Low-carbon Targets Research Articles

The role of digital governance on carbon emission performance: evidence from the cities in yangtze river delta, China

Rapid industrialization and ambitious socio-economic targets have presented significant challenges to China’s carbon neutrality process. However, digital transformation offers new opportunities for sustainable development. This research examines the influence of digital governance (Digov) on carbon emission performance (Cep) and explores its underlying mechanisms. The study utilizes data from cities in China’s Yangtze River Delta from 2011 to 2019. The results show that digital governance has significantly improved carbon emission performance, a conclusion that remains robust even after conducting a series of rigorous tests and addressing endogeneity concerns. The main impact mechanisms of digital governance on carbon emission performance include energy intensity reduction, energy consumption scale reduction, industrial structure adjustment, and energy consumption structure optimization.Furthermore, the results indicate that the variation in carbon emission reduction due to digital governance can be attributed to differences in city administrative level, city size, and government capacity. In particular, digital governance plays a pivotal role in facilitating the sustainable transformation of resource-based cities.From the perspective of digital governance, this study provides effective recommendations and valuable insights for achieving low-carbon targets and promoting sustainable development of cities.

Price discovery in carbon exchange traded fund markets

In this study, we analyze the price discovery in four carbon exchange-traded funds (ETF) markets: (i) VanEck Low Carbon Energy ETF (Vaneck), (ii) iShares MSCI ACWI Low Carbon Target ETF (iShare), (iii) SPDR MCSI ACWI Climate Paris Aligned ETF (SPDR), and (iv) Xtrackers Emerging Markets Carbon Reduction and Climate Improvers ETF (Xtrackers) using daily closing prices of the four carbon ETFs from December 6, 2018, to November 30, 2022. All four ETF prices are found to have a single unit root implying the efficiency of these ETF markets (LeRoy 1989). However, Johansen's (1991) cointegration test reveals that these four ETFs are driven by not one but three common stochastic trends. Further Analysis reveals that iShares and SPDR markets are driven by the same market force (common stochastic trend). Based on the generalized information share (GIS), we find that approximately 57.89% and 42.11% of the price discovery occurs in the iShares and SPDR markets, respectively. We further analyze the impact of the COVID-19 pandemic by dividing the whole sample into pre-COVID and COVID subsamples. In the pre-COVID period, the GIS measures for the iShares and SPDR are 88.69% and 11.31%, respectively. However, GIS measures for the iShares and SPDR are 1.04% and 98.96%, respectively, in the COVID period indicating a significant impact of COVID-19 on price discovery.

Photothermal Cocatalytic Carbonylation of Isobutyl Amine with CO2 over Bi2O3 Polymorphs under Visible-Light Irradiation

Effective capture and utilization of CO2 is critical to reduce greenhouse gas emissions and to reach the low-carbon economy target. Herein, bismuth oxides with four different crystallized phases (α-, β-, δ-, γ-) are successfully synthesized and employed for the first time as photo, thermal, and photothermal catalysts for the successful catalytic carbonylation of isobutyl amine with CO2 to N,N′-diisobutylurea. The results displayed that the photothermal catalytic performances of Bi2O3 polymorphs followed the order of α-Bi2O3 > δ-Bi2O3 > γ-Bi2O3 > β-Bi2O3, in which the conversion of i-BuNH2 and the selectivity of N,N′-diisobutylurea for α-Bi2O3 was 50.38% and 91.79%, respectively, using N-methyl-2-pirrolidinone (NMP) as solvent and 500 W Xe lamp as the light source under the conditions of 1.0 MPa CO2 (initial pressure at room temperature) and 4 h reaction time at 100 °C. Further characterization of Bi2O3 polymorphs including XRD, SEM, BET, XPS, EPR, TPC, PL, and UV–vis absorption spectra reveals that such differences in the photothermal catalytic activity of Bi2O3 could be closely related to the efficiencies of photoinduced carriers separation. And the surface oxygen vacancies rather than bulk oxygen vacancies are favorable for the improvement of their both thermal and photothermal catalytic performances in the carbonylation of i-BuNH2 with CO2.

Greenhouse gas emissions from extractive industries in a globalized era

The extractive industry consumes vast amounts of energy and is a major contributor to greenhouse gas (GHG) emissions. However, its climatic impacts have not yet been fully accounted for. In this study, we estimated the GHG emissions from extractive activities globally with a focus on China, and assessed the main emission drivers. In addition, we predicted the Chinese extractive industry emissions in the context of global mineral demand and cycling. As of 2020, GHG emissions from the global extractive industry had reached 7.7 billion tons of CO2 equivalents (CO2e), accounting for approximately 15.0% of the global anthropogenic GHG emissions (excluding GHG emissions from land use, land-use change, and forestry activities (LULUCF), with China being the largest emitter, accounting for 3.5% of global emissions. Extractive industry GHG emissions are projected to peak by 2030 or even earlier to achieve low-carbon peak targets. The most critical pathway for reducing GHG emissions in the extractive industry is to control emissions from coal mining. Therefore, reducing methane emissions from mining and washing coal (MWC) should be prioritized.

Effects of urbanization on CO2 emissions, water use and the carbon-water coupling in a typical dual-core urban agglomeration in China

Cities are the main carbon emitters and water consumers, therefore the development of cities is closely relative to carbon-water coupling, but the changes of this relationship during the urbanization is unclear. As a typical emerging dual-core urban agglomeration, carbon-water coupling during the urbanization process in Chengdu-Chongqing urban agglomeration (CCUA) is beneficial for achieving the goal of carbon peaking by 2030 and carbon neutralization by 2060 committed by the Chinese Government. Results showed that economic growth mainly promoted the increase of carbon emissions and water use while the intensity effect mainly restrained their growth. Meanwhile, the decoupling between CO2 emissions and economy was increasing while the coupling between water use and economy was strengthened. These relationships promoted CCUA to enter a low-carbon development period after 2011, but the growth of water use has not been effectively suppressed. This indicated that CCUA has partly achieved the low carbon target but water-saving strategies should be paid more attention.

Greening strategy through implementation of sustainable landscape design towards low carbon school

The increased societal attention and urgency towards combating global climate change and transitioning the position towards Low Carbon Cities (LCC) has prompted many green initiatives developed by government agencies including schools to seek solutions through promoting eco-school planning development as part of the Environmental Education (EE) awareness being emphasis in curricula. This research explores the underlying mechanism of the greening elements as one of the planning initiatives which enable the inclusion of how low carbon practice action plans can be conducted in school. The methodology adopted emphasized the ground case study at Sekolah Kebangsaan Tangok, Bachok, Kelantan to testify to the integration of theory and practice of sustainable low carbon in the school community with environmental education. Such integration draws on attention to contextual knowledge of reducing carbon dioxide emissions as one of the most important factors in the implementation and execution of greening components for a sustainable school program. The discussion of findings concentrated on the implementation of greening strategies from sustainable landscape design and framework for carbon measures from three components, which are the trajectory of low carbon target, benefits analysis matrix, and constraint analysis that can be implemented in school to track the level of CO2 emissions and sequestration. This research provides a significant contribution in creating ‘commercialized’ environmental knowledge to the school communities that paved the way towards transition for Low Carbon Society as the social sustainable strategy that inculcates climate change adaptation for the future generation.

Safe-haven properties of green bonds for industrial sectors (GICS) in the United States: Evidence from Covid-19 pandemic and Global Financial Crisis

The Covid-19 pandemic unfolds the vulnerability of financial markets at the time of rare disasters. To hedge the mean-dependent risk, investors rely upon traditional assets such as gold; however, the tail-dependent risk, especially during market turbulence, considerably dampened the hedging effectiveness. On the contrary, green bonds emphasize sustainable investment in the long term and have become an inevitable tool to hedge against financial risks, and climate risks, and rare disasters. Thus, this study explores the hedging and safe haven aspects of the bullish market of green bonds against bearish markets of industry sectors across the United States (U.S.) over the period of 1st January 2008 to 7th May 2021, including the Global Financial Crisis and the Covid-19 pandemic. The findings of cross-quantilogram analysis disclose that green bonds reap diversification benefits during overall market conditions as well as market turmoil, hence confirm the safe-haven behavior of green bonds. Furthermore, our results disclose that the potential role of investment in green bonds can reboot the economy without affecting low-carbon transition targets.

Investigating the rationale for low-carbon production techniques in agriculture for climate change mitigation and fostering sustainable development via achieving lowcarbon targets.

In China, agricultural activities are a major source of greenhouse gas emissions, ranking second only to another significant source. This presents a significant obstacle to reducing emissions and jeopardizes both the availability of food and the sustainable growth of agriculture. It is primarily the farmers who utilize cultivated land and are thus accountable for the initiation of these emissions. Farmers' role is significant in adopting green and low-carbon (LC) agricultural production practices, and their actions are directly tied to the achievement of the dual goals of carbon reduction. Understanding their motivations for engaging in LC production and the factors that influence their willingness to do so is important for both theory and practice. In this study, data was collected from 260 questionnaires in 13 counties across five major cities in Shaanxi Province. The purpose was to identify factors that impact farmers' motivation and willingness to engage in LC agriculture using linear regression analysis. A structural equation model was constructed to better understand the underlying mechanisms that influence farmers' actions towards LC farming practices. The study's findings indicate that (1) farmers' behavior towards LC production practices is notably impacted by internal motivation based on joy and internal motivation based on responsibility (IMR); (2) IMR has the most pronounced effect on farmers' adoption of LC production practices; (3) the internal motivation based on joy, IMR, behavior attitude, subjective norm, and perceived behavior control are related to each other; and (4) the multi-group analysis of the data indicates that the impact of internal motivation based on joy and IMR on adopting sustainable farming practices may vary among different groups. It is essential to support farmers who have strong intrinsic motivation to engage in sustainable agriculture. Additionally, policymakers must promote positive attitudes towards sustainable farming to achieve the desired environmental (LC) objectives.

Does “low-carbon pilot policy” affect the carbon intensity of construction industry? Exploring the implementation mechanism and effectiveness in China

PurposeCarbon reduction in the construction industry is related to the achievement of carbon emission peaks and carbon neutrality targets. Therefore, exploring the influence of current carbon reduction policies on the construction industry is necessary. China’s low-carbon pilot (LCP) policy has been extensively studied, while LCPs mechanism and effectiveness on carbon reduction in the construction industry remain to be explored.Design/methodology/approachThis study selected four provincial LCP regions as case studies and adopted the grounded theory method for case studies to analyze the implementation mechanism of the LCP policy on carbon reduction in the construction industry. Then, this study adopted the propensity score matching and difference-in-differences regression (PSM-DID) approach to evaluate the influence of the LCP policy on carbon intensity (CI) in the construction industry by using panel data taken from 30 provinces in China between 2008 and 2017.FindingsThe authors found that (1) the LCP policy promotes carbon reduction in the construction industry through the crossing implementation mechanism of five vertical support approaches and five horizontal support approaches. (2). The LCP policy can significantly reduce CI in the construction industry.Originality/valueThe study not only explored how is the LCP policy implemented, but also examined the effectiveness of the LCP policy in the construction industry. The policy implications of this study can help policy-makers better achieve low-carbon development targets in the construction industry.

Identifying the critical factors of transmission efficiency loss in China’s natural gas network

China’s market-oriented reform supports the sustainable development of energy mix and the low-carbon target, and natural gas has bridged the transition from traditional fossil energy to clean and renewable energies. The third-party access policy, launched recently by China’s natural gas market, drives the decouple between gas trade and transport. The decouple might lead to the transmission resources of physical network not optimally used, which is caused by the contractual arrangement between entry and exit capacities in commercial network. Aiming at this issue, we established a mathematical programming with equilibrium constraints (MPEC) to integrate the allocations of commercial capacity and physical flows, based on a minimum cost maximum flow problem (MCMF) abstracted from China’s existing gas network. The MPEC model was then used to strategically evaluate the transmission efficiency, and identify the critical factors of its loss. Our results show that there is transmission efficiency loss of China’s gas network from the shortage of geospatial gas supply and the invisible segmentation of gas network due to interdicted cost of pipeline, bottleneck of pipeline capacity and economic radius of gas supply chains to transport gas. Therefore, the critical factor of the loss to be identified will be helpful for strategically reducing the cost of decoupling gas trade and transport.

Two stage robust planning of park integrated energy system considering low carbon

The development of integrated energy systems is a significant way of improving energy efficiency and encouraging renewable energy absorption. However, the uncertainty of renewable energy and loads raise severe challenges to integrated energy system planning. Besides, under the low carbon background, the relationship between reducing carbon emissions and increasing the absorption of renewable energy is not investigated clearly in the planning of the park integrated energy system. Thus, this paper proposes a two-stage robust planning method considering low carbon and uncertainty. Firstly, the input-output model of energy conversion equipment in the park integrated energy system is described. Secondly, the objective function and constraints and are set up. Specifically, the carbon emission limits and renewable energy penetration target are introduced in the constraints. On this basis, the two-stage robust planning model with min-max-min structure is established, after transformation, column-and-constraint generation is used for the solution. Case study shows the ability and cost of the park integrated energy system to promote low-carbon emission reduction and renewable energy consumption. Moreover, it proves that although there is some synergy between the low carbon target and the renewable energy consumption target, maximum renewable energy consumption does not mean minimum carbon emissions, and vice versa, and in some cases increasing renewable energy penetration does not necessarily reduce carbon emissions.

Balancing renewable energy and river resources by moving from individual assessments of hydropower projects to energy system planning

As governments and non-state actors strive to minimize global warming, a primary strategy is the decarbonization of power systems which will require a massive increase in renewable electricity generation. Leading energy agencies forecast a doubling of global hydropower capacity as part of that necessary expansion of renewables. While hydropower provides generally low-carbon generation and can integrate variable renewables, such as wind and solar, into electrical grids, hydropower dams are one of the primary reasons that only one-third of the world’s major rivers remain free-flowing. This loss of free-flowing rivers has contributed to dramatic declines of migratory fish and sediment delivery to agriculturally productive deltas. Further, the reservoirs behind dams have displaced tens of millions of people. Thus, hydropower challenges the world’s efforts to meet climate targets while simultaneously achieving other Sustainable Development Goals. In this paper, we explore strategies to achieve the needed renewable energy expansion while sustaining the diverse social and environmental benefits of rivers. These strategies can be implemented at scales ranging from the individual project (environmental flows, fish passage and other site-level mitigation) to hydropower cascades to river basins and regional electrical power systems. While we review evidence that project-level management and mitigation can reduce environmental and social costs, we posit that the most effective scale for finding balanced solutions occurs at the scale of power systems. We further hypothesize that the pursuit of solutions at the system scale can also provide benefits for investors, developers and governments; evidence of benefits to these actors will be necessary for achieving broad uptake of the approaches described in this paper. We test this hypothesis through cases from Chile and Uganda that demonstrate the potential for system-scale power planning to allow countries to meet low-carbon energy targets with power systems that avoid damming high priority rivers (e.g., those that would cause conflicts with other social and environmental benefits) for a similar system cost as status quo approaches. We also show that, through reduction of risk and potential conflict, strategic planning of hydropower site selection can improve financial performance for investors and developers, with a case study from Colombia.

Особенности и эффективность наносекундной лазерной абляции высокоуглеродистой стали сканирующим пучком импульсного излучения Yb:YAG лазера

The experiments results on the ablation of high-carbon (> 97 % Fe, 1.3 % C) and low-carbon (> 97 % Fe, 0.3 % C) steel targets by a nanosecond pulse laser radiation scanning beam are presented. The dependence of the depth and energy efficiency of ablation on the power density in the range q = 4·108 – 1010 W/cm2 has been determined. It has been established that the maximum efficiency of material removal is achieved at q = 4·109 W/cm2 for a high-carbon steel target and in the range q = 7·108 – 5·109 W/cm2 for a low-carbon steel target. The size distribution of ejected microparticles was determined. It has been established that a back flow of particles occurs upon irradiation of high-carbon steel and the flow origin mechanism is associated with nanosized condensate particles. Based on the reflectivity measurements and the electron microscopy microstructure study of the irradiated surface, it has been suggested that the mechanism for the higher efficiency of ablation of high-carbon steel compared to low-carbon steel is the condensation process of supersaturated carbon vapors on the target surface that increases the irradiated target surface absorptivity and, consequently, the material removal efficiency of the subsequent scanning pass is increased.

