Reduction Path Research Articles

Carbon Peak Prediction and Carbon Reduction Path Simulation under the Dual Carbon Target: A Case Study of Jiangsu Province

To build a low-carbon and harmonious society that supports sustainable development, China has set forth the significant strategic goal of achieving carbon peaking by 2030 and carbon neutrality by 2060, commonly referred to as the dual carbon target. The key to achieving this target lies in scientifically and accurately predicting the timeline for carbon peaking, followed by developing effective carbon reduction paths. Using Jiangsu Province as an example, this study utilizes energy and economic data from 2010 to 2020 and introduces a penalized Lasso-Kaya model to forecast carbon emissions. The applicability of deep learning models, such as LSTM, in carbon peak prediction is also validated. Based on this, three levels of carbon reduction targets were established: baseline, steady progress, and ambitious. Through parameter simulation, the study derives an optimal carbon reduction path for Jiangsu Province through 2060. Consequently, this paper proposes a quantitative assurance mechanism for carbon reduction that maximizes economic growth, providing a valuable reference for future policy intervention.

Pathways to Carbon Neutrality in Civil Engineering

Abstract. With the development of the global economy and trade exchanges worldwide, urban infrastructure and industrial development have become part of the competition among countries. However, the construction industry and the production of chemical materials emit a large amount of carbon dioxide, leading to the continuous deterioration of the environment, so it is necessary to effectively reduce emissions. As a synonym for global emission reduction, carbon neutrality plays an important role in different industries, especially in civil engineering. In this paper, we start with building materials and green construction to explore the realization of carbon neutrality at the source and center of carbon emission in civil engineering. Firstly, we introduce the low-carbon production technologies of cement and steel, including calcium recycling and membrane separation technology in the cement industry, high-temperature combustion technology and carbon capture technology in steel industry. Then, we take renewable concrete as an example to discuss the emission reduction path of green building materials. Finally, it outlines how to carry out green construction, introduces assembly carbon reduction technology and energy integration system, and demonstrates the possibility of this green construction program in the case of "T&A House".

Assessing the utility of low-emission pilot policies for facilitating pollution reduction and carbon mitigation: An empirical investigation using multi-temporal double difference analysis

Collaborative governance for pollution reduction and carbon mitigation can effectively resist the pressure brought about by ecological and environmental changes while reducing policy costs. To explore the “win-win” path of pollution reduction and carbon mitigation,” based on panel data from 286 cities in China from 2000 to 2021, this study regards the low-carbon city pilot policy (LCCP) as a quasi-natural experiment and explores its impact on urban carbon emissions and pm2.5 concentration. Multiple testing methods, including multi-temporal double difference, spatial autocorrelation, local cold and hot spot analysis, kernel density analysis, standard deviation ellipse, spatial Durbin model, and PSM-DID, were used to verify the credibility and scientificity of the research results. The results showed that (1) LCCP had a direct effect on reducing pollution and carbon emissions, reducing co2 emissions by 3% and pm2.5 by 2.9%, with a synergistic effect of 20.2%; (2) the synergistic effect of LCCP on pollution and carbon reduction was indirectly achieved through green finance, green technological innovation, and green transportation, with impacts of 3.6%, 5.5%, and 2.4% in eastern, central, and non-resource based cities, respectively; and (3) the spillover effect coefficient of LCCP on carbon emission reduction in surrounding cities was −0.040 and that on pm2.5 concentration was −1.232, which are significant at the 10% and 1% levels, respectively.

Influencing Factors and Emission Reduction Paths of Industrial Carbon Emissions Under Target of “Carbon Peaking”: Evidence from China

Influencing Factors and Emission Reduction Paths of Industrial Carbon Emissions Under Target of “Carbon Peaking”: Evidence from China

Nickel-Doped Facet-Selective Copper Nanowires for Activating CO-to-Ethanol Electrosynthesis.

Ethanol isa promising energy vector for closing the anthropogenic carbon cycle through reversible electrochemical redox. Currently, ethanol electrosynthesissuffers from low product selectivity due to the competitive advantage of ethylene in CO2/CO electroreduction. Here, a facet-selective metal-doping strategy is reported, tuning the reaction kinetics of CO reduction paths and thus enhancing the ethanol selectivity. The theoretical calculations reveal that nickel (Ni)doped Cu(100) surface facilitates water dissociation to form adsorbed hydrogen, which promotesselective electrochemical hydrogenation of a key C2 intermediate (*CHCOH) toward ethanol path over ethylene path. Experimentally, a solution-phase synthesis of a Ni-doped {100}-dominated Copper nanowires (Cu NWs) catalyst is reported, enabling an ethanol Faradaic efficiency of 56% and a selectivity ratio of ethanol to ethylene of 2.7, which are ≈4 and 15 times larger than those of undoped Cu NWs, respectively. The operando spectroscopic characterizationsconfirm that Ni-doping in Cu NWs can alter the interfacial water activity and thus regulate the C2 product selectivity. With further electrode engineering, a membrane electrode assembly electrolyzer using Ni-doped Cu NWs catalysts demonstrates an ethanol Faradaic efficiency over 50% at 300mA cm-2 with a full cell voltage of ≈2.7V and operates stably for over 300 h.

The Social Psychological Explanations for the Effects of Social Media Marketing and Traditional Media on Voting Intentions

ABSTRACT Politicians use social media to drive voting intentions. The authors draw on self-enhancement and uncertainty reduction elements of social identity theory to present a framework that merges media data and social media sentiment toward the candidate to predict voting intentions. The authors estimate econometric models to data collected during the Brazilian presidential elections. The results support the influence of posts’ sentiment toward the candidate, owned social media, earned social media, and the candidate’s number of followers. They unveil social psychological pathways in driving intentions: a self-enhancement, an uncertainty reduction path, and an interaction between candidate’s number of followers and traditional earned media.

A large-scale group decision-making framework based on two-dimensional picture fuzzy sets in the selection of optimal carbon emission reduction alternatives

This article proposes the concept of two-dimensional picture fuzzy sets (TDPFS). This new framework extends the original picture fuzzy sets (PFS) by incorporating a confidence level to evaluate expert opinions using probability. This innovation facilitates the stratification and dimensionality reduction of large-scale expert groups, while also offering a new perspective for examining group decision-making problems. This article determines the weights of each subgroup by considering the confidence level of expert evaluation, the cohesion of the subgroups, and the size of the subgroups. This approach simplifies the decision-making process by transforming the originally complex large-scale group decision-making problem into a traditional decision-making problem. Finally, the traditional consensus reaching process (CRP) ensures that experts meet specific consensus requirements in decision-making. To verify the feasibility and practicality of the framework in practical applications, we applied it to the selection of carbon emission reduction paths and alternatives in China’s iron and steel industry. This practice not only demonstrates the theoretical value of our research results but also highlights its potential in practical operations.

Carbon emissions reduction path of logistics industry in Hebei, China: based on internal factors

To explore the optimal carbon emissions reduction path for the logistics industry in Hebei Province, China, this paper considers internal factors such as logistics agglomeration, transportation structure, and technology innovation as regulatory measures. The system dynamics method is employed to simulate the effects of carbon emissions reduction for each factor. Then, based on examining the interactive relationships among these internal factors, the paper proposes the optimal carbon emissions reduction path for Hebei Province’s logistics industry under different sequences of implementing the three measures. The results indicate that logistics agglomeration, transportation structure, and technological innovation can contribute to varying degrees of carbon emissions reduction in logistics. By 2030, it is projected that logistics agglomeration will result in a reduction of 21,799 million tons of carbon emissions while transportation structure and technology innovation will lead to reductions of 23,459 million tons and 20,778 million tons respectively compared to the BAU scenario. Furthermore, intricate interactions exist among these three internal measures. The optimal path for reducing carbon emissions is TSI-AGD-LTI. Specifically, to optimize the transportation structure first, relieve the pressure of logistics carbon emissions aggravated by logistics agglomeration, promote the cross-regional transfer of logistics carbon emissions, and then improve the level of technology innovation to strengthen further the logistics carbon emissions reduction effect of transportation structure adjustment.

Synergistic impact of digital finance and urban agglomeration policy on carbon emission reduction

This study employs a sample of 283 Chinese cities in 2005−2021 to investigate how digital finance (DIF) promotes low-carbon development from an urban agglomeration (UA) perspective. The moderated mediation and multiperiod difference-in-differences models are utilized to explore DIF’s potential carbon emission reduction paths and the moderation mechanism of UA policies. This research yields some valuable and robust conclusions. First, DIF and UA policies promote carbon emission reduction with noticeable regional variations. Second, green technology innovation (GTI) and industrial structure upgrading (ISU) play a crucial negative mediating role in the impact of DIF on carbon intensity. Third, UA policies have further enhanced the carbon emission reduction capabilities of DIF, GTI, and ISU. Fourth, UA policies enhance their role when DIF positively fosters GTI but does not exhibit a moderating effect when DIF positively facilitates ISU.

Carbon emission scenario analysis of data centers in China under the carbon neutrality target

The low-carbon transformation of data centers is of great significance to achieve the goals of carbon peaking and carbon neutrality. This study compared and analyzed the overall situation of data centers in China. Based on China's CO2 emission and intensity targets in key years, the four variables of energy efficiency improvement rate, nonfossil energy consumption proportion, negative emission technology intensity, and waste energy utilization rate were introduced, and a net zero emission path model of data centers was established. Using scenario analysis to predict the total CO2 emissions and emission intensity from 2021 to 2060, three emission reduction path scenarios were obtained. Results showed that the energy consumption of data centers increased gradually, the carbon emissions first increased and then decreased, and the power usage effectiveness (PUE) of the data centers decreased gradually. The carbon peak time of the three scenarios is 2030, and the time for carbon neutrality is 2055, 2053, and 2051 in three scenarios. The data center industry should further improve the energy efficiency utilization rate, increase the proportion of nonfossil energy consumption, strengthen the technological innovation of carbon capture and storage, enhance the level of carbon sink, and optimize the utilization rate of waste energy.

Simulation of hydrogen transportation development path and carbon emission reduction path based on LEAP model - A case study of Beijing-Tianjin-Hebei Region

Hydrogen-fuelled vehicles have attracted significant attention around the world recent years as the main form of hydrogen transportation. Chinese government in September 2020 has introduced corresponding supporting policies. In particular, Beijing-Tianjin-Hebei urban agglomeration is the first batch of pilot cities. To research the development of hydrogen transportation and carbon emission reduction paths in Beijing-Tianjin-Hebei urban agglomeration, we construct LEAP-Beijing-Tianjin-Hebei Urban Agglomeration Hydrogen Transportation model, and simulate it based on the scenario analysis method. The results show that the total hydrogen demand reaches 7,975,860 tonnes in the year 2060. And the freight transportation sector is the largest hydrogen consumer in transportation. For carbon emission reduction, transportation sector under different scenarios could achieve net-zero emission in year 2060, with total emission reduction 431.19 million metric tonnes. We suggest that the promotion of hydrogen transportation should be carried out in stages. Early large-scale development of hydrogen-fuelled vehicles in sectors such as passenger cars and specialized vehicles is not significant in emission reduction, and it is more appropriate to start with medium and large-sized commercial vehicles. Gradually extend to the whole transportation sector after the technology of hydrogen-fuelled vehicles is mature and the supply capacity of clean hydrogen is improved.

GHG emission quantification and reduction pathway of subway shield tunnel engineering: a case study on Guangzhou Metro, China.

The shield method is a commonly used construction technique in subway tunnel engineering. However, studies on greenhouse gas (GHG) emissions specifically in subway shield tunnel engineering are lacking. This study aims to investigate the GHG emission characteristics and GHG reduction pathways during the construction period of subway shield tunnels. Firstly, based on the life cycle assessment (LCA) method, a greenhouse gas (GHG) emission quantification model for the shield tunnel construction period was developed using a multi-level decomposition of construction. Then, the GHG emission level and intensity during the construction period of a case project are quantified, and its emission characteristics and GHG reduction potential points are assessed. Finally, a comprehensive path for GHG reduction in subway shield tunnel engineering is proposed. The research results indicate that constructing 1 km of subway shield tunnel can generate 19,294.28 t CO2eq. Among these, material production element dominates the emissions with a percentage of 89.05%, while transportation and mechanical construction elements contribute 1.81% and 9.14%, respectively. From the structure perspective, the main structure contributes 88.73% of total emissions, while the ancillary structure contributes 11.27%. Among them, the working shaft and tunnel segments are the main sources of emissions for the main structure, accounting for 23.65% and 65.08%, respectively. Connecting channel and end reinforcement are the main emission sources of the ancillary structures, accounting for 43.63% and 31.30%, respectively. These findings provide a scientific foundation for the environmentally friendly transformation of urban railway development regarding pursuing "carbon peaking and carbon neutrality" strategic goals.

The mechanism and path of pollution reduction and carbon reduction affecting high quality economic development - taking the Yangtze River Delta urban agglomeration as an example

In the wake of the COVID19 pandemic, what is crucial for the continued promotion of ecological civilization construction and sustainable green development in China is to achieve the dynamic and balanced development between pollution reduction, carbon emission reduction, and economic growth. Therefore, the indexes of CO2 emissions, pollution reduction intensity, and high-quality economic development are quantified in this study by using the panel data related to 26 cities in the Yangtze River Delta urban agglomeration(YRDUA) from 2010 to 2020. Furthermore, kernel density analysis, GIS spatial analysis, and other methods are employed to demonstrate the spatial and temporal patterns of pollution reduction intensity, CO2 emission levels, and the characteristics of high-quality economic development in the YRDUA. In order to reveal the dynamic relationship between pollution reduction, carbon emission reduction, and high-quality economic development, a panel vector autoregressive model (PAVR) was established and the system generalized method of moments was used to estimate the model coefficients. Additionally, Granger causality tests, impulse response analysis, and variance decomposition were conducted. There is a fluctuating upward trend shown by the overall level of CO2 emissions in the YRDUA, with significant spatial nonuniformity exhibited in carbon emissions. Despite the self-promotion mechanism playing a more significant role in the high-quality economic development in the YRDUA and its three regions, the impact of pollutant and carbon emissions on high-quality economic development is quite limited. A significant promoting effect is exhibited in those high and moderately high-quality economic development regions, while nonlinear effects are observed in those high and moderately high-quality economic development regions. As for the interactive relationships, the three factors are correlated with each other to a more significant extent in those high and moderately high-quality economic development regions, which contributes to mutual influence and causal relationship. However, there is no effective interactive mechanism observed among the three factors in the whole area and low-quality economic development regions, with high-quality economic development playing a major role in environmental pollution and carbon emission reduction.

Research on carbon emission accounting and carbon emission reduction path of coal preparation plant

“Peak carbon dioxide emissions、Carbon neutrality” is the two stage goal of carbon emission reduction proposed by China. Carbon emission accounting is the basic premise for effectively carrying out various carbon emission reduction work and promoting the green transformation of the economy. The coal industry is one of the key objects of carbon emission reduction. Taking Zhenneng Coal Preparation Plant as the research object, this paper studies the carbon emission in the production process of the coal preparation plant and the selection of carbon emission factors, and constructs the carbon emission accounting model of the coal preparation plant. It is calculated that the carbon dioxide equivalent emission per 1 t of coal products produced by the coal preparation plant in 2018–2022 is 15.4391 kgCO2e. Based on the carbon emission reduction path at home and abroad, the development suggestions for carbon emission reduction in coal preparation plants are put forward. It is of great significance to establish a unified and standardized carbon emission accounting system for the coal industry, achieve the goal of “double carbon” and promote the comprehensive green and low-carbon transformation of economic and social development.

Instant rerouting of photosynthetic electron transport to O2 reduction after the plasma membrane excitation of Chara in the presence of methyl viologen

—Action potential (AP) of excitable plant cells is an important signaling event that can differentially alter physicochemical and physiological processes in various parts of the same cell. In giant cells of characean algae, the AP propagation has minor effect on photosynthetic electron transport in areas with high activity of plasmalemmal H+-pump but inhibits linear electron flow in regions featuring high passive H+/OH− conductance of the plasma membrane (PM). Uneven spatial distributions of local periplasmic and cytoplasmic pH facilitate the operation of distinct (CO2-dependent and O2-mediated) pathways of photoinduced electron flow, which presumably accounts for differential influence of AP on photosynthesis. The excitation of Chara australis cell in the presence of methyl viologen (MV), a redox mediator with the prooxidant action, provides a convenient model system to clarify the influence of voltage-dependent ion fluxes across PM on photosynthetic activity of chloroplasts. This study shows that permeation of MV to their target sites in chloroplasts is restricted by PM in resting cells, but MV easily passes through ionic channels opened during the PM depolarization. This gated permeation of MV gives rise to strong non-photochemical quenching, decrease in the effective quantum yield of linear electron flow, apparent O2 uptake, and, finally, the enhanced ROS production, as detected by the fluorescent probe dichlorofluorescein. Taken together, the results indicate that the AP generation in the presence of MV acts as trigger for instant redirection of photosynthetic linear electron flow from CO2-dependent route to the path of O2 reduction with the eventual formation of H2O2 as a dominant and most stable ROS form.

Regional Difference and Spatial Convergence of Land Use Carbon Emissions in Three Urban Agglomerations of Yangtze River Economic Belt

It is of great significance to explore the regional differences of land use carbon emission （LUCE） in the Yangtze River Economic Belt and the path of coordinated emission reduction for regional sustainable development. Based on the LUCE estimation method, this study scientifically calculated the LUCE of the three major urban agglomerations of the Yangtze River Economic Belt （Yangtze River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing urban agglomeration） from 2010 to 2020. Kernel density estimation and the spatial convergence model were used to study the dynamic evolution, regional differences, and convergence characteristics of LUCE. The results showed that： ① The carbon absorption of forest land, water areas, grassland, and unused land were relatively small in terms of carbon emissions from cultivated land and construction land. The carbon emission of construction land increased gradually, whereas the carbon absorption of four carbon sinks fluctuated little during the study period. ② The core density curves of different urban agglomerations showed different distribution patterns, extensibility, and polarization characteristics but generally tended to be balanced. ③ From 2010 to 2020, the LUCE of the Yangtze River Economic Belt as a whole showed the spatio-temporal characteristics of increasing first and then decreasing and high in the east and low in the west. The LUCE of the central cities of the three urban agglomerations were at the highest level steadily, and stable coupling mechanisms had not been established between the economic development level and the ecological environment. ④ The LUCE of the three urban agglomerations in the Yangtze River Economic Belt all had absolute β convergence and also had conditional β convergence under the model control variables such as economic development level, urbanization level, industrial structure, population density, and environmental regulation, etc., and the conditional convergence speed was greater than the absolute convergence speed in each region. The convergence speed of the Yangtze River Delta urban agglomeration was the slowest. The above conclusions provide support for the coordinated emission reduction path of the three urban agglomerations in the Yangtze River Economic Belt and are also conducive to actively and steadily promoting the realization of the goals of carbon peak and carbon neutralization.

Digital infrastructure construction and regional mineral resource dependence in China: Heterogeneous characteristics and transmission mechanisms from mining industry

The emergence of the digital economy has challenged many of the theories of traditional environmental resource economics. As an emerging production factor, data have a significant impact and substitutability with digital technology on fossil energy utilization, which also makes the impact of digital infrastructure construction (DIG) on the allocation of mineral resources easily underestimated. This study is based on China's DIG and explores its impact on regional mineral resource dependence (NRD) in 30 provinces of China. We find that, with a 1% increase in DIG, NRD declines by 7.6%, with a lag effect between the two. The analysis of heterogeneous characteristics revealed the heterogeneous effects and dissimilation roles of DIG's effect on NRD. In terms of heterogeneous effects, in regions with high levels of resource endowment and low digital-economy contributions, DIG's empowering effects were more obvious. In terms of dissimilation roles, the facility foundation has played a more prominent role than digital access. We also find that, enhancing resource allocation efficiency, innovation output efficiency, and energy utilization efficiency can mediate the effects of DIG on NRD. Our findings can offer policy insights for reducing NRD to promote high-quality DIG, achieving differentiated digital empowerment patterns, and building multichannel resource reduction paths. This work also has reference value for green transformation in other developing countries and resource-based industries under the 2030 sustainable development goals.

Study on the establishment of air pollutant and carbon emission inventory and collaborative emission reduction potential of China's coking industry from 2012 to 2022

Coking industry is usually regarded as a high pollution and high energy consumption industry. China is accelerating its efforts to reduce pollution and carbon emissions in the industrial sector, which has received little attention as the world's largest producer of coke. Therefore, in this study, the trend of air pollution and carbon emissions in China's coking industry and the path of coordinated emission reduction were studied. The results indicate that the average annual emissions of PM, SO2, NOx, VOCs, and CO2 in China's coking industry from 2012 to 2022 amount to 205.98, 69.47, 193.45, 599.80 Gg and 191.10 Tg, respectively. The main sources of PM, SO2, NOx, VOCs and CO2 in coking industry were coal preparation (51.5 %), charge and pushing (39.5 %), coke oven gas (99.8 %), byproduct recovery (47.0 %) and fuel combustion (87.5 %). The emissions from coking plants in central and southern Shanxi, eastern and southern Hebei, and central Shandong are the most concentrated. Ultra-low emission transformation and deep treatment of VOCs have greatly reduced pollutant emissions in key areas of air pollutant control, but the actual emission reduction effect of these measures has been weakened by the additional emissions caused by the increase of coke production in other non-key areas. The research on synergetic emission reduction path shows that there is a great synergistic benefit between air pollutants and CO2 emission reduction in coking industry. It is estimated that the APeq (air pollutants and carbon equivalent) of China's coking industry in 2025, 2028 and 2030 will decrease by 38.2 %, 63.5 % and 70.8 % respectively compared with 2022. With the continuous promotion of pollution reduction and carbon reduction measures, the emission reduction potential of China's coking industry will gradually shift from key areas to non-key areas.

Analysis on the spatial correlation network and driving factors of carbon emissions in China's logistics industry

Promoting the green development of the logistics industry has become a focal point of attention in China. This study combines an improved gravity model and social network analysis method, focusing on the nineteen provinces of the Yangtze Economic Belt and Yellow River Basin. It constructs a spatial correlation network of carbon emissions in the logistics industry from 2010 to 2021, exploring its formation mechanism and spatial evolution characteristics. The study utilizes a quadratic assignment procedure model to investigate internal driving factors. Building upon this, the study employs an improved STIRPAT model to predict the emission reduction path of the future logistics industry. Results are as follows: (1) Carbon consumption is most pronounced in Shandong, Jiangsu, and Shanghai. The carbon emission shows the characteristics of larger downstream; (2) The bridges of carbon emission-related networks gradually shift from Shandong to Shanxi, Anhui, and Sichuan. Carbon emissions in each sector and spatial spillover effects exhibit dynamic correlations and interactive influences; (3) Energy intensity, freight volume, and the spatial correlation network of the logistics industry are highly correlated; (4) The overall carbon emissions from the logistics industry show a decreasing trend in the future. Anhui and Shaanxi provinces will have high carbon emissions in 2035. The conclusions aim to provide policy suggestions for the region's low-carbon transformation.

Analysis of the Measurement of Transportation Carbon Emissions and the Emission Reduction Path in the Yangtze River Economic Belt under the Background of “Dual Carbon” Goals

Carbon emissions from the Yangtze River Economic Belt are an important element of China’s carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country’s overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios.