Properties and Performance of Photocatalytic Concrete

Mahsa Heidari Dolatabadi

A thesis submitted in conformity with the requirements for the degree of Master of Applied Science Graduate Department of Civil Engineering University of Toronto

Mahsa Heidari Dolatabadi

Master of Applied Science

Graduate Department of Civil Engineering University of Toronto

2013 Abstract

This research program is focused on the photocatalytic cement with emphasis on evaluating impacts on concrete’s physical, transport and durability properties. The scope of this project is to examine three key aspects of photocatalytic concrete including: a critical review of currently reported applications; an examination of air pollution concentrations in Ontario to assess the potential effectiveness of photocatalytic concrete, with respect to NOx; and an experimental study to characterize the material properties.

Research findings revealed comparability between photocatalytic concrete and conventional concrete in mechanical and fluid transport properties. Although photocatalytic concrete resisted rapid freeze and thaw damage very well, in terms of de-icer salt scaling performance, only formed surface performed well and highly variable results for photocatalytic and GU concrete was observed for the finished surface.

Acknowledgments

First and foremost, I would like to express my sincere appreciation to my supervisors, Professor Daman Panesar and Professor Doug Hooton, for their guidance, support, and friendship. Most of all, I would like to extend my gratitude to Professor Daman Panesar, who never ceased in challenging me and sharing her precious time and positive insights, for offering me the research assistant position and providing me with such a life changing experience. I am obliged for her patience and encouragement during this project.

I also place on record my sincere thanks to Olga Perebatova, who has rendered aid above and beyond the line duty. This project would not have been possible without her unconditional help and support.

Also, I would like to take this opportunity and gratefully acknowledge:

 The financial support provided by the Ministry of Transportation Ontario, the Natural Sciences and Engineering Research Council of Canada (NSERC), and the Department of Civil Engineering;  The material supply by Essroc Cement Corporation Canada, Euclid Concrete Admix, and BASF Canada;  The technical support provided by talented Giovanni Buzzeo, Renzo Basset, and Bob Manson;  The laboratory preparation and testing assistance provided by Benjamin Shindman, Majella Anson-Cartwright, Ardavan Amirchoupani, and Eric Liu.

I am indebted to many people during my time at University of Toronto:

 Majella, my best friend, mentor, officemate, for always being my rock! Without knowing she was in my corner I could never have made it through;  Ardavan and Eric, my amazing officemates and partners in crime, for their assistance, support, and being the best friends anyone could ask for;  The Concrete Materials Group for providing me with countless unforgettable memories which I will cherish for the rest of my life.

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Finally, most important of all, from the depth of my heart, thanks to my dearest family:

 My mom and dad for their moral and emotional support. Thank you for being so patient with me during the though emotional times. Words cannot even begin to express my gratitude for the strength you provided me with throughout the challenging moments;  My one and only sister, my bestie, my joy, Maral. Thank you for always being there to listen to me ramble and offering me an oasis of solitude in the eye of the storm. Without you, I truly am nothing;  My cousin, Maryam. You showed me how to dream, aim, find, and pursue a purpose in my life. Thank you for always believing in me.

Table of Contents

Properties and Performance of Photocatalytic Concrete ...... i

Acknowledgments ...... iii

Table of Contents ...... v

List of Tables ...... ix

List of Figures ...... xi

Chapter 1 Introduction ...... 1

1.1 Background ...... 1

1.2 Objectives and Scope ...... 2

Chapter 2 Literature Review ...... 4

2.1 TiO2 and Photocatalytic Concrete ...... 4

2.2 Photocatalytic Mechanism ...... 6

2.3 Properties ...... 8

2.3.1 Self-cleaning ...... 8

2.3.2 De-polluting ...... 9

2.3.3 Other Properties ...... 15

2.4 Applications ...... 16

2.4.1 Field Studies ...... 17

Chapter 3 Potential Impacts of Photocatalytic Concrete on Air Quality in Ontario ...... 20

3.1 Introduction ...... 20

3.2 What is Smog? ...... 21

3.3 Air Quality in Ontario Cities ...... 22

3.4 Pollution Fluctuations ...... 26

3.4.1 Hourly Trend ...... 26

3.4.2 Monthly Trend ...... 29

3.5 Estimated Removal Efficiency ...... 32

Chapter 4 Experimental Program ...... 35

4.1 Introduction ...... 35

4.2 Materials ...... 35

4.2.1 Cementing Materials ...... 35

4.2.2 Aggregate ...... 37

4.2.3 Chemical Admixtures ...... 37

4.3 Phase I ...... 38

4.3.1 Introduction ...... 38

4.3.2 Mix Design ...... 38

4.3.3 Mixing, Casting and Curing ...... 38

4.3.4 Testing Procedure ...... 39

4.4 Phase II ...... 40

4.4.1 Introduction ...... 40

4.4.2 Mix Design ...... 41

4.4.3 Mixing, Casting and Curing ...... 41

4.4.4 Testing Procedure ...... 42

4.5 Phase III ...... 44

4.5.1 Introduction ...... 44

4.5.2 Mix Design ...... 46

4.5.3 Mixing, Casting and Curing ...... 46

4.5.4 Testing Procedure ...... 47

4.6 Phase IV ...... 49

4.6.1 Introduction ...... 49

4.6.2 Mix Design ...... 50

4.6.3 Mixing, Casting and Curing ...... 50 vi

Chapter 5 Results and Discussion ...... 51

5.1 Phase I ...... 51

5.1.1 Compressive Strength ...... 51

5.1.2 Porosity ...... 53

5.1.3 Effects of Paste Mix Design Variables – Phase I ...... 55

5.2 Fresh Concrete Properties ...... 56

5.2.1 Phase II ...... 56

5.2.2 Phase III ...... 56

5.2.3 Phase IV ...... 57

5.2.4 Discussion of the Effects of Mix Design Variables ...... 58

5.3 Mechanical Properties ...... 59

5.3.1 Phase II ...... 59

5.3.2 Phase III ...... 62

5.3.3 Phase IV ...... 65

5.3.4 Discussion of the Effects of Mix Design Variables ...... 69

5.4 Transport Properties ...... 69

5.4.1 Phase II ...... 69

5.4.2 Phase III ...... 70

5.4.3 Phase IV ...... 72

5.4.4 Discussion of the Effects of Mix Design Variables ...... 74

5.5 Durability Properties ...... 74

5.5.1 Phase III ...... 74

5.5.2 Phase IV ...... 81

5.5.3 Effects of Mix Design Variables ...... 85

Chapter 6 Conclusion ...... 87

Chapter 7 Recommendations for Future Work ...... 89 vii

References ...... 90

Appendix A: Hourly Pollution Data for Toronto E Station ...... 97

Appendix B: Monthly Pollution Data for Cities with the Greatest Number of Smog Advisories in Ontario ...... 99

Appendix C: Pollution Conversion (ppb to mg/h/m2) ...... 104

Appendix D: Test Data ...... 109

D.1 Phase II ...... 109

D.2 Phase III ...... 113

D.3 Phase IV ...... 120

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List of Tables

Table 3.1: Air quality index range ...... 23

Table 3.2: Limiting values for emissions in Ontario ...... 24

Table 3.3: Regions in Ontario with the highest smog advisories ...... 25

Table 3.4: Station locations ...... 26

Table 3.5: Percentage removal efficiency (%) ...... 34

Table 4.1: Chemical composition of cementing materials ...... 36

Table 4.2: Density of powder materials ...... 37

Table 4.3: Mix design proportions (Phase I) ...... 39

Table 4.4: Mix design proportions (Phase II) ...... 41

Table 4.5: Fresh concrete properties tests ...... 42

Table 4.6: Mechanical properties tests ...... 43

Table 4.7: Mix proportions used for the foam index test method ...... 45

Table 4.8: Mix design proportions (Phase III) ...... 46

Table 4.9: Transport properties tests ...... 47

Table 4.10: Durability properties tests ...... 48

Table 4.11: Mix design proportions (Phase IV) ...... 50

Table 5.1: Strength and porosity assessments (Phase I) ...... 52

Table 5.2: Fresh properties of plastic concrete (Phase II) ...... 56

Table 5.3: Fresh properties of plastic concrete (Phase III) ...... 57

Table 5.4: Fresh properties of plastic concrete (Phase IV) ...... 57

Table 5.5: Air content characterization (Phase III) ...... 64

Table 5.6: Air content characterization (Phase IV) ...... 67

List of Figures

Figure 2.1: TiO2 reaction process ...... 5

Figure 2.2: Photocatalytic mechanism ...... 7

Figure 2.3: Photocatalytic conversion of NOx to HNO3 ...... 8

Figure 2.4: effects of flow rate and relative humidity on NOx reduction efficiency ...... 10

Figure 2.5: Dynamic method, fixed [NO] ...... 13

Figure 2.6: abrasion and wear resistance properties of TiO2 ...... 16

Figure 3.1: Windsor DT O3 hourly data from May to Sept ...... 27

Figure 3.2: Windsor DT NOx hourly data from May to Sept ...... 27

Figure 3.3: Windsor DT O3 hourly data from Oct to April ...... 28

Figure 3.4: Windsor DT NOx hourly data from Oct to April ...... 28

Figure 3.5: O3 monthly data for regions in Ontario with the highest smog advisories ...... 30

Figure 3.6: NOx monthly data for regions in Ontario with the highest smog advisories ...... 31

Figure 3.7: Average monthly NO concentration (mg/h/m2) ...... 33

Figure 3.8: Average monthly NO concentration for Toronto (mg/h/m2) ...... 33

Figure 4.1: Mix#1 and Mix#2 before addition of AEA solution (left), foam on the surface after addition of AEA and shaking for 45s (right) ...... 45

Figure 5.1: Strength of samples (Phase I) ...... 53

Figure 5.2: Porosity of samples (Phase I) ...... 54

Figure 5.3: Porosity vs. Strength ...... 55

Figure 5.4: Air content vs. Slump ...... 58 xi

Figure 5.5: Compressive strength of concrete (Phase II) ...... 60

Figure 5.6: Density of concrete (Phase II) ...... 60

Figure 5.7: Ultrasonic pulse velocity (Phase II) ...... 61

Figure 5.8: Air content (Phase II) ...... 61

Figure 5.9: Compressive strength of concrete (Phase III) ...... 62

Figure 5.10: Density of concrete (Phase III) ...... 63

Figure 5.11: Ultrasonic pulse velocity (Phase III) ...... 63

Figure 5.12: Air content (Phase III) ...... 65

Figure 5.13: Compressive strength of concrete (Phase IV) ...... 66

Figure 5.14: Ultrasonic pulse velocity (Phase IV) ...... 66

Figure 5.15: Air content of concrete (Phase IV) ...... 68

Figure 5.16: Influence of air content on compressive strength (28d) ...... 68

Figure 5.17: Rapid chloride permeability of concrete (Phase II) ...... 69

Figure 5.18: Rapid chloride permeability of concrete (Phase III) ...... 70

Figure 5.19: Initial sorptivity of finished and formed surface concrete at 28 days (Phase III) ....71

Figure 5.20: Initial sorptivity of finished and formed surface concrete at 56 days (Phase III) ....71

Figure 5.21: Rapid chloride permeability of concrete (Phase IV) ...... 72

Figure 5.22: Initial sorptivity of finished and formed surface concrete at 28 days (Phase IV) ....73

Figure 5.23: Influence of air content on RCPT result at 28d ...... 73

Figure 5.24: Salt scaling mass loss of finished surface (Phase III) ...... 76

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Figure5.25: Salt scaling mass loss of formed surface (Phase III) ...... 76

Figure 5.26: GU concrete (finished surface) after 50 freeze-thaw cycle (Phase III) ...... 77

Figure 5.27: PH concrete (formed surface) after 50 freeze-thaw cycle (Phase III) ...... 77

Figure 5.28: GU concrete (formed surface) after 50 freeze-thaw cycle (Phase III) ...... 78

Figure 5.29: PH concrete (formed surface) after 50 freeze-thaw cycle (Phase III) ...... 78

Figure 5.30: Durability factor after 300 rapid freeze-thaw cycles (Phase III) ...... 79

Figure 5.31: GU and GU+25%GGBFS prisms after 300 rapid freeze-thaw cycles (Phase III) ...80

Figure 5.32: PH and PH+25%GGBFS prisms after 300 rapid freeze-thaw cycles (Phase III) ....80

Figure 5.33: Salt scaling mass loss of finished surface (Phase IV) ...... 82

Figure 5.34: Salt scaling mass loss of formed surface (Phase IV) ...... 82

Figure 5.35: GU concrete (finished surface) after 50 freeze-thaw cycle (Phase IV) ...... 83

Figure 5.36: PH concrete (finished surface) after 50 freeze-thaw cycle (Phase IV) ...... 83

Figure 5.37: GU concrete (formed surface) after 50 freeze-thaw cycle (Phase IV) ...... 84

Figure 5.38: PH concrete (formed surface) after 50 freeze-thaw cycles (Phase IV) ...... 84

Figure 5.39: Influence of air content on salt scaling for finished surface after 50 cycles ...... 85

Figure 5.40: Influence of air content on salt scaling for formed surface after 50 cycles ...... 86

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Chapter 1 Introduction 1.1 Background

Photocatalytic concrete is an innovative advancement in material science that enables the photocatalytic phenomenon to occur within the building material itself and has good potential to reduce airborne pollutants such as sulfur oxide (SOx), particulate matter (PM10), volatile organic compounds (VOCs), and nitrogen oxide (NOx). Photocatalysis is a process that uses the power of the ultraviolet (UV-A) portion of sunlight to accelerate the natural oxidation process to decompose pollutants. In the past decade, photocatalytic technologies have been applied to glass, ceramic, and cement-based materials. The photocatalytic mechanism is not new, in fact the process has been understood and applied since the 1960s (Fujishima et al., 2000). There has been considerable focus on water treatment technologies, but the application of photocatalytic oxidation to construction materials has been gaining attention since the 1990s. More recently, photocatalysis has been integrated directly into construction building materials. Its effectiveness as a sustainable option is currently being assessed through pilot studies in France, Italy, the Netherlands, and Japan. Photocatalytic concrete is also known as smog-eating and self-cleaning concrete because it assists in air pollution reduction (Essroc Italcementi Group, 2009).

Environmental pollution has raised global attention of the need to implement environmentally friendly technologies and practices. Industry flue gases, local traffic and diesel engines play major roles in generating emissions like volatile organic compounds (VOCs), hydrocarbons that have evaporated from chemical plants; nitrogen oxides (NOx) produced primarily by internal combustion engines; and sulphur oxides (SOx) formed when fuel such as coal and oil is burned

(Hassan, 2010). NOx (NO and NO2) is responsible for ozone and particulate build-up through photochemical reactions with hydrocarbon (Barbesta and Schaffer, 2009). Due to these highly reactive gases, there are a variety of health and environmental impacts such as urban smog and acid rain, which harms forests, crops and aquatic life. Since the passage of the Clean Air Act in

1970, in the United States, the concentration of principal air pollutants, except NOx, have decreased (Hassan, 2010).

Thus, NOx emissions have been a focus of environmental regulations and can be controlled by two different approaches: the reduction of NOx back to molecular nitrogen (N2), or its oxidation to nitrogen dioxide (NO2) and nitric acid (HNO3). For example, the oxidation of nitric acid completes the nitrogen fixation and has useful applications such as in fertilizers. Many organic compounds and air pollutants can be decomposed by ultraviolet radiation but this process is extremely slow. The conversion of NOx to low concentrated nitrates makes this pollutant compound soluble in water, which can be flushed away by rain. This type of photochemical conversion is called photocatalytic oxidation (PCO) (Husken, 2009).

The sun can provide up to 3×1024 J of energy per year, which is 10,000 times more than the whole world’s annual energy consumption (Butcher et al., 1992). The fact that many compounds of air pollutants such as NOx and SOx can be decomposed by ultraviolet radiation has led to the exploration of the uses of solar energy in context with building materials (Diamanti et al., 2008).

Photocatalytic materials contain nano-particles of titanium dioxide (TiO2); that can accelerate the oxidation and decomposition of organic and inorganic compounds in the presence of sunlight. Photo means light and catalysis is the process that accelerates the rate of reaction without being consumed (TioCem, 2010). TiO2 has the ability to enhance the durability of concrete by accelerating the breakdown of organic pollutants and micro-organisms to help reduce concrete discoloration and deterioration. It can be applied to water and cement to act as purification when used as a catalyst, which can be activated with the UV-A part of sunlight (Ballari et al., 2009).

1.2 Objectives and Scope

The intent of this study is to test photocatalytic concrete properties and long-term performance. This study also examines its potential pollution abating effectiveness in Ontario. The potential usage of photocatalytic concrete cannot solely be based on its benefits related to pollution degradation; a complete evaluation of its durability is required as well as other critical factors that need to be considered in selecting environmentally friendly building materials. There is a current need for improved materials and evaluation of crucial parameters that influence and impact the physical and mechanical properties of the photocatalytic concrete. 2

The scope of this research is:

 To conduct a detailed literature review.

 To conduct a laboratory experimental program to characterize the mechanical, transport and durability properties of photocatalytic concrete in comparison with conventional concrete.

 To examine high pollution regions in Ontario (including Toronto) and assess the interplay between pollutant concentrations.

 To identify regions where photocatalytic concrete infrastructure has the potential to be most effective based on the experimental results and the literature reported ranges for

NOx abatement rates.

 To reveal the influence of environmental conditions, particularly temperature, on the photocatalytic pollution degradation mechanism in order to develop a correlation between photocatalytic effectiveness and seasonal climate.

Chapter 2 Literature Review

2.1 TiO2 and Photocatalytic Concrete

Titanium is the world’s fourth most abundant metal and the ninth most abundant element, constituting about 0.63% of the Earth’s crust (Carp et al., 2004). TiO2 is a semiconductor, non- toxic, and chemically stable material. It can be crystallized into three different molecule structures: rutile, anatase, and brookite. Rutile is used as a pigment for relatively white paints with low photocatalytic reactivity. Both the anatase and rutile forms act similarly in photocatalysis (Hunger et al., 2008). Anatase is preferable due to its high reactivity (Pacheo- Torgal and Jalali, 2011).

TiO2 can be integrated in the cement manufacturing process to produce photocatalytic cement. Normal daylight can be used for the photocatalytic reaction (Beeldens, 2006). When this type of cement is used in concrete structures, a charge is created on the surface that reacts with external substances to decompose air pollutants such as NOx (Chusid, 2006). TiO2 can be integrated within the concrete pavement surface to act as an accelerator of a natural oxidation process. It promotes faster decomposition of NOx and SOx from the air. (Essroc Italcementi Group, 2008).

As shown in Figure 2.1, when TiO2 is activated by UV light, in a catalytic reaction it first breaks down NOx gases into nitric acid (HNO3) that then adhere to water droplets. These water droplets will then be washed away by rain. Photocatalytic effect is associated with a reduced nitric oxide

(NO) oxidation to nitrates and these ions are flushed from the surface as a weak HNO3. The whole reaction results in a significant reduction in the concentration of pollutants from the atmosphere when used on or in a concrete structure that is exposed to UV-A and placed close to the pollution source (Hassan, 2010).

For pavement block applications, since PCO turns the pollutants into water soluble compounds, the porosity of the block is very important in the ability to remove NO, and an increase in the porosity will promote pollution removal. The porosity is affected by aggregate size, water-to- cement ratio, and, in general, the mix design of the concrete (Poon and Cheung, 2007).

