Scenario analysis of the Indonesia carbon tax impact on carbon emissions using system dynamics modeling and STIRPAT model

This study aims to develop a system dynamic(SD)forecasting model based on the STIRPAT model to forecast the effect of an IDR 30 per kg CO_(2)e carbon tax on carbon emissions,estimate future carbon emissions under ten scenarios,without and with the carbon tax,and estimate the environmental Kuznets curve(EKC)to predict Indonesia’s carbon emission peak.Carbon emission drivers in this study are decomposed into several factors,namely energy structure,energy intensity,industrial structure,GDP per capita,population,and fixed-asset investment.This study included nuclear power utilization starting in 2038.The research gaps addressed by this study compared to previous research are(1)use of the ex-ante approach,(2)inclusion of nuclear power plants,(3)testing the EKC hypothesis,and(4)contribution to government policy.The simulation results show that under the carbon tax,carbon emissions can be reduced by improving renewable energy structures,adjusting industrial structures to green businesses,and emphasizing fixed asset investment more environmentally friendly.Moreover,the result approved the EKC hypothesis.It shows an inverse U-shaped curve between GDP per capita and CO_(2)emissions in Indonesia.Indonesia’s fastest carbon emission peak is under scenario seven and is expected in 2040.Although an IDR 30 per kg CO_(2)e carbon tax and nuclear power will take decades to reduce carbon emissions,the carbon tax can still be a reference and has advantages to implement.This result can be a good beginning step for Indonesia,which has yet to gain experience with a carbon tax that can be implemented immediately and is helpful to decision-makers in putting into practice sensible measures to attain Indonesia’s carbon emission peaking.This research provides actionable insights internationally on carbon tax policies,nuclear energy adoption,EKC dynamics,global policy implications,and fostering international cooperation for carbon emission reductions.

Regional Climate Damage Quantification and Its Impacts on Future Emission Pathways Using the RICE Model

This study quantified the regional damages resulting from temperature and sea level changes using the Regional Integrated of Climate and Economy(RICE)model,as well as the effects of enabling and disabling the climate impact module on future emission pathways.Results highlight varied damages depending on regional economic development and locations.Specifically,China and Africa could suffer the most serious comprehensive damages caused by temperature change and sea level rise,followed by India,other developing Asian countries(OthAsia),and other high-income countries(OHI).The comprehensive damage fractions for China and Africa are projected to be 15.1%and 12.5%of gross domestic product(GDP)in 2195,with corresponding cumulative damages of 124.0 trillion and 87.3 trillion United States dollars(USD)from 2005 to 2195,respectively.Meanwhile,the comprehensive damage fractions in Japan,Eurasia,and Russia are smaller and projected to be lower than 5.6%of GDP in 2195,with cumulative damages of 6.8 trillion,4.2 trillion,and 3.3 trillion USD,respectively.Additionally,coastal regions like Africa,the European Union(EU),and OHI show comparable damages for sea level rise and temperature change.In China,however,sea level-induced damages are projected to exceed those from temperature changes.Moreover,this study indicates that switching the damage modules on or off affects the regional and global emission trajectories,but the magnitude is relatively small.By 2195,global emissions under the experiments with all of the damage modules switched off,only the sea level damage module switched on,and only the temperature damage module switched on,were 3.5%,2.3%and 1.2%higher than those with all of the damage modules switched on,respectively.

Synergistic dance of digital economy and green finance on carbon emissions:Insights from China

China has recently implemented a dual-carbon strategy to combat climate change and other environmental issues and is committed to modernizing it sustainably.This paper supports these goals and explores how the digital economy and green finance intersect and impact carbon emissions.Using panel data from 30 Chinese provinces over the period 2011-2021,this paper finds that the digital economy and green finance can together reduce carbon emissions,and conducts several robustness tests supporting this conclusion.A heterogeneity analysis shows that these synergistic effects are more important in regions with low levels of social consumption Meanwhile,in the spatial dimension,the synergistic effect of the local digital economy and green finance adversely impacts the level of carbon emissions in surrounding areas.The findings of this paper provide insights for policymakers in guiding capital flow and implementing carbon-reduction policies while fostering the growth of China’s digital economy and environmental sustainability.

Structural Characteristics and Influencing Factors of Carbon Emission Spatial Association Network:A Case Study of Yangtze River Delta City Cluster,China

City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.

Modeling of the effect of hydrogen injection on blast furnace operation and carbon dioxide emissions

The effect of hydrogen injection on blast furnace operation and carbon dioxide emissions was simulated using a 1D steady-state zonal model.The maximum hydrogen injection rate was evaluated on the basis of the simulation of the vertical temperature pattern in the blast furnace with a focus on the thermal reserve zone.The effects of blast temperature and oxygen enrichment were also examined to estimate coke replacement ratio,productivity,hydrogen utilization efficiency,and carbon dioxide emission reduction.For blast temperature of 1200℃,the maximum hydrogen injection rate was 19.0 and 28.3 kg of H_(2)/t of hot metal(HM)for oxygen enrichment of 2vol%and 12vol%,respectively.Results showed a coke replacement ratio of 3-4 kg of coke/kg of H_(2),direct CO_(2) emission reduction of 10.2%-17.8%,and increased productivity by up to 13.7%depending on oxygen enrichment level.Increasing blast temperature further reduced the direct CO_(2) emissions.Hydrogen utilization degree reached the maximum of 0.52-0.54 H_(2)O/(H_(2)O+H_(2)).The decarbonization potential of hydrogen injection was estimated in the range from 9.4 t of CO_(2)/t of H_(2) to 9.7 t of CO_(2)/t of H_(2).For economic feasibility,hydrogen injection requires revolutionary progress in terms of low-cost H_(2) generation unless the technological change is motivated by the carbon emission cost.Hydrogen injection may unfavorably affect the radial temperature pattern of the raceway,which could be addressed by adopting appropriate injection techniques.

Intensity Allocation Criteria of Carbon Emissions Permits and Regional Economic Development in China——Based on a 30-Province/Autonomous Region Computable General Equilibrium Model

The intensity allocation criteria of carbon emissions permits and its influence on China＇s regional development are analyzed through the 30-province/autonomous region computable general equilibrium （CGE） model. Simulation results show that： industrial intensity criteria without taking regional economic development into account deepen the unbalance of regional economic development; regional intensity criteria without taking industrial properties into account exert little negative impact on regional harmonious development, but relatively high negative influence on high-carbon emission industries. The two-step allocation scheme that the central government allocates emissions permits to provincial governments based on regional economic development and then provincial governments allocate emissions permits to emission resources or entities based on industrial properties is a feasible and operable choice.

An Empirical Study on China＇s Energy Supply-and-Demand Model Considering Carbon Emission Peak Constraints in 2030

China＇s energy supply-and-demand model and two related carbon emission scenarios, including a planned peak scenario and an advanced peak scenario, are designed taking into consideration China＇s economic development, technological progress, policies, resources, environmental capacity, and other factors. The analysis of the defined scenarios provides the following conclusions： Primary energy and power demand will continue to grow leading up to 2030, and the growth rate of power demand will be much higher than that of primary energy demand. Moreover, low carbonization will be a basic feature of energy supply-and-demand structural changes, and non-fossil energy will replace oil as the second largest energy source. Finally, energy- related carbon emissions could peak in 2025 through the application of more efficient energy consumption patterns and more low-carbon energy supply modes. The push toward decarbonization of the power industry is essential for reducing the peak value of carbon emissions.

Economic development, energy demand, and carbon emission prospects ofChina's provinces during the 14th Five-Year Plan period: Application ofCMRCGE model

This study focuses on a national regional coordinated development strategy and adopts China Multi-Regional Computable General Equilibrium model to analyze the economic and social development, energy demand, and carbon emissions of the provinces during the 14th Five-Year Plan (FYP, 2021 2025) period based on the economic development and energy demand since the New Normal. The main conclusions are the following: 1) Under the guidance of the regional coordinated development strategy, 13 provinces/municipalities are expected to have a per capita gross domestic product (GDP) of more than US$15,000, and 16 provinces/municipalities will have a per capita GDP of US$10,000 15,000. All provincial economies are expected to achieve steady and rapid development by the end of the 14th FYP. 2) The total energy consumption of the provinces is expected to reach 5.45 Gtce (excluding Tibet) in 2025, and the average annual growth rate is approximately 1.5%. The growth of energy demand will remain in low speed. The key point of energy demand will gradually shift from the eastern to the middle area, while the proportion of energy use in the western provinces will remain stable, which is consistent with the economic development stage and regional coordinated development strategy. 3) The annual average carbon intensity (mainly considering carbon emissions from energy use) of the provinces will approximately with most provinces dropping by over 4.0%. The trend of a considerable decline in carbon intensity, as observed in recent years, is expected to continue.

Assessing China 2030 carbon emissions from fossil fuels:based on system dynamics model

The Chinese government has set ambitious targets to reduce the per unit of GDP by 40% ~45% during 2005 to 2020 and achieve the intensity peaking of carbon emissions of CO2 emissions a- round 2030. The T21 national development model for China was developed for the purpose of analy- zing the effects of long-term national policies that relate to carbon emissions, loss of farm land, water shortage, energy security, food security, and their contributions to this reduction target. The focus of this paper is on the policies that have substantial impacts on carbon emissions from fossil fuels. Four scenarios are developed with the model to simulate future carbon emissions ： 1 ） the BAU （ busi- ness as usual） scenario, showing the likely results of continuing current policies; 2 ） the TECH （technology） scenario showing the effects of more investment in renewable energy sources and promoting more energy efficient technologies; 3 ） the BEHAVIOR scenario, showing how government tax and price policies, together with public education programs, would instigate behaviour changes towards more sustainable living; and 4 ） the TECH＆BEHA scenario, which shows the results of combining scenarios 2 and 3. The simulation results show that CO2 emissions reduction targets of China are achievable, but also require great effort to put in.

Estimation of Building’s Life Cycle Carbon Emissions Based on Life Cycle Assessment and Building Information Modeling: A Case Study of a Hospital Building in China

Throughout the life cycle, the buildings emit a great deal of carbon dioxide into the atmosphere, which directly leads to aggravation in the greenhouse effect and becomes a severe threat to the environment and humans. Researchers have made numerous efforts to accurately calculate emissions to reduce the life cycle carbon emissions of residential buildings. Nevertheless, there are still difficulties in quickly estimating carbon emissions in the design stage without specific data. To fill this gap, the study, based on Life Cycle Assessment (LCA) and Building Information Modeling (BIM), proposed a quick method for estimating Building’s Life Cycle Carbon Emissions (BLCCE). Taking a hospital building in Chuzhou City, Anhui Province, China as an example, it tested its possibility to estimate BLCCE. The results manifested that: 1) the BLCCE of the project is 40,083.56 tCO2-eq, and the carbon emissions per square meter per year are 119.91 kgCO2-eq/(m2·y);2) the stage of construction, operational and demolition account for 7.90%, 91.31%, and 0.79% of BLCCE, respectively;3) the annual carbon emissions per square meter of hospital are apparently higher than that of villa, residence, and office building, due to larger service population, longer daily operation time, and stricter patient comfort requirements. Considering the lack of BLCCE research in Chinese hospitals, this case study will provide a valuable reference for the estimated BLCCE of hospital building.

Research on whole life cycle carbon emission model of typical buildings

Based on the theory of life cycle assessment(LCA),this article analyzes the influence factors on carbon emissions from residential buildings.In the article,the life cycle of residential buildings has been divided into five stages:building materials production period,construction period,operation and maintenance period,demolition period,and solid waste recycle and disposal period.Based on this definition,the authors provide a theoretical model to calculate carbon emissions of residential building life cycle.In particular,the factor of human activities was introduced in the calculation of carbon emissions from the buildings.Furthermore,the authors put forward a model for calculation with the unit of carbon emissions for per-capita living space.

Statistical Model for Estimating Carbon Dioxide Emissions from a Light-Duty Gasoline Vehicle

The objective of this research was development of a statistical model for estimating vehicle tailpipe emissions of carbon dioxide (CO2). Forty hours of second-by-second emissions data (144,000 data points) were collected using an On-Board emissions measurement System (Horiba OBS-1300) installed in a 2007 Dodge Charger car. Data were collected for two roadway types, arterial and highway, around Arlington, Texas, and two different time periods, off peak and peak (both a.m. and p.m.). Multiple linear regression and SAS software were used to build emission models from the data, using predictor variables of velocity, acceleration and an interaction term. The arterial model explained 61% of the variability in the emissions;the highway model explained 27%. The arterial model in particular represents a reasonably good compromise between accuracy and ease of use. The arterial model could be coupled with velocity and acceleration profiles obtained from a micro-scale traffic simulation model, such as CORSIM, or from field data from an instrumented vehicle, to estimate percent emission reductions associated with local changes in traffic system operation or management.

Review of Carbon Emissions Trading Production Model and Research on Its Applications in China

With the Kyoto Protocol entering into effect in many countries one after another,carbon trading has come into being and developed quickly.China is the main supplier of carbon emissions rights in the world,but such transactions are still in the stage of Clean Development Mechanism (CDM) projects without its own trading system,which is not conducive for China to win the rights of carbon pricing in the international market.Low-carbon and emissions reduction is the international trend nowadays,and therefore,it is particularly necessary and urgent to investigate the issue of carbon trading in China.In this paper,the authors have reviewed Putty-Clay Vintage,which is a model of production function for carbon trading,revealing the main points,contributions and shortcomings of the model.Combined with China's national conditions,the authors have investigated the application of this model in China's carbon trading from four different angles,including enterprise production optimization,financial market development,national macro-economy,and the allocation of emission quota.This study aims to provide China's enterprises with an analytical framework when participating in carbon trading in the future and it is beneficial for them to make optimal production planning when considering the cost of carbon emissions reduction.

Research on Spatial-Temporal Characteristics and Driving Factor of Agricultural Carbon Emissions in China

Macroscopic grasp of agricultural carbon emissions status, spatial-temporal characteristics as well as driving factors are the basic premise in further research on China’s agricultural carbon emissions. Based on 23 kinds of major carbon emission sources including agricultural materials inputs, paddy ifeld, soil and livestock breeding, this paper ifrstly calculated agricultural carbon emissions from 1995 to 2010, as well as 31 provinces and cities in 2010 in China. We then made a decomposed analysis to the driving factors of carbon emissions with logarithmic mean Divisia index （LMDI） model. The results show：（1） The amount of agricultural carbon emissions is 291.1691 million t in 2010. Compared with 249.5239 million t in 1995, it increased by 16.69%, in which, agricultural materials inputs, paddy ifeld, soil, enteric fermentation, and manure management accounted for 33.59, 22.03, 7.46, 17.53 and 19.39%of total agricultural carbon emissions, respectively. Although the amount exist ups and downs, it shows an overall trend of cyclical rise; （2） There is an obvious difference among regions：the amount of agricultural carbon emissions from top ten zones account for 56.68%, while 9.84%from last 10 zones. The traditional agricultural provinces, especially the major crop production areas are the main source regions. Based on the differences of carbon emission rations, 31 provinces and cities are divided into ifve types, namely agricultural materials dominant type, paddy ifeld dominant type, enteric fermentation dominant type, composite factors dominant type and balanced type. The agricultural carbon emissions intensity in west of China is the highest, followed by the central region, and the east zone is the lowest; （3） Compared with 1995, efifciency, labor and structure factors cut down carbon emissions by 65.78, 27.51 and 3.19%, respectively;while economy factor increase carbon emissions by 113.16%.

Multi-model comparison of CO2 emissions peaking in China:Lessons from CEMF01 study

The paper summarizes results of the China Energy Modeling Forum's(CEMF)first study.Carbon emissions peaking scenarios,consistent with China's Paris commitment,have been simulated with seven national and industry-level energy models and compared.The CO2 emission trends in the considered scenarios peak from 2015 to 2030 at the level of 9e11 Gt.Sector-level analysis suggests that total emissions pathways before 2030 will be determined mainly by dynamics of emissions in the electric power industry and transportation sector.Both sectors will experience significant increase in demand,but have low-carbon alternative options for development.Based on a side-by-side comparison of modeling input and results,conclusions have been drawn regarding the sources of emissions projections differences,which include data,views on economic perspectives,or models'structure and theoretical framework.Some suggestions have been made regarding energy models'development priorities for further research.

