Costs Of Greenhouse Gas Emissions Research Articles

Comparative study of maximum power point tracking techniques for hybrid renewable energy system

ABSTRACTThe power generation demand is increasing day-by-day throughout the world, therefore, the use of hybrid systems becomes a significant solution. The hybrid renewable energy system (HRES) is used for delivering power in various regions in order to overcome intermittence of wind and solar resources. Because of increasing environmental problems, for example, greenhouse gas emission and energy cost have interested novel research into substitute methods in favour of electrical power generation. Maximum Power Point Tracking (MPPT) control method is a vast deal of novel research used for enhancing the efficiency of HRES. The authors have revealed that the hybrid techniques i.e. Global MPPT, fuzzy-neuro systems, Adaptive Neuro-Fuzzy Inference System (ANFIS), Perturbed and Observe (P&O) + Adaptive Neural Network (ANN) etc. can provide best results as compared to other MPPT control methods. This paper offering a state of art review of MPPT control techniques for HRES.

Energy, exergy, economic and environmental analysis and optimization of a novel biogas-based multigeneration system based on Gas Turbine-Modular Helium Reactor cycle

Biogas for supply of power plants can play a paramount role in reducing greenhouse gas emission and extra cost of a fossil fuel based plants. Regarding this aspect of biogas heat source, a novel biogas-based multigeneration system is proposed and modeled under privilege of first and second laws of thermodynamics, economic, and environmental perspectives. Furthermore, multi-criteria optimization of this integrated system is carried out from 4E (energy, exergy, exergoeconomic, and environmental) analysis standpoints. The introduced multigeneration system is able to produce optimum cooling capacity, heating capacity, net power, distilled water, and hydrogen of 123.59 MW, 0.73 MW, 280.35 MW, 18.14 kg/s, and 0.2432 kg/s, respectively. Under this circumstance, the thermal efficiency, exergy efficiency, unit product cost (UPC) of the system, and environmental penalty cost rate are calculated 72.75%, 50.21%, 6.79 $/GJ, and 168 $/h, respectively. Additionally, among all components, reactor core and among different sub-systems, the gas turbine-modular helium reaction (GT-MHR) cycle has the highest contribution to the overall exergy destruction. Finally, a complete sensitivity study based on key thermodynamic, thermoeconomic, and environmental parameters is performed and results are extended and discussed.

Developing commute optimization system to minimize negative environmental impacts and time of business commuters

The objective of this research is to develop a novel and innovative system, called Business+ Commute Optimization System (B+COS) that is capable of identifying the optimal selection of individualized commute alternatives of employees in a business to minimize their greenhouse gas (GHG) emissions, air pollution, and commute time. B+COS is designed to identify the optimal travel behavior for each commuter (e.g., drive car, carpool, use public transit, bike or walk) while maintaining convenience and incentivizing commuters using monetary incentives. The system consists of a geographical information system (GIS) and a multi-objective optimization model. The GIS is designed to measure and quantify business commute attributes such as emissions, commute cost, and time of each commute option. The multi-objective optimization model is designed to generate optimal trade-offs among two optimization objectives (1) minimizing equivalent social cost of GHG emissions and air pollution, and (2) minimizing total commute time of business commuters. Performance of the system is evaluated and verified using a case study of 21 commuters. Results show the capabilities of the new system in identifying Pareto-optimal solutions of the two optimization objectives for various tolerances of commute time increase ranging from 5 to 25 min. The promising results highlight the effectiveness of such an innovative system to minimize transportation-related emissions and commute time for businesses.

How to achieve less emissions from freight transport in Sweden

Purpose For the case of Sweden, this paper aims to determine how a range of different infrastructure fees and taxes influences modal split, port throughputs, air emissions, societal costs of greenhouse gas (GHG) emissions and air pollution, as well as logistics costs. Design/methodology/approach The Swedish national freight model is used to simulate a range of different proposed infrastructure fees, one by one and in combination. The volume of emissions of CO2-equivalents, NOx, SOx and PM under the different scenarios is calculated in both volume and monetary terms, by applying national emission factors and EU values for external costs. Findings Road user fees are calculated to have the largest impact on the modal split, GHG emissions and air pollution. The impact increases slightly when road user fees are combined with higher fees for sea and rail and/or gate fees in all Swedish ports. The imposition of gate fees over €30 per truck in all ports leads to shifts in cargo to land-based modes and to ports outside Sweden. The logistics costs in Sweden are found to be three to ten times higher than the benefits of reduced GHG emissions and air pollution, although other benefits to society need to be considered as well. Research limitations/implications Methods which attempt to evaluate alternative approaches to the internalisation of the external costs caused by transport need to be further developed. In particular, they need to encompass a more holistic perspective on “benefits to society”, other than merely reductions in GHG emissions and air pollution. To facilitate international acceptance and adoption, such methods require agreements to be reached on common definitions and routines. Practical implications The results can be used as basis for policy-making. They illustrate the environmental impacts of the fees and taxes one by one and in combination and to what extent these reinforce each other and should be co-ordinated. Social implications The outcomes are relevant to national and international policymakers and authorities, as well as port authorities, shippers and transport companies who need to determine unilateral strategies on how to reduce GHG emissions and air pollution, without undermining their wider business objectives. Originality/value The approach is original in facilitating the testing of policies which impact on the transport system and the environment across different dimensions. The work has additional value in informing policy because of its use of Sweden’s national freight transport model.

Comparison of Efficiency between Biogas Plant and Liquid Compost Plant Including the Use of Liquid Fertilizer: Estimation of Greenhouse Gas Emissions and Disposal Costs Using LCA

Comparison of Efficiency between Biogas Plant and Liquid Compost Plant Including the Use of Liquid Fertilizer: Estimation of Greenhouse Gas Emissions and Disposal Costs Using LCA

Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources

The application of renewable energy resources in a power system has received significant attention owing to the environmental impacts and fluctuations of fossil fuel prices. Consequently, renewable energy resources have become important sources to generate power at the commercial level due to their various benefits, coupled with the government incentives and public supports. This research work is focused on the evaluation of the reliability, economic and environmental benefits of renewable energy resources in a microgrid system. The lifecycle analysis of a microgrid system that consists of the photovoltaic, wind turbine generator, electric storage system and diesel generator is implemented in this study to test their commercial prospects in rural communities that have no access to electricity due to economic and technical constraints. The objective of this research work is to minimize the cost of energy, lifecycle cost, the annual cost of load loss and lifecycle greenhouse gas emission cost as well as to improve the overall benefit of green technologies in the proposed microgrid system. This objective is achieved by utilizing the basic probability concept to obtain the reliability performance indicators such as expected energy not served, loss of load expectation and loss of load probability, in addition to utilizing an fmincon optimization tool in the MATLAB environment to investigate the environmental and economic effects of renewable energy resources in a power system. The suitability of the model is tested on six case studies by using the same load profile, wind speed and irradiation of the site and diesel generator power capacity. The market factors such as interest rate and price of diesel fuel as well as forced outage rate, annual peak load variation and distributed generation penetration level are utilized to study their impacts on the operation of a microgrid system. The results obtained in this study demonstrate the optimal feasibility of renewable energy resources in a microgrid system. This indicates that it offers a significant reduction in the values of lifecycle cost, cost of energy, greenhouse gas emission cost and the annual cost of load loss when compared with case study 1. This research work shows that the utilization of green technologies in a microgrid system optimizes the reliability, cost savings, lifecycle cost and environmental impact. The technique adopted in the study can serve as a reference for rural electrification projects and solve socioeconomic problems that are associated with power outages.

