Next Article in Journal
Cultivation of Black Soldier Fly (Hermetia illucens) Larvae for the Valorization of Spent Coffee Ground: A Systematic Review and Bibliometric Study
Previous Article in Journal
Impact of Heat Stress on the In-Line Registered Milk Fat-to-Protein Ratio and Metabolic Profile in Dairy Cows
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 14
Issue 2
10.3390/agriculture14020204
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Managemental Impacts on Particulate Matter Emission in Tunnel-Ventilated Broiler Houses

by
Hyo-Jae Seo
,
Il-Hwan Seo
* and
Byung-Wook Oh
Department of Rural Construction Engineering, College of Agriculture & Life Sciences, Jeonbuk National University, 567, Baekje-daero, Jeonju-si 54896, Republic of Korea
*
Author to whom correspondence should be addressed.
Agriculture 2024, 14(2), 204; https://doi.org/10.3390/agriculture14020204
Submission received: 18 September 2023 / Revised: 18 December 2023 / Accepted: 19 January 2024 / Published: 27 January 2024
(This article belongs to the Section Farm Animal Production)
Browse Figures
Review Reports Versions Notes

Abstract

:
In livestock houses, particulate matter (PM) is a critical factor not only for disease and odor spread but also for the work environment. In particular, workers are exposed to high concentrations of organic particulate matter and harmful gases while performing their tasks, and, as they age, they become more vulnerable to respiratory diseases. This study analyzed the PM concentrations in commercial broiler houses, focusing on the differences in ventilation rates according to the season and the type of work, categorized into a static work period (SWP) and dynamic work period (DWP). In the regional monitoring using gravimetric methods, the average PM concentrations were found to be within acceptable limits, with TSP at 1042 µg/m3, PM-10 at 718 µg/m3, and PM-2.5 at 137 µg/m3. These values did not exceed the recommended exposure limits for inhalable dust at 2400 µg/m3 and respirable dust at 160 µg/m3 in chicken farmers. However, in the personal monitoring using a real-time aerosol spectrometer, it was revealed that the aerosol concentrations during DWP exceeded the standards by up to 214%. Specifically, during DWP, the concentrations were 1.74 times higher for TSP, 1.40 times higher for PM-10, and 1.22 times higher for PM-2.5 compared to SWP. It was observed that during the movement of workers, the physical generation of particles around 10 µm, such as feed and bedding, occurred due to the movement of chickens, which influenced the aerosol concentration.

1. Introduction

Korea has distinct seasons, with significant seasonal variations in external environmental conditions. As the scale of livestock farming increases, closed forced ventilation systems are used to adapt to the widely fluctuating external environment and create suitable breeding conditions [1,2,3]. In closed livestock houses with a high breeding density, workers are exposed to particulate matter (PM), including organic dust and harmful gases, during agricultural works. Workers in broiler houses are consistently exposed to PM due to frequent barn management compared to other livestock species [4,5]. The livestock PM contains various bacteria, molds, and harmful gases, such as ammonia, hydrogen sulfide, methane, acetaldehyde, formaldehyde, methylamine, and carbon monoxide [6,7,8,9]. The aging of agricultural workers raises serious concerns about the health issues resulting from the inhalation of PM, which can lead to respiratory and immune system disorders, as well as conditions such as asthma [10,11,12,13,14,15,16]. Endotoxin-containing PM with a diameter of 10 µm or less can have a significant impact, not only on livestock activity and productivity but also on the health of workers [17,18,19,20,21,22,23,24,25,26].
To reduce the generation of PM and improve the working environment inside broiler houses, it is crucial to assess the status and characteristics of PM within the facility through field monitoring. Generally, active sampling, which involves collecting air samples using an air intake device and analyzing them, is used for the monitoring of particulate matter. Research on the field monitoring of aerosols in livestock facilities has predominantly utilized gravimetric methods, which involve capturing airborne particulate matter in filters to measure the PM concentrations in representative areas inside the barn [20,23,27,28,29,30]. For real-time monitoring in the air, the optical scattering method has been recently used, measuring scattered light on suspended particulate matter to determine the concentration of particulate matter [31,32]. A previous analysis of particulate matter showed that as the activity of chickens increased, the concentration of PM inside the poultry house also increased [33]. Furthermore, the extended use of litter material leads to the accumulation and drying of excrement, further elevating dust levels [28,34,35]. Particulate matter generation from the floor varies with the season and the age of the chicken, with higher concentrations observed during the winter when maintaining minimal ventilation rates [36,37,38]. An analysis of the fine dust generated within the broiler house using a scanning electron microscope (SEM) revealed that feathers, feces, bedding material, and feed particles were the primary sources of dust [27,37].
However, research on the human occupational environment, specifically analyzing PM concentrations through worker-centered monitoring, has been quite rare. At present, even with automated work environments, workers still need to continuously perform daily tasks inside the livestock houses. Workers engage in various activities, such as feeding, harvesting, the culling of sick or unproductive chickens, the management of feeding and watering systems, facility maintenance, and more. Depending on the type of task, workers may be exposed to different types and concentrations of particulate matter. Therefore, for real-time analysis based on the type of task and workflow, it is crucial to utilize real-time active samplers to analyze the concentration and characteristics of particulate matter exposure based on worker-centered monitoring.
The purpose of this study was to analyze the concentration of particulate matter (PM) to which workers are exposed, depending on the type of work performed inside a tunnel-ventilated broiler house. Regional and personal monitoring were conducted in representative tunnel-ventilated broiler houses in Korea. Regional monitoring was performed using fixed air samplers and filters, employing the gravimetric method to analyze the PM concentration at different locations within the broiler house. For personal monitoring, individuals wore personal monitoring equipment that utilized light scattering devices to measure the PM concentration at the breathing height in real time as they moved and worked. Through video analysis, we aimed at distinguishing working characteristics and gaining insights into the characteristics of worker-exposed aerosols within the broiler house. Video analysis was conducted during the personal monitoring to differentiate the types of work and for a comparative analysis with real-time data.

