Indirect Carbon Emissions Research Articles

The impact of replacing chemical nitrogen fertilizer with monosodium glutamate waste liquid residue on yield, quality, and carbon emission of rice production

Replacing chemical nitrogen (N) fertilizer with monosodium glutamate waste liquid residue (MSGWLR) is beneficial for achieving clean production in both the monosodium glutamate (MSG) industry and agriculture. However, the impact of this method on rice production and environment has not yet been clear. This study adopted field experiments to clarify the rice yield, quality and carbon emissions applying conventional application of chemical N fertilizer (CF), reduction of N fertilizer by 20% (N80%), based on reduction of chemical N fertilizer by 20% and replacing 50% chemical N fertilizer with MSGWLR (MSGWLR50%), and replacing 100% chemical N fertilizer (MSGWLR100%). The results showed that compared with CF treatment, MSGWLR100% showed no significant changes in rice yield, milling quality, fatty acid value, and taste quality. The chalkiness rate of rice significantly decreased, and the protein content significantly increased. On the other hand, the carbon emissions from rice production treated with MSGWLR100% were the lowest, with a 58.5% decrease in global warming potential (GWP) compared to CF treatment. This was mainly because MSGWLR100% treatment could provide rich and balanced nutrients for rice growth, and it did not promote greenhouse gas (GHG) emissions from paddy field. At the same time, it effectively reduced the indirect carbon emissions in chemical fertilizer production by reducing chemical N fertilizer. Therefore, the MSGWLR100% fertilization treatment is beneficial for cleaner production in the MSG industry and rice cultivation.Graphical

Research on carbon emission measurement techniques for accounting and grid auxiliary services

Abstract Comprehensive and accurate carbon measurement in industrial parks is an important prerequisite for grasping the current status of carbon emissions in industrial parks and exploring their carbon reduction potential. In industrial parks, a large amount of indirect or direct carbon emissions will be generated in common processes such as power use, fuel consumption, and industrial processes, and how to realize the real-time and accurate measurement of indirect and direct carbon emissions in industrial parks will become the key foundation for promoting carbon reduction and emission reduction in industrial parks. This paper focuses on the impact of auxiliary services provided by distributed power generation on carbon emissions and the integration of multi-energy carbon emission measurement technology to carry out carbon emission accurate measurement technology research, puts forward an accurate measurement method of indirect electricity carbon emission in industrial parks considering auxiliary services, and forms a carbon emission measurement technology solution in line with the new energy power generation and multiple energy use in industrial parks to provide data support for the low-carbon transformation of electric power in the parks. The study will provide data support for the low-carbon transformation of electric power and energy in the industrial park.

An Empirical Analysis of Carbon Emissions in Higher Education Institutions: A Case Study of Zhejiang Ocean University Using Emission Factor Methodology

In recent years, with the increase in greenhouse gas emissions, global warming has created a series of complex ecological challenges. Colleges and universities are still in the exploratory stage of constructing low-carbon campuses. This study takes the campus of Zhejiang Ocean University as the research object and obtains carbon emission data from it based on the emission coefficient method by visiting the site and issuing a questionnaire survey. A total of 246 questionnaires were collected in this study, which were quantitatively analyzed to further understand the composition of the carbon emission structure of universities and put forward the corresponding energy-saving and emission-reducing suggestions. This study actively responds to the national call for energy saving and emission reduction and aims to provide a data reference as well as scientific support for the construction of a low-carbon campus. The results show that in 2021, the carbon emissions of Zhejiang Ocean University were 3.39 × 107 kg, of which direct carbon emissions were 3.34 × 105 kg, accounting for 0.99% of the total carbon emissions; indirect carbon emissions were 1.50 × 107 kg, accounting for 44.33% of the total; and other indirect carbon emissions were 1.85 × 107 kg, accounting for the remaining 54.68%. Also, this study found that individuals in colleges and universities pay attention to carbon emissions, but it is difficult for them to maintain a low-carbon approach in daily life. Based on the results of the analysis, this study proposes a series of effective measures to reduce carbon emissions at the campus of Zhejiang Ocean University, unite students in colleges and universities, and fully implement the concepts of energy saving, emission reduction, and sustainable development in college life.

