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    An environmental risk assessment for a DDX-contaminated agricultural area in Turkey: soil vs. plant or human vs. animal
    (Springer Heidelberg, 2021) Korucu, Mahmut Kemal; Elibol, Pinar Sevim; Isleyen, Mehmet
    This study is the first research attempt to assess the environmental risks of an agricultural area contaminated with the p,p '-DDT and its metabolites (DDX) on human and terrestrial species through exposure to soil and agricultural products, simultaneously. The study was carried out for a DDX-contaminated agricultural area in Turkey. Soil samples obtained in two different harvest applications were analyzed in terms of DDX levels. Similarly, stem, leaf, and fruit samples of an agricultural product grown on the same soils were analyzed. Using the results of these analyses, DDX intake values were calculated for 5 different human receptor groups, 4 different bird species, and 4 different mammal species, and the risk values were calculated by using a stochastic approach based on a Monte Carlo simulation. Findings indicated a substantial level of carcinogenic risk in the human receptor groups. Furthermore, a significant risk of reproductive toxicity was determined for the birds and mammals. The findings prominently showed that these risks can develop not only through exposure to DDX-contaminated soils but also through the consumption of plants grown on these soils.
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    An environmental risk assessment for a DDX-contaminated agricultural area in Turkey: soil vs. plant or human vs. animal (May, 10.1007/s11356-021-14154-4, 2021)
    (Springer Heidelberg, 2021) Korucu, Mahmut Kemal; Elibol, Pinar Sevim; Isleyen, Mehmet
    [Abstract Not Available]
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    A mixed integer linear programming model for long-term planning of municipal solid waste management systems: Against restricted mass balances
    (Pergamon-Elsevier Science Ltd, 2020) Batur, Maliki Ejder; Cihan, Ahmet; Korucu, Mahmut Kemal; Bektas, Nihal; Keskinler, Bulent
    Long-term planning of municipal solid waste management systems is a complex decision making problem which includes a large number of decision layers. Since all different waste treatment and disposal processes will show different responses to each municipal solid waste component, it is necessary to separately evaluate all waste components for all processes. This obligation creates an obstacle in the programming of mass balances for long-term planning of municipal solid waste management systems. The development of an ideal mixed integer linear programming model that can simultaneously respond to all essential decision layers including waste collection, process selection, waste allocation, transportation, location selection, and capacity assessment has not been made possible yet due to this important modeling obstacle. According to the current knowledge of the literature, all mixed integer linear programming studies aiming to address this obstacle so far have had to restrict many different possibilities in their mass balances. In this study, a novel mixed integer linear programming model was formulated. ALOMWASTE, the new model structure developed in this study, was built to take into consideration different process, capacity, and location possibilities that may occur in complex waste management processes at the same time. The results obtained from a case study showed the feasibility of new mixed integer linear programming model obtained in this study for the simultaneous solution of all essential decision layers in an unrestricted mass balance. The model is also able to provide significant convenience for the multi-objective optimization of financial-environmental-social costs and the solution of some uncertainty problems of decision-making tools such as life cycle assessment. (C) 2020 Elsevier Ltd. All rights reserved.