Article(id=1149741762295546326, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, articleNumber=1003-3033(2024)02-0103-07, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2024.02.1813, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1691942400000, receivedDateStr=2023-08-14, revisedDate=1699977600000, revisedDateStr=2023-11-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1752049397300, onlineDateStr=2025-07-09, pubDate=1709049600000, pubDateStr=2024-02-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752049397300, onlineIssueDateStr=2025-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752049397300, creator=13701087609, updateTime=1752049397300, updator=13701087609, issue=Issue{id=1149741761771258326, tenantId=1146029695717560320, journalId=1146031787341344770, year='2024', volume='34', issue='2', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752049397175, creator=13701087609, updateTime=1756468934610, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1168278645379440971, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1168278645379440972, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1149741761771258326, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=103, endPage=109, ext={EN=ArticleExt(id=1149741762605924824, articleId=1149741762295546326, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Research on spatio-temporal evolution of fire-economy-environment based on coupling coordination analysis, columnId=1149733271128420907, journalTitle=China Safety Science Journal, columnName=Safety social science and safety management, runingTitle=null, highlight=null, articleAbstract=

In order to explore the spatial and temporal evolution characteristics of fire,economy and environment,based on the data of fire,economy and environment in China from 2000 to 2019,a fire-economy-environment coupling coordination model was established to study the coupling development level of fire,economy and environment system. Combined with ESDA method,the spatial and temporal evolution characteristics and aggregation of each subsystem in 31 provinces were studied,and the spatial correlation analysis of fire,economy and environment was carried out based on Moran 'I test. The research shows that the comprehensive development of fire,economy and environment has been well coupled from 2000 to 2019. From the time dimension,the coupling degree and coordination degree showed an upward trend from 2000 to 2019. The coupling degree was affected by the fire comprehensive score,and the coordination degree was affected by the economic subsystem. From the spatial dimension,economic development is the main factor affecting the coupling coordination degree of 31 provinces. From the analysis of the spatial and temporal evolution of the coupling relationship,the provincial coupling degree is aggregated with time,and the coupling coordination degree is random in spatial aggregation. The different effects of fire,economy and environment on coupling coordination lead to different coordination types and spatial aggregation states.

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为探究火灾、经济、环境的时空演化特征,基于2000—2019年中国火灾、经济、环境数据,建立火灾-经济-环境耦合协调模型,研究火灾、经济、环境系统的耦合发展水平;结合探索性空间数据分析(ESDA)方法研究我国31个省域各子系统时空演变特征及聚集性,并基于Moran' I检验开展火灾、经济、环境空间相关性分析。研究结果表明:2000—2019年火灾、经济和环境综合发展耦合良好。从时间维度上,2000—2019年耦合度和协调度呈上升趋势,耦合度受火灾综合得分影响,协调度受经济子系统影响;从空间维度上,经济发展是影响31个省域耦合协调度的主要因素。从耦合关系时空演变分析看,省域耦合度随时间呈聚集状态,耦合协调度在空间聚集中呈随机性。火灾、经济和环境对耦合协调的不同影响,导致协调类型及空间聚集状态不同。

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向 月 (1988—),女,重庆人,博士研究生,讲师,主要从事建筑防火、火灾风险及人员疏散方面的研究。E-mail:

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向 月 (1988—),女,重庆人,博士研究生,讲师,主要从事建筑防火、火灾风险及人员疏散方面的研究。E-mail:

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向 月 (1988—),女,重庆人,博士研究生,讲师,主要从事建筑防火、火灾风险及人员疏散方面的研究。E-mail:

