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1
Guven, Denizhan, M. Özgür Kayalica, and Gülgün Kayakutlu. "CO2 emissions analysis for East European countries: the role of underlying emission trend." Environmental Economics 11, no. 1 (June 5, 2020): 67–81. http://dx.doi.org/10.21511/ee.11(1).2020.07.
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This paper aims to analyze the impact of energy consumption, economic structure, and manufacturing output on the CO2 emissions of East European countries by applying the Structural Time Series Model (STSM). Several explanatory factors are used to construct the model using annual data of the 1990–2017 period. The factors are: total primary energy supply, GDP per capita and manufacturing value added, and, finally, a stochastic Underlying Emission Trend (UET). The significant effects of all variables on CO2 emissions are detected. Based on the estimated functions, CO2 emissions of Belarus, Ukraine, Romania, Russia, Serbia, and Hungary will decrease, by 2027, to 53.2 Mt, 103.2 Mt, 36.1 Mt, 1528.2 Mt, 36 Mt, and 36.1 Mt, respectively. Distinct from other countries, CO2 emissions of Poland will extend to 312.2 Mt in 2027 due to the very high share of fossil-based supply (i.e., coal and oil) in Poland. The results also indicate that the most forceful factor in CO2 emissions is the total primary energy supply. Furthermore, for Poland, Romania, Hungary, and Belarus, the long-term impact of economic growth on CO2 emissions is negative, while it is positive for Russia, Ukraine, and Serbia. The highest long-term manufacturing value-added elasticity of CO2 emissions is calculated for Serbia and Belarus.
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Yuan, Yongke, Yixing Wang, Yuanying Chi, and Feng Jin. "Identification of Key Carbon Emission Sectors and Analysis of Emission Effects in China." Sustainability 12, no. 20 (October 19, 2020): 8673. http://dx.doi.org/10.3390/su12208673.
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Analysis of sectors’ emission effects is crucial for identifying key emission sectors and reducing carbon. Current literature for calculating sectors’ emission effects in China ignore intermediate demand. This might introduce inaccuracy into the analyzed results. To solve this gap, this paper used an alternative input–output method to analyze sectors’ emission effects in China. Firstly, it identifies the key emission sectors and their emission effect characteristics from 2005 to 2017. Then, the reasons for the changes in these sectors’ emission effects are analyzed. Lastly, emission effects were further decomposed so that the driving relationships of emissions among these sectors can be sorted out. The results show that the overall key emission sectors were metal smelting and processing and nonmetal mineral products. The backward-emission-dominant sectors were construction, chemical products, other services (such as finance, health and education), metal products, and so on. The forward-emission-dominant sectors were production and supply of electricity and heat, transportation, storage, postal, and telecommunications services. In 2017, transportation, storage, postal, and telecommunications services’ own final demand emissions and forward emissions accounted for 41.7% and 58.3%, respectively, of this sector’s direct emissions. Moreover, from 2005 to 2017, the main sector emission paths affecting the growth of China’s emissions shifted from manufacturing and construction industries to service industries. Accordingly, strategies for emission reduction, such as substituting pollution inputs, were proposed and analyzed. The research provides an important reference for the Chinese government to adopt appropriate measures to reduce carbon.
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Dragičević, Viktor, Marina Levak, Anton Turk, and Ivan Lorencin. "Ship production processes air emissions analysis." Pomorstvo 36, no. 1 (June 30, 2022): 164–71. http://dx.doi.org/10.31217/p.36.1.19.
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Compliance with modern environmental norms and regulations is an increasingly important requirement in the shipbuilding process of ship design and construction. Related to the ship production process, volatile organic compounds (VOCs), nitric oxides and particulate matter are the main emissions of harmful gases in the shipyard. This paper analyzes air emissions from the ship production process in a shipyard. Air emissions are quantified from either in-situ measurements from emission sources, or by materials that are used in the shipbuilding process, and the acquired data from those measurements is calculated as yearly emissions. Emission quantities of VOCs, nitric oxides, carbon dioxide, carbon monoxide and particulates are analyzed regarding possible reduction techniques considering efficiency and investment costs for using these methods. In conclusion, the best available and feasible emission reduction methods are suggested, and a suggestion for achieving the goal of a net zero emission shipyard.
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WANG, Xingmin, Jing WU, Zheng WANG, Xiaoting JIA, and Bing BAI. "Accounting and Characteristics Analysis of CO2 Emissions in Chinese Cities." Chinese Journal of Urban and Environmental Studies 08, no. 01 (March 2020): 2050004. http://dx.doi.org/10.1142/s2345748120500049.
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Accurate estimation of CO2 emissions is a prerequisite for scientific low-carbon emission policymaking. Based on 20 types of energy consumption data at the prefecture level in China, this paper re-estimates the CO2 emissions of 198 prefecture-level cities in 2016 by using the method of carbon emission coefficient. The spatial pattern and scale characteristics are analyzed, and the conclusions are as follows: (1) Overall, China’s urban CO2 emissions show a certain degree of spatial separation in terms of the total amount, per capita emissions, and emission intensity. Cities with the highest CO2 emissions in China are mainly concentrated in North China, East China and Chongqing, while cities with the highest per capita CO2 emissions and emission intensity are mainly concentrated in Northwest and North China. (2) Different types of cities have different CO2 emission characteristics. Resource-based cities have a higher total amount and emission intensity; tourism and underdeveloped cities both have lower values; while super-large-sized cities and many very-large-sized cities have higher CO2 emissions, but their emission intensities are usually lower; and no obvious rules are found in other cities. (3) Spatial analysis shows that cities with higher CO2 emissions are clustered. The Beijing–Tianjin–Hebei region, the Yangtze River Delta region, Shandong Province, and Shanxi–Henan–Anhui resource-producing areas are the agglomeration areas of high-emission cities. (4) Scale analysis shows that the characteristics of CO2 emissions at different scales are different. Provincial-level research can help to identify the environmental impact and total effect of carbon emissions, while urban-scale research is helpful to explore the diversity and phases of cities. Finally, based on the main conclusions of this study, the corresponding urban low-carbon policy implications are drawn.
5
Chen, Zhen. "Analysis on Carbon Emission Right Theories." Applied Mechanics and Materials 644-650 (September 2014): 5235–38. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.5235.
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Since China’s National Development and Reform Commission approved the first seven pilot cities to carbon emission right trading, carbon emission trading is now flourishing in the country. However, in practice, the carbon emission trading emerges many problems and short in some basic theories to safeguard. In theory, the nature of carbon emission right still has no uniform academic definition. What is carbon emission right? There is an academic contend to illustrate it, such as usufruct right, property right, new property and other theories. What’s more, defining the nature of carbon emission right is the premise to ensure that carbon emissions trading system work smoothly.
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Stepanović, Nemanja, and Vladan Tubić. "Analysis of ecological benefits of traffic flow electrification." Put i saobraćaj 65, no. 2 (July 9, 2019): 19–27. http://dx.doi.org/10.31075/pis.65.02.04.
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Road transport is responsible for 22% of the total CO2 emissions, 39% of NOx emission and 10% share of particulate matters (PM10, PM2.5) emission. The use of passenger cars, as an extremely dominant category of vehicles, is at constant growth, which causes an increase or insufficient reduction of Greenhouse Gas emission, despite the technological improvements of exaust emission devices. Due to the growing harmful effects on the environment and human health, as well as the recent scandals associated with internal combustion engine tehcnology („Dieselgate scandal”), development of new technology is fast forward toward electric vehicles.The biggest automotive corporations plans dominant fleet electrification in the next 10 years. However, sudden share increase of the electric vehicles in the traffic flow can lead to the capacity overcoming of the electricity grid network, or the issue of the "ecological footprint" of such a trend. In this paper, the overall environmental impact (so-called Well-to-Wheel analysis) of the increasing number of electric vehicles was analysed. Comparison analysis of vehicles equipped with internal combustion egines and electric vehicles showed the absence of Greenhouse Gass emisson reduction in countries with low percentage of electricity gained from renewable energy sources. Well-to-Wheel analysis was also conducted for several scenarios of electric vehicles participation in traffic flow in Republic of Serbia i.e their influence on electricity grid network and its emission.
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Honghai, Yu, Wang Zhi, Chen Li, and Wu Jianan. "CO2 Emission Calculation and Emission Characteristics Analysis of Typical 600MW Coal-fired Thermal Power Unit." E3S Web of Conferences 165 (2020): 01029. http://dx.doi.org/10.1051/e3sconf/202016501029.
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In order to effectively reduce the total CO2 emissions of coal-fired power plants and reduce greenhouse gas emissions, the relevant data of a typical 600MW coal-fired power plant in the past five years was collected and investigated, and CO2 emissions and emission intensity were calculated. And the results were used to measure the CO2 emission level of coal-fired power plants. By comparing and analyzing the CO2 emission intensity and emission trend of 600MW coal-fired units with different unit types and different fuel types, the CO2 emission characteristics of typical 600MW coal-fired power plants are obtained.
8
Jang, Sunhee, Ki-Han Song, Daejin Kim, Joonho Ko, Seongkwan Mark Lee, Sabeur Elkosantini, and Wonho Suh. "Road-Section-Based Analysis of Vehicle Emissions and Energy Consumption." Sustainability 15, no. 5 (March 1, 2023): 4421. http://dx.doi.org/10.3390/su15054421.
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To monitor air pollution on roads in urban areas, it is necessary to accurately estimate emissions from vehicles. For this purpose, vehicle emission estimation models have been developed. Vehicle emission estimation models are categorized into macroscopic models and microscopic models. While the calculation is simple, macroscopic models utilize the average speed of vehicles without accounting for the acceleration and deceleration of individual vehicles. Therefore, limitations exist in estimating accurate emissions when there are frequent changes in driving behavior. Microscopic emission estimation models overcome these limitations by utilizing the trajectory data of each vehicle. In this method, the total emissions in a road segment are calculated by adding together the emissions from individual vehicles. However, most research studies consider the total vehicle emissions in a road section without considering the difference in vehicle emissions at different locations of a selected road section. In this study, a road segment between two intersections was divided into sub-sections, and energy consumption and emission generation were analyzed. Since there are unique driving behaviors depending on the section of the road segment, energy consumption and emission generation patterns were identified. The findings of this study are expected to provide more detailed and quantitative data for better modeling of energy consumption and emissions in urban areas.
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Xu, Aixia, and Xiaoyong Yang. "Analysis of total carbon emission of the logistics industry in Guangdong and solutions to emission reduction." E3S Web of Conferences 245 (2021): 01020. http://dx.doi.org/10.1051/e3sconf/202124501020.
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The input-output method is employed in this study to measure the total carbon emission of the logistics industry in Guangdong. The findings revealed that the carbon emission of direct energy consumption of the logistics industry in Guangdong is far above the actual carbon emissions, the second and third industries play a significant role in carbon emission of indirect energy consumption in the logistics industry in Guangdong. To reduce energy consumption and carbon emissions in Guangdong, it is not only important to control the carbon emissions in the logistics industry, but strengthen carbon emission detection in relevant industries, improve the energy utilization rate and reduce emissions in other industries, and move towards low-carbon sustainable development.
10
Zhang, Ye, Yating Song, Tianshi Feng, and Yanyan Chen. "Comparative Analysis of Emission Characteristics of In-Use China II–V Gasoline, Hybrid, Diesel-Fueled Vehicles." Atmosphere 14, no. 2 (January 29, 2023): 272. http://dx.doi.org/10.3390/atmos14020272.
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Increasingly stringent regulations regarding vehicle emissions have contributed to the diversification of vehicle technologies, resulting in the increasing complexity of typical vehicles that make up a fleet. In order to investigate the real gas emissions of different typical vehicles, tests were conducted using a portable emission measurement system (PEMS) in Beijing and emission studies were conducted on eight light-duty passenger vehicles (LDPVs, including light-duty gasoline passenger vehicles and hybrid electric vehicles), eight heavy-duty passenger vehicles (HDPVs), and four light-duty trucks (LDTs). The results show that the emissions of relevant pollutants from LDPV meet the emission standard limits. The emission factors of CO2, CO, NOX, and HC of China IV and China V hybrid electric vehicles (HEVs) are much smaller than the emission standard limits and the emission factors of other vehicles, which have better emission reduction effects. Among LDPV, heavy-duty passenger vehicles (HDPVs), and LDT, the emissions of HDPV and LDT are extremely high. Emission characteristics vary on different types of roads, with the highest emission factors generally occurring on secondary roads. The micro-trip method was used to explore the influence of speed on emission factors. HEV are less sensitive to speed changes and can still maintain a low emission level at low speeds. The average speed and emission factors of HDPV in micro-trip has a strong correlation.
11
Zhang, Dan, Xiaowei Wang, Tao Gao, Xiaojun Jing, Yongzhan Huo, and Gang Li. "Plateau PEMS emission characteristics analysis of heavy-duty diesel vehicles with different technical routes." E3S Web of Conferences 352 (2022): 03048. http://dx.doi.org/10.1051/e3sconf/202235203048.
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Real driving emission characteristics of heavy-duty diesel vehicles with different technical routes were conducted by portable emission measurement system (PEMS) tests at different altitudes of 1400 meter and 2300 meter. Results show that the use of EGR will lead to increased particulate matter emissions but has little effect of NOx emissions. The EGR application exhibits a large effect on the PN emission but a little effect on NOx emission. PN emissions were strongly correlated with engine load during the PEMS test. The higher the engine load, the higher the PN emissions even at lower altitudes. There are large differences in PEMS test results even at the same altitude.
12
Tong, Qing, Sheng Zhou, Yuefeng Guo, Yang Zhang, and Xinyang Wei. "Forecast and Analysis on Reducing China’s CO2 Emissions from Lime Industrial Process." International Journal of Environmental Research and Public Health 16, no. 3 (February 11, 2019): 500. http://dx.doi.org/10.3390/ijerph16030500.
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China greenhouse gas inventories show that CO2 emissions from the lime industrial process are large scales and closely related to the development of its downstream industries. Therefore, there is high importance to analyze and forecast on reducing China’s CO2 emissions from lime industrial process. The aims of this paper are to make up the research gaps in China and provide a quantitative reference for related authorities to formulate relevant policies. The prediction method in this paper is consistent with the published national inventory, which is an activity data based method to predict carbon dioxide emissions from the industrial process of four categories of lime products. Three future scenarios are assumed. The business as usual scenario (BAU) is a frozen scenario. There are two emission reduction scenarios (ERS and SRS) assumed under different emission reduction strength considering combined industrial process CO2 emission reduction approaches from both the production side and the consumption side. The results show that between 2020 and 2050, China’s lime industrial process has an increasingly significant CO2 emission reduction potential, enabling both emission intensity reductions and total emission reductions to be achieved simultaneously. Based on the simulation results from emission reduction scenarios, compared with 2012 level, in 2050, the emission intensity can be reduced by 13–27%, the total lime production can be reduced by 49–78%, and the CO2 emissions in the lime industrial process can be reduced by 57–85%.
13
Jasiński, Remigiusz. "Analysis of Particle Emissions from a Jet Engine including Conditions of Afterburner Use." Energies 15, no. 20 (October 18, 2022): 7696. http://dx.doi.org/10.3390/en15207696.
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Particle emissions from aircraft engines are mainly related to the emission of particles with very small diameters. The phenomena of the formation of particles in various operating conditions of turbine engines are known. However, it is difficult to find the results of research on the use of the afterburner in the literature. Increased aviation activity within military airports and situations such as air shows are associated with a very intense emission of particles, and pose a direct threat to human health. This article presents an analysis of particulate matter emissions from a military aircraft engine, with particular emphasis on operation with an afterburner. The parameters of the emission of particles determined were: PM Number Emissions Index (EIN), Particle Number Emissions Intensity (EN), PM Mass Emission Index (EIM), PM Mass Emission Intensity (EM), Differential Particle Number Emission Index, Differential Particle Volume Emission Index, and Differential Particle Mass Emission Index. The value of EIN for the afterburner use was the lowest among the whole operation range of the engine and was equal to 1.3 × 1015 particles per kilogram. The use of an afterburner resulted in a sharp increase in the EIM coefficient, which reached 670 mg/kg. Despite a very large increase in fuel consumption, the EIM coefficient turned out to be over 60 times greater than in the case of 100% engine thrust.
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Hao, Lijun, Hang Yin, Junfang Wang, Miao Tian, Xiaohu Wang, Yunshan Ge, Yoann Bernard, and Åke Sjödin. "Research on Analysis Method of Remote Sensing Results of NO Emission from Diesel Vehicles." Atmosphere 13, no. 7 (July 13, 2022): 1100. http://dx.doi.org/10.3390/atmos13071100.
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Remote sensing technology has been used for gasoline vehicle gaseous emissions monitoring for nearly 30 years. However, the application effect of the remote sensing detection of diesel vehicle tailpipe emission concentrations is unsatisfactory. Therefore, several approaches were proposed to analyze the remote sensing results for gaseous exhaust emissions from diesel vehicles, including the concentration ratios of gaseous emission components to carbon dioxide (CO2) and fuel-based emission factors. Based on our experimental results, these two metrics have some high values in low-speed or low-load conditions of vehicles, which introduces uncertainty when evaluating vehicle emission levels. Therefore, an inversion calculation method originally developed for remote sensing light duty diesel vehicle gaseous emissions was used for the remote sensing of nitrogen monoxide (NO) tailpipe concentrations in heavy duty diesel vehicles, and validated by PEMS tested emission results. For the first time, the above three options for evaluating the NOx emission level of diesel vehicles, including the concentration ratio of NO to CO2, the fuel-based NO emission factor and the estimated tailpipe NO emission concentration were investigated, and some influencing factors were also discussed. The remote sensing tailpipe NO emission concentration can be directly used to evaluate diesel vehicle NO emission levels compared with the two other metrics.
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Wang, Haiying, Yue Wang, Hong Mi, Jianbin Zang, and Shuangshuang Wang. "Analysis of Carbon Emission Energy Inventory from Refrigerant Production and Recycling Carbon Compensation." Applied Sciences 12, no. 1 (December 21, 2021): 1. http://dx.doi.org/10.3390/app12010001.
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At present, the massive emissions of carbon dioxide and nitrogen oxides and other greenhouse gases caused by human activities have caused more and more serious negative effects on global climate change. In order to cope with global warming and achieve sustainable development, achieve “carbon neutrality” as soon as possible. In the refrigeration industry, it is necessary to reduce greenhouse gas emissions related to refrigerants, including the production, use, and recycling of refrigerants. This paper has carried out the calculation of greenhouse gas emissions during the refrigerant preparation process, and compared and analyzed the emission reductions of refrigerant recycling and reuse; the research based on the energy consumption of the refrigerant production process uses the greenhouse gas emission inventory analysis method to Taking refrigerant R134a as an example, the carbon emission accounting boundary of the production process is set, the emission source is determined, the emission is calculated based on the emission factor method, and the emission inventory is established; the carbon offset effect of the recycling and reuse of the refrigerant is analyzed. The research results show that if the entire refrigerant industry fully recycles waste refrigerants, it can reduce carbon emissions by about 29.7% compared to just producing new refrigerants.
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Yu, Zhen, Yuan Zhang, Juan Zhang, and Wenjie Zhang. "Analysis and prediction of the temporal and spatial evolution of carbon emissions in China’s eight economic regions." PLOS ONE 17, no. 12 (December 1, 2022): e0277906. http://dx.doi.org/10.1371/journal.pone.0277906.
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Facing increasingly severe environmental problems, as the largest developing country, achieving regional carbon emission reduction is the performance of China’s fulfillment of the responsibility of a big government and the key to the smooth realization of the global carbon emission reduction goal. Since China’s carbon emission data is updated slowly, in order to better formulate the corresponding emission reduction strategy, it is necessary to propose a more accurate carbon emission prediction model on the basis of fully analyzing the characteristics of carbon emissions at the provincial and regional levels. Given this, this paper first calculated the carbon emissions of eight economic regions in China from 2005 to 2019 according to relevant statistical data. Secondly, with the help of kernel density function, Theil index and decoupling index, the dynamic evolution characteristics of regional carbon emissions are discussed. Finally, an improved particle swarm optimization radial basis function (IPSO-RBF) neural network model is established to compare the simulation and prediction models of China’s carbon emissions. The results show significant differences in carbon emissions in different regions, and the differences between high-value and low-value areas show an apparent expansion trend. The inter-regional carbon emission difference is the main factor in the overall carbon emission difference. The economic region in the middle Yellow River (ERMRYR) has the most considerable contribution to the national carbon emission difference, and the main contributors affecting the overall carbon emission difference in different regions are different. The number of regions with strong decoupling between carbon emissions and economic development is increasing in time series. The results of the carbon emission prediction model can be seen that IPSO-RBF neural network model optimizes the radial basis function (RBF) neural network, making the prediction result in a minor error and higher accuracy. Therefore, when exploring the path of carbon emission reduction in different regions in the future, the IPSO-RBF neural network model is more suitable for predicting carbon emissions and other relevant indicators, laying a foundation for putting forward more scientific and practical emission reduction plans.
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Li, Ying, Lei Li, Ming Na, and Shengjiang Zhao. "Analysis on the Efficiency of Anhui’s Industrial Sectors under the Carbon Emission Constraints." Journal of Finance Research 3, no. 1 (April 29, 2019): 33. http://dx.doi.org/10.26549/jfr.v3i1.1363.
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This paper uses the SBM-DDF model to measure the green inefficiency of all kinds of industries in Anhui Province under the constraint of carbon emissions from 2006 to 2014. The results show that whether from the perspective of the overall industries in Anhui Province or from the perspective of separate industry groups, the sources of the green inefficiency are mainly from insufficient industrial output, followed by excessive emissions of CO2. The green inefficiency values of each group (from big to small) are sized down by high-emission industries, medium-emission industries and low-emission industries respectively. During the period of research, the effect of the emission reduction in high-emission industries was not significant, and the potential of reducing the green inefficiency in the medium-emission and low-emission industries by increasing the output was not large.
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Tseng, Sheng-Wen. "Analysis of Energy-Related Carbon Emissions in Inner Mongolia, China." Sustainability 11, no. 24 (December 8, 2019): 7008. http://dx.doi.org/10.3390/su11247008.
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Inner Mongolia has shown both rapid economic growth and a large renewable energy base, this has come about by the introduction of the “Western Development” strategy and renewable energy policy of the Chinese Government. However, this has led to a contradictory situation where both high carbon emission and reduction exist together. The average economic growth of Inner Mongolia reached 15.76% between 2006 and 2016, which caused huge CO2 emissions. However, promotion of the renewable energy policy (since 2005) resulted in an energy self-sufficiency rate that reached 270.80% by 2016. In this study of the Inner Mongolia carbon emission situation, the logarithmic mean divisia index (LMDI) model was used to analyze the factors affecting carbon emission fluctuations from 2005 to 2016. The decoupling elasticity index was then used to measure the decoupling effect of the economic growth and carbon emissions. The results of this research show that: firstly, CO2 emissions increased rapidly from 651.03 million tons in 2006 to 1723.24 million tons in 2013. Despite a slight decline in CO2 emissions, a level above 1600 million tons was maintained between 2014 and 2016. Secondly, the industry sector was the main source of CO2 emissions in Inner Mongolia, and coal-based fuel played a determining role. Thirdly, in this study, two important contributions were made, including the discovery of two new drivers: labor and emission intensity factors. Further, findings about the effect of the six industrial sectors, economic structure, energy density, and emission intensity factors were also decomposed. It was found that during research period, the population factor, labor factor, and labor productivity factor all had a positive influence on CO2 emissions, whereas the economic structure factor and emission intensity factor had different impacts on the CO2 emissions depending on the particular industrial sector. Furthermore, the energy intensity of six industrial sectors contributed to the decrease in aggregate CO2 emissions. Finally, in this study, it was also found that economic growth and CO2 growth in Inner Mongolia presented a weak decoupling state. Policy recommendations based on these results have been presented.
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Chontanawat, Jaruwan, Paitoon Wiboonchutikula, and Atinat Buddhivanich. "Decomposition Analysis of the Carbon Emissions of the Manufacturing and Industrial Sector in Thailand." Energies 13, no. 4 (February 12, 2020): 798. http://dx.doi.org/10.3390/en13040798.
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Since the 1990s, CO2 emissions have increased steadily in line with the growth of production and the use of energy in the manufacturing sector in Thailand. The Logarithmic Mean Divisia Index Method is used for analysing the sources of changes in CO2 emissions as well as the CO2 emission intensity of the sector in 2000–2018. On average throughout the period, both the amount of CO2 emissions and the CO2 emission intensity increased each year relative to the baseline. The structural change effect (effect of changes of manufacturing production composition) reduced, but the intensity effect (effect of changes of CO2 emissions of individual industries) increased the amount of CO2 emissions and the CO2 emission intensity. The unfavourable CO2 emission intensity change came from the increased energy intensity of individual industries. The increased use of coal and electricity raised the CO2 emissions, whereas the insignificant change in emission factors showed little impact. Therefore, the study calls for policies that decrease the energy intensity of each industry by limiting the use of coal and reducing the electricity used by the manufacturing sector so that Thailand can make a positive contribution to the international community’s effort to achieve the goal of CO2 emissions reduction.
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Lin, Qiaowen, Lu Zhang, Bingkui Qiu, Yi Zhao, and Chao Wei. "Spatiotemporal Analysis of Land Use Patterns on Carbon Emissions in China." Land 10, no. 2 (February 1, 2021): 141. http://dx.doi.org/10.3390/land10020141.
