The Research of AQI Index Changing Regularity Mainly in Tianjin Ziyu Guo

Transcription

1 nd Intenational Confeene on Eduation Tehnology, Management and Humanities Siene (ETMHS 06 The Reseah of AQI Index Changing Regulaity Mainly in Tianjin Ziyu Guo Shool of Institute of Eletial and Eletoni Engineeing, Noth China Eleti Powe Univesity, Baoding07000, China Keywods:AQI, Guass model, Empiial fomula, Tempeatue Abstat. In eent yeas, the poblem of haze is beoming moe and moe seious in Beijing, Tianjin and Hebei povine.based on the ai quality data of Januay and Mah 05, the autho has managed to investigate the hanging tend of AQI index in Beijing, Tianjin and Hebei by applying a mathematial model. Speial attention was paid to find out the elationship between Tianjin and the pollutants in its suounding aea. A mathematial model egading the fatos affet AQI index was built. As the same time, the autho also tied to investigate the inteelationship of AQI index among diffeent aeas.. Intodution Fo the fist poblem, the autho was inspied by the Gauss model and found that the fitting degee of the existing data of the Fou ode Gauss funtion was vey high. In ode fo futhe investigation, the autho divide the image of AQI index in the same aea in one day into the sum of fou Gauss funtion,and then, put them in the same axis to show fo us.by ompaing and ontasting, it was found that tempeatue affeted all thee Gauss Funtion. As a esult, this eseah believed the Guass model of the aea s AQI is mainly affeted by tempeatue. Fo the foth unetain peak, this eseah pape thought it was due to the unetain fatos like wind powe and ain et. In addition, the effets of its suounding aeas wee not negligible. Fo the seond question, spss softwae was used to fit the daily AQI index and the AQI index of evey hou between diffeent ities. In ode to eliminate the thid paty effet, the autho used the Patial oelation analysis and onfim the fist question s onlusion of the inteelationships among aea s AQI. Though the linea analysis of patial oelation oeffiient and distane by using SPSS between the ental ity and the suounding ities, we geneally found that the elationship between distane and patial oelation oeffiient is invesely popotional. If we use f ( to expess the oelation between the ities, we will get f ( ( is the exponent. of. Then, this eseah has done a oelation analysis between an aea s vaious meteoologial onditions and AQI by using spss. The autho has found that AQI has lose elationship between the highest tempeatue and lowest tempeatue. Based on this, when exluding the effets of lage wind speed and exteme weathes, this eseah believed a quantitative expession of the distane and tempeatue an be used to desibe the funtional elationship of diffeent aeas.. Model. The AQI hanging egulation in an aea based on Gauss model Based on the pevious modeling pepaation, the existing The Gauss diffusion model desibed the distibution of ontaminant onentation in spae, the detailed fomula is: C ( x, y, z, H y (z H exp{ [ ]} y z y z Q In ode to obtain the fomula of the onentation distibution along x-axis, we made Z=0 Y=0 and found that 06. The authos - Published by Atlantis Pess 635

2 above: C----the pollutant onentations of evey point in spae(x,y,z Q----the stength of soue,emissions off pollutants in unit of time ----aveage speed of wind y, z ----pollutantt diffusion oeffiient Simplyfing the fomula, the funtions f off pollutant onentationsan hanging in spae an be obtained xb ( C( x a e Based on analysis, this pollutant may be due to many aspets. Fistly it was possibly aused by the dishage fom an aea. In addition, it may also due to the weathe onditions like wind o ainfall o suounding aea s effet made AQI flutuate fo etainn time. In this eseah, we all the flutuation of AQI gaph in the aea aused by pollutantt Gauss impulse. Afte doing moe eseah, itt was foundd that we an use Gauss funtionn to best-fitt the satte with many peaks. And a egional AQI uve is usually multimodal, using Gauss funtion fitting ould ahieve bette esult. Fo the espetive funtional gaphh of the AQI satte points fo diffeent timing in one day, we an divide it into a sum of some Gauss funtions. By doing so we ould math the pevious analysis of impat of the aea fom pollutant. In addition, we ould esolve uves of daily AQI to obtain some fatos whih affet AQI signifiantly. Though fitting it was found that Fou ode Gausss fitting ould ahieve elatively good g esult. The fitting funtion is shown below: tb y( t a e Typial fitting effet is as follows Q C( x,0,0, H exp( a e tb y z a 3 e tb 3 3 H a 4 z e tb 4 4 Fig. Januay 5th in i Tianjin Fig. Mah 6th inn Tianjin Inspied by this, this pape divided the AQI hanging gaph of one aea in one day into summation of the 4 Gauss funtion and shown them in the same axis. In ode to have a bette epesentativeness, some andom days off Shijiazhuang and Tianjin T weee seleted and gaph poessed. The 4 pitues below wee gaphs fom 3 d Mah of o Shijiazhuang, 4 th Mah, 3 d Mah and nd Januay of Tianjin espetively. Based on the fou pitue above, we ouldd know thatt an aea s AQI A hanging tend in one day ae deided by fou fatos. Dawn, mid-noon and evening would all podue one Gauss impulse. The positions of the peak value of these 3 Gausss impulse emain the same on thee time line. They ae at 4 o lok, o lok and o lok. Wheeas the gauss funtion aused by othe fatos(wind, ain et. had diffeent peak value position evey day. Afte doing moee eseah, we ould know that the effets of dawn, mid-noon and evening wee pobably due to tempeatue. The flutuations of tempeatue aused the pollutant to Synthesis and deompose and then affet the intensity i of pollutant in the ai. Besides this, aoding to Toble's Fist Law, the effets among diffeent aeas 636

3 ae not negligible. Hene, we ould know that fo the hanging of AQI in onee day, tempeatue was the main fato and its effet was also moe peditable and stable. The effet fom suoundings aeas weee also ompaetivly impotant. Wheeas wind and ains wee w diffeent evey day and thei effets wee diffeent evey day. Based on the above disussion, using Gauss model to analysis one aea s ai quality index, this pape thought if we exlude the effet of wind powe and exteme weathe, the intenal envionment that impat AQI is pobably tempeatue. Howeve, extenal envionmental fatos fom suounding aeas may also affet it. Fig.3 Mah 3 th in Tianjin Fig.4 Januay nd in Tianjin. The AQI elationships among aeas Pevious by using Gauss fitting, this pape onluded that one aea s hanging tend weee onluded by tempeatue and suounding aeas. In ode to analysis how aeas inte-affet by SPSSS in Januay, Mah, as the epesentative of the elationship between the dailyy AQI. And andomly hose one hou as unit, ities s AQI elationship and seletedd 8 ities whih has the most signifiant oelation. We knew that the pollutant fom eah ity might affet eah othe o it ould be easily affeted by thid paty pollutant. In ode to obtain the inteelationship between two ities moe auately, we must exlude the effet fom othe ities and puely analysis the two ities net oelation. Hene we use spss to find the 8 ities patial oelation oeffiient espetively. eah othe, this eseah hose Tianjinn and Hebei s ities as the objets. We espetivelyanalyze 637

4 Although some aeas AQI hange has high oelation, it was affeted a geatly by pollutants fom othe aeas. We wee not hundedd peent sue these two ities must inte-affet eah othe. In ode to exludee the effetss of pollutants fom othe ities, this t pape hose 7 pais of ities patial oelation oeffiient as eseah objetives. Table 7 pais of ities patial oelationn oeffiientt City Distane( (km Patial oelation oeffiient City Distane( (km Patial oelation oeffiient Tianjin-Shijiazhuang Tianjin-Cangzhou Tianjin-Tangshan Tianjin-Chengde Tianjin-Baoding Tianjin-HandaT an Tianjin-Langfang Afte analysis we found thatt thee wass an invese elationship between the oelation and distane. We let f ( be the oelationn among ities, then f (, in whih is the exponent of distane. In ode to the magnitude of the, this pape use MATLAB uve fitting toolbox, fitting fom 0. to 3.We foundd that when is.5,the fitting effet is the best. The inte-effett between aeas and the distane has an invese elationship. When a=0. and a=.0, the fitting f effett is as follows: Fig.5 a=0. R-squae= Fig.6.a=.0 R-squae= When a is diffeent,we an get diffeent Reliability. Table The diffeent eliability of diffeent a R squae R squae Afte obtaining the oelations fo eahh pai of aeas, this pape p wouldd investigate how the weathe fatos affet a aea s aveage AQI.. Afte doing moe eseah, an aea s AQI was affeted by the hignest tempeatue, lowest tempeatue,wind speed, pessue, humidity, ainfalll and loud density. Based on the above Gauss fitting ananlysis, tempeatue iss pobably the main fato. Using the SPSS to ananlysis, Tianjin s Januay aveage AQII fo hignest tempeatue, lowest 638

5 tempeatue and tempeatue diffeene wee Tianjin s Mah aveage AQI fo hignest tempeatue, lowest tempeatue and tempeatue diffeene wee the oelation was quite lage. This meant AQI was affeted lagely by highest tempeatue and lowest tempeatue but not tempeatue diffeene. This is beause the tempeatue will affet moleules speed and pollutant s diffusion speed. This also math the onlusion dawn fom Gauss fitting we disussed above. The oelation oeffiient of Tianjin s Januay and Mah aveage AQI and wind speed wee 0.7 and 0.55 espetively. Although oelation oeffiient was not vey lage, it still has some effet. At the same time, based on the analysis esult, the monthly aveage AQI and othe weathe s oelation oeffiient flutuate. We ould not onfim whethe they have lea elationship. Howeve, it was wothy to mention that beause Tianjin s Januay and Mah has little ainfall hene we ould not analyze whethe monthly aveage AQI was affeted by ainfall. Based on the above analysis, daily aveage AQI was mainly affeted by highest tempeatue and lowest tempeatue. Howeve, it was weake elationship with wind speed and othe fatos. We an assume when the wind powe is negligible, daily aveage AQI was only elated to highest tempeatue and lowest tempeatue. k y y F( Tmax, Tmin,( 0 i i 3. Summay. the effet among aeas wee elated to distane. Lage distane, smalle effet and smalle distane will lead to lage effet.. when the distane between aeas is extemely small. The inte-effet has a negative oelation with distane. When the distane is vey lage, the effet will beome invesely popotional and even beome squae invese elationship. The deeasing tend beame flatte. 3. An aea was not only affeted by its suounding aea, but also affeted by its own envionment. When the wind powe was not extemely stong o it was unde extemely bad weathe, the main intenal envionmental fato was tempeatue. At about 4 am and 0pm a Gauss impulse would be podued and made AQI inease hene deease the ai quality onsistently. Afte doing moe eseah we ould know the eason was beause the ogani pollutant podued by atmosphee hemial eation will gow at an amazing speed at night. This made the ai quality duing night vey bad. Usually duing night, ealy moning and sunset an invesion laye would be podued easily. This aused the gound tempeatue to be lowe than the tempeatue in the sky and pollutants in the ai would not be able to diffuse. This would math the analysis of effet about moning and night based on Gauss model.gauss fitting out at noon will geneate a Gaussian impulse, and this eseah was not able to find a easonable explanation. Howeve, this pape made an assumption that the umulative effet of pollution soue in the moning. The exat eason is waiting fo futhe eseah. Refeenes []Jiang Hongbin, Deng Shunxi, Guo Qingni, et al. Based on a modified Gauss model eseah of diffusion afte dangeous gas shot time leaked.[j]. Gansu Siene, 03,9(:4-45. []Ding Feng. The exploe of Pevention and teatment dietions in Beijing,Tianjin and Hebei povine.[j]. View, 04,: [3]Dong He. The appliation of patial poblems about PM.5 in the ai of Guass smoke and ain model.[n]. The leaned jounal of eight one Hei Longjiang agiultue univesity 04,6(3: