Changes In Carbon Emissions Research Articles

Spatiotemporal Dynamics of CO2 Emissions in China Based on Multivariate Spatial Statistics

With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are “Low–Low” at the provincial level, and “Low–Low” and “High–High” at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China’s carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies.

On the Transmission Mechanism of Carbon Finance Promoting the Green Transformation of Traditional Industries in China

This article clarifies the specific impact mechanism of carbon finance on the industrial transformation of Anhui Province in China by studying the changes in carbon emissions and the current status of industrial development in Anhui. Through research and investigation, it has been found that the impact of carbon finance on industrial transformation is mainly reflected in four aspects: (1) Carbon finance enables some enterprises to have more funds to improve production processes and reduce carbon emissions in the production process through carbon emission trading. (2) Carbon finance promotes its transformation by changing the operating mechanism of the market, lowering entry barriers, and allowing more enterprises to enjoy the dividends of carbon finance. (3) Carbon finance uses financial means to eliminate high energy consuming and high emission enterprises and optimize industrial structure. (4) The emergence of carbon finance will encourage the government to increase support for financial related talents, cultivate more talents in carbon finance, change the management mode of enterprises, and enhance their international competitiveness. This article proposes countermeasures and suggestions from the perspective of promoting environmental protection and industrial green transformation and development.

Quantifying high-resolution carbon emissions driven by land use change in the Guangdong-Hong Kong-Macao Greater Bay Area

Accurate research on carbon emission spatial distribution is vital for achieving carbon neutrality. Previous studies suffered from scale effects, demanding enhanced resolution. This study collected and computed land use carbon emission data for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). It also introduced a novel method to downscale this data into 30 m raster format using night light and NDVI data. The study showed a consistent annual rise in GBA land use carbon emissions, accompanied by increasing disparities. At the city level, emissions in the highest-ranking cities were 58 times higher than those in the lowest-ranking ones. Impervious land carbon emissions held over 90% sway over total carbon emissions, making them the primary driver of land use-related carbon emissions. Remarkably, high-emission zones, such as coastal cities Guangzhou, Foshan, Dongguan, and Hong Kong, expanded outward, forming multi-tiered, high-density carbon areas, giving rise to an “∩” shape pattern. Carbon emission change rates from cropland were modest, characterized by a pattern of fluctuation. Moreover, spatial autocorrelation and K-means cluster analyses uncovered a noticeable spatial correlation among urban land use carbon emissions in the GBA. Consequently, a compelling case exists for enhancing inter-city cooperation to collectively pursue regional emission reduction objectives.

Carbon emissions changes of animal husbandry in China: Trends, attributions, and solutions: A spatial shift-share analysis

China is a major livestock producer confronting the dual challenges of rising demand for animal-based food consumption and decreasing carbon emissions. To effectively address these issues, it is crucial to understand the trends of carbon emissions from animal husbandry and the competitive advantages of carbon emission reduction in different regions. This study uses panel data from 31 provinces from 2004 to 2020 to investigate the contributing factors to carbon emissions and explore ways to reduce carbon intensity in animal husbandry. The analysis employs spatial shift-share analysis and the spatial Durbin model. Our findings indicate that life-cycle carbon emissions associated with animal husbandry in China decreased from 572.411 Mt CO2eq to 520.413 Mt CO2eq over time, with an average annual decline of 0.568 %. The annual contribution of output value and internal industry-mix adjustment to carbon emission growth is 22.639 MT CO2eq and 6.226 MT CO2eq, respectively. On the other hand, the annual contribution of carbon efficiency improvement to carbon emission reduction is much higher, at 36.316 MT CO2eq. However, there is significant regional heterogeneity in the spatial decomposition of the carbon efficiency change component. The Northeastern region, Northwest and along the Great Wall demonstrate neighborhood advantages in enhancing carbon efficiency. In contrast, the South China and Southwest regions rely more on local carbon efficiency advantages to reduce the carbon intensity of animal husbandry. Furthermore, the carbon intensity in local and neighboring areas can be reduced through environmental regulations and industrial agglomeration. While technical progress significantly negatively impacts carbon intensity in neighboring regions, it does not contribute to reducing the carbon intensity of local animal husbandry. The findings provide valuable insights for local governments, aiding them in recognizing the pros and cons of carbon reduction in animal husbandry and strengthening regional cooperation in emission reduction management.

