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Agriculture plays a central role in maintaining food security and achieving sustainable development for human society. It is a challenge for the agricultural sector to mitigate greenhouse gas (GHG) emissions and maintain agricultural production. However, dual-level uncertainties exist in the processes of agricultural GHG accounting and emission reduction management. In this research, an integrated approach for identifying adaptation strategies in agricultural GHG emission reduction management was developed through incorporating life cycle analysis (LCA) of agricultural production into a general mathematical programming model. This approach strengthened the applicability of LCA and the comprehensiveness of programming models in generating agricultural adaptive actions under different GHG emission restriction targets. Also, dual-level uncertainties of LCA and adaptation management can be effectively addressed. A case study was proposed to illustrate application of the approach in Dalian City, China. The results indicated that farming patterns in eight districts would change significantly. The total area of maize fields would account for the primary proportion (i.e., 40-45 %) in its agricultural sector. Rice, peanut and cabbage fields would be the minor contributors in terms of GHG emissions. In addition to effective rainfall (i.e., [156, 259] mm/ha), a certain amount of water would be supplied for agricultural irrigation to maximize the city's agricultural yields. Compared with other agricultural crops, rice fields would need the largest amount of irrigation water (i.e., [153.72, 277.98] Mt) to meet the requirements of local government plans. [ABSTRACT FROM AUTHOR]

Concerns over water conflicts between human beings and ecosystems are increasing. Also, wastewater discharged by manufacturing industries is causing multiple ecological and environmental impacts in many regions. In this research, to comprehensively assess ecological and environmental impacts of wastewater discharged from large-scale industries, a hybrid life-cycle and fuzzy-set-pair analyses (HLCA-FSPA) approach was proposed. This approach represented an integration of life cycle analysis, set pair analysis, and fuzzy sets theory. The developed method could improve previous studies in systematically reflecting impacts of industrial wastewater in terms of multiple dimensions, and considering uncertain parameters in the evaluation process. It could give a complete and robust assessment of wastewater environmental and ecological impacts based on life cycle inventory/database and uncertainty analyses. The developed HLCA-FSPA method was then applied to a pulp and paper mill in Shandong Province of China. The results indicated that the impact of wastewater at the stage of pulp production was under the limit of China's wastewater discharge standard (i.e., level III) with the connection degree of 0.47. Comparatively, the impact level of the entire life cycle of copying paper production was III with a slightly decreased connection degree (i.e., 0.38). Such a difference reflected possibility variations of the impacts at different stages. The results also indicated that the developed method can be expanded to other areas based on the corresponding LCA database. Thus, the results could provide scientific bases for supporting decision-making in industrial wastewater management to mitigate the associated ecological and environmental impacts. [ABSTRACT FROM AUTHOR]

In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation. [ABSTRACT FROM AUTHOR]