May 2003 • NREL/SR-540-33797 

R.E. Morris and Y. Jia 

ENVIRON International Corporation 

Novato, California 

Impact of Biodiesel Fuels on Air 

Quality and Human Health: 

Task 4 Report 

Impacts of Biodiesel Fuel Use on PM 

National Renewable Energy Laboratory 

1617 Cole Boulevard 

Golden, Colorado 80401-3393 

NREL is a U.S. Department of Energy Laboratory 

Operated by Midwest Research Institute • Battelle • Bechtel 

Contract No. DE-AC36-99-GO10337 
May 2003 • NREL/SR-540-33797 

Impact of Biodiesel Fuels on Air 

Quality and Human Health: 

Task 4 Report 

Impacts of Biodiesel Fuel Use on PM 

R.E. Morris and Y. Jia 

ENVIRON International Corporation 

Novato, California 

NREL Technical Monitor: K.S. Tyson and R. McCormick

Prepared under Subcontract No. AXE-9-29079-01

National Renewable Energy Laboratory 

1617 Cole Boulevard 

Golden, Colorado 80401-3393 

NREL is a U.S. Department of Energy Laboratory 

Operated by Midwest Research Institute • Battelle • Bechtel 

Contract No. DE-AC36-99-GO10337 
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ES-1

EXECUTIVE SUMMARY 

BACKGROUND

Biodiesel fuels have been investigated for a number of reasons, such as an extender for 

petroleum-based fuels derived from a domestic renewable energy source. But lately the primary 

interest is the potential for a more environmentally benign fuel. The potential for exhaust 

emission reductions and reductions in emissions toxicity have the most interest. Several studies 

have shown that large reductions in hydrocarbon, particulate, and carbon monoxide emissions 

are expected from its use either as a neat fuel or as a blend with petroleum-derived fuels. 

There are several areas in the United States that are currently in nonattainment for particulate 

matter of 10 μm or less (PM10). In addition, there is a new fine particulate matter (PM2.5) which 

may result in new areas being in nonattainment for PM. Biodiesel fuel use is estimated to reduce 

several precursors to PM (e.g., PM, SO2, and VOC) and increase others (NOx). Thus, the net 

affect of biodiesel fuel use on ambient PM levels is unclear based on analyzing changes in 

emissions alone, so it as assessed using air quality modeling. 

APPROACH 

The South Coast (Los Angeles) Air Basin (SoCAB) region of southern California was selected to 

assess the effects of biodiesel fuel use because it is currently a PM10 nonattainment area and 

ammonium nitrate (for which NOx is a precursor) is a major component of the PM. Thus, the 

SoCAB would provide a conservative (i.e., tending toward overstatement) assessment of the 

impacts of biodiesel fuel on PM. The CAMx photochemical grid model was applied to the 

SoCAB for an April 1998 through March 1999 annual modeling period to estimate the effects a 

100% and 50% penetration of an 20%/80% biodiesel/diesel fuel mixture (B20) in the Heavy 

Duty Diesel Vehicle (HDDV) fleet would have on PM levels. The effects of biodiesel fuel use 

was separately assessed for particulate sulfate, nitrate, ammonium, elemental carbon (EC), 

organic carbon (OC), other fine particulate, coarse matter, total PM10 and PM2.5 mass, and 

exposure to PM10 and PM2.5. 
 

ES-2

RESULTS 

Table ES-1 summarizes the estimated maximum increases and decreases in total PM10 and PM2.5

mass and PM components due to a 100% penetration of a B20 fuel in the HDDV fleet. The 

results for the 50% B20 penetration are approximately half of the 100% B20 penetration 

scenario. The increases and decreases of the PM due to the biodiesel fuel use are extremely 

small and should be considered not significant. The largest effect is for particulate nitrate that 

exhibits both small increases and decreases due to the B20 fuel. The decreases in nitrate occur in 

the more populated portions of the SoCAB, whereas the increases occur east of the SoCAB in 

the desert. The 100% B20 biodiesel fuel scenario is estimated to reduce exposure to annual and 

24-hour exceedances of the PM10 standard by 4% and 7%, respectively over use of a standard 

diesel fuel. 

Table ES-1. Estimated maximum increases and decreases in PM concentrations (μg/m3) in the 

SoCAB due to a 100% penetration of a B20 biodiesel fuel in the HDDV fleet. 

Annual Average Maximum 24-Hour Average 

PM Species 

Maximum 

Increase 

Maximum 

Decrease 

Maximum 

Increase 

Maximum 

Decrease 

Sulfate 0.00 -0.03 0.00 -0.07 

Nitrate +0.04 -0.09 +0.58 -1.12 

Ammonium +0.01 -0.03 +0.15 -0.34 

EC 0.00 -0.06 0.00 -0.10 

OC 0.00 -0.15 0.00 -0.27 

Other PFIN 0.00 -0.01 0.00 -0.01 

Other PCRS 0.00 -0.01 0.00 -0.01 

PM10 Mass +0.04 -0.31 +0.62 -1.61 

PM2.5 Mass +0.04 -0.30 +0.62 -1.61 
i

TABLE OF CONTENTS 

Page 

EXECUTIVE SUMMARY................................................................................................... ES-1

Background..........................................................................................................................ES-1 

Approach ............................................................................................................................ES-1 

Results ............................................................................................................................ES-2 

1. INTRODUCTION................................................................................................................ 1-1 

Background............................................................................................................................ 1-1 

Overview of Approach........................................................................................................... 1-2 

2. EMISSION INVENTORIES FOR PM MODELING 

 OF BIODIESEL FUEL IMPACTS.............................................................................. 2-1 

Temporal Allocation and Speciation ..................................................................................... 2-1 

Emission Scenarios ................................................................................................................ 2-1 

Emission Summaries.............................................................................................................. 2-2 

Spatial Distribution of Emissions .......................................................................................... 2-4 

3. PM CONCENTRATION MODELING RESULTS ......................................................... 3-1 

PM Species Impacts............................................................................................................... 3-1 

4. SUMMARY AND CONCLUSIONS .................................................................................. 4-1 

 Biodiesel Fuel Impacts on PM Concentrations...................................................................... 4-1 

 Biodiesel Fuel Impacts on PM Exposure and Dosage ........................................................... 4-2 

 Conclusions............................................................................................................................ 4-3 

REFERENCES.......................................................................................................................... R-1 
ii

TABLES 

Table 2-1. Average change in HDDV mass emissions due to use 

 of a biodiesel fuel over use of a standard diesel fuel ........................................... 2-2 

Table 2-2. Summary of domain-wide total on-road diesel, area plus 

 point sources, and total NOx, VOC, CO, SOx, and PM 

 emissions in the SoCAB (tons per day) for the 1997 

 Standard Diesel Base Case and 1997 100% and 50% 

 Penetration of a B20 Biodiesel fuel scenarios. .................................................... 2-3 

Table 4-1. Estimated maximum increases and decreases in 

 PM concentrations(μ g/m3

) in the SoCAB due to a

 100% penetration of a B20 biodiesel fuel in the HDDV fleet. ............................ 4-2 

Table 4-2. Summary of integrated exposure metrics for annual and 

 24-hour PM10 and PM2.5 concentrations (μg/m3

) exceeding the NAAQS........... 4-3 

FIGURES 

Figure 2-1. Total NOx emissions (tons per day) and change in 

 NOx emissions due to the 100% B20 biodiesel fuel 

 scenario for a typical 1998 summer day in the SoCAB....................................... 2-5 

Figure 2-2. Total VOC emissions (tons per day) and change in 

 VOC emissions due to the 100% B20 biodiesel fuel 

 scenario for a typical 1998 summer day in the SoCAB....................................... 2-6 

Figure 2-3. Total CO emissions (tons per day) and change in CO 

 emissions due to the 100% B20 biodiesel fuel scenario 

 for a typical 1998 summer day in the SoCAB ..................................................... 2-7 

Figure 2-4. Total PM emissions (tons per day) and change in 

 PM emissions due to the 100% B20 biodiesel fuel 

 scenario for a typical 1998 summer day in the SoCAB....................................... 2-8

Figure 3-1. Estimated annual average sulfate concentrations (μg/m3

) 

 for the 1998/1999 standard diesel base case simulations (top) 

 and differences in annual average sulfate concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case). ....................................................................... 3-3 

Figure 3-2. Estimated maximum 24-hour average sulfate concentrations 

 (μg/m3

) for the 1998/1999 standard diesel base case simulations 

 (top) and differences in maximum 24-hour average sulfate 

 concentrations between the Base Case and 100% B20 

 biodiesel emissions scenarios (100% B20-Base Case)........................................ 3-4 

