Evaluation and Projection of Population Exposure to Temperature Extremes over the Beijing−Tianjin−Hebei Region Using a High-Resolution Regional Climate Model RegCM4 Ensemble

Temperature extremes over rapidly urbanizing regions with high population densities have been scrutinized due to their severe impacts on human safety and economics.First of all,the performance of the regional climate model RegCM4 with a hydrostatic or non-hydrostatic dynamic core in simulating seasonal temperature and temperature extremes was evaluated over the historical period of 1991–99 at a 12-km spatial resolution over China and a 3-km resolution over the Beijing−Tianjin−Hebei(JJJ)region,a typical urban agglomeration of China.Simulations of spatial distributions of temperature extremes over the JJJ region using RegCM4 with hydrostatic and non-hydrostatic cores showed high spatial correlations of more than 0.8 with the observations.Under a warming climate,temperature extremes of annual maximum daily temperature(TXx)and summer days(SU)in China and the JJJ region showed obvious increases by the end of the 21st century while there was a general reduction in frost days(FD).The ensemble of RegCM4 with different land surface components was used to examine population exposure to temperature extremes over the JJJ region.Population exposure to temperature extremes was found to decrease in 2091−99 relative to 1991−99 over the majority of the JJJ region due to the joint impacts of increases in temperature extremes over the JJJ and population decreases over the JJJ region,except for downtown areas.Furthermore,changes in population exposure to temperature extremes were mainly dominated by future population changes.Finally,we quantified changes in exposure to temperature extremes with temperature increase over the JJJ region.This study helps to provide relevant policies to respond future climate risks over the JJJ region.

Increased population exposures to extreme precipitation in Central Asia under 1.5℃and 2℃global warming scenarios

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℃and 2℃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℃GWS and 14.18%(13.25%)under 2℃GWS.Controlling temperature rise can be effective in reducing population exposures to EP.For instance,limiting the temperature increase to 1.5℃instead of 2℃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.

Increased population exposure to precipitation extremes in China under global warming scenarios

Precipitation extremes are among the most dangerous climate-related hazards over China, and they are expected to significantly increase in the future in both frequency and intensity. Exposure to precipitation extremes and changes therein are determined by extreme events and the corresponding population changes. Here, the authors analyze the changing population exposure across China in the future using ensembles of high-resolution simulations with Reg CM4 and population scenarios. The authors find that aggregate exposure over China increases by nearly 21.6% under the RCP4.5-SSP2 scenario by the end of this century, although populations are projected to decrease. East China will experience the largest absolute increase in exposure from 424 million person-events to 546 million person-events, while the Tibetan Plateau region will experience the largest relative increase of nearly 44.4%. This increase in exposure mainly results from the climate effect contribution. Further assessments indicate that the exposure increase over China does not rely on the greenhouse gas emissions and population growth scenarios, but the higher emissions scenario generally leads to higher exposure regardless of population growth, highlighting the efficacy of mitigation efforts in reducing exposure to precipitation extremes.

Mercury Levels Assessment in the Population of Aby and Frambo Villages in the Vinicity of Aby Lagoon in Côte d’Ivoire (West Africa)

The Minamata Convention in the aim to protect human life and the environment, seeks to reduce mercury (Hg) by monitoring it concentrations in the environment. Artisanal and Small-scale Gold Mining (ASGM) has been identified as the most important anthropogenic source of human exposure to Hg. In this context, the main goal of this study was to assess the level of mercury in hair of two (2) populations living along two lagoons respectively Aby and Tendo, in Ivory Coast. To reach this goal, hair samples of 138 residents were collected and analyzed by using Cold Vapor Atomic Fluorescence Spectrophotometry (CV-AFS) technique for mercury concentration. Results showed that for the entire population the Hg mean was 2.34 μg/g. Also, they were ranged between 0.15 to 8.53 μg/g and presented substantial differences amongst the villages. In Aby village, we observed the highest Hg concentrations (Mean = 2.62 μg/g). Our findings showed that almost the entire sample group (82%) exceed the USEPA recommended limit, furthermore 56% of them exceed the normal level of WHO and 2% of the respondent has the unhealthy levels of mercury (≥6 μg Hg/g) of hair by WHO standards. Gender differences in hair mercury varies greatly among reports. Lower levels in women’s hair compared to men were reported in the both village. Considering age, the lowest concentrations were observed with children. However, when we take in account the age groups, data suggested that the most exposed sub-population of [18-29] years old is from Aby village in opposite at Frambo village, the same case those who were ≥ 40 years old. It’s convenient to note that, the proportion of Mercury levels would not to be neglected among studied population especially with the resident from Aby village. So, some measures need to be taken at the political level to control mercury contamination.

GIS-based analysis of population exposure to PM2.5 air pollution-A case study of Beijing

PM_（2.5）, formally defined as particulate matter with diameter less than 2.5 μm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and long-term exposures to PM_（2.5） are strongly linked with respiratory diseases. In this study, various types of spatio-temporal data were collected and used to estimate the spatio-temporal variation of PM2.5 exposure in Beijing in 2014. The seasonal and daily variation of the population-weighted exposure level（PWEL） in 2014 was estimated and compared. The results show that the population exposure to ambient air pollution differs significantly in the four seasons, and the exposure levels in winter and spring are notably higher than the other seasons; the exposure level changes greatly from North to South, and each sub-district maintains similarity to neighboring sub-districts.

Changes in Extreme Maximum Temperature Events and Population Exposure in China under Global Warming Scenarios of 1.5 and 2.0°C: Analysis Using the Regional Climate Model COSMO-CLM

We used daily maximum temperature data（1986–2100） from the COSMO-CLM（COnsortium for Small-scale MOdeling in CLimate Mode） regional climate model and the population statistics for China in 2010 to determine the frequency, intensity, coverage, and population exposure of extreme maximum temperature events（EMTEs） with the intensity–area–duration method. Between 1986 and 2005（reference period）, the frequency, intensity, and coverage of EMTEs are 1330–1680 times yr^–1, 31.4–33.3℃, and 1.76–3.88 million km^2, respectively. The center of the most severe EMTEs is located in central China and 179.5–392.8 million people are exposed to EMTEs annually. Relative to 1986–2005, the frequency, intensity, and coverage of EMTEs increase by 1.13–6.84, 0.32–1.50, and15.98%–30.68%, respectively, under 1.5℃ warming; under 2.0℃ warming, the increases are 1.73–12.48, 0.64–2.76,and 31.96%–50.00%, respectively. It is possible that both the intensity and coverage of future EMTEs could exceed the most severe EMTEs currently observed. Two new centers of EMTEs are projected to develop under 1.5℃ warming, one in North China and the other in Southwest China. Under 2.0℃ warming, a fourth EMTE center is projected to develop in Northwest China. Under 1.5 and 2.0℃ warming, population exposure is projected to increase by 23.2%–39.2% and 26.6%–48%, respectively. From a regional perspective, population exposure is expected to increase most rapidly in Southwest China. A greater proportion of the population in North, Northeast, and Northwest China will be exposed to EMTEs under 2.0℃ warming. The results show that a warming world will lead to increases in the intensity, frequency, and coverage of EMTEs. Warming of 2.0℃ will lead to both more severe EMTEs and the exposure of more people to EMTEs. Given the probability of the increased occurrence of more severe EMTEs than in the past, it is vitally important to China that the global temperature increase is limited within 1.5℃.

Projected changes in population exposure to extreme heat in China under a RCP8.5 scenario

Overall population exposure is measured by multiplying the annual average number of extremely hot days by the number of people exposed to the resultant heat. Extreme heat is also subdivided into high temperature（HT） and extremely high temperature（EHT） in cases where daily maximum temperature exceeds 35℃ and 40℃, respectively. Chinese population exposure to HT and EHT over four periods in the future（i.e., 2021–2040, 2041–2060, 2060–2081 and 2081–2100） were projected at the grid cell level in this study using daily maximum temperature based on an ensemble mean of 21 global climate models under the RCP8.5 scenario and with a population projection based on the A2 r socio-economic scenario. The relative importance of population and climate as drivers of population exposure was evaluated at different spatial scales including national and meteorological geographical divisions. Results show that, compared with population exposure seen during 1981–2010, the base period, exposure to HT in China is likely to increase by 1.3, 2.0, 3.6, and 5.9 times, respectively, over the four periods, while concomitant exposure to EHT is likely to increase by 2.0, 8.3, 24.2, and 82.7 times, respectively. Data show that population exposure to HT is likely to increase significantly in Jianghuai region, Southwest China and Jianghan region, in particular in North China, Huanghuai region, South China and Jiangnan region. Population exposure to EHT is also likely to increase significantly in Southwest China and Jianghan region, especially in North China, Huanghuai, Jiangnan, and Jianghuai regions. Results reveal that climate is the most important factor driving the level of population exposure in Huanghuai, Jianghuai, Jianghan, and Jiangnan regions, as well as in South and Southwest China, followed by the interactive effect between population and climate. Data show that the climatic factor is also most significant at the national level, followed by the interactive effect between population and climate. The rate of contribution of climate to national-level projected changes in exposure is likely to decrease gradually from ca. 70% to ca. 60%, while the rate of contribution of concurrent changes in both population and climate is likely to increase gradually from ca. 20% to ca. 40% over the four future periods in this analysis.

Projected increases in population exposure of daily climate extremes in eastern China by 2050

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.

Population exposure to precipitation extremes in the Indus River Basin at1.5℃,2.0℃and 3.0℃warming levels

Adverse effects of extreme events are the major focus of climate change impact studies.Precipitation-related extremes has substantial so-cioeconomic impacts under the changing climate.Quantifying population exposure to precipitation extreme is the fundamental aspect ofpopulation risk assessments in the climate hotspot of Indus River Basin.This study investigates the population exposure to precipitation ex-tremes at 1.5℃,2.0℃,and 3.0℃global warmings in the Indus River Basin using daily precipitation data,and projected population undershared socioeconomic pathways(SSPs).The IntensityeAreaeDuration method was applied to detect the extreme precipitation event by tracingthe rainstorm process,calculated based on five downscaled and bias-corrected Global Climate Model(GCM)outputs from Coupled ModelIntercomparison Project Phase 5(CMIP5)under four Representative Concentration Pathways(RCP2.6,RCP4.5,RCP6.0,and RCP8.5).Theexposure of the population is finally estimated by combing SSP1 with 1.5℃,SSP2 with 2.0℃,and SSP5 with 3.0℃warming levels.Resultsshow that warming over the Indus River Basin is projected to be higher than that of the global average.Both the extreme precipitation events andpopulation exposure are projected to increase with warming level.With regard to the reference period(1986e2005),the frequency,duration,andimpacted area of extreme precipitation are projected to increase by 13.2%,7.4%,and 1.6%annually under 1.5℃in the Indus River Basin,respectively.Whereas,an additional 0.5℃and 1.5℃warming can lead to further increase in the frequency of 16.6%,17.3%,as well as theduration of 8.6%,12%,and areal coverage of 2.1%,5.3%,respectively.The population exposure to extreme precipitation is projected to increaseby 72.4%,122.7%,and 87.6%,respectively,at SSP1 with 1.5℃,SSP2 with 2.0℃and SSP5 with 3.0℃warming levels compare to thereference period.The demographic change is responsible more for the tremendous increment of population exposure in the Indus River Basin.Ifthe population was held constant to the level of 2010,the increase of population exposure would be 4.4%,8.8%,and 17.6%,respectively,at1.5℃,2.0℃,and 3.0℃warming levels.Spatially,the prominent increment of population exposure is projected in the central and southwesternIndus River Basin.This study highlights that limiting the increase of temperature to 1.5℃can substantially reduce population exposure toextreme precipitation events in the Indus River Basin,compared to an additional warming.Simultaneously,urge paid to formulate policies onpopulation growth to reduce future exposure.

Air Pollution Exposure Based on Nighttime Light Remote Sensing and Multi-source Geographic Data in Beijing

Air pollution is a problem that directly affects human health,the global environment and the climate.The air quality index(AQI)indicates the degree of air pollution and effect on human health;however,when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored.In the present study,multi-source data were combined to map the distribution of the AQI and population data,and the analyze their pollution population exposure of Beijing in 2018 was analyzed.Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018.Using Luojia-1 nighttime light remote sensing data,population statistics data,the population of Beijing in 2018 and point of interest data,the distribution of the permanent population in Beijing was estimated with a high precision of 200 m×200 m.Based on the spatialization results of the AQI and population of Beijing,the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level(PWEL)formula.The results show that the southern region of Beijing had a more serious level of air pollution,while the northern region was less polluted.At the same time,the population was found to agglomerate mainly in the central city and the peripheric areas thereof.In the present study,the exposure of different districts and towns in Beijing to pollution was analyzed,based on high resolution population spatialization data,it could take the pollution exposure issue down to each individual town.And we found that towns with higher exposure such as Yongshun Town,Shahe Town and Liyuan Town were all found to have a population of over 200000 which was much higher than the median population of townships of51741 in Beijing.Additionally,the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same,with the peak value being in winter and the lowest value being in summer.The exposure intensity in population clusters was relatively high.To reduce the level and intensity of pollution exposure,relevant departments should strengthen the governance of areas with high AQI,and pay particular attention to population clusters.

Role of adaptation measures in addressing heatwave exposure in China

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 SSP5JSSP5-8.5 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.

长三角城市群多情景暴雨人口暴露度时空演变分析

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 165meteorological 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.

High-resolution multi-scale air pollution system:Evaluation of modelling performance and emission control strategies

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 Macao 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 Macao SAR.The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas.

Sorely reducing emissions of non-methane short-lived climate forcers will worsen compound flood-heatwave extremes in the Northern Hemisphere

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 in-tensities 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 O.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)×10^(5)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.

Synergistic PM_(2.5)and O_(3)control to address the emerging global PM_(2.5)-O_(3)compound pollution challenges

In recent years,the issue of PM_(2.5)-O_(3)compound pollution has become a significant global environmental concern.This study examines the spatial and temporal patterns of global PM_(2.5)-O_(3)compound pollution and exposure risks,firstly at the global and urban scale,using spatial statistical regression,exposure risk assessment,and trend analyses based on the datasets of daily PM_(2.5)and surface O_(3)concentrations monitored in 120 cities around the world from 2019 to 2022.Additionally,on the basis of the common emission sources,spatial heterogeneity,interacting chemical mechanisms,and synergistic exposure risk levels between PM_(2.5)and O_(3)pollution,we proposed a synergistic PM_(2.5)-O_(3)control framework for the joint control of PM_(2.5)and O3.The results indicated that:(1)Nearly 50%of cities worldwide were affected by PM_(2.5)-O_(3)compound pollution,with China,South Korea,Japan,and India being the global hotspots for PM2.5-O3 compound pollution;(2)Cities with PM_(2.5)-O_(3)compound pollution have exposure risk levels dominated by ST t ST(Stabilization)and ST t HR(High Risk).Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries,with unequal exposure characteristics;(3)The selected cities showed significant positive spatial correlations between PM_(2.5)and O_(3)concentrations,which were consistent with the spatial distribution of the precursors NOx and VOCs;(4)During the study period,52.5%of cities worldwide achieved synergistic reductions in annual average PM_(2.5)and O_(3)concentrations.The average PM_(2.5)concentration in these cities decreased by 13.97%,while the average O_(3)concentration decreased by 19.18%.This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low–carbon transition.

气候变化背景下极端热事件劳动适龄人口暴露度的全球和区域变化

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.

Time-varying road network design for urban hazmat transportation

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.

Analysis of air quality characteristics of Beijing–Tianjin–Hebei and its surrounding air pollution transport channel cities in China

Beijing–Tianjin–Hebei(BTH)and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality portraits.The results showed that particulate matter with aerodynamic diameters of<2.5μm(PM2.5),particulate matter with aerodynamic diameters of<10μm(PM10)and SO2 improved significantly in 31 cities from2015 to 2018,but ozone deteriorated.Air quality in BTH and the surrounding areas showed obvious seasonal characteristics,among which PM2.5,PM10,SO2,and NO2 showed a"U"type distribution from January to December,while O3 had an"inverted U"distribution.The hourly changes in air quality revealed that peaks of PM2.5,PM10 and NO2 appeared from 8:00 to 10:00,while those for O3 appeared at 15:00–16:00.The exposure characteristics of the 31 cities showed that six districts in Beijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated cities.Additionally,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation)and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.