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Application of the urban airshed model in the Lower Fraser Valley, British Columbia Suzuki, Natalie M. 1997

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A P P L I C A T I O N O F T H E U R B A N A I R S H E D M O D E L IN T H E L O W E R F R A S E R V A L L E Y , BRITISH C O L U M B I A By Natalie M . Suzuki B. A.Sc. (Chem. Eng.) University of British Columbia, 1983 Dipl. Meteorology University of British Columbia, 1991  A T H E S I S S U B M I T T E D IN P A R T I A L F U L F I L L M E N T O F THE REQUIREMENTS FOR T H E DEGREE OF M A S T E R OF SCIENCE  in T H E FACULTY OF G R A D U A T E STUDIES ATMOSPHERIC SCIENCE  We accept this thesis as conforming to the required standard  T H E UNIVERSITY OF BRITISH C O L U M B I A  August .1997 © Natalie M . Suzuki, 1997  In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives.  It is understood that copying or publication of this thesis for  financial gain shall not be allowed without my written permission.  Atmospheric Science The University of British Columbia 2075 Wesbrook Place Vancouver, Canada V 6 T 1W5  Date:  9?  /v?/zc  Abstract The Lower Fraser Valley ( L F V ) of southwestern British Columbia is periodically subject to unacceptably high concentrations of ground-level ozone (O3). To investigate the factors which influence elevated 0  3  concentrations in the L F V , a three-dimensional  Eulerian model called the Urban Airshed Model was used to simulate an historical O 3 episode which occurred between July 17-19, 1985. The results showed generally satisfactory model performance for predicted O 3 levels across the region, relative to model performance parameters established elsewhere. Peak unpaired accuracies ranged from -2% to -24% and normalized gross error ranged from 35.6-36.9% over the three-day simulation. However, there was a tendency for the model to underestimate O 3 concentrations, as reflected in the normalized bias, which ranged from -29.1 to -31.3%. Spatial patterns of predicted O 3 concentrations indicated that higher O 3 concentrations were observed along the valley walls and tributary valleys than on the valley floor where most of the population resides. Overall model performance based on nitrogen dioxide levels was within established parameters, although concentrations were typically underestimated and performance at two stations was poor. As a further means of assessing model performance, three indicator species (NOy, 0 / N O z and H 2 O 2 / H N O 3 ) were calculated to determine 3  the ozone sensitivity of the modelled airshed. The findings suggest that with the exception of sites located far downwind of the major source region, conditions tended to be VOC-limited.  ii  Table of Contents  List of Tables  vi  List of Figures  viii  Acknowledgments  xiii  1  Introduction  1  1.1  Research Objectives  11  1.2  Methodology  11  1.3  Thesis Outline  11  2 Technical Description of Models 2.1  2.2  13  Urban Airshed Model  13  2.1.1  Governing Equations  13  2.1.2  Modelled Processes  16  2.1.3  Advection  16  2.1.4  Turbulent Diffusion  17  2.1.5  Surface Removal Processes  19  2.1.6  Chemical Processes  19  2.1.7  Emissions  23  CSU-RAMS  24  3 Episode and Domain Selection 3.1  26  Episode Selection  26 iii  3.2 4  3.1.1  Data Availability  27  3.1.2  Characterization of a Typical Episode  29  3.1.3  Characterization of the Selected Episode  30  Domain Selection  39  Model Inputs  41  4.1  Boundary and Initial Conditions  41  4.1.1  BOUNDARY  41  4.1.2  REGIONTOP  43  4.1.3  AIRQUALITY  44  4.1.4  TOPCONC  44  4.2  4.3  Meteorological Data  45  4.2.1  WIND  45  4.2.2  DIFFBREAK  47  4.2.3  TEMPERATUR  52  4.2.4  METSCALARS  52  Emissions Data  53  4.3.1  Mobile Sources  55  4.3.2  Point Sources  56  4.3.3  Gasoline Marketing Sources  58  4.3.4  Area Sources  61  4.3.5  US Sources  63  4.4  Terrain Data  63  4.5  Chemical Parameters  64  4.6  Simulation Control Parameters  64  iv  5  6  M o d e l Results and Discussion  66  5.1  Model Performance Criteria  66  5.2  Ozone  67  5.3  Nitrogen Dioxide  84  5.4  Discussion  99  Summary  107  List of References  109  v  List o f Tables  1.1  U A M Applications  10  2.1  State species in C B M - I V  22  3.1  Location of air quality monitoring sites in the L F V , 1985  27  3.2  Exceedances of ambient 0  38  4.1  U A M input files  4.2  Clean boundary conditions, South Coast Air Quality Management District  3  objectives in the L F V , 17-21 July 1985. . . .  42  ( S C A Q M D , 1990) 4.3  43  Maximum predicted and observed values of Zj at sites in Delta, Surrey and QEP, Vancouver between 17-19 July 1985  52  4.4  Annual emissions estimates for the B C (1985) and Washington (1990) L F V 54  4.5  Episodic adjustments of motor vehicle emissions  56  4.6  Default landuse types and terrain factors (Sheih et al., 1986)  64  5.1  Observed and predicted maximum one-hour O 3 concentrations in ppb and corresponding hour (PST) at monitoring stations in the L F V , 17-19 July 1985  5.2  5.3  79  Model performance based on predicted and observed maximum one-hour O 3 concentrations at stations in the L F V , 17-19 July 1985  82  Model 0  83  3  performance statistics for the L F V , 17-19 July 1985  vi  5.4  Observed (Obs.)and predicted (Pred.) maximum one-hour NO2 concentrations in ppb at monitoring stations in the L F V , 17-19 July 1985, along with the respective time of day (Hr)  5.5  Model performance based on observed and predicted maximum one-hour N0  5.6  96  concentrations at stations in the L F V , 17-19 July 1985  97  Model N 0 performance statistics for the L F V , 17-19 July 1985  98  2  2  vii  List of Figures  1.1  Map of the Lower Fraser Valley showing topography, coastline, major population centres and geographical features  3.1  3  Map of L F V , showing location of air quality and meteorological monitoring sites present in July 1985. Coastline and 100 m contours are shown by solid and dashed lines, respectively. Units are in U T M coordinates (x 10  3  m) 3.2  28  (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 bPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 17 July 1985 at 1200Z (0400 PST). Small rectangle in southeast quarter of each plot identifies modelling domain  3.3  31  (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 18 July 1985 at 1200Z (0400 P S T ) . Small rectangle in southeast quarter of each plot identifies modelling domain  3.4  32  (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 19 July 1985 at 1200Z (0400 PST). Small rectangle in southeast quarter of each plot identifies modelling domain  viii  33  3.5  (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 20 July 1985 at 0000Z (19 July at 1700 PST). Small rectangle in southeast quarter of each plot identifies modelling domain  3.6  34  (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); and (c) 500 hPa geopotential height (m), all for 21 July 1985 at 1200Z (0400 P S T ) . Small rectangle in southeast quarter of each plot identifies modelling domain  3.7  36  Hourly temperature (solid lines) and wind vectors (arrows) at (a) Y V R and (b) Y X X , 16-21 July 1985  3.8  37  Modelling domain, as delineated by thick, solid lines. Coastline and 100 m contrours depicted by thin, solid lines and dotted lines, respectively.  4.1  .  40  Surface (level 1) wind fields prepared for U A M at (a) 0900 P S T and (b) 1500 P S T , 17 July 1985. Vector length is proportional to wind speed. Observations shown by thick arrows. Wind speeds in m/s  4.2  48  Surface (level 1) wind fields prepared for U A M at (a) 0900 P S T and (b) 1500 P S T , 18 July 1985. Vector length is proportional to wind speed. Observations shown by thick arrows. Wind speeds in m/s  4.3  49  Surface (level 1) wind fields prepared for U A M at (a) 0900 P S T and (b) 1500 P S T , 19 July 1985. Vector length is proportional to wind speed. Observations shown by thick arrows. Wind speeds in m/s  4.4  50  Mixed layer depth at sites in Delta (top panel), Surrey (middle panel) and Queen Elizabeth Park (QEP) (lower panel), Vancouver. Lines depict predicted values; circles show observed data  ix  51  4.5  (a) V O C and (b) NOx emissions (in t/d) from mobile sources in the L F V . Washington sources were not included  4.6  57  Annual (a) V O C and (b) NOx emissions (in t/y) from point sources in the L F V . Circles denote point source emissions. Circle diameter is proportional to emissions  4.7  59  V O C emissions (in t/d) from gasoline marketing sources in the L F V . Sources from Washington were not included  4.8  (a) V O C and (b) NOx emissions (in t/d) from area sources in the L F V . Washington sources were not included  5.1  60  Predicted and observed 0  3  62  concentrations at stations T02, T03, T04 and  T05 in the L F V , 17-19 July 1985. Solid lines represent predicted concentrations and hatched lines show the range in neighbouring grid cells. Open circles indicate observations 5.2  68  Predicted and observed 0 concentrations at stations T07, T09 and T14 in 3  the L F V , 17-19 July 1985. Solid lines represent predicted concentrations and hatched lines show the range in neighbouring grid cells. Open circles indicate observations 5.3  69  Predicted and observed 0  3  concentrations at stations T15, T16, T i l and  T12 in the L F V , 17-19 July 1985. Solid lines represent predicted concentrations and hatched lines show the range in neighbouring grid cells. Open circles indicate observations 5.4  Contours of predicted 0  3  70  at 20 ppb intervals on 17 July 1985 at (a) 0900  PST, (b) 1200 PST, (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations. Missing values are indicated by "-99".  x  72  5.5  Contours of predicted O 3 at 20 ppb intervals on 18 July 1985 at (a) 0900 PST, (b) 1200 PST, (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations. Missing values are indicated by "-99". .  5.6  Contours of predicted 0  3  74  at 20 ppb intervals on 19 July 1985 at (a) 0900  PST, (b) 1200 PST, (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations. Missing values are indicated by "-99". . 5.7  76  Comparison of predicted vs. observed O 3 concentrations (above) and comparison of residual (predicted-observed) vs. observed O 3 concentrations (below), all sites 17-19 July 1985  5.8  81  Predicted and observed N 0 concentrations at stations T02, T03, T04 and 2  T05 in the L F V , 17-19 July 1985. Solid lines show predicted values. Open circles indicate observed data 5.9  85  Predicted and observed NO2 concentrations at stations T07, T09 and T14 in the L F V , 17-19 July 1985. Solid lines show predicted values. Open circles indicate observed data  86  5.10 Predicted and observed NO2 concentrations at stations T15, T16, T i l and T12 in the L F V , 17-19 July 1985. Solid lines show predicted values. Open circles indicate observed data  87  5.11 Contours of predicted NO2 at 20 ppb intervals on 17 July 1985 at (a) 0900 P S T , (b) 1200 PST, (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations  88  5.12 Contours of predicted NO2 at 20 ppb intervals on 18 July 1985 at (a) 0900 PST, (b) 1200 PST, (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations  90  xi  5.13 Contours of predicted N 0 at 20 ppb intervals on 19 July 1985 at (a) 2  0900 P S T , (b) 1200 P S T . (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations  92  5.14 (a) Comparison of predicted vs. observed O 3 concentrations, and (b) comparison of residual (predicted-observed) vs. observed O 3 concentrations, all sites 17-19 July 1985  95  5.15 Sensitivity indicators based on predictions at stations T02, T03 and T05. Triangles show values for 18 July, diamonds for 19 July  104  5.16 Sensitivity indicators based on predictions at stations T07, T09 and T14. Triangles show values for 18 July, diamonds for 19 July  105  5.17 Sensitivity indicators based on predictions at stations T15, T i l and T12. Triangles show values for 18 July, diamonds for 19 July  xii  106  Acknowledgments  Throughout this project, I have benefited from the help of many people to whom I am deeply grateful. First and foremost, I would like to thank Dr. Douw Steyn, my supervisor, for being a constant source of ideas and encouragement, and for refusing to give up on me. I would also like to thank my other committee members, Dr. T i m Oke and Dr. Ian McKendry, who provided useful comments on my draft thesis. Special thanks go to Dr. Xiaoming Cai who was responsible for the meteorological fields used in my simulations; Bruce Thomson of Environment Canada who provided support in carrying out this work and who continues to carry the torch in terms of airshed modelling in the Lower Fraser Valley; Dr. Don Singleton (NRC), Dr. Rob McLaren (York University) and Sue Boehme (NRC) for providing assistance in the development of the emissions input files; and A l Percival of the Greater Vancouver Regional District for providing the air quality data. Vincent Kujala and Jim Mintha provided valuable assistance in sorting out my computer woes. Paul Jance was responsible for the one great map in this document. A d ditional thanks go to the staff of the A i r Resources Branch, Ministry of Environment, Lands and Parks, and particularly to Dr. Richard Bennett and Hu Wallis, for their encouragement and understanding. Finally, I would like to thank my family, and in particular, my husband Roy Hourston, for being a constant source of encouragement and the calm in the eye of the storm - I couldn't have done it without you!  xiii  Chapter 1 Introduction  Ozone (O3) is a colourless and reactive gas that is found in trace amounts in the atmosphere. In the troposphere, it is formed during the reaction of nitrogen oxides (NO^) and volatile organic compounds (VOCs) in the presence of sunlight (Haagen-Smit, 1952). It is known to affect enzyme systems in the lungs and to cause a decrease in pulmonary function (Rowe et al., 1983; Bates and Vedal, 1994; Brauer and Brook, 1997), to cause foliar injury to vegetation (e.g. Runeckles and Chevrone, 1992; Lefohn et al., 1997; Treshow and Anderson, 1989; Wright, 1988)), and to cause the rapid degradation of materials such as rubber. The current Maximum Acceptable National A i r Quality Objective (NAAQO) for O 3 is 82 ppb. Between 1984-1992, exceedances of this objective in the Lower Fraser Valley (LFV) of British Columbia (BC) occurred on 8.5% of all days during the months of JulySeptember.  Due to the periodically unacceptable levels of 0  3  in the L F V , the region  was designated as one of three O 3 non-attainment areas under the national N O x / V O C Management Plan ( C C M E , 1990) and required to submit interim targets for emission caps to reduce O 3 concentrations. The South Atlantic Region and the Windsor-Quebec City Corridor were the other two designated non-attainment areas. Relative to the eastern non-attainment zones, the L F V is isolated from other source regions by virtue of local topography.  As shown in Figure 1.1, the L F V is a funnel-  shaped valley, beginning near the town of Hope and spreading westward to the Straight of Georgia, approximately 120 km away. The L F V is enclosed to the north by the Coast  1  Chapter  1.  2  Introduction  Mountains, and to the southeast by the Cascade Mountains. The northern valley walls are punctuated by a series of north-south tributary valleys. The L F V has a current population of roughly 2 million persons which is growing rapidly at a rate of approximately 0.04 million per year ( G V R D , 1994). The major population centre is the City of Vancouver, which lies on the western edge of the L F V . However, much of the current growth is occuring in areas to the east of Vancouver. Associated with the growth in population is an increase in the number of motor vehicles. Recent estimates indicate that motor vehicles in the L F V contribute roughly 80% of pollutants associated with 0  3  formation ( G V R D , 1994).  While the population and its associated activities influence pollutant emissions, the physical environment in which the L F V is situated has a profound influence on local circulation patterns, and, hence, on the transport of pollutants within the valley. Under certain synoptic conditions, temperature differences between the Straight of Georgia and the adjacent land surface give rise to daytime sea breezes and nighttime land breezes in the L F V (Emslie, 1968; Hay and Oke, 1985; CSC,1982; Steyn and Faulkner, 1986; Steyn et al., 1990; Miao, 1993, Cai and Steyn, 1995). The differential heating and cooling between valley walls and valley floor may also give rise to slope and drainage winds (Hay and Oke, 1985; Mass, 1982). The so-called "chimney effect", in which pollutants are vented along heated valley walls, has been shown to contribute to the development of polluted layers aloft (McKendry et al., 1997). The role of tributary valleys in providing a cleansing mechanism has also been observed, in which daytime up-valley flows carrying 0 3 - r i c h air are followed by nocturnal downslope flows characterized by low O 3 concentrations (Banta et al., 1997). Under stagnant conditions, these thermally induced winds may result in the recirculation and buildup of O 3 and its precursors to unsatisfactory levels. Steyn et al. (1990) characterized such an episode which took place between 1-3 September 1988.  On 3  Figure 1.1: Map of the Lower Fraser Valley showing topography, coastline, major population centres and geographical features.  Chapter 1.  Introduction  4  September, a maximum one-hour O 3 concentration of 213 ppb was recorded. This was one of the highest O 3 concentrations ever recorded in Canada. Pacific'93 (Steyn et al., 1997) represented an intensive field study conducted during the summer of 1993 to better understand the chemical and physical factors, at the surface and aloft, which contribute to O 3 episodes in the L F V . Because O 3 is predominantly a secondary product in the troposphere, its control is achieved through the control of its precursors, NOx and VOCs. However, a very nonlinear relationship exists between 0  and its precursors.  3  The fundamental reactions  involved in the photochemical formation of O 3 are as follows (from N R C , 1991):  + hv = NO + OCD)  N0  2  0( P) + 0 3  2  + M  NO + 0  3  (1.1)  =  0 + M ( M = N ,0 )  (1.2)  =  N0  (1.3)  3  2  2  2  + 0  2  Here, the production of NO2 requires the consumption of O 3 . Hence, in the absence of other species to enhance the NO-to-N02 conversion, a photostationary state is assumed, in which the concentration of O 3 can be estimated as [0 ]=ji[NO]/k2[NO]  (1.4)  3  where j i is the photodissociation constant for reaction 1.1 and k is the rate constant for 2  reaction 1.3. In the polluted troposphere, odd-hydrogen species play a key role in enhancing the conversion of N O to N02- These species include: the hydroxyl radical (OH), the hydrogen peroxy radical (HO2) and the organic peroxy radical (RO2). The hydroxyl radical is formed through the photolysis of 0  and the subsequent reaction of 0 ( D ) with waX  3  ter vapour. The peroxy radicals are predominantly formed through the photolysis of  Chapter 1.  Introduction  5  aldehydes and other intermediate VOCs. The reactions are summarized as follows: Oz + hv 0( D)  2  RH + OH i? + 0 R0  2  = 20H  (1.6)  = R + H0  (1.7)  =  (1.8)  2  2  + NO  #0  2  = RO + N0  (1.9)  2  RO + 0  2  = RCHO + H0  (1.10)  = R + CHO  (1.11)  =  #0  (1.12)  =  HONO2  2  RCHO + hv CHO + 0  (1.5)  2  + H0  l  = 0 + OCD),V < 320nm  2  0 # + 7V0 + M 2  2  + CO + M  (1.13)  Major sinks of the odd-hydrogen species include the following: H0  2  R0  2  + H0  2  = H0  + H0  2  = ROOH + O2  (1.15)  2  = HN0  (1.16)  OH + N0  2  +0  2  2  3  (1.14)  The formation of peroxyacetyl nitrate (PAN) is another potential sink, particularly in urban environments. The numerous competing reactions reflect the fact that the relationship between O3 and its precursors is highly nonlinear. Isopleths of constant O3 concentrations plotted for various mixtures of VOCs and N O x (e.g. N R C , 1991) show that reductions in N O x levels at constant V O C concentrations may result in higher or lower O3 levels, depending on whether the environment is V O C - or NOx-limited. To add to the complexity, these conditions will vary both temporally and spatially within a single airshed.  Chapter 1.  Introduction  6  Two fundamentally different approaches can be taken to determine whether N O x or V O C reductions are the most effective means of controlling O 3 levels: (i) an observationbased approach and (ii) an emission-based approach, utilizing photochemical air models. The observation-based approach utilizes atmospheric observations at a given site to determine the sensitivity of real air masses to changes in 0  3  precursors. Applications  range in complexity from comparing these observations to expected values, to using the observations as inputs to a photochemical model. The simplest techniques utilize ambient concentrations of individual species, or the ratio of different species which consistently assume different values depending on whether the conditions are NOx- or VOC-sensitive. These species or ratios of species are referred to as sensitivity indicators. Examples are the VOC-to-NOx ratio, total nitrogen (NOy) concentration, formaldehyde (HCHO) to NOy ratio, 03-to-NOz ratio (where NOz=NOyNOx) and hydrogen peroxide  (H2O2)  to nitric acid (HNO3) ratio. Each is described in  the following. The VOC-to-NOx ratio is an obvious indicator to describe how reductions in V O C and N O x emissions affect 0  3  concentrations. The transition between VOC-sensitive and  NOx-sensitive conditions typically occurs near a VOC-to-NOx ratio of about 8:1 (NRC, 1991). NOx-limited conditions occur at lower values while VOC-limited conditions occur at higher values. In practice, ratios obtained from measurements taken in the early morning (e.g. 0600-0900 LAT) at the urban centre are typically used. Milford et al. (1990) expressed the following concerns with this approach: • The air mass sampled in the urban centre during the morning may not be the one that produces peak O 3 concentrations later in the day and further downwind. • Contributions from precursor sources after the sampling period are ignored. • The reactivity of the V O C mixture is not considered.  Chapter 1.  Introduction  7  • Urban plumes tend to shift from VOC-sensitive to NOx-sensitive as they move downwind because N O x becomes depleted more quickly than VOCs. NOy includes all nitrogen species which can be converted into N O x during photochemical activity: NOx, P A N ,  H N 0  3  nitrous acid (HONO), all organic nitrates and  ,  nitrate radicals. It can therefore be viewed as a NOx reservoir. Unlike NOx, which is relatively short-lived, NOy has a similar lifetime as O 3 . Studies have shown that where afternoon NOy is greater than 20 ppb, conditions are VOC-sensitive (Milford et al., 1989; Rao et al., 1993; Sillman et al., 1993; Milford et al., 1994). A limitation with respect to this indicator is the difficulty in measuring NOy. A reactivity-weighted alternative to the VOC-to-NOx ratio is the ratio of H C H O to NOy. Formaldehyde is readily photolysed, yielding by-products which react to form oddhydrogen species. As such, the HCHO-to-NOy ratio is a much better indicator of 0  3  sensitivity than the VOC-to-NOx ratio. Studies indicate that a transition from V O C - to NOx-sensitive conditions occurs near ratios of 0.28 (Sillman, 1995). The photolysis of 0  3  is another major source of odd-hydrogen species. As the concen-  tration of aldehydes generally increases with O 3 concentration, it may be assumed that the source of odd-hydrogen species is proportional to 0 . 3  products of NOx.  NOz represents the reaction  Hence, the ratio of 0 - t o - N O z may be used to describe the transition 3  from NOx- to VOC-sensitive chemistry. Sillman (1995) reported this transition near a ratio of 7, where values less than 7 represent VOC-sensitive conditions. The ratio of  H 2 0 2 - t o - H N 0  represents the competition between reactions 1.17 and  3  1.18 for odd hydrogen. H0  2  + H0  =  2  = HNO  OH + N0  2  Both  H 2 O 2  and  H N 0  3  H0 2  +0  2  (1.17)  2  (1.18)  z  are major sinks of odd hydrogen. Where  H  2  0  2  dominates, O H  Chapter 1.  Introduction  8  (and therefore 0 ) increases with increasing NOx: 3  HO2 + NO  = OH + NO2  (1.19)  and decreases with increasing VOCs: RH + OH (+0 ) 2  = R0  2  + H0 2  (1.20)  Where H N O 3 dominates, O H (and therefore O3) decreases with increasing NOx. The transition from N O x to VOC-sensitive chemistry occurs near ratios of 0.3-0.5 (Sillman, 1995). While sensitivity indicators can provide guidance on which precursor should be reduced to attain the most efficient reduction in O3 levels, they cannot provide a quantitative estimate of what that change will be, nor can they predict how the changes will vary spatially over an entire airshed. For that, it is necessary to employ a photochemical model which can represent the pertinent physical and chemical processes in the atmosphere which affect ozone concentrations. Photochemical models were first developed in the early 1970's, in response to the passage of the Clear A i r Act Amendments in the United States. These amendments established provisions for uniform national air quality standards and ordered states to develop abatement programs to meet these standards.  Modelling became a necessary  tool to demonstrate attainment. There are three basic types of photochemical model: (i) box models, (ii) trajectory (Lagrangian) models, and (iii) grid-based (Eulerian) models. Seinfeld (1988) provides an overview of each model type. Box models are the most simplistic, as they treat the domain as a single cell. The ground and the inversion height represent the lower and upper boundaries. Emissions are assumed to mix uniformly and instantaneously throughout the domain. A characteristic  Chapter 1.  Introduction  9  wind is specified, and the inversion height is allowed to vary with time, thereby providing a ventilation mechanism for the domain. Lagrangian models follow a single column of air that is advected by the mean horizontal wind. The column is defined by the ground and the inversion height, and may be divided into vertical layers. Emissions are injected into the column as it passes over emission sources. Chemical transformations, removal processes and vertical diffusion can be simulated. In Eulerian models, the domain is divided into a number of grid cells. The governing equations representing atmospheric processes are then solved for each grid cell. Eulerian models typically require more detailed input data and greater computer resources than the other two model types. However, they are the only models that can predict the temporal and spatial variations in pollutant patterns in a three-dimensional domain. Hence, Eulerian models are best-suited for urban air quality studies such as in the L F V where a prognostic capability is required. Major Eulerian photochemical models in use in North America include the following: Urban Airshed Model Version IV (UAM-IV) (Morris and Myers, 1990); U A M - V (Haney et a l , 1990); CIT (McRae et al., 1982; McRae and Seinfeld, 1983); California A i r Resources Board airshed model ( C A L G R I D ) (Yamartino et al., 1992); the Regional Acid Deposition Model ( R A D M ) (Chang et al., 1987); and the Regional Oxidant Model (ROM) (Lamb, 1983). Within the L F V , the use of two different photochemical models has been recently reported. The C A L G R I D model was used in conjunction with the Mesoscale Compressible Community Model (MC2) to evaluate model performance for an 0  3  episode occurring  between 17-21 July 1985 (Hedley and Singleton, 1997; Hedley et al., 1997) and to evaluate the effectiveness of various alternative fuel scenarios (Hedley et al.,1996). Systems Applications International applied the U A M - V to evaluate model performance for the same July 1985 episode (Lolk et al., 1995) and to the evaluate emission control scenarios  Chapter 1.  Introduction  10  Table 1.1: U A M Applications  Location  References  Atlanta Baton Rouge Denver Los Angeles Basin Netherlands New York Santa Barbara/Ventura Co. St. Louis/ Philadelphia Tokyo, Japan  Morris et al. (1990a) Haney et al. (1990) Dennis and Downton (1984) S C A Q M D (1990) Builtjes and Reynolds (1982) Rao et al. (1987) Tesche and McNally (1991) Morris et al. (1990b) Wakamatsu et al., (1990)  for B C Hydro (Haney, 1997). In this research, the U A M - I V will be used. It is the preferred model for O 3 regulatory analysis in the United States, as specified by the U.S. Environmental Protection Agency (U.S. E P A ) . It has been used extensively throughout the United States and in other countries, as shown in Table 1.1. This research was begun in parallel with the C A L G R I D application in the L F V . While it represents a less advanced treatment than the U A M - V or C A L G R I D models, the U A M - I V is an established model which has been well-documented. Although not the purpose of this research, this study provides further reinforcement of the findings obtained in the other modelling applications in the L F V .  Chapter 1.  1.1  Introduction  11  Research Objectives The goal of this research is to apply the U A M - I V to the L F V . Model performance  will be evaluated in terms of the ability of the model to recreate an historical O 3 episode. Established statistical parameters will be applied to assess the results. Sensitivity indicators will also be calculated from model output as a further means of assessing model performance.  1.2  Methodology The first step will be the selection of an historical multi-day ozone episode to be  modelled. This will be followed by model domain selection, which is dependent on the circulation patterns observed or expected during the episode as well as the important sources that are to be included in the study. Episode and domain selection will then define the meteorological, emissions and air quality data required by the model, including the spatial and temporal scales to be used. The model will be run to simulate the historical episode, and predicted O 3 and NO2 concentrations compared against observed values. Model performance will be characterized in terms of the acceptable range of statistical performance indicators established from a review of other modelling studies. Finally, the model results will be compared with established indicators to assess the sensitivity of the modelled airshed to V O C and NOx.  1.3  Thesis Outline In Chapter 2, the theory behind the U A M - I V is presented.  Individual modules  comprising the model are described. In Chapter 3, the characteristics of the selected O 3 episode and a description of the modelling domain are presented. The preparation of model input files to describe the  Chapter 1.  Introduction  12  meteorology, emissions and air quality during the episode is described in Chapter 4. Model results are compared against observational data in Chapter 5. Model performance is characterized based on the ability of the model to predict spatial and temporal variations in O 3 and NO2 concentrations.  Sensitivity indicators calculated based on  model results are also presented. Major findings are summarized in Chapter 6.  Chapter 2  Technical Description of Models  Although the focus of this study is the application of U A M - I V , additional models have been used by others to produce meteorological fields and eission estimates. In the following, a detailed description of the U A M and its modelled processes will be followed by brief descriptions of the mesoscale model, C S U - R A M S , and the models used to estimate source emissions.  2.1  Urban Airshed Model The development of the U A M dates back to 1969 when the National A i r Pollution  Control Administration ( N A P C A ) , a predecessor of the U.S. E P A , contracted with Systems Applications Inc. (SAI) to develop an air quality model which could be used to assess urban O 3 and to evaluate control strategies for abatement programs. A n overview of model development is provided by Scheffe and Morris (1993). 2.1.1  Governing Equations  The U A M simulates the physical and chemical fate of inert or chemically reactive species in the atmosphere through solution of the species continuity equation: S C J  _ _  6t _  6(u-Cj)  5(v • Cj)  5x  5y  + fa<*»S>  +  S(w • Cj)  Sz +  13  S<*TJ>  Chapter 2. Technical Description of Models  +  14  Ri + Si + Lt  (2.21)  where Q is the concentration of species i which has been averaged spatially (x,y,z ) over the volume of a grid cell and temporally (t) over the interval of an integration time step; u , v and w are wind velocities in the x , y and z directions, respectively; KH  and Ky are horizontal and vertical eddy diffusivities;  Ri is net rate of production of species i by chemical reactions; Si is emission rate of species i ; and Li is net rate of removal of species i by dry deposition. By assuming that the chemical species do not alter the meteorology to any significant degree, Equation 2.21 can be solved independently of the coupled Navier-Stokes and energy equations (Reynolds et al., 1974). Due to the presence of nonlinear terms in the equation, a numerical solution is required. To facilitate the use of finite difference methods, the vertical dimension is normalized to an independent variable p: p=  *-H {x,y,t) b  H (x,y,t)-H (x,y,t) t  V  b  '  ;  where H and H are the elevations of the surface and top of the domain, respectively. b  t  Upon transformation of vertical coordinate z to p, and after neglecting cross-derivative diffusion terms which are assumed to be negligibly small, Equation 2.21 becomes A  A  — (AH • Q ) + — (u • AH • Cj) ot ox  A  +  +  A  —(vAH-Ci) dy  RiAH  + SiAH  + —(W-Ci) dp  =  (2.23)  Chapter 2. Technical Description of Models  15  where W  =w  — u(  6H 5x  b  + P  5AH Sx  )-v(  5y  + P  5AH 5y  AH  (2.24)  and  AH = H (x,y,t) t  H (x,y,t) b  (2.25)  As noted by Reynolds et al. (1974), Equation 2.23 is an approximate equation as opposed to the fundamental equation governing the dynamic behaviour of pollutants in the atmosphere. Its application is subject to the following limitations: • the time resolution A i is large compared with the Lagrangian time scale of turbulence; • A i is small compared with the characteristic temporal scales for — gradients in the mean velocity field; — gradients in the mean turbulence velocity correlations; — gradients in the source emission rates; — changes in the rate of production or depletion of a species by chemical reactions. • the average distance that a fluid particle travels in A i is small compared with the characteristic spatial scales for — gradients in the mean velocity field; — gradients in the mean turbulence velocity correlations; — gradients in the source emission rates.  Chapter  2.  Technical Description  of  Models  16  Based on data obtained in the Los Angeles Basin, Reynolds et al. (1974) found that Equation 2.23 was applicable for perturbations in the concentration field with horizontal scales greater than 2 km, vertical scales greater than 20 m, and temporal scales greater than 10 s. 3  Equation 2.23 is solved using the method of time-splitting, or fractional steps, as proposed by Yanenko (1971). During each time step, the equation is solved for 1. advection/diffusion in the x-direction; 2. advection/diffusion in the y-direction; 3. injection of pollutant emissions and advection/diffusion in the z -direction; 4. chemical transformations. The master or advection time step is determined based on grid size and maximum wind speed. To maintain numerical stability, the chemistry and vertical diffusion time steps must be an integral portion of the advection time step.  2.1.2  Modelled Processes  The mechanisms used to describe the transport, removal and chemical transformation of pollutants in the atmosphere are presented in the following.  2.1.3  Advection  The horizontal dispersion of pollutants is primarily through advection. The advective part of Equation 2.23: A  A  - (AH • ) + — (u • AH • a) = 0 Ci  (2.26)  Chapter 2. Technical Description of Models  17  and -(AH-c )  +  i  —(vAH-c )=0  (2.27)  l  is solved using the Smolarkiewicz scheme (1983), which is a positive definite upstream scheme reported to be less diffusive and more computationally efficient than the S H A S T A scheme (Boris and Book, 1973) applied in previous versions of the U A M . A detailed description of this scheme is provided in Morris and Myers (1990).  2.1.4  Turbulent Diffusion  The diffusive part of Equation 2.23: (2.28) is solved using an explicit finite difference method. Turbulent fluxes are parameterized using a closure approximation frequently referred to as either gradient transport theory or K-theory, where it is assumed that turbulent fluxes are proportional to local gradients. The proportionality constant (KH in the horizontal; Ky in the vertical) is known by a variety of names, including eddy viscosity and eddy diffusivity. K  H  and Ky are difficult to measure. Given that in the horizontal, advection generally  dominates over diffusion, a nominal constant value of 50 m - s 2  _1  is given to K . H  Greater  care is given to the treatment of Ky, as diffusion often dominates over advection in the vertical. Ky is calculated as a function of stability class, ground-level wind speed, reference height, surface roughness and height of the grid cell. For stable conditions,  (fc".*)exp(-fetg)  Ky =  (2.29)  1 + 4.7*  for neutral conditions where 0 < z < 0.45%, K  v  = -f(a  + an A + a X + a A ) 2  0  3  3  4  4  (2.30)  Chapter 2. Technical Description of Models  18  for neutral conditions where z > 0.45y, K  = 0.01m /s  (2.31)  2  v  and for unstable conditions: K  v  = w* (3 Zl  + A C +  0  /3 (2C - 1) + 2  2  &(4C 3  3C) + /? (8C - 8c? + 1) 4  4  2  (2.32)  where  C= 2£-l, « .  =  « . - ( i t )  1  /  3  .  /=Coriolis parameter, A;=von Karman constant, u*=friction velocity, Zj^inversion height, i> =geostrophic wind component, 9  L=Monin-Obukhov length, and the coefficients a* and $ are c*o=7.396xlO- #,=0.152 4  ai=6.082 x 10- A =0.080 2  a =2.532 #,=-0.039 2  a =-1.272 x 10 /? =0.032 3  3  a =l-517 x 10 /? =0.020 4  4  For lapse rates less than -0.011°C/m above the mixing layer, Equation 2.30 or Equation 2.31 for neutral conditions is used. Otherwise, if neutral or unstable conditions are present in the lower levels, then Ky aloft is set to 0.01 m . If stable conditions are present 2  in the lower levels, then Ky aloft is calculated using Equation 2.29.  Chapter 2. Technical Description of Models  2.1.5  19  Surface Removal Processes  Dry deposition is the only surface removal process treated in the U A M . It is treated as a three-stage process: 1. transport of pollutants through the atmosphere to just above the surface; 2. transport of pollutants to the actual surface; 3. uptake of the pollutants by vegetation or surface material through absorption, adsorption or chemical reaction. The U A M utilizes a deposition velocity concept, in which the deposition velocity Vd% is inversely proportional to the sum of the resistance to transport R and the resistance to t  surface removal R f s  V  di  =  (2-33)  R is a function of wind velocity at 10m elevation and friction wind velocity, while R is t  si  a function of pollutant and surface types. The deposition velocity is then related to the uptake flux F^ by the following equation: F  di  =V •C di  gi  (2.34)  where C i is the ground level concentration of species i . A more detailed description of g  the parameterization of surface removal processes is given in Killus (1984).  2.1.6  Chemical Processes  Chemical transformations taking place in the atmosphere are described by a chemical kinetic mechanism. This mechanism is comprised of a set of reactions and associated rate constants in the form of coupled ordinary differential equations.  Chapter 2. Technical Description of Models  20  To explicitly model all the pertinent species and reactions taking place in the atmosphere would require a prohibitive number of computations and C P U time. In fact, Peters et al. (1995) report that the integration of chemical rate equations can consume as much as 98% of the total C P U time in Eulerian modelling simulations. Two major approaches have been developed to reduce the number of hydrocarbon species which are included in the chemical mechanism: the lumped molecule approach and the lumped structure approach. The former method organizes hydrocarbons using molecular surrogates. Examples are the S A P R C mechanism (Carter, 1990) which is used in the C A L G R I D photochemical model, and the Stockwell mechanism (Stockwell, 1990) which is used in the Regional Acid Deposition Model (Chang et al., 1987). The latter method disaggregates hydrocarbons on the basis of bond type. As this approach requires fewer chemical reactions, it is computationally more efficient. The Carbon Bond IV Mechanism (CBM-IV) , which is used in the U A M , represents a lumped structure approach (Whitten et al., 1980; Gery et al., 1988, 1989). Four types of species are considered in the C B M - I V : • inorganic species which are treated explicitly: ozone, N O x and H O x chemistry; • organic species which are treated explicitly: — formaldehyde, because it is formed in all oxidation reactions involving hydrocarbons and is very reactive; — ethene, because it constitutes a large fraction of hydrocarbon emissions, is unusually unreactive for an alkene, and yields a high percentage of formaldehyde under most conditions; — isoprene, because it constitutes a large fraction of biogenic hydrocarbon emissions and is very reactive.  Chapter 2. Technical Description of Models  21  • organic species which are represented by carbon (C) bond surrogates: — paraffins: single C bonds; — olefins: C-C double bonds; — aldehydes: C - C H O bond and also 2-alkenes which tend to react very quickly to produce aldehyde products. • organic species which are represented by molecular surrogates: — toluene: seven-C species used as surrogates for monoalkylbenzene structures; — xylene: eight-C species used as surrogates for dialkyl- and trialkylbenzenes. The C B M - I V represents a condensed version of the C B M - E X which is described in Gery et al. (1988). C B M - E X is a more detailed mechanism that contains over 120 reactions. A number of steps were carried out to condense this mechanism: • eliminate unimportant reactions and products, • create a universal peroxy radical, thereby eliminating many organic peroxy radicals, • apply mathematical and algebraic manipulations to limit the number of reactions, and • lump secondary reaction products, especially relating to isoprene chemistry. The condensed version contains 33 state species, as shown in Table 2.1. More than 80 reactions are included in the mechanism. Due to the wide range of rate constants involved, the differential equations describing the mechanism are referred to as a "stiff" system. To facilitate computations, quasi-steady state assumptions are used for the low-mass, fast-reacting (i.e. stiff) species. The Crank-Nicholson algorithm is applied to solution of the other state species.  Chapter 2. Technical Description of Models  Table 2.1: State species in C B M - I V  Species Name  nitric oxide nitrogen dioxide nitrogen trioxide dinitrogen pentoxide nitrous acid nitric acid peroxynitric acid oxygen atom (singlet) oxygen atom (triplet) hydroxyl radical water ozone hydroperoxy radical hydrogen peroxide carbon monoxide formaldehyde high-molecular-weight aldehydes peroxyacyl radical peroxyacyl nitrate paraffin carbon bond secondary organic oxy radical olefinic carbon bond ethene toluene cresol and higher-molecular-weight phenols toluene-hydroxyl radical adduct methylphenoxy radical high-molecular-weight aromatic oxidation ring fragment xylene methylglyoxal isoprene N O - t o - N 0 operator NO-to-nitrate operator 2  Representation  NO N02 N03 N205 HONO HN03 PNA OlD 0 OH H20 03 H02 H202 CO FORM ALD2 C203 PAN PAR ROR OLE ETH TOL CRES T02 CRO OPEN XYL MGLY ISOP X02 X02N  Chapter 2. Technical Description of Models  23  Dodge (1989, 1990) reviewed three chemical mechanisms used in photochemical models:  C B M - I V , the Carter-Atkinson-Lurmann-Lloyd (CAL) mechanism (Carter et al.,  1986; Lurmann et al., 1987) which is part of the S A P R C family of models, and a mechanism developed by Stockwell (1988) for use in R A D M (Chang et a l , 1987). Both the S A P R C and Stockwell mechanisms use a lumped molecule approach, although the latter utilizes a generalized organic species to represent similar organics. In general, Dodge found good agreement between the three mechanisms, and points out that this should be expected, since the developers relied on the same kinetic data evaluation sources during mechanism development. The major differences involve predictions under high levels of N O and aromatics, and at low temperatures. Of particular note, the C B M - I V x  consistently predicted lower concentrations of ozone at low temperatures. Jefferies and Tonnesen (1994) compared results obtained using the SAPRC90 (Carter, 1990) and C B M - I V chemical mechanisms in a Lagrangian box model. Both mechanisms gave similar predictions of total reactivity and O 3 maxima. However, at low N O x levels, the SAPRC90 mechanism was more reactive and produced higher O 3 maxima, while the C B M - I V mechanism produced more nitrate and became NOx-limited earlier in the day.  2.1.7  Emissions  Emissions within an airshed originate from a wide range of sources, including point, area, mobile and biogenic sources. Methodologies used by others to develop emission estimates in the L F V are discussed in Chapter 4. For the purposes of simulating these emissions within an Eulerian model such as the U A M , emissions data must be processed so that (i) spatial and temporal distributions reflect the simulation period, (ii) emissions are injected into the appropriate vertical grid cell, and (iii) organic species are attributed to the appropriate surrogate group. The Emissions Preprocessor System Version 1.0 (EPS1.0) was developed to prepare  Chapter 2. Technical Description of Models  24  emission inventories that are compatible with the format required by the U A M (Causley, 1990). The spatial and temporal allocation of emissions and the chemical speciation are achieved by associating spatial, temporal and source codes with the appropriate distribution factors. Emissions injected into a grid cell are mixed instantaneously throughout the cell. Ground-level emissions are input to the lowest level of grid cells. Elevated emissions are injected to the appropriate vertical cell corresponding to the total effective plume rise A h , which is calculated by an emissions preprocessor using the algorithms recommended p  by Briggs (1971) and summarized in Morris and Myers (1990).  2.2  CSU-RAMS The lack of an extensive wind monitoring network, the complexity of the terrain in  the L F V , and the importance of mesoscale flows such as land/sea breezes and mountain/valley winds necessitated the use of a prognostic non-hydrostatic model. For these reasons, the Colorado State University Regional Atmospheric Modelling System (CSUR A M S ) , hereafter referred to as R A M S , was chosen to generate the three-dimensional wind fields which are required by the U A M . R A M S is a second-generation model to the C S U Mesoscale Model (CSUMM) developed by Pielke (1974). It is very flexible, representing a merging of three different atmospheric models: a non-hydrostatic cloud model and two hydrostatic mesoscale models (McNider and Pielke, 1981; Tremback et al., 1986; Tripoli and Cotton, 1982). It is based upon the full set of primitive dynamical equations, and includes optional parameterizations for such processes as turbulent diffusion, terrestrial radiation, and moist processes (Walko and Tremback, 1991). Solution of these equations is through finite difference methods. To improve the efficiency of numerical solutions, the Arakawa-C grid  Chapter 2. Technical Description of Models  25  stagger is employed. R A M S has been applied in a number of studies in the L F V . Steyn and McKendry (1988) used a primitive version of R A M S to simulate meteorological fields in the L F V for 23 August 1985. Miao and Steyn (1994) simulated conditions on the same day using RAMS2a. Steyn and Cai (1994) applied RAMS2a to an 0 occurring between 17-20 July 3  1985. Cai and Steyn (1995) repeated this simulation using the next-generation mode, RAMS3a.  Chapter 3  Episode and Domain Selection  Model performance is evaluated on the basis of its ability to replicate observed 0  3  concentrations during a particular historical episode. Domain selection is dependent on defining the area of interest and then adjusting for the meteorological conditions during the episode which may affect airflow into and out of the region. Hence, both episode and domain selection must precede the preparation of model inputs, as they help define the air quality, emissions and meteorological databases to be used. In the following, the criteria and rationale for episode and domain selection are presented.  3.1  Episode Selection An 0  3  episode which occurred between 17-20 July 1985 was selected for further  study. Episode selection was based on the following criteria (after Seinfeld, 1988): • The episode exhibited elevated O3 concentrations. • The episode was a multi-day event. • The episode was characteristic of typical O3 episodes in the region. • Satisfactory databases of aerometric, emissions and meteorological data were available to characterize the modelling domain during the episode. A more detailed description of the episode and of the available data is provided in the following. 26  Chapter 3. Episode and Domain Selection  27  Table 3.1: Location of air quality monitoring sites in the L F V , 1985.  3.1.1  Station ID  Location  T01 T02 T03 T04 T05 T06 T07 T08 T09 T10 Til T12 T13 T14 T15 T16  Downtown Vancouver Kitsilano, Vancouver Marpole Kensington Park, Burnaby Confederation Park, Burnaby Second Narrows Anmore Lions Gate S T P Rocky Point Park, Pt. Moody Eagle Ridge Abbotsford Airport Chilliwack Airport North Delta Burnaby Mountain Surrey East Pitt Meadows  UTME (x 10 m)  UTMN (x 10 m)  491.3 488.2 492.1 502.1 499.9 598.5 510.2 490.3 511.1 512.9 545.5 576.8 507.3 506.8 522.4 521.7  5458.7 5456.6 5450.4 5458.4 5459.0 5460.8 5461.9 5462.9 5458.4 5459.0 5430.4 5444.6 5445.0 5458.3 5442.2 5450.9  3  3  Data Availability  The G V R D and the B.C. Ministry of Environment, Lands and Parks ( M E L P ) operate a relatively dense network of air quality monitors in the L F V . In July 1985, O 3 data were monitored at 16 sites as shown in Figure 3.1 and Table 3.1. The highest density of stations was found along Burrard Inlet, in the vicinity of major oil refineries. The spatial resolution of O 3 data in the central valley was and still is comparatively poor, although sites in Abbotsford, Chilliwack and, more recently, Hope provide valuable information on the eastern extent of O 3 episodes.  