2. Materials and Methods

2.1. Experimental Farms

The target experimental farms involved in the experiment consisted of five commercial broiler houses representatively used in Korea, utilizing forced tunnel ventilation systems (Table 1). The five broiler houses selected for the experiment had an average capacity of 25,000 chickens each, with a similar stocking density of approximately 0.053 m2/head (Table 2). These farms utilized wood shavings as bedding material and operated automatic feeding and watering systems. All the experimental farms, while varying slightly in size, utilized tunnel and negative-pressure forced ventilation systems for air exchange. The ventilation systems regulated the ventilation rate by adjusting the output of 50 ventilation fans with 26,200 cubic meters per hour (CMH) (Euroemme EM50, Munters Inc., Kista, Sweden) installed on one end wall based on the environmental temperature. Open inlets were installed on the opposite side to allow fresh external air to enter in a negative-pressure manner. The vaccination and biosecurity levels were consistent across all farms, which were considered excellent for chickens, controlled by a large distribution company. They followed an all-in, all-out procedure, where, after the broilers were shipped out, thorough cleaning was conducted and all litter was replaced. To ensure the most consistent environmental conditions as possible, monitoring was conducted when the broilers were approximately four weeks old across all farms.

2.2. Aerosol Collection and Measurement

The spatial aerosol concentration distribution within the broiler houses was measured using passive samplers, while real-time active samplers were employed to measure the working environment along the workers’ routes (Figure 1a). For the spatial concentration analysis, total suspended particulate (TSP), particulate matter under 10 µm (PM-10), and particulate matter under 2.5 µm (PM-2.5) were measured through passive sampling. TSP was measured by fixing a polytetrafluoroethylene (PTFE) filter (SKC Inc., Eighty Four, PA, USA, 2.0 μm, 37 mm) into a three-stage cassette, which was connected to a compact air sampler (AirChek TOUCH, SKC. Inc., Eighty Four, PA, USA) with an airflow rate of 2 L/min. PM-10 and PM-2.5 were measured by connecting PTFE filters to PEM impactors (Personal Environmental Monitor, SKC. Inc., Eighty Four, PA, USA), capable of capturing aerosols below 2.5 µm and 10 µm, respectively, and using a compact air sampler with an airflow rate of 4 L/min. For the analysis of the aerosol concentrations to which workers were exposed, an active sampling method was employed, which allowed real-time monitoring along the workers’ routes, including size-segregated monitoring. To understand the real-time aerosol concentration and size distribution, an aerosol spectrometer (11-D, Grimm Inc., Hamburg, Germany) was utilized, measuring aerosol concentrations divided into 31 size bins ranging from 0.253 µm to 35.15 µm at 6-s intervals (Figure 1b).
The filters used to capture particulate matter were adequately dried for over 48 h in a constant-temperature and -humidity chamber (KA33-73, Korea Ace Science Inc., Seoul, Korea) before and after sampling. The dried filters were then weighed three times each using a microbalance (BM-22, AND Weighing Inc., Tokyo, Japan) with sensitivity of 0.001 mg, and the average value of these measurements was determined as the aerosol’s weight. Blank filters, which were filters not used for any air sampling, were also prepared to correct the results. To calculate the aerosol concentration, Equation (1) was used, taking into account the weight difference of the filters before and after monitoring, as well as the error in filter weight due to sample collection, transportation, and pre-processing steps, while considering the weight of the blank filters.
P M = [ W S p − W S i − ( W B p − W B i ) ] V a
V a = Q × 293 293 + T × P 760   mmHg × t
Here, in the provided equations, W S p represents the weight of the filter after sampling (µg). W S i represents the weight of the filter before sampling (µg). W B p represents the weight of the blank filter after sampling (µg). W B i represents the weight of the blank filter before sampling (µg). V a signifies the total volume of the sample collection (m3). The flow rate (Q) is corrected to a standard temperature and pressure (0 °C, 1 atm) and is calculated as shown in Equation (2). In this equation, Q represents the flow rate measured by the standard flow meter. T and P represent the temperature (°C) and pressure (atm), respectively. t denotes the total sampling time (s). These equations were used to calculate and adjust the aerosol concentration based on various measurements and corrections.