Figure 3-3. Estimated annual average particulate nitrate concentrations 

 (μg/m3

) for the 1998/1999 standard diesel base case simulations 

 (top) and differences in annual average particulate nitrate 

 concentrations between the Base Case and 100% B20 

 biodiesel emissions scenarios (100% B20-Base Case)........................................ 3-7
iii

Figure 3-4. Estimated maximum 24-hour average particulate nitrate 

 concentrations (μg/m3) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 maximum 24-hour average particulate nitrate concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case). ....................................................................... 3-8

Figure 3-5. Estimated annual average ammonium concentrations 

 (μg/m3

) for the 1998/1999 standard diesel base case 

 simulations (top) and differences in annual average 

 ammonium concentrations between the Base Case and 

 100% B20 biodiesel emissions scenarios (100% B20-Base Case).................... 3-10 

Figure 3-6. Estimated maximum 24-hour average ammonium 

 concentrations (μg/m3

) for the 1998/1999 standard diesel 

 base case simulations (top) and differences in maximum 

 24-hour average ammonium concentrations between the 

 Base Case and 100% B20 biodiesel emissions scenarios 

 (100% B20-Base Case)...................................................................................... 3-11 

Figure 3-7. Estimated annual average Elemental Carbon (EC) 

 concentrations (μg/m3

) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 annual average Elemental Carbon (EC) concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case) ...................................................................... 3-13 

Figure 3-8. Estimated maximum 24-hour average Elemental Carbon 

 (EC) concentrations (μg/m3

) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 maximum 24-hour average Elemental Carbon (EC) 

 concentrations between the Base Case and 100% B20 

 biodiesel emissions scenarios (100% B20-Base Case)...................................... 3-14 

Figure 3-9. Estimated annual average Organic Carbon (OC) 

 concentrations (μg/m3

) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 annual average Organic Carbon (OC) concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case). ..................................................................... 3-15 

Figure 3-10. Estimated maximum 24-hour average Organic Carbon 

 (OC) concentrations (μg/m3

) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 maximum 24-hour average Organic Carbon (OC) 

 concentrations between the Base Case and 100% B20 

 biodiesel emissions scenarios (100% B20-Base Case)...................................... 3-16 

Figure 3-11. Estimated annual average other fine particulate 

 concentrations (μg/m3

) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 annual average other fine particulate concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case). ..................................................................... 3-18 
iv

Figure 3-12. Estimated maximum 24-hour average other fine 

 particulate concentrations (μg/m3) for the 1998/1999 

 standard diesel base case simulations (top) and differences 

 in maximum 24-hour average other fine particulate 

 concentrations between the Base Case and 100% B20 

 biodiesel emissions scenarios (100% B20-Base Case)...................................... 3-19 

Figure 3-13. Estimated annual average coarse particulate matter 

 concentrations (μg/m3

) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 annual average coarse particulate matter concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case) ...................................................................... 3-20 

Figure 3-14. Estimated maximum 24-hour average coarse 

 particulate matter concentrations (μg/m3

) for the 

 1998/1999 standard diesel base case simulations (top) 

 and differences in maximum 24-hour average coarse 

 particulate matter concentrations between the Base Case 

 and 100% B20 biodiesel emissions scenarios (100% B20-Base Case). ............ 3-21 

Figure 3-15. Estimated annual average PM10 concentrations 

 (μg/m3) for the 1998/1999 standard diesel base case 

 simulations (top) and differences in annual average 

 PM10 concentrations between the Base Case and 100% 

 B20 biodiesel emissions scenarios (100% B20-Base Case). ............................. 3-23 

Figure 3-16. Estimated maximum 24-hour average PM10 concentrations 

 (μg/m3) for the 1998/1999 standard diesel base case 

 simulations (top) and differences in maximum 24-hour 

 average PM10 concentrations between the Base Case and 

 100% B20 biodiesel emissions scenarios (100% B20-Base Case).................... 3-24 

Figure 3-17. Estimated annual average fine particulate (PM2.5) 

 concentrations (μg/m3) for the 1998/1999 standard 

 diesel base case simulations (top) and differences in 

 annual average fine particulate (PM2.5) concentrations 

 between the Base Case and 100% B20 biodiesel emissions 

 scenarios (100% B20-Base Case). ..................................................................... 3-26 

Figure 3-18. Estimated maximum 24-hour average fine particulate 

 matter (PM2.5) concentrations (μg/m3

) for the 1998/1999 

 standard diesel base case simulations (top) and differences 

 in maximum 24-hour average fine particulate matter 

 (PM2.5) concentrations between the Base Case and 100% 

 B20 biodiesel emissions scenarios (100% B20-Base Case). ............................. 3-27 
1-1 

1. INTRODUCTION 

BACKGROUND

Biodiesel fuels have been investigated for a number of reasons, such as an extender for 

petroleum-based fuels derived from a domestic renewable energy source. But lately the primary 

interest is the potential for a more environmentally benign fuel. One potential benefit of 

biodiesel is that it can biologically degrade, making spills and leaks less of a concern. However, 

the potential for exhaust emission reductions and reductions in emissions toxicity are of the most 

interest. Several studies have shown that large reductions in hydrocarbon, particulate, and 

carbon monoxide emissions are expected from its use either as a neat fuel or as a blend with 

petroleum-derived fuels. 

There have been several studies regarding the effects of biodiesel fuels on exhaust emissions of 

NOx, VOC, CO, and particulate matter (PM). Almost all of these studies have examined 

emissions from heavy-duty diesel vehicle (HDDV) engines. However, the effects of biodiesel 

use on ambient air quality have not been quantified. Thus, the National Renewable Energy 

Laboratory (NREL) has retained ENVIRON International Corporation to estimate the air quality 

and resultant health effect impacts from the use of biodiesel fuels in several cities in the U.S. 

Effects of Biodiesel Fuel on Particulate Matter 

Currently there is a Federal health based National Ambient Air Quality Standard (NAAQS) for 

particulate matter with a mean geometric diameter of 10 microns or less (PM10). There is also a 

new fine particulate standard for PM of 2.5 microns or less (PM2.5). The Federal PM10 standard 

consists of a 24-hour standard that is basically the fourth highest value in three years with a 150 

μg/m3 threshold and an annual standard with a 50 μg/m3 threshold. The fine particulate standard 

thresholds are 65 and 15 μg/m3 for the 24-hour and annual time frames, respectively. 

PM consists of many different compounds some of that are interrelated with common set of 

precursors and processes, others that are not. The main components of PM and their primary 

sources are as follows: 

SO4 Sulfate (SO4) that is formed secondarily from SO2 emissions; 

NO3 Ammonium Nitrate (NH4NO3) that is formed from NOx and ammonia emissions; 

EC Elemental Carbon primary emitted from burning (e.g., vegetative, charbroiling, 

etc.) and combustion (e.g., coal, gasoline, and diesel) 

OC Organic Carbon that is primary emitted from burning and combustion and 

formed secondarily from some VOCs; 

PM Other PM that is primary emitted that includes many compounds including crustal 

material, metals, sea salt, etc. 

Test data indicate that biodiesel fuel use in heavy duty diesel vehicles (HDDVs) tends to increase 

NOx emissions but reduce emissions of volatile organic compounds (VOC), carbon monoxide 

(CO), particulate matter (PM, including EC and OC), and sulfur dioxide (SO2). Thus, on the one 

hand biodiesel fuel use will increase one PM precursors (NOx), on the other it will decrease 

others (VOC, primary PM, and SO2). Thus, the ultimate effect of biodiesel fuel use on ambient 
1-2 

PM levels cannot be determined by analyzing emissions changes alone. It must be investigated 

using air quality modeling of the key constituents of PM. 

Purpose 

This document is the Task 4 Report for the NREL “Impacts of Biodiesel Fuels on Air Quality 

and Human Health “ study. The objective of Task 4 is to estimate the effects of the use of 

biodiesel fuels on PM10 levels and the resultant exposure to elevated levels of PM10. Annual PM 

modeling of the South Coast (Los Angeles) Air Basin (SoCAB) region of Southern California 

was conducted for a standard diesel and biodiesel fuel scenarios and the effects on PM10 and 

PM2.5 and exposure to elevated PM10 and PM2.5 levels were estimated. 

