Sector Carbon Research Articles

Urban Management for Building-Sector Decarbonization: Focusing on the Role of Low-Carbon Policies

The building sector is a major source of anthropogenic carbon emissions worldwide. While existing studies have extensively explored the socioeconomic and technological impacts on carbon emissions generated from building operations, few have assessed the effectiveness of low-carbon policies in curbing the increasing trend of building sector carbon emissions. This study examines the impacts of low-carbon policy intensity on building sector carbon emissions using a two-way fixed effects model on a 6-year panel (2015–2020) dataset for 286 cities in China. Our findings indicate that, on average, the aggregated intensity of low-carbon policies fails to pose any significant impacts on carbon emissions from building operations. This is partly due to the variations in different types of policy. Specifically, a 10% increase in the intensity of energy conservation policy results in a 0.05% decrease in carbon emissions, whereas capacity utilization policies are associated with an increase in building-operation carbon emissions. Moreover, these policy–emission relationships vary across building types and end-use sources. In particular, energy conservation policies are negatively associated with emissions from cooking and heating, but positively related to emissions generated from appliances and cooling. In comparison, capacity utilization policies tend to encourage additional emissions from most sources. This study highlights the partial effectiveness of energy conservation policies in curbing building sector carbon emissions and underscores the need for additional efforts in tackling the rebound effects to realize building sector decarbonization.

Comparative Study of Cradle-to-Gate Carbon Emissions from Steel and Concrete Structures of Bangladeshi Industrial Projects

Sustainable practice is necessary for the construction industry's environmental impact, particularly carbon footprint. A "cradle-to-gate" Life Cycle Assessment of the embodied carbon emissions of two structural systems, steel and reinforced concrete, is presented for an industrial building in Bangladesh. By quantifying these emissions through BIM modeling and emission factor databases, the analysis shows that steel-framed structures have a significantly higher carbon footprint than their concrete alternatives, mainly because of the energy-intensive steel production processes. Emissions from raw material extraction, transportation, and manufacturing stages are detailed and assessed. The results show that steel structures produce 60% more embodied carbon than reinforced concrete counterparts, primarily due to raw material emissions, with other emissions from aluminum and rebar in both systems. These findings provide a basis for construction material selection and highlight the need for low-carbon approaches to reduce the sector's carbon footprint in rapidly urbanizing areas like Bangladesh. Further research should extend to the end-of-life impacts and more localized emission data to continue to refine sustainable construction strategies.

Aerogarden: An aeroponics innovation project linking artificial intelligence and sustainability

Every year, 10.8 to 19.1 billion tonnes of CO2 are emitted through food exports, which accounts for roughly 21% - 37% of the world’s global total emissions. In the urge to expand businesses and ensure availability of all crops throughout the year, the quality of air is being compromised. The demand for crops rises in tandem with population growth and improvements in human well-being. In addition, most of these exported crops lose their nutritional value due to the unhealthy exposure of preservatives and other farming chemicals. There are multiple factors involved in crop production: land, labour, transportation, storage etc. Aeroponics is a relatively new farming system that eradicates numerous problems by using less land and water and requiring minimal labour and nutrients. The aim of this project is to convert the aeroponic farming unit into a 100% carbon-neutral, self-reliant unit called Aerogarden by integrating modern technology like Artificial Intelligence (AI). Every household having an Aerogarden unit can access fresh organic vegetables and microgreens that actually retain their nutritional value. By achieving this goal, non-agricultural nations' dependence on food imports will lessen, which will ultimately result in a reduction in the sector's carbon footprint. By giving people a way to directly support the international movement, the project also aims to support the UN's initiative to achieve the 17 Sustainable Development Goals.

Unraveling the bioenergy production potential of native Scenedesmus and Nannochloropsis species by ameliorating non-polar lipids and desirable fatty acid production

This study investigated the biodiesel potential of aboriginal microalgal strains Scenedesmus sp. S01, Scenedesmus sp. S02, Nannochloropsis sp. S01, and Nannochloropsis sp. S02 under nitrogen-repletion (N+) and nitrogen-depletion (N-) conditions to minimize the energy sector's carbon footprint. Onset of the study, Nannochloropsis sp. S01 yielded higher biomass and chlorophyll of 1.41 g/L and 11.28 mg/g, respectively, over other species. Regarding macromolecules, Nannochloropsis sp. S01 had higher protein and lipid content of 37.09 % and 30 %, respectively, under the N+ condition, while it accumulated 34.27 % lipids in the N_ condition, of which non-polar lipids occupied 69 %. Among the Scenedesmus species, Scenedesmus sp. S02 showed high biomass, chlorophyll, and lipid content. The higher lipid-to-biodiesel conversion was noticed in Scenedesmus sp. S02, Nannochloropsis sp. S01 at about 71.02 %, which was further confirmed by FTIR. The biodiesel of all strains revealed palmitic acid as the most prevalent fatty type, accounting for between 30 and 37 %, and all species exhibited higher levels of SFAs between 37.21 and 46.54 %, followed by MUFAs (31–44 %) and low levels of PUFAs (8–20 %). Eventually, the mainstream fuel quality properties analyzed in this study, namely higher heating value, density, viscosity, oxidative stability, iodine value, and cetane number, satisfy the ASTM and EN biodiesel standards.

A maximum log-likelihood based data fusion model for estimating household’s vehicle purchase decision

ABSTRACT The growing adoption of electric vehicles offers a potential opportunity to reduce transportation sector carbon footprint. In our research, we studied vehicle purchase behavior with emphasis on alternative fuel vehicles using the vehicle purchase dataset ‘MaritzCX New Vehicle Customer Study.’ This study consisted of a two-level modeling approach. In the first level, purchasing of a new car was estimated based on consumers socio-economic characteristics. In the second level, the vehicle purchase decision was examined with a two-dimensional dependent variable – vehicle type and fuel type. We employed an innovative data fusion approach that probabilistically links records from MaritzCX with records from National Household Travel Survey with the objective of identifying new independent variables affecting the decision process while maximizing data fit. The final model included a host of independent variables from four different categories: vehicle-, economic-, demographic-, and spatial characteristics. Finally, the model results were employed to conduct an elasticity analysis.

When differentiated carbon tax policy meets LBD of renewable energy and electrification of energy end-use: Policy implications of sectoral differentiation of carbon productivity and carbon emission

The impact of environmental policy stringency on energy efficiency innovation has been studied well without considering renewable energy storage and electrification to meet demand for energy structural transition in China. Based on these past studies, this paper introduces the CGE model to analyze carbon tax stringency via carbon productivity by accounting for the electrification and learning-by-doing effect of renewable energy. Through comparing the performance of the uniform and differentiated carbon tax, it is found that the differentiated carbon tax always has a worse environmental performance in reducing carbon emissions due to less energy efficiency improvement than uniform one. While uniform carbon tax at stricter level gains more economic and environmental benefits on sectoral and overall aspects in long term because of greater improvement on sectoral carbon productivity in energy-intensive industries. Furthermore, these findings at a large level reveal the intricate interaction among carbon tax, sectoral carbon productivity, renewables-related subsidy, electrification, and the learning-by-doing of renewables for accelerating the energy structural transition and simultaneously achieving the coordination between economic growth and environmental protection.

Analysis of Sustainable Efficiency of Freight Transport in Major European Economies: An Integrated Multi-Region Input-Output and DEA Approach

This paper integrates the multi-region input-output model (MRIO) and data envelopment analysis (DEA) methods to analyze the freight transport efficiency in Europe. Social, economic, and environmental influences were combined into a sustainable efficiency rating of the freight transport sector of Germany, France, Italy, Spain, and the Netherlands. First, the freight transport sector's carbon footprint (CFP) was quantified using the MRIO model. The lifecycle-based CFP emissions of freight transport activities were assessed using a dataset from 2000 to 2018. Nineteen stochastic model-based MRIO lifecycle assessments were built for each country. Secondly, sixty instances of DEA models were created using a linear program for each mode in the selected countries. Thirdly, the sustainable efficiency scores were determined for each freight transport mode in each country over four periods: 2000–2004, 2005–2009, 2010–2014, and 2015–2018. The results illustrate that the sustainable efficiency score of inland, water, and air transport modes ranged from 0.38 to 1.

A study on the path planning and optimization of carbon peaking and carbon neutrality in the highway service area

The transportation sector is a major source of greenhouse gas emissions. Reducing emissions of the Highway Service Area (HSA) can help decrease the sector's carbon footprint and serve as a model for green transformation. Consequently, this study firstly employs the Life Cycle Assessment (LCA) to calculate the carbon emissions during the operational phase of a certain HSA in 2022, and then analyses the emission structure. Subsequently, four emission reduction pathways are identified, including Photovoltaic (PV) power generation, electrification retrofitting, forestry carbon sinks, and green roofs, in terms of both Three 100 Initiatives and carbon neutrality measures. On this basis, the planning of carbon peak and carbon neutral strategies for this service area under different scenarios are carried out, taking into account the dual carbon targets and relevant policies. The findings indicate that: (1) the HSA emitted approximately 766.84 tons of carbon emissions in 2022, with 96.53 % from purchased electricity. (2) PV power generation offers the optimal emission reduction benefits among four emission reduction pathways. (3) In carbon peaking scenarios, initiating PV construction is the optimal emission reduction strategy. (4) In most carbon neutrality scenarios, the simultaneous implementation of PV construction and bamboo planting can meet the neutrality requirements by 2060. However, if the HSA continues to develop economically after 2030, the economy could grow until 2035 to meet neutrality requirements. These findings can guide emission reduction strategies for other HSAs, accelerating the sector's transition to low-carbon emissions while supporting the development of policies for zero-carbon HSAs.

(Non-)terrestrial and (Non-)local pathways of behavioral policy diffusion in European cities’ climate action plans: Contextual, cultural, and leadership framing

This study investigates the spread of innovative behavioral (green nudging) policies within city-level Climate Action Plans (CAPs) across the European Union, focusing on how these innovations diffuse and the factors influencing their adoption. Using textual analysis with a dataset consisting of CAPs from 40 cities across Europe, we categorized various green nudging innovations and then tracked their origins and uptake. Then, we employed fsQCA (Fuzzy set qualitative comparative analysis) to identify the key factors driving diffusion. The findings reveal that while certain innovations, particularly in the building and transportation sectors, have achieved widespread adoption, other initiatives like community co-creation and urban parks have seen lower diffusion. Local terrestrial factors, especially sectoral carbon emissions, are significant drivers, with cities facing higher emissions more likely to adopt these policies. Interestingly, local emissions levels and strong climate leadership emerge as more critical determinants than economic status or climate similarities. The study identifies two primary diffusion pathways—Cultural Leadership for Emission Reduction and Local Adaptive Synergy—demonstrating the diverse strategies cities employ based on their unique contexts. This research highlights the importance of expanding green nudging measures in CAPs beyond technological and infrastructure domains to promote low-carbon behaviors comprehensively.

Environmentally sustainable opportunities for health systems: Metered-dose inhaler prescribing, dispensing, use and waste at a tertiary academic centre.

The Canadian health sector's carbon footprint is among the highest in the world and is responsible for 4.6% of Canada's total greenhouse gas emissions, a quarter of which is linked to pharmaceuticals, with metered-dose inhalers (MDIs) contributing disproportionally high amounts. To describe MDI prescribing, dispensing, use and waste patterns at a Canadian tertiary care academic hospital. In a retrospective point-prevalence cohort study, 100 consecutive patients discharged from medical and surgical services who were prescribed at least 1 MDI during their admission were included. Data were collected to describe patient demographics, MDI prescribing, dispensing, use and waste patterns. Use and waste data were applied to annual purchasing data to estimate annual usage and waste. Financial cost was computed using local purchasing estimates and carbon cost was calculated using published estimates. In 100 consecutively discharged patients, 315 MDIs were dispensed in total, of which 96 were unused. This represents 61,440 actuations dispensed, with 56,773 (92%) of doses unused or wasted. Waste data were applied to annual estimates, with a calculated annual carbon footprint of 315.8 tons of carbon dioxide equivalent (tCO2e). We estimate that a 20% waste reduction would result in carbon savings of 68.5 tCO2e. If 20% of salbutamol prescriptions were switched to the dry powder inhaler alternative, terbutaline, a 14% reduction in waste would be required to offset the additional monetary cost. This study suggests that 92% of MDI doses are unused and wasted. Opportunities for waste reduction exist and would be associated with both financial and carbon savings.

Sectoral carbon emission prediction and spatial modeling framework: A local climate zone-based case study of the Guangdong-Hong Kong-Macao Greater Bay Area

Understanding the spatio-temporal pattern of carbon emission (CE) is prerequisite for formulating carbon reduction policies. Previous studies emphasized quantitative analysis of CE inventory while ignoring sectoral spatial distribution. This study fills this gap by developing a framework for coupling the CE quantitative prediction model with the sectoral CE spatial model based on the Long-range Energy Alternatives Planning (LEAP) model, spatial proxy data and local climate zone (LCZ). The framework's sectoral CE results reveal a great varied landscape within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), one of the leading bay areas in the world with rapid urbanization and emphasis on low-carbon development, under four carbon reduction scenarios. By 2060, the CN3 scenario that considers both energy-supply and consumption sides, predicts a drastic emission cut to 35.76 million tons, just 10 % of the business as usual (BAU) scenario's forecast, mainly from transportation (29.45 million tons) and industry (9.34 million tons) sectors. Besides, compared with the common CE spatial products, the spatial simulation results of sectoral CE in our framework present detailed spatial differences at the jurisdictional level. The findings are conducive for governments to formulate accurate CE reduction and optimization strategies of the cities towards to the 2060 carbon neutrality.

Integrating Consumption-Based Metrics into Sectoral Carbon Budgets to Enhance Sustainability Monitoring of Building Activities

Climate policies such as sectoral carbon budgets use national greenhouse gas emissions inventories to track the decarbonization of sectors. While they provide an important compass to guide climate action, the accounting framework in which they are embedded lacks flexibility for activities that are international and at the crossroads of different sectors. The building activities, being largely linked with important upstream emitters such as energy production or industrial activities, which can take place outside of national borders, are such an example. As legislation increasingly addresses the whole-life carbon emissions of buildings, it is vital to develop cross-sectoral accounting methods that effectively measure and monitor the overall impact of buildings. Such methods are essential for creating sound and holistic decarbonization pathways that align with sustainability policies. This article aims to provide a consistent approach for depicting the life-cycle emissions of buildings at the national level, using France as a case study. By integrating the different emission scopes with decarbonization pathways, this approach also enables the creation of comprehensive whole-life carbon budgets. The results show that the French building stock footprint reached 162 MtCO2eq in 2019, with 64% attributed to operational emissions, primarily from fossil fuel combustion, and the remainder to embodied emissions, mainly from upstream industrial and energy sectors. Overall, 20% of the emissions occurred outside the national borders. Under various global decarbonization pathways, the significance of embodied emissions is projected to increase, potentially comprising 78% of the life-cycle emissions by 2050 under the current policies. This underscores the necessity for climate policies to address emissions beyond territorial and operational boundaries.

A spatial analysis of the economic returns to land‐use change from agriculture to renewable energy production: Evidence from Ireland

AbstractCountries are looking to reduce their agricultural sector's carbon footprint while encouraging economic and environmental sustainability. One proposed method of making agriculture more sustainable while maintaining farm incomes is through the production of bioenergy feedstocks. We examine the spatial aspect of the production of renewable energy feedstocks in Ireland. Two feedstocks are looked at—grass silage and short‐rotation coppice (SRC) willow. Spatial microsimulation analysis is utilised to assess the spatial suitability for alternative land uses, simulating land‐use change to compare economic returns with the current agricultural use. A farm‐based carbon subsidy is modelled based on avoided agricultural emissions and carbon sequestered. We find that midlands counties, especially those in the north midlands, have the highest proportion of land where feedstocks would be more profitable than the current agricultural use. Counties on the western seaboard have the lowest proportion of land where feedstocks would give greater returns. The amount of land where feedstocks are more profitable increases as greater carbon subsidies are provided. Of the two feedstocks assessed, SRC willow cultivation is more profitable than grass silage production. The overwhelming majority of land where producing feedstocks would be more profitable has cattle farming as its current use.

Sectoral carbon dioxide emissions and environmental sustainability in Pakistan

Global greenhouse gases and carbon dioxide emissions have escalated to concerning levels. Given the growing urbanization, industrialization, and energy consumption, it is crucial to understand how carbon dioxide emissions from various sectors influence environmental sustainability in Pakistan. The prime objective of this study is to examine the nexus between sectoral carbon dioxide emissions and environmental sustainability in Pakistan, analyzing data from 1971 to 2014. The study employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) method and the Autoregressive Distributive Lag (ARDL) model to analyze patterns and relationships, providing insights into how each sector's emissions contribute to the overall environmental impact. The results highlight that the independent variables – economic growth, population growth, and energy consumption - are the most significant contributors to overall carbon dioxide emissions, driven by the high consumption of fossil fuels. At an aggregate/disaggregate level, various models show mixed associations between dependent variables such as overall carbon dioxide emissions, carbon dioxide emissions from gaseous fuel consumption, carbon dioxide emissions from liquid fuel consumption, carbon dioxide emissions from solid fuel consumption, carbon dioxide emissions from residential buildings, commercial and public services, and carbon dioxide emissions from the transportation sector with the independent variables. Pairwise Granger causality confirms a unidirectional causality among various pairs of relationships. The study suggests that policymakers in Pakistan adopt a multi-sectoral approach to achieve environmental sustainability. It also recommends accelerating the transition to renewable energy sources such as solar, wind, and hydropower to reduce dependence on fossil fuels.

Digital economy's role in shaping carbon emissions in the construction field: Insights from Chinese cities

Achieving net-zero greenhouse gas emissions in the construction sector is essential to sustainable development policy. Previous studies have ignored the impact of the digital economy on carbon emissions in the construction industry. Using relevant city-level data from China from 2011 to 2021 and employing ArcGIS and Stata software, this study examines the current status of carbon emissions from the construction industry and investigates the impact of the digital economy on these emissions. The findings reveal that (1) from 2011 to 2021, carbon emissions of the construction industry have a pattern of decreasing-increasing-decreasing-increasing across the country. There is an increasing concentration of areas with high and relatively high carbon discharges in Heilongjiang, Jilin, Ningxia, Inner Mongolia, Shanxi, Guangxi, and Guizhou. (2) The standard deviation ellipse indicates the core area of carbon emissions in China's construction industry is moving northeast and becoming more decentralized. (3) Through a series of robustness tests, the digital economy has been proven to effectively reduce carbon emissions from the construction sector in municipal areas. (4) In severely cold regions, mild regions, and high-population-density cities, the digital economy reduces building sector's carbon output. However, it stimulates carbon emissions in the hot summer and cold winter regions. (5) Mechanism tests show that the digital economy reduces China's urban construction carbon emissions by fostering technological progress and green innovation. Urban resilience further strengthens the contribution of the digital economy to reducing carbon discharges in the urban construction sector of China. This article presents empirical evidence demonstrating how the digital economy empowers the construction industry to curtail emissions.

Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine. This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants. We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States. The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons. These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

Promoting the "Chinese experience" of carbon neutrality—Evidence of carbon emission pilot governance in Guangdong Province based on the EIO-LCA model

With the increasing global consensus on promoting carbon neutrality, China's efforts in carbon reduction governance are particularly prominent in Guangdong Province. This study focuses on utilizing data from 29 production sectors in Guangdong Province for the period of 2007–2020. The IPCC 2006 methodology was applied to estimate sectoral carbon emissions, and the Economic Input-Output-Life Cycle Assessment model was used to calculate the direct, indirect, and implied carbon emissions of each sector in Guangdong Province. In-depth analysis was conducted using the Carbon Emission Reduction Potential model. According to the findings, direct carbon emissions from the food sector have increased by 232.2 %. The manufacturing of specialized equipment and the apparel industry have successfully reduced their overall carbon emissions by 97.68 % and 73.15 %, respectively. Additionally, it is worth noting that architecture plays a significant role in driving the increase in carbon emissions within the electric power industry; the fluctuation of implied carbon emissions is more pronounced in the energy industry and non-metal products industry on the supply side, as well as in the chemical industry and electric power industry on the demand side; the potential emission reduction benefits of the electronics manufacturing industry have not been fully explored. In terms of carbon emission reduction potential, the first tier is primarily in the energy supply and metal processing sectors, while the second tier is mainly in the mining industry and electronic equipment manufacturing sector. The third tier focuses on the light industry and transportation sectors.