2.3. Experimental Procedure

2.3.1. Regional PM Monitoring

To analyze the spatial PM concentration in the broiler house with a forced ventilation system, total suspended particulate (TSP), PM-10, and PM-2.5 were measured (Figure 1). The broiler house was divided into three sections: the inlet area near the entrance, the middle area, and the outlet area near the exhaust fans. Monitoring devices were installed in these areas, as shown in Figure 2. During the experiment conducted in the summer season, negative pressure was created by operating exhaust fans on one end wall, allowing fresh air to enter through the opposite side inlets. In all experimental farms, real-time PM sampling was conducted for a total of 6 h, primarily from 10 AM to 4 PM, covering the general working hours. The duration of fine dust measurements was set at 6 h, considering the time-weighted average exposure limit specified in the Occupational Safety and Health Act.
The direction of PM capture and the flow rate near the sampling device can significantly impact the concentration results. When dealing with fine particles, their size and weight can influence whether they settle due to gravity and humidity or continue to move primarily along the airflow. The PM sampling direction was oriented downward to avoid dust deposition, as shown in Figure 3. To analyze the PM concentrations that affected workers, the sampling inlet was positioned at a height of 1.5 m above the floor, which is the typical breathing height for workers. The air intake was placed at least 30 cm away from the structure that held the equipment. This design was implemented to prevent any interference caused by the proximity of the intake to the structure holding the fine dust sampling equipment, as close proximity can lead to the underestimation of concentrations compared to real-time analysis results. To ensure stability during the 6-h sampling period and to prevent equipment damage or tipping, the monitoring devices were securely fastened and installed while avoiding the worker’s path. Additionally, thorough disinfection and sanitation measures were implemented before installation to facilitate monitoring in the commercial broiler houses.
To analyze the physical characteristics related to the generation and dispersion of particulate matter, the collected PM filters were analyzed using scanning electron microscopy (SEM) to examine the size and shape of the PM. The filters containing trapped PM were coated with a 10-nm-thick layer of platinum–palladium. An SEM-EDX (Supra 40VP, ZEISS Inc., Oberkochen, Germany) was employed to analyze images at various resolutions.

2.3.2. Personal PM Monitoring

To analyze the concentration and characteristics of PM to which workers are exposed inside commercial broiler houses, real-time PM monitoring was conducted using an aerosol spectrometer along the working paths with tunnel ventilation systems of similar scale and operation methods. Monitoring points were strategically located within 30 cm of the workers’ noses and mouths, at a height of about 1.5 m above the floor, using Tygon tubes. Personal monitoring was performed during periods when generally repeated daily tasks were performed, between 10:00 a.m. and 4:00 p.m., such as broiler house management and maintenance. For a comparative analysis with real-time measurement data based on work types and routes, video recording equipment (Hero 9 Black, GoPro Inc., San Mateo, CA, USA) was installed near the entrance (Figure 4).
Real-time measurements of PM concentrations were taken at 6-s intervals, and, based on the results of the particle size analysis and video analysis, we differentiated between the dynamic work period (DWP), when workers were moving for management purposes, and the static work period (SWP), when they remained in a stationary position for maintenance purposes. To reduce data errors, we calculated the concentration of the remaining data, excluding the front and back 10% of data for each of the two periods, as the concentration for the given work period. The average duration of the moving period was 3.04 ± 1.63 min, while the working period lasted 2.27 ± 1.12 min. To enhance the data stability and remove outliers, we deleted the front and back 10% of data from both DWP and SWP in the 6-s interval real-time data, and then calculated the average to obtain a single dataset. Statistical analysis was conducted to ascertain whether there were significant differences in concentrations between DWP and SWP according to particle sizes. The collected data were analyzed by the SPSS ver. 22.0 program using descriptive statistics, and an independent-samples t-test was performed.

