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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]

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]

[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]

• 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] • 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]

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]

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]

[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]

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]

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]

• 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]

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]

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]

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]

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]

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]

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]

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]

Accurate and non-destructive monitoring of wheat nitrogen nutrition is of great significance for field fertilizer management to ensure crop yield and quality, reduce environmental pollution, and improve economic benefits. Compared with spectral vegetation indices (which are sensitive to greenness and structural parameters), or active fluorescence (which is limited to small-scale studies), solar-induced chlorophyll fluorescence (SIF) provides a direct measure of crop response to environmental stress and photosynthetic characteristics. However, there has been few studies comparing agronomic parameters, photosynthetic parameters, vegetation indices and SIF as an indicator of nitrogen status. In this paper, we therefore explore these measures as tools for monitoring nitrogen nutrition. During the 2016–2017 growing season, we conducted a field experiment in Rugao, Jiangsu Province, China, using winter wheat (Triticum aestivum L.) and different nitrogen treatments. The sensitivity of SIF indices, vegetation indices, photosynthetic parameters and agronomic parameters to crop nitrogen status were compared. Our results demonstrated that, compared with vegetation indices and agronomic parameters, the ratio of SIF emission peaks (FY 687 /FY 761) responded to nitrogen status most rapidly at both the leaf and canopy scales, as soon as the fourth day after treatment (DAT4). A wheat nitrogen nutrition index (NNI), based on FY 687 /FY 761 , was used to construct a leaf dry matter (LDM-based NNI) diagnostic model, which will be beneficial for monitoring and diagnosing the nitrogen nutrition status of wheat leaves. Our results also illuminate the physiological mechanism that enables SIF to be used as a tool to monitor nitrogen nutrient status, primarily through changes in the proportion of light energy distribution. These findings provide theoretical and technical support for monitoring and diagnosing wheat nitrogen nutrition status based on SIF technology. • SIF indices can better trace the change of crop nitrogen status than VIs. • Non-destructive diagnosis of nitrogen was achieved using the index FY 687 / FY 761. • The LDM-based NNI diagnostic model has high accuracy. • The light energy distribution explains the mechanism of SIF to trace N status. [ABSTRACT FROM AUTHOR]

• Reducing factor misallocation can increase agricultural productivity and farmer income. • A theoretical framework shows how farmland leasing affects aggregated TFP. • Efficient factor reallocation could theoretically result in a 23.6% increase in TFP. • An 1% increase in farmland leasing leads to a 1.087% gain in aggregate TFP. • An 1% increase in farmland leasing results in a 0.267% reduction in misallocation. Reducing factor misallocation is crucial for enhancing agricultural aggregate total factor productivity (TFP) and narrowing the income gap between urban and rural areas in China. This paper presents a theoretical framework illustrating how farmland leasing affects aggregated TFP via the reduction of misallocation. Utilizing a comprehensive dataset of cost and benefit survey for Jiangsu rice farmers, monthly surface climatological data, and soil characteristic information from FAO, this study finds that efficient factor reallocation could theoretically result in a 23.6% increase in aggregate TFP. In practice, a 1% increase in farmland leasing leads to a 1.087% gain in aggregate TFP and a 0.267% reduction in misallocation using IV regression. These effects become larger after the Three Rights Separation (TRS) reform compared to prior conditions. The mediation effects of farmland leasing on TFP through misallocation reduction are only observed in Southern Jiangsu, possibly due to farmland concentration. [ABSTRACT FROM AUTHOR]

The governments play an important role in allocation of land resources In China. However, few studies have focused on the local governments' spatial arrangement of land supply within their jurisdictions. Using the Jiangsu Province as a study area, this paper reveals the Chinese local governments' spatial response of land leasing to the industrial policy. Competition between localities for relative economic performance forces local governments to implement two spatial strategies in land leasing, maximizing economic performance and beggar thy neighbor. Rational prefectural governments are inspired to place policy-favored industries in municipal district or location closer to prefectural city center. First, allocating policy-favored industries the land adjacent to the city center or in municipal district will help to attract industrial investment. Second, assigning policy-favored industries far from the administrative boundary contributes to reduce the positive spatial spillovers to the neighboring jurisdictions. However, local governments may also adopt inter-regional cooperation strategy of not intervening in the location of land leasing for the industries closely linked to the advantageous industries of neighboring regions. • Chinese local government makes spatial arrangement of land leasing under industrial policy. • Local governments place key industries closer to prefecture-level city center. [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]

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]

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 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]

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]

Literature in population and development studies has examined the positive effects of rural-urban migration on the livelihoods and living standards of migrant workers. Less attention has been paid to the rural households trapped in poverty despite having family members working in the city. Drawing on a survey of rural households in the north of Jiangsu province, China, this paper examines how migration and an urban income affect the consumption patterns of poor rural households. The results confirm that among the rural poor, households with migrating members tend to have higher disposable incomes than immobile households. However, considerably higher living costs in the city compel these migrant households to be frugal and often split the family between the city and the rural home to minimize total household expenditures. Their incomes are often depleted by the costs of essential goods and services, such as housing, education, medication, transport, and other daily necessities. The findings reflect that many of China's poorest rural households are on the horns of a dilemma—having a job in the city mitigates poverty but often leads to the misery of family separation and the need to endure harsh living conditions for family members in the city. This urges policy changes to facilitate family migration and enhance rural welfare and resource provisions, especially in healthcare and education. • Migration affects the consumption patterns of poor rural households. • Urban livelihoods mitigate poverty but cause family separation and substandard living. • Policy recommendations to facilitate family migration and enhance education and healthcare. [ABSTRACT FROM AUTHOR]

For offshore structures such as offshore wind turbines (OWT), typhoon is usually considered one of the most critical threats to structural safety performances and service life due to its heavy wind, wave, and even coexisted storm surge. Meanwhile, it is challenging to obtain the systematic data from the environmental conditions, structural dynamic vibrations and the SCADA record, when typhoon passes by the offshore wind farm. Taking into account these situations, a real-time multi-source monitoring system enabling the investigation of the typhoon impact on the performances of OWT, has been firstly established and implemented to a 4.0 MW mono-pile OWT in Rudong, Jiangsu, China. One of the major contributions in this work is to develop the monitoring system using a unique environment of real-world data that has been synchronously obtained from waves, winds, vibrational accelerations, inclinations of towers and SCADA data during the typhoon "In-fa" passing by the wind farm, and provide the scientific community with the underlying standards and technical recommendations. To investigate the influence caused by "In-fa", comparison results of the measured data in the range of June to August have been analysed. It is worth noting that two conclusions have been obtained: (1) the region near the nacelle is not always the most critical vibrational area. Actually, the change of the maximum structural response in the position under different external loads should be applied to effectively evaluate the structural safety; (2) the measured accelerations exhibit an obvious decay process in the presence of the turbine rotor-stop, but not the yaw rigid-body motion. This observation promotes the accurate identification of modal parameters for the long-term monitoring. Consequently, these valuable findings to facilitate the assessment of structural operational conditions have been developed into two guide-lines. All the data and analyses presented in this paper provide a valuable insight into the design, energy efficiency, safety monitoring and damage diagnosis of OWT structures. • A novel systematic study on OWT performances considering the typhoon "In-fa" impact is conducted. • A real-time multi-source monitoring system with data management is developed. • Influences of the typhoon on dynamic performances of Mono-pile OWTs are discussed via the field-data analysis. • Two guide-lines for long-term monitoring and safety assessment are established. [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]

The southeast region of China is frequently affected by summer heat waves. Nanjing, a metropolitan city in Jiangsu Province, China, experienced an extreme 14-day heat wave in 2013. Extreme heat can not only induce health outcomes in terms of excess mortality and morbidity (hospital admissions) but can also cause productivity losses for self-paced indoor workers and capacity losses for outdoor workers due to occupational safety requirements. All of these effects can be translated into productive working time losses, thus creating a need to investigate the macroeconomic implications of heat waves on production supply chains. Indeed, industrial interdependencies are important for capturing the cascading effects of initial changes in factor inputs in a single sector on the remaining sectors and the economy. To consider these effects, this paper develops an interdisciplinary approach by combining meteorological, epidemiological and economic analyses to investigate the macroeconomic impacts of heat waves on the economy of Nanjing in 2013. By adopting a supply-driven input-output (IO) model, labour is perceived to be a key factor input, and any heat effect on human beings can be viewed as a degradation of productive time and human capital. Using this interdisciplinary tool, our study shows a total economic loss of 27.49 billion Yuan for Nanjing in 2013 due to the heat wave, which is equivalent to 3.43% of the city's gross value of production in 2013. The manufacturing sector sustained 63.1% of the total economic loss at 17.34 billion Yuan. Indeed, based on the ability of the IO model to capture indirect economic loss, our results further suggest that although the productive time losses in the manufacturing and service sectors have lower magnitudes than those in the agricultural and mining sectors, they can entail substantial indirect losses because of industrial interdependencies. This important conclusion highlights the importance of incorporating industrial interdependencies and indirect economic assessments in disaster risk studies. [ABSTRACT FROM AUTHOR]

Member participation in decision-making is a critical part of resource co-management. However, little is known about the welfare consequences of participation. This paper analyzes the impact of cooperative member participation in decision-making on their incomes, using data from 364 members of China's land cooperative program. We distinguish two levels of participation in decision-making – voting and obtaining financial information – and use a bivariate probit model and propensity score matching to estimate their impact. The results indicate that household head's age, gender and education and family size, wealth, and political affiliation determine participation in decision-making. Participation in either voting or obtaining financial information has a positive impact on cooperative members' land income. There is also a strong joint effect of voting and obtaining information, with an increase in land income of > 16%. We conclude that broad participation can ensure more equitable access to land income for members. [ABSTRACT FROM AUTHOR]

The space in the process of urbanization is undergoing a great transition from physical space to social space. The relations between society and space become more important and complicated than ever. As a critical social theory, production of space means that urbanization has been reshaped by social factors or forces like capital, power and class, so that the urban space finally becomes their production and process. Based on socio-spatial dialectic, the main methodology of spatial production, urban space (re)shapes social relations and processes. The different spatial scales have and continuously produce the different social relations. In the researches about production of space, little work has been done on the index system to assess the extent of production of space and to analyze middle-scale region. This article designs a set of simple index system to reflect the spatial influences of capital, power as well as class, and chooses Jiangsu Province as a typical case because of its rapid and differential urbanization to indicate the process of spatial production from 2000 to 2015. In this index system, capital is represented by fixed-asset investment, real estate investment and foreign direct investment; power is represented by the index of the constructed urban land area; the index reflecting class is the urban-rural income ratio. Based on the analysis of these changing indexes, this paper finds that urbanization in Jiangsu is hybrid process: the forces from capital and power greatly contribute to rapid urbanization and high urbanization level, however, the gaps among the three sub-regions in the province and rural-urban income inequality have not decreased accordingly. Conversely, these gaps enlarge in some periods. This kind of urbanization pattern is characterized by large-scale spatial expansion, and is driven by capital and power, but there are many latent social risks and spatial inequality. In the process of spatial production, space and society interact, entangle and (re)shape the pattern of urbanization in the end. [ABSTRACT FROM AUTHOR]

Housing problems in China have recently aroused wide range of interests of scholars. Housing demand, which is a classical discussing point in academia, also acts as reference for governments to enact loose, tense or neutral housing policies. However, studies scrutinizing the housing demand structure, particularly from consumption and investment perspectives are scant. Existing researches have mostly focused on the mature housing market in large cities in China, and the housing market in small cities has rarely been addressed. In this study, housing demand is deliberated in two respective dimensions of rent/own and consumption/investment demand. Price elasticities are obtained through formulating demand functions of each demand category with micro-data collected through questionnaire survey in small cities in Jiangsu. Underpinned by the set of elasticity coefficients, detailed housing demand structure can be calculated proportionately. Results suggest that the improvement and investment housing needs have outweighed basic consumption demand in small cities in Jiangsu Province. Housing price rising has a promoting effect on residential housing demand, which is in stark contrast to the existing studies on price elasticity of housing demand in large cities in China. Factors of urbanization significantly influence the housing need of residents in small cities. Improvement of urbanization rate would contribute to the consumption demand booming while prosperity of tertiary industry would boost improvement and investment housing demand. Not only could the analytic methodology of housing demand structure demonstrated in this paper be referenced, but the empirical answers carry vital implications for governments implementing diverse policy design in large and small cities in China. [ABSTRACT FROM AUTHOR]

Carbon emissions (CE) have a profound impact on the natural environment of the surface, and the ecologic environment quality (EEQ) affects the conversion and absorption of CE. CE and EEQ have an interaction and mutual influence relationship. The connection between them includes not only local interactions but also the long-range distance of external systems. It is critical to measure CE and EEQ and coordinate their association in order to increase the effectiveness of CE and EEQ collaborative governance. However, the traditional remote sensing ecological index (RSEI) model ignores the importance of air quality. Furthermore, there is limited current research on the local and telecoupling relationship between CE and the EEQ. To fill these research gaps, this paper first used night light data to dynamically monitor CE. Then we proposed an upgraded RSEI model (RSEInew) to assess EEQ. Finally, the local and telecoupling coordination degree (LTCCD) model was suggested to further investigate their relationship in the Yangtze River Economic Belt (YREB) from 2000 to 2019. The results showed that: (1) Total CE in the YREB increased from 837.5738 million tons to 4757.3794 million tons between 2000 and 2019 but has not yet reached its peak. Jiangsu and Zhejiang are at the forefront in terms of CE and have huge emission reduction potential. (2) The YREB's overall EEQ has deteriorated over the last 20 years. The average RSEInew value ranged between 0.52 and 0.71, with "medium" and "good" EEQ levels dominating. (3) The LTCCD of CE and EEQ in the YREB has increased year by year. This study can deliver a reference for decision-makers to synergistically formulate carbon emission reduction plans and environmental protection schemes. • Ecologic environment quality should combine regional characteristics, our RSEInew model could evaluate it with introduces PM2.5. • Carbon emissions and the ecologic environment quality interact with each other, with near- and long-range interactions. • The LTCCD model enable to analysis the local and telecoupling relationships of CE and EEQ. [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]

Transportation in Jiangsu province has been developed rapidly. However, the development was accompanied with a large amount of energy consumption and carbon emissions. Combined with the coefficient in 2006 Intergovernmental Panel on Climate Change (IPCC) guidelines for national greenhouse gas inventories and China's calorific value, this article calculated the carbon emission coefficient of usual energy covered by Jiangsu Statistical Yearbook (JSY) in detail. Based on this, carbon emission of transportation in Jiangsu Province from 1995 to 2012 was easily estimated. And from the result which appears clearly that the construction of energy consumption was changed in 2011. According to China Electricity Power Yearbook (CEPY) and China Energy Statistical Yearbook (CESY), carbon emission caused by electricity power indirectly could be estimated. With the help of Tapio model, this paper conducted a research on decoupling relationship between economic growth and carbon emission of transportation in Jiangsu Province with consideration of electricity. The results show that the amount of carbon emission by electric power is significant, which makes no difference on the overall decoupling states with an obvious periodical characteristic of Weak Decoupling (Expansive Coupling)-Expansive Negative Decoupling-Weak Decoupling. Transportation has made great achievements on reducing pollution and carbon emission in Jiangsu Province since the Eleventh Five-Year Plan, and would be better on low-carbon development in potential. However, there is still a large step to realize low-carbon transportation in reality. [ABSTRACT FROM AUTHOR]

In this paper, GM(1,N r) model is established to improve the traditional GM(1,N) model from three aspects: (1) transforming the original sequence to satisfy the modeling conditions with particle swarm optimization algorithm; (2) introducing grey incidence analysis to obtain the grey incidence ranking and carrying out stepwise test for significant variables to determine the number of variables; and (3) predicting the related factor sequence through the improved GM(1,1) model. Empirical analysis shows that the proposed GM(1,N r) model has remarkable good prediction performance compared with the traditional grey forecasting model. It is also demonstrated that the extraction of influencing factors can significantly improve the prediction effectiveness, especially when pursuing the best fitting effect on small sample data. The findings indicate that the electricity consumptions of Jiangsu Province in the next several years will be at a high level and keep rising, with a predicted value of 9712.48 billion kilowatt-hours in 2030. The findings can help the government and energy related institutions to develop management policies on energy demand, and the proposed model can also be extended for the application in other regions. • Propose a new model to improve the traditional GM(1,N) model. • Adopt a new method to find the best value to satisfy the modeling conditions. • Use the grey incidence analysis with stepwise examination to identify factors. • Combine the improved GM(1,1) model to improve the performance of GM(1,N). • Apply this new model to analysis electricity consumption in Jiangsu Province. [ABSTRACT FROM AUTHOR]

• A grey multivariate model with dynamic sinusoidal term is proposed. • The Moore-Penrose generalized inverse matrix is used in the least square method. • The validation set is introduced to the training process of model parameters. • The relationship between sample size and model accuracy is discussed. To solve the problem that the grey multivariate prediction model cannot well simulate systems with periodic oscillations, a novel multivariate grey model called the GM(1,N|sin) power model is proposed. The power exponential term and dynamic sinusoidal function are developed to represent the nonlinear relationship and periodic oscillations of the independent and dependent variables in the proposed model, respectively. First, the discrete time response formula for generating the simulated values at each time point is given. Second, the nonlinear programming model based on the particle swarm optimization algorithm is established to solve the power exponential and periodic coefficients. In addition, to enhance the generalization ability of the parameters, an improved nonlinear programming model considering the accuracy of the validation set is constructed. Finally, in the case studies, the quarterly electricity consumption of Jiangsu Province and PM 2.5 concentrations in Nanjing are adopted to test the effectiveness of this model, and the results are obtained respectively through the GM(1,N|sin) power model and alternative models. The results indicate that the accuracy of GM(1,N|sin) power model in the time series with periodic oscillations outperforms the other six models in this paper. [ABSTRACT FROM AUTHOR]

The upscaling of farming operations in China has been advancing rapidly in recent years. This trend is likely to increase the use of agricultural machinery inputs, and possibly also the use of chemical pesticides, which is already extremely high. The relationship between farm size and the intensity of chemical pesticide usage is a subject of debate, and little is known about the mechanisms that might underlie this relationship. In this paper, we apply an integrated framework of larger-scale farming, agricultural mechanization and the intensity of chemical pesticide usage to examine and quantify the mediating effect of agricultural mechanization on the relationship between larger-scale farming and the use of chemical pesticides. Results obtained by applying seemingly unrelated regression (SUR) considering two-way fixed-effects and mediation analysis to county-level data for Jiangsu Province (2002–2019) suggest that an increase of 1% in the ratio of scale of farming is related to a total decline of 0.070% in chemical pesticide usage per hectare of land. Mediation analysis subsequently identifies mechanical sowing/transplanting is the only mediating variable, through which an increase of 1% in the ratio of scale of farming reduces the unit consumption of chemical pesticides by 0.017%. [ABSTRACT FROM AUTHOR]

