Appendix: Laboratory Testing Methods A.1 Heavy Metals Testing Based on Method 200.8 (USEPA 1994), nitric and hydrochloric acid digestion was carried out to extract total recoverable heavy metals from the collected build-up, atmospheric deposition and air samples. Hot Block digester was used for the digestion. Hot Block digester provides an efficient method for digesting water, wastewater, soil and sludge samples for metals analysis (Environmental Express 2005). This digestion system allows samples to be digested in a small area with minimum heat loss. Samples were digested at 95 C for 2.5 h without boiling inside a fume cupboard. After allowing samples to reach room temperature, the samples were made up to the original volume. Subsequently, samples were filtered using 0.45-micron syringe filters followed by adding internal standards, including the blanks and certified reference material (CRM). Detection and determination of heavy metals were carried out by Inductively Coupled Plasma Mass Spectrometer (ICP-MS). ICP-MS was selected after considering its ability to detect heavy metals even at low concentrations (ranging from 0.001 to 0.005 mg/l). Firstly, the instrument was tuned by testing a specially made solution prepared by mixing beryllium, magnesium, cobalt, indium and lead stock solutions in 1% nitric acid to produce a concentration of 100 μg/l of each element. This solution is referred to as a tuning solution. Tuning solution was used to determine acceptable instrument performance prior to calibration and sample analysis. After satisfactory tuning, sample sequence including calibration standards were prepared. Consequently, samples in the liquid matrix were introduced into the machine by pneumatic nebulisation into radio frequency plasma where energy transfer processes cause atomisation and ionisation. The ions were extracted from the plasma through a differentially pumped vacuum interface and separated based on their mass-to-charge ratio by a quadrupole mass spectrometer. The ions transmitted through the quadrupole were detected by an electron multiplier. The Author(s) 2018 J.M.A. Gunawardena et al., Influence of Traffic and Land Use on Urban Stormwater Quality, SpringerBriefs in Water Science and Technology, DOI 10.1007/978-981-10-5302-3 77
78 Appendix: Laboratory Testing Methods After the sample sequence was tested along with calibration standards, calibration curves were set up ensuring that the residual mean square (R 2 ) was greater than or equal to 0.98. The concentration of the targeted heavy metals in actual samples were calculated using already established calibration curves. Subsequently, CRM recovery for heavy metals was compared against values given in the standard certificate and was found to be within 85 115%, which was considered acceptable. This was one of the most important quality assurance checks. A.2 PAHs Testing PAHs were tested for samples in the atmosphere and build-up on road surfaces. Analysis was carried out as per Method TO-13A and Method 610 (USEPA 1999). (a) Air sample testing While particulate-bound PAHs were collected using a filter paper, gas phase PAHs were collected using polyurethane foam (PUF) sorbents. PUF sorbents and quartz filter papers were tested separately to determine the gas and particulate phase PAHs in the atmosphere as per TO-13A (USEPA 1999). The initial step was to extract half of the filter paper and PUF sorbent by Soxhlet extraction using 10% diethyl ether in hexane solvent. Before extraction, surrogate standards were added. The extract was concentrated by Kuderna-Danish (K-D) evaporator, followed by sodium sulphate cleanup using column chromatography to remove potential interferences prior to analysis by GC-MS. The sample was further concentrated by N 2 blow-down and then analysed by GC-MS. Prior to testing, internal standards were added to the samples, blanks and CRM. Method development was to detect all target PAHs with a uniquely identifiable peak in the chromatogram. It was found that temperature programming was one of the most important methods to achieve good separation of PAHs. Additionally, injection volume, flow rate of carrier gas, detection mode and its resolution were changed until optimum separation was achieved. The separation of 16 PAHs was a difficult exercise, as some PAHs have the same molecular weight, but different configurations and almost the same boiling points. However, after a number of trial runs, the test method was developed to the required level of accuracy so that all the target PAH compounds could be separated. Calibration was carried out with five concentration levels by diluting external standards. As recommended by the GC-MS user manual, standards were tested initially. Then samples were tested using already developed and calibrated test method. Subsequently, sample concentrations were calculated using data analysis software available with the GC-MS. As a part of the quality assurance procedure, CRM recovery for PAHs was compared against values given in the standard certificate and found to be within 85 115% as specified. (b) Road surface build-up sample testing Road surface build-up samples were tested to determine the PAHs present in the ground phase. Method 610 (USEPA 1999) was adopted to test build-up samples for PAHs. This is the method
Appendix: Laboratory Testing Methods 79 recommended for the analysis of organic compounds in municipal and industrial wastewaters. The testing procedure was similar to that for air sample testing. However, instead of Soxhlet extraction, liquid liquid extraction technique was used to extract build-up samples as specified in Method 610 (USEPA 1999). Herngren (2005) found that this is an efficient technique to extract PAHs in the liquid matrix. All the other steps were the same as that employed for the testing of PAHs in air samples. The extraction of PAHs was done using a 500 ml separatory funnel. As specified, a 100 ml aliquot from each sample was extracted with a 60 ml of extraction solvent. The sample aliquot was mixed with solvent in the separatory funnel for 2 min with periodic venting to release excess pressure. The separatory funnel was then kept for 10 min without disturbing so that the organic layer was separated. Subsequently, the organic layer was separated into a beaker by carefully regulating the bottom valve. The same sample was extracted three times with 60 ml of extraction solvent as described above.
References Environmental Express. 2005. HotBlockTM digestion system operation and instruction manual. Environmental Express. Herngren, L. 2005. Build-up and wash-off process kinetics of PAHs and heavy metals on paved surfaces using simulated rainfall. Brisbane: Queensland University of Technology. USEPA. 1994. Determination of trace elements in water and wasters by inductively coupled plasma-mass spectrometry-method 200.8. Cincinnati, OH: U.S. Environmental Protection Agency.. 1999. Compendium of methods for the determination of toxic organic compounds in ambient air. 2nd ed. Cincinnati, OH: U.S. Environmental Protection Agency. The Author(s) 2018 J.M.A. Gunawardena et al., Influence of Traffic and Land Use on Urban Stormwater Quality, SpringerBriefs in Water Science and Technology, DOI 10.1007/978-981-10-5302-3 81
Index A Adsorption, 3, 30, 74 75 Airborne particulate matter, 3 Antecedent dry day (ADD), 7 9, 18, 20, 22, 36 38, 40, 52, 59, 61 Anthropogenic activities, 18, 19, 25, 28, 30, 33, 36, 58 Atmospheric build-up, 18, 23, 24, 27 36, 38, 49, 51, 73 Atmospheric deposition, 3, 4, 8 9, 13, 17 19, 21 25, 27, 28, 36 38, 41, 45, 49, 51, 52, 57, 58, 72 74 Average daily traffic volume, 20, 29, 30, 38, 40, 42, 66 B Boundary conditions, 55, 57 59, 73 Build-up, 2 5, 7 13, 17, 18, 22 23, 25, 28, 40 46, 49, 51 53, 55 57, 59 63, 67, 72, 73, 75 Build-up rate, 22, 59, 61 Bulk deposition, 19, 20, 36 40, 49 C Cation exchange, 3, 75 Co-fraction, 59, 62, 63, 74 E EPA SWMM, 56, 58, 62, 67, 73 exhaust emission, 3, 4, 13, 38, 40, 52, 72 G Geographical information systems (GIS), 56, 73 Gold Coast City Council (GCCC), 57 H Heavy duty traffic volume (HDTV), 20, 29, 30, 33, 42, 46, 67 Heavy metal (HMs), 1 4, 8, 13, 23, 24, 28 32, 37, 41 45, 49, 51, 52, 55, 59, 63 65, 67, 71, 72, 74, 75 Heavy molecular weight PAH, 52, 72 Human health, 4, 6, 13, 32, 42, 52, 72, 74 I Influential factor, 2, 4, 9, 11, 17, 30, 40, 42, 74 L Land use, 1 5, 10, 17, 18, 20, 25, 27 53, 63, 64, 66, 68, 71 74 Light molecular weight PAHs, 32, 52, 71, 72 D Dry deposition, 7, 8, 19 20, 36 39, 49, 72, 74 M Mathematical modelling., 73 The Author(s) 2018 J.M.A. Gunawardena et al., Influence of Traffic and Land Use on Urban Stormwater Quality, SpringerBriefs in Water Science and Technology, DOI 10.1007/978-981-10-5302-3 83
84 Index Mean mass median aerodynamic diameter (MMMAD), 37 MIKE URBAN, 10, 56 Model for urban stormwater improvement conceptualization (MUSIC), 56 Model input parameters, 55, 57 Model schematisation, 55, 57, 58 Model selection, 55, 56 Model setup, 55 63 Multiple liner regression, 64 S Sample collection, 25 Spatial variability, 30, 32, 52, 71, 72 Stormwater pollution, 2, 17, 27, 49, 55, 72, 73 Stormwater quality, 55 68, 71, 73, 74 Stormwater quality prediction, 2, 55 Stormwater quantity, 57 Stormwater runoff, 1, 5, 8 10, 13, 17, 27, 37, 42, 45, 52, 63, 64, 67, 72, 74 Stormwater treatment system, 56, 68 N Nitric oxide (NO 2 ), 7 P Particle size distribution, 9, 41 Polycyclic aromatic hydrocarbons (PAHs), 1, 3, 5, 8, 13, 23, 24, 28, 32 36, 45 47, 51, 52, 55, 59, 62 64, 67, 71, 72, 74 Power of the test, 67 Predictive equations, 2, 63 68, 73 Principal component analysis (PCA), 30, 31, 33, 34, 38, 39, 42, 43, 45, 47, 49, 51 PROMETHEE, 63, 64, 67 T Time exponent, 61 Total organic carbon (TOC), 24, 38, 42, 44, 45 Total solid, 24, 36 38, 40, 42, 52, 59, 62, 64, 65, 68 Toxic-response factor, 42 Traffic congestion, 6, 8, 18, 20, 38, 42, 46, 66 U Urban stormwater quality, 1 13, 73 Urban traffic, 7, 8, 13, 17, 25, 28, 74 Urbanisation, 1 R Rainfall depth, 36, 38, 40, 52, 58, 63, 64 Rainfall event, 1, 2, 7, 8, 11, 13, 17, 19, 20, 62 64 Regression coefficient, 67 Road surface roughness, 9 Runoff rate, 61, 62 W Wash-off, 2, 10 13, 17, 23, 55, 56, 59 63, 67 Wash-off coefficient, 11, 61 Wash-off exponent, 61 Wet deposition, 2, 3, 6, 8, 13, 17, 19, 20, 36 40, 52, 57 59, 72 Wind speed, 30