Total Carbon Emissions Research Articles

Understanding the Social Determinants of Household Carbon Emissions for Carbon Mitigation Policies: The Case of Mersin, Turkey

Households are the main consumer-side source of carbon emissions. In Europe, consumer-based CO2 consumption per capita fell from 10.8 tons to 7.8 tons between 1990 and 2022, but in Turkey, the same data showed a rise from 4 tons to 5 tons. Strategies to reduce carbon emissions have recently shifted their focus from the production side to the consumption side. However, because different social segments have varying levels of price sensitivity and differing levels of necessity regarding consuming different items, a simple tax policy only targeting the consumption side is doomed to fail. This has prompted a discussion of the factors influencing carbon emissions on the consumption side and how those factors affect the amount of emissions. This study aims to identify the social determinants affecting household carbon emission levels and to demonstrate that such differences play an important role in effective and efficient carbon emission reduction strategies. In this case study, an appropriate testing method was used to test whether there are significant differences in dependent variables (carbon emissions) between categories of independent variables (the social determinants of households). As our literature review demonstrates, the social determinants of households and the local context were found to have an impact on carbon emissions in the case study. Nevertheless, we found that the degree of association lessens when the relationship between the dependent variables and the independent variables is re-evaluated while controlling for income level. Consequently, it may be concluded that the primary element influencing carbon emissions is income. In our field study, on the other hand, poverty stood out as another important factor affecting the level of carbon emissions. Poverty affects total household carbon emissions in two different ways, causing both carbon-intensive consumer goods and household appliances with low energy efficiency to be preferred because they are cheap to purchase. Therefore, the fight against poverty should be recognized as an important component of carbon reduction policies in Turkey, and the issue of environmental justice should not be ignored, because we know that 30% of the population was living in poverty (compared to the other 70% receiving the national median income) in 2022.

Spatiotemporal evolution of carbon emissions and influencing factors in county-level based on nighttime lighting data: a case study in Huaihai economic zone core city

ABSTRACT Driven by China’s carbon peaking and carbon neutrality goals, this study constructs a carbon emission inversion model for 57 county-level in the core city cluster of the Huaihai Economic Zone. It analyzes the spatial-temporal characteristics of carbon emissions in these counties between 2001 and 2021. It also explores the impacts of different socio-economic factors on carbon emissions by adopting geographically and temporally weighted regression methods. The results showed that: (1) From 2001 to 2021, the total carbon emissions of counties increased from 63.42 Mt to 279.89 Mt, and the distribution pattern of the region is “high in the middle and low in the east and west.” (2) Carbon emissions have significant positive spatial correlations, with the global Moran’s I index showing a wave-like downward trend from 0.233 to 0.0954, indicating that the spatial concentration of carbon emissions in different counties is gradually decreasing, and the differences show a trend of narrowing. (3) Significant spatial and temporal heterogeneity is among the influencing factors. It is mainly manifested in population size and industrial structure, while economic scale and technological progress are the dominant factors in carbon emissions. The research results will inform county-level low-carbon development.

Response of Low Carbon Level to Transportation Efficiency in Megacities: A Case Study of Beijing, China

Global warming caused by massive carbon dioxide emissions can lead to a chain of ecological disasters. As one of the main sources of carbon emissions, transportation is of great significance, and the evaluation of its connections with carbon emissions is necessary to achieve “carbon neutrality”. Taking Beijing as an example, this study evaluated traffic efficiency (TE) by utilizing principal component analysis and fuzzy comprehensive evaluation. Using the Tapio decoupling model and coupling coordination degree model, the corresponding relationship between urban low carbon level (LCL) and TE was explored. The results showed the following: (1) The total carbon emission (CE) level exhibited fluctuating variation from increasing to decreasing. The carbon emission intensity (CEI) continued to slow down, and the rapid growth of population density played a key role in low-carbon development. (2) The traffic operations continually showed a positive trend in development. TE increased from a step-like to a slow shape, until it declined in 2020 due to the pandemic. (3) TE and LCL both developed from low coordination to an extreme level of coordination. Per capita carbon emission (CEP) and TE presented an inverted U-shaped curve; meanwhile, with increases in TE, the decline in CEI slowed. In addition, the weak decoupling of TE changed to become strong, due to CE and CEP, and maintained a strong decoupling state from CEI. (4) There is a necessity for the rational planning of land use for transportation infrastructure, the encouragement of a combination of public and private transportation, and the strengthening of the maintenance of the relative infrastructure and the management of traffic behaviors to attain a win–win situation. The results provide a reference for optimizing the traffic structure to achieve “carbon neutrality”.

Comparison on Environmental Benefits of Municipal Solid Waste Management in Suzhou Before and After Classification

In order to systematically understand the urban environmental benefit improvement of municipal solid waste （MSW） classification, based on the disposal data of MSW before and after the MSW classification in Suzhou from 2017 to 2021, the environmental impact potential （EIP） of the MSW collection-transportation-disposal process was calculated, and the environmental benefits of the MSW integrated management in Suzhou to 2035 were predicted. After the MSW classification in Suzhou at the end of 2019, the EIP （in terms of PET2000, the same below） of the per unit weight of MSW was reduced by 18.38% from 2.34×10-13 t-1 in 2017 to 1.91×10-13 t-1 in 2021. The environmental benefits of the MSW integrated management could be improved by classification. Based on the Suzhou MSW removal and transportation situation in 2021, different classification and disposal scenarios were established to calculate. It was found that after the classification effect showed gradient improvement, and the disposal capacity matched accordingly, the environmental benefits of MSW were further improved. Under the planning disposal capacity scenario of "zero waste to landfill", the EIP and the total carbon emissions of per unit weight of MSW should be reduced by 23.96% and 30.73%, respectively, compared with the actual situation in 2021. Based on the linear model of population and economic development level of Suzhou, it is expected that the annual production of MSW in Suzhou will be increased to 6.965 million tons in 2035. Under the background of continuous improvement of MSW classification and continuous optimization of city appearance and environment in Suzhou, based on the status quo of terminal disposal capacity in Suzhou, the EIP of per unit weight of MSW after improving the efficiency of classification by 2035 was predicted to be 1.54×10-13 t-1, the total EIP would be 1.05×10-6, and the total carbon emissions would increase to 3.80 million tons. Under the ideal scenario of expanding the scale of waste disposal, "zero landfill" of raw MSW, and full resource utilization of food waste, the EIP of per unit weight of MSW in 2035 was predicted to be 1.28×10-13 t-1, and the total EIP and the total carbon emissions would be 8.69×10-7 and 3.23 million tons, respectively, which was approximately 5.65% and 1.23% less than the actual scenario in 2021, respectively. The EIP and carbon emissions of MSW integrated management could be controlled better by the coordinated promotion of classified collection and transportation and quality disposal.

A Bottom-Up Carbon Emission Assessment Model for Carbon Emission Control at the Level of Rural Detailed Planning

Incorporating green and low-carbon building targets into the rural planning management system requires scientific and quantitative methods for assessing carbon emissions from rural land use. At present, the research in this field mainly focuses on urban areas, but there are fewer theoretical and practical studies on the assessment of carbon emissions from rural land use. This paper proposes a new carbon emission assessment method based on land use modes, and the model can not only assess carbon emissions but also directly reflect the carbon emission intensity of different land use spaces in rural areas and guide the carbon emission control of construction land in village planning. In this paper, we take suburban rural areas in Hunan Province as an example and establish a land use carbon emission assessment model with 13 indicators in five dimensions: total carbon emission, carbon emission efficiency, carbon emission intensity per unit of land use, carbon emission structure of land use, and carbon emission intensity of buildings, based on the bottom-up field research data. We practised our method in Jinlong Town, Hunan Province, and gave examples of model applications. It was found that the carbon emission calculation method based on the carbon emission intensity of land use can be used to calculate the current status of carbon emissions in different villages in Jinlong Town. At the same time, the carbon emission assessment results can be used as a scientific basis for carbon emission control in detailed village planning in Jinlong Town. In general, the carbon emission assessment model can complete the assessment of land carbon emissions in rural areas and provide a low-carbon land use management tool for the government.

Quantifying heterogeneous impacts of 2D/3D built environment on carbon emissions across urban functional zones: A case study in Beijing, China

Rapid urbanization has led to a significant increase in carbon emissions (CES), adversely affecting the urban ecological environment. As fundamental units in urban planning and management, urban functional zones (UFZs) exhibit similar energy consumption patterns. Previous studies on urban CES have often focused on large-scale regions, lacking research on CES differentials at the scale of UFZs. This study, using Beijing as a case study, employed multi-source geospatial data to estimate CES and analyze influencing factors at the UFZ scale. First, a multi-scale semantic segmentation network was constructed to produce UFZ map using high-resolution remote sensing images and OpenStreetMap road data. Second, a top-down approach was employed, incorporating nighttime light data to calculate the UFZ-scale CES to analyze differences in CES among various UFZs. Finally, factors influencing urban CES, including socioeconomic factors and two-dimensional (2D) and three-dimensional (3D) urban built environment, were analyzed using Pearson analysis and GeoDetector analysis. Results indicate that: 1) Among the 2813 UFZs in Beijing, the majority belong to residential zones (34.23 %), followed by institutional zones (20.33 %); 2) The total CES in study area amount to 4.07 × 107 tons. Commercial zones contribute significantly higher CES than other UFZs, followed by residential zones. 3) For different types of UFZs, the impact of various factors on CES differs significantly. Population density, the highest building height, base area, and average building volume are the main correlation factors. Spatial analysis of CES at the UFZ scale contributes to the management of low-carbon cities, energy allocation, and optimization of urban planning implementation.

Optimization research on energy consumption and carbon emissions in hydrogen-blended natural gas pipeline networks considering compressor performance - A case study of the west-east gas pipeline (line 1)

The blending of hydrogen into natural gas can utilize existing natural gas pipeline infrastructure to achieve long-distance, large-scale, and cost-effective hydrogen transportation. However, the introduction of hydrogen poses a series of new technical and safety challenges to the operation of natural gas pipelines. Addressing these issues, this paper focuses on minimizing compressor station energy consumption and carbon emissions as objective functions, conducting a comprehensive analysis of station operation modes. Incorporating the characteristics of the model, the soft frost search strategy, the hard frost penetration mechanism, and the positive greedy selection mechanism are introduced to propose the IRIME algorithm. Comparisons are made with well-performing optimization algorithms using classical test functions to evaluate algorithm performance. To further validate the algorithm's accuracy, the West-East Gas Pipeline (Line 1) is considered, comparing the convergence speed and precision of the IRIME algorithm, leading to its selection for solving the model. Furthermore, consider analyzing the impact of different hydrogen blending ratios on the performance curves and operating points of compressors. Results indicate that compared to conditions without hydrogen blending, the compressor outlet temperature and pressure drop increase for hydrogen blending ratios of 5%, 10%, 15%, and 20%; as the hydrogen blending ratio increases, the efficiency of fuel-driven compressors, efficiency of electrically driven compressors, and average efficiency of compressor units decrease; with an increase in hydrogen blending ratio, carbon emissions from fuel-driven compressors and electric-driven compressors both decrease. In conclusion, with an increasing hydrogen blending ratio, total energy consumption increases by 3.14%, 5.69%, 8.68%, and 10.90%, while total carbon emissions decrease by 2.99%, 5.36%, 8.32%, and 10.68%. These findings provide valuable insights for operational guidance in the field.

Can place-based policy reduce carbon emissions? Evidence from industrial transformation and upgrading exemplary zone in China

The effect of the place-based policies on sustainable development has received substantial attention in economic research. In China, the industrial transformation and upgrading exemplary zone policy is a prominent example of such policies, as it targets old industrial and resource-based cities. The paper provides an early assessment of the policy’s capability to reduce carbon emissions. Specifically, we use data from old industrial and resource-based cities for the period of 2012–2019 and apply the difference-in-differences method to examine the policy’s influence on total carbon emissions and intensity. The results show that the policy can effectively reduce carbon emissions through reducing energy consumption, promoting urban green innovation and tertiary industry agglomeration. Compared to resource-based cities, cities with a low level of economic development and central, western cities, this impact is more notable in old industrial cities, cities with a high level of economic development and eastern cities. Additional analysis reveals that the policy has beneficial spatial radiation impacts on the nearby cities as well. In the meanwhile, the strategy may have a synergy effect on reducing carbon emissions and pollution. The results of this study may have an impact on how nations implement place-based policies and reduce carbon emissions.

