SACRAMENTO METROPOLITAN 

AIR QUALITY MANAGEMENT DISTRICT 

STAFF REPORT 

Rule 421, Mandatory Episodic Curtailment of Wood and Other Solid Fuel Burning

Proposed Amendments 

September 9, 2009 

Prepared by: Marc Cooley 

 Assistant Air Quality Engineer 

Reviewed by: Kevin J. Williams, Ph.D. 

 Program Coordinator 

 Aleta Kennard 

 Program Supervisor 

Approved by: Brigette Tollstrup 

 Division Manager
Staff Report 

Rule 421 

September 9, 2009, Page 2 

BACKGROUND 

Particulate matter (PM) is a mixture of very small liquid droplets and solid particles. Adverse 

health effects are linked to particles that are less than 10 microns in diameter (PM10), and fine 

particles that are less than 2.5 microns in diameter (PM2.5). 

Sacramento does not meet state or federal health standards for fine particle air pollution 

(PM2.5). Sacramento will be formally designated nonattainment for the federal health standards 

later this year. Fine particulate matter is linked to serious adverse health effects, including 

aggravated asthma, heart attacks, and premature death in people with heart or lung disease. 

The largest single source of Sacramento's wintertime PM2.5 emissions is wood and other solid 

fuel burning in fireplaces, wood inserts, wood stoves and pellet stoves. New health studies 

have increased the concern about wood smoke health impacts, including the impact to children. 

The District has implemented three control measures to reduce emissions from wood burning: 

1) provide financial incentives to remove or replace fireplaces and dirty stoves with cleaner 

burning options, 2) prohibit installation of new fireplaces and dirty wood stoves, and 3) prohibit 

burning on days when weather conditions cause wood smoke to be trapped near the ground 

and build up to unhealthy levels. 

Rule 421, Mandatory Episodic Curtailment of Wood and Other Solid Fuel Burning, prohibits 

wood and other solid fuel burning when PM2.5 concentrations are forecast to exceed the federal 

health standard. Rule 421 is in effect from November 1st through the end of February. When 

PM2.5 concentrations are forecast to exceed the federal health standard of 35 μg/m3 but will not 

exceed 40 μg/m3, burning is prohibited, except in EPA certified wood stoves or pellet stoves. 

This is called a Stage 1 No Burn day. When PM2.5 concentrations are forecast to exceed 40 

μg/m3, all burning is prohibited. This is called a Stage 2 No Burn day. The rule does not apply 

to fireplaces and stoves that burn gaseous fuels (natural gas and propane), and exempts 

burning that is the sole source of heat, or in situations when not burning would be a financial 

hardship to a resident. 

Staff commissioned two studies of the effectiveness of our wood burning control efforts, 

specifically Rule 421. The first study, conducted by Sonoma Technology, Inc. (STI) examined 

the air quality benefits on forecast No Burn days in the last two seasons. The second study, 

conducted by Aurora Research Group, examined the public awareness and response to the 

rule. These studies showed significant improvements in air quality. The Aurora survey showed 

that 92% of the respondents were aware of burning restrictions and from their actions 

Sacramento County saw up to a 23% reduction in PM2.5 concentrations. The studies showed 

significant reductions and when curtailment days are called the largest air quality improvement 

occurred in the PM2.5 concentrations in the early evenings. 

Although the public response to the rule and air quality improvements were significant, they are 

not sufficient to meet the health standards. There were 20 unhealthful days during the winter 

2008/2009 season. The study also showed that two contributing factors to the unhealthful air 

quality days are the underprediction in the forecasts and lower air quality benefit on Stage 1 

days. Therefore, Staff is proposing to amend Rule 421 to: 

• Maintain the two stage program but reduce the concentration thresholds for prohibiting 

burning. 
Staff Report 

Rule 421 

September 9, 2009, Page 3 

Other options for modifying the rule that are included for Board consideration are: 

• Maintain the two-stage curtailment program but further reduce the concentration 

thresholds for prohibiting burning than the Staff recommendation; and/or 

• Eliminate the two-stage curtailment program and replace it with a single-stage 

curtailment program with a reduced concentration threshold; and/or 

• Incorporate a provision that automatically drops the threshold to 20 ug/m3 if the District 

does not meet our federal air quality deadline (2015 or 2019). 

HEALTH IMPACTS 

Particulate matter (PM) is a mixture of very small liquid droplets and solid particles. Adverse 

health effects are linked to particles that are less than 10 microns in diameter (PM10), and fine 

particles that are less than 2.5 microns in diameter (PM2.5). The District is currently designated 

as a nonattainment area for the state and federal1

 health standards for PM10 and for the state 

health standard for PM2.5. In addition, the District will be nonattainment for the federal PM2.5 

health standard when formal designations are published later this year. 

Wood smoke also emits other air contaminants including volatile organic compounds (VOCs) 

and nitrogen oxides (NOx) which are precursors to aerosol forms of PM2.5, and toxic and/or 

cancer-causing substances, such as benzene, formaldehyde and benzo-a-pyrene, a polycyclic 

aromatic hydrocarbon (PAH). In addition, wood smoke is a component of black carbon. 

According to the U.S. Environmental Protection Agency (EPA), health studies have linked 

exposure to particulate matter, especially fine particles, to several significant health problems, 

including: 

• increased respiratory symptoms, such as irritation of the airways, coughing, or difficulty 

breathing; 

• decreased lung function; 

• aggravated asthma; 

• development of chronic bronchitis; 

• irregular heartbeat; 

• nonfatal heart attacks, 

• premature death in people with heart or lung disease; and 

• increased risk of cardiovascular and cerebrovascular events in post-menopausal 

women. 

Exposure to particulate matter pollution can cause coughing, wheezing, and decreased lung 

function even in otherwise healthy children and adults. EPA estimates that thousands of elderly 

people die prematurely each year from exposure to fine particles. In addition, a recent study 

(Dominici et al., 2006) of the correlation between PM2.5 concentrations and hospital admission 

rates concluded that short-term exposure to PM2.5 increases the risk of hospitalization for 

cardiovascular and respiratory diseases. 

 

1

 Based on 1998-2000 monitoring data, EPA made a finding (February 15, 2002 Federal Register, 

Volume 67, Number 32, Page 7082 et seq.) that Sacramento County attained the federal ambient 

PM10 standard by the applicable December 31, 2000 attainment deadline. Note that this EPA finding 

did not redesignate the Sacramento District to attainment. 
Staff Report 

Rule 421 

September 9, 2009, Page 4 

The California Air Resources Board (CARB) heard the results of several studies2 that showed 

smoke from wood fires aggravates lung and heart disease and increases the number of hospital 

admissions. The research results indicate exposure to wood smoke may reduce lung function 

and reduce the blood’s ability to clot properly. In addition, wood smoke exposure may also 

increase substances in the body that lead to cardiovascular and pulmonary inflammation. The 

studies also found that up to 70 percent of smoke from chimneys can re-enter a home or 

neighboring residences. 

The research further found that children are more likely to be harmed by PM2.5 and wood 

smoke than adults because their respiratory systems are still developing, they breather more air 

per pound of body weight, and they are more active outdoors. Recent studies have concluded 

that children breathing PM2.5 and wood smoke are likely to experience: 

• more coughing and wheezing, 

• reduced lung function if they have asthma3

, 

• permanent reduction in lung air capacity4, 

• ten percent increased hospital admissions from respiratory problems5, and 

• decreases in memory function and scores on intelligence tests6. 

In 2008, CARB updated their studies of mortality effects from elevated PM2.5 concentrations. 

They now estimate that in the Sacramento Metropolitan Area, up to 600 premature deaths 

would be avoided at an economic benefit of over $0.9 billion per year if the region met the state 

and federal annual PM2.5 standards. 

In addition, studies have shown that with less air pollution, people will walk and bicycle more for 

recreation and transportation7. People who live in an area more conducive to walking have 

been shown to walk more, weigh less, and have lower blood pressure8,9. Rule 421 has the 

potential to increase walking of residents by decreasing wood burning emissions. Furthermore, 

the analysis of Rule 421 effectiveness has shown the largest air quality improvement occurred 

in the early evening, when people are more likely to be active or commuting home from work or 

school. Staff has received feedback from some members of the public that the reduction in 

wood smoke has made it nicer to walk and has reduced health concerns from breathing wood 

smoke. 

 

2

 California Air Resources Board, The potential health impacts of residential wood burning, Jan. 2009, 

http://www.arb.ca.gov/research/health/healthup/Jan09.pdf 

3

 Allen R et al 2008, Changes in lung function and airway inflammation among asthmatic children 

residing in wood smoke-impacted urban area. Inhal Toxicol. 20(4):423-433 

4 Gauderman WJ et al, The Effect of Air Pollution on Lung Development from 10 to 18 Years of Age. N 

Engl J Med 351;11:1057-1063, Sept 2004 

5

 Anderson ZJ et al, Ambient particle source apportionment and daily hospital admissions among 

children and elderly in Copenhagen. J Expos Sci Environ Epidemiol. 17(7):625-636. 

6

 Suglia F et al, Association of Black Carbon with Cognition among Children in a Prospective Birth Cohort 

Study. American Journal of Epidemiology. 2008:167:280-286 

7 Pikora T et al, Developing a framework for assessment of the environmental determinants of walking 

and cycling. Social Science & Medicine. 56 (2003): 1693-1703 

8 Frank LD et al, Many Pathways from Land Use to Health. Journal of the American Planning Association. 

72 (2006): 75-87

9 Fuzhong L et al, Built environment and changes in blood pressure in middle aged and older adults. 

Preventive medicine. 48(2009)237-241. 
Staff Report 

Rule 421 

September 9, 2009, Page 5 

LEGAL MANDATES 

Federal Mandates: The District is currently designated as a nonattainment area for the federal

PM10 standards. Sacramento does not meet federal health standards for fine particle air 

pollution (PM2.5). On December 22, 2008, the EPA Administrator signed rules designating the 

Sacramento area as nonattainment for the federal 24-hour PM2.5 health standard of 35 μg/m3

. 

The designations are under review by the new administration and are expected to be published 

in the coming months. Attainment plans are expected to be due in late 2012 and the attainment 

deadline will be 2014, but may be extended to 2019 if properly justified to EPA. 

The plan must include transportation conformity budgets and control measures. Transportation 

conformity budgets will require that future transportation projects stay within the specified 

emission levels to meet attainment and progress goals. Failure to submit a plan can result in 

withholding of federal transportation project approvals and funding. 

 

Attainment of the federal health standards is determined using the design value (three-year 

average of the 98th percentile PM2.5 concentrations). When Rule 421 was adopted, our design 

value was based on 2004-2006 data. Since that time, PM2.5 concentrations have increased, 

likely due to weather influences. Sacramento will likely need more reductions than previously 

estimated to attain. It is likely that the current Rule 421 alone will not be enough to attain before

the plan is due. Strengthening Rule 421 by lowering the concentration thresholds will help to 

further reduce PM2.5 concentrations during winter months, potentially reducing the need for 

other, more costly regulatory measures. 

PM2.5 Design Value10

Monitoring Station μg/m3

Del Paso Manor, Years 2004-2006 48.7 

Del Paso Manor, Years 2006-2008 51.811

Federal Health Standard 35 

State Mandates: The District is currently designated as a nonattainment area for the state 

PM10 and PM2.5 standards. Senate Bill (SB) 656 required CARB to adopt a list of the most 

feasible and cost effective control measures to make progress towards state and federal PM10 

and PM2.5 standards. The following table lists the District’s PM control measures for wood 

burning fireplaces and wood burning heaters. 

PM Control Measure Status 

1

Require use of USEPA-Certified Phase II or 

equivalent devices Implemented in Rule 417 

2

Public Awareness Program with either a voluntary 

curtailment or mandatory curtailment Implemented in Rule 421 

 

10 This data was acquired at Del Paso Manor station located in Sacramento County that has a federal 

reference method monitor. The average value is calculated according to procedures specified in 

Appendix N of Title 40, Code of Federal Regulations Part 50. The procedures require selection of the 

98th percentile monitored concentration. For example, in 2006 the 98th percentile was the eighth 

highest reading. 

11 Design value calculated with exceptional event data from 2008 forest fires removed. 
Staff Report 

Rule 421 

September 9, 2009, Page 6 

PM Control Measure Status 

3

Require replacement of non-certified units upon sale 

of property Not implemented 

4

Restrict number of wood burning fireplaces and 

wood stoves allowed in new residential 

developments 

Partially implemented in Rule 417 

5

Control of wood moisture content. Prohibit burning

materials that are not intended for use in 

fireplace/heater. 

Implemented in Rule 417 

Rule 417, adopted on October 26, 2006, implemented control measures 1 and 5, and partially 

implemented control measure 4. Although Rule 417 exceeds the control measures by 

prohibiting the installation of any wood burning fireplaces in new residential developments, it 

doesn’t limit the number of certified wood burning stoves in a residence. Rule 421 implemented 

control measure 2. Control measure 3, which addresses replacement of noncertified units upon 

sale of property, has not yet been implemented. Staff recommended postponing the 

implementation of the control measures that have not been fully implemented until the benefits 

could be assessed from the original adoption of Rule 421. Staff is still considering 

postponement of these measures to assess the benefits of amendments to Rule 421. All of the 

PM2.5 measures will be reconsidered during development of the federal PM2.5 attainment plan. 

The District's strategy to improve particulate matter air quality includes a three-pronged 

approach to reducing emissions from wood burning: providing financial incentives, regulating 

new wood burning installations, and reducing burning from existing fireplaces and wood stoves. 

The program to provide financial incentives to remove or replace existing fireplaces and dirty 

wood stoves was established in June 2006. On October 26, 2006 the Board of Directors 

approved Rule 417 to prohibit installing new fireplaces and dirty wood burning devices. The last 

prong was adopted on October 25, 2007, as Rule 421, Mandatory Episodic Curtailment of Wood 

and Other Solid Fuel Burning. Residents and businesses that take advantage of the financial 

incentives to install gaseous fuel burning devices are exempt from our wood burning 

regulations. 

2009 WOOD BURNING SURVEY 

Aurora Research Group conducted a telephone survey of Sacramento County residents in April 

2009. This survey was similar to the telephone survey Aurora previously conducted in April 

2007. The purpose of this study was to gauge public awareness of mandatory No Burn 

restrictions and to gauge the effectiveness and compliance rates of Rule 421 on Burning 

Discouraged, Stage 1 and Stage 2 No Burn days. 

The 2009 Aurora phone survey received responses from 400 random digit dial telephone 

surveys from county residents, including a subset of 6% who would be classified as low-income 

residents based on federal guidelines. Only those who have the capability to burn wood or 

pellets were included in the 400 surveys. To get an accurate compliance rate only the 

respondents who burned last season were focused on. Of the burners, 57% complied with all 

the Stage 1 restriction days (this accounts for certified device owners who are allowed to burn) 

and 70% complied with all the Stage 2 restriction days. 
Staff Report 

Rule 421 

September 9, 2009, Page 7 

Other key findings are: 

• 50% of all respondents who had the capability to burn wood or pellets did not burn at all 

last winter. 

• 50% of all respondents burned sometime during the last winter season. 30% of all 

respondents burned wood less than once per week. 11% indicated burning more than 

once a week. 

• No respondents indicated wood burning as their sole source of heat. 

• Among the 45% of those who reduced their burning of wood last winter, 35% of those 

who burned less did so because of air quality or health concerns, or because they heard 

a request not to burn. 

• 71% of all respondents know that it is their obligation to check to see if burning is 

permitted. 

• 85% of those respondents aware of the mandatory curtailment restrictions saw or heard 

about a mandatory curtailment episode on TV and radio. 

• 59% of all respondents rated residential wood burning fireplaces as a serious part of 

wintertime air pollution. However, 82% rated traffic as a serious part of wintertime air 

pollution with 20% more rating traffic as very serious compared to wood burning as very 

serious. 

The final Aurora report is included in Appendix C. 

Rule 421 Effectiveness Analysis and Results 

The District contracted with STI to study the air quality benefits from Rule 421. They conducted 

three different analyses; a cluster analysis, Chemical Mass Balance (CMB) modeling, and 

numerical modeling. 

• Cluster Analysis

Cluster analysis involves grouping days with similar meteorology. For each group, 

the analysis then compares the PM2.5 concentrations on days prior to the adoption 

of Rule 421 to days after Rule 421 was in effect. The difference in PM2.5 

concentrations can be largely attributed to the benefits achieved by Rule 421. 

A total of 11 day-pairs (22 days) with similar meteorological conditions was 

compared. Half of the 22 days occurred prior to adoption of Rule 421 and the other 

half of the days were either Stage 1 or Stage 2 No Burn days. The results of the 

cluster analysis showed an average reduction in 24-hour average PM2.5 

concentration on a Stage 1 day of 4 μg/m3 (10% reduction) and on a Stage 2 day of 

12 μg/m3 (23% reduction.) The greatest reduction of PM2.5 concentrations occurred 

during the evening hours. 

• Chemical Mass Balance (CMB) model

A CMB model uses analysis of the chemical species contained in particulate matter 

collected on filters to determine which emissions sources contribute to the PM2.5 

problem. Studies have established a "fingerprint" of chemical species that are 
Staff Report 

Rule 421 

September 9, 2009, Page 8 

associated with different emissions sources. The CMB model then uses this 

information to quantify the contribution from each source type. 

 

The results of the CMB modeling indicate the average wood smoke contribution on 

days when PM2.5 concentrations were high was at least 11 μg/m3 (27%) and as high 

as 19 μg/m3 of the total PM2.5 concentration12. These results indicate that it is 

possible to achieve a PM2.5 reduction on the order of 10 to 20 μg/m3 on a Rule 421 

No Burn day. This percentage is consistent with emissions inventory13. 

• Numerical Modeling

STI runs a gridded air quality modeling system called BlueSky Gateway14. This 

model system provides hourly predictions of PM2.5 concentrations for the entire 

United States, including Sacramento, using weather information, emissions data, and 

an air quality model to represent the chemical reactions that occur in the 

atmosphere. BlueSky Gateway’s sub-components include the weather model, called 

MM5, an emissions model, called Sparse Matrix Operator Kernel Emissions 

(SMOKE), and the Community Multiscale Air Quality model (CMAQ). STI estimated 

PM2.5 concentrations assuming 100% curtailment. Because the model represents 

the entire United States, and consequently has a fairly coarse resolution, peak 

concentrations may be under-predicted by the model.

The initial results of the modeling analysis show that the average PM2.5 reduction 

with complete curtailment was 5.2 μg/m3 or 21%. 

STI updated the modeling for this analysis on August 20th to account for less than 

100% compliance. The analysis was modified by applying the 57% emission 

reduction for Stage 1 No Burn days and the 70% emission reduction for Stage 2 No 

Burn days. The updated results of the modeling analysis show that the average 

PM2.5 reduction on a Stage 1 No Burn day was 5.2 μg/m3 or 13% and on a Stage 2 

No Burn day was 6.4 μg/m3 or 17%. 

• Other data analysis

STI also determined how many days during the 2008/2009 season that benefits from 

Rule 421 avoided an exceedance of the federal health standard. A total of 20 days 

exceeding the NAAQS violations were observed, and had Rule 421 not been in 

effect there would have been about 13 additional days on which the NAAQS was 

exceeded. 

 

12 Along with PM2.5, burning wood emits nitrogen oxides and organic compounds. Nitrogen oxides and 

organic compounds then react in the atmosphere to form secondary PM2.5. However, because there 

are many other sources of organic compounds and nitrogen oxides, it is not possible to specifically 

quantify the amount of this secondary PM2.5 that is from wood burning. Therefore, 11 μg/m3

, is a 

conservative estimate of the wood smoke contribution to total PM2.5 concentrations. 

13 If all secondary PM2.5 compounds were excluded, the percentage of PM2.5 associated with wood 

smoke would be 58%, similar to the percentage estimated using emissions inventory methods. 

14 The model grid resolution is 36 kilometers.
Staff Report 

Rule 421 

September 9, 2009, Page 9 

Finally, STI evaluated the potential for underpredictions in the air quality forecast. No 

Burn forecasts are made based on the air quality and weather forecasts for each 

day. To provide greater certainty in avoiding federal health standard violations, STI 

recommends the thresholds be reduced to account for the potential underprediction. 

The STI report is included in Appendix D. 

SUMMARY OF PROPOSED AMENDMENTS 

When Rule 421 was first adopted, forecasting error had not been quantified nor considered 

when determining the thresholds. The recent STI studies analyzed the current program, 

including the forecasting error. With this additional information and consideration of actual Rule 

421 air quality benefits and comments received at public workshop, concentration thresholds 

can now be re-examined. Staff evaluated lowering the thresholds to strengthen the rule for 

three reasons; 1) the studies indicate that although the public awareness and air quality benefits 

are very good, we are still not meeting state or federal health standards, 2) when the thresholds 

were established Staff did not have information to consider the potential for underpredicting air 

quality forecasts or actual air quality benefit information, and 3) recent health studies indicate 

that serious health consequences can be specifically attributed to wood smoke and that updated 

CARB health information estimates higher mortality rates in Sacramento from high PM2.5 

concentrations. 

Four amendment options are being evaluated: 

Recommended Change - Reduce the Stage 1 threshold from 35 to 31 μg/m3 to account for 

the potential underprediction in air quality forecasts. Reduce the Stage 2 threshold from 40 

to 35 μg/m3 to account for the actual benefits that occur on Stage 1 No Burn days. 

This is the Recommended Change because, as noted, an adjustment is needed to account 

for the potential underprediction in air quality forecasts and the actual Stage 1 benefit of 4 

μg/m3

. Staff originally estimated the Stage 1 benefit at 5 μg/m3 during the adoption of Rule 

421. 

Option A – Change to a single-stage program, thereby eliminating the exemption for EPA 

certified wood stoves and pellet stoves. Set the No Burn threshold to 30 μg/m3 and either 

maintain the voluntary threshold at 25 μg/m3

 or reduce it to 20 μg/m3. These thresholds are 

consistent with the San Joaquin Valley APCD program, and are more likely to meet Clean 

Air Act requirements for reasonably available control measures. Option A is expected to 

result in 8 more No Burn days. 

This was the recommended change that was presented at the public workshops. However, 

many comments at the workshops expressed concern that eliminating a two-stage program, 

with its exemption for EPA certified devices and pellet stoves on Stage 1 days, would 

reduce the incentive for people to switch to cleaner devices and also be unfair to those who 

have already invested in cleaner devices. 

Option B - Reduce the Stage 1 threshold to 25 μg/m3 and the Stage 2 threshold to 30 μg/m3

to be consistent with the San Joaquin Valley No Burn threshold. Reduce the voluntary 

threshold to 20 μg/m3. Option B is expected to result in 21 additional No Burn days. 
Staff Report 

Rule 421 

September 9, 2009, Page 10 

Contingency Option - Include a provision to automatically change to a single-stage (if not 

already) program with a reduced threshold of 20 μg/m

3

 if Sacramento does not meet the 

federal health standards by the required deadlines, either 2014 or 2019. Using the past 5 

years of data, this would result in up to approximately 41 No Burn days. However, due to 

uncertainty in the effectiveness of future control measures to improve air quality the actual 

numbered days would likely be lower. 

In addition, Staff recommends adopting the administrative change that clarifies the intent that 

first-time violators must complete and pass (i.e. a test or other method) the smoke awareness 

course. 

IMPACTS AND BENEFITS FROM POTENTIAL RULE CHANGES 

Staff used PM2.5 concentration data collected over the last 5 seasons to estimate the number 

of No Burn days that might be called each winter if the new potential thresholds were 

established. 

Every additional No Burn day would be expected to have a 10% improvement in air quality for 

Stage 1 days, and 23% improvement in air quality for Stage 2 days. 

• Staff recommendation – 5 more No Burn days than the current rule 

• Option A – 8 more No Burn days than the current rule 

• Option B – 21 more No Burn days than the current rule 

Staff estimated the number of additional exceedances of the federal health standard that might 

be avoided by applying the STI estimated benefit. The estimation of the number of days 

avoided over the federal health standard was based on the 2007/2008 and 2008/2009 season 

daily forecasts. 

The method was: 

1) If the actual forecast concentration would have resulted in a change in No Burn status; 

e.g. from a Stage 1 day to a Stage 2 day, then 

2) The observed concentration was adjusted downward by STI’s estimate of the average 

benefit on Stage 1 and Stage 2 No Burn days. 

3) The adjusted concentration for each day was compared to the federal health standard. 

If the adjusted concentration was below the 35 μg/m3

 health standard it was counted as 

an avoided exceedance. 

The table below shows the number of avoided exceedance days. The primary reason that 

the number of avoided exceedance days doesn’t vary between the options is because the 

analysis relies on historic observed air quality data and actual forecasts for 2007-2009, 

rather than a theoretical benefit that reflects the different projected emissions under each 

option. If there were no days where the air quality levels and forecasts fit into the 

boundaries that define the differences in the thresholds, then it was not counted as an 

avoided exceedance. There were only ten days (five per season) historically where the 

actual exceedance could have been avoided. The future could see different air quality 

levels, possibly more preventable days. 
Staff Report 

Rule 421 

September 9, 2009, Page 11 

The number of avoided exceedance days will likely be higher in the future because, 

unfortunately, on our very worst days, a 23% air quality improvement hasn’t been enough to 

attain the standards. But as air quality improves, 23% may be enough and the actual number of 

days avoided will be higher. 

Optional threshold changes (μg/m3) 

 Current rule Recommended 

Change Option A Option B 

Voluntary threshold 25 25 20 or 25 20 

Stage 1 threshold 35 31 Eliminated 25 

Stage 2 threshold 40 35 30 30 

Impacts and Benefits 

 Stage 1 Stage 2 Stage 1 Stage 2 Single Stage Stage 1 Stage 2 

# of days in 2004/2005 7 9 9 16 29 17 29 

# of days in 2005/2006 7 14 1 21 27 15 27 

# of days in 2006/2007 5 24 4 29 37 10 37 

# of days in 2007/2008 7 8 4 15 20 14 20 

# of days in 2008/2009 7 26 6 33 43 10 43 

Average # of No Burn 

days 7 16 5 23 31 13 31 

Average total no. of 

mandatory No Burn 

days 

23 28 31 44 

Average additional # of 

No Burn days – 5 8 21 

Average # of voluntary 

No Burn days 22 1715 33 @ 20 μg/m3 

13 @ 25 μg/m3 20 

# of avoided days over 

the federal health 

standard 

13 16 17 18 

# of additional avoided 

days over the federal 

health standard 

– 3 4 5 

EMISSIONS INVENTORY 

The California Air Resources Board is responsible for preparing the wood burning emission 

inventory for Sacramento County. Wood smoke is the single largest directly emitted PM2.5 

emissions source, 49% as reported by the CARB’s 2005 California Emission Forecast System 

 

15 The number of days is lower than the current rule, even though the threshold has not changed, 

because some of the previous voluntary days would become mandatory No Burn days. 
Staff Report 

Rule 421 

September 9, 2009, Page 12 

(CEFS) wintertime PM2.5 emissions inventory for Sacramento County. The 2005 emissions 

inventory is 8.30 tons on an average winter day from wood burning in Sacramento County. 

CARB estimates are based on a 1987 survey conducted in Healdsburg, California that 

suggested that 0.28 cords of wood is burned per household per year16. This wood usage 

amount was assumed statewide. The inventory using this methodology was calculated using 

heating degree days. 

The residential wood smoke combustion emissions inventory is being re-evaluated by CARB in 

preparation for upcoming federal PM2.5 plans. CARB is evaluating Staff’s 2007 rule 

development work which suggests the inventory is significantly underestimated. Additionally, 

several relevant surveys have been conducted since CARB last modified the methodology. The 

revised methodology relies on breakdown of device types, wood usage per device type per 

year, updated emission fireplace factor and wood cord weight. The methodology will use 

regional information when appropriate for device breakdowns to further refine a region’s 

inventory. 

This revised CARB methodology estimates PM2.5 emissions from wood burning in Sacramento 

County of 2,036 tons per year and 10.14 tons on an average17 winter day. Since not all wood 

burning occurs during the winter months (November through April), the methodology uses a 

temporal profile to estimate wood usage for the entire year. The amount of wood burned during 

the 120 days of the CBYB program accounts for 69.1% of all wood fuel burned in a year and 

90.9% of the fuel is burned in the months of November through April. 

 

16California Air Resources Board, Area Source Methodology, Section 7.1, Residential Wood Combustion, 

Revised July 1997 

17 Based on a 120-day winter with 90.9% of wood burned in the winter period 
Staff Report 

Rule 421 

September 9, 2009, Page 13 

2005 Revised Methodology Wintertime PM2.5 Inventory by Source 

The changes represent a reduction in the Fireplace PM2.5 Emission Factor, use of cord weight, 

total number of devices, changes in the usage characteristics for the various wood devices into 

conventional (non-certified), Phase II certified non-catalytic, Phase II certified catalytic, and 

pellet device. In Sacramento County the largest source of wintertime PM2.5 emissions is wood 

smoke. 

For detailed calculations see Appendix E, Emissions Calculations. 

The changes between the CARB CEFS inventory and the revised methodology are graphical 

shown below: 

Other Burning

2%

(0.38 tpd)

Fugitive Dust

17%

(3.23 tpd)

Cooking

3%

(0.57 tpd)

Other Mobile

7%

(1.37 tpd)

Farming

2%

(0.41 tpd)

Motor Vehicles

8%

(1.45 tpd)

Fuel Burning

4%

(0.69 tpd)

Other Sources

3%

(0.42 tpd)

Wood Smoke

54%

(10.14 tpd)
Staff Report 

Rule 421 

September 9, 2009, Page 14 

The overall increase in emissions are due to a variety of factors, some increase emissions, 

others decrease emissions relative to the old methodology. Overall there is a significant 

reduction in projected fireplace emissions and increase in wood stove and fireplace insert 

emissions as shown below. 

The graph below shows the revised methodology inventory by device type which shows the 

largest portion of the wood smoke inventory is from uncertified wood stoves and inserts. In 

Sacramento County the devices that contribute most to PM2.5 emissions are wood inserts. 

Contribution for fireplaces has significantly decreased based on a revised fireplace emission 

factor, percent of fireplaces used, amount of wood used and accounting for supplemental 

heating or aesthetic fireplace use. 

Sacramento Residential Wood Combustion

2005 PM2.5 Winter Planning Inventory 

Old Versus New

OLD

OLD

OLD

NEW

NEW

NEW

0.00

2.00

4.00

6.00

8.00

10.00

12.00

Fireplaces Wood Stoves Total

PM2.5, Tons/Day

6.97

8.30

1.33

2.03

8.11

10.14
Staff Report 

Rule 421 

September 9, 2009, Page 15 

The new CARB information shows that replacing fireplaces with EPA certified wood stoves or 

wood inserts and generally pellet stoves does not reduce overall emissions. 

Device Type 

Emission Factor 

(lbs PM2.5/ton 

fuel burned) 

PM2.5 per 

device per 

year (lbs/year) 

Fireplace – 

 Aesthetic 

 Heating 

23.6 

23.6 

3 

24 

Uncertified wood stove 

Catalytic wood stove 

Non-Catalytic wood stove 

30.6 

20.4 

14.6 

71 

47 

34 

Uncertified wood insert 

Catalytic wood insert 

Non-Catalytic wood insert 

30.6 

20.4 

14.6 

57 

38 

27 

Pellet stove 3.06 6 

Sacramento Residential Wood Combustion

2005 PM2.5 Winter Planning Inventory 

New Inventory

uncertified

uncertified

0.14

2.03 certified

certified

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

Fireplaces Wood Stoves Fireplace Inserts Pellet Stoves

PM2.5, Tons/Day

1.83

0.61

3.94

1.59
Staff Report 

Rule 421 

September 9, 2009, Page 16 

Direct 

Average Wintertime Observed PM2.5 Contributions 

The PM2.5 emission inventory shown above only tells part of the story. As noted previously, 

PM2.5 includes both directly emitted particles characterized in the emission inventory above, 

and PM2.5 aerosols formed by chemical reactions between gaseous pollutants, called 

precursors, in the atmosphere, in particular VOC, NOx and ammonia. Studies use chemical 

analyses of filters that have collected PM2.5 from Sacramento’s air to ascribe collected PM2.5 

concentrations to precursor and directly emitted PM2.5 emissions sources. These studies are 

generally referred to as chemical mass balances. The results from STI’s recent chemical mass 

balance are shown below. 

Along with PM2.5, burning wood emits nitrogen oxides and organic compounds. Nitrogen oxides 

and organic compounds then react in the atmosphere to form secondary PM2.5. However, 

because there are many other sources of organic compounds and nitrogen oxides, it is not 

possible to specifically quantify the amount of this secondary PM2.5 that is from wood burning. 

Therefore, 11 μg/m3

 is a conservative estimate of the wood smoke contribution to total PM2.5 

concentrations. 

EMISSION REDUCTIONS

The primary effect of the proposed amendments will be to reduce the PM2.5 concentrations on 

additional peak days, reduce adverse health effects, particularly for those in sensitive groups, 

and make additional progress to attain the state and federal annual and 24-hour health 

standards. 
Staff Report 

Rule 421 

September 9, 2009, Page 17 

The emissions reductions were calculated using results from the 2009 Aurora Survey of burning 

behavior during the Rule 421 No Burn program. That survey reported 90% of those who burn 

were aware of the burning restrictions. The study results were used to determine that there was 

a 57% reduction in the number of people burning on Stage 1 No Burn days (EPA certified and 

pellet stoves are allowed to burn), and a 70% reduction in burning on Stage 2 No Burn days18

. 

The Stage 1 No Burn reduction is assumed to be only on those who are not allowed to burn. All 

certified wood stoves, wood inserts and all pellet stoves are assumed to be burning on Stage 1. 

The emissions reduction for Stage 1 when accounting for all devices is 43%. 

The emission reductions are based on the revised methodology and use the Sacramento 

specific data from the Houck and 2007 Aurora survey, the methodology estimates that wood 

burning devices in Sacramento County: 

• 155,649 residence have open hearth fireplaces 

• 25,105 residences have wood stoves 

• 80,335 residences have wood burning inserts 

• 15,063 residences have pellet stoves 

Of the homes with wood burning equipment: 

• 98,059 residences with fireplaces burn wood or manufactured logs 

• 15,816 residences with wood stoves burn wood 

• 50,611 residences with wood burning inserts burn wood 

• 9,490 residences with pellet stoves burn pellets 

• 69% use wood burning fireplaces more for aesthetics 

• 31% use wood burning fireplaces more for supplemental heating 

• 20% residences with wood burning fireplaces burn manufactured logs 

• 43% of wood stoves are Phase II certified 

• 45% of wood inserts are Phase II certified 

The average wood usage per residence: 

• Aesthetic Fireplace Users – 0.069 cords per year19

• Supplemental Heating Fireplace Users – 0.65619

• Pellet Stove Users – 4,000 pounds per year20

• Wood Stove Users – 1.5 cords per year20

• Wood Insert Users – 1.2 cords per year20

Based on the temporal profile used in the revised CARB methodology for Residential Wood 

Combustion, 69.1% of the annual emissions from wood burning occur in the months of 

November through February, when Rule 421 is in effect. The table below summarizes the daily 

average emissions during November – February and the estimated emission reductions from 

Stage 1 and Stage 2 days. Each option has the same emission reduction per No Burn day; 

 

18 Cooley memo to Morley Chavero, “Burner Only Compliance/Emission Reduction Rates”, July 1, 2009. 

19 Houck, James E., Mangino Joseph, Brooks,Garry and Huntley, Roy, “Recommended Procedure for 

Compiling Emission Inventory National, Regional and County Level Activity Data for Residential Wood 

Combustion Source Category”, U.S. EPA Emission Inventory Conference, 2001. 

20 Broderick, D. and Houck, J., OMNI Consulting Services, Inc, “Results of Wood Burning Survey – 

Sacramento, San Joaquin, and San Francisco Areas, University of California Berkeley/CARB – GIS 

Study”, January 15, 2003. 
Staff Report 

Rule 421 

September 9, 2009, Page 18 

however, the options differ in the additional number of No Burn days that would occur. Detailed 

calculations and data sources are presented in Appendix E. 

The table below summarizes the average winter day inventory for the wintertime season and 

potential emission reductions. Detailed calculations and data sources are presented in 

Appendix E. 

Reductions (tons/day) 

Pollutant 

Nov. – Feb. 

Daily Average Emissions 

(tons/day) 

Stage 1 Day Stage 2 Day 

PM10 11.95 5.17 8.37 

PM2.5 11.47 4.97 8.03 

NOx 1.39 0.59 0.76 

CO 78.5 22.3 54.8 

VOC 35.2 18.9 24.6 

 Note: Each option has the same reduction per No Burn day but the number of No Burn days 

differs in each option. 

OTHER DISTRICTS 

Since Rule 421 was adopted, three other California air districts have adopted or amended 

similar measures. 

San Joaquin Valley Unified Air Pollution Control District (SJVUAPCD) adopted its rule 

prohibiting wood burning on forecast poor air quality days on July 17, 2003. The threshold for 

prohibiting burning was set to the federal PM2.5 health standard at the time, 65 μg/m3 or 

greater. On October 16, 2008 they lowered their threshold to 30 μg/m3 and will automatically 

lower that threshold to 20 μg/m3 if they fail to attain the federal health standard of 65, by April 

2015. The 20 μg/m3 threshold would be implemented 60 days after the effective date of EPA’s 

published finding of failure to attain for PM2.5. 

Bay Area Air Quality Management District (BAAQMD) and South Coast Air Quality Management 

District (SCAQMD) also recently adopted similar mandatory No Burn rules. The BAAQMD 

threshold is 35 μg/m3

 and became effective on November 1, 2008. The SCAQMD rule 

becomes effective November 1, 2011, with a threshold of 35 μg/m3

. None of these three 

districts exempt EPA certified devices or pellet stoves from mandatory No Burn restrictions. 

Feather River Air Quality Management District (FRAQMD) has proposed amendments to Rule 

3.17 – Wood Burning Appliances. A workshop is scheduled for the end of August. FRAQMD 

has proposed to allow the APCO issued voluntary advisory to curtail emissions to an advisory 

with specific recommended actions such as allow, reduce, curtail, limit specific areas, or a 

request to cease. The advisory would continue to be voluntary. 

Additionally, Butte County AQMD is considering adopting mandatory No Burn restrictions. The 

Chico City Council recommended Butte County AQMD adopt a No Burn regulation with a 

threshold of 25 μg/m3

. They propose to exempt EPA certified stoves. 
Staff Report 

Rule 421 

September 9, 2009, Page 19 

Other areas with wood burning restrictions include the state of Oregon as well as specific 

counties and agencies in Oregon; the state of Washington and specific jurisdictions; numerous 

areas of Idaho: Denver, Colorado; Mammoth Lakes, California; several counties in Utah; 

Maricopa County, Arizona; and Albuquerque, New Mexico. Many other areas have voluntary 

restrictions or are considering adopting mandatory restrictions. 

The restrictions in Oregon are based on PM10 and have not yet been updated for PM2.5 

standards. The state of Washington has a two stage curtailment with exemptions for certified 

devices and pellet stoves on Stage 1, with a Stage 1 threshold of 35 μg/m3. Several clean air 

agencies in Washington have adopted the state regulation that includes exemptions for sole 

source, financial hardship and startup period. 

COST IMPACT 

Section 40703 of the California Health and Safety code requires that the District consider and 

make public its findings relating to the cost effectiveness of implementing an emission control 

measure. 

