Project Overview. Project Area- Airshed and Class 1 Areas. Air Quality Report Final June 9, 2014

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1 EDITOR S NOTE: This report was submitted as a draft for the NEPA writer s use in incorporating relevant information into Chapter 3 of the Draft EIS-Affected Environment and Environmental Consequences. Subsequent reviews, corrections, and additional information, some of which are a result of the response to comments on the Draft EIS, to the Chapter 3 were completed in the Final EIS, rather than in this report Project Overview The southwest Jemez Mountain landscape restoration project, proposes several actions that could affect air quality in the surrounding communities near the project area. The primary concern from an air quality perspective is the public health impacts from smoke produced from proposed tool of prescribed fire. In this section, this issue will be explored. Included in this section is a project overview including a description of the area and communities that could be exposed to smoke as well as a description of applicable laws and policy related to air quality, as it relates to the proposed action and alternatives. The existing conditions relative to air quality will be discussed as well as the effects that past actions, similar to those being considered here, had on air quality. The environmental consequences of each alternative are presented, as well as the consideration of cumulative effects could have on air quality. Project Area- Airshed and Class 1 Areas The project area is located within the Middle Rio Grande Airshed (NMED 2003). All airsheds in New Mexico are based on watershed boundaries developed by the New Mexico Water Quality Control Commission. Although the Middle Rio Grande River basin covers many counties, the project area lies completely within Sandoval County. The project area is primarily north and east of Ponderosa and the Jemez Pueblo. The project area also includes a portion of the Jemez Pueblo, the community of Jemez Springs, as well as many other small communities. There are two Class 1 areas within 50 miles of the project area, Bandelier National Monument and San Pedro Parks Wilderness. Bandelier National Monument is approximately 15 miles to the east of the project area and San Pedro Parks Wilderness is approximately 25 miles northwest of the project area. Class 1 areas are identified in the Clean Air Act, as areas that require the highest level of protection for both National Ambient Air Quality Standards (NAAQS) and Visibility. Topography, Winds and Receptors The project is located in the Jemez Mountains north of Albuquerque. Elevations range from about 6,100 feet near the Community of Ponderosa to over 10,100 feet on near Cerro Pelado Peak. The project area generally drains in a southwesterly direction into the Rio Guadalupe, Jemez River, and Vallecito Creek, which all come together just north of the Jemez Pueblo. From there, the flow is generally southeasterly towards the Rio Grande Valley near Rio Rancho, and the Albuquerque metro area, which is approximately 25 miles away. In mountainous terrain, winds are often influenced by the differential heating of slopes. In general, upslope and up-canyon winds can be expected on sunny afternoons with downslope and down-canyon winds developing overnight and continuing until around sunrise. Average wind patterns from the nearest Remote Automated Weather Station (RAWS) in Jemez from May 1 through October 31, from 1985 through 2012, are represented in Figure 1 for May and October. The prevailing winds typically blow from southwest to northeast (southwesterly winds), during the day and then reverse direction overnight. Winds in the spring and summer are stronger during the day with lower winds overnight, as represented by the top row for day and nighttime winds in May. The second row in Figure 1 represents typical winds in October, with lighter daytime winds and stronger downslope winds at night. The down drainage flows typical of fall are coupled with strong inversions that tend to trap cool air close to the surface through the evening and into the morning, during that time period. This influence is not typical during the spring and summer when any cool air is dispersed quickly once the sun can heat up the valley floors.

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3 Figure 1. Wind Rose Data from Jemez Remote Automated Weather Station for May and October, daytime and nighttime wind direction and speed. Based on data from The primary concern from this project from an air quality perspective is smoke from prescribed fire. There are several populations that could potentially be impacted by poor air quality associated from prescribed fire. Generally those communities nearest a given project, particularly those down drainage, would have the greatest impacts (e.g. Ponerosa, Jemez Pueblo, etc). However, potential impacts further away in Bernalillo County, and the Middle and Upper Rio Grande Valley, including the cities of Rio Rancho, Albuquerque, Santa Fe, Los Alamos, and Espanola could be expected. In conducting the effects analysis, smoke sensitive receptors or resources within the potentially affected area that may be sensitive to smoke impacts were identified. Sensitive receptors include populations or specific places, views, hospitals, airports, schools, highways, or businesses that would likely be impacted by smoke coming from the project area. The following specific sensitive receptors were identified and considered: the Community of Ponderosa, the Jemez Pueblo, San Yisidro, Jemez Springs, and the Zia Pueblo, which would primarily be effected by smoke settling in the drainages at night. During the day with predominately southwesterly winds, the communities most likely impacted would be Los Alamos, and White Rock. In addition, Bandelier National Monument, a Class 1 Area, is approximately 15 miles to the southwest of the project area.