Chapter 3. Episode and Domain Selection  28  1  1  \  7  f  CO  6  o o O  \  •  \  >  \  >  } \  460  •  > >  1  1  1 1  +  airports  •  echo sounder  A  tethersonde  •  •  •  •  •  \  \A  s  \  1  >  r  +  .  1  vi  / A  5 Iz>  1  air quality s t a t i o n s  O  < r? / n  / fs  >  480  500  s  >  '/  —  \  s  /  M  520  \ 540  560  580  600  UTM Coordinates (x 10*3)  Figure 3.1: Map of L F V , showing location of air quality and meteorological monitoring sites present in July 1985. Coastline and 100 m contours are shown by solid and dashed lines, respectively. Units are in U T M coordinates (x 10 m) 3  Temperature, humidity, cloud cover and wind data are regularly collected at the Vancouver International Airport ( Y V R ) , which is located along the coast, and Abbotsford International Airport ( Y X X ) , which is located in the central valley. Additional wind and temperature data are collected at some of the G V R D and M E L P monitoring stations, as listed in Cai and Steyn (1995). Augmenting the regularly available air quality and meteorological data are the following datasets obtained during or for 1985: • an emissions inventory prepared for base year 1985 ( G V R D , 1988); • tethersonde data from Queen Elizabeth Park (QEP) in Vancouver for 17 and 19 July 1985, obtained as part of a study into the development of the mixed layer in  Chapter 3. Episode and Domain Selection  29  the Lower Mainland (Steyn and Wallis, 1986); • back-trajectory analyses from three sites in the region for 17, 19 and 20 July 1985 (Coligado, 1988). Such information is important for both model input preparation and model performance evaluation.  3.1.2  Characterization of a Typical Episode  Between May and September, the most prevalent synoptic regimes for surface O 3 events in southwestern British Columbia are persistent or slow-moving anticyclones which are eastward extensions of the North Pacific High (CSC, 1985). Anticyclones are generally associated with light winds and large-scale subsidence resulting in the adiabatic warming of the subsiding air, clear skies, and the formation of temperature inversions aloft. The lack of synoptic forcing allows for the development of local thermally induced flow patterns such as sea breeze/land breeze circulations and mountain/valley circulations, which may result in the recirculation and accumulation of pollutants in the airshed (Steyn and Faulkner, 1986). In a study of the climatology of O 3 episodes in the L F V , McKendry (1994) characterized the various synoptic patterns related to ozone episodes at station T09 in Port Moody. He found that of the days in which O 3 concentration exceeded 82 ppb at T09, 47% were associated with the presence of a low-level thermal trough and a 500 hPa upper level-ridge of high pressure, in agreement with the general findings of Taylor (1991). The remaining episode days were characterized by either an upper-level low off the British Columbia coast combined with a weak surface pressure gradient (44% of episode days) or a persistent southerly flow at 500 hPa and weak flow at the surface (6% of episode days). McKendry also found that episode days are associated with a reduction in the  Chapter 3. Episode and Domain Selection  30  strength of the sea breeze, suggesting that the thermal trough acts to suppress sea breeze development.  3.1.3  Characterization of the Selected Episode  Synoptic Meteorological Profile  Daily surface pressure fields, temperature fields at 850 hPa, and geopotential height fields at 850 hPa and 500 hPa between 17-21 July 1985 are shown in Figures 3.2-3.6. A persistent feature throughout the episode was the broad surface high extending northward over the Pacific Ocean, off the west coasts of British Columbia and Washington. Superimposed on this were two additional features which McKendry (1994) identified as characteristic of ozone episodes in the region: a low-level thermal trough and an upperlevel ridge. The thermal trough was aligned over the coast of southwestern B C on 18 and 19 July. Associated with this trough was warm air advection from the southeast, as evident in the 850 hPa temperature plots which showed temperatures over the region increase from about 16°C on 18 July to 20°C the next day. During this period, the upper-level ridge at 500 hPa migrated slowly eastward. Geopotential heights over southwestern B C increased from 5800 m to greater than 5820 m. Surface O 3 concentrations measured in the L F V indicated elevated 0  3  levels (i.e. >82 ppb) at several sites between 18-20 July.  By 21 July, the O 3 episode was over. The surface trough had migrated inland and 850 hPa temperatures had dropped to approximately 18°C. Upper-level geopotential heights remained above 5820 m, but flow patterns changed from meridional to nearly zonal.  Chapter 3. Episode and Domain Selection  (a)  31  (b)  Figure 3.2: (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 17 July 1985 at 1200Z (0400 PST). Small rectangle in southeast quarter of each plot identifies modelling domain.  Chapter 3. Episode and Domain Selection  (a)  32  (b)  Figure 3.3: (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 18 July 1985 at 1200Z, (0400 PST). Small rectangle in southeast quarter of each plot identifies modelling domain.  Chapter 3. Episode and Domain Selection  (a)  33  (b)  Figure 3.4: (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 19 July 1985 at 1200Z (0400 PST). Small rectangle in southeast quarter of each plot identifies modelling domain.  Chapter 3. Episode and Domain Selection  (a)  34  (b)  (d) /  '  x  ^  |  / 0  Figure 3.5: (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); (c) 850 hPa geopotential height (m); and (d) 500 hPa geopotential height (m), all for 20 July 1985 at 0000Z (19 July at 1700 PST). Small rectangle in southeast quarter of each plot identifies modelling domain.  Chapter 3. Episode and Domain Selection  35  Mesoscale Meteorological Profile The episode was characterized by high temperatures, clear skies, light onshore breezes during the daytime and extended periods of calm or offshore winds at night, as indicated by measurements at Y V R and Y X X which are shown in Figures 3.7(a) and (b), respectively. Maximum surface temperatures during the episode peaked at 27.4°C at Y V R and 33.2°C on 19 July, and remained high on the 20th. Daytime winds at Y V R and Y X X on 18 and 19 July were predominantly westerly. On 20 July, the day in which the highest 0  3  concentrations were observed, a southerly component was evident at both sites. Of note, these patterns were also observed during an extreme 0  3  episode occurring in September  1988 (Steyn et al., 1990). While several hours of calm were observed at Y X X on the morning of 21 July, strong easterlies were observed at Y V R . While still warm, daytime temperatures on 21 July were significantly lower than observed on the preceding days. Acoustic sounder measurements at sites in Delta and Surrey indicated that with the exception of 17 July, elevated daytime thermal structures were strong and consistent throughout the episode (Steyn and Wallis, 1986). Maximum mixed layer depths (MLDs) at the Delta site decreased from about 620 m on 17 July to 590 m on 19 July. A t the Surrey site, maximum M L D s decreased from approximately 840 m on 17 July to 650 m on 18 and 19 July. For comparison purposes, the maximum M L D observed at the Surrey site during the September 1988 episode was 470 m (Steyn et al., 1990).  Tethersonde  measurements from Queen Elizabeth Park, Vancouver indicated that maximum M L D s decreased from approximately 530 m on 17 July to 320 m on 19 July.  Air Quality Profile A number of stations in the L F V reported exceedances of the one-hour Maximum Acceptable Level for 0  3  (82 ppb) between 18-20 July 1985, and four of the stations  Chapter 3. Episode and Domain Selection  36  Figure 3.6: (a) Sea level pressure (hPa); (b) 850 hPa temperature (°C); and (c) 500 hPa geopotential height (m), all for 21 July 1985 at 1200Z (0400 P S T ) . Small rectangle in southeast quarter of each plot identifies modelling domain.  July 1985  Figure 3.7: Hourly temperature (solid lines) and wind vectors (arrows) at (a) Y V R and (b) Y X X , 16-21 July 1985.  CO  Chapter 3. Episode and Domain Selection  38  Table 3.2: Exceedances of ambient O 3 objectives in the L F V , 17-21 July 1985.  Date  July July July July July  Number of Stations Exceeding:  17 18 19 20 21  Maximum Desirable (51 ppb)  Maximum Acceptable (82 ppb)  Maximum Tolerable (153 ppb)  Ozone Maxima (ppb)  6/11 9/12 7/12 12/12 7/12  0/11 3/12 4/12 6/12 0/12  0/11 0/12 0/12 0/12 0/12  69 104 107 110 80  reported exceedances on consecutive days. A summary of the number of exceedances is presented in Table 3.2. The highest recorded concentrations during the episode were 107 ppb at station T12 in Chilliwack on July 19 and 110 ppb at station T15 in Surrey on July 20. The lowest O 3 concentrations and the highest NO2 concentrations were observed at sites located slightly upwind or within the urban core (stations T02, T03, T04 and T05). Conversely, the highest O 3 concentrations and the lowest NO2 concentrations were found at sites downwind of the urban plume (T15, T16, T i l and T12). Elevated O 3 levels were also found at T07 and T09, which are located at the eastern end of Burrard Inlet and in close proximity to oil refineries which were operating at the time. High nighttime O 3 concentrations at T14, located on Burnaby Mountain, reflect the buildup of 0  3  aloft and  the lack of available N O x sources near this elevated site. No exceedances of the one-hour Maximum Acceptable Level for N 0 (210 ppb) were 2  observed during the episode. However, elevated concentrations were observed at stations  Chapter 3. Episode and Domain Selection  39  T04 and T05 in Burnaby. The highest concentrations recorded during the episode were 100 ppb at T05 on 18 July and 86 ppb at T05 on 19 July.  3.2  Domain Selection The selected modelling domain is as shown in Figure 3.8. The dimensions of the  domain were 140 km by 110 km, with the origin located at U T M coordinates 460000 E and 5390000 N . For a grid cell size of 5 km by 5 km, this translated to a domain of 28 by 22 cells. Domain selection was based on the following criteria (after Seinfeld, 1988): 1. domain boundaries should contain all important current and future emission sources; 2. necessary air quality, emissions and meteorological data should be available for the domain; and 3. local circulation cells should be well-contained within the domain boundaries. As described in the previous section, air quality, emissions and meteorological data were available for the British Columbia side of the L F V . However, similarly detailed data were not available for the Washington State side. Clearly, both the British Columbia and Washington sides of the L F V had to be included in the modelling simulation in order to capture the major sources and recirculating wind patterns transporting pollutants in the valley. A back-trajectory study by Coligado (1988) for 17, 19 and 20 July 1985 indicated that air parcels originating from the Washington State side of the L F V produced maximum one-hour O 3 concentrations that were as high or higher than air parcels originating in the G V R D . Preliminary trajectory studies performed by Miao (1993) for a sea breeze day (23 August 1985) indicated that sea breeze circulation and upslope/downslope winds were important pollutant transport mechanisms in the L F V . A larger domain is also preferable from the point of view of minimizing boundary effects on the main area  Chapter 3. Episode and Domain Selection  40  Figure 3.8: Modelling domain, as delineated by thick, solid lines. Coastline and 100 m contrours depicted by thin, solid lines and dotted lines, respectively. of interest. However, this is tempered by the added computational requirements and the availability of observational data to help characterize the expanded domain. The selected domain size encompasses most of the L F V , with the exception of the town of Hope, B C to the east, and areas to the south of Bellingham, Washington. It is very similar to the typical domain size of 140 km x 120 km (4 km by 4 km grid cells) that was found by Tesche (1991) in reviewing 67 papers and reports on U A M studies.  Chapter 4  Model Inputs  U A M simulations require a total of 13 input files, as listed in Table 4.1. These files are used to define boundary and initial conditions, meteorological fields, emissions, terrain, chemical parameters and simulation control parameters. Further details regarding the preparation of these files are provided in the following.  4.1  Boundary and Initial Conditions The preparation of files describing model boundaries, associated boundary conditions  and initial conditions are described in this section. 4.1.1  BOUNDARY  The B O U N D A R Y files specifies (i) time-invariant lateral boundaries, and (ii) average hourly pollutant concentrations in each boundary cell.  Dimensions of the modelling  domain were 140 by 110 km, beginning at 460000 U T M E and 5390000 U T M N , as discussed in Section 3.2. Due to a lack of monitoring data near the domain boundaries, clean boundary conditions were based on those used by the South Coast A i r Management District for the Los Angeles Basin ( S C A Q M D , 1990). These values are listed in Table 4.2. Reactive organic gas (ROG) and carbon monoxide (CO) concentrations of 10.3 ppbv and 200 ppbv, respectively, compare well with total non-methane hydrocarbon and C O concentrations of 9.4 ppbv and 161 ppbv measured during low-level (0.1 km) flights off the west coast of Vancouver Island in April 1985 (Greenberg et al., 1990). This suggests 41  Chapter 4. Model Inputs  42  Table 4.1: U A M input files  Input File  Description  BOUNDARY  specifies the lateral domain boundaries and the concentrations of each species along each boundary.  REGIONTOP  specifies the height of the top of the domain; this height may vary in time and space.  AIRQUALITY  specifies the concentrations of each species in each grid at the start of the simulation.  TOPCONC  specifies the hourly concentrations of each species for each grid cell along the top of the domain.  TERRAIN  specifies the roughness and deposition factors for each grid cell along the bottom of the domain.  DIFFBREAK  specifies the hourly mixed layer depth (or diffusion break) during the daytime and the hourly inversion height at night.  WIND  specifies the hourly u and v wind components for each grid cell, the hourly maximum wind speed, and the hourly average wind speed along each boundary.  TEMPERATUR  specifies the hourly gridded temperature field.  METSCALARS  specifies the hourly values of meteorological parameters that do not vary spatially. This includes the N O 2 photolysis rate constant, the concentration of H 0 vapour, the temperature gradients above and below the diffusion break, atmospheric pressure and exposure class. 2  EMISSIONS  specifies hourly gridded emissions from low-level species.  PTSOURCE  specifies hourly emissions from elevated sources which are injected into the appropriate grid cells. This file includes stack parameters.  CHEMPARAM  specifies the species to be simulated, reaction rate constants, upper and lower bounds, activation energies, reference temperature, and resistances to surface sinks.  SIMCONTROL  specifies the period of simulation, model options, and information on the integration time steps.  Chapter 4. Model Inputs  43  Table 4.2: Clean boundary conditions, South Coast A i r Quality Management District ( S C A Q M D , 1990).  Species  NO N02 03 OLE PAR TOL XYL FORM ALD2 ETH MEOH ETOH ISOP total R O G CO  Concentrations (ppm)  0.00025 0.0005 0.04 0.00055 0.00622 0.0000914 0.00004 0.0005 0.0005 0.00011 0.0001 0.0001 0.0001 0.0103 0.2  that the S C A Q M D boundary conditions at least provide the correct order of magnitude for the L F V application.  4.1.2  REGIONTOP  The R E G I O N T O P file specifies the top of the modelling domain. General practice is to set it to a constant level approximately 50 to 200 m above the maximum mixed layer depth (Morris and Myers, 1990). In the present application, it was set to to coincide with a height of 1372 m in the R A M S sigma coordinate system. The following conversion was  Chapter 4. Model Inputs  44  used to obtain terrain-parallel coordinates: (H -z ) ztop = „ ti V  where z  t o p  s  1  • 1372m  . . (4.35)  is the height of the top of the modelling domain, H is the top of the R A M S  domain (19 km) and z is the surface elevation The height of 1372 m was obtained through s  consideration of the number and heights of the vertical layers used in R A M S which would provide adequate resolution of the mesoscale flows important in pollutant transport in the L F V . 4.1.3  AIRQUALITY  Initial conditions are provided in the A I R Q U A L I T Y file.  The initial concentra-  tions are based on observations made at the simulation start time. To obtain a threedimensional concentration field, station values were first interpolated horizontally using an inverse distance weighting factor. Chemical species were assumed to be well-mixed below the inversion height, and were scaled back to the concentrations at the top of the modelling domain which were specified by the R E G I O N T O P file. Where initial concentrations were not available for certain species, clean air conditions as used in the B O U N D A R Y file (Table 4.2) were applied.  4.1.4  TOPCONC  Boundary conditions aloft are defined in the T O P C O N C file. In the absence of monitoring data at this elevation, clean boundary conditions as shown in Table 4.2 were used.  Chapter 4. Model Inputs  4.2  45  Meteorological Data Meteorological output to describe wind fields, mixing heights and surface tempera-  tures were generated in a mesoscale modelling study using the R A M S 2 a model (Steyn and Cai, 1994). Treatment of the data within the current research was limited to conversion of the data to a format compatible with the U A M .  4.2.1  WIND  The W I N D file contains gridded, hourly-averaged values of horizontal wind components u and v, hourly maximum wind speeds, and hourly averaged wind speeds for each boundary. The values of u and v were obtained by adjusting R A M S output to the format and grid coordinates required for the wind preprocessor U A M W N D . A feature of U A M - I V is that cell heights vary with the height of the mixed layer depth. In contrast, the vertical structure of R A M S is fixed. Vertical interpolation of R A M S output to a structure compatible with U A M input requirements can mask such important local-scale features as sea breezes and land breezes. For the purpose of this application, cell heights in the W I N D preprocessor were fixed to levels coinciding with cell heights in the lower eight layers of the R A M S model. Cell interfaces were set at the following heights above ground level: 100 m, 215 m, 347 m, 499 m, 674 m, 875 m, 1106 m and 1372 m. Cell heights were adjusted from sigma coordinates to terrain-following coordinates as described in Section 4.1.2. Horizontal wind fields also required adjustments.  The wind vectors u and v are  calculated at the centre of each grid cell in the U A M , while they are calculated along perpendicular grid faces in R A M S , as summarized in Steyn and Cai (1994). The R A M S wind fields were for a grid size of 2.5 km by 2.5 km and a domain origin of 453750  Chapter 4. Model Inputs  46  U T M E and 5385750 U T M N . To convert to the U A M domain, a six-point inversedistance-weighted interpolation scheme was applied to RAMS-generated values of u and v. Interpolations near domain boundaries were based on four- or three-point schemes, depending on the availability of neighbouring grid cells. The wind fields were subject to further adjustments in U A M W N D . Vertical velocity w is calculated based on three-dimensional divergence minimization. A stability adjustment is then applied to ensure zero vertical velocities at the top of the domain. Horizontal velocities u and v are then adjusted until the calculated divergence is within acceptable parameters. U A M W N D produces hourly, gridded horizontal wind speeds (in km/h) for each layer, in addition to hourly maximum wind speeds and average wind speeds along the boundaries. Wind fields produced by U A M W N D at 0900-1000 P S T and 1500-1600 P S T for each day of the episode are shown in Figure 4.1-4.3. Vector length is proportional to wind speed.  Observed winds at Vancouver International Airport ( Y V R ) , the University of  British Columbia ( U B C - located on the northwest 'tip of the City of Vancouver) and Abbotsford International Airport ( Y X X ) are indicated by thicker arrows. Aside from the morning of 17 July, when initialization effects are still evident, morning wind patterns were characterized by strong northwesterly winds channelling down the Straight of Georgia. The simulated wind fields captured the start of the onshore sea breeze, which typically began about 1000 PST. However, it is evident that the modelled wind fields had a much stronger southerly component than the winds observed at Y V R and U B C . B y late afternoon, the onshore wind pattern had been firmly established, while wind speeds over the Straight of Georgia had slackened considerably. Another characteristic of the afternoon wind fields is the strong southerly winds over such north-south channels as Indian Arm, Pitt River/Pitt Lake, Stave River/Stave Lake and Harrison River/Harrison Lake. These channels lie to the north of the major emissions  Chapter 4. Model Inputs  47  area, and as such these flow patterns have large implications on pollutant transport to these wilderness/recreational areas. 4.2.2  DIFFBREAK  The D I F F B R E A K file specifies hourly, gridded heights of the daytime mixed layer and the nocturnal inversion base (hereafter referred to as z^). The D I F F B R E A K preprocessor calculates Zj using an algorithm developed by Kelly (1981) in which Zj is defined as the level at which the potential temperature exceeds that based on screen-level temperature measurements. To maintain dynamical consistency with other meteorological parameters, potential temperature estimates from the R A M S model were used. Modelled results and observed data for sites in Delta, Surrey, and Queen Elizabeth Park (QEP), Vancouver are shown in Figure 4.4. Predicted and observed daily maxima are presented in Table 4.3. Predicted values represent hourly averages. Data obtained from Q E P are based on an evaluation of tethersonde soundings. Data from the Delta and Surrey sites are from acoustic sounder measurements.  No observations from Q E P and Delta were  available for 18 July. Figure 4.4 indicates that aside from the first day of the simulation, when model start-up effects may have dominated, predicted values generally agreed with observed data in terms of the magnitude and timing of the daily maxima. However, there was a tendency to underestimate z;. At the Surrey site, the simulated development of the mixed layer was somewhat delayed compared to observed data, although the magnitude of the daily maximum z; agreed well. At Q E P on 19 July, the morning development of z, was well-characterized, but the second maxima during the mid-afternoon was not captured.  Chapter  4. Model  Inputs  48  (a) 1  1  * \  /  <• . «  \  t * i  1 .  1 t  < t  \  1 r-i— « . x  ,  » t \ *  < \ \  <: j."V: /. .; . . .  fl\  .'•'>-•.•':':• • •  |<::' :  .  - \  \  .  . \  \  .  .  1 .  ,  / I 1  :  \  • I I I  , . "  , •  ,r  i t /.•-'•' S -- •  -i.x,  X.X^X.x^xix. x, x. x x - -* • X X. X. X. ^ ~X X X, >'<"".: ^ x x x x x x . ^ x X N X X x  k  -.y.X \*  I  1  \  v  \  xix  x x x_ V x x x.-x X X x x ^ /x X X X x x x\X X X X X x *-  X X X \  \ "x X \  'V  \  \  * * \ 1  '•• I''  '  ^- - •  1  460  J  1  500  t  i  x  i i  1 _ 520  5<0  UTM E 110**3 M l  0.M1IT01 UAXSIDH *KCTO*  (b) "T"  >. . -  .  \  \  * \  — / I  s  "T"  / t / y\ 1 I  .  ^ ^ ^ r  s I  \ I I.  /  /  y \ \  /  y /  1  /  ,  I  s ^ t \  ,  ^ ,  ,  /  ,  z.UJr*';. '': i - - '('~.K ' — ' t' '  ' ' '  :  S\\.,  i f-  ± ~ s y'\A\k .-1. " >•  S.  — / .7: '  y Ji :  j/  I  s  ^  y — y f  /  ^  t t t t 1I • I 1 I  r \ i-  ^ ^ - ^ ^ ' W . — - i -./-~ J s .—. — / ' ~ . t x.-x.-^^a-xOx." x. C x-x. - — - *r -  x.-x.x.x_ x; x x x x  -  —  . —'  * -  I  I  .!.••  r r /: </ si :  :  - xix.?- —  S.X.X.XV..X x x x x x x x - - -  -  -  X X. X. N X X. x -  k  X x x x x x,  > > ^ ^ ^  A•  \—  - * - - - <••' >  »  »  \ i  i  — •  500  520  540  UTM E (10**3 Ml  Figure 4.1: Surface (level 1) wind fields prepared for U A M at (a) 0900 P S T and (b) 1500 PST, 17 July 1985. Vector length is proportional to wind speed. Observations shown by thick arrows. Wind speeds in m/s.  Chapter 4. Model Inputs  49  (a) 1  • - \  \  M  \  t  -\ . ; - 1 M - (•• <r' • y>i 4 .» 1 r' / / '  \  i  /  /  \  \  t  1  <  i  v.  /  ?  '. -  i  t  •  •  '  i-.t  t  .••  •»  . , v  r  /  N  t  '  / :  / .  *  * s  "  C>  t  ;  t \  \'\  * - *  "  %  1  %  ' /  4 \  \  \ * /  \  ' • /  x  ' t  r i . t r  t'~-y  ^  -. I  \  *,  <  >-?.  i  .  .  .  .  s  I  \  i  *  ,  yv \"  , - -  • -—-  .  . 't  •  •  :  \  \  .  - .  •  \ V\ V V  t  \  •  - — •*  528  1  1 •  S/l  ' ' ' / / / .  "  \ \  /  - - ;  -  » \  /  * * y  • \ ' ! - v < • - ... < - .  - \  1  4  '  v  •  - •  >  M  J  /  / i \ \  .  ;  • -V \ \ " - - -1. •/  . \  u  1  /If;)/ , / \ jlj i Jr } t iAh/./ /Ji;/  r'/  .  1  /  1  /  '  '  t  .  '. i  '/  •  '  • \  -  v  1 V •  /••'/  . v ~ • •  ** ^  - -*  \  1  ,1 *  i  54B  UTM E 110**3 Ml  (b) . \  .  / / .  I I ,  _ ^  -  ^ /  ^ _ / \  *  -;i'V ^ _ / % -  ,  ^  ^ ^ ^ >.'  .. ^..^// _ _ ^ ^ . —  —  —i.  520 •  /  I  \  1  / /^-,^/? r  _ ^ _- ^j; :  / / / ^ ^• _.  „ r  /  s  ^  _ ^ - ^ I i , 1  T/  ' /..-''''/  540  UTM E (10**3 MI  0 6*6B O tI lanwuw VECTOR  Figure 4.2: Surface (level 1) wind fields prepared for U A M at (a) 0900 P S T and (b) 1500 PST, 18 July 1985. Vector length is proportional to wind speed. Observations shown by thick arrows. Wind speeds in m/s.  Chapter 4. Model Inputs  50  (a)  520 540 UTM E (10**3 HI  (b) "T"  -~ — ^ _ / / _ ^ , _ _ _  - \  /  /  \  t  t  ,  /  s\  \  i  /  s  *  t  /  .  /  /  ^ , \  \  s ^ ,  .  . .  ;'/:  s  x ^- —../f;/  s  u .'.'•'AX.i— ~4, _  s\  ^*  A  ;^z^*^'-*>-  \ I  /  V ^ s t j \ j  ^  _4 -  t  / r  . . . \ \ \ -  ^ — / 1 /  -^>*^ ^  ^  ^  s  f  /  /  /  /  /  /  ^  • ^  - ^ r — '  .  .. . . \ . .. , \ \ < -  .  . ; \ \ \: . _ , 1 1 /" .  - - t I f ./,•'  -  ..  ././;///•  .  . ^ ^ v. ^ x x N  %  \  %  ^ V;  "  --•  <-'^  ^  ••>  N  Y\ \ ^  \  V  ^ ^ ^. ^.  —  —<  *—'-r — — — ^  %  .  \ ' ' 520  540  560  UTM E <10»*3 M)  T 0.P5EHI VECTOR  Figure 4.3: Surface (level 1) wind fields prepared for U A M at (a) 0900 P S T and (b) 1500 PST, 19 July 1985. Vector length is proportional to wind speed. Observations shown by thick arrows. Wind speeds in m/s.  Chapter 4. Model Inputs  800  1  .  '  .  1  r-  QEP _  o  -  200  .  1  -  -p-600 ^400  1  —.  1000  51  CD 0 0  <BP  <?  -  Q  n  OO  -  1  0 0  12 17 July  ,  — 24  i  —  i  — 36  18 July  i  1  — 48  60  I  0  72  19 July  Figure 4.4: Mixed layer depth at sites in Delta (top panel), Surrey (middle panel) and Queen Elizabeth Park (QEP) (lower panel), Vancouver. Lines depict predicted values; circles show observed data.  Chapter 4. Model  Inputs  52  Table 4.3: Maximum predicted and observed values of z* at sites in Delta, Surrey and QEP, Vancouver between 17-19 July 1985.  Location Delta Surrey QEP  4.2.3  17 July Obs. Pred. 619 844 527  389 365 301  18 July Obs. Pred.  651 -  518 605 322  19 July Obs. Pred. 522 651 317  587 634 274  TEMPERATUR  Hourly gridded surface temperatures are required to simulate temperature-dependent chemistry. Together with mixing heights (Section 4.2.2) and atmospheric lapse rates (Section 4.2.4), the temperature data are used to generate a three-dimensional temperature field. For this application, temperature data were obtained from R A M S output rather than an interpolation of surface-based measurements due to the limited number of observations available. Temperature data were horizontally adjusted using a six-point smoothing scheme to convert to the U A M coordinate system.  4.2.4  METSCALARS  The M E T S C A L A R S file contains data for six meteorological parameters which are assumed to be spatially invariant: • NO2 photolysis rate: This parameter was calculated as a function of the day of the year and location using the preprocessor program S U N F U N C . • exposure class: This parameter represents a measure of the near-surface stability due to heating or cooling. It was treated as a function of solar zenith angle, which  Chapter 4. Model  Inputs  53  was obtained from the S U N F U N C output, and total observed cloud cover. Cloud cover estimates were based on airport observations at Y V R and Y X X . Averaged over the two sites, hourly cloud cover was less than 5/10th on 17 July. Clear skies were reported 18-19 July. • surface pressure: Atmospheric, pressure is used in the conversion of emissions from molar units to concentration units by volume. The default value of 1 atm (101.3 kPa) was used. • atmospheric lapse rates below and above the diffusion break: Hourly lapse rates below the diffusion break were based on hourly averaged lapse rates calculated from R A M S output. Similar treatment for the lapse rate above the diffusion break resulted in unrealistic estimates. Instead, lapse rates derived from tethersonde measurements at a site in Langley during Pacific'93 for similar meteorological conditions were used (Pryor, personal communication). • water vapour concentration: Concentrations are required for chemical reactions which contain water as a reactant. Values were calculated from relative humidity and surface temperature measurements obtained at Y V R and Y X X .  4.3  Emissions Data The EMISSIONS and P T S O U R C E files contain hourly speciated emissions from  merged low-level and elevated sources, respectively. These files were prepared by passing emissions data through the emissions preprocessing system EPS1.0 (Causley, 1990). B C emissions data were based on the G V R D emissions inventory for base year 1985 ( G V R D , 1988). Included in the inventory were emission estimates for the following criteria pollutants: VOCs, NOx, C O , sulphur oxides (SOx) and total particulate (TSP).  Chapter 4. Model Inputs  54  Table 4.4: Annual emissions estimates for the B C (1985) and Washington (1990) L F V  Sector  SOx tonnes/year  NOx tonnes/year  TSP tonnes/year  CO tonnes/year  VOC tonnes/year  B.C.: mobile area point gas total  3217 1026 8842 0 13085  46632 3058 8722 0 58412  116335 3831 21844 0 142010  394525 5212 12908 0 412645  55619 33796 7729 7194 104338  Wash.: mobile area point total  303 388 9244 9935  4742 1189 4592 10523  3600 3232 1906 8738  35048 16915 45163 97126  4795 22113 7246 34154  23020  68935  150748  509771  138492  56.8 43.2  84.7 15.3  94.2 5.8  80.9 19.1  75.4 24.6  TOTAL % B.C. % Wash.  A similar inventory of emissions from U.S. sources in the L F V was not available for base year 1985. For comparison purposes, 1985 estimates from B C sources and 1990 emission estimates from U.S. sources (B.H. Levelton, 1993) are provided in Table 4.4. Using improved methodologies, refinements were subsequently made to the 1985 inventory which resulted in changes to emission estimates ( G V R D , 1994). Total N O x emissions from all sources decreased by 1.7%. Total V O C and C O emissions increased by 5.9% and 16.4%, respectively. Masked within these overall changes were substantial changes within certain sectors.  Most notably, N O x emissions from point sources  Chapter 4. Model Inputs  55  decreased by 23.5% and V O C emissions from area sources increased by 34.1%. As the final emission estimates were not available at the time that the input files were being prepared for the simulation, the revised estimates were not used in this study. However, as noted in the following, some refinements were incorporated in an effort to provide better temporal and spatial characterization. 4.3.1  Mobile Sources The mobile emissions inventory was comprised of emissions from vehicular, aircraft  and airport, rail and marine sources. Motor vehicles were the dominant source, contributing 92.2% of total mobile emissions ( G V R D , 1988). Hence, particular attention was paid to the preparation of motor vehicle emissions for application in the U A M . Motor vehicle emissions were based on speed classes and vehicle kilometres travelled (VkmT) estimates from the G V R D ' s regional transportation model Emme/2, and emission factors calculated using M O B I L E 3 , a computerized system developed by the U.S. E P A . M O B I L E 3 calculations were performed using a base temperature of 10°C. Temperature is known to have a strong effect on evaporative emissions from mobile sources. Based on M O B I L E 4 emission factors, Cardelino and Chameides (1990) estimated that for an increase in ambient temperatures from 22°C to 29°C, mobile emissions in the Atlanta study area would increase 47%. M O B I L E 3 did not contain an algorithm responsive to changes in ambient temperature, nor did it consider area-specific gas volatilities or evaporative running losses, the latter of which may contribute an additional 20% to V O C emissions (Pierson et al., 1990). To adjust the emission factors to represent episodic temperatures, correction factors were obtained using output from Mobile 4.1c (McLaren, personal communication), the Canadian version of MOBILE4.1 which represented the most recent advancements in the M O B I L E series of emission models at the time. A summary of the resultant emissions is given in Table 4.5 and Figure 4.5. Deviations  Chapter 4. Model Inputs  56  Table 4.5: Episodic adjustments of motor vehicle emissions  Scenario  Ambient Temperature  Base 17 July 1985 18 July 1985 19 July 1985  (°C)  NOx Emissions (tonnes/day)  V O C Emissions (tonnes/day)  10.0 23.1 22.5 27.6  158.2 161.5 161.9 155.5  189.9 181.2 179.9 191.3  from the base case emissions were surprisingly small. The N R C attribute this finding to the loose preparation techniques employed for the M O B I L E 3 simulations, and also to the fact that episodic temperatures were not exceptionally high (i.e. not above 30°C) (McLaren, personal communication).  4.3.2  Point Sources  Point sources refer to facilities under management permit and generally include all major industrial operations. For the current modelling application, emissions from a total of 341 B C point sources ( G V R D , 1988) and four of the largest U.S. point sources in the L F V (Franzmann, personal communication) were included. A more detailed treatment of U.S. emissions was not available at the time model inputs were being prepared. Annual V O C and N O x emissions are shown in Figure 4.6(a) and (b), respectively. Clearly, the largest V O C sources were located along the eastern end of Burrard Inlet and to the north of Bellingham. Petroleum refineries were associated with the majority of these emissions. In contrast, the largest N O x sources were located along the Fraser River in Delta and Richmond (cement plants). The B C Hydro Burrard Thermal Generating  Chapter 4.  Model  Inputs  57  Figure 4.5: (a) V O C and (b) N O x emissions (in t/d) from mobile sources in the L F V . Washington sources were not included.  Chapter 4. Model Inputs  58  Plant, which is one of the largest stationary N O x sources in the L F V when operating at full capacity, was not operating in 1985. Stack parameters were required to classify each source as low-level or elevated. Stack parameters were available for twenty of the largest facilities in the Lower Mainland and for the U.S. sources. The following default values were used for the remaining sources: stack height 3.0 m, stack diameter 0.2 m, stack velocity 4.0 m/s and stack temperature 294.0 K (Causley, 1990). Elevated sources were defined as those sources where emissions occurred above the elevated plume height cutoff of 50 m. The remaining sources were treated as low-level sources. Emissions data from the elevated sources were passed through the P T S O U R C E preprocessor, where plume rise calculations were made to determine the vertical cell into which emissions would be injected. Emissions from low-level sources were passed through the EMISSIONS preprocessor. Temporal adjustments to the emissions were limited to seasonal and day-of-the-week adjustments. Episodic adjustments were not attempted due to the large effort required to check operating records of the individual facilities and the amount of time elapsed since the 1985 episode. 4.3.3  Gasoline Marketing Sources  Gasoline marketing sources were primarily comprised of bulk storage facilities, loading facilities, and service stations. Those refinery sources already covered under the point source category were not included. Contributions from this sector were small, accounting for only 7% of total V O C emissions. Service stations were responsible for almost 47% of this amount, while truck loading and bulk users accounted for approximately 19% and 15%, respectively (B.H. Levelton, 1989). The spatial variations in annual V O C emissions are represented in Figure 4.7. Emissions from gasoline marketing sources are affected by ambient temperature, and  Chapter 4. Model Inputs  59  (a)  460  480  500  520  540  560  580  600  460  480  500  520  540  560  580  600  UTM Coordinates (x 10*3)  Figure 4.6: Annual (a) V O C and (b) N O x emissions (in t/y) from point sources in the L F V . Circles denote point source emissions. Circle diameter is proportional to emissions.  Chapter 4.  Model  460  Inputs  480  60  500  520  540  560  580  600  UTM Coordinates (x 10*3)  Figure 4.7: V O C emissions (in t/d) from gasoline marketing sources in the L F V . Sources from Washington were not included. in the case of external floating tanks, by wind speed. Equations based on those used in the original calculations (B.H. Levelton, 1989) were applied to estimate month-specific and day-specific correction factors for emissions from truck loading facilities, bulk storage tanks and service station vehicle refueling. Losses from underground storage tanks at service stations were not considered. These emissions are dependent on initial fuel temperature, which in turn is strongly dependent on earth temperature as well as time between fuel drops, tank thermal time constant and initial and added fuel volume (Nichols and Hardcastle, 1983). Given the complexity of these calculations and the fact that soil temperatures are not expected to greatly vary below depths of 0.75 m (Oke, 1978), particularly over a three-day period, episodic corrections were not attempted. Hourly emissions from truck loading facilities were estimated, and found to vary by as  Chapter 4. Model Inputs  61  much as 30% over the course of a day. However, given the fact that V O C emissions from gas marketing sources are dominated by emissions from mobile, area and point sources, and that no episodic corrections were made for point sources, further adjustments to the emissions were not merited. 4.3.4  Area Sources Area sources comprised all sources not covered in the above-mentioned categories.  This inventory included emissions from natural sources, combustion operations, solid waste incineration and general evaporative losses. The general methodology used to estimate the base case emissions consisted of using surrogate quantities with emission factors which were independent of temperature or season. Space heating emissions were adjusted to reflect variations with heat load, and particulate emissions were adjusted to reflect variations with wind speed. However, for biogenic emissions and evaporative solvent losses, which respectively comprised 60% and 30% of area source V O C emissions, no such adjustments were provided. In addition, reference temperatures were not reported for the given emission factors. Hence, episodic adjustments of the biogenic and evaporative emissions were not possible based on the available data. To address the seasonality and diurnal nature of biogenic emissions, emission factors generated using PC-BEIS and recommended by Lamb were applied to existing land use factors. These factors were used in the final biogenic emission estimates for the 1990 emissions inventory (B.H. Levelton and Western Research, 1993), which was not available in its final form at the time at which these inputs were being prepared for the simulation. Total area emissions in the L F V are summarized in Figure 4.8.  Chapter 4.  Model  Inputs  62  Figure 4.8: (a) V O C and (b) NOx emissions (in t/d) from area sources in the L F V . Washington sources were not included.  Chapter 4. Model Inputs  4.3.5  63  US Sources  As seen in Table 4.4, emissions in the L F V are dominated by emissions from B C sources. U.S. sources account for approximately 15% of total N O x emissions and 25% of total V O C emissions in the L F V . As noted previously, detailed emissions from the Washington inventory were not available at the time model inputs were being prepared. However, emissions from the following point sources were included: the Intalco aluminum smelter, Georgia Pacific, and the B P O i l and A R C O oil refineries. In 1987, these four industrial complexes contributed approximately 7900 tonnes of VOCs and 4500 tonnes of NOx. Compared to total point source estimates in the 1990 inventory, this would account for more than 100% of V O C and NOx emissions. A rough estimate of biogenic emissions from U.S. sources was also included in the simulation. This was done by applying emission factors developed by Lamb (B.H. Levelton and Western Research, 1993) to land use types derived by Miao (1993) for the U.S. domain.  4.4  Terrain Data The T E R R A I N file describes the characteristics of the underlying surface. It specifies  (i) gridded roughness lengths, and (ii) gridded deposition factors for the domain. Both roughness lengths and deposition factors are based on studies by the Argonne National Laboratory (Sheih et al., 1986) for specific landuse types. Landuse types found in the L F V were based on those used by Miao (1993), who relied on local landuse maps and observations. Landuse types found in the L F V are listed in Table 4.6 along with the corresponding terrain factors.  Chapter 4. Model Inputs  64  Table 4.6: Default landuse types and terrain factors (Sheih et al., 1986).  4.5  Landuse Type  Surface Roughness (m)  Deposition Factor  Urban Agricultural Coniferous forest including wetlands Mixed forest Water Non-forest wetlands Mixed agricultural and range  3.00 0.25  0.2 0.5  1.00 1.00 0.0001 0.15  0.3 0.3 0.03 0.3  0.10  0.5  Chemical Parameters The C H E M P A R A M S file contains a list of the chemical species, reaction proper-  ties, and stoichiometric coefficients for the reactions found in C B M - I V . Although not reproduced here, a detailed description may be found in Morris and Myers (1990).  4.6  Simulation Control Parameters The S I M C O N T R O L file contains simulation control data which specifies • simulation start and end times and dates; • simulation options such as flags for restart, surface removal, and availability of point source, temperature and terrain data; • maximum time step and maximum number of time steps;  Chapter  4.  Model  Inputs  65  • minimum chemistry time step, maximum number of iterations, relative error tolerance, and a darkness criterion to determine if night chemistry is necessary; • output and print options. The 66-hour simulation was carried out for the period between 0600 L S T on 17 July 1985 and 2400 P S T on 19 July 1985. The surface removal option was used. A maximum time slice and the maximum number of time slices in a time step were set at 0.1 hour and 1, respectively, as recommended by Morris and Myers (1990). Recommended criteria for chemistry time step (.00001 hour), maximum number of iterations (20) and relative error tolerance required for convergence of the chemistry step (.02) were also used.  Chapter 5 Model Results and Discussion  The criteria used to assess model results are presented, followed by an evaluation of model performance based on concentrations predicted for O 3 and its precursor N 0 . Fac2  tors which may have influenced model performance are discussed. Sensitivity indicators are determined for various sites as a further means of assessing model performance.  5.1  Model Performance Criteria Model performance is evaluated in terms of the model's ability to reproduce diurnal  and spatial patterns of pollutant concentrations during a 66-hour simulation extending from 0600 P S T on 17 July 1985 to 2400 P S T on 19 July 1985. This will be done by • comparing time series of predicted and observed concentrations, • comparing contours based on predicted concentrations with observed values, • comparing predicted and observed maximum concentrations for each station for each day of the simulation, • comparing the values of statistical parameters (peak accuracy, bias and gross error) to accepted criteria. Based on a review of photochemical modelling studies, Tesche et al. (1990) reported that on average, photochemical simulations produce peak (unpaired) accuracies, overall bias and gross error statistics of ±15-20%, ±5-15% and 30-35%, respectively. The California 66  Chapter  5. Model Results and  67  Discussion  Air Resources Board ( C A R B ) recommends similar statistics as typical U A M performance goals for 0  3  ( C A R B , 1990). Corresponding performance goals for N 0 are ±50%, ± 3 0 % 2  and 50%, respectively. These criteria will be applied to model output as a means of assessing the acceptability of model performance.  5.2  Ozone  Time series comparing observed and predicted O 3 concentrations are shown in Figures 5.1-5.3 for the 11 monitoring stations reporting O 3 concentrations during this episode. Symbols represent hourly observed concentrations while the solid, thick lines represent predicted concentrations that have been hourly averaged and distance-weighted from the grid averages of the four nearest grid cells. Hatched lines indicate the range of minimum and maximum predicted concentrations over the nine nearest grid cells. Stations have been grouped together as follows: • Stations T02, T03, T04 and T05 are within or near the urban core; • Stations T07 and T09 are suburban sites that are located at the eastern end of Burrard Inlet, and T14 is an elevated site located on Burnaby Mountain, and • Stations T15, T16, T i l and T12 are suburban or rural sites located downwind of the main source area. A number of observations can be made from the time series shown in Figures 5.1-5.3: • The model can reproduce the typical diurnal O 3 patterns in which peak concentrations are observed during mid-afternoon and minimum concentrations are observed at night.  Chapter 5. Model Results and Discussion  68  Figure 5.1: Predicted and observed O 3 concentrations at stations T02, T03, T04 and T05 in the L F V , 17-19 July 1985. Solid lines represent predicted concentrations and hatched lines show the range in neighbouring grid cells. Open circles indicate observations.  Chapter 5. Model Results and Discussion  69  Figure 5.2: Predicted and observed 0 concentrations at stations T07, T09 and T14 in the L F V , 17-19 July 1985. Solid lines represent predicted concentrations and hatched lines show the range in neighbouring grid cells. Open circles indicate observations. 3  Chapter 5. Model Results and Discussion  70  120  A  • 0  o  T15 .  0 0  o °°o 0  o/~/y. o // \  0°/ ^ ° o  °  ^>V /  o  ^ e A p  /  o o n 0022-/ 0  12  24  36  48  60  17 July  18 July  19 July  17 July  18 July  19 July  7i  140  140  T11  120 100 80 60 40 20  °(hnnnr,rP 0  Onnnnnnrvi  12  36  60  17 July  18 July  19 July  140  7;  T12  120 100 80 60 40 20  12  36  60  17 July  18 July  19 July  7!  Figure 5.3: Predicted and observed O 3 concentrations at stations T15, T16, T i l and T12 in the L F V , 17-19 July 1985. Solid lines represent predicted concentrations and hatched lines show the range in neighbouring grid cells. Open circles indicate observations.  Chapter 5. Model Results and Discussion  71  • The model tends to underpredict O 3 concentrations during the day, and overpredict at night when observed values approach zero. The latter feature is particularly noticeable at stations T i l and T12, which are located downwind of the main source region. • W i t h the exception of the first day of the simulation, the morning buildup of O 3 is represented quite well at most stations. However, the predicted morning buildup of O 3 levels at stations T07 and T09 is seen to lag the observations, even though there is good agreement in the timing of the daily maximum. The buildup of O 3 at rural sites T i l and T12 is also very poorly reproduced on 19 July. Spatial patterns of predicted O 3 concentrations (surface layer) are depicted in Figures 5.4-5.6. For each day of the simulation, 0  3  isopleths at 0900, 1200, 1500 and 1800  P S T are presented. Contours are plotted at 20 ppb intervals, beginning at 40 ppb. As shown in Figure 5.4, the morning of 17 July is characterized by relatively low O 3 concentrations throughout the entire modelling domain. B y 1500 P S T , concentrations in excess of 60 ppb are found over a wide band extending eastward along the Coast Mountains from Burrard Inlet, and a smaller area extending up-valley from Abbotsford to Chilliwack. As expected, 0  3  levels are depressed over the major source region, most  likely the result of N O scavenging. By 1800 PST, ozone patterns are displaced further up the valley. The predicted patterns for 18 July shown in Figure 5.5 are characterized by higher concentrations over a much broader area than the previous day. At 0900 P S T , spatial patterns are still very disorganized, but it is clear that levels are depressed over an area including Burrard Inlet and downtown Vancouver. A t 1200 P S T , O 3 levels in excess of 60 ppb are located over the Coast Mountains, north of Indian A r m and Pitt Lake, and over a wide band extending eastward from Boundary Bay in South Surrey towards  Figure 5.4: Contours of predicted 0 at 20 ppb intervals on 17 July 1985 at (a) 0900 PST, (b) 1200 P S T , (c) 1500 P S T and (d) 1800 PST. Large numbers indicate observed concentrations. Missing values are indicated by "-99". 3  Figure 5.4 (Continued).  Figure 5.5: Contours of predicted O 3 at 20 ppb intervals on 18 July 1985 at (a) 0900 PST, (b) 1200 PST, (c) 1500 P S T and (d) 1800 PST. Large numbers indicate observed concentrations. Missing values are indicated by "-99".  Chapter 5. Model Results and Discussion  (c)  "I  75  AVERAGE  , 85199/15.00 - 85199/16.00, level  1. species 03  AVERAGE  , 85199/18.00 - 85199/19.00, level  1, species 03  5 4 5 0 V-  (d)  520 X  540  560  (meters)  Figure 5.5 (Continued).  580  60  Figure 5.6: Contours of predicted O3 at 20 ppb intervals on 19 July 1985 at (a) 0900 P S T , (b) 1200 P S T , (c) 1500 P S T and (d) 1800 PST. Large numbers indicate observed concentrations. Missing values are indicated by "-99".  Chapter 5. Model Results and Discussion  Figure 5.6  (Continued).  Chapter 5. Model Results and Discussion  Chilliwack. A n additional region of elevated 0  78  3  is found over the Straight of Georgia,  to the south of Saturna Island. In contrast, depressed concentrations less than 40 ppb are found over an area encompassing Burrard Inlet. elevated 0  3  At 1500 P S T , a large band of  concentrations extends in an almost north-south fashion over the central  valley. Maximum concentrations are found at the northern and southern ends of this band, with O 3 concentrations in excess of 80 ppb at the north end of Pitt Lake and more than 100 ppb to the southeast of Abbotsford. The very high concentrations observed at downwind sites T15 (97 ppb) and T12 (103 ppb) and the moderately high concentrations at T07 and T09 were not predicted by the model. The small region of elevated 0  3  concentrations located off Saturna Island at 1200 P S T has now moved in a southeasterly direction down the Straight of Georgia. The area of depressed concentrations observed over Burrard Inlet at 1200 P S T has now grown to encompass most of Vancouver, North Burnaby and Port Moody. By 1800 P S T , the large area of elevated O 3 concentrations stretching across the valley has been displaced to the southeast, suggesting transport over the Cascade Mountains. The area of depleted O 3 has grown further to include most of the G V R D and much of the Washington State side of the L F V . Similar patterns are observed for 19 July, although maximum concentrations are somewhat higher. At 1200 P S T , 0  3  concentrations in excess of 80 ppb are found over  the Coast Mountains. The model fails to capture the elevated concentrations observed at T07 and T09. In contrast to the previous day, elevated 0 levels are not found off Saturna 3  Island. A t 1500 P S T , the O 3 patterns are displaced further northward than found on the previous day. Peak concentrations in excess of 100 ppb are found to the north of Pitt Lake. High concentrations observed at stations T15 and T16 are not captured. B y 1800 PST, the entire pattern is shifted eastward. Maximum predicted and observed ground-level 0  3  concentrations are presented in  Table 5.1 on a daily basis for each station. The times of the respective maxima are also  Chapter 5. Model Results and Discussion  79  Table 5.1: Observed and predicted maximum one-hour 0 concentrations in ppb and corresponding hour (PST) at monitoring stations in the L F V , 17-19 July 1985. 3  Station 1 2 3 4 5 6 7 9 11 12 14 15 16  17 July 1985 Obs. Hr Pred.  Hr  18 July 1985 Obs. Hr Pred.  Hr  29.6 39.5 38.4 19.1 41.7  15 15 14 10 14  33.2 39.3 36.6 26.6 26.9  13 12 12 13 13  42.2 39.9 51.9 53.6 66.6  13 14 14 15 14  39.4 44.3 46.4 34.7 34.6  13 12 13 13 13  -  -  -  -  -  -  -  -  63.7 61.0 69.2 73.9 42.1 71.3 66.0  14 14 15 17 14 16 15  41.7 32.0 60.5 72.6 29.8 47.6 40.6  14 14 16 17 13 14 13  74.2 84.0 95.4 102.5 58.7 104.4 79.0  15 14 14 16 14 15 15  49.5 41.9 89.7 71.9 37.1 70.1 61.3  14 14 16 18 14 13 15  presented. Maximum observed 0  3  19 July 1985 Obs. Hr Pred.  Hr  33.0 31.7 45.6 50.3 63.4 42.0 79.9 95.0 106.7 107.2 39.0 87.8 95.0  12 12 12 13 13 13 14 13 14 16 13 13 14  14 12 13 14 12 14 13 15 14 16 2 15 12  40.8 45.7 43.3 40.5 39.7 43.4 53.2 45.3 63.1 81.7 43.4 69.9 59.9  concentrations increased over the three-day period,  registering 73.9 ppb (T12), 104.4 ppb (T15) and 107.2 ppb (T12) on the 17th, 18th, and 19th, respectively. Maximum predicted concentrations over the same period were 72.6 ppb (T12), 89.7 ppb ( T i l ) and 81.7 ppb (T12), respectively.  The time of the  predicted maxima coincided with observations on the 17th and 19th, and lagged by one hour on the 18th. As indicated previously by the time series in Figures 5.1-5.3, there is an overwhelming tendency for the model to underpredict O 3 levels. A l l predicted concentrations and all residuals calculated between the predicted and observed concentrations are compared .against hourly observations in Figure 5.7. These plots indicate that there is a tendency for the model to overpredict low concentrations  Chapter 5. Model Results and Discussion  80  (i.e. <20 ppb) and to underpredict concentrations in excess of 40 ppb. Mean bias and error based on predicted and observed O3 concentrations are presented for each station in Table 5.2. Paired observations and model predictions were only included where observations exceeded 20 ppb, and the number of pairs is also provided in Table 5.2. Although a slight tendency to overpredict 0  3  concentrations is noted for the  two stations located on the west side of Vancouver (T01 and T02) on each day of the simulation, data from the other stations indicate an overwhelming tendency to underpredict peak 0  3  concentrations. This is evident even when relaxing spatial criteria to  include the predicted concentrations in the nine nearest grid cells. Mean normalized bias ranged from 15.2% at T01 to -49.9% at T09 on the 17th, 14.8% at T01 to -57.7% at T09 on the 18th, and 38.8% at T01 to -61.8% at T09 on the 19th. Mean normalized gross error ranged from 14.4% at T03 to 49.9% at T09 on the 17th, 17.2% at T03 to 57.7% at T09 on the 18th, and 14.2% at T03 to 61.8% at T09 on the 19th. From the time series shown in Figures 5.1-5.3 and these performance statistics, it is evident that model performance is worst for those sites located immediately on the downwind side of the urban core, which is the main source region. Model performance was particularly poor for stations T04, T05 and T09, which are each located toward the eastern end of Burrard Inlet and in close proximity to petroleum refineries, and station T14, which is an elevated site. Averaged over all paired data from all stations, normalized bias ranged from -28.5 to -31.3% and normalized gross error ranged from 35.6% to 36.9% over the three days of the simulation. As a further measure of model performance, the accuracy of peak 0  3  concentrations  paired and unpaired in space and time for the three-day simulation are summarized in Table 5.3, together with mean bias and gross error. Peak unpaired accuracy increased over the three-day simulation from -1.8% to -23.8%. However, results generally agreed with the performance goal of ±15-20% recommended by Tesche et al. (1990).  The  Chapter 5. Model Results and Discussion  81  Observed Ozone (ppb)  60 | 40 - •  0  .  20  40  60  80  100  120  Observed Ozone (ppb)  Figure 5.7: Comparison of predicted vs. observed O3 concentrations (above) and comparison of residual (predicted-observed) vs. observed 0 concentrations (below), all sites 17-19 July 1985. 3  Chapter 5. Model Results and Discussion  82  Table 5.2: Model performance based on predicted and observed maximum one-hour 0 concentrations at stations in the L F V , 17-19 July 1985.  Station  17 July 1985 Error No. Bias  1 2 3 4 5 6 7 9 11 12 14 15 16  0.152 0.122 -0.012  0.153 0.263 0.144  4 6 6  -  -  -  -0.353  0.405  -  -  -0.336 -0.499 -0.225 -0.355 -0.388 -0.344 -0.383  Total  -0.291  18 July 1985 Bias Error No.  9  0.148 0.096 -0.122 -0.468 -0.493  0.174 0.402 0.172 0.467 0.493  5 8 7 8 14  -  -  -  -  0.336 0.499 0.250 0.389 0.484 0.348 0.383  10 10 12 11 13 13 10  -0.277 -0.577 -0.191 -0.223 -0.490 -0.297 -0.203  0.348 0.577 0.219 0.285 0.490 0.312 0.223  0.356  104  -0.313  0.375  3  19 July 1985 Error No. Bias  14 12 12 10 22 14 7  0.388 0.263 -0.079 -0.470 -0.551 -0.168 -0.231 -0.618 -0.250 -0.188 -0.384 -0.325 -0.256  0.388 0.263 0.142 0.470 0.551 0.168 0.387 0.618 0.288 0.262 0.385 0.325 0.311  4 6 9 10 12 2 20 13 12 13 11 19 12  133  -0.285  0.369  143  timing of peak predictions agreed well with observations on 17 and 19 July, and lagged the observed maxima by one hour on 18 July. The mean normalized gross error, which averaged 37% over the three-day period, was just outside of the performance goal of 30-35%. The poorest performance was for mean normalized bias, which averaged 30% and compared poorly to the goal of 5-15%. This statistic reflects the fact that there was an overwhelming tendency for the model to underestimate O 3 concentrations.  Chapter 5. Model Results and Discussion  Table 5.3: Model 0  3  83  performance statistics for the L F V , 17-19 July 1985.  Performance measure  17 July 1985  18 July 1985  19 July 1985  73.9 (T12)  104.4 (T15)  107.2 (T12)  72.6 (T12)  89.7 ( T i l )  81.7 (T12)  -1.8% -1.8% -1.8%  -32.6% -19.4% -14.1%  -23.8% -23.8% -23.8%  Time of observed O 3 maximum  1600-1700 P S T  1400-1500 P S T  1500-1600 P S T  Time of predicted O 3 maximum  1600-1700 P S T  1500-1600 P S T  1500-1600 P S T  Mean normalized bias  -29.1%  -31.3%  -28.5%  Mean normalized gross error  35.6%  37.5%  36.9%  Maximum observed 0 concentration (ppb)  3  Maximum predicted O 3 concentration (ppb) Peak accuracy paired in space and time unpaired in space unpaired in space and time  Chapter 5.  5.3  Model Results and  84  Discussion  Nitrogen Dioxide Model performance is also evaluated in terms of the model's ability to reproduce N 0  2  concentrations. Time series of modelled and observed N 0 concentrations are compared 2  in Figures 5.8-5.10. The following observations can be made from these time series: • The model can reproduce diurnal patterns of N 0 at those stations located near 2  Burrard Inlet (T04,T05,T07 and T09) and in South Vancouver (T03). • Reproduction of observed patterns is very poor at stations T02 and T14, where the timing of peak levels is out of phase. • The model tends to underpredict peak N 0 concentrations. 2  Poor model performance at station T02 reflects the inability of the model to simulate rather unusual local conditions in which observed N 0  2  concentrations monotonically  increased throughout the episode. The characteristic diurnal patterns were not evident. Monitor malfunction was ruled out by the local monitoring agency ( G V R D , personal communication). Factors which may have contributed to this result include large and persistent N O x emissions and/or depressed mixing heights in the vicinity of the station, which is located on the roof of a high school in a residential/light commercial area of Vancouver. Spatial patterns of N 0 concentrations predicted for 17-19 July 1985 are depicted in 2  Figures 5.11-5.13. For each day, N 0 isopleths at 0900 P S T , 1200 P S T , 1500 P S T and 2  1800 P S T are presented along with observed values. Contours are plotted at 10 ppb intervals, beginning at 10 ppb. At 0900 P S T on 17 July, the 10 ppb contour extends across the valley in a northwestsoutheast fashion. Concentrations in excess of 30 ppb are found to the northeast of  Chapter 5. Model Results and Discussion  85  Figure 5.8: Predicted and observed NO2 concentrations at stations T02, T03, T04 and T05 in the L F V , 17-19 July 1985. Solid lines show predicted values. Open circles indicate observed data.  Chapter 5. Model Results and Discussion  86  Figure 5.9: Predicted and observed N 0 concentrations at stations T07, T09 and T14 in the L F V , 17-19 July 1985. Solid lines show predicted values. Open circles indicate observed data. 2  Chapter 5. Model Results and Discussion  87  Figure 5.10: Predicted and observed N 0 concentrations at stations T15, T16, T i l and T12 in the L F V , 17-19 July 1985. Solid lines show predicted values. Open circles indicate observed data. 2  Chapter 5. Model Results and Discussion  88  Figure 5.11: Contours of predicted N 0 at 20 ppb intervals on 17 July 1985 at (a) 0900 PST, (b) 1200 P S T , (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations. 2  Chapter 5. Model Results and Discussion  Figure 5.11  (Continued).  89  Chapter 5. Model Results and Discussion  90  (a) 5500 ,  AVERAGE , 85199/ 9.00 - 85199/10.00, level 1, species N02 1 1 1 1 , 1 1 1 1 1 , 1  5490 \-  Figure 5.12: Contours of predicted N 0 at 20 ppb intervals on 18 July 1985 at (a) 0900 P S T , (b) 1200 P S T , (c) 1500 P S T and (d) 1800 PST. Large numbers indicate observed concentrations. 2  Chapter 5. Model Results and Discussion  (c) AVERAGE 1 1  5500 ,  5490  ,  , 85199/15.00 - 85199/16.00, level 1, species N02 1 , 1 , 1 , 1 1 1 1  -  5480 -  „•:.,•''.  Figure 5.12 (Continued).  91  Chapter 5. Model Results and Discussion  92  (a) AVERAGE  «  , 85200/ 9.00 - 85200/10.00, level  1. species N02  5450  520 X  540 (meters)  (b)  AVERAGE  , 85200/12.00 - 85200/13.00, level  520 X  1, species N02  540 (meters)  Figure 5.13: Contours of predicted N 0 at 20 ppb intervals on 19 July 1985 at (a) 0900 PST, (b) 1200 P S T . (c) 1500 P S T and (d) 1800 P S T . Large numbers indicate observed concentrations. 2  Chapter 5. Model Results and Discussion  (c)  AVERAGE  .  93  , 85200/15.00 - 85300/16.00, level  1, species NOZ  , 85300/18.00 - 85200/19.00, level  1, species N02  5450  (d)  AVERAGE  r  1  i  -i  13.••  _i  i  i_  I 520 X  Figure 5.13  :_j  i^J  u  540 (meters)  (Continued).  1  q  Chapter 5. Model Results and Discussion  94  Burrard Inlet, toward the Pitt River valley. At 1200 PST, the L-shaped plume extends from the eastern end of Burrard Inlet to the Pitt River, and then spreads up the Pitt River valley to Pitt Lake. However, little change in the maximum concentrations are noted. By 1500 P S T , the northern extension of the plume is no longer evident. N 0  2  concentrations in excess of 40 ppb are predicted over the area between Burrard Inlet and the Pitt River. Predicted N 0 concentrations at 0900 P S T on 18 and 19 July are much higher than 2  predicted on 17 July. Strong concentration gradients are centred over Burrard Inlet and North Burnaby. However, comparisons with observed values at station T05 in Burnaby (100 ppb) indicate that N 0 concentrations in this region were still greatly underpredicted 2  during the morning hours. The afternoon hours are characterized by lower concentrations and weaker gradients, with predicted values in excess of 30 ppb found to the east of Burrard Inlet. These observations are further reflected in Table 5.4, which lists the daily maximum predicted and observed N 0 concentrations, and the respective times of these maxima, 2  for each station. Maximum concentrations are greatly underpredicted at stations T04, T05 and T12 on 18 July, and at stations T05 and T12 on 19 July.  The timing of  observed maximum concentrations occurs during the late morning/early afternoon at most stations. However, at the downwind station T12 and the elevated station T14, the model predicts maxima to occur in the late evening. Predicted concentrations and the associated residuals (predicted - observed) are compared against observations in Figure 5.14. It is clear from this figure that the model has a tendency to underpredict N 0 concentrations above 30 ppb. 2  Similar model performance statistics as calculated for O 3 were also calculated for N 0 , 2  and the results are shown for individual stations in Table 5.5 and overall in Table 5.6. Paired predictions and observations were only included where observations exceeded 20  Chapter 5. Model Results and Discussion  95  Figure 5.14: (a) Comparison of predicted vs. observed 0 concentrations, and (b) comparison of residual (predicted-observed) vs. observed 0 concentrations, all sites 17-19 July 1985. 3  3  Chapter 5. Model Results and Discussion  96  Table 5.4: Observed (Obs.)and predicted (Pred.) maximum one-hour N 0 concentrations in ppb at monitoring stations in the L F V , 17-19 July 1985, along with the respective time of day (Hr). 2  Station 1 2 3 4 5 6 7 Q O 9 10 11 12 13 14 15 16  Obs.  17 July 1985 Hr Pred.  21 21 10 22  18 July 1985 Hr Pred.  Hr  Obs.  23 17 18 24  43.0 30.0 86.0 100.0  -  -  -  -  -  28.0  12  20.4  10  46.0  21 8 10 9 10  35.0 38.0 -  22 12  36.7 32.7  18 19  59.0 55.0  11 10  -  -  -  -  48.0 40.0 24.0  11 23 1  17.3 40.2 17.4  21 18 21  -  -  -  -  21.0 23.0 48.0 40.0  14.6 17.6 37.3 32.7  Hr  Obs.  Hr  52.5 35.0 48.4 53.0 32.2  9 8 11 11 12  58.0 38.0 62.0 86.0 66.0 22.0  24 7 9 9 20 12  47.1 35.0 55.3 52.4 47.2 34.8  9 1 11 11 10 12  38.6 35.0  19 8 21 11 1 21  44.5 40.8  12 12  -  -  -  -  48.0 55.0 62.0  21 11 23 24  8.0 32.7 44.3  12 13 7 24 12  -  -  41.0 42.0 39.0 44.0 52.0 30.0  -  -  -  -  19 July 1985 Hr Pred.  -  -  6.3 27.6 46.3 11.0 -  7 1 12 8 -  ppb. From Table 5.5, it is seen that the lowest mean bias and error is reported for stations T03 and T04. The highest mean bias and error values are reported for stations T02, T12, T13 and T15. However, poor data availability at stations like T15 prevent any further discussion of these results. On each day of the episode, maximum observed N 0 concentrations were recorded in 2  North Burnaby, at monitoring stations in close proximity to existing oil refineries located along Burrard Inlet: 48.0 ppb (T04) on the 17th, 100.0 ppb (T05) on the 18th, and 86.0 ppb (T05) on the 19th. A station in North Delta, T13, also recorded a maximum N 0  2  Chapter 5. Model Results and Discussion  97  Table 5.5: Model performance based on observed and predicted maximum one-hour N 0 concentrations at stations in the L F V , 17-19 July 1985. Station  2 3 4 5 6 7 9 10 12 13 14 15 Total  17 July 1985 Bias Error No.  18 July 1985 Error No. Bias  -0.606 -0.373 -0.038 -0.114  0.606 0.373 0.207 0.183  3 3 16 19  -0.274 -0.094 -0.194 -0.365  0.682 0.295 0.248 0.365  13 10 17 23  -  -  -  -  -  -  -0.307 0.038 -0.048 -0.612 0.071  0.307 0.188 0.185 0.612 0.283 0.269  2 12 11 9 5 80  -0.214 -0.209 -0.247 -0.247 -0.429 -0.334  0.258 0.326 0.338 0.338 0.480 0.463 0.405  5 19 12 12 10 17 131  -0.144  -0.295  2  19 July 1985 Bias Error No. -0.485 -0.156 -0.069 -0.418 -0.201 0.522 -0.282 -0.210 -0.931 -0.487 -0.217 -0.758 -0.307  0.556 0.292 0.335 0.430 0.312 0.522 0.390 0.341 0.931 0.533 0.458 0.758 0.433  21 11 17 21 7 2 21 17 3 11 12 3 146  concentration of 48.0 ppb on the 17th. Maximum predicted concentrations on each of the three days were 40.2 ppb at T14, 53.0 ppb at T05 and 55.3 ppb at T04, respectively. Peak concentrations were underpredicted by 49.0%, 63.3% and 53.9% on the three days, when paired in space and time. Relaxing spatial and temporal requirements, peak concentrations were underestimated by 16.3%, 47.8% and 37.1%. This was well within the acceptable N 0 criteria used by 2  C A R B (1990). The time of peak concentrations was a minimum of 7 hours late on the 17th and 2 hours late on the 18th, when compared to observations. Poor performance on the 17th may be attributed to model start-up effects. Peak modelled concentrations  Chapter 5. Model Results and Discussion  98  Table 5.6: Model N 0 performance statistics for the L F V , 17-19 July 1985. 2  Performance measure  17 July 1985  18 July 1985  19 July 1985  48.0 (T04/T13)  100.0 (T05)  86.0 (T05)  40.2 (T14)  53.0 (T05)  55.3 (T04)  -49.0% -16.3%  -63.3% -47.8%  -53.9% -37.1%  Time of observed N 0 maximum  0900-1100 P S T  0800-0900 P S T  0800-1100 P S T  Time of predicted N 0 maximum  1700-1800 P S T  1000-1100 P S T  0800-0900 P S T  Mean normalized bias  -14.4%  -29.5%  -30.7%  Mean normalized gross error  26.9%  40.5%  43.3%  Maximum observed N 0 concentration (ppb)  2  Maximum predicted N 0 concentration (ppb)  2  Peak accuracy paired in space and time unpaired in space and time  2  2  were within the period of maximum observed concentrations on the 19th. Mean normalized bias increased from -14.4% to -30.7% over the three-day simulation. This compares favourably with the performance goal of +/- 30%. Mean normalized gross error similarly increased, from 26.9% to 43.3%, but were well within the performance goal of 50%.  Chapter 5. Model Results and Discussion  5.4  99  Discussion Although the general features of the 17-19 July 1985 0  is clear that the model tended to underpredict both 0  3  3  episode were reproduced, it  and N 0 concentrations. Due to 2  the number of input requirements by the model, it is difficult to isolate just one factor which may have contributed to these findings. However, some of the more important factors are discussed in the following. Firstly, the evaluation of model performance was based on comparisons between observations made at a single point and model results volume-averaged over a grid cell with dimensions of 5 km by 5 km in the horizontal and 100 m or greater in the vertical. Hence, some discrepancies are expected between observed and predicted values. Previous studies have indicated that predicted peak 0  3  concentrations decrease with increasing grid size  (Seigneur et al., 1981). Where sub-grid-scale effects are masked by grid cell averages, the discrepancy between predicted and observed concentrations will be larger. This may explain the poor characterization of NO2 concentrations at station T02 in Vancouver, as shown in Figure 5.8. A comparison of predicted wind fields and observations in Section 4.2.1 indicated that modelled wind fields had a greater southerly component than observed winds during the morning hours. This suggests that the influence of the Coast Mountains on local wind fields may have been overestimated. As a result, precursors emissions occurring in the Vancouver/Burnaby area during the morning rush hour would have been transported northwards, as reflected by the isopleths of predicted NO2 concentrations at 0900 P S T shown in Figures 5.11-5.13. This may partly explain the underpredicted 0  3  concentra-  tions at sites located further up the valley. However, this does not discount the finding that elevated 0  3  concentrations may occur along the valley walls. In fact, lidar data  collected by McKendry et al. (1997) during Pacific'93 (Steyn et al., 1997) support this  Chapter 5. Model Results and Discussion  100  finding, showing that pollutants are vented along the valley walls during the daytime. The mixed layer depth defines the vertical extent of mixing in the atmosphere. As such, an overestimate of Zj will yield an underestimate of predicted concentrations. It was shown in Figure 4.4) that values of z; were slightly underpredicted at sites in Vancouver, Delta and Surrey. While it is possible that Zj values were overpredicted at sites further inland, maximum predicted values for Abbotsford on 18 and 19 July (660 and 750 m) compared well with measurements made during Pacific'93 (Hayden et al., 1997). However, it is possible that the influence of marine bodies such as Burrard Inlet was underestimated, resulting in overpredicted values of z; near sites such as T07 and T09. The evaluation of model performance has been limited to an assessment of surface level concentrations, due in large part to the lack of measurements aloft. Station T14 on Burnaby Mountain provides an opportunity to investigate how well the vertical profiles were resolved. While predicted O3 concentrations agreed well with observations, NO2 concentrations were poorly characterized, particularly on 18 July when the predicted maximum was approximately 12 hours out of phase with the observed maximum. A number of factors in addition to the vertical structure may have contributed to this finding, including a failure to accurately characterize wind trajectories and local emissions near this site. The chemical mechanism represents a condensed version of the hundreds, if not thousands of reactions taking place in the atmosphere. Hence, it is accepted that the chemical mechanism introduces some degree of uncertainty in the predicted values. In a comparison of C B M - I V (Whitten et al., 1980; Gery et al., 1988, 1989) and the C A L (Carter et a l , 1986; Lurmann et al., 1987) and Stockwell mechanisms (1990), Dodge (1989) found that the three mechanisms generally yielded similar results. Although this does not imply that the mechanisms were therefore correct, they do include the most up-to-date kinetic data and therefore, the "best science" of the time.  Chapter 5. Model Results and Discussion  101  The emissions inventory is typically one of the largest sources of uncertainty in any modelling study due to the fact that it is impossible to characterize all sources contributing to N O x and V O C emissions. Depending on whether conditions are NOx- or VOC-sensitive, underestimated N O x or V O C emissions may respectively result in underpredicted O3 concentrations. It has been acknowledged that the 1985 inventory used in this simulation provided a rough first estimate ( G V R D , 1988) and further refinements have since been made to this inventory ( G V R D , 1994). As noted in Section 4.3, although overall changes were not large, changes within specific sectors were significant. They included a 23.5% reduction in N O x emissions from point sources and a 34.1% increase in V O C emissions from area sources. Mobile emission estimates used in the simulation were based on Mobile3c and Mobile4.1c estimates. The Cassiar Tunnel study conducted during Pacific'93 (Gertler et al., 1997) showed that Mobile4.1c underpredicted observed NOx and V O C concentrations by 29 and 23%, respectively. However, it was noted that the observed data were obtained under a best case scenario in which vehicles operated under hot-stabilized conditions and at constant speeds. Hence, higher emissions would be expected from vehicles operating under more normal conditions (i.e. variable speed and acceleration). As a means of explaining how errors in V O C or NOx emissions may have effected predictions, sensitivity indicators were considered. Sensitivity indicators are used to determine whether regions are V O C - or NOx-sensitive (Sillman, 1994; Milford et al., 1994; Chameides et al., 1992; Kleinman, 1986; Kleinman, 1991). They provide a means of estimating airshed characteristics without the use of photochemical air quality models. Sensitivity indicators can similarly be applied to the analyses of modelling results as tools for model performance evaluation. The following sensitivity indicators were used: NOy (Milford et al., 1989; Rao et al., 1993; Sillman et al., 1993; Milford et al., 1994), HCHO-to-NOy ratio (Sillman, 1995),  Chapter 5. Model Results and Discussion  102  and 0 3 - t o - N O z ratio (Sillman, 1995). VOC-sensitive conditions were indicated by the following values: NOy concentration >20 ppb; 0 - t o - N O z ratio <7; and HCHO-to3  NOy ratio <0.28.  The indicators were calculated for daytime conditions only, when  photochemical activity is occurring. NOy estimates are for the period from 0700-1800 PST, while the other indicators are for the period from 1200-1800 P S T . Only those values from 18-19 July 1985 are shown, thereby excluding values which may have been influenced by model start-up effects on 17 July. Sensitivity indicators calculated for stations T02, T03 and T05 are shown in Figure 5.15. Each of these stations is located slightly upwind of or in close proximity to the main source region, and so VOC-limited conditions would be expected. None of the three stations had consistent results for all three indicators, but both NOy concentrations and the HCHO-to-NOy ratio indicated that conditions near station T05 were VOC-limited. As shown in Figure 5.1, O 3 concentrations are underpredicted at this site. Hence, the indicator results suggest that V O C emissions or at least the reactivity of V O C emissions may have been underestimated near T05. Sensitivity indicators for stations T07, T09 and T14 are depicted in Figure 5.16. While the 0 3 - t o - N O z ratio indicated NOx-limited conditions, both NOy and the H C H O to-NOy ratio indicated VOC-limited conditions at all three sites. This finding is also supported by the fact that N 0 concentrations were underestimated at these sites, sug2  gesting insufficient radicals to drive N 0 formation, as depicted in Equations 1.7-1.9. 2  Uncertainties with respect to the vertical profile of pollutants at station T14, an elevated site, also likely contributed to the poor performance at this site. Finally, indicators for stations T15, T i l and T12 are presented in Figure 5.17. A l l three indicators show NOx-limited conditions for most hours of the afternoon.  This  is as expected for an aged air mass at such downwind sites. Underpredicted peak O 3 concentrations (Figure 5.3) at the three sites suggests that N O x emissions, either locally  Chapter 5. Model Results and Discussion  or downwind, were underestimated.  103  The fact that the model could not reproduce the  very low O3 concentrations observed at night also suggests that local N O x emissions were underestimated.  9 !  1  100  .  T02  -  80  o z  6 0  -  -  40  IE  60 -  g  40  Q.  1  1  I  20 0  (pp  1  80  A  12 Hour (PST)  140 120 100 80 o 60 z 40 20 0  1  T02  -  A  &  1  15  —i  18  •  1  2  •  i  3  4  NOz  40 NOy  (ppb)  100 AT03  i  1  60 (ppb)  100  c  s  1  T03 80  1[  co o  c CO  60  CL  A  co O  •+ -ft- *  •A  *  *  CO  ;  o" S3  * '  12  A  15  18  '  '  >  3 NOz  Hour (PST)  4 (ppb)  40 NOy  60 (ppb)  40 NOy  60 (ppb)  100  100r T05 80 .a Q. a. CO  O  60 40 20 -  .•A  •A  •  A  o L 12 Hour (PST)  15  2  3 NOz  4 (ppb)  5  Figure 5.15: Sensitivity indicators based on predictions at stations T02, T03 and T05. Triangles show values for 18 July, diamonds for 19 July.  £  10  i  T07  1  •  S  6  1  4  0 0 1  12  15  18  1  Hour (PST)  2  3  4  5  A  A  /  *  , * » ^ A *  2  6  20  NOz (ppb)  -  40  60  80  100  80  100  NOy (ppb)  100.  12  15  18  20  Hour (PST)  40  10  ~ i  T14  A  B  6  1  4  0 1  12  15  18  1  A  CL  0  1  *  .a  Hour (PST)  60  NOy (ppb)  2  •  / /  •  20  40  60  100  NOy (ppb)  Figure 5.16: Sensitivity indicators based on predictions at stations T07, T09 and T14. Triangles show values for 18 July, diamonds for 19 July.  Chapter 5. Model Results and Discussion  106  oo  CO  1  CD  CO  (qdd) OHOH  (qdd) OHOH  (qdd) e o  (qdd) CO  (qdd) e o  1  1  1  1  1  1  I  30  <K  <•  <• •* O  -  <»•  -  a* I-  « «  -  «  • •  -  m J-  (73 , 0-  <•  <•  -  <»  3 O  X  •» -  | l  o X  « •  •*  e i  p w  «  >  •  CD  ~  (qdd) OHOH  i  CO  (qdd)  (D  4  A Q N  ^  (qdd)  A Q N  ^  w  (O  (qdd)  m A Q N  LO  Chapter 6 Summary  The U A M - I V was applied to the L F V for an historical O 3 episode occurring between 17-19 July 1985. Model performance was evaluated in terms of its ability to reproduce O3 and NO2 concentrations observed during this episode. Major findings included the following: • Diurnal characteristics of ambient O3 and NO2 concentrations were generally reproduced in the model simulation. • Unpaired peak accuracy, mean normalized bias and mean gross error averaged 13%, -30% and 37%, respectively, for 0 . Model performance was worst for those 3  sites located immediately on the downwind side of the main source region. • Corresponding statistics for NO2 were -34%, -25% and 37%, respectively. • The model typically underpredicted peak 0  and NO2 concentrations.  3  • Some degree of underprediction was expected since comparisons were made between observations taken at a single point and model results volume-averaged over a grid cell of dimensions 5 km x 5 km in the horizontal and 100 m or greater in the vertical. • The model also overpredicted nocturnal 0  3  concentrations at those stations in  which observed concentrations approached zero. • Spatial patterns showed depressed O 3 concentrations over much of Vancouver and Burnaby, reflecting the titrating effect of N O emissions in the urban areas. 107  Chapter 6.  108  Summary  • These patterns also indicated that higher 0  3  concentrations occurred along the  valley walls as opposed to the valley floor where most of the population resides. In particular, areas of elevated O 3 concentrations were predicted to occur at the head of the Pitt River valley and to the southeast of Abbotsford in Washington State. Observations made during Pacific'93 by McKendry et al. (1997) support the findings over the Pitt River valley. • Spatial patterns of N 0 revealed high concentrations and strong gradients to the 2  north of station T05 in North Burnaby. • These findings and a comparison of predicted and observed winds suggests that the influence of the Coast Mountains on local winds during the morning hours, as manifested by a southerly wind component, was overestimated. As a result, 0  3  concentrations may have been overpredicted along the valley walls and underpredicted at inland sites along the valley floor, such as at sites in Surrey, Abbotsford and Chilliwack. • A further source of large uncertainty in the modelling study was the emissions inventory. • Sensitivity indicators (NOy, HCHO-to-NOy ratio and 0 3 - t o - N O z ratio) calculated using predicted concentrations indicated that sites in Burnaby and Port Moody were VOC-limited. Underpredicted O 3 concentrations at these sites may be partially attributed to either underestimated V O C emissions or underestimated reactivity of the V O C mixture in the main source region. • Indicators also showed that downwind sites in Surrey, Abbotsford and Chilliwack were NOx-limited. This helps to explain why the model overpredicted nocturnal O 3 concentrations, particularly in Abbotsford and Chilliwack.  List of References  B . H . 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