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International Journal of Environmental Research and Public Health, 2022, 19(4): 133 395-133 410., articleTitle=Spatiotemporal differentiation and driving force analysis of the high-quality development of urban agglomerations along the Yellow River basin, refAbstract=null)], funds=[Fund(id=1168128785640595955, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, awardId=cstc2021jcyj-msxmX0809, language=CN, fundingSource=重庆市自然科学基金面上项目资助(cstc2021jcyj-msxmX0809), fundOrder=null, country=null), Fund(id=1168128785686733300, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, awardId=KJQN202001537, language=CN, fundingSource=重庆市教委科学技术研究计划青年项目(KJQN202001537), fundOrder=null, country=null), Fund(id=1168128785762230773, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, awardId=2021YFS0362, language=CN, fundingSource=四川省重点研发项目(2021YFS0362), fundOrder=null, country=null)], 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figureFileBig=6GeR4yl55LZpMDkzfu0OJg==, tableContent=null), ArticleFig(id=1168128784315195876, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=CN, label=图1, caption=火灾-经济-环境系统指标的选取, figureFileSmall=XKaEOunYUzhJEGg01c/Nrg==, figureFileBig=6GeR4yl55LZpMDkzfu0OJg==, tableContent=null), ArticleFig(id=1168128784382304741, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=EN, label=Fig.2, caption=Comprehensive development trend of fire-economy-environment system from 2000 to 2019, figureFileSmall=qElftO8E31zucojjhIx0vQ==, figureFileBig=kpQ8+M/XbEkg1JTQ/7iMeQ==, tableContent=null), ArticleFig(id=1168128784449413606, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=CN, label=图2, caption=2000—2019年火灾-经济-环境系统综合发展趋势, figureFileSmall=qElftO8E31zucojjhIx0vQ==, figureFileBig=kpQ8+M/XbEkg1JTQ/7iMeQ==, tableContent=null), 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tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=EN, label=Fig.6, caption=Trend chart and confidence value of Moran' I value from 2000 to 2019, figureFileSmall=DOQ4A/ERyKn6T0IEE2xlEQ==, figureFileBig=X9qx/ufbjKlbjSnNWb1Yxg==, tableContent=null), ArticleFig(id=1168128785007256046, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=CN, label=图6, caption=2000—2019年Moran' I值趋势图和置信值, figureFileSmall=DOQ4A/ERyKn6T0IEE2xlEQ==, figureFileBig=X9qx/ufbjKlbjSnNWb1Yxg==, tableContent=null), ArticleFig(id=1168128785133085167, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=EN, label=Tab.1, caption=

Types of coupling coordination degree of fire-economy-environment system

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耦合度
阶段
D 耦合协调
度类型
衰退失
调阶段
0≤D<0.4 0.0≤D<0.1 极度失调
0.1≤D<0.2 严重失调
0.2≤D<0.3 中度失调
0.3≤D<0.4 轻度失调
过渡
阶段
0.4≤D<0.6 0.4≤D<0.5 濒临失调
0.5≤D<0.6 勉强协调
耦合协
调阶段
0.6≤D≤1 0.6≤D<0.7 初级协调
0.7≤D<0.8 中级协调
0.8≤D<0.9 良好协调
0.9≤D≤1 优质协调
), ArticleFig(id=1168128785250525680, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=CN, label=表1, caption=

火灾-经济-环境系统耦合协调度类型

, figureFileSmall=null, figureFileBig=null, tableContent=
耦合度
阶段
D 耦合协调
度类型
衰退失
调阶段
0≤D<0.4 0.0≤D<0.1 极度失调
0.1≤D<0.2 严重失调
0.2≤D<0.3 中度失调
0.3≤D<0.4 轻度失调
过渡
阶段
0.4≤D<0.6 0.4≤D<0.5 濒临失调
0.5≤D<0.6 勉强协调
耦合协
调阶段
0.6≤D≤1 0.6≤D<0.7 初级协调
0.7≤D<0.8 中级协调
0.8≤D<0.9 良好协调
0.9≤D≤1 优质协调
), ArticleFig(id=1168128785422492145, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=EN, label=Tab.2, caption=