OVERVIEW OF APPROACH 

There are currently several PM10 nonattainment areas in the United States that have performed 

PM10 modeling as part of their State Implementation Plan (SIP) planning. In the NREL 

Biodiesel Study Modeling Protocol we identified four potential PM modeling databases that 

could be used for the biodiesel fuel PM impact assessment (ENVIRON, 2000): 

• A 1995 South Coast Air Basin (SoCAB) database used by the linear chemistry 

UAM/LC model to develop the PM10 plan in the 1997 AQMP/SIP; 

• An October 1995 episode database developed for the full-science UAM-AERO 

model; 

• A 1995 UAM/LC database for the Phoenix area; and 

• A 1997/1998 annual database for the SoCAB developed as part of the Multiple Air 

Toxics and Exposure Study (MATES-II). 

The Phoenix PM problem has a relatively smaller contribution due to secondary PM (sulfate and 

nitrate) compared to the SoCAB. Since biodiesel fuel is estimated to increase NOx emissions, 

then performing the PM assessment for the SoCAB where nitrate levels are high was believed to 

be a fairer assessment of its potential benefits and adverse effects on PM levels. Thus, the 

Phoenix database was eliminated from consideration. 

Although in the past the SoCAB has violated both the 24-hour and annual PM10 standards, more 

recent measurements show the maximum 24-hour PM10 concentrations right at the standard, 

whereas the annual standard is still exceeded. Thus, the impacts of biodiesel fuel use on both, 

maximum 24-hour and annual PM concentrations needs to be assessing, which eliminates the 

episodic October 1995 UAM-AERO database from consideration. Either the 1995 or 1997/1998 

PM modeling database would be adequate for assessing the effects of biodiesel use on PM 

concentrations in the SoCAB. Both annual periods are currently being used by the South Coast 

Air Quality Management District (SCAQMD) for their PM10 control plan being developed as 

part of the 2002 Air Quality Management Plan (AQMP) and SIP efforts. Ultimately the 

1997/1998 MATES-II database was selected for the following reasons: 

• It is more recent than the 1995 database; 

• It has been set up for the CAMx model that is more up to date and current than the 

UAM/LC model; and 

• It was used for the NREL study Task 5 biodiesel impacts on exposure and human 

health effects air toxics modeling. 
1-3 

Overview of the 1997/1998 MATES-II Annual Modeling Database 

As part of the Multiple Air Toxics Exposure Study (MATES-II), the South Coast Air Quality 

Management District (SCAQMD) applied the UAM-Tox photochemical and air toxics grid 

model for a year (April 1998-March 1999). Air toxic concentration estimates were obtained 

across the South Coast (Los Angeles) Air Basin (SoCAB) for approximately 50 toxic 

compounds. The UAM-Tox used a 105 by 60 horizontal array of 2-km by 2-km grid cells to 

cover the SoCAB and five vertical layers up to a region top of 2-km AGL. Hourly threedimensional meteorological inputs were generated for April 1, 1998 through March 31, 1999 

using the CALMET diagnostic meteorological model and surface and upper-air meteorological 

observations. 

As part of Task 5 of the NREL Biodiesel Study, air toxics modeling of the SoCAB was 

performed to assess the effects of biodiesel fuel use on human health (Morris and Jia, 2002). 

The Task 5 air toxics modeling built off of a study for the Coordinating Research Council (CRC) 

and Department of Energy (DOE) Project A-42-2 “Air Toxics Modeling” (ENVIRON, 2002). 

The CRC/DOE air toxics modeling study developed a new CAMx air toxics modeling system 

and applied it to the SoCAB for the MATES-II annual period. The same CAMx hourly 

meteorological fields for the April 1998 through March 1999 period as used in the CRC and 

NREL Task 5 air toxics modeling were used in the Task 4 PM modeling assessment of the 

NREL Biodiesel Fuel Impact Study. However, all new emissions were developed for PM 

precursors. The reader is refereed to the NREL Biodiesel Impact Study Task 5 report (Morris 

and Jia, 2002) or the CRC Project A-42-2 report (ENVIRON, 2002) for details on the 

development of the CAMx meteorological inputs. Details on the development of the PM 

emissions are provided in Section 2 of this report. 

The MATES-II hourly CALMET meteorological inputs and UAM-Tox emission for April 1, 

1998 through March 31, 1999 were acquired from the SCAQMD. The CALMET diagnostic 

meteorological model was run for the April 1998 – March 1999 year and a CALMET-CAMx 

converter program was used to convert the CALMET output to the meteorological variables and 

formats needed by CAMx. CAMx was configured using a 65 by 40 5-km by 5-km grid that 

covered the SoCAB. CAMx was set up with 6 vertical layers of spatially and temporally 

constant thickness up to a region top of 2,000-m AGL. 

The latest emissions inventory modeling system for the SoCAB was acquired from the California 

Air Resources Board (ARB). These emissions were based on the EMFAC2001 mobile source 

emissions model and included NOx, VOC, CO, SOx, and PM for anthropogenic and biogenic 

sources. However, it did not include ammonia emissions. Thus, the ammonia emissions for the 

SoCAB were adapted from the October 1995 UAM-AERO database. Emissions consisted of 

hourly gridded emissions for a typical day by month accounting for seasonal variations in 

activity levels as well as temperature effects. 

The CAMx model was run for the April 1998 – March 1999 period to generate 24-hour average 

and annual average PM10 and PM2.5 concentration estimates. 

The effects of a 100% and 50% penetration of a 20%/80% biodiesel/diesel fuel (B20) into the 

Heavy Duty Diesel Vehicle (HDDV) fleet on diesel NOx, SOx, VOC, CO, and PM emissions 

was implemented in the 1998/1999 baseline mobile source emissions. The impacts of a standard 

diesel and a 100% and 50% penetration of a B20 fuel in the HDDV fleet on PM2.5 and PM10

concentrations were simulated. 
2-1

2. EMISSION INVENTORIES FOR PM MODELING 

OF BIODIESEL FUEL IMPACTS 

The latest Gridded Emissions Modeling (GEM) system setup for the South Coast Air basin 

(SoCAB) was acquired from the California Air Resources Board (ARB). GEM was set up to 

generate gridded hourly speciated photochemical modeling inventories for the South Coast Air 

Basin (SoCAB) and the August 1997 Southern California Ozone Study (SCOS) episode. Onroad mobile source emissions were generated using the EMFAC2001 mobile source emissions. 

The ARB GEM included NOx, SOx, VOC, CO, and PM emissions. However, it did not include 

any ammonia emissions. Thus, the gridded hourly ammonia emissions inventory from the 

October 1995 UAM-AERO database was used. 

TEMPORAL ALLOCATION AND SPECIATION 

The August 1997 emissions were projected to 1998/1999 years and adjusted to obtain typical 

average emissions for each month of the April 1998 through March 1999 modeling period. 

These adjustments accounted for the seasonal effects on anthropogenic emissions as well as the 

temperature effects on biogenic emissions. 

The GEM VOC species were speciated into the classes used by the Carbon Bond IV (CB4) 

chemical mechanism used in the CAMx Mechanism 4 PM chemical mechanism. The CB4 

chemistry in Mechanism 4 is similar to the standard CB4 chemistry only biogenic terpenes are 

treated as a separate species (OLE2) to track the secondary organic aerosol (SOA) from terpenes. 

The GEM PM emissions were speciated into the following PM components: 

• Sulfate; 

• Particulate Nitrate; 

• Elemental Carbon (EC); 

• Organic Carbon (OC); 

• Other Fine (<2.5 μm) Particulate Matter (PFIN); and 

• Other Coarse (2.5-10 μm) Particulate Matter (PCRS). 

EMISSION SCENARIOS 

Both standard diesel and biodiesel fuel scenarios were analyzed. The biodiesel fuel scenarios 

assumed that a 20%/80% biodiesel/diesel fuel mixture (B20) was used in just the heavy duty 

diesel vehicle (HDDV) fleet portion of on-road motor vehicles. The following emissions 

scenarios were simulated: 

• Standard Diesel Fuel Base Case; 

• 50% Penetration of a B20 Fuel in the HDDV Fleet; and 

• 100% Penetration of a B20 Fuel in the HDDV Fleet. 
2-2

The change in tailpipe emissions in the HDDV due to use of a biodiesel fuel was based on an 

analysis of engine test data as summarized by Lindjhem and Pollack (2000). Table 2-1 lists the 

net change in fleet average HDDV tail pipe emissions due to the use of a biodiesel fuel over use 

of a standard diesel fuel. 

Table 2-1. Average change in HDDV mass emissions due to use of a biodiesel fuel over use of a 

standard diesel fuel. 

