Hot Summers: Effect of Extreme Temperatures on Ozone in Sydney, Australia

Concurrent Heat Waves and Extreme Ozone (O3) Episodes: Combined Atmospheric Patterns and Impact on Human Health

More recurrent heat waves and extreme ozone (O₃) episodes are likely to occur during the next decades and a key question is about the concurrence of those hazards, the atmospheric patterns behind their appearance, and their joint effect on human health. In this work, we use surface maximum temperature and O₃ observations during extended summers in two cities from Morocco: Casablanca and Marrakech, between 2010 and 2019. We assess the connection between these data and climate indices (North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), and Saharan Oscillation (SaO)). We then identify concurrent heat waves and O₃ episodes, the weather type behind this concurrence, and the combined health risks. Our findings show that the concurrence of heat waves and O₃ episodes depends both on the specific city and the large-scale atmospheric circulation. The likely identified synoptic pattern is when the country is under the combined influence of an anticyclonic area in the north and the Saharan trough extending the depression centered in the south. This pattern generates a warm flow and may foster photochemical pollution. Our study is the first step toward the establishment of an alert system. It will help to provide recommendations for coping with concurrent heat waves and air pollution episodes.

Air quality and health impact of 2019-20 Black Summer megafires and COVID-19 lockdown in Melbourne and Sydney, Australia

Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia's most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series' of nitrogen dioxide (NO₂), ozone (O₃), carbon monoxide CO and particulate matter with diameter < 2.5 μm (PM_2.5), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM_2.5 (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM_2.5 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6-343.) excess deaths and 3490.0 (95% CI 1325.9-5653.5) additional hospitalisations were likely as a result of PM_2.5 and O₃ exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO₂ decreased by 21.5 and 8% in Victoria and NSW respectively. O₃ and PM_2.5 remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.

Seasonal Variation of Biogenic and Anthropogenic VOCs in a Semi-Urban Area Near Sydney, Australia

Volatile organic compounds (VOCs) play a key role in the formation of ozone and secondary organic aerosol, the two most important air pollutants in Sydney, Australia. Despite their importance, there are few available VOC measurements in the area. In this paper, we discuss continuous GC-MS measurements of 10 selected VOCs between February (summer in the southern hemisphere) and June (winter in the southern hemisphere) of 2019 in a semi-urban area between natural eucalypt forest and the Sydney metropolitan fringe. Combined, isoprene, methacrolein, methyl-vinyl-ketone, α-pinene, p-cymene, eucalyptol, benzene, toluene xylene and tri-methylbenzene provide a reasonable representation of variability in the total biogenic VOC (BVOC) and anthropogenic VOC (AVOC) loading in the area. Seasonal changes in environmental conditions were reflected in observed BVOC concentrations, with a summer peak of 8 ppb, dropping to approximately 0.1 ppb in winter. Isoprene, and its immediate oxidation products methacrolein (MACR) and methyl-vinyl-ketone (MVK), dominated BVOC concentrations during summer and early autumn, while monoterpenes comprised the larger fraction during winter. Temperature and solar radiation drive most of the seasonal variation observed in BVOCs. Observed levels of isoprene, MACR and MVK in the atmosphere are closely related with variations in temperature and photosynthetically active radiation (PAR), but chemistry and meteorology may play a more important role for the monoterpenes. Using a nonlinear model, temperature explains 51% and PAR 38% of the isoprene, MACR and MVK variation. Eucalyptol dominated the observed monoterpene fraction (contributing ~75%), with p-cymene (20%) and α-pinene (5%) also present. AVOCs maintain an average concentration of ~0.4 ppb, with a slight decrease during autumn–winter. The low AVOC concentrations observed indicate a relatively small anthropogenic influence, generally occurring when (rare) northerly winds transport Sydney emissions to the measurement site. The site is influenced by domestic, commercial and vehicle AVOC emissions. Our observed AVOC concentrations can be explained by the seasonal changes in meteorology and the emissions in the area as listed in the NSW emissions inventory and thereby act as an independent validation of this inventory. We conclude that the variations in atmospheric composition observed during the seasons are an important variable to consider when formulating air pollution control policies over Sydney given the influence of biogenic sources during summer, autumn and winter.

