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Aerosol Particle Statistics During Wildfire Events and Their Impact on Air

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Aerosol Particle Statistics During Wildfire Events and Their Impact on Air University of Nevada, Reno Aerosol particle statistics during wildfire events and their impact on air quality in Reno, NV A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Atmospheric Science by Grzegorz Swistak Dr. Andrey Y. Khlystov/Thesis Advisor August 2019 Copyright by Grzegorz Swistak 2019 © All Rights Reserved THE GRADUATE SCHOOL We recommend that the thesis prepared under our supervision by Entitled be accepted in partial fulfillment of the requirements for the degree of , Advisor , Committee Member , Graduate School Representative David W. Zeh, Ph.D., Dean, Graduate School i ABSTRACT Ambient aerosol examination is an important task for a number of reasons, including air pollution, public health impacts, visibility and climate change. While there are numerous studies relating the direct impact of small airborne particles on the above-mentioned fields, not much information exists on the impact of wildfire on urban aerosol properties. This research focuses on the investigating differences between measured urban aerosol size parameters between wildfire events and periods unaffected by fire plumes in Reno, NV, as well as what implications these differences might have on Reno’s environmental conditions and human health. In order to achieve that, a Scanning Mobility Particle Sizer (SMPS) instrument was installed inside the Desert Research Institute (DRI) building in Northern Reno, Nevada. The SMPS operated constantly between July 13th of 2017 and August 13th of 2018. The aerosol data was then downloaded, converted and analyzed using Python scripts in order to visualize and compare the variability of the air particle statistics and how it relates to forest fire smoke impacts. Particle number mean volume concentration was on average 13 to 15 times higher during the wildfire events, than that of the non-wildfire baseline events samples. ii ACKNOWLEDGEMENTS Group of people helped me made this research possible, therefore I would like to extend my gratitude to everyone involved. I want to thank my advisor, Dr. Andrey Khlystov for his patience, assistance, guidance and for providing me with all the supplementary knowledge needed to understand and finish this project. I would like to thank my committee members, Dr. Vera Samburova and Dr. Patrick Arnott for their mentorship, shared knowledge and assistance with the obstacles I encountered along the way. I also want to thank my fellow students and colleagues from the Desert Research Institute and from the University of Nevada, Reno for their invaluable assistance, primarily Chiranjivi Bhattarai, who was crucially involved with the instrumentation preparation, set up and maintenance and Hatef Firouzkouhi for his knowledge and assistance with coding. My sincere thanks and appreciation go to my other fellow students and peers from the Organic Analytical Lab, who were always helpful and offered any assistance possible – Yeongkwon, Irina, Deep, Megan and Kevin. Lastly, I would like to thank my family, especially my wife Alicja and cousin Beata for their help and support. iii TABLE OF CONTENTS ABSTRACT i ACKNOWLEDGEMENTS ii TABLE OF CONTENTS iii LIST OF TABLES iv LIST OF FIGURES v INTRODUCTION 1 METHODS 4 Measurement equipment and SMPS Principles 4 Data analysis 5 Wildfires and aerosol particle statistics 6 RESULTS 8 Detwiler Fire: July 16th, 2017 – August 24th, 2017 10 October 2017 Northern California wildfires: October 8th, 2017 – October 31st, 2017 14 Ferguson & Carr fires: July 13th, 2018 – August 30th, 2018 18 July 4th, 2018 23 CONCLUSIONS / DISCUSSION 26 REFERENCES 28 iv LIST OF TABLES Table 1 Event dates selected for particle statistics analysis, based on high total volume concentration. 7 Table 2 National Ambient Air Quality Standards (as of January 1, 2019). 8 Table 3 Detwiler Fire total number concentration and total volume concentration statistics. 