Does carbon intensity constraint policy improve industrial green production performance in China? A quasi-DID analysis

Whether or not carbon regulation policies can achieve the “double dividend” of carbon reduction and economic growth is vital for realizing the sustainable development of a certain country. This paper investigates the effects of a carbon intensity constraint policy (CICP) that the Chinese government put forward in 2009 on the green production performance (GPP, i.e., the environmentally sensitive productivity growth considering carbon emissions to be an undesirable output) of industrial sector (the largest carbon emitter in China) for the first time. Based on a non-radial and non-oriented DEA (data envelopment analysis) measure method, we first adopt the Luenberger indicator to estimate the GPP of China's 36 industrial sub-sectors over 2001–2013. Furthermore, regarding the CICP proposed in 2009 as a natural experiment, we assess the effects of such a policy on China's industrial GPP by using the quasi-difference-in-differences (quasi-DID) method. The results show that China's industrial GPP presents a circuitous downward trend after experiencing a transient rise. The heterogeneity of the GPP among industrial sub-sectors exists, and the increase in industrial output is the crucial driver of improving the GPP. China's industrial GPP has deteriorated after implementing the CICP, and the negative effect of such a policy is larger and larger over time. Such empirical results indicate that although the carbon regulation policy in China has achieved a surface success, the policy causes a factor substitution effect to hinder the improvement of the GPP. Therefore, China's current CICP is not effective in realizing the “double dividend” of carbon reduction and industrial growth.     

Who turns the global thermostat and by how much?

Increasing attention is being given to the option of engineering the climate via Solar Radiation Management (SRM) as a potential component in future climate policies. We set up a quantitative model to analyze efficient levels of SRM deployment against the climatic and economic background conditions projected by the various Shared Socioeconomic Pathways (SSPs) baseline scenarios for the year 2050. The model combines three features of the data: i) SRM deployment is regionally uneven in the way it affects grid-cell temperature and precipitation, ii) temperature and precipitation affect Gross Value Added (GVA) at the grid-cell level and the effect for both takes the form of an inverted U-shape relationship, implying that optimal temperature and precipitation levels with respect to output do exist, and iii) different assumptions about economic growth and its distribution over regions, as projected by the SSPs, increase the relative share of global GVA for currently rather poor countries with high average temperatures. We find that in global terms, economically efficient levels of SRM are affected more by region-specific economic growth projections than by regional climate-change impacts. Globally, the economically efficient SRM level is proportional to the (global) GVA-weighted mean temperature increase, which varies considerably according to the various growth projections (for equal climatic background conditions). Achieving the optimal temperature in each scenario is constrained by the influence of SRM on precipitation.     

Bioenergy plantations or long-term carbon sinks? – A model based analysis

In order to mitigate climate change bio-productive land may be used mainly in two ways: afforestation with long-rotation forests with the primary aim to act as carbon sinks, and short-rotation forests that are used for energy purposes and thereby replace fossil fuels. Under an ambitious climate target, land that may be used for both bioenergy plantations and long-rotation forests, are likely to be scarce, and thereby competition between long-rotation forests and bioenergy plantations can be expected. The goal of the study is to analyze the cost-effectiveness of bioenergy plantations versus long-rotations forests aimed at capturing and storing carbon. The study is performed by solving and analyzing a linear optimization model that links the energy system, an afforestation sector and the pulp and timber market. Many earlier studies tend to suggest that long-rotation forests offer lower costs per ton of CO₂ avoided. Our study, however, shows that long-rotation forests for the purpose of carbon sequestration will not be cost-effective in the long run under a stringent climate policy. Thus, economic efficiency considerations tend to support short-rotation plantations for high carbon prices. The reason for this is that scarcity of land increases the opportunity cost of land, a feature which is generally not captured in static near-term analysis, but it is captured in a dynamic model like ours. For less stringent carbon targets long-rotation forests, that are harvested and sold as timber are cost-effective during a transient phase.     

How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics

Carbon allowances are a new class of financial instrument which aim to assist in limiting the extent and impact of global warming and climate change. The feedback mechanism in the “Carbon-Energy-Finance” system makes the information connectedness dynamics more complex since we add equity, bond and non-energy commodity assets into the system. Using modified error variance decomposition and network diagrams, we quantify and systematically analyze how the European carbon market connects with information from a wide range of other markets. Our results indicate: (i) the nature of information spillover changes over time, with system-wide return connectedness being higher and more variable than the volatility interdependence; (ii) both the oil and carbon markets closely connect with equity and non-energy commodity markets rather than bond markets; (iii) we identify three structural breaks in carbon volatility and their implication for carbon-finance linkages; (iv) financial risk-type macroeconomic factors make greater contributions to system-wide connectedness than commodity factors. These findings have economic implications for investors, portfolio managers and policymakers.     

How do China's petrochemical markets react to oil price jumps? A comparative analysis of stocks and commodities

The profound impacts of oil price jumps have caught the attention of scholars. Because the 2008 global financial crisis has seemingly already passed, the existence of oil price jumps is in doubt. In this paper, we provide evidence that the threat of dynamic jumps still exists in the global oil market in the post-crisis period, while the stocks and commodities of China's petrochemical markets are both affected by those jumps. To the best of our knowledge, this is the first study of the reaction of petrochemical markets to oil price jumps in the post-crisis period. In addition, a comparative analysis of petrochemical stocks and petrochemical commodity market is provided. In particular, we analyze the reactions of the returns and volatility of these markets to oil price jumps. We obtained the following findings. First, the returns of petrochemical stocks and petrochemical commodities are both negatively affected by current oil price jumps, while the effects of lagged jumps on these returns are opposite. Theoretically, the former is a reflection of panic induced by extreme risk information, while the latter is a reflection of rationality in speculators. Second, the volatilities of petrochemical stocks and petrochemical commodities respond differently to oil price jumps. The former is not affected, whereas the latter is positively and negatively affected by current and last oil price jumps, respectively. Finally, all the above conclusions still hold when considering the effects of normal oil price volatility, even after the co-movement between oil prices and petrochemical markets is eliminated.     

China’s aggregate embodied CO2 emission intensity from 2007 to 2012: A multi-region multiplicative structural decomposition analysis

The striking disparities among China’s provinces suggest the need for regionalized carbon emission intensity mitigation measures. This study extends the aggregate embodied energy/emission intensity measures proposed by Su and Ang (2017) to a national multi-region setting, defines the aggregate embodied CO2 emission intensity (AECI) indicators at the aggregate, provincial, and final demand category levels from the demand perspective, and adopts multiplicative structural decomposition analysis (SDA) to identify the driving factors of the historical changes over the 2007–2012 period in China. On the basis of China’s latest multiregion input-output tables, we find that (a) the AECIs show heterogeneities across the provinces and final demand categories, with the AECIs of inland provinces higher than those of coastal provinces and the AECIs of investment and export higher than those of consumption; (b) the generally downward trends of the AECIs hold at different levels, and the improvements in carbon emission performances are more pronounced in inland provinces, presenting a convergence toward the levels of developed coastal provinces; (c) according to the multiplicative SDA results, the input structure effect and the emission intensity effect generally contribute to the decline of AECIs. By providing a deeper understanding of carbon emission performance and its driving factors at the subnational level, our study finally proposes some policy recommendations.     

Hydrogen and multiwall carbon nanotubes production by catalytic decomposition of methane: Thermogravimetric analysis and scaling-up of Fe–Mo catalysts

Fe-based catalysts doped with Mo were prepared and tested in the catalytic decomposition of methane (CDM), which aims for the co-production of CO₂-free hydrogen and carbon filaments (CFs). Catalysts performance were tested in a thermobalance operating either at isothermal or temperature programmed mode by monitoring the weight changes with time or temperature, respectively, as a result of CF growth on the metal particles. Maximum performance of Fe–Mo catalysts was found at the temperature range of 700–900 °C. The addition of Mo as dopant resulted in an increase in the rate and amount of deposited carbon, reaching an optimum in the range 1.7–5.1% (mol) of Mo for Fe–Mo/Al₂O₃ catalysts, whereas for Fe–Mo/MgO catalyst an optimum at 5.1% Mo loading was obtained. XRD study revealed the effect of the Mo addition on the Fe₂O₃/Fe crystal domain size in the fresh and reduced catalysts. Tubular carbon nanostructures with high structural order were obtained using Fe–Mo catalysts, mainly as multiwall carbon nanotubes (MWCNTs) and bamboo carbon nanotubes. Fe–Mo catalysts showing best results in thermobalance were tested in a rotary bed reactor leading to high conversions of methane (70%) and formation of MWCNTs (5.3 g/h).     

