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There have only been a few wintertime studies of heavy-duty vehicle (HDV) NO

The maritime sector poses significant challenges in controlling the emission of harmful pollutants, such as particulate matter, and reducing their impact on coastal areas and the atmospheric environment. Efforts to regulate the sector necessitate new knowledge and methods to characterise the evolution and physicochemical transformation of maritime particle emissions dispersing in port areas. An experimental campaign at the Port of Rafina, Greece, was conducted with this in mind. In this paper, we report on the first multi-characteristic particle measurements, including particle number (PN), lung deposited surface area (LDSA), and black carbon (BC), performed at both land and sea using a novel instrument set-up mounted on an unmanned aerial vehicle (UAV). Land-based measurements showed that LDSA averages, which are influenced by particle number and size, increase up to 20 times above background levels as an emission plume progresses downwind, whereas BC concentrations, which are dominated by mass, are ~12 times higher than the background concentration. Ground and UAV-based particle comparisons showed that PN and LDSA measurements exhibit greater differences than BC relative to the plume's location. Ground-based sensors had ~50% lower LDSA and PN concentrations, whereas BC was about equal. The experimental observations are further substantiated by coupling a Gaussian plume dispersion model and a new computationally attractive approach, known as the Incompletely Stirred Reactor Network (ISRN) method, to predict the three-dimensional evolution of particle characteristics considering the effects of dilution, segregation, and physicochemical transformations, such as coagulation. Based on simplifying assumptions for the particle size distribution sources within the port area, the ISRN estimates suggest that the discrepancy between various metrics can be partly explained by coagulation, responsible for a non-linear increase in particle size, depending on the local level of dilution and mixing intensity, leading up to a ~25% decrease in PN and LDSA compared to BC. Combined, measurements and modelling highlight the effect of the sampling location and the importance of monitoring more than one particle metric to characterise particle evolution.

Emission measurements were collected from heavy-duty (HDVs) and medium-duty vehicles (MDVs) at the Peralta weigh station long-term measurement site near Anaheim, CA, in 2017. Two Fuel Efficiency Automobile Test units sampled elevated and ground-level exhaust vehicles totaling 2 315 measurements. HDVs (1844 measurements) exhibited historical reductions in fuel specific oxides of nitrogen (NOx) from the 2008 measurements (55%) with increased use of exhaust gas recirculation and selective catalytic reduction systems. However, as these technologies have aged, the in-use benefits have declined. Infrared % opacity measurements of tailpipe soot decreased 14% since 2012 with increased diesel particulate filter (DPF) use, DPF longevity, and fleet turnover. Sixty-three percent of the HDV fleet in 2017 was chassis model year 2011+ compared to only 12% in 2012. The observed MDV fleet (471 measurements) was 1.4 years older than the HDV fleet with average NOx 14% higher. A significant reduction in MDV NOx occurred ∼2 m...

Energy storage systems (ESS) are becoming increasingly important as high shares of renewable energy generation causes increased variability and intermittency of the power supply. With more renewable energy production, power markets are presented with possible overgeneration due to renewable sources being incompatible with electric loads and storage capacity. ESSs are viewed as underpinning technology which can support the energy system resilience in these areas. However, with various ESS technology options, configurations and performance characteristics it is difficult to compare the installed economic competitiveness across different technologies and desired applications in a standardized format. This work provides a novel economic assessment framework for evaluating the levelized cost of storage, annualized life-cycle cost and expected annual revenues of 10 grid-based and hydrogen-based ESSs based on their application potential. The economic assessment framework also includes a price-taker revenue optimization model with a stochastic analysis to determine uncertainties.

A future energy system for road transport requires optimised energy use and primary energy decarbonisation to achieve global CO2 reduction goals. Simultaneously decarbonising transport with other sectors of the economy places additional demands on limited low-carbon energy sources, requiring efficient processes within a fuel pathway from energy source to -energy use. Battery electric vehicles (BEVs) and fuel-cell electric vehicles (FCEVs) are low-carbon options that reduce tailpipe emissions, but differ in overall efficiency, associated carbon intensity, and cost. Current commercialised technologies, as well as theoretical maximums, are aggregated in a stochastic analysis to quantify the energy efficiency and CO2 differences for BEV and FCEV energy systems. Carbon capture and storage improves source-to-wheels CO2 intensity for hydrogen produced from steam methane reformation (27 gCO2/km with carbon capture and store and 140 gCO2/km without for light-duty FCEVs). Light-duty BEVs have a lower CO2 intensity (11 gCO2/km) using decarbonised grid electricity and are 65% more efficient than light-duty FCEVs using grid energy. These effects translate to heavy-good vehicles but with added complexity. In a maximised trailer volume scenario, electric and fuel-cell heavy-good vehicles have similar projected carbon intensities from a natural gas primary energy source, but electric heavy-good vehicle using conventional battery systems or an electric road system are able to achieve a 55% and 67% carbon reduction (gCO2/m3 km) compared to fuel-cell heavy-goods vehicles, respectively.

Air pollution and in particular PM2.5 emissions are a major problem worldwide. Road transport is a significant contributor to PM2.5 emissions in urban areas and as such it is important to understand and be able to accurately model the effects of vehicles on PM2.5 emissions. In this paper a computer vision algorithm is introduced which is able to extract vehicle trajectories from video footage. The algorithm has a 100% accuracy for overall total vehicle counting. Comparing the speeds predicted by the computer vision script to manually following a single vehicle feature on the video file, the average relative speed accuracy is 2.7% at a 1 Hz time resolution. Using these vehicle trajectories in an instantaneous vehicle emissions model and also as input to COPERT v5, tailpipe PM2.5 emissions were estimated and compared to on-road measurements. It was shown that a local sensor is not sufficient to determine vehicle tailpipe emissions due to the influence of meteorological conditions and other emission sources. Combining computer vision with an instantaneous vehicle emissions model is a useful method to evaluate changes in emissions caused by transport policies.

Two California heavy-duty fleets have been measured in 2013, 2015, and 2017 using the On-Road Heavy-Duty Measurement System. The Port of Los Angeles drayage fleet has increased in age by 3.3 model years (4.2–7.5 years old) since 2013, with little fleet turnover. Large increases in fuel-specific particle emissions (PM) observed in 2015 were reversed in 2017, returning to near 2013 levels, suggesting repairs and or removal of high emitting vehicles. Fuel-specific oxides of nitrogen (NOx) emissions of this fleet have increased, and NOx after-treatment systems do not appear to perform ideally in this setting. At the Cottonwood weigh station in northern California, the fleet age has declined (7.8 to 6 years old) since 2013 due to fleet turnover, significantly lowering the average fuel-specific emissions for PM (−87%), black carbon (−76%), and particle number (−64%). Installations of retrofit-diesel particulate filters in model year 2007 and older vehicles have further decreased particle emissions. Cottonwood f...

The University of Denver repeated its 2013 fuel specific gaseous and particle emission measurements on two California heavy-duty vehicle fleets. In 2015 1456 measurements at the Port of Los Angeles and 694 measurements at the Cottonwood weigh station in northern California were collected. The Port fleet changed little since 2013, increasing the average age (+1.8 years), accompanied by an increase in particle mass (PM) by +266% (0.03 ± 0.01 to 0.11 ± 0.01 gPM/kg of fuel) and black carbon (BC) by +300% (0.02 ± 0.003 to 0.08 ± 0.01 gBC/kg of fuel). Particle number (PN) also increased (1.5 × 1014 ± 2.5 × 1013 to 2.8 × 1014 ± 2.8 × 1013 PN/kg of fuel) by a smaller percentage (+87%). Chassis model year 2008 and 2009 vehicles currently dominate the fleet, accounting for the majority of these increases. The long-haul Cottonwood fleet decreased in fleet age (−0.6 model years), where half the decreases in fuel specific PM (−66%), BC (−65%), and PN (−19%) emissions are due to the newer fleet; an increased fraction o...

The University of Denver has collected on-road fuel specific vehicle emissions measurements in the Chicago area since 1989. This nearly 30 year record illustrates the large reductions in light-duty vehicle tailpipe emissions and the remarkable improvements in emissions control durability to maintain low emissions over increasing periods of time. Since 1989 fuel specific carbon monoxide (CO) emissions have been reduced by an order of magnitude and hydrocarbon (HC) emissions by more than a factor of 20. Nitric oxide (NO) emissions have only been collected since 1997 but have seen reductions of 79%. This has increased the skewness of the emissions distribution where the 2016 fleet's 99th percentile contributes ∼3 times more of the 1990 total for CO and HC emissions. There are signs that these reductions may be leveling out as the emissions durability of Tier 2 vehicles in use today has almost eliminated the emissions reduction benefit of fleet turnover. Since 1997, the average age of the Chicago on-road fleet has increased 2 model years and the percentage of passenger vehicles has dropped from 71 to 52% of the fleet. Emissions are now so well controlled that the influence of driving mode has been completely eliminated as a factor for fuel specific CO and NO emissions.

Two California heavy-duty fleets have been measured in 2013, 2015, and 2017 using the On-Road Heavy-Duty Measurement System. The Port of Los Angeles drayage fleet has increased in age by 3.3 model years (4.2-7.5 years old) since 2013, with little fleet turnover. Large increases in fuel-specific particle emissions (PM) observed in 2015 were reversed in 2017, returning to near 2013 levels, suggesting repairs and or removal of high emitting vehicles. Fuel-specific oxides of nitrogen (NO