Postgraduate Program in Environmental Engineering (PPGEA), Federal University of Santa Catarina (UFSC), 88040900, Florianópolis, Brazil. CAPES Foundation scholarship holder (main author), Brazilian Ministry of Education, Brasília, Brazil; WG Environmental Health, Department of Biomedical Sciences, University of Veterinary Medicine Vienna, Veterinärplatz 1, A-1210 Vienna, Austria.
Central Institute for Meteorology and Geodynamics, Hohe Warte 38, A-1190 Vienna, Austria.
J Environ Sci (China). 2019 May;79:11-24. doi: 10.1016/j.jes.2018.09.018. Epub 2018 Sep 28.
In recent years, there has been a growing concern about potential impacts on public health and wellbeing due to exposure to environmental odour. Separation distances between odour-emitting sources and residential areas can be calculated using dispersion models, as a means of protecting the neighbourhood from odour annoyance. This study investigates the suitability of using one single year of meteorological input data to calculate reliable direction-dependent separation distances. Accordingly, we assessed and quantified the inter-annual variability of separation distances at two sites with different meteorological conditions, one in Brazil and the other in Austria. A 5-year dataset of hourly meteorological observations was used for each site. Two odour impact criteria set in current regulations were selected to explore their effect on the separation distances. The coefficient of variation was used as a statistical measure to characterise the amount of annual variation. Overall, for all scenarios, the separation distances had a low degree of inter-annual variability (mean coefficient of variation values from 8% to 21%). Reasonable agreements from year to year were therefore observed at the two sites under investigation, showing that one year of meteorological data is a good compromise to achieve reliable accuracy. This finding can provide a more cost-effective solution to calculate separation distances in the vicinity of odour sources.
近年来,由于接触环境异味,人们越来越关注其对公众健康和福祉的潜在影响。可以使用扩散模型来计算散发异味的源与居民区之间的隔离距离,以此保护居民区免受异味困扰。本研究旨在探讨使用一年的气象输入数据来计算可靠的、随方向变化的隔离距离的适用性。因此,我们评估和量化了两个具有不同气象条件的地点的隔离距离的年际变化,一个在巴西,另一个在奥地利。每个地点都使用了 5 年的每小时气象观测数据集。选择了现行法规中规定的两个异味影响标准来探索它们对隔离距离的影响。变异系数被用作描述年度变化量的统计度量。总的来说,对于所有情况,隔离距离的年际变化程度较低(平均值的变异系数值在 8%至 21%之间)。因此,在所研究的两个地点,各年份之间存在合理的一致性,表明一年的气象数据是实现可靠精度的良好折衷方案。这一发现为计算异味源附近的隔离距离提供了一种更具成本效益的解决方案。