Biodiesel Fuel NOx PM CO VOC SO2

B20 +2.4% -8.9% -13.1% -17.9% -20% 

B100 +13.2% -55.3% -42.7% -63.2% -100% 

The emissions from sources of on-road total diesel vehicles (TDV) can be controlled and 

adjusted by the GEM emission modeling system. The effects of the 100% and 50% B20 

emission scenarios were accounted for by applying the change in emissions in Table 2-1 due to 

the B20 fuel accounting for the B20 penetration rate and the fraction of the on-road mobile 

source diesel emissions due to the HDDV fleet. For example, for the 50% B20 biodiesel fuel 

scenario the NOx emissions from all on-road HDDV were increased by 1.18 percent (1.18 = 2.4 

x 0.50 x 0.986) to account for the 50% penetration factor of the B20 fuel and the EMFAC2001 

estimate that 98.6% of the NOx emissions in the summer 1998 on-road mobile source emissions 

diesel inventory are due to HDDVs. 

EMISSION SUMMARIES 

Table 2-2 summarizes the NOx, VOC, SOx, and PM emissions in the SoCAB domain for the 

three diesel fuel scenarios and for the summer and winter periods. For the standard diesel base 

case, on-road diesel vehicles account for 22%, 0.5%, 0.4%, 7%, and 0.7% of the NOx, VOC, 

CO, SOx, and PM emissions in the SoCAB, respectively. The changes in the diesel vehicle 

emissions due to the 100% B20 emissions scenario are very close but slightly lower than the 

changes in HDDV emissions in Table 2-1 accounting for the small contributions of light and 

medium duty diesel vehicle emissions to the total on-road diesel vehicles. The change in total 

NOx, VOC, CO, SOx, and PM emissions in the SoCAB from the 100% B20 scenario are, 

respectively, +0.5%, -0.1%, -0.1%, -1.3%, and –0.1%. 
2-3

Table 2-2. Summary of domain-wide total on-road diesel, area plus point sources, and total NOx, VOC, CO, SOx, an

the SoCAB (tons per day) for the 1997 Standard Diesel Base Case and 1997 100% and 50% Penetration of a B20 Bio

 1998 Summer Baseline 1998 Summer 100% B20 Biodiesel 1998 Summe NOX TOG CO SOX PM NOX TOG CO SOX PM NOX TOG 

TOTAL DIESEL 336.5 13.5 35.3 7.7 8.0 344.5 11.3 30.9 6.2 7.3 340.5 12.4 

On-Road Mobile 932.9 860.5 6912.3 38.1 23.7 940.9 858.2 6907.8 36.6 23.1 936.9 859.4 

Area+Point 571.1 1489.3 1466.9 73.3 1076.0 571.1 1489.3 1466.9 73.3 1076.0 571.1 1489.3 

Total 1504.0 2349.8 8379.2 111.4 1099.7 1512.0 2347.5 8374.8 110.0 1099.1 1508.0 2348.6 

% Change % 

TOTAL DIESEL 2.38 -16.57 -12.55 -19.30 -8.30 1.19 -8.28 

Total 0.53 -0.10 -0.05 -1.33 -0.06 0.27 -0.05 

 1999 Winter Baseline 1999 Winter 100% B20 Biodiesel 1999 Winte

TOTAL DIESEL 364.1 14.8 31.7 5.4 7.9 372.7 12.4 27.7 4.3 7.3 368.4 13.6 

On-Road Mobile 1009.4 944.5 6204.4 26.7 23.6 1018.0 942.0 6200.4 25.7 23.0 1013.7 943.3 

Area+Point 503.7 1484.3 1528.4 72.1 1070.7 503.7 1484.3 1528.4 72.1 1070.7 503.7 1484.3 

Total 1513.1 2428.8 7732.8 98.8 1094.3 1521.7 2426.3 7728.8 97.8 1093.7 1517.4 2427.5 

% Change % 

TOTAL DIESEL 2.36 -16.58 -12.53 -19.31 -8.30 1.18 -8.29 

Total 0.57 -0.10 -0.05 -1.05 -0.06 0.28 -0.05 
2-4

SPATIAL DISTRIBUTION OF EMISSIONS 

Figures 2-1 through 2-4 display the spatial distribution of the, respectively, NOx, VOC, CO, and 

PM emissions for the standard diesel Base Case and differences in the emissions between the 

Base Case and 100% penetration of a B20 biodiesel fuel emission scenarios for a typical summer 

day. The differences between the Base Case and 50% B20 fuel scenario are similar with 

differences half of those for the 100% B20 fuel scenario. 

The highest NOx emissions occur in the areas with the most roadways and population (Figure 2-

1, top). The maximum NOx emissions of 15 tons per day (TPD) occurs in downtown Los 

Angeles where congestion and the confluence of the 5, 10, 60, and 110 freeways produces high 

mobile source NOx emissions. Elevated NOx emissions occur in downtown Los Angeles 

stretching north into the San Fernando Valley, west toward Santa Monica and down the coast, 

south toward Anaheim, and east following freeway 10 and 60 to San Bernardino and Riverside. 

The effects of a 100% penetration of a B20 biodiesel fuel are to increase NOx emissions mainly 

along the major freeways in the SoCAB (Figure 2-1, bottom). All of the major freeways are 

clearly visible in the NOx emissions difference plot. The maximum NOx increase due to the 

100% B20 scenario (0.11 TPD) occurs in downtown Los Angeles. 

The spatial distribution of the daily total summer VOC emissions is similar to the NOx emissions 

only it appears to be more rooted to population centers rather than major roadways (Figure 2-2, 

top). The reductions in VOC emissions for the 100% B20 scenario (Figure 2-2, bottom) are not 

as great as the NOx increases with a maximum reduction of 0.03 TPD occurring in downtown 

Los Angeles. Similar results are seen for the spatial distribution of the CO emissions (Figure 2-

3). 

The distribution of the PM emissions is a little different than the other three pollutants (Figure 2-

4). Although downtown Los Angeles still produces the highest primary PM emissions (8 TPD), 

there are several other “hot spot” PM emissions locations: 

• downtown Los Angeles; 

• downtown Anaheim in Orange; 

• Ontario in Western San Bernardino County; 

• Corona south of Ontario in Riverside County; 

• San Bernardino; 

• Victorville north of Ontario in San Bernardino County; and 

• Lancaster/Palmdale north of Los Angeles in Los Angeles County. 

Although the downtown Los Angeles and Anaheim PM hot spots are likely dominated by mobile 

sources, the rest likely have major contributors from other source categories (especially the more 

rural Victorville and Lancaster locations to the north of the SoCAB). 

As seen for the other pollutants, the reductions in PM emissions between the 1997 Base Case and 

100% B20 scenario follow the major roadways in the SoCAB. The maximum reduction in PM 

due to the 100% B20 fuel use is 0.01 TPD in downtown Los Angeles. 
2-5

Figure 2-1. Total NOx emissions (tons per day) and change in NOx emissions due to the 100% 

B20 biodiesel fuel scenario for a typical 1998 summer day in the SoCAB. 

300 350 400 450 500 550 600

3700

3750

3800

3850

0

2

4

6

8

10

12

14

16

18

20

max = 15 TPD

total = 1339 TPD

Daily Total NOX Emissions (tpd)

1998 Summer Baseline in the South Coast Air Basin

300 350 400 450 500 550 600

3700

3750

3800

3850

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.05

0.075

0.1

max = 0.1094 TPD 

 Increases in Daily Total NOX Emissions (tpd)

100% Penetration B20 Biodiesel

1998 Summer in the South Coast Air Basin
2-6

Figure 2-2. Total VOC emissions (tons per day) and change in VOC emissions due to the 100% 

B20 biodiesel fuel scenario for a typical 1998 summer day in the SoCAB 

300 350 400 450 500 550 600

3700

3750

3800

3850

0

2

4

6

8

10

12

14

16

18

20

max = 22 TPD

total = 1838 TPD

Daily Total VOC Emissions (tpd)

1998 Summer Baseline in the South Coast Air Basin

300 350 400 450 500 550 600

3700

3750

3800

3850

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.05

0.075

0.1

max = 0.0296 TPD 

 Reductions in Daily Total VOC Emissions (tpd)

100% Penetration B20 Biodiesel

1998 Summer in the South Coast Air Basin
2-7

Figure 2-3. Total CO emissions (tons per day) and change in CO emissions due to the 100% 

B20 biodiesel fuel scenario for a typical 1998 summer day in the SoCAB 

300 350 400 450 500 550 600

3700

3750

3800

3850

0

10

20

30

40

50

60

70

80

90

100

max = 95 TPD

total = 7911 TPD

Daily Total CO Emissions (tpd)

1998 Summer Baseline in the South Coast Air Basin

300 350 400 450 500 550 600

3700

3750

3800

3850

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.05

0.075

0.1

max = 0.064 TPD 

 Reductions in Daily Total CO Emissions (tpd)