Pathway for China's provincial carbon emission peak: A case study of the Jiangsu Province

This study establishes the LEAP-Jiangsu model and uses the improved multilevel logarithmic mean Divisia index, Tapio decoupling, and synergistic effect models to explore the carbon reduction paths. The improved multilevel logarithmic mean Divisia index model analyzed the influencing factors of the historical and future carbon emissions. A provincial LEAP model was established to predict the time and value of carbon emission peaks. The Tapio decoupling and synergistic effect models were used to clarify the relationship between carbon emissions and economic development, the synergistic effect of carbon and pollutant reduction, and the terminal sector's carbon reduction potential. The results show that Jiangsu Province will most likely achieve carbon peaking in 2025∼2030, and the peak carbon emission is about 792∼853.9 Mt. Terminal energy intensity, power production structure, and terminal energy consumption structure are the main influencing factors of carbon reduction, with a cumulative contribution rate of about 74.4 %–83.5 %. The power production structure is critical in promoting the decoupling of economic development and carbon emissions. The contribution rates of energy intensity reduction, industrial structure optimization, improving terminal electrification level, and energy structure adjustment are 30.3 %, 26.2 %, 20.9 %, and 17 %, respectively. Coordinating carbon reduction measures will have better synergistic carbon and pollutant reduction effects.

Role of Environmental Policy Stringency on Sectoral CO2 Emissions in EU-5 Countries: Disaggregated Level Evidence by Novel Quantile-Based Approaches

Consistent with the increasing awareness of environmental problems, countries have applied various measures to combat climate change by preventing environmental degradation of the environment. In this context, a set of measures in different areas and sectors have been taken. Although it is possible to consider each of them, instead, using a more comprehensive index, such as the Environmental Policy Stringency Index, can be appropriate in examining the effects of environmental measures in curbing emissions. Accordingly, this research examines the effect of Environmental Policy Stringency Index on sectoral carbon dioxide (CO2) emissions in the European Union Five countries (namely, Germany, Spain, France, United Kingdom, and Italy) by using data for the period 1990/Q2-2020/Q4, performing novel quantile-based approaches. The outcomes show that at higher quantiles, Environmental Policy Stringency Index provides (a) a decrease in building sector CO2 emissions in France, the United Kingdom, and Italy; (b) a decline in industrial combustion sector CO2 emissions in France and Italy; (c) a curb power sector CO2 emissions in Germany, Spain, and France; (d) a decrease in transport sector CO2 emission in Germany and France; (e) there are causalities from Environmental Policy Stringency Index to sectoral CO2 emissions across quantiles except for some ones; (f) the outcomes are verified as robust. The outcomes prove the differentiating effects of Environmental Policy Stringency Index across sectors under the empirical examinations, quantiles, and countries. Thus, the study discusses various policy endeavors, such as consideration of the varying structure of environmental measures, application of nonlinear approaches, and focusing on some sectors to go fast in curbing sectoral CO2 emissions.

The heterogenicity features revealed based on the regional and sectoral carbon metabolic system: An empirical analysis of heavy-polluted cases in China

The Chinese government has made a positive response and policies to address global climate change, regions and sectors has become more important in reducing carbon emission. This study used the indicator of carbon emission intensity to evaluate the reduction effect of carbon emission of heavy-polluted regions and sectors, and also their features in China. The results indicated firstly, the aggregated carbon emission intensity of regions was primarily influenced by their embodied added value. From 2012 to 2015, the regions’ embodied added value increased more than 2 times. Secondly, the embodied carbon emission of the manufacture of chemical products sectors in regions were dominated by emission implied in metabolic path length greater than five, which took the proportion of more than 30% of emission. This showed that emission reduction policies for heavy-polluted sectors should focus on controlling the emission implied in trading with downstream sectors, and also demonstrated that the heavy-polluted sectors drove the reduction of carbon emission of other sectors. Thirdly, the carbon emission of heavy-polluted sectors in coastal regions fell due to implementing the carbon emission trading scheme policy, while heavy-polluted sectors in the inland regions radiated to their upstream and downstream sectors. This study analyzes regional and sectoral carbon emission reduction effect and provides theoretical and practical bases for urban development.