Air Quality Monitoring Using Model: A Review

Transcription

1 Internatonal Journal of Scence and Research (IJSR), Inda Onlne ISSN: Ar ualt Montorng Usng Model: A Revew Ukagwe, Sandra A., Osoka, Emmanuel C., Department of Chemcal Engneerng, Federal Unverst of Technolog, P.M.B 56, Owerr, Imo State, Ngera Abstract: Ar polluton s a global envronmental challenge that has contnued to receve worldwde attenton despte the recent declne n concentraton of atmospherc pollutants followng strngent envronmental protecton regulatons. The major source of ths polluton remans fossl fuels; hence the urgent need for cleaner energ sources. Ths stud presents a revew of the models appled n montorng ambent ar qualt. The prmar am of ar polluton modelng s to dentf and quanttatvel characterze pollutant emsson at ts source and subsequent dsperson through the atmosphere, subject to meteorologcal condtons, phscal and chemcal transformatons. The common models and model assumptons for modelng ar polluton and qualt were crtcall revewed and analzed n ths work for applcaton n both forecastng and estmaton of ar pollutants on the bass of consdered causes and n ar qualt assessment and ar polluton control. Kewords: Pollutants, Gaussan, Dsperson, Models. Introducton Substances alterng phscal or chemcal propertes of the ar, added n suffcent concentraton to produce a measurable effect on man or vegetaton, are consdered as pollutants. Man studes have emphaszed that localzed crtcal concentratons of pollutants can serousl affect ar qualt. As a consequence, the relatonshp between observed concentratons of ar pollutants and human receptors s searched for. The evdence of ar polluton effects on man, anmals and vegetaton has suggested the need for better understandng of the nvolved phenomena. On account of ts effect on human lfe, ar polluton n urban and ndustral areas has become a major problem. Its characterstcs have not changed sgnfcantl n recent tmes, but the atmospherc process knowledge and the control technolog has greatl mproved. The qualt of ar n an atmosphere depends on the number of sources of pollutants, the rate at whch pollutants are sent nto the atmosphere and the ablt of the atmosphere to dsperse these pollutants, whch s largel controlled b weather patterns. Moble sources whch ncludes a varet of vehcles, road s the largest source of ar polluton, wth emsson varng from one tpe of vehcle to another, tpe of drvng, vehcle age, polluton control equpment, degree of mantenance and other factors []. Ar polluton model s the mathematcal or statstcal descrpton of the meteorologcal transport and dsperson processes usng source and meteorologcal parameters for a specfc perod of tme. Model calculatons result n estmates of pollutant concentraton for specfc locatons and tme. Ar polluton models can be used to perform both forecastng and estmaton of ar pollutant on the bass of consdered causes, thus the are appled n ar qualt assessment and ar polluton control. Montorng ar qualt helps n better understandng the sources, movements and effects of varous pollutants n the atmosphere. It also helps to ensure that facltes whch are releasng pollutants nto the ar are wthn the lmts establshed b natonal standards and gudelnes. Volume Issue 9, September 03 The data collected helps to control sources of ar polluton wthn an area, and to negotate wth governments n other jursdctons for controls on ar polluton that crosses borders. The more nformaton avalable on ar polluton, the more effectvel ar qualt and the envronment can be enhanced and protected. Although strngent regulatons on engne performance and fuel formulaton have brought about a declne n the amount of ar polluton produced b ndvdual vehcles brngng down the overall amount of ar polluton caused b moble sources, there s stll cause for concern because the number of vehcles on the roads and hghwas have ncreased consderabl over the ears and hence more pollutants are beng released nto the atmosphere. Ths work s a revew of researches on ar polluton and ar qualt montorng models.. Revew of Prevous Works Aronca [] appled Euleran model (equaton ) to estmate the quantt of gas produced and released nto the atmosphere from a landfll. c c c u w ( uc ) ( vc ) wc () t x x z u, vandware fluctuatons of the speed components along x,, and z axes respectvel, and c s the pollutant concentraton. The soluton of eq. () s gven b Gaussan model (eq. ()) z z c e e () u z = flow rate of the emtted pollutant, gven b: c( x,, z) uddz Constant (3) And the quanttes and z are representatve of the sde dmensons of the medum profle of the concentraton and the Gaussan standard devatons on the planes (x, ) and (, z). The estmated the monthl bogas emsson from the landfll nto the atmosphere to be about 60% of the total bogas produced b the landfll. Modelng of the same landfll usng LandGEM software gave the gas emtted as Paper ID:

2 Internatonal Journal of Scence and Research (IJSR), Inda Onlne ISSN: % of the total produced b the landfll. A more sophstcated dsperson model ma be requred to valdate ther work. Zhao and Wu [3] developed a model whch the called Partcle flter group model, for modelng partcle fate n ventlaton sstem. The model can be used to predct partcle fate n an entre ventlaton sstem b calculatng the concentraton and quantt of partcle deposted n each part of the sstem. The model ma also be used to calculate the partcle dstrbuton wthn the sstem. Equatons (4) and (5) show Partcle flter group model freshc o Pf d c n, sp P P P (4) C n, sp s r, return sd r oom, s r d B r oom, sp, / ( S P P ) r, return s p r d P P P s r, return sd r oom, s r d Where s the reccled ar flow rate, s the r, return s suppl ar flow rate, P rd s the penetraton coeffcent of return duct and S p s the generatng rate of the th partcle source. fresh s the fresh flow rate and C o s the partcle concentraton of the outdoor ar. The valdated the model expermentall. Hence partcle concentraton and deposton quantt at each part of a ventlaton sstem can be calculated easl, whch can help n the control of ndoor partcle concentraton. Mok et al [4] used a modfed Gaussan plume model to smulate the dsperson of a non-reactve ar pollutant (SO ) released nto the atmosphere under a non-homogenous wnd condton through a mult-puff approach. The appled the equatons (6) and (7) below to a specfc urban case stud and the result obtaned were compared to measured ar qualt data. Optmal nterpolaton technque, whch s based on correlaton functons determned from hstorcal ar concentraton data was added to the developed model whch mproved ther result. q R h (6) e c( x, x,0, t) exp X exp E 3 T E T ( ) ( h nh ) ( h ) exp e exp e n nh (7) 3 3 Where and 3 = varances of the Gaussan concentraton dstrbutons R ( x (8) Ut) X U = average veloct n the horzontal x X = horzontal drecton normal to x n = number of reflectons Sabapath [5] studed ar qualt outcomes of fuel qualt and vehcular technolog n an Indan ct, where fuel qualt and vehcular technolog measures were mplemented. The ar qualt was montored usng hgh volume gravmetrc samples at dfferent locatons wthn the ct. Monthl average concentratons for the four pollutants SO, NOx, SPM and RSPM were collated for four dfferent tme perods for a longtudnal assessment of whether there have been an ar qualt mprovements resultng from the vehcle technolog and fuel qualt (5) Volume Issue 9, September 03 polces mplemented n the ct. A one-wa sngle-factor analss of varance was carred out usng the monthl average concentratons for the four pollutants n each tme perod to test the hpothess that polluton levels n each tme perod are lower than the precedng tme perods. Exceedance above the annual standards was also analzed. Results from the stud showed substantal mprovement n ar qualt (Mean monthl average S0 concentraton reduced from 43. μgm -3 to 7.5 μgm -3 ) over the ct n spte of a 50% ncreased traffc loads. Trabass [6] studed operatonal models that use solutons of the advecton-dffuson equaton based on the assumptons of homogeneous wnd and edd dffusvt coeffcents (equaton 9). He ntroduced a new parameterzaton for the model usng a soluton that accepts wnd and edd dffusvt profles descrbed b power functons of heght. The performance of the model wth the new parameterzaton was assessed usng expermental data. c C ( x,, z ) e x p (9) C = cross-wnd ntegrated concentratons, = cross-wnd dstance = lateral dffuson parameter. If varatons n the wnd veloct (u) and exchange coeffcent (Kz) wth heght (z) are u u ( z z ) (0) K z K (( z z ) Z s the heght where u and K are evaluated and equaton (9) can be wrtten as p q zh ( ) z uz ( z h ) uz ( zh) c () exp Iv Kx Kx Kx Where x = along-wnd drecton, = source emsson, h = source effectve heght., v ( ) /, p ( ) /, q Sportsse [7] dd a comparatve stud of the box model and the Euleran model n hs and consdered a monodmensonal Euleran model b neglectng wnd veloct, whch s the practcal stuaton for peaks of polluton (no wnd, no transport far from source), assumng constant mxng heght and dffusve coeffcent wth tme, the equaton can be wrtten as: c c () K ( z ) ( c ) t z z Wth the followng boundar condtons: c, at z = H, c K o K v at z = 0 depc E () t z z and a Box model based on the assumpton of a perfectl strred reactor. dc (3) ( ct ( t), t S( t) ( E( t) vdepc dt H () t H (t) = mxng heght. He derved an error band for the devaton assocated wth the speces defned b e () t c () t c () t Paper ID: e () t

3 Internatonal Journal of Scence and Research (IJSR), Inda Onlne ISSN: Where c and c denote the solutons of the box model and the average of the Euleran soluton. Hs analss showed the dependence of the error nduced b the Box model on the fluctuaton of concentraton. Relatve error at a fxed tme to compare both models, Eqn. 4 n c ( t ) c ( t ) ERR( t) (4) n c ( t ) Result obtaned showed that errors assocated wth the Box model grew wth tme and the were much bgger than the usual threshold of % advocated n ar polluton model. Svacoumar et al [8] modeled an ndustral complex to determne the mpact of NOx emsson resultng from varous ar polluton sources wthn the complex vz ndustres, vehcles, etc usng Gaussan dsperson model, ther model consderatons ncluded: Producton capactes, Raw materals utlzed n the ndustres wthn the complex, Fuel consumpton, Stack emsson characterstcs, Vehcular count surve and Meteorologcal data collected usng wnd montorng nstrument. Model result gave 53% as the ndustral contrbuton of NOx. Model performance evaluated usng statstcal analss showed good agreement between the two wth 68% accurac. Ando [9] proposed a novel black box approach for ar polluton modelng. The target of ths approach s predcton, on the bass of meteorologcal forecasts, of the ar polluton concentraton as a functon of the expected causes. The model s expected to forecast as well as estmate ar pollutants on the bass of the consdered causes so that t can be appled n emsson control scheme to determne sutable control measures. 3. Analss of Important Research Contrbuton ma not alwas be the best model to appl because of a number of drawbacks, the major one beng the lnear summaton of the model whch s the bass of ts smplct, but t s reasonable to assume that a lot of naccuraces assocates wth ths model s as a result of ths assumpton, because most processes occurrng n the atmospheres durng the release and dsperson of pollutant are not lnearl related. Also, Gaussan-plume models assume pollutant s transported n a straght lne nstantl from the source to receptors who ma be several hours or more n transport tme awa from the source, dsregardng wnd speed. Ths mples that Gaussan plume models cannot account for causalt effects, especall f the receptor s at an apprecable dstance awa from the source. Gaussanplume models cannot handle low wnd speed or calm condtons effectvel due to the nverse wnd speed dependence of the stead-state plume equaton. Unfortunatel worst-case ar polluton effects are recorded under these condtons. Terran effect was poorl consdered n the Gaussan plume model hence n moderate terran areas, Gaussan models tpcall overestmate terran mpngement effects durng stable condtons. Wth the stead-state assumpton n the Gaussan models, t s assumed that the atmosphere s unform across the entre arshed, so that transport and dsperson condtons are unchanged for the duraton of tme t takes the pollutant to reach the receptor. Ths however hardl occurs n the atmosphere. A lot of atmospherc processes and features produce nonhomogenetes n the atmospherc boundar laer that can affect pollutant transport and dsperson. 3. Box Models Several models exst for modelng ar polluton and ar qualt n an atmosphere, but models commonl used, whch were also used n the artcles beng revewed are: Gaussan plume models; Box models; Euleran models and Lagrangan models among others. 3. Gaussan Plume Models Gaussan plume models are most often used for predctng the dsperson of contnuous, buoant ar polluton plumes orgnatng from ground-level or elevated sources. It assumes that the ar pollutant dsperson has a Gaussan dstrbuton, meanng that the pollutant dstrbuton has a normal probablt dstrbuton. In the Gaussan plume model, the atmosphere s assumed stagnant and homogeneous, and the downwnd concentratons of a pollutant along the vertcal and crosswnd dmenson are assumed to be normall dstrbuted. Also the probablt dstrbuton of wnd veloct s assumed ndependent of tme and locaton. The Gaussan plume model shows reasonable results and requres relatvel smple nput nformaton whch nclude wnd speed, wnd drecton, the dsperson parameters σ, σz, and dstance from sources. The Gaussan-plume models are wdel used, well understood, eas to appl, wth assumptons, errors and uncertantes that are generall well understood. However t Volume Issue 9, September 03 Box models are wdel used n ar polluton modelng; the provde smple descrpton of ar qualt n urban areas, especall where emssons data are onl avalable on a farl coarse grd, and also produce acceptable results when appled n modelng. Under sutable condtons, the box model offers the possblt of enablng an accurate emssons concentratons relatonshp to be developed wth mnmum mathematcal complext. However, as an emprcal model, t should be valdated before beng adopted n a specfc area [7]. Also, the box model s so specfc that a model developed n one area cannot be mplemented on another area wthout valdaton. Thus even though the box model s useful especall because of low computer cost, ts ablt to accuratel predct dsperson of ar pollutants over an arshed s lmted because of ts numerous smplfng assumptons. 3.3 Euleran Model The Euleran model, often called the numercal approach, conssts of usng the contnut equaton of mathematcal phscs to develop a descrpton of the phscal and chemcal processes that govern the relatons between emssons and concentratons. Though the Euleran approach provdes detaled representaton of dsperson, t can be extremel complcated, demands a large amount of nput data, and s computatonall ntensve. The Euleran Paper ID:

4 Internatonal Journal of Scence and Research (IJSR), Inda Onlne ISSN: approach has n prncple fundamental advantages especall n the descrpton of phscal processes over the Gaussan approach though t cannot readl be mplemented n urban areas and s also dffcult to appl n complex dsperson geometr. It has also been observed over tme that the complex modelng approaches do not provde a substantal mprovement n results. Ths s one of the reasons the Gaussan dsperson model s wdel used model. 3.4 Lagrangan Model The Lagrangan model s based on a probablstc descrpton of the moton of pollutant partcles n the atmosphere to derve expressons for pollutant concentratons. It allows accurate modelng of the spatal varaton of turbulent dffusvt. Lagrangan model has the advantage of more accurate calculaton of the advecton and dsperson from varous sources and allow more complete characterzaton of the mpact of turbulence on the transport of ar pollutants. Tpcal Lagrangan model treat the dsperson of plumes better than Euleran models but the chemcal nteractons nduced b the mxng of ntersectng plumes s gnored. The most serous drawback of Lagrangan model s ts excessve demand of computng tme even wth toda's powerful computers, t s stll extremel tresome to use due to the large amount of computng data requred, and ths makes the model unattractve for man practcal applcatons, such as assessment of ar polluton n a long-term. Gualter and Tartagla [0] developed a model to estmate the concentraton of NOx n a street canon, the model whch s based on CORINAIR emsson nventor software, consdered traffc data, meteorologcal data, ste and road topograph. The authors dd a good job of settng up a smplfed street canon model to account for the behavor of tpcal reactve pollutant emtted b vehcles, but the model s so smplfed that the accurac s ver low. For nstance, the model onl consdered NOx as comng from vehcles alone. A model that consdered the concentratons of NOx usng a combnaton of (a plume model) drect contrbuton from vehcles and (a box model) the recrculatng part of the pollutants n the street, would have gven a more accurate representaton of the actual concentraton of NOx n the street because the most characterstc feature of the street canon wnd flow s the formaton of wnd vortex, such that the drecton of the wnd at street level s opposte to the flow above. Ths flow condton usuall leads to a stuaton n whch the pollutants emtted from traffc n the street are prmarl transported towards the upwnd buldng, whle the downwnd sde s prmarl exposed to background polluton and polluton that has recrculated n the street. In general, there s alwas crculaton of wnd n the street, whch when captured b a model ncreases the accurac of the model, even though the model complext ncreases. A major plus to the model s takng nto account wnd speed condtons, because n traffc nduced turbulence, an mportant feature s the ablt to predct polluton concentratons at low wnd speed condtons, because most severe polluton epsode often occur at such tmes. Even though NOx formaton tme s ver small, tme of exchange wth the background ar s apprecable and should have been consdered n the model; takng nto account the resdence Volume Issue 9, September 03 tme of pollutants n the street. Urban background O 3 and NO pla mportant role n NO formaton n the street ar. Ths model also dd not consder advecton and convecton whch are major means of transport n fluds. Takng those nto account would have greatl mproved the accurac of the model result. Fnall, Parameterzaton of vehcle condtons n the model ether deduced from analss of expermental data or model tests results would have further mproved the model performance. Because t would have represented processes that were not drectl captured b the model, but then fndng a set of consstent parameterzaton for models s not alwas ver eas. 3.5 The KAPPAG models These are non-gaussan models developed b Trabass [6] based on the analtcal solutons of the advecton-dffuson equaton. The can be appled b usng as nputs smple ground level meteorologcal data. Fundamental parameters for the model were all evaluated b ground levelmeasurement. Included n the model also are parameterzaton for wnd and edd dffusvt. The model can handle multples sources and receptors under varng condtons. The model gave good results when compared to the Gaussan model proposed b EPA. Based on avalable nformaton about the model propertes, ts consderatons are ver narrow whch s adequate for specfc crcumstances, but t s unlkel that t can to handle accuratel man of the complextes generall encountered n ar polluton modelng. For nstance all of ts consderaton was at ground level, whch s onl a tn fracton of ar polluton condton. The onl major consderaton of ths model s wnd whch s also another small fracton of meteorologcal condtons, when other condtons lke atmospherc stablt, mxng heght etc are taken nto consderaton; the model wll most lkel break down. To mprove the use of these models, t wll need to take account of what s happenng n the vertcal structure of the atmosphere and thus should consder a certan heght, n addton, more meteorologcal parameters should be consdered because meteorolog s a strong determnant of pollutant dsperson, so a good descrpton of meteorolog s vtal because the effects are cumulatve. Emssons from contamnant are a vtal requrement n modelng. An emsson factor wll be a bg plus to these models. 4. Improvng Ar ualt Montorng Models Ar qualt models are needed to determne the effect of pollutants on human health and the envronment and to protect people from ar polluton b forecastng what ma happen to the qualt of the ar under dfferent potental emssons-control strateges and varng weather condtons. Dsperson models can take man forms lke graphs, tables or formulae. In recent tmes, dsperson models more commonl take the form of computer programs. The process of ar polluton modelng generall contans four stages (data nput, dsperson calculatons, dervng concentratons and analss). The accurac and uncertant of each stage must Paper ID:

5 Internatonal Journal of Scence and Research (IJSR), Inda Onlne ISSN: be known and evaluated to ensure a relable assessment of the sgnfcance of an potental adverse effects. Currentl, the most commonl used dsperson models are stead-state Gaussan-plume models. These are based on mathematcal approxmaton of plume behavor and are the easest models to use. The ncorporate a smple descrpton of the dsperson process, and some fundamental assumptons that do not accuratel reflect realt. Hence wth these lmtatons the Gaussan models can onl provde reasonable results wthn the lmts of the assumpton made even wth the most cautous applcaton. An mprovement n ths area would be the adopton of a more sophstcated and specfc approach to descrbng emsson and dsperson usng the fundamental propertes of the atmosphere rather than relng on general mathematcal approxmaton. Ths wll enable better treatment of dffcult stuatons such as complex terran and long-dstance transport and wll produce more realstc results. Snce the accurac of predcton of ground-level concentratons of contamnants from a dscharge s based on the accurac of nput data, t s essental that at all tme, accurate nput parameters be used for modelng. Factors nfluencng these parameters should be carefull consdered. Models tend to be specfc, so that the choce of an partcular model should take nto consderaton the nature of the envronment beng modeled, because that wll determne whether or not an accurate and realstc result wll be obtaned. Sometmes the sophstcaton of a model pla lttle role n the output from the model f t s not a good representaton of the stuaton requred. Hence results from advanced models should not be automatcall assumed to be better than those ganed from smpler models. Another mportant factor n effectve dsperson modelng s the choce of an approprate model to match the scale of mpact and the sgnfcant potental effects ncludng the senstvt of the recevng envronment. Model valdaton whch ensures that model meet ts ntended requrement s an essental step n modelng that s often overlooked. Model valdaton s ver essental especall when new models are beng tred out. A comparson of the manuals and valdaton studes of the model beng consdered wth exstng ones wll provde the modeler wth some gudance on the accurac of hs result. Modeler must recognze that there are lmtatons to the scope of a model s applcaton and to the accurac of the predctons from each model; ths should alwas be consdered when applng results to real lfe stuatons. Fnall, regulator bodes should advance research to develop, evaluate and mprove ar qualt montorng models for the assessment not just pollutant of nterest but also evaluate the nteractons of the pollutant wth other envronmental contamnants. 5. Concluson References [] C.D. Cooper, and F.C. Alle Ar Polluton Control Engneerng 3 rd Edton, Waveland Press Inc, USA, 00. [] S. Aronca, Estmaton of Bogas Produced b the Landfll of Palermo; Applng a Gaussan Model Waste Management (9) pp , 009. [3] B. Zhao and J. Wu, Modelng Partcle Fate n Ventlaton Sstem Part : Model development Buldng and Envronment; (44), pp , 009. [4] K. M. Mok, A.I. Mranda and K.U. Long A Gaussan Puff Model wth Optmal Interpolaton for Ar Polluton Modelng Assessment Internatonal Journal for Envronment and Polluton, (35) pp., 008. [5] A. Sabapath, Ar ualt Outcomes of Fuel ualt and Vehcular Technolog Improvement n Bangalore ct, Inda Transportaton Research Part D, (3) pp , 008. [6] T. Trabass, Operatonal Advanced Ar Polluton Modelng Pure Appled Geophscs, (60), pp.5 6, 003. [7] B. Sportsse, Box Models versus Euleran Models n Ar Polluton Modelng Atmospherc Envronment (35), pp , 00. [8] R. Svacoumar, A.D. Bhaanarkar, S.K. Goal, S.K. Gadkar and A.L. Aggarwal Ar Polluton Modelng for an Industral Complex and Model Performance Evaluaton Envronmental Polluton, () pp , 00. [9] B. Ando, Models for Ar ualt Management and Assessment IEEE Transactons on Sstems, Man, and Cbernetcs Part C: Applcatons and Revews (30), pp. 3, 000. [0] G. Gualter, and M. Tartagla, A Street Canon Model for Estmatng NOx Concentratons due to Road Traffc Computatonal Mechancs Publcatons, Southampton, ROYAUME-UNI; 997. Authors Profle Ukagwe, Sandra A. s a lecturer n the Department of Chemcal Engneerng, Federal Unverst of Technolog, Owerr, Ngera. She obtaned her B.Eng degree n Chemcal n Engneerng from the same unverst n 00 and M.A.Sc also n Chemcal Engneerng from Rerson Unverst, Toronto, Canada n 00. Her passon s envronmental sustanablt, her research nterests are Bofuels, Ar Polluton and Control. Osoka, Emmanuel C receved the B.Eng and M.Eng degrees n Chemcal Engneerng from Federal Unverst Owerr, Ngera n 000 and 009 respectvel. He s a lecturer wth the Department of Chemcal Engneerng n the same nsttuton, wth nterest n Modelng, Smulaton, Optmzaton and Control. He has several publcatons to hs credt. The stud of ar polluton and ar qualt montorng has evolved from smple box model studes to advanced models that can handle dfferent meteorologcal condtons and complex stuatons, such that the problem of ar polluton even though not et solved s better understood and can be better controlled. Volume Issue 9, September 03 Paper ID: