Assessing relocation strategies of urban air quality monitoring stations by GA-based compromise programming

Tseng, C. C.; Chang, Ni‐Bin

doi:10.1016/s0160-4120(01)00036-8

Cited by 32 publications

(20 citation statements)

References 15 publications

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“…They include "site-by-site" method which is suitable for identification of monitors which could be relocated [3], "bottom-up" method which analyses phenomena that lead to increased concentrations of pollutants [4] and network optimisation using different analysis techniques including statistical methods, principal component analysis and cluster analysis, for identification of redundant measuring points [5,6]. Many authors also use different methods of multi-criteria analysis: combined with other methods [7÷14] or independently [15,16,17].…”

Section: Introductionmentioning

confidence: 99%

Decision making framework for decreasing the redundancy of air quality monitoring stations in Vojvodina Province (Serbia)

et al. 2016

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Original scientific paper Air quality monitoring stations are used for quick and reliable assessment of air quality. Although the stations are expensive, very often their number on certain territory exceeds optimal number of stations leading to their redundancy, increased costs, overlapping of data etc. To enable analysis of quantitative and qualitative criteria, authors propose an approach based on well-known decision support tool called analytic hierarchy process (AHP). As the first step in defining the decision framework for decreasing redundancy of stations locally and regionally in Vojvodina Province, three experts were asked to identify key performance indicators for assessing the performance of the stations. Fifteen indicators were selected and divided into three groups (Environmental objectives; Location/Technical objectives; and Social/Economic objectives). Experts evaluated performance of two stations in Municipality of Kikinda. Station KIMA showed better overall performance, so it is suggested to responsible authorities to relocate monitors from KISA station to KIMA station and thus decrease maintenance and operation costs. Keywords: air quality monitoring station; analytic hierarchy process; multi-criteria; redundancyOkvir za donošenje odluka o smanjenju suvišnih stanica za praćenje kvalitete zraka u pokrajini Vojvodina (Srbija)Izvorni znanstveni članak Stanice za praćenje kvalitete zraka se koriste za brzo i pouzdano vrednovanje kvalitete zraka. Bez obzira što su stanice skupe, vrlo često njihov broj na određenom teritoriju prelazi optimalni broj stanica što rezultira njihovim viškom, povećanim troškovima, preklapanjem podataka itd. Da bi omogućili analizu kvantitativnih i kvalitativnih kriterija, autori predlažu pristup temeljen na dobro poznatom alatu za donošenje odluka pod nazivom Analitički hijerarhijski proces (AHP). U prvom koraku definiranja okvira za donošenje odluka o smanjenju suvišnih stanica na lokalnoj i regionalnoj razini u pokrajini Vojvodini, tri eksperta su identificirala ključne indikatore za ocjenjivanje karakteristika stanica. Petnaest indikatora je izabrano i podijeljeno u tri grupe (ciljevi životne sredine, ciljevi lokacije/tehnički; socijalno/ekonomski ciljevi). Prema predloženoj metodologiji eksperti su vrednovali dvije stanice u općini Kikinda. Stanica KIMA je imala bolje ukupne karakteristike, zbog čega je odgovornima predloženo da premjeste mjernu opremu iz KISA stanice u KIMA stanicu te tako smanje troškove održavanja i operacijske troškove.Ključne riječi: analitički hijerarhijski proces; stanica za praćenje kvalitete zraka; višak; višekriterijski

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Section: Introductionmentioning

confidence: 99%

Decision making framework for decreasing the redundancy of air quality monitoring stations in Vojvodina Province (Serbia)

et al. 2016

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“…Results of application of this method to the AQMN for the city of Kaohsiung in South Taiwan indicated that the grey compromise programing model is a useful tool in evaluating the expansion alternatives with respect to different types of decision-making processes. Tseng and Chang (2001) in a companion study of Chang and Tseng (1999) developed a GA-based compromise programming technique to assess relocation strategy of air quality monitoring stations. Experience gained in this study pointed out that as the number of pollutants and objectives increases simultaneously, the higher number of candidate location are selected in the relocation strategy.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of air quality monitoring network around an oil refinery plant: a holistic approach

Benis

Fatehifar

2015

Int. J. Environ. Sci. Technol.

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In this study, a multi-objective method for allocating the number and configuration of an air quality monitoring network based on non-dominated sorting genetic algorithm II has been presented. The multiple cell approach based on the solution of an Eulerian Model built on K-theory was used to predict the dispersion of emitted pollutants (SO 2 , CO, NO x ) from different emission sources. The multi-objective optimization method proposed in this study utilized two objectives: (1) maximum coverage area with respect to continuity of covered area and minimum overlap among coverage areas and (2) detection of violations over ambient standards. The concept of sphere of influence was used to determine the spatial area coverage of the monitoring station, and a weighing function was employed to measure the capability of a designed network to detect violations of air quality standards. The results show that three stations are suitable for the study region with coverage efficiency of 80 %. Analyzing the effect of cutoff correlation coefficient r c shows that, when the r c increases, although the coverage area decreases, the covered region will be well represented and overlap region will decrease.

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“…Of course, many of these methodologies allow network reduction or extension and weighted criteria under suitable social, economic or technical restrictions (e.g. Langstaff et al, 1967;Husain and Khan, 1983;Shindo et al, 1990;TrujilloÁVentura and Ellis, 1991;Nychka and Saltzman, 1998;Tseng and Chang, 2001;Bocquet, 2005aBocquet, , 2005bKanaroglou et al, 2005;Kao and Hsieh, 2006;Abida et al, 2008;Elkamel et al, 2008;Abida and Bocquet, 2009;Ainslie et al, 2009;Mofarrah and Husain, 2010;Wu et al, 2010;Romary et al, 2011;Saunier et al, 2011;Sturman et al, 2011;Wu and Bocquet, 2011;Ruiz-Ca´rdenas et al, 2012;Osses et al, 2013;Singh et al, 2013;Wang et al, 2013;Cioaca and Sandu, 2014;Go´mez-Losada et al, 2014;Romary et al, 2014;Zidek et al, 2000Zidek et al, , 2014.…”

Section: Introductionmentioning

confidence: 99%

Analysis and optimal design of air quality monitoring networks using a variational approach

Henríquez¹,

Osses²,

Gallardo³

et al. 2015

Tellus B: Chemical and Physical Meteorology

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A B S T R A C T Air quality networks need revision and optimisation as instruments and network requirements, both scientific and societal, evolve over time. Assessing and optimising the information content of a monitoring network is a non-trivial problem. Here, we introduce a methodology formulated in a variational framework using an air quality model to simulate the dispersion of carbon monoxide (CO) as a passive tracer at the city scale. We address the specific case of adding or removing stations, and the more general situation of optimally distributing a given number of stations in a domain taking into account transport patterns and spatial factors such as population density and emission patterns. We consider three quality indicators: precision gain, information gain and degrees of freedom for a signal. These metrics are all functions of the singular values of the sensitivity matrix that links emissions and observations in the variational framework. We illustrate the application of the methodology in the case of Santiago (33.58S, 70.58W, 500 m a.s.l.), a city of ca. 7 million inhabitants with significant pollution levels. We deem information gain as the best of the above indicators for this case. We then quantify the actual evolution of Santiago's network and compare it with the optimal configuration suggested by our methodology and with results previously obtained using a statistical approach. The application is restricted to diurnal and summer conditions, for which the dispersion model shows a good agreement with observations. The current method offers advantages in that it allows extending a network to include new sites, and it explicitly considers the effects of dispersion patterns, and desired weighting functions such as emission fluxes and population density. We find that Santiago's air quality has improved two-fold since 1988, regarding CO under diurnal summer conditions. Still, according to our results, the current configuration could be improved by integrating more suburban stations in the southwest of the basin.

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Assessing relocation strategies of urban air quality monitoring stations by GA-based compromise programming

Cited by 32 publications

References 15 publications

Decision making framework for decreasing the redundancy of air quality monitoring stations in Vojvodina Province (Serbia)

Decision making framework for decreasing the redundancy of air quality monitoring stations in Vojvodina Province (Serbia)

Optimal design of air quality monitoring network around an oil refinery plant: a holistic approach

Analysis and optimal design of air quality monitoring networks using a variational approach

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