Evaluation of environmental consequences affecting human health in the current and optimal cropping patterns in the eastern Lorestan Province, Iran

Planning for optimal use of resources and reduction of environmental impacts, in addition to resource protection, is associated with increasing farmers' revenues and boosting the regional economy. Given the limited resources and environmental impacts of agricultural activities on human health, it is necessary to determine an appropriate cropping pattern. The present research aimed to maximize net profit and minimize environmental impacts, including the releases of carcinogens, noncarcinogens, ozone layer depletion, ionizing radiation, and respiratory inorganics and organics on human health. In this study, an optimal cropping pattern of irrigated and rainfed crops was proposed for the east of Lorestan Province using multi-objective nonlinear programming (MOP). Results showed that the cropping areas of chickpea, rapeseed, and potatoes decreased by 50% in the irrigated crop of MOP model and that of lentil in the MOP model of rainfed crops compared with the current pattern. Another important result was increases in the cropping areas of lentil and bean in the MOP pattern of irrigated crops and wheat in the rainfed MOP model. The environmental impacts of agricultural sector on human health can be reduced by determining an optimal cropping pattern. The implementation of this model in the region reduced the emissions of carcinogens (4%), noncarcinogens (9%), respiratory inorganics (17%), ionizing radiation (14%), ozone layer depletion (17%), and respiratory organics (15%) compared with the existing situation along with an increased net profit of $968,483. According to the findings, consideration of environmental objectives affecting human health is essential in the optimization of the cropping pattern. In addition to optimal use of water and land resources, using the proposed model helps to increase profits and reduce environmental consequences on human health.

Automated summary

By using multi-objective nonlinear programming, an optimal cropping pattern for irrigated and rainfed crops in the east of Lorestan Province was proposed. The study found that the optimized cropping pattern can reduce environmental impacts of agriculture on human health and increase net profit.