3. Results

3.1. Regional PM Monitoring

The temperature and humidity were monitored to understand the regional PM distribution both inside and outside the livestock facilities (Table 2). During the summer season, when the external temperatures exceeded 30 degrees Celsius, full ventilation was achieved. In contrast, during the transitional season of autumn, when the external temperatures were around 20 °C, approximately 5.2 °C lower than the internal temperature, the ventilation rates were reduced to less than 15% of the maximum capacity. The ventilation rates varied according to the size of the experimental commercial broiler house, with an average of 12.0 cubic meters per hour (CMH)/head during the summer, and 2.1 CMH/head during the transitional seasons.
The average PM concentrations across all experimental farms were as follows: TSP 1042 µg/m3, PM-10 718 µg/m3, and PM-2.5 137 µg/m3 (Figure 5). Analyzing the data relative to the particle size for each farm revealed that PM-10 accounted for 68.9% of the total PM concentration, while PM-2.5 accounted for 13.1%. This indicates a higher proportion of particles around 10 µm in size. This observation is attributed to mechanically generated particles from materials such as bedding (wheat straw) and feed particles, which tend to be around 10 µm in size [39]. To confirm this, particles captured on filters were analyzed using SEM, showing that the captured fine particles were around 10 µm in size and exhibited a rounded shape, originating from bedding and feed materials (Figure 6). This finding aligns with previous research suggesting that particles generated from sources like feed and bedding exhibit similar size and shape characteristics [27,40,41].
The results of regional monitoring conducted on five experimental farms with similar ventilation systems and stocking densities showed that the concentration of indoor PM decreased as the ventilation rate increased. In farms operating at a summer peak ventilation of 12.0 CMH/head, the average concentrations were found to be TSP at 244.4 µg/m3, PM-10 at 141.3 µg/m3, and PM-2.5 at 35.1 µg/m3. During the transitional seasons with ventilation rates at 2.1 CMH/head, the average concentrations increased to TSP at 2240 µg/m3, PM-10 at 1583 µg/m3, and PM-2.5 at 289 µg/m3.
Donham et al. (2000) [20] established exposure standards for chicken farmers for inhalable dust and respirable dust at 2400 µg/m3 and 160 µg/m3, respectively. Based on these standards, the regional monitoring results during periods of high ventilation were all within the specified limits. However, when the ventilation rate was reduced to 17.5% of its maximum, the PM concentration increased by 9.17 times for TSP, 11.2 times for PM-10, and 8.2 times for PM-2.5. As a result, the levels exceeded the worker exposure standards by up to 1.16 times for inhalable dust and up to 3.14 times for respirable dust. Considering that field measurements captured PM-2.5, whereas respirable dust has a size of 2.5 µm or smaller, it is reasonable to assume that the actual exposure of farm workers to respirable dust may be higher than indicated by the measurements. This suggests a potential health risk for farm workers in terms of respiratory diseases related to exposure to respirable dust. When the ventilation rates were high, PM with sizes around 10 µm was predominantly generated from the broiler house, representing 57.8% of TSP. In contrast, during periods of low ventilation, internally generated PM was not effectively expelled to the outside, and it accumulated inside, resulting in a higher relative ratio of 70.7%.

3.2. Personal PM Monitoring

During the static work period (SWP), workers were exposed to average concentrations of TSP 1733 µg/m3, PM-10 942 µg/m3, and PM-2.5 106 µg/m3. In the dynamic work period (DWP), the PM concentrations were increased for TSP by 3012 µg/m3, PM-10 by 1318 µg/m3, and PM-2.5 by 129.2 µg/m3, showing 1.74 times, 1.40 times, and 1.22 times higher concentrations, respectively, compared to SWP. The higher PM concentration during the DWP was attributed to an increase in chicken activity within the broiler house, leading to the significant generation of particles around 10 µm in size, such as feed, litter, and floor materials. As shown in Figure 7, PM-1.0, which is mainly generated by chemical reactions, showed relatively minor variations in concentration. When compared to the exposure standards of chicken farmers, inhalable dust was found to increase by an average of 1.25 times and up to 3.5 times, while respirable dust increased by an average of 1.2 times and up to 1.89 times during the DWP. This indicates that workers are exposed to higher dust concentrations during the DWP compared to during the SWP.
The analysis of PM concentrations by the particle size to which broiler farmers are exposed revealed a significant increase in PM concentrations around 10 µm during the DWP, confirming the exposure to high aerosol levels during workers’ movement (Figure 8). Under the high ventilation rates of the hot season, TSP increased by a substantial 2.46 times, and PM-10 increased by 2.13 times, during the DWP compared to the SWP. In contrast, during the relatively low-ventilation period, TSP exhibited a relatively lower increase of 1.38 times, and PM-10 increased by 1.24 times, during the DWP compared to the SWP. It was observed that the PM concentration to which workers were exposed not only increased as the operating ventilation rate of the farm decreased, but also tended to rise during dynamic work activities or movement within the farm. Therefore, when working in the broiler house, it is necessary to take measures to reduce the indoor PM concentrations based on personal protective equipment and sufficient ventilation rates, especially during entry or chronic exposure periods, even under normal circumstances.
To understand the correlation of the PM concentrations between the SWP and DWP, the combination of the average concentrations to which workers were exposed during the SWP and DWP was presented for all experimental periods based on video analysis (Figure 9). As the particle size increases, the graph’s slope becomes steeper, indicating a larger increase in concentration during the DWP. Based on the experimental results, the aerosol concentrations to which workers were exposed during the DWP were found to be 1.76 times higher for particles larger than 10 µm, 1.29 times higher for particles ranging from 2.5 to 10 µm, and 1.11 times higher for particles smaller than 2.5 µm. Figure 9 shows the increase in concentration between the DWP and SWP for each particle size using the aerosol spectrometer. It can be observed that as the particle size increases, the increase in concentration during the DWP becomes more pronounced. These results can be utilized to apply weights when devising standards for fine dust exposure for workers in broiler farms in the future. Instead of applying a uniform standard for PM exposure, factors such as the work environment and the type of work can be considered.
To assess the statistical significance of the PM concentrations in size during the DWP and SWP, an independent-sample t-test was conducted (Table 3). The statistical analysis showed significant differences between the PM concentrations during the DWP and SWP. Specifically, during the DWP, when broiler activities increased workers’ movement, TSP and PM-10 exhibited extremely high significance levels, with p-values below 0.001 each. However, for PM-1.0, the p-value was 0.098, indicating that there was no significant difference.

