Sampling points number and location optimization of particulate matter concentration monitoring in a large naturally ventilated dairy barn

被引：0
|
作者：
Li Y. [1 ,2 ]
Fang Z. [1 ]
Lu Y. [1 ,2 ]
Liang C. [1 ,2 ,3 ]
Shi Z. [1 ,2 ,3 ]
Wang C. [1 ,2 ,3 ]
机构：
[1] College of Water Resources and Civil Engineering, China Agricultural University, Beijing
[2] Key Laboratory of Agricultural Engineering in Structure and Environment, Ministry of Agriculture and Rural Affairs, Beijing
[3] Beijing Engineering Research Center on Animal Healthy Environment, Beijing
来源：
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2023年 / 39卷 / 09期
关键词：
clustering; concentration; monitoring; naturally ventilated dairy barn; optimization; particulate matter; ventilation;
D O I：
10.11975/j.issn.1002-6819.202302038
中图分类号：
学科分类号：
摘要：
Particulate matter (PM) concentration can be real-time monitored to assess the environmental risks and make emission reduction measures in dairy barns. However, a great challenge is remained on arranging as few sampling points as possible to accurately monitor the PM concentration in an intensive barn, particularly with the rapid development of large dairy barns in China. This study aims to design an appropriate monitoring layout with the optimal PM sampling number and location. An online monitoring system was built to continuously detect the PM concentration inside a naturally ventilated dairy barn using the Internet of Things (IoT) and sensing technologies. A total of 17 sampling points were set inside three relatively independent sections of the investigated barn. The total suspended particle (TSP) and PM2.5 concentrations were monitored in real time for the six months during the field test. The uniformity of PM concentration was evaluated on the spatial distribution of PM concentration among the three sections and the difference in sampling heights. The systematical clustering and error analysis were also performed on the sampling of PM concentration. The optimal sampling was determined to compare the measurement with the six regular ones under three environmental controls (namely, EC1: Fans and spraying, EC2: Fans, EC3: No fans and no spraying). The average PM concentration from the 17 sampling points was treated as the true value during data analysis. Results showed that no significant difference was found for the TSP and PM2.5 concentration among the three measuring sections of the barn (P>0.05). TSP concentration sampled at the height of 9.0 m was significantly lower than that at the 1.5 and 2.5 m heights (P<0.05). There was no statistical difference in the PM2.5 concentration among different sampling heights (P>0.05). The concentrations of TSP and PM2.5 sampled at the height of 2.5 m were uniformly distributed among three sections of the barn. The sampling point setting down the ridge opening (approximately 9.0 m above the floor surface) was necessary for the TSP concentration monitoring. In TSP and PM2.5 concentrations, the sum of absolute errors between the true values and the optimized sampling under three ECs were 6.4%-22.6% and 4.7%-14.2%, respectively, indicating all smaller than those of six regular monitoring (P<0.05). Generally, the number of PM sampling points was appropriately reduced to consider the monitoring costs and practical operability. The final PM monitoring was determined with the optimized sampling number and location in a naturally ventilated dairy barn. Six PM sampling points were set inside a dairy barn: one sampling point 1.0−2.0 m down the ridge openings in the central of the barn, two sampling points at a 2.5 m height above the cubicles, and three sampling points distributed at milking alley, feed delivery alley and manure alley at a 2.5 m height, respectively. Among them, the three sampling points down the ridge opening and above the cubicles should be diagonally arranged along the barn. The final PM sampling can be expected to achieve both the accuracy and economy of PM real-time monitoring for a naturally ventilated dairy barn. © 2023 Chinese Society of Agricultural Engineering. All rights reserved.
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页码：201 / 209
页数：8
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