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Air Quality Impacts during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, California

Air Quality Impacts during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, California fire Article Air Quality Impacts during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, California 1 , 2 3 3 1 Ricardo Cisneros * , Donald Schweizer , Hamed Gharibi , Pooya Tavallali , David Veloz and Kathleen Navarro Department of Public Health, University of California, Los Angeles, CA 90095, USA; dveloz@ucmerced.edu USDA Forest Service, Pacific Southwest Region, 1600 Tollhouse Road, Clovis, CA 93611, USA; dschweizer@ucmerced.edu (D.S.); kathleen_navarro@firenet.gov (K.N.) Health Sciences Research Institute, University of California, Los Angeles, CA 90095, USA; hgharibi@ucmerced.edu (H.G.); ptavallali@ucmerced.edu (P.T.) * Correspondence: rcisneros@ucmerced.edu Abstract: The Rough Fire started on 31 July 2015 from a lightning strike, spread to over 61,000 ha and burned parts of the Sierra and Sequoia National Forests and the Sequoia & Kings Canyon National Parks, in California. Health advisories for smoke were issued in rural areas around the fire and in urban areas of the Central Valley. PM2.5 concentrations in rural and urban areas were used to assess the air quality impacts from the fire. Before the Rough Fire, 24-h PM2.5 concentrations for all 3 3 sites ranged from 1 g m o 50 gm . During the wildfire, the 24-h PM2.5 concentrations ranged 3 3 from 2 gm to 545 gm , reaching hazardous levels of the federal Air Quality Index (AQI). The results indicate that the largest PM2.5 smoke impacts occurred at locations closer to and downwind of the fire in mountain communities of the Sierra Nevada, while the smoke impacts were lower in the urban areas. Keywords: Rough Fire; air quality; California; particulate matter; wildfire Citation: Cisneros, R.; Schweizer, D.; Gharibi, H.; Tavallali, P.; Veloz, D.; Navarro, K. Air Quality Impacts 1. Introduction during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, Increased fuels from historic wildland fire suppression and climate change lengthening California. Fire 2021, 4, 31. https:// the fire season are creating a post-suppression era where large high-intensity wildland fires doi.org/10.3390/fire4030031 are becoming more common and leading to increased smoke exposure [1–12]. Wildland fires are an important natural process of disturbance, essential to the health of California’s Received: 9 June 2021 fire-prone ecosystems. The past suppression policy and climate change have led to an Accepted: 19 June 2021 accumulation of unburned fuel that, when lighted, explodes and causes destructive forest Published: 22 June 2021 fires [13]. The San Joaquin Valley, in California, is heavily impacted by air pollution from anthropogenic activities with negative consequences to human health [14–19]. In Publisher’s Note: MDPI stays neutral addition to the loss of property and life that can occur from large high-intensity wildland with regard to jurisdictional claims in fires, the smoke from these fires, in an already anthropogenically polluted environment, published maps and institutional affil- could have devastating impacts on human respiratory health. Previous studies have iations. found associations between exposure to wildfire smoke and self-reported respiratory symptoms [20,21], increases in respiratory emergency department (ED) visits, respiratory physician visits, and respiratory hospitalizations [19,22,23]. Clearly, we need strategies to allow this natural process on protected wilderness areas while minimizing the impacts to Copyright: © 2021 by the authors. human health from the inevitable release of smoke from a large high-intensity wildland Licensee MDPI, Basel, Switzerland. fire when suppression fails. This article is an open access article The Rough Fire, an example of a large high-intensity fire that occurs when suppression distributed under the terms and fails, started on 31 July 2015 from a lightning strike and spread to over 61,000 ha. The conditions of the Creative Commons Rough Fire burned in parts of the Sierra and Sequoia National Forests and the Sequoia & Attribution (CC BY) license (https:// Kings Canyon National Parks. The fire was contained over 4 months later on approximately creativecommons.org/licenses/by/ November 2nd, and officially declared extinct in December. The majority (90%) of the fire 4.0/). Fire 2021, 4, 31. https://doi.org/10.3390/fire4030031 https://www.mdpi.com/journal/fire Fire 2021, 4, 31 2 of 12 consumption activity was completed by October 2nd. During the fire, there were unstable conditions that, together with severe drought, led to extreme fire conditions that allowed the fire to grow, on occasion, to over 4047 ha per day. When the fire activity was at its maximum, there were over 3700 fire personnel assigned to the fire suppression efforts. Previous studies [4,24–26] have concluded that the majority of the smoke impacts from southern Sierra Nevada fires occur downwind of the fire and away from the San Joaquin Valley. In the complex terrain of the Sierra Nevada, ground-level wind patterns are driven by the mountainous terrain. The predominant wind patterns in this area are towards the east and north-east, and the smoke transport from these previous studies have followed these patterns particularly at ground level. The Rough Fire burned at a lower elevation than the fires in these studies. When the smoke from these higher elevation fires moved toward the San Joaquin Valley, it typically did not reach the ground probably because the smoke was above the mixing height [4,24]. The Rough Fire burned at a lower elevation, with less timber (primarily oak-brush- chaparral), and closer to the San Joaquin Valley, well within the daytime mixing height. The location of the fire could mean a different smoke exposure pattern than in previously published case studies. Air quality health advisories created by the San Joaquin Valley Air Pollution Control District suggested that the air quality in urban locations of the central San Joaquin Valley was impacted by the Rough Fire. The different circumstance could mean a different outcome than previously reported in past studies in this area and, additionally, be more extreme because of the size and intensity of this fire. Thus, the hypothesis of the present case study is that the Rough Fire impacted the air quality in urban locations in the San Joaquin Valley. In this study, we are using PM2.5 as an indicator for smoke from the Rough Fire, as it has been shown to be an excellent indicator for the exposure to forest fire smoke [4]. The objective of this study is to examine the air quality impacts of PM2.5 from the Rough Fire on the San Joaquin Valley, rural communities throughout the Sierra Nevada, and urban areas surrounding the fire. 2. Materials and Methods 2.1. Study Location Time Frame The study includes urban locations in the San Joaquin Valley, mountain communities located on the western slope of the Sierra Nevada, and communities in the Owens Valley east of the Sierra Nevada (Figure 1). The selected locations were near the Rough Fire and sites that reported smoke impacts during the fire. The case study period is from May 31st through October 2nd. The Rough Fire started on July 31st and was declared contained on November 2nd 2015. Most of the fire activity decreased by October 2nd. Daily fire growth information data for the Rough Fire were obtained from the Sierra Wildland Fire Reporting System and National Forest Staff. 