Particulate Matter Emissions over the Oil Sands Regions in ... · Draft 4 / 58 38 1．Introduction 39 1.1 Overview of the oil sands industry in Canada 40 Oil sand is a naturally occurring

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Particulate Matter Emissions over the Oil Sands Regions in

Alberta, Canada

Journal: Environmental Reviews

Manuscript ID er-2016-0112.R3

Manuscript Type: Review

Date Submitted by the Author: 06-Jun-2017

Complete List of Authors: Xing, Zhenyu; University of Calgary, Department of Mechanical and Manufacturing Engineering, Schulich School of Engineering; University of Calgary, The Centre for Environmental Engineering Research and Education, Schulich School of Engineering Du, Ke; University of Calgary, Department of Mechanical and Manufacturing Engineering, Schulich School of Engineering; University of

Calgary, The Centre for Environmental Engineering Research and Education, Schulich School of Engineering

Keyword: oil sands, particulate matter, primary emission, secondary organic aerosol, source apportionment

https://mc06.manuscriptcentral.com/er-pubs

Environmental Reviews

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1

Particulate Matter Emissions over the Oil Sands Regions in Alberta, Canada 2

Zhenyu Xinga,b, Ke Dua,b,* 3

a Department of Mechanical and anufacturing Engineering, Schulich School of 4

Engineering, University of Calgary, Calgary, Alberta, Canada T2N1N4 5

b The Centre for Environmental Engineering Research and Education, Schulich 6

School of Engineering, University of Calgary, Calgary, Alberta, Canada T2N1N4 7

* Corresponding author. Tel.: +1 403 220 7883; Fax: +1 403 282 8406. E-mail address: 8

[email protected] (K. Du). 9

10

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Abstract 11

Particulate matter (PM) emissions from the expanded oil sands development in 12

Alberta are becoming a focus among the aerosol science community due to its 13

significant negative impact on the regional air quality and climate change. Open-pit 14

mining, petroleum coke (petcoke) dust, and the transportation of oil sands and waste 15

materials by heavy-duty trucks on unpaved roads, could release PM into the air. 16

Incomplete combustion of fossil fuels by engines and stationary boilers leads to the 17

formation of carbonaceous aerosols. In addition, wildfire and biogenic emissions 18

surrounding the oil sands regions also have the potential to contribute primary PM to 19

the ambient air. Secondary organic aerosol (SOA) formation has been revealed as an 20

important source of PM over nearby and distant areas from oil sands region. This 21

review summarizes the primary PM sources and some secondary aerosol formation 22

mechanisms, which are linked to oil sands development. It also reviews the 23

approaches that can be applied in aerosol source apportionment. Meteorological 24

condition is an important factor that may influence the primary PM emission and 25

secondary aerosol formation in Alberta’s oil sands regions. Current concern should 26

not be limited to the primary emission of atmospheric PM. Secondary formation of 27

aerosols, especially SOA originating from photochemical reaction, should also be 28

taken into consideration. To obtain a more comprehensive understanding of the 29

sources and amount of PM emissions based on the bottom-up emission inventory 30

approach, investigations on how to reduce the uncertainty in determination of 31

real-world PM emission factors for the variable sources are needed. Long-range 32

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transport trajectories of fine PM from Alberta’s oil sands regions remain unknown. 33

34

Keywords 35

oil sands, particulate matter, primary emission, secondary organic aerosol, source 36

apportionment 37

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1．Introduction 38

1.1 Overview of the oil sands industry in Canada 39

Oil sand is a naturally occurring mixture of mineral solids (83-88%), water (3-5%) 40

and bitumen (8-14%), which is a heavy and extremely viscous oil. To produce usable 41

fuels, such as gasoline and diesel, oil sand must be pre-treated before it can be 42

processed by refineries (Gosselin et al., 2010). As the third-largest oil reserve in the 43

world, it is estimated that there are 166.3 billion barrels of confirmed oil reserves in 44

Canada’s oil sands regions, accounting for 97% of the total confirmed oil reserves. In 45

northern Alberta, the oil sands region spans 142,200 km2 of land in the Athabasca oil 46

sands region (AOSR), Cold Lake and Peace River oil sands areas (Figure 1). Total oil 47

sands production reached about 2.3 million barrels per day in 2014 (ST53, 2016). 48

1.2 Current oil sands production technologies 49

1.2.1 Bitumen recovery 50

A combination of open pit mining and in situ techniques is used in the extraction 51

of bitumen from oil sands. Currently, only ~20% of the total reserves can be 52

recovered by open pit mining, while ~80% of reserves must be recovered via in situ 53

operations or other techniques (CAPP, 2015). 54

As a surface mining technique of extracting oil sands from the earth, open-pit 55

mining is largely applied in oil sands reserves which are within 75 m below the 56

surface. Oil sands are scooped out of the surface and then crushed using heavy 57

equipment, followed by the injection of hot water to form an oil sands liquid mixture. 58

The liquid mixture is then transported to extraction plants. A large amount of hot 59

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water is needed in the extraction plants in order to separate out the various 60

components in the large separation vessels with a given settling time (Gosselin et al., 61

2010). During the separation process, to maximize the bitumen recovery rates, various 62

additives such as NaOH, Na3C6H5O7 (sodium citrate), and some diluents are used as 63

well (Small et al., 2015). 64

In-situ extraction methods are used to recover bitumen that lies deeper beneath the 65

surface (greater than 75 m underground). There are various in-situ methods of 66

bitumen extraction, including Steam Assisted Gravity Drainage (SAGD), Cyclic 67

Steam Stimulation (CSS), the Vapor Extraction Process (VAPEX), Cold Heavy Oil 68

Production with Sand (CHOPS) and Toe to Heel Air Injection (THAI). SAGD and 69

CSS are the most common methods, while the others are relatively new and in their 70

experimental stages (Jimenez 2008; Greaves et al., 2001). 71

Two horizontal wells with slightly different heights are needed in the SAGD 72

technique. While steam is injected continuously into the top well, the fluidity of 73

bitumen increases in the “steam chamber” and it flows to the lower well (Ali 1997; 74

Butler 1998). There are three stages in the CSS method, including steam injection, 75

soak, and oil production. The process is initiated with a continuous injection of steam 76

into a well. A high temperature of 300︒C is maintained for several weeks to months, 77

whereby the oil sands become less viscous. The hot bitumen flows to the well, and is 78

subsequently pumped out from the well (Pebdani 1986). Unlike the steam applied in 79

the SAGD method, the VAPEX requires hydrocarbon solvents to dilute the bitumen 80

and make it flow (Butler and Mokrys, 1991). Application of CHOPS is very limited in 81

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Alberta’s oil sands developments as it involves pumping out bitumen without any heat. 82

This is not ideal because most of the bitumen contained in Alberta’s oil sands has poor 83

fluidity, with the exception for the oil sands in the Peace River area. 84

1.2.2 Upgrading of bitumen 85

Once the bitumen has been removed from the sand, the next step is to upgrade it 86

into synthetic crude oil. There are four main steps involved in upgrading bitumen into 87

synthetic crude oil (SCO). 88

Thermal conversion or coking uses heat to break down or ‘crack’ the long 89

hydrocarbon molecules in the bitumen (Speight, 2000; Scott and Fedorak, 2004). 90

Further refinement is achieved through a catalytic conversion, which breaks the oil 91

molecules into much smaller and more refineable hydrocarbons. After coking and 92

catalytic conversion, the semi-refined bitumen is distilled, a process which separates 93

the different components in the bitumen. The gas oils, kerosene and naptha, which 94

were separated during the distillation process, are then subjected to a process called 95

hydrotreating (Speight, 2000). This process stabilizes the hydrocarbon by adding 96

hydrogen to the unsaturated molecules and removes impurities such as nitrogen and 97

sulfur (Meyers, 2004). 98

Oil sands development in Alberta is an industry with high consumption of fossil 99

fuels (Ordorica-Garcia et al., 2007), significant land disturbance (Audet et al., 2014; 100

Rooney et al., 2012), and massive generation of solid waste such as stockpiles of 101

petcoke from bitumen upgrading (Scott and Fedorak, 2004; Fedorak and Coy, 2006; 102

Zhang et al., 2016). The higher amount of greenhouse gas emissions and disturbances 103

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on the local air and water quality from the oil sands industry over the conventional 104

crude oil production make the former a focus of debate among scientists and decision 105

makers on whether the crude oil from oil sands is dirty or not (Schindler, 2010). All 106

the existing methods will result in the emission of air pollutants from various 107

operations, including fugitive dust caused by open pit mining, exhaust gas from heavy 108

equipment, volatilization from tailings and flue gas emissions during bitumen 109

upgrading procedures. 110

The objective of this review is to provide a comprehensive understanding of the 111

emission sources of particulate matter (PM), including primary emission and 112

secondary formation, caused by oil sands development. In this review, the possible 113

sources and characteristics of primary PM in oil sands region are summarized. 114

Mechanisms of PM secondary formation are also discussed along with the source 115

apportionment approaches that can be applied in tracking the PM generated from oil 116

sands industry. To more fully understand the aerosol emissions caused by oil sands 117

industry in Alberta, it is important that quantification of secondary organic aerosol 118

(SOA) contribution and the formation mechanisms of the SOA are addressed in future 119

studies. 120

2. Emission sources in Alberta’s oil sands regions 121

2.1 Primary emission 122

Particulate matter can either be directly emitted into the atmosphere from primary 123

sources or formed from the gaseous precursors through atmospheric chemical 124

reactions. The primary emissions of PM vary significantly depending on the 125

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characteristics of human activities and natural conditions. Generally speaking, the 126

main components of primary PM include carbonaceous particles emitted from 127

incomplete combustion of carbonaceous fuels, dust from resuspension of soil dust, 128

and biogenic particles. 129

Canada’s oil sands deposits are located in the northern regions of the Western 130

Canada Sedimentary Basin, which holds most of Canada’s conventional oil and gas 131

reserves in Alberta, Saskatchewan, and British Columbia (Gosselin et al., 2010). 132

Northern Alberta, where the majority of oil sands development is occurring, is located 133

in Canada’s boreal zone. The boreal forest in northern Alberta consists of broad 134

lowland plains and extensive hill systems (Natural Regions Committee, 2006). 135

According to the latest census, about 100,000 people reside and work near the oil 136

sands region in Alberta (Statistics Canada, 2016). The natural characteristics and 137

anthropogenic activities in Alberta’s oil sands regions should be considered carefully 138

when discussing the primary PM emissions. The following section describes the 139

major types of primary sources of PM in oil sands region and the factors, which may 140

influence the PM emission. 141

2.1.1 Re-suspension of surface dust 142

Open-pit mining is feasible in most oil sands reservoirs located in Athabasca oil 143

sands region. In northeastern Alberta, about 715 km2 of land has been disturbed by oil 144

sands mining and upgrading operations (Stringham, 2012). Open-pit mining activities 145

include operations such as topsoil or vegetation cover removal, overburden removal, 146

and oil sands extraction. During the removal operation of muskeg and overburden 147

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above oil sands formations, the destruction of vegetation cover makes the soil dust 148

re-suspended in the near surface atmosphere. The crushing and removal of overburden 149

rocks also contributes to the emission of particles. In the open-pit mining areas, the 150

transportation of oil sands and waste materials requires large numbers of heavy-duty 151

trucks on unpaved roads. The fugitive soil dust raised by these vehicles is an 152

important coarse particulate emission source (Wang et al., 2015a and 2015b). 153

In the AOSR, unpaved roads, parking lots, or bare land with a high abundance of 154

loose clay and silt materials and that experience frequent mechanical disturbances (by 155

traffic or other activities) have the highest dust emissions (Wang et al., 2015a). To 156

characterize the fugitive dust source profiles, Wang et al. (2015b) also collected PM2.5 157

and PM10 (PM with an aerodynamic diameter smaller than 2.5 and 10µm) samples 158

from re-suspended surface dust in the AOSR. It was found that the major components 159

are minerals, organic and elemental carbon, and ions. Individual profiles were 160

grouped into six categories, including paved road dust, unpaved road dust close to and 161

distant from oil sand operations, overburden soil, tailings sands, and forest soils. 162

Elemental carbon, sulfate, lead isotope (206Pb, 208Pb) and several organic compounds 163

typical of combustion emissions and bitumen are enriched relative to forest soils due 164

to fugitive dust sources near oil sands operations. 165

In addition to the re-suspended surface soil dust resulting from the oil sands 166

open-pit mining operations, petcoke dust is another important primary source of 167

atmospheric PM (Scott and Fedorak, 2004). Being a byproduct of bitumen upgrading 168

procedures, petcoke is usually stored as solid waste on-site or integrated into 169

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reclaimed landscapes (ST98 2016). It is estimated that over the lifetime of the oil 170

sands extraction operations, the total volume of coke will be 1 billion m3 (Fedorak 171

and Coy, 2006). One of the main threats associated with petcoke piles is the fugitive 172

dust emission in the form of fine PM (Caruso et al., 2015). Large black stockpiles of 173

petcoke on mine sites are susceptible to wind erosion and the potential re-suspension 174

of dust in the ambient air (Zhang et al., 2016). The chemical characteristics of 175

particles caused by oil sands mining and upgrading operations are consistent with the 176

chemical species of the surface dust (Wang et al., 2015; Jautzy et al., 2015). The 177

unique species or the ratios among species in the surface dust can serve as tracers in 178

tracking the contributions of oil sands mining operations to regional PM 179

concentrations. 180

2.1.2 Fossil fuel combustion-generated PM 181

The combustion of fossil fuels is known to contribute appreciable amounts of fine 182

particles to the atmosphere. Because of the lower value of energy returned on 183

investment (EROI, roughly 25:1 for conventional oil, 5:1 or less for oil sands) in the 184

oil sands industry (Herweyer and Gupta, 2008; Brandt et al., 2013), more fuels, 185

especially fossil fuels, are required to recover and upgrade the heavy, tar-like oil. In 186

Alberta, 33.9% of natural gas were consumed in oil sands production in 2015 and oil 187

sands production industry will continue to be the largest consumer of natural gas in 188

the coming years (ST98 2016). 189

The sources of fossil fuel combustion in the oil sands areas include stationary 190

boilers, furnaces, and stationary and mobile internal combustion engines (heavy-duty 191

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trucks and shovels). The primary PM consists of inorganic or organic species, or a 192

combination of the two. The emissions depend on the composition of the fuels, the 193

combustion conditions, and the effectiveness of the particle removal devices. Wang et 194

al. (2016) reported real-world PM emission factors obtained from the non-road use of 195

heavy-duty trucks (CAT 797B, one of the world’s largest trucks, capable of hauling 196

345Mt of material) and concluded that PM emissions were highly varied among oil 197

sands facilities. 198

Most of the fossil fuel is combusted to produce heat and provide hydrogen to 199

break down the long hydrocarbon molecules that form bitumen (Nimana et al., 2015a; 200

Nimana et al., 2015b). Flue gas originating from in-situ bitumen recovery and 201

upgrading of oil sands is always emitted via stacks, which can be considered as a 202

point source of air pollutants. During oil sands production, fossil fuels are not only 203

combusted to generate hot steam, but also used in the engines of heavy-duty 204

equipment and trucks, as well as to generate power in power plants. Heavy-duty 205

equipment and trucks are commonly powered by diesel engines, while the power 206

plants in Alberta consume a large portion of natural gas and coal. Unlike emissions 207

via stacks in power plants, PM emission from heavy-duty equipment and trucks is 208

always treated as an area source (ECCC, 2017). Particles formed during combustion 209

of fossil fuels can be characterized by the multimodal particle size distribution 210

(usually at the nanometer or micrometer orders, Abdul-Khalek et al., 1999; Shi et al., 211

1999; Lighty et al., 2000; Linak et al., 2000) and containing a great variety of organic 212

compounds (Rogge et al., 1993; Schauer et al., 2002; Lighty et al., 2011). 213

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2.1.3 Wildfires, residential wood combustion, and primary biogenic aerosols 214

Wild fire (biomass open burning) and biogenic aerosols are the two main natural 215

sources of PM in the Alberta’s oil sands regions. Being surrounded by boreal forest, 216

atmospheric PM over Alberta’s oil sands regions is occasionally affected by forest 217

fires (NASA 2016). Residential wood combustion, which alone accounted for 9% of 218

total PM2.5 emission in Canada in 2014, is the primary non-industrial source of fine 219

particles in Alberta (ECCC, 2016b). 220

PM emissions from wild fires can be influenced by certain fuel properties (such as 221

fuel types, spatial distribution of fuels, and moisture content) and combustion physics 222

(meteorological conditions, scale and chracteristics of the fire) (Radke et al., 1991). 223

While CO2 (1564.8 g/kg_fuel) and H2O (459 g/kg_fuel) are the predominant 224

emissions from wildfires, OC (5.2 g/kg_fuel) and fine PM (10.3 g/kg_fuel) are 225

revealed as the main constituents of the particulate emissions (NRC, 2004; Liu et al., 226

2014). Published emission factors of PM varied from laboratory simulation (1.9-82.1 227

g/kg) to field measurement (0.5-42 g/kg), from smouldering stage (34 g/kg) to 228

flaming stage (9 g/kg), from boreal forest (12.7 g/kg) to grassland (5.4 g/kg) 229

(McMeeking et al., 2009; Alves et al., 2011; Nance et al., 1993; Andreae and Merlet 230

2001). The accumulation mode generally dominates biomass smoke mass (Radke et 231

al., 1991). In North American plumes, organic aerosol constituted more than 80% of 232

the total mass in the submicron range (Kondo et al., 2011). Modeling studies revealed 233

that the boreal forest fires are a major source of carbon in the atmosphere (Kasischke 234

et al., 1995), and the emissions from the boreal regions of North America itself 235

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accounted for about 10% of the annual average global emissions during the past 236

decades (van der Werf et al., 2006). Jolleys et al. (2015) conducted several airborne 237

measurements of biomass burning organic aerosol from boreal forest fires in Canada, 238

and provided further insight to the variability associated with biomass burning 239

emissions and the evolution process of biomass burning organic aerosol. The biomass 240

burning organic aerosol (BBOA) production and composition could be significantly 241

influenced by combustion conditions and aging processes. However, there remains 242

considerable uncertainty regarding the drivers of organic aerosol processing and the 243

extent of their possible effects on the aging process of BBOA (Jolleys et al., 2015). 244

Primary biogenic aerosol (PBA) particles are emitted directly from the biosphere 245

to the atmosphere (Després et al., 2007). The PBA consists of many different types of 246

particles, including pollen, spores, bacteria, algae, protozoa, fungi, fragments of 247

leaves, excrement and fragments of insects (Simoneit, 1989). PBA covers an 248

extremely broad range of sizes and is morphologically very diverse (Després et al., 249

2012). On a global scale, the PBA can be as much as 25% of total mass of aerosol 250

particles which implies the underestimation of sources of biogenic aerosol in the past 251

(Jaenicke, 2005). 252

2.1.4 Factors influencing primary emissions 253

Each sector of primary particles emission sources can be influenced by a number 254

of factors, making the estimation of primary PM emission a complex task. Table 1 255

lists the potential components, which may have an influence on the emission rate of 256

primary particles in each sector. For the primary PM emissions from carbonaceous 257

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fuels combustion, the two common influencing factors are chemical composition and 258

combustion condition. In the Alberta’s oil sands regions, a large portion of primary 259

particles is emitted from sources that are susceptible to meteorological conditions. 260

Warm, dry and windy weather may contribute to the re-suspension of surface soil dust, 261

including petcoke dust, and the occurrence of wildfires (McTainsh et al., 2005; 262

Schepanski et al., 2009; Lei and Wang, 2014; Wise 2008; Calder et al., 2015). 263

Regarding the meteorological influence on the concentration of airborne biogenic 264

aerosol particles, it is difficult to obtain a conclusive assessment because of the large 265

variability in biogenic aerosols (Miguel et al., 2006; Huffman et al., 2012; Huffman et 266

al., 2013). 267

Primary PM emissions are estimated using the bottom-up emission inventory 268

approach, which fundamentally depends on the values of emission factors. Even 269

though the emission factors do not influence the PM emissions in the real world, their 270

values do have significant impact on our estimation of PM emissions using models. 271

Therefore, the values of emission factors can be considered as another important 272

factor that could influence our understanding of PM emissions. 273

2.2 Secondary formation 274

Aerosols formed through nucleation of gas-phase species in the atmosphere are 275

another source of atmospheric PM. The secondary aerosol formation is also known as 276

new particle formation (NPF). NPF is responsible for a major fraction of particle 277

number concentration over urban areas and downwind areas of significant volatile 278

organic compounds (VOCs) emission sources (Zhang et al., 2012; Iida et al., 2008). 279

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NPF processes can be summarized as shown in Figure 2. It was estimated that due to 280

the evaporation and atmospheric oxidation of low-volatility organic vapors from 281

mined oil sands material, 45-84 metric tonnes of secondary organic aerosol could be 282

produced per day (Liggio et al., 2016). The findings highlight the importance of 283

secondary formation in determining of the atmospheric PM in Alberta’s oil sands 284

regions, and even in North America. 285

Field measurements have revealed that the atmospheric aerosols over the areas 286

influenced by human activities typically consist of large amounts of secondary 287

constituents, including organic matter, sulfate, nitrate, and ammonium (Guo et al., 288

2014; Huang et al., 2014). The formation of particle-phase organic matter, sulfate, and 289

nitrate is attributed to the emissions of gaseous precursors such as VOCs, SOx, NH3, 290

and NOx, respectively (Guo et al., 2014). In the following section, emissions of SOx, 291

VOCs, NOx and NH3 in the Alberta’s oil sands regions will be described, followed by 292

the identified mechanisms of secondary aerosol formation. Factors which have the 293

potential to affect NPF processes are also summarized at the end of this section. 294

2.2.1 Emissions of gaseous precursors 295

SOx 296

The oxides of sulfur (SOx) are a group of inorganic air pollutants containing 297

sulfur combined with varying amounts of oxygen. The most common SOx pollutant is 298

sulfur dioxide (SO2) that generally arises from the combustion of materials containing 299

sulfur, typically fossil fuels (Groen and Craig, 1994; Mitra-Kirtley et al., 2016; 300

Marriott et al., 2015). Hydrogen sulfide (H2S) present in natural gas or emitted during 301

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oil sands extraction is usually oxidized to SO2 during high-temperature combustion. 302

The statistical summary of the previous 5-year (2011-2015) comparisons for ambient 303

H2S concentration in excess of the AAAQOs showed that since 2013, the exceedance 304

has decreased significantly, but still remains a concern (WBEA 2016). 305

Emissions of SOx during oil sands production can be traced back to the stack 306

emissions from power plants and from stationary steam generating stations where 307

fossil fuels are extensively combusted. In Alberta, oil sands extraction and processing 308

(in-situ and open-pit mining), bitumen and heavy oil upgrading emitted 67670 metric 309

tonnes of SOx, accounting for 12% of total SOx emissions in Alberta in 2014 (ECCC, 310

2016b). 311

NOx and NH3 312

The oxides of nitrogen (NOx) are a group of inorganic air pollutants containing 313

nitrogen combined with varying amounts of oxygen. Of note, with sunlight and VOCs, 314

NOx can contribute to the accumulation of ground level ozone (O3), which has 315

negative effects on public health. Nitrogen dioxide (NO2) and nitric oxide (NO) are 316

the two common NOx pollutants, which arise from high-temperature combustion of 317

fuels, such as the fuel combustion in internal combustion engines. Emissions from 318

trucks and other heavy duty equipment in the operation area, produce elevated 319

concentrations of NOx. Alberta’s oil sands production was estimated to emit 59769 320

metric tonnes of NOx, accounting for 5% of total NOx emission in Alberta in 2014 321

(ECCC, 2016b). 322

Ammonia (NH3) emissions can result from various sources such as aqueous 323

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mixtures of floating agents containing NH3 used for separating and recovering 324

bitumen from oil sands, hydrotreating process (in which N is removed as NH3) and 325

volatilization from tailing ponds which are contaminated with NH3. In Alberta, total 326

ammonia (NH3) released to the air from oil sands production was 1065 metric tonnes 327

in 2014 (ECCC, 2016b). Other sources of NH3 include agricultural activities, 328

biological decay processes, wildfire smoke, and other industry activities such as 329

catalytic converters. 330

VOCs 331

VOCs represent a wide range of organic chemicals, which have sufficient vapor 332

pressure to evaporate into the atmosphere as a gas at ambient temperatures. VOCs 333

include a wide range of individual organic chemicals and chemical mixtures, but 334

common to all VOCs is that they are highly volatile. VOCs can be emitted as volatile 335

fugitive emissions from the handling of volatile organic chemicals such as gasoline, 336

diesel, organic solvents and petroleum sources. 337

Emissions of VOCs from the oil sands industry can be classified into two groups: 338

fugitive emissions from the oil sands and its products and/or the diluent used to lower 339

the viscosity of the extracted bitumen (i.e. C4-C9 alkanes, C5-C6 cycloalkanes, C6-C8 340

aromatics); and emissions associated with the mining effort, such as upgraders (C2-C4 341

alkanes, C2-C4 alkenes, C9 aromatics, short-lived solvents such as C2Cl4 and C2HCl3, 342

and longer-lived species such as HCFC-22 and HCFC-142b) (Simpson et al., 2010). 343

Sources of VOCs fugitive emissions include tailing outfalls, oily films, bitumen slicks, 344

and mature fine tailings. Bitumen extraction techniques, tailing treatment processes, 345

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and tailing properties are the three main aspects linked to VOCs emissions from oil 346

sands industry (Small et al., 2015). VOCs emitted from nearby vegetation cover and 347

wildfire are another two non-negligible sources in specific episodes that have seasonal 348

patterns (Leaitch et al., 1998; Tarvainen et al., 2005; Tunved et al., 2006; Simpson et 349

al., 2011). Field measurements conducted in Whistler, British Columbia in 2010, 350

where the forest characterization is similar to the boreal forest of North Alberta, 351

revealed that biogenic VOC (monoterpenes and isoprene) emissions could be 352

enhanced in summer due to high temperature and solar radiation (Lee et al., 2016). 353

2.2.2 Mechanisms of secondary formation 354

2.2.2.1 Nucleation 355

Nucleation is a process of phase transition resulting in the formation of critical 356

nuclei. The nucleation rate is dominated by the chemical composition of the critical 357

nucleus and the gaseous concentration of the nucleating species (McGraw and Zhang 358

2008). H2SO4 and HNO3 are the two most common nucleating species because of 359

their low vapor pressure at typical atmospheric temperature and humidity. Nucleation 360

of H2SO4 and HNO3 has been studied intensively during the past decades, since they 361

are the two main contributors to global acid deposition, and sulfate, along with nitrate, 362

represents an important component of the nucleation mode aerosols in most areas of 363

the world. 364

Photochemical oxidation of SO2 and NOx in the presence of molecular oxygen 365

and water is the main source of atmospheric gas-phase sulfuric acid (H2SO4) and 366

nitric acid (HNO3). When the concentrations of gaseous H2SO4 and HNO3 approach 367

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the minimum required concentrations under environmental temperature and humidity, 368

phase transition will occur. Formations of critical nucleus can be described using the 369

following reaction equations (John and Spyros, 2006): 370

�� +�� +� → �� +� (1) 371

�� + �� → �� + �� (2) 372

�� + �� +� → �� +� (3) 373

� + �� → �� (4) 374

�� + �� +� → �� +� (5) 375

It is noteworthy that due to the complex composition of ambient air and various 376

meteorological conditions, oxidation of SOx and NOx is not limited to the reactions 377

listed above. A number of studies have revealed several additional pathways, 378

including heterogeneous reactions between SO2 and atmospheric oxidants, i.e., ozone, 379

hydrogen peroxide, organic peroxide, oxygen, OH radical, and nitrogen dioxide; 380

catalytic oxidation by transition metals, and oxidation by Criegee intermediates 381

(Zhang et al., 2015). 382

The nucleation process discussed above is also referred to as homogeneous 383

nucleation. Homogeneous nucleation of atmospheric nanoparticles is always 384

heteromolecular, involving two or more interacting vapor species. Critical nuclei 385

formation occurs when the abundances of nucleating vapors exceed the threshold 386

concentrations, which is required to form liquid/solid-phase from gaseous vapors 387

under specific environmental conditions. It is theoretically estimated that the critical 388

nucleus has a diameter of the order of 1 nm (Zhang et al., 2012). 389

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However, because of the observed inconsistency between laboratory simulation 390

and field measurements, the proposed mechanisms, including the binary nucleation, 391

ternary nucleation, ion-induced nucleation, and the nucleation involving iodine 392

species, cannot provide a consistent explanation of aerosol nucleation under a wide 393

range of environmental conditions (Zhang et al., 2015). 394

2.2.2.2 Particles growth 395

Atmospheric particle growth represents the size growth of both primary PM and 396

secondary critical nucleus. Due to the process of particles’ growth in ambient air, a 397

mixture of primary and secondary PM makes it difficult to physically separate the 398

secondary aerosol from the aging particles. Figure 3 describes the transformation from 399

the gaseous precursor through critical nucleus to aerosol particles with the size up to 400

several micrometers. Small nanoparticles formed during a nucleation grow quickly in 401

the atmosphere. Condensation of low-volatility vapors and reversible portioning of 402

semi-volatile vapors are the major contributors to the growth of aerosols. At this stage, 403

heterogeneous chemical reactions between gas-phase chemical species and the newly 404

formed nanoparticles augment the molecular clusters to aerosol particles with the size 405

varying within five orders of magnitude (tens of nanometers to several micrometers). 406

Based on current knowledge, airborne particle growth processes consist of five 407

aspects: gas-particle partitioning of organic matter, particle-phase reactions of organic 408

matter, sulfate formation, nitrate formation, and aging of primary particles (Zhang et 409

al., 2015). In the following section, these five aspects are summarized into three 410

sectors (i.e., the formation of secondary organic aerosol, the formation of secondary 411

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inorganic aerosol, and aging of primary particles) and are discussed briefly. 412

Formation of secondary organic aerosols 413

The formation of organic matter is an extremely complex process that involves 414

numerous physical-chemical reactions. Due to the large portion of organic matter in 415

airborne aerosols, studies on the formation of organic matter have been a frontier area 416

in atmospheric research. Even though many mechanisms have been revealed, there 417

are a number of aspects remaining poorly understood (Zhang et al., 2015). Recent 418

developments in the study of the sources, formation mechanisms and the physical and 419

chemical transformations of organic particulate matter have been reviewed by 420

Donahue et al. (2009). An unambiguous definition of primary/secondary organic 421

aerosols would assist air-quality managers and climate scientists to more accurately 422

estimate the impact of sources that emit both organic vapors and primary organic 423

aerosols on regional air quality and climate impacts (Donahue et al., 2009). 424

Semi-volatile organic compounds (SVOCs) undergo partitioning between the gas 425

and particle phases. The gas-particle partitioning includes two processes: physical 426

adsorption (Dachs and Eisenreich, 2000) and absorption (Odum et al., 1996). 427

Gas-particle partitioning is controlled by physical properties of both phases and the 428

phase separation, both of which are difficult to quantify. Therefore, mathematical 429

modeling studies based on thermodynamic equilibrium considerations always failed 430

to reproduce the field measurement results. 431

Photo-oxidation of VOCs, such as aromatics and isoprene, lead to significant 432

formation of oxygenated VOCs in the atmosphere (Hildebrandt et al., 2009; Karl et al., 433

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2009; Kourtchev et al., 2005). The acid-catalyzed reactions of organic compounds on 434

acid aerosols have been revealed as another chemical pathway for the transition of 435

gaseous organic compounds into aerosols (Casale et al., 2007). In the presence of NO2, 436

oxidation reactions of VOCs produce peroxynitrates (RO2NO2) and more strongly 437

bound mono- and multifunctional alkylnitrates (RONO2), which are susceptible to 438

being captured by existing aerosol particles (LaFranchi et al., 2009; Wolfe et al., 439

2009). Large multifunctional organic nitrates generated from oxidation of alkanes and 440

alkenes readily form SOA by partitioning to particle phase due to their volatility 441

(Ziemann 2011). 442

NH3 is the most abundant basic gas and the most important neutralization agent 443

for atmospheric PM. Amines have stronger basicity than ammonia and are more likely 444

to participate in acid-base reactions in the condensed phase, because of substitution by 445

one or more organic functional groups (Zhang et al., 2012). Although ammonia and 446

amines are highly volatile, both engage readily in multiphase reactions with organic 447

species, contributing to aerosol nucleation and growth. 448

Formation of secondary inorganic aerosols (sulfate and nitrate) 449

SO2 is also oxidized into sulfate via heterogeneous reactions in the aqueous 450

phase of aerosols. H2SO4 will be neutralized by basic gases, including NH3 and 451

amines if present in ambient air. In addition to neutralization reactions, amines 452

displace ammonium cations in ammonium sulfate salts. Although weaker and more 453

volatile than sulfuric acid, nitric acid can be transformed into nitrate salts via the 454

reactions with ammonia, amine, and dust, in the aerosol phase. Amines also react with 455

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nitric acid and ammonium nitrate to form aminium nitrates by the acid-base and 456

replacement reactions, respectively. NH4+, HSO4

−, SO42−, and NO3

- produced by these 457

reactions constitute the secondary inorganic component in aerosols. 458

Aging of primary PM 459

Primary PM undergoes an aging process due to coating with organic and 460

inorganic constituents. Like the growth of newly formed particles in the atmosphere, 461

primary particles can serve as the particle phase similar to the critical nucleus for the 462

secondary formation of organic matter, sulfate, and nitrate. Aging of primary PM may 463

result in significant changes of mixing states, particle morphology, hygroscopicity, 464

and optical properties. 465

Black carbon (BC) is an important constituent of primary PM because of its 466

considerable portion in the total aerosol mass and its significant light-absorbing 467

properties which is one of the factors dominating the climate impact of aerosols 468

(Bond et al., 2013). Since BC is emitted as a byproduct of incomplete combustion of 469

carbonaceous fuels, the oil and gas industry has become an important source of BC in 470

Alberta as it burns large quantities of fossil fuels every day (ECCC, 2016a). After 471

partitioning of organic and inorganic gaseous species, heterogeneous reactions, and 472

coagulation with other aerosol constituents, fresh BC particles become aged, resulting 473

in significantly altered properties. The enhanced light-absorbing properties of BC due 474

to internal mixing with SOA has been revealed by laboratory simulation and field 475

measurements (Schnaiter et al., 2005; Cappa et al., 2012). 476

Coating of inorganic salts and hygroscopic oxidized organic species on primary 477

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PM during atmospheric aging process considerably improves their cloud-forming 478

capability by increasing the particle hygroscopicity. This interaction between primary 479

PM and secondary aerosols is considered another important indirect impact on global 480

and regional climate change caused by aerosol emissions, in conjunction with the new 481

particle formation process. 482

2.2.3 Factors influencing secondary formation of atmospheric PM 483

As discussed above, the secondary formation of atmospheric PM is a complex 484

process with a number of micro-physicochemical reactions. Nearly all the secondary 485

aerosol formation processes are triggered by oxidation of gas-phase precursors. Thus 486

the oxidizing capacity of the lower atmosphere plays a leading role in secondary 487

aerosol formation. 488

The principle oxidants in the lower atmosphere are O3 and the two by-products 489

of O3 photodissociation, the hydroxyl radical (OH) and hydrogen peroxide (H2O2). 490

Discharges of O3 precursor trace gases (CO, NOx, and hydrocarbons) from 491

anthropogenic activities and natural sources are believed to alter the atmospheric 492

oxidizing capacity (Thompson, 1992). The role of OH in determining the atmospheric 493

oxidizing capacity is vital, but its formation mechanisms remain uncertain, as 494

highlighted by the discrepancy between modelling results and real-world 495

measurements (Hofzumahaus et al., 2009). 496

New particles formation is also controlled by the physical properties of oxidized 497

products, which serve as the critical nucleus. H2SO4 and HNO3 are the two most 498

common nucleating species that have been investigated intensively to date. 499

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Theoretical studies and field measurements also emphasized the importance of 500

physical and meteorological parameters in nucleation events in the continental 501

boundary layer (Boy and Kulmala, 2002). UV-A solar radiation and low concentration 502

of water vapor were found to be the most favorable conditions for the new particles’ 503

formation processes than the precursors of the critical nucleus and other 504

meteorological factors, including solar radiation, ambient temperature, humidity, 505

atmospheric pressure, total cloud amount, and transport of air masses (Charron et al., 506

2007). 507

The role of micrometeorology in aerosol formation was studied by Nilsson et al. 508

(2001a) in a field study. It was found that the fresh nucleation particles were detected 509

within two hours from the onset of strong turbulent kinetic energy, independent of 510

how fast the boundary layer evolved. Effects of air masses and the synoptic weather 511

were also revealed in recent years. According to field measurements conducted in 512

northern Europe, nucleation processes are more likely to occur in maritime air masses 513

during their transition to continental air masses (Sogacheva et al., 2005; Nilsson et al., 514

2001b). 515

3. Estimate of PM emissions and source apportionment 516

3.1 Bottom-up emission inventory 517

Bottom-up emission inventory is a direct way to estimate the primary emissions of 518

atmospheric PM. Emission factors and source signatures are necessary to quantify the 519

primary emissions of PM when using the bottom-up inventory method (Fuzzi et al., 520

2015). Emission factors recommended by the United States Environmental Protection 521

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Agency (US-EPA) are the most widely accepted datasets when appying the bottom-up 522

emission approach (US-EPA, 2017). 523

The bottom-up method is currently applied by Environment and Climate Change 524

Canada (ECCC) to estimate air pollutants emissions. According to the recent air 525

pollutants emission inventory report, oil sands open-pit mining and processing, in-situ 526

extraction and processing, and bitumen and heavy oil upgrading emitted 2962, 5481, 527

and 8268 metric tonnes of PM2.5, PM10, and total particulate matter, respectively in 528

the year of 2014 (ECCC, 2016b). Information on the emissions of aerosol precursors, 529

such as SOx, NOx, and VOCs, are also very valuable for developing the bottom-up 530

emission inventory. However, due to the lack of knowledge on mechanisms of 531

secondary aerosol formation over Alberta’s oil sands regions, it is still a challenge to 532

fully estimate the contributions of possible sources based on this bottom-up emission 533

inventory method. 534

Estimating of the PM and gaseous aerosol precursors emissions require numerous 535

emission factors that are different for various sources. Hence, there exist 536

disagreements over the specific emission factors that must be used for each operation 537

and on their application to cases quite different from the ones in which they were 538

actually obtained. Sources’ coverage is another factor that could lead to uncertainties 539

when the bottom-up emission inventory approach is applied. Disputes over the 540

emission factors and sources coverage result in uncertainties in estimates based on 541

bottom-up emission inventory to some extent. Being one of the dominant industries, 542

the oil sands industry in Alberta is suspected to be responsible for the atmospheric PM 543

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abundance over the oil sands production area and surrounding populated areas due to 544

primary emissions and secondary formation (Timoney and Lee, 2009; Howell et al., 545

2014; Liggio et al., 2016). Since the secondary formation of organic aerosols remain 546

obscure, there has been an underestimation of the impact of the oil sands industry on 547

atmospheric PM emissions (Liggio et al., 2016). 548

3.2 Receptor models: source apportionment techniques 549

In addition to the bottom-up approach, there is another method known as the 550

top-down approach or the receptor modelling that is commonly applied in 551

apportioning the PM sources. Receptor models rely on mathematical approaches 552

and/or a mass balance principle to quantify the contribution of sources to samples 553

collected at the receptor sites. In practice, such models quantify the apportionment 554

based on the tracers or fingerprints of the sources, which are usually characterized by 555

chemical composition or by individual tracers (Norris et al., 2014; Viana et al., 2008a; 556

Zheng et al., 2002; Zhang et al., 2009). Receptor-based methods employing molecular 557

markers that have high source specificity but only a small fraction of the total 558

apportioned mass are classified as “tracer-based” techniques, whereas methods 559

utilizing the properties corresponding to the total mass at the cost of reduced chemical 560

specificity are classified as “ensemble-based” approaches (Fuzzi et al., 2015). 561

There are several models and statistical techniques that are widely applied in 562

apportioning the PM sources worldwide, including CMB model (chemical mass 563

balance, US-EPA, 1987), constrained physical receptor model (COPREM, Wåhlin, 564

2003), principal component analysis (PCA, Thurston and Spengler, 1985), positive 565

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matrix factorization (PMF, Paatero and Tapper, 1994), UNMIX, and multi-linear 566

engine (ME, Paatero, 1999). CMB requires a very detailed knowledge of sources and 567

emission profiles. Thus, CMB is the most commonly used method when the sources 568

profiles are fully understood. On the other hand, PCA and PMF are the most 569

commonly used models when relatively limited quantitative knowledge of sources 570

and emission profiles are available (Viana et al., 2008b). 571

In the Alberta’s oil sands regions, the “ensemble-based” receptor model has been 572

widely applied to track the sources of air emissions. Epiphytic lichens are the 573

widely-applied bio-indicator to find the effects of oil sands development on the 574

surrounding ecosystem (Percy 2012). Isotopic mass balance is an emerging 575

technology in tracing emission sources, which has been widely applied in identifying 576

the influence of oil sands development on the surronding ecosystems. By coupling the 577

lead isotope ratios (207Pb/206Pb and 208Pb/206Pb) in the lichen, it was possible to assess 578

the impacts of air emissions from oil sands mining and processing operations (Graney 579

et al., 2012). Proemse et al. (2012a; 2012b; 2013) found that δ18O values of nitrate 580

and sulfate and ∆17O values of nitrate in stack PM emissions are unique, suggesting 581

that they may constitute suitable tracers for quantifying contributions from oil sands 582

development. Impacts of oil sands mining operations could be tracked by using 583

molecular concentration patterns and ratios of the polynuclear aromatic hydrocarbons 584

(PAHs) (Yunker et al., 2002; Studabaker et al., 2012; Cho et al., 2014; Summers et al., 585

2016; Manzano et al., 2016). Also by using the PAHs in air and snow samples as 586

tracers, influence of petcoke dust emissions on ambient air quality has been revealed 587

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(Zhang et al., 2016; Manzano et al., 2017). Principal components analysis 588

incorporating PAHs concentrations and profiles in lichens and source materials 589

revealed that oil sands mining operations were the primary sources of PAHs at 590

receptor sites (Studabaker et al., 2012). Application of compound-specific isotope 591

analysis (CSIA) technique could significantly improve source discrimination of PAHs 592

in the AOSR (Jautzy et al., 2013 and 2015). The dual (δ2H, δ13C) CSIA approach 593

proposed by Jautzy et al. (2015) has been successfully applied in the source 594

apportionment of PAHs in sediments in the AOSR, suggesting its potential in tracking 595

the oil sands industrial emissions, and thereby quantifying the influence of oil sands 596

development on atmospheric organic aerosols. While the Hg concentration in the 597

lichen, Hypogymnia physodes could not provide any evidence for the significant 598

contribution of oil sands mining and energy production facilities to regional Hg 599

deposition, ∆199Hg and ∆201Hg values could be significantly influenced by energy 600

production activities within 150km of the AOSR (Blum et al., 2012). 601

Field measurements of multi-elements in Athabasca River and its tributaries 602

showed that the bitumen upgraders and local oil sands development could release 13 603

elements (Sb, As, Be, Cd, Cr, Cu, Pb, Hg, Ni, Se, Ag, Tl, and Zn), which are 604

considered as priority pollutants under the US Environmental Protection Agency’s 605

Clean Water Act, in particulate phase (Kelly et al., 2010). Since V, Ni, and Zn are 606

metals known to be emitted in high quantities from the oil sands upgraders, the 607

significant relationship between methylmercury (MeHg) and these metals in 608

snowpack in the AOSR suggests that MeHg could be directly emitted into the 609

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atmosphere from industrial processes. Hence MeHg could be applied to trace the 610

sources of atmospheric PM back to oil sands development (Kirk et al., 2014). 611

Multi-elements analysis of source and lichen samples was performed by Landis et al. 612

(2012) to elucidate the sources and spatial distribution of inorganic air pollution in the 613

AOSR. Source apportionment findings based on four mathematical modelling 614

approaches, including PCA, CMB, PMF and Unmix, showed that the largest impact 615

on inorganic species in H. physodes tissue was related to fugitive dust (Landis et al., 616

2012). Other than the indirect way to track sources of industrial emissions based on 617

bio-indicators in oil sands regions, source apportionment based on atmospheric PM 618

samples could provide more direct results and findings. By using the atmospheric 619

coarse (PM10-2.5) and fine PM (PM2.5) samples, Landis et al. (2017) applied the PMF 620

model to apportion sources of the ambient airborne PM in Fort MacKay. The results 621

showed that 58% of PM2.5 and 83% of PM10-2.5 at the Fort MacKay community site 622

originated from oil sands production operations (Landis et al., 2017). 623

Back-trajectory analysis is a powerful tool in assessing the influences of 624

emission sources located in the upwind directions. Hybrid Single-Particle Lagrangian 625

Integrated Trajectory (HYSPLIT) model developed by NOAA/ARL (Draxler and 626

Hess, 1998) is commonly used when the effect of long-range transport of air masses 627

was significant on the receptor sites (Jaffe et al., 1999). It is noteworthy that the 628

current back-trajectory analysis cannot be used to quantitatively determine the 629

contributions of the sources located in the upwind areas. Therefore, the trajectory 630

analysis is often used in combination with the other top-down approaches, for 631

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example, PCA, PMF, and tracer analysis when diagnosing the cause of a pollution 632

event (Parsons et al., 2013; Sapkota et al., 2005; Jaffe et al., 1999). 633

4. Knowledge/technology gaps and the direction of future studies 634

With the increasing attention on air pollutants emissions, more and more 635

advanced measures and techniques aiming at mitigating these emissions are being 636

implemented (Gosselin et al., 2010). Accurate air emission inventories are 637

fundamental to propose technically defensible and cost-effective regulatory 638

requirements. It is necessary to reconcile the PM emissions by applying standardized 639

methodologies and up-to-date emission factors to get accurate PM emission estimates. 640

Therefore, development of emission factors for specific oil sands operations is 641

necessary before conducting estimations using the bottom-up emission inventory 642

approach. The extent to which the condensable PM emitted from stationary 643

combustion sources contribute to the total mass of ambient PM also remains unknown. 644

Watson et al. (2012) reviewed the contemporary air pollutants’ emission 645

characterization methods and proposed several improvements that could better 646

characterize real-world emissions in Alberta’s oil sands industry. By using the 647

proposed approaches, stack emissions and heavy-duty haulers exhaust emissions were 648

determined (Wang et al., 2012&2015), providing valuable information for future 649

researchers to better estimate the PM emissions from oil sands industrial processes. 650

However, the uncertainties remain very high because of the large variations in 651

emissions among facilities (Wang et al., 2015). As a result, investigations on how to 652

reduce the uncertainty in determining the real-world PM emission factors for the 653

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variable sources are necessary. 654

SOA is becoming a hotspot in aerosol research communities because of the 655

extremely complex formation processes. Mechanisms of gaseous organic precursors 656

transferring to SOA under the specific meteorological conditions are less understood. 657

