To see the other types of publications on this topic, follow the link: Emissions trading Mathematical models.
Journal articles on the topic 'Emissions trading Mathematical models'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Emissions trading Mathematical models.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Qiu, Xiao Ming, and Jia Sheng Yang. "Emissions Trading System and Supporting Policies under an Emissions Reduction Framework." Advanced Materials Research 518-523 (May 2012): 4863–68. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.4863.
Full textAbstract:
This paper, through building mathematical models, makes an analysis on the emissions trading system under an abatement framework. And the authors obtained four conclusions: (1) The impact by environmental taxes on the existing firms’ choices of optimal discharging amounts is uncertain, the existing firms’ discharging amounts will be on the decrease with the increased prices of emissions permits, and paid initial emissions allowances will reduce the existing firms’ profits; (2) Under an intertemporal trading system, the existing firms’ holding the permits conforms to the principle of profit maximization; (3) Under the intertemporal trading system, the prices for emissions permits for the entrant firms are always on the rise and so are their access costs into the industries, thus frustrating local governments’ efforts in attracting investments; and (4) Emissions reduction policies are good regulatory instruments for promoting local economic welfare and realizing sustainable development. The paper also gives some suggestions for triggering and activating the emissions trading system and formulating supportive policies.
2
Pasicko, Robert, Slavica Robic, and Zeljko Tomsic. "Modelling CO2 emissions impacts on Croatian power system." Thermal Science 14, no. 3 (2010): 655–69. http://dx.doi.org/10.2298/tsci1003655p.
Full textAbstract:
Today?s electrical energy landscape is characterized by new challenges such as deregulation, liberalization of energy markets, increased competition, growing demands on security of supply, price insecurities, and demand to cut CO2 emissions. All mentioned challenges are calling for consideration of various options (like nuclear, coal, gas or renewable scenarios) and for better understanding of energy systems modelling in order to optimize proper energy mix. Existing models are not sufficient any more and planners will need to think differently in order to face these challenges. European emission trading scheme (EU ETS) started in 2005 and it has great influence on power system short term and long term planning. Croatia is obliged to establish a national scheme for trading of greenhouse gas emission allowances from the year 2010, which will be focused on monitoring and reporting only until accession to EU when it will be linked with EU ETS. Thus, for Croatian power system it is very important to analyze possible impacts of CO2 emissions. Analysis presented in this paper was done by two different models: mathematical model, based on short run marginal costs (SRMC, relevant for fuel switch in existing power plant and merit order change) and long run marginal costs (LRMC, relevant for new investment decisions); and electricity market simulation model PLEXOS, which was used for modelling Croatian power system during development of the Croatian energy strategy in 2008. Results of the analysis show important impacts that emission trading has on Croatian power system, such as influence of emission price rise on price of electricity and on emission quantity, and changes in power plants output that appear with emission price rise. Breakeven point after which gas power plant becomes more competitive than coal is 62 ?/tCO2 for SRMC and 40 ?/tCO2 for LRMC. With CO2 prices above 31 ?/tCO2 wind is more competitive than gas or coal, which emphasizes importance that emission price has on competitiveness of renewables.
3
Tsai, Wen-Hsien. "Carbon Taxes and Carbon Right Costs Analysis for the Tire Industry." Energies 11, no. 8 (August 14, 2018): 2121. http://dx.doi.org/10.3390/en11082121.
Full textAbstract:
As enterprises are the major perpetrators of global climate change, concerns about global warming, climate change, and global greenhouse gas emissions continue to attract attention, and have become international concerns. The tire industry, which is a high-pollution, high-carbon emission industry, is facing pressure to reduce its carbon emissions. Thus, carbon prices and carbon trading have become issues of global importance. In order to solve this environmental problem, the purpose of this paper is to combine mathematical programming, Theory of Constraints (TOC), and Activity-Based Costing (ABC) to formulate the green production decision model with carbon taxes and carbon right costs, in order to achieve the optimal product mix decision under various constraints. This study proposes three different scenario models with carbon taxes and carbon right used to evaluate the effect on profit of changes in carbon tax rates.
4
André, Francisco J., and Luis Miguel de Castro. "Market Power in Output and Emissions Trading." Games 11, no. 4 (October 12, 2020): 43. http://dx.doi.org/10.3390/g11040043.
Full textAbstract:
This article focuses on the strategic behavior of firms in the output and the emissions markets in the presence of market power. We consider the existence of a dominant firm in the permit market and different structures in the output market, including Cournot and two versions of the Stackelberg model, depending on whether the permit dominant firm is a leader or a follower in the output market. In all three models, the firm that dominates the permit market is more sensitive to its initial allocation than its competitor in terms of abatement and less sensitive in terms of output. In all three models, output is decreasing and the permit price is increasing in the permit dominant firm’s initial allocation. In the Cournot model, permit dominance is fruitless in terms of output and profit if the initial allocation is symmetric. Output leadership is more relevant than permit dominance since an output leader always tends to, ceteris paribus, produce more and make more profit whether it also dominates the permit market or not. This leadership can only be overcompensated for by distributing a larger share of permits to the output follower, and only if the total number of permits is large enough. In terms of welfare, Stackelberg is always superior to Cournot. If the initial permit allocation is symmetric, welfare is higher when the same firm dominates the output and the permit market at the same time.
5
Lucas, D. D., C. Yver Kwok, P. Cameron-Smith, H. Graven, D. Bergmann, T. P. Guilderson, R. Weiss, and R. Keeling. "Designing optimal greenhouse gas observing networks that consider performance and cost." Geoscientific Instrumentation, Methods and Data Systems 4, no. 1 (June 16, 2015): 121–37. http://dx.doi.org/10.5194/gi-4-121-2015.
Full textAbstract:
Abstract. Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH2FCF3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.
6
Lucas, D. D., C. Yver Kwok, P. Cameron-Smith, H. Graven, D. Bergmann, T. P. Guilderson, R. Weiss, and R. Keeling. "Designing optimal greenhouse gas observing networks that consider performance and cost." Geoscientific Instrumentation, Methods and Data Systems Discussions 4, no. 2 (December 23, 2014): 705–49. http://dx.doi.org/10.5194/gid-4-705-2014.
Full textAbstract:
Abstract. Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH2FCF3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.
7
Weiss, Ray F., and Ronald G. Prinn. "Quantifying greenhouse-gas emissions from atmospheric measurements: a critical reality check for climate legislation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1943 (May 28, 2011): 1925–42. http://dx.doi.org/10.1098/rsta.2011.0006.
Full textAbstract:
Emissions reduction legislation relies upon ‘bottom-up’ accounting of industrial and biogenic greenhouse-gas (GHG) emissions at their sources. Yet, even for relatively well-constrained industrial GHGs, global emissions based on ‘top-down’ methods that use atmospheric measurements often agree poorly with the reported bottom-up emissions. For emissions reduction legislation to be effective, it is essential that these discrepancies be resolved. Because emissions are regulated nationally or regionally, not globally, top-down estimates must also be determined at these scales. High-frequency atmospheric GHG measurements at well-chosen station locations record ‘pollution events’ above the background values that result from regional emissions. By combining such measurements with inverse methods and atmospheric transport and chemistry models, it is possible to map and quantify regional emissions. Even with the sparse current network of measurement stations and current inverse-modelling techniques, it is possible to rival the accuracies of regional ‘bottom-up’ emission estimates for some GHGs. But meeting the verification goals of emissions reduction legislation will require major increases in the density and types of atmospheric observations, as well as expanded inverse-modelling capabilities. The cost of this effort would be minor when compared with current investments in carbon-equivalent trading, and would reduce the volatility of that market and increase investment in emissions reduction.
