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Spatiotemporal Analysis of Surface Water Tetrachloroethene in New Jersey

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##### Spatiotemporal Analysis of Surface Water Tetrachloroethene in New Jersey

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**Spatiotemporal Analysis ofSurface Water Tetrachloroethene in**New Jersey Presentation of the project of Yasuyuki Akita Temporal GIS Fall 2004**Agenda**• About Tetrachloroethene • Monitoring Data • Details of BME Method • BME Analysis • Results of BME Analysis • New Criterion • Model Comparison • Conclusion**About Tetrachloroethene**• Tetrachloroethene: C2Cl4 • Volatile organic compound • Nonflammable colorless liquid at room temperature • Ether-like odor • Synonym: Tetrachloroethylene, Perchloroethylene, and PCE**Use and Production**• Mainly Used for dry cleaning, chemical intermediates, and industrial solvent • PCE used in dry cleaning industry has been declining during 90s • Recent Demand: 763 million lb (1980) 318 million lb (1999)**Exposure pathway**• Primary route • Inhalation • Ingestion of contaminated food and water • Widely distributed in environment • 38% of surface water sampling sites in the U.S. • 771 of the 1430 National Priorities List sites • 154 of 174 surface water samples in N.J. (1977~1979)**Health Effect of Tetrachloroethene**• Acute Effect (inhalation exposure) • Dizziness, headache, sleepiness, confusion, nausea, difficulty in speaking and walking, unconsciousness, and death • Chronic Effect (oral/inhalation exposure) • Detrimental effect to kidney and liver**Carcinogenicity**• Reasonably anticipated to be a human carcinogen (US DHHS) • Group 2A (Probably carcinogenic to humans) (IARC) • Animal studies: tumors in liver and kidney**Quality Standard for Tetrachloroethene**• Maximum Contaminant Level (MCL) in drinking water - 0.005 mg/L • Surface Water Quality Standard in New Jersey - 0.388 μg/L N.J. adopted more stringent standard**Monitoring Dataset for New Jersey**• Data Source • NJDEP/USGS Water Quality Network Website • EPA STORET database • Data used in this study • 369 measured values • 171 monitoring stations • From 1999 to 2003**Monitoring Data – Histogram**Raw Data Log-Transformed Data**What we want to know is …**• Challenge of our research • Assess all river reaches • Taking into account the space/time variability Framework for the space/time estimation Bayesian Maximum Entropy (BME) analysis of TGIS**Space/Time Random Field**• The concentration field is modeled in terms of Space/Time Random Field (S/TRF) • Collection of random variables S/TRF: Collection of all possible realization • Stochastic characterization of S/TRF is provided by multivariate PDF**Knowledge Base**• General Knowledge Base: G • Describe global characteristics of the random field of interest • Expressed as statistical moments • Site-specific knowledge Base: S • Available monitoring data over the space/time domain of interest • Total Knowledge Base: K • K = G∪ S**General Knowledge Base G**Mean Trend • Global trend of the S/TRF of interest • Covariance • Measure of dependency between two points • Sill = variance = covariance(r=0) • Range shows the extent that co-variability exists**BME analysis of Temporal GIS**• Prior stage • Examine all general knowledge base G and calculate Prior PDF • Integration stage • Update Prior PDF using Bayesian conditionalization on the site-specific knowledge base S and obtain posterior PDF • Interpretive stage • Obtain estimation value from Posterior PDF**BME analysis of Temporal GIS**• General KB Prior PDF • Update prior PDF with Site-specific KB • Bayesian conditionalization • Posterior PDF is given by conditional probability**t**t Posterior PDF at estimation point long long lati lati fK(ck) Estimation Value Summary of BME analysis of TGIS • General KB • Mean trend • Covariance • Site-Specific KB • Hard Data BME Estimation Point Data Point**S/TRF for Log-transformed PCE concentration**• S/TRF representing Log-tranformed concentration: • Residual field describes purely stochastic aspect of the concentration field Mean Trend Residual Field**Mean Trend of Log-transformed concentration field**• Mean trend consist of two components • Purely spatial component • Purely temporal component • Each component is calculated by exponential smoothing**Mean Trend – Temporal Component**• Increase from Jan. 1999 to Jan. 2003 • Decrease from Jan. 2003~**Mean Trend – Spatial Component**• Contaminated Area • Northeastern region • Southwestern region**Homogeneous/Stationary S/TRF**Log-transformed data • Homogeneous/Stationary Random Field • Its mean trend is constant • Its covariance is only function of the spatial lag and temporal lag Removing the mean trend Residual data for S/TRF:**Experimental Data**Covariance Model Covariance Surface**BME Estimation – Spatial Distribution**(Apr. 15, 2002)**BME Estimation – Contaminated Area**Area above the quality standard: 0.388μg/L (Apr. 15, 2002) • BME mean estimate • Upper bound of the BME 68% confidence interval • Upper bound of the BME 95% confidence interval**BME Estimation – Along River Stream**• Equidistance points along river stream • More accurate estimation for surface water**BME Estimation – Along River Stream**• Fraction of river miles that does not attain the quality standard**Assessment Criterion**• S/TRF is characterized by Posterior PDF • Area under the curve = Probability Prob[PCE>QSTD]=Area under the curve (QSTD<PCE<∞)**Assessment Criterion**Prob[Non-Attainment]=Prob[PCE>0.388μｇ] • Highly Likely in Attainment • Prob[Non-Attainment]<10% • Highly Likely in Non-Attainment • Prob[Non-Attainment]>90% • Non-Assessment • 10%≦Prob[Non-Attainment]≦90% • More Likely Than Not in Non-Attainment • Prob[Non-Attainment]>50%**Identifying Contaminated WMAs**• The state of New Jersey is divided into 20 Watershed Management Area (WMA) • Assess which part of the state is contaminated • Contribution of each WMA to the fraction of river miles assessed as • Highly Likely in Non-Attainment • More Likely Than Not in Non-Attainment**Contribution of WMAs**• Highly Likely in Non-Attainment**Contribution of WMAs**• More Likely Than Not in Non-Attainment