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Traffic related non-tailpipe particulate matter emissions can rival the continuously decreasing tailpipe emissions in modern fleets. Non-tailpipe emissions have become the dominating source of traffic emissions in California already. This study measured ambient PM2.5 and PM10 concentrations at near road environments for two major highways in California, I-5 in Anaheim and I-710 in Long Beach. A total of 51 elements were measured from filter samples collected over four-hour intervals for a two-week period in the winter of 2020 before the statewide lockdown by the COVID-19 pandemic. Iron was the most abundant element in APM10 (differences between downwind and upwind sites), contrib-uting to 30 % and 24% of total measured elements in APM10 at the I-5 and I-710 locations, respectively. Iron correlated highly with other brake wear markers (e.g., titanium, copper, barium, manganese, and zirconium) with coefficient of determination (r2) ranging from 0.67 to 0.90 in both PM2.5 and PM10. Silicon was the second most abundant element, contributing to 21 % of total measured elements in APM2.5 and APM10. Silicon showed strong correlations with crustal elements such as calcium (r2 = 0.90), aluminum (r2 = 0.96), and potassium (r2 = 0.72) in APM2.5, and the correla-tions were even higher in APM10. Barium had a weak correlation with zinc, a commonly used maker for tire wear, with r2 = 0.63 and r2 = 0.11 for APM10 at the I-5 and I-710 locations respectively. Barium showed a positive correlation with crosswind speed and could serve as a good brake wear PM marker. Hourly PM2.5 concentrations of iron and zinc showed cyclic peaks from 0800 to 1000 hat I-5 during weekdays. Particle mass distributions showed peaks near-7 mu m, while particle number distributions showed peaks near 2.1 mu m and 6.5 mu m, respectively. This is consistent with brake wear and road dust size ranges previously reported.

A full 3D numerical simulation of the two-phase flow made up of (bio)diesel and particles, has been carried out to reproduce the deposition pattern of particles in a BOSCH automotive filter. From a probability density function (PDF), a simple Eulerian-Eulerian two-phase model is proposed for diesel and particles. The proposed formulation allows for a detailed description of the relationship between the velocity and size of the particles. A Brinkman-Darcy approximation has been considered for the flow through the filtering paper and is proved to be sufficient for the typical filter working conditions. The new tool is able to reproduce the deposition pattern shown by the used filters.

In recent years, renewable portfolio standards (RPS), which require a certain percentage of electricity sold to consumers to come from renewable resources, have been established by many state governments to mitigate emissions of greenhouse gases and air pollutants in the United States. Nevada's RPS set a target of 50% of electricity to come from renewable sources by 2030. By coupling the U.S. Environmental Protection Agency's AVoided Emissions and geneRation Tool (AVERT) and CO-Benefits Risk Assessment (COBRA) model, this study assesses potential emission reductions from fossil fuels owing to this requirement and regional health benefits via improved air quality, as well as how these benefits vary spatially under high and low projected electricity demands in 2030. Successful implementation of the RPS could produce health benefits equivalent to USD 3-8 million per year for Nevada residents and up to USD 164 million per year for the entire U.S. Nevada is ranked only 6th among states benefiting from the policy, while California and Washington obtain the most health benefits. There is also inequity among Nevada counties, partly caused by the county population and proximity to major fossil fuel power plants. Lowering electricity demands by 5% in Nevada would lead to a similar to 10% increase in health benefits. These findings should empower public support of RPS policies and energy conservation to reduce air pollution and public health inequity for the region.

Optical properties of particulate matter emitted by fires, pilot study