Surface ozone exceedances in Melbourne, Australia are shown to be under NOx control, as demonstrated using formaldehyde:NO2 and glyoxal:formaldehyde ratios

Two and a half years of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of nitrogen dioxide (NO₂), formaldehyde (HCHO) and glyoxal (CHOCHO) are presented alongside in-situ ozone (O₃) measurements in Melbourne, Australia. Seasonal and diurnal cycles, vertical profiles and relationships with key meteorological variables are provided. NO₂ and CHOCHO were found at highest concentration for low wind speeds implying that their sources were predominantly localised and anthropogenic. HCHO showed an exponential relationship with temperature and a strong wind direction dependence from the northern and eastern sectors, and therefore most likely originated from oxidation of biogenic volatile organic compounds (VOCs) from surrounding forested and rural areas. The glyoxal:formaldehyde ratio (R_gf), reported for the first time in Australia, was consistently high compared to values elsewhere in the world with a mean of 0.105 ± 0.0503 and tended to increase with increasing anthropogenic influence. The HCHO:NO₂ ratio (R_fn) was used to characterise tropospheric ozone formation conditions. A strong relationship was found between high temperature, low R_gf, high R_fn and high ozone surface concentrations. Therefore, we propose that both R_gf and R_fn may be useful indicators of tropospheric ozone production regimes and concentrations. The R_fn showed that the vast majority of high ozone production episodes occurred under NO_x-limited conditions, suggesting that surface ozone pollution events in Melbourne could be curtailed using NO_x emission controls.

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

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.

A Clean Air Plan for Sydney: An Overview of the Special Issue on Air Quality in New South Wales

This paper presents a summary of the key findings of the special issue of Atmosphere on Air Quality in New South Wales and discusses the implications of the work for policy makers and individuals. This special edition presents new air quality research in Australia undertaken by (or in association with) the Clean Air and Urban Landscapes hub, which is funded by the National Environmental Science Program on behalf of the Australian Government’s Department of the Environment and Energy. Air pollution in Australian cities is generally low, with typical concentrations of key pollutants at much lower levels than experienced in comparable cities in many other parts of the world. Australian cities do experience occasional exceedances in ozone and PM2.5 (above air pollution guidelines), as well as extreme pollution events, often as a result of bushfires, dust storms, or heatwaves. Even in the absence of extreme events, natural emissions play a significant role in influencing the Australian urban environment, due to the remoteness from large regional anthropogenic emission sources. By studying air quality in Australia, we can gain a greater understanding of the underlying atmospheric chemistry and health risks in less polluted atmospheric environments, and the health benefits of continued reduction in air pollution. These conditions may be representative of future air quality scenarios for parts of the Northern Hemisphere, as legislation and cleaner technologies reduce anthropogenic air pollution in European, American, and Asian cities. However, in many instances, current legislation regarding emissions in Australia is significantly more lax than in other developed countries, making Australia vulnerable to worsening air pollution in association with future population growth. The need to avoid complacency is highlighted by recent epidemiological research, reporting associations between air pollution and adverse health outcomes even at air pollutant concentrations that are lower than Australia’s national air quality standards. Improving air quality is expected to improve health outcomes at any pollution level, with specific benefits projected for reductions in long-term exposure to average PM2.5 concentrations.

Air Quality Impacts of Smoke from Hazard Reduction Burns and Domestic Wood Heating in Western Sydney

Air quality was measured in Auburn, a western suburb of Sydney, Australia, for approximately eighteen months during 2016 and 2017. A long open-path infrared spectrometer sampled path-averaged concentrations of several gaseous species, while other pollutants such as PM 2.5 and PM 10 were sampled by a mobile air quality station. The measurement site was impacted by a number of indoor wood-heating smoke events during cold winter nights as well as some major smoke events from hazard reduction burning in the spring of 2017. In this paper we compare the atmospheric composition during these different smoke pollution events and assess the relative overall impact on air quality from domestic wood-heaters and prescribed forest fires during the campaign. No significant differences in the composition of smoke from these two sources were identified in this study. Despite the hazard reduction burning events causing worse peak pollution levels, we find that the overall exposure to air toxins was greater from domestic wood-heaters due to their higher frequency and total duration. Our results suggest that policy-makers should place a greater focus on reducing wood-smoke pollution in Sydney and on communicating the issue to the public.