4. Conclusions

The particulate matter (PM) concentrations varied depending on the working types and ventilation rates. During dynamic work periods (DWPs), where workers are moving, the concentration of PM increases compared to static work periods (SWPs), where work is performed in a stationary position. This effect is particularly noticeable at lower ventilation rates, where PM is not sufficiently expelled to the outside and accumulates indoors. Under these conditions, the concentration of TSP increases by 1.38 times and PM-10 by 1.24 times in the DWP compared to the SWP. The increasing PM mainly comprises particles around 10 µm in size, typically found in feed and floor materials, indicating a need for improvements in the work environment focused on these elements. To mitigate the impact of PM with particle sizes around 10 µm that workers are exposed to during tasks, the use of personal protective equipment and the sufficient operation of ventilation systems that can reduce physical particulate matter are recommended. The results of this study can be utilized to establish evaluation criteria for the effectiveness of personal respiratory protective equipment in reducing PM exposure during working periods. Additionally, they can be applied to develop and refine exposure standards for PM concentrations for different types of work and ventilation rates by applying them as weighting factors.

Author Contributions

H.-J.S. and B.-W.O. generally conducted the field monitoring, experimental analysis, methodology, and data interpretation. H.-J.S. undertook the writing, conceptualization, and interpretation of the data. I.-H.S. designed and supervised the experiment. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) and the Korea Smart Farm R&D Foundation (KosFarm) through the Smart Farm Innovation Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) and the Ministry of Science and ICT (MSIT), Rural Development Administration (RDA), 421019-04.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kleven, S. Mycoplasmas in the etiology of multifactorial respiratory disease. Poult. Sci. 1998, 77, 1146–1149. [Google Scholar] [CrossRef] [PubMed]
  2. Seo, I.-H.; Lee, I.-B.; Moon, O.-K.; Kim, H.-T.; Hwang, H.-S.; Hong, S.-W.; Bitog, J.; Yoo, J.-I.; Kwon, K.-S.; Kim, Y.-H. Improvement of the ventilation system of a naturally ventilated broiler house in the cold season using computational simulations. Biosyst. Eng. 2009, 104, 106–117. [Google Scholar] [CrossRef]
  3. Wathes, C. Aerial emissions from poultry production. World’s Poult. Sci. J. 1998, 54, 241–251. [Google Scholar] [CrossRef]
  4. Kim, K.-R.; Kim, H.; Lee, K.; Chae, H.-S. Exposure to dust and organic gas during chicken entrance and shipment tasks in poultry farms. J. Korean Soc. Occup. Environ. Hyg. 2014, 24, 471–477. [Google Scholar] [CrossRef]
  5. Viegas, S.; Faísca, V.; Dias, H.; Clérigo, A.; Carolino, E.; Viegas, C. Occupational exposure to poultry dust and effects on the respiratory system in workers. J. Toxicol. Environ. Health Part A 2013, 76, 230–239. [Google Scholar] [CrossRef] [PubMed]
  6. Bottcher, R.W. An environmental nuisance: Odor concentrated and transported by dust. Chem. Senses 2001, 26, 327–331. [Google Scholar] [CrossRef] [PubMed]
  7. Donham, K.; Haglind, P.; Peterson, Y.; Rylander, R.; Belin, L. Environmental and health studies of farm workers in Swedish swine confinement buildings. Occup. Environ. Med. 1989, 46, 31–37. [Google Scholar] [CrossRef]
  8. Olson, D.K.; Bark, S.M. Health hazards affecting the animal confinement farm worker. AAOHN J. 1996, 44, 198–204. [Google Scholar] [CrossRef]
  9. Wang, K.; Shen, D.; Dai, P.; Li, C. Particulate matter in poultry house on poultry respiratory disease: A systematic review. Poult. Sci. 2023, 102, 102556. [Google Scholar] [CrossRef]
  10. Castañeda, A.R.; Bein, K.J.; Smiley-Jewell, S.; Pinkerton, K.E. Fine particulate matter (PM2.5) enhances allergic sensitization in BALB/c mice. J. Toxicol. Environ. Health Part A 2017, 80, 197–207. [Google Scholar] [CrossRef]
  11. Moran, R.E.; Bennett, D.H.; Garcia, J.; Schenker, M.B. Occupational exposure to particulate matter from three agricultural crops in California. Int. J. Hyg. Environ. Health 2014, 217, 226–230. [Google Scholar] [CrossRef]
  12. Poole, J.A.; Romberger, D.J.; Wyatt, T.A.; Staab, E.; VanDeGraaff, J.; Thiele, G.M.; Dusad, A.; Klassen, L.W.; Duryee, M.J.; Mikuls, T.R. Age impacts pulmonary inflammation and systemic bone response to inhaled organic dust exposure. J. Toxicol. Environ. Health Part A 2015, 78, 1201–1216. [Google Scholar] [CrossRef]
  13. Yang, W.; Guo, M.; Liu, G.; Yu, G.; Wang, P.; Wang, H.; Chai, T. Detection and analysis of fine particulate matter and microbial aerosol in chicken houses in Shandong Province, China. Poult. Sci. 2018, 97, 995–1005. [Google Scholar] [CrossRef]
  14. Yasmeen, R.; Ali, Z.; Tyrrel, S.; Nasir, Z.A. Assessment of respiratory problems in workers associated with intensive poultry facilities in Pakistan. Saf. Health Work 2020, 11, 118–124. [Google Scholar] [CrossRef]
  15. Younis, F.; Salem, E.; Salem, E. Respiratory health disorders associated with occupational exposure to bioaerosols among workers in poultry breeding farms. Environ. Sci. Pollut. Res. 2020, 27, 19869–19876. [Google Scholar] [CrossRef] [PubMed]
  16. Zhou, Y.; Xu, B.; Wang, L.; Zhang, C.; Li, S. Fine Particulate Matter Perturbs the Pulmonary Microbiota in Broiler Chickens. Animals 2023, 13, 2862. [Google Scholar] [CrossRef] [PubMed]
  17. Adell, E.; Calvet, S.; Pérez-Bonilla, A.; Jiménez-Belenguer, A.; García, J.; Herrera, J.; Cambra-Lopez, M. Air disinfection in laying hen houses: Effect on airborne microorganisms with focus on Mycoplasma gallisepticum. Biosyst. Eng. 2015, 129, 315–323. [Google Scholar] [CrossRef]
  18. Banhazi, T.; Seedorf, J.; Laffrique, M.; Rutley, D. Identification of the risk factors for high airborne particle concentrations in broiler buildings using statistical modelling. Biosyst. Eng. 2008, 101, 100–110. [Google Scholar] [CrossRef]
  19. Cambra López, M. Control of Particulate Matter Emissions from Poultry and Pig Houses. Ph.D. Thesis, Universitat Politècnica de València, Valencia, Spain, 2010. [Google Scholar]
  20. Donham, K.J.; Cumro, D.; Reynolds, S.J.; Merchant, J.A. Dose-response relationships between occupational aerosol exposures and cross-shift declines of lung function in poultry workers: Recommendations for exposure limits. J. Occup. Environ. Med. 2000, 42, 260–269. [Google Scholar] [CrossRef]
  21. Li, Z.; Xiong, Y.; Wang, S.; Wang, C.; Ji, B.; Liu, Y.; Liang, C.; Tong, Q. Assessing particulate matter concentration level and its limit exceedance based on year-round field measurements of different laying hen building systems. Biosyst. Eng. 2023, 226, 266–279. [Google Scholar] [CrossRef]
  22. Radon, K.; Weber, C.; Iversen, M.; Danuser, B.; Pedersen, S.; Nowak, D. Exposure assessment and lung function in pig and poultry farmers. Occup. Environ. Med. 2001, 58, 405–410. [Google Scholar] [CrossRef]
  23. Takai, H.; Pedersen, S.; Johnsen, J.O.; Metz, J.; Koerkamp, P.G.; Uenk, G.; Phillips, V.; Holden, M.; Sneath, R.; Short, J. Concentrations and emissions of airborne dust in livestock buildings in Northern Europe. J. Agric. Eng. Res. 1998, 70, 59–77. [Google Scholar] [CrossRef]
  24. Wilson, D.J.; Gabriel, E.; Leatherbarrow, A.J.; Cheesbrough, J.; Gee, S.; Bolton, E.; Fox, A.; Fearnhead, P.; Hart, C.A.; Diggle, P.J. Tracing the source of campylobacteriosis. PLoS Genet. 2008, 4, e1000203. [Google Scholar] [CrossRef]
  25. Zuskin, E.; Mustajbegovic, J.; Schachter, E.N.; Kern, J.; Rienzi, N.; Goswami, S.; Marom, Z.; Maayani, S. Respiratory function in poultry workers and pharmacologic characterization of poultry dust extract. Environ. Res. 1995, 70, 11–19. [Google Scholar] [CrossRef]
  26. dos Anjos Magri, C.; Garofallo Garcia, R.; Binotto, E.; Duarte da Silva Lima, N.; de Alencar Nääs, I.; Sgavioli, S.; de Castro Burbarelli, M.F. Occupational risk factors in health of broiler-farm workers: A systematic review. Arch. Environ. Occup. Health 2021, 76, 482–493. [Google Scholar] [CrossRef]
  27. Cambra-López, M.; Hermosilla, T.; Lai, H.T.; Montero, M.; Aarnink, A.J.; Ogink, N.W. Source identification and quantification of particulate matter emitted from livestock houses. In Proceedings of the International Symposium on Air Quality and Manure Management for Agriculture Conference Proceedings, Dallas, TX, USA, 13–16 September 2010; p. 41. [Google Scholar]
  28. Kim, K.Y. Distribution of concentration and emission of dust according to types of poultry buildings in Korea. J. Environ. Health Sci. 2017, 43, 185–193. [Google Scholar] [CrossRef]
  29. Seo, H.-J.; Oh, B.-W.; Kim, H.-C.; Sin, S.-J.; Seo, I.-H. Concentrations of particulate matter exposed to farm workers in the broiler houses. J. Korean Soc. Agric. Eng. 2020, 62, 27–37. [Google Scholar] [CrossRef]