8
Han, Qiang, Zhenlong Yang, Zheng Zhang, and Liang Shen. "Offline and Online Channel Selection of Low-Carbon Supply Chain under Carbon Trading Market." Mathematical Problems in Engineering 2021 (January 4, 2021): 1–17. http://dx.doi.org/10.1155/2021/6627937.
Full textAbstract:
This paper investigates the low-carbon product manufacturer’s different decision behavior in the offline traditional retail channel and online e-commerce channel when the carbon trading market has been established. The low-carbon product manufacturer is both in the carbon trading market and product market. In the former market, the manufacturer can gain profits by selling its emission quota. In the latter market, the manufacturer has two sales channel options, the traditional offline retailer and the online e-commerce platform. These two channels make two supply chains, the manufacturer-led offline one and the e-commerce platform-led online one. This paper combines the carbon trading market with the product market, formulates different Stackelberg game models, compares the manufacturer’s decision under two channels and the impact of channels on the carbon emission, does sensitivity analysis, and verifies the conclusions with numerical examples. Our findings are (1) the establishment of the carbon market will help the manufacturer reduce its carbon emission, especially for those sensitive to the carbon price and those with too much emissions; (2) whether the manufacturer turns to the online channel depends on the consumers’ sensitivity to the sales service, and consumers’ attention will guide the way to the online mode; (3) which mode is conducive to carbon emission reduction relies on the product type: the e-commerce platform does well for daily necessities of mass production while the traditional channel is better for experience goods.
9
Helena Božić. "THE PURPOSES AND METHODS OF ENERGY SYSTEM MODELING." Journal of Energy - Energija 55, no. 5 (January 20, 2023): 530–49. http://dx.doi.org/10.37798/2006555398.
Full textAbstract:
This article describes the purpose of energy system modeling and the classification of planning models according to approaches and methodologies. The advent of modern computers and computer programs has simplified the use of planning models. Such models employ powerful mathematical algorithms and databases which can solve highly complex problems in a relatively short time. This has led to energy-ecology-economy (E3) models, which are simultaneously able to consider questions in connection with energy supply, ecology and economics. The characteristics of a MARKAL model are presented separately through an example of integration with other planning models. It is demonstrated that the application of an optimizing MARKAL model for the planning of the energy supply system of the Republic of Croatia is of great significance for the analysis of the energy market of South Eastern Europe, the use of renewable energy sources, energy efficiency and emission trading.
10
Wang, Xiaoya. "The impact of China's entry into the carbon trading market on European carbon prices." BCP Business & Management 34 (December 14, 2022): 1542–50. http://dx.doi.org/10.54691/bcpbm.v34i.3210.
Full textAbstract:
As the world's largest greenhouse gas emission country, the success or failure of the Chinese national carbon emissions trading market will largely determine climate change’s further development. Chinese national carbon market, which was opened on July 16, 2021, will also exert spillover effects on carbon trading markets in other countries, including the European carbon emissions trading market, which will have a more significant impact. This paper uses the double difference model(DID), sets the price of European certification emission reduction(CER) as the dependent variable, and takes China's entering into the carbon emissions trading market and the RMB exchange rate as the independent variable to test the influences of China's entering in the carbon emissions trading market on the European CER price. After that, non-linear machine learning models such as support vector machines are used to fit and predict the price of European CER, which further verifies that the opening of the Chinese national carbon emissions trading market contributes to a decline in European CER price.
11
Solomon, Barry D., and Hugh S. Gorman. "State-Level Air Emissions Trading: The Michigan and Illinois Models." Journal of the Air & Waste Management Association 48, no. 12 (December 1998): 1156–65. http://dx.doi.org/10.1080/10473289.1998.10463751.
Full text
12
Li, Hui, Rou Li, Meng Shang, Yu Liu, and Dandan Su. "Cooperative decisions of competitive supply chains considering carbon trading mechanism." International Journal of Low-Carbon Technologies 17 (December 2, 2021): 102–17. http://dx.doi.org/10.1093/ijlct/ctab085.
Full textAbstract:
Abstract Carbon emissions trading policy is a market mechanism which promotes global greenhouse gas emissions reduction and reduces global carbon dioxide emissions. The emissions reduction in the supply chain operation has become a hot issue in supply chain management. Thus, this paper studies the optimal cap setting and pricing in chain-to-chain system under carbon emissions trading mechanism. Based on the double decentralized scenario, the five different cooperation models are established by introducing the structural cooperation and the contractual cooperation (the wholesale price contract) of supply chains. The optimal solutions of these models are obtained through the Stackelberg game and Nash game. The results show that the bargaining power of the supply chains is changed by the asymmetric competition structure. Besides, the government should emphasize the influencing factors change of the cap in the process of setting carbon emissions cap.
13
Sun, Hao, and Guangkuo Gao. "Bank Credit Financing and Trade Credit Financing Based on Carbon Emission Trading." Mathematical Problems in Engineering 2022 (January 19, 2022): 1–11. http://dx.doi.org/10.1155/2022/6781650.
Full textAbstract:
Bank credit financing and trade credit financing are two basic ways for small- and medium-sized enterprises to solve financial difficulties. We studied a supply chain financing (SCF) system with one capital-constrained manufacturer and one capital-rich supplier, in which manufacturers can choose bank credit financing (BCF) or trade credit financing (TCF) to solve financial difficulties. Unlike the traditional SCF, we considered the influence of the carbon emission trading mechanism, and we designed BCF and TCF models and derived the equilibrium strategies of the supply chain members under a carbon-constrained environment. The research shows that the emission reduction level of manufacturers increases with the increase in carbon emission trading price, and the output of manufacturers increases with the increase in emission reduction level of manufacturers. When the manufacturer’s emission reduction level is low, the supplier’s benefits under BCF are higher than those under TCF. There is a threshold for the manufacturer’s emission reduction level. When the emission reduction level is higher than this threshold, the manufacturer chooses BCF mode with higher benefits; on the contrary, TCF mode is more profitable.
14
Li, Xiaoqi, Dingfei Guo, and Chao Feng. "The Carbon Emissions Trading Policy of China: Does It Really Promote the Enterprises’ Green Technology Innovations?" International Journal of Environmental Research and Public Health 19, no. 21 (November 3, 2022): 14325. http://dx.doi.org/10.3390/ijerph192114325.
Full textAbstract:
The carbon emissions trading policy has profound impacts on the production and operation of enterprises. The aim of this study is to examine the effects of the carbon emissions trading policy on enterprises’ green technology innovations by using PSM−DID models. The results showed that: (1) the carbon emissions trading policy has a facilitating effect on green technology innovation of China’s enterprises in pilot cities; (2) there is significant spatial heterogeneity in this effect and it is extremely beneficial to enterprises’ green technology innovations in eastern China; and (3) the trading policy is proved to have significant positive effects on green technology innovations of non-state and non-high-tech enterprises, while it has no effects on that of state-owned and high-tech enterprises. The above findings were corroborated by the placebo test and other methods.
