Evaluation of traffic exhaust contributions to ambient carbonaceous submicron particulate matter in an urban roadside environment in Hong Kong

Abstract

Abstract. Road traffic has significant impacts on air quality particularly in densely urbanized and populated areas where vehicle emissions are a major local source of ambient particulate matter. Engine type (i.e., fuel use) significantly impacts the chemical characteristics of tailpipe emission, and thus the distribution of engine types in traffic impacts measured ambient concentrations. This study provides an estimation of the contribution of vehicles powered by different fuels (gasoline, diesel, LPG) to carbonaceous submicron aerosol mass (PM 1 ) based on ambient aerosol mass spectrometer (AMS) and elemental carbon (EC) measurements and vehicle count data in an urban inner city environment in Hong Kong with the aim to gauge the importance of different engine types to particulate matter burdens in a typical urban street canyon. On an average per-vehicle basis, gasoline vehicles emitted 75 and 93 % more organics than diesel and LPG vehicles, respectively, while EC emissions from diesel vehicles were 45 % higher than those from gasoline vehicles. LPG vehicles showed no appreciable contributions to EC and thus overall represented a small contributor to traffic-related primary ambient PM 1 despite their high abundance (∼ 30 %) in the traffic mix. Total carbonaceous particle mass contributions to ambient PM 1 from diesel engines were only marginally higher (∼ 4 %) than those from gasoline engines, which is likely an effect of recently introduced control strategies targeted at commercial vehicles and buses. Overall, gasoline vehicles contributed 1.2 µg m −3 of EC and 1.1 µ m −3 of organics, LPG vehicles 0.6 µg m −3 of organics and diesel vehicles 2.0 µg m −3 of EC and 0.7 µg m −3 of organics to ambient carbonaceous PM 1 .

Tracking separate contributions of diesel and gasoline vehicles to roadside PM<sub>2.5</sub> through online monitoring of volatile organic compounds and PM<sub>2.5</sub> organic and elemental carbon: a 6-year study in Hong Kong

“…Another plausible reason for the elevated OC observed in wintertime is the enhanced partitioning of semivolatile organic compounds (SVOCs) into the particle phase due to lower temperature and higher organic aerosol loading. Previous studies at the same monitoring site show that VE-related organic aerosol (derived from PMF analysis of organic aerosol mass spectra) decreases by 40 % in summer relative to spring despite consistency in traffic flow volume, which points to a sizable influence of the gas-particle partitioning of SVOCs (Lee et al, 2017).…”

“…The success has been verified by results from an ad hoc roadside study and a study comparing the emissions in a local tunnel between 2003 and 2015 (Lee et al, 2017;Wang et al, 2018). Most HK studies in the past only reported overall PM vehicle contributions due to the lack of separate local source profiles for diesel and gasoline vehicles and constraints in the PMF model posed by a lack of vehicle type specific tracers (Li et al, 2012;Huang et al, 2014;Cheng et al, 2015;Sun et al, 2016). Some studies achieved the separation either by using nonlocal source profiles in the CMB model or by coupling vehicle-type-specific traffic data collected in a short period with aerosol-mass-spectrometry-based PMF (Zheng et al, 2006;Lee et al, 2017).…”

“…In Hong Kong (HK), the PM vehicle contribution from diesel vehicles has reduced significantly over the last 2 decades, resulting from a series of ambitious control efforts. The success has been verified by results from an ad hoc roadside study and a study comparing the emissions in a local tunnel between 2003 and 2015 (Lee et al, 2017;Wang et al, 2018). Most HK studies in the past only reported overall PM vehicle contributions due to the lack of separate local source profiles for diesel and gasoline vehicles and constraints in the PMF model posed by a lack of vehicle type specific tracers (Li et al, 2012;Huang et al, 2014;Cheng et al, 2015;Sun et al, 2016).…”

“…The station is located at the junction of two trunk roads with an annual average daily traffic count of ∼ 45 000 (Transport Department, 2018). Previous vehicle counting exercises showed that private cars fueled by gasoline, goods vehicles and buses fueled by diesel, and taxis running on LPG made up 32 %, 22 %, 16 % and 29 %, respectively, of the vehicle fleet in the sampling area (Lee et al, 2017). In addition to the busy traffic, there are small shops, restaurants, and tall residential and commercial buildings in the immediate vicinity of the station.…”

“…Most HK studies in the past only reported overall PM vehicle contributions due to the lack of separate local source profiles for diesel and gasoline vehicles and constraints in the PMF model posed by a lack of vehicle type specific tracers (Li et al, 2012;Huang et al, 2014;Cheng et al, 2015;Sun et al, 2016). Some studies achieved the separation either by using nonlocal source profiles in the CMB model or by coupling vehicle-type-specific traffic data collected in a short period with aerosol-mass-spectrometry-based PMF (Zheng et al, 2006;Lee et al, 2017). The lack of a robust means to differentiate between diesel and gasoline contributions to PM vehicle calls for the need to develop a more effective source apportionment strategy, especially considering the long-term need in monitoring their impact on air quality.…”