Developing a real-world testing protocol for evaluating particulate and greenhouse gas emissions from Australian wood heaters.
Bibliographic record
Abstract
Wood heater smoke is one of the most important sources of air pollution in Australia and leads to several hundred avoidable deaths every year. (Borchers Arriagada et al., 2024) <br>Reducing this substantial burden requires a well-coordinated, funded and multifaceted approach. This includes the development of much safer, less polluting wood combustion appliances than those currently available (Pearce & Scott, 2021), enforcement of local environmental laws to protect neighbours affected by polluting emissions, and incentives, education and regulation to support behaviour change away from highly polluting heating choices and practices (Johnston et al., 2013; Kirkby & McNeill, 2020). <br>The development of safer and less polluting wood heaters requires an emissions testing protocol designed for evaluating the magnitude of polluting emissions that occur when appliances are used in the community. However, such a protocol does not currently exist in regulatory approaches in Australia. The testing protocol used in current Australian and New Zealand Standards (AS/NZS4012-4013), does not reflect typical wood heater operations in a household and as a result, grossly under-estimates emissions that occur when the appliances are used after sale (Johnston et al., 2023). Lowering of existing wood heater emission limits over many years, within the AS/NZS4012-4013 protocol, has not led to any documented reductions in community air pollution from wood heaters nor improvements in community health. <br>Countries in regions with similar air quality problems from wood heaters, such as New Zealand, North America, and Europe face similar problems with wood heaters and are moving towards real-world testing protocols (Marin et al., 2022; Marius et al., 2017; Schön et al.). Standards based on real world testing have been shown to result in rapid technological advancements with much cleaner, ultra-low emissions appliances. (Pearce & Scott, 2020, 2021). However, Australia cannot simply adopt these approaches. We need to develop our own testing methods due to our different dominant fuels (Eucalypt hardwoods) which burn differently to softwoods such as pine, which are largely used in NZ, North America and Europe. <br>Here we report on work undertaken by the University of Tasmania using their purpose-built facility in FireLab3 for undertaking emissions and efficiency testing of wood heaters. The team have developed the Tasmania Protocol, a reproducible protocol for burning hardwoods in a wide range of heating appliances in a way that much more closely aligns with burning practices common in the community than the AS/NZS4012-4013 (Appendix 1). <br>Implementation of the new protocol, with appropriate independent governance and auditing and enforcement, will provide an opportunity for innovation and reform in wood heater design for vastly improved air quality and community health, enabling Australians to benefit from existing and new low emissions technologies. It will also enable more realistic characterisation of the magnitude of climate forcing emissions from wood heaters used in the community. In addition to specifying a new testing protocol, several specific recommendations are made for ongoing research, governance and enforcement of wood heater testing standards and protocols. Implementation of these procedures and protocols will enable considerably improved, and long overdue, community health protection from the harmful impacts of wood heater pollution in Australia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".