The presence of light, which is in direct contact with the pavement surface, is also a significant factor (Ballari et al., 2010). This is a promising approach for self-cleaning surfaces and for solving the environmental problem, such as air pollution, by degradation of NOx (Poon and Cheung, 2007).

Figure 2.1: TiO2 reaction process (TioCem, 2010)

Some of the applications of TiO2 nano-particles in the construction industry include self cleaning, air cleaning, acting as an anti-bacterial, and anti-fogging (Pacheo-Torgal and Jalali, 2010). The study of photocatalytic technology started as a treatment for water polluted with toxic substances and has become this technology’s main task. Recently, commercial products such as anti-fog products for mirrors and glasses, anti-bacterials, fibres, water purifiers, self- cleaning items such as car coatings, and construction materials have incorporated TiO2 (Essroc Italcementi Group, 2009). In the past decade, Europeans have started implementing the self- cleaning benefits of photocatalytic concrete technology on building surfaces, which allows maintaining an unaltered aesthetic appearance over time (Cassar et al., 2007).

More recently, photocatalysis has been applied as a coating on the surface of buildings and pavements for its de-polluting effect rather than for self-cleaning. Similar projects have been launched in the European and American market with the aim of having a positive impact on urban air quality (Ircelyon, 2010). Hassan (2009) showed through a life cycle assessment (LCA) that a TiO2 coating will have an overall positive effect on the environment. An LCA is an investigation and evaluation of all the environmental impacts of a given product for every stage 5

of its existence, including material extraction and processing, manufacturing, transportation, use, and disposal. Since photocatalytic concrete is a fairly new technology, its structural properties and functional characteristics are not fully uncovered. Further research and studies are required in order to demonstrate the benefits of this innovative (Crispino and Lambrugo, 2007).

2.2 Photocatalytic Mechanism

TiO2 is the primary photocatalytic ingredient and studies have shown that TiO2 incorporated into building materials can keep surfaces clean (surface-cleaning) and significantly reduce smog-forming air pollutants (pollution abatement) (Italcementi, 2008).

The photocatalytic mechanism required for TiO2 to degrade pollutants is illustrated in Figure

2.2. As soon as a TiO2 surface is exposed to UV light, two types of photochemical reactions occur: photo-induced redox reactions of the absorbed pollutants and photo-induced hydrophilic conversion. When TiO2 absorbs UV-A radiation from sunlight or an illuminated light source such as a fluorescent lamp, it will produce pairs of electrons and holes. In the presence of light, the electrons become excited and produce energy. The photo-produced holes represent stored energy. The excess energy creates the negative-electron (e-) and positive-hole (h+) pair (Gens Nano, 2011). With water and UV light present, the electron hole reacts with the OH-group from adsorbed water, generating hydroxyl radicals and charged species at the surface of the catalyst (Husken et al., 2009).

During this encounter, an OH- group loses an electron and highly reactive hydroxyl radicals can form. Such radicals react with airborne pollutant molecules that are adsorbed by the particle’s surface. These reaction products remain on the surface until they are fully oxidized (Gens Nano, 2011).

Figure 2.2: Photocatalytic mechanism (Gens Nano, 2011)

In addition, the reducing power of the electrons can induce the reduction of molecular oxygen - (O2) to superoxide (O2 ). This is as effective as the holes and hydroxyl radicals in the chain reactions for breaking down organic compounds (Beeldens, 2006). Figure 2.3 demonstrates the photocatalytic conversion of NO, which leads to the formation of weak nitric acid HNO3. Most cement formulations are alkaline, which neutralizes HNO3. As shown in Equations 2.1 to 2.3, acid reacts with calcium carbonate, locking the NOx gases up in calcium nitrate and releasing

CO2 and water (Chen and Poon, 2009).

1 푁푂 + 2 푂2 → 푁푂2 (2.1)

1 2푁푂2 + 2 푂2 + 퐻2푂 → 2퐻푁푂3 (2.2)

퐻푁푂3 + 퐶푎퐶푂3 ↔ 퐶푎(푁푂3)2 + 퐻2푂 + 퐶푂2 (2.3)

Figure 2.3: Photocatalytic conversion of NOx to HNO3 (Chen and Poon, 2009)

2.3 Properties

2.3.1 Self-cleaning

The self-cleaning effectiveness of photocatalytic concrete is a function of the TiO2 content of the cement as well as TiO2 particle size. Pacheo-Torgal and Jalali (2011) demonstrated that higher

TiO2 content in cement increases the self-cleaning activity in the photocatalytic cement paste in comparison to cement mortars. Folli et al. (2010) studied the effect of TiO2 particle size on self- cleaning by investigating the degradation of Rhodamine B (RhB). The study found that mortars made with 100% anatase microsized (m-TiO2) with a particle size of 154 ± 48 nm showed higher self-cleaning results than nanosized (n-TiO2) mortar with a particle size of 18 ± 5 nm. 2 This is due to the fact that the m-TiO2 had a high surface area of 8.7 m /g for RhB absorption and a very low rate for recombination of photo-produced holes in the particle volume.

Furthermore, both m-TiO2 and n-TiO2 tend to overcharge the surface in high pH conditions, but m-TiO2 dispersion is better due to its relatively smaller agglomerates and relatively larger pores (Folli et al., 2010).

2.3.2 De-polluting

Berdahl and Akbari (2008) investigated the de-polluting rate of photocatalytic concrete consist of cement that included about 1% to 5% anatase TiO2 nano-particles. The results determined 2 3 3 that 1 m of TiO2 catalytic surface can clean up to 200 m of NOx and about 60 m of VOCs per day.

Folli et al.’s (2010) study on the influence of TiO2 particle size on the photocatalysis pollution- abating ability was conducted with the use of oxidation of gaseous NOx in the photocatalytic reactor. The study found that 100% anatase n-TiO2 mortar showed higher activity rather than m-

TiO2. NOx particles can easily penetrate and since n-TiO2 clusters had a higher available 2 specific area of 78.9 m /g, incorporation of n-TiO2 will enhance the de-pollution property (Folli et al., 2010).

An increase in the curing age as well as surface carbonation results in a decrease in the NOx removal efficiency of the TiO2 contained concrete. With an increase in curing time, the hydration products will increase, filling up the capillary pores and resulting in the development of diffusion barriers to both reactants and photons (Chen and Poon, 2009).

It has been found that porosity and surface roughness of the TiO2 cementitious materials affect their air-cleaning potential (Ramirez et al., 2010). In a review of nanotechnology, Pacheo-Torgal and Jalali (2011) mentioned that there is higher reduction in NOx by TiO2 cementitious composites that have high surface porosity. Furthermore, the type of surface finishing treatment can influence the active surface area, and shot-blasted paving block has higher rates of photocatalytic reaction at the surface in comparison to untreated paving block due to the increase in surface area (TioCem, 2010).

The impacts of common roadway contaminants on the photocatalytic reaction (NOx removal ability) and surface porosity of the top photocatalytic concrete layer over road pavements were examined by Dylla et al. (2011). The impacts of three contaminant types on the NOx removal efficiency, namely, dirt, motor oil, and de-icing salts were investigated. The results show that oil has the worst impact. In addition, as demonstrated in Figure 2.4, the study showed that the flow rate of the contaminants as well as lower relative humidity impact the removal efficiency. A

lower flow rate and lower humidity are favourable for increasing the rate of NOx removal of photocatalytic layer (Dylla et al., 2011).

Figure 2.4: Effects of flow rate and relative humidity on NOx reduction efficiency (Dylla et al., 2011)

Furthermore, Asadi et al. (2012) conducted a field study to investigate the parameters that influence the removal efficiency of the photocatalytic asphalt pavement. The results indicate that the maximum NOx removal efficiency of the TiO2 ranges from 34% to 62%. In addition, it has been found that an increase in relative humidity and flow rate will decrease the NOx removal efficiency of the photocatalytic-pervious concrete (Asadi et al., 2012).

The de-polluting efficiency of the TiO2-containing concrete blocks made out of local waste materials such as recycled aggregate (RA) and crushed recycled glass cullet were examined in

Poon and Cheung’s 2007 study. This efficiency was then compared with the natural TiO2- containing concrete as well as the influence of particle size in each case. A smaller amount of fine particles leads to a higher porosity for the surface layer. The study demonstrated that lower cement to aggregate ratio would result in a higher NO removal efficiency. The samples were tested at different curing ages and the results show that the removal efficiency would be stabilized after an initial decrease, which happens in the first 90 days (Poon and Cheung, 2007).

2.3.2.1 Measurement and Mathematical Modeling

Several studies have investigated modelling to determine the de-polluting efficiency of photocatalytic concrete. For example, the NOx flow-through method is described in Japanese 2 standard JIS TR Z 0018 (Cassar et al., 2007). For this test, a TiO2 paving block 100×200 mm is placed in water under a UV-transparent glass plate in a metal container while the surface of the sample is exposed to air with a NO concentration of 1 parts per million (ppm) by volume at a flow rate of 3 litre per minute (L/min), all while under controlled humidity and temperature. The NO removal efficiency is a function of temperature, relative humidity and contact time. The efficiency is measured based on a comparison between the inlet and outlet concentration of the - pollutants as well as the NO3 concentration of the water, in which the sample is immersed

(Cassar et al., 2007). Chen and Poon (2009) calculated the amount of NOx removal QNO x (µmol m-2) based on a similar testing procedure that complies with the ISO standard 22197-1:

f NO 0− NO dt − ( NO 2 − NO 2 0)dt Q = 22.4 (2.4) NO x A×T

Where NO 0 and NO are, respectively, the inlet and outlet concentration of NO, NO2 0 and

NO2 are, respectively, the inlet and outlet concentration of NO2 , t is the removal operation time, A is the sample surface area (m2), f is the flow rate (L/min) , and T is the duration of photocatalytic process. The constants were the UV-A intensity 0.6 ± 0.1 (w/m2), a temperature of 50ºC, and 30% relative humidity (Chen and Poon, 2009).

The dynamic method, with a fixed concentration of NO, is also used to assess the de-polluting efficiency (Cassar et al., 2007). The test apparatus consists of the reactor, which allows a sample of size 100×200 mm2; a light source with a UV-A radiation range of 300 to 400 nm; a testing gas supply restraining two stages of gas flows, polluted and transport fluid, with a flow volume of 3 L/min; and an analyzer to measure concentrations at 5-second intervals. Based on this test set-up, a model is derived to explain the reaction process in the reactor (Hunger and Brouwers, 2009).

The degradation of NO is illustrated in Figure 2.5 and can be measured by the NOx reduction percentage Q (Cassar et al., 2007):

NO Q = 1 − out × 100 (2.5) NO in

There are several stages in the conversion of NOx including the mass transfer from gas to catalyst surface, absorption by the surface, a photochemical reaction on the surface, desorption from the surface, and then a mass conversion into the fluid at the surface of the concrete (Zhao and Yang, 2003). The conversion rate at the surface should not be ignored because the degradation rate is much lower than the diffusion rate (Hunger et al., 2010).

Figure 2.5: Dynamic method, fixed [NO] (Husken et al., 2009)

It should be noted that only absorbed NO can be oxidized. In order to express this adsorption process, the Langmuir equation is used (Zhao and Yang, 2003):

μ Ka C θ = max (2.6) 1+ Ka C

where θ is the adsorbed NO amount per gram of the catalyst, μmax is the maximum amount of compounds adsorbed on the catalyst surface, Ka is the adsorption equilibrium constant, and C is the concentration of the contaminants in the gas phase. The degradation influencing factors include light intensity, reactant concentration, oxygen concentration, water vapour content, and temperature (Zhao and Yang, 2003). At different reaction times, the photocatalytic activity of nitrogen oxide reduction, AF (m·h-1), can be calculated as follows:

(C − C ) Q AF = Light Off Light On × × I (2.7) CLight Off S

where C is the concentration of NOx, NO2, and NO at equilibrium, S is the geometrical surface area, and I is the intensity of the luminous flux in W/m2. Overall, the de-polluting efficiency will increase if the contact time is longer, the temperature is higher, and the relative humidity is lower (Cassar et al., 2007).

Aside from the direct monitoring of NO reduction of the air, there is an indirect technique to measure the NOx reduction by the photocatalytic process. This is done by measuring the deposited nitrate salts (NO3) on the surface of the photocatalytic material (Beeldens, 2008).

Since nitrates are soluble in water, NO3 is collected from the sample by washing the surface.

The collected NO3 is then converted into NO2 by utilizing a colorimetric method of cadmium reduction, based on EPA Method 353.2, in order to measure the NO3 concentration (Osborn et al., 2012).

Knowing the nitrate concentration, the volume of NO contaminant in litres can be calculated by Equation 2.8:

Mass Contaminent (g) L.kPa 1 V = g × 8.3144 × T × (2.8) contaminant Molecular Weight ( ) mol .K air P (kPa ) contaminant mol air where 푇 and 푃 are the air temperature and pressure, respectively (Osburn et al., 2012).

2.3.3 Other Properties

Nazari and Riahi (2011) investigated the effects of TiO2 on the physical and mechanical properties of concrete that contained 45% ground granulated blast furnace slag (GGBFS) as a binder. The addition of GGBFS improves workability and decreases water demand, as it increases the paste volume due to the lower relative density of slag (Hinczak, 1990). The study examined the flexural strength, the pore structure by mercury intrusion porosimetry (MIP), X- ray diffraction (XRD), scanning microscopy (SEM), and heat of hydration and mass loss of the specimens by thermo-gravimetric analysis (TGA). The results showed that the addition of up to

3% TiO2 nano-particles by mass could increase the flexural strength, improve the pore structure and dispersion of the particles, and progress the formation of hydrated products (Nazari and Riahi, 2011).

Studies have investigated the early hydration behaviour of C3S pastes with the addition of TiO2. Results showed that the rate of hydration increased with addition of chemically non-reactive

TiO2 particles due to decrease in particle size (Jaypalan, 2010). However, Lee and Kurtis’s

(2010) study showed that hydration acceleration occurs only with 10% to 15% TiO2 pastes, while the hydration is delayed with 5% TiO2 paste. The compressive, tensile and flexural strengths of the cement mortar incorporating TiO2 were investigated in an attempt to provide a relationship between the TiO2 powders’ particle size and mechanical properties mortars (Kawakami et al., 2007).

In terms of durability, a study was conducted on a TiO2 concrete coating using SEM and energy dispersive spectroscopy (EDS) to determine the effects of wearing abrasion and wearing by a loaded-wheel tester (LWT) and rotary abrasion (RA) on the distribution of TiO2 particles on the surface (Hassan et al., 2010). The results show that NOx removal efficiency depends on the contaminant flow rates, air humidity, mix design of the coating, ambient temperature, and TiO2 content. Overall, the coating with 5% TiO2 was the most efficient in terms of the NO removal. As shown in Figure 2.6, after undergoing LWT and RA, there was a slight reduction in the rate of removal for the 5% TiO2 sample, whereas the sample with 3% TiO2 showed better removal efficiency after LWT than to RA. Furthermore, EDS results showed that there was no considerable change in the concentration of TiO2 (Hassan et al., 2010).

Figure 2.6: Effect of abrasion and wear resistance on NOx removal efficiency of TiO2 (Hassan et al., 2010) 2.4 Applications

There are various applications for photocatalytic materials in the construction industry. These applications range from self-cleaning facades to solar reactors for wastewater treatments. TiO2 can be used both as an additive in concrete and as paint for coating. The goal is to have as much

TiO2 as possible at the surface of the material (Beeldens, 2006).

In the construction industry, actual applications of TiO2 nano‐particles in concrete are minimal and are typically reserved for those fabricated bi‐layer concrete systems with a relatively high unit price. The reason for this is that TiO2 nano‐particles are expensive in relation to concrete, especially in the large volumes that are normally used to build concrete structures. Typical examples of products currently found are special concrete blocks, bricks, tiles or roof tiles where the TiO2 is applied as a top‐layer or coating (Broekhuizen et al., 2010).

The effectiveness of the photocatalytic oxidation reactions is related to the area of the photocatalytic surface exposed to air and sunlight, allowing a variety of possible applications for cement-based photocatalytic materials in horizontal applications, such as concrete pavements and roofing tiles; on vertical applications, such as in paints, renderings, concrete panels, and sound-absorbent elements for buildings and roads; and in tunnels that are equipped with UV-A lamps (Cassar et al., 2007).

2.4.1 Field Studies

Although environmental and operational variables complicate the assessment of field NOx reduction, various field studies have been done to quantify NOx reduction and to confirm the results from pilot and laboratory studies:

 Italcementi Group (2008) installed a thin layer of photocatalytic mortar on an asphalt road in a heavily travelled (over 1000 vehicles/hour) two-way road in the Segrate area of Milan as their first photocatalytic experiment. The results, which were dependent on light intensity, relative humidity, pollution concentration, and wind speed and direction, showed up to 60%

improvement in NOx abatement with the best results achieved during a light intensity of 90,000 lux, temperature of 32ºC, relative humidity of 46%, and wind speed of 0.7 m/s (Italcementi, 2008).

 Another project by Italcementi Group was conducted in Paris, France. For this project, a photocatalytic concrete overlay was placed on a 6,000 m2 section of the street that was traveled by more than 13,000 cars. Results showed an initial pollution decrease of at least 20% (Italcementi, 2008).

 During the restoration of the Umberto tunnel in Rome, Italy in 2007, 9,000 m2 of the tunnel was covered in a photocatalytic cementious paint called CIMAX Ecosystem. The results

indicated about a 20% NOx reduction (Italcementi, 2008). Another tunnel application of photocatalytic material was done in in Milan, Italy on Porpora Street, which is traversed by 30,000 vehicles/day. This time, both the road pavement and the tunnel ceiling were covered by cast-in-place photocatalytic concrete pavement and a non-cementitious photocatalytic paint treatment, respectively. Under the low intensity light conditions, results showed close

to 23% lower NOx reduction compared to usual light intensity levels (Italcementi, 2008).

 The Belgian Road Research Centre (BRRC) studied the application of 10,000 m2 photocatalytic concrete on the side roads of a main entrance axis in the city of Antrep

(Beeldens, 2006). Results from on-site the indirect technique to evaluate NOx degradation measurements revealed a decrease in the pollution peaks. This confirmed the laboratory

results, which showed evidence of reduction efficiency over time due to the surface

deposition of NO3 (Beeldens, 2006).

 The Photocatalytic Innovative Coverings Applications for Depollution Assessment (PICADA) research group project was partially funded by the European Union and comprised of companies and universities from many European countries. It started on January 2002 and ended in 2005, and its goal was “to develop a range of photocatalytic materials and to evaluate their effect at a large scale, typically street canyons” (PICADA,

2010). Results for NOx abatement varied from 20% to 80% depending on wind conditions.

 There have been different projects to test the effectiveness of photocatalytic coating on noise barriers. An air quality innovation program performed in the Netherlands showed no

evidence that a coating of titanium dioxide on noise barriers removes harmful NOx emissions

from the air. Several explanations were suggested for the disappointing results: short contact time between the air and the barrier, relatively unfavourable weather conditions because of the direction of the wind and light intensity, high relative humidity of 55% to 95%, and frequent low temperatures (IPL, 2009).

 Another noise barrier project in France to evaluate the in situ effectiveness of a unique coating system of NOxer, a coating system for vertical structures, on noise barrier walls. The air pollution levels were monitored at different measurement stages to isolate the catalytic effects from the other variables. Results showed a reduction of 10% to 15% in the immediate vicinity of the wall on both sides (IRF, 2010).

 In Tokyo, two types of photocatalytic noise barrier panels, an open panel and a windowed panel, were placed alongside a heavy traffic (113,000 vehicles per day) highway. The windowed panel had a glass covering and air was pumped into contact with the

photocatalytic surface. The reported average percentage removal of NOx for the windowed panel was 31% to 69% (Berdahl and Akbari, 2007).

 In the United States, the first field installation of photocatalytic pavement was studied by Asadi et al. (2012) to evaluate the field efficiency of photocatalytic asphalt pavement as well as the effects of different operational parameters on NO degradation. For this project, a 18

water-soluble nano-TiO2 solution was sprayed on a section of asphalt pavement in Baton Rouge, LA. Results from the hourly comparison of the NO measurements before and after

the TiO2 application show reduction efficiencies of 16% to 90%. Furthermore, based on their parametric study, it was shown that the most effective factors on photocatalytic oxidation were traffic level, relative humidity, and solar radiation, while in-service operating conditions did not contribute to the reduction of the photocatalytic ability (Asadi et al., 2012). Aside from ambient air monitoring technique, Dylla et al. (2012) utilized the indirect

technique to evaluate NOx degradation at the same location. The indirect method values were lower than the direct method “since not all of the nitrates were eluted in the time allowed for the sample collection” (Dylla et al., 2012). Results show that both direct and

indirect methods for the NOx degradation measurements confirm that the photocatalytic reactions occur in the field and are influenced by environmental factors such as relative humidity, wind speed and direction, light intensity and solar radiation (Dylla et al., 2012).

 Osborn et al. (2012) studied the air-purifying asphalt and concrete photocatalytic pavement site located on Louisiana State University campus. The spray coating used was a mixture of

aqueous TiO2 anatase nanoparticles. The indirect field measurement was done to evaluate the photocatalytic NO degradation by measuring deposited nitrate salts on the pavement surface. The results confirmed that the operating conditions had negligible effects on the efficiency of the photocatalytic process and this process had the highest activity during the first four days of the installation (Osborn et al., 2012).

Chapter 3 Potential Impacts of Photocatalytic Concrete on Air Quality in Ontario 3.1 Introduction

An examination of the potential beneficial impacts of photocatalytic concrete on air quality in Ontario warrants knowledge of (i) cities with the poorest air quality and their corresponding pollution levels, and (ii) the abating efficiency of photocatalytic concrete. Ontario air quality data is documented by the Ministry of the Environment Ontario (2012) at www.airqualityontario.com. The range of pollution-abating effectiveness of photocatalytic concrete reported in the literature varies widely for both laboratory studies and field applications. Literature reports show that implementing a photocatalytic concrete cover or a photocatalytic coating can reduce NOx concentrations by up to 80% (PICADA, 2010). At the same time, some studies have shown that the photocatalytic applications reduce NOx levels by only 20% (PICADA, 2010). The wide range of abatement efficiencies is strongly linked to the sensitivities of the photocatalytic processes to environmental conditions such as irradiance, wind, relative humidity and temperature (Churchill and Panesar, 2012). Awareness of daily and annual pollution level fluctuations in the absence of photocatalytic processes is necessary to be able to adequately interpret any reduction in pollution as a result of photocatalysis in field applications. This chapter will:

 Identify Ontario cities with the poorest air quality based on approximately 11 years of reported pollution data from the Ministry of the Environment Ontario website (www.airqualityontario.com).  Examine hourly and monthly trends in pollution fluctuations and measurements.  Estimate the potential pollution reduction for two scenarios; the first scenario reflects the case where photocatalytic concrete exhibits a relatively low rate of abatement, and the second scenario will assume a relatively high rate of abatement.

Outcomes from this section are anticipated to provide insight regarding optimum applications and locations for photocatalytic concrete. In addition, the results will also emphasize the importance for natural daily and seasonal pollution fluctuations that must be considered when measuring field pollution data in efforts to quantify pollution reductions as a result of photocatalysis.

3.2 What is Smog?

Smog, or smoky fog, is the result of series of complex photochemical and chemical reactions that happen during lack of dispersion due to insufficient atmospheric turbulence. The main components of smog are ground-level ozone (O3) and fine particulate matter (PM2.5) (Piver, 1987).

As mentioned in chapter 2, NOx (NO and NO2) is responsible for ozone and particulate build-up through photochemical reactions with hydrocarbon (Barbesta and Schaffer, 2009). Thus, O3 is a result of photochemical reaction of NOx and VOCs; Photo-dissociation of nitrogen dioxide

(NO2) into nitric oxide (NO) and oxygen free radicals which reacts with abundant oxygen resulting in formation of O3 (Piver, 1987):

ℎ푣 . 푁푂2 푁푂 + 푂 (4.1) . 푂 + 푂2 → 푂3 (4.2)

푂3 + 푁푂 → 푁푂2 + 푂2 (4.3)

As illustrated by Equations 4.1, 4.2, and 4.3, a steady state, constant level of O3 production will be reached if there are no other chemicals to compete for oxygen free radicals. The dissociation of the O3 requires higher energy (UV portion) of the visible electromagnetic spectrum than NO2. Hence, “the naturally occurring ozone in the stratosphere is beneficial as it shields the earth from harmful ultraviolet radiation, while ozone at ground level is a major environmental and health concern” (MOE, 2010).

PM2.5 includes smoke, fumes, dust and pollen that are 2.5 microns in diameter or less. In

Ontario, the main occurrences for both O3 and PM2.5 are in transportation corridors. Exposure to high levels of O3 and PM2.5 can cause leading health problems such as chest tightness, coughing and has been linked to increased hospital admissions and premature death (MOE, 2010).

Generally, the process of ground level ozone formation and changes in concentrations of O3 and

NOx are very complex. When there is significant concentration of low molecular weight particulates from automobile exhaust (PM2.5), they replace O3 in Equation 4.3 and react with NO to produce NO2. This decreases the rate of O3 removal by NO, which increases the O3 concentration. Meteorological conditions that reduce the atmospheric rate of dispersion and dilution of air pollutants are also responsible for changes in concentration of O3 (Piver 1987). For example, during early hours of morning, there is a nocturnal temperature inversion effect; lower rate of emission removal by air motion than the rate of entry to the air from exhaust emissions. As a result, there exists a stable atmosphere with high concentration of nitric oxide, and nitrogen dioxide. Ozone concentration is more or less at a steady state due to high concentrations of NO2 and NO. During midday, due to the increase in temperature of earth’s surface related to that of the air above the earth’s surface, the atmosphere becomes more unstable. This increases the vertical air movement and mixing of air pollutants, hence PM2.5 replaces O3 in Equation 4.3. As a result the concentration of O3 increases, while the concentration of NO2 and NO decrease. In Ontario, elevated concentrations of ozone are generally observed during noon to early evening on hot sunny days from May to September (MOE, 2010).

3.3 Air Quality in Ontario Cities

The provincial real-time air quality monitoring system has been operated by the Ontario Ministry of Environment since 1988. Across Ontario, the Ministry has a network of 40 ambient air quality monitoring stations. The air quality index (AQI) ranges of values correspond to very poor to very good air quality, as shown in Table 3.1.

The calculation for AQI is not straightforward and is not covered in this project, but briefly, it is in part based on limiting values for emissions in Ontario as shown in Table 3.2. Further information on the computation of the AQI can be retrieved from (MOE, 2012). 22

Table 3.3 presents a summary of Ontario regions with the highest number of smog advisories issued and the highest number of advisory days based on the Ministry of the Environment Ontario (MOE, 2012). The region of Windsor-Essex-Chatham-Kent has the highest number of smog advisories and the highest number of advisory days and so it is examined further in this study. The City of Toronto had the second most number of smog advisories issued and the seventh highest number of advisory days. The City of Toronto is also further examined largely because of the current field application of photocatalytic highway noise barriers located on the south side of Highway 401 between the Don Valley Parkway and Victoria Park Avenue.

Table 3.1: Air quality index range (MOE, 2012)

AQI Reading Interpretation

0-15 Very Good

16-31 Good

32-49 Moderate

50-99 Poor

100 plus Very Poor

Table 3.2: Limiting values for emissions in Ontario (MOE, 2012)

Pollutant Unit AAQC* Averaging time

O3 ppb 80 1 hr

100 24 hr

NOx ppb 200 1 hr

20 Annual

SO2 ppb 100 24 hr

250 1 hr

CO 13 8 hr ppm 30 1 hr

3 PM2.5 µg/m 30 24 hr

TRS µg/m3 14 24 hr * AAQC : Ambiant Air Quality Criteria (AAQCs)

Table 3.3: Regions in Ontario with the highest smog advisories

Rank No. of Rank No. of based on Air Quality Forecast advisories based on no. advisory no. of Region issued of advisories days advisory issued (2003–2010) (2003–2010) days

Windsor-Essex- 1 1 52 (highest) 158 (highest) Chatham-Kent

Halton-Peel 51 2 142 4

City of Toronto 51 2 139 7

City of Hamilton 50 3 142 4

Elgin 50 3 155 2 9 York-Durham 50 3 135 (lowest)

Simcoe-Delhi-Norfolk 49 4 143 3

Dunnville-Caledonia- 49 4 140 6 Haldimand

Oxford-Brant 49 4 141 5

Sarnia-Lambton 49 4 141 5 5 London-Middlesex 48 (lowest) 138 8

3.4 Pollution Fluctuations

3.4.1 Hourly Trend

The locations of the Windsor DT and four Toronto air quality monitoring stations are indicated in Table 3.4. This study only examines the hourly fluctuations of two selected locations: Windsor DT and Toronto E stations. The Toronto E station was chosen because it is the closest station to the field trial of the photocatalytic noise barrier. Figures 3.1 and 3.2 show the hourly data of O3 and NOx concentrations at the Windsor DT station for May to September, respectively and Figures 3.3 and 3.4 show similar trends for the relatively cooler months, namely, October to April. The data in the plot is an average of the data available from 2000-

2011. The data shows that there are large changes in O3 and NOx concentrations throughout the day for relatively warm temperature months (i.e., May to September). Appendix A shows the corresponding plots, for Toronto E station, and they follow the same trends observed for the Windsor DT station.

Table 3.4: Station locations

Air Quality Forecast Station Name Location of the Station Region

Windsor-Essex- Windsor DT 467 University Ave. W. Chatham-Kent

Toronto DT Bay St./Wellesley St. W.

Toronto W 125 Resources Rd. City of Toronto Toronto E Kennedy Rd./Lawrence Ave. E.

Toronto N Hendon Ave./Yonge St.

May 60 Jun Jul Aug 50 Sep

(ppb)

3 30

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour

Figure 3.1: Windsor DT O3 hourly data from May to Sept (2000-2011)

May 60 Jun Jul Aug 50 Sep

(ppb) x 30

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour

Figure 3.2: Windsor DT NOx hourly data from May to Sept (2000-2011)

60 Oct Nov 50 Dec Jan Feb Mar 40 Apr

(ppb)

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour Figure 3.3: Windsor DT O3 hourly data from Oct to April (2000-2011)

60 Oct Nov Dec 50 Jan Feb Mar Apr 40

(ppb)

NO 30

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour Figure 3.4: Windsor DT NOx hourly data from Oct to April (2000-2011)

3.4.2 Monthly Trend

The average monthly data of all the pollutant concentrations of the regions in Ontario with highest smog advisories were examined. Figure 3.5 shows the monthly data of O3 concentration for all of the stations. The data in the plot is an average of the data available from 2000-2011.

Based on the data in Figure 3.5, regions with the highest O3 concentrations were selected for further investigation of their other pollutants concentrations. Figure 3.6 shows the monthly data of NOx for those regions. Although none of Toronto’s stations were within the top 5 stations with high O3 concentration.

As shown in Figures 3.5 and 3.6, the average monthly O3 and NOx concentration fluctuation is consistent with the hourly data and it follows the same trend as the hourly data; with an increase in temperature, there is an increase in O3 concentration and a decrease in the concentration of

NOx.

This data reveals that the hourly and monthly changes in pollution concentrations are an important factor to account for when monitoring air quality. The pollution-abating effectiveness of photocatalytic concrete field applications may be over-estimated or underestimated if hourly or monthly changes in pollution concentration levels are not accounted for in the air pollution monitoring program.

Windsor DT Windsor W 60 Oakville Toronto DT Toronto W Toronto E Toronto N 50 Hamilton DT Hamilton MT Hamilton W Port Stanley Oshawa Brantford 40 Sarnia London

(ppb)

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month

Figure 3.5: O3 monthly data for regions in Ontario with the highest smog advisories (2000- 2011)

Windsor DT Hamilton MT Oshawa Brantford Sarnia Toronto DT Toronto W 60 Toronto E Toronto N

(ppb) 30

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month

Figure 3.6: NOx monthly data for regions in Ontario with the highest smog advisories (2000-2011)

3.5 Estimated Removal Efficiency

To estimate the potential NO removal efficiency of the photocatalytic concrete, a total of eight stations are considered. Four stations, Windsor DT, Hamilton MT, Sarnia, and Oshawa, were selected based on their high O3 concentration level and geographic location in Ontario. In addition four Toronto stations were also considered, namely, Toronto DT, W, E and N.

Appendix B presents the average monthly pollution concentrations from 2000-2011 for NOx,

NO2, and NO of the above mentioned stations.

Using the average month wind speed data reported by Windfinder (2012), the NO concentrations in mg/h/m2 were calculated based on Equation 4.4 and shown in Figures 3.7 and 3.8:

(푏×푐×273.15×푑) 퐴 = (4.4) 22.4136×(273.5+푒)×760 where 퐴 is the concentration of NO (mg/h/m2), 푏 is the concentration of NO (ppm), 푐 is the molecular weight of NO, 푑 is the atmospheric pressure (mmHg), and 푒 is the ambient air temperature (˚C).

In addition, Figures 3.7 and 3.8 show two horizontal lines that represent two abatement levels, a relatively low NO degradation rate and a relatively high NO degradation rate, which are 6 and 20 mg/h/m2, respectively. The basis for these abatement rates is detailed in Churchill and Panesar (2012). Table 3.5 presents the maximum and minimum NO concentration for each monitoring station. The month in which the maximum and minimum are observed are also reported. In general, it is observed that the maximum available NO is most commonly found in February, whereas the minimum NO concentrations for all stations except Sarnia occurs in July. The percentage removal efficiency is calculated based on the low and high abatement rates of 6 and 20 mg/h/m2, respectively. Considering a 6 mg/h/m2 abatement rate, up to 20% NO abatement can be achieved, and if an abatement rate of 20 mg/h/m2 occurs, up to 67% NO abatement is estimated at the Hamilton MT location. In Toronto, a range of 3% to 24% removal efficiency is calculated. In general, these estimates fall within the pollution abatement effectiveness reported in the literature.

Windsor DT Hamilton MT Oshawa 600 Sarnia

)

2 400

NO (mg/h/m NO

200

2 NOx Abatement Rate: 20 mg/h/m 0 2 NOx Abatement Rate: 6 mg/h/m Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month

Figure 3.7: Average monthly NO concentration (mg/h/m2) (2000-2011)

Toronto DT Toronto W Toronto E 600 Toronto N

)

2 400

NO (mg/h/m

200

2 NOx Abatement Rate: 20 mg/h/m

0 2 NOx Abatement Rate: 6 mg/h/m Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month

Figure 3.8: Average monthly NO concentration for Toronto (mg/h/m2) (2000-2011)

Table 3.5: Percentage removal efficiency (%)

Removal Efficiency (%)

Available NO Abatement Rate Station 6.00 20.00 Name Month (mg/h/m2) (mg/h/m2) (mg/h/m2)

Windsor Max Dec 363.35 1.65 5.50 Min

DT Min Jul 58.08 10.33 34.44 Max

Hamilton Max Nov 173.70 3.45 11.51 Min

MT Min Jul 30.07 19.95 66.51 Max

Max Feb 173.86 3.45 11.50 Min Sarnia Min Aug 54.77 10.96 36.52 Max

Max Feb 222.34 2.70 9.00 Min Oshawa Min Jul 56.19 10.68 35.59 Max

Toronto Max Feb 295.82 2.03 6.76 Min

DT Min Jul 83.63 7.17 23.91 Max

Max Feb 684.68 0.88 2.92 Min Toronto W Min Jul 227.75 2.63 8.78 Max

Max Feb 546.44 1.10 3.66 Min Toronto E Min Jul 146.70 4.09 13.63 Max

Max Feb 409.62 1.46 4.88 Min Toronto N Min Jul 93.22 6.44 21.45 Max

Chapter 4 Experimental Program 4.1 Introduction

The objective of the experimental part of the research is to compare conventional concrete made using GU cement to concrete containing photocatalytic cement in context with mechanical, transport and durability properties. The experimental program has been divided into four phases:

 Phase I: Investigating cement paste  Phase II: Investigating concrete  Phase III: Investigating concrete with finished and formed surfaces, with minimum variance in the amount of air content  Phase IV: Investigating concrete with finished and formed surfaces, with minimum variance in both air content and slump

4.2 Materials

Throughout the experimental work the following materials were used:

4.2.1 Cementing Materials

Ordinary portland cement (OPC), obtained from Holcim Cement, Mississauga, Canada; Saylor’s portland cement type I/II (GU) and photocatalytic TX Active Aria GB cement (PH), both of which were obtained from Essroc Cement Corporation shipped from Front Royal Cement; and Grade 100 GGBFS was obtained from Holcim Cement Canada. The chemical composition for each of the cementing materials used in the experiments is shown in Table 4.1.

Recognizing that photocatalytic cement is not typically used in combination with supplementary cementing materials because it will dilute the pollution abating effectiveness, GGBFS is blended with OPC, GU and PH to assess if the expected behaviour will occur in the presence of TiO2.

Table 4.1: Chemical composition of cementing materials

Main OPC GU PH GGBFS

Constituent (%) (%) (%) (%)

SiO2 17.15 19.1 16.83 34.07

Al2O3 4.04 3.69 3.12 7.33

Fe2O3 2.19 3.06 2.72 0.45

CaO 57.43 61.3 55.12 35.77

MgO 3.03 2.67 3.23 14.16

SO3 5.75 6.37 4.27 1.24

K2O 1.27 1.12 0.89 0.55

Na2O 0.32 0.23 0.34 0.45

TiO2 0.24 0.2 5.71 0.53

The density of the materials was measured using a stereo pyncometer. The device employs Archimede’s principle of fluid displacement to determine the volume of solid objects. The displaced fluid is helium gas that penetrates the finest pores. The equation to calculate is (Quantachrome Instruments, 2007):

푉퐴 푉푃 = 푉퐶 + 푃 (4.1) 1− 2 푃3

푆푎푚푝푙푒 푀푎푠푠 (𝑔) 퐷푒푛푠𝑖푡푦 = (4.2) 푉푃

3 3 where 푉푃 is volume of powder (cm ), 푉퐶 is the volume of sample cell holder (cm ), 푉퐴is the added volume, 푃2 pressure reading after pressurizing cell (psi), and 푃3is pressure reading (psi) 36

after adding 푉퐴. This test was run 3 times per sample and the average density of each material is shown in Table 4.2.

Table 4.2: Density of powder materials

Material Source Density (g.cm-3)

OPC Holcim 3.11

GU Essroc 3.14

PH Essroc 3.18

GGBFS Holcim 2.95

4.2.2 Aggregate

4.2.2.1 Coarse Aggregate

The coarse aggregate used was a crushed limestone with a maximum size of 13 mm and was supplied by Dufferin Aggregates Milton Quarry. The specific gravity and absorption of the coarse aggregate were 2.89 and 1.97%, respectively.

4.2.2.2 Fine Aggregate The fine aggregate used was natural sand from the CBM Sunderland Pit. The specific gravity, fineness modulus and absorption of the sand were experimentally determined to be 2.72, 2.50 and 0.63%, respectively.

4.2.3 Chemical Admixtures The air-entraining admixture (AEA) used in phases I, II, and III of the experimental program was Airextra, obtained from Euclid Concrete Admix, with a specific gravity of 1.07. In phase IV, MicroAir with a specific gravity of 1.01 was used as the AEA. Glenium 7700, a polycarboxylate-based high range water reducing admixture with a specific gravity of 1.064, was used as the superplasticizer (HRWR). Both MicroAir and HWR were provided by BASF Canada.

4.3 Phase I

4.3.1 Introduction

The objective of this phase of the research involves investigation and comparison of conventional cement pastes made using OPC and GU to cement paste containing PH in context with strength and porosity. The preliminary selection of cement paste mix design variables are based on the findings reported in the literature. The effects of water to cement ratio (w/c), the presence of GGBFS, and the curing age have also been examined. Furthermore, the difference between OPC and GU in comparison to PH was also investigated.

4.3.2 Mix Design

Ten mix designs were prepared for the experimental program as summarized in Table 4.3.

4.3.3 Mixing, Casting and Curing

The ASTM C305-06 mixing procedure was used. The dry paddle and dry bowl were placed in the mixing position in the mixer. The measured amount of the materials was introduced into the bowl in the following manner: hand-mix the dry cementing material for 30s; place the water in the mixing bowl; add the mixed cementing material to the water and allow 30s for the absorption of the water; start the mixer at the slow speed (140 ± 5r/min) for 30s; stop the mixer for 15s and scraped down the paste on sides of the bowl into the batch; start the mixer at medium speed (285 ± 10r/min) and mix for 60s.

For each mixture, six cubes were cast into molds of 50mm × 50mm × 50 mm and compacted in two layers using a plastic compacting bar, where each layer was compacted 25 times. Then the molds were immediately covered with plastic to avoid moisture loss, and were kept at room temperature (23 ± 2°C) for 24 hours. Then the specimens were demolded and cured in a lime- saturated water container at room temperature prior to test days.

Table 4.3: Mix design proportions (Phase I)

OPC GU PH GGBFS w/c ratio Mix # Mix ID (%) (%) (%) (%)

1 OPC0.42-I 100 0 0 0 0.42

2 GU0.42-I 0 100 0 0 0.42

3 OPC0.5-I 100 0 0 0 0.5

4 OPC25S0.42-I 75 0 0 25 0.42

5 GU25S0.42-I 0 75 0 25 0.42

6 OPC25S0.5-I 75 0 0 25 0.5

7 PH0.42-I 0 0 100 0 0.42

8 PH0.5-I 0 0 100 0 0.5

9 PH25S0.42-I 0 0 75 25 0.42

10 PH25S0.5-I 0 0 75 25 0.5

4.3.4 Testing Procedure

4.3.4.1 Cube Strength

The cube strength of the cement paste was determined based on ASTM C109 after 3 and 28 days. Prior to the test, samples were removed from the curing environment, surface dried by towel, and weighed.

4.3.4.2 Mercury Intrusion Porosimetry (MIP)

The Quantachrome Autoscan Porosimeter device was used to determine the total porosity of all the paste mix designs. MIP measures porosity by entering mercury into the (dried) capillary pore system of materials under pressure. The Washburn equation is used:

−4훾 푐표푠휃 푃 = (4.3) 푑 where 푃 is pressure, 훾 is the surface tension of the liquid, 휃 is the contact angle of the liquid, and 푑 is the capillary diameter (Abell et al., 1999). The total porosity was evaluated by using the MIP device. After the compressive strength test, the paste specimens were crushed and left to soak in liquid nitrogen for 5 to 10 minutes to terminate the hydration process. The specimens were then placed in the vacuum freezer at -20±2 °C for 24 hours followed by vacuum oven at 40±2°C for another 24 hours, while surrounded by silica gel and soda lime to minimize the occurrence of carbonation. Prior to the MIP test, the samples were ground by mortar and pestle into small pieces to pass 5mm sieve and remain on 2.5mm sieve.

4.4 Phase II

4.4.1 Introduction

The objective of this phase of the research involves a comparison of conventional concrete made using GU cement to concrete containing PH cement in context with mechanical and transport properties. The preliminary selection of concrete mix design variables are based on the findings reported in the literature and phase I of this report.

It should be noted that PH cement, produced by Essroc, is simply the GU cement, from Essroc with the addition of proprietary particles of TiO2. OPC was eliminated from the mix design to minimize the variables due to different cement suppliers.

The properties of photocatalytic concrete samples were compared with conventional concrete at w/c of 0.42. The effects of the presence of 25% ground granulated blast furnace GGBFS as well as the curing age were also examined.

4.4.2 Mix Design

All mixes had a total cementing material design mass of 428.6 kg/m3 and a w/c ratio of 0.42. The coarse aggregate content for all mixes was 900 kg/m3. Table 4.4 presents the concrete mix design proportions. Table 4.4: Mix design proportions (Phase II)

Cementing Material Aggregate Mix Mix ID Water AEA # GU PH GGBFS Coarse Sand

3 Units kg/m mL/100kgcement

1 GU-II 428.6 0 0 900 875 180 52

2 GU25S-II 321.4 0 107.1 900 867 180 52

3 PH-II 0 428.6 0 900 876 180 52

4 PH25S-II 0 321.4 107.1 900 869 180 52

4.4.3 Mixing, Casting and Curing The ASTM C192-07 mixing procedure was used. All mixtures were prepared in 40 L batches in a 65 L capacity pan mixer. First all the dry ingredients were added at once and mixed for 1 min; the AEA was diluted in the mixing water; the mixing water was added and mixed for 3 min; stop the mixer for 3 min and allow the mix to rest; start the mixer and mix for another 2 min.

For each mixture, sixteen cylinders (100mm x 200mm) were cast and compacted in three layers, where each layer was compacted 25 times. Then the cylinders were immediately covered with plastic lid to avoid moisture loss, and were kept at curing room at 23±2°C and 100% RH for 24 hours. The samples were then demolded and kept in the same curing room until testing.

4.4.4 Testing Procedure

4.4.4.1 Fresh Concrete Properties

The following tests, listed in Table 4.5, were evaluated for each of the four mix designs.

Table 4.5: Fresh concrete property tests

Type of test Standard Units

Slump CSA A23.2-5C mm

Air Content ASTM C231 %

Density CSA A23.2-6C kg/m3

4.4.4.2 Mechanical Properties

Mechanical properties of the four mix designs were evaluated after 28 and 56 days of curing. All of the tests are listed in Table 4.6.

4.4.4.2.1 Compressive Strength

Compressive strength of the concrete cylinders was determined based on CSA A23.2-9C. Three cylinders per mix design and curing age were tested. Prior to the test, samples were removed from the curing environment, both ends of the cylinders were ground (5 to 10 mm), surface dried by towel, weighted, and the dimensions were measured.

4.4.4.2.2 Hardened Density

Density of the concrete specimens was determined based on CSA A23.2-11C. Two cylinders per mix design and curing age were tested. Prior to the test, cylinders were removed from the curing environment, cut into half the length, weighted, and the dimensions were measured.

4.4.4.2.3 Ultrasonic Pulse Velocity (UPV)

Ultrasonic pulse velocity (UPV) of the concrete specimens was determined based on ASTM C597, to help in assessing the uniformity and relative changes in the quality of concrete in

different mixes. Three cylinders per mix design and curing age were tested. Prior to the test, samples were removed from the curing environment, both ends of the cylinders were ground (5 to 10mm), surface dried by towel, weighted, and the dimensions were measured.

4.4.4.2.4 Hardened Air Content

Air content of the hardened concrete samples were measured based on ASTM C547. One cylinder per mix design and curing age was tested. Prior to the test, the cylinder was removed from the curing environment, cut into half lengthwise, and each half was cut into two sections with a height of about 80mm.

Table 4.6: Mechanical property tests

Type of test Standard Units

Compressive Strength CSA A23.2-9C MPa

Hardened Density CSA A23.2-11C kg/m3

UPV ASTM C597 m/s

Hardened Air Content ASTM C457 %

4.4.4.3 Transport Properties

The transport properties of the four mix designs were evaluated after 28 and 56 days of curing.

4.4.4.3.1 Rapid Chloride Permeability

A rapid chloride permeability test (RCPT) was performed based on ASTM C1202 to determine the resistance to chloride ion penetration. Two cylinders per mix design and curing age were tested. Prior to the test, the cylinders were removed from the curing environment, cut into two sections of 50mm thick, and the dimensions were measured.

4.5 Phase III

4.5.1 Introduction

The objective of this phase of research involves a comparison of mechanical, transport and durability properties the conventional concrete made using GU cement to concrete containing PH, both with finished and formed surfaces. The properties of the photocatalytic concrete samples have been investigated by comparing them with conventional concrete at w/c of 0.42. The effects of the presence of GGBFS as well as the curing age were also examined.

4.5.1.1 Foam Index Test

Prior to the phase III mix design, due to the low plastic air content of the photocatalytic concrete in phase II and the difficulty in entraining air in PH concrete, the foam index test was conducted to help determine the proper amount of required air-entraining admixture (AEA) sufficient to produce a stable air-void system in the photocatalytic concrete.

For this test, the aqueous solutions of the air entraining admixture were prepared in 2%, 6%, 10%, and 15% strengths of air entraining admixture by volume. The mixture of 20 grams cement and 50 ml distilled water was mixed for 60s followed by the addition of diluted air- entraining solution in the intervals. The mixture was shaken for 45s. If the foam on the surface is not stable and in the continuous layer, further air-entraining solution should be added until a stable and continuous foam is achieved. The minimum amount of air‐entraining admixture needed to produce stable foam was established as the foam index (Lashley, 2009). Average foam index values were calculated based on the following steps:

(1) massAEA = massAEAsol/ 5* = massAEA

(2) massAEA / kgcem [gAEA/ kgcem] = massAEA/20 [g cem] x 1000 [gcem /kgcem]

(3) densityAEA = density[gAEA/mL]

(4) foam index [mLAEA/ kg cem] = massAEA/kgcem / densityAEA

*Using a 1:4 dilute AEA solution

Table 4.7: Paste mix proportions used for the foam index test methods

GU PH Distilled Water Foam Index

(g) (g) (g) (ml AEA/kgcem)

Mix #1 20 0 50 1.25

Mix #2 0 20 50 0.47

Figure 4.1: Mix#1 and Mix#2 before addition of AEA solution (left), foam on the surface after addition of AEA and shaking for 45s (right)

As illustrated in Figure 4., the surface of the mixture of PH and water (mix#2) is not as clear as mix#1 and already started the formation of the foam on the surface. In addition, results from the fresh air content test of the trial batches were not consistent with the results from the foam index test. Based on the fresh air content test (ASTM C231), in order to reach 5% air content for concrete with GU and PH cement, the required AEA (ml/kgcem) is 0.75 and 5.25 respectively.

It can be concluded that due to the surface appearance of the mix#2, the foam index test is not a good indicator of required AEA for mixes with PH cement.

4.5.2 Mix Design

All mixes had a total cementing material design mass of 429 kg/m3 and a w/c of 0.42. The coarse aggregate content for all mixes was 892 kg/m3. Table 4.9 presents the concrete mix design proportions.

Table 4.8: Mix design proportions (Phase III)

Cementing Material Aggregate Mix Mix ID Water AEA # GU PH GGBFS Coarse Sand

3 Units kg/m mL/100kgcement

1 GU-III 429 0 0 892 883 180 74

2 GU25S-III 321 0 107 892 875 180 78

3 PH-III 0 429 0 892 884 180 530

4 PH25S-III 0 321 107 892 877 180 530

4.5.3 Mixing, Casting and Curing

The ASTM C192-07 mixing procedure was used. All mixtures were prepared in 60 L batches in a 65 L capacity pan mixer. First, all the dry ingredients were added at once and mixed for 1 min; the AEA was diluted in the mixing water; the mixing water was added and mixed for 3 min; mixing was stopped for 3 min, and then the mixture was mixed for another 2 min.

For each mixture, eighteen cylinders (100mm x 200mm), four slabs (300mm x 200mm x 75mm), and two prisms (75mm x 75mm x 300mm) were cast and compacted in three layers, with each layer compacted 25 times. The cylinders were then immediately covered with plastic lids to avoid moisture loss, and were kept in a curing room at 23±2°C and 100% relative humidity for 24 hours. The samples were then demolded and kept in the same curing room until testing. Slabs were immediately covered with plastic and kept at room temperature for the first 24 hours. Then they were demolded and kept in a curing room at 23±2°C and 100% relative

humidity for 14 days, followed by dry curing in a room at 23±2°C and 50% relative humidity for another 14 days. As for the prisms, they were immediately covered with plastic and kept at room temperature for the first 24 hours. They were then demolded and kept in a curing room at 23±2°C and 100% relative humidity for 28 days.

4.5.4 Testing Procedure

4.5.4.1 Fresh Concrete Properties

The testing procedures for fresh properties were the same as in Phase II.

4.5.4.2 Mechanical Properties

The testing procedures for mechanical properties were the same as in Phase II.

4.5.4.3 Transport Properties

All of the tests are listed in Table 4.9. The testing procedure for RCPT was the same as in Phase II.

Table 4.9: Transport property tests

Type of test Standard Units

RCPT ASTM C1202 Coulombs

Sorptivity ASTM C1585 mm/sec1/2

4.5.4.3.1 Sorptivity

Sorptivity testing was performed based on ASTM C1585 to determine the sorption coefficient (mm/sec1/2). Three cylinders per mix design and curing age were tested. As soon as the samples reached the targeted curing age of 28 and 56 day at 100% relative humidity, they were removed from the curing environment, weighed, and the dimensions were measured. The specimens were then conditioned at 50°C and 80% relative humidity for three days, followed by 15 days in a sealed container at room temperature. To evaluate the effect of surface on sorptivity, both top (finished) and bottom (formed) surfaces of a standard cylinder were tested. 47

4.5.4.4 Durability Properties

All the durability tests performed are listed in Table 4.10. Slabs and prisms were used for scaling resistance and rapid freezing and thawing tests, respectively.

Table 4.10: Durability property tests

Type of test Standard Units

Resistance to Salt Scaling MTO LS-412 Kg/m2

Resistance to Rapid Freezing and Thawing ASTM C666 %

4.5.4.4.1 Resistance to Salt Scaling

Salt scaling testing was performed using on MTO LS-412 to determine the resistance to scaling of a horizontal concrete surface exposed to freeze/thaw cycles in the presence of a 3% NaCl de- icing solution. Two slabs per mix design were tested. Prior to the test, samples were removed from the curing environment and prepared based on the standard.

The specimens were subjected to 50 freeze/thaw cycles, with one cycle lasting 24 hours. The samples were kept in freezing condition for 16 to 18 hours at –18±2ºC and then in thawing condition for 6 to 8 hours at 23±2ºC and 50±5% relative humidity. The dry mass of the flaked off material from the surface of the concrete slabs, was measured every five cycles. A salt scaling value of 0.8 kg/m2 is the specified acceptance limit in accordance with OPSS 1351.

4.5.4.4.2 Resistance to Rapid Freezing and Thawing Damage

Freeze/thaw resistance was performed using on ASTM C666 Procedure A to determine the relative dynamic modulus and durability factor of the specimens as an indicator of internal micro-cracking in the concrete. Two prisms per mix design were tested. The relative dynamic modulus, Pc, and the durability factor, DF, were calculated using Equations 4.4 and 4.5.

푛2 푃 = 1 × 100 (4.4) 푐 푛2

푃푁 퐷퐹 = (4.5) 300 where n1 is the fundamental transverse frequency after c freeze/thaw cycles, n is the fundamental transverse frequency prior to cycling, and N is the number of cycles at which testing was terminated. The specimens were measured at the intervals of 36 to 40 cycles for both the length change and fundamental transverse frequency.

4.6 Phase IV

4.6.1 Introduction

Due to poor scaling results for PH concrete in Phase III, which is explained in chapter 5, a new set of mix designs were tested in Phase IV to trigger the primary difference in slump. The objective of this phase of research involved an examination of the effects of the addition of a polycarboxylate-based high range water reducing admixture in comparison to conventional concrete made using GU cement to concrete containing photocatalytic, both with finished and formed surfaces, on the following properties:

 Mechanical properties: Compressive Strength, UPV, and Hardened Air content;  Transport properties: RCPT and Sorptivity;  Durability properties: Resistance to Salt Scaling.

The properties of the photocatalytic concrete samples have been investigated by comparing them with conventional concrete at w/c of 0.42.

4.6.2 Mix Design

Table 4.11: Mix design proportions (Phase IV)

Cementing Aggregate Material Mix # Mix ID Water AEA HRWR

GU PH Coarse Sand

3 Units kg/m mL/100kgcement

1 GU-IV 429 0 892 883 180 5.7 116

3 PH-IV 0 429 892 884 180 29 300

4.6.3 Mixing, Casting and Curing

The ASTM C192-07 mixing procedure was used. All mixtures were prepared in 60 L batches in a 65 L capacity pan mixer. First, all the dry ingredients were added at once and mixed for 1 min; the AEA was diluted in the mixing water; the mixing water was added, then the HRWR was added and mixed for 3 min; mixing was stopped for 3 min, and then the mixture was mixed for another 2 min.

For each mixture, nine cylinders (100mm x 200mm) and four slabs (300mm x 200mm x 75mm) were cast and compacted in three layers, with each layer compacted 25 times. The cylinders were then immediately covered with plastic lids to avoid moisture loss, and were kept in a curing room at 23±2°C and 100% relative humidity for 24 hours. The cylinders were then demolded and kept in the same curing room for 28 days. Slabs were immediately covered with plastic after the casting and kept at room temperature for the first 24 hours. Then they were demolded and kept in a curing room at 23±2°C and 100% relative humidity for 14 days, followed by dry curing in a room at 23±2°C and 50% relative humidity for another 14 days.

Chapter 5 Results and Discussion 5.1 Phase I

The compressive strength and the total porosity of all the specimens at 3 and 28 days of curing are shown in Table 5.1. It should be noted that the results for compressive strength and total porosity are the average of 3 measurements. However, for mix PH25S0.42-I the strength at age of 3 days is the average of two measurements due to one outlier.

5.1.1 Compressive Strength

As shown in Figure 5., all the samples demonstrated a consistent trend of increase in strength with further curing regardless of their mix design proportions. The error bar is ± one standard deviation. Both OPC and GU demonstrate similar cube strength at w/c of 0.42 which shows the different source of cement does not have a significant effect on the strength. However, addition of 25% slag reduces the strength in GU sample.

For all the samples, the strength is decreasing with the increase in water to cement ratio (from 0.42 to 0.5). This trend stays the same with the addition of 25% GGBFS. At early ages, it is expected that the presence of GGBFS reduces the cube strength, owing to its latent hydraulic and pozzolanic properties. However, addition of the 25% GGBFS as a substitute for OPC and PH, at lower w/c ratio and longer curing age, enhances the strength about 2% to 3%. It should be noted that for all mixtures, the coefficient of variation for all strength measurements was less than 10.5 %.

Table 5.1: Strength and porosity assessments (Phase I) Compressive Strength Total Curing Average Standard Coefficient of Porosity MIX ID Age (Day) (MPa) Deviation Variation (%) (%) 3 45.3 1.5 3.3 27.1 OPC0.42-I 28 67.1 2.8 4.1 18.1 3 46.8 3.4 7.3 24.4 GU0.42-I 28 75.7 1.4 1.8 20 3 31.8 0.8 2.7 31.9 OPC0.5-I 28 50 2.5 5.1 25.2 3 40.2 1.9 4.7 23.6 OPC25S0.42-I 28 68.4 4.8 7.1 17.5 3 25.9 1.3 5.1 24.6 GU25S0.42-I 28 55.7 1.7 3.1 22.4 3 26.3 2.7 10.2 33.4 OPC25S0.5-I 28 46.7 2.5 5.3 25 3 40.1 1.3 3.3 34.8 PH0.42-I 28 60.1 1.3 2.2 18.7 3 20 0.2 1 43.1 PH0.5-I 28 32 0.9 2.8 36 3 37.2 0.8 2.3 29.3 PH25S0.42-I 28 62 1.8 3 26.3 3 8.3 0.2 2.8 50 PH25S0.5-I 28 23.5 0.5 2 44.6

100 3d 28d

Cube Strength (MPa)

PH0.5-I

PH0.42-I

G-IU0.42 OPC0.5-I

OPC0.42-I

PH25S0.5-I

PH25S0.42-I

GU25S0.42-I OPC25S0.5-I

OPC25S0.42-I

Mix ID Figure 5.1: Strength of Samples (Phase I) Note: Each bar represents the average of three measurements except for PH25S0.42-I at 3d (two measurements)

5.1.2 Porosity

Figure 5. shows the relationship between the total porosity of the samples with respect to their mix design and curing age base on MIP analysis. Regardless of the mix design proportions, the porosity of the samples decreases with longer curing. At early age and lower w/c, the porosity of PH cement paste is approximately 28% and 42% higher than that of OPC cement paste and GU cement paste, respectively. However, after 28 day of curing, this difference at low w/c reduces to near 3% with OPC cement paste. At 28 day, the porosity of the PH sample is 7% lower than that of GU.

Furthermore, at w/c of 0.42, the addition of 25% GGBFS increases the early age porosity of PH cement paste for up to 24% and 16% in comparison to OPC and GU, respectively. For the OPC and PH samples at w/c of 0.5, the addition of 25% GGBFS does not have a significant effect on the total intruded porosity when compared to the samples without GGBFS.

60 3d 28d 50

Porosity (%) Porosity 20

PH0.5-I

PH0.42-I

GU0.42-I OPC0.5-I

OPC0.42-I

PH25S0.5-I

PH25S0.42-I

GU25S0.42-I OPC25S0.5-I

OPC25S0.42-I

Mix ID Figure 5.2: Porosity of samples (Phase I) Note: Each bar represents one measurement

5.1.3 Effects of Paste Mix Design Variables – Phase I

GU0.42-I GU25S0.42-I 80 OPC0.42-I OPC0.5-I 70 OPC25S0.42-I OPC25S0.5-I PH0.42-I 60 PH0.5-I PH25S0.42-I 2 50 R = 0.8397 PH25S0.5-I 3d 40 28d

Cube Strength (MPa) Cube Strength 20 R2= 0.6908

0 20 30 40 50

Porosity (%) Figure 5.3: Porosity vs. Strength

As mentioned previously, the variables for Phase I were w/c ratio, curing age and the addition of GGBFS. Figure 5. shows the relationship between porosity and strength at different curing age of the samples. Regardless of the type of cement, samples with lower water cement ratio of 0.42 improved both strength and pore structure, with GU0.42 ranking the best. Furthermore, PH samples at w/c of 0.5 show the lowest strength and the highest porosity. Data obtained at 28 days improved statistical fit, with R-square value of 0.84, when compared to samples tested at 3 day.

Furthermore, Figure 5. shows that samples containing PH cement are following the same trend as the other samples, which indicates that PH cement behaves similarly to OPC and GU cement.

5.2 Fresh Concrete Properties

5.2.1 Phase II Table 5.2 presents the fresh state physical properties of each concrete mix design. Although samples with PH cement show decrease in slump, addition of GGBF improves workability by increase in slump. Fresh air content results indicate that the same amount of AEA affects PH concrete differently when compared to GU concrete; In Table 4.4, the same amount of AEA were used for all the mixes, however results in Table 5.2 indicated that PH-II and PH25S-II have different fresh air content when compared to GU and GU25S.

Table 5.2: Fresh properties of plastic concrete (Phase II)

Apparent Air Slump Mix # Mix ID Air Content Content* Density (kg/m3) (mm) (%) (%)

1 GU-II 127 5.00 4.02 2429

2 GU25S-II 130 5.00 4.02 2409

3 PH-II 97 2.50 1.52 2449

4 PH25S-II 125 2.50 1.52 2438 *Aggregate correction factor of 0.98% is applied. 5.2.2 Phase III

Table 5.3 presents the fresh-state physical properties of each concrete mix design in Phase III. The four concrete mix designs have a wide range of slump values. The PH concrete had very low slumps (70-75mm) and the GU cements had markedly higher slumps (160-210 mm). This drastic difference in slump is believed to be related to difficulty in entraining air and in turn to the large differences in AEA dosages used. As indicated in Table 4.8, the GU mixtures used approximately 75 mL of AEA while the PH concrete required 530 mL of AEA per 100 kg of cement.

Table 5.3: Fresh properties of plastic concrete (Phase III)

Apparent Air Slump Mix # Mix ID Air Content Content* Density (kg/m3) (mm) (%) (%)

1 GU-III 210 6.8 5.82 2375

2 GU25S-III 160 5.7 4.72 2399

3 PH-III 70 5.6 4.62 2394

4 PH25S-III 75 5.6 4.62 2396 *Aggregate correction factor of 0.98% is applied.

5.2.3 Phase IV

Table 5.4 presents the fresh properties of the two concrete mixes tested in phase IV. Due to addition of HRWR, the PH mix slump value is not only closer to that of the GU mix when compared to the previous phase, but also higher than that of the GU mix. The air contents were within the 5-8% target, and the densities were similar for both mixes.

Table 5.4: Fresh properties of plastic concrete (Phase IV)

Apparent Air Slump Density Mix # Mix ID Air Content Content* (mm) (kg/m3) (%) (%)

1 GU-IV 170 6.5 5.52 2373

2 PH-IV 192 7.6 6.62 2325 *Aggregate correction factor of 0.98% is applied.

5.2.4 Discussion of the Effects of Mix Design Variables

220

200

180

160

140 GU-II GU25S-II PH-II Slump (mm) Slump 120 PH25S-II GU-III 100 GU25S-III PH-III PH25S-III 80 GU-IV PH-IV 60 2 4 6 8 10

Air Content (%) Figure 5.4: Air Content vs. Slump

As shown in Figure 5.4, as the air content increases in GU samples, the slump increases too. However, for PH samples and addition of HRWR is necessary to increase and improve the slump.

5.3 Mechanical Properties

5.3.1 Phase II

Results from the compressive strength test are shown in Figure 5.5. For all the concrete samples, at lower curing ages, it is expected that the presence of GGBFS will reduce the compressive strength, owing to its latent hydraulic properties. However, addition of the GGBFS at longer curing age typically enhances the compressive strength.

Although incorporating PH cement reduced compressive strength of the concrete by approximately 10%, regardless of the curing age, addition of 25% GGBFS improved the strength in PH samples. Furthermore, all the samples, regardless of the type of cement, show an increase in compressive strength of approximately 10% with longer curing age.

The density of the samples is shown in Figure 5.6. The density of all the samples was almost the same, regardless of mix design.

UPV results reflect the homogeneity of the concrete. It should be noted that results might change with the presence of cracks. As shown in Figure 5.7, although UPV measurements for all mixes increase linearly with age, samples with PH cement show lower UPV in comparison to the GU samples due to lower ƒ’c. At age 56 day, all the samples have UPV of approximately 5000 m/s.

The fresh and hardened air content results are shown in Figure 5.8. The hardened air content test was done to compare the plastic air content with the hardened air content as well as the change in hardened air content after 28 and 56 days of curing. The results confirm that the plastic air content could be used as the primary indication for the air content of the concrete. Also, the results show that the addition of 25% GGBFS results in a decrease of approximately 12 and 15% in the hardened air content of the GU and PH samples after 56 days, respectively. This is due to the increase in hydration products in the samples with GGBFS.

70 28d 56d 60

Compressive Strength (MPa) Strength Compressive

0 GU-II GU25S-II PH-II PH25S-II Mix ID Figure 5.5: Compressive strength of concrete (Phase II) Note: Each bar represents the average of three measurements

2600 Fresh Dry Density (28d) Dry Density (56d) 2500

)

3 2400

2300

Density (kg/m Density

2200

2100 GU-II GU25S-II PH-II PH25S-II Mix ID Figure 5.6: Density of Concrete (Phase II) Note: Each symbol represents one measurement for fresh and two measurements for dry density

6000 28d 56d 5000

4000

3000

2000

Ultrasolnic Pulse Velocity (m/s) Pulse Velocity Ultrasolnic 1000

0 GU-II GU25S-II PH-II PH25S-II Mix ID Figure 5.7: Ultrasonic pulse velocity (Phase II) Note: Each bar represents the average of three measurements

6 Fresh Hardened (28d) 5 Hardened (56d)

Air Content (%) 2

0 GU-II GU25S-II PH-II PH25S-II Mix ID Figure 5.8: Air content (Phase II) Note: Each symbol represents one measurement for fresh and the average of two measurements for hardened concrete.

5.3.2 Phase III

Compressive strength results at 28 and 56 days are shown in Figure 5.9. By 28 days, all of the concrete samples achieved compressive strengths of 40 MPa or greater. At 56 days, the PH concrete demonstrated approximately 5% decrease in compressive strength when compared to GU concrete. Although addition of 25% GGBFS improved the strength in both GU and PH samples, PH25S-III showed 13% decrease in strength when compared to GU25S-III.

The density of the samples is shown in Figure 5.10. The density of all the samples at 56 days is within a range of 2200 to 2300 kg/m3, which reflects normal density concrete. As shown in Figure 5.11, the UPV measurements for all mixes at age 56 day are in a narrow range of approximately 4700 to 4900 m/s. This range of UPV measurements is typical for dense, homogeneous concrete with compressive strengths greater than 40 MPa.

28d 56d 60

Compressive Strength (MPa) Strength Compressive

0 GU-III GU25S-III PH-III PH25S-III

Mix ID Figure 5.9: Compressive strength of concrete (Phase III) Note: Each bar represents the average of three measurements and the error bar represents standard deviation 62

2600 Fresh Dry Density (28d) Dry Density (56d) 2500

)

3 2400

2300

Density (kg/m Density

2200

2100 GU-III GU25S-III PH-III PH25S-III Mix ID Figure 5.10: Density of concrete (Phase III) Note: Each symbol represents one measurement for fresh and two measurements for dry density

6000 28d 56d 5000

4000

3000

UPV (m/s)

2000

1000

0 GU-III GU25S-III PH-III PH25S-III

Mix ID Figure 5.11: Ultrasonic pulse velocity (Phase III) Note: Each bar represents three measurements and the error bar represents standard deviation

Given the difficulty in entraining air in the PH concrete, the hardened air void content was further examined. Table 5.5 shows additional information on the air characterization of the GU and PH mixes. All mixes have the hardened air content of 5- 6.6%, the spacing factor of 0.11- 0.18 mm, and the specific surface of 33-39 mm2/mm3 and the results were within an acceptable limit. Figure 5.12 presents the fresh air content plotted with the hardened air content at 56 days. The results show similar fresh and hardened air content measurements for all mixtures, falling between target air content of 5-8%. This result confirms the plastic air content measurements and will play an important factor for the freeze-thaw durability performance.

Table 5.5: Air content characterization (Phase III)

Specific Hardened Spacing Void Surface Apparent Fresh Air Content Factor Frequency (mm2/mm3 Air Air (%) (mm) (intercepts/mm) Mix ID of air) Content Content* (%) (%) 28d 56d 28d 56d 28d 56d 28d 56d

Average of Two Measurements

GU-III 6.8 5.82 6.54 6.56 34.07 39.23 0.13 0.12 0.48 0.70

GU25S- 5.7 4.72 5.07 5.83 35.42 39.25 0.14 0.11 0.46 0.61 III

PH-III 5.6 4.62 5.18 5.36 34.31 30.51 0.16 0.18 0.41 0.38

PH25S- 5.60 4.62 5.28 5.36 33.13 33.13 0.16 0.15 0.45 0.42 III *Aggregate correction factor of 0.98% is applied.

10 Fresh Hardened (28d) Hardened (56d) 8

Air Content (%) Content Air

0 GU-III GU25S-III PH-III PH25S-III

Mix ID

Figure 5.12: Air content of concrete (Phase III) Note: Each symbol represents ones measurements for fresh and the average of two measurements for hardened concrete.

5.3.3 Phase IV

Results from the compressive strength test at 28 days are shown in Figure 5.13. By 28 days, GU sample achieved compressive strengths of approximately 45 MPa, which is higher than the previous phase by more than 6%, while PH sample resulted in a lower compressive strength of approximately 35 MPa, which is lower by more than 14%.

The 28 day UPV measurements, shown in Figure 5.14, for all mixes are in generally lower range (4400 to 4800m/s) in comparison to the previous phase III (4700 to 4900m/s). This is expected since Phase IV concrete has relatively higher air content (6.5 to 8%) in comparison to the air content of the concrete in Phase III (5.6 to 6.8%).

28d

Compressive Strength (MPa) Strength Compressive

0 GU-IV PH-IV

Mix ID Figure 5.13: Compressive strength of concrete (Phase IV) Note: Each bar represents the average of three measurements and the error bar represents standard deviation

6000 28d

5000

4000

3000

UPV (m/s)

2000

1000

0 GU-IV PH-IV

Mix ID Figure 5.14: Ultrasonic pulse velocity (Phase IV) Note: Each bar represents three measurements and the error bar represents standard deviation

Table 5.6 shows additional information on the air characterization of the GU and PH mixes. Figure 5.15 presents the fresh air content and the hardened air content at 28 days. The results show similar fresh and hardened air content measurements for all mixtures, falling between 6.5- 8%.

Previously, in Phase III, AirExtra was used as an AEA. Although the hardened air content of the GU samples are almost the same, when compared to Phase III, using different brand of AEA and addition of HRWR results in an increase in both spacing factor and the specific surface of air. For PH samples, when compared to the previous page, increase in both fresh and hardened air content results in decrease of both spacing factor and specific surface of air.

Table 5.6: Air content characterization (Phase IV)

Specific Hardened Spacing Surface Void Frequency Apparent Fresh Air Content Factor (mm2/mm3 of (intercepts/mm) Mix Air Air (%) (mm) air) ID Content Content* (%) (%) 28d 28d 28d 28d

Average of Two Measurements

GU-IV 6.5 5.52 6.51 22.6 0.19 0.37

PH-IV 7.6 6.62 8.04 25.44 0.15 0.5 *Aggregate correction factor of 0.98% is applied.

10 Fresh Hardened (28d)

Air Content (%) Content Air

0 GU-IV PH-IV

Mix ID Figure 5.15: Air content of concrete (Phase IV) Note: Each symbol represents ones measurements for fresh and the average of two measurements for hardened concrete.

60 GU-II GU25S-II 55 PH-II PH25S-II GU-III GU25S-III 50 PH-III PH25S-III GU-IV 45 PH-IV

28d Compressive Strength (MPa) Strength 28d Compressive 35

30 2 4 6 8 10 28d Hardened Air Content (%)

Figure 5.16: Influence of air content on compressive strength (28d)

5.3.4 Discussion of the Effects of Mix Design Variables

As shown in Figure 5.16, for both GU and PH samples, there is a decrease in compressive strength with an increase in the air content. Utilizing different brand of AEA and addition of HRWR improves the strength of GU sample with no effect on the hardened air content, while it reduces the strength in PH sample and increases its air content.

5.4 Transport Properties

5.4.1 Phase II The RCPT results, shown in Figure 5.17, indicate that the chloride permeability of all the mixes with 25% GGBFS are less than 2000 Coulombs. PH samples show the highest chloride permeability.

28d 56d 6000

4000

2000

Adjusted charge passed (Coulombs)

0 GU-II GU25S-II PH-II PH25S-II

Mix ID Figure 5.17: Rapid chloride permeability of concrete (Phase II) Note: Each bar represents the average of two measurements 69

5.4.2 Phase III The RCPT results are shown in Figure 5.18. Both the GU25S and the PH25S have similar RCPT values at 28 and 56 days. At 28 days, the RCPT of the GU and PH concrete is similar. For all mixtures, the RCPT decreases with age as expected.

The initial sorptivity of finished and formed surfaces at 28 and 56 days are shown in Figure 5.19 and Figure 5.20, respectively. It is apparent that there is a greater sorptivity for finished (top) surfaces in comparison to formed (bottom) surfaces. This is attributed to a more porous surface layer in finished surface than to that of formed. As expected, the sorptivity coefficient of the finished surface was greater than that of the formed surface, while this rate decreased with higher curing period. Concrete with PH cement did not have any effect on the sorptivity coefficient. The addition of 25% GGBFS resulted in an increase in initial sorptivity rate of both GU and PH specimens.

28d 56d 6000

4000

RCPT (Coulombs) RCPT 2000

0 GU-III GU25S-III PH-III PH25S-III

Mix ID Figure 5.18: Rapid chloride permeability of concrete (Phase III) Note: Each bar represents the average of two measurements, except for PH at 28d (three measurements)

50 Finished

) Formed

1/2 40

mm/sec

-4

Initial Sorptivity (x10 Sorptivity Initial

0 GU-III GU25S-III PH-III PH25S-III MIX ID Figure 5.19: Initial sorptivity of finished and formed surface concrete at 28 days (Phase III) Note: Each bar represents the average of three measurements

50 Finished Formed

) 40

1/2

mm/sec

-4 30

Initial Sorptivity (x10 Sorptivity Initial

0 GU-III GU25S-III PH-III PH25S-III

MIX ID Figure 5.20: Initial sorptivity of finished and formed surface concrete at 56 days (Phase III) Note: Each bar represents the average of three measurements 71

5.4.3 Phase IV

Figure 5.21 shows the RCPT results for phase IV mixes. At 28 days, when compared to phase III, the RCPT of both GU and PH is high. The relative increase in RCPT results is higher for PH and this can be related to the improvement in the pore structure of the samples in Phase IV.

The initial rate of absorption of the samples followed the same trend; higher than that found in the previous phase, especially in the formed surface samples.

