Carbon Intensity Reduction Research Articles

Sustainable opportunities to recover power plants’ waste heat: a benchmark of techno-economically optimized heat pumps

Current climate targets, adopted worldwide, pursue the decarbonization of all energy sectors. In power generation, the spread of RES has caused the shift of the Combined Cycle Gas Turbine (CCGT) power plants’ traditional role from providing constant baseload power to flexible operations providing services and backup capacity to the grid, as a consequence, the revenues opportunities on the traditional electricity markets (e.g., day-ahead, and intra-day markets) are no longer certain. At the same time is urgent to address a significant carbon intensity reduction in the heating sector, which is responsible for a large part of the current greenhouse gas emissions. Exploiting the low-exergy waste heat of CCGT’s water-cooled condenser as a thermal source for vapor compression heat pumps can meet two targets. On one hand, the revenues from heat production enhance the viability of the CCGT power plant, often essential for the security of the electrical supply. On the other hand, the heat delivered to the user represents a low-carbon alternative to traditional gas-fired boilers or even to air-sourced heat pumps characterized by lower efficiency. This work assesses the recovery of thermal energy from the sea cooling water at the bottoming cycle condenser of Tirreno Power 794 MWel CCGT in Vado Ligure through a high-temperature heat pump using R600 as a working fluid. Cooling water represents a privileged heat source and the integration into the power plant’s site allows running the HP at a lower cost than the electricity retail price. The case study takes into account the new Vado Ligure sports hall, to size the HP and explore the economic and environmental performances. The proposed layout is compared with the main solutions available: air source heat pump, gas, and electric boilers. The results show that on a lifespan of 20 years such integration of a heat pump with a CCGT could lead to consistent economical savings and emissions cuts.

Impact of digital finance on energy-based carbon intensity: Evidence from mediating effects perspective

This research measures energy-based carbon intensity based on energy consumption of 30 Chinese provinces and investigates the impact of digital finance. First, the baseline results were examined through panel data model. Second, we reveal the “black box” system of digital finance and energy-based carbon intensity through mediating effects model. Third, by employed panel quantile regression model, we examine the heterogeneity of the effects of various factors under different carbon intensity quantile. The main quantitative results are as follows: (1) Digital finance shows significant sustainable effect, and its growth of 1% will reduce the carbon intensity by about 0.092%. (2) The intermediary effects of technological innovation and energy structure are −0.0663 and 0.007, respectively, accounting for 41.88% and 19.36% of the total effects. Both are significant transmission mechanisms. (3) When the carbon intensity in >0.9 quantile, digital finance shows a positive coefficient. On the contrary, the coefficient at <0.75 quantile is negative and its absolute value increases with the decrease of quantile. It shows that with the reduction of carbon intensity, the positive impact of digital finance gradually increases. (4) In the eastern, central and western regions, a 1% increase in digital finance will reduce the carbon intensity by 0.147%, 0.096% and 0.089% respectively. This research provides a reference for regional governments to use digital finance tools to promote sustainable development.

Methodology for assessing the maximum potential impact of separations opportunities in industrial processes

Separation technologies currently used in U.S. manufacturing industries are estimated to account for more than 20% of plant energy consumption. However, accurately determining the impact of new separation technology solutions can sometimes be difficult, especially when evaluating a slate of new candidate separation technologies, each of which has its own separation performance, energy demand, and capital cost. In these cases, a typical approach is to assess each new separation technology by collecting performance and cost information and then using that information to develop a techno-economic analysis to identify overall benefits. While this approach is thorough, it can be time consuming and can hinder reaching a critical understanding of the potential of a given separation challenge, especially when there is no known solution. To address these issues, we developed an assessment methodology, using industrial screening processes, that can be used to better understand the potential impacts of addressing a given separation challenge. This paper presents an overview of our separation challenge stream assessment methodology. The methodology involves defining an “ideal” separator and deriving the associated minimum separation energy. The “ideal” separator represents the most optimistic outlook of a given opportunity so the maximum impact from existing and not-yet-developed solutions can be assessed. Using established biorefinery models, we applied the methodology to 10 different separation challenge streams from two different biomass conversion platforms to identify the type of information that can be obtained. Three of the ten challenge streams assessed had maximum possible cost savings predictions &amp;gt;20%, and associated reductions in process energy carbon intensity ranging from 0 to 54%. Two streams had cost and energy savings potential that were &amp;lt; 5%. Some of the opportunity drivers from the various assessments include higher product yields, reduction or elimination of downstream equipment, new co-products, and cost savings associated with raw materials and energy consumption. The information from these assessments can help guide the selection or development of new separation technology solutions based on the various potential factors that drive the projected benefits.