4 Figure 2. Air quality sites, climate stations, smoke sensitive areas and Class 1 Airsheds of Concern Relevant policy, law, and regulation. This section evaluates and compares the existing and reference conditions of the air resource within the assessment area, specifically regarding pollutants and visibility. Reference conditions refer to the national and state standards for managing air quality. The Clean Air Act (CAA) and its amendments require the EPA to set National Ambient Air Quality Standards (NAAQS) for pollutants considered harmful to public health and the environment. The act also allows states to adopt additional ambient air quality standards. Both the state and EPA are responsible for improving visibility in New Mexico under Sections 308 and 309 of the CAA. New Mexico has been implementing an approved State Implementation Plan (SIP) under Phase I of these requirements since Currently, the state is in the process of pursuing the Phase II visibility protection regulations, commonly referred to as the Regional Haze Rule. The goal of the Regional Haze Rule is return visibility in Class 1 Areas to conditions prior to anthropogenic impacts by Included in the state s EPA approved SIP is a Smoke Management Program. The NAAQS were established to set limits to protect public health, including the health of sensitive populations such as asthmatics, children, and the elderly, as well as to protect against decreased visibility, damage to animals, crops, vegetation, and buildings. The Environmental Protection Agency (EPA) set NAAQS for six principal pollutants referred to as criteria pollutants. These pollutants are lead, sulfur dioxide, nitrogen dioxide, ozone, particulate matter less than 10 microns in diameter (PM 10) and less than 2.5 micron-size particulate matter (PM 2.5). The New Mexico Environment Department is responsible for regulating NAAQS for these pollutants in New Mexico to protect human health and welfare. Air quality in a given location is defined by pollutant concentrations in the atmosphere. The NAAQS represent maximum acceptable concentrations. Table 1 presents the NAAQS that must be met to comply with the Clean Air Act. Table 1. National Ambient Air Quality Standards Primary Standards Pollutant Level Averaging Time Carbon Monoxide 9 ppm (10 mg/m 3 ) 8-hour (1) 35 ppm (40 mg/m 3 ) 1-hour (1) Lead 0.15 µg/m 3 (2) Rolling 3-Month Average 1.5 µg/m 3 Quarterly Average Nitrogen Dioxide 53 ppb (3) Annual (Arithmetic Average) 100 ppb 1-hour (4) Particulate Matter (PM 10) 150 µg/m 3 24-hour (5) Particulate Matter (PM 2.5) 12.0 µg/m 3 Annual (6) (Arithmetic Average) Ozone 35 µg/m 3 24-hour (7) ppm (2008 std) 0.08 ppm (1997 std) 8-hour (8) 8-hour (9) 0.12 ppm 1-hour (10) Sulfur Dioxide 0.03 ppm Annual (Arithmetic Average) 0.14 ppm 24-hour (1)

5 75 ppb (11) 1-hour (1) Not to be exceeded more than once per year. (2) Final rule signed October 15, (3) The official level of the annual NO 2 standard is ppm, equal to 53 ppb, which is shown here for the purpose of clearer comparison to the 1-hour standard (4) To attain this standard, the 3-year average of the 98th percentile of the daily maximum 1-hour average at each monitor within an area must not exceed 100 ppb (effective January 22, 2010). (5) Not to be exceeded more than once per year on average over 3 years. (6) To attain this standard, the 3-year average of the weighted annual mean PM2.5 concentrations from single or multiple community-oriented monitors must not exceed 15.0 µg/m3. (7) To attain this standard, the 3-year average of the 98th percentile of 24-hour concentrations at each population-oriented monitor within an area must not exceed 35 µg/m3 (effective December 17, 2006). (8) To attain this standard, the 3-year average of the fourth-highest daily maximum 8-hour average ozone concentrations measured at each monitor within an area over each year must not exceed ppm. (effective May 27, 2008) (9) (a) To attain this standard, the 3-year average of the fourth-highest daily maximum 8-hour average ozone concentrations measured at each monitor within an area over each year must not exceed 0.08 ppm. (b) The 1997 standard and the implementation rules for that standard will remain in place for implementation purposes as EPA undertakes rulemaking to address the transition from the 1997 ozone standard to the 2008 ozone standard. (c) EPA is in the process of reconsidering these standards (set in March 2008). (10) (a) EPA revoked the 1-hour ozone standard in all areas, although some areas have continuing obligations under that standard ("anti-backsliding"). (b) The standard is attained when the expected number of days per calendar year with maximum hourly average concentrations above 0.12 ppm is < 1. (11) (a) Final rule signed June 2, To attain this standard, the 3-year average of the 99th percentile of the daily maximum 1-hour average at each monitor within an area must not exceed 75 ppb. Smoke is a mixture of fine particulates and gases, and contains a wide range of pollutants, which can remain suspended in the atmosphere anywhere from a few seconds to several months. The pollutants in the greatest amount produced during combustion of organic material, such as would be found in smoke from a wildfire, include carbon dioxide (CO 2), particulate matter (PM), nitrogen oxides (NO X), and hydrocarbons. Lead, SO 2, and other compounds, including toxics and carcinogens, are also contained in wood smoke but in such small amounts that they are less of a concern in terms of their effect on human health, than PM. NO x and hydrocarbons can react with each other in the presence of sunlight and produce ground level ozone. While many of these pollutants as well as some toxic pollutants are present from smoke from wildland fire, PM 2.5 is the pollutant of greatest concern and is the most likely to result in public health impacts. PM 2.5, which has an aerodynamic diameter of 2.5 micro meters or less and can become imbedded deep in the lungs. PM 2.5 is a major component of smoke and is produced in large quantities in both prescribed fire and wildfires. It also has the ability to be dispersed great distances due to its small size which enables to stay aloft in the atmosphere over long distances. Particulate matter has the potential to impair human health and visibility. PM 10 causes eye, nose, and throat irritation. Because of its relatively larger size, it remains in the upper respiratory tract. PM 2.5, due to its smaller size, travels to the lungs and can cause more serious health impairments, especially in individuals with pre-exisiting health issues related to the

