Bottom-up Analysis of GHG Emissions from Shipbuilding Processes for Low-carbon Ship Production in Korea

PDF HTML阅读 XML下载 导出引用 引用提醒 西安市温室气体排放的动态分析及等级评估 DOI: 10.5846/stxb201305271199 作者: 作者单位: 陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院,陕西师范大学旅游与环境学院 作者简介: 通讯作者: 中图分类号: 基金项目: 陕西省软科学研究计划项目(2012KRM48);国家社会科学基金项目(14XKS019);黄土高原土壤侵蚀与旱地农业国家重点实验室基金(10501-1214) Dynamic analysis of greenhouse gas emission and evaluation of the extent of emissions in Xi'an City, China Author: Affiliation: College of Tourism and Environmental Sciences, Shaanxi Normal University,,,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:为了解西安市温室气体排放的动态规律和排放水平,基于全球标杆的温室气体排放等级评价方法,并采用国际公认的《2006年IPCC国家温室气体清单指南》和基于IPCC的《省级温室气体编制指南》推荐的方法对西安市的温室气体排放进行了动态分析和排放等级评估。结果表明,从1995年到2011年,西安市温室气体排放呈快速上升趋势,16年间温室气体排放量从1207.16×104t 上升为3934.17×104t,年均增高7.66%。增幅最高的是水泥温室气体(年均增高11.75%)、废弃物(8.77%)和能源(7.63%),农业年均降低1.74%,林业固碳年圴增加3.56%。从温室气体构成看,能源占80.13%-90.55%,水泥占1.75%-7.49%,农业占1.86%-8.01%,林业固碳占-2.58%—5.22%,废物处理占7.52%-16.38%。可见能源消费的增加是导致西安市温室气体排放增长的主要原因,林业碳汇能力有待提高。万元GDP温室气体排放不断降低,说明西安市碳减排方面的科技进步在不断提高。人均、单位面积温室气体排放量和排放指数增速很快,年均增幅分别达5.84%、7.66%和6.84%。西安市温室气体排放等级持续增高,16年间从较低等级(Ⅰc)上升为中下等级(Ⅱa),目前距应对气候变暖目标(Ⅰb)已高出两个亚级,温室气体排放增高的趋势不容忽视。 Abstract:Global warming caused by greenhouse gas emission may cause severe environmental and social problems. Greenhouse gas accounting has become a hotly debated research topic. Internationally, some research has been undertaken on greenhouse gas accounting and some progress has been made; however, there are many shortcomings in this field. The main problem is that current research is mainly focused on carbon emission, particularly carbon emission from fossil fuel combustion, and is less involved in carbon fixation and ways of assessing regional carbon emission levels. In addition, the actual emission figures for greenhouse gases nationally and regionally in China were unknown. Although much research relates to carbon emission, the results are difficult to compare owing to inconsistent research methods and standards. Xi'an City, a historical and cultural tourist city in China, lies in the radiation center of the Guan-Tian economic zone. It is the economic, cultural, education, manufacturing and high-tech industry hub of northwest China. Xi'an will be an international metropolis in China in the near future. However, research relating to the greenhouse gas footprint in Xi'an is scarce. In this paper, the author proposed an evaluation system for greenhouse gas (GHG) emission to the level of global benchmarking using the methods recommended by the 2006 IPCC Guidelines for National Greenhouse Gas Inventories and the Chinese Guidelines for Provincial Greenhouse Gas Inventories, and using this a dynamic analysis of GHG emission and evaluation of the extent of GHG emission in Xi'an City was performed. The results showed that, from 1995 to 2011, GHG emission showed a rapidly rising trend in Xi'an City, increasing from 1207.16×104t to 3934.17×104t, which represented an average annual increase of 7.66%. The largest increase was for cement (an average annual increase of 11.75%), waste (8.77%) and energy (7.63%) GHG. Agricultural GHG emission showed an annual reduction of 1.74%, while forestry carbon sequestration showed an annual average increase of 3.56%. In a breakdown of emissions, energy GHG accounted for 80.13%-90.55%, cement GHG for 1.75%-7.49%, agricultural GHG for 1.86%-8.01%, forestry carbon sequestration for -2.58%—5.22%, and waste treatment GHG for 7.52%-16.38%. An increase in energy consumption is the main cause of the increase in GHG emission in Xi'an City, and forestry carbon sequestration capacity needs to be improved. In Xi'an City, the GHG emission per 10,000 Yuan GDP was constantly decreasing, and progress in the science and technology of carbon emission has continuously improved. The GHG emission per capita, per unit area and per carbon emission index has increased very quickly, showing an average annual increase of 5.84%, 7.66% and 6.84% respectively. The carbon emission state in Xi'an City has increased continually from a low level (Ⅰc) to a middle level (Ⅱa), which was an increase of two sub-grades and which was two grades higher than the target set for the control of global climate warming. The increasing trend in carbon emission cannot be ignored. 参考文献 相似文献 引证文献

In recent years, the issue of climate change has gained significant attention and become a focal point of discussion in various sectors of civil society. Governments, individuals, and scientists worldwide are increasingly concerned about the observed changes in climate patterns, often attributed to the rising levels of greenhouse gases. In this context, the main objective of this study is to assess the greenhouse gas emissions associated with the railway system in the state of Pernambuco, Brazil, and compare them with other national case studies, aiming to obtain greenhouse gas emission parameters specific to the railway system and propose mitigation models to address this environmental impact in the air. To achieve this goal, a comprehensive life cycle assessment (LCA) methodology was employed to examine the life cycle of the Pernambuco Metro. This involved conducting an inventory of resource inputs and emissions using actual observed data. Additionally, a comparative analysis of greenhouse gas emissions across different urban rail transport systems is presented to provide valuable contextual insights. The study findings reveal that the total greenhouse gas emissions from the Pernambuco rail system amount to 6170.54 t CO2e. Considering a projected total service life of 50 years, the estimated greenhouse gas emissions for the entire life cycle of the system’s operation and maintenance reach 308,550 t CO2e. The interdisciplinary nature of this research highlights the significance of studying the atmospheric effects of the Pernambuco railway system as a crucial parameter for designing strategies and technologies aimed at reducing air pollution within the region. Through quantifying and analyzing the greenhouse gas emissions of the Pernambuco rail system, this study provides valuable insights that contribute to addressing concerns related to climate change and promoting sustainable practices. It underscores the importance of developing effective strategies to mitigate air pollution and facilitates informed decision-making for the future of urban transportation systems.

Global economic development has highlighted the issue of climate change, which is one of the most important environmental issues plaguing human beings. It is widely agreed that excessive greenhouse gas (GHG) emissions are important factors contributing to global warming. Many countries have formulated corresponding GHG emission reduction plans to deal with climate change issues. An important GHG emission source is released from sewage-sludge treatment systems. However, there has not been a comprehensive quantitative GHG emissions evaluation system in the case of sewage-sludge treatment systems, due to multiple emission sources, complex processes, and different standards. In previous studies, the Guidelines for National Greenhouse Gas Inventories (Intergovernmental Panel on Climate Change, IPCC, 2006) and Chinese Greenhouse Gas Inventory (National Center for Climate Change Strategy and International Cooperation, NCSC, 2005) were widely applied to estimate GHG emissions from sewage-sludge treatment. However, IPCC does not consider CO2 emissions from sewage treatment, and NCSC does not consider CO2 emissions from the sewage treatment and N2O emissions from sludge treatment. Therefore, the following have been conducted in this study: (1) A GHG estimation model basing on Life Cycle Thinking (LCT) was constructed, and the research objects were CH4, N2O, and CO2 that were produced by the sewage-sludge treatment system. The estimation model of CO2 and N2O, which were ignored in the IPCC report, were analyzed and discussed. The models of the GHG emission estimation were summarized and improved in the urban sewage-sludge treatment system under the different sewage-sludge treatment process scenarios. (2) The GHG emission load of major urban sewage-sludge treatment processes was analyzed, and the level and key links of environmental impacts generated by different processes were identified. This helps to understand and compare the environmental impacts of different treatment processes and provides suggestions for the sustainable development of wastewater treatment processes. (3) The GHG emission characteristics of nine scenarios of different sewage-sludge treatment processes were analyzed, and the environmental impacts caused by energy consumption and chemicals consumption were studied. Consequently, the sewage-sludge treatment process under low carbonization and low environment impact were proposed.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

ABSTRACTIncreasing population in many countries consumed natural resources and generates secondary product. These secondary products may be in the form of pollutants and liberated in the atmosphere. In this paper, an analysis was performed for green house gas (GHG) emission from municipal solid waste disposal for Faridabad city, India. Land filling and waste-to-energy methods were considered for GHG emission and analysis was performed based on Intergovernmental Panel on Climate Change (IPCC) model. GHG emission and linear pinch analysis (LPA) were performed based on the 50% collection efficiency in Faridabad city over a period of 10 years (2015–2025). Two scenarios of emission forecasting, such as land filling and waste to energy (incineration), were incorporated in this study. Hybrid analysis was presented for emission forecasting and emission reduction to develop a sustainable municipal solid waste management system for Faridabad. A target of 20% and 30% reduction in GHG emission was formulated with the help of LPA. The result shows that GHG in Faridabad city has been continuously changed from 2015 to 2025.The result represented here could be a decision support matrix for municipalities to develop integrated municipal solid waste management system for upcoming smart cities in India. Moreover, another novelty of this study reflects that cities having approximate same population, waste characteristics, and waste management technology could adopt this model for saving of GHG inventory and target-based reduction.

Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., GHG emission factor) as a random variable did not alter the mean; however, it yielded higher uncertainty of GHG emissions compared to the case when treating a coefficient constant. The non-parametric bootstrap method reduces the variance of GHG. A mathematical model for estimating GHG emissions should treat the GHG emission factor as a random variable. When the estimated probability density function (PDF) of the original dataset is incorrect, the nonparametric bootstrap method, not the parametric MCS method, should be the method of choice for the uncertainty analysis of GHG emissions.

At present, urban greenhouse gas (GHG) emissions from different wastewater treatment stages are attracting increasing attention. Based on the Guidelines of the China Greenhouse Gas List Compilation (Trial) and the IPCC National Greenhouse Gas List Guidelines in 2006, this paper evaluated urban GHG emissions from wastewater treatment in China from 2011 to 2020. The contribution rates of GHG emissions to the total GHG emissions were calculated for the different wastewater treatment stages. The variations in annual GHG emissions and differences in GHG emissions among different regions and provinces were also analyzed. The total amount of equivalent CO2 emissions reaches 1478.51 million tons, and the annual average amount of equivalent CO2 emissions from 2011 to 2020 is 147.9 million tons, which shows a trend of decreasing first and then increasing. The distribution of GHG emissions from wastewater treatment is uneven among provinces and regions; Guangdong Province has the highest emission, while the Xizang autonomous Region has the lowest. The correlation and contribution rate analysis revealed that paper production and chemical and side food production could discharge a large amount of wastewater with a high COD content, which may have an important impact on GHG emissions during the wastewater treatment stages. According to the study results, CH4 accounts for the largest proportion (63.08%) of the total GHG emissions. The most important source of CH4 comes from the industrial wastewater treatment stage. The annual average CO2 emissions account for 22.24% of the total GHG emissions, which are mainly from the power and chemical consumption stage. The annual average N2O emissions account for 14.68% of the total GHG emissions and are mainly from the wastewater collection and discharge stage. Therefore, in the future, GHG emission reduction strategies should focus on CH4 emissions in the industrial wastewater treatment stage and develop CH4 recycling and utilization technologies.

Comprehensive analysis of greenhouse gases emissions and microbial dynamics in glacier-fed lakes across various ablation stages.

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia

Tropical reservoirs serve a crucial role in the efficient management of water resources contributing to public supply, irrigation, and flow regulation. However, they often emerge as significant sources of greenhouse gas (GHG) emissions and social conflicts. These aquatic ecosystems are located in various Brazilian biomes, such as the Belo Monte Hydroelectric Plant (UHE), situated in the Amazon biome, and the Pedreira and Duas Pontes reservoirs, currently under construction in the Atlantic Forest biome. Each of these reservoirs reflects the complexity of interactions between environmental and social factors, requiring meticulous analysis in light of growing concerns about climate change.The proposed research includes the collection and analysis of environmental and operational data related to these reservoirs, considering crucial variables such as flooded area, types of aquatic vegetation present, and local climatic data. A central focus of the study is to understand how social practices and land use in adjacent areas influence greenhouse gas (GHG) emissions. To achieve this, a comprehensive analysis of agricultural and urban activities that may affect both the availability of organic matter and the decomposition dynamics in the reservoirs is conducted.The methodology adopted utilizes a socio-hydrological approach, allowing for an in-depth investigation of the interrelationships between social and environmental factors. The research includes the application of the G-Res tool to calculate the greenhouse gas (GHG) emissions resulting from management practices in the reservoirs. The aim is to understand the community's perceptions regarding water, conservation practices, and their correlations with GHG emissions, with the goal of providing practical recommendations that promote more efficient and sustainable water management.The study aims to develop future solutions that address interconnected environmental and social issues, aligning with the goals of water sustainability in Brazil, minimizing GHG emissions, and encouraging sustainable practices; thereby contributing to the conservation of water resources and improving the quality of life for local communities. Keywords: Tropical Reservoirs, Greenhouse Gases, Sustainable Water Management, Socio-Hydrological Approach, Tropical Biomes.

A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms

global warming related to GHG (greenhouse gases) emissions from industries is a major issue globally. Furthermore, GHG emissions from the fishery industries also represent an important issue, as indicated by The Code of Conduct for Responsible Fisheries at the Cancun, Mexico, meeting in 1992 and by the Kyoto protocol in 2005. Korea pronounced itself to be a voluntary exclusion management country at the 16th IPCC at Cancun, Mexico, in 2010. However, few analyses of GHG emissions from Korean fisheries have been performed. Therefore, a quantitative analysis of GHG emissions from the major Korean fisheries is needed before guidelines for reducing GHG emissions from the fishing industry can be established. aim of this study was to assess the present GHG emissions from the Korean Purse seine fishery using the LCA (life cycle assessment) method. system boundary and allocation method were defined for the LCA analysis. fuel consumption factor of the purse seine fishery was also calculated. GHG emissions for the edible fish were evaluated by determining the weights of whole fish and gutted fish. Finally, the GHG emissions required to produce 1kg of whole fish and 1kg of edible fish were deduced. results will help determine the GHG emissions from the fishery. They will also be helpful to stakeholders and the government in understanding the circumstances involved in GHG emissions from the fishing industry.

How will Canada’s greenhouse gas emissions change by 2050? A disaggregated analysis of past and future greenhouse gas emissions using bottom-up energy modelling and Sankey diagrams

Statistical analysis of greenhouse gas emissions of South Korean residential buildings

The Australian dairy industry contributes ~1.6% of the nation’s greenhouse gas (GHG) emissions, emitting an estimated 9.3 million tonnes of carbon dioxide equivalents (CO2e) per annum. This study examined 41 contrasting Australian dairy farms for their GHG emissions using the Dairy Greenhouse Gas Abatement Strategies calculator, which incorporates Intergovernmental Panel on Climate Change and Australian inventory methodologies, algorithms and emission factors. Sources of GHG emissions included were pre-farm embedded emissions associated with key farm inputs (i.e. grains and concentrates, forages and fertilisers), CO2 emissions from electricity and fuel consumption, methane emissions from enteric fermentation and animal waste management, and nitrous oxide emissions from animal waste management and nitrogen fertilisers. The estimated mean (±s.d.) GHG emissions intensity was 1.04 ± 0.17 kg CO2 equivalents/kg of fat and protein-corrected milk (kg CO2e/kg FPCM). Enteric methane emissions were found to be approximately half of total farm emissions. Linear regression analysis showed that 95% of the variation in total farm GHG emissions could be explained by annual milk production. While the results of this study suggest that milk production alone could be a suitable surrogate for estimating GHG emissions for national inventory purposes, the GHG emissions intensity of milk production, on an individual farm basis, was shown to vary by over 100% (0.76–1.68 kg CO2e/kg FPCM). It is clear that using a single emissions factor, such as milk production alone, to estimate any given individual farm’s GHG emissions, has the potential to either substantially under- or overestimate individual farms’ GHG emissions.