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.

Rapid detection of high-emitting vehicles by on-road remote sensing technology improves urban air quality.

Vehicle emissions are the most important source of air pollution in the urban environment worldwide, and their detection and control are critical for protecting public health. Here, we report the use of on-road remote sensing (RS) technology for fast, accurate, and cost-effective identification of high-emitting vehicles as an enforcement program for improving urban air quality. Using large emission datasets from chassis dynamometer testing, RS, and air quality monitoring, we found that significant percentages of in-use petrol and LPG vehicles failed the emission standards, particularly the high-mileage fleets. The RS enforcement program greatly cleaned these fleets, in terms of high-emitter percentages, fleet average emissions, roadside and ambient pollutant concentrations, and emission inventory. The challenges of the current enforcement program are conservative setting of cut points, single-lane measurement sites, and lack of application experience in diesel vehicles. Developing more accurate and vertical RS systems will improve and extend their applications.

Reducing vehicle fuel consumption and exhaust emissions from the application of a green-safety device under real driving.

Vehicle emissions have a significantly negative impact on climate change, air quality and human health. Drivers of vehicles are the last major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reports investigation of the effects of an on-board green-safety device on fuel consumption and emissions for both experienced and inexperienced drivers. A portable emissions measurement system (PEMS) was installed on a diesel light goods vehicle (LGV) to measure real-driving emissions (RDE), including total hydrocarbons (THC), CO CO2, NO, NO2 and particulate matter (PM). In addition, driving parameters (e.g. vehicle speed and acceleration) and environmental parameters (e.g. ambient temperature, humidity and pressure) were recorded in the experiments. The experimental results were evaluated using the Vehicle Specific Power (VSP) methodology to understand the effects of driving behavior on fuel consumption and emissions. The results indicated that driving behavior was improved for both experienced and inexperienced drivers after activation of the on-board green-safety device. In addition, the average time spent was shifted from higher to lower VSP modes by avoiding excessive speed, and aggressive accelerations and decelerations. For experienced drivers, the average fuel consumption and NO, NO2 and soot emissions were reduced by 5%, 56%, 39% and 35%, respectively, with the on-board green-safety device. For inexperienced drivers, the average reductions were 6%, 65%, 50% and 19%, respectively. Moreover, the long-term formed habits of experienced drivers are harder to be changed to accept the assistance of the green-safety device, whereas inexperienced drivers are likely to be more receptive to change and improve their driving behaviors.

Impact of drivers on real-driving fuel consumption and emissions performance.

Eco-driving has attracted great attention as a cost-effective and immediate measure to reduce fuel consumption significantly. Understanding the impact of driver behaviour on real driving emissions (RDE) is of great importance for developing effective eco-driving devices and training programs. Therefore, this study was conducted to investigate the performance of different drivers using a portable emission measurement system. In total, 30 drivers, including 15 novice and 15 experienced drivers, were recruited to drive the same diesel vehicle on the same route, to minimise the effect of uncontrollable real-world factors on the performance evaluation. The results show that novice drivers are less skilled or more aggressive than experienced drivers in using the accelerator pedal, leading to higher vehicle and engine speeds. As a result, fuel consumption rates of novice drivers vary in a slightly greater range than those of experienced drivers, with a marginally higher (2%) mean fuel consumption. Regarding pollutant emissions, CO and THC emissions of all drivers are well below the standard limits, while NOx and PM emissions of some drivers significantly exceed the limits. Compared with experienced drivers, novice drivers produce 17% and 29% higher mean NOx and PM emissions, respectively. Overall, the experimental results reject the hypothesis that driver experience has significant impacts on fuel consumption performance. The real differences lie in the individual drivers, as the worst performing drivers have significantly higher fuel consumption rates than other drivers, for both novice and experienced drivers. The findings suggest that adopting eco-driving skills could deliver significant reductions in fuel consumption and emissions simultaneously for the worst performing drivers, regardless of driving experience.

Evaluating in-use vehicle emissions using air quality monitoring stations and on-road remote sensing systems.

This study investigated real world in-use vehicle emissions using two regulatory techniques simultaneously, namely on-road remote sensing (RS) systems and air quality (AQ) monitoring stations, aiming to provide a full pollution profile from tailpipe to roadside and atmosphere. Two large AQ and RS datasets collected during 2012-2018 were analyzed. The effects of various emission control programmes on the trends of tailpipe emissions and air quality were evaluated. Correlations between tailpipe emissions and roadside and ambient air quality were also explored. The results showed a decreasing trend of NO2 at both roadside and ambient AQ stations from 2013 to 2016, which was attributed to the intensive implementation of a series of vehicle emissions control programmes. Although NO2 was decreasing, O3 was generally increasing for all AQ stations. AQ data showed that O3 had little correlation with either NO2 or NOx, but was mainly determined by NO2/NOx ratio. Roadside NO2/NOx ratio increased first and then decreased or stabilized after 2014, while ambient NO2/NOx ratio increased steadily. RS data showed that the overall NO decreased quickly during 2012-2015 and then decreased moderately after 2015. The decrease was mainly attributed to the effective NO reduction from LPG vehicles. However, diesel NO remained high and reduced relatively slowly during the study period. Gasoline vehicles were relatively clean compared with LPG and diesel vehicles. Finally, good correlations were demonstrated between NO measured by RS sites and NOx measured by roadside AQ stations, indicating that vehicle emissions were the major contributor to roadside NOx pollution. Ambient NOx emissions could be affected by various sources, leading to different correlation levels between RS and ambient AQ results.

Large eddy simulation of vehicle emissions dispersion: Implications for on-road remote sensing measurements.

On-road remote sensing technology measures the concentration ratios of pollutants over CO2 in the exhaust plume in half a second when a vehicle passes by a measurement site, providing a rapid, non-intrusive and economic tool for vehicle emissions monitoring and control. A key assumption in such measurement is that the emission ratios are constant for a given plume. However, there is a lack of study on this assumption, whose validity could be affected by a number of factors, especially the engine operating conditions and turbulence. To guide the development of the next-generation remote sensing system, this study is conducted to investigate the effects of various factors on the emissions dispersion process in the vehicle near-wake region and their effects on remote sensing measurement. The emissions dispersion process is modelled using Large Eddy Simulation (LES). The studied factors include the height of the remote sensing beam, vehicle speed, acceleration and side wind. The results show that the measurable CO2 and NO exhaust plumes are relatively short at 30 km/h cruising speed, indicating that a large percentage of remote sensing readings within the measurement duration (0.5 s) are below the sensor detection limit which would distort the derived emission ratio. In addition, the valid measurement region of NO/CO2 emission ratio is even shorter than the measurable plume and is at the tailpipe height. The effect of vehicle speed (30-90 km/h) on the measurable plume length is insignificant. Under deceleration condition, the length of the valid NO/CO2 measurement region is shorter than under cruising and acceleration conditions. Side winds from the far-tailpipe direction have a significant effect on remote sensing measurements. The implications of these findings are discussed and possible solutions to improve the accuracy of remote sensing measurement are proposed.

A remote sensing emissions monitoring programme reduces emissions of gasoline and LPG vehicles.

Vehicle emissions are a major source of air pollution in Hong Kong affecting human health. A 'strengthened emissions control of gasoline and liquefied petroleum gas (LPG) vehicles' programme has been operating in Hong Kong since September 2014 utilising remote sensing (RS) technology. RS has provided measurement data to successfully identify high emitting gasoline and LPG vehicles which then need to be repaired or removed from the on-road vehicle fleet. This paper aims to evaluate the effectiveness of this globally unique RS monitoring programme. A large RS dataset of 2,144,422 records was obtained covering the period from 6th January 2012 to 30th December 2016, of which 1,206,762 records were valid and suitable for further investigation. The results show that there have been significant reductions of emissions factors (EF) for 40.5% HC, 45.3% CO and 29.6% NO for gasoline vehicles. Additionally, EF reductions of 48.4% HC, 41.1% CO and 58.7% NO were achieved for LPG vehicles. For the combined vehicle fleet, the reductions for HC, CO and NO were 55.9%, 50.5% and 60.9% respectively during this survey period. The findings demonstrate that the strengthened emissions control programme utilising RS has been very effective in identifying high emitting vehicles for repair so as to reduce the emissions from gasoline and LPG vehicles under real driving.

Characterisation of diesel vehicle emissions and determination of remote sensing cutpoints for diesel high-emitters.

Diesel vehicles are a major source of air pollutants in cities and have caused significant health risks to the public globally. This study used both on-road remote sensing and transient chassis dynamometer to characterise emissions of diesel light goods vehicles. A large sample size of 183 diesel vans were tested on a transient chassis dynamometer to evaluate the emission levels of in-service diesel vehicles and to determine a set of remote sensing cutpoints for diesel high-emitters. The results showed that 79% and 19% of the Euro 4 and Euro 5 diesel vehicles failed the transient cycle test, respectively. Most of the high-emitters failed the NO limits, while no vehicle failed the HC limits and only a few vehicles failed the CO limits. Vehicles that failed NO limits occurred in both old and new vehicles. NO/CO2 ratios of 57.30 and 22.85 ppm/% were chosen as the remote sensing cutpoints for Euro 4 and Euro 5 high-emitters, respectively. The cutpoints could capture a Euro 4 and Euro 5 high-emitter at a probability of 27% and 57% with one snapshot remote sensing measurement, while only producing 1% of false high-emitter detections. The probability of high-emitting events was generally evenly distributed over the test cycle, indicating that no particular driving condition produced a higher probability of high-emitting events. Analysis on the effect of cutpoints on real-driving diesel fleet was carried out using a three-year remote sensing program. Results showed that 36% of Euro 4 and 47% of Euro 5 remote sensing measurements would be detected as high-emitting using the proposed cutpoints.

Fuel consumption and emissions performance under real driving: Comparison between hybrid and conventional vehicles.

Hybrid electric vehicles (HEVs) are perceived to be more energy efficient and less polluting than conventional internal combustion engine (ICE) vehicles. However, increasing evidence has shown that real-driving emissions (RDE) could be much higher than laboratory type approval limits and the advantages of HEVs over their conventional ICE counterparts under real-driving conditions have not been studied extensively. Therefore, this study was conducted to evaluate the real-driving fuel consumption and pollutant emissions performance of HEVs against their conventional ICE counterparts. Two pairs of hybrid and conventional gasoline vehicles of the same model were tested simultaneously in a novel convoy mode using two portable emission measurement systems (PEMSs), thus eliminating the effect of vehicle configurations, driving behaviour, road conditions and ambient environment on the performance comparison. The results showed that although real-driving fuel consumption for both hybrid and conventional vehicles were 44%-100% and 30%-82% higher than their laboratory results respectively, HEVs saved 23%-49% fuel relative to their conventional ICE counterparts. Pollutant emissions of all the tested vehicles were lower than the regulation limits. However, HEVs showed no reduction in HC emissions and consistently higher CO emissions compared to the conventional ICE vehicles. This could be caused by the frequent stops and restarts of the HEV engines, as well as the lowered exhaust gas temperature and reduced effectiveness of the oxidation catalyst. The findings therefore show that while achieving the fuel reduction target, hybridisation did not bring the expected benefits to urban air quality.

Tackling nitric oxide emissions from dominant diesel vehicle models using on-road remote sensing technology.

Remote sensing provides a rapid detection of vehicle emissions under real driving condition. Remote sensing studies showed that diesel nitrogen oxides emissions changed little or were even increasing in recent years despite the tightened emission standards. To more accurately and fairly evaluate the emission trends, it is hypothesized that analysis should be detailed for individual vehicle models as each model adopted different emissions control technologies and retrofitted the engine/vehicle at different time. Therefore, this study was aimed to investigate the recent nitric oxide (NO) emission trends of the dominant diesel vehicle models using a large remote sensing dataset collected in Hong Kong. The results showed that the diesel vehicle fleet was dominated by only seven models, accounting for 78% of the total remote sensing records. Although each model had different emission levels and trends, generally all the dominant models showed a steady decrease or stable level in the fuel based NO emission factors (g/kg fuel) over the period studied except for BaM1 and BdM2. A significant increase was observed for the BaM1 2.49 L and early 2.98 L models during 2005-2011, which we attribute to the change in the diesel fuel injection technology. However, the overall mean NO emission factor of all the vehicles was stable during 1991-2006 and then decreased steadily during 2006-2016, in which the emission trends of individual models were averaged out and thus masked. Nevertheless, the latest small, medium and heavy diesel vehicles achieved similar NO emission factors due to the converging of operation windows of the engine and emission control devices. The findings suggested that the increasingly stringent European emission standards were not very effective in reducing the NO emissions of some diesel vehicle models in the real world.

Emission measurement of diesel vehicles in Hong Kong through on-road remote sensing: Performance review and identification of high-emitters.

A two-year remote sensing measurement program was carried out in Hong Kong to obtain a large dataset of on-road diesel vehicle emissions. Analysis was performed to evaluate the effect of vehicle manufacture year (1949-2015) and engine size (0.4-20 L) on the emission rates and high-emitters. The results showed that CO emission rates of larger engine size vehicles were higher than those of small vehicles during the study period, while HC and NO were higher before manufacture year 2006 and then became similar levels between manufacture years 2006 and 2015. CO, HC and NO of all vehicles showed an unexpectedly increasing trend during 1998-2004, in particular ≥6001 cc vehicles. However, they all decreased steadily in the last decade (2005-2015), except for NO of ≥6001 cc vehicles during 2013-2015. The distributions of CO and HC emission rates were highly skewed as the dirtiest 10% vehicles emitted much higher emissions than all the other vehicles. Moreover, this skewness became more significant for larger engine size or newer vehicles. The results indicated that remote sensing technology would be very effective to screen the CO and HC high-emitters and thus control the on-road vehicle emissions, but less effective for controlling NO emissions. No clear correlation was observed between the manufacture year and percentage of high-emitters for ≤3000 cc vehicles. However, the percentage of high-emitters decreased with newer manufacture year for larger vehicles. In addition, high-emitters of different pollutants were relatively independent, in particular NO emissions, indicating that high-emitter screening criteria should be defined on a CO-or-HC-or-NO basis, rather than a CO-and-HC-and-NO basis.