15
Thibodeaux, L. J., K. T. Valsaraj, C. Springer, and G. Hildebrand. "Mathematical models for predicting chemical vapor emissions from landfills." Journal of Hazardous Materials 19, no. 1 (January 1988): 101–18. http://dx.doi.org/10.1016/0304-3894(88)85076-3.
Full text
16
Guo, Jianfeng, Bin Su, Guang Yang, Lianyong Feng, Yinpeng Liu, and Fu Gu. "How Do Verified Emissions Announcements Affect the Comoves between Trading Behaviors and Carbon Prices? Evidence from EU ETS." Sustainability 10, no. 9 (September 12, 2018): 3255. http://dx.doi.org/10.3390/su10093255.
Full textAbstract:
Verified emissions announcements are the most influential events in the European Union emissions trading scheme (EU ETS); they reveal demand information and have a significant impact on the carbon market. The extant literature tends to focus on examining the impacts of these verification events on the prices of carbon allowances, while scholars barely discuss how trading behaviors react to the announcements. Moreover, most of the studies are carried out from a macroeconomic perspective. This paper fills this gap by analyzing the impacts of the verified emissions announcements on the comoves of trading behaviors and carbon prices in Phase I (2005–2007) and Phase II (2008–2012). Specifically, we construct GARCH models to investigate the events’ heterogeneous influences in different periods, i.e., the complete periods, the announcement periods, the pre- and post-announcement periods. We observe that the verified emissions announcements boost the volume of compliance trading, particularly in Phase I. Furthermore, we show that the over-allocation of carbon allowances can be even more influential in disturbing the comoves than the verification events. Our microeconomic findings confirm the maturity of EU ETS in Phase II, exhibiting good agreement with the extant macroeconomic literature.
17
Liou, Je-Liang, and Pei-Ing Wu. "Equity criterion for initial rights CO2 emissions allocations under emissions trading: cooperation or conflict among nations?" Environment and Development Economics 20, no. 5 (September 5, 2014): 587–610. http://dx.doi.org/10.1017/s1355770x14000618.
Full textAbstract:
AbstractThis study constructs comprehensive operational equitable initial rights of emissions allocation models by estimating the total abatement cost based on the criteria of egalitarianism, sovereignty, the ability to pay, polluter pays and various scenarios of the Greenhouse Development Rights (GDRs) framework among groups of countries or individual nations. The analyses provide the potential crux regarding the agreements, cooperation and/or conflict among nations for joining the trading. The results show that the polluter pays principle generates the greatest total abatement cost saving for upper-middle and low-middle income nations, but not for others. Full capacity GDRs apply to China, egalitarianism to India and sovereignty to the United States on an individual basis. The results show that the disagreement and gaps with regard to an equitable initial allocation of rights among groups or individual nations is one of the possible obstructions and hindrances to the promotion and formation of a world trading scheme.
18
Duan, Chener, Yiran Mi, and Ziye Lan. "Analysis models for China's carbon trading market: comparison and outlook." IOP Conference Series: Earth and Environmental Science 1011, no. 1 (April 1, 2022): 012012. http://dx.doi.org/10.1088/1755-1315/1011/1/012012.
Full textAbstract:
Abstract At the national and international levels, human-induced climate change has become a significant political concern, with the large rise in carbon dioxide concentration being a pressing issue that must be addressed. Carbon trading has shown to be one of the most successful strategies to accomplish energy saving and emission reduction as a flexible tool for dealing with climate change. As the nation with the highest carbon emissions today, China’s research on its carbon trading market has a guiding significance to the globe. The study findings of different models focusing on carbon trading markets are presented from three aspects: carbon emission reduction efficiency, carbon market efficiency, and internal information change trends in the carbon market. The results show that the efficiency of China’s pilot carbon market is currently poor, with just a mediocre efficiency attained. The existing carbon market’s key issues are its low transaction volume and weak market liquidity. Based on the comprehensive review of and comparison among existing models studying the carbon trading market, we proposed plausible suggestions for future research directions and development methods of the carbon trading market, including the utilization of carbon tax, improved market transparency, and government oversight.
19
Klepikova, O., J. Danylchuk, and T. Zagray. "Information and analytical technologies in trading enterprise management." 101, no. 101 (December 30, 2021): 113–23. http://dx.doi.org/10.26565/2311-2379-2021-101-11.
Full textAbstract:
The article considers economic and mathematical methods and information technologies for managing the processes of trade enterprise. Economic and mathematical models for solving warehousing logistics problems, stochastic and statistical models of inventory management, models of optimal management and queuing systems are analyzed. Flexible tools are used to increase the efficiency of trade enterprise management and timely decision-making. The tools combine the use of mathematical models, a simulation model and information-analytical technologies. The study was carried out in three stages. The simulation model is designed in the software iThink. The simulation model was used to forecast sales, incomes, expenses and profit, processes of goods purchases, which take into account the factors of seasonality and the rest of production both in a warehouse and in the enterprise as a whole. The efficiency indicators of the enterprise are calculated and the possibility of payroll depending on income and dividends to owners is analyzed. An investment project has been designed in the software «Alt-Invest». This project analyzes the possibility of opening a new store with regard for financial activities, the development of a business plan for an investment project, the preparation of financial feasibility study, and the assessment of the impact of external factors and internal parameters on the overall effectiveness of the project. A comparative assessment is carried out in order to select the most promising project option. ABC-XYZ scenario was designed in the software platform Loginom. Using this analysis, the product range was divided into groups depending on the revenue and financial capabilities of the enterprise.
20
Liu, Tianle, Chaoyang Chen, Jiahao Zhang, and Zhihong Chen. "Research on Maximization of Investment Income Based on Linear Method." BCP Business & Management 26 (September 19, 2022): 656–65. http://dx.doi.org/10.54691/bcpbm.v26i.2019.
Full textAbstract:
In this paper, we analyze the trading process of investment by building models for evaluating and trading investment products and using mathematical and economic knowledge and methods. We obtain the purchase coefficients and trading recommendations by quantifying the indicators of investment products. And through linear and nonlinear equations to get the trading volume. All in all, our goal is to obtain the largest income throughout the whole trading date sequence. In the end, we discuss the shortcoming of the model.
21
Barybin, M., V. Karashchuk, O. Kletskaya, E. Kiritseva, and V. Dzhus. "MODEL OF THE MUTUAL INFLUENCE OF ENVIRONMENTAL ASPECTS AND ENERGY RATIONING ON TRAIN TRACTION IN RAILWAY LOGISTICS." Collection of scientific works of the State University of Infrastructure and Technologies series "Transport Systems and Technologies" 1, no. 38 (December 24, 2021): 247–61. http://dx.doi.org/10.32703/2617-9040-2021-38-244-24.
Full textAbstract:
The article deals with the issues of environmental taxation of carbon dioxide emissions by the countries of the European Union and the methodology for calculating the amount of emissions by regulatory documents of Ukraine. It is established that our country's methodology is not adapted to real operating conditions under the influence of cross-border carbon taxation and the "Emissions Trading System". A mathematical model of the impact of power generating stations of states and their contribution to the overall energy balance of the country on the environmental cost and mass emissions of 1 kWh of electricity generation is proposed. The amount of electricity losses during its transportation from the power plant to the electric moving warehouse is determined and is taken into account in the total amount of deductions for the "Emissions Trading System" for DC and AC railway networks. Schemes of transit and local cargo routes are considered on the basis of a real fleet of traction rolling stock of Railways and a network of logistics lines. The passport characteristics of locomotives are analyzed and the amount of emissions and deductions during operation at Rated mode and idle speed is determined. Specific norms for selected routes and train conditions are calculated. The total costs, their cost and the amount of emissions and taxation of selected routes are determined, and rational economic and environmental logistics lines of train traffic are determined on their basis.
