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ABSTRACT Based on Coupled Model Intercomparison Project phase 6 (CMIP6) simulations, we found that the frequency and intensity of daytime–nighttime compound hot extremes (HEs) in the mid‐high latitudes of Asia (MHA) are expected to increase. The most significant increase is anticipated under the shared socioeconomic pathway (SSP) 5‐8.5, while the smallest increase is expected under SSP1‐2.6. Notably, unlike the decreasing trends of independent HEs since 2050 under the high emission scenarios, the compound HEs, which comprise the largest proportion, are expected to continuously increase and intensify. To better understand the impact of these changes on human society, we also focused on changes in population exposed to HEs. The findings reveal that population exposure to compound and nighttime HEs is projected to increase most rapidly under SSP3‐7.0, with estimates indicating increases of 10.06 and 3.80 times, respectively, by the end of the century. The most significant increases are expected in the mid‐latitudes, where changes in HEs are most pronounced. Climate change is the primary driver behind the rising population exposure to compound and nighttime HEs, with its impact expected to grow over time. Conversely, exposure to daytime HEs is primarily influenced by population changes, particularly in urban areas. Therefore, effective climate change mitigation and adaptive strategies are crucial to reducing future population exposure to HEs in MHA. [ABSTRACT FROM AUTHOR]

Heatwaves (HWs) pose a severe threat to human and ecological systems. Here we assess the projected changes in heatwaves over Latin America using bias corrected high-resolution regional climate simulations under two Representative Concentration Pathway scenarios (RCPs). Heatwaves are projected to be more frequent, long-lasting, and intense in the mid-century under both RCP2.6 and RCP8.5 scenarios, with severe increases under the RCP8.5 scenario. Even under the low emissions scenario of RCP2.6, the frequency of heatwaves doubles over most of the region. A three- to tenfold rise in population exposure to heatwave days is projected over Central and South America, with climate change playing a dominant role in driving these changes. Results show that following the low emission pathway would reduce 57% and 50% of heatwave exposure for Central and South American regions respectively, highlighting the need to control anthropogenic emissions and implement sustainable practices. [ABSTRACT FROM AUTHOR]

Global climate projections show that humid heat extremes will expand toward the higher latitudes, making the midlatitudes hotspots for these extremes. Therefore, a thorough explanation of their regional characteristics becomes crucial, given that the changes in these extremes can potentially render a large proportion of the global population at risk. Here, we perform the first analysis of historical and projected changes in the intensity and frequency of humid heat extremes and quantify the population exposure to these extremes in Turkey, using long‐term simulations from the non‐hydrostatic mesoscale model of Consortium for Small‐scale Modeling (COSMO‐CLM) under the RCP8.5 emission scenario. We portray not only the nationwide changes in the humid heat extremes and population exposure but also their regional aspects by exploiting the K‐means clustering algorithm. Our results suggest significant future increases in the intensity and frequency of these extremes over a wide geographical area, which includes the surroundings of Adana, Antalya, Izmir, Sakarya, Ordu and Diyarbakir, most of which are coastal locations. Over most of these regions, severe humid heat stress is expected to last nearly a month every year, with almost 56% of the land area is projected to experience local historical upper tail heat stress conditions for at least an additional 10 consecutive hours. Further, we explicate a significant rise in the number of people exposed to severe humid heat stress, concentrated along most coastal regions, by as much as 1.6 million person‐days. More than 20% of Turkey's population may confront severe humid heat stress for at least 1 h, with that percentage falling to 4.15% for at least five consecutive hours, which indicates that people will not only endure more intense humid heat stress but also be exposed to these conditions consecutively over a period of many hours. [ABSTRACT FROM AUTHOR]

Abstract Heatwaves (HWs) pose a severe threat to human and ecological systems. Here we assess the projected changes in heatwaves over Latin America using bias corrected high-resolution regional climate simulations under two Representative Concentration Pathway scenarios (RCPs). Heatwaves are projected to be more frequent, long-lasting, and intense in the mid-century under both RCP2.6 and RCP8.5 scenarios, with severe increases under the RCP8.5 scenario. Even under the low emissions scenario of RCP2.6, the frequency of heatwaves doubles over most of the region. A three- to tenfold rise in population exposure to heatwave days is projected over Central and South America, with climate change playing a dominant role in driving these changes. Results show that following the low emission pathway would reduce 57% and 50% of heatwave exposure for Central and South American regions respectively, highlighting the need to control anthropogenic emissions and implement sustainable practices.

The increase in extreme precipitation (EP) may pose a serious threat to the health and safety of population in arid and semi-arid regions. The current research on the impact of EP on population in Central Asia (CA) is insufficient and there is an urgent need for a comprehensive assessment. Hence, we opted for precipitation and temperature data under two Shared Socioeconomic Pathways (SSP2–4.5 and SSP5–8.5) from ten Global Climate Models (GCMs), which were obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). By integrating population data in 2020 and 2050 (SSP2 and SSP5), we investigated the future changes in EP and population exposure in CA under 1.5 °C and 2 °C global warming scenarios (GWSs). Our analysis indicates that EP in CA is projected to increase with global warming. Under the SSP5–8.5, the maximum daily precipitation (Rx1day) exhibits an average response rate to global warming of 3.58 %/K (1.99–4.06 %/K). With rising temperatures, an increasing number of areas and populations in CA will be impacted by EP, especially in the Fergana valley. Approximately 25% of the population (land area) in CA is exposed to Rx1day with increases of more than 8.31% (9.32%) under 1.5 °C GWS and 14.18% (13.25%) under 2 °C GWS. Controlling temperature rise can be effective in reducing population exposures to EP. For instance, limiting the temperature increase to 1.5 °C instead of 2 °C results in a 2.79% (1.75%–4.59%) reduction in population exposure to Rx1day. Finally, we found that climate change serves as the predominant factor influencing the population exposure to EP, while the role of population redistribution, although relatively minor, should not be disregarded. Particularly for prolonged drought, the role of population redistribution manifests negatively.

The persistent occurrence of extreme precipitation events presents considerable challenges to the well-being, assets, and sustainable progress of the population in China. During this century, the trends, change points, and spatial variability of population exposure to precipitation extremes remain unclear. This study assesses how the exposure changes in future decades, using climate predictions from CMIP6 models and population projections under the SSP2-4.5 and SSP5-8.5 scenarios. We identify the initial decade and duration when exposure exceeds dangerous level, and also reveal the movements of the geographical centroids in different regions. It is found that under the SSP5-8.5 scenario, both precipitation extremes and population exposure to these extremes would be more severe, in contrast to the SSP2-4.5 scenario. Under the SSP2-4.5 scenario, 47.88% of the study area is projected to experience dangerously high levels of population exposure to precipitation extremes compared to the baseline. Under the SSP5-8.5 scenario, the areas experiencing dangerous exposure levels would increase by 4.11% by the 2030s, with 18.76% of areas experiencing earlier occurrences. In the North China Plain, the geographic centroid of population exposure is expected to move toward southward. These findings aid governmental authorities in identifying crucial timeframes, devising effective response strategies, and adjusting spatial disaster reduction resource allocation plans. [ABSTRACT FROM AUTHOR]

Non-methane short-lived climate forcer (SLCF) or near-term climate forcer (NTCF) emissions, as a significant driver of climate change, can be reduced to improve air quality. These reductions may contribute to additional warming of the climate system in the short term, thereby strongly affecting the likelihood of climate extremes. However, there has been no quantitative assessment of the impact of non-methane SLCF mitigation on compound flood–heatwave extremes (CFHEs). This study quantitatively investigates the changes in future (2031–2050 versus 1995–2014) CFHEs and the resulting population exposure in the Northern Hemisphere (NH) due to non-methane SLCF reductions. We used multi-model ensemble simulations under two future scenarios from the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The two future scenarios share the same greenhouse gas (GHG) emissions but have weak (Shared Socioeconomic Pathway (SSP) 3–7.0) versus strong (SSP3-7.0-lowNTCF) levels of air quality control measures. The results show that future non-methane SLCF reductions during 2031–2050 results in about a 7.3% ± 2.3% increase in grid exposure to CFHEs in the NH relative to the period 1995–2014. The frequency, intensity, and duration of CFHEs increase by varying degrees. During the period 2031–2050, the frequency of CFHEs across the NH increases by 2.9 ± 0.9 events per decade due to non-methane SLCF reductions. The increases in CFHE frequency are more pronounced in East Asia, South Asia, Siberia, and northern and eastern North America. In East and South Asia, the intensities of both heatwaves and floods corresponding to CFHEs increase markedly, where heatwave magnitude (HWM) increases by 0.3 ± 0.2 K in East Asia and weighted average precipitation (WAP) increases by 18.3% ± 15.3% and 12.0% ± 4.5% in East Asia and South Asia, respectively. In other regions, rising temperatures dominate the increase in CFHEs. With regard to the duration of CFHEs, future reductions in non-methane SLCFs increases the duration of CFHEs in the NH by 0.3 ± 0.1 d. Regionally, the sensitivity of CFHE frequency to global warming caused by non-methane SLCF mitigation is 1.2–1.9 times higher than that caused by GHG forcing. Non-methane SLCFs results in NH-averaged increases in population exposure to CFHEs of (5.0 ± 2.0) × 105 person·event in the period 2031–2050. This study emphasizes the importance of considering the impacts of cleaner air in future responses to compound extremes and corresponding societal planning.

