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Geostatistics in Environmental Pollution and Risk Assessment

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).

Deadline for manuscript submissions: closed (28 February 2011) | Viewed by 201923

Special Issue Editor

Prof. Dr. Yu-Pin Lin

E-Mail Website
Guest Editor
Department of Bioenvironmental Systems Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
Interests: ecological hydrology monitoring and modeling in drainage basins; global change land use modeling; landscape ecology; system dynamic modeling of wetlands; spatial analysis and modeling; blockchain; spatial dynamic modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pollutants in the environment, such as in soil, air and water, occasionally exhibit complex spatial variations and patterns that may complicate efforts to identify the characteristics of the pollutants, particularly in developing areas. Such complex variations and patterns influence the exposure to risk and the development of public health policies at a certain level. Therefore, spatial mapping of polluted areas and assessment of pollution risks are essential because the derived information can contribute significantly to efforts to formulate environmental action strategies and public health policies.

Geostatistics provides various effective methods that can (1) quantify the spatial distribution of a pollutant; (2) improve spatial estimates or simulate exposure concentrations; and (3) spatially quantify and characterize pollution risks for the environment and health risks for humans by using geostatistical methods that exploit the derived geospatial data. In recent years, geostatistical methods have been widely applied in studies of environmental pollution, such as in soil, air and water, to characterize the spatial structures of pollutants, delineate polluted areas, assess pollution risks, and even characterize the spatial patterns of diseases. Accordingly, this special issue focuses on applications of geostatistical methods in environmental pollution and risk assessment studies. Research papers on novel geostatistical techniques that improve such studies are particularly welcome.

Prof. Dr. Yu-Pin Lin
Guest Editor

Keywords

  • geostatistics
  • geostatistical estimation and simulation
  • spatial uncertainty
  • spatial and temporal pattern analysis
  • air, soil and water pollution
  • exposure assessment and risk assessment
  • toxicity and hazard assessment
  • ecological risk assessment
  • spatiotemporal modeling

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Published Papers (19 papers)

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Research

412 KiB  
Short Note
A GIS-Aided Assessment of the Health Hazards of Cadmium in Farm Soils in Central Taiwan
by Po-Huang Chiang, Ta-Chien Chan and Dennis P. H. Hsieh
Int. J. Environ. Res. Public Health 2011, 8(9), 3759-3763; https://doi.org/10.3390/ijerph8093759 - 20 Sep 2011
Cited by 5 | Viewed by 7034
Abstract
A geostatistical method was developed to examine the correlation, or lack of it, between the levels of cadmium (Cd) detected in farm soils and those detected in the human specimens collected from residents around the contaminated areas in Changhua County where cadmium contamination [...] Read more.
A geostatistical method was developed to examine the correlation, or lack of it, between the levels of cadmium (Cd) detected in farm soils and those detected in the human specimens collected from residents around the contaminated areas in Changhua County where cadmium contamination of staple rice has been documented. We used the Taiwan EPA environment data in 2002 and human data which were generated by the National Health Research Institutes during 2003–2005. Kriging interpolation methods were used to determine soil Cd concentrations. A Zonal statistical function was performed to assess the individual exposure. Soil Cd levels and tissue Cd levels in residents were analyzed for contamination hotspots and other areas to determine correlation between the two variables. Three Cd contamination hotspots were identified, in which no correlation was found between soil Cd levels and tissue Cd levels in residents. Our results demonstrate how GIS spatial modeling technique can be used to estimate distribution of pollutants in an area using a limited number of data points. Results indicated no association between the soil contamination and the exposure of residents to Cd, suggesting that both the soils and the residents are receptors of Cd as a pollutant from as yet unidentified sources. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1332 KiB  
Article
Estimation of the Effect of Soil Texture on Nitrate-Nitrogen Content in Groundwater Using Optical Remote Sensing
by Yongyoot Witheetrirong, Nitin Kumar Tripathi, Taravudh Tipdecho and Preeda Parkpian
Int. J. Environ. Res. Public Health 2011, 8(8), 3416-3436; https://doi.org/10.3390/ijerph8083416 - 19 Aug 2011
Cited by 31 | Viewed by 9537
Abstract
The use of chemical fertilizers in Thailand increased exponentially by more than 100-fold from 1961 to 2004. Intensification of agricultural production causes several potential risks to water supplies, especially nitrate-nitrogen (NO3−-N) pollution. Nitrate is considered a potential pollutant because its [...] Read more.
The use of chemical fertilizers in Thailand increased exponentially by more than 100-fold from 1961 to 2004. Intensification of agricultural production causes several potential risks to water supplies, especially nitrate-nitrogen (NO3−-N) pollution. Nitrate is considered a potential pollutant because its excess application can move into streams by runoff and into groundwater by leaching. The nitrate concentration in groundwater increases more than 3-fold times after fertilization and it contaminates groundwater as a result of the application of excess fertilizers for a long time. Soil texture refers to the relative proportion of particles of various sizes in a given soil and it affects the water permeability or percolation rate of a soil. Coarser soils have less retention than finer soils, which in the case of NO3−-N allows it to leach into groundwater faster, so there is positive relationship between the percentage of sands and NO3−-N concentration in groundwater wells. This study aimed to estimate the effect of soil texture on NO3−-N content in groundwater. Optical reflectance data obtained by remote sensing was used in this study. Our hypothesis was that the quantity of nitrogen leached into groundwater through loam was higher than through clay. Nakhon Pathom province, Thailand, was selected as a study area where the terrain is mostly represented by a flat topography. It was found that classified LANDSAT images delineated paddy fields as covering 29.4% of the study area, while sugarcane covered 10.4%, and 60.2% was represented by “others”. The reason for this classified landuse was to determine additional factors, such as vegetation, which might directly affect the quantity of NO3−-N in soil. Ideally, bare soil would be used as a test site, but in fact, no such places were available in Thailand. This led to an indirect method to estimate NO3−-N on various soil textures. Through experimentation, it was found that NO3−-N measured through the loam in sugarcane (I = 0.0054, p < 0.05) was lower than clay represented by paddies (I = 0.0305, p < 0.05). This had a significant negative impact on the assumption. According to the research and local statistical data, farmers have always applied an excess quantity of fertilizer on paddy fields. This is the main reason for the higher quantity of NO3−-N found in clay than loam in this study. This case might be an exceptional study in terms of quantity of fertilizers applied to agricultural fields. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1101 KiB  
Article
Spatial Variation of Surface Soil Available Phosphorous and Its Relation with Environmental Factors in the Chaohu Lake Watershed
by Yongnian Gao, Junfeng Gao and Jiongfeng Chen
Int. J. Environ. Res. Public Health 2011, 8(8), 3299-3317; https://doi.org/10.3390/ijerph8083299 - 15 Aug 2011
Cited by 11 | Viewed by 7766
Abstract
The study presented in this paper attempts to evaluate the spatial pattern of soil available phosphorus, as well as the relation between soil available phosphorus and environment factors including elevation, slope, precipitation, percentage of cultivated land, percentage of forest land, percentage of construction [...] Read more.
The study presented in this paper attempts to evaluate the spatial pattern of soil available phosphorus, as well as the relation between soil available phosphorus and environment factors including elevation, slope, precipitation, percentage of cultivated land, percentage of forest land, percentage of construction land and NDVI using statistical methods and GIS spatial analysis techniques. The results showed that the Spline Tension method performed the best in the prediction of soil available phosphorus in the Chaohu Lake watershed. The spatial variation of surface soil available phosphorus was high in Chaohu Lake watershed and the upstream regions around Chaohu Lake, including the west of Chaohu lake (e.g., southwest of Feixi county, east of Shucheng county and north of Lujiang county) and to the north of Chaohu Lake (e.g., south of Hefei city, south of Feidong county, southwest of Juchao district), had the highest soil available phosphorus content. The mean and standard deviation of soil available phosphorus content gradually decreased as the elevation or slope increased. The cultivated land comprised 60.11% of the watershed and of that land 65.63% belonged to the medium to very high SAP level classes, and it played a major role in SAP availability within the watershed and a potential source of phosphorus to Chaohu Lake resulting in eutrophication. Among the land use types, paddy fields have some of the highest maximum values and variation of coefficients. Subwatershed scale soil available phosphorus was significantly affected by elevation, slope, precipitation, percentage of cultivated land and percentage of forest land and was decided by not only these environmental factors but also some other factors such as artificial phosphorus fertilizer application. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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659 KiB  
Article
Seasonal Variation of Water Quality and Phytoplankton Response Patterns in Daya Bay, China
by Cui-Ci Sun, You-Shao Wang, Mei-Lin Wu, Jun-De Dong, Yu-Tu Wang, Fu-Lin Sun and Yan-Ying Zhang
Int. J. Environ. Res. Public Health 2011, 8(7), 2951-2966; https://doi.org/10.3390/ijerph8072951 - 15 Jul 2011
Cited by 41 | Viewed by 9671
Abstract
Data collected from 12 stations in Daya Bay in different seasons in 2002 revealed the relation between water quality and phytoplankton response patterns. The results showed that Daya Bay could be divided into wet and dry seasons by multivariate statistical analysis. Principal component [...] Read more.
Data collected from 12 stations in Daya Bay in different seasons in 2002 revealed the relation between water quality and phytoplankton response patterns. The results showed that Daya Bay could be divided into wet and dry seasons by multivariate statistical analysis. Principal component analysis indicated that temperature, chlorophyll a and nutrients were important components during the wet season (summer and autumn). The salinity and dissolved oxygen were the main environmental factors in the dry season (winter and spring). According to non-metric multidimensional scaling, there was a shift from the large diatoms in the dry season to the smaller line-chain taxa in the wet season with the condition of a high dissolved inorganic nitrogen and nitrogen to phosphorous concentration ratio. Nutrient changes can thus alter the phytoplankton community composition and biomass, especially near the aquaculture farm areas. There was no evidence of an effect of thermal water from the nearby nuclear power plants on the observed changes in phytoplankton community and biomass in 2002. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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448 KiB  
Article
Using Geographically Weighted Regression (GWR) to Explore Spatial Varying Relationships of Immature Mosquitoes and Human Densities with the Incidence of Dengue
by Chia-Hsien Lin and Tzai-Hung Wen
Int. J. Environ. Res. Public Health 2011, 8(7), 2798-2815; https://doi.org/10.3390/ijerph8072798 - 6 Jul 2011
Cited by 144 | Viewed by 17009
Abstract
The only way for dengue to spread in the human population is through the human-mosquito-human cycle. Most research in this field discusses the dengue-mosquito or dengue-human relationships over a particular study area, but few have explored the local spatial variations of dengue-mosquito and [...] Read more.
The only way for dengue to spread in the human population is through the human-mosquito-human cycle. Most research in this field discusses the dengue-mosquito or dengue-human relationships over a particular study area, but few have explored the local spatial variations of dengue-mosquito and dengue-human relationships within a study area. This study examined whether spatial heterogeneity exists in these relationships. We used Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models to analyze spatial relationships and identify the geographical heterogeneities by using the information of entomology and dengue cases in the cities of Kaohsiung and Fengshan in 2002. Our findings indicate that dengue-mosquito and dengue-human relationships were significantly spatially non-stationary. This means that in some areas higher dengue incidences were associated with higher vector/host densities, but in some areas higher incidences were related to lower vector/host densities. We demonstrated that a GWR model can be used to geographically differentiate the relationships of dengue incidence with immature mosquito and human densities. This study provides more insights into spatial targeting of intervention and control programs against dengue outbreaks within the study areas. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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766 KiB  
Article
Nationwide Desert Highway Assessment: A Case Study in China
by Xuesong Mao, Fuchun Wang and Binggang Wang
Int. J. Environ. Res. Public Health 2011, 8(7), 2734-2746; https://doi.org/10.3390/ijerph8072734 - 30 Jun 2011
Cited by 6 | Viewed by 10169
Abstract
The natural environment affects the construction of desert highways. Conversely, highway construction affects the natural environment and puts the ecological environment at a disadvantage. To satisfy the variety and hierarchy of desert highway construction and discover the spatio-temporal distribution of the natural environment [...] Read more.
The natural environment affects the construction of desert highways. Conversely, highway construction affects the natural environment and puts the ecological environment at a disadvantage. To satisfy the variety and hierarchy of desert highway construction and discover the spatio-temporal distribution of the natural environment and its effect on highway construction engineering, an assessment of the natural regional divisions of desert highways in China is carried out for the first time. Based on the general principles and method for the natural region division, the principles, method and index system for desert highway assessment is put forward by combining the desert highway construction features and the azonal differentiation law. The index system combines the dominant indicator and four auxiliary indicators. The dominant indicator is defined by the desert’s comprehensive state index and the auxiliary indicators include the sand dune height, the blown sand strength, the vegetation coverage ratio and the annual average temperature difference. First the region is divided according to the dominant indicator. Then the region boundaries are amended according to the four auxiliary indicators. Finally the natural region division map for desert highway assessment is presented. The Chinese desert highways can be divided into three sections: the east medium effect region, the middle medium-severe effect region, and the west slight-medium effect region. The natural region division map effectively paves the way for the route planning, design, construction, maintenance and ongoing management of desert highways, and further helps environmental protection. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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Graphical abstract

268 KiB  
Article
Investigation of Spatial and Temporal Trends in Water Quality in Daya Bay, South China Sea
by Mei-Lin Wu, You-Shao Wang, Jun-De Dong, Cui-Ci Sun, Yu-Tu Wang, Fu-Lin Sun and Hao Cheng
Int. J. Environ. Res. Public Health 2011, 8(6), 2352-2365; https://doi.org/10.3390/ijerph8062352 - 22 Jun 2011
Cited by 22 | Viewed by 7724
Abstract
The objective is to identify the spatial and temporal variability of the hydrochemical quality of the water column in a subtropical coastal system, Daya Bay, China. Water samples were collected in four seasons at 12 monitoring sites. The Southeast Asian monsoons, northeasterly from [...] Read more.
The objective is to identify the spatial and temporal variability of the hydrochemical quality of the water column in a subtropical coastal system, Daya Bay, China. Water samples were collected in four seasons at 12 monitoring sites. The Southeast Asian monsoons, northeasterly from October to the next April and southwesterly from May to September have also an important influence on water quality in Daya Bay. In the spatial pattern, two groups have been identified, with the help of multidimensional scaling analysis and cluster analysis. Cluster I consisted of the sites S3, S8, S10 and S11 in the west and north coastal parts of Daya Bay. Cluster I is mainly related to anthropogenic activities such as fish-farming. Cluster II consisted of the rest of the stations in the center, east and south parts of Daya Bay. Cluster II is mainly related to seawater exchange from South China Sea. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1133 KiB  
Article
Evaluating and Mapping of Spatial Air Ion Quality Patterns in a Residential Garden Using a Geostatistic Method
by Chen-Fa Wu, Chun-Hsien Lai, Hone-Jay Chu and Wen-Huang Lin
Int. J. Environ. Res. Public Health 2011, 8(6), 2304-2319; https://doi.org/10.3390/ijerph8062304 - 20 Jun 2011
Cited by 26 | Viewed by 9553
Abstract
Negative air ions (NAI) produce biochemical reactions that increase the levels of the mood chemical serotonin in the environment. Moreover, they benefit both the psychological well being and the human body’s physiological condition. The aim of this research was to estimate and measure [...] Read more.
Negative air ions (NAI) produce biochemical reactions that increase the levels of the mood chemical serotonin in the environment. Moreover, they benefit both the psychological well being and the human body’s physiological condition. The aim of this research was to estimate and measure the spatial distributions of negative and positive air ions in a residential garden in central Taiwan. Negative and positive air ions were measured at thirty monitoring locations in the study garden from July 2009 to June 2010. Moreover, Kriging was applied to estimate the spatial distribution of negative and positive air ions, as well as the air ion index in the study area. The measurement results showed that the numbers of NAI and PAI differed greatly during the four seasons, the highest and the lowest negative and positive air ion concentrations were found in the summer and winter, respectively. Moreover, temperature was positively affected negative air ions concentration. No matter what temperature is, the ranges of variogram in NAI/PAI were similar during four seasons. It indicated that spatial patterns of NAI/PAI were independent of the seasons and depended on garden elements and configuration, thus the NAP/PAI was a good estimate of the air quality regarding air ions. Kriging maps depicted that the highest negative and positive air ion concentration was next to the waterfall, whereas the lowest air ions areas were next to the exits of the garden. The results reveal that waterscapes are a source of negative and positive air ions, and that plants and green space are a minor source of negative air ions in the study garden. Moreover, temperature and humidity are positively and negatively affected negative air ions concentration, respectively. The proposed monitoring and mapping approach provides a way to effectively assess the patterns of negative and positive air ions in future landscape design projects. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1121 KiB  
Article
Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods
by Hwa-Lung Yu, Chih-Hsih Wang, Ming-Che Liu and Yi-Ming Kuo
Int. J. Environ. Res. Public Health 2011, 8(6), 2153-2169; https://doi.org/10.3390/ijerph8062153 - 14 Jun 2011
Cited by 44 | Viewed by 9355
Abstract
Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were [...] Read more.
Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005–2007. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1005 KiB  
Article
Spatial Pattern Analysis of Heavy Metals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics
by Xiao-Ni Huo, Wei-Wei Zhang, Dan-Feng Sun, Hong Li, Lian-Di Zhou and Bao-Guo Li
Int. J. Environ. Res. Public Health 2011, 8(6), 2074-2089; https://doi.org/10.3390/ijerph8062074 - 8 Jun 2011
Cited by 54 | Viewed by 10908
Abstract
This study explored the spatial pattern of heavy metals in Beijing agricultural soils using Moran’s I statistic of spatial autocorrelation. The global Moran’s I result showed that the spatial dependence of Cr, Ni, Zn, and Hg changed with different spatial weight matrixes, and [...] Read more.
This study explored the spatial pattern of heavy metals in Beijing agricultural soils using Moran’s I statistic of spatial autocorrelation. The global Moran’s I result showed that the spatial dependence of Cr, Ni, Zn, and Hg changed with different spatial weight matrixes, and they had significant and positive global spatial correlations based on distance weight. The spatial dependence of the four metals was scale-dependent on distance, but these scale effects existed within a threshold distance of 13 km, 32 km, 50 km, and 29 km, respectively for Cr, Ni, Zn, and Hg. The maximal spatial positive correlation range was 57 km, 70 km, 57 km, and 55 km for Cr, Ni, Zn, and Hg, respectively and these were not affected by sampling density. Local spatial autocorrelation analysis detected the locations of spatial clusters and spatial outliers and revealed that the pollution of these four metals occurred in significant High-high spatial clusters, Low-high, or even High-low spatial outliers. Thus, three major areas were identified and should be receiving more attention: the first was the northeast region of Beijing, where Cr, Zn, Ni, and Hg had significant increases. The second was the southeast region of Beijing where wastewater irrigation had strongly changed the content of metals, particularly of Cr and Zn, in soils. The third area was the urban fringe around city, where Hg showed a significant increase. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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252 KiB  
Article
Spatial Variations of Heavy Metals in the Soils of Vegetable-Growing Land along Urban-Rural Gradient of Nanjing, China
by Shi-Bo Fang, Hao Hu, Wan-Chun Sun and Jian-Jun Pan
Int. J. Environ. Res. Public Health 2011, 8(6), 1805-1816; https://doi.org/10.3390/ijerph8061805 - 25 May 2011
Cited by 24 | Viewed by 10187
Abstract
China has experienced rapid urbanization in recent years. The acceleration of urbanization has created wealth and opportunity as well as intensified ecological and environmental problems, especially soil pollution. Our study concentrated on the variation of heavy metal content due to urbanization in the [...] Read more.
China has experienced rapid urbanization in recent years. The acceleration of urbanization has created wealth and opportunity as well as intensified ecological and environmental problems, especially soil pollution. Our study concentrated on the variation of heavy metal content due to urbanization in the vegetable-growing soil. Laws and other causes of the spatial-temporal variation in heavy metal content of vegetable-growing soils were analyzed for the period of urbanization in Nanjing (the capital of Jiangsu province in China). The levels of Cu, Zn, Pb, Cd and Hg in samples of vegetable-growing soil were detected. The transverse, vertical spatio-temporal variation of heavy metals in soil was analyzed on the base of field investigations and laboratory analysis. The results show that: (1) in soil used for vegetable production, the levels of heavy metals decreased gradually from urban to rural areas; the levels of the main heavy metals in urban areas are significantly higher than suburban and rural areas; (2) the means of the levels of heavy metals, calculated by subtracting the sublayer (15–30 cm) from the toplayer (0–15 cm), are all above zero and large in absolute value in urban areas, but in suburban and rural areas, the means are all above or below zero and small in absolute value. The causes of spatial and temporal variation were analyzed as follows: one cause was associated with mellowness of the soil and the length of time the soil had been used for vegetable production; the other cause was associated with population density and industrial intensity decreasing along the urban to rural gradient (i.e., urbanization levels can explain the distribution of heavy metals in soil to some extent). Land uses should be planned on the basis of heavy metal pollution in soil, especially in urban and suburban regions. Heavily polluted soils have to be expected from food production. Further investigation should be done to determine whether and what kind of agricultural production could be established near urban centers. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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457 KiB  
Article
A Geostatistical Approach to Assess the Spatial Association between Indoor Radon Concentration, Geological Features and Building Characteristics: The Case of Lombardy, Northern Italy
by Riccardo Borgoni, Valeria Tritto, Carlo Bigliotto and Daniela De Bartolo
Int. J. Environ. Res. Public Health 2011, 8(5), 1420-1440; https://doi.org/10.3390/ijerph8051420 - 6 May 2011
Cited by 33 | Viewed by 10390
Abstract
Radon is a natural gas known to be the main contributor to natural background radiation exposure and second to smoking, a major leading cause of lung cancer. The main source of radon is the soil, but the gas can enter buildings in many [...] Read more.
Radon is a natural gas known to be the main contributor to natural background radiation exposure and second to smoking, a major leading cause of lung cancer. The main source of radon is the soil, but the gas can enter buildings in many different ways and reach high indoor concentrations. Monitoring surveys have been promoted in many countries in order to assess the exposure of people to radon. In this paper, two complementary aspects are investigated. Firstly, we mapped indoor radon concentration in a large and inhomogeneous region using a geostatistical approach which borrows strength from the geologic nature of the soil. Secondly, knowing that geologic and anthropogenic factors, such as building characteristics, can foster the gas to flow into a building or protect against this, we evaluated these effects through a multiple regression model which takes into account the spatial correlation of the data. This allows us to rank different building typologies, identified by architectonic and geological characteristics, according to their proneness to radon. Our results suggest the opportunity to differentiate construction requirements in a large and inhomogeneous area, as the one considered in this paper, according to different places and provide a method to identify those dwellings which should be monitored more carefully. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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862 KiB  
Article
Combining a Fuzzy Matter-Element Model with a Geographic Information System in Eco-Environmental Sensitivity and Distribution of Land Use Planning
by Jing Zhang, Ke Wang, Xinming Chen and Wenjuan Zhu
Int. J. Environ. Res. Public Health 2011, 8(4), 1206-1221; https://doi.org/10.3390/ijerph8041206 - 18 Apr 2011
Cited by 21 | Viewed by 10055
Abstract
Sustainable ecological and environmental development is the basis of regional development. The sensitivity classification of the ecological environment is the premise of its spatial distribution for land use planning. In this paper, a fuzzy matter-element model and factor-overlay method were employed to analyze [...] Read more.
Sustainable ecological and environmental development is the basis of regional development. The sensitivity classification of the ecological environment is the premise of its spatial distribution for land use planning. In this paper, a fuzzy matter-element model and factor-overlay method were employed to analyze the ecological sensitivity in Yicheng City. Four ecological indicators, including soil condition,, water condition,, atmospheric conditions and biodiversity were used to classify the ecological sensitivity. The results were categorized into five ranks: insensitive, slightly sensitive, moderately sensitive, highly sensitive and extremely sensitive zones. The spatial distribution map of environmental sensitivity for land use planning was obtained using GIS (Geographical Information System) techniques. The results illustrated that the extremely sensitive and highly sensitive areas accounted for 14.40% and 30.12% of the total area, respectively, while the moderately sensitive and slightly sensitive areas are 25.99% and 29.49%, respectively. The results provide the theoretical foundation for land use planning by categorizing all kinds of land types in Yicheng City. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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741 KiB  
Article
Assessment of Water Quality in a Subtropical Alpine Lake Using Multivariate Statistical Techniques and Geostatistical Mapping: A Case Study
by Wen-Cheng Liu, Hwa-Lung Yu and Chung-En Chung
Int. J. Environ. Res. Public Health 2011, 8(4), 1126-1140; https://doi.org/10.3390/ijerph8041126 - 15 Apr 2011
Cited by 50 | Viewed by 11315
Abstract
Concerns about the water quality in Yuan-Yang Lake (YYL), a shallow, subtropical alpine lake located in north-central Taiwan, has been rapidly increasing recently due to the natural and anthropogenic pollution. In order to understand the underlying physical and chemical processes as well as [...] Read more.
Concerns about the water quality in Yuan-Yang Lake (YYL), a shallow, subtropical alpine lake located in north-central Taiwan, has been rapidly increasing recently due to the natural and anthropogenic pollution. In order to understand the underlying physical and chemical processes as well as their associated spatial distribution in YYL, this study analyzes fourteen physico-chemical water quality parameters recorded at the eight sampling stations during 2008–2010 by using multivariate statistical techniques and a geostatistical method. Hierarchical clustering analysis (CA) is first applied to distinguish the three general water quality patterns among the stations, followed by the use of principle component analysis (PCA) and factor analysis (FA) to extract and recognize the major underlying factors contributing to the variations among the water quality measures. The spatial distribution of the identified major contributing factors is obtained by using a kriging method. Results show that four principal components i.e., nitrogen nutrients, meteorological factor, turbidity and nitrate factors, account for 65.52% of the total variance among the water quality parameters. The spatial distribution of principal components further confirms that nitrogen sources constitute an important pollutant contribution in the YYL. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1867 KiB  
Article
Applying Factor Analysis Combined with Kriging and Information Entropy Theory for Mapping and Evaluating the Stability of Groundwater Quality Variation in Taiwan
by Guey-Shin Shyu, Bai-You Cheng, Chi-Ting Chiang, Pei-Hsuan Yao and Tsun-Kuo Chang
Int. J. Environ. Res. Public Health 2011, 8(4), 1084-1109; https://doi.org/10.3390/ijerph8041084 - 8 Apr 2011
Cited by 88 | Viewed by 11046
Abstract
In Taiwan many factors, whether geological parent materials, human activities, and climate change, can affect the groundwater quality and its stability. This work combines factor analysis and kriging with information entropy theory to interpret the stability of groundwater quality variation in Taiwan between [...] Read more.
In Taiwan many factors, whether geological parent materials, human activities, and climate change, can affect the groundwater quality and its stability. This work combines factor analysis and kriging with information entropy theory to interpret the stability of groundwater quality variation in Taiwan between 2005 and 2007. Groundwater quality demonstrated apparent differences between the northern and southern areas of Taiwan when divided by the Wu River. Approximately 52% of the monitoring wells in southern Taiwan suffered from progressing seawater intrusion, causing unstable groundwater quality. Industrial and livestock wastewaters also polluted 59.6% of the monitoring wells, resulting in elevated EC and TOC concentrations in the groundwater. In northern Taiwan, domestic wastewaters polluted city groundwater, resulting in higher NH3-N concentration and groundwater quality instability was apparent among 10.3% of the monitoring wells. The method proposed in this study for analyzing groundwater quality inspects common stability factors, identifies potential areas influenced by common factors, and assists in elevating and reinforcing information in support of an overall groundwater management strategy. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1699 KiB  
Article
Field-Scale Spatial Variation of Saline-Sodic Soil and Its Relation with Environmental Factors in Western Songnen Plain of China
by Fan Yang, Guangxin Zhang, Xiongrui Yin and Zhijun Liu
Int. J. Environ. Res. Public Health 2011, 8(2), 374-387; https://doi.org/10.3390/ijerph8020374 - 31 Jan 2011
Cited by 32 | Viewed by 10140
Abstract
The objectives of this study were to investigate the degree of spatial variability and variance structure of salinization parameters using classical and geostatistical method in Songnen Plain of China, which is one of largest saline-sodic areas in the World, and to analyze the [...] Read more.
The objectives of this study were to investigate the degree of spatial variability and variance structure of salinization parameters using classical and geostatistical method in Songnen Plain of China, which is one of largest saline-sodic areas in the World, and to analyze the relationship between salinization parameters, including soil salinity content (SC), electrical conductivity (EC), sodium adsorption ratio (SAR), and pH, and seven environmental factors by Pearson and stepwise regression analysis. The environmental factors were ground elevation, surface ponding time, surface ponding depth, and soil moistures at four layers (0–10 cm, 10–30 cm, 30–60 cm, and 60–100 cm). The results indicated that SC, EC, and SAR showed great variations, whereas pH exhibited low variations. Four salinization parameters showed strongly spatial autocorrelation resulting from the compound impact of structural factors. The empirical semivariograms in the four parameters could be simulated by spherical and exponential models. The spatial distributions of SC, EC, SAR and pH showed similar patterns, with the coexistence of high salinity and sodicity in the areas with high ground elevation. By Pearson analysis, the soil salinization parameters showed a significant positive relationship with ground elevation, but a negative correlation with surface ponding time, surface ponding depth, and soil moistures. Both correlation and stepwise regression analysis showed that ground elevation is the most important environmental factor for spatial variation of soil sanilization. The results from this research can provide some useful information for explaining mechanism of salinization process and utilization of saline-sodic soils in the Western Songnen Plain. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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798 KiB  
Article
An Integrated Approach for Assessing Aquatic Ecological Carrying Capacity: A Case Study of Wujin District in the Tai Lake Basin, China
by Chen Zeng, Yaolin Liu, Yanfang Liu, Jiameng Hu, Xiaogang Bai and Xiaoyu Yang
Int. J. Environ. Res. Public Health 2011, 8(1), 264-280; https://doi.org/10.3390/ijerph8010264 - 24 Jan 2011
Cited by 25 | Viewed by 12578
Abstract
Aquatic ecological carrying capacity is an effective method for analyzing sustainable development in regional water management. In this paper, an integrated approach is employed for assessing the aquatic ecological carrying capacity of Wujin District in the Tai Lake Basin, China. An indicator system [...] Read more.
Aquatic ecological carrying capacity is an effective method for analyzing sustainable development in regional water management. In this paper, an integrated approach is employed for assessing the aquatic ecological carrying capacity of Wujin District in the Tai Lake Basin, China. An indicator system is established considering social and economic development as well as ecological resilience perspectives. While calculating the ecological index, the normalized difference vegetation index (NDVI) is extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) time-series images, followed by spatial and temporal analysis of vegetation cover. Finally, multi-index assessment of aquatic ecological carrying capacity is carried out for the period 2000 to 2008, including both static and dynamic variables. The results reveal that aquatic ecological carrying capacity presents a slight upward trend in the past decade and the intensity of human activities still exceeded the aquatic ecological carrying capacity in 2008. In terms of human activities, population has decreased, GDP has quadrupled, and fertilizer application and industrial wastewater discharge have declined greatly in the past decade. The indicators representing aquatic ecosystem conditions have the lowest scores, which are primarily attributed to the water eutrophication problem. Yet the terrestrial ecosystem is assessed to be in better condition since topographic backgrounds and landscape diversity are at higher levels. Based on the work carried out, it is suggested that pollutant emission be controlled to improve water quality and agricultural development around Ge Lake (the largest lake in Wujin District) be reduced. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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1413 KiB  
Article
Hotspot Analysis of Spatial Environmental Pollutants Using Kernel Density Estimation and Geostatistical Techniques
by Yu-Pin Lin, Hone-Jay Chu, Chen-Fa Wu, Tsun-Kuo Chang and Chiu-Yang Chen
Int. J. Environ. Res. Public Health 2011, 8(1), 75-88; https://doi.org/10.3390/ijerph8010075 - 30 Dec 2010
Cited by 48 | Viewed by 13690
Abstract
Concentrations of four heavy metals (Cr, Cu, Ni, and Zn) were measured at 1,082 sampling sites in Changhua county of central Taiwan. A hazard zone is defined in the study as a place where the content of each heavy metal exceeds the corresponding [...] Read more.
Concentrations of four heavy metals (Cr, Cu, Ni, and Zn) were measured at 1,082 sampling sites in Changhua county of central Taiwan. A hazard zone is defined in the study as a place where the content of each heavy metal exceeds the corresponding control standard. This study examines the use of spatial analysis for identifying multiple soil pollution hotspots in the study area. In a preliminary investigation, kernel density estimation (KDE) was a technique used for hotspot analysis of soil pollution from a set of observed occurrences of hazards. In addition, the study estimates the hazardous probability of each heavy metal using geostatistical techniques such as the sequential indicator simulation (SIS) and indicator kriging (IK). Results show that there are multiple hotspots for these four heavy metals and they are strongly correlated to the locations of industrial plants and irrigation systems in the study area. Moreover, the pollution hotspots detected using the KDE are the almost same to those estimated using IK or SIS. Soil pollution hotspots and polluted sampling densities are clearly defined using the KDE approach based on contaminated point data. Furthermore, the risk of hazards is explored by these techniques such as KDE and geostatistical approaches and the hotspot areas are captured without requiring exhaustive sampling anywhere. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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995 KiB  
Article
Spatiotemporal Trends in Oral Cancer Mortality and Potential Risks Associated with Heavy Metal Content in Taiwan Soil
by Chi-Ting Chiang, Ie-Bin Lian, Che-Chun Su, Kuo-Yang Tsai, Yu-Pin Lin and Tsun-Kuo Chang
Int. J. Environ. Res. Public Health 2010, 7(11), 3916-3928; https://doi.org/10.3390/ijerph7113916 - 5 Nov 2010
Cited by 30 | Viewed by 10782
Abstract
Central and Eastern Taiwan have alarmingly high oral cancer (OC) mortality rates, however, the effect of lifestyle factors such as betel chewing cannot fully explain the observed high-risk. Elevated concentrations of heavy metals in the soil reflect somewhat the levels of exposure to [...] Read more.
Central and Eastern Taiwan have alarmingly high oral cancer (OC) mortality rates, however, the effect of lifestyle factors such as betel chewing cannot fully explain the observed high-risk. Elevated concentrations of heavy metals in the soil reflect somewhat the levels of exposure to the human body, which may promote cancer development in local residents. This study assesses the space-time distribution of OC mortality in Taiwan, and its association with prime factors leading to soil heavy metal content. The current research obtained OC mortality data from the Atlas of Cancer Mortality in Taiwan, 1972–2001, and derived soil heavy metals content data from a nationwide survey carried out by ROCEPA in 1985. The exploratory data analyses showed that OC mortality rates in both genders had high spatial autocorrelation (Moran’s I = 0.6716 and 0.6318 for males and females). Factor analyses revealed three common factors (CFs) representing the major pattern of soil pollution in Taiwan. The results for Spatial Lag Models (SLM) showed that CF1 (Cr, Cu, Ni, and Zn) was most spatially related to male OC mortality which implicates that some metals in CF1 might play as promoters in OC etiology. Full article
(This article belongs to the Special Issue Geostatistics in Environmental Pollution and Risk Assessment)
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