Evaluating portable air cleaner effectiveness in residential settings to reduce exposures to biomass smoke resulting from prescribed burns.

AIM: Prescribed burning is the most common method employed to reduce fuel loads in flammable landscapes. This practice is designed to reduce the hazard associated with uncontrolled bushfires. Prescribed burns are frequently conducted close to residential areas, and the associated smoke impacts can adversely affect community health. Particulate matter is the predominant pollutant within the smoke and is strongly and consistently linked with adverse health effects. Outdoor smoke readily infiltrates buildings and reduces the quality of indoor air. Portable air cleaners containing high-efficiency particulate air (HEPA) filters are a promising indoor air quality intervention for reducing outdoor smoke exposure. METHODS: We provided 10 homes from semirural regions of Victoria, Australia, with HEPA cleaners and conducted continuous monitoring of indoor and outdoor fine particulate matter (PM2.5) for 2-4 weeks during prescribed burning periods. We calculated the potential improvements to indoor air quality when operating a HEPA cleaner during a smoke episode. Ventilation measures were conducted to identify points of smoke ingress and housing characteristics that could lead to higher infiltration rates. RESULTS: Depending on the house, the use of HEPA cleaners resulted in a reduction in indoor PM2.5 concentrations of 30-74%. CONCLUSIONS: HEPA cleaners have the potential to substantially improve indoor air quality during episodic smoke episodes.

Wood heater smoke and mortality in the Australian Capital Territory: a rapid health impact assessment.

OBJECTIVES: To estimate the number of deaths and the cost of deaths attributable to wood heater smoke in the Australian Capital Territory. STUDY DESIGN: Rapid health impact assessment, based on fine particulate matter (PM2.5 ) data from three outdoor air pollution monitors and published exposure-response functions for natural cause mortality attributed to PM2.5 exposure. SETTING: Australian Capital Territory (population, 2021: 454 000), 2016-2018, 2021, and 2022 (2019 and 2020 excluded because of the impact of extreme bushfires on air quality). MAIN OUTCOME MEASURES: Proportion of PM2.5 exposure attributable to wood heaters; numbers of deaths and associated cost of deaths (based on the value of statistical life: $5.3 million) attributable to wood heater smoke. RESULTS: Wood heater emissions contributed an estimated 1.16-1.73 µg/m3 to the annual mean PM2.5 concentration during the three colder years (2017, 2018, 2021), or 17-25% of annual mean exposure, and 0.72 µg/m3 (15%) or 0.89 µg/m3 (13%) during the two milder years (2016, 2022). Using the most conservative exposure-response function, the estimated annual number of deaths attributable to wood heater smoke was 17-26 during the colder three years and 11-15 deaths during the milder two years. Using the least conservative exposure-response function, an estimated 43-63 deaths per year (colder years) and 26-36 deaths per year (milder years) were attributable to wood heater smoke. The estimated annual equivalent cost of deaths was $57-136 million (most conservative exposure-response function) and $140-333 million (least conservative exposure-response function). CONCLUSIONS: The estimated annual number of deaths in the ACT attributable to wood heater PM2.5 pollution is similar to that attributed to the extreme smoke of the 2019-20 Black Summer bushfires. The number of wood heaters should be reduced by banning new installations and phasing out existing units in urban and suburban areas.

Five Years of Accurate PM2.5 Measurements Demonstrate the Value of Low-Cost PurpleAir Monitors in Areas Affected by Woodsmoke.

Low-cost optical sensors are used in many countries to monitor fine particulate (PM2.5) air pollution, especially in cities and towns with large spatial and temporal variation due to woodsmoke pollution. Previous peer-reviewed research derived calibration equations for PurpleAir (PA) sensors by co-locating PA units at a government regulatory air pollution monitoring site in Armidale, NSW, Australia, a town where woodsmoke is the main source of PM2.5 pollution. The calibrations enabled the PA sensors to provide accurate estimates of PM2.5 that were almost identical to those from the NSW Government reference equipment and allowed the high levels of wintertime PM2.5 pollution and the substantial spatial and temporal variation from wood heaters to be quantified, as well as the estimated costs of premature mortality exceeding $10,000 per wood heater per year. This follow-up study evaluates eight PA sensors co-located at the same government site to check their accuracy over the following four years, using either the original calibrations, the default woodsmoke equation on the PA website for uncalibrated sensors, or the ALT-34 conversion equation (see text). Minimal calibration drift was observed, with year-round correlations, r = 0.98 ± 0.01, and root mean square error (RMSE) = 2.0 µg/m3 for daily average PA PM2.5 vs. reference equipment. The utitilty of the PA sensors without prior calibration at locations affected by woodsmoke was also demonstrated by the year-round correlations of 0.94 and low RMSE between PA (woodsmoke and ALT-34 conversions) and reference PM2.5 at the NSW Government monitoring sites in Orange and Gunnedah. To ensure the reliability of the PA data, basic quality checks are recommended, including the agreement of the two laser sensors in each PA unit and removing any transient spikes affecting only one sensor. In Armidale, from 2019 to 2022, the continuing high spatial variation in the PM2.5 levels observed during the colder months was many times higher than any discrepancies between the PA and reference measurements. Particularly unhealthy PM2.5 levels were noted in southern and eastern central Armidale. The measurements inside two older weatherboard houses in Armidale showed that high outdoor pollution resulted in high pollution inside the houses within 1-2 h. Daily average PM2.5 concentrations available on the PA website allow air pollution at different sites across regions (and countries) to be compared. Such comparisons revealed major elevations in PA PM2.5 at Gunnedah, Orange, Monash (Australian Capital Territory), and Christchurch (New Zealand) during the wood heating season. The data for Gunnedah and Muswellbrook suggest a slight underestimation of PM2.5 at other times of the year when there are proportionately more dust and other larger particles. A network of appropriately calibrated PA sensors can provide valuable information on the spatial and temporal variation in the air pollution that can be used to identify pollution hotspots, improve estimates of population exposure and health costs, and inform public policy.

A Review of Artificial Neural Network Models Applied to Predict Indoor Air Quality in Schools.

BACKGROUND: Indoor air quality (IAQ) in schools can affect the performance and health of occupants, especially young children. Increased public attention on IAQ during the COVID-19 pandemic and bushfires have boosted the development and application of data-driven models, such as artificial neural networks (ANNs) that can be used to predict levels of pollutants and indoor exposures. METHODS: This review summarises the types and sources of indoor air pollutants (IAP) and the indicators of IAQ. This is followed by a systematic evaluation of ANNs as predictive models of IAQ in schools, including predictive neural network algorithms and modelling processes. The methods for article selection and inclusion followed a systematic, four-step process: identification, screening, eligibility, and inclusion. RESULTS: After screening and selection, nine predictive papers were included in this review. Traditional ANNs were used most frequently, while recurrent neural networks (RNNs) models analysed time-series issues such as IAQ better. Meanwhile, current prediction research mainly focused on using indoor PM2.5 and CO2 concentrations as output variables in schools and did not cover common air pollutants. Although studies have highlighted the impact of school building parameters and occupancy parameters on IAQ, it is difficult to incorporate them in predictive models. CONCLUSIONS: This review presents the current state of IAQ predictive models and identifies the limitations and future research directions for schools.

Pandemic products and volatile chemical emissions.

The recent pandemic (COVID-19) has seen a sweeping and surging use of products intended to clean and disinfect, such as air sprays, hand sanitizers, and surface cleaners, many of which contain fragrance. However, exposure to fragranced cleaning products has been associated with adverse effects on human health. Products can emit a range of volatile chemicals, including some classified as hazardous, but relatively few ingredients are disclosed to the public. Thus, relatively little is known about the specific emissions from these products. This study investigates the volatile organic compounds (VOCs) emitted from "pandemic products" that are being used frequently and extensively in society. In addition, among these emissions, this study identifies potentially hazardous compounds, compares so-called green and regular versions of products, and examines whether ingredients are disclosed to the public. Using gas chromatography/mass spectrometry, 26 commonly used pandemic products, including 13 regular and 13 so-called green versions, were analyzed for their volatile emissions. Product types included hand sanitizers, air disinfectants, multipurpose cleaners, and handwashing soap. All products were fragranced. The analyses found the products collectively emitted 399 VOCs with 127 VOCs classified as potentially hazardous. All products emitted potentially hazardous compounds. Comparing regular products and green products, no significant difference was found in the emissions of the most prevalent compounds. Further, among the 399 compounds emitted, only 4% of all VOCs and 11% of potentially hazardous VOCs were disclosed on any product label or safety data sheet. This study reveals that pandemic products can generate volatile emissions that could pose risks to health, that could be unrecognized, and that could be reduced, such as by using fragrance-free versions of products.

Biofouling potential and material reactivity in a simulated water distribution network supplied with stormwater recycled via managed aquifer recharge.

The injection of stormwater into aquifers for storage and recovery during high water demand periods is a promising technology for augmenting conventional water reserves. Limited information exists regarding the potential impact of aquifer treated stormwater in distribution system infrastructure. This study describes a one year pilot distribution pipe network trial to determine the biofouling potential for cement, copper and polyvinyl chloride pipe materials exposed to stormwater stored in a limestone aquifer compared to an identical drinking water rig. Median alkalinity (123 mg/L) and colour (12 HU) in stormwater was significantly higher than in drinking water (82 mg/L and 1 HU) and pipe discolouration was more evident for stormwater samples. X-ray Diffraction and Fluorescence analyses confirmed this was driven by the presence of iron rich amorphous compounds in more thickly deposited sediments also consistent with significantly higher median levels of iron (∼0.56 mg/L) in stormwater compared to drinking water (∼0.17 mg/L). Water type did not influence biofilm development as determined by microbial density but faecal indicators were significantly higher for polyvinyl chloride and cement exposed to stormwater. Treatment to remove iron through aeration and filtration would reduce the potential for sediment accumulation. Operational and verification monitoring parameters to manage scaling, corrosion, colour, turbidity and microbial growth in recycled stormwater distribution networks are discussed.