Search Results (181)

Robust high spatiotemporal resolution daily PM_2.5 exposure estimates are limited in Australia. Estimates of daily PM_2.5 and the PM_2.5 component from extreme pollution events (e.g., bushfires and dust storms) are needed for epidemiological studies and health burden assessments attributable to these events. We sought to: (1) estimate daily PM_2.5 at a 5 km × 5 km spatial resolution across the Australian continent between 1 January 2001 and 30 June 2020 using a Random Forest (RF) algorithm, and (2) implement a seasonal-trend decomposition using loess (STL) methodology combined with selected statistical flags to identify extreme events and estimate the extreme pollution PM_2.5 component. We developed an RF model that achieved an out-of-bag R-squared of 71.5% and a root-mean-square error (RMSE) of 4.5 µg/m³. We predicted daily PM_2.5 across Australia, adequately capturing spatial and temporal variations. We showed how the STL method in combination with statistical flags can identify and quantify PM_2.5 attributable to extreme pollution events in different locations across the country. Full article

This study evaluates bushfire smoke as a workplace hazard for firefighters by characterising its chemical composition and potential health risks in Western Australia. Portable Fourier Transform Infrared (FTIR) spectrometry was used to measure airborne chemical concentrations at prescribed burns across five regions, including peat (acid sulphate) fire events. Samples were collected during both flaming and smouldering phases, as well as in perceived “clear” air resting zones. Results indicated that carbon monoxide (CO) was the dominant gas, reaching concentrations of 205 ppm at the fire front, followed by nitrogen monoxide (26 ppm) and methane (19 ppm). Peat fires produced distinct profiles, with ammonia (21.5 ppm) and sulphur dioxide (9.5 ppm) concentrations higher than those observed in typical bushfires. Smouldering phases emitted higher chemical concentrations than flaming phases 75% of the time. Even clear air zones contained measurable chemicals, with CO levels averaging 18 ppm, suggesting that firefighters are not free from exposure during rest periods. These findings highlight the need for fit-for-purpose respiratory protective equipment (RPE) and improved rest protocols to minimise exposure. The study underscores the importance of comprehensive health monitoring programs for firefighters to mitigate long-term health risks. Full article

Serious concerns exist that the increasing frequency of fires may delay the recovery of ozone given increasing temperatures due to climate change. Australian bushfires from September 2019 to February 2020 were catastrophic. A random forest spatial-temporal (RF sp) analysis using satellite data to detect an association between Australian bushfires and stratosphere ozone on the local depletion of ozone in the vicinity of fires in three regions of Australia (Pacific Ocean, Victoria, NSW) has shown a significant reduction in ozone attributable to aerosols from fires. By intervention analysis, increases in aerosols in all three regions were shown to have a significant and ongoing impact 1–5 days later on reducing ozone (p < 0.0001). Intervention analysis also gave similar periods of aerosol exceedance to those found by Hidden Markov models (HMMs). HMMs established a significant and quantifiable decline in ozone due to bushfire-induced aerosols, with significant lags of 10–25 days between times of aerosol exceedance and subsequent ozone level decline in all three regions. Full article

The sustainable management of protected areas has increasingly become difficult due to the lack of updated information on land use and land cover transformations caused by anthropogenic pressures. This study investigates the spatiotemporal dynamics of the Dinderesso and Peni classified forests in Burkina Faso from 1986 to 2022. First, a data driven method was adopted to investigate these forests degradation dynamics. Hence, relevant Landsat images data were collected, segmented, and analyzed using QGIS SCP plugin Random Forest algorithm. Ninety percent of the overall adjusted classification accuracies were obtained. The analysis also showed significant degradation and deforestation with high wooded vegetation classes such as clear forest and wooded savannah (i.e., tree savannah) converging to lower vegetation classes like shrub savannah and agroforestry parks. A second investigation carried out through surveys and field trips revealed key anthropogenic drivers including agricultural expansion, demographic pressure, bad management, wood cutting abuse, overexploitation, overgrazing, charcoal production, and bushfires. These findings highlight the critical need for better management to improve these protected areas. Full article

Evidence has previously shown that outer tunics (turnout coats) worn by firefighters at structural fires are contaminated with harmful chemicals which subsequently off-gas from the material. However, there is limited research on whether this phenomenon extends to wildland firefighter uniforms. This pilot study aimed to explore if the tunics of volunteer bushfire and forestry firefighters in Western Australia off-gas any contaminants after exposure to prescribed burns or bushfires, and whether there is a need to explore this further. Nine tunics were collected from firefighters following nine bushfire and prescribed burn events, with a set of unused tunics serving as a control. Chemical analysis was performed on these tunics to assess levels of acrolein, benzene, formaldehyde, and sulphur dioxide contamination. The assessment involved measuring chemical off-gassing over a 12 h period using infrared spectrometry. Tunics worn by firefighters appear to adsorb acrolein, benzene, formaldehyde, and sulphur dioxide from bushfire smoke and these contaminants are emitted from firefighting tunics following contamination at elevated concentrations. Further investigation of this research with a larger study sample will be beneficial to understand this phenomenon better and to determine the full extent and range of chemical contaminants absorbed by all firefighter clothing. Full article

In most Sub-Saharan African countries, such as Togo, forest ecosystems provide ecosystem services to the local population. These ecosystem services are of vital importance to the local populations, who depend on the benefits derived from their use to meet their socio-economic needs. The permanent dependence of these populations on ecosystem services is a major factor accelerating the degradation of natural resources, which are already under pressure from climatic factors. The present study assesses the provisioning of ecosystem services provided by the relics forest in the southeast region of the Mono Biosphere Reserve in Togo. Individual interviews and group discussions were carried out with 420 households in fourteen villages around the reserve to identify the current uses of woody species. The results show that 100% of the respondents cited plant species, such as Mitragyna inermis, Lonchocarpus sericeus, and Diospyros mespiliformis, as used for wood. Species, such as Mimusops andogensis and Triplohiton scleroxylon, were cited as exclusively used for wood by 94% and 86%, respectively. Other species, such as Vitex doniana and Dialium guineense, in addition to their use for wood (93% and 70%), were cited, respectively, by 97% and 98% of respondents as used for fruit, and by 82% and 90% for their leaves. The heavy daily use of these species compromises their sustainability. An analysis of Sorensen’s similarity index, according to gender, age, ethnic group, and sector of activity, revealed a variation in this index ranging from 0.6 to 1, reflecting households’ knowledge of the use of these seven species. The local populations are already feeling the effects of the low availability of these commonly used species. According to them, the depletion of these resources is caused mainly by agricultural clearing, illegal logging, and bushfires. Full article

Natural disasters such as bushfires are a test of individual and group resilience, and in extreme cases, threaten the sustainability of communities. Bushfires have long been common in Australia, although anthropogenic climate change has exacerbated their prevalence and severity. The aim of the present study was to assess the individual resilience and disaster-specific adaptation and resilience of community members in the wake of a bushfire event. Using a quantitative, cross-sectional design, an adult community sample of 165 residents of Noosa Shire in regional Queensland, Australia completed the 25-item Connor-Davidson Resilience Scale (CD-RISC©) and the 43-item Disaster Adaptation and Resilience Scale (DARS). Mean scores for the CD-RISC© indicated significantly greater resilience (p < 0.001) than reported previously for a large Australian community cohort. Similarly, the DARS scores indicated significantly greater adaptation and resilience (p < 0.001) than that of a comparable cohort in the USA. The two oldest groups of residents (66+ years and 51–65 years) reported significantly greater adaptation and resilience than the group of younger residents (≤50 years; p < 0.001). The study findings provide the Noosa Shire community with an objective baseline from which they can assess the efficacy of future resilience-building initiatives and, more broadly, offer a valuable point of reference for future disaster-related research. Full article

Coastally trapped southerly wind changes are prominent during southeast Australia’s warm season (spring and summer). These abrupt, often gale force, wind changes are known locally as Southerly Busters (SBs) when their wind speeds reach 15 m/s. They move northwards along the coast, often producing very large temperature drops. SBs exceeding 21 m/s are severe SBs (SSBs). SBs have both positive and negative impacts. They bring relief from oppressively hot days but can cause destructive wind damage, worsen existing bushfires, and endanger aviation and marine activities. This study assesses the impacts of global warming (GW) and associated climate change on SBs and SSBs, using observational data from 1970 to 2022. Statistical analyses determine significant trends in annual frequency counts of SBs and SSBs, particularly during the accelerated GW period from the early–mid-1990s. It was found that the annual combined count of SBs and SSBs had increased, with SSBs dominating from 1970 to 1995, but SB frequencies exceeded SSBs from 1996 to 2023. The ascendency of SB frequencies over SSBs since 1996 is explained by the impact of GW on changes in global and local circulation patterns. Case studies exemplify how these circulation changes have increased annual frequencies of SBs, SSBs, and their combined total. Full article

The prevalence of the invasive species African Lovegrass (Eragrostis curvula, ALG thereafter) in Australian landscapes presents significant challenges for land managers, including agricultural losses, reduced native species diversity, and heightened bushfire risks. Uncrewed aerial system (UAS) remote sensing combined with AI algorithms offer a powerful tool for accurately mapping the spatial distribution of invasive species and facilitating effective management strategies. However, segmentation of vegetations within mixed grassland ecosystems presents challenges due to spatial heterogeneity, spectral similarity, and seasonal variability. The performance of state-of-the-art artificial intelligence (AI) algorithms in detecting ALG in the Australian landscape remains unknown. This study compared the performance of four supervised AI models for segmenting ALG using multispectral (MS) imagery at four sites and developed segmentation models for two different seasonal conditions. UAS surveys were conducted at four sites in New South Wales, Australia. Two of the four sites were surveyed in two distinct seasons (flowering and vegetative), each comprised of different data collection settings. A comparative analysis was also conducted between hyperspectral (HS) and MS imagery at a single site within the flowering season. Of the five AI models developed (XGBoost, RF, SVM, CNN, and U-Net), XGBoost and the customized CNN model achieved the highest validation accuracy at 99%. The AI model testing used two approaches: quadrat-based ALG proportion prediction for mixed environments and pixel-wise classification in masked regions where ALG and other classes could be confidently differentiated. Quadrat-based ALG proportion ground truth values were compared against the prediction for the custom CNN model, resulting in 5.77% and 12.9% RMSE for the seasons, respectively, emphasizing the superiority of the custom CNN model over other AI algorithms. The comparison of the U-Net demonstrated that the developed CNN effectively captures ALG without requiring the more intricate architecture of U-Net. Masked-based testing results also showed higher F1 scores, with 91.68% for the flowering season and 90.61% for the vegetative season. Models trained on single-season data exhibited decreased performance when evaluated on data from a different season with varying collection settings. Integrating data from both seasons during training resulted in a reduction in error for out-of-season predictions, suggesting improved generalizability through multi-season data integration. Moreover, HS and MS predictions using the custom CNN model achieved similar test results with around 20% RMSE compared to the ground truth proportion, highlighting the practicality of MS imagery over HS due to operational limitations. Integrating AI with UAS for ALG segmentation shows great promise for biodiversity conservation in Australian landscapes by facilitating more effective and sustainable management strategies for controlling ALG spread. Full article

Pyrocumulonimbus (pyroCb) thunderclouds, produced from extreme bushfires, can initiate frequent cloud-to-ground (CG) lightning strikes containing extended continuing currents. This, in turn, can ignite new spot fires and inflict massive harm on the environment and infrastructures. This study presents a 3D numerical thundercloud model for estimating the lightning of different types and its striking zone for the conceptual tripole thundercloud structure which is theorized to produce the lightning phenomenon in pyroCb storms. More emphasis is given to the lower positive charge layer, and the impacts of strong wind shear are also explored to thoroughly examine various electrical parameters including the longitudinal electric field, electric potential, and surface charge density. The simulation outcomes on pyroCb thunderclouds with a tripole structure confirm the presence of negative longitudinal electric field initiation at the cloud’s lower region. This initiation is accompanied by enhancing the lower positive charge region, resulting in an overall positive electric potential increase. Consequently, negative surface charge density appears underneath the pyroCb thundercloud which has the potential to induce positive (+CG) lightning flashes. With wind shear extension of upper charge layers in pyroCb, the lightning initiation potential becomes negative to reduce the absolute field value and would generate negative (−CG) lightning flashes. A subsequent parametric study is carried out considering a positive correlation between aerosol concentration and charge density to investigate the sensitivity of pyroCb electrification under the influence of high aerosol conditions. The suggested model would establish the basis for identifying the potential area impacted by lightning and could also be expanded to analyze the dangerous conditions that may arise in wind energy farms or power substations in times of severe pyroCb events. Full article

Much of eastern and southeastern Australia (SEAUS) suffered from historic flooding, heat waves, and drought during the quasi-decadal 2010–2022 period, similar to that experienced globally. During the double La Niña of the 2010–2012 period, SEAUS experienced record rainfall totals. Then, severe drought, heat waves, and associated bushfires from 2013 to 2019 affected most of SEAUS, briefly punctuated by record rainfall over parts of inland SEAUS in the late winter/spring of 2016, which was linked to a strong negative Indian Ocean Dipole. Finally, from 2020 to 2022 a rare triple La Niña generated widespread extreme rainfall and flooding in SEAUS, resulting in massive property and environmental damage. To identify the key drivers of the 2010–2022 period’s precipitation and temperature extremes due to accelerated global warming (GW), since the early 1990s, machine learning attribution has been applied to data at eight sites that are representative of SEAUS. Machine learning attribution detection was applied to the 52-year period of 1971–2022 and to the successive 26-year sub-periods of 1971–1996 and 1997–2022. The attributes for the 1997–2022 period, which includes the quasi-decadal period of 2010–2022, revealed key contributors to the extremes of the 2010–2022 period. Finally, some drivers of extreme precipitation and temperature events are linked to significant changes in both global and local tropospheric circulation. Full article

Climate change has resulted in a worldwide increase in intensity and frequency of extreme weather events including bushfires. Previous research has shown that communities often do not engage in disaster preparedness, even when sufficient education and resources are provided. With the projected increase in natural disasters, preparedness is paramount, and more research is needed to gain an understanding into what impacts community preparedness in the face of climate change. This study investigated one rural Australian community’s preparedness for the 2019–2020 bushfires. Thirteen Australian adults who resided within a small rural community in New South Wales during the 2019–2020 bushfires participated in semi-structured interviews. Data were analysed using inductive thematic analysis. Participants reported being unprepared for the 2019–2020 bushfires and that the community has started to prepare for future bushfires. However, they also described a belief in ‘climate cycles’ rather than climate change, limiting engagement in preparedness for future hazards. Participants also reported that they did not talk about the 2019–2020 bushfires, although described experiencing residual anxiety. Recommendations included support needed for rural communities to help with future preparedness efforts and mental health symptoms. Full article

Fire regimes have shaped extant vegetation communities, and subsequently fuel arrays, in fire-prone landscapes. Understanding how resilient fuel arrays are to fire regime attributes will be key for future fire management actions, given global fire regime shifts. We use a network of 63-field sites across the Sydney Basin Bioregion (Australia) to quantify how fire interval (short: last three fires <10 years apart, long: last two fires >10 years apart) and severity (low: understorey canopy scorched, high: understorey and overstorey canopy scorched), impacted fuel attribute values 2.5 years after Australia’s 2019–2020 Black Summer fires. Tree bark fuel hazard, herbaceous (near-surface fuels; grasses, sedges <50 cm height) fuel hazard, and ground litter (surface fuels) fuel cover and load were higher in areas burned by low- rather than high-severity fire. Conversely, midstorey (elevated fuels: shrubs, trees 50 cm–200 m in height) fuel cover and hazard were higher in areas burned by high- rather than low-severity fire. Elevated fuel cover, vertical connectivity, height and fuel hazard were also higher at long rather than short fire intervals. Our results provide strong evidence that fire regimes rearrange fuel arrays in the years following fire, which suggests that future fire regime shifts may alter fuel states, with important implications for fuel and fire management. Full article

The 2019–2020 Australian bushfire season had a devastating impact on native wildlife. It was estimated that 3 billion native animals were impacted by the fires, yet there are few estimates of the number of animals that were rescued and rehabilitated post-fire. Focusing on the state of New South Wales (NSW) and Kangaroo Island, South Australia, we used a case study approach to determine the number of marsupials that were reported rescued due to the 2019–2020 bushfires in these areas and analysed species-specific trends in rescue and release success. In NSW, we found 889 reports of fire-affected marsupials in 2019–2020, mostly comprising kangaroos and wallabies (macropods; n = 458), koalas (n = 204), and possums (n = 162), with a smaller number of wombats (n = 43) and other marsupial species. Most reports of fire-affected marsupials occurred 6–8 weeks after fire ignition, and there was no difference in temporal frequency of rescues between marsupial groups. For the three main groups, the probability of survival and subsequent release differed, with macropods having the lowest probability of release after rescue (0.15 ± 0.04) compared to koalas (0.47 ± 0.04) and possums (0.55 ± 0.10). The type of injury was the main predictor of survival during rehabilitation for all three marsupial groups, with those malnourished/moribund or with traumatic injuries less likely to survive rehabilitation. Death or euthanasia occurred on the day of rescue for 77% of macropods, 48% of possums and 15% of koalas. Koalas most often died during rehabilitation rather than on the day of rescue, with 73% either dying or being euthanised between day 1 and 30 post-rescue, representing a potential welfare concern. On Kangaroo Island, koalas were the most frequently rescued marsupial species; most euthanasia cases and deaths occurred in a hospital, whereas other marsupials were mostly euthanised at triage. In both jurisdictions, koalas were over-represented while possums were under-represented relative to baseline population densities and wildlife rescue trends in the years before the 2019–2020 bushfires. These species differences in presentation post-fire warrant further investigation, as do the differences in triage, survival and release outcomes. It is hypothesised that the high intensity and large scale of the 2019–2020 fires impeded marsupial fire evasion tactics, as evidenced by the small number of animals found for rescue, and the differing rates of presentation relative to underlying population densities for the main marsupial groups. Based on our findings, there is a need for detailed record keeping and data sharing, development of consistent and evidence-based triage, treatment and euthanasia guidelines and deployment of trained wildlife emergency rescue teams with advanced search techniques to minimise animal suffering where safe to do so. Full article