Chinese Cement Research Articles

Early Opportunities for Onshore and Offshore CCUS Deployment in the Chinese Cement Industry

The promotion of deep decarbonization in the cement industry is crucial for mitigating global climate change, a key component of which is carbon capture, utilization, and storage (CCUS) technology. Despite its importance, there is a lack of empirical assessments of early opportunities for CCUS implementation in the cement sector. In this study, a comprehensive onshore and offshore source–sink matching optimization assessment framework for CCUS retrofitting in the cement industry, called the SSM-Cement framework, is proposed. The framework comprises four main modules: the cement plant suitability screening module, the storage site assessment module, the source–sink matching optimization model module, and the economic assessment module. By applying this framework to China, 919 candidates are initially screened from 1132 existing cement plants. Further, 603 CCUS-ready cement plants are identified, and are found to achieve a cumulative emission reduction of 18.5 Gt CO2 from 2030 to 2060 by meeting the CCUS feasibility conditions for constructing both onshore and offshore CO2 transportation routes. The levelized cost of cement (LCOC) is found to range from 30 to 96 (mean 73) USD·(t cement)−1, while the levelized carbon avoidance cost (LCAC) ranges from −5 to 140 (mean 88) USD·(t CO2)−1. The northeastern and northwestern regions of China are considered priority areas for CCUS implementation, with the LCAC concentrated in the range of 35 to 70 USD·(t CO2)−1. In addition to onshore storage of 15.8 Gt CO2 from 2030 to 2060, offshore storage would contribute 2.7 Gt of decarbonization for coastal cement plants, with comparable LCACs around 90 USD·(t CO2)−1.

Effect of Variable Synthesis Conditions on the Formation of Ye'elimite-Aluminate-Calcium (YAC) Cement and Its Hydration in the Presence of Portland Cement (OPC) and Several Accessory Additives.

In the presented study, ye'elimite-aluminate-calcium (YAC) cement was synthesized. Complete synthesis of crystalline phases was achieved at a temperature of 1300 °C, which is 150 °C lower than the temperature standardly used in the processes of obtaining calcium aluminate cements (CAC). The greatest amount of ye'elimite phase (Klein complex), roughly 87% by mass, was acquired utilizing a sulphur ion transporter derived from artificial dihydrate gypsum obtained in the flue gas desulphurization process (variation I). In the case of anhydrite, the amount of synthesized crystalline ye'elimite in the clinker was 67% by weight (variant II). Depending on the synthesis conditions in the clinkers, the quantity of obtained calcium aluminates (C12A7, CA, and CA2) ranged from 20 to 40% by weight. Studies on the hydration process of YAC cement samples showed that the main products are hydrated calcium aluminates and dodecahydrate calcium alumino-sulphate. In sinters of YAC and OPC, no crystalline ettringite was observed. Hydration analysis of Chinese cement revealed the presence of crystalline ettringite and dodecahydrate calcium alumino-sulphate, as well as hydrated calcium silicates of the CSH type accompanied with pseudo-crystalline Al(OH)3. The obtained clinkers from variants I and II constitute a special binder, which, due to its phase composition after hydration, can be used in the construction of reactors for biogas production in eco-energy applications.

An Industrial Load Classification Method Based on a Two-Stage Feature Selection Strategy and an Improved MPA-KELM Classifier: A Chinese Cement Plant Case

Accurately identifying industrial loads helps to accelerate the construction of new power systems and is crucial to today’s smart grid development. Therefore, this paper proposes an industrial load classification method based on two-stage feature selection combined with an improved marine predator algorithm (IMPA)-optimized kernel extreme learning machine (KELM). First, the time- and frequency-domain features of electrical equipment (active and reactive power) are extracted from the power data after data cleaning, and the initial feature pool is established. Next, a two-stage feature selection algorithm is proposed to generate the smallest features, leading to superior classification accuracy. In the initial selection phase, each feature weight is calculated using ReliefF technology, and the features with smaller weights are removed to obtain the candidate feature set. In the reselection stage, the k-nearest neighbor classifier (KNN) based on the MPA is designed to obtain the superior combination of features from the candidate feature set concerning the classification accuracy and the number of feature inputs. Third, the IMPA-KELM classifier is developed as a load identification model. The MPA improvement strategy includes self-mapping to generate chaotic sequence initialization and boundary mutation operations. Compared with the MPA, IMPA has a faster convergence speed and more robust global search capability. In this paper, actual data from the cement industry within China are used as a research case. The experimental results show that after two-stage feature selection, the initial feature set reduces the feature dimensionality from 58 dimensions to 3 dimensions, which is 5.17% of the original. In addition, the proposed IMPA-KELM has the highest overall recognition accuracy of 93.39% compared to the other models. The effectiveness and feasibility of the proposed method are demonstrated.

