A Thesis entitled. Risk Assessment Approach for evaluating recycled material use in road construction: A Pilot Study

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1 A Thesis entitled Risk Assessment Approach for evaluating recycled material use in road construction: A Pilot Study By: Faisal Fahd Submitted as partial fulfillment of the requirements for Masters of Science degree in Civil Engineering Advisor: Dr. Defne Apul College of Graduate studies The University of Toledo December 2008

2 The University of Toledo College of Engineering I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Faisal Fahd ENTITLED Risk Assessment Approach for Evaluating Recycled Materials Use in Road Construction: A Pilot Study BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science in Civil Engineering Thesis Advisor: Dr. Defne Apul Recommendation concurred by Committee Dr. Cyndee Gruden On Dr. Ashok Kumar Final Examination Dean, College of Engineering

3 An Abstract of Risk Assessment Approach for Evaluating Recycled Materials Use in Road Construction: A Pilot Study Faisal Fahd Submitted as partial fulfillment of the requirements for the degree of Master of Science in Civil engineering The University of Toledo December 2008 Large quantities of industrial by-products like steel slag, fly ash and bottom ash are produced as residues. A fraction of these by-products are being reused in structural fills and roads while the rest is being disposed in landfills. If the use of these by-products in roads as base layers is encouraged then we can save on the environmental contamination that the extraction of natural aggregates causes. Large areas of land are allocated for landfill sites. If the by-products are reused in roads then we can save on the land sites and also save on the costs of extraction (mining, crushing etc) of the natural aggregates. This research calculates the possible human health risks to construction workers working with the by-products in road construction. This thesis also calculates the risk to groundwater due to the placing of these by-products in road base layers. The risk model was created to assess the risk to construction workers and groundwater also incorporates results from a fate and transport model, HYDRUS for assessing the risk to groundwater In risk assessment for construction workers, average daily dose (intake) of each constituent metal of the industrial waste material to a construction worker was calculated. iii

4 The calculated average daily dose was compared with reference dose and slope factors of that metal to find the carcinogenic and non-carcinogenic risk pertaining to the ingestion, dermal contact and inhalation of by-products. The industrial by-products placed in the base layers of the roads can seep through the soil profile and enter the ground water table. The concentrations that ultimately reach the ground water were calculated using HYDRUS. The results from HYDRUS were plugged back in the excel model to assess the risk to ground water. The concentrations of the metals in ground water were multiplied with their slope factors to obtain carcinogenic risk, and the same concentrations in ground water were divided over the reference dose to obtain the noncarcinogenic risk The risk value should be less than 1 in a million to term no risk due to carcinogenic effects from that metal to humans and the value for hazard quotient for noncarcinogenic risk should be less than 1. The results from the risk model suggested no carcinogenic risk due to inhalation to construction workers from any of the slag types in road construction. However, some constituent metals in the steel slag appeared to pose a carcinogenic risk due to particulate ingestion. These were chromium and beryllium in all the slag types and cadmium and nickel causing risk only in basic oxygen slag and electric arc furnace slag. When the noncarcinogenic risk was assessed of various types of steel slag for construction workers, there were some hazard quotiont values higher than 1, the target risk value. The high risk values in the results suggest that a probabilistic risk approach should be adopted rather than a conservative and deterministic present approach. Also limitations of data on bioaccessibility, reference dose and slope factors contributed to high risk values in this research. iv

5 Table of Contents Abstract...iii List of figures:... vii List of tables:...viii 1.0 Introduction By-Product Reuse in Road Construction: Issues with By-Product Reuse Risk to Construction Workers: Leaching of Metals: Monetary Advantage ) Motivation for Research ) Objectives ) Risk Assessment Methodology: ) Risk Assessment of Construction Workers: ) Exposure Pathways ) Soil Screening Levels ) Average Daily Dose ) Risk Assessment Methodology for Groundwater ) Exposure Pathways: ) Contaminant Fate and Transport Modeling ) Road Section Considered ) HYDRUS Input Parameters ) Sensitivity Analysis Using Factorial Method ) Risk Results v

6 6.1) Carcinogenic Risk to Construction Workers Non-Cancer Risk to Construction Workers ) Proctor s Research ) Risk Assessment Results Based On Contaminated Groundwater ) HYDRUS sensitivity Results ) Conclusions ) Risk Model ) Human Health Risk to Construction Workers ) Risk from Contaminated Groundwater ) Sensitivity Analysis ) Future Research ) Reference: Reference: Appendix:...93 vi

7 List of figures: Figure 1: Overview of risk assessment to construction workers Figure 2: Exposure pathways Figure 3: Overview of risk assessment methodology for groundwater Figure 4: A schematic diagram of the leaching process Figure 5: Exposure pathways for groundwater Figure 6: Road section Figure 7: Time information from HYDRUS Figure 8: Boundary conditions Figure 9: Bulk density information Figure 10: Bottom concentration Vs Time (days) for Kd Figure 11: Bottom concentration VS time (days) for Kd Figure 12: Bottom concentration VS time (Kdb and Kds are 10) Figure 13: Bottom concentration VS time (Kdb= 1 and Kds= 10) Figure 14: Bottom concentration Vs Time (days) with decrease in road base layer depth vii

8 List of tables: Table 1: Total metal concentration in steel slag (mg/kg) Table 2: Total metal concentrations in Coal Combustion Products Table 3: Average background concentrations (mg/kg) of metals in US soils (Draggun and Chiasson 2001) Table 4: Carcinogenic SSL for dermal contact and ingestion Table 5: Parameters used in SSL and ADD equations Table 6: HYDRUS input parameters Table 7: Four scenarios where Kd (L/kg) values were varied Table 8: Precipitation data Table 9: Sign table of factorial experiments Table 10: List of COI's in blast furnace slag Table 11: List of Constituents of interests in basic oxygen slag Table 12: List of constituents of interest in electric furnace slag Table 13: ADD (mg/kg-day) values for blast furnace slag Table 14: ADD (mg/kg-day) for basic oxygen slag Table 15: ADD (mg/kg-day) values for electric arc furnace slag Table 16: Number of metals posing carcinogenic risk in each slag type Table 17: Cancer risk values for blast furnace slag Table 18: Cancer risk values for basic oxygen slag Table 19: cancer risk values for Electric arc furnace slag Table 20: Non carcinogenic risk values of basic oxygen slag Table 21: Non carcinogenic risk values for blast furnace slag viii

9 Table 22: Non cancer risk values of electric arc furnace slag Table 23: Number of metals that pose a suggestive non cancer in various slag types Table 24: List of COI s for construction workers in Proctor et al Table 25: ADD for groundwater ingestion from blast furnace slag Table 26: ADD values for basic oxygen slag Table 27: ADD values from groundwater ingestion from electric arc furnace slag Table 28: Rankings of carcinogenic risk values Table 29: Summary of non-carcinogenic risk values Table 30: Cancer risk values from groundwater due to blast furnace slag Table 31: Cancer risk values from groundwater for basic oxygen slag Table 32: Cancer risk values from groundwater for electric arc furnace Table ix

10 1.0 Introduction Use of alternative materials in construction activities is encouraged nowadays. The alternative materials in this research are steel slag, fly ash, and bottom ash. These materials are the residues in steel making and coal combustion. As these materials are residues, they need to be disposed and hence they are placed in landfills. These materials could be used in a productive way by using them in construction activities like in road base, landscape aggregate, erosion control aggregate, gabions and ripraps (Proctor et al 2002). The construction activity that is of concern for this particular research is use of the steel slag and coal combustion products in road base layers. The present research focuses on the calculation of health risk to construction workers in a road site that uses alternative materials in its road base layers. The workers come in contact with the construction materials (alternative materials) due to dermal contact, ingestion and inhalation of the soil and contaminated particles. An Excel model was created to assess the risk to construction workers who work with the alternative materials in road construction. Also, the risk to people inhabiting around such roads due to the contamination of ground water was calculated using the same model. 1

11 2.1 By-Product Reuse in Road Construction: The various by-products used in the present research are steel slag, fly ash and bottom ash. Steel slag is the co-product of the steel production. Fly ash and bottom ash are the by-products in coal combustion. These products are combined with other regularly used construction materials to form products that are used in roads. For typical iron ore grades (60% to 66% iron), a blast furnace will normally produce 0.25 to 0.30 metric tons of slag per ton of crude iron, while slag output is as high as 1.0 to 1.2 tonne for lower grade iron ore (Van Oss, 2005). The three types of steel slag used in present research are blast furnace slag, basic oxygen slag and electric arc furnace slag. These slag types are distinguished by the method of steel production adopted. The residue from a blast furnace is blast furnace slag, the residue from electric arc furnace is electric arc furnace slag and the residue from basic oxygen furnace is basic oxygen furnace slag. In blast furnace method, blast or hot compressed air is sent from the bottom of the smelting furnace tower. An electric arc furnace is a furnace that heats charged materials by means of an electric charge (Generally a graphite rod). Basic oxygen furnace is a steel making furnace, in which molten iron ore is converted into steel due to oxidizing action of oxygen blown into the melt under a basic slag. 2

12 Over 120 million tonnes of coal combustion products (CCP) are produced each year by coal-burning electric utilities in the USA (Lin Li et al 2005). CCP include fly ash and bottom ash. Fly ash constitutes 60% of the total mass of CCP produced in the US and bottom ash constitutes 20%. (Lin Li et al 2005). According to the American Coal Ash Association (ACAA), 70 million tons of fly ash was produced in 2003 in the United States with only 39% of it being reused in a variety of applications. The remainder is disposed in waste containment facilities such as landfills (USEPA 2002a). Of the 18.6 million tons of bottom ash produced in USA, 45% of it is being reused for various structural filling purposes. Of the total product, about 10% of fly ash and 21% of bottom ash are used in structural and embankment fills (ACAA, 2007). Proper implementation of the industrial by-products as road materials provides a number of significant benefits to the road construction industry as well as to the country. Some examples are listed below: Conservation of natural resources Reduced volume of waste to landfills Lower cost construction materials Lower waste disposal costs Reduced cartage demands Promotion of a clean, green image. It is a general notion that the materials of natural, geological origin are environmentally benign at their point of use in a road construction site. However, this is not necessarily the case. The natural aggregates used in road base layers have constituent 3

13 metals that may contaminate the soil layers below the road base and eventually seep through to the ground water below (Peploe and Dawson 2006). 2.2 Issues with By-Product Reuse Risk to Construction Workers: Construction workers may come in direct physical contact or orally ingest the air borne particles from the by-product road construction materials. Many secondary materials go through a hot process (e.g. slag s, fly ash and bottom ash) and some metal elements may be at relatively high solid concentrations in the mineral fabric, but it may be difficult or even impossible for these metals to find a route out, even if the mineral is crushed. For this reason, solid analysis on construction materials may be useful for classification but is likely to give larger concentrations than are meaningful for assessing a hazard. Bioavailability is what a biological organism can extract from a material. The equation to calculate carcinogenic and non-carcinogenic risk comprises of the term bioavailability. But the data on the percentages of bioavailability of each metal in slag and CCP are not known. For this reason, total metal concentrations were used in this research instead of bio-available concentrations, which means, the value of bioavailability for metals with no data is assumed as 100%. This assumption results in an over estimate of risk values Leaching of Metals: Steel slag, fly ash or bottom ash has many constituent metals in them. The various metals present in steel slag are arsenic, antimony, aluminum, barium, cadmium, calcium, cobalt, copper, chromium, thallium, iron, lead, magnesium, manganese, mercury, 4

14 molybdenum, nickel, phosphorous, selenium, silicon, silver, sulphur, tin and zinc. The constituents of fly ash and bottom ash predominantly include cobalt, chromium, copper, manganese, nickel, lead and zinc (Sushil 2006). Steel slag, fly ash, bottom ash and other by-products that are to be used in road construction can be placed in road base layers. These constituent metals may seep out of the by-product matrix and leach through the soil layer to the ground water. This process of leaching through the soil profile to ground water is not a quick process. Contaminants may take decades to seep through the soil profile (Apul et al 2007). This process is governed by the phenomenon of advection and dispersion. Advection is the process in which the pollutants or the contaminants are carried by the flow of water. Dispersion is the process of solute spreading out from path expected to be followed by advection alone. Various dispersion mechanisms are 1. Pore channel velocity: molecules travel at different velocities. 2. Mixing of pore channels, tortuosity, branching. 3. Difference in pore sizes (different velocities) 4. Variable conductivity in soil layers. The groundwater is the source of water consumption in regular households. Thus, these metals might become a source of carcinogenic and non-carcinogenic risk to people who consume this groundwater Monetary Advantage: The industrial by-products like steel slag or fly ash and bottom ash are disposed of in landfills if they are not beneficially reused. If we can use these by-products in road base layers, we save on the expenditure incurred due to extraction, crushing and 5

15 transportation of the natural aggregates which are usually used on road construction. In the transportation industry, soft soils encountered during road construction are removed and replaced with crushed rock to form a sturdy working platform for pavement construction. This construction practice can be costly, particularly if the rock needs to be hauled to the construction site. As a result, transportation agencies are seeking less costly methods to stabilize soft soils and construct working platforms. In such cases, industrial by-products can be used to construct lower cost working platforms that provide equal support as those constructed with crushed rock. (USEPA 2002a). 6

16 3.0) Motivation for Research According to the Federal Highway Administration (FHWA, 2001), there are nearly 4 million miles of roads in the U.S. These roads require large volumes of materials for construction and maintenance purposes which generally are harvested from natural resources. If industrial by-products could be used in road base layers, then we can save on the cost and environmental emissions that incur due to the extraction of natural aggregates. The emerging urgency of industrialists and researchers in the use of industrial by-products should be complemented with a risk assessment study of the contaminated site. IWEM is a tool that has been used to evaluate the concentration of leachate that reaches ground water from secondary materials used in landfills (USEPA 2002a). However, the risk was not calculated for the people residing around that road layer. Also, except for the work by Proctor et al (2002), the risk to construction workers who work in road sites which have by-products in their base layers has not been calculated previously. 7

17 4.0) Objectives The objectives of this present research were: 1. Develop a risk model in Microsoft Excel interface. 2. To calculate human health risk to construction workers who work using industrial by-products in road base layers 3. To calculate the risk to inhabitants around roads that have by-products in their road base layers. 4. To find the factor amongst partition coefficient of base layer, partition coefficient of soil layer and the depth of the base layer that has the most effect on leachate concentration from industrial by-products used in road base layers. 8

18 5.0) Risk Assessment Methodology: Both carcinogenic and non-carcinogenic risks were calculated in this research. Cancer risk is defined as the probability of developing cancer over a lifetime as a result of exposure to a potential carcinogen. The estimated risks are the upper bound excess lifetime cancer risk for an individual. Upper bound refers to the method of determining a slope factor, where the upper bound value for the slope of the dose-response curves is used. Excess means the estimated cancer risk is in addition to the already existing background risk of an individual contracting cancer from all other causes. Non cancer risk is the estimated risk from chemicals that exhibit chronic, non-cancer toxicity (USEPA 2002b). 5.1) Risk Assessment of Construction Workers: An overview of the method used for calculation of risk to construction workers is shown in Figure 1. The total metal concentration in the alternative materials is first compared with the background concentration of that metal in the US soils. The data of the total metal concentration was obtained from the literature with appropriate references provided in Tables 1 and 2. The background concentration is defined as the ambient concentrations of the metals in US soils. The background concentration of the metals is tabulated with appropriate reference in table 3. If the total metal concentration of a 9

19 particular metal is higher than the background concentration, then that particular metal is termed as the Constituent of interest (COI). Such COI s are then compared with the soil screening levels (SSL) to check if they are higher than the soil screening levels. (Soil screening levels are discussed in detail in section of this document.) The soil screening levels calculated are carcinogenic SSL for dermal contact and ingestion, carcinogenic SSL for inhalation, non-carcinogenic SSL dermal contact and ingestion, non-carcinogenic SSL for inhalation. The values of the calculated SSL for the exposure pathways of carcinogenic and non-carcinogenic scenario mentioned are presented in table 4. In present research, the smallest value amongst the calculated soil screening level for each exposure pathway is presented in table 4 is selected and compared with the COI. In table 4 metals that have no data on their reference dose (Rfd) are represented by not applicable (NA) (see appendix for details). Once the COI s are higher in concentration than the stipulated screening levels then the average daily dose for that COI is calculated and the risk associated with the metal (COI) is assessed. Carcinogenic risk and noncarcinogenic risk is calculated for each exposure pathway that the construction workers are exposed to. The calculation of risk (human health risk) incurred to construction workers due to their exposure to soil ingestion, dermal contact and particulate inhalation is done once the average daily dose is established for each of the exposure pathway. The equation for risk (carcinogenic and non-carcinogenic) is given by USEPA2002b. Carcinogenic risk is given in Equation 1: Carcinogenic risk = ADD*Slope factor of the metal Equation 1 Slope factor is defined as the factor representing the upper-bound (approximating a 95 percent confidence limit) estimate of the slope of the dose-response curve in the low-dose region for carcinogens. The units of the slope factor are expressed as (mg/kg/day) 10

20 Non-carcinogenic risk was calculated using Equation 2: Non-carcinogenic risk (Hazard quotient) = ADD/Reference dose of the metal Equation 2 Reference dose is defined as an estimate (with uncertainty spanning perhaps an order of magnitude) of daily exposure to the human population that is likely to be without an appreciable risk of deleterious non-cancer effects during a lifetime. To find risk from each COI the total dose from environmental exposures to one COI is compared to the USEPA acceptable dose for that constituent. To grossly characterize the potential hazard or carcinogenic risk due to additivity from multiple chemical exposures, the hazard indices and cancer risk for all COI s are summed for each secondary material used. (Proctor et al 2002). In the present research instead of summing up of all the hazard and risk values for a secondary material, the hazard indices/risk values of all the exposure pathways of each metal is summed up and results subsequently analyzed. The present research is a deterministic analysis rather than a probabilistic analysis. Hence the risk values are on a very conservative end. With the conservative risk values I felt it was better to assess each metal so that we can not only identify metals that pose or contribute to high risk values but also identify the exposure pathway such as., ingestion, dermal contact and inhalation that are causing such a risk. 11

21 Table 1: Total metal concentration in steel slag (mg/kg) Metals Blast furnace slag Basic oxygen slag Electric arc furnace slag Thallium ND Chromium Vanadium Beryllium Antimony ND Aluminum Arsenic 1.9 ND 2.2 Barium Cadmium ND Calcium Copper Cobalt Iron Lead Magnesium Manganese Mercury ND Molybdenum Nickel Phosphorous Selenium Silicon Silver ND Sulphur Tin Zinc (Proctor at el., 2002) 12

22 Table 2: Total metal concentrations in Coal Combustion Products Concentration of metals in CCP Fly ash (mg/kg) Bottom ash (mg/kg) Chromium Copper Cobalt Lead Manganese Nickel Zinc (Sushil, 2006) 13

23 Table 3: Average background concentrations (mg/kg) of metals in US soils (Draggun and Chiasson 2001) Illinois Indiana Michigan Minnesota Wisconsin Ohio Chromium Cadmium Beryllium Cobalt Copper Antimony Arsenic Barium Magnesium Manganese Mercury Molybdenum Nickel Selenium Silver Thallium Tin Vanadium Zinc Lead Phosphorous Iron Sulphur Silicon Calcium Aluminum

24 Table 4: Carcinogenic SSL for dermal contact and ingestion Non-Carcinogenic scenario Carcinogenic scenario SSL dermal contact and ingestion SSL inhalation SSL dermal contact and ingestion SSL inhalation Thallium Chromium NA Vanadium Beryllium Antimony Aluminum NA Arsenic Barium Cadmium Calcium NA NA 0 0 Copper NA Cobalt NA Iron NA Lead NA NA 0 0 Magnesium NA NA 0 0 Manganese Mercury Molybdenum NA Nickel Phosporous NA Selenium Silicon NA NA 0 0 Silver Sulphur NA NA 0 0 Tin NA Zinc NA

25 Background concentration of the metal in US soil Concentration of the metal in steel slag. Concentration in steel slag > Background concentration No Selected metal is not a COI Yes Concentration in steel slag >Soil screening level No Yes Selected metal is COI Determination of average daily dose of the constituent metal of the steel slag Carcinogenic risk is given as: Risk = ADD* slope factor Determination of risk for the construction workers Non carcinogenic risk is given as : Risk = ADD/Rfd Figure 1: Overview of risk assessment to construction workers 16

26 5.1.1) Exposure Pathways USEPA defines exposure pathway as the course a chemical or physical agent takes from a source to an exposed organism. An exposure pathway describes a unique mechanism by which an individual or population is exposed to chemicals or physical agents at or originating from a site. Each exposure pathway includes a source or release from a source, an exposure point, and an exposure route. If the exposure point differs from the source, a transport/exposure medium (e.g. air) or media (in cases of inter media transfer) also is included (USEPA, 2001). For purposes of this study, the chemicals or the physical agents described in the above definition are the constituent metals in the alternative road construction materials. The various constituent metals of the steel slag are arsenic, antimony, aluminum, barium, cadmium, calcium, cobalt, copper, chromium, thallium, iron, lead, magnesium, manganese, mercury, molybdenum, nickel, phosphorous, selenium, silicon, silver, sulphur, tin and zinc (Procter et al., 2002). The constituents of fly ash and bottom ash predominantly include cobalt, chromium, copper, manganese, nickel, lead and zinc (Sushil 2006). The various exposure pathways considered in this research are shown in Figure 3. The boxes in red represent the exposure pathway for construction workers. The road construction workers who work with the alternative materials come in direct physical contact with the industrial by-products. They also have the chance of ingesting the contaminants and inhaling the airborne particulates of the pollutants. Hence the exposure pathways of dermal contact, oral ingestion and inhalation should be assessed for the risk. 17

27 Construction workers scenario Use of alternative materials in road construction People residing around roads Physical contact Oral ingestion Oral ingestion (daily water intake) Inhalation of pollutant particulates Figure 2: Exposure pathways 5.1.2) Soil Screening Levels Soil screening levels (SSL) are used to identify areas, chemicals, and pathways of concern that need further investigation (i.e., through the Remedial Investigation/Feasibility Study) and those that require no further attention under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). Soil screening levels are the concentration which when reached; the metal is considered a possible potential hazard and would be sidelined for further study. It is always better that the concentrations of the metals in steel slag stay below the soil screening levels. 18

28 Soil screening levels were calculated using the equations 4-1, 4-2, 4-3, and 4-4 as provided in USEPA (2002) and are presented in table 4. There are various parameters used to calculate the soil screening levels as shown in the formulae and listed in Table 5. The default value of the parameters like the average body weight of the worker, exposure frequency, exposure duration, soil ingestion rate, skin surface area were obtained from USEPA (2002). The values of chemical specific parameters like contact rate for soil ingestion, contact rate for dermal contact and contact rate for inhalation are obtained from Proctor et al (2002). The default values of these parameters could be changed in the model, if the user wants to input different values. The concentration of the metals in steel slag were checked against the soil screening values to see if they are less than the soil screening levels. If they are not below the soil screening levels then the site is a possible potential health hazard and further study is needed. If they are less than the soil screening levels then the metals might not pose any risk, but in my research, soil screening levels are calculated for all the metals but instead of assessing only the metals termed as COI s all the constituent metals of the by-products are checked for risk i.e., the model doesn t show only the risk values due to COI but shows risk values of all the constituent metals of the selected base layer. The default values of the parameters used in SSL equations are listed in table 5. The soil screening level equations discussed below are of the commercial/industrial/non-residential scenario. The term non-residential land use encompasses a broad range of possible site uses, including commercial, industrial, agricultural and recreational. (USEPA 2002). 19

29 Table 5: Parameters used in SSL and ADD equations. Risk parameter Reference Default value Average Body weight USEPA 2002(b). 70 kg of the workers Averaging time USEPA 2002(b) 70 years Exposure frequency USEPA 2002(b), 225 days/year Skin adherence factor USEPA 2002(b) 0.2 Exposed skin area USEPA 2002(b) 3300 sq.cm Soil ingestion rate USEPA 2002(b) 100 mg/day Inhalation rate USEPA 2002(b) 20 cubic meter/day Exposure duration USEPA 2002(b) 1 years Target cancer risk Target hazard risk Contact rate for soil ingestion Contact rate for dermal contact Contact rate for inhalation USEPA 2002(b) and Proctor et al 2002 USEPA 2002(b) and Proctor et al 2002 Proctor et al 2002, Proctor et al 2002, Proctor et al 2002, One in ten thousand 0 to 1. The number used in present research is 1. chemical specific Chemical specific Chemical specific Background concentration of the metal in Region 5 Concentration of the Draggun and Chiasson 2001, Proctor et al 2002, metal in Steel Slag Oral slope factor Proctor et al 2002, RAIS ( ) Reference dose oral Proctor et al 2002 and RAIS ( ) Chemical specific Chemical specific Chemical specific, presented in appendix Chemical specific, presented in appendix 20

30 Soil screening level for carcinogenic contaminants for the exposure pathway of dermal absorption and soil ingestion: SSL = (TR*BW*AT*365 d/yr)/[(ef*ed*10-6 kg/mg)((sf O *IR)+(SF ABS *AF*ABS d *SA*EV))] Equation 3 TR= Target risk. This value is the maximum risk value the user wants. The cancer risks must lie in between one-in-million to one-in-ten thousand, according to Proctor et al (2002). BW=Average body weight. The default value of this parameter (70 Kg) is provided by USEPA (2002). AT= Averaging time. The default value of this parameter (70 years) is provided by USEPA (2002). EF= Exposure frequency. The default value of this parameter (225 days in a year) is provided by USEPA (2002). ED= Exposure duration. The default value of this parameter (1 year) is provided by USEPA (2002). SF o = Oral slope factor. Definition of this term is provided in the section 5.1 of this document. The value was obtained from Risk Assessment Information Systems. (RAIS) ( ) and Proctor et al (2002). AF= Skin-soil adherence factor. The default value of this parameter (0.2mg/cm 2 ) is provided by USEPA (2002). ABS d = Dermal adjusted slope factors. The value of dermal adjusted slope factors is obtained using exhibit 3-3 and appendix c of USEPA (2002). 21

31 SA= Skin surface exposed area. The default value of this parameter (3300 sq.cm) is provided by USEPA (2002). EV=Event frequency. The default value (1) of this parameter is provided by USEPA (2002). Soil screening level for non-carcinogenic contaminants for the exposure pathway of dermal absorption and soil ingestion SSL= (THQ*BW*AT*365 d/yr)/ [(EF*ED*10-6 kg/mg)((ir/rfd o )+(AF*ABS d *SA*EV/RFD abs ))]--- Equation 4 THQ= Target hazard quotient. This value of THQ lies in a range of 0 to 1 and is the maximum risk value the user wants. The hazard index (how to arrive at this value is discussed later in this document) used in present research is 1. (Proctor et al., 2002) RFD o = Oral reference dose. Definition of this term is provided in section 5.1 of this document. The value is obtained from RAIS ( and Proctor et al RFD abs = Dermal adjusted reference dose. The value of dermal adjusted slope factors is obtained using the equation 4-3 of USEPA (2004). Soil screening level for carcinogenic contaminants for the exposure pathway of inhalation SSL= (TR*AT*365 d/yr)/ (URF*1000µg/mg*EF*ED/PEF) ---Equation 5 URF= Inhalation unit risk. URF is defined as the upper-bound excess lifetime cancer risk estimated to result from continuous exposure to an agent at a concentration of 1µg/m 3 in air. Values of which are provided in appendix C exhibit c5 of USEPA 2002 (units are (µg/m 3 ) -1 ). The values of unit risk factor are constituent metal specific. 22

32 PEF= Particulate emission factor (1.636*10 9 m 3 /Kg). This default value is provided in USEPA Soil screening level for non-carcinogenic contaminants for the exposure pathway of inhalation SSL= (THQ*AT*365 d/yr)/(ef*ed /(RFC*PEF))---Equation 6 RFC= Reference concentration. It is defined as an estimate (with uncertainty spanning an order of magnitude) of continuous inhalation exposure to the human population that is likely to be without an appreciable risk of deleterious non-cancer effects during a lifetime. The values of reference concentration are constituent specific ) Average Daily Dose A number of methodologies have been developed to estimate the exposure of an individual to toxic compounds in a soil matrix. While some approaches are designed to estimate dermal exposure, others include an absorption factor to permit the calculation of absorbed dose. The major factors that are considered for calculation of average daily dose (ADD) in the dermal exposure route are chemical in contact with the skin, exposure concentration, the extent of skin surface area exposed, the duration of exposure, the absorption of the chemical through the skin, the internal dose, and the amount of chemical that can be delivered to a body (bioavailability). ADD is the dose rate averaged over a pathway-specific period of exposure expressed as a daily dose on a per-unit-bodyweight basis. The ADD is used for exposure to chemicals with non-carcinogenic nonchronic effects (USEPA 1997). The units of ADD are mg/kg-day. 23

33 Equations 7,8, and 9 were used to calculate the ADD for exposure routes of dermal contact, ingestion, and inhalation, respectively. Default values for these equations are given below. These were obtained from USEPA 1997 and Proctor et al 2002 as shown in table 5. For dermal contact with chemicals in soil or water, dermal absorbed average daily dose can be estimated using Equation 7 (U.S. EPA, 1997): ADD = EV*ED*EF*SA*DA event /(BW*AT) Equation 7 Where, EV = event frequency (events/day) default value is 1. (Proctor et al 2002). ED = exposure duration (default value 1 yr) EF = exposure frequency (default value 225 days/yr) SA = skin surface area available for contact (3300 sq.cm) BW = body weight (70 Kg) AT = averaging time, (days) for non-carcinogenic effects. AT = ED for carcinogenic effects. AT = 70 yrs or 25,550 days The average daily dose equation for soil ingestion was calculated using Equation 8. ADD = SI*EPC*ED*EF*B*CF / (BW*AT) -----Equation 8 Where, SI = Soil ingestion rate. Default value being 100 mg/day EPC = Exposure point concentration. B = Bio-accessibility. (Values of bio-accessibility are chemical specific and are obtained from Proctor et al (2002)). The bio-accessibility values used in the present research are presented in appendix of this document. CF = Conversion factor. (10-6 mg/kg) 24

34 Soil ingestion rate is the quantity of the soil or industrial by-products used in the road construction. The construction workers while working with the industrial byproducts would likely ingest the particles of by-products in voluntarily through the mouth. But the present research does not take into account the total amount of the constituent concentration to calculate risk as only a part of the total quantity of the contaminant may cause risk to the individual. This percentage which is actively involved in causing risk to the individual by getting absorbed in the intestines is called the bioaccessibility of that material and is represented by term B in the equation 8 above. EPC is the exposure point concentration. EPC is the total concentration of the metal in the source of contamination. Here the source of contamination is the industrial by-products like the steel slag, CCP and foundry sand. EPC for the exposure routes of soil ingestion and dermal quantity is the total concentration of the metal for which assessment is done. As an example for the metal manganese (Mn), the concentration of Mn in blast furnace slag is 8168 mg/kg. So the EPC for Mn for the exposure routes of soil ingestion and dermal contact is 8168 mg/kg. The EPC value for the same metal for the exposure route of particulate inhalation is different. The equation for average daily dose for the particulate inhalation exposure is given by the equation 9: ADD = IR*ET*EPC air *ED*EF*B*CF / (BW*AT) ----Equation 9 Where, IR = Inhalation rate of the construction workers (cubic meter/hour) ET = exposure time of the construction workers. (Hours/day) EPC for the inhalation route of exposure is given by 25

35 EPC air = EPC/PEF Where PEF is the particulate emission factor. USEPA has developed a guidance regarding the mass of soil that can be suspended per time (emission rate) during construction activities like bulldozing, scraping, back hoeing etc. But these rates are very much site specific. Therefore USEPA recommends use of an estimate of emission rate that represents general construction activities like land clearing, drilling and blasting etc. The default value recommended for the PEF for total suspended slag particles is 8.75*10 5 m 3 /Kg. (Proctor et al 2002) 5.2) Risk Assessment Methodology for Groundwater Figure 3 illustrates the structure of risk assessment method used for groundwater contamination. Information of the road such as road dimensions, types of soil layers and partition coefficients were input in the HYDRUS model which output leachate concentrations that reached the groundwater. Once the leachate concentration to groundwater was established from HYDRUS, the leachate concentration was multiplied with a dilution factor of 20 as recommended by USEPA (2002 b). The average daily dose of the contaminants in the groundwater that reach the homes were divided (or multiplied) with their reference dose (or slope factors) to establish any non-carcinogenic (or noncarcinogenic risk) to the inhabitants living in proximity to the road with industrial byproducts in their base layers. 26

36 Site geology and hydrology Dimensions of road section HYDRUS 1D Precipitation rates Subsurface soil parameters Establish leachate concentrations in groundwater. ADD Calculations Noncarcinogenic risk Risk = ADD/Rfd Carcinogenic risk Risk = ADD* slope factor Figure 3: Overview of risk assessment methodology for groundwater 27

37 The equation of average daily dose is given by Swartjes (1999). ADD GW = C GW *IR*EF*ED/ (BW*AT*365) ---Equation 10 Where, ADD GW = Average daily dose due to ingestion of groundwater by an adult. Unit of ADD GW is mg/kg-day. C GW = Concentration of contaminant at groundwater. This value is obtained from HYDRUS and is tabulated in table 9. The units of C GW are mg/l. IR = Ingestion rate. Default value of the ingestion rate is obtained from USEPA The default value is 2 L/day. EF = Number of days exposed in a year. The value of EF taken for this research is 365 days/year. This value is assumed so as to obtain a conservative risk number. The total duration of the project is assumed to be 1 year. Hence exposure frequency of 365 days in a year will give a very conservative value ) Exposure Pathways: A schematic diagram describing the leaching process is shown in figure 4. The constituent metals in base materials may seep out of by-product matrix and leach through the soil layer to the ground water. The groundwater is the source of consumption of water in some households: about 50 percent of the United States population receives its drinking water from groundwater. (USEPA 1999). Hence the exposure pathway of ingestion (water intake) to the people living around the roads with alternative materials in 28

38 the base layers was considered. Base layer Asphalt layer Sub base layer Soil layer Ground water Figure 4: A schematic diagram of the leaching process. Other exposure pathways for the inhabitants in house with supply of drinking water from the contaminated groundwater source are the exposure pathway of dermal contact due to the use of the possible contaminated water for washing dishes etc and exposure pathway of inhalation due to the vapors that come from activities like bathing etc. But, for simplicity and lack of data the exposure pathway of ingestion (water intake) was the only one considered in this research. Figure 5 shows the exposure pathways for inhabitants living around roads. The boxes in red represent the exposure pathways considered in this research for assessing the risk due to groundwater contamination. 29

39 Construction workers scenario Use of alternative materials in road construction People residing around roads Physical contact Oral ingestion Oral ingestion (daily water intake) Inhalation of pollutant particulates Figure 5: Exposure pathways for groundwater 5.2.2) Contaminant Fate and Transport Modeling The leaching and transport of contaminants to groundwater were modeled using HYDRUS. HYDRUS is a Microsoft windows based modeling environment for analysis of water flow and solute transport in variably saturated porous media. HYDRUS 1D was used in the present research to simulate the water flow and solute transport. The leachate concentration reaching the groundwater from the soil surface was obtained as an output from HYDRUS. The HYDRUS model was run for a unit concentration of contaminant placed in soil base layer. The resulting groundwater concentration from the model was multiplied with the total concentration of that metal in the selected base layer material to find the total leachate concentration reaching the groundwater for the specific 30

40 contaminant. This method of using the unit concentration and multiplying with appropriate base layer metal concentration as opposed to running the simulation for every base layer metal concentration reduced the number of simulations (for each metal) to just one simulation for a given pavement scenario ) Road Section Considered A road cross section was modeled in 1 dimension. In the model, there was an asphalt layer with a depth of 0.2m. This layer was followed by base and sub base layer. In the present simulation the distinction between base and sub base layer was not considered. Hence the base and sub base layer had the same Kd value. Below the base and sub base layer is soil layer till groundwater. Total depth of the road cross section and the soil profile was 1 m. After the 1 m profile was the ground water. The depth of the ground water from the soil surface was assumed to be 1 m always for the present research. This value of 1 m is far below the actual depth of ground water table in state of Ohio given by Ohio department of natural resources and thus will lead to a conservative risk assessment. ( Figure 6 represents the soil column modeled in this research. The red color of the profile represents the asphalt layer; blue color depicts the alternative material base layers. The green color depicts the soil layer below the base layer. The depth of the total soil profile from the top of the asphalt layer to the top of groundwater table was 1 m. The depth of the asphalt layer and small aggregate layer was 0.2 m, depth of the base layer 31

41 using industrial by-products is 0.13 m and depth of the soil layer below the base layer was 0.67 m. Figure 6: Road section 32

42 5.2.4) HYDRUS Input Parameters A summary of input parameters used in HDYRUS is given in Table 6. The depth of the soil profile is assumed as 1 m. The model is run for 15 years with 171 precipitation records being input in HYDRUS model. The precipitation records are the mean monthly precipitation of Cleveland (CLEVELAND HOPKNS INTL AP CLE N W) from 1985 to 2000 obtained from National climatic data centre. ( 33

43 Table 6: HYDRUS input parameters Parameter Value Comment Depth of vertical profile modeled (and the depth to groundwater) Number of days for which HYDRUS is run Time variable boundary conditions Water flow upper boundary conditions Water flow lower boundary conditions Diffusion coefficient (m 2 /day) 1 m Assumption made to represent a worst case scenario 5475 days (15 years) Arbitrarily chosen time range 171 This is the number of precipitation data input in the model (mean monthly precipitation data) ml Atmospheric BC with surface runoff Constant pressure head if the infiltration capacity of the surface was exceeded, the precipitation becomes runoff 6.25 E-005 Apul et al This condition is selected as it is assumed that below the soil profile (1 m), ground water is present. Bulk density of asphalt (tonne per cubic meter) Bulk density of steel slag (tonne per cubic meter) Bulk density of soil layer (tonne per cubic meter) 2.5 Apul et al H. Ziari (2007) Obtained from HYDRUS model. 34

44 Partition Coefficient: There are many input parameters in HYDRUS: a sensitivity analysis was performed to establish the parameters that most affect the leachate concentration to groundwater. The various parameters that were analyzed in the present research were the partition coefficient (Kd) of the road base layer, Kd of the soil profile below the base layer and depth of the ground water (i.e. the depth of the green section in Figure 6) Table 7 shows the scenarios used in the risk model and the sensitivity analysis. In these four scenarios, partitioning coefficients (Kd values) were varied in base and soil layers. The partitioning coefficient (Kd) parameter is a measure of the potential for the adsorption of dissolved contaminants in contact with soil. Kd values are often used in fate and contaminant transport calculations. Partitioning coefficient (Kd) is defined as the ratio of the contaminant concentration associated with the solid to the contaminant concentration in the surrounding aqueous solution when the system is at equilibrium. Table 7: Four scenarios where Kd (L/kg) values were varied Kd value for base layer Kd value for soil layer Scenario 1 Lower (Kd=1) Lower (Kd=1) Scenario 2 Lower (Kd=1) Higher (Kd=10) Scenario 3 Higher (Kd=10) Lower (Kd=1) Scenario 4 Higher (Kd=10) Higher (Kd=10) 35

45 Climatic Input Parameters: The duration for which the leachate is analyzed and considered was 15 years (5475 days). The screenshot showing the time information is shown in figure 7. The numbers of time variable boundary records were 171. Time variable boundary records were the number of times precipitation had occurred. In this research, the precipitation taken is monthly average from NCDC, hence after every 30 days a precipitation record was entered with the average rainfall for that month. The precipitation data used in the HYDRUS model is shown in table 8 with appropriate references. Figure 7: Time information from HYDRUS 36

46 Table 8: Precipitation data Year Month Average precipitation (inches) 1985 January 1.98 February 0.49 March 3.84 April 2.97 May 2.40 June 7.94 July 3.36 August 5.51 September 2.07 October 3.41 November 1.02 December January 1.03 February 2.84 March 2.20 April 3.47 May 1.33 June 0.65 July 3.42 August 3.35 September 1.77 October 2.51 November 4.63 December January 2.07 February 1.73 March 3.46 April 3.73 May 9.14 June 5.22 July 3.02 August 1.09 September 4.61 October 4.50 November 3.61 December January 2.35 February 4.70 March 0.86 April 4.57 May 6.10 June 1.72 July 5.62 August 4.79 September

47 October 4.92 November 2.28 December January 2.18 February 2.31 March 3.64 April 4.22 May 3.24 June 1.37 July 1.69 August 2.79 September 3.40 October 2.65 November 2.92 December January 3.32 February 2.65 March 3.05 April 3.77 May 3.01 June 2.66 July 9.12 August 4.58 September 3.25 October 2.27 November 6.54 December January 4.44 February 2.61 March 3.85 April 3.16 May 1.56 June 5.18 July 2.58 August 1.52 September 5.94 October 3.52 November 4.06 December January 2.66 February 0.83 March 1.30 April 3.70 May 1.67 June 3.35 July 2.46 August 5.35 September 1.73 October

48 November 2.52 December January 5.81 February 1.73 March 1.72 April 4.33 May 3.96 June 3.67 July 5.39 August 2.00 September 1.03 October 4.08 November 3.88 December January 2.69 February 1.63 March 2.81 April 5.61 May 2.08 June 3.89 July 3.18 August 0.79 September October 4.65 November 5.03 December January 1.77 February 2.93 March 3.26 April 2.20 May 4.21 June 3.34 July 1.51 August 5.26 September 4.25 October 1.63 November 2.58 December January 3.92 February 1.89 March 3.25 April 6.07 May 1.92 June 2.97 July 2.72 August 3.02 September 1.20 October 2.36 November

49 December January 3.64 February 2.36 March 1.65 April 3.89 May 1.54 June 1.43 July 4.66 August 1.80 September 1.93 October 3.06 November 3.31 December January 2.63 February 2.05 March 1.57 April 3.72 May 5.46 June 5.72 July 2.57 August 4.72 September 3.29 October 3.56 November 2.55 December January 1.59 February 1.63 March 2.43 April 2.33 May 3.84 June 3.96 July 0.68 August 3.31 September 3.90 October 5.56 November 2.62 December 2.53 Reference: National climatic data center (NCDC). 40

50 The boundary conditions selected in HYDRUS are shown in figure 8.The upper boundary condition was Atmospheric BC with surface runoff. The upper boundary in the scenario is the asphalt surface on the top of the road. On the road surface some pressure head builds up when precipitation exceeds infiltration capacity of asphalt surface layer. The boundary condition was so selected that if the infiltration capacity of the surface was exceeded, the precipitation became runoff and thus this volume of water (excess water) did not enter the HYDRUS column. The lower boundary condition was a constant pressure head representing the groundwater table Material Properties The bulk density of the asphalt (2.5 t/cubic meter) was selected for material one. The bulk density of asphalt was obtained from D.S.Apul (2005). The bulk density of steel slag is given for material two, and the information is obtained from H. Ziari (2007). 41

51 Figure 8: Boundary conditions 42

52 Figure 9: Bulk density information Table 6 presents all the parameters used in the HYDRUS model with the values and units. 43

53 5.2.5) Sensitivity Analysis Using Factorial Method In the current research I studied 3 factors affecting the leachate. In such a case the experiments are performed in each factor have two levels. One level was designated as the high level and the other level was called the low level. If there are P factors, then the there are 2 p treatments for the experiment. Such experiments are called 2 p experiments. Since we had 3 factors in this research I used 2 3 factorial experiments to assess which factor had the maximum impact on the leachate. In 2 3 factorial there are three factors and 2 3 = 8 treatments. Eight treatments are the eight HYDRUS runs obtained by changing the three factors (Factor 1: Kd of base; Factor 2: Kd of soil, Factor 3: depth of the road layer). To find the effect of each factor which is called the main effect of that factor, the difference between the mean response when the factor is at its high level and the mean response when the factor is at its low level is considered. For better understanding of the factorial experiments let us denote the factors in the present research with the notation of A, B and C: A being the Kd of the base layer, B being the Kd of the soil layer and C is the denoted as the depth of the road layer. There could be an interaction of the factors in a factorial experiment. The interactions are one for each pair of factors and one the three way interaction. The two way interactions are denoted by AB, AC, and BC and the three way interaction by ABC. The 2 3 factorial experiment shown in Table 9 the treatments are denoted with lowercase letters, with the letter indicating that a factor is at its high level and the third factor is at the low level. The symbol 1 is used to denote the treatment when all the factors are at the low level. The maximum concentration of the contaminants 44

54 obtained each time HYDRUS is run is denoted by C. These concentrations C come from the 8 treatments of HYDRUS. The positive sign in table 9 represents a factor in high level (i.e., a higher value is assigned for that factor as an input in HYDRUS), and the negative sign in table 9 represents a factor in low level (i.e., a lower value is assigned for that factor as an input in HYDRUS). Table 9: Sign table of factorial experiments Treatment Average concentration A B C AB AC BC ABC 1 C 1 = ve -ve -ve +ve +ve +ve -ve A C a = ve -ve -ve -ve -ve -ve -ve B C b = -ve +ve -ve -ve -ve -ve -ve C C c =0.21 -ve -ve +ve -ve -ve -ve -ve Ab C ab = ve +ve -ve +ve -ve -ve -ve Ac C ac = ve -ve +ve -ve +ve -ve -ve Bc C bc = -ve +ve +ve -ve -ve +ve -ve Abc C abc =0.25 +ve +ve +ve +ve +ve +ve +ve 45

55 6.0) Risk Results 6.1) Carcinogenic Risk to Construction Workers The results from the excel model pointed towards a suggestive evidence of cancer potential. According to the EPA guidelines for carcinogenic risk assessment, if there is appropriate evidence from human or animal data suggesting carcinogenicity, which raises a concern for carcinogenic effects but is judged not sufficient for a stronger conclusion then the appropriate term to be used is suggestive evidence of carcinogenic potential. I choose to term the carcinogenic risk in the present document as suggestive evidence of carcinogenic potential as the present research is a more conservative approach rather than a probabilistic one. Also, the same approach is adopted for non-carcinogenic risk assessment. The metals that are termed as COI s in steel slag are shown in table 10, 11 and 12. Table 10 lists the COI in blast furnace slag, table 11 lists the COI in basic oxygen slag and table 12 lists the COI in electric arc furnace slag. Blast furnace slag had least number of COI s amongst the three slag types and electric arc furnace slag the highest. 46

56 Table 10: List of COI's in blast furnace slag Metals in steel slag Concentration in steel slag mg/kg. (Proctor et al 2002) Chromium Beryllium Aluminum Calcium Iron Magnesium Manganese Phosphorous Selenium Silicon Sulphur Tin Concentration in US soils mg/kg. (Draggun and Chiasson 2001) 47

57 Table 11: List of Constituents of interests in basic oxygen slag Metals in steel slag Concentration in steel slag mg/kg. (Proctor et al 2002) Thallium 10 0 Chromium Vanadium Beryllium Antimony Aluminum Cadmium Calcium Copper Iron Lead Magnesium Manganese Molybdenum Phosphorous Selenium Silicon Silver 19 0 Sulphur Concentration in US soils mg/kg. (Draggun and Chiasson 2001) 48

58 Table 12: List of constituents of interest in electric furnace slag List of metals Concentration in steel slag mg/kg. (Proctor et al 2002) Thallium 14 0 Chromium Vanadium Beryllium Antimony Aluminum Barium Cadmium Calcium Copper Iron Lead Manganese Molybdenum Nickel Phosphorous Silicon Silver 13 0 Tin 12 0 Zinc Concentration in US soils mg/kg. (Draggun and Chiasson 2001) 49

59 The ADD values calculated for the various types of steel slag (blast furnace slag, basic oxygen slag and electric arc furnace slag respectively) are presented in the tables 13, 14 and 15. The highest ADD value amongst the slag types was calculated for vanadium (5.55E-01 mg/kg) for the exposure pathway of dermal contact, for the exposure pathway of ingestion calcium has highest ADD value (9.62E-00mg/Kg) and calcium (1.07E-08 mg/kg) for the exposure pathway of inhalation. 50

60 Table 13: ADD (mg/kg-day) values for blast furnace slag Metals Average daily dose for dermal contact Average daily dose for soil ingestion Average daily dose for inhalation Chromium 9.93E E E-10 Vanadium 3.25E E E-13 Beryllium 2.73E E E-12 Aluminum 2.83E E E-09 Arsenic 1.21E E E-14 Barium 1.97E E E-11 Calcium 1.8E E E-08 Copper 5.54E E E-13 Cobalt 3.12E E E-13 Iron 2.3E E E-09 Lead 5.47E E E-13 Magnesium 4.78E E E-09 Manganese 5.2E E E-09 Molybdenum 1.02E E E-14 Nickel 1.21E E E-14 Phosphorous 2.52E E E-11 Selenium 3.25E E E-13 Silicon 1.15E E-09 Sulphur 7.61E E E-10 Tin 1.34E E E-14 Zinc 2.61E E E-12 51

61 Table 14: ADD (mg/kg-day) for basic oxygen slag Metals Average daily dose for dermal contact Average daily dose for soil ingestion Average daily dose for inhalation Thallium 3.82E E E-12 Chromium 9.76E E E-10 Vanadium 2.05E E E-11 Beryllium 6.36E E E-14 Antimony 2.67E E E-13 Aluminum 2.32E E E-09 Barium 6.56E E E-12 Cadmium 2.94E E E-12 Calcium 1.90E E E-09 Copper 2.42E E E-12 Cobalt 3.5E E E-13 Iron 1.28E E E-09 Lead 5.6E E E-12 Magnesium 3.83E E E-09 Manganese 1.09E E E-09 Molybdenum 8.97E E E-12 Nickel 3.82E E E-13 Phosphorous 2.39E E E-10 Selenium 1.15E E E-13 Silicon 4.35E E E-09 Silver 1.21E E E-13 Sulphur 1.01E E E-11 Tin 5.22E E E-13 52

62 Table 15: ADD (mg/kg-day) values for electric arc furnace slag Metals Average daily dose for dermal contact Average daily dose for soil ingestion Average daily dose for inhalation Thallium 8.91E E E-13 Chromium 2.3E E E-09 Vanadium 5.55E E E-11 Beryllium 8.91E E E-14 Antimony 2.91E E E-12 Aluminum 2.45E E E-09 Barium 4.07E E E-11 Cadmium 6.56E E E-12 Calcium 2.64E E E-09 Copper 1.29E E E-12 Iron 1.31E E E-09 Lead 2.42E E E-12 Magnesium 3.75E E E-09 Manganese 1.49E E E-09 Molybdenum 2.23E E E-12 Nickel 2.67E E E-12 Phosporous 1.28E E E-11 Selenium 1.27E E E-13 Silicon 5.15E E E-09 Silver 8.27E E E-13 Sulphur 1.31E E E-11 Tin 7.64E E E-13 Zinc 1.33E E E-12 53

63 The risk results (carcinogenic and non-carcinogenic) for various types of steel slag (namely blast furnace slag, basic oxygen slag and electric arc furnace slag) are presented in tables 17 to 22. To obtain the risk values ADD values are divided over the Rfd (reference dose) to obtain hazard quotient (non-cancer risk) i.e., the total dose from environmental exposures to one COI is compared to USEPA acceptable dose for that constituent and ADD values are multiplied with the slope factors to obtain the cancer risk values for a COI. To grossly characterize the potential hazards due to additivity from multiple metal (contaminant) exposures, the hazard indices for all COI are summed for each scenario. (Proctor et al 2002). The total hazard index for a secondary material should be less than 1 in order to declare that material safe for non-cancer risk and the total cancer risk should be less than one in ten thousand. Some risk values presented for an individual metal/contaminant in the tables 17 to 22 are very high. These risk values can be attributed to the quantitative and conservative approach of this research and also these values do not give an exact picture of the risk from individual constituent metals of the secondary materials. This discussion is further continued in section.the risk value from each constituent metal of the secondary materials is determined so as to identify the specific constituent metal that contributes highest in the risk value. Table 16 shows the suggestive carcinogenic risk results of various steel slag types and number of metals that pose a risk in each exposure pathway. For all three types of the slag, none of the metals posed a cancer risk from dermal contact and particulate inhalation. This was determined by comparing the calculated risk value with a value of one in a million. To find the total cancer risk due to a contaminant, cancer risk is summed from all the exposure pathways 54

64 and the same is presented in table 17 to 22 (Proctor et al 2002).Table 16 provides a summary of the information presented in tables 17 to

65 Table 16: Number of metals posing carcinogenic risk in each slag type Type of steel slag Metals posing carcinogenic risk Basic oxygen slag Chromium, beryllium, cadmium and nickel Blast furnace slag Chromium and beryllium Electric arc furnace slag Chromium, beryllium, cadmium and nickel The carcinogenic risk values of blast furnace slag are shown in table 17.For blast furnace slag the metals posing a cancer risk to construction workers are chromium and beryllium. (Risk values are above 1 in ten thousand). The carcinogenic risk results for basic oxygen slag are shown in table 18. Chromium, beryllium, cadmium and nickel were found above the target risk value for the construction workers. The cancer risk values of electric arc furnace slag are presented in table 19. Electric arc furnace slag also had chromium, beryllium, cadmium and nickel above the target cancer risk value. The risk value is 0 if that constituent metal does not have data on oral slope factor or is not a metal causing cancer risk. The risk value is ND if the data on concentration of the constituent metal in steel slag is not present. 56

66 Table 17: Cancer risk values for blast furnace slag Thallium ND Chromium 0.79 Vanadium 0 Beryllium Antimony ND Aluminum 0 Arsenic 0 Barium 0 Cadmium ND Calcium 0 Copper 0 Cobalt 0 Iron 0 Lead 0 Magnesium 0 Manganese 0 Mercury ND Molybdenum 0 Nickel 0 Phosphorous 0 Selenium 0 Silicon 0 Silver ND Sulphur 0 Tin 0 Zinc 0 Fluorine 0 57

67 Table 18: Cancer risk values for basic oxygen slag Thallium 0 Chromium 1.89E+00 Vanadium 0 Beryllium 1.42E-04 Antimony 0 Aluminum 0 Arsenic ND Barium 0 Cadmium 8.24E-03 Calcium 0 Copper 0 Cobalt 0 Iron 0 Lead 0 Magnesium 0 Manganese 0 Mercury 0 Molybdenum 0 Nickel 1.63E-04 Phosphorous 0 Selenium 0 Silicon 0 Silver 0 Sulphur 0 Tin 0 Zinc 0 Fluorine 0 58

68 Table 19: cancer risk values for Electric arc furnace slag Thallium 0 Chromium 4.47E+00 Vanadium 0 Beryllium 1.99E-04 Antimony 0 Aluminum 0 Arsenic 1.06E-04 Barium 0 Cadmium 1.78E-02 Calcium 0 Copper 0 Cobalt 0 Iron 0 Lead 0 Magnesium 0 Manganese 0 Mercury 0 Molybdenum 0 Nickel 1.14E-03 Phosphorous 0 Selenium 0 Silicon 0 Silver 0 Sulphur 0 Tin 0 Zinc 0 Fluorine 0 It is interesting to note that the metals that showed signs of suggestive cancer risk among various types of steel slag like chromium, beryllium, cadmium and nickel have cancer risk value of order 10 1 over the target value. These carcinogenic risk value calculated may not be high or considered as risk as the present study is quantitative rather than a probabilistic approach and hence suggests at a more conservative risk values. 59

69 6.2. Non-Cancer Risk to Construction Workers The results from the excel model point towards a suggestive evidence of noncarcinogenic risk to construction workers due to use of industrial by-products in road construction (Table 20, 21, and 22). Basic oxygen slag does suggest a non-carcinogenic risk due to thallium, chromium, vanadium, aluminum, iron, manganese, phosphorous and cadmium. Cadmium in basic oxygen slag posed little non-carcinogenic risk as the risk value was little over the target value. 60

70 Table 20: Non carcinogenic risk values of basic oxygen slag Thallium 4.09E+01 Chromium 2.30E+01 Vanadium 9.89E+01 Beryllium 6.56E-03 Antimony 3.44E-01 Aluminum 2.93E+03 Arsenic ND Barium 2.12E-02 Cadmium 2.70E+00 Calcium ND Copper 3.05E-02 Cobalt 8.84E-03 Iron 2.16E+01 Lead ND Magnesium ND Manganese 4.35E+01 Mercury 1.37E-02 Molybdenum 9.06E-01 Nickel 1.44E-02 Phosphorous 6.04E+03 Selenium 1.23E-01 Silicon ND Silver 1.83E-01 Sulphur ND Tin 4.39E-04 Zinc 6.75E-03 Fluorine 0.00E+00 Blast furnace slag had a suggestive non cancer potential for construction workers due to significant concentration of chromium, aluminum, manganese and phosphorous. Iron also posed a small amount of suggestive non cancer risk to the construction workers. Manganese is the only metal in BFS that caused a non cancer risk due to high risk value of dermal contact exposure pathway for the construction workers. Other metals that posed non carcinogenic risk from BFS apart from manganese were a result of high risk value contributions from the exposure pathway of ingestion. 61

71 Table 21: Non carcinogenic risk values for blast furnace slag Thallium ND Chromium 9.64E+00 Vanadium 3.89E-02 Beryllium 5.79E-01 Antimony ND Aluminum 3.57E+03 Arsenic 2.08E-01 Barium 6.37E-02 Cadmium ND Calcium ND Copper 6.99E-03 Cobalt 7.88E-03 Iron 3.64E+00 Lead ND Magnesium ND Manganese 7.56E+01 Mercury ND Molybdenum 1.03E-02 Nickel 4.57E-03 Phosphorous 6.36E+02 Selenium 3.49E-02 Silicon ND Silver ND Sulphur ND Tin 1.13E-04 Zinc 4.39E-03 Fluorine 0.00E+00 62

72 Electric arc furnace (EAF) has chromium, manganese, aluminum and phosphorous with significant non cancer risk contributed by the pathway of ingestion, while metals that posed little risk for ingestion were thallium, vanadium, antimony, cadmium and iron. The non-carcinogenic risk associated with the electric arc furnace slag is presented in table 22. It is an interesting observation that none of the steel slag types has any non-carcinogenic risk/hazard pertaining to contaminated particulate inhalation. Also most of the metals in the steel slag posed risk only through the exposure pathway of contaminated particulate ingestion. Table 22: Non cancer risk values of electric arc furnace slag Thallium 5.80E+00 Chromium 5.45E+01 Vanadium 2.65E+03 Beryllium 9.18E-03 Antimony 4.67E+00 Aluminum 3.09E+03 Arsenic 2.41E-01 Barium 1.32E-01 Cadmium 5.86E+00 Calcium ND Copper 1.62E-01 Cobalt ND Iron 2.21E+01 Lead ND Magnesium ND Manganese 4.99E+01 Mercury 0.00E+00 Molybdenum ND Nickel 1.01E-01 Phosphorous 3.24E+03 Selenium 1.37E-01 Silicon ND Silver 1.25E-01 Sulphur ND Tin 6.43E-04 Zinc 2.24E-02 Fluorine ND 63

73 Table 23: Number of metals that pose a suggestive non cancer in various slag types Particulate ingestion Dermal contact Particulate inhalation Basic oxygen slag Thallium, vanadium None chromium, aluminum, cadmium, iron, manganese and phosphorus Blast furnace slag Chromium, Manganese None aluminum, Iron and Phosphorous. Electric arc furnace slag Chromium, Vanadium None manganese, aluminum, Phosphorous, thallium, antimony, cadmium and iron. It is interesting to observe that some metals in all the slag types showed signs of suggestive non-carcinogenic risk due to ingestion, while only one metal showed signs of cancer risk for the exposure pathway of dermal contact. But this metal is not the same in all the slag types. In BOS and EAF slag the metal that showed signs of risk due to dermal contact was vanadium while in BFS the metal was manganese. 64

74 6.3) Proctor s Research The risk approach used in the present research for construction workers is adopted from Proctor et al Proctor has done a probabilistic risk assessment. The selection of COI s in Proctor et al 2002 is by comparing the constituent metal concentration in steel slag and the background concentration. This comparison was performed using a Behrens- Fisher t-test for all metals. Metal concentrations in slag that were less than or equal to background concentrations in soil were considered to pose no potential hazard and were not retained for further evaluation. Table 24 presents the list of COI s in Proctor s research. The number of COI s of Proctor is less than the number in this thesis as my thesis adopts a deterministic approach rather than a probabilistic approach. 65

75 Table 24: List of COI s for construction workers in Proctor et al Slag type COI in steel slag Blast furnace slag Beryllium and Chromium Basic oxygen slag Chromium, Manganese and Vanadium. Electric arc furnace slag Chromium, Manganese and Vanadium. The list of COI in Proctor research is far less than the list in my thesis as the COI s in Proctor s research. Subsequently the number of metals for which risk was calculated was less in Proctor s research and according to Proctor et al 2002, basic oxygen slag and electric arc furnace slag posed hazard (non-carcinogenic risk) for construction workers and non of the slag types were a concern for cancer risk. 66

76 6.4) Risk Assessment Results Based On Contaminated Groundwater The risk assessment for inhabitants who live around the roads with alternative materials in their base layers was done using the same excel model. The risk assessment for the inhabitants can be carcinogenic and non-carcinogenic. Carcinogenic risk is termed as suggestive evidence of cancer potential and similarly is non-carcinogenic risk termed as suggestive evidence of non-cancer potential. As discussed earlier in section risk values are calculated by dividing the ADD over the reference dose (Rfd) and multiplying ADD with slope factor to obtain the hazard (non-carcinogenic risk) and carcinogenic potential. The ADD for the inhabitants ingesting the contaminated groundwater is calculated using Swartjes The ADD values due to blast furnace steel slag calculated for the inhabitants are presented in tables 25, 26 and 27 shown below. 67

77 Table 25: ADD for groundwater ingestion from blast furnace slag. Constituent metals Thallium Chromium Vanadium Beryllium Antimony Aluminum Arsenic Barium Cadmium Calcium Copper Cobalt Iron Lead Magnesium Manganese Mercury Molybdenum Nickel Phosphorous Selenium Silicon Silver Sulphur Tin Zinc Average daily dose for oral ingestion ND 1.23E E E-01 ND 9.13E E E+00 ND 5.84E E E E E E E+02 ND 3.29E E E E E+03 ND 2.46E E E-01 68

78 Table 26: ADD values for basic oxygen slag Metals Thallium Chromium Vanadium Beryllium Antimony Aluminum Arsenic Barium Cadmium Calcium Copper Cobalt Iron Lead Magnesium Manganese Mercury Molybdenum Nickel Phosporous Selenium Silicon Silver Sulphur Tin Zinc Average daily dose for oral ingestion of water 2.06E E E E E E+02 ND 2.12E E E E E E E E E E E E E E E E E E E+00 69

79 Table 27: ADD values from groundwater ingestion from electric arc furnace slag Metals Thallium Chromium Vanadium Beryllium Antimony Aluminum Arsenic Barium Cadmium Calcium Copper Cobalt Iron Lead Magnesium Manganese Mercury Molybdenum Nickel Phosporous Selenium Silicon Silver Sulphur Tin Zinc Average daily dose for oral ingestion of groundwater 2.88E E E E E E E E E E E E E E E E E E E E E E E E E E+00 70

80 The concentrations of contaminants in groundwater are determined by running the HYDRUS model. Section discusses about the various scenarios analyzed in the present research by altering the Kd values of base layer and soil layer. These scenarios (also termed as groups in this thesis) and were presented in table 7. There are four groups/scenarios namely, group 1, group 2, group 3 and group 4. The risk values of a constituent metal of a secondary material largely depended on the input parameters Kd of base layer and the Kd of the soil layer i.e., the group it belonged to. Tables 28 and 29 provide a summary of the risk values corresponding to the group for all the secondary materials alternative materials used in present research. These ranking are provided so as to show the scenario that caused highest risk. These ranking are based on the comparison of the final risk values obtained from the excel risk model for each scenario. Table 28: Rankings of carcinogenic risk values Group 1 Group 2 Group 3 Group 4 Basic oxygen slag Blast furnace slag Electric arc furnace slag

81 Table 29: Summary of non-carcinogenic risk values Group 1 Group 2 Group 3 Group 4 Basic oxygen slag Blast furnace slag Electric arc furnace slag From tables 28 and 29, it is evident that the worst case would be group 3 and we assessed the risk to groundwater due to the group 3 scenario. Group 3 scenario has high Kd for base layer and low Kd for soil layer below the base layers. Tables 28, 29 and 30 show the risk values obtained from the risk model for cancer risk for blast furnace slag, basic oxygen slag and electric arc furnace slag respectively. The risk values calculated are high which suggests that a risk assessment with a probabilistic approach is warranted in order to accurately assess the risk. 72

82 Table 30: Cancer risk values from groundwater due to blast furnace slag Thallium ND Chromium 2.53E+00 Vanadium 0.00E+00 Beryllium 4.07E-02 Antimony ND Aluminum 0.00E+00 Arsenic 2.93E-03 Barium 0.00E+00 Cadmium ND Calcium 0.00E+00 Copper 0.00E+00 Cobalt 0.00E+00 Iron 0.00E+00 Lead 0.00E+00 Magnesium 0.00E+00 Manganese 0.00E+00 Mercury ND Molybdenum 0.00E+00 Nickel 1.64E-03 Phosphorous 0.00E+00 Selenium 0.00E+00 Silicon 0.00E+00 Silver ND Sulphur 0.00E+00 Tin 0.00E+00 Zinc 0.00E+00 Fluorine 0.00E+00 73

83 Table 31: Cancer risk values from groundwater for basic oxygen slag Thallium 0.00E+00 Chromium 6.06E+00 Vanadium 0.00E+00 Beryllium 4.42E-03 Antimony 0.00E+00 Aluminum 0.00E+00 Arsenic ND Barium 0.00E+00 Cadmium 2.64E-02 Calcium 0.00E+00 Copper 0.00E+00 Cobalt 0.00E+00 Iron 0.00E+00 Lead 0.00E+00 Magnesium 0.00E+00 Manganese 0.00E+00 Mercury 0.00E+00 Molybdenum 0.00E+00 Nickel 5.18E-03 Phosphorous 0.00E+00 Selenium 0.00E+00 Silicon 0.00E+00 Silver 0.00E+00 Sulphur 0.00E+00 Tin 0.00E+00 Zinc 0.00E+00 74

84 Table 32: Cancer risk values from groundwater for electric arc furnace Thallium 0.00E+00 Chromium 1.43E+01 Vanadium 0.00E+00 Beryllium 6.19E-03 Antimony 0.00E+00 Aluminum 0.00E+00 Arsenic 3.39E-03 Barium 0.00E+00 Cadmium 5.71E-02 Calcium 0.00E+00 Copper 0.00E+00 Cobalt 0.00E+00 Iron 0.00E+00 Lead 0.00E+00 Magnesium 0.00E+00 Manganese 0.00E+00 Mercury 0.00E+00 Molybdenum 0.00E+00 Nickel 3.63E-02 Phosphorous 0.00E+00 Selenium 0.00E+00 Silicon 0.00E+00 Silver 0.00E+00 Sulphur 0.00E+00 Tin 0.00E+00 Zinc 0.00E+00 It is an interesting observation that all the metals pose carcinogenic risk all the three types of steel slag. But there is a significant difference in the risk values with respect to each slag type. 75

85 Table 32: Non-cancer risk values from groundwater for blast furnace slag Thallium Chromium Vanadium Beryllium Antimony Aluminum Arsenic Barium Cadmium Calcium Copper Cobalt Iron Lead Magnesium Manganese Mercury Molybdenum Nickel Phosphorous Selenium Silicon Silver Sulphur Tin Zinc ND 3.09E E E+00 ND 4.57E E E+00 ND NA 2.24E E E+02 NA NA 1.79E+02 ND 3.29E E E E+00 NA ND NA 3.60E E-01 76

86 Table 33: Non-cancer risk values from groundwater for basic oxygen slag Thallium 1.29E+02 Chromium 7.39E+01 Vanadium 1.66E+02 Beryllium 2.06E-01 Antimony 1.08E+01 Aluminum 3.75E+01 Arsenic ND Barium 5.30E-01 Cadmium 4.32E+00 Calcium NA Copper 9.77E-01 Cobalt 2.83E-01 Iron 6.90E+02 Lead NA Magnesium NA Manganese 8.62E+02 Mercury 3.43E-01 Molybdenum 2.90E+01 Nickel 3.09E-01 Phosphorous 1.93E+05 Selenium 3.70E+00 Silicon NA Silver 3.91E+00 Sulphur NA Tin 1.41E-02 Zinc 2.16E-01 77

87 Table 34: Non-cancer risk values from groundwater for electric arc furnace slag Thallium 1.80E+02 Chromium 1.74E+02 Vanadium 8.55E+01 Beryllium 2.88E-01 Antimony 1.26E+01 Aluminum 3.96E+01 Arsenic 7.54E+00 Barium 3.29E+00 Cadmium 9.36E+00 Calcium NA Copper 5.19E+00 Cobalt 2.73E-01 Iron 7.08E+02 Lead NA Magnesium NA Manganese 9.05E+02 Mercury 0.00E+00 Molybdenum 7.20E+00 Nickel 2.16E+00 Phosphorous 1.04E+05 Selenium 4.11E+00 Silicon NA Silver 2.67E+00 Sulphur NA Tin 2.06E-02 Zinc 7.17E-01 It can be observed from the model that the non cancer risk values pertaining to the use alternative materials for group 3 scenario are very high. This result of this very high non cancer risk values could be of concern. But as stated earlier in the document, these values are only a suggestive evidence of non-carcinogenic risk to the humans who ingest the contaminated ground water. In order to check the actual risk, the average daily dose of all the metals that posed a suggestive non-cancer risk was checked against the MCL of those metals. The list of MCL is presented in table 36.If the average daily dose was higher than the MCL of that metal in the groundwater than the risk value does show some concern. 78

88 Table 36: List of MCL s for inorganic contaminants. Metals MCL (mg/l) Potential health effects from ingestion Antimony Increase in blood cholesterol, decrease in blood sugar Arsenic Skin damage or problems with circulatory systems, and may have increased risk of getting cancer Barium 2 Increase in blood pressure Beryllium Intestinal lesions Cadmium Kidney damage Chromium 0.1 Allergic dermatitis Copper 1.3 Short term exposure: Gastrointestinal distress Long term exposure: liver or kidney damage Lead Kidney problems; high blood pressure Mercury Kidney damage Selenium 0.05 Hair or finger nail loss; numbness in fingers or toes; circulatory problems Thallium Hair loss; changes in blood; kidney, intestine or liver problems. The concentration of all the contaminants reaching the groundwater from the secondary materials was found in excess to their MCL s. 79

89 6.2.1) HYDRUS sensitivity Results: The partition coefficient does show some significant affect on the bottom concentration vs. time graph. This change is shown below in figures 10 and 11. Figure 10 shows the graph between bottom concentration and time in years for a partitioning coefficient (Kd) of 1 for the base layers. Figure 11 shows the similar graph but with a partition coefficient of 10 for the base layer. Figure 10: Bottom concentration Vs Time (days) for Kd 1. Figure 11 shows the graph between bottom concentrations vs. time in days with Kd value of 10. The graph is shifted towards right side pointing towards delay in time for the contaminants reaching the groundwater. 80

90 Figure 11: Bottom concentration VS time (days) for Kd 10 The number of days taken for the total concentration of contaminants to reach the groundwater is increased by more than 100%. The Kd value of the soil layer between the road base layer and the groundwater is also increased to 10 and the figure 12 shows the graph between time and bottom concentration. 81

91 Figure 12: Bottom concentration VS time (Kdb and Kds are 10) As the partition coefficient values of the base layer and the soil layer are raised to 10, the maximum concentration value or the peak of the graph between the time and bottom concentration in figure 12 has moved up and the total time required for the contaminants to leach to groundwater has decreased by small amount. The pattern of the leachate is now checked for low partition coefficient value for base layer but high value for soil layer. Figure 13 is graphed between time and bottom concentration with base layer Kd value of 1 and soil layer Kd value of

92 Figure 13: Bottom concentration VS time (Kdb= 1 and Kds= 10) The peak of the graph between the time and bottom concentration is the highest as shown in figure 13 above. The depth of the soil profile is decreased to 0.8 m in order to observe the change in the leachate concentration and transport. Using the original depth of 1 m for the soil profile the graph between bottom leachate concentration Vs time is shown in figure 14. If the depth of the soil profile is decreased with other parameters being same then the resulting graph is shown in figure 14 below. 83

93 Figure 14: Bottom concentration Vs Time (days) with decrease in road base layer depth There is no significant difference in the graph between the default scenario and the scenario in which the depth of the road base layer is decreased. To find the main effect of each factor, the following equation is used. Estimated mean response for factor A at high level = (C a +C ab +C ac + C abc )/ Equation 10 Similarly each row with a negative sign in the table 8 represents a treatment with factor A at its low level. Estimated mean response for factor A at low level = (C 1 + C b +C c + C bc )/4 ----Equation 11 The main effect of factor A is calculated using the equation shown below. A effect estimate = difference of equation and equation. 84