6000 28d

5000

4000

3000

RCPT (Coulombs) RCPT 2000

1000

0 GU-IV PH-IV

Mix ID Figure 5.21: Rapid chloride permeability of concrete (Phase IV) Note: Each bar represents the average of two measurements

50 Finished

) Formed

1/2 40

mm/sec

-4

Initial Sorptivity (x10 Sorptivity Initial

0 GU-IV PH-IV MIX ID Figure 5.22: Initial sorptivity of finished and formed surface concrete at 28 days (Phase IV) Note: Each bar represents the average of three measurements

6000

4000 GU-II GU25S-II PH-II PH25S-II GU-III 28d (Coulombs) RCPT 2000 GU25S-III PH-III PH25S-III GU-IV PH-IV 0 0 2 4 6 8 10 28d Hardened Air Content (%) Figure 5.23: Influence of air content on RCPT results at 28d

5.4.4 Discussion of the Effects of Mix Design Variables

As shown in Figure 5.23, the RCPT results for all the PH samples are about or higher than 4000 coulombs, despite of the amount of AEA used. This can be due the TiO2 in the photocatalytic cement, which acts as a semiconductor. This demonstrates that RCPT test may not be appropriate testing photocatalytic concrete.

Since the RCPT test is related to capillary absorption, the samples need to maintain a continuous liquid phase for chloride ingress. For GU samples, utilizing different brand of AEA and addition of HRWR improves the pore structure development of the concrete samples.

5.5 Durability Properties

5.5.1 Phase III

Results from the resistance to salt scaling test for finished and formed surfaces are shown in Figure 5.24 and Figure 5.25, respectively. Based on the results of up to 50 freeze-thaw cycles, the finished surface scaled more than the formed surface for the same concrete mix design. As expected, the poorer scaling performance of the finished surface is attributed to the effects of bleed water and/or variations in surface microstructure due to the finishing technique. For both the finished and the formed surface, the PH and PH25S exhibit greater mass losses. The influence of the fine particle size of the TiO2 on surface scaling may be a potential explanation but needs to be examined further.

Figure 5.24 shows that the finished surface of PH and PH25S concrete exhibits much greater scaling losses compared to GU and GU25S even after 5 freeze thaw cycles, at which point they had already exceeded the 0.80 kg/m2 OPSS 1351 acceptance limit. Figure 5.25 shows that for the formed surface, although the PH mixtures are scaling more than the GU concrete, the cumulative mass loss after 50 freeze-thaw cycles is less than the OPSS limit of 0.80 kg/m2.

As expected, the concrete containing 25% GGBFS exhibited greater scaling mass loss compared to those without GGBFS, irrespective of whether GU or PH cements were used and whether the formed or finished surface was tested. Theories of the influence of GGBFS on salt scaling are well reported in literature and will not be discussed in this report (Copuroglu, 2006; Boyd and Hooton, 2007; Valenza and Sherer, 2006).

In terms of visual ranking, based on ASTM C672, as shown in Figures 5.26 and 5.27, for finished surface samples, GU samples are closer to visual rating of 2, while PH samples can be ranked at 5. For formed surfaces, as shown in Figures 5.28 and 5.29, GU samples had a visual ranking of 1 and the PH samples had a visual ranking of 4.

4 GU-Fin GU25S-Fin PH-Fin

) PH25S-Fin

2 3 MTO Limit (0.80)

Cumulative Mass Loss (Kg/m Mass Cumulative

0 0 10 20 30 40 50 60

Cycles Figure 5.24: Salt scaling mass loss of finished surface (Phase III) Note: Each symbol represents the average of two measurements

4 GU-For GU25S-For PH-For

) PH25S-For

2 3 MTO Limit (0.80)

Cumulative Mass Loss (Kg/m Mass Cumulative

0 0 10 20 30 40 50 60

Cycles Figure 5.25: Salt scaling mass loss of formed surface (Phase III) Note: Each symbol represents the average of two measurements

Figure 5.26: GU concrete (finished surface) after 50 freeze-thaw cycle (Phase III)

Figure 5.27: PH concrete (finished surface) after 50 freeze-thaw cycle (Phase III)

Figure 5.28: GU concrete (formed surface) after 50 freeze-thaw cycle (Phase III)

Figure 5.29: PH concrete (formed surface) after 50 freeze-thaw cycle (Phase III)

Rapid freeze/thaw testing was used to evaluate the durability factor of the prisms. Figure 5.30 illustrates the durability factors that were calculated in accordance with the recommendation is ASTM C666 after 300 freeze/thaw cycles. The durability factors range from 92% to 97%. This reveals that all mix designs are resisting damage well.

Figure 5.31 and Figure 5.32 show the appearance and conditions of the prisms after 300 rapid freeze-thaw cycles.

100

Durability Factor (%) Factor Durability

0 GU GU25S PH PH25S Mix ID Figure 5.30: Durability factor after 300 rapid freeze-thaw cycles (Phase III) Note: Each bar represents the average of two measurements

Figure 5.31: GU and GU+25%GGBFS prisms after 300 rapid freeze-thaw cycles (Phase III)

Figure 5.32: PH and PH+25%GGBFS prisms after 300 rapid freeze-thaw cycles (Phase III)

5.5.2 Phase IV

Results from the resistance to salt scaling test are shown in Figures 5.33 and 5.34 for the finished and formed surface, respectively. Based on the results the finished surface of both mix GU and PH mixes already exceeded the 0.80 kg/m2 OPSS 1351 acceptable limit just after the first 5 freeze-thaw cycles. For the formed surface, the PH mixtures are scaling less than the GU concrete and the cumulative mass loss after 50 freeze-thaw cycles is well below the OPSS limit of 0.80 kg/m2.

In terms of visual ranking, based on ASTM C672, as shown in Figures 5.26 and 5.27, for finished surface samples, both GU and PH samples were closer to visual rating of 4, while the GU formed surface and PH formed surface, as shown in Figures 5.28 and 5.29, had a visual ranking of 3 and 1, respectively.

4 GU-Fin-IV PH-Fin-IV MTO Limit (0.8)

)

2 3

Cumulative Mass Loss (Kg/m Mass Cumulative

0 0 10 20 30 40 50 60

Cycles Figure 5.33: Salt scaling mass loss of finished surface (Phase IV)

4 GU-For-IV PH-For-IV MTO Limit (0.8)

)

2 3

Cumulative Mass Loss (Kg/m Mass Cumulative

0 0 10 20 30 40 50 60

Cycles Figure 5.34: Salt scaling mass loss of formed surface (Phase IV)

Figure 5.35: GU concrete (finished surface) after 50 freeze-thaw cycle (Phase IV)

Figure 5.36: PH concrete (finished surface) after 50 freeze-thaw cycle (Phase IV)

Figure 5.37: GU concrete (formed surface) after 50 freeze-thaw cycle (Phase IV)

Figure 5.38: PH concrete (formed surface) after 50 freeze-thaw cycle (Phase IV)

5.5.3 Effects of Mix Design Variables

As shown in Figures 5.39 and 5.40, the addition of HRWR resulted in improved salt-scaling resistance for PH samples with formed surfaces while it had an opposite effect on finished surfaces for both GU and PH.

4 GU-III

) GU25S-III 2 PH-III PH25S-III 3 GU-IV PH-IV

Cummulative Mass Loss (Kg/m Cummulative 1

0 0 2 4 6 8 10

Hardened Air Content (%) Figure 5.39: Influence of air content on salt-scaling for finished surface after 50 cycles

4 GU-III GU25S-III

) PH-III

2 PH25S-III 3 GU-IV PH-IV

Cummulative Mass Loss (Kg/m Cummulative

0 0 2 4 6 8 10 Hardened Air Content (%)

Figure 5.40: Influence of air content on salt-scaling for formed surface 50 cycles

Chapter 6 Conclusion

Photocatalytic concrete is a rapidly emerging and innovative technology in material science that exhibits self-cleaning and pollution-abating properties owing to the presence of titanium dioxide. Although the pollution-abating effectiveness of photocatalytic concrete has been proven in laboratory and field studies around the world, a close examination of the material properties have not been reported as widely.

Key conclusions from this study include:

 For Hamilton MT station, the NO abatement estimates of photocatalytic concrete are:

o For a relatively lower abatement rate (6 mg/h/m2), a maximum NO abatement rate of 20% is achieved. This estimate is calculated based on the eleven year average NO concentration of 30 mg/h/m2 for the month of July.

o For a relatively higher abatement rate (20 mg/h/m2), a maximum NO abatement rate of 67%. This estimate is calculated based on the eleven year average NO concentration of 30 mg/h/m2 for the month of July.

 In Toronto, for a 20 mg/h/m2 abatement rate of photocatalytic concrete, estimated range of 3% to 24% NO removal efficiency can be achieved. In general, these estimates fall within 20-80% range of pollution abatement effectiveness reported in the literature.

 The mechanical and fluid transport properties of photocatalytic concrete are comparable to conventional GU concrete:

o In Phase III at 28 days, where hardened air contents for GU concrete is 6.5% and for PH concrete is 5.2%, with total cementitious material of 429 k/m3 and water to cement ratio of 0.42, the compressive strength ranges between 39-48 MPa.

o In Phase IV at 28 days, where hardened air content for GU concrete is 6.5% and for PH concrete is 7.6%, with total cementitious material of 429 k/m3 and water to cement ratio of 0.42 plus the addition of HRWR, the compressive strength of the photocatalytic concrete decreased by approximately 13% while the compressive strength of the GU concrete increased by approximately 6% when compared to phase III. The decrease in compressive strength of the photocatalytic concrete could be explained by the increase in the air content.

o RCPT values in different phases gave inconsistent results.

 Air was much more difficult to entrain in photocatalytic concrete compared to GU concrete. However, with 5% to 7% air, photocatalytic concrete can achieve good freeze-thaw resistance, comparable to air-entrained GU concrete.

 In terms of de-icer salt scaling performance:

o Formed surface performed well and achieved relatively lower mass loss. Although formed surface PH concrete mass loss was greater than that of GU, it was still below 0.8 even after 50 cycles.

o Highly variable results for PH and GU concrete was observed for the finished surface. This is particularly important because photocatalytic concrete is only economically feasible if it is applied as a cover.

o Utilizing different brands of AEA with addition of HRWR improved the scaling performance of the photocatalytic concrete for the formed surface. Possible explanations are the relatively higher air content and a better workability (higher slump).

Chapter 7 Recommendations for Future Work

Further research is necessary to investigate why photocatalytic concrete performs poorer than conventional concrete in the salt-scaling test.

This can be done by investigating different methods for surface finishes as well as utilizing different admixtures to optimize the entrained air content. Until this is resolved, it is suggested that photocatalytic concrete should be restricted from de-icer salt expose. Admixtures need to be evaluated to ensure that they do not decrease the effectiveness of the photocatalytic activity of concrete.

Furthermore, due to inconclusive RCPT results, other tests should be carried out in order to investigate the penetration resistance of the photocatalytic concrete.

References

Abell, A.B., Willis, K.L., and Lange, D.A. (1999). "Mercury intrusion porosimetry and Image analysis of cement-based materials", Colloid and Interface Science, V. 211, No. 1, pp. 39-44.

AEA Technology. (2005). Damages per tonne emission of PM2.5, NH3, SO2, NOx and VOCs from each EU25 member state. Clean Air for Europe Programme, European Commission (http://ec.europa.eu/index_en.htm).

Asadi, S., Hassan, M.M., Kervern, J.T., and Rupnow, T. (2012). “Development of photocatalytic pervious concrete pavement for air and storm water improvements”, Proceedings of the 91st annual Transportation Research Board meeting, Washington, D.C, January, 2012.

Asadi, S., Hassan, M.M., Dylla, H., and Mohammad, L.N. (2012). “Evaluation of field performance of photocatalytic asphalt pavement in ambient air purification”, Proceedings of the 91st annual Transportation Research Board meeting, Washington, D.C, January, 2012.

Ballari, M.M., Hunger, M., Husken, G., and Brouwers, H.J.H. (2010). “NOx photocatalytic degradation employing concrete pavement containing titanium dioxide”, Applied Catalysis B: Environmental, V. 95, pp. 245-254.

Barbesta, M., and Schaffer, D. (2009). “Concrete that cleans itself and the air”, Concrete International, V. 31, No. 2, pp. 49-51.

Beeldens, A. (2006). “An environmental friendly solution for air purification and self-cleaning effect: the application of TiO2 as photocatalyst in concrete”, Belgian Road Research Centre Brussels, Proceedings of 10th International Symposium on Concrete Roads, Belgium.

Beeldens, A. (2008). “Air purification by pavement blocks: final results of the research at the BRRC”, Transport Research arena Europe (TRA) 2008, Ljubljana

Bein, P. (1997). Reviews of Transport 2021 costs of transporting people in the Lower Mainland. British Columbia Ministry of Transportation and Highways Planning Services Branch. (www.gov.bc.ca/tran), at www.geocities.com/davefergus/Transportation/0ExecutiveSummary.htm

Bellekom, S., Potting, J., and Benders, R. (2006). Feasibility of applying site-dependent impact assessment of acidification in LCA. The International Journal of Life Cycle Assessment, 11, 6, 417-424. Retrieved from http://dx.doi.org/10.1065/lca2005.08.221

Berdahl, P., and Akbari, H. (2008) “Evaluation of titanium dioxide as a photocatalyst for removing air pollutants”, California Energy Commission, PIER Energy-Related Environmental Reseach Program, CEC-500-2007-112.

Bouzoubaa, N. and Fournier, B. (2003). Current situations of SCMs in Canada. Ottawa: Materials Technology Laboratory (MTL)/CANMET, Technical Report 4.

Bowlby, W. (1992). NCHRP Synthesis101: In-service experience with traffic noise barriers. Transportation Research Board, National Research Council. pp. 63.

Boyd, A., and Hooton, R. D., (2007), “Long-Term Performance of Concretes Containing Supplementary Cementing Materials”, Journal of Materials in Civil Engineering, Vol. 19, Iss. 10, pp. 820 –825

Broekhuizen, P.V., Broekhuizen, F.V., Cornelissen, R., Lucas, R. (2010) “Use of nanomaterials in the European construction industry and some occupational health aspects thereof”, Nanoparticle Research, V. 13, pp. 447-462.

Burtraw, D. And Szambelan, S. J. (2009). “U.S. emissions trading markets for SO2 and NOx”, Resources for the Future, Discussion Paper RFF DP 09-40.

Butcher, S.S., Charlson, R.J., Orians, G.H., and Wolf G.V. (1992). “Global biogeochemical cycles”, Academic Press Inc., V. 50, p. 46.

Campella, L., Borzetti, F., Cassar, L. (2007). Photocatalytic Cement: A New Approach to Environmental Protection. RILEM International Symposium on Photocatalysis, Environment and Construction Materials, Firenze, Italia. 203-210.

Carp, O., Huisman, C.L., Reller, A. (2004) “Photoinduced reactivity of titanium dioxide”, Progress in Solid State Chemistry, V. 32, pp. 33-177.

Cassar, L., Beeldens, A., Pimpinelli, N., Guerrini, G.L. (2007). "Photocatalysis of cementitious materials" International RILEM Symposium Photocatalysis, Environment and Construction Materials-TDP, Florence, Italy, pp. 131-145.

Chen, J. and Poon, C. (2009). “Photocatalytic construction and building materials: From fundamentals to applications”, Building and Environment, V.44, No. 9, pp. 1899-1906.

Chen, J. and Poon, C. (2009). "Photocatalytic cementitious Mmaterials: influence of the microstructure of cement paste on photocatalytic pollution degradation", Environ. Sci. Technol, V.43, No. 23, pp. 8948-8952.

Churchill, C.J., and Panesar, D.K. (2012). “Life-cycle cost analysis of highway noise barriers designed with photocatalytic cement”, Structure and Infrastructure Engineering: Maintenace, Management, Life-Cycle Design and Performance, DOI:10.1080/15732479.2011.653574. pp.16.

Chusid, M. (2006). “Words you should know: depollution, photocatalysis”, Concrete, Economic, Social, Environmental, http://www.sustainableconcrete.org.nz/page/depolluting- concrete.aspx, Accessed November, 2010. 91

Copuroglu O. (2006). Frost salt scaling of cement-based materials with a high slag content. Ph.D. Dissertation: Delft, Technical University of Delft.

Crispino, M., and Lambrugo, S. (2007). "An experimental characterization of a photocatalytic mortar for road bituminous." International RILEM Symposium Photocatalysis, Environment and Construction Materials-TDP, Florence, Italy, pp. 211-218.

Diamanti, M.V., Ormellese, M., and Pedeferri, M. (2008). “Characterization of photocatalytic and superhydrophilic properties of mortars containing titanium dioxide”, Cement and Concrete Research, V. 38, pp. 1349-1353.

Dylla, H., Hassan,M.M., Schmitt,M., Rupnow,T., Mohammad, L.N., and Wright, E. (2011). "Effects of roadway contaminants on titanium dioxide photodegradation of NOx", Transportation Research Board 90th Annual Meeting, Washington, D.C, Paper #11-1105.

Dylla, H., Hassan, M.M., Osborn, D. (2012). “Field evaluation of photocatalytic concrete pavement’s ability to remove nitrogen oxides”, Proceedings of the 91st annual Transportation Research Board meeting, Washington, D.C, January 2012.

Essroc Italcementi Group (2009). "Concrete that cleans itself and the environment", presentation on behalf of Essroc Italcementi Group at CONSTRUCT2009, Indiana Convention Center, Indianapolis, IN.

FHWA (2002). Highway Economic Requirements System: Technical Report, Federal Highway Administration, U.S. Department of Transportation (www.fhwa.dot.gov); at http://isddc.dot.gov/OLPFiles/FHWA/010945.pdf.

Folli, A., Pochard, I., Nonat, A., Jakobsen, U.H., Shepherd, A.M., and Macphee, D.E. (2010). "Engineering photocatalytic cement: understanding TiO2 surface chemistry to control and modulate photocatalytic performances." The American Ceramic Society, V. 93, No. 10, pp. 3360-3369.

Gens Nano: Green Earth Nano Science Inc. (2011). “Mechanism of photocatalysis”, MCH Nano Solutions , http://www.mchnanosolutions.com/mechanism.html, Accessed May, 2011.

Hassan, M.M. (2009). “Life-cycle assessment of titanium dioxide coatings”, Proceedings of the 2009 Construction Research Congress, pp. 836-845.

Hassan, M.M. (2010). “Quantification of the environmental benefits of ultrafine/nano titanium dioxide photocatalyst coatings for concrete pavement using hybrid life cycle assessment,” Journal of Infrastructure Systems, V.16, No. 2, pp. 160-166.

Hassan, M.M., Dylla, H., Mohammad, L.N., Rupnow, T. (2010). "Evaluation of the durability of titanium dioxide photocatalyst coating for concrete pavement", Construction and Building Materials, V. 24, No. 8, pp. 1456-1461.

Herrmann, J.M. Péruchon, L. Puzenat, E., and Guillard C. (2007). Photocatalysis: from fundamentals to self-cleaning glass application. Proceedings international RILEM symposium on photocatalysis, environment and construction materials-TDP 2007 P. Baglioni, L. Cassar (Eds.), RILEM Publications, Bagneux, 2007, pp. 41–48.

Hinczak, I. (1990). “Alternative cement- the blue circle experience”, Proceedings of the Onoda Pacific Conference, Sydney, Australia, pp. 1-21.

Hohmeyer O., and Gartner M., 1992. The costs of climate change report to the Commission of European communities, Fraunhofer Institut fur Systemtechnik und Innovations, Karlsruhe.

Holland, M. and Watkiss, P. (2002). Estimates of marginal external costs of air pollution in Europe, European Commission (www.ec.europa.eu); at http://europa.eu.int/comm/environment/enveco/studies2.htm

Hunger, M., and Brouwers, H.J.H. (2009). "Self-cleaning surfaces as an innovative potential for sustainable concrete." Proceedings of the International Conference on Concrete Construction, London, UK, pp. 545-552.

Hunger, M., Husken, G., and Brouwers, H.J.H. (2008). “Photocatalysis applied to concrete products – Part 1: Principles and test procedure”, ZKG International, V. 61, No. 8, pp. 77-85.

Hunger, M., Husken, G., Brouwers, H.J.H. (2008). “Photocatalysis applied to concrete products – Part 2: Influencing factors and product performance”, ZKG International, V. 61, No. 10, pp. 76-84.

Hunger, M., Husken, G., and Brouwers, H.J.H. (2010). "Photocatalytic degradation of air pollutants - From modeling to large scale application." Cement and Concrete Research, V. 40, No. 2, pp. 313-320.

Husken, G., Hunger, M., and Brouwers, H.J.H. (2009). “Experimental study of photocatalytic concrete products for air purification,” Building and Environment, V. 44, No. 12, pp. 2463- 2474.

Ibusuki, T. (2002). Cleaning Atmospheric Environment, Chapter 8 in Photocatalysis: Science and Technology, M. Kaneko and I. Okura, eds., Kodansha Ltd., Tokyo.

International review of the Air Quality Innovation Programme (IPL). (2009). “Scientific board review”, Report number IPL-8, http://www.ipl-airquality.nl/project.php?name=katal-laag, Accessed December, 2010.

International Road Federation (IRF). (2010). “IRF urban mobility bulletin”, IRF Geneva, August 2010, http://www.irfnet.org/files-upload/pdf-files/irf_urbanmobility_web.pdf, Accessed December, 2010.

Italcementi Group: Technical Report. (2008). “Tx Active: The photocatalytic Active Principle”, http://txactive.us/, Accessed October, 2010.

Ircelyon: Institute of Researches on Catalysis and Environment in Lyon. (2010). “Photocatalytic remediation processes on air quality”, PhotoPAQ, http://photopaq.ircelyon.univ-lyon1.fr/Objectives, Accessed October, 2010.

Jacob, D.J. (1999). “Introduction to atmospheric chemistry”, Princeton University Press, Chapter 12, http://acmg.seas.harvard.edu/people/faculty/book/bookchap12.html

Jayapalan, A.R., Lee, B.Y., and Kurtis, K.E. (2009). ”Effect of nano-sized titanium dioxide o early age hydration of portland cement”, Nanotechnology in construction, Proceedings of the 3rd international symposium on nanotechnology in construction, Prague, Czech Republic, pp. 267-273.

Kawakami, M., Furumura, T., and Tokushige, H. (2007). "NOx removal effects and physical properties of cement mortar incorporating titanium dioxide powder." International RILEM Symposium on Photocatalysis. Florence, Italy, pp. 163-170.

Lashley, L. (2009). “The compatibility and performance of cementitious materials and chemical admixtures”, Thesis submitted for the degree of Master’s of Applied Science, University of Toronto.

Lee, B.Y., and Kurtis, K. (2010). "Influence of Tio2 nanoparticles on early C3S hydration", Journal of the American Ceramic Society, V. 93, No. 10, pp. 3399-3405.

Maibach, M., Banfi, S., Doll, C., Rothengatter, W., Schenkel, P., Sieber N. and Zuber, J. (2000). External costs of transport– accident, environmental and congestion costs in Western Europe. Published by INFRAS/IWW, Zürich/Karlsruhe.

Ministry of Environment Ontario (1991). “A Guide to the Ontario Air Quality Index System” http://www.ontla.on.ca/library/repository/mon/25002/118790.pdf, Accessed March 2012.

Ministry of Environment Ontario (2010). “Air Quality in Ontario – Report for 2010”, http://www.ene.gov.on.ca/documents/resource/stdprod_095558.pdf, Accessed March 2012.

Ministry of Environment Ontario (2012). “Air Quality Ontario”, http://www.airqualityontario.com, Accessed March 2012.

Morgan, S.M., Kay, D.H., and Bodapati, S.N. (2001). Study of noise barrier life-cycle costing. Journal of Transportation Engineering. Vol. 127, No. 3, 230-236.

Nazari, A., Riahi, S., Shamekhi, S.F., and Khademno, A. (2010). "Assessment of the effects of the cement paste composite in presence TiO2 nanoparticles", Journal of American Science, V. 6, No. 4, pp. 43-46.

Nazari, A., and Riahi, S. (2011). "The effect of TiO2 nanoparticles on physical, thermal and mechanical properties of concrete using ground granulated blast furnace slag as binder." Materials Science and Engineering, V. 528, pp. 2085-2092.

Ortiz, I.M. (2003). Life cycle assessment as a tool for green chemistry: Application to kraft pulp industrial wastewater treatment by different advanced oxidation processes. Masters Thesis. Institut de Ciència i Tecnologia Ambientals, The Universitat Autònoma de Barcelona.

Osborn, D., Hassan, M.M., and Dylla, H. (2012). “Quantification of NOx reduction via nitrate accumulation on a TiO2 photocatalytic concrete pavement”, Proceedings of the 91st annual Transportation Research Board meeting, Washington, D.C, January, 2012.

Pacheo-Torgal, F., and Jalali, S. (2011). "Nanotechnology: advantages and drawbacks in the field of construction and building materials." Construction and Building Materials, V. 25, pp. 582-590.

Photocatalytic Innovative Coverings Applications for Depollution Assessment (PICADA). (2010). http://www.picada-project.com/domino/SitePicada/Picada.nsf?OpenDataBase, Accessed October, 2010.

Piver, Warren T. (1987). “Predicting Concentrations of Atmospheric Pollutants”, Methods for Assessing the Effects of Mixtures of Chemicals, SCOPE 30, SGOMSEC 3, pp. 635-650.

Poon, C.S., and Cheung, E. (2007). "NO removal efficiency of photocatalytic paving blocks prepared with recycled materials." Construction and Building Materials, V. 21, No. 8, pp. 1746- 1753.

PPG: Residential Glass. (2011). “Hydrophilic process”, PPG Idea Scapes, http://www.ppg.com/corporate/ideascapes/resglass/homeowners/product/sunclean/Pages/Hydro philicProcessBig.aspx , Accessed November, 2011.

Prusinski, J.R., Marceau, M.L. and VanGeem, M.G. (2004). Life Cycle Inventory of Slag Cement Concrete, in Proceedings of the Eighth CANMET/ACI International Conference on Fly Ash, Silica Fume, Slag and Natural Pozzolans in Concrete, pp. 33.

Quantachrome Instruments. (2007). “Density - stereopycnometer”, Quantachrome Instruments Web site, http://www.quantachrome.com/density/stereopycnometer.html, Accessed Septeber, 2011.

Ramirez, A.M., Demeestere, K., Belie, N.D., Mantyla, T., and Levanen, E. (2010). “Titanium dioxide coated cementitious materials for air purifying purposes: preparation, characterization and toluene removal potential”, Building and Environment, V. 45, No. 4, pp.832-838.

RWDI. (2006). South Fraser perimeter road regional air quality assessment: technical volume 16 of the environmental assessment application. British Columbia Ministry of Transportation (www.gov.bc.ca/tran/).

Smith, S. (2010). A Critical Literature review of Photocatalytic (“Smog-Eating”) Concrete. MEng Thesis. Civil Engineering Department, University of Toronto.

Treasury Board of Canada. (2007). Benefit-cost analysis guide. Ottawa: Government of Canada.

TioCem. (2010). “Innovative building materials - reduction of pollution with TioCem”, Light Southwest Cement, http://www.lehighpermanente.com/tiocem-new, Accessed November 2010.

Valenza, J., and Scherer, G.W. (2006). “Mechanism for Salt Scaling”, Journal of American Ceramic Society, V. 89, No.4, p.1161-1179.

Wang, M.Q., Santini, D.J., and Warinner, S.A. (1995). Monetary values of air pollutants emissions in various U.S. regions,. Transportation Research Record 1475 (www.trb.org), pp. 33- 41.

Watkiss, P., Holland, M., Hurley, F. and Pye, S. (2006). Damage costs for air pollution. Final report to the United Kingdom’s Department of Environment Food and Rural Affairs retrieved from http://archive.defra.gov.uk/environment/quality/air/airquality/panels/igcb/documents/dcs- report2006.pdf

Whitlock, C.H., Brown, D.E. Chandler, W.S., DiPasquale, R.C., Meloche, N., Leng, G.J., Gupta, S.K., Wilber, A.C., Ritchey, N.A., Carlson, A.B., Kratz, D.P., and Stackhouse, P.W. (2000). Release 3 NASA surface meteorology and solar energy data set for renewable energy industry use. Data retrieved from http://eosweb.larc.nasa.gov/sse/

Windfinder. (2012). WindFinder.com GmbH & Co. KG, http://www.windfinder.com/windstats/, Accessed March 2012.

Yu, J. C. (2002). Ambient Air Treatment by Titanium Dioxide (TiO2) Based Photocatalyst in Hong Kong, Technical Report Prepared for the Environmental Protection Department, Hong Kong HKSAR, Tender Ref. AS 00-467, 1-42. Located at: www.epd.gov.hk/epd/english/environmentinhk/air/studyrpts/files/finalized_technical_report.pd.

Zhao, J., and Yang, X. (2003). "Photocatalytic oxidation for indoor air purification: a literature review." Building and Environment, V. 38, No.5, pp. 645-654.

Appendix A: Hourly Pollution Data for Toronto E Station

May 60 Jun Jul Aug 50 Sep

(ppb)

3 30

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour Figure A.1: Toronto E O3 hourly data from May to Sept (2000-2011)

Oct 60 Nov Dec Jan 50 Feb Mar Apr 40

(ppb)

3 30

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour Figure A.2: Toronto E O3 hourly data from Oct to April (2000-2011)

May 60 Jun Jul Aug 50 Sep

(ppb) x 30

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour Figure A.3: Toronto E NOx hourly data from May to Sept (2000-2011)

Oct Nov Dec 60 Jan Feb Mar Apr

(ppb)

H1 H2 H3 H4 H5 H6 H7 H8 H9

H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 H24 Hour

Figure A.4: Toronto E NOx hourly data from Oct to April (2000-2011)

Appendix B: Monthly Pollution Data for Cities with the Greatest Number of Smog Advisories in Ontario

60 Windsor DT Hamilton MT Port Stanley 50 Oshawa Brantford Sarnia

(ppb)

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.1: Average monthly O3 concentration (2000-2011)

60 Toronto DT Toronto W Toronto E 50 Toronto N

(ppb)

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.2: Average monthly O3 concentration for Toronto (2000-2011)

60 Windsor DT Hamilton MT Oshawa 50 Brantford Sarnia

(ppb) 30

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.3: Average monthly NOx concentration (2000-2011)

(ppb) 30

10 Toronto DT Toronto W Toronto E Toronto N 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.4: Average monthly NOx concentration for Toronto (2000-2011)

100

60 Windsor DT Hamilton MT 50 Oshawa Brantford Sarnia

(ppb) 30

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.5: Average monthly NO2 concentration (2000-2011)

60 Toronto DT Toronto W 50 Toronto E Toronto N

(ppb) 30

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.6: Average monthly NO2 concentration for Toronto (2000-2011)

101

60 Windsor DT Hamilton MT 50 Oshawa Brantford Sarnia 40

NO (ppb)

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.7: Average monthly NO concentration (2000-2011)

60 Toronto DT Toronto E 50 Toronto N Toronto W

NO (ppb)

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.8: Average monthly NO concentration for Toronto (2000-2011)

102

30 Windsor DT Hamilton MT 25 Oshawa Brantford Sarnia

3 15

µg/m

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.9: Average monthly PM2.5 concentration (2000-2011)

30 Toronto DT Toronto W 25 Toronto E Toronto N

3 15

µg/m

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure B.10: Average monthly PM2.5 concentration for Toronto (2000-2011)

103

Appendix C: Pollution Conversion (ppb to mg/h/m2)

Table C.1: Toronto DT Average Average wind speed [NO] Air TORONTO DT Toronto Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 10 19 19000 -2 10.30 0.0139 263.86 FEB 12 22 22000 -1 10.01 0.0134 295.82 MAR 11 20 20000 6 7.62 0.0100 199.55 APR 12 22 22000 8 5.83 0.0076 166.78 MAY 8 15 15000 17 4.87 0.0061 91.99 JUN 10 19 19000 21 4.47 0.0056 105.57 JUL 9 17 17000 26 4.02 0.0049 83.63 AUG 9 17 17000 23 4.67 0.0058 98.04 SEP 8 15 15000 19 5.85 0.0073 109.90 OCT 10 19 19000 12 9.40 0.0121 229.14 NOV 9 17 17000 8 10.35 0.0135 228.89 DEC 11 20 20000 0 9.34 0.0125 250.07

Table C.2: Toronto W Average Average wind speed [NO] Air TORONTO W Toronto Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 10 19 19000 -2 20.98 0.0283 537.60 FEB 12 22 22000 -1 23.16 0.0311 684.68 MAR 11 20 20000 6 20.65 0.0271 541.09 APR 12 22 22000 8 15.35 0.0200 439.11 MAY 8 15 15000 17 13.35 0.0168 252.32 JUN 10 19 19000 21 11.39 0.0142 269.02 JUL 9 17 17000 26 10.96 0.0134 227.75 AUG 9 17 17000 23 13.78 0.0170 289.24 SEP 8 15 15000 19 18.28 0.0229 343.27 OCT 10 19 19000 12 24.06 0.0309 586.29 NOV 9 17 17000 8 27.71 0.0360 612.61 DEC 11 20 20000 0 21.35 0.0286 571.70

104

Table C.3: Toronto E Average Average wind speed [NO] Air TORONTO E Toronto Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 10 19 19000 -2 18.29 0.0247 468.73 FEB 12 22 22000 -1 18.49 0.0248 546.44 MAR 11 20 20000 6 14.35 0.0188 375.92 APR 12 22 22000 8 9.73 0.0127 278.47 MAY 8 15 15000 17 8.27 0.0104 156.42 JUN 10 19 19000 21 7.67 0.0095 181.13 JUL 9 17 17000 26 7.06 0.0086 146.70 AUG 9 17 17000 23 8.86 0.0109 185.89 SEP 8 15 15000 19 12.27 0.0154 230.38 OCT 10 19 19000 12 17.34 0.0222 422.47 NOV 9 17 17000 8 20.45 0.0266 452.21 DEC 11 20 20000 0 17.56 0.0235 470.22

Table C.4: Toronto N Average Average wind speed [NO] Air TORONTO N Toronto Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 10 19 19000 -2 14.04 0.0189 359.81 FEB 12 22 22000 -1 13.86 0.0186 409.62 MAR 11 20 20000 6 11.53 0.0151 302.18 APR 12 22 22000 8 8.47 0.0110 242.41 MAY 8 15 15000 17 6.81 0.0086 128.71 JUN 10 19 19000 21 5.52 0.0069 130.42 JUL 9 17 17000 26 4.49 0.0055 93.22 AUG 9 17 17000 23 5.47 0.0068 114.92 SEP 8 15 15000 19 8.20 0.0103 153.92 OCT 10 19 19000 12 13.40 0.0172 326.42 NOV 9 17 17000 8 16.91 0.0220 373.87 DEC 11 20 20000 0 14.20 0.0190 380.17

105

Table C.5: Windsor DT Average Average wind speed [NO] Air Windsor DT Windsor Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 11 20 20000 -2 12.74 0.0172 343.70 FEB 10 19 19000 0 11.93 0.0160 303.34 MAR 10 19 19000 5 8.81 0.0116 220.02 APR 12 22 22000 11 5.05 0.0065 142.97 MAY 9 17 17000 18 4.51 0.0057 96.26 JUN 9 17 17000 23 4.06 0.0050 85.26 JUL 8 15 15000 25 3.16 0.0039 58.08 AUG 8 15 15000 24 4.31 0.0053 79.57 SEP 8 15 15000 20 6.38 0.0080 119.33 OCT 9 17 17000 14 10.09 0.0128 218.34 NOV 10 19 19000 7 12.89 0.0168 319.58 DEC 10 19 19000 0 14.28 0.0191 363.35

Table C.6: Oshawa Average Average wind speed [NO] Air Oshawa Oshawa Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 9 17 17000 -3 7.97 0.0108 183.39 FEB 10 19 19000 -1 8.71 0.0117 222.3381 MAR 10 19 19000 5 7.36 0.0097 183.72 APR 10 19 19000 8 5.51 0.0072 136.26 MAY 8 15 15000 16 4.98 0.0063 94.48 JUN 9 17 17000 20 4.35 0.0054 92.18 JUL 7 13 13000 24 3.51 0.0043 56.19 AUG 7 13 13000 22 3.55 0.0044 57.25 SEP 7 13 13000 20 4.69 0.0059 76.06 OCT 8 15 15000 12 8.04 0.0103 154.66 NOV 7 13 13000 7 10.46 0.0137 177.53 DEC 8 15 15000 1 9.97 0.0133 199.42

106

Table C.7: Hamilton MT Average Average wind speed [NO] Air Hamilton MT Hamilton Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 5 9 9000 0 10.44 0.0140 125.7994 FEB 5 9 9000 1 12.01 0.0160 144.1651 MAR 6 11 11000 6 9.15 0.0120 131.8332 APR 6 11 11000 9 7.64 0.0099 108.9826 MAY 5 9 9000 16 6.84 0.0087 77.8584 JUN 5 9 9000 21 4.72 0.0059 52.8643 JUL 4 7 7000 27 3.53 0.0043 30.0724 AUG 4 7 7000 24 4.26 0.0052 36.6691 SEP 4 7 7000 19 7.38 0.0092 64.6683 OCT 4 7 7000 12 11.52 0.0148 103.3916 NOV 5 9 9000 9 14.89 0.0193 173.6982 DEC 4 7 7000 2 11.51 0.0153 107.0664

Table C.8: Brantford Average Average wind speed [NO] Air Brantford Oxford Lake Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 5 9 9000 1 10.44 0.0139 125.3405 FEB 5 9 9000 13 12.01 0.0153 138.1194 MAR 5 9 9000 10 9.15 0.0118 106.3398 APR 3 6 6000 19 7.64 0.0096 57.4103 MAY n/a n/a n/a 6.84 JUN n/a n/a n/a 4.72 JUL n/a n/a n/a 3.53 AUG n/a n/a n/a 4.26 SEP n/a n/a n/a 7.38 OCT n/a n/a n/a 11.52 NOV n/a n/a n/a 14.89 DEC n/a n/a n/a 11.51

107

Table C.9: Sarnia Average Average wind speed [NO] Air Sarnia Blackwell/Sarnia (SARNIA) Temp Month Knots km/h m/h ºC (ppb) (mg/m3) (mg/h/m2) JAN 11 20 20000 -3 5.70 0.0077 154.3496 FEB 12 22 22000 -1 5.88 0.0079 173.8628 MAR 11 20 20000 4 3.99 0.0053 105.3741 APR 13 24 24000 9 3.33 0.0043 103.7213 MAY 10 19 19000 15 3.07 0.0039 74.0867 JUN 9 17 17000 20 3.32 0.0041 70.4415 JUL 8 15 15000 23 3.19 0.0039 59.0529 AUG 8 15 15000 22 2.95 0.0037 54.7678 SEP 9 17 17000 18 3.43 0.0043 73.1834 OCT 10 19 19000 12 4.66 0.0060 113.4253 NOV 10 19 19000 7 6.71 0.0088 166.3340 DEC 11 20 20000 0 6.40 0.0086 171.3059

