• 환경영향평가
• /
• 제9권4호
• /
• pp.349-362
• /
• 2000

In the study, the feasibility of landscape ecological measures as indices system for interpretation and evaluation of regional ecosystem was investigated through the application to Yongin City. Each patch metrics well showed the class structure and supplemented the class metrics, and class metrics also showed well the landscape structure and supplemented the landscape metrics. And the change analysis through subtraction of two set of landscape ecological measurement in two point of time showed the dynamic trends very well. One of the dynamic trends in Yongin City was the rapid fragmentation. While there was no landcover data on Yongin City, using Landsat data and remote sensing techniques were proved to be efficient and effective to produce the digital landcover data.

• 신재생에너지
• /
• 제18권2호
• /
• pp.60-72
• /
• 2022

The environmental, social, and governance (ESG) score is gaining recognition as important nonfinancial investment criteria. With climate change emerging as a global issue, energy companies must pay attention to the ESG impact on corporate performance. In this study, the ESG impact on the performance of energy companies was analyzed based on 23 companies selected from the S&P 500. The panel corrected standard error methodology was used. The Refinitiv ESG score was the independent variable, and financial performance metrics, such as Tobin's Q, return on assets, and return on equity, were the dependent variables. It was found that the ESG score is positively associated with long-term corporate value but not with short-term profitability in the electricity utility industry. Among the subcategories of ESG, the environmental and social scores also showed positive correlations with long-term corporate value. A direct incentive policy is recommended that can offset expenses for ESG activities to reduce carbon emission in the energy sector.

• Environmental Analysis Health and Toxicology
• /
• 제30권sup호
• /
• pp.3.1-3.11
• /
• 2015

Objectives This study presents the indicators and proxy variables for the quantitative assessment of green chemistry technologies and evaluates the relative importance of each assessment element by consulting experts from the fields of ecology, chemistry, safety, and public health. Methods The results collected were subjected to an analytic hierarchy process to obtain the weights of the indicators and the proxy variables. Results These weights may prove useful in avoiding having to resort to qualitative means in absence of weights between indicators when integrating the results of quantitative assessment by indicator. Conclusions This study points to the limitations of current quantitative assessment techniques for green chemistry technologies and seeks to present the future direction for quantitative assessment of green chemistry technologies.

• 환경영향평가
• /
• 제21권3호
• /
• pp.483-501
• /
• 2012

본 연구에서는 2005 - 2006년 기간 동안 국내 인공호의 환경영향평가를 위해 LEHA 다변수 생태모형(Lentic Ecosystem Health Assessment Model)을 청평호에 적용하였고, 생태 건강도 모델값을 산정하였다. LEHA 생태 평가모형은 생물학적 변수($B_p$), 물리적 변수($P_p$), 화학적 변수($C_p$)의 11개 주요 메트릭으로 구성되었고, 이를 통합하여 생태 건강도 등급을 평가하였다. 생물학적 변수($B_p$)는 수환경의 질적 저하에 따라서 감소하는 민감종 메트릭($M_2$, NSS) 및 충식종 메트릭($M_5$, % $I_n$)이 이용되었고, 두 메트릭 모델값은 각각 1.5%, 32.4%로서 낮게 나타났다. 반면, 내성종($M_3$, % $T_s$)과 잡식종 메트릭($M_4$, % $O_m$) 값은 43%, 62%로서 높게 나타나 호수생태계의 질적 저하가 확인되었다. 물리적 서식지 변수($P_p$)는 수변 식피율($M_9$, % $V_c$)로서 1차 조사에 비해 2차 조사에 높게 나타났으며, 상류에서 하류로 갈수록 메트릭 모델 값이 감소하는 것으로 나타났다. 이는 정수역의 증가로 서식환경의 단순화와 인근 수체에서 실시되고 있는 잦은 골재 채취로 인한 서식지의 하상구조 변경이 악영향을 준 것으로 사료되었다. 한편, 화학적 수질특성 변수($C_p$)는 수체의 이온(양이온/음이온) 특성을 나타내는 전기전도도($M_{10}$, $C_I$)와 부영양 상태를 평가하는 Chl-a의 부영양화 지수($M_{11}$, $TSI_{CHL}$)로서 메트릭 모델값은 계절별 변이는 크게 나타났고, 지점 간의 공간변이는 미미한 것으로 나타나, "양호상태"로 평가되었다. LEHA 다변수 모델에 의거한 청평호의 환경영향평가에 의하면, 생태 건강도 LEHA 모델값은 1차 조사에서 30.7로 "보통-악화상태", 2차 조사에서 28로 "악화상태"를 보여 계절 변이 특성을 보였다. 지점별 LEHA 모델값은 호수의 정수대(S5)에서 28로 최소치를 보였고, 그 외 지점들도 29 - 30으로 지점 간 미미한 차이를 보였다. 청평호의 종합적인 환경영향평가에 의하면, 이 화학적인 수질기준 측면에서는 "양호상태"를 보인 반면, 생물학적 기준에서는 "악화상태"를 보였는데, 이는 빈번한 준설작업으로 인한 물리적 서식지 교란이 영향을 준 것으로 사료되었다.

