Non-ferrous Metal Industry Research Articles

Transforming tire-derived char into powerful arsenic adsorbents by mild modification

A large amount of arsenic-containing wastewater discharged by the non-ferrous metal industry will cause serious environmental problems if it is not properly treated. Pyrolysis char of waste tire is a kind of solid waste. Since the surface properties of tire derived char (TC) are affected by tar/ash adhesion during pyrolysis, it is necessary to modify TC to treat wastewater containing As(V) effectively as an adsorbent. At present, most studies on the modification of TC are prepared into activated carbon by high temperature activation in N2 atmosphere. In this study, TC was modified at room temperature and air atmosphere, and Fe(OH)3-TCNaOH adsorbent with particle size of 61–75 μm was obtained under the premise of the removal rate of As(V) and the settling performance of the adsorbent. When the initial concentration of As(V) was 5 mg/L, the removal rate of As(V) by Fe(OH)3-TCNaOH with a particle size of 61–75 μm could reach 90% within 30 min under a wide pH range (3–9). The adsorption of As(V) by Fe(OH)3-TCNaOH was most affected by the coexistence of PO43-, which resulted in the removal rate of As(V) decreased by about 20%. The adsorption mechanism shows that the significant increase in the number of 3–5 nm mesoporous pores of Fe(OH)3-TCNaOH and the formation of H bonds are beneficial to the adsorption of Fe(OH)3-TCNaOH to As(V), and improve the stability of Fe-As complex.

Possibility and pathways of China's nonferrous metals industry to achieve its carbon peak target before 2030: A new integrated dynamic forecasting model

The Chinese government has mandated that the nonferrous metals industry (NMI) achieve carbon peaking before 2030. Consequently, nonscientific mitigation measures, such as indiscriminate closure of production lines, have been implemented. An appropriate carbon peak pathway must be developed NMI. This study designs three carbon peaking pathways for two subsectors within the industrial chain of the NMI according to the latest industry policies and industry characteristics. Subsequently, a novel integrated dynamic assessment model is constructed in this study to evaluate the probability of carbon peaking under various pathways and choose an appropriate one. Results indicate that: (1) Under the baseline development pathway, the likelihood of meeting the target as anticipated is 61.6 % for the nonferrous metal mining and processing industry (MS) and 9.9 % for the nonferrous metal smelting and refining industry (SS). (2) The low-carbon scenario is the most suitable development path for both subsectors. Under this pathway, the likelihood of MS and SS reaching their targets on time increases to 100 % and 87.4 %, respectively. MS likely peaked in 2013, with a peak at 28 Mt. SS is projected to peak in carbon emissions by 2025, with the highest probability of peaking between 417.6 Mt and 424.5 Mt. If no fluctuations will takes place during the implementation of low-carbon policies, then the peak would occur at 423.9 Mt (3) In this pathway, the industrial value added and energy intensity have the greatest influence on the probability of missing the deadline. This study enriches prediction methods for CO2 emissions and offers guidance to the Chinese nonferrous metal industry for effectively achieving the peak carbon target.

Exploring the effect of green finance on green development of China’s energy-intensive industry—A spatial econometric analysis

An indispensable part of the green revolution is the green development of the Energy-intensive Industry (EII), which is crucial for China to achieve its “double carbon” target. EII is one of the key sectors bound by the green finance policy, whose development level is susceptible to regional conditions. Therefore, this research constructs a spatial Durbin model using provincial panel data (2001-2019) to empirically examine the impact of green finance on EII’s green total factor productivity (GTFP). Evidence shows that green finance boosts EII’s GTFP significantly and there is a spatial spillover effect. Specifically, the results demonstrate that the spatial spillover effect’s regional heterogeneity is positive in the eastern, central and northeastern regions, and negative in the weatern region. Furthermore, there is a spatial inhibitory effect on two subindustries of EII, i.e., Manufacture of Non-metallic Mineral Products industry and Smelting and Pressing of Non-ferrous Metals industry, proving the spatial spillover effect’s sectoral heterogeneity for green finance. This research provides experimental evidence and policy suggestions for enhancing the promotion impact of green finance on EII’s GTFP.