Cost to Businesses: Businesses with solid fuel burning devices other than for cooking would 

have a cost savings from reduced wood use, because they generally burn wood for aesthetic 

purposes. An increase in the number of No Burn days will increase the cost savings. Staff 

does not have information to quantify the impact, if any, to these businesses due to the loss of 

ambience. There will be an additional impact to wood retailers, because mandatory curtailment 

will reduce the amount of wood burned by the public, and therefore, the amount of wood sold by 

retailers. Using the current average number of No Burn days in the winter season (7 Stage 1 

days and 16 Stage 2 days) as a baseline, the impact to wood retailers varies for each option. 

The estimated value of the wood products not purchased due to reduced burning on the 

additional mandatory curtailment days is shown in the following table: 

Average number of additional 

No Burn days for each option 

compared to 

current Rule 421 averages 

Value of wood products not 

purchased 

($ per season) 

Recommended 

Change 5 $577,781 

Option A 8 $1,137,064 

Option B 21 $1,620,987 

Contingency 

Option 41 $4,211,867 

Note: 

1. Rule 421 average number of No Burn days is 23. 

2. Percent of all wood burned that is purchased is 51.4% (Houck 2003). 

Cost to Public: The majority of the people affected by the rule burn wood for ambiance and 

would have cost savings from reduced wood use. For people who use wood as their primary or 

supplemental heat source, there will be a shift in costs from wood to an alternate source for 
Staff Report 

Rule 421 

September 9, 2009, Page 20 

heat. Anecdotal information from comments during public workshops suggests that some 

consumers may have reduced heating costs from using wood or pellets as a supplemental heat 

source. The data below shows that it costs less per unit of heat delivered to use natural gas or 

electricity than to use wood21. Reported cost savings may result from personal comfort choices 

and/or because supplemental sources heat main living areas while other rooms remain cooler 

than the home’s alternative heat source would provide, resulting in a net reduction in heat 

delivered. Staff cannot rely on anecdotal information to estimate community scale impacts of 

the additional No Burn days. 

The average cost of heating a home with a wood stove for 30 days is $236 and a pellet stove is 

$172 while the cost is $153 for electricity and $88 for natural gas. 

Overall Rule Amendment Cost Effectiveness: The cost effectiveness of the amendments 

can be calculated by using the cost (lost sales for wood suppliers). In this case the 

recommended option cost effectiveness is estimated to be $3.14-$5.32 per pound of PM2.5. To 

put these costs into perspective, it is useful to compare the cost effectiveness for other District 

rules. District Rule 417, Wood Burning Appliances, cost $4.19/lb of PM2.5 in today’s dollar. It 

should be noted that most of the District’s existing rules are for controlling ozone precursors, 

usually VOC or NOx. Rule 421 also achieves NOx reductions. The cost effectiveness of this 

rule is $2.80 - $4.86 per pound of NOx + PM2.5. The 2005 amendments to District Rule 411, 

NOx from Boilers, Process Heaters and Steam Generators cost $13.90/lb of NOx. The cost 

effectiveness of the gasoline dispensing regulations (Rule 449, Transfer of Gasoline into Vehicle 

Fuel Tanks; 12/17/1991 rule amendments) is at the higher end of the cost effectiveness range, 

costing $17/lb of VOC in today's dollars. Rule 452, Can Coating (8/21/1990 rule amendments), 

is at the low end of the range at a cost of $1/lb of VOC in today's dollars. 

 

21 In the case that free wood is delivered to the residence at no cost, there would be an increase in fuel 

cost. 

22 Socioeconomic Impact Analysis for SMAQMD Rule 421 Amendments, ERG, 2009 

Heating Device Thermal Efficiency Fuel Cost per MMbtu 

Fireplace 7% $206.23 

Certified Wood Stove 63% $22.91 

Pellet Stove 76% $28.29 

Propane Fireplace 75% $34.24 

Natural Gas Fireplace 75% $14.54 

Electric Fireplace >99% $25.23 

Gas Central Heat & Air 80% $13.63 

Electric Central Heat & Air 100% $25.23 

Propane Central Heat & Air 80% $32.10 

Note: 

1. Used as primary source of heat 

2. PG&E rates for natural gas (Winter 2009) 

3. SMUD rates for electricity (Winter 2009) 

4. Average cost of cord of wood22 = $269, average cost of pellets22 = $344/ton, and Cost of propane = 

$2.31/gallon 
Staff Report 

Rule 421 

September 9, 2009, Page 21 

DISTRICT IMPACT 

The amendments and costs to the District for Rule 421 fall into three general areas: 1) 

forecasting PM2.5 air quality, 2) public outreach to continue to educate and inform individuals, 

and 3) enforcement/compliance. 

Daily forecasting will continue. If amendments are adopted, the additional number of No Burn 

days will not cause an increase in forecasting costs. Additionally, the Staff time and media 

outreach efforts that are utilized to educate the public about the health effects of particulate 

matter pollution and the Check Before You Burn program will continue without increased costs. 

Compliance and enforcement will continue in the same manner. The original estimate of Staff 

resources when Rule 421 was adopted was 0.3 FTE compared to the actual 1.2 FTE to 

administer the 10 Stage 1 days and 28 Stage 2 days experienced in the 2008/2009 season. 

Using a ratio of the options to last season, and keeping in mind that last season was an above 

average year for the number of No Burn days, the estimated Staff resources for the additional 

No Burn days for the enforcement/compliance effort are 0.16 FTE, 0.25 FTE, or 0.66 FTE for 

the Recommended Change, Option A, or Option B respectively, specifically for the following: 

1) Surveillance by inspection Staff on the additional No Burn days for at least 1 hour per 

day per inspection Staff member (including weekends). 

2) Responding to the increase in reported burning or smoke complaints from the public due 

to the additional No Burn days. 

3) Handling of the increase in Notice of Violations (NOVs) from the additional No Burn 

days. 

SOCIOECONOMIC IMPACT ANALYSIS 

CHSC Section 40728.5 requires a district to perform an assessment of the socioeconomic 

impacts before adopting, amending, or repealing a rule that will significantly affect air quality or 

emission limitations. The District Board is required to actively consider the socioeconomic 

impacts of the proposal and make a good faith effort to minimize adverse socioeconomic 

impacts. 

CHSC Section 40728.5 requires discussion of: 

1. The type of industry or business, including small business, affected by the proposed rule or 

rule amendments. 

2. The impact of the proposed rule or rule amendments on employment and the economy of 

the region. 

3. The range of probable costs, including costs to industry or business, including small 

business. 

4. The availability and cost-effectiveness of alternatives to the proposed rule or rule 

amendments. 

5. The emission reduction potential of the rule or regulation. 

6. The necessity of adopting, amending, or repealing the rule or regulation to attain state and 

federal ambient air standards. 
Staff Report 

Rule 421 

September 9, 2009, Page 22 

Eastern Research Group (ERG) prepared a report for the District that contains a detailed 

socioeconomic analysis of the proposed rule amendments. This report is included as Appendix 

G. The paragraphs below summarize the socioeconomic findings. 

Type of industry or business, including small business, affected by the proposed rule: Rule 421 

applies to the use of solid fuel burning appliances and fires. The rule has the potential to affect 

fuel suppliers as well as businesses (e.g., restaurants, drinking establishments) and residents 

who burn wood for ambience or as a source of heat. Fuel suppliers include large retail stores 

(e.g., supermarkets and hardware stores) in addition to small independent dealers that sell 

wood as either a primary source of income (wood lots) or a secondary source of income (e.g., 

tree service or landscape companies). Companies that produce manufactured logs are also 

potentially affected. For a more detailed description of the businesses affected, refer to 

Appendix G. 

Impact on employment and economy in the District of the proposed rule: The fuel suppliers, 

particularly the small independent dealers, are the group with the potential to be most affected 

by the proposed amendments, due to lost sales. Two scenarios were analyzed to determine 

worst case impacts on either suppliers or buyers of wood. Under the first scenario (the worst 

case for suppliers), it was assumed that the suppliers would absorb the entire cost of the lost 

sales volume without the ability to raise prices to compensate. To estimate the impacts, it was 

assumed (again, worst case) that the total loss in sales for Sacramento County would be borne 

either entirely by the independent wood dealers or entirely by the large retail stores. Under this 

scenario, the lost revenue, percentage of total revenue and the potential loss of jobs were 

determined, as presented in the following tables. 

Small Independent Wood Dealers 

Recommended Option Option A Option B Contingency Option 

Total Revenue $7,683,905 $7,683,905 $7,683,905 $7,683,905 

Lost Revenue $352,025 $669,899 $1,074,327 $2,622,768 

% Lost Revenue 4.6% 8.7% 14.0% 34.1% 

Potential Job Loss 2.8 5.3 8.5 20.6 

Large Retail Stores 

Recommended Option Option A Option B Contingency Option 

Total Revenue $112,145,169,000 $112,145,169,000 $112,145,169,000 $112,145,169,000 

Lost Revenue $577,781 $1,137,064 $1,620,987 $4,211,867 

% Lost Revenue 0.01% 0.03% 0.04$ 0.10% 

Potential Job Loss 0 0 0 0 

Four companies were identified as producers of manufactured logs that are sold in Sacramento 

County. One of these companies, Duraflame, is located in nearby Stockton. Staff was unable 

to determine the market share for Duraflame logs in the county. If Duraflame represented 100% 

of the market share (worst case), the potential impact of lost sales to company revenues and 

associated employment would be: 

• 0.5% of revenue and 1.2 jobs for the Recommended Option 

• 0.8% of revenue and 2.1 jobs for Option A 

• 1.8% of revenue and 4.4 jobs for Option B 

• 3.8% of revenue and 9.4 jobs for the Contingency Option 
Staff Report 

Rule 421 

September 9, 2009, Page 23 

Residents and businesses that burn wood for ambience would experience a cost saving by not 

burning on the additional No Burn days. For residents who burn wood for heat, there could be a 

decrease or an increase in cost depending on the particular circumstances. For residents who 

purchase their wood, there would be a decrease in cost get by switching to an alternative heat 

source on No Burn days. The average cost to heat a home using wood is higher than either 

electricity or natural gas, as discussed in the Cost Impact section of this staff report. Residents 

who get their wood for free would experience a cost increase; however, the maximum impact is 

less than 0.25% of the median household income for Sacramento County. 

Under the second scenario, fuel suppliers would raise prices to compensate for the loss in sales 

volume. In this case, those who get their wood for free would experience the same cost impacts 

as in the first scenario, but no additional cost impacts. Those who pay for their wood would pay 

higher prices for the days they are allowed to burn, which would offset the savings they would 

experience from using alternative fuels on No Burn Days. 

A more detailed economic analysis is included in Appendix G. 

Range of probable costs, including costs to industry or business, including small business of the 

proposed rule: As noted in the Cost Impact section of this staff report, the total cost, in terms of 

the value of wood not purchased, is $577,781 per year for the Recommended Option and 

$1,137,064 - $4,211,867 per year for the other options. If wood sellers cannot compensate for 

the loss in revenue by raising prices, these lost revenues would be spread over a variety of 

wood sellers, including large retail stores, small businesses that sell wood as a primary or 

secondary income, and manufacturers of manufactured logs. A more detailed analysis of the 

probable costs is included in Appendix G. 

Availability and cost effectiveness of alternatives to the proposed rule: Alternatives to the 

proposed amendments include: not amending the rule; adopting different thresholds for Rule 

421 for the Recommend Option, such as Options A, B, or the Contingency Option; and adopting 

other measures to reduce emissions from wood burning devices, such as requiring replacement 

of noncertified devices upon sale of property and/or limiting the number of devices allowed per 

acre. Not amending the rule would not increase costs to impacted businesses but would not 

increase the effectiveness of the rule in reducing the number of days that exceed the PM2.5 

health standard. This could require the adoption of more costly measures in the future, most of 

which have much lower potential for reducing emissions from wood burning, and therefore lower 

effectiveness in reducing the number of days that exceed the PM2.5 health standard. 

Alternatives to the Recommended Option for reducing the thresholds were analyzed as Options 

A, B, and the Contingency Options. These options have the same cost effectiveness to the 

proposed option, in the range of $$3.14-$5.32 per pound of PM2.5. Each option reduces the 

number of days exceeding the PM2.5 health standard compared to the Recommended Option 

but also increases the number of No Burn days, and therefore the total cost, of the rule. 

Additional wood burning control measures were analyzed as further study measures as part of 

the District’s response to SB 656. The cost effectiveness in 2005 for requiring replacement of 

non-certified units upon sale of property was estimated to be $2.62 - $6.03/lb, however, the 

emission reductions are much less than those achievable through mandatory No Burn days. 

San Joaquin Valley APCD estimated a reduction of 2% for replacement of non-certified units 

upon sale of property. Staff estimates a reduction of 3.1% for replacement of non-certified units 

upon sale of property using the same assumptions from 2005 but using updated emission 
Staff Report 

Rule 421 

September 9, 2009, Page 24 

inventory numbers. The cost effectiveness for replacement is estimated to be $7.48. Using this 

assumption, the reduction for Sacramento County would be 0.36 tons per day. 

Other measures that are available to reduce PM2.5 emissions that were identified during the 

SB656 process include measures to reduce fugitive dust from agricultural tilling; chipping and 

grinding activities; composting; paved and unpaved roads; street sweepers; and construction, 

grading, and demolition; as well as add-on controls for charbroilers. None of these measures 

approaches the potential of No Burn days in reducing PM2.5 emissions. Strengthening Rule 

421 now may avoid the need to adopt some of these measures in the future. 

Emission reduction potential of the proposed amendments: The proposed rule is estimated to 

achieve reductions of 4.97 tons of PM2.5 per Stage 1 day and 8.03 tons of PM2.5 per Stage 2 

day. Each option has the same emission reduction per No Burn day; however, the options differ 

in the additional number of No Burn days that would occur. (See discussion under Emission 

Reductions section of this staff report.) 

Necessity of adopting the amendments: A more effective Rule 421 is necessary to reduce the 

number of unhealthy air quality days that violate the federal 24-hour PM2.5 health standard and 

to provide further emission reductions that will contribute to attainment of the state and federal 

PM2.5 standards and state PM10 standards. 

PUBLIC COMMENTS 

Staff conducted five public workshops throughout Sacramento County between July 13th and 

July 22nd. Each workshop started with a structured presentation of the four options with time 

available for questions and comments. The workshops were held in downtown Sacramento, 

Carmichael, Folsom, Galt and at the District office. 

Noticing for these public meetings included: 

• Letters to all elected officials in Sacramento County 

• Ad in the Our Region section of the Sacramento Bee

• Notices to newspapers across Sacramento County 

• Notices to radio stations across the region 

• Letters to homeowner associations 

• Notice on the District’s Web site 

• Notices by mail to the District’s list of parties interested in rule development. 

Workshop Location Date Time 

La Sierra Community Center 

Room 800 

5325 Engle Rd., Carmichael 

July 14 6:00 p.m. 

Tsakopoulos Library Galleria 

828 I Street, East Meeting Room, Sacramento July 15 5:30 p.m. 

SMAQMD District Office 

777 12th Street, 3rd Floor, Sacramento July 16 1:30 p.m. 

Chabolla Center 

610 Chabolla Avenue, Galt July 20 6:00 p.m. 

Folsom Community Center, Ballroom 

52 Natoma Street, Folsom July 22 6:30 p.m. 
Staff Report 

Rule 421 

September 9, 2009, Page 25 

In addition, Staff conducted stakeholder industry meetings on July 9th and August 17th. The 

stakeholder meetings were attended by HBPA and various retailers. Attendees, comments and 

responses are listed in Appendix F. 

Staff received comments and questions at the workshops, through the mail, e-mail and at 

stakeholder meetings. Comments and responses are listed in Appendix F. 

ENVIRONMENTAL REVIEW AND COMPLIANCE 

Rule 421 was created as part of the response to the requirements of Senate Bill 656 that the 

District implement cost-effective control measures for particulate matter emissions. Staff finds 

that the proposed rule is exempt from the California Environmental Quality Act as an action by a 

regulatory agency for protection of the environment (Class 8 Categorical Exemption, Section 

15308 State CEQA Guidelines) and because it can be seen with certainty that there is no 

possibility that the activity in question may have a significant adverse effect on the environment 

(Section 15061(b)(3), State CEQA Guidelines). 

 

California Public Resources Code (Section 21159) requires an environmental analysis of the 

reasonably foreseeable methods of compliance. Staff anticipates that users of solid fuel burning 

devices will comply with No Burn day restrictions by not burning for ambience and, where wood 

burning provides supplemental heat, by using alternative sources such as natural gas or 

electricity. The use of these alternative fuels will result in a decrease in the emissions of 

particulate matter and other air pollutants, including greenhouse gasses, with a corresponding 

improvement in air quality and public health. 

There has been some debate as to whether the burning of wood should be considered “carbon 

neutral,” because even though carbon dioxide is released from the burning of wood, carbon 

dioxide was absorbed by the living trees. Burning simply returns that carbon dioxide to the 

atmosphere, thus the term “neutral.” However, the term “carbon neutral” is something of a 

misnomer, because other greenhouse gasses, including methane and nitrous oxide (much more 

potent greenhouse gasses than carbon dioxide) and black carbon particles (another global 

warming pollutant), are released when wood is burned, while only the carbon dioxide is 

absorbed by living trees. Carbon neutrality, at least with respect to carbon dioxide emissions, 

depends on a number of factors, including whether the wood has been harvested from a 

sustainable resource. Both BAAQMD23 and SJVAPCD24 have found that a large percentage of 

the firewood being burned comes from nonsustainable activities. In particular, there has been a 

loss in the acreage of oak woodlands in Northern California, including the foothills on the 

eastern side of the Central Valley, attributable to urban growth, firewood harvesting, and land 

clearing for vineyards and developments. Similar activities have been conducted in Sacramento 

County and the surrounding areas. It may take as long as 200 years for young trees to 

approach the carbon storage capacity of old growth forests. 

Nevertheless, Staff has examined the net effect on greenhouse gas emissions under two 

bounding scenarios: 1) the burning of wood is not carbon neutral, and 2) the burning of wood is 

 

23 BAAQMD, Draft Environmental Impact Report for the Bay Area Air Quality Management District’s 

Proposed Regulation 6, Rule 3 Wood-Burning Devices, May 2008 

24 SJVAPCD, Final Staff Report Proposed Amendments to Rule 4901, October 2008 
Staff Report 

Rule 421 

September 9, 2009, Page 26 

carbon neutral with respect to carbon dioxide. It should be noted that there are greenhouse gas 

emissions associated with electricity due to fuel burned at electrical power plants. The following 

table shows the results of this analysis, based on equal heat outputs using natural gas or 

electricity rather than wood combustion on No Burn days. 

GHG Emissions (metric tons/yr CO2 Equiv.) 

Heat Source Recommended 

Change Option A Option B Contingency Option 

Wood 6,249 11,891 19,070 46,557 

Wood – Carbon (CO2) neutral 552 1,051 1,686 4,116 

Natural Gas 1,270 2,418 3,877 9,466 

Electricity – Only CO2 1,418 2,698 4,326 10,561 

As shown in the table, if wood burning is not carbon neutral, there is a net decrease in 

greenhouse gas emissions from using natural gas or electricity instead of wood on No Burn 

days. If wood burning is carbon (CO2) neutral, there is a net increase in greenhouse gas 

emissions from using the replacement fuels on No Burn days. Under the Recommended 

Option, assuming that wood burning is carbon (CO2) neutral, and wood is replaced by electricity 

on No Burn days, there is as net increase in greenhouse gas emissions of 866 metric tons per 

year of CO2 equivalents, which represents only 0.005% of the greenhouse gas emission 

inventory for Sacramento County and 0.0002% of the California inventory. 

Even in the worst case (Contingency Option, using electricity instead of wood), the increase in 

greenhouse gas emissions represents only 0.04% of the greenhouse gas emission inventory for 

Sacramento County and 0.001% of the California inventory. 

Staff has concluded that no significant environmental impacts will be caused by compliance with 

the proposed rule. 

FINDINGS 

The California Health and Safety Code (HSC), Division 26, Air Resources, requires local 

districts to comply with a rule adoption protocol as set forth in Section 40727 of the Code. This 

section has been revised through legislative mandate to contain six findings that the District 

must make when developing, amending, or repealing a rule. These findings, effective January 

1, 1992, and their definitions are listed in the table below. 

Rule 421 – Required Findings

Finding Finding Determination 

Authority: The District must find that a provision of 

law or of a state or federal regulation permits or 

requires the District to adopt, amend, or repeal the 

rule. 

The District is authorized to amend Rule 421 by 

California Health and Safety Code (HSC) Sections 

40001, 40702, 40716, 41013 and 42402.5. [HSC 

Section 40727(b)(2)]. 

Necessity: The District must find that the rulemaking 

demonstrates a need exists for the rule, or for its

amendment or repeal. 

It is necessary to adopt the proposed amendments to

Rule 421 to reduce the number of unhealthy air quality 

days that violate the federal 24-hour PM2.5 health 

standard. [HSC Section 40727(b)(1)]. 

Clarity: The District must find that the rule is written The District has reviewed the proposed rule and 
Staff Report 

Rule 421 

September 9, 2009, Page 27 

Finding Finding Determination 

or displayed so that its meaning can be easily 

understood by the persons directly affected by it. 

determined that it can be understood by the affected 

parties. In addition, the record contains no evidence that 

people directly affected by the rule cannot understand 

the rule. [HSC Section 40727(b)(3)]. 

Consistency: The rule is in harmony with, and not in 

conflict with or contradictory to, existing statutes, 

court decisions, or state or federal regulations. 

The District has found the proposed rule does not conflict 

with, and is not contradictory to, existing statutes, court 

decisions, or state or federal regulations. [HSC Section 

40727(b)(4)]. 

Non-Duplication: The District must find that either: 

1) The rule does not impose the same requirements 

as an existing state or federal regulation; or (2) that 

the duplicative requirements are necessary or proper 

to execute the powers and duties granted to, and 

imposed upon the District. 

The proposed rule does not duplicate any existing state 

or federal regulations. Rule 421 does not duplicate the 

federal requirements because it requires curtailment of 

use of any fires or solid fuel burning device on certain 

days. [HSC Section 40727(b)(5)]. 

Reference: The District must refer to any statute, 

court decision, or other provision of law that the 

District implements, interprets, or makes specific by 

adopting, amending or repealing the rule. 

In adopting the proposed rule, the District is 

implementing the requirements of HSC Section 39614 

(SB 656). [HSC Section 40727(b)(6)]. 

Additional Informational Requirements: In 

complying with HSC Section 40727.2, the District 

must identify all federal requirements and District

rules that apply to the same equipment or source 

type as the proposed rule or amendments. 

Appendix A includes a comparison with federal 

requirements. [HSC Section 40727.2]. 

REFERENCES 

1. Morley Chavero, Dawn, and Holobow, Naomi, “2009 Wood Burn Awareness Survey,” 

May 2009 

2. MacDonald, Clinton P., Craig, Kenneth J., DeWinter, Jennifer L., Pasch, Adam N., 

Brown, Steve G., and Wheeler, Neil J. M., “Evaluation of Sacramento Metropolitan 

Air Quality Management District’s Check Before You Burn Program,” May 2009 

3. Fields, Paula, Kaplan, Maureen, and Lamb-Janney, Lilli., “Socioeconomic Impact 

Analysis for SMAQMD Rule 421 Amendments,” August 2009. 

4. STAPPA-ALAPCO, EPA, Emissions Inventory Improvement Program. (EIIP) 2001. 

“Residential Wood Combustion”, Volume III, Chapter 2 

5. Broderick, David R., and Houck, James E. 2003, Emissions Inventory Improvement 

Program (EIIP) Residential Wood Combustion Coordination Project” 

6. Houck, James. 2003 “Results of Wood Burning Survey – Sacramento, San Joaquin, 

and San Francisco Areas, University of California Berkeley/California Air Resources 

Board – GIS Study” 

7. U.S. Environmental Protection Agency, Compilation of Air Pollutant Emission 

Factors, Volume I Stationary Point and Area Sources, AP-42, Section 1.4 – Natural 

Gas Combustion, 1998 
Staff Report 

Rule 421 

September 9, 2009, Page 28 

8. U.S. Environmental Protection Agency, Compilation of Air Pollutant Emission 

Factors, Volume I Stationary Point and Area Sources, AP-42, Section 1.9 – 

Residential Fireplaces, 1996 

9. U.S. Environmental Protection Agency, Compilation of Air Pollutant Emission 

Factors, Volume I Stationary Point and Area Sources, AP-42, Section 1.10 – 

Residential Wood Stoves, 1996 

10. 2006 Winter Emission Inventory for PM2.5, Sacramento County, 2007 CARB 

Almanac, 2006 Baseline, extracted 4/15/2009, 

 http://www.arb.ca.gov/app/emsinv/fcemssumcat2007.php
APPENDIX A 

40727.2 Matrix 

 Comparative Requirements 

Elements of 

Comparison 

Specific 

Provisions Proposed Rule 421 Rule 417 

40CFR60 

Subpart AAA 

Exemptions Cookstoves 

Sole source of heat 

Religious Activity 

Economic Hardship 

Gaseous fueled 

appliances 

Cookstoves Open masonry 

fireplaces constructed 

on site 

Boilers 

Furnaces 

Cookstoves 

Devices with air-to-fuel 

ratio > 35-to-1, minimum 

burn rate > 11 lb/hr, 

firebox > 20 cubic ft, or 

weight > 1,760 lb 

Averaging 

Provisions 

 None none none 

Units none g/hr g/hr 

 none Catalytic Units: 4.1 

g/hr 

Non-Catalytic Units: 

7.5 g/hr 

Catalytic Units: 4.1 g/hr 

Non-Catalytic Units: 7.5 

g/hr 

Emissions 

Limits 

Compliance 

alternatives 

none Pellet stoves, masonry 

heaters 

none 

Operating 

Parameters 

Prohibits operation on 

days with PM2.5 

concentration projected 

above: Recommended 

Change - 31 μg/m3 

Option A (A.1 or A.2) - 

30 μg/m3

. 

Option B - 25 μg/m3

Prohibits burning trash 

and other specified 

fuels 

none 

Work Practice 

Requirements 

 None Wood advertised by 

retailers as 

“seasoned” or “dry” 

must contain less than 

20% moisture. 

none 

Monitoring/ Recordkeeping none none none 

Records Frequency none none none 

Monitoring/ 

Testing 

Test Methods none Wood Moisture 

Content, ASTM 

D4442-92 

Test methods: 

-PM: Method 28 

-Emissions 

Concentration, if a 

dilution tunnel sampling 

location uses: Method 

5G 

-Emissions 

Concentration, if a stack 

location is used: Method 

5H 
APPENDIX B 

List of Changes to Rules 

Rule 421, Episodic Curtailment of Wood and Other Solid Fuel Burning 

Proposed rule changes implementing administrative change

NEW 

SECTION 

NUMBER 

EXISTING 

SECTION 

NUMBER 

PROPOSED CHANGES 

402.1 Same Clarify the intent that first-time violators must complete and pass 

(i.e. a test or other method) the smoke awareness course. 

Proposed rule changes implementing Recommended Change 

NEW 

SECTION 

NUMBER 

EXISTING 

SECTION 

NUMBER 

PROPOSED CHANGES 

301.2 Same Adjust Stage 1 threshold to 31 μg/m3. 

301.3 Same Adjust Stage 2 threshold to 35 μg/m3. 

302 Same Change Voluntary Curtailment section numbering to be 

consistent with the Mandatory Curtailment section. 

302.1 N/A Adjust Voluntary Curtailment to 25 μg/m3 to 31 μg/m3. 

Proposed rule changes implementing Option A (A.1 or A.2)

NEW 

SECTION 

NUMBER 

EXISTING 

SECTION 

NUMBER 

PROPOSED CHANGES 

N/A 115 Eliminate exemption. 

N/A 116 Eliminate exemption. 

N/A 208 Eliminate definition no longer used. 

N/A 209 Eliminate definition no longer used. 

208 210 Renumbered. 

209 211 Renumbered. 

N/A 301.2 Eliminate Stage 1 Mandatory Curtailment. 

301.2 301.3 Change Stage 2 to a single stage Mandatory Curtailment and 

adjust threshold to 30 μg/m3

. 

302 Same Change Voluntary Curtailment section numbering to be 

consistent with the Mandatory Curtailment section. 

302.1 N/A Set Voluntary Curtailment Range to 25 μg/m3 to 30 μg/m3

 (A.1) or 

20 μg/m3 to 30 μg/m3 (A.2). 

Proposed rule changes implementing Option B

NEW 

SECTION 

NUMBER 

EXISTING 

SECTION 

NUMBER 

PROPOSED CHANGES 
301.2 Same Adjust Stage 1 threshold to 25 μg/m3

. 

301.3 Same Adjust Stage 2 threshold to 30 μg/m3. 

302 Same Change Voluntary Curtailment section numbering to be 

consistent with the Mandatory Curtailment section. 

302.1 N/A Adjust Voluntary Curtailment to 20 μg/m3 to 25 μg/m3. 

Additional proposed rule changes either Recommended Change or Option B with Contingency 

Option

NEW 

SECTION 

NUMBER 

EXISTING 

SECTION 

NUMBER 

PROPOSED CHANGES 

301.4 N/A Add a contingency mandatory curtailment. The contingency 

mandatory curtailment changes the rule to a single stage with a 

threshold of 20 μg/m3. 

302.2 N/A Add a contingency voluntary curtailment. The contingency 

voluntary curtailment has a reduced threshold of 15 μg/m3. 

Additional proposed rule changes Option A (A.1 or A.2) with Contingency Option

NEW 

SECTION 

NUMBER 

EXISTING 

SECTION 

NUMBER 

PROPOSED CHANGES 

208 Same Maintain U.S. EPA definition. 

209 210 Renumbered. 

210 211 Renumbered. 

301.3 N/A Add a contingency mandatory curtailment. The contingency 

mandatory curtailment changes the rule to a single stage with a 

threshold of 20 μg/m3. 

302.2 N/A Add a contingency voluntary curtailment. The contingency 

voluntary curtailment has a reduced threshold of 15 μg/m3. 
APPENDIX C 

Final Aurora Survey Report 

(See May 2009 Board Letter)
2618 Stoughton Way, Sacramento, CA 95827 

www.auroraresearchgroup.com

(916) 363-8682 

Sacramento Metropolitan Air Quality Management District 

2009 WOOD BURN AWARENESS SURVEY

FINAL REPORT

MAY, 2009 

SUBMITTED BY: 

DAWN MORLEY CHAVERO & 

NAOMI E. HOLOBOW, PH.D. 

FOR
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 2 

 Table of Contents 

EXECUTIVE HIGHLIGHTS (3 PAGES) .....................................................................................................3

PROJECT BACKGROUND & OBJECTIVES ..............................................................................................6

RESEARCH METHODOLOGY.................................................................................................................7

RESULTS & CONCLUSIONS..................................................................................................................9

WINTERTIME AIR QUALITY ISSUES.......................................................................................................9

Residential Wood Burning Fireplaces......................................................................................... 9 

CURRENT RESULTS................................................................................................................... 9 

COMPARISON WITH PREVIOUS RESULTS................................................................................... 10 

GROUP DIFFERENCES ............................................................................................................. 10 

Seriousness of Other Causes of Air Pollution........................................................................... 11 

CURRENT RESULTS................................................................................................................. 11 

COMPARISON WITH PREVIOUS RESULTS................................................................................... 12 

GROUP DIFFERENCES ............................................................................................................. 13 

KNOWLEDGE OF PARTICULATE MATTER ............................................................................................14

CURRENT RESULTS.................................................................................................................. 14 

COMPARISON WITH PREVIOUS RESULTS................................................................................... 14 

GROUP DIFFERENCES ............................................................................................................. 15 

WOOD BURNING ACTIVITY ................................................................................................................16

Inventory.................................................................................................................................... 16 

CURRENT RESULTS................................................................................................................. 16 

COMPARISON WITH PREVIOUS RESULTS................................................................................... 18 

Usage of Device........................................................................................................................ 18 

CURRENT RESULTS................................................................................................................. 18 

COMPARISON WITH PREVIOUS RESULTS................................................................................... 22 

GROUP DIFFERENCES ............................................................................................................. 24 

AWARENESS OF THE CHECK BEFORE YOU BURN PROGRAM ..............................................................25

Unaided Awareness: Aware of No Burn Notices ..................................................................... 25 

CURRENT RESULTS................................................................................................................. 25 

Unaided Awareness: Familiarity with the Check Before You Burn Program ........................... 26 

CURRENT RESULTS................................................................................................................. 26 

Aided Awareness: Familiarity with the Check Before You Burn Program ............................... 29 

CURRENT RESULTS................................................................................................................. 29 

Awareness of Different Levels of the Program ......................................................................... 31 

CURRENT RESULTS................................................................................................................. 31 

GROUP DIFFERENCES ............................................................................................................. 32 

Knowledge about Different Aspects of the Program................................................................. 34 

CURRENT RESULTS................................................................................................................. 34 

GROUP DIFFERENCES ............................................................................................................. 35 

COMPLIANCE WITH THE CHECK BEFORE YOU BURN PROGRAM ..........................................................35

Among Those Aware at Each Level.......................................................................................... 35 

CURRENT RESULTS................................................................................................................. 35 

Among the Total Respondent Base .......................................................................................... 36 

CURRENT RESULTS................................................................................................................. 36 

GROUP DIFFERENCES ............................................................................................................. 37 

COMMUNICATION CHANNELS.............................................................................................................39

Among Those Aware of the Check Before You Burn Levels .................................................... 39 

CURRENT RESULTS................................................................................................................. 39 

COMPARISON WITH PREVIOUS RESULTS................................................................................... 40 

GROUP DIFFERENCES ............................................................................................................. 40 

DEMOGRAPHICS ...............................................................................................................................41
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 3 

EXECUTIVE HIGHLIGHTS (3 PAGES) 

These conclusions are based on the results of a random-digit-dial (RDD) telephone survey 

conducted with a random sample of Sacramento County residents who owned wood burning 

devices in March and early April 2009. 

Wintertime Air Quality Issues

 Nearly six in ten (59%) Sacramento County respondents with wood burning devices 

acknowledged that residential wood burning was a serious cause of wintertime air 

pollution. 

- There appears to be a move in the right direction in terms of improved understanding, 

with a 5% increase over the 2007 survey results, although this is not statistically 

significant. 

- Significantly more females than males rated residential wood burning as a serious 

pollution problem. 

 However, residential wood burning was not felt to be as serious a problem as traffic 

in contributing to wintertime air pollution. 

- The most serious cause of wintertime air pollution was viewed to be traffic (32% rated it 

a “very serious” contributor), followed by industry (19%) agricultural burning (15%), and 

finally residential wood burning (12%).

- Results this year are generally similar to those found in 2007. 

- Significantly more females than males rated traffic and industry as serious causes of 

pollution. Caucasians were less likely than other ethnicities to rate industry and 

agricultural burning as serious causes of wintertime air pollution. 

 Approximately seven in ten respondents considered themselves to be 

knowledgeable about particulate matter (PM) pollution, although only 12% of these 

felt “very” knowledgeable. 

- In terms of overall knowledge of PM pollution, the current results were similar to the 

results found in the 2007 survey. 

- Older respondents were noticeably more knowledgeable than younger respondents, 

highlighting a need for better informing younger residents about PM pollution. 

Knowledge about PM pollution also varied by gender, household size, education, 

ethnicity, and income. 

Wood Burning Activity

 By study design, all respondents had at least one wood burning device in their 

home, the majority (83%) of which included an indoor fireplace. 

− The type of wood burning devices found in homes remains unchanged since 2007.

− Only a third of fireplace inserts (36%) and wood or pellet stoves (33%) were EPAcertified or pellet devices and 18% of all respondents had heard about the Change Out 

Incentive Program. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 4 

 Fifty percent (50%) of all respondents did not use their wood burning device last 

winter. Among those who did, the majority burned wood, pellets or manufactured 

logs less than once a week. 

- Significantly fewer wood burning device owners lit up at least once during the 2008-09 

winter season (50%) than two years ago (64% in the 2007 survey). 

- Fewer burners in 2009 than in 2007 were lighting a fire on “most nights” while more are 

burning wood “mainly on weekends.” There was a slight drop in the total proportion of 

burners who lit fires at least once a week (from 58% in 2007 to 54% in 2009), although 

the difference was not statistically significant. 

- Respondents who burned wood, pellets, or manufactured logs this past winter were 

more likely than those who did not to have access to the Internet, have some post 

secondary education, and live in wealthier households. 

 Forty-five percent (45%) said they burned less this past winter compared to a typical 

winter. Of these, one in five (21%) attributed the decrease to the existence of No 

Burn days. Combined with the 12% who were motivated to reduce their wood 

burning behavior because of air quality reasons, and the 2% who cited health-related 

reason, a total of 35% chose to burn less last winter in order to help decrease 

wintertime air pollution. 

- The 5% who burned more wood, pellets and manufactured logs this winter did so 

because they felt it was cheaper than the heater, had wood, and felt that this winter 

was colder than normal. 

Awareness of the Check Before You Burn Program

 The outreach messages have been successful in reaching the population: three in 

four (76%) respondents recalled the No Burn day messages that notified them not to 

burn wood (unaided awareness). 

- Name recognition of Check Before You Burn is also high, with 72% claiming to be 

somewhat or very familiar with the Check Before You Burn program. However, not 

everyone was able to accurately describe it. 

 The program has already achieved successful visibility: when results of the unaided 

and aided awareness questions were combined, overall, 92% of all respondents 

were aware of the Check Before You Burn program. 

 In terms of awareness of different levels of the program, approximately seven in ten 

respondents (74%) who were aware of Check Before You Burn were also aware of 

the Burning Discouraged, Burn Cleanly and Stage 2- All Burning Prohibited levels. 

 However, recognition of the Stage 1 - No Burn Unless Exempt level was much lower, 

at just over half (54%) of these respondents. Although it could be attributed to the 

lower level of exposure to that level (there were fewer actual Stage 1 No Burn days), 

program organizers might want to consider increasing efforts aimed at educating 

the public specifically about Stage 1 requirements. Alternatively, they might also 

consider eliminating the Stage 1 category altogether in order to reduce confusion. 

- There were very few demographic features that distinguished those aware of each of 

the levels from those not aware, indicating that the program can continue to be aimed 

at the general population rather than targeting specific groups of individuals. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 5 

 The majority of respondents (71%) recognize that it is their responsibility to see if it 

is permissible to burn wood and nearly half (47%) of the respondents who were 

aware of the Stage 1 and Stage 2 levels knew that it was illegal to burn manufactured 

logs on Stage 1 and Stage 2 No Burn days.

- Demographically speaking, there was no difference between those who were aware of 

the program details, such as the requirement to check before burning and the 

prohibition of manufactured logs being used in fireplaces during Stage 1 and Stage 2 

No Burn days, and those who were not. 

Compliance with the Check Before You Burn Program

 Compulsory measures appear to be more effective than voluntary requests: among 

those who were aware of each level, compliance with all Stage 1 and Stage 2 No 

Burn days was significantly higher (at nearly 90%) than voluntary compliance when 

burning was simply discouraged (only 26%). 

