Fleet-average Emission Factors Research Articles

Evolution and mitigation of vehicular emissions due to India's Bharat Stage Emission Standards – A case study from Delhi

Vehicular emissions are the major contributors of particulate matter and ozone pollution, which has a greater negative impact on human health, climate and vegetation. Bharat Stage emission standards (BSES) are implemented in India to reduce vehicular emissions and there are several stages of BS norms (BS–I, BS-II, BS-III, BS-IV and BS-VI) proposed since 2000. Currently BS-VI emission norms are implemented nationwide from 2020 onwards. The BS standards came into force in prior advance in Delhi region compared to the other cities. Hence, the current study presents an introspection of the impact of several stages of BS norms in reducing the vehicular emissions in Delhi. The impact is studied through the survival fraction of the vehicles in use with different norms, the fleet average emission factors and the fuel consumption for the years 2012–2022. The analysis shows that the emissions from light-duty vehicles (LDV) are significantly higher than the emissions from heavy-duty vehicles (HDV). In the 2017–2022 age group, the PM2.5 and VOC emissions showed a gradual decrease when compared to the 2012–2017 age group, whereas the CO, NOx, PM10 and BC emissions were fluctuating. Overall, in the case of LDV, except for NOx, all the emissions are controlled as an impact of different stages of BS norms and in the case of HDV almost all the pollutants are regulated. The NOx emissions show a positive correlation with vehicular population and the correlation has not changed with the different norms. Though the NOx emission limits are regulated tightly at each stage of the norms, the increase in NOx emissions is unavoidable. This is due to the discrepancy between real-world conditions and laboratory testing. Enforcing BS-VI standards is expected to eliminate this discrepancy and the advanced aftertreatment technologies adopted in BS-VI engines should interact in a balanced way such that the control of one pollutant should minimize the emission of other pollutants.

Effective emissions reduction of high-mileage fleets through a catalytic converter and oxygen sensor replacement program

High-mileage vehicles such as taxis make disproportionately large contributions to urban air pollution due to their accelerated engine deterioration rates and high operation intensities despite their small proportions of the total fleet. Controlling emissions from these high-mileage fleets is thus important for improving urban air quality. This study evaluates the effectiveness of a pilot repair program in reducing emissions from taxis in Hong Kong which account for about 2 % of the total licensed vehicles. The emission factors of a large sample of 684 in-service taxis (including 121 for an emission survey program and 563 for a pilot repair program) were measured on transient chassis dynamometers. The results showed that 63 % of the sampled taxis failed the driving cycle test before the pilot repair program. Most of failed taxis were NO related and 91 % of failed taxis exceeded the emission limits of at least two regulated pollutants simultaneously. After the pilot repair program by replacing catalytic converters and oxygen sensors, the failure rate was significantly reduced to only 7 %. In addition, the fleet average NO, HC and CO emission factors were reduced by 85 %, 82 % and 56 %, respectively. In addition, on-road remote sensing measurements confirmed the real-world emission reductions from the taxis that participated in the pilot repair program. These findings led to the implementation of a large-scale replacement program for all taxis in Hong Kong during 2013–2014, which was estimated to have reduced the total HC, CO and NO emissions by about 420, 2570 and 1000 t per year, respectively (equivalent to 5–8 % emission reductions from the whole road transport sector). Therefore, reducing emissions from the small high-mileage fleets is a highly cost-effective measure to improve urban air quality.

Evolution of Vehicle Emission Factors in a Megacity Affected by Extensive Biofuel Use: Results of Tunnel Measurements in São Paulo, Brazil.

Since 2001, four emission measurement campaigns have been conducted in multiple traffic tunnels in the megacity of São Paulo, Brazil, an area with a fleet of more than 7 million vehicles running on fuels with high biofuel contents: gasoline + ethanol for light-duty vehicles (LDVs) and diesel + biodiesel for heavy-duty vehicles (HDVs). Emission factors for LDVs and HDVs were calculated using a carbon balance method, the pollutants considered including nitrogen oxides (NOx), carbon monoxide (CO), and sulfur dioxide, as well as carbon dioxide and ethanol. From 2001 to 2018, fleet-average emission factors for LDVs and HDVs, respectively, were found to decrease by 4.9 and 5.1% per year for CO and by 5.5 and 4.2% per year for NOx. These reductions demonstrate that regulations for vehicle emissions adopted in Brazil in the last 30 years improved air quality in the megacity of São Paulo significantly, albeit with a clear delay. These findings, especially those for CO, indicate that official emission inventories underestimate vehicle emissions. Here, we demonstrated that the adoption of emission factors calculated under real-world conditions can dramatically improve air quality modeling in the region.