In-Situ Steam Generation Using Mist Water-Air Injection as Enhanced Oil Recovery and Energy Efficiency Process: Kinetic Modeling and Numerical Simulation Approach

Summary In the current energy transition era, oil exploitation and especially the development of heavy oil reservoirs are facing big challenges to overcome the possible limitations in terms of economy (oil price), energy efficiency, and carbon footprint. Particularly, thermal enhanced oil recovery processes need to be re-evaluated in an attempt to harness the injected and produced energy. In that sense, Ecopetrol is evaluating new strategies to optimize the current steam injection process using different hybrid technologies from laboratory to field scale. One of the most attractive initiatives is evaluating the in-situ steam generation using mist water-air injection. This process involves simultaneous air and water injection into the formation through a set of nozzles. It looks to use part of the in-situ oil as a fuel, using the reservoir not only as a tank of energy but also as a steam generator. The main contribution of the technique concerning conventional steam generation is the use of the heat from the combustion of the residual oil to generate an in-situ steam front to transfer the uncontacted oil. This is reflected in reduced carbon dioxide (CO2) emissions, reduced fuel and water requirements, and increased oil production and net energy recovery. This article describes the methodology, results, history matching, and kinetic modeling of experimental evaluations and the upscaling of the experimental observations to a representative sector model from a Colombian heavy oil field. Results are described in terms of incremental oil recovery, energy efficiency, and carbon intensity compared with the baseline (a traditional steamflooding scenario). The technology of in-situ steam generation using mist waterair injection led to benefits in terms of better energy use and reducing the external fuel dependency for steam generation at the surface. Additionally, it was possible to identify improvements in incremental oil recovery (around 90%), energy efficiency (about 10 times less energy required to produce 1 m3 of oil), and reduction in carbon intensity (up to 91%) considering as baseline a conventional steamflooding scenario. These results will be key input parameters for designing and commissioning future applications in the Colombian fields.

Impact assessment and mechanism of water conservancy policy on carbon emission performance under the background of artificial intelligence

AbstractArtificial intelligence technology is constantly developing and changing. Due to the continuous development of technology and production of carbon emissions, various problems have occurred, forcing various regions to start promoting low‐carbon work. What kind of method can effectively and quickly improve the performance of carbon emissions has become one of the current research topics that has attracted much attention. In response to this problem, it is of great significance to study in the field of carbon emission performance improvement methods. With the in‐depth research on carbon emissions, the research on the intervention of water conservancy policies in carbon emissions has gradually been carried out, and its functional effects are of great significance to solve the problem of improving carbon emissions performance. This paper has aimed to study the impact and mechanism of water conservancy policy on carbon emission performance in the context of artificial intelligence. Through the analysis and research of the water conservancy policy under artificial intelligence, the double difference model (DID) is used to evaluate it, so that it can show the impact and mechanism on carbon emission performance, so as to solve the problem of improving carbon emission performance. This paper has analysed water policy, carbon emission performance and DID model under artificial intelligence. Its influence and mechanism have been experimentally analysed, and related theoretical formulas have been used to explain. The results have shown that the water conservancy policy has a significant and continuous driving effect on the reduction of carbon emission intensity, and its interaction coefficient under the control variable is −0.934, which is significantly negative. Further analysis of variables has shown that the energy intensity coefficient is 0.714, and the secondary industry coefficient is 0.924, which are both positive and significant. Water conservancy policies mainly reduce carbon intensity through the improvement of energy efficiency and industrial structure upgrading. It can be seen that water conservancy policies under artificial intelligence can meet the needs of improving carbon emission performance, and the level of economic growth and green development has been greatly improved.