Research on operation decision of thermal power units with both electricity spot trading and carbon emissions trading

Low carbon operation is one of the goals of the energy revolution, and the thermal power units are required to achieve more carbon emission reduction for achieving the carbon peaking and carbon neutrality goals. To help thermal power units participating in both electricity spot trading and carbon trading to optimize their operational decisions, a cost-benefit model for thermal power units that take into account both electricity spot trading and carbon trading is built from two perspectives: low-carbon technology and low-carbon policy, combining low-carbon instruments with market mechanisms. The objective is to maximize the profitability of the unit, and the effectiveness of the proposed model is proved by simulation using actual measurement data. The results proves that the proposed model can balance low carbon target and economic aspects, and is also useful for thermal power units to optimize their operational decisions under different scenarios.

Deep neural networks for estimation of temperature values for thermal ageing evaluation of nuclear power plant equipment

The average age of the world's nuclear power plants in operation today is over 30 years, which will force big decisions in the next decade related to the continuity of operation of these plants. If most of these plants are shut down after 40 years, it could place considerable stress on electricity systems, and push the Paris treaty's low-carbon energy production targets by 2050 even further out of reach. When NPPs are reaching the end of its lifetime, a license renewal is required. In the license renewal process it is necessary to present a set of documents, one of which is an environmental qualification program of electrical equipment, which includes a survey of the ageing management of all structures, systems and components, mainly those related to safety equipment. The main ageing affects are changes in physical properties due to the temperature, radiation, humidity, etc. Received by structures, systems and components since their operation starts, but these data may not be available, for various reasons, and the ageing studies will be hampered. In this article is proposed a methodology based on Deep Neural Network in order to simulate virtual temperature sensors, using as parameters measurements of real plant detectors in order to support ageing evaluation. For implementation and testing of the proposed approach, data from Brazilian pressurized water reactor were used. The results of the experiments described here with the proposed methodology show a promising path for solving this problem.

Do globalization and nuclear energy intensify the environmental costs in top nuclear energy-consuming countries?

Nuclear energy is considered an effective alternative to ensure global energy safety, and it has recently started to be promoted as a climate change mitigation solution to achieve low-carbon energy transition targets. Considering this view, this study aims to assess the environmental cost reduction by using nuclear energy efficiency and technological innovation from the prospects of the globalization process. Therefore, the relationship among carbon emissions, nuclear energy, globalization, and technological innovation was assessed in the top ten nuclear energy-consuming countries from 1990 to 2017 while controlling for economic growth and renewable energy. This study applied Common Correlated Effects Mean Group (CCEMG), Augmented Mean Group (AMG), and Dumitrescu-Hurlin causality techniques for model estimation that solves the problem of cross-sectional dependence and slope heterogeneity. The empirical results indicated that nuclear energy and technological innovation diminish environmental costs by reducing carbon emissions. However, globalization increases environmental costs by releasing more carbon emissions into the atmosphere. Moreover, bidirectional causality exists among nuclear energy, renewable energy, and carbon emissions. Consequently, the highest nuclear energy-consuming countries must utilize nuclear energy efficiency to control environmental costs and a cost-effective path to a low-carbon economy. Finally, this perspective intended to appeal to policymakers to do a better job of substantiating their decisions.

Analysis on Energy Conservation and Emission Reduction Efficiency and Influencing Factors for Ports around Bohai in China under the Low Carbon Target

The ports around Bohai in China were taken as the object of study in this research. In light of the panel data from 2014 to 2020, the super-efficiency SBM model was applied to measure and calculate the energy conservation and emission reduction efficiency of ports. In addition, the indicator system of influencing factors for energy conservation and emission reduction efficiency was constructed on the basis of the STIRPAT model, which provided a brand-new research perspective on environmental regulation, and the research method of ridge regression was applied for studying the influencing factors of energy conservation and emission reduction. The conclusion shows: except for the energy conservation and emission reduction efficiency of Qingdao port and Tianjin port reaching the significant degree, the energy conservation and emission reduction efficiency of other ports turned out to be invalid in the years of measurement, manifesting a relatively lower situation in the overall energy conservation and emission reduction efficiency for ports around Bohai; the major influencing factor for the energy conservation and emission reduction efficiency of the ports around Bohai is environmental regulation, which has played a prominent positive role; the technical factors also play an active role in enhancing energy conservation and emission reduction efficiency, and present a reversed tendency with resource endowment; the comprehensive economic strength can contribute to the efficiency of energy conservation and emission reduction of the ports.

Optimization of Spatial Land Use Patterns with Low Carbon Target: A Case Study of Sanmenxia, China.

Land use change is an important factor in atmospheric carbon emissions. Most of the existing studies focus on modeling the land use pattern for a certain period of time in the future and calculating and analyzing carbon emissions. However, few studies have optimized the spatial pattern of land use from the perspective of the impact of carbon emission constraints on land use structure. Therefore, in this study, the effects of land use change on carbon emissions from 1990 to 2020 were modeled using a carbon flow model for Sanmenxia, Henan, China, as an example. Then, the land use carbon emission function under the low carbon target was constructed, and the differential evolution (DE) algorithm was used to obtain the optimized land use quantity structure. Finally, the PLUS model was used to predict the optimal spatial configuration of land use patterns to minimize carbon emissions. The study produced three major results. (1) From 1990 to 2020, the structural change of land use in Sanmenxia mainly occurred between cultivated land, forest land, grassland and construction land. During this period of land use change, the carbon emissions from construction land first increased and then decreased, but despite the decrease, carbon emissions still exceeded carbon sinks, and the carbon metabolism of land use was still far from equilibrium. (2) Between 2010 and 2020, the area of cultivated land began to decrease, and the area of forest land rapidly increased, and land-use-related carbon emissions showed negative growth. This showed that the structural adjustment of energy consumption in Sanmenxia during the period decreased carbon emissions in comparison with the previous period. (3) A comparison of predicted optimized land use patterns with land use patterns in an as-is development scenario showed a decrease in construction land area of 23.05 km2 in 2030 with a steady increase in forest land area and a decrease in total carbon emission of 20.43 t. The newly converted construction land in the optimized land use pattern was concentrated in the ribbon-clustered towns built during urban expansion along the Shaanling basin of the Yellow River and the Mianchi-Yima industrial development area.

Would Financial Development Help China Achieve Carbon Peak Emissions?

China has committed to reaching carbon peak before 2030. To realize the carbon peak goal, financial development plays an essential role in developing a green economy. Based on the panel data of 30 provinces in China from 2006 to 2019, this paper explores the impact of financial development on carbon intensity both theoretically and empirically. A financial development index system is constructed and computed using the entropy method. A spatial lag panel data model is employed to empirically test the interaction effect of financial development on carbon intensity. Moreover, the mediating effects of industrial upgrading and technological innovation are further investigated. The results show that: first, carbon intensity generates strong spatial spillover effects between provinces in China. Second, financial development significantly reduces carbon intensity, and is most pronounced in central China, followed by western and eastern China. Third, industrial upgrading and technological innovation are important channels to assist financial development in cutting down carbon intensity, and both produce positive spatial spillover effects. These findings suggest that inter-regional cooperation and coordination on financial development, industrial upgrading, and technological innovation are conducive to achieving low-carbon development targets. This research not only has practical significance to China, but also provides global reference value to other countries.

We're in this together: Sustainable energy and economic competitiveness in the EU

The paper elaborates an empirical study on the relation between trade competitiveness and energy policy based on a bilateral gravity model applied to a panel of 19 EU countries over the period 1990–2015. We focus on harmonisation of domestic policies and on the speed of convergence towards low-carbon energy targets. By explicitly connecting international trade with innovation and economic competitiveness, we fill a gap in the literature on the sustainable energy transition. Our analysis yields three main findings. First, bilateral policy alignment matters for trade performance. Second, the more balanced and comprehensive the domestic policy mix, the higher the export capacity. Third, countries at the frontier of the EU transition process gain market shares at the expense of those lagging behind.