108

Appendix D: Test Data D.1 Phase II

Table D.1: Compressive Strength (Phase II)

Compressive Strength (CSA.A23.2-9C) Curing MIX Age Strength Strength ID Average Co.V. (Day) Reading Reading St.Dev (MPa) (%) (KN) (Mpa) 392.8 48.07 28 398.8 48.81 48.43 0.37 0.76 395.5 48.41 GU 437.1 53.49 56 433.5 53.05 52.46 1.41 2.70 415.5 50.85 436.3 53.40 28 410.0 50.18 52.48 2.01 3.82 440.1 53.86 G25S 468.3 57.31 56 483.0 59.11 58.17 0.90 1.55 474.8 58.10 351.8 43.05 28 351.5 43.01 42.12 1.58 3.76 329.2 40.29 PH 383.4 46.92 56 382.2 46.77 46.92 0.16 0.33 384.7 47.08 418.4 51.20 28 426.2 52.16 51.84 0.55 1.06 426.2 52.15 PH25S 468.8 57.37 56 449.8 55.05 56.14 1.17 2.08 457.7 56.01

109

Table D.2: Ultrasonic Pulse Velocity (Phase II)

UPV (ASTM C 597) Curing Average MIX ID Age UPV Pulse Length Pulse Co.V. (Day) Reading Velocity St.Dev. (mm) Velocity (%) (µSec) (m/s) (m/s) 197 40.4 4.88×103 28 195 40.2 4.85×103 4859.5 14.5 0.30 196 40.4 4.85×103 GU 199 40.2 4.95×103 56 198 40.1 4.94×103 5001.4 99.7 1.99 198 38.7 5.12×103 197 42.4 4.65×103 28 198 42.6 4.65×103 4654.1 12.2 0.26 197 42.2 4.67×103 G25S 197 38.8 5.08×103 56 199 38.8 5.13×103 5035.6 119.7 2.38 197 40.2 4.90×103 196 42.0 4.67×103 28 197 42.6 4.62×103 4645.8 21.1 0.45 197 42.4 4.65×103 PH 200 40.2 4.97×103 56 197 40.2 4.90×103 4917.5 51.3 1.04 198 40.6 4.88×103 197 44.2 4.46×103 28 196 44.2 4.43×103 4456.2 21.4 0.48 197 44.0 4.48×103 PH25S 200 40.0 5.00×103 56 193 40.4 4.78×103 4917.4 122.1 2.48 200 40.2 4.97×103

110

Table D.3: Mass Measurements for Density (Phase II)

Density (CSA A23.2-11C)

Average Curing Average Average Average MIX Oven Age Section Diameter Submerged Boiled Suspended ID Volume Dry (Day) average Mass Mass Mass (mm3) Mass (mm) B C D A (Kg) (Kg) (Kg) (Kg) 1 2 28 102.52 5 3 8.25×10 1.88 1.97 1.97 1.12 4 GU 1 2 56 102.19 5 3 8.20×10 1.85 1.97 1.97 1.12 4 1 2 28 102 5 3 8.17×10 1.88 1.95 1.95 1.11 4 GU25S 1 2 56 101.86 5 3 8.14×10 1.84 1.95 1.95 1.11 4 1 2 28 102.68 5 3 8.28×10 1.89 1.97 1.97 1.13 4 PH 1 2 56 102.02 5 3 8.17×10 1.83 1.94 1.94 1.10 4 1 2 28 102.13 5 3 8.19×10 1.87 1.94 1.94 1.11 4 PH25S 1 2 56 102.08 5 3 8.18×10 1.84 1.97 1.97 1.12 4

111

Table D.4: Absorption and Density (Phase II) absorption absorption Density Density Curing (after Dry Density (after (after (after immersion MIX ID Age immersion and (Oven-dried) immersion) immersion) and boiling) (Day) boiling) Kg/m3 % Kg/m3 Kg/m3 % 28 4.65 4.65 2222.3 2325.7 2325.6 GU 56 6.31 6.30 2187.6 2325.8 2325.6 28 3.63 3.64 2244.0 2325.4 2325.6 GU25S 56 6.15 6.13 2191.2 2325.9 2325.6 28 4.48 4.47 2226.1 2325.7 2325.6 PH 56 5.51 5.51 2204.1 2325.6 2325.6 28 3.64 3.61 2244.4 2326.1 2325.6 PH25S 56 7.23 7.20 2169.3 2326.2 2325.6

Table D.5: Rapid Chloride Permeability (Phase II)

RCPT (ASTM C 1202) Curing MIX Age Section ID Average Total Adjusted (Day) Co.V. Diameter Charge Average Charge Average St.Dev (%) (mm) Passed Passed

1 102.8 3397 2947 28 3661.5 3176.5 2 102.30 3926 3406 324 10.22 GU 1 102.81 2929 2541 56 2 102.33 3209 3069 2784 2662.5 171 6.45 1 102.32 1719 1491 28 2 102.15 1699 1709 1474 1482.5 12 0.81 GU25S 1 102.05 1192 1034 56 2 102.03 1240 1216 1076 1055 30 2.82 1 102.54 7093 6153 28 2 102.49 5386 6239.5 4672 5412.5 1047 19.35 PH 1 102.22 5752 4990 56 2 101.71 4585 5168.5 3977 4483.5 716 15.98 1 102.20 2298 1993 28 2 101.68 2299 2298.5 2034 2013.5 29 1.44 PH25S 1 102.29 1757 1524 56 2 101.82 1566 1661.5 1358 1441 117 8.15

112

D.2 Phase III

Table D.6: Compressive Strength (Phase III)

Compressive Strength (CSA.A23.2-9C) Curing MIX Age Strength Strength ID Average Co.V. (Day) Reading Reading St.Dev. (MPa) (%) (KN) (Mpa) 352.1 43.09 28 339.3 41.53 42.24 0.64 1.53 344.0 42.10 GU 365.7 44.75 56 374.2 45.80 45.45 0.49 1.08 374.2 45.79 392.3 48.01 28 374.8 45.87 46.37 1.19 2.56 369.6 45.23 G25S 424.9 52.00 56 416.4 50.96 51.88 0.71 1.37 430.6 52.69 321.3 39.32 28 332.2 40.66 39.74 0.65 1.64 320.7 39.24 PH 352.1 42.25 56 350.8 42.10 42.90 1.03 2.41 369.6 44.36 336.1 41.14 28 343.3 42.01 41.63 0.36 0.87 341.0 41.73 PH25S 370.4 45.33 56 378.0 46.26 44.77 1.49 3.34 349.2 42.73

113

Table D.7: Ultrasonic Pulse Velocity (Phase III)

UPV (ASTM C 597) Curing MIX Average Age UPV Pulse ID Length Pulse Co.V. (Day) Reading Velocity St.Dev. (mm) Velocity (%) (µSec) (m/s) (m/s) 195 42.2 4.62×103 28 197 40.6 4.85×103 4.71×103 99.79 2.12 197 42.2 4.67×103 GU 197 40.4 4.88×103 56 199 40.6 4.90×103 4.9×103 20.51 0.42 201 40.8 4.92×103 200 42.0 4.76×103 28 197 40.2 4.9×103 4.7×103 103.95 2.18 197 42.4 4.65×103 G25S 200 40.2 4.97×103 56 200 40.2 4.97×103 4.97×103 0.00 0.00 200 40.2 4.97×103 198 42.6 4.65×103 28 200 42.4 4.72×103 4.7×103 28.81 0.61 200 42.6 4.7×103 PH 199 42.2 4.71×103 56 200 42.2 4.74×103 4.73×103 11.17 0.24 200 42.2 4.74×103 210 42.6 4.93×103 28 198 42.2 4.69×103 4.76×103 117.17 2.46 199 42.6 4.67×103 PH25S 201 42.4 4.74×103 56 200 42.4 4.72×103 4.71×103 19.26 0.41 199 42.4 4.69×103

114

Table D.8: Mass Measurements for Density (Phase III)

Density (CSA A23.2-11C)

Curing Average Average Average Average MIX Oven Submerged Boiled Suspended Age Section Diameter ID Volume Dry Mass Mass Mass Mass (Day) Average (mm3) A B C D (mm) (Kg) (Kg) (Kg) (Kg)

1 2 28 102.23 8.2×105 1.83 1.92 1.92 1.09 3 4 GU 1 2 56 102.23 8.2×105 1.81 1.90 1.90 1.08 3 4 1 2 28 101.85 8.14×105 1.86 1.94 1.94 1.11 3 4 GU25S 1 2 56 102.24 8.2×105 1.84 1.92 1.92 1.10 3 4 1 2 28 102.16 8.2×105 1.84 1.92 1.92 1.10 3 4 PH 1 2 56 102.03 8.17×105 1.82 1.91 1.91 1.10 3 4 1 2 28 102.53 8.25×105 1.88 1.94 1.94 1.11 3 4 PH25S 1 2 56 101.52 8.09×105 1.84 1.91 1.92 1.11 3 4

115

Table D.9: Absorption and Density (Phase III)

absorption absorption Density after Curing after Dry Density Density after MIX after immersion Age immersion (Oven-dried), immersion, ID immersion, and boiling, (Day) and boiling, Kg/m3 Kg/m3 % Kg/m3 %

28 5.00 4.71 2220.3 2331.4 2325 GU 56 5.22 5.16 2210.2 2325.5 2324.3 28 4.09 3.98 2248.9 2340.9 2338.5 GU25S 56 4.35 4.35 2232.9 2330.0 2330.1 28 4.26 4.33 2244.6 2340.4 2341.9 PH 56 4.81 5.03 2228.4 2335.6 2340.6 28 3.28 3.39 2256.8 2330.9 2333.4 PH25S 56 3.80 4.37 2254.9 2340.7 2353.4

Table D.10: Rapid Chloride Permeability (Phase III) RCPT (ASTM C 1202) Curing MIX Average Total Adjusted Age Section Co.V. ID Diameter Charge Average Charge Average St.Dev (Day) (%) (mm) Passed Passed 1 5013 4349 28 4396.5 3814 535 14.03 2 102.18 3780 3279 GU 1 3312 2873 56 2761.0 2414 459 19.01 2 101.91 2210 1955 1 1690 1466 28 1609.0 1395 70 5.05 2 102.3 1528 1325 GU25S 1 1165 1011 56 1138.5 997 13 1.35 2 101.92 1112 984 1 5210 4519 28 2 101.93 3146 3959.7 2729 3434 895 23.63 PH 3 3523 3056 1 4009 3618 56 4244.5 3714 96 2.60 2 102.57 4480 3811 1 1643 1425 28 1707.0 1480 55 3.75 2 102.26 1771 1536 PH25S 1 924 802 56 953.0 835 33 4.01 2 102.01 982 869

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Table D.11: Initial Sorptivity – GU and GU+25%GGBFS at 28d (Phase III)

Initial GU (28d) GU25S (28d) Sorptivity

Surface FINISHED FORMED FINISHED FORMED

Section 1 2 3 1 2 3 1 2 3 1 2 3

x10(- 14.98 17.95 15.85 5.02 6.79 5.82 5.65 27.41 40.07 28.01 24.22 4.18 4)mm/sec1/2

Average 16.26 5.88 33.74 26.11 ST.Dev 1.53 0.89 8.95 2.68 Co.V. (%) 0.09 0.15 0.27 0.10

Table D.12: Initial Sorptivity – GU and GU+25%GGBFS at 56d (Phase III)

Initial GU (56d) GU25S (56d) Sorptivity

Surface FINISHED FORMED FINISHED FORMED

Section 1 2 3 1 2 3 1 2 3 1 2 3

x10(- 17.38 23.72 12.33 5.65 6.30 6.38 7.09 17.31 22.18 14.98 6.29 14.98 4)mm/sec1/2

Average 17.81 6.11 19.75 14.98 ST.Dev 5.70 0.40 3.45 0.00 Co.V. (%) 0.32 0.07 0.17 0.00

Table D.13: Initial Sorptivity – PH and PH+25%GGBFS at 28d (Phase III)

Initial PH (28d) PH25S (28d) Sorptivity

Surface FINISHED FORMED FINISHED FORMED

Section 1 2 3 1 2 3 1 2 3 1 2 3

x10(- 17.28 11.57 18.59 13.15 9.53 8.35 19.35 24.80 12.56 16.09 10.76 9.22 4)mm/sec1/2

Average 15.81 10.34 18.91 12.03 ST.Dev 3.73 2.50 6.13 3.60 Co.V. (%) 0.24 0.24 0.32 0.30

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Table D.14: Initial Sorptivity – PH and PH+25%GGBFS at 56d (Phase III)

Initial PH (56d) PH25S (56d) Sorptivity

Surface FINISHED FORMED FINISHED FORMED

Section 1 2 3 1 2 3 1 2 3 1 2 3

x10(- 13.44 13.17 14.03 11.05 13.07 9.63 16.01 23.23 15.96 9.64 14.49 14.98 4)mm/sec1/2

Average 13.55 11.25 18.40 13.04 ST.Dev 0.44 1.73 4.18 2.95 Co.V. (%) 0.03 0.15 0.23 0.23

Table D.15: Salt-Scaling Mass Loss (Phase III)

Avg. Mass/Area (Kg/m2) Mix ID GU G25S PH PH25S

Surface Finished Formed Finished Formed Finished Formed Finished Formed

5 0.055 0.016 0.179 0.034 0.899 0.032 1.184 0.080 10 0.085 0.024 0.249 0.053 1.492 0.101 1.815 0.314 15 0.099 0.032 0.276 0.065 1.739 0.131 2.021 0.379

20 0.110 0.044 0.291 0.071 1.851 0.149 2.116 0.421 25 0.121 0.049 0.302 0.077 1.895 0.185 2.198 0.451 30 0.136 0.054 0.309 0.083 1.928 0.224 2.291 0.477 # Cycles # 35 0.147 0.059 0.316 0.090 1.962 0.265 2.396 0.529 40 0.165 0.068 0.319 0.101 1.984 0.293 2.483 0.560 45 0.173 0.075 0.326 0.115 2.008 0.324 2.569 0.583 50 0.183 0.082 0.333 0.135 2.039 0.394 2.695 0.635

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Table D.16: ASTM C666 Freeze-Thaw Data (Phase III) Prism # #1 #2 Relative Relative Dynamic Dynamic Length Durability Length Durability Frequency Modulus Frequency Modulus change Factor change Factor MIX ID Cycles of of Hz elasticity Hz elasticity (%) (%) (%) (%) (%) (%) 0 3319 3374

36 3271 97.13 0.01 97.13 3333 97.58 0.00 97.58 76 3274 97.31 0.01 97.31 3326 97.17 0.01 97.17 112 3271 97.13 -0.02 97.13 3339 97.94 0.01 97.94 GU 141 3267 96.89 0.02 96.89 3336 97.76 0.02 97.76 187 3266 96.83 0.03 96.83 3325 97.12 0.03 97.12 229 3266 96.83 0.03 96.83 3323 97.00 0.02 97.00 262 3193 92.55 0.02 92.55 3317 96.65 0.02 96.65 300 3180 91.80 0.04 91.80 3304 95.89 0.03 95.89 0 3417 3434

36 3368 97.15 0.00 97.15 3362 95.85 0.00 95.85 76 3358 96.58 0.00 96.58 3389 97.40 0.16 97.40 112 3362 96.81 0.01 96.81 3382 96.99 0.00 96.99 GU25S 141 3350 96.12 0.01 96.12 3370 96.31 0.02 96.31 187 3341 95.60 0.02 95.60 3370 96.31 0.02 96.31 229 3339 95.49 0.02 95.49 3368 96.19 0.02 96.19 262 3338 95.43 0.02 95.43 3363 95.91 0.01 95.91 300 3331 95.03 0.03 95.03 3357 95.57 0.02 95.57 0 3281 3154

36 3278 99.82 0.01 99.82 3143 99.30 -2.12 99.30 76 3218 96.20 0.01 96.20 3136 98.86 0.01 98.86 112 3222 96.44 0.01 96.44 3136 98.86 0.01 98.86 PH 141 3214 95.96 0.04 95.96 3130 98.48 -0.02 98.48 187 3186 94.29 0.02 94.29 3123 98.04 0.02 98.04 229 3182 94.06 0.02 94.06 3122 97.98 0.01 97.98 262 3175 93.64 0.02 93.64 3120 97.86 0.01 97.86 300 3168 93.23 0.03 93.23 3114 97.48 0.02 97.48 0 3276 3353

36 3219 96.55 0.01 96.55 3294 96.51 0.00 96.51 76 3216 96.37 0.02 96.37 3283 95.87 0.00 95.87 112 3227 97.03 0.01 97.03 3304 97.10 0.01 97.10 PH25S 141 3196 95.18 0.01 95.18 3293 96.45 0.01 96.45 187 3173 93.81 0.03 93.81 3256 94.30 0.01 94.30 229 3188 94.70 0.03 94.70 3243 93.55 0.01 93.55 262 3144 92.10 0.02 92.10 3240 93.37 0.01 93.37 300 3137 91.69 0.03 91.69 3235 93.09 0.02 93.09

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D.3 Phase IV

Table D.15: Compressive Strength (Phase IV)

Compressive Strength (CSA.A23.2-9C) Curing MIX Age Strength Strength ID Average Co.V. (Day) Reading Reading St.Dev. (MPa) (%) (KN) (Mpa) 361.2 44.2 GU 366.9 44.9 45 0.65 1.45 374.2 45.8 28 276.4 33.8 PH 279.7 34.3 34.7 0.95 2.72 294.4 36.0

Table D.16: Ultra Pulse Velocity (Phase IV)

UPV (ASTM C 597) Curing Average MIX UPV Pulse Age Length Pulse Co.V. ID Reading Velocity St.Dev. (Day) (mm) Velocity (%) (µSec) (m/s) (m/s) 197 40.2 4.9×103 GU 198 40.6 4.9×103 4.8×103 82.1 1.70 199 42.2 4.7×103 28 195 44.2 4.4×103 PH 200 44.2 4.5×103 4.5×103 46.8 1.05 200 44.6 4.5×103

Table D.17: Rapid Chloride Permeability (Phase IV) RCPT (ASTM C 1202) Curing MIX Age Section Average Total Adjusted Co.V. ID (Day) Diameter Charge Average Charge Average St.Dev (mm) Passed Passed (%) 1 3398 2948 GU 102.22 3188.5 2766 182 6.58 2 2979 2584 28 1 6444 5590 PH 101.98 5926.5 5187 402 7.76 2 5409 4785

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Table D.18: Salt-Scaling Mass Loss (Phase IV)

Avg. Mass/Area (Kg/m2) Mix ID GU PH

Surface Finished Formed Finished Formed 5 0.860 0.014 1.119 0.014 10 0.934 0.050 1.849 0.030 15 0.961 0.068 2.126 0.043

20 0.987 0.090 2.363 0.058 25 1.006 0.111 2.545 0.070 30 1.019 0.128 2.706 0.080 # Cycles # 35 1.035 0.162 2.888 0.092 40 1.040 0.195 3.037 0.098 45 1.048 0.252 3.192 0.100 50 1.058 0.301 3.312 0.105

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