Spatial and temporal variations in environmental impacts of heavy metal emissions from China's non-ferrous industry: An enterprise-specific assessment

In China, the non-ferrous metal industry is the sector with the highest emissions of arsenic, cadmium, mercury and lead, causing serious impacts on human health and the ecosystem. However, current heavy metal emission inventories are inadequate for figuring out their exposures and associated environmental impacts due to the lack of detailed data. Here, we constructed a high-resolution, enterprise-specific, and long-term dataset detailing heavy metal emissions from the non-ferrous industry in China from 1981 to 2020, using comprehensive enterprise information. Furthermore, an environmental impact assessment was performed using the characterization factors of the IMPACT World + model. Results show that: (1) from 1981 to 2020, the total heavy metal emissions of China's non-ferrous industry reached 144,697 tons (t), with atmospheric emissions (104,524 t) exceeding aquatic ones (40,173 t). (2) The industry's emissions showed a rising and then declining trend, with significant spatial heterogeneity, where heavy metal emissions concentrated in the central and western parts of Yunnan, the southern part of Hunan, the northern part of Guangxi, Henan along the Yellow River, the intersection of Gansu and Shaanxi, the central and eastern parts of Liaoning, and the eastern part of Inner Mongolia. (3) The environmental impact on human health was 1.19 × 107 DALY, and the value of ecosystem quality was 7.26 × 109 species·yr. The top 10 % of enterprises with the largest environmental impacts contributed over 60 % of human health risks and 62 % of ecosystem quality impacts. Improving the removal efficiency of heavy metals by 10 % within the four major industry classes could lead to a 9.92 % reduction in human health impacts and a 9.77 % reduction in ecosystem quality impacts within the non-ferrous metals industry. The findings of this study can provide insights for pollution control, environmental risk reduction, and sustainable development in the non-ferrous metals industry.

A data and knowledge driven autonomous intelligent manufacturing system for intelligent factories

The non-ferrous metal industry is encountering several challenges, including production efficiency, manufacturing information fragmentation, and human health problems, which highlights the importance of implementing autonomous intelligent manufacturing systems (AIMS). Recently, the foundation model like GPT-4, has garnered attentions due to its exceptional capabilities and proficiency in diverse domains and tasks, facilitating the realization of AIMS. However, the existing foundation models can only address basic general-purpose tasks and are difficult to use for industrial applications. In this paper, we propose a data and knowledge driven AIMS with industrial-generative pretrained Transformer (Industrial-GPT) for intelligent factories. The paradigms and architecture of autonomous intelligent factories are firstly defined. Then, we explore the mechanism with knowledge graph, digital twin, and Industrial-GPT, including multi-level autonomous perception, cross layer and domain cognition, and event-driven collaborative decision-making. Finally, the detailed case study is based on the cooperation with a zinc smelting intelligent factory to achieve networked collaborative manufacturing, and explores the theory and realization mechanism of AIMS on a small scale. We explore the experimental analyses, evaluation mechanisms and platform applications of AIMS at the workshop level. We believe this will help to realize larger scale AIMS in the future.

Assessing influential factors of Chinese industrial aqueous cadmium emissions based on machine learning and shapley additive explanations

As the main contributor of cadmium (Cd) pollution in China, industrial aqueous Cd emissions are influenced by both industrial and socioeconomic characteristics owing to their “environmental service” nature. It is essential to understand the relationship between these characteristics and industrial aqueous Cd emissions during industrialization. In this study, a data-driven framework was proposed to reveal these relationships. The framework comprises two key steps. i) Three state-of-the-art tree-based machine learning models, including LightGBM, Gradient Boosting Decision Tree and Random Forest, were trained to capture the relationships among variables. ii) Shapley additive explanation was utilized to decompose the contribution of the characteristics to the prediction for each sample. The trained LightGBM model demonstrated the most superior performance in predicting industrial aqueous Cd emissions in test datasets (R2=0.881±0.0431， RMSE=58.260±11.839， MAE=27.743±3.274), significantly overperforming traditional linear regression model. Our analysis revealed that during our sample period, the influence of industrial characteristics on regional industrial aqueous Cd emissions was approximately 1.796 times greater than that of socioeconomic characteristics. Shifts in the characteristics of the non-ferrous metal industry contributed to approximately 74% of the average increase in industrial aqueous Cd emissions in China approximately. Regional emissions were found to be positively affected by average size and density but negatively affected by the operation duration of local non-ferrous metal industrial firms. Further driver analysis showed that the growth trajectory of emissions in China can be split into three stages based on the main drivers and growth rate: 2000–2002, 2003–2004, and 2005–2007. The proposed framework overcomes the limitations of the previous methods in terms of application scope, potential factor considerations, and regression structure predefinition. Our analysis implies that policymakers should proactively adjust industrial policies and emissions regulations in response to market shocks and industrial shifts, to a better management of industrial aqueous Cd emissions.

The Specific Impact of Environmental Regulations on the Comparative Advantage of Resource-Based Industries

With the increasing emphasis on global environmental issues and the deepening of the concept of sustainable development, the application and impact of environmental regulation are becoming increasingly prominent. Especially for pollution-intensive products, the impact of environmental regulation on the import and export trade of different pollution-intensive products is subject to various factors. The impact of environmental regulation on different resource-based industries still needs a lot of research. Through the method of literature analysis, this paper integrates the literature on the impact of environmental regulation on resource-based industries and concludes that the overall impact of environmental regulation on resource-based industries is positive and significant. For the paper and pulp industry, both exogenous and endogenous environmental regulations have enhanced its comparative advantage. For the non-ferrous metal and non-metallic mineral industry, environmental regulation can promote its technological progress and gain comparative advantage.

The Nonferrous Metals Society of China

Notice of 2023 (the third) International Conference of Non-Ferrous Materials (ICNFM)To: All related unitsThe “International Conference of Non-Ferrous Materials” is an important academic conference in the field of non-ferrous metals materials sponsored by the Non-ferrous Metals Society of China and co-organized by a number of universities, research institutes and enterprises engaged in the non-ferrous metals industry. It is held once a year, and the 2023 one will be the third conference. There are more than 10 academicians and more than 400 talents participating in the conference. The conference adopts various forms of exchange and discussion such as conference reports, branch reports, wall poster exchanges and exhibitions.List of Conference Introduction, Organization, Parallel Sessions Setting, Registration are available in this Pdf.

Drivers and decoupling analysis of carbon emissions in the non-ferrous metal industry-evidence from 28 provinces in China.

Emissions from the non-ferrous metal industry are a major source of carbon emissions in China. Understanding the decoupling of carbon emissions from the non-ferrous metal industry and its influencing factors is crucial for China to achieve its "double carbon" goal. Here, we applied the Tapio decoupling model to measure the decoupling status and developmental trends of carbon output and emissions of the non-ferrous metal industry in China. The panel interaction fixed effects model is used to empirically analyze the influencing factors of carbon emissions in China's non-ferrous metal industry. The results show that carbon emissions from China's non-ferrous metal industry have experienced three main states: strong decoupling, growth connection, and negative growth decoupling. The carbon emissions of the non-ferrous metal industry in some eastern and central provinces from 2000 to 2004 were in a negative decoupling state. Most provinces in the western and central regions were either in a strong or weak decoupling state based on the developmental trend of the decoupling state of carbon emissions. However, from 2015 to 2019, the decoupling status of carbon emissions in most provinces in western and central China had a significantly negative, weakly negative, or a negative growth decoupling status. Energy structure, energy intensity, cost, and non-ferrous metal production all have a positive driving effect on carbon emissions in the non-ferrous metal industry. Production had a mitigating effect on carbon emissions in the non-ferrous metal industry between 2010-2014 in the eastern region of China. From the results of our study, we propose policy recommendations to promote a strong decoupling of carbon emissions from the non-ferrous metal industry by improving energy structure, reducing energy intensity, and optimizing production capacity.

The robustness and disturbance within China's industrial complex network under carbon border tariffs.

Since the European Commission proposed in July 2021 to implement a Carbon Border Adjustment Mechanism (CBAM), the impact mechanism has received increasing attention worldwide. This study aims to analyze the impact of carbon border tariffs on China's carbon-intensive industries and simulate the risk transmission within China's industrial complex network based on thecomplex network modeling and cascading failure analysis. The results showed that the industries subject to carbon border tariffs played an essential role in China's entire industrial structure, which is closely related to industries including construction, metal, and manufacturing. If the carbon border tariffs are imposed on the steel industry, China's relevant industries will be reduced by 1.29%, followed by the fertilizer industry and non-ferrous metal industry with proportions of 1.11% and 0.95%, respectively. When the industrial transmission threshold reaches 0.8, the export shocks will affect the entire industrial network, leading to a rapid growth in the number of infected industries. By depicting the industrial linkage and impact mechanism of carbon border tariffs, this study is expected to provide practical suggestions and implications for carbon-intensive industries towards sustainable low-carbon transition under carbon border tariffs.

Use of molecular composition and compound-specific isotope analysis for source appointment of PAHs in sediments of a highly industrialized area

This study utilized both conventional molecular analysis and compound-specific isotopic techniques to identify the sources of polycyclic aromatic hydrocarbons (PAHs) in sediments of Ulsan Bay, South Korea. The concentrations of 15 traditional and 11 emerging PAHs were determined in sediments from 21 source sites and 26 bay sites. The concentrations and compositions of traditional and emerging PAHs varied significantly, even at sites close to the source areas. The results obtained from diagnostic ratios and the positive matrix factorization model for source identification were inconsistent in adjacent source areas. The δ13C profiles of PAHs, such as phenanthrene (Phe), fluoranthene (Fl), pyrene (Py), and benz[a]anthracene (BaA) in the sediments showed distinct features depending on the surrounding sources. In urban sediments, lighter δ13CPhe values were observed (mean: −25.1‰), whereas relatively heavier values of δ13CPy were found in petroleum industry areas (mean: −23.4‰). The Bayesian isotope mixing model indicates that the predominant source of PAHs in Ulsan Bay sediments was the petroleum industry (45%), followed by the non-ferrous metals industry (30%), automobile industry (18%), and urban areas (6.3%). These results demonstrated the utility of stable isotopes in assessing the sources and contributions of PAHs in small-scale regions. However, there are still limitations in compound-specific isotope analysis of PAHs, including insufficient end-members for each source, difficulty in analysis, and the influence of non-point sources; thus, further study is needed to expand its application.

Research on the Factors Influencing CO2 Emission Reduction in High-Energy-Consumption Industries under Carbon Peak

In the context of reaching peak carbon emissions, it is crucial to develop carbon reduction strategies for high-energy-consuming industries as part of a broader societal transition from dependence on high-pollution energy sources to low-pollution alternatives. This study focuses on carbon emission reduction in the non-ferrous metal industry, which is known for its significant energy consumption. It employs the Logarithmic Mean Divisia Index (LMDI) model to conduct empirical analyses from three perspectives: carbon emission decomposition, regionalization analysis, and carbon emission prediction. The objective is to explore the carbon emission characteristics of high-energy-consuming industries in China and provide theoretical support for future policies aimed at reducing carbon emissions in these industries. The findings reveal that the economic scale of the non-ferrous metal industry has a positive correlation with carbon emissions, while carbon emission coefficients exhibit a negative correlation. Moreover, in the prediction scenarios considered, the increase in carbon emissions resulting from the economic-scale factor accounted for 75.28%, 87.46%, and 65.21% respectively, indicating that it has the most significant influence among all factors analyzed. The study further demonstrates that under stable and active emission reduction scenarios, the future potential for carbon dioxide emission reduction in the non-ferrous metal industry is estimated to reach 858.47 million tons and 1384.65 million tons, respectively. These figures represent twice and three times the emissions recorded in 2021. By analyzing the factors influencing emission reduction, targeted regulations can be implemented to develop practical and effective strategies for reducing carbon emissions in the industry. From the analysis conducted, it can be deduced that high-energy-consuming industries, particularly the non-ferrous metal industry, exhibit relatively high levels of carbon emissions. Consequently, it is imperative to implement proactive measures to reduce these emissions. Additionally, the industry’s carbon emissions are heavily influenced by changes in economic scale due to its high dependence on it. This highlights the importance of considering economic factors when devising strategies to mitigate carbon emissions. Furthermore, the potential for improvement in the non-ferrous metal industry’s energy structure and carbon emission coefficients is limited. Simply relying on technological innovation alone may not suffice to achieve significant emission reduction goals. Therefore, it becomes crucial for the government to develop tailored emission reduction targets and policies based on the industry’s specific circumstances to attain optimal results.