Mathematical Modeling and Indirect Carbon Emission Reduction Analysis of Urban Wastewater Treatment Systems Under Different Temperature Conditions

In the context of achieving the two-carbon target, this study utilized a wastewater treatment plant in Shenyang City as a case study to accurately calculate indirect emissions related to energy and chemical consumption within the energy-intensive wastewater treatment industry. Sumo software was employed for precise mathematical modeling. Considering the operational characteristics of wastewater treatment plants in cold regions, this study innovatively divided the annual operation cycle into two periods, namely normal temperature and low temperature, and determined the optimal operational parameters under a low-carbon mode. The results indicate that precise regulation of dissolved oxygen concentration to 0.5–1.5 mg/L (normal temperature period) and 1–2 mg/L (low temperature period) can significantly reduce carbon emissions related to electricity consumption by 13,781.9 t CO2-eq. From the perspective of chemical consumption, adjusting the dosage of polyaluminum chloride (PAC) to 75% and sodium acetate to 70% during the normal temperature period can lead to a reduction in indirect carbon emissions of 1614.4 t CO2-eq compared to the same period last year. During the low-temperature period, by reducing the dosage of polyaluminum chloride to 80% and sodium acetate to 75%, the indirect carbon emissions can be reduced by 1557.3 t CO2-eq compared to the corresponding period last year. After optimization, USD 1.49 million can be saved. This study simulated the operation conditions of cold-region urban wastewater treatment plants at different times to effectively control carbon emissions resulting from energy and chemical consumption in wastewater treatment. This result can provide innovative ideas for energy saving and carbon reduction in cold-region wastewater treatment plants.

Energy, environmental footprints and economic benefit of substituting inorganic fertilizer with organic manure for winter wheat in Huanghuaihai Plain

Manure substitution shows promise for nitrogen (N) management, food security, energy balance and environmental costs reduction. However, there is limited research on this practice in the Huanghuaihai Plain. This study aimed to investigate the energy use efficiency, economic benefits, carbon and nitrogen footprint under two types of N fertilizer (U, urea and M, organic manure), two application rates of N (180 kg N ha−1, U1 for 100 % urea and M1 for 100 % organic manure; 90 kg N ha−1, U2 for 50 % urea and M2 for 50 % organic manure) and no fertilizer application treatment (CK) for winter wheat from 2017 to 2019. Results showed that grain yield and agricultural input cost under N application rate of 90 kg N ha−1 was 15.5 % and 7.8 % lower than that of 180 kg N ha−1, respectively, leading to a significant decrease in economic benefit. Under the same N rate, M1 obtained higher grain yield than U1, grain yield of M2 did no differ in that of U2. Total energy inputs and agricultural input costs of M were 9.5 % and 3.6 % lower than U, resulting in higher energy use efficiency and economic benefit. The reduced agricultural input for M was primarily due to a decrease in the application of inorganic fertilizer. Compared with other treatments, U2+M2 obtained higher grain yield, energy use efficiency, and economic benefit. The carbon and nitrogen footprint on unit grain yield of U1 was increased by 13.7 %-24.1 % and 3.9 %-19.6 %, which was attributed to the increase in direct N2O emissions, indirect carbon emission and losses of reactive N from agricultural inputs. Overall, U2+M2 sustained high productivity and reduced the environmental impact. Substituting inorganic fertilizer with organic manure was a promising strategy to improve agricultural production with less agricultural inputs and environmental footprints in the Huanghuaihai Plain.

