Indirect Emissions Research Articles

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.

Chinese Household Carbon Footprint: Structural Differences, Influencing Factors, and Emission Reduction Strategies Analysis

The wide variation in household characteristics, such as household size, income, and age, can lead to significant differences in carbon footprints. Based on data from 1132 Chinese households in 2021, this study examines the structural differences, multiple influencing factors, and mitigation strategies of household carbon footprints (HCFs) in China. The results indicate that indirect emissions, primarily from energy and food consumption, account for the largest share of household carbon footprints, making up over 65% of total emissions. Households with lower carbon footprints are characterized by a per capita living area of less than 20 square meters, rural residences, and shared living arrangements. Carbon footprints for the elderly and minors are lower than adults, while households with higher monthly incomes have the highest carbon footprints. The Multivariate Analysis of Variance (MANOVA) reveals that the main factors influencing HCF include household size, income, and single status, with a more pronounced impact on affluent households than on average households. High-income households have the potential to reduce their carbon footprints through investments in energy-efficient technologies, whereas low-income households are more susceptible to the effects of household size and geographic location. It is recommended that policymakers adopt differentiated measures, such as setting higher reduction targets for larger and wealthier households while providing incentives and technical support to low-income households to achieve meaningful carbon reductions. More effective and equitable low-carbon policies can be formulated by addressing these structural disparities and leveraging the unique characteristics of different household types.

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.

Greenhouse Gas Emissions from Cold Chains in Agrifood Systems

Cold chains are essential components of agrifood system activities, from storage and food processing to transport, retail, and household consumption. We devise a comprehensive methodology, validated against established data, to estimate both direct (due to refrigerant use) and indirect (from energy use) greenhouse gas emissions from agrifood system cold chains, expanding previous approaches, which had focused on direct emissions only. We found that in 2022, world-total indirect emissions from energy use in cold chains were more than twice the direct component from refrigerants. This resulted in a new estimate of world-total GHG emissions from agrifood system cold chains of 1.32 Gt CO2eq in 2022, with significant growth over the past two decades (0.52 Gt CO2eq in 2000). Household consumption and food processing represented the most significant contributors to agrifood system emissions from cold chains, together representing in 2022 three-fourths of the total. These results align well with known global patterns of energy use in the refrigeration sector and highlight the importance of targeting cold chains within agrifood system with GHG emission mitigation actions.

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.

Sustainable Logistics: Synergizing Passive Design and PV–Battery Systems for Carbon Footprint Reduction

As more companies strive for net-zero emissions, mitigating indirect greenhouse gas emissions embedded in value chains—especially in logistics activities—has become a critical priority. In the European logistics sector, sustainability and energy efficiency are receiving growing attention, given the sector’s intersectional role in both transportation and construction. This transition toward low-carbon logistics design not only reduces carbon emissions but also yields financial benefits, including operational cost savings and new market opportunities. This study examines the impact of passive design strategies and low-carbon technologies in a Swedish logistics center, assessed using the low-carbon design criteria from the BREEAM International standard, version 6. The findings show that passive energy-efficient measures, such as the installation of 47 skylights for natural daylighting, reduced light power density in accordance with AHSHARE 90.1-2019 and the integration of free night flushing, contribute to a 23% reduction in total energy consumption. In addition, the integration of 600 PV panels and 480 batteries with a capacity of 268 ampere-hours and 13.5 kWh storage, operating at 50 volts, delivers a further 56% reduction in carbon emissions. By optimizing the interaction between passive design and active low-carbon technologies, this research presents a comprehensive feasibility analysis that promotes sustainable logistics practices while ensuring a future-proof, low-carbon operational model.

Health benefits of US light-duty vehicle electrification: Roles of fleet dynamics, clean electricity, and policy timing

We present a dynamic perspective to quantify the air quality-related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NOx, SO2, PM2.5, NH3, and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NOx emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality-related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits.

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.

