Establishment of an Automatic Real-Time Monitoring System for Irrigation Water Quality Management.

In order to provide the real-time monitoring for identifying the sources of pollution and improving the irrigation water quality management, the integration of continuous automatic sampling techniques and cloud technologies is essential. In this study, we have established an automatic real-time monitoring system for improving the irrigation water quality management, especially for heavy metals such as Cd, Pb, Cu, Ni, Zn, and Cr. As a part of this work, we have first provided several examples on the basic water quality parameters (e.g., pH and electrical conductance) to demonstrate the capacity of data correction by the smart monitoring system, and then evaluated the trend and variance of water quality parameters for different types of monitoring stations. By doing so, the threshold (to initiate early warming) of different water quality parameters could be dynamically determined by the system, and the authorities could be immediately notified for follow-up actions. We have also provided and discussed the representative results from the real-time automatic monitoring system of heavy metals from different monitoring stations. Finally, we have illustrated the implications of the developed smart monitoring system for ensuring the safety of irrigation water in the near future, including integration with automatic sampling for establishing information exchange platform, estimating fluxes of heavy metals to paddy fields, and combining with green technologies for nonpoint source pollution control.

A multiple model approach for evaluating the performance of time-lapse capsules in trapping heavy metals from water bodies.

Adsorption by ion-exchange resins has been widely used as a cost-effective method for removing numerous hazardous materials, particularly heavy metals, from aqueous solutions. For effectively detecting the illegal discharge of industrial wastewater containing heavy metals, we developed "time-lapse capsules" to trap metallic ions from water bodies. Despite recent progress in the development of time-lapse capsules, a fundamental understanding was still needed to unravel the adsorption behavior of different heavy metals for further improvement of the design and scale-up of the capsule. In this study, three different approaches, viz., response surfaces (from the statistical point of view), time-dependent diffusion-controlled models (from the kinetic point of view), and adsorption isotherms (from the equilibrium point of view), were utilized to evaluate the effect of operating factors on the adsorption of heavy metals from watershed using time-lapse capsules. The obtained results indicated that the key parameters, such as adsorption rate constant, diffusivity, and maximum adsorption capacity, could provide insights into the basis of design criteria.

Rapid assessment of heavy metal pollution using ion-exchange resin sachets and micro-XRF core-scanning.

Conventional pollution monitoring strategies for heavy metals are often costly and unpractical. Innovative sampling and analytical approaches are therefore needed to efficiently monitor large areas. This study presents a novel, simple, fast, and inexpensive method to monitor heavy metal pollution that uses cation-exchange resin sachets and the micro-XRF core-scanning technique (XRF-CS). The resin passive samplers act as concentrators of cationic species and can be readily deployed spatially and temporally to record pollution signals. The large number of analytical tasks are then overcome by the fast and non-destructive XRF-CS to precisely assess elemental concentrations. Quantifying element loading involves direct comparison with a set of identically prepared and scanned resin reference standards containing Ca, Ti, Cr, Mn, Ni, Cu, Zn, Pb. The results show that within the test range (from 0-1000 s mg kg-1), the calibration lines have excellent regressions (R2 ≥ 0.97), even at the shortest exposure time (1 s). A pilot field survey of a suspected polluted area in central Taiwan, where 30 resin sachets had been deployed, identified a pollution hot spot in a rapid and economical manner. Therefore, this approach has the potential to become a valuable tool in environmental monitoring and forensics.

Greywater treatment by granular filtration system using volcanic tuff and gravel media.

The main objective of this study was to evaluate the efficiency of a granular filtration system (GFS) in greywater treatment under arid and semi-arid conditions. Six GFSs were designed, constructed, and monitored for approximately 13 months. Each GFS served a single rural Jordanian home by treating their greywater. Volcanic tuff media were used as the filtration media in three of the GFSs while the remaining three GFSs used gravel media. Results show that the biological oxygen demand, chemical oxygen demand, and total suspended solids of the effluent were significantly lower as compared to the influent and demonstrated a removal efficiency of 73%, 65%, and 85%, respectively, when using volcanic tuff media. The removal efficiency was 49%, 51%, and 76%, respectively, when using gravel media. There was a significant increase in the electrical conductivity, pH, potassium (K+), magnesium (Mg2+), chloride (Cl-), sodium (Na+), sulfate (SO42-), bicarbonates (HCO3-), sodium adsorption ratio, and exchangeable sodium percentage in the effluents of the GFS that used volcanic tuff media. The study suggests that GFSs can adequately treat greywater under arid conditions. However, gravel media produce less concentrated effluent compared to the volcanic tuff media.

Lead isotope characterization of petroleum fuels in Taipei, Taiwan.

Leaded gasoline in Taiwan was gradually phased out from 1983 to 2000. However, it is unclear whether unleaded gasoline still contributes to atmospheric lead (Pb) exposure in urban areas. In this study, Pb isotopic compositions of unleaded gasolines, with octane numbers of 92, 95, 98, and diesel from two local suppliers in Taipei were determined by multi-collector inductively coupled plasma mass spectrometry with a two-sigma uncertainty of ± 0.02 %. Lead isotopic ratios of vehicle exhaust (²°8Pb/²°7Pb: 2.427, ²°6Pb/²°7Pb: 1.148, as estimated from petroleum fuels) overlap with the reported aerosol data. This agreement indicates that local unleaded petroleum fuels, containing 10-45 ng·Pb·g⁻¹, are merely one contributor among various sources to urban aerosol Pb. Additionally, the distinction between the products of the two companies is statistically significant in their individual ²°8Pb/²°6Pb ratios (p-value < 0.001, t test). Lead isotopic characterization appears to be applicable as a "fingerprinting" tool for tracing the sources of Pb pollution.

Geospatial disparities and the underlying causes of major cancers for women in Taiwan.

Some specific types of cancer still pose a severe threat to the health of Taiwanese women. This study focuses on determining the geographical locations of hot spots and causal factors related to the major categories of cancers in Taiwanese women. Cancer mortality data from 1972 to 2001 of 346 townships in Taiwan were obtained from the Atlas of Cancer Mortality. Principal component analysis was conducted to determine the primary categories of female cancers. The spatial patterns of hot spots and cold spots for each major cancer category were identified using the local indicator of spatial association. Finally, the regional differences between the hot spots and cold spots were compared to confirm the possible factors causing cancer throughout Taiwan. A total of 21 cancer types in women were divided into seven major categories, which accounted for 68.0% of the total variance. The results from the spatial autocorrelation analysis showed significant spatial clusters of the cancer categories. Based on the overall consistency of results between this study and those of previous research, this study further identified the high-risk locations and some specific risk factors for major cancer types among Taiwanese women.

Assessing and mapping spatial associations among oral cancer mortality rates, concentrations of heavy metals in soil, and land use types based on multiple scale data.

In this study, a deconvolution procedure was used to create a variogram of oral cancer (OC) rates. Based on the variogram, area-to-point (ATP) Poisson kriging and p-field simulation were used to downscale and simulate, respectively, the OC rate data for Taiwan from the district scale to a 1 km × 1 km grid scale. Local cluster analysis (LCA) of OC mortality rates was then performed to identify OC mortality rate hot spots based on the downscaled and the p-field-simulated OC mortality maps. The relationship between OC mortality and land use was studied by overlapping the maps of the downscaled OC mortality, the LCA results, and the land uses. One thousand simulations were performed to quantify local and spatial uncertainties in the LCA to identify OC mortality hot spots. The scatter plots and Spearman's rank correlation yielded the relationship between OC mortality and concentrations of the seven metals in the 1 km cell grid. The correlation analysis results for the 1 km scale revealed a weak correlation between OC mortality rate and concentrations of the seven studied heavy metals in soil. Accordingly, the heavy metal concentrations in soil are not major determinants of OC mortality rates at the 1 km scale at which soils were sampled. The LCA statistical results for local indicator of spatial association (LISA) revealed that the sites with high probability of high-high (high value surrounded by high values) OC mortality at the 1 km grid scale were clustered in southern, eastern, and mid-western Taiwan. The number of such sites was also significantly higher on agricultural land and in urban regions than on land with other uses. The proposed approach can be used to downscale and evaluate uncertainty in mortality data from a coarse scale to a fine scale at which useful additional information can be obtained for assessing and managing land use and risk.

Applying factor analysis combined with kriging and information entropy theory for mapping and evaluating the stability of groundwater quality variation in Taiwan.

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 NH(3)-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.

Hotspot analysis of spatial environmental pollutants using kernel density estimation and geostatistical techniques.

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.

Possible association between nickel and chromium and oral cancer: a case-control study in central Taiwan.

Oral cancer is one of the most common cancers in Taiwan. Changhua County, in central Taiwan, has an extremely high prevalence of oral cancer, along with a high concentration of metal-related industries and soil metal contamination. The aim of this study was to clarify the possible association between metals and oral cancer within this specific area. This study recruited 101 oral cancer patients and 104 controls from the Changhua Christian Hospital. All subjects completed a questionnaire that asked about demographic information; cigarette, alcohol, and betel quid use; and environmental and occupational exposure history. Blood samples were collected and tested for metal concentrations with inductively coupled plasma mass spectrometry. A multiple logistic regression model illustrated that oral cancer was significantly associated with the blood levels of nickel and chromium (both with P<0.0001) after controlling for potential confounders. This study suggested a potential role of these two metals in the mechanism of oral cancer development.

A critical exploration of blood and environmental chromium concentration among oral cancer patients in an oral cancer prevalent area of Taiwan.

The growing incidence of oral cancer (OC) in Taiwan has become a crucial public health concern. In particular, Changhua, a county in central Taiwan, carries persistently high OC incidence rate, with an alarmingly high male/female ratio of OC incidence. Previous epidemiological studies had found that the incidence is spatially correlated with the level of soil content to certain heavy metals in the central Taiwan area. Soil and the human body both intake environmental heavy metals, which can be absorbed through various ways. The soil metal concentration is an index of possible environmental exposure to heavy metal, and the blood metal concentration somewhat reflects the level of the exposure on the human body. Metallic carcinogen is likely to generate free radicals and play a role in many cancers, and many studies had reported that environmental exposure to heavy metals is an important risk factor for developing cancer. Studies on animals showed that chronic intake of chromium (Cr) could induce OC. This study aims to explore the association between the Cr concentration in the farm soil and in the blood of OC patients. We recruited 79 OC patients from Changhua County, with their lifestyle being adjusted in regression analysis. The results showed that the Cr concentration in the blood of OC patients is significantly higher than the background value, and is positively associated with the Cr concentration in the soil surrounding their residence (p-value < 0.023). Because Changhua County is only with moderate prevalence of the known OC habitual risk factors, an environmental factor related to heavy metal Cr exposure is suspected. Future investigations may verify the causal relation between Cr and OC.

Spatiotemporal trends in oral cancer mortality and potential risks associated with heavy metal content in Taiwan soil.

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.

Arsenic and lead (beudantite) contamination of agricultural rice soils in the Guandu Plain of northern Taiwan.

This study investigates the species of As and Pb (beudantite) residues present in the seriously contaminated agricultural rice soils of the Guandu Plain. Two pedons in the Guandu Plain agricultural soils, each pedon separated into five horizons (each of 20 cm) were collected for this study. Soil samples were packed into a column for leaching with simulated acid rains. Soil pH ranged from 5.1 to 7.1 with high base saturation. Soils can be classified as clay loam, mixed, thermic, Typic or Umbric Albaqualfs. The XRD analysis indicated the beudantite particles are present in clay fractions, showing high concentrations of As and Pb. This is because of 50-100 years ago irrigation water was introduced from Huang Gang Creek of hot springs containing high concentrations of As and Pb. Only low concentrations of As and Pb can be leached out with simulated acid rains (i.e., pHs 2 and 4), even through 40 pore volumes of leaching experiments. The sequential extraction experiments resulted in the high portions of As and Pb remaining in the amorphous, Fe and Al oxyhydroxides and residual fractions. Thus, the remediation of As and Pb in this agricultural rice paddy soils merits further study.

Elucidating the underlying causes of oral cancer through spatial clustering in high-risk areas of Taiwan with a distinct gender ratio of incidence.

This study aimed to elucidate whether or not high-risk clusters of oral cancer (OC) incidence spatially correlate with the prevalence rates of betel quid chewing (BQC) and cigarette smoking (CS) in Taiwan. The spatial autocorrelation and potential clusters of OC incidence among the 307 townships and heavy metal content of soil throughout Taiwan were identified using the Anselin's local Moran test. Additionally, the spatial correlations among the incidence of OC, the prevalence of BQC and CS and heavy metal content of soil were determined based on a comparison of spatial clusters. High-risk OC (Moran's I = 0.638, P <0.001) clusters were located in central and eastern Taiwan, while "hot spots" of BQC and CS prevalence were located mainly in eastern Taiwan. The distributions of BQC and CS lifestyle factors (P <0.001) were spatially autocorrelated. The "hot spots" of OC largely coincided with the "hot spots" of BQC, except for the Changhua and Yunlin counties, which are located in central Taiwan. However, high soil contents of nickel and chromium (P <0.001) in central Taiwan also coincided with the high-risk areas of OC incidence. In particular, Changhua county has incurred several decades of serious heavy-metal pollution, with inhabitants living in polluted areas having high-risk exposure to these metals. Results of this study suggest that, in addition to BQC and CS, anthropogenic pollution may profoundly impact the complexity of OC aetiology in central Taiwan.

Spatiotemporal analysis and mapping of oral cancer risk in changhua county (taiwan): an application of generalized bayesian maximum entropy method.

PURPOSE: Incidence rate of oral cancer in Changhua County is the highest among the 23 counties of Taiwan during 2001. However, in health data analysis, crude or adjusted incidence rates of a rare event (e.g., cancer) for small populations often exhibit high variances and are, thus, less reliable. METHODS: We proposed a generalized Bayesian Maximum Entropy (GBME) analysis of spatiotemporal disease mapping under conditions of considerable data uncertainty. GBME was used to study the oral cancer population incidence in Changhua County (Taiwan). Methodologically, GBME is based on an epistematics principles framework and generates spatiotemporal estimates of oral cancer incidence rates. In a way, it accounts for the multi-sourced uncertainty of rates, including small population effects, and the composite space-time dependence of rare events in terms of an extended Poisson-based semivariogram. RESULTS: The results showed that GBME analysis alleviates the noises of oral cancer data from population size effect. Comparing to the raw incidence data, the maps of GBME-estimated results can identify high risk oral cancer regions in Changhua County, where the prevalence of betel quid chewing and cigarette smoking is relatively higher than the rest of the areas. CONCLUSIONS: GBME method is a valuable tool for spatiotemporal disease mapping under conditions of uncertainty.

Incidence of oral cancer in relation to nickel and arsenic concentrations in farm soils of patients' residential areas in Taiwan.

BACKGROUND: To explore if exposures to specific heavy metals in the environment is a new risk factor of oral cancer, one of the fastest growing malignancies in Taiwan, in addition to the two established risk factors, cigarette smoking and betel quid chewing. METHODS: This is an observational study utilized the age-standardized incidence rates of oral cancer in the 316 townships and precincts of Taiwan, local prevalence rates of cigarette smoking and betel quid chewing, demographic factors, socio-economic conditions, and concentrations in farm soils of the eight kinds of heavy metal. Spatial regression and GIS (Geographic Information System) were used. The registration contained 22,083 patients, who were diagnosed with oral cancer between 1982 and 2002. The concentrations of metal in the soils were retrieved from a nation-wide survey in the 1980s. RESULTS: The incidence rate of oral cancer is geographically related to the concentrations of arsenic and nickel in the patients' residential areas, with the prevalence of cigarette smoking and betel quid chewing as controlled variables. CONCLUSIONS: Beside the two established risk factors, cigarette smoking and betel quid chewing, arsenic and nickel in farm soils may be new risk factors for oral cancer. These two kinds of metal may involve in the development of oral cancer. Further studies are required to understand the pathways via which metal in the farm soils exerts its effects on human health.

Combining a finite mixture distribution model with indicator kriging to delineate and map the spatial patterns of soil heavy metal pollution in Chunghua County, central Taiwan.

This study identifies the natural background, anthropogenic background and distribution of contamination caused by heavy metal pollutants in soil in Chunghua County of central Taiwan by using a finite mixture distribution model (FMDM). The probabilities of contaminated area distribution are mapped using single-variable indicator kriging and multiple-variable indicator kriging (MVIK) with the FMDM cut-off values and regulation thresholds for heavy metals. FMDM results indicate that Cr, Cu, Ni and Zn can be individually fitted by a mixture model representing the background and contamination distributions of the four metals in soil. The FMDM cut-off values for contamination caused by the metals are close to the regulation thresholds, except for the cut-off value of Zn. The receiver operating characteristic (ROC) curve validates that indicator kriging and MVIK with FMDM cut-off values can reliably delineate heavy metals contamination, particularly for areas lacking background information and high heavy metal concentrations in soil.

Assessing impacts of typhoons and the Chi-Chi earthquake on Chenyulan watershed landscape pattern in central Taiwan using landscape metrics.

The Chi-Chi earthquake (ML=7.3) occurred in the central part of Taiwan on September 21, 1999. After the earthquake, typhoons Xangsane and Toraji produced heavy rainfall that fell across the eastern and central parts of Taiwan on November 2000 and July 2001. This study uses remote sensing data, landscape metrics, multivariate statistical analysis, and spatial autocorrelation to assess how earthquake and typhoons affect landscape patterns. It addresses variations of the Chenyulan watershed in Nantou County, near the earthquake's epicenter and crossed by Typhoon Toraji. The subsequent disturbances have gradually changed landscape of the Chenyulan watershed. Disturbances of various types, sizes, and intensities, following various tracks, have various effects on the landscape patterns and variations of the Chenyulan watershed. The landscape metrics that are obtained by multivariate statistical analyses showed that the disturbances produced variously fragmented patches, interspersed with other patches and isolated from patches of the same type across the entire Chenyulan watershed. The disturbances also affected the isolation, size, and shape-complexity of patches at the landscape and class levels. The disturbances at the class level more strongly affected spatial variations in the landscape as well as patterns of grasslands and bare land, than variations in the watershed farmland and forest. Moreover, the earthquake with high magnitude was a starter to create these landscape variations in space in the Chenyulan watershed. The cumulative impacts of the disturbances on the watershed landscape pattern had existed, especially landslides and grassland in the study area, but were not always evident in space and time in landscape and other class levels.