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The power industry's low carbon transition is pivotal for achieving carbon reduction and sustainable development. This study uses the super epsilon-based measurement (Super-EBM) model and the Malmquist index to evaluate the power industry's low carbon transition efficiency using data from 30 provinces in China from 2010 to 2020, and utilizes the Tobit model to comprehensively analyze the factors affecting the low carbon transition of power industry. In addition, this paper examines the spatial differences in the power industry's low carbon transition efficiency as well as its distributional characteristics and dynamic evolutionary patterns. Conclusion is drawn as follows this paper analyzes the regional differences, spatial distribution characteristics and dynamic evolutionary trends of the power industry's low carbon transition. The main conclusions are as follows: (1) The power industry's low carbon transition efficiency in China shows an uptrend, with the western China region having the highest overall level of efficiency, greater fluctuations in the central China region, and more stability in the eastern China region, technological progress is a central factor in increasing total factor productivity, the efficiency of the power industry's low carbon transition is positively influenced by the electricity prices, and negatively influenced by the energy structure, environmental regulations and economic structure; (2) the Intraregional differences and hypervariable density are the main reasons sources of the overall differences in the efficiency of the power industry's low carbon transition; Intraregional differences in the eastern, central, and western China regions are decreasing year by year, but the efficiency of the power industry's low carbon transition in the western China region is still distributed in a multipolar way; (3) The dynamic evolutionary trends of the efficiency distribution of the low carbon transition in power industry is influenced by the type of spatial lag in the neighboring area. Where areas with low efficiency makes it difficult to achieve short-term leapfrog development, and areas with a cluster of high-efficiency provinces are prone to "Siphon Effect". The findings provide a theoretical basis for promoting the efficiency of the power industry's low carbon transition and coordinating the strategic adjustment of economic and environmental green development. [ABSTRACT FROM AUTHOR]

Purpose: The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development. Design/methodology/approach: In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China's green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively. Findings: After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas. Originality/value: Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model. [ABSTRACT FROM AUTHOR]

China's industrial sector generally relies on electricity as its main source of energy, and industrial production can be affected if there are problems with the electricity supply. In order to deal with the uncertain electricity supply and achieve the "dual carbon" target, the industrial sector needs to take effective measures to enhance carbon total factor productivity (CTFP). We use the biennial Luenberger productivity index (BLPI) to try to provide strategies for low-carbon industrial development in China. The results indicate that the overall CTFP of China's industrial sector showed an increasing trend from 2006 to 2019. Technology change was the main contributor to the change in CTFP, but fluctuations in efficiency change remained a challenge. Differences were observed between the light industry sector (LIS) and the heavy industry sector (HIS) in terms of changes in CTFP, with LIS showing more stable changes and HIS experiencing larger fluctuations. Most sub-sectors showed increased CTFP during the sample period. R&D investment and R&D personnel have a positive impact on CTFP, while energy structure is found to hinder CTFP. According to the research results of this study, we offer the corresponding policy implications. This study is the first to explore the balance between low-carbon goals and industrial production from the perspective of improving CTFP, providing a new viewpoint on the contributions of technological innovation to solving socio-economic issues. [ABSTRACT FROM AUTHOR]

This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb–Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb–Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions. [ABSTRACT FROM AUTHOR]

This article discusses the changes in carbon productivity and economic growth patterns in China. We calculated carbon productivity using panel data from BRICS and G7 countries between 2001 and 2019 and developed a methodology to estimate economic growth patterns by combining carbon productivity and economic growth. As the world's top carbon emitter, China can combat global climate change by increasing carbon productivity. We show that (i) China has a high growth rate of carbon productivity; however, the carbon productivity level only accounts for about 20% of developed countries. (ii) When determining economic growth patterns from a low-carbon perspective, China has transitioned from high-carbon type II to low-carbon type III. However, low-carbon economic growth is common in developed countries, and (iii) it can improve carbon productivity by reducing energy-averaged carbon emission factors. It assists the government in determining how to implement low-carbon economic development policies by examining economic growth from a low-carbon perspective. [ABSTRACT FROM AUTHOR]

