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ADMS-EIA模型在规模化畜禽养殖场恶臭影响预测中的应用 被引量:1

Application of ADMS-EIA Model in Prediction of Odor Effect in Large-Scale Livestock and Poultry Farms
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摘要 由于规模化畜禽养殖场的推广是发展现代畜牧业的重要组成,然而在规模化畜禽养殖场的养殖过程中,恶臭导致的污染问题已变得愈发严重,制约了规模化畜禽养殖场的健康发展。因此,对规模化畜禽养殖场恶臭影响进行简便、准确地预测,对于在决策源头预防恶臭污染,优化规模化畜禽养殖场选址及平面布置着重要意义。以上海某规模化畜禽养殖场案例为典型,利用ADMS-EIA模型对其产生的恶臭影响进行了预测分析。结论表明:在营运期间采取合理的恶臭污染控制措施后,规模化养殖场产生的恶臭对厂界四周及周边居民无明显影响。ADMS-EIA模型可以对规模化畜禽养殖场产生的恶臭污染物影响进行较为准确的预测,为规模化养殖场绿色发展夯实可靠的基础和有效的环保技术支持。 The promotion of large-scale livestock and poultry farms is an important component of developing modern animal husbandry.However,in the process of large-scale livestock and poultry breeding,the pollution caused by odor has become more and more serious,which restricts the healthy development of large-scale livestock and poultry farms.Therefore,simple and accurate prediction of the odor impact of large-scale livestock and poultry farms is of great significance for preventing odor pollution at the decision-making source and optimizing the site selection and layout of large-scale livestock and poultry farms.In this paper,a case of a large-scale livestock and poultry farm in Shanghai was taken as a typical case,and the ADMS-EIA model was used to predict and analyze the odor effect.The result of prediction analysis shows that the stench produced by large-scale farms has no obvious effect on the residents around the factory boundary after taking reasonable measures to control the stench pollution during operation.The ADMS-EIA model can accurately predict the impact of odor pollutants produced by large-scale livestock and poultry farms,which lays reliable foundation for the green development of large-scale livestock and poultry farms and provides effective technical support for environmental protection.
作者 顾耘东 陆祥炜 骆蓓菁 Gu Yundong;Lu Xiangwei;Luo Beijing(Shanghai Investigation,Design&Research Institute,Shanghai 200434,China)
出处 《绿色科技》 2021年第10期185-187,190,共4页 Journal of Green Science and Technology
关键词 规模化畜禽养殖场 恶臭 ADMS-EIA模型 空气污染 large-scale livestock and poultry farms odor ADMS-EIA air pollution
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