2.2. Air Quality Data Meteorological (Relative Humidity and Temperature) and PM data were compiled 2.5 from sites in the San Joaquin Valley and in the Sierra Nevada during the Rough Fire. There were 22 site locations used in this assessment (Table 1). The available air quality data were obtained from the California Air Resource Board (CARB) network and from the USDA Forest Service (FS). FS data were obtained using federal equivalency method (FEM) beta-attenuation monitors like those used at the CARB sites. Additional FS data were obtained from temporary environmental beta-attenuation monitors using protocol that provides a sufficient level of agreement with the FEM monitors, to be used comparatively at 24 h (daily) averages [27]. The sites were selected based on air quality data availability and the likelihood of the site being impacted by the fire. Satellite imagery, fire dispersion models (e.g., HYSPLIT, BlueSky), and on-site personal observations of smoke were used to determine smoke impacts. The air quality data provided by federal and state agencies must pass several quality control tests before being released. Fire 2021, 4, 31 3 of 12 Fire 2021, 4, x FOR PEER REVIEW 3 of 12 Figure 1. Location of study area and location of air quality monitors. Figure 1. Location of study area and location of air quality monitors. Daily fire growth information data for the Rough Fire were obtained from the Sierra Table 1. Distribution of 24-hr average PM concentrations before (1 June–30 July 2015) and during (31 July–2 October 2015) 2.5 Wildland Fire Reporting System and National Forest Staff. the Rough Fire, arranged by region and distance to fire. N is the number of 24-hr average measurements at the location. 2.2. Air Quality Data Pre-Wildfire During-Wildfire (1st June to 30th July) (31st July to 2nd October) Sampling Meteorological (Relative Humidity and Temperature) and PM2.5 data were compiled Stations Mean Percentile Mean Percentile from sites in the San Joaquin Valley and in the Sierra Nevada during the Rough Fire. There N Min Max N Min Max 25 50 75 25 50 75 (SD) (SD) were 22 site locations used in this assessment (Table 1). The available air quality data were Sierra Nevada (North) obtained from the California Air Resource Board (CARB) network and from the USDA North-Fork 41 14 (12) 6 8 11 12 50 64 19 (14) 5 8 12 24 55 Forest Service (FS). FS data were obtained using federal equivalency method (FEM) beta- Yosemite 60 7 (3) 3 5 7 9 16 64 17 (27) 2 7 9 12 165 Prather 2 11 (0.2) 11 11 11 11 11 64 18 (16) 4 9 11 22 99 attenuation monitors like those used at the CARB sites. Additional FS data were obtained Trimmer 0 NA NA NA NA NA NA 52 24 (19) 4 11 15 33 89 from temporary environmental beta-attenuation monitors using protocol that provides a Sierra Nevada (Central) sufficient level of agreement with the FEM monitors, to be used comparatively at 24 h Ash Mountain 58 9 (3) 3 6 8 11 16 51 16 (12) 3 8 12 19 62 Pinehurst 60 8 (2) 4 6 8 10 13 62 21 (17) 6 10 11 30 53 (daily) averages [27]. The sites were selected based on air quality data availability and the Wishon 0 NA NA NA NA NA NA 28 70 (54) 9 18 67 114 204 likelihood of the site being impacted by the fire. Satellite imagery, fire dispersion models Cedar Grove 0 NA NA NA NA NA NA 47 99 (94) 10 19 53 175 381 Hume Lake 0 NA (e.g. NA , HYSP NA LIT, BNA lueSky NA ), and o NA n-site p 37 erson128 al o (138) bservati7 ons of22 smok58 e were 198 used t545 o deter- Sierra Nevada (South) mine smoke impacts. The air quality data provided by federal and state agencies must Springville 0 NA NA NA NA NA NA 20 9 (3) 6 8 9 10 18 pass several quality control tests before being released. Kernville 60 10 (1) 7 9 10 11 13 52 14 (6) 6 10 13 16 38 Camp Nelson 0 NA NA NA NA NA NA 21 12 (5) 5 8 11 15 27 2.3. Air Quality Index The Air Quality Index (AQI) is a system created by the Environmental Protection Agency for reporting daily air quality. The AQI has 6 categories with thresholds depend- ing on the air pollutant of interest. The 6 categories are good, moderate, unhealthy for Fire 2021, 4, 31 4 of 12 Table 1. Cont. Pre-Wildfire During-Wildfire (1st June to 30th July) (31st July to 2nd October) Sampling Stations Mean Percentile Mean Percentile N Min Max N Min Max 25 50 75 25 50 75 (SD) (SD) Sierra Nevada (East) Bishop 60 6 (3) 1 3 6 8 20 64 14 (17) 2 5 9 17 97 Devils Postpile 42 11 (9) 4 7 8 11 55 62 15 (12) 3 8 12 20 70 Lone Pine 60 7 (2) 4 6 7 8 12 64 9 (5) 4 6 6 12 27 Central Valley (North) Clovis 60 13 (4) 6 10 12 16 21 64 15 (6) 4 11 14 19 34 Fresno 60 8 (3) 4 6 8 10 15 60 11 (5) 3 7 10 13 25 Madera 60 11 (2) 6 9 11 13 18 64 11 (5) 3 7 11 15 27 Merced 50 9 (3) 4 7 8 11 16 64 12 (6) 4 7 10 15 40 Central Valley (South) Hanford 60 9 (3) 4 6 8 11 20 64 12 (6) 4 7 12 15 32 Porterville 35 8 (3) 4 6 9 10 15 60 13 (6) 6 9 11 16 37 Visalia 51 9 (3) 4 7 8 10 17 60 14 (10) 3 8 11 15 58 NA: Not Available data. Bolded mean PM2.5 concentrations indicate statistically significant differences between pre-fire and during-fire concentrations at the 0.05 significance level using the Mann–Whitney Test. 2.3. Air Quality Index The Air Quality Index (AQI) is a system created by the Environmental Protection Agency for reporting daily air quality. The AQI has 6 categories with thresholds depending on the air pollutant of interest. The 6 categories are good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, and hazardous. These categories correspond to EPA breakpoints (0–12, 12.1–35.4, 35.5–55.4, 55.5–150.4, 150.5–250.4, 250.5–500 gm ) when determining the AQI for the daily or 24 h PM concentration. 2.5 3. Results Smoke Impacts on PM Concentrations 2.5 The air quality impacts during the Rough Fire were localized in the central Sierra Nevada and extended to the northern and eastern Sierra monitoring sites during the study period. Air monitors in the Central Valley were impacted on a few occasions but to a lesser degree (Table 1, Figures 2 and 3). Table 1 and Figures 2–7 show PM 24-h average concentrations before and during the 2.5 fire. Without fire emissions, 24-h PM concentrations for all sites ranged from 1 gm 2.5 3 3 to 50 gm . During the wildfire, the 24-h PM concentrations ranged from 2 gm to 2.5 545 gm . The Central Valley (North) sites consisted of Fresno, Clovis, Madera, and Merced (Figure 2). Prior to the fire, Fresno experienced a mean PM2.5 concentration of 8 g/m with a maximum of 15 gm-3; Clovis a PM2.5 average of 13 gm and a maximum of 3 3 3 21 gm ; Madera a PM2.5 average of 11gm and a maximum of 18 gm ; and Merced 3 3 a PM2.5 average of 9 gm and a maximum of 16 gm . During the fire, Fresno PM2.5 3 3 increased to 11 gm and the PM2.5 maximum to 25 gm ; Clovis PM2.5 increased 3 3 to 15 gm and the maximum to 34 gm ; Madera PM2.5 stayed the same and the maximum increased to 27 gm ; and Merced’s mean PM2.5 concentration increased to 3 3 12 gm with a maximum of 40 gm . During the fire, PM2.5 concentrations reached an AQI of moderate and unhealthy for sensitive groups on one occasion in Merced. Fresno is the only location that experienced statistically significant differences between the pre-fire and the during-fire PM2.5 concentrations (Table 1). Fire 2021, 4, 31 5 of 12 Fire 2021, 4, x FOR PEER REVIEW 5 of 12 Fire 2021, 4, x FOR PEER REVIEW 5 of 12 Figure 2. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 2. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 Figure 2. growth data w 24-Hour PM ere available 2.5 conce at ntrations with the beginning Air Quality of the fire. Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Figure 3. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 3. growth data w 24-Hour PM ere available 2.5 conce at ntrations with the beginning Air Quality of the fire. Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 3. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Table 1 and Figures 2–7 show PM2.5 24-h average concentrations before and during −3 Table 1 and Figures 2–7 show PM2.5 24-h average concentrations before and during the fire. Without fire emissions, 24-h PM2.5 concentrations for all sites ranged from 1 µgm −3 the fire. Without fire emissions, 24-h PM2.5 concentrations for all sites ranged from 1 µgm Fire 2021, 4, x FOR PEER REVIEW 6 of 12 Fire 2021, 4, x FOR PEER REVIEW 6 of 12 Fire 2021, 4, 31 6 of 12 −3 −3 to 50 µgm . During the wildfire, the 24-h PM2.5 concentrations ranged from 2 µgm to 545 −3 −3 to 50 µgm . During the wildfire, the 24-h PM2.5 concentrations ranged from 2 µgm to 545 −3 µgm . −3 µgm . Figure 4. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 4. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 Figure 4. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Figure 5. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 5. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. Figure 5. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Fire 2021, 4, 31 7 of 12 Fire 2021, 4, x FOR PEER REVIEW 7 of 12 Fire 2021, 4, x FOR PEER REVIEW 7 of 12 Figure 6. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 6. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. Figure 6. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Figure 7. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. Figure 7. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 7. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Fire 2021, 4, 31 8 of 12 The Central Valley (South) sites consisted of Hanford, Porterville and Visalia (Figure 3). 3 3 Hanford experienced a mean PM2.5 of 9 gm and a PM2.5 maximum of 20 gm before the fire started. During the fire, Hanford’s mean PM2.5 increased to 12 gm and the 3 3 maximum to 32 gm . Before the fire, Porterville had a mean PM2.5 of 8 gm and 3 3 a maximum of 15 gm ; during the fire, the mean PM2.5 increased to 13 gm and 3 3 the maximum increased to 37 gm . Before the fire, Visalia had a mean of 9 gm and a maximum of 17 gm . During the fire, the mean PM2.5 in Visalia increased to 3 3 14 gm and the maximum to 58 gm . The PM2.5 concentrations experienced at all these locations, before and during the fire, were statistically significant, indicating a PM2.5 impact from the Rough Fire. These locations spiked during August 12th–21st and September 7th–14th (Figures S1 and S2). During the latter time, the PM2.5 concentrations reached an AQI of very unhealthy at Visalia. Prior to the fire, in the Sierra Nevada (North), the mean PM2.5 concentrations ranged between 3 and 50 gm . However, when the fire started, the PM2.5 concentration range increased to 2–165 gm . The majority of the sites experienced their first increase in PM2.5 from August 17th to August 31st (Figure 4). AQIs during this time were in the moderate and unhealthy to sensitive groups for PM2.5. The highest levels of PM2.5 occurred during a second spike, which happened from September 4th to September 14th. During this period, the levels reached AQIs of unhealthy and unhealthy for sensitive groups. The concentrations started to decrease after September 20th, and the AQI dropped to the good category after October 20th. For the Sierra Nevada (Central) sites, the only locations that were monitoring the air quality prior to the fire were Pinehurst and Ash Mountain at Sequoia National Park (Figure 5). For the remaining central Sierra Nevada sites, temporary air quality monitoring equipment was installed upon the onset of the fire. Comparing the data available prior to the fire in the Central Sierra Nevada sites, the mean PM2.5 concentration was 8 gm in Pinehurst and 9 gm in Ash Mountain. During the fire, the mean PM2.5 increased to 3 3 21 gm in Pinehurst and to 16 gm at Ash Mountain. During the fire, the mean PM2.5 concentrations at all of the Sierra Nevada (Central) sites ranged from 16–128 gm , with 3 3 24 h maximums ranging from 53 gm to 545 gm . PM2.5 concentrations increased on August 6th and remained high until September 21st; during this period, the daily AQI was often in the unhealthy category and reached the very unhealthy and hazardous levels. The PM2.5 AQI at all sites decreased to the good category after October 15th. Data before the fire started in the Sierra Nevada (South) sites were only available for Kernville (Figure 6). At Kernville, prior to the fire, the mean PM2.5 concentration was 3 3 10 gm and the mean of the 24 h maximum was 13 gm . During the fire, the mean PM2.5 concentration increased to 14 gm , with the mean 24-h maximum increasing to 38 gm . During the fire, at all sites, the mean PM2.5 concentrations ranged from 9–14 gm . The PM2.5 concentrations started to increase on August 3rd, with highs on August 20th. During the fire, the PM2.5 AQIs in these locations stayed in the good and moderate categories. These sites were the least impacted Sierra Nevada air monitoring sites during the Rough Fire. Prior to the fire, the mean PM2.5 concentrations in the Sierra Nevada (East) sites ranged from 6 to 11 gm (Figure 7). During the fire, the mean PM2.5 concentrations 3 3 range increased to 9–15 gm . Bishop experienced a mean PM2.5 of 6 gm and a 3 3 maximum of 20 gm before the fire; and during the fire a mean of 14 gm and 3 3 maximum of 97 gm . Devils Postpile had a mean PM2.5 of 12 gm and maximum of 55 gm before the fire started. During the fire, Devils Postpile’s mean PM2.5 increased to 3 3 15 gm and the maximum increased to 70 gm . Lone Pine experienced a mean PM2.5 3 3 24-h concentration of 7 gm and a maximum of 12 gm before the fire began. During the fire, Lone Pine’s PM2.5 concentration increased to 9 gm and the maximum increased to 27 gm . The PM2.5 concentrations at these sites reached an AQI of unhealthy on three occasions and unhealthy for sensitive groups on five occasions. The air quality improved to an AQI of good at these locations after September 20th. Fire 2021, 4, 31 9 of 12 4. Discussion PM2.5 was seen to increase at many of the sites during the Rough Fire and in some areas reached hazardous air quality levels. The hypothesis of the present study was that the air quality of urban locations in the San Joaquin Valley was impacted by the Rough Fire because of the region’s lower elevation, causing the fire to burn nearer to urban areas. The findings suggest that the smoke from the fire impacted PM2.5 at urban locations in the San Joaquin Valley. These smoke impacts occurred on two occasions and caused AQI to reach an unhealthy level only in Visalia. Previous studies of wildfires on federal lands higher up in the Sierra Nevada have not found significant impacts to PM2.5 in the San Joaquin Valley [24–26]. The Rough Fire was different from these other fires because it primarily burned at a lower elevation and nearer the San Joaquin Valley, and the increased smoke production from this high-intensity wildfire was likely the cause of the increased PM2.5 at the lower elevation sites [10,28]. Similarly to the findings of previous studies, the majority of the impacts occurred at the higher southern Sierra Nevada sites, downwind of dominant transport patterns and east of the San Joaquin Valley. The PM2.5 concentrations observed in the mountain locations were 10 times greater than the ones observed in the San Joaquin Valley, reaching AQIs of hazardous (Figures 2–7). The results of this study indicate that even for this high- intensity forest fire occurring at a lower elevation in the Sierra Nevada, the largest smoke impacts are observed at the more rural mountain communities closer to and downwind of the fire. 4.1. Case-Crossover Analysis The present study conducted an epidemiological analysis (case-crossover analysis) to understand if the exposure to PM2.5 concentrations before and during the fire would have an impact on the health (respiratory diseases) of residents in urban locations. This analysis was only conducted for the San Joaquin Valley residents. The association was only found for PM2.5 exposure and asthma ED visits before the fire started [OR: 1.195 (95% CI: 1.001, 1.427)]. During the fire there was a decrease in asthma ED visits (OR: 0.327 (95% CI: 0.177–0.604) for every 10 g/m increase in PM2.5. No other associations between PM2.5 and ED visits due to the other respiratory diseases were found for the during-wildfire and pre-wildfire periods. A possible explanation for the lack of association, even with the increase of PM2.5 during the fire, is the robust smoke communication at the local, state, and federal levels. News releases and media warnings for residents on the risk of smoke exposure were widespread, in addition to the smoke-educated public in this smoke-prone area. Smoke alerts and health advisories put out by air regulators and fire managers informed residents and potentially allowed them to limit their personal exposure to PM2.5 by spending more time indoors or avoiding outdoor activities during the highest hours of ambient PM2.5. The purpose of this paper is not to conduct a health assessment. A more focused study is needed to investigate and confirm these findings. Another limitation of this assessment was the fact that the mountain locations that experienced the highest impact to PM2.5 from smoke did not have enough cases to be included in the epidemiological analysis because of the combination of lower population densities in these areas and the relatively short duration of smoke exposure. Future studies using more fires with known impacts from smoke in these less densely populated rural areas are needed to understand if there are effects at these locations during periods of wildland fire smoke. 4.2. Smoke Management Implications Wildland fire is inevitable in the fire prone ecosystems of California. Smoke managers should prioritize having smoke-educated and prepared communities, where individuals are encouraged to have air filters for use during a wildfire and can easily access timely predictive information on local smoke conditions during the incident. Large high-intensity wildfires appear to be the new normal in California in these lower elevation areas nearer urban areas. The smoke from these fires is of great concern to Fire 2021, 4, 31 10 of 12 the foothill communities. Additionally, foothill communities experience smoke from fires that are more typical of the historic normal and may become averse to all wildland fire smoke. Education and the communication of the need for some smoke exposure to limit large smoke events is essential for an effective smoke management in this area. 5. Conclusions Smoke from the Rough Fire, a lower-elevation, large, and high-intensity wildfire, reached the San Joaquin Valley sites, impacting PM2.5 on two occasions. PM2.5 increased at many of the sites during the wildfire, especially when the fire was consuming large areas. The PM2.5 levels in the Sierra Nevada locations reached a hazardous AQI. Similarly to previous studies, the largest smoke impacts were observed at the more rural mountain communities closer to and downwind of the fire. These findings suggest smoke managers should expect large high-intensity wildland fires that occur when suppression fails, particu- larly those occurring at lower elevations, to have an increased potential of exposure for the higher concentrated populations in areas of the San Joaquin Valley. Smoke management policies should adjust their limited resources to focus on the communication to rural areas where the largest smoke impacts occur, along with educating the general public on the importance of routinely allowing fire within the historic size and intensity levels in this fire-prone ecosystem and the seemingly paradoxical benefits of reduced smoke exposure over time through this approach. More research is needed to see if there is an elevation threshold for smoke impacts to the urban areas from fires with a size and intensity that are more typical of the historic normal, particularly in the federally protected wilderness, that could help air and land managers to better assess the risk to air quality from smoke. Furthermore, the increase in PM2.5 during the fire did not create a subsequent impact to ED visits for asthma and other respiratory diseases in the Central Valley. This needs to be further studied, to confirm the findings, and expanded, to include rural communities more heavily impacted by smoke. The role smoke alerts and health advisories played in informing residents and allowing them to avoid outdoor activities during the times of the highest smoke levels needs a more thorough assessment. These air quality advisories during an event, along with pre-fire season planning for residential air filter use during a smoke event, are potentially vital tools in protecting human health from wildland fire smoke, particularly during the large high-intensity fires. Supplementary Materials: The followings are available online at https://www.mdpi.com/article/ 10.3390/fire4030031/s1. Author Contributions: Conceptualization, writing—review & editing R.C. and D.S.; formal analysis, software, and data curation, H.G. and P.T.; review & editing, D.V. and K.N. All authors have read and agreed to the published version of the manuscript. 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Navarro, K.M.; Cisneros, R.; O’Neill, S.M.; Schweizer, D.; Larkin, N.K.; Balmes, J.R. Air-Quality Impacts and Intake Fraction of PM2.5 during the 2013 Rim Megafire. Environ. Sci. Technol. 2016, 50, 11965–11973. [CrossRef] [PubMed] Fire 2021, 4, 31 12 of 12 25. Schweizer, D.; Cisneros, R. Wildland fire management and air quality in the southern Sierra Nevada: Using the Lion Fire as a case study with a multi-year perspective on PM2.5 impacts and fire policy. J. Environ. Manag. 2014, 144, 265–278. [CrossRef] [PubMed] 26. Cisneros, R.; Schweizer, D.; Zhong, S.; Hammond, K.; Perez, M.A.; Guo, Q.; Traina, S.; Bytnerowicz, A.; Bennett, D. Analysing the effects of the 2002 McNally fire on air quality in the San Joaquin Valley and southern Sierra Nevada, California. Int. J. Wildland Fire 2012, 21, 1065–1075. [CrossRef] 27. Schweizer, D.; Cisneros, R.; Shaw, G. A comparative analysis of temporary and permanent beta attenuation monitors: The importance of understanding data and equipment limitations when creating PM2.5 air quality health advisories. Atmos. Pollut. Res. 2016, 7, 865–875. [CrossRef] 28. Schweizer, D.; Cisneros, R.; Traina, S.; Ghezzehei, T.A.; Shaw, G. Using National Ambient Air Quality Standards for fine particulate matter to assess regional wildland fire smoke and air quality management. J. Environ. Manag. 2017, 201, 345–356. [CrossRef] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fire Multidisciplinary Digital Publishing Institute