Transient Combustion Characteristics of Methane-Hydrogen Mixtures in Porous Media Burner.

The combustion of conventional methane-hydrogen mixtures is associated with challenges such as combustion instability and excessive pollutant emissions. This study explores the advantages of porous media, which include a wide operating range, enhanced combustion stability, high combustion efficiency, and reduced pollutant emissions. We conducted numerical transient simulations to investigate methane-hydrogen combustion within a porous media, focusing on a cylindrical double-layer porous burner geometry. The research analyzes the temperature, combustion rate, and diffusion characteristics of the methane-hydrogen-precipitated gas flame within the porous media. Additionally, it examines variations in the position and width of the high-temperature region along with changes in carbon and nitrogen emissions. The computations were carried out for different hydrogen blending ratios over the time interval of 0-0.4 s. The results unveil the transient combustion characteristics of hydrogen-enriched methane within a porous media, offering valuable insights for the subsequent optimization of porous media burners (PMB). This study provides a theoretical foundation for enhancing the efficiency and environmental performance of combustion processes involving methane-hydrogen mixtures.

Evolution characteristics, carbon emission effects and influencing factors of production-living-ecological space in Taihang Mountain poverty belt, China

The rapid advancement of urbanization and industrialization in China has gradually spread to the poor mountainous areas, which has not only brought about rapid economic development but has also caused the increasing competition for production-living-ecological spaces (PLES) and many ecological and environmental problems, carbon emissions have also increased. As an economically less developed and ecologically fragile area in China, whether the transition of the PLES in the mountain poverty belt has unique characteristics? How the PLES transition in mountainous areas affects carbon emissions and what are the important factors affecting carbon emissions? To explore these issues in depth, we studied the Taihang Mountain area in Shijiazhuang (TMS) using remote sensing image interpretation data from 2000, 2010, and 2020, and we analyzed the PLES evolution characteristics, carbon emission changes, carbon emission effects and its influencing factors of PLES. The results are as follows: 1) The TMS was dominated by ecological and production space. From 2000 to 2020, the production space decreased by 384.66 km2, the ecological space increased by 123.80 km2, and the living space increased by 260.86 km2. Agricultural production space was mainly converted to ecological and rural living space. Industrial and mining productive space was mainly converted to agricultural productive space and urban living space. 2) The study area was in a state of carbon deficit, the transition of ecological space and agricultural productive space to industrial and mining productive space and living space were the main transition types caused the carbon emissions increasing, and that of industrial and mining productive space to agricultural productive space was the main type caused the carbon emissions decreasing. 3) The proportion of construction land, urbanization rate and proportion of secondary industry are the main factors leading to the increase of carbon emissions. Per capita energy consumption, forest coverage and proportion of tertiary industry are the main factors leading to the decrease of carbon emissions. This can provide new ideas for research on carbon emissions from land-use changes and a theoretical basis for the optimization of territorial space in the mountainous areas of China.

Future Scenarios of Urban Nighttime Lights: A Method for Global Cities and Its Application to Urban Expansion and Carbon Emission Estimation

As of 2018, approximately 55% of the world’s population resides in cities, and it is projected that this proportion will reach 68% by 2050. Population growth in urban areas leads to various impacts on society and the environment. In this study, we have developed a method for generating future scenarios of nighttime lights. What makes this method unique is its ability to (1) generate future gridded nighttime light intensity scenarios for cities, (2) generate future scenarios that preserve the distribution pattern of nighttime light intensity, and (3) generate scenarios that reflect urban policies. By applying this developed method, we have estimated nighttime light data for 555 cities worldwide and predicted future urban expansion and changes in carbon emissions for each SSP scenario. Consequently, both urban areas and carbon emissions are estimated to increase for the entire set of target cities, with patterns varying among cities and scenarios. This study contributes to the advancement of urban scenario research, including the estimation of future urban area expansion and carbon emissions.

Municipal solid waste incineration bottom ash recycling assessment: Carbon emission analysis of bottom ash applied to pavement materials

Inspired by the concept of conserving resources, bottom ash has been increasingly utilized in road construction as a readily available waste material. This study sought to address this gap by quantifying the carbon benefits associated with bottom ash application. Through a comprehensive analysis grounded in life cycle theory, author evaluated the changes in energy consumption and carbon emissions before and after the integration of bottom ash into the road construction process. The analysis employed the raw material production stages of different pavement materials as the system boundary. By determining the optimal amount of bottom ash and calculating the associated values, the study proposed an efficient application scheme for utilizing bottom ash in urban engineering construction projects. The results showed that bottom ash had the least carbon reduction effect in permeable bricks, followed by cement concrete and cement stabilized macadam mixture. The most significant effect was observed in asphalt mixtures. However, energy consumption increased with the addition of bottom ash in asphalt mixtures, whereas it decreased in the other three products. The carbon reduction after applying bottom ash was predicted based on the annual growth rate of urban road construction. Under the premise of maintaining the non-destructive application performance of asphalt mixtures, the optimal carbon reduction benefit for a 20% addition of bottom ash was approximately 17,369.9 tons. In cement-stabilized crushed stone mixtures, the optimal carbon reduction benefit ws achieved with a bottom ash content of 30%, approximately 15,797.7 tons. The practice of utilizing bottom ash in road works was significant in terms of maximising the benefits of carbon reduction.

Carbon Emission Drivers and Critical Paths in the Interaction of the "Local-Domestic-International" Economic Cycle - A case study of Beijing

Abstract It is crucial to study the carbon emissions worldwide induced by urban consumption activities. Taking consumption-oriented city Beijing as an example, we constructed a nested multi-regional input-output model (MRIO), and measured carbon emissions and value-added in local, domestic, and international systems. Furthermore, the structural decomposition analysis (SDA) and structural path analysis (SPA) was applied to analyze cross-system driving forces and key paths of carbon emission changes. The conclusions show: (1) Beijing's consumption leads to the highest carbon emissions in the domestic system but the highest value-added in the local system. There is spatial inconsistency in carbon emissions and value-added. (2) The intermediate commodity input-output effect (ICIOE) of intra-domestic provinces is the main driving factors contributing to the reduction of carbon emissions. In contrast, the ICIOE of inter-domestic provinces is the main factor leading to the rise. (3) In the top 10 types of key paths for Beijing’s consumption-based carbon emissions (CBCE) growth, electric power and construction sectors in domestic systems are key sectors. Chemical products and transport equipment in foreign systems are key sectors for Beijing’s CBCE decrease. Our findings suggest Beijing enhancing cross-system cooperation to achieve carbon reduction targets. JEL classification numbers: R15. Keywords: Consumption-based carbon emissions, Multi-regional input-output, Structural decomposition analysis, Structural path analysis.

Carbon emission change based on land use in Gansu Province.

Carbon emissions from land use change have become one of the main sources of regional carbon emissions. In order to explore the changes, 87 districts and counties in Gansu Province are taken as research objects. Based on the remote sensing data and statistical data of land use, the carbon emission coefficient method was used to investigate the spatial characteristics of land use carbon emission of each district and county in Gansu Province in recent 20years from the perspective of carbon ecological support coefficient and per capita carbon footprint. The main results are as follows: (1) the growth of land use carbon emissions in Gansu Province from 2000 to 2020 was significant, but the growth of carbon emissions after 2010 was fast, and the growth of carbon sinks was relatively slow. (2) The ecological support coefficient of carbon emissions at county level in Gansu Province showed a trend of high in the south and low in the north, high in the east and low in the west, and this trend became more and more obvious with the passage of time. (3) Based on carbon emission, county population, and carbon ecological support capacity, the per capita carbon footprint of each county in Gansu Province was analyzed. The results showed that the per capita carbon footprint in Gansu Province was increasing, indicating that the gap between carbon emission and carbon absorption in each county was widening. By the above result, the author divides the counties of Gansu Province into three regions, low-carbon maintenance area, green development area, and ecological optimization area, and puts forward development suggestions for different regions, respectively. Therefore, this paper can also provide a theoretical reference for the formulation of carbon neutral planning measures in inland northwest China.

