Two decades of trends in urban particulate matter concentrations across Australia.

Australia is a highly developed country with low population density. Capital cities are situated mainly around the coastline and are subjected to different meteorological conditions. This complex set of drivers is expected to result in varying trends in particulate matter (PM) mass concentrations in urban ambient air across the country. Thus, the aim of this study was to determine the long-term trends in PM10 and PM2.5 concentrations in capital cities, and to analyse the factors that influenced such trends. The spatial variability of PM concentrations within the capital cities was first established to identify representative stations. Then trends were determined using the Mann-Kendall trend test, Sen's slope, and the generalised additive model. The results show that, in general, the PM concentrations in Australian cities are relatively low (12.1-21.7 µg m-3 mean daily PM10 and 4.6-8.7 µg m-3 mean daily PM2.5) and within the WHO daily limit 95% of the time. Over the past two decades, very small declines of 8.0 × 10-5-1.1 × 10-3 µg m-3.yr-1 for PM10 and 7.7 × 10-5-2.6 × 10-3 µg m-3.yr-1 for PM2.5 were observed while some stations exhibited increase in concentration based on available data; more stations showed a significant monotonic decline for PM10 than PM2.5. This is attributed to the effectiveness of the implemented emission reduction policies particularly for vehicle exhaust and power generation, given the simultaneous increase in the demand for energy and the number of vehicles over the last two decades. Regarding climate, in the coastal cities of Sydney and Brisbane, high rainfall and strong winds aid in maintaining low PM concentrations despite the significant anthropogenic emissions, while higher PM levels in Darwin can be attributed to its tropical savannah climate, which makes it prone to bushfires and necessitates regular prescribed burnings. PM concentrations increase when exceptional events such as bushfires and dust storms are induced by the extreme climate variability. Further reduction of PM concentrations in Australian cities is unlikely, considering the expanding urbanisation and the changing climate.

Global Survey of Antibiotic Resistance Genes in Air.

Despite its emerging significant public health concern, the presence of antibiotic resistance genes (ARGs) in urban air has not received significant attention. Here, we profiled relative abundances (as a fraction, normalized by 16S rRNA gene) of 30 ARG subtypes resistant to seven common classes of antibiotics, which are quinolones, ß-lactams, macrolides, tetracyclines, sulfonamides, aminoglycosides, and vancomycins, in ambient total particulate matter (PM) using a novel protocol across 19 world cities. In addition, their longitudinal changes in PM2.5 samples in Xi'an, China as an example were also studied. Geographically, the ARGs were detected to vary by nearly 100-fold in their abundances, for example, from 0.07 (Bandung, Indonesia) to 5.6 (San Francisco, USA). The ß-lactam resistance gene blaTEM was found to be most abundant, seconded by quinolone resistance gene qepA; and their corresponding relative abundances have increased by 178% and 26%, respectively, from 2004 to 2014 in Xi'an. Independent of cities, gene network analysis indicates that airborne ARGs were differentially contributed by bacterial taxa. Results here reveal that urban air is being polluted by ARGs, and different cities are challenged with varying health risks associated with airborne ARG exposure. This work highlights the threat of urban airborne transmission of ARGs and the need of redefining our current air quality standards in terms with public health.

Ultrafine particles and PM2.5 in the air of cities around the world: Are they representative of each other?

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM2.5 (mass concentration of particles with aerodynamic diameter < 2.5 µm) and factors that influence their concentrations. Hourly average PNC and PM2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 103 to 19.5 × 103 particles·cm-3 and from 7.0 to 65.8 µg·m-3 for PNC and PM2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM2.5 demonstrated that a high PNC level does not lead to a high PM2.5, and vice versa. The particle number-to-mass ratio (in units of 109 particles·µg-1) ranged from 0.14 to 2.2, >1 for roadside sites and <1 for urban background sites with lower values for more polluted cities. The Pearson's r ranged from 0.09 to 0.64 for the log-transformed data, indicating generally poor linear correlation between PNC and PM2.5. Therefore, PNC and PM2.5 measurements are not representative of each other; and regulating PM2.5 does little to reduce PNC. This highlights the need to establish regulatory approaches and control measures to address the impacts of elevated UFP concentrations, especially in urban areas, considering their potential health risks.