남극 장보고기지 건설 시 온실가스 배출량 산정

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system. The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis. The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 104 t CO2eq year−1, 64.9%) is the most significant for total GHG emissions (5.65 × 104 t CO2eq year−1) because a huge amount of CH4 (3.51 × 104 t CO2eq year−1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH4 emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions. This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

Abstract. Conferences, meetings and congresses are an important part of today's economic and scientific world. But the environmental impact, especially from greenhouse gas emissions associated with travel, can be extensive. Anthropogenic greenhouse gas (GHG) emissions account for the warming of the atmosphere and oceans. This study draws on the need to quantify and reduce greenhouse gas emissions associated with travel activities and aims to give suggestions for organizers and participants on possible ways to reduce greenhouse gas emissions, demonstrated on the example of the European Geography Association (EGEA) Annual Congress 2013 in Wasilkow, Poland. The lack of a comprehensive methodology for the estimation of greenhouse gas emissions from travel led to an outline of a methodology that uses geographic information systems (GIS) to calculate travel distances. The calculation of travel distances in GIS is adapted from actual transportation infrastructure, derived from the open-source platform OpenStreetMap. The methodology also aims to assess the possibilities to reduce GHG emissions by choosing different means of transportation and a more central conference location. The results of the participants of the EGEA congress, who shared their travel data for this study, show that the total travel distance adds up to 238 000 km, with average travel distance of 2429 km per participant. The travel activities of the participants in the study result in total GHG emissions of 39 300 kg CO2-eq including both outward and return trip. On average a participant caused GHG emissions of 401 kg CO2-eq. In addition, the analysis of the travel data showed differences in travel behaviour depending on the distance between conference site and point of origin. The findings on travel behaviour have then been used to give an estimation of total greenhouse gas emissions from travel for all participants of the conference, which result in a total amount of 79 711 kg CO2-eq. The potential for reducing greenhouse gas emissions by substituting short flights with train rides and car rides with bus and train rides is limited. Only 6 % of greenhouse gas emissions could be saved by applying these measures. Further considerable savings could only be made by substituting longer flights (32.6 %) or choosing a more central conference location (26.3 %).

Diversity in reservoir surface morphology and climate limits ability to compare and upscale estimates of greenhouse gas emissions

Wastewater treatment plants (WWTPs) using membrane bioreactor (MBR) technology have been considered a significant source of greenhouse gas (GHG) emissions. This study chose a small-scale wastewater treatment plant using MBR technology to estimate its potential for GHG emissions. The total GHG emissions from this wastewater treatment plant ranged from 2,802 to 11,946kg CO2 -eq/month within the 4-year study period, and they were mainly attributable to electricity consumption (79.94%) followed by chemical usages (17.13%) and on-site GHG emissions (2.93%). The on-site GHG emissions varied monthly, but most of them ranged from 80 to 160kg CO2 -eq/month. The aeration tank was an important operating unit for GHG emissions. Off-site GHG emissions mainly came from carbon dioxide (CO2 ) emissions resulting from electricity consumption. The results of this study provide useful information about the potential of GHG emissions from WWTPs using MBR technology and indicate that WWTPs can be sustainably managed. PRACTITIONER POINTS: Wastewater treatment plants have been considered a source of greenhouse gas emissions. Total greenhouse gas emissions from the wastewater treatment plants using membrane bioreactor were mainly attributable to electricity consumption. On-site greenhouse gas emissions were relatively insignificant in this study.