Prospects for Long-Distance Cascaded Liquid—Gaseous Hydrogen Delivery: An Economic and Environmental Assessment

As an important energy source to achieve carbon neutrality, green hydrogen has always faced the problems of high use cost and unsatisfactory environmental benefits due to its remote production areas. Therefore, a liquid-gaseous cascade green hydrogen delivery scheme is proposed in this article. In this scheme, green hydrogen is liquefied into high-density and low-pressure liquid hydrogen to enable the transport of large quantities of green hydrogen over long distances. After long-distance transport, the liquid hydrogen is stored and then gasified at transfer stations and converted into high-pressure hydrogen for distribution to the nearby hydrogen facilities in cities. In addition, this study conducted a detailed model evaluation of the scheme around the actual case of hydrogen energy demand in Chengdu City in China and compared it with conventional hydrogen delivery methods. The results show that the unit hydrogen cost of the liquid-gaseous cascade green hydrogen delivery scheme is only 51.58 CNY/kgH2, and the dynamic payback periods of long- and short-distance transportation stages are 13.61 years and 7.02 years, respectively. In terms of carbon emissions, this scheme only generates indirect carbon emissions of 2.98 kgCO2/kgH2 without using utility electricity. In sum, both the economic and carbon emission analyses demonstrate the advantages of the liquid-gaseous cascade green hydrogen delivery scheme. With further reductions in electricity prices and liquefication costs, this scheme has the potential to provide an economically/environmentally superior solution for future large-scale green hydrogen applications.

Carbon footprint evaluation for electric vehicles considering green electricity trading

Electric vehicles (EVs) are often seen as a symbol of environmental friendliness. However, while EVs themselves do not directly emit carbon, the electricity they rely on may still contribute to carbon emissions. It is challenging to accurately assess the environmental impact of different types of electric energy used in charging stations due to unified pricing transactions. This hinders the precise measurement of each EVs' carbon footprint. To address this issue, this paper proposes a method for evaluating the carbon footprint based on Carbon Emission Flow (CEF) and energy traceability. A carbon integral mechanism is designed based on the China Certified Emission Reduction (CCER) scheme for coupling EVs with green electricity trading. These elements are integrated into the EV carbon footprint evaluation. Furthermore, the EVs' carbon footprint is minimized to select the lowest-carbon charging path for EVs owners. The feasibility of this proposed method is verified using an example from IEEE33 which quantifies EV footprints and indirect carbon emissions within the distribution network, ultimately encouraging consumption of green electricity by EVs and promoting more environmentally friendly modes of travel.

Analysis of the non-equilibrium and evolutionary driving forces of carbon emissions in China's construction industry

Clarifying the historical characteristics and influencing factors of carbon emissions in the construction industry is essential for formulating targeted emission reduction policies. The study utilized Dagum Gini coefficient and geographical detector to measure and analyze the regional disequilibrium characteristics and key driving factors of carbon emissions from the construction industry in China. The results indicate that regional disparities are the primary drivers of spatial imbalances in carbon emissions from China's construction industry. Indirect and interactive carbon emission driving forces were the main drivers of the spatial imbalance of carbon emissions. The output value of the regional economy and industrial structure exerted a significance influence. Notably construction output value, industrial structure and energy efficiency emerged as the main interaction factors. From these findings, four main conclusions are drawn: Controlling the carbon emission of building materials significantly alleviates the spatial imbalance of carbon emission in China's construction industry. The principle of regional coordinated carbon emission reduction in the construction industry should be followed. The regional economic level and industrial structure differences significantly affect the non-equilibrium of construction industry's carbon emissions. Accelerate the development of energy infrastructure can help to improve the construction industry's carbon emission balance. For the first time, Dagum Gini coefficient was combined with geographical detector analysis to study the disequilibrium of carbon emissions in the construction industry. This approach identified new multi-factor interaction driving forces, contributing to a deeper understanding of carbon emissions in the construction sector.

Carbon footprint of solar based mini-grids in Africa: Drivers and levers for reduction

The massive development of mini-grids (MGs) is seen as a promising alternative to the extension of national grids to achieve universal access to electricity. MGs based on solar photovoltaic are often recognized fully consistent with net-zero CO2 emissions objectives. However, if they have low or even no direct emissions from diesel consumption, they embed indirect carbon emissions due to solar panels and batteries manufacturing. Electrification policies, mainly based on the levelized costs of electricity (LCOE), should likely account for the carbon footprints (CFP) of possible electrification strategies.In this work, we assess the CFP of hybrid MGs (solar, battery, diesel) for rural electrification in Africa. We consider a large number of MG configurations for many locations across the continent. For each location, we identify the lowest CFP and LCOE, and estimate their dependency to meteorological and socio-economic factors.Our results show that: (i) the lowest CFP depends on location and is around 200gCO2/kWh; (ii) it can be higher than the CFP of certain African national grids; (iii) the CFP of hybrid MGs can be lower than the CFP of MGs relying only on solar PV; (iv) for most techno-economic and environmental assumptions, moderate LCOE increases allow significant CFP reductions.

Two-Stage Robust Optimization of Integrated Energy Systems Considering Uncertainty in Carbon Source Load

Integrated Energy Systems (IESs) interconnect various energy networks to achieve coordinated planning and optimized operation among heterogeneous energy subsystems, making them a hot topic in current energy research. However, with the high integration of renewable energy sources, their fluctuation characteristics introduce uncertainties to the entire system, including the corresponding indirect carbon emissions from electricity. To address these issues, this paper constructs a two-stage, three-layer robust optimization operation model for IESs from day-ahead to intra-day. The model analyzes the uncertainties in carbon emission intensity at grid-connected nodes, as well as the uncertainty characteristics of photovoltaic, wind turbine, and cooling, heating, and electricity loads, expressed using polyhedral uncertainty sets. It standardizes the modeling of internal equipment in the IES, introduces carbon emission trading mechanisms, and constructs a low-carbon economic model, transforming the objective function and constraints into a compact form. The column-and-constraint generation algorithm is applied to transform the three-layer model into a single-layer main problem and a two-layer subproblem for iterative solution. The Karush–Kuhn–Tucker (KKT) condition is used to convert the two-layer subproblem into a linear programming model. A case study conducted on a park shows that while the introduction of uncertainty optimization increases system costs and carbon emissions compared to deterministic optimization, the scheduling strategy is more stable, significantly reducing the impact of uncertainties on the system. Moreover, the proposed strategy reduces total costs by 5.03% and carbon emissions by 1.25% compared to scenarios considering only source load uncertainty, fully verifying that the proposed method improves the economic and low-carbon performance of the system.

Maximizing biomass utilization: An integrated strategy for coproducing multiple chemicals

Lignocellulosic biomass is one of the viable solutions to alleviate the global warming. However, the limited utilization of biomass majorly focused on cellulose and hemicellulose restricts the economic and environmental feasibilities. To cope with this issue, we proposed an integrated process of co-producing 1,6-hexanediol (1,6-HDO) with tetrahydrofuran and adipic acid from biomass, referred to as Strategy A. To compare the impacts of lignin upgrading and feedstock, Strategy B, which co-produces tetrahydrofuran alone, and Strategy C, which is the traditional route to produce 1,6-HDO from fossil fuels, were used. Heat networks are also designed to reduce operating costs and indirect carbon emissions due to energy consumption, saving 87% and 83% of the heat and cooling requirements, respectively, in Strategy A. The market competitiveness of Strategy A was evaluated by determining the minimum selling price through techno-economic analysis, and sustainability was thoroughly investigated by quantifying the environmental impacts through both midpoint and endpoint life-cycle assessments (LCAs). Strategy A was found to be the most favorable both economically (US$3,402/ton) and environmentally (−26.9 kg CO2 eq.). This indicates that lignin valorization is not only economically but also environmentally preferred. Finally, changes in economic and environmental feasibilities depending on economic, process, and environmental parameters were investigated using sensitivity and uncertainty analyses. The results of these analyses provide valuable insight into bio-based chemical production.

Comparison of Carbon Emissions from Traditional Treatment and Source Separation Treatment of Rural Domestic Sewage

Based on the carbon emission accounting method for domestic sewage, combined with the current situation of rural domestic sewage treatment, the carbon emissions of traditional schemes and source separation schemes under the three scenarios of single household, multi-household, and pipeline treatments were calculated. The results showed that the net carbon emissions （calculated as CO2） of the single household, multi-household, and pipeline treatment traditional schemes were 1.21, 3.37, and 2.69 kg·m-3, respectively. The net carbon emissions （calculated as CO2） of the single household, multi-household, and pipeline treatments in source separation schemes were -0.50, -0.04, and -0.54 kg·m-3, respectively, achieving zero or even negative carbon emissions. The direct and indirect carbon emissions of the source separation scheme were lower than those of the traditional scheme under all three scenarios. The carbon compensation measures in the source separation scheme mainly came from the land use of urine after storage and treatment. By separating blackwater from graywater at the source, the Source Separation Program achieved resource utilization of highly concentrated pollutants in blackwater, reducing emissions while generating significant carbon offsets. Therefore, efforts should be made to promote the separation and treatment of rural domestic sewage sources, improve the utilization rate of rural domestic sewage resources, and achieve green and low-carbon development of rural domestic sewage treatment.

Low‐carbon economic schedule of the H2DRI‐EAF steel plant integrated with a power‐to‐hydrogen system driven by blue hydrogen and green hydrogen

AbstractHydrogen direct reduction iron coupled with electronic arc furnace (H2DRI‐EAF) technology, as an important technology for decarbonisation in the iron and steel industry, has the advantages of high electrification and low carbon emissions. However, the large demand for hydrogen in this technology relies significantly on the production of electrolytic hydrogen, leading to a substantial increase in power consumption in the steel production process. Moreover, the use of an unclean power source in electrolytic hydrogen production leads to increases in indirect carbon emissions, reducing the low‐carbon attributes of the technology. This study investigates the integrated flexible operation mode of a steel plant. An illustrating method is utilised for modelling the entire steel production process and power to hydrogen (PtH2) process in detail for the H2DRI‐EAF steel plant, which includes natural gas, photovoltaic, wind power self‐provided power plants, and carbon capture and storage (CCS) systems. A mixed integer linear programming (MILP) model is developed for the comprehensive scheduling of the steel mill. The results of the case studies indicate that by reliably integrating the production of renewable energy and natural gas power plants, the PtH2 system can fully consume the renewable energy output while ensuring the smooth progress of steel production and maximising the reduction of carbon emissions from hydrogen production and the total cost of steel production.

Efficiency improvement of wastewater treatment plants under the background of “double carbon”: a case study in Jiujiang city, China

Wastewater treatment plants (WWTPs) play a crucial role in modern urban water environmental protection. However, they face challenges related to high operational costs and carbon emissions. This study focused on addressing these issues through an analysis of four urban WWTPs in Jiujiang city, China. The study involved comparing the size and processes of the plants, evaluating influent and effluent water quality, assessing energy consumption and chemical usage, and calculating both direct and indirect carbon emissions. The results demonstrated that the high operational costs and increased carbon emissions in these WWTPs were primarily attributed to low hydraulic loadings, low influent concentration, and high energy and chemical consumption. In response, three targeted scenarios were proposed to enhance the efficiency of the WWTPs and reduce carbon emissions. These scenarios involved adjusting the amount of wastewater imported into the WWTPs to meet the designed capacity, optimizing operating costs, or combining both approaches. Among the scenarios, Scenario 3 emerged as the most effective in terms of improving efficiency and reducing carbon emissions. The operational costs for WWTPs could be reduced in the range of 0.42–1.04 RMB/m3, representing a reduction rate of 35%–57%. Additionally, carbon emissions could be lowered from 15.02 to 598.85 gCO2e/m3, corresponding to a reduction of 2.91%–41.38%. Although Scenario 2 exhibited a lower carbon emission reduction of 14.8–316.33 gCO2e/m3, it was identified as the most feasible and easily implementable high-efficiency solution at present, with a reduction in operational costs ranging from 0.43 to 1.31 RMB/m3. To achieve zero energy consumption and zero carbon emissions in wastewater treatment in the future, it is recommended to undertake additional measures, such as enhancing dosing system accuracy, implementing tail gas collection, adopting photovoltaic power generation, implementing carbon sequestration techniques, and exploring wastewater heat source recycling. These findings provide valuable insights for optimizing the operational efficiency of urban WWTPs, reducing carbon emissions, and promoting sustainable wastewater treatment practices in Jiujiang city, China.