Index weight of fire-economy-environment system

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火灾
指标
权重 a i 经济
指标
权重
b j
环境
指标
权重
c k
火灾
起数
0.266 4 人均
GDP/元
0.256 7 工业SO2
放量万t
0.203 9
死亡
人数
0.210 3 国内生
产总值/
亿元
0.241 4 工业废水
总排放量/
万t
0.187 9
受伤
人数
0.202 4 城镇居民
可支配收
入/元
0.224 3 工业固体废
物产量/
万t
0.148 0
直接经
济损失/
万元
0.320 8 社会消费
品零售总
额/亿元
0.277 6 城镇建成
区绿化覆
盖率/%
0.154 5
生活垃圾
无害化处
理率/%
0.305 8
), ArticleFig(id=1168128785502183922, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1149741762295546326, language=CN, label=表2, caption=

火灾-经济-环境系统指标权重

, figureFileSmall=null, figureFileBig=null, tableContent=
火灾
指标
权重 a i 经济
指标
权重
b j
环境
指标
权重
c k
火灾
起数
0.266 4 人均
GDP/元
0.256 7 工业SO2
放量万t
0.203 9
死亡
人数
0.210 3 国内生
产总值/
亿元
0.241 4 工业废水
总排放量/
万t
0.187 9
受伤
人数
0.202 4 城镇居民
可支配收
入/元
0.224 3 工业固体废
物产量/
万t
0.148 0
直接经
济损失/
万元
0.320 8 社会消费
品零售总
额/亿元
0.277 6 城镇建成
区绿化覆
盖率/%
0.154 5
生活垃圾
无害化处
理率/%
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基于耦合协调分析的火灾-经济-环境时空演化研究
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向月 1 , 骆鑫 1, 2 , 秦毅 1 , 钱一诺 1
中国安全科学学报 | 安全社会科学与安全管理 2024,34(2): 103-109
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中国安全科学学报 | 安全社会科学与安全管理 2024, 34(2): 103-109
基于耦合协调分析的火灾-经济-环境时空演化研究
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向月1 , 骆鑫1, 2, 秦毅1, 钱一诺1
作者信息
  • 1 重庆科技大学 安全工程学院,重庆 401331
  • 2 安徽理工大学 安全科学与工程学院,安徽 淮南 232000
  • 向 月 (1988—),女,重庆人,博士研究生,讲师,主要从事建筑防火、火灾风险及人员疏散方面的研究。E-mail:

Research on spatio-temporal evolution of fire-economy-environment based on coupling coordination analysis
Yue XIANG1 , Xin LUO1, 2, Yi QIN1, Yinuo QIAN1
Affiliations
  • 1 Safety Engineering Institute,Chongqing University of Science and Technology,Chongqing 401331,China
  • 2 College of Safety Science and Engineering,Anhui University of Science and Technology,Huainan Anhui 232000,China
出版时间: 2024-02-28 doi: 10.16265/j.cnki.issn1003-3033.2024.02.1813
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为探究火灾、经济、环境的时空演化特征,基于2000—2019年中国火灾、经济、环境数据,建立火灾-经济-环境耦合协调模型,研究火灾、经济、环境系统的耦合发展水平;结合探索性空间数据分析(ESDA)方法研究我国31个省域各子系统时空演变特征及聚集性,并基于Moran' I检验开展火灾、经济、环境空间相关性分析。研究结果表明:2000—2019年火灾、经济和环境综合发展耦合良好。从时间维度上,2000—2019年耦合度和协调度呈上升趋势,耦合度受火灾综合得分影响,协调度受经济子系统影响;从空间维度上,经济发展是影响31个省域耦合协调度的主要因素。从耦合关系时空演变分析看,省域耦合度随时间呈聚集状态,耦合协调度在空间聚集中呈随机性。火灾、经济和环境对耦合协调的不同影响,导致协调类型及空间聚集状态不同。

