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With the continuous development of global economic and trade activities, environmental problems have become an important factor restricting the sustainable development of all countries. How to realize the coordinated development of international trade and environmental protection has become a major issue facing the international community. Since China joined the WTO, its share of international trade has been increasing continuously. In order to deeply analyze the influence of international carbon emission trading policy on domestic carbon emissions, we use an input–output model and a GTAP analysis method to theoretically calculate the carbon emissions of the international trade of various departments in Shandong Province. At the same time, the implicit carbon emission index of various industries in 2022 is calculated through the direct energy consumption coefficient. The results show that there are significant differences in the impact of the carbon tariff system on different industries. In terms of the carbon emission index, the food processing industry showed a decrease of 18.99 Mt, while the implied carbon emission of the tobacco, textile and leather manufacturing industry reached 30.56 Mt due to the continuous expansion of trade scale. In contrast, the implied carbon emission level of the metal product processing industry reached 5.3 Mt, while the carbon emission of traditional trading industries such as coal mining was almost unaffected by international trade, and its carbon emission index reached the highest level of 5.89 in 2020. In terms of trade impact, high-trade industries such as the food processing industry are significantly affected by the carbon tariff policy, and their share has dropped from 5.89% to 3.95% in the past decade. The carbon emissions generated by GDP growth established by the GTAP model are more convincing. This model can directly reflect the energy efficiency of a region from the side. Based on the present situation of international trade, this paper analyzes the inequality of the current carbon tariff system, and puts forward some policies to optimize the energy structure to reduce carbon emissions and expand domestic demand to reduce the dependence on international trade. Through the GTAP model, we put forward policy suggestions to optimize the energy structure to reduce carbon emissions and the dependence on international trade by expanding domestic demand. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in China's manufacturing sector, the low-carbon transition of the steel industry is urgent. CO2 capture, utilization, and storage (CCUS) technology is one of the effective measures to reduce carbon emissions in steel industry. In this paper, a comprehensive assessment model of source–sink matching-levelized cost in China's steel industry is constructed to evaluate the potential, economy, and spatial distribution of CCUS retrofits of blast furnaces in the BF-BOF steel industry. The results show that, if no extra incentive policy is included, the levelized cost of carbon dioxide (LCOCD) of 111 steel plants with a 420.07 Mt/a CO2 abatement potential ranges from −134.87 to 142.95 USD/t. The levelized cost of crude steel (LCOS) range of steel plants after the CCUS retrofits of blast furnaces is 341.81 to 541.41 USD/t. The incentives such as carbon market and government subsidies will all contribute to the early deployment of CCUS projects. The CCUS technology could be prioritized for deployment in North China, Northwest China, and East China's Shandong Province, but more powerful incentives are still needed for current large-scale deployment. The research results can provide references for the early deployment and policy formulation of CCUS in China's steel industry. [ABSTRACT FROM AUTHOR]

Renewable energy's integral role in addressing the global climate crisis underscores the importance of crafting coordinated policies to bolster its growth. Shandong Province, as China's largest carbon emitter, presents an intriguing case study. Leveraging policy text analysis and the coupling coordination model, this research investigates the interplay among the diverse policy instruments within Shandong Province's renewable energy policies. The findings reveal a harmonious and varied array of policy instruments. Yet, notable disparities emerge when examining secondary policy instruments across different types of renewable energy. Consequently, this paper offers strategic recommendations to improve the coupling coordination and utilization of policy instruments across various types of renewable energy. The ultimate aim is to strengthen policy synergies, overhaul the energy structure, and make a meaningful contribution to global climate change mitigation efforts. [ABSTRACT FROM AUTHOR]

Carbonation curing on steel slag is one of the most promising technologies for the iron and steel industry to manage its solid waste and carbon emissions. However, the technology is still in its demonstration stage. This paper investigates the market stakeholders of carbonation curing on steel slag for construction materials for its effective application by taking China as a case study. A holistic analysis of the competition, market size, and stakeholders of carbonation curing on steel slag was carried out through a literature review, a survey, a questionnaire, and interviews. The results showed that carbonation curing on steel slag had the advantages of high quality, high efficiency, low cost, and carbon reduction compared with other technologies. Shandong province was the most suitable province for the large-scale primary application of the technology. Stakeholder involvement to establish information platforms, enhance economic incentives, and promote adequate R&D activities would promote carbonation curing of steel slag into practice. This paper provides a reference for the commercialization of carbonation curing on similar calcium- and magnesium-based solid waste materials. [ABSTRACT FROM AUTHOR]

To understand the change in overburden structure after coal seam group mining, we investigated the overburden characteristics and bearing capacity of abandoned coal mines in a coal seam group. We provide a theoretical basis for the construction and utilization of a coal mining subsidence area under a complex geological environment. This paper takes the construction project of Zhongtie Huizhi Square in Zhangqiu District, Jinan City, Shandong Province as the engineering background. According to the occurrence conditions of the study area, theoretical analysis, similar simulation, numerical simulation, and engineering practice verification are used. The overburden structure characteristics of abandoned mines in a shallow-buried coal seam group were studied. The results show that the development height of the water-carrying fractured zone after the mining of the 3#, 4#, and 9# coal seams is 17 m, 19.5 m, and 27.1 m, respectively, which shows that the height of water flow in the fractured zone is proportional to the buried depth of the coal seam after coal seam mining. After the model is set aside for three months, the degree of development of the residual fracture in the goaf is analyzed, and the distribution law of residual porosity in the longwall old goaf of a shallow-buried multiple coal seam is obtained. The development rate of residual fissures on both sides of the goaf is between 20.31% and 42.31%. The residual fracture development rate in the middle is relatively small, being between 8.21% and 18.53%. We comprehensively analyzed the characteristics of overlying strata in the abandoned mine under actual stratum conditions, and compared the empirical calculation results, theoretical research, similar simulation, and numerical simulation results in the specification with the engineering practice to prove the reliability of the research. [ABSTRACT FROM AUTHOR]

Short-term load forecasting plays a significant role in the operation of power systems. Recently, deep learning has been generally employed in short-term load forecasting, primarily in the extraction of the characteristics of digital information in a single dimension without taking into account of the impact of external variables, particularly non-digital elements on load characteristics. In this paper, we propose a joint MFF-SAM-GCN to realize short-term load forecasting. First, we utilize a Bi-directional Long Short-Term Memory (Bi-LSTM) network and One-Dimensional Convolutional Neural Network (1D-CNN) in parallel connection to form a multi-feature fusion (MFF) framework, which can extract spatiotemporal correlation features of the load data. In addition, we introduce a Self-Attention Mechanism (SAM) to further enhance the feature extraction capability of the 1D-CNN network. Then with the deployment of a Graph Convolutional Network (GCN), the external non-digital features such as weather, strength, and direction of wind, etc., are extracted. Moreover, the generated weight matrices are incorporated into the load features to enhance feature recognition ability. Finally, we exploit Bayesian Optimization (BO) to find the optimal hyperparameters of the model to further improve the prediction accuracy. The simulation is taken from our proposed model and six benchmark schemes by using the bus load dataset of the Shandong Open Data Network, China. The results show that the RMSE of our proposed MFF-SAM-GCN model is 0.0284, while the SMAPE is 9.453%,the MBE is 0.025, and R-squared is 0.989, which is better than the selected three traditional machine learning methods and the three deep learning models. [ABSTRACT FROM AUTHOR]

CO2 is being considered as an effective alternative working fluid for geothermal applications due to its superior fluid dynamics and heat transfer properties compared to water. Utilizing sedimentary rocks for geothermal energy recovery through a CO2-plume geothermal system, especially in carbonate reservoirs, has been shown to be a practical approach that eliminates the need for hydraulic fracturing. However, uncertainties remain regarding the thermal and hydraulic behavior, particularly the chemical interactions between CO2 and carbonate rocks. This study develops a comprehensive wellbore–reservoir coupling reactive transport model based on specific information obtained from the Ordovician limestone geothermal reservoir in Shandong, China. The model aims to assess the feasibility of heat extraction in carbonate reservoirs by evaluating the heat extraction performance and fluid–rock interaction. The results indicate a rapid temperature drop after CO2 breakthrough due to the Joule–Thomson effect. Simultaneously, the fluid transitions into and maintains a two-phase state throughout the operation. Chemical reactions within the reservoir are not aggressive since complete mixing between unsaturated water and CO2 only occurs in the vicinity of the production well, highlighting the potential of utilizing carbonate reservoirs for efficient heat extraction in geothermal systems. Further research is needed to optimize the performance of CO2-based geothermal systems in carbonate reservoirs. [ABSTRACT FROM AUTHOR]

This paper presents an integrated approach for mathematical statistics, theoretical analysis, and a field test to investigate the distribution law of in-situ stress and its engineering practice of rock burst control. The test site is located in the Juye mining area, Shandong Province, China. The main conclusions included: (1) There are two types of in-situ stress states in the Juye mining area, σH > σV > σh (42.42%) and σH > σh > σV (57.57%), which are mainly caused by the tectonic stress of the Heze and Fushan faults (The σH, σV, and σh is the maximum principal stress, vertical principal stress or intermediate principal stress and minimum principal stress respectively). (2) The lateral pressure coefficients KH, Kh, and Kav show a non-linear distribution with increased depth, approaching 1.32, 0.96, and 1.41, respectively. The variation range of the horizontal difference stress μd is 0.09–0.58. (3) The average value of the stress gradient is 3.05 MPa/100 m, and the main directions of the maximum horizontal principal stress are northeast–southwest, and northwest–southeast. (4) A new combined supporting strategy, incorporating optimization of roadway layout, anti-impact support system design, and local reasonable pressure relief, was proposed for the rock burst control, and its validity was verified via field monitoring. All these design principles and support strategies for the rock burst control presented in this study can potentially be applied to other similar projects. [ABSTRACT FROM AUTHOR]

Medium-depth geothermal energy mainly consists of two types, hydrothermal and dry-heat rock. With huge resource reserves, its exploration and development are of great significance to the transformation of China's energy structure and the realization of the goal of "Double-Carbon". From the differences in the electrical characteristics between hydrothermal and hot dry rock geothermal resources, this project uses the numerical modeling of the wide field electromagnetic (WFEM) method as a tool to design a model of typical geothermal resources. Then, we summarize and analyze the detection capability of the WFEM by calculating the WFEM response under the conditions of different depths, resistivity values, thickness-to-depth ratios and other parameters. Moreover, aiming at the key problems faced by the WFEM in real applications, we discuss the factors affecting the detection accuracy and give solutions to improve the reliability of the detection results. Finally, the medium-depth geothermal energy detection in the Jiyang Depression of Shandong is presented as an example, showing how the WFEM detection technique was used with the inversion result profile obtained. By comparing the results of geomagnetic and seismic detection on the same survey line, it is demonstrated that the WFEM method has great potential in the exploration of medium-depth geothermal energy and can be the preferred method. [ABSTRACT FROM AUTHOR]

As the world's largest developing country, China currently is undergoing rapid urbanization and motorization, which will result in far-reaching impacts on energy and the environment. According to estimates, energy use and carbon emissions in the transportation sector will comprise roughly 30% of total emissions by 2030. Since the late 1990s, transportation-related issues such as energy, consumption, and carbon emissions have become a policy focus in China. To date, most research and policies have centered on vehicle technologies that promote vehicle efficiency and reduced emissions. Limited research exists on the control of greenhouse gases through mode shifts in urban transportation-in particular, through the promotion of public transit. The purpose of this study is to establish a methodology to analyze carbon emissions from the urban transportation sector at the Chinese city level. By using Jinan, the capital of China's Shandong Province, as an example, we have developed an analytical model to simulate energy consumption and carbon emissions based on the number of trips, the transportation mode split, and the trip distance. This model has enabled us to assess the impacts of the transportation mode split on energy consumption and carbon emissions. Furthermore, this paper reviews a set of methods for data collection, estimation, and processing for situations where statistical data are scarce in China. This paper also describes the simulation of three transportation system development scenarios. The results of this study illustrate that if no policy intervention is implemented for the transportation mode split (the business-as-usual (BAU) case), then emissions from Chinese urban transportation systems will quadruple by 2030. However, a dense, mixed land-use pattern, as well as transportation policies that encourage public transportation, would result in the elimination of 1.93 million tons of carbon emissions-approximately 50% of the BAU scenario emissions. [ABSTRACT FROM AUTHOR]

With the continuous implementation of a plan for reconstruction of "Beautiful Countryside" in China, the rural environment and appearance of rural houses have been significantly improved. However, those houses in cold areas of China have great trouble with indoor temperature and heating-related energy consumption. After investigating the current situation of the layout, building envelope, indoor temperature, and energy consumption of the rural houses renovated by the plan of "Beautiful Countryside" in Shandong Province, this paper puts forward the improvement measures of raising indoor temperature and reducing energy consumption. On this basis, a typical rural house was selected, and DesignBuilder was utilized to simulate the effects before and after the application of different renovation measures for this house. The results show that the main way to raise indoor temperature and reduce energy consumption is to improve the thermal insulation performance of the building envelope, including renovation of the roof, exterior walls, doors and windows, and attached sunspace. In addition, combined with the achievements of "Beautiful Countryside" reconstruction, this paper shall propose specific renovation practices which are suitable for different rural houses. Based on the level of economic development in rural areas, it also puts forward some feasible renovation paths for different rural areas, and further provides references for other areas to carry out relevant work in the future. [ABSTRACT FROM AUTHOR]

Concerning the vision of achieving carbon neutral and peak carbon goals, wind energy is extremely important as a renewable and clean energy source. However, existing research ignores the implicit features of the data preprocessing technique and the role of the internal mechanism of the optimization algorithm, making it difficult to achieve high-accuracy prediction. To fill this gap, this study proposes a wind speed forecasting model that combines data denoising techniques, optimization algorithms, and machine learning algorithms. The model discusses the important parameters in the data decomposition technique, determines the best parameter values by comparing the model's performance, and then decomposes and reconstructs the wind speed time series. In addition, a novel optimization algorithm is used to optimize the parameters of the machine learning algorithm using a waiting strategy and an aggressive strategy to improve the effectiveness of the model. Several control experiments were designed and implemented using 10-min wind speed data from three sites in Penglai, Shandong Province. Based on the numerical comparison results and the discussion of the proposed model, it is concluded that the developed model can obtain high accuracy and reliability of wind speed prediction in the short term relative to other comparative models and can have further applications in wind power plants. [ABSTRACT FROM AUTHOR]

The Ri-Qing-Wei Basin is a newly discovered Late Mesozoic rift basin on the eastern Shandong coast in recent years. Thick, continuous deposited source rocks are found in the Lingshan Island scientific drilling project. Therefore, it is necessary to evaluate the distribution and hydrocarbon generation potential of source rocks in this area. Organic geochemical experiments were carried out on samples from the core of LK-1 and outcrops in the Lingshan Island, the Laoshan area, and the Jimo Zhougezhuang area to evaluate the maturity, abundance, and type of organic matter in source rocks. The results show that the cumulative thickness of the source rocks in the study area is more than 500 m, and the TOC content is generally greater than 1.0%. The organic matter type is good (mainly type II1 and type II2 kerogen) and the Ro value is more than 2.0. The thermal evolution degree of the organic matter is high with natural gas predominantly generated. We carried out Rock-Eval, PY-GC and gold tube experiments on low-maturity samples of Laikong 2 and established a chemical kinetic model to quantitatively evaluate the study area in combination with sedimentary burial history and thermal history data. The results show that the total resources of the five sags in the study area are about 476 billion cubic meters, and the average resource intensity is about 82.2 million cubic meters/km2. Among them, the resource intensities of the Lingshan Island Sag and Laoshan Sag are 112.6 million cubic meters/km2 and 98.8 million cubic meters/km2, respectively. Studied sites are "small and fertile" and may be used as favorable exploration prospect areas. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the impact of pollution control on industrial production efficiency in 31 provinces and cities in the Yellow River and Non-Yellow River basins in China from 2013 to 2017, using the methods of the directional distance function (hereinafter referred to as DDF) and the technology gap ratio (hereinafter referred to as TGR) in parallel, while taking the industrial production sector (labor force, total capital formation, energy consumption and industrial water consumption) and the pollution control sector (wastewater treatment funds and waste gas treatment funds) as input variables. Undesirable outputs (total wastewater discharge, lead, SO2 and smoke and dust in wastewater) and an ideal output variable (industrial output value) are taken as output variables. It is found that the total efficiency of DDF in the Non-Yellow River Basin is 0.9793, which is slightly better than 0.9688 in the Yellow River Basin. Among the 17 provinces and cities with a total efficiency of 1, only Shandong and Sichuan are located in the Yellow River Basin. The TGR values of 31 provinces, cities and administrative regions are less than 1, and the average TGR value of the Yellow River Basin is 0.3825, which is lower than the average TGR value of the Non-Yellow River Basin of 0.5234. We can start by improving the allocation of manpower and capital, implementing the use of pollution prevention and control funds, improving the technical level of industrial production, improving pollutant emission, and increasing output value to improve overall efficiency performance. This study uses the parallel method, taking the industrial production department and the pollution control department as inputs, to objectively evaluate the changes in industrial production efficiency and technology gap in the Yellow River and Non-Yellow River basins, which is conducive to mastering the situation of pollution control and industrial production efficiency, and provides the reference for SDG-6- and SDG-9-related policy making. [ABSTRACT FROM AUTHOR]