On-highway vehicle emission factors, and spatial patterns, based on mobile monitoring and absolute principal component score

An important component of air quality engineering is quantifying in-use, fleet-average emission factors, and the spatial patterns of vehicle emissions. We report here that an absolute principal component score (APCS) analysis of on-road mobile measurements is a straightforward, efficient method for identifying the major contributors of traffic-related pollutants, deriving fuel-based emission factors, and mapping spatial patterns. Specifically, we applied the APCS model to on-highway measurements of nitrogen oxides (NOX), carbon monoxide (CO), carbon dioxide (CO2), black carbon (BC), and particle number (PN) obtained from a mobile platform deployed over a 5-day sampling period in Chengdu, China. Data were collected for (1) heavy-duty diesel truck (HDDT) plumes (“chase data”) and (2) the general on-road environment (“non-chase data”). The bootstrapped APCS model was used to estimate area-wide, fuel-based average emission factors and their respective 95% confidence intervals. Two components representing diesel trucks and gasoline vehicles were extracted from non-chase data, accounting for 67% of the variance of the on-highway concentrations. Two additional principal components extracted from HDDT chase data, representing normal and high emission features, further separating the emissions characteristics of HDDTs. The fleet-average emission factors for NOX, CO, BC, and PN were 2.2, 50.3, 0.023 g/kg, and 0.32 × 1015 particles/kg for gasoline-powered vehicles, respectively; 33, 3.7, 0.19 g/kg, and 3.3 × 1015 particles/kg fuel for HDDTs' normal emission feature, respectively; and 105, 29, 2.5 g/kg fuel, and 16 × 1015 particles/kg fuel for HDDTs' high emission feature, respectively. APCS results for chase data revealed the existence of high emitters among Chengdu's HDDT fleet, with emission factors 3 to 13 times higher than the normal HDDT vehicles. Although the high emitters are a minority of the fleet, they disproportionately contribute to the overall emissions; emission control policies may wish to target such vehicles.

Chemical and physical characterization of traffic particles in four different highway environments in the Helsinki metropolitan area

Abstract. Traffic-related pollution is a major concern in urban areas due to its deleterious effects on human health. The characteristics of the traffic emissions on four highway environments in the Helsinki metropolitan area were measured with a mobile laboratory, equipped with state-of-the-art instrumentation. Concentration gradients were observed for all traffic-related pollutants, particle number (CN), particulate mass (PM1), black carbon (BC), organics, and nitrogen oxides (NO and NO2). Flow dynamics in different environments appeared to be an important factor for the dilution of the pollutants. For example, the half-decay distances for the traffic-related CN concentrations varied from 8 to 83 m at different sites. The PM1 emissions from traffic mostly consisted of organics and BC. At the most open site, the ratio of organics to BC increased with distance to the highway, indicating condensation of volatile and semi-volatile organics on BC particles. These condensed organics were shown to be hydrocarbons as the fraction of hydrocarbon fragments in organics increased. Regarding the CN size distributions, particle growth during the dilution was not observed; however the mass size distributions measured with a soot particle aerosol mass spectrometer (SP-AMS), showed a visible shift of the mode, detected at ∼ 100 nm at the roadside, to a larger size when the distance to the roadside increased. The fleet average emission factors appeared to be lower for the CN and higher for the NO2 than ten years ago. The reason is likely to be the increased fraction of light-duty (LD) diesel vehicles in the past ten years. The fraction of heavy-duty (HD) traffic, although constituting less than 10 % of the total traffic flow, was found to have a large impact on the emissions.