Urban density, directed technological change, and carbon intensity: An empirical study based on Chinese cities

Technological change is one of the most effective methods to reduce carbon intensity. Meanwhile, cities are essential carriers of technological change and carbon emissions. Considering the extensive land expansion in urbanization which always manifests in the density of urban economic activity, this paper analyzes the relationship between urban density and carbon intensity and also the mediating role of directed technological change to explore the interaction among them. First, the authors construct a theoretical model that considers the knowledge production sector, final goods production sector, and technical choice. Second, based on the panel data of 280 cities in China from 2008 to 2017, the authors use the two-way fixed effect regression, mediation-effect regression, and panel-threshold model to examine the results. The results show that: (1) The increase in urban density helps to reduce carbon intensity. (2) Capital-saving technological change is a mediating factor in the path of urban density's effect on carbon intensity. (3) With the increase in market size, the effect of urban density on capital-saving technological change weakens, thereby weakening the inhibitory effect on carbon intensity. Findings can provide a reference for reducing carbon intensity in other countries to formulate reasonable and practical policies for sustainable urbanization, especially for developing countries.

Ship Energy Efficiency and Maritime Sector Initiatives to Reduce Carbon Emissions

With stricter IMO regulations on CO2 taking effect in 2023 and ambitious goals to reduce carbon intensity by 2030, the maritime industry is scrambling to clean up its act. Conventional methods and equipment are now being reevaluated, upgraded or completely replaced. The difference between a short-term fix and a long-term sustainable option is how flexible vessels will be to use new energy sources or technology as they become viable. The review discusses the recent literature on renewable energy sources, technical and operational strategies for new and existing ships, technology maturity, and alternative fuels. It is found that the IMO’s targets can be met by combining two or three technologies, or via a radical technology shift which can provide innovative, high-efficiency solutions from an environmental and economic standpoint. It has also been noted that policies and enforcement are essential management instruments for mitigating the unfavourable environmental effects of marine transportation and directing the maritime industry toward sustainability on a regional, national, and international scale.

Development of an empirical model to quantify carbon emissions for machining of cylindrical parts.

As a result of growing environmental issues and stringent carbon emission (CEM) regulations imposed throughout the globe, low CEM has become one of the essential requirements of manufacturing industries. Low-carbon manufacturing, which aims to reduce carbon intensity and improve process efficiency, has evolved as emerging issue that has encouraged a lot of research into quantifying the CEM of different manufacturing processes. To comply with increasingly stringent CEM regulations and achieve low carbon manufacturing, manufacturing industries require accurate CEM data for their products. In this work, an empirical model is developed to quantify carbon emissions for machining of cylindrical parts. The CEM associated with a cylindrical part machining is decomposed into CEM from electrical energy consumption, material consumption, cutting tool wear, and coolant consumption and from the disposal of machining waste materials. Electrical energy consumption of a machine tool is further decomposed into different energy modules: startup, standby, spindle acceleration, idle, rapid positioning, air-cutting, and cutting for accurate quantification of CEM. Energy consumption models are developed for each module, and are integrated to quantify the total energy consumption of the machine tool. Finally, the developed model is applied on a cylindrical part with three different process plans to validate the developed model for practical implementation in industry. The proposed model can be utilized in the manufacturing industry to quantify carbon emissions based on different process parameters before machining a cylindrical part to achieve low carbon manufacturing process planning and scheduling.

How does financial inclusion affect environmental degradation in the six oil exporting countries? The moderating role of information and communication technology

Progress in financial inclusion has played a major role in economic development and poverty reduction. However, the environmental impact of financial inclusion calls for urgent implementation of environmental strategies to mitigate climate change. Financial inclusion forces the policies of developed countries to advance and not affect the present and future development of developing countries. Therefore, the current study aims to investigate the direct effects of information and communication technology (ICT) usage on environment as well as its moderating role on the association between financial inclusion and environmental degradation for six oil exporting countries (United Arab Emirates, Saudi Arabia, Russia, Kuwait, Canada, and the United States), using annual panel data from 1995 to 2019. We also analyze the validity of the environmental Kuznets curve (EKC) phenomenon for the entire sample, as well as the role of energy consumption and population. Employing the Method of Moments Quantile Regression (MMQR) with fixed effects, this study supported the existence of EKC phenomenon here as linkage amid human development index and carbon intensity. We find that energy consumption significantly increases carbon intensity. The empirical results showed that the application of internet- and mobile use as indicators of ICT usage lead to environmental preservation in the six oil exporting economies. Also, we observe that financial inclusion has mitigating effects on pollutant emissions, contributing to environmental preservation. Interaction between ICT usage and financial inclusion jointly reduces carbon intensity in all quantile distributions. A robustness check using an alternative proxy of the financial inclusion also confirms that ICT usage significantly and negatively moderates the association between financial inclusion and carbon intensity. Based on the findings of this study, the selected oil exporting countries should integrate financial inclusion with environmental policies to reduce carbon intensity.