Towards a low-carbon and beautiful world: assessing the impact of digital technology on the common benefits of pollution reduction and carbon reduction.

When ecology thrives, civilization thrives, and when ecology declines, civilization declines. Based on panel data from 30 provinces in China from 2000 to 2021, this study used marginal abatement costs to estimate the co-benefits of pollution reduction and carbon reduction. Two-way fixed effect and two-stage intermediary effect models were used to evaluate the impact of digital technology on co-benefits and its indirect channels. The results indicated that China's total carbon emissions maintained a steady growth trend, while air pollution showed a fluctuating declining trend. Reaching peak carbon neutrality calls for more innovative solutions. Under joint emission reduction efforts, the study revealed marginal abatement cost savings of 535.8 million yuan/million tons and 6216.5 million yuan/μg/m3 for carbon reduction and pollution reduction, respectively. Most importantly, the study confirmed that joint emission reduction programs can reduce environmental governance costs more than individual emission reductions can, and the co-benefits increased from 37.983 to 44.757. The co-benefits generally showed a trend of fluctuation and increases and had the characteristics of phased transformation. Intragroup differences and cross-overlapping between regions made regional differences in co-benefits obvious. The subversive, permeable, and integrated features of digital technology have resulted in the all-around transformation of the economy and society, and the new technology-economy paradigm has significantly improved co-benefits. The conclusion remains valid after robustness testing and controlling for endogeneity problems. The results of the mechanism analysis suggest that digital technology can indirectly improve synergies through the intermediary channels of fostering green technology innovation, reducing energy consumption intensity and improving the energy structure.

Promoting Decarbonization in China: Revealing the Impact of Various Energy Policies on the Power Sector Based on a Coupled Model

The carbon emissions of the power industry account for over 50% of China’s total carbon emissions, so achieving carbon peak and carbon neutrality in the power sector is crucial. This study aims to simulate the impacts of three energy policies—carbon constraints, the development of a high proportion of renewable energy, and carbon trading—on China’s energy transition, economic development, and the power sector’s energy mix. Through the construction of a dynamic computable general equilibrium (CGE) model for China and its integration with the SWITCH-China electricity model, the impact of diverse energy policies on China’s energy transition, economic progress, and the power mix within the electricity industry has been simulated. The integration of the SWITCH-China model can address the limitations of the CGE model in providing a detailed understanding of the specific intricacies of the electricity sector. The results indicate that increasing the stringency of carbon restrictions compels a reduction in fossil energy use, controlling the output of coal-fired power units, and thereby reducing carbon emissions. The development of a high proportion of renewable energy enhances the cleanliness of the power sector’s generation structure, further promoting the national energy transition. Implementing a carbon trading policy, where the entire industry shares the burden of carbon reduction costs, can effectively mitigate the economic losses of the power sector. Finally, the policies to further enhance the implementation of carbon trading policies, strengthen effective governmental regulation, and escalate the deployment of renewable energy sources are recommended.