Will the miniaturization of household size promote household carbon emissions in China? Analysis based on CFPS data

As the proportion of household carbon emissions to global carbon emissions continues to increase, reducing carbon emissions from household consumption has become an important way to achieve the goals of carbon peaking and carbon neutrality. How the trend of miniaturization of household size will affect household carbon emissions is a matter of concern. This paper uses a sample of 9,090 households from the China Family Panel Studies (CFPS) database in 2018 to empirically study the impact of changes in household size on household carbon emissions, from the perspective of household consumption structure and urban-rural areas. The research results indicate that the miniaturization of household size will increase household carbon emissions, the impact of household size on indirect HCEs is greater than on direct HCEs. The impact of household size on indirect HCEs is heterogeneous in consumption structure and the impact of household size on indirect HCEs from housing, transportation is greater than that of other consumption items. The impact of household size on urban household carbon emissions is greater than that in rural areas. The upgrading of household consumption structure and the miniaturization of household size promote the increase of HCEs jointly. Therefore, this paper proposes that under the trend of household miniaturization, energy-saving and emission reduction policies should focus on reducing indirect households carbon emissions, optimizing household structure and household consumption structure, enhancing environmental awareness among family members, establishing and improving the green consumption system, and building environment-friendly households.

Renewable methanol production based on in situ synergistic utilization of excavated waste and landfill gas: life cycle techno-environmental-economic analysis

Excavated waste (EW) and landfill gas (LFG), as the two main landfill products, are essential objects of Enhanced landfill mining (ELFM). In this study, for the in situ synergistic utilization of LFG and the residue-derived fuel (RDF) from EW, an RDF-LFG to methanol (MeOH) unit with high exergy efficiency and low carbon emission is proposed. Then, to evaluate the environmental impacts and economic feasibility comprehensively, the life cycle assessment (LCA) and life cycle cost (LCC) are conducted on the EW-LFG to MeOH system based on the Aspen Plus simulation data of the RDF-LFG to MeOH unit. The system using EW landfilled in 2005 & 2015 as feedstocks are named Scheme A & B, respectively. The results show that both schemes have an exergy efficiency of more than 70 %. Regarding environmental impacts, RDF-LFG to MeOH, EW pretreatment, Storage and transport of products, and EW Mining are the main contributors. This study pays particular attention to global warming (GW) potential. The direct and indirect carbon emission of the RDF-LFG to MeOH unit are about 35 and 650 kg CO2 eq/ton MeOH, and the life-cycle GW of the EW-LFG to MeOH system is between 707 to 874 kg CO2 eq/ton MeOH. Levelized cost (LC) and levelized profit (LP) are about 452 $/ ton MeOH and 94 $/ton MeOH. With the transformation of the power grid, the decrease in carbon emission factor of power grids can improve both the environmental, and economic performance of the EW-LFG to MeOH system. Methanol selling price, carbon tax and electricity cost are the major sensible factors to the economic feasibility.