Impact of incorporating greenhouse gas emission intensities in selection indexes for sow productivity traits

Genetic improvement programmes should incorporate emerging challenges about environmental concerns into breeding goals. The large volume of pig meat production implies important greenhouse gas (GHG) emissions despite its lower carbon footprint per animal in front of ruminant productions. The different breeding goals considered by swine industry depending on different purebred lines, or line crosses adapted to different market demands and production constraints, could mask the effect of incorporating GHG emissions into selection indexes for improving sow productivity traits in nucleus populations. This paper analysed this effect following a methodological approach consisting in augmenting existing selection indexes derived from profit functions. An index previously described in the literature including litter size at birth, piglet perinatal survival, piglet survival to weaning, age at first conception and weaning to conception interval, was employed. This index was expanded to include GHG emissions calculating the emission intensities per litter, assuming a finished pig market and different scenarios and financial costs of GHG emissions. Results indicated that the inclusion of GHG emissions diminished the economic weight of litter size and piglet survival vs. the age at first conception and the interval weaning to conception, but did not affect significantly the contributions of these traits in the selection indexes. The improvement of sow productivity traits diluted relevantly the GHG emissions per piglet produced, and so, per kg of pork produced. The approach used in this study, despite its limitations in front of bio-economic models, has shown to be a simple and flexible way to analyse the effect of incorporating GHG emissions into existing selection indexes.

Assessment of energy efficiency in buildings using synergistic walling material

Energy-efficient buildings assist in conserving energy and are currently prioritised due to increases in the cost of energy and greenhouse gas emissions. In this investigation, a low-thermal-conductivity walling material (bricks) was developed using co-fired blended ash (CFBA) for conserving energy in buildings. Physico-mechanical properties of the developed product were investigated according to Indian standards. Also, the thermal conductivity of the bricks was investigated. Building performance analysis was carried out with the help of a case study. Computational models for the single- (G), double- (G + 1) and triple- (G + 2) storeyed buildings were designed using the Autodesk Revit tool. The developed models were analysed for energy efficiency using building information modelling. With respect to fly ash bricks, the CFBA brick model estimated a 5% reduction in number of bricks as well as the dead load of the structure and resulted in peak cooling load reduction by 8, 11 and 15% for G, G + 1 and G + 2 storeyed buildings, respectively.

The economics of alternative crop production systems in the context of farmer participation in carbon trading markets

ABSTRACT Using scaled up data from an experimental farm platform in Scotland, we examined the relative economics of a conventional and a low-carbon integrated management system for two (otherwise identical) farms. By employing a novel market-based approach, we factored the market costs of greenhouse gas (GHG) emissions on the relative economics of both systems. Specifically, farmers are considered to be awarded emission credits in accordance with Scotland’s agricultural emissions reduction targets. Farmers are then considered to trade their net GHG emissions in an emissions trading scheme, with the integrated system expected to benefit from this arrangement due to its lower emissions. In further sensitivity analyses, we also considered the effect of premium pricing of integrated system crops on the relative economics of both systems. We find that in both the status quo and emissions trading scenarios, the conventional system is significantly more profitable. In the emissions trading scenario, an emissions price roughly three times the reported median prices over the last five years is required for the integrated system’s profitability to break-even with the conventional system. However, even at prevailing emissions prices, a 20% premium pricing of the integrated system crops enables near parity in the profitability of both systems. We conclude that in order to facilitate greater adoption of low-carbon systems, policies may be needed to encourage farmers’ realization of the cost of their externalities, in particular GHG emissions. At the same time, support should be given to a market system that recognizes premium prices for low-carbon system products.

Pathways to a fully sustainable electricity supply for Nigeria in the mid-term future

