PMID- 31254084
OWN - NLM
STAT- MEDLINE
DCOM- 20190910
LR  - 20200225
IS  - 1573-2959 (Electronic)
IS  - 0167-6369 (Linking)
VI  - 191
IP  - Suppl 2
DP  - 2019 Jun 28
TI  - Determination of the physical domain for air quality monitoring stations using 
      the ANP-OWA method in GIS.
PG  - 299
LID - 10.1007/s10661-019-7422-3 [doi]
AB  - Air pollution is a major concern in some megacities of Iran. Specific cities in 
      the country have reached an extremely harmful level of air pollution which poses 
      a serious risk to the daily lives of Iranians. According to news reports, the air 
      quality index of the city of Tehran hovers around 159, which is more than three 
      times the World Health Organization's advised maximum. For the purpose of air 
      pollution abatement, it is necessary to precisely know the air pollution 
      distribution in the area. In order to obtain this figure, it is necessary to 
      properly locate the city's air quality monitoring stations that measure the 
      spatial pollutant distribution. According to various reports, the city must have 
      at least 56 air quality monitoring stations to properly measure Tehran's air 
      quality. However, there are currently only 20 stations within the city. Thus, the 
      main purpose of this study was to identify the most sufficient areas for 
      deploying new air quality monitoring stations. This study provided an integration 
      of hybrid multi-criteria decision-making (MCDM) theories and geographical 
      information system (GIS) processes in order to determine suitable areas to 
      establish air quality monitoring stations. Unlike traditional models, the 
      proposed MCDM method, ANP-OWA, is an efficient decision analysis which considers 
      dependencies between criteria and defines different scenarios between pessimistic 
      and optimistic conditions for decision makers. This method was applied to several 
      parameters such as point, area, and line sources; population density; sensitive 
      receptors; distance from current air quality stations; prediction error; and 
      spatial distribution of CO, NO(2), SO(2), and PM(10) pollutants. The output 
      results specified several suitable locations to establish air pollution 
      monitoring stations within Tehran Province. The stability and reliability of the 
      output results were evaluated with a robust sensitivity analysis method. 
      Moreover, the results demonstrated that the proposed method can produce stable 
      results. Obtaining knowledge regarding population density, distance from current 
      air quality stations, and spatial distribution of CO pollutant criteria is 
      essential when selecting locations for air quality monitoring stations.
FAU - Kazemi-Beydokhti, M
AU  - Kazemi-Beydokhti M
AD  - School of Surveying and Geospatial Engineering, College of Engineering, 
      University of Tehran, Tehran, Iran.
FAU - Abbaspour, R Ali
AU  - Abbaspour RA
AD  - School of Surveying and Geospatial Engineering, College of Engineering, 
      University of Tehran, Tehran, Iran. abaspour@ut.ac.ir.
FAU - Kheradmandi, M
AU  - Kheradmandi M
AD  - School of Surveying and Geospatial Engineering, College of Engineering, 
      University of Tehran, Tehran, Iran.
FAU - Bozorgi-Amiri, A
AU  - Bozorgi-Amiri A
AD  - School of Industrial Engineering, College of Engineering, University of Tehran, 
      Tehran, Iran.
LA  - eng
PT  - Journal Article
DEP - 20190628
PL  - Netherlands
TA  - Environ Monit Assess
JT  - Environmental monitoring and assessment
JID - 8508350
RN  - 0 (Air Pollutants)
SB  - IM
MH  - Air Pollutants/*analysis
MH  - Air Pollution/*analysis
MH  - Algorithms
MH  - Cities
MH  - *Environmental Monitoring
MH  - *Geographic Information Systems
MH  - Humans
MH  - Iran
MH  - *Neural Networks, Computer
MH  - Reproducibility of Results
OTO - NOTNLM
OT  - ANP-OWA
OT  - Air quality monitoring stations
OT  - Site selection
OT  - Tehran Province
EDAT- 2019/06/30 06:00
MHDA- 2019/09/11 06:00
CRDT- 2019/06/30 06:00
PHST- 2017/08/22 00:00 [received]
PHST- 2019/03/20 00:00 [accepted]
PHST- 2019/06/30 06:00 [entrez]
PHST- 2019/06/30 06:00 [pubmed]
PHST- 2019/09/11 06:00 [medline]
AID - 10.1007/s10661-019-7422-3 [pii]
AID - 10.1007/s10661-019-7422-3 [doi]
PST - epublish
SO  - Environ Monit Assess. 2019 Jun 28;191(Suppl 2):299. doi: 
      10.1007/s10661-019-7422-3.