Could environmental courts reduce carbon intensity? Evidence from cities of China

Environmental courts play an important role in pollution control. It is unclear whether environmental courts could help to achieve China's carbon peak and carbon neutrality goals. This study investigates the impact of environmental courts on carbon intensity, using the data of 281 cities of China during 2003–2017. Using the multi-period difference-in-differences (DID) model, this study first evaluates the impact of environmental courts on carbon intensity taking the establishment of environmental courts as a quasi-natural experiment. Then, this study examines the influence mechanisms of environmental court on carbon intensity from the perspective of administrative enforcement, green innovation ability and cooperative effect of pollution control. Finally, this study analyses the heterogeneity test from the perspective of public participation, whether it is a low-carbon pilot city and geographical location. The main results are: (1) Environmental courts could reduce carbon intensity, which is supported by a series of robustness tests. (2) Environmental courts could reduce carbon intensity through improving administrative enforcement of local government and green innovation ability of firms and playing the cooperative effect in pollution control. (3) Heterogeneity test results show that in cities with high public participation, environmental courts could reduce carbon intensity more effectively. Compared with non-low-carbon pilot cities, environmental courts have a bigger role in reducing carbon intensity in low-carbon pilot cities. Compared with the middle cities of China, environmental courts also have a bigger role in reducing carbon intensity in eastern and western cities. This study provides new insights for China to reduce carbon intensity from the perspective of the establishment and implementation of environmental courts, and policy implications of how to effectively play the role of environmental courts in achieving carbon peaks and carbon neutrality goals are finally suggested.

Assessing the Drivers of Carbon Intensity Change in China: A Dynamic Spatial–Temporal Production-Theoretical Decomposition Analysis Approach

As carbon intensity (CI) can better reflect the coordinated relationship between carbon emissions and economic growth, the related research has gradually increased in recent years. To better explore the influence of production technology and spatial variations on CI disparities in China, this paper constructs a dynamic spatial–temporal production-theoretical decomposition analysis (DST-PDA) model to explore the dynamic spatial disparities and temporal variations of driving factors on CI in different regions. Moreover, this paper further investigates the impact of production-related factors, such as carbon emission technology’s change with regard to carbon intensity, and explores the benchmarking catch-up effect and the effort on reducing CI by setting benchmarks and dynamic comparative analysis, which could provide guidance for some underperforming regions. The main results are as follows: (1) The overall trends of CI increased from 2007–2019, and the northwest region had the largest growth rate. (2) Energy intensity was the dominant driver to reduce CI, and technological changes also played a great role in decreasing CI. Conversely, carbon emissions efficiency had negative effects on reducing CI. (3) The spatial variations of the contributions in factors to reduce CI have gradually increased. Resource-dependent development areas have great potential to reduce carbon intensity by improving energy and carbon emission efficiencies. The northwest has great potential to reduce CI by introducing advanced technologies. Some policies are proposed based on the results.

The spatial spillover effect of China's carbon emissions trading policy on industrial carbon intensity: Evidence from a spatial difference-in-difference method

The carbon emissions trading (CET) market has been viewed as an effective way to improve CO2 emissions performance against the background of achieving China's carbon neutrality before 2060. This study investigates the spatial spillover effects of the CET policy on industrial carbon intensity reduction by developing spatial difference-in-differences (SDID) models. Then, a mediating effect model is used to test whether technological progress is a mediating variable of the spillover effects of the CET policy. The results show that the CET policy has negative spatial spillover effects, implying that the local CET policy has significantly reduced the industrial carbon intensity in the surrounding area. Technological progress is confirmed to be a mediating variable by which the CET policy reduces carbon intensity in the surrounding area. Hence, we suggest establishing a unified CET system including all industries with high emissions in China, and upgrading the low carbon technologies as soon as possible.

Reduction effect of carbon markets: A case study of the Beijing-Tianjin-Hebei region of China

The carbon market is a crucial market-oriented tool in achieving carbon neutrality and has been adopted by many countries and regions. China has established a policy system covering eight carbon trading pilots since 2013 and has implemented effective practices. Despite the evaluation of the carbon markets at the national level, few studies identified the carbon emission reduction effect for a specific region or assessed the differentiated characteristics that may significantly impact the development of the carbon market. This study took the Beijing-Tianjin-Hebei (BTH) region as the research sample and aimed to estimate the carbon emission reduction effect of the carbon market by using a difference-in-differences approach. Our findings suggested that the carbon market in the BTH region effectively reduced its carbon intensity by 14.04%. Our estimations were robust after using a winsorization panel or establishing a new control group. Furthermore, the results also indicated that the carbon market’s effect on reducing carbon intensity differs across cities and shows an increasing trend yearly. Relevant recommendations for promoting carbon trading policies were proposed.

WIND ASSISTED PROPULSION: INVESTIGATIONS ON THE USE OF SHIP HOLISTIC MODELS FOR PERFORMANCE ANALYSIS

Wind propulsion is one of the most promising technologies to reduce carbon intensity of ships. However, with variable thrust production and induced drift action, sail’s contribution to propulsion is to be evaluated in different ways from traditional propulsors. For sail retrofit projects, where vessels are initially designed to be optimal at single transit speeds with propulsion engine, wind assistance may also induce a degradation of operational efficiency and limit the extend of energy savings. For these reasons, performance analysis should evolve to account for complex energy transfers between propulsion domain and energy systems. A novel Modelica based model is presented in this article, where manoeuvres and energy modelling are used jointly to predict overall efficiency of wind assisted ship concepts. The model is used to evaluate the impact of retrofitting 4 Flettner rotors on the Duisburg test case (DTC) equipped with diesel engines mechanical propulsion system, with oil fired and exhaust gases steam plants and electricity generation from gensets and turbogenerator. Finally, from the analysis of DTC performance in a sweep of wind conditions, potential solutions to increase sailing efficiency are presented, offering new research directions in vessel design adaptation to natural propulsion.

Education and its impact on renewable energy demand, carbon intensity, and green growth: do digital financial inclusion and environmental policy stringency matter in China.

Various targets need to be accomplished before the dream of sustainable development comes true. Among these targets, increasing renewable energy demand, reducing carbon intensity, and achieving green growth are the most noticeable. Therefore, the present study focuses on capturing digital financial inclusion's impact on renewable energy demand, carbon intensity, and green growth in the presence of ICT trade and environmental policy stringency in China. To empirically estimate the model, we have applied ARDL covering the time span from 1995 to 2020. The results state that the estimated coefficients attached to education, ATMS, and environmental policy stringency are positively significant in the renewable energy and green growth model and negatively significant in the carbon intensity model. From these results, we confer that education, digital financial inclusion, and environmental policy stringency are good for increasing renewable energy demand, reducing carbon intensity, and achieving green growth in China. In the short run, some of the estimates are negative; hence, we conclude that the results are inconclusive. The results recommend some imperative policy suggestions.

Reducing the carbon intensity of international shipping – The impact of energy efficiency measures

The International Maritime Organisation (IMO) has set a target to reduce the carbon intensity of shipping, or CO2 emissions per transport work, by at least 40% by 2030 from 2008 levels. While short-term measures which focus on improving energy efficiency have been implemented, their impact on carbon intensity trends of international shipping over time has not been quantified. This study quantifies and attributes the contribution of various driving factors to the overall change in carbon intensity of international shipping by ship type. The carbon intensity changes of each ship type are quantitatively linked to the overall carbon intensity target of the IMO. The study results highlight that reductions in carbon intensity at the ship-type and global level have been largely a result of decreases in energy intensity from 2012 to 2018 but reductions became smaller in the later period (2015–2018), underscoring the limits to energy efficiency measures. Furthermore, this study highlights the additional insights that can be drawn on the transport mode and freight activity profiles from the joint analysis of demand and supply-side indicators, revealing not only the changes in freight activity and capacity utilization, but also the shifts in capacity miles travelled for different shipping modes.

Study on the extension of the dynamic benchmark system of per capita carbon emissions in China's county.