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Nowadays, China is the world’s second largest economy and largest carbon emitter. This paper calculates the carbon emission intensity and the carbon emissions per capita of land use in 30 provinces at the national level in China from 2006 to 2016. A spatial correlation model is used to explore its spatiotemporal features. The results show that (1) China’s land use carbon emissions continued to grow from 2006 to 2016. The spatial heterogeneity of carbon emission intensity of land use initially decreased and then increased during this period. The carbon emission of land use pattern reached a peak in 2015 and the land use carbon emission intensity was relatively lower in east China; (2) southern China accounts for a majority of the total Chinese carbon sink. Better economic structure, land use structure and industrial structure will lead to lower carbon emission intensity of land use; (3) carbon emissions per capita of land use in China are affected not only by land development intensity, urbanization level, and energy consumption structure, but also by the population policy. It is significant to formulate differentiated energy and land use policies according to local conditions. This study not only provides a scientific basis for formulating different carbon emission mitigation policies for the local governments in China, but also provides theoretical reference for other developing countries for sustainable development. It contributes to the better understanding of the land use patterns on carbon emissions in China.
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Wójcik-Gront, Elżbieta. "Analysis of Sources and Trends in Agricultural GHG Emissions from Annex I Countries." Atmosphere 11, no. 4 (April 15, 2020): 392. http://dx.doi.org/10.3390/atmos11040392.
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The vast majority of the scientific community believe that anthropogenic greenhouse gas (GHG) emissions are the predominant cause of climate change. One of the GHG emission sources is agriculture. Following the International Panel on Climate Change (IPCC) guidelines regarding GHG emission calculation, agriculture is responsible for around 10% of the overall global emissions. Agricultural GHG emissions consist of several emission source categories and several GHGs. In this article were described the results of multivariate statistical analyses performed on data gathered during the period 1990–2017 from the inventories of 43 Annex I countries (parties to the United Nations Framework Convention on Climate Change, UNFCCC, listed in Annex I of the Convention). Trends in the agricultural GHG emissions were analyzed. Generally, the global agricultural GHG emissions are increasing, while the emissions from Annex I countries are decreasing. Apart from the application of urea, emissions from all other sources, such as enteric fermentation, manure management, rice cultivation, agricultural soils, field burning of agricultural residues, and liming are decreasing. Based on multivariate analysis, the most different countries, in terms of GHG emission sources composition in agriculture and emission trends, are Australia, Japan, New Zealand and USA. The rest of the Annex I countries are mostly from Europe and their shares and trends are similar, with slight differences between countries depending, among others, on the date of joining the European Union.
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Malaťák, J., and L. Passian. "Heat-emission analysis of small combustion equipments for biomass." Research in Agricultural Engineering 57, No. 2 (June 27, 2011): 37–50. http://dx.doi.org/10.17221/28/2010-rae.
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The article addresses the urgent questions regarding the use of biomass as a fuel for combustion equipment of the heat output up to 25 kW. The article is based on the determined elemental analyses of six samples of fuel taken both from the wood mass and herbaceous biomass. These samples underwent the stoichiometric analysis of fuels. After the stoichiometric analysis the heat-emission characteristics were determined on two combustion equipments. The results of carried out elemental and stoichiometric analyses indicate higher values of nitrogen, sulphur and chlorine concentration in herbaceous biomass from agriculture compared to the analyzed wood mass. The selection of combustion equipment is particularly influenced by increased contents of sulphur and chlorine (corrosive behaviour). The net calorific value of the analyzed samples taken from the wood mass is higher than of samples taken from the herbaceous biomass. The net calorific value of fuels from herbaceous biomass is reduced due to a higher content of ashes in the fuel. The results of thermal-emission analyses show higher values of nitrogen oxides, sulphur and chlorine concentrations in the herbaceous biomass compared to the analyzed wood mass. The emission concentrations of carbon monoxide for wood fuels and herbaceous biomass also depend on the type of combustion equipment and setting of combustion air volume. The increased emissions of hydrogen chloride generated by various combustion equipments are primarily caused by the volume of combustion air and the amount of chlorine in the fuel itself. The higher the volume of combustion air brought into the combustion chamber is, the higher the emissions of hydrogen chloride are. Based on the analyses we can also draw a conclusion that the spaces of combustion equipment during combustion should be most burdened with the herbaceous biomass.
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Zhang, Xiufan, and Decheng Fan. "The Spatial-Temporal Evolution of China’s Carbon Emission Intensity and the Analysis of Regional Emission Reduction Potential under the Carbon Emissions Trading Mechanism." Sustainability 14, no. 12 (June 17, 2022): 7442. http://dx.doi.org/10.3390/su14127442.
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It is of great significance to study the regional differences and temporal and spatial evolution of China’s carbon emission intensity under the carbon emissions trading mechanism, and to explore the potential for regional emission reduction. This paper uses the Theil index and Moran index to analyze the regional differences and temporal and spatial evolution trend of carbon emission intensity in China from 2010 to 2019, further constructs the emission reduction effect standard of carbon emissions trading mechanisms, discusses the emission reduction effect of the trading mechanisms, and measures the regional emission reduction potential according to the environmental learning curve. The results showed that: (1) China’s overall carbon emissions continued to increase, but the carbon emission intensity showed an overall decreasing trend. There are strong regional differences in China’s carbon emission intensity. The carbon emission intensity in the western region is higher, and the overall regional difference is decreasing year by year. (2) China’s carbon emissions trading mechanism has a significant reduction effect, but the total quota slack of the Tianjin, Beijing, and Chongqing carbon emissions trading pilot markets is loose. (3) Shanghai, Shanxi, Jiangxi, Guizhou, Inner Mongolia, and Beijing are high-efficiency carbon emission reduction provinces (more than 35%), and Fujian and Xinjiang are low-efficiency carbon emission reduction provinces (less than 15%). It is necessary to further develop the demonstration effect of high emission reduction potential areas and increase the emission reduction efforts in low emission reduction potential areas.
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Sivaram, P. M., N. Gowdhaman, D. Y. Ebin Davis, and M. Subramanian. "Carbon Footprint Analysis of an Educational Institution." Applied Mechanics and Materials 787 (August 2015): 187–91. http://dx.doi.org/10.4028/www.scientific.net/amm.787.187.
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Global warming and climate change are the foremost environmental challenges facing the world today. It is our responsibility to minimize the consumption of energy and hence reduce the emissions of greenhouse gases. Companies choose ‘Carbon Footprint’ as a tool to calculate the greenhouse gas emission to show the impact of their activities on the environment. In this working paper, we assess the carbon foot print of an educational institution and suggest suitable measures for reducing it. Greenhouse gas emitting protocol for an academic institution in terms of tones of equivalent CO2 per year is projected using three basic steps includes planning (assessment of data’s), calculation and estimation of CO2 emitted. The estimation of carbon foot print is calculated by accounting direct emission from sources owned/controlled by the educational institution and from indirect emission i.e. purchased electricity, electricity produced by diesel Generator (DG), transport, cooking (Liquefied Petroleum Gas) and other outsourced distribution. The CO2 absorbed by trees are also accounted. Some of the options are identified in order to reduce CO2 level. The information of corporate carbon footprint helps us identifying the Green House Gases (GHG) emission “hot spots” and identifies where the greatest capacity exists in order to reduce the GHG emissions. The main prioritization goes to transport and then followed by DG, cooking and then electricity. The per capita CO2 emission and the total CO2 emission for a typical educational institution are estimated.
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Park, Jun Chul, Yong Woo Hwang, Jun Beum Kim, and Young Woon Kim. "Material Flow Analysis of Trichloroethylene in Korea." Journal of Korean Society of Environmental Engineers 42, no. 4 (April 30, 2020): 188–96. http://dx.doi.org/10.4491/ksee.2020.42.4.188.
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Objectives:According to the material flow analysis, the domestic flow of trichloroethylene with the highest emission among carcinogens in group 1 was determined. The purpose of this study is to provide basic data for efficient chemical management and establish measures to reduce emissions.Methods:In this study, the material flow analysis of trichloroethylene was analyzed in Korea in 2014. The material flow chart was presented using STAN 2.6 software. The flow of trichloroethylene by region and industry was analyzed to identify the characteristics of each flow, and the emission reduction method was presented.Results and Discussion:Trichloroethylene was used up to 79.8% in the Seoul metropolitan area, 45.6% in the manufacturing of other machinery and equipment, and 29.4% in the manufacturing of fabricated metal products except machinery and furniture. Trichloroethylene was emitted 42.0% in the manufacturing of rubber and plastics products and 26.8% in the manufacturing of primary metals. The analysis of emissions by company size resulted in 3.9% of total emissions from large companies, 61.6% from mid-sized companies, and 34.5% from small-sized companies. Trichloroethylene was used in various industries and regions, with higher emissions compared to its use.Conclusions:Trichloroethylene has been emitted in large quantities relative to its usage. The study found that the management of chemicals in small businesses was insufficient. This result of the material flow analysis is used as basic data to reduce emissions of chemicals. The result of the study helps to recognize the risk of chemicals and suggest alternative materials, introduce inter-company information and expert exchange system, introduce a total amount of carcinogens emission system, implement duties in the emission reduction plan, and consider emission reduction incentives. In addition, measures to improve risk are proposed to establish risk-based database.