The race between global economic growth and carbon emissions: based on a comparative study of developed and developing countries.

In recent years, there has been a persistent intensification of the global greenhouse effect. Balancing carbon emission reduction with economic growth poses an unprecedented global challenge. To better comprehend the relationship between economic growth and carbon emissions, this study first utilized the Tapio decoupling index to compare the decoupling relationship (the USA, Japan, and Germany) and three developing countries (China, India, and Russia) from 2000-2020. Additionally, the logarithmic mean Divisia index (LMDI) method was employed to investigate the factors influencing changes in carbon emissions. Our findings indicate that (1) the USA and Germany basically achieved strong decoupling; China, India, and Russia mainly showed weak decoupling; and Japan showed recessive decoupling. (2) Economic growth predominantly contributed to increased carbon emissions, with a lesser impact from population growth. A significant reduction in energy intensity restrained carbon emissions growth, as did energy structure replacement in most countries, excluding Japan. Based on this, a decoupling effort index was formulated. It has shown that the decoupling efforts made by developing countries are weaker than those of developed countries, primarily attributed to a lesser degree of decoupling between energy intensity and structure. This paper offers valuable insights for developing countries undergoing a low-carbon economic transformation. They should counterbalance carbon emission escalation resulting from economic growth through technological and energy structure improvements.

Study on industrial carbon emissions in China based on GDIM decomposition method and two decoupling effects.

The driving factors of China's industrial carbon emissions are decomposed by generalized Divisia index method (GDIM), so as to study the reasons for the change of China's industrial carbon emissions. The decoupling effect of China's industrial carbon emissions and economic growth is examined by speed decoupling and quantity decoupling. The speed decoupling is calculated by Tapio decoupling elasticity and emission reduction effort function, and the quantity decoupling is measured by environmental Kuznets curve (EKC). The results show that the positive driving factors are output size effect > industrial energy consumption effect > population size effect, and the negative driving factors are investment carbon emission effect > output carbon intensity effect > per capita output effect > economic efficiency effect > energy intensity effect. The elasticity of emission reduction is basically greater than that of energy conservation, indicating that there is still abundant room for efforts in emission reduction. The overall decoupling effect of carbon emissions is undecoupling-strong decoupling-undecoupling. Quadratic EKC shape is "U" shape, and the inflection point is 11.0987; the shape of cubic EKC is "N," and the inflection points are - 0.0137 and 2.4069, respectively, which satisfies the hypothesis of EKC curve.

Enhanced future vegetation growth with elevated carbon dioxide concentrations could increase fire activity

Many regions of the planet have experienced an increase in fire activity in recent decades. Although such increases are consistent with warming and drying under continued climate change, the driving mechanisms remain uncertain. Here, we investigate the effects of increasing atmospheric carbon dioxide concentrations on future fire activity using seven Earth system models. Centered on the time of carbon dioxide doubling, the multi-model mean percent change in fire carbon emissions is 66.4 ± 38.8% (versus 1850 carbon dioxide concentrations, under fixed 1850 land-use conditions). A substantial increase is associated with enhanced vegetation growth due to carbon dioxide biogeochemical impacts at 60.1 ± 46.9%. In contrast, carbon dioxide radiative impacts, including warming and drying, yield a negligible response of fire carbon emissions at 1.7 ± 9.4%. Although model representation of fire processes remains uncertain, our results show the importance of vegetation dynamics to future increases in fire activity under increasing carbon dioxide, with potentially important policy implications.

Unveiling the changes of carbon emissions along supply chains: Drivers and sustainable mitigation strategies

China's annual carbon emissions decreased year by year during 2013–2016 and increased after 2016. Such fluctuation prompts important questions about the factors that drove the decrease and increase, and the desired pathway(s) to sustain a continuous reduction. With the consideration of supply-demand relationships, we quantitatively evaluate the socioeconomic drivers of carbon emission changes along supply chains. Here we find that from a supply perspective, industrial adjustment has negative impacts on the emission reduction of service-driven paths. For paths involving the electricity-generation sector, the adjustment of primary input structure has positive effects on path-level emission reduction (since 2007). The construction sector can adjust its consumption structure to help accelerate the system's low-carbon transition. For the supply- and demand-oriented paths, the mitigation effects of emission intensity will weaken if more sectors are involved in production activities. Further emission reductions may rely on both reducing emission intensity and minimizing the utilization of deep-processed products.Synopsis: An extensive path-and layer-related decomposition analysis may have significant implications for fast-growing economies in pursuing carbon neutrality.

