Compressed Natural Gas Vehicles Research Articles

Comparative Overview of Compressed Natural Gas Vehicle (CNGV) and Electric Vehicle (EV)

Comparative Overview of Compressed Natural Gas Vehicle (CNGV) and Electric Vehicle (EV)

Impact of electric and clean-fuel vehicles on future PM2.5 and ozone pollution over Delhi

We investigate the impact of adoption of electric vehicles and cleaner fuels on future surface levels of PM2.5 and ozone over Delhi for two contrasting seasons, pre-monsoon and post-monsoon. We run the WRF-Chem atmospheric transport model at high resolution (4 km) with two transport emission scenarios for year 2030: (1) a scenario with electrification of two- and three-wheelers and light commercial vehicles, and (2) a scenario which also includes conversion of diesel vehicles to compressed natural gas (CNG). Compared to the baseline values in 2019, the scenario with both electrification and conversion of diesel vehicles to CNG has a greater reduction in PM2.5 concentrations (up to 5%) than the electrification of two- and three-wheelers and light commercial vehicles alone (within 1%), mainly due to the the greater reduction in primary emissions of PM2.5 and black carbon from diesel conversion to CNG. Vehicles electrification could result in an increase in the daily maximum 8-hours ozone concentrations, which are partially offset by additionally converting to CNG—by −1.9% and +2.4% during pre-monsoon and post-monsoon seasons. This reflects higher NOx emissions from the CNG vehicle scenario compared to electrification-alone scenario, which limits the increase of surface ozone in the VOC-limited chemical environment over Delhi. Our findings highlight the importance of a coordinated strategy for PM2.5 and ozone when considering traffic emission controls, and highlight that the transition to electric vehicles should be accompanied by the conversion of diesel vehicles to CNG to limit surface ozone increase and achieve greater reduction in PM2.5 concentrations over Delhi. However, the small changes in PM2.5 and in ozone compared to the baseline scenario highlight the importance of joint emissions reduction from other sectors to achieve substantial progress in PM2.5 and ozone air quality in Delhi.

Emissions from heavy-duty diesel, natural gas, and diesel-hybrid electric vehicles – Part 1. NOx, N2O and NH3 emissions

The current study characterized nitrogen oxide (NOx), nitrous oxide (N2O), and ammonia (NH3) emissions from 14 heavy-duty vehicles from different vocations (school bus, transit bus, refuse hauler, delivery vehicle, and goods movement vehicle) over different drive cycles using a chassis dynamometer. Test vehicles with engines ranging in model year from 2009 to 2018 and including diesel and compressed natural gas (CNG) vehicles. The diesel vehicles included both vehicles without selective catalytic reduction (no-SCR) and with SCR certified to the 0.2 g per brake horsepower-hour (g/bhp-hr) [0.27 g/kilowatt-hour (kW-hr)] NOx emissions standard that were operated with diesel fuel, with a subset tested on hydrotreated vegetable oil (HVO). The CNG vehicles were all three-way catalyst (TWC) equipped and certified to either the 0.2 or 0.02 g/bhp-hr NOx standard [0.27 or 0.027 g/kW-hr]. This study is part of a larger project that included over 200 in-use heavy-duty vehicles, which is one of the most extensive studies of emissions from modern heavy-duty vehicles to date. NOx, NH3, and N2O emissions varied depending on the vocation and the technology. Average NOx emissions for the Urban Dynamometer Driving Schedule (UDDS) cycle over all vehicles ranged from 0.003 to 6.16 g/bhp-hr [0.004 to 8.25 g/kW-hr] and from 0.02 to 17.2 g/mile [0.012 to 10.7 g/km], with the diesel vehicles showing the highest emissions, the 0.2 g/bhp-hr certified CNG vehicles showing lower emissions, and the 0.02 g/bhp-hr certified CNG vehicles showing very low emissions. NOx emissions over other different cycles were generally in the same range as those for the hot start UDDS, with the highway cycles generally showing the lowest emissions. CNG vehicles had relatively high NH3 emissions ranging from 0.13 to 0.34 g/bhp-hr [0.17 to 0.46 g/kW-hr] and from 0.44 to 0.97 g/mile [0.27 to 0.6 g/km] over the hot start UDDS compared to the SCR-equipped diesel vehicles due to NH3 formation across the TWC. N2O emissions did not show consistent trends and were near/at the detection limits for a number of the vehicles.

Uneven exposure of compressed natural gas (CNG) and hydrogen (H2) cylinders: Fire and extinguishment tests

Vehicles that are powered by gaseous fuel, e.g., compressed natural gas (CNG) or hydrogen (H2), may, in the event of fire, result in a jet flame from a thermally activated pressure relief device (TPRD), or a pressure vessel explosion. There have been a few incidents for CNG vehicles where the TPRD was unsuccessful to prevent a pressure vessel explosion in the event of fire, both nationally in Sweden and internationally. If the pressure vessel explosion would occur inside an enclosure such as a road tunnel, the resulting consequences are even more problematic. In 2019 the authors investigated the fire safety of CNG cylinders exposed to localized fires. One purpose of the tests conducted in 2021 reported in this paper is to investigate whether extinguishment with water, e.g., from a tunnel deluge system, may compromise the safety of vehicle gas cylinders in the event of fire. Steel cylinders handles the situation with localizde fire and/or cooling with water well. Composite tanks can rupture if the fire exposure degrades the composite material strength, and the TPRD is not sufficiently heated to activate, e.g., if the fire is localized or if the TPRD is being cooled by water, which prevents its activation.

An endpoint model for life cycle impact assessment in China and preliminary normalization values: A case study of vehicles

Life cycle assessment (LCA) has become a vital tool for selecting and developing green products to support decision-making. While there are various regional evaluation models for conducting life cycle impact assessment (LCIA), which is one of the key steps in LCA, a systematic LCIA model is still lacking in China. In this study, we propose an endpoint damage model for LCIA. We focus on three endpoint damage categories and eleven environmental impact categories based on local characteristics in China. By using the emission factor method, extrapolation method and other methods, the total emission of each pollutant is quantified. Localized per capita normalization values were calculated. Then, the potential value for environmental impact (PVEI) is acquired, which could be used to represent the impact of pollutant emissions and resource and energy consumption on the environment. With a base year of 2017, the regional per capita normalization values of human health, ecosystem quality and resources in China are 1.94 × 10−2 DALY, 6.08 × 10−5 species, and 2.47 × 103 MJ, respectively. The developed methodology is validated by applying it to the LCIA of vehicles, and the PVEI of three vehicles is ranked as follows: methanol vehicle (MV) > battery electric vehicle (BEV) > compressed natural gas vehicle (CNGV). The findings support the development of an LCIA method for China. The localization parameters supplement and improve the method of life cycle assessment in China, improve the scientificity of life cycle assessment results, and make the evaluation results more in line with China's actual conditions.

In-use NOx and black carbon emissions from heavy-duty freight diesel vehicles and near-zero emissions natural gas vehicles in California's San Joaquin Air Basin

This study assessed the real-world nitrogen oxide (NOx) and black carbon emissions from six goods movement heavy-duty diesel and compressed natural gas (CNG) vehicles operating in California's San Joaquin Valley and Sacramento regions. The diesel vehicles were all equipped with diesel oxidation catalysts (DOCs) and diesel particulate filters (DPFs), while two diesel vehicles were also equipped with selective catalytic reduction (SCR). All CNG vehicles were equipped with three-way catalysts and fitted with stoichiometric engines meeting the optional ultra-low NOx standard of 0.02 g/bhp-hr. Emissions measurements were conducted with a portable emissions measurement systems (PEMS) during typical goods movement vehicle operation. Black carbon emissions were about 3–7 times higher for the CNG vehicles than those of the DPF-equipped diesel vehicles. NOx emissions for the CNG vehicles were found at or below the optional NOx standard and on average 35 times lower NOx than those of the diesel vehicles. Diesel vehicle NOx hotspots were identified in urban areas and intersections with frequent stop-and-go driving events, whereas the CNG vehicles showed uniform NOx emissions rates along the route. The dispersion modeling results showed elevated NOx and PM emissions exposures to receptors in close proximity to the highway. Our findings suggest that real-time emissions measurements at the tailpipe provide more accurate population exposure assessments near freight corridors compared to utilizing trip-averaged emissions rates values in dispersion models. Under the present test conditions, >70 % of black carbon and NOx were emitted within disadvantaged communities, characterized by low-income minority populations.

Recommendations for emission testing and control of exhaust particles from a late technology mono-fuel CNG vehicle

The current study characterizes sub-23nm volatile and non-volatile particle emissions from a late technology (Euro 6d-temp) port-fuel injection vehicle, operating with compressed natural gas (CNG) as the primary fuel and E10 gasoline, as a reserve fuel. In part of the testing, gasoline was replaced with alkylate fuel or was doped with an octane booster (MMT), to understand fuel impacts better. Alkylate use resulted to the lowest total particle number (TPN) emission levels, below that of the Euro 6 limit. Increased sensitivity to primary sampling temperature was observed for CNG due to the high H/C ratio that causes water condensation in the exhaust. A minimum sampling temperature of 70oC is recommended to avoid water particles in CNG operation. The study also assessed the potential of a particle filter (PF) in controlling total and solid CNG exhaust particles. Results indicate effective PF filtration of non-volatile and volatile particles, especially in the sub-23 nm size range. Gasoline and CNG tests with PF suggest TPN10 emissions in the order of 5 × 1011 p/km, below the Euro 6 and Euro 7 regulation limit. Adopting PF as part of the aftertreatment layout would be required for control of solid and total particle emissions from CNG vehicles.

Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill

Compressed Natural Gas (CNG) is an affordable fuel with a higher octane number. However, older CNG kits without electronic controls have the potential to supply more fuel when driving downhill due to the vacuum in the intake manifold. Therefore, this article presents a development of a CNG control system that accommodates road inclination angles to improve fuel efficiency. Machine learning is involved in this work to process engine speed, throttle valve position, and road slope angle. The control system is designed to ensure reduced fuel consumption when the vehicle is operating downhill. The results showed that the control system increases fuel consumption by 25.7% when driving downhill which an inclination of 5ᵒ. The AFR increased from 17.5 to 22 and the CNG flow rate decreased from 17.7 liters/min to 13.8 liters/min which is promising for applying to CNG vehicles.

Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data

Abstract. This paper presents a bottom-up methodology to estimate multi-pollutant hourly gridded on-road traffic emission using advanced traffic flow and speed data for Delhi. We have used the globally adopted COPERT (Computer Programme to Calculate Emissions from Road Transport) emission functions to calculate the emission as a function of speed for 127 vehicle categories. At first, the traffic volume and congestion (travel time delay) relation is applied to model the 24 h traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in morning–evening rush hours. We estimated an annual emission of 1.82 Gg for PM (particulate matter), 0.94 Gg for BC (black carbon), 0.75 Gg for OM (organic matter), 221 Gg for CO (carbon monoxide), 56 Gg for NOx (oxides of nitrogen), 64 Gg for VOC (volatile organic compound), 0.28 Gg for NH3 (ammonia), 0.26 Gg for N2O (nitrous oxide) and 11.38 Gg for CH4 (methane) for 2018 with an uncertainty of 60 %–68 %. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (>50 %) across all pollutants except PM, BC and NOx, and within them the 2W (two-wheeler motorcycles) are the major contributors. Diesel-fuelled vehicles contribute most of the PM emission. Diesel and CNG (compressed natural gas) vehicles have a substantial contribution in NOx emission. This study provides very detailed spatiotemporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic-related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022).

Novel short-term national strategies to promote the use of renewable hydrogen in road transport: A life cycle assessment of passenger car fleets partially fuelled with hydrogen

This work presents an energy analysis combined with a comparative environmental life cycle assessment (LCA) of eight different passenger car fleets that use renewable hydrogen and a conventional fuel (natural gas or gasoline) under the same total energy input and the same hydrogen-to-mixture energy ratio. The fleets under comparison involve vehicles that use the two fuels separately or in a mixture. Using Italy as an illustrative country, this research work aims to help policy-makers implement well-supported strategies to promote the use of hydrogen in road transport in the short term. The proposed strategies achieve a carbon footprint reduction between 7 % and 35 % with respect to their conventional fleet benchmark. Within the current context, the results suggest the energy and environmental suitability of using hydrogen blends as short-term solutions, involving vehicles that require minor modifications with respect to current compressed natural gas vehicles and gasoline vehicles, while paving the way for pure hydrogen mobility.

Prediction of First Ply Failure of Composite Pressure Vessels Under Internal Pressure: A review

Composite pressure vessels (i.e. types III and IV) are widely used for compressed natural gas (CNG) vehicles, as storage cylinders to reduce the weight while maintaining high mechanical properties. These vessels can achieve 70-80% of weight saving, as compared to steel vessels (type I). So, prediction of first ply failure and burst pressure of these vessels is of great concern. Thus, this paper involved a review of literature regarding the first ply failure and burst pressure of composite pressure vessels (types III and IV). The review included the researches related to the simulation, mathematical modeling, and experimental analysis. The study focused on simulation-related research more than others due to the complexities of mathematical modeling of such problems in addition to the high cost of experimental tests. The results indicated that the stacking sequence of layers, vessel thickness and the type of selected composites were the main factors that mainly affect the vessel burst pressure performance. Accordingly, the optimization in the vessel structure (composite fabric architecture) parameters plays an important role in the performance of burst pressure. This in turn will lead to a high vessel durability, longer life-time and better prediction of burst pressure. Furthermore, the study showed that the prediction of first ply failure is more important than burst pressure knowledge of pressure vessels because it gives an initial prediction of vessel failure before the final failure occurrence. This in turn, may prevent the catastrophic damage of vessel.

System dynamics-based assessment of novel transport options adoption in India.

The adoption of novel transport options such as ethanol blended fuel (E85) vehicles, electric vehicles (EV), and compressed natural gas (CNG) vehicles to replace conventional petrol (gasoline) and diesel vehicles is not yet well understood. This work develops a system dynamics (SD) model to study the adoption of these novel options for private transport needs in India as a function of technology performance, cost, and other sector specific features. For EVs, expected growth in battery technology and the inconvenience due to lack of charging infrastructure are considered. Since ethanol production sector is still scaling up, model captures the inter-relationships between demand, supply, producer’s profit, and investment in capacity increase. The growth in compressed biogas (CBG) plants and inconvenience due to lack of gas refilling stations are considered for CNG vehicles. For petrol and diesel, the effect of demand on consumer prices and its effect on ownership cost is modelled. A multi-multinominal logit model is used to capture selection of transport option as a function of total ownership costs. Model simulations are performed till 2050, and quantify the adoption trends as well as resulting total greenhouse gas emissions considering life cycle perspective for all the technological options. Simulation results show that E85, EVs and CNG vehicles would constitute 34 % of total private vehicle stock by 2050, resulting in 668.75 million tonnes of CO_2 emissions. The targets set by the government for EV adoption and blending rate of ethanol will not be achieved, and significant improvement is costs and infrastructure are needed. Various policy options to improve adoption of new options are explored, identifying the technology development targets.Graphic abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s10098-022-02398-8.

Plug-in hybrid electric refuse vehicle routing problem for waste collection

Commercial waste collection is an essential service requiring efficient and reliable provision for customers. At the operational level, one of the most challenging problems is to design a set of refuse vehicle routes to collect waste from a set of bins. To be used multiple times, these vehicles must be emptied regularly throughout the day. This paper investigates a waste collection problem with a homogeneous fleet of plug-in hybrid electric refuse vehicles powered by two different power sources, i.e., electricity and compressed natural gas (CNG). In addition, realistic fuel consumption functions are used to estimate total energy requirements for each type of fuel, including refueling and recharging, and the detailed energy consumption along the path between two nodes of interest. We propose a Hybrid Threshold Acceptance (HTA) algorithm for this problem and denote it as the Hybrid Waste Collection Problem (HWCP). Extensive computational experiments confirm that the proposed HTA algorithm provides good results against current state-of-the-art algorithms designed for the electric vehicle routing problem. Out detailed computational results demonstrate the performance of our method considering either full or partial recharging, as well as the effect of different battery/tank capacities. Compared to the standard CNG or electric vehicles, we also show the benefits of using a fleet of hybrid electric refuse vehicles in terms of operational costs and total distance traveled.

Emissions of Euro 6 Mono- and Bi-Fuel Gas Vehicles

Compressed natural gas (CNG) and liquefied petroleum gas (LPG) are included in the group of promoted transport fuel alternatives in Europe. Most studies on emissions factors are based on old technology CNG and LPG fueled vehicles. Furthermore, there are not many data at low ambient temperatures, on-road driving, or unregulated pollutants, such as ammonia (NH3). In this study we measured the emissions of one Euro 6b CNG light commercial vehicle, one Euro 6b and one Euro 6d-Temp bi-fuel LPG passenger car, one Euro 6d-Temp bi-fuel CNG passenger car, and four Euro 6d-Temp CNG passenger cars. Tests included on-road testing and worldwide harmonized light vehicles test cycles (WLTC) in the laboratory with cold and hot engine, at 23 °C and −7 °C. The results showed 10–23% CO2 savings in gas modality compared to gasoline, lower CO and particle number emissions, and relatively similar total and non-methane hydrocarbons and NOx emissions. The ammonia emissions were high for all vehicles and fuels; higher than gasoline and diesel vehicles. The results also showed that, following the introduction of the real-driving emissions regulation, even though not applicable to the examined vehicles, Euro 6d-Temp vehicles had lower emissions compared to the Euro 6b vehicles.

Influencing factors of trucking companies willingness to shift to alternative fuel vehicles

Freight transportation is a manifestation of a vibrant economy, but it is also associated with negative externalities such as greenhouse gas emissions. To mitigate these impacts, freight vehicles using alternative fuels have been developed, but they are not widely adopted. Moreover, there is not much information on the factors that could incentivize trucking companies to adopt such vehicles, especially in emerging economies where diesel engines dominate the market. Using Colombia as a case study, this paper aims to evaluate the factors that influence businesses to shift towards acquiring trucks powered by alternative fuels, applying an econometric approach based on discrete choice models. Results suggest that demand for alternative fuel vehicles (AFVs) is highly sensitive to purchase costs, operational range, and environmental awareness. Hybrid fuel alternatives seem to be preferred over electric and compressed natural gas vehicles. The analysis is supplemented with the estimation of marginal substitution rates, elasticities, and the simulation of scenarios considering subsidies and tax exemptions, from which we identify implications and draw policy recommendations to promote the use of AFVs.

Scenario-based robust energy management of CCHP-based virtual energy hub for participating in multiple energy and reserve markets

The multi-energy systems can operate and schedule the distributed energy resources (DERs) locally to supply the multi-type loads and participate in the energy markets by aggregating the output power of DERs. Recently, the virtual energy hub (VEH) concept, derived from the energy hub and virtual power plant concepts, has been proposed for participating in the electrical and thermal markets. In this paper, robust self-scheduling of a VEH for participating in the energy and reserve markets is presented. The thermal reserve market is proposed to maintain the real-time thermal power balance and compensate for the effects of thermal demand uncertainty. Various types of DERs for supplying loads of each energy carrier are considered. Compressed natural gas (CNG) station is discussed and modeled linearly in the developed VEH to provide the fuel needed by Hybrid CNG and plug-in electric vehicles, which used the CNG as their secondary energy resource. A scenario-based robust approach is developed and presented to maximize the VEH profit and control the downside risk without adding surplus constraints. Finally, the proposed model is simulated in three case studies to evaluate its performance and effectiveness. • Self-scheduling of virtual energy hub for participating in the bilateral markets. • Thermal and electrical reserve markets. • Hybrid CNG and Plug-in electric vehicles. • CNG station for supplying needed CNG fuel. • Downside risk control via developed scenario-based robust method.

Life cycle assessment of methanol vehicles from energy, environmental and economic perspectives

As a new alternative fuel vehicle for energy reserve strategy, the development of methanol vehicles in China has been at the forefront. Completed pilot projects have demonstrated that methanol vehicles can effectively reduce fuel costs and pollutant emissions during driving. In addition to methanol vehicles, alternative fuel vehicles such as electric vehicles and compressed natural gas vehicles also maintain a sound development momentum in China. It is essential to understand which one has more advantages from sustainable development. This paper uses the Energy, Environment, and Economy (3E) evaluation method to analyze the energy consumption, environmental emission, and economy of methanol, electric, gas, and gasoline vehicles from the whole life cycle perspective. A comprehensive index evaluation model was constructed, and the development potential of the three alternative fuel vehicles was ranked under four different scenarios (energy-oriented, environment-oriented, economic-oriented, and equilibrium scenarios). This research shows that methanol vehicles have higher total energy consumption than gasoline vehicles in the whole life cycle. In terms of greenhouse gas emissions, compared with gasoline vehicles, methanol, and compressed natural gas vehicles decreased by 8.79 tons and 12.45 tons, respectively. At the same time, methanol vehicles have a better economic benefit than gasoline vehicles (37%), which is the same as the completed pilot projects. In addition, results also show that due to the advantages of low renovation cost and fuel price, the user’s cost of methanol vehicles is more down than blade electric vehicles, which makes them have better development potential compared with electric and compressed natural gas vehicles in the economic-oriented and equilibrium scenario. Therefore, methanol vehicles can be used as alternative fuel vehicles for long-term development in China.

Analysis of the application of power-to-gas (P2G) technology in the road transport system of South Africa

A shift towards new transport platforms has been proposed to mitigate transport GHG emissions in South Africa. This paper aims to develop a PtG model that simulates the production of alternative fuels for new transport platforms under the recently promulgated South African IRP 2019 energy framework. The study uncovers potential excess electricity of 13.1 TWh, from which 182 kton of hydrogen or 372 kton of methane can be produced from a 3.68 GW electrolyzer. The P2G technology can supply over and above the projected hydrogen fuel cell vehicles (HFCVs) fuel demands and only 19% of the compressed natural gas vehicles (CNGVs) fuel requirements. GHG emissions reductions of 1.64 MtCO2 and 346 kton CO2 can be attainable when the P2G products are utilized in FCVs and CNGVs, respectively. An LCOE of $0.18/kWh and $0.30/kWh can be expected at an electricity price of $0.04/kWh for hydrogen and methane production.

Comparison of the emission factors of air pollutants from gasoline, CNG, LPG and diesel fueled vehicles at idle speed

The emission factor (EF) is a parameter used to assess vehicle emissions. Many studies have reported EFs for vehicles in driving conditions. However, the idling emissions should not be neglected in characterizing actual vehicle emissions in congested large cities, where idling is very common on the road. Whereas, EF data for idling vehicles have scarcely been reported in the literature, let alone comparison of different fuels. In this study, the EFs of passenger cars burning four types of fuels - gasoline, compressed natural gas (CNG), diesel, and liquefied petroleum gas (LPG) were measured and compared. The emissions data for CO, CO2, unburned hydrocarbon (HC), and NO were recorded to calculate fuel-based EFs in units of g pollutants/kg fuel burned. EFs for CO, HC, and NO were compared for the four fuels. Diesel vehicles had the highest EF for CO, with an average value of 35.12 ± 21.37 g/kg fuel, due to low concentration of CO2 in lean operation compared to CO emission. CNG vehicles had the highest EF for HC, with an average value of 28.15 ± 11.97 g/kg fuel, due to high concentration of unburned methane gas due to slow CNG flame speed whereas diesel vehicles again had the highest EF for NO due to high temperature and pressure and freezing of NO decomposition reaction, with an average value of 12.07 ± 5.37 g/kg fuel. Further comparison was conducted to analyze the effects of two additional variables on EF: engine displacement volume and model/brand year. Only the gasoline-fueled vehicles showed an increase in EFs (for CO, HC and NO) with the vehicle age according to the model year. However, no clear correlation was observed for CNG, LPG, and diesel-fueled vehicles. Finally, the EF results were compared with those reported in the literature, which have been measured in various countries under both idling and non-idling conditions. Because the idling EFs were not substantially smaller than those under moving conditions, and vehicles spend substantial time idling in large cities, idling emissions should not be ignored in the emission inventories for large cities.

Particle Number Emissions of Gasoline, Compressed Natural Gas (CNG) and Liquefied Petroleum Gas (LPG) Fueled Vehicles at Different Ambient Temperatures

Compressed natural gas (CNG) and liquefied petroleum gas (LPG) are included in the group of promoted transport fuel alternatives for traditional fossil fuels in Europe. Both CNG and LPG fueled vehicles are believed to have low particle number and mass emissions. Here, we studied the solid particle number (SPN) emissions >4 nm, >10 nm and >23 nm of bi-fuel vehicles applying CNG, LPG and gasoline fuels in laboratory at 23 °C and sub-zero (−7 °C) ambient temperature conditions. The SPN23 emissions in CNG or LPG operation modality at 23 °C were below the regulated SPN23 limit of diesel and gasoline direct injection vehicles 6×1011 1/km. Nevertheless, the limit was exceeded at sub-zero temperatures, when sub-23 nm particles were included, or when gasoline was used as a fuel. The key message of this study is that gas-fueled vehicles produced particles mainly <23 nm and the current methodology might not be appropriate. However, only in a few cases absolute SPN >10 nm emission levels exceeded 6×1011 1/km when >23 nm levels were below 6×1011 1/km. Setting a limit of 1×1011 1/km for >10 nm particles would also limit most of the >4 nm SPN levels below 6×1011 1/km.