Remote Sensing Data and a Potential Model of Vehicle Exhaust Emissions

In June 1991, General Motors Research and Development Center (GMR&D) participated in a remote sensing study conducted by the California Air Resources Board and the U. S. Environmental Protection Agency. During this study, the GMR&D remote sensor was used to measure the carbon monoxide (CO) and hydrocarbon (HC) emissions from approximately 15,000 vehicles. The vehicle type (passenger car, light-duty truck, or medium/heavy-duty truck), manufacturer, and model year were identified for each vehicle by acquiring registration data from the state of California. Analyses were performed separately for each vehicle type and for passenger cars by separate model years. The data indicate that the passenger cars with the highest 10% of CO emissions generated approximately 58% of the total CO from all cars. Similarly, the 10% highest HC-emitting cars generated 65% of the total HC from cars. It was found that for each model year of vehicle, the distribution of emission concentrations followed a logarithmic relationship. The logarithmic functions that describe these relationships can be used to estimate the fraction of vehicles that emitted at or above any given concentration of CO or HC. However, these logarithmic functions only describe measured distributions for vehicles emitting more than 1% CO and 0.015% HC.     

Characterization of On-Road Vehicle NO Emissions by a TILDAS Remote Sensor

ABSTRACT

A tunable infrared laser differential absorption spectrometer (TILDAS) was used to remotely sense the nitric oxide (NO) emissions from 1,473 on-road vehicles. The real-world measurement precision of this instrument in the limit of low NO concentration is 5 ppm of the vehicle exhaust, which corresponds to a 3o detection limit of 15 ppm. Our analysis of the distribution of negative concentration measurements produced during this experiment supports this claim, showing that the instrumental noise for this set of measurements was at most 8 ppm in the limit of low NO concentration. The high sensitivity of this instrument allowed us to measure the NO emissions of even the cleanest vehicles. The measured vehicle fleet NO emissions closely fit a gamma distribution with 10% of the fleet contributing about 50% of the total fleet emissions. Newer vehicles had lower NO emissions than older ones, but high NO emitters were found in every vehicle age cohort. On a vehicle-by-vehicle basis, NO emissions correlated very weakly with vehicle velocity, acceleration, power per unit mass, carbon monoxide (CO) emissions, and hydrocarbon (HC) emissions. High NO emitting vehicles could not be identified by remote sensing of CO or HC emissions and vice versa. When we compared the NO emissions for 117 vehicles measured more than one time, about half of the high NO emitters were found to be very consistent, while the other half varied significantly.     

Comparison of vehicle activity and emission inventory between Beijing and Shanghai

Vehicle emission inventory is a critical element for air quality study. This study created systemic methods to establish a vehicle emission inventory in Chinese cities. The methods were used to obtain credible results of vehicle activity in Beijing and Shanghai. On the basis of the vehicle activity data, the International Vehicle Emission model is used to establish vehicle emission inventories. The emissions analysis indicates that 3 t of particulate matter (PM), 199 t of nitrogen oxides (NO(x)), 192 t of volatile organic compounds (VOCs), and 2403 t of carbon monoxide (CO) are emitted from on-road vehicles each day in Beijing, whereas 4 t of PM, 189 t of NO(x), 113 t of VOCs, and 1009 t of CO are emitted in Shanghai. Although common features were found in these two cities (many new passenger cars and a high taxi proportion in the fleet), the emission results are dissimilar because of the different local policy regarding vehicles. The method to quantify vehicle emission on an urban scale can be applied to other Chinese cities. Also, knowing how different policies can lead to diverse emissions is beneficial knowledge for other city governments.     

Multispecies remote sensing measurements of vehicle emissions on Sherman Way in Van Nuys,California

