• KIEAE Journal
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• v.14 no.1
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• pp.75-81
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• 2014

This study aims at investigating the benefit of actively controlling humidity to improve thermal comfort and energy efficiency in climate zones other than hot-dry. For this research purpose, three thermal control strategies, which adopted different initiative degrees in humidity control, were developed - i) temperature controls, ii) temperature and humidity controls, and iii) thermal sensation controls. Performance of the developed strategies were experimentally tested in a full scale mock up of an office environment. The study revealed that air temperature was better controlled in the occupied zone under the first two strategies than the thermal sensation based strategy. On the other hand, the thermal sensation-based strategy maintained thermal sensation levels more comfortably. In addition, energy consumption was significantly reduced when humidity was actively controlled for thermal comfort. The thermal sensation-based control strategy consumed significantly less electricity than the first two strategies. From these findings, this study indicated that adoption of an active humidity control system based on thermal sensation can provide increased thermal comfort as well as energy savings for summer seasons in climatic zones other than hot-dry.

• Environmental Engineering Research
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• v.18 no.2
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• pp.57-63
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• 2013

Arid areas have a significant problem with water supply due to climate change and high water demand. More than 3,000 years ago, Persians started constructing elaborate tunnel systems called Qanat for extracting groundwater for agriculture and domestic usages in arid and semi-arid areas and dry deserts. In this paper, it has been demonstrated that ancient methods of water management, such as the Qanat system, could provide a good example of human wisdom to battle with water scarcity in a sustainable manner. The purpose of this paper is twofold: Review of old wisdom of Qanat-to review the history of this ancient wisdom from the beginning until now and study the Qanat condition at the present time and to explore why (notwithstanding that there are significant advantages to the Qanat system), it will no longer be used; and suggestions for future water management-to suggest a number of new methods based on new materials and technology to refine and protect Qanats. With these new suggestions it could be possible to refine and reclaim this method of extracting water in arid areas. Also, a new multi-purpose water management model has been introduced based on rainwater infiltration management over the Qanat system as the model can be applied either in dry or wet cities to solve current urban water problems.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.E1
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• pp.9-18
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• 2006

Aerosol hygroscopic properties were measured by a tandem differential mobility analyzer (TDMA) system during the Aerosol Characterization Experiment (ACE)-Asia campaign from 31 March to 1 May 2001. Two high flow differential mobility analyzers (DMAs) were used to maximize the count rate on board the Center for Interdisciplinary Remotely Piloted Aircraft (CIRPAS) Twin Otter aircraft. Hygroscopic growth factor distributions of particles having initial dry nanoparticle diameters of 0.040, 0.059, 0.086, 0.126, 0.186, 0.273, 0.400, and $0.586{\mu}m$ were measured during 19 research flights. Data collected during 12 of those flights were used to investigate aerosol mixing state and the influence of aerosol source region on size-resolved hygroscopicity. The uniformity in size-resolved hygroscopicity was quantified to facilitate comparison between measurements made in different air masses. Hygroscopic growth factors are strongly dependent on source region and sizes. Mean hygroscopic growth factors were observed to be greatest when the air mass origin was from the south. The mean growth factors for continental sources decreased with initial size from 1.47 to 1.27 for $0.040{\mu}m\;and\;0.586{\mu}m$, but increased with initial size from 1.44 to 1.8 for $0.040{\mu}m\;and\;0.400{\mu}m$ dry diameters for marine sources.

• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.2
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• pp.93-97
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• 2007

A Silkworm breeding programme was designed to develop a robust but productive bivoltine silkworm hybrid of Bombyx mori L. suitable for rearing throughout the year in tropical climate by utilizing indigenous polyvoltine and productive bivoltine breeds. The breeding was carried out under high temperature ($36^{\circ}C{\pm}1^{\circ}C$) and low humidity ($50{\pm}5%$) conditions in the environmental chamber. By $F_{12}$, three oval and three dumbbell breeds were isolated with higher survival and productive merits. These breeds were utilized in the hybrid evaluation along with other popular breeds. Based on combining ability test results, the hybrid $SR_2{\times}SR_5$ was selected for large scale testing and evaluated in different seasons. The evaluation studies indicated that the hybrid has higher viability and productive merits and it is suitable to rear throughout the year. The hybrid $SR_2{\times}SR_5$ recorded a survival of 92.0%, cocoon shell weight of 0.417 g, cocoon shell percentage of 23.0 and a filament length of 1042 meters under hot and dry conditions of environmental chamber compared to the control thermo-tolerant hybrid $CSR18{\times}CSR19$.