Has China's coal consumption actually reached its peak? National and regional analysis considering cross-sectional dependence and heterogeneity

To investigate whether China's coal consumption has actually peaked, this study tests the national and regional coal Kuznets curve (CKC) hypothesis by using a panel dataset of 30 provinces covering 2000 to 2016. To fully capture the trends of coal consumption at the national, regional, and provincial levels, this study proposes a novel regional division method based on coal dependence and economic level. Considering the potential cross-sectional dependence and slope homogeneity, the newly developed methods allowing for heterogeneous slope coefficients are employed. The whole panel and subpanel results validate the CKC hypothesis for China, and province-specific results are mixed. The subpanel results reveal that only in the coal-dependent developing region has the peak of coal consumption not been reached, and for other regions, coal consumption displays a downward trend along with gross domestic product (GDP) increases. Furthermore, the province-specific results suggest that coal consumption will continue to increase slightly in certain provinces. This study implies that to reduce coal consumption, the coal-dependent developing region and provinces with a future turning point should act with great urgency to achieve a balance of economic growth and environmental responsibility. In addition, policymakers formulating coal consumption reduction policy in China must consider the remarkable differences across regions and provinces.     

What will China's carbon emission trading market affect with only electricity sector involvement? A CGE based study

On December 29, 2017, China's Carbon Trading Scheme (ETS) was officially launched, and it may be the largest emission trading platform in the world. This paper establishes 5 counter-measured scenarios based on the recently launched China's national ETS market and constructs a dynamic recursive Computable General Equilibrium model to study the impact of national ETS on the economy, energy, and environment. We find that the national ETS will have a negative impact on GDP by 0.19%–1.44%. The national ETS can significantly increase the price of electricity, however, the increase in the prices of other commodities will be much lower than that of electricity. As long as the mechanism of the ETS market remains unchanged, emission reduction per year will increase linearly. Economic output and CO₂ emission are sensitive to Annual Decline factor (ADF). This paper argues that China's national ETS market is an effective tool to reduce CO₂ emission, and we suggest that ADF could be 0.5% when allocating carbon allowance for the electricity sector. This could balance economic output and CO₂ reduction. Also, it is easy to achieve the goal of “double control” (total amount and intensity) in China.     

Impacts of booming economic growth and urbanization on carbon dioxide emissions in Chinese megalopolises over 1985–2010: an index decomposition analysis

Given the booming economic growth and urbanization in China, cities have become crucial to sustaining this development and curbing national emissions. Understanding the key drivers underlying the rapid emissions growth is critical to providing local solutions for national climate targets. By using index decomposition analysis, we explore the factors contributing to the carbon dioxide (CO₂) emissions in Chinese megalopolises from 1985 to 2010. An additional decomposition analysis of the industry sector is performed because of its dominant contribution to the total emissions. The booming economy and expanding urban areas are the major drivers to the increasing CO₂ emissions in Chinese megalopolises over the examined period. The significant improvement in energy intensity is the primary factor for reducing CO₂ emissions, the declining trend of which, however, has been suspended or reversed since 2000. The decoupling effect of the adjustments in the economic structure only occurred in three megalopolises, namely, the Yangtze River Delta (YRD), the Beijing-Tianjin-Heibei Megalopolis (BTJ), and the Pearl River Delta (PRD). In comparison, the impacts of urban density and carbon intensity are relatively marginal. The further disaggregated decomposition analysis in the industry sector shows that energy intensity improvements were widely achieved in 36 sub-industries in the PRD. The results also indicate the concentrations of energy-intensive industries in the PRD, posing a major challenge to local governments for a low-carbon economy. As economic growth and urbanization continue, reductions in energy intensity and clean energy therefore warrant much more policy attentions due to their crucial roles in reducing carbon emissions and satisfying the energy demand.     

Who formulates renewable-energy policy? A Swedish example

A broad participation by stakeholders and an extensive reliance on expert advice are often seen as preconditions for a legitimate and successfully implemented renewable energy policy. However, we have lacked systematic data for testing this argument. This article’s contribution is to examine the actors who take part in the making of Swedish energy policy with the help of data on the composition of various committees of inquiry over the last twenty years (1988–2009). Swedish renewable energy policy is often characterised with words like “pioneering” and “forerunner”, suggesting that the policy-making process in this area engages many different experts and stakeholders. Our data give only some support to this argument. Results point to a noteworthy predominance of politicians, civil servants, and representatives of state agencies within the policy-process. Producers of uranium and fossils based energy have been engaged more often than producers of renewable energy. Experts have played a prominent role, but this is mostly due to the participation of expert bureaucrats rather than of scientists. The study suggests that a better understanding of the making of energy policy, both in Sweden and elsewhere, requires greater attention to the networks and role of various state employees.     

R&D intensity and carbon emissions in the G7: 1870–2014

We examine the effect of research and development (R&D) intensity on carbon dioxide (CO₂) emissions in the Group of Seven (G7) countries since the nineteenth century using a non-parametric panel data model. Our estimates suggest that the relationship between R&D and CO₂ emissions is time-varying. The estimated time-varying coefficient function of R&D was negative for three quarters of the period studied, but was positive for a 35-year period (1955–1990) during the second half of the twentieth century. Our non-parametric local linear estimates show that the common trend functions gradually increased for the first 110 years (1870–1980), but then flattened out and showed a slight decrease for the next three decades.     

Car dieselization: A solution to China's energy security?

Recently, there is a renewed interest in car dieselization in China to address the challenge of oil security. We developed an econometric model to estimate the vehicle fuels and crude oil demands. The results indicate that if the average travel distance of cars is maintained at the level of 2010–16,000 km/yr, and if the distillation products mix of the refineries remains unchanged, China's crude oil demand in 2020 will reach 1060 million tonnes (Mt), which also results in an excess supply of 107 Mt of diesel. A new balance of diesel supply and demand can be reached and crude oil demand can be significantly reduced to 840 Mt by improving the production ratio between diesel and gasoline on the supply side and promoting passenger vehicle dieselization on the demand side. The crude oil demand will be reduced to 810 Mt in 2020, if the vehicle travel distance gradually drops to 12,000 km/yr. If so, dieselization will provide a rather limited added value—only 6% further oil saving by 2020. Dieselization is not a silver bullet but it depends on a series of key factors: growth rate of gross domestic products (GDP), vehicle sales, and vehicle annual travel distance.     

Energy use,industrial soot and vehicle exhaust pollution—China's regional air pollution recognition,performance decomposition and governance

The identification of “industrial soot” or “vehicle exhaust” pollution facilitates developing proper measures for the mitigation of regional air pollution. In order to identify the pollution types at a regional level, this paper applies the Luenberger productivity indicator to decompose air pollutant emissions performance. Furthermore, we simultaneously consider pollution rates and the productivity change. Thus, we propose a new modeling framework allowing for the variable-specific decomposition of the environmental performance along time and quantity dimensions to identify the underlying patterns. The panel data for 30 provinces and autonomous regions are then applied to identify regional atmospheric pollution type. The results show that SO₂ emission from industrial soot and NO_x emissions from vehicle exhaust constitute an important source of regional atmospheric environmental inefficiency, though the former seems to be more decisive. The southeast coastal provinces showed generally lower levels of inefficiency, compared to the northwest inland area. During the period of the 11th Five-Year Plan of China, industrial SO₂ emission performance contributed to the increase in the atmospheric environmental productivity, while traffic NO_x emissions acted as a negative factor in this regard. Therefore, the government should seek to increase the intensity of environmental regulation in transportation sector. At the country level, technical progress associated with both types of pollutions was positive and thus exceed the negative efficiency change for the same variables. In particular, in Beijing-Tianjin-Hebei region, the productivity changes in industrial SO₂ emissions and traffic NO_x emissions indicate a “stably advancing” type. The results further indicate that there are 18 provinces of China which have experienced mixed-type pollution. Jilin and Hainan were classified as provinces experiencing vehicle exhaust gas pollution, whereas Guizhou was defined as that subject to industrial soot pollution. The government should formulate and implement diversified support and regulation policies to govern SO₂ and NO_x pollution at the regional level.     

Can China achieve its 2030 energy development targets by fulfilling carbon intensity reduction commitments?

China has proposed carbon intensity targets and energy development targets for 2030. This study investigates the linkages between these targets and assesses if China can achieve its energy development targets by fulfilling its carbon reduction commitments. To this end, it quantitatively evaluates the impact of carbon emission controls on the Chinese economy using a dynamic computable general equilibrium model. The results show that China's carbon abatement pledge cannot guarantee achievement of all energy objectives. China is likely to reach the upper limit of its carbon intensity target in 2020 and the lower limit in 2030 if current abatement efforts are maintained. To achieve the upper limit in 2030, the carbon price will be CNY 83/tCO₂. The energy consumption target for 2020 is likely to be realized but the 2030 target is not. A more stringent price constraint on carbon emissions would be helpful to the achievement of the non-fossil energy target in 2030, but would have a limited promoting effect on natural gas development. Our results reveal the linkages between China's energy targets and carbon emission targets, which is valuable to the cost-effective dual control of energy consumption and carbon emission.     

CO2 emissions from household consumption in India between 1993–94 and 2006–07: A decomposition analysis

CO₂ emission from anthropogenic activities is one of the major causes of global warming. India being an agriculture dependent country, global warming would mean monsoon instability and consequent food scarcity, natural disasters and economic concerns. However with proper policy interventions, CO₂ emissions can be controlled. Input–output analysis has been used to estimate direct and indirect CO₂ emissions by households for 1993–94, 1998–99, 2003–04 and 2006–07. Complete decomposition analysis of the changes in CO₂ emissions between 1993–94 and 2006–07 has been done to identify the causes into pollution, energy intensity, structure, activity and population effects according to broad household consumption categories. Results indicate that activity, structure and population effects are the main causes of increase in CO₂ emission from household fuel consumption. To identify the causes at the sectoral level a second decomposition has been done for changes between 2003–04 and 2006–07 to identify the causes in the next stage. Finally alternative energy policy options have been examined for each consumption category to reduce emissions. Combined strategies of technology upgradation, fuel switching and market management in order to reduce CO₂ emissions for sectors like Batteries, Other non-electrical machinery, Construction and Electronic equipments (including Television), for which all the effects are positive, need to be adopted.     

China's carbon emissions embodied in (normal and processing) exports and their driving forces, 2006–2012

This paper constructed a time-series extended input–output dataset (2006–2012) to analyze China's carbon emissions embodied in both normal and processing exports at a detailed 135-sector level. The structural decomposition analysis (SDA) was further applied to shed light on the driving forces behind the changes in their embodied emissions over the entire time period. This empirical study confirms the importance of using the extended model for analyzing the trade-related embodiment, especially for processing exports. The embodied emissions in both normal and processing exports first increased from 2006 to 2008, then dropped during the global financial crisis (2008–2009), and then rose again after 2009. The embodied emissions as a percentage of total CO₂ emissions were quite stable before and after the global financial crisis, at around 24% over the 2006–2008 period, and 18% over the 2010–2012 period. From 2006 to 2012, emission intensity played the key role in reducing the embodied emissions (around 595 Mt CO₂), while the total export effect contributed the most to the increase in embodied emissions (around 552 Mt CO₂). Similar analysis can be applied to other indicators, such as energy, water, GHG emissions, pollutants and materials.     

Metallic and carbonaceous –based catalysts performance in the solar catalytic decomposition of methane for hydrogen and carbon production

Solar catalytic decomposition of methane (SCDM) was investigated in a solar furnace facility with different catalysts. The aim of this exploratory study was to investigate the potential of the catalytic methane decomposition approach providing the reaction heat via solar energy at different experimental conditions. All experiments conducted pointed out to the simultaneous production of a gas phase composed only by hydrogen and un-reacted methane with a solid product deposited into the catalyst particles varying upon the catalysts used: nanostructured carbons either in form of carbon nanofibers (CNF) or multi-walled carbon nanotubes (MWCNT) were obtained with the metallic catalyst whereas amorphous carbon was produced using a carbonaceous catalyst. The use of catalysts in the solar assisted methane decomposition present some advantages as compared to the high temperature non-catalytic solar methane decomposition route, mainly derived from the use of lower temperatures (600–950 °C): SCDM yields higher reaction rates, provides an enhancement in process efficiency, avoids the formation of other hydrocarbons (100% selectivity to H₂) and increases the quality of the carbonaceous product obtained, when compared to the non-catalytic route.     

CO2 emissions,GDP and energy intensity: A multivariate cointegration and causality analysis for Greece, 1977–2007

This paper deals with the causal relationship analysis between Gross Domestic Product, Energy Intensity and CO₂ emissions in Greece from 1977 to 2007, by means of Johansen cointegration tests and Granger-causality tests based on a multivariate Vector Error Correction Modeling. Results indicate that there is a set of uni-directional and bi-directional causalities among the selected time series. We performed a model Variance Decomposition Analysis using Choleski technique and we provided a comparison with other studies. The findings of the study have significant policy implications for countries like Greece as the decoupling of CO₂ emissions and economic growth seems quite unlikely.     

Do urbanization and industrialization affect energy intensity in developing countries?

Against a backdrop of concerns about climate change, peak oil, and energy security issues, reducing energy intensity is often advocated as a way to at least partially mitigate these impacts. This study uses recently developed heterogeneous panel regression techniques like mean group estimators and common correlated effects estimators to model the impact that income, urbanization and industrialization has on energy intensity for a panel of 76 developing countries. In the long-run, a 1% increase in income reduces energy intensity by − 0.45% to − 0.35%. Long-run industrialization elasticities are in the range 0.07 to 0.12. The impact of urbanization on energy intensity is mixed. In specifications where the estimated coefficient on urbanization is statistically significant, it is slightly larger than unity. The implications of these results for energy policy are discussed.