A Study on Carbon Emission in Logistics Industry: Creating Awareness to Reduce

Objective: Climate change is a reality we cannot ignore and now more than ever we need visible action irrespective of our geographic location or economic status. This study explores the multifaceted hurdles impeding scope 3 emission reduction initiatives within the logistic sector, challenges that create barriers in their investment decisions, regulatory pressures, unavailability of technology and monitoring support, etc. Theoretical Framework: Globally, alerts are being created for climate actions that are lacking and resulting in huge gaps between the target set and covered. Bangladesh is leading the way towards green initiatives scope 1 (Direct emission) and 2 (Indirect emission) but not visible driving scope 3 emission reduction (All indirect emissions in a company’s value chain, including downstream transportation). Method: Employing a qualitative approach, data was gathered through interviews and meetings with 500 or more green factories in Bangladesh. Due to less time and political barriers, could not continue the research and accumulate more data. Results and Discussion: The findings highlight revealing key barriers such as unavailability of technology, overly expensive options or huge investment for intensive technology, limited access to those technologies, lack of skilled resources, monitoring and reporting challenges, lack of collaboration, etc. that are creating obstacles for climate actions all around the world. Research Implications: Awareness and collaboration could bring a positive impact to reduce the significant challenges that the logistics industry confronts in reducing Scope 3 emissions, obliging collaborative efforts among service providers, manufacturers end users. Originality/Value: Policy interventions and technological upgrades can emphasize the significance of unified action in transforming the logistics landscape towards sustainability which would impact positively and make a difference.

Impact of a forage legume or nitrogen fertilizer application on ammonia volatilization and nitrous oxide emissions in Brachiaria pastures

ABSTRACT The largest proportion of greenhouse gas (GHG) emissions in the Agriculture sector of the Brazilian national GHG inventory is derived from the large (>200 million head) herd of cattle. The greatest contribution to these emissions comes from the enteric methane from cattle, but the direct and indirect emissions of nitrous oxide (N 2 O) from cattle excreta and N fertilizer are responsible for approximately 9 % of all national anthropogenic GHG emissions. Ammonia (NH 3 ) can be volatilized from N fertilizer and cattle excreta and deposited in sites remote from the source, constituting an indirect source of N 2 O. This study aimed to determine whether direct N 2 O emissions and NH 3 volatilization from N-fertilized pastures were greater than those derived from a mixed grass-legume pasture without N fertilizer addition. Emissions of N 2 O and NH 3 from excreta and N fertilizer from a Palisade grass (Urochloa brizantha cv. Marandu) monoculture fertilized with 2 × 60 kg N ha -1 yr -1 urea were compared to those from a mixed Palisade grass-forage peanut (Arachis pintoi) pasture. Dung and urine were collected from these cattle, and NH 3 losses and N 2 O emissions from the excreta and from N fertilizer were monitored using static chamber techniques. Volatilization of NH 3 and N 2 O emissions were found to be greater from urine than from dung. Ammonia losses from excreta and urea fertilizer were low, not exceeding 6.8, 1.1, and 4.7 % of the N applied as urine, dung, and fertilizer, respectively. The N 2 O emissions showed a tendency to be greater for the urine from the N-fertilized compared to the mixed grass-legume pasture, and the N 2 O emissions from the urine of the N-fertilized pasture ranged from 0.08 to 0.94 % of applied urine N. The N 2 O emission from the N fertilizer was at maximum 0.46 % of the applied N. The direct N 2 O emissions and the loss of NH 3 by volatilization (indirect N 2 O emission) from the excreta of cattle grazing the mixed grass-legume pasture were similar to, or lower than, the grazed grass monoculture fertilized with 120 kg N ha -1 yr -1 . As the mixed pasture received no N fertilizer and hence no GHG emission from its manufacture or application, introducing forage peanut to the Urochloa brizantha pastures shows potential to be responsible for lower GHG emissions than the N fertilized grass pasture.

