Assessment of Euro 5 diesel vehicle NOx emissions by laboratory and track testing

Prati, Maria Vittoria; Costagliola, Maria Antonietta; Zuccheroso, Andrea; Napolitano, Pierpaolo

doi:10.1007/s11356-019-04486-7

Cited by 14 publications

(7 citation statements)

References 16 publications

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“…Figures 13 to 16, also show N O x efficiency abatement trend over the time for each experimental scenario. According to, 53 , 54 a reliable estimation of N O x abatement is provided by:…”

Section: Description Of the Selective Catalytic Reduction Systemmentioning

confidence: 99%

Improving the NO_x reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Petrillo

Prati²,

Santini

et al. 2021

International Journal of Engine Research

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This paper deals with the possibility of improving the urea dosage control for the Selective Catalytic Reduction Systems (SCR) of an Euro VI d diesel light commercial vehicle in order to increase [Formula: see text] after-treatment reduction performance. To this aim, first, we assess the effective emissions abatement performance for the appraised diesel vehicle via real-world experimental campaign, carried out according to the Real Driving Emissions (RDE) tests on urban, extra-urban and motorway road sections in Naples, Italy. Based on these real-world data, we derive a parameterized control-oriented model for the SCR system which is, then, exploited for the designing of an alternative urea injection logic which could be able to maximize the [Formula: see text] reduction efficiency while minimizing tailpipe ammonia slip. Specifically, the optimal AdBlue injection rate is designed according to a Nonlinear Model Predictive Control Approach which allows obtaining a proper trade-off between the [Formula: see text] abatement and the urea overdosing problem. The effectiveness of the proposed controller is evaluated by comparing the performance assessed for the appraised SCR system during the experimental tests with the ones achievable if the Euro VI diesel would be equipped with the proposed control strategy. Numerical simulation discloses the effectiveness of the NMPC controller in ensuring improved [Formula: see text] reduction with performance complying with the emissions norms, main in avoiding excessive ammonia slip and in guaranteeing a reduced feed ratio w.r.t. to the standard industrial SCR controller mounted on the vehicle.

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“…Figures 13 to 16, also show N O x efficiency abatement trend over the time for each experimental scenario. According to, 53 , 54 a reliable estimation of N O x abatement is provided by:…”

Section: Description Of the Selective Catalytic Reduction Systemmentioning

confidence: 99%

Improving the NO_x reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Petrillo

Prati²,

Santini

et al. 2021

International Journal of Engine Research

Self Cite

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“…These uncertainties lead to even greater ambiguity in the subsequent air quality modeling results and pollution control strategies, which may compromise the effectiveness of air pollution reduction policies. Moreover, the 2015 Volkswagen scandal showed that the automotive industry purposely cheated in laboratory tests; the actual on-road pollutant emissions were much higher than those presented in the official laboratory tests [45,46]. This bias has resulted in appreciable health damages [47,48].…”

Section: Incremental Contribution Of Pm 25 Levels At Roadsides Of Vementioning

confidence: 99%

Fusion of Environmental Sensing on PM2.5 and Deep Learning on Vehicle Detecting for Acquiring Roadside PM2.5 Concentration Increments

Wang

Lin

Liu

et al. 2020

Sensors

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Traffic emission is one of the major contributors to urban PM2.5, an important environmental health hazard. Estimating roadside PM2.5 concentration increments (above background levels) due to vehicles would assist in understanding pedestrians’ actual exposures. This work combines PM2.5 sensing and vehicle detecting to acquire roadside PM2.5 concentration increments due to vehicles. An automatic traffic analysis system (YOLOv3-tiny-3l) was applied to simultaneously detect and track vehicles with deep learning and traditional optical flow techniques, respectively, from governmental cameras that have low resolutions of only 352 × 240 pixels. Evaluation with 20% of the 2439 manually labeled images from 23 cameras showed that this system has 87% and 84% of the precision and recall rates, respectively, for five types of vehicles, namely, sedan, motorcycle, bus, truck, and trailer. By fusing the research-grade observations from PM2.5 sensors installed at two roadside locations with vehicle counts from the nearby governmental cameras analyzed by YOLOv3-tiny-3l, roadside PM2.5 concentration increments due to on-road sedans were estimated to be 0.0027–0.0050 µg/m3. This practical and low-cost method can be further applied in other countries to assess the impacts of vehicles on roadside PM2.5 concentrations.

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“…The main focus of occupational agents among mechanic workers has been mostly addressed to polycyclic aromatic hydrocarbons (PAH) and NOx content in engine exhaust (e.g. Gürü et al 2002;León-Mejía et al 2019;Prati et al 2019), hence to the recommendation of installing devices for exhaust abatement and ventilation; a practice widely adopted by industrial mechanic workshops.…”

Section: Introductionmentioning

confidence: 99%

Occupational exposure to rare earth elements in mechanic workshops

Trifuoggi

Aiani

Pagano

et al. 2022

Preprint

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Rare earth elements (REEs) such as cerium and lanthanum are utilized in oil refining and as catalytic additives in the production of diesel fuel aimed at optimizing fuel combustion. Background reports from animal studies demonstrated several REE-associated adverse effects, some of which following REE inhalation of diesel exhaust particulate. This study was aimed at evaluating the occupational exposure to REEs in diesel exhaust among two groups of mechanic workers; the first group involving 20 workers from artisanal workshops lacking exhaust abatement devices in Avellino province (Italy) and the second treatment group encompassing 82 workers (controls) from two industrial industrial-shaped workshops in Como (Italy) equipped with exhaust abatement devices. The evaluated endpoints in the two donor groups were: a) urine concentrations of 1-hydroxypyrene (1-OHP), as an indicator of exposure to polycyclic aromatic hydrocarbons (PAHs); b) urine REE concentrations, and c) REE concentrations in scalp hair. The results showed significantly higher urine 1-OHP concentrations in the first treatment group vs. controls (0.28 ± 0.07 mg/L vs. 0.12 ± 0.35 mg/L) (p<0.05), along with significantly higher frequency of smokers in these workers cases vs. controls (47.6% vs. 11.1%;) (p<0.05), and significantly higher urine REE concentrations in the same cases vs. controls (0.14 ± 0.04 mg/L vs. 0.07 ± 0.04 mg/L; ) (p<0.001). REE concentrations in scalp hair were not significantly different between the two donor groups suggesting that REEs might not be sequestered to hair during detoxification pathways.

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Assessment of Euro 5 diesel vehicle NOx emissions by laboratory and track testing

Cited by 14 publications

References 16 publications

Improving the NO_x reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Improving the NO_x reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Fusion of Environmental Sensing on PM2.5 and Deep Learning on Vehicle Detecting for Acquiring Roadside PM2.5 Concentration Increments

Occupational exposure to rare earth elements in mechanic workshops

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Assessment of Euro 5 diesel vehicle NOx emissions by laboratory and track testing

Cited by 14 publications

References 16 publications

Improving the NOx reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Improving the NOx reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Fusion of Environmental Sensing on PM2.5 and Deep Learning on Vehicle Detecting for Acquiring Roadside PM2.5 Concentration Increments

Occupational exposure to rare earth elements in mechanic workshops

Contact Info

Product

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Improving the NO_x reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Improving the NO_x reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control