• Journal of Korean Society on Water Environment
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• v.26 no.3
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• pp.482-490
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• 2010

In this study 17 GCMs' simulations of late 20th century climate in Korea are examined. A regionally averaged time series formed by averaging the temperature and precipitation values at all the Korean grid points. In order to compare general circulation models with observations, observed spatially averaged temperature and precipitation is calculated using 24 stations for 1971 to 2000. The annual mean difference between models and observed data are compared. For temperature, most models have a slight cold bias. The models with least bias in annual average temperature are NIES(MIROC3.2 hires), GISS(AOM) and INGV(SXG2005). For precipitation, almost all models have a dry bias, and for some the bias exceeds 50%. Models with lowest bias are NIES(MIROC3.2 hires), CCCma(CGCM3-T47) and MPI-M(ECHAM5-OM). The models' simulated seasonal cycles show that for temperature, CSIRO(Mk3.0) has the best followed by CCCma(CGCM3-T47) and CCCma(CGCM3-T63), and for precipitation, NIES(MIROC3.2 hires) has the best followed by CSIRO(Mk3.0) and CNRM(CM3). In the assessment using Taylor diagram, CCCma(CGCM3-T47) ranks the best for temperature, and NIES(MIROC3.2 hires) ranks the best for precipitation.

• Journal of Forest and Environmental Science
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• v.38 no.2
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• pp.110-121
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• 2022

Leaf functional traits widely have been used to understand the environmental controls of resource utilization strategy of plants along the environmental gradients. By using key leaf functional traits, we quantified the relationships between leaf traits and local climate throughout the distributional range of Rhododendron caucasicum Pall. in eastern and western Georgian mountains (the South Caucasus). Our results revealed, that all traits showed high levels of intraspecific variability across study locations and confirmed a strong phenotypic differentiation of leaf functional variation along the east-west longitudinal gradient in response to the local climate; out of the explored climatic variables, the moisture factors related to precipitation and number of precipitation and dry days for winter and growth seasons were more strongly related to leaf trait variation than the elevation and air temperature. Among studied leaf traits, the leaf specific area (SLA) showed the highest level of variability indicating the different resource utilization strategies of eastern and western-central Rh. caucasicum individuals. High SLA leaves for western-central Caucasian individuals work in relatively resource-rich environments (more humid in terms of precipitation amount and the number of precipitation days in winter) and could be explained by preferential allocation to photosynthesis and growth, while eastern Caucasian samples work in resource-poor environments (less humid in terms of precipitation amount and the number of precipitation days in winter) and the retention of captured resources is a higher priority appearing in a low SLA leaves. However, more evidence from a broader study of the species throughout its distribution range by including additional environmental factors and molecular markers are needed for firmer conclusions of intraspecific variability of Rh. caucasicum.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.86-94
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• 2023

Climate change is more rapid in the Arctic than elsewhere in the world, and increased precipitation and warming are expected cause changes in biogeochemical processes due to altered microbial communities and activities. It is crucial to investigate microbial responses to climate change to understand changes in carbon and nitrogen dynamics. We investigated the effects of increased temperature and precipitation on microbial biomass and community structure in dry tundra using two depths of soil samples (organic and mineral layers) under four treatments (control, warming, increased precipitation, and warming with increased precipitation) during the growing season (June-September) in Cambridge Bay, Canada (69°N, 105°W). A phospholipid fatty acid (PLFA) analysis method was applied to detect active microorganisms and distinguish major functional groups (e.g., fungi and bacteria) with different roles in organic matter decomposition. The soil layers featured different biomass and community structure; ratios of fungal/bacterial and gram-positive/-negative bacteria were higher in the mineral layer, possibly connected to low substrate quality. Increased temperature and precipitation had no effect in either layer, possibly due to the relatively short treatment period (seven years) or the ecosystem type. Mostly, sampling times did not affect PLFAs in the organic layer, but June mineral soil samples showed higher contents of total PLFAs and PLFA biomarkers for bacteria and fungi than those in other months. Despite the lack of response found in this investigation, long-term monitoring of these communities should be maintained because of the slow response times of vegetation and other parameters in high-Arctic ecosystems.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.2
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• pp.145-153
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• 2017

This study was aimed to find yield prediction model of Italian ryegrass using climate big data and geographic information. After that, mapping the predicted yield results using Geographic Information System (GIS) as follows; First, forage data were collected; second, the climate information, which was matched with forage data according to year and location, was gathered from the Korean Metrology Administration (KMA) as big data; third, the climate layers used for GIS were constructed; fourth, the yield prediction equation was estimated for the climate layers. Finally, the prediction model was evaluated in aspect of fitness and accuracy. As a result, the fitness of the model ($R^2$) was between 27% to 95% in relation to cultivated locations. In Suwon (n=321), the model was; DMY = 158.63AGD -8.82AAT +169.09SGD - 8.03SAT +184.59SRD -13,352.24 (DMY: Dry Matter Yield, AGD: Autumnal Growing Days, SGD: Spring Growing Days, SAT: Spring Accumulated Temperature, SRD: Spring Rainfall Days). Furthermore, DMY was predicted as $9,790{\pm}120$ (kg/ha) for the mean DMY(9,790 kg/ha). During mapping, the yield of inland areas were relatively greater than that of coastal areas except of Jeju Island, furthermore, northeastern areas, which was mountainous, had lain no cultivations due to weak cold tolerance. In this study, even though the yield prediction modeling and mapping were only performed in several particular locations limited to the data situation as a startup research in the Republic of Korea.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.409-420
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• 2012

Since the Industrial Revolution, CO2 levels have been increasing with climate change. In this study, Analyze time-series changes in snow cover quantitatively and predict the vanishing point of snow cover statistically using remote sensing. The study area is Mt. Kilimanjaro, Tanzania. 23 image data of Landsat-5 TM and Landsat-7 ETM+, spanning the 27 years from June 1984 to July 2011, were acquired. For this study, first, atmospheric correction was performed on each image using the COST atmospheric correction model. Second, the snow cover area was extracted using the NDSI (Normalized Difference Snow Index) algorithm. Third, the minimum height of snow cover was determined using SRTM DEM. Finally, the vanishing point of snow cover was predicted using the trend line of a linear function. Analysis was divided using a total of 23 images and 17 images during the dry season. Results show that snow cover area decreased by approximately $6.47km^2$ from $9.01km^2$ to $2.54km^2$, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Using the trend line result shows that the snow cover area decreased by approximately $0.342km^2$ in the dry season and $0.421km^2$ overall each year. In contrast, the annual increase in the minimum height of snow cover was approximately 9.848 m in the dry season and 11.251 m overall. Based on this analysis of vanishing point, there will be no snow cover 2020 at 95% confidence interval. This study can be used to monitor global climate change by providing the change in snow cover area and reference data when studying this area or similar areas in future research.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.703-714
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• 2017

This paper analyzes the impact of two climate change scenarios on flow rate and water quality of the Yongdam Dam and its basin using CE-QUAL-W2 and SWAT, respectively. Under RCP 4.5 and RCP 8.5 scenarios by IPCC, simulations were performed for 2016~2095, and the results were rearranged into three separate periods; 2016~2035, 2036~2065 and 2066~2095. Also, the result of each year was divided as dry season (May~Oct) and wet season (Nov~Apr) to account for rainfall effect. For total simulation period, arithmetic average of flow rate and TSS (Total Suspended Solid) and TP (Total Phosphorus) were greater for RCP 4.5 than those of RCP 8.5, whereas TN (Total Nitrogen) showed contrary results. However, when averaged within three periods and rainfall conditions the tendencies were different from each other. As the scenarios went on, the number of rainfall days has decreased and the rainfall intensities have increased. These resulted in waste load discharge from the basin being decreased during the dry period and it being increased in the wet period. The results of SWAT model were used as boundary conditions of CE-QUAL-W2 model to predict water level and water quality changes in the Yongdam Dam. TSS and TP tend to increase during summer periods when rainfalls are higher, while TN shows the opposite pattern due to its weak absorption to particulate materials. Therefore, the climate change impact must be carefully analyzed when temporal and spatial conditions of study area are considered, and water quantity and water quality management alternatives must be case specific.