CE 510 Hazardous Waste Engineering Department of Civil Engineering Southern Illinois University Carbondale Instructor: Jemil Yesuf Dr. L.R. Chevalier Lecture Series 4: Source Analysis Course Goals Review the history and impact of environmental laws in the United States Understand the terminology, nomenclature, and significance of properties of hazardous wastes and hazardous materials Develop strategies to find information of nomenclature, transport and behavior, and toxicity for hazardous compounds Elucidate procedures for describing, assessing, and sampling hazardous wastes at industrial facilities and contaminated sites Predict the behavior of hazardous chemicals in air, surface impoundments, soils, groundwater and treatment systems Assess the toxicity and risk associated with exposure to hazardous chemicals Apply scientific principles of hazardous wastes management, remediation and treatment Fundamental Concepts Covered Materials Balance/Waste Audits Hazardous Waste Site Assessments Source Sampling: Statistics Materials Balance/Waste Audits Water treatment chemicals Laboratory chemical wastes Industrial Facility Catalyst Lubricating Oils Maintenance Material Spent Chemicals Losses: Incorporated into Product Volatilization Spillage Spent and dirty filters Waste Oil See Figure 4.2 p. 214 Materials Balance/Waste Audits Overall Strategy Convert to mass Convert to mass flux Cannot add concentrations Mass In – Mass Out + Rxn = Accum. Problem 4.2 in Text The following records are available for a small company that manufactures semi-conductors. The chemical used most at the plant is TCA, and the primary loss mechanism is volatilization. Using the following data, estimate the maximum volatilization rate. Note: S.G. of TCA = 1.339 Acquisitions: Date Vol. (L) 8-Jan 208 6-Feb 833 26-Feb 416 15-Mar 208 11-Apr 208 2-May 625 Purity (%) 92 95 88 97 90 95 RCRA Manifests: Date Waste No. 28-Feb F001 20-Apr F001 21-May F001 30-May F001 Vol.(L) 1140 386 462 1287 Discharges: Wastewater characteristics: 18.9 x 106 L/day (5 MGD) at 0.5 mg/L TCA C (%) 22 13 45 36 Solution 1. Acquisitions: (208 L)(1.339 kg/L)(0.92) + . . . = 3122 kg 2. Wastewater discharges = (18.9 x 106 L/day)(143 days)(0.5 mg/L) (1kg/106 mg) = 1351 kg 3. RCRA Manifests: = (1140 L)(1.339 kg/L)(0.22) + . . . = 1302 kg Solution 4. Total Mass of TCA leaving the facility: = 1351 kg + 1302 kg = 2653 kg 5. Total TCA volatilized: = 3122 kg – 2653 kg = 469 kg 6. Volatilization rate: = (469 kg)/(143 days) = 3.3 kg/day ......end of example Problem 4.3 in Text A plastic formulation facility receives one of its synthetic chemicals, dimethyl phthalate, by steady flow through a supply pipe at a flow rate of 200 L/day. The dimethyl phthalate is used in synthesis reactors for making a plasticized polymer at a rate of 0.8 moles/min. Partially reacted polymers are precipitated from specific reactions containing fluids with 1200 mg/kg (dry wt.) dimethyl phthalate. If 30,000 kg of the sludge (with an average water content of 85%) are generated each day, how much dimethyl phthalate is unaccounted for? Note: S.G. = 1.191, MW = 194 g/mole Solution 1. Mass balance: In – Out + Rxn = Accum. If Out = 0 then In + Rxn = Accumulated 2. Determine the mass of dimethyl phthalate supplied (200 L/day)(1.191 kg/L) = 238.2 kg/d Solution 3. Determine the mass lost due to the reaction (0.8 moles/min)(194 g/mol)(60 min/hr)(24 hr/d) = 223.5 kg/d In + (-Rxn) = 238.2 – 223.5 = 14.7 kg/d 4. Determine the mass of dimethyl phthalate in the sludge (1200 mg/kg)(30,000 kg/d)(0.15) = 5.4 x 106 mg/d = 5.4 kg/d 5. Mass unaccounted for: 14.7 kg/d – 5.4 kg/d = 9.3 kg/d ......end of example Hazardous Waste Site Assessments Phase I Paper research (background search) Chemical inventory evaluation Interviews with current and former personnel Interviews with community Regulatory agency record searches Title searches Areal photographs Permits and violations If suspicions of hazardous waste contamination are confirmed, Phase II is warranted Hazardous Waste Site Assessments Phase II Finalizing any searches that were incomplete in Phase I Detailed evaluation of pathways and potential receptors Random sampling and analysis If contamination occurred, Phase III Hazardous Waste Site Assessments Phase III Determine the extent of contamination Area, volume, concentration With appropriate sampling designs, contaminant concentration data over depth and area Provides sufficient information to assess the site hazard (need for site cleanup) Provides criteria for the design of remedial process Source Sampling: Statistics Homogeneous source Aqueous waste in a drum No concentration gradients No layering from density difference One sample represents the waste Most hazardous waste is heterogeneous Sludges Soils Lagoons Characterization of the waste is expensive Reliable analysis with sophisticated instrumentation Quality Assurance Report preparation Source Sampling: Statistics Two fundamental statistical concepts for sampling plan: Accuracy How close a measured value is to the true value Error allowed, a Corresponding parameter is the confidence level (1-a) Precision Measure of the variability between samples D, deviation from the true value – precision requirement Source Sampling: Statistics Population True value of global data A number that describes a population is called a parameter Parameters include Mean, m; Variance, s2 ; Standard deviation, s Sample Data set collected from population A number that describes a sample is called a statistic statistics include Average, x; Sample variance, s2 ; Sample Standard deviation, S. Source Sampling: Statistics Why sample the source material (population)? Sampling errors and analytical errors? Which one is greater and why? If we take a sample and calculate a statistic, we often use that statistic to infer something about the population from which the sample was drawn. Source Sampling: Statistics Degrees of freedom: A parameter used in statistical distributions that represents the sample size minus the number of parameters being estimated df = n-1 x Xi n S 2 X i X n 1 2 Source Sampling: Statistics Sampling procedures Search sampling (historic information) Using prior knowledge of the site Probability sampling Designed so that samples which have an equal chance of being chosen are collected Simple random sampling Stratified random sampling A series of simple random sampling stacked on top of one another Others Probability Sampling Based on the t-distribution A probability density function that is used to evaluate sample means when the population variance (σ2) is not known but can be estimated by S2. This value is found in tables. X m Need to know the size of the t S n sample set and the confidence level desired. i.e., t = (df, α) See Appendix E. Determining sampling points Divide source area into a grid of sampling units (blocks) Assign a number to each block of the grid Use a random number generator to determine sampling points Determining the number of samples Initial or previous data Determine average and S2 Determine the student’s two sided t with n-1 degrees of freedom for a confidence level of (1-a)% Determine the regulatory threshold, RT (e.g. toxicity characteristic leaching protocol (TCLP)) 2 n t S D 2 2 where D X RT Confidence Interval (CI) CI X t a S 2 n 1 2 This parameter is needed to determine whether or not a hazardous chemical is present at concentrations which are measured below RT. Procedure for the Simple Randomized Sampling of RCRA Hazardous Waste Sources Collect a 3-6 random samples to obtain preliminary estimates of the average and variance Estimate the minimum number of samples using a specified confidence interval 2 n t S D 2 2 where D X RT Using a sampling grid and random number assignments, collect and analyze at least the minimum number of samples from the waste source Procedure for the Simple Randomized Sampling of RCRA Hazardous Waste Sources Determine the average and variance from the detailed sampling plan If the sample mean is ≥ the regulatory threshold (RT), the compound is present in hazardous concentrations If the sample mean is ≤ RT Determine the confidence interval If the upper CI < RT, the compound is not present Class example from Text: A drying bed holding sludge from an electroplating process is to be sampled for cadmium content. The dimensions of the drying bed are 6 m X 6 m, and the sample volume will require an area 40 cm X 40 cm. Five preliminary samples were collected randomly with the following results: 25, 36, 49, 28, and 48 mg/kg Cd. Based on this information, develop a simple randomized sampling scheme. Determine (1) number of samples required for 95% confidence limits within 5 mg/kg of the sample mean, and (2) the location of the samples in the sludge bed. Solution For the five preliminary samples, Xbar 25 36 49 28 48 5 kg 5 S 2 (X i Xbar ) i 1 n 1 and S 123 11 . 1 37 mg 2 123 Cd Solution From the Student’s t table (Appendix E), for df =n-1=4, and using α = 0.025, t95% = 2.776. Note that 2α=5%, error level for 95% confidence level). The number of samples (n) is: n t 2 95 % D S 2 2 2 ( 2 . 776 ) (123 ) 5 2 round up to 38 samples . 37 . 9 samples Solution The number of sampling units in both directions is: 8 m/0.4 m = 20 unit, and 6 m/0.4 m = 15 units Total sampling units is 20 x 15 = 300. Then select 38 random number between 1 and 300. MS Excel has a built-in function RANDBETWEEN(). RANDBETWEEN(1, 300) at 38 cells will generate 38 sampling locations in the 20x15 grid. spreadsheet ......end of example Stratified Random Sampling Strategy involves dividing a site into layers or strata (subpopulations) Strata are evaluated separately Increases sampling precision for the entire population For soils, the strata are simply horizontal layers at different depths Stratified Random Sampling Mean for each strata is determined by: n yi i 1 y n The mean over all strata is: L y Nh y h / N h 1 where L = total number of strata Nh = total number of sampling units in the hth stratum N = total number of sampling units in all strata Stratified Random Sampling Sample variance within each stratum: V y h 2 Sh nh nh 1 nh y n 1 i yh 2 i 1 h Variance of the sample mean over all strata: 2 S 2 V y 2 N h h N h 1 n h 1 L Summary of Important Points and Concepts Waste audits, which are based on materials balance, can be used to determine losses from volatilization, spillage, authorized removals to secure landfills or incineration, or improper management. Waste audits also serve as a basis for waste minimization and pollution prevention plans. Assessment of contaminated sites is based on a multi-step approach, with each phase characterized by succeeding complexity. (Phase I, II, and III) Summary of Important Points and Concepts Source materials, such as soils and sludges, are most effectively sampled using probability sampling. Simplified random sampling is used in system which there is no gradient in contaminant concentration with depth. It is also the basis for probability sampling. Stratified random sampling is used to sample systems where different strata contain a range of concentrations.