Investigating Background Contaminant Levels in San Francisco ...

Investigating Background Contaminant Levels in San Francisco ...

Background Trace Element Concentrations in the Franciscan Complex, San Francisco, CA MS Thesis Defense Megan Simpson March 16, 2004 The Problem Superfund clean-up sites are overwhelming problem in US

-Hunters Point Shipyard -Presidio To assess a site for contamination, background trace element levels need to be determined Introduction This study examines background trace element levels in the Franciscan Complex (chert, sandstone, sandstone, greenstone, serpentinite)

Samples analyzed for trace element levels (chromium, cobalt, nickel, lead, strontium) strontium) Performed statistical analyses and created trace element distribution maps Purpose Will aid in understanding of the distribution of background trace elements data reflects naturally occurring levels found in

native bedrock Assist environmental clean-up projects by providing source of baseline data for measuring soil quality Expand current trace element level database Previous Research Work by Kearney Foundation in 1996 looked looked at trace elements in soil

often often referenced in remediation remediation projects, land use planning only only two samples close to San Francisco Area Work by Schlocker in 1974 looked looked at potassium feldspar in sandstone fewer fewer samples (5-7) for each rock type

My work enhances the range of sample locales and quantities What elements are we looking for? Previous Previous work work shows shows Cr, Cr, Co,

Co, Ni, Ni, Pb Pb and and Sr Sr to to be be prominent prominent in in soil soil and

and rock rock within within SF SF Presidio Presidio and and Hunters Hunters Point Point have have high

high levels levels much much time time and and energy energy dedicated dedicated to to cleancleanup up of

of these these sites sites Geologic Background San Francisco is part of the Mesozoic Franciscan Complex, which formed in accretionary wedge Franciscan Complex Source: U.S. Geological Survey

Subduction zone ~200-80 mya Franciscan Complex Sandstone Greenstone Melange up to 10,000 ft thick Also chert, shale, limestone, conglomerate

Serpentinite Depositional Environment Most likely a low latitude marine environment: marine fossils in some clastic rocks, Radiolaria in chert highly fractured, interbedded greenstones (rapid cooling of hot lava) Conglomerate and massive graywacke beds created by turbidity currents

further evidence: shale layers between graded beds, small scale current bedding, ripple marks Methods and Materials Prior to sampling aerial photographs Sampling Samples were collected from 45 accessible outcrops around SF

Clean hands/dirty hands technique (minimizes cross contamination) At least 5 fresh rock chips collected from outcrop and pooled Latitude/longitude of location noted with GPS unit Aerial Photography USGS collection from 1940s-1970s Provided insight into

previous industrial activity Showed sampling areas free from major contaminating factors No evidence of alteration of background levels Presidio Area

Presidio Potrero Hill Twin Peaks/ Glen Park McLaren Park 45 sample locations

Chert Sample Locations 15 samples Glen Canyon Park, Twin Peaks light tan to red distinct bedded layers with folding Greenstone Sample Locations 8 samples McLaren Park, Corona

Heights, Twin Peaks highly fractured extensively weathered dark gray to dark reddish-brown Sandstone Sample Locations 10 samples McLaren park, Castro large, thick bedded outcrops

randomly fractured highly weathered brown to gray Serpentinite Sample Locations 12 samples Potrero Hill, Presidio, Baker Beach greenish-gray to blue highly weathered, sheared

soft, friable Geochemical Analysis 48 samples submitted to SGS Mineral Services in Toronto (45 plus 2 blind duplicates and 1 reference sample) Tested for 40 trace elements using ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry) Samples decomposed using mixture of HCl, Nitric, Perchloric, HF Digestion is aspirated and elemental emission signal is

measured for elements Results and Discussion Identification of outcrop samples Geochemical results Statistical analysis Mann-Whitney and ANOVA Developed trace element distribution maps Identification of Outcrop Samples Field Identification

Thin sections from each rock type (Univ of Utah) X-ray Diffraction (XRD) evaluation Thin Sections (USGS Petrographic Microscope) Thin Sections (USGS Petrographic Microscope) X-ray Diffraction

Scattering of x-rays from a crystal where resulting interference pattern determines structure of crystal Performed by Mineral Services Lab at USGS Showed minerals consistent with each rock type Serpentinite (lizardite, chrysotile) Chert (quartz) Sandstone (quartz) Greenstone (albite, diopside) XRD of Chert

Count/s 7000 Quartz 0 40 2 theta Geochemical Results

Results for Cr, Co, Pb, Ni, Sr compared to data from Schlocker show: Chromium Strontium Cobalt Nickel Lead 4.5 4

3.5 Frequency 3 2.5 2 1.5 1 Statistical analysis comparing my data to

Schlockers data 0.5 0 Assists in description and analysis of data generated descriptive statistics (mean, std dev, ranges, etc.) histograms (show distribution and observations of sample) tests for normality (data fits bell shaped curve)

Komolgorov-Smirnov, Shapiro-Wilk Q plots (compare data to linear ideal) Statistical Testing If data is normally distributed, randomly collected, Student t test can be used If data is not normally distributed, MannWhitney U test is appropriate Tests on Schlocker data showed data not normally distributed, therefore Mann-Whitney U analyses most appropriate to demonstrate

significant differences between datasets Mann-Whitney U Test Data obtained from two random samples (n1 and n2) Samples are combined, each value assigned a rank (smallest is rank 1, largest is rank n1+ n2) U statistic based on totals of ranks (Ta, Tb) The smaller value of either Ta or Tb, the greater the evidence that samples from different populations Tests were performed using 95% confidence level (95% of all samples give interval that includes the

mean, 5% would give interval that does not) Hypothesis Null hypothesis states: the difference between the mean ranks of the datasets is not statistically significant OR average level of specific trace element found in given rock type in Schlockers data is not statistically different from average level of same element, same rock

type found in my data Comparison of Trace Element Levels between Schlocker and Simpson Datasets using Mann Whitney Test Chromium significant differences seen in serpentinite (means of 564 vs. 1384 mg/kg) and chert (means of 3 vs. 22 mg/kg) data no significant differences seen in greenstone and sandstone Cobalt

significant differences seen in sandstone (means of 25 vs. 7 mg/kg) and serpentinite (means of 59 vs. 81 mg/kg) no significant differences seen in chert and greenstone Nickel significant differences seen in all rock types: chert (means of 43 vs. 22 mg/kg), greenstone (means of 180 vs. 46 mg/kg), sandstone (means of 57 vs. 27 mg/kg), serpentinite (means of 3000

vs. 1773 mg/kg) Lead significant differences seen in chert (means of 0.25 vs. 40 mg/kg) and sandstone (means of 2.6 vs. 14 mg/kg) no test on greenstone and serpentinite Strontium significant difference seen only in chert (means of 5 vs. 38 mg/kg) ANOVA

Determines significant differences in the means of two or more datasets Performed on my data comparing means of same trace element between four rock types Data is normally distributed, equal variances, from randomly collected samples Null hypothesis: means of sample populations are statistically equal Mean (mg/kg) and Standard Deviation for each

rock type in conjunction with ANOVA results a Identical letters indicate no significant difference at the 95% confidence level. b,c Non-identical letters indicate a significant difference at the 95% confidence level Chromium and nickel concentrations are ~15-35 times higher in serpentinite Trace Element Distribution Maps

Created to illustrate levels of trace elements throughout San Francisco Within sampled areas, data is accurate Outside of sampled areas (west, upper northeast, southeast corners) data is interpolated ArcInfo/ArcMap 8.3 Inverse Distance Weighted (IDW) interpolation method assumes each sample point has a local influence that decreases with distance Chromium Distribution Map

N Cobalt Distribution Map Strontium Distribution Map Lead Distribution Map Nickel Distribution Map

Conclusion This study: enhances understanding of background trace element distribution in Franciscan Complex will assist in development of future environmental clean-up studies expands trace element database Improvements to this dataset:

increasing sample size/location examining other trace elements sampling soil

Recently Viewed Presentations

  • C H E M I S T R Y - Austin Community College

    C H E M I S T R Y - Austin Community College

    Quality Assurance / Quality Control An Overview for MLAB 2360 - Clinical 1 * * * * * * * * * Quality Assurance & Quality Control Common Westgard rules 41s Four consecutive control measurements exceed the same mean plus...
  • CRP Payment System and Job Development Process

    CRP Payment System and Job Development Process

    CRP Intake Meeting & Plan for Employment Provider Services. After Referral Meeting CRP meets in person with client to complete intake process and together write CRP Plan for Employment Provider Services. CRP provides a copy of the plan to the...
  • Free Will, Moral Responsibility and the Physical ... - Naturalism

    Free Will, Moral Responsibility and the Physical ... - Naturalism

    Worldview Naturalism. Advisories and Disclaimers. Causal Determinism. Fully Caused Creatures. Agent Determinism: Persons as Causers. The Replay: Could You Have Done Otherwise? The Contra-Causal Assumption. Explanation vs. Justification. Compassion and Control. Addiction and Other Apps. Want to release your inner...
  • Introduction to Intel x86 Assembly and Architecture

    Introduction to Intel x86 Assembly and Architecture

    Introduction to Intel x86 Assembly, Architecture, Applications, & Alliteration ... Different OS start it at different addresses by convention A stack is a Last-In-First-Out (LIFO/FILO) data structure where data is "pushed" on to the top of the stack and "popped"...
  • Frank-Wolfe optimization insights in machine learning

    Frank-Wolfe optimization insights in machine learning

    Frank-Wolfe optimization insights in machine learning. Simon . Lacoste-Julien. INRIA / École Normale Supérieure. SIERRA Project Team. SMILE- November 4th 2013
  • Body Actions - Ms Wasif's Classes 2013 (RSC)

    Body Actions - Ms Wasif's Classes 2013 (RSC)

    Body Actions. Year 7 Dance Theory. Elements of movement. The elements of movement provides us with a way to explain a dance based on theory. Movement can be interpreted based on time, space and energy. This can be applied by...
  • The Practice of Biblical Worship: Submission - BibleTalk.tv

    The Practice of Biblical Worship: Submission - BibleTalk.tv

    The sacrifice you desire is a broken spirit, you will not reject a broken and repentant heart O God.- Psalms 51:12The Lord is close to the brokenhearted. ... Because of submission to God's will which is the true practice of...
  • SUPERFUND JOB TRAINING INITIATIVE Melissa Friedland, SuperJTI Program

    SUPERFUND JOB TRAINING INITIATIVE Melissa Friedland, SuperJTI Program

    40-hr HAZWOPER. OSHA-10. CPR/First Aid. We had a great group of recruits and they worked really hard throughout the training. Trainees completed courses in environmental justice, interpersonal communication, cultural competence and effective work habits. EPA contractor Skeo Solutions provided this...