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 PM_2.5 (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 PM_2.5 concentrations.

Airborne particulate matter (PM) is a major health risk in urban settings. Ammonia (NH₃) from vehicle exhaust is an under-recognised ingredient in the formation of inorganic PM and there remains a shortage of data to properly quantify the role of NH₃ from vehicles in PM formation. An Open-path Fourier transform infra-red (OP-FTIR) spectrometer measured atmospheric NH₃, carbon monoxide (CO) and carbon dioxide (CO₂) at high temporal resolution (5 min) in Western Sydney over 11 months. The oxides of nitrogen (NO₂ and NO; NO_x) and sulphur dioxide (SO₂) were measured at an adjacent air quality monitoring station. NH₃ levels were maxima in the morning and evening coincident with peak traffic. During peak traffic NH₃:CO ratio ranged from 0.018 to 0.022 ppbv:ppbv. Results were compared with the Greater Metropolitan Region 2008 (GMR2008) emissions inventory. Measured NH₃:CO was higher during peak traffic times than the GMR2008 emissions estimates, indicating an underestimation of vehicle NH₃ emissions in the inventory. Measurements also indicated the urban atmosphere was NH₃ rich for the formation of ammonium sulphate ((NH₄)₂SO₄) particulate was SO₂ limited while the formation of ammonium nitrate (NH₄NO₃) was NH₃ limited. Any reduction in NO_x emissions with improved catalytic converter efficiency will be accompanied by an increase in NH₃ production and potentially with an increase in NH₄NO₃ particulate.

Although large areas of semi-arid land are extensively cropped, few studies have investigated the effect of nitrogen (N) fertiliser on nitrous oxide (N2O) emissions in these regions (Galbally et al. 2010). These emissions need to be measured in order to estimate N losses and calculate national greenhouse gas inventories. We examined the effect of different agronomic management practices applied to wheat (Triticum aestivum) grown on an alkaline Vertosol in south-eastern Australia on N2O emissions. In 2007, N2O emissions were measured over 12 months, during which N fertiliser (urea) was applied at sowing or N fertiliser plus supplementary irrigation (50 mm) was applied during the vegetative stage and compared with a treatment of no N fertiliser or irrigation. In a second experiment (2008), the effect of source of N on N2O emissions was examined. Wheat was grown on plots where either a pulse (field peas, Pisum sativum) or pasture legume (barrel medic, Medicago truncatula) crop had been sown in the previous season compared with a non-legume crop (canola, Brassica napus). To account for the N supplied by the legume phase, N fertiliser (50 kg N ha–1 as urea) was applied only to the wheat in the plots previously sown to canola. Fluxes of N2O were measured on a sub-daily basis (up to 16 measurements per chamber) by using automated chamber enclosures and a tuneable diode laser, and treatment differences were evaluated by a linear mixed model including cubic smoothing splines. Fluxes were low and highly variable, ranging from –3 to 28 ng N2O-N m–2 s–1. The application of N fertiliser at sowing increased N2O emissions for ~2 months after the fertiliser was applied. Applying irrigation (50 mm) during the vegetative growth stage produced a temporary (~1-week) but non-significant increase in N2O emissions compared with plots that received N fertiliser at sowing but were not irrigated. Including a legume in the rotation significantly increased soil inorganic N at sowing of the following wheat crop by 38 kg N ha–1 (field peas) or 57 kg ha–1 (barrel medic) compared with a canola crop. However, N2O emissions were greater in wheat plots where N fertiliser was applied than where wheat was sown into legume plots where no N fertiliser was applied. Over the 2 years of the field study, N2O emissions attributed to fertiliser ranged from 41 to 111 g N2O-N ha–1, and averaged of 75 g N2O-N ha–1 or 0.15% of the applied N fertiliser. Our findings confirm that the proportion of N fertiliser emitted as N2O from rainfed grain crops grown in Australian semi-arid regions is less than the international average of 1.0%.

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.

Detection and quantification of greenhouse-gas emissions is important for both compliance and environment conservation. However, despite several decades of active research, it remains predominantly an open problem, largely due to model errors and assumptions that appear at each stage of the inversion processing chain. In 2015, a controlled-release experiment headed by Geoscience Australia was carried out at the Ginninderra Controlled Release Facility, and a variety of instruments and methods were employed for quantifying the release rates of methane and carbon dioxide from a point source. This paper proposes a fully Bayesian approach to atmospheric tomography for inferring the methane emission rate of this point source using data collected during the experiment from both point- and path-sampling instruments. The Bayesian framework is designed to account for uncertainty in the parameterisations of measurements, the meteorological data, and the atmospheric model itself when performing inversion using Markov chain Monte Carlo (MCMC). We apply our framework to all instrument groups using measurements from two release-rate periods. We show that the inversion framework is robust to instrument type and meteorological conditions. From all the inversions we conducted across the different instrument groups and release-rate periods, our worst-case median emission rate estimate was within 36 % of the true emission rate. Further, in the worst case, the closest limit of the 95 % credible interval to the true emission rate was within 11 % of this true value.

The development and validation of management practices to mitigate greenhouse gas (GHG) emissions from livestock require accurate emission measurements. This study assessed the accuracy of a practical inverse dispersion modelling (IDM) technique to quantify methane (CH₄) emitted from a small cattle herd (16 animals) confined to a 63 m × 60 m experimental pen. The IDM technique calculates emissions from the increase in the CH₄ concentration measured downwind of the animals. The measurements were conducted for 7 d. Two types of open-path (OP) gas sensors were used to measure concentration in the IDM calculation: a Fourier transform infrared spectrometer (IDM-FTIR) or a CH₄ laser (IDM-Laser). The actual cattle emission rate was measured with a tracer-ratio technique using nitrous oxide (N₂O) as the tracer gas. We found very good agreement between the two IDM emission estimates (308.1 ± 2.1 – mean ± SE – and 304.4 ± 8.0 g CH₄ head⁻¹ d⁻¹ for the IDM-FTIR and IDM-Laser respectively) and the tracer-ratio measurements (301.9 ± 1.5 g CH₄ head⁻¹ d⁻¹). This study suggests that a practical IDM measurement approach can provide an accurate method of estimating cattle emissions.