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Industrial wastewater discharge has become the main cause of water pollution in China. However, the spatial interaction mechanism between industrial structure and water pollution is still unclear. Accordingly, we evaluated and analyzed spatiotemporal changes of the agglomeration pattern of pollution-intensive industrial enterprises and the evolution of the water environmental pollution pattern, as well as the correlation between them. The study results show that the polluting industrial enterprises were located mainly along the Yangtze River and Taihu Lake Basin in southern Jiangsu in 2013 and 2018. However, we observed a spatial trend of pollution transfer to northern Jiangsu. The industrial water pollution discharge presents the distribution pattern of facing rivers, seas, lakes and cities. Papermaking and paper products industry are the leading factors of COD and NH 3 –N pollution, with explanatory power of 0.3666 and 0.6201 respectively. The spatial positive coupling effect between the concentration degree of polluting enterprises and the intensity of water environment pollution discharge is 94.95% of the region. The spatial agglomeration of polluting industrial enterprises is an important cause of water environment pollution. They promote and couple each other, proving the existence of "Pollution haven" and "Porter hypothesis". [Display omitted] • The polluting industrial enterprises are located mainly along the Yangtze River and Taihu Lake Basin. • Papermaking and paper products industry are the leading factors of COD and NH 3 –N pollution. • The spatial agglomeration of polluting industrial enterprises is a significant cause of water environment pollution. • This study proves the existence of "Pollution haven" and "Porter hypothesis". • This study fills the gap in the spatial response mechanisms of different industrial structures and pollutants. [ABSTRACT FROM AUTHOR]

Intangible capital stock is an important variable of current concern for all sectors, which is a new driving force of innovation-driven economic growth. However, there is still room for improvement in the estimation method of China's intangible capital stock, and the analysis of the estimation results is not yet sufficient. For this purpose, this paper firstly re-estimates China's intangible capital stock using the CHS classification framework, especially in the estimation methods of software capital and scientific R&D capital, and makes a lot of improvements. Then, this paper uses not only the growth model but also the mediating effect model to classify the intangible capital in the CHS framework into explanatory and mediating variables of economic growth, and proposes that the explanatory variables are what drive new driving force of China's economic growth and the intangible capital stock estimated in this paper. Finally, this paper provides a detailed analysis of the changes, structure, and distribution of the explanatory variables. The results find that (1) software capital and scientific R&D capital are the new driving forces of China's economic growth; (2) China's national stock of current-valued intangible capital rose from 0.4 trillion yuan to 16.4 trillion yuan from 2001–2017, with software capital stock growing faster than scientific R&D capital stock; (3) Intangible capital stock is mainly distributed in a few regions such as Beijing, Guangdong, Jiangsu and Shanghai; (4) The structure of intangible capital in most regions is not reasonable, and there is a bias towards software capital or scientific R&D capital; (5) The rapid growth of intangible capital stock in Jiangsu and other regions is one of the reasons for their fast economic growth rate, while the slow growth of intangible capital stock in Heilongjiang and Liaoning has led to a decline in their economic growth rate. [ABSTRACT FROM AUTHOR]

In this paper, the numerical calculation model of salt cavern hydrogen storage was established based on the proposed salt cavern hydrogen storage in a bedded salt mine in Jiangsu Province of China. The effects of the minimum internal pressure, maximum internal pressure, average internal pressure and injection-production rate on the stability and tightness of the storage were explored respectively. The results revealed that: (1) The volume shrinkage rate and the plastic zone distribution of the surrounding rock decreased with the increase of the minimum internal pressure, and increased with the decrease of the maximum internal pressure. (2) When the depth of salt cavern is around 1700 m , its long-term stability cannot meet the requirements according to the traditional standard of 0.3–0.8 times of the vertical stress at the cavern roof. It is therefore suggested that the minimum internal pressure of the storage should be increased to 0.4 times of the vertical stress at the cavern roof. (3) The tightness evaluation indexes, including leak range, pore pressure distribution of hydrogen, and cumulative leakage of hydrogen in surrounding rock, all increased with the increase of average pressure and amplitude of internal pressure. (4) Under the same average internal pressure and injection-production frequency, the greater the injection-production rate (the amplitude of internal pressure), the smaller the cumulative leakage rate is. Therefore, increasing the injection-production rate is beneficial to the storability of the hydrogen storage. • Different internal pressures are set to study the stability and tightness of the salt cavern for hydrogen storage. • Raising the minimum internal pressure can enhance the stability of the salt cavern. • The amplitude of internal pressure is the key factor affecting the tightness of the salt cavern. • The selection of internal pressure for hydrogen storage should take into account the effects of multiple factors. [ABSTRACT FROM AUTHOR]

The park-level integrated energy system characterized by electricity heat cooling storage is regarded as a viable solution to energy and environmental crises due to its cleanliness and high efficiency. However, decision-makers encounter challenges in picking the optimum construction scheme. The paper introduces the matter element extension into the investment decision-making of the park-level integrated energy system. To begin, the paper analyzes the composition of the evaluation index system from the basic composition of the park-level integrated energy system, and establishes a standard system for comprehensive performance analysis, including economic, environmental, energy, security, and intelligence. Second, the subjective weight is calculated using the fuzzy analytic hierarchy process, the objective weight is calculated using the entropy weight. The matter element extension is used to evaluate the alternatives' performance. Finally, an industrial park in Jiangsu Province of China is selected as a case to verify. The results show that good comprehensive performance can be obtained by using photovoltaic, wind turbines, electric energy storage, ice storage, and heat pumps. The decision-making results will not be affected by the change in subjective and objective weight and the change in index weight within 20 %, but changes in matter-element classification would. • Intelligent performance criterion is introduced. • The evaluation system includes economy, environment, energy, security, intelligence. • A decision-making framework for the park-level integrated energy system is established. • A variety of sensitivity analyses were performed. • Using renewable energy and energy storage can obtain good comprehensive performance. [ABSTRACT FROM AUTHOR]

Abstract: Mobility and bioavailability of soil heavy metals strongly depend on their fractions. Secondary-phase fraction (SPF) of heavy metal, including acid-soluble, reducible and oxidizable fractions, is considered as direct and potential hazardous fraction to organisms. The ratio of SPF to the total concentration of heavy metal represents its bioavailability. In this study, 126 topsoil samples were collected in Kunshan, Jiangsu, China. Fraction concentrations of heavy metals, and their bioavailability and spatial distributions were determined, and relationships between their fractions and types of industry zones were analyzed. Results showed that Cd and Pb had the greatest SPFs among all metals (78.61% and 62.60%, respectively). Great SPFs of Cd and Pb were observed in the dyeing and paper-making industry zone, while great SPFs of Cr, Cu, Zn, Ni were in the smelting and plating industry zone. For most metals, fraction distributions were controlled by soil organic matter and clay contents. Spatial principal component analysis showed SPFs of heavy metals can be explained by two principle components (PCs). PC1 represented SPFs of Cd, Cr, Cu, Pb and Zn, while PC2 represented SPFs of Ni and Co. The spatial distributions of SPFs were influenced by geochemical character, industrial sewage irrigation and soil physico-chemical properties. [Copyright &y& Elsevier]

[Display omitted] • We constructed an industrial waste metabolism input-output model. • We considered the industrial wastewater, industrial waste gas and industrial solid waste. • We accounted for both direct and indirect industrial waste discharge. • The dominant sectors and ecological utility relationships of systems are identified. • The results support the formulation of waste management plans in Jiangsu Province. The enormous discharge of industrial waste seriously hinders the sustainable development of cities. However, most studies only involve a single or limited category of industrial pollutants, ignoring the environmental pressure caused by multiple resources and environmental factors. This paper combines input-output analysis and ecological network analysis to construct an industrial waste metabolic input–output (IWMIO) model, which explores the industrial waste discharge and discharge relationships among different sectors in Jiangsu Province from the three aspects of industrial wastewater, industrial waste gas, and industrial solid waste. The results show that the indirect discharge of industrial waste is greater than the direct discharge in the industrial waste metabolism system. TI (Tertiary industry), CI (Chemical industry), SPM (Smelting and pressing of metals), and PSEH (Production and supply of electricity and heat) dominate the industrial waste metabolism system. In addition, MWC (Mining and washing of coal), MNMP (Manufacture of non-metallic mineral products), SPM (Smelting and pressing of metals) have more mutualism and competition relationships with other sectors, so the control of industrial waste discharge in these sectors contributes to achieving emission reduction targets. Based on the research results, this paper proposes corresponding policy recommendations such as considering both direct and indirect emissions of sectors when formulating waste reduction policies and developing pertinent industrial waste reduction programs based on the characteristics of the identified sectors. The results of this paper are helpful to identify the dependence and influence relationships of various sectors in the industrial waste metabolism system, promote industrial waste discharge control, and provide theoretical support for the adjustment of industrial structure and the formulation of related policies in Jiangsu Province. [ABSTRACT FROM AUTHOR]

