气候变化研究进展 ›› 2022, Vol. 18 ›› Issue (6): 707-719.doi: 10.12006/j.issn.1673-1719.2021.271
张化1,4(
), 李汶莉2,3, 李雪敏2,3, 董琳2,3, 杨有田2,3, 张国明1,4, 许映军1,4
收稿日期:2021-12-02
修回日期:2022-03-07
出版日期:2022-11-30
发布日期:2022-10-27
作者简介:张化,男,高级工程师,基金资助:
ZHANG Hua1,4(
), LI Wen-Li2,3, LI Xue-Min2,3, DONG Lin2,3, YANG You-Tian2,3, ZHANG Guo-Ming1,4, XU Ying-Jun1,4
Received:2021-12-02
Revised:2022-03-07
Online:2022-11-30
Published:2022-10-27
摘要:
中国城镇和乡村住房建筑地震设防水平差距较大,暴露在低设防农村与高密集城镇下的人口因此面临较高的地震风险,面向地震设防风险分析未来城乡人口及暴露特征具有重要意义。本文基于地震烈度区划图和人口-发展-环境(PDE)模型,模拟分析了5种共享社会经济路径(SSPs)情景下的未来城乡人口地震灾害时空暴露。结果表明:(1)除SSP3下城镇人口数量持续增加外,其他SSP情景下各地区城镇人口数量均先增后降,农村人口数量受城镇化影响呈持续下降趋势;(2)城镇与农村地震灾害高、较高人口暴露等级空间分布相似,集中在华北、西南与东部沿海地区;(3)相较于有设防的城镇地区,无设防农村地震人口暴露等级偏高,高暴露、较高暴露等级的数量偏多,未来城镇人口暴露等级有所上升,而农村人口暴露等级逐渐降低。
张化, 李汶莉, 李雪敏, 董琳, 杨有田, 张国明, 许映军. 面向地震设防风险的未来中国城乡人口情景及暴露特征[J]. 气候变化研究进展, 2022, 18(6): 707-719.
ZHANG Hua, LI Wen-Li, LI Xue-Min, DONG Lin, YANG You-Tian, ZHANG Guo-Ming, XU Ying-Jun. Analysis of urban and rural population scenarios and exposure characteristics in China in the future for the prevention of earthquake risk[J]. Climate Change Research, 2022, 18(6): 707-719.
图2 第五代中国地震动峰值加速度(PGA)区划图 注:g表示重力加速度,1g≈9.81 m/s2,0.1g代表的地震动峰值加速度则为0.981 m/s2。图来源于中国地震局。
Fig. 2 Seismic ground motion parameters zonation map (PGA) of China (China Earthquake Administration)
图5 2015年城乡人口模拟结果误差分析 注:柱状图的顶部为误差线,误差线长度越长,模拟结果一致性越低。图中大部分地市误差线较短,一致性较高。
Fig. 5 Error analysis of urban and rural population simulation results in 2015
| [1] | 张培震, 邓起东, 张竹琪, 等. 中国大陆的活动断裂、地震灾害及其动力过程[J]. 中国科学:地球科学, 2013, 43 (10): 1607-1620. |
|
Zhang P Z, Deng Q D, Zhang Z Q, et al. Active faults, earthquake disasters and their dynamic processes in Chinese mainland[J]. Scientia Sinica: Terrae, 2013, 43 (10): 1607-1620 (in Chinese)
doi: 10.1360/zd-2013-43-10-1607 URL |
|
| [2] | 刘培玄, 王伟. 我国农村典型民居抗震设防问题分析与建议[J]. 中国减灾, 2019 (21): 16-19. |
| Liu P X, Wang W. Analysis and suggestions on seismic fortification of typical rural houses in China[J]. Disaster Reduction in China, 2019 (21): 16-19 (in Chinese) | |
| [3] | 金晓霞. 不设防农村与高风险城市之痛[J]. 中国减灾, 2011 (7): 12-14. |
| Jin X X. Defects of unprotected rural areas and high-risk cities[J]. Disaster Reduction in China, 2011 (7): 12-14 (in Chinese) | |
| [4] | 张津. 甘肃农村地震成灾机制及防震减灾研究[D]. 中国地震局兰州地震研究所, 2014. |
| Zhang J. Research on earthquake disaster formation mechanism and disaster reduction in rural area of Gansu province[D]. Lanzhou Institute of Seismology, 2014 (in Chinese) | |
| [5] | 叶耀先. 农村建设抗震[J]. 建筑技术与设计, 2008 (7): 84-93. |
| Ye Y X. Earthquake resistance of rural construction[J]. Architecture Technology & Design, 2008 (7): 84-93 (in Chinese) | |
| [6] | 周福霖. 隔震、消能减震与结构控制体系: 终止我国城乡地震灾难的必然技术选择[J]. 城市与减灾, 2016 (5): 1-10. |
| Zhou F L. Seismic isolation, energy dissipation and structural control system: the inevitable technical choice to end the urban and rural earthquake disaster in China[J]. Urban and Disaster Reduction, 2016 (5): 1-10 (in Chinese) | |
| [7] | 国务院办公厅. 《国家综合防灾减灾规划(2016—2020年)》[EB/OL]. 2017 [2022-06-15]. http://www.gov.cn/zhengce/content/2017-01/13/content_5159459.htm. |
| General Office of The State Council. National comprehensive plan of disaster prevention and mitigation (2016-2020)[EB/OL]. 2017 [2022-06-15]. http://www.gov.cn/zhengce/content/2017-01/13/content_5159459.htm (in Chinese) | |
| [8] | 吴绍洪, 赵东升. 中国气候变化影响、风险与适应研究新进展[J]. 中国人口·资源与环境, 2020, 30 (6): 1-9. |
| Wu S H, Zhao D S. Progress on the impact, risk and adaptation of climate change in China[J]. China Population, Resources and Environment, 2020, 30 (6): 1-9 (in Chinese) | |
| [9] |
van Vuuren D P, Riahi K, Moss R, et al. A proposal for a new scenario framework to support research and assessment in different climate research communities[J]. Global Environmental Change, 2012, 22 (1): 21-35
doi: 10.1016/j.gloenvcha.2011.08.002 URL |
| [10] |
van Vuuren D P, Kriegler E, O’Neill B C, et al. A new scenario framework for climate change research: scenario matrix architecture[J]. Climatic Change, 2014, 122: 373-386
doi: 10.1007/s10584-013-0906-1 URL |
| [11] | 姜彤, 赵晶, 景丞, 等. IPCC共享社会经济路径下中国和分省人口变化预估[J]. 气候变化研究进展, 2017, 13 (2): 128-137. |
| Jang T, Zhao J, Jing C, et al. National and provincial population projected to 2100 under the shared socioeconomic pathways in China[J]. Climate Change Research, 2017, 13 (2): 128-137 (in Chinese) | |
| [12] |
Huang J, Qin D, Jiang T, et al. Effect of fertility policy changes on the population structure and economy of China: from the perspective of the shared socioeconomic pathways[J]. Earth’s Future, 2019, 7: 250-265
doi: 10.1029/2018EF000964 URL |
| [13] |
Chen Y, Guo F, Wang J, et al. Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100[J]. Scientific Data, 2020, 7: 255-262
doi: 10.1038/s41597-020-00597-w URL |
| [14] | 姜彤, 王艳君, 袁佳双, 等. “一带一路”沿线国家2020—2060年人口经济发展情景预测[J]. 气候变化研究进展, 2018, 14 (2): 155-164. |
| Jang T, Wang Y J, Yuan J S, et al. Projection of population and economy in the Belt and Road countries (2020-2060)[J]. Climate Change Research, 2018, 14 (2): 155-164 (in Chinese) | |
| [15] |
Lutz W, KC S. Global human capital: integrating education and population[J]. Science, 2011, 333 (6042): 587-592
doi: 10.1126/science.1206964 pmid: 21798940 |
| [16] |
KC S, Lutz W. The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100[J]. Global Environmental Change, 2014, 42 (1): 181-189
doi: 10.1016/j.gloenvcha.2014.06.004 URL |
| [17] | 郑晓瑛, 陈功, 庞丽华, 等. 中国人口、人力资本变化趋势[J]. 市场与人口分析, 2007 (1): 3-13. |
| Zheng X Y, Chen G, Pang L H, et al. Future population and human capital in China[J]. Population and Development, 2007 (1): 3-13 (in Chinese) | |
| [18] |
Zhang J, Gao P, Fang F. An ATPSO-BP neural network modelling and its application in mechanical property prediction[J]. Computational Materials Science, 2019, 163: 262-266
doi: 10.1016/j.commatsci.2019.03.037 URL |
| [19] | 曹桂英, 任强. 未来全国和不同区域人口城镇化水平预测[J]. 人口与经济, 2005 (4): 51-56, 67. |
| Cao G Y, Ren Q. The national and regional urbanization projection for China[J]. Population & Economics, 2005 (4): 51-56, 67 (in Chinese) | |
| [20] |
Shang H L, Smith P W F, Bijak J, et al. A multilevel functional data method for forecasting population, with an application to the United Kingdom[J]. International Journal of Forecasting, 2019, 32 (3): 629-649
doi: 10.1016/j.ijforecast.2015.10.002 URL |
| [21] | 王豫燕, 王艳君, 姜彤. 江苏省暴雨洪涝灾害的暴露度和脆弱性时空演变特征[J]. 长江科学院院报, 2016, 33 (4): 27-32. |
| Wang Y Y, Wang Y J, Jang T. Spatial-temporal characteristics of exposure and vulnerability to flood disaster in Jiangsu province[J]. Journal of Yangtze River Scientific Research Institute, 2016, 33 (4): 27-32 (in Chinese) | |
| [22] | 李柔珂, 李耀辉, 徐影. 未来中国地区的暴雨洪涝灾害风险预估[J]. 干旱气象, 2018, 36 (3): 341-352. |
| Li R K, Li Y H, Xu Y. Projection of rainstorm and flooding disaster risk in China in the 21st century[J]. Journal of Arid Meteorology, 2018, 36 (3): 341-352 (in Chinese) | |
| [23] | Liao X L, Xu W, Zhang J L, et al. Global exposure to rainstorms and the contribution rates of climate change and population change[J]. Science of The Total Environment, 2019 (663): 644-653 |
| [24] |
杨佩国, 靳京, 赵东升, 等. 基于历史暴雨洪涝灾情数据的城市脆弱性定量研究:以北京市为例[J]. 地理科学, 2016, 36 (5): 733-741.
doi: 10.13249/j.cnki.sgs.2016.05.011 |
|
Yang P G, Jin J, Zhao D S, et al. An urban vulnerability study based on historical flood data: a case study of Beijing[J]. Scientia Geographica Sinica, 2016, 36 (5): 733-741 (in Chinese)
doi: 10.13249/j.cnki.sgs.2016.05.011 |
|
| [25] | 韩钦梅, 吕建军, 史培军. 湖北省暴雨人口暴露时空特征与贡献率研究[J]. 灾害学, 2018, 33 (4): 191-196. |
| Han Q M, Lyu J J, Shi P J. Spatial temporal characteristics and contribution rate of rainstorm population exposure in Hubei[J]. Journal of Catastrophology, 2018, 33 (4): 191-196 (in Chinese) | |
| [26] | 井源源, 方建, 史培军. 未来气候变化情景下湖北省极端降水的人口暴露分析[J]. 北京师范大学学报: 自然科学版, 2020, 56 (5): 700-709. |
| Jing Y Y, Fang J, Shi P J. Analysis of population exposure to extreme precipitation in Hubei province under the climate change scenarios[J]. Journal of Beijing Normal University: Natural Science, 2020, 56 (5): 700-709 (in Chinese) | |
| [27] | 王军, 王广州. 中国育龄人群的生育意愿及其影响估计[J]. 中国人口科学, 2013, 4: 26-35. |
| Wang J, Wang G Z. Reproductive population’s fertility desire and its influence in China[J]. Chinese Journal of Population Science, 2013, 4: 26-35 (in Chinese) | |
| [28] | 庄亚儿, 姜玉, 王志理, 等. 当前我国城乡居民的生育意愿: 基于2013年全国生育意愿调查[J]. 人口研究, 2014, 38 (3): 3-13. |
| Zhuang Y E, Jang Y, Wang Z L, et al. Fertility intention of rural and urban residents in China: results from the 2013 national fertility intention survey[J]. Population Research, 2014, 38 (3): 3-13 (in Chinese) | |
| [29] | 中华人民共和国住房和城乡建设部. GB55002—2021建筑与市政工程抗震通用规范[S]. 北京: 中国建筑出版传媒有限公司, 2021. |
| Ministry of Housing and Urban-Rural Development of People’s Republic of China. GB55002—2021 general standard for earthquake resistance of building and municipal engineering[S]. Beijing: China Architecture Publication Medium Limited Company, 2021 (in Chinese) | |
| [30] |
Ni H H, Chen A, Chen N. Some extensions on risk matrix approach[J]. Safety Science, 2010, 48: 1269
doi: 10.1016/j.ssci.2010.04.005 URL |
| [31] |
Eskesen S D, Tengborg P, KampmannJ, et al. Guidelines for tunnelling risk management: international tunnelling association, working group No.2[J]. Tunnelling and Underground Space Technology, 2004, 19 (3): 217-237
doi: 10.1016/j.tust.2004.01.001 URL |
| [32] | 孙柏涛. 中国编第五代地震区划图超九成农村房屋无抗震措施[EB/OL]. 2011 [2021-11-22]. http://cn.chinagate.cn/povertyrelief/2011-11/14/content_23906357.htm. |
| Sun B T. The fifth seismic ground motion parameters zonation map compiled more than 90% of rural houses have no seismic measures[EB/OL]. 2011 [2021-11-22]. http://cn.chinagate.cn/povertyrelief/2011-11/14/content_23906357.htm (in Chinese) | |
| [33] | 曹丽格, 方玉, 姜彤, 等. IPCC影响评估中的社会经济新情景(SSPs)进展[J]. 气候变化研究进展, 2012, 8 (1): 74-78. |
| Cao L G, Fang Y, Jiang T, et al. Advances in shared socio-economic pathways for climate change research and assessment[J]. Climate Change Research, 2012, 8 (1): 74-78 (in Chinese) | |
| [34] | 翁宇威, 蔡闻佳, 王灿. 共享社会经济路径(SSPs)的应用与展望[J]. 气候变化研究进展, 2020, 16 (2): 215-222. |
| Weng Y W, Cai W J, Wang C. The application and future directions of the shared socioeconomic pathways (SSPs)[J]. Climate Change Research, 2020, 16 (2): 215-222 (in Chinese) |
| [1] | 丁永建, 张世强, 陈仁升, 秦甲, 赵求东, 刘俊峰, 阳勇, 何晓波, 苌亚平, 上官冬辉, 韩添丁, 吴锦奎, 李向应. 气候变化对冰冻圈水文影响研究综述[J]. 气候变化研究进展, 2025, 21(1): 1-21. |
| [2] | 秦卓凡, 廖宏, 代慧斌. 气候变化影响我国大气重污染事件的研究进展[J]. 气候变化研究进展, 2025, 21(1): 56-68. |
| [3] | 吕学都, 陈佳琪, 葛慧, 朱乙丹. 气候金融实践与发展建议[J]. 气候变化研究进展, 2025, 21(1): 78-90. |
| [4] | 陈德亮, 谭显春, 彭喆, 闫洪硕, 程永龙. 人工智能在气候研究和服务中的机遇与挑战[J]. 气候变化研究进展, 2024, 20(6): 669-681. |
| [5] | 高翔. 国际条约下的气候资金问题辨析[J]. 气候变化研究进展, 2024, 20(6): 799-807. |
| [6] | 朱磊, 张丽忠, 蒋莹, 徐剑锋, 黄艳, 孙淑欣. 工业部门的气候适应研究进展[J]. 气候变化研究进展, 2024, 20(6): 721-735. |
| [7] | 欧阳志云, 张观石, 应凌霄. 气候变化对青藏高原生态系统分布范围和生态功能的影响研究进展[J]. 气候变化研究进展, 2024, 20(6): 699-710. |
| [8] | 陆春晖, 袁佳双, 黄磊, 张永香. 从IPCC看全球盘点中的关键科学问题及其对中国的启示[J]. 气候变化研究进展, 2024, 20(6): 736-746. |
| [9] | 周泽宇, 王君华, 曹颖. 全球适应气候变化行动进展评估及相关工作建议[J]. 气候变化研究进展, 2024, 20(6): 764-772. |
| [10] | 牛振国, 景雨航, 张东启, 张波. 气候变化背景下青藏高原湿地生态系统响应特征:回顾与展望[J]. 气候变化研究进展, 2024, 20(5): 509-518. |
| [11] | 吴沛泽, 陈莎, 刘影影, 李晓桐, 杜展霞, 崔淑芬, 姜克隽. 低排放分析平台LEAP:应对气候变化下的应用与挑战[J]. 气候变化研究进展, 2024, 20(5): 611-623. |
| [12] | 德吉玉珍, 拉巴, 巴桑旺堆, 白玛玉措, 旦增益嘎, 平措旺丹, 德吉央宗. 近50年西藏那曲西南部湖泊变化特征及其对气候变化的响应[J]. 气候变化研究进展, 2024, 20(5): 534-543. |
| [13] | 张靖宇, 曹龙. 海洋和陆地碳循环对二氧化碳正负排放响应的模拟研究[J]. 气候变化研究进展, 2024, 20(4): 416-427. |
| [14] | 潘晓滨, 刘尚文. 应对气候变化背景下我国转型金融法制化路径探析[J]. 气候变化研究进展, 2024, 20(4): 465-474. |
| [15] | 程阳, 韩振宇. 全球升温1.5℃和2℃下中国群发性高温事件与人口暴露度预估[J]. 气候变化研究进展, 2024, 20(3): 278-290. |
| 阅读次数 | ||||||
|
全文 |
|
|||||
|
摘要 |
|
|||||
|