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Ma, Zhongmin, Yuanyuan Yang, Peiting Sun, Hui Xing, Shulin Duan, Hongfei Qu, and Yongjiu Zou. "Analysis of Marine Diesel Engine Emission Characteristics of Different Power Ranges in China." Atmosphere 12, no. 9 (August 27, 2021): 1108. http://dx.doi.org/10.3390/atmos12091108.
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In order to accurately assess China’s port air pollution caused by the shipping industry, two main methods can be used to calculate the emissions of ships, including the method based on ship fuel consumption and the method based on ship activities. Both methods require accurate diesel engine emission factors, or specific emissions. In this paper, the emission characteristics of NOX, CO, CO2 and THC from 197 domestic marine diesel engines were tested under bench test conditions by a standard emission measurement system. The diesel engines were divided into six Classes, A~F, according to their power distribution, and the fuel-based emission factors and energy-based emission factors of marine main engine and auxiliary engine meeting IMO NOX Tier II standards were given. The results showed that the main engine fuel-based emission factors of NOX, CO, CO2 and THC from Class A to Class F were 33.25~76.58, 2.70~4.33, 3123.92~3166.47 and 1.10~2.64 kg/t-fuel, respectively; and the energy-based emission factors were 6.57~11.75, 0.56~0.81, 530.28~659.71 and 0.18~0.61 g/kW h, respectively. The auxiliary engine fuel-based emission factors of NOX, CO, CO2 and THC from Class A to Class D were 27.17~39.81, 2.66~5.12, 3113.01~3141.34 and 1.16~2.87 kg/t-fuel respectively; and their energy-based emission factors were 6.06~8.33, 0.47~0.77, 656.86~684.91 and 0.21~0.61 g/kW h, respectively. The emission factors for different types of diesel engines were closely related to the diesel engine load, and the relation between them could be expressed by quadratic polynomial or power function. The results of this paper provide valuable data for the estimation of waterway transportation exhaust emissions and comprehensive understanding of the emission characteristics of marine diesel engines.
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Ma, Zhongmin, Taili Du, Shulin Duan, Hongfei Qu, Kai Wang, Hui Xing, Yongjiu Zou, and Peiting Sun. "Analysis of Exhaust Pollutants from Four-Stroke Marine Diesel Engines Based on Bench Tests." Journal of Marine Science and Engineering 11, no. 2 (February 14, 2023): 413. http://dx.doi.org/10.3390/jmse11020413.
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Implementation of new emissions regulations calls for a reassessment of the emissions levels of newly built ships sailing in Chinese regions. In this paper, marine diesel engines are subjected to emissions bench tests using high-precision testing equipment. A total of 135 marine diesel engines meeting the Limits and Measurement Methods for Exhaust Pollutants from Marine Engines (CHINA I/II) were first systematically analyzed. The emission factors of marine main engines (ME) and auxiliary engines (AE) were obtained under different displacements. The results show that the fuel-based emission factors for NOX + HC and CO meeting CHINA I/II are 25.80~44.87/16.47~46.35 and 2.47~13.22/1.64~5.62 kg/t-fuel, respectively. The energy-based emission factors for NOX + HC, CO, CO2, and PM satisfying CHINA I/II are 5.70~9.24/3.70~9.07, 0.49~2.30/0.36~0.99, 620~683/612~718, and 0.05~0.36/0.05~0.27 g/kWh, respectively. Additionally, the specific emission of NOx rises with the increase in single-cylinder displacement, so the CO emission limit of pure diesel fuel is recommended to be lower than 5 g/kWh. The results in this paper provide valuable basic data for research on and estimation of ship emissions in waterway transportation and for understanding the emission characteristics of marine diesel engines.
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Niu, Ziheng, Jianliang Xiong, Xuesong Ding, and Yao Wu. "Analysis of China’s Carbon Peak Achievement in 2025." Energies 15, no. 14 (July 10, 2022): 5041. http://dx.doi.org/10.3390/en15145041.
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To solve the problem of rising energy use and CO2 emissions, China issued the 14th Five-Year Plan in 2020, emphasizing the need to reduce its carbon intensity and achieve a carbon emission peak before 2030. In order to estimate the future path of carbon peak in China, a novel dataset was constructed to analyze 30 provinces in China, and found that the realization of carbon peaking in 2025 requires a reduction of 1.072 million tons of carbon emissions in 2025, at which point peak carbon emissions will be 11,008.4 million tons. Due to this energy gap caused by carbon emission reduction the total amount of clean electricity has reached 3600 billion kWh. In carbon emission allowance trading, provinces with large carbon emissions, like Jiangsu and Guangdong, prefer to buy carbon allowances, while those with small carbon emissions like Shanxi and Inner Mongolia prefer to sell carbon allowances. In the energy trading market, the overall situation meets the 14th Five-Year Plan of west-east and north-south power transmission, except for Shanghai, Hainan, Hubei, and other provinces selling power, due to excessive power generation from a particular energy source.
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Wang, Hanyun, Chen Tan, Tao Wang, Shengteng Wang, Jihua Huang, and Hao Xu. "Calculation and Analysis of Carbon Emissions in the Construction Industry of Zhejiang Province." E3S Web of Conferences 406 (2023): 03045. http://dx.doi.org/10.1051/e3sconf/202340603045.
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High rise buildings with large volume, high energy consumption, and high carbon emission base have become the focus of emission reduction work in public building types. The key issue of reducing carbon emissions throughout the entire lifecycle of high-rise buildings is how to predict their carbon emissions during the design phase, which is also a current research hotspot. As a developed province in southern China, Zhejiang bears important emission reduction tasks and responsibilities in the construction industry. This article applies the carbon emission factor method to calculate the carbon dioxide emissions in the construction sector of Zhejiang Province from 2005 to 2022. Based on Kaya’s identity, a carbon emission calculation model is established. Combined with scenario analysis method, the carbon emissions in the construction sector of Zhejiang Province from 2023 to 2060 are predicted and compared under different scenarios. The results show that under the scenario of technological breakthrough, the construction field can achieve the carbon peak goal by 2025, but in order to achieve the carbon neutrality goal by 2060, the existing energy conservation measures and carbon reduction technologies need to be strengthened.
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Zhu, Anyu, Qifei Wang, Dongqiao Liu, and Yihan Zhao. "Analysis of the Characteristics of CH4 Emissions in China’s Coal Mining Industry and Research on Emission Reduction Measures." International Journal of Environmental Research and Public Health 19, no. 12 (June 16, 2022): 7408. http://dx.doi.org/10.3390/ijerph19127408.
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CH4 is the second-largest greenhouse gas and has a significant impact on global warming. China has the largest amount of anthropogenic coal mine methane (CMM) emissions in the world, with coal mining emissions (or gas emissions) accounting for 90% of total energy industry emissions. The results of CH4 emission inventories from previous studies vary widely, with differences in the spatial and temporal dimensions of gas emission factors of belowground mining being the main points of disagreement. Affected by the policies of “eliminating backward production capacity” and “transferring energy base to the northwest”, China’s coal production layout has changed greatly in the past ten years, but the closely related CH4 emission factors have not been dynamically adjusted. This paper investigated 23 major coal producing provinces in China, obtained CH4 emission data from coal mining, calculated CH4 emission factors in line with current production conditions, and studied the reduction measures of coal mine gas emission. According to the CH4 emission data of China’s coal mines in 2018, 15.8 Tg of methane is released per year in the coal mining industry in China, and 11.8 Tg after deducting recycling. Shanxi Province’s CH4 emissions are much higher than those of other provinces, accounting for 35.5% of the country’s total emissions. The weighted CH4 emission factor of coal mining in China is 6.77 m3/t, of which Chongqing is the highest at approximately 60.9 m3/t. Compared with the predicted value of the IPCC, the growth trend of CCM has slowed significantly, and the CH4 utilization rate has gradually increased. This change may be aided by China’s coal industry’s policy to resolve excess capacity by closing many high-gas and gas outburst coal mines. In addition, the improvement of coal mine gas extraction and utilization technology has also produced a relatively significant effect. This paper determines the distribution of methane emissions and emission sources in China’s coal mining industry, which is useful in formulating CCM emission reduction targets and adopting more efficient measures.
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Liu, Mo Ru, and Hua Yu Wang. "A Theoretical Analysis of Carbon Emission Trading System in China and the Perfection of its Rules and Regulations." Applied Mechanics and Materials 448-453 (October 2013): 4530–35. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.4530.
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The Carbon emission trading mechanism is an important tool to tackle climate change, promote low-carbon economic development, and facilitate ecological civilization construction. The Carbon emission trading system is set up based on the overall amount control. It controls the greenhouse gas emissions through the marketing mechanism, and reduces the cost of carbon emission control. Through theoretical analyses of the property rights of carbon emission right and the legal relationship of carbon emissions trading ,the theoretical basis for the carbon emissions trading mechanism is established. Currently, the measures to improve the carbon emissions trading mechanisms in China mainly consist of perfecting the trading platform, improving the marketing regulation system, promoting legislations of the total amount control of carbon emissions and the initial allocation of carbon emissions right so as to realize the optimal environmental capacity allocation of carbon emissions.
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Barth, Matthew, Theodore Younglove, Tom Wenzel, George Scora, Feng An, Marc Ross, and Joseph Norbeck. "Analysis of Modal Emissions From Diverse In-Use Vehicle Fleet." Transportation Research Record: Journal of the Transportation Research Board 1587, no. 1 (January 1997): 73–84. http://dx.doi.org/10.3141/1587-09.
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The initial phase of a long-term project with national implications for the improvement of transportation and air quality is described. The overall objective of the research is to develop and verify a computer model that accurately estimates the impacts of a vehicle’s operating mode on emissions. This model improves on current emission models by allowing for the prediction of how traffic changes affect vehicle emissions. Results are presented that address the following points: vehicle recruitment, preliminary estimates of reproducibility, preliminary estimates of air conditioner effects, and preliminary estimates of changes in emissions relative to speed. As part of the development of a comprehensive modal emission model for light-duty vehicles, 28 distinct vehicle/technology categories have been identified based on vehicle class, emission control technology, fuel system, emission standard level, power-to-weight ratio, and emitter level (i.e., normal versus high emitter). These categories and the sampling proportions in a large-scale emissions testing program (over 300 vehicles to be tested) have been chosen in part based on emissions contribution. As part of the initial model development, a specific modal emissions testing protocol has been developed that reflects both real-world and specific modal events associated with different levels of emissions. This testing protocol has thus far been applied to an initial fleet of 30 vehicles, where at least 1 vehicle falls into each defined vehicle/technology category. The different vehicle/technology categories, the emissions testing protocol, and preliminary analysis that has been performed on the initial vehicle fleet are described.
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Song, Xiaowei, and Yongpei Hao. "Vehicular Emission Inventory and Reduction Scenario Analysis in the Yangtze River Delta, China." International Journal of Environmental Research and Public Health 16, no. 23 (November 29, 2019): 4790. http://dx.doi.org/10.3390/ijerph16234790.
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Vehicular emissions have become an important source of air pollution, and their effective reduction control is essential to protect the environment. The aim of this study was to establish multi-year vehicular emission inventories for ten important air pollutants and to analyze emission control policy scenarios based on these inventories. The inter-annual emission analysis results showed that the ten pollutant emissions had different change trends during the past decade. The emissions of CO, non-methane volatile organic compounds (NMVOCS), NOx, PM2.5, PM10, and CH4 tended to increase first and then decrease, but the years in which they began to decrease varied; the emissions of CO2 and NH3 showed the most significant growth trends, increasing by 567% and 4004% in 2015 compared with 1999, while the emissions of N2O and SO2 showed a general increasing trend and decreased obviously in a certain year. Eight scenarios based on emission inventories were designed; compared with the BAU scenario, the ESV scenario was the most effective policy to control NOx, PM2.5, and CH4 emissions; the radical AER scenario could decrease the vehicular emissions of CO, NMVOCs, PM10, CO2, N2O, and NH3; and the RFS scenario could reduce vehicular SO2 emissions significantly by 93.64%.
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Lv, Zongyan, Lei Yang, Lin Wu, Jianfei Peng, Qijun Zhang, Meng Sun, Hongjun Mao, and Jie Min. "Comprehensive Analysis of the Pollutant Characteristics of Gasoline Vehicle Emissions under Different Engine, Fuel, and Test Cycles." Energies 15, no. 2 (January 17, 2022): 622. http://dx.doi.org/10.3390/en15020622.
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Vehicle exhaust emissions have seriously affected air quality and human health, and understanding the emission characteristics of vehicle pollutants can promote emission reductions. In this study, a chassis dynamometer was used to study the emission characteristics of the pollutants of two gasoline vehicles (Euro 5 and Euro 6) when using six kinds of fuels. The results show that the two tested vehicles had different engine performance under the same test conditions, which led to a significant difference in their emission characteristics. The fuel consumption and pollutant emission factors of the WLTC cycle were higher than those of the NEDC. The research octane number (RON) and ethanol content of fuels have significant effects on pollutant emissions. For the Euro 5 vehicle, CO and particle number (PN) emissions decreased under the WLTC cycle, and NOx emissions decreased with increasing RONs. For the Euro 6 vehicle, CO and NOx emissions decreased and PN emissions increased with increasing RONs. Compared with traditional gasoline, ethanol gasoline (E10) led to decreases in NOx and PN emissions, and increased CO emissions for the Euro 5 vehicle, while it led to higher PN and NOx emissions and lower CO emissions for the Euro 6 vehicle. In addition, the particulate matter emitted was mainly nucleation-mode particulate matter, accounting for more than 70%. There were two peaks in the particle size distribution, which were about 18 nm and 40 nm, respectively. Finally, compared with ethanol–gasoline, gasoline vehicles with high emission standards (Euro 6) are more suitable for the use of traditional gasoline with a high RON.
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Pan, Zhongjian, Yu Deng, and Lizhi Cheng. "Regular Analysis of Aero-Diesel Piston Engine between Combustion Chamber Size and Emission." International Journal of Aerospace Engineering 2019 (May 5, 2019): 1–12. http://dx.doi.org/10.1155/2019/8690906.
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The emission of aero-engines has been a focused issue, studying the regular of combustion chamber size on engine emission performance, with an aviation diesel piston engine as the object of study; the numerical model of diesel combustion spray and emission model are analyzed; and the dynamics grid of the combustion chamber is meshed by FIRE software, analyzing the relationship between the reentrant diameter, the maximum depth of the combustion chamber, and the emission generation, comparing the NOx and soot emissions under different combustion chamber sizes. The results show that reducing appropriately the reentrant-max diameter ratio and max diameter-max depth ratio of the combustion chamber can reduce emissions when maintaining the same compression ratio by adjusting the mid-depth. Modifying the geometry parameters of the combustion chamber to verify regularity, it was found that engine NOx emission decreased by 28% and soot emission decreased by 3.6% when changing the size, which verified the correctness of regular analysis.
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Gu, Alun, Sheng Zhou, Shuangqing Xu, and Qing Tong. "Energy Industry Methane Emissions Trajectory Analysis in China until 2050." Atmosphere 13, no. 12 (November 28, 2022): 1989. http://dx.doi.org/10.3390/atmos13121989.
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Methane (CH4) is an important greenhouse gas. There is increasing attention to CH4 abatement strategies because of its contribution to short-term warming and strong benefits of decreasing CH4 emissions. China greenhouse gas inventory methods are used to predict CH4 emissions from the energy industry and to assess the potentials of CH4 abatement policies and techniques by 2050. The NDC scenario results show using oil and gas as transitional clean energy sources instead of coal will increase CH4 emissions from oil and gas industries at least 70%, but CH4 emissions from the coal industry will decrease 45%, meaning total CH4 emissions from the energy industry will continually decrease at least 30% in 2030 compared with 2020. Energy-related CH4 emissions might peak around 2025, ahead of CO2 emission peaking. CH4 emissions will then decrease slightly and decrease markedly after 2030. Emissions in 2050 are expected to be 32% lower than emissions in 2020. In an extreme scenario, emissions may be 90% lower in 2050 than in 2020. It is suggested that the verification system for the energy industry’s CH4 emission accounting at the national level be improved and CH4 control targets in line with national emission targets and the “14th Five-Year Plan” development stage be formulated.
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Jia, Chengye, Shuang Feng, Hong Chu, and Weige Huang. "The Heterogeneous Effects of Urban Form on CO2 Emissions: An Empirical Analysis of 255 Cities in China." Land 12, no. 5 (April 28, 2023): 981. http://dx.doi.org/10.3390/land12050981.
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Urban form is closely related to CO2 emissions and the accurate estimation of the impact of urban form on CO2 emissions plays an important role in tackling climate change caused by the emission of greenhouse gases. In this paper, we quantitatively investigate the effects of urban form on CO2 emission and its efficiency from three perspectives: urban expansion, compactness, and complexity. By using panel quantile regression with fixed effects, we show that: (1) The estimation results about the relationship between urban form and CO2 emission and its efficiency are consistent with the literature. (2) The partial effects of urban form without controlling for socioeconomic factors are heterogeneous throughout the conditional distribution of CO2 emission and its efficiency. (3) Taking into consideration that the partial effects of urban form on CO2 emission and its efficiency might depend on the magnitude of socioeconomic factors, we include interaction terms into our model and find that the interaction effects between socioeconomic factors and urban form are heterogeneous across cities with different levels of CO2 emission and its efficiency. Our empirical findings shed light on the optimization of urban form in improving the CO2 emission efficiency, providing policy makers with effective ways of reducing CO2 emissions across cities with different levels of CO2 emissions.
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Wang, Zhihong, Penghui Wu, Nenghui Yu, Yuanjun Zhang, and Zhijun Wang. "Analysis of the influence of RDE test data processing methods on the emission results of China 6 light duty vehicles." E3S Web of Conferences 268 (2021): 01022. http://dx.doi.org/10.1051/e3sconf/202126801022.
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The CO2 moving average window(MAW) method is used to process RDE (real drive emissions) emissions data in China 6 light duty vehicle emissions regulations, while the Euro 6 light duty vehicle emission regulations allow to use both of MAW and power binning(PB) method to deal with RDE emission data. In order to study the difference between the two data processing methods and analyze the differences in the emission results, 10 different types of light duty vehicles are conducted RDE test with PEMS (portable emissions measurement system), and the test data are processed by the two methods separately. The results show that there is a little difference between MAW and PB, while both of them can satisfy the vehicle emission assessment. The PB method calculates the emission factors higher than the MAW method. After removing the cold start and idle condition data, the results of PB is similar to MAW. Besides, reducing the average speed limit of urban working conditions in PB has a greater impact on the urban driving condition emission factor, but less on the whole cycle emission factor.
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Li, Wei, Hao Li, Huixia Zhang, and Shuang Sun. "The Analysis of CO2Emissions and Reduction Potential in China’s Transport Sector." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/1043717.
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China’s transport sector is responsible for approximately 10% of national CO2emissions. In the process of industrialization and urbanization of China, emissions from transport sector would continuously increase. In order to investigate the emissions and reduction potential and provide the policy guidance for policymakers in China’s transport sector, this study decomposed the CO2emissions using the Kaya identity, calculated the contribution based on the Logarithmic Mean Divisia Index (LMDI) method to explore the underlying determinants of emissions change, and then constructed different scenarios to predict the emissions and estimate the potential of emission reduction in the future. Results indicated that carbon emissions in China’s transport sector have increased from 123.14 Mt in 1995 to 670.76 Mt in 2012. Income effect is the dominant factor that results in the increase of emissions while energy intensity effect is the main driving force to lower carbon emissions. The transportation modal shifting, transportation intensity change, and population growth have the positive but relatively minor impact on emissions. The accumulated emission reduction is expected to be 1825.97 Mt, which is 3 times more than the emissions in 2010. Policy recommendations are thus put forward for future emission reduction.
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Feng, Yanbiao, Jue Yang, and Zuomin Dong. "Fuel Selections for Electrified Vehicles: A Well-to-Wheel Analysis." World Electric Vehicle Journal 12, no. 3 (September 9, 2021): 151. http://dx.doi.org/10.3390/wevj12030151.
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Electrified vehicles (xEV), especially the battery electric vehicle (BEV), are burgeoning and growing fast in China, aimed at building a sustainable, carbon-neutral future. This work presents an overview and quantitative comparison of the carbon-neutral vehicles fuel options based on the well-to-wheel (WTW) analysis. A more intuitionistic figure demonstrates the fuel options for greenhouse gas (GHG) emissions and describes the sustainability. Electricity and hydrogen shift the tailpipe emissions to the upstream process, forming larger WTW emissions from a fuel cycle view. The electricity WTW GHG emission reaches as much as twice that of gasoline. However, the high efficiency of the electric drive system improves the WTW emission performance from a vehicle view, making the lowest WTW emission of BEV. The fuel options’ technical and environmental perspectives are presented. Finally, long-term carbon-neutral vehicle development is discussed.
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Yang, Na, Zilong Zhang, Bing Xue, Junxia Ma, Xingpeng Chen, and Chenyu Lu. "Economic Growth and Pollution Emission in China: Structural Path Analysis." Sustainability 10, no. 7 (July 23, 2018): 2569. http://dx.doi.org/10.3390/su10072569.
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The relationship between economic growth and environmental pollution has long been a controversial topic. However, simply the detection of the existence of environmental Kuznets curve (EKC) is not enough to understand how economic growth induced environmental pollution. This study investigated the path and mechanism of the effect of economic growth on the emission of two types of environmental pollutants, that is, industrial smoke and dust and sulfur dioxide, by using a structural equation model and a sample of 283 prefecture-level cities in China in 2005 and 2015. The research results show that economic growth exerted both direct and indirect effects on the emission of the two environmental pollutants. In addition to a direct impact through the economic scale effect, economic growth also indirectly impacted the two environmental pollutants emissions through three mediators, that is, industrial structure, technological innovations and environmental regulations. For different pollutants, the effect paths of economic growth on their emission showed both similarities and differences. First, with regards to industrial smoke and dust emissions and sulfur dioxide emissions, the effects of economic growth on the amount of these two emissions through environmental regulations and the industrial structure were negative inhibitory effects and positive promoting effects, respectively. This means that in prefectural-level cities in China, environmental regulation factors have produced some effects in reducing the emissions of these two pollutants while the industrial structure (level of industrialization) can increase the emissions of these two pollutants. However, the effect strength of these two paths shows a gradual weakening. Second, these two paths differ in effect strength and its changes. The positive promoting effects of the industrial structure on pollutant emission are significantly higher than the inhibitory effects of environmental regulation. In addition, our study also found that the direct impact path of economic growth on environmental pollution also passed significance testing, particularly in 2015. This shows that other reasons affect pollutant emission, such as system factors, spatial migration of industries and so forth.
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Fatkhullah, Mukhammad, Nugroho Rinadi Pamungkas, Muhammad Alhada Fuadilah Habib, and Iwed Mulyani. "Reducing Greenhouse Gas Emissions through Community-based Action: an Analysis of the Program Kampung Iklim in Indonesia." Asean Social Work Journal 11, no. 1 (June 30, 2023): 28–37. http://dx.doi.org/10.58671/aswj.v11i1.33.
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One strategy to deal with climate change is accelerating greenhouse gas (GHG) emissions reduction through a community-based approach. In Indonesia, the government pursues community engagement to reduce GHG emissions through the Program Kampung Iklim (ProKlim). We collected data from 2015-2018, then measured emission reductions (ER) in the waste, livestock, agriculture, energy, and forestry sectors by subtracting baseline and mitigation emissions. The analysis compares the emission reductions achieved through Community-based Action (CBA) to the national emission reduction achievement. The results show that the sector with the most participation rates and the most significant contributor to emission reductions in ProKlim is the energy and waste sector. On the other hand, the sectors that attract the least public attention and emission reduction are the livestock and agriculture sectors. Through 61 community groups and 138 actions, from 2015 to 2018, CBA contributed 133,312.38 tons of CO2e emission reductions, 0.012% to national emission reductions, with the participation value equivalent to USD$266.080. Based on this number, CBA can be the answer to Indonesia's low position in international carbon trading. A strategy that focuses on increasing community participation is needed to optimize the contribution of the CBA to large-scale national emission reductions.
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Huang, Yuan Sheng, and Jie Xu. "Research on Carbon Emission Measurement of Electricity Sector Based on Scenario Analysis Method." Applied Mechanics and Materials 367 (August 2013): 327–32. http://dx.doi.org/10.4028/www.scientific.net/amm.367.327.
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Delivering a low-carboneconomy puts ourselves on a path to cut CO2 emission, which is the maincontributor to global warming. Developing low-carbon technology in electricityindustry will play an important role in future since electricity always beingthe biggest emission source. This paper analysis electricity carbon emissions usedscenario analysis method in Baoding, forecasts power load based on economictargets and energy efficiency targets, and analysis CO2 emissions by coal powernew technology application scenarios, and then ,carried out some suggestions onthe electricity sector’s CO2 emission reduction work used the analysis results.