Global climate change is aggravating the occurrence of pests and diseases, however, pesticide residue caused by the abuse of chemical pesticides is emerging as a worldwide issue with a great threat to the ecological environment, human health, and food security. Biopesticide application, a component of climate-smart agricultural practices, is viewed as a vital alternative for agricultural sustainable development. Due to the additional cost attached to externalities and information insufficiency, the adoption rates of biopesticide are still quite low in most developing countries. By using panel data of 3143 rural households from 2020 to 2021 in Jiangsu Province, this paper builds a theoretical framework of whether and how specialized agricultural service (SAS) for specialized pest control affects farmers' biopesticide application, and then employs an Endogenous Switching Probit model to verify this effect and its channels empirically. The empirical results show that the SAS purchase can increase significantly the probability of smallholders' biopesticide adoption by 30.8%. Without consideration of the self-selection bias, this probability would drop to 16.2%. The potential channels of the SAS influencing farmers' biopesticide application are technology popularization (training) and machinery substitution resulting from SAS. Moreover, our findings also indicate that the effects of SAS on biopesticide adoption are heterogeneous, and vary with farmers' education level, cooperative members, and land size. This paper provides the first empirical evidence for the effect of SAS on biopesticide promotion, which is expected to contribute to agricultural sustainable development and food safety in most developing countries. [Display omitted] • Climate-smart agricultural practices play a vital role in global adaptation to climate change. • We examine the effects of specialized agricultural services on biopesticide application in China. • Theoretical framework and endogenous switching probit model are employed to identify these effects. • Specialized agricultural service affects biopesticide adoption mainly through two channels. • These effects are heterogeneous and vary with farmers' different characteristics. [ABSTRACT FROM AUTHOR]

[Display omitted] • A model for multi-objective optimization operation of multiple water sources under uncertainties was proposed. • Uncertainties in inflow and water demand forecasts can be considered simultaneously, and the correlation between uncertainties can be considered quantitatively. • The impact of inflow-water demand forecast uncertainties and their correlations on water resource operations are explored for water resources managers. Uncertainties in inflow and water demand forecasts bring risks to water resources management. Therefore, the research on multi-objective optimization operation of multiple water sources under uncertainties holds critical research significance and application value. This paper proposes a model for the multi-objective optimization operation of multiple water sources that can consider the inflow and water demand forecast dual uncertainties. In handling uncertainties, this paper adopts a scenario generation method based on joint distribution-Monte Carlo (JDMC), which allows for a quantitative consideration of the correlation between uncertainties. Moreover, the variable weight method and LINGO 20.0 are employed for solving multi-objective optimization issues to obtain stable Pareto frontiers. The proposed model is applied to the water receiving area inside Jiangsu Province of the South-to-North Water Transfer East Route Project (SNWTERP) in China. The main findings are as follows: 1) The impact of the inflow and water demand forecast uncertainties on the operation results is synergistic rather than antagonistic. Considering only a single uncertainty may result in water receiving area facing more severe water shortages or purchasing spot water at high prices. 2) There is a strong spatial correlation between uncertainties. If we ignore or only qualitatively consider the correlation between uncertainties, the impact of uncertainties on operation results will be underestimated or overestimated. 3) The Pareto frontiers are convex functions, indicating that decision-makers should choose a solution in the middle part. [ABSTRACT FROM AUTHOR]

• A novel discrete multivariable grey prediction model considering the spatial proximity effect is proposed. • The complete spatial distance index is designed to quantify the intensity of the spatial proximity effect. • The spatial proximity effect term is constructed and incorporated into the grey prediction framework. • The proposed method extends the application field of the grey forecasting technology. • The novel forecasting method significantly outperforms a range of benchmark models. The temporal and spatial characteristics of the collected data typically play an essential role in time series forecasting. However, traditional grey models pay more attention to temporal information, meanwhile disregarding the presence of spatial features critical to producing accurate forecasts. Moreover, the grey theory has few attempts to overcome this problem. Given this situation, this paper proposes a novel multivariable grey prediction model considering the spatial proximity effect for time series forecasting. More specifically, the complete spatial distance index is defined initially based on the geographical and economic distance to quantify the intensity of the spatial proximity impact. On this basis, the spatial proximity effect term is constructed and incorporated into the conventional discrete multivariable grey model, establishing the novel model. Subsequently, the particle swarm optimization algorithm determines the optimal weight coefficient in the developed index. For illustration and verification purposes, the proposed model performs experiments predicting Jiangsu's economic outputs compared to five prevalent benchmarks. Furthermore, three statistical metrics, the Diebold-Mariano test, the Monte Carlo experiments, and the probability density analysis are employed to validate the model's efficacy and robustness. Empirical results demonstrate that the proposed method outperforms all five competitors with strong robustness and broad generalization. Therefore, this new model is used for forecasting Jiangsu's future economic outputs from 2021 to 2025. [ABSTRACT FROM AUTHOR]

[Display omitted] • The evolution of construction land expansion and space conflicts were visualized. • An index for analyzing the intensity of territorial space conflicts is constructed. • The intensity distribution of space conflicts is consistent with its dynamic changes. • Territorial space conflict changes are related to construction land expansion. • The collaboration degree between conflicts and socioeconomic factors is discussed. In rapidly urbanizing areas, intense human development activities and fierce competition for spatial resources have led to apparent territorial space conflicts. This paper selects Jiangsu Province as the study area to explore the spatiotemporal evolution characteristics and response relationship between the expansion of county-level construction land and territorial space conflicts from 1985 to 2020 to provide a reference for regional territorial space optimization. The results show that the construction land expansion intensity (CEI) at the county level showed a spatial characteristic of greater power in the southeast than in the northwest. The spatial expansion mode (SEI) was mainly characterized by spread type, with construction land experiencing marginal expansion, the emergence of new independent expansion points, and then the expansion process of agglomeration distribution. From 1985 to 2020, there was a significant increase in territorial space conflicts and an increase in spatial aggregation at the county level. The regions with high space conflicts intensity index (SCII) values and high increase in space conflicts intensity changes (SCII C) were mainly located in Xuzhou, Nanjing, and at the junction of Changzhou, Wuxi, Suzhou, and Zhenjiang. There was a positive correlation between CEI and SCII C , and the correlation of positive correlation units increased from south to north. There was a positive correlation between SEI and SCII C , and the units with a strong positive correlation were mainly located in Xuzhou, Nantong, Changzhou, and Wuxi. The changes in population density and GDP also affect SCII C. This paper strengthens the understanding of the spatiotemporal evolution characteristics and related relationships of construction land expansion and territorial space conflicts at the county level over a long time, which can provide a decision-making basis and reference for the regulation of county construction land expansion, territorial space optimization in Jiangsu Province. [ABSTRACT FROM AUTHOR]

This paper, through a case study of the Gengche Township in north Jiangsu (Subei), unveils how a less-favored region breaks out of the old industry path of waste recycling and processing and embarks on a green new one specializing in E-commerce. Drawing on key concepts in evolutionary economic geography, we propose a conceptual framework that addresses how entrepreneurial agents enact the processes of asset modification at multiple scales for new green path development in a rural context. Based on on-site interviews and survey, our analysis reveals that rural lead entrepreneurs and state elites pioneered and opened windows of opportunities for change, then legitimized by the state with wider support towards old path breaking. These state interventions enforce the bottom-up process of new green path development. In this process, extra-regional knowledge linkages and assets help facilitate the E-commerce development. It is concluded that rural new path development processes are not only contingent on local pre-conditions but are tempo-spatially dependent on collective actions of entrepreneurial multi-actors in identifying, transplanting and modifying local and non-local assets. The Gengche case demonstrates that rural new green path development in China requires the formation of strong system-level rural agency engaging in multi-scalar asset modification. • The transformation trajectory of Gengche, a previous poverty township, was investigated. • Rural lead entrepreneurs and state elites pioneered and opened windows of opportunities for change. • State interventions enforce the bottom-up process of new green path development. • Extra-regional knowledge linkages and assets help facilitate the E-commerce development. [ABSTRACT FROM AUTHOR]

Offshore artificial islands represent a novel way to develop and utilize marine space resources. Previous research has focused on predicting erosion and deposition distributions following the islands construction, utilizing laboratory experiments and numerical simulations. However, the absence of long-term continuous monitoring has hindered systematic studies on the geomorphological processes of these islands. A 20-years of underwater terrain monitoring scheme was conducted before and after construction of the Rudong Artificial Island in Jiangsu Province, China. The results were combined with on-site observations of tidal currents, suspended sediment concentrations, and surficial sediment to investigate the evolution of the water channel–sand ridge system and the development process of local scour around the artificial island. The results indicated that after the construction of the artificial island, its surrounding water channels showed an overall evolution trend of the north channel shifting towards the north, the middle channel widening and moving south, and the south channel extending westward and southward. Scour has been observed at the four corners of the artificial island, with the peak depths of 7.3 m, 5.6 m, 13.7 m, and 12.2 m at the southwest, northwest, northeast, and southeast corners respectively. The scour in the southwest and northwest corners reached an equilibrium within five years. However, in the southeast corner, continuous erosion of the shoal on the southeast side of the artificial island enhanced the local hydrodynamic force, leading to further scour development. The large-scale scour in the northeast corner was mainly caused by changes in the local flow field following the construction of water intake pipelines and their protection projects. These geomorphological changes are the joint results of the natural evolution of the radial sand ridges and local erosion and deposition from engineering construction. Currently, the sandbanks surrounding the island are still undergoing dynamic evolution following engineering construction, and local scour around the island has not yet reached equilibrium. • This paper focused on the geomorphological processes around an artificial island. • The island was built on a silty coast where tidal currents dominated its evolution. • Field terrain, hydrology, and sediment data spanning twenty years were collected. • The evolution of the radial sand ridges after the island construction was studied. • The development process and causes of local scour around the island were analyzed. [ABSTRACT FROM AUTHOR]

China is gradually and directly making rural collective land available on the land market. It is important to understand how stakeholders collectively treat and manage this land, and if this collective action leads to effective and sustainable results. This paper, however, revises Ostrom's framework of collective action by constructing the joint analysis of social capital, trust, and cooperation performance, in order to better capture the distinction between voluntary action and enforced action of stakeholders towards a sustainable goal. We analyze the role of voluntary collective action through higher-order structural equation modeling (HSEM), applied to a database consisting of 324 households in Jiangsu Province, China, collected in 2022 and 2023. The results suggest that social capital effectively promotes villagers' trust in policy implementers by establishing new institutions, increasing actors' trustworthiness, and improving channels of information exchange, and the first two means are more effective than the latter. We also demonstrate the significant positive effect of trust on cooperation performance, with trusting relationships with familiar groups and the credible behavior of policy implementers affecting performance outcomes of collective action. Moreover, social capital drives cooperation performance through the mediating effect of mutual trust that it breeds. With this revised framework and verified hypotheses one can thus create more effective policies to avoid inequality and informality in the land marketization process in China. [ABSTRACT FROM AUTHOR]

The operation of existing renewable power grid and trailer-based hydrogen chain integrated system generally ignores the adjustability of energy transfer process, leading to unsatisfactory results. To address the problem, a flexible energy transfer strategy for integrated electric‑hydrogen systems with hydrogen vessels (HVs) is proposed in this paper. First, the continuous adjustability of working time (i.e., transiting and berthing time) of HVs is reasonably modelled without relying on fixed scheduling step. Meanwhile, both the controllability of the transmission line components and the role of overlying ice in enhancing the line thermal stability are analyzed. Additionally, a value assessment model for flexible energy transfer is developed which considers time-related fees (e.g., HV berthing fees) and frequency-related fees (e.g., HV tying/untying fees) of hydrogen transportation, the melting ice value of line power heating, power reserve costs and generation costs. On this basis, an energy scheduling strategy is designed for integrated electric‑hydrogen systems to minimize daily operating costs. This scheduling model is first linearized as a mixed-integer linear programming problem and then solved efficiently using decomposition method. Finally, case studies on a modified IEEE-RTS79 power system and river network in Jiangsu Province verify the effectiveness of the proposed strategy. • A flexible hydrogen transfer model of HVs is developed. • A flexible electricity transfer model is proposed. • A value assessment model for flexible energy transfer is established. • A new algorithm is proposed to solve the dispatching model efficiently. [ABSTRACT FROM AUTHOR]

Rural China has undergone dramatic socioeconomic and spatial restructuring as a result of rapid urbanization and the implementation of a series of top-down reforms. In this paper, based on the actor-network perspective, we examine the actor translation process associated with implementation of various governmental strategies in Haoqiao, a poor village located in the northern Jiangsu Province in China. We mainly focus on interactions between participants as well as their influences on the rural restructuring process. The findings proved the crucial role of township government in implementing restructuring at village-level. Motivated by acquisition of land-related finance, the performance evaluation system of local officials, and public accountability, the town government is keen to mobilize others in the action coalition promoting rural restructuring. However, it is noteworthy that many farming households are reluctant to comply with community planning, because they have to cover large price gap between their old houses and residential land and new houses for resettlement. We also discuss the motivations for diverse human actors and the potentially negative impacts that domestic macro-economic situation plays on the circulation of rural residential land consolidation which mainly underpin the rural restructuring. • Linkage among institutional changes, incentives, local actors' behaviors, and rural restructuring is explored. • Actor-network approach is used to describe the actor coalition constructing process leading to rural restructuring. • As one of the public actors, the town government plays a crucial role in promoting rural restructuring. • The land revenue plays major part in mobilizing public actors compared with public accountability. • Farming households with poor social capital are represented by powerful actors in the decision-making process. [ABSTRACT FROM AUTHOR]

After decades of rapid economic growth and massive rural-to-urban migration, rural poverty in China has been largely alleviated. Existing literature has highlighted the crucial role played by non-farm employment in the rural population's escape from poverty. However, despite some engagement in non-farm employment, a huge population in rural China remains poor. Why rural households remain poor in spite of non-farm employment has not been sufficiently explored by scholars. To fill the research gap, this paper explores the underlying mechanisms of poverty among the poor rural population, based on a recent questionnaire survey (n = 2,822) conducted in rural North Jiangsu in China. Our multinomial logistic regression model and OLS regression model show that education is positively associated with the likelihood of engaging in non-farm sectors. Relatively low education attainment of working-age household members (secondary education and below) restricted the earnings from non-farm activities, reducing the likelihood of escaping poverty. Supporting higher education for their children is often a heavy burden for poor non-agricultural rural households, driving them into the poverty trap. The results also show that significant family events, such as severe illness and children's college enrollment, have kept rural households poor, even if some household members have participated in non-farm activities through migration or working in the local non-rural sector. In addition, instead of being looked after, some apparently dependent family members (the elderly) undertake agricultural activities and domestic work to support the out-migration of the labor force in poor rural households to enable household wealth accumulation. The findings suggest that policymakers should implement a series of reforms, especially regarding improvement in health insurance and education and the economic development in the local areas (incl. rural areas and nearby towns) to deal with rural poverty. • Identify features of poor rural households who choose to escape the poverty trap through non-agricultural work. • Education investment may be insufficient for escaping the poverty trap if the education of the household workforce remains low. • Dependent family members at home contribute to improving the discretionary incomes of poor rural households. • Illness and college study prohibite poor rural households from taking non-agricultural work to escape poverty. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative integration of geothermal and solar energies to assess the production of power, cooling, and freshwater. These products are achieved through a modified absorption refrigeration cycle, a modified organic Rankine cycle, and humidification-dehumidification subsystems driven by a flash-binary configuration. The performance of the setup is evaluated using both thermodynamic and economic approaches. Additionally, three multi-objective optimizations are applied to determine a suitable optimal state. The approaches reveal net power, cooling, and freshwater production rates of 807.3 kW, 1345 kW, and 7.96 kg/s, respectively. The designed setup requires a total capital investment cost of $2,490,310 and has a payback period of 5.76 years in the base mode. The study highlights that the temperature difference of superheating significantly impacts the total capital investment cost and exergy efficiency, while the cooling production is mainly influenced by the evaporator temperature. The final optimal state achieved an exergy efficiency of 15.98 % and a net present value of $1,999,864. Overall, this innovative hybrid geothermal-solar setup demonstrates a viable solution for sustainable energy production, combining power generation, cooling, and freshwater production in a single integrated system. The findings support the system's potential for real-world applications, particularly in regions with suitable geothermal and solar resources. • Designing a novel multi-generation driven by solar and geothermal energies. • Considering the energy, exergy, and economic analyses for the performance evaluation. • Producing 807.7 kW net power, 1592 kW cooling, and 8.8 kg/s freshwater. • Achieving 15.98 % of exergy efficiency with a payback period of 5.36 years. [ABSTRACT FROM AUTHOR]

Carbon emissions from the tourism industry are an important measure of the impact tourism has on the environment. Previous studies are predominantly focused on the static estimation of carbon emission from tourism transport. The effective estimation and analysis of carbon emission flows from self-driving tourism, and it’s related determinants, has become increasingly important. Using expressway traffic flow data at the level of toll-gate across Jiangsu Province in China (2014), this paper has estimated the carbon emission flows from self-driving tourism between counties, analyzed the spatial patterns of its inflow, outflow and net flows, and modelled the determinants of these flows globally and locally using the geographically weighted regression method. The spatial distribution of these flows show high concentration in the South, gradually decreasing to the North. The two geographically weighted regression models demonstrate that the determinants of both inflows (the per capita gross domestic product. and the scenic spot’s score) and outflows (the per capita and total population of permanent residents) indicate spatial non-stationarity across Jiangsu province. The flow perspective and geographically weighted regression methods used in this paper have been proven to be effective in theoretical understanding and methodogical analysis of carbon emission trading. It is concluded that the spatial variation of these determinants has provided important evidence for carbon emission trading at county level. This suggests that local governments should take the variations of per capita gross domestic product, score of attractive spots and total population of permanent residents into the process of estimating carbon emission trading between counties. [ABSTRACT FROM AUTHOR]

The Neopyropia aquaculture area located in Subei Shoal has garnered considerable attention due to the green tide in the Yellow Sea. Acid treatment is widely used in Neopyropia culture, both in the seedling and mature stages. In light of this, we propose the implementation of acid treatment technology in the Neopyropia aquaculture area within Subei Shoal, with the primary aim of mitigating the proliferation of green macroalgae on the rafts. This, in turn, is anticipated to elevate the yield and overall quality of Neopyropia. In this paper, we provide a comprehensive overview of the application of acid treatment technology in Neopyropia aquaculture, elucidating the key acid solutions used and the underlying mechanisms governing acid treatment. Furthermore, we delve into early prevention strategies for countering the green tide within the Neopyropia aquaculture region of northern Jiangsu Province, ultimately striving to augment the quality of Neopyropia cultivation and propose effective measures for curtailing the scale of green tide. [Display omitted] • Introducing the acid treatment in the Neopyropia aquaculture. • Introducing the damage mechanism of acid solution to green macroalgae. • Providing suggestions for further research on green tide prevention. • Acid treatment will not have harmful effects on marine environment. [ABSTRACT FROM AUTHOR]

Industrial steam heating is a significant aspect of energy consumption in China, playing a crucial role in industrial energy efficiency. Historically, demand response research has predominantly focused on the electricity sector, with limited emphasis on steam supply. This study explores a novel Time-of-Use pricing approach for steam heating systems, anchored in the demand response theory of price incentives. It develops a peak-valley segmentation method by considering both the load differences between supply and demand and the thermal storage capacity of the pipeline system. Additionally, the paper delves into user response characteristics to formulate an optimized Time-of-Use pricing model for steam heating systems. Implemented in a Jiangsu-based case study, the model demonstrates significant efficiency improvements: it reduces the peak-valley load difference by up to 68.3% and cuts steam purchasing costs by ¥135,000. Furthermore, the alignment between the users' total steam load curve and the heat source's steam supply is enhanced by 18.8%, illustrating the model's effectiveness in balancing demand and supply. • Cluster analysis to extract steam user load characteristics. • Divide peak/valley times based on network storage and user traits. • Create a multi-objective Time-of-Use model for steam pricing optimization. • Carry out a case validation in an actual industrial park in Jiangsu. [ABSTRACT FROM AUTHOR]

With the development of the industrial Internet of Things (IIOT), an amount of industrial multivariate time series (IMTS) data has been collected by various sensors. IMTS data anomaly detection plays an important role in industrial process monitoring and operation condition identification. Many real-world IMTS datasets usually have a large number of redundant features, which may lead to deviation of the anomaly detection model and misunderstanding of potential feature correlation. Hence, it is essential to select features that have critical and effective effects on anomalies and operation conditions. In this paper, a feature selection that introduces knowledge-based target variables into inner feature selectors (IFSs) is proposed as a wrapper method, referred to as ILSFS. The IFS is constructed by integrating a timing fitter, which is established based on the long and short-term memory (LSTM) network, with the Shapley Additive explanation (SHAP) assisted to eliminate unimportant features. The experiments were conducted on two datasets: the vertical roller mill dataset (VMD) of a slag milling factory in Jiangsu Province and the public server machine dataset (SMD). Compared with None feature selection, SVM-RFE, LGBM -Boruta, Genetic-based methods, and other SHAP-assisted feature selection methods such as XGBSVFIR and ShapHT+, the experiment results highlighted the proposed methodology ILSFS improves the best F1 score of each the above baselines by 0.2799, 0.2208, 0.2647, 0.1882, 0.3775, 0.2765 for the VMD and 0.1475, 0.0586, 0.0567, 0.0638, 0.0519, 0.2250 for the SMD on the downstream anomaly detection. The best precision of the ILSFS for the VMD and the SMD was 0.8224 and 0.9499, respectively, while its best recall was 0.7353 and 0.4902, respectively. • An Inner Feature Selector (IFS) is constructed by the LSTM-based network fitting integrated with SHAP-assisted. • An unsupervised wrapper feature selection method ILSFS based on IFSs is proposed. • Several comparison experiments were conducted to validate the efficiency of our proposed method on an anomaly detection task. [ABSTRACT FROM AUTHOR]

The food quality and safety incidents occurring continually in China are greatly sapping consumers' confidence in the food industry. Accordingly, this paper sets four characteristics (quality and safety, traceability information, traceability information authenticity certification, and price) with different levels of these characteristics for traceable pork as an example food product. The rational preferences and irrational characteristics of consumers were studied based on a survey of 636 consumers in Suzhou City, Jiangsu Province, China, using the hierarchical Bayesian estimation method and mixed Logit choice model. The results of the choice experiment (CE) based on the assumption of rational preferences indicated that Chinese consumers have the highest preferences for pork with a green certification mark, complete traceability information, and government-certified traceability information authenticity on the whole. In contrast, the findings of the irrational characteristics model built based on the CE showed that Chinese consumers have a higher degree of dependence on slaughtering and processing information than on complete traceability information, indicating that there may be differences in influence on consumer behaviors between consumers' rational preferences and irrational characteristics. The contributions of this paper are as follows: on the one hand, it tries to construct a suitable theoretical basis for irrational characteristics of consumers, and on the other hand, it can take the consumers' degree of dependence on safety characteristics as a point of penetration to improve food quality and safety in practice. • Construct a suitable theoretical basis for irrational characteristics of consumers. • Consumers have the highest degree of dependence on slaughtering information. • Rationality and irrationality have different effects on consumer choice. [ABSTRACT FROM AUTHOR]

Remanufacturing industry can solve the issues of resource depletion and environment deterioration by reducing consumptions of raw materials and minimizing emissions of wastes. It has been strongly promoted by Chinese government in recent years. However, its current development situation has been unsatisfactory all the time. The aim of this paper is to evaluate development level of remanufacturing industry of China and point out future directions of industrial improvement. To achieve the above objective, this paper establishes an evaluation index system of remanufacturing industry and puts forward an improved grey fixed weight clustering method, which is suitable for assessing remanufacturing industry. Then taking Jiangsu Province of China as a practical case, this method is used to evaluate its remanufacturing industry and identify rank order of improvement measures for each city. Research results show that overall development level of remanufacturing industry is still low and development unbalance is remarkable. Two more important findings are as follows: The first is that rank orders of improvement measures for all cities are different from each other and decision maker should adopt differentiated industrial policies and improvement measures. The second is that the cities which belong to the 2nd and 3rd grey class should paid more attention to improvement measures for four evaluation sub-indices: Annual sale of remanufacturing industry, Total assets of remanufacturing enterprise, Total investment of under construction and Total number of research institution and university participated in remanufacturing. The major contribution of this study is to offer an effective decision-making approach for evaluation of remanufacturing industry. It helps in classifying development levels of remanufacturing industry in different cities and providing decision makers with a scientific basis for adopting appropriate industrial policies and improvement measures, which will efficiently enhance remanufacturing industry in the future. [ABSTRACT FROM AUTHOR]

This paper proposes a novel strategy to forecast the short-term wind power using model structure selection in combined with data fusion technique. The available inputs are usually treated as an integrated one for the predictive modeling, which ignores the fusion of the different types of inputs. This results the relationship between the multi-inputs and desired outputs are not effectively reflected in forecasting procedure. Moreover, the performances of the various types of data fusion methods are susceptible to the wind power distribution and critical factors such as smoothness, overlapping, the intrinsic amount of information evaluation and the number of neighbor points. These outlined factors can result the lower generality ability of the proposed methods due to the insufficient optimization of the model structure. So this paper presents short-term wind power forecasting method using model structure selection technique in combined with four representative fusions of dimensionality reduction methods to optimize the model structure, promote the computational efficiency and improve the forecasting accuracy. Experimental evaluation based on the real data from the wind farm in Jiangsu province is given to verify the effectiveness of the proposed method by comparing the traditional techniques. [ABSTRACT FROM AUTHOR]

• An extensible local-global network is proposed for sensor heterogeneity in physical intrusion monitoring based on DOFS for the first time. • A deep isolation forest (DIF) is proposed to improve performance of local classifiers in extremely imbalanced, large-scale and high-dimensional cases. • The semi-sharing strategy and parallel computing framework of proposed network are introduced to reduce the computation costs in training and monitoring. • The characteristics of the proposed method are detailedly discussed in theory, and the effectiveness is verified through real-field experiments. This paper proposes a local–global semi-sharing network (LGSSN) for heterogeneous signals in physical intrusion monitoring. The signals are collected by heterogeneous distributed optical fiber sensor (DOFS). The local classifier of LGSSN is constructed via a hybrid model deep isolation forest (DIF). It can extract the dominant representations of original high-dimensional signals through deep autoencoders (DAE). Then, an isolation forest (IF) is added to the last layer to obtain local classification for extremely imbalanced cases. In addition, the network is simplified by semi-sharing strategy, and a parallel computing framework is presented for accelerating the process. Further, the final decision on monitoring state is acquired by a Bayesian inference-based global integrated monitor (GIM) with enhanced classification accuracy. The proposed strategy is tested on a monitoring application along the Nanjing Metro Line S7, Jiangsu Province, China. Comparative experimental results illustrate the feasibility and effectiveness of proposed strategy. [ABSTRACT FROM AUTHOR]

The current research concentrated upon customers' consuming behaviors towards hydrogen vehicle in Jiangsu province, China. This paper discussed the associations between factors related to competitions in industries and customers' consuming behaviors. Different from previous literature, the present study explored whether industrial agglomeration would affect customers willingness to purchase hydrogen vehicles. Results from empirical analysis showed that industrial structure height in a city was positively associated with customers' acceptance towards hydrogen vehicles. This indicated that in addition to economic and environmental factors, the agglomeration of industrial activities from industry competition would increase customers purchase intention for hydrogen vehicle. • Industry agglomeration's impacts on hydrogen vehicle's consumption are discussed. • Housing burden is related to the degree of reluctance to buy hydrogen vehicles. • Willingness to energy-saving products and hydrogen vehicles is correlated. • The economic mechanism behind Chinese hydrogen vehicle industry is discussed. [ABSTRACT FROM AUTHOR]

As a major energy consumption province in China, Jiangsu Province is a key area for carbon emission reduction in China. Grasping the future trends of carbon emission in Jiangsu Province will help to find effective ways to reduce carbon emission. This paper proposes the STIRPAT-IGWO-SVR model, including screening the carbon emission influencing factors based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, optimizing the parameters of the support vector regression (SVR) model using the gray wolf optimization (GWO) algorithm improved by the differential evolution (DE) algorithm, and sets five scenarios to predict and compare the carbon emissions of Jiangsu Province under different scenarios. In addition, the Tapio decoupling model is used to analyze the decoupling relationship of carbon emission and economic growth in each scenario. The results show that the STIRPAT-IGWO-SVR model proposed in this paper shows good performance compared with other models. For Jiangsu Province, improving the energy structure has the strongest inhibitory effect on carbon emission, stronger than reducing energy intensity, and far stronger than optimizing the industrial structure. Compared with a single plan, even if the measures are slightly weakened, the implementation of combined planning measures can more effectively control carbon emission. • Predict and compare carbon emission and its decoupling status under 5 scenarios. • Propose the STIRPAT-IGWO-SVR model. • Use the GWO algorithm improved by the DE algorithm to optimize the SVR model. • The STIRPAT-IGWO-SVR model shows good performance compared with other models. • The combined planning measures can more effectively control carbon emission. [ABSTRACT FROM AUTHOR]

Environmental efficiency improvement has played a crucial role in the theory and practice of stimulating clean production. This paper analyzes the interaction between environmental efficiency and output efficiency, particularly whether they reinforce each other or compete with each other, on the basis of a data set of 137 firms in the textile industry in China's Jiangsu Province. In the first stage, generalized data envelopment analysis is applied to calculate efficiency measures of energy, waste water, waste gas, soot, and output efficiency taking capital, labor, water, and energy as inputs, industrial output value as desirable output, and waste water discharges, waste gas and soot emissions as undesirable outputs. In the second stage analysis, a structural equation model with latent variables is applied to analyze the interaction between the latent variable environmental efficiency, measured by the four observed environmental indicators, and output efficiency, taking also into account the endogenous variable profit. The main outcomes of the structural equation model are the following. Firstly, environmental efficiency negatively impacts on profit while profit positively impacts on environmental efficiency. In a similar vein, output efficiency is found to depress profit while profit increases output efficiency. Thirdly, environmental efficiency has a positive impact on output efficiency while there is no effect of output efficiency on environmental efficiency. Fourthly, taxes impair a firm's output efficiency. From the findings it follows that a swap of general taxes for an energy tax is likely to improve both output efficiency and energy efficiency. The latter outcome implies a win–win situation which will facilitate the further implementation and adoption of environmental policy. Finally, the paper illustrates the applicability of structural equation modeling in efficiency analysis. [ABSTRACT FROM AUTHOR]

Surface water plays a vital role in natural environment and human development. The research of water extraction method using remote sensing image is a hot topic, which has been widely developed in water index, classification, subpixel, and other aspects. Compared with other methods, a water-index based method has the advantages of fast speed and convenience. The characteristics of surface water, such as wide coverage and instability, make the water index stand out in monitoring large area of surface water. However, land surface in water environment is complex, and the main factors that reduce water extraction accuracy are also different, such as shadow in urban areas and water leakage in unshaded areas. The current index is bound to weaken the information in the water body when suppressing shadows, and vice versa. To address these issues, contrast difference water index (CDWI) and shadow difference water index (SDWI) are proposed in this paper by improving the modified normalized difference water index (MNDWI). CDWI is used to enhance water information, which is suitable for areas without building shadows. SDWI is used to eliminate the shadow of buildings, which is suitable for urban areas. Moreover, background difference water index (BDWI) was proposed by combining the advantages of CDWI and SDWI through a background regularizer B, which is used to extract surface water under complex background. The regularizer B represents the similarity between local background features of the image and the reference urban area, which is used to locally weight SDWI and CDWI, so that BDWI can automatically enhance the water body in the shadowless area and eliminate the shadow of buildings. The water extraction results of BDWI, MNDWI, the tasseled cap wetness index (TCW), the automatic water extraction index (AWEInsh, AWEIsh), and the water index 2015 (WI2015) were used for comparison. Other methods tend to perform well only in built-up areas or non-built-up areas, while the BDWI can extract surface water under various backgrounds with high accuracy and stability. The overall accuracy produced by the BDWI was 91.58–97.57%, CDWI was 84.85–97.09%, SDWI was 81.63–94.40%, MNDWI was 80.19–95.64%, TCW was 82.33–95.98%, AWEIsh was 87.50–96.37%, AWEInsh was 80.59–98.78%, and WI2015 was 78.24–98.38%. Combining water index with image local information is helpful to improve the accuracy of water extraction in large and complex environment. Finally, surface water in Jiangsu Province, China was extracted through BDWI and the changes in 1985, 2000, and 2015 were analyzed. [ABSTRACT FROM AUTHOR]

