Mapping Soil Properties in the Haihun River Sub-Watershed, Yangtze River Basin, China, by Integrating Machine Learning and Variable Selection.

Mapping soil properties in sub-watersheds is critical for agricultural productivity, land management, and ecological security. Machine learning has been widely applied to digital soil mapping due to a rapidly increasing number of environmental covariates. However, the inclusion of many environmental covariates in machine learning models leads to the problem of multicollinearity, with poorly understood consequences for prediction performance. Here, we explored the effects of variable selection on the prediction performance of two machine learning models for multiple soil properties in the Haihun River sub-watershed, Jiangxi Province, China. Surface soils (0-20 cm) were collected from a total of 180 sample points in 2022. The optimal covariates were selected from 40 environmental covariates using a recursive feature elimination algorithm. Compared to all-variable models, the random forest (RF) and extreme gradient boosting (XGBoost) models with variable selection improved in prediction accuracy. The R2 values of the RF and XGBoost models increased by 0.34 and 0.47 for the soil organic carbon, by 0.67 and 0.62 for the total phosphorus, and by 0.43 and 0.62 for the available phosphorus, respectively. The models with variable selection presented reduced global uncertainty, and the overall uncertainty of the RF model was lower than that of the XGBoost model. The soil properties showed high spatial heterogeneity based on the models with variable selection. Remote sensing covariates (particularly principal component 2) were the major factors controlling the distribution of the soil organic carbon. Human activity covariates (mainly land use) and organism covariates (mainly potential evapotranspiration) played a predominant role in driving the distribution of the soil total and soil available phosphorus, respectively. This study indicates the importance of variable selection for predicting multiple soil properties and mapping their spatial distribution in sub-watersheds.

Pollution and risk assessment of potentially toxic elements in soils from industrial and mining sites across China.

Potentially toxic elements in soils (SPTEs) from industrial and mining sites (IMSs) often cause public health issues. However, previous studies have either focused on SPTEs in agricultural or urban areas, or in a single or few IMSs. A systematic assessment of the pollution and risk levels of SPTEs from IMS at the national scale is lacking. Here, we obtained SPTE (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) concentrations from IMSs across China based on 188 peer-reviewed articles published between 2004 and 2022 and quantified their pollution and risk levels using the pollution index and risk assessment model, respectively. The results indicated that the average concentrations of the eight SPTEs were 4.42-270.50 times the corresponding background values, and 19.58% of As, 14.39% of Zn, 12.79% of Pb, and 8.03% of Cd exceeded the corresponding soil risk screening values in these IMSs. In addition, 27.13% of the examined IMS had one or more SPTE pollution, mainly distributed in the southwest and south central China. On the examined IMSs, 81.91% had moderate or severe ecological risks, which were mainly caused by Cd, Hg, As, and Pb; 23.40% showed non-carcinogenic risk and 11.70% demonstrated carcinogenic risk. The primary exposure pathways of the former were ingestion and inhalation, while that for the latter was ingestion. A Monte Carlo simulation also confirmed the health risk assessment results. As, Cd, Hg, and Pb were identified as priority control SPTEs, and Hunan, Guangxi, Guangdong, Yunnan, and Guizhou were selected as the key control provinces. Our results provide valuable information for public health and soil environment management in China.

Decoupling environmental impact from economic growth to achieve Sustainable Development Goals in China.

Developing countries, such as China, have achieved unprecedented success in a single Sustainable Development Goal (SDG), which usually leads to trade-offs between the three pillars of sustainability, and even destroys sustainability. Quantifying the degrees of coupling among the pillars is essential to support policymakers' systematic actions to minimize trade-offs and maximize co-benefits between the pillars, and simultaneously achieve all SDGs. However, assessing the degrees of coupling among the pillars for the full SDGs is lacking. Here, we evaluate the progress of the pillars towards the SDGs and quantify the degrees of coupling among them at both national and sub-national levels in China from 2000 to 2015. The results indicate that the degrees of coupling among the pillars were almost constant while the degrees of coupling between the pillars and economic growth declined over time. The degrees of coupling between environmental impact and economic growth accounted for 52%-83% of the SDGs' progress. Reducing the degrees of coupling helps achieve simultaneously economic growth and environmental protection. The higher the degrees of coupling, the lower progress. This trend was universal among all provinces (sub-national level) regardless of their development levels. Our study highlights not only the necessity to track the degrees of coupling among the pillars, but also decoupling environmental impact from economic growth to achieve the SDGs.

A Novel Fault Diagnosis Scheme for Rolling Bearing Based on Convex Optimization in Synchroextracting Chirplet Transform.

Synchroextracting transform (SET) developed from synchrosqueezing transform (SST) is a novel time-frequency (TF) analysis method. Its concentrated TF spectrum is obtained by applying a synchroextracting operator into TF transformation co-efficients on the TF plane. For this class of post-processing TF analysis methods, the main research focuses on the accurate estimation of instantaneous frequency (IF). However, the performance of TF analysis is greatly affected by the strong frequency modulation (FM) signal. In particular, the actual measured mechanical vibration signals always contain strong background noise, which decreases the resolution of TF representation, resulting in an inaccurate ridge extraction. To solve this problem, an improved penalty function based on the convex optimization scheme is firstly introduced for signal denoising. Based on the superiority of the linear chirplet transform (LCT) in dealing with modulated signals, the synchroextracting chirplet transform (SECT) is employed to sharpen the TF representation after the convex optimization denoising operation. To verify the effectiveness of the proposed method, the numerical simulation signals and the measured fault signals of rolling bearing are carried out, respectively. The results demonstrate that the proposed method leads to a better solution in rolling bearing fault feature extraction.

Spatio-temporal variation and source changes of potentially toxic elements in soil on a typical plain of the Yangtze River Delta, China (2002-2012).

The spatio-temporal variation and temporal changes in the sources of Cr, Pb, Cd, Hg, and As in soil on the Hangzhou-Jiaxing-Huzhou (H-J-H) Plain were analysed based on 4,359 soil samples collected in 2002 and 2012. Geostatistical and spatial analysis methods were used to explore the spatio-temporal variation in the pollution levels and 'pollution hotspots' for potentially toxic elements (PTEs), and the positive matrix factor model was used to quantitatively appoint and analyse temporal changes in PTE sources. The results indicated that the PTE content in most parts of the survey area were at a safe level in both 2002 and 2012, but a clearly upward trend was detected for Cr, Pb, and Cd. Moreover the pollution index for Cr, Pb, Cd, and the Nemerow composite pollution index increased in the west but decreased in the east of the H-J-H Plain from 2002 to 2012. The pollution index for Hg and As presented the opposite spatial pattern. It is obvious that there have been changes in the spatial pattern of pollution hotspots for PTEs on the H-J-H Plain from 2002 to 2012. Four sources of PTEs in soil were quantitatively appointed. In 2002, 2012, the dominant sources of Cr, Cd, Hg, and As were soil parent materials, industrial activities, atmospheric deposition and agricultural inputs, respectively. The dominant source of Pb in the soil changed from traffic emissions to soil parent materials, indicating the benefit of banning the use of leaded gasoline in China. This study highlights the importance of monitoring soil environmental quality and highlights the significance of spatio-temporal variation in PTEs in suburban zones or transitional areas undergoing rapid industrialization and urbanization, like the H-J-H Plain.

Preliminary risk assessment of regional industrial enterprise sites based on big data.