The Ri-Qing-Wei basin is located in the central Sulu Orogeny on the eastern side of the Tanlu fault zone in eastern Shandong province. To the north, the Jiaonan uplift separates it from the Jiaolai basin, where drilling in the lower Cretaceous sedimentary rock of the Laiyang group has indicated good oil and gas reserves. Drilling in the Ri-Qing-Wei basin, in contrast, is in the preliminary exploration stage. Lingke 1, the only scientific well, is on Lingshan Island on the basin boundary, and it encountered a large set of source rocks 700 m thick. The two basins were comprehensively compared and analyzed based on comprehensive fieldwork, drilling, core data, seismic profiling, sedimentary filling sequence, tectonic evolution history, basin burial history, geothermal history, and geochemical characteristics of the source rocks. The results showed three things: (1) from the late Jurassic to the early Cretaceous (the Laiyang period), subduction of the paleo-Pacific plate under the Eurasian plate delaminated the lithospheric mantle of the Sulu Orogeny, thus forming a series of passive continental rift basins. Of these, the Ri-Qing-Wei is central and the Jiaolai is its branch. After the active rift stage in the Qingshan period and the depression stage in the Wangshi period, the burial depth of the source rocks in the Ri-Qing-Wei basin was up to 6000 m, while the maximum burial depth in the Jiaolai basin was about 3000 m. The paleogeotemperature of both basins exceeded 125 °C, indicating that the source rocks were very mature. (2) A comprehensive comparison of their geochemical characteristics—organic matter abundance, type, and maturity—showed that both basins have oil-generating potential. It is worth noting that the magmatic activity in the Qingshan period had a positive effect on the evolution of the source rocks but was not the key factor: burial depth was. (3) Oil and gas failed to accumulate in the Jiaolai basin because they were destroyed by the lateral tectonic activities. During the right-lateral strike-slip stage (50 ± 5 Ma) during the late Wangshi, the Jiaolai basin was strongly uplifted over a range of more than 1000 m by the Tanlu and Wulian-Mouji fault zones along the boundary. The Wangshi group, as a cap rock, was eroded, and oil and gas overflowed along the fault that reached the surface. The late Wangshi period uplift of the Ri-Qing-Wei basin was less than 1000 m because the source rock was deeper, and the reverse faults in the basin were sealed well. The uplift did little damage to the oil in the Ri-Qing-Wei basin. Above all, tectonic evolution was the main controlling factor of oil accumulation in the study area, and the layers of the Laiyang group in the Ri-Qing-Wei basin have oil and gas potential, making it a prospective target for unconventional offshore oil and gas exploration. [ABSTRACT FROM AUTHOR]

On-site development of wave energy resources is a promising way to overcome power-shortage problems on islands. It is necessary to select suitable islands to deploy wave power plants, which are influenced by multiple factors related to resources, technology, economy, society, and environment. This study develops a two-stage decision framework to identify feasible islands and determine priority order based on geographic information systems (GIS) and multicriteria decision-making (MCDM). In the exclusion stage, unfeasible marine areas are excluded based on exclusion criteria and feasible island alternatives are identified. In the evaluation stage, alternatives are evaluated by evaluation criteria using the combined weighting method and the technique for order of preference by similarity to ideal solution (TOPSIS)-grey relation analysis (GRA) method. As the combined weighting method is based on the fuzzy group decision-making (GDM)-analytic hierarchy process (AHP) and the entropy method, it can effectively reduce subjective deviation. The proposed framework is applied in Shandong Province. It identifies 13 inhabited islands feasible for constructing wave power plants, among which Daguan, South Changshan, and Xiaoguan are the optimal ones. Sensitivity analysis is performed to verify the feasibility of the proposed framework. The results show that it is effective and could provide reference for practical engineering. [ABSTRACT FROM AUTHOR]

Total-factor energy efficiency (TFEE) is widely used to measure energy efficiency under the data envelopment analysis (DEA) framework, but the efficiencies obtained from DEA are structurally biased upward, and thus TFEE tends to overestimate energy efficiency. This research thus applies the bootstrapped DEA approach to correct the bias of TFEE. Using a dataset consisting of 30 provinces of China in the period 2016–2019, the bootstrapped-based test supports technology with variable returns to scale. The biased-corrected TFEE also indicates that energy consumption on average can be scaled down by 42.36%, rather than the biased value of 19.4%. The bootstrapped clustering partitions provinces into three groups: Cluster 1, with Guizhou as the representative medoid, includes half of the superior coastal provinces in terms of actual energy consumption and TFEE and half of the competitive inland provinces, whereas Cluster 3 outperforms Cluster 2 in terms of TFEE, but the actual energy consumption is higher, with Shandong and Hebei as the representative medoids, respectively. Lastly, empirical results imply that the northeast and central regions need more government attention and resources to practice sustainable development and improve TFEE. [ABSTRACT FROM AUTHOR]