Оценка нейрофизиологических параметров состояния нервной системы у работающих в производстве цветных металлов

A comprehensive assessment of the health status includes the functional exploration of the central and peripheral nervous systems. Results of the neurophysiological examination allow elaboration of effective personified therapeutic and preventive programs for the core personnel of non-ferrous metal industry. Our objective was to study functional disorders of the central and peripheral nervous systems in smelter operators for further development of risk-based rehabilitation programs for workers engaged in production of non-ferrous metals. Two cohorts of male workers were examined. The case cohort included 60 smelter operators of a large metallurgical plant situated in the Sverdlovsk Region and the control cohort consisted of 50 unexposed employees. The cohorts were matched by age and years of work experience. The mean age of smelter operators was 37.8 ± 7.9 years and their mean length of current employment was 4.1 ± 4.6 years, while the total length of work under hazardous occupational conditions was 7.1 ± 6.0 years. The case cohort included 39 operators of refinery boilers (mean age: 35.6 ± 7.2 years, mean length of employment: 4.2 ± 4.7 years) and 21 operators of the ore thermal furnace (mean age: 41.9 ± 7.6 years, mean length of current employment: 3.9 ± 4.4 years). All subjects underwent a neurocognitive examination (higher brain function testing), electroneuromyography, the somatosensory evoked response test, and electroencephalography. The results of examining the higher brain function enabled us to form the neurocognitive profile of the workers. We revealed signs of mild cognitive impairment in 30 % and a decrease in the cognitive reserve in 35 % of the cases. The diagnosed peripheral nervous system disorders included distal sensory polyneuropathy of the upper and lower extremities, carpal and cubital tunnel syndromes, cervical and lumbar radiculopathy. The comprehensive neurophysiological examination helps detect early changes in the central and peripheral nervous systems. The findings should be taken into account when developing personal medical rehabilitation programs.

Assessment of neurophysiological parameters of the nervous system in non-ferrous foundry workers

A comprehensive assessment of the health status includes the functional exploration of the central and peripheral nervous systems. Results of the neurophysiological examination allow elaboration of effective personified therapeutic and preventive programs for the core personnel of non-ferrous metal industry. Our objective was to study functional disorders of the central and peripheral nervous systems in smelter operators for further development of risk-based rehabilitation programs for workers engaged in production of non-ferrous metals. Two cohorts of male workers were examined. The case cohort included 60 smelter operators of a large metallurgical plant situated in the Sverdlovsk Region and the control cohort consisted of 50 unexposed employees. The cohorts were matched by age and years of work experience. The mean age of smelter operators was 37.8 ± 7.9 years and their mean length of current employment was 4.1 ± 4.6 years, while the total length of work under hazardous occupational conditions was 7.1 ± 6.0 years. The case cohort included 39 operators of refinery boilers (mean age: 35.6 ± 7.2 years, mean length of employment: 4.2 ± 4.7 years) and 21 operators of the ore thermal furnace (mean age: 41.9 ± 7.6 years, mean length of current employment: 3.9 ± 4.4 years). All subjects underwent a neurocognitive examination (higher brain function testing), electroneuromyography, the somatosensory evoked response test, and electroencephalography. The results of examining the higher brain function enabled us to form the neurocognitive profile of the workers. We revealed signs of mild cognitive impairment in 30 % and a decrease in the cognitive reserve in 35 % of the cases. The diagnosed peripheral nervous system disorders included distal sensory polyneuropathy of the upper and lower extremities, carpal and cubital tunnel syndromes, cervical and lumbar radiculopathy. The comprehensive neurophysiological examination helps detect early changes in the central and peripheral nervous systems. The findings should be taken into account when developing personal medical rehabilitation programs.