The traditional upscaling approach to greenhouse gas (GHG) emission estimates of inland waters is imprecise, but more precise methods based on environmental drivers are a longstanding challenge. Mexico lacks GHG emission estimates for its inland waters, and only sparse but scientifically validated information is available. This study provides the first GHG emission estimates from Mexican inland waters using 4275 GHG flux measurements from 26 distinctive waterbodies and one local and another global surface area dataset (INEGI and HydroLAKES). GHG emission factors were calculated and subsequently upscaled to estimate total national GHG emissions from the inland waters and compare to other emission measures based on mean global emission factors or size-productivity weighted (SPW) models. Mean (standard error) annual fluxes from all inland waters were 2.2 (5.3) kg CO2 m−2 yr−1, 0.6 (1.14) kg CH4 m−2 yr−1, and 1.0 × 10−3 (6.0 × 10−4) kg N2O m−2 yr−1. Estimates for natural waterbodies are annual average release rates between 74 (87) and 139 (163.23) Tg CO2eq while artificial waterbodies reach between 32 (2) and 21 (21) Tg CO2eq according to INEGI and HydroLAKES datasets, respectively. Considerable uncertainty was determined in the calculated mean emission factor, mostly for anthropogenic emissions. Waterbody area and chlorophyll a concentration were used as proxies to model CO2 and CH4 fluxes through regression analysis. According to SPW and IPCC models, computed mean annual CH4 emission factors were close to our estimates and exhibited a strong influence from eutrophication. In a likely scenario of increased eutrophication in Mexico, an increase in total net emissions from inland waters could be expected.

Disaggregated greenhouse gas emission inventories from agriculture via a coupled economic-ecosystem model

As a significant source of greenhouse gas emissions, objectively understanding the quantity of emissions from the livestock industry and their spatiotemporal evolution is crucial for advancing low-carbon and green development in regional livestock industries. Therefore, based on the Life Cycle Assessment (LCA) method, this study estimated greenhouse gas emissions from the livestock industry across 11 municipal regions in Jiangxi Province from 2002 to 2022, revealing the spatiotemporal characteristics of these emissions. The study also employed the Logarithmic Mean Divisia Index (LMDI) model to analyze the influencing factors. The results showed that (1) between 2002 and 2022, total greenhouse gas emissions from Jiangxi Province’s livestock industry exhibited an upward trend, increasing from 13.52 million tons to 21.27 million tons, with an average annual growth rate of 2.36%. (2) During the study period, the spatial patterns of super-high-emission and light-emission zones remained relatively stable, while medium and heavy emission zones showed dynamic evolution. (3) Intensity effects, agricultural structural effects, and rural population size played a suppressive role in livestock greenhouse gas emissions, while regional development levels and urbanization levels were key drivers of increased emissions. Therefore, governments should accelerate the implementation of clean production models, enhance technological innovation, promote pollution reduction at the source, and develop differentiated livestock development strategies based on regional resource endowments and demographic–economic characteristics.

Defining sustainable diets by comparing greenhouse gas emissions from different food groups: a systematic review

BackgroundHealth authorities are increasingly integrating environmental sustainability considerations into food-based dietary guidelines. However, concerns persist about the accuracy of the data used to assess environmental impacts, as well as the extent to which these guidelines are followed in practice. AimTo compare dietary greenhouse gas (GHG) emissions estimates using different top-down and bottom-up life cycle assessment (LCA) databases; and to estimate GHG emissions of food consumption within the ranges set for meat and dairy in recently proposed environmentally sustainable diets. MethodsDietary GHG emissions were estimated for participants in the 2019–2021 Icelandic National Dietary Survey (n = 822) using three publicly available LCA databases from Denmark, the US, and France. GHG emissions among participants whose consumption was aligned with the EAT-Lancet diet, the 2021 Danish food-based dietary guidelines and the 2023 Nordic Nutrition Recommendations were also quantified. ResultsThe mean dietary GHG emissions among participants were 6.3, 6.1, and 6.1 kg CO2-eq/day based on the Danish (top-down), US (bottom-up), and French (bottom-up) databases, respectively. The relative ranking of foods was also consistent across all three databases. For example, the relative contribution of total CO2-eq (% range for the three databases) was highest for red meat (39–51%), followed by dairy (10–17%) and beverages (9–13%). The contribution from plant-based foods (6–10%), seafood (4–11%), and poultry/eggs (<5%) was modest. The dietary habits of most participants (86%) were outside the ranges for meat and dairy consumption as set by the three sustainable diets. However, participants reporting consumption within the ranges for meat and dairy had mean GHG emissions ranging between 4.2 and 4.7 kg CO2-eq/day, depending on the diet. In comparison, the mean for participants not adhering to the sustainable diets was 7.7 kg CO2-eq/day. These results are higher than those reported in other Nordic and European studies, likely due to high consumption of lamb, beef, and dairy, and low consumption of plant-based food. ConclusionAll three LCA databases provided similar estimates for total dietary GHG emissions and relative ranking of different food groups. Based on current dietary habits in Iceland, adherence to environmentally sustainable diets would lead to a substantial reduction in dietary GHG emissions.

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

본 연구에서는 산재되어 있는 부산항 입출항 선박의 개별 활동도(정박 접안 특성) 및 선박제원 정보를 기존 항만운영정보시스템(PORT-MIS) DB에 연계 구축하기 위한 방법론을 제시하고, 연계 구축된 3가지 DB를 이용하여 18개월(2009.01~2010.06) 동안 부산항에 입출항한 선박의 온실가스 배출량을 산정하여 그 결과를 비교 분석하였다. 본 연구에서는 선박의 기본 활동도 변수만을 포함하고 있는 저해상도의 L-PORT-MIS DB에 각 선박의 정박시간 자료를 추가하여 중해상도의 M-PORT-MIS DB를 연계 구축하였으며, 각 선박의 온실가스 배출량에 직접적인 영향을 주는 엔진출력 등과 같은 선박제원 정보를 연계시켜 고해상도의 H-PORT-MIS DB를 구축하였다. 각 활동도 DB를 이용한 선박의 온실가스 배출량 산정결과, 선박 활동도의 해상도가 높아질수록 총 온실가스 배출량은 감소하는 것으로 분석되었다. 구체적으로 저해상도 및 중해상도의 선박 활동도 자료를 이용할 경우에는 과거에 집계화된 정박 및 접안 특성에 의존하여 온실가스 배출량이 과다 산정되는 반면, 고해상도의 선박 활동도 자료를 이용할 경우에는 각 선박의 개별 접안 정박 특성과 엔진출력이 고려되는바 H-PORT-MIS DB를 이용한 선박의 온실가스 배출량은 보다 신뢰성 높은 추정치로 판단된다. 이처럼 부산항을 입출항하는 개별 선박의 특성을 반영하여 온실가스 배출량을 산정했을 경우 그 추정치는 기존 추정치와 매우 달라질 수 있어 실효성 있는 온실가스 저감대책 수립을 위해서는 본 연구에서 제안한 DB의 연계 구축이 시급하다. This study presents the linkage method combining the existing Port Management Information System (PORT-MIS) DB with the scattered vessel activity data sets including the hotelling and maneuvering characteristics and specification information of the vessels arriving and departing from the port of Busan from January 2009 to June 2010. By linking the data sets, this study made three types of vessel activity databases: L-PORT-MIS DB with low-level vessel activities, M-PORT-MIS DB with medium-level vessel activities such as hotelling time, H-PORT-MIS DB with high-level vessel activities such as hotelling time, engine power, etc. The greenhouse gas (GHG) emissions estimation results show that total GHG emissions decreases when the detailed vessel activities are employed. This decrease in the total GHG emissions by the level of vessel activities implies that the GHG emissions from the low and medium level vessel activities are overestimated due to the aggregated hotelling/maneuvering times and speeds resulting from the past vessel specifications. Therefore, the GHG emissions using the H-PORT-MIS DB are more reliable GHG emission estimates in that the vessel specifications and the observed hotelling time of each vessel are employed in the estimation process. Hence, the high-level vessel activity dataset should be constructed to implement more suitable countermeasures for reducing the GHG emissions in the port of Busan.