THE HOUSING UNITS OF THE POSITIVE CLIMATE NEIGHBORHOOD PEDRA BRANCA SC/BR

In response to the global climate crisis, urgent measures are required to reduce greenhouse gas emissions in alignment with the goals of the Paris Agreement. As energy consumption accounts for 36% of total emissions, and buildings contribute significantly to both direct and indirect emissions, it is crucial to enhance the energy efficiency and self-sufficiency of buildings. This article conducts a case study to evaluate the formal structure, spatial layout, and sustainable strategies employed in residential units within the Pedra Branca neighborhood (Santa Catarina, Brazil), using the methodology developed by Brandão and Schneider. The findings indicate that the housing units predominantly consist of three bedrooms, along with two to four bathrooms. The analysis revealed partial integration between the kitchen and service areas, with full integration being less common. Corridor layouts were found to make the greatest contribution to sustainability and internal space quality. Although some configurations did not directly support cross-ventilation, there was a clear focus on environmental comfort and the use of passive design strategies. This study highlights the potential of such configurations to improve energy performance and contribute to the development of climate-positive neighborhoods.

Small business, big footprint: the digital carbon footprint dilemma in small and medium-sized enterprises

A major contributor to climate change is the emissions from Information and Communication Technology (ICT) devices and digitalisation. Energy use, heat production, and the operation of assets all contribute to the production of harmful emissions. However, indirect emissions, such as production and disposal, also play a role. We rely mainly on the output of small and medium-sized enterprises (SMEs). This paper focuses on the emissions of SMEs. Is it certain that cloud services (remote data storage and management) leave a much smaller carbon footprint than ICT devices for own use? These two solutions lead to a paradox: using more modern devices to produce less emissions requires more energy and generates more heat. This article analyses how to resolve this paradox for SMEs.

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.

Unraveling a novel biphasic CO2 capture process through rigorous modeling

Modification of the chemical absorbent is a crucial aspect in the field of CO2 capture. Nevertheless, the consequences arising from the utilization of modified solvents have not been thoroughly examined on a process scale. This study investigates a biphasic chemical absorption process for CO2 capture using a blended solvent composed of 2-ethylamino ethanol (EAE), diethylene glycol diethyl ether (DEGDEE), and water. The design was based on rigorous consideration of the physical properties of the pure components and the solution, as well as chemical equilibrium. Our results indicate that the proposed biphasic process reduces specific regeneration energy by 6.45 % compared to the conventional method using monoethanolamine (MEA) solution as a solvent (biphasic: 3.41 GJ/Ton; conventional: 3.63 GJ/Ton). Furthermore, it presents the advantage of utilizing low-temperature waste heat for solvent stripping, resulting in a notable 56 % decrease in indirect emissions (biphasic process: 0.119 Ton/Ton, conventional: 0.274 Ton/Ton). When processing flue gases that are more diluted in CO2, the CO2-e of the biphasic process was only slightly increased. Finally, the techno-economic analysis demonstrated that the biphasic process exhibits minimum required treatment prices (MRTPs) comparable to those of conventional methods for treating flue gases with CO2 concentrations ranging from 10 to 19 mol% (biphasic: 0.755 to 1.452 USD/kg, conventional: 0.756 to 1.455 USD/kg). This finding highlights the economic potential of the biphasic process. Overall, this investigation sheds light on the potential of intensifying the CO2 capture process in a biphasic environment.

