Measuring dust levelin a mechanically ventilated piglet ... · concentration inside the...

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Measuring dust level in a mechanically ventilated piglet house considering worker’s respiratory welfare

Kyeong-seok Kwon and In-bok Lee, Department of Rural Systems Engineering, Research In-stitute for Agriculture and Life Science, College of Agricultural and Life Sciences, Seoul Na-tional University, 599, Gwankno, Gwanku, Seoul, 151-921, Republic of Korea

Abstract

Concentration and generation of aerial dust in a confined pig house has been an emerging concern in respect of worker’s respiratory welfare and animal productivity. Dust comes from feed, hair, flake, feces, etc. inside the facility and is known to be harmful to the workers as well as to the animals. When human are constantly exposed to the specific range of dust concen-tration, workers can surfer chronic or acute respiratory symptoms and have high probability of manifesting disease such as asthma, phlegm, cough, etc. To create the proper aero-environ-mental condition considering respiratory health of farmers and animals inside livestock house, understanding on mechanism of dust generation should take precedence. In presented study, as a first step, the concentration of the aerial particulate matter such as TSP, PM10, inhalable and respirable dusts were periodically measured in a mechanically ventilated piglet house and then statistically analyzed. When the level of pig activity was relatively increasing and feeding system was operating, higher trends of dust concentration, especially inhalable dust were ob-served while the level of dust were exceeded the threshold limit considering pulmonary func-tion of pig farmers. This implied that concentration of aerial dust was closely connected with the activity of animals and feed supply. Multiple linear regression analysis was also conducted according to the measured independent variables such as ventilation rate, age of piglet, num-ber of piglet, air temperature and pig activity index. From the statistical approach, linear re-gression equation was induced and could be evaluated according to the designed variables (TSP: R2=0.87, p-value=2.100e-17, PM10: R2=0.90, p-value=4.300e-18, inhalable dust: R2=0.83, p-value=0.00036, respirable dust: R2=0.86, p-value=0.00014). It was concluded that the statistical relationship determined between dust concentration and environmental variables investigated in this study were very significant and practical in conducting dust reduction re-searches.

Keywords: dust, pig house, respiratory welfare

1. Introduction

Scale of livestock house has been steadily increased and modernized to meet demand of meat consumption. Mechanically forced ventilation system has been come to the fore and widely adopted to increase total yields per unit facility and control rearing condition carefully. However, working condition is still very poor and it shows highly intensive level of odor, dust, organic matter, etc. inside facility comparing with other working place of business. Among the various pollutant matter inside pig house, bulk of dust can be generated from feed particles, hair, dan-der, feces, etc. and bring about various problems (Donham et al., 1986; Heber et al., 1988; Cambra et al., 2010). Organic biological materials such as endotoxin, bacteria, virus, fungi, etc. can be stuck to the surface of dust particle and it acts as a potential and direct harmful factor

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to the health of human and animals (Donham et al., 1986; Nilson, 1992). Various dose-re-sponse studies proved that pig farmers usually have higher prevalence of chronic or acute respiratory symptoms like cough, phlegm, bronchitis, allergic reaction and asthma-like symp-toms (Radon et al., 2001). Dust also affects the productivity of animals, induces disease man-ifestation and increases the mortality rate. In addition, dust can transport gaseous matters like odor, ammonia, hydrogen sulfide, methane, etc. and cause the aesthetic displeasure or further cause the social problem. The contagious animal epidemic like FMD and HPAI can also out-break through the airborne dust which roll the dispersion of the viruses. Therefore controlling of the aerial dust in a pig house has been emerging concern in respect of respiratory welfare of workers and animals and social and economic reasons. However, in Korea, there is no legislation or regulation in terms of controlling air quality of livestock house and only few re-searches on monitoring of dust in the facility is available. Therefore, the several key issue can be presented to solve the mentioned problem especially in terms of the respiratory welfare of the workers. It is significant to understand the mechanisms of the dust generation, and it needs to investigate the correlativity of the environmental variables related with aerial dust and then, the strategy of dust reduction should be induced. In this study, as a first step, we conducted periodic aerial dust monitoring inside the mechanically ventilated piglet house. From the col-lected data, we tried to find the correlation relationship between dust concentration and envi-ronmental variables like ventilation quantity, pig-activity level, feeding method, etc. through the multiple linear regression analysis to understand the mechanism of the dust generation.

2. Materials and methods

2.1 Experimental piglet house

Periodic field experiments to measure the dust concentration were carried out in one of the conventional mechanically forced piglet house in Yeo-ju city, South Korea. One piglet room was chosen as the experimental room to intensively investigate the experimental variables and dust level. The experimental room was 6m wide, 12m long and 2.7m high (Figure 1). The piglet house was ventilated using the roof duct and side exhaust fan and the fresh outdoor air can enter to the animal zone through the perforated ceiling. About 150~160 heads of piglet were raised in each piglet room and the room was divided into four sections by fences. Two feedbox were located at each section and dried-feed was automatically supplied according to the cen-tral control system.

2.2 Monitoring of aerial dust in the experimental piglet house

Monitoring of aerial dust in the experimental piglet house was regularly conducted from 8. 2012 to 12. 2013. Sampling the concentration of TSP and PM10 was carried out following NIOSH official process test. Experimental devices were installed at 1.5m height considering the aver-age working height and the location of installation of each sampler was depicted at Figure 2. Sampling time was 6-7 hours and concentration of each sampled dust was gauged based on the gravimetric method. Measurement of the concentration of inhalable and respirable dust was conducted using the Aerosol-spectrometer (Grimm, Inc., Germany) according to the de-signed experimental situation such as pig activity level, ventilation quantity, feed supply condi-tion, etc. Each data was continuously recorded for 5~10 min. Figure 3 shows the scenes of experiment in the target piglet house.

2.3 Monitoring of experimental variables for statistical analysis

Various environmental variables such as thermal distribution inside facility, weather data, ven-tilation quantities, age of piglet, number of piglet, etc. were measured and investigated to es-tablish the correlation between dust concentration and designed variables (Figure 4). 21 t-type thermocouples and data-logger (GL820, Graphtec, Inc., Germany) were installed to gain ther-mal data at 1.5 height from the pit ground considering average working height inside and out-side experimental facility. Weather station (WatchDog, Spectrum tech, Inc., USA) was installed


at open terrain to record the wind direction, wind speed, solar radiation, rainfall, air temperature and relative humidity. The ventilation quantities of experimental piglet house were measured by air flow-meter (self-product by A3EL) and manometer (TSI Inc., USA). The flow rate of each ventilation system was measured according to the whole range of the controlled level of output (10~90%) stage by stage to depict the flow rate – ventilation output curve. Portable web-cam-era was installed to record the every movement of piglets according to the situation and from the scene analysis, relative pig activity index was evaluated based on the piglet’s behaviors. Farming information like age of piglets, number of piglets, cleaning schedule, disease mani-festation were also collected through questionary investigations.

3. Results and Discussions

3.1 Periodic monitoring of TSP and PM10

Partial monitoring results of TSP and PM10 concentration inside the experimental piglet house are shown in figure 5. When the experiment was conducted at 10. 2012, total 83 heads of piglet whose age was 55days were raising in the experimental room, mean outdoor air tem-perature was 15.95℃ and ventilation quantities was 992.17m3/h. Total 186 heads of piglet with 54days age were raising in the room at 12. 2012 and the mean outdoor air temperature showed the usual tendencies of winter season with -3.05℃ and ventilation output kept minimum with 531.87m3/h. From the measured data, it was observed that higher concentration of dust was mostly detected near the feeder and at middle of piglet room although various factors could influence the generation of aerial dust concentration. Especially, the results of collected dust concentration at the part of feeder (10. 2012) showed quite higher than the results of 12. 2012. The reason of showing difference level of dust could be explained by installation height of feed supply pipe (the details will be presented). The plastic pipe line for feed supply was installed in the direction of the depth from the upper surface of the feeder as usual while the feed pipe was installed 15cm high from the top surface of the feeder at 10. 2012 and it meant that dust can spread and disperse more easily than other experimental conditions.

3.2 Periodic monitoring of inhalable and respirable dust

From the real-time scene analysis with measured dust concentration data, relative level of pig-activity was categorized based on the piglet’s behavior. In case when every piglet are lying calmly on the pit ground, this can be defined as pig-activity level 1, when some piglets are lying and the others are having feed during feeding periods, those situation can be defined as the pig-activity level 2 and when every piglet extremely and actively moved, it can be categorized as the pig-activity level 3. Figure 6 and 7 illustrate the some of the measured result of the concentration of inhalable and respirable dust according to the given experimental situation such as pig-activity level and feeding periods. As the level of pig-activity was increased, grow-ing trends of the concentration of the measured dust especially, inhalable dust were observed and these phenomena were also found when feeding system was operated. These tendencies implied that dust generation was intimately related with the activity of the animals and feed supply. In comparison to the threshold dust concentration suggested by Donham et al. (1995) which is related to the respiratory health of pig farmers, measured inhalable dust were exceed 2.5mg/m3 when the pig-activity level were 2 and 3, feeding periods and at the place of near the exhaust duct (2. 2013). In case of the results of 4. 2013 experiment, it was found that every value was exceeded the recommendation concentration except the result measured from the outdoor site. Measured concentration of respirable dust were exceeded the value of 0.23mg/m3 when the pig-activity level was 3 and feeding periods at 2. 2013 experiment and every meas-ured value was over the limit except the results measured from the outdoor site at 4. 2013 experiment. These facts demonstrated the possibilities of fomenting harmful aero-environment for human respiratory system, implying that pig farmers should wear the personal protective equipment such as mask during the mentioned situation.

3.3 Dust concentration according to the installation height of feed pipe


Feeding management was automatically operated two times per each day while the installation height of the feed supply pipes were randomly controlled by the pig farmers. Two pipes were installed every feeder in the depth direction from the top surface of the feeder. The status of pipe such as installation depth was checked every visiting and the aerial dust were measured using the Aerosol spectrometer near the feeder (1.5m high from the pit ground). Figure 8 shows the results of the measured mean concentration of inhalable and respirable dust according to the installation height of the pipe respectively. The inhalable dust showed the inverse linearity according to the installation depth of the pipe except one data point. As the feed supply pipes were installed more deeply, level of dispersed inhalable dust was decreased dramatically fol-lowing the inversed linear relationship. In comparison to the inhalable dust, results of the res-pirable dust measured near the feeder according to the pipe installation method did not show specific characteristics and it meant that the results were not statistically significant according to the given conditions.

3.4 Multiple regression analysis of sampled TSP and PM10

Multiple regression analysis was conducted on the basis of the collected concentration of TSP and PM10. The independent variables selected for the statistical approach were as in the fol-lowing; ventilation quantities (m3/s), age of piglet (days), number of piglet (heads), outdoor air temperature (℃), air temperature difference between indoor and outdoor. As a result of the statistical analysis, the exact significance of F value was about 2.100e-17 and it meant that derived linear equation by sampled TSP was statistically explained well (R2=0.87). Each coef-ficient of the independent variables and computed statistic values were reported at table 1. The computed rank of significantly contributing towards TSP concentration was as follows: ventilation quantity, age of piglet, number of piglet, outdoor air temperature and air temperature difference between indoor and outdoor. Many earlier studies reported that relatively lower con-centration of dust was found in the summer season in comparison to that of winter season and it meant that ventilation is the one of the most influential factor for dust environment. Likewise, our results showed same conclusion for TSP and could be supported by the mentioned earlier studies. In case of the multiple regression analysis of PM10 concentration, computed critical F value was 4.3e-18 and this also indicated that derived equation from sampled fine particles was statistically explained well (R2= 0.90). The studied independent variables were all satisfied with value of the significance level 0.05 (Table 2). Ventilation was also the most influential variable to the generation of PM10.

3.5 Multiple regression analysis of sampled inhalable and respirable dust

Multiple regression analysis of sampled inhalable and respirable dust were conducted based on the measured independent variables such as ventilation quantity, age of piglet, number of piglet, outdoor air temperature, air temperature difference between outdoor and indoor and Pig-activity level. Computed statistical values will be presented in table 3 and 4 respectively. From the computed results of statistical analysis, the exact significance of F value was about 0.00036 and this implied that the difference of the measured inhalable dust was statistically explained well according to the chosen independent variables (R2=0.83). Reviewing the computed P-value of each independent variable, almost variables could not statistically explained the difference of inhalable dust except ventilation and P.A.X2. Here, P.A.X1 was the dummy variable for evaluating the difference between pig-activity level 1 and 2 while P.A.X2 was for examining the difference between pig-activity level 1 and 3 respectively. In this analysis, the results showed that the concentration of the inhalable dust was statistically pretty higher when the piglet was very vigorously active comparing the result when the every piglet was lying on the pit, implying that the movement of the piglet could considerably contribute to the aerial dust environment. From the ANOVA table, the degree of contribution toward inhalable dust concentration could be analyzed and the rank was as follows; ventilation quantity, P.A.X2, outdoor air temperature, age of piglet, P.A.X1, air temperature difference and number of piglet. As mentioned earlier part, ventilation was the most influential factor to the generation of the target dust. The computed critical F value from the multiple regression analysis of the


respirable dust was 0.000136 and this also indicated that measured data were statistically explained well with regard to set variables and derived regression equation.The studied almost independent variables were evaluated about the value of significance level 0.05 except number of piglet and P.A.X1 and its calculated value of R2 was about 0.86. Contrary to the results of the inhalable dust, the most influential factor toward the generation of the respirable dust was air temperature difference and the rank of rest follows as next; outdoor air temperature, age of piglet, ventilation quantity, P.A.X2, number of piglet and P.A.X1 respectively.

4. Conclusions

Dust comes from feed, hair, flake, feces, etc. inside the facility and is very harmful to the work-ers as well as to the animals. Therefore controlling and reducing the dust is very significant to create sound aero-environmental condition of the livestock house. In this study, as a first step, periodic dust monitoring was conducted to understand the mechanism of dust generation in a mechanically ventilated piglet house. From the periodic measurement and analysis, it could be concluded that animal’s behavior and feed supply were influential factor for dust generation like preceding research. Ventilation was the most critical factor among the designed experi-mental variables for contributing to the dust concentration and these facts represent the prac-tical ground of the setting strategy for controlling and reducing the dust inside the piglet house. CFD technique will be adopted to study and suggest the efficient measure for dust control based on the statistical approach presented in this study.

5. Acknowledgements

This work was carried out with the support of “Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ008678)”, Rural Development Administra-tion, Republic of Korea.

6. References

Cambra-Lopez Maria, Aarnink, A. J. A., Zhao, Y., Calvet, S., Torres, A. G. (2010) Airborne particulate matter from livestock production systems: A review of an air pollution problem. En-vironmental Pollution, 158(2010), 1-17. Donham Kelley J., Popendorf, W., Palmgren, U., Larsson, L. (1986) Characterization of dusts collected from swine confinement buildings. Americal Journal of Industrial Medicine, 10(3), 294. Donham Kelley J., Reynolds, S. J., Whitten, P., Merchant, J. A., Burmeister, L.., Popendorf, W. J. (1995) Respiratory dysfunction in swine production facility workers-dose-response rela-tionships of environmental exposures and pulmonary-function. American Journal of Industrial Medicine, 27(3), 405-418. Nilsson C. (1982) Dust Investigations in Pig Houses. Report 25. Swedish University of Agricultural Sciences, Department of Farm Buildings, Division of Farm Building Construction, 93. Radon K., Weber, C., Iversen, M., Danuser, B., Pedersen, S., Nowak, D. (2001) Exposure assessment and lung function in pig and poultry farmers. Occupational and Environmental Med-icine, 58(6), 405-410.


Figure 1 Schematic diagram and scenes of experimental piglet house located Yeoju city, Korea

.

Figure 2 Location of installation of air sampler for TSP and PM10 and thermocouples for measuring thermal conditions of experimental piglet house

Figure 3 Scenes of sampling TSP and PM10 using air sampler and measuring the level of inhalable

and respirable dust in experimental piglet house

Figure 4 Measurement of environmental variables of experimental piglet house to investigate the

correlation between dust concentration and experimental variables


Figure 5 Measured dust concentration of TSP and PM10 inside the experimental piglet house at 10.

2012 (a) and 12. 2012 (b)

Figure 6 Meausred dust concentration of inhalable (a) and respirable (b) dust inside the experimental

piglet house according to the situation at 2. 2013

Figure 7 Meausred dust concentration of inhalable (a) and respirable (b) dust inside the experimental

piglet house according to the situation at 4. 2013

Figure 8 Scatter diagram of concentration of inhalable (a) and respirable (b) dust according to the

installation height of the feed supply pipe


Table 1 Computed coefficient of each variable, standard error, t-statistics and p-value from multiple linear regression analysis from sampled TSP

Coefficient Standard error t-statistics P-value y-intercept 2.573 0.297 8.655 8.5100E-11 Ventilation -1.416 0.253 -5.592 1.600E-06

Age of piglet -0.009 0.003 -3.362 0.002 Number of piglet -0.003 0.001 -2.288 0.027

Outdoor air temperature 0.008 0.008 1.029 0.309 Air temperature difference 0.002 0.003 0.605 0.549

Table 2 Computed coefficient of each variable, standard error, t-statistics and p-value from multiple linear regression analysis from sampled PM10

Coefficient Standard error t-statistics P-value y-intercept -0.883 0.455 -1.939 0.060 Ventilation -0.992 0.136 -7.312 8.000E-09

Age of piglet -0.009 0.002 -5.569 2.100E-06 Number of piglet -0.002 0.001 -2.719 0.010

Outdoor air temperature 0.117 0.019 6.062 4.200E-07 Air temperature difference 0.114 0.019 6.123 3.500E-07

Table 3 Computed coefficient of each variable, standard error, t-statistics and p-value from multiple linear regression analysis from sampled inhalable dust

Coefficient Standard error t-statistics P-value y-intercept 0.121 5.469 0.022 0.983 Ventilation -7.960 2.605 -3.055 0.009


P.A.X1 (*) 0.857 0.642 1.334 0.205 P.A.X2 (*) 1.884 0.642 2.933 0.012


Table 4 Computed coefficient of each variable, standard error, t-statistics and p-value from multiple linear regression analysis from sampled respirable dust

Coefficient Standard error t-statistics P-value y-intercept -2.525 0.716 -3.528 0.004 Ventilation -0.888 0.341 -2.605 0.022


P.A.X1 (*) 0.061 0.084 0.726 0.481 P.A.X2 (*) 0.166 0.084 1.970 0.071



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