Environmental performance of the Chinese cement enterprise: An empirical analysis using a text-based directional vector

Cement industry is both energy-intensive and pollution-intensive, imposing significant negative externalities on sustainability. However, previous studies have not sufficiently focused on China's cement industry; thus, there is a lack of information on efficiency and cost, limiting policy effectiveness. Using a directional-distance-function-based model and firm-level data, this study measures the technical efficiency and shadow price of SO2 and PM in China's cement industry from 1998 to 2010. In response to the debates on the selection of directional vector, this is the first study that proposes a new directional vector determined via text analysis. We use the five-year plans as a breakthrough point to construct a corpus, establish a lexicon, and introduce a text analysis in order to reveal the policy preference, and finally, solve this directional vector. Through this improvement, we highlight the inherent meanings of the directional vector and provide a new insight into the directional-distance-function-based method. We solve this new directional vector to be (0.98, −0.13, −0.13), implying that the preference for economic growth is significantly greater than that for environmental protection. The conditional median marginal abatement costs of SO2 and PM are estimated to be 29,070 and 1374 yuan/ton, respectively. The annual trends of technical efficiency and shadow price are depicted, and the heterogeneities of regions, provinces, cities, and pollutants are revealed.

Equilibrium Optimizer-Based Joint Time-Frequency Entropy Feature Selection Method for Electric Loads in Industrial Scenario

A prerequisite for refined load management, crucial for intelligent energy management, is the precise classification of electric loads. However, the high dimensionality of electric load samples and poor identification accuracy of industrial scenarios make it difficult to be used in actual production. As such, this research presents a selection approach equilibrium optimizer-based joint time-frequency entropy feature selection method for electric loads in industrial scenarios to address these issues. The method first introduces entropy value features based on extracting time-frequency domain features and then uses an equilibrium optimizer (EO) to screen the joint feature set. A Chinese cement plant was chosen as the acquisition site for the experiments, and the low-frequency data from power equipment were gathered to form an original dataset for power analysis. The features screened by the EO were used as model inputs to verify the effectiveness of the EO on the joint feature set under K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), random forest (RF), and discriminant analysis (DA) models. Experimental results show that introducing entropy value features for the joint feature set can significantly improve the classification performance. The average accuracy of the features screened by the EO was as high as 95.58% on SVM, while the computation time was 0.75 s. Therefore, for industrial electricity scenarios, the approach suggested in this research can enhance the identification accuracy of electric loads and significantly reduce the computation time of the model to a great extent. This has essential research significance for intelligent energy management in real industrial scenarios.

Emission characteristics of dioxin during solid waste co-processing in the Chinese cement industry

Development of co-processing technology in the cement industry in China is important for environmentally sound disposal and recycling of waste, and contributes to sustainable development of the cement industry. However, dioxin pollution could negatively affect promotion of this technology. Therefore, it is necessary to study the emission characteristics of dioxins in cement kilns. In this study, the emission characteristics of dioxins and factors influencing their generation during co-processing solid wastes were studied in 14 new dry cement kilns. The dioxin concentrations were very similar regardless of whether solid wastes were fed into the kiln. In blank runs without co-processing, the average dioxin concentration was 0.0097 ng international toxic equivalents (I-TEQ)/Nm3. By comparison, that for co-processing solid wastes was 0.012 ng I-TEQ/Nm3. These values meet the relevant emission standards. The type of co-processed solid wastes had almost no effect on the dioxin concentration. At larger production scales, the concentration of dioxin emitted in the flue gas decreased. The dioxin concentrations in kiln dust were obviously higher than those in clinker and raw materials. The average emission factor of dioxin per ton of cement was 30 ng I-TEQ/t, which is equivalent to that in cement kilns in other countries.