As part of the 2010 Van Nuys tunnel study, researchers from the University of Denver measured on-road fuel-specific light-duty vehicle emissions from nearly 13,000 vehicles on Sherman Way (0.4 miles west of the tunnel) in Van Nuys, California, with its multispecies Fuel Efficiency Automobile Test (FEAT) remote sensor a week ahead of the tunnel measurements. The remote sensing mean gram per kilogram carbon monoxide (CO), hydrocarbon (HC), and oxide of nitrogen (NO_x) measurements are 8.9% lower, 41% higher, and 24% higher than the tunnel measurements, respectively. The remote sensing CO/NO_x and HC/NO_x mass ratios are 28% lower and 20% higher than the comparable tunnel ratios. Comparisons with the historical tunnel measurements show large reductions in CO, HC, and NO_x over the past 23 yr, but little change in the HC/NO_x mass ratio since 1995. The fleet CO and HC emissions are increasingly dominated by a few gross emitters, with more than a third of the total emissions being contributed by less than 1% of the fleet. An example of this is a 1995 vehicle measured three times with an average HC emission of 419 g/kg fuel (two-stroke snowmobiles average 475 g/kg fuel), responsible for 4% of the total HC emissions. The 2008 economic downturn dramatically reduced the number of new vehicles entering the fleet, leading to an age increase (>1 model year) of the Sherman Way fleet that has increased the fleet's ammonia (NH₃) emissions. The mean NH₃ levels appear little changed from previous measurements collected in the Van Nuys tunnel in 1993. Comparisons between weekday and weekend data show few fleet differences, although the fraction of light-duty diesel vehicles decreased from the weekday (1.7%) to Saturday (1.2%) and Sunday (0.6%).

Implications: On-road remote sensing emission measurements of light-duty vehicles on Sherman Way in Van Nuys, California, show large historical emission reductions for CO and HC emissions despite an older fleet arising from the 2008 economic downturn. Fleet CO and HC emissions are increasingly dominated by a few gross emitters, with a single 1995 vehicle measured being responsible for 4% of the entire fleet's HC emissions. Finding and repairing and/or scrapping as little as 2% of the fleet would reduce on-road tailpipe emissions by as much as 50%. Ammonia emissions have locally increased with the increasing fleet age.     

A Fuel-Based Motor Vehicle Emission Inventory

Abstract

A fuel-based methodology for calculating motor vehicle emission inventories is presented. In the fuel-based method, emission factors are normalized to fuel consumption and expressed as grams of pollutant emitted per gallon of gasoline burned. Fleet-average emission factors are calculated from the measured on-road emissions of a large, random sample of vehicles. Gasoline use is known at the state level from sales tax data, and may be disaggregated to individual air basins. A fuel-based motor vehicle CO inventory was calculated for the South Coast Air Basin in California for summer 1991. Emission factors were calculated from remote sensing measurements of more than 70,000 in-use vehicles. Stabilized exhaust emissions of CO were estimated to be 4400 tons/day for cars and 1500 tons/day for light-duty and medium- duty trucks, with an estimated uncertainty of ±20% for cars and ±30% for trucks. Total motor vehicle CO emissions, including incremental start emissions and emissions from heavy-duty vehicles were estimated to be 7900 tons/day. Fuelbased inventory estimates were greater than those of California's MVEI 7F model by factors of 2.2 for cars and 2.6 for trucks. A draft version of California's MVEI 7G model, which includes increased contributions from high-emitting vehicles and off-cycle emissions, predicted CO emissions which closely matched the fuel-based inventory. An analysis of CO mass emissions as a function of vehicle age revealed that cars and trucks which were ten or more years old were responsible for 58% of stabilized exhaust CO emissions from all cars and trucks.     

Ammonia emissions from a representative in-use fleet of light and medium-duty vehicles in the California South Coast Air Basin

We used Fourier Transform Infrared Spectroscopy (FTIR) to measure tailpipe ammonia emissions from a representative fleet of 41 light and medium-duty vehicles recruited in the California South Coast Air Basin. A total of 121 chassis dynamometer emissions tests were conducted on these vehicles and the test results were examined to determine the effects of several key variables on ammonia emissions. Variables included vehicle type, driving cycle, emissions technology, ammonia precursor emissions (i.e. CO and NOx) and odometer readings/model year as a proxy for catalyst age. The mean ammonia emissions factor was 46 mg km^?1 (σ = 48 mg km^?1) for the vehicle fleet. Average emission factors for specific vehicle groups are also reported in this study. Results of this study suggest vehicles with the highest ammonia emission rates possess the following characteristics: medium-duty vehicles, older emissions technologies, mid-range odometer readings, and higher CO emissions. In addition, vehicles subjected to aggressive driving conditions are likely to be higher ammonia emitters. Since the vehicles we studied were representative of recent model year vehicles and technologies in urban airsheds, the results of our study will be useful for developing ammonia emissions inventories in Los Angeles and other urban areas where California-certified vehicles are driven. However, efforts should also be made to continue emissions testing on in-use vehicles to ensure greater confidence in the ammonia emission factors reported here.     

Analysis of Remote Sensing Errors of Omission and Commission Under FTP Conditions

Abstract

Second-by-second modal emissions data from a 73-vehicle fleet of 1990 and 1991 light duty cars and trucks driven on the Federal Test Procedure (FTP) driving cycle were examined to determine remote sensing errors of commission in identifying high emissions vehicles. Results are combined with a similar analysis of errors of omission based on modal FTP data from high emissions vehicles. Extremely low errors of commission combined with modest errors of omission indicate that remote sensing should be very effective in isolating high CO and HC emitting vehicles in a fleet of late model vehicles on the road.     

Black carbon and polycyclic aromatic hydrocarbon emissions from vehicles in the United States-Mexico border region: pilot study

The investigators developed a system to measure black carbon (BC) and particle-bound polycyclic aromatic hydrocarbon (PAH) emission factors during roadside sampling in four cities along the United States-Mexico border, Calexico/Mexicali and El Paso/Juarez. The measurement system included a photoacoustic analyzer for BC, a photoelectric aerosol sensor for particle-bound PAHs, and a carbon dioxide (CO2) analyzer. When a vehicle with measurable emissions passed the system probe, corresponding BC, PAH, and CO2 peaks were evident, and a fuel-based emission factor was estimated. A picture of each vehicle was also recorded with a digital camera. The advantage of this system, compared with other roadside methods, is the direct measurement of particulate matter components and limited interference from roadside dust. The study revealed some interesting trends: Mexican buses and all medium-duty trucks were more frequently identified as high emitters of BC and PAH than heavy-duty trucks or passenger vehicles. In addition, because of the high daily mileage of buses, they are good candidates for additional study. Mexican trucks and buses had higher average emission factors compared with U.S. trucks and buses, but the differences were not statistically significant. Few passenger vehicles had measurable BC and PAH emissions, although the highest emission factor came from an older model passenger vehicle licensed in Baja California.     

Emission Factors for High-Emitting Vehicles Based on On-Road Measurements of Individual Vehicle Exhaust with a Mobile Measurement Platform

ABSTRACT

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO_x), and particle mass with aerodynamic diameter below 2.5 μm (PM_2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO_x, black carbon (BC), PM_2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO_x and CO fleet-average emission factors and more than 60% of PM_2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM_2.5, and NO_x tended to cluster among the same vehicles.

IMPLICATIONS This study presents the characterization of on-road vehicle emissions in Wilmington, CA, by sampling individual vehicle plumes. Approximately 5% of the vehicles were high emitters, whose emissions were more than 5 times the fleet-average values. These high emitters were responsible for 30% and more than 50% of the average emission factors of LDGVs and HDDVs, respectively. It is likely that as the overall fleet becomes cleaner due to more stringent regulations, a small fraction of the fleet may contribute a growing and disproportionate share of the overall emissions. Therefore, long-term changes in on-road emissions need to be monitored.     

A Multipurpose Flare Stack for Control of Chemical Process Wastes

Abstract

To test the effectiveness of California’s vehicle inspection/ maintenance (I/M) program, exclusive of vehicle-owner intervention, a fleet of more than 1,100 vehicles that previously had failed California’s Smog Check test were sent to randomly selected Smog Check stations in the Los Angeles area for covert inspections and repairs. The two-speed idle test was used for repairs. For those vehicles that were repaired at the first inspection, their FTP emission reductions were 25%, 14%, and 11% for hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NO_x), respectively, although emissions testing for NO_x was not performed at the Smog Check stations. Idle HC and CO emissions increased for 35% and 43% of the vehicles, respectively, after repairs. This data set shows that most vehicles that fail the Smog Check inspection are only marginal emitters, with 61% and 44% of the total potential for HC and CO emission reductions, respectively, coming from only 10% of the vehicles that currently fail the inspection. When the vehicles were rank-ordered by idle emissions from dirtiest to cleanest, emission reduction costs for the highest-emitting 10% of the fleet averaged $l,100/ton and $250/ton for HC and CO, respectively, attributing all the costs to each pollutant exclusively. For the remaining vehicles, costs increased dramatically.     

Particle mass emission rates from current-technology, light-duty gasoline vehicles

Now that the U.S. Environmental Protection Agency has promulgated new National Ambient Air Quality Standards for PM2.5, work will begin on generating the data required to determine the sources of ambient PM2.5 and the magnitude of their contributions to air pollution. This paper summarizes the results of an Environmental Research Consortium program, carried out under the auspices of the U.S. Council for Automotive Research. The program focused on particulate matter (PM) emissions from representative, current-technology, light-duty gasoline vehicles produced by DaimlerChrysler Corp., Ford Motor Co., and General Motors Corp. The vehicles, for the most part taken from the manufacturer's certification and durability fleets, were dynamometer-tested using the three-phase Federal Test Procedure in the companies' laboratories. The test fleet was made up of a mixture of both low-mileage (2K-35K miles) and high-mileage (60K-150K miles) cars, vans, sport utility vehicles, and light trucks. For each vehicle tested, PM emissions were accumulated over 4 cold-start tests, which were run on successive days. PM emission rates from the entire fleet (22 vehicles total) averaged less than 2 mg/mile. All 18 vehicles tested using California Phase 2 reformulated gasoline had PM emission rates less than 2 mg/mile at both low and high mileages.     

Determining gaseous emission factors and driver's particle exposures during traffic congestion by vehicle-following measurement techniques

Vehicle gaseous emissions (NO, CO, CO2, and hydrocarbon [HC]) and driver's particle exposures (particulate matter < 1 microm [PM1], < 2.5 microm [PM2.5], and < 10 microm [PM10]) were measured using a mobile laboratory to follow a wide variety of vehicles during very heavy traffic congestion in Macao, Special Administrative Region, People's Republic of China, an urban area having one of the highest population densities in the world. The measurements were taken with high time resolution so that fluctuations in the emissions can be seen readily during vehicle acceleration, cruising, deceleration, and idling. The tests were conducted in close proximity to the vehicles, with the inlet of a five-gas analyzer mounted on the front bumper of the mobile laboratory, and the distance between the vehicles was usually within several meters. To measure the driver's particle exposures, the inlets of the particle analyzers were mounted at the height of the driver's breathing position in the mobile laboratory, with the driver's window open. A total of 178 and 113 vehicles were followed individually to determine the gaseous emission factor and the driver's particle exposures, respectively, for motorcycle, passenger car, taxi, truck, and bus. The gaseous emission factors were used to model the roadside air quality, and good correlations between the modeled and monitored CO, NO2, and nitrogen oxide (NO(x)) verified the reliability of the experiments. Compared with petrol passenger cars and petrol trucks, diesel taxies and diesel trucks emitted less CO but more NO(x). The impact of urban canyons is shown to cause a significant increase in the PM1 peak. The background concentrations contributed a significant amount of the driver's particle exposures.     

Particle Mass Emission Rates from Current-Technology,Light-Duty Gasoline Vehicles

ABSTRACT

Now that the U.S. Environmental Protection Agency has promulgated new National Ambient Air Quality Standards for PM_2.5, work will begin on generating the data required to determine the sources of ambient PM_2.5 and the magnitude of their contributions to air pollution. This paper summarizes the results of an Environmental Research Consortium program, carried out under the auspices of the U.S. Council for Automotive Research. The program focused on particulate matter (PM) emissions from representative, current-technology, light-duty gasoline vehicles produced by DaimlerChrysler Corp., Ford Motor Co., and General Motors Corp. The vehicles, for the most part taken from the manufacturer's certification and durability fleets, were dynamometer-tested using the three-phase Federal Test Procedure in the companies' laboratories. The test fleet was made up of a mixture of both low-mileage (2K-35K miles) and high-mileage (60K-150K miles) cars, vans, sport utility vehicles, and light trucks. For each vehicle tested, PM emissions were accumulated over 4 cold-start tests, which were run on successive days. PM emission rates from the entire fleet (22 vehicles total) averaged less than 2 mg/mile. All 18 vehicles tested using California Phase 2 reformulated gasoline had PM emission rates less than 2 mg/ mile at both low and high mileages.     

A Mathematical Model for Predicting Trends in Carbon Monoxide Emissions and Exposures on Urban Arterial Highways

Abstract

The roadway is one of the most important microenvironments for human exposure to carbon monoxide (CO). To evaluate long-term changes in pollutant exposure due to in-transit activities, a mathematical model has been developed to predict average daily vehicular emissions on highways. By utilizing measurements that are specific for a given location and year (e.g., traffic counts, fleet composition), this model can predict emissions for a specific roadway during various time periods of interest, allowing examination of long-term trends in human exposure to CO. For an arterial highway in northern California, this model predicts that CO emissions should have declined by 58% between 1980 and 1991, which agrees fairly well with field measurements of human exposure taken along that roadway during those two years. An additional reduction of up to 60% in CO emissions is predicted to occur between 1991 and 2002, due solely to the continued replacement of older cars with newer, cleaner vehicles.     

Modelling fuel consumption and pollutant emissions based on real-world driving patterns: the HBEFA approach

Emissions of passenger cars and light-duty vehicles with complex exhaust gas after-treatment are difficult to predict, especially if the prediction is only based on kinematic parameters without vehicle-specific data. A new method for modelling fleet emission factors based on testbench data is presented. It has been used for modern passenger cars and light-duty vehicles (EURO-2 and -3) in the new version 2.1 of the German-Austrian-Swiss Handbook Emission Factors for Road Transport (HBEFA). The new method, not relying on vehicle-specific data, avoids decomposing the measured real-world driving behaviour and all associated uncertainties. Emission factors can be predicted for any given driving pattern which is characterised through kinematic parameters or representative time series of vehicle speed. The methodology determines the linear combination of measured driving patterns that is most representative for the driving pattern whose emissions are to be predicted. The approach is illustrated using testbench real-world measurements of 44 passenger cars of technology stages EURO-2 and -3.     

Three decades of on-road mobile source emissions reductions in South Los Angeles

In May 2018, the University of Denver repeated on-road optical remote sensing measurements at two locations in Lynwood, CA. Lynwood area vehicle tailpipe emissions were first surveyed in 1989 and 1991 because the area suffered from a large number of carbon monoxide (CO) air quality violations. These new measurements allow for the estimation of fuel-specific CO and total hydrocarbon (HC) emissions reductions, changes in the longevity of emission-control components, and the prevalence of high emitters in the current fleet. Since 1989 CO emissions decreased approximately factors of 10 (120 ± 8 to 12.3 ± 0.2 gCO/kg of fuel) and 20 (210 ± 8 to 10.4 ± 0.4 gCO/kg of fuel) at our I-710/Imperial Highway and Long Beach Blvd. sites, respectively. These reductions are also reflected in the local ambient air measurements. Tailpipe HC emissions have decreased by a factor of 25 (50 ± 4 to 2.1 ± 0.3 gHC/kg of fuel) since 1991 at the Long Beach Blvd. location. The decreases are so dramatic that the vast majority of vehicles now have HC measurements that are indistinguishable from zero. The decreases have increased the skewedness of the emissions distribution with the 99th percentile now responsible for more than 37% (CO) and 28% (HC) of the totals. Ammonia emissions collected in 2018 at both Lynwood locations peak with 20-year-old vehicles (1998 models), indicating long lifetimes for catalytic converters.

In 1989 and 1991, the on-road Lynwood fleets had significantly higher emissions than fleets observed in other locations within the South Coast Air Basin. The 2018 fleets now have means and emissions by model year that are consistent with those observed at other sites in Los Angeles and the U.S. This indicates that modern vehicle combustion management and after-treatment systems are achieving their goals regardless of community income levels.

Implications: Recent on-road vehicle emission measurements at two locations in the Lynwood, CA area, first visited in 1989, found significant fuel specific CO and HC emission reductions. CO emissions have decreased by a factor of 10 and 20 at each location and HC emissions have declined by a factor of 25. This has increased the skewedness in both species emissions distribution. The 2018 fleets have means and emissions by model year that are now consistent with those observed at other U.S. sites indicating that modern vehicle emissions control advancements are achieving their goals regardless of community income levels.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

Black Carbon and Polycyclic Aromatic Hydrocarbon Emissions from Vehicles in the United States–Mexico Border Region: Pilot Study