Air Quality Impacts during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, California

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fire Article Air Quality Impacts during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, California 1 , 2 3 3 1 Ricardo Cisneros * , Donald Schweizer , Hamed Gharibi , Pooya Tavallali , David Veloz and Kathleen Navarro Department of Public Health, University of California, Los Angeles, CA 90095, USA; dveloz@ucmerced.edu USDA Forest Service, Pacific Southwest Region, 1600 Tollhouse Road, Clovis, CA 93611, USA; dschweizer@ucmerced.edu (D.S.); kathleen_navarro@firenet.gov (K.N.) Health Sciences Research Institute, University of California, Los Angeles, CA 90095, USA; hgharibi@ucmerced.edu (H.G.); ptavallali@ucmerced.edu (P.T.) * Correspondence: rcisneros@ucmerced.edu Abstract: The Rough Fire started on 31 July 2015 from a lightning strike, spread to over 61,000 ha and burned parts of the Sierra and Sequoia National Forests and the Sequoia & Kings Canyon National Parks, in California. Health advisories for smoke were issued in rural areas around the fire and in urban areas of the Central Valley. PM2.5 concentrations in rural and urban areas were used to assess the air quality impacts from the fire. Before the Rough Fire, 24-h PM2.5 concentrations for all 3 3 sites ranged from 1 g m o 50 gm . During the wildfire, the 24-h PM2.5 concentrations ranged 3 3 from 2 gm to 545 gm , reaching hazardous levels of the federal Air Quality Index (AQI). The results indicate that the largest PM2.5 smoke impacts occurred at locations closer to and downwind of the fire in mountain communities of the Sierra Nevada, while the smoke impacts were lower in the urban areas. Keywords: Rough Fire; air quality; California; particulate matter; wildfire Citation: Cisneros, R.; Schweizer, D.; Gharibi, H.; Tavallali, P.; Veloz, D.; Navarro, K. Air Quality Impacts 1. Introduction during the 2015 Rough Fire in Areas Surrounding the Sierra Nevada, Increased fuels from historic wildland fire suppression and climate change lengthening California. Fire 2021, 4, 31. https:// the fire season are creating a post-suppression era where large high-intensity wildland fires doi.org/10.3390/fire4030031 are becoming more common and leading to increased smoke exposure [1–12]. Wildland fires are an important natural process of disturbance, essential to the health of California’s Received: 9 June 2021 fire-prone ecosystems. The past suppression policy and climate change have led to an Accepted: 19 June 2021 accumulation of unburned fuel that, when lighted, explodes and causes destructive forest Published: 22 June 2021 fires [13]. The San Joaquin Valley, in California, is heavily impacted by air pollution from anthropogenic activities with negative consequences to human health [14–19]. In Publisher’s Note: MDPI stays neutral addition to the loss of property and life that can occur from large high-intensity wildland with regard to jurisdictional claims in fires, the smoke from these fires, in an already anthropogenically polluted environment, published maps and institutional affil- could have devastating impacts on human respiratory health. Previous studies have iations. found associations between exposure to wildfire smoke and self-reported respiratory symptoms [20,21], increases in respiratory emergency department (ED) visits, respiratory physician visits, and respiratory hospitalizations [19,22,23]. Clearly, we need strategies to allow this natural process on protected wilderness areas while minimizing the impacts to Copyright: © 2021 by the authors. human health from the inevitable release of smoke from a large high-intensity wildland Licensee MDPI, Basel, Switzerland. fire when suppression fails. This article is an open access article The Rough Fire, an example of a large high-intensity fire that occurs when suppression distributed under the terms and fails, started on 31 July 2015 from a lightning strike and spread to over 61,000 ha. The conditions of the Creative Commons Rough Fire burned in parts of the Sierra and Sequoia National Forests and the Sequoia & Attribution (CC BY) license (https:// Kings Canyon National Parks. The fire was contained over 4 months later on approximately creativecommons.org/licenses/by/ November 2nd, and officially declared extinct in December. The majority (90%) of the fire 4.0/). Fire 2021, 4, 31. https://doi.org/10.3390/fire4030031 https://www.mdpi.com/journal/fire Fire 2021, 4, 31 2 of 12 consumption activity was completed by October 2nd. During the fire, there were unstable conditions that, together with severe drought, led to extreme fire conditions that allowed the fire to grow, on occasion, to over 4047 ha per day. When the fire activity was at its maximum, there were over 3700 fire personnel assigned to the fire suppression efforts. Previous studies [4,24–26] have concluded that the majority of the smoke impacts from southern Sierra Nevada fires occur downwind of the fire and away from the San Joaquin Valley. In the complex terrain of the Sierra Nevada, ground-level wind patterns are driven by the mountainous terrain. The predominant wind patterns in this area are towards the east and north-east, and the smoke transport from these previous studies have followed these patterns particularly at ground level. The Rough Fire burned at a lower elevation than the fires in these studies. When the smoke from these higher elevation fires moved toward the San Joaquin Valley, it typically did not reach the ground probably because the smoke was above the mixing height [4,24]. The Rough Fire burned at a lower elevation, with less timber (primarily oak-brush- chaparral), and closer to the San Joaquin Valley, well within the daytime mixing height. The location of the fire could mean a different smoke exposure pattern than in previously published case studies. Air quality health advisories created by the San Joaquin Valley Air Pollution Control District suggested that the air quality in urban locations of the central San Joaquin Valley was impacted by the Rough Fire. The different circumstance could mean a different outcome than previously reported in past studies in this area and, additionally, be more extreme because of the size and intensity of this fire. Thus, the hypothesis of the present case study is that the Rough Fire impacted the air quality in urban locations in the San Joaquin Valley. In this study, we are using PM2.5 as an indicator for smoke from the Rough Fire, as it has been shown to be an excellent indicator for the exposure to forest fire smoke [4]. The objective of this study is to examine the air quality impacts of PM2.5 from the Rough Fire on the San Joaquin Valley, rural communities throughout the Sierra Nevada, and urban areas surrounding the fire. 2. Materials and Methods 2.1. Study Location Time Frame The study includes urban locations in the San Joaquin Valley, mountain communities located on the western slope of the Sierra Nevada, and communities in the Owens Valley east of the Sierra Nevada (Figure 1). The selected locations were near the Rough Fire and sites that reported smoke impacts during the fire. The case study period is from May 31st through October 2nd. The Rough Fire started on July 31st and was declared contained on November 2nd 2015. Most of the fire activity decreased by October 2nd. Daily fire growth information data for the Rough Fire were obtained from the Sierra Wildland Fire Reporting System and National Forest Staff. 