The ongoing climate change is expected to lead to a significant increase in the frequency and intensity of climate extremes. However, the impact of cold and hot temperatures on labour loss, through causing premature deaths in the future, remains largely unknown. We collected historic daily all-cause mortality data during 1986-2019 from 1066 locations in seven countries. A two-stage time-series approach was applied to estimate associations between non-optimum temperatures and the productivity-adjusted life year (PALY) loss due to premature deaths. These associations were then combined with projected daily temperatures under three climate change scenarios from 2021 to 2100 to quantify future PALY losses attributable to temperatures. Overall, we projected an increase in heat-related PALY loss and a decrease in cold-related PALY loss in the future. Under the SSP5-8.5 scenario, the heat-related PALY loss is projected to increase by 7.5% by the end of 2100 compared to the historical period (2001-2020), resulting in a net increase in excess PALY loss of 6.8%, greater than the net changes projected under the SSP3-7.0 (5.7%) and SSP1-2.6 (0.6%) scenarios. Brazil and Thailand were projected to experience an increase in excess heat-related PALY loss, while a reduction in excess cold-related PALY loss was projected to be most prominent in Thailand. The magnitude of the change in both heat- and cold-related PALY loss was largely affected by socioeconomic factors, such as GDP per capita and the deprivation level. This study provides a better understanding of the impacts of climate change on labour loss and provides evidence to inform targeted adaptation strategies and policy responses aimed at mitigating the socioeconomic impacts of climate change.

Background:Non-optimum temperatures have been linked to increased mortality, but the cause-, age-, and sex-specific impacts remain largely unclear. This study investigates the temperature-mortality relationships for nine causes of death across multiple countries/territories and explores subgroup differences by sex and age. Methods:We analysed the non-linear and lagged associations between temperature and mortality in 1117 locations from ten countries or territories (Australia, Brazil, Canada, Chile, Mexico, New Zealand, Philippines, South Korea, Taiwan, and Thailand) covering country-specific periods within 2000-2019, using a two-stage time-series design. In the first stage, a quasi-Poisson generalised linear regression with a distributed lag non-linear model was fitted to estimate the location-specific mortality risk associated with temperature. We then applied a meta-regression model in the second stage to synthesise the associations for cause-specific mortality. Stratified analyses were conducted by sex and age group, and the attributable fraction (AF) of mortality was subsequently estimated. Findings:We identified three distinct exposure-response patterns: an inverse J-shaped curve with higher risks from extreme cold for most causes, a U-shaped curve for all-cause and respiratory mortality, and a J-shaped curve for injury and external causes with greater risks at extreme heat. Significant differences in temperature-related mortality risks were observed across age and sex groups, with the direction and magnitude of these differences varying by cause of death. We estimated that 2.03 million deaths were attributable to non-optimum temperatures during the study period, corresponding to 4.38% (95% CI: 2.02, 6.59) of all-cause mortality. The highest AFs were observed for mental disorders (6.53%), nervous (6.40%), and cardiovascular causes (5.71%). For most causes of death, cold temperatures accounted for the largest proportion of mortality. However, for deaths related to infectious as well as injury and external causes, heat exposure contributed to the majority of the mortality. Interpretation:Our findings demonstrated substantial variations in temperature-related mortality by cause of death, sex, and age. This analysis highlights the need for tailored public health strategies that address the unique vulnerabilities of specific demographic groups across different causes of death, with targeted interventions to mitigate temperature-related health risks. Future work should focus on improving estimation in data-sparse subgroups and developing cause-, age-, and sex-specific projections of temperature-related health risks under future climate scenarios. Funding:The Australian Research Council, Australian National Health and Medical Research Council, VicHealth, and National Research Council of Thailand.

