• Journal of Advanced Marine Engineering and Technology
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• 제38권2호
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• pp.123-132
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• 2014

The maritime sector is advancing with dedicated endeavor to reduce greenhouse gas in addressing issues with regards to global warming. Since 01 January 2013, the International Maritime Organization (IMO) regulation mandatory requirement for Energy Efficiency Design Index (EEDI) has been in place and should be satisfied by newly-built ships of more than 400 gross tonnage and the Ship Energy Efficiency Management Plan (SEEMP) for all ships type. Therefore, compliance to this necessitates planning during the design stage whereas verification can be carried-out through an acceptable method during sea trial. The MEPC-approved 2013 guidance, ISO 15016 and ISO 19019 on EEDI serves the purpose for calculation and verification of attained EEDI value. Individual ships EEDI value should be lower than the required value set by these regulations. The key factors for EEDI verification are power and speed assessment and their synchronization. The shaft power can be measured by telemeter system using strain gage during sea trial. However, calibration of shaft power onboard condition is complicated. Hence, it relies only on proficient technology that operates within the permitted ISO allowance. On the other hand, the ship speed can be measured and calibrated by differential ground positioning system (DGPS). An actual test on a newly-built vessel was carried out to assess the correlation of power and speed. The Energy-efficiency Design Index or Operational Indicator Monitoring System (EDiMS) software developed by the Dynamics Laboratory-Mokpo Maritime University (DL-MMU) and Green Marine Equipment RIS Center (GMERC) of Mokpo Maritime University was utilized for this investigation. In addition, the software can continuously monitor air emission and is a useful tool for inventory and ship energy management plan. This paper introduces the synchronization and identification method between shaft power and ship speed for EEDI verification in accordance with the ISO guidance.

• Asian Journal of Atmospheric Environment
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• 제5권1호
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• pp.41-46
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• 2011

The port of Busan is the fifth busiest container port in the world in terms of total mass of 20-foot equivalent units transported. Yet no attempts have been made to estimate the greenhouse gas (GHG) emissions from the port of Busan by accounting for all port-related activities of the various transportation modes. With these challenges in mind, this study estimates the first activity-based GHG emissions inventory in the port of Busan, which consists of four transportation modes: marine vessels, cargo-handling equipment, heavy-duty trucks, and railroad locomotives. The estimation results based on the most recent and complete port-related activity data are as follows. First, the average annual transportation GHG emission in the port of Busan during the analysis period from 2000 to 2007 was 802 Gg $CO_2$-eq, with a lower value of 773 Gg $CO_2$-eq and an upper value of 813 Gg $CO_2$-eq. Second, the increase in the transportation-related GHG emissions in the port of Busan during the analysis period can be systematically explained by the amount of cargo handled ($R^2$=0.98). Third, about 64% of total GHG emissions in the port of Busan were from marine vessels because more than 40% of all maritime containerized trade flows in the port were transshipment traffic. Fourth, approximately 22% of the total GHG emissions in the port of Busan were from on-road or railroad vehicles, which transport cargo to and from the port of Busan. Finally, the remaining 14% of total GHG emissions were from the cargo handling equipment, such as cranes, yard tractors, and reach stackers.

• 상하수도학회지
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• 제25권5호
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• pp.691-697
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• 2011

In this study, by using the Water footprint technique, the water consumption by washing machines, which holds higher ranks in using water than any other electric appliances, was analyzed during their life cycle. The life cycle is defined as raw materials production step, manufacturing step, and using step. In raw materials production step, Input materials were researched by using LCI DB(Life Cycle Inventory Database) and the water consumption was calculated with consideration of approximately 65% Input materials which were based weight. In manufacturing step, the water consumption was calculated by the amount of energy used in assembly factories and components subcontractors and emission factor of energy. In using step, referring to guidelines on carbon footprint labeling, the life cycle is applied as 5 years for a washing machine and 218 cycles for annual bounds of usage. The water and power consumption for operating was calculated by referring to posted materials on the manufacture's websites. The water consumption by nation unit was calculated with the result of water consumption by a unit of washing machine. As a result, it shows that water consumption per life cycle s 110,105 kg/unit. The water consumption of each step is 90,495 kg/unit for using, 18,603 kg for raw materials production and 1,006 kg/unit for manufacturing, which apparently shows that the using step consume the most water resource. The water consumption by nation unit is 371,269,584tons in total based on 2006, 83,385,649 tons in both steps of raw material production and manufacturing, and 287,883,935 tons in using step.

• 대한치매학회지
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• 제16권3호
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• pp.72-77
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• 2017

Background and Purpose Although sleep disturbances are common and considered a major burden for patients with Alzheimer's disease (AD), the fundamental mechanisms underlying the development and maintenance of sleep disturbance in AD patients have yet to be elucidated. The aim of this study was to examine the correlation between regional cerebral blood flow (rCBF) and sleep disturbance in AD patients using technetium-99m hexamethylpropylene amine oxime single-photon emission computed tomography (SPECT). Methods A total of 140 AD patients were included in this cross-sectional study. Seventy patients were assigned to the AD with sleep loss (SL) group and the rest were assigned to the AD without SL group. SL was measured using the sleep subscale of the Neuropsychiatric Inventory. A whole-brain voxel-wise analysis of brain SPECT data was conducted to compare the rCBF between the two groups. Results The two groups did not differ in demographic characteristics, severity of dementia, general cognitive function, and neuropsychiatric symptoms, with the exception of sleep disturbances. The SPECT imaging analysis displayed decreased perfusion in the bilateral inferior frontal gyrus, bilateral temporal pole, and right precentral gyrus in the AD patients with SL group compared with the AD patients without SL group. It also revealed increased perfusion in the right precuneus, right occipital pole, and left middle occipital gyrus in the AD with SL group compared with the AD without SL group. Conclusions The AD patients who experienced sleep disturbance had notably decreased perfusion in the frontal and temporal lobes and increased rCBF in the parietal and occipital regions. The findings of this study suggest that functional alterations in these brain areas may be the underlying neural correlates of sleep disturbance in AD patients.

• 한국농공학회논문집
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• 제63권3호
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• pp.97-105
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• 2021

Most of the rural development projects for the welfare of residents are mainly new construction and remodeling projects for community buildings such as village halls and senior citizens. However, in the case of the construction industry, it has been studied that 23% of the total carbon dioxide emissions generated in Korea are generated in the building-related sector. (GGIC, 2015) In order to reduce the emission of environmental pollutants resulting from construction of rural community buildings, there is a need to establish a system for rural buildings by predicting the environmental impact. As a result of this study, the emissions of air pollutants from buildings in rural communities were analyzed by dividing into seven stages: material production, construction, operation, maintenance, demolition, recycling, and transportation activities related to disposal. As a result, 12 kg of carbon dioxide (CO), 0.06 kg of carbon monoxide (CO), 0.02 kg of methane (CH), 0.04 kg of nitrogen oxides (NO), 0.02 kg of sulfurous acid gas (SO), and non-methane volatile organics per 1m of buildings in rural communities It was analyzed that 0.02 kg of compound (NMVOC) and 0.00011 kg of nitrous oxide (NO) were released. This study proved that environmentally friendly design is possible with a quantitative methodology for the comparison of operating energy and air pollutant emissions through the design specification change based on the statement of the rural community building. It is considered that it can function as basic data for further research by collecting major structural changes and materials of rural community buildings.

• 한국환경복원기술학회지
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• 제25권3호
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• pp.17-28
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• 2022

We evaluated the effect of CO₂ offsetting by estimating changes in carbon uptake under various forest management scenarios and proposed forest management strategies to achieve carbon neutrality. Paju and Goseong, which have relatively large forest areas but different industrial characteristics, were selected for the study sites. The current state of forest distribution was analyzed using forest type maps and aerial photographs, and the amount of carbon uptake was calculated using the equation presented by the IPCC Guidelines for National Greenhouse Gas Inventories and the national emission/absorption coefficients from the Korea National Greenhouse Gas Inventory Report. As of 2015, the forest carbon absorption in Paju and Goseong was 49,931 t/yr and 94,225 t/yr, respectively, and the annual carbon absorption per unit area was 2.28 t/ha/yr and 2.16 t/ha/yr. Under the forest management scenarios, the annual maximum carbon absorption per unit area is estimated to increase to 5.68 t/ha/yr in Paju and 4.22 t/ha/yr in Goseong, and this absorption would increase further if urban forests were additionally created. Even if the current forests of Paju and Goseong are maintained as they are, emissions from electricity use can be sufficiently offset. However, by applying appropriate forest management strategies, emissions from sectors other than electricity use could be offset. This study can be applied to the establishment of carbon absorption strategies in the forest sector to achieve carbon neutrality.

• 한국농림기상학회지
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• 제20권1호
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• pp.88-100
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• 2018

벼 재배 논에서 발생하는 메탄 배출량은 농업 부문에서 가장 큰 온실가스 배출원이지만 자연 환경 및 경작 관행에 따라 지역차가 크게 나타난다. 이를 가시화하고 그 원인과 특성을 분석하기 위해, 2010 농림어업총조사 자료를 바탕으로 IPCC 지침에 따라 행정구역별 메탄 배출량을 산정하고, 그 결과를 지도로 제작하였다. 산출된 단위 면적 당 메탄 배출량의 전국 평균은 $380{\pm}74kg\;CH_4\;ha^{-1}yr^{-1}$로 나타났으며, 전반적으로 서부 지역이 동부 지역보다 더 높은 추세를 보였다. 지역차를 발생시키는 주요인은 $SF_o$ 보정인자이며, 여기에 경작 일수가 그 차이를 상쇄하거나 심화시키는 역할을 하는 것으로 나타났다. 현장에서 관측한 메탄플럭스 자료와 이론적으로 산출된 값들을 비교했을 때, 사례에 따라 크고 작은 차이를 보였다. 최근의 지구 온난화 경향을 반영하는 28의 메탄 GWP 값을 적용할 경우, 전국 논의 총 메탄 배출량은 8,742 천 톤 $CO_2eq$로서, 국가 온실가스 인벤토리 보고서에 제시된 10,048 천 톤 $CO_2eq$보다 13% 낮게 계산되었다. 이 연구에서 제작된 상세지도를 통해 메탄 배출량의 지역차를 명확히 인식할 수 있으며, 주요 조절 인자에 대한 분석은 실질적인 메탄 저감 대책을 마련하는 데 중요한 과학적 근거를 제공할 것으로 기대된다.

• 한국토양비료학회지
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• 제43권5호
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• pp.705-715
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• 2010

기후변화협약과 탄소배출권문제 등 환경에 관한 관심과 규제 등이 국제적 주요 관심 사항이 되고 있는 상황에서 농업생산에 대한 환경영향평가의 필요성이 대두되고 있다. 현재 우리나라는 환경부에서 시행하는 탄소성적표지제도 도입에서 농업분야의 LCI (Life Cycle Invemtory)database 부재를 이유로 1차 농산물을 대상에서 제외하고 있다. 따라서 농산물 탄소성적표지제도 도입을 위한 농업분야 LCI database에 대한 연구와 구축이 시급한 실정이다. 따라서 본 연구는 농업생산체계에 대한 LCA 적용을 위하여 시설상추를 대상으로 LCI 구축과 LICA 수행을 위한 방법론을 고찰하였다. LCA의 방법론은 ISO 14040 규격에 의거하여 연구 목적 및 범위, LCI분석 (전과정 목록분석), LCIA(전과정 영향평가), 해석의 단계로 구성되었다. 연구 목적은 시설 상추재배체계에 대한 LCA 방법론 적용이며, 기능단위는 상추 1 kg 생산으로 하였다. LCI 구축을 위한 영농 투입물과 산출물에 대한 데이터 수집은 농진청의 농축산물소득자료를 중심으로 관련 통계, 문헌자료를 통하여 수집하였다. LCI 구축을 위한 자료 수집결과 상추를 재배할 때 투입되는 물질 중 유기질 비료와 무기질 비료의 시용과, 식물보호제의 투입이 주요배출인자로 분석되었다. 농업활동으로 배출되는 주요 환경부하물질은 비료가 시용된 토양으로부터 대기로 발생되는 $N_2O$와 수계로 배출되는 ${NO_3}^-$, ${PO_4}^-$과 농약잔류물질로부터 발생되는 유기화학물질, 농기계에 쓰이는 화석연료 연소에 의한 대기오염물질 등 이었다. LCIA는 해외의 LCA 방법론과 LCA적용사례를 조사하여 농업분야 LCIA 방법론에 대하여 고찰하였다. LCIA는 분류화, 특성화, 정규화(일반화), 가중화의 4단계로 이루어지며, 이 중 분류화와 특성화는 의무절차이고, 정규화와 가중화는 선택사항이다. 해석단계는 LCI 분석결과와 LCIA 결과에 대하여 검증하고, 결과로부터 도출된 환경적 문제점과 개선안 등을 제시한다. LCA 수행에 사용하는 국내 소프트웨어는 지경부와 환경부에서 개발하여 보급하고 있는 'PASS'와 'TOTAL' 이다. 그러나 국내 프로그램에 적용되고 있는 환경영향평가 모델은 국외에서 개발한 기존모델들이다. 그러므로 보다 정확한 농업분야 LCA 분석이 가능하도록 추후 국내 농업환경에 적합한 영향평가 모델 및 특성화, 일반화, 가중화 계수의 선정 등이 이루어져야 할 것이다.

• 한국대기환경학회지
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• 제33권4호
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• pp.377-392
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• 2017

A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.

• 한국토양비료학회지
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• 제43권6호
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• pp.904-910
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• 2010

고추생산체계에 대한 탄소성적을 평가하기 위하여 노지재배 (건고추)와 시설재배 (풋고추)로 구분하여 LCI database 구축하고 전과정 영향평가를 통한 잠재적 환경영향을 평가하였다. LCI 구축을 위한 영농 투입량과 배출물 산정결과 고추 1 kg 생산의 비료 사용량은 노지재배가 2.55E+00 kg $kg^{-1}$ redpepper로 시설재배의 7.74E-01 kg $kg^{-1}$ greenpepper 보다 많았다. 농약 투입은 노지재배와 시설재배가 각각 5.38E-03 kg $kg^{-1}$ redpepper, 2.98E-04 kg $kg^{-1}$ greenpepper으로 노지재배에서의 농약투입량이 훨씬 높았다. 고추생산 중 대기로 배출된 $CO_2$, $CH_4$, $N_2O$의 합은 노지고추가 5.84E-01 kg $kg^{-1}$ redpepper, 2.81E+00 greenpepper로 시설고추가 높았다. 고추 생산체계에 대한 탄소원단위성적 산정결과 노지재배가 4.13E+00 kg $CO_2$-eq. $kg^{-1}$ redpepper, 시설재배 풋고추가 4.70E+00 kg $CO_2$-eq. $kg^{-1}$ greenpepper 였다. 시설재배 (풋고추)는 $CO_2$발생량이 많았고, 노지재배 (건고추)는 $CH_4$와 $N_2O$ 발생량이 많았다. 전과정 영향평가 결과 GWP의 특성화값은 노지재배가 4.13E+00 kg $CO_2$-eq. $kg^{-1}$, 시설재배가 4.70E+00 kg $CO_2$-eq. $kg^{-1}$이었고, GWP범주에 대한 기여도는 노지재배가 약 52%, 시설재배 약 48%로 거의 비슷하였다.