22
Wang, Qian, Cuiyun Gao, and Shuanping Dai. "Effect of the Emissions Trading Scheme on CO2 Abatement in China." Sustainability 11, no. 4 (February 18, 2019): 1055. http://dx.doi.org/10.3390/su11041055.
Full textAbstract:
This article takes advantage of the pilot Emissions Trading Scheme (ETS) project to estimate the causal impact of the ETS on CO2 abatement in China. The CO2 emissions and CO2 intensities of each province are calculated by using the fossil fuel data of 30 provincial administration regions from 2006 to 2016. Then difference in difference (DiD) models and propensity score matching (PSM) with panel data are applied to estimate the causal impact of the pilot ETS project. Results show that the pilot regions reduce their CO2 emissions and intensities more than the non-pilot regions under the pilot ETS project. The pilot ETS project significantly induced 12% decreases in the nominal CO2 intensity and 7.6% decrease in the real CO2 intensity, after controlling for regional heterogeneity, but its reduction effects on CO2 emissions are insignificant. Decreasing the proportion of coal to total energy consumption may be the main channel of the pilot ETS project inducing CO2 abatement. The estimated results for control variables indicate that upgrading industrial structures, attracting FDI, and purifying the export structure have significant effects on CO2 abatement.
23
Zhou, Ying, and Yan Ping Chen. "Equilibrium Analysis of Upstream and Downstream Enterprises in the Emissions Trading Based on the Model of Treatment Costs." Advanced Materials Research 1010-1012 (August 2014): 742–47. http://dx.doi.org/10.4028/www.scientific.net/amr.1010-1012.742.
Full textAbstract:
This article saw upstream and downstream enterprises in the same watershed as two overalls.Firstly, created a mathematical programming model of pollution control costs and upstream and downstream enterprises’ emissions reductions.Harnessed the method which solved the feasible solutions of the vector optimization problems meeting Kuhn-Tucker conditions to calculate two companies’ marginal treatment costs and put them as the market price of emission rights trading.Then created two companies’ benefit functions and found their Nash equilibrium outputs and incomes.Next analyzed the impacts of the emission trading price on two companies’ equilibrium and calculated the specific range of price parameter.Finally, gets the conclusion that only a reasonable emission trading price can lead to rational resources allocation.
24
Liu, Yong. "Residents’ Willingness and Influencing Factors on Action Personal Carbon Trading: A Case Study of Metropolitan Areas in Tianjin, China." Sustainability 11, no. 2 (January 12, 2019): 369. http://dx.doi.org/10.3390/su11020369.
Full textAbstract:
Personal carbon trading offers a powerful and innovative instrument with which to achieve reductions in carbon emissions. Meanwhile, residents’ personal carbon trading willingness and the factors influencing such willingness have critical effects on the acceptance of personal carbon trading. Therefore, the present research uses a questionnaire survey in metropolitan areas of Tianjin China and the results indicated that most of the interviewees (74.92%) agreed or strongly agreed that they would participant in personal carbon trading. Moreover, according to the results of multiple regression models, governmental policies and residents’ environmental awareness and motivations were positively related to their personal carbon trading willingness. However, personal barriers to personal carbon trading were negatively related to personal carbon trading willingness. Control variables, such as gender and incomes, were not significantly related to personal carbon trading willingness. Thus, monitoring residents’ emission and trading patterns, emphasizing effective, transparent, and fair policies, as well as mitigating uncertainty could all be effective ways to increase the acceptance of personal carbon trading.
25
Yeh, Shih-Kuo, and Bing-Huei Lin. "Term Structure Fitting Models and Information Content: An Empirical Examination in Taiwanese Government Bond Market." Review of Pacific Basin Financial Markets and Policies 06, no. 03 (September 2003): 305–48. http://dx.doi.org/10.1142/s0219091503001110.
Full textAbstract:
In this study, we apply empirical methodologies, which are essentially curve fitting techniques, and use cross-sectional bond price data to estimate and analyze the Taiwanese government bond (TGB) term structure of interest rates. We choose two economic models: the Vasicek model and the CIR model, and one mathematical model: the B-spline approximation function, as the discount bond function to extract the term structure from market coupon bond prices. To assess the fitting performances and investigate the economic information content of the term structure fitting models, we compare the estimation errors and examine whether trading mis-priced bonds according the fitting model, can provide excess returns. The hypothesis is that the mathematical model can fit the term structure better than the economic models. But the economic models, which contain economic information, are able to explain the term structure dynamics. Thus the economic models can perform better in identifying mis-priced bonds and in predicting excess trading returns, than the mathematical model. Using the methodologies in this study, we can investigate the term structure fitting problems and look at the economic information content of the term structure fitting models.
26
Vlasov, Gennady, Leonid Syritsyn, Vyacheslav Tchemerinski, and Nikolai Zhakomin. "INVESTIGATION INTO EFFICIENCY OF ADSORPTION PROCESS DURING UTILIZATION OF CURING GASES IN TYRE PRODUCTION." JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT 13, no. 4 (December 31, 2005): 153–59. http://dx.doi.org/10.3846/16486897.2005.9636865.
Full textAbstract:
The problem considered in the paper is mathematical and physical modeling of the adsorption process during utilization of gas emissions of cured tyres and tyre components. The paper contains synthesis and analysis of mathematical models for violent and moderate gassing. It describes an adsorption scheme, formulates an experimental dependence of productivity upon the concentration of emissions in an absorber chamber of a system used for trapping of curing gas emissions and vapors.
27
Mannina, Giorgio, Alida Cosenza, and George Ekama. "Mathematical modelling of greenhouse gas emissions from membrane bioreactors: A comprehensive comparison of two mathematical models." Bioresource Technology 268 (November 2018): 107–15. http://dx.doi.org/10.1016/j.biortech.2018.07.106.
Full text
28
Puskás-Tompos, András. "Energy Trading Perspectives in the Digital Era." Proceedings of the International Conference on Business Excellence 14, no. 1 (July 1, 2020): 16–27. http://dx.doi.org/10.2478/picbe-2020-0003.
Full textAbstract:
AbstractThe aim of the paper research is to identify and improve business models in energy trading by analyzing the current situation and developing scenarios for the evolution of business models in the Digital Era. It is very important to analyze, identify and track those directions that we believe will drive energy trading in order to be able to design and create new sustainable business models. We highlight the possibilities and ways of improving the energy trading, analyzing the rapid evolution of the field, generated by the emergence of several new factors that can influence this industry. Beside those directions at which electricity trading is heading in the Digital Era, the research also describes main innovations in the field such as Smart Grids, Blockchain Technology, Peer-to-peer trading platforms and Demand Response through which the purpose is to attract final consumers to the energy trading on web platforms or mobile applications with which they can properly control their electric appliances and self-generation units in their homes, all these supervised and guided by artificial intelligence. The type of research proposed to identify the current condition and to be able to develop new trading models is empirical research through qualitative analysis. Beyond incentives and monetary benefits, the focus is on final consumer education and increased awareness towards a more conscious, optimal and rational consumption of electricity that can lead to both a better use of the energy production from renewable sources and a reduction of pollutant fossil fuel electricity generation and carbon dioxide emissions without endangering the proper functioning of the electricity systems. Previous researches are based more on incentivizing or penalizing end consumers in present paper, more emphasis is placed on attracting the end consumer to his own electricity trading through mentioned innovation, but also supervised and guided by artificial intelligence.