火灾-经济-环境  /  耦合协调度  /  时空演化  /  探索性空间数据分析(ESDA)  /  熵值法

In order to explore the spatial and temporal evolution characteristics of fire,economy and environment,based on the data of fire,economy and environment in China from 2000 to 2019,a fire-economy-environment coupling coordination model was established to study the coupling development level of fire,economy and environment system. Combined with ESDA method,the spatial and temporal evolution characteristics and aggregation of each subsystem in 31 provinces were studied,and the spatial correlation analysis of fire,economy and environment was carried out based on Moran 'I test. The research shows that the comprehensive development of fire,economy and environment has been well coupled from 2000 to 2019. From the time dimension,the coupling degree and coordination degree showed an upward trend from 2000 to 2019. The coupling degree was affected by the fire comprehensive score,and the coordination degree was affected by the economic subsystem. From the spatial dimension,economic development is the main factor affecting the coupling coordination degree of 31 provinces. From the analysis of the spatial and temporal evolution of the coupling relationship,the provincial coupling degree is aggregated with time,and the coupling coordination degree is random in spatial aggregation. The different effects of fire,economy and environment on coupling coordination lead to different coordination types and spatial aggregation states.

fire-economy-environment system  /  coupling coordination degree  /  spatio-temporal evolution  /  exploratory spatial data analysis (ESDA)  /  entropy method
向月, 骆鑫, 秦毅, 钱一诺. 基于耦合协调分析的火灾-经济-环境时空演化研究. 中国安全科学学报, 2024 , 34 (2) : 103 -109 . DOI: 10.16265/j.cnki.issn1003-3033.2024.02.1813
Yue XIANG, Xin LUO, Yi QIN, Yinuo QIAN. Research on spatio-temporal evolution of fire-economy-environment based on coupling coordination analysis[J]. China Safety Science Journal, 2024 , 34 (2) : 103 -109 . DOI: 10.16265/j.cnki.issn1003-3033.2024.02.1813
