Emission Reduction Capability Research Articles

Multi-objective optimal sizing and design of renewable and diesel-based autonomous microgrids with hydrogen storage considering economic, environmental, and social uncertainties

The multifaceted nature of human society necessitates the consideration of various indicators when planning and designing energy systems. The success of energy systems is contingent on their ability to reliably meet demands while satisfying different objectives that align with societal needs. This paper presents the multi-objective optimal design and configuration of hydrogen-storage-based microgrids to reliably meet electric load demands in remote regions while considering economic, environmental and social uncertainties. A comprehensive Mixed Integer Linear Programming (MILP) was adopted to model the microgrid consisting of renewable energy systems (RES), hydrogen energy storage system (HESS), battery energy storage system (BESS), and diesel generator (DG). Advanced Interactive Multidimensional Modelling System (AIMMS) was used to perform the deterministic and robust optimisation with special consideration on cost-greenhouse emissions minisation and employment generation maximisation. This study further performs a comparative analysis between hydrogen-based microgrids and lithium-ion battery-based microgrids in terms of the key objectives. In overall performance, the configuration consisting of photovoltaic (PV), wind turbine (WT), fuel cell (FC), electrolyser (EL) and low-pressure tank (LPT) outplays the other configurations considered in terms of total job factor, levelised cost of electricity, renewable energy penetration factor, carbon emission reduction capability. Considering both deterministic and robust solutions of the configuration, the levelised cost of electricity ranges between 0.131 and 0.169 $/kWh, the total lifetime cost varies from $2,002,100 to $6,784,740, and the job provision factor ranges between 0.339 and 0.447. Nevertheless, there is a need for further reduction of the investment cost for its continued technological and market penetration. This is a good basis for the adoption of hydrogen-based storage systems with renewable energy systems.

Effects of Biochar on Gaseous Carbon and Nitrogen Emissions in Paddy Fields: A Review

The paddy field is a major source of gaseous carbon and nitrogen emissions, and reducing these emissions is of great significance for mitigating greenhouse effects and non-point source pollution in farmland. Biochar, derived from agricultural waste, possesses a stable structure, large specific surface area, abundant pore structures, and surface functional groups. These characteristics could enhance soil physicochemical properties and microbial activity, thereby facilitating the dual goals of increasing crop yield and reducing emissions. Based on numerous studies, this review summarizes the effects of biochar on the emissions of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and ammonia volatilization (NH3), as well as on global warming potential (GWP) and greenhouse gas emission intensity (GHGI). It elucidates the mechanism of emission reduction by biochar amendment from the perspective of carbon and nitrogen conversion processes and soil physicochemical and biological properties. Numerous studies showed the application of 5~40 t ha−1 biochar reduced CO2, CH4, N2O, and NH3 emissions by 1.64~89.6%, 8.6~89.6%, 10~90%, and 12.27~53%, respectively. A small number of studies found that the application of 5~48 t ha−1 biochar increased CO2, CH4, N2O, and NH3 emissions by 12~37%, 19.85~176%, 13~84.23%, and 5.47~70.9%, respectively. Most scholars have found that biochar has varying degrees of emission reduction capabilities in different parts of the world. Therefore, future research directions have been suggested for utilizing biochar to reduce carbon and nitrogen emissions in paddy fields.

Construction and Application of Regional Carbon Performance Evaluation Index System: The Case of Chinese Provinces