Analysis of Carbon Emission Reduction with Using Low-Carbon Demand Response: Case Study of North China Power Grid

The power sector is the single industry with the largest carbon emission in China, the carbon emission of which accounts for more than 40% of China’s total carbon emissions. In relevant research on the simulation of power system operation, current studies focus more on energy conservation and economical operation, while few consider the low-carbon optimization of the power system from the perspective of carbon emissions. In addition, in relevant research on carbon reduction in the power system, current studies focus more on controlling the direct carbon emission of the source side and less on the indirect carbon emissions of the load side, which focus on the reverse effect of a user’s electricity consumption behavior on the carbon reduction goals of the power system. This article delved into a deterministic simulation model of power system operation based on time series load curves and proposed a carbon reduction mechanism called the low-carbon demand response mechanism, which guides users to actively respond and reduce the carbon emission of power systems. In addition, this article conducted an empirical analysis based on the planning data of the North China Power Grid. To minimize carbon emissions, a simulation of low-carbon optimization operation for the North China Power Grid in 2040 was carried out. Then, based on the simulation results, an analysis of the carbon reduction benefits of low-carbon demand response was carried out. Ultimately, the empirical analysis verified that low-carbon optimization operation and low-carbon demand response technology possess significant carbon reduction potential for the power system.

A Comparative Study of Carbon Emissions from Industrial and Domestic Wastewater Treatment Plants under the Background of Carbon Neutralization

This paper studied the characteristics of the carbon emission of an industrial wastewater treatment plant (IWWTP) and a domestic WWTP (DWWTP) located in a high-tech industrial park of Shaanxi Province, China. The results showed that the total carbon emissions of the IWWTP and DWWTP were 10.13 kg/t and 1.84 kg/t in 2020, respectively. Indirect carbon emissions play a dominant role in the total carbon emission of the IWWTP, which accounts for about 97.6% of the total amount. The direct carbon emissions of greenhouse gases (e.g., CH4, N2O) account for about 62% of the total carbon emissions in the DWWTP, followed by the indirect carbon emissions generated by electricity consumption (31.06%) and chemical consumption (6.94%). Additionally, the centralized recycling and re-utilization of the wastewater could achieve 1.06 kg/t and 1.16 kg/t of carbon emission reduction in the IWWTP and DWWTP, respectively, while the carbon emissions of the DWWTP are inversely proportional to the treatment capacity. Therefore, it is of great value to collect and utilize intensively the recycled water to achieve the goal of regional carbon emission reduction and carbon neutralization of WWTPs in industrial parks.

Monitoring high-carbon industry enterprise emission in carbon market: A multi-trusted approach using externally available big data

Carbon markets are widely recognized as effective strategies for regulating carbon emissions from the enterprises of the high-carbon industry. Accurate monitoring of emissions in these enterprises is crucial for ensuring fair and trusted carbon trading. However, traditional monitoring methods have encountered various challenges including poor accuracy, low frequency, significant hysteresis and weak credibility. Addressing these concerns, this paper introduces a novel, multi-trusted, high-frequency monitoring approach for the measurement of both direct and indirect carbon emissions of enterprises, utilizing externally available multi-source big data, vertical federated long short-term memory network with a self-attention mechanism (VF-LSTMSA) and additive homomorphic encryption. The efficacy of this model is thoroughly assessed via case studies on six hourly datasets from the power and steel sectors. Our principal findings include: (1) In the current scenario, the proposed VF-LSTMSA model demonstrates superior federated efficiency, improving with the inclusion of more federated participants. (2) The VF-LSTMSA model surpasses other prevalent AI models, achieving a Mean Absolute Percentage Error (MAPE) of less than 9% across power and steel datasets. (3) The advanced high-frequency carbon emission monitoring method exhibits errors of +0.28%, +1.29%, and −0.41% in the current scenario monitoring task, suggesting that the model effectively leverages multi-source externally available big data to precisely monitor the target enterprise's carbon emissions while safeguarding multi-party data security. These findings suggest that the proposed monitoring method can accurately track corporate hourly carbon emissions, significantly improving the carbon trading and verification processes for enterprises

A strategy to assess the use-phase carbon footprint from energy losses in electric vehicle battery

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy.