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This paper reports a case study of the community revitalization initiative in Bishan Village, Anhui Province, China, which is art-oriented and overseen by the renowned art curator Ou Ning and his colleagues. The Bishan Project, launched in 2011, is analysed as an attempt to revive the countryside through cultural and creative innovations. This responds to the recent emphasis in rural studies on arts and creativities as effective interventions into rural revival and development. To comprehend the vibrant, resilient, and innovative ruralities that are proliferating around the world, the post-productivism thesis casts important light on the revival and revalorization of rural places by way of the diversification of rural livelihoods and economies. However, the focus on cultural consumption by urban consumers cannot account for the varied constellations of economic, social, and cultural innovations that contribute to the swift reinvention of rurality. Engaging instead with the literature on rural creativity, which examines the crucial role of creative practices in restoring rural subjectivities and remedying the social fabrics in rural regions, this study suggests that creative initiatives intervene in and catalyst the restoration of local cultures and social relations, and contribute to an evolutionary resilience that is nonetheless contested and indeterminate, revolving around tensions between the cultural authority of artists and villagers' uneven participation; and between local villagers' aspiration for economic development and artists' reluctance to capitalize on rural creativities. • The need to theorize reinvention of rurality becomes imperative amid urban-rural integration. • The post-productivism approach sheds light on the diversification of rural livelihoods. • The rural creativity literature pays more attention to endogenous development. • Socially engaged arts provide a relational means of knowledge making. • This paper investigates art-based rural revitalization in Bishan Village, China. [ABSTRACT FROM AUTHOR]

Although a large number of reviews have studied different scales of forest ecosystem services, few have concentrated on accounting the spatiotemporal dynamic changes of forest ecosystem services in a region. To make a more accurate accounting, this paper selects intense data sets that assess the physical quantity and value of forest ecosystem services in Anhui provinces from 2009 to 2014. Regulating and supporting services such as water conservation, carbon sequestration and oxygen release, soil conservation and air purification are included in the paper as variables. Optimize analysis was further conducted in order to identify the spatial and temporal heterogeneity during the study period. We establish a dynamic ecosystem services assessment model with the coefficient of spatial heterogeneity and coefficients of scarce resources and social development to analyze the trend of the value in Anhui province. This model is designed for comparisons of forest services in different scales in Anhui province. The results demonstrate that the total value of forest ecosystem services is beyond the previous estimation while using spatiotemporal visualization. The implications are that the evaluation of forest ecosystem services should be measured more accurately with the help of big data in the future. [ABSTRACT FROM AUTHOR]

• A large-area digital soil mapping method based on environmental-similarity is proposed. • The distance-decay relationship is adaptively determined by spatial distribution of samples. • Adaptively considering spatial distance to samples improves soil prediction accuracy. Digital soil mapping (DSM) based on environmental similarity may be used to predict the soil properties at unvisited locations based on the soil–environment relationship at each sample locations, which is more suitable for large-area (or regional scale) predictive mapping with comparatively limited soil samples than (geo-)statistical DSM methods with high requirements for the quantity and spatial distribution of samples. Recently, the DSM method based on environmental similarity but with inadequate consideration of the First Law of Geography was improved by considering the spatial distance to samples by means of the inverse distance weight (IDW), following the assumption that the more similar the environmental conditions and the shorter the spatial distance between the locations of interest and a sample are, the more similar the soil properties of the two locations. However, the current consideration of spatial distance by a constant distance-decay parameter should be improper across a whole large area under mapping due to the spatial variation of both sample distribution and the environmental conditions over a large area. In this paper, we propose a new large-area DSM method based on environmental similarity with adaptive consideration of spatial distance to samples by using adaptive distance-decay parameter values across a large area. An evaluation experiment to predict the soil organic matter at a depth of 0–20 cm at a 90-m resolution with a total of 659 soil samples in Anhui Province (approximately 134000 km2), China, was carried out. Evaluation results show that the proposed method (named iPSM-AdaIDW) achieved higher accuracy (with a root mean square error, or RMSE, of 8.273 g/kg) than two representative environmental-similarity-based DSM methods, i.e., individual Predictive Soil Mapping (iPSM) (without considering the spatial distance to samples) (RMSE = 8.878 g/kg) and iPSM considering spatial distance with a constant distance-decay parameter across the study area (RMSE = 8.310 g/kg), and a representative of large-area DSM not based on environmental similarity, i.e., the random forest kriging method (RMSE = 9.647 g/kg). For large areas with quantitively limited and unevenly distributed samples, the proposed method can achieve more applicable and accurate predictions. [ABSTRACT FROM AUTHOR]

Knowledge of vertical distribution of air pollutants is important for understanding the mechanisms underlying haze pollution. In this paper, we characterize the vertical structure of air pollutants based on ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements in the wintertime in Hefei, East China. Both NO 2 and aerosol show exponentially decreasing profile with high concentrations concentrated close to the surface, suggesting the major emissions are at ground level. SO 2 profiles extend to slightly higher altitudes than NO 2 , which might be due to the SO 2 emissions from elevated point sources (e.g., power plants). Elevated HCHO was observed in the middle layer during noon time, probably indicating that the larger effect of the photochemical formation of atmospheric HCHO rather than direct HCHO emissions. Potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models were used to evaluate the potential sources of Hefei's air pollution in the lower, middle and upper boundary layer. The results revealed that the major regional source of NO 2 and aerosol were located in the northern and eastern part of Anhui and the transport mainly occured in the lower layer. Transported SO 2 from the northwestern regions in the middle layer made great contribution to SO 2 in Hefei. HCHO was mostly produced locally while the transport of HCHO from potential source areas was negligible. To further explore the potential source contributions affecting haze pollution, PSCF and CWT analysis for heavy haze episodes suggested that the potential source areas for aerosol were almost located in the northern region, the northwestern region, and the YRD region. Our findings provide a more comprehensive understanding for regional transport through the study on potential sources at different altitudes, which are useful for designing collaborative air pollution control strategies on a regional scale. • Vertical distribution of air pollutants is investigated to identify potential sources at different altitudes during winter. • Both NO 2 and aerosol show exponentially decreasing profile with high concentrations concentrated close to the surface. • SO 2 and HCHO profile typically extended to higher altitudes than NO 2 and aerosol did during winter. • The main potential sources for aerosol were located in the northern region, the northwestern region, and the YRD region. • This study is useful for designing collaborative air pollution control strategies on a regional scale. [ABSTRACT FROM AUTHOR]

Green Mining Construction (GMC) is the Chinese national strategy of the environmental regulation of the mining industry to motivate mining enterprises to improve their resource utilization efficiency, protect the environment and harmonize the relationship between enterprises and communities. This paper uses system dynamics (SD) and the Malmquist-Luenberger (ML) Index to model the sustainable effect of the policy instruments of Green Mining Construction, namely, environmental taxes and subsidies. A case study of typical coal mining enterprises in Anhui, China, is provided to demonstrate the application of the proposed model in which the corporate performances of three optional strategies in response to the Green Mining Construction policies are examined. The responsive strategies are categorized as scale expansion, technical innovation and environmental protection. The simulation results show the following: (i) The environmental taxes and subsidies with disparate rates can help enterprises that focus on technical innovation and environmental protection perform better, albeit with a certain degree of lag. (ii) The synergy impact of subsidies and taxes is not significantly more than the separate ones. (iii) Environmental regulations reduce the productivity of mining enterprises, but to varying extents. This negative effect of environmental regulation should be compensated by other measures. This study offers insights to help enterprises select optimal strategies in response to the Green Mining Construction policies and to inform the government of possible sustainable policy designs to promote the Green Mining Construction. The limitations of the model are discussed for further improvements in simulating the effect of environmental regulation. • The hybrid model is used to test the effect of mining environmental policy in China. • Environmental taxes and subsidies are effective, but there are delays. • The effect of policy combination is not better than that of the single policy. • The model negates the Porter hypothesis, but there are differences among enterprises. [ABSTRACT FROM AUTHOR]

Abstract In the late 1990s, China initiated the Conversion of Croplands to Forest Program (CCFP) and the Ecological Welfare Forest Program (EWFP) based on the Payments for Ecosystem Services (PES) principle. Positive socioeconomic outcomes of the programs are essential for the long-term success of eco-environment conservation. However, there is lack of understanding of their longer-term (over 10 years) impacts on rural livelihoods. In this paper, we examine income distribution and inequality of rural households under CCFP and EWFP in rural Anhui, China after 12 years of program implementation. Results show that CCFP-participating households have higher income inequality than non-participants, while the EWFP does not have a significant effect. Local off-farm work and out-migration with remittances are the two principal income sources and both add to inequality. A regression-based decomposition of inequality shows that the CCFP indirectly alters livelihoods by increasing out-migration with remittances, but it also adds to inequality from shifting livelihoods to non-agricultural activities. Meanwhile, EWFP payments positively affect agricultural incomes and contribute 16% to agricultural income inequality. Finally, human capital, natural capital and physical capital all play important roles in generating income and inequality, but the factors affecting inequality from agricultural and non-agricultural activities are different. Highlights • We examine rural household income distribution under two concurrent PES programs. • CCFP positively affects non-farm income via out-migration followed by remittances. • EWFP positively affects agricultural income and adds slightly to inequality. • Factors affecting agricultural and non-agricultural income distributions differ. [ABSTRACT FROM AUTHOR]

• Theoretical model was proposed to analyze the time-dependent behavior of RRU; • The model was used to analyze the convergences of roadway in a mining project; • Good agreements were achieved from analytical solutions and field monitored data; • Stress in rock decayed over time when sudden stress was imposed on the RRU. The energy-absorbing bolt is an advanced reinforcing element in rock mass to absorb the deformation energy. In this paper, the time-dependent reinforcement provided by the energy-absorbing bolt was analyzed based on assumptions of the reinforced rock unit (RRU) model for systematic bolting. The energy-absorbing bolt was simulated with an ideal elastic–plastic material law. The rheological behavior of the energy-absorbing bolt was represented by the connection of a Hookean elastic element and a Saint Venant element in series. The constitute model and creep behavior of the RRU under a sudden stress change were obtained by assuming the rock was a general Kelvin material. It showed the RRU exhibited an instantaneous jump in the strain, transient creep, and steady-state creep under a sudden change of external stress. The resulting stress in the rock decreased progressively as that in the energy-absorbing bolt could sustain the loading as large as its designed yielded stress. The constitutive models of RRU were applied to predict the convergences of surrounding rock mass in a mining roadway, in Anhui province, China. Good agreements were achieved between the analytical solutions and the field-monitored data. [ABSTRACT FROM AUTHOR]

Researches revealed that there has been existed a relatively stable and positive relationship between economic growth and electricity consumption. However, the inconsistency between them appeared in 2008. Therefore, it is urgent to analyze whether the GDP in China is cheated and to seek the underlying reasons contributed to the deviation. Anhui province is selected to act our study area. In order to explore the underlying reasons of the deviation between economic growth and electricity consumption, a multivariable regression models is established in this paper. Empirical results are as follows: (1) real GDP, industrial structure (IS), heating degrees days (HDD), cooling degree days (CDD), investment in fixed assets (IF) are all positive factors for the consumption of electricity; (2) IS is the major contributor to raising the consumption of electricity, followed by IF, CDD, HDD, and GDP; (3) energy intensity (EI) and financial development (FD) are negative factors, when the value of EI increase 1.0%, the consumption of electricity will decrease 7.4%; (4) if the electricity consumption caused by other factors except GDP is eliminated, the deviation would almost shrink; (5) the real growth rate of GDP of Anhui province is authentic. [ABSTRACT FROM AUTHOR]

• Presents a data-driven measurement, evaluation, and identification method. • Uses a coupling coordination degree model for three regional agriculture subsystems. • Suggests ways to reduce costs, increase social support, and enhance competitiveness. This study aims to evaluate the relationship between the agriculture economy environment, and society from the perspective of system theory and then put forward targeted suggestions for sustainable development of Anhui's agriculture in China. Based on the collection of relevant data and the objective weighting of indicators, the entropy weight method is used to measure the comprehensive development level of regional agriculture. The coupling coordination degree model is employed to evaluate the coupling coordination level among the three subsystems of regional agriculture. The obstacle degree model is used to identify the key obstacle factors. The case study results show that the main obstacles of the coordination system are the use of pesticides, the number of agricultural scientific and technological achievements, the application of agricultural plastic film, the number of farmers' technical training schools, and the proportion of animal husbandry. Accordingly, the paper posits suggestions, such as reducing the input of pesticides and agricultural plastic films in agricultural production, improving the social support level of agricultural science, technology, and education, and enhancing the competitiveness of animal husbandry in the Anhui Province. This study provides theoretical and methodological support for the coupled and coordinated development of regional agricultural economy, ecology and society(EES). [ABSTRACT FROM AUTHOR]

• The reliability of soil-environment relationships at sample points was evaluated. • The prediction trustworthiness results at unvisited locations was evaluated. • The estimated prediction trustworthiness is indicative of prediction accuracy. • The method is robust regardless of the processing orders of sample points. Observations of soil at georeferenced sample points are the indispensable input to digital soil mapping (DSM) models that relate soil properties and types to the soil-forming environment. Many existing DSM methods require soil samples to be collected following a pre-defined sampling pattern. This requirement is often not met due to various operational reasons. The individual sample-based predictive soil mapping (iPSM) method has been developed to avoid this requirement. However, the prediction accuracy of iPSM depends heavily on the reliability of the known sample points used in prediction. Unreliable sample points are those with unreliable soil-environment relationship: the target soil property value and environmental covariate data are not correctly paired at the sample point location. Such unreliable sample points will lead to poorly constructed models and low prediction accuracy. This paper presents a new method to estimate the reliability of soil-environment relationship at each sample location and to evaluate the trustworthiness of prediction at each unvisited location. Under the assumption that sample points with similar environmental conditions have similar soil property values, the method first identifies the sample points that are environmentally similar to the sample point to be evaluated, then uses their agreement on the targeted soil property to evaluate the reliability of soil-environment relationship at the sample point. The effectiveness of the method was assessed in a case study located in Anhui Province in China to map soil organic matter content (SOM, %) in the topsoil. When the reliability threshold increased from 0.5 to 0.8, more unreliable sample points are excluded from prediction: 41% of total sample points were excluded when the threshold was set to 0.5, and 88% were excluded when the threshold was set to 0.8. As a result, less unknown area could be predicted – only nine validation points were predictable with the 0.8 reliability threshold. However, the prediction accuracy was improved: the root mean squared error, RMSE, decreased from 1.37% to 0.63%, and R2 increased from 0.21 to 0.98. Prediction trustworthiness at each unvisited location was also produced along with prediction accuracy, which was negatively related to the absolute prediction residuals. This study shows that the reliability of individual sample points is an important determinant of the prediction accuracy of the iPSM method. When applying iPSM method, an optimal trade-off between prediction accuracy and completeness of the predicted map needs to be found by adjusting the reliability threshold on the sample points used in prediction. [ABSTRACT FROM AUTHOR]

In this paper, we present a case study of the Fanshan lithocap developing in the Luzong intracontinental volcanic basin to indicate the direction of mineralization because lithocaps are generally related to the porphyry-epithermal system. The Fanshan lithocap formed in the magmatic-hydrothermal environment and then superimposed by supergene environment. We predicted the direction of mineralization of Fanshan lithocap using the formation environment, alunite at 1480 nm peak positions, whole-rock geochemistry, magmatic-hydrothermal alunite geochemistry, and alteration zones. Precious metals mineralization may occur in the depth of Dafanshan alunite mining area (star position in figure), copper mineralization potential may be in the Huangtun area, which is located in the northeast of the Dafanshan alunite mining area. • Short-wave infrared spectroscopy was used to distinguish and recognize mineral species. • Fanshan lithocap was formed in a magmatic hydrothermal environment superimposed by a supergene environment. • Spatial variation of alteration zones indicate the mineralization direction. • Copper and gold mineralization nearby is explored in the Luzong basin. Lithocaps in island-arc settings are genetically related to porphyry-epithermal systems and can be used to guide exploration for porphyry deposits. The Fanshan area of the Luzong basin in the eastern China, hosts a large lithocap but no porphyry or epithermal deposits have been found. The Fanshan lithocap in the Luzong basin is centred on the Dafanshan alunite mining district with vuggy quartz–alunite–pyrite, quartz–dickite–kaolinite ± alunite, quartz–kaolinite and kaolinite–illite ± smectite from northeast to southeast. The alteration zoning reflects the gradual decrease in the temperatures and acidities of the fluids. Four types of alunite including bladed alunite, needle alunite, granular alunite, and powdery alunite suggest that the Fanshan lithocap formed in the magmatic-hydrothermal and supergene environment. From the southwest to the northeast of the Dafanshan district, Pb and 106Pb/(Na + K) in the alunite samples gradually decrease, Au content gradually increases, but the Cu content does not change significantly. The peak positions at 1480 nm and the Na content of the magmatic-hydrothermal alunite gradually increase, whereas Pb and 106Pb/(Na + K) in the alunite minerals gradually decrease. This suggests that the source of the hydrothermal fluids and a potential zone of precious metal mineralization area may be in the northeast of the Dafanshan district, and the potential area of copper mineralization may be in the Huangtun area northeast of the Luzong basin. [ABSTRACT FROM AUTHOR]

Here we present our workflow and the final results of the 3D prospectivity modeling around the Zhuchong deposit undertaken during this study shown in terms of degree of connection values. The workflow is the core guiding ideology of our work. During the ore formation prediction, we tried to use weights of evidence method and artificial neural networks method to deal with the 3D cells data. And the results indicate these two methods can well predict the location of the known ore bodies. The reason may be that the copper deposits in Zhuchong Fe-Cu deposit are not concentrated but scattered, which makes making a certain influence to training samples in the neural network method. Which cause the defective result of neural network the result of neural network method is defective. What's more, the weight of evidence is also faster than the neural network method in speed. The results of the two prediction methods are roughly consistent. The similarity between these two prediction results indirectly reflects that two methods are feasible in Zhuchong Fe-Cu deposit. In the meanwhile, the prediction results are proved reliable and useful. The final prediction zone of metallogentic can be used as a target area for further exploration in Zhuchong mining area. • We use 3D ore formation prospectivity modeling and weights of evidence method and artificial neural networks method on the Zhuchong Fe-Cu deposit. • Result indicates that areas of known mineralization can be used to train 3D datasets to identify areas that are highly prospective for future exploration. • Compared the prediction results of the weight of evidence and the neural network, synthetically considering, for Zhuchong skarn Fe-Cu-Au deposit, the weight of evidence is more appropriate for the metallogenic prediction work. Our work has guiding significance for future deep prospecting and exploitation for other similar Fe-Cu skarn deposits. Three-dimensional (3D) metallogenic prospectivity modeling has become increasingly important in deep Fe-Cu skarn mineralization prospecting. The selection of prediction models and their comparison are of great significance. In this paper, we integrated the geological and geophysical data from the Zhuchong Fe-Cu deposit in the Yueshan orefield (Anhui, eastern China) to establish the local 3D geological framework. We extracted the 3D ore-controlling factors quantitatively by means of 3D spatial analysis methods, and compared the 3D mineralization locations predicted by the weight of evidence method and the artificial neural network method. The results show that both methods can locate most of the known orebodies, suggesting that both are relatively reliable. In addition, the weight of evidence method performed distinctly better than the artificial neural network method in terms of both prediction effectiveness and efficiency. Therefore, the weight of evidence method may be more applicable in 3D prospectivity modelling for Fe-Cu skarn deposits in the region. Finally, the composite area predicted by the two methods is taken as the final prediction result of the mineralization area of the deposit. And it is suggested that in the quantitative 3D prediction, multiple selection of different methods with good adaptability should be involved in the prediction at the same time, and compound prediction method should be used to delineate the target area. Our work has guiding significance for future deep prospecting and exploitation for other similar Fe-Cu skarn deposits. [ABSTRACT FROM AUTHOR]