Retrograde intrarenal surgery (RIRS) is one of the primary treatments for renal stones. The ureteral access sheath (UAS) was widely used in RIRS. 1,2 The aim of this paper is to introduce a new UAS, the distal active flexible vacuum-assisted ureteral access sheaths (DAFV-UAS), for the renal calculus during RIRS. A 56-year-old female presented to the outpatient clinics of our hospital with a left renal lower calyx stone. Abdominal CT demonstrated that the left kidney's lower calyx stone size was 10.54 × 10.38 mm, and the mean Hounsfield density was 965HU. After adequate anti-infective treatment, the DAFV-UAS was used in RIRS. No perioperative complications were observed. The left renal stone had been cleared completely. The DAFV-UAS (10/12.5 Fr, 38 cm, creek, Jiangsu, China) includes a good flexibility and deformability tube at the tip, about 10 cm long. It has an active bending function, negative pressure suction function, and the function of convenient flexible ureteroscopy (f-URS) entry and exit of the ureter. 3 In this case, the f-URS adopted a 7.5 Fr single-use digital f-URS. The Irrigation method was automated irrigation system, and the flow was 30 mL/min. The suction level was 0.02 mpa. With the help of DAFV-UAS, the field of view is always clean, the small gravel particles can be sucked out from the sheath gap, and the larger gravel particles are sucked out by withdrawing the scope intermittently. DAFV-UAS is a promising new device which allows for negative pressure suction directed right at a renal stone and efficient and effective stone clearance. [ABSTRACT FROM AUTHOR]

China's ecological redline (ER) policy is one of the spatial planning approaches for ecosystem services to land management practices. Exploring ER can promote the international community's understanding of institutional reform and the scientific cognition needed to move from sustainable development theory to practice. Recently, the main decision-making department of ER has been transitioned from the ecological environment department to the natural resources department to better implement environmental management policies. The early ER based on ecosystem services hotspots cannot meet the rigid requirements of protection and development, adjustments have been made based on land management practices. Nevertheless, it is not known whether this adjustment process has an impact on regional ecosystems. This paper attempts to analyze the impact of ER adjustment in Jiangsu on the regional ecosystem from three aspects: ecological network stability, ecological source connectivity, and ecological function importance. The results show that (1) the habitat components formed by ER have been reduced from 144 before adjustment to 125 after adjustment. Fragmented habitat components are gradually merged through the ER adjustment to form a more stable network structure. (2) The number of adjusted high-value connectivity regions of source ER increases, and ER adjustment reduces the resistance of high-intensity man-made disturbances and improves the connectivity between ERs. (3) The main ecological functions around ER have not changed significantly before and after the adjustment. The reduction of low-value functional agglomeration areas is the main performance characteristics of local ecological function changes. Overall, ER adjustment strategy based on land management practices has not negatively affected regional ecosystems. The results have a scientific reference for natural resource management and ecological environment protection in regions with rapid urbanization and highly land-intensive areas around the world. • This paper elaborated on the content of ER adjustment in Jiangsu, China. • ER adjustment based on land management practice is to determine space management units. • A holistic-individual-local framework was used to explore the impact of ER adjustment. • Results can provide ideas for protected areas planning in global intensification regions. [ABSTRACT FROM AUTHOR]

Water surface photovoltaic (PV) is in the early stage of development, facing the problem of weighing economic and environmental benefits. Due to the lack of long-term statistical data and complex environmental impact, it is difficult to carry out effective benefit assessment for water surface PV projects based on existing methods. This paper, focusing on ecological environment impact instead of carbon emission, proposes the economic and environmental synergies assessment model of water surface PV projects. The core of the model is to use the gain estimation of cross-spectrum analysis to evaluate the consistent fluctuation of economic benefit and environmental benefit. In order to expose the gain spectrum, the trend component of economic benefit is extracted by singular spectrum analysis, and the biological and chemical factors of environmental benefit are identified by factor analysis. An empirical study on a 10MWp "fishery and photovoltaics integration" demonstration project in Jiangsu Province of China is conducted. The assessment result shows that the economic and environmental synergies of the project are not optimal, and the economic benefit should be reduced to mitigate the ecological damage. The empirical study shows that the assessment model is insensitive to factor weight distribution, and is not affected by noise. • The model is applicable when data is few but detailed, early in projects. • The model has advantages of robustness in dealing with multi-index and noise. • If focusing on water quality, the synergies of the case study project will be poor. [ABSTRACT FROM AUTHOR]

The 3D modeling method based on parallel geological cross-sections is suitable for modeling large-scale bedrock geological bodies. However, there are usually more branching, pinch-out strata, deformation structures (such as faults and folds), and the correspondence problem of geological boundaries between adjacent cross-sections. These problems have become the most crucial obstacle in the current application of 3D geological modeling based on parallel geological cross-sections. To this end, this paper proposes a topological reasoning automatic processing method for the consistency of parallel geological cross-sections to obtain topologically consistent adjacent cross-sections efficiently. The method involves (1) Stratigraphic inference based on the distance and topological relationships, transforming strata with m:n relationships into three relatively simple cases of 1:1, 1:n, and 1:0; (2) Splitting branching strata based on the Voronoi diagram, transforming strata with 1:n relationships into 1:1 relationships; (3) Dealing pinch-out strata based on the method of filling virtual strata, transforming strata with 1:0 relationships into 1:1 relationships (4) Topologically consistent processing of stratigraphic boundaries based on automatic recognition of no-corresponding arcs and addition of virtual stratum. Based on experiments in the Longtoushan Hill area in Jiangsu Province, China, and the southeast side of Chandler Mountain, Alabama, USA, this method can effectively replace the many manual processes such as determining the location of pinch-out adding auxiliary cross-sections and performing branching strata correspondence in the current application of 3D geological modeling based on arc segments. The geological cross-sections processed based on this method have an exemplary data structure and consistent topological relationships. The 3D geological modeling algorithm based on parallel cross-sections has the advantages of low algorithm complexity, high automation, and stable modeling quality. • An automated method for topology-consistent processing of parallel geological cross-sections was developed. • The strata with corresponding complex relationships can be converted into one-to-one corresponding arc segment sets. • The method lays a sound data foundation for 3D modeling using parallel cross-sections. [ABSTRACT FROM AUTHOR]

Wide-shallow composite bucket structure is a new offshore wind power foundation structure developed in recent years. The field information on long-term natural frequency of composite bucket supported offshore wind turbine under complex marine environment is necessary for structural design, maintenance and serviceability assessment. In this paper, an analysis of 170 days of field data from Jiangsu offshore wind farm, China is presented in detail. The natural excitation technique combined with eigen system realization algorithm is used for the analysis of natural frequency. Subsequently, the long-term features of the natural frequency, and the effect of environmental factors (wind and wave) on natural frequency and their statistical characteristics are comprehensively investigated. The normal distribution is found to be suitable for characterizing the statistical feature of natural frequency. Pearson's correlation revealed that there is a negative correlation between natural frequencies and wind speed/wave height. Furthermore, considering the uncertainty of wind speed and wave height, the probability distribution of first natural frequency of offshore wind turbine is acquired by Monte Carlo simulation, which can lay the foundation for the structure design, modal validation and damage diagnosis of wind turbine. • Natural frequency extracted from long-term monitoring data of an offshore wind turbine are investigated. • Effect of environmental factors (wind and wave) on the natural frequency and their statistical characteristics are evaluated. • Probability distributions of first natural frequency of offshore wind turbine is acquired by Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

To efficiently utilize renewable energy sources primarily consisting of wind and solar power, large-scale compressed air energy storage (CAES) can be implemented using underground salt caverns. In this paper, the abundant wind and solar energy resources and the geological conditions of the three major salt mines in Jiangsu Province are introduced. A geomechanical model is established based on the Huai'an rock salt formation. The simulation results show that as the internal air pressure (IAP) increases, the safety factor increases, and the displacement, plastic zone, volume shrinkage, and equivalent strain decrease. Based on the above results, the minimum IAPs of caverns AN 13 and AN 21 are recommended to be 10–12 MPa. According to estimates, to store 15% of wind and solar power in Jiangsu Province through CAES by 2050, a 9894.0 × 104 m3 salt cavern volume is needed, of which at least 77.8 million m3 can be provided by salt mining enterprises. The cost of reconstructing an underground salt cavern is 12.1 billion yuan, while the investment in surface equipment is 746.7 billion yuan. We provide an economical and feasible solution for achieving carbon neutrality in Jiangsu Province in this study. • A CAES salt cavern is utilized to achieve a 100% renewable energy power system in Jiangsu Province. • The non-salt interlayers significantly reinforce the stability of CAES salt caverns. • The minimum internal air pressure of the CAES salt cavern is recommended to be 10–12 MPa in Huai'an. • A preliminary evaluation of the investment cost of CAES salt caverns is analyzed. [ABSTRACT FROM AUTHOR]

The reconstruction of arable land patterns over historical periods is one of critical research issues in the study of land use and land cover change (LUCC). Taking into account the continuous distribution of arable land and spatial constraints, this paper proposes a constrained cellular automata model to reconstruct historical arable land patterns. The paper describes model establishment, parameter calibration, and results validation in detail. The model was applied to Jiangsu Province, China, and was compared with a conventional spatial allocation method. The results showed that the methodology developed in this study can more objectively reflect the evolution of the pattern of arable land over historical periods, in terms of similarity with contemporary pattern, than the spatial allocation methods and can provide an effective basis for the historical study of arable land. [ABSTRACT FROM AUTHOR]

Industry has always been an important driving force to promote social and economic development, and the development of industry is inseparable from energy consumption. In the process of modern production, more and more modern advanced equipment is put into use, and the main power source of these equipment is electricity. However, the production of electricity is limited by conditions. Therefore, the main purpose of this paper is to simulate and forecast the industrial power consumption of Jiangsu Province through the nonlinear transformation of time variables, so that the industrial enterprises in Jiangsu can reasonably arrange the next power demand and ensure the smooth progress of industrial activities. The final research results show that the time series regression prediction model proposed in this paper can effectively simulate and predict the results of industrial power consumption, with an accuracy of 1.02 %. • Consider fewer factors, which saves time and cost and can obtain higher prediction accuracy. • Only consider the impact of the current time, without considering the impact of the lag time. • Taking Jiangsu, an industrial province as an example, can better guide other provinces. [ABSTRACT FROM AUTHOR]

The North China Plain is the main producing area of winter wheat in China. Due to the relatively poor condition of water resources, the competition of water between industry and agriculture is fierce. The increasing shortage of water resources has led to serious overexploitation of groundwater in some areas. Agricultural development is faced with severe challenges. In order to ensure regional food security and sustainable winter wheat planting, 52 cities of North China Plain (NCP), in the following of the paper, use the shorted name NCP，were taken as research units to analyze the matching characteristics of agricultural water and land resources, so as to reveal the direction of irrigated agriculture development and winter wheat suitable planting layout considering their balance in future. The paper firstly analyzed the cultivated area determined by water resource and irrigation development by agricultural available water, and then pointed out the direction of water-suited planting layout of winter wheat. The results showed that: 1) the Gini coefficient showed an increasing trend, which indicated that the area of cultivated land and irrigation area supported by water resources have nearly reached the upper limit. The large-scale extension of both cultivated and irrigation area is impossible under the restriction of water. 2) The amount of agricultural available water resources per unit of effective irrigation area and the effective precipitation increased gradually from north to south in the NCP, but the spatial distribution of water requirement of winter wheat in its growth period changed in the opposite way. This indicated the poor spatiotemporal match between winter wheat planting and water resources, leading to the cost of spending more water to maintain wheat production. 3), The further development of irrigation and the water-suited planting of winter wheat should pay attention to the southern part of the plain with rich water (such as southern Henan Province, Jiangsu Province, Anhui Province, etc.) to ensure the regional agricultural development. That is of great significance to the regional sustainable development, water shortage alleviation and national grain safety. ● Restraining the irrigation area and winter wheat in NCP. ● Moderately development irrigation area in south of the NCP. ● Water-suited planting layout of Winter wheat. [ABSTRACT FROM AUTHOR]

Abstract: The spatial and sectoral distribution of Foreign Direct Investment (FDI) in China has changed dramatically in the past two decades. FDI was largely concentrated in the Pearl River Delta (PRD) and other Southern Coastal provinces in early stages and shifted to the Yangtze River Delta (YRD) and the Bohai Economic Rim (BER) sequentially in later stages. It created unique and dynamic paths of the spatial evolution of FDI in China. Although many provinces have received relatively more FDI since the late 2000s, Guangdong and Jiangsu are still the two major recipients of FDI in China, demonstrating and over-arching polarization process. Furthermore, most FDI in China has been in the manufacturing sector, making China well-known as the “World Factory of Manufacturing”. This paper analyses the most recent trends, characteristics and patterns of FDI in China. It portrays the factors that determined the investment location and the dynamic pathways of different kinds of FDI. This paper also foresees the possible changes in spatial and sectoral distribution of FDI in the near future and provides policy suggestions for both China and other developing countries in seeking new FDI inflows and transforming their industrial structures and economies in this particular phase of globalization. [Copyright &y& Elsevier]

• We examine the impacts of social relations and public interventions on rent deviation of land rental market in rural China. • Social relations based on blood ties and geographical location increase rent deviation and lead to loss of the efficiency and equity. • Public interventions imposed by local governments or village collectives reduce rent deviation and improve the efficiency and equity. • Public interventions affect rent deviation by dismantling the lock-in effect of social relations. The price mechanism plays an important role in allocating resources and enhancing economic efficiency and equity of land markets. In this paper, we examine the impacts of social relations between rental partners and public interventions imposed by local governments or village collectives on land rent deviation and discuss efficiency and equity impacts as well. Household-level data collected in 2014 covering 907 households in 30 villages in Jiangsu Province, China, are used for empirical analysis. We find that social relations based on blood ties and geographical location increase the levels of land rent deviation and lead to a loss of efficiency and equity of the segmented land rental market. However, public interventions, i.e., land use limitations, collective permission and collective organization, may contribute to reducing land rent deviation and improving the efficiency and equity of the market. Further evidence suggests that public interventions induce land rental transactions among partners other than relatives or familiar villagers. [ABSTRACT FROM AUTHOR]

Tourism development is an important topic within tourism and regional studies. However, previous studies have lacked focus regarding the coexistence of spatial and temporal effects, where the mixed analysis of global and local influencing factors has been limited. This paper employs a semiparametric GWR model to explore the spatiotemporal relationships between regional tourism economy and influencing variables. Results indicate that in the areas of better tourism economic development, spatiotemporal lag factors play a key promotion role, while in the areas of lower tourism economic development, spatiotemporal lag factors play a restraining role. In comparison with traditional analysis methods, semiparametric GWR was found to be superior in analyzing regional tourism economies as it accounts for spatiotemporal relationship at both global and local scales. [ABSTRACT FROM AUTHOR]

Highlights • Multiphase flow in the fractured medium was investigated using the method of "multiple interacting continua" (MINC). • The formation processes of calcite vein and its impact on the sealing efficiency of caprock were discussed. • The simulation results were validated using the field observations of the natural CO 2 gas fields. • The formation of calcite vein eventually prevented the CO 2 from leaking through the fracture at a long time scale. Abstract For the long-term CO 2 geological storage, the evolution of the caprock sealing efficiency has received increasing attention. In this paper, the Huangqiao CO 2 gas field in Jiangsu Province, China, where the calcite veins have been found in the lower part of mudstone caprock, is considered as a natural analogue site for CO 2 geological sequestration (CCS). To ascertain the dynamic formation process of calcite vein and its impact on the evolution of caprock sealing efficiency, a one-dimensional model was designed to represent the fractured reservoir-caprock system. Numerical simulations were performed using the multiphase reactive transport program TOUGHREACT. Sensitivity analyses of fracture permeability and calcite reaction rate were made. The simulation results illustrate that calcium bicarbonate decomposes to form calcium carbonate and release CO 2 from solution due to the pressure decay as the CO 2 -rich fluids migrate upwards along the fracture. The formation of calcite vein decreases the porosity and permeability significantly, which can enhance the integrity and sealing efficiency of caprock. Sensitivity analyses indicate that the formation of calcite vein is facilitated by the fast fluid flow, and calcite vein tends to form in the vicinity of reservoir-caprock interface under the slow-flow condition as the decrease of fracture permeability. Information currently available in Huangqiao CO 2 gas field and some other area describing the formation of calcite vein shows good agreement with our simulation results. The mudstone caprock with fractures and faults is able to keep CO 2 from leaking for a long time as the case of Huangqiao area. The methods and analyses presented here may be useful for CO 2 storage sites with similar conditions. [ABSTRACT FROM AUTHOR]

Abstract In recent years, although China's energy intensity has gradually decreased, the total consumption of energy commodities has increased sharply. Levying an excise tax on energy commodities is one of the keys to control energy consumption. This paper constructed a Computable General Equilibrium model to simulate levying an energy excise tax in Jiangsu province, which is one of China's strong economic provinces with lower endowments of energy resources. The results show that the energy excise tax is beneficial for energy saving, while levying energy will cause economic and welfare declines. When at a level tax rate of 5%, 10%, and 15%, the loss of GDP will reach 0.27%, 0.66%, and 1.13% respectively, and the incomes of inhabitants and enterprises alike will decrease. When the energy tax revenue used to compensate for the welfare losses suffered by inhabitants or enterprises, there is a double dividend effect (energy saving and increasing income). Moreover, the simulation indicated that a 5% improvement of energy efficiency brings about a "backfire" phenomenon, with an increase of 142% in energy consumption. However, when considering the cost of energy-efficiency improvements, the rebound effect will be significantly decreased. Policy suggestions are further recommended to help improve the energy policy in regard to reducing energy consumption. Highlights • CGE model is proposed to evaluate the effect of energy excise tax. • Levying energy excise tax with refund measures could result in a double dividend. • The rebound effect of energy efficiency improvement is quantified. [ABSTRACT FROM AUTHOR]

Abstract: At present there is the different level in China''s circular economy development. To better measure the level of regional circular economy development, this paper builds the evaluation system of regional circular economy development, reflected the characteristic of resources recycling specially, and put forward the Fuzzy Comprehensive Evaluation Method to analysis circular economy development level in single region and Comparison Evaluation Method to analysis circular economy development level in different regions, so that enhance the evaluate ability in evaluation model and evaluation method of circular economy developing level. On this basis, this paper makes the empirical study on regional differences evaluation in circular economy development level through three typical provinces, Jiangsu, Heilongjiang, Qinghai Province. [Copyright &y& Elsevier]

Abstract: The paper applies Environmental Kuznets Curve theory to an empirical study of the correlation among Suzhou''s waste disposal, economic growth and trade growth. The paper arrives at the conclusion that Suzhou''s environment may continue to worsen. To sustain its trade growth, Suzhou should optimize its export mix, promote technological innovation and implement industrial restructuring in order that a balance should be achieved between economic growth and environment. [Copyright &y& Elsevier]

Abstract: In this paper, a quantitative analysis among 20 industrial sectors has been made to see the scale effect, structural effect and technical effect on the environment. Some conclusions can be drawn from the research. The scale effect has a negative effect on the environment while structural effect and technical effect have a positive effect. But the scale effect is far more than the total sum of structural effect and technical effect. In order to promote sustainable development of foreign trade in Jiangsu and reduce the environmental degradation caused by exporting, the paper holds that the industrial exporting structure should be further optimized, technological innovation should be promoted. [Copyright &y& Elsevier]

Abstract: Based on the literature research, this paper establishes a conceptual model of the environmental responsibility affected urban residential housing energy saving investment behavior, and taking Xuzhou as an example, through the 212 valid samples, using the structural equation model, this paper does some inspection and correction for the conceptual model. Results show that the stronger the environmental responsibility is, the stronger the energy-saving behavior intention, and the stronger the energy-saving behavior intention is, the stronger the behavior of residence energy-saving investment, and the environmental responsibility has a indirect positive effect on the behavior of residence energy saving investment via the energy-saving behavior intention, but it can’t affect the behavior of residence energy saving investment directly. The ownership of the house, the family structure and the education level has some differences in character variations for urban residential housing energy saving investment behavior, and the effect of other demographic variables is non-significant. [Copyright &y& Elsevier]

Abstract: Firstly, this paper defined urban residents low carbonization energy consumption behavior as two aspects: the purchasing and choosing behavior and daily using behavior, and then based on the literature researches, this paper developed the conceptual model of social norms affecting urban residents low carbon energy consumption behavior. Taking Xuzhou as an example, through 280 valid sample, using LISREL 8.7, this paper verified and corrected the conceptual model, The results showed that the stronger the social norms of low carbon energy-saving orientation, the stronger the residents low carbon behavior intention; The stronger the residents low carbon behavior intention, the more positive the low carbonization energy consumption behavior; Social norms cannot directly play a role in residents’ energy consumption behavior, can only have indirectly and positive effect on residents behavior via behavior intention. [Copyright &y& Elsevier]

Abstract This paper presents an investigation to evaluate the influence of basic geotechnical properties on the electrical resistivity (ρ) of marine clay. The resistivity piezocone cone penetration tests (RCPTU) were conducted to measure the resistivity at 6 sites in Jiangsu, China. The correlationship between resistivity and soil parameters, including salt content of pore fluid (c s), clay content (w c), sensitivity (S t), plasticity index (I p), unit weight (γ), and moisture content (w), was investigated to understand the mechanisms controlled the changes in resistivity. The results reveal that ρ value was strongly controlled by both c s and w c , in which the ρ decreased rapidly with an increase in c s and w c by forms of power and exponential functions, respectively. Resistivity decreased with an increase in I p for the low plasticity clays (I p < 10%), while it presented almost a constant value (8 Ω·m) for medium and high plasticity soils (I p > 10%). For the range of resistivity studied, poor statistical relationships between ρ and S t , γ , and w were observed, which was mainly due to the dilution effect of controlling factors (viz., c s and w c). These observations could provide assistance to engineering designers in the interpretation of resistivity surveys in marine clay areas. Highlights • c s and w c are the main controlling factors of marine clay resistivity. • Leaching and mineralogy play a non-ignorable role on soil resistivity. • Resistivity range of marine soft clays in eastern Jiangsu, China is 5 to 150 Ω∙m. • Electrical resistivity testing technology provides assistance to marine clay surveying. [ABSTRACT FROM AUTHOR]

Human disturbance is one of the essential forces affecting changes in landscape patterns. Studying the relationship between human disturbances and landscape patterns is of significance for regional conservation and ecosystem management. An understanding of this relationship is also crucial for the mitigation of conflicts between socioeconomic development and environmental protection. In this study, using remote sensing data and geographical information system technology, we created a quantitative method to assess the intensity of human disturbance on the landscape by introducing the concept of hemeroby. By means of the measurement of hemeroby and statistical approaches, we quantitatively analyzed the temporal and spatial changes of human disturbances and their effects on landscape patterns in the Jiangsu coastal zone, China, from 1995 to 2013. The results showed that the intensity of human disturbance gradually increased from 1995 to 2013. While the increasing rate of intensity of human disturbance has slowed down from early period (1995–2002) to later period (2002–2013) because of differences in exploitation activities and regional development policies. Spatially, the hemeroby increased most obviously in the southern counties and northern Ganyu County, resulting from port construction and tidal flat reclamation. Depending on the different degrees of human disturbance, landscape patterns showed obvious differences. Compared with low-level and high-level human disturbance, mid-level human disturbance contributed to more fragmented landscape, more complex patch shape, lower connectivity, and higher diversity. A correlation analysis between landscape indices and hemeroby suggested that the landscape patterns in regions with high-level human disturbance were relatively sensitive to changes in the intensity of human activities. The findings in this paper provide additional spatial information and theoretical guidance for regional conservation and ecosystem management in the Jiangsu coastal zone, China. [ABSTRACT FROM AUTHOR]