Heatwaves are increasing in frequency and intensity, yet their impacts on hospitalizations for mental and behavioural disorders remain insufficiently quantified across countries. Here we show, using a time-stratified case-crossover analysis of 2,618,307 warm-season hospitalization records from 852 locations in Brazil, Canada, Chile and New Zealand from 2000 to 2019, that sustained extreme heat was associated with increased hospitalization risk. Heatwaves were primarily defined as periods with daily mean temperature above the location-specific 97.5th percentile for at least 4 consecutive days. Under this definition, the relative risk was 1.033 (95% confidence interval, 1.007–1.059) on the same day and 1.056 (1.011–1.103) cumulatively from the same day through the next 8 days. Associations were stronger among older adults and residents of low-population-density areas. These findings indicate that prolonged extreme heat can acutely increase mental health-related hospital demand and support targeted preparedness during severe heatwaves. In an analysis of more than 2 million hospitalizations during warm seasons in four countries, extreme and prolonged heatwaves were associated with increased risk of hospitalization for mental and behavioural disorders.

Extreme heat is intensifying under climate change, yet evidence on regional and temporal variation in heat-related morbidity remains limited. Here we analyzed over 100 million emergency department (ED) visits across five countries and territories from 2000 to 2019 using a time-stratified case-crossover design to quantify associations between summer temperature and acute healthcare demand. Here we show that higher summer temperatures are associated with increased risks of ED visits across all study regions. At the 95th percentile of local daily maximum temperature, cumulative excess odds ratios are highest in Australia (42.1%, 95% confidence interval 38.1-46.2) and Taiwan (25.7%, 16.7-35.3), followed by Brazil (18.0%, 17.6-18.4), New Zealand (16.6%, 13.5-19.7), and Canada (6.1%, 4.1-8.1). Over time, heat-related risks declined in Australia but increased in Brazil. These findings reveal substantial regional and temporal heterogeneity in vulnerability and underscore the need for locally tailored heat-health adaptation strategies under a warming climate.

Many infection risk models rely on the well-mixed assumption, neglecting variations in aerosol concentration and particle size distribution. Additionally, these models lack real-time aerosol data integration, limiting their ability to assess infection risk and safe occupancy time dynamically. While CFD-based models provide spatiotemporal aerosol distribution, they often use predefined emission rates that do not account for particle size effects. This study presents a novel radius-resolved infection risk model that estimates infection probability and maximum occupancy time based on measured aerosol concentrations. The model directly utilizes the pathogen concentration derived from in-situ aerosol measurements to estimate real-time infection risk at the sensor location. Furthermore, CFD simulations incorporating the particle size distribution of exhaled aerosols in a stale air classroom environment are applied to generate spatiotemporal infection risk and safe occupancy time maps. The effects of the infected occupant's position, particle radius, activity level, and age on infection risk are investigated. Results highlight significant spatial variability, with our model estimating infection risk 20% lower than the well-mixed model at the sensor but over three times higher near the infector, underscoring the limitations of well-mixed models. Maximum occupancy time maps reveal that, in certain locations, nearly half of the occupants remain uninfected after 25 min, whereas, in other locations, only three occupants remain uninfected. This demonstrates that infection probability is an inadequate safety metric, while maximum safe occupancy time is more reliable. The developed model can serve as an estimator of infection risk and safe occupancy time for adaptive ventilation and filtration strategies.

Evaluating the short-term exposure to wildfire-specific fine particulate matter (PM2.5) showed greater risks of hospitalization for all major respiratory diseases than non-wildfire PM2.5. When developing air quality guidelines, it is also important to consider that PM2.5 from varying sources can have different health effects, which require targeted health and environmental policy approaches.

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021, 2022 and 2023. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the seventh report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. We also examine selected indicators of trends in health and climate change in New Zealand. Our analyses show the exposure to heatwaves is growing in Australia, increasing the risk of heat stress and other health threats such as bushfires and drought. Our analyses also highlight continuing deficiencies in Australia's response to the health and climate change threat. A key component of Australia's capacity to respond to bushfires, its number of firefighting volunteers, is in decline, dropping by 38 442 people (17%) in just seven years. Australia's total energy supply remains dominated by fossil fuels (coal, oil and natural gas), and although energy from coal decreased from 2021 to 2023, energy from oil increased, and transport energy from petrol grew substantially in 2021-22 (the most recent year for which data are available). Greenhouse gas emissions from Australia's health care sector in 2021 rose to their highest level since 2010. In other areas some progress is being made. The Australian Government completed the first pass of the National Climate Risk Assessment, which included health and social support as one of the eleven priority risks, based in part on the assessed severity of impact. Renewable sources such as wind and solar now provide almost 40% of Australia's electricity, with growth in both large-scale and small-scale (eg, household) renewable generation and battery storage systems. The sale of electric vehicles reached an all-time high in 2023 of 98 436, accounting for 8.47% of all new vehicle sales. Although Australia had a reprieve from major catastrophic climate events in 2023, New Zealand experienced cyclone Gabrielle and unprecedented floods, which contributed to the highest displacement of people and insured economic losses over the period of our analyses (ie, since the year 2010 and 2000 respectively). Nationally, regionally and globally, the next five years are pivotal in reducing greenhouse gas emissions and transitioning energy production to renewables. Australia is now making progress in this direction. This progress must continue and accelerate, and the remaining deficiencies in Australia's response to the health and climate change threat must be addressed. There are strong signs that Australians are increasingly engaged and acting on health and climate change, and our new indicator on health and climate change litigation in Australia demonstrates the legal system is active on this issue in this country. Our 2022 and 2023 reports signalled our intentions to introduce indicators on Aboriginal and Torres Strait Islander health and climate change, and mental health and climate change in Australia. Although the development of appropriate indicators is challenging, these are key areas and we expect our reporting on them will commence in our next report.

Biomass combustion, including wildfires and residential wood burning, is a significant source of particulate matter (PM2.5) in Australia, with potentially distinct health effects due to its unique chemical composition. This study aimed to quantify the association between exposure to ambient biomass-attributable PM2.5 and the risk of preterm birth and stillbirth across pregnancy windows in Sydney, Australia, from 2010 to 2020. We conducted case-control studies nested within a cohort of 578,391 singleton pregnancies, including 29,954 preterm births and 2,928 stillbirths. Controls were randomly selected using risk-set sampling. Daily all-source PM2.5 estimates at a 5 km resolution were obtained from a previous study. Days exceeding the 95th percentile of all-source PM2.5 at statistical area level 4 without significant dust storm pollution were classified as biomass-affected days. For these days, biomass-attributable PM2.5 was estimated using the remainder component from a seasonal trend decomposition, with the seasonal and trend components representing nonbiomass-attributable PM2.5. Conditional logistic regressions were used to analyze associations between biomass-attributable PM2.5 exposure and outcomes, adjusting for area-level socioeconomic factors, temperature, humidity, and temporal and seasonal trends. The odds ratio for preterm birth per interquartile range increase in biomass-attributable PM2.5 was 1.002 (95% CI = 0.997, 1.007) for the entire pregnancy average exposure, with similar null results across trimesters. For stillbirth, the odds ratio was 1.002 (95% CI = 0.985, 1.019) for the entire pregnancy average exposure, with comparable null findings across trimesters. These results suggest that in Sydney, biomass-attributable PM2.5 exposure during pregnancy may not increase the risk of preterm births or stillbirths.

Under a warming climate, wildfires are becoming more frequent and severe. Multicountry studies evaluating associations between wildfire fine particulate matter (PM2.5) and respiratory hospitalizations are lacking. Here we evaluate the short-term effects of wildfire-specific PM2.5 on respiratory hospitalizations from 1,052 communities across Australia, Brazil, Canada, Chile, New Zealand, Vietnam, Thailand and Taiwan, during 2000-2019. A 1 mu g m-3 increase in wildfire-specific PM2.5 was associated with increased hospitalization risks for all-cause respiratory, asthma, chronic obstructive pulmonary disease, acute upper respiratory infection, influenza and pneumonia by 0.36%, 0.48%, 0.38%, 0.42%, 0.79% and 0.36%, respectively. Higher risks were observed among populations <= 19 or >= 60 years old, from low-income or high non-wildfire PM2.5 communities, and residing in Brazil, Thailand, Taiwan and Vietnam. Australia and New Zealand exhibited a greater hospitalization risk for asthma associated with wildfire-specific PM2.5. Compared with non-wildfire PM2.5, wildfire-specific PM2.5 posed greater hospitalization risks for all respiratory diseases and a greater burden of asthma. Wildfire-specific PM2.5 contributed to 42.4% of PM2.5-linked respiratory hospitalizations, dominating in Thailand. Overall, the substantial contribution of wildfire-specific PM2.5 to respiratory hospitalizations demands continued mitigation and adaptation efforts across most countries. Intervention should be prioritized for influenza, children, adolescents, the elderly and populations in low-income or high-polluted communities.

The transition to renewable energy in Australia represents a significant opportunity for First Nations communities to benefit from developments on their land. In partnership with the Indigenous Land and Sea Corporation and the First Nations Clean Energy Network, the authors conducted research exploring this opportunity, with a specific focus on the barriers preventing First Nations from achieving these benefits and what different groups of actors could do to help overcome these barriers. In this paper we present the findings from a series of semistructured interviews with Traditional Owners, First Nations groups, renewable energy developers and industry representatives, legal experts and other academics. We identified two groups of barriers - overarching barriers including ongoing disadvantage and a lack of funding and resourcing for First Nations groups, and barriers specific to renewable energy developments such as the absence of Indigenous free, prior and informed consent in project approval processes and unclear, non-uniform legislative frameworks. To overcome these barriers, we recommend strategies for different actors. For example, governments could implement Indigenous free, prior and informed consent in regulatory regimes and the renewable energy industry could establish cultural education and training programs for company staff.

Biomass combustion, including wildfires and residential wood burning, is a significant source of particulate matter (PM2.5) in Australia, with potentially distinct health effects due to its unique chemical composition. This study aimed to quantify the association between exposure to ambient biomass-attributable PM2.5 and the risk of preterm birth and stillbirth across pregnancy windows in Sydney, Australia, from 2010 to 2020. We conducted case-control studies nested within a cohort of 578,391 singleton pregnancies, including 29,954 preterm births and 2,928 stillbirths. Controls were randomly selected using risk-set sampling. Daily all-source PM2.5 estimates at a 5 km resolution were obtained from a previous study. Days exceeding the 95th percentile of all-source PM2.5 at statistical area level 4 without significant dust storm pollution were classified as biomass-affected days. For these days, biomass-attributable PM2.5 was estimated using the remainder component from a seasonal trend decomposition, with the seasonal and trend components representing nonbiomass-attributable PM2.5. Conditional logistic regressions were used to analyze associations between biomass-attributable PM2.5 exposure and outcomes, adjusting for area-level socioeconomic factors, temperature, humidity, and temporal and seasonal trends. The odds ratio for preterm birth per interquartile range increase in biomass-attributable PM2.5 was 1.002 (95% CI = 0.997, 1.007) for the entire pregnancy average exposure, with similar null results across trimesters. For stillbirth, the odds ratio was 1.002 (95% CI = 0.985, 1.019) for the entire pregnancy average exposure, with comparable null findings across trimesters. These results suggest that in Sydney, biomass-attributable PM2.5 exposure during pregnancy may not increase the risk of preterm births or stillbirths.

Electric vehicles (EVs) with vehicle-to-grid (V2G) technology offer a dual solution to decarbonise the energy and transport sectors. This paper evaluates the potential for Australia's passenger and light commercial EV fleet to replace large-scale battery storage under a 100% renewable energy system in the National Electricity Market. By simulating various levels of V2G battery availability, we assess the impact on energy production costs, renewable energy capacity and storage needs in a grid that includes a fully electrified residential sector. Our results show that leveraging 10%-50% of the available V2G battery capacity can significantly lower grid storage costs while providing all the storage requirements needed for a full year of energy balancing. With infrastructure costs considerably lower than large-scale grid batteries, V2G presents a cost-effective path to decarbonisation. We also explore policy mechanisms, such as competitive V2G feed-in tariffs, to incentivise early adoption and promote large-scale EV participation in the energy market.

Presently, there is no standardized framework or metrics identified to assess regional climate model precipitation output. Because of this, it can be difficult to make a one-to-one comparison of their performance between regions or studies, or against coarser-resolution global climate models. To address this, we introduce the first steps toward establishing a dynamic, yet standardized, benchmarking framework that can be used to assess model skill in simulating various characteristics of rainfall. Benchmarking differs from typical model evaluation in that it requires that performance expectations are set a priori. This framework has innumerable applications to underpin scientific studies that assess model performance, inform model development priorities, and aid stakeholder decision-making by providing a structured methodology to identify fit-for-purpose model simulations for climate risk assessments and adaptation strategies. While this framework can be applied to regional climate model simulations at any spatial domain, we demonstrate its effectiveness over Australia using high-resolution, 0.5 degrees 3 0.5 degrees simulations from the CORDEX-Australasia ensemble. We provide recommendations for selecting metrics and pragmatic benchmarking thresholds depending on the application of the framework. This includes a top tier of minimum standard metrics to establish a minimum benchmarking standard for ongoing climate model assessment. We present multiple applications of the framework using feedback received from potential user communities and encourage the scientific and user community to build on this framework by tailoring benchmarks and incorporating additional metrics specific to their application.

Background: Non-optimum temperatures are associated with a considerable mortality burden. However, there is a lack of evaluation of labour productivity losses related to premature deaths due to non-optimum temperatures. This study aimed to quantify the labour productivity burden associated with premature deaths related to non-optimum temperatures and explore the potential socio-economic vulnerabilities. Methods: Daily all-cause mortality data were collected from 1,066 locations in 7 countries (Australia, Brazil, Canada, Chile, New Zealand, South Korea, and Thailand). Productivity-Adjusted Life-Year (PALY) loss due to each premature death was calculated to measure the labour productivity loss, by multiplying the years of working life lost by the proportion of the equivalent full-time (EFT) workers. A two-stage times series design and the generalized linear regression model with a quasi-Poisson family were applied to assess the association between non-optimum temperatures and the PALY loss due to premature deaths. Results: We observed a U-shaped relationship between temperature and PALY lost due to premature mortality. We estimated that 2.51% (95% eCI: 2.05%, 2.92%) of PALY losses could be attributed to non-optimal temperatures, with cold-related deaths contributing 1.26% (95% eCI: 0.94%, 1.54%) and heat-related deaths contributing 1.25% (95% eCI: 0.96%, 1.51%). Cold temperature contributed to the most PALYs lost in those aged 45–54 and 55–64, while heat-related losses predominated among the 15–44 age group. We also observed that the fractions of PALY lost attributed to extreme heat were positively associated with the relative deprivation index, while negatively associated with GDP per capita. Conclusion: This multi-country study highlights that non-optimum temperatures led to a considerable labour productivity loss and socioeconomically disadvantaged communities experience greater losses.

The MJA-Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021 and 2022. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. In this, the sixth report of the MJA-Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses. Our results highlight the health and economic costs of inaction on health and climate change. A series of major flood events across the four eastern states of Australia in 2022 was the main contributor to insured losses from climate-related catastrophes of $7.168 billion - the highest amount on record. The floods also directly caused 23 deaths and resulted in the displacement of tens of thousands of people. High red meat and processed meat consumption and insufficient consumption of fruit and vegetables accounted for about half of the 87 166 diet-related deaths in Australia in 2021. Correction of this imbalance would both save lives and reduce the heavy carbon footprint associated with meat production. We find signs of progress on health and climate change. Importantly, the Australian Government released Australia's first National Health and Climate Strategy, and the Government of Western Australia is preparing a Health Sector Adaptation Plan. We also find increasing action on, and engagement with, health and climate change at a community level, with the number of electric vehicle sales almost doubling in 2022 compared with 2021, and with a 65% increase in coverage of health and climate change in the media in 2022 compared with 2021. Overall, the urgency of substantial enhancements in Australia's mitigation and adaptation responses to the enormous health and climate change challenge cannot be overstated. Australia's energy system, and its health care sector, currently emit an unreasonable and unjust proportion of greenhouse gases into the atmosphere. As the Lancet Countdown enters its second and most critical phase in the leadup to 2030, the depth and breadth of our assessment of health and climate change will be augmented to increasingly examine Australia in its regional context, and to better measure and track key issues in Australia such as mental health and Aboriginal and Torres Strait Islander health and wellbeing.