• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

印度智慧城市热浪特征加剧。

Heat waves characteristics intensification across Indian smart cities.

作者信息

Goyal Manish Kumar, Singh Shivam, Jain Vijay

机构信息

Department of Civil Engineering, Indian Institute of Technology Indore, Indore, India.

出版信息

Sci Rep. 2023 Sep 7;13(1):14786. doi: 10.1038/s41598-023-41968-8.

DOI:10.1038/s41598-023-41968-8
PMID:37679392
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10484900/
Abstract

Indian cities have frequently observed intense and severe heat waves for the last few years. It will be primarily due to a significant increase in the variation in heat wave characteristics like duration, frequency, and intensity across the urban regions of India. This study will determine the impact of future climate scenarios like SSP 245 and 585 over the heat wave characteristics. It will present the comparison between heat waves characteristics in the historical time (1981 to 2020) with future projections, i.e., D (2021-2046), D (2047-2072), and D (2073-2098) for different climate scenarios across Indian smart cities. It is observed that the Coastal, Interior Peninsular, and North-Central regions will observe intense and frequent heat waves in the future under SSP 245 and 585 scenarios. A nearly two-fold increase in heat wave' mean duration will be observed in the smart cities of the Interior Peninsular, Coastal, and North Central zones. Thiruvananthapuram city on the west coast has the maximum hazard associated with heat waves among all the smart cities of India under both SSPs. This study assists smart city policymakers in improving the planning and implementation of heat wave adaptation and mitigation plans based on the proposed framework for heat action plans and heat wave characteristics for improving urban health well-being under hot weather extremes in different homogeneous temperature zones.

摘要

在过去几年中,印度各城市经常出现强烈且严重的热浪。这主要是由于印度城市地区热浪特征(如持续时间、频率和强度)的变化显著增加。本研究将确定未来气候情景(如SSP 245和585)对热浪特征的影响。它将呈现历史时期(1981年至2020年)与未来预测(即不同气候情景下印度智慧城市的D(2021 - 2046年)、D(2047 - 2072年)和D(2073 - 2098年))之间的热浪特征比较。研究发现,在SSP 245和585情景下,沿海、半岛内陆和中北部地区未来将出现强烈且频繁的热浪。半岛内陆、沿海和中北部地区的智慧城市中,热浪的平均持续时间将增加近两倍。在这两种SSP情景下,西海岸的 Thiruvananthapuram 市在印度所有智慧城市中与热浪相关的危害最大。本研究有助于智慧城市政策制定者根据拟议的热行动计划框架和热浪特征,改进热浪适应和缓解计划的规划与实施,以在不同均匀温度区的极端炎热天气下改善城市居民的健康福祉。

相似文献

1
Heat waves characteristics intensification across Indian smart cities.印度智慧城市热浪特征加剧。
Sci Rep. 2023 Sep 7;13(1):14786. doi: 10.1038/s41598-023-41968-8.
2
Projection of future temperature extremes, related mortality, and adaptation due to climate and population changes in Taiwan.台湾地区未来因气候和人口变化导致的极端温度预测、相关死亡率及适应对策。
Sci Total Environ. 2021 Mar 15;760:143373. doi: 10.1016/j.scitotenv.2020.143373. Epub 2020 Nov 1.
3
Future Heat Waves in Different European Capitals Based on Climate Change Indicators.基于气候变化指标的不同欧洲首都未来的热浪情况。
Int J Environ Res Public Health. 2019 Oct 17;16(20):3959. doi: 10.3390/ijerph16203959.
4
The extreme heat wave of July-August 2021 in the Athens urban area (Greece): Atmospheric and human-biometeorological analysis exploiting ultra-high resolution numerical modeling and the local climate zone framework.2021 年 7 月至 8 月雅典市区极端热浪:利用超高分辨率数值模拟和地方气候区框架的大气和人体生物气象学分析。
Sci Total Environ. 2023 Jan 20;857(Pt 1):159300. doi: 10.1016/j.scitotenv.2022.159300. Epub 2022 Oct 8.
5
Persistent heat waves projected for Middle East and North Africa by the end of the 21st century.预计到 21 世纪末,中东和北非地区将出现持续的热浪。
PLoS One. 2020 Nov 17;15(11):e0242477. doi: 10.1371/journal.pone.0242477. eCollection 2020.
6
Extreme Heat Kills Even in Very Hot Cities: Evidence from Nagpur, India.即使在酷热城市,极端高温也会致命:来自印度那格浦尔的证据。
Int J Occup Environ Med. 2020 Oct;11(4):188-195. doi: 10.34172/ijoem.2020.1991.
7
Heat waves in South Korea: differences of heat wave characteristics by thermal indices.韩国热浪:不同热指数下热浪特征的差异。
J Expo Sci Environ Epidemiol. 2019 Oct;29(6):790-805. doi: 10.1038/s41370-018-0076-3. Epub 2018 Oct 3.
8
Quantifying future climate extreme indices: implications for sustainable urban development in West Africa, with a focus on the greater Accra region.量化未来气候极端指数:对西非可持续城市发展的影响,重点关注大阿克拉地区。
Discov Sustain. 2024;5(1):167. doi: 10.1007/s43621-024-00352-w. Epub 2024 Jul 29.
9
Heat risk assessment for the Brussels capital region under different urban planning and greenhouse gas emission scenarios.不同城市规划和温室气体排放情景下的布鲁塞尔首都大区热风险评估。
J Environ Manage. 2019 Nov 1;249:109210. doi: 10.1016/j.jenvman.2019.06.111. Epub 2019 Aug 19.
10
The impact of heat waves on mortality in seven major cities in Korea.热浪对韩国七个主要城市死亡率的影响。
Environ Health Perspect. 2012 Apr;120(4):566-71. doi: 10.1289/ehp.1103759. Epub 2012 Jan 20.

本文引用的文献

1
Co-occurrence of urban heat and the COVID-19: Impacts, drivers, methods, and implications for the post-pandemic era.城市高温与新冠疫情的共同出现:影响、驱动因素、方法及对疫情后时代的启示
Sustain Cities Soc. 2023 Mar;90:104387. doi: 10.1016/j.scs.2022.104387. Epub 2022 Dec 30.
2
Hot weather hazard analysis over India.印度高温天气危害分析。
Sci Rep. 2022 Nov 17;12(1):19768. doi: 10.1038/s41598-022-24065-0.
3
Strong influence of north Pacific Ocean variability on Indian summer heatwaves.北太平洋变化对印度夏季热浪的强烈影响。
Nat Commun. 2022 Sep 12;13(1):5349. doi: 10.1038/s41467-022-32942-5.
4
Analysis of heatwave characteristics under climate change over three highly populated cities of South India: a CMIP6-based assessment.气候变化下印度南部三个人口稠密城市热浪特征分析:基于 CMIP6 的评估。
Environ Sci Pollut Res Int. 2023 Sep;30(44):99013-99025. doi: 10.1007/s11356-022-22398-x. Epub 2022 Aug 6.
5
Anthropogenic influence on the changing risk of heat waves over India.人为因素对印度热浪变化风险的影响。
Sci Rep. 2022 Feb 28;12(1):3337. doi: 10.1038/s41598-022-07373-3.
6
Population exposure to compound extreme events in India under different emission and population scenarios.印度在不同排放和人口情景下的人口面临的复合极端事件。
Sci Total Environ. 2022 Feb 1;806(Pt 1):150424. doi: 10.1016/j.scitotenv.2021.150424. Epub 2021 Sep 20.
7
Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6.耦合模式比较计划第六阶段提供的南亚气候预估的偏差校正结果。
Sci Data. 2020 Oct 12;7(1):338. doi: 10.1038/s41597-020-00681-1.
8
Past warming trend constrains future warming in CMIP6 models.过去的变暖趋势限制了CMIP6模型中的未来变暖。
Sci Adv. 2020 Mar 18;6(12):eaaz9549. doi: 10.1126/sciadv.aaz9549. eCollection 2020 Mar.
9
Real time extended range prediction of heat waves over India.印度热浪的实时延伸范围预测。
Sci Rep. 2019 Jun 21;9(1):9008. doi: 10.1038/s41598-019-45430-6.
10
Increasing probability of mortality during Indian heat waves.在印度热浪期间,死亡率增加。
Sci Adv. 2017 Jun 7;3(6):e1700066. doi: 10.1126/sciadv.1700066. eCollection 2017 Jun.