100% Penetration B20 Biodiesel

1998 Summer in the South Coast Air Basin
2-8

Figure 2-4. Total PM emissions (tons per day) and change in PM emissions due to the 100% 

B20 biodiesel fuel scenario for a typical 1998 summer day in the SoCAB 

300 350 400 450 500 550 600

3700

3750

3800

3850

0

1

2

3

4

5

6

7

8

max = 8 TPD

total = 979 TPD

Daily Total PM Emissions (tpd)

1998 Summer Baseline in the South Coast Air Basin

300 350 400 450 500 550 600

3700

3750

3800

3850

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

max = 0.0113 TPD 

 Reductions in Daily Total PM Emissions (tpd)

100% Penetration B20 Biodiesel

1998 Summer in the South Coast Air Basin
3-1

3. PM CONCENTRATION MODELING RESULTS

In this section we present the particulate matter (PM) modeling results of the annual simulations 

of the April 1998 through March 1999 period for the biodiesel fuel emission scenarios and 

compare them with the standard diesel base case simulation. There are currently 24-hour and 

annual Federal standards for PM of 10 μm or less (PM10) with threshold concentrations of 150 

and 50 μg/m3

, respectively. In 1997, EPA promulgated a new fine particulate (PM2.5) standard 

with 24-hour and annual thresholds of 65 and 15 μg/m3, respectively. The new fine particulate 

standard was challenged and was vacated by the Court. On appeal, the new fine particulate 

standard was reinstated, but has not fully been implemented and attainment designations are not 

expected until 2005. Thus, in this study we assess the effects of biodiesel fuel use on both PM10

and PM2.5. 

Because PM is composed of many different constituents it is difficult to understand the changes 

in PM concentrations when multiple PM precursor emissions are changed, some with increases 

and others with decreases, as with the biodiesel fuel impacts. Thus to better understand the 

effects of the biodiesel fuel we not only examine its impacts on total PM10 and PM2.5 mass, but 

also its impacts on each of the major pm components. In this section we analyze the annual 

average and maximum 24-hour average concentrations and impacts of biodiesel fuel for the 

following species: 

• Sulfate 

• Particulate Nitrate 

• Ammonium; 

• Elemental Carbon; 

• Organic Carbon; 

• Other Fine PM; 

• Coarse PM; 

• Total PM10 mass; and 

• Total PM2.5 mass; 

PM SPECIES IMPACTS 

The spatial distribution of the annual average and yearly maximum 24-hour average 

concentrations for each of the PM10 components is examined below. Because the biodiesel fuel 

scenarios have a small effect on the total emissions in the SoCAB (see Table 2-2), the spatial 

distribution of PM estimates for the 1998/1999 Base Case and 1998/1999 biodiesel fuel 

scenarios are almost identical. Thus, we present absolute modeling results of the spatial 

distribution of annual and maximum 24-hour average PM concentrations for only the 1998/1999 

Base Case. We also present the spatial distribution of the differences in concentrations between 

the 1998/1999 Base Case and the 1998/1999 100% B20 biodiesel fuel scenario. The difference 

in the estimated PM concentrations between the 50% B20 scenario and the base case have a very 

similar pattern and approximately half the magnitude of the differences in the 100% B20 

scenario, so are not presented. 
3-2

Sulfate Concentrations 

Figure 3-1 presents the spatial distribution of the estimated annual average sulfate concentrations 

for the 1998/1999 standard diesel Base Case scenario (top) and the differences in the annual 

average sulfate concentrations between the Base Case and the 100% B20 emissions scenario 

(bottom). Similar plots for the maximum 24-hour average sulfate concentrations are displayed in 

Figure 3-2. The highest estimated annual average sulfate concentration is 8.2 μg/m3 and occurs 

in the Port of Los Angeles and Port of Long Beach area on the coast just west of Long Beach. 

This is also where the highest SO2 emissions occur due primarily to marine vessel emissions and 

port operations. Away from the port area, the annual average sulfate concentrations are much 

lower, typically less than 3 μg/m3. The use of a 100% B20 biodiesel fuel is estimated to result in 

extremely small reductions in annual average sulfate concentrations across the SoCAB (Figure 3-

1, bottom). The maximum sulfate reduction due to 100% B20 use is 0.025 μg/m3

 and occurs in 

downtown Los Angeles. Unlike annual average sulfate concentrations that are centered on the 

port area, the reductions in sulfate due to biodiesel fuel use are highest over the densest urban 

areas (Los Angeles to Anaheim) and then fall off and follow the major roadways in the more 

rural areas (e.g., freeways 5, 15, and 60). 

The maximum 24-hour average sulfate concentrations in the 1998/1999 Base Case simulation is 

16.3 μg/m3 and occurs at the port area west of Long Beach (Figure 3-2). Elevated yearly 

maximum 24-hour average estimated sulfate concentrations in excess of 8 μg/m3 stretch from the 

port area up to downtown Los Angeles. The peak reduction in annual maximum 24-hour sulfate 

concentrations due to the 100% B20 fuel scenario is 0.074 μg/m3 and occurs in downtown Los 

Angeles. The use of the biodiesel fuels results in small reductions (< 0.1 μg/m3

) in maximum 

24-hour sulfate concentrations across the SoCAB with no areas of sulfate increases. 
3-3

Figure 3-1. Estimated annual average sulfate concentrations (μg/m3) for the 1998/1999 standard 

diesel base case simulations (top) and differences in annual average sulfate concentrations 

between the Base Case and 100% B20 biodiesel emissions scenarios (100% B20-Base Case). 
3-4

Figure 3-2. Estimated maximum 24-hour average sulfate concentrations (μg/m3

) for the 

1998/1999 standard diesel base case simulations (top) and differences in maximum 24-hour 

average sulfate concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case).
3-5

Particulate Nitrate Concentrations 

Figures 3-3 and 3-4 display the, respectively, annual average and annual maximum 24-hour 

average particulate nitrate concentrations for the standard diesel Base Case and the differences in 

particulate nitrate concentrations between the Base Case and 100% B20 emissions scenario. The 

peak annual average particulate nitrate concentration is 22 μg/m3 and occurs in Orange County. 

Elevated annual average particulate nitrate concentrations exceeding 20 μg/m3 occur in Orange 

County and in the Ontario area and vicinity. Annual average particulate nitrate concentrations in 

excess of 18 μg/m3

 occur over the major urban areas in Los Angeles, Orange, and western 

Riverside and San Bernardino Counties. The effects of the 100% B20 fuel are to cause annual 

average particulate nitrate concentration increases and decreases (Figure 3-3, bottom). The 

maximum annual average particulate nitrate increase and decrease due to the 100% B20 fuel are 

+0.04 μg/m3 in the Coachella Valley in Riverside County and – 0.09 μg/m3

 around Santa Ana in 

Orange County. The reductions in annual average particulate nitrate occur in the populated areas 

of Los Angeles, Orange, Riverside, and San Bernardino Counties and are higher in magnitude 

than the increases that tend to occur to the east and northwest of the population centers of the 

SoCAB. However, both the particulate nitrate increases and decreases are extremely small and 

should be considered insignificant. 

The maximum 24-hour average particulate nitrate concentrations during the modeling year occur 

in the eastern part of the SoCAB in the Riverside area, which is also where the maximum 24-

hour observed nitrate concentrations tend to occur. The peak estimated 24-hour particulate 

nitrate concentrations is 121 μg/m3

 near Riverside, which is a little bit higher than the maximum 

values typically observed at Riverside (typically around 100 μg/m3

) but not unreasonable given 

the sparseness of the PM monitoring network and 1:6 day usual sampling frequency. The effects 

of the 100% B20 scenario on the maximum 24-hour average particulate nitrate concentrations 

are to have areas of concentration increases and decreases. The particulate nitrate decreases due 

to the 100% B20 fuel tend to occur in the more populated areas of the SoCAB with maximum 

decreases in excess of 1 μg/m3 occurring in western Riverside County stretching from Corona to 

Lake Elsinore. The largest increase in maximum 24-hour average particulate nitrate due to the 

100% B20 fuel is 0.6 μg/m3

 and occurs near Palm Springs. There are pockets of particulate 

nitrate increases of 0.2 μg/m3 or greater near Palm Springs, Hemet, and in the Coachella Valley. 

