The Influences of Diesel Particulate Filter Installation on Air Pollutant Emissions for Used Vehicles

Tsai, Ying I.; Yang, Hsi-Hsien; Wang, Lin‐Chi; Huan, Jing-Liang; Young, Li-Hao; Cheng, Man-Ting; Chiang, Pen‐Chi

doi:10.4209/aaqr.2011.05.0066

Cited by 12 publications

(5 citation statements)

References 25 publications

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“…Our estimates of the heavy duty CO and BC factors are higher than those derived from remote sensing by Bishop and co-workers (Bishop et al 2015) (Preble et al 2015) for drayage trucks equipped with diesel particle filters (DPF) in the Port of Los Angeles (see Table 3), and also higher than those derived from dynamometer-testing of DPF-equipped trucks by both Tsai and colleagues (Tsai et al 2011) and by May and colleagues (May et al 2014).…”

Section: Discussioncontrasting

confidence: 56%

Ambient air quality measurements from a continuously moving mobile platform: Estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores

Larson

Gould

Riley

et al. 2017

Atmospheric Environment

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We have applied the absolute principal component scores (APCS) receptor model to on-road, background-adjusted measurements of NOx, CO, CO 2 , black carbon (BC), and particle number (PN) obtained from a continuously moving platform deployed over nine afternoon sampling periods in Seattle, WA. Two Varimax-rotated principal component features described 75% of the overall variance of the observations. A heavy-duty vehicle feature was correlated with black carbon and particle number, whereas a light-duty feature was correlated with CO and CO 2 . NO x had moderate correlation with both features. The bootstrapped APCS model predictions were used to estimate area-wide, average fuel-based emission factors and their respective 95% confidence limits. The average emission factors for NOx, CO, BC and PN (14.8, 18.9, 0.40 g/kg, and 4.3×10 15 particles/kg for heavy duty vehicles, and 3.2, 22.4, 0.016 g/kg, and 0.19×10 15 particles/kg for light-duty vehicles, respectively) are consistent with previous estimates based on remote sensing, vehicle chase studies, and recent dynamometer tests. Information on the spatial distribution of the concentrations contributed by these two vehicle categories relative to background during the sampling period was also obtained.

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Section: Discussioncontrasting

confidence: 56%

Ambient air quality measurements from a continuously moving mobile platform: Estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores

Larson

Gould

Riley

et al. 2017

Atmospheric Environment

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“…For example, the Chinese government has imposed restrictions on major pollution sources including vehicles, power plants, transport, and industry sectors (Liu et al, 2016 ) and promulgated the “Atmospheric Pollution Prevention and Control Action Plan” in September 2013, which was intended to reduce PM 2.5 by 25% by 2017 relative to 2012 levels (Huang et al, 2014 ). Science-based technologies have been developed for control of air pollutants, such as diesel particulate filters (Tsai et al, 2011 ) and activated carbon filtering as adsorbent for xylene and NO 2 (Guo et al, 2001 ). Catalytic oxidization and chemisorption methods have been used for indoor formaldehyde removal (Pei and Zhang, 2011 ; Wang et al, 2013 ).…”

Section: Measures For Reducing Air Pollutionmentioning

confidence: 99%

Phylloremediation of Air Pollutants: Exploiting the Potential of Plant Leaves and Leaf-Associated Microbes

et al. 2017

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Air pollution is air contaminated by anthropogenic or naturally occurring substances in high concentrations for a prolonged time, resulting in adverse effects on human comfort and health as well as on ecosystems. Major air pollutants include particulate matters (PMs), ground-level ozone (O3), sulfur dioxide (SO2), nitrogen dioxides (NO2), and volatile organic compounds (VOCs). During the last three decades, air has become increasingly polluted in countries like China and India due to rapid economic growth accompanied by increased energy consumption. Various policies, regulations, and technologies have been brought together for remediation of air pollution, but the air still remains polluted. In this review, we direct attention to bioremediation of air pollutants by exploiting the potentials of plant leaves and leaf-associated microbes. The aerial surfaces of plants, particularly leaves, are estimated to sum up to 4 × 108 km2 on the earth and are also home for up to 1026 bacterial cells. Plant leaves are able to adsorb or absorb air pollutants, and habituated microbes on leaf surface and in leaves (endophytes) are reported to be able to biodegrade or transform pollutants into less or nontoxic molecules, but their potentials for air remediation has been largely unexplored. With advances in omics technologies, molecular mechanisms underlying plant leaves and leaf associated microbes in reduction of air pollutants will be deeply examined, which will provide theoretical bases for developing leaf-based remediation technologies or phylloremediation for mitigating pollutants in the air.

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“…(Biswas et al, 2009) and different PAHs can easily condense on other particles (Chow and Watson, 2007). In diesel exhaust emissions of HDV around 560-760 µg/m 3 PAH were detected (Tsai et al, 2011). Considering the fact that adverse health effects can be affected by small volatile particles and also by adsorbed volatile compounds on the particle surface, the detection of the ambient aerosol without separation of the volatile particles is very important, though the comparability between different studies and situations is poor.…”

Section: Emission Factorsmentioning

confidence: 99%

Size Resolved Particle Number Emission Factors of Motorway Traffic Differentiated between Heavy and Light Duty Vehicles

Nickel

Kaminski

Hellack

et al. 2013

Aerosol Air Qual. Res.

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It is well accepted that airborne particles can induce adverse health effects dependent on the source, composition, morphology and size. Studies indicate that ultrafine particles (diameter < 100 nm) are of specific importance. Therefore, upwind and downwind field measurements of particle number size distributions (14-750 nm), nitrogen oxides, PM 10 and PM 1 mass concentrations were performed to derive information on sources of those types of particles from motorways. The measurement stations were located at a motorway in a rural area with flat terrain and unhindered air flow situation. The mean particle number concentration was 20,900 #/cm 3 downwind and 3,400 #/cm 3 upwind of the motorway. The highest total particle number concentration at the downwind station was 141,000 #/cm 3 . About 90% of these particles were < 100 nm. The measured data were used to derive size-dependent emission factors (EF) using the NO x tracer method. This method is based on listed NO x EF (HBEFA, 2010). The average total particle number EF per vehicle was determined to be 3.5 × 10 14 particles/km. The average particle EF was 2.1 × 10 14 particles/km and 11.8 × 10 14 particles/km for light duty vehicles (LDV) and heavy duty vehicles (HDV). The higher EF for HDV is mainly caused by particles with diameters below 50 nm. The comparison of EF from the literature show the importance of the particle size range investigated. Especially particles at the lower size detection limit contribute to total particle number concentrations and hence determine the EF significantly. In the EURO V directive, particle number emission limits of 6 × 10 11 particles/km were set for diesel passenger cars. This value is defined for non-volatile particles > 23 nm. The EF for the given size range (> 23 nm) determined in this study were significantly higher with 1.0 × 10 14 for LDV.

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The Influences of Diesel Particulate Filter Installation on Air Pollutant Emissions for Used Vehicles

Cited by 12 publications

References 25 publications

Ambient air quality measurements from a continuously moving mobile platform: Estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores

Ambient air quality measurements from a continuously moving mobile platform: Estimation of area-wide, fuel-based, mobile source emission factors using absolute principal component scores

Phylloremediation of Air Pollutants: Exploiting the Potential of Plant Leaves and Leaf-Associated Microbes

Size Resolved Particle Number Emission Factors of Motorway Traffic Differentiated between Heavy and Light Duty Vehicles

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