Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

Vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.

Real-world vehicle emission factors in Chinese metropolis city—Beijing

The dynamometer tests with different driving cycles and the real-world tests are presented. Results indicated the pollutants emission factors and fuel consumption factor with ECE15+EUDC driving cycle usually take the lowest value and with real world driving cycle occur the highest value, and different driving cycles will lead to significantly different vehicle emission factors with the same vehicle. Relative to the ECE15+EUDC driving cycle, the increasing rate of pollutant emission factors of CO, NOx and HC are -0.42—2.99, -0.32 —0.81 and -0.11—11 with FTP75 testing, 0.11—1.29, -0.77—0.64 and 0.47—10.50 with Beijing 1997 testing and 0.25—1.83, 0.09—0.75 and -0.58—1.50 with real world testing. Compared to the carburetor vehicles, the retrofit and MPI+TWC vehicles' pollution emission factors decrease with different degree. The retrofit vehicle(Santana) will reduce 4.44%—58.44% CO, -4.95%—36.79% NOx, -32.32%—33.89% HC, and -9.39%—14.29% fuel consumption, and especially that the MPI+TWC vehicle will decrease CO by 82.48%—91.76%, NOx by 44.87%—92.79%, HC by 90.00%—93.89% and fuel consumption by 5.44%—10.55%. Vehicles can cause pollution at a very high rate when operated in high power modes; however, they may not often operate in these high power modes. In analyzing vehicle emissions, it describes the fraction of time that vehicles operate in various power modes. In Beijing, vehicles spend 90% of their operation in low power modes or decelerating.

A remote sensing system of vehicle emissions based on tunable diode laser technology

As being an effective real-time method of monitoring vehicle emissions on-road, a remote sensing system based on the tunable diode laser （TDL） technology was presented, and the key technologies were discussed. A field test in Guangzhou（Guangdong, China） was performed and was found that the factors, such as slope, instantaneous speed and acceleration, had significant influence on the detectable rate of the system. Based on the results, the proposal choice of testing site was presented.

Projection pursuit model of vehicle emission on air pollution at intersections based on the improved bat algorithm

The projection pursuit model is used to study the assessment of air pollution caused by vehicle emissions at intersections. Based on the analysis of the characteristics and regularities of vehicle emissions at intersections, a vehicle emission model based on projection pursuit is established, and the bat algorithm is used to solve the optimization function. The research results show that the projection pursuit model can not only measure the air pollution of vehicle emissions at intersections, but also effectively evaluate the level of vehicle exhaust emissions at intersections. Taking the air pollution caused by vehicle emissions at intersections as the research object and considering the influence factors of vehicle emissions on air pollution comprehensively, the evaluation index system of vehicle emissions at intersections on air pollution is constructed. Based on large data analysis, a prediction model of air pollution caused by vehicle emissions at intersections is constructed, and an improved bat algorithm is used to realize the assessment process. The application results show that the prediction model of vehicle emissions at intersections can define the degree of air pollution caused by vehicle emissions, and it has good guiding significance and practical value for solving the problem of air pollution caused by vehicle emissions.

Ammonia in urban atmosphere can be substantially reduced by vehicle emission control:A case study in Shanghai, China

To investigate the impact of emission controls on ammonia(NH_(3)) pollution in urban atmosphere, observation on NH_(3)(1 hr interval) was performed in Shanghai before, during and after the 2019 China International Import Expo (CIIE) event, along with measurements on inorganic ions, organic tracers and stable nitrogen isotope compositions of ammonium in PM_(2.5). NH_(3)during the CIIE period was 6.5±1.0μg/m^(3), which is 41% and 32% lower than that before and after the event, respectively. Such a decrease was largely ascribed to the emission controls in nonagricultural sources, of which contribution for measured NH_(3)in control phase abated by ~20% compared to that during uncontrol period. Molecular compositions of PAHs and hopanes further suggested a dominant role of the reduced vehicle emissions in the urban NH_(3)abatement during the CIIE period. Our results revealed that vehicle exhaust emission control is an effective way to mitigate NH_(3)pollution and improve air quality in Chinese urban areas.

