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The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase in mining activities, PM10 (air-borne particles with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The present study was initiated to quantitatively examine the spatial and temporal variability of PM10 pollution in the region. An earlier paper of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns were quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology–air pollution relationships were visualised and interpreted on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs. the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs. elevated PM10 pollution in the valley. Two local meteorological patterns, the hot–dry–northwesterly wind conditions and the hot–dry–calm conditions, were found to be the most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of an eastward migrating continental high-pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere. [ABSTRACT FROM AUTHOR]

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase in mining activities, PM10 (airborne particles with an aerodynamic diameter of less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley: one in the west/northwest and the other in the southeast. Wavelet analysis revealed the annual cycle to be the most persistent temporal mode of PM10 variability in both subregions, with intermittent signals also observed at time scales of around 120, 30~90, and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere. [ABSTRACT FROM AUTHOR]

Dust storms and wildfires occur frequently in south-eastern Australia. Their effects on the ecology, environment and population exposure have been the focus of many studies recently. Dust storms do not emit ground-sequestered carbon, but wildfires emit significant quantities of carbon into the atmosphere. However, both natural events promote phytoplankton growth in water bodies because carbon, and other trace elements such as iron, deposit on the surface water of oceans. Carbon dioxide is reabsorbed by phytoplankton via photosynthesis. The carbon balance cycle due to dust storms and wildfires is not well known. Recent studies on the carbon emission of the 2019–2020 summer wildfires in eastern Australia indicated that this megafire event emitted approximately 715 million tonnes of CO2 (195 Tg C) into the atmosphere from burned forest areas. This study focusses on the association of dust storms and wildfires in southeastern Australia with phytoplankton growth in the Tasman Sea due to the February 2019 dust storm event and the 2019–2020 Black Summer wildfires. Central Australia and western New South Wales were the sources of the dust storm emission (11 to 16 February 2019), and the Black Summer wildfires occurred along the coast of New South Wales and Victoria (from early November 2019 to early January 2020). The WRF-Chem model is used for dust storm simulation with the AFWA (Air Force Weather Agency of the US) dust emission version of the GOCART model, and the WRF-Chem model is used for wildfire simulation with FINN (Fire Emission Inventory from NCAR) emission data. The results show the similarities and differences in the deposition of particulate matter, phytoplankton growth and carbon reabsorption patterns in the Tasman Sea from these events. A higher rate of deposition of PM2.5 on the ocean surface corresponds to a higher rate of phytoplankton growth. Using the WRF-Chem model, during the 5-day dust storm event in February 2019, approximately ~1230 tons of total dust was predicted to have been deposited in the Tasman Sea, while ~132,000 tons of PM10 was deposited in the early stage of the wildfires from 1 to 8 November 2019. [ABSTRACT FROM AUTHOR]

Soil-derived dust emissions have been widely associated with health and environmental problems and should therefore be accurately and reliably estimated and assessed. Of these emissions, the inhalable PM10 and PM2.5 are difficult to estimate. Consequently, to calculate PM10 and PM2.5 emissions from soil erosion, an approach based on an artificial neural network (ANN) model which provides a multilayered, fully connected framework that relates input parameters and outcomes was proposed in this study. Owing to the difficulty in obtaining the actual emissions of soil-derived PM10 and PM2.5 over a broad area, the PM10 and PM2.5 simulated results of the ANN model were compared with the published results simulated by the widely used wind erosion prediction system (WEPS) model. The PM10 and PM2.5 emission results, based on the WEPS, agreed well with the field data, with R2 values of 0.93 and 0.97, respectively, indicating the potential for using the WEPS results as a reference for training the ANN model. The calculated r, RMSE and MAE for the results simulated by the WEPS and ANN were 0.78, 3.37 and 2.31 for PM10 and 0.79, 1.40 and 0.91 for PM2.5, respectively, throughout Southern Xinjiang. The uncertainty of the soil-derived PM10 and PM2.5 emissions at a 95% CI was (−66–106%) and (−75–108%), respectively, in 2016. The results indicated that by using parameters that affect soil erodibility, including the soil pH, soil cation exchange capacity, soil organic content, soil calcium carbonate, wind speed, precipitation and elevation as input factors, the ANN model could simulate soil-derived particle emissions in Southern Xinjiang. The results showed that when the study domain was reduced from the entire Southern Xinjiang region to its five administrative divisions, the performance of the ANN improved, producing average correlation coefficients of 0.88 and 0.87, respectively, for PM10 and PM2.5. The performances of the ANN differed by study period, with the best result obtained during the sand period (March to May) followed by the nonheating (June to October) and heating periods (November to February). Wind speed, precipitation and soil calcium carbonate were the predominant input factors affecting particle emissions from wind erosion sources. The results of this study can be used as a reference for the wind erosion prevention and soil conservation plans in Southern Xinjiang. [ABSTRACT FROM AUTHOR]

A better understanding of background tropospheric ozone delivers multiple benefits. Robust estimates of regional background ozone are required to understand the limits of anthropogenic emissions controlling ozone reduction. Long-term estimates of background ozone assist in characterising changes in atmospheric composition and can help quantify the influence of human activity on the atmosphere. Background tropospheric ozone measurements representative of continental air masses are scarce in Australia. Here, we use k-means clustering to identify a cluster of measurements from the long-term air quality monitoring station at Oakdale, NSW, which are likely to be representative of background air. The cluster is associated with NOx-limited air masses of continental origin. From this analysis, we estimate background ozone representative of Eastern Australia. We find recent (2017–2022) mean ozone mixing ratios of 28.5 ppb and identify a statistically significant (α = 0.05) trend in the mean of +1.8 (1.0–2.8) ppb/decade. Our methods demonstrate that some long-term monitoring stations within or near urban areas can provide suitable conditions and datasets for regional Global Atmosphere Watch monitoring. [ABSTRACT FROM AUTHOR]

The emission of black carbon (BC) particles, which cause atmospheric warming by affecting radiation budget in the atmosphere, is the result of an incomplete combustion process of organic materials. The recent wildfire event during the summer 2019–2020 in south-eastern Australia was unprecedented in scale. The wildfires lasted for nearly 3 months over large areas of the two most populated states of New South Wales and Victoria. This study on the emission and dispersion of BC emitted from the biomass burnings of the wildfires using the Weather Research Forecast–Chemistry (WRF–Chem) model aims to determine the extent of BC spatial dispersion and ground concentration distribution and the effect of BC on air quality and radiative transfer at the top of the atmosphere, the atmosphere and on the ground. The predicted aerosol concentration and AOD are compared with the observed data using the New South Wales Department of Planning and Environment (DPE) aethalometer and air quality network and remote sensing data. The BC concentration as predicted from the WRF–Chem model, is in general, less than the observed data as measured using the aethalometer monitoring network, but the spatial pattern corresponds well, and the correlation is relatively high. The total BC emission into the atmosphere during the event and the effect on radiation budget were also estimated. This study shows that the summer 2019–2020 wildfires affect not only the air quality and health impact on the east coast of Australia but also short-term weather in the region via aerosol interactions with radiation and clouds. [ABSTRACT FROM AUTHOR]

Although carbonyl compounds are a key species with atmospheric oxidation capacity, their concentrations and sources have not been sufficiently characterized in various atmospheres, especially in desert areas. In this study, atmospheric carbonyl compounds were measured from 16 May to 15 June 2018 in Tazhong in the central Taklimakan Desert, Xinjiang Uygur Autonomous Region, China. Concentrations, chemical compositions, and sources of carbonyl compounds were investigated and compared with those of different environments worldwide. The average concentration of total carbonyls during the sampling period was 11.79 ± 4.03 ppbv. Formaldehyde, acetaldehyde, and acetone were the most abundant carbonyls, with average concentrations of 6.08 ± 2.37, 1.68 ± 0.78, and 2.52 ± 0.68 ppbv, respectively. Strong correlations between formaldehyde and other carbonyls were found, indicating same or similar sources and sinks. A hybrid single-particle Lagrangian integrated trajectory was used to analyze 72 h back trajectories. The values of C1/C2 (formaldehyde to acetaldehyde, 3.22–4.59) and C2/C3 (acetaldehyde to propionaldehyde, 15.00–17.03) from different directions and distances of the trajectories were consistent with the characteristics of a remote area. Relative to various environments, the carbonyl concentration in the Tazhong desert site was lower than that in urban areas and higher than that in suburban and remote areas, implying contributions from local primary and secondary sources. The obtained data can be used to improve the source and sink estimation of carbonyls at the regional scale. [ABSTRACT FROM AUTHOR]