Based on the panel data of 11 provinces and cities in the Yangtze River Economic Belt of China from 2011 to 2018, the DEA model and Malmquist index were used to calculate the industrial carbon unlocking efficiency of the Yangtze River Economic Belt in a static and dynamic way, and the Tobit model was used to empirically test its influencing factors. The results show that (1) the overall efficiency of industrial carbon unlocking in the Yangtze River Economic Belt is on the rise, but there are regional differences. The efficiency of industrial carbon unlocking in the lower reaches of the Yangtze River is higher than that in the upper and middle reaches. (2) The total factor productivity of industrial carbon unlocking in the Yangtze River Economic Belt has increased steadily on the whole, and technological progress is the main source of growth. (3) Industrial carbon unlocking efficiency is affected by many factors. Environmental regulation and degree of openness have a promoting effect on industrial carbon unlocking efficiency, while government investment and innovation level have a restraining effect on industrial carbon unlocking efficiency. [ABSTRACT FROM AUTHOR]

In the light of China's synergistic need to achieve Sustainable Development Goals (SDG) 10 and 13, it is necessary to consider the potential nexus between common prosperity and carbon reduction. Therefore, this work proposes a new comprehensive measure to assess the degree of common prosperity in 30 Chinese provinces from 2006 to 2019. Furthermore, we examine the impact of common prosperity on carbon emissions applying the system-generalized method of moments (SYS-GMM) approach. All major conclusions are as follows: (1) the level of common prosperity has continued to increase between 2006 and 2019; (2) common prosperity and carbon reduction are compatible with each other, i.e., common prosperity significantly reduces carbon emissions; (3) common prosperity reduces carbon emissions indirectly by improving labor productivity and upgrading industrial structure; (4) carbon emissions are indirectly increased by common prosperity through the expansion of gross fixed capital formation and higher levels of urbanization, and (5) in provinces with higher levels of common prosperity and lower levels of carbon emissions, common prosperity has a considerably greater influence on carbon emissions. Finally, we suggest several policy implications for promoting China's sustainable development. [ABSTRACT FROM AUTHOR]

This study investigates the relationship among technology innovation, emission trading schemes, and carbon productivity based on data from firms participating in the Korean Emission Trading Scheme. First, the total factor carbon productivity based on stochastic frontier analysis is estimated by industry and it is confirmed that changes in carbon productivity vary by industry. Based on the estimated carbon productivity, panel data analysis is conducted to determine the effects of innovation and environmental policy on carbon productivity. The results show that R&D investment and environmental policy play an important role in promoting carbon productivity. In this study, the factors affecting carbon productivity are also analyzed by industry. Comparative analysis across industries confirms that factors affecting environmental performance vary by industry. Innovation does not significantly affect carbon productivity in assembling industries, but in the process industry, R&D investment plays an important role in increasing environmental performance. [ABSTRACT FROM AUTHOR]

Power technology innovation has been positioned as an effective way to contribute to China's carbon productivity. However, limited empirical evidence exists on the impact of power technology innovation on carbon productivity. Thus, based on the annual panel dataset of 30 China's provinces from 2001 to 2019, this study explored whether and how power technology innovation promotes or impedes the improvement of carbon productivity. First, carbon productivity in the framework of total factor was calculated based on the metafrontier Malmquist-Luenberger productivity index. Second, the effect of power technology innovation on carbon productivity was investigated using the spatial Durbin model. And we also examined whether heterogeneous power technology innovations have a synergistic effect on carbon productivity. Third, influence mechanism of power technology innovation affecting carbon productivity was identified. Results show that (1) there are notable differences in China's provincial carbon productivity, which is characterized by the spatial correlation. (2) Local power technology innovation has a promotion effect on carbon productivity in both local and neighboring provinces. Moreover, the promotion effect of breakthrough power technology innovation is stronger than that of incremental power technology innovation. (3) Catching-up Effect and Innovation Effect are important transmission channels through which power technology innovation improves carbon productivity. Finally, policy recommendations are provided. [ABSTRACT FROM AUTHOR]

