Emergency rescue capability evaluation on urban fire stations in China

Journal Pre-proof Emergency rescue capability evaluation on urban fire stations in China Mengmeng Chen, Kai Wang, Xiangluan Dong, Haili Li

PII:

S0957-5820(19)31340-0

DOI:

https://doi.org/10.1016/j.psep.2019.12.028

Reference:

PSEP 2045

To appear in:

Process Safety and Environmental Protection

Received Date:

13 July 2019

Revised Date:

8 December 2019

Accepted Date:

23 December 2019

Please cite this article as: Chen M, Wang K, Dong X, Li H, Emergency rescue capability evaluation on urban fire stations in China, Process Safety and Environmental Protection (2019), doi: https://doi.org/10.1016/j.psep.2019.12.028

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Emergency rescue capability evaluation on urban fire stations in China Mengmeng Chena,b, Kai Wanga,b,1, Xiangluan Donga,b, Haili Lia,b a School

of Emergency Management and Safety Engineering, China University of Mining & Technology (Beijing), Beijing 100083,

China b

Beijing Key Laboratory for Precise Mining of Intergrown Energy and Resources, China University of Mining and Technology

(Beijing), Beijing 100083, China

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Abstract: Fire station plays an important role in ensuring the safety of people, property and environment. In order to improve the emergency rescue capability of the fire station, its influence factors are distinguished and a capability evaluation system is established in the present paper. The system is composed of goal layer, criteria layer and sub-criteria layer. The goal layer is the evaluation objective, namely, the emergency rescue capability of urban fire station. The criteria layer and sub-criteria layer contain five indexes and 25 indexes, respectively. Within the established evaluation system, the fuzzy comprehensive evaluation (FCE) method is chosen to analyze the decision problem. The weight of each index included in the system is determined based on the Analytical Hierarchy Process (AHP) method. Thus, the level of the emergency rescue capability of the fire station can be evaluated quantitatively. At last, a fire station in Zhengzhou city is taken as an example to verify the effectiveness of the established system. The results reveal that the emergency rescue capability of the fire station is in general level. Accordingly, the measures to strengthen the rescue capacity of the referred fire station are put forward. Keywords: fire station; emergency rescue capability; influence factors; FCE

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1. Introduction

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The domino effect of the accidents in urban area, such as the explosion in chemical industries (Kamil, et al., 2019), failure of urban buried gas pipelines (Wang, et al., 2017) and etc. seriously threaten the urban safety. Though the urban safety has been greatly improved in China, major fire accidents still occur frequently, causing a large number of casualties and loss of property. For example, the catastrophic fire and explosion of Tianjin port in China directly led to 165 deaths and losses of about 6.866 billion yuan in 2015 (Zhao, 2016). The fire and explosion occurred in Xiangshui, Jiangsu province resulted in 78 deaths and 617 injuries in 2019 (Zhang, et al., 2019). According to the fire statistics published in China Fire Yearbook (2018), the accident number, corresponding deaths and direct economic losses from 2000 to 2017 are obtained and presented in Fig. 1. A number of 4214328 fire accidents have occurred since the year of 2000, resulting in direct economic loss of about 42.4 billion yuan, 33535 deaths and 32198 injuries. The number of the accidents and associated casualties show a decreasing trend from 2000 to 2012 and then rise quickly until 2013 is reached. The direct economic loss is relatively steady from 2000 to 2012. But it grows rapidly in 2013, which reaches about 2.2 times that in 2012. Though the curves in Fig. 1 exhibit a downward trend since 2014, there are still many accidents and associated casualties occurring in China, which influences social stability drastically. Fire station is the primary unit designed for urban firefighting and emergency rescue activities. The efficiency of the fire station has been greatly improved in the past decades. As shown in Fig. 2, the response times of the fire station increase from 209000 to 1189000 during the period from 2000 to 2017 in China. The number of response vehicles increase from 738000 to 2248000 during the time bucket. Though the number of people rescued by the firefighters experience local fluctuations from 2000 to 2017, it increases to 1Corresponding

author. School of Emergency Management and Safety Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China. E-mail address: [email protected] (K. Wang). 1

157008 from 12527 within the referred period. It is worth to note that the evolution trend of the curve showing response times due to fire accident in Fig. 2 is in line with that of the curve plotting accidents number in Fig. 1.

5

3.5 Direct economic losses

×103

Accidents number Direct economic losses Associated deaths Associated injures

×103 4.5

3.0

4.0 3.5

3.0

3

2.0

2.5 2.0

2

1.5

Associated deaths

2.5 Accidents number

4

3.0 2.5 2.0 1.5

Associated injures

×105 4.0

×105

1.0

1.5 1

1.0 2002

2004

2006

2008 2010 Year

2012

2014

0.5

2016

ro of

1.0 2000

Fig. 1. The number of accidents, deaths, injured and direct economic loss between 2000 and 2017

20

60 40

15 20 10 2002

2004

2006

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2000

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2008 2010 Year

200

200 180 160 140 120 100

150 People rescued

25

80

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30

100

220

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35

Response times Response times due to fire Response vehicles People rescued

120

Response times

Response times due to fire

40

×103

×104 240

×104

Response vehicles

×104

100

50

80 60

0

40 2012

2014

2016

Fig. 2. The number of response times, response times due to fire, response vehicles and rescued people between 2000 and 2017

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At present, the research of fire station mainly emphasizes on the spatial location. For instance, Chaudhary et al. (2016) thought that the fire station location was related to four factors in Kathmandu Metropolitan City, the capital city of Nepal, including the distance from roads, land cover, distance from rivers and population density. Reilly and Mirchandani (1985) researched on fire station location in Albany, New York, highlighting the importance of maximizing accessibility to potential demand and a maximum response standard. Chevalier et al. (2012) presented a decision-aid tool for the location determination of fire-stations in Belgium, including the risk-modeling approach and the optimization of the location. The primary objective of the fire station is to save lives. Accurate evaluation of the emergency rescue capability of fire station is the foundation work for urban emergency management. Thus, the aim of the present study is to identify the key elements, which influence the rescue capacity of urban fire station, and moreover, establish a rescue capability evaluation system for the fire station. Accordingly, in the next section, influence factors of the rescue capability of the fire station are first determined by literature review and expert consultation. A scientific and systematic evaluation system is established and the analysis process of FCE method is introduced in 2

Section 3. A fire station is chosen to verify the capability of the established evaluation system in Section 4. Based on the analysis result, the measures to strengthen the function of the referred fire station are proposed in Section 5. Some contents of the system, which need to be further improved, are discussed in Section 6. The last section presents the main conclusions.

2. Establishment of rescue capability evaluation system for fire station 2.1. Influence factors of the rescue capability 2.1.1. Personnel

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Fire station is mainly composed of firefighters and fire appliances. At present, the standards of the National Fire Protection Association (NFPA) for firefighters are NFPA1710 (for career firefighters) and NFPA1720 (for volunteers). Both NFPA1710 and NFPA1720 standards contain the basic requirements of emergency response time of fire station, emergency medical services, resources management (such as the safety and health, training and communication), etc., which reflect the rescue capability of the fire station. The number of firefighters has direct influences on the rescue capability. Hodous et al. (2004) reviewed firefighter fatalities from 1998 to 2001. They identified eight frequently occurring recommendations that highlighted three general areas of concern. One of the three concern areas was the adequate staffing and the adherence to contemporary incident command practices. Svensson and Särdqvist (2001) thought that the capability of the fire station to fight fires was related to their ability to reach the burning area in large spaces. Furthermore, Jiang et al. (2012) focused on the accident cases involving firefighter death and analyzed the ages, types on duty and seasons of the death of the firefighters. The results showed that the deaths and injuries of the firefighters can be reduced by improving the personal protection, the ability of setting up reconnaissance, the procedure of firefighting, the review of firefighting, the safety education and the ability of fire commanders. The physical condition of the firefighters also directly affects the rescue capability of fire station. The obesity is an important personal problem influencing physical condition of the firefighters in recent years (Kales et al., 2007; Geibe et al., 2008). More and more studies (Donovan et al., 2009; Choi et al., 2011; Jitnarin et al., 2014; Brown et al., 2015) have focused on the investigation of the factors influencing the firefighter obesity. Psychological condition affects the firefighters' action greatly, which is closely related the rescue effort. Smith et al. (2018) examined the relationship between psychological factors, (such as work stress, work-family conflict and the burnout) and safety behavior outcomes. The results indicated that the stress and work-family conflict were associated with the burnout, and the burnout, which was a personal stress-related action, did negatively impact on the safety performance of the firefighter in the fire station. Finney et al. (2015) introduced a comprehensive Suicide Prevention Program for Houston Fire Department. The purpose, methodology, and implementation were summarized in three phases involved in the program. Svensson (2001) pointed out that the organization and coordination ability of the fire commanders also played an important role in the fire rescue process, who determines the allocation of firefighters and fire appliances as well as the development of the fire-fighting tactics (Svensson, 2002). Based on previous works, the factors associated with the rescue capability of the fire workers are mainly reflected in seven aspects, which are summarized in Table 1. The seven aspects can be classified into adequate staffing, emergency response ability, equipment operation skill, physical condition, psychological condition, firefighting knowledge, and organization and coordination ability of the fire commanders.

2.1.2. Equipment Fire equipment is indispensable to the firefighting work. Among various equipment types, fire vehicle is an important equipment to extinguish the fire (Yeboah and Park, 2018). Xie and Wang (2013, 2014) presented the application of heavy compressed air foam truck in fighting high-rise building fires. Wang et al. (2011) introduced the 3rd generation fire truck, including turbojet fire truck, water mist fire truck, and compressed air-foam A/B fire truck etc. Given truth that a large number of firefighters were burned during fire-fighting effort (Karter and Badger, 3

2000), the protective equipment should be used to guarantee the safety of the firefighters. In order to achieve such aims, numerous works have been performed on the protective clothing (Raimundo and Figueiredo, 2009; Fu et al., 2015) in the worldwide. In firefighting practice, the protective footwear (Irzmańska, 2015), protective clothing (Park et al., 2011), respirator, rescue helmet, safety rope, life jacket, and fire axe etc. are vital to the safety of the firefighters. In China, fire extinguishing equipment is an essential part in fire stations, which can be divided into water injection equipment and water conveying equipment. The former contains the spray gun, mobile fire cannon, and foam hook pipe etc. The latter is composed of fire hose, water absorber, water separator, and water pocket etc. Rescue equipment also plays an important role in the firefighter operations since the fire station undertakes various emergency rescue activities in society. It includes the transfer equipment (such as the various pumps, adsorption pad and oil fence) and washing equipment (such as disinfectant, strong acid and strong base agent etc.). Herein, the fire equipment in fire station mainly includes fire vehicles, protective equipment of the firefighters, fire extinguishing equipment, and rescue equipment. Table 1. Personnel influences of the rescue capability Source

Index

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Factors involved Adequate staffing

Hodous et al. (2004)

Emergency response time

NFPA1710; NFPA1720; Svensson and Särdqvist (2001)

Emergency response ability

Personal protection,

Jiang et al. (2012)

Equipment operation skill

reconnaissance, procedure of firefighting

Kales et al., 2007; Geibe et al., 2008; Donovan et al., 2009;

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Obesity, burnout

Adequate staffing

Physical condition

Choi et al., 2011; Jitnarin et al., 2014; Brown et al., 2015 Stress, work-family conflict,

Smith et al. (2018); Finney et al. (2015)

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suicide

Psychological condition

NFPA1710; NFPA1720; Jiang et al. (2012)

Firefighting knowledge

Allocation of firefighters and

Jiang et al. (2012); Svensson (2001, 2002)

Organization and coordination

appliances, formulation of fire-fighting tactics

2.1.3. Environment

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Training, safety education

ability of fire commanders

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The emergency response time is critical to the efficiency of fire rescue activities. Different countries have different requirements on the response time. In China, fire brigades need to reach the farthest area of their jurisdiction within 5 min after receiving the dispatch order (Chen and Guo, 1999). In Ontario of Canada, the fire department is required to reach the downtown core in 3 min, the urban boundaries in 5 min (Claridge and Spearpoint, 2013). In the UK, the national standards of fire cover originally contained four categories of risk degree (A, B, C and D, where A indicates the highest risk). Corresponding to different risk degrees, the required response time are 5, 8, 10 and 20 min, respectively (PD 7974-5, 2003). At present, more and more researchers have placed an emphasis on identification of the factors influencing the emergency response time (Claridge and Spearpoint, 2013). For example, Kiran and Jonathan (2017) pointed out that the response time was affected by the season, number of children (aged 14 years and below), socioeconomic households and street layouts. The average response time for the dispatch of fire forces is strongly associated with the road and traffic conditions (Chaudhary et al., 2016; Sufianto and Green, 2012). Water source are indispensable for the firefighting. The fire hydrant is an important equipment to provide water for extinguishing the fire (Shadin and Tahar, 2015). The fire hydrants installed throughout the urban water distribution system, which allows fire fighters to connect fire hose or fire spraying gun with the hydrants to put out a fire. Therefore, the number and location of the fire hydrants significantly affect the efficiency of firefighting work. Fire hydrant system can be divided into indoor fire hydrant system and outdoor fire hydrant system. The indoor fire hydrant is installed in the fire hydrant box. It can extinguish the fire inside the 4

building by connecting the water belt or water spraying gun. The outdoor fire hydrant system can not only supply water for fire vehicle, but also connect water belt or water spraying gun to extinguish the fire outside the building. Moreover, the natural water source is another source of water supply, which should meet some special requirement when serving for firefighting (GB 50974-2014). Accordingly, the road and traffic conditions, outdoor hydrant coverage, indoor hydrant coverage, and natural water source also have a great influence on the rescue capability of the fire station.

2.1.4. Management

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Wong and Xie (2014) concluded that a comprehensive fire safety management approach should contain fire management team plan, fire emergency procedure and maintenance plan, which demonstrate the responsibility of the staff (such as fire safety directors, fire safety managers, and senior fire wardens etc.), staff training plan (such as training course, fire drills, operational procedures etc.), and maintenance procedures etc. clearly. Baker et al. (2013) thought that the emergency plan and fire procedures, risk assessment, fire training, maintenance of fire equipment and organizational arrangement etc. played an important role in the process of fire safety management. Therefore, in respect of the management, staff on-duty management, equipment maintenance, firefighting emergency plan, and fire safety training are the important items for the fire station. Staff on-duty management can guarantee the staff on each post is in good working state and the division of their responsibilities is clearly. The equipment of the fire station is closely related to whether the fire can be extinguished in time by the station. Herein, the equipment maintenance is of great significance in the daily management work of the fire station. As discussed by Tseng et al. (2008), emergency plan plays a vital role in controlling casualties and environmental damages. Firefighting emergency plan can not only help firefighters deal with emergencies efficiently, but also assist the commanders to make appropriate decisions during the commanding process. Fire safety training contains the fire-fighting training and self-rescue knowledge training, equipment operation method training, fire drills etc., which can greatly improve the emergency rescue abilities of the firefighters. Thus, the regulation formulation and implementation of the above-mentioned items are essential to fire stations. Furthermore, the potential hazards and condition of fire equipment in the fire station should be inspected regularly.

2.1.5. Financial input

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As noted previously, the fire station contains the fire appliance and staff. There are fixed costs to equip the fire station with the necessary fire appliances as well update them (Plane and Hendrick, 1997; Badri et al., 1998). Thus, the establishment and maintenance of the fire station require certain fund. Such amount of money reaches about 2 million dollars for a new fire station (Murray, 2013). Generally, the cost of fire station varies with a series of objective changes, which include but are not limited to the vehicle and personnel increases, aging of equipment, and technological innovations etc. (Murray, 2013). In addition, the staff also needs a high fund (Church et al., 2001). Such money is used for safety training, fire drills, safety education and other activities of the fire station. The financial input can guarantee the capability of fire protection and response services of the fire station to a large extent, which includes personnel cost, equipment cost, management cost, and equipment consumption and maintenance cost.

2.2. Establishment of rescue capability evaluation system Based on the analysis result of Section 2.1, the evaluation system of emergency rescue capability for urban fire station can be established (shown in Fig. 3). The rescue capability of fire station is mainly reflected in five aspects, which are considered as the indexes in the criteria level. The five aspects refer to personnel (U1), equipment ((U2), environment (U3), management (U4), and financial input (U5). In the present paper, the goal layer is emergency rescue capability of urban fire stations (U). After that, the factor set U={U1, U2, U3, U4, U5} is built. In order to analyze and evaluate the rescue level of fire stations, the referred five indexes (criteria layer) are further decomposed. In respect to factor U1, adequate staffing (U11), emergency response ability (U12), equipment 5

operation skill (U13), physical condition (U14), psychological condition (U14), firefighting knowledge (U16), and organization and coordination ability of fire commanders (U17) are taken into consideration. The factor U2 is mainly composed of fire vehicles (U21), protective equipment (U22), emergency rescue equipment (U23), and fire extinguishing equipment (U24). The factor U3 contains the road and traffic conditions (U31), natural water source (U32), municipal hydrant coverage (U33), and indoor hydrant coverage (U34). Regarding the factor U4, it is separated into personnel duty management (U41), equipment maintenance (U42), fire safety inspection (U43), firefighting emergency plan (U44), regulation formulation and implementation (U45), and fire safety training (U46). Factor U5 is split into four indexes, including personnel cost (U51), equipment cost (U52), management cost (U53), and equipment consumption and maintenance cost (U54). Accordingly, 25 indexes are included in the sub-criteria layer. Emergency rescue capability U of urban fire station

U5 Financial input

U46 U51

U52

U53

Equipment consumption and maintenance cost

U45

Management cost

U44

Equipment cost

U43

Personnel cost

Regulation formulation and implementation

U34 U41 U42

Fire safety training

Firefighting emergency plan

Fire safety inspection

U33

Equipment maintenance

U32

Personnel duty management

U24 U31

Indoor hydrant coverage

U23

Municipal hydrant coverage

U22

Natural water source

U17 U21

Road and traffic conditions

Firefighting knowledge

U16

Fire extinguishing equipment

Psychological condition

U15

Emergency rescue equipment

Physical condition

U14

Protective equipment

Equipment operation skill

U13

Fire vehicles

Emergency response ability

U12

Organization and coordination ability of fire commanders

Adequate staffing

U11

U4 Management

U3 Environment

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U2 Equipment

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U1 Personnel

U54

3. Description of the FCE method

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Fig. 3. Evaluation system of emergency rescue capability for urban fire station

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The evaluation of the system where the objective is influenced by a single variable fairly is quite simple. Once the variables involved in the system increases, the traditional evaluation methods become imprecision or unsuitable (Guo et al., 2009). Considering the uncertainty and vagueness of the decision problems, both the fuzzy theory and traditional evaluation method should be incorporated in practices. In evaluating the system with many variables related the objective, the determination of the weight of the influences is an important work. There are many methods being used to determine the indexes weights, including the objective and subjective methods. The characteristics of commonly used methods are summarized in Table 2 (Liu and Wu, 2017; Saaty, 1996; Chen, 2019; Galeshchuk, 2016; Deng, 1989; Hesamian and Akbari, 2019). In this study, the indexes chosen to evaluate the emergency rescue capability of urban fire station have no collected sample data. Thus, the objective empowerment evaluation method cannot be used to determine the index weight. Accordingly, the subjective weight analysis method is utilized to determine the index weight. As shown in Table 2, the expert estimation method only conducted on the descriptive statistics, which is difficult to guarantee the result rationality. In the AHP and binomial coefficient methods, qualitative judgment of the experts is transformed to be quantitative. Thus, the result is more reliable than that of expert estimation method. In the binomial coefficient method, the calculated weights of different indexes are prone to be equal. That means the determined weight value may be inconsistent with the real situation. Regarding the AHP method, there are also some problems. For example, the judgments of different experts are prone to be contradictory. However, considering the difficulty in quantification analysis of the indexes included in this study, the AHP method, which quantifies the experts' qualitative judgment based on subjective experience knowledge, is more suitable. Thus, the AHP method is chosen to determine the weights of the indexes included in the evaluation system. 6

Table 2. Various techniques for determining the weights and their description Classification

Common characteristics

Method

Description Advantage: 1. makes full use of the knowledge of the experts and

Expert estimation method

takes various external factors into account; 2. simple calculation process; 3. not limited by sample data. Disadvantage: difficult to ensure the reasonability of the results in case of too many indexes. Advantage: 1. takes the advantage of both qualitative analysis and

Subjective

Influenced by the

weighting

experience and

method

quantitative analysis; 2. decomposes the complex system into AHP

knowledge of the experts

multi-criteria layers; 3. Not limited by sample data. Disadvantage: difficult to meet the consistency test when there are too many indexes at the same layer. Advantage: 1. quantifies the qualitative judgments of the experts; 2. easy to judge relative importance between different indexes; 3. not

coefficient

limited by sample data.

method

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Binomial

Disadvantage: deviations may exist in the determined weights; weights of different indexes are prone to be equal.

Advantage: 1. relatively simple calculation process; 2. the result is objective; 3. not limited by the number of the indexes.

method

Disadvantage: fails to reflect the correlation between different

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Entropy

indexes and the problem of information overlap remains unsolved.

Realize quantitative

network

analysis of the indexes;

analysis

High requirements of the

weighting

sample data;

method

Neglect the experience

experts.

Grey

correlation analysis

Principal

component

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is scientific and reasonable; 4. not limited by the number of indexes. Disadvantage: high requirements on the quality of the sample data. Advantage: 1. relatively simple calculation process; 2. not limited by

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and knowledge of the

dynamic evaluation characteristics; 3. relative weight of the indexes

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Objective

Advantage: 1. adaptable to nonlinear and complex problems; 2.

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Neural

analysis

the number of the indexes. 3. the errors caused by missed sample information are greatly decreased; 4. the result is objective. Disadvantage: determination of the resolution coefficient value is subjective; the problem of information overlap remains unsolved. Advantage: 1. the problem of information overlap between various indexes is solved; 2. the result is objective; 3. not limited by the number of the indexes; 3. wide application scope. Disadvantage: relatively complex calculation process; assumption of the linear relationship between different indexes.

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Based on the fuzzy theory and AHP method, the FCE method is developed, which composed of the following steps (Chen et al, 2018): Step 1: establish the factor set. A factor set consists of various factors influencing the evaluation objective (U). The factors associated with the evaluation objective can be generally divided into criteria layer (Ui) and sub-criteria layer (Uij). After this, the factor set U={U1, U2,…,UN} is determined where N is the number of factors in criteria layer. Moreover, each factor of the criteria layer is decomposed into the factor set of the sub-criterion layer, which is expressed as Ui={Ui1, Ui2,…,Uin} where i=1,2, ,…, N and n is the number of factors involved in the sub-criterion layer corresponding to the factor in the criterion layer. In this paper, five factors are contained in the criteria layer. The factor set U is then written as U={U1, U2, U3, U4, U5}. Based on the factors identified in Section 2, the factor set of the sub-criteria layer is expressed as U1={U11, 7

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U12, U13, U14, U15, U16, U17}; U2={U21, U22, U23, U24}; U3={U31, U32, U33, U34}; U4={U41, U42, U43, U44, U45, U46}; U5={U51, U52, U53, U54}. Step 2: determine the comment set. A comment set V is used to determine the levels of the evaluation objective. Generally, the comment set is expressed as V={V1,V2 ,…, Vm}, where, m is the number of the evaluation grades. In the present paper, the emergency rescue capability of urban fire station is classified into five levels. Level V1 means the fire emergency rescue capability of urban fire station is very good (fine), which can deal with the emergencies very well. Level V2 indicates the fire emergency rescue capability of urban fire station is good (standard), which can deal with the emergencies. Level V3 represent the fire emergency rescue capability of urban fire station is not bad (general), which can basically deal with the emergencies. Level V4 means the fire emergency rescue capability of urban fire station is low (bad), which cannot effectively deal with the emergencies. Level V5 indicates the fire emergency rescue capability of urban fire station is very low (worse), which cannot deal with the emergencies. Therefore, the comment set V= {V1, V2, V3, V4, V5} transforms into V= {fine, standard, general, bad, worse}. At the end of this step, the values of the five grades for the fire emergency rescue capability of urban fire station are given and listed in Table 3. Table 3. The score criteria corresponding to the five grades Grade

Fine

Standard

General

Bad

Worse

E

E≥85

70≤E＜85

60≤E＜70

45≤E＜60

E＜45

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Step 3: establish the single factor evaluation matrix. The factor Uij in the sub-criterion layer is quantified and its single factor evaluation matrix is rij  (rij1 , rij2 , rij3 , rij4 , rij5 ) . Where, rijk means the degree of Uij subordinated to the

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comment Vk where 0≤ rijk ≤1 and k=1,2,3,4,5. In this light, the single factor evaluation matrix (Ri) of the criterion layer is obtained:

ri15   ri52  (1) …  rin3  Step 4: determine each factor's weight. The index weight represents the importance of the factor in the ri12 ri 22 … rin2

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 ri11  1 r Ri   i 2 …  1  rin

… … … …

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evaluation system. In this paper, AHP method is chosen to determine the weight of each factor. AHP approach was introduced by Thomas. L. Saaty (1996), which allows multi-criteria evaluation. According to the AHP method, a hierarchical decision system needs to be established by decomposing the evaluation objective into multi-criteria layers. It is convenient to conduct pairwise comparisons for the decision maker. In applying the AHP, the decision maker can only focus on the comparison of two factors. That makes the observer unaffected by other factors. The mainly process is presented as following. (1) Establish the hierarchy structure. In the present paper, the evaluation objective is the emergency rescue capability of urban fire stations (U). As noted in Section 3, U is decomposed into criteria layer and sub-criteria layer, which contains five and 25 factors, respectively. Accordingly, a three multi-layer analysis model is formed according to the relationship existing between different factors. (2) Construct the judgment matrix (P). The judgment matrix is constructed by carrying out pairwise comparison on the factors in the present layer which is related one factor in the upper layer. The aim of such comparison is to determine relative importance between the factors in the present layer in respect to the related factor in the upper layer. Regarding the relative importance, it is characterized by the integers from 1 to 9. The larger value means the current index is more important than the comparison index. For example, the judgment matrix (P) of U (goal layer)-Ui (criteria layer) in this paper is yielded by: 8

 a11   a21 P   a31   a41 a  51

a12

a13

a14

a22

a23

a24

a32

a33

a34

a42

a43

a44

a52

a53

a54

a15   a25  a34   a45  a55 

(2)

where, apq stands for relative importance between the index Up and Uq, whose value is selected from Table 4. The larger value means index Up is more important than index Uq to the objective U. The subscript p and q vary from 1 to 5 as there are five factors in the criteria layer. The results of the comparison are written as a matrix (Eq. 2), which is generally named as the judgment matrix. Table 4. The scales in the judgment matrix and their implications Scale

Linguistic scale of importance Equally important

3

Weakly more important

5

Strongly more important

7

Very strongly more important

9

Absolutely more important

2,4,6,8

Intermediate value of the above adjacent judgment

1, 1/2, …, 1/9

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1

The importance degrees of two factors are contrary to the above results.

(3) Calculate each factor weight. The weight can be calculated by

-p

PW  maxW

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where λmax means the maximum eigenvalue of the matrix P; W is the eigenvector corresponding to λmax. If the dimension of the matrix P is large, λmax can be yielded by 1 n ( PW )i max   n i 1 Wi

(3)

(4)

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Then the desired feature vector is obtained, which is expressed as: W  (W1 ,W2 ,…,Wn )T Accordingly, the weight .

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vectors of the evaluation objective and factor Ui in the criterion layer can be acquired. (4) Check the consistency of judgment matrix. Since the judgment matrix is obtained by subjective judgment of the experts, many logical errors may occur possibly. Therefore, the consistency check should be carried out to estimate the rationality of the judgment matrix. The judgment matrix requires consistency testing with the following method. In equations (5) and (6), CR is the consistency ratio of the judgment matrix; CI is the consistency index of the judgment matrix; RI is the random index of the judgment matrix; n is the order of matrix. The magnitude of RI depends on the dimension of the judgment matrix. When the matrix dimension varies from 1 to10, the suggested value for RI is listed in Table 5. The judgment matrix meets the consistency requirement if the value of CR is equal to or smaller than 0.1. Otherwise, the judgments matrix needs re-examination. CR  CI 

CI RI

(5)

1 (max  n) n 1

(6)

Table 5. RI values of random consistency index n

1

2

3

4

5

6

7

8

9

10

RI

0

0

0.58

0.9

1.12

1.24

1.32

1.41

1.45

1.49

Step 5: determine the FCE vector (Bi) of Ui of the criterion layer. The vector Bi is obtained by 9

Bi  Wi

 ri11  1 r Ri  ( wi1 , wi 2 ,…win )  i 2 …  1  rin

ri12 ri 22 … rin2

ri15   ri52   (bi1 , bi 2 , bi 3 , bi 4 , bi 5 ) …  rin3 

… … … …

where wij refers to the weight of the factor in the sub-criteria layer, and

n

w

ij

j 1

(7)

1.

Step 6: the evaluation grade can be determined by the FCE vector. According to the weights wi and the FCE vector Bi corresponding to the factors belonging to the criterion layer, the FCE vector C of the evaluation objective can be obtained.  b11 b12  b b21 C  ( w1 , w2 , …, w5 )  21 … …   b51 b52

… … … …

b15   b25   (C1 , C2 , …, C5 ) …  b55 

(8)

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If the evaluation set C does not satisfy the normalization, the normalization of C should be carried out. And the normalized set is written as C  (C1 , C2 , C3 , C4 , C5 ) , where C' reflects the percentage occupied by the evaluation objective in the comment set V. Based on the maximum subordination principle, the evaluation grade of the evaluation objective can be obtained from C'.

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4. Practical application

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Zhengzhou city is the provincial capital of Henan province, China. The commercial buildings and residential buildings are the main constructions of the city. In this section, the emergency rescue capability of one fire station in Zhengzhou city is taken as an example. Its service area is shown in Fig. 4a, which is circled by the red line. The figures 4b and 4c present the main roads of the service area and the map of fire station respectively. The fire station is constructed in May, 2006. The area of its jurisdiction is about 40 square kilometers. There are 28 staffs belonging to this fire station, including two fire commanders, nine vehicle drivers, three correspondents and fourteen firefighters (14).

Fig. 4. The jurisdiction area of the chosen fire station

In this study, the required information is collected through questionnaires. Two kinds of questionnaires are 10

used, one is to estimate the relative importance of the factors contained in the evaluation system and the other one is to investigate the actual condition of this fire station. Ten experts familiar with this fire station contribute to the questionnaire survey and interview. The importance of the indexes in the criteria layer and sub-criteria layer is different. To obtain the weight of each index, the value corresponding to different indexes is first scored by the experts. Then, the index weights are calculated based on the AHP method. The result of the questionnaires completed by different experts is calculated separately. And the final weight of each index is equal to the average weight calculated from all questionnaires. After the analysis, the result shows that all CR values are less than 0.1, which can meet the consistency test requirement. The weight vectors corresponding to U1, U2, U3, U4 and U5, which are involved in the judgment matrix U, are presented as following: W=[0.2,0.2,0.2,0.2,0.2], W1=[0.2,0.17,0.12,0.14,0.13,0.11,0.13], W2=[0.39,0.28,0.19,0.14], W3=[0.33,0.36,0.18,0.13], W4=[0.27,0.22,0.17,0.14,0.11,0.09], W5=[0.34,0.38,0.20,0.08]. An index with a high weight value in the vector implies it is more important than other indexes at the same layer. Based on the method referred in the last section, the weights of different indexes are presented in Table 6.

layer

layer

Personnel U1

Weight

0.2

Sub-criterion layer

Weight

Adequate staffing U11

0.20

Emergency response ability U12

0.17

Equipment operation skill U13

0.12

Physical condition U14

0.2

input U5

0.2

0.3

0

0.2

0.3

0.5

0

0

0.1

0.5

0.4

0

0

0.3

0.5

0.2

0

0.11

0.1

0.3

0.5

0.1

0

0.13

0.1

0.5

0.4

0

0

0.39

0.3

0.5

0.2

0

0

Protective equipment U22

0.28

0.2

0.6

0.2

0

0

Emergency rescue equipment U23

0.19

0.1

0.8

0.1

0

0

Fire extinguishing equipment U24

0.14

0.1

0.8

0.1

0

0

Road and traffic conditions U31

0.33

0

0.4

0.6

0

0

Natural water source U32

0.36

0

0.1

0.9

0

0

Municipal hydrant coverage U33

0.18

0.1

0.2

0.7

0

0

Indoor hydrant coverage U34

0.13

0

0.1

0.8

0.1

0

Personnel duty management U41

0.27

0.3

0.3

0.4

0

0

Equipment maintenance U42

0.22

0.2

0.4

0.4

0

0

Fire safety inspection U43

0.17

0.3

0.3

0.4

0

0

Firefighting emergency plan U44

0.14

0.2

0.4

0.4

0

0

0.11

0.3

0.6

0.1

0

0

Fire safety training U46

0.09

0.1

0.4

0.4

0.1

0

Personnel cost U51

0.34

0.2

0.3

0.4

0.1

0

Equipment cost U52

0.38

0.4

0.5

0.1

0

0

Management cost U53

0.20

0.1

0.2

0.4

0.3

0

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Emergency rescue capability for urban fire stations U

0.5

0

Regulation formulation and implementation U45

Financial

0.2

0.13

ur U4

0

0

0.2

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Worse

0.3

Fire vehicles U21

U3

Bad

0.3

fire commanders U17

0.2

General

0.2

Organization and coordination ability of

Environment

Standard

0.2

Firefighting knowledge U16

U2

Fine

0.14

Psychological condition U15

Equipment

Results of single factor evaluation

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Table 6. Computed weights for all factors

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Equipment consumption and maintenance cost U54

0.08

0.1

0.4

0.5

0

0

According to the factors in the sub-criteria layer, another questionnaire is compiled to investigate the rescue capability influences of the fire station. Then, the questionnaire filled by the respondents are comprehensively analyzed to determine the degree of each factor subordinated to the five levels of the comment set V. After that, the single factor evaluation results are achieved and shown in Table 6. According to the equation (7), the FCE vector of the index U1 in criteria layer is: B1 =(0.098,0.316,0.447,0.139,0)

With the same method, B2, B3, B4 and B5 are determined, respectively, which are: B2  (0.206, 0.627, 0.167， 0， 0); B3  (0.018, 0.217, 0.752, 0.013, 0); B4  (0.246, 0.378, 0.367, 0.009, 0); B5  (0.248， 0.364， 0.294, 0.094, 0).

Based on the FCE vectors and the weights of the indexes in criteria layer, the FCE vector is determined: C  (0.1632,0.3804,0.4054,0.051,0)

5. Safety suggestions

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Note that, since the evaluation set C satisfies the normalization, the normalization of C does not need to carry out. Based on the estimation set V={fine, standard, general, bad, worse}, it is concluded that, regarding the selected fire station, the FCE evaluation status value corresponding to the level of “fine” is 0.1632. The value of 0.3804 corresponds to the level of “standard”. The value of 0.4054 corresponds to the level of “general”, and the value corresponding to level of “bad” is 0.051. Therefore, according to maximum subordination principle, the evaluation grade of the evaluation objective belongs to “general”. For further validating the evaluation result of emergency rescue capability of the selected fire station, the fire station is comprehensively graded. In the present paper, the comment set is assigned a value and the comment vector is F=[85 70 60 45 0]T. Then the score of the selected fire station can be calculated as follows: E  C  F  67.119 According to result E', the score falls within the region of [60, 70]. Herein, the status of this fire station belongs to level 3, which is in accordance with the previous judgment obtained from the maximum subordination principle.

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The evaluation results show that the rescue capability of the chosen fire station can basically deal with the emergencies. However, incidents and accidents occur frequently in its jurisdiction area due to rapid economic development in China. Such real condition needs the fire stations have relatively high emergency handling capacity. Based on the single factor evaluation results listed in Table 6 and the expert consultation, the levels of some factors, related to the personnel (U1), environment (U3), management (U4), and financial input (U5) are relatively low. For example, in terms of the personnel, more attention should be paid to strengthen the physical condition, psychological condition and firefighting knowledge of the firefighters. Regarding the environment, the road and traffic conditions within the jurisdiction area of the fire station significantly affect the speed of fire vehicles and the personnel to reach the rescue site. And the outdoor and indoor hydrants cannot meet the needs of the firefighting. In respect to the management, personnel duty management, equipment maintenance, fire safety inspection and fire safety training should be strengthened. For financial input, the personnel cost and management cost should be increased. Accordingly, some safety suggestions for improving the rescue capability of the evaluated fire station are put forward in the following. (1) Fire safety training. Fire safety training should be conducted regularly, which contains the training course and fire drill. The content of training course should be formulated according to the roles and responsibilities of the trainees. The course content includes but not limit to the way to raise an alarm, how to deal with the alarm, how to use the firefighting equipment, distribution of escape routes, firefighting access routes, evacuation procedures etc. 12

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The training course provides the trainees with the basic fire knowledge and working skills. Fire drills can ensure that the firefighters are able to deal with the emergencies correctly and efficiently. By formulating fire emergency plans for major accidents and conducting fire drills, the deficiencies of the plans designed for the emergency rescue can be identified in time. (2) Intelligent monitoring system establishment. Regarding the fire station, the important places, fire alarm equipment and firefighting equipment in their jurisdiction should be monitored by establishing an intelligent monitoring system. Once the monitored object appears abnormal condition, the system will display a warning state in real time (flashing on the screen). The location, quantity and pressure of the outdoor and indoor hydrants also should be monitored by the system. It can ensure that the fire vehicles are capable to find the water source quickly if a fire occurs and the hydrants are in normal condition. Meanwhile, the system can also monitor the road and traffic conditions. The route with good approachability can be found based on the system when fire vehicles need to reach the accident site emergently. (3) Psychological counseling. Fire rescue work is life-threatening for firefighters. Firefighters are under potential pressure from various aspects, especially from the risk of their own death, colleague death and rescued person death. Such pressure drastically influences their mental health. Thus, the psychological counseling room should be established to serve as a mind harbor for the firefighters. The professional equipment and facilities, such as music relaxation equipment, psychological sand table, catharsis equipment etc., can be used for constructing the psychological counseling room. The professional counselors regularly provide the firefighters with psychological counseling program. (4) Skill training. Skill training also plays an important role in improving the rescue capability of firefighters. Appropriate training can improve the firefighters' adaptability, persistence and comprehensive ability in the rescue work. However, excessive and inappropriate training can damage the firefighters' health. Therefore, the skill training program and training method should be constantly revised according to the standard requirements, past training experience and expert recommendations. Furthermore, some theoretical models and emergency evacuation simulation platforms can be developed to simulate the emergencies to assist the firefighters in the skill training. For example, the Oak Ridge Evacuation Modeling System (OREMS) is a simulation model designed to analyze the emergency evacuation schemes for large-scale transportation network (Li et al., 2011). Furthermore, as mentioned in Section 2, the equipment of the fire station mainly includes fire vehicle, protective equipment, emergency rescue equipment and fire extinguishing equipment. In fact, the fire station can equip with some advanced firefighting equipment and facilities to deal with special disasters. The advanced equipment, such as firefighting robots and fire drone, can extinguish the fire quickly and protect the firefighters from dangers. In addition, the government not only needs to raise the income of the firefighters to ensure their daily lives but also needs to increase the fund of the management to ensure daily management work of the fire station.

6. Discussion on the evaluation system

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In addition to the indexes considered in this study, the structure of the road network within the jurisdiction of the fire station also affects its rescue capability. Usually, there are many roads connecting the fire station and the accident site. Regarding the firefighters, how to choose the fastest path to reach the accident site is an important problem. Whether the selected route can reach the destination in time? Will any congestion be encountered when the fire vehicles are moving forward? Is the rescue channel occupied or blocked along the selected path? The problems abovementioned are closely related to the rescue capability of the fire station. The traffic convenience for fire vehicles and firefighters from the fire station to the accident site can be regarded as the approachability. The concept of approachability was originally proposed by Hansen in 1959. With the development of geographic information system (GIS), the relevant theories are extensively used to establish the models for spatiotemporal approachability analysis. Such models are utilized to illustrate the influences of geographic environment and 13

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geographic scale on individual approachability (Kwan, 1998). Based on large-scale applications of the GIS technology, neural network and multi-criteria decision analysis are extended and applied to the study of the approachability. After that, there are many approachability evaluation models being proposed, including time-distance measure method, space separation measure method and gravity model etc. Specifically, the time-distance method is widely used in approachability research, which refers to the time required to cross the space distance. Based on the ArcGIS software, Chen (2010) used the weighted average time-distance as an index in analyzing the traffic approachability of counties and cities in Anhui province, China. Shan (2010) established the road network dataset model based on network analyst extension of ArcGIS. With the referred model, the shortest time method and shortest distance method are used to analyze the approachability of highway traffic network in Xuzhou of Jiangsu province, China. Though the time-distance method is suitable for the study of emergency response service, it is too simple to accurately measure the approachability. The map presented in Fig. 4b shows the main roads of the jurisdiction area (green) under protection of the service provided by the fire station referred in this study. Obviously, there are many roads (blue lines) forming the complex traffic network. In case of fire accident at position A (shown in Fig. 4b), the fire vehicles and firefighters can arrive at the fire ground along several paths. Given so many selections, the fire station commander should pick one route on the network to guarantee that the fire vehicles and firefighters are able to reach the destination as quickly as possible. To achieve such aims, the ArcGIS software is capable to simulate the optimal rescue path of the fire station. Meanwhile, the approachability resistance analysis and approachability evaluation would be carried out to ensure the quick and accurate implementation of the rescue work. After departure of the fire vehicles and firefighters, many unexpected things on the way may lead to the delay of the arriving time. For example, the fire vehicle may be blocked by other vehicles; the indoor and outdoor firefighting channels may be occupied and other potential unfavorable events. To avoid such conditions, the public awareness campaign should be conducted to improve the public safety awareness. The drivers of other vehicles will automatically give way to the fire vehicles when they pay attention to the fire safety. Besides, people would not occupy the specific fire channels in daily life. Thus, increasing the publicity and education of the safety knowledge is conducive to fire rescue activities. By taking the referred factors into account, both urban emergency response time and response plan are able to be more rationally evaluated and optimized. In order to predict emergence response time, a Fire Emergency Vehicle Agent was established by GIS analysis in combination with road network, population density and landuse data. The agent is effective in evaluating the road-deciding behavior and driving speed of the fire emergency vehicle (FEV) driver on the way to the accident location. Then, the response of the emergency service can be easily achieved (Bandyopadhyay and Singh, 2016a). Moreover, agent-based geosimulation is proposed and utilized to assess urban emergency response (UER) plans (Bandyopadhyay and Singh, 2018). There are seven components in the agent-based geosimulation frame work, where the real-world entities, such as FEV, people and geographic topology of urban area, are represented by agent-based modeling entities. Thus, a comprehensive model can be developed for urban emergency response system, which is used to simulate the emergency plan under various scenarios. According to the simulating results, the micro-deficiencies existing in the current UER plan can be identified. In addition, Cellular Automata (CA) (Ren et al., 2015), Dijkstra's Algorithm (Xu et al., 2007), Genetic Algorithm (GA) (Ahn and Ramakrishna, 2003), etc. can be used to optimize the path selection between the fire station and the destination. CA model is composed of discrete space, time and variables, which divides a particular space into many discrete lattice elements. These discrete lattice elements are named as cells and used to simulate real-word entities involved in fire rescue work. Dijkstra's algorithm is adaptable to solve the shortest path problem of fixed points. It records a weighted graph for all vertices. With the weight graph, the shortest path from one point to other points can be obtained. Recently, the spatial factors, such as road length, width, land use and population density, are combined with Dijkstra's algorithm in evaluating the route selection behavior of FEV drivers (Bandyopadhyay and Singh, 2016b). However, due to the large-scale and real-time application of traffic routing and path planning, 14

Dijkstra's algorithm is inefficient and time consuming. GA is a computational model extensively used to simulate the natural selection and genetic mechanism of Darwinian biological evolution. It is recently modified to solve the shortest path problem by transforming such problem into optimal solution identification problem. With the referred methods, accurate evaluation of urban emergency response time and response plan is able to be realized in further study.

7. Conclusion

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Urban fires continue to threat the safety of human beings lives and social properties. There is an imperious need for identifying the emergency capability of the fire station since it is the main force to minimize the bad consequences of the emergencies. The accurate evaluation of the rescue capability is also vital to the design optimization in the construction of the urban fire station. In this work, an evaluation system for the emergency rescue capability of the urban fire station is established based on the literature review and expert consultation. The system takes the emergency rescue capability as the goal layer, which is divided into the criteria layer and sub-criteria layer. Subsequently, the indexes of the criteria layer are separated into five aspects, including the personnel, equipment, environment, management and financial input. The sub-criteria layer contains 25 indexes, which are obtained from analyzing the indexes involved in criteria layer. Due to the fuzziness and uncertainty of the indexes, the FCE method is chosen to evaluate the emergency rescue capability of urban fire station. The work flow of the FCE method is presented in detail. After that, a fire station in Zhengzhou city is taken as a practical example to verify the effectiveness of the established evaluation system. Ten experienced experts familiar with the selected fire station contribute to the ascertaining of the weight of the lower layer indexes related to the same upper layer index. Meanwhile, each index in the sub-criteria is scored according to the actual condition of the fire station. Thus, it is promised that the proper values are identified for all indexes involved in the system. The analysis results show that the rescue level of the selected fire station is general. In order to improve the rescue capability of fire station, fire safety training, intelligent monitoring system, psychological counseling and skill training should be implemented. Note in the present study, the topology and approachability of the jurisdiction area are not considered in the system. Such influences would be taken into account in further study.

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Funding

This work was supported by the National Natural Science Foundation of China [grant number 51874314]; and the State Key Research Development Program of China [grant number 2016YFC0801402].

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References

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We have no conflicts of interest to declare.

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