Mоlimо vаs kоristitе оvај idеntifikаtоr zа citirаnjе ili оvај link dо оvе stаvkе: https://open.uns.ac.rs/handle/123456789/2904
Nаziv: Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O3 Air Quality Monitoring Network in Vojvodina Province, Serbia
Аutоri: Vujić, Bogdana 
Srđević, Zorica 
Srđević, Bojan 
Dаtum izdаvаnjа: 1-окт-2017
Čаsоpis: Environmental Modeling and Assessment
Sažetak: © 2017, Springer International Publishing Switzerland. A monitoring network of ground-level ozone (O3) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O3 monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O3 monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.
URI: https://open.uns.ac.rs/handle/123456789/2904
ISSN: 14202026
DOI: 10.1007/s10666-017-9560-8
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