• 환경영향평가
• /
• 제21권3호
• /
• pp.391-407
• /
• 2012

The loss of connectivity and fragmentation of forest landscapes are seriously hindering dispersal of many forest-dwelling species, which may be critical for their viability and conservation by decreasing habitat area and increasing distance among habitats. For understanding their environmental impacts, numerous spatial models exist to measure landscape connectivity. However, general relationships between functional connectivity and landscape structure are lacking, there is a need to develop landscape metrics that more accurately measure landscape connectivity in whole landscape and individual patches. We reviewed functional and structural definition of landscape connectivity, explained their mathematical connotations, and applied representative 13 indices in 3 districts of Seoul having fragmented forest patches with tits, the threshold distance was applied 500m by considering the dispersal of tits. Results of correlation and principal component analysis showed that connectivity indices could be divided by measurement methods whether they contain the area attribute with distance or not. Betweenness centrality(BC), a representative index measuring distance and distribution among patches, appreciated highly stepping stone forest patches, and difference of probability of connectivity(dPC), an index measuring including area information, estimated integrated connectivity of patches. Therefore, for evaluating landscape connectivity, it is need to consider not only general information of a region and species' characteristics but also various measuring methods of landscape connectivity.

• 한국환경복원기술학회지
• /
• 제27권3호
• /
• pp.29-43
• /
• 2024

Legally protected species are one of the crucial considerations in the field of natural ecology when conducting environmental impact assessments (EIAs). The occurrence of legally protected species, especially 'Endangered Wildlife' designated by Ministry of Environment, significantly influences the progression of projects subject to EIA, necessitating clear investigations and presentations of their habitats. In perspective of statistics, a minimum of 30 occurrence coordinates is required for population prediction, but most of endangered wildlife has insufficient coordinates and it posing challenges for distribution prediction through modeling. Consequently, this study aims to propose modeling methodologies applicable when coordinate data are limited, focusing on Rodgersia podophylla, representing characteristics of endangered wildlife and northern plant species. For this methodology, 30 random sampling coordinates were used as input data, assuming little survey data, and modeling was performed using individual models included in BIOMOD2. After that, the modeling results were evaluated by using discrimination capacity and the reality reflection ability. An optimal modeling technique was proposed by ensemble the remaining models except for the MaxEnt model, which was found to be less reliable in the modeling results. Alongside discussions on discrimination capacity metrics(e.g. TSS and AUC) presented in modeling results, this study provides insights and suggestions for improvement, but it has limitations that it is difficult to use universally because it is not a study conducted on various species. By supporting survey site selection in EIA processes, this research is anticipated to contribute to minimizing situations where protected species are overlooked in survey results.

• 환경영향평가
• /
• 제32권6호
• /
• pp.407-418
• /
• 2023

본 연구는 한국의 주요 개발사업에서의 지형변화지표를 분석하고, 지형 변화 지표 사이의 상관관계를 분석하여 각 입지유형과 경사유형에 따른 기반 지형변화지표를 도출하였다. 이를 통해 미래 개발사업에 있어서 토지 이용 및 조성의 효율성을 높이며 환경에 대한 영향을 최소화하는 지속 가능한 개발 방향으로 기여하고자 한다. 또한, 연구 결과를 실제 현장에 적용하기 위해 국내 지형 관련 규정을 조사하고 해당 규정과 연구 분석 결과 간의 부합성과 활용 가능성에 대해 논의하였다. 이를 토대로, 향후 연구에 있어서 보다 정확하고 유용한 지형변화 지표의 활용을 위한 방안을 탐구하고자 한다. 결과적으로, 관광단지개발사업에서는 평지, 구릉지, 산지 순으로 지형변화가 주로 이루어지며, 구릉지와 산지에서의 지형변화도 평지에 비해 높은 것으로 분석되었다. 또한, 산업단지 조성사업에서는 급경사지(20°-30°)와 험준지(30°-40°), 도시개발 사업에서는 경사지(15°-20°), 체육시설 조성사업에서는 경사지와 급경사지, 관광단지 조성사업에서는 경사지(15°-20°)와 급경사지(20°-30°)에서의 지형변화지표 평균이 다른 경사도에 비해 높은 것으로 확인되었다. 연구 결과는 앞으로 국내 개발 사업에서 지형 훼손을 최소화하는 전략을 개발하는 데 기여할 수 있으며, 환경 영향 평가를 수행할 때 필요한 참고 자료로 활용될 수 있다.