Factors affecting the pilot trading market of carbon emissions in China

Climate change and carbon emissions are major problems which are attracting worldwide attention. China has had its pilot carbon emission trading markets in seven regions for more than 3 years. What affects carbon emission trading market in China is a big question. More attention is paid to how China promotes the carbon emission trading schemes in the whole country. This paper addresses concerns about the functioning of carbon emission trading schemes in seven pilot regions and takes the weekly data from November 25, 2013, to March 19, 2017. We employ a vector autoregressive model to study how coal price, oil price and stock index have affected the carbon price in China. The results indicate that carbon price is mainly affected by its own historical price; coal price and stock index have negative effects on carbon price, while oil price has a negative effect on carbon price during the first 3 weeks and then has a positive effect on carbon price. More regulatory attention and economic measures are needed to improve market efficiency, and the mechanisms of carbon emission trading schemes should be improved.

Analysis and forecast of residential building energy consumption in Chongqing on carbon emissions

Carbon emissions mainly result from energy consumption. Carbon emissions inevitably will increase to some extent with economic expansion and rising energy consumption. We introduce a gray theory of quantitative analysis of the energy consumption of residential buildings in Chongqing,China,on the impact of carbon emission factors. Three impacts are analyzed,namely per capita residential housing area,domestic water consumption and the rate of air conditioner ownership per 100 urban households. The gray prediction model established using the Chongqing carbon emission-residential building energy consumption forecast model is sufficiently accurate to achieve a measure of feasibility and applicability.

Digital economy,industrial structure,and carbon emissions:An empirical study based on a provincial panel data set from China

This paper uses the mediation effect and a spatial panel model using panel data from 30 provinces in China from 2011 to 2019 to study the relationship between the digital economy,industrial structure,and carbon emission.The research results show that the development of digital economy can effectively promote the reduction of carbon emissions.The development of the digital economy has a significant role in promoting the rationalization of the industrial structure.The digital economy not only directly suppresses carbon emissions,but also indirectly has a significant inhibitory effect on carbon emissions by promoting the rationalization and improvement of the industrial structure.The development of the digital economy suppresses the optimization of the industrial structure.The improvement of industrialization has hindered the industrialization process.It is necessary to strengthen research and development into digital technology and enhance the capacity of the digital economy to promote carbon emissions reduction.

How does ecological civilization construction affect carbon emission intensity?Evidence from Chinese provinces’panel data

Ecological civilization construction is a new concept and trend in the era of China's high-quality development.It requires the collaborative propulsion of an ecological economic civilization,ecological social civilization,and ecological environment civilization.Reducing carbon emission intensity is an important issue facing the Chinese government in the backdrop of global warming.Thus,studying the influence of ecological civilization construction on carbon emission intensity from different perspectives has important theoretical and practical significance.In this study,the influences of the three subsystems of an ecological civilization on carbon emission intensity are empirically analyzed using Chinese provincial panel data from 2004 to 2016 and a spatial Durbin model based on the STIRPAT model.First,the Moran's I of carbon emission intensity in Chinese provinces was between 0.425 and 0.473.This indicates positive spatial correlation and illustrates that the carbon emission intensity of China's provinces can influence each other.The reasons behind this correlation include close ties between neighboring provinces and similarities in natural,economic,and social characteristics.Second,the correlation coefficients of ecological economic civilization,ecological social civilization,and ecological environment civilization to carbon emission intensity are−4.743139,2.865884,and−0.3246447,respectively.This illustrates that an ecological economic civilization and ecological environment civilization can reduce carbon emission intensity,while an ecological social civilization can increase it.To reduce total carbon emission intensity,the three subsystems of ecological civilization should have a negative relationship with carbon emission intensity,so the effect of ecological social civilization on carbon emission intensity should be changed.Third,the spatial spillover effect of ecological social civilization did not pass the significance test.The correlation coefficients of spatial spillover effect to ecological economic civilization and ecological environment civilization are 2.046531 and−3.238323,respectively.Improving the ecological economic civilization can increase the carbon emission intensity of periphery provinces,while improving the ecological environment civilization can reduce it.Thus,it is necessary to enhance cooperation between periphery provinces and establish a trans-provincial cooperation mechanism for reducing carbon emissions.

Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City, China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.