The planetary boundary layer height (PBLH) is one of the key factors in influencing the dispersion of the air pollutants in the troposphere and, hence, the air pollutant concentration on ground level. For this reason, accurate air pollutant concentration depends on the performance of PBLH prediction. Recently, ceilometers, a lidar instrument to measure cloud base height, have been used by atmospheric scientists and air pollution control authorities to determine the mixing level height (MLH) in improving forecasting and understanding the evolution of aerosol layers above ground at a site. In this study, ceilometer data at an urban (Lidcombe) and a rural (Merriwa) location in New South Wales, Australia, were used to investigate the relationship of air pollutant surface concentrations and surface meteorological variables with MLH, to validate the PBLH prediction from two air quality models (CCAM-CTM and WRF-CMAQ), as well as to understand the aerosol transport from sources to the receptor point at Merriwa for the three case studies where high PM10 concentration was detected in each of the three days. The results showed that surface ozone and temperature had a positive correlation with MLH, while relative humidity had negative correlation. For other pollutants (PM10, PM2.5, NO2), no clear results were obtained, and the correlation depended on the site and regional emission characteristics. The results also showed that the PBLH prediction by the two air quality models corresponded reasonably well with the observed ceilometer data and the cause and source of high PM10 concentration at Merriwa can be found by using ceilometer MLH data to corroborate back trajectory analysis of the transport of aerosols to the receptor point at Merriwa. Of the three case studies, one had aerosol sources from the north and north west of Merriwa in remote NSW, where windblown dust is the main source, and the other two had sources from the south and south east of Merriwa, where anthropogenic sources dominate. [ABSTRACT FROM AUTHOR]

A measurement program designed to evaluate health impacts or benefits of using ethanol blend petrol examined exhaust and evaporative emissions from 21 vehicles representative of the current Australian light duty petrol (gasoline) vehicle fleet using a composite urban emissions drive cycle. The fuels used were unleaded petrol (ULP), ULP blended with either 5% ethanol (E5) or 10% ethanol (E10). The resulting data were combined with inventory data for Sydney to determine the expected fleet emissions for different uptakes of ethanol blended fuel. Fleet ethanol compatibility was estimated to be 60% for 2006, and for the air quality modelling it was assumed that in 2011 over 95% of the fleet would be ethanol compatible. Secondary organic aerosol (SOA) formation from ULP, E5 and E10 emissions was studied under controlled conditions by the use of a smog chamber. This was combined with meteorological data from Sydney for February 2004 and the emission data (both measured and inventory data) to model pollutant concentrations in Sydney's airshed for 2006 and 2011. These concentrations were combined with the population distribution to evaluate population exposure to the pollutant. There is a health benefit to the Sydney population arising from a move from ULP to ethanol blends in spark-ignition vehicles. Potential health cost savings for Urban Australia (Sydney, Melbourne, Brisbane and Perth) are estimated to be A$39 million (in 2007 dollars) for a 50% uptake (by ethanol compatible vehicles) of E10 in 2006 and $42 million per annum for a 100% take up of E10 in 2011. Over 97% of the estimated health savings are due to reduced emissions of PM2.5 and consequent reduced impacts on mortality and morbidity (e.g., asthma, cardiovascular disease). Despite more petrol-driven vehicles predicted for 2011, the quantified health impact differential between ULP and ethanol fuelled vehicles drops from 2006 to 2011. This is because modern petrol vehicles, with lower emissions than their older counterparts, will make up a higher proportion of the fleet in the future. Hence the beneficial effects of reductions in particulate matter become less significant as the fleet as a whole produces lower emissions. [ABSTRACT FROM AUTHOR]

Dust storms originating from Central Australia and western New South Wales frequently cause high particle concentrations at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affected air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model—Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in the WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints, namely mortality, respiratory and cardiac disease hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. Generally, the health impact is similar in order of magnitude to that caused by biomass burning events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory disease hospitalisation for this dust event (161) compared to the fire event (24). [ABSTRACT FROM AUTHOR]

Biomass burnings either due to Hazards Reduction Burnings (HRBs) in late autumn and early winter or bushfires during summer periods in various part of the world (e.g., CA, USA or New South Wales, Australia) emit large amount of gaseous pollutants and aerosols. The emissions, under favourable meteorological conditions, can cause elevated atmospheric particulate concentrations in metropolitan areas and beyond. One of the pollutants of concern is black carbon (BC), which is a component of aerosol particles. BC is harmful to health and acts as a radiative forcing agent in increasing the global warming due to its light absorption properties. Remote sensing data from satellites have becoming increasingly available for research, and these provide rich datasets available on global and local scale as well as in situ aethalometer measurements allow researchers to study the emission and dispersion pattern of BC from anthropogenic and natural sources. The Department of Planning, Industry and Environment (DPIE) in New South Wales (NSW) has installed recently from 2014 to 2019 a total of nine aethalometers to measure BC in its state-wide air quality network to determine the source contribution of BC and PM2.5 (particulate Matter less than 2.5 μm in diameter) in ambient air from biomass burning and anthropogenic combustion sources. This study analysed the characteristics of spatial and temporal patterns of black carbon (BC) in New South Wales and in the Greater Metropolitan Region (GMR) of Sydney, Australia, by using these data sources as well as the trajectory HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) modelling tool to determine the source of high BC concentration detected at these sites. The emission characteristics of BC in relation to PM2.5 is dependent on the emission source and is analysed using regression analysis of BC with PM2.5 time series at the receptor site for winter and summer periods. The results show that, during the winter, correlation between BC and PM2.5 is found at nearly all sites while little or no correlation is detected during the summer period. Traffic vehicle emission is the main BC emission source identified in the urban areas but was less so in the regional sites where biomass burnings/wood heating is the dominant source in winter. The BC diurnal patterns at all sites were strongly influenced by meteorology. [ABSTRACT FROM AUTHOR]

As atmospheric fresh soot particles age, they become coated with other chemical species. This transforms their physicochemical properties and affects their optical characteristics, which is of great importance to air quality, the environment and climate change. One of the predominantly occurring states of soot particles in the ambient environment is the core-shell mixing state. In this study, we used the core-shell model to calculate the optical absorption, scattering and extinction efficiency, absorption proportion and absorption exponent of coated soot particles. We then investigated the effects of different core sizes (D0), incident wavelengths (λ), coating materials and coating thicknesses on these optical characteristics. Absorption efficiency and absorption proportion of soot particles decreased as the coating became thicker, at core sizes of D0 = 20, 50 and 100 nm and λ = 405, 532 and 781 nm, regardless of the type of coating material. As the coating thickness increased, the absorption exponent (β) of inorganic-coated soot particles tended to rise and then fall, while the β value of organic-coated soot particles kept increasing. Our results advance our scientific understanding of the interaction of optical properties with chemical composition, mixing state, and aging processes of soot particles in the atmosphere. [ABSTRACT FROM AUTHOR]

A field sampling campaign of volatile organic compounds (VOCs) was conducted during ozone polluted days at three sites of botanic gardens (HP), industrial areas (XS), and traffic residential mixed areas (ZH) in Hangzhou. The sampling was performed using stainless steel canisters from 6:00 to 20:00 synchronously with a time interval of 2 h on 17 May, 26 June, 20 July, 24 August, and 26 September 2018. A total of 107 species of VOCs for each sample were quantified using two standard gases with a pre-concentrator coupled by GC/MS. The Positive Matrix Factorization (PMF) model was used to identify the major VOC sources and assess their contribution to VOC concentrations. The effects of VOCs on O3 formation were investigated, based on propylene-equivalent concentrations (Prop-E), ozone formation potential (OFP), and Smog Production Model (SPM). It was found that the concentration of ozone during the sampling days tended to be highest in the downwind area while the concentrations of VOCs and NO2 in HP were rather low. The most reactive species were isoprene, ethylene, m-xylene, toluene, and propylene. The average total VOC volume mixing ratios in HP, XS, and ZH were 32.00, 36.63, and 50.34 ppbv, respectively. Bimodal profiles of propane and n-butane were exhibited in ZH while unimodal diurnal variation of isoprene was performed in HP. Liquefied petroleum gas/natural gas (LPG/NG) usage, aged background, and secondary source were identified as the major contributors to total VOCs in Hangzhou, accounting for 19.65%, 15.53%, and 18.93%, respectively. [ABSTRACT FROM AUTHOR]