Quantifying the uncertainties in life cycle greenhouse gas emissions for UK wheat ethanol

This is the final version of the article. Available from IOP Publishing via the DOI in this record.Biofuels are increasingly promoted worldwide as a means for reducing greenhouse gas (GHG) emissions from transport. However, current regulatory frameworks and most academic life cycle analyses adopt a deterministic approach in determining the GHG intensities of biofuels and thus ignore the inherent risk associated with biofuel production. This study aims to develop a transparent stochastic method for evaluating UK biofuels that determines both the magnitude and uncertainty of GHG intensity on the basis of current industry practices. Using wheat ethanol as a case study, we show that the GHG intensity could span a range of 40-110 gCO2e MJ-1 when land use change (LUC) emissions and various sources of uncertainty are taken into account, as compared with a regulatory default value of 44 gCO2e MJ-1. This suggests that the current deterministic regulatory framework underestimates wheat ethanol GHG intensity and thus may not be effective in evaluating transport fuels. Uncertainties in determining the GHG intensity of UK wheat ethanol include limitations of available data at a localized scale, and significant scientific uncertainty of parameters such as soil N2O and LUC emissions. Biofuel polices should be robust enough to incorporate the currently irreducible uncertainties and flexible enough to be readily revised when better science is available. © 2013 IOP Publishing Ltd

Thermodynamic and experimental evaluation of a cloud chamber for ultrafine particle detection

Particle sensing based on condensational growth has long been the basis for robust nanoparticle measurement. Increasingly cloud chamber devices offer the potential for low-cost and portable measurement when operated semi-continuously with relatively small system volumes. Models based on isentropic and isenthalpic expansion are derived to predict the time evolution of temperature, saturation ratio, particle growth, and resultant light extinction in cloud chambers. A laboratory cloud chamber is fabricated and experiments using NaCl aerosol particles as the condensation nucleus are conducted to verify the models. The isentropic model, suggests that the temperature drops 0.6 ℃ within 40 ms, and accordingly, the saturation ratio reaches 1.04. For an aerosol with lognormal distribution, the predicted geometric mean diameter grows more than 5 times while the distribution narrows due to ∝1/p growth in the continuum regime. The performance of the cloud chamber agrees with the system physics and reference instruments, with relative error in measured extinction coefficient and signal intensities of ±5%. Detailed error propagation shows that the measured number concentrations agree well with reference instruments and the underlying theory. The lower limit of detection (~4×10^6 cm^-3) for the device is suitable for fire detection and emissions characterization

Quantifying the role of vehicle size, powertrain technology, activity and consumer behaviour on new UK passenger vehicle fleet energy use and emissions under different policy objectives

This paper quantifies the impacts of policy objectives on the composition of an optimum new passenger vehicle fleet. The objectives are to reduce individually absolute energy use and associated emissions of CO$_2$, NO$_x$ and PM$_{2.5}$. This work combines a top down, diversity-led approach to fleet composition with bottom-up models of 23 powertrain variants across nine vehicle segments. Changing the annual distance travelled only led to the smallest change in fleet composition because driving less mitigated the need to shift to smaller vehicles or more efficient powertrains. Instead, managing activity led to a ‘re-petrolisation’ of the fleet which yielded the largest reductions in emissions of NO$_x$ and PM$_{2.5}$. The hybrid approach of changing annual distance travelled and increasing willingness to accept longer payback times incorporates management of vehicle activity with consumers’ demand for novel vehicle powertrains. Combining these changes in behaviour, without feebates, allowed the hybrid approach to return the largest reductions in energy use and CO$_2$ emissions. Introducing feebates makes low-emitting vehicles more affordable and represents a supply side push for novel powertrains. The largest reductions in energy use and associated emissions occurred without any consumer behaviour change, but required large fees (£79–99 per g CO$_2$/km) on high-emitting vehicles and were achieved using the most specialised fleets. However, such fleets may not present consumers with sufficient choice to be attractive. The fleet with best diversity by vehicle size and powertrain type was achieved with both the external incentive of the feebate and consumers modifying their activity. This work has a number of potential audiences: governments and policy makers may use the framework to understand how to accommodate the growth in vehicle use with pledged reductions in emissions; and original equipment manufacturers may take advantage of the bottom-up, vehicle powertrain inputs to understand the role their technology can play in a fleet under the influence of consumer behaviour change, external incentives and policy objectives.The authors acknowledge the Engineering and Physical Sciences Research Council funding provided for this work under the Centre for Sustainable Road Freight Transport (EP/K00915X/1) and the Energy Efficient Cities Initiative (EP/ F034350/1)

Measuring ultrafine aerosols by direct photoionization and charge capture in continuous flow

Direct ultraviolet (UV) photoionization enables electrical charging of aerosol nanoparticles with- out relying on the collision of particles and ions. In this work, a low-strength electric field is applied during particle photoionization to capture charge as it is photoemitted from the par- ticles in continuous flow, yielding a novel electrical current measurement. As in conventional photocharging-based measurement devices, a distinct electrical current from the remaining pho- tocharged particles is also measured downstream. The two distinct measured currents are proportional to the total photoelectrically active area of the particles. A three dimensional numerical model for particle and ion (dis)charging and transport is evaluated by comparing simulations of integrated electric currents with those from charged soot particles and ions in an experimental photoionization chamber. The model and experiment show good quantitative agreement for a single empirical constant, KcI, over a range of particle sizes and concentrations providing confidence in the theoretical equations and numerical method used

Real-world environmental impacts from modern passenger vehicles operating in urban settings

Real-world testing of a set of modern vehicles show most petrols meet their Euro standards for nitrous oxides (NO$_{x}$), while most diesel vehicles exceed them. However, that some diesel vehicles met their Euro standards implies exceedances are not peculiar to the fuel. Likewise, the compliance of the tested petrol vehicles with the standard does not mean all petrol vehicles do. Engine maps were synthesised which reproduced trip level emissions to within 10% of that gathered under real-world driving conditions. Average velocity alone, such as what is used in COPERT, is a poor predictor of emissions. Stepwise linear models showed NO$_{x}$ emissions could be predicted accurately by incorporating other metrics, such as maximum deceleration and the variance of velocity over the driving cycle. The models were validated on three driving cycles where all vehicles met their Euro standards, save Euro 6 diesel vehicles on the US highway cycle. COPERT overestimated NO$_{x}$ from all vehicles. More work is required to combine driving cycle metrics with vehicle characteristics, such as mass and peak engine torque, to identify the conditions under which vehicles exceed their Euro limits.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by WIT Press

Using portable emissions measurement systems (PEMS) to derive more accurate estimates of fuel use and nitrogen oxides emissions from modern Euro 6 passenger cars under real-world driving conditions

Data from portable emissions measurement systems (PEMS) and other sources have allowed the discrepancy between type approval and real-world fuel economy and nitrogen oxides (NOx) emissions to be both identified and quantified. However, a gap in the knowledge persists because identifying this discrepancy does not allow us to predict real-world fuel economy and emissions accurately. We address this gap in the knowledge using a bottom-up approach: a PEMS is used across a range of Euro 6 petrol and diesel vehicles, from which internally-consistent powertrain models are derived. These training vehicles are simulated over 20 real-world and regulated driving cycles. 26 metrics representing driving, vehicle and ambient characteristics are used to develop quantile regression (QR) models for three vehicle groups: direct-injection petrol vehicles with three way catalysts; diesel vehicles with selective catalytic reduction; and diesel vehicles with lean NOx traps. 95% prediction intervals are used to assess the predictive accuracy of the QR models from a set of validation vehicles. Across the vehicle groups, QR models for both fuel economy and NOx emissions depended on the dynamics of the driving cycles more than the engine characteristics or ambient conditions. The 95% prediction interval for fuel economy enclosed most of the observed values from the PEMS test, with similar prediction error to COPERT in most cases. The bene ts of the QR approach were more pronounced for NOx emissions, where the majority of PEMS observed data was enclosed in the 95% PI and median prediction error was up to two times lower than COPERT.EPSR

Unsteady bipolar diffusion charging in aerosol neutralisers: A non-dimensional approach to predict charge distribution equilibrium behaviour

High total particle concentration and small particle size are common features of aerosols encountered in the field of aerosol-based nanotechnology that can potentially lead to non-equilibrium issues in the neutraliser upon SMPS characterisation, resulting in large errors in size distribution measurements. Experiments show that the commonly assumed n⋅tn⋅t product rule fails to predict equilibrium behaviour in aerosol neutralisers under these conditions, as it does not capture the influence of total particle concentration and particle size. The aim of this work is to provide an equilibrium indicator that identifies situations where equilibrium is not reached in the neutraliser as a function of residence time, ion generation rate, total particle concentration, and particle size. Bipolar diffusion charging equations are solved numerically in a one-dimensional model first, and a non-dimensional analysis of the results is carried out in order to map equilibrium behaviour as a function of two non-dimensional groups, the non-dimensional ion concentration, and the non-dimensional neutraliser residence time. Solving the three-dimensional form of the charging equations in the geometry of the neutraliser then enables one to find good agreement in terms of equilibrium behaviour between experiments and predictions from the non-dimensional model. The three-dimensional model captures the complexity of the physics of unsteady particle charging inside a neutraliser. This work then discusses this as a new approach to non-equilibrium behaviour prediction in neutralisers, providing a tool supplementing the n⋅t product rule that can be used in practice.The authors express their thanks to Cambustion ltd. for the loan of the TSI 3077A neutraliser. The project was supported by the EPSRC Cambridge NanoDTC, EP/G037221/1, the Cambridge Home EU Scholarship Scheme (CHESS Fund) and the Schiff Foundation Studentships.This is the final published version. It was first made available by Elsevier at http://www.sciencedirect.com/science/article/pii/S0021850215000440#

Engine maps of fuel use and emissions from transient driving cycles

Air pollution problems persist in many cities throughout the world, despite drastic reductions in regulated emissions of criteria pollutants from vehicles when tested on standardised driving cycles. New vehicle emissions regulations in the European Union and United States require the use of OBD and portable emissions measurement systems (PEMS) to confirm vehicles meet specified limits during on-road operation. The resultant in-use testing will yield a large amount of OBD and PEMS data across a range of vehicles. If used properly, the availability of OBD and PEMS data could enable greater insight into the nature of real-world emissions and allow detailed modelling of vehicle energy use and emissions. This paper presents a methodology to use this data to create engine maps of fuel use and emissions of nitrous oxides (NO$_x$), carbon dioxide (CO$_2$) and carbon monoxide (CO). Effective gear ratios, gearbox shift envelopes, candidate engine maps and a set of vehicle configurations are simulated over driving cycles using the ADVISOR powertrain simulation tool. This method is demonstrated on three vehicles – one truck and two passenger cars – tested on a vehicle dynamometer and one driven with a PEMS. The optimum vehicle configuration and associated maps were able to reproduce the shape and magnitude of observed fuel use and emissions on a per second basis. In general, total simulated fuel use and emissions were within 5% of observed values across the three test cases. The fitness of this method for other purposes was demonstrated by creating cold start maps and isolating the performance of tailpipe emissions reduction technologies. The potential of this work extends beyond the creation of vehicle engine maps to allow investigations into: emissions hot spots; real-world emissions factors; and accurate air quality modelling using simulated per second emissions from vehicles operating in over any driving cycle.Engineering and Physical Sciences Research Council (Centre for Sustainable Road Freight Transport (EP/K00915X/1), Energy Efficient Cities Initiative (EP/ F034350/1)

Can UK passenger vehicles be designed to meet 2020 emissions targets? A novel methodology to forecast fuel consumption with uncertainty analysis

Vehicle manufacturers are required to reduce their European sales-weighted emissions to 95 g CO2/km by 2020, with the aim of reducing on-road fleet fuel consumption. Nevertheless, current fuel consumption models are not suited for the European market and are unable to account for uncertainties when used to forecast passenger vehicle energy-use. Therefore, a new methodology is detailed herein to quantify new car fleet fuel consumption based on vehicle design metrics. The New European Driving Cycle (NEDC) is shown to underestimate on-road fuel consumption in Spark (SI) and Compression Ignition (CI) vehicles by an average of 16% and 13%, respectively. A Bayesian fuel consumption model attributes these discrepancies to differences in rolling, frictional and aerodynamic resistances. Using projected inputs for engine size, vehicle mass, and compression ratio, the likely average 2020 on-road fuel consumption was estimated to be 7.6 L/100 km for SI and 6.4 L/100 km for CI vehicles. These compared to NEDC based estimates of 5.34 L/100 km (SI) and 4.28 L/100 km (CI), both of which exceeded mandatory 2020 fuel equivalent emissions standards by 30.2% and 18.9%, respectively. The results highlight the need for more stringent technological developments for manufacturers to ensure adherence to targets, and the requirements for more accurate measurement techniques that account for discrepancies between standardised and on-road fuel consumption.NEDC data measurements were supplied by CAP Consulting. The authors are also grateful to the Energy Efficient Cities Initiative and the EPSRC (EP/F034350/1) for funding this work.This is the author accepted mansucript. The final version is available via Elsevier at http://dx.doi.org/10.1016/j.apenergy.2015.03.04