Tropical cyclones frequently occur in densely populated coastal areas of China, causing serious casualties. Based on the data of tropical cyclones in the Northwestern Pacific from 1980 to 2020, the present study analyzed the spatiotemporal distribution characteristics of the generation and landfall of tropical cyclones that landed in China. Combined with spatialized population data of China during the same period, sensitivity experiments were conducted to analyze the main influencing factors of the changes in tropical cyclone exposure and their respective contribution rate. The results show that: (1) From 1980 to 2020, a total of 1217 tropical cyclones were generated in the Northwestern Pacific, 270 of which landed in China, and the frequency of cyclones generated and those landed in China showed a decreasing trend; among them, 88 tropical cyclones of typhoon intensity or higher made landfall, showing a slowly increasing trend, and the frequency of strong typhoons increased significantly. (2) Tropical cyclones of typhoon intensity or higher mainly landed in Guangdong, Zhejiang, Hainan, Fujian, and Jiangsu provinces in descending order of landing frequency, while super typhoons concentrated in Guangdong, Zhejiang, Fujian, and Hainan provinces. (3) From 1980 to 2020, the total population exposed to tropical cyclones of typhoon intensity or higher in China was 3.58 billion, and the exposed population in 2016 was 250 million, the highest in history; the cumulative affected area during the same period was 9.5×106 km², and Guangxi had the largest cumulative exposure area, 2.1 × 106 km². (4) The contribution rate of tropical cyclones to population exposure was the highest in all periods, exceeding 60%; it first increased and then decreased over the interdecadal time scale, reaching a peak of 80.3% during 2000-2009; the contribution rate of population and other factors showed synchronous changes (first decrease and then increase with time), and the increase in the contribution of population was greater. [ABSTRACT FROM AUTHOR]

The Huaihe River basin (HRB) of China located in the climate transition zone between warm temperate and subtropical areas is highly sensitive to climatic change. However, the changes in future climate extreme events under anthropogenic warming and the population exposure to these climate extremes in HRB remain unexplored. Here, using the eight commonly used extreme climate indices and based on the bias‐corrections of 16 global climate models (GCMs) in CMIP6, we present a projection and uncertainty analysis of extreme events and investigate the corresponding population exposure risk in HRB under three shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, SSP5‐8.5). The 16‐GCM ensemble mean projects an evident warming trend under all three scenarios with a total increase of 25.6–68.0 days in summer days (>25°C) by the end of the century in HRB. Larger increases (decreases) in maximum and minimum temperatures (frost days) are projected in the western HRB. Very heavy rain days (R20mm), maximum 5‐day precipitation (RX5day) and simple daily intensity index (SDII) will experience intensification across most of HRB (especially in southern and western HRB). The consecutive dry days is projected to decrease in northwestern HRB and increase in southern HRB. However, there is a large spatial variability in GCM uncertainty with a higher SSP scenario generally having higher uncertainty. Increases in summer days and R20mm exacerbate population exposure in HRB in near future (2030–2059), but in far future (2070–2099) although summer days (R20mm) continues to rise, population exposure is expected to decrease due to the rapid decline in population density. [ABSTRACT FROM AUTHOR]

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding of their impact on human health and socio-economic realms. This study delves into the anticipated implications of elevated global temperatures, specifically the 1.5 and 2.0 °C warming scenarios under the SSP2-4.5 and SSP5-8.5 pathways, on population and GDP exposure to heatwaves in China. We also evaluated the aggregated impacts of climate, population, and GDP and their interactions on future socio-economic exposure across China. We leveraged data sourced from the climatic output of Coupled Model Intercomparison Project Phase 6 (CMIP6) for heatwave analysis and integrated population and GDP projections under divergent Shared Socio-economic Pathways (SSPs), including SSP2-4.5 (low emission) and SSP5-8.5 (high-emission). Results indicate a drastic surge in the number of heatwave days under both warming scenarios, particularly in regions like Xinjiang (XJ), North China (NC), and South China (SC) subregions, with a notable disparity in the elevation of heatwave days among different levels. There is an alarming surge in population exposure, escalating approximately 7.94–8.70 times under the 1.5 °C warming scenario and markedly increasing by 14.48–14.75 times by the 2100s relative to the baseline (1985–2014) under the more extreme 2.0 °C warming level. Likewise, the study unveils a substantial elevation in GDP exposure, ranging from 40.65 to 47.21 times under the 1.5 °C warming level and surging dramatically by 110.85–113.99 times under the 2.0 °C warming level. Further analyses disclose that the climate effect predominantly influences changes in population exposure, constituting 72.55–79.10% of the total change. Meanwhile, the interaction effect notably shapes GDP exposure alterations, contributing 77.70–85.99% to the total change. The comprehensive investigation into alterations in population and GDP exposure under varying warming scenarios, coupled with the quantification of each contributing factor, holds paramount importance in mitigating the detrimental repercussions of heatwaves on both human life and socio-economic landscapes. [ABSTRACT FROM AUTHOR]

In this study changes in the heatwave characteristics and associated population exposure for the five months (March–July) of the year is examined over India. The study considered 1.5 °C, 2 °C, and 3 °C global warming levels (GWL) and for two time periods, i.e., the near future (T1; 2021–2050) and the distant future (T2; 2071–2100) using the Coupled Model Intercomparison Phase 6 (CMIP6) framework. This study identifies the heatwave using the extreme heatwave factor (EHF). The findings demonstrate a significant rise in mean summer heatwave frequency, duration, and severity with increasing GWLs. With the increase in GWLs, most of the regions of India would face severe heatwave but the Himalayan, Coastal, and Northeast regions are the most vulnerable to heat waves and associated severity. The March (18-fold) and April (9-fold) months show the maximum increase in severity compared to the months of May, June, and July from the current world (1991–2020). The population exposure showed significant regional variations, with the Coastal and Northeast regions seeing the highest exposure for all SSPs and warming periods, and the Himalayan region experiencing the lowest exposure. Comparing the population under all SSP, climate change contributes more to total exposure. The total exposure increases 1.4–1.6 folds from 1.5 to 2 °C GWL under all SSPs over India. [ABSTRACT FROM AUTHOR]

Heatwaves have significant effects on ecosystems and human health. Human habitability is impacted severely as human exposure to heatwaves is projected to increase, however, the contribution of soil moisture effects to the increased exposure is unknown. We use data from four climate models, in which two experiments are used to isolate soil moisture effects and in this way to examine projected changes of soil moisture contributions to projected increases in heatwave events. Contributions from soil moisture to future population exposure to heatwaves are also investigated. With soil moisture effects combined with global warming, the longest yearly heatwaves are found to increase by up to 20 days, intensify by up to 2°C in mean temperature, with an increasing of frequency by 15% (the percentage relative to the total number of days for a year) over most mid‐latitude land regions by 2040–2070 under the SSP585 high emissions scenario. Furthermore, soil moisture changes are found to have a significant role in projected increases of multiple heatwave characteristics regionally compared with the global land area and contribute to more global population exposed to heatwaves. Plain Language Summary: Heatwaves have great impacts on human health, agriculture, economy, and many other related societal factors. Existing research has not formed a comprehensive understanding of the influences from soil moisture and drought on population exposure to global heatwaves. This study aims to provide a better perception and quantification of soil moisture effects on changes of both heatwaves per se and population exposure to heatwaves, which will help to enhance further insights of climate change impacts on human society. Using outputs from dedicated climate model experiments, it is found detectable contributions from soil moisture changes on exacerbating heatwaves and increasing population exposure to them. This study can inform evidence‐based policies and potential land management techniques such as irrigation, land radiative management, and forestation, for mitigating the impacts of climate extremes. Key Points: We conducted the first global analysis of soil moisture effects on population exposure to heatwavesEffects of projected soil moisture changes constitute a strong component in the exacerbation of heatwaves over most land regionsPopulation exposure to heatwaves rises sharply in Asia, Australia, US, Europe, and central and southern Africa [ABSTRACT FROM AUTHOR]

This study utilizes climate scenario data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and population gridded data from shared socioeconomic pathways (SSPs) to identify extreme precipitation and high‐temperature events, along with their impact on the population in China and its subregions for both the near‐term future (2020–2050) and the long‐term future (2070–2100). The precipitation and temperature extremes in China are expected to increase during 2020–2100, and they will increase continuously with increasing radiative forcing. The spatial pattern of increases is similar across all SSPs‐RCPs scenarios, with a larger rise in the southern study area. Population exposure to extreme precipitation in China is anticipated to rise from 2020 to 2050 and decline from 2070 to 2100 under all scenarios, with a more pronounced decrease in SSP4‐6.0, and there is a transmutation in the chief determinant of populace vulnerability to extreme precipitation, transitioning from factors contingent upon population to those contingent upon climate from 2020–2050 to 2070–2100. In addition, temperature exhibits a general increasing trend in the impact area and population exposure from 2020–2050 to 2070–2100, concentrated in eastern and southern China. The exposed population's high‐value areas will continually expand with rising radiation forcing. Factors influencing population exposure to extremely high temperatures from 2020 to 2100, including climate, population, and their interaction, exhibit stable contribution rates, with population remaining the dominant factor. [ABSTRACT FROM AUTHOR]

Sensor-based air monitoring instruments (SAMIs) can provide high-resolution air quality data by offering a detailed mapping of areas that air quality monitoring stations (AQMSs) cannot reach. This enhances the precision of estimating PM2.5 concentration levels for areas that have not been directly measured, thereby enabling an accurate assessment of exposure. The study period was from 30 September to 2 October 2019 in the Guro-gu district, Seoul, Republic of Korea. Four models were applied to assess the suitability of the SAMIs and visualize the temporal and spatial distribution of PM2.5. Assuming that the PM2.5 concentrations measured at a SAMI located in the center of the Guro-gu district represent the true values, the PM2.5 concentrations estimated using QGIS spatial interpolation techniques were compared. The SAMIs were used at seven points (S1–S7) according to the distance. Models 3 and 4 accurately estimated the unmeasured points with higher coefficients of determination (R2) than the other models. As the distance from the AQMS increased from S1 to S7, the R2 between the observed and estimated values decreased from 0.89 to 0.29, respectively. The auxiliary installation of SAMIs could resolve regional concentration imbalances, allowing for the accurate estimation of pollutant concentrations and improved risk assessment for the population. [ABSTRACT FROM AUTHOR]

Flood event set generation, as employed in catastrophe risk models, relies on gauge information that is not available in data‐scarce regions. To overcome this limitation, we develop a stochastic fluvial and pluvial flood model of Southeast Asia, using freely and globally available discharge data from the global hydrological model GloFAS and rainfall from the ERA5 reanalysis. We use a conditional multivariate statistical model to produce a synthetic catalog of 10,000 years of flood events. We calculate the flood population exposure associated with each flood event using freely available population data from WorldPop and generate exposure probability exceedance curves. We validate the population exposure curves against observed flood disaster data from EM‐DAT, showing that our methodology provides exposure estimates that are in line with historical observations. We find that there is a 1% probability that more than 30 million people will be exposed to flooding in a given year according to our event set. This number is roughly half the population living in the 100‐year return period flood zone of Fathom's hazard maps, suggesting most studies based on static flood maps overestimate exposure. This analysis provides significant progress over previous non‐stochastic studies which are only able to compute total or average exposure within a given floodplain area and demonstrates that a reanalysis‐based stochastic flood model can be designed to generate reliable estimates of population exposure probability exceedance. This study is a step toward a fully global catastrophe model for floods capable of providing exposure and loss estimates worldwide. Key Points: Global hydrological models can be used to drive a large‐scale stochastic flood inundation model in Southeast AsiaA reanalysis‐based stochastic flood model generates realistic flood eventsThe computed flood exposure exceedance curve for Southeast Asia compares well to the EM‐DAT database [ABSTRACT FROM AUTHOR]

The Yangtze River basin is a typical region of the world that has a well-developed economy but is also greatly affected by multiple climate extremes. An improved understanding of future climate trends and associated exposures in this region is urgent needed to address socioeconomic risks. This research aims to quantify historical and future projected population exposure to precipitation extremes in the Yangtze basin using meteorological records and downscaled climate models. The study found that the hazard zone for precipitation extremes during baseline period was primarily located in the mid-lower Yangtze basin, particularly around the Poyang Lake watershed. Climate projections for 2050 indicate a further increase in the occurrence of precipitation extremes in this hazard zone, while a decrease in extreme events is detectable in the upper Yangtze basin under higher radiative forcing. Future socioeconomic scenarios suggest a tendency for population growth and migration towards the lower Yangtze basin, resulting in aggravated climate risks in megacities. Multi-model simulations indicate that population exposure to precipitation extremes in the lower Yangtze basin will increase by 9–22% around 2050, with both climate and population factors contributing positively. Shanghai, Changsha, Hangzhou, Ganzhou, and Huanggang are identified as hotspot cities facing the highest foreseeable risks of precipitation extremes in the Yangtze basin.

Due to climate change, rapid warming and its further intensification over different parts of the globe have been recently reported. This has a direct impact on human health, agriculture, water availability, power generation, various ecosystems, and socioeconomic conditions of the exposed population. The current study thus investigates the frequency and duration of heatwaves, human discomfort, and exposure of the human population to these extremes using the high-resolution regional climate model experiments under two Representative Concentration Pathways (RCP2.6, RCP8.5) over India. We find that more than 90% of India will be exposed to uncomfortable warm nights by the end of the 21st century with the highest rise over western India, Madhya Pradesh (MP), Uttar Pradesh (UP), Punjab, and the Haryana region. States like Odisha, Chhattisgarh, eastern parts of MP and UP, and some parts of J&K will be the worst hit by the intense and frequent heatwaves and human discomfort followed by the densely populated Indo-Gangetic plains under RCP8.5. Strict enforcement of the stringent policies on stabilization of population growth, improvement of local adaptive capacities, and economic status of the vulnerable population along with enforcing effective measures to curb greenhouse gas emissions are important to reduce human exposure to future heat stress. We demonstrate that a proper mitigation-based development (RCP2.6) instead of a business-as-usual scenario (RCP8.5) may help to reduce 50–200 heatwave days, 3–10 heatwave spells, and 10–35% warm nights over the Indian region. Consequently, this can avoid the exposure of 135–143 million population to severe discomfort due to extreme heat conditions by the end of the 21st century. [ABSTRACT FROM AUTHOR]

Climate extremes, such as hot temperature and heavy precipitation events, have devastating effects on human societies. As the planet gets warmer, they have become more intense and more frequent. To avoid irreversible damages from climate extremes, many countries have committed to achieving net‐zero anthropogenic carbon emissions, or carbon neutrality, by the 2050s. Here, we quantify the impact of carbon neutrality on population exposure to climate extremes using multi‐model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP)1‐1.9 and SSP3‐7.0 scenarios. It is found that the increasing population exposure to hot‐temperature and heavy‐precipitation extremes under SSP3‐7.0 scenario can be substantially reduced by 87%–98% in the late 21st century by achieving the carbon neutrality based on SSP1‐1.9 scenario. The benefits of carbon neutrality are particularly pronounced in Africa and Asia. The potential benefits of carbon neutrality are also significant in North America, Europe, and Oceania, where a reduction in climate extremes is more than twice as important as population decline in reducing population exposure to climate extremes. These results provide important scientific support for ongoing efforts to achieve net‐zero carbon emissions by the 2050s to reduce potential climate risk and its inequity across continents. Plain Language Summary: To avoid irreversible damages from climate extremes in a warming climate, net‐zero anthropogenic carbon emissions, or carbon neutrality, has been proposed. However, how much damages from climate extremes can be mitigated by achieving the carbon neutrality has not been quantitatively assessed. Here, we show that achieving carbon neutrality could lead to a significant and widespread reduction in population exposure to hot‐temperature and heavy‐precipitation extremes by 87%–98% in the late 21st century. The benefits of carbon neutrality are particularly large in Africa and Asia. Even in North America, Europe, and Oceania, where the developed countries are concentrated, population exposure to climate extremes is projected to decrease significantly, primarily due to reduced climate extremes with a minor contribution of population decline. This finding underscores the critical importance of ongoing efforts to achieve net‐zero carbon emissions by the 2050s to reduce potential climate risk and its inequity across continents. Key Points: By the 2050s, carbon neutrality reduces population exposure to climate extremes by 87%–98% compared to current global warming ratesAfrica and Asia are projected to experience the most dramatic reductions in population exposure to climate extremes by carbon neutralityIn North America, Europe, and Oceania, climate extreme change plays a more important role in population exposure to climate extremes [ABSTRACT FROM AUTHOR]

Population exposure is a dominant representation of rainstorm hazard risks. However, the refined precipitation data in temporal resolution and the comparison of exposure to different rainstorm events remain relatively unexplored. Hourly precipitation data from 165 meteorological stations w used to investigate the spatiotemporal evolution of population exposure to different rainstorm scenarios in the prefecture-level cities for different periods and age groups. The Geographical Detector was adopted to quantitatively analyze the influencing factors and contribution rates to changes in population exposure during each period. The results revealed that population exposure to persistent rainstorms and abrupt rainstorms was low in the center and high in the surrounding areas, and the high exposure value decreased significantly in the 2010s. Additionally, as the duration of rainstorm events increased, the center of the high-value area of population exposure shifted southward. The distribution of population exposure was closely related to the age structure, demonstrating strong consistency with the distribution of different age groups. Except for abrupt rainstorms, the contribution rates of the average land GDP and urbanization rate to the exposure of all rainstorm scenarios increased significantly. This implies that the main factors influencing population exposure have shifted from meteorological to socioeconomic factors. [ABSTRACT FROM AUTHOR]

A high percentage of the world's population lives in areas where air pollutant concentrations exceed the World Health Organization guidelines. This work aims to develop and test, a high-resolution multi-scale air pollution modelling system by integrating a set of adequate tools. This system is able to provide detailed air pollutant concentrations in urban areas and support air quality management strategies through a better identification of different atmospheric processes. It also allows furthering the design and assessment of air pollution control measures for a specific area. To evaluate its performance and suitability, the system was applied to the Macau Special Administrative Region (SAR), China, one of the most densely populated areas on earth, during a winter period when this area is affected by high levels of Particulate Matter (PM). Although the developed system tends to underestimate the PM concentrations, it revealed a good performance in reproducing the temporal and spatial air pollution patterns. Several exceedances of the Chinese air quality standards were calculated and high population exposure to PM pollution was estimated. The tested urban atmospheric emission reduction scenarios have shown air quality improvements, indicating that emission reduction measures at urban level should focus on the domestic sector. However, it is crucial to implement joint pollution prevention strategies with neighbouring regions to improve the air quality in Macau SAR. The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas. [ABSTRACT FROM AUTHOR]

Introduction: Computed tomography (CT) is one of the most widely used diagnostic procedures in modern medicine. Despite many technical improvements, CT still exposes patients to significantly higher doses of radiation than other methods of diagnostic imaging. The presented analysis of the number of CT scans performed in Poland in 2022 aims to designate priorities in the process of optimising radiation protection and makes it possible to identify those examinations and patient groups for which action is particularly justified. Material and methods: The data presented is based on an analysis of the National Health Fund (NHF) database of medical services reimbursed in 2022. According to the NHF data, approximately 5.1 million CT examinations were performed. The coding of reimbursed medical procedures used by the NHF in 2022 included 45 different CT procedures. Results: The highest ratio of the number of examinations performed to the number of patients was found in the age group 59-75 years (average 1.35). This ratio varied according to examination type and was closest to 1 for spine and extremities examinations (between 1.1 and 1.2 on average). Irrespective of patients' age and type of examination, the proportion of female and male patients fluctuates around 50%. Approximately 82% of head and neck examinations are single-phase CTs. Examinations with two or more phases account for about 17% and less than 1%, respectively. Conclusions: Over the past 10 years, both the number of CT scanners and the number of annually performed scans have doubled. Relative to the population size, this is a rate of about 22 scanners per one million people, an average level for European countries, ranging from a maximum of around 37 for Italy and Germany to around 20 for France, Spain, and Romania, according to Eurostat data. [ABSTRACT FROM AUTHOR]

Abstract Heatwaves have significant effects on ecosystems and human health. Human habitability is impacted severely as human exposure to heatwaves is projected to increase, however, the contribution of soil moisture effects to the increased exposure is unknown. We use data from four climate models, in which two experiments are used to isolate soil moisture effects and in this way to examine projected changes of soil moisture contributions to projected increases in heatwave events. Contributions from soil moisture to future population exposure to heatwaves are also investigated. With soil moisture effects combined with global warming, the longest yearly heatwaves are found to increase by up to 20 days, intensify by up to 2°C in mean temperature, with an increasing of frequency by 15% (the percentage relative to the total number of days for a year) over most mid‐latitude land regions by 2040–2070 under the SSP585 high emissions scenario. Furthermore, soil moisture changes are found to have a significant role in projected increases of multiple heatwave characteristics regionally compared with the global land area and contribute to more global population exposed to heatwaves.

Heatwave exposure has increased dramatically because of climate warming and population growth, along with their interactive effects. However, effective adaptation measures can reduce these impacts. Nonetheless, the dynamic changes, regional inequality in adaptive capacity and their potential contributions to reducing exposure in the future remain unclear. This study quantifies the impact of adaptive capacity and underscores regional variations in heatwave magnitudes, population exposure and adaptation levels in China. We projected the future adaptive capacity using air-conditioner penetration, factoring in climate cooling requirements and individuals’ purchasing power. Utilising population and gross domestic product (GDP) data from four Shared Socioeconomic Pathways (SSP1, SSP2, SSP3 and SSP5) and daily temperature data from four SSP-based emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5), we estimated heatwave duration, population exposure and avoided impacts through adaptation across China and its sub-regions. Results show a substantial increase in heatwave duration in Southwest and Southern China, especially under the SSP5-8.5 scenario, with a projection of 163.2 ± 36.7 d during 2081–2100. Under the SSP3|SSP3-7.0 scenario, total exposure reaches 156.4 ± 76.8 billion person d per year, which is the highest among all scenarios and 23 times greater than that in 1986–2005 without adaptation. Upon considering adaptation measures, a noteworthy reduction in population exposure is observed, especially in the SSP3|SSP3-7.0 and SSP5|SSP5-8.5 scenarios, with reductions of (62.6 ± 3.9) % and (65.8 ± 5.1) %, respectively, compared with the scenario without adaptation during 2081–2100. Remarkable regional disparities in avoided impacts are also evident, with variations of up to 50% across different regions. The implementation of effective and environmentally friendly adaptation measures can notably address climate change, thereby alleviating the profound threats posed to human well-being.

Hazmat transportation in cities faces significant risks that may cause catastrophic losses to humans. From the perspective of the regulator, the main responsibility is to mitigate hazmat transport risk by determining the availability of road networks to hazmat carriers. Based on the time-variant population distribution, the hazmat transport risk was assessed via the total population exposure associated with the resident and variable populations at different times. We propose a risk-minimizing urban hazmat road network design model for multiple types of hazmats, considering time-varying traffic. The model was applied to a realistic case study of hazmat transportation in a densely populated urban area with complex traffic in Shanghai, China.

In the context of global climate change and urban expansion, urban residents are encountering greater rainstorm waterlogging risk. Quantifying population exposure to rainstorms is an important component of rainstorm waterlogging risk assessments. This study utilized a two-dimensional hydrodynamic model to simulate the inundation water depth and inundation area resulting from rainstorms, with return periods of 5, 10, 50, and 100 years, in the Xiong'an New Area, and overlaid the gridded population data in 2017 and in 2035 under SSP2 to assess the change in population exposure. The results show that the average inundation depth and area increase were from 0.11 m and 207.9 km2 to 0.18 m and 667.2 km2 as the rainstorm return period increased from once in 5 years to once in 100 years. The greatest water depths in the main urban areas were mainly located in the low-lying areas along the Daqing River. The total population exposed to rainstorm waterlogging for the 5-, 10-, 50-, and 100-year return periods was 0.31, 0.37, 0.50, and 0.53 million, respectively, in 2017. However, this is projected to rise significantly by 2035 under SSP2, increasing 2–4-fold compared with that in 2017 for the four return periods. Specifically, the projected population exposure is expected to be 0.7, 1.0, 1.8, and 2.0 million, respectively. The longer the return period, the greater the increase in population exposure. The proportion of the population exposed at the 0.05–0.2 m water depth to the total population exposure decreases as the return periods increases, whereas the proportion changes in the opposite direction at the 0.2–0.6 m and >0.6 m depth intervals. Spatially, high-exposure areas are concentrated in densely populated main urban regions in the Xiong'an New Area. In the future, more attention should be paid to densely populated low-lying areas and extreme recurrence rainstorm events for urban flood-risk management to ensure population safety and sustainable urban development. [ABSTRACT FROM AUTHOR]

Effective risk management requires accurate assessment of population exposure to volcanic hazards. Assessment of this exposure at the large-scale has often relied on circular footprints of various sizes around a volcano to simplify challenges associated with estimating the directionality and distribution of the intensity of volcanic hazards. However, to date, exposure values obtained from circular footprints have never been compared with modelled hazard footprints. Here, we compare hazard and population exposure estimates calculated from concentric radii of 10, 30 and 100 km with those calculated from the simulation of dome- and column-collapse pyroclastic density currents (PDCs), large clasts, and tephra fall across Volcanic Explosivity Index (VEI) 3, 4 and 5 scenarios for 40 volcanoes in Indonesia and the Philippines. We found that a 10 km radius—considered by previous studies to capture hazard footprints and populations exposed for VEI ≤ 3 eruptions—generally overestimates the extent for most simulated hazards, except for column collapse PDCs. A 30 km radius – considered representative of life-threatening VEI ≤ 4 hazards—overestimates the extent of PDCs and large clasts but underestimates the extent of tephra fall. A 100 km radius encapsulates most simulated life-threatening hazards, although there are exceptions for certain combinations of scenario, source parameters, and volcano. In general, we observed a positive correlation between radii- and model-derived population exposure estimates in southeast Asia for all hazards except dome collapse PDC, which is very dependent upon topography. This study shows, for the first time, how and why concentric radii under- or over-estimate hazard extent and population exposure, providing a benchmark for interpreting radii-derived hazard and exposure estimates. [ABSTRACT FROM AUTHOR]

For correct assessment of health risks after low-dose irradiation, calculation of radiation exposure estimates is crucial. To verify the calculated absorbed doses, instrumental methods of retrospective dosimetry are used. We compared calculated and instrumental-based estimates of external absorbed doses in the residents of Dolon, Mostik and Cheremushki villages, Kazakhstan, affected by the first nuclear weapon test performed at the Semipalatinsk Nuclear Test Site (SNTS) on August 29, 1949. The 'instrumental' doses were retrospectively estimated using the Luminescence Retrospective Dosimetry (LRD) and Electron Spin Resonance (ESR) methods. Correlation between the calculated individual cumulative external absorbed whole-body doses based on typical input data and ESR-based individual doses in the same people was strong (r = 0.782). It was even stronger between the calculated doses based on individual questionnaires' input data and the ESR-based doses (r = 0.940). Application of the LRD method is useful for validation of the calculated settlement-average cumulated external absorbed dose to air. Reconstruction of external exposure can be supplemented with the data from later measurements of soil contamination with long-lived radionuclides, such as, 137Cs. Our results show the reliability of the calculational method used for the retrospective assessment of individual external doses. [ABSTRACT FROM AUTHOR]

Abstract Climate extremes, such as hot temperature and heavy precipitation events, have devastating effects on human societies. As the planet gets warmer, they have become more intense and more frequent. To avoid irreversible damages from climate extremes, many countries have committed to achieving net‐zero anthropogenic carbon emissions, or carbon neutrality, by the 2050s. Here, we quantify the impact of carbon neutrality on population exposure to climate extremes using multi‐model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP)1‐1.9 and SSP3‐7.0 scenarios. It is found that the increasing population exposure to hot‐temperature and heavy‐precipitation extremes under SSP3‐7.0 scenario can be substantially reduced by 87%–98% in the late 21st century by achieving the carbon neutrality based on SSP1‐1.9 scenario. The benefits of carbon neutrality are particularly pronounced in Africa and Asia. The potential benefits of carbon neutrality are also significant in North America, Europe, and Oceania, where a reduction in climate extremes is more than twice as important as population decline in reducing population exposure to climate extremes. These results provide important scientific support for ongoing efforts to achieve net‐zero carbon emissions by the 2050s to reduce potential climate risk and its inequity across continents.

Extreme heat-precipitation events, such as heatwaves and extreme precipitation, can have substantial impacts on the population, particularly in urbanized watersheds. However, few studies have investigated individual and compound extreme heat-precipitation events, causing much valuable information loss for watershed climate risk management. This study focuses on the Pearl River Basin (PRB), a highly urbanized area in southern China, and aims to predict changes in population exposure to extreme heat-precipitation events. To achieve this, a ranked ensemble global climate model (GCM) was used to generate projections for individual extreme precipitation, heatwaves, and sequential and coincident heat waves and precipitation extremes (SHWPs and CHWPs) under three future scenarios (SSP-RCPs). The main findings of the study are as follows: Precipitation extremes represent increasing extreme days and intensity under all three scenarios across the PRB. Towards the end of the 21st century, the SSP5-8.5 scenario predicts that heat waves will last ten times longer than historical records. Comparing two types of compound extreme events, we conclude that the 21st century will see a near-term high risk for SHWPs and a long-term high risk for CHWPs in the PRB. Furthermore, in both individual and compound heat-precipitation events, five hotspot cities in the PRB (i.e., Guangzhou, Dongguan, Foshan, Shenzhen, and Huizhou) will face higher population exposure to extreme heat-precipitation events. These cities share common characteristics: key to economic development, coastal, and densely populated. This study can provide insight into extreme climate risk management in other tropical and subtropical basins.

Climate change is often described as the average changes in temperature and precipitation; however, it is the change in climate extremes determines the levels of socioeconomic impacts related to climate change. It is generally believed that global warming drives increase in frequency, intensity and duration of precipitation extremes, but these changes vary regionally. Focusing on the relationships between evolution of extreme events and long-term climate change, here we propose a novel classification scheme based on Kӧppen's system and changes in mean and variability of precipitation, divide the global climate into 20 different changing types and reveal the regional evolution of precipitation extremes. We find that precipitation extremes ascend significantly in wetting regions, especially in tropical and temperate zones, independent with changed variability. As for drying regions, the evolution of extremes is related to precipitation variability. An increase of extremes can still be detected in fluctuant-drying areas, while a slight decrease can be seen in stabilized-drying areas. It is surprising to find increase in both wetness and dryness extremes which implies higher intensity of meteorological hazards in densely populated areas. Based on the current and projected growth of population exposure to precipitation extremes, we identify some hotspots with high potential risk in the future.

Climate extremes pose severe threats to human health, economic stability and environmental sustainability, especially in densely populated areas. It is generally believed that global warming drives increase in frequency, intensity and duration of climate extremes, and socioeconomic exposure plays a dominant role in climate impacts. In order to promote climate risk governance at regional level, the historical and projected trends in the population exposure to climate extremes are quantified in eastern China using downscaled climate simulations and population growth scenarios. The frequency of temperature extremes (tx35days) is projected to more than double by 2050 in nearly half of prefecture-level cities in eastern China, leading to an 81.8% increment of total exposure under SSP2-4.5 scenario. The increasing trend is also detectable in the frequency of precipitation extremes (r20mm) in eastern China, and the exposure increment is projected to be 22.9% by 2050, with a near equivalent contributions of both climate change and population growth. Spatially, temperature exposure mainly grows in southern Hebei, western Shandong and inland Guangdong provinces, while precipitation exposure raises principally in southeast coastal areas of China. Based on the historical baseline and projected amplification of population exposure, we identify some hotspot cities such as Guangzhou, Shanghai, Dongguan and Hangzhou that response to climate change dramatically and confront greater potential risk of climate extremes in the coming future.

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding of their impact on human health and socio-economic realms. This study delves into the anticipated implications of elevated global temperatures, specifically the 1.5 and 2.0 °C warming scenarios under the SSP2-4.5 and SSP5-8.5 pathways, on population and GDP exposure to heatwaves in China. We also evaluated the aggregated impacts of climate, population, and GDP and their interactions on future socio-economic exposure across China. We leveraged data sourced from the climatic output of Coupled Model Intercomparison Project Phase 6 (CMIP6) for heatwave analysis and integrated population and GDP projections under divergent Shared Socio-economic Pathways (SSPs), including SSP2-4.5 (low emission) and SSP5-8.5 (high-emission). Results indicate a drastic surge in the number of heatwave days under both warming scenarios, particularly in regions like Xinjiang (XJ), North China (NC), and South China (SC) subregions, with a notable disparity in the elevation of heatwave days among different levels. There is an alarming surge in population exposure, escalating approximately 7.94–8.70 times under the 1.5 °C warming scenario and markedly increasing by 14.48–14.75 times by the 2100s relative to the baseline (1985–2014) under the more extreme 2.0 °C warming level. Likewise, the study unveils a substantial elevation in GDP exposure, ranging from 40.65 to 47.21 times under the 1.5 °C warming level and surging dramatically by 110.85–113.99 times under the 2.0 °C warming level. Further analyses disclose that the climate effect predominantly influences changes in population exposure, constituting 72.55–79.10% of the total change. Meanwhile, the interaction effect notably shapes GDP exposure alterations, contributing 77.70–85.99% to the total change. The comprehensive investigation into alterations in population and GDP exposure under varying warming scenarios, coupled with the quantification of each contributing factor, holds paramount importance in mitigating the detrimental repercussions of heatwaves on both human life and socio-economic landscapes.

Climate change is altering the conditions to which communities have adapted. The Köppen–Geiger classification system can provide a compact metric to identify regions with notable changes in climatic conditions. Shifting Köppen–Geiger climate zones will be especially impactful in regions with large populations. This study uses high-resolution datasets on Köppen–Geiger climate zones and populations to quantify the number of people affected by shifting climate zones (i.e., population exposure to shifting climate zones). By the end of this century, 9–15% of the Earth’s land surface is projected to shift its climate zone. These shifts could affect 1.3–1.6 billion people (14–21% of the global population). Many of the affected people live in areas that were classified as temperate in the historical period. These areas are projected to be classified as tropical or arid in the future. This study presents a new metric for exposure to climate change: the number of people living in areas whose climate zone classification is projected to shift. It also identifies populations that may face climatic conditions in the future that deviate from those to which they have adapted.

BackgroundChloropropanol esters (MCPDE) have attracted much attention in recent years as a kind of new contaminant found in various refined oils. The pollution of 3-monochloropropane-1,2-diol esters (3-MCPDE) is the most prominent. 3-MCPDE is hydrolyzed in organisms to 3-monochloropropane-1,2-diol which has been shown to have reproductive toxicity, nephrotoxicity, and potential carcinogenicity. Infant formula powders can be polluted by 3-MCPDE when refined edible oils are added during production.ObjectiveTo assess the risk of exposure to 3-MCPDE related to the consumption of infant formula powders for children aged 0-3 years in Shanghai market using the food consumption data and the data of 3-MCPDE contamination in these foods.MethodsGas chromatography-mass spectrometry was used to determine 3-MCPDE in 133 samples of infant formula powders in Shanghai. Using a multistage stratified random sampling method, a total of 807 infants and toddlers aged 0-3 years were randomly selected from each district/rural/town in Shanghai, including 208 children aged 0-6 months, 276 children aged 6-12 months, and 323 children aged 12-36 months. The food consumption data was investigated using food frequency questionnaire (FFQ) distributed by combining telephone inquiries and face-to-face interviews among guardians. Population's probability distributions of 3-MCPDE exposure were assessed by @Risk 7.5 software and Monte Carlo simulation algorithm. According to the dietary intake assessment model and the tolerable daily intake (TDI) of 3-MCPDE of 2.00 μg·(kg·d)−1 proposed by the European Food Safety Authority (ESFA), a risk assessment of exposure to 3-MCPDE was conducted for infants and toddlers aged 0 to 3 years old in Shanghai who consumed 3-MCPDE via infant formula powders.ResultsThe average concentration of 3-MCPDE in 133 samples of infant formula powders was 0.115 mg·kg−1 with a positive rate of 100.00%. Among different types of formula powders, infant formula powders for infants of 0-6 months had the highest concentrations of 3-MCPDE and fat [0.136 mg·kg−1 and 25.2 g (per 100 g sample) in average respectively]. There was a positive correlation between fat concentration and 3-MCPDE concentration in the samples (r=0.438, P

Study region: Lower Chao Phraya River Basin (LCPRB), Thailand. Study focus: This study aims to make a robust assessment based on a large ensemble d4PDF dataset and a flood-inundation model Inundation Model Coupling Rainfall-runoff (IMCR) for the LCPRB. Inundation area and depth for 100-year flooding are evaluated for the flood volume of capacity greater than 2000 m3/s for both past (1951–2010) and future (2051–2100) climates. This study also evaluates the affected population exposure in the region for both past and future climate scenarios. New hydrological insights for the region: The IMCR inundation simulation findings indicate that compared to the historical climate, the inundation area increases by an average of 1.0–1.4 times, and the critical area (depth >3 m) increases by an average of 1.1–1.3 times. On the other hand, the exposed population in the future, with respect to the SSP5 scenario ''Taking the Highway,'' is expected to decrease on average by 0.7–0.9 times in comparison to the past climate for depth > 0 m. However, keeping the population constant as in the past, the exposed population is likely to increase on average by 1.3–1.4 times in comparison to the past climate for depth > 0 m.

This work investigates the possible future changes and impacts in spatiotemporal variation and regional features of multivariate compound heatwaves (CHWs) in China using the latest Universal Thermal Climate Index from the Coupled Model Intercomparison Project Phase 6 simulations (CMIP6). Results indicate both strong CHWs and extremely threatening CHWs in China are projected to increase substantially in both frequency and spatial extent under different future climate scenarios while with discernible regional disparities. The more severe global warming is, and the greater the extremity of the heatwave events is, the faster the increase in CHWs is. These findings are derived from the CMIP6 projections calibrated using the robust empirical quantiles method. Climate change causes more areas and people to be exposed to CHWs. Notably, the population exposure to dangerous CHWs will increase significantly in northwest China and will appear in northeast China after the mid‐21st century under the high emission scenario. Plain Language Summary: Extreme multivariate compound heatwaves (CHWs) may have devastating impacts on human health and have attracted significant societal attention. We explored the possible future changes in dangerous multivariate CHWs in China based on the latest Universal Thermal Climate Index (UTCI) from the Coupled Model Intercomparison Project Phase 6 simulations (CMIP6) project. Results show that the CMIP6 UTCI in China has a warm bias compared to the observations. A nonparametric quantile mapping using a robust empirical quantiles method is employed which can effectively correct this bias and is used to constrain future CMIP6 projections to reduce uncertainties. Two categories of dangerous CHWs are investigated in the current work, that is, strong compound heatwaves and extremely threatening CHWs. Results indicate an expected acceleration in the rate of CHWs and population exposure after the mid‐21st century, primarily driven by climate changes. Moreover, the rate of acceleration is found to be more pronounced for CHWs of higher extremities and in the context of the increased severity of global warming. Additionally, population exposure to extremely threatening CHWs will increase significantly not only in southeastern China but also in northwestern and northeastern regions. Our study highlights the critical importance of mitigating climate change to minimize the threat posed by dangerous CHWs to human populations. Key Points: A nonparametric quantile mapping method can effectively correct the warm bias in the latest Coupled Model Intercomparison Project Phase 6 simulations Universal Thermal Climate Index in ChinaThe increasing rate of compound heatwaves (CHWs) in China will accelerate with the increase in the event extremity and severity of warmingPopulation exposure to CHWs will increase significantly in northwest and northeast China in a warmer world [ABSTRACT FROM AUTHOR]

The Paris Agreement proposed two global warming levels relative to the preindustrial period, with the ideal objective of 1.5°C warming and an upper boundary of 2.0 °C. However, the years when the temperature will first reach 1.5 or 2.0°C vary in different regions. Therefore, climate extremes and their population exposure are still not clear at regional or global warming levels. This study investigated climate extremes in China at different Chinese and global warming with 16 CMIP6 models under the middle SSP245 scenario. In China, the year when 1.5°C warming is projected to occur is 2020 and 2035 for 2.0°C warming. These values are more than 10 years earlier than the corresponding global warming levels of 2030 and 2049. Population exposure to percentile‐based heat extremes at global 1.5°C warming is projected to greatly increase relative to those when 1.5°C warming occurs in China due to increases in climate extremes, and exposure to absolute heat extreme indices is projected to decrease from Chinese to global 2.0°C warming under the joint impacts of increases in extremes and population decreases. Furthermore, from Chinese to global 1.5°C warming, about 344 million people will experience increased exposure to heat, wet and dry extremes, and around 468 and 371 million people will be affected by increased exposure to heat–wet and heat–dry extremes, respectively. Thus, a more adaptive strategy should be proposed to cope with the future possible natural hazards caused by heat–wet and heat–dry extremes. Plain Language Summary: In general, heat extremes are projected to increase in a warmer climate. However, changes in surface air temperature will vary among different regions at regional and global warming levels which might impact future climate extremes and their population exposure. The heat extremes, heavy precipitation amount and consecutive days with no precipitation, and population exposure to these extremes were investigated at global and Chinese 1.5 or 2.0°C warming levels. The years when 1.5 and 2.0°C warming will occur in China are more than 10 years earlier than those of global warming levels, respectively. About 344 million people will be involved in increased exposure to above three types of extremes moving from Chinese to global 1.5°C warming. Thus, more adaptive strategies should be established to cope with the possible increased risks in the future. Key Points: Warming by 1.5 and 2.0°C will occur more than 10 years earlier in China compared with global warming levelsPopulation exposure to percentile‐based heat extremes in China is projected to greatly increase from Chinese to global 1.5°C warmingAbout 400 million people will experience increased exposure to heat–wet and heat–dry extremes from Chinese to global 1.5°C warming [ABSTRACT FROM AUTHOR]

The increase in record‐breaking extreme events caused by climate change poses a threat to human health and well‐being. Understanding the future impacts of such events on global populations can provide decision‐making support for policies aiming to mitigate climate change. Here, we investigated the population exposure to eight climate extreme indices and drivers of exposure trajectories based on National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections Coupled Model Intercomparison Project 6 and population projection data under four shared socioeconomic pathway scenarios at a spatial resolution of 0.25° × 0.25°. The results show that by the mid‐twenty‐first century, most regions worldwide, especially Africa and South America, will continue to experience record‐breaking temperatures and compound drought and heatwaves (CDHWs). Regarding population exposure, under SSP3‐7.0 in the late twenty‐first century, the mean value of the multimodel median expected annual exposure (EAE) of all extreme temperature indices and CDHW reaches 8.12 billion persons per year. Population exposure hotspots will be concentrated in Central Africa, South Asia, Southeast Asia, and East Asia, mostly in developing countries, where 55.01%–87.42% of the EAE is found. The drivers of exposure trajectories are spatially heterogeneous. The increase in record‐breaking probability contributes more than population growth to EAE growth in most regions of the world except Central Asia, the Middle East, and most of Africa. These findings reveal the future trajectories of record‐breaking probabilities and population exposures for climate extremes, which can inform understanding of the intersections between climate change and population change and future risk management. Plain Language Summary: Climate change causes rapid increases in extreme weather events that threaten human health and well‐being. Understanding the future impacts of climate change on the global population can inform policies aiming to mitigate climate change. Here, we investigated the spatiotemporal dynamics of future record‐breaking extreme temperature and precipitation events, sequential precipitation and heatwaves (hot extremes after heavy precipitation), and compound drought and heatwaves (cooccurring dry and hot extremes) (CDHWs) and analyzed how populations may be potentially affected by these events based on the latest available climate model data and future population projections. The results show that by the mid‐twenty‐first century, most regions worldwide, especially Africa and South America, will continue to experience record‐breaking temperatures and CDHWs. Regions where populations will be most affected include Central Africa, South Asia, Southeast Asia, and East Asia, mostly developing countries. This increase in the affected population is due to the growth of the population and the increase in record‐breaking extreme events; record‐breaking extreme event increases contribute more than population growth in most regions of the world except Central Asia, the Middle East, and most of Africa. Overall, this study projected the spatiotemporal patterns of unprecedented climate extremes and affected populations to inform risk management. Key Points: Africa and South America will experience successive record‐breaking extreme events and even compound droughts and heatwavesPopulation exposure will be highly uneven and largely concentrated in underdeveloped areasA record‐breaking increase in probability will be the major driver of the increase in population exposure in most regions of the world [ABSTRACT FROM AUTHOR]

This study employs precipitation data sets from historical trials on 20 CMIP6 global climate models and four shared socioeconomic pathway scenario trials (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to predict trends in extreme precipitation changes in Henan Province quantitatively, while ascertaining the risk of population exposure to extreme precipitation in this area. The capacity of the CMIP6 models to simulate extreme precipitation indices from 1985 to 2014 is assessed using CN05.1 daily precipitation observational data. The correlation coefficients of the multi-model ensemble median's simulation of the extreme precipitation indices are approximately 0.8, with a standard deviation ratio closer to 1 compared with the single models, demonstrating superior modeling ability. Analyses using the multi-model ensemble median demonstrate an overall increase in the total amount, frequency, and intensity of extreme precipitation in Henan throughout this century, particularly in its southern regions; in the mid-century high-emission scenario (SSP5-8.5), the maximum increase in annual total precipitation exceeds 150 mm, and it can be over 250 mm in the late-century period. For the entire province, the maximum five-day precipitation increase relative to the historical period is nearly 25 mm in the late-century SSP5-8.5 scenario. The spatiotemporal concentration of precipitation will significantly increase, heightening the risk of flood disasters. Comparative analysis reveals that, under the same population prediction, the total population exposure will be higher in high radiative forcing scenarios than in low radiative forcing scenarios, especially in Kaifeng City, where the total population exposure in SSP1 and SSP5-8.5 exceeds that in SSP1-2.6 by 2 million person-days. However, in the same radiative forcing scenario, the total population exposure in the development pathway dominated by traditional fossil fuels (SSP5) will not be significantly higher than that in the sustainable development pathway (SSP1), indicating that population activity in this century will not be the main contributor to changes in total exposure. Overall, for Henan, in the same population forecast scenario, population exposure to extreme precipitation will gradually rise with global warming. [ABSTRACT FROM AUTHOR]

Xinjiang is one of the world's most sensitive and vulnerable regions to climate change. However, little is known about the current status and changes in thermal comfort conditions in this area. Using the Universal Thermal Climate Index (UTCI) derived from the newly available high-resolution dataset HiTiSEA, the spatial–temporal pattern and changes thereof over annual and seasonal scales across Xinjiang from 1981 to 2019 were evaluated. The results reveal that the distribution and change of thermal comfort in Xinjiang have apparent regional heterogeneity and seasonal characteristics. Across all scales, 7 of 10 UTCI thermal stress categories were observed, from slight cold stress to strong heat stress. Annually, the mean UTCI is 3 °C and has significantly increased at 0.37 °C decade−1. The mean number of comfortable days (CDs) is 114 days, with a range from 0 to 189 days. On the space scale, the Tarim Basin experiences the highest UTCI value, while the Ili River Valley, the north side of the Tianshan Mountains, and the peripheral areas of the Tarim Basin have a higher number of CDs. Seasonally, summer has the highest UTCI value, while winter is the lowest. The trend for all seasons is upward, and spring increases fastest. Results also indicate that air temperature has a positive correlation with climate comfort, and the influence of air temperature on climate comfort is most significant. Further research indicates that the range and intensity of population exposure to uncomfortable climates in Xinjiang have increased. The distribution and expansion of population exposure are similar to the population density. These findings contribute to a systematic understanding of the local climate environment and can be helpful for the assessment of the impact of climate change and optimize tourism development. [ABSTRACT FROM AUTHOR]

The increasing prevalence of warmer trends and climate extremes exacerbate the population's exposure to urban settlements. This work investigated population exposure changes to mean and extreme climate events in different Agro‐Ecological Zones (AEZs) of Pakistan and associated mechanisms (1979−2020). Spatiotemporal trends in mean and extreme temperatures revealed significant warming mainly over northern, northeastern, and southern AEZs. In contrast, mean‐to‐extreme precipitation changes showed non‐uniform patterns with a significant increase in the northeast AEZs. Population exposure to mean (extreme) temperature and precipitation events increased two‐fold during 2000–2020. The AEZs in urban settlements (i.e., Indus Delta, Northern Irrigated Plain, and Barani/Rainfall) show a maximum exposure to extreme temperatures of about 70–100 × 106 (person‐days) in the reference period (1979−1999), which increases to 140–200 × 106 person‐days in the recent period (2000−2020). In addition, the highest exposure to extreme precipitation days also increases to 40–200 × 106 person‐days during 2000–2020 than 1979−1999 (20–100 × 106) person‐days. Relative changes in exposure are large (60%–90%) for the AEZs across northeast Pakistan, justifying the spatial population patterns over these zones. Overall, the observed changes in exposure are primarily attributed to the climate effect (50%) over most AEZs except Northern Irrigated Plain for R10 and R20 events, where the interaction effect takes the lead. The population exposure rapidly increased over major AEZs of Pakistan, which could be more vulnerable to extreme events due to rapid urbanization and population growth in the near future. Plain Language Summary: This study investigates the impact of climate change on population in different AEZs of Pakistan from 1979 to 2020. The findings depict widespread warming trends in northern, northeastern, and southern AEZs of Pakistan, whereas changes in precipitation patterns are non‐uniform, with a notable increase in the northeast zone. The study reveals that population exposure to temperature and precipitation events doubled between 2000 and 2020. Urban AEZs such as the Indus Delta, Northern Irrigated Plain, and Barani/Rainfall exhibit the largest exposure to extreme temperatures and precipitation, with exposure increasing over time. The northeast zones of Pakistan experience the highest relative changes in exposure, highlighting the vulnerability of these AEZs to climate events. Climate effect account for the majority of observed exposure changes in AEZs, except Northern Irrigated Plain, where interaction effect plays a key role. The findings suggest that as urbanization and population growth continue, major AEZs in Pakistan are becoming increasingly susceptible to extreme climate events in the future. Key Points: Spatiotemporal trends in mean to extreme temperature (precipitation) events reveal widespread warming across Agro‐Ecological ZonesPopulation exposure to mean (extreme) temperature and precipitation events increases two‐fold in recent climate periodObserved changes in population exposure are primarily attributed to the climate effect (50%) over major Agro‐Ecological Zones [ABSTRACT FROM AUTHOR]

Extreme precipitation events (EPEs) and heatwaves (HWs) can trigger floods, droughts, and other natural disasters, resulting in severe socioeconomic losses in eastern China. However, the accurate links between EPEs and HWs and future changes in these extremes are not fully resolved, which potentially impedes disaster warning and preparedness efforts. This study examines historical and future changes in summer EPEs and HWs in eastern China based on observations and model outputs from the Coupled Model Intercomparison Project Phase 6. The results show that EPEs and HWs in eastern China have increased in the past four decades and are projected to rise in the future. According to multi-model projections, the Yangtze River Basin, along with areas to its south, are expected to experience an increase in compound disasters due to HWs and EPEs. High values of the multi-year mean total population exposure to EPEs and HWs are observed in the North China Plain, Yangtze River Delta, Sichuan Basin, and southeast coast. The total population exposure to EPEs shows a decreasing trend under Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios during 2021–2100, consistent with future population decline. However, the annual total population exposure to HWs will increase, reaching nearly 3.0 billion and 5.0 billion by the end of the century under the SSP245 and SSP585 scenarios, respectively. Within the context of global warming, the relationship between the mean-state of precipitation and maximum temperature as well as the relationship between extreme precipitation and heatwaves shift from negative correlation in the historical period to positive correlation in future projections for eastern China. [ABSTRACT FROM AUTHOR]

Climate change is altering the conditions to which communities have adapted. The Köppen–Geiger classification system can provide a compact metric to identify regions with notable changes in climatic conditions. Shifting Köppen–Geiger climate zones will be especially impactful in regions with large populations. This study uses high-resolution datasets on Köppen–Geiger climate zones and populations to quantify the number of people affected by shifting climate zones (i.e., population exposure to shifting climate zones). By the end of this century, 9–15% of the Earth's land surface is projected to shift its climate zone. These shifts could affect 1.3–1.6 billion people (14–21% of the global population). Many of the affected people live in areas that were classified as temperate in the historical period. These areas are projected to be classified as tropical or arid in the future. This study presents a new metric for exposure to climate change: the number of people living in areas whose climate zone classification is projected to shift. It also identifies populations that may face climatic conditions in the future that deviate from those to which they have adapted. [ABSTRACT FROM AUTHOR]

At first glance, assessing future landslide‐exposed population appears to be a straightforward task if landslide hazard estimates, climate change, and population projections are available. However, the intersection of landslide hazard with socioeconomic elements may result in significant variation of estimated landslide exposure due to considerable variations in population projections. This study aims to investigate the effects of different sources of population data on the evaluation of landslide‐exposed population in China under four Shared Socioeconomic Pathways (SSPs) scenarios. We utilize multiple global climate models (GCMs) from Coupled Model Intercomparison Project Phase 6 and six high‐resolution spatially explicit static and dynamic population data sets to drive available landslide models. The results indicate an overall rise in landslide hazard projections, with an increase in the potential impact area of 0.4%–2.7% and an increase in the landslide frequency of 4.7%–20.1%, depending on the SSPs scenarios and future periods. However, the likely changes in future landslide exposed population, as modeled by incorporating population data from different sources with landslide hazard, yield divergent outcomes depending on the population data source. Thus, some of the projections depict an increase in future landslide exposure, while others show a clear decrease. The nationwide divergence ranged from −64% to +48%. These divergent findings were mainly attributed to differences in population data and a lesser extent to variations in GCMs. The present findings highlight the need to pay closer attention to the dynamic evolution of the elements at risk and the associated data uncertainties. Plain Language Summary: As climate change continues, extreme rainfall is expected to become more frequent and intense. This can lead to changes in landslide risks and how population is exposed to them. While previous studies have mainly focused on how the landslide likelihood may change in time, few have paid attention to how dynamic socioeconomic factors play a role in determining landslide risk. In this study, we used multiple global climate models and different population data sets to investigate how different sources of population information can affect estimates of future landslide risks in China. Overall, we found that landslide hazard is likely to increase in the future. However, when we incorporated different population data into our models, we found divergent results in terms of the number of people exposed to these phenomena. Depending on the population data used, the estimates ranged from a decrease of about 64% to an increase of 48%. These different outcomes were mainly due to variations in population data we used, although climate models also had an impact. These conflicting estimates highlight the need to consider changes in elements at risk when assessing disaster risks and developing targeted measures to adapt to and mitigate the effects of climate change. Key Points: Future landslide exposure is assessed by combining landslide model with spatially explicit population and global climate model dataPotential impact areas and frequency of landslides in China under climate change are projected to increase by 0.4%–2.7% and 4.7%–20.1%, respectivelyVarying sourced population projections may induce divergent signals (−64% to +48%) of landslide‐exposed population under climate change [ABSTRACT FROM AUTHOR]

Despite recent progress in assessing future population exposure, few studies have focused on the exposure of certain vulnerable groups, such as working people. Working in hot environments can increase the heat-related risk to human health and reduce worker productivity, resulting in broad social and economic implications. Based on the daily climatic simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) and the age group-specific population projections, we investigate future changes in working-age population exposure to heat extremes under multiple scenarios at global and continental scales. Projections show little variability in exposure across scenarios by mid-century (2031–2060), whereas significantly greater increases occur under SSP3-7.0 for the late century (2071–2100) compared to lower-end emission scenarios. Global exposure is expected to increase approximately 2-fold, 6-fold and 16-fold relative to the historical time (1981–2010) under SSP1-2.6, SSP2-4.5 and SSP3-7.0, respectively. Asia will have the largest absolute exposure increase, while in relative terms, the most affected region is Africa. At the global level, future exposure increases are primarily caused by climate change and the combined effect of climate and working-age population changes. Climate change is the dominant driver in enhancing future continental exposure except in Africa, where the main contributor is the combined effect. [ABSTRACT FROM AUTHOR]

Recent decades have witnessed accelerated climate changes across the Qinghai-Tibet Plateau (QTP) and elevated socioeconomic exposure to meteorological hazards. The QTP is called the “the third pole”, exerting remarkable impact on environmental changes in its surrounding regions. While few reports are available for addressing multi-hazard risks over the QTP, we develop an integrated indicator system involving multiple meteorological hazards, i.e., droughts, rainstorms, snowstorms and hailstorms, investigating the spatiotemporal patterns of major hazards over the QTP. The hazard zones of droughts and rainstorms are identified in the southern Gangdise Mountains, the South Tibet Valley, the eastern Nyenchen-Tanglha Mountains, the Hengduan Mountains and West Sichuan Basin. Snowstorm hazard zones distribute in the Himalayas, the Bayan Har Mountains and the central Nyenchen-Tanglha Mountains, while hailstorm hazard zones cluster in central part of the QTP. Since the 21st century, intensified rainstorms are detectable in the densely populated cities of Xining and Lhasa and their adjacent areas, while amplified droughts are observed in grain production areas of the South Tibet Valley and the Hengduan Mountains. Snowstorm hazards show large interannual variations and an increase in pastoral areas, although the overall trend is declining slightly. The frequency of hailstorms gradually decreases in human settlements due to thermal and landscape effects. Mapping meteorological hazards regionalization could help to understand climate risks in the QTP, and provide scientific reference for human adaptation to climate changes in highly sensitive areas.

Sensor-based air monitoring instruments (SAMIs) can provide high-resolution air quality data by offering a detailed mapping of areas that air quality monitoring stations (AQMSs) cannot reach. This enhances the precision of estimating PM2.5 concentration levels for areas that have not been directly measured, thereby enabling an accurate assessment of exposure. The study period was from 30 September to 2 October 2019 in the Guro-gu district, Seoul, Republic of Korea. Four models were applied to assess the suitability of the SAMIs and visualize the temporal and spatial distribution of PM2.5. Assuming that the PM2.5 concentrations measured at a SAMI located in the center of the Guro-gu district represent the true values, the PM2.5 concentrations estimated using QGIS spatial interpolation techniques were compared. The SAMIs were used at seven points (S1–S7) according to the distance. Models 3 and 4 accurately estimated the unmeasured points with higher coefficients of determination (R2) than the other models. As the distance from the AQMS increased from S1 to S7, the R2 between the observed and estimated values decreased from 0.89 to 0.29, respectively. The auxiliary installation of SAMIs could resolve regional concentration imbalances, allowing for the accurate estimation of pollutant concentrations and improved risk assessment for the population.