Preparation of battery-grade Li2CO3 efficiently by high shear dispersion at low temperature

With the significant increase of market demand, battery-grade lithium carbonate has become an imperative research. However, it is difficult for commercially available battery-grade lithium carbonate to simultaneously meet all criteria such as dispersion, particle size, particle size distribution, and purity. Here, we proposed a flexible method to prepare battery-grade lithium carbonate with small particle size, uniform size distribution, high purity, and good dispersion by using a high shear dispersion reactor under low-temperature conditions. First, a numerical simulation model was established, and the feasibility of this proposed method was verified by computational fluid dynamics (CFD). Then, the factors of yield optimization on Li2CO3 were analyzed based on response surface methodology (RSM) by using a 3-level 4-factor Box-Behnken statistical design with a fixed lithium solution concentration as the input parameter. Moreover, the reaction kinetics, size distribution, crystal morphology, and purity of Li2CO3 were investigated. The obtained Li2CO3 possessed the average particle size in 5.85 μm and total particle size range from 1.56 to 12.97 μm, which both exhibited a ten-fold reduction compared with it prepared under conventional preparation conditions. Finally, the Li2CO3 products with 99.81% purity met the requirements of the Chinese non-ferrous metal industry standard (YS/T582-2013) for battery-grade Li2CO3. We anticipate that this work may shed light on developing efficient and controllable method for the preparation of battery-grade Li2CO3.

Effect of pH value on effectiveness of biopolymer-based treatment of bauxite mine slurry

Effective dehydration and flocculation of mine slurries or sludge is important for nonferrous metal industries and environmental engineering. However, the mechanisms for the flocculation of slurry remain largely unclear. This paper presents the results of a series of flocculation tests, which was conducted on the slurry suspensions treated by xanthan gum (flocculant) at different pH values. It is shown that the settlement rate of mine slurry particles can be accelerated by adding xanthan gum, and the maximum sedimentation rate was obtained at a pH value of 5.9, and the final volume of flocs is significantly increased due to the addition of the flocculant. In addition, the settlement rates of xanthan gum-treated slurry suspensions at the pH values of 3, 5 and 7 decrease slightly compared with the reference slurry suspensions with pH=5.9, and the slurries remained stable as suspensions at the pH value of 9 and 11. The zeta potential measurement and SEM image analysis show that flocculation occurs primarily due to electrostatic attraction between slurry particles and the flocculants, and the bridging effect between the carboxylic groups in the side chains of xanthan gum molecule and the suspension particles.

Potential of major by-products from non-ferrous metal industries for CO2 emission reduction by mineral carbonation: a review.

By-products from the non-ferrous industry are an environmental problem; however, their economic value is high if utilized elsewhere. For example, by-products that contain alkaline compounds can potentially sequestrate CO2 through the mineral carbonation process. This review discusses the potential of these by-products for CO2 reduction through mineral carbonation. The main by-products that are discussed are red mud from the alumina/aluminum industry and metallurgical slag from the copper, zinc, lead, and ferronickel industries. This review summarizes the CO2 equivalent emissions generated by non-ferrous industries and various data about by-products from non-ferrous industries, such as their production quantities, mineralogy, and chemical composition. In terms of production quantities, by-products of non-ferrous industries are often more abundant than the main products (metals). In terms of mineralogy, by-products from the non-ferrous industry are silicate minerals. Nevertheless, non-ferrous industrial by-products have a relatively high content of alkaline compounds, which makes them potential feedstock for mineral carbonation. Theoretically, considering their maximum sequestration capacities (based on their oxide compositions and estimated masses), these by-products could be used in mineral carbonation to reduce CO2 emissions. In addition, this review attempts to identify the difficulties encountered during the use of by-products from non-ferrous industries for mineral carbonation. This review estimated that the total CO2 emissions from the non-ferrous industries could be reduced by up to 9-25%. This study will serve as an important reference, guiding future studies related to the mineral carbonation of by-products from non-ferrous industries.

Analysis of China's non-ferrous metals industry's path to peak carbon: A whole life cycle industry chain based on copper

Copper is an essential nonferrous metal, and the adjustment of its whole industry chain structure is conducive to realizing a carbon peak in the nonferrous metal industry. We have performed a life cycle assessment to calculate the carbon emissions of the copper industry. Based on the carbon emissions scenarios of shared socioeconomic pathways (SSPs), we have utilized material flow analysis and system dynamics to analyze the structural changes in the copper industry chain from 2022 to 2060 in China. The results show that (1) the flows and in-use stocks of all types of copper resources will increase significantly. The overall copper supply may meet demand around 2040–2045 due to secondary copper production potentially replacing primary copper production to a large extent, and trade supply is the primary pathway for meeting copper demand. (2) The total carbon emissions from the regeneration system are the smallest (4 %), followed by the production and trade subsystems, accounting for 48 %. The embodied carbon emissions from copper product trade in China have expanded annually. (3) Under the SSP scenario, the copper chain carbon emission peak will be achieved by approximately 2040. Based on a balanced copper supply and demand scenario, the recycled copper recovery efficiency must reach 84.6 %, and the energy structure (the proportion of non-fossil energy in electricity) must reach 63.8 % by 2030 to achieve the carbon peak target for the copper industry chain in China. The above conclusions indicate that actively promoting adjustments in the energy structure and resource recovery processes may help encourage the carbon peak of nonferrous metals in China by realizing the carbon peak of the copper industry.

Analisis Sifat Mekanik Pada Material Standar Paduan COR ALSi10Mg(b) Dari Skrap Aluminium

The metal industry in Tegal Regency is classified into ferrous and non-ferrous metal industries. The shipping component industry is the leading producer of the non-ferrous metal industry. The problem faced by the non-ferrous metal processing industry, especially the Small and Medium Industry ship components is the availability of standard materials as raw materials at affordable prices. Instead, SMEs use scrap material to reduce selling prices, as a result of which product quality does not meet the required specifications. This research made 2 (two) formulas of AlSi10Mg(b) from an aluminum scrap mixture where AlSi10Mg(b) is one of the standard materials of cast aluminum alloy recognized by Biro Klasifikasi Indonesia (BKI). The study aimed to recommend raw material formulas to SMEs to ship components to make products according to BKI standards. The research began by collecting a database of aluminum scrap composition, then simulating calculations with an Excel program to obtain theoretical chemical composition so that the need for aluminum scrap was produced. The two standard material formulas of AlSi10Mg(b) are made from different main scrap where formula 1 is the piston, and formula 2 is the brake lining with the supporting scrap is the pan, aluminum elbow, and aluminum plate as well as the AlSi49 and AlMg20 master alloys. The simulation results are then cast with the sand-casting method. The cast results are made of specimens testing chemical composition and hardness. The results of the chemical composition test show that both formulas are in accordance with the conditions of AlSi10Mg(b) cast alloy, namely the percentage of Silicon (Si) and Magnesium (Mg) in formula 1 is 9.16% and 0.39% while formula 2 is 10.69% and 0.22%. Both formulas are still with Copper (Cu) content that still exceeds the limit of above 0.1%. The hardness value has met BKI standards above 50HBN.

Has China’s carbon emissions trading (CET) policy improved green investment in carbon-intensive enterprises?

This paper develops an intertemporal theoretical model of enterprises’ green investment behavior to reveal the role of carbon emissions trading (CET) in promoting enterprise green investment. Then, based on the panel data of China's carbon-intensive listed enterprises in 2009–2017, this paper employs the difference-in-differences (DID) method to empirically evaluate the effect of CET on enterprise green investment and discusses the regional and industrial heterogeneity of this effect. The results indicate that: first of all, in theory, China’s CET can improve the green investment ratio of CET-covered enterprises; however, in the sample period, the CET reduced green investment ratio by 0.4% in CET-covered enterprises. Second, the CET increased the green investment ratio of CET-covered enterprises in Hubei by 12%, but decreased the green investment ratio by 4% and 49% in Guangdong and Tianjin, respectively, and it had no significant effect on enterprise green investment in other CET pilots. Third, the CET had a subtle promotional effect on the green investment of CET-covered enterprises in chemical and nonferrous metal industries, with the opposite effect on other carbon-intensive industries.