The areas of particulate nitrate decreases of –0.2 μg/m3 or more include most of Orange County, 

pockets in Los Angeles County, and in western San Bernardino and Riverside Counties. Over 

the remainder of the domain the changes in particulate nitrate due to the 100% B20 fuel are < 

+0.2 μg/m3

. The increases (maximum of 0.6 μg/m3) and decreases (maximum of –1.1 μg/m3) of 

particulate nitrate due to the 100% B20 fuel are very small and should be considered not 

significant. 

The reason why the 100% B20 fuel results in increases and decreases in particulate nitrate 

concentrations when NOx emissions are increased has to do on the competing effects of the 

increases in the particulate nitrate precursor emissions (i.e., NOx emission increases) and 

reductions in atmospheric reactivity due to the reductions in the VOC and CO and increases in 

the NOx. The competing effects are summarized as follows: 

• The biodiesel fuel results in small increases in NOx emissions so if nitrate formation rates 

remained the same would produce more total nitrate (combined nitric acid and particulate 

nitrate) and potentially more particulate nitrate if ammonia is available to neutralize the 

gaseous nitric acid and form particulate ammonium nitrate; 
3-6

• The lower SO2 emissions of the biodiesel fuel reduces sulfate thereby releasing 

ammonium that was bound to the sulfate that is now available to convert gaseous nitric 

acid to particulate ammonium nitrate thereby increasing particulate nitrate concentrations 

(note that the sulfate reductions are small so this is a very small effect, see Figures 3-1 

and 3-2); 

• The lower VOC and CO emissions and higher NOx emissions of the biodiesel fuel 

reduces photochemical activity (atmospheric reactivity) reducing the oxidation rate of 

NOx to total nitrate thereby reducing the particulate nitrate concentrations. 

The western to central part of the SoCAB (from the coast to about San Bernardino/Riverside) is 

where the NOx inhibition effect on photochemistry occurs. That is, it is where reductions in 

NOx emissions tends to speed up photochemistry so forms more ozone and vice versa. This is 

also the area where ozone formation is more VOC-limited; that is in the City of Los Angeles 

area, VOC emission reductions are more effective at reducing photochemical reactivity and 

ozone formation than NOx controls. Thus, the biodiesel fuel increase in NOx and reductions in 

VOC emissions further reduces photochemical reaction rates in this area resulting in less nitrate 

formed. However, further east of about San Bernardino/Riverside or so, ozone formation is 

more NOx-limited so the increases in NOx emissions of the biodiesel increases photochemistry 

and nitrate precursors resulting in higher particulate nitrate concentrations. 
3-7

Figure 3-3. Estimated annual average particulate nitrate concentrations (μg/m3

) for the 

1998/1999 standard diesel base case simulations (top) and differences in annual average 

particulate nitrate concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case). 
3-8

Figure 3-4. Estimated maximum 24-hour average particulate nitrate concentrations (μg/m3

) for 

the 1998/1999 standard diesel base case simulations (top) and differences in maximum 24-hour 

average particulate nitrate concentrations between the Base Case and 100% B20 biodiesel 

emissions scenarios (100% B20-Base Case). 
3-9

Ammonium Concentrations 

The spatial distribution of the 1998/199 Base Case annual average ammonium concentrations 

(Figure 3-5) is a combination of the spatial distribution of the annual average sulfate (Figure 3-1) 

and nitrate (Figure 3-3) concentrations reflecting the fact that the particulate ammonium is 

associated with the particulate sulfate and nitrate concentrations. The highest annual average 

ammonium estimate is at the port area, which is the sulfate hot spot, whereas the remainder of 

the annual average ammonium distribution follows the particulate nitrate distribution reflecting 

the higher particulate nitrate than sulfur concentrations in the SoCAB away from the port area. 

The spatial distribution of the difference in annual average ammonium concentrations between 

the Base Case and 100% B20 scenario (Figure 3-5, bottom) is an identical pattern as the 

differences for particulate nitrate (Figure 3-3, bottom) and approximately 30% of the magnitude 

reflecting the difference in the ammonium (18 g/mole) and nitrate (62 g/mole) molecular weights 

(18/62=0.29). Like the particulate nitrate, the areas of annual average ammonium reductions 

occur over the population centers in the SoCAB, with a maximum reduction of –0.03 in Orange 

County, and areas of annual ammonium increases occur mainly east of the SoCAB in the desert 

regions with a maximum increase of +0.01 μg/m3

. 

The spatial distribution of the maximum 24-hour average ammonium concentrations (Figure 3-6) 

follow the distribution of the maximum 24-hour average nitrate concentrations (Figure 3-4) with 

about a third of the magnitude. The effects of the ammonium associated with the sulfate 

concentrations is not as apparent in the 24-hour average ammonium concentrations as was seen 

in the annual average values because the maximum 24-hour ammonium concentrations are 

associated with the maximum nitrate days, not the maximum sulfate days. Because of the 

difference in molecular weights, the amount of ammonium associated with the 16 μg/m3 peak 24-

hour sulfate concentration in the Port area (Figure 3-2) is 3 μg/m3, which is a barely noticeable 

amount in the maximum 24-hour average ammonium plot (Figure 3-6). As for maximum 24-

hour particulate nitrate, the reductions in ammonium due to the 100% B20 fuel occur in the 

populated areas of the SoCAB and the pockets of ammonium increases occur mainly in the Palm 

Springs and Coachella Valley areas east of the SoCAB.
3-10

Figure 3-5. Estimated annual average ammonium concentrations (μg/m3

) for the 1998/1999 

standard diesel base case simulations (top) and differences in annual average ammonium 

concentrations between the Base Case and 100% B20 biodiesel emissions scenarios (100% B20-

Base Case). 
3-11

Figure 3-6. Estimated maximum 24-hour average ammonium concentrations (μg/m3) for the 

1998/1999 standard diesel base case simulations (top) and differences in maximum 24-hour 

average ammonium concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case). 
3-12

Elemental Carbon (EC) Concentrations 

There are three “hot spots” (> 2 μg/m3

) of annual average elemental carbon (EC) concentrations 

in the 1998/1999 Base Case simulation (Figure 3-7): (1) downtown Los Angeles, where the 

region-wide maximum annual EC concentration of 2.8 μg/m3 occurs; (2) the port area where the 

high EC concentrations are likely due to the marine diesel engines; and (3) around Corona/Norco 

in western Riverside County. The source of this third hot spot is not known. The effects of the 

biodiesel fuel are to reduce EC concentrations throughout the SoCAB. The maximum annual EC 

reduction due to the 100% B20 fuel is –0.06 μg/m3 and occurs in downtown Los Angeles. This 

reduction is not significant. The highest annual average EC reductions occur in the populated 

areas and along the major roadways in the SoCAB. The peak maximum 24-hour EC 

concentration for the 1998/1999 Base Case simulation is 5.4 μg/m3

 and occurs in downtown Los 

Angeles (Figure 3-8). Elevated maximum 24-hour concentrations stretch from downtown Los 

Angeles to the port and Anaheim areas and in the Corona/Norco and Ontario areas. With the 

exception of the port area, the effects of the 100% B20 biodiesel fuel are to reduce maximum 24-

hour EC concentrations where the higher EC concentrations reside. The largest reduction is -

0.10 μg/m3

 that occurs in downtown Los Angeles. These reductions in EC due to the biodiesel 

fuel are not measurable so are not significant. 

Organic Carbon (OC) Concentrations 

The maximum annual average primary organic carbon (OC) concentrations estimated in the Base 

Case simulation is 5.4 μg/m3 and occurs in downtown Los Angeles (Figure 3-9). Elevated 

annual average OC concentrations are estimated in the population centers of the SoCAB. Unlike 

for EC, there is no OC hot spot in the port area. The effects of the 100% B20 fuel are to reduce 

annual OC concentrations across the SoCAB, with a maximum reduction of –0.15 μg/m3 (an 

insignificant amount) occurring in downtown Los Angeles. The highest annual OC reductions 

due to the 100% B20 fuel occur in areas with the highest population and along the major 

roadways. The highest maximum 24-hour average OC concentrations occur in an area stretching 

from Los Angeles to Anaheim and in Ontario. The peak 24-hour OC concentration is 11.1 μg/m3

and occurs over downtown Los Angeles (Figure 3-10). The effects of the 100% B20 fuel are to 

reduce the maximum 24-hour OC concentrations with the maximum reduction (-0.27 μg/m3) 

occurring at the same place as where the highest estimated maximum 24-hour average OC 

concentration occurs. Again, the reductions in OC due to the biodiesel fuel are below the level 

that is typically reported from monitoring so are not significant.
3-13

Figure 3-7. Estimated annual average Elemental Carbon (EC) concentrations (μg/m3) for the 

1998/1999 standard diesel base case simulations (top) and differences in annual average 