Ambitious actions focused on rapid defossilisation of today’s energy systems require greater urgency, in order to avert unmanageable impacts of climate change. Transitioning to a cost-effective and carbon-neutral energy system in Nigeria and across the globe by the second half of this century is vital. This study explores a paradigmatic pathway to a fully sustainable energy system for Nigeria, by 2050. The research approach is to simulate a cost-optimised transition pathway towards 100% renewable energy based power system for Nigeria, using a linear optimisation model. The model is based on hourly resolution for an entire year. The country researched is structured into 6 sub-regions. The optimisation for each of the 5-year time periods is carried out based on assumed costs and technological status until 2050 for all energy technologies involved. The levelised cost of electricity declines from 54 €/MWh in 2015 to 46 €/MWh in 2050 for the power sector in the Best Policy Scenario and further declines to 35 €/MWh with sector coupling. Whereas, the cost of electricity increased to 75 €/MWh in the Current Policy Scenario without greenhouse gas emission cost. The results clearly reveal that integrating a renewable energy technology mix with a wide variety of storage technologies is the most competitive and least cost electricity option for Nigeria in the mid-term future, as indicated by the Best Policy Scenario. In particular, the compatibility and predominant role of solar photovoltaics and batteries is paramount towards a rapid transition of Nigeria’s power sector, due to highly favourable economics. This study concludes with the implications of a stable and supportive policy environment, transitioning to a defossiliated energy system in Nigeria could be achieved in the mid-term future. This study is the first of its kind in full hourly resolution for Nigeria, and demonstrates the need for carrying out detailed analyses in examining gaps in energy transition understanding based on various policy constraints for developing countries in comparable climates.

Evaluation of the economics of desalination by integrating greenhouse gas emission costs: An empirical application for Chile

Abstract Desalinated water is an alternative and feasible water source that can help solve water scarcity problems. However, most desalination plants are operated using fossil fuels, which contribute to greenhouse gas (GHG) emissions. To face the problem of climate change, many countries are developing policies that promote renewable energy for electricity production. These policies might impact desalination costs. This paper proposes a methodology to evaluate the economics of desalination by integrating investment costs, operational and maintenance costs, and GHG emissions costs. This method will enable us to determine the impact of renewable energy polices on desalination costs. The empirical application was developed for Chile, a country with a promising future in renewable energy, and revealed that the full costs of desalinated water decrease by approximately 22% when the current electricity production mix is changed to predominantly renewable energy production. Moreover, this application illustrated the relevance of adopting a carbon tax to motivate the switch to renewable energy. This study demonstrates that the adoption of renewable energy policies involves a notable synergy with water issues.

The impacts of policies to reduce CO2 emissions within the concrete supply chain

The production of concrete is a significant source of global carbon dioxide (CO2) emissions that contribute to climate change. Many technical solutions exist for reducing emissions along the concrete supply chain. However, wide scale adoption of these technologies is hindered by a market failure – the cost of greenhouse gas emissions is not adequately reflected in cement and concrete transactions. Here, we compare three instruments meant to correct this critical market failure, including: 1) carbon-pricing policies, such as carbon taxes and cap-and-trade programs; 2) command and control policies; and 3) voluntary incentives. We evaluate each policy instrument for its capacity to reduce emissions cost effectively, guarantee emission reductions, spur technological innovation, and generate revenue. Our analysis shows that these criteria favor carbon pricing policies. However, cement and concrete markets are often concentrated and trade exposed. Therefore, regulators should design pricing policies that both combat leakage and do not limit production below socially optimal levels.

A series-parallel inventory-redundancy green allocation system using a max-min approach via the interior point method

PurposeThe purpose of this study is to develop a novel and practical series-parallel inventory-redundancy allocation system in a green supply chain including a single manufacturer and multiple retailers operating in several positions without any conflict of interests. The manufacturer first produces multi-product and then dispatches them to the retailers at different wholesale prices based on a common replenishment cycle policy. In contrast, the retailers sell the purchased products to customers at different retail prices. In this way, the manufacturer encounters a redundancy allocation problem (RAP), in which the solution subsequently enhances system production reliability. Furthermore, to emphasize on global warming and human health concerns, this paper pays attention both the tax cost of industrial greenhouse gas (GHG) emissions of all produced products and the limitation for total GHG emissions.Design/methodology/approachThe manufacturer intends not only to maximize the total net profit but also to minimize the mean time to failure of his production system using a RAP. To achieve these objectives, the max-min approach associated with the solution method known as the interior point method is utilized to maximize the minimum (the worst) value of the objective functions. Finally, numerical experiments are presented to further demonstrate the applicability of the proposed methodology. Sensitivity analysis on the green supply chain approach is also performed to obtain more insight.FindingsThe computational results showed that increasing the number of products and retailers might lead into a substantial increase in the total net profit. This indicated that the manufacturer would feel adding a new retailer to the green supply chain strongly. Moreover, an increase in the number of machines provides significant improvement in the reliability of the production system. Furthermore, the results of the performed sensitivity analysis on the green approach indicated that increasing the number of machines has a substantial impact on both the total net profit and the total tax cost. In addition, not only the proposed green supply chain was more efficient than the supply chain without green but also the proposed green supply chain was very sensitive to the tax cost of GHG emission rather than the number of machines.Originality/valueIn summary, the motivations are as follows: the development of a bi-objective series-parallel inventory-RAP in a green supply chain; proposing a hybrid inventory-RAP; and considering the interior point solution method. The novel method comes from both theoretical and experimental techniques. The paper also has industrial applications. The advantage of using the proposed approach is to generate additional opportunities and cost effectiveness for businesses and companies that operate utilizing the green supply chain under an inventory model.