  30. Shin, S.-J.; Song, E.-S.; Kim, J.-W.; Lee, J.-H.; Gautam, R.; Kim, H.-J.; Kim, Y.-G.; Cho, A.-R.; Yang, S.-J.; Acharya, M. Major environmental characteristics of swine husbandry that affect exposure to dust and airborne endotoxins. J. Toxicol. Environ. Health Part A 2019, 82, 233–243. [Google Scholar] [CrossRef]
  31. Lee, B.-J.; Park, S.-S. Evaluation of PM10 and PM2.5 concentrations from online light scattering dust monitors using gravimetric and beta-ray absorption methods. J. Korean Soc. Atmos. Environ. 2019, 35, 357–369. [Google Scholar] [CrossRef]
  32. Choi, S.-I.; An, J.-A.; Jo, Y.-M. Review of analysis principle of fine dust. Korean Ind. Chem. News 2018, 21, 16–23. [Google Scholar]
  33. Yasmeen, R.; Ali, Z.; Tyrrel, S.; Nasir, Z.A. Estimation of particulate matter and gaseous concentrations using low-cost sensors from broiler houses. Environ. Monit. Assess. 2019, 191, 470. [Google Scholar] [CrossRef]
  34. Fernández, A.P.; Demmers, T.G.; Tong, Q.; Youssef, A.; Norton, T.; Vranken, E.; Berckmans, D. Real-time modelling of indoor particulate matter concentration in poultry houses using broiler activity and ventilation rate. Biosyst. Eng. 2019, 187, 214–225. [Google Scholar] [CrossRef]
  35. Kwon, K.S.; Jo, Y.S.; Lee, I.B.; Ha, T.H.; Hong, S.W. Measurement of dust concentration in a mechanically ventilated broiler house and analysis of dust generation from ground beds. J. Korean Soc. Agric. Eng. 2014, 56, 31–43. [Google Scholar] [CrossRef]
  36. Choi, H.; Yeon, G.; Song, J.; Kang, H.; Kwon, D.; Yoo, Y.; Barroga, A.; Yang, C.; Chun, S.; Kim, Y. Seasonal dust concentration and characteristics of windowless broiler building. J. Anim. Environ. Sci. 2005, 11, 197–206. [Google Scholar]
  37. Dai, P.; Shen, D.; Tang, Q.; Huang, K.; Li, C. PM2.5 from a broiler breeding production system: The characteristics and microbial community analysis. Environ. Pollut. 2020, 256, 113368. [Google Scholar] [CrossRef]
  38. Kabelitz, T.; Biniasch, O.; Ammon, C.; Nübel, U.; Thiel, N.; Janke, D.; Swaminathan, S.; Funk, R.; Münch, S.; Rösler, U. Particulate matter emissions during field application of poultry manure-The influence of moisture content and treatment. Sci. Total Environ. 2021, 780, 146652. [Google Scholar] [CrossRef] [PubMed]
  39. Shen, D.; Wu, S.; Dai, P.; Li, Y.; Li, C. Distribution of particulate matter and ammonia and physicochemical properties of fine particulate matter in a layer house. Poult. Sci. 2018, 97, 4137–4149. [Google Scholar] [CrossRef]
  40. Heber, A.; Stroik, M.; Faubion, J.; Willard, L. Size distribution and identification of aerial dust particles in swine finishing buildings. Trans. ASAE 1988, 31, 882–887. [Google Scholar] [CrossRef]
  41. Pearson, C.; Sharples, T. Airborne dust concentrations in livestock buildings and the effect of feed. J. Agric. Eng. Res. 1995, 60, 145–154. [Google Scholar] [CrossRef]
Agriculture 14 00204 g001
Figure 1. Particulate matter spatial distribution and working environment monitoring equipment for broiler farms. (a) Spatial distribution monitoring equipment (air sampler, PEM monitor); (b) working environment monitoring equipment (aerosol spectrometer).
Figure 1. Particulate matter spatial distribution and working environment monitoring equipment for broiler farms. (a) Spatial distribution monitoring equipment (air sampler, PEM monitor); (b) working environment monitoring equipment (aerosol spectrometer).
Agriculture 14 00204 g001
Agriculture 14 00204 g002
Figure 2. Schematic diagram for regional PM distribution monitoring and personal PM monitoring in broiler houses.
Figure 2. Schematic diagram for regional PM distribution monitoring and personal PM monitoring in broiler houses.
Agriculture 14 00204 g002
Agriculture 14 00204 g003
Figure 3. Configuration of local dust concentration monitoring equipment installed in the experimental broiler house.
Figure 3. Configuration of local dust concentration monitoring equipment installed in the experimental broiler house.
Agriculture 14 00204 g003
Agriculture 14 00204 g004
Figure 4. Real-time monitoring through working route of working environment and aerosol spectrometer measurements. (a) Dynamic work period (DWP); (b) static work period (SWP); (c) personal monitoring device with aerosol spectrometer; (d) video collection.
Figure 4. Real-time monitoring through working route of working environment and aerosol spectrometer measurements. (a) Dynamic work period (DWP); (b) static work period (SWP); (c) personal monitoring device with aerosol spectrometer; (d) video collection.
Agriculture 14 00204 g004
Agriculture 14 00204 g005
Figure 5. PM concentration monitored by the air sampler with the filters in the experimental broiler houses.