THE CHALLENGE OF BENCHMARKING CARBON EMISSIONS IN MARITIME PORTS

The carbon footprint of ports is an essential step in understanding the most impactful activities in ports and designing reduction strategies to comply with the ambitious target set up by the International Maritime Organization (IMO) of cutting GHG emissions by 50% until 2050 (compared to 2008 levels). Acknowledging the importance of decarbonization, several ports have started to report their carbon emissions in recent years. However, currently, there is not a commonly acknowledged approach to quantify the carbon footprint of ports, making the benchmarking of ports that is the main goal of this paper, a challenging task. The focus is on the topmost polluting European ports, although other major ports outside Europe are also considered. Results show that considering only GHG emissions controlled by port authorities (Scope 1) and emissions related to purchased electricity by port authorities (Scope 2), the carbon footprint of EU ports ranges from 0.017 kg CO2 eq./tonne to 1.27 kg CO2 eq./tonne. When, in addition, indirect emissions from sources not owned or controlled by port authorities (Scope 3) are considered, then the range of values varies from 2.0 to 5.4 kg CO2 eq./tonne. Moreover, results show that Scope 3 is usually neglected in the inventory of emissions of ports due mainly to the complexity of setting the boundaries and extensive data collection. However, when emissions associated with vessels are considered, the contribution of Scope 3 becomes dominant, with shares higher than 97%. Finally, given the importance of having consistent benchmarks for the carbon footprint of ports, this paper further suggests the need for adopting a standardized approach to calculate the carbon footprint of ports.

High-fidelity model development of CO2 booster refrigeration systems in supermarkets using field measurements

Supermarket refrigeration systems adopting traditional refrigerants with high global warming potential (GWP) have impacts on global warming for indirect and direct greenhouse gases (GHG) emissions. CO2 is a popular low-GWP alternative. The transcritical operation of CO2 systems worsens their energy performance, but provides recoverable heat as a heat source to reduce gas consumption. To evaluate operation performance, data-driven models, trained by historical data, are weak in implementation with datasets outside the scope of training data; in contrast, theoretical models have better extrapolation ability to calculate all operation conditions of CO2 systems at supermarket. Existing theoretical modeling approaches often lack validation against the limited public-access data, which reduces model reliability for further applications, and adopt oversimplified inference methods for unmeasured variables, which increases the risks of breaking thermodynamic laws and lowering model accuracy. This study therefore develops a steady-state theoretical model for CO2 booster refrigeration systems validated against field measurements from three UK supermarkets. The available measurements are utilized to the best level to ensure model accuracy and physical interpretability. Proposed methods to infer missing variables in CO2 systems include condenser outlet temperature, evaporating temperature, compressor isentropic efficiency and compressor mass flow rate. Results show that proposed inference methods enhance the abilities of the proposed modelling approach to ensure data integrity, avoid breaking thermodynamic laws, and improve model accuracy by reflecting real-time actual values of unmeasured variables rather than rough assumptions. The proposed modeling approach provides satisfactory accuracy validated using high-resolution measurements across the whole year from three real supermarkets.

Batch-sizing and machinability data systems for milling operations: An optimal sustainable cost of quality approach

Nowadays, manufacturers make every effort to achieve a higher quality of their products at an attractive cost. With all the introduced legislation and incentives in the developed world to address global warming, machining shops in the West also strive to cut greenhouse emissions. This article offers an optimal approach to the micro Computer-Aided Process Planning (CAPP) problem to optimize the internal quality cost and buffering effect while keeping the environmental impact low. To optimize the machining parameters, the mathematical model is developed for different milling operations, face, side, and peripheral. cutting speed, feed rate, axial depth of cut, radial depth of cut, nose radius, and batch sizing while maximizing profit and meeting customer demand. A Mixed-Integer Nonlinear Programming (MINLP) model is formulated and solved using Classical Constrained Nonlinear Optimization (CCNO) and Genetic Algorithms (GAs). Surface roughness, used as a metric to evaluate the desired quality level of a finished machined part type, is modeled as a Gaussian random variable to model the surface roughness of the machined part utilizing a cumulative normal distribution. The ratio of rework and scrap is calculated in terms of the surface roughness of the machined part shifting away from the target and exceeding upper and lower specification limits. The internal failure cost model, addressing both scrap and rework, is developed based on Taguchi’s quadratic loss function. CCNO is employed to validate the results obtained by GAs, relaxing the lot-sizing integrality constraint and, thus, the convexity of the produced relaxed model. An iterative method employing a developed multi-regression model is used to solve for the expended power consumption (an inherent highly nonlinear environmental criterion of the developed model) within both GAs and CCNO. This study reveals that the machining parameters substantially impact the cost components of the objective function as well as the scrap and rework quantities. A stringent quality cost target can force the model to optimize the feed rate and nose radius to minimize the internal failure quality cost while improving the environmental impact, including direct and indirect power consumption and CO2 emissions considerations.

Beyond the Average: emissions from electricity and the implications of decarbonization policies in Guangdong

Various policy interventions have been proposed to decarbonize the Chinese economy through the electricity sector. This study is the first to use generation-by-plant data to analyze the emissions from the electricity sector in a Chinese region and evaluate the environmental impacts of various policy interventions. Using regression techniques, the average emission factor, marginal emission factor, and marginal displacement factor, are estimated for different pollutants of Guangdong, the most affluent and populous province in China. Results reveal a decline in average emission factors over the sample period of 2017-2021, owing to the expansion of renewable energy. This study also finds a less pronounced disparity between marginal emission factors and average emission factors compared with that in developed countries, probably due to the prevalence of coal-burning plants and lower renewable energy penetration in Guangdong. Using the estimated emission factors, this study also examines the environmental effect of time-of-use tariffs, indirect emissions of electric vehicles, and carbon displacement effect of wind energy. The conclusions reveals that the time-of-use tariffs moderately reduced CO2 emissions, and the extensive adoption of electric vehicles and wind energy substantially reduces carbon emissions, indicating that decarbonizing the economy needs the coordination of various policies.

Operational greenhouse gas emissions of various energy carriers for building heating

The decarbonisation of the building heating sector requires a shift from decentralised fossil fuel heating appliances to systems converting energy carriers with low greenhouse gas (GHG) emissions. However, for certain energy carriers, a considerable portion of GHG emissions arises upstream during production, processing and transportation, rather than during energy conversion. Accurately quantifying these indirect GHG emissions typically requires life cycle assessments, which are often resource-intensive and impractical during the early stages of energy system design. This study introduces operational GHG emissions as a pragmatic metric for the preliminary assessment of energy carrier environmental impact in building heating applications. These operational GHG emissions include both direct CO2 emissions and indirect CO2, CH4 and N2O emissions. Based on a comprehensive literature analysis, average estimates are proposed for the operational GHG emissions of various energy carriers within a European context, including natural gas, oil, coal and wood, as well as the average European and Belgian electricity grid, and hydrogen from various production methods. The findings underscore the significant contribution of indirect GHG emissions, as the selection of the energy carrier with the lowest environmental impact hinges on whether direct emissions alone or the broader operational GHG emissions are considered. By integrating operational GHG emissions into the early design stages of energy systems, stakeholders can make more informed decisions about which energy systems warrant further investigation, thereby facilitating more sustainable energy system development from the outset.

China's provincial power decarbonization transition in a carbon neutral vision

The power sector plays a crucial role in achieving the China's carbon neutrality target. However, there remain knowledge gaps regarding provincial emission reduction efforts toward carbon neutrality and the impact of carbon flows embodied in electricity transmissions. This study built a modeling framework, linking a bottom-up multi-regional power system model and Quasi-Input-Output approach, to investigate the provincial-level power system transition. Multiple combined scenarios based on shared socio-economic developments and different carbon mitigation policies were designed for a comprehensive assessment. Results indicates that the transition of the power system by 2060, under various scenarios, necessitates 7–7.8 TW of wind and solar photovoltaic power, 4810–6309 TWh of electricity transmissions, and 140–262 GW of coal power retrofits. Notably, carbon emission flows will accumulatively reach 12.7–18.7 Gt from 2020 to 2060. Inner Mongolia will bear a cumulative of more than 5 Gt of carbon flows from North China. When considering the indirect emissions, load centers such as Shandong will have higher peak emissions, and Shandong will replace Inner Mongolia as the largest emitter province. In addition, provincial emission factors under the influence of complex electricity transmissions and carbon flows are estimated.