Measurements of real-world vehicle CO and NO x fleet average emissions in urban tunnels of two cities in China

Urban tunnels located in the city center areas, can alleviate traffic pressure and provide more convenient traffic for people. Vehicles emit pollutants that are significant contributors to air pollution inside and at the outlet of tunnels. Ventilation is the most widely used method to dilute pollutants in tunnels. To calculate the design required air volume flow accurately, vehicle emissions should be exactly determined. Emission factors are important parameters to estimate vehicle emissions. To characterize carbon monoxide (CO) and nitrogen oxides (NOX) emission factors for a mixed vehicle fleet under real-world driving conditions of urban China, we measured CO and NOX concentrations in Shanghai East Yan'an Road tunnel and Changsha Yingpan Road tunnel in 2012 and 2013. In-use fleet average CO and NOX emission factors were calculated according to tunnel pollutants mass balance models. The results showed that the maximum CO concentration in August was 86 ppm, while in October it was 45 ppm in Shanghai East Yan'an Road tunnel. The maximum concentrations of CO and NOX were 33 ppm and 2 ppm in Changsha Yingpan Road tunnel, respectively. In-use fleet average CO emission factors of East Yan'an Road tunnel, with gradient of −3% ∼ 3%, were 1.266 (±0.889) ∼ 3.974 (±2.189) g km−1 vehicle−1. In-use fleet average CO and NOX emission factors of Yingpan Road tunnel with gradient of −6% ∼ 6% amounted to 0.754 (±0.561) ∼ 6.050 (±5.940) g km−1 vehicle−1 and 0.121 (±0.022) ∼ 0.818 (±0.755) g km−1 vehicle−1, respectively. The dependences of CO and NOX emission on roadway gradient and vehicle speed were found. The average CO and NOX emission factors increased with the ascending of roadway gradient as well as reverse with vehicle speed. These findings provide meaningful reference for ventilation design and environmental assessment of urban tunnels, and further help provide basic data to formulate relevant standards and norms.

Historical evaluation of vehicle emission control in Guangzhou based on a multi-year emission inventory

The Guangzhou government adopted many vehicle emission control policies and strategies during the five-year preparation (2005–2009) to host the 2010 Asian Games. This study established a multi-year emission inventory for vehicles in Guangzhou during 2005–2009 and estimated the uncertainty in total vehicle emissions by taking the assumed uncertainties in fleet-average emission factors and annual mileage into account. In 2009, the estimated total vehicle emissions in Guangzhou were 313 000 (242 000–387 000) tons of CO, 60 900 (54 000–70 200) tons of THC, 65 600 (56 800–74 100) tons of NOx and 2740 (2100–3400) tons of PM10. Vehicle emissions within the urban area of Guangzhou were estimated to be responsible for ∼40% of total gaseous pollutants and ∼25% of total PM10 in the entire city. Although vehicle use intensity increased rapidly in Guangzhou during 2005–2009, vehicle emissions were estimated to have been reduced by 12% for CO, 21% for THC and 20% for PM10 relative to those in 2005. NOx emissions were estimated to have remained almost constant during this period. Compared to the “without control” scenario, 19% (15%–23%) of CO, 20% (18%–23%) of THC, 9% (8%–10%) of NOx and 16% (12%–20%) of PM10 were estimated to have been mitigated from a combination of the implementation of Euro III standards for light-duty vehicles (LDVs) and heavy-duty diesel vehicles and improvement of fuel quality. This study also evaluated several enhanced vehicle emission control actions taken recently. For example, the enhanced I/M program for LDVs was estimated to reduce 11% (9%–14%) of CO, 9% (8%–10%) of THC and 2% (2%–3%) of NOx relative to total vehicle emissions in 2009. Total emission reductions by temporary traffic controls for the Asian Games were estimated equivalent to 9% (7%–11%) of CO, 9% (8%–10%) of THC, 5% (5%–6%) of NOx and 10% (8%–13%) of PM10 estimated total vehicle emissions in 2009. Those controls are essential to further vehicle emission mitigation in Guangzhou required by the new National Ambient Air Quality Standards.

On-Road Measurement of Gas and Particle Phase Pollutant Emission Factors for Individual Heavy-Duty Diesel Trucks

Pollutant concentrations in the exhaust plumes of individual diesel trucks were measured at high time resolution in a highway tunnel in Oakland, CA, during July 2010. Emission factors for individual trucks were calculated using a carbon balance method, in which pollutants measured in each exhaust plume were normalized to measured concentrations of carbon dioxide. Pollutants considered here include nitric oxide, nitrogen dioxide (NO(2)), carbon monoxide, formaldehyde, ethene, and black carbon (BC), as well as optical properties of emitted particles. Fleet-average emission factors for oxides of nitrogen (NO(x)) and BC respectively decreased 30 ± 6 and 37 ± 10% relative to levels measured at the same location in 2006, whereas a 34 ± 18% increase in the average NO(2) emission factor was observed. Emissions distributions for all species were skewed with a small fraction of trucks contributing disproportionately to total emissions. For example, the dirtiest 10% of trucks emitted half of total NO(2) and BC emissions. Emission rates for NO(2) were found to be anticorrelated with all other species considered here, likely due to the use of catalyzed diesel particle filters to help control exhaust emissions. Absorption and scattering cross-section emission factors were used to calculate the aerosol single scattering albedo (SSA, at 532 nm) for individual truck exhaust plumes, which averaged 0.14 ± 0.03.

Effects of improved spatial and temporal modeling of on-road vehicle emissions

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5–15% higher NOx and PM emission rates during the weekdays and 15–40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled. Implications: Air quality model performance relies partly on on-road mobile source emission inventories accurately allocated, both spatially and temporally. This work demonstrates the importance of characterizing the mix of heavy-duty diesel versus light-duty gasoline vehicle activity on an hourly basis on weekdays and weekends by road type. Incorporating detailed activity data increases weekday average NOx and PM emissions 5–15%, with early morning hour emission increases approaching 100%, compared to using one average vehicle activity mix. Application of the methodologies described in this paper will improve the accuracy of on-road emission inventories in the understanding of ozone photochemistry and PM formation.

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 (NOx), and particle mass with aerodynamic diameter below 2.5 μm (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 NOx, 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 NOx 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 NOx 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.

On-Road Vehicle Emission Control in Beijing: Past, Present, and Future

Beijing, the capital of China, has experienced rapid motorization since 1990; a trend that is likely to continue. The growth in vehicles and the corresponding emissions create challenges to improving the urban air quality. In an effort to reduce the impact of vehicle emissions on urban air quality, Beijing has adopted a number of vehicle emission control strategies and policies since the mid 1990 s. These are classified into seven categories: (1) emission control on new vehicles; (2) emission control on in-use vehicles; (3) fuel quality improvements; (4) alternative-fuel and advanced vehicles; (5) economic policies; (6) public transport; and (7) temporal traffic control measures. Many have proven to be successful, such as the Euro emission standards, unleaded gasoline and low sulfur fuel, temporal traffic control measures during the Beijing Olympic Games, etc. Some, however, have been failures, such as the gasoline-to-LPG taxi retrofit program. Thanks to the emission standards for new vehicles as well as other controls, the fleet-average emission rates of CO, HC, NO(X), and PM(10) by each major vehicle category are decreasing over time. For example, gasoline cars decreased fleet-average emission factors by 12.5% for CO, 10.0% for HC, 5.8% for NO(X), and 13.0% for PM(10) annually since 1995, and such a trend is likely to continue. Total emissions for Beijing's vehicle fleet increased from 1995 to 1998. However, they show a clear and steady decrease between 1999 and 2009. In 2009, total emissions of CO, HC, NO(X), and PM(10) were 845,000 t, 121,000 t, 84,000 t, and 3700 t, respectively; with reductions of 47%, 49%, 47%, and 42%, relative to 1998. Beijing has been considered a pioneer in controlling vehicle emissions within China, similar to the role of California to the U.S. The continued rapid growth of vehicles, however, is challenging Beijing's policy-makers.

