• Title/Summary/Keyword: environmental quality

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Investigation and Analysis of Water Quality Environmental for Preparing a Natural Learning and Experimental Area in Bukchun and Boundary (북천지역 자연학습 체험단지 조성을 위한 수질 환경성 조사 및 분석)

  • 정종현;최석규;이종현;정덕영;이강우
    • Journal of Environmental Health Sciences
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    • v.28 no.2
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    • pp.11-22
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    • 2002
  • This study analyzes the river system and water quality conditions of Bukchun in order to establish a basic plan for Preparing a natural learning and experimental area of environmental ecosystem in Bukchun, Gyeongju. It also tries to establish an integrated plan for water management of Bukchun stream based on water contaminants. In addition, after analysing the water quality at 13 points during the non-rainy season, the effluent of municipal wastewater was of relatively better quality with I ~ II grade, below the water quality standard of the river, except in points near Samsung apartments. However, analysing the Hyeongsangang and the effluent of Bomunho and Duckdongdam in rainy season, the water quality was II ~ III grade according to environmental standard. The water Quality of those samples was strongly dependent of non-point source.

Environmental Quality in Indonesia: Disruption by Economic Agents

  • AZWARDI, Azwardi;SUKANTO, Sukanto;ADNAN, Nazeli;KURNIAWAN, Arika
    • Asian Journal of Business Environment
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    • v.12 no.1
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    • pp.17-24
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    • 2022
  • Purpose: This study aims to determine the effect of economic agents, such as the amount of government expenditure on the environment, households, manufacturing industry, and shipping activities; on environmental degradation in Indonesia. Research design, data, and methodology: This study is conducted with 264 observations from panel data of 33 provinces during 2010-2017. Environmental degradation is measured by using the environmental quality index collected from Indonesian Ministry of Forestry and Indonesian Central Bureau of Statistics. Three testing models are used to test the panel data, namely Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). Results: The research findings show that the amount of government expenditure on the environment, households, and shipping activities have a negative and significant effects on environmental degradation, while the number of manufacturing industry has positive and significant effect on environmental degradation. Unlike the previous studies, the result also shows that government expenditure on environmental has a positive and significant effect on environmental quality index. Conclusion: It can be concluded that even though Indonesian government spent a low budget on environment, their environmental regulation has succeeded both in reducing environmental degradation and increasing the environmental quality as indicated by Indonesian environmental quality index.

Development of Water Quality Modeling in the United States

  • Ambrose, Robert B;Wool, Tim A;Barnwell, Thomas O.
    • Environmental Engineering Research
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    • v.14 no.4
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    • pp.200-210
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    • 2009
  • The modern era of water quality modeling in the United States began in the 1960s. Pushed by advances in computer technology as well as environmental sciences, water quality modeling evolved through five broad periods: (1) initial model development with mainframe computers (1960s - mid 1970s), (2) model refinement and generalization with minicomputers (mid 1970s - mid 1980s), (3) model standardization and support with microcomputers (mid 1980s - mid 1990s), (4) better model access and performance with faster desktop computers running Windows and local area networks linked to the Internet (mid 1990s - early 2000s), and (5) model integration and widespread use of the Internet (early 2000s - present). Improved computer technology continues to drive improvements in water quality models, including more detailed environmental analysis (spatially and temporally), better user interfaces and GIS software, more accessibility to environmental data from on-line repositories, and more robust modeling frameworks linking hydrodynamics, water quality, watershed and atmospheric models. Driven by regulatory needs and advancing technology, water quality modeling will continue to improve to better address more complicated water bodies and pollutant types, and more complicated management questions. This manuscript describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions.

An Application of GIS to Water Quality Management (GIS를 이용한 하천수질관리)

  • Yang, Hyung-Jae;Lee, Yoo-Won;Kim, Min
    • Journal of Environmental Impact Assessment
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    • v.3 no.2
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    • pp.25-32
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    • 1994
  • This study was carried out as the Anyang creek water quality management using Geographic Information System (GIS) is the purpose of this pilot project to apply a GIS to environmental management field. Analysis of water quality data has been investigated using GIS with modeling of water quality management for the Anyang creek. The results of this study are summarized as follows: 1. The concentration of Mercury in sediment was increased rapidly nearby A26(Nightsoil Treatment Plant) and maximum was showed at A18 (Imgok bridge). Cadmium was increased rapidly at A35(Chulsan bridge). 2. River water quality management using visible computer system as GIS is effective to make decision for water quality management plan and database of environmental factors should be completed before applying GIS. 3. When water pollution accident is occurred in the river water system, pollutant source can be traced and analysed systematically using GIS to manage pollutants discharged into the river water system.

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Feasibility Study for the Location of Air Quality Monitoring Network in Daegu Area (대구지역 대기오염자동측정망 위치의 타당성 분석)

  • Choi, Sung-Woo;Lee, Jung-Beom
    • Journal of Environmental Science International
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    • v.20 no.1
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    • pp.81-91
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    • 2011
  • Air quality monitoring networks are very important facilities to manage urban air pollution control and to set up an environmental policy. Since air quality monitoring network of Daegu was allocated from 1980s to mid-90s, there is need to reevaluate it and relocated its site. This study was evaluated the position of Daegu air quality monitoring station by unit environmental sensitivity index, grid emission rate, CAI (Comprehensive Air-quality Index) point. The investigation domain covered an area of 16 $\times$ 24 km centered at the metropolitan area of Daegu with grid spacing of 2 km. The location of alternative air quality monitoring networks was selected through optimization and quintiles analysis of total score. The result showed that all things considered, new air quality monitoring network need to install grid numbers 10, 28, 36, 37, 46. We also recommand three scenarios of alternative air quality monitoring network when considering unit environmental sensitivity index, emission rate and CAI point.