 In terms of the total base of respondents (all of whom owned wood burning devices), 

32% complied with every voluntary Burning Discouraged request, 42% complied 

with every Stage 1-No Burn Unless Exempt directive; and 52% complied with all 

Stage 2-All Burning Prohibited days. In other words, compliance increased as the 

level of restrictions increased. 

- Compliance was relatively independent of demographics -- there were only three 

features that distinguished compliers from others within each level of the program: 

home owners, those older than 35 years of age, and those whose ethnicity was 

Caucasian were more likely to comply. 

- Among EPA-certified device owners only, compliance with Stage 1 No Burn Unless 

Exempt days was just as high as it was for Stage 2 days, even though they were legally 

allowed to burn on Stage 1 days. This indicates that there was no advantage to 

keeping Stage 1 and offers additional support for considering the possible 

elimination of Stage 1 from the program entirely. 

Communication Channels

 Using news media to announce No Burn days is an effective communication 

channel: the vast majority of respondents aware of the program heard about the No 

Burn days on television and radio (85%), followed by newspapers (58%). 

- The general news media was also the preferred communication channel identified in 

the 2007 baseline survey. 

- How respondents heard about whether or not they could burn wood was relatively 

independent of demographic features, indicating once again that the public education 

campaign can continue to be aimed at the population in general to be effective. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 6 

PROJECT BACKGROUND & OBJECTIVES

The mission of the Sacramento Metropolitan Air Quality Management District (SMAQMD) is 

to protect public health and the environment through innovative and effective programs that 

aim to improve air quality in Sacramento County. The winter season program runs from 

November 1 to February 28 and focuses on reducing the amount of fine particulate matter 

(PM) pollution that is caused by burning wood in fireplaces, woodstoves, and outside fire pits 

and chimeneas. The Check Before You Burn program has been in place since 2007 and 

expects residents to inform themselves of the day’s burn status before they consider burning 

wood, pellets or manufactured logs. It consists of four stages as illustrated in Table 1. 

Table 1 

PROGRAM LEVEL DESCRIPTION # OF OCCURRENCES IN 

2008-09 SEASON1

The public is allowed 

to burn and the 

burning of 

manufactured fire logs 

is acceptable. 

54 

Residents are 

requested to 

voluntarily not burn 

and the burning of 

manufactured logs is 

acceptable. 

28 

Burning is prohibited

unless EPA-certified 

wood burning or pellet 

devices are used. 

Manufactured fire logs 

in fireplaces are 

banned from use. 

10 

Burning of any solid 

fuel, including wood, 

manufactured logs 

and pellets, is 

prohibited. 

28 

 

1

 The specific number of occurrences at each program level was provided by Marc Cooley, Air Quality Engineer for the 

Sacramento Metropolitan Air Quality Management District in an e-mail received on April 29, 2009. The number of 

Burn Cleanly days was calculated by subtracting the number of Burning Discouraged, Stage 1 and Stage 2 days from 

the total number of days in the season (November 1 to February 28). 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 7 

The current study was designed to conduct interviews with a representative sample of 

Sacramento County residents who own an indoor or outdoor wood or pellet burning 

device to assess public awareness, perceptions and behavior. More specifically, the 

objectives of this study were to assess: 

− Wood burning activity, 

− Overall awareness of the Check Before You Burn program, 

− Message awareness and whether or not residents distinguish the various 

stages of the program, 

− The effectiveness of the current program, 

− The comparison of current results with the 2007 baseline survey results 

(when appropriate), and 

− Relevant demographic information. 

RESEARCH METHODOLOGY

Aurora Research Group was contracted to conduct this public opinion research study. For 

this study, random-digit-dialed (RDD) telephone interviews were completed with a 

representative sample of 400 Sacramento County residents who owned a wood burning 

device either inside or outside their home. 

The margin of error for the study as a whole was + or – 4.9%, at the 95% confidence level. In 

other words, we are 95% sure that the true population parameters lie within +/- 4.9% of the 

sample statistics. As an example, if a response category to a question were chosen by 50% 

of respondents, we would be 95% sure that the true population parameters would be between 

45.1% and 54.9% (50.0% +/- 4.9%). 

Using the 2007 survey as a first draft, Aurora Research Group designed the questionnaire 

which addressed the previously-mentioned objectives, and SMAQMD staff approved the final 

survey. Most of the questions were asked in a closed-ended format, but two questions were 

asked as open-ended. Verbatim responses were captured and later categorized for 

quantitative analyses. (Transcripts of all the verbatim responses will be provided in the 

statistical binder). The questionnaire was translated into Spanish and 2% of the general base 

study interviews were conducted in Spanish. The questionnaire was programmed for a CATI 

system and interviews took approximately 14 minutes on average to administer. Respondents 

were screened for age (adults at least 18 years old2

), ownership of a wood burning device 

(indoor or outdoor) and to confirm residency in Sacramento County. Interviewing took place 

between March 26 and April 9, 2009.

Methods of Analysis

Survey results were analyzed using univariate and bi-variate statistical techniques. The type 

of analysis depended upon the kind of variable analyzed and the hypotheses that were 

generated through an examination of the initial results. Unless otherwise noted, frequency 

 

2

 In order to speak with someone under 18 years of age, by law we would need to get the parents’ written permission. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 8 

percentages cited in this document represent adjusted frequencies, meaning that 

percentages have been adjusted to account for any non-responses (refusals to answer) or 

non-qualified responses (questions not answered due to answers to previous questions). 

Researchers are interested in assessing whether or not the differences in observed 

percentages between certain groups of individuals are due to chance, or if they represent 

real differences among the subpopulations. Differences are identified by running statistical 

analyses and are discussed in the report. Statistical significance within crosstabulation 

tables was calculated using chi square (χ2) statistics. Tests of proportion were used to 

identify differences in responses between questions or groups of respondents. The level of 

significance was generally set to a p value of .01. 

Caveat: 

The sole purpose of this report is to provide a collection, categorization and summary of 

public opinion data. Aurora Research Group intends to neither endorse nor criticize the 

Eastern Research Group, Inc (ERG) or Sacramento Metropolitan Air Quality Management 

District; or their policies, products, board of directors or staff. The Client shall be solely 

responsible for any modifications, revisions, or further disclosure/distribution of this report. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 9 

RESULTS & CONCLUSIONS

The survey results are organized and presented as follows: wintertime air quality issues, 

knowledge of particulate matter, wood burning activity, awareness of and compliance with the 

Check Before You Burn program, and the use of communication channels. Within each section 

of the report, the current survey results (of wood burning device respondents) are first 

presented. Next, the current results are compared with the results of the baseline survey 

conducted in 2007 with a representative sample of Sacramento County residents, who owned or 

did not own wood burning devices. Finally, any statistically significant group differences due to 

demographic characteristics (age, income, ethnicity, gender, internet access, the number of 

people living in the house, home ownership, Air Alert subscription, or education3

) are presented. 

In other words, up to nine separate cross-tabulations will have been conducted for each 

question. If no group results are described, it is an indication that there were no significant 

differentiators for a particular question. Unless otherwise specified, the reported results exclude 

responses of “undecided” as well as refusals. The order of topics presented in the report was 

chosen as the most logical in terms of meeting the information requirement objectives of the 

study and does not necessarily conform to the order of the questions within the survey. 

Wintertime Air Quality Issues 

Residential Wood Burning Fireplaces 

CURRENT RESULTS

 1 Nearly six in ten (59%) Sacramento County respondents with wood 

burning devices acknowledged that residential wood burning was a 

serious cause of wintertime air pollution. 

Respondents were asked to rate the seriousness of wintertime air pollution 

caused by residential wood burning fireplaces. Results, excluding responses 

of undecided/don’t know, are presented in Figure 1. It can be seen that 

nearly half (46%) thought it was a “somewhat” serious problem and a further 

13% said it was a “very” serious problem, for a combined total of 59% of 

respondents who acknowledged wood burning to be a serious cause of air 

pollution. However, it can also be seen that about four in ten respondents 

(41%) thought residential wood burning was not a serious contributor, 

indicating an ongoing need for public education. 

 

3

 The reader is referred to the demographic characteristics section near the end of this report to see how the demographics 

were categorized. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 10 

FIGURE 1 – SERIOUSNESS OF WINTERTIME AIR POLLUTION CAUSED 

BY RESIDENTIAL WOOD BURNING FIREPLACES

Very 

Serious

13%

Somewhat 

Serious

46%

Not at all 

Serious

41%

COMPARISON WITH PREVIOUS RESULTS

 2 There appears to be a move in the right direction in terms of improved 

understanding – 5% more owners of wood burning devices this year 

than in 2007 rated residential wood burning as a serious cause of 

wintertime air pollution. However, this is not statistically significant. 

Two years ago (in 2007) respondents4

 were asked the same question about 

residential wood burning. Results indicated that, among those who owned a 

wood burning device, a combined total of 54% respondents in 2007 

compared with 59% this year felt that residential wood burning was a serious 

cause of wintertime air pollution – a 5% increase. These results, although not 

statistically significant, nevertheless indicate a move in the right direction in 

terms of public education. 

GROUP DIFFERENCES

 3 Significantly more females than males rated residential wood burning 

as a serious pollution problem. 

To see if there were any features that distinguished those respondents who 

said residential wood burning was not a serious cause of wintertime air 

pollution from those who said it was, results were dichotomized (percent “not 

at all serious” versus percent “somewhat + very serious”), and a series of chisquare analyses was conducted. Variables included in the analyses 

included: age, income, education, gender, ethnicity, home ownership, number 

of people in household, access to the internet, and Air Alert subscription. 

 

4

 It should be noted that respondents in 2007 represented the general population of Sacramento County and included 

both wood burning households as well as non wood burning households. In order to make an appropriate comparison, 

we recalculated the 2007 results to include only those who had a wood burning device. In 2009 we spoke with only 

respondents who had wood burning devices. 

59% 

combined 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 11 

Only one feature showed a significant difference: gender. Significantly more 

females (66%) than males (55%) thought residential wood burning was a 

serious cause of air pollution. No other demographic characteristics emerged: 

neither ethnicity, education, age, internet access, the number of people living 

in the house, nor whether or not they subscribed to Air Alerts were significant. 

In other words, older residents were just as likely as younger residents to say 

wood burning was a serious issue or not; better educated respondents 

responded similarly to less educated ones, etc. 

In short, because there were so few demographic differences, a public 

education campaign dealing with the sources and seriousness of 

wintertime air pollution that is designed to target residents of all

descriptions in Sacramento County should be effective. However, if 

there were a way of educating males in particular about the pollution 

problems associated with wood-burning, there could be added benefits, 

as they demonstrated a significant information gap compared with 

females. 

Additionally, although not surprising, those who burned wood, pellets, or 

manufactured logs (50%) at least once last winter were significantly more 

likely than those who refrained (33%) to say that wood burning pollution was 

not a serious contributor to poor wintertime air quality. 

Seriousness of Other Causes of Air Pollution 

CURRENT RESULTS

 4 The most serious cause of wintertime air pollution was viewed to be 

traffic (32% rated it a “very serious” contributor), followed by industry 

(19%), agricultural burning (15%), and finally residential wood burning 

(12%). In other words, residential wood burning was not felt to be as 

serious a problem as traffic in contributing to wintertime air pollution. 

In addition to residential wood burning fireplaces, respondents were also 

asked to rate how traffic, industry, and agricultural burning contributed to 

wintertime air pollution. Results, including responses of undecided/don’t 

know5

, are presented in Figure 2. It can be seen, first of all, that traffic was 

considered to be the most serious cause of wintertime air pollution: 

approximately one third of respondents (32%) said it was a “very” serious 

problem. Only 19% of all respondents felt that industry was to blame and 

15% felt that agricultural burning was responsible. Residential wood-burning 

fireplaces were seen as the least serious causes of wintertime air pollution: 

only 12% rated wood-burning as “very” serious. 

 

5 Typically, in attitudinal surveys, the percentage of undecided/don’t know responses is low (between 0% and 4%). We 

chose to present the percentage of undecided/don’t know responses in Figure 2 because two questions resulted in a 

relatively high percentages (8% and 9%) of respondents saying they did not know, a volunteered response rather than 

an actual response category. These indicate specific areas where more public education on the causes of 

wintertime air pollution (industry and agricultural burning) could be beneficial. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 12 

This indicates that further public education about the causes of wintertime air 

pollution is warranted. It also attests to the ability of successful public 

education campaigns to influence public perceptions, insofar as the majority 

of the general population understands that traffic causes air pollution, 

regardless of the season. For example, in the Sacramento area, the 

summertime Spare The Air program has been in effect since 1995 and, 

although it is not the only source of education, it is now highly recognizable 

among the local population in general.6

 

Figure 2 – Seriousness: Source of Wintertime Air Pollution 

(includes undecided responses) 

12

15

19

32

44

38

45

50

39

38

29

15

5

9

8

3

0% 20% 40% 60% 80% 100%

Wood-Burning

Fireplaces

Agricultural

Burning

Industry

Traffic

Very serious Somewhat serious Not at all serious Undecided

COMPARISON WITH PREVIOUS RESULTS

 5 Results this year are generally similar to those found in 2007 with 

among respondents who owned a wood burning device. 

In order to compare this year’s results with those from 2007, the undecided 

responses as well as the responses from non wood burning device owners 

were eliminated and percentages were recalculated. The combined 

responses of “somewhat” plus “very serious” for each source of wintertime 

pollution in both survey years are presented in the next chart. It can be seen 

that, in general, results are very similar – traffic in both years was viewed as 

the most serious contributor to pollution in both 2007 and 2009. As 

previously mentioned, there is a 5% increase in the percentage of 

respondents who said residential wood burning was a serious polluter, but 

the difference is not statistically significant. 

 

6

 See: SMAQMD 2008 Air Quality & Transportation Telephone Tracking Survey, Aurora Research Group, January 2009: 

nearly three quarters (74%) of all respondents were familiar with the summertime Spare The Air program. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 13 

Figure 3 – Seriousness: Source of Wintertime Air Pollution by Survey Year 

(Somewhat + Very Serious Combined; Excludes undecided responses 

among wood burning device owners) 

87

65 61

54

84

69

58 59

0

25

50

75

100

Traffic Industry Agricultural

Burning

Residential

Wood

Burning

Fireplaces

2007 2009

GROUP DIFFERENCES

 6 Significantly more females than males rated traffic and industry as 

serious causes of pollution. Caucasians were less likely than other 

ethnicities to rate industry and agricultural burning as serious causes 

of wintertime pollution. 

A total of 27 chi-square analyses (3 questions x 9 demographic features) 

were run to see if there were any demographic features that distinguished 

those who rated the causes of wintertime air pollution as serious from those 

who did not. There were only a few analyses that yielded significant 

differences: 

• females were significantly more likely than males to say that traffic

(88% vs. 80%) and industry (75% vs. 62%) were serious causes, 

• respondents less than 55 years of age were more likely than those 

older than 55 to say that industry was a serious cause of winter air 

pollution (78% vs. 59%), and 

• non-Caucasians were more likely than Caucasians to say that 

industry (82% vs. 64%) and agricultural burning (74% vs. 55%) were 

serious polluters. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 14 

Knowledge of Particulate Matter 

CURRENT RESULTS

 7 Approximately seven in ten respondents considered themselves to be 

knowledgeable about PM pollution, although only 12% of these felt 

“very” knowledgeable.

The survey asked respondents to rate their level of knowledge of particulate 

matter or PM pollution, using a three-point scale. Results are shown in the 

next pie chart. About six in ten respondents (59%) reported being 

“somewhat” knowledgeable, and a further 12% said they were “very” 

knowledgeable, for a combined total of 71%. Conversely, 29% did not feel 

they knew anything about the subject. There were no undecided responses. 

FIGURE 4 – KNOWLEDGE OF PM POLLUTION

Not At All 

Knowledgeable

29%

Very 

Knowledgeable

12%

Somewhat 

Knowledgeable

59%

COMPARISON WITH PREVIOUS RESULTS

 8 In terms of overall knowledge of particulate matter pollution, the current 

results were similar to the results found in the 2007 survey. 

The question about knowledge of PM pollution was also asked in the 2007 

baseline survey. The next figure compares current results with those from 

the two years ago (respondents with wood burning devices only). There were 

no statistically significant differences between the two years – respondents’ 

levels of knowledge of PM pollution were generally similar. 

71% 

Combined 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 15 

FIGURE 5 – KNOWLEDGE OF PM POLLUTION BY SURVEY YEAR

15% 12%

63% 59%

22% 29%

0%

20%

40%

60%

80%

100%

2007 2009

Not At All

Knowledgeable

Somewhat

Knowledgeable

Very

Knowledgeable

GROUP DIFFERENCES

 9 Knowledge about PM pollution varied by many demographic features – 

gender, household size, age, education, ethnicity, and income. Older 

respondents were noticeably more knowledgeable than younger 

respondents, highlighting a need for better informing younger residents 

about PM pollution. 

Results were dichotomized (responses of “somewhat” knowledgeable were 

combined with “very” knowledgeable vs. “not at all” knowledgeable) and chisquare analyses were run to see if there were any demographic features that 

distinguished those who claimed to be knowledgeable about PM pollution 

from those who were not. Many differences emerged: 

• males were significantly more likely than females to say they were 

knowledgeable (77% vs. 66%), 

• respondents living in households with one or two people were 

more knowledgeable than households with three or more 

members (79% vs. 63%), 

• older respondents were more knowledgeable than younger ones 

(85% of those 65 and older; vs. 75% of those between 45 and 64 

years of age; vs. 65% of those aged between 35 to 44; vs. only 

34% of those under 35 years), 

• better educated respondents were more knowledgeable than less 

educated (80% of those with college degrees vs. 60% with high 

school or some college), 

• Caucasian respondents claimed more knowledge than nonCaucasians (78% vs. 51%), and 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 16 

• wealthier households were more knowledgeable than less wealthy 

(79% of those with household incomes of over $100,000 vs. 67% 

of those in households earning less than $100,000 per year).

Wood Burning Activity 

Inventory 

CURRENT RESULTS

 10 By study design, all respondents had at least one wood burning device 

in or outside their home, the majority (83%) of which included an indoor 

fireplace. However, only a third of wood or pellet stoves (33%) or 

fireplace inserts (36%) were reported to be EPA-certified. 

The sampling design included only those Sacramento County residents who 

owned either an indoor or an outdoor wood burning device. As a follow up to 

the screening question, a series of questions was asked to determine the 

types of devices owned. Each respondent was asked about each device 

and, as a result, the results in the following chart do not sum to 100%. It can 

be seen that most homes (83%) were equipped with an indoor fireplace. 

Other less common indoor devices include wood or pellet stoves (7%) and 

fireplace inserts (6%). 

In terms of outdoor devices, 11% said they had an outdoor pit, and a few 

respondents reported owning a chimenea (4%).

FIGURE 6 – TYPE OF WOOD BURNING DEVICE

(AMONG ALL RESPONDENTS)

83%

7% 6% 4% 11%

0%

20%

40%

60%

80%

100%

Indoor

Fireplace

Wood or

pellet stove

Fireplace

insert

Outdoor pit Chimenea

All respondents were asked if their wood burning or pellet burning device was 

certified by the Environmental Protection Agency (EPA) or not. Overall, only 

11% of all respondents said their device was EPA-certified. The remaining 

majority either said it was not (62%) or were unsure (27%). 

Then the results were examined by type of device and these results are 

shown in the next chart. It can be seen that the one third of the wood burning 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 17 

devices were EPA-certified among fireplace insert owners (36%) and wood or 

pellet stove owners (33%). 

FIGURE 7 – INCIDENCE OF EPA-CERTIFIED WOOD BURNING DEVICES

36%

44%

20% 27%

33%

40%

0%

20%

40%

60%

80%

100%

Fireplace Insert Wood/Pellet Stove

EPA certified Not certified Don't know/Refused

Respondents were then asked a series of follow-up questions aimed at 

identifying how someone would find out whether or not a wood burning 

device was EPA-certified. In general, the majority of those surveyed said 

they would search online, either by conducting a Google search (73%) or 

visiting the District’s web site (www.airquality.org) (68%). Almost half said 

they would visit a retailer in the industry (48%). The results are shown in the 

next chart. 

FIGURE 8

TO FIND OUT IF WOOD BURNING DEVICE IS EPA-CERTIFIED, WOULD YOU... 

73%

68%

46%

37%

0% 20% 40% 60% 80% 100%

Other contact

Visit retailer

Visit

www.airquality.org

Google search

Friend/family, 6%

EPA, 5%

County, 4%

Manufacturer, 3%

The news, 3%

Fire department, 3%

Property mgr., 2%

Local utility, 2%

Other, 9%
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 18 

 11 Only 18% of all respondents had heard about the Change Out Incentive 

Program.

All respondents were asked if they had heard about the Change Out 

Incentive Program, which provides funding to help Sacramento County 

residents replace older, more polluting wood stoves and fireplaces with 

cleaner-burning, EPA-certified or equivalent units. Only 18% said they were 

familiar with the program, while eight in ten said they had not heard of it. 

FIGURE 9 – AWARENESS OF CHANGE OUT INCENTIVE PROGRAM

(EXCLUDING 1% OF UNDECIDEDS)

No

82%

Yes

18%

COMPARISON WITH PREVIOUS RESULTS

 12 The type of wood burning devices found in homes that have wood burning 

devices remains unchanged since 2007. 

Additional analyses compared the types of wood burning devices found in 

homes in 2007 and 2009. In 2007, this question was asked of the general 

population. In order to conduct a year-to-year comparison, the respondents 

who did not have a wood burning device in the 2007 were excluded and the 

percentages were recalculated. Results indicated that 80% of those who 

owned a wood burning device in 2007 had an indoor fireplace, which is very 

similar to the 83% found in the 2009 survey. 

Usage of Device 

CURRENT RESULTS

 13 Fifty percent (50%) of all respondents did not use their wood burning 

device last winter. Among those who did, the majority burned wood, 

pellets or manufactured logs less than once a week, while 19% burned 

at least once a week.

Respondents were asked about the frequency of burning wood last winter 

and the results are shown in the following graph. First of all, it can be seen 

that half of those surveyed said they did not burn wood, pellets or 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 19 

manufactured logs at all between November 2008 and February 2009. 

Among those who did, the largest group (30%) burned wood less than once a 

week (the 19% who said less than once a week plus the 7% who burned 

mainly on the weekends and the 4% who burned less than once a month). A 

combined total of 19% burned at least once a week, although only 3% of 

these recalled burning most nights. 

FIGURE 10 – FREQUENCY OF USE: HOW OFTEN DID YOU BURN WOOD,

PELLETS OR MANUFACTURED LOGS LAST WINTER? 

Once a week

8%

Most nights

3%

2-3 times/week

8%

Mainly 

weekends

7%

Not at all

50%

Burned wood, 

pellets, or mfg. 

logs last winter

50%

Other

1%

Less than once 

a month

4%

Less than once 

a week

19%

 14 Forty-five percent (45%) said they burned less last winter compared 

with a typical winter. The most common reason (21%) given for this 

change in behavior was the No Burn days. Combined with the 12% who 

were motivated to reduce their wood burning behavior because of air 

quality reasons, and the 2% who cited health related reasons, a total of 

35% chose to burn less last winter in order to help decrease wintertime 

air pollution.

In order to better understand the wood burning frequency results, we asked 

all respondents to compare this year’s level of wood burning activity with that 

of a typical winter. In other words, did they burn wood, pellets, and 

manufactured logs less, the same, or more from November 2008 to February 

2009 than during a typical winter? As shown in the following chart, 45% of all 

respondents claimed to have reduced their burning activity last winter 

compared with a typical year. A similar percentage (41%) said they burned 

just as much as they have in the past. Only 5% said there had been an 

increase in amount of their wood burning last winter, and 9% were 

undecided. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 20 

FIGURE 11 – FREQUENCY OF USE COMPARED WITH PREVIOUS WINTERS

Did You Burn Less, the Same, or More this 

Past Winter than a Typical Winter?

(among all respondents)

45% 41%

5% 9%

0%

20%

40%

60%

80%

100%

Less The same More Don’t

know/Refused

Those who burned less were asked to briefly explain why. When the openended responses were categorized, we found that 21% specifically 

mentioned No Burn days, 12% said they burned less for air quality reasons, 

and 2% mentioned health concerns. Ten percent said they no longer use 

their device, while 7% found wood burning to be too expensive now. 

FIGURE 12 – REASONS FOR BURNING LESS THIS WINTER

THAN A TYPICAL YEAR

Air quality 

reasons

12%

No longer use it

10%

Financial 

concerns

7%

Other

6%

Not cold 

enough/No 

need

16%

Health concerns

2%

Have small kids

2%

No Burn days

21%

Had less wood

Device not 2%

working

3%

Not at home a 

lot

5%

Inconvient

6%

Use heater 

instead

8%
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 21 

Some of the categorized verbatim comments for the most common reasons 

for burning less wood included: 

No Burn messages

- “Because of the burn regulations. 

- Because of the air quality control messages of non-burn days and we try to 

follow that. 

- Because of the rules we now check before we burn. 

- For the contamination and also that we have to call before burning. 

- Stupid laws because we burn wood to heat home. 

- The Air Alerts and there were a lot of days I couldn’t burn. 

- The new laws in effect. 

- They put quite a few restrictions on burning, so we're trying to do something 

else. 

- We burned less to do to the wood burning laws in effect. 

- We were watching for which days were okay to burn. 

- You have to look before you burn. I just don't have the time.” 

Poor air quality

- “Air pollution. 

- Because I don't want to put the pollution in the air. I only burn when it rains. 

- Due to the contamination to the world environment. 

- I'm aware of the carbon footprints burning wood leaves behind. 

- I realized it was bad for the environment and haven't burned since. 

- Just because we were concerned about air quality. 

- Pollution concerns. 

- The environment. All the other pollution. Fires in your home are nice but the 

smoke is going in the air.” 

No need/Not as cold this winter

- “I don't think the winter was a harsh this year. 

- Global warming, It wasn't that cold this last winter. 

- I personally think it was a warmer winter and was gone a lot for work 

functions. 

- It seemed like it was less cold. 

- It started to get warmer earlier here. 

- It was a warm winter with no rain. 

- It wasn't as cold. 

- The mild winter.” 

Financial reasons

- “Because I couldn't afford it. 

- Because I have to pay for it. The Dura-Flame logs are a rare treat for me 

because of the expense. 

- Can't afford it. 

- I did not have the money to buy the wood. 

- The cost of the wood and the fire burning logs, we were cutting back on 

money, because it doesn't really heat our house. 

- The cost of wood went up. 

- The economy, buying the wood.” 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 22 

Increased heater use

- “Because I use my heater more. 

- My husband died and I don't have anybody to bring in the wood and set the 

fire. I don't need the fire going because I have the heating. 

- I use my heater. Time consuming. 

- I use the heater much more than the fireplace because you have to gather 

the wood. I don't have time even it's cheaper. 

- We were using central air.” 

Health-related reasons

- “Because my wife is allergic to the smell and to the smoke. 

- Sometimes the smell causes headaches. 

- I have a lung problem.” 

 15 The 5% who burned more wood, pellets and manufactured logs this 

winter than in the past did so because they felt it was cheaper than 

using the heater, they had wood, and they felt that this winter was 

colder than normal. 

Twenty respondents (or 5% of all respondents surveyed) said they burned 

more wood this winter than a typical winter. Two respondents were 

undecided as to why. Reasons given for increasing wood burning activity 

included:7

- the lower cost than the heater (5 respondents); 

- the availability of wood this year (4); 

- the lower temperature (3); and 

- other reasons (6). 

COMPARISON WITH PREVIOUS RESULTS

 16 Overall wood burning activity has dropped since 2007, with significantly 

fewer wood burning device owners lighting up at least once during the 

wintertime (50%) than in the previous survey (64%). 

The 2007 results indicated that the majority (64%) of wood-burning device 

owners burned wood last winter at least once during the winter months, which 

is significantly higher than the 50% found in the 2009 survey. 

 

7

 These results should be treated with caution as there are so few respondents, which is why the results are not 

presented in percentages but actual number of respondents. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 23 

FIGURE 13 – USAGE AMONG DEVICE OWNERS 

(by survey year) 

50%

36%

50%

64%

0%

25%

50%

75%

100%

2007 2009

Non-Users (Have, But Do NOT Use)

Users (Have & Use)

*

(* indicates a statistically significant difference) 

 17 Further analyses indicated that fewer burners in 2009 than in 2007 were 

lighting a fire on “most nights” and more are burning wood “mainly on 

weekends.” The total proportion of users who burned at least once a 

week dropped slightly from 58% in 2007 to 54%, although the difference 

was not found to be statistically significant. 

In terms of wood burning frequency, the results of year-to-year comparison 

analyses indicated that significantly fewer respondents who used their wood 

burning devices were lighting a fire “most nights” (6%) in 2009 than in 2007 

(16%) and significantly more were burning “mainly on the weekends” (from 

5% in 2007 to 15% in 2009). However, in terms of weekly behavior, there was 

no significant difference found between the total percent of device-owning 

respondents who said they burned at least once a week this winter (54%) and 

those who gave a similar response in the 2007 survey (58%). 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 24 

FIGURE 14 – FREQUENCY OF WOOD BURNING ACTIVITY

(AMONG WOOD BURNING USERS EXCLUDING UNDECIDED RESPONSES) 

(BY SURVEY YEAR) 

16%

21%

16%

31%

11%

15% 16% 15%

5%

32%

6%

17%

0%

10%

20%

30%

40%

50%

Most

nights *

2-3 times

a week

Mainly on

weekends

*

Once a

week

Less than

once a

week

Once a

month or

less

2007 2009

(* indicates a statistically significant difference) 

GROUP DIFFERENCES

 18 There were only three demographic characteristics that distinguished 

burners from non-burners: more burners than non burners had 

access to the Internet, some post secondary education, and lived in 

wealthier households. 

In order to try and characterize “burner” households in Sacramento County 

from those that did not burn any wood, pellets or manufactured logs last 

winter, a series of chi-square analyses were conducted, including all 

demographic features. Results indicated that those who were categorized 

as “burners” were significantly more likely to have: 

− Access to the Internet (52% vs. no access, 24%), 

− Had some post-secondary education (50% vs. not, 38%), and 

− Household earnings of at least $50,000 (54% vs. lower, 34%). 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 25 

FIGURE 15 – DISTINCTIVE DEMOGRAPHIC CHARACTERISTICS OF 

“BURNERS” VS. NON-BURNERS

(2009 SURVEY RESULTS) 

76%

62%

38%

66%

34%

52% 50% 54%

24%

48% 50% 48%

0%

20%

40%

60%

80%

100%

No access Internet

access

High school At least

some college

Income under

$50,000

Income

$50,000 or

more

Non-burners Burners

Additional analyses compared the responses of “burners” and “non-burners” 

in terms of why they burned less this winter compared with a typical year. 

Results indicated that “burners” were significantly more likely than nonburners to say that it wasn’t cold enough (17% vs. 3%). 

Awareness of the Check Before You Burn Program 

Unaided Awareness: Aware of No Burn Notices 

CURRENT RESULTS

 19 The outreach messages have been successful in reaching the 

population: three in four (76%) respondents recalled the No Burn day 

messages that notified them not to burn wood. 

When respondents were asked if they had heard, read, or seen any news 

stories, radio commercials, or e-mails informing them not to use their wood 

burning fireplaces or outdoor fire pits because of poor air quality last winter, 

the majority recalled some form of exposure (76%). One in five respondents 

(21%) said they did not recall hearing or seeing a No Burn message and 3% 

were undecided for a total of 24% who were unaware. 

Those who were aware of the No Burn messages were asked if they decided 

not to burn wood because of them. About half said they had not reduced 

their burning (48%) or were undecided (3%). The other half (49%) reduced 

the number of fires they burned last winter because of the notices they heard 

or saw. This translates into 37% of all respondents that reduced wood 

burning because of the publicity, as shown in the next graph. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 26 

FIGURE 16 – AWARENESS OF MESSAGES AND CHANGE IN BEHAVIOR

(AMONG ALL RESPONDENTS)

Unaware or 

Undecided

24%

NonResponse 

(3%)

Aware, but 

still burned 

wood (36%)

Aware, and 

reduced 

wood 

burning 

(37% of total 

population)

Aware of 

No Burn 

messaging

76%

Unaided Awareness: Familiarity with the Check Before You Burn Program 

CURRENT RESULTS

 20 Name recognition of Check Before You Burn is also high, with 72% 

claiming to be familiar with the Check Before You Burn program. 

However, not everyone was able to accurately describe it. 

All respondents were asked about their familiarity with the Check Before 

You Burn program, using a three-point scale. This question was 

designed to evaluate respondents’ unaided awareness of the program 

name. Results, as shown in Figure 16, are fairly evenly split among the 

three responses: 38% said they were very familiar with the program and 

34% said they were “somewhat” familiar with it for a total of 72% who 

claimed to be familiar. The remaining 28% admitted to being not at all 

familiar with the Check Before You Burn program. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 27 

FIGURE 17 – UNAIDED AWARENESS: FAMILIARITY WITH THE CHECK BEFORE 

YOU BURN PROGRAM

(EXCLUDING UNDECIDED RESPONSES) 

Very 

Familiar

38%

Not At All 

Familiar

28%

Somewhat 

Familiar

34%

Verification of what was actually known about the program was determined 

by asking those who said they were “somewhat” or “very” familiar with the 

Check Before You Burn program to briefly describe it. Responses were 

recorded and then categorized and coded. Overall the vast majority 

accurately described aspects of the program, but a few responses indicated 

some misperceptions. Complete transcripts of all descriptions will be 

available in the statistical report. 

41% mentioned the need to check to see if wood burning is permitted 

on a particular day. A sample of some of the verbatim responses includes: 

- “Basically, you check in the newspaper to see if you can burn or not. There are 

two conditions to check. There are voluntary restrictions and then there are days 

you can not burn at all unless it is your only heat source. 

- Check the paper or web site if it’s a burn day or not. 

- Everyday we check the paper to see if it is burn or no burn day. 

- I call before I burn. 

- I know that you can look in the paper or online to see if burning is allowed those 

days. 

- I know there is an alert system on the news that tells you when not to burn. 

- I have the number in my cell phone and I would call before I burn. 

- On a particular day somebody decides whether or not we can have a fire due to 

the quality of air and we have to call a number to find out if we can have a fire 

that night, or we can check online too. 

- That we have to call to see if we can use our chimenea. 

- We are supposed to check everyday before we do any burning that's allowed by 

the county to help the air quality. 

- We usually check online and I think there is also a number you can call and they 

tell you if it is a non-burn day. We watch a morning news show and it mentions it 

too. Our neighbors often talk about it. 

- You can be fined if you're burning on a day you're not supposed to burn, and you 

can check online to find out. 

72% combined
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 28 

23% mentioned the no burn days in general. A sample of these verbatim 

responses includes: 

− “Days that recommended not to burn. 

− Depending upon the air quality that day is the condition whether we can burn 

wood on that day or not. I would assume somebody makes that decision 

whether we can burn a fire or not. I get that information in the paper daily. 

− If it is limited or restricted to burn. Or no burning what so ever. 

− On certain burn you can burn and some days you can't. 

− Some days you can burn and some you can’t. And some days it is just 

discouraged. 

− That there were days that we should not burn and days that we are allowed to 

burn. I tried to abide by them but there were days when it was very cold and it 

was more economical to burn than to use other heating sources. 

− There's a day that you can burn and if air quality is bad you can't burn. There's 

an index or something. 

− There are no burn days.” 

17% indicated that the program told them when to burn and not to burn. 

They mentioned the messages they see on the news or read in the 

newspaper, although didn’t specifically say they had to check before 

they burned wood. 

− “We were notified that there are certain days that we can burn, and they notify us 

if air quality is poor. 

− Control the smog in the area. On the news it tells you if you can burn on that 

day. 

− I know that the news on certain channels they will give you an update on the 

status. 

− On the news, they tell when to burn and not to burn. 

− That they notify when you’re supposed to burn and not to burn. 

− That there is a warning that's issued in newspapers, TV, and radio. 

− They announce on the TV what days to burn or not to burn wood. 

− They check the day before to put up a sign or notice for the next day to let people 

know about when it's okay to burn. 

− They forecast what they think the air quality is going to be for that day and then 

tell us whether we can burn or not. They give us a scale. I don't feel they are 

honest about it. 

− They have notices on the nightly news on TV telling you whether or not it's okay 

to burn. 

− They just tell us day to day whether we can burn or not. 

− They just tell you what certain days are high danger for that day, so they tell you 

not to burn. 

− They put it in the Bee that you shouldn't burn on a particular day because of the 

air quality. 

− They put it in the paper everyday with the weather forecast, if you can burn or 

not. 

− They tell you on T.V. not to burn. 

− Well I just know that they advertise it on the news and when they do, I don’t burn 

fires. I don’t check online or anything.” 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 29 

However, 3% may feel that the program is optional and voluntary. A 

sample of these comments includes:

− “Days that recommended not to burn. 

− I heard that there are some burn days that they suggest you don't burn because 

of air quality. I believe it showed in the paper those days. 

− It is an optional program with notices in the local newspapers regarding whether 

or not fire burning is recommended on a particular day. It would be helpful if they 

put the info about it in the same place in the newspaper (The Sacramento Bee). 

− The Sacramento Bee and the TV Stations & NPR mention when there is a no 

burn day. Right now the program is voluntary and they are probably not going to 

be able to enforce it and there is a waiver if you are poor. 

− I know the program is out there, and they are trying to restrict burning because it 

causes particulates in the air. 

− The city encourages non-burning and certain days of the week and an incentive 

for converting to a better solution to eliminate the harmful stuff. 

− It provides educational information about knowing the air quality before you burn.” 

A few (2%) had misconceptions about the focus of the No Burn 

program. A sample of those comments includes:

− “It is about burning of substances and what it produces. 

− Make sure to keep the chimney clean and check the shaft and make sure it is 

open. 

− You are supposed to have your flue checked, not sure of the frequency. Make 

sure the flue is open. 

− You can burn leaves and garden waste and you are supposed to check to see if 

it is okay to burn. 

− You have to get a permit for outside fires for burning leaves, trash. Anything you 

burn has to be in a container.” 

6% said they were familiar with the program, but when asked to 

describe it, they simply gave (mostly negative) commentary. A sample 

of these comments includes:

− “That they are nosy and it is none of their damn business. 

− I just know that there are times when the air pollution is really bad. 

− I don't believe it means anything. I think it is a bunch of boohoo. There are not 

that people that burn uncontrollably, to a point that would matter to the air quality 

control. 

− I just don't burn anymore, air quality doesn't allow us. It's just not fair. 

− It is a pain in the rear end. 

− It sucks. We have more cars blowing out more smoke than fireplaces burning for 

a couple of hours. 

− The conditions that need to prevail in order to be looked at to see what is going 

to build up in the air so as long as we have a breeze i don't worry about it. 

− The risk of burning and not burning.” 

Aided Awareness: Familiarity with the Check Before You Burn Program 

CURRENT RESULTS

All respondents, regardless of their familiarity with the program were then 

read the following description: 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 30 

You may or may not have heard that in Sacramento County, it is now law that 

from November to February residents and businesses are prohibited from using 

indoor or outdoor fireplaces, wood stoves, fire pits and chimeneas that burn 

wood, pellets, manufactured logs or any other solid fuel on days when air quality 

is forecast to be unhealthy to breathe. It is your responsibility to Check Before 

You Burn, to see if it is permissible to light a fire. 

 21 Among respondents who previously were not at all familiar with Check 

Before You Burn, the majority said it sounded familiar to them after 

being read a description. 

The 28% of respondents who were previously unfamiliar with the program 

were asked if it sounded it familiar after hearing the brief description. Six in 

ten (60%) said it did. 

FIGURE 18 – AIDED AWARENESS: FAMILIARITY WITH PROGRAM 

AFTER HEARING A DESCRIPTION

(AMONG THOSE NOT FAMILIAR IN THE UNAIDED QUESTION)

No

Yes 40%

60%

 22 The program has already achieved successful visibility: when results 

of the unaided and aided awareness questions were combined, overall, 

92% of all respondents were aware of the Check Before You Burn 

program. 

Overall awareness of the program was measured through a combination of 

responses. To be considered “aware”, a respondent: remembered seeing or 

hearing notices not to burn; or said they were somewhat or very familiar with 

the Check Before You Burn program (unaided awareness); or said that the 

program sounded familiar to them after hearing a description of it (aided 

awareness). Combining the results of these unaided and aided awareness 

questions indicated that the vast majority of all 400 respondents (370 

respondents, or 92%) were aware of the program. Only 8% were still 

unfamiliar (or undecided or refused to answer) with the Check Before You 

Burn program, as shown in the next chart. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 31 

FIGURE 19 – OVERALL AWARENESS: UNAIDED + AIDED AWARENESS

(AMONG ALL 400 SURVEY RESPONDENTS)

Unaware,

Undecided, 

or

Refused

Aware 8%

92%

Awareness of Different Levels of the Program 

CURRENT RESULTS

 23 Approximately seven in ten respondents (74%) who were aware of 

Check Before You Burn were also aware of the Burn Cleanly, Burning 

Discouraged and Stage 2- All Burning Prohibited levels. However, 

recognition of the Stage 1- No Burn Unless Exempt level was much 

lower, at just over half (54%) of these respondents. Although it could be 

attributed to less exposure to that level (there were fewer actual Stage 1 

days), program organizers might want to consider increasing efforts 

aimed at educating the public specifically about Stage 1 requirements. 

Alternatively, they might also consider eliminating the Stage 1 category 

altogether in order to reduce confusion. 

The 370 respondents who were aware of the Check Before You Burn 

program (either in the aided or unaided questions) were asked more 

specifically about their awareness of each of the four levels in the program, 

using the scale: not at all, somewhat, or very aware. The four levels of the 

Check Before You Burn program include: 

 Burn Cleanly. The public is allowed to burn and the burning of 

manufactured fire logs is acceptable at this level. 

 Burning Discouraged. This is when residents are requested to 

voluntarily not burn. 

 Stage 1 – No Burn Unless Exempt. At this level, burning is 

prohibited unless EPA-certified wood burning or pellet devices are 

used. First time violations will result in a $50 fine or a requirement to 

take a compliance course. Fines for subsequent violations will be 

higher. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 32 

 Stage 2 – All Burning Prohibited. At this level the burning of any

solid fuel, including wood, manufactured logs and pellets, is prohibited 

with the same penalties as in Stage 1. 

Results of respondents’ awareness of each of the four levels are shown in the 

next chart. It can be seen, first of all, that the voluntary restriction (Burning 

Discouraged) is the most widely recognized level – 74% of the respondents 

who were aware of Check Before You Burn were also aware of the Burning 

Discouraged level (combined responses of “somewhat” and “very” aware). 

This was followed closely by awareness of the Burn Cleanly level (71%), and 

Stage 2 – All Burning Prohibited level (67%). However, it can also be seen 

that awareness of Stage 1 – No Burn Unless Exempt is significantly 

lower than the other three levels – only 54% of these respondents were 

aware of this level. It is recommended that further efforts be made to educate 

the population about this particular level. Alternatively, they might also 

consider eliminating the Stage 1 category altogether in order to reduce 

confusion.

It should be noted that this lower level of awareness of Stage 1 No Burn days 

may be due to the decreased exposure to this particular level. There were 

fewer Stage 1 No Burn days in the 2008-09 season than Stage 2 and Burning 

Discouraged: only 10 days compared with 28 Stage 2 No Burn days and 28 

Burning Discouraged days. 

FIGURE 20 – AWARENESS OF SPECIFIC PROGRAM LEVELS

(AMONG THOSE AWARE OF CHECK BEFORE YOU BURN; EXCLUDING UNDECIDED RESPONSES)

43% 43% 32% 44%

28% 31%

22%

23%

29% 26%

46%

33%

0%

20%

40%

60%

80%

100%

Burn Cleanly

(71% aware)

Burning

Discouraged

(74% aware)

Stage 1 No

Burn Unless

Exempt (54%

aware) *

Stage 2 All

Burning

Prohibited (67%

aware)

Very aware Somewhat aware Not at all aware

* indicates a statistically significant difference from the other three levels 

GROUP DIFFERENCES

 24 There were very few demographic features that distinguished those 

aware of each of the levels from those not aware, indicating that the 

program can continue to be aimed at the general population rather than 

targeting specific groups of individuals. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 33 

Results were dichotomized (responses of “somewhat” aware were combined 

with “very” aware vs. “not at all” aware) and 36 chi-square analyses (4 levels 

x 9 demographic variables) were run to see if there were any demographic 

features that distinguished those who were aware of each level from those 

who were not. Results indicated that in general, awareness of the four levels 

of the program did not vary by demographics – males were just as aware 

(and unaware) as females, better educated respondents were just as aware 

as less educated, households with high incomes were just as aware as those 

with lower incomes, those living with alone were just as aware as those living 

with other people, etc. The few differences that did emerge indicated that: 

• owners were significantly more aware of all four levels than were 

those who rented, 

• those older than 35 years were significantly more aware of the Burn 

Cleanly and Burning Discouraged levels than were those younger 

than 35 (73% vs. 50%; and 77% vs. 47% respectively), 

• those who had Internet access were significantly more aware of the 

Stage 2 – All Burning Prohibited level than those who did not have 

access (70% vs. 46%), and 

• Caucasians were significantly more aware of the Burn Cleanly level 

than non-Caucasians (75% vs. 59%). 

Additional analyses were conducted among the small group of respondents 

who reported having an EPA-certified wood burning device to see if 

awareness of each program level varied. In general, awareness among 

those with EPA-certified devices was similar across the four program levels. 

Any differences shown in the chart below were not found to be statistically 

significant, which may be attributed to the small size of this subgroup: only 45 

respondents. 

FIGURE 21 – AWARENESS OF SPECIFIC PROGRAM LEVELS

(AMONG THOSE WITH AN EPA-CERTIFIED DEVICE; EXCLUDING UNDECIDED RESPONSES)

56% 60% 57% 60 %

33% 28%

19% 21 %

11% 12%

24% 19 %

0%

20%

40%

60%

80%

100%

Burn Cl eanl y Burn ing

Discou raged 

Stage 1 No

Burn Unl ess

Exempt 

Stag e 2 All

Bu rning

Pro hibi ted

Very aware Somewhat aware Not at all aware
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 34 

Knowledge about Different Aspects of the Program 

CURRENT RESULTS

 25 The majority of respondents (71%) recognize that it is their 

responsibility to see if it is permissible to burn wood. 

All 400 respondents were asked: “Before today, did you know that it was your

obligation to check to see if you were permitted to burn wood on any given 

day or night during the winter?” Seventy-one percent said they did, while the 

remaining 29% were unaware of this fact. 

FIGURE 22 – AWARENESS OF PERSONAL OBLIGATION 

TO CHECK BEFORE BURNING

(AMONG ALL 400 SURVEY RESPONDENTS)

No

29%

Yes

71%

 26 Nearly half (47%) of the respondents who were aware of the Stage 1 and 

Stage 2 levels knew that it was illegal to burn manufactured logs on 

Stage 1 and Stage 2 No Burn days. 

Respondents who were aware of the Stage 1 and Stage 2 levels were asked 

if they knew that it was illegal to burn manufactured logs on Stage 1 and 

Stage 2 No Burn days. More than half (53%) were unaware of this fact, while 

the remaining 47% said they knew this information.
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 35 

FIGURE 23 – AWARENESS OF RULE AGAINST BURNING MANUFACTURED 

LOGS ON STAGE 1 AND STAGE 2 NO BURN DAYS

(AMONG THOSE WHO WERE AWARE OF THE STAGE 1 AND STAGE 2 LEVELS)

No

53%

Yes

47%

GROUP DIFFERENCES

 27 Demographically speaking, there was really no difference between 

those who were aware of the program details from those who were not.

There were no demographic characteristics that distinguished those who knew 

it was their responsibility to check before they burned from those who did not. 

Similarly, no statistically significant differences were found in the demographic 

responses between those who knew it was illegal to burn manufactured logs 

on Stage 1 and Stage 2 No Burn days and those who did not. 

Compliance with the Check Before You Burn Program 

Among Those Aware at Each Level 

CURRENT RESULTS

 28 Compulsory measures appear to be more effective than voluntary 

requests: among those who were aware of each level, compliance with 

all Stage 1 and Stage 2 No Burn days was significantly higher (at nearly 

90%) than voluntary compliance when burning was simply discouraged 

(only 26%). 

Those who were aware of each of the levels higher than the Burn Cleanly 

level were asked how frequently they complied with the notices during the 

past winter. It can be seen in the following chart that respondents were more 

willing to comply with the law (illegal to burn) than with a request (burning 

discouraged), with 87% saying they complied with all Stage 1 No Burn days 

and a similar (89%) percent indicating compliance with Stage 2 No Burn 

days, compared with only 26% who said they chose not to burn each time 

burning was discouraged. Conversely, the percentage of respondents who 

said they did not comply with any burn days was highest when burning was 

discouraged (55% of respondents) than when it was compulsory – only 7% 

defied the Stage 1 No Burn days and 6% defied the Stage 2 No Burn days. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 36 

FIGURE 24 – COMPLIANCE WITH THE CHECK BEFORE YOU BURN PROGRAM 

BY SPECIFIC LEVEL

(AMONG THOSE AWARE OF EACH LEVEL; EXCLUDING UNDECIDED RESPONSES) 

26%

19%

5% 5%

55%

7% 6%

87% 89%

0%

20%

40%

60%

80%

100%

Burning Discouraged Stage 1 No Burn

Unless Exempt

Stage 2 All Burning

Prohibited

All of them At least one, but not all None

Among the Total Respondent Base 

CURRENT RESULTS

 29 In terms of the total base of respondents (all of whom owned wood 

burning devices), 32% complied with every voluntary Burning 

Discouraged request, 42% complied with every Stage 1-No Burn Unless 

Exempt directive; and 52% complied with all Stage 2-All Burning 

Prohibited days. In other words, compliance increased as the level of 

restrictions increased. 

In order to generalize to the entire base of respondents, compliance within 

each level was re-calculated: those who said they either complied with all 

burn days or at least one of them were coded as “compliers”; all other 

respondents (those who did not comply, those who were undecided, those 

who were unaware of each level and those who refused to answer) were 

combined and coded as “non compliers.” When based on the total population 

of respondents, it can be seen in the next chart that of the total base of 

respondents, all of whom owned wood-burning devices, 52% complied with 

all Stage 2 No Burn days this past winter and a further 3% complied with at 

least one of them, indicating that over half of the population complied with the 

mandatory Burning Prohibited level of the Check Before You Burn program. 

It can also be seen that compliance with all notices increased as the 

restrictions increased. In other words, significantly fewer respondents 

refrained from burning on all voluntary Burning Discouraged days (32%) than 

with all Stage 1 No Burn days (42%); and in turn, significantly more 

respondents complied with all Stage 2 No Burn days (52%). 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 37 

FIGURE 25– COMPLIANCE WITHIN THE TOTAL GROUP OF RESPONDENTS

(INCLUDES ALL 400 RESPONDENTS) 

32% 42% 52%

12% 2%

3%

56% 56% 45%

0%

20%

40%

60%

80%

100%

Burning

Discouraged (44%

compliers)

Stage 1 No Burn

Unless Exempt (44%

compliers)

Stage 2 All Burning

Prohibited (55%

compliers)

Complied with all Complied with at least one but not all Non-complier

GROUP DIFFERENCES

 30 Compliance was relatively independent of demographics -- there were 

only three features that distinguished compliers from others within 

each level of the program: home owners, those older than 35 years, and 

those whose ethnicity was Caucasian were more likely to comply. 

Respondents who complied all the time were combined with those who 

complied at least once within each of the three program levels and analyses 

comparing compliers versus all other respondents were run to determine if 

there were any distinguishing demographic features. In total, 27 analyses 

were run (3 levels x 9 demographic variables). 

Results indicated that, in general, those who were aware of and complied 

with each of the three Check Before You Burn levels had the same 

demographics as those who did not comply – both males and females 

complied or did not with Burning Discouraged, or Stage 1 or Stage 2; less 

well educated respondents were just as likely (or not) to comply as those 

better educated, households with low incomes were just as likely to comply 

within each level as those with higher incomes, those living with alone were 

just as likely to comply as those living with other people, etc. The few 

differences that did emerge indicated that more compliers within each of the 

three levels: 

• owned their homes than rented them: 

 Burning Discouraged - (47% owners vs. 31% renters), 

 Stage 1 – (47% vs. 28%), and 

 Stage 2 – (59% vs. 42%), 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 38 

• were over 35 years of age than under 35 years of age: 

 Burning Discouraged - (47%% older vs. 21% younger), 

 Stage 1 – (46% vs. 21%), and 

 Stage 2 – (58% vs. 30%), 

• were Caucasian than non-Caucasian 

 Burning Discouraged - (49% Caucasian vs. 30% nonCaucasian), and 

 Stage 2 – (61% vs. 41%). 

 31 Among EPA-certified device owners, compliance with Stage 1 No Burn 

days was just as high as it was for Stage 2 days, even though they were 

exempt and legally allowed to burn on Stage 1 No Burn days. 

Additional analyses were conducted among the small group (45 respondents) 

who reported having an EPA-certified wood burning device to see if their level 

of compliance varied by program level. It can be seen in the following chart 

that EPA-certified device owners were just as likely to comply with Stage 1 

No Burn days when they were exempt as they were with Stage 2 days, 

indicating that there is no advantage to keeping the Stage 1 No Burn 

Unless Exempt level in the program8

. They were also significantly more 

likely to comply with all Stage 1 and Stage 2 No Burn days (both 84%) as 

they were with Burning Discouraged days (55%). 

FIGURE 26 – COMPLIANCE WITH SPECIFIC PROGRAM LEVELS

(AMONG THOSE WITH AN EPA-CERTIFIED DEVICE; EXCLUDING UNDECIDED RESPONSES)

55%

24%

21% 6% 6%

9% 9%

84% 84%

0%

20%

40%

60%

80%

100%

Burning Discouraged Stage 1 No Burn

Unless Exempt

Stage 2 All Burning

Prohibited

Complied with all Complied with at least one, but not all Non-complier

 

8 Given that there is already some confusion about Stage 1 qualifiers, this analysis offers additional support for possibly 

eliminating the Stage 1 level from the Check Before You Burn program. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 39 

Communication Channels 

Among Those Aware of the Check Before You Burn Levels 

CURRENT RESULTS

 32 Using news media to announce No Burn days is an effective 

communication channel: the vast majority of respondents aware of the 

program heard about the No Burn days on television and radio (85%), 

followed by newspapers (58%). 

Respondents who were aware of any of the Check Before You Burn levels 

(i.e. those who said they were either “somewhat” or “very” aware of the Burn 

Cleanly, Burning Discouraged, Stage 1-No Burn Unless Exempt, or Stage 2-

All Burning Prohibited levels) were asked how they heard about the No Burn 

days during the past winter. The exact wording of the question was: 

I am going to read you a list of possible ways that residents could have found out 

about the air quality and whether or not they could burn wood on a particular day. 

I’d like you to tell me how you might have heard about the No Burn days during 

this past season. Did you ... 

Results are presented in the next chart. It can be seen that the vast majority 

of these respondents (85%) heard about No Burn days via television and 

radio. Nearly six in ten (58%) read about the No Burn days in the newspaper, 

and approximately one fifth (21%) saw the information on a web site. Eight 

percent (8%) called a telephone number to hear a recorded message and 

only 2% of these respondents were Air Alert subscribers – that is, those who 

received either an e-mail or a text message from the District. Further efforts 

could be made to increase the number of Air Alert subscribers and to 

better publicize the phone-in telephone number. Of those who said they 

learned about the No Burn days some other way, the most frequently 

mentioned channel was via word of mouth, through friends, neighbors and 

colleagues. 

FIGURE 27 – COMMUNICATION CHANNELS 

(AMONG THOSE AWARE OF PROGRAM, EXCLUDING UNDECIDED RESPONSES) 

85

58

21

15

8

2

0 20 40 60 80 100

See or hear it in the general news media,

such as TV and radio?

Newspaper

See the information on a website? 

Other? (Heard about it by word of mouth)

Call a telephone number and listen to a

recorded message?

Receive an email or a text on your cell

phone?
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 40 

COMPARISON WITH PREVIOUS RESULTS

 33 The general news media was also the preferred communication channel 

identified in the 2007 baseline survey. 

In the 2007 baseline survey, respondents were read a list of possible ways 

that residents could find out about whether or not they could burn wood in the 

event that a mandatory no-burn rule was adopted, and were asked to rate 

each one in terms of how effective it would be for them personally, using a 

four-point scale: poor, fair, good, or excellent. Results indicated that 84% of 

respondents said they would prefer to hear about No Burn days (combined 

ratings of “good” plus “excellent”) via the general news media of television, 

radio, and newspapers; the same percentage who actually did hear about the 

No Burn days through television and radio this year. However, the 

percentages of respondents who, in 2007, thought they would prefer to visit a 

web site (43%), receive an e-mail (41%), or call a telephone number (40%) 

were in all cases substantially higher than the percentage of respondents in 

2009 who actually used these means to find out about No Burn days (21%, 

2%, and 8% respectively). 

FIGURE 28 – 2007 HYPOTHETICAL PREFERRED COMMUNICATION CHANNELS 

VS. 2009 ACTUAL USE

84

43

41

40

85

21

2

8

0 20 40 60 80 100

General news media

Posting information on a web

site

Receive an e-mail or a text on

your cell phone

Call a telephone number and

listen to a recorded message

2007 (Good + Excellent) 2009 (Yes)

GROUP DIFFERENCES

 34 How respondents heard about whether or not they could burn wood 

was relatively independent of demographic features, indicating that the 

public education campaign can continue to be aimed at the population 

in general to be effective. 

Chi square analyses were run to determine if there were any demographic 

features that distinguished those who heard about the No Burn days via 

television and radio, via newspaper, or via the web site from those who did not.9

 

 

9 The percentages who heard the messages via email or by calling a telephone number were too small to be analyzed by 

demographics. 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 41 

Results indicated that in general, the communication channels respondents 

used to hear about whether they could burn wood were independent of 

demographic features – both males and females learned about the No Burn 

days via the general media, newspaper, or via the web site; less well 

educated respondents were just as likely to have used the three channels as 

those better educated, households with low incomes were just as likely to 

have used the channels as those with higher incomes, those living with alone 

were just as likely as those living with other people, etc. The few differences 

that did emerge indicated that: 

• those who learned about the No Burn days from the newspaper

were more likely to own their homes (61%) than to rent them 

(40%); and to be older than 45 years of age (62%) than younger 

than 45 years (42%), and 

• those who accessed the web site were more likely to be younger 

than 45 years of age (34%) than those aged between 45 and 64 

years (21%) or 65 years and older (8%). 

Demographics 

 35 A plurality of respondents who owned wood burning devices and lived in 

Sacramento County were: females who live with one to three other people in a 

home they own. They hold a college degree, have access to the Internet, are 

non-subscribers to Air Alert, are at least 45 years of age, self-identify as 

Caucasian, and have an annual household income of at least $50,000. 

Table 2 provides the reader with the respondent demographics from the interviews 

conducted with the sample of Sacramento county residents who had wood burning 

devices either inside or outside their homes. 

Table 2 

 GENDER PERCENT

Female 52% 

Male 48% 

Total 100% 

 SURVEY LANGUAGE PERCENT

English 98% 

Spanish 2% 

Total 100% 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 42 

AIR ALERT SUBSCRIPTION PERCENT

No 94% 

Yes 4% 

Non-response 2% 

Total 100% 

ETHNIC BACKGROUND PERCENT

African-American 5% 

Asian/Pacific Islander 6% 

Caucasian 70% 

Hispanic/Latino 11% 

Something else 3% 

Non-response 5% 

Total 100% 

HOUSEHOLD SIZE PERCENT

Live alone 15% 

Two members 35% 

Three members 18% 

Four members 20% 

Five or more members 11% 

Non-response 1% 

Total 100% 

ACCESS TO THE INTERNET PERCENT

Yes 89% 

No 10% 

Non-response 1% 

Total 100% 
Sacramento Metropolitan Air Quality Management District 

2009 Wood Burn Awareness Survey 

Final Results Report 

May, 2009

Dawn Morley Chavero & Naomi E. Holobow, Ph.D. Page 43 

HOME OWNERSHIP PERCENT

Own 86% 

Rent 16% 

Non-response 1% 

Total 100% 

EDUCATION PERCENT 

High school or less 17% 

Some college 24% 

Trade/vocational school 4% 

College degree 37% 

Post-graduate degree 16% 

Non-response 2%

Total 100% 

AGE PERCENT 

18-24 3% 

25-34 8% 

35-44 17% 

45-54 26% 

55-64 21% 

65 and older 23% 

Refused 2% 

Total 100% 

2008 ANNUAL 

HOUSEHOLD INCOME

PERCENT 

Under $20,000 6% 

$20,000 to $49,999 16% 

$50,000 to $99,999 37% 

$100,000 or more 27% 

Non-response 14% 

Total 100% 
APPENDIX D 

STI Final Report 

Evaluation of SMAQMD’s Check Before You Burn Program 

(See May 2009 Board Letter)
EVALUATION OF SACRAMENTO 

METROPOLITAN AIR QUALITY 

MANAGEMENT DISTRICT’S 

“CHECK BEFORE YOU BURN” PROGRAM 

FINAL REPORT 

STI-909014.06-3612-FR2 

By: 

Clinton P. MacDonald 

Kenneth J. Craig 

Jennifer L. DeWinter 

Adam N. Pasch 

Steven G. Brown 

Neil J. M. Wheeler 

Sonoma Technology, Inc. 

1455 North McDowell Blvd., Suite D 

Petaluma, CA 94954-1169 

Prepared for: 

Sacramento Metropolitan Air Quality 

Management District 

777 12th Street, 3rd Floor 

Sacramento, CA 95814 

May 6, 2009 

Updated August 24, 2009 
iii

ACKNOWLEDGMENTS 

The authors of this report thank several Sonoma Technology, Inc. staff who contributed 

to this project: Hilary Hafner and Paul Roberts for their scientific advice and guidance; Charley 

Knoderer for creating the air quality climatology plots used in this report; and Steve Reid and 

Sandy Smethurst for editing this report. 
v

TABLE OF CONTENTS 

Section Page

ACKNOWLEDGMENTS ............................................................................................................. iii

LIST OF FIGURES ...................................................................................................................... vii 

LIST OF TABLES......................................................................................................................... ix 

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

2. SUMMARY OF FINDINGS ............................................................................................. 2-1 

3. METHODS......................................................................................................................... 3-1 

3.1 Program Effectiveness.............................................................................................. 3-1 

3.2 CMB Modeling......................................................................................................... 3-6 

3.2.1 CMB Background......................................................................................... 3-7 

3.2.2 Data Processing and Quality Assurance....................................................... 3-7 

3.2.3 Source Profiles and Model Certainty ......................................................... 3-10 

3.3 Season Representativeness ..................................................................................... 3-12 

3.4 No-burn Thresholds................................................................................................ 3-13 

3.5 Build-up Day Rule.................................................................................................. 3-13 

4. FINDINGS ......................................................................................................................... 4-1 

4.1 Program Effectiveness.............................................................................................. 4-1 

4.2 CMB Modeling......................................................................................................... 4-4 

4.3 Season Representativeness ..................................................................................... 4-11 

4.4 No-burn Thresholds................................................................................................ 4-14 

4.5 Build-up Day Rule.................................................................................................. 4-15 

5. REFERENCES................................................................................................................... 5-1

APPENDIX A: ADDITIONAL FINDINGS ON THE EFFECTIVENESS OF THE 

BURNING CURTAILMENT PROGRAM TOWARD MEETING THE NAAQS A-1
vii

LIST OF FIGURES 

Figure Page

3-1. Example of surface and 500-mb weather patterns used to determine matching d 

day-pairs.......................................................................................................................... 3-4 

3-2. Reconstructed mass of samples during winter 2008/2009.............................................. 3-8 

3-3. Average reconstructed concentrations plus the difference between the total 

reconstructed and measured concentrations for all winter 2008-2009 sample dates...... 3-9 

3-4. Allocation of annual wood-burning emissions by month............................................. 3-16 

3-5. BlueSky Gateway model grid in the Sacramento County region ................................. 3-17 

4-1. Average hourly PM2.5 time series for the Stage 2 and Stage 1 day pairs........................ 4-3 

4-2. Source contribution estimates for each profile averaged across all winter 2008-2009 

sample dates, all 2008/2009 Stage dates, Stage 1 days with matching no-restriction 

days, Stage 2 days with matching no-restriction days, no-restriction days with 

meteorology similar to Stage days.................................................................................. 4-5 

4-3. Percent of contributions to total calculated concentrations for the eucalyptus, oak, 

almond, and combined wood burning source profile...................................................... 4-8 

4-4. Number of days that PM2.5 concentrations exceeded the NAAQS from the 

2004/2005 through 2008/2009 winter seasons, and estimated number of days 

PM2.5 concentrations would have exceeded the NAAQS without the CBYB 

program......................................................................................................................... 4-12 

4-5. Number of meteorologically conducive days for high PM2.5 concentrations for the 

2004/2005 through 2008/2009 winter seasons ............................................................. 4-12 

4-6. Distribution of peak daily PM2.5 AQI by category for the 2008/2009 season 

observed and estimated if there was no CBYB program.............................................. 4-13 

4-7. Average PM2.5 pollution episode length for the 2004/2005 through 2008/2009 

winter seasons ............................................................................................................... 4-13 

4-8. Time series of BlueSky Gateway PM2.5 concentrations in northeast Sacramento 

County for November 29 through November 30, 2008, for one-day and two-day 

residential wood-burning curtailment scenarios ........................................................... 4-17 

4-9. Time series of observed average hourly PM2.5 concentrations using data from 

Folsom and Del Paso Manor for November 29 through November 30, 2008.............. 4-17 
viii

LIST OF FIGURES 

Figure Page

4-10. Time series of BlueSky Gateway PM2.5 concentrations in northeast Sacramento 

County for December 9, 2008, through December 10, 2008, for one-day and 

two-day residential wood-burning curtailment scenarios............................................. 4-18 

4-11. Time series of observed average hourly PM2.5 concentrations using data from 

Folsom and Del Paso Manor for December 9, 2008, through December 10, 2008...... 4-18 

A-1. BlueSky Gateway model grid in the Sacramento County region .................................. A-7
ix

LIST OF TABLES 

Table Page

3-1. The 12 meteorological variables used in the cluster analysis......................................... 3-2 

3-2. Meteorological conditions for a matching day-pair: December 2, 2006, 

a no-restriction day, and January 11, 2009, a Stage 2 day.............................................. 3-3 

3-3. Matching days when meteorological conditions were similar........................................ 3-5 

3-4. PM2.5 concentrations comparisons for a day-pair: December 2, 2006, 

a no-restrictions day, and January 11, 2009, a Stage 2 day ............................................ 3-6 

3-5. Species data below method detection limits for each sample date in 

winter 2008-2009............................................................................................................ 3-9 

3-6. Chemical species included in CMB as fitting or floating species ................................ 3-11 

3-7. Cases selected for modeling analysis............................................................................ 3-14 

3-8. 2007 Sacramento County residential wood combustion emission estimates 

used in BlueSky Gateway simulations.......................................................................... 3-15 

3-9. 2009 Sacramento County residential wood combustion emission estimates 

from the CEFS database................................................................................................ 3-15 

3-10. SMOKE PM2.5 speciation profile.................................................................................. 3-16 

4-1. Average reduction (benefit) for all day-pairs, Stage 2 day-pairs, and 

Stage 1 day-pairs............................................................................................................. 4-2 

4-2. The 24-hour PM2.5 concentration reduction for each day-pair ....................................... 4-4 

4-3. Reduction in wood smoke contributions for the cluster sample dates............................ 4-7 

4-4. Performance metrics for the combined oak/eucalyptus wood burning profile............... 4-9 

4-5. Percent of wood smoke contributions to total calculated mass for each 

wood-burning profile .................................................................................................... 4-10 

4-6. Forecast bias (forecast minus observation) for various criteria.................................... 4-14 

4-7. Carryover impacts estimated by the BlueSky Gateway for northeast 

Sacramento County....................................................................................................... 4-15 

4-8. Relative carryover impacts predicted by BlueSky Gateway for Sacramento County .. 4-16 
x

LIST OF TABLES 

Table Page

A-1. Cases selected for BlueSky modeling analysis.............................................................. A-5 

A-2. SMOKE PM2.5 speciation profile................................................................................. A-6 

A-3. Modeled benefits of State 1 and Stage 2 burn bans estimated by the BlueSky 

Gateway for northeast Sacramento County ................................................................... A-9 

A-4. Relative benefit of Stage 1 and Stage 2 burn bans predicted by BlueSky Gateway 

for Sacramento County ................................................................................................ A-10 
1-1

1. INTRODUCTION 

On October 25, 2007, the Sacramento Metropolitan Air Quality Management District 

(SMAQMD) adopted Rule 421, Mandatory Episodic Curtailment of Wood and Other Solid Fuel 

Burning. The rule established a burning curtailment program with three messages and/or 

restrictions that are distributed to the public before a possible curtailment. The 

message/restriction depends on the “next-day” 24-hr average PM2.5

1

 concentration forecast for 

Sacramento County, which is issued every day by 11 a.m. The messages/restrictions based on 

the forecasted concentrations follow: 

 PM2.5 forecast >25 μg/m3

 to ≤35 μg/m3: Voluntary curtailment during which burning is 

discouraged. 

 PM2.5 forecast >35 μg/m3

 to ≤40 μg/m3: Stage 1 mandatory curtailment, during which no 

burning is allowed except in U.S. Environmental Protection Agency (EPA)-certified 

woodstoves and inserts or pellet stoves. 

 PM2.5 forecast >40 μg/m3

: Stage 2 mandatory curtailment during which no burning is 

allowed in any device. 

Rule 421 is in effect each “winter” from the beginning of November through the end of 

February. The rule has been in place for two “winters”. However, for the first “winter” of the 

program, the rule was in effect from December 1, 2007 through the end of February 2008. 

The primary objective of the work described in this report is to (1) determine the 

effectiveness of Rule 421 in reducing PM2.5 concentrations in Sacramento County; and (2) to 

provide information that can be used to determine whether any program changes should be 

considered to help Sacramento County attain National Ambient Air Quality Standards (NAAQS) 

for PM2.5. This work was divided into two phases: (1) Phase I results are presented in this report 

and (2) Phase II work will take place during summer 2009 and findings will be reported in 

September 2009. 

Several questions were posed by SMAQMD and addressed by Sonoma Technology, Inc. 

(STI) in Phase I: 

 What is the effectiveness of the burning curtailment program toward meeting the 

NAAQS? 

 Does chemical mass balance modeling (CMB)2

 confirm the effectiveness findings? 

 Was the 2008/2009 wood-burning season representative of normal PM2.5 concentrations? 

 What should the no-burn threshold be to help reduce PM2.5 below the NAAQS? 

 Should no-burn days be called on the day prior to forecasted high-PM2.5 concentration 

days (days expected to exceed NAAQS) to help lower pollution during PM2.5 episodes? 

 

1

 PM2.5 includes particles in the air that are less then 2.5 microns in diameter. 2

 CMB modeling uses observations of PM2.5 species and the known abundances of chemical species from emission 

sources (e.g., wood burning, automobile exhaust, dust, etc.) to determine the contribution from each source type to 

each measured PM2.5 daily sample. 
1-2

To address these questions, STI performed a combination of numerical modeling, CMB 

modeling, and data analysis to develop weight-of-evidence findings on the effectiveness of 

Rule 421 in reducing ambient PM2.5 concentrations. This approach provides greater certainty in 

the findings compared to those uncertainty findings based on modeling or analysis alone. A 

similar approach is being taken by the Bay Area Air Quality Management District (BAAQMD) 

and was taken by the San Joaquin Valley Unified Air Pollution Control District (SJVUAPCD) to 

address the effectiveness of their no-burn programs. 

After completing the work presented in the body of this report, STI conducted modeling 

analyses to provide additional information to address the question: “What is the effectiveness of 

the burning curtailment program toward meeting the NAAQS?” The findings from the 

additional analyses are provided in Appendix A and are consistent with the results of the data 

analysis described in the main body of the report. The addition of Appendix A is the reason this 

report was updated on August 24, 2009. 
2-1

2. SUMMARY OF FINDINGS 

Answers to the key questions posed by SMAQMD are summarized in this section. 

Additional details of Phase I findings can be found in Section 4. 

Question 1: What is the effectiveness of the burning curtailment program toward meeting 

NAAQS? 

Answers: 

1. Daily PM2.5 data collected by Beta Attenuation Monitors (BAMs)3

 show that the NAAQS 

threshold of 35.5 μg/m3 was exceeded on 20 days during the 2008/2009 winter. Analysis 

of a limited number of days4

 indicated that without Rule 421 there would have been 

about 13 additional days on which the NAAQS was exceeded. 

2. Data analysis results of a limited number of days2

 show the average reduction of the daily 

24-hr average PM2.5 concentration on 

a. Stage 1 days was about 4 μg/m3

 or 10% of the total PM2.5 concentration and 

b. Stage 2 days was about 12 μg/m3 or 23% of the total PM2.5 concentration. 

3. Data analysis results show the greatest reduction of PM2.5 concentrations resulting from a 

burn ban occurred during the evening hours. The average reduction during the evening 

on 

a. Stage 1 days was 19 μg/m3

 and 

b. Stage 2 days was 23 μg/m3. 

4. Data analysis results suggest that, without a burn ban, the change in the concentration 

from the day prior would have been greater. The average change in the 24-hr daily 

average concentration from a day prior on 

a. Stage 1 days was 5 μg/m3 greater and 

b. Stage 2 days was 17 μg/m3 greater. 

 

3

 Official NAAQS exceedance days for non-attainment designation are based on Federal Reference Monitor (FRM) 

data. To be NAAQS compliant for PM2.5 , about two days per year can exceed NAAQS assuming samples taken 

every third day and about 5 days if the sampling frequency were daily. 

4

 Eleven day-pairs were analyzed to derive this result. Each day-pair consists of two days with similar 

meteorology: one day on which a Stage 1 or Stage 2 burn ban was issued and a second day on which no burning 

restrictions were imposed. Therefore, for each day-pair, differences in PM2.5 concentrations between days could be 

primarily attributed to a Stage 1 or Stage 2 burn ban. Because of the limited number of day-pairs, the results derived 

from analysis should be viewed as rough approximations. 
2-2

Question 2: Does CMB modeling confirm the effectiveness findings? 

Answers: 

1. Review of CMB output indicates that the average wood smoke contribution on days 

when PM2.5 concentrations were high was at least 9.4 μg/m3

, or 25% of the total PM2.5

concentration,5

 and was as high as 19 μg/m3, or 40%, on individual days. These results 

indicate that it is possible to achieve a PM2.5 reduction on the order of 10 to 20 μg/m3

through the curtailment of wood burning and support Question 1 findings. 

2. Review of CMB output indicates that the average reduction of the daily 24-hr average 

PM2.5 concentration for Stage 1 and Stage 2 days combined was 1.5 μg/m3

, or 3.6% of 

the total PM2.5 mass. However, because data for this CMB analysis were only available 

for a limited number of days, we have less confidence in this finding than in the data 

analysis findings for Question 1 above. 

Question 3: Was the 2008/2009 wood burning season representative of normal PM2.5

concentrations? 

Answer: 

Data analysis results show that the 2008/2009 winter season represented an average year, 

with 20 days exceeding the NAAQS. Without curtailment, the 2008/2009 winter season 

would have had an estimated 33 days exceeding NAAQS. 

Question 4: What should the no-burn threshold be to most effectively reduce PM2.5 below 

the NAAQS? 

Answer: 

Calculations show that to help reduce PM2.5 below the NAAQS, the no-burn thresholds 

should be set as follows: 

1. Single-stage program – 31 μg/m3. 

2. Two-stage program – 31 μg/m3

 for Stage 1 and 35 μg/m3 for Stage 2. 

These thresholds include a margin of safety equal to the median forecast bias for days on 

which (a) burning was discouraged and (b) the concentrations were under predicted. 

Question 5: Should no-burn days be called on the day prior to forecasted high PM2.5

concentration days to help lower pollution during PM2.5 episodes? 

Answer: 

Modeling analysis results show that the average contribution of carryover from the prior 

(build-up) day to the average 24-hr PM2.5 concentration on a “Stage” day was 0.7 μg/m3, or 

2.2% of the total observed PM2.5 concentration. The range of contributions of carryover for 

 

5

 Due to the nature of CMB analysis, it is not possible to attribute secondary PM2.5 (organic carbon and ammonium 

nitrate) to wood smoke emissions, even though wood smoke contributes to the formation of secondary PM2.5. 

Therefore, 9.4 μg/m3, or 25%, is likely a low-end estimate of the wood smoke contribution to total PM2.5

concentrations. 
2-3

days investigate was 0.0 to 2.7 μg/m3, or 0 to 10.6%. Therefore, at this time, there is 

insufficient evidence that a no-burn day called on the day prior to high PM2.5 concentration 

days will significantly lower pollution during PM2.5 episodes. 
3-1

3. METHODS 

STI performed cluster analysis, CMB modeling, and numerical modeling to address the 

questions listed in Section 2. This section discusses the methods used to perform each of these 

analyses and is organized according to the question(s) addressed by each analysis. 

3.1 PROGRAM EFFECTIVENESS 

This subsection describes the methods used to answer the question: What is the overall 

effectiveness of Rule 421 toward meeting the PM2.5 24-hr National Ambient Air Quality 

Standard (NAAQS)? 

To address this question, STI compared wintertime PM2.5 concentrations on selected days 

prior to the adoption of Rule 421 (i.e., days when no restrictions on burning were in effect from 

November 1, 2004, through November 30, 2007) to days when Rule 421 was in effect (i.e., a 

Stage 1 or Stage 2 burn ban was issued). Only recent years’ data were used in the analysis to 

limit the influence of emission changes on PM2.5 concentrations due to non-woodburning 

emission control measures and population changes. PM2.5 concentrations were only compared 

on days when meteorological conditions were similar; thus, the difference in PM2.5

concentrations between days could be primarily6

 attributed to a Stage 1 or Stage 2 burn ban. 

To identify days with similar meteorology, STI performed cluster analysis. Cluster 

analysis involves grouping like objects (in this case, days) into clusters based on the similarity of 

the objects’ characteristics (in this case, meteorology). For this analysis, the similarity (or 

variation) between days was determined by calculating the Euclidean distance using the 

normalized values of meteorological variables such as wind speed, temperature, etc. Euclidean 

distance is the sum of root mean square differences of each variable between days or clusters. 

