Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: from the perspective of upstream and downstream wastewater-based epidemiology (WBE).

Recently, many efforts have been made to address the rapid spread of newly identified COVID-19 virus variants. Wastewater-based epidemiology (WBE) is considered a potential early warning tool for identifying the rapid spread of this virus. This study investigated the occurrence of SARS-CoV-2 in eight wastewater treatment plants (WWTPs) and their sewerage systems which serve most of the population in Taoyuan City, Taiwan. Across the entire study period, the wastewater viral concentrations were correlated with the number of COVID-19 cases in each WWTP (Spearman's r = 0.23-0.76). In addition, it is confirmed that several treatment technologies could effectively eliminate the virus RNA from WWTP influent (> 90%). On the other hand, further results revealed that an inverse distance weighted (IDW) interpolation and hotspot model combined with the geographic information system (GIS) method could be applied to analyze the spatiotemporal variations of SARS-CoV-2 in wastewater from the sewer system. In addition, socio-economic factors, namely, population density, land use, and income tax were successfully identified as the potential drivers which substantially affected the onset of the COVID-19 outbreak in Taiwan. Finally, the data obtained from this study can provide a powerful tool in public health decision-making not only in response to the current epidemic situation but also to other epidemic issues in the future.

Differentiating the Spatiotemporal Distribution of Natural and Anthropogenic Processes on River Water-Quality Variation Using a Self-Organizing Map With Factor Analysis.

To elucidate the historical improvement and advanced measure of river water quality in the Taipei metropolitan area, this study applied the self-organizing map (SOM) technique with factor analysis (FA) to differentiate the spatiotemporal distribution of natural and anthropogenic processes on river water-quality variation spanning two decades. The SOM clustered river water quality into five groups: very low pollution, low pollution, moderate pollution, high pollution, and very high pollution. FA was then used to extract four latent factors that dominated water quality from 1991 to 2011 including three anthropogenic process factors (organic, industrial, and copper pollution) and one natural process factor [suspended solids (SS) pollution]. The SOM revealed that the water quality improved substantially over time. However, the downstream river water quality was still classified as high pollution because of an increase in anthropogenic activity. FA showed the spatiotemporal pattern of each factor score decreasing over time, but the organic pollution factor downstream of the Tamsui River, as well as the SS factor scores in the upstream major tributary (the Dahan Stream), remained within the high pollution level. Therefore, we suggest that public sewage-treatment plants should be upgraded from their current secondary biological processing to advanced treatment processing. The conservation of water and soil must also be reinforced to decrease the SS loading of the Dahan Stream from natural erosion processes in the future.

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters.

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.

Probabilistic health risk assessment for ingestion of seafood farmed in arsenic contaminated groundwater in Taiwan.

Seafood farmed in arsenic (As)-contaminated areas is a major exposure pathway for the ingestion of inorganic As by individuals in the southwestern part of Taiwan. This study presents a probabilistic risk assessment using limited data for inorganic As intake through the consumption of the seafood by local residents in these areas. The As content and the consumption rate are both treated as probability distributions, taking into account the variability of the amount in the seafood and individual consumption habits. The Monte Carlo simulation technique is utilized to conduct an assessment of exposure due to the daily intake of inorganic As from As-contaminated seafood. Exposure is evaluated according to the provisional tolerable weekly intake (PTWI) established by the FAO/WHO and the target risk based on the US Environmental Protection Agency guidelines. The assessment results show that inorganic As intake from five types of fish (excluding mullet) and shellfish fall below the PTWI threshold values for the 95th percentiles, but exceed the target cancer risk of 10(-6). The predicted 95th percentile for inorganic As intake and lifetime cancer risks obtained in the study are both markedly higher than those obtained in previous studies in which the consumption rate of seafood considered is a deterministic value. This study demonstrates the importance of the individual variability of seafood consumption when evaluating a high exposure sub-group of the population who eat higher amounts of fish and shellfish than the average Taiwanese.

Assessing and managing the health risk due to ingestion of inorganic arsenic from fish and shellfish farmed in blackfoot disease areas for general Taiwanese.

This paper assesses health risks due to the ingestion of inorganic arsenic from fish and shellfish farmed in blackfoot disease areas by general public in Taiwan. The provisional tolerable weekly intake of arsenic set by FAO/WHO and the target cancer risk assessment model proposed by USEPA were integrated to evaluate the acceptable consumption rate. Five aquacultural species, tilapia (Oreochromis mossambicus), milkfish (Chanos chanos), mullet (Mugil cephalus), clam (Meretrix lusoria) and oyster (Crassostrea gigas) were included. Monte Carlo analysis was used to propagate the parameter uncertainty and to probabilistically assess the health risk associated with the daily intake of inorganic As from farmed fish and shellfish. The integrated risk-based analysis indicates that the associated 50th and 95th percentile health risk are 2.06×10(-5) and 8.77×10(-5), respectively. Moreover, the acceptable intakes of inorganic As are defined and illustrated by a two dimensional graphical model. According to the relationship between C(inorg) and IR(f) derived from this study, two risk-based curves are constructed. An acceptable risk zone is determined (risk ranging from 1×10(-5) to 6.07×10(-5)) which is recommended for acceptable consumption rates of fish and shellfish. To manage the health risk due to the ingestion of inorganic As from fish and shellfish in BFD areas, a risk-based management scheme is derived which provide a convenient way for general public to self-determine the acceptable seafood consumption rate.

Determining the probability of arsenic in groundwater using a parsimonious model.

Spatial distributions of groundwater quality are commonly heterogeneous, varying with depths and locations, which is important in assessing the health and ecological risks. Owing to time and cost constraints, it is not practical or economical to measure arsenic everywhere. A predictive model is necessary to estimate the distribution of a specific pollutant in groundwater. This study developed a logistic regression (LR) model to predict the residential well water quality in the Lanyang plain. Six hydrochemical parameters, pH, NO3- -N, NO2- -N, NH+ -N, Fe, and Mn, and a regional variable (binary type) were used to evaluate the probability of arsenic concentrations exceeding 10 microg/L in groundwater. The developed parsimonious LR model indicates that four parameters in the Lanyang plain aquifer, (pH, NH4+, Fe(aq), and a component to account for regional heterogeneity) can accurately predict probability of arsenic concentration > or =1 microg/Lin groundwater. These parameters provide an explanation for release of arsenic by reductive dissolution of As-rich FeOOH in NH4+ containing groundwater. A comparison of LR and indicator kriging (IK) show similar results in modeling the distributions of arsenic. LR can be applied to assess the probability of groundwater arsenic at sampled sites without arsenic concentration data apriori. However, arsenic sampling is still needed and required in arsenic-assessment stages in other areas, and the need for long-term monitoring and maintenance is not precluded.

Assessing carcinogenic risks associated with ingesting arsenic in farmed smeltfish (Ayu, Plecoglossus altirelis) in aseniasis-endemic area of Taiwan.

This study spatially analyzed potential carcinogenic risks associated with ingesting arsenic (As) contents in aquacultural smeltfish (Plecoglossus altirelis) from the Lanyang Plain of northeastern Taiwan. Sequential indicator simulation (SIS) was adopted to reproduce As exposure distributions in groundwater based on their three-dimensional variability. A target cancer risk (TR) associated with ingesting As in aquacultural smeltfish was employed to evaluate the potential risk to human health. The probabilistic risk assessment determined by Monte Carlo simulation and SIS is used to propagate properly the uncertainty of parameters. Safe and hazardous aquacultural regions were mapped to elucidate the safety of groundwater use. The TRs determined from the risks at the 95th percentiles exceed one millionth, indicating that ingesting smeltfish that are farmed in the highly As-affected regions represents a potential cancer threat to human health. The 95th percentile of TRs is considered in formulating a strategy for the aquacultural use of groundwater in the preliminary stage.

Evaluation of potential health risk of arsenic-affected groundwater using indicator kriging and dose response model.

This study analyzed the potential health risk associated with the ingestion of arsenic-affected groundwater in the arseniasis-endemic Lanyang plain of northeastern Taiwan. Indicator kriging was used to estimate arsenic concentrations in groundwater. Target cancer risk (TR) and dose response functions were adopted to evaluate the potential health risk based on the estimated arsenic concentration distributions. The estimated arsenic concentrations in groundwater reveal that arsenic concentrations (>50 microg/L) in well water are high in six townships - JiaoSi, YiLan, JhungWei, WuJie, DonShan and LouDon. Highest arsenic concentrations (70.32 microg/L) are in the YiLan and the JhungWei townships. The estimated TR values at the arsenic-affected townships are ten times more than an acceptable standard (10(-6)). The largest TR values are 145.5 and 91.2 times higher than an acceptable standard for males and females, respectively. The estimated annual mortalities by arsenic-induced internal cancers occur in the YiLan township (ten cases), LouDon (five cases), WuJie (three cases), JhungWei (two cases) and DonShan (one case). The highest number of mortalities per year in the study area is 24. Residents of the six townships with high arsenic-affected groundwater should use tap water as drinking water and use groundwater only for other purpose. The well water in other townships in the Lanyang plain has no adverse effects on human health.