Michael D. Moran

Modelling gaseous dry deposition in AURAMS: A unified regional air-quality modelling system

An upgraded parameterization scheme for gaseous dry-deposition velocities has been developed for a new regional air-quality model with a 91-species gas-phase chemistry mechanism, of which 48 species are “transported” species. The well-known resistance analogy to dry deposition is adopted in the present scheme, with both O3 and SO2 taken as base species. Stomatal resistances are calculated for all dry-depositing species using a “sunlit/shaded big-leaf” canopy stomatal resistance submodel. Dry-ground, wet-ground, dry-cuticle, and wet-cuticle resistances for O3 and SO2, and parameters for calculating canopy stomatal resistance and aerodynamic resistance for these two base species are given as input parameters for each of the 15 land-use categories and/or five seasonal categories considered by the scheme. Dry-ground, wet-ground, dry-cuticle, and wet-cuticle resistances for the other 29 model species for which dry deposition is considered to be a significant process are scaled to the resistances of O3 and SO2 based on published measurements of their dry deposition and/or their aqueous solubility and oxidizing capacity. Mesophyll resistances are treated as dependent only on chemical species. Field experimental data have then been used to evaluate the schemes performance for O3 and SO2. Example sets of modelled dry-deposition velocities have also been calculated for all 31 dry-deposited species and 15 land-use categories for different environmental conditions. This new scheme incorporates updated information on dry-deposition measurements and is able to predict deposition velocities for 31 gaseous species for different land-use types, seasons, and meteorological conditions.

A comparison of models to estimate in-canopy photosynthetically active radiation and their influence on canopy stomatal resistance

Abstract The models for photosynthetically active radiation (PAR) used in a multi-layer canopy stomatal resistance (CSR) model developed by Baldocchi et al. (Atmospheric Environment 21 (1987) 91–101) and in a two-big-leaf CSR model developed by Hicks et al. (Water, Air and Soil Pollution 36 (1987) 311) are investigated in this study. The PAR received by shaded leaves in Baldocchi et al. (1987) is found to be larger than that predicted by a canopy radiative-transfer model developed by Norman (in: Barfield, Gerber, (Eds.), Modification of the Aerial Environment of Crops. ASAE Monograph No. 2. American Society for Agricultural. Engineering, St. Joseph, MI, 1979, p. 249) by as much as 50% even though the Baldocchi et al. (1987) model is indirectly based on Normans model. This larger value of PAR results in turn in a smaller CSR by as much as 30% for canopies with larger leaf area indexes. A new formula to predict vertical profiles for PAR received by shaded leaves inside a canopy is suggested in the present study based on Norman (1979) and agrees well with the original model of Norman (1979). The simple treatment used in Hicks et al. (1987) for canopy-average PAR received by shaded leaves is found to diverge for canopies with leaf area indexes not close to two A new empirical formula for canopy-average PAR is then suggested for use in a two-big-leaf model, and it is shown that under most conditions the modified two-big-leaf CSR model can predict reasonable values when compared with the more complex multi-layer CSR model. Both the modified multi-layer CSR model and the modified two-big-leaf CSR model are also shown to predict reasonable dry deposition velocities for O 3 when compared to several sets of measurements.

Mass-Conservation Issues in Modelling Regional Aerosols

The problem of using mass-inconsistent winds in tracer advection is relatively well recognized in the air quality modelling community. As pointed out by (1999), an inconsistency in the air-density and wind fields is equivalent to an additional source term in the tracer continuity equation, which will lead to mass-conservation violation in air quality models. There are a number of causes of mass inconsistency in the input air- density and wind fields for air quality models. For example, the continuity equation for air density is not always included as one of the prognostic equations in meteorological models, and air density is then a diagnostic variable; staggering of space and time grids in meteorological models for momentum and thermal variables can affect the accuracy of the solution of the continuity equation; furthermore, de-staggering in air quality (AQ) models can also introduce mass inconsistency. Various methods (both formal and ad hoc) have been used in practice to correct the error introduced by mass-inconsistent winds. This usually involves corrections to the winds to make them mass consistent (e.g., Odman and Russell, 1999) and adjustment to tracer fields through a correction to air density (e.g., Lu et al., 1997). (1999) also suggested a number of ways of correcting the mass-inconsistency error in air quality models based on a formal analysis of his continuity equation formulated in a generalised coordinate system.

Cloud Processing of Gases and Aerosols in a Regional Air Quality Model (AURAMS): Evaluation Against Aircraft Data

Clouds play an active role in the processing and cycling of chemicals in the atmosphere. Gases and aerosols can enter cloud droplets through absorption/condensation (of soluble gases) and activation and impact scavenging (of aerosol particles). Once inside the cloud droplets these tracers can dissolve, dissociate, and undergo chemical reactions. It is believed that aqueous phase chemistry in cloud is the largest contributor to sulphate aerosol production. Some of the aqueousphase tracers will be removed from the atmosphere when precipitation forms and reaches the ground. However, the majority of clouds are non-precipitating, and upon cloud dissipation and evaporation, the tracers, physically and chemically altered, will be released back to the atmosphere. Updrafts and downdrafts in convective clouds are also efficient ways of redistributing atmospheric tracers in the vertical. It is therefore important to represent these cloud-related physical and chemical processes when modelling the transport and transformation of atmospheric chemical tracers, particularly aerosols. A new multiple-pollutant (unified) regional air-quality modelling system, AURAMS, with sizeand chemical-composition-resolved aerosols is being developed at the Meteorological Service of Canada. In the current version of AURAMS, many of the cloud processes mentioned above are represented. Evaluation of the model performance is underway for several selected periods (e.g., Makar et al., 2004a,b; Bouchet et al., 2004). In this paper we will focus on a comparison against aircraft measurements conducted during the EMEFS-1 campaign in the summer of

Wintertime and Summertime Evaluation of the Regional Pm Air Quality Model Aurams

Three dimensional air quality models have established themselves as valuable tools for the development of emission control strategies. They give scientists the ability to investigate the consequences of multiple emission reduction scenarios as well as research optimum sets of pollutant and/or precursor emission reductions under various meteorological conditions. This capability is becoming crucial as advances in atmospheric science in the past decades have revealed numerous links between ground-level air pollution problems such as ozone, acid rain and particulate matter (PM) (Hidy et al., 1998). With the recognition of PM, especially, as a severe human health concern (Samet et al., 2000; Brook et al., 2002), efforts have lately focused on addressing this new issue without compromising any achievement in reducing ozone and acid rain. As demonstrated by (1997), decreasing VOCs, which are ozone precursors, could free nitrogen oxides and results, under certain conditions, in an increase in PM mass. The so-called ‘one atmosphere’ models are therefore desirable to study PM issues.

High Resolution Nested Runs of the AURAMS Model with Comparisons to PrAIRie2005 Field Study Data

The PrAIRie2005 campaign took place in the summer of 2005 in the city of Edmonton, Alberta. The measurement campaign was designed and led by air-quality modellers with the scientific objective of determining the extent to which air pollution events in the city are the result of locally emissions versus long-range transport. A nested version of the AURAMS model was constructed for post-campaign simulations and evaluation against the measurement data. The nested model runs at different resolutions, the highest of which is a 3 km horizontal resolution centered on the urban area.