Low-carbon economy has become the current global economic development trend, and corporate carbon disclosure has attracted more and more attention from scholars and investors. This study creatively explores the mechanism of corporate carbon disclosure on total factor productivity with financing structure as a mediating variable. The content analysis method is employed to assess carbon disclosure that is suitable for Chinese enterprises. Through the mediating effect model and Sobel test, the internal mechanism of carbon disclosure affecting total factor productivity is analyzed, with Chinese heavy polluting enterprises from 2015 to 2018 as research samples. The results show that, firstly, carbon disclosure has a positive effect on the improvement of total factor productivity. The effect of monetary carbon disclosure on the improvement of total factor productivity is higher than that of non-monetary carbon disclosure. Secondly, the financing structure has a mediating effect between carbon disclosure and total factor profductivity, and the mediating effect of internal financing capabilities is better than those of external financing costs. Finally, external financing costs and internal financing capabilities have mediating effects in both heterogeneous carbon disclosure and total factor productivity. The mediating effect of internal financing capabilities is significantly higher than the mediating effect of external financing costs. The effect of monetary carbon disclosure on total factor productivity indirectly through internal financing capabilities is higher than that of non-monetary carbon disclosure. [ABSTRACT FROM AUTHOR]

This study aims to explore the driving determinants on the export-related carbon intensity (ECI) of China, to better understand the impact of international trade on climate change governance and facilitate China's carbon intensity mitigation goals. First, China's ECI evolution and its gaps with the USA and India are measured during 2002–2014. Then, the main drivers of China's ECIvert study further discusses the influencing factors of ECI in the manufacturing industry using the environmental-extended STIRPAT model and GMM method. The results show that (1) China's overall ECI increases from 1.50 Kg/US$ in 2002 to 1.92 Kg/US$ in 2005 and then decreases to 1.27 Kg/US$ in 2014. The ECI of the manufacturing industry is significantly higher than that of the agriculture and service industry. China's ECI gap with the USA is greater than that with India, and both show a downward trend. (2) Carbon emission coefficient is the domain factor to reduce China's ECI during 2002–2014; the effects of the value-added coefficient, input–output structure, and final demand are limited. The input structure dominantly expands China's ECI gaps both with the USA and India, followed by the value-added coefficient. The carbon emission coefficient enlarges the ECI gap with the USA while reduces that with India. (3) Industrial productivity and value-added rate are negatively correlated with ECI in the manufacturing industry, while per capita capital stock plays the opposite role. The positive correlation between energy intensity and CIE becomes significant after distinguishing technology heterogeneity. In contrast to the non-tech-intensive manufacturing industry, the increase of backward GVCs participation of tech-intensive ones will reduce the ECI. The threshold effect of backward GVCs participation exists in the whole manufacturing industry. Targeted ECI reduction policy implications are suggested. [ABSTRACT FROM AUTHOR]

In the context of low-carbon economic development, carbon productivity has effectively integrated the two major objectives of carbon reduction and economic growth, and increasing carbon productivity has become the main approach to address global climate change. Using data from China's input–output table for 2002–2017, this study measures the evolutionary characteristics and influencing factors of carbon productivity from the perspective of embodied carbon emission in China's industrial sector. The results indicate that, first, China's industrial sectors' carbon productivity shows an increasing trend from 25.22 to 65.3 million yuan/10,000 tons of CO2 in 2002–2017, but the overall level is low. The energy efficiency factor is a major element affecting improvement in carbon productivity. Second, the carbon productivity of the 28 industrial sectors shows an increasing trend. There is a significant gap in the carbon productivity between different industrial sectors. The energy efficiency factor in all industrial sectors is positive, indicating that energy efficiency is a positive factor in increasing carbon productivity. Third, from largest to smallest in the carbon productivity are the primary, tertiary, and secondary industries. Finally, this paper recommends several approaches to improve carbon productivity from the perspectives of technology, differentiated policies of carbon emission reduction, and industrial structure adjustment. [ABSTRACT FROM AUTHOR]