6 respiratory and circulatory system. Exposure to PM 2.5 is associated with premature death, heart attacks, and stroke (Pope 2002)(Pope 2004)(Brook 2004). Additionally it can trigger asthma attacks among those with asthma and respiratory problems ((Sheppard 1999)(Delfino 2009)(Elliott 2013). Carbon monoxide is another major product of prescribed fire and wildfire smoke, but as a gas, it is quickly diluted in the atmosphere. Carbon monoxide can be of concern to firefighters and those conducting prescribed burns as a result of working quite close to the source of the smoke, but in general has little impact away from the immediate project area and only for those in the immediate vicinity of any wildland fire. Ozone has been associated with smoke from prescribed fire and wildfire. While ozone is not directly produced by wildland fire, precursors of ozone are found in smoke. Ozone is formed by the interaction of nitrogen oxides (NO x) and volatile organic compounds (VOCs) in the presence of sunlight. Both NO x and VOCs are produced from wildland fire. Ozone production from wildland fire is a complex process involving numerous variables including fire emissions, chemical and photochemical reactions, aerosol effects on chemistry, as well as local and downwind meteorological patterns (Jaffe 2012). Wildfires have been shown to contribute to ozone concentrations downwind however predicting it is a challenge (Jaffee 2012). Ozone has been shown to result in a number of health effects and symptoms across a wide range of the population, including inducing respiratory symptoms such as coughing, pain, discomfort, and tightness in the chest, inflammation of the lung, loss of lung function, and asthma attacks (EPA 2013). Affected Environment The affected environment within and surrounding the project area meets air quality standards for the six criteria pollutants, so is not listed as a non-attainment area (USEPA 2012). As defined by the Clean Air Act, a non-attainment area is one that does not meet the standards for one or more of the six criteria pollutants. The area within and surrounding the project area typically has excellent air quality conditions, though there is some concern from elevated ozone levels in the Albuquerque metro area. In addition there have been impacts from smoke from wildland fire in many of the communities near the project area in recent years. Regarding wildland fire, the criteria pollutants of concern are ozone and PM2.5, which are being monitored in the assessment area. Air quality monitors at several locations were used in this assessment to evaluate existing pollutant and visibility data. Data from nearby monitors were examined for all criteria pollutants. As noted previously, air quality in the area is considered to be very good, typically well below standards set by EPA and NMED to protect human health and the environment. The area meets all air quality standards and there are no nonattainment areas nearby. Monitoring data for ozone and particulate matter (PM2.5) is presented here, since these are the criteria pollutants of greatest concern. While the monitoring stations nearest the project area are located in the Middle Rio Grande Valley and are strongly influenced by the urban Albuquerque metro area, they are typically well below the standards deemed protective of human health. While air quality on the forest, without the immediate influence of the metro area is likely better, smoke from the project area can impact the nearby areas which have permanent monitoring stations, which is why these monitors were chosen. Data from visibility monitors at San Pedro Parks Wilderness and at Bandelier National Park, (Interagency Monitoring for Protection of Visual Environments or IMPROVE 2009), both nearby Class 1 areas, were also examined. Particulate Matter

7 Particulate matter less than 2.5 micrometers in diameter is a criteria pollutant. PM2.5 is produced by all types of burning including power plants, combustion engines, woodstoves, and wildland fire. Figure 3 shows annual arithmetic mean for PM 2.5 from 2006 to The 12 ug/m 3 standard was reduced from 15 ug/m 3 in March Over the last seven years the annual values have been well below the current standard. Figure 4 shows the values 98th percentile concentrations for the 24-hour standard of 35 ug/m 3. The standard for PM2.5 requires the 98th percentile of the 24-hour average concentration to be at or below 35ug/m 3, averaged over three years. Concentrations of PM 2.5 are far below the annual and 24-hour standards. Annual Arithmetic Mean PM 2.5 Selected Sites Standard = 12 ug/m 3 * PM 2.5 (ug/m 3 ) Del Norte High School South East Heights Santa Fe Runnels Figure 3. Annual arithmetic mean of PM 2.5 (ug/m 3 ) at selected sites, (*Annual mean averaged over 3 years)

8 98 th Percentile 24-hour PM 2.5 Selected Sites Standard = 35 ug/m 3 * 25 PM 2.5 (ug/m 3 ) Del Norte High School South East Heights Santa Fe Runnels Figure th percentile PM 2.5 concentration (ug/m 3 ) at selected sites, (*98 th percentile averaged over 3 years) While the area typically has very good air quality, there have been some notable impacts from smoke from wildland fire over the last several years in many of the potentially affected communities. Large wildfires in 2011, notably the Wallow fire in Arizona and the Las Conchas fire, adjacent to this project area, had significant impacts from smoke. For example, Albuquerque, which is over 150 miles away from the Wallow fire, had notable impacts over several days from smoke, with the 24-hour standard of 35 ug/m 3 exceeded over several days in the beginning of June 2011 (Figure 5).

9 Wallow fire growth and PM 2.5 (ug/m3) concentrations in Albuquerque Max and 24 Average Acres PM 2.5 (ug/m 3 ) 5/31/2011 6/1/2011 6/2/2011 6/3/2011 6/4/2011 6/5/2011 6/6/2011 6/7/2011 6/8/2011 6/9/2011 6/10/2011 6/11/2011 6/12/2011 6/13/ hour Standard 35 (ug/m3) 6/14/2011 6/15/2011 6/16/2011 6/17/2011 6/18/2011 6/20/2011 6/19/ Acres MAX 1-hr 24-hr AVE Figure 5. Wallow Fire growth and PM2.5 concentrations in Albuquerque, daily maximum 1-hour and 24-hour averages. (Only potential exceedances on the 24- hour of 35 ug/m 3 standard are shown.) Los Alamos also had significant impacts from smoke from the Las Conchas wildfire as did many of the Pueblos directly below the fire. One notable difference between the impacts in Albuquerque during the Wallow fire and in Los Alamos during the Las Conchas fire, were the magnitude. Both the 1-hour maximum and 24-hour averages were greater. For example, there were several days when the 1-hour averages in Los Alamos during the Las Conchas fire were 2-5 times higher than the highest days in Albuquerque during the Wallow fire. Figure 6, below shows the days that had measured values above the 24-hour standard for PM2.5 of 35 ug/m 3 in Los Alamos during the Las Conchas fire in While Albuquerque had 7 days with values that potentially exceeded the 24-hour standard, the range of values was generally between 40 and 60 ug/m 3 PM2.5. By comparison, Los Alamos had potentially 10 days when the 24-hr average was above the standard that summer, the range of values was much higher, with five days with measured values over 100 ug/m 3 of PM2.5. Most of these differences can be attributed to the proximity of the wildfires. The Wallow fire was more than 150 miles from Albuquerque, while the Las Conchas fire was within a mile or two of Los Alamos at times. Fortunately, Los Alamos residents had been evacuated during most of the worst days in terms of air quality.

10 hour averages of PM 2.5 in Los Alamos during the Las Conchas fire in (ug/m 3 ) * 250 PM 2.5 (ug/m 3 ) /27 6/28 6/29 6/30 7/1 7/2 7/3 7/4 7/5 7/6 7/7 7/8 7/9 * Only days were shown that exceeded the 24-hour standard for PM2.5 of 35 ug/m 3. Figure hour averages of PM2.5 in Los Alamos during the Las Conchas fire in (ug/m 3 ) While typically, the most significant impacts from smoke are associated with wildfires, there have been impacts from prescribed fires as well. In 2012, the Santa Fe National Forest conducted two prescribed fires near the proposed project area in the Jemez Mountains that resulted in impacts in both in communities nearest the project, but also in Albuquerque. On October 17 th and 18 th of 2012, The Santa Fe National Forest conducted an approximately 7,000 acre prescribed burn in the Jemez Mountains. Figure 7 presents 24 hour averages for PM2.5 at monitoring locations in the Albuquerque metro area during the San Juan prescribed burn. The two days following the burn had the greatest impacts in the Albuquerque area, with increases in the 24 hour average for PM2.5, however these were below the 24 hour standard of 35 ug/m 3. There were periods of higher levels of smoke in the Middle Rio Grande Valley on the 19 th and 20 th, as smoke drained down into the valley. For a period of four to five hours, from approximately 6 to 10 am, smoke concentrations were measured between approximately 35 and 65 ug/m 3, through the valley, and visibility dropped to less than 3 miles in the downtown area at about 9 am. These levels correspond with Moderate impacts based on the Air Quality Index (AQI), developed by the EPA and used by California Air Resource Board, for short term impacts (less than 24 hours) from smoke from wildfires (AIRNow 2013)(CARB 2013). Not shown in the figure were monitored values, in the town of Ponderosa, directly below the prescribed fire. In Ponderosa, impacts were significantly higher, with the 24-hour averages for PM2.5, peaking at 155 ug/m 3 on Oct. 19 th and 47 ug/m 3 on Oct. 20 th. Based on the AQI, this corresponds to a Very Unhealthy Alert and Unhealthy for Sensitive Groups, respectively. Both the proximity to the prescribed fire as well as conditions during the time of the burn, that resulted in a relatively large area that was smoldering overnight and meteorological conditions that resulted in smoke settling

11 in low lying areas overnight and into the morning, were likely the cause of the higher impacts. In addition, conditions in the early fall typically result in smoke lingering into the morning longer, since it takes longer for the sun to heat the valley floors, which in turn leads to smoke dispersing more slowing, under these conditions. PM 2.5 (ug/m 3 ) hour average for PM 2.5 values at selected sites during the San Juan Prescribed burn 10/17/ /18/ /19/ /20/ /21/2012 ABQ-North Valley ABQ-South Valley Bernalillo Santa Fe-Airport Figure hour averages of PM2.5 at selected sites during the San Juan prescribed fire in (ug/m 3 ) The San Juan prescribed fire was followed by the Chaparral prescribed burn approximately 1 week later. This burn occurred during the week of October 29 th when approximately 1,500 acres were treated. Again there were similar impacts in the Albuquerque metro area, as seen in Figure 8. There were approximately 3 days of elevated PM2.5 concentrations measured in the Moderate level for 24-hours based on the AQI. During this prescribed fire a monitor was not deployed in the drainages below the prescribed fire but there were reports of elevated smoke in the Jemez Pueblo during this time.

12 30 24-hour averages for PM 2.5 at selected sites during the Chaparral Prescribed burn PM 2.5 (ug/m 3 ) Oct 30-Oct 31-Oct 1-Nov 2-Nov 3-Nov 4-Nov ABQ-North Valley ABQ-South Valley Bernalillo Santa Fe- Airport Figure hour averages of PM2.5 at selected sites during the Chaparral prescribed fire in (ug/m 3 ) Elevated PM2.5 concentrations can be attributed to both prescribed fires and wildfires, as have occurred in the area over the last several years. Communities closest to the fire typically experience the greatest impacts. Wildfires often have greater impacts than prescribed fire, both in terms of concentrations and duration of impacts of PM2.5 concentrations. While generally, the area has very good air quality in terms on particle pollution, there have been incidences of Unhealthy air quality based on the AQI associated from both wildfire and prescribed fire in the past several years. Ozone Ozone is a secondary pollutant that forms as a result of chemical reactions in the atmosphere when the primary pollutants of nitrogen oxides (NOx) and Volatile Organic Compounds (VOC) are exposed to sunlight. The precursors to ozone are generally produced as emissions from combustion of fossil fuels. Sources in this area include two power plants near Farmington in San Juan County, engine exhaust from oil and gas development, and mobile sources including cars, trucks and recreational vehicles. However, smoke from wildland fire does contain precusors for ozone, and fire smoke has been known to contribute to increased ozone concentrations under certain conditions (Jaffe 2012). Ozone levels are monitored in the geographic area. Figure 5 shows the 4th highest value for 8-hour ozone from 2007 through The ozone standard is ppm (for the 3-year average of the 4th highest value of 8-hour ozone). Although standards are currently being met, one monitored site in Albuquerque has exceeded the standard for two years, though the 3 year average is below the standard. However, during recent events described in the previous section, no significant impacts to ozone concentrations occurred as a result of the wildfires or prescribed fires in the communities in the project area, including the Albuquerque and Santa Fe metro areas. In addition due to the complexity and uncertainty of ozone modeling from wildfires and since no impacts have been noted in recent years from wildland fire events, impacts to ozone levels was not considered as part of this analysis.

13 O 3 (ppm) th Highest 8-hour O 3 Selected Sites Standard = 75 ppb* Del Norte High School Far North East Heights South Valley Mountain View South East Heights Westside Santa Fe Airport Figure 5. 4 th highest 8-hour ozone concentrations (ppm) for selected monitoring sites, (*Standard applies to 4 th highest daily maximum 8-hour value averaged over 3 years) Visibility Visibility relates to conditions that allow humans to see and appreciate the inherent beauty of the landscape features, and these conditions can be greatly impacted by particular matter and gasses that are in smoke or dust (Malm 2000). Visibility and other air quality standards are most stringent within designated Class 1 areas, such as in wilderness areas over 5000 acres and national parks over 6000 acres. Thus, most air quality visibility monitoring is conducted in the Class 1 areas, shown in Figure 2. The IMPROVE network was established in 1985 to measure visibility at Class 1 areas. The IMPROVE site monitors at Bandelier National Park and the San Pedro Parks station measure aerosols and particulate matter that can contribute to reduced visibility and identify the chemicals and emissions responsible for human-caused visibility impairment (FLAG 2002). The Regional Haze Rule sets a goal to return these areas to natural visibility conditions by Figures 6 and 7 show the visibility conditions on the 20% worst visibility days at San Pedro Parks Wilderness and Bandelier National Park, from 2000 through It also shows the glide path that would be necessary in order to return visibility conditions to normal by 2064, based on baseline data from 2006 through Measurements are in deciviews (an index that approximates the amount of visibility change that can be observed by the human eye) and beta extinction (a more scientific measure of light reduction). As of 2010, both Class 1 areas were slightly ahead of schedule but further improvements will be needed to meet the national visibility goal. In 2011, visibility was impacted at both monitoring locations as a result of smoke from the Las Conchas and Wallow fires.

14 Figure 6. Visibility Conditions on Worst 20% Visibility Days for San Pedro Parks Wilderness and Glide Path to 2064 Goal. Figure 7. Visibility Conditions on Worst 20% Visibility Days for Bandelier National Park and Glide Path to 2064 Goal. Environmental Consequences Methodology The following section analyzes the potential emissions from the5 alternatives being considered. Emissions were evaluated rather than direct air quality impacts, due to the high degree of uncertainty associated with assessing impacts, for future actions, such as prescribed fire. This is because the most significant factor that affects impacts to air quality is the meteorology at a specific time which a project is implemented. Impacts to ozone levels, visibility, and direct PM 2.5 concentrations downwind were not directly analyzed, due to the high level of uncertainty with modeling these conditions and the significant variability associated with such an assessment. The primary factor necessary for understanding these