Spatial-temporal evolution of carbon emissions and spatial-temporal heterogeneity of influencing factors in the Bohai Rim Region, China.

The total change in carbon emissions in the Bohai Rim Region (BRR) plays a guiding role in the policy formulation of carbon emission reduction in northern China. Taking the 43 cities in the BRR as an example, the spatial-temporal evolution of carbon emissions in the BRR was analyzed using kernel density estimation (KDE), map visualization, and standard deviation ellipses, and the spatial autocorrelation model was used to explore the spatial clustering of carbon emissions. On this basis, the spatial-temporal heterogeneity of the factors influencing carbon emissions is explained using a Geodetector. The results are as follows: (i) During the study period, the carbon emissions in the BRR were on the rise, the share of carbon emissions in the Beijing-Tianjin-Hebei region (BTHR) and Liaoning Province was decreasing, and the contribution of Shandong Province was gradually enhanced. The spatial distribution of carbon emissions shows a geographical pattern of "middle-high and low-outside." (ii) Carbon emissions from different regions show the characteristics of BTHR > Shandong Province > Liaoning Province. The high-value carbon emission area continues to move from the northwest of Beijing-Tianjin-Hebei to the southeast. (iii) Municipal carbon emissions showed a significant positive spatial correlation in the later part of the study. The high-high aggregation area is in Tianjin, and the low-low aggregation area is in Liaoning Province. (iv) The level of transport development contributes to carbon emissions with the highest growth rate, followed by industrial structure. There are also regional differences in the dominant influences on municipal carbon emission differences. Population size, urbanization, and economic development level are the core influencing factors of carbon emissions in the BTHR, Shandong Province, and Liaoning Province, respectively. In addition, the explanatory power of the interaction between the level of economic development and other factors on carbon emissions is at a high level.

Research on the estimation and spatial pattern of net tourism carbon emissions in the Yellow River Basin from 2009 to 2019.

Based on panel data and remote sensing data of cities in the Yellow River Basin in China from 2009 to 2019, and using the tourism carbon footprint and tourism carbon carrying capacity models, the tourism carbon emissions, tourism carbon carrying capacity, and net tourism carbon of 65 cities in the Yellow River Basin were calculated. The balance and dynamic changes in carbon emissions and carbon fixation of urban tourism in the past ten years were compared. The results show that (1) tourism carbon emissions in the Yellow River Basin are generally on the rise, along with a distribution characteristic of downstream > middle reaches > upstream with obvious characteristics of urban agglomeration centrality within the basin; (2) the carbon carrying capacity of tourism is higher than that of tourism. The growth of carbon emissions is relatively slow, showing a spatial distribution pattern of high in the west and low in the east, which is mainly related to the geographical environment and economic development of the city; (3) the tourism carbon emissions and tourism carbon carrying capacity in the upstream areas can basically maintain a balance, but in the middle and lower reaches of the region, they show a carbon surplus. There is a significant positive spatial correlation in urban net tourism carbon emissions, and the clusters are mainly H-H and L-L.

Energy Flow Modeling and Low Carbon Analysis of Processoriented Production Line

Nowadays, energy and environmental problems are becoming more and more prominent, and the energy-based manufacturing industry also needs to face huge energy consumption problems. Therefore, production processes need to be investigated from an energy efficiency perspective at an early design stage so that maximum benefits can be obtained at low cost, low time and low risk. This process industry carbon emissions system does not calculate the consumption of raw materials and electricity in a generalized way at the boundaries of the plant. Rather, we delve into each step of the process and perform mathematical modeling of the process through a graphical approach, incorporating each link and factor that constitutes and influences the change in carbon emissions, and performing an aggregation of carbon emissions for the entire production line. It facilitates the subsequent improvement and optimization of the entire process-based production line, providing the basis for implementing and establishing the best energy-saving system.

Multi-source data-driven technology research on carbon emission dynamics prediction in electric power industry

Abstract This paper analyzes the trend of power generation structure and carbon emission changes in the power industry and decomposes and analyzes the influencing factors of carbon emission in the power industry by using the LMDI decomposition method. Combined with the analysis of the influencing factors of carbon emissions in the power industry from 2016 to 2022, the carbon emissions of the power industry in the Yellow River Basin are simulated by the scenario analysis method. Four simulation scenarios were constructed based on the economic scale, industrial structure, industrial electricity consumption intensity, thermal power fuel conversion rate, and power supply structure. The IPSO-LSTM model for carbon emission prediction was created after optimizing the LSTM neural network prediction model. Combining the scenario analysis method to set the amount of changes in the high carbon, baseline, and low carbon scenarios of the influencing factors, the carbon emissions from the power sector in different scenarios are predicted for the years 2025-2035. From 2025 to 2035, the carbon emissions from the power sector in the three scenarios, except for the energy transition scenario, show a trend of increasing, then decreasing, and then increasing over the study period. The energy transition scenario shows a pattern of increasing and decreasing carbon emissions from the power sector.

Carbon footprints: Uncovering multilevel spatiotemporal changes of ship emissions during 2019–2021 in the U.S.

Quantifying and understanding changes in carbon emissions is essential for the U.S. shipping industry to reduce carbon emissions, especially after its return to the Paris Agreement. We estimated carbon emissions from 48,321 ships in the U.S. Exclusive Economic Zone (EEZ) using the power-based method based on 3.6 billion Automatic Identification System (AIS) reports. We explored the characterization of carbon emissions from the national, regional, and port levels during 2019–2021 by allocating emissions on a 1 km*1 km grid through an activity-weighted method. The results show: (1) Due to the COVID-19 pandemic, emissions within the EEZ show a temporal trend of decreased and then rebound, specifically from 32.628 Tg in 2019 to 30.741 Tg in 2020 and then bounced to 31.786 Tg in 2021. The spatial differences in emissions show significant heterogeneity; (2) There are significant differences in emissions by vessel type, flag, and operational mode for the four regions of the U.S. (Great Lakes, Gulf Coast, Pacific Coast, and Atlantic Coast). Thus, emissions in these regions show different variability patterns over three years. Notably, “port congestion” led to record high emissions on the Pacific Coast; (3) Containerized cargo contributes the most to port core area emissions, so most ports with higher throughputs have higher emissions, with Long Beach and Los Angeles having the highest. Emissions from coastal ports are high and volatile, while inland ports are low and stable. This study provides the U.S. with a high spatiotemporal resolution inventory of carbon emissions from ships, and the findings are expected to provide some reference for controlling ship emissions.

Development of a framework to forecast the urban residential building CO2 emission trend and reduction potential to 2060: A case study of Jiangxi province, China

Investigating the CO2 abatement potential of urban residential building from systematic perspective is essential to reach the urban carbon neutrality target. However, previous studies on building CO2 emission trend forecasting were mainly focused on the building operational phase. In this study, a new framework that includes four building stages under a system dynamic model is developed to simulate urban residential building carbon emission changes and the related reduction potentials under three scenarios in Jiangxi Province up to 2060. Results showed that the overall process carbon emission dynamic had already peaked in 2014 under the three scenarios, with a peak value of 38.52 Mt. It then fell to 9.56 Mt in 2060 under the baseline (BAU) scenario. More importantly, seven carbon abatement measures were adopted during four building activities in this study, and the total carbon reduction was not the sum of the carbon reduction potential of the individual measures. Some carbon abatement strategies displayed synergistic effects such as low-carbon electrification where the combination of electrification and clean energy power generation was the largest contributor to reduced carbon emissions during building operation as a comprehensive carbon reduction measure. By contrast, extending a building's lifetime restrained the carbon abatement potential during the demolition stage, and it inhibited the carbon emission reduction by 24.84 Mt. These results highlight the significant need for effective policy interventions for clean production and the need to improve prefabricated building proportions, promote electrification, improve energy efficiency, strengthen recycling practices, and extend building lifetimes to promote decarbonization of urban residential building system development.