Composition of Clean Marine Air and Biogenic Influences on VOCs during the MUMBA Campaign

Volatile organic compounds (VOCs) are important precursors to the formation of ozone and fine particulate matter, the two pollutants of most concern in Sydney, Australia. Despite this importance, there are very few published measurements of ambient VOC concentrations in Australia. In this paper, we present mole fractions of several important VOCs measured during the campaign known as MUMBA (Measurements of Urban, Marine and Biogenic Air) in the Australian city of Wollongong (34°S). We particularly focus on measurements made during periods when clean marine air impacted the measurement site and on VOCs of biogenic origin. Typical unpolluted marine air mole fractions during austral summer 2012-2013 at latitude 34°S were established for CO2 (391.0 ± 0.6 ppm), CH4 (1760.1 ± 0.4 ppb), N2O (325.04 ± 0.08 ppb), CO (52.4 ± 1.7 ppb), O3 (20.5 ± 1.1 ppb), acetaldehyde (190 ± 40 ppt), acetone (260 ± 30 ppt), dimethyl sulphide (50 ± 10 ppt), benzene (20 ± 10 ppt), toluene (30 ± 20 ppt), C8H10 aromatics (23 ± 6 ppt) and C9H12 aromatics (36 ± 7 ppt). The MUMBA site was frequently influenced by VOCs of biogenic origin from a nearby strip of forested parkland to the east due to the dominant north-easterly afternoon sea breeze. VOCs from the more distant densely forested escarpment to the west also impacted the site, especially during two days of extreme heat and strong westerly winds. The relative amounts of different biogenic VOCs observed for these two biomes differed, with much larger increases of isoprene than of monoterpenes or methanol during the hot westerly winds from the escarpment than with cooler winds from the east. However, whether this was due to different vegetation types or was solely the result of the extreme temperatures is not entirely clear. We conclude that the clean marine air and biogenic signatures measured during the MUMBA campaign provide useful information about the typical abundance of several key VOCs and can be used to constrain chemical transport model simulations of the atmosphere in this poorly sampled region of the world.

Evaluation of Regional Air Quality Models over Sydney and Australia: Part 1—Meteorological Model Comparison

The ability of meteorological models to accurately characterise regional meteorology plays a crucial role in the performance of photochemical simulations of air pollution. As part of the research funded by the Australian government’s Department of the Environment Clean Air and Urban Landscape hub, this study set out to complete an intercomparison of air quality models over the Sydney region. This intercomparison would test existing modelling capabilities, identify any problems and provide the necessary validation of models in the region. The first component of the intercomparison study was to assess the ability of the models to reproduce meteorological observations, since it is a significant driver of air quality. To evaluate the meteorological component of these air quality modelling systems, seven different simulations based on varying configurations of inputs, integrations and physical parameterizations of two meteorological models (the Weather Research and Forecasting (WRF) and Conformal Cubic Atmospheric Model (CCAM)) were examined. The modelling was conducted for three periods coinciding with comprehensive air quality measurement campaigns (the Sydney Particle Studies (SPS) 1 and 2 and the Measurement of Urban, Marine and Biogenic Air (MUMBA)). The analysis focuses on meteorological variables (temperature, mixing ratio of water, wind (via wind speed and zonal wind components), precipitation and planetary boundary layer height), that are relevant to air quality. The surface meteorology simulations were evaluated against observations from seven Bureau of Meteorology (BoM) Automatic Weather Stations through composite diurnal plots, Taylor plots and paired mean bias plots. Simulated vertical profiles of temperature, mixing ratio of water and wind (via wind speed and zonal wind components) were assessed through comparison with radiosonde data from the Sydney Airport BoM site. The statistical comparisons with observations identified systematic overestimations of wind speeds that were more pronounced overnight. The temperature was well simulated, with biases generally between ±2 °C and the largest biases seen overnight (up to 4 °C). The models tend to have a drier lower atmosphere than observed, implying that better representations of soil moisture and surface moisture fluxes would improve the subsequent air quality simulations. On average the models captured local-scale meteorological features, like the sea breeze, which is a critical feature driving ozone formation in the Sydney Basin. The overall performance and model biases were generally within the recommended benchmark values (e.g., ±1 °C mean bias in temperature, ±1 g/kg mean bias of water vapour mixing ratio and ±1.5 m s−1 mean bias of wind speed) except at either end of the scale, where the bias tends to be larger. The model biases reported here are similar to those seen in other model intercomparisons.

