10.6 Paved Road Dust

Categories 1759, 1760, 1761, and 1762

10.6.1 Introduction

Paved road dust, the fugitive dust particles raised from the movements of motor vehicles on paved public road surfaces, are discussed in this section. Depending on the road types, the fugitive dust were accounted for by the four categories below. It’s a major source of particulate matter (PM) in Bay Area and was considered as non-permitted area source.

Category # Description Classification
1759 Paved Freeways Area
1760 Paved Major Roads Area
1761 Paved Collectors Area
1762 Paved Local Streets Area

10.6.2 Methodology

The methodology for estimating fugitive particulate emissions from vehicular travel on paved roads was updated in U.S. EPA’s latest AP-42 document448. The methodology was adapted and refined by CARB for developing statewide emissions inventory449.

The District has developed the road dust emissions primarily based on CARB’s methodology and underlying data but with updates as necessary and appropriate. A brief description is given in the remaining of the section.

(a) Activity Data / Throughput

The activity data for the paved road dust categories are vehicle miles traveled (VMT). The county-specific VMT of each calendar year from 1990-2040 were modeled by CARB’s EMission FACtor (EMFAC) model450. The most up-to-date version of the model at the time of this work is EMFAC2017, which only covers year 2000 and after. For years between 1990-1999, VMT data generated by the EMFAC2011 model in the District’s archive were used.

(b) Road Type Distribution / Fractions

The VMT data from EMFAC model cover all paved public roadways in each county. The county-specific travel fractions for each roadway type derived by CARB from 2008 data of California Department of Transportation (Caltrans) Highway Performance Monitoring Systems (HPMS) were used to split VMT into each roadway type2.

(c) Emission Factors

Emission factors are a function of fleet average vehicle weight, silt loading and precipitation as shown in the following equation:

\[ E = k \left({sL}\right)^{0.91} \times \left({W}\right)^{1.02} \times \left(1 - \frac{P}{4N}\right) \] where:

  • \(E\) is the particulate emission factor in pounds per vehicle miles traveled (VMT);

  • \(k\) is the particle size multiplier used to compute PM10 (0.0022 lb/VMT);

  • \(sL\) is the roadway silt loading in grams per square meter;

  • \(W\) is the fleet average vehicle weight in tons;

  • \(P\) is the number of “wet” days with at least 0.254 mm (0.01") of precipitation during the annual averaging period; and

  • \(N\) is the number of days in the annual averaging period (365 days per year).

Except for the fleet average vehicle weight, all parameters were adopted from CARB methodology document. The number of wet days (\(N\)) for each county was acquired from the most appropriate meteorological station for that county by CARB.

Default silt loading for freeways were adopted from U.S.EPA AP-42 document1 while the silt loading for the remaining road types were derived from 42 California-specific silt measurements conducted by Midwest Research Institute (MRI), University of California, Davis (UCD) and University of California, Riverside (UCR) as summarized in CARB’s methodology document2.

The average vehicle weight (\(W\)) was calculated for each county and year based on the vehicle weight of each vehicle class using the fleet mix as weighting factors. The fleet mix is the VMT fractions of each vehicle class in the entire fleet derived from EMFAC VMT data. It varies among counties and years.

(d) Control Factors

The District doesn’t regulate emissions from on-road mobile sources directly. No control factors were applied as currently there is no active regulations in the District or at State level to mitigate the PM emissions from paved road dust.

(e) Speciation

The equation in the subsection (c) above only estimates emission factor for PM10. CARB’s chemical speciation profile # 471 based on paved road dust sampling conducted by CARB and MRI were used to estimate PM and PM2.5451. According to the profile, PM10 is 45.72% of PM while PM2.5 is 15% of PM10.

(f) Sample Calculations

Step by step sample calculation was provided in CARB’s methodology document2. See details in the relevant section.

10.6.3 Changes in Methodology

The following changes has been made compared with previous base year inventory:

  1. Process change. Emissions were estimated for each year, county and road type directly as detailed inputs became available. Previous base year inventory only estimates emissions of base year 2011 for the entire Bay Area and then applied county fractions, road type fractions, growth profiles to populate emissions by county, road type and year.

  2. Equation/Parameter changes.

  1. The latest emission factor equation from USEPA’s AP-42 document was adopted.

  2. The silt loading for freeway/expressway of 0.02 has been corrected to 0.015 according to CARB’s methodology document.

  3. Instead of using the default value of 2.4 tons, the fleet average vehicle weight (\(W\)) was calculated for each county and year based on its specific fleet mix, which reflects the impact from fleet turnover across counties and over time.

  1. Instead of using the annual growth (less than 0.1%) derived from Metropolitan Transportation Commission (MTC) roadways center line miles (CLM) data to predict future emissions, the District calculated the emissions directly based on future year VMT predicted by EMFAC model.

10.6.4 Emissions

A summary of emissions by category, county, and year are available via the associated data dashboard for this inventory publication. Paved road dust is the largest source of PM10 and a major source of PM2.5. With close proximity to urban population, its impact become more and more significant as the PM emissions of other major sources, such as tailpipe emissions from on-road vehicles, continue to decrease due to stringent regulations or advanced technologies.

10.6.6 Uncertainties

There are known limitations with the current method for estimating emission from paved road dust. The parameters used are not always based on data specific to Bay Area or up to date. For example, the silt loading factors are statewide default values averaged from samples taken outside of Bay Area back in late 1990s. A Monte-Carlo analysis suggested that there could be a 50% of uncertainty introduced by the parameters. More importantly, the emission factor equation is an empirical expression of a regression model based on 83 profile emission tests conducted more than a decade ago and at low or moderate vehicle traveling speed, i.e., 1 - 55 miles per hour (mph). It has not been verified against high speed or high traffic volume conditions. Recognizing the unknown magnitude of uncertainty with the current emission factor equation, Caltrans is leading a research program to conduct a new road dust emissions measurement study and develop more reasonable and realistic road dust emission factor equation(s). Along with USEPA and CARB, the District is working with Caltrans closely to monitor the research progress and will review the final reports once it’s ready. The program products will then be used to improve the future emission estimate method for paved road dust.

10.6.7 Contact

Author: Yuan Du

Reviewer: Abhinav Guha, Tan Dinh

Last Update: November 06, 2023

10.6.8 References & Footnotes

  1. USEPA. January 2011. AP-42, Fifth Edition Compilation of Air Pollutant Emissions Factors, Volume 1: Stationary Point and Area Sources, Section 13.2.1, Paved Roads. https://www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-air-emissions-factors#5thed↩︎

  2. CARB. March 2018. 7.9 Entrained Road Travel, Paved Road Dust. https://ww3.arb.ca.gov/ei/areasrc/fullpdf/full7-9_2018.pdf↩︎

  3. CARB. MSEI - Modeling Tools - EMFAC Software and Technical Support Documentation. https://ww2.arb.ca.gov/our-work/programs/mobile-source-emissions-inventory/msei-modeling-tools-emfac-software-and↩︎

  4. CARB. Speciation Profiles Used in CARB Modeling. https://ww2.arb.ca.gov/speciation-profiles-used-carb-modeling↩︎