The investigators developed a system to measure black carbon (BC) and particle-bound polycyclic aromatic hydrocarbon (PAH) emission factors during roadside sampling in four cities along the United States–Mexico border, Calexico/Mexicali and El Paso/Juárez. The measurement system included a photoacoustic analyzer for BC, a photoelectric aerosol sensor for particle-bound PAHs, and a carbon dioxide (CO₂) analyzer. When a vehicle with measurable emissions passed the system probe, corresponding BC, PAH, and CO₂ peaks were evident, and a fuel-based emission factor was estimated. A picture of each vehicle was also recorded with a digital camera. The advantage of this system, compared with other roadside methods, is the direct measurement of particulate matter components and limited interference from roadside dust. The study revealed some interesting trends: Mexican buses and all medium-duty trucks were more frequently identified as high emitters of BC and PAH than heavy-duty trucks or passenger vehicles. In addition, because of the high daily mileage of buses, they are good candidates for additional study. Mexican trucks and buses had higher average emission factors compared with U.S. trucks and buses, but the differences were not statistically significant. Few passenger vehicles had measurable BC and PAH emissions, although the highest emission factor came from an older model passenger vehicle licensed in Baja California.     

Estimation of road vehicle exhaust emissions from 1992 to 2010 and comparison with air quality measurements in Genoa,Italy

An investigation into road transport exhaust emissions in the Genoa urban area was performed by comparing the quantities of carbon monoxide (CO), nitrogen oxides (NO_x), nitrogen dioxide (NO₂) and particulate matter (PM) emitted by different vehicle categories with air quality measurements referred to the same pollutants. Exhaust emissions were evaluated by applying the PROGRESS (computer PROGramme for Road vehicle EmiSSions evaluation) code, developed by the Internal Combustion Engines Group of the University of Genoa, to eight different years (from 1992 to 2010), considering spark ignition and Diesel passenger cars and light duty vehicles, heavy duty vehicles and buses, motorcycles and mopeds. Changes in terms of vehicles number, mileage and total emissions are presented together with relative distributions among the various vehicle categories. By comparing 1992 and 2010 data, calculated trends show a 7% increase in the number of vehicles, with total mileage growing at a faster rate (approx. 22%); total emissions decrease considerably, by approximately 50% for NO_x and PM, 70% for HC and 80% for CO, due to improvements in engines and fuels forced by the stricter European legislation and the fleet renewal, while primary NO₂ emission will be very close to 1992 level, after a decrease of about 18% in 2000.Air quality was analysed by selecting traffic and background measuring stations from the monitoring network managed by the Environmental Department of the Province of Genoa: average annual concentrations of considered pollutants from 1994 to 2007 were calculated in order to obtain the relative historical trends and compare them with European public health limits and with road vehicle emissions. Though an important reduction in pollutant concentrations has been achieved as a consequence of cleaner vehicles, some difficulties in complying with present and/or future NO₂ and PM₁₀ limits are also apparent, thus requiring suitable measures to be taken by the local authorities.     

Improved Version of Anion-exchange Resin-based Desulfurization Process for Alkali Metal Sulfates

Abstract

Vehicle gaseous emissions (NO, CO, CO₂, and hydrocarbon [HC]) and driver’s particle exposures (particulate matter <1 μm [PM₁], <2.5 μm [PM_2.5], and<10 μm [PM₁₀]) were measured using a mobile laboratory to follow a wide variety of vehicles during very heavy traffic congestion in Macao, Special Administrative Region, People’s Republic of China, an urban area having one of the highest population densities in the world. The measurements were taken with high time resolution so that fluctuations in the emissions can be seen readily during vehicle acceleration, cruising, deceleration, and idling. The tests were conducted in close proximity to the vehicles, with the inlet of a five-gas analyzer mounted on the front bumper of the mobile laboratory, and the distance between the vehicles was usually within several meters. To measure the driver’s particle exposures, the inlets of the particle analyzers were mounted at the height of the driver’s breathing position in the mobile laboratory, with the driver’s window open. A total of 178 and 113 vehicles were followed individually to determine the gaseous emission factor and the driver’s particle exposures, respectively, for motorcycle, passenger car, taxi, truck, and bus. The gaseous emission factors were used to model the roadside air quality, and good correlations between the modeled and monitored CO, NO₂, and nitrogen oxide (NO_x) verified the reliability of the experiments. Compared with petrol passenger cars and petrol trucks, diesel taxies and diesel trucks emitted less CO but more NO_x. The impact of urban canyons is shown to cause a significant increase in the PM₁ peak. The background concentrations contributed a significant amount of the driver’s particle exposures.