An accurate and inexpensive preliminary risk assessment of industrial enterprise sites at a regional scale is critical for environmental management. In this study, we propose a novel framework for the preliminary risk assessment of industrial enterprise sites in the Yangtze River Delta, which is one of the fastest economic development and most prominent contaminated regions in China. Based on source-pathway-receptors, this framework integrated text and spatial analyses and machine learning, and its feasibility was validated with 8848 positive and negative samples with a calibration and validation set ratio of 8:2. The results indicated that the random forest performed well for risk assessment; and its accuracy, precision, recall, and F1 scores in the calibration set were all 1.0, and the four indicators for the validation set ranged from 0.97 to 0.98, which was better than that for the other models (e.g., logistic regression, support vector machine, and convolutional neural network). The preliminary risk ranking of industrial enterprise sites by the random forest showed that high risks (probabilities) were mainly distributed in Shanghai, southern Jiangsu, and northeastern Zhejiang from 2000 to 2015. The relative importance of the site industrial, production, and geographical features in the random forest was 69%, 22%, and 9%, respectively. Our study highlights that we could quickly and effectively establish a priority (or ranking) list of industrial enterprise sites that require further investigations, using the proposed framework, and identify potentially contaminated sites.

Identification and risk prediction of potentially contaminated sites in the Yangtze River Delta.

Identification and risk prediction of potentially contaminated sites (PCS) are crucial for the management of contaminated sites. However, the identification and risk prediction methods of PCS are lacking at a regional scale. Here, we established the fuzzy matching algorithm based on the site's name for identifying PCS in the Yangtze River Delta (YRD) from 2000 to 2020. The results showed that PCS in the YRD increased by over ten times, from 336 in 2000 to 4191 in 2020. Socio-economic and physical geography drive the growth of PCS and its spatiotemporal distribution, while the former has a more significant impact than the latter. We also presented a risk probability zoning strategy based on the source-pathway-receptor model, and proposed the patch-generating land-use simulation model to predict the risk probability of PCS in 2030. The results of risk probability zoning from 2000 to 2020 indicated that the local government of the YRD has started to pay attention to PCS management and risk control while developing social and economic. The results of risk prediction demonstrated that the proportion of low-risk probability pixels is 96.1% in 2030. Therefore, the planned indicator in the Action Plan on contaminated sites established by the State Council of China can be achieved in the YRD. Our experience in identifying and predicting PCS can inform how the local government worldwide manages PCS and tackles future challenges of achieving the ambition of site pollution control.

How the Air Clean Plan and carbon mitigation measures co-benefited China in PM2.5 reduction and health from 2014 to 2020.

China implemented a stringent Air Clean Plan (ACP) since 2013 to address environmental and health risks caused by ambient fine particulate matter (PM2.5). However, the policy effectiveness of ACP and co-benefits of carbon mitigation measures to environment and health are still largely unknown. Using satellite-based PM2.5 products produced in our previous study, concentration-response functions, and the logarithmic mean Divisia index (LMDI) method, we analyzed the spatiotemporal dynamics of premature deaths attributable to PM2.5 exposure, and quantitatively estimated the policy benefits of ACP and carbon mitigation measures. We found the annual PM2.5 concentrations in China decreased by 33.65 % (13.41 µg m-3) from 2014 to 2020, accompanied by a decrease in PM2.5-attributable premature deaths of 0.23 million (95 % confidence interval (CI): 0.22-0.27), indicating the huge benefits of China ACP for human health and environment. However, there were still 1.12 million (95 % CI: 0.79-1.56) premature deaths caused by the exposure of PM2.5 in mainland China in 2020. Among all ACP measures, clean production (contributed 55.98 % and 51.14 % to decrease in PM2.5 and premature deaths attributable to PM2.5) and energy consumption control (contributed 32.58 % and 29.54 % to decrease in PM2.5 and premature deaths attributable to PM2.5) made the largest contribution during the past seven years. Nevertheless, the environmental and health benefits of ACP are not fully synergistic in different regions, and the effectiveness of ACP measures reduced from 2018 to 2020. The co-effects of CO2 and PM2.5 has become one of the major drivers for PM2.5 and premature deaths reduction since 2018, confirming the clear environment and health co-benefits of carbon mitigation measures. Our study suggests, with the saturation of clean production and source control, more targeted region-specific strategies and synergistic air pollution-carbon mitigation measures are critical to achieving the WHO's Air Quality Guideline target and the UN's Sustainable Development Goal Target in China.

Current Status and Temporal Trend of Potentially Toxic Elements Pollution in Agricultural Soil in the Yangtze River Delta Region: A Meta-Analysis.

Potentially toxic elements (PTEs) pollution in the agricultural soil of China, especially in developed regions such as the Yangtze River Delta (YRD) in eastern China, has received increasing attention. However, there are few studies on the long-term assessment of soil pollution by PTEs over large regions. Therefore, in this study, a meta-analysis was conducted to evaluate the current state and temporal trend of PTEs pollution in the agricultural land of the Yangtze River Delta. Based on a review of 118 studies published between 1993 and 2020, the average concentrations of Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni were found to be 0.25 mg kg-1, 0.14 mg kg-1, 8.14 mg kg-1, 32.32 mg kg-1, 68.84 mg kg-1, 32.58 mg kg-1, 92.35 mg kg-1, and 29.30 mg kg-1, respectively. Among these elements, only Cd and Hg showed significant accumulation compared with their background values. The eastern Yangtze River Delta showed a relatively high ecological risk due to intensive industrial activities. The contents of Cd, Pb, and Zn in soil showed an increasing trend from 1993 to 2000 and then showed a decreasing trend. The results obtained from this study will provide guidance for the prevention and control of soil pollution in the Yangtze River Delta.

Experimental study and numerical simulation of the kinetic energy recovery of the mine's exhaust gas.

In mines, the exhaust gas is mainly discharged from main ventilators in free dissipation state. The effective recovery of its kinetic energy is lucrative from economical and technical standpoints. This study is focused on recovering the kinetic energy of the exhaust gas without deteriorating the main ventilator's safe operation or increasing power dissipation. The related experiments and numerical simulations were performed for the conical diffusers with diffusing angles of 16° and inlet diameters of 220 and 320 mm, respectively. By examining the start-up and operation states of the wind turbines using inlet collectors with conical, circular arc, and cone-arc shapes, it was found that the wind speed at the inlet of the drainage tube exceeded 4 and 20 m/s at the minimal and maximal distances from the wind turbine, respectively. The wind speed at the overflow tube outlet was no less than 1.8 m/s, proving a certain recovery of kinetic energy by the wind turbine. Thus, the critical distance between the diffuser and the inlet collector should be at least four times the diffuser's inlet diameter. Finally, the velocity, pressure, and flow fields in the vortex core regions of the kinetic recovery system with different types of inlet collectors were simulated with the FLUENT commercial software package. The simulation results revealed that the circular-arc collector outperformed other three tested configurations in kinetic energy recovery.Implications: This study is focused on recovering the kinetic energy of the exhaust gas without deteriorating the main ventilator's safe operation or increasing power dissipation. China is a country with coal as its main energy source, which releases over ten billion cubic meters of the exhaust gas annually. In addition to low-concentration methane, there is also the exhaust gas released at a velocity of about 20 m/s, which kinetic energy recovery would be very lucrative.The significance of this study is that the mine's main ventilator outlet was simplified as two conical diffusers with parameters α=16°/n=2 and α=16°/n=2.5, and the optimal critical distance between the diffuser and the collector was determined as 4Di, where Di was the diffuser's inlet diameter. Under that optimal condition, the system can achieve the maximum power without affecting the ventilator's normal operation. It is instructive to make full use of and manage the exhaust gas in mine that fits the journal on the purpose of air waste management.Finally, we provide a statement serious that the article is original and unpublished and is not being considered for publication elsewhere.

An integrated assessment methodology for management of potentially contaminated sites based on public data.

Ranking assessment of potentially contaminated sites (PCS) provides a great quantity of information (namely the risk screening list) that is usually examined by environmental managers, and therefore reduces the cost of risk management in terms of site investigation. Here we propose an integrated assessment methodology to establish a risk screening list of PCS in China using the Choquet integral correlation coefficient (ICC), which takes the uncertainty and interaction of PCS attributes into explicit account. The proposed method globally considers the importance and ordered positions of PCS attributes while reflecting their overall ranking. The model evaluation and actual validation results demonstrate the success in PCS ranking by the proposed method, which is superior to other methods such as the intuitionistic fuzzy multiple attribute decision-making, the technique for order preference by similarity to an ideal solution, and the weighted average. The resulting spatial distribution of Choquet ICC indicates that high-attention PCS in China are mainly located in Guangdong, Jiangsu, Zhejiang, and Shandong Provinces. This study is the first attempt to conduct a ranking assessment of PCS across China. The proposed assessment method based on Choquet ICC offers a step towards establishing a risk screening list of PCS globally.

[Evaluation of carrying capacity and spatial pattern matching on urban-rural construction land in the Poyang Lake urban agglomeration, China]. / çŽ¯é„±é˜³æ¹–åŸŽå¸‚ç¾¤åŸŽä¹¡å»ºè®¾ç”¨åœ°çš„æ‰¿è½½èƒ½åŠ›è¯„ä»·åŠç©ºé—´æ ¼å±€åŒ¹é .

Land carrying capacity is one of the important research fields for land management and sustainable use. Urban-rural construction land is an essential component of land use type, the rationality of whose structure and layout is crucial to the sustainable use of land. Here, we executed the evaluation of the suitability of urban-rural construction land development, accounted the bearable critical threshold of urban-rural construction land, calculated the bearable abundance of urban-rural construction land, and compared with the current urban-rural construction land, analyzed the matching of the space layout, and then obtained the remaining development intensity of each county (city or district) of the Poyang Lake urban agglomeration. The results showed that the most suitable, more suitable, less suitable and unsuitable area about the evaluation results of urban-rural construction land development suitability were 3130.62, 2477.29, 867.03 and 29509.14 km2, respectively. The bearable critical threshold of urban-rural construction land (developable strength) was 16.6%, and the value of each county (city, district) was 7.7%-100%. The abundance of urban-rural construction land in each county (city, district) was mainly 0.15-1.30. The remaining development intensity was 12.3%, and the spatial matching degree was 0.76. The remaining develo-pment intensity of each county (city, district) was 4.9%-53.5%, and the spatial matching degree of each county (city, district) was 0.11- 1.00, with a wide range. Our results would help to clarify the relationship between the current development status and the rational development status, which could provide a basis for the refined management of urban-rural construction land and the regulatory policies' formulation of spatial pattern optimization.

[Spatial and Temporal Variability of Soil C-to-N Ratio of Yugan County and Its Influencing Factors in the Past 30 Years].

The soil carbon-to-nitrogen (C/N) ratio of soils is a sensitive indicator of soil quality and an indicator for assessing the carbon and nitrogen nutrition balance of soils. Its variation is significant in reflecting the carbon and nitrogen cycling of soils. An accurate knowledge of how the C/N ratio varies spatially and temporally and the driving factors at county scale is of great significance to the extrapolation of balanced fertilization based on soil C/N ratio regulation as well as to the protection of the ecological environment. This study was based on 200 points of surface soil samples (0-20 cm) collected during the second National Soil Survey in 1982 and 423 points of surface soil samples (0-20 cm) collected during the soil test-based formulated fertilization project in 2012 in Yugan County. Combined with the soil parent material, soil type, farmland-use type, terrain factors, pH, straw incorporation pattern, and nitrogen fertilizer rate over the past 30 years, spatial and temporal variability characteristics of the soil C/N ratio were analyzed by using ordinary kriging methods, and the effects of the influencing factors were quantified by regression analysis. The results indicated that the mean value of the C/N ratio was 10.05 and 11.18 in 1982 and 2012, respectively. The coefficient of variation was 19.40% and 25.04%, respectively, which suggested the soil C/N ratio had moderate variability in the study area. The ratios of nugget to sill were 15.91% and 71.25% in 1982 and 2012, respectively. This means that the leading factor from the structural factors (parent material and soil type) into the stochastic factors (nitrogen fertilizer rate and straw incorporation pattern). In the past 30 years, most of the regional soil C/N ratio increased significantly especially the eastern region. The spatial variability of soil C/N in 1982 was mainly affected by soil parent material, soil type, terrain factor, and pH, with the degree of influence of each variable at 17.3%, 14.2%, 7.4%, and 2.3%. In 2012, the spatial variability was mainly affected by soil parent material, soil type, farmland-use type, terrain factor, straw incorporation pattern, and nitrogen fertilizer rate, with the degree of influence of each variable of 8.7%, 23.5% 28.2%, 12.2%, 12.6%, and 42.3%, respectively. To maintain the steady growth of the soil C/N ratio, it is suggested that the return of carbon be incorporated with the input of nitrogen, such as incorporating crop residues into the soil and inputting more organic fertilizers into the soil in future farming practices.

Spatio-temporal distribution of soil nitrogen in Poyang lake ecological economic zone (South-China).

Revealing the spatio-temporal distribution of soil nitrogen (N) contributes to N management and prevention of N pollution. The objective of this work is to study the spatio-temporal distribution of soil N and their driving factors in the topsoil (0-20 cm) of farmland in Yugan county, China in 1982 and 2012. Data were collected from 200 sampling sites of the second national soil survey in Yugan in 1982 and 423 sampling sites of the soil testing and formula fertilization project in 2012. On average total N (TN) and available N (AN) significantly increased from 1.50 g kg-1 and 153.04 mg kg-1 in 1982 to 1.58 g kg-1 and 179.75 mg kg-1 in 2012, respectively. The distance of spatial autocorrelation for TN increased from 2.79 to 6.18 km and from 2.97 to 18.00 km for AN from 1982 to 2012. The nugget/sill ratio for TN (0.472 in 1982 and 0.581 in 2012) indicated that soil TN driving by natural characteristics in 1982 to human activities in 2012. The nugget/sill ratio for soil AN (0.471 in 1982 and 0.688 in 2012) indicated that soil AN is more influenced by human activities. The major factors driving the spatio-temporal distribution of soil N was N application rate. To promote the sustainable development of agriculture and eco-environment, we should improve the awareness of farmers on chemical fertilizers (particularly N) and the level of N fertilizer management, increase the use of manure and organic fertilizer and facilitate rational fertilization by farmers.

[Spatial Variability of C-to-N Ratio of Farmland Soil in Jiangxi Province].

Spatial variability of soil carbon-to-nitrogen ratio (C/N) at the provincial scale was analyzed using ordinary kriging methods. The effects of the factors influencing C/N were quantified by regression analysis based on 16,582 points of surface soil samples (0-20 cm) collected during the project of soil-test-based formulated fertilization in Jiangxi Province in 2012. The results showed that soil C/N ranged from 2.98 to 52.67, with an average of 11.72. The coefficient of variation was 25.17%, suggesting moderate variability. The nugget-to-sill ratio was 88.44%, meaning that the stochastic factors played a more important role in the spatial variability of soil C/N between the structural and stochastic factors. The spatial distribution of soil C/N was relatively smooth and the high-value areas were mainly distributed in Pengze County-Jiujiang City, Shangli County-Pingxiang City, and Lean County-Fuzhou City. The terrain factors, farmland-use type, parent material, soil type, and the level of nitrogen fertilizer had significant impacts on the spatial variability of soil C/N (P<0.05), but the degree of influence was different for each factor. Soil C/N indicated a significant positive Pearson's correlation with elevation and the slope of slope (P<0.05). The terrain factors explained 0.3% of the spatial variability of soil C/N and the farmland-use could explain 1.4%. The explanatory power of soil groups, subgroups, and soil family were 2.7%, 3.6%, and 5.5% respectively. The level of nitrogen fertilizer could explain 33.4% of the spatial variability of soil C/N, which showed that the amount of nitrogen fertilizer was the main factor that controls the spatial distribution of soil C/N.