Occurrence and Coupling of Heat and Ozone Events and Their Relation to Mortality Rates in Berlin, Germany, between 2000 and 2014

Episodes of hot weather and poor air quality pose significant consequences for public health. In this study, these episodes are addressed by applying the observational data of daily air temperature and ozone concentrations in an event-based risk assessment approach in order to detect individual heat and ozone events, as well as events of their co-occurrence in Berlin, Germany, in the years 2000 to 2014. Various threshold values are explored so as to identify these events and to search for the appropriate regressions between the threshold exceedances and mortality rates. The events are further analyzed in terms of their event-specific mortality rates and their temporal occurrences. The results reveal that at least 40% of all heat events during the study period are accompanied by increased ozone concentrations in Berlin, particularly the most intense and longest heat events. While ozone events alone are only weakly associated with increased mortality rates, elevated ozone concentrations during heat events are found to amplify mortality rates. We conclude that elevated air temperatures during heat events are one major driver for increased mortality rates in Berlin, but simultaneously occurring elevated ozone concentrations act as an additional stressor, leading to an increased risk for the regional population.

Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models During Recent Field Campaigns in Australia, Part II: Comparison of WRF/Chem and WRF/Chem-ROMS and Impacts of Air-Sea Interactions and Boundary Conditions

Air-sea interactions play an important role in atmospheric circulation and boundary layer conditions through changing convection processes and surface heat fluxes, particularly in coastal areas. These changes can affect the concentrations, distributions, and lifetimes of atmospheric pollutants. In this Part II paper, the performance of the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are intercompared for their applications over quadruple-nested domains in Australia during the three following field campaigns: The Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2) and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). The results are used to evaluate the impact of air-sea interaction representation in WRF/Chem-ROMS on model predictions. At 3, 9, and 27 km resolutions, compared to WRF/Chem, the explicit air-sea interactions in WRF/Chem-ROMS lead to substantial improvements in simulated sea-surface temperature (SST), latent heat fluxes (LHF), and sensible heat fluxes (SHF) over the ocean, in terms of statistics and spatial distributions, during all three field campaigns. The use of finer grid resolutions (3 or 9 km) effectively reduces the biases in these variables during SPS1 and SPS2 by WRF/Chem-ROMS, whereas it further increases these biases for WRF/Chem during all field campaigns. The large differences in SST, LHF, and SHF between the two models lead to different radiative, cloud, meteorological, and chemical predictions. WRF/Chem-ROMS generally performs better in terms of statistics and temporal variations for temperature and relative humidity at 2 m, wind speed and direction at 10 m, and precipitation. The percentage differences in simulated surface concentrations between the two models are mostly in the range of ±10% for CO, OH, and O3, ±25% for HCHO, ±30% for NO2, ±35% for H2O2, ±50% for SO2, ±60% for isoprene and terpenes, ±15% for PM2.5, and ±12% for PM10. WRF/Chem-ROMS at 3 km resolution slightly improves the statistical performance of many surface and column concentrations. WRF/Chem simulations with satellite-constrained boundary conditions (BCONs) improve the spatial distributions and magnitudes of column CO for all field campaigns and slightly improve those of the column NO2 for SPS1 and SPS2, column HCHO for SPS1 and MUMBA, and column O3 for SPS2 at 3 km over the Greater Sydney area. The satellite-constrained chemical BCONs reduce the model biases of surface CO, NO, and O3 predictions at 3 km for all field campaigns, surface PM2.5 predictions at 3 km for SPS1 and MUMBA, and surface PM10 predictions at all grid resolutions for all field campaigns. A more important role of chemical BCONs in the Southern Hemisphere, compared to that in the Northern Hemisphere reported in this work, indicates a crucial need in developing more realistic chemical BCONs for O3 in the relatively clean SH.

Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models during Recent Field Campaigns in Australia, Part I: Model Description and WRF/Chem-ROMS Evaluation Using Surface and Satellite Data and Sensitivity to Spatial Grid Resolutions

