Dataset of vehicle chase measurements in real-world subfreezing winter conditions

This dataset comprises thorough measurements of light-duty vehicles emissions conducted in Siilinjärvi and Kuopio, Finland, during February 2021, using a mobile laboratory. The measurements focused on subfreezing conditions to capture emissions nuances during cold weather. Measurements were carried out on minimally trafficked roads to diminish external disturbances. The dataset includes a large number of variables from gas and particle emissions. Gaseous emissions of CO, CO2, and NOx were measured. Measured variables of particle emissions were number concentration (CPC), size distribution (ELPI+), black carbon concentration (AE33), and chemical composition (SP-AMS). A total of six light-duty vehicles were investigated, featuring three diesel and three gasoline engines. The measurements incorporated three distinct drive scenarios: subfreezing-cold start, preheated-cold start (utilizing either electrical or fuel-operated auxiliary heaters), and hot start (where a vehicle engine has reached the optimal temperature through prior driving). Each drive type was replicated twice, resulting in six driven rounds per vehicle and 36 rounds in total. Additionally, daily background measurements were conducted by following the same route without chasing a specific vehicle. Meteorological conditions during the measurements were representative of winter in Finland, with outside temperatures ranging from -9 °C to -28 °C. The effect of weather conditions on the measurements were minimal. Only a minor effect was due to the occasional snowfall, especially on the last day when the road surface was snowy, and the car being chased lifted the snow from the road surface. We didn't recognize other factors, such as high wind speeds or major road dust emissions, that could have affected the measurement results. This dataset serves as a valuable resource for comparing emissions under diverse environmental conditions, particularly in real-life winter settings where data are scarce. Furthermore, it provides an opportunity for meta-analysis of emission factors from various passenger vehicle types. The dataset's richness and specificity make it a valuable contribution to the understanding of winter-time vehicular emissions.

Hydrocarbon adsorption mechanism of modern automobile engines and methods of reducing hydrocarbon emissions during cold start process: A review

With the global emphasis on environmental protection and increasingly stringent emission regulations for internal combustion engines, there is an urgent need to overcome the problem of large hydrocarbon (HC) emissions caused by unstable engine cold starts. Synergistic engine pre-treatment (reducing hydrocarbon production) as well as after-treatment devices (adsorbing and oxidizing hydrocarbons) is the fundamental solution to emissions. In this paper, the improvement of hydrocarbon emissions is summarized from two aspects: pre-treatment and after-treatment. The pre-treatment for engine cold start mainly focuses on summarizing the intake control, fuel, and engine timing parameters. The after-treatment mainly focuses on summarizing different types of adsorbents and modifications (mainly including different molecular sieve structures and sizes, preparation conditions, silicon aluminum ratio, ion exchange modification, and heterogeneity, etc.), adsorptive catalysts (mainly including optimization of catalytic performance and structure), and catalytic devices (mainly including coupling with thermal management equipment and HC trap devices). In this paper, a SWOT (strength, weakness, opportunity, and threat) analysis of pre-treatment and after-treatment measures is conducted. Researchers can obtain relevant research results and seek new research directions and approaches for controlling cold start HC emissions.

The application prospect and challenge of the alternative methanol fuel in the internal combustion engine

In the context of global carbon neutrality, the internal combustion engines aim to further reduce the carbon emission and improve the fuel economy for the transportation sector. Methanol is treated as a renewable, reliability, and applicability energy, which also shows some superior physicochemical properties compared to the traditional fossil fuels. However, some challenges such as cold start issue, low fuel economy, high unregulated emissions need to address before the methanol widely applies in the engines. This article comprehensively reviews the physicochemical properties and production processes of the methanol, the cold start issue of the methanol engine, and emission and combustion characteristics of the methanol engine for evaluating its potential effect of emission reduction and energy saving in the transportation sector. In addition, different optimization strategies and advanced technologies are proposed and comprehensively discussed in this paper for addressing the issues of the cold start, combustion and emissions of the methanol engines in the real application. Finally, the conclusions and prospects of the methanol engine are presented for promoting its application in the transportation sector and further reducing the carbon emission in the near future, thereby achieving the carbon peak and carbon neutrality in the China.

Novel insights into the NOx emissions characteristics in PEMS tests of a heavy-duty vehicle under different payloads

Real Drive Emission (RDE) test with Portable Emission Measurement System (PEMS) is a widely adopted way to assess vehicle emission compliance. However, the current NOx emissions calculation method stipulated in the China VI emission standard easily ignores the NOx emissions during cold start and low-power operation. To study the effect of cold start and low-power operation on the calculation of NOx emissions in the PEMS test, in this study, a China VI Heavy-Duty Vehicle (HDV) for urban use was used to conduct PEMS tests under various vehicle payload conditions. The data analysis results show that the increase in vehicle payload is beneficial to reducing the specific NOx emissions and passing the NOx emission compliance test because the increased payload improves the NOx conversion efficiency of the SCR system. Cold start duration has no obvious relationship with vehicle payload, accounting for only about 4∼6% in each test, but contributing more than 30% of NOx emissions. Due to the effect of the power threshold and the 90th cumulative percentile, the cold start data has little influence on the result of the NOx emissions assessment and the maximum variation of the NOx emissions result in this study is an 8% rise. For the HDV for urban use, the variation of the power threshold resulting from vehicle payload is small, no more than 2% in this study. The presence of the power threshold makes almost only the low-power operation in the second half of urban driving have an impact on the NOx emissions calculation, which may make more than 50% of NOx emissions in the PEMS test be neglected. The impact of the low-power operation on NOx emissions calculation result will be significantly enhanced if all windows are considered in the Moving Average Window (MAW) method. In the meantime, the degree of variation is closely related to the NOx emissions level during the first half of urban driving. The maximum deterioration of NOx emission assessment result can be more than 90% in this study.

3D graph neural network with few-shot learning for predicting drug-drug interactions in scaffold-based cold start scenario

Understanding drug-drug interactions (DDI) of new drugs is critical for minimizing unexpected adverse drug reactions. The modeling of new drugs is called a cold start scenario. In this scenario, Only a few structural information or physicochemical information about new drug is available. The 3D conformation of drug molecules usually plays a crucial role in chemical properties compared to the 2D structure. 3D graph network with few-shot learning is a promising solution. However, the 3D heterogeneity of drug molecules and the discretization of atomic distributions lead to spatial confusion in few-shot learning. Here, we propose a 3D graph neural network with few-shot learning, Meta3D-DDI, to predict DDI events in cold start scenario. The 3DGNN ensures rotation and translation invariance by calculating atomic pairwise distances, and incorporates 3D structure and distance information in the information aggregation stage. The continuous filter interaction module can continuously simulate the filter to obtain the interaction between the target atom and other atoms. Meta3D-DDI further develops a FSL strategy based on bilevel optimization to transfer meta-knowledge for DDI prediction tasks from existing drugs to new drugs. In addition, the existing cold start setting may cause the scaffold structure information in the training set to leak into the test set. We design scaffold-based cold start scenario to ensure that the drug scaffolds in the training set and test set do not overlap. The extensive experiments demonstrate that our architecture achieves the SOTA performance for DDI prediction under scaffold-based cold start scenario on two real-world datasets. The visual experiment shows that Meta3D-DDI significantly improves the learning for DDI prediction of new drugs. We also demonstrate how Meta3D-DDI can reduce the amount of data required to make meaningful DDI predictions.

Updating emission inventories for vehicular organic gases: Indications from cold-start and temperature effects on advanced technology cars

