Segment-based CO2 emission evaluations from passenger cars based on deep learning techniques

The overall level of emissions from the Swiss passenger cars is strongly dependent on the fleet composition. Despite technology improvements, the Swiss passenger cars fleet remains emissions intensive. To analyze the root of this problem and evaluate potential solutions, this paper applies deep learning techniques to evaluate the inter-class (namely micro, small, middle, upper middle, large and luxury class) and intra-class (namely sport utility vehicle and non-sport utility vehicle) differences in carbon dioxide (CO2) emissions. This paper takes full use of novel semi-supervised fuzzy C-means (SSFCM), random forest and AdaBoost models as well as model fusion to successfully classify passenger vehicles and enable segment-based CO2 emission evaluations

Robust vehicle classification based on deep features learning

This paper aims to introduce a scientific Semi-Supervised Fuzzy C-Mean (SSFCM) clustering approach for passenger cars classification based on the feature learning technique. The proposed method is able to classify passenger vehicles in the micro, small, middle, upper middle, large and luxury classes. The performance of the algorithm is analyzed and compared with an unsupervised fuzzy C-means (FCM) clustering algorithm and Swiss expert classification dataset. Experiment results demonstrate that the classification of SSFCM algorithm has better correlation with expert classification than traditional unsupervised algorithm. These results exhibit that SSFCM can reduce the sensitivity of FCM to the initial cluster centroids with the help of labeled instances. Furthermore, SSFCM results in improved classification performance by using the resampling technique to deal with the multi-class imbalanced problem and eliminate the irrelevant and redundant features

Vehicle dimensions based passenger car classification using fuzzy and non-fuzzy clustering methods

There has been globally continuous growth in passenger car sizes and types over the past few decades. To assess the development of vehicular specifications in this context and to evaluate changes in powertrain technologies depending on surrounding frame conditions, such as charging stations and vehicle taxation policy, we need a detailed understanding of the vehicle fleet composition. This paper aims therefore to introduce a novel mathematical approach to segment passenger vehicles based on dimensions features using a means fuzzy clustering algorithm, Fuzzy C-means (FCM), and a non-fuzzy clustering algorithm, K-means (KM). We analyze the performance of the proposed algorithms and compare them with Swiss expert segmentation. Experiments on the real data sets demonstrate that the FCM classifier has better correlation with the expert segmentation than KM. Furthermore, the outputs from FCM with five clusters show that the proposed algorithm has a superior performance for accurate vehicle categorization because of its capacity to recognize and consolidate dimension attributes from the unsupervised data set. Its performance in categorizing vehicles was promising with an average accuracy rate of 79% and an average positive predictive value of 75%

Chemical composition and radiative properties of nascent particulate matter emitted by an aircraft turbofan burning conventional and alternative fuels

Aircraft engines are a unique source of carbonaceous aerosols in the upper troposphere. There, these particles can more efficiently interact with solar radiation than at ground. Due to the lack of measurement data, the radiative forcing from aircraft exhaust aerosol remains uncertain. To better estimate the global radiative effects of aircraft exhaust aerosol, its optical properties need to be comprehensively characterized. In this work we present the link between the chemical composition and the optical properties of the particulate matter (PM) measured at the engine exit plane of a CFM56-7B turbofan. The measurements covered a wide range of power settings (thrust), ranging from ground idle to take-off, using four different fuel blends of conventional Jet A-1 and hydro-processed ester and fatty acids (HEFA) biofuel. At the two measurement wavelengths (532 and 870 nm) and for all tested fuels, the absorption and scattering coefficients increased with thrust, as did the PM mass. The analysis of elemental carbon (EC) and organic carbon (OC) revealed a significant mass fraction of OC (up to 90 %) at low thrust levels, while EC mass dominated at medium and high thrust. The use of HEFA blends induced a significant decrease in the PM mass and the optical coefficients at all thrust levels. The HEFA effect was highest at low thrust levels, where the EC mass was reduced by up to 50 %–60 %. The variability in the chemical composition of the particles was the main reason for the strong thrust dependency of the single scattering albedo (SSA), which followed the same trend as the fraction of OC to total carbon (TC). Mass absorption coefficients (MACs) were determined from the correlations between aerosol light absorption and EC mass concentration. The obtained MAC values (MAC532=7.5±0.3 m2 g−1 and MAC870=5.2±0.9 m2 g−1) are in excellent agreement with previous literature values of absorption cross section for freshly generated soot. While the MAC values were found to be independent of the thrust level and fuel type, the mass scattering coefficients (MSCs) significantly varied with thrust. For cruise conditions we obtained MSC532=4.5±0.4 m2 g−1 and MSC870=0.54±0.04 m2 g−1, which fall within the higher end of MSCs measured for fresh biomass smoke. However, the latter comparison is limited by the strong dependency of MSC on the particles' size, morphology and chemical composition. The use of the HEFA fuel blends significantly decreased PM emissions, but no changes were observed in terms of EC∕OC composition and radiative properties

Effective density of aircraft engine PM revisited : effects of engine thrust, engine type, fuel, and sample conditioning

Aircraft gas turbine engines emit soot agglomerates with varying size, shape, and composition as a function of their operating condition. A useful parameter, which accounts for particle morphology, is effective density. Effective density is used to relate particle number and mass emissions in aviation PM emission models. However, measurement data of PM effective density from commercial aircraft turbine engines are very limited. Here, we report the size‐dependent effective density of PM sampled from commercial aircraft turbine engines in an engine test cell using a standardized sampling and measurement system. We used tandem DMA‐CPMA classification as in our previous study (Durdina et al. 2014). The novelty of this work is reduced scan time from over 10 minutes down to 1 minute per sample with the same hardware configuration, wider range of particle sizes, measurement of different engines, and a larger database with better data quality. The fast method allowed us to measure various engine types during their post‐overhaul test runs with short test points. We also performed effective density measurements during two dedicated test campaigns of the same engine. These campaigns investigated the effects of an alternative fuel blend on emissions and the evolution of the exhaust plume downstream of the engine exit plane. In the latter campaign, the effective density was measured with and without the treatment with a catalytic stripper approximately 25 m downstream of the engine exit plane. Figure 1 shows the compiled results obtained for all engines and fuels tested with exhaust samples taken at the engine exit plane and 25 m downstream with a catalytic stripper. The results confirm the thrust dependence of the effective density distributions reported previously. The most distinct differences are between the effective density distributions at idle thrust (Figure 1, a) and medium to high thrust (Figure 1, b). This trend was qualitatively the same for all engines tested. In contrast to our previous report, the effective densities at medium and high thrust did not follow the mass‐mobility relationship determined previously. The best fit of the data is an exponential function. The fit functions determined have potential applications in aircraft PM emissions modeling and measurement. The size‐dependent densities can be used to estimate PM mass concentration from particle size distributions measured using mobility particle sizers. The density functions can be used to improve particle loss correction models in sampling systems for aircraft engine emissions

Non-volatile particle emissions from aircraft turbine engines at ground-idle induce oxidative stress in bronchial cells

Aircraft emissions contribute to local and global air pollution. Health effects of particulate matter (PM) from aircraft engines are largely unknown, since controlled cell exposures at relevant conditions are challenging. We examined the toxicity of non-volatile PM (nvPM) emissions from a CFM56-7B26 turbofan, the world's most used aircraft turbine using an unprecedented exposure setup. We combined direct turbine-exhaust sampling under realistic engine operating conditions and the Nano-Aerosol Chamber for In vitro Toxicity to deposit particles onto air-liquid-interface cultures of human bronchial epithelial cells (BEAS-2B) at physiological conditions. We evaluated acute cellular responses after 1-h exposures to diluted exhaust from conventional or alternative fuel combustion. We show that single, short-term exposures to nvPM impair bronchial epithelial cells, and PM from conventional fuel at ground-idle conditions is the most hazardous. Electron microscopy of soot reveals varying reactivity matching the observed cellular responses. Stronger responses at lower mass concentrations suggest that additional metrics are necessary to evaluate health risks of this increasingly important emission source

Contributions of residential coal combustion to the air qualityin Beijing–Tianjin–Hebei (BTH), China: a case study

In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing-Tianjin-Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1% of PM2.5 (fine particulate matter) and 42.6% of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30% decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0% on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields

Characterizing and predicting nvPM size distributions for aviation emission inventories and environmental impact

Concerns about civil aviation’s air quality and environmental impacts have led to recent regulations on nonvolatile particulate matter (nvPM) mass and number emissions. Although these regulations do not mandate measuring particle size distribution (PSD), understanding PSDs is vital for assessing the environmental impacts of aviation nvPM. This study introduces a comprehensive data set detailing PSD characteristics of 42 engines across 19 turbofan types, ranging from unregulated small business jets to regulated large commercial aircraft. Emission tests were independently performed by using the European and Swiss reference nvPM sampling and measurement systems with parallel PSD measurements. The geometric mean diameter (GMD) at the engine exit strongly correlated with the nvPM number-to-mass ratio (N/M) and thrust, varying from 7 to 52 nm. The engine-exit geometric standard deviation ranged from 1.7 to 2.5 (mean of 2.05). The study proposes empirical correlations to predict GMD from N/M data of emissions-certified engines. These predictions are expected to be effective for conventional rich-burn engines and might be extended to novel combustor technologies if additional data become available. The findings support the refinement of emission models and help in assessing the aviation non-CO2 climate and air quality impacts

Der Marktplatz ist geräumt: Herausforderungen der Ökonomisierung politischer Räume für den Verfassungsstaat

Einmal mehr muss das Bundesverfassungsgericht (BVerfG) entscheiden, ob Massnahmen zur Euro-Rettung verfassungsmässig sind. Dabei sucht das BVerfG seiner Mission nachzukommen, den vom Grundgesetz garantierten politischen Raum zu schützen. Doch das Entscheidungsprimat eigens zur Bewältigung der europäischen Staatsschuldenkrise geschaffener Institutionen wie dem Europäischen Stabilitätsmechanismus lässt diese politischen Räume durch die Hegemonie ökonomischer Rationalitätserwägungen zunehmend verschwinden. Dies fordert den Verfassungsstaat gleich doppelt heraus: Erstens beschleunigt die Finanzkrise die Verschiebung von Entscheidungskompetenzen auf supranationale und transnationale Ebenen und entledigt den Verfassungsstaat und seine Institutionen der Möglichkeit, bei der Beantwortung folgenreicher Zukunftsfragen eine wesentliche Rolle zu spielen. Daraus folgt, zweitens, dass der Verfassungsstaat um eine seiner Primärlegitimationen gebracht wird, ein Forum für die Formulierung des Gemeinwohls im politischen Prozess zu bieten