WangYWangC. Classification of extreme heatwave events in the Northern Hemisphere through a new method. Clim Dyn2023. Online ahead of print. DOI: 10.1007/s00382-022-06649-8.
2.
ChenHZhaoLChengLZhangYWangHGuKBaoJYangJLiuZHuangJChenYGaoXXuYWangCCaiWGongPLuoYLiangWHuangC. Projections of heatwave-attributable mortality under climate change and future population scenarios in China. Lancet Reg Health West Pac2022; 28: 100582.
3.
LiuXSunTFengQ. Dynamic spatial spillover effect of urbanization on environmental pollution in China considering the inertia characteristics of environmental pollution. Sustainable Cities and Society2020; 53: 101903.
4.
RomanelloMDi NapoliCDrummondPGreenCKennardHLampardPScammanDArnellNAyeb-KarlssonSFordLBBelesovaKBowenKCaiWCallaghanMCampbell-LendrumDChambersJvan DaalenKRDalinCDasandiNDasguptaSDaviesMDominguez-SalasPDubrowREbiKLEckelmanMEkinsPEscobarLEGeorgesonLGrahamHGuntherSHHamiltonIHangYHanninenRHartingerSHeKHessJJHsuSCJankinSJamartLJayOKelmanIKiesewetterGKinneyPKjellstromTKnivetonDLeeJLemkeBLiuYLiuZLottMBatistaMLLoweRMacGuireFSeweMOMartinez-UrtazaJMaslinMMcAllisterLMcGushinAMcMichaelCMiZMilnerJMinorKMinxJCMohajeriNMoradi-LakehMMorrisseyKMunzertSMurrayKANevilleTNilssonMObradovichNO'HareMBOreszczynTOttoMOwfiFPearmanORabbanihaMRobinsonERocklovJSalasRNSemenzaJCShermanJDShiLShumake-GuillemotJSilbertGSofievMSpringmannMStowellJTabatabaeiMTaylorJTrinanesJWagnerFWilkinsonPWinningMYglesias-GonzalezMZhangSGongPMontgomeryHCostelloA. The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels. Lancet2022; 400(10363): 1619–1654.
5.
ChenTSarnatSEGrundsteinAJWinquistAChangHH. Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012. Environ Health Perspect2017; 125(5): 057009.
6.
EbiKLCaponABerryPBroderickCde DearRHavenithGHondaYKovatsRSMaWMalikAMorrisNBNyboLSeneviratneSIVanosJJayO. Hot weather and heat extremes: health risks. Lancet2021; 398(10301): 698–708.
7.
BekkarBPachecoSBasuRDeNicolaN. Association of air pollution and heat exposure with preterm birth, low birth weight, and stillbirth in the us: A systematic review. JAMA Netw Open2020; 3(6): e208243.
8.
GuanYXiaoYWangYZhangNChuC. Assessing the health impacts attributable to PM2.5 and ozone pollution in 338 Chinese cities from 2015 to 2020. Environ Pollut2021; 287: 117623.
9.
XiaoXXuYZhangXWangFLuXCaiZBrasseurGGaoM. Amplified Upward Trend of the Joint Occurrences of Heat and Ozone Extremes in China over 2013–20. Bulletin of the American Meteorological Society2022; 103(5): E1330–E1342.
10.
ZhangYYangPGaoYLeungRLBellML. Health and economic impacts of air pollution induced by weather extremes over the continental U.S. Environ Int2020; 143: 105921.
11.
LiuSChengYYanLYuCW. Characteristic and sources of atmospheric ozone in Xi'an. Indoor and Built Environment2019; 28(9): 1254–1262.
12.
HeGYuCWFLuCDengQ. The Influence of Synoptic Pattern and Atmospheric Boundary Layer on PM10 and Urban Heat Island. Indoor and Built Environment2013; 22(5): 796–807.
13.
RenCYuCWCaoSJ. Development of urban air environmental control policies and measures. Indoor and Built Environment2023; 32(2): 299–304.
14.
HanLZhaoJGaoYGuZ. Prediction and evaluation of spatial distributions of ozone and urban heat island using a machine learning modified land use regression method. Sustainable Cities and Society2022; 78: 103643.
15.
WangJQYuCWCaoSJ. Planning for sustainable and ecological urban environment: Current trends and future developments. Indoor and Built Environment2023; 32(4): 627–631.
16.
HanLZhaoJGaoYGuZXinKZhangJ. Spatial distribution characteristics of PM2.5 and PM10 in Xi'an City predicted by land use regression models. Sustain Cities Soc2020; 61: 102329.
17.
HanLZhaoJZhangTZhangJ. Urban ventilation corridors exacerbate air pollution in central urban areas: Evidence from a Chinese city. Sustainable Cities and Society2022; 87: 104129.
18.
SrivastavaAShuklaSSinghPJhaPK. Spatio-temporal dynamics of land use/cover and land surface temperature in Prayagraj city, India. Indoor and Built Environment2023. Epub ahead of print. DOI: 10.1177/1420326X231159633.
19.
MengMXiCFengZCaoSJ. Environmental co-benefits of urban design to mitigate urban heat island and PM2.5 pollution: Considering prevailing wind's effects. Indoor and Built Environment2022; 31(7): 1787–1805.
20.
ZhangYYuWLiYLiH. Comparative research on the air pollutant prevention and thermal comfort for different types of ventilation. Indoor and Built Environment2021; 30(8): 1092–1105.
21.
YangJHuLWangC. Population dynamics modify urban residents' exposure to extreme temperatures across the United States. Sci Adv2019; 5(12): eaay3452.
22.
SunCHuangCYuCW. Environmental exposure and infants health. Indoor and Built Environment. Epubl ahead of print, 2023, DOI: 10.1177/1420326X231154985.
23.
BaiLLiCYuCWHeZ. Air pollution and health risk assessment in Northeastern China: A case study of Jilin Province. Indoor and Built Environment2021; 30(10): 1857–1874.
24.
MarquetOTello-BarsocchiniJCouto-TrigoDGomez-VaroIMaciejewskaM. Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments. Int J Health Geogr2023; 22: 3. DOI: 10.1186/s12942-023-00325-8.
25.
XuSZouBXiongYWanNFengHHHuCXLinY. High spatiotemporal resolution mapping of PM2.5 concentrations under a pollution scene assumption. Journal of Cleaner Production2021; 326: 129409.
26.
WeiBYSuGWLiuFG. Dynamic assessment of spatiotemporal population distribution based on mobile phone data: a Case Study in Xining City, China. Int J Disaster Risk Sci2023. Epub ahead of print. DOI: 10.1007/s13753-023-00480-3.
27.
GuoRQiYZhaoBPeiZYWenFWuSZhangQ. High-resolution urban air quality mapping for multiple pollutants based on dense monitoring data and machine learning. Int J Environ Res Public Health2022; 19(13): 8005.
28.
HuangYPYuanMLuYP. Spatially varying relationships between surface urban heat islands and driving factors across cities in China. Environment and Planning B-Urban Analytics and City Science2019; 46(2): 377–394.
29.
ZhangCHuYAdamsMDLiuMLiBShiTLiC. Natural and human factors influencing urban particulate matter concentrations in central heating areas with long-term wearable monitoring devices. Environ Res2022; 215: 114393.
30.
LuYPYueWZLiuYHuangYP. Investigating the spatiotemporal non-stationary relationships between urban spatial form and land surface temperature: A case study of Wuhan, China. Sustainable Cities and Society2021; 72: 103070.
31.
ZhangGRuiXPosladSSongXFanYWuB. A method for the estimation of finely-grained temporal spatial human population density distributions based on cell phone call detail records. Remote Sensing (Basel, Switzerland)2020; 12(16): 2572.
32.
LuoHTangXWuHKongLWuQCaoKSongYLuoXWangYZhuJWangZ. The impact of the numbers of monitoring stations on the national and regional air quality assessment in China During 2013-18. Adv Atmos Sci2022; 39(10): 1709–1720.
33.
Van NguyenTZhouLChongAYLLiBPuX. Predicting customer demand for remanufactured products: a data-mining approach. European Journal of Operational Research2020; 281(3): 543–558.
YinCXiaoJZhangT. Effectiveness of chinese regulatory planning in mitigating and adapting to climate change: comparative analysis based on Q methodology. Sustainability (Basel, Switzerland)2021; 13(17): 9701.