Emission characteristics and inventory of volatile organic compounds from the Chinese cement industry based on field measurements

Volatile organic compounds (VOCs) are major precursors of ozone (O3) and secondary organic aerosols (SOA), which degrade air quality and pose a serious risk to human health and ecological systems. Previous studies on the emission characteristics of VOCs have predominantly focused on petrochemical and solvent-using sources, while localized studies on the cement industry are scarce in China. Field measurements for four cement plants were carried out in this study to investigate the emission levels, source profiles, and secondary pollutant generation potential of 98 VOCs species emitted from rotary and shaft kilns in China. Furthermore, a species-differentiated VOCs emission inventory was compiled for the Chinese cement industry in 2019. The results demonstrated that the mass concentration of VOCs emitted from shaft kiln was more than 20-fold higher than that emitted from rotary kilns, and the alkanes was the dominant species (56%) in shaft kilns, while oxygenated VOCs (OVOCs) and halocarbons were the main species in rotary kilns. Moreover, alkenes & alkyne were the dominant contributors to ozone formation potential (OFP) in shaft kilns, whereas alkenes & alkyne and OVOCs were comparable and prominent contributors in rotary kilns. In contrast, secondary organic aerosol potential (SOAP) for the two types of kilns was dominated by aromatics. In 2019, approximately 18.18 kt VOCs were emitted from cement production and were found to be largely concentrated in the southeast and central provinces of China. Considering the influence on environmental conditions, high OFP-contributing species in cement kilns are suggested to be a priority in the pollution mitigation of O3. This study provides a new, comprehensive, and reasonable cognition of the current VOCs emissions from both rotary and shaft kilns in China, which will aid in a better understanding of VOCs emission characteristics and guide future policy-making.

Environmental Regulation, Technological Innovation and Industrial Environmental Efficiency: An Empirical Study Based on Chinese Cement Industry

China’s cement production has been the highest worldwide for decades and contributes significant environmental pollution. Using the DEA-Tobit model, the paper empirically analyzes the impact of environmental regulation and technological innovation on industrial environmental efficiency with data from the Chinese Cement Industry. The results show that both environmental regulation and technological innovation have a significant role in promoting the environmental efficiency of the cement industry. Among all the influencing factors, the improvement of pollution disposal capacity has the biggest positive effect on environmental efficiency, while the energy-saving effect caused by environmental regulation is not obvious, the factor endowment structure has no substantial impact on environmental efficiency. Adhering to the strategy of “reducing emissions mainly and saving energy as auxiliary”, continuously optimizing the energy consumption structure, raising the level of industrialization and industrial agglomeration are conducive to the sustainable development of the Chinese cement industry.

Granger Causality Analysis of Foreign Trade in Cement Products and Ecological Impact in China

This paper presents an in-depth study and analysis of the impact of foreign trade on cement products and the ecological environment in China through Granger causality analysis. Based on the theoretical basis of foreign trade, ecological environment, and the relationship between them, a general equilibrium model is used to empirically analyze the “three effects” of foreign trade in Chinese cement products on the ecological environment, and the effects of import and export trade on ecological environment and the net effects are calculated, respectively. Then, based on the data of domestic and foreign cement product production and trade, the purpose, scope, and environmental impact factors of the ecological impact of foreign trade of Chinese cement products were determined by the life cycle assessment method, and the inventory analysis was carried out in phases based on the six aspects of nonrenewable resource depletion, global warming, photochemical ozone generation, acidification, eutrophication, and human health damage. The results were characterized and standardized, and the hierarchical analysis method was used to weight the evaluation of each environmental impact type, and finally, the resource consumption coefficient and environmental impact load index values and corresponding ratios were determined based on the green product evaluation method. This paper establishes an index system for the ecological and environmental impacts of foreign trade of cement products, which is a guide for the ecological and environmental impacts of foreign trade of other products in China. The results of the study on the ecological and environmental impacts of foreign trade of Chinese cement products also have important practical significance for the formulation of regulations and standards related to the cement industry, the adjustment of the import and export structure of cement products, and the improvement of production equipment and processes.

Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model

In recent decades, China’s cement production has been the highest in the world, but the extensive development model, which has been formed for a long time, has brought serious damage to the natural environment. In order to promote the transformation of the production mode of China’s cement industry, this paper adopts the nonparametric frontier method to analyze the environmental efficiency of China’s cement manufacturing industry using the input–output and pollutant emission data of China’s cement manufacturing industry from 2004 to 2016. The results show that the overall environmental efficiency of China’s cement industry is low, and there is still much room for improvement. Moreover, there are serious imbalances from very low to very high between different regions. Further investigation found that during the study period, strict environmental supervision brought an average compliance cost of CNY 23.41 billion to China’s cement manufacturing industry, but the overall environmental efficiency increased by 23.9 percentage points. Based on these findings, we believe that the focus of environmental supervision of China’s cement manufacturing industry at this stage is to reduce pollution emissions, and force cement enterprises to carry out technological innovation through mandatory emission reduction measures. When formulating policies, the Chinese government needs to explore the best way for environmental supervision between minimizing compliance costs and maximizing efficiency, so as to promote the sustainable development of China’s cement manufacturing industry.

Emission Characteristics of Dioxin During Solid Waste Co-Processing in the Chinese Cement Industry

Emission Characteristics of Dioxin During Solid Waste Co-Processing in the Chinese Cement Industry

Assessment of popular techniques for co-processing municipal solid waste in Chinese cement kilns

Assessment of popular techniques for co-processing municipal solid waste in Chinese cement kilns

The impact of environmental regulation on firm performance: Evidence from the Chinese cement industry

The relationship between environmental regulation and firm performance is a central question in environmental economics. Although many empirical works study this question, economists have not reached a consensus on the nature of the relationship or the mechanism that drives it. Based on the off-peak production policy in the Chinese cement market, this paper uses the differences-in-differences model to study the impact of environmental regulation on the revenue and profit of listed companies. We find that the environmental regulation has negative impacts on firms’ revenue and profit. According to further analysis, the main reason for this firm performance decline is that the relatively large elasticity of market demand prevents enterprises from passing regulatory costs through to consumers. Although the policy has caused the cement price to increase by 8%, it has led cement consumption to decrease by 16%.

Co-control effect evaluation of the energy saving and emission reduction measures in Chinese cement industry

Co-control effect evaluation of the energy saving and emission reduction measures in Chinese cement industry

Establishment of High-Resolution Atmospheric Mercury Emission Inventories for Chinese Cement Plants Based on the Mass Balance Method.

China is the world's largest cement-related mercury emitter. Atmospheric mercury inventories for China's cement industry are essential for appraising global mercury emissions and have been widely developed in previous studies associated with considerable uncertainties. In this study, we compiled high tempo-spatial resolution atmospheric mercury emission inventories for Chinese cement plants using the mass balance method and plant-level input-output data. The effects of industry policies were investigated based on the inventories for 2007 and 2015. Nationwide emissions increased from 80 to 113 t due to rapid expansion of production and kiln-type substitution yet partly offset by policies involving capacity structure reformation. Pollution decreased in winter in northern China, thanks to the targeting policies. Mercury input, output, and storage in cement kilns in China were estimated. The uncertainty remarkably decreased relative to previous inventories. This study demonstrates the feasibility of establishing high-resolution emission inventories with the application of the mass balance method for all the individual plants nationwide and thus has implications for similar studies. This work also improves our understanding of the spatial patterns and temporal evolution of mercury emissions in China, thus offering references for the implementation of environment policies and the Minamata Convention on Mercury in China.

A Systematic Approach to Calculate Unit Emergy Values of Cement Manufacturing in China Using Consumption Quota of Dry and Wet Raw Materials

The Chinese cement industry produced 2150 million metric tons of cement in 2014, accounting for 58.1% of the world’s total. This industry has a hugely destructive effect on the environment owing to its pollution. The environmental impact of cement manufacturing is a major concern for China. Although researchers have attempted to estimate impacts using life cycle assessment approaches, it lacks the ability to provide a holistic evaluation of the impacts on the environment. Emergy analysis, through ecological accounting, offers environmental decision making using elaborate book keeping. In spite of the high environmental impact of the cement industry, there has only been a handful of research work done to compute the unit emergy values (UEVs) of cement manufacturing in China. A thorough study of existing UEVs of cement manufacturing in China showed pitfalls that may lead to inaccurate estimations if used in emergy analysis. There is a strong need for a new, updated UEV for cement manufacturing in China, particularly reflecting both the dry and wet raw materials in the manufacturing process. This paper develops a methodology to calculate the nonrenewable resources used in cement manufacturing, particularly using mainstream cement production line. Our systematic approach-based UEV estimates of cement manufacturing in China using the quota method are 2.56 × 1012 sej/kg (wet material) and 2.46 × 1012 sej/kg (dry material). Emergy indicators such as environmental loading ratios which were calculated at 2390 (wet material) and 2300 (dry material); emergy yield ratios at 15.7 and 15.8; and emergy sustainability indices at 0.0066 and 0.0069 for dry and wet materials used in cement manufacturing, respectively; these show the immense impact on the environment in China.

Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion

The cement industry is a significant contributor to anthropogenic CO2. For China, the cement industry is crucial for development, considering the surging urbanization. CO2 emissions from the industry are detrimental to the planet, its ecosystem, and inhabitants. Forecasting of the emissions is a critical step in the emissions' mitigation strategies, and to achieve sustainable development. However, the level of uncertainty accompanying CO2 estimates leads to discrepancies in predictions. The current work aims to study the estimation of cement industry CO2 emissions from an uncertainty-driven technical perspective, and present a forecast for the Chinese cement industry emissions using a novel grey prediction model. By modeling the framework of China's cement industry and the CO2 emissions estimation techniques as grey systems with partially known information, this study develops an interval grey number-based approach to calculate the relative uncertainty. A grey sequence is generated from the whitenization of the interval grey numbers to represent annual emissions from different sources. The proposed approach is more flexible than the conventional midpoint estimate-based approach recommended by JCGM. The proposed model, V-GM(1,N), is found to give the highest accuracy of 97.29% in simulating the actual cement industry CO2 emissions data from 2005 to 2018. Comparative analysis of the proposed model with other forecasting models revealed the superiority of the model. The proposed framework, involving the forecasting model and uncertainty analysis approach, is likely to facilitate the decision-makers in making realistic and reliable forecasts at reasonable computational costs.

CO2 emissions from the Chinese cement sector: Analysis from both the supply and demand sides

AbstractChina is the largest producer and consumer of cement worldwide, and cement production entails the release of substantial carbon dioxide (CO2) emissions. As the cement sector is a crucial sector of the Chinese economy, understanding the role of supply‐ and demand‐side factors may help accelerate efforts to mitigate CO2 emissions. However, few studies have analyzed the critical factors affecting CO2 emissions in the sector based on a combined supply‐ and demand‐side perspective. In this study, we developed an integrated framework that included eleven indicators covering both the supply and demand sides. Results revealed that improving cement production technology cannot offset CO2 emissions from the growth in demand for cement. Improving technology on the supply side would considerably reduce CO2 emissions from Chinese cement production; nevertheless, the combination of rapid urbanization, GDP growth, and an ultra‐high fixed capital formation ratio on the demand side increased CO2 emissions nearly 25‐fold from 1990 to 2015. Notably, some demand‐side factors also had an effect that reduced CO2 emissions. The in‐use stock per unit of fixed capital formation and output per in‐use stock reduced CO2 emissions by 332 million metric tons, which is comparable to the contribution of technological progress. Based on these results, we examine why these demand‐side factors substantially influence CO2 emissions in the Chinese cement sector, and we provide recommendations for policy‐makers on carbon‐reduction measures in this CO2‐intensive sector.

The hydration properties of blended cement containing ultrafine fly ash with particle size less than 17 μm from the circulating fluidized bed combustion of coal gangue

This paper presents the proposal of the particle size range of circulating fluidized bed fly ash (CFA) that was positively associated with properties of blended cement by gray correlation analysis. Then, the hydration characteristics of blended cement containing ultrafine CFA (UCFA) with the above-suggested particle size distribution are studied from the physical and mechanical properties, hydration heat, non-evaporable water content, morphologies and pore structure. The results show that there is a positive association between CFA particles of less than 17 μm (especially 3–8 μm) and property of blended cement, while there is a negative association for particles of more than 17 μm, so the particles content of less than 17 μm should be improved in CFA as much as possible. The industrial UCFA, whose particle content of less than 17 μm reaches 98.18%, is prepared. The blended cement containing 10% UCFA possesses excellent properties, which ever surpasses pure portland cement. Furthermore, the physical and mechanical properties of blended cement containing no more than 30% UCFA meets the Chinese cement standard of 42.5 grade. With increase in the addition amount of UCFA, the hydration rate and degree of blended cement are gradually decreased and the influence is small at the addition amount of no more than 30%. The addition of 10% UCFA can optimize the pore structure of cement system, and the effect of 30% UCFA on the microstructure of cement gradually decreases with ages.

Calculating of CO2 emission factors for Chinese cement production based on inorganic carbon and organic carbon

Cement industry is one of the largest anthropogenic carbon dioxide (CO2) emitters in the world, and its emission accounts for 5–7% of the total anthropogenic CO2 emission. As the biggest cement producer, China has attracted worldwide attention in mitigating cement CO2 emission. Many studies did not reflect China's actual emission due to not fully knowing the de-facto cement production in China. The carbon emission factors (EFs) are important parameters to calculate CO2 emission. There are uncertainties in determining Chinese carbon emission factors on cement production. This study analyzed the composition of samples from cement production lines in China and used the raw material carbonate method (RMCM) to calculate process-related EFs of new suspension pre-heater and pre-calciner (NSP) kilns, and it shows that RMCM is more accurate and simpler than other methods. This research also indicates that process-related EF is more accurate when calculation is based on the carbonate (inorganic carbon, IC) decomposition ratio, and the combustion-related EF is more proper when multiplying the total organic carbon (TOC) by the organic carbon combustion ratio, because the majority of the clinkers always contain small amounts of the carbonate that are not fully decomposed and small amounts of fossil fuels (FFs) that are not completely combusted.