Regional risk assessment approaches to land planning for industrial polluted areas in China: the Hulunbeier region case study

Grid-Scale Regional Risk Assessment of Potentially Toxic Metals Using Multi-Source Data

Understanding the risks posed by potentially toxic metals (PTMs) in large regions is important for environmental management. However, regional risk assessment that relies on traditional field sampling or administrative statistical data is labor-intensive, time-consuming, and coarse. Internet data, remote sensing data, and multi-source data, have the advantage of high speed of collection, and can, thereby, overcome time lag challenges and traditional evaluation inefficiencies, although, to date, they are rarely applied. To evaluate their effectiveness, the current study used multi-source data to conduct a 1 km scale assessment of PTMs in Yunnan Province, China. In addition, a novel model to simulate potentially hazardous areas, based on atmospheric deposition, was also proposed. Assessments reveal that risk areas are mainly distributed in the east, which is consistent with the distribution of mineral resources in the province. Approximately 3.6% of the cropland and 1.4% of the sensitive population are threatened. The risk areas were verified against those reported by the government and the existing literature. The verification exercise confirmed the reliability of multi-source data, which are cost-effective, efficient, and generalizable for assessing pollution risks in large areas, particularly when there is little to no site-specific contamination information.

Land-Use Change and Health Risks in the Process of Urbanization: A Spatiotemporal Interpretation of a Typical Case in Changzhou, China

China has undergone rapid urban expansion in recent decades. At the same time, environmental pollution and its risk to public health have increased. However, the relationship between urban land-use changes and health is ambiguous and insufficiently understood. Based on a typical city-scale case—namely, Changzhou, China—this research aimed to interpret the evolution of health risks alongside land-use change during the process of urbanization. We gathered data from multiple sources, including population mortality data, socioeconomic data, remote-sensing images, data for the points of interest of enterprises, and relevant information on environmental health events and cancers. The results showed that Changzhou’s urbanization was typical insofar as it was characterized by massive growth in industry, a rapid increase in the urban population, and urban land expansion. Health risks related to environmental pollution increased considerably with urban land expansion over time, and they increased with proximity to the pollution. The results from a generalized linear model confirmed that Changzhou’s urbanization triggered increasing health risks. Our study interpreted the relationship between urban land expansion and health risks from a spatiotemporal perspective. It can be used as a reference for urban planning and policymaking with regard to urban environmental health.

Early Warning of Internal Leakage in Heat Exchanger Network Based on Dynamic Mechanism Model and Long Short-Term Memory Method

In the process of butadiene rubber production, internal leakage occurs in heat exchangers due to excessive pressure difference. It leads to the considerable flow of organic matters into the circulating water system. Since these organic matters are volatile and prone to explode in the cold water tower, internal leakage is potentially dangerous for the enterprise. To prevent this phenomenon, a novel intelligent early warning and risk assessment method (DYN-EW-QRA) is proposed in this paper by combining dynamic simulations (DYN), long short-term memory (LSTM), and quantitative risk assessment (QRA). First, an original internal leakage mechanism model of a heat exchanger network is designed and simulated by DYN to obtain datasets. Second, the potential relationships between variables that have a direct impact on the hazards of the accident are deeply learned by LSTM to predict the internal leakage trends. Finally, the QRA method is used to analyze the range and destructive power of potential hazards. The results show that DYN-EW-QRA method has excellent performance.

Remediation of organophosphorus pesticide polluted soil using persulfate oxidation activated by microwave

Contaminated sites from pesticide industry have attracted global concern due to the characteristics of organic pollution with high concentrations and complete loss of habitat conditions. Remediation of organophosphorus pesticide polluted soil using microwave-activated persulfate (MW/PS) oxidation was investigated in this study, with parathion as the representative pesticide. Approximately 90 % of parathion was degraded after 90 min of MW/PS oxidation treatment, which was superior to those by single PS or MW treatment. Relatively greater performances for parathion degradation were obtained in a relatively larger PS dosage, higher microwave temperature, and lower organic matter content. Appropriate soil moisture favored parathion degradation in soil. SO₄^-, OH, O₂^-, and ¹O₂ generated in the MW/PS system all contributed to parathion degradation. Multiple spectroscopy analyses indicated that PO and PS bonds in parathion were destroyed after MW/PS oxidation, accompanied by generation of hydroxylated and carbonylated byproducts. The soil safety after parathion degradation was assessed via model prediction. Furthermore, MW/PS oxidation also exhibited great performance for degradation of other organophosphorus pesticides, including ethion, phorate, and terbufos.

Copula-based exposure risk dynamic simulation of dual heavy metal mixed pollution accidents at the watershed scale

Most heavy metal exposure and pollution results from multiple industrial activities, including metal processing in refineries, and microelectronics. These issues pose a great threat to human health, ecological balance, and even societal stability. During 2012-2017, China, in particular, faced the challenge of 23 heavy metals accidents, six of which were extraordinarily serious accidents. Accidental environmental pollution is rarely caused by a single heavy metal, but rather by heavy metal mixtures. To address the need for a joint exposure risk assessment for heavy metal mixed pollution accidents at the watershed scale, a Copula-based exposure risk dynamic simulation model was proposed. A coupled hydrodynamic and accidental heavy metal exposure model is constructed for an hourly simulation of the exposure fate of heavy metals from each risk source once accidental leakage has occurred. The Copula analysis was introduced to calculate the dual heavy metal joint exposure probability in real time. This method was applied to an acute Cr⁶⁺-Hg²⁺ joint exposure risk assessment for 43 electroplating plants in nine sub-watersheds within the Dongjiang River downstream basin. The results indicated seven risk sources (i.e., S1, S4, H18, H23, H27-H28, and H34) that presented relatively high exposure risk to their surrounding sub-watersheds. Spatially, the acute exposure risk level was highest in the tributary basin (sub-watershed XW) than in the mainstream (sub-watershed DW2) and the river network (sub-watershed RW) of the lower reaches of the Dongjiang River. This research highlights an effective probabilistic approach for performing a joint exposure risk analysis of heavy metal mixed pollution accidents at the watershed scale.

Establishment of an integrated decision-making method for planning the ecological restoration of terrestrial ecosystems

Ecological restoration of terrestrial ecosystems facilitates environmental protection and enhances sustainable development of land resources. With increasingly severe land degradation, new and effective methods must be developed for the restoration of ecological functions. In this study, we developed a regional risk assessment approach to support the planning of ecological restoration of a terrestrial ecosystem located in the Daye area in central China. The study area was divided into six sub-regions where ecological risks were characterized by building a non-linear model to represent ecological interactions among the risk components there. Socio-economic conditions in the areas were evaluated and presented using an analytic hierarchy process. Assessment of different stakeholders there was conducted based on multiple-criteria decision analysis. Then, integrated assessment was performed using the technique of order preference for an ideal solution. We divided the degraded land in Daye into areas with different priorities for restoration or rectification and presented corresponding sequential time intervals for the action. The results are as follows: (i) the top priority rectification areas (totaling 358 km²) are mainly distributed in northeast and northwest regions; (ii) the high priority rectification areas are concentrated in the central region spanning 226 km²; (iii) the medium priority rectification areas comprised a large amount of arable and forest land spanning 605 km²; and (iv) the low priority rectification areas cover the rest part of the Daye area spanning 195 km². The assessment tool was proven to be useful in planning regional ecological restoration in terrestrial ecosystems.

Identification of Priority Areas for Soil and Water Conservation Planning Based on Multi-Criteria Decision Analysis Using Choquet Integral

Soil erosion risk assessment is an essential foundation for the planning and implementation of soil and water conservation projects. The commonality among existing studies is that they considered different indicators (e.g., rainfall and slope) in order to determine the soil erosion risk; however, the majority of studies in China neglect one important indicator, namely the slope aspect. It is widely accepted that the vegetation and distribution of rainfall differs according to the different slope aspects (such as sunny slope and shady slope) and these attributes will accordingly influence the soil erosion. Thus, existing studies neglecting this indicator cannot reflect the soil erosion well. To address this problem, a flexible soil erosion risk assessment method that supports decision makers in identifying priority areas in soil and water conservation planning was developed in the present study. Firstly, in order to verify the impact of the slope aspect on soil erosion, field investigations were conducted, and its impact on the characteristics of the community in the study area was analyzed. Secondly, six assessment indicators were selected, including slope gradient, precipitation, NDVI, land use, soil texture and slope aspect. Next, a developed multi-criteria decision analysis (MCDA) method based on the Choquet integral was adopted to assess the soil erosion risk. The MCDA method, combining objective data with subjective assessment based on Choquet integral, could solve the weight problem encountered when using the quantitative method. The parameters required can be modified according to the soil erosion types, assessment scales, and data availability. The synergistic and inhibitory effects among the soil erosion parameters were also considered in the assessment. Finally, the soil erosion risk results in the Xinshui River watershed revealed that more attention should be paid to the slope of farmland and grassland during the planning and management of soil and water conservation projects. The methodology used in the current study can support decision makers in planning and implementing soil and water conservation measures in regions with different erosion types.

Using decision methods to examine the potential impact of intersectoral action programs

Objectives

In public health today, there is a widespread call for intersectoral action (ISA) programs, in which two or more sectors cooperate to address a problem. This trend raises a question of how to appropriately assess the effectiveness and cost-effectiveness of ISA programs. To assess the impact of ISA, evaluation methods should provide a framework for simultaneously considering the impact of two or more interventions when selecting from a portfolio of programs. There is a gap in literature on such methods. In this research note, from a narrative review, we report and describe methods that could be useful for evaluating ISA programs. Subsequently, we present a hypothetical case study to demonstrate the use of these methods.

Results

We identified four methods that have potential to assess the joint impact of multiple interventions: economic evaluation, portfolio analysis, multiple-criteria decision analysis, and programme budgeting and marginal analysis. To keep pace with the desire to use strong evidence to inform the selection and design of ISA programs, methods must evolve to support these initiatives. This research note seeks to begin a dialogue on existing decision methods which may be used to assist decision makers with funding and resource allocation decisions of ISA programs.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3609-x) contains supplementary material, which is available to authorized users.

Development of relative risk model for regional groundwater risk assessment: a case study in the lower Liaohe River Plain, China

Increasing pressure on water supply worldwide, especially in arid areas, has resulted in groundwater overexploitation and contamination, and subsequent deterioration of the groundwater quality and threats to public health. Environmental risk assessment of regional groundwater is an important tool for groundwater protection. This study presents a new approach for assessing the environmental risk assessment of regional groundwater. It was carried out with a relative risk model (RRM) coupled with a series of indices, such as a groundwater vulnerability index, which includes receptor analysis, risk source analysis, risk exposure and hazard analysis, risk characterization, and management of groundwater. The risk map is a product of the probability of environmental contamination and impact. The reliability of the RRM was verified using Monte Carlo analysis. This approach was applied to the lower Liaohe River Plain (LLRP), northeastern China, which covers 23604 km². A spatial analysis tool within GIS which was used to interpolate and manipulate the data to develop environmental risk maps of regional groundwater, divided the level of risk from high to low into five ranks (V, IV, III, II, I). The results indicate that areas of relative risk rank (RRR) V cover 2324 km², covering 9.8% of the area; RRR IV covers 3986 km², accounting for 16.9% of the area. It is a new and appropriate method for regional groundwater resource management and land use planning, and is a rapid and effective tool for improving strategic decision making to protect groundwater and reduce environmental risk.