E. Bucur, V. Danciulescu, G. Tanase, C. Lehr, A. Vasile
{"title":"ODOUR POLLUTION ASSESSMENT THROUGH INDIRECT METHODS BASED ON THE MONITORING OF TECHNOLOGICAL PARAMETERS - CASE STUDY","authors":"E. Bucur, V. Danciulescu, G. Tanase, C. Lehr, A. Vasile","doi":"10.21698/rjeec.2019.101","DOIUrl":null,"url":null,"abstract":"The odours in the ambient air, through the discomfort that they induce, represent an actual problem for the communities located nearby companies with technological processes that emit in the air different strong and unpleasant odorous substances. The standard method for odour assessment involves measuring the concentration through dynamic olfactometry according with SR EN 13725:2003, a very complex method that requires specialized working staff and expensive equipment. The paper presents an indirect method for odour assessment in the ambient air, based on monitoring the process and meteorological data - Predictive Emission Monitoring Systems (PEMS) and it is applied to a livestock farm. Using the multiple regression analysis of the monitoring data for the most important specific technological and meteorological parameters it can be developed a mathematical model that could be used for the calculation of odour concentration in air, without the necessity of direct measurement, after the initial step. For the case study presented in the paper, the distance between the slurry lagoon was identified as a significant statistical parameter that can determine in a proportion of 72% the concentration of odour in the ambient air nearby the farm; the margin of error for odour concentration assessment, according to the model validation tests, is ± 8%, acceptable value for an estimation method by mathematical modelling.","PeriodicalId":21370,"journal":{"name":"Romanian Journal of Ecology & Environmental Chemistry","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Romanian Journal of Ecology & Environmental Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21698/rjeec.2019.101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The odours in the ambient air, through the discomfort that they induce, represent an actual problem for the communities located nearby companies with technological processes that emit in the air different strong and unpleasant odorous substances. The standard method for odour assessment involves measuring the concentration through dynamic olfactometry according with SR EN 13725:2003, a very complex method that requires specialized working staff and expensive equipment. The paper presents an indirect method for odour assessment in the ambient air, based on monitoring the process and meteorological data - Predictive Emission Monitoring Systems (PEMS) and it is applied to a livestock farm. Using the multiple regression analysis of the monitoring data for the most important specific technological and meteorological parameters it can be developed a mathematical model that could be used for the calculation of odour concentration in air, without the necessity of direct measurement, after the initial step. For the case study presented in the paper, the distance between the slurry lagoon was identified as a significant statistical parameter that can determine in a proportion of 72% the concentration of odour in the ambient air nearby the farm; the margin of error for odour concentration assessment, according to the model validation tests, is ± 8%, acceptable value for an estimation method by mathematical modelling.
环境空气中的气味,通过它们引起的不适,代表了位于公司附近的社区的实际问题,这些公司在空气中排放各种强烈而令人不快的气味物质。气味评估的标准方法包括根据SR EN 13725:2003通过动态气味测定法测量浓度,这是一种非常复杂的方法,需要专业的工作人员和昂贵的设备。本文提出了一种基于过程监测和气象数据的环境空气气味间接评价方法——预测排放监测系统(PEMS),并应用于某家畜养殖场。通过对最重要的具体技术和气象参数的监测数据进行多元回归分析,可以建立一个数学模型,该模型可用于计算空气中的气味浓度,而无需在初始步骤后进行直接测量。在本文中提出的案例研究中,浆液泻湖之间的距离被确定为一个重要的统计参数,可以决定农场附近环境空气中72%的气味浓度;根据模型验证测试,气味浓度评估的误差范围为±8%,这是通过数学建模估计方法的可接受值。