摘要
Between 1997 and 1999 a comprehensive survey of airborne pollutant concentrations within, and emissions from, 160 Australian piggery buildings was undertaken. The primary aim of the study was to model the concentrations and emissions of different airborne pollutants and thus identify potential reduction techniques. The main factors identified as significantly influencing airborne pollutant concentrations were building type, pen hygiene, pig flow management, seasons, building volume, ventilation airflow rate, air temperature, relative humidity, and farm size (as expressed by number of sows on site). These effects were included in comprehensive statistical models to explain the variation in measured concentrations and emission rates. The models developed were validated and fine-tuned using the “leave-one-out” cross-validation technique. This article details the validation technique used that was aimed to maximise the value of available experimental data and further improves the practicality of the models developed. The main result of the study was the development of an improved model. The study results, and the resulting prediction models, should help improve air quality in piggery buildings by providing decision makers with an awareness of the environmental conditions inside and outside of piggery buildings. In turn, that should lead to improvements in the health and welfare of pigs and piggery staff and the sustainability of the piggery operations.
摘要译文
1997年至1999年间在空气中的污染物浓度和排放的综合调查，从160猪舍澳大利亚建筑被承担。这项研究的主要目的是模拟的浓度和不同的空气污染物的排放，从而确定潜在的还原技术。认定为显著影响空气污染物浓度建筑类型，笔卫生，猪流管理，季节，建筑容积，通风气流速度的主要因素，空气温度，相对湿度，和农场规模（所表达的母猪在现场数）。这些影响被纳入综合统计模型来解释测量浓度和排放速率的变化。开发的模型进行了验证，并使用了“留一出”交叉验证技术微调。本文将详细介绍使用的验证技术，旨在最大限度地利用现有的实验数据的价值，并进一步提高开发的模型的实用性。该项研究的主要结果是改进模型的发展。这项研究的结果，将得到的预测模型，应有助于决策者提供的内部环境条件的认识和猪舍建筑外改善猪舍建筑空气质量。反过来，这应导致改善健康和猪和猪场工作人员福利和猪舍运营的可持续性。
T.M. Banhazi; D.L. Rutley; W.S. Pitchford. Validation and fine-tuning of a predictive model for air quality in livestock buildings[J]. Biosystems Engineering, 2010,105(3): 395–401