自2000年以来,我国各地区经济发展不均衡、城市人口密集度的增大直接影响了火灾的发生,经济发达地区加大消防建设会减少火灾发生,因此,经济发展水平对火灾损失的影响具有双重性。此外,经济、火灾等因素对环境的影响很大,火灾不仅对周围社区及生态平衡造成危害,而且燃烧释放的污染物会对人体造成伤害[1]。因此,经济与环境、经济与火灾、环境与火灾之间存在多层次多维度的相互联系,三者共同构成一个动态开放的有机系统。
不同地区的火灾形势、经济水平和环境破坏程度需从多维度分析。多数学者主要对火灾、经济和环境开展耦合协调研究。孙鹏哲等[2]采用典型相关性分析火灾、经济、人口是否存在协调发展,发现经济发达且人口密集地区火灾发生更加频繁;宋洁[3]建立耦合协调模型分析黄河流域人口、经济、环境协调度的时空特征,得出经济和环境为黄河流域系统协调度的主要影响因素。SHEKEDE等[4]分析时空差异的同时,也直观地分析聚集热点及其相关性程度,对火灾、环境等提出更好的管理策略。ZHANG Xiaoxiang等[5]通过人员伤亡、经济损失分析火灾时空动态,预判南京的火灾发展趋势。CIZUNGU等[6]以时空为切入点,通过趋势和空间聚类分析,预测城市发展。以上研究为火灾、经济、环境等因素分析提供了技术基础,但忽略了区域性耦合关系和空间相关性两者结合,难以有效分析因素间耦合协调的时空分布差异,且现有研究对区域火灾、经济、环境耦合的时空演化特征探究较少。
鉴于此,笔者拟通过构建耦合协调模型,运用探索性空间数据分析(Exploratory Spatial Data Analysis,ESDA)方法,结合地理信息系统、Geoda技术分析耦合关系时空维度及空间相关性,以期得到火灾-经济-环境系统演变特征和省域聚集状态,并为火灾安全防控提出理论依据。
统计并分析2000—2019年我国(不含港澳台地区)火灾起数、死亡人数、受伤人数、国内生产总值(Gross Domestic Product,GDP)、工业SO2排放量等数据(数据来源于《中国火灾统计年鉴》《中国消防年鉴》《中国消防救援年鉴》《中国统计年鉴》以及各市统计年鉴),使用回归填补法填补了2018、2019年西藏环境系统中生活垃圾无害化处理率指标数据[7]
基于省域各数据的客观性、相关性和可获取性,及耦合协调的导向性、可操作性[8]。建立火灾-经济-环境协调指标体系,并采用熵值法确定各指标权重。
1) 构建指标体系。为建立火灾-经济-环境协调指标体系,选择火灾、经济和环境作为一级指标,并选取13个二级指标来评估3个子系统的性能,火灾-经济-环境系统指标的选取如图1所示:
采用极差法将数据进行标准化处理[9],以消除数量级、正负方向(正向规定为P,负向规定为N)和量纲对评价的影响,见下式:
x i j ( y i j z i j ) = a i j - m i n a i j m a x a i j - m i n a i j m a x a i j - a i j m a x a i j - m i n a i j
式中, x i j y i j z i j分别为火灾、经济、环境子系统具体指标; a i j为具体二级指标。标准化后的 x i j y i j z i j在[0,1]之间,数值越大表示贡献越大,协调发展速度越快。
2) 指标权重的确定。基于客观赋值法确定各指标权重,能够避免主观赋值法存在的缺陷[9]。利用熵值法确定指标权重。
① 计算第j项指标的熵值 e j
e j = - 1 l n n i = 1 m p i l n p i j
式中:n为评价年数;m为各子系统中二级指标个数; p i j为指标概率, p i j = x i j n i = 1 n   x i j n
② 熵值法确定指标的权重 w j
w j = g i j = 1 m   g i
式中 g j为指标 x j y j z j差异性系数, g j = 1 - e j g j越大,表明应越重视该指标。
为量化火灾-经济-环境系统的协调发展水平,借鉴前人研究思路[10],构建耦合协调度模型。
1) 耦合度CC用于衡量火灾子系统、经济子系统和环境子系统之间的耦合程度。C的取值范围在0~1,通常C越接近1表示耦合度越大,接近0表示变量之间无发展关系[10],见下式:
C = f ( x ) × g ( y ) × h ( z ) f ( x ) + g ( y ) + h ( z ) 3 3 1 3
其中,3个子系统分别用下面3种函数表示。
火灾子系统:
f ( x i j ) = i = 1 m a i x ' i
经济子系统:
g ( y i j ) = j = 1 n b j y ' j
环境子系统:
h ( z i j ) = k = 1 p c k z ' k
2) 综合发展指数T
T = α f ( x i j ) × β g ( y i j ) × γ h ( z i j )
式中 α β γ为火灾、经济和环境的待定系数。考虑到火灾、经济、环境系统同等重要[2] α β γ分别取1/3。
3) 协调度D
D = C × T
将火灾-经济-环境系统耦合协调度分为衰退失调类、过渡类和耦合协调类3种阶段及10种类型,构建耦合协调度等级划分标准[10],见表1
采用ESDA技术分析全国省域火灾-经济-环境耦合空间特征。ESDA以空间相关性为核心,基于大量数据描述空间分布及联系,揭示数据的空间依赖性与差异性[11]。其中,全局Moran 's I将空间自相关作为一个整体进行量化,而局部空间关联指标(Local Indicators of Spatialassociation,LISA)则使用局部Moran' s I来衡量每个特定位置的空间自相关程度。此外,ESDA方法还有利于识别局部空间聚类模式和空间离群值[11]
全局莫兰指数:
I 1 = i = 1 n   j = 1 n   W i j z i - z - z j - z - σ 2 i = 1 n j = 1 n   W i j
局部莫兰指数:
I 2 = z i - z - σ 2 j i j = 1 n W i j z j - z -
式中: z -为当评价年数为n时的平均值; z i为位置i处的变量值; z j为其他位置的值(其中,j=i); σ 2z的方差; W i j z i z j之间的距离权重。
权重 W i j可通过距离带来确定,距离之内的样本具有相同的权重,而距离之外的样本权重为0。
全局Moran' I取值在[-1,1]之间。 I 1 < 0表示空间负相关,相邻区域之间存在差异; I 1 = 0,空间缺乏相关性,表示随机分布; I 1 > 0空间正相关,表示研究单元在空间中表现出聚集性。
空间自相关性无法描述聚集位置,因此,采用Getis-Ord检验局部空间中是否存在热点(高值空间聚类)和冷点(低值空间聚类)[12]
G i * = j = 1 n W i j z i j = 1 n   z j
式中 G i *为空间聚类位置, G i * = 1表示空间相邻, G i * = 0反之。 G i * > 0表示相邻省域之间属于高值聚集区;反之,相邻省域之间属于低值聚集区。
为了更直观地表达各省域的耦合关系,对火灾-经济-环境系统的耦合数据进行可视化分析;通过软件GeoDa测量整体Moran 's I和局部Moran' s I值,进行空间相关性分析。
选取2000—2019年火灾、经济、环境数据,并确定各二级指标的权重,见表2。采用加权评价法计算各一级指标f(x)、g(y)、h(z)的发展指数和综合发展指数T,并绘制趋势图,如图2所示。
分析图2可知:2000—2012年火灾子系统综合得分最高,环境和经济子系统得分相对较低。2012年前,我国经历了2次全球金融危机,导致经济综合得分较低,但整体呈上升趋势。2012—2013年火灾子系统综合得分呈下降趋势,由0.88降至0.28,达到最低值,火灾子系统处于劣势,由于2013年统计口径增加了森林火灾、草原火灾等,直接经济损失达到48.5亿元,火灾起数388 821起,导致4项指标比2012年均增长2倍。2014年后,火灾综合得分缓慢增加,政府更加重视消防工作,逐步完善消防相关政策及法规。此外,我国经济增长的同时对消防救援的投入也增加,火灾发生得到改善,安全进一步提高。近20年环境子系统整体处于上升趋势,2004—2007年出现较小波动,其中,2005年我国环境综合得分达最低点,“十五”计划实施的最后一年,环境保护工作取得新进展。然而,由于经济增长迅速,资源和能源成本高,主要污染物排放总量增加,经济发展与环境发展之间起相互制约作用。整体来说,2000—2019年综合评价指数呈上升趋势,2013年出现较小波动,之后得分维持在0.45~0.75,综合发展水平较好,在发展经济的同时,平衡火灾和环境的发展。
根据《中国统计年鉴》和《中国消防年鉴》等数据,得到不同年份火灾-经济-环境的耦合度、协调度及其类型。图3为火灾-经济-环境耦合度、协调分布图。从图3可以看出,2000—2019年协调度与耦合度发展趋势大致相同,呈逐年增长趋势,其中,2013年协调度出现波动,之后缓慢增长。结合2.1节各子系统发展指数分析,火灾指数出现较大波动,经济、环境指数呈逐年增长,说明经济不仅对环境造成影响,也会影响火灾发生,这种对环境和火灾影响的模式制约其耦合度和协调度的提高。
2000—2019年我国火灾-经济-环境系统发展总体呈上升趋势,其中,2000年处于低水平耦合阶段,表现为经济发展明显滞后于火灾和环境发展,2001年三者处于颉颃时期;2002—2006年迅速达到磨合时期;2007年后,我国火灾、经济、环境达到共同发展阶段,进入高水平耦合时期,此时系统整体处于协调发展。
从耦合度增长趋势分析,2001年比2000年增长0.353,2001年我国经济、环境综合得分均增加,其中,火灾4项指标中受伤人数、死亡人数和直接经济损失相比2000年分别降低14.1%、22.7%、8%。此外,2006、2013和2019年出现轻微下降,其他年份平稳增长。研究表明:2013年我国火灾情况处于劣势状态,但消防救援出动首次超过百万,比2012年增加36.5%。纵观全年,由于消防管理缺失及消防设备落后,导致农村、住宅火灾共占62.5%。此外,2013年吉林发生2起重特大火灾导致火灾指标增大。因此,火灾综合得分导致火灾耦合度轻微下降。
从耦合协调类型分析,2000—2019年耦合协调度呈上升趋势,其中,2000—2005年处于严重失调与濒临失调之间,影响耦合协调的主要因素依然是经济系统;2006年进入勉强协调阶段,经济发展处于制约地位;2008—2016年处于初级协调阶段和中级协调阶段之间;2013年降至初级阶段,在此期间,火灾子系统成为主要制约因素,火灾综合得分相比2012年下降25.6%。2015年达到中级协调阶段,我国火灾、经济、环境系统处于同步发展趋势,但协调度处于中级阶段较低模式;2017年正式迈入良好协调发展,耦合协调度在2018—2019年出现轻微下降,经济发展制约生态环境和火灾发展。因此,随着经济不断提升,环境破坏和生活中火灾的发生对安全防控起着重大威胁。
通过上述分析,以2010年为分界点,2003年后,环境和火灾得分逐渐下降,经济制约占主导地位,处于濒临失调阶段;2010—2017年期间,火灾制约开始占主导地位,正式进入良好协调阶段。因此,选取2003、2010、2017年31个省份(不含港澳台)的数据,计算耦合协调度,绘制各省域火灾-经济-环境耦合协调类型分布图,分析火灾-环境-经济系统空间耦合协调特征。由于中国各省域火灾、经济和环境耦合协调发展在空间上存在明显差异,因此,耦合协调类型分为5类:濒临失调、勉强协调、初级协调、中级协调和良好协调,如图4所示。
图4可以看出,2003年大多数省域处于初级协调发展类型,濒临失调类型的省份只有贵州;西北地区多数省域属于勉强协调类型,包含青海、甘肃等11个省份受经济发展的制约导致地区耦合协调度降低;中级、良好协调类型分布于天津、福建、北京和上海。以长江为界限,上游地区协调度最高的为重庆,沿中游和下游各城市耦合协调度逐渐增强;其中,浙江、上海耦合协调度较为显著,两者耦合协调度相差0.23。从各子系统分析,上海为环境制约类型,火灾和经济综合得分分别为0.83、0.77,整体为中上水平;浙江为火灾制约类型,2003年浙江省火灾起数和经济损失位列第1,死亡人数位列第2,3项指标导致火灾综合得分为0.11,处于劣势状态。因此,火灾是导致浙江为勉强协调类型的主要因素。
2010年相比2003年协调发展类型较稳定发展水平。西藏、新疆、云南协调类型滞后较为明显,从初级协调下降至勉强协调,火灾、经济、环境综合得分均下降,导致协调类型处于低水平阶段。濒临失调类型只有甘肃。其中,相比较2003年中级协调类型增加上海、浙江等4个省域;上海从协调类型降至中级协调,因火灾、经济综合得分下降,导致三者耦合协调程度降低。从图4能直观看出,沿海城市耦合协调度上升,山东、江苏耦合协调度的提高受火灾综合得分剧烈增加的影响,子系统略微降低。因此,耦合协调程度受火灾影响较大。
2017年沿海地区耦合协调度相比2010年发生显著性变化。其中,山东、江苏、福建耦合协调度主要受火灾、经济子系统下降的影响;浙江耦合协调度下降30.46%,为勉强协调类型。对比结果表明:我国东部地区耦合协调度普遍高于西部地区,东部地区三者发展建设同步,协调程度较强。
综合3个年份时间节点分析,火灾、经济子系统对耦合协调度影响较大。不同省份制约类型分布如图5所示,2003、2010、2017年中经济制约类型占比最大,火灾制约类型地区占比保持不变,环境制约类型地区出现增加,占比由3.2%升至6.4%。因此,在省域角度分析中,经济发展是影响31个省域耦合协调度的关键因素。经济发展对火灾环境耦合协调度显著提高,降低发达区域经济发展对环境的依赖和破坏,有助于加强火灾安全的综合治理。
考虑到年份间耦合协调度的空间分布,各省之间的耦合度和耦合协调度可能表现出局部空间自相关。因此,对2000—2019年31个省域耦合度进行Moran' I检验,具体结果如图6所示。
在1%显著性水平下,省域耦合协调度空间相关性拒绝了“非空间相关性”的假设。选取上述 3个年份和Moran' I最大值、最小值的年份开展分析,发现历年Moran' I检验结果的置信值P值为0.003~0.01,这意味着在1%的置信度区间内原假设不成立,即各省域的耦合度存在空间自相关性。2000—2019年指数呈N型曲线,随时间表现出增-减-增趋势,但整体呈增长趋势。其中,2000—2007年耦合度Moran' I指数呈增长趋势,2007—2015年指数下降至0.246,2015年后逐渐上升,各省域的耦合度在空间分布上随时间呈现聚集状态。
同样,对31个省域的耦合协调度进行空间自相关性分析。对2000—2019年31个省域的耦合协调度进行Moran' I检验,得出Moran' I指数范围为0.133~0.582,与耦合度的趋势一致。2000—2019年,耦合协调度空间聚集冷点主要集中在西部地区,如新疆、西藏、甘肃等,而聚集热点则位于东部地区,如浙江、江苏等。然而,2013、2015、2017年聚集的热点地区仅有河北发生变化,但对应的随机检验莫兰指数的结果在1%的显著性水平下无法拒绝无空间自相关性的假设。这也说明耦合协调度在空间聚集中的相关性呈现随机性,各地区在发展经济的同时,必须平衡火灾的发生与环境的保护,这为三者协调发展增加了难度。
1) 综合发展分析显示,经济制约型持续12年占主导地位,但整体综合指数随时间呈上升趋势。
2) 在时间维度上,经济影响火灾、环境子系统,同时制约耦合度及协调度的提高;从省域空间维度分析,中国经济主要集中在东部沿海城市,这些地区的耦合协调类型高于其他地区。经济发展是影响31个省域耦合协调度的关键因素之一,也是影响火灾安全最关键的因素
3) 从耦合关系空间分析,各省域耦合度在空间分布上随时间呈聚集状态。耦合协调度呈西冷东热聚集状态,但也可能发生不稳定性变化,说明耦合协调度在空间聚集中具有一定的随机性。
4) 各地区经济发展的不同造成火灾和环境各方面的差异。由于研究条件和能力的限制,火灾-经济-环境系统的研究需从多个维度考虑,纳入不同性质的指标深入研究,以提高安全防控可靠性。在后续研究中,可尝试从消防部署、救援、灾害治理等入手,进一步提升指标有效性。
  • 重庆市自然科学基金面上项目资助(cstc2021jcyj-msxmX0809)
  • 重庆市教委科学技术研究计划青年项目(KJQN202001537)
  • 四川省重点研发项目(2021YFS0362)
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doi: 10.16265/j.cnki.issn1003-3033.2024.02.1813
  • 接收时间:2023-08-14
  • 首发时间:2025-07-09
  • 出版时间:2024-02-28
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  • 收稿日期:2023-08-14
  • 修回日期:2023-11-15
基金
重庆市自然科学基金面上项目资助(cstc2021jcyj-msxmX0809)
重庆市教委科学技术研究计划青年项目(KJQN202001537)
四川省重点研发项目(2021YFS0362)
作者信息
    1 重庆科技大学 安全工程学院,重庆 401331
    2 安徽理工大学 安全科学与工程学院,安徽 淮南 232000
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2种不同金属材料的力学参数

Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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