大型自然通风奶牛舍空气颗粒物浓度监测方法中采样间隔优化
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S815.9

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国家自然科学基金项目(31972614);国家现代农业(奶牛)产业技术体系(CARS-36)。


Optimization of sampling intervals for particulate matter concentration monitoring in a large naturally ventilated dairy barn
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    摘要:

    规模化奶牛养殖产生的颗粒物会对人员和奶牛的呼吸道以及周边环境健康产生不利影响。对于奶牛舍空气颗粒物的实时连续监测,除了监测点数量和位置外,监测设备的采样间隔同样会影响监测结果的准确性。为确定合理的采样间隔,该研究采用环境物联网技术在大型自然通风奶牛舍内共计布置了17个采样点,对秋季至冬季舍内的总悬浮颗粒物(total suspended particulate, TSP)和细颗粒物(PM2.5)浓度进行连续6个月的实时监测,计算舍内17个采样点的平均浓度(视为“真值”)。基于误差分析法,分别计算了30 min和1、2、3、6、12 h采样间隔下秋季和冬季的颗粒物浓度日均值,以及10、15、20、30 min和1 h采样间隔下白天、夜间与生产管理操作期间的颗粒物浓度小时均值及其与真值的相对误差(Er),统计了Er在5%与10%范围内的占比情况,以66.7%作为可接受标准,确定了秋冬季节颗粒物浓度日均值和小时均值的最大可接受采样间隔。结果显示,在5%的相对误差允许范围内,秋冬季节TSP日均值的最大可接受采样间隔为2 h(秋季)和1 h(冬季),PM2.5为3 h(秋季)和1 h(冬季);白天TSP小时均值的最大可接受采样间隔为20 min(秋季)和15 min(冬季),夜间TSP为30 min(秋季)和15 min(冬季),秋冬季节白天和夜间的PM2.5的最大采样间隔均为30 min;当TSP和PM2.5的最大可接受采样间隔为10 min和20 min时,测量数据可以较好地反映秋冬季节生产管理操作对舍内颗粒物浓度的影响。研究对于畜禽舍颗粒物监测中传感器采样频率的设定具有重要意义。

    Abstract:

    Generation and emission of particulate matter (PM) from dairy farming have a potential effect on the health and welfare of the animals, farm workers and even the neighbors. Monitoring accuracy of the PM concentration depends much on the number and location of sampling points as well as the sampling interval (SI). Most PM studies used intermittent sampling methods, such as sampling the concentration for a couple of days in a season or in several seasons, which were unable to accurately reflect the actual PM concentration level and variation inside the intensive dairy building. To determine the reasonable SI of PM sensors, this study developed an Internet of Things (IoT)-based monitoring system for PM concentration in an intensive naturally ventilated dairy barn, in which a 17-point continuous concentration monitoring of PM less than 2.5 μm in aerodynamic diameter (PM2.5) and the total suspended particulate (TSP) was carried out in autumn and winter, and its 5-minute mean values were regarded as relatively true values (RTV). Using error analysis, the daily averaged PM concentration with 30 min and 1, 2, 3, 6, 12 h SI in autumn and winter and the hourly mean PM concentration with 10, 15, 20, 30 min and 1 h SI during the day (05:00-23:00), night (23:00-05:00) and daily management periods (05:00-07:00, 13:00-15:00, 21:00-23:00) were first computed, respectively; then their relative errors (Er) with RTV were counted within 5% and 10% range; and finally, the maximum accepted SI for daily and hourly mean PM concentration measurements were determined based on acceptance criteria in bioanalytical method (66.7%).The results showed that within 5%, when the SI for TSP concentration were set within 2 h (in autumn) and 1h (in winter), and they were within 3 h (in autumn) and 1 h (in winter) for PM2.5 measuring, respectively. It can accurately obtain the daily average PM concentration of the naturally ventilated dairy barn in autumn and winter. When the SI were at 20 min (in autumn) and 15 min (in winter) in daytime, and 30 min (in autumn) and 15 min (in winter) in nighttime for the TSP measurements, and 30 min for PM2.5 daytime and nighttime (in autumn and winter), an accurate monitoring could be obtained on hourly mean PM concentration and its fluctuations. When the sampling interval for TSP was 10 min, and the interval for PM2.5 was on 20 min in autumn and winter, respectively, the measurement data can reflect the impact of daily management on the PM concentration inside the barn. The findings of this study can be applied as a standardized procedure to continuously track the PM concentration in an intensive naturally ventilated dairy barn.

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鲁煜建,方志伟,李永振,梁超,施正香,王朝元.大型自然通风奶牛舍空气颗粒物浓度监测方法中采样间隔优化[J].农业工程学报,2023,39(9):210-216. DOI:10.11975/j. issn.1002-6819.202302037

LU Yujian, FANG Zhiwei, LI Yongzhen, LIANG Chao, SHI Zhengxiang, WANG Chaoyuan. Optimization of sampling intervals for particulate matter concentration monitoring in a large naturally ventilated dairy barn[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2023,39(9):210-216. DOI:10.11975/j. issn.1002-6819.202302037

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  • 收稿日期:2023-02-09
  • 最后修改日期:2023-04-20
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  • 在线发布日期: 2023-05-26
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