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

Abstract

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 6 th January 2012 to 30 th 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.

Statistical evaluation of on-road vehicle emissions measurement using a dual remote sensing technique

“…The above studies observed opposite NO emission trends due to the different fuel types concerned, i.e. gasoline and LPG vehicles in Bishop and Haugen (2018); Organ et al (2019) vs diesel vehicles in Huang et al (2018c); Pujadas et al (2017). RS studies showed that gasoline NOx reduced obviously in the past 15-20 years but diesel NOx did not reduce over the same period including those vehicles equipped with exhaust after-treatment systems for NOx control (Carslaw and Rhys-Tyler, 2013;Chen and Borken-Kleefeld, 2014).…”

“…RS can measure the emissions of a large number of vehicles over a short time, which are widely used to examine the emission trends as a result of various factors, such as more stringent vehicle emission standards (Carslaw et al, 2011;Chen and Borken-Kleefeld, 2014;Lau et al, 2012;Pujadas et al, 2017), engine technology advancement (Huang et al, 2018c;Sjödin, 1994), engine deterioration (Borken-Kleefeld and Chen, 2015;Chen and Borken-Kleefeld, 2016) and other vehicle emission control programs such as fleet renewal and inspection and maintenance (I/M) programs (Bishop et al, 2013;Bishop et al, 2012;Organ et al, 2019;Stedman et al, 1997). These studies all used only one set of RS system.…”

“…Sharp reductions of emission factors (g/kg fuel) of light-duty vehicles were observed, with CO reduced by one order of magnitude since 1989, HC by a factor of >20 since 1989 and NO by 79% since 1997. Organ et al (2019) evaluated the effectiveness of a high-emitter enforcement program for gasoline and liquefied petroleum gas (LPG) vehicles using RS technology in Hong Kong. They found significant overall reductions of 55.9% for HC, 50.5% for CO and 60.9% for NO during 2012 to 2016.…”

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

“…Since 1 September 2014, the Hong Kong Environmental Protection Department (HKEPD) started using on-road remote sensing technology to detect high-emitting petrol and liquefied petroleum gas (LPG) vehicles for enforcement (HKEPD, 2018). The enforcement program has been very effective in reducing the emissions from petrol and LPG vehicles (Huang et al, 2018b;Organ et al, 2019). However, diesel vehicles, a major source of NOx emissions, are excluded because the current remote sensing system would likely produce significant false detections of diesel high-emitters.…”

A Method to Assess and Reduce Pollutant Emissions of Logistic Transportation under Adverse Weather

“…For example, developing electric and hybrid electric vehicles to improve engine fuel efficiency, and autonomous vehicles to improve eco-traffic. Optimizing traffic management measures is mainly about intelligent traffic control methods [24][25][26][27][28]. The research shows that reducing the delay time and the number of stops at intersections by controlling traffic signals on an urban route network can reduce vehicle emissions [27].…”