The mortality burden attributable to wood heater smoke particulate matter (PM2.5) in Australia.

Air pollution is the leading environmental risk factor for mortality worldwide. In Australia, residential wood heating is the single largest source of pollution in many regions of the country. Estimates around the world and in some limited locations across Australia have shown that the health burden attributable to wood heating PM2.5 is considerable, and that there is great potential to reduce this burden. Here, we aimed to calculate the mortality burden attributable to wood heating emissions (WHE)-related PM2.5 throughout Australia and estimate the potential health benefits of reducing WHE-related air pollution, by replacing wood heaters with cleaner heating technologies. In summary, we used a four-stage process to (1) compile a nationwide WHE inventory, (2) generate annual exposure estimates of WHE-PM2.5, (3) estimate the annual mortality burden attributable to wood heater use across Australia for the year 2015, and (4) assess the potential health benefits of replacing existing wood heaters with cleaner heating technologies. We estimated that population weighted WHE-PM2.5 exposure across Australia for 2015 ranged between 0.62 µg/m3 and 1.35 µg/m3, with differing exposures across State/Territories. We estimated a considerable mortality burden attributable to WHE-PM2.5 ranging between 558 (95 % CI, 364-738) and 1555 (95 % CI, 1180-1740) deaths annually, depending on the scenario assessed. We calculated that replacing 50 % of the current wood heater stock, with zero or lower emission technologies could produce relevant health benefits, of between $AUD 1.61 and $AUD 1.93 billion per year (303-364 attributable deaths). These findings provide a preliminary and likely conservative assessment of the health burden of wood heater smoke across Australia, and an estimation of the potential benefits from replacing the current wood heater stock with cleaner technologies. The results presented here underscore the magnitude of the health burden attributable to wood heating in Australia.

Mortality burden attributable to exceptional PM2.5 air pollution events in Australian cities: A health impact assessment.

Background: People living in Australian cities face increased mortality risks from exposure to extreme air pollution events due to bushfires and dust storms. However, the burden of mortality attributable to exceptional PM2.5 levels has not been well characterised. We assessed the burden of mortality due to PM2.5 pollution events in Australian capital cities between 2001 and 2020. Methods: For this health impact assessment, we obtained data on daily counts of deaths for all non-accidental causes and ages from the Australian National Vital Statistics Register. Daily concentrations of PM2.5 were estimated at a 5 km grid cell, using a Random Forest statistical model of data from air pollution monitoring sites combined with a range of satellite and land use-related data. We calculated the exceptional PM2.5 levels for each extreme pollution exposure day using the deviation from a seasonal and trend loess decomposition model. The burden of mortality was examined using a relative risk concentration-response function suggested in the literature. Findings: Over the 20-year study period, we estimated 1454 (95 % CI 987, 1920) deaths in the major Australian cities attributable to exceptional PM2.5 exposure levels. The mortality burden due to PM2.5 exposure on extreme pollution days was considerable. Variations were observed across Australia. Despite relatively low daily PM2.5 levels compared to global averages, all Australian cities have extreme pollution exposure days, with PM2.5 concentrations exceeding the World Health Organisation Air Quality Guideline standard for 24-h exposure. Our analysis results indicate that nearly one-third of deaths from extreme air pollution exposure can be prevented with a 5 % reduction in PM2.5 levels on days with exceptional pollution. Interpretation: Exposure to exceptional PM2.5 events was associated with an increased mortality burden in Australia's cities. Policies and coordinated action are needed to manage the health risks of extreme air pollution events due to bushfires and dust storms under climate change.

A deep learning approach to identify smoke plumes in satellite imagery in near-real time for health risk communication.

