Nine pig farms were evaluated for the welfare quality in Korea using animal- and environment-based parameters (particularly air quality parameters) during the winter of 2013. The Welfare Quality® (WQ®) protocol consists of 12 criteria within four principles. The WQ® protocol classifies farms into four categories ranging from 'excellent' to 'not classified'. Each of these criteria has specific measures for calculating scores. Calculations for the welfare scores were conducted online using the calculation model in the WQ® protocol. Environment-based parameters like microclimate (i.e., temperature, relative humidity, air speed, and particulate matter), bacteria (total airborne bacteria, airborne total coliform, and airborne total Escherichia coli), concentration of gases (carbon dioxide, ammonia, and hydrogen sulfide) were measured to investigate the relationship between animal- and environment-based parameters. Correlations between the results of animal- and environment-based parameters were estimated using spearman correlation coefficient. The overall assessments found that five out of nine farms were 'acceptable', and four farms were 'enhanced'; no farm was 'not classified'. The average score for the four principles across the nine farms, in decreasing order, were 'good feeding' (63.13 points) > 'good housing' (59.26 points) > 'good health' (33.47 points) > 'appropriate behaviors' (25.48 points). In the result of the environment aspect, the relative humidity of farms 2 (93.4%), 3 (100%), and 9 (98%) was much higher than the recommended maximum relative humidity of 80%, and four out of the nine farms had ammonia concentrations greater than 40 ppm. Ammonia had negative correlations with 'positive social behaviors' and positive emotional states: content, enjoying, sociable, playful, lively, happy and it had positive correlations with negative emotional states: aimless, distressed. The concentration of carbon dioxide had negative correlations with positive emotional states; calm, sociable, playful, happy and it had a positive correlation with negative emotional state; aimless. Our results indicate that the control of the environment for growing pigs can help improve their welfare, particularly via good air quality (carbon dioxide, ammonia, hydrogen sulfide).
Park, Duck-Shin;Kwon, Soon-Bark;Cho, Young-Min;Park, Eun-Young;Jeong, Woo-Tae;Lee, Ki-Young
Journal of Environmental Health Sciences
/
v.38
no.1
/
pp.51-56
/
2012
Objectives: High concentrations of airborne particulate matters (PM) can affect the health of passengers using public transportation. The objectives of this research were to develop a PM control system for a railway cabin and to evaluate the performance of the device under conditions of an actual journey. Methods: This study measured the concentrations of $PM_{10}$ and $PM_{2.5}$ simultaneously in a reference cabin and a cabin with the PM control device. Results: The average $PM_{10}$ concentration in the reference cabin was 100 ${\mu}g/m^3$, and the $PM_{10}$ concentration in the cabin with the control device was 79 ${\mu}g/m^3$. While the overall control efficiency of the control device was 15.4%, reduction was more effective for peak $PM_{10}$ concentration. However, $PM_{2.5}$ levels did not differ greatly between the reference cabin and the cabin with the control device. The ratio of $PM_{2.5}$ to $PM_{10}$ was 0.37. $PM_{10}$ concentrations in cabins were not associated with ambient concentrations, indicating that the main sources of $PM_{10}$ were present in cabins. Additionally, average $CO_2$ concentration in the cabins was 1,359 ppm, less than the maximum of 2,000 ppm set out by the Korean Ministry of Environment's guideline. The $CO_2$ concentration in cabins was significantly associated with the number of passengers: the in-cabin concentration = $23.4{\times}N+460.2$, where N is the number of passengers. Conclusions: Application of the PM control device can improve $PM_{10}$ concentration, especially at peak levels but not $PM_{2.5}$ concentration.
Vehicles, especially diesel-using, are a major source of airborne particulate matter(PM), nitrogen dioxide($NO_2$) and so on in metropolitan cities such as Seoul. Therefore workers, who are mainly merchants, near roadside may be highly exposed to air pollutants from exhausted emissions of vehicles. This means that occupational type and location can affect the workers'health by exposure to outdoor pollutions of ambient as well as indoor pollutions of working condition, respectively. In this study, we simultaneously measured the PM3.5 and $NO_2$concentrations in indoor and outdoor of shoes repair shops in Seoul, which were generally located at roadside in Korea. Shoes repairmen were highly exposed to PM3.5 and $NO_2$ both indoor and outdoor of repair shops comparing with other sub-population groups. High exposure to air pollutants for shoes repairmen was considered to be outdoor source from exhausted emission of vehicles and indoor source from working condition. The $PM3.5/NO_2$ concentration ratio was $1.17{\pm}$0.59 in roadside, of which ratio was higher 7han ratios of other studies. This result suggested that major air pollutant in Seoul was fine particle. Also, this PM3.5 to $NO_2$ ratio will be used in environmental exposure and risk assessment by estimation of PM3.5 concentration as measuring the only $NO_2$ concentration with small and accurate $NO_2$ passive sampler.
In the present study, we made measurements of PM-bound metal concentrations from seven different urbanized locations in Seoul for the period covering March 2001 through May 2002. The measurement data were analyzed to explore the possible influences of spatial factors on metal distribution characteristics. To check for the importance of such aspects on metal distribution characteristics, the measured data were compared between different metals and between different sites by several criteria including (1) coefficient of variation (CV) values; (2) temporal variability; and (3) the abundance of strongly correlated pairs. The overall results of our study indicate strong diversity in the distribution characteristics of different metals. It is found that some metals (like Fe, Mn, and Pb) tend to exhibit strong compatibility among different study sites. However, no such compatibility appears to exist for certain metals like Cu. To account for the importance of spatial factors, complex relationships between source/sink processes and geochemical characteristics of a given metallic component may have to be examined in a systematic manner.
Samples of size-fractionated PM10 (airborne particulate matter with aerodynamic diameter less than $10\mu\textrm{m}$) were collected at an urban site in Jeju city from May to September 2002. The mass concentration and chemical composition of the samples were measured. The data sets were then applied to the CMB receptor model to estimate the source contribution of PM10 in Jeju area. The average PM10 mass concentration was 28.80$\mu\textrm{g}/m^3$ ($24.6~33.49\mu\textrm{g}/m^3$), and the FP (fine particle with aerodynamic diameter less than $2.l\mu\textrm{m}$ fraction in PM10 was approximately 8% higher than the CP (coarse particle with aerodynamic diameter greater than $2.l\mu\textrm{m}$ and less than $10\mu\textrm{m}$ fraction in PM10. The CP composition was obviously different from the FP composition, that is, the most abundant water soluble species was nitrate ion in the FP, but sulfate ion in the CP. Also sulfur was the most dominant element in the FP, however, sodium was that in the CP. From CMB receptor model results, it was found that road dust was the largest contributor to the CP mass concentration (45% of the CP) and ammonium nitrate, domestic boiler, and marine aerosol were major sources to the CP mass. However, the secondary aerosol was the most significant contributor to the FP mass concentration (45% of the FP). In this study, it was suggested that the contributions of soil dust and gasoline vehicle became very low due to collinearity with road dust and diesel vehicle, respectively.
Trace elements in air samples artificially loaded on filters with urban dust and the bulk material of urban dust as an environmental sample were determined non-destructively using instrumental neutron activation analysis. Standard reference material (Urban Dust, SRM 1648) of the National Institute of Standard and Technology was used for the analytical quality control. The relative error for 37 elements was less than 15% and the standard deviation was less than 10%. 29 elements in the urban dust and 21 elements in the loaded filter sample were determined respectively. To evaluate the proficiency and reliability of the measurement, data intercomparison was performed and 39 analytical laboratories participated in the analysis using different analytical methods; neutron activation analysis, particle induced X-ray emission analysis, X-ray fluorescence analysis and atomic absorption spectrometry. Z-scores were calculated using the standard deviation of the laboratorie's mean as target standard deviation, and a good result was obtained that the values fall between -1 and +1 except some elements.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.24
no.1
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pp.65-73
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2014
Objectives: The purposes of this study are to investigate workers' exposures to respirable particles generated in taconite mines and to compare two metric methods for mass concentrations using direct-reading instruments. Methods: Air monitorings were conducted at six mines where subjects have been exposed primarily to particulate matters in crushing, concentrating, and pelletizing processes. Air samples were collected during 4 hours of the entire work shift for similarly exposure groups(SEGs) of nine jobs(N=37). Following instruments were employed to evaluate the workplace: a nanoparticle aerosol monitor(particle size range; 10-1000 nm, unit: ${\mu}m^2/cc$, Model 9000, TSI Inc.); DustTrak air monitors($PM_{10}$, $PM_{2.5}$, unit: $mg/m^3$, Model 8520, TSI Inc.); a condensation particle counter(size range; 20-1000 nm, unit: #/cc, P-Trak 8525, TSI Inc.); and an optical particle counter(particle number by size range $0.3-25{\mu}m$, unit: #/cc, Aerotrak 9306, TSI Inc.). Results: The highest airborne concentration among SEGs was for furnace operator followed by pelletizing maintenance workers in number of particle and surface area, but not in mass concentrations. The geometric means of $PM_{2.5}$ by the DustTrak and the Ptrak/Aerotrak were $0.04{\mu}m$(GSD 2.52) and $0.07{\mu}m$(GSD 2.60), respectively. Also, the geometric means of RPM by the DustTrak and the Ptrak/Aerotrak were $0.16{\mu}m$(GSD 2.24) and $0.32{\mu}m$(GSD 3.24), respectively. The Pearson correlation coefficient for DustTrak $PM_{2.5}$ and Ptrak/Aerotrak $PM_{2.5}$ was 0.56, and that of DustTrak RPM and Ptrak/Aerotrak RPM was 0.65, indicating a moderate positive association between the two sampling methods. Surface area and number concentration were highly correlated($R^2$ = 0.80), while $PM_{2.5}$ and RPM were also statistically correlated each other($R^2$ = 0.79). Conclusions: The results suggest that it is possible to measure airborne particulates by mass concentrations or particle number concentrations using real-time instruments instead of using the DustTrak Aerosol monitor that monitor mass concentrations only.
Journal of Korean Society of Environmental Engineers
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v.28
no.10
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pp.1038-1045
/
2006
A series of experiments was conducted to test the compatibilities of two different techniques to determine elemental concentrations by INAA and ICP-MS based on both the NIST SRM 2783(air particulate on filter media) and the field samples for PM10. For NIST SRM the results of INAA were more accurate and precise for all target elements than those of ICP-MS. The comparative data set for PM10 samples collected in an industrial complex area showed that mean of concentration ratio, derived for the two different methods such as C(INNA/ICP-MS), were distinguished from each other: (1) Ba, Cu, K Mg, Na, and Sb: $0.9{\sim}1.1$; (2) Al, Co, Fe, and Mn: $0.8{\sim}1.2$; and (3) Se, Ti, and Zn: >1.3. When the results obtained from both methods were evaluated in terms of regression analysis, paired t-test, and Wilcoxon signed-rank test, the results of many elements determined from PM10 samples(such as Al, Ba, Co, Cu, Fe, K, Mn, Nd, and Sb) exhibited a fairly good agreement between the two methods, despite a wide range of variation.
This study was conducted to investigate seasonal distributions of fine particles ($PM_{2.5}$) and associated polycyclic aromatic hydrocarbons (PAHs) at three cities. $PM_{2.5}$ samples were collected on glass fiber filters at urban (Chuncheon), metropolitan (Seoul), and industrial complex sites (Ulsan) from September, 2002 to February, 2004 using the Andersen FH 95 Particulate Sampler. About five 24-hour samples were collected from each site per season. The filters were analyzed for mass and six selected PAHs concentrations. $PM_{2.5}$ concentrations were the highest either in winter or spring, which could be attributed to the increase of fossil fuel combustion in winter or the transport of yellow sand to the Korean peninsula from China in spring, respectively. Regional $PM_{2.5}$ concentrations were higher in the order of Seoul>Chuncheon>Ulsan without statistical difference among cities. The filters were extracted using dichloromethane in an ultrasonicator and analyzed for six PAHs (anthracene, fluoranthene, pyrene, benzo[a]anthracene, chrysene, and benzo[a]pyrene) with HPLC. Total PAHs concentrations were statistically different among seasons in each site, and the highest concentrations were observed in winter at each sampling site. For total samples collected, the median total PAHs concentrations in Chuncheon ($4.6ng/m^3$) and Seoul ($4.4ng/m^3$) were approximately two times higher than that in Ulsan ($2.1ng/m^3$). Chrysene was a component found in the highest proportion among total PAHs at each site. Carcinogenic risks calculated based on the BaP toxic equivalency factors (TEFs) over the whole sampling period were higher in the order of Chuncheon>Seoul>Ulsan. This study suggests that the atmosphere of Chuncheon is contaminated with particulate matter and PAHs at the levels equivalent to those of Seoul and that an appropriate measure needs to be taken to mitigate human health risks from inhalation exposure to airborne fine particles.
Indoor air quality(IAQ) in workplace and residential environments has been concern of people. Recently, Ministry of Environment in Korea has recognized the potential risk on the healthy effect related to indoor air pollution at home. Therefore, the purpose of this study was performed to measure the indoor air pollutants of IAQ at different homes and investigate to compare the perception of IAQ recognition at home from questionnaire survey in Seoul. We estimated the IAQ of selected 6 homes based on site region and housing type. The indoor air pollutants and parameters such as temperature, relative humidity, respirable suspended particulate matter($PM_{10}$), formaldehyde(HCHO), total bacteria counts, carbon monooxide(CO) and carbon dioxide($CO_2$) were monitored for summer and winter. In monitoring results, the respirable suspended particulate matter(($PM_{10}$) and indoor airborne bacteria level of home 5 and 6 were higher than the standard of the public $150{\;}{\mu}g/m^3$ and $500{\;}{\mu}g/m^3$, the level formaldehyde(HCHO) was exceed 0.1 ppm of the standard of Korea at all monitored homes. In statistics analysis, we could find a correlation between the building age and the concentration of CO, TBC were significant at 0.01 level and Relative Humidity was significant at 0.05 level for summer. Finally, the important air pollutants of IAQ in home were HCHO and total bacteria counts(TBC). And we performed a questionnaire survey of 500 people about their awareness for the importance of IAQ in our home during same period. In results, all most response of occupant has recognized the importance of IAQ at home. Therefore, it can be concluded that the IAQ of selected 6 home studied was perceived as acceptable, it is recommended that the government related IAQ was suggested the guideline and control of IAQ problems, and the occupants need to be effort to reduce the exposure of sources to undesirable pollutants.
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