Temporal-spatial dynamic characteristics of vehicle emissions on intercity roads in Guangdong Province based on vehicle identity detection data

Estimating intercity vehicle emissions precisely would benefit collaborative control in multiple cities.Considering the variability of emissions caused by vehicles,roads,and traffic,the 24-hour change characteristics of air pollutants(CO,HC,NO_(X),PM_(2.5))on the intercity road network of Guangdong Province by vehicle categories and road links were revealed based on vehicle identity detection data in real-life traffic for each hour in July 2018.The results showed that the spatial diversity of emissions caused by the unbalanced economywas obvious.The vehicle emissions in the Pearl River Delta region(PRD)with a higher economic level were approximately 1–2 times those in the non-Pearl RiverDelta region(non-PRD).Provincial roads with high loads became potential sources of high emissions.Therefore,emission control policies must emphasize the PRD and key roads by travel guidance to achieve greater reduction.Gasoline passenger cars with a large proportion of traffic dominated morning and evening peaks in the 24-hour period and were the dominant contributors to CO and HC emissions,contributing more than 50%in the daytime(7:00–23:00)and higher than 26%at night(0:00–6:00).Diesel trucks made up 10%of traffic,but were the dominant player at night,contributed 50%–90%to NO_(X) and PM_(2.5) emissions,with amarked 24-hour change rule of more than 80%at night(23:00–5:00)and less than 60%during daytime.Therefore,targeted control measures by time-section should be set up on collaborative control.These findings provide time-varying decision support for variable vehicle emission control on a large scale.

Characterization of on-road CO, HC and NO emissions for petrol vehicle fleet in China city

Vehicle emissions are a major source of air pollution in urban areas. The impact on urban air quality could be reduced if the trends of vehicle emissions are well understood. In the present study, the real-world emissions of vehicles were measured using a remote sensing system at five sites in Hangzhou, China from February 2004 to August 2005. More than 48000 valid gasoline powered vehicle emissions of carbon monoxide （CO）, hydrocarbons （HC） and nitrogen oxide （NO） were measured. The results show that petrol vehicle fleet in Hangzhou has considerably high CO emissions, with the average emission concentration of 2.71 %±0.02%, while HC and NO emissions are relatively lower, with the average emission concentration of （153.72±1.16）×10-6 and （233.53±1.80）×10-6, respectively. Quintile analysis of both average emission concentration and total amount emissions by model year suggests that in-use emission differences between well maintained and badly maintained vehicles are larger than the age-dependent deterioration of emissions. In addition, relatively new high polluting vehicles are the greatest contributors to fleet emissions with, for example, 46.55% of carbon monoxide fleet emissions being produced by the top quintile high emitting vehicles from model years 2000-2004. Therefore, fleet emissions could be significantly reduced if new highly polluting vehicles were subject to effective emissions testing followed by appropriate remedial action.

Rural vehicle emission as an important driver for the variations of summertime tropospheric ozone in the Beijing-Tianjin-Hebei region during 2014-2019

Tropospheric ozone(O_(3))pollution is increasing in the Beijing-Tianjin-Hebei(BTH)region despite a significant decline in atmospheric fine aerosol particles(PM_(2.5))in recent years.However,the intrinsic reason for the elevation of the regional O_(3)is still unclear.In this study,we analyzed the spatio-temporal variations of tropospheric O_(3)and relevant pollutants(PM_(2.5),NO_(2),and CO)in the BTH region based on monitoring data from the China Ministry of Ecology and Environment during the period of 2014-2019.The results showed that summertime O_(3)concentrations were constant in Beijing(BJ,0.06μg/(m^(3)·year))but increased significantly in Tianjin(TJ,9.09μg/(m^(3)·year))and Hebei(HB,6.06μg/(m3·year)).Distinct O_(3)trends between Beijing and other cities in BTH could not be attributed to the significant decrease in PM_(2.5)(from-5.08 to-6.32μg/(m3·year))and CO(from-0.053 to-0.090 mg/(m^(3)·year))because their decreasing rates were approximately the same in all the cities.The relatively stable O_(3)concentrations during the investigating period in BJ may be attributed to a faster decreasing rate of NO_(2)(BJ:-2.55μg/(m^(3)·year);TJ:-1.16μg/(m^(3)·year);HB:-1.34μg/(m3·year)),indicating that the continued reduction of NOx will be an effective mitigation strategy for reducing regional O_(3)pollution.Significant positive correlations were found between daily maximum8 hr average(MDA8)O_(3)concentrations and vehicle population and highway freight transportation in HB.Therefore,we speculate that the increase in rural NO_(x)emissions due to the increase in vehicle emissions in the vast rural areas around HB greatly accelerates regional O_(3)formation,accounting for the significant increasing trends of O_(3)in HB.

Development of database of real-world diesel vehicle emission factors for China

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT（Computer Programmer to calculate Emissions from Road Transport） and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5（Highway Vehicle Particulate Emission Modeling Software） models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent,which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models.

City-specific vehicle emission control strategies to achieve stringent emission reduction targets in China's Yangtze River Delta region

The Yangtze River Delta（YRD） region is one of the most prosperous and densely populated regions in China and is facing tremendous pressure to mitigate vehicle emissions and improve air quality.Our assessment has revealed that mitigating vehicle emissions of NOx would be more difficult than reducing the emissions of other major vehicular pollutants（e.g.,CO,HC and PM_（2.5）） in the YRD region.Even in Shanghai,where the emission control implemented are more stringent than in Jiangsu and Zhejiang,we observed little to no reduction in NOx emissions from 2000 to 2010.Emission-reduction targets for HC,NOx and PM_（2.5） are determined using a response surface modeling tool for better air quality.We design city-specific emission control strategies for three vehicle-populated cities in the YRD region：Shanghai and Nanjing and Wuxi in Jiangsu.Our results indicate that even if stringent emission control consisting of the Euro 6/VI standards,the limitation of vehicle population and usage,and the scrappage of older vehicles is applied,Nanjing and Wuxi will not be able to meet the NOx emissions target by 2020.Therefore,additional control measures are proposed for Nanjing and Wuxi to further mitigate NOx emissions from heavy-duty diesel vehicles.

Modeling and predicting low-speed vehicle emissions as a function of driving kinematics

An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system （PEMS） under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics （speed and acceleration） of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data.

MODELING THE CONGESTION COST AND VEHICLE EMISSION WITHIN MULTIMODAL TRAFFIC NETWORK UNDER THE CONDITION OF EQUILIBRIUM

Traditional system optimization models for traffic network focus on the treatment of congestion, which usually have an objective of minimizing the total travel time. However, the negative externality of congestion, such as environment pollution, is neglected in most cases. Such models fall short in taking Greenhouse Gas （GHG） emissions and its impact on climate change into consideration. In this paper, a social-cost based system optimization （SO） model is proposed for the multimodal traffic network considering both traffic congestion and corresponding vehicle emission. Firstly, a variation inequality model is developed to formulate the equilibrium problem for such network based on the analysis of travelers＇ combined choices. Secondly, the computational models of traffic congestion and vehicle emission of whole multimodal network are proposed based on the equilibrium link-flows and the corresponding travel times. A bi-level programming model, in which the social-cost based SO model is treated as the upper-level problem and the combined equilibrium model is processed as the lower-level problem, is then presented with its solution algorithm. Finally, the proposed models are illustrated through a simple numerical example. The study results confirm and support the idea of giving the priority to the development of urban public transport, which is an effective way to achieve a sustainable urban transportation.

Emission Patterns under Alternative Congestion and Motor Vehicle Pollution Mitigation Policies in Shanghai

As a megacity with thriving economy, Shanghai is experiencing rapid motorisation and confronted with traffic congestion problems despite its low car ownership. It is of value to look into the policies on emission control of motor vehicle and congestion reduction in such a city to explore how to reconcile mobility enhancement with the environment. Results of a dynamic simulation displayed time paths of emissions from motor vehicles in Shanghai over the period from 2000 to 2020. The simulation results showed that early policies on emission control of motor vehicle could bring about far-reaching effects on emission reduc- tion, and take advantage of available low-polluting technologies and technical innovation over time. Travel demand management would play an important role in curbing congestion and reducing motor vehicle pollution by calming down car ownership rise and deterring inefficient trips as well as reducing fuel waste caused by congestion.

Measurement of Emissions from Passenger-Picking-up Vehicles at Airport Terminals

Rather than parking at nearby hourly parking lots, many passenger-picking-up vehicles prefer to idle at terminals and/or drive cycling around terminal facilities. As a result, extra vehicle emissions may be produced in an airport area. Even though there are limited studies on such emissions at airports, these estimations were normally based on the date emission models, which might cause bias in emission estimations. This paper proposes an approach to employ the floating car method and Global Positioning System （GPS） to record speeds and acceleration rates of idling and cycling vehicles at airport terminals. The tests were conducted under different time periods and traffic demands with different waiting time. The speeds and acceleration rates are synthesized to yield Vehicle Specific Power＇s （VSP） and Operational Mode （OM） distributions. Utilizing the Environmental Protection Agency （EPA） emission estimation model Motor Vehicle Emission Simulator （MOVES）, pollutants and green house gas emission indexes （e.g. NOx, CO, CO2 and HC） and fuel consumptions can be easily estimated. As an illustration of the proposed approach, the research team collected GPS data at a terminal in Houston William Hobby Airport （HOU）, and calculated the VSP distributions and OM distributions. Emissions of passenger-picking-up vehicles around these congested airport terminals.

Comparison of the Mutagenicity of Exhaust Emissions From Motor Vehicles Using Leaded and Unleaded Gasoline as Fuel

While Unleaded gasoline has the advantage of eliminating lead from automobile exhaust, its potential to reduce the exhaust gas and particles, merits further examination. In the present studies,the concentrations of hydrocarbons (HC) and earbon monoxides (CO) in emissions were analyzed on Santana engine Dynamometer under a standard test cycle, and total exhaust particles were collected from engines using leaded and unleaded gasoline. It was found that unleaded gasoline reduced the emissions of CO and HC, and decreased the quantity of vehicle exhaust particulate matters by 60%.With the unlead gasoline, only 23 kinds of organic substances, adsorbed in the particles, were identified by gas chromatography/mass spectrometer (GC/MS) while 32 components were detected using the leaded gasoline. The results of in vitro Salmonella/ microsomal test and micronucleus induction assay in CHL cells indicated that both types of gasoline increased the number of histidine-independent colonies and the frequencies of micronucleus induction; no significant differellce was found in their mutagenicity.

COMPOSITIVE EMISSION CONTROL SYSTEM OF GASOLINE VEHICLE

The working principle of a kind of compositive emission control system is inquired into, which includes exhaust heater, secondary air supplement, exhaust gas recirculation （EGR）, thermal reactor and catalytic converter, etc. The purification effect of CO, HC and NOx emission of the gasoline spark ignite （S.I.） engine is studied. The entire vehicle driving cycle tests based on the national emission standard and a series of the gasoline engine-testing bench tests including full load characteristic experiment, load characteristic experiment and idle speed experiment are done. The results show that the system has a very good emission control effect to CO, HC and NOx of gasoline engine. The construction of the system is very simple and can be mounted on the exhaust pipe conveniently without any alteration of the vehicle-use gasoline engine.