Elemental Carbon (EC) concentrations between the Base Case and 100% B20 biodiesel 

emissions scenarios (100% B20-Base Case). 
3-14

Figure 3-8. Estimated maximum 24-hour average Elemental Carbon (EC) concentrations 

(μg/m3) for the 1998/1999 standard diesel base case simulations (top) and differences in 

maximum 24-hour average Elemental Carbon (EC) concentrations between the Base Case and 

100% B20 biodiesel emissions scenarios (100% B20-Base Case). 
3-15

Figure 3-9. Estimated annual average Organic Carbon (OC) concentrations (μg/m3

) for the 

1998/1999 standard diesel base case simulations (top) and differences in annual average Organic 

Carbon (OC) concentrations between the Base Case and 100% B20 biodiesel emissions scenarios 

(100% B20-Base Case). 
3-16

Figure 3-10. Estimated maximum 24-hour average Organic Carbon (OC) concentrations 

(μg/m3) for the 1998/1999 standard diesel base case simulations (top) and differences in 

maximum 24-hour average Organic Carbon (OC) concentrations between the Base Case and 

100% B20 biodiesel emissions scenarios (100% B20-Base Case). 
3-17

Other Fine Particulate Matter (PM2.5)

Figure 3-11 displays the annual average of the other fine particulate (PFIN) concentrations (i.e., 

PM2.5 that is not EC, OC, sulfate, or nitrate). There are several “hot spot” locations of elevated 

(> 10 μg/m3) PFIN concentrations that occur over downtown Los Angeles, in the Corona/Norco 

area, up near Victorville, and two side-by-side hot spots near Lancaster/Palmdale. The peak 

annual average PFIN concentration of 16.1 μg/m3 occurs near Victorville in San Bernardino 

County. The effect of the 100% B20 biodiesel fuel scenario is to have extremely small 

reductions in the PFIN concentrations with a maximum annual reduction of only –0.005 μg/m3

that occurs in downtown Los Angeles. The maximum 24-hour PFIN concentrations have a 

similar distribution to the annual values (Figure 3-12). Again, the effects of the 100% B20 fuel 

on maximum 24-hour PFIN concentrations are very small with the maximum reduction being -

0.01 μg/m3

 that occurs in Los Angeles. These reductions are not significant. 

Coarse Particulate Matter (PM2.5-10)

Figures 3-13 and 3-14 display plots of annual and maximum 24-hour concentrations for coarse 

PM with a mean diameter between 2.5 μm and 10 μm (PCRS). There are five main locations of 

elevated PCRS concentrations: downtown Los Angeles and Anaheim, Ontario, Victorville, and 

Lancaster/Palmdale. The peak annual average coarse PM concentration is 31 μg/m3 and occurs 

in Ontario. The peak 24-hour PCRS concentration is 57 μg/m3 and also occurs in Ontario. The 

effect of the 100% B20 biodiesel emissions scenario is to have extremely small reductions in the 

coarse PM. The maximum annual and 24-hour average reduction in PCRS due to the 100% B20 

fuel are, respectively, -0.008 and –0.012 μg/m3 (insignificant changes).
3-18

Figure 3-11. Estimated annual average other fine particulate concentrations (μg/m3

) for the 

1998/1999 standard diesel base case simulations (top) and differences in annual average other 

fine particulate concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case). 
3-19

Figure 3-12. Estimated maximum 24-hour average other fine particulate concentrations (μg/m3) 

for the 1998/1999 standard diesel base case simulations (top) and differences in maximum 24-

hour average other fine particulate concentrations between the Base Case and 100% B20 

biodiesel emissions scenarios (100% B20-Base Case). 
3-20

Figure 3-13. Estimated annual average coarse particulate matter concentrations (μg/m3

) for the 

1998/1999 standard diesel base case simulations (top) and differences in annual average coarse 

particulate matter concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case). 
3-21

Figure 3-14. Estimated maximum 24-hour average coarse particulate matter concentrations 

(μg/m3

) for the 1998/1999 standard diesel base case simulations (top) and differences in 

maximum 24-hour average coarse particulate matter concentrations between the Base Case and 

100% B20 biodiesel emissions scenarios (100% B20-Base Case). 
3-22

PM10 Mass Concentrations

The spatial distribution of the annual average estimated total PM10 mass concentrations for the 

1998/1999 Base Case is shown in Figure 3-15, along with the differences in annual average PM10

concentrations between the 100% B20 scenario and the Base Case. The maximum estimated 

annual average PM10 concentration (76 μg/m3

) is approximately 50% higher than the Federal 

annual standard (50 μg/m3) and a little bit (20%) higher than the maximum observed value that 

occurred during this period (63 μg/m3

). The location of the estimate PM10 peak (Ontario) is also 

where the peak coarse PM (PCRS) annual average of 31 μg/m3 occurred so that approximately 

40% of the PM10 peak is due to coarse PM, which is not typical for the SoCAB. Clearly there is 

a coarse PM emissions artifact in the Ontario area that is driving this peak value. Ignoring the 

Ontario hot spot, estimated maximum annual PM10 concentrations are in the 50-65 μg/m3 range 

stretching from downtown Los Angeles to Anaheim and in western San Bernardino and 

Riverside Counties. 

The changes in annual PM10 concentrations due to the use of the 100% B20 fuel exhibit mostly 

decreases across the SoCAB with a maximum decrease of 0.31 μg/m3

. In the far eastern portion 

of the domain, slight increases in PM10 are estimated from the use of the 100% B20 fuel with a 

maximum increase of 0.04 μg/m3

. The PM10 reduction benefits of the biodiesel fuel are larger in 

magnitude and cover the population regions of the SoCAB, whereas the disbenefits are smaller 

and cover areas that are mostly desert. However, both the PM10 mass increases and decreases 

due to the 100% B20 biodiesel fuel use are extremely small and are probably not significant. 

The estimated maximum 24-hour average PM10 concentrations in the SoCAB during the 

1998/1999 year are shown in Figure 3-16. The peak 24-hour estimated PM10 concentration (186 

μg/m3) is 24% higher than the Federal standard (150 μg/m3) and approximately 20% higher than 

the maximum value observed in the SoCAB during this period (153 μg/m3

 in 1999), but lower to 

the maximum value observed in the recent past (219 μg/m3 in 1995). Elevated maximum 24-

hour PM10 concentrations in excess of 180 μg/m3

 are estimated to occur in the Riverside area, 

which is where the observed highest 24-hour PM10 concentrations typically occur. Elevated 

PM10 concentrations in excess of 160 are estimated to occur in the Riverside/San Bernardino, 

Ontario, and Anaheim areas. 

The effect of the 100% B20 emissions scenario results in both increases and decreases in 

maximum 24-hour total PM10 mass in the modeling domain. PM10 reductions are estimated in 

the populated areas of the SoCAB with a maximum reduction of -1.0 μg/m3 estimated to occur 

around Lake Elsinore in southwestern Riverside County. East of the SoCAB in the mainly desert 

regions there are slight increases in PM10 due to the 100% B20 fuel use with the highest increase 

in maximum 24-hour PM10 concentrations of +0.6 μg/m3. 
3-23

Figure 3-15. Estimated annual average PM10 concentrations (μg/m3

) for the 1998/1999 standard 

diesel base case simulations (top) and differences in annual average PM10 concentrations 

between the Base Case and 100% B20 biodiesel emissions scenarios (100% B20-Base Case). 
3-24

Figure 3-16. Estimated maximum 24-hour average PM10 concentrations (μg/m3) for the 

1998/1999 standard diesel base case simulations (top) and differences in maximum 24-hour 

average PM10 concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case). 
3-25

PM2.5 Mass Concentrations 

The maximum estimated annual average fine particulate (PM2.5) concentration for the standard 

diesel Base Case simulation is 53 μg/m3 in Los Angeles, approximately 350% above the new 

annual PM2.5 standard of 15 μg/m3

 (Figure 3-17). Annual average PM2.5 concentrations more 

than double the Federal Standard are estimated to occur over most of the populated areas of the 

SoCAB. The use of a 100% B20 biodiesel fuel is estimated to cause small reductions in PM2.5

concentrations in the more populated areas of the SoCAB with a maximum reduction of –0.3 

μg/m3 estimated to occur in Los Angeles. The 100% B20 fuel is estimated to cause very small 

increases in PM2.5 concentrations in the eastern desert portions of the domain with a maximum 

increase of + 0.04 μg/m3. 

The peak maximum 24-hour PM2.5 concentration is 178 μg/m3

, approximately 275% above the 

Federal Standard of 65 μg/m3, and occurs in the Riverside area (Figure 3-18). The 100% B20 

biodiesel fuel is estimated to result in areas of PM2.5 increases and decreases. The decreases 

occur in the more populated areas of the SoCAB, whereas the increases occur in the desert area 

east of San Bernardino/Riverside. The highest decrease in maximum 24-hour average PM2.5

concentrations is –1.6 μg/m3 and occurs near Lake Elsinor. Whereas the maximum increase of 

+0.6 μg/m3 occurs near Palm Springs. 
3-26

Figure 3-17. Estimated annual average fine particulate (PM2.5) concentrations (μg/m3

) for the 

1998/1999 standard diesel base case simulations (top) and differences in annual average fine 

particulate (PM2.5) concentrations between the Base Case and 100% B20 biodiesel emissions 

scenarios (100% B20-Base Case). 
3-27

Figure 3-18. Estimated maximum 24-hour average fine particulate matter (PM2.5) 

concentrations (μg/m3

) for the 1998/1999 standard diesel base case simulations (top) and 

differences in maximum 24-hour average fine particulate matter (PM2.5) concentrations between 

the Base Case and 100% B20 biodiesel emissions scenarios (100% B20-Base Case). 
4-1

4. SUMMARY AND CONCLUSIONS 

The effects of biodiesel fuel on ambient particulate matter (PM) concentrations in the South 

Coast Air Basin (SoCAB) were estimated using the Comprehensive Air-quality Model with 

extensions and an April 1998 through March 1998 annual modeling database. The effects of the 

biodiesel fuel on both total PM10 and PM2.5 mass concentrations as well as each of the major PM 

compounds were analyzed: 

• Sulfate 

• Particulate Nitrate 

• Ammonium 

• Elemental Carbon (EC) 

• Organic Carbon (OC) 

• Other fine particulate matter (PFIN) 

• Other coarse particulate matter (PCRS) 

BIODIESEL FUEL IMPACTS ON PM CONCENTRATIONS 

The air quality effects of a 20%/80% biodiesel/diesel (B20) fuel used in the Heavy Duty Diesel 

Vehicle (HDDV) fleet was assessed and compared against a standard diesel fuel scenario. Both 

a 100% and 50% penetration of B20 into the HDDV fleet was modeled. The HDDV NOx 

emission increases and decreases in VOC, CO, and PM emissions due to the B20 fuel use were 

accounted for. 

The spatial distributions of the impacts of the B20 fuel were analyzed. The impacts of the B20 

fuel tended to be greatest where major roadways and population centers existed. Table 4-1 

summarizes the maximum increase and maximum decrease for each of the major PM 

components as well as PM10 and PM10 total mass for the 100% B20 scenario. The impact of the 

50% B20 scenario was approximately half of the 100% B20 scenario. 

As seen in Table 3-1, the increases and decreases in PM concentrations due to the biodiesel fuel 

use are extremely small and should probably be considered not significant. The biodiesel fuel 

use has the biggest impacts on the ammonium nitrate, EC, and OC PM species. The biodiesel 

fuel use is estimated to have areas of increases and decreases in ammonium nitrate and total 

PM10 and PM2.5 mass and only areas of decreases for sulfate, EC, OC, PFIN, and PCRS. It is 

interesting to note that the areas of decreases in ammonium nitrate and total PM10 and PM2.5

mass occurs in the populated areas of the SoCAB, whereas the areas of increases correspond to 

areas east of the SoCAB in the desert. 
4-2

Table 4-1. Estimated maximum increases and decreases in PM concentrations (μg/m3) in the 

SoCAB due to a 100% penetration of a B20 biodiesel fuel in the HDDV fleet. 

Annual Average Maximum 24-Hour Average

PM Species 

Maximum 

Increase 

Maximum 

Decrease 

Maximum 

Increase 

Maximum 

Decrease 

Sulfate 0.00 -0.03 0.00 -0.07 

Nitrate +0.04 -0.09 +0.58 -1.12 

Ammonium +0.01 -0.03 +0.15 -0.34 

EC 0.00 -0.06 0.00 -0.10 

OC 0.00 -0.15 0.00 -0.27 

Other PFIN 0.00 -0.01 0.00 -0.01 

Other PCRS 0.00 -0.01 0.00 -0.01 

PM10 Mass +0.04 -0.31 +0.62 -1.61 

PM2.5 Mass +0.04 -0.30 +0.62 -1.61 

BIODIESEL FUEL IMPACTS ON PM EXPOSURE AND DOSAGE 

The impacts of the 100% B20 and 50% B20 biodiesel fuel scenarios on exposure to elevated 

PM10 and PM2.5 concentrations was calculated using two integrated exposure metrics: 

Exposure: Number of grid cells the annual and number of grid cell-days the 24-hour 

PM10 and PM2.5 concentration exceeded the PM10 and PM2.5 NAAQS, respectively. 

Dosage: Similar to Exposure only multiplied by the concentrations in the grid cell 

exceeding the NAAQS. 

The biodiesel fuel scenarios are estimated to reduce PM10 exposure (number of grid cells 

exceeding the annual PM10 standard) by approximately 1 and 3 percent for the 50% and 100% 

B20 scenarios, respectively with a reduction in dosage being slightly greater (2 and 4 percent). 

The areal extent of the exposure to exceedances of the 24-hour PM10 standard is reduced even 

more, approximately 5 and 9 percent for the 50% and 100% B20 scenarios, respectively. 

Slightly lower reductions are seen for the 24-hour PM10 dosage reduction due to the 50% and 

100% B20 fuel scenarios (4 and 7 percent). 

Smaller percent reductions in exposure and dosage to elevated PM2.5 concentrations are seen 

because there are so many more occurrences of exceedance of the standard than seen for the 

PM10 standard. The biodiesel fuels are estimated to have no effect in exposure to exceedances of 

the annual average PM2.5 concentrations exceeding the annual standard and small reductions in 

dosage (0.2 and 0.5 percent). For the 24-hour PM2.5 concentrations, the 100% and 50% B20 

biodiesel fuel are estimated to have small reductions in both exposure (0.3 and 0.6 percent) and 

dosage (0.6 and 1.1 percent). 

The changes in PM10 and PM2.5 exposure and dosage due to the use of the biodiesel fuel are 

small and like the changes in concentrations may not be significant. However, it is encouraging 

that directionally the biodiesel fuels do exhibit a net reduction in exposure and dosage to annual 

average and 24-hour average coarse and fine particulate matter concentrations in excess of the 

NAAQS. 
4-3

Table 4-2. Summary of integrated exposure metrics for annual and 24-hour PM10 and PM2.5

concentrations (μg/m3) exceeding the NAAQS. 

Std Diesel 50% B20 Biodiesel 100% B20 Biodiesel

Exposure Metric μg/m3 μg/m3 % μg/m3 % 

Annual Average PM10 Exposure Metrics 

 Exposure 92 91 -1.1% 89 -3.3% 

 Dosage 441 433 -1.9% 425 -3.7% 

24-Hour PM10 Exposure Metrics 

 Exposure 285 274 -3.9% 264 -7.4% 

 Dosage 2327 2246 -3.5% 2184 -6.1% 

Annual Average PM2.5 Exposure Metrics 

 Exposure 1014 1014 0.0% 1014 0.0% 

 Dosage 11114 11088 -0.2% 11063 -0.5% 

24-Hour PM2.5 Exposure Metrics 

 Exposure 31380 31285 -0.3% 31192 -0.6% 

 Dosage 588109 584638 -0.6% 581487 -1.1% 

CONCLUSIONS 

The two biodiesel fuel scenarios analyzed have nearly identical impacts on PM10 and PM2.5 as 

the standard diesel fuel scenario. The changes in PM concentrations, exposure, and dosage are 

sufficiently small that they may be considered insignificant by some. Both PM10 and PM2.5

concentration increases and decreases are estimated due to the use of biodiesel fuels, it is 

encouraging that the reductions in PM10 and PM2.5 due to biodiesel fuels are greater in magnitude 

and extent than the increases and occur in the more populated locations of the SoCAB as 

compared to the increases that are smaller and occur in the desert east of the SoCAB. 
R-1

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Impact of Biodiesel Fuels on Air Quality and Human Health: Task 4 Report, Impacts of 

Biodiesel Fuel Use on PM

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R.E. Morris, Y. Jia 

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This document is the Task 4 report for the NREL “Impacts of Biodiesel Fuels on Air Quality and Human Health” study. The 

objective of Task 4 is to estimate the effects of the use of biodiesel fuels on particulate matter levels and the resulting exposure 

to elevated levels of particulate matter.

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