than the average diet of poultry, respectively.

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Section: Introductionmentioning

confidence: 99%

Investigation of parameters in restaurant food waste for use as poultry rations

et al. 2022

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“…The Fuzzy satisfying method is used to opt the best trade-off solution out of the provided Pareto solutions. In this approach, a fuzzy membership is devoted to each Pareto front solution some value between 0 and 1 which is calculated by ( 14) [41]- [43].…”

Section: Fuzzy Satisfying Methodsmentioning

confidence: 99%

An Economic and Environmental Optimization Model in a Micro Grid with Demand Response

Zadeh

Derakhshan

Hakimi

et al. 2022

Environmental and Climate Technologies

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To accommodate the current energy system with the renewable energy source, the concept of micro grid (MG) has been developed. Using such systems, different advantage such as minimization of power loss, operating cost, and emission can be achieved. In this paper, the 24-hour power and heat based MG scheduling is investigated under environmental aspects and economic issues as bi-objective modelling in the presence of demand response (DR) program for decreasing greenhouse gas emission and system operation cost. The investigation of the MG contains energy storage system, boiler and combined heat and power (CHP). For solving the problem, first the Pareto optimal solutions have been obtained by the weighted-sum technique, then the fuzzy satisfying approach has been used to get optimal trade-off result. To confirm the performance of the method, the problem is solved in two-case to demonstrate the effects of DR on MG scheduling.

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“…These integrated methods could also leverage insights from non-ML implementations of interactions between human and Earth systems at varying scales (Arneth, Brown, and Rounsevell 2014;Nazemi and Wheater 2015;Thornton et al 2017;) by using data-driven causal inference learning processes such as causal complex network analysis to identify feedback among the processes. We can also harness machine learning to relate patterns in data across scales and to facilitate reduction of model bias (Molajou, Pouladi, and Afshar 2021;Sert, Bar-Yam, and Morales 2020). Additional opportunities within this space include the synchronous, bidirectional integration of existing human system models with existing Earth system or specific domains as well as exploitation of transfer learning methods.…”

Section: Coupling Of Human and Earth System Modelsmentioning

confidence: 99%