15 effects in populated areas of these pollutants are the meteorological conditions during any specific wildland fire event. Due to the variability and uncertainty of specific meteorological conditions at any given time and that each alternative could be implemented in identical conditions, it is best to drop this variable from the analysis, since it would make evaluating any differences between alternatives irrelevant. Therefore this analysis compares the modeled emission of various pollutants, to draw distinctions between alternatives, while holding weather conditions constant. While this approach does not predict direct impacts, it does provide some indication of the relative magnitude between alternatives, based on the predicted emissions between each alternative. The primary environmental impacts to air quality analyzed in this assessment are total emissions from prescribed fire. Presented here are total emissions for PM 2.5 and carbon dioxide (CO 2) for each alternative, the average emissions of each treatment by alternative, the average annual emissions, and the maximum annual emissions. Consume, v. 3.0 was used to model the five alternatives. Consume is a fuels model commonly used to estimate smoke emissions. Basic input data, such as fuel types, the type of fire (prescribed fire or wildfire), the condition of the unit (has it been mechanically treated or is the fire simulate a natural broadcast burn), and environmental conditions (fuel moisture) are entered into the model. The model then estimates emissions for a variety of pollutants, such as PM2.5 and carbon dioxide. For this analysis, the alternatives were modeled based on estimated acres of four main fuel types, ponderosa pine, wet and dry mixed conifer, and piñon-juniper forests. Alternatives were varied by acres for prescribed fire and those acres that were harvested and then treated with prescribed fire. Fuels moistures were used consistent with conditions in which prescribed fire would take place. For each fuel type, it was assumed that fire suppression and grazing had affected the fuel loads, by increasing the standing biomass in each fuel type, from a natural fire regime that would have reduced the biomass available to burn. The wildfire scenario had the same footprint (area) as the prescribed fire alternatives and assumed that 30% of the area burned with high severity, which is similar to other large wildfires in this area in these fuel types. To make the comparison meaningful, it was assumed that all the acres were burned according to the constraints in each alternative. However, it is understood that under any of the alternatives the final footprint could vary significantly, both as a result of final implementation and recognizing the fire both from prescribed fire and wildfire leaves a mosaic of burned and unburned fuel across the landscape, which is the largest factor influencing uncertainty in the analysis. A complete set of assumptions and outputs for all pollutants modeled is in the record (Hall 2013). Ozone concentrations approaching the federal standard as a result of prescribed fire, is not expected to be significant. Furthermore as a result of the high level of uncertainty associated with the models, the lack of data to support such models, the significant amount of resources required for such an analysis, and the highly uncertain results from such an analysis, direct modeling of ozone was not done. In addition, past wildfires in the area have not resulted in impacts to ozone concentrations in the analysis area, so it was assumed that emissions from prescribed fire is not likely to result in significant impacts to ozone concentrations in the analysis area. Impacts from toxics known to be present in smoke, metals including mercury, radionuclides, by products of accelerants, are not expected to result in any significant public health impacts. Direct modeling of impacts from toxics was not done, due to the high level of uncertainty in such an analysis, both in terms of quantifying the amounts both produced and estimated concentrations downwind, and the high degree of uncertainty quantifying health impacts. In addition, since significant impacts have been shown from PM from smoke from wildfire and prescribed fire, it was determined to focus on those pollutants, rather than pollutants not known to have resulted in significant impacts.

16 Vehicle emissions, associated from roadwork, equipment used for mechanical treatments, thinning, and harvesting wood are not expected to result in significant impacts from any of the alternatives. Impacts from these types of emissions were not directly modeled, except for carbon dioixide, to illustrate the emissions relative to those from prescribed fire. Most emissision were not modeled due to the high degree of uncertainty associated with such an analysis and that air quality in the project area is considered to be very good such that the relatively small amount of emissions from such actions, and the relatively short period that these actions would take place, would be considered negligible to the broader airshed. In addition, emissions from any of these actions are already reduced by federal fuel standards. Fugitive dust from roadwork and quarries, is not expected to create significant impacts to air quality. Impacts from these types of emissions was not directly modeled. This is also due to the high degree of uncertainty associated with such an analysis and that air quality in the project area is considered to be very good such that the relatively small amount of emissions from such actions would be considered negligible to the broader airshed. Any actions building roads or mining quarries, is likely to last for a very short period of time, a few months rather than years, and the dust would be isolated to very small areas and would pose a threat to visibility or air quality standards. In addition, fugitive dust from the construction, operation, and maintenance of quarries and roads, could be reduced by federal contract requirements dictating standard specifications and best management practices to reduce fugitive dust, if deemed necessary for a particular project (FHA 2003)(USFS 2012). In the DEIS, emissions associated from other operations such as mechanical haversting, timber hauling, gravel operations, road maintenance, construction, and decommissioning, was not modeled or considered since it was likely insignificant compared to the emissions from prescribed fire and further any emissions would likely be negligible in terms of potential impacts to NAAQS in the surrounding area. To address commenters concerns, this analysis has now been included below. Summary of environmental impacts by alternative The primary environmental impacts to air quality analyzed in this assessment are emissions from prescribed fire. To distinguish between alternatives, the maximum acres of the project area that could have prescribed fire applied were modeled for each alternative to assess the maximum amount of potential emissions from each alternative. The main differences between alternatives relevant to this assessment are: the number of acres that could have prescribed fire: whether the acres have been harvested prior to using prescribed fire or not; and the type of vegetation on each acre treated by prescribed fire. For this assessment, approximately 72,000 acres were treated with prescribed fire for both Alternatives 1, 3, and 5. The main difference for this assessment between Alternatives 1, 3, and 5 are the proportions of acres that are primarily ponderosa pine, wet and dry mixed conifer, and piñonjuniper. Alternative 2, assumed approximately 18,000 acres would be treated with prescribed fire and Alternative 4, assumed that prescribed fire would only be used on acres that had not been harvested or approximately 40,000 acres. The specific location in the project area was not considered since any type of fire in the project area would affect the same airshed. Presented here are total emissions for PM 2.5 and carbon dioxide (CO 2) for each alternative, the average emissions of each treatment by alternative, the average annual emissions, and the maximum annual emissions. Total Project Emissions by Alternative Modeled total emissions were greatest in Alternatives 1, 3, and 5, with no significant distinction between the three alternatives. Total emissions were least in Alternative 2, the No Action Alternative, with estimated total emissions approximately 19% of Alternatives 1, 3, and 5. Alternative 4 had approximately

