Jens Gallus

Bio: Jens Gallus is an academic researcher from University of Wuppertal. The author has contributed to research in topics: Portable emissions measurement system. The author has an hindex of 2, co-authored 2 publications receiving 138 citations. Previous affiliations of Jens Gallus include Ford-Werke GmbH.

Impact of driving style and road grade on gaseous exhaust emissions of passenger vehicles measured by a Portable Emission Measurement System (PEMS)

Abstract: Motivated by the upcoming Euro-6c regulation including Real Driving Emissions (RDE), the present study addresses the impact of different driving styles and route characteristics on on-road exhaust emissions. Gaseous emissions of two Diesel test vehicles (Euro-5 and Euro-6) were measured using a Portable Emission Measurement System (PEMS) on an RDE compliant test route. The driving parameters relative positive acceleration (RPA), mean positive acceleration (MPA) and v ∗ a pos 95 allowed a favorable classification of different driving styles. The comparison of driving parameters for normal PEMS trips with reference data obtained from the World harmonized Light-duty Test Cycle (WLTC) and from Field Operational Tests (FOT) indicated a good representation of normal driving. Severe driving led to elevated CO 2 and NO x emissions as compared to normal trips while CO and HC did not allow a distinct classification of different driving styles. Route characteristics of four different routes were investigated applying the parameter cumulated altitude gain using Google Elevation data. The distance specific NO x emissions were in the same range for trips with comparable driving dynamics on routes with similar cumulated altitude gain. Based on repetitive measurements the road grade was calculated within 100 m segments. CO 2 and NO x emissions measured by a PEMS showed a linear increase with road grade. Larger emissions at higher road grades could be explained by more frequent high engine load points. In this study cumulated altitude gain and road grade were directly correlated to emissions measured by the PEMS and the step from 0 to 5% road grade led to a CO 2 increase of 65–81% and a NO x increase of 85–115%.

Eco-driving technology for sustainable road transport: A review

Abstract: Road transport consumes significant quantities of fossil fuel and accounts for a significant proportion of CO2 and pollutant emissions worldwide. The driver is a major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reviews the major factors, research methods and implementation of eco-driving technology. The major factors of eco-driving are acceleration/deceleration, driving speed, route choice and idling. Eco-driving training programs and in-vehicle feedback devices are commonly used to implement eco-driving skills. After training or using in-vehicle devices, immediate and significant reductions in fuel consumption and CO2 emissions have been observed with slightly increased travel time. However, the impacts of both methods attenuate over time due to the ingrained driving habits developed over the years. These findings imply the necessity of developing quantitative eco-driving patterns that could be integrated into vehicle hardware so as to generate more constant and uniform improvements, as well as developing more effective and lasting training programs and in-vehicle devices. Current eco-driving studies mainly focus on the fuel savings and CO2 reduction of individual vehicles, but ignore the pollutant emissions and the impacts at network levels. Finally, the challenges and future research directions of eco-driving technology are elaborated.

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

Abstract: 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.

The cultural barriers to a low-carbon future: A review of six mobility and energy transitions across 28 countries

Abstract: This review focuses on how culture can complicate and impede attempts at promoting more efficient, more sustainable, and often more affordable forms of mobility as well as energy use in homes and buildings. In simpler terms: it illustrates the cultural barriers to a low-carbon, low-energy future across 28 countries. Rather than focus on energy supply, it deals intently with energy end-use, demand, and consumption. In terms of low-carbon transport and mobility, it examines the cultural barriers to aggressive driving, speeding, and eco-driving; automated vehicles; and ridesharing and carpooling. In terms of cooking and building energy use, it examines the cultural barriers to solar home systems, improved cookstoves, and energy efficient heating, cooling, and hot water practices. For each case, the review synthesizes a wide range of studies showing that culture can operate as a salient but often unacknowledged barrier to low-carbon transitions as well as sustainability transitions more generally. The paper concludes with recommendations aimed at catalyzing the effectiveness and efficiency with which policymakers, researchers and practitioners are able to research, develop, demonstrate and deploy culturally appropriate technologies and policies for a low-carbon transition.