Figure 5. PM concentration monitored by the air sampler with the filters in the experimental broiler houses.
Agriculture 14 00204 g005
Agriculture 14 00204 g006
Figure 6. Image of the PM particle in experimental broiler house taken from SEM analysis.
Figure 6. Image of the PM particle in experimental broiler house taken from SEM analysis.
Agriculture 14 00204 g006
Agriculture 14 00204 g007
Figure 7. Real-time dust concentration according to working route by particle size; blue and red dotted lines represent inhalable and respirable exposure standards for chicken farmers, respectively. (a) PM-1.0 concentration; (b) PM-2.5 concentration; (c) PM-10 concentration; (d) TSP concentration.
Figure 7. Real-time dust concentration according to working route by particle size; blue and red dotted lines represent inhalable and respirable exposure standards for chicken farmers, respectively. (a) PM-1.0 concentration; (b) PM-2.5 concentration; (c) PM-10 concentration; (d) TSP concentration.
Agriculture 14 00204 g007
Agriculture 14 00204 g008
Figure 8. Real-time PM concentration according to working route and particle size. (a) Summer season; (b) autumn season.
Figure 8. Real-time PM concentration according to working route and particle size. (a) Summer season; (b) autumn season.
Agriculture 14 00204 g008
Agriculture 14 00204 g009
Figure 9. Correlation analysis of dust concentrations by particle size according to working route and trend curve of PM by working route. (a) PM concentration over 10 µm; (b) PM concentration over 2.5–10 µm; (c) PM concentration below 2.5 µm; (d) trend curve of PM concentration.
Figure 9. Correlation analysis of dust concentrations by particle size according to working route and trend curve of PM by working route. (a) PM concentration over 10 µm; (b) PM concentration over 2.5–10 µm; (c) PM concentration below 2.5 µm; (d) trend curve of PM concentration.
Agriculture 14 00204 g009
Table 1. Internal and external air temperature and humidity in the experimental broiler houses.
Table 1. Internal and external air temperature and humidity in the experimental broiler houses.
Farm
(Location, City)		SeasonDateInternalExternal Weather Conditions
Temp. (°C)RH. (%)Temp. (°C)RH. (%)TSP (µg/m3)PM-10 (µg/m3)
A (Jin-an)summer9 September 201926.085.024.490.214.69.4
B (Young-gwang)30 July 202028.784.030.874.889.157.4
C (Young-gwang)31 July 202029.977.332.869.155.542.9
D (Ik-san)autumn28 October 201925.846.818.543.223.111.4
E (Ik-san)4 November 201924.950.221.846.725.813.3
Table 2. Ventilation system and breeding information in the experimental broiler houses.
Table 2. Ventilation system and breeding information in the experimental broiler houses.
FarmNo. of Chickens (Heads)Floor Area
(m2)		Stock Density
(m2/Head)		Ventilation System Configuration
(Activated/Overall Fans)		Ventilation Rate
(CMH/Head)		Fan Operation Rate
A90004500.05Outlet exhaust fans (4/6)11.6466%
B30,00015000.05Outlet exhaust fans (14/14)12.23100%
C34,50018800.054Outlet exhaust fans (16/16)12.15100%
D24,00016000.067Outlet exhaust fans (2/16)2.1813%
E26,00012000.046Outlet exhaust fans (2/13)2.0215%
Table 3. Comparison of PM concentration according to each size of particulate matter (Unit: µg/m3).
Table 3. Comparison of PM concentration according to each size of particulate matter (Unit: µg/m3).
CategoriesTSPPM-10
MeanS.D.p-valueMeanS.D.p-value
DWP295716030.000117910640.001
SWP17721167839854
CategoriesPM-2.5PM-1.0
meanS.D.p-valuemeanS.D.p-value
DWP110.9104.40.01726.129.80.098
SWP87.395.723.426.4
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Seo, H.-J.; Seo, I.-H.; Oh, B.-W. Managemental Impacts on Particulate Matter Emission in Tunnel-Ventilated Broiler Houses. Agriculture 2024, 14, 204. https://doi.org/10.3390/agriculture14020204

AMA Style

Seo H-J, Seo I-H, Oh B-W. Managemental Impacts on Particulate Matter Emission in Tunnel-Ventilated Broiler Houses. Agriculture. 2024; 14(2):204. https://doi.org/10.3390/agriculture14020204

Chicago/Turabian Style

Seo, Hyo-Jae, Il-Hwan Seo, and Byung-Wook Oh. 2024. "Managemental Impacts on Particulate Matter Emission in Tunnel-Ventilated Broiler Houses" Agriculture 14, no. 2: 204. https://doi.org/10.3390/agriculture14020204

APA Style

Seo, H.-J., Seo, I.-H., & Oh, B.-W. (2024). Managemental Impacts on Particulate Matter Emission in Tunnel-Ventilated Broiler Houses. Agriculture, 14(2), 204. https://doi.org/10.3390/agriculture14020204

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop