Evaluation of Regional Air Quality Models over Sydney, Australia: Part 2, Comparison of PM2.5 and Ozone

Abstract

Accurate air quality modelling is an essential tool, both for strategic assessment (regulation development for emission controls) and for short-term forecasting (enabling warnings to be issued to protect vulnerable members of society when the pollution levels are predicted to be high). Model intercomparison studies are a valuable support to this work, being useful for identifying any issues with air quality models, and benchmarking their performance against international standards, thereby increasing confidence in their predictions. This paper presents the results of a comparison study of six chemical transport models which have been used to simulate short-term hourly to 24 hourly concentrations of fine particulate matter less than and equal to 2.5 µm in diameter (PM2.5) and ozone (O3) for Sydney, Australia. Model performance was evaluated by comparison to air quality measurements made at 16 locations for O3 and 5 locations for PM2.5, during three time periods that coincided with major atmospheric composition measurement campaigns in the region. These major campaigns included daytime measurements of PM2.5 composition, and so model performance for particulate sulfate (SO42−), nitrate (NO3−), ammonium (NH4+) and elemental carbon (EC) was evaluated at one site per modelling period. Domain-wide performance of the models for hourly O3 was good, with models meeting benchmark criteria and reproducing the observed O3 production regime (based on the O3/NOx indicator) at 80% or more of the sites. Nevertheless, model performance was worse at high (and low) O3 percentiles. Domain-wide model performance for 24 h average PM2.5 was more variable, with a general tendency for the models to under-predict PM2.5 concentrations during the summer and over-predict PM2.5 concentrations in the autumn. The modelling intercomparison exercise has led to improvements in the implementation of these models for Sydney and has increased confidence in their skill at reproducing observed atmospheric composition.

Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

“…Brief descriptions of each model are provided below. Further information including model setup, descriptions and relevant references for specific parameterizations can be found in Monk et al [25] and Guérette et al [26].…”

“…Each of the models was run over four nested domains, downscaling from the regional (80-81 km resolution, encompassing all of Australia), to 3 km for the domain centered on the Greater Sydney Region [25,26]. Although the models have consistent horizontal grids, they differ in their number of vertical layers and in the height of their first layer.…”

“…The NSW EPA inventory, however, refers to an area that is smaller than the larger modelling domains. Consequently, in addition to this scheme, as discussed by Guérette et al [26], W-UM1, W-UM2, W-NC1 and W-NC2 used additional emissions information from EDGAR for parts of the domains not covered by the NSW EPA inventory. Furthermore, C-CTM and O-CTM contain a parameterization for wood smoke emission based on heating degree days, and C-CTM alone included wildfire emissions.…”

“…Specifically, meteorology, particle precursor trace gases, and fine particles measured at Westmead (NSW, Australia) in autumn 2012 are compared with corresponding values simulated by seven models operated by ANSTO, CSIRO, the NSW Office of Environment and Heritage (NSW OEH), the University of Melbourne, and North Carolina State University. The model runs from which the results for this study have been selected formed part of a larger, more comprehensive inter-comparison/evaluation exercise (see [25][26][27]).…”

“…This will result in less than optimum comparisons between observed and simulated meteorological quantities. Detailed evaluations at more appropriate sites are the subject of separate investigations (e.g., [25,26,[29][30][31]).…”