International Journal of Environmental Research and Public Health

Research

17 pages, 3683 KiB

Open AccessArticle

A System Dynamics Model for Ecological Environmental Management in Coal Mining Areas in China

by Fulei Shi, Haiqing Cao, Chuansheng Wang and Cuiyou Yao

Int. J. Environ. Res. Public Health 2020, 17(6), 2115; https://doi.org/10.3390/ijerph17062115 - 23 Mar 2020

Cited by 3 | Viewed by 5952

In recent years, mounting attention has been paid to ecological environmental management in coal mining areas in China. This paper conducts a system dynamics (SD) model for ecological environmental management in coal mining areas. Firstly, the whole causal loop diagram of the system [...] Read more.

In recent years, mounting attention has been paid to ecological environmental management in coal mining areas in China. This paper conducts a system dynamics (SD) model for ecological environmental management in coal mining areas. Firstly, the whole causal loop diagram of the system is built to illustrate the general system. Secondly, five subsystems are presented according to the causal loop diagram. Then, given the stable investment for ecological environmental management in coal mining areas, our objective is to find a better allocation that can get the best ecological environmental quality in coal mining areas. Notably, we present six allocations of the investment for ecological environmental management in coal mining areas. The results show that, in allocation 4, we can get the best ecological environmental quality in coal mining areas. That is, the best improvement of mining environment can be achieved by distributing the treatment cost highly on the proportion of investment in green vegetation. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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28 pages, 10134 KiB

Open AccessArticle

Presentation and Verification of an Optimal Operating Scheme Aiming at Reducing the Ground Vibration Induced by High Dam Flood Discharge

by Jijian Lian, Lin Chen, Chao Liang and Fang Liu

Int. J. Environ. Res. Public Health 2020, 17(1), 377; https://doi.org/10.3390/ijerph17010377 - 6 Jan 2020

Cited by 7 | Viewed by 4054

Abstract

Ground and environmental vibrations induced by high dam flood discharge from the Xiangjiaba hydropower station (XHS) has significant adverse effects on nearby building safety and the physical and mental health of surrounding residents. As an effective approach to simulate the flow-induced vibration of [...] Read more.

Ground and environmental vibrations induced by high dam flood discharge from the Xiangjiaba hydropower station (XHS) has significant adverse effects on nearby building safety and the physical and mental health of surrounding residents. As an effective approach to simulate the flow-induced vibration of hydraulic structures, the hydro-elastic experiment approach has been extensively applied and researched by Chinese scholars, but the relevant systematic research is rarely reported in international journals. Firstly, the hydraulic and structural dynamic similarity conditions that should be satisfied by the hydro-elastic model are briefly reviewed and derived. A hydro-elastic model of the XHS was further constructed using self-developed high-density rubber, and the vibration isolation system (including open trenches and flexible connects) was applied to avoid the external disturbances of pump operation, vehicle vibration and other experiments in the laboratory. Based on the data of model and prototype dynamic tests, a back propagation (BP) neural network was established to map the acceleration of the physical model to the ground in the prototype. In order to reduce the ground vibration, experiments were carried out to meticulously evaluate the ground vibration intensity under more than 600 working conditions, and the optimal operation scheme under different discharge volumes is presented here in detail. According to the prototype test data in 2013, 2014, and 2015, ground vibrations were significantly reduced by applying the presented optimal operation principle which indicates that the presented hydro-elastic approach and the vibration attenuation operation scheme were effective and feasible. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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25 pages, 7633 KiB

Open AccessArticle

Application of Spatiotemporal Hybrid Model of Deformation in Safety Monitoring of High Arch Dams: A Case Study

by Chongshi Gu, Xiao Fu, Chenfei Shao, Zhongwen Shi and Huaizhi Su

Int. J. Environ. Res. Public Health 2020, 17(1), 319; https://doi.org/10.3390/ijerph17010319 - 2 Jan 2020

Cited by 33 | Viewed by 3243

Abstract

As an important feature, deformation analysis is of great significance to ensure the safety and stability of arch dam operation. In this paper, Jinping-I arch dam with a height of 305 m, which is the highest dam in the world, is taken as [...] Read more.

As an important feature, deformation analysis is of great significance to ensure the safety and stability of arch dam operation. In this paper, Jinping-I arch dam with a height of 305 m, which is the highest dam in the world, is taken as the research object. The deformation data representation method is analyzed, and the processing method of deformation spatiotemporal data is discussed. A deformation hybrid model is established, in which the hydraulic component is calculated by the finite element method, and other components are still calculated by the statistical model method. Since the relationship among the measuring points is not taken into account and the overall situation cannot be fully reflected in the hybrid model, a spatiotemporal hybrid model is proposed. The measured values and coordinates of all the typical points with pendulums of the arch dam are included in one spatiotemporal hybrid model, which is feasible, convenient, and accurate. The model can predict the deformation of any position on the arch dam. This is of great significance for real-time monitoring of deformation and stability of Jinping-I arch dam and ensuring its operation safety. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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22 pages, 3542 KiB

Open AccessArticle

Spatial-Temporal Variability of Soil Organic Matter in Urban Fringe over 30 Years: A Case Study in Northeast China

by Hongbin Liu, Shunting Li and Yuepeng Zhou

Int. J. Environ. Res. Public Health 2020, 17(1), 292; https://doi.org/10.3390/ijerph17010292 - 31 Dec 2019

Cited by 5 | Viewed by 3050

Abstract

The study on soil organic matter (SOM) is of great importance to regional cultivated land use and protection. Based on data collected via continuous and high-density soil samples (0–20 cm) and socio-economic data collected from household survey and local bureau of statistics, this [...] Read more.

The study on soil organic matter (SOM) is of great importance to regional cultivated land use and protection. Based on data collected via continuous and high-density soil samples (0–20 cm) and socio-economic data collected from household survey and local bureau of statistics, this study employs geostatistics and economic statistical methods to investigate the spatial-temporal variation of SOM contents during 1980–2010 in the urban fringe of Sujiatun district in Shenyang City, China. We find that: (1) as to temporal variation, SOM contents in the study sites decreased from 30.88 g/kg in 1980 to 22.63 g/kg in 2000. It further declined to 20.07 g/kg in 2010; (2) in terms of spatial variation, the closer to city center, the more decline of SOM contents. Contrarily, SOM contents could even rise in outer suburb area; and (3) SOM content variation may be closely related to human factors such as farmers’ land use target and behaviour including inputs of chemical and organic fertilizers, types of crops and etc. These findings are conductive to grasp the overall trend of SOM variation and the influence of farmers’ land use behaviour on it. Furthermore, they could provide support for policymakers to agricultural planning and land use monitoring, which consequently aids the improvement of soil quality and food production in the urban fringe areas. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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23 pages, 6688 KiB

Open AccessArticle

An Azure ACES Early Warning System for Air Quality Index Deteriorating

by Dong-Her Shih, Ting-Wei Wu, Wen-Xuan Liu and Po-Yuan Shih

Int. J. Environ. Res. Public Health 2019, 16(23), 4679; https://doi.org/10.3390/ijerph16234679 - 24 Nov 2019

Cited by 6 | Viewed by 4283

Abstract

With the development of industrialization and urbanization, air pollution in many countries has become more serious and has affected people’s health. The air quality has been continuously concerned by environmental managers and the public. Therefore, accurate air quality deterioration warning system can avoid [...] Read more.

With the development of industrialization and urbanization, air pollution in many countries has become more serious and has affected people’s health. The air quality has been continuously concerned by environmental managers and the public. Therefore, accurate air quality deterioration warning system can avoid health hazards. In this study, an air quality index (AQI) warning system based on Azure cloud computing platform is proposed. The prediction model is based on DFR (Decision Forest Regression), NNR (Neural Network Regression), and LR (Linear Regression) machine learning algorithms. The best algorithm was selected to calculate the 6 pollutants required for the AQI calculation of the air quality monitoring in real time. The experimental results show that the LR algorithm has the best performance, and the method of this study has a good prediction on the AQI index warning for the next one to three hours. Based on the ACES system proposed, it is hoped that it can prevent personal health hazards and help to reduce medical costs in public. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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14 pages, 4041 KiB

Open AccessArticle

Modeling Group Behavior to Study Innovation Diffusion Based on Cognition and Network: An Analysis for Garbage Classification System in Shanghai, China

by Junjun Zheng, Mingyuan Xu, Ming Cai, Zhichao Wang and Mingmiao Yang

Int. J. Environ. Res. Public Health 2019, 16(18), 3349; https://doi.org/10.3390/ijerph16183349 - 11 Sep 2019

Cited by 21 | Viewed by 4405

Abstract

In real life, garbage has caused great pollution to the environment. A garbage classification system is an effective way to manage this issue, and is an innovation in Shanghai, China. Innovation diffusion is the topic of this paper. This study uses a mathematical [...] Read more.

In real life, garbage has caused great pollution to the environment. A garbage classification system is an effective way to manage this issue, and is an innovation in Shanghai, China. Innovation diffusion is the topic of this paper. This study uses a mathematical statistics method to formulate individual bounded rationality, and uses the specific graph structure of a scale-free network to characterize group structure. Then, a model of group behavior is constructed and the simulation experiment is run on the Python platform. The results show that: (1) In the case of general cognitive ability and high value innovation, most individuals in the group will accept the innovation in the process of innovation dissemination in a garbage classification system after several rounds of the game; (2) it is more helpful to improve the cognitive ability of individuals and the true value of innovation for the diffusion of innovation; and (3) the larger a group, the greater the scope of innovation diffusion and the more time is needed. It is helpful to expand the scope and reduce the time of innovation diffusion by increasing connections among individuals. The innovation of this study is the characterization of individual bounded rationality, which has a certain theoretical value. Meanwhile, the research results of this paper have important practical significance for the promotion of garbage classification, which can be used to popularize the concept of garbage classification. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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15 pages, 2182 KiB

Open AccessArticle

An Evolutionary Game Model for Industrial Pollution Management under Two Punishment Mechanisms

by Chuansheng Wang and Fulei Shi

Int. J. Environ. Res. Public Health 2019, 16(15), 2775; https://doi.org/10.3390/ijerph16152775 - 3 Aug 2019

Cited by 19 | Viewed by 3000

Abstract

In recent years, with the rapid development of the economy, industrial pollution problems have become more and more serious. This paper constructs an evolutionary game model for industrial pollution between the local governments and enterprises to study the dynamic evolution path of a [...] Read more.

In recent years, with the rapid development of the economy, industrial pollution problems have become more and more serious. This paper constructs an evolutionary game model for industrial pollution between the local governments and enterprises to study the dynamic evolution path of a game system and the evolutionary stable strategy under two punishment mechanisms. The results show that, in a static punishment mechanism (SPM), the strategy between governments and enterprises is uncertain. Moreover, the evolutionary trajectory between governments and enterprises is uncertain. However, under the dynamic punishment mechanism (DPM), the evolution path between governments and enterprises tends to converge to a stable value. Thus, the DPM is more conducive than the SPM for industrial pollution control. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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10 pages, 821 KiB

Open AccessArticle

Employing a Fuzzy-Based Grey Modeling Procedure to Forecast China’s Sulfur Dioxide Emissions

by Che-Jung Chang, Guiping Li, Shao-Qing Zhang and Kun-Peng Yu

Int. J. Environ. Res. Public Health 2019, 16(14), 2504; https://doi.org/10.3390/ijerph16142504 - 13 Jul 2019

Cited by 7 | Viewed by 2219

Abstract

Effective determination of trends in sulfur dioxide emissions facilitates national efforts to draft an appropriate policy that aims to lower sulfur dioxide emissions, which is essential for reducing atmospheric pollution. However, to reflect the current situation, a favorable emission reduction policy should be [...] Read more.

Effective determination of trends in sulfur dioxide emissions facilitates national efforts to draft an appropriate policy that aims to lower sulfur dioxide emissions, which is essential for reducing atmospheric pollution. However, to reflect the current situation, a favorable emission reduction policy should be based on updated information. Various forecasting methods have been developed, but their applications are often limited by insufficient data. Grey system theory is one potential approach for analyzing small data sets. In this study, an improved modeling procedure based on the grey system theory and the mega-trend-diffusion technique is proposed to forecast sulfur dioxide emissions in China. Compared with the results obtained by the support vector regression and the radial basis function network, the experimental results indicate that the proposed procedure can effectively handle forecasting problems involving small data sets. In addition, the forecast predicts a steady decline in China’s sulfur dioxide emissions. These findings can be used by the Chinese government to determine whether its current policy to reduce sulfur dioxide emissions is appropriate. Full article

(This article belongs to the Special Issue Application of Advanced Analytical Techniques to Solve Environmental Problems)

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