• Journal of Biosystems Engineering
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• v.28 no.3
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• pp.225-230
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• 2003

This study was carried out to analyze the environmental variation of layer house at Iowa State in the USA. The analyzed seasons for this study were summer and winter. Analyzing factors are inside temperature and relative humidity, carbon dioxide concentration, ammonia concentration and emission. All factors were collected every 30 second from each house with portable monitoring units. In this study, two types of laying hen houses were monitored at the same season. One was a manure belt house, the other was a high-rise house. In order to estimate the ventilation rates of the laying hen houses, carbon dioxide concentration balance was used in this study. Ammonia concentrations and emission rates of the manure belt house are much lower than those of the high rise house. Daily mean ammonia concentrations in the manure belt house and high-rise house ranged from 3 to 7 ppm and 5 to 34 ppm, respectively. The daily ammonia emission rates averaged 0.68g/h$\cdot$500kg and 0.73g/h$\cdot$500kg for the manure belt house and 0.93g/h$\cdot$500kg and 2.89g/h$\cdot$500kg for the high-rise house in summertime and wintertime, respectively. Summertime is associated with much higher ammonia emission rates than wintertime because of much higher ventilation rates and ambient air temperature, even though the concentrations may be lower.

• Journal of Food Hygiene and Safety
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• v.23 no.3
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• pp.276-283
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• 2008

To provide the research strategy for protection of children's health from hazardous chemical, we reviewed the hazardous chemicals can be exposed through maternity, children's life style and living environment. Recently, diseases related with children's living condition were focused as asthma, atopy, childhood developmental disability, congenital malformations and obesity. Children can be exposed to hazardous chemicals through an ambient air, water, soil, food, toys and other factors such as floor dust. Also children's health was deeply related with a wrong life style and neglectful caring by a lack of knowledge and information of harmful ones at parents and child care center's nursers. According to the previous study, the chemical risk factor of children's health were identified as inorganic arsenic, bisphenol A, 2,4-D, dichlorvos, methylmercury, PCBs, pesticide, phthalates, PFOA/PFOS, vinyl chloride, et al. Domestic studies for identification of causality between children exposure to chemicals and resulted hazardous effects were not implemented. The confirmation of chemical risk factors through simultaneously performing toxicological analysis, human effect study, environmental/human monitoring, and risk assessment is needed for good risk management. And also, inter-agency collaboration and sharing information can support confirming scientific evidence and good decision making.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.2
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• pp.113-126
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• 2002

This study was carried out to evaluate the temporal (daily, weekly, and seasonal) variations of volatile organic compounds (VOCs) concentrations at a road-side site in a heavy-traffic central area of Metropolitan Taegu. Ambient air sampling was undertaken continuously for 14 consecutive days in each of four seasons from the spring of 1999 to the winter of 2000. The VOC samples were collected using adsorbent tubes, and were determined by thermal desorption coupled with GC/MS analysis. A total of 10 aromatic VOCs of environmental concern were determined, including benzene, toluene, ethylbenzene, m＋p-xylenes, styrene, o-xylene, 1,3,5-trimethylbenzene, 1,2,4-trimethylbenzene, and naphthalene. Among 10 target VOCs, the most abundant compounds appeared to be toluene (1.5 ∼ 102 ppb) and xylenes (0.1 ∼ 114 ppb), while benzene levels were in the range of 0.3 ∼6 ppb. It was found that the general trends of VOC levels were significantly dependent on traffic conditions at the sampling site since VOC concentrations were at their maximum during rush hours (AM 7∼9 and PM 7 ∼9). However, some VOCs such as toluene, xylenes, and ethylbenzene were likely to be affected by a number of unknown sources other than vehicle exhaust, being attributed to the use of paints, and/or the evaporation of solvents used nearby the sampling site. In some instances, extremely high concentrations were found for these compounds, which can not be explained solely by the impact of vehicle exhaust. The results of this study may be useful for estimating the relative importance of different emission sources in large urban areas. Finally, it was suggested that the median value might be more desirable than the arithmetic mean as a representative value for the VOC data group, since the cumulative probability distribution (n=658) does not follow the normal distribution pattern.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.6
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• pp.573-583
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• 2005

Fugitive dust, which is emitted in the ambient air without first passing through a stack or duct designed to control flow, is frequently generated by means of wind erosion from storage yards at Pohang Steel Wokrs. The size distribution of fugitive dust is mostly in the range of coarse particulate which is deposited as soon as emitted and less harm to human health; however $20\%$ of fugitive dust contains PM 10 known as one of most harmful airborne pollutant. Consequently, effective control and reduction of fugitive dust is strongly requested by the local society, but it is not easy so far because the generation and dispersion of fugitive dust highly depends on meteorological conditions, and it being occurred for irregularity. This research presented a fugitive dust control system for each meteorological condition by providing statistical prediction data obtained from a statistical analysis on the probability of generating the threshold velocity at which the fugitive dust begins to occur, and the frequency occurring by season and by time of the wind direction that can generate atmospheric pollution when the dispersed dust spreads to adjacent residential areas. The research also built a fugitive dust detection system which monitors the weather conditions surrounding storage yards and the changes in air quality on a real-time basis and issues a warning message by identifying a situation where the fugitive dust disperses outside the site boundary line so that appropriate measures can be taken on a timely basis. Furthermore, in respect to the spraying of water to prevent the generation of fugitive dust from the storage piles at the storage yard, an advanced statistical meteorological analysis on the weather conditions in Pohang area and a case study of fugitive dust dispersion toward outside of working field during $2002\∼2003$ were carried out in order to decide an optimal water-spraying time and the number of spraying that can prevent the origin of fugitive dust emission. The results of this research are expected to create extremely significant effects in improving surrounding environment through actual reduction of the fugitive dust produced from the storage yard of Pohang Steel Works by providing a high-tech warning system capable of constantly monitoring the leakage of fugitive dust and water-spray guidance that can maximize the water-spraying effects.

• Smart Structures and Systems
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• v.17 no.3
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• pp.363-389
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• 2016

Deficient modes that cannot be always identified from different sets of measurement data may exist in the application of operational modal analysis such as the stochastic subspace identification techniques in large-scale civil structures. Based on a recent work using the long-term ambient vibration measurements from an instrumented cable-stayed bridge under different wind excitation conditions, a benchmark problem is launched by taking the same bridge as a test bed to further intensify the exploration of mode identifiability. For systematically assessing this benchmark problem, a recently developed SSI algorithm based on an alternative stabilization diagram and a hierarchical sifting process is extended and applied in this research to investigate several sets of known and blind monitoring data. The evaluation of delicately selected cases clearly distinguishes the effect of traffic excitation on the identifiability of the targeted deficient mode from the effect of wind excitation. An additional upper limit for the vertical acceleration amplitude at deck, mainly induced by the passing traffic, is subsequently suggested to supplement the previously determined lower limit for the wind speed. Careful inspection on the shape vector of the deficient mode under different excitation conditions leads to the postulation that this mode is actually induced by the motion of the central tower. The analysis incorporating the tower measurements solidly verifies this postulation by yielding the prevailing components at the tower locations in the extended mode shape vector. Moreover, it is also confirmed that this mode can be stably identified under all the circumstances with the addition of tower measurements. An important lesson learned from this discovery is that the problem of mode identifiability usually comes from the lack of proper measurements at the right locations.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.577-586
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• 2016

Hazardous air pollution caused by heavy metals in the air is at a serious level. Although manganese(Mn), one of the heavy metals, is a non-carcinogenic substance, it has a harmful influence on the human body. It is partially measured because automatic monitoring technologies have not yet be fully established. We introduced a statistical model for the daily concentration of manganese. Incorporating a linkage between Mn and meteorology, the proposed model is formulated in way to identify meteorological effects and to allow for seasonal trends, enabling not only accurate measurement of manganese concentration, but also information about the evaluation on a Hazard Quotient (non-cancer risk).

• Journal of Preventive Medicine and Public Health
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• v.48 no.3
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• pp.151-169
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• 2015

Objectives: The deleterious effects of air pollution on various health outcomes have been demonstrated. However, few studies have examined the effects of air pollution on liver enzyme levels. Methods: Blood samples were drawn up to three times between 2008 and 2010 from 545 elderly individuals who regularly visited a community welfare center in Seoul, Korea. Data regarding ambient air pollutants (particulate matter ${\leq}2.5{\mu}m$ [$PM_{2.5}$], nitrogen dioxide [$NO_2$], ozone [$O_3$], carbon monoxide, and sulfur dioxide) from monitoring stations were used to estimate air pollution exposure. The effects of the air pollutants on the concentrations of three liver enzymes (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and ${\gamma}$-glutamyltranspeptidase [${\gamma}$-GTP)]) were evaluated using generalized additive and linear mixed models. Results: Interquartile range increases in the concentrations of the pollutants showed significant associations of $PM_{2.5}$ with AST (3.0% increase, p=0.0052), ALT (3.2% increase, p=0.0313), and ${\gamma}$-GTP (5.0% increase, p=0.0051) levels; $NO_2$ with AST (3.5% increase, p=0.0060) and ALT (3.8% increase, p=0.0179) levels; and $O_3$ with ${\gamma}$-GTP (5.3% increase, p=0.0324) levels. Significant modification of these effects by exercise and alcohol consumption was found (p for interaction <0.05). The effects of air pollutants were greater in non-exercisers and heavy drinkers. Conclusions: Short-term exposure to air pollutants such as $PM_{2.5}$, $NO_2$, and $O_3$ is associated with increased liver enzyme levels in the elderly. These adverse effects can be reduced by exercising regularly and abstinence from alcohol.

• The Plant Pathology Journal
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• v.34 no.3
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• pp.236-240
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• 2018

Crop yield is critically related to the physiological responses and disease resistance of the crop, which could be strongly affected by high temperature conditions. We observed the changes in the growth of barley under higher than ambient air-temperature conditions using a temperature gradient field chamber (TGFC) during winter and spring. Before the stem extension stage of barley growth, Cladosporium sp. spontaneously appeared in the TGFC. The severity of disease became serious under warmer temperature conditions. Further, the stomata closed as the severity of the disease increased; however, stomatal conductance at the initial stage of disease was higher than that of the normal leaves. This was likely due to the Iwanov effect, which explains that stressed plants rapidly and transiently open their stomata before longer-term closure. In this study, we tested three optical methods: soil-plant analysis development (SPAD) chlorophyll index, photochemical reflectance index (PRI), and maximum quantum yield (Fv/Fm). These rapid evaluation methods have not been used in studies focusing on disease stress, although some studies have used these methods to monitor other stresses. These three indicative parameters revealed that diseased barley exhibited lower values of these parameters than normal, and with the increase in disease severity, these values declined further. Our results will be useful in efficient monitoring and evaluation of crop diseases under future warming conditions.

• Smart Structures and Systems
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• v.26 no.1
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• pp.35-47
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• 2020

This paper proposes the use of transmissibility functions combined with a machine learning algorithm, Artificial Neural Networks (ANNs), to assess damage in a truss bridge. A new approach method, which makes use of the input parameters calculated from the transmissibility function, is proposed. The network not only can predict the existence of damage, but also can classify the damage types and identity the location of the damage. Sensors are installed in the truss joints in order to measure the bridge vibration responses under train and ambient excitations. A finite element (FE) model is constructed for the bridge and updated using FE software and experimental data. Both single damage and multiple damage cases are simulated in the bridge model with different scenarios. In each scenario, the vibration responses at the considered nodes are recorded and then used to calculate the transmissibility functions. The transmissibility damage indicators are calculated and stored as ANNs inputs. The outputs of the ANNs are the damage type, location and severity. Two machine learning algorithms are used; one for classifying the type and location of damage, whereas the other for finding the severity of damage. The measurements of the Nam O bridge, a truss railway bridge in Vietnam, is used to illustrate the method. The proposed method not only can distinguish the damage type, but also it can accurately identify damage level.

• Korean Journal of Agricultural Science
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• v.47 no.1
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• pp.59-66
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• 2020

Particulate matter (PM) is regarded as a major threat to public health and safety in urban areas. Despite a variety of efforts to systemically monitor the distribution of PM, the limited amount of sampling sites may not provide sufficient coverage over the areas where the monitoring stations are not located in close proximity. This study examined the capacity of using remotely sensed data to estimate the PM10 and PM2.5 concentrations in Seoul, South Korea. Multiple linear regression models were developed using the multispectral band data from the Moderate-resolution imaging spectro-radiometer equipped on Terra (MODIS) and Operational Land Imager equipped on Landsat 8 (Landsat 8) and meteorological parameters. Compared to MODIS-derived models (r² = 0.25 for PM10, r² = 0.30 for PM2.5), the Landsat 8-derived models showed improved model reliabilities (r² = 0.17 to 0.57 for PM10, r² = 0.47 to 0.71 for PM2.5). Landsat 8 model-derived PM concentration and ground-truth PM measurements were cross-validated to each other to examine the capability of the models for estimating the PM concentration. The modeled PM concentrations showed a stronger correlation to PM10 (r = 0.41 to 0.75) than to PM2.5 (r = 0.14 to 0.82). Overall, the results indicate that Landsat 8-derived models were more suitable in estimating the PM concentrations. Despite the day-to-day fluctuation in the model reliability, several models showed strong correspondences of the modeled PM concentrations to the PM measurements.