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Li, Sen, Yanwen Lan, and Lijun Guo. "Analysis of Carbon Emission and Its Temporal and Spatial Distribution in County-Level: A Case Study of Henan Province, China." Nature Environment and Pollution Technology 21, no. 2 (June 1, 2022): 447–56. http://dx.doi.org/10.46488/nept.2022.v21i02.003.
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Estimating carbon emissions and assessing their contribution are critical steps toward China’s objective of reaching a “carbon peak” in 2030 and “carbon neutrality” in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs.
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Chen, Xiaoli, Zhiwei Liao, Zhihua Gao, Qian Li, Peng Lv, Guangyu Zheng, and Kun Yang. "A Calculation Model of Carbon Emissions Based on Multi-Scenario Simulation Analysis of Electricity Consumption." Sustainability 14, no. 14 (July 18, 2022): 8765. http://dx.doi.org/10.3390/su14148765.
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In order to reach the peak of carbon emission in China by 2030 and to meet the low-carbon conversion of energy and the growing demand for electricity, this study aims to propose a more accurate and scientific method to calculate the carbon emissions of the entire power industry chain. This paper analyzes the historical actual operation data of the energy and power industry from 2000 to 2020, and originally proposes a carbon emission calculation model based on a multi-scenario simulation analysis of electricity consumption. This paper is an original study from the perspective of the whole industry chain of electricity production, transmission, and consumption. Firstly, a carbon emission model of the power system is established based on the carbon emission composition and transmission mechanism of the whole power industrial chain, which consists of calculation models for carbon emissions from overall electricity demand and carbon emissions from electricity network losses. Secondly, the concept of carbon emission coefficient is proposed, and the key parameters of the carbon emission coefficient of the power system are obtained through the econometric model. On this basis, the carbon emission coefficient is obtained by regression fitting of multiple key parameters according to historical data. Finally, electricity consumption per unit output value (ECPUOV) and per capita electricity consumption (PCEC) are used to predict electricity consumption in the next 15 years. This paper also makes a quantitative analysis of the relationship between CO2 emissions from the power system and electricity consumption. This paper takes G province, which ranks first in total energy consumption and economic aggregate in China, as an example and calculates its CO2 emissions and achievement of peak CO2 emissions by multi-scenario analysis. The case study results show that the low carbon scenario(LC) is the best route for G province to peak CO2 emissions from energy consumption. The method proposed in this paper can set an achievable goal of 2030 carbon peaking for the government and industry policymakers, and find a feasible implementation path.
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Gao, You Shan, and Ai Hong Wang. "Energy Consumption and Emissions Analysis of Natural Gas Exploitation." Advanced Materials Research 335-336 (September 2011): 1525–29. http://dx.doi.org/10.4028/www.scientific.net/amr.335-336.1525.
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Abstract. This paper analyzed the primary energy consumption and emission of VOC, CO, NOx, SO2, PM, CO2, CH4, N2O during natural gas (NG) exploitation, it showing that more than 65% of VOC, NOX, SOx, CH4, CO2and greenhouse gas were discharged by electric energy and heat energy consumption during NG exploitation in all technique energy emission. Because of its important in NG exploitation, the consumption of electric energy and heat energy and its emissions produced should be reduced in order to reduce the emissions of NG exploitation.
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Geng, Guannan, Qiang Zhang, Randall V. Martin, Jintai Lin, Hong Huo, Bo Zheng, Siwen Wang, and Kebin He. "Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis." Atmospheric Chemistry and Physics 17, no. 6 (March 28, 2017): 4131–45. http://dx.doi.org/10.5194/acp-17-4131-2017.
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Abstract. Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing six gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem-modeled tropospheric NO2 vertical columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 vertical columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 vertical columns. Using vehicle population and an updated road network for the on-road transport sector could substantially enhance urban emissions and improve the model performance. When further applying industrial gross domestic product (IGDP) values for the industrial sector, modeled NO2 vertical columns could better capture pollution hotspots in urban areas and exhibit the best performance of the six cases compared to satellite-based NO2 vertical columns (slope = 1.01 and R2 = 0. 85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.
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Ottosen, T. B., K. E. Kakosimos, C. Johansson, O. Hertel, J. Brandt, H. Skov, R. Berkowicz, T. Ellermann, S. S. Jensen, and M. Ketzel. "Analysis of the impact of inhomogeneous emissions in the Operational Street Pollution Model (OSPM)." Geoscientific Model Development 8, no. 10 (October 13, 2015): 3231–45. http://dx.doi.org/10.5194/gmd-8-3231-2015.
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Abstract. Semi-parameterized street canyon models, as e.g. the Operational Street Pollution Model (OSPM®), have been frequently applied for the last two decades to analyse levels and consequences of air pollution in streets. These models are popular due to their speed and low input requirements. One often-used simplification is the assumption that emissions are homogeneously distributed in the entire length and width of the street canyon. It is thus the aim of the present study to analyse the impact of this assumption by implementing an inhomogeneous emission geometry scheme in OSPM. The homogeneous and the inhomogeneous emission geometry schemes are validated against two real-world cases: Hornsgatan, Stockholm, a sloping street canyon; and Jagtvej, Copenhagen; where the morning rush hour has more traffic on one lane compared to the other. The two cases are supplemented with a theoretical calculation of the impact of street aspect (height / width) ratio and emission inhomogeneity on the concentrations resulting from inhomogeneous emissions. The results show an improved performance for the inhomogeneous emission geometry over the homogeneous emission geometry. Moreover, it is shown that the impact of inhomogeneous emissions is largest for near-parallel wind directions and for high aspect ratio canyons. The results from the real-world cases are however confounded by challenges estimating the emissions accurately.
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Ottosen, T. B., K. E. Kakosimos, C. Johansson, O. Hertel, J. Brandt, H. Skov, R. Berkowicz, T. Ellermann, S. S. Jensen, and M. Ketzel. "Analysis of the impact of inhomogeneous emissions in a semi-parameterized street canyon model." Geoscientific Model Development Discussions 8, no. 2 (February 4, 2015): 935–77. http://dx.doi.org/10.5194/gmdd-8-935-2015.
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Abstract. Semi-parameterized street canyon models, as e.g. the Operational Street Pollution Model (OSPM®), have been frequently applied for the last two decades to analyse levels and consequences of air pollution in streets. These models are popular due to their speed and low input requirements. One often used simplification is the assumption that emissions are homogeneously distributed in the entire length and width of the street canyon. It is thus the aim of the present study to analyse the impact of this assumption by implementing an inhomogeneous emission geometry scheme in OSPM. The homogeneous and the inhomogeneous emission geometry schemes are validated against two real-world cases: Hornsgatan, Stockholm, a sloping street canyon; and Jagtvej, Copenhagen; where the morning rush hour has more traffic on one lane compared to the other. The two cases are supplemented with a theoretical calculation of the impact of street aspect (height / width) ratio and emission inhomogeneity on the concentrations resulting from inhomogeneous emissions. The results show an improved performance for the inhomogeneous emission geometry over the homogeneous emission geometry. Moreover, it is shown that the impact of inhomogeneous emissions is largest for near-parallel wind directions and for high aspect ratio canyons. The results from the real-world cases are however confounded by challenges estimating the emissions accurately.
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Woo, Donghan, and Namkyun Im. "Spatial Analysis of the Ship Gas Emission Inventory in the Port of Busan Using Bottom-Up Approach Based on AIS Data." Journal of Marine Science and Engineering 9, no. 12 (December 20, 2021): 1457. http://dx.doi.org/10.3390/jmse9121457.
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Dense hub port-cities have been suffering from ship gas emissions causing atmospheric pollution and a threat to the health of coastal residents. To control ship gas emissions, many regulations have been established internationally. Analyses of ship gas emission inventories are essential to quantify mass and track emission changes over time in a given geographical area. Based on the gas emissions inventory, applicable regulations such as Emission Control Area (ECA) realization and Vessel Speed Reduction (VSR) may be established. The ship gas emission inventory (CO2, CO, NOx, SOx and PM) from the Busan Port (BP), including the North Port (NP) and Gamcheon Dadae-po Port (GDP), which is the biggest port in the Republic of Korea and which is also surrounded by residential, commercial, and industrial areas, were spatially analyzed. To calculate geographical ship gas emissions in real-time, this study introduces a bottom-up methodology using Automatic Identification System (AIS) data. According to the geographical density analysis of the gas emissions inventory, this study highlights that about 35% of the annual ship gas emissions of BP in 2019 were concentrated in the passageway to NP because of high ship speeds when leaving or arriving at the port. To protect the health of coastal residents, ship speed limit regulations along the passageway should be revised based on our spatial analysis results. The spatial analysis of the ship gas emission inventory in BP will be useful basic data for properly evaluating the local gas emission state on newly established or revised environmental regulations for BP.