Assessment of Vehicular Greenhouse Gas Emissions and Potentials for Reduction in A University Campus: Case Study of Bayero University Kano

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.

The Republic of Korea submitted its updated Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change (UNFCCC) Secretariat in December 2021. The updated NDC target is to reduce total national greenhouse gas (GHG) emissions by 40% from the 2018 level, which is 727.6 Mt CO2eq, by 2030. According to the updated NDC, local governments are also required to revise their GHG reduction plans. In addition, local governments should self-inspect the progress and major achievements of the GHG reduction plan every year in accordance with the evaluation guideline of the Ministry of Environment. Of 6 metropolitan cities, Gyeonggi Province shows the highest GHG emissions in the country, which accounts for about 17% of the total national GHG emissions in 2021. Ironically, Goyang City, a basic local government of Gyeonggi Province, was selected as one of the seven best local governments for carbon neutrality in 2021. The City has set a reduction target of 32.8% below BAU by 2030 and prepared a plan to implement reduction targets by sector. Over the last decade, building and transportation sectors have been the major sources of GHG emissions in Goyang City, accounting for approx. 70% of the city’s total GHG emissions. The city promotes zero-energy building (ZEB) for newly constructed buildings and encourages green remodeling for existing buildings in order to reduce GHG emissions in the building sector. It is essential to introduce renewable energy such as solar, geothermal, hydrothermal, etc. for ZEB and green remodeling. In this study, therefore, the potential for solar power generation, which is most easily applicable to the building sector, and GHG reduction were calculated for residential buildings in Goyang City. To calculate the available area for solar power on the roof of residential buildings, spatial data was constructed using high-resolution aerial photographs and the outline of the building roof was extracted through AI training data. AcknowledgementsThis research was carried out as a part of KICT Research Program (Data-Centric Checkup Technique of Building Energy Performance) funded by the Ministry of Science and ICT.

Demand for materials to support economic and social development has made the mining and materials production industry one of the most energy-intensive sectors and a major contributor to greenhouse gas (GHG) emissions. This study quantified the energy intensity for all potash production processes throughout the mine lifetime and the GHG emissions and intensities of potash production under different energy supply scenarios (purchased grid electricity alone or a combination of grid electricity and self-generated electricity using local biomass as fuel feedstock). A total of 40.4%, 42.5%, and 17.1% of the overall energy demand is distributed to the energy required for ore extraction, potash recovery, and daily project operations, respectively. The overall energy intensities (MJ/ton of potash concentrate produced) are lower during the production phase (1,028 ± 13) than during the mine development (5,003 ± 2,766) and closure (1,759 ± 430) phases because 1.5-2.3 more ore is extracted in the former phase. The assessment of total GHG emissions confirmed lower annual emissions from the project operation solely based on grid electricity (153.18 kt CO2 eq) than those of the operations based on biomass electricity production using only palm kernel shells (283.67-287.42 kt CO2 eq) and a mixture of palm kernel shells and fuel woods (247.23-251.22 kt CO2 eq). Uncertainty analyses indicate 1.6- to 1.7-fold lower or 1.4-fold greater total annual GHG emissions than emissions estimated via a deterministic calculation approach. Over the 20-year project lifetime, up to 5,748.4 kt CO2 eq will be emitted if electricity is generated solely from the combustion of palm kernel shells. The differences in the environmental performance of potash production observed through comparisons of GHG emission intensities between this study and other potash production companies are caused mainly by the mining method, source of energy for project operation, and utilization of renewable energy.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

PDF HTML阅读 XML下载 导出引用 引用提醒 长三角城市群碳排放与城市用地增长及形态的关系 DOI: 10.5846/stxb201707101242 作者: 作者单位: 浙江大学公共管理学院土地科学与不动产研究所,浙江大学公共管理学院土地科学与不动产研究所,浙江大学公共管理学院土地科学与不动产研究所,浙江大学公共管理学院土地科学与不动产研究所,浙江大学环境与资源学院农业遥感与信息技术应用研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金面上项目（41771244）；国家留学基金（201706320200）；中央高校基本科研业务费专项资金资助；浙江大学文科教师教学科研发展专项项目 Relationships between carbon emission, urban growth, and urban forms of urban agglomeration in the Yangtze River Delta Author: Affiliation: Institute of Land Science and Property, School of Public Affairs, Zhejiang University,,Institute of Land Science and Property, School of Public Affairs, Zhejiang University,, Fund Project: National Natural Science Foundation of China（Grant No.41771244）; China Scholarship Council (Grant No.201706320200); supported by “the Fundamental Research Funds for the Central Universities”; supported by “the Teaching and Research Development Funds for Humanities and Social Sciences of Zhejiang University” 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:城市是一种重要的碳源，城市扩张过程中的用地面积增长和空间特征变化均会影响城市碳排放。分析1995-2015年长三角城市群碳排放重心转移，查明碳排放和城市用地增长的脱钩状态时空变化，并通过构建面板数据模型探究城市形态对碳排放的影响，得出以下结论：（1）1995-2015年长三角城市群碳排放重心经历了西南向-西北向-东南向-西北向的转移过程，这种转移过程与其相应时期内部分城市的工业发展与产业结构调整有关；（2）1995-2015年，长三角城市群碳排放与城市用地增长的脱钩状态存在着显著的时空异质性。研究区由以扩张负脱钩为主变化为以弱脱钩为主，2005年以后，区域之间的脱钩差异开始缩小，总体来看研究区脱钩状态趋向于同质。至2015年，近70%的城市已达到了脱钩，其中上海等城市实现了强脱钩；（3）连续完整的地块在区域内的主导程度会对城市碳排放产生负向的影响，而城市用地斑块的破碎化程度和聚集程度对碳排放有着正向的影响，且相对而言，聚集程度的正向影响更为显著。 Abstract:Cities are one of many carbon sources. According to the Intergovernmental Panel on Climate Change (IPCC) AR5, CO2 emissions from fossil fuel combustion and industrial processes contributed about 78% to the total Green House Gas (GHG) emission increase between 1970-2010. Total annual anthropogenic GHG emissions have increased by about 10GtCO2-eq between 2000-2010. The increase directly came from energy (47%), industry (30%), transport (11%), and building (3%) sectors, which mainly exist in cities. Urban expansion and urbanization can affect urban carbon emission. Studies show that there is a long-term and stable relationship between urbanization and carbon dioxide emissions. The relationships between urban carbon emissions and indicators, including urban development intensity, urban land use, and the industrial sector, are studied extensively. During urban expansion, the quantitative and spatial features of urban lands can both affect carbon emissions. Therefore, urban form was added to the possible factors influencing carbon emissions in this study, which may be different from previous research that has focused on the relationship between urban growth and carbon emissions. However, in some related research, when urban form has been added to the indicators, the objects were residents or the transport sector, and they lacked quantitative indicators to verify the conclusions. The definition of "urban form" in this study was landscape pattern which was characterized by landscape metrics, and the study area consisted of 13 cities in the Yangtze River Delta. In this study, we analysed the shift of the gravity center from 1995-2015 for carbon emissions of the study area, and defined the decoupling index as well as analysing the temporal-spatial changes of the decoupling relationships between carbon emissions and urban growth in the study area. We also built panel data models to estimate the impact of urban forms on carbon emissions. Based on that, the conclusions are as follows:(1) The shift of the gravity center from 1995-2015 for carbon emissions of the study area was southwest-northwest-southeast-northwest. The shift may be related to the development of industry and change of industrial structure in some cities during this period. (2) There was a significant temporal-spatial heterogeneity in the decoupling relationships between carbon emissions and urban growth from 1995-2015. The leading decoupling relationship between carbon emissions and urban growth of the study area changed from expansive negative decoupling to weak decoupling from 1995-2015. The difference of decoupling relationships between cities narrowed after 2005 and the overall decoupling relationship of the study area became homogeneous. In 2015, almost 70% of cities reached the decoupling state and the decoupling states of Shanghai, Shaoxing, and Taizhou were strong. (3) Urban carbon emissions can be negatively influenced by the dominance of complete patches, and positively influenced by the degree of fragmentation and aggregation of urban patches. Carbon emissions can be more sensitive to the more aggregative distribution of the urban patches. This study analysed the relationship between carbon emissions and urban growth, as well as exploring how urban form can affect carbon emissions. The conclusions could provide scientific references for the policy making of low-carbon development strategies and land use and urban planning of urban agglomeration in the Yangtze River Delta. 参考文献 相似文献 引证文献

Sheepfolds represent significant hot spot sources of greenhouse gases (GHG) in semi-arid grassland regions, such as Inner Mongolia in China. However, the annual contribution of sheepfolds to regional GHG emissions is still unknown. In order to quantify its annual contribution, we conducted measurements of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) fluxes at two sheepfold sites in the Baiyinxile administrative region of Inner Mongolia for 1 year, using static opaque chamber and gas chromatography methods. Our data show that, at an annual scale, both sheepfolds functioned as net sources of CO2, CH4 and N2O. Temperatures primarily determined the seasonal pattern of CO2 emission; 60–84% of the CO2 flux variation could be explained by temperature changes. High rates of net CH4 emissions from sheepfold soils were only observed when animals (sheep and goats) were present. While nitrous oxide emissions were also stimulated by the presence of animals, pulses of N2O emissions were also be related to rainfall and spring-thaw events. The total annual cumulative GHG emissions in CO2 equivalents (CO2: 1; CH4: 25; and N2O: 298) were quantified as 87.4 ± 18.4 t ha−1 for the sheepfold that was used during the non-grazing period (i.e., winter sheepfold) and 136.7 ± 15.9 t ha−1 used during the grazing period (i.e., summer sheepfold). Of the annual total GHG emissions, CH4 release accounted for approximately 1% of emissions, while CO2 and N2O emissions contributed to approximately 59% and 40%, respectively. The total GHG emission factor (CO2 + CH4 + N2O) per animal for the sheepfolds investigated in this study was 30.3 kg CO2 eq yr−1 head−1, which translates to 0.3, 18.8 and 11.2 kg CO2 eq yr−1 head−1 for CH4, CO2 and N2O, respectively. Sheepfolds accounted for approximately 34% of overall N2O emissions in the Baiyinxile administrative region, a typical steppe region within Inner Mongolia. The contribution of sheepfolds to the regional CO2 or CH4 exchange is marginal.

In this study, we allocate Greenhouse gas (GHG) emissions of electricity transmission to the consumers. As an allocation basis, we introduce energy distance. Energy distance takes the transmission load on the electricity energy system into account in addition to the amount of electricity consumption. As a case study, we estimate regional GHG emissions of electricity transmission loss in Chile. Life cycle assessment (LCA) is used to estimate the total GHG emissions of the Chilean electric power system. The regional GHG emission of transmission loss is calculated from the total GHG emissions. We construct the network model of Chilean electric power grid as an undirected network with 466 nodes and 543 edges holding the topology of the power grid based on the statistical record. We analyze the total annual GHG emissions of the Chilean electricity energy system as 23.07 Mt CO2-eq. and 1.61 Mt CO2-eq. for the transmission loss, respectively. The total energy distance for the electricity transmission accounts for 12,842.10 TWh km based on network analysis. We argue that when the GHG emission of electricity transmission loss is estimated, the electricity transmission load should be separately considered. We propose network theory as a useful complement to LCA analysis for the complex allocation. Energy distance is especially useful on a very large-scale electric power grid such as an intercontinental transmission network.

Life-cycle assessment of greenhouse gas emissions from dairy production in Eastern Canada: A case study

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.

Wetland is one of the ecosystem types with the largest density of organic carbon pool. The threat of declining wetland water level to carbon pools and the resulting greenhouse gas (GHG) emissions have attracted much attention. However, an assessment of emissions from degraded wetlands containing the three major greenhouse gases is still lacking. We compiled a global GHG exchange dataset that shows the non-linear water-heat pattern of GHG emissions. Combined with the Wetland Extended Trends Index, we estimated that the total GHG emissions from global degraded wetlands are 276.4 Gt CO2eq during 1950-2020. The emissions of carbon dioxide, methane, and nitrous oxide are equivalent to 10.8%, - 0.5%, and 30.5% of anthropogenic sources, respectively. Under the historical trend of wetland degradation, the emissions may increase by 1.5 times from 2021 to 2100, reaching 408 Gt CO2eq. Accordingly, wetland restoration can reduce anthropogenic carbon dioxide emissions by 10%.

In the past decades, the greenhouse gas (GHG) emissions from pig production in China have been increasing rapidly, which has become a huge challenge in fulfilling China’s “carbon neutral” commitment. However, few studies have focused on reducing the GHG emissions from pig production in view of households’ pork consumption. This study analyzed the temporal and spatial pattern of the GHG emissions from pig production in China in 2001–2020 through geographical information system, optimized the pig production in China, and estimated thepotentialGHG emissions reduction from pig production in China in 2020 through spatial analysis based on pork surplus or deficit. Results show that the temporal and spatial pattern of the GHG emissions from pig production and its proportion in the total GHG emissions from livestock production in China in 2001–2020 varied differently at the province level and conformed to the “Hu Huanyong Line” mode. The largest and smallest GHG emissions from pig production were 108.93 million tons (MT) in 2014 and 78.10 MT in 2020, respectively. The largest and smallest proportions of GHG emissions from pig production in the total GHG emissions from livestock production were 77.52% in Zhejiang in 2013 and 0.13% in Tibet in 2009, respectively. Moreover, a potential optimization scheme of pig production in China in 2020 was provided and a method of GHG emissions reduction from pig production is proposed. The results indicate that the total potentialGHG emissions reduction from pig production on the basis of households’ pork consumption could reach 35.21 MT, accounting for 45.09% of the total GHG emissions from pig production and 10.27% of the total GHG emissions from livestock production in China in 2020. These findings areusefulin the spatial layout planning of pig production, agricultural GHG reduction, and global warming mitigation.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Greenhouse gas (GHG) emissions resulting from the Land Use, Land-Use Change, and Forestry sector (LULUCF) are estimated and reported in National Communications to the United Nations Framework Convention on Climate Change (UNFCCC). By definition, the LULUCF sector is a “greenhouse gas (GHG) inventory sector that covers emissions and removals of greenhouse gases resulting from direct human-induced land use, land-use change and forestry activities”. In principle, the annual GHG national inventory should be transparent, consistent, comparable, complete, and accurate. Also, it should be able to systematically account for all changes in land use and forest cover over many years. In this context, it is essential to investigate the development of an automated approach for mapping local GHG emissions/removals from the LULUCF sector for integration at the national level. In view of that, the aim of this work was to develop a semi-automated model for estimating GHG emissions and removals form the LULUCF sector at the local level. The specific objectives were to 1) map changes in land use and forest cover between two consecutive years, and 2) assess GHG emissions and removals from the LULUCF sector. The methodology of work comprised the use of Geographic Object-Based Image Analysis (GEOBIA) for modelling changes in the LULUCF sector and, subsequently, estimating GHG emissions/removals between two consecutive years. The combined use of Very High Resolution (VHR) SPOT imagery (2.5 m colour) and field data was involved in identifying and mapping land-use changes between 2014 and 2015. Subsequently, GHG emissions and removals were estimated using customized features in GEOBIA and following the 2003 Intergovernmental Panel on Climate Change “Good Practice Guidance for Land Use, Land-Use Change and Forestry”, which adopts a land use category-based approach to estimate emissions/removals from all land categories and all relevant GHGs. An accuracy assessment of the initial classification was conducted with the use of reference data. The overall classification accuracy of the LULUCF mapping in 2014 was found to be 83%, while the Kappa Index of Agreement (KIA) was 0.74. The developed GEOBIA model estimated for the year 2015 net annual GHG removals of -1.613 Gg of CO2 eq. (i.e., an approximate increase of 12.7% in removals between 2014 and 2015). Future work will involve further development of the model to account for all possible changes in the LULUCF sector and test the transferability of the model to other sites.

Greenhouse gas (GHG) emissions is one of the major environmental concerns of shale gas development. To better understand this specific environmental impact, this chapter develops a hybrid life cycle inventory (LCI) model to estimate the energy use and greenhouse gas (GHG) emissions of China’s shale gas development. Results suggest a total average energy use per well of 123 TJ (range: 74–165 TJ) and total average GHG emissions per well of 9505 tCO2e (range: 5346–13551 tCO2e). Most of the energy use and GHG emissions are indirect impacts embodied in fuels and materials. Energy use and GHG emissions from the drilling stage comprise the largest share in both totals due to large amounts of diesel used as fuel in the well drilling process and the materials used in the well casing process. Furthermore, the comparison shows that the energy use and GHG emissions of shale gas development in China will be much higher than the U.S.KeywordsShale gas developmentLife-cycle analysisGHG emissionsEnergy useEmbodied energy

Kupang city is growth rapidly and located in a strategic position between Australia and Timor Leste. A sharp increase of GHG emission along with environmental pollution, contamination of water, air and improper waste disposal practices as its consequence to the global environment. The city's government ambition to evaluate impact of economic activity on greenhouse gases (GHG) emission contribution. This paper outlined pollutant sectors that contribute substantially to GHG emission in Kupang along with its structure, and count an estimated amount of emission coefficients for 27 economy sectors. More in-depth explanation about indirect coefficient pollutant emission which beneficial not only for calculation of the emission amount but more as inventory data for LCA. The paper is investigated review the trends of some priority sectors, then introduction of indirect coefficients of pollutant sectors, and showed the Pollutant Emission Structure for Kupang. After that, an estimated amount of Kupang GHG emission under BAU is also counted and confirmed. The paper only considers GHG emission issues while air pollutant emission only be provided as inventory data but will not be used as exogenous data for this paper. In the final part a brief explanation and implications of GHG emission policy in Kupang are identified. A detailed of input-output data for individual process are provided includes all groups of processes or industry sectors relevant to economy activities in Kupang City. A time period for Global Warming Potential (GWP) 20 year and 100 years are used to forecasted amounts share of total GHG emission in Kupang and Indonesia by 2020 compared to 2010. As results first, the GHG emission and air pollutant coefficients for 27 sectors in Kupang based on method is presented in NIES which use to count the GHG emission. These also become an Inventory data for researchers of regional science in Indonesia, however, geography and socioeconomic conditions in every region is different, so that some criteria will be applied. Second, found total GHG emission in Kupang is $1.0164\mathrm{x} 10^{-3}$ Gt or around 0.047% compared to total GHG emission by 2010 and 0.034% compared to total GHG emission by 2020 in Indonesia. The study suggests to government consider a proper method in decide a reliable environmental policy and technical measures to reach GHG emission targets by 2020. Third, total share of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> e in Indonesia emitted from Kupang for GWP 20 years and 100 years respectively were came out as follow.