PMID- 36152706
OWN - NLM
STAT- MEDLINE
DCOM- 20221026
LR  - 20221026
IS  - 1873-6424 (Electronic)
IS  - 0269-7491 (Linking)
VI  - 314
DP  - 2022 Dec 1
TI  - Assessment of red tide risk by integrating CRITIC weight method, TOPSIS-ASSETS 
      method, and Monte Carlo simulation.
PG  - 120254
LID - S0269-7491(22)01468-3 [pii]
LID - 10.1016/j.envpol.2022.120254 [doi]
AB  - This study proposes a red tide risk assessment method based on intercriteria 
      correlation (CRITIC), technique for order preference by similarity to an ideal 
      solution (TOPSIS), assessment of estuarine trophic status (ASSETS) methods and 
      Monte Carlo simulation (MCS) to calculate the probability of each risk level. The 
      integrated TOPSIS-ASSETS method is used to calculate the risk levels of each 
      year, where index weight is determined by CRITIC method. MCS method is employed 
      to calculate the probability of each risk level. The results showed that level 
      III to level V indicates high possibility of red tides in the case study area 
      (Tolo Harbor). The highest risk rating was level V in 1988. The change of the 
      risk level of red tide is consistent with the real situation of the occurrence of 
      red tide. Another case of the east part of Skagerrak Strait shows that the 
      results of this method are consistent with field situation. When there is an 
      error between the evaluation results and the real situation, MCS can further 
      suggest the probability of error in the evaluation results. Meanwhile, 
      sensitivity analysis was used to test the performance of the evaluation model and 
      two comparative methods. The results show that the proposed risk assessment 
      method has better performance than other methods and can provide an effective 
      risk evaluation for red tide management.
CI  - Copyright (c) 2022 Elsevier Ltd. All rights reserved.
FAU - Chen, Yu-Lin
AU  - Chen YL
AD  - Department of Civil Engineering, School of Naval Architecture, Ocean, and Civil 
      Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic 
      address: chenyvl@sjtu.edu.cn.
FAU - Shen, Shui-Long
AU  - Shen SL
AD  - MOE Key Laboratory of Intelligent Manufacturing Technology, Department of Civil 
      and Environmental Engineering, College of Engineering, Shantou University, 
      Guangdong, 515063, China. Electronic address: shensl@stu.edu.cn.
FAU - Zhou, Annan
AU  - Zhou A
AD  - Discipline of Civil and Infrastructure, School of Engineering, Royal Melbourne 
      Institute of Technology, Victoria, 3001, Australia. Electronic address: 
      annan.zhou@rmit.edu.au.
LA  - eng
PT  - Journal Article
DEP - 20220921
PL  - England
TA  - Environ Pollut
JT  - Environmental pollution (Barking, Essex : 1987)
JID - 8804476
SB  - IM
MH  - *Harmful Algal Bloom
MH  - Monte Carlo Method
MH  - Risk Assessment
OTO - NOTNLM
OT  - CRITIC weight method
OT  - Monte Carlo simulation
OT  - Red tide
OT  - Risk assessment
OT  - TOPSIS-ASSETS method
COIS- Declaration of competing interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2022/09/25 06:00
MHDA- 2022/10/27 06:00
CRDT- 2022/09/24 19:23
PHST- 2022/08/01 00:00 [received]
PHST- 2022/09/15 00:00 [revised]
PHST- 2022/09/19 00:00 [accepted]
PHST- 2022/09/25 06:00 [pubmed]
PHST- 2022/10/27 06:00 [medline]
PHST- 2022/09/24 19:23 [entrez]
AID - S0269-7491(22)01468-3 [pii]
AID - 10.1016/j.envpol.2022.120254 [doi]
PST - ppublish
SO  - Environ Pollut. 2022 Dec 1;314:120254. doi: 10.1016/j.envpol.2022.120254. Epub 
      2022 Sep 21.