17 39% of the total emissions of Alternatives 1, 3, and 5. Figure 8 and 9, below, illustrates the differences between alternatives using the total metric tons of PM 2.5 and carbon dioxide (CO 2) estimated for each alternative. Emissions from each fuel type for acres treated with prescribed fire only and those acres that were mechanically harvested and then treated with prescribed fire were modeled for the five alternatives. All pollutants modeled, resulted in the same pattern between alternatives, though the total emissions for each pollutant varied. As illustrated below, with approximately 19,000 metric tons of PM 2.5 for Alternatives 1, 3, and 5 and approximately 2.4 million metric tons of CO 2 in Alternatives 1, 3, and 5. Also for reference, Figures 8 & 9 has the estimated modeled emissions for PM2.5 and CO2, from a wildfire, assuming that a wildfire was contained in the same footprint as Alternatives 1, 3, and 5. In each case, wildfire s total emissions exceed that of any of the alternatives. It should be noted however, that a wildfire would likely occur over single event potentially lasting for several weeks, while all of the proposed alternatives would occur incrementally over a period of approximately 10 years for the initial treatments modeled here, to occur. 25,000 PM 2.5 Emissions By Alternative (Metric Tons PM 2.5 ) 20,000 Tons PM ,000 10,000 5,000 0 Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Wildfire Prescribed fire Mechanical & Prescribed fire Figure 8. Total PM 2.5 Emission By Alternative (Metric Tons PM 2.5)

18 Tons CO2 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000, ,000 0 CO 2 Emissions by Alternative (Metric Tons CO 2 ) Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Wildfire Prescribed fire Mechanical & Prescribed fire Figure 9. Total CO 2 Emission By Alternative (Metric Tons CO 2) Average emissions of each treatment by alternative While total emission for each pollutant is the most illustrative difference between alternatives, the tons per acre of emissions for various treatments is also important to note. Alternatives 1-3, and 5 are all a combination of prescribed fire and mechanical treatments that are then treated with prescribed fire. Alternative 4 only treats acres with prescribed fire that have not been treated mechanically. Figure 10 below, shows the estimated average metric tons/acre of emissions of PM 2.5 that would be produced for various treatments. While other pollutants were also modeled only PM2.5 emissions are shown because they are the most significant concern. In addition, while the average metric tons/acre varies between pollutants, they all follow the same pattern as demonstrated in figure 10. The modeled metric tons/acre shows that acres that have been mechanically treated and then burned produce the most emissions on a per acre basis. This is a result of higher fuel loads from the slash or activity fuels that have been left behind after a unit has been mechanically harvested. On a per acre basis, prescribed fire of natural fuels (acres not previously harvested) produces the least amount of emissions. Also presented is the average metric tons/acre of PM 2.5 for all the acres combined for each alternative. While the estimated metric tons/acre for prescribed fire vs. the metric tons/acres from units harvested and then burned fairly consistent between alternatives, any differences is a result of the various proportions of fuel types and their treatment type between alternatives. For example, alternatives 1, 3, and 5, approximately 73% of the acres that are mechanically harvested and burned are ponderosa pine, vs. approximately 71% of the acres that are mechanically treated and then burned in alternative 2 are the dry mixed conifer fuel type. While the main driver in the differences in total emissions between alternatives, is the total number of acres treated by fire, the average metric tons/acre varies considerably by treatment type. Figure 10 shows the average amount of PM2.5 produced in metric tons per acre under each alternative by treatment type. The metric tons per acre are presented in addition to the total emissions, to further illustrate the differences between alternatives, and to also address the uncertainty between alternatives regarding their final footprints. This analysis is presented to draw distinction between alternatives at the smallest scale, reducing the greatest factor contributing to the uncertainty, which are the total acres treated with prescribed fire under each alternative. The combined emissions per acre provide the weighted average between treatments across each alternative. The wildfire emissions present the weighted average

19 of emissions per acre combining a mixture of burn severity and crown fire, based on similar severities seen on recent large fires in the Jemez Mountains Average emissions PM 2.5 by alternative, by treatment (metric tons/acre) Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Wildfire Prescribed fire Mechanical & Prescribed fire Combined Figure 10. Average emissions of PM 2.5 by alternative (metric tons/acre PM 2.5) Maximum and average annual emissions Unless the project area were to have a wildfire burn the entire area at one time, it is assumed that individual prescribed burns would be implemented annually over a 10 year time period, in order treat the entire project area. These individual prescribed burns could range anywhere from a couple hundred acres up to 15,000 acres in a single year. To estimate the relative magnitude of emissions between alternatives both the maximum amount of a single prescribed fire was modeled as well as the annual average emissions between alternatives. Figure 11, illustrates the differences in estimated emissions between alternatives for a 15,000 prescribed fire, or the estimated maximum size of a single prescribed fire. Alternatives 1, 3, and 5 produced the most emission of PM 2.5, with an estimated amount of approximately 4,400 tons of PM 2.5. Alternative 4 and 2 produced approximately 30% less emissions of PM 2.5. While the acres for each of the prescribed burns modeled for each alternative was the same the estimated tons per acre of emissions is different, which is represented in the emission reductions for alternatives 2 and 4. It is assumed that a prescribed fire such as this would take more than a week to implement, and based on past monitoring data presented earlier in this assessment, concentrations would likely fall into the Unhealthy category of the AQI for several days during the prescribed burn, in communities directly below the individual project. However, this is based on the specific meteorological conditions at the time of those prescribed burns and may not represent the impacts that could be associated with any of these alternatives. The emissions presented in Figure 11 only represent the maximum emissions of PM 2.5 from the assumed largest prescribed burn that could be implemented. Thus the figure represents the relative difference in the magnitude of emissions.

20 5,000 Maximum emissions PM 2.5 by Alternativeassuming 15,000 acre prescibed burn (tons ) 4,000 3,000 2,000 1,000 0 Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Figure 11. Maximum emissions from a single prescribed fire of PM 2.5 by alternative Figure 12, illustrates the average annual emissions, in tons of PM 2.5 from each alternative. The assessment is based on the average acres between alternatives, assuming the entire project area would be treated over a 10 year period. For Alternatives 1, 3, and 5, it is assumed that they would treat between 7,000 and 8,000 acres annually with prescribed fire. Alternative 2, would treat approximately 2,000 acres per year, and Alternative 4 would treat approximately 4,000 acres per year with prescribed fire. Assuming that the tons/acre of emissions are consistent with the combined tons/acre of PM2.5 in Figure 10, Alternatives 1, 3, and 5 would produce the most emissions annually. Alternative 2 and Alternative 4 would produce the least amount of emissions of PM 2.5 (tons) compared to Alternatives 1, 3, and 5 with reductions of 82% and 61%, respectively. 2,500 Average Annual Emissions PM 2.5 (tons) 2,000 1,500 1, Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Figure 12. Average annual emissions of PM 2.5 by alternative

21 It should be noted that Figure 11 represents the maximum emissions for a single year and Figure 12 represents the average emissions for a single year over the life of the project. In reality, some years could have more or less prescribed burning based on conditions in that specific year. For example, if meteorological conditions or conditions in the forest are not consistent with those defined in the design criteria, there would be no prescribed fires that year. Alternatively, some years there could be more prescribed burning, if conditions were very conducive to using prescribed fire. Estimates in Figures 11 and 12 are just the best estimates at maximum emissions and average emissions between alternatives, and are presented to illustrate potential differences between alternatives and should not be construed as actual emissions in a given year.

22 To address concerns from commenters, an analysis of emissions associated from other operations such as mechanical harvesting, timber hauling, gravel operations, road maintenance, construction, and decommissioning was conducted for carbon dioxide, using the carbon content of gasoline, diesel fuel, and aviation gasoline (EPA, 2004). For each alternative, emissions were calculated using the carbon content of the associated fuels, the amount of operations that is assumed to occur for each activity under each alternative, and the fuel efficiency of each operation. For example, for each alternative that would remove biomass from the forest, the total volume of material was calculated. Based on this volume and the volume a log truck could remove and total number of round trips was calculated. This value was then used with the fuel efficiency of a truck, and the estimated distance that it would need to travel, to estimate the total amount of metric tons of carbon dioxide that would be associated with hauling material off the forest. A similar calculation was conducted for harvesting, road maintenance, construction, and decommissioning, prescribed fire operations not including smoke, and gravel operations. All calculations and assumptions can be seen in project record (Napp, 2014). Figure 13, illustrates the total estimated emissions of carbon dioxide from non-prescribed fire activities in metric tons by alternative for the life of the project. Alternatives, 1, 3, 4, and 5 have similar emissions, producing approximately and estimated amount of 2,100 metric tons of carbon dioxide over the life of the project. In each alternative, harvesting produces approximately 70% of the total carbon dioxide emissions resulting from non-prescribed fire carbon dioxide emissions. 2,500 Total non-smoke emissions of carbon dioxide by alternative (metric tons) 2,000 1,500 1, Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Harvesting Gravel Roads Air Ops/RX Burn Figure 13. Total emissions of carbon dioxide by alternative (metric tons CO2) not including smoke from prescribed fires. Alternatives 1, 3, 4, and 5 produce approximately the same amount of carbon dioxide.

23 When compared to carbon dioxide produced from smoke in each alternative, non-smoke related emissions of carbon dioxide are estimated to be less than 1% of the total carbon dioxide emissions over the life of the project for all alternatives. Table 5 shows the estimated carbon dioxide in metric tons produced for various operations including carbon dioxide from smoke associated with prescribed fire. In comparison, the sum of all non-smoke carbon dioxide emissions from Alternatives 1, 3, 4 or 5 for the life of the project is equal to approximately 1.5 hours of carbon dioxide emissions from an average coal fired power plants or approximately 473 passenger vehicles per year (EPA 2014). Table 1.Metric Tons of Carbon Dioxide, by category for each alternative. Operation Alternative 1 Alternative 2 Alternative 3 Alternative 4 Alternative 5 Harvesting 1, ,444 1,525 1,664 Gravel Roads Air Operations/Prescribed fire Smoke / Prescribed fire 2,388, ,004 2,353,482 1,063,991 2,373,331 Effects of Forest Plan amendments on alternatives There are twelve proposed forest plan amendments for alternatives 1-4. These amendments effect treatments in areas associated with various wildlife species (Mexican Spotted Owl (MSO), Northern Goshawk, turkey, and Peregrine Falcon) and the management of Visual Quality. These amendments have very small and insignificant effects on air quality as it relates from distinguishing one alternative from another. This is primary a result of the small areas affected by the amendments. For example, eliminating the MSO amendments from analysis in Alternative 5, resulted in a less than 1% change in emissions between alternatives 1 and 3. Considering the degree of uncertainty in the models and the analysis, this amount of change is insignificant and does not allow for a meaningful distinction between the three alternatives. Since the air quality analysis examined effects at the project level, these amendments have no effect of the results of the analysis and have insignificant effects on air quality. Climate Change Recent research has demonstrated that there is a close relationship with increased areas burned in wildfires and higher temperatures in the west (Westerling 2006). Future predictions of the southwestern climate forecast a drier future, which in turn leads to an increase in wildfire risk (Seager 2012). While forests store large amounts of carbon, research has consistently shown that after a wildfire, they become a source of releasing carbon into the atmosphere for decades afterwards, even after the initial loss of carbon in smoke (Dore 2012). The same research shows that forests are far more resilient to drier conditions and act as carbon sinks, absorbing CO 2 from the atmosphere more that they release, within a few years after thinning projects and prescribed fire projects (Dore 2012)(Fule 2012)(Stephens 2012)(Honig 2012).