Upper Hunter Valley Particle Characterization Study 2nd Progress Report

The objective of the Upper Hunter Valley Particle Characterization Study is to determine the major components and sources of particulate matter (as PM2.5 – particles with a diameter of less than 2.5 micrometres) in the two main population centres in the Upper Hunter Valley, namely Singleton and Muswellbrook. This 2nd Progress Report presents an update on the project, some preliminary results, and a description of the CSIRO analysis technique.© 2012 CSIR

Upper Hunter Valley Particle Characterization Study 3rd Progress Report

The objective of the Upper Hunter Valley Particle Characterization Study is to determine the major components and sources of particulate matter (as PM2.5 – particles with a diameter of less than 2.5 micrometres) in the two main population centres in the Upper Hunter Valley, namely Singleton and Muswellbrook. This 3rd Progress Report presents an update on the project and some quality checks of the data.© 2013 CSIR

Upper Hunter Valley particle characterization study: 1st progress report – site commissioning and methodology

The objective of the Upper Hunter Valley Particle Characterization Study is to determine the major components and sources of particulate matter (as PM2.5 – particles with a diameter of less than 2.5 micrometres) in the two main population centres in the Upper Hunter Valley, namely Singleton and Muswellbrook. This 1st Progress Report outlines the design of the project, the methodology, and the commissioning phase.© 2012 CSIR

Sydney particle characterisation study PM2.5 source apportionment in the Sydney Region between 2000 and 2014

The Australian Nuclear Science and Technology Organisation (ANSTO) has been applying accelerator based nuclear techniques to the characterisation of fine PM2.5 ambient air pollution since the early 1990s. Over the decades large long-term databases have been acquired at dozens of sites both in Australia and internationally on the PM2.5 mass together with over 23 different elemental and chemical species that make up this fine particle pollution. In this study we used data previously collected by ANSTO from four of our long-term sampling sites covering the period from 1 January 2000 to 31 December 2014. Positive matrix factorisation (PMF) source apportionment techniques were applied to this data to identify seven different source components or fingerprints that make up the measured total PM2.5mass at each of these four sites. The primary aim of this study was to: convert the existing 15-year PM2.5 mass and elemental datasets for four given sites in the Sydney basin into identifiable source fingerprints quantify the absolute and the percentage contribution of each of these fingerprints to the total fine PM2.5 mass provide seasonal and annual variations for each of the source fingerprints provide a readily accessible database containing the daily source fingerprints and their contributions covering the 15-year period from 2000–2014 for four given sites in the Sydney basin if possible, identify and quantify the major contributors of fine particle pollution to the ambient air quality in Sydney. Typically fine particles were collected over 24-hour periods twice a week (104 filters per year) at Lucas Heights, Richmond, Mascot and Liverpool sites over a 15-year period from 2000 to 2014. In all, around 6000 sampling days are represented by this study. Each of these filters was analysed for the 23 elemental and chemical species: hydrogen (H), sodium (Na), al uminium (Al), silicon (Si), phosphorous (P), sulfur (S), chlorine (Cl), potassium (K), calcium (Ca), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), selenium (Se), bromium (Br), lead (Pb), bl ack carbon (BC) and total nitrogen (TotN) to concentrations down to 1ngm–3 of air sampled. TotN is the total nitrogen from ammonium and nitrate ions. © 2016 ANST

Can IBA techniques quantify the contributions of deserts, winter domestic heating and coal fired power stations to the ambient fine particle air pollution concentrations in the Sydney Basin?

ANSTO has used accelerator based ion beam analysis (IBA) techniques to characterise, fingerprint and source fine particles in and around Australia since the early 1990's. This large database covering many years allows us to now look quantitatively at fine particle sources, including automobiles, smoke, sea spray, soils and industrial emissions. This talk will discuss the accelerator based IBA techniques and how they are used to identify the contributions of windblown soils, wood heating and coal fired power stations to ambient air pollution in the Sydney Basin between 1998 and the present

Strength-endurance training reduces the hamstrings strength decline following simulated football competition in female players

Hamstring strains are the most common injury in multiple sprint sports, with inadequate eccentric hamstring strength and fatigue identified as important risk factors. Resistance training interventions aimed at reducing injury risk typically focus on the development of maximum strength, while little is known about the impact of training on hamstring fatigue resistance. The present study compared the effects of strength endurance (SE) with a strength intervention (S) on the eccentric hamstring strength decline induced by a simulated soccer match. Twenty-one female soccer players were randomly assigned to a S group (n = 10) or a SE group (n = 11). Hamstrings and quadriceps isokinetic concentric and eccentric peak torque (PT) were assessed at 120°.s-1 and hamstrings-to-quadriceps ratio (HEcc:QCon) calculated, pre- and immediately post a 90-min simulated match (BEAST90). This was repeated following a 7-week intervention of either three to five sets of 6RM leg curl and stiff-leg deadlift with 3-min inter-set rest (S), or the same exercises performed using three sets of 12–20 RM with 45–90 s inter-set rest (SE). At baseline, the simulated match led to significant declines in hamstrings eccentric peak torque (EccPT) in both groups in both dominant (D) and non-dominant (ND) legs [SE: (D: −15.5, ND: −15.6%), P = 0.001 to 0.016; S: (D: −12.3%, ND: −15.5%), P = 0.001 to 0.018]. After the 7-week intervention, we observed a group*intervention*match interaction such that there was no significant decline in EccPT in the SE group following the simulated match (D: 5.3%, ND: 2.0%), but there remained significant declines in the S group (D: −14.2%, ND: −15.5%, P = 0.018–0.001). Similarly, in the SE group, there was a significant decrease in the HEcc:QCon in D before (−14.2%, P = 0.007), but not after the training intervention, whereas declines were observed in the S group both at baseline, and following the intervention (D: −13.9%, ND: −15.6%, P = 0.045). These results demonstrate that SE training can reduce the magnitude of the EccPT decline observed during soccer competition. As inadequate eccentric strength and fatigue are both risk factors for hamstring injury, SE training should be considered along with the development of peak eccentric strength, as a component of programs aimed at reducing injury risk in multiple-sprint sports

Long term fine aerosols at the Cape Grim global baseline station: 1998 to 2016

Fine aerosol measurements have been undertaken at the Cape Grim global baseline station since 1992. Ion beam analysis techniques were then used to determine the elemental composition of the samples from which source fingerprints can be determined. In this study six source fingerprints were identified to contribute to the measurements of PM2.5 at Cape Grim (from 1998 to 2016); fresh sea salt (57%), secondary sulfate and nitrates (14%), smoke (13%), aged sea salt (the product of NaCl reactions with SO2; 12%), soil dust (2.4%) and industrial metals (1.5%). Back trajectory analysis showed that local Tasmanian sources of soil dust contributed to the high soil dust measurements. High measurements of secondary aerosols were recorded when air masses were arriving from the Australian mainland, in the direction of the Victorian power stations. When air masses were arriving from the baseline sector, the maximum concentration of aged sea salt was 1.3 μg/m3, compared to overall maximum of 4.9 μg/m3. For secondary sulfates and nitrates the maximum concentrations were 2.5 and 7.5 μg/m3 from the baseline sector and overall, respectively. While measurements at Cape Grim can be affected from long range transport from mainland Australia and some local Tasmanian sources, the average concentrations of anthropogenic sources are still considerably lower than those measured at more populated areas. For example, at Lucas Heights (located south-west of the Sydney central business district, with little local sources) the average concentrations of secondary sulfates/nitrates and aged sea air were 1.4 and 1.0 μg/m3, respectively; compared to average concentrations of 0.8 and 0.6 μg/m3, at Cape Grim. The average concentrations of smoke were compatible at the two sites. The impact of primary aerosols from vehicle exhaust at Cape Grim was limited and no corresponding fingerprint was resolved.Crown Copyright © 2017 Published by Elsevier Lt

Particulate pollution in the Sydney Region: source diagnostics and synoptic controls

Airborne particulate matter (PM2.5) was sampled at Richmond and Liverpool, located in the Sydney Basin, Australia, and ion beam analysis was used to obtain the elemental composition. Using self-organising maps to classify synoptic weather systems, it was found that high PM2.5 concentrations were associated with high pressure systems located to the east of the sampling sites. The highest median sulfur was associated with weak synoptic conditions and high soil dust days were more often associated with frontal systems. To investigate the effect of local flows in the Sydney Basin, the Weather Research and Forecasting model (WRF) was used to generate meteorological data of 12 km resolution. A comparison was made between back trajectories generated using the higher-resolution WRF data, the 0.5° by 0.5° Climate Forecast System data and the 1° by 1° Global Data Assimilation System data. It was found that for high soil dust days, there were small differences between the different back trajectories. However, under weak synoptic conditions (high sulfur days), the back trajectories generated from higher resolution data showed larger variations over a 24 hr period. This was attributed to the meandering of local winds and seabreezes. Lower altitude back trajectories, generated from low resolution data, passed more often over the power stations located on the western side of the Great Dividing Range (while the sampling sites are on the east). This demonstrates the need for higher resolution meteorological data for generating low altitude back trajectories when the source and receptor are separated by hilly terrain. In estimating the number of high sulfur days for which a power station was crossed, there was up to 20% difference at Liverpool and up to 10% difference at Richmond, between back trajectories starting at different altitudes and generated from meteorological data of three different resolutions

The IAEA/RCA fine and coarse PMF receptor fingerprint database

This document accompanies the IAEA Master Positive Matrix Factorisation (PMF) Databases (fine and coarse). These databases have been generated from the 14 member state RCA Project RAC/07/015, “Characterization and Source Identification of Particulate Air Pollution in the Asia Region”. It fulfils the obligation under an IAEA contract to provide a fine and coarse ambient air PMF database with explanatory notes by February 2016 to the IAEA. The aim of this document is to provide instructional steps and related information necessary for navigating and utilising the IAEA Master Positive Matrix Factorisation (PMF) databases. It is important to note that interpretation of the PMF fingerprints and apportionment contained in either the coarse or fine databases are beyond the scope of this document. However, several countries have already published peer-reviewed papers related to their sites PMF source fingerprinting and source apportionment results. Comprehensive lists of publications are provided in Appendix 2

Receptor Modelling using PMF2: influence on source fingerprints and their contributions using different input options and measurement uncertainties

Receptor modelling is used to determine source fingerprints, from measurements at the receptor site, and then apportion the measured mass to the identified possible sources. Mathematical techniques used to solve this problem include Principal Component Analysis and multivariate techniques such as Positive Matrix Factorisation and UNMIX. In this report PMF analysis is carried out using the PMF2 program. When using PMF2 a number of options control the optimisation process and by varying the options the final solution might be impacted. In addition the uncertainties associated with the measurement have an impact on the solution. Here we systematically vary the PMF2 options and the specified uncertainties of each measurement and compare each solution to a base case solution which has recently been published for the selected dataset. The main findings were that the uncertainties in the measurements and the number of factors chosen to be recovered were the key quantities for the PMF analysis of the considered dataset