How would the organic gas emission inventories of future urban vehicles change with new features of advanced technology cars? Here, volatile organic compounds (VOCs) and intermediate volatile organic compounds (IVOCs) from a fleet of Chinese light-duty gasoline vehicles (LDGVs) were characterized by chassis dynamometer experiments to grasp the key factors affecting future inventory accuracy. Subsequently, the VOC and IVOC emissions of LDGVs in Beijing, China, from 2020 to 2035, were calculated and the spatial-temporal variations were recognized under a scenario of fleet renewal. With the tightening of emission standards (ESs), cold start contributed a larger fraction of the total unified cycle VOC emissions due to the imbalanced emission reductions between operating conditions. It took 757.47 ± 337.75 km of hot running to equal one cold-start VOC emission for the latest certified vehicles. Therefore, the future tailpipe VOC emissions would be highly dependent on discrete cold start events rather than traffic flows. By contrast, the equivalent distance was shorter and more stable for IVOCs, with an average of 8.69 ± 4.59 km across the ESs, suggesting insufficient controls. Furthermore, there were log-linear relationships between temperatures and cold-start emissions, and the gasoline direct-injection vehicles performed better adaptability under low temperatures. In the updated emission inventories, the VOC emissions were more effectively reduced than the IVOC emissions. The start emissions of VOCs were estimated to be increasingly dominant, especially in wintertime. By winter 2035, the contribution of VOC start emissions could reach 98.98 % in Beijing, while the fraction of IVOC start emissions would decrease to 59.23 %. Spatially allocation showed that the high emission regions of tailpipe organic gases from LDGVs have transferred from road networks to regions of intense human activities. Our results provide new insights into tailpipe organic gas emissions of gasoline vehicles, and can support future emission inventories and refined assessment of air quality and human health risk.

The impacts from cold start and road grade on real-world emissions and fuel consumption of gasoline, diesel and hybrid-electric light-duty passenger vehicles

Progressively stringent regulations regarding vehicle emissions and fuel economy have spurred technology diversification in light-duty passenger vehicles (LDPVs). To assess the real-world emissions and fuel economy performances of hybrid electric vehicles (HEVs) compared to conventional internal combustion engine (ICE) vehicles, on-road measurements of ten gasoline, four diesel and six full hybrid LDPVs were performed using portable emissions measurement systems (PEMS) in Macao, China. The hot-running emission results indicate that the high emission risks of gasoline vehicles are associated with high mileage and old model years. Diesel vehicles are found to be the highest pollutant emitters in this study due to the intentional removal of aftertreatment systems. Under hot-running conditions, HEVs, as expected, could achieve carbon-reduction benefits of approximately 30 % (i.e., lower CO₂ emissions and fuel consumption) compared to their conventional gasoline counterparts, while no measurable reduction in pollutant emissions was observed except in NO_X (~70 % reduction). In contrast, the cold-start extra emissions (CSEEs) of CO₂ reached 120-364 g/start for these HEVs, even exceeding the maximum values of conventional gasoline vehicles. However, the higher CO₂ CSEEs of HEVs can be far offset by their hot-running emission reduction benefits. For tailpipe pollutants, the CSEEs of the HEVs were reduced by 21 %-68 % on average in comparison to those of conventional gasoline vehicles. Furthermore, strong correlations (R² values of 0.69-0.89) between the road grades and relative emissions were observed. These results can provide necessary information regarding the improvement of future LDPV emission models and inventories.

Numerical study on the wall-impinging diesel spray soot generation and oxidation in the cylinder under cold-start conditions of a diesel engine

The combustion of wall-impinging diesel spray of heavy-duty diesel engines deteriorates combustion quality under cold-start conditions, making it difficult to control soot emissions. To investigate the causes of soot increase in the combustion of wall-impinging spray at low temperature and low speed starting conditions, the effect of the starting fuel mass on the soot formation and oxidation process was analyzed using a multidimensional computational fluid dynamics (CFD) model. The results show that the diesel spray is guided by the piston wall and the limited space, the spray impinged on the wall and the vapor-phase fuel flowed in the spray interaction zone. Thus, the soot mainly accumulates in the spray interaction zone, the region near the cylinder head and the bowl wall in the combustion chamber bowl. The soot from the vapor of deposited fuel film in the piston bowl wall and near wall region accumulates continuously in the after combustion stage, becoming the main source of soot emissions at the time of exhaust valve opening (EVO). Increasing the mass of starting fuel raises the mass of the rich mixture and wall-impinging fuel, which enhances the mismatch between fuel and air, resulting in higher soot generation, while soot is more difficult to be completely oxidized by OH radicals, and ultimately soot emissions increase significantly. It can be deduced that the engine-optimized injection strategy may mitigate the increase in soot emissions at high start-up fuel injection conditions.

Effects analysis on hydrocarbon light-off performance of a catalytic gasoline particulate filter during cold start

In order to study the hydrocarbon combustion in the low-temperature catalytic process of a catalytic gasoline particulate filter (CGPF) during cold start, a mathematical model of the CGPF is established and verified firstly. Then, take T₅₀ (a temperature when the hydrocarbon conversion rate reaches 50%) as hydrocarbon light-off (LO) temperature; the effects of different exhaust parameters and structural parameters on hydrocarbon light-off performance and reaction rate are investigated based on simulation results. Finally, orthogonal experiment analysis is employed to further obtain the most significant factors and suggested parameter solution. The results show that the hydrocarbon LO performance of the CGPF during cold start is positively correlated with exhaust oxygen concentration, porosity, and filter length, but it is negatively correlated with exhaust flow rate and exhaust water vapor concentration. In addition, the inlet of the channel has a significant HC reaction when the oxygen concentration reaches 2.2%, and porosity mainly influences the front half part of the filter. Moreover, the influence degree relationship of the five factors is oxygen > mass flow > porosity > length > water vapor, and the optimum solution of length, vapor, mass flow, porosity, and oxygen is 150 mm, 12.31%, 0.002 kg/s, 0.55, and 2.2%, respectively. This work offers us great reference value for CGPF performance enhancement and hydrocarbon abatement of a GDI engine.

Study on pollutant emission characteristics of different types of diesel vehicles during actual road cold start

The current regulations of heavy-duty vehicles in China do not include the emissions in the cold start stage into the overall emission evaluation. However, the speed of heavy-duty diesel vehicles in the cold start stage is often low and the proportion of idle-conditions is large, resulting in the difference between the actual test results and evaluation results of emissions. Therefore, in order to accurately evaluate the impact of emission during cold start on the overall emission, in this study, the OBS-ONE portable vehicle emission test equipment was used to test the emission of three representative heavy-duty diesel vehicles with different types under actual road driving conditions, and the cumulative averaging (CA) method was adopted to calculate and analyze the test emission data. Firstly, the cold start emission of different types of heavy-duty vehicles was evaluated. The results show that the contribution rate of pollutant emission in the cold start stage is high, in which NOx emission accounts for 40-90% of the whole trip. It was unreasonable for regulations to exclude data in the cold start stage. The cold start duration of vehicle A is nearly 300 s longer than that of vehicle C, however, the NOx and PN emission factors of vehicle A are nearly 10 times and 100 times smaller than that of vehicle C at the cold start stage respectively. The cold start duration, fuel consumption and the emission factors in cold start stage of different types of heavy-duty diesel vehicles do not have a unified law. Secondly, the emission characteristics and differences of different types of heavy-duty vehicles are studied at the instantaneous level, and the internal mechanism causing the emission differences is explored and revealed. In the cold stage, CO₂ emission shows a good correlation with the fuel consumption. CO, NOx emissions show a good correlation with the fuel consumption when the engine and post-treatment temperature are low, and CO and NOx emissions decrease with the increase of engine and post-treatment temperature. PN emissions are mainly related to the engine working state. Finally, the influence of dynamic parameters v·a and RPA on pollutant emission was analyzed. The results show that driving force is an important factor affecting CO₂ emission, and RPA has no obvious correlation with emission at cold start stage.

Predict multi-type drug-drug interactions in cold start scenario

Background

Prediction of drug–drug interactions (DDIs) can reveal potential adverse pharmacological reactions between drugs in co-medication. Various methods have been proposed to address this issue. Most of them focus on the traditional link prediction between drugs, however, they ignore the cold-start scenario, which requires the prediction between known drugs having approved DDIs and new drugs having no DDI. Moreover, they're restricted to infer whether DDIs occur, but are not able to deduce diverse DDI types, which are important in clinics.

Results

In this paper, we propose a cold start prediction model for both single-type and multiple-type drug–drug interactions, referred to as CSMDDI. CSMDDI predict not only whether two drugs trigger pharmacological reactions but also what reaction types they induce in the cold start scenario. We implement several embedding methods in CSMDDI, including SVD, GAE, TransE, RESCAL and compare it with the state-of-the-art multi-type DDI prediction method DeepDDI and DDIMDL to verify the performance. The comparison shows that CSMDDI achieves a good performance of DDI prediction in the case of both the occurrence prediction and the multi-type reaction prediction in cold start scenario.

Conclusions

Our approach is able to predict not only conventional binary DDIs but also what reaction types they induce in the cold start scenario. More importantly, it learns a mapping function who can bridge the drugs attributes to their network embeddings to predict DDIs. The main contribution of CSMDDI contains the development of a generalized framework to predict the single-type and multi-type of DDIs in the cold start scenario, as well as the implementations of several embedding models for both single-type and multi-type of DDIs. The dataset and source code can be accessed at https://github.com/itsosy/csmddi.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04610-4.

Effects of ambient temperature and cold starts on excess NOx emissions in a gasoline direct injection vehicle

Studies have demonstrated that vehicles with gasoline direct injection (GDI) engines produce significantly higher emissions during a cold start than under hot-stabilized periods. A cold start is typically defined by the temperature of the engine or the catalytic converter; its extended effect on emissions, after the vehicle reaches the warm-up stage, has seldom been investigated. In this study, the influence of the post cold start period on nitrogen oxides (NO_x) emissions was evaluated using real-world measurements. Vehicle on-board diagnostic data, fuel consumption, and emissions of multiple pollutants were collected on a 2020 GDI sports utility vehicle equipped with a Portable Emission Measurement System (PEMS). A total of 31 trips, with two drives per day, were conducted along arterial roads and highways in Toronto, Canada. The results indicate that during the first trip of the day after an overnight soak, the average NO_x emission rate was 0.27 g/litre and 0.037 g/km, 384% and 299% higher than the emission rate on the second trip of the day. The amount of trip total NO_x emissions is positively associated with the length of the catalytic converter warm-up period with correlation coefficient 0.67. We also observe that the catalyst warm-up time is negatively correlated with ambient temperature, and a negative relationship between ambient temperature and NO_x emissions throughout the trip is depicted with correlation coefficient -0.44. The measured data reveal an extended effect of the cold start on NO_x emissions even after the temperatures of the engine coolant and catalyst reach a stable level.

Engine cold start analysis using naturalistic driving data: City level impacts on local pollutants emissions and energy consumption

The analysis of vehicle cold start emissions has become an issue of utmost importance since the cold phase occurs mainly in urban context, where most of the population lives. In this sense, this research work analyzes and quantifies the impacts of cold start in urban context using naturalistic driving data. Furthermore, an assessment of the influence of ambient temperature on the percentage of time spent on cold start was also performed. Regarding the impacts of ambient temperature on cold start duration, a higher percentage of time spent on cold start was found for lower ambient temperatures (80% of the time for 0°C and ~50% for 29°C). Results showed that, during cold start, energy consumption is >110% higher than during hot conditions while emissions are up to 910% higher. Moreover, a higher increase on both energy consumption and emissions was found for gasoline vehicles than for diesel vehicles. When assessing the impacts on a city perspective, results revealed that the impacts of cold start increase for more local streets. The main finding of this study is to provide evidence that a higher increase on emissions occurs on more local streets, where most of the population lives. This kind of knowledge is of particular relevance to urban planners in order to perform an informed definition of public policies and regulations to be implemented in the future, to achieve a cleaner and healthier urban environment.

Impact of cold temperature on Euro 6 passenger car emissions

Hydrocarbons, CO, NOx, NH3, N2O, CO2 and particulate matter emissions affect air quality, global warming and human health. Transport sector is an important source of these pollutants and high pollution episodes are often experienced during the cold season. However, EU vehicle emissions regulation at cold ambient temperature only addresses hydrocarbons and CO vehicular emissions. For that reason, we have studied the impact that cold ambient temperatures have on Euro 6 diesel and spark ignition (including: gasoline, ethanol flex-fuel and hybrid vehicles) vehicle emissions using the World-harmonized Light-duty Test Cycle (WLTC) at -7 °C and 23 °C. Results indicate that when facing the WLTC at 23 °C the tested vehicles present emissions below the values set for type approval of Euro 6 vehicles (still using NEDC), with the exception of NOx emissions from diesel vehicles that were 2.3-6 times higher than Euro 6 standards. However, emissions disproportionally increased when vehicles were tested at cold ambient temperature (-7 °C). High solid particle number (SPN) emissions (>1 × 1011 # km-1) were measured from gasoline direct injection (GDI) vehicles and gasoline port fuel injection vehicles. However, only diesel and GDI SPN emissions are currently regulated. Results show the need for a new, technology independent, procedure that enables the authorities to assess pollutant emissions from vehicles at cold ambient temperatures. Harmful pollutant emissions from spark ignition and diesel vehicles are strongly and negatively affected by cold ambient temperatures. Only hydrocarbon, CO emissions are currently regulated at cold temperature. Therefore, it is of great importance to revise current EU winter vehicle emissions regulation.

Characteristics of black carbon emissions from in-use light-duty passenger vehicles

Mitigating black carbon (BC) emissions from various combustion sources has been considered an urgent policy issue to address the challenges of climate change, air pollution and health risks. Vehicles contribute considerably to total anthropogenic BC emissions and urban BC concentrations. Compared with heavy-duty diesel vehicles, there is much larger uncertainty in BC emission factors for light-duty passenger vehicles (LDPVs), in particular for gasoline LDPVs, which warrants further studies. In this study, we employed the dynamometer and the Aethalometer (AE-51) to measure second-by-second BC emissions from eight LDPVs by engine technology and driving cycle. The average BC emission factors under transient cycles (e.g., ECE-15, New European Driving Cycle, NEDC, Worldwide Harmonized Light Vehicles Test Cycle, WLTC) are 3.6-91.5 mg/km, 7.6 mg/km and 0.13-0.58 mg/km, respectively, for diesel (N = 3), gasoline direct injection (GDI) (N = 1) and gasoline port-fuel injection (PFI) engine categories (N = 4). For gasoline PFI LDPVs, the instantaneous emission profiles show a strong association of peak BC emissions with cold-start and high-speed aggressive driving. Such impacts lead to considerable BC emission contributions in cold-start periods (e.g., the first 47 s-94 s) over the entire cycle (e.g., 18-76% of the NEDC and 13-36% of the WLTC) and increased BC emission factors by 80-440% under the WLTC compared to the NEDC. For diesel BC emissions, the size distribution exhibits a typical unimodal pattern with one single peak appearing approximately from 120 to 150 nm, which is largely consistent with previous studies. Nevertheless, the average mass ratios of BC to particle mass (PM) range from 0.38 to 0.54 for three diesel samples, representing substantial impacts from both driving and engine conditions. The significant discrepancy between gasoline BC emission factors obtained from tailpipe exhaust versus ambient conditions suggest that more comparative measurements and fine-grained simulations should be designed and implemented to address this discrepancy.

Exhaust emissions of volatile organic compounds of powered two-wheelers: effect of cold start and vehicle speed. Contribution to greenhouse effect and tropospheric ozone formation

Powered two-wheeler (PTW) vehicles complying with recent European type approval standards (stages Euro 2 and Euro 3) were tested on chassis dynamometer in order to measure exhaust emissions of about 25 volatile organic compounds (VOCs) in the range C1-C7, including carcinogenic compounds as benzene and 1,3-butadiene. The fleet consists of a moped (engine capacity ≤ 50 cm(3)) and three fuel injection motorcycles of different engine capacities (150, 300 and 400 cm(3)). Different driving conditions were tested (US FPT cycle, constant speed). Due to the poor control of the combustion and catalyst efficiency, moped is the highest pollutant emitter. In fact, fuel injection strategy and three way catalyst with lambda sensor are able to reduce VOC motorcycles' emission of about one order of magnitude with respect to moped. Cold start effect, that is crucial for the assessment of actual emission of PTWs in urban areas, was significant: 30-51% of extra emission for methane. In the investigated speed range, moped showed a significant maximum of VOC emission factor at minimum speed (10 km/h) and a slightly decreasing trend from 20 to 60 km/h; motorcycles showed on the average a less significant peak at 10 km/h, a minimum at 30-40 km/h and then an increasing trend with a maximum emission factor at 90 km/h. Carcinogenic VOCs show the same pattern of total VOCs. Ozone Formation Potential (OFP) was estimated by using Maximum Incremental Reactivity scale. The greatest contribution to tropospheric ozone formation comes from alkenes group which account for 50-80% to the total OFP. VOC contribution effect on greenhouse effect is negligible with respect to CO2 emitted.