• 한국BIM학회 논문집
• /
• 제9권1호
• /
• pp.32-41
• /
• 2019

As population in Sarasota and Manatee Counties, Florida in the United States is projected to increase, land use changes from land development happen continuously. The more land development means the more impervious surfaces and stormwater runoff to Sarasota Bay, which causes critical impact on the resiliency of the ecosystem. In order to decrease its impact on water quality and the ecosystem function of Sarasota Bay, it is important to assess the resilient status of communities that create negative impacts on the ecosystem. Three types of guiding principles of resiliency for Sarasota Bay watershed are suggested. To assess resiliency status, three indexes - vulnerability index, socio-economic index, and ecological index are developed and analyzed by using geographic information system for each census tract in the two counties. Since each indicator for vulnerability index, socio-economic index, and ecological index is measured with different metrics, statistical standardizing method - distance from the best and worst performers is used for this study to directly compare and combine them all to show total resilience score for each census tract. Also, the ten most and the ten least scores for the total resilience index scores are spatially distributed for better understanding which census tracts are most or least resilient. As Sarasota Watershed boundary is also overlaid, it is easy to understand how each census tract attains its resilience and how each census tract impacts to Sarasota Bay ecosystem. Based on results of the resiliency assessment several recommendations, guidelines, or policies for attaining or enhancing resiliency are suggested.

• 한국산업보건학회지
• /
• 제16권4호
• /
• pp.334-345
• /
• 2006

The objectives of this study were to analyze and compare 24 hrs personal exposure levels of MF at microenvironments such as home, school, educational institute, internet pc game room, transportation, and other places according to time activity patterns using various metrics for children attending the primary schools located near and away from the power lines, and to characterize the major microenvironments and impact factors attributed personal exposure level. The study was carried out for 44 children attending a primary school away from the lines(school A) and 125 children attending a school away from 154 kV power lines(school B), all who aged 12 years and were 6 grade, from July 2003 to December 2003. All participants filled in a questionnaire about characteristics, residence, use of electrical appliances and others. Children wore a small satchel in which EMDEX II and Lite (Enertech, Co. Ltd) and a diary of activity list for period of registration in 20 minutes blocks. All statistical calculations were made with the SAS System, Releas 6.12. The summary of results was presented below. First, about the characteristics of subjects, there no differences between two groups. The subject almost spent about 56 % of their time at home and about 20~25 % of their time at school. Fifty percent of children spent 2 hours at private educational institutes. Second, the personal exposure measurements of children in school B was statistically higher than those of children in school A by various metrics such as arithmetic mean, geometric mean, percentile(5, 25, 50, 75, 95), maximum, rate of change metric, constant field metric. The arithmetic and geometric mean magnetic fields during the time the children were at school B were 0.98 and $0.86{\mu}T$ and were about 23 times higher than those of children were at school A. In conclusion, the significant major determinants of personal exposure level is the distance from the power line to microenvironments.

• 한국환경과학회지
• /
• 제25권4호
• /
• pp.603-613
• /
• 2016

Fog may have a significant impact on road conditions. In an attempt to improve fog predictability in Jeju, we conducted machine learning with various data mining techniques such as tree models, conditional inference tree, random forest, multinomial logistic regression, neural network and support vector machine. To validate machine learning models, the results from the simulation was compared with the fog data observed over Jeju(184 ASOS site) and Gosan(185 ASOS site). Predictive rates proposed by six data mining methods are all above 92% at two regions. Additionally, we validated the performance of machine learning models with WRF (weather research and forecasting) model meteorological outputs. We found that it is still not good enough for operational fog forecast. According to the model assesment by metrics from confusion matrix, it can be seen that the fog prediction using neural network is the most effective method.