As global warming becomes increasingly severe, reducing carbon emissions and promoting low-carbon development has become an international consensus. Against this backdrop, evaluating regional carbon performance helps better understand the carbon emission status, emission reduction capabilities, and low-carbon development levels, providing a scientific basis for formulating targeted carbon emission reduction policies. This study constructed a “5E” regional carbon performance evaluation index system from five dimensions: economy, effectiveness, efficiency, environmentality, and equity. Then, this study evaluated and analyzed the carbon performance of 30 provinces in China from 2008 to 2021 using the entropy weight TOPSIS method. The research results indicated that (1) during the sample period, China’s carbon performance ranged from 0.416 to 0.504, exhibiting a steady upward trend; the highest score among the first-level indicators was Effectiveness, while the lowest was Economy; (2) in terms of carbon performance among China’s three major regions, it showed a decreasing pattern from east to west, with the growth potential of the central and western regions being greater than that of the eastern region; (3) in 2033, the carbon performance of China in the eastern region, the central region, and the western region will reach 0.602, 0.612, 0.613, and 0.582, respectively. A carbon performance evaluation carries significant practical and strategic implications. Our study can provide a reference for policymakers to assess carbon emission performance and improve carbon management efficiency and decision-making levels.

Carbon emission reduction capability assessment based on synergistic optimization control of electric vehicle V2G and multiple types power supply

With the increasing proliferation of electric vehicles (EVs) and the integration of renewable energy sources into the power system, significant challenges have arisen for power system load balancing and stability control. The carbon emission reduction capability of power systems through coordinated optimization control of electric vehicles and power sources has garnered considerable attention. This paper evaluates the impact of Vehicle-to-Grid (V2G) and power source coordinated optimization control on the carbon emission reduction capability of power systems, proposing a technique that takes into account the dynamic characteristics of electric vehicles, power sources, and carbon emissions. This approach integrates V2G technology, renewable energy generation, and load demand into a framework aimed at optimizing power system operations and minimizing carbon emissions. A case study using real load data from a city assesses the impact of EV V2G and power source coordinated optimization control on carbon reduction. The results indicate that by 2025, peak-valley regulation will reach 1211,000 MW, with a carbon reduction of 138,783.799 tons, corresponding to a total reduction ratio of 1.101%. This research can provide valuable insights for policymakers, power system operators, and researchers.

A REVIEW OF EGR APPLICATION FOR AUTOMOTIVE INDUSTRY

Exhaust gas recirculation (EGR) has been widely adopted as an effective strategy to reduce harmful emissions and improve fuel efficiency in internal combustion engines. This review paper aims to provide a comprehensive analysis of the utilization of EGR in various types of internal combustion engines. The review covers the principles of EGR operation, its effects on engine performance, emission reduction capabilities, challenges, and prospects. By evaluating the existing literature and research findings, this paper seeks to offer insights into the potential of EGR as a crucial technology for sustainable and environmentally friendly auto-motive propulsion systems.

Optimal Configuration of Hybrid Energy Storage Capacity in a Grid-Connected Microgrid Considering Laddering Carbon Trading and Demand Response

In order to enhance the carbon emission reduction capability and economy of the microgrid, a capacity optimization configuration method considering laddered carbon trading and demand response is proposed for a grid-connected microgrid consisting of photovoltaic, battery and hydrogen storage devices. Combined with the mathematical model and system structure of each unit in the microgrid, the integrated operation control strategy is determined in this paper. A demand response model containing three load types is developed to reduce the stress on the storage and generation side. A carbon-trading mechanism is introduced into the operating costs to establish a configuration model with annual overall profit and power supply reliability as the optimization objectives. The non-dominated sorting genetic algorithm II is used to optimize the capacity of each unit, and the effectiveness of this model is verified by taking a microgrid in a region in Northwest China as an example to analyze the impacts of ladder carbon trading and demand response on the configuration results and system operation.

The achievement of carbon emission reduction targets for three typical tourism industries: A coordinated analysis based on efficiency and potential

The cultural, leisure, and natural tourism industries are selected, which are the greatest tourism carbon emitters and have significantly different carbon sources and sinks. We analyzed the realization mechanism of tourism emission reduction, classified their emission reduction capability coordinated efficiency and potential, and analyze their preferential implementation strategies. Our results show that: (1) The direction of tourism emission reduction includes increasing the value-added potential of desired and undesired outputs and improving the technologies in tourism energy-saving and emission-reduction. (2) The average emission reduction potentials are 51.31%, 59.99%, and 42.01% for the cultural, leisure, and natural tourism industries, respectively, and the average net carbon efficiencies are 0.578, 0.650, and 0.602, respectively. (3) For the cultural tourism, the strategy of reducing the tourism output inefficiency (S-ROIE) is optimal for provinces with high-efficiency and high-potential; the strategy of reducing the carbon emission inefficiency (S-REIE) is optimal for provinces with high-efficiency and low-potential; the S-ROIE is optimal for regions with low-efficiency and low-potential; the strategy of technology progress in energy-saving (S-ESTP) is optimal for provinces with low-efficiency and high-potential. (4) For the leisure tourism, the S-ESTP is optimal for provinces with high-efficiency and high-potential; the S-REIE is optimal for provinces with high-efficiency and low-potential; the S-ROIE is optimal for provinces with low-efficiency and low-potential; the strategy of technology progress in emission reduction (S-ERTP) is optimal for provinces with low-efficiency and high-potential. (5) For the natural tourism, the S-REIE is optimal for provinces with high-efficiency and high-potential; the S-ROIE is optimal for provinces with high-efficiency and low-potential; the S-ERTP is optimal for provinces with low-efficiency and low-potential; the S-REIE is optimal for provinces with low-efficiency and high-potential

Impact assessment of crude oil mix, electricity generation mix, and vehicle technology on road freight emission reduction in China.

To achieve net zero emissions, the global transportation sector needs to reduce emissions by 90% from 2020 to 2050, and road freight has a significant potential to reduce emissions. In this context, emission reduction paths should be explored for road freight over the fuel life cycle. Based on panel data from 2015 to 2020 in China, China's version of the GREET model was established to evaluate the impact of crude oil mix, electricity mix, and vehicle technology on China's reduction in road freight emissions. The results show that the import share of China's crude oil has increased from 2015 to 2020, resulting in an increase in the greenhouse gas (GHG) emission intensity of ICETs in the well-to-tank (WTT) stage by 7.3% in 2020 compared with 2015. Second, the share of China's coal-fired electricity in the electricity mix decreased from 2015 to 2020, reducing the GHG emission intensity of battery electric trucks (BETs), by approximately 6.5% in 2020 compared to 2015. Third, different vehicle classes and types of BETs and fuel cell electric trucks (FCETs) have different emission reduction effects, and their potentials for energy-saving and emission reduction at various stages of the fuel life cycle are different. In addition, in a comparative study of vehicle technology, the results show that (1) for medium-duty trucks (MDTs) and heavy-duty trucks (HDTs), FCETs have lower GHG emission intensity than BETs, and replacing diesel-ICETs can significantly reduce GHG emissions from road freight; (2) for light-duty trucks (LDTs), BETs and FCETs have the highest GHG emission reduction potential; thus, improving technologies such as electricity generation, hydrogen fuel production, hydrogen fuel storage, and transportation will help to improve the emission reduction capabilities of BETs and FCETs. Therefore, policymakers should develop emission standards for road freight based on vehicle class, type, and technology.

Allocation and optimization of carbon emission permits considering fairness and efficiency under the dual-carbon background

Reasonable and effective allocation of carbon emission permits is one of the important tasks to achieve the goal of carbon neutrality. Based on the difference in carbon emission reduction contribution and capability of the industries, this paper proposes a carbon emission permits allocation and optimization scheme that take into account fairness and efficiency. First, based on fairness principle, establish a carbon emission quota system of the six industries and determine the index weights, and use the comprehensive index method to realize the initial allocation of carbon emission permits. Then, on the basis of evaluating the initial carbon emission permits allocation efficiency, based on efficiency principle, the zero sum gains data envelopment analysis (ZSG-DEA) model is used to iteratively obtain the optimal allocation scheme of carbon emission permits. Example analysis shows that the carbon permit allocation and optimization model based on fairness and efficiency principles proposed can realize the optimal allocation of industrial carbon emission permits, ensure the optimal efficiency of industrial carbon permit allocation, and provide adequate support for the carbon emission reduction decisions of the six industries.

Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method

To balance China's socio-economic development and emission reduction goals, a fair and effective provincial carbon emission allowance (CEA) allocation is necessary. By considering the implied emissions of inter-provincial power transfer, this study designed a dynamic multi-criteria CEA allocation model based on four criteria-egalitarianism, historical responsibility, emission reduction capability, and emission efficiency-to calculate the provincial CEA year by year before 2030. The efficiency and fairness of the CEA scheme were evaluated through the Data envelopment analysis (DEA) model, the environmental Gini coefficient, and its grouped decomposition method. The national overall CEA, the results revealed, will peak during the 15th Five-Year Plan (FYP) period. Specifically, the CEA for eastern and central China is expected to peak first during the 14th FYP period, while the northeast region's CEA remains stable and that of the western region continues to grow. Provinces with high carbon emissions, high carbon emission intensity and high per capita carbon emissions and provinces with particularly high carbon emissions will face great pressure regarding emission reduction, and their CEA peaks are expected to arrive before 2025 and 2030 respectively. The CEA of the less-developed provinces will have a surplus. In terms of time, the high-emission provinces face greater emission reduction pressure during the 15th FYP period than during the 14th FYP period. In terms of scheme evaluation, the scheme achieved a double improvement in fairness and efficiency compared with the current actual emissions of various provinces. Reducing the differences in per capita CEA between the different regions and provinces in the western and eastern regions will help improve the scheme's fairness. This study overcomes the existing researches' shortcomings on the large differences in the distribution of emission reduction pressures in key provinces and is more feasible in practice.

Assessing the environmental benefits of battery packs from multi‐vehicle and multi‐region perspective: Aiming for lightweight and carbon neutrality

AbstractVehicle lightweight and carbon neutrality turn out to be the critical goals in developing new energy vehicles. As an important part of electric vehicles, power battery packs have an impact on the environment. In this study, multiple environmental assessment indicators were grouped into a comprehensive index, namely the green characteristic index, and the green characteristic index was used to comprehensively evaluate the environmental impact of 11 kinds of battery packs. This study calculates and analyzes the environmental impact values of battery packs in different regions for four types of small, medium, intermediate, and limousine cars. Finally, the uncertainty analysis was carried out. Research has found that micro battery packs have a lower potential environmental impact than advanced battery packs, so smaller, more energy‐efficient battery electric vehicles (BEVs) generally perform better than larger BEVs for vehicle models. During the operation stage of the battery pack, the environmental impact value of carbon footprint and ecological footprint is greatly affected by the regional power structure. Running the battery pack in China will generate higher carbon footprint and ecological footprint. In addition, the green characteristic index is more affected by the stage of use. When the scene is switched, the larger the model of the electric vehicle, the more obvious its environmental emission reduction capability. This highlights the benefits of high‐efficiency electrical structures in large electric vehicles, which can reduce environmental impact by increasing lifetime and charging efficiency, reducing the loss of transport power in the area, and improving the weight‐to‐energy relationship for BEVs.

Optimal design of wind-powered hydrogen refuelling station for some selected cities of South Africa

The transport sector is considered as one of the sectors producing high carbon emissions worldwide due to the use of fossil fuels. Hydrogen is a non-toxic energy carrier that could serve as a good alternative to fossil fuels. The use of hydrogen vehicles could help reduce carbon emissions thereby cutting down on greenhouse gases and environmental pollution. This could largely be achieved when hydrogen is produced from renewable energy sources and is easily accessible through a widespread network of hydrogen refuelling stations. In this study, the techno-economic assessment was performed for a wind-powered hydrogen refuelling station in seven cities of South Africa. The aim is to determine the optimum configuration of a hydrogen refuelling station powered by wind energy resources for each of the cities as well as to determine their economic viability and carbon emission reduction capability. The stations were designed to cater for 25 hydrogen vehicles every day, each with a 5 kg tank capacity. The results show that a wind-powered hydrogen refuelling station is viable in South Africa with the cost of hydrogen production ranging from 6.34 $/kg to 8.97 $/kg. These costs are competitive when compared to other costs of hydrogen production around the world. The cities located in the coastal region of South Africa are more promising for siting wind powered-hydrogen refuelling station compared to the cities located on the mainland. The hydrogen refuelling stations could reduce the CO2 and CO emissions by 73.95 tons and 0.133 tons per annum, respectively.

Reducing Emissions CO, CO2, and HC, on Vehicles with Gasoline Fuel

Merauke Regency is the largest regency in Papua with the highest fuel consumption by regency/city in Papua Province. The high fuel consumption is proportional to the emissions produced, so research on emissions absorbing media is needed to reduce emissions. Active charcoal has the ability to adsorption of emissions, one of the raw materials is plants. Bus wood (eucalyptus) which grows a lot in Merauke can be used as raw material for activated charcoal which is used as an absorber of emissions. Research with the title “application of eucalyptus charcoal as emission adsorbent to reduce vehicle exhaust emissions” processes wood logs into emission adsorbents, through carbonation and activation processes, then activated charcoal is applied to vehicle vehicles and subsequent emission tests, to determine emission reduction capabilities. Based on the results of emission tests, the use of activated charcoal as an emission adsorber can reduce emissions. 0.07% CO emissions decreased to 0.01%, HC emissions 84 ppm, decreased to 39 ppm, and 14.7% CO2 decreased 4.4%.

A Comprehensive Evaluation of Carbon Emission Reduction Capability in the Yangtze River Economic Belt.

The Yangtze River Economic Belt (YREB) is an essential part of China’s goal of reducing its national carbon emissions. Focusing on economic and social development, the development of science and technology, carbon sinks, energy consumption, and carbon emissions, this paper uses “the Technique for Order of Preference by Similarity to Ideal Solution mode” (TOPSIS) and “an obstacle factor diagnosis method” to measure the reduction capacity of each province and municipality of the YREB. Key obstacles to achieving the goal of carbon emission reduction are also identified. The main finding is that the emission reduction capacities of Shanghai, Jiangsu and Zhejiang in China’s east is far greater than that of all other provinces and municipalities, the main obstacle of Shanghai, Jiangsu, and Zhejiang are carbon sinks, energy consumption and carbon emission, and other provinces and municipalities are social and economic development. Taking into consideration those evaluation results and obstacles, paths for carbon emission reduction are delineated through a four-quadrant matrix method with intent to provide suitable references for the development of a low-carbon economy in the YREB.

Multi-objective green design model to mitigate environmental impact of construction of mega columns for super-tall buildings

The mega columns used in super-tall buildings are several meters in size; thus, a greater quantity of construction materials are required than for a general column. Considering the environmental impact, research on a green design model for super-tall buildings is necessary. This design model should minimize both CO2 emissions and cost in the mega-column construction and design phases with consideration of the member or building size. In this regard, a multi-objective green design model (MOGDM) capable of minimizing construction cost and reducing CO2 emissions is proposed in this study. The MOGDM is applied to the design of mega columns for a super-tall building and its performance is evaluated based on the average environmental impact reduction rate (AER) and the average increase-in-cost reduction rate (AICR); these indexes are developed to assess the CO2 emission and construction cost reduction capability. Under the loading scenarios considered in this study, the average AER and AICR for the MOGDM output are 6.76% and 58.02%, respectively. Thus, the evaluation results confirm that the MOGDM proposed in this study can effectively reduce CO2 emissions and cost in the design and construction phases of mega columns for super-tall buildings.

Cost savings and emission reduction capability of wind-integrated power systems

In the face of energy crisis and environmental impacts of conventional energy sources, renewable energy sources have attracted tremendous interest. Among many resources, wind energy has proven to be a promising renewable energy option in recent times. The primary objective of utilizing renewable energy is its environmental sustainability and the idea of emission reduction constitutes a prominent part in it. The emission here refers to the CO2, SO2 and NOx emissions from thermal power plants. However, recent research works suggest that there remains a considerable anomaly between the claims of emission reduction by wind energy developers and the actual emissions, particularly with the integration of wind power into the grid system. The estimation methodology involving tools like wind resource assessment and energy capture may not provide accurate estimates due to some power system generation and operational constraints. The objective of the present study is to analyse the impact of wind turbine ratings and economic emission dispatch (EED) on the generation cost and emissions in wind integrated power systems. In this regard, the study investigates the concept of emission factor and wind-integrated EED. Wind turbines available at different rated power and rated speeds are incorporated in four different test power systems and the actual cost and emissions over a selected period are evaluated. Finally, the impact of the wind power integration on the generation cost savings and emission reduction is investigated.

Multi crowd fast power control algorithm based on neighborhood opportunistic learning

For improving the energy-saving power generation scheduling in the electric power industry energy saving and emission reduction capability and enhance the safety and economy of power energy structure, we based on neighborhood opportunity learning multi intelligent power quickly swarm intelligent control algorithm is presented in this paper. Firstly, the proposed algorithm is based on the characteristic value of each neighborhood characteristic value which is obtained by chance mining. The system can obtain the real-time sensing data of each neighborhood power station. This algorithm establishes a neighborhood modular architecture. The algorithm in the opportunity to automate the operation of the module information on the opportunity to learn. Secondly, based on the opportunity to learn and fast variation of the power vector, the algorithm is derived to control the power generation fast group. The algorithm of the multiple power generation control system through the opportunity to control and quickly set the mapping link. Finally, the experimental results show that the proposed algorithm has a significant advantage in real-time, reliability and cost of intelligent management and fast control of power generation to adapt to a variety of power generation devices.

Developing CBDR-RC indices for fair allocation of emission reduction responsibilities and capabilities across countries

The aim of this paper is to develop two indices for quantifying common but differentiated responsibilities (CBDR) and respective capabilities (RC) of countries in mitigating climate change. These composite indices can help facilitate fair allocation of GHG emission reduction responsibilities across countries. Indices are formulated by taking into account the economic, environmental, social, and technical indicators of a given country. These indicators are usually highly correlated. An index using these indicators must take this high correlation into account, otherwise it will either over or underestimate the responsibility and the capability of a country. This study takes the correlation between the indicators into account in developing the CBDR and RC indices via the principal components method. However, the novelty of this study arises from measuring and using economic, social, technical, and environmental indicators together in creating the composite indices. The CBDR and RC are constructed for 50 countries that are responsible for at least 81% of global GHG emissions, including OECD countries and emerging economies. The Cluster Analyses are employed to classify the countries according to their CBDR and RC scores. The results suggest revision of current responsibility and capability classifications of the UNFCCC.

Operational Emission Reduction Capability of Regional Power System

Based on the current development status of China power system, this article aims to analyze factors that have influence on operations emission reduction capability of regional power system, and develop mathematical model for emission reduction capability measurement. The great potential emission reduction capability will be calculated by applying this model to Jilin Province.

A new apartment construction technology with effective CO2 emission reduction capabilities

This construction industry is responsible for over 30% of the total industrial CO2 emission in Korea, and bearing wall apartment housing represents more than 50% of all housing in Korea. A new multi-residential Modularized Hybrid System (MHS) for construction of apartment housing may reduce the amounts of construction material used as well as the amounts of CO2 emission. This paper collected and compared data on the CO2 emission properties of construction materials for bearing wall and new MHS apartments including concrete, reinforcing steels, formwork, and gypsum board. MHS construction techniques reduce CO2 emission by 25.1% by requiring less concrete and reinforcing steels for slabs and walls that would otherwise be needed in conventional bearing wall structures. This paper also shows that migration to a Rahmen structure utilizing an MHS frame can provide an alternative solution to reducing CO2 emission.