BACKGROUND: Wildland fire (wildfire; bushfire) pollution contributes to poor air quality, a risk factor for premature death. The frequency and intensity of wildfires are expected to increase; improved tools for estimating exposure to fire smoke are vital. New-generation satellite-based sensors produce high-resolution spectral images, providing real-time information of surface features during wildfire episodes. Because of the vast size of such data, new automated methods for processing information are required. OBJECTIVE: We present a deep fully convolutional neural network (FCN) for predicting fire smoke in satellite imagery in near-real time (NRT). METHODS: The FCN identifies fire smoke using output from operational smoke identification methods as training data, leveraging validated smoke products in a framework that can be operationalized in NRT. We demonstrate this for a fire episode in Australia; the algorithm is applicable to any geographic region. RESULTS: The algorithm has high classification accuracy (99.5% of pixels correctly classified on average) and precision (average intersection over union = 57.6%). SIGNIFICANCE: The FCN algorithm has high potential as an exposure-assessment tool, capable of providing critical information to fire managers, health and environmental agencies, and the general public to prevent the health risks associated with exposure to hazardous smoke from wildland fires in NRT.

Impact of exposure to mine fire emitted PM2.5 on ambulance attendances: A time series analysis from the Hazelwood Health Study.

BACKGROUND: For six weeks from February 9, 2014, smoke and ash from a fire in the Morwell open cut brown coal mine adjacent to the Hazelwood power station covered parts of the Latrobe Valley, in south eastern Australia. AIMS: To evaluate the health impact of the mine fire, daily counts of ambulance attendances from July 2010 to March 2015 were analysed. METHODS: Time series models were used to evaluate the relative risk of ambulance attendances during the mine fire, in comparison with the remainder of the analysis period, and to also assess the risk of ambulance attendances associated with lagged effects of exposure to mine fire-related PM2.5 levels. The models controlled for factors likely to influence ambulance attendances including seasonality, long-term temporal trends, day of the week, daily maximum temperature and public holidays. RESULTS: A 10 µg/m3 increase in fire-related PM2.5 was found to be associated with a 42% (95%CI: 14-76%) increase in ambulance attendances for respiratory conditions and a 7% (0-14%) increase in all ambulance attendances over a 20-day lag period. A smaller effect associated with exposure to fire-related PM2.5 was identified when assuming shorter lag effects. Similar results were identified when assessing whether ambulance attendances increased during the 30-day mine fire period. There was a 15% (8-21%) increased risk of ambulance attendances for all conditions and a 47% (19-81%) increased risk for respiratory conditions during the mine fire period. CONCLUSIONS: Exposure to smoke and ash from a fire in an open cut brown coal mine was associated with increased ambulance attendances, particularly for respiratory conditions. These findings guide the development and implementation of effective and timely strategies and health service planning to respond and mitigate health risks that arise in affected communities during future major air pollution episodes.

Roof cavity dust as an exposure proxy for extreme air pollution events.

Understanding exposure to air pollution during extreme events such as fire emergencies is critical for assessing their potential health impacts. However, air pollution emergencies often affect places without a network of air quality monitoring and characterising exposure retrospectively is methodologically challenging due to the complex behaviour of smoke and other air pollutants. Here we test the potential of roof cavity (attic) dust to act as a robust household-level exposure proxy, using a major air pollution event associated with a coal mine fire in the Latrobe Valley, Australia, as an illustrative study. To assess the relationship between roof cavity dust composition and mine fire exposure, we analysed the elemental and polycyclic aromatic hydrocarbon composition of roof cavity dust (<150µm) from 39 homes along a gradient of exposure to the mine fire plume. These homes were grouped into 12 zones along this exposure gradient: eight zones across Morwell, where mine fire impacts were greatest, and four in other Latrobe Valley towns at increasing distance from the fire. We identified two elements-barium and magnesium-as 'chemical markers' that show a clear and theoretically grounded relationship with the brown coal mine fire plume exposure. This relationship is robust to the influence of plausible confounders and contrasts with other, non-mine fire related elements, which showed distinct and varied distributional patterns. We conclude that targeted components of roof cavity dust can be a useful empirical marker of household exposure to severe air pollution events and their use could support epidemiological studies by providing spatially-resolved exposure estimates post-event.

The mortality effect of PM2.5 sources in the Greater Metropolitan Region of Sydney, Australia.

We describe an assessment of the impact on mortality of eight major sources of PM2.5 in the Greater Metropolitan Region of Sydney, Australia (GMR). We modeled exposure to PM2.5 for the year July 2010 to June 2011 and estimated the burden of current mortality attributable to these sources. We also estimated the number of life-years that would be produced if emissions from wood heaters and power stations, the two largest emissions sources, were reduced. Wood heaters (assuming a real-world emissions factor of 11.4 g of PM2.5 per kg of wood burned) were the most important source of PM2.5 exposure, responsible for around 24.0% of the total anthropogenic PM2.5 concentration. On-road sources and power stations were also important, responsible for 16.9% and 10.5% of anthropogenic PM2.5 exposure respectively. Around 1.2% of mortality (5,900 YLL) was attributable to long-term exposure to all anthropogenic PM2.5, including 0.3% (1,400 YLL) attributable to wood heater-related PM2.5, 0.2% (990 YLL) to on-road sources and 0.1% (620 YLL) to power stations. Compared to ongoing emissions at 2010/11 levels, we estimated that a sustained reduction in emissions from wood heaters due to the introduction of an emissions standard of 1.5 g of PM2.5 per kilogram of wood burned (real world emissions factor of 3.9 g of PM2.5 per kg of wood burned) and the associated reduction in PM2.5 population exposure would produce 90,000 life-years among the cohort of people alive in 2010/11. Complete removal of sulphur oxide emissions from power stations would produce 14,000 life-years and complete removal of nitrogen oxide emissions would produce 38,000 life-years. A range of sensitivity analyses indicate the true impact of PM2.5 from these sources is likely to be at least as large as these estimates. This assessment shows that eight sources are responsible for more than 60% of exposure to anthropogenic PM2.5 in the Sydney GMR. Although the burden of mortality attributable to each source is relatively small, interventions that achieve sustained reductions in emissions could provide substantial health benefits, which are likely to far outweigh the costs.

Avoidable Mortality Attributable to Anthropogenic Fine Particulate Matter (PM2.5) in Australia.

Ambient fine particulate matter <2.5 µm (PM2.5) air pollution increases premature mortality globally. Some PM2.5 is natural, but anthropogenic PM2.5 is comparatively avoidable. We determined the impact of long-term exposures to the anthropogenic PM component on mortality in Australia. PM2.5-attributable deaths were calculated for all Australian Statistical Area 2 (SA2; n = 2310) regions. All-cause death rates from Australian mortality and population databases were combined with annual anthropogenic PM2.5 exposures for the years 2006-2016. Relative risk estimates were derived from the literature. Population-weighted average PM2.5 concentrations were estimated in each SA2 using a satellite and land use regression model for Australia. PM2.5-attributable mortality was calculated using a health-impact assessment methodology with life tables and all-cause death rates. The changes in life expectancy (LE) from birth, years of life lost (YLL), and economic cost of lost life years were calculated using the 2019 value of a statistical life. Nationally, long-term population-weighted average total and anthropogenic PM2.5 concentrations were 6.5 µg/m3 (min 1.2-max 14.2) and 3.2 µg/m3 (min 0-max 9.5), respectively. Annually, anthropogenic PM2.5-pollution is associated with 2616 (95% confidence intervals 1712, 3455) deaths, corresponding to a 0.2-year (95% CI 0.14, 0.28) reduction in LE for children aged 0-4 years, 38,962 (95%CI 25,391, 51,669) YLL and an average annual economic burden of $6.2 billion (95%CI $4.0 billion, $8.1 billion). We conclude that the anthropogenic PM2.5-related costs of mortality in Australia are higher than community standards should allow, and reductions in emissions are recommended to achieve avoidable mortality.

Associations between long-term exposure to ambient air pollution and Parkinson's disease prevalence: A cross-sectional study.

BACKGROUND: Epidemiological studies have reported contradictory results regarding the effects of ambient air pollution on Parkinson's disease (PD). This study investigated the associations between long-term exposure to particulate matter <2.5 µm in diameter (PM2.5) and nitrogen dioxide (NO2) and PD among participants in the 45 and Up Study, which comprised adults older than 45 years living in New South Wales, Australia. METHODS: We conducted a cross-sectional analysis of long-term exposure to PM2.5 and NO2 concentrations and prevalence of PD using data from around 240,000 cohort members from the 45 and Up Study, NSW. Annual average concentrations of NO2 and PM2.5 were estimated at the participants' residential address using satellite-based land use regression models. Logistic regression was used to quantify the associations between these pollutants and ever physician-diagnosed PD, after adjusting for a range of individual- and area-level covariates. RESULTS: Among the 236,390 participants with complete data, 1,428 (0.6%) reported physician-diagnosed PD. Annual mean PM2.5 and NO2 concentrations for the cohort were 5.8 and 11.9 µg m-3, respectively, and were positively, but not statistically significantly associated with PD. The odds ratio for a 1 µg m-3 increase in PM2.5 was 1.01 (95% confidence interval (CI): 0.98-1.04). The adjusted odds ratio for a 5 µg m-3 increase in NO2 was 1.03 (95% CI: 0.98-1.08). In subgroup analyses, larger associations for NO2 were observed among past smokers (OR 1.11 (95% CI: 1.02-1.20) per 5 µg m-3 increase). CONCLUSIONS: Overall, we found limited evidence of associations between long-term exposure to NO2 or PM2.5 and PD. The associations observed among past smokers require further corroboration.

All-cause mortality and long-term exposure to low level air pollution in the '45 and up study' cohort, Sydney, Australia, 2006-2015.

BACKGROUND: Epidemiological studies show that long-term exposure to ambient air pollution reduces life expectancy. Most studies have been in environments with relatively high concentrations such as North America, Europe and Asia. Associations at the lower end of the concentration-response function are not well defined. OBJECTIVES: We assessed associations between all-cause mortality and exposure to annual average particulate matter <2.5 µm (PM2.5) and nitrogen dioxide (NO2) in Sydney, Australia, where concentrations are relatively low. METHODS: The '45 and Up Study' comprises a prospective longitudinal cohort from the state of New South Wales, Australia with 266,969 participants linked to death registry data. We analyzed data for the participants who resided in Sydney at baseline questionnaire (n = 75,268). Exposures to long-term pollution were estimated using annual averages from a chemical transport model (PM2.5), and a satellite-based land-use regression model (NO2). Socio-demographic information was extracted from the baseline questionnaire. Cox proportional hazard models were applied to estimate associations, while adjusting for covariates. RESULTS: In our cohort mean annual PM2.5 was 4.5 µg/m3 and mean NO2 was 17.8 µg/m3. The mortality rate was 4.4% over the 7 years of follow up. Models that adjusted for individual-level and area-level risk factors resulted in a detrimental non statistically significant hazard ratio (HR) of 1.05 (95% CI: 0.98-1.12) per 1 µg/m3 increase in PM2.5, and 1.03 (95% CI: 0.98-1.07) per 5 µg/m3 increase in NO2. CONCLUSIONS: We found evidence that low-level air pollution exposure was associated with increased risk of mortality in this cohort of adults aged 45 years and over, even at the relatively low concentrations seen in Sydney. However, a clear determination of the association with mortality is difficult because the results were sensitive to some covariates. Our findings are supportive of emerging evidence that exposure to low levels of air pollution reduces life expectancy.

Long-term exposure to low concentrations of air pollutants and hospitalisation for respiratory diseases: A prospective cohort study in Australia.

BACKGROUND: Short- and long-term spatiotemporal variation in exposure to air pollution is associated with respiratory morbidity in areas with moderate-to-high level of air pollution, but very few studies have examined whether these associations also exist in areas with low level exposure. OBJECTIVES: We assessed the association between spatial variation in long-term exposure to PM2.5 and NO2 and hospitalisation for all respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), and pneumonia, in older adults residing in Sydney, Australia, a city with low-level concentrations. METHODS: We recorded data on hospitalisations for 100,084 participants, who were aged >45 years at entry in 2006-2009 until June 2014. Annual NO2 and PM2.5 concentrations were estimated for the participants' residential addresses and Cox proportional hazards regression was used to model the association between exposure to air pollutants and first episode of hospitalisation, controlling for personal and area level covariates. We further investigated the shape of the exposure-response association and potential effect modification by age, sex, education level, smoking status, and BMI. RESULTS: NO2 and PM2.5 annual mean exposure estimates were 17.5 µg·m-3 and 4.5 µg·m-3 respectively. NO2 and PM2.5 was positively, although not significantly, associated with asthma. The adjusted hazard ratio for a 1 µg·m-3 increase in PM2.5 was 1.08, 95% confidence interval 0.89-1.30. The adjusted hazard ratio for a 5 µg·m-3 increase in NO2 was 1.03, 95% confidence interval 0.88-1.19. We found no positive statistically significant associations with hospitalisation for all respiratory diseases, and pneumonia while negative associations were observed with COPD. CONCLUSIONS: We found weak positive associations of exposure to air pollution with hospitalisation for asthma while there was no evidence of an association for all respiratory diseases.

Blending Multiple Nitrogen Dioxide Data Sources for Neighborhood Estimates of Long-Term Exposure for Health Research.

Exposure to traffic related nitrogen dioxide (NO2) air pollution is associated with adverse health outcomes. Average pollutant concentrations for fixed monitoring sites are often used to estimate exposures for health studies, however these can be imprecise due to difficulty and cost of spatial modeling at the resolution of neighborhoods (e.g., a scale of tens of meters) rather than at a coarse scale (around several kilometers). The objective of this study was to derive improved estimates of neighborhood NO2 concentrations by blending measurements with modeled predictions in Sydney, Australia (a low pollution environment). We implemented the Bayesian maximum entropy approach to blend data with uncertainty defined using informative priors. We compiled NO2 data from fixed-site monitors, chemical transport models, and satellite-based land use regression models to estimate neighborhood annual average NO2. The spatial model produced a posterior probability density function of estimated annual average concentrations that spanned an order of magnitude from 3 to 35 ppb. Validation using independent data showed improvement, with root mean squared error improvement of 6% compared with the land use regression model and 16% over the chemical transport model. These estimates will be used in studies of health effects and should minimize misclassification bias.

The mortality effect of ship-related fine particulate matter in the Sydney greater metropolitan region of NSW, Australia.

This study investigates the mortality effect of primary and secondary PM2.5 related to ship exhaust in the Sydney greater metropolitan region of Australia. A detailed inventory of ship exhaust emissions was used to model a) the 2010/11 concentration of ship-related PM2.5 across the region, and b) the reduction in PM2.5 concentration that would occur if ships used distillate fuel with a 0.1% sulfur content at berth or within 300 km of Sydney. The annual loss of life attributable to 2010/11 levels of ship-related PM2.5 and the improvement in survival associated with use of low-sulfur fuel were estimated from the modelled concentrations. In 2010/11, approximately 1.9% of the region-wide annual average population weighted-mean concentration of all natural and human-made PM2.5 was attributable to ship exhaust, and up to 9.4% at suburbs close to ports. An estimated 220 years of life were lost by people who died in 2010/11 as a result of ship exhaust-related exposure (95% CIß: 140-290, where CIß is the uncertainty in the concentration-response coefficient only). Use of 0.1% sulfur fuel at berth would reduce the population weighted-mean concentration of PM2.5 related to ship exhaust by 25% and result in a gain of 390 life-years over a twenty year period (95% CIß: 260-520). Use of 0.1% sulfur fuel within 300 km of Sydney would reduce the concentration by 56% and result in a gain of 920 life-years over twenty years (95% CIß: 600-1200). Ship exhaust is an important source of human exposure to PM2.5 in the Sydney greater metropolitan region. This assessment supports intervention to reduce ship emissions in the GMR. Local strategies to limit the sulfur content of fuel would reduce exposure and will become increasingly beneficial as the shipping industry expands. A requirement for use of 0.1% sulfur fuel by ships within 300 km of Sydney would provide more than twice the mortality benefit of a requirement for ships to use 0.1% sulfur fuel at berth.

A brief history of vascularized free flaps in the oral and maxillofacial region.

Vascularized free flaps are now the reference standard for the reconstruction of defects after cancer resection in oral and maxillofacial surgery and other specialties and have an interesting and surprisingly long history. We reviewed the history of free flap use in oral and maxillofacial surgery and show their place in the wider context of surgical progress. An overview is given of both soft tissue and bony reconstruction in the pre-free flap era and the development of vascular anastomosis and microsurgery--one of the main foundations of free flap surgery. The emergence of free flaps from 1959 through to the early 1970s is documented. The history of 19 of the more common free flaps used in oral and maxillofacial surgery is described, from the jejunal flap in 1959 through to the posterior tibial artery flap in 1985. For each, the origin and first reported use in the head and neck are discussed. Free flap surgery has continued to evolve, with developments in perforator and chimeric flaps, and new flaps continue to be described. An appreciation of the surgical history is important in understanding where we are today. Our review should give the practicing surgeon an idea of the origins of the currently used techniques.

The impact of climate change on ozone-related mortality in Sydney.

Coupled global, regional and chemical transport models are now being used with relative-risk functions to determine the impact of climate change on human health. Studies have been carried out for global and regional scales, and in our paper we examine the impact of climate change on ozone-related mortality at the local scale across an urban metropolis (Sydney, Australia). Using three coupled models, with a grid spacing of 3 km for the chemical transport model (CTM), and a mortality relative risk function of 1.0006 per 1 ppb increase in daily maximum 1-hour ozone concentration, we evaluated the change in ozone concentrations and mortality between decades 1996-2005 and 2051-2060. The global model was run with the A2 emissions scenario. As there is currently uncertainty regarding a threshold concentration below which ozone does not impact on mortality, we calculated mortality estimates for the three daily maximum 1-hr ozone concentration thresholds of 0, 25 and 40 ppb. The mortality increase for 2051-2060 ranges from 2.3% for a 0 ppb threshold to 27.3% for a 40 ppb threshold, although the numerical increases differ little. Our modeling approach is able to identify the variation in ozone-related mortality changes at a suburban scale, estimating that climate change could lead to an additional 55 to 65 deaths across Sydney in the decade 2051-2060. Interestingly, the largest increases do not correspond spatially to the largest ozone increases or the densest population centres. The distribution pattern of changes does not seem to vary with threshold value, while the magnitude only varies slightly.

Quantifying the health impacts of air pollution under a changing climate-a review of approaches and methodology.

Climate change has been predicted to affect future air quality, with inevitable consequences for health. Quantifying the health effects of air pollution under a changing climate is crucial to provide evidence for actions to safeguard future populations. In this paper, we review published methods for quantifying health impacts to identify optimal approaches and ways in which existing challenges facing this line of research can be addressed. Most studies have employed a simplified methodology, while only a few have reported sensitivity analyses to assess sources of uncertainty. The limited investigations that do exist suggest that examining the health risk estimates should particularly take into account the uncertainty associated with future air pollution emissions scenarios, concentration-response functions, and future population growth and age structures. Knowledge gaps identified for future research include future health impacts from extreme air pollution events, interactions between temperature and air pollution effects on public health under a changing climate, and how population adaptation and behavioural changes in a warmer climate may modify exposure to air pollution and health consequences.

The Australian Air Quality Forecasting System: the use of green scenarios of motor vehicle usage as an educational tool.

The Australian Air Quality Forecasting System (AAQFS) is one of several newly emerging, high-resolution, numerical air quality forecasting systems. The system is briefly described. A public education application of the air quality impact of motor vehicle usage is explored by computing the concentration and dosage of particulate matter less than 10 microm in aerodynamic diameter (PM10) for a commuter traveling to work between Geelong and Melbourne, Victoria, Australia, under "business-as-usual" and "green" scenarios. This application could be routinely incorporated into systems like AAQFS. Two methodologies for calculating the dosage are described: one for operational use and one for more detailed applications. The Clean Air Research Programme-Personal Exposure Study in Melbourne provides support for this operational methodology. The more detailed methodology is illustrated using a system for predicting concentrations due to near-road emissions of PM10 and applied in Sydney.

An approach for estimating exposure to ambient concentrations.

The degree of certainty in epidemiological studies is probably limited more by estimates of exposure than by any other component. We present a methodology for computing daily pollutant concentration fields that reduces exposure uncertainty and bias by taking account of spatial variation in air quality. This approach, using elliptical influence functions, involves the optimum blending of observations from a monitoring network with gridded pollution fields predicted by the complex air quality model TAPM. Such fields allow more information to be incorporated in the exposure fields used in epidemiological studies, rather than having to assume that ambient exposure is the same across a whole city and/or that individuals remain at the one location for the duration of a study.