The upscaling of farming operations in China has been advancing rapidly in recent years. This trend is likely to increase the use of agricultural machinery inputs, and possibly also the use of chemical pesticides, which is already extremely high. The relationship between farm size and the intensity of chemical pesticide usage is a subject of debate, and little is known about the mechanisms that might underlie this relationship. In this paper, we apply an integrated framework of larger-scale farming, agricultural mechanization and the intensity of chemical pesticide usage to examine and quantify the mediating effect of agricultural mechanization on the relationship between larger-scale farming and the use of chemical pesticides. Results obtained by applying seemingly unrelated regression (SUR) considering two-way fixed-effects and mediation analysis to county-level data for Jiangsu Province (2002–2019) suggest that an increase of 1% in the ratio of scale of farming is related to a total decline of 0.070% in chemical pesticide usage per hectare of land. Mediation analysis subsequently identifies mechanical sowing/transplanting is the only mediating variable, through which an increase of 1% in the ratio of scale of farming reduces the unit consumption of chemical pesticides by 0.017%. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, China vigorously develops clean energy and renewable energy. As a result, offshore wind power projects have grown rapidly. The success of offshore wind power projects depends on the location of offshore wind power station(OWPS), and this paper aims to develop a hybrid decision-making framework to address the location of offshore wind power stations. Firstly, a comprehensive evaluation attribute system of offshore wind power station site selection is innovatively constructed, including wind resources, construction conditions, economy, environment and risks. Secondly, probabilistic linguistic term set(PLTS) is used to describe uncertain information, which improves the reliability of decision information. Thirdly, The Best-worst method (BWM) based on probabilistic language term sets determines the weights of attributes, which ensures the accuracy of the attribute weight. Finally, an extended TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) method is proposed to rank the alternatives. The proposed method is applied to the location selection of offshore wind power station in Jiangsu Province, China. Through sensitivity analysis and comparative analysis, it is verified that the proposed model has good stability and applicability. • A new multi-attribute decision-making model is proposed. • Establish the evaluation attribute system of offshore wind power station location. • Expression of evaluation information by probability language. • Probability Language and Best-worst Method Combined to Calculate Attribute Weight. • An improved Interactive and Multicriteria Decision Making method is proposed. [ABSTRACT FROM AUTHOR]

Governments and scholars are taking a closer look at risk assessment of areas developing chemical industries because of the repeated occurrence of chemical explosion accidents along coastal regions. The paper constructs an indicator system for Jiangsu Province based on three dimensions: risk source strength, receptor vulnerability, and risk prevention capability. It comprehensively evaluates the risks under stress from the chemical industry since the implementation of the coastland development strategy. The results show that a first rise in and then a decline in comprehensive risk along the coast of Jiangsu Province could be observed from 2007 to 2017. As a whole, the risk of contamination was dispersed, while locally, it accumulated and gradually shifted to areas along the river and adjacent coastal areas. High-risk areas are mainly distributed in chemical industry clusters. Risk sources continue to intensify with the increase in heavy chemical industry clusters. Generally, receptor vulnerability was high in the west, low in the east, high in the north and south, and low in the middle. The Tongyu River, Sheyang River, coastal wetlands, and canals in Nantong are among the most vulnerable areas. There is still a weak overall situation, with a pattern of 'high-low-high' staggered distribution from south to north, even though the risk prevention capacity is growing steadily. [ABSTRACT FROM AUTHOR]

The existing research on watershed ecological compensation pays less attention to the special basin (without significant relationship between upstream and downstream or the compensation subject and object are distributed on the left and right banks of the basin), which makes the previous research methods difficult to be effectively used. Therefore, it is necessary to explore a new method to solve the problem of ecological compensation in special basin. Taking Taihu Lake Basin (Jiangsu section) as an example, this paper first calculates the ecosystem service value (ESV) of the region from 2005 to 2018, and makes a spatial-temporal analysis; through the construction of land use intensity index system and coupling coordination degree model, the relationship between ESV and land use intensity is explored, and the reasons for its change are explored; finally, this paper constructs a compensation standard accounting model based on GDP, basin area and population, and applies it to the accounting of compensation standard and the identification of compensation subject and object. The results show that: from 2005 to 2018, the land use of this area changed greatly, mainly reflected in farmland and urban land; ESV decreased by 21.41%, which was mainly affected by the change of land use, the downturn of grain market, and farmers' going out to work; the coupling coordination degree of land use intensity and ESV in this area entered the stage of coordinated development from 2010, but the situation of each city was quite different; population, area and GDP have a great influence on compensation subject and object, and compensation standard. This study can not only provide a complete methodology for governments to implement ecological compensation in special basins, and improve the existing ecological compensation theory. [ABSTRACT FROM AUTHOR]