29
Miśkiewicz, Radosław, Krzysztof Matan, and Jakub Karnowski. "The Role of Crypto Trading in the Economy, Renewable Energy Consumption and Ecological Degradation." Energies 15, no. 10 (May 22, 2022): 3805. http://dx.doi.org/10.3390/en15103805.
Full textAbstract:
The rapid growth of information technology and industrial revolutions provoked digital transformation of all sectors, from the government to households. Moreover, digital transformations led to the development of cryptocurrency. However, crypto trading provokes a dilemma loop. On the one hand, crypto trading led to economic development, which allowed attracting additional resources to extending smart and green technologies for de-carbonising the economic growth. On the other hand, crypto trading led to intensifying energy sources, which provoked an increase in greenhouse gas emissions and environmental degradation. The paper aims to analyse the connections between crypto trading, economic development of the country, renewable energy consumption, and environmental degradation. The data for analysis were obtained from: Our World in Data, World Data Bank, Eurostat, Ukrstat, Crystal Blockchain, and KOF Globalisation Index. To check the hypothesis, the paper applied the Pedroni and Kao panel cointegration tests, FMOLS and DOLS panel cointegration models, and Vector Error Correction Models. The findings concluded that the increasing crypto trading led to enhanced GDP, real gross fixed capital formation, and globalisation. However, in the long run, the relationship between crypto trading and the share of renewable energies in total energy consumption was not confirmed by the empirical results. For further directions, it is necessary to analyse the impact of crypto trading on land and water pollution.
30
Cowie, Annette, Richard Eckard, and Sandra Eady. "Greenhouse gas accounting for inventory, emissions trading and life cycle assessment in the land-based sector: a review." Crop and Pasture Science 63, no. 3 (2012): 284. http://dx.doi.org/10.1071/cp11188.
Full textAbstract:
Governments, organisations and individuals have recognised the need to reduce their greenhouse gas (GHG) emissions. To identify where savings can be made, and to monitor progress in reducing emissions, we need methodologies to quantify GHG emissions and sequestration. Through the Australian Government’s Carbon Farming Initiative (CFI) landholders may generate credits for reducing emissions and/or sequestering carbon (C). National GHG inventories for the United Nations Framework Convention on Climate Change, and accounting under the Kyoto Protocol use a sectoral approach. For example, fuel use in agriculture is reported in the transport component of the energy sector; energy use in producing herbicide and fertiliser is included in the manufacturing section of the energy sector; sequestration in farm forestry is reported in the land use, land-use change and forestry sector, while emissions reported in the agriculture sector include methane (CH4) from ruminant livestock, nitrous oxide (N2O) from soils, and non-carbon dioxide (CO2) GHG from stubble and savannah burning. In contrast, project-level accounting for CFI includes land-use change, forestry and agricultural sector emissions, and significant direct inputs such as diesel and electricity. A C footprint calculation uses a life cycle approach, including all the emissions associated with an organisation, activity or product. The C footprint of a food product includes the upstream emissions from manufacturing fertiliser and other inputs, fuel use in farming operations, transport, processing and packaging, distribution to consumers, electricity use in refrigeration and food preparation, and waste disposal. Methods used to estimate emissions range from simple empirical emissions factors, to complex process-based models. Methods developed for inventory and emissions trading must balance the need for sufficient accuracy to give confidence to the market, with practical aspects such as ease and expense of data collection. Requirements for frequent on-ground monitoring and third party verification of soil C or livestock CH4 estimates, for example, may incur costs that would negate the financial benefit of credits earned, and could also generate additional GHG emissions. Research is required to develop practical on-farm measures of CH4 and N2O, and methods to quantify C in environmental plantings, agricultural soils and rangeland ecosystems, to improve models for estimation and prediction of GHG emissions, and enable baseline assessment. There is a need for whole-farm level estimation tools that accommodate regional and management differences in emissions and sequestration to support landholders in managing net emissions from their farming enterprises. These on-farm ‘bottom-up’ accounting tools must align with the ‘top-down’ national account. To facilitate assessment of C footprints for food and fibre products, Australia also needs a comprehensive life cycle inventory database. This paper reviews current methods and approaches used for quantifying GHG emissions for the land-based sectors in the context of emissions reporting, emissions trading and C footprinting, and proposes possible improvements. We emphasise that cost-effective yet credible GHG estimation methods are needed to encourage participation in voluntary offset schemes such as the CFI, and thereby achieve maximum mitigation in the land-based sector.
31
Orlova, A. M., and O. V. Grevtsov. "Overview of Existing Mathematical Models for Estimating and Predicting Greenhouse Gas Emissions." Quality and life 24, no. 4 (December 20, 2019): 37–46. http://dx.doi.org/10.34214/2312-5209-2019-24-4-37-46.
Full text
32
Liu, Daming, Xianglin Zhong, Yaqi Li, Xudong Zhen, Shaoyun Lu, and Yuanyuan Xue. "Prediction of Uncontrolled Refueling Emissions from Gasoline Vehicles Based on Mathematical Models." IOP Conference Series: Earth and Environmental Science 585 (November 4, 2020): 012033. http://dx.doi.org/10.1088/1755-1315/585/1/012033.
Full text
33
Yan, Qingyou, Xingbei Ai, and Jinmeng Li. "Low-Carbon Economic Dispatch Based on a CCPP-P2G Virtual Power Plant Considering Carbon Trading and Green Certificates." Sustainability 13, no. 22 (November 10, 2021): 12423. http://dx.doi.org/10.3390/su132212423.
Full textAbstract:
To improve the economic benefits of power systems in the process of achieving multi-energy complementation and decarbonization, this paper proposes a dispatching optimization model for virtual power plants (VPP) that considers carbon trading and green certificates. Firstly, the structure of the VPP system integrating wind and solar generators (WP and PV), power-to-gas (P2G), carbon capture power plants (CCPP) and price-based demand response (PBDR) is established. Secondly, the two-way interactive trading models among the VPP, carbon trading and green certification market are constructed. Then, the dispatching optimization model of the VPP is constructed. Finally, the numerical example is solved and analyzed by the chaotic particle swarm optimization algorithm, which verifies the rationality and effectiveness of the new model. The results show that: (1) when the VPP considers the CCPP-P2G, the cost of the system is reduced by USD 2550.48, while the CO2 emissions are reduced by nearly 50%; (2) the addition of PBDR reduces the CO2 emissions of the thermal power unit, which has reduced the cost of carbon tax by nearly 27.8%, further reducing the cost of the VPP; (3) the introduction of the carbon trading and green certificate market has reduced the operating cost of the VPP by nearly 22.24%.
34
Păuna, Cristian. "Reliable Signals and Limit Conditions for Automated Trading Systems." Review of Economic and Business Studies 11, no. 2 (December 1, 2018): 9–20. http://dx.doi.org/10.1515/rebs-2018-0070.