The statistical technique used in the cluster analysis was “K-means”. K-means clustering splits a 

set of days into a selected number of clusters by maximizing the between-cluster variation and 

minimizing the within-cluster variation of the meteorological variables. 

The data considered for use in the cluster analysis included 19 surface meteorological 

parameters and 40 upper-air meteorological parameters derived from hourly data collected at the 

Sacramento Executive Airport and twice-daily radiosonde data from Metropolitan Oakland 

International Airport. Of these 59 meteorological variables, only 12 were determined critical for 

differentiating day types (see Table 3-1). Therefore, data for these 12 meteorological variables 

collected on winter days (November 1 through the end of February) for 2004 through 2009 were 

ultimately used in the cluster analysis. 

 

6

 Other factors that may cause differences in PM2.5 concentrations include, but are not limited to, changes in 

population, changes in emissions from non-woodburning sources such as transportation due to fleet turnover, and 

changes in the PM2.5 monitoring techniques. 
3-2

Table 3-1. The 12 meteorological variables used in the cluster analysis. 

Maximum surface temperature (°C) 

Minimum surface temperature (°C) 

Average surface dew point temperature (°C) 

Average daytime cloud cover 

Average overnight cloud cover 

Precipitation (inches) 

6 a.m. – 6 p.m. PST vector averaged wind speed (knots) 

6 a.m. – 6 p.m. PST vector averaged wind direction (°) 

4 a.m. PST 500-mb heights (m-agl) 

4 a.m. PST 700-mb relative humidity (%) 

4 a.m. PST 850-mb temperature (°C) 

4 a.m. PST 925-mb temperature (°C) 

Once the cluster analysis was complete, STI meteorologists reviewed the results to 

further refine the day matches and ensure that the matched days were very similar 

meteorologically. This step was critical because small differences in meteorology can have a 

moderate impact on PM2.5 concentrations. In particular, meteorologists reviewed the point 

measurements of the variables in Table 3-1 for each day and the large-scale weather patterns 

over the western United States at the surface and at the 500-mb pressure level of the atmosphere 

(~18,000 ft). Reviewing large-scale weather patterns, the meteorologist looked for and noted the 

similarity of the following features between matching days: 

 location of surface high-pressure systems; 

 orientation and strength of the surface pressure gradient; 

 500-mb height patterns (e.g., ridges of high-pressure, troughs of low pressures); and 

 any other features of interest (e.g., a thermal trough on the California coast). 

Table 3-2 illustrates an example of the meteorological conditions for a matching day pair 

which includes a “no-restriction” day (December 2, 2006) and a “Stage 2” day (January 11, 

2009). Figure 3-1 shows the surface and 500-mb weather charts for these days. Figure 3-1 and 

the data in Table 3-2 indicate that these days were meteorologically similar, that is, most all 

weather parameters important to PM2.5 concentrations were similar on both days. Following are 

examples of comparisons of meteorological parameters between days: (1) the maximum surface 

temperatures were 15°C and 16°C on the no-restriction and Stage 2 days, respectively, while the 

6 a.m. to 6 p.m. PST vector-averaged wind speeds were 0 knots on both days and (2) a ridge of 

high pressure at 500-mb, a thermal trough of low pressure on the California coast, and a 

northwest to southeast-orientated pressure gradient of similar strength (shown in Figure 3-1) 

occurred on both days. As a result of these meteorological similarities, differences in PM2.5

concentrations between these two days can be attributed primarily to the burn ban. 

The meteorologists also evaluated the prior-day 24-hr average PM2.5 concentrations when 

selecting days for comparison. For example, if a “no-restriction” day and a “Stage 1” day were 
3-3

meteorologically very similar, yet the prior-day PM2.5 concentrations were very different (i.e., 

difference greater than ~15 μg/m3

), then the day pair was eliminated from the day matches. 

The cluster analysis and subsequent subjective review resulted in 11 matching days (day 

pairs). The matching days are shown in Table 3-3. Each day pair consisted of two days with 

similar meteorology: one day on which a Stage 1 or Stage 2 burn ban was called and a second 

day for which there were no burning restrictions. The PM2.5 concentration data were compared 

for each day pair using PM2.5 data from the site within the urban core of Sacramento County with 

the highest 24-hr average concentration and with data available for both days in the day-pair. 

For all day-pairs except one, the data collected at Del Paso Manor (DPM) were used; T Street 

data were used for the January 11, 2007/November 27, 2008 day-pair. For all dates except two, 

the data used were collected by beta attenuation monitors (BAM). Because BAM data were 

missing, Federal Reference Monitor (FRM) data collected at DPM were used for December 2, 

2006, and December 11, 2008. The BAM and FRM data were obtained from EPA’s Air Quality 

System (AQS) (www.epa.gov/ttn/airs/airsaqs/). Because FRM data were not available on 

January 11, 2009, for the December 2, 2006/January 11, 2009 day-pair, FRM data were 

compared to BAM data. 

Table 3-2. Meteorological conditions for a matching day-pair: December 2, 

2006, a no-restriction day, and January 11, 2009, a Stage 2 day.

Del Paso Manor on 

Saturday, 

Dec 02, 2006 – No 

Restrictions 

Del Paso Manor on 

Sunday, 

Jan 11, 2009 – Stage 2 

Meteorologic Cluster 1 1 

Location of surface high pressure system Oregon Oregon 

Orientation of surface pressure gradient Northwest-Southeast Northwest-Southeast 

Strength of surface pressure gradient Moderate Moderate 

Surface feature of interest Thermal trough on coast Thermal trough on coast 

500-mb pattern Ridge Ridge 

Maximum surface temperature (°C) 15 16 

Minimum surface temperature (°C) -2 -2 

Average surface dew point temperature (°C) 1 2 

Average daytime cloud cover 0 1 

Average overnight cloud cover 0 0 

Precipitation (inches) 0 0 

6 a.m. – 6 p.m. PST vector averaged wind speed 

(knots) 

0 0 

6 a.m. – 6 p.m. PST vector averaged wind 

direction (°) 

0 72 

4 a.m. PST 500-mb heights (m-agl) 5766 5887 

4 a.m. PST 700-mb relative humidity (%) 8 3 

4 a.m. PST 850-mb temperature (°C) 12 14 

4 a.m. PST 925-mb temperature (°C) 13 15 
3-4

Surface Pressure

500-mb Heights

December 02, 2006 January 11, 2009

No Restrictions Stage 2

Ridge of high pressure 

Thermal trough 

Figure 3-1. Example of surface and 500-mb weather patterns used to determine 

matching day-pairs. December 2, 2006, was a no-restriction day and January 11, 

2009 was a Stage 2 day.
3-5

Table 3-3. Matching days when meteorological conditions were similar7. 

No Restrictions Dates Burn Ban Dates Stage Value 

November 25, 2007 November 28, 2008 2 

November 25, 2007 February 17, 2008 1 

December 2, 2006 January 11, 2009 2 

December 2, 2006 December 11, 2008 2 

February 3, 2005 January 30, 2009 2 

February 3, 2005 January 14, 2009 2 

December 22, 2004 January 29, 2009 1 

December 30, 2006 December 14, 2007 1 

November 19, 2005 November 30, 2008 1 

February 2, 2005 January 13, 2009 2 

January 11, 2006 November 27, 2008 2 

For the 11 day-pairs, the PM2.5 concentration differences between the no-restriction and 

Stage 1 or Stage 2 days were determined for the following averaging times: 

 24-hr (12 a.m. to 12 a.m. PST); 

 prior-day 24-hr (12 a.m. to 12 a.m. PST); 

 morning (12 a.m. to 9 a.m. PST); 

 daytime (10 a.m. to 4 p.m. PST); and 

 evening (5 p.m. to 11 p.m. PST). 

In addition, we compared the daily 24-hr average PM2.5 concentrations on the days listed 

in Table 3-3 to concentrations on the day prior to each of these dates and calculated the 

concentration change between the consecutive days. We then compared the change in 

concentration for burn-ban days with the amount of change in concentration for their respective 

no-restriction dates. The purpose of this analysis was to determine how a burn ban affects the 

change in concentration from the day prior to a burn-ban day. 

STI used the 24-hr daily average PM2.5 concentration differences between the 

no-restriction and Stage 1 or Stage 2 days to estimate PM2.5 concentrations in 2008/2009 for a no 

burn-ban scenario. The results were used to estimate the number of days that would have 

exceeded NAAQS if there was no “Check Before You Burn” (CBYB) program. This method is 

detailed in Section 3.3. 

The results of this analysis provide an estimate of benefit from Rule 421. For example, 

Table 3-4 shows the PM2.5 concentrations for December 22, 2004, and January 29, 2009. The 

 

7

 Different no-burn stages were called on November 28, 2008, and February 17, 2008, yet the days are compared to 

the same no-restriction day because the no-burn stages are based on forecasted meteorology; whereas, the day-pairs 

are based on observed meteorology. 
3-6

most important column is column 4, “No Restriction minus Stage 1”, a measure of the reduction 

in PM2.5 concentrations resulting from the Stage 1 burn ban. In this example, the total reduction 

in the 24-hr average PM2.5 concentrations resulting from the Stage 1 burn ban was 11 μg/m3, 

with a maximum reduction of 43 μg/m3

 occurring during evening hours. After completing this 

analysis for each day pair, STI averaged the results for each averaging period listed in bullets on 

the preceding page. 

Table 3-4. PM2.5 concentrations comparisons for a day-pair: December 22, 2004, 

a no-restrictions day, and January 29, 2009, a Stage 1 day. 

Del Paso Manor 

on Wednesday, 

Dec 22, 2004 – 

No Restrictions 

Del Paso Manor 

on Thursday, 

Jan 29, 2009 – 

Stage 1 

No 

Restrictions 

Minus 

Stage 1 

24-hr (12 a.m. – 11 p.m. PST) average PM2.5

concentrations (μg/m3

) 40 29 11 

Morning (12 a.m. – 9 a.m. PST) average PM2.5

concentrations (μg/m3

) 26 31 -5 

Daytime (10 a.m. – 4 p.m. PST) average PM2.5

concentrations (μg/m3

) 21 21 0 

Evening (5 p.m. – 11 p.m. PST) average PM2.5

concentrations (μg/m3

) 77 34 43 

Prior-day 24-hr (12 a.m. – 11 p.m. PST) 

average PM2.5 concentrations (μg/m3

) 16 22 -5 

Concentration change from the prior day 

(μg/m3

) 23 7 16 

3.2 CMB MODELING 

The methods used to answer the questions that follow are discussed in this subsection. 

The following question (in boldface) was the main focus of the analyses; important secondary 

questions related to these analyses are italicized. 

Does CMB modeling confirm the effectiveness findings from Question 1? 

How variable is the wood smoke contribution based on the various wood burning 

profiles? 

How well does CMB predict the wood smoke contribution?

STI applied CMB modeling to speciated PM2.5 data to determine the contribution of 

residential wood smoke to total PM2.5 concentrations for various groups of days and compared 

the findings to the “effectiveness” findings described in Section 3.1. The day groups included 

 all 2008-2009 “winter” days;

 all Stage 1 and Stage 2 days in 2007-2009;

 Stage 1 days that were matched to days with no burning restrictions because of similar 

meteorology between matched days;
3-7

 Stage 2 days that were matched to days with no burning restrictions because of similar 

meteorology between matched days; and 

 no-restriction days (i.e., no burn ban was issued) that were matched to Stage 1 and Stage 

2 days because of similar meteorology between matched days. 

Days with similar meteorological conditions (i.e., matching days) were determined using 

the cluster analysis results described in Section 3.1. However, the criteria for the selection of 

meteorologically similar days included in the CMB modeling were less restrictive than the 

criteria used in the data analysis described in Section 3.1. We were less restrictive because the 

number days for which speciated ambient data were available for comparison were limited. The 

result of less restriction is that the meteorology was only moderately similar between matching 

days; thus, differences in wood smoke contributions between matching days cannot solely be 

attributed to a burn ban. The no-restriction days were selected from winter days during 

November 2007 through February 2009 when no burn ban was in effect, as well as from the 

winters prior to the CBYB program (November 2003 through February 2007). The final set of 

matching no-restriction days and Stage days used to compare the contribution of wood smoke are 

discussed in Section 4.2. 

The data used for CMB modeling were validated, speciated 24-hr samples of PM2.5 data 

collected at Del Paso Manor. The data were collected every third day. Ambient concentrations 

and uncertainty values were obtained from SMAQMD for the 2008-2009 “winter” (November 

2008–February 2009) and from EPA’s Air Quality System (AQS) for previous “winters” 

(2003–2008). The source profiles used in CMB modeling were obtained from Katarzyna 

Turkiewicz from the California Air Resources Board (ARB). Wood-burning source profiles 

from different types of wood were used in sensitivity tests to determine the range of wood smoke 

contributions. Standard CMB performance metrics were used to gauge confidence in results. 

3.2.1 CMB Background 

CMB is a receptor model used to identify and characterize the mixture and magnitude of 

sources contributing to ambient pollutant concentrations. Known source profiles are linearly fit 

to ambient data using a least squares solution. Model outputs represent the contributions of 

various emission sources to the observed ambient concentrations. In CMB, only source profiles 

(i.e., the fraction of each species emitted from each source type), and ambient data collected at 

the receptor are required as model inputs. Underlying CMB assumptions include (1) accurate 

identification of source types and abundances (source profiles); (2) independent source 

compositions (i.e., abundances are unique to each profile); and (3) consistent profiles between 

source and receptor (i.e., no mass removal and constant emissions) and throughout the sampling 

period. In this analysis, these assumptions were met to a similar degree as in published 

literature. 

3.2.2 Data Processing and Quality Assurance 

Each species was blank-adjusted by subtracting the median blank mass of that species 

from three blanks taken during 2008-2009. After blank-adjusting mass values, total mass was 
3-8

reconstructed from the speciated data for comparison with the total measured mass on the filter 

(Figures 3-2 and 3-3). This comparison helps us understand how well the chemical species 

represent the total mass on the filter. Organic carbon was adjusted to organic matter (OM) using 

a factor of 1.4 to account for oxygen and hydrogen associated with the carbon (Malm et al., 

2004; Turpin and Lim, 2001). The factor of 1.4 is generally viewed as a low-end factor, but was 

used in this analysis because it provided the best reconstruction of total mass. The unknown 

fractions, calculated as the difference between the reconstructed and measured totals, were 

typically less than 20% of the total reconstructed concentration throughout the sampling period, 

indicating that most of the PM2.5 mass is well explained by the measured chemical species. 

Additional quality assurance included investigation of ambient data values below instrument 

method detection limits (MDLs) (Table 3-5). Species frequently below detection were generally 

not included in the model; if a species was relatively abundant in source profiles, such as 

aluminum in the soil profile, it was included. AQS-reported uncertainties were used for 

individual species, and an uncertainty of 5.5% was used for total mass, as reported by Research 

Triangle Institute in the 2008-2009 data submittal to SMAQMD. 

17-Nov-08

20-Nov-08

23-Nov-08

26-Nov-08

29-Nov-08

02-Dec-08

05-Dec-08

08-Dec-08

11-Dec-08

14-Dec-08

17-Dec-08

20-Dec-08

23-Dec-08

26-Dec-08

29-Dec-08

01-Jan-09

04-Jan-09

07-Jan-09

10-Jan-09

13-Jan-09

16-Jan-09

19-Jan-09

22-Jan-09

25-Jan-09

28-Jan-09

31-Jan-09

03-Feb-09

06-Feb-09

09-Feb-09

12-Feb-09

-10

0

10

20

30

40

50

60

Reconstructed Concentration (ug/m3)

Other

Soil

Ammonium Nitrate

Ammonium Sulfate

Elemental Carbon

Organic Matter

Figure 3-2. Reconstructed mass of samples during winter 2008/2009. “Other” is 

defined as the difference between the measured total filter mass minus the sum of 

soil, ammonium, nitrate, ammonium sulfate, organic matter, and elemental 

carbon. A negative value indicates the sum of species was greater than the 

measured mass.8

 

 

8

 Calculations were based on standard Interagency Monitoring of Protected Visual Environments (IMPROVE) 

methodology (IMPROVE). Soil was calculated as (Aluminum*2.2+Silicon*2.49+ Calcium*1.63 +Iron*2.42 

+Titanium*1.94); ammonium nitrate was calculated as Nitrate*1.29; ammonium sulfate was calculated as 

Sulfur*4.125; and organic matter was calculated as Organic Carbon*1.4. 
3-9

Average Winter 2008-2009

Reconstructed Concentration

Organic Matter

14 μg/m3, 56%

Elemental

Carbon

4 μg/m3, 6%

Ammonium

Sulfate

1.3 μg/m3, 5%

Ammonium

Nitrate

7.3 μg/m3, 30%

Other

0.17 μg/m3, 0.7%

Soil

0.33 μg/m3, 1%

*Average reconstruc

concentration = 24 u

Figure 3-3. Average reconstructed concentrations plus the difference between the 

total reconstructed and measured concentrations (the difference is shown as 

“other”) for all winter 2008-2009 sample dates. 

Table 3-5. Species data below method detection limits for each sample date in 

winter 2008-2009. 

Page 1 of 2 

Date Al NH4 Br Ca Cl Cu EC Fe K Pb Mn Na Ni NO3 OC K 

(ion) Si Na (ion) SO4 Ti V Zn 

11/17/08 X X X X X 

11/20/08 X X X X X X X 

11/23/08 X X X X X 

11/26/08 X X X X X 

11/29/08 X X X X X X X X 

12/02/08 X X X X X X X X 

12/05/08 X X X X X 

12/08/08 X X X X X X X 

12/11/08 X X X X X 

12/14/08 X X X X X X X X 

12/17/08 X X X X X X X X X X 

12/20/08 X X X X X X 

12/23/08 X X X X X X X X X 

12/26/08 X X X X X X X 

12/29/08 X X X X X 

01/01/09 X X X X X X X X X X 

01/04/09 X X X X X X 

01/07/09 X X X X X X X X X 

01/10/09 X X X X X X 
3-10

Table 3-5. Species data below method detection limits for each sample date in 

winter 2008-2009. 

Page 2 of 2 

Date Al NH4 Br Ca Cl Cu EC Fe K Pb Mn Na Ni NO3 OC K 

(ion) Si Na 

(ion) SO4 Ti V Zn 

01/13/09 X X X X X 

01/16/09 X X X X 

01/19/09 X X X X X X 

01/22/09 X X X X X X X X 

01/25/09 X X X X X X X X 

01/28/09 X X X X X X X 

01/31/09 X X X X X X 

02/03/09 X X X X X X 

02/06/09 X X X X X X X X X 

02/09/09 X X X X X X 

02/12/09 X X X X X X 

3.2.3 Source Profiles and Model Certainty 

Source profile abundances and uncertainties were obtained from the ARB for the known 

major source types. The profiles included four wood smoke varieties (oak, eucalyptus, almond, 

and tamarisk), one combination wood smoke profile calculated as 50% oak and 50% eucalyptus, 

one mobile source profile (combined gas and diesel), ammonium sulfate, ammonium nitrate, 

pure organic carbon (OC), and dust. STI also created an additional wood smoke combination 

profile, calculated as one-third each oak, eucalyptus, and almond. Key species for wood 

burning, mobile sources, and dust are detailed in Table 3-6. OC, elemental carbon (EC), and 

potassium were used as markers for wood burning, since levoglucosan data, a more unique tracer 

for wood burning, were not available. We anticipate that mobile source emissions and wood 

burning will account for much of the OC, but there are multiple, smaller sources of OC that are 

not characterized, so a profile of entirely OC is used to account for these additional small 

sources. Ammonium sulfate and ammonium nitrate profiles are used for mass closure; these 

species are secondary products and so cannot be ascribed to individual sources with CMB. 

The model was run for all the winter 2008-2009 sampling dates. Twenty-one species 

were used in the CMB model, as shown in Table 3-6. The fourteen fitting species selected in the 

model were abundant in the source profiles, logical markers for the predominant sources, and 

typically above method detection limits. The remaining seven floating species were of lesser 

abundance and served to validate the model and satisfy degrees of freedom requirements 

(Coulter, 2004). Sensitivity tests were performed to determine the range of results for each of 

the different wood-burning profiles. Examining these results allowed us to put bounds on the 

source contribution estimate for wood burning, even if a given wood profile was not wholly 

representative of the mix of wood burned in the area. The best performing and most reasonable 

wood burning profile was selected for further use, measuring model performance by three 

standard CMB methods: 
3-11

 R square is a measure of the fraction of variance in measured concentrations that is 

explained by the variance in calculated concentrations. Higher R square values indicate 

better agreement between measured and calculated data sets; a value greater than 0.8 is 

considered good agreement and was required for these analyses. 

 Chi square is the weighted sum of squares of the differences between calculated and 

measured fitting species concentrations. Lower chi square values indicate better 

agreement between the measured and calculated data. A chi square value less than 1 

indicates very good agreement, and a chi square between 1 and 2 indicates acceptable 

agreement. Chi square values of less than 2 were required for these analyses. 

 The total mass calculated by the model should be reasonable when compared to measured 

mass, falling between 80% and 120% of the measured mass. In addition, the source 

contribution estimates were evaluated for significance, and the ratio of 

calculated/measured concentrations for fitting species were compared between profiles. 

Table 3-6. Chemical species included in CMB as fitting or floating species. 

Marker species for emission sources are highlighted in yellow. Under the column 

heading “Fit”, cells with an “x” indicate species that were used in all CMB runs, 

and blank cells indicate species that were not always used because of poor fit or 

data below the MDL. 

Species Fit Source 

Aluminum x Dust 

Ammonium x Ammonium sulfate, ammonium nitrate 

Bromine x Gas/diesel 

Calcium x Dust 

Chlorine Multiple 

Copper x Gas/diesel, dust 

Elemental carbon x Wood burning, gas/diesel 

Iron x Dust 

Potassium Multiple 

Lead Multiple 

Manganese Multiple 

Sodium Multiple 

Nickel Multiple 

Nitrate x Ammonium nitrate 

Organic carbon x Wood burning, gas/diesel 

Potassium (cation) x Wood burning 

Silicon x Dust 

Sodium (cation) Multiple 

Sulfate x Ammonium sulfate 

Titanium x Multiple 

Zinc x Multiple 
3-12

3.3 SEASON REPRESENTATIVENESS 

The methods used to answer the questions that follow are discussed in this subsection. 

The following question (in boldface) was the main focus of the analyses; an important secondary 

question related to these analyses is italicized. 

Was the 2008/2009 wood burning season representative of normal PM2.5 concentrations? 

What would have the 2008/2009 wood burning season have been like without the CBYB 

program? 

STI used various metrics to summarize PM2.5 conditions for winter 2008/2009 and 

compared those metrics to past “winters” (2004/2005, 2005/2006, 2006/2007, and 2007/2008). 

Only data from recent years were used in the analysis to limit the influence of emission changes 

on PM2.5 concentrations due to non-woodburning emission control measures and population 

changes. For this analysis, we used BAM data collected at DPM because (1) there was a 

complete set of data for this site for the period of interest and (2) it is typically the site with the 

highest daily concentrations in Sacramento County. The metrics calculated for each year 

included 

 number of days in each Air Quality Index (AQI) category; 

 number of days on which the NAAQS was exceeded; and 

 average episode length. An episode is defined as one or more consecutive days 

exceeding the NAAQS. 

STI also compared the number of days in 2008/2009 when meteorological conditions 

were conducive to high PM2.5 concentrations to the number of such days in each of the prior four 

years. This comparison was made by reviewing the meteorological conditions and observed air 

quality concentrations on all winter days from November 2004 through February 2009. 

Conducive conditions include 

 surface high pressure north or east of Sacramento; 

 aloft high pressure over California; 

 relatively warm aloft temperatures and a temperature inversion; 

 cool and cloud-free nights; and 

 light winds during the day and night. 

When comparing these conditions to observed air quality, we determined that observed 

air quality concentrations were the best metric to define days when meteorology was conducive 

to poor air quality. In particular, we defined meteorologically conducive days as days when peak 

24-hr average PM2.5 concentrations exceeded 24 μg/m3

. We also reviewed the number of days 

above 29 μg/m3 to confirm that our choice of threshold did not significantly change the relative 

difference in days with conducive meteorology between years. 

Finally, STI used the burn-benefit results from the Question 1 analysis to estimate PM2.5

concentrations in 2008/2009 had no CBYB program been in place. This estimate was calculated 
3-13

by adding the average Stage 1 burn-ban benefit to the observed concentrations on Stage 1 days 

and the average Stage 2 burn-ban benefit to the observed concentrations on Stage 2 days. The 

observed concentrations were adjusted using data collected using BAM monitors. STI then 

recalculated the metrics for the 2007/2008 and 2008/2009 seasons using the adjusted data. Of 

particular focus was the reduction in the number of days exceeding NAAQS due to the CBYB 

program. 

3.4 NO-BURN THRESHOLDS 

This subsection describes the methods used to answer the question: What should the 

no-burn threshold be to reduce PM2.5 below NAAQS? 

To address this question for the single-stage program, STI estimated the median bias in 

the daily PM2.5 forecasts and subtracted it from the NAAQS threshold to determine the burn-ban 

threshold. This calculation was necessary because, in practice, if a PM2.5 concentration of 

30 μg/m3

 is forecast with a forecast error of 5 μg/m3, an observed concentration of 35 μg/m3 is 

possible given the forecast error. Therefore, the threshold for a no-burn call should be lowered 

to 30 μg/m3

 (35 minus 5). 

For a two-stage program, STI determined a PM2.5 threshold for which a Stage 1 call will 

not be sufficient to prevent a violation of the NAAQS. To determine this threshold, STI added 

the anticipated PM2.5 reduction resulting from a Stage 1 call (obtained from the data analyses 

performed to address Question 1) to the NAAQS of 35 μg/m3 and subtracted the forecast error. 

For example, if the average reduction achieved on a Stage 1 day is 4 μg/m3, the no-burn 

threshold for a Stage 2 day (ignoring forecast error) should be 39 μg/m3

 (35 +4). If forecast error 

is 5 μg/m3, the threshold for a Stage 2 no-burn call day should be lowered to 34 μg/m3 (39-5). 

The forecast error used in the these calculations was determined by calculating the 

median forecast bias for days during the 2008/2009 winter season when burning was 

discouraged. Using the forecast bias from burning-discouraged days was determined to be the 

most appropriate estimate of the actual forecast error for the following reasons: (1) on days 

when a Stage 1 or Stage 2 burn ban is called, the forecast error can be altered by the 

effectiveness of the burn ban; (2) on clean days, precise forecasts of absolute PM2.5

concentrations tend to be emphasized less compared to days on which a burn ban may be 

necessary; and (3) on days when burning is discouraged, forecast accuracy is emphasized, yet 

there is no burn ban to alter forecast error. 

3.5 BUILD-UP DAY RULE 

This subsection describes the methods used to answer the question: Should no-burn 

days be called on the day prior to forecasted high PM2.5 concentration days to help lower 

pollution during PM2.5 episodes? 

STI used the BlueSky Gateway air quality modeling system. BlueSky Gateway is an 

operational PM2.5 forecasting system developed for the U.S. Forest Service to predict PM2.5

concentrations resulting from wildfires and other emission sources on a national scale at coarse 
3-14

(36 km) resolution. BlueSky Gateway combines meteorological predictions from the 

Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model 

(MM5) with air quality predictions from the Community Multiscale Air Quality (CMAQ) model. 

STI has operated BlueSky Gateway twice daily since its Summer 2007 inception. 

Though BlueSky Gateway was designed primarily to track and predict PM2.5

concentrations resulting from wildfires, the modeling system is run with full gaseous and aerosol 

chemistry to predict the fate of all types of natural and anthropogenic PM2.5 emission sources, 

including residential wood burning. Details pertinent to the use of BlueSky Gateway to address 

the questions posed by SMAQMD are presented below. Additional details can be found in 

(Craig et al., 2007). 

STI performed simulations for several two-consecutive-day periods using the BlueSky 

Gateway modeling system to evaluate the contribution of carryover on multi-day pollution 

episodes. BlueSky Gateway was run for several days prior to each case date (with residential 

wood burning allowed) to provide initialized concentration fields for the sensitivity simulations. 

Nine cases from the 2008/2009 winter burning season were selected for this analysis, as 

shown in Table 3-7. Each case consists of a “build-up” day on which burning was discouraged, 

followed by a “Stage” day on which a Stage 1 or Stage 2 burn ban was called. In several 

instances, these cases represented the beginning of extended periods of elevated PM2.5

concentrations that necessitated burn bans on several consecutive days in Sacramento County. 

Table 3-7. Cases selected for modeling analysis. 

Case Date Burn 

Category 

Observed 

PM2.5 (μg/m3

) 

11/16/2008 Discouraged 30.8 1 11/17/2008 Stage 1 23.8 

11/22/2008 Discouraged 49.4 2 11/23/2008 Stage 2 60.7 

11/29/2008 Discouraged 35.6 3 11/30/2008 Stage 1 42.3 

12/2/2008 Discouraged 33.3 4 12/3/2008 Stage 2 29.3 

12/9/2008 Discouraged 34.0 5 12/10/2008 Stage 2 40.5 

1/4/2009 Discouraged 31.1 6 1/5/2009 Stage 2 25.7 

1/6/2009 Discouraged 25.5 7 1/7/2009 Stage 2 29.2 

1/9/2009 Clean 17.8 8 1/10/2009 Stage 2 43.5 

1/28/2009 Discouraged 21.6 9 1/29/2009 Stage 1 28.9 
3-15

For each case, STI ran the two-consecutive-day simulations for two residential 

wood-burning scenarios: 

1. 100% burning curtailment in Sacramento County only on the Stage day. 

2. 100% burning curtailment in Sacramento County on both the build-up and the Stage 

days. 

The modeled difference in PM2.5 concentrations between these two emission scenarios on 

the Stage day yields the relative benefit of adding a burn ban on the build-up day. The modeled 

impacts of carryover were examined at various receptor locations throughout Sacramento 

County. 

Residential wood combustion emission estimates were taken from the 2002 National 

Emission Inventory (NEI), processed through version 2.3 of the Sparse Matrix Operator Kernel 

Emissions Modeling System (SMOKE), and projected to 2007 using growth factors generated by 

EPA’s Economic Growth Analysis System (EGAS) version 4.0. The residential wood 

combustion emission estimates used in BlueSky Gateway are listed in Table 3-8. These 

estimates are within approximately 5% of the 2009 California Air Resources Board (ARB) 

residential wood-burning emission estimates for Sacramento County obtained from the 

California Emission Forecast System (CEFS)

(http://www.arb.ca.gov/app/emsinv/fcemssumcat2005.php), as shown in Table 3-9. SMOKE 

speciates the total PM2.5 mass according to the speciation profile shown in Table 3-10 and 

applies temporal profiles to convert annualized emissions to episode-specific hourly emissions. 

The allocation of annual wood-burning emissions by month is shown in Figure 3-4. The default 

SMOKE seasonal profile applied to residential wood combustion emissions was judged to be 

reasonable and resulted in average winter day PM2.5 emissions of 10.4 tons for Sacramento 

County. The default SMOKE diurnal temporal profile for residential wood combustion was 

replaced with a more appropriate profile developed by ARB. 

Table 3-8. 2007 Sacramento County residential wood combustion emission 

estimates (tons/year) used in BlueSky Gateway simulations. 

Source CO NOx PM10 PM2.5 SO2 VOC 

Fireplaces 11,150.9 114.8 1,428.1 1,374.8 17.5 600.1 

Woodstoves 1,789.9 25.3 279.8 269.4 3.8 130.8 

Total 12,940.8 140.1 1,708.0 1,644.2 21.3 730.9 

Table 3-9. 2009 Sacramento County residential wood combustion emission 

estimates (tons/year) from the CEFS database. 

Source CO NOx PM10 PM2.5 SO2 VOC 

Fireplaces 11,744.3 120.9 1,504.2 1,448.0 18.5 632.0 

Woodstoves 1,788.3 25.5 279.6 269.1 3.7 130.5 

Total 13,532.6 146.4 1,783.8 1,717.1 22.1 762.5 
3-16

Table 3-10. SMOKE PM2.5 speciation profile. 

Profile # Model Species Model Species Name Mass Fraction 

22061 PEC Primary elemental carbon 0.1077 

22061 PMFINE Fine mode PM (metals and 

other species) 0.3208 

22061 PNO3 Primary nitrate aerosol 0.0022 

22061 POA Primary organic aerosol 0.5656 

22061 PSO4 Primary sulfate aerosol 0.0037 

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Percentage of Annual Emissions

Figure 3-4. Allocation of annual wood-burning emissions by month. 

Because of the relatively coarse horizontal resolution of BlueSky Gateway (36 km), peak 

concentrations may be underestimated by the model as localized emissions are artificially diluted 

into relatively large model grid cells. Figure 3-5 illustrates the size of BlueSky Gateway model 

grid cells relative to Sacramento County. To address the effects of model resolution, the use of 

absolute modeled concentration differences was avoided, and instead the relative difference 

between the two emission control scenarios was used to determine the impact of carryover. 
3-17

Figure 3-5. BlueSky Gateway model grid in the Sacramento County region. Grid 

cells highlighted in red indicate the four cells that encompass most of Sacramento 

County. 
4-1

4. FINDINGS 

Findings related to each question listed in Section 2 are summarized in this section and 

are organized according to the main question addressed by each analysis. 

4.1 PROGRAM EFFECTIVENESS 

Detailed in this subsection are the findings applicable to Question 1: What is the 

effectiveness of program toward meeting NAAQS? 

STI compared wintertime PM2.5 concentrations on days prior to the adoption of Rule 421 

(i.e., no burning restrictions) to days when Rule 421 was in effect (i.e., when a Stage 1 or Stage 2 

burn ban was issued). PM2.5 concentrations were only compared for days when meteorological 

conditions were similar; thus, the difference in PM2.5 concentrations between days could be 

primarily attributed to a Stage 1 or Stage 2 burn ban. Cluster analysis and subsequent subjective 

review resulted in 11 matching days (day pairs), which are shown in Table 3-3. Each day pair 

consists of two days with similar meteorology: one day on which a Stage 1 or Stage 2 burn ban 

was issued and a second day on which no burning restrictions were imposed. Overall, seven 

Stage 2 day pairs and four Stage 1 day pairs were identified. Because of the limited number of 

day pairs, the results derived from analysis should be viewed as rough approximations. 

Table 4-1 lists the average reduction in PM2.5 concentrations for various averaging 

periods (24-hr, morning, daytime, and evening) that resulted from a Stage 1 or Stage 2 burn ban. 

Figure 4-1a shows time series of the average hourly PM2.5 concentrations for all Stage 2/ 

no-restriction day pairs. Figure 4-1b shows time series of the average hourly PM2.5

concentrations for all Stage 1/no-restriction day pairs. Table 4-2 lists the 24-hr PM2.5

concentration reduction (benefit) for each of the 11 day-pairs. The tables and figures illustrate 

the following findings: 

 The average reduction resulting from a Stage 1 burn ban was 4 μg/m3, or 10% of the total 

PM2.5 mass that would have occurred without the reduction. For example, if a 

concentration of 36 μg/m3

 was observed on a day with a Stage 1 burn ban, the 

concentration would have been about 40 μg/m3

 on average without a burn ban. 

 The reductions resulting from a Stage 1 burn ban ranged from -11 μg/m3 to 10 μg/m3

. A 

reduction was observed on three of the four days (Table 4-2). 

 The average reduction resulting from a Stage 2 burn ban was 12 μg/m3

, or 23% reduction 

of the total PM2.5 mass that would have occurred without the reduction. For example, if a 

concentration of 40 μg/m3

 was observed on a day with a Stage 2 burn ban, the 

concentration would have been about 52 μg/m3 on average without the Stage 2 burn ban. 

 The reductions resulting from a Stage 2 burn ban ranged from -6 μg/m3 to 30 μg/m3. A 

reduction was observed on six of the seven days (Table 4-2). 

 The greatest reduction in PM2.5 concentrations resulting from a burn ban occurred during 

the evening hours. This reduction can be seen in the large separation between the dashed 

red line (average “No Restriction” days) and solid green lines (average Stage 1 or Stage 2 
4-2

days) in Figures 4-1a and 4-1b. The average reduction during the evening was 23 μg/m3

and 19 μg/m3

 for Stage 2 and Stage 1 days, respectively. This result is consistent with 

the observation that most people burn in the evening as indicated in the ARB residential 

wood-burning emission estimates for Sacramento County obtained from the CEFS. 

 The average change in the 24-hr daily average concentration from a day prior to a Stage 2 

day was 17 μg/m3

 less than the change from a day prior to a no-restriction day (see the 

last row in Table 4-1). This result suggests that without a Stage 2 burn ban, 

concentrations would have been, on average, 17 μg/m3 higher than without a burn ban. 

 The average change in the 24-hr daily average concentration from a day prior to a Stage 1 

day was 5 μg/m3

 less than the change from a day prior to a no-restriction day (see the last 

row in Table 4-1). This result suggests that without a Stage 1 burn ban, concentrations 

would have been on average 5 μg/m3 higher than without a burn ban. 

Table 4-1. Average reduction (benefit) for all day-pairs, Stage 2 day-pairs, and 

Stage 1 day-pairs. 

Benefit 

Stage 1 and 2 (μg/m3)

Benefit 

Stage 2 (μg/m3) 

Benefit 

Stage 1 (μg/m3) 

24-hr 9 12 4 

Morning 8 11 3 

Daytime -7 -4 -11 

Evening 21 23 19 

Change from the prior day 12 17 5 
4-3

(a) 

(b) 

Figure 4-1. Average hourly PM2.5 time series for the (a) Stage 2 and (b) Stage 1 

day pairs. The dashed red line represents the average hourly PM2.5 concentrations 

for the No Restriction days associated with each day pair, and the solid green line 

represents the average hourly PM2.5 concentrations of the Stage days associated 

with each day pair. The green box show the estimated total reduction (benefit) in 

the 24-hr average PM2.5 concentrations due to the burn ban. 
4-4

Table 4-2. The 24-hour PM2.5 concentration reduction (benefit) for each day-pair. 

Green cells indicate a benefit from the burn ban. 

Day Pairs 

No Restrictions Date Burn Ban Date Burn Ban 

Category 

24-hr Daily 

Average PM2.5 

Concentration 

Reduction 

(μg/m3

) 

Concentration change 

from a “prior” day to 

a no-restriction day 

minus 

the concentration 

change from a prior 

“day” to a Stage day

November 25, 2007 November 28, 2008 Stage 2 15 13 

November 25, 2007 February 17, 2008 Stage 1 9 3 

December 2, 2006 January 11, 2009 Stage 2 23 26 

December 2, 2006 December 11, 2008 Stage 2 30 30 

February 3, 2005 January 30, 2009 Stage 2 6 1 

February 3, 2005 January 14, 2009 Stage 2 -5 2 

December 22, 2004 January 29, 2009 Stage 1 10 16 

December 30, 2006 December 14, 2007 Stage 1 6 8 

November 19, 2005 November 30, 2008 Stage 1 -11 -7 

February 2, 2005 January 13, 2009 Stage 2 -6 12 

January 11, 2006 November 27, 2008 Stage 2 18 31 

4.2 CMB MODELING 

The findings applicable to the questions that follow are detailed in this subsection. The 

following question (in boldface) was the main focus of the analyses; important secondary 

questions related to these analyses are italicized. 

Does CMB modeling confirm the effectiveness findings? 

How variable is the wood smoke contribution based on the various wood-burning 

profiles? 

How well does CMB predict the wood smoke contribution?

Figure 4-2a-e shows the average source contributions to total PM2.5 concentration at Del 

Paso Manor for five day-groupings. The wood smoke contribution and other observations 

derived from these figures are noted below.

1. Figure 4-2a shows that, on all 2008-2009 winter days, the average wood smoke 

contribution was 7.1 μg/m3 or 29% of the total PM2.5 mass. Thus, if wood burning were 

reduced to negligible levels, the burn ban could produce concentration reductions of this 

magnitude. This finding supports the estimated reduction in PM2.5 concentrations 

resulting from burn bans described in Section 4.1 regarding Question 1. 
4-5

(a) (b)

(c) (d)

 (e)

Figure 4-2. Source contribution estimates for each profile averaged across (a) all 

winter 2008-2009 sample dates, (b) all 2008/2009 Stage dates, (c) Stage 1 days 

with matching no-restriction days, (d) Stage 2 days with matching no-restriction 

days, (e) no-restriction days with meteorology similar to Stage days. 
4-6

2. Figure 4-2b shows that, on all 2007/2009 Stage 1 and Stage 2 days, the average wood 

smoke contribution was 9.4 μg/m3

 or 25% of the total PM2.5 mass. 

3. Figure 4-2c shows that, on Stage 1 days that were matched to days with no burning 

restrictions because of similar meteorology, the average wood smoke contribution was 

10.5 μg/m3

 or 25% of the total PM2.5 mass. 

4. Figure 4-2d shows that, on Stage 2 days that were matched to days with no burning 

restrictions because of similar meteorology, the average wood smoke contribution was 

10.6 μg/m3 or 23% of the total PM2.5 mass. 

5. Figure 4-2e shows that, on no-restriction days from 2005 – 2007 (i.e., no burn ban was 

issued) that were matched to Stage 1 and Stage 2 days because of similar meteorology, 

the average wood smoke contribution was 12.1 μg/m3

 or 26% of the total PM2.5 mass. 

The combination of the findings 3 through 5 suggest that CMB modeling indicates a 

reduction of PM2.5 from a Stage 1 or Stage 2 burn is about 1.5 μg/m3

 (12.1 – 10.5). This amount 

is much less than that revealed in the data analysis (see Section 4.1) and is probably not a 

significant enough difference to conclude that there was a benefit from burn bans. However, 

because data for only a limited number of days were available for this CMB analysis, the 

matching pairs of no-restriction to burn-ban days were not as meteorologically similar as those 

used in the data analysis. Therefore, differences in meteorology between days may account for 

the limited reduction in PM2.5 concentrations resulting from burn bans identified using CMB. 

Table 4-3 shows the reduction in wood smoke contributions for each matching pair of 

no-restriction to burn-ban days. Of note, the only cluster having several meteorologically similar 

dates for comparison, including five unrestricted dates and four Stage dates, showed a 4.0 μg/m3

reduction for burn-ban days compared to no-restriction days. In addition, the maximum 

contribution of wood smoke for this cluster of days was 40% or 18.8 μg/m3 of the total PM2.5

concentration and occurred December 4, 2006. 

In the Sacramento County emission inventory, residential wood burning accounts for 

approximately 50% of the primary PM2.5 emissions. This percentage is consistent with CMB 

results. Ammonium nitrate and ammonium sulfate are secondarily produced and are not 

included in the emission inventory estimate. If these species are ignored in Figure 4-2, wood 

burning would account for approximately 50% of the remaining mass. 

Secondary Question 1: How variable is the wood smoke contribution based on the various 

wood-burning profiles? 

Three wood-burning source profiles were evaluated to determine the most appropriate 

burning profile for Sacramento County. The estimated wood smoke contribution to total 

calculated concentration was consistent among the three wood-burning profiles (oak, eucalyptus, 

and almond) and the two combination profiles. Source contribution estimates for the almond, 

oak, eucalyptus, and combined profiles varied between 4% and 8% (Figure 4-3). Variability 

was the greatest on Stage 2 and unrestricted dates. The consistency among the results using the 

oak, eucalyptus and almond profiles promotes confidence in the overall performance of CMB 

modeling in quantifying wood burning. As anticipated, the results when using the Tamarisk 

profile (tamarisk is a type of grass) were unrealistic, and the model performance was poor. The 

average wood smoke contribution was 82%, and the average measured mass calculated by the 
4-7

model was 139%, measurably exceeding the 120% threshold. This profile represents grassland 

burning, so if results had been good for wintertime data, the data or profiles being used would be 

suspect, but since the results were poor, we have more confidence in the other burning profiles 

and results. 

Table 4-3. Reduction in wood smoke contributions for the cluster sample dates. 

Wood Smoke Contribution Meteorological Cluster Date (Stage Level) Percent Concentration (μg/m3

) 

1 2/3/2005 16 7.8 

1 12/4/2006 40 18.8 

1 1/9/2007 37 16.7 

1 1/24/2007 32 17.3 

1 2/2/2007 23 10.9 

1 1/19/2008 (1) 27 11.9 

1 12/11/2008 (2) 21 10.0 

1 1/10/2009 (2) 32 11.9 

1 1/13/2009 (2) 20 7.3 

Non-Stage 29 14.3 Average Stage (1 or 2) 25 10.3 

Reduction 4.0 

3 11/21/2005 33 12.3 

3 2/5/2007 26 8.6 

3 11/23/2008 (2) 29 13.3 

Non-Stage 29 10.5 Average Stage (1 or 2) 29 13.3 

Reduction -2.8 

6 12/15/2005 18 5.3 

6 12/5/2008 (1) 30 10.0 

Reduction -4.7 

7 1/18/2007 35 17.5 

7 12/14/2007 (1) 28 12.1 

Reduction 5.4 

9 1/11/2006 17 5.8 

9 11/26/2008 (1) 27 8.1 

Reduction -2.3 

All Clusters 

Non-stage 28 12.1 

Stage (1) 28 10.5 

Stage (2) 25 10.6 Average 

Stage (1 or 2) 27 10.6 

Reduction 1.5 
4-8

Figure 4-3. Percent of contributions to total calculated concentrations for the 

eucalyptus, oak, almond, and combined wood-burning source profile. 

Secondary Question 2: How well is CMB at predicting the contribution? 

Three metrics were used to assess the certainty in CMB model predictions: R-square, chi 

square, and a comparison of the total mass calculated by the model and measured mass. Overall, 

CMB prediction statistics were within tolerances so comparison of source contributions among 

days is reasonable (Table 4-4). In addition, using profiles of almond, eucalyptus, oak, oak and 

eucalyptus combined, and oak, almond, and eucalyptus combined provided a similar estimate of 

the contribution of wood smoke to total PM2.5 mass (Table 4-5). 

The combined oak and eucalyptus profile performed very well in the CMB analysis. On 

all but two sample dates the R square values were greater than 0.8, indicating variance in the data 

was explained well by the model. The two exceptions were unrestricted burn dates, for which 

total measured concentrations were low (less than 10 μg/m3

), where poorer model performance is 

expected. Only three samples exceeded the chi square performance metric on dates with 

substantial mass (approximately 20 μg/m3

 or greater). The model was unable to identify at least 

80% of the measured mass on only two dates, November 26 and November 29, which had 

concentrations in excess of 35 μg/m3. However, on these dates the total concentrations 

reconstructed from ambient speciated data were also much less than the measured 

concentrations, so we expect the model calculated mass to be relatively low. Performance was 

also gauged using the ratio of the calculated to measured concentration for each fitting species. 

Ratios substantially greater than 1 were selectively not included as fitting species for certain 
4-9

sample dates. The ratio for EC was typically between 1 and 2. The CMB calculations could be 

improved by using levoglucosan data to provide a more unique tracer. 

Table 4-4. Performance metrics for the combined oak/eucalyptus wood-burning 

profile. Red indicates Stage 2 days, orange indicates Stage 1 days, clear indicates 

burning discouraged days, green indicates burn cleanly days, and yellow indicates 

fitting statistics outside of criteria. 

Date 

Observed 

Concentration 

(μg/m3

) 

Reconstructed 

Concentration 

(μg/m3) 

R 

Square

Chi 

Square 

Percent of 

Measured Mass 

11/17/2008 18.3 17.9 0.89 1.36 98 

11/20/2008 12.3 14.4 0.97 1.10 118 

11/23/2008 55.3 46.3 0.98 0.74 84 

11/26/2008 37.7 29.9 0.96 1.23 79 

11/29/2008 30.3 23.3 0.98 0.62 77 

12/2/2008 26.3 23.3 0.97 1.16 89 

12/5/2008 40.7 32.9 0.97 1.43 81 

12/8/2008 28.1 24.4 0.94 1.76 87 

12/11/2008 50.3 48.6 0.96 0.95 97 

12/14/2008 6.4 5.2 0.74 6.60 82 

12/17/2008 18.5 21.1 0.98 0.79 114 

12/20/2008 20.9 20.1 0.96 1.50 96 

12/23/2008 8.3 8.8 0.95 1.34 107 

12/26/2008 11.3 12.3 0.91 2.17 109 

12/29/2008 22.6 21.4 0.96 1.01 95 

1/1/2009 19.6 17.2 0.91 3.50 88 

1/4/2009 26.3 22.9 0.97 0.96 87 

1/7/2009 21.9 20.7 0.93 3.09 94 

1/10/2009 40.3 37.3 0.96 1.00 93 

1/13/2009 38.1 37.1 0.93 2.76 97 

1/16/2009 47.5 45.1 0.94 1.75 95 

1/19/2009 24.6 22.8 0.90 1.70 93 

1/22/2009 20.9 17.1 0.96 1.30 82 

1/25/2009 7.3 5.9 0.78 7.06 80 

1/28/2009 15.2 15.5 0.95 1.21 102 

1/31/2009 29.8 28.2 0.95 1.36 95 

2/3/2009 21.9 22.6 0.92 1.36 103 

2/9/2009 12.4 12.9 0.91 1.77 104 

2/12/2009 5.1 6.7 0.89 2.77 132 
4-10

Table 4-5. Percent of wood smoke contributions to total calculated mass for each 

wood-burning profile. Red indicates Stage 2 days, orange indicates Stage 1 days, 

clear indicates burning discouraged days, and green indicates burn cleanly days. 

Burn cleanly days are days with no burning restrictions and concentrations were 

less than 25 μg/m3. Due to collinearity between sources, some days were unable 

to be fit by the model (blank percent contribution). 

 Percent Contribution (%) 

Date 

Total PM2.5

Concentration 

(μg/m3) 

Almond Eucalyptus Oak Oak and 

Eucalyptus 

Oak, Almond, 

and Eucalyptus Tamarisk 

11/17/2008 18.3 27 31 26 28 28 

11/20/2008 12.3 29 24 26 26 67 

11/23/2008 55.3 27 31 26 29 28 73 

11/26/2008 37.7 26 30 25 28 27 71 

11/29/2008 30.3 39 45 38 42 41 92 

12/2/2008 26.3 21 24 20 22 22 58 

12/5/2008 40.7 30 35 29 32 31 76 

12/8/2008 28.1 32 37 31 34 33 83 

12/11/2008 50.3 20 23 19 21 20 50 

12/14/2008 6.4 52 57 49 53 53 109 

12/17/2008 18.5 34 39 33 36 36 86 

12/20/2008 20.9 46 39 42 41 95 

12/23/2008 8.3 42 35 38 38 85 

12/26/2008 11.3 38 43 36 40 39 91 

12/29/2008 22.6 29 33 27 30 30 75 

1/1/2009 19.6 31 26 29 28 72 

1/4/2009 26.3 47 40 44 42 96 

1/7/2009 21.9 28 33 28 30 30 77 

1/10/2009 40.3 30 35 29 32 31 78 

1/13/2009 38.1 19 22 18 20 20 56 

1/16/2009 47.5 21 24 20 22 21 59 

1/19/2009 24.6 38 43 36 39 39 91 

1/22/2009 20.9 33 39 33 36 36 86 

1/25/2009 7.3 32 27 30 30 74 

1/28/2009 15.2 38 43 36 40 39 91 

1/31/2009 29.8 24 28 23 25 25 67 

2/3/2009 21.9 41 46 40 43 42 92 

2/6/2009 6.8 47 103 

2/9/2009 12.4 48 54 46 50 49 105 

2/12/2009 5.1 57 49 53 52 111 

Avg. no 

restriction 

days 

43 44 39 41 41 93 

Avg. Stage 1 28 32 27 29 29 73 

Avg. Stage 2 28 32 27 29 29 71 
4-11

4.3 SEASON REPRESENTATIVENESS 

The findings applicable to the questions that follow are detailed in this subsection. The 

following question (in boldface) was the main focus of the analyses; an important secondary 

question related to these analyses is italicized. 

Was the 2008/2009 wood burning season representative of normal PM2.5

concentrations? 

What would have the 2008/2009 season been like without the “Check Before You Burn” 

(CBYB) program? 

Compared to the preceding four years, the 2008/2009 winter season represents an average 

year in terms of the number of days exceeding the NAAQS. According to the daily BAM 

measurements from DPM, there were 20 exceedance days9

 during the 2008/2009 “winter” 

season, compared to an average of 16 exceedances for the preceding four “winters” (2004/2005, 

2005/2006, 2006/2007, and 2007/2008) (see Figure 4-4). In addition, 2008/2009 represents a 

polluted year in terms of the number of days when meteorological conditions were conducive to 

poor air quality and was similar to 2006/2007 in that regard (see Figure 4-5). When the average 

burn-ban benefit for Stage 1 and Stage 2 days (findings discussed in Section 4.1) was added to 

the observed daily concentrations on Stage 1 and Stage 2 days, the number of exceedance days in 

2008/2009 increased from 20 to 33 (see Figure 4-4). Therefore, the CBYB program could have 

reduced the number of exceedance days during the 2008/2009 winter season by about 40% (or 

13 days). 

Figure 4-6 shows the distribution of peak daily (a) observed AQI and (b) estimated AQI 

if there was no CBYB program for the 2008/2009 season. As noted in the figure, calculations 

show that the CBYB program resulted in a significant reduction in the number of days with 

Unhealthy for Sensitive Groups and Unhealthy AQI levels. 

Figure 4-7 shows the average PM2.5 pollution episode length for the 2004/2005 through 

2008/2009 winter seasons; “episode” is defined as the number of consecutive days exceeding the 

NAAQS. Figure 4-7 show the average episode length in 2008/2009 of about 3.3 days, the 

longest average episode length among winters evaluated (along with the winter of 2005/2006). 

When the average episode length is recalculated using the estimated number of days that PM2.5

concentrations would have exceeded the NAAQS without the CBYB program, the 2008/2009 

average episode length increases to more than 4 days (see Figure 4-7). 

 

9

 Official NAAQS exceedance days for non-attainment designation are based on FRM data. To be NAAQScompliant for PM2.5 , the NAAQS can be exceeded about two days a year if samples were taken every third day, and 

about five days if the sampling frequency was daily. 
4-12

0

5

10

15

20

25

30

35

2004/2005

2005/2006

2006/20072007/2008

2007/2008*

2008/2009

2008/2009*

Year

Number of Days

*Estimate if Stage 1 and Stage 2 days were not called

0

5

10

15

20

25

30

35

2004/2005

2005/2006

2006/20072007/2008

2007/2008*

2008/2009

2008/2009*

Year

Number of Days

*Estimate if Stage 1 and Stage 2 days were not called

Figure 4-4. Number of days that PM2.5 concentrations exceeded the NAAQS 

from the 2004/2005 through 2008/2009 winter seasons (solid bars), and estimated 

number of days PM2.5 concentrations would have exceeded the NAAQS without 

the CBYB program (striped bars). NAAQS exceedances were determined using 

the daily BAM data collected at Del Paso Manor. 

Figure 4-5. Number of meteorologically conducive days for high PM2.5

concentrations for the 2004/2005 through 2008/2009 winter seasons. 
4-13

 2008/2009 2008/2009 Adjusted 

Figure 4-6. Distribution of peak daily PM2.5 AQI by category for the 2008/2009 

season observed (left) and estimated if there was no CBYB program (right). AQI 

categories were determined using daily BAM data from all sites within 

Sacramento County. 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

2004/2005

2005/2006

2006/2007

2007/2008

2007/2008*

2008/2009

2008/2009*

Year

Number of Days

Figure 4-7. Average PM2.5 pollution episode length for the 2004/2005 through 

2008/2009 winter seasons. Solid bars indicate calculations based on observations; 

striped bars indicate estimates if Stage 1 and Stage 2 days were not called. 

NAAQS exceedances were determined using the daily BAM data collected at Del 

Paso Manor. 
4-14

4.4 NO-BURN THRESHOLDS 

The findings applicable to Question 4 are detailed in this subsection: What should the 

no-burn threshold be to reduce PM2.5 below NAAQS? 

Based on our calculations, to reduce the number of days exceeding NAAQS, the no-burn 

thresholds should be set as follows: 

 A single stage program threshold should be about 31 μg/m3

. To derive this threshold, the 

median forecast bias was subtracted from the NAAQS threshold. Because the forecast 

bias was 4.4 μg/m3

 the threshold for a no-burn call is 35 μg/m3 minus 4.4 μg/m3, or 30.6 

μg/m3. 

 A two-stage program threshold should be 31 μg/m3 for Stage 1 and 35 μg/m3 for Stage 2. 

To derive the Stage 2 threshold, we determined the PM2.5 concentration for which a 

Stage 1 call will not be sufficient to prevent a violation of the NAAQS. To calculate this 

threshold, the anticipated PM2.5 reduction resulting from a Stage 1 call was added to 

NAAQS and forecast error was then subtracted. Because the average reduction achieved 

on a Stage 1 day is 4 μg/m3, the no-burn threshold for a Stage 2 day (ignoring forecast 

error) is 39 μg/m3 (35 μg/m3 + 4 μg/m3). Subtracting the forecast error of 4.4 μg/m3

results in a Stage 2 threshold of 34.6 μg/m3

 (39 μg/m3 minus 4.4 μg/m3). 

During the 2008/2009 wood-burning season, these new thresholds would have reduced 

the number of days exceeding the NAAQS from 21 days to 16 days. This conclusion was 

determined by counting the number of days in 2008/2009 when the following criteria were met: 

(1) a burn ban was not called, (2) observed concentrations exceeded the NAAQS, and (3) the 

benefit of the Stage 1 or Stage 2 call would have lowered concentrations below the NAAQS. 

The forecast error of 4.4 μg/m3 cited above was determined by calculating the median 

forecast bias from days during the 2008/2009 winter season when burning was discouraged (see 

Table 4-6). The reason for using the forecast bias from the burning-discouraged category was 

discussed in Section 3.4. 

Table 4-6. Forecast bias (forecast minus observation) for various criteria. The 

red cell indicates the forecast error used for the threshold calculations. 

Day Type Median Bias 

(μg/m3

) 

Median bias for 

under forecasted days

(μg/m3

) 

Median bias for over 

forecasted days 

(μg/m3) 

All 1.8 -4.1 4.7 

Burn Clearly 1.2 -3.5 3.7 

Burning Discouraged 4.1 -4.4 6.4 

Burn Clearly and Burning 

Discouraged 1.4 -3..9 4.2 

Stage 1 and Stage 2 5.2 -5.3 12.7 

Stage 2 5.1 -4.7 12.9 

Stage 1 5.2 -7.1 11.3 
4-15

4.5 BUILD-UP DAY RULE 

The findings applicable to Question 5 are detailed in this subsection: Should no-burn 

days be called on the day prior to high PM2.5 concentration days to help lower pollution 

during PM2.5 episodes? 

Modeling analysis shows that the average contribution of carryover from the preceding 

build-up day to the average 24-hr PM2.5 concentration on the Stage day was 0.7 μg/m3

, or 2.2% 

of the total observed PM2.5 concentration. The range of contributions of carryover was 0.0 to 

2.7 μg/m3, or 0 to 10.6%. Therefore, a no-burn call on the build-up day preceding high PM2.5

concentration days will not significantly lower pollution during PM2.5 episodes. The supporting 

details associated with this finding follows. 

For each of the nine selected cases, the benefit of calling an additional burn ban on buildup days was determined by computing the relative difference in model-predicted Stage-day 24-hr 

average PM2.5 concentrations between the two emission scenarios. Two measures of modeled 

carryover impact were computed: (1) a relative percentage impact, and (2) an estimated 

concentration impact determined by multiplying the relative percentage impact by the peak 24-hr 

average PM2.5 concentration observed in Sacramento County on the Stage day. 

Modeled PM2.5 values were extracted at several receptors in Sacramento County. At 

36-km resolution, most of Sacramento County is covered by four model grid cells (Figure 3-4). 

These grid cells divide Sacramento County into approximate quadrants. The northeast quadrant 

(northeast Sacramento County) covers a significant portion of the county’s residential population 

and includes the Del Paso Manor, Folsom, and Sloughhouse PM2.5 monitoring sites. This 

quadrant also contains the largest residential wood-burning emissions and is, therefore, 

considered representative of residential areas of Sacramento County. 

Modeled carryover impacts for northeast Sacramento County are listed in Table 4-7. The 

relative carryover impact (i.e., the additional benefit of a build-up day burn curtailment) varied 

from case to case, but ranged between 0.1% and 3.6% in eight of the nine cases. The impact was 

10.6% on January 5, 2009. The estimated concentration impact was less than 1.0 μg/m3 on seven 

of the nine cases. The estimated impact was 1.5 μg/m3

 on December 10, 2008, and 2.7 μg/m3 on 

January 5, 2009. 

Table 4-7. Carryover impacts estimated by the BlueSky Gateway for northeast 

Sacramento County. 

Stage Date Relative Carryover 

Impact 

Observed Peak 24-hour Average 

PM2.5 Concentration (μg/m3

) 

Estimated Carryover 

Impact (μg/m3) 

11/17/2008 0.44% 23.8 0.11 

11/23/2008 0.90% 60.7 0.55 

11/30/2008 0.18% 42.3 0.08 

12/3/2008 1.04% 29.3 0.30 

12/10/2008 3.62% 40.5 1.46 

1/5/2009 10.62% 25.7 2.73 

1/7/2009 2.26% 29.2 0.66 

1/10/2009 0.07% 43.5 0.03 

1/29/2009 0.28% 28.9 0.08 
4-16

Carryover impacts were determined for all four Sacramento County grid cells 

(Table 4-8). The 10.62% impact in northeast Sacramento County on January 5, 2009, was the 

regional peak impact for all cases. Peak daily regional carryover impacts ranged from 0.39% to 

3.62%, except on January 5, 2009. The daily carryover impact was greatest in northeast 

Sacramento County on only four of the nine cases, indicating that modeled impacts of burn 

curtailment often occur outside the region of peak residential burning emissions. 

Table 4-8. Relative carryover impacts predicted by BlueSky Gateway for 

Sacramento County. Peak daily carryover impacts are boldfaced; peak carryover 

impact for all nine cases is italicized. 

Stage Date 

Northeast 

Sacramento 

County 

Northwest 

Sacramento 

County 

Southwest 

Sacramento 

County 

Southeast 

Sacramento 

County 

11/17/2008 0.44% 0.86% 1.55% 0.33% 

11/23/2008 0.90% 0.86% 0.42% 0.50% 

11/30/2008 0.18% 0.24% 0.39% 0.37% 

12/3/2008 1.04% -0.12% -0.26% 1.00% 

12/10/2008 3.62% 0.86% 0.30% 1.14% 

1/5/2009 10.62% 1.52% 2.10% 6.86% 

1/7/2009 2.26% -0.04% 0.01% 3.38% 

1/10/2009 0.07% 0.31% 1.14% 0.08% 

1/29/2009 0.28% 0.20% 0.65% 0.91% 

Time series plots show the temporal behavior of modeled PM2.5 concentrations from both 

emission scenarios and illustrate how the impact of carryover evolved throughout the simulation. 

The time series in Figure 4-8 indicates a day with little predicted Stage-day carryover benefit 

(0.18 %). Significant differences between the two emission scenarios are apparent during the 

morning and evening hours of the build-up day as residential wood burning peaks. However, 

BlueSky Gateway predicted a reduction in PM2.5 concentrations in both simulations after the 

evening PM2.5 peak. This reduction may be a result of winds transporting cleaner air into the 

grid cell. Benefits of wood-burning curtailment achieved during the build-up day were lost as 

the time series from the two emission scenarios quickly converge. As a result, PM2.5

concentrations during most of the Stage day are almost identical, and the Stage-day carryover 

benefit is small. 

Figure 4-9 shows the observed average hourly PM2.5 concentrations using BAM data 

from Folsom and Del Paso Manor for November 29 through November 30, 2008. As noted in 

the figure, although the modeled and observed concentrations exhibit a similar diurnal pattern, 

the observed concentrations are two to three times greater than the modeled concentrations. 

Causes of the differences between the modeled and observed concentrations are discussed in 

Section 4.5 under “Modeling Caveats”. 
4-17

A somewhat larger (3.62%) Stage-day carryover benefit was predicted on December 10, 

2008 (Figure 4-10). This simulation differs from the November 30, 2008 case in that the 

predicted benefit from burn curtailment during the build-up day is larger, and an evening cleanout was not predicted; instead, concentrations rose after the evening PM2.5 concentration peak. 

As a result, the large carryover benefit generated during the build-up day carried several hours 

into the Stage day. However, by morning on the Stage day, predicted concentrations from both 

simulations were nearly the same again, though a small residual benefit remained throughout the 

Stage day. As a result, though the carryover impact on December 10, 2008, is larger than on 

November 30, 2008; the overall impact on the Stage-day 24-hr average PM2.5 concentration is 

3.6%. Figure 4-11 shows the observed average hourly PM2.5 concentrations using data from 

Folsom and Del Paso Manor for December 9, 2008, through December 10, 2008. As noted in 

the figure, there is a marked difference in the modeled and observed concentrations on December 

10, 2008. Causes of the differences between the modeled and observed concentrations are 

discussed in Section 4.5 under “Modeling Caveats”. 

0

5

10

15

20

25

0

3

6

9

12

15

18

21

0

3

6

9

12

15

18

21

Hour (PST)

PM2.5 (ug/m3)

2-Day Curtailment 1-Day Curtailment

Figure 4-8. Time series of BlueSky Gateway PM2.5 concentrations in northeast 

Sacramento County for November 29 through November 30, 2008, for one-day 

and two-day residential wood-burning curtailment scenarios. 

0

5

10

15

20

25

30

35

40

45

50

55

60

0

3

6

9

12

15

18

21

0

3

69

12

15

18

21

Hour (PST)

PM2.5 (ug/m3)

Figure 4-9. Time series of observed average hourly PM2.5 concentrations using 

data from Folsom and Del Paso Manor for November 29 through November 30, 

2008. 
4-18

0

5

10

15

20

25

30

35

40

45

50

0

3

6

9

12

15

18

21

0

3

6

9

12

15

18

21

Hour (PST)

PM2.5 (ug/m3)

2-Day Curtailment 1-Day Curtailment

Figure 4-10. Time series of BlueSky Gateway PM2.5 concentrations in northeast 

Sacramento County for December 9, 2008, through December 10, 2008, for 

one-day and two-day residential wood-burning curtailment scenarios. 

0

10

20

30

40

50

60

0

3

6

9

12

15

18

21

0

3

6

9

12

15

18

21

Hour (PST)

PM2.5 (ug/m3)

Figure 4-11. Time series of observed average hourly PM2.5 concentrations using 

data from Folsom and Del Paso Manor for December 9, 2008, through December 

10, 2008. 

Modeling Caveats 

The following limitations should be considered when interpreting results from the 

BlueSky Gateway modeling system: 

 Because of the relatively coarse (36 km) horizontal grid resolution, predicted PM2.5

concentrations in Sacramento County are only modeled with 4 grid cells. Emissions from 

localized sources are diluted into relatively large model grid volumes. This artificially 

smoothes over localized emission patterns, and tends to result in an under prediction of 

PM2.5 concentrations. 

 Wind fields modeled at 36 km resolution are not always representative of the observed 

localized wind fields that drive dispersion characteristics at local scales. As a result, 
4-19

differences between modeled and observed PM2.5 concentrations are to be expected, as 

PM2.5 concentrations can be highly sensitivity to the local wind field. 

 Predicted PM2.5 concentrations are subject to any biases and errors inherent in the 

meteorological model used to produce meteorological data for the air quality model. 

 Sensitivity simulations were performed with 100% curtailment in residential wood 

burning, whereas actual curtailment is likely less than 100%. 
5-1

5. REFERENCES 

Coulter C.T. (2004) EPA-CMB8.2 users manual. Prepared by the Air Quality Modeling Group, 

Emissions, Monitoring, and Analysis Division, Office of Air Quality Planning and 

Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC, 

December. 

Craig K.J., Wheeler N.J.M., Reid S.B., Gilliland E.K., and Sullivan D.C. (2007) Development 

and operation of national CMAQ-based PM2.5 forecast system for fire management. 

Presented at the 6th Annual CMAS Conference, Chapel Hill, NC, October 1-3, by 

Sonoma Technology, Inc., Petaluma, CA (STI-3228). 

Malm W.C., Schichtel B.A., Pitchford M.L., Ashbaugh L.L., and Eldred R.A. (2004) Spatial and 

monthly trends in speciated fine particle concentration in the United States. Journal of 

Geophysical Research (Atmospheres) 109 (D3) (D03306, doi:10.1029/2003JD003739). 

Turpin B.J. and Lim H.-J. (2001) Species contribution to PM2.5 mass concentrations: revisiting 

common assumptions for estimating organic mass. Aerosol Sci. Technol. 35 (10), 602-

610. 
A-1

APPENDIX A 

ADDITIONAL FINDINGS ON THE EFFECTIVENESS OF THE BURNING 

CURTAILMENT PROGRAM TOWARD MEETING THE NAAQS 
A-3

A. INTRODUCTION 

After completing the report entitled “Evaluation of Sacramento Metropolitan Air Quality 

Management District’s ‘Check Before You Burn’ Program” on May 6, 2009, STI conducted 

additional modeling analyses to provide additional information to address the question: “What is 

the effectiveness of the burning curtailment program toward meeting the NAAQS?” This 

appendix reports on the findings from the modeling analyses. The addition of this appendix is 

the reason for the report update on August 24, 2009. 

For these analyses, STI used a three-dimensional photochemical model to estimate PM2.5 

concentrations under three scenarios for 37 winter days in 2008/2009. The model used estimated 

emissions from residential wood burning (1) with no burning restrictions; (2) under a Stage 1 

burn ban; and (3) under a Stage 2 burn ban. The differences in PM2.5 concentrations between the 

no-burning restriction scenario and each burn ban scenario were then calculated to provide an 

estimate of the PM2.5 reduction attributable to the Stage 1 and Stage 2 burn bans. Note that the 

three-dimensional photochemical model includes both secondary and primary PM2.5; therefore, 

the benefits reported in the appendix are reductions in total PM2.5 concentrations due to 

wood-burning restrictions. 

A.1 SUMMARY OF FINDINGS 

In summary, modeling analyses show that 

• the average benefit of a Stage 1 burn ban on the 24-hr average PM2.5 concentration was 

5.2 μg/m3

, or 13.7% of the total PM2.5 concentration; 

• the average benefit of a Stage 2 burn ban was 6.4 μg/m3

, or 16.9% of the total PM2.5 

concentration; 

• the maximum benefit of a Stage 1 burn ban was 8.7 μg/m3, or 18.4%; and 

• the maximum benefit of a Stage 2 burn ban was 10.8 μg/m3

, or 22.7%. 

These modeling results are consistent with the results from the data analysis described in 

the main report. 

A.2 METHOD 

STI used the BlueSky Gateway air quality modeling system. BlueSky Gateway is an 

operational PM2.5 forecasting system developed for the U.S. Forest Service to predict PM2.5

concentrations resulting from wildfires and other emissions sources on a national scale at coarse 

(36 km) resolution. BlueSky Gateway combines meteorological predictions from the 

Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model 

(MM5) (Grell et al., 1994; Dudhia, 1993) with air quality predictions from the Community 

Multiscale Air Quality (CMAQ) model (ENVIRON International Corporation, 2008). STI has 

operated BlueSky Gateway twice daily since its inception in the summer of 2007 (Craig et al., 

2007) . 
A-4

Though BlueSky Gateway was designed primarily to track and predict PM2.5

concentrations from wildfires, the modeling system is run with full gaseous and aerosol 

chemistry to predict the fate of PM2.5 emissions from all types of natural and anthropogenic 

sources, including residential wood burning. Details on the use of BlueSky Gateway to address 

the questions posed by SMAQMD are presented below. Additional details can be found in 

Development and Operation of National CMAQ-Based PM2.5 Forecast System for Fire 

Management (Craig et al., 2007). 

STI performed numerous BlueSky Gateway simulations to evaluate the benefit of Stage 1 

and Stage 2 burn bans on polluted days. Thirty-seven cases from the 2008/2009 winter burning 

season, as shown in Table A-1, were selected for this analysis. In most cases, PM2.5

concentrations were predicted to be high enough to issue a Stage 1 or Stage 2 burn ban. To 

provide initialized concentration fields for the simulations, BlueSky Gateway models with no 

burning restrictions were run for several days prior to each case date until midnight PST of the 

case date. 

For each case date, three simulations were performed: 

1. Base case simulation with no burning curtailment in Sacramento County. 

2. Sensitivity simulation with Stage 1 burn restrictions applied to Sacramento County. 

3. Sensitivity simulation with Stage 2 burn restrictions applied to Sacramento County. 

Wood combustion emission rates for the Stage 1 and Stage 2 burn-ban scenarios were 

developed by applying 57% and 70% across-the-board reduction factors to the Sacramento 

County 2009 wood smoke emissions estimates. Reduction factors were provided by the District 

on the basis of burn ban compliance rates determined by survey. 

Simulations were executed for a 24-hour period starting at midnight PST on the case 

date, for consistency with the timing of actual burn curtailment (midnight to midnight on the day 

for which a burn ban is issued). The modeled difference in PM2.5 concentrations between the 

base case simulation and the sensitivity simulations yields the relative benefit (expressed as a 

percent reduction in concentration) of a Stage 1 or Stage 2 burn ban. A concentration benefit can 

be estimated by multiplying the relative percentage benefit by the observed peak 24-hr average 

PM2.5 concentration in Sacramento County. 
A-5

Table A-1. Cases selected for BlueSky Gateway modeling analysis. 

Case 

Date 

Observed Peak 

24-hour Average 

PM2.5

Concentration 

(μg/m3)

Burn 

Category 

11/17/2008 23.8 Stage 1 

11/22/2008 49.4 Discouraged

11/23/2008 60.7 Stage 2 

11/24/2008 43.0 Stage 2 

11/25/2008 36.3 Stage 1 

11/26/2008 43.1 Stage 1 

11/27/2008 30.5 Stage 2 

11/28/2008 30.0 Stage 2 

11/30/2008 42.3 Stage 1 

12/3/2008 29.3 Stage 2 

12/4/2008 30.3 Stage 2 

12/5/2008 45.5 Stage 1 

12/6/2008 38.9 Stage 2 

12/7/2008 32.0 Stage 1 

12/10/2008 40.5 Stage 2 

12/11/2008 49.3 Stage 2 

12/12/2008 69.8 Discouraged

1/5/2009 25.7 Stage 2 

1/7/2009 29.2 Stage 2 

1/10/2009 43.5 Stage 2 

1/11/2009 55.2 Stage 2 

1/12/2009 38.0 Stage 2 

1/13/2009 43.5 Stage 2 

1/14/2009 50.2 Stage 2 

1/15/2009 42.5 Stage 2 

1/16/2009 50.1 Stage 2 

1/17/2009 45.6 Stage 2 

1/18/2009 28.1 Stage 2 

1/19/2009 28.3 Stage 2 

1/20/2009 23.2 Stage 2 

1/29/2009 28.9 Stage 1 

1/30/2009 39.7 Stage 2 

1/31/2009 35.1 Stage 2 

2/1/2009 26.7 Stage 2 

2/2/2009 29.5 Stage 2 

2/3/2009 28.0 Stage 2 

2/4/2009 24.7 Stage 1 
A-6

Estimates of residential wood combustion emissions for Sacramento County were 

developed from 2009 county-level average winter day emissions estimates provided by the 

District. These emissions were based on the California Air Resources Board (ARB) version 1.06 

emissions inventory, which uses a 2002 base year. County-level emissions were spatially 

allocated according to census data on households with wood heating as the primary heating 

source. Emissions were allocated to model grid cells with the Sparse Matrix Operator Kernel 

Emissions (SMOKE) Modeling System (Houyoux et al., 2000). 

Residential wood combustion emissions outside of Sacramento County were taken from 

the 2002 National Emission Inventory (NEI), processed through SMOKE, and projected to 2007 

by using growth factors generated by EPA’s Economic Growth Analysis System (EGAS) 

version 4.0 (E.H. Pechan & Associates, 2001). For wood combustion emissions from all 

counties, the standard SMOKE speciation profile was used to disaggregate total PM2.5 emissions 

into individual model species (Table A-2), and the default SMOKE diurnal profile for residential 

wood combustion was replaced with a more appropriate profile developed by the ARB. 

Table A-2. SMOKE PM2.5 speciation profile 

Profile # Model Species Model Species Name Mass Fraction 

22061 PEC Primary elemental carbon 0.1077 

22061 PMFINE Fine mode PM (metals and 

other species) 0.3208 

22061 PNO3 Primary nitrate aerosol 0.0022 

22061 POA Primary organic aerosol 0.5656 

22061 PSO4 Primary sulfate aerosol 0.0037 

Because of the relatively coarse horizontal resolution of BlueSky Gateway (36 km), peak 

concentrations may be underestimated by the model as localized emissions are artificially diluted 

into relatively large model grid cells. Figure A-1 illustrates the size of BlueSky Gateway model 

grid cells relative to Sacramento County. To address the effects of such coarse resolution, STI 

avoided using absolute modeled concentration differences and instead used the relative

difference between the base case (no burn restriction) scenario and the Stage 1 and Stage 2 

sensitivity scenarios to assess the benefit of the burn ban. 
A-7

Figure A-1. BlueSky Gateway model grid in the Sacramento County region. 

Grid cells highlighted in red indicate the four cells that encompass most of 

Sacramento County. 

A.3 MODELING CAVEATS 

The following limitations should be considered when interpreting results from the 

modeling analyses: 

 Because of the relatively coarse horizontal grid resolution used in the model, PM2.5

concentrations are only estimated in four grid cells, which cover Sacramento County. 

Emissions from localized sources are diluted in the relatively large model grid volumes. 

This dilution artificially smoothes over localized emission patterns and tends to result in 

an under-estimation of PM2.5 concentrations.

 Wind fields modeled at 36-km resolution are not always representative of the localized 

winds that drive transport and dispersion on local scales. As a result, differences between 

modeled and observed PM2.5 concentrations are to be expected, as PM2.5 concentrations 

can be highly sensitive to the local winds. 

 Estimations of PM2.5 concentrations are subject to any biases and errors inherent in the 

meteorological model used to provide data to the air quality model. 
A-8

A.4 FINDINGS 

Modeling analysis results show that the average benefit of a Stage 1 burn ban on the 

regional peak 24-hr average PM2.5 concentration was 5.2 μg/m3, or 13.7% of the total observed 

PM2.5 concentration. The average benefit of a Stage 2 burn ban was 6.4 μg/m3

, or 16.9% of the 

total observed PM2.5 concentration. The range of benefits of a Stage 1 burn ban was from 2.2 to 

8.7 μg/m3, or from 7.8 to 18.4%. The range of benefits of a Stage 2 burn ban was from 2.7 to 

10.8 μg/m3

, or from 9.7 to 22.7%. 

Modeled estimates of PM2.5 concentrations were extracted at several receptors in 

Sacramento County. At 36-km resolution, most of Sacramento County is covered by four model 

grid cells (Figure A-1). These grid cells divide Sacramento County approximately into 

quadrants. The northeast quadrant (northeast Sacramento County) covers a significant portion of 

the county’s residential population and includes the Del Paso Manor, Folsom, and Sloughhouse 

PM2.5 monitoring sites. This quadrant is responsible for the largest amount of residential 

wood-burning emissions and is, therefore, considered representative of residential areas of 

Sacramento County. 

Modeled Stage 1 and Stage 2 burn-ban benefits for northeast Sacramento County are 

listed in Table A-3. Modeled benefits varied from case to case, but were never less than 

2.2 μg/m3 for a Stage 1 burn ban, or 2.7 μg/m3 for a Stage 2 burn ban. Relative benefits of Stage 

1 burn bans exceeded 10% for 31 of 37 modeled cases, while relative benefits of Stage 2 burn 

bans exceeded 10% for all but one modeled case. The maximum modeled relative benefit 

occurred on November 17, 2008, with relative benefits of 18.4% and 22.7% for Stage 1 and 

Stage 2 burn bans, respectively. The maximum modeled concentration benefit occurred on 

January 16, 2009, with benefits of 8.7 μg/m3 and 10.8 μg/m3 for Stage 1 and Stage 2 burn bans, 

respectively. 

Relative burn-ban benefits were determined for all four Sacramento County grid cells 

(Table A-4). The maximum relative benefit from Stage 1 and Stage 2 burn bans was in 

northeast Sacramento County, on November 17, 2009. In all cases, benefits were greater in 

northeast Sacramento County than in other parts of Sacramento County, as residential 

wood-burning emissions were highest in northeast Sacramento County. Southwest Sacramento 

County had the smallest benefit for all but one case. 
A-9

Table A-3. Modeled benefits of Stage 1 and Stage 2 burn bans estimated by the 

BlueSky Gateway for northeast Sacramento County. 

Stage Date 

Observed Peak 24-hour 

Average PM2.5

Concentration (μg/m3

) 

Relative Stage 1 

Benefit 

Estimated Stage 1 

Benefit (μg/m3

) 

Relative Stage 2 

Benefit 

Estimated Stage 2 

Benefit (μg/m3) 

11/17/2008 23.8 18.4% 4.4 22.7% 5.4 

11/22/2008 49.4 13.5% 6.7 16.7% 8.3 

11/23/2008 60.7 12.6% 7.6 15.5% 9.4 

11/24/2008 43.0 9.9% 4.2 12.2% 5.2 

11/25/2008 36.3 11.9% 4.3 14.8% 5.4 

11/26/2008 43.1 12.7% 5.5 15.7% 6.8 

11/27/2008 30.5 17.4% 5.3 21.4% 6.5 

11/28/2008 30.0 12.8% 3.8 15.8% 4.7 

11/30/2008 42.3 16.9% 7.1 20.8% 8.8 

12/3/2008 29.3 13.0% 3.8 16.0% 4.7 

12/4/2008 30.3 8.9% 2.7 10.9% 3.3 

12/5/2008 45.5 16.8% 7.7 20.8% 9.5 

12/6/2008 38.9 12.4% 4.8 15.3% 6.0 

12/7/2008 32.0 13.4% 4.3 16.5% 5.3 

12/10/2008 40.5 8.2% 3.3 10.1% 4.1 

12/11/2008 49.3 9.7% 4.8 12.0% 5.9 

12/12/2008 69.8 7.8% 5.5 9.7% 6.8 

1/5/2009 25.7 8.6% 2.2 10.6% 2.7 

1/7/2009 29.2 11.8% 3.4 14.5% 4.2 

1/10/2009 43.5 16.8% 7.3 20.8% 9.1 

1/11/2009 55.2 12.2% 6.7 15.0% 8.3 

1/12/2009 38.0 17.5% 6.7 21.6% 8.2 

1/13/2009 43.5 16.6% 7.2 20.6% 9.0 

1/14/2009 50.2 15.3% 7.7 19.0% 9.6 

1/15/2009 42.5 16.6% 7.0 20.5% 8.7 

1/16/2009 50.1 17.4% 8.7 21.5% 10.8 

1/17/2009 45.6 16.7% 7.6 20.7% 9.4 

1/18/2009 28.1 16.0% 4.5 19.8% 5.6 

1/19/2009 28.3 15.1% 4.3 18.8% 5.3 

1/20/2009 23.2 14.1% 3.3 17.4% 4.0 

1/29/2009 28.9 16.6% 4.8 20.5% 5.9 

1/30/2009 39.7 14.6% 5.8 18.0% 7.2 

1/31/2009 35.1 11.2% 3.9 13.8% 4.8 

2/1/2009 26.7 11.9% 3.2 14.8% 3.9 

2/2/2009 29.5 11.9% 3.5 14.6% 4.3 

2/3/2009 28.0 14.8% 4.2 18.3% 5.1 

2/4/2009 24.7 14.9% 3.7 18.2% 4.5 
A-10

 

Table A-4. Relative benefit (%) of Stage 1 and Stage 2 burn bans predicted by 

BlueSky Gateway for Sacramento County. The maximum and minimum relative 

benefits at each receptor are boldfaced. 

Stage Date 

Northeast Sacramento 

County 

Northwest Sacramento 

County 

Southwest Sacramento 

County 

Southeast Sacramento 

County 

 Stage 1 Stage 2 Stage 1 Stage 2 Stage 1 Stage 2 Stage 1 Stage 2 

11/17/2008 18.4 22.7 8.7 10.8 4.3 5.3 9.1 11.2 

11/22/2008 13.5 16.7 4.9 6.0 2.3 2.9 3.6 4.5 

11/23/2008 12.6 15.5 3.2 3.9 1.3 1.6 2.9 3.6 

11/24/2008 9.9 12.2 3.3 4.1 0.8 1.0 2.0 2.5 

11/25/2008 11.9 14.8 4.7 5.8 2.1 2.6 3.9 4.8 

11/26/2008 12.7 15.7 2.2 2.6 0.9 1.1 4.0 5.0 

11/27/2008 17.4 21.4 4.9 6.1 2.2 2.7 9.9 12.2 

11/28/2008 12.8 15.8 2.2 2.7 1.0 1.2 4.5 5.5 

11/30/2008 16.9 20.8 6.1 7.5 2.2 2.6 5.6 6.9 

12/3/2008 13.0 16.0 4.4 5.4 2.1 2.6 4.9 6.1 

12/4/2008 8.9 10.9 1.9 2.4 1.1 1.3 3.8 4.7 

12/5/2008 16.8 20.8 5.9 7.3 4.5 5.5 9.8 12.0 

12/6/2008 12.4 15.3 3.7 4.5 2.6 3.2 7.9 9.7 

12/7/2008 13.4 16.5 3.6 4.4 1.9 2.4 6.9 8.5 

12/10/2008 8.2 10.1 1.7 2.0 0.9 1.1 3.9 4.8 

12/11/2008 9.7 12.0 2.1 2.5 1.2 1.4 5.2 6.4 

12/12/2008 7.8 9.7 2.8 3.4 0.7 0.9 2.1 2.6 

1/5/2009 8.6 10.6 5.1 6.2 1.3 1.6 2.3 2.8 

1/7/2009 11.8 14.5 3.0 3.6 1.7 2.1 5.2 6.4 

1/10/2009 16.8 20.8 6.3 7.7 5.0 6.1 10.7 13.1 

1/11/2009 12.2 15.0 3.5 4.3 2.8 3.5 8.6 10.5 

1/12/2009 17.5 21.6 6.8 8.4 7.0 8.6 11.7 14.5 

1/13/2009 16.6 20.6 6.7 8.3 5.3 6.5 11.4 14.1 

1/14/2009 15.3 19.0 5.3 6.5 3.9 4.8 9.4 11.7 

1/15/2009 16.6 20.5 7.0 8.6 4.1 5.1 8.8 10.9 

1/16/2009 17.4 21.5 7.1 8.7 5.0 6.1 11.8 14.5 

1/17/2009 16.7 20.7 5.8 7.2 4.0 4.9 9.8 12.0 

1/18/2009 16.0 19.8 6.2 7.7 4.8 5.9 9.9 12.3 

1/19/2009 15.1 18.8 6.8 8.4 6.6 8.1 10.4 12.9 

1/20/2009 14.1 17.4 6.4 7.9 5.6 6.9 8.5 10.5 

1/29/2009 16.6 20.5 5.9 7.3 3.4 4.2 6.0 7.6 

1/30/2009 14.6 18.0 4.9 6.1 3.3 4.0 9.2 11.3 

1/31/2009 11.2 13.8 3.1 3.8 1.8 2.3 7.2 8.8 

2/1/2009 11.9 14.8 4.0 4.9 2.8 3.5 7.8 9.6 

2/2/2009 11.9 14.6 5.3 6.6 2.2 2.7 3.5 4.4 

2/3/2009 14.8 18.3 7.1 8.8 2.4 2.9 4.6 5.7 

2/4/2009 14.9 18.2 8.7 10.9 3.1 3.9 5.0 6.3 
A-11

REFERENCES

Craig K.J., Wheeler N.J.M., Reid S.B., Gilliland E.K., and Sullivan D.C. (2007) Development 

and operation of national CMAQ-based PM2.5 forecast system for fire management. 

Presented at the 6th Annual CMAS Conference, Chapel Hill, NC, October 1-3, by 

Sonoma Technology, Inc., Petaluma, CA (STI-3228). 

Dudhia J. (1993) A non-hydrostatic version of the Penn State/NCAR mesoscale model: 

validation tests and simulation of an Atlantic cyclone and cold front. MWRv 121, 1493-

1513. 

E.H. Pechan & Associates, Inc. (2001) Economic Growth Analysis System: Version 4.0 

Reference Manual. Final draft prepared for Emission Factor and Inventory Group, 

Emissions, Monitoring, and Analysis Division, Office of Air Quality Planning and 

Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC, January. 

ENVIRON International Corporation (2008) User’s guide - Comprehensive Air Quality Model 

with Extensions (CAMx). Version 4.50. Prepared by ENVIRON International 

Corporation, Novato, CA, May. Available on the Internet at 

http://www.camx.com/files/CAMxUsersGuide_v4.5.pdf. 

Grell G.A., Dudhia J., and Stauffer D.R. (1994) A description of the fifth-generation Penn 

State/NCAR mesoscale model (MM5). Prepared by the National Center for Atmospheric 

Research, Boulder, CO, NCAR Technical Note-398. 

Houyoux M., Vukovich J., and Brandmeyer J. (2000) Sparse Matrix Operator Kernel Emissions 

Modeling System (SMOKE) user manual. Prepared by MCNC-North Carolina 

Supercomputing Center, Environmental Programs, Research Triangle Park, NC. 
APPENDIX E 

Emissions Calculations 

The baseline emissions are based on historical usage patterns. Emissions are calculated as 

follows: 

Emissions = (Number of Homes) x (fraction of homes w/ device) x (fraction of homes w/ device 

that burn) x (Average amount of wood burned per home) x (EFburning) 

This calculation is repeated for each type of device, and the totals are summed. These 

emissions are assumed to all be emitted during the Check Before You Burn season, which 

includes 120 days. It is assumed that the percent of fuel burned in November through February 

is 69.1% of all wood burned. 

The reduction from a day of mandatory curtailment is calculated by taking 1/120th of the total 

calculated emissions, and adjusting this amount by the emissions reduction rate determined 

from the 2009 Aurora survey. The total reduction for the season for each option is calculated as 

the daily reduction times the expected additional number of days of mandatory curtailment. 

Stage 1 and Stage 2 No Burn days are differentiated by allowing all certified and pellet devices 

to burn on Stage 1 and using stage specific emissions reduction rates. 

The variables used and the calculations are summarized in the following tables: 
2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

B C D E

Source

Total Residences in Sacramento County 502095 Units State of CA Finance Dept, 2008

% of Homes w/ fireplace 31% Aurora, 2007

% of Homes w/ fireplace that burn wood 63% Aurora, 2007

% of Homes that burned that burned cord wood 80% Aurora, 2007

% of Homes w/fireplace that burn wood for heat 31% Aurora 2007

% of Homes w/fireplace that burn wood for aesthetic 69% Aurora, 2007

% of Homes that used fireplace and burned Manf. Logs 20% Aurora, 2007

% of Homes w/ wood stove 5% Aurora, 2007

% of Homes w/ wood stove that are Phase II certified 43% Houck, 2003

 % of the Phase II wood stoves that are catalytic 17% Houck, 2003

% of Homes w/ stove that burn 63% Aurora, 2007

% of Homes w/ wood insert 16% Aurora, 2007

% of Homes w/ wood insert that are Phase II certified 45% Houck, 2003

 % of the Phase II wood inserts that are catalytic 50% Houck, 2003

% of Homes w/ inserts that burn 63% Aurora, 2007

% of Homes w/ insert that burn wood 87% Aurora, 2007

% of Homes w/pellet stove 3% Aurora, 2007

% of Homes w/pellet stove that burned 63% Aurora, 2007

Average Wood Usage Per Household that burns wood 

(heat) 0.656 cord/home Houck, 2001

Average Wood Usage Per Household that burns wood 

(aesthetic) 0.069 cord/home Houck, 2001

Average Manufactured Log Use Per Household that 

burns wood 19 Log/yr Houck, 2003

Average Wood Use Per Household that burns wood 

(stove) 1.5 cord/home Houck, 2003

Average Wood Use Per Household that burns wood 

(insert) 1.2 cord/home Houck, 2003

Average Pellet Use Per Household that burns wood 4000 lb/yr Houck, 2004

Percent of Wood that is Purchased 51.4% Houck, 2003

Heating Value of Wood Btu/lb Representative of Certifed Units 6,050

Heating Value of Manufactured Log 15,700 Btu/lb Houck, Wax-Sawdust Firelogs

Uncontrolled Fireplace EF 23.6 lb PM10/ton of wood Pechan, 2006

Uncontrolled Stove/Insert EF 30.6 lb PM10/ton of wood AP 42 1.10

Controlled (non-catalytic) Stove/Insert EF 14.6 lb PM10/ton of wood AP 42 1.10

Controlled (catalytic) Stove/Insert EF 20.4 lb PM10/ton of wood AP 42 1.10

Manufactured Log EF 29.4 lb PM10/ton of log Li, 2006

Pellet Stove EF 3.06 lb PM10/ton of wood Houck, 2006 (MARAMA)

Wood Smoke PM2.5/PM10 Fraction 0.96 CARB Estimate

NG PM10 EF lb/MMBtu AP 42 1.4 0.007

NOx EF Fireplace lb/ton of wood AP 42 1.9 2.6

NOx EF Uncontrolled Stove lb/ton of wood AP 42 1.9 2.8

NOx EF Phase II Stove lb/ton of wood AP 42 1.9 2.0

NOx EF Pellet Stove lb/ton of wood Houck, 2006 (MARAMA) 3.8

CO EF Fireplace lb/ton of wood 2002 NEI, Pechan, 2006 128.0

CO EF Uncontrolled Stove lb/ton of wood AP 42 1.10 230.8

CO EF Phase II Stove lb/ton of wood AP 42 1.10 140.8

CO EF Pellet Stove lb/ton of wood Houck, 2006 (MARAMA) 15.9

VOC EF Fireplace lb/ton of wood AP 42 1.9 229.0

VOC EF Uncontrolled Stove lb/ton of wood AP 42 1.10 53.0

VOC EF Phase II Stove lb/ton of wood AP 42 1.10 12.0

VOC EF Pellet Stove lb/ton of wood Houck, 2006 (MARAMA) 0.04

Thermal Efficiency Fireplace 7% Houck, 1998

Thermal Efficiency Certified Stove/Insert 63% Representative of Certified Units

Thermal Efficiency NG Fireplace 75% Houck, 1998

Incremental Cost to install Certified Fireplace Insert 2,500.00 $ John Crouch, HPBA

Incremental Cost to install NG Fireplace Insert 3,00 $ Staff Survey 0.00

Incremental Cost to install Gas Log set 300.00 $ Staff Survey

Cost of Wood ($/per Cord) 269.00 ERG, 2009

Cost of Manufactured Log ($/per Log) 5.00 ERG, 2009

Cost of Pellet ($/per Bag) ERG, 2009 6.88

Cost of NG ($/MMBtu) Staff Survey 10.91

Cost of Electricity ($/kWh) Staff Survey 0.09

Burn Rate of Wood in Fireplace 6.60 lb/hr Houck, 1998

Burn Rate of Manufactured Log in Fireplace 3.00 hr/log Houck, Wax-Sawdust Firelogs

Median Burn Rate Certified Fireplace Insert 3.16 lb/hr Representative of Certified Units

Heat Input Rate NG Insert 30,000 BTU/hr Staff Survey

Weight of an Average Cord of Wood 1.54 ton/cord Houck & Eagle, 2006

Weight of Manufactured Log 5.00 lb/log Broderick, 2003

% of Fuel Burned in November through February 69.1% CARB Inventory Methodology

Information
Recommended Change - Stage 1

Total Housing Units 502095 57%

Threshold 31 μg/m3Stage 1 Days 5

Wood Burning Appliance Types Fireplace Stoves Inserts Pellet Stoves Total

% 31% 5% 16% 3.0% 55%

# total 155649 25105 80335 15063 276152

# total that burn 98059 15816 50611 9490 173976

# Phase II certified out of total that burn 6801 22775

# Catalytic out of the Phase II certified 1156 11388

Cords of fuel burned per winter day Nov-Feb 125 137 350

Tons of fuel burned Nov thru Feb (heat+asthetic) 23046 25246 64629

Tons PM2.5 Emissions from cord wood Nov-Feb 271.9

Manufactured logs burned per winter day Nov-Feb 2146

Tons Manufactured logs burned Nov thru Feb 644

Tons PM2.5 Emissions from logs Nov thru Feb 9.5

Total Fireplace Emissions Nov thru Feb 281.4

Cords of fuel burned per winter day (Nov-Feb) noncertified 78 192

Cords of fuel burned per winter day (Nov-Feb) certified 59 157

Tons of fuel burned Nov-Feb uncertified 14390 35546

Tons of fuel burned Nov-Feb Phase II - non cat 9010 24139

Tons of fuel burned Nov-Feb phase II - cat 1845 4944

Tons PM2.5 Emissions Nov-Feb from uncertified 220.2 543.8

Tons PM2.5 Emissions Nov-Feb from phase II 65.8 176.2

Tons PM2.5 Emissions Nov-Feb from phase II - catalytic 18.8 50.4

Total Stove Emissions Nov thru Feb 304.8 770.5

Tons fuel burned per winter pellet stove per day 109

Tons PM2.5 Emissions from Pellet Stove Nov thru Feb 20.1

$ amount of fuel used per winter day Nov thru Feb 33 $ 36,748 ,635 $ 94,075 $ 37,597 $ 202,055.77 $ 

$ amount of reduced fuel used per No Burn day Nov-Feb 19,172 $ 11,939 $ 29,493 $ - $ 60,604.08 $ 

PM2.5 Total Uncontrolled Emissions (lb/day) Nov-Feb 5,079 4,690 12,842 334 22,945

PM2.5 Total Reduction (lb/day) Nov-Feb 2,673 2,092 5,167 - 9,931

Percent Reduction per curtailment day 57.0% 41.2% 40.2% 0.0% 43.3%

Overall PM2.5 Cost Effectiveness ($/ton) $ 6,273.10

Overall PM2.5 Cost Effectiveness ($/lb) $ 3.14

NOx Uncontrolled (lb/day) 540 517 1,314 415 2,786

NOx Reduction (lb/day) 295 308 749 - 1,351

NOx from NG 45 10 110 - 165

Net NOx Reduction 250 298 639 - 1,186

CO Uncontrolled (lb/day) 25,253 36,229 93,852 1,738 157,071

CO Reduction (lb/day) 8,749 14,394 21,612 - 44,755

CO from NG 38 8 93 - 139

Net CO Reduction 8,712 14,386 21,519 - 44,616

VOC Uncontrolled (lb/day) 44,191 7,487 18,731 4.37 70,410

VOC Reduction (lb/day) 3,623 25,189 8,949 - 37,760 

VOC from NG 2 1 6 - 9 

Net VOC Reduction 3,620 25,189 8,943 - 37,751

Stage 1 Compliance Rate
Recommended Change - Stage 2

Total Housing Units 502095 70%

Threshold 35 μg/m3Stage 2 Days 23

Wood Burning Appliance Types Fireplace Stoves Inserts Pellet Stoves Total

% 31% 5% 16% 3.0% 55%

# total 155649 25105 80335 15063 276152

# total that burn 98059 15816 50611 9490 173976

# Phase II certified out of total that burn 6801 22775

# Catalytic out of the Phase II certified 1156 11388

Cords of fuel burned per winter day Nov-Feb 125 137 350

Tons of fuel burned Nov thru Feb (heat+asthetic) 23046 25246 64629

Tons PM2.5 Emissions from cord wood Nov-Feb 271.9

Manufactured logs burned per winter day Nov-Feb 2146

Tons Manufactured logs burned Nov thru Feb 644

Tons PM2.5 Emissions from logs Nov thru Feb 9.5

Total Fireplace Emissions Nov thru Feb 281.4

Cords of fuel burned per winter day (Nov-Feb) noncertified 78 192

Cords of fuel burned per winter day (Nov-Feb) certified 59 157

Tons of fuel burned Nov-Feb uncertified 14390 35546

Tons of fuel burned Nov-Feb Phase II - non cat 9010 24139

Tons of fuel burned Nov-Feb phase II - cat 1845 4944

Tons PM2.5 Emissions Nov-Feb from uncertified 220.2 543.8

Tons PM2.5 Emissions Nov-Feb from phase II 65.8 176.2

Tons PM2.5 Emissions Nov-Feb from phase II - catalytic 18.8 50.4

Total Stove Emissions Nov thru Feb 304.8 770.5

Tons fuel burned per winter pellet stove per day 109

Tons PM2.5 Emissions from Pellet Stove Nov thru Feb 20.1

$ amount of fuel used per winter day Nov thru Feb 33 $ 36,748 ,635 $ 94,075 $ 37,597 $ 202,055.77 $ 

$ amount of reduced fuel used per No Burn day Nov-Feb 23,545 $ 25,724 $ 65,853 $ 26,318 $ 141,439.04 $ 

PM2.5 Total Uncontrolled Emissions (lb/day) Nov-Feb 5,079 4,690 12,842 334 22,945

PM2.5 Total Reduction (lb/day) Nov-Feb 3,283 3,556 8,989 234 16,062

Percent Reduction per curtailment day 70.0% 70.0% 70.0% 70.0% 70.0%

Overall PM2.5 Cost Effectiveness ($/ton) $ 10,645.16

Overall PM2.5 Cost Effectiveness ($/lb) $ 5.32

NOx Uncontrolled (lb/day) 517 540 1,314 415 2,786 

NOx Reduction (lb/day) 378 362 920 291 1,950

NOx from NG 103 12 265 58 438

Net NOx Reduction 259 366 655 232 1,512

CO Uncontrolled (lb/day) 36,229 25,253 93,852 1,738 157,071 

CO Reduction (lb/day) 17,677 25,360 65,696 1,216 109,949

CO from NG 87 10 222 - 319

Net CO Reduction 25,273 17,667 65,474 1,216 109,630

VOC Uncontrolled (lb/day) 7,487 44,191 18,731 4.37 70,410 

VOC Reduction (lb/day) 30,934 5,241 13,112 3 49,287

VOC from NG 6 1 15 3 21 

Net VOC Reduction 5,235 30,933 13,097 (0) 49,266

Stage 2 Compliance Rate
Option B - Stage 1

Total Housing Units 502095 57%

Threshold 31 μg/m3Stage 1 Days 5

Wood Burning Appliance Types Fireplace Stoves Inserts Pellet Stoves Total

% 31% 5% 16% 3.0% 55%

# total 155649 25105 80335 15063 276152

# total that burn 98059 15816 50611 9490 173976

# Phase II certified out of total that burn 6801 22775

# Catalytic out of the Phase II certified 1156 11388

Cords of fuel burned per winter day Nov-Feb 125 137 350

Tons of fuel burned Nov thru Feb (heat+asthetic) 23046 25246 64629

Tons PM2.5 Emissions from cord wood Nov-Feb 271.9

Manufactured logs burned per winter day Nov-Feb 2146

Tons Manufactured logs burned Nov thru Feb 644

Tons PM2.5 Emissions from logs Nov thru Feb 9.5

Total Fireplace Emissions Nov thru Feb 281.4

Cords of fuel burned per winter day (Nov-Feb) noncertified 78 192

Cords of fuel burned per winter day (Nov-Feb) certified 59 157

Tons of fuel burned Nov-Feb uncertified 14390 35546

Tons of fuel burned Nov-Feb Phase II - non cat 9010 24139

Tons of fuel burned Nov-Feb phase II - cat 1845 4944

Tons PM2.5 Emissions Nov-Feb from uncertified 220.2 543.8

Tons PM2.5 Emissions Nov-Feb from phase II 65.8 176.2

Tons PM2.5 Emissions Nov-Feb from phase II - catalytic 18.8 50.4

Total Stove Emissions Nov thru Feb 304.8 770.5

Tons fuel burned per winter pellet stove per day 109

Tons PM2.5 Emissions from Pellet Stove Nov thru Feb 20.1

$ amount of fuel used per winter day Nov thru Feb 33 $ 36,748 ,635 $ 94,075 $ 37,597 $ 202,055.77 $ 

$ amount of reduced fuel used per No Burn day Nov-Feb 19,172 $ 11,939 $ 29,493 $ - $ 60,604.08 $ 

PM2.5 Total Uncontrolled Emissions (lb/day) Nov-Feb 5,079 4,690 12,842 334 22,945

PM2.5 Total Reduction (lb/day) Nov-Feb 2,673 2,092 5,167 - 9,931

Percent Reduction per curtailment day 57.0% 41.2% 40.2% 0.0% 43.3%

Overall PM2.5 Cost Effectiveness ($/ton) $ 6,273.10

Overall PM2.5 Cost Effectiveness ($/lb) $ 3.14

NOx Uncontrolled (lb/day) 517 540 1,314 415 2,786 

NOx Reduction (lb/day) 308 295 749 - 1,351

NOx from NG 45 10 110 - 165

Net NOx Reduction 250 298 639 - 1,186

CO Uncontrolled (lb/day) 36,229 25,253 93,852 1,738 157,071 

CO Reduction (lb/day) 14,394 8,749 21,612 - 44,755

CO from NG 38 8 93 - 139

Net CO Reduction 8,712 14,386 21,519 - 44,616

VOC Uncontrolled (lb/day) 7,487 44,191 18,731 4.37 70,410 

VOC Reduction (lb/day) 25,189 3,623 8,949 - 37,760

VOC from NG 2 1 6 - 9 

Net VOC Reduction 3,620 25,189 8,943 - 37,751

Stage 1 Compliance Rate
Option B - Stage 2

Total Housing Units 502095 70%

Threshold 35 μg/m3Stage 2 Days 23

Wood Burning Appliance Types Fireplace Stoves Inserts Pellet Stoves Total

% 31% 5% 16% 3.0% 55%

# total 155649 25105 80335 15063 276152

# total that burn 98059 15816 50611 9490 173976

# Phase II certified out of total that burn 6801 22775

# Catalytic out of the Phase II certified 1156 11388

Cords of fuel burned per winter day Nov-Feb 125 137 350

Tons of fuel burned Nov thru Feb (heat+asthetic) 23046 25246 64629

Tons PM2.5 Emissions from cord wood Nov-Feb 271.9

Manufactured logs burned per winter day Nov-Feb 2146

Tons Manufactured logs burned Nov thru Feb 644

Tons PM2.5 Emissions from logs Nov thru Feb 9.5

Total Fireplace Emissions Nov thru Feb 281.4

Cords of fuel burned per winter day (Nov-Feb) noncertified 78 192

Cords of fuel burned per winter day (Nov-Feb) certified 59 157

Tons of fuel burned Nov-Feb uncertified 14390 35546

Tons of fuel burned Nov-Feb Phase II - non cat 9010 24139

Tons of fuel burned Nov-Feb phase II - cat 1845 4944

Tons PM2.5 Emissions Nov-Feb from uncertified 220.2 543.8

Tons PM2.5 Emissions Nov-Feb from phase II 65.8 176.2

Tons PM2.5 Emissions Nov-Feb from phase II - catalytic 18.8 50.4

Total Stove Emissions Nov thru Feb 304.8 770.5

Tons fuel burned per winter pellet stove per day 109

Tons PM2.5 Emissions from Pellet Stove Nov thru Feb 20.1

$ amount of fuel used per winter day Nov thru Feb 33 $ 36,748 ,635 $ 94,075 $ 37,597 $ 202,055.77 $ 

$ amount of reduced fuel used per No Burn day Nov-Feb 23,545 $ 25,724 $ 65,853 $ 26,318 $ 141,439.04 $ 

PM2.5 Total Uncontrolled Emissions (lb/day) Nov-Feb 5,079 4,690 12,842 334 22,945

PM2.5 Total Reduction (lb/day) Nov-Feb 3,283 3,556 8,989 234 16,062

Percent Reduction per curtailment day 70.0% 70.0% 70.0% 70.0% 70.0%

Overall PM2.5 Cost Effectiveness ($/ton) $ 10,645.16

Overall PM2.5 Cost Effectiveness ($/lb) $ 5.32

NOx Uncontrolled (lb/day) 540 517 1,314 415 2,786

NOx Reduction (lb/day) 362 378 920 291 1,950

NOx from NG 103 12 265 58 438

Net NOx Reduction 259 366 655 232 1,512

CO Uncontrolled (lb/day) 25,253 36,229 93,852 1,738 157,071

CO Reduction (lb/day) 25,360 17,677 65,696 1,216 109,949

CO from NG 87 10 222 - 319

Net CO Reduction 25,273 17,667 65,474 1,216 109,630

VOC Uncontrolled (lb/day) 44,191 7,487 18,731 4.37 70,410

VOC Reduction (lb/day) 5,241 30,934 13,112 3 49,287 

VOC from NG 6 1 15 3 21 

Net VOC Reduction 5,235 30,933 13,097 (0) 49,266

Stage 2 Compliance Rate
Option A1 or A2 - Single Stage 

Total Housing Units 502095 70%

Threshold 35 μg/m3Single Stage Days 31

Wood Burning Appliance Types Fireplace Stoves Inserts Pellet Stoves Total

% 31% 5% 16% 3.0% 55%

# total 155649 25105 80335 15063 276152

# total that burn 98059 15816 50611 9490 173976

# Phase II certified out of total that burn 6801 22775

# Catalytic out of the Phase II certified 1156 11388

Cords of fuel burned per winter day Nov-Feb 125 137 350

Tons of fuel burned Nov thru Feb (heat+asthetic) 23046 25246 64629

Tons PM2.5 Emissions from cord wood Nov-Feb 271.9

Manufactured logs burned per winter day Nov-Feb 2146

Tons Manufactured logs burned Nov thru Feb 644

Tons PM2.5 Emissions from logs Nov thru Feb 9.5

Total Fireplace Emissions Nov thru Feb 281.4

Cords of fuel burned per winter day (Nov-Feb) noncertified 78 192

Cords of fuel burned per winter day (Nov-Feb) certified 59 157

Tons of fuel burned Nov-Feb uncertified 14390 35546

Tons of fuel burned Nov-Feb Phase II - non cat 9010 24139

Tons of fuel burned Nov-Feb phase II - cat 1845 4944

Tons PM2.5 Emissions Nov-Feb from uncertified 220.2 543.8

Tons PM2.5 Emissions Nov-Feb from phase II 65.8 176.2

Tons PM2.5 Emissions Nov-Feb from phase II - catalytic 18.8 50.4

Total Stove Emissions Nov thru Feb 304.8 770.5

Tons fuel burned per winter pellet stove per day 109

Tons PM2.5 Emissions from Pellet Stove Nov thru Feb 20.1

$ amount of fuel used per winter day Nov thru Feb 33 $ 36,748 ,635 $ 94,075 $ 37,597 $ 202,055.77 $ 

$ amount of reduced fuel used per No Burn day Nov-Feb 23,545 $ 25,724 $ 65,853 $ 26,318 $ 141,439.04 $ 

PM2.5 Total Uncontrolled Emissions (lb/day) Nov-Feb 5,079 4,690 12,842 334 22,945

PM2.5 Total Reduction (lb/day) Nov-Feb 3,283 3,556 8,989 234 16,062

Percent Reduction per curtailment day 70.0% 70.0% 70.0% 70.0% 70.0%

Overall PM2.5 Cost Effectiveness ($/ton) $ 10,645.16

Overall PM2.5 Cost Effectiveness ($/lb) $ 5.32

NOx Uncontrolled (lb/day) 517 540 1,314 415 2,786 

NOx Reduction (lb/day) 378 362 920 291 1,950

NOx from NG 103 12 265 58 438

Net NOx Reduction 259 366 655 232 1,512

CO Uncontrolled (lb/day) 36,229 25,253 93,852 1,738 157,071

CO Reduction (lb/day) 17,677 25,360 65,696 1,216 109,949

CO from NG 87 10 222 - 319

Net CO Reduction 25,273 17,667 65,474 1,216 109,630

VOC Uncontrolled (lb/day) 7,487 44,191 18,731 4.37 70,410 

VOC Reduction (lb/day) 30,934 5,241 13,112 3 49,287

VOC from NG 6 1 15 3 21 

Net VOC Reduction 5,235 30,933 13,097 (0) 49,266

Stage 2 Compliance Rate
APPENDIX G 

ERG Final Report 

Socioeconomic Evaluation 
SOCIOECONOMIC IMPACT 

ANALYSIS FOR SMAQMD 

 RULE 421 AMENDMENT 

Final Report 

Sacramento Metropolitan 

 Air Quality Management District 

Program Coordination Division 

777 12th Street, 3rd Floor 

Sacramento, CA 95814

August 21, 2009
SOCIOECONOMIC IMPACT ANALYSIS 

FOR SMAQMD RULE 421 AMENDMENT 

Final Report 

Prepared for: 

Sacramento Metropolitan 

Air Quality Management District 

Program Coordination Division 

777 12th Street, 3rd Floor 

Sacramento, CA 95814 

Prepared by: 

Eastern Research Group, Inc. (ERG) 

8950 Cal Center Drive 

Suite 348 

Sacramento, CA 95826

August 21, 2009
Socioeconomic Impact Analysis - Rule 421 Amendment 

Final, August 21, 2009 

i

TABLE OF CONTENTS 

Section Page 

EXECUTIVE SUMMARY .............................................................................................................1

1.0 INTRODUCTION ...................................................................................................................3

2.0 OPTIONS AND QUANTITIES AFFECTED.........................................................................4

3.0 SUPPLIER INDUSTRIES ......................................................................................................4

3.1 Industry Characterization........................................................................................... 6 

3.1.1 Very Small Independents............................................................................... 7 

3.1.2 Small Independents—Primary Business........................................................ 7 

3.1.3 Small Independents—Secondary Business.................................................... 8 

3.1.4 Retailers—Wood Bundles ............................................................................. 9 

3.1.5 Manufactured Logs ...................................................................................... 10 

3.1.6 Pellets........................................................................................................... 11 

3.2 Potential Impacts...................................................................................................... 12 

3.2.1 Small Independents—Primary and Secondary Business ............................. 12 

3.2.2 Retail Stores................................................................................................. 15 

3.2.3 Manufactured Log Companies..................................................................... 18 

3.2.4 Pellet Manufacturers and Retailers .............................................................. 18

4.0 CONSUMERS.......................................................................................................................18

4.1 No Cost Increase Scenario....................................................................................... 18 

4.1.1 Residents...................................................................................................... 19 

4.2 Price Increase Scenario............................................................................................ 21 

4.2.1 Industries and Businesses ............................................................................ 21 

4.2.2 Residents...................................................................................................... 21

5.0 CONCLUSIONS ...................................................................................................................22

6.0 REFERENCES ......................................................................................................................24 

Tables Page 

ES1 Summary of Impacts on Wood Suppliers ............................................................................2 

1 Options and Fuel Quantities Affected..................................................................................5 

2 Small Independent Wood Dealers–Primary Business .........................................................7 

3 Small Independent Wood Dealers–Primary Business Revenues and Number 

 of Employees .......................................................................................................................7 

4 Small Independent Wood Dealers–Secondary Business .....................................................8 
Socioeconomic Impact Analysis - Rule 421 Amendment 

Final, August 21, 2009 

ii

TABLE OF CONTENTS - Continued 

5 Small Independent Wood Dealers–Secondary Business Revenues and Number 

 of Employees .......................................................................................................................9 

6 Retail Stores in Sacramento County Potentially Selling Wood Bundles...........................10 

7 Value of Wood, Manufactured Logs, and Pellets not Purchased ......................................13 

8 Upper Bound Potential Impacts on Independent Wood Dealers .......................................14 

9 Potential Impact on Retail Stores.......................................................................................17 

10 Increased Costs as a Percentage of Median Household Income for Households 

 that Burn Wood..................................................................................................................22 

11 Summary of Impacts on Wood Suppliers ..........................................................................23 

Figures Page 

1 Supplier Types for Wood and Other Solid Fuels.................................................................6 

2 Consumers of Wood and Other Solid Fuel: No Cost Increase Scenario ...........................19 
Socioeconomic Impact Analysis - Rule 421 Amendment 

Final, August 21, 2009 

1

EXECUTIVE SUMMARY 

Rule 421, Mandatory Episodic Curtailment of Wood and Other Fuel Burning, is being 

proposed for amendment. SMAQMD is considering four options for modifying the rule: 

• Recommended Option: Reduce Stage 1 threshold from 35 to 31 μg/m3

 and reduce 

Stage 2 threshold from 40 to 35 μg/m3. 

• Option A: Eliminate 2 stages; set no-burn threshold to 30 μg/m3, and either keep the 

voluntary threshold at 25 μg/m3 or reduce it to 20 μg/m3. 

• Option B: Reduce Stage 1 threshold to 25 μg/m3

, reduce Stage 2 threshold to 30 

μg/m3

, and reduce voluntary threshold to 20 μg/m3. 

• Contingency Option: Eliminate 2 stages; set no-burn threshold to 20 μg/m3

ERG—through information supplied by SMAQMD, Yellow Book searches, and Internet 

searches—identified independent wood dealers, manufactured log producers, pellet 

manufacturers, and retail stores potentially affected by the rule. ERG searched databases such as 

Dun & Bradstreet’s Million Dollar Directory and manta.com to identify revenues and the number 

of employees at each company or at their Sacramento County location(s). 

ERG evaluated the four options under two different economic scenarios (i.e., price 

increase or no price increase) and used worst case analyses to avoid the potential to 

underestimate costs. 

For residential consumers of wood and other solid fuels, SMAQMD has mitigated 

impacts on low income populations by including a hardship exemption. If suppliers raise prices 

to maintain revenues when sales volumes decline, the estimated price increase is less than onequarter of one percent (<0.25 percent) of the 2007 median household income for Sacramento 

County. 

