International Analysis of Sources and Human Health Risk Associated with Trace Metal Contaminants in Residential Indoor Dust.

People spend increasing amounts of time at home, yet the indoor home environment remains understudied in terms of potential exposure to toxic trace metals. We evaluated trace metal (and metalloid) concentrations (As, Cu, Cr, Mn, Ni, Pb, and Zn) and health risks in indoor dust from homes from 35 countries, along with a suite of potentially contributory residential characteristics. The objective was to determine trace metal source inputs and home environment conditions associated with increasing exposure risk across a range of international communities.

The relevance of particle size distribution and bioaccessibility on human health risk assessment for trace elements measured in indoor dust.

Trace metal contaminants in indoor dust pose a significant potential exposure risk to people because of the time spent indoors and the readily ingested and inhaled fine-grained composition of indoor dusts. However, there is limited trace metal data available on the specific interaction of dust particle size fraction and their respective bioaccessibility/bioavailability and its consequent effect on health risk assessment. This study addresses this knowledge gap by examining bioaccessible and bioavailable trace element concentrations (As, Cr, Cu, Mn, Ni, Pb, Zn) in 152 discrete size fractions from 38 indoor vacuum samples from a larger dataset (n = 376) of indoor dust from Sydney, Australia.

Human exposure and risk associated with trace element concentrations in indoor dust from Australian homes.

This study examines residential indoor dust from 224 homes in Sydney, Australia for trace element concentrations measured using portable X-ray Fluorescence (pXRF) and their potential risk of harm. Samples were collected as part of a citizen science program involving public participation via collection and submission of vacuum dust samples for analysis of their As, Cr, Cu, Mn, Ni, Pb and Zn concentrations. The upper 95% confidence level of the mean values for 224 samples (sieved to <250 μm) were 20.

Environmental sustainability assessment using dynamic Autoregressive-Distributed Lag simulations-Nexus between greenhouse gas emissions, biomass energy, food and economic growth.

Increasing population demand has triggered the enhancement of food production, energy consumption and economic development, however, its impact on climate change has become a global concern. This study applied a novel environmental sustainability assessment tool using dynamic Autoregressive-Distributed Lag (ARDL) simulations for model estimation of the relationships between greenhouse gas (GHG) emissions, energy, biomass, food and economic growth for Australia using data spanning from 1970 to 2017. The study found an inversed-U shaped relationship between energy consumption and income level, showing a decarbonized and services economy, hence, improved energy efficiency.