Field Performance Evaluation of Candidate Samplers for National Reference Method for PM2.5 (PM2.5 국가기준측정장비 선정을 위한 비교 측정 연구)

  • Lee, Yong Hwan;Park, Jin Su;Oh, Jun;Choi, Jin Soo;Kim, Hyun Jae;Ahn, Joon Young;Hong, You Deog;Hong, Ji Hyung;Han, Jin Seok;Lee, Gangwoong
    • Journal of Korean Society for Atmospheric Environment
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    • v.31 no.2
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    • pp.157-163
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    • 2015
  • To establish National Reference Method (NRM) for $PM_{2.5}$, operational performance of 5 different commercial gravimetric-based $PM_{2.5}$ measuring instruments was assessed at Bulkwang monitoring station from January 23, 2014 to February 28, 2014. First, physical properties, design, and functional performance of the instruments were assessed. Evaluation was carried out to determine whether operating method for the instruments and levels of QA/QC activities meet the data quality objectives (DQOs). To verify whether DQOs were satisfied, reproducibility of QA/QC procedures, accuracy, relative sensitivity, limit of detection, margin of error, and coefficient of determination of the instruments were also evaluated. Results of flow rate measurement of 15 candidate instruments indicated that all the instruments met performance criteria with accuracy deviation of 4.0% and reproducibility of 0.6%. Comparison of final $PM_{2.5}$ mass concentrations showed that the coefficient of determination ($R^2$) values were greater than or equal to 0.9995, and concentration gradient ranged from 0.97 to 1.03. All the instruments satisfied criteria for NRM with the estimated precision of 1.47~2.60%, accuracy of -1.90~3.00%, and absolute accuracy of 1.02~3.12%. This study found that one particular type of measuring instrument was proved to be excellent, with overall evaluation criteria satisfied.

Environmental Impact Assessment and Environmental Monitoring in Korea (한국에서의 환경영향평가와 환경측정)

  • Kang, In-Goo;Kim, Myung-Jin
    • Journal of Environmental Impact Assessment
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    • v.4 no.3
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    • pp.31-39
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    • 1995
  • Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.

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Assessment of Trophic State for Daecheong reservoir Using Landsat TM Imagery Data (Landsat TM 영상자료를 이용한 대청호의 영양상태 평가)

  • Han, E.J.;Kim, K.T.;Jeong, D.H.;Cheon, S.Y.;Kim, S.J.;Yu, S.J.;Hwang, J.Y.;Kim, T.S.;Kim, M.H.
    • Journal of Environmental Impact Assessment
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    • v.7 no.1
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    • pp.81-91
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    • 1998
  • The objective of this study was to use remotely sensed data, combined with in situ data, for the assessment of trophic state for Daecheong reservoir. Three Landsat TM(Thematic Mapper) imagery data were processed to portray trophic state conditions. The remotely sensed data and the measured data were obtained on 20 June 1995. Regression models have been developed between the chlorophyll-a concentration and reflectance which was converted to Landsat TM digital data. The regression model was determined based on the correlation coefficient which was higher than 0.7 and was applied to the entire study area to generate a distribution map of chlorophyll-a and trophic state. The equation, providing estimates of chlorophyll-a concentration, represented the year-to-year spatial variation of trophic zones in the reservoir. Satellite remote sensing data derived from Landsat TM had been successfully used for trophic slate mapping in Daecheong reservoir.

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Comparison of the Real-time Measurements for PM2.5 and Quality Control Method (PM2.5 자동측정장비 비교 및 정도관리 방안)

  • Park, Mikyung;Park, Jin Su;Jo, Mira;Lee, Yong Hwan;Kim, Hyun Jae;Oh, Jun;Choi, Jin Soo;Ahn, Joon Young;Hong, You Deog
    • Journal of Korean Society for Atmospheric Environment
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    • v.33 no.6
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    • pp.616-625
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    • 2017
  • Measurements using five real-time particle samplers were compared to measurements using three NRM (National Reference Method system) filter-based samplers(Gravimetric method) at Incheon, Korea, between May and August, 2014. The purpose of this study was to suggest the quality assurance/quality control (QA/QC) method of each instrument for use in a real-time continuous particle sampler to measure the mass of airborne particles with an aerodynamic diameter less than $2.5{\mu}m$ ($PM_{2.5}$). Five real-time particle samplers of BAM1020, FH62C_14, TEOM, PM-711 and SPM-613 were evaluated by comparing its measured 23 hr average $PM_{2.5}$ concentrations with those measured with NRM filter-based samplers simultaneously. The parameters(e.g. Inlet heating condition, Slope factor, Film response, Intercept, Background, Span value) of the real-time samplers were optimized respectively by conducting test performance evaluation during 7 days in field sampling. For example, inlet heating temperature of TEOM sampler controls $35{\sim}40^{\circ}C$ to minimize the fluctuation of the real-time measurement data and background value of BAM1020 is the key factor affecting the accuracy of $PM_{2.5}$ mass concentration. We classified the $PM_{2.5}$ concentration according to relative humidity (80%) to identify water absorbed in aerosols by measuring the ${\beta}$-ray samplers(BAM1020, FH62C_14) and TEOM. ${\beta}$-ray samplers were not strongly affected by relative humidity that the difference of the average $PM_{2.5}$ concentration was about 5%. On the other hand, The TEOM sampler overestimated $PM_{2.5}$ mass concentration about 15% at low relative humidity (<80%).