Amid global climate imperatives and intensified economic competition, pivoting from China's conventional growth paradigms to innovative economic catalysts emerges as pivotal for its transformative agenda. Drawing on panel data from 141 principal urban conglomerates spanning 2011–2021, this investigation delves into the intricate nexus between the digital economy and carbon total factor productivity. Our empirical analysis unveils a U-shaped trajectory characterizing the digital economy - carbon total factor productivity interplay, accompanied by a congruent spatial spillover dynamic. While digital economy fortifies environmental governance mechanisms through amplified data and media channels, such regulatory frameworks, albeit efficacious in emission abatement, may inadvertently impede economic vitality, thus attenuating carbon total factor productivity. Progressing from digital economy's foundational phase to its comprehensive deployment, its reverberations on capital productivity manifest in a U-shaped curve, invigorating local carbon total factor productivity while potentially undermining adjacent regions. This digital economy - carbon total factor productivity interrelation is accentuated in advanced, non-resource-reliant metropolises with subdued innovation propensities. This discourse proffers nuanced policy implications for sculpting digital economy trajectories and bolstering carbon total factor productivity in a sustainable context. [Display omitted] • The digital economy demonstrates a U-shaped spatial spillover impact on carbon total factor productivity. • The digital economy influences carbon total factor productivity through governmental environmental regulations. • The digital economy influences carbon total factor productivity through capital productivity. [ABSTRACT FROM AUTHOR]

Low-carbon pilot (LCP) policy aims to not only achieve economic development but also address climate change problems in China. With a difference-in-difference (DID) approach, this study provides empirical evidence to support the policy's implementation by analysing its impacts on green total factor productivity (GTFP). We find that the implementation of the low-carbon pilot policy has a significant positive impact on GTFP. The low-carbon pilot policy significantly improves the GTFP in the year following implementation, and its efficacy diminishes over time. In terms of mechanism analysis, the policy enables China to achieve win-win development through industry structure adjustment and foreign direct investment (FDI) inflows. Innovation does not immediately improve GTFP, although the low-carbon pilot policy promotes regional innovation. Our results provide strong support for China's recent third set of low-carbon pilot policies. As for global mitigation strategy, countries should incorporate the low-carbon development path into their strategic planning. In particular, developing countries should enforce more efforts on low-carbon development as such development path may improve their green productivity. It helps narrow the gap between developing and developed countries. [ABSTRACT FROM AUTHOR]

There is a concern that engineered carbon nanoparticles, when manufactured on an industrial scale, will pose an explosion hazard. Explosion testing has been performed on 20 codes of carbonaceous powders. These include several different codes of SWCNTs (single-walled carbon nanotubes), MWCNTs (multi-walled carbon nanotubes) and CNFs (carbon nanofibers), graphene, diamond, fullerene, as well as several different control carbon blacks and graphites. Explosion screening was performed in a 20 L explosion chamber (ASTM E1226 protocol), at a concentration of 500 g/m 3 , using a 5 kJ ignition source. Time traces of overpressure were recorded. Samples typically exhibited overpressures of 5–7 bar, and deflagration index K St = V 1/3 (d P /d t ) max ∼ 10–80 bar m/s, which places these materials in European Dust Explosion Class St-1. There is minimal variation between these different materials. The explosive characteristics of these carbonaceous powders are uncorrelated with primary particle size (BET specific surface area). [ABSTRACT FROM AUTHOR]

The current industrial production of aluminum from alumina is based on the electrochemical Hall-Héroult process, which has the drawbacks of high-greenhouse gas emissions, reaching up to 0.70 kg CO2-equiv/kg Al, and large energy consumption, about 0.055 GJ/kg Al. An alternative process is the carbothermic reduction of alumina. Thermodynamic equilibrium calculations and experiments by induction furnace heating indicated that this reaction could be achieved under atmospheric pressure only above 2200°C. Lower required reaction temperatures can be achieved by alumina reduction under vacuum. This was experimentally demonstrated under simulated concentrated solar illumination and by induction furnace heating. By decreasing the CO partial pressure from 3.5 mbar to 0.2 mbar, the temperature required for almost complete reactant consumption could be decreased from 1800°C to 1550°C. Deposits condensed on the relatively cold reactor walls contained up to 71 wt% of Al. Almost pure aluminum was observed as Al drops, while a gray powder contained 60–80% Al and a yellow-orange powder contained only Al4C3, Al-oxycarbides and Al2O3. [ABSTRACT FROM PUBLISHER]

The paper investigates the determinants of productivity growth in China. It also analyses the sustainability of the country's industrial growth by estimating sectoral productivity, accounting for energy usage and emission since the market-oriented reforms launched in the late 1970s. The empirical analysis indicates that productivity is the most significant driver of growth. The substantial productivity improvement of China's industry is mainly attributable to high-tech light industrial sectors. Heavy industry lags behind in terms of productivity and overall technical change. [ABSTRACT FROM AUTHOR]