13 Table 4 October 2017 Northern California wildfires total number concentration and total volume concentration statistics. 17 Table 5 Ferguson and Carr wildfires total number concentration and total volume concentration statistics. 21 Table 6 July 4th, 2018 total number concentration and total volume concentration statistics. 24 v LIST OF FIGURES Figure 1 SMPS design schematics. Data from: Wang and Flagan (2002). 5 Figure 2 Monthly Air Quality Index Summary of PM2.5. Source: 2009-18 Washoe County, Nevada Air Quality Trends Report. Air Quality Management Division. 9 Figure 3 Monthly Air Quality Index Summary of PM2.5. Source: 2008-17 Washoe County, Nevada Air Quality Trends Report. Air Quality Management Division. 10 Figure 4 EPA’s Air Quality Index map for 07/15/2017, corresponding to the Baseline 1 data from SMPS. 11 Figure 5 EPA’s Air Quality Index map for 07/16/2017, corresponding to the Plume 1 data from SMPS. 11 Figure 6 EPA’s Air Quality Index map for 07/19/2017, corresponding to the Plumes 2 and 3 data from SMPS. 11 Figure 7 Total number concentration and total volume concentration of aerosol particles over time during Detwiler Fire. 12 Figure 8 Aerosol particle size distribution (PSD) for Detwiler Fire. 14 Figure 9 EPA’s Air Quality Index map for 10/11/2017, corresponding to the Plume 1 data from SMPS. 15 Figure 10 EPA’s Air Quality Index map for 10/10/2017, corresponding to the Baseline 1 data from SMPS. 15 Figure 11 EPA’s Air Quality Index map for 10/12/2017, corresponding to the Baseline 2 data from SMPS. 16 Figure 12 Total number concentration and total volume concentration of aerosol particles over time during October 2017 Northern California wildfires. 16 Figure 13 Aerosol particle size distribution (PSD) for October 2017 Northern California wildfires. 18 Figure 14 EPA’s Air Quality Index map for 08/02/2018, corresponding to the Baseline 1 data from SMPS. 19 Figure 15 EPA’s Air Quality Index map for 08/03/2018, corresponding to the Plume 1 data from SMPS. 20 Figure 16 EPA’s Air Quality Index map for 08/04/2018, corresponding to the Plume 2 data from SMPS. 20 Figure 17 Total number concentration and total volume concentration of aerosol particles over time during Ferguson and Carr wildfires. 21 Figure 18 Aerosol particle size distribution (PSD) for Ferguson and Carr wildfires. 22 Figure 19 EPA’s Air Quality Index map for 07/04/2018. 23 Figure 20 Total number concentration and total volume concentration of aerosol particles over time during the 4th of July weekend. 24 Figure 21 Aerosol particle size distribution (PSD) for 4th of July 2018. 25 1 INTRODUCTION Daily increases in particulate matter (PM) mass have been researched and established to have direct impact on increases in morbidity and mortality (L Bell, 2012). Studies clearly showed that PM is associated with negative human health effects (Bernard, Samet, Grambsch, Ebi, & Romieu, 2001), which include increased hospital admissions and emergency room visits, respiratory infections, wheezing and exacerbation of asthma, chronic bronchitis and chronic obstructive pulmonary disease (COPD), cardiovascular diseases, decreased lung function and premature mortality (National Center for Environmental Assessment (Research Triangle Park N.C.), 2009). Certain groups, like children, older adults, people with pre-existing heart or lung diseases, people with diabetes are most likely to be affected by the increased particulate matter pollution (Zanobetti, Schwartz, & Gold, 2000). PM exposure can be manifested by temporary symptoms like eye, nose and throat irritation, shortness of breath, cough, phlegm, chest tightness, asthma attacks, acute bronchitis, respiratory infections, heart attack or arrythmia (National Center for Environmental Assessment (Research Triangle Park N.C.), 2009). People with lung diseases may experience additional symptoms, including trouble breathing, wheezing, chest discomfort and unusual fatigue (United States. Environmental Protection Agency. Office of Air and Radiation. & AIRNow Program (U.S.), 2003). According to the World Health Organization (WHO) the PM2.5 poses greater risk to mortality, mainly as a result of long-term exposure, than the coarse particles in the PM10 group