Estimating Transportation-Related Greenhouse Gas Emissions in the Port of Busan, S. Korea

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.

Greenhouse gas (GHG) emissions were a major causal factor of global warming that further impacts climate change. This study aimed to inventory the sources of greenhouse gas emissions from the livestock sector in Bangka Belitung. The GHG emissions in the livestock sector was calculated using the Tier-2 method based on guidance from IPCC 2006. Secondary data were collected from multiple sources, including livestock population, enteric CH4 emission factors, and the production and management of local livestock manure. The results of the calculation of GHG emissions in Bangka Belitung from 2018-2022 showed a significant increase from 25.54 to 33.32 Gg CO2 eq, with an accumulation of 139.43 Gg CO2 eq over five years. Beef cattle became the largest contributor to GHG emissions, with enteric fermentation CH4 emissions of 104.34 Gg CO2 eq, accounting for 91.90% of the total CH4 emissions from enteric fermentation sources and 74.84% of the total GHG emissions in Bangka Belitung. The largest contributor to GHG emissions was 78.62% or 109.62 Gg CO2 eq from enteric fermentation sources of ruminants, while N2O emissions from manure management reached 29.10 Gg CO2 eq, and the smallest CH4 emissions were 0.70 Gg CO2 eq, sourced from livestock manure

Navigating Sustainability through Greenhouse Gas Emission Inventory: ESG Practices and Energy Shift in Bangladesh’s Textile and Readymade Garment Industries

Spatiotemporal Trends of the Carbon Footprint of Sugar Production in China

The shipping industry, particularly containerized cargo transport, plays a vital role in global trade, but it is also a significant contributor to greenhouse gas (GHG) emissions. With increasing pressure to reduce carbon footprints and achieve sustainability targets, the U.S. maritime sector is seeking innovative solutions to lower its environmental impact. Optimizing fuel usage, improving operational efficiencies, and adopting alternative fuels are essential strategies to decarbonize maritime transport. However, these complex challenges require sophisticated tools for simulating and analyzing different fuel and routing strategies. The US Department of Energy, Advanced Research Projects Agency - Energy funded a project to focuses on developing an advanced decision-support tool to optimize fuel deployment and intermodal freight routing for domestic container shipping in the U.S., aiming to reduce GHG emissions and improve operational efficiency. This project aims to develop an advanced decision-support tool that leverages modeling and simulation to optimize fuel deployment and intermodal freight route planning for domestic container shipping across U.S. maritime corridors. The tool's central goal is to simulate and assess vessel operations, considering both environmental impact and operational efficiency, with a focus on reducing greenhouse gas (GHG) emissions through intelligent fuel selection and optimized routing strategies. The project will integrate traditional oil-based vessel technologies with alternative/Low emission fuels, specifically methanol and ammonia/hydrogen, to evaluate these technologies' potential for decarbonizing the maritime sector. The modeling scope encompasses several critical aspects of container shipping operations: it will simulate container and containership movements across key U.S. maritime routes, including both open sea and inland waterways (e.g., from Los Angeles to Seattle). The simulation will track vessel movements in real-time, incorporating key operational events such as departures, arrivals, refueling, and port dwell times. The model will identify and analyze a range of domestic vessel types, initially using baseline information on oil-powered ships and comparing them with vessels using alternative fuels. This comparison will allow for an evaluation of energy consumption, operational efficiency, and emissions reductions achievable with different fuel mixes. A key feature of the model will be its ability to estimate energy consumption and emissions under various operating conditions. The model will take into account a broad range of factors, such as cargo weight, vessel type, sea currents, wind conditions, and route specifics to generate highly accurate simulations of energy usage and emissions per voyage. By using advanced modeling techniques, the tool will create a detailed reduced-order model, informed by real-world operational data, which can be generalized and applied across various domestic corridors and routes. This will allow for scalable insights and flexible application, making the tool useful for a variety of real-world shipping scenarios. The role of advanced modeling and simulation is crucial in enabling the detailed analysis required to understand complex maritime operations. The model will simulate dynamic operational events (such as docking, refueling, or delays) and intermodal transport interactions, optimizing freight routing across different transport modes (water, rail, and truck) to minimize overall GHG emissions. This approach allows for a comprehensive, whole-system analysis that considers both direct emissions from maritime transport and indirect emissions from associated modes of transport. Moreover, the model will interface with external systems simulators, to incorporate data on port-to-port container origin-destination (OD) flows, port storage, and dwell times. These external inputs will be integrated into the model to ensure that port operations, cargo handling, and intermodal logistics are optimized for efficiency and emissions reduction. This integration of multiple data sources and transport modes will enable the simulation to reflect the complexities of the real-world intermodal network, offering insights on how best to allocate freight across water, rail, and road to achieve the lowest possible emissions. Through the use of advanced modeling and simulation, the tool will generate actionable insights to guide policy makers, shipping operators, and environmental regulators in their efforts to decarbonize U.S. domestic shipping. The ability to simulate and compare different fuel types, vessel configurations, and routing strategies will help stakeholders make data-driven decisions that balance economic feasibility with environmental sustainability. Ultimately, the tool will help identify pathways to reduce the carbon footprint of domestic container shipping, offering a roadmap for adopting cleaner, more efficient maritime transport practices while improving operational performance. By enabling the detailed modeling and simulation of complex maritime systems, this project will contribute significantly to the development of sustainable maritime transport policies and technologies, providing a critical resource for advancing the transition to a low-carbon economy in the U.S. shipping sector.

Reducing greenhouse gases (GHGs) emissions plays an important role in preventing global warming and climate change. It is generally known that domestic wastewater management activities are significant contributors to the emissions due to its biological process that produces methane, nitrous oxide, and carbon dioxide. Various studies related to GHGs emissions from this sector have been conducted. However, only limited studies focused on the on-site sewage treatment. Since 72% of total existing wastewater treatment facilities in Indonesia are on-site systems, this study attempted to estimate GHGs emissions from each component in the system using the IPCC method. Depok City was chosen as the study case and the estimation was limited to on-site treatment tank, wastewater collection tank, and fecal sludge treatment system. Our study estimated that the total annual emissions from the on-site sewage system in Depok City were 232.45 Gg CO2eq, consisted of 232.39 Gg CO2eq of on-site emissions and 0.0662 Gg CO2eq of off-site emissions. Among the system component, direct emissions from the on-site treatment such as septic tanks is the highest contributor to the total emission (70% followed by direct emission from fecal sludge treatment plant (19%). Through scenario evaluations, this study suggests that converting private septic tanks into the communal type is the most effective strategy in reducing total GHGs emissions from on-site wastewater treatment systems.

ObjectivesTo assess greenhouse gas (GHG) emissions from a regional hospital laundry unit, and model ways in which these can be reduced.DesignA cradle to grave process-based attributional life-cycle assessment.SettingA large hospital...

Mortality, Greenhouse Gas Emissions, and Consumer Cost Impacts of Replacing Short Car Trips with Cycling: A Health Impact Assessment Study

Shared mobility options, such as car sharing, are often claimed to be more sustainable, although evidence at an individual or city level may contradict these claims. This study aims to improve understanding of the effects of car sharing on transport-related emissions at an individual and city level. This is done by quantifying the greenhouse gas (GHG) emissions of the travel habits of individuals before and after engaging with car sharing. The analysis uses a well-to-wheel (WTW) approach, including both business-to-consumer (B2C) and peer-to-peer (P2P) car-sharing fleets. Changes in GHG emissions after engaging in car sharing vary among individuals. Transport-related GHG emissions caused by car-free individuals tend to increase after they engage in car sharing, while emissions caused by previous car owners tend to fall. At the city level, GHG emissions savings can be achieved by using more efficient cars in sharing systems and by implementing greener mobility policies. Changes in travel habits might help to reduce GHG emissions, providing individuals migrate to low-carbon transport modes. The findings can be used to support the development and implementation of transport policies that deter car ownership and support shared mobility solutions that are integrated in city transport systems.

The influence of crop and chemical fertilizer combinations on greenhouse gas emissions: A partial life-cycle assessment of fertilizer production and use in China

Population growth in Pekalongan City leads to increased community activities, which in turn raises Greenhouse Gas (GHG) emissions in the transportation, waste, and domestic sectors. This study aims to inventory and project GHG emissions, develop reduction strategies, and design regulations to mitigate these emissions. The method used to inventory GHG emissions from the transportation sector is based on Tier 1 and 2 approaches, while the waste and domestic sectors use the Intergovernmental Panel on Climate Change 2006 method with Tier 1 accuracy. The results of the inventory and projection show that GHG emissions in the transportation sector will reach 455.084 Gg CO2eq by 2032. Strategies to reduce these emissions include optimizing green open spaces (RTH), rejuvenating public transportation, and developing a Bus Rapid Transit (BRT) system, which collectively are expected to reduce emissions by 1.23%. In the waste sector, projected emissions amount to 27.88 Gg CO2eq. Planned strategies, such as increasing waste service coverage to the Degayu Landfill, optimizing waste facilities, and utilizing biogas, can reduce emissions by 15.85%. In the domestic sector, projected emissions are 27.97 Gg CO2eq, with the strategy of developing community-based livestock biogas expected to reduce emissions by 0.22%

BackgroundPolicies to mitigate climate change by reducing greenhouse gas (GHG) emissions can yield public health benefits by also reducing emissions of hazardous co-pollutants, such as air toxics and particulate matter. Socioeconomically disadvantaged communities are typically disproportionately exposed to air pollutants, and therefore climate policy could also potentially reduce these environmental inequities. We sought to explore potential social disparities in GHG and co-pollutant emissions under an existing carbon trading program—the dominant approach to GHG regulation in the US and globally.Methods and findingsWe examined the relationship between multiple measures of neighborhood disadvantage and the location of GHG and co-pollutant emissions from facilities regulated under California’s cap-and-trade program—the world’s fourth largest operational carbon trading program. We examined temporal patterns in annual average emissions of GHGs, particulate matter (PM2.5), nitrogen oxides, sulfur oxides, volatile organic compounds, and air toxics before (January 1, 2011–December 31, 2012) and after (January 1, 2013–December 31, 2015) the initiation of carbon trading. We found that facilities regulated under California’s cap-and-trade program are disproportionately located in economically disadvantaged neighborhoods with higher proportions of residents of color, and that the quantities of co-pollutant emissions from these facilities were correlated with GHG emissions through time. Moreover, the majority (52%) of regulated facilities reported higher annual average local (in-state) GHG emissions since the initiation of trading. Neighborhoods that experienced increases in annual average GHG and co-pollutant emissions from regulated facilities nearby after trading began had higher proportions of people of color and poor, less educated, and linguistically isolated residents, compared to neighborhoods that experienced decreases in GHGs. These study results reflect preliminary emissions and social equity patterns of the first 3 years of California’s cap-and-trade program for which data are available. Due to data limitations, this analysis did not assess the emissions and equity implications of GHG reductions from transportation-related emission sources. Future emission patterns may shift, due to changes in industrial production decisions and policy initiatives that further incentivize local GHG and co-pollutant reductions in disadvantaged communities.ConclusionsTo our knowledge, this is the first study to examine social disparities in GHG and co-pollutant emissions under an existing carbon trading program. Our results indicate that, thus far, California’s cap-and-trade program has not yielded improvements in environmental equity with respect to health-damaging co-pollutant emissions. This could change, however, as the cap on GHG emissions is gradually lowered in the future. The incorporation of additional policy and regulatory elements that incentivize more local emission reductions in disadvantaged communities could enhance the local air quality and environmental equity benefits of California’s climate change mitigation efforts.

It is essential to abstract the key information from accounting results of greenhouse gas (GHG) emissions because it can provide a highly generalized and clear picture of GHG emissions, which is especially helpful for the public and policy makers. To clearly display the composition of GHG emissions, the concept of spectrum analysis is introduced and defined in this paper. Next, a multilayer analysis framework for national GHG emissions was proposed, which is represented by a pyramid of three layers: total emissions (first layer), emissions decomposed by gas type or sector (second layer), and emissions decomposed by both gas type and sector (third layer). Based on the analysis results from the first to third layers, the main compositional information of national GHG emissions was gradually summarized and analyzed until a spectrum of GHG emissions was acquired. The spectrum of GHG emissions displays the compositional structure of national GHG emissions in the different layers, which is helpful in identifying priorities for emissions reduction. A case study of Germany’s GHG emissions during 1990–2012 was conducted, which indicated that CO2 and the energy sector were the biggest contributors to the total GHG emissions. Some suggestions for reducing GHG emissions are offered based on the obtained results. And the potential development of spectrum analysis for GHG emissions is also expected from aspects of both research and technology.

Hidden greenhouse gas emissions for water utilities in China's cities

Whole-farm systems modelling of greenhouse gas emissions from pastoral suckler beef cow production systems