For commercial consumers of wood and other solid fuels (e.g. restaurants and lodgings), 

burning is discretionary. If suppliers raise prices, each business is anticipated to weigh the 

increased price against the perceived benefit to the business’s ambience to determine whether or 

not to pay the increased prices. No employment losses are anticipated in this sector as a result of 

the rule amendment. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

Final, August 21, 2009 

2

 Impacts to wood and solid fuel suppliers are summarized in Table ES1. If the suppliers 

are able to raise prices to compensate for lower sales volumes, there are no impacts under any of 

the options. If suppliers are unable to raise prices, then small impacts might occur. 

 Impacts on retailers are negligible. 

Table ES1. Summary of Impacts on Wood Suppliers

Scenario and 

Potential 

Impact Option 

Independent 

Wood Dealers

Manufactured 

Log 

Producers 

Retail 

Stores 

Wood Stove 

and Pellet 

Retailer 

Price Increase 

Potential Loss in Revenues 

 

Recommended 

Option 0% 0% 0% 0%

 Option A 0% 0% 0% 0%

 Option B 0% 0% 0% 0%

 Contingency Option 0% 0% 0% 0%

Potential Loss in Employment 

 

Recommended 

Option 0 0 0 0

 Option A 0 0 0 0

 Option B 0 0 0 0

 Contingency Option 0 0 0 0

No Price Increase 

Potential Loss in Revenues 

 

Recommended 

Option 4.6% 0.5% 0.01% 0.01%

 Option A 8.7% 0.8% 0.03% 0.03%

 Option B 14.0% 1.8% 0.04% 0.04%

 Contingency Option 34.1% 3.8% 0.10% 0.10%

Potential Loss in Employment 

 

Recommended 

Option 2.8 1.2 0 0

 Option A 5.3 2.1 0 0

 Option B 8.5 4.4 0 0

 Contingency Option 20.6 9.4 0 0

The results reported in Table ES1 are based on worst case analyses, which incorporate 

such assumptions as: 

• No independent wood dealers located outside of Sacramento County sell wood within 

Sacramento County. If such dealers exist, the impacts would be reduced 

proportionately by the fraction of wood sold in Sacramento Country by extra-county 

dealers. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

Final, August 21, 2009 

3

• All impacts from reduced sale of manufactured logs are absorbed by the one 

manufactured log producer that is headquartered in California. In reality, the impacts 

would reflect that company’s market share of manufactured log sales in Sacramento 

County. 

1.0 INTRODUCTION 

Rule 421, Mandatory Episodic Curtailment of Wood and Other Fuel Burning, is being 

proposed for amendment. Under the current regulation, a Stage 1 “no-burn day” prohibits 

burning except in EPA certified wood devices or pellet devices. A Stage 2 no-burn day prohibits 

all burning. The rule does not apply to fireplaces and devices that burn gaseous fuels (natural gas 

or propane). The rule exempts burning that is the sole source of heat or in situations when not 

burning would be a financial hardship to a resident. 

Sacramento County exceeds state or federal health standards for fine particle air pollution 

(PM2.5). The burning of wood or other solid fuel constitutes the single largest source of fine 

particle emissions for this region during the wintertime. As a result, SMAQMD is considering 

four options for modifying the rule: 

• Recommended Option: Reduce Stage 1 threshold from 35 to 31 μg/m3 and reduce 

Stage 2 threshold from 40 to 35 μg/m3. 

• Option A: Eliminate 2 stages; set no-burn threshold to 30 μg/m3

, and either keep the 

voluntary threshold at 25 μg/m3 or reduce it to 20 μg/m3. 

• Option B: Reduce Stage 1 threshold to 25 μg/m3, reduce Stage 2 threshold to 30 

μg/m3, and reduce voluntary threshold to 20 μg/m3. 

• Contingency Option: Eliminate 2 stages; set no-burn threshold to 20 μg/m3

 Section 2.0 of this report describes the quantities of wood, manufactured logs, and pellets 

that would not be burned pursuant to a no-burn day, examines the change in the number of Stage 

1 and Stage 2 no-burn days under each option, and estimates the annual quantities of fuel not 

burned for each option. 

The proposed amendments have the potential to affect both the businesses which supply 

the fuel as well as the residents that consume the fuel. Section 3.0 describes the suppliers, the 

steps taken to identify the potentially affected industry sectors and prices, and estimates the 

potential impact of the options. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

Final, August 21, 2009 

4

Section 4.0 of this report describes the consumers potentially affected by the changes. 

Section 5.0 of this report summarizes conclusions regarding the four options evaluated. 

This socioeconomic analysis uses two bounding assumptions to study the suppliers and 

consumers. The first scenario is that suppliers are not able to raise prices. This scenario 

maximizes the potential impacts on the suppliers but minimizes them for the consumers. The 

second scenario is that suppliers are able to maintain their income by raising prices. The second 

scenario minimizes impacts on suppliers but maximizes them for consumers. What is likely to 

happen lies in the middle of the findings. There are also places where “worst case” assumptions 

are made in order not to underestimate potential impacts. These are noted throughout the report. 

2.0 OPTIONS AND QUANTITIES AFFECTED 

Table 1 summarizes the estimated quantities of fuel not burned and not purchased under 

each of the three options plus the contingency option. The fuel categories are firewood, 

manufactured logs, and pellets. For each fuel source, SMAQMD has estimated a range in the 

quantity not burned during a Stage 1 and Stage 2 no-burn day. For each of the options, 

SMAQMD calculated the change in the number of Stage 1 and Stage 2 burn days. For example, 

Option A is considered to result in 15 more Stage 2 days and 7 fewer Stage 1 days for a net 

increase of 8 no-burn days. 

Table 1 also provides estimates of the changes by type of wood product. For example, 

pellets are affected only by the change in the number of Stage 2 no-burn days, while firewood 

may or may not be purchased; the economic analysis is structured to address this possibility. 

 3.0 SUPPLIER INDUSTRIES 

Section 3.1 describes the characteristics of the fuel suppliers while Section 3.2 examines 

the potential impacts of the Rule 421 options on these groups. 
Socioeconomic Impact Analysis – Rule 421 Amendment 5

Final, August 21, 2009 Table 1. Options and Fuel Quantities Affected Change in Number of No Burn Days Products Not Product

Burned Per Day Recommended Option Option A Option B Contingency Option 

Products Units 

Stage 

1 

Stage 

2 

Stage 

1 

Stage 

2 

Stage 

1 

Stage 

2 

Stage 

1 

Stage 

2 

Stage 

1 

Stage 

2 

Recommended 

Option 

Opt

A 

Wood cord 225 428 -2 7 -7 15 6 15 -7 48 2,546 4Manufactured Fire Logs log 1,223 1,502 -2 7 -7 15 6 15 -7 48 8,068 13Pellets ton 0 77 -2 7 -7 15 6 15 -7 48 539 1

Quantity Not Purchased 

Products Units 

Percent 

Purchased 

Recommended 

Option 

Option 

A 

Option 

B 

Contingency 

Option 

Wood cord 51.4% 1,309 2,490 3,994 9,750 Manufactured Fire Logs log 100.0% 8,068 13,969 29,868 63,535 Pellets ton 100.0% 539 1,155 1,155 3,696 

Sources: SMAQMD, 2009; Williams, 2009; and Houck, 2003.
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

6

3.1 Industry Characterization 

ERG identified six types of fuel suppliers that could potentially be affected by the 

amendments to Rule 421 (See Figure 1). Consumers can purchase wood from local dealers 

whether they are individuals (“very small independents”) or small independent companies as a 

primary or secondary line of business. These three types of fuel suppliers conduct their business 

directly with the consumer and tend to sell in units of cords or fractions of cords. Thus, any price 

increase by these suppliers is borne directly by the consumer and, conversely, any reduction in 

fuel demand affects the suppliers’ revenues. 

Figure 1. Supplier Types for Wood and Other Solid Fuels 

Suppliers

Very Small

Independents

Small

Independents

Non-Local

Manufactured Logs

Pellets

Primary Business

Secondary Business

Retailer

Retailer

Retailer

Consumers

Consumers

Consumers

Consumers

Consumers

Consumers

Consumers might purchase wood or other solid fuel from retailers, such as local grocery 

or hardware stores. The fuel might take the form of wood bundles, manufactured logs, or pellets. 

For these supply chains, impacts might fall on manufacturers (if located in Sacramento County), 

retailers, and consumers. Section 3.1 describes the characteristics of the fuel suppliers while 

Section 3.2 examines the potential impacts of the Rule 421 options on these groups. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

7

3.1.1 Very Small Independents 

ERG examined craigslist and Penny Saver to locate what we term “very small 

independents.” These appear to be individuals that sell small quantities of firewood as a source 

of secondary income. Addition information (e.g., sales location, financial information, or even 

primary income source) for this sector could not be located. Thus, although we found about 25 

individuals in this sector, we cannot estimate impacts except to say that, as a group they form a 

very small part of the supply, so it is likely that, as a group, they would incur a proportionally 

very small part of the impacts.

3.1.2 Small Independents—Primary Business 

Based on information provided by SMAQMD, and through local Yellow Pages and 

Internet searches, ERG identified eight businesses that sell firewood as a primary business (See 

Table 2). Of the eight businesses, ERG found information on the annual revenues and number of 

employees for seven of them. Annual revenues ranged from $58,000 to $800,000 while the number 

of employees ranged from 1 to 12 (See Table 3). 

Table 2. Small Independent Wood Dealers—Primary Business

Company Name 

Hillerman Farms N.P.C. Firewood 

Hurd's Firewood Pak & Save Firewood 

M&M Firewood Tony's Firewood 

Muschetto's Firewood LLC Turner's Firewood Service 

Table 3. Small Independent Wood Dealers—Primary Business Revenues and 

Number of Employees 

Parameter Annual Revenues Employees 

Minimum $58,000 1 

Maximum $800,000 12 

Average $474,321 4 

Imputed total $3,794,571 35 

ERG computed the average revenues and number of employees (roughly $474,300 and 4 

employees, respectively) and used the average values for the business for which no information 

could be found. With this imputation, we calculated that the small independent wood dealers in 

Sacramento County represent 35 jobs and about $3.8 million in annual revenue. All of the 

businesses in Table 2 are small businesses. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

8

These businesses are listed with one of two NAICS codes: 423990 or 454319. NAICS 

423990 is Other Miscellaneous Durable Goods Merchant Wholesalers. Although firewood 

merchant wholesalers are part of NAICS 423990, so are merchant dealers for prerecorded DVDs 

CDs, audio tapes, coin-operated games, musical instruments and accessories, luggage, and other 

miscellaneous durable goods. Thus, the Census data contained under this NAICS code includes 

information for a wide variety of other goods. NAICS 454319 encompasses only firewood and 

coal dealers that sell directly to the public. According to the 2007 County Business Patterns

(most current available), 5 establishments for NAICS code 454319 and 30 establishments for the 

wider ranging NAICS 423990 are located in Sacramento County (Census, 2009a). 

ERG called these wood dealers for prices per cord of wood, and determined that the 

average price is $301/cord. Wood dealers reported selling almond, cedar, cherry, eucalyptus, 

oak, peach, pine, and walnut. The wood dealers also supplied descriptors such as "semi-dry" and 

"dry" and generic labels such as "hardwood" and "mixed hardwood." 

3.1.3 Small Independents—Secondary Business 

 Based on information provided by SMAQMD, and through local Yellow Pages and 

Internet searches, eight businesses sell firewood as a secondary business (See Table 4). That is, 

these businesses do landscaping, tree pruning, and similar activities. Rather than disposing of the 

wood that is cut during the course of their primary business, these companies sell the firewood as 

a secondary income. Of the eight businesses, ERG found information on the annual revenues and 

number of employees for six. Annual revenues ranged from $48,000 to $820,000 while the 

number of employees ranged from 1 to 8 (See Table 5). 

Table 4. Small Independent Wood Dealers—Secondary Business 

Company Name 

A-1 Rock & Materials 

Bill's Firewood and Tree Service 

Bill's Urban Forest Mgmt. 

Foothill's Firewood & Christmas Trees 

Jaime Santos Tree Service 

Longer Decorative Rock & Ready Mix 

Premier Landscaping 

Tree Pros Incorporated 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

9

 Table 5. Small Independent Wood Dealers—Secondary Business Revenues 

and Number of Employees 

Parameter Annual Revenues Employees 

Minimum $48,000 1 

Maximum $819,000 8 

Average $486,167 3 

Imputed total $3,889,333 25 

 ERG computed the average revenues and number of employees (roughly $486,000 and 

three employees respectively) and used the average values for the business for which no 

information could be found. With this imputation, ERG calculated that the small independent 

wood dealers in Sacramento County represent 25 jobs and nearly $3.9 million in revenue. All 

businesses listed in Table 4 are small businesses. 

Consistent with the idea that selling firewood is a secondary business for these 

companies, most of them are listed with a different set of NAICS codes: 

• 236210: Industrial Building Construction 

• 444220: Nursery and Garden Centers 

• 453998: All Other Miscellaneous Store Retailers 

• 454319: Other Fuel Dealers 

• 541320: Landscape Architectural Services 

• 561730: Landscaping Services 

Census data, then, would contain information on a variety of activities other than selling 

firewood. ERG called these wood dealers for prices per cord of wood. The average price is 

$237/cord. The species provided by the dealers are the same as mentioned in Section 3.1.2.

3.1.4 Retailers—Wood Bundles 

Through local Yellow Pages and Internet searches, ERG compiled a list of retail stores and 

verified that each retailer operated a store in Sacramento County. Table 6 is the resultant list of 25 

retail stores that might sell wood bundles. 
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August 21, 2009 

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Table 6. Retail Stores in Sacramento County Potentially Selling Wood Bundles

Company

Ace Hardware 7-Eleven 

The Home Depot Beverages & More 

Lowe's Food Maxx 

CVS Food Source 

Costco Foods Co. 

Safeway Raley's 

Kmart Bel Air 

Michaels Nugget Market 

Orchard Supply Hardware Pitco 

Rite Aid Save Mart Supermarkets 

Sam's Club Smart & Final 

Target Winco Foods 

Wal-mart 

 ERG called each of the businesses to ask if they sold firewood and, if so, who supplied the 

firewood. Of the 25 businesses: 

• 7 of them did not sell firewood 

• 9 knew their firewood supplier 

• 9 did not know their firewood supplier 

All nine businesses that knew their firewood supplier also knew that the supplier was an 

outside company and not a local wood dealer. Four brands/companies were specifically 

mentioned: California Hotwood, CalOak Firewood, Lazzari Fuel and Best of the West. The first 

three businesses are located in neighboring counties (Stanislaus, San Mateo, and Butte, 

respectively). Best of the West appears to be a brand sold only by Smart & Final which is 

headquartered in Los Angeles. Thus, to estimate impacts on Sacramento County, the retailers, 

but not the companies that supply them, need to be considered. 

3.1.5 Manufactured Logs 

ERG identified four manufactured log companies whose products are sold in Sacramento 

County (and elsewhere in California and other states): 

• Duraflame, Inc., headquartered in Stockton, CA 

• Enviro-Log, headquartered in Fitzgerald, GA 

• Landmann USA, headquartered in Cartersville, GA 

• Jarden Corporation, headquartered in Daleville, IN 
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August 21, 2009 

11

Jarden Corporation manufactures Java Log, Northland, Pine Mountain, and Starter Logg 

through its Branded Consumables segment.1

 For 2008, the Branded Consumables segment 

reported $805 million in net sales while Jarden Corporation reported $5,383 million (Jarden, 

2008). 

Duraflame is the only company that has its principal office in California. However, as a 

company, it reports having approximately 250 employees. This exceeds the state small business 

size standard of 100 employees. 

As shown above, Landmann USA and Enviro-Log are not headquartered in California; 

therefore, none of the four producers of manufactured logs meet the definition of a California 

small business. 

ERG obtained 24 price estimates for manufactured logs. These ranged from roughly 

$2.20/log to $7.51/log with an average of $4.91/log. For calculating the estimated costs, ERG 

rounded this value to $5.00/log. 

3.1.6 Pellets 

ERG searched www.woodpelletprice.com and http://www.pelletheat.org/3/residential/ 

fuelAvailability.cfm#west to identify North American wood pellet retailers and manufacturers. 

ERG then looked at each supplier’s website to see if they delivered to Sacramento County and 

compiled a list of manufacturers and retailers. The manufacturers include: 

• Bear Mountain Forest Products Inc., headquartered in Portland, OR 

• West Oregon Wood Products, headquartered in Columbia City, OR 

• Rocky Mountain Pellet Company, Inc., headquartered in Walden, CO, and 

• Traeger Pellet Grills, LLC., headquartered in Silverton, OR. 

None of these businesses meet the definition of a California small business because none 

are headquartered in the state. 

 

1

 American Fire Log is co-located with the Pine Mountain Corporation address; thus it is likely to be another brand name 

manufactured by Jarden Corporation even though it is not specifically mentioned in Jarden Corporation’s 10-K form for 2008. 

(Jarden, 2008.) 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

12

ERG identified a wood stove retailer—a California small business—that also sold pellets. 

ERG located the private company in manta.com which reported annual company revenues were 

in the range of $2.5 million to $5 million. In addition, major retailers such as Home Depot and 

Lowe’s also sell pellets. ERG found pellet prices of about $7.49 per 40-lb bag for local nonchain retailers and $6.27 per 40-lb bag for local chain stores (e.g., Lowe’s). ERG used a midpoint value of $6.88 per bag to calculate a cost of $344/ton. 

3.2 Potential Impacts 

 Table 7 lists the quantity of fuel not purchased (from Table 1) with the average prices by 

fuel type as of summer 2009. ERG could not identify the relative market share for very small 

independents, small independents for which selling wood is a primary business, or small 

independents for which selling wood is a secondary business. As a result, Table 7 calculates the 

value of wood not sold based on a price of $269/cord—the mid-point between the prices for 

primary and secondary wood dealers. The cost of the recommended Option is approximately 

$0.6 million, and the estimated costs for Option A, Option B, and the Contingency Option are 

$1.1 million, $1.6 million, and $4.2 million, respectively. The potential impacts of these lost 

sales are examined by industry sector. 

3.2.1 Small Independents—Primary and Secondary Business 

ERG examined impacts on small independent wood dealers under two scenarios. The 

first scenario assumed that wood dealers are not able to raise prices to maintain their income 

while selling a smaller quantity of wood. The second scenario examined the price increase that 

would offset the smaller quantity of wood sold.

No Price Increase 

 For the purpose of examining the upper bound of impacts (worst case) on these small 

businesses, ERG assumed that the total loss in the value of wood sales was borne entirely by 

independent wood dealers in Sacramento County. In addition, the dealers are assumed to be 

unable to recoup any income by raising prices. (In this scenario, no impacts are borne by 

consumers because there are no price increases.) 
Socioeconomic Impact Analysis – Rule 421 Amendment 13

Final, August 21, 2009 Table 7. Value of Wood, Manufactured Logs, and Pellets Not Purchased Quantity Not Purchased Value Not Purc

Products Units Recommended Option Option A Option B Contingency Option Cost Per Unit Recommended Option Option A OWood cord 1,309 2,490 3,994 9,750 $269 $352,025 $669,899 $1Manufactured Fire Logs log 8,068 13,969 29,868 63,535 $5 $40,340 $69,845 $Pellets ton 539 1,155 1,155 3,696 $344 $185,416 $397,320 Aggregate Cost $577,781 $1,137,064 $1
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

14

Table 8 shows the impacts on wood dealers under a no-price increase scenario. The value 

of wood not purchased is estimated at $0.35 million (Recommended Option), $0.67 million 

(Option A), $1.07 million (Option B), and $2.62 million (Contingency Option). The total 

revenue for independent wood dealers in Sacramento County is approximately $7.68 million (see 

Tables 3 and 5). Thus, the lost value is about: 

• 4.6 percent of revenues for the Recommended Option 

• 8.7 percent of revenues for Option A 

• 14.0 percent of revenues for Option B 

• 34.1 percent of revenues for the Contingency Option. 

Table 8. Upper Bound Potential Impacts on Independent Wood Dealers 

Value Not Purchased 

Parameter 

Recommended 

Option Option A Option B 

Contingency 

Option 

Value Not Purchased $352,025 $669,899 $1,074,327 $2,622,768 

Group Revenues $7,683,905 $7,683,905 $7,683,905 $7,683,905

Percent of Group Revenues 4.6% 8.7% 14.0% 34.1%

Group Employment 60 60 60 60

Upper Bound Estimate of 

Employment Loss 2.8 5.3 8.5 20.6

Sacramento County (May 2009) 

Labor Force 687,758 687,758 687,758 687,758

Employment 610,444 610,444 610,444 610,444

Unemployment rate 11.2% 11.2% 11.2% 11.2%

Unemployment rate after option 11.2% 11.2% 11.2% 11.2%

Change due to option 0.0% 0.0% 0.0% 0.0%

Source: Tables 3, 5, and 7; BLS, 2009. 

ERG assumed that a small business might react by laying off workers in response to 

lower revenues and that this reaction would be proportional to the loss in income incurred as a 

result of an increase in no-burn days. As a group, independent wood dealers employ 

approximately 60 people in Sacramento County (See Tables 3 and 5). Thus, the potential loss in 

jobs might be about 3 for the Recommended Option, 5 for Option A, 8 to 9 for Option B, and 

nearly 21 for the Contingency Option. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

15

ERG examined local area unemployment statistics for Sacramento County as of May 

2009 (BLS, 2009). The local unemployment rate would not change significantly under any of the 

options considered. 

As mentioned above, these impacts are calculated with the assumption that all impacts 

fall only on independent wood dealers in Sacramento County. If there are wood dealers in 

neighboring counties that sell wood in Sacramento County, then the potential loss in the value of 

wood not sold would be spread across a larger group of companies with a proportional decrease 

in the impact. 

Price Increase 

The wood dealers could potentially raise prices to recoup the lost value of wood not sold 

due to increased no-burn days. Table 8 indicates that price increases of approximately 5 percent 

would mitigate any revenue losses from reduced wood sales under the Recommended Option. 

For Options A and B, price increases between 9 and 14 percent would offset a lower volume of 

sales. Under the Contingency Option, a price increase of 34 percent would mitigate impacts on 

the wood dealers. In this scenario, impacts are borne by the consumers and not the wood dealers. 

3.2.2 Retail Stores 

Retail stores might sell firewood, manufactured logs, and/or pellets. For the analysis of 

this sector, ERG made the worst case assumption that the entire cost of the option for all fuel 

sources is borne by retail stores. (If this were accurate, there would be no impacts on 

independent fuel dealers, or manufacturers of pellets and logs.) 

For retail stores, we examined the percentage loss in revenue as a measure of impacts 

because we did not know the profit made on each unit.2

 The San Joaquin Valley Unified Air 

Pollution Control District (SJVUAPCD, 2008) used net profit rates in its analysis. But because 

we would need to assume that the profit rates are comparable across all items sold, the 

percentage of revenues and the percentage of profits lost would be the same. 

 

2

 SJVUAPCD (2008), Appendix C, Table 7 compares the value of lost sales to the estimated net profits by type of retailer. This 

is akin to saying that firewood sales are all profit (i.e., there are no wholesale costs or operating costs). 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

16

Table 9 summarizes the analysis. First, ERG started with the taxable transactions at retail 

stores in California for fiscal year 2007-2008 (California, 2009 [Table 19]) for general 

merchandise stores, drug stores, food stores, and building material retail stores. These types of 

retail stores accounted for $112 billion in sales. In order to analyze the potential effects of the 

options on the wood stove retailers that also sold wood pellets (see Section 3.1.6), ERG added a 

column for the retailer type, entered the mid-point value for the revenues, and scaled the reported 

revenues for the other types of retailers to keep the same value of total sales.3

Second, ERG multiplied the taxable transactions by the percentage of retail sales in 

Sacramento County (California, 2009 [Table 20]) for retail types other than wood stove and 

pellet retailers. Because the revenues represent sales to Sacramento retailers, 100 percent of the 

revenues are from wood stove and pellet retailers. 

 The distribution of firewood and solid fuel sales among types of retail stores is taken 

from SJVUAPCD (2008). ERG summed the entries for lumber/building materials and hardware 

stores because California (2009) did not provide a separate line entry for hardware stores. ERG 

calculated the percentage of Sacramento sales represented by wood stove and pellet retailers, and 

scaled the SJVUAPCD distribution of firewood and solid fuel sales to accommodate the 

additional type of retailer. 

 The block of entries labeled “Value of Lost Sales” in Table 9 is the prorated cost of an 

option for that type of retail store. Note that the entries listed in the Total column correspond to 

the estimated option costs in Table 7. The block of entries labeled “Percentage of Lost Sales” is 

the percentage that these costs comprise of store revenues. Under the Recommended Option, the 

estimated fraction of lost sales does not exceed 0.03 percent for any type of retail store. Under 

Options A and B, estimated fraction of lost sales does not exceed 0.08 percent. Even under the 

Contingency Option, the costs comprise less than 0.25 percent of total revenues for any type of 

retail store. It is unlikely that such small percentages in lost revenue would lead to any job losses. 

 

3

 ERG multiplied the revenues for each retailer type by (1- ($3.75 million/$112 billion)) or 0.999967, the fraction of California 

revenues from these retailer types represented by the wood stove and pellet dealer. 
Socioeconomic Impact Analysis – Rule 421 Amendment 17

Final, August 21, 2009 Table 9. Potential Impact on Retail Stores Parameter General Merchandise Stores Drug Stores Food Stores Lumber/ Building Materials* Stove And Pell

Retailers in Sacramento County 

State Sales $52,709,151,410 $6,560,470,618 $22,883,207,787 $29,988,589,184 $3,750,0Sacramento Fraction of State Sales 3.63% 3.63% 3.63% 3.63% 100.00Estimated Sacramento Sales $1,913,342,196 $238,145,083 $830,660,443 $1,088,585,787 $3,750,0Firewood Sales by Retail Store Type 29.2% 9.6% 41.0% 20.2% 0.1Value of Lost Sales Recommended Option $168,557 $55,416 $236,672 $116,604 $5Option A $331,717 $109,058 $465,767 $229,475 $1,0Option B $472,892 $155,471 $663,992 $327,138 $1,4Contingency Option $1,228,732 $403,967 $1,725,275 $850,013 $3,8Percentage of Lost Sales Recommended Option 0.01% 0.02% 0.03% 0.01% 0.01Option A 0.02% 0.05% 0.06% 0.02% 0.03Option B 0.02% 0.07% 0.08% 0.03% 0.04Contingency Option 0.06% 0.17% 0.21% 0.08% 0.10

Source: California, 2009, SJVUAPCD (2008), and manta.com. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

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 ERG further examined the potential impact on wood stove and pellet dealers in 

Sacramento. The estimated losses in pellet sales (rather than all revenues) are less than one-half 

of one percent (<0.05 percent) for the Recommended Option, less than 1.25 percent for Options 

A and B, and approximately 3.2 percent for the Contingency Option. Job losses are not 

anticipated with these small changes in revenue. 

3.2.3 Manufactured Log Companies 

There are no manufactured log companies within Sacramento County but Duraflame is 

headquartered in nearby Stockton, CA. Annual revenues for Duraflame are available through 

Dun & Bradstreet’s Million Dollar Directory. ERG examined the impacts under the worst-case

assumption that Duraflame bore the entire loss of value from manufactured logs (i.e., no 

impacts to Enviro-Log, Landmann USA, and Jarden Corporation). The estimated losses 

represent: 

• 0.5 percent of total revenues or less for the Recommended Option 

• 0.8 percent of total revenues or less for Option A, 

• 1.8 percent of total revenues or less for Option B, and 

• 3.8 percent of total revenues or less for the Contingency Option. 

The associated potential loss in employment would be 1.2, 2.1, 4.4, or 9.4 jobs under the 

Recommended Option, Option A, Option B, and the Contingency Option, respectively. The 

actual loss in revenues or employment would be much less than shown above, and would be 

prorated by the proportion of Duraflame’s revenues represented by sales in Sacramento County, 

compared to the other manufacturers. 

3.2.4 Pellet Manufacturers and Retailers 

ERG did not identify any pellet manufacturers within Sacramento County. (See Section 

3.2.2 for impacts of lost sales to wood stove and pellet retailers in Sacramento County.) 

4.0 CONSUMERS 

4.1 No Cost Increase Scenario 

The economic impact analysis for the consumers is illustrated in the logic flowchart in 

Figure 2. In this scenario, the suppliers are assumed to be unable to raise prices. Wood and other 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

19

solid fuels might be burned for two reasons: ambience (which is discretionary), and heat (which 

is not discretionary). 

Figure 2. Consumers of Wood and Other Solid Fuel: No Cost Increase Scenario

Wood-Burning

Ambience Heat

Commercial Residential

Cost

savings

due to

burning

less wood

Cost

savings

due to

burning

less wood

Residential

Increased Cost for

Alternate Heat

Source

Exemption

Applies

Alternate Source

is Less Expensive

(Cost Savings)

Alternate Heating

Source?

No

Pay for Wood?

Yes

No Hardship? No

Yes

Yes

Exemption

Applies

4.1.1 Residents 

If residents burn wood or other solid fuels only for ambience, then they would realize a 

cost savings due to reduced wood use. 

If residents burn wood or other fuels for heat, SMAQMD has structured the regulation to 

mitigate economic impacts, particularly the impacts on low-income residents. For these 

residents, impacts differ based on whether or not they have an alternate source of heat.4

Residents with no alternate source of heat are exempt from Rule 421. Low-income residents may 

qualify for an exemption based on economic hardship. 

 

4

 A telephone survey conducted in April 2009 for SMAQMD found no respondents that indicated wood burning as their sole 

source of heat (SMAQMD, 2009). Although uncommon, there may be rare cases where burning wood or other solid fuel would 

be the only heat source. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

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For consumers with alternate heat sources, the potential impacts differ according to the 

following scenarios: 

• Pay for wood, wood used for central heating 

• Pay for wood, wood used for zonal heating 

• Do not pay for wood 

 SMAQMD (2009) examined the relative costs of heating by fireplace, certified wood 

stove, electricity, and natural gas and found that heating with wood was the most expensive. For 

consumers that pay for wood and use it to heat the entire living space (“central heating”), these 

consumers will realize cost savings due to switching to a lower cost source of heat. 

 Wood can be used to heat a room while leaving other rooms unheated (“zonal heating”). 

Consumers that fall into this scenario might see an increase in costs due to the change from 

heating one room with wood to heating all rooms by central heating. ERG could not locate data 

to quantify these relative costs and thus could not quantify the potential impacts for this scenario. 

In this scenario, if the consumer incurs a financial hardship, the exemption would apply. 

If, however, the consumers did not pay for wood, they would incur the costs of the 

alternative heat source for the additional no-burn days. The average cost of heating a home for 

30 days is $153 for electricity and $88 for natural gas. The average per-day costs to heat a home 

are $5.10 and $2.93 for electricity and natural gas respectively (SMAQMD, 2009). The 

incremental numbers of no-burn days for which the consumers would have to pay for heat by 

Option are: 

• Recommended Option: 5 additional no-burn days for a cost between $15 to $25 

• Option A: 8 additional no-burn days for a cost between $23 to $41 

• Option B: 21 additional no-burn days for a cost between $62 to $107 

• Contingency Option: 41 additional no-burn days for a cost between $120 to $209 

In 2007, the median household income for Sacramento County was $56,283 (Census, 

2009b). The increased costs do not exceed 0.05 percent of household income for the 

Recommended Option, 0.07 percent for Option A, 0.19 percent for Option B, or 0.37 percent for 

the Contingency Option regardless of whether the household heats with electricity or natural gas. 
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August 21, 2009 

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The typical household would not be disproportionately impacted by the cost for using an 

alternative source of heat. If this is not the case, however, the resident can apply for an 

exemption based on economic hardship. 

4.2 Price Increase Scenario 

In this scenario, fuel suppliers are able to raise prices to maintain their income while 

selling less wood and other solid fuels, and consumers would bear the increased costs. Table 8 

indicates that lost value to wood dealers is about: 

• 4.6 percent of revenues for the Recommended Option 

• 8.7 percent of revenues for Option A 

• 14.0 percent of revenues for Option B 

• 34.1 percent of revenues for the Contingency Option 

Assuming that wood sales comprise the sole source of income, as is likely for independent 

primary wood dealers, the companies could maintain their income with price increases of 4.6 

percent for the Recommended Option, 8.7 percent under Option, 14 percent under Option B, and 

34 percent under the Contingency Option. Given the findings in Sections 3.2.2, retailer prices for 

manufactured logs and pellets are unlikely to increase by more than a negligible amount. 

4.2.1 Industries and Businesses 

As shown in Figure 2, industries and businesses such as restaurants and hotel lobbies 

might burn wood and other solid fuels for ambience. Thus, burning is discretionary for these 

commercial entities. If no cost increase occurs, industries and businesses might see a cost savings 

due to reduced fuel use. If a cost increase occurs, we anticipate that each location would evaluate 

the price increase with respect to the (typically non-monetized) benefit of “ambience” or 

increased prices to consumers, and would decide whether to pay the higher prices or reduce the 

amount burned. ERG anticipates no employment losses as a result of increased prices for a 

discretionary business practice. 

4.2.2 Residents 

Houck (2003) surveyed wood burning pattern for households in the Sacramento area. He 

found that households with fireplaces burned an average of 0.92 cords per season while those 

with stoves burned an average of 1.5 cords per season. ERG calculated the amount a household 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

22

spent on wood, recalculated the amount spent after small independent wood dealers increased 

their prices to maintain income levels under the new regulation, and then calculated the increased 

cost to the consumer. 

The calculations are shown in Table 10. The price increases range from $11/season to 

$138/season depending on the option and whether the household used a fireplace or stove. ERG 

compared the cost increases to Sacramento County 2007 median household income ($56,283; 

Census, 2009b). The cost increases do not exceed one-quarter of one percent of median 

household income. 

Table 10. Increased Costs as a Percentage of Median Household Income for 

Households that Burn Wood 

 Households that Burn Wood 

Parameter Fireplace Stove 

Amount burned per season (cords) 0.92 1.5 

Price ($/cord) $269 $269 

Cost per Season $247 $404 

Estimated Price Increase 

Recommended Option 4.6% 4.6% 

Option A 8.7% 8.7% 

Option B 14.0% 14.0% 

Contingency Option 34.1% 34.1% 

New Cost Per Season 

Recommended Option $259 $422 

Option A $269 $439 

Option B $282 $460 

Contingency Option $332 $541 

Incremental Cost 

Recommended Option $11 $18 

Option A $22 $35 

Option B $35 $56 

Contingency Option $84 $138 

Percent of 2007 Median Income 

Recommended Option 0.02% 0.03% 

Option A 0.04% 0.06% 

Option B 0.06% 0.10% 

Contingency Option 0.15% 0.24% 

5.0 CONCLUSIONS 

ERG evaluated four options under two different economic scenarios (price increase or no 

price increase) and used worst case analyses to avoid the potential to underestimate costs. 
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

23

For residential consumers of wood and other solid fuels, SMAQMD has mitigated impacts 

on low income populations through a hardship exemption. If suppliers raise prices to maintain 

revenues when sales volumes decline, the estimated price increased are less than one-quarter of one 

percent (<0.25 percent) of the 2007 median household income for Sacramento County. 

For commercial consumers of wood and other solid fuels (e.g. restaurants and lodgings), 

burning is discretionary. If suppliers raise prices, each business is anticipated to weigh the increased 

price against the perceived benefit to the business’s ambience to determine whether or not to pay the 

increased prices. No employment losses are anticipated in this sector as a result of the rule. 

 Impacts to wood and solid fuel suppliers are summarized in Table 11. If the suppliers are 

able to raise prices to compensate for lower sales volumes, there are no impacts under any of the 

options. If suppliers are unable to raise prices, then small impacts might occur. 

Table 11. Summary of Impacts on Wood Suppliers

Scenario and 

Potential Impact Option 

Independent 

Wood Dealers 

Manufactured 

Log Producers 

Retail 

Stores 

Wood Stove and 

Pellet Retailer 

Price Increase 

Potential Loss in Revenues 

 Recommended Option 0% 0% 0% 0%

 Option A 0% 0% 0% 0%

 Option B 0% 0% 0% 0%

 Contingency Option 0% 0% 0% 0%

Potential Loss in Employment 

 Recommended Option 0 0 0 0

 Option A 0 0 0 0

 Option B 0 0 0 0

 Contingency Option 0 0 0 0

No Price Increase 

Potential Loss in Revenues 

 Recommended Option 4.6% 0.5% 0.01% 0.01%

 Option A 8.7% 0.8% 0.03% 0.03%

 Option B 14.0% 1.8% 0.04% 0.04%

 Contingency Option 34.1% 3.8% 0.10% 0.10%

Potential Loss in Employment 

 Recommended Option 2.8 1.2 0 0

 Option A 5.3 2.1 0 0

 Option B 8.5 4.4 0 0

 Contingency Option 20.6 9.4 0 0

 

Impacts on retailers are negligible.
Socioeconomic Impact Analysis - Rule 421 Amendment 

August 21, 2009 

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The results reported in Table 11 are based on worst case analyses which incorporate such 

assumptions as: 

• No independent wood dealers located outside of Sacramento County sell wood within 

Sacramento County. If such dealers exist, the impacts would be reduced proportionately 

by the fraction of wood sold in Sacramento Country by extra-county dealers. 

• All impacts from reduced sale of manufactured logs are absorbed by the one manufactured 

log producer that is headquartered in California. In reality, the impacts would reflect that 

company’s market share of manufactured log sales in Sacramento County. 

6.0 REFERENCES 

BLS, 2009. Bureau of Labor Statistics. Local Area Unemployment Statistics (LAUS). 

Sacramento County, California. 

California, 2009. California Board of Equalization. Annual Report for Fiscal Year 2007-2008. 

Appendix A, Tables 19 and 20. Available at: 

http://www.boe.ca.gov/annual/pdf/2008/table19_08.xls and 

http://www.boe.ca.gov/annual/pdf/2008/table20_08.xls

Census, 2009a. U.S. Census Bureau. County Business Patterns: 2007. Accessed through 

http://censtats.census.gov/cgi-bin/cbpnaic/cbpdetl.pl for Sacramento County. August 3. 

Census, 2009b. U.S. Census Bureau. Quick Facts for Sacramento County, California. Available 

at: http://quickfacts.census.gov/qfd/states/06/06067.html

Houck, 2003. Houck, James. “Results of Wood Burning Survey-—Sacramento, San Joaquin, and San 

Francisco Areas.” University of California Berkeley/California Air Resources Board.Jarden, 2008. 

Jarden Corporation, 2008. Jarden Corporation Form 10-K for the fiscal year ended December 31, 

2008. Available at: http://www.sec.gov

SJVUAPCD, 2008. San Joaquin Valley Unified Air Pollution Control District. Proposed 

Amendments to Rule 4901 (Wood Burning Fireplaces and Wood Burning Heaters). Final Staff 

Report. October 16. 

SMAQMD, 2009. Rule 421, Mandatory Episodic Curtailment of Wood and Other Solid Fuel 

Burning. Staff Report. Proposed Amendments. Sacramento Metropolitan Air Quality 

Management District. July 2. 

Williams, 2009. Personal communication between Kevin J. Williams, SMAQMD and Maureen 

Kaplan, ERG, August 14.