Limited attention has been given to the presence of MPs in the atmospheric environment, particularly in indoor environments where people spend about 90% of their time. This study quantitatively assesses the prevalence, source and type of MPs in Australian homes with the goal of evaluating human health exposure potential. Thirty-two airborne indoor deposited dust samples were collected in glass Petri dishes from Sydney (Australia) homes, over a one-month period in 2019. Participants completed a questionnaire on their household characteristics. Samples were analysed using a stereomicroscope, a fluorescent microscope and micro-Fourier transform infrared (FTIR) spectroscopy for their colour, size, shape and composition. Inhalation and ingestion rates were modelled using US EPA exposure factors. Microplastic fibre deposition rates ranged from 22 to 6169 fibres/m²/day. Deposited dust comprised 99% fibres. The highest proportion of fibres (19%) were 200–400 μm in length. The majority were natural (42%); 18% were transformed natural-based fibres; and 39% were petrochemical based. A significant difference was observed between the deposition rate and the main floor covering (p-value <0.05). Polyethylene, polyester, polyamide, polyacrylic, and polystyrene fibres were found in higher abundance in homes with carpet as the main floor covering. Where carpet was absent, polyvinyl fibres were the most dominant petrochemical fibre type, indicating the role of flooring materials (e.g. wood varnishes) in determining MP composition. Vacuum cleaner use was significantly related to MP deposition rates (p-value <0.05). MP ingestion rates peaked at 6.1 mg/kg-Bw/year for ages 1–6, falling to a minimum of 0.5 mg/kg-Bw/year in >20 years age group. Mean inhaled MP weight and count was determined to be 0.2±0.07 mg/kg-Bw/year and 12891±4472 fibres/year. Greatest inhalation intake rates were for the <0.5-yr age group, at 0.31 mg/kg-Bw/year. The study data reveal that MPs are prevalent in Australian homes and that the greatest risk of exposure resides with young children. Notwithstanding the limited number of global studies and the different methods used to measure MPs, this study indicates Australian deposition and inhalation rates are at the lower end of the exposure spectrum.

The prevalence of allergic diseases in Australian children is high, but few studies have assessed the potential role of outdoor air pollution in allergic sensitization. We investigated the association between outdoor air pollution and the prevalence of aeroallergen sensitization in a national cross-sectional study of Australian children aged 7–11 years. Children were recruited from 55 participating schools in 12 Australian cities during 2007–2008. Parents completed a detailed (70-item) questionnaire. Outdoor nitrogen dioxide (NO₂), as a proxy for exposure to traffic-related emissions, was estimated using measurements from regulatory monitors near each school and a national land-use regression (LUR) model. Three averaging periods were assessed, using information on duration of residence at the address, including lifetime, previous (lifetime, excluding the last year), and recent (the last year only). The LUR model was used as an additional source of recent exposure estimates at school and home addresses. Skin prick tests (SPTs) were performed to measure sensitization to eight common aeroallergens. Multilevel logistic regression estimated the association between NO₂ and sensitization (by individual allergens, indoor and outdoor allergens, and all allergens combined), after adjustment for individual- and area-level covariates. In total, 2226 children had a completed questionnaire and SPT. The prevalence of sensitization to any allergen was 44.4%. Sensitization to house dust mites (HDMs) was the most common (36.1%), while sensitization to Aspergillus was the least common (3.4%). Measured mean (±s.d.) NO₂ exposure was between 9 (±2.9) ppb and 9.5 (±3.2) ppb, depending on the averaging period. An IQR (4 ppb) increase in measured previous NO₂ exposure was associated with greater odds of sensitization to HDMs (OR: 1.21, 95% CI: 1.01–1.43, P = 0.035). We found evidence of an association between relatively low outdoor NO₂ concentrations and sensitization to HDMs, but not other aeroallergens, in Australian children aged 7–11 years.

Children’s respiratory health are particularly vulnerable to outdoor air pollution, but evidence is lacking on the very acute effects of air pollution on the risk of acute upper respiratory infections (AURI) and acute lower respiratory infections (ALRI) in children. This study aimed to evaluate the risk of cause-specific AURI and ALRI, in children within 24 h of exposure to air pollution. We obtained data on emergency cases, including 11,091 AURI cases (acute pharyngitis, acute tonsillitis, acute obstructive laryngitis and epiglottitis, and unspecified acute upper respiratory infections) and 11,401 ALRI cases (pneumonia, acute bronchitis, acute bronchiolitis, unspecified acute lower respiratory infection) in Brisbane, Australia, 2013–2015. A time-stratified case-crossover analysis was used to examine the hourly association of AURI and ALRI with high concentration (95th percentile) of four air pollutants (particulate matters with aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅), ozone (O₃), nitrogen dioxide (NO₂)). We observed increased risk of acute tonsillitis associated with PM₂.₅ within 13–24 h (odds ratio (OR), 1.45; 95% confidence interval [CI], 1.02–2.06) and increased risk of unspecified acute upper respiratory infections related to O₃ within 2–6 h (OR, 1.38, 95%CI, 1.12–1.70), NO₂ within 1 h (OR, 1.19; 95%CI, 1.01–1.40), and PM₂.₅ within 7–12 h (OR, 1.21; 95%CI, 1.02–1.43). Cold season and nigh-time air pollution has greater effects on AURI, whereas greater risk of ALRI was seen in warm season and daytime. Our findings suggest exposures to particulate and gaseous air pollution may transiently increase risk of AURI and ALRI in children within 24 h. Prevention measures aimed at protecting children’s respiratory health should consider the very acute effects of air pollution.

Although short-term exposure to air pollution can trigger sudden heart attacks, evidence is scarce regarding the relationship between sub-daily changes in air pollution level and the risk of acute myocardial infarction (AMI). Here we assessed the intraday effect of air pollution on AMI risk and potential effect modification by pre-existing cardiac risk factors. Hourly data on emergency department visits (EDVs) for AMI and air pollutants in Brisbane, Australia during 2013–2015 were acquired from pertinent government departments. A time-stratified case-crossover analysis was adopted to examine relationships of AMI risk with hourly changes in particulate matters (aerodynamic diameter ≤ 2.5 μm (PM₂.₅) and ≤10 μm (PM₁₀)) and gaseous pollutants (ozone and nitrogen dioxide) after adjusting for potential confounders. We also conducted stratified analyses according to age, gender, disease history, season, and day/night time exposure. Excess risk of AMI per 10 μg/m³ increase in air pollutant concentration was reported at four time windows: within 1, 2–6, 7–12, and 13–24 h. Both single- and multi-pollutant models found an elevated risk of AMI within 2–6 h after exposure to PM₂.₅ (excessive risk: 12.34%, 95% confidence interval (CI): 1.44%–24.42% in single-pollutant model) and PM₁₀ within 1 h (excessive risk: 5.21%, 95% CI: 0.26%–10.40% in single-pollutant model). We did not find modification effect by age, gender, season or day/night time, except that PM₂.₅ had a greater effect on EDVs for AMI during night-time than daytime. Our findings suggest that AMI risk could increase within hours after exposure to particulate matters.

Antarctic trace element records could provide important insights into the impact of human activities on the environment over the past few centuries. In this study, we investigated the atmospheric concentrations of 14 representative heavy metals (Al, As, Cd, Co, Cu, Fe, K, Mg, Mn, Pb, Sb, Sr, Tl and V) from 174 samples collected in a 4-m snow pit at Dome Argus (Dome A) on the East Antarctic Plateau, covering the period from 1950 to 2016 A.D. We found great variability in the annual concentration of all metals. The crustal enrichment factors suggest that the concentrations of some heavy metals (Cd, Sb, Cu, As and Pb) were likely influenced by anthropogenic activities in recent decades. An analysis of source regions suggests that heavy metal pollution at Dome A was largely caused by human activities in Australia and South America (e.g. mining production, leaded gasoline). Based on the relationship between the trace elements fluxes and sea ice concentration (SIC), sea surface temperature (SST) and annual mean air temperature at 2 m above the ground (T₂ₘ), our analysis shows that deposition and transport of atmospheric aerosol at Dome A were influenced by circum-Antarctic atmospheric circulations.

Investigating environmental pollution is important to understand its impact on endangered species such as green turtles (Chelonia mydas). In this study, we investigated the accumulation and potential toxicity of selected persistent organic pollutants (POPs) and naturally occurring MeO-PBDEs in liver, fat, kidney and muscle of turtles (n = 30) of different gender, size, year of death, location and health status. Overall, POP concentrations were low and accumulation was highest in liver and lowest in fat which is likely due to the poor health of several animals, causing a remobilization of lipids and associated compounds. PCBs and p,p’-DDE dominated the POP profiles, and relatively high MeO-PBDE concentrations (2′-MeO-BDE 68 up to 192 ng/g lw, 6-MeO-BDE 47 up to 79 ng/g lw) were detected in all tissues. Only few influences of factors such as age, gender and location were found. While concentrations were low compared to other marine wildlife, biological toxicity equivalences obtained by screening the tissue extracts using the micro-EROD assay ranged from 2.8 to 356 pg/g and the highest values were observed in muscle, followed by kidney and liver. This emphazises that pollutant mixtures found in the turtles have the potential to cause dioxin-like effects in these animals and that dioxin-like compounds should not be overlooked in future studies.

A substantial increase in the usage of organophosphate esters (OPEs) as flame retardants and plasticizers in rubbers, textiles, upholstered furniture, lacquers, plastics, building materials and electronic equipment has resulted in their increasing concentrations in the environment over time. However, little is known about the concentrations and fate of OPEs and their metabolites (mOPEs) in biota, including chicken eggs. The aim of this study was to understand the spatial variation in the concentrations in chicken eggs and the partitioning between yolk and albumin. In total, 153 chicken eggs were purchased across Australia and analysed for 9 OPEs and 11 mOPE. Most of the compounds were found to be deposited in egg yolk, where diphenyl phosphate (DPHP, 3.8 ng/g wet weight, median) and tris(2-chloroisopropyl) phosphate (TCIPP, 1.8 ng/g wet weight, median) were predominant mOPE and OPE, respectively. Moreover, no spatial differences in concentrations of OPEs and mOPEs in eggs purchased from different locations were found in this study. Although comparable levels of ∑OPEs were detected in egg yolk and albumin, much higher concentrations of ∑mOPEs were found in yolk than albumin. Meanwhile, a negative correlation (R² = 0.964, p = 0.018) was found between the molecular mass of analytes and partitioning coefficient of Cyₒₗₖ/Cyₒₗₖ₊ₐₗbᵤₘᵢₙ (defined as chemical concentration in egg yolk divided by the sum of chemical concentrations in both yolk and albumin). These results indicate that n-octanol/water partition coefficients (log KOW) may not be a crucial factor in the distribution of OPEs and mOPEs between egg yolk and albumin, which is important in understanding distribution of emerging organic contaminants in biota.

Microplastic (MP) pollution is an emerging issue in aquatic sciences. Little comparative information currently exists about the problem in coastal systems exposed to different levels of human impact. Here we report a year-long study on the abundance of MP in the water column of three estuaries on the east-coast of Australia. The estuaries are subject to different scales of human impact; the Clyde estuary has little human modification, the Bega estuary has a small township and single wastewater treatment works discharging to its waters, and the Hunter estuary which has multiple townships, multiple wastewater treatment plants, and heavy industry. MP abundance followed an expected pattern with the lowest abundance in the low-impact Clyde estuary (98 part. m³), moderate levels of MP in the moderately impacted Bega estuary (246 part. m³), and high MP abundance in the highly impacted Hunter estuary (1032 part. m³). The majority of particles were <200 μm and fragment-like rather than fiber-like. MP abundance was positively related to maximum antecedent rainfall in the Bega estuary, however there are no clear environmental factors that could explain MP variation in the other systems. MP were generally higher in summer and following freshwater inflow events. On the Hunter estuary MP abundance was at times as high as zooplankton abundance, and within the range of numbers reported in other highly impacted systems globally. The results confirm that higher levels of human impact lead to greater plastic pollution and highlight the need to examine aquatic ecosystems under a range of conditions in order to adequately characterize the extent of MP pollution in rivers and coastal systems.

Determining sources of heavy metals in soils, sediments and groundwater is important for understanding their fate and transport and mitigating human and environmental exposures. Artificially imported fill, natural sediments and groundwater from 240 ha of reclaimed land at Fishermans Bend in Australia, were analysed for heavy metals and other parameters to determine the relative contributions from different possible sources. Fishermans Bend is Australia's largest urban re-development project, however, complicated land-use history, geology, and multiple contamination sources pose challenges to successful re-development. We developed a method for heavy metal source separation in groundwater using statistical categorisation of the data, analysis of soil leaching values and fill/sediment XRF profiling. The method identified two major sources of heavy metals in groundwater: 1. Point sources from local or up-gradient groundwater contaminated by industrial activities and/or legacy landfills; and 2. contaminated fill, where leaching of Cu, Mn, Pb and Zn was observed. Across the precinct, metals were most commonly sourced from a combination of these sources; however, eight locations indicated at least one metal sourced solely from fill leaching, and 23 locations indicated at least one metal sourced solely from impacted groundwater. Concentrations of heavy metals in groundwater ranged from 0.0001 to 0.003 mg/L (Cd), 0.001–0.1 mg/L (Cr), 0.001–0.2 mg/L (Cu), 0.001–0.5 mg/L (Ni), 0.001–0.01 mg/L (Pb), and 0.005–1.2 mg/L (Zn). Our method can determine the likely contribution of different metal sources to groundwater, helping inform more detailed contamination assessments and precinct-wide management and remediation strategies.