Research on the molecular processes of SOA formation is recommended, so as to 658

obtain an accurate yield of SOA and reconcile the regional impact of the oil sands 659

industry on atmospheric issues and public health. 660

In addition to the bottom-up emission inventory method, several receptor models 661

such as PMF and CMB are also widely applied in sourcing the atmospheric PM. 662

Instead of atmospheric PM samples bio-indicators (lichen or moss) and snow samples 663

have been widely applied to trace industrial emissions in the Alberta’s oil sands 664

regions (Kelly et al., 2009 and 2010; Kirk et al., 2014; Cho et al., 2014; Manzano et 665

al., 2016; Barrie and Kovalick, 1980). Source profiles, such as stack emission, 666

petcoke, fine tailings, heavy-duty vehicles etc., were also identified with different 667

approaches (Proemse et al., 2012a; Zhang et al., 2016; Wang et al., 2015; Landis et al., 668

2012; Manzano et al., 2017). The identification of source profiles enables the 669

application of PMF and CMB model to elucidate the sources which are associated 670

with oil sands development. Recently, a number of source apportionment studies 671

based on bio-indicators have revealed the influence of oil sands development on the 672

nearby regional environment (e.g. 150km in radius from the diverse sources) (Krupa 673

2012). However, studies focus on the source apportionment of atmospheric PM over 674

the populated areas are rare (Landis et al., 2017). 675

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Atmospheric fine particles can travel from 100s to 1000s of kilometers during 676

their lifetime (days to weeks) (John and Spyros, 2006). Therefore, fine PM emitted or 677

formed from oil sands development is theoretically a potential source of atmospheric 678

PM over broad regions. Taking the long-range transport of atmospheric fine PM into 679

consideration, the environmental impact of oil sands development should be 680

investigated from a much broader perspective. As a potential threat of air quality, 681

quantification of the influence of oil sands development on atmospheric PM over 682

populated urban areas is worthwhile. Deposition of atmospheric PM on snowpack 683

could result in reduction of surface albedo due to the light absorbing impurities in PM 684

(e.g. BC), causing another climate forcing aspect of aerosol particles (Flanner et al., 685

2007 and 2009; Doherty et al., 2014). For example, Kirk et al. (2014) reported areal 686

deposition of particulate organic carbon in snowpack providing insights into the 687

extent of the distribution of fine PM. Most BC measured in the remote Arctic is the 688

result of long-range transport, with source regions located from areas outside of the 689

Arctic (Law and Stohl, 2007; AMAP, 2011). Determining the source regions and/or 690

source types of Arctic BC remains highly uncertain because of the limited and varying 691

ability of approaches (AMAP, 2011). Identifying the role of the Alberta’s oil sands 692

regions and/or oil sands industry in determining the atmospheric PM over Canadian 693

Arctic regions and populated urban areas is another aspect regarding the long-range 694

transport of fine PM emitted from Alberta’s oil sands regions. 695

5. Summary and conclusions 696

Oil sands open-pit mining and processing, in-situ extraction and processing, and 697

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bitumen upgrading are responsible for both significant primary PM emission and 698

secondary aerosol formation. Meteorological conditions are important factors that 699

may cause seasonal variations or accidental change in the primary PM abundance in 700

the atmosphere. The composition of fossil fuels and combustion conditions are the 701

two main factors influencing the emissions and properties of primary PM. Natural 702

sources of PM in the Alberta’s oil sands regions, i.e. primary particles originating 703

from wildfire and biogenic sources, should not be ignored during warm, dry and 704

windy periods. 705

Secondary formation of inorganic and organic aerosols constitute a considerable 706

portion of PM in ambient air over oil sands areas and surrounding populated regions. 707

The important secondary aerosol precursors emitted from the oil sands industry, 708

namely, SOx, NOx, NH3, and VOCs may form aerosol particles via a number of 709

mechanisms. The oxidizing capacity of ambient air could be determined by the NOx 710

and VOCs concentrations and may control the formation of secondary aerosols from 711

gaseous precursors. Even though the regional micrometeorology could also influence 712

secondary aerosol formation, the role of micrometeorology in Alberta’s oil sands 713

regions is rarely discussed. 714

The bottom-up emission inventory is currently applied in sourcing the 715

atmospheric PM over Alberta’s oil sands regions and urban areas (ECCC, 2016c). In 716

addition to this approach, mathematical models based on source profiles also have the 717

potential to interpret the source contributions at receptor sites. Utilization of isotopic 718

analysis identified its potential for applications in the atmospheric PM source 719

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apportionment over areas influenced by oil sands mining and processing operations. 720

Future studies are suggested to focus on the reduction of uncertainties in 721

determining the PM emission factors associated with the oil sands industry, and 722

source apportionment of atmospheric PM over populated areas which are close to the 723

oil sands mining and upgrading facilities (e.g. Fort MacKay and Fort McMurray). 724

Understanding the influence of Alberta’s oil sands development on the PM found in 725

the Canadian Arctic ambient air and snow pack is another aspect regarding the 726

long-range transport of fine PM emitted from Alberta’s oil sands regions. Secondary 727

aerosol formation originating from the oil sands development is also a worthwhile 728

aspect for a more complete understanding of the environmental impact of the oil 729

sands industry. 730

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Acknowledgement 731

The authors would like to thank NSERC Discovery grant for the financial support. We 732

also acknowledge the data sources of air pollutants emission for Wood Buffalo region: 733

the National Pollutant Release Inventory (NPRI). We thank Mr. Neeraj Prakash for his 734

critical comments and proof reading of this paper. 735

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Figure 1. Distribution of oil sands deposits in Alberta. Source: Canadian Center

for Energy Information

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Figure 2. Schematic representation of the formation, growth, and processing of atmospheric PM (Zhang et al., 2012) and the main

sources of gaseous precursors

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Figure 3. A schematic representation of the nucleation process in the atmosphere

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Table 1. Potential factors influencing primary PM emissions

Sectors Re-suspension of

surface dust

Fossil fuel combustion Wildfires and

residential wood

burning

Biogenic

Stationary boiler &

furnaces

Mobile vehicles

(heavy-duty trucks

and automobiles)

Influencing

factors

1. Physical property of

surface soil:

moisture content,

viscosity, density

etc.;

2. Paved/unpaved

roads;

3. Physical property of

oil sands;

4. Wind speed;

5. Operating

experience;

6. Emission control

measures

1. Composition of

the fuels;

2. Combustion

condition;

3. Device

maintenances;

4. Emission control

measures;

1. Composition of

the fuels;

2. Mode of vehicle

operation;

3. Road conditions;

4. Vehicle loading;

5. Operating

experience;

6. Aging of engines;

7. Emission control

measures;

1. Composition of

fuels (types of

fuel, i.e. boreal

forest or

grassland);

2. Distribution of the

fuels;

3. Combustion

stages, i.e. flaming

or smouldering

burning;

4. Meteorological

condition;

5. Climate change

1. Seasonal

fluctuation,

including

fluctuation of

ambient

temperature,

humanity, solar

radiation, vegetation

coverage, etc.;

2. Characteristics of

ecosystem;

3. Meteorological

condition;

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Particulate Matter Emissions over the Oil Sands Regions in ... · Draft 4 / 58 38 1．Introduction 39 1.1 Overview of the oil sands industry in Canada 40 Oil sand is a naturally occurring