The increasing global demand for vegetable oils has resulted in a significant increase in the area under oil palm in the tropics during the last couple of decades, and this is projected to increase further. The Roundtable on Sustainable Palm Oil discourages the conversion of peatlands to oil palm and rubber plantations. However, our understanding of the effects on soil organic carbon (SOC) stocks and associated greenhouse gas (GHG) emissions of land use conversion is incomplete, especially for mineral soils under primary forests, secondary forests, rubber and other perennial plantations in the tropics. In this review we synthesised information on SOC stocks and GHG emissions from tropical mineral soils under forest, oil palm and rubber plantations and other agroecosystems across the tropical regions. We found that the largest SOC losses occurred after land use conversion from primary forest to oil palm and rubber plantations. Secondary forest and pasture lands showed lower SOC losses as well as total GHG (CO2, N2O and CH4) emissions when converted to oil palm and rubber plantations. However, due to the limited data available on all three GHG emissions, there remains high uncertainty in GHG emissions estimates, and regional GHG accounting is more reliable. We recommend long-term monitoring of oil palm and other perennial plantations established on tropical mineral soils on different soil types and regions on SOC stock changes and total GHG emissions and evaluate appropriate management practices to optimise production and sustainable economic returns, and minimise environmental impact.

In this study, a comparative analysis was presented to detect the quota of urban and rural areas from total greenhouse gas (GHG) emissions in 26 selected countries of the Middle East and Central Asia (MECA) during 1994–2014. For this purpose, 18 independent variables such as land area, population characteristics, energy use and consumption, gross domestic product (GDP), CO2 emissions, etc., were considered in addition to one dependent variable of total GHG emissions. Statistical modeling to investigate GHG emissions was constructed comprising the quantitative procedures of the correlation test and clustering analysis, which can be considered as the fundamental basis of each econometric analysis. The GHG emissions from the urban (rural) sector of total countries in 2014 were obtained as 3313.4 (1135.6) Mt of CO2 equivalents, which is about 74.5% (25.5%) of the total GHG emissions (4449.1 Mt of CO2 equivalents) in the MECA region. The correlation test between GHG emissions and urban indicators revealed the significant records (R from 0.745 to 0.981) compared with rural indicators (R from 0.337 to 0.890). Based on the clustering analysis of the countries, Cluster A, comprised of three countries of Iran, Saudi Arabia, and Turkey, was categorized as countries with very high contributing to the total GHG emissions in the MECA region (~ 43.3%). The quotas of emissions from urban and rural sectors in the Cluster A were estimated as 83.1% and 16.9% from the total GHG emissions in 2014 (1921.3 Mt of CO2), while the same quotas were predicted as 73.1% and 26.9% from the total GHG emissions in 2030 (1921.3 Mt of CO2). This study carried out comprehensive research on the GHG emissions from the urban and rural areas in a crucial region of the world, which is faced with the rising growth of population, urbanization, globalization, high-energy use, and fuel consumption.

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

A procedure for estimating Greenhouse gas (GHG) emissions from a wastewater reclamation plant in Beijing was developed based on the process chain model. GHG emissions under two typical water reclamation treatment processes, the coagulation-sedimentation-filtration traditional process and advanced biological treatment process, were examined. The total on-site GHG emissions were estimated to be 0.0056 kg/m3 and 0.6765 kg/m3 respectively, while total off-site GHG emissions were estimated to be 0.3699 kg/m3 and 0.4816 kg/m3. The overall GHG emissions were 0.3755 kg/m3 under the type 1 treatment, which is much lower than that under the type 2 of 1.1581 kg/m3. Emissions from both processes were lower than that from the tap water production. Wastewater reclamation and reuse should be promoted as it not only saves the water resources but also can reduce the GHG emissions. Energy consumption was the most significant source of GHG emissions. Biogas recovery should be employed as it can significantly reduce the GHG emissions, especially under the type 2 treatment process. Considering the wastewater treatment and reclamation process as a whole, the type 2 treatment process has advantages in reducing the GHG emissions per unit of pollutant. This paper provides scientific basis for decision making.