County is the center of China’s socio-economic development and the key node for urban–rural integration. Also, the county is an important carrier for promoting urban and rural green development. Improving green and low-carbon development capabilities and formulating county-level low-carbon standards will play a significant role in promoting China’s new people-oriented urbanization and rural revitalization. Although there have been extensive studies on low-carbon benchmarks, over half of the benchmarks tend to ignore the development stage of the evaluated region and its needs. When the region’s economy reaches a certain level, constraints from low-carbon targets may limit the local development process. This study firstly allocated county carbon intensity reduction targets (CIRT) by considering the differences in county carbon reduction capacity and responsibility. Secondly, a dynamic benchmark system of per capita carbon emissions (PCCE) in counties in China is constructed. Finally, we took Changxing County in Zhejiang Province as a research case to verify the dynamic benchmark of PCCE. According to the carbon intensity target reduction rate (CITRR), China’s counties can be divided into three categories: low carbon emissions reduction capability-responsible counties (L-CERCRC), medium carbon emissions reduction capability-responsible counties (M-CERCRC), and high carbon emissions reduction capability-responsible counties (H-CERCRC). The results show that (1) due to the national CO2 emission reduction target in 2030, the carbon intensity will be 60% lower than in 2005, the CITRR for China’s 1510 counties range from 8.36 to 137.83%; the average CITRR is 48.40%. (2) Changxing County’s CITRR is 57.71%, which belongs to the H-CERCRC. The PCCE of Changxing County will be much higher than the benchmark when the carbon peak is reached in the future. (3) For reaching the aiming benchmark, Changxing County is suggested to adjust its relevant influencing factors of PCCE for converting local’s PCCE reaching to the benchmark within a certain time period. The dynamic benchmark system for PCCE in China’s counties established in this study is economically sensitive, which not only takes the differences of counties into account, but also meets the needs of counties’ diverse development form stages. This system provides counties a few coordinated directions which can improve the local’s economic development and reduce greenhouse gas (GHGs) emissions through the development progress.

Digital financial inclusion and carbon neutrality: Evidence from non-linear analysis

To find out how digital financial inclusion affects carbon neutrality, this research analyzes its non-linear influence on carbon intensity and carbon sequestration via a sample of 277 cities in China from 2011 to 2017. Based on rigorous theoretical analysis and empirical testing, results show that the marginal impact of digital financial inclusion on carbon intensity first decreases and then increases, whereas the marginal impact of digital financial inclusion on carbon sequestration keeps decreasing. The marginal decrease is due to a limited financial audience, and the marginal increase is due to individual optimization and scale effects brought by a good external pulling force. The results of the mediating effect show that digital financial inclusion promotes the reduction of carbon intensity by increasing per capita disposable income and digitization, while such inclusion promotes the increase of carbon sequestration by means of green space and green technology. To refine the impact, we carry out heterogeneity analysis from two aspects and four instruments of finance as well as different characteristics of cities. From this, a series of subtle findings arise that are conducive to the implementation of specific policies. Finally, several methods prove the results' robustness, thus increasing the validation of this paper's core conclusion.

The impact of promoting new energy vehicles on carbon intensity: Causal evidence from China

The transport sector accounts for about a quarter of the world’s carbon emissions. Given the huge future growth of the carbon emissions of the transport sector and its tight links to socio-economic development, the introduction of new energy vehicles can not only reduce carbon emissions but also decarbonize the entire economic system by decreasing carbon intensity. Taking advantage of a promotion project in China as a natural experiment, this paper explores the causal effect of promoting new energy vehicles on reducing carbon intensity. Our empirical results show that the promotion of new energy vehicles decreases the carbon intensity in demonstration cities by about 4.5% and decomposition analyses show that less than one-fifths of the decrease comes from the reduction of carbon emissions, and the other four-fifths result from the increases in outputs. Mechanism analyses suggest that in terms of passenger vehicles, this project increases the number of newly registered pure electric passengers motor vehicles, but has no influence on public transportation and taxis. Moreover, the promotion of new energy vehicles by this project is not brought about by the subsidy policy for the private purchase of them. We also put forward some policy recommendations for constructing a low-carbon transport system.

The role of population agglomeration played in China's carbon intensity: A city-level analysis

Population agglomeration is an important foundation for urban development, and continuous reductions in carbon emissions need to be considered by urban development planners. However, there is an intrinsic link between population agglomeration and carbon emissions, and only a few studies have discussed this important topic. This study examines how population agglomeration affects carbon intensity using a panel dataset of 272 Chinese cities (2004–2017). Our empirical findings suggest that population agglomeration can effectively reduce carbon intensity. This holds true after a full endogeneity discussion and a range of robustness tests. Meanwhile, the two-step mechanism analysis shows that service industry agglomeration, industrial structure optimisation, and green technology innovation are three important channels for population agglomeration for cutting carbon intensity. The heterogeneity analysis indicates that the effects of population agglomeration on carbon intensity vary across different periods and regions. Valuable information to enable the reduction of carbon intensity is presented from the perspective of population agglomeration.