Carbon Pricing: Correcting Climate Change's Market Failure

Abstract Climate change is the result of a market failure to account for the cost of greenhouse gas emissions to society, and pricing carbon is a powerful solution to correct this externality. Stud...

Optimal design of a hybrid electric propulsive system for an anchor handling tug supply vessel

Hybrid electric propulsive systems (HEPSs) attract increasing research interest due to their environmental and economic merits. However, the design optimization of HEPSs with the single objective of fuel saving may result in increased greenhouse gas (GHG) emission and high cost. The present study proposes a multi-objective optimization method to obtain an optimal trade-off with respect to fuel consumption, GHG emission, and lifecycle cost. Due to high convergence in solving constrained multi-objective optimization problems, the non-dominated sorting genetic algorithm II (NSGA-II) is developed to explore an optimal design space. Performance tests are conducted on a real-time hardware-in-the-loop (HIL) platform. The hybrid diesel/battery/shore power system on an anchor handling tug supply vessel is considered as a study case. The results of the proposed NSGA-II are compared with those from a single-objective optimization pursuing minimum fuel consumption. The proposed method outputs designs that can significantly reduce GHG emission and lifecycle cost by sacrificing low fuel consumption when compared with that of single objective optimization. Furthermore, the HEPS designed by the proposed method exhibits advantages over the conventional propulsive system in terms of all the three aspects.

Optimal sizing and location of renewable energy based DG units in distribution systems considering load growth

In recent years, scientists have extensively focused on renewable energy resources such as wind power and solar units to reduce the consumption of fossil fuels as the main source of environmental pollutions. One of the main challenges for the production of wind and solar energies is that they often involve uncertainties due to the stochastic natures of wind speeds and solar radiation. Therefore, the existing uncertainties in the resources of wind and solar units must be considered in the planning procedure of distribution systems for having a reliable performance. To consider uncertainties in the output power of renewable energy resources, a new formulation is proposed to determine the optimal location and sizing of solar and wind units in the distribution system. To achieve this, Particle Swarm Optimization (PSO) algorithm as a robust technique is employed to find the best location and sizing of wind, solar and fuel cell units in the distribution system. The main objective of the present work is to minimize the Total Harmonic Distortion (THD), the total power losses, the total cost of DG units (including investments, replacement, operation and maintenance costs) and greenhouse gas emissions. Different types of loads such as linear and non-linear loads as well as load growth are also considered in the distribution system. To demonstrate the effectiveness of the proposed algorithm, 31-bus test system is considered as the case study. Our findings show that the use of renewable energy resources significantly reduces the greenhouse gas emissions in the mentioned system. Furthermore, the simulation results reveal that DG units must be added at some years to keep the voltage within its allowable limits.

Data-driven approaches to integrated closed-loop sustainable supply chain design under multi-uncertainties

Abstract In this paper, the problem of sustainable closed-loop supply chain (CLSC) design under multi-uncertainties is studied. To identify an efficient way to enhance environmental and operational benefits of CLSC, we use “Big Data and propose data-driven approaches to generating robust CLSC designs that mitigate uncertainty and greenhouse gas (GHG) emissions burdens. More specifically, in addressing multi-uncertainties (i.e., buyers’ expectations, demands, and recovery uncertainties), a distributed robust optimization model (DRO) and an adaptive robust model (ARO) are developed for designing carryings and waste disposal facility locations of CLSC. Both models use historical data based on uncertain parameters for previous periods to make decisions on future stages in a robust way. Moreover, we incorporate K-L divergence into an ambiguous set of uncertain parameters to measure the value of data. The results of numerical analysis show the need to account for K-L divergence in an ambiguous set of DRO models, as GHG emission costs increase even when little K-L divergence disturbance is in place. Furthermore, from the data-driven framework, we find that government subsidies and an accurate estimation method (i.e., less K-L divergence) enhance environmental and operational benefits. Regarding model robustness levels, solutions generated from our ARO models outperform deterministic solutions not only in terms of their average objective value but also in terms of differences from ideal solutions.

Optimal Sizing and Arrangement of Tidal Current Farm

This paper proposes a bi-level programming-based optimization method to determine the sizing of tidal current farm (TCF) and the arrangement of tidal current turbines reaching the minimized comprehensive generation cost of tidal power. Not only the characteristics of tidal current velocity and wake effects but also the economic costs and environmental benefits brought by TCF integration are all incorporated in the proposed method. The method includes a power output model of TCF that can capture the characteristics of tidal current velocity and turbine wake effects, and a bi-level optimization model that takes into account the penalty costs of greenhouse gas emissions, the operation costs of power system, and the investment cost of tidal current turbines. The bi-level model is solved using a genetic algorithm and a quadratic programming technique. The effectiveness and adaptability of the proposed method are demonstrated using the measured data of tidal current velocity and the IEEE 30-bus test system.

A PROPOSED FRAMEWORK OF ENVIRONMENTAL DISCLOSURE ABOUT THE GREENHOUSE GAS EMISSIONS AND ITS REFLECTION ON FINANCIAL PERFORMANCE

This research aims to study the relationship between environmental disclosure on the cost of greenhouse gas emissions and financial performance. The researcher relied on an applied study on a sample of the listed industrial companies in the Egyptian Stock Exchange of 14 companies during the period from 2009 to 2016. The sample size was 183 companies. The researcher collected the data needed to conduct the applied study based on several sources, which are represented by the Egyptian Stock Exchange through its electronic website from financial lists and reports through Egypt Information Dissemination Company and Mubasher Egypt website, in addition to the data available for some establishments on its website On the Internet The researcher also relied on the analysis of the study data on descriptive statistics to test the hypotheses of the study, and a set of statistical methods represented in the method of correlation analysis Pearson and the method of multiple regression analysis. The researcher concluded from the results of the statistical analysis to accept the main assumption that there is a statistically significant relationship between the environmental disclosure of the cost of the outputs and the financial performance at a significant level (a≤0.05). The main recommendations made by the study: The study concluded that several recommendations were made to increase the institutional awareness and the NGOs in the Egyptian environment regarding the importance of accounting disclosure on the cost of greenhouse gas emissions. The need to issue an accounting standard by professional bodies and organizations to regulate the disclosure of gas emissions Global warming, leading to an increase in the quality of accounting information.

Combining Parameters of Fuel and Greenhouse Gas Costs as Single Objective Function for Optimization of Power Flow

The Kyoto Protocol is a protocol that highlights on greenhouse gases that have been adopted by many countries. Based on this protocol, power plants that produce emissions are encouraged to pay compensation. Conventionally, optimization of fuel mix in the electric power system components has not involved emission charges on the electricity system. This paper proposes a single objective function of a mathematical model for the calculation of power flow optimization involving greenhouse gas emissions costs to the fuel cost function. The single objective function derived using the mathematical model approach with linear heat rate function, in order to get the relationship between the fuel cost function with GHG emission. Namely, the function of energy costs as a combination of fuel costs and GHG emission costs can be shown as a quadratic function.