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The present study aimed to investigate the status of energy consumption and environmental impacts in the raisin production using life cycle assessment (LCA) approach. Required data were collected from 50 grape producers in Dena county and raisin production workshop in Yasuj county through questionnaire and face-to-face interview. The energy equivalent of inputs and outputs was obtained using related specific energy coefficients and environmental indices including abiotic depletion (AD), acidification (AC), eutrophication (EUP), global warming (GW), ozone layer depletion (OLD), human toxicity (HT), fresh water aquatic ecotoxicity (FE), marine aquatic ecotoxicity (ME), terrestrial ecotoxicity (TE) and photochemical oxidation (PO) were compared in vineyard, processing workshop, packaging and transportation phases using Simapro software and CML2 baseline 2000 modeling approach. Results showed that based on the production of 500 g packaged raisin, total input energy for vineyard and processing workshop was calculated as 8.70 and 32.7 MJ and energy ratio was 3.38 and 0.7, respectively. The contribution of electricity energy input in vineyard and grape energy input in processing factory to the related total energy were calculated as 28% and 90%, respectively. Results obtained from the analysis of environmental indices showed that the GW index is 4.258 kg CO 2 eq per production of 500 g packaged raisin, which inputs production and consumption in vineyard had a contribution of 95% to GW index. In other indices, emissions related to the vineyard was higher than three other stages. Farmyard manure (FYM), machines and adhesive tape in factory sector were indicated as major contributor to pollutant emissions in vineyard, processing and packaging, respectively. • The total input energy for vineyard and processing plant was calculated as 8.70 and 32.7 MJ. • The contribution of electricity energy was calculated as 28% of energy input total. • FYM was indicated as major contributor to emissions in vineyard sector. • Machines were indicated as major contributor to emissions in processing plant. [ABSTRACT FROM AUTHOR]

The aim of this study is to perform a life cycle and energy flow assessments of Municipal Solid Waste (MSW). These latter are modeled using Artificial Neural Network (ANN) for integrated waste management system in Tehran Municipality, Iran. The initial data used in this study have been obtained from Waste Management Organization of Tehran Municipality, while the required data related to the background system were extracted from the EcoInvent 2.2 database. Based on the obtained results from the energy cycle analysis, energy consumptions for transportation and processing plus recycling were calculated as 227.02 and 155.95 Gigajoules (GJ), respectively for 8500 t MSW. This energy consumption has led to the production of 18,884.03 GJ energy output (recycled materials) with an energy ratio of 121.56. A high energy ratio demonstrated that recycling of municipal solid is a new gateway against energy challenges. By optimizing energy consumption, especially energy related to transportation, this ratio could increase more than before. The results obtained from Life Cycle Assessment (LCA) indicate that transportation is considered the most important hot spot in the recycling of MSW while recycling papers is the main contributor to the redaction of environmental indicators in the recycling system. More intensity is observed for indicators related to toxicity due to the lack of waste disposal and to the entry of undesirable substances in natural resources. The 5-7-7-11 structure is the best topology to predict the amount of recycled materials and the impacts of environmental emissions from MSW recycling process developed by feed-forward back-propagation ANN models which are based on Levenberg-Marquardt (LM) training algorithm. Coefficient of determination values for train are in the ranges of 0.926–0.978 and have excellent performance in predicting all the output parameters based on the input parameters. [ABSTRACT FROM AUTHOR]