Full textAbstract:
Abstract Automated trading software is a significant part of the business intelligence system in a modern investment company today. The buy and sell orders are built and sent almost instantly by computers using special trading and computational strategies. The trading decisions are made by automated algorithms. In this paper it will be presented one of these mathematical models which generate trading signals based only on the time price series. The algorithm combines several known computing techniques to build a trading indicator to automate the trades. With this method, buy decisions on oversold intervals and sell decisions on overbought price values can be built. Limit conditions in order to close the long and short trades can be also automatically generated. More trading signal types based on this model will be revealed. Trading results obtained with all these signals will be presented in order to qualify this methodology developed especially for algorithmic trading.
35
Cong, Jing. "Research on the Factors Affecting Carbon Emissions Based on Multivariate Regression Models." Scientific and Social Research 4, no. 3 (March 16, 2022): 102–7. http://dx.doi.org/10.26689/ssr.v4i3.3664.
Full textAbstract:
Carbon peak and carbon neutrality are two new terms that are being mentioned more frequently, and the measurement of carbon emissions has become an important research topic. Based on relevant data, this paper studies the relationship and evolution law of the driving factors of carbon emissions from energy structure and industrial structure as well as the result factors of carbon emissions from energy consumption, and then establishes corresponding mathematical models. The driving factors, result factors, and relationship attributes that are difficult to measure in the carbon emissions from energy structure and industrial structure are analyzed to fathom the evolution law of carbon emissions and absorption. Based on the results, phased and global suggestions for carbon neutrality have been suggested, taking into account the characteristics of different industries and regions.
36
Zoltáni, Tenke A. "Carbon as an Emerging Tool for Risk Management." International Journal of Applied Logistics 4, no. 4 (October 2013): 51–69. http://dx.doi.org/10.4018/ijal.2013100104.
Full textAbstract:
Since 2005, when the European Union Emissions Trading Scheme (EU ETS) launched, green adoption in business and industry has been marred by fraudulent carbon credits, VAT swindlers and carbon cowboys, inefficiencies of a nascent market, and not least of all by legislative uncertainty. The disrepute afforded by these examples hindered low carbon growth and deterred emerging business models from adopting more carbon friendly practices. But, as this article argues, the shift toward liberal environmentalism has yielded a new generation of businesses seeking to incorporate carbon assets, emissions trading, and sustainability strategies across the value chain. Central to this shift is the notion of carbon as a tool for risk management in businesses, which occurred through the instrumentalisation of CO2 into a tradable asset. By utilising carbon as a financial instrument, businesses are able to manage project risk, market risk, and reputational risk more effectively. This article demonstrates this argument through industry examples and provides practical advice for businesses today.
37
Branger, E., S. Grape, S. Jacobsson Svärd, P. Jansson, and E. Andersson Sundén. "Comparison of prediction models for Cherenkov light emissions from nuclear fuel assemblies." Journal of Instrumentation 12, no. 06 (June 6, 2017): P06007. http://dx.doi.org/10.1088/1748-0221/12/06/p06007.
Full text
38
Chael, Nathan, Christophe Crombez, and Pieterjan Vangerven. "Spatial Models, Legislative Gridlock, and Resource Policy Reform." Annual Review of Resource Economics 11, no. 1 (October 5, 2019): 83–100. http://dx.doi.org/10.1146/annurev-resource-100517-022958.
Full textAbstract:
This review evaluates the use of spatial models for the analysis of policy making. First, we examine spatial theory and its applications in a variety of institutional settings. We discuss how the preferences of the actors involved in political processes, the steps in those processes, and the locations of the reversion policies affect the policies that emerge from the processes. To illustrate this and analyze how the rights of political actors determine the extent of policy reform and the occurrence of gridlock, we use a spatial model of European Union (EU) policy making. We apply the model to major EU reforms in two resource policy areas: the Common Agricultural Policy reforms of the past two decades and the recent reforms of the Emissions Trading System.
39
Liao, Wenzhu, Lin Liu, and Jiazhuo Fu. "A Comparative Study on the Routing Problem of Electric and Fuel Vehicles Considering Carbon Trading." International Journal of Environmental Research and Public Health 16, no. 17 (August 27, 2019): 3120. http://dx.doi.org/10.3390/ijerph16173120.
Full textAbstract:
In order to explore the impact of using electric vehicles on the cost and environment of logistics enterprises, this paper studies the optimization of vehicle routing problems with the consideration of carbon trading policies. Both the electric vehicle routing model and the traditional fuel vehicle routing model are constructed aiming at minimizing the total costs, which includes the fixed costs of vehicles, depreciation costs, penalty costs for violating customer time window, energy costs and carbon trading costs. Then a hybrid genetic algorithm (HGA) is proposed to address these two models, the advantages of greedy algorithm and random full permutation are combined to set the initial population, at the same time, the crossover operation is improved to retain the excellent gene fragments effectively and the hill climbing algorithm is embedded to enhance the local search ability of HGA. Furthermore, a case data is used with HGA to carry out computational experiments in these two models and the results indicate that first using electric vehicles for distribution can indeed reduce the carbon emissions, but results in a low customer satisfaction compared with using fuel vehicles. Besides, the battery capacity and charge rate have a great influence on total costs of using electric vehicles. Second, carbon price plays an important role in the transformation of logistics companies. As the carbon price changes, the total costs, carbon trading costs, and carbon emissions of using electric vehicles and fuel vehicles are affected accordingly, yet the trends are different. The changes of carbon quota have nothing to do with the distribution scheme and companies’ transformation but influence the total costs of using electric and fuel vehicles for distribution, and the trends are the same. These reasonable proposals can support the government on carbon trading policy, and also the logistics companies on dealing the relationship between economic and social benefits.
40
Goicoechea, Nestor, and Luis María Abadie. "Optimal Slow Steaming Speed for Container Ships under the EU Emission Trading System." Energies 14, no. 22 (November 9, 2021): 7487. http://dx.doi.org/10.3390/en14227487.
Full textAbstract:
Slow steaming is an operational measure in ocean-going vessels sailing at slow speeds. It can help climate mitigation efforts by cutting down marine fuel consumption and consequently reducing CO2 and other Greenhouse Gas Emissions (GHG). Due to climate change both the European Union (EU) and the International Maritime Organization (IMO) are analysing the inclusion of international shipping in the EU Emissions Trading System (ETS) in the near future or alternatively implementing a carbon tax. The paper proposes a methodology to decide the optimal speed of a vessel taking into account its characteristics and the factors that determine its economic results. The calculated cash flow can be used in valuation models. The methodology is applied for a case study for any container ship in a range from 2000 to 20,000 Twenty-foot Equivalent Units (TEU) on a leg of a round trip from Shanghai to Rotterdam. We calculate how speed reduction, CO2 emissions and ship owner’s earnings per year may vary between a business-as-usual scenario and a scenario in which shipping is included in the ETS. The analysis reveals that the optimal speed varies with the size of the vessel and depends on several variables such as marine fuel prices, cargo freight rates and other voyage costs. Results show that the highest optimal speed is in the range of 5500–13,000 TEUs whether or not the ETS is applied. As the number of TEUs transported in a vessel increases emissions per TEU decrease. In an established freight rate market, the optimal speed fluctuates by 1.8 knots. Finally, the medium- and long-term expectations for slow steaming are analysed based on future market prices.
41
Qi, Yawei, Wenxiang Peng, Ran Yan, and Guangping Rao. "Use of BP Neural Networks to Determine China’s Regional CO2 Emission Quota." Complexity 2021 (January 5, 2021): 1–14. http://dx.doi.org/10.1155/2021/6659302.
Full textAbstract:
China declared a long-term commitment at the United Nations General Assembly (UNGA) in 2020 to reduce CO2 emissions. This announcement has been described by Reuters as “the most important climate change commitment in years.” The allocation of China’s provincial CO2 emission quotas (hereafter referred to as quotas) is crucial for building a unified national carbon market, which is an important policy tool necessary to achieve carbon emissions reduction. In the present research, we used historical quota data of China’s carbon emission trading policy pilot areas from 2014 to 2017 to identify alternative features of corporate CO2 emissions and build a backpropagation neural network model (BP) to train the benchmark model. Later, we used the model to calculate the quotas for other regions, provided they implement the carbon emission trading policy. Finally, we added up the quotas to obtain the total national quota. Additionally, considering the perspective of carbon emission terminal, a new characteristic system of quota allocation was proposed in order to retrain BP including the following three aspects: enterprise production, household consumption, and regional environment. The results of the benchmark model and the new models were compared. This feature system not only builds a reasonable quota-related indicator framework but also perfectly matches China’s existing “bottom-up” total control quota approach. Compared with the previous literature, the present report proposes a quota allocation feature system closer to China’s policy and trains BP to obtain reasonable feature weights. The model is very important for the establishment of a unified national carbon emission trading market and the determination of regional quotas in China.
42
Lv, Yang, Xinhua Bi, Quanxi Li, and Haowei Zhang. "Research on Closed-Loop Supply Chain Decision Making and Recycling Channel Selection under Carbon Allowance and Carbon Trading." Sustainability 14, no. 18 (September 13, 2022): 11473. http://dx.doi.org/10.3390/su141811473.
Full textAbstract:
The massive emission of carbon dioxide and other greenhouse gases has begun to threaten the survival of human beings and the balance of the Earth’s ecology. If carbon emission is left unchecked, we will face terrible consequences. Closed-loop supply chain operation is an effective way to improve economic and environmental benefits at the same time. This paper attempts to study the decision-making and recycling channel selection of CLSC under carbon allowance and carbon trading policies. This paper constructs a closed-loop supply chain consisting of a manufacturer, a retailer and a third-party recycler, and uses the Stackelberg game-theoretic method to decide variables such as the product price and recycling rate of CLSC under three recycling models. Through the analysis and comparison of the manufacturer’s profit of and the carbon emissions in different models, the following conclusions are drawn. (1) When the manufacturer recycles WEEE, the supply chain obtains the most profit. (2) When the retailer recycles WEEE, the carbon emissions of the supply chain are lowest. (3) The manufacturer tends to choose the M model, which is the manufacturer recycling model. The T model and the R model have little difference in carbon emissions. For easier management, the government prefers to choose the T model, which is the third-party recycler recycling model.
43
Luo, Zhao, Jinghui Wang, Ni Xiao, Linyan Yang, Weijie Zhao, Jialu Geng, Tao Lu, Mengshun Luo, and Chenming Dong. "Low Carbon Economic Dispatch Optimization of Regional Integrated Energy Systems Considering Heating Network and P2G." Energies 15, no. 15 (July 29, 2022): 5494. http://dx.doi.org/10.3390/en15155494.
Full textAbstract:
Against a background of the energy internet and low-carbon electricity, regional integrated energy system (RIES) has become a key way to achieve sustainable energy development, leading to reduced operating costs and system carbon emissions, and improved system operating efficiency. This paper puts forward a low-carbon economic dispatching optimization method for RIES with a heating network and power-to-gas (P2G). First, the heating network model and the mathematical model of P2G were constructed. Second, the carbon trading mechanism was introduced, the objective function being: to minimize the sum of the system operating cost and carbon trading cost; and ensure that the balance of cooling, heating, electric power, and the operating constraints—of RIES and the heating network—were comprehensively considered. Finally, the CPLEX optimization software simulation was used. The results show that the proposed method can take into account both low-carbon and economic factors, and can provide a reference for RIES low-carbon economic dispatch.
44
Pandey, Kamal, and Bhaskar Basu. "Mathematical modeling for short term indoor room temperature forecasting using Box-Jenkins models." Journal of Modelling in Management 15, no. 3 (February 12, 2020): 1105–36. http://dx.doi.org/10.1108/jm2-08-2019-0182.
Full textAbstract:
Purpose The rapid urbanization of Indian cities and the population surge in cities has steered a massive demand for energy, thereby increasing the carbon emissions in the environment. Information and technology advancements, aided by predictive tools, can optimize this energy demand and help reduce harmful carbon emissions. Out of the multiple factors governing the energy consumption and comfort of buildings, indoor room temperature is a critical one, as it envisages the need for regulating the temperature. This paper aims to propose a mathematical model for short-term forecasting of indoor room temperature in the Indian context to optimize energy consumption and reduce carbon emissions in the environment. Design/methodology/approach A study is conducted to forecast the indoor room temperature of an Indian corporate building structure, based upon various external environmental factors: temperature and rainfall and internal factors like cooling control, occupancy behavior and building characteristics. Expert insight and principal component analysis are applied for appropriate variables selection. The machine learning approach using Box–Jenkins time series models is used for the forecasting of indoor room temperature. Findings ARIMAX model, with lagged forecasted and explanatory variables, is found to be the best-fit model. A predictive short-term hourly temperature forecasting model is developed based upon ARIMAX model, which yields fairly accurate results for data set pertaining to the building conditions and climatic parameters in the Indian context. Results also investigate the relationships between the forecasted and individual explanatory variables, which are validated using theoretical proofs. Research limitations/implications The models considered in this research are Box–Jenkins models, which are linear time series models. There are non-linear models, such as artificial neural network models and deep learning models, which can be a part of this study. The study of hybrid models including combined forecasting techniques comprising linear and non-linear methods is another important area for future scope of study. As this study is based on a single corporate entity, the models developed need to be tested further for robustness and reliability. Practical implications Forecasting of indoor room temperature provides essential practical information about meeting the in-future energy demand, that is, how much energy resources would be needed to maintain the equilibrium between energy consumption and building comfort. In addition, this forecast provides information about the prospective peak usage of air-conditioning controls within the building indoor control management system through a feedback control loop. The resultant model developed can be adopted for smart buildings within Indian context. Social implications This study has been conducted in India, which has seen a rapid surge in population growth and urbanization. Being a developing country, India needs to channelize its energy needs judiciously by minimizing the energy wastage and reducing carbon emissions. This study proposes certain pre-emptive measures that help in minimizing the consumption of available energy resources as well as reducing carbon emissions that have significant impact on the society and environment at large. Originality/value A large number of factors affecting the indoor room temperature present a research challenge for model building. The paper statistically identifies the parameters influencing the indoor room temperature forecasting and their relationship with the forecasted model. Considering Indian climatic, geographical and building structure conditions, the paper presents a systematic mathematical model to forecast hourly indoor room temperature for next 120 h with fair degree of accuracy.
45
Xu, Tianyi, Yanlong Meng, and Yukun Bai. "The prediction of financial market based on BP neural network is used to maximize the income of investment." BCP Business & Management 26 (September 19, 2022): 409–15. http://dx.doi.org/10.54691/bcpbm.v26i.1990.
