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Meeting the Paris Agreement on climate change requires substantial investments in low-emissions energy and significant improvements in end-use energy efficiency. These measures can also deliver improved air quality and there is broad recognition of the health benefits of decarbonising energy. Monetising these health benefits is an important part of a robust assessment of the costs and benefits of renewable energy and energy efficiency programs (clean energy programs (CEP)) and a variety of methods have been used to estimate health benefits at national, regional, continental and global scales. Approaches, such as unit damage cost estimates and impact pathways, differ in complexity and spatial coverage and can deliver different estimates for air pollution costs/benefits. To date, the monetised health benefits of CEP in Australia have applied international and global estimates that can range from 2–229USD/tCO2 (USD 2016). Here, we calculate the current health damage costs of coal-fired power in New South Wales (NSW), Australia’s most populous state, and the health benefits of CEP. Focusing on PM2.5 pollution, we estimate the current health impacts of coal-fired power at 3.20USD/MWh, approximately 10% of the generation costs, and much lower than previous estimates. We demonstrate the need for locally specific assessment of the air pollution benefits of CEP and illustrate that without locally specific information, the relative costs/benefits of CEP may be significantly over- or understated. We estimate that, for NSW, the health benefits from CEP are 1.80USD/MWh and that the current air pollution health costs of coal-fired power in NSW represent a significant unpriced externality.

Recently, there has been a substantial increase in the availability and use of low-cost particulate matter sensors in a wide range of air quality applications. They carry the promise of revolutionising air quality monitoring, yet considerable reservations exist regarding their performance and capabilities, thus hindering the broader-scale utilization of these devices. In order to address these concerns and assess their feasibility and accuracy for various applications, we evaluated six low-cost PM2.5 sensors (the Sharp GP2Y1010AU0F, Shinyei PPD42NS, Plantower PMS1003, Innociple PSM305, Nova SDS011 and Nova SDL607) in laboratory and field conditions using two combustion aerosols, concrete dust and ambient particles. In assessing the performance of these sensors, we focussed on indicators such as the linearity, accuracy and precision, critically differentiating between these qualities, and employed inter-comparison (the coefficient of determination, R2). In the laboratory, all sensors responded well, with an R2 > 0.91 when the PM2.5 concentration was > 50 µg m–3, as measured by the DustTrak. In particular, the PMS1003 demonstrated good accuracy and precision in both laboratory and ambient conditions. However, some limitations were noted for the tested sensors at lower concentrations. For example, the Sharp and Shinyei sensors showed poor correlations (R2

Air pollution has significant impacts on human health. Temperature inversions, especially near surface temperature inversions, can amplify air pollution by preventing convective movements and trapping pollutants close to the ground, thus decreasing air quality and increasing health issues. This effect of temperature inversions implies that trends in their frequency, strength and duration can have important implications for air quality. In this study, we evaluate the ability of three reanalysis-driven high-resolution regional climate model (RCM) simulations to represent near surface inversions at 9 sounding sites in southeast Australia. Then we use outputs of 12 historical and future RCM simulations (each with three time periods: 1990?2009, 2020?2039, and 2060?2079) from the NSW/ACT (New South Wales/Australian Capital Territory) Regional Climate Modelling (NARCliM) project to investigate changes in near surface temperature inversions. The results show that there is a substantial increase in the strength of near surface temperature inversions over southeast Australia which suggests that future inversions may intensify poor air quality events. Near surface inversions and their future changes have clear seasonal and diurnal variations. The largest differences between simulations are associated with the driving GCMs, suggesting that the large-scale circulation plays a dominant role in near surface inversion strengths. Fil: Ji, Fei. New South Wales. Office of Environment and Heritage; Australia Fil: Evans, Jason Peter. University of New South Wales; Australia Fil: Di Luca, Alejandro. University of New South Wales; Australia Fil: Jiang, Ningbo. New South Wales. Office of Environment and Heritage; Australia Fil: Olson, Roman. Yonsei University; Corea del Sur Fil: Fita Borrell, Lluís. Centre National de la Recherche Scientifique; Francia. Universite Pierre et Marie Curie; Francia. Laboratoire de Meteorologie Dynamique; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Argüeso, Daniel. Universidad de Las Islas Baleares. Departamento de Fisica; España Fil: Chang, Lisa T. C.. New South Wales. Office of Environment and Heritage; Australia Fil: Scorgie, Yvonne. New South Wales. Office of Environment and Heritage; Australia Fil: Riley, Matt. New South Wales. Office of Environment and Heritage; Australia

Ozone and particle pollution are of concern for the Sydney basin, in particular during warm months (November to March) when pollution levels can exceed national standards. Previous studies on the relationship between synoptic circulation and air quality focused on high pollution days or aggregated air quality conditions over the region as a whole. This study provides both temporal and spatial analyses of the synoptic processes affecting warm-month ozone and particle pollution in Sydney. A warm-month synoptic catalogue was developed by applying the self-organising map method to the NCEP/NCAR geopotential height reanalysis for south-east Australia. The catalogue was linked to mesoscale meteorological features such as drainage flows and sea breezes, and subsequently to the spatial variability in air quality across the Sydney basin. The typical synoptic types commonly associated with high or low ozone and PM10 levels, as well as variations in visibility, were identified. The results suggest that, due to Sydney's subtropical coastal-basin environment, the interaction between meso- and synoptic-scale features determine local air quality conditions in the region, rather than the synoptic conditions alone. Emissions from bushfires appear to have considerable impacts on the synoptic modulation to visibility and PM10 levels, with such impacts tending to be more at a local scale. In contrast, no comparable impacts were found for ozone pollution. For ozone and visibility, the probability for an exceedance day under some synoptic types varied considerably over time, implying that there might have been a shift in the role of synoptic modulation to local air quality associated with changes in air emissions profiles. This study provides a leap in our understanding of the relationship between synoptic circulation and air quality in a coastal-basin environment. The results are useful for improving air quality forecasting in Sydney, with the methodology developed readily applicable to similar regions elsewhere.

The increasing rate of urbanization requires effective and reliable techniques for air quality monitoring and control. For this, the Air Pollution Model and Chemical Transport Model (TAPM-CTM) has been developed and used in Australia with emissions inventory data, synoptic data and terrain data used as its input parameters. Since large uncertainties exist in the emissions inventory (EI), further refinements and improvements are required for accurate air quality prediction. This study evaluates the performance of urban air quality forecasting, using TAPM-CTM, and improves accuracy of air pollution estimation by using a two-stage optimization technique to upgrade EI with validation from monitoring data. The first stage is based on statistical analysis for EI correction and the second stage is based on the unscented Kalman filter (UKF) to take into account the spatio-temporal distributions of air pollutant levels utilizing a Matern covariance function. The predicted nitrogen monoxide (NO) and nitrogen dioxide (NO 2 ) concentrations with a priori emissions are first compared with observations at monitoring stations in the New South Wales (NSW). Ozone (O 3 ) is also considered since at the ground level it represents a major air pollutant affecting human health and the environment. In the second stage, with the improved EI, TAPM-CTM model errors are reduced further by using the UKF to calibrate EI. Results obtained show effectiveness of the proposed technique, which is promising for air quality inverse modeling, an important aspect of air pollution control in smart cities to achieve environmental sustainability.

Ozone and fine particles (PM2.5) are the two main air pollutants of concern in the New South Wales Greater Metropolitan Region (NSW GMR) due to their contribution to poor air quality days in the region. This paper focuses on source contributions to ambient ozone concentrations for different parts of the NSW GMR, based on source emissions across the greater Sydney region. The observation-based Integrated Empirical Rate model (IER) was applied to delineate the different regions within the GMR based on the photochemical smog profile of each region. Ozone source contribution was then modelled using the CCAM-CTM (Cubic Conformal Atmospheric model-Chemical Transport model) modelling system and the latest air emission inventory for the greater Sydney region. Source contributions to ozone varied between regions, and also varied depending on the air quality metric applied (e.g., average or maximum ozone). Biogenic volatile organic compound (VOC) emissions were found to contribute significantly to median and maximum ozone concentration in North West Sydney during summer. After commercial and domestic sources, power generation was found to be the next largest anthropogenic source of maximum ozone concentrations in North West Sydney. However, in South West Sydney, beside commercial and domestic sources, on-road vehicles were predicted to be the most significant contributor to maximum ozone levels, followed by biogenic sources and power stations. The results provide information that policy makers can use to devise various options to control ozone levels in different parts of the NSW Greater Metropolitan Region.

The two-fold utility (data projection and cluster analysis) of a two-phase batch self-organizing map (SOM) procedure (CP2) has been previously explored using the NCEP/NCAR geopotential height data for east Australia. That study focused on examining the performance of CP2 in comparison with a traditional cluster analysis procedure, CP1, for the purpose of synoptic typing. The present paper provides additional documentation on the implementation of CP2 for the same region, with broader considerations on the effect of SOM map size, seasonality, data standardization and the choice of neighbourhood functions. A total of 215 SOMs (classifications) were trained through CP2 with various data processing and parameter settings. The examination of these SOMs shows that the two-fold utility of CP2 leads to supplementary visualization of the dominant synoptic patterns over the study region. For SOMs of the same map size (i.e. number of synoptic types), cluster analysis via CP2 provides data groupings with relatively high accuracy and large separation but reduced level of pattern self-organization, while data projection via CP2 tends to create data groupings with a high level of pattern self-organization but reduced accuracy and separation. The choice of map size affects the accuracy, separation and self-organization of data groupings. As a compromise, a map size of 10–20 for cluster analysis and 20–30 for data projection is recommended for the study region. To account for the seasonality and latitudinal heterogeneity in the activity of synoptic systems, a relatively larger SOM size is needed to capture typical synoptic features prevailing in different seasons. Data standardization helps to provide a relatively balanced representation between larger-scale synoptic systems (e.g. anticyclones) and smaller-scale synoptic features (e.g. thermal lows), and also improves the level of pattern self-organization on the SOM across seasons. The additional documentation in this paper encourages a wider application of CP2 in environmental research.

Exposure to particulate matter results in adverse health outcomes, especially in sensitive members of the community. Many communities that co-exist with industry are concerned about the perceived impact of emissions from that industry on their health. Such concerns have resulted in two studies in the Hunter Valley of New South Wales, Australia. The chemical composition of samples of particulate matter, collected over two 12-month sampling periods (2012 and 2014&ndash, 2015) at six sites in the Hunter Valley and across two size fractions (PM2.5 and PM2.5&ndash, 10) were input to a receptor model to determine the source of particulate matter influencing particle composition at the sites. Fourteen factors were found to contribute to particle mass. Of these, three source profiles common to all sites, size fractions, and sampling periods were sea salt, industry-aged sea salt and soil. Four source profiles were common across all sites for PM2.5 including secondary sulphate, secondary nitrate, mixed industry/vehicles, and woodsmoke. One source profile (other biomass smoke) was only identified in PM2.5 at Singleton and Muswellbrook, two source profiles (mixed industry/shipping and vehicles) were only identified in PM2.5 at Newcastle, Beresfield, Mayfield, and Stockton, and one source (primary nitrate) was only identified at Stockton in PM2.5. Three sources (bioaerosol, light absorbing particles (coal dust), and industry) were only identified in the PM2.5&ndash, 10 size fraction at Mayfield and Stockton. The contribution of the soil factor to PM2.5 mass was consistent across the sites, while the fresh sea salt factor decreased with distance from the coast from 23% at Stockton to 3% at Muswellbrook, and smoke increased with distance from the coast. Primary industry was greatest at Stockton (due to the influence of ammonium nitrate emitted from a prilling tower) and lowest inland at Muswellbrook. In general, primary emissions across the sites accounted for 30% of the industry sources. The largest contribution to PM2.5 was from secondary sources at all sites except at Muswellbrook, where woodsmoke and industry sources each made an equal contribution of 40%. In general, secondary reactions accounted for approximately 70% of the industry source, although at Stockton, with the presence of the prilling tower, this split was 50% primary and 50% secondary and at Muswellbrook, the split was 20% primary and 80% secondary. These findings add to the evidence base required to inform policies and programs that will improve air quality in the Hunter Valley.

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.