The role of light duty vehicles in future air pollution: a case study of Sacramento

On-road light-duty vehicles (LDVs) play an important role in contributing to urban air pollution. Although vehicles are getting cleaner, regional growth in vehicle population and vehicle miles traveled would somewhat offset California's efforts in transportation pollution reduction. To better understand the role of LDVs in future air pollution, we conduct a case study for Sacramento, California, and investigate future trends in urban air pollution attributable to the light-duty fleet. Results indicate that ambient concentrations of CO, NO x , and total organic gases (TOGs) caused by future light-duty fleets would dramatically decrease over coming years. The resulting concentrations in 2030 might be as low as approximately 20% of the 2005 concentrations. These reflect the improvements in vehicle/fuel technologies and standards in California. However, the future particulate matter (PM10) pollution could be slightly worse than that caused by the 2005 fleet. This is a result of the growing fleet-average emission factors of particulates from 2005 to 2030. For purposes of future particulate control, more attention needs to be paid to LDVs, besides heavy-duty vehicles.

Improving spatial concentration estimates for nitrogen oxides using a hybrid meteorological dispersion/land use regression model in Los Angeles, CA and Seattle, WA

Predictions from a simple line source dispersion model, Caline3, were included as a covariate in a land use regression (LUR) model for NO X /NO 2 in Los Angeles, CA and Seattle, WA. The Caline3 model prediction assumed a unit emission factor for all roadway segments (1.0 g/vehicle-mile). The NO X and/or NO 2 measurements for LA and Seattle were obtained from a comprehensive measurement campaign that is part of the Multi-Ethnic Study of Atherosclerosis Air Pollution Study (MESA Air). The measurement campaigns in both cities were approximately 2 weeks in duration employing approximately 145 measurement sites in Greater LA and 26 sites in Seattle. The best “standard” LUR model (obtained without the inclusion of the Caline3 predictions) in LA had R 2 values of 0.53 for NO X and 0.74 for NO 2. The leave-one-out cross-validated R 2 values for NO X and NO 2 were 0.45 and 0.71, respectively. The equivalent “standard” NO 2 model for Seattle had an R 2 of 0.72 and a leave-one-out cross-validated R 2 of 0.63. When the Caline3 variable was included in the LA hybrid model, the R 2 values were 0.71 and 0.79 for NO X and NO 2, respectively. The corresponding cross-validated R 2 values were 0.66 and 0.77, for NOX and NO2, respectively. In Seattle, the inclusion of the Caline3 variable resulted in a NO 2 model with an R 2 of 0.81 and a corresponding cross-validated R 2 of 0.67. In LA, hybrid model performance was not affected by excluding roadways with annual average daily traffic volumes (AADT) < 100,000. When the Caline3 predictions for heavy-duty trucks and lighter-duty vehicles were modelled as separate terms, the estimated fleet average NO X emission factors were 8.9 (SE = 0.7) and 0.16 (SE = 0.12) grams NO X /vehicle mile for heavy-duty and lighter-duty vehicles, respectively. These values are consistent with fleet average emission factors computed for LA with EMFAC 2007.

Evaluation of mobile emissions contributions to Mexico City's emissions inventory using on-road and cross-road emission measurements and ambient data

Abstract. Mobile emissions represent a significant fraction of the total anthropogenic emissions burden in the Mexico City Metropolitan Area (MCMA) and, therefore, it is crucial to use top-down techniques informed by on-road exhaust measurements to evaluate and improve traditional bottom-up official emissions inventory (EI) for the city. We present the measurements of on-road fleet-average emission factors obtained using the Aerodyne mobile laboratory in the MCMA in March 2006 as part of the MILAGRO/MCMA-2006 field campaign. A comparison of our on-road emission measurements with those obtained in 2003 using essentially the same measurement techniques and analysis methods indicates that, in the three year span, NO emission factors remain within the measured variability ranges whereas emission factors of aldehydes and aromatics species were reduced for all sampled driving conditions. We use a top-down fuel-based approach to evaluate the mobile emissions from the gasoline fleet estimated in the bottom-up official 2006 MCMA mobile sources. Within the range of measurement uncertainties, we found probable slight overpredictions of mean EI estimates on the order of 20–28% for CO and 14–20% for NO. However, we identify a probable EI discrepancy of VOC mobile emissions between 1.4 and 1.9; although estimated benzene and toluene mobile emissions in the inventory seem to be well within the uncertainties of the corresponding emissions estimates. Aldehydes mobile emissions in the inventory, however, seem to be underpredicted by factors of 3 for HCHO and 2 for CH3CHO. Our on-road measurement-based estimate of annual emissions of organic mass from PM1 particles suggests a severe underprediction (larger than a factor of 4) of PM2.5 mobile emissions in the inventory. Analyses of ambient CO, NOx and CO/NOx concentration trends in the MCMA indicate that the early morning ambient CO/NOx ratio has decreased at a rate of about 1.9 ppm/ppm/year over the last two decades due to reductions in CO levels rather than by NOx. These trends, together with the analysis of fuel sales and fleet size, suggest that the relative contribution of diesel vehicles to overall NOx levels has increased over time in the city. Despite the impressive increase in the size of the vehicle fleet between 2000 and 2006, the early morning ambient concentrations of CO and NOx have not increased accordingly, probably due to the reported low removal rates of older vehicles, which do not have emissions control technologies, and partially due to the much lower emissions from newer gasoline vehicles. This indicates that an emission-based air quality improvement strategy targeting large reductions of emissions from mobile sources should be directed towards a significant increase of the removal rate of older, highly-polluting, vehicles.

Evaluating the air quality impacts of the 2008 Beijing Olympic Games: On-road emission factors and black carbon profiles

The aggressive traffic interventions and emission control measures implemented to improve air quality during the 2008 Beijing Olympic Games created a valuable case study to evaluate the effectiveness of these measures on mitigating air pollution and protecting public health. In this paper, we report the results from our field campaign in summer 2008 on the on-road emission factors of carbon monoxide, black carbon (BC) and ultrafine particles (UFP) as well as the ambient BC concentrations. The fleet average emission factors for light-duty gasoline vehicles (LDGV) showed considerable reduction in the Olympic year (2008) compared to the pre-Olympic year (2007). Our measurement of Black Carbon (BC), a primary pollutant, at different elevations at the ambient site suggests consistent decrease in BC concentrations as the height increased near the ground level, which indicates that the nearby ground level sources, probably dominated by traffic, contributed to a large portion of BC concentrations in the lower atmospheric layer in Beijing during summertime. These observations indicate that people living in near ground levels experience higher exposures than those living in higher floors in Beijing. The BC diurnal patterns on days when traffic control were in place during the Olympic Games were compared to those on non-traffic-control days in both 2007 and in 2008. These patterns strongly suggest that diesel trucks are a major source of summertime BC in Beijing. The median BC concentration on Olympic days was 3.7 μg m −3, which was dramatically lower than the value on non-traffic-control days, indicating the effectiveness of traffic control regulations in BC reduction in Beijing.

Modeled and observed ozone sensitivity to mobile-source emissions in Mexico City

Abstract. The emission characteristics of mobile sources in the Mexico City Metropolitan Area (MCMA) have changed significantly over the past few decades in response to emission control policies, advancements in vehicle technologies and improvements in fuel quality, among others. Along with these changes, concurrent non-linear changes in photochemical levels and criteria pollutants have been observed, providing a unique opportunity to understand the effects of perturbations of mobile emission levels on the photochemistry in the region using observational and modeling approaches. The observed historical trends of ozone (O3), carbon monoxide (CO) and nitrogen oxides (NOx) suggest that ozone production in the MCMA has changed from a low to a high VOC-sensitive regime over a period of 20 years. Comparison of the historical emission trends of CO, NOx and hydrocarbons derived from mobile-source emission studies in the MCMA from 1991 to 2006 with the trends of the concentrations of CO, NOx, and the CO/NOx ratio during peak traffic hours also indicates that fuel-based fleet average emission factors have significantly decreased for CO and VOCs during this period whereas NOx emission factors do not show any strong trend, effectively reducing the ambient VOC/NOx ratio. This study presents the results of model analyses on the sensitivity of the observed ozone levels to the estimated historical changes in its precursors. The model sensitivity analyses used a well-validated base case simulation of a high pollution episode in the MCMA with the mathematical Decoupled Direct Method (DDM) and the standard Brute Force Method (BFM) in the 3-D CAMx chemical transport model. The model reproduces adequately the observed historical trends and current photochemical levels. Comparison of the BFM and the DDM sensitivity techniques indicates that the model yields ozone values that increase linearly with NOx emission reductions and decrease linearly with VOC emission reductions only up to 30% from the base case. We further performed emissions perturbations from the gasoline fleet, diesel fleet, all mobile (gasoline plus diesel) and all emission sources (anthropogenic plus biogenic). The results suggest that although large ozone reductions obtained in the past were from changes in emissions from gasoline vehicles, currently significant benefits could be achieved with additional emission control policies directed to regulation of VOC emissions from diesel and area sources that are high emitters of alkenes, aromatics and aldehydes.

Comparison of average particle number emission factors for heavy and light duty vehicles derived from rolling chassis dynamometer and field studies

Fleet aggregate emission factors for particle number for light duty vehicles and heavy duty vehicles are available from a number of field studies by calculation from airborne concentrations. Data are also available from laboratory chassis dynamometer studies in which particle number emissions from engines of a range of capacity and technologies have been measured. In this study the data from the PARTICULATES project database of laboratory test bed measurements have been aggregated to estimate fleet average particle number emission factors for light duty and heavy duty vehicles which have then been compared with the results of field measurement studies. Measurements carried out by [Jones, A.M., Harrison, R.M., 2006. Estimation of the emission factors of particle number and mass fractions from traffic at a site where mean vehicle speeds vary over short distances. Atmospheric Environment 40, 7125–7137] at the Marylebone Road London, represented an ‘urban’ fleet and were estimated by the aggregated laboratory measured emission factors within one or two standard deviations of their values. For light and heavy duty vehicles travelling with an average speed of 39.5 km h −1 the NO x emission factors were estimated to be 0.62 and 5.88 g veh −1 km −1, respectively, and the PM 2.5 emission factors were estimated to be, respectively, 0.017 and 0.17 g veh −1 km −1. The total particle number emission factors (including volatiles) were estimated for light and heavy duty vehicles travelling according ‘urban’ Common ARTEMIS Driving Cycle (CADC) to be 6.31 × 10 13 and 70.6 × 10 13 num veh −1 km −1 and these were both within one standard deviation of the values measured using the field data. Similarly, the fractionated solid particle number emission factors (excluding volatiles), measured for the aerodynamic diameter ranges, 30–50 nm, 50–100 nm and 100–1000 nm, were estimated to within one standard deviation of the equivalent measured emission factors for the light duty vehicles and to within two standard deviations of the equivalent measured emission factors for the heavy duty vehicles. Extending this work to estimate the total number emission factors measured by other research groups, conditions representing both the ‘rural’ and ‘highway’ Common ARTEMIS Driving Cycles were considered. For the light duty vehicles, a general increase in the calculated value of the total number emission factor was observed with increased fleet speed and the observed scatter was accounted for by the split in the fleet according to the vehicle's fuel, whether gasoline or diesel. The calculated values of the total number emission factors for the heavy duty vehicles also show an increase with speed after 60 km h −1. High values are observed at 20 km h −1 suggesting an underlying inverted binomial trend similar to that observed for gaseous emission factors and arguably supported by the field measured values. The scatter of the calculated points about this trend was accounted for by the distribution of the fleet across the vehicle weight and emission legislation categories. With the exception of three of the field research studies considered – where the measured emission factors were significantly underestimated by the aggregated laboratory emission factors – there was a general agreement in the order of magnitude between the calculated and field emission factors, but not to the high degree shown for the Marylebone Road data. Furthermore, dilution temperature, fuel sulphur content and tunnel deposition effects did not individually account for the observed discrepancies in this work and point to the need for correction factors derived from these parameters together with additional information such as dilution ratio in giving a more complete description.

Estimation of particle resuspension source strength on a major London Road

Non-exhaust particles from road traffic arise from both abrasion sources and the resuspension of particles from the road surface. This paper reports a new combination of existing methods for indirect estimation of resuspension emission factors for Marylebone Road, London, a busy multi-lane highway in a street canyon. The method involves firstly estimating the total source strength of coarse particles (PM 2.5–10) arising from the road by calculating the roadside incremental concentration of coarse particles above the urban background. This is converted to a source strength by its ratio to NO x whose source strength is estimated from the knowledge of the traffic mix and mean speed. This coarse particle source strength is assumed to represent the sum of resuspension emissions and the coarse particle component of abrasion emissions. Using information on the traffic mix and speed, the abrasion emissions have been calculated from the EMEP/CORINAIR emissions factor database, the result subtracted from the total coarse particle emissions in order to yield resuspension emissions, and combined with traffic count data to derive fleet-average emission factors. Using the fact that the traffic mix differs substantially between weekdays and weekends, separate average emission factors for light- and heavy-duty vehicles have been estimated. In addition to traffic mix, the influence of wind speed and the time elapsed since the last rainfall upon resuspension have been estimated. Wind speed was found to have by far the larger influence, although this was still secondary to the number of heavy-duty vehicles. Uncertainties arising from the choice of urban background site and poor data quality are discussed.

Vehicle fleet emissions of black carbon, polycyclic aromatic hydrocarbons, and other pollutants measured by a mobile laboratory in Mexico City

Abstract. Black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) are of concern due to their effects on climate and health. The main goal of this research is to provide the first estimate of emissions of BC and particle-phase PAHs (PPAHs) from motor vehicles in Mexico City. The emissions of other pollutants including carbon monoxide (CO), oxides of nitrogen (NOx), volatile organic compounds (VOCs), and particulate matter of diameter 2.5 μm and less (PM2.5) are also estimated. As a part of the Mexico City Metropolitan Area field campaign in April 2003 (MCMA-2003), a mobile laboratory was driven throughout the city. The laboratory was equipped with a comprehensive suite of gas and particle analyzers, including an aethalometer that measured BC and a photoionization aerosol sensor that measured PPAHs. While driving through traffic, the mobile lab continuously sampled exhaust plumes from the vehicles around it. We have developed a method of automatically identifying exhaust plumes, which are then used as the basis for calculation of fleet-average emissions. In the approximately 75 h of on-road sampling during the field campaign, we have identified ~30 000 exhaust measurement points that represent a variety of vehicle types and driving conditions. The large sample provides a basis for estimating fleet-average emission factors and thus the emission inventory. Motor vehicles in the Mexico City area are estimated to emit 1700±200 metric tons BC, 57±6 tons PPAHs, 1 190 000±40 000 tons CO, 120 000±3000 tons NOx, 240 000±50 000 tons VOCs, and 4400±400 tons PM2.5 per year, not including cold start emissions. The estimates for CO, NOx, and PPAHs may be low by up to 10% due to the slower response time of analyzers used to measure these species. Compared to the government's official motor vehicle emission inventory for the year 2002, the estimates for CO, NOx, VOCs, and PM2.5 are 38% lower, 23% lower, 27% higher, and 25% higher, respectively. The distributions of emission factors of BC, PPAHs, and PM2.5 are highly skewed, i.e. asymmetric, while those for benzene, measured as a surrogate for total VOCs, and NOx are less skewed. As a result, the total emissions of BC, PPAHs, and PM2.5 could be reduced by approximately 50% if the highest 20% of data points were removed, but "super polluters" are less influential on overall NOx and VOC emissions.

Carbon monoxide modeling from transportation sources

Street canyon module and gaussian line source module of a regional-scale dispersion model Indic Airviro were used to simulate ambient carbon monoxide (CO) concentrations due to traffic flow at two roadside monitoring locations in Singapore. The fleet average emission factors for each vehicle category was estimated from US EPA MOBILE 5 A guidelines as a function of speed, vehicle deterioration rates and model years. 1-h CO concentrations and worst case 8-h levels have been simulated and compared with measured readings. This study used model-simulated rooftop concentration levels from non-localized sources as background levels at the two sites. The resulting CO concentrations correlate well with actual measured levels and provide a unique approach to predict the impact of CO from transportation.