Study On Prediction And Control Measures Of Motor Vehicle Pollutant Emission

Before1990s, air pollution in China belonged to the mixed pollution of coal smoke,which main pollution source come from industrial emissions exhaust. However, Since1990s,along with the continuous high—speed increase of motor vehicles, motor vehicle emissions(e.g. NOX, CO, SO2) that are mainly exhausted from civil vehicles and motorcycles, havegradually replaced the mixed pollution of coal smoke and become the primary source of airpollution especially in some mega cities. Meanwhile, because people of some mega cities areoverabundant, buildings are exorbitant and roadways are congested, motor vehicle emissionsare hardly diffused. As a result, air pollution consistency in our country is higher than that inmost developed countries. Motor vehicle emissions have further pricked up air pollution andharm for health, brought great pressure to environment and given a challenge to environmentprotection. Although our government is devoted to decrease urban traffic pressure andemissions exhaust from motor vehicles, and has achieved great achievement. Emissionsexhaust basically has increased year by year. Therefore, study on control measures of motorvehicle pollutant emission is meaningful.After introducing the research status on possession of motor vehicles and its emissionscontrol measures at home and abroad, present situation, future developing tendency andcontrol measures of emissions exhaust were studied in the dissertation. Main relative researchresults are as follows:（1）In the late1990s, along with the continuous high—speed increase of motor vehicles,motor vehicle emissions that are mainly exhausted from automobiles, low-speed automotivesand motorcycles, have increased gradually year by year. Motor vehicles pollutant emissionsbecome the primary source of air pollution.（2）Applying ecological footprint（abbreviation, EF）theories and model in discussionof road transportation sustainable development ability, a road transportation EF model is built.The EF model mainly includes road transportation EF demand mainly composed byconstruction land EF demand as well as fossil energy land EF demand and road transportationregional ecological bearing capacity. The dissertation explains the use process of the model by calculation with nationalpossession of road vehicles. The calculation results shows that EF of our nation roadtransportation are all in ecological deficit since2000, which means that road transportation EFhas already meet the requirements of sustainable development and has the trend ofprogressive deterioration. As a result, energy consumption and emissions exhaust fromvehicles must be paid much attention.（3）Applying grey system theory, the dissertation has presented a motor vehiclespossession GM（1,1）predicting model x (1)(k+1)=77273.6e0.137400721k67000according tooriginal data from2005to2009. Then it used residue error test, concentration factordeviation test, relational coefficient test and after-test residue checking to test the correctnessof the GM（1,1） model. The results show that the accuracy of GM（1,1）model meet therequirements of forecasting precision of grey system. The possession of motor vehicles innext few years is forecasted correctly.（4）Applying improved trial method and building linear programming equation,optimum method to determine smoothing coefficient a is gained. Then smoothingcoefficients of motor vehicles total prediction as well as automobile prediction andmotorcycle prediction have been respectively achieved, which are α=0.87, α=1andα=0.73. Choosing process of smoothing coefficient a shows that improved trial methodnot only can obviously reduce calculation workload of it, but also its result is very accurate.（5）Applying combination forecasting method and according to metrics variance cova-riance, weighted coefficient of grey prediction result and double exponential smoothingprediction result of motor vehicles total prediction is separately w1=0.87, w2=0.13. Thena combination forecasting modelfc=0.87f1+0.13f2is built based on the result of weightedcoefficient. The total possession of motor vehicles in next few years is forecasted correctly. Possession of various types of motor vehicles from2010to2015is also obtained in thesimilar method.（6）Applying linear regression theory to analyze the emission exhaust data from2005to2009, a linear regression model between possession and its emissions has been constructedY t=4214.947+0.0545Xt（where,X tis the value of independent variable in t phase, Y isthe predictive value in t phase）, which correlation coefficient equals to0.98. Predictivevalue of emissions from2010to2015is gained through the linear regression model.（7）CO, HC, NOXand PM is chosen as the main pollution factors. A road trafficenvironment capacity model is built based on improved single box model. Model parameterssuch as mixed layer height, speed of dry deposition and wet deposition of motor emissions, aswell as chemical conversion are determined. So, objective year’s road traffic environmentcapacity is gained.（8）The amount of motor vehicle exhaust is usually determined by vehicle’s annualaverage driving mileage, emission factor of very type vehicle and possession of motorvehicles. Therefore, some measures are put forward in the dissertation to control and decreasemotor NOXaccording to these three factors.