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

https://cyberleninka.org/article/n/618304.pdf

CO2 emissions and energy demands of vehicles tested under the NEDC and the new WLTP type approval test procedures

Nowadays, the massive car-hailing data has become a popular source for analyzing traffic operation and road congestion status, which unfortunately has seldom been extended to capture detailed on-road traffic emissions. This study aims to investigate the relationship between road traffic emissions and the related built environment factors, as well as land uses. The Computer Program to Calculate Emissions from Road Transport (COPERT) model from European Environment Agency (EEA) was introduced to estimate the 24-h NOx emission pattern of road segments with the parameters extracted from Didi massive trajectory data. Then, the temporal Fuzzy C-Means (FCM) Clustering was used to classify road segments based on the 24-h emission rates, while Geographical Detector and MORAN’s I were introduced to verify the impact of built environment on line source emissions and the similarity of emissions generated from the nearby road segments. As a result, the spatial autoregressive moving average (SARMA) regression model was incorporated to assess the impact of selected built environment factors on the road segment emission rate based on the probabilistic results from FCM. It was found that short road length, being close to city center, high density of bus stations, more ramps nearby and high proportion of residential or commercial land would substantially increase the emission rate. Finally, the 24-h atmospheric NO2 concentrations were obtained from the environmental monitor stations, to calculate the time variational trend by comparing with the line source traffic emissions, which to some extent explains the contribution of on-road traffic to the overall atmospheric pollution. Result of this study could guide urban planning, so as to avoid transportation related built environment attributes which may contribute to serious atmospheric environment pollutions.

Analyzing spatiotemporal traffic line source emissions based on massive didi online car-hailing service data

The particulate matter (PM) emissions of gasoline vehicles were much lower than those of diesel vehicles until the introduction of diesel particulate filters (DPFs) in the early 2000s. At the same time, gasoline direct injection (GDI) engines started to become popular in the market due to their improved efficiency over port fuel injection (PFI) ones. However, the PM mass and number emissions of GDI vehicles were higher than their PFI counterparts and diesel ones equipped with DPFs. Stringent PM mass levels and the introduction of particle number limits for GDI vehicles in the European Union (EU) resulted in significant PM reductions. The EU requirement to fulfill the proposed limits on the road resulted to the introduction of gasoline particulate filters (GPFs) in EU GDI models. This review summarizes the evolution of PM mass emissions from gasoline vehicles placed in the market from early 1990s until 2019 in different parts of the world. The analysis then extends to total and nonvolatile particle number emissions. Care is given to reveal the impact of ambient temperature on emission levels. The discussion tries to provide scientific input to the following policy-relevant questions. Whether particle number limits should be extended to gasoline PFI vehicles, whether the lower limit of 23 nm for particle number measurements should be decreased to 10 nm, and whether low ambient temperature tests for PM should be included.

Christoph Börensen

Papers

On-road particle number measurements using a portable emission measurement system (PEMS)