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Predicting future air quality in Australian cities dominated by eucalypt emissions requires an understanding of their emission potentials in a warmer climate. Here we measure the temperature response in isoprene emissions from saplings of four different Eucalyptus species grown under current and future average summertime temperature conditions. The future conditions represent a 2050 climate under Representative Concentration Pathway 8.5, with average daytime temperatures of 294.5 K. Ramping the temperature from 293 to 328 K resulted in these eucalypts emitting isoprene at temperatures 4–9 K higher than the default maximum emission temperature in the Model of Emissions of Gases and Aerosols from Nature (MEGAN). New basal emission rate measurements were obtained at the standard conditions of 303 K leaf temperature and 1000 µmol m -2 s -1 photosynthetically active radiation and converted into landscape emission factors. We applied the eucalypt temperature responses and emission factors to Australian trees within MEGAN and ran the CSIRO Chemical Transport Model for three summertime campaigns in Australia. Compared to the default model, the new temperature responses resulted in less isoprene emission in the morning and more during hot afternoons, improving the statistical fit of modelled to observed ambient isoprene. Compared to current conditions, an additional 2 ppb of isoprene is predicted in 2050, causing hourly increases up to 21 ppb of ozone and 24-hourly increases of 0.4 µgm-3 of aerosol in Sydney. A 550 ppm CO2 atmosphere in 2050 mitigates these peak Sydney ozone mixing ratios by 4 ppb. Nevertheless, these forecasted increases in ozone are up to one-fifth of the hourly Australian air quality limit, suggesting that anthropogenic NOx should be further reduced to maintain healthy air quality in future. [ABSTRACT FROM AUTHOR]

South-east Australia, characterized by arid and semi-arid climate, has experienced large-scale rainfall reductions in recent decades. Larger temporal and spatial drought conditions are predicted in future. The temperate south east coastal zone is characterized by dense forests of Eucalyptus. Drought conditions have implications for the functioning of these indigenous ecosystems, and for emissions of reactive gases that are upwind of major metropolitan regions along the eastern coast. Here, we focus on the impact of drought on the emission of isoprene, a volatile organic compound emitted by a range of trees and shrubs. Previous model calculations grossly overestimate observations of the isoprene mixing ratio, potentially due to overestimated emission factors for native vegetation, but could also be due to drought-induced isoprene emission reductions. We develop the implementation of the Model of Emissions of Gases and Aerosols from Nature (MEGAN) within the CSIRO Chemical Transport Model to include a parameterization of drought using soil moisture. We test this parameterization using two approaches. First, we drive MEGAN using soil moisture fields from two Australian land surface models achieving reductions in isoprene emissions of 24–52% during summer. Second, we use a simple statistical approach to nudge model soil moisture towards satellite observations from the Soil Moisture and Ocean Salinity (SMOS) instrument. This work is the first application of SMOS towards isoprene emission modelling, providing a constraint on surface soil moisture which extends to global scales. Applying these soil moisture approaches, domain average isoprene emissions reduce by 38–58% in summer. Using these results, errors in basal emissions are likely in the region of 40%. Comparison of modelled soil moisture to observations using root density weighted averages across depths of 4 m showed minor differences of up to 0.04 m3 m−3. We find that the choice of land surface model used in the SMOS assimilations has a greater impact on isoprene emissions than adjusting either the nudging strength or the number of soil levels these satellite data may influence. However there are only small differences of 3% when using hourly or 24-hourly soil moisture input data to drive the emission calculations, suggesting that the lower temporal availability of satellite data does not reduce model quality. As the spatial resolution of satellite observations of atmospheric composition and land surface properties begin to approach the resolution of regulatory air quality models, we anticipate that these data will improve model predictive skills further. Image 1 • Decreased isoprene emissions in arid Australia using soil moisture function. • Developed technique to nudge model soil moisture towards satellite SMOS data. • Isoprene emissions decrease by 38–58% and reduce modelled bias. • 3% difference incurred when using daily (rather than hourly) soil moisture input. • Remaining error in basal isoprene emission factors approximately 40%. [ABSTRACT FROM AUTHOR]

We present the first representation of grass pollen in a 3-D dispersion model in Australia, tested using observations from eight counting sites in Victoria. The region's population has high rates of allergic rhinitis and asthma, and this has been linked to the high incidence of grass pollen allergy. Despite this, grass pollen dispersion in the Australian atmosphere has not been studied previously, and its source strength is untested. We describe 10 pollen emission source methodologies examining the strengths of different immediate and seasonal timing functions, and the spatial distribution of the sources. The timing function assumes a smooth seasonal term, modulated by an hourly meteorological function. A simple Gaussian representation of the pollen season worked well (average r=0.54), but lacked the spatial and temporal variation that the satellite-derived enhanced vegetation index (EVI) can provide. However, poor results were obtained using the EVI gradient (average r=0.35), which provides the timing when grass turns from maximum greenness to a drying and flowering period; this is due to noise in the spatial and temporal variability from this combined spatial and seasonal term. Better results were obtained using statistical methods that combine elements of the EVI dataset, a smooth seasonal term and instantaneous variation based on historical grass pollen observations (average r=0.69). The seasonal magnitude is inferred from the maximum winter-time EVI, whereas the timing of the season peak is based on the day of the year when the EVI falls to 0.05 below its winter maximum. Measurements are vital to monitor changes in the pollen season, and the new pollen measurement sites in the Victorian network should be maintained. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

• Soil emissions were a continuous source of NO to the atmosphere at both sites. • Meteorological conditions affect soil NO emission. • Diel variations of solar radiation and VPD partly explain soil NO diel patterns. • Diel patterns indicate both anthropogenic and biogenic sources of NO. • Soils contributed a small but significant fraction of atmospheric NO x at both sites. Nitrogen oxides, particularly NO and NO 2 (NO x), are primary air pollutants that also play an essential role in the atmospheric oxidation of volatile organic compounds, resulting in ozone and secondary organic aerosol formation. It is therefore critical to fully characterise NO x sources and sinks to understand tropospheric photochemistry and hence local- to regional-scale air quality. Human activities such as transport and power plants are well-known NO x emission sources in urban areas, whereas natural sources such as soils have been considered to contribute more substantially in rural and remote areas. However, soil NO emissions are poorly characterised and therefore underrepresented in models. To improve our understanding of soil as a source of NO, we measured diurnal patterns in soil NO concentrations at a suburban site in the UK and a remote field site in Australia to determine whether soils contribute to local atmospheric NO, and to identify the potential drivers of soil NO emissions. Mean soil NO concentrations in both UK campaigns 1.76 ± 0.92 ppb in summer and 0.91 ± 0.37 ppb in winter) were higher than those measured in Australia (0.73 ± 0.73 ppb). The diel patterns of NO concentrations (both sites) and emissions rates (Australia) showed a clear peak corresponding to local emission sources, but variation in NO was also related to either vapour pressure deficit (R 2 = 0.88 in UK summer, R 2 = 0.51 in Australia, both p < 0.05) or solar radiation (R 2 = 0.06 with p > 0.4 in UK summer, R 2 = 0.71 with p < 0.05 in Australia) during the daylight hours, indicating biogenic origin of soil NO. Our work demonstrates that biogenic soil emissions of NO are non-negligible, estimated at around 1.32 % of total NO emissions at the remote site, and 0.22 % at the urban site, and must be accounted for in global and regional atmospheric chemistry-climate modelling and NO x reduction strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

The world's most severe thunderstorm asthma event occurred in Melbourne, Australia on 21 November 2016, coinciding with the peak of the grass pollen season. The aetiological role of thunderstorms in these events is thought to cause pollen to rupture in high humidity conditions, releasing large numbers of sub-pollen particles (SPPs) with sizes very easily inhaled deep into the lungs. The humidity hypothesis was implemented into a three-dimensional atmospheric model and driven by inputs from three meteorological models. However, the mechanism could not explain how the Melbourne event occurred as relative humidity was very low throughout the atmosphere, and most available grass pollen remained within 40 m of the surface. Our tests showed humidity induced rupturing occurred frequently at other times and would likely lead to recurrent false alarms if used in a predictive capacity. We used the model to investigate a range of other possible pollen rupturing mechanisms which could have produced high concentrations of SPPs in the atmosphere during the storm. The mechanisms studied involve mechanical friction from wind gusts, electrical build up and discharge incurred during conditions of low relative humidity, and lightning strikes. Our results suggest that these mechanisms likely operated in tandem with one another, but the lightning method was the only mechanism to generate a pattern in SPPs following the path of the storm. If humidity induced rupturing cannot explain the 2016 Melbourne event, then new targeted laboratory studies of alternative pollen rupture mechanisms would be of considerable value to help constrain the parameterisation of the pollen rupturing process., Competing Interests: The authors have declared that no competing interests exist.