Full textAbstract:
In the financial market, investors often buy and sell volatile assets to maximize returns. We can use statistical and mathematical tools, mathematical models and computer technology to trade and get excess return ratio. Firstly, we established a price prediction model based on BP neural network, trained the network through the trading prices of bitcoin and gold before 2016, and then predicted the price of the next day every day from September 11, 2016 to September 10, 2021. Through the comparison with the real value and the horizontal comparison of other models, the prediction effect of this model is good. Then, the programming model is used to maximize the benefits in the next day as the objective function, and the constraints are that the amount after the transaction cannot be negative and there is no gold trading in part of the time. Considering the risk in the final transaction model, the planning model is established to find the optimal investment scheme at this time. Finally, the daily investment plan and the final total value are $3886.8.
46
Son, Dongmin, Joonrak Kim, and Bongju Jeong. "Optimal Operational Strategy for Power Producers in Korea Considering Renewable Portfolio Standards and Emissions Trading Schemes." Energies 12, no. 9 (May 1, 2019): 1667. http://dx.doi.org/10.3390/en12091667.
Full textAbstract:
Globally, many countries are experiencing economic growth while concurrently increasing their energy consumption. Several have begun to consider a low-carbon energy mix to mitigate the environmental impacts caused by increased fossil fuel consumption. In terms of maximizing profits, however, power producers are not sufficiently motivated to expand capacity due to high costs. Thus, the Korean government initiated the Renewable Portfolio Standard (RPS), an obligation to generate a certain proportion of a producer’s total generation using renewable energy for power producers with capacities of 500 MW or more, and the Emissions Trading Scheme (ETS), designed to attain a carbon emissions reduction goal. We propose a mathematical model to derive the optimal operational strategy for maximizing power producer profits with a capacity expansion plan that meets both regulations. As such, the main purpose of this study was to obtain the optimal operational strategy for each obligatory power producer. To that end, we defined a 2 × 2 matrix to classify their types and to conduct scenario-based analyses to assess the impact of major factor changes on solutions for each type of power producer. Finally, for the power generation industry to operate in a sustainable and eco-friendly manner, we extracted policy implications that the Korean government could consider for each type of power producer.
47
Raho, Brenda, Gianpiero Colangelo, Marco Milanese, and Arturo de Risi. "A Critical Analysis of the Oxy-Combustion Process: From Mathematical Models to Combustion Product Analysis." Energies 15, no. 18 (September 6, 2022): 6514. http://dx.doi.org/10.3390/en15186514.
Full textAbstract:
Fossil fuels are the most widely used resource for energy production. Carbon dioxide (CO2) emissions are correlated with climate change, and therefore these emissions must be reduced in the future. It is possible by means of many different technologies, and one of the most promising seems to be oxyfuel combustion. This process, with oxygen and recirculating gas, produces a concentrated stream of CO2 and water. In recent years, many scientists carried out research and studies on the oxyfuel process, but a sufficient level of knowledge was not yet reached to exploit the great potential of this new technology. Although such areas of research are still highly active, this work provides an overview and summary of the research undertaken, the state of development of the technology, and a comparison of different plants so far.
48
Munidasa, Sineka, Richard Eckard, Xuezhao Sun, Brendan Cullen, David McGill, Deli Chen, and Long Cheng. "Challenges and opportunities for quantifying greenhouse gas emissions through dairy cattle research in developing countries." Journal of Dairy Research 88, no. 1 (February 2021): 3–7. http://dx.doi.org/10.1017/s0022029921000182.
Full textAbstract:
AbstractThe global dairy sector is facing the challenge of reducing greenhouse gas (GHG) emissions whilst increasing productivity to feed a growing population. Despite the importance of this challenge, many developing countries do not have the required resources, specifically funding, expertise and facilities, for quantifying GHG emissions from dairy production and research. This paper aims to address this challenge by discussing the magnitude of the issue, potential mitigation approaches and benefits in quantifying GHG emissions in a developing country context. Further, the paper explores the opportunities for developing country dairy scientists to leverage resources from developed countries, such as using existing relevant GHG emission estimation models. It is clear that further research is required to support developing countries to quantify and understand GHG emissions from dairy production, as it brings significant benefits including helping to identify and implement appropriate mitigation strategies for local production systems, trading carbon credits and achieving the nationally determined contribution obligations of the Paris Agreement.
49
Dou, Xun, Li Song, Shengnan Zhang, Lulu Ding, Ping Shao, and Xiaojun Cao. "Multi-Time Scale Trading Simulation of Source Grid Load Storage Based on Continuous Trading Mechanism for China." Sensors 22, no. 6 (March 18, 2022): 2363. http://dx.doi.org/10.3390/s22062363.
Full textAbstract:
The proportion of new energy in power systems is increasing yearly. How to deal with the adverse impact of new energy output uncertainty on its participation in trading from the mechanism level is an urgent problem in China that must be solved. A source grid load storage (SGLS) continuous trading mechanism and a multi-time scale trading simulation method are proposed which meet the needs of Chinese new energy consumption and satisfies the trading needs of Chinese power market players. Firstly, the connection mechanism of mid-long term, day-ahead, and intra-day SGLS interactive trading is established, and the meaning and ways of continuous development are defined. Secondly, the clearing model of SGLS trading based on the continuous trading mechanism is established to provide mathematical models and strategic methods for various resources to participate in SGLS trading. Then, the multi-time scale trading simulation of SGLS based on the continuous trading mechanism is carried out to obtain the trading strategies of different trading subjects. The example results show that compared with the trading mechanism based on deviation assessment, the one-day trading cost is reduced by 4.20% and the consumption rate of new energy is increased by 6.53%. It can be seen that the mid-long term–day-ahead–day SGLS interactive trading connection mechanism has advantages in reducing trading costs and improving the consumption rate of new energy. It can flexibly deal with the trading scenario of domestic new energy consumption and new energy reverse peak shaving, which has an effect on the adverse impact of trading and operation deviation caused by source load uncertainty on trading.
50
Taylor, Lyla L., David J. Beerling, Shaun Quegan, and Steven A. Banwart. "Simulating carbon capture by enhanced weathering with croplands: an overview of key processes highlighting areas of future model development." Biology Letters 13, no. 4 (April 2017): 20160868. http://dx.doi.org/10.1098/rsbl.2016.0868.
Full textAbstract:
Enhanced weathering (EW) aims to amplify a natural sink for CO 2 by incorporating powdered silicate rock with high reactive surface area into agricultural soils. The goal is to achieve rapid dissolution of minerals and release of alkalinity with accompanying dissolution of CO 2 into soils and drainage waters. EW could counteract phosphorus limitation and greenhouse gas (GHG) emissions in tropical soils, and soil acidification, a common agricultural problem studied with numerical process models over several decades. Here, we review the processes leading to soil acidification in croplands and how the soil weathering CO 2 sink is represented in models. Mathematical models capturing the dominant processes and human interventions governing cropland soil chemistry and GHG emissions neglect weathering, while most weathering models neglect agricultural processes. We discuss current approaches to modelling EW and highlight several classes of model having the potential to simulate EW in croplands. Finally, we argue for further integration of process knowledge in mathematical models to capture feedbacks affecting both longer-term CO 2 consumption and crop growth and yields.