Investigation of performance and emission characteristics of waste cooking oil as biodiesel in a diesel engine

Biodiesel is one of the most popular prospective alternative fuels and can be obtained from a variety of sources. Waste frying oil is one such source along with the various raw vegetable oils. However, some specific technical treatments are required to improve certain fuel properties such as viscosity and calorific value of the biodiesel being obtained from waste cooking oil methyl ester （WCOME）. Various treatments are applied depending on the source and therefore the composition of the cooking oil. This research investigated the performance of WCOME as an alternative biofuel in a four-stroke direct injection diesel engine. An 8-mode test was undertaken with diesel fuel and five WCOME blends. The best compromise blend in terms of performance and emissions was identified. Results showed that energy utilization factors of the blends were similar within the range of the operational parameters （speed, load and WCOME content）. Increasing biodiesel content produced slightly more smoke and NOx for a great majority of test points, while the CO and THC emissions were lower.

Correlation between carbon emissions,fuel consumption of vehicles and speed limit on expressway

This paper aimed to investigate the correlation between carbon emissions,fuel consumption,and speed limit.A theoretical model was derived based on the energy conservation law,which expresses the relationship between vehicle's fuel consumption and speed.Subsequently,a total of 40 sets of fuel consumption data were collected through field tests to verify the accuracy of the theoretical model at different speeds and different road longitudinal slope combinations.The fuel consumption was then converted to carbon emissions according to the carbon emission factors specified by Intergovernmental Panel on Climate Change(IPCC).In the field experiment,two types of cars and trucks,which are most common on the expressways in China,were selected.Finally,the travel speed under different posted speed limits was obtained through the previously established model,and the carbon emission changes of different vehicle types at different limited speeds are calculated.The results show that the speed limit has a significant impact on fuel consumption and carbon emissions.When the speed limit increased from 80 to 120 km/h,average vehicle speeds increased about 21%-27%,and fuel consumption and carbon emissions increased from approximately 33%-38%.Another interesting result was that the vehicle's fuel consumption and carbon emissions are only affected by speed.The results of the study explore the effect of speed limits on carbon emissions and provide evidence for road managers to set reasonable speed limits.

Ozone forming potential and sulfur effects on in-use vehicles of the metropolitan area of Mexico City

The largest urban areas of Mexico cities have witnessed high levels of air pollution in the past few decades. The most important air pollutants are ozone and paniculate matter with levels that are still far above current air quality standard. In this work we studied exhaust and evaporative emissions of Mexico City metropolitan area （MAMC） vehicles using fuels in which sulfur content was varied from 89×10^-6 to 817×10^-6, and calculated the ozone forming potential of emissions as well as the specific reactivity of the exhaust for each average fleet-fuel combinations. Data on emission levels were compared to those obtained in 2000 for the same vintage of vehicles. The almost twofold increase in emissions found could be due to degradation of the exhaust emissions control systems.

A signal coordination algorithm for two adjacent intersections based on approximate dynamic programming

To reduce vehicle emissions in road networks, a new signal coordination algorithm based on approximate dynamic programming （ADP） is developed for two intersections. Taking the Jetta car as an experimental vehicle, field tests are conducted in Changchun Street of Changchun city and vehicle emission factors in complete stop and uniform speed states are collected. Queue lengths and signal light colors of approach lanes are selected as state variables, and green switch plans are selected as decision variables of the system. Then the calculation model of the optimization index during the planning horizon is developed based on the basis function method of the ADP. The temporal-difference algorithm is employed to update the weighting factor vector of the approximate function. Simulations are conducted in Matlab and the results show that the established algorithm outperforms the conventional coordination algorithm in reducing vehicle emissions by 8.2%. Sensitive analysis of the planning horizon length on the evaluation index is also conducted and the statistical results show that the optimal length of the planning horizon is directly proportional to the traffic load.