Abstract: An enterprise benefit model is built up in this paper on the basis of economic and technical elements as well as ecological resource elements to study the enterprise benefit issue of two industrial production and organizat ion patterns, the cluster production and circulatory production from the double perspectives of economic benefit and ecological benefit. The results suggest that the economic benefit of traditional cluster production is notably superior to that of circulatory production and the ecological benefit of circulatory production is in turn notably superior to that of the traditional cluster production. Based on the respective strong points of the abovementioned industrial production and organization patterns, a new industrial organization pattern, i.e. circulatory industrial cluster pattern enabling the uniform optimization of economic and ecological benefits is brought forth in this paper. Under the background of low-carbon economy, this pattern is the best approach to the construction of green growth pole in western regions. [Copyright &y& Elsevier]

The extensive distribution of bamboo forests in South and Southeast Asia plays an important role in the global carbon budget. It is an urgent task to accurately and in good time estimate carbon stock within these areas. In this study, linear regression, partial least-squares (PLS) regression and backpropagation artificial neural network (BP-ANN) with a Gaussian error function as the activation function of the hidden layers (Erf-BP) were used to estimate aboveground carbon (AGC) stock of Moso bamboo in Anji, Zhejiang Province, China. Based on the combined use of Landsat Thematic Mapper (TM) and field measurements, the results indicate that the Erf-BP model provided the best estimation performance, and the linear regression model performed the poorest. This study indicates that remote sensing is an effective way of estimating AGC of Moso bamboo in a large area. [ABSTRACT FROM AUTHOR]

Corporations are being monitored as to their carbon base. The level of carbon in the atmosphere is reaching dangerous levels that threaten corporate productivity, as well as human health. Remember that humans are carbon-based life forms. This Article discusses ha detail efforts to halt the release of carbon into the atmosphere and mitigate global warming, from state-led initiatives to litigation in lower courts and the U.S. Supreme Court. It concludes that incentivitizing corporations to adopt renewable energy practices is the best way to address corporate citizenship and environmental responsibility. [ABSTRACT FROM AUTHOR]

Results are presented from commercial trials performed to examine the effect of the properties of the charge and the parameters of the charging equipment on the formation of the bed during the charging of sintering machines. To simultaneously increase the degree of segregation of the charge and alleviate its over-compaction during the charging operation, it will be necessary to improve the design of the charging system and search for new technical solutions to obtain the necessary charging parameters. [ABSTRACT FROM AUTHOR]

Abstract: A critical ecological question in plantation management is whether fertilization, which generally increases yield, results in enhanced C sequestration over short rotations. We present a rotation-length hybrid process model (SECRETS-3PG) that was calibrated (using control treatments; CW) and verified (using fertilized treatments; FW) using daily estimates of H2O and CO2 fluxes, canopy leaf area index (L), and annual estimates of tree growth and dimension. Herein, we focus on two decades of loblolly pine (Pinus taeda L.) growth and establishment for stands growing on a nutrient poor, droughty soil (SETRES; Southeast Tree Research and Education Site) in North Carolina, USA, on a site previously occupied by a ∼30-year-old natural long-leaf pine (P. palustris Mill.) stand. The SECRETS-3PG model combines: (1) a detailed canopy process model with hourly and daily resolution, (2) a biometrically accurate tree and stand growth module for monthly allocation, 3-PG, and (3) empirical models of soil CO2 efflux (R S). Simulated L, quadratic mean tree diameter, and total standing biomass all tracked field measurements over a 10-year period. Simulated maintenance respiration, canopy transpiration, and R S mirrored, with minor exceptions, short-term independently acquired data. Model correspondence with the independent measurements provided a basis for making short-term estimates of net ecosystem productivity (NEP) and longer-term estimates of net primary production (NPP) over the 20-year period from planting. Simulations suggest that optimum fertilization amendments; (1) increased NEP by more than 10-fold over control – FW (952gCm−2 a−1) and CW (71gCm−2 a−1) – at maximum NPP and (2) increased NPP two-fold (1334 and 669gCm−2 a−1 for FW and CW, respectively) at maximum L. Seasonal patterns in NEP suggest that autumn and winter may be critical periods for C uptake in nutrient-limited loblolly pine stands. We conclude that increased L in response to improved nutrition may enable loblolly pine to achieve positive annual NEP earlier in rotation. [Copyright &y& Elsevier]

Combustion using silicon carbide coated, carbon-carbon composite porous inert media (PIM) was investigated. Two combustion modes, surface and interior, depending upon the location of flame stabilization, were considered. Combustion performance was evaluated by measurements of pressure drop across the PIM, emissions of NOx and CO, and the lean blow-off limit. Data were obtained for the two combustion modes at identical conditions for a range of reactant flowrates, equivalence ratios, and pore sizes of the PIM. Results affirm PIM combustion as an effective method to extend the blow-off limit in lean premixed combustion. [ABSTRACT FROM AUTHOR]

Cost modelling provides a unified framework for optimising industrial processes by simultaneously considering all the key metrics that characterise the performance of a process. The broad scope of cost modelling is to correlate the process parameters with the plant performance metrics and, in turn, relate these to the overall process cost. In the present paper, the concept of cost modelling will be elaborated in a case study on the gas carburising operation. The cost model for the case carburisation process relates the controllable parameters (carbon potential and T-t set points) to the relevant cost drivers (energy, productivity, gas consumption, emissions) and quality parameters (case depth, grain size and distortion). These cost drivers and quality parameters are transformed to obtain the overall normalised production cost using appropriate cost functions. The cost model is subsequently used to optimise the carburisation cycle by the exhaustive search method for boost stage optimisation and by the differential evolution method, a genetic algorithm based technique, for the entire cycle optimisation, with the objective of minimising the production cost. This approach resulted in significant energy reduction (14%) and productivity enhancement (20%) in an industrial carburising operation. [ABSTRACT FROM AUTHOR]

Results are presented for a laboratory study of the substance composition of a periclase-carbon torcrete mix for restoring a converter lining, comparative methods for testing a torcrete mix under laboratory conditions, and the main production parameters for a torcrete mix under existing production conditions. Industrial tests are performed in the converter section of the OAO MMK oxygen-converter workshop. The life of a torcrete layer is two melts. [ABSTRACT FROM AUTHOR]

International policy actions to constrain carbon emissions create substantial risks and opportunities for firms. In particular, production processes that are relatively high emitting will be more sensitive to the uncertain costs of emitting carbon dioxide and might further reflect productive inefficiencies. We employ a productive efficiency model to evaluate firms' carbon emission levels relative to those of best-practice (efficient) peers with comparable production structures. By accounting for total factor productivity and sector-relative performance aspects, this measure of carbon efficiency helps to quantify and rank firms' relative dependence on carbon in the production process. We investigate the impact of carbon efficiency on various financial performance outcomes and evaluate the role of general resource efficiency in explaining these impacts. Using an international sample of 1572 firms over the years 2009–2017, we find superior financial performance in carbon-efficient (best-practice) firms. On average, a 0.1 higher carbon efficiency is associated with a 1.0% higher profitability and 0.6% lower systematic risk. While carbon efficiency closely relates to resource efficiency, it also has distinct financial performance impacts, particularly lowering systematic risk. Overall, our findings suggest that carbon-efficient production can be valuable from both operational and risk management perspectives. • Firms producing relatively abundant carbon emissions may be more sensitive to uncertain carbon costs and exhibit resource use inefficiencies • We estimate carbon efficiency in a joint production framework and investigate its relationship with financial performance outcomes • Carbon efficiency reflects the extent to which minimum feasible carbon emissions are generated in a given production structure • We find superior operating performance and lower systematic risk levels in carbon-efficient (best-practice) firms in the period 2009–2017 • Carbon efficiency can partly be regarded as 'Resource efficiency in disguise' [ABSTRACT FROM AUTHOR]

South American masterbatch producer Comai Ltda is increasing its production capacity for carbon black, white and additive masterbatches based on polypropylene, polyethylene and polystyrene by around 10 000 tonnes/year. [Copyright &y& Elsevier]

Features the Sievers 900 series total organic carbon analyzers from Ionics Instrument Business Group. Offer of improved analytical performance, productivity and reliability; Analysis time and accurate calibration; Touch-screen display.