Air pollution and associated human exposure are important research areas in Greater Sydney, Australia. Several field campaigns were conducted to characterize the pollution sources and their impacts on ambient air quality including the Sydney Particle Study Stages 1 and 2 (SPS1 and SPS2), and the Measurements of Urban, Marine, and Biogenic Air (MUMBA). In this work, the Weather Research and Forecasting model with chemistry (WRF/Chem) and the coupled WRF/Chem with the Regional Ocean Model System (ROMS) (WRF/Chem-ROMS) are applied during these field campaigns to assess the models’ capability in reproducing atmospheric observations. The model simulations are performed over quadruple-nested domains at grid resolutions of 81-, 27-, 9-, and 3-km over Australia, an area in southeastern Australia, an area in New South Wales, and the Greater Sydney area, respectively. A comprehensive model evaluation is conducted using surface observations from these field campaigns, satellite retrievals, and other data. This paper evaluates the performance of WRF/Chem-ROMS and its sensitivity to spatial grid resolutions. The model generally performs well at 3-, 9-, and 27-km resolutions for sea-surface temperature and boundary layer meteorology in terms of performance statistics, seasonality, and daily variation. Moderate biases occur for temperature at 2-m and wind speed at 10-m in the mornings and evenings due to the inaccurate representation of the nocturnal boundary layer and surface heat fluxes. Larger underpredictions occur for total precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. The model performs well at 3-, 9-, and 27-km resolutions for surface O3 in terms of statistics, spatial distributions, and diurnal and daily variations. The model underpredicts PM2.5 and PM10 during SPS1 and MUMBA but overpredicts PM2.5 and underpredicts PM10 during SPS2. These biases are attributed to inaccurate meteorology, precursor emissions, insufficient SO2 conversion to sulfate, inadequate dispersion at finer grid resolutions, and underprediction in secondary organic aerosol. The model gives moderate biases for net shortwave radiation and cloud condensation nuclei but large biases for other radiative and cloud variables. The performance of aerosol optical depth and latent/sensible heat flux varies for different simulation periods. Among all variables evaluated, wind speed at 10-m, precipitation, surface concentrations of CO, NO, NO2, SO2, O3, PM2.5, and PM10, aerosol optical depth, cloud optical thickness, cloud condensation nuclei, and column NO2 show moderate-to-strong sensitivity to spatial grid resolutions. The use of finer grid resolutions (3- or 9-km) can generally improve the performance for those variables. While the performance for most of these variables is consistent with that over the U.S. and East Asia, several differences along with future work are identified to pinpoint reasons for such differences.

Understanding Spatial Variability of Air Quality in Sydney: Part 1—A Suburban Balcony Case Study

There is increasing awareness in Australia of the health impacts of poor air quality. A common public concern raised at a number of “roadshow” events as part of the federally funded Clean Air and Urban Landscapes Hub (CAUL) project was whether or not the air quality monitoring network around Sydney was sampling air representative of typical suburban settings. In order to investigate this concern, ambient air quality measurements were made on the roof of a two-storey building in the Sydney suburb of Auburn, to simulate a typical suburban balcony site. Measurements were also taken at a busy roadside and these are discussed in a companion paper (Part 2). Measurements made at the balcony site were compared to data from three proximate regulatory air quality monitoring stations: Chullora, Liverpool and Prospect. During the 16-month measurement campaign, observations of carbon monoxide, oxides of nitrogen, ozone and particulate matter less than 2.5-µm diameter at the simulated urban balcony site were comparable to those at the closest permanent air quality stations. Despite the Auburn site experiencing 10% higher average carbon monoxide amounts than any of the permanent air quality monitoring sites, the oxides of nitrogen were within the range of the permanent sites and the pollutants of greatest concern within Sydney (PM2.5 and ozone) were both lowest at Auburn. Similar diurnal and seasonal cycles were observed between all sites, suggesting common pollutant sources and mechanisms. Therefore, it is concluded that the existing air quality network provides a good representation of typical pollution levels at the Auburn “balcony” site.

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

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

Urban Air Quality in a Coastal City: Wollongong during the MUMBA Campaign

We present findings from the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign, which took place in the coastal city of Wollongong in New South Wales, Australia. We focus on a few key air quality indicators, along with a comparison to regional scale chemical transport model predictions at a spatial resolution of 1 km by 1 km. We find that the CSIRO chemical transport model provides accurate simulations of ozone concentrations at most times, but underestimates the ozone enhancements that occur during extreme temperature events. The model also meets previously published performance standards for fine particulate matter less than 2.5 microns in diameter (PM2.5), and the larger aerosol fraction (PM10). We explore the observed composition of the atmosphere within this urban air-shed during the MUMBA campaign and discuss the different influences on air quality in the city. Our findings suggest that further improvements to our ability to simulate air quality in this coastal city can be made through more accurate anthropogenic and biogenic emissions inventories and better understanding of the impact of extreme temperatures on air quality. The challenges in modelling air quality within the urban air-shed of Wollongong, including difficulties in accurate simulation of the local meteorology, are likely to be replicated in many other coastal cities in the Southern Hemisphere.