2.2. Air Quality Data Meteorological (Relative Humidity and Temperature) and PM data were compiled 2.5 from sites in the San Joaquin Valley and in the Sierra Nevada during the Rough Fire. There were 22 site locations used in this assessment (Table 1). The available air quality data were obtained from the California Air Resource Board (CARB) network and from the USDA Forest Service (FS). FS data were obtained using federal equivalency method (FEM) beta-attenuation monitors like those used at the CARB sites. Additional FS data were obtained from temporary environmental beta-attenuation monitors using protocol that provides a sufficient level of agreement with the FEM monitors, to be used comparatively at 24 h (daily) averages [27]. The sites were selected based on air quality data availability and the likelihood of the site being impacted by the fire. Satellite imagery, fire dispersion models (e.g., HYSPLIT, BlueSky), and on-site personal observations of smoke were used to determine smoke impacts. The air quality data provided by federal and state agencies must pass several quality control tests before being released. Fire 2021, 4, 31 3 of 12 Fire 2021, 4, x FOR PEER REVIEW 3 of 12 Figure 1. Location of study area and location of air quality monitors. Figure 1. Location of study area and location of air quality monitors. Daily fire growth information data for the Rough Fire were obtained from the Sierra Table 1. Distribution of 24-hr average PM concentrations before (1 June–30 July 2015) and during (31 July–2 October 2015) 2.5 Wildland Fire Reporting System and National Forest Staff. the Rough Fire, arranged by region and distance to fire. N is the number of 24-hr average measurements at the location. 2.2. Air Quality Data Pre-Wildfire During-Wildfire (1st June to 30th July) (31st July to 2nd October) Sampling Meteorological (Relative Humidity and Temperature) and PM2.5 data were compiled Stations Mean Percentile Mean Percentile from sites in the San Joaquin Valley and in the Sierra Nevada during the Rough Fire. There N Min Max N Min Max 25 50 75 25 50 75 (SD) (SD) were 22 site locations used in this assessment (Table 1). The available air quality data were Sierra Nevada (North) obtained from the California Air Resource Board (CARB) network and from the USDA North-Fork 41 14 (12) 6 8 11 12 50 64 19 (14) 5 8 12 24 55 Forest Service (FS). FS data were obtained using federal equivalency method (FEM) beta- Yosemite 60 7 (3) 3 5 7 9 16 64 17 (27) 2 7 9 12 165 Prather 2 11 (0.2) 11 11 11 11 11 64 18 (16) 4 9 11 22 99 attenuation monitors like those used at the CARB sites. Additional FS data were obtained Trimmer 0 NA NA NA NA NA NA 52 24 (19) 4 11 15 33 89 from temporary environmental beta-attenuation monitors using protocol that provides a Sierra Nevada (Central) sufficient level of agreement with the FEM monitors, to be used comparatively at 24 h Ash Mountain 58 9 (3) 3 6 8 11 16 51 16 (12) 3 8 12 19 62 Pinehurst 60 8 (2) 4 6 8 10 13 62 21 (17) 6 10 11 30 53 (daily) averages [27]. The sites were selected based on air quality data availability and the Wishon 0 NA NA NA NA NA NA 28 70 (54) 9 18 67 114 204 likelihood of the site being impacted by the fire. Satellite imagery, fire dispersion models Cedar Grove 0 NA NA NA NA NA NA 47 99 (94) 10 19 53 175 381 Hume Lake 0 NA (e.g. NA , HYSP NA LIT, BNA lueSky NA ), and o NA n-site p 37 erson128 al o (138) bservati7 ons of22 smok58 e were 198 used t545 o deter- Sierra Nevada (South) mine smoke impacts. The air quality data provided by federal and state agencies must Springville 0 NA NA NA NA NA NA 20 9 (3) 6 8 9 10 18 pass several quality control tests before being released. Kernville 60 10 (1) 7 9 10 11 13 52 14 (6) 6 10 13 16 38 Camp Nelson 0 NA NA NA NA NA NA 21 12 (5) 5 8 11 15 27 2.3. Air Quality Index The Air Quality Index (AQI) is a system created by the Environmental Protection Agency for reporting daily air quality. The AQI has 6 categories with thresholds depend- ing on the air pollutant of interest. The 6 categories are good, moderate, unhealthy for Fire 2021, 4, 31 4 of 12 Table 1. Cont. Pre-Wildfire During-Wildfire (1st June to 30th July) (31st July to 2nd October) Sampling Stations Mean Percentile Mean Percentile N Min Max N Min Max 25 50 75 25 50 75 (SD) (SD) Sierra Nevada (East) Bishop 60 6 (3) 1 3 6 8 20 64 14 (17) 2 5 9 17 97 Devils Postpile 42 11 (9) 4 7 8 11 55 62 15 (12) 3 8 12 20 70 Lone Pine 60 7 (2) 4 6 7 8 12 64 9 (5) 4 6 6 12 27 Central Valley (North) Clovis 60 13 (4) 6 10 12 16 21 64 15 (6) 4 11 14 19 34 Fresno 60 8 (3) 4 6 8 10 15 60 11 (5) 3 7 10 13 25 Madera 60 11 (2) 6 9 11 13 18 64 11 (5) 3 7 11 15 27 Merced 50 9 (3) 4 7 8 11 16 64 12 (6) 4 7 10 15 40 Central Valley (South) Hanford 60 9 (3) 4 6 8 11 20 64 12 (6) 4 7 12 15 32 Porterville 35 8 (3) 4 6 9 10 15 60 13 (6) 6 9 11 16 37 Visalia 51 9 (3) 4 7 8 10 17 60 14 (10) 3 8 11 15 58 NA: Not Available data. Bolded mean PM2.5 concentrations indicate statistically significant differences between pre-fire and during-fire concentrations at the 0.05 significance level using the Mann–Whitney Test. 2.3. Air Quality Index The Air Quality Index (AQI) is a system created by the Environmental Protection Agency for reporting daily air quality. The AQI has 6 categories with thresholds depending on the air pollutant of interest. The 6 categories are good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, and hazardous. These categories correspond to EPA breakpoints (0–12, 12.1–35.4, 35.5–55.4, 55.5–150.4, 150.5–250.4, 250.5–500 gm ) when determining the AQI for the daily or 24 h PM concentration. 2.5 3. Results Smoke Impacts on PM Concentrations 2.5 The air quality impacts during the Rough Fire were localized in the central Sierra Nevada and extended to the northern and eastern Sierra monitoring sites during the study period. Air monitors in the Central Valley were impacted on a few occasions but to a lesser degree (Table 1, Figures 2 and 3). Table 1 and Figures 2–7 show PM 24-h average concentrations before and during the 2.5 fire. Without fire emissions, 24-h PM concentrations for all sites ranged from 1 gm 2.5 3 3 to 50 gm . During the wildfire, the 24-h PM concentrations ranged from 2 gm to 2.5 545 gm . The Central Valley (North) sites consisted of Fresno, Clovis, Madera, and Merced (Figure 2). Prior to the fire, Fresno experienced a mean PM2.5 concentration of 8 g/m with a maximum of 15 gm-3; Clovis a PM2.5 average of 13 gm and a maximum of 3 3 3 21 gm ; Madera a PM2.5 average of 11gm and a maximum of 18 gm ; and Merced 3 3 a PM2.5 average of 9 gm and a maximum of 16 gm . During the fire, Fresno PM2.5 3 3 increased to 11 gm and the PM2.5 maximum to 25 gm ; Clovis PM2.5 increased 3 3 to 15 gm and the maximum to 34 gm ; Madera PM2.5 stayed the same and the maximum increased to 27 gm ; and Merced’s mean PM2.5 concentration increased to 3 3 12 gm with a maximum of 40 gm . During the fire, PM2.5 concentrations reached an AQI of moderate and unhealthy for sensitive groups on one occasion in Merced. Fresno is the only location that experienced statistically significant differences between the pre-fire and the during-fire PM2.5 concentrations (Table 1). Fire 2021, 4, 31 5 of 12 Fire 2021, 4, x FOR PEER REVIEW 5 of 12 Fire 2021, 4, x FOR PEER REVIEW 5 of 12 Figure 2. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 2. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 Figure 2. growth data w 24-Hour PM ere available 2.5 conce at ntrations with the beginning Air Quality of the fire. Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Figure 3. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 3. growth data w 24-Hour PM ere available 2.5 conce at ntrations with the beginning Air Quality of the fire. Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 3. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Table 1 and Figures 2–7 show PM2.5 24-h average concentrations before and during −3 Table 1 and Figures 2–7 show PM2.5 24-h average concentrations before and during the fire. Without fire emissions, 24-h PM2.5 concentrations for all sites ranged from 1 µgm −3 the fire. Without fire emissions, 24-h PM2.5 concentrations for all sites ranged from 1 µgm Fire 2021, 4, x FOR PEER REVIEW 6 of 12 Fire 2021, 4, x FOR PEER REVIEW 6 of 12 Fire 2021, 4, 31 6 of 12 −3 −3 to 50 µgm . During the wildfire, the 24-h PM2.5 concentrations ranged from 2 µgm to 545 −3 −3 to 50 µgm . During the wildfire, the 24-h PM2.5 concentrations ranged from 2 µgm to 545 −3 µgm . −3 µgm . Figure 4. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 4. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 Figure 4. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Figure 5. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 5. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. Figure 5. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Fire 2021, 4, 31 7 of 12 Fire 2021, 4, x FOR PEER REVIEW 7 of 12 Fire 2021, 4, x FOR PEER REVIEW 7 of 12 Figure 6. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 6. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. Figure 6. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Figure 7. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire growth data were available at the beginning of the fire. Figure 7. 24-Hour PM2.5 concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire Figure 7. 24-Hour PM concentrations with Air Quality Index (AQI) breakpoints for monitoring sites. Note: no daily fire 2.5 growth data were available at the beginning of the fire. growth data were available at the beginning of the fire. Fire 2021, 4, 31 8 of 12 The Central Valley (South) sites consisted of Hanford, Porterville and Visalia (Figure 3). 3 3 Hanford experienced a mean PM2.5 of 9 gm and a PM2.5 maximum of 20 gm before the fire started. During the fire, Hanford’s mean PM2.5 increased to 12 gm and the 3 3 maximum to 32 gm . Before the fire, Porterville had a mean PM2.5 of 8 gm and 3 3 a maximum of 15 gm ; during the fire, the mean PM2.5 increased to 13 gm and 3 3 the maximum increased to 37 gm . Before the fire, Visalia had a mean of 9 gm and a maximum of 17 gm . During the fire, the mean PM2.5 in Visalia increased to 3 3 14 gm and the maximum to 58 gm . The PM2.5 concentrations experienced at all these locations, before and during the fire, were statistically significant, indicating a PM2.5 impact from the Rough Fire. These locations spiked during August 12th–21st and September 7th–14th (Figures S1 and S2). During the latter time, the PM2.5 concentrations reached an AQI of very unhealthy at Visalia. Prior to the fire, in the Sierra Nevada (North), the mean PM2.5 concentrations ranged between 3 and 50 gm . However, when the fire started, the PM2.5 concentration range increased to 2–165 gm . The majority of the sites experienced their first increase in PM2.5 from August 17th to August 31st (Figure 4). AQIs during this time were in the moderate and unhealthy to sensitive groups for PM2.5. The highest levels of PM2.5 occurred during a second spike, which happened from September 4th to September 14th. During this period, the levels reached AQIs of unhealthy and unhealthy for sensitive groups. The concentrations started to decrease after September 20th, and the AQI dropped to the good category after October 20th. For the Sierra Nevada (Central) sites, the only locations that were monitoring the air quality prior to the fire were Pinehurst and Ash Mountain at Sequoia National Park (Figure 5). For the remaining central Sierra Nevada sites, temporary air quality monitoring equipment was installed upon the onset of the fire. Comparing the data available prior to the fire in the Central Sierra Nevada sites, the mean PM2.5 concentration was 8 gm in Pinehurst and 9 gm in Ash Mountain. During the fire, the mean PM2.5 increased to 3 3 21 gm in Pinehurst and to 16 gm at Ash Mountain. During the fire, the mean PM2.5 concentrations at all of the Sierra Nevada (Central) sites ranged from 16–128 gm , with 3 3 24 h maximums ranging from 53 gm to 545 gm . PM2.5 concentrations increased on August 6th and remained high until September 21st; during this period, the daily AQI was often in the unhealthy category and reached the very unhealthy and hazardous levels. The PM2.5 AQI at all sites decreased to the good category after October 15th. Data before the fire started in the Sierra Nevada (South) sites were only available for Kernville (Figure 6). At Kernville, prior to the fire, the mean PM2.5 concentration was 3 3 10 gm and the mean of the 24 h maximum was 13 gm . During the fire, the mean PM2.5 concentration increased to 14 gm , with the mean 24-h maximum increasing to 38 gm . During the fire, at all sites, the mean PM2.5 concentrations ranged from 9–14 gm . The PM2.5 concentrations started to increase on August 3rd, with highs on August 20th. During the fire, the PM2.5 AQIs in these locations stayed in the good and moderate categories. These sites were the least impacted Sierra Nevada air monitoring sites during the Rough Fire. Prior to the fire, the mean PM2.5 concentrations in the Sierra Nevada (East) sites ranged from 6 to 11 gm (Figure 7). During the fire, the mean PM2.5 concentrations 3 3 range increased to 9–15 gm . Bishop experienced a mean PM2.5 of 6 gm and a 3 3 maximum of 20 gm before the fire; and during the fire a mean of 14 gm and 3 3 maximum of 97 gm . Devils Postpile had a mean PM2.5 of 12 gm and maximum of 55 gm before the fire started. During the fire, Devils Postpile’s mean PM2.5 increased to 3 3 15 gm and the maximum increased to 70 gm . Lone Pine experienced a mean PM2.5 3 3 24-h concentration of 7 gm and a maximum of 12 gm before the fire began. During the fire, Lone Pine’s PM2.5 concentration increased to 9 gm and the maximum increased to 27 gm . The PM2.5 concentrations at these sites reached an AQI of unhealthy on three occasions and unhealthy for sensitive groups on five occasions. The air quality improved to an AQI of good at these locations after September 20th. Fire 2021, 4, 31 9 of 12 4. Discussion PM2.5 was seen to increase at many of the sites during the Rough Fire and in some areas reached hazardous air quality levels. The hypothesis of the present study was that the air quality of urban locations in the San Joaquin Valley was impacted by the Rough Fire because of the region’s lower elevation, causing the fire to burn nearer to urban areas. The findings suggest that the smoke from the fire impacted PM2.5 at urban locations in the San Joaquin Valley. These smoke impacts occurred on two occasions and caused AQI to reach an unhealthy level only in Visalia. Previous studies of wildfires on federal lands higher up in the Sierra Nevada have not found significant impacts to PM2.5 in the San Joaquin Valley [24–26]. The Rough Fire was different from these other fires because it primarily burned at a lower elevation and nearer the San Joaquin Valley, and the increased smoke production from this high-intensity wildfire was likely the cause of the increased PM2.5 at the lower elevation sites [10,28]. Similarly to the findings of previous studies, the majority of the impacts occurred at the higher southern Sierra Nevada sites, downwind of dominant transport patterns and east of the San Joaquin Valley. The PM2.5 concentrations observed in the mountain locations were 10 times greater than the ones observed in the San Joaquin Valley, reaching AQIs of hazardous (Figures 2–7). The results of this study indicate that even for this high- intensity forest fire occurring at a lower elevation in the Sierra Nevada, the largest smoke impacts are observed at the more rural mountain communities closer to and downwind of the fire. 4.1. Case-Crossover Analysis The present study conducted an epidemiological analysis (case-crossover analysis) to understand if the exposure to PM2.5 concentrations before and during the fire would have an impact on the health (respiratory diseases) of residents in urban locations. This analysis was only conducted for the San Joaquin Valley residents. The association was only found for PM2.5 exposure and asthma ED visits before the fire started [OR: 1.195 (95% CI: 1.001, 1.427)]. During the fire there was a decrease in asthma ED visits (OR: 0.327 (95% CI: 0.177–0.604) for every 10 g/m increase in PM2.5. No other associations between PM2.5 and ED visits due to the other respiratory diseases were found for the during-wildfire and pre-wildfire periods. A possible explanation for the lack of association, even with the increase of PM2.5 during the fire, is the robust smoke communication at the local, state, and federal levels. News releases and media warnings for residents on the risk of smoke exposure were widespread, in addition to the smoke-educated public in this smoke-prone area. Smoke alerts and health advisories put out by air regulators and fire managers informed residents and potentially allowed them to limit their personal exposure to PM2.5 by spending more time indoors or avoiding outdoor activities during the highest hours of ambient PM2.5. The purpose of this paper is not to conduct a health assessment. A more focused study is needed to investigate and confirm these findings. Another limitation of this assessment was the fact that the mountain locations that experienced the highest impact to PM2.5 from smoke did not have enough cases to be included in the epidemiological analysis because of the combination of lower population densities in these areas and the relatively short duration of smoke exposure. Future studies using more fires with known impacts from smoke in these less densely populated rural areas are needed to understand if there are effects at these locations during periods of wildland fire smoke. 4.2. Smoke Management Implications Wildland fire is inevitable in the fire prone ecosystems of California. Smoke managers should prioritize having smoke-educated and prepared communities, where individuals are encouraged to have air filters for use during a wildfire and can easily access timely predictive information on local smoke conditions during the incident. Large high-intensity wildfires appear to be the new normal in California in these lower elevation areas nearer urban areas. The smoke from these fires is of great concern to Fire 2021, 4, 31 10 of 12 the foothill communities. Additionally, foothill communities experience smoke from fires that are more typical of the historic normal and may become averse to all wildland fire smoke. Education and the communication of the need for some smoke exposure to limit large smoke events is essential for an effective smoke management in this area. 5. Conclusions Smoke from the Rough Fire, a lower-elevation, large, and high-intensity wildfire, reached the San Joaquin Valley sites, impacting PM2.5 on two occasions. PM2.5 increased at many of the sites during the wildfire, especially when the fire was consuming large areas. The PM2.5 levels in the Sierra Nevada locations reached a hazardous AQI. Similarly to previous studies, the largest smoke impacts were observed at the more rural mountain communities closer to and downwind of the fire. These findings suggest smoke managers should expect large high-intensity wildland fires that occur when suppression fails, particu- larly those occurring at lower elevations, to have an increased potential of exposure for the higher concentrated populations in areas of the San Joaquin Valley. Smoke management policies should adjust their limited resources to focus on the communication to rural areas where the largest smoke impacts occur, along with educating the general public on the importance of routinely allowing fire within the historic size and intensity levels in this fire-prone ecosystem and the seemingly paradoxical benefits of reduced smoke exposure over time through this approach. More research is needed to see if there is an elevation threshold for smoke impacts to the urban areas from fires with a size and intensity that are more typical of the historic normal, particularly in the federally protected wilderness, that could help air and land managers to better assess the risk to air quality from smoke. Furthermore, the increase in PM2.5 during the fire did not create a subsequent impact to ED visits for asthma and other respiratory diseases in the Central Valley. This needs to be further studied, to confirm the findings, and expanded, to include rural communities more heavily impacted by smoke. The role smoke alerts and health advisories played in informing residents and allowing them to avoid outdoor activities during the times of the highest smoke levels needs a more thorough assessment. These air quality advisories during an event, along with pre-fire season planning for residential air filter use during a smoke event, are potentially vital tools in protecting human health from wildland fire smoke, particularly during the large high-intensity fires. Supplementary Materials: The followings are available online at https://www.mdpi.com/article/ 10.3390/fire4030031/s1. Author Contributions: Conceptualization, writing—review & editing R.C. and D.S.; formal analysis, software, and data curation, H.G. and P.T.; review & editing, D.V. and K.N. All authors have read and agreed to the published version of the manuscript. 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Journal

Fire – Multidisciplinary Digital Publishing Institute

Published: Jun 22, 2021

Keywords: Rough Fire; air quality; California; particulate matter; wildfire

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