Analyzing energy utilization influence on tourism and low-carbon development: Insights from Xianju National Park in China

National parks are rare natural resources that provide refuges for wildlife, harmonious ecology, and leisure activities. These protected areas, which include a variety of ecosystems, habitats for wildlife, and geological wonders, have been set aside to preserve and highlight the beauty of the natural world. Under the goals of carbon neutrality of all countries in the world, it is urgently need to pay attention to the relationship between climate change and protected natural resources. This study uses the Xianju pilot national park as an example to identify key activities that increase carbon absorptions and reduce carbon emissions, calculate the carbon sink of national park construction, and discuss whether tourism industry can achieve low carbon or even negative emissions based on the analysis of low-carbon measures of national parks. Using the Mento-Carlo method, we find that the total carbon sink in Xianju National Park is around 70832–97930 tons CO2, which accounts for about 10 % of Xianju County's total carbon emissions. This illustrates that the development of tourism has indeed brought benefits to the low carbon development of Xianju National Park. From the perspective of stakeholders, this paper also summarizes the stakeholders, relevant actions and policy tools for Xianju National Park to carry out low-carbon tourism. Finally, compared with the development experience of national parks in France and the United States, this paper gives policy suggestions on low-carbon development of Xianju National Park, and proposes to mobilize stakeholders to participate in low-carbon tourism and low-carbon governance.

Carbon Footprint Reduction Associated With Multidisciplinary Pediatric Airway Clinics: A Program Evaluation Study.

Health care is a significant contributor to the climate crisis. Multidisciplinary clinics (MDC) may reduce carbon emissions by combining multiple appointments into one. This is the first program evaluation study to quantify the carbon footprint associated with multidisciplinary pediatric airway clinics. Retrospective. Children's Hospital at London Health Sciences Center, London, Canada. Pediatric airway MDC allows patients to see otolaryngology and respirology in one appointment. The carbon and financial savings (Canadian Dollars) of all patients attending the MDC from January 1, 2018 to December 31, 2022 were calculated. Patient postal codes and institutional parking rates were inputted into the CASCADES carbon accounting tool. Total distance was divided into unsustainable (vehicles) and sustainable (transit, walking, cycling) transportation to calculate carbon emissions. Travel costs included cost/kilometer for vehicles (maintenance, license/registration, insurance, fuel) and costs/ride for transit. A total of 560 MDC appointments for 300 patients saved 77,785 km. Total carbon emissions saved from travel averted was 16.21 tonnes. The total carbon emissions saved, minus public transit, was 15.60 tonnes. Using the Natural Resources Canada Greenhouse Gas Equivalencies Calculator, 16.21 tonnes are approximately equivalent to 5 passenger vehicles, 6906 L of gasoline, 3.8 homes' energy, and 10.8 homes' electricity use for one year, 36.6 barrels of oil consumed, and 675 propane cylinders. Travel costs of $28,891.83 (no parking), $30,519.40 ($4 minimum parking fee), or $33,774.55 ($12 maximum parking fee) were saved. MDC effectively reduced carbon emissions and offered patients financial savings. Similar models can be adapted across institutions to help mitigate climate change.

Roofing Highways With Solar Panels Substantially Reduces Carbon Emissions and Traffic Losses

AbstractPhotovoltaic (PV) installations are a leading technology for generating green electricity and reducing carbon emissions. Roofing highways with solar panels offers a new opportunity for PV development, but its potential of global deployment and associated socio‐economic impacts have not been investigated. Here, we combine solar PV output modeling with the global highway distribution and levelized cost of electricity to estimate the potential and economic feasibility of deploying highway PV systems worldwide. We also quantify its co‐benefits of reducing CO2 equivalent emissions and traffic losses (road traffic deaths and socio‐economic burdens). Our analysis reveals a potential for generating 17.58 PWh yr−1 of electricity, of which nearly 56% can be realized at a cost below US$100 MWh−1. Achieving the full highway PV potential could offset 28.78% (28.21%–29.1%) of the global total carbon emissions in 2018, prevent approximately 0.15 million road traffic deaths, and reduce US$0.43 ± 0.16 trillion socio‐economic burdens per year. Highway PV projects could bring a net return of about US$14.42 ± 4.04 trillion over a 25‐year lifetime. To exploit the full potential of highway PV, countries with various income levels must strengthen cooperation and balance the multiple socio‐economic co‐benefits.

Study on the Optimal Configuration of Battery Energy Storage System in Distribution Networks Considering Carbon Capture Units

Background: The implementation of Battery Energy Storage Systems (BESSs) and carbon capture units can effectively reduce the total carbon emissions of distribution networks. However, their widespread adoption has been hindered by the high investment costs associated with the BESSs and power generation costs of carbon capture units. Objective: The objective of this paper is to optimize the location and sizing of BESSs in distribution networks that comprise renewable power plants and coal-fired power units with carbon capture systems. The optimization process aims to minimize the grid’s impact from the configuration while maximizing economic cost savings and the benefits of reducing carbon emissions. Methods: A bi-layer optimization model is proposed to determine the configuration of BESSs. The upper layer of the model optimizes the size and operation strategy of the BESSs to minimize the configuration and power generation costs, using YALMIP and CPLEX optimization tools. Carbon emission reduction benefits are considered through deep peak-shaving and carbon tax. The lower layer of the model aims to optimizes the placement of the BESSs to minimize voltage fluctuation and network loss in the power grid. To achieve this, we improved the efficiency of the Nondominated Sorting Genetic Algorithm II (NSGA-II) to update the BESS’s placement. Results: The IEEE33-bus and IEEE118-bus systems were utilized for simulation and comparison in various scenarios. The findings demonstrate that the proposed configuration method can decrease the cost of investment and power generation. Furthermore, it reduces the degree of node voltage fluctuation and network loss in the distribution network. Conclusion: The study reveals that determining the optimal scale of BESSs can mitigate high energy consumption in carbon capture systems and improve the overall performance of power systems that integrate carbon capture technology and renewable power plants.

Investigation into Spatial and Temporal Differences in Carbon Emissions and Driving Factors in the Pearl River Delta: The Perspective of Urbanization

Urbanization is a significant indicator of city progress, and as urbanization advances, carbon emissions exhibit an increasing trend that must not be disregarded. Therefore, it is imperative to thoroughly examine the spatial and temporal variations as well as the factors influencing carbon emissions during the urbanization process. In this paper, based on the 2009–2019 PRD region, carbon emissions are measured from energy consumption, industrial production process, solid waste, and wastewater according to the IPCC coefficients, and spatial and spatial differences in carbon emissions are combined with spatial analysis and the drivers analyzed using the gray correlation scale. The results show that: (1) The total carbon emissions in the PRD region have been increasing over the study period, and the distribution of total carbon emissions shows a pattern of “strong in the east and weak in the west”, with energy consumption accounting for the highest proportion of carbon emissions. (2) The global Moran Index of carbon emissions in the PRD has been decreasing, with low and low clustering concentrated in Shaoguan and Zhaoqing, high and high clustering concentrated in Dongguan and Shenzhen, and low and high clustering concentrated in Shenzhen and Guangzhou, with cold spots mainly concentrated in Zhaoqing and hot spots mainly distributed in Guangzhou, Shenzhen, and Dongguan. (3) The degree of economic growth has a substantial influence on carbon emissions in the PRD cities, and the influence of technical advancement has intensified. Guangzhou City is propelled by low-carbon regulations that have a more equitable influence on all elements. Zhuhai City has a more significant influence on energy intensity, while Foshan City has a more noticeable decrease in the effect of foreign investment. To address the issue of carbon emissions, the government should establish appropriate rules to regulate carbon emissions in areas with high emissions, foster collaborative efforts across cities, and encourage the growth of environmentally friendly enterprises.

CO2 emission characteristics modeling and low-carbon scheduling of thermal power units under peak shaving conditions

To accommodate the high penetration of renewable power, the operational flexibility of thermal power units is highly required by the power system, so thermal power units frequently operate under peak shaving conditions. The CO2 emission characteristics of a thermal power unit are significantly influenced by the load factor, and also by the installed capacity and design parameters of the thermal power unit. Therefore, detailed CO2 emission characteristics of thermal power units should be modeled and considered in the low-carbon scheduling of the power system. In this study, thermal power units are classified by live steam parameters, installed capacities, reheat stages, cooling modes, and operation modes, and the models of detailed CO2 emission characteristics are developed and validated. The turbine isentropic efficiency, boiler thermal efficiency, and auxiliary power consumption are comprehensively considered in the CO2 emission model. A new indicator is defined to evaluate the reduction of carbon emissions in a power system when a TPU accommodates per unit of renewable power generation, and an optimization method for low-carbon scheduling based on it is proposed. Finally, a reference case study is conducted. Results show that the total carbon emissions for a day of the proposed low-carbon scheduling method are 0.06 %−0.20 % less than the efficiency priority method, and 1.53 %−2.36 % less than the capacity weighting method.

Black monster or green giant? Revaluating the role of Chinese multinational enterprises in Belt and Road countries on carbon emissions

The Belt and Road (B&R) initiative, which brings emissions from China to the B&R countries, has gained considerable attention. By building a multiregional input-output model that distinguishes firm ownership, we measured the carbon emissions produced by Chinese multinational enterprises (MNEs) in B&R countries in reality and set two extreme counterfactual scenarios to evaluate the emission impacts of Chinese MNEs' overseas production activities on B&R countries: In Scenario 1, Chinese MNEs' production activities in B&R countries were replaced by local domestic producers; and in Scenario 2, the same amounts of outputs produced by Chinese MNEs in B&R countries were imported from China. We find that compared to the reality, in Scenario 1, a total carbon emission increase of 29.06 million tons (Mt) was observed in B&R countries, while in Scenario 2, a cumulative emission increase of 165.00 Mt worldwide, from the year 2005–2016, was observed indicating that the foreign direct investment related production activities of Chinese MNEs create a ‘green’ benefit for B&R countries and the world. Case studies show the detailed emissions mitigation effects of Chinese MNEs. This study sheds light on a possible way to facilitate the development of economies' emission control with the involvement of MNEs with higher energy efficiency and to simultaneously realise global emission mitigation goals.

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.

Blessing or curse? The role of digital technology innovation in carbon emission efficiency

Digital technology advancement provides a significant impetus to achieve China's "dual-carbon" goals, yet it also gives rise to a series of challenges. Therefore, studying the relationship between digital technology innovation and carbon emission efficiency is of paramount importance. This study theoretically analyzes and empirically tests the influence of digital technology innovation (DTI) on total factor carbon emission efficiency (TFCE) using panel data from 268 Chinese cities between 2006 and 2021. The results indicate that: (1) DTI exhibits a "U-shaped" pattern on urban TFCE, with a decrease followed by an increase. (2) Conventional technological innovation (TI) also displays a "U-shaped" relationship with TFCE, with the turning point occurring earlier than that of DTI. DTI surpasses TI in bringing about later-stage improvements in carbon emission efficiency. (3) Mechanism tests reveal that digital technology innovation indirectly affects TFCE through energy effects, technological effects, structural effects, and regulatory effects. (4) The impact of DTI on urban TFCE varies significantly due to differences in geographical location and resource endowments. (5) The development of urban polycentricity advances the turning point at which DTI enhances TFCE while amplifying both the initial "pro-carbon" effect and the subsequent "carbon reduction" effect of DTI. (6) DTI has a spatial spillover effect on urban TFCE. This study provides empirical evidence and policy recommendations for policymakers to advance the digitalization, greening, and decarbonization transformation of cities.

Carbon footprint of household meat consumption in China: A life-cycle-based perspective

The food industry accounts for 25% of global carbon emissions, of which animal food accounts for 57%. Therefore, the reduction of carbon emissions from meat products consumption is one of the important issues of global climate governance. This study calculates and compares the carbon footprints of major meat products in China at various stages of production and consumption and the trends of their development based on life cycle assessment and questionnaires, which will help to understand the emission characteristics and reduction potential of the food sector in China. The results show that the main stages of the life cycle and the size of the total carbon footprint of the meat category for the same unit standard exhibit the following order: beef > mutton > pork > poultry (chicken and duck) > seafood (fish and shrimp); the farming factor has a greater impact on carbon emissions, followed by transportation and a smaller impact at the meal-making stage; from 2010 to 2021, China's total meat products consumption and carbon emissions continue to increase, but the structure of meat consumption is gradually diversified and balanced, and the trend of carbon emissions shows a slowdown in growth with structural changes. Finally, based on the results of the study, this paper proposes countermeasures for meat production and consumption.