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

Localized regional environmental risk in mountainous urban areas of Southwest China: identification, assessment, and management strategies in Kunming

In recent decades, the escalating frequency of environmental risk events, arising from sources such as industrial accidents, chemical spills, or other anthropogenic activities, has intensified threats to the ecological environment. The targeted identification of high-risk areas, formulation of control lists for key risk sources within regions, and the implementation of differentiated management strategies remain significant challenges. This study employed an administrative region environmental risk assessment and gridded environmental risk analysis method to comprehensively evaluate the environmental risks in the city of Kunming, China. The results indicated a fourfold increase in the number of environmental risk sources from 2012 to 2022. The sources were found to be widely distributed across the entire region but exhibited localized clustering. The environmental risk receptors were primarily concentrated around a local lake, in densely populated counties, and near rivers and drinking water sources. Risk hotspot areas within the target region were identified using the gridded environmental risk analysis method. A list of 29 key control areas was proposed, including nine industrial parks and 20 streets. Measures were proposed for handling unexpected incidents. The findings provide data useful for policy formulation and environmental management in similar regions of mountainous cities.

Identifying the pollution risk pattern from industrial production to rural settlements and its countermeasures in China

Impacted by large-scale and rapid rural industrialization in the past few decades, China's rural settlements are confronted with the risk of heavy metal pollution stemming from industrial production, which might pose a significant threat to the rural habitat and the well-beings. This study devised a relative risk model for industrial heavy metal pollution to the rural settlements based on the source-pathway-receptor risk theory. Using this model, we assessed the risk magnitudes of heavy metal pollution from industrial production at a 10 km × 10 km grid scale and identified the characteristics of the risk pattern in China. Our finding reveals: (1) the relative risk values of wastewater, waste gas and total heavy metal pollution are notably concentrated within a confined spectrum, with only a small number of units are characterized by high-risk level; (2) Approximately 21.57 % of China's rural settlements contend with heavy metal pollution, with 4.17 %, 9.84 % and 7.55 % being subjected to high, medium and low risks, respectively; (3) The high-risk units mainly is concentrated in the developed areas such as Yangtze River Delta, Pearl River Delta, and the Beijing-Tianjin metropolitan area, also dispersed in the plain areas with high rural population density. Guided by these insights, this study puts forth regionally tailored prevention and control strategies, as well as distinct process prevention and control strategies.

Can we redevelop ammonia nitrogen contaminated sites without remediation? The key role of subsurface pH in human health risk assessment

Nitrogen fertilizer supports global food production, but its manufacturing results in substantial ammonia nitrogen (AN) contaminated sites which remain largely unexplored. In this study, ten representative AN contaminated sites were investigated, covering a wide range of subsurface pH, temperature, and AN concentration. A total of 7232 soil samples and 392 groundwater samples were collected to determine the concentration levels, migration patterns, and accurate health risks of AN. The results indicated that AN concentrations in soil and groundwater reached 12700 mg/kg and 12600 mg/L, respectively. AN concentrations were higher in production areas than in non-production areas, and tended to migrate downward from surface to deeper soil. Conventional risk assessment based on AN concentration identified seven out of the ten sites presenting unacceptable risks, with remediation costs and CO2 emissions amounting to $1.67 million and 17553.7 tons, respectively. A novel risk assessment model was developed, which calculated risks based on multiplying AN concentration by a coefficient fNH3 (the ratio of NH3 to AN concentration). The mean fNH3 values, primarily affected by subsurface pH, varied between 0.02 and 0.25 across the ten sites. This new model suggested all investigated sites posed acceptable health risks related to AN exposure, leading to their redevelopment without AN-specific remediation. This research offers a thorough insight into AN contaminated site, holds great realistic significance in alleviating global economic and climate pressures, and highlights the need for future research on refined health risk assessments for more contaminants.

Indirect Estimation of Heavy Metal Contamination in Rice Soil Using Spectral Techniques

The rapid growth of industrialization and urbanization in China has led to an increase in soil heavy metal pollution, which poses a serious threat to ecosystem safety and human health. The advancement of spectral technology offers a way to rapidly and non-destructively monitor soil heavy metal content. In order to explore the potential of rice leaf spectra to indirectly estimate soil heavy metal content. We collected farmland soil samples and measured rice leaf spectra in Xushe Town, Yixing City, Jiangsu Province, China. In the laboratory, the heavy metals Cd and As were determined. In order to establish an estimation model between the pre-processed spectra and the soil heavy metals Cd and As content, a genetic algorithm (GA) was used to optimise the partial least squares regression (PLSR). The model's accuracy was evaluated and the best estimation model was obtained. The results showed that spectral pre-processing techniques can extract hidden information from the spectra. The first-order derivative of absorbance was more effective in extracting spectral sensitive information from rice leaf spectra. The GA-PLSR model selects only about 10% of the bands and has better accuracy in spectral modeling than the PLSR model. The spectral reflectance of rice leaves has the capacity to estimate Cd content in the soil (relative percent difference [RPD] = 2.09) and a good capacity to estimate As content in the soil (RPD = 2.97). Therefore, the content of the heavy metals Cd and As in the soil can be estimated indirectly from the spectral data of rice leaves. This study provides a reference for future remote sensing monitoring of soil heavy metal pollution in farmland that is quantitative, dynamic, and non-destructive over a large area.

Spatiotemporal assessment and scenario simulation of the risk potential of industrial sites at the regional scale

Spatiotemporal risk and future evolutionary distribution characteristics of industrial sites are crucial for regional environmental supervision. However, traditional site survey methods have long cycles, high costs, and small coverage and usually only consider the static risk of a single industrial site to a single receptor. Low-cost, large-scale, and long-term multi-source data can compensate for the shortcomings of traditional site surveys. Previous studies have rarely considered the spatiotemporal heterogeneity of industrial sites and assessed their dynamic risks at the regional scale. This study used China's Yangtze River Delta Urban Agglomeration as the study area. We assessed the risk potential of industrial sites from 2000 to 2020 using multi-source and multiperiod data. We also simulated the risk potential for 2030 and 2050 using a patch-generating land use simulation (PLUS) model under different scenarios. The results indicated that the proportion of medium- and high-risk potential grids from 2000 to 2020 ranged from 2.53 % to 5.61 % in the study area, with the vast majority of areas (94.39 %-97.47 %) having low- or no-risk potential. The PLUS model exhibited remarkable reliability from 2005 to 2020, with the overall accuracy, Kappa coefficient, and Moran's index ranging from 83 % to 89 %, 0.38 to 0.59, and 0.34 to 0.56, respectively. The future prediction results indicated that the number of high-risk potential grids (>5 %) showed an upward trend under natural development scenarios in 2030 and 2050 and a downward trend under the ten-chapter soil pollution action plan or strict control scenarios. This study provides vital information for addressing the challenges of industrial site management and environmental risks in similar regions.

Impact of ecological conservation policies on land use and carbon stock in megacities at different stages of development

Urban expansion, especially the construction of megacities, increases carbon emissions and adversely affects the carbon storage of terrestrial ecosystems. However, scientific land-use management policies can increase carbon storage. This study takes two megacities at different stages of development, Beijing and Tianjin, as examples to explore the impact of different ecological conservation scenarios on both urban land use and carbon storage to provide recommendations for the construction planning of large cities with low-carbon development as the goal. Furthermore, we coupled the patch-generating land use simulation (PLUS) model with the integrated valuation of ecosystem services and tradeoffs (InVEST) model to simulate land use and carbon storage under a natural development scenario, a planned ecological protection scenario (PEPS), and a policy-based ecological restoration scenario (PERS). From 2000 to 2020, both cities had different degrees of construction land expansion and carbon loss, and Tianjin's dynamic degree of construction land was 0.94% higher than Beijing's, with a carbon loss 183,536.19 Mg higher than Beijing's; this trend of reducing carbon reserves will continue under the natural development scenario (NDS). Under the PEPS and PERS, the carbon stock of both cities increases, and the impact on Tianjin is greater, with an increase of 4.51% and 8.04%, respectively. Under PERS, the carbon stock increases the most, but the dynamic degree of construction land use is negative for both cities. Beijing's carbon stock is 0.40% lower than Tianjin's, which deviates slightly from the trend of urban economic development. Megacities in the rapid development stage can refer to Tianjin, strictly following the ecological protection land planning scope and vigorously implementing ecological restoration policies to effectively increase regional carbon stock. Megacities in the mature stage of development can refer to Beijing, and flexibly implement ecological restoration policies to increase regional carbon stock without affecting the city's economic development.

Food-water-land-ecosystem nexus in typical Chinese dryland under different future scenarios

Healthy coupling of the food-water-land-ecosystem (FWLE) nexus is the basis for achieving sustainable development (SD), and FWLE in drylands is frontier scientific issues in the study of coupled human land systems. To comprehensively safeguard the future food, water, and ecological security of drylands, this study examined the implications for FWLE linkages in a typical Chinese dryland from the perspective of future land-use change. First, four different land-use scenarios were proposed using a land-use simulation model with a gray multi-objective algorithm, including an SD scenario. Then, the variation of three ecosystem services was explored: water yield, food production, and habitat quality. Finally, redundancy analysis was used to derive the future drivers of FWLE and explore their causes. The following results were obtained. In the future in Xinjiang, under the business as usual scenario, urbanization will continue, forest area will decrease, and water production will decline by 371 million m³. In contrast, in the SD scenario, this negative impact will be substantially offset, water scarcity will be alleviated, and food production will increase by 1.05 million tons. In terms of drivers, the anthropogenic drivers will moderate the future urbanization of Xinjiang to some extent, with natural drivers dominating the sustainable development scenario by 2030 and a potential 22 % increase in the drivers of precipitation. This study shows how spatial optimization can help protect the sustainability of the FWLE nexus in drylands and simultaneously provides clear policy recommendations for regional development.

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.

Simulation of land use trends and assessment of scale effects on ecosystem service values in the Huaihe River basin, China

Land use demand change in the Huaihe River basin (HRB) and ecosystem service values (ESVs) in watersheds are important for the sustainable development and use of land resources. This paper takes the HRB as the research object, and using remote sensing images of land use as the data source adopts the comprehensive evaluation analysis method of ESVs based on equivalent factors and sensitivity analysis of the performance characteristics of ESV changes of different land use types. The PLUS model is used to predict spatiotemporal land use change characteristics to 2030 combining inertial development, ecological development, and cultivated land development. The spatial distribution and aggregation of ESVs at each scale were also explored by analyzing ESVs at municipal, county, and grid scales. Considering also hotspots, the contribution of land use conversion to ESVs was quantified. The results showed that (1) from 2000 to 2020, cultivated land decreased sharply to 28,344.6875 km², while construction land increased sharply to 26,914.563 km², and the change of other land types was small. (2) The ESVs in the HRB were 222,019 × 10¹² CNY in 2000, 235,015 × 10¹² CNY in 2005, 234,419 × 10¹² CNY in 2010, 229,885 × 10¹² CNY in 2015, and 224,759 × 10¹² CNY in 2020, with an overall fluctuation, first increasing and then decreasing. (3) The ESVs were 219,977 × 10¹² CNY, 218,098 × 10¹² CNY, 219,757 × 10¹² CNY, and 213,985 × 10¹² CNY under the four simulation scenarios of inertial development, ecological development, cultivated land development, and urban development, respectively. At different scales, the high-value areas decreased, and the low-value areas increased. (4) The hot and cold spots of ESV values were relatively clustered, with the former mainly clustered in the southeast region and the latter mainly clustered in the northwest region. The sensitivity of ecological value was lower than 1, while the ESV was inelastic to the ecological coefficient, and the results were plausible. The mutual conversion of cultivated land to water contributed the most to ESVs. Based on the multi-scenario simulation of land use in the HRB by the PLUS model, we identified the spatial distribution characteristics of ESVs at different scales, which can provide a scientific basis and multiple perspectives for the optimization of land use structure and socio-economic development decisions.

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.

Spatio-Temporal Dynamic of the Land Use/Cover Change and Scenario Simulation in the Southeast Coastal Shelterbelt System Construction Project Region of China

The National Coastal Shelterbelt System Construction Project (NCSSCP) was proposed to increase the afforestation area and neutralize the impact of urbanization, especially in the southeast coastal sub-region of China. In this study, we identified the spatio-temporal evolution characteristics and predicted the land use and land cover changes (LUCC) associated with this project by modeling scenarios, seeking to explore the path of sustainable development. The spatial structure was analyzed using the landscape pattern index approach and the land use transfer matrix. By coupling the Markov model and patch-generating a land-use simulation model (PLUS), different scenarios were analyzed to predict the quantity and spatial changes. According to the results, based on the current trends and due to the impact of urbanization, the forest area was predicted to decrease by 633.19 km2, whilst appearing more spatially fragmented and separated. However, with the completion of the NCSSCP target, the forest area was predicted to increase by 1666.12 km2, and the spatial structure would appear more cohesive and concentrated. From an overall perspective, the afforestation target of NCSSCP will not be completed under the present trend. It is difficult for the afforestation speed of the NCSSCP to keep up with the speed of urbanization. Therefore, giving consideration to both the afforestation speed and quality and reducing the speed of urbanization to balance the economy and ecology would be beneficial in terms of the realization of the aims of sustainable development.

Landscape Evolution and Simulation of Rural Settlements around Wetland Park Based on MCCA Model and Landscape Theory: A Case Study of Chaohu Peninsula, China

As a transitional zone between urban and rural areas, the peri-urban areas are the areas with the most intense urban expansion and the most frequent spatial reconfiguration, and in this context, it is particularly important to reveal the evolution pattern of rural settlements in the peri-urban areas to provide reference for the rearrangement of rural settlements. The study takes five townships in the urban suburbs, and explores the scale, shape, spatial layout, and spatial characteristics of the urban suburbs of Hefei from 1980 to 2030 under the influence of urban-lake symbiosis based on spatial mathematical analysis and geographical simulation software. The study shows that: (1) the overall layout of rural settlements in the study area is randomly distributed due to the hilly terrain, but in small areas there is a high and low clustering phenomenon, and the spatial density shows the distribution characteristics of “high in the east and low in the west”; (2) since the reform and opening up, there are large spatial differences in the scale of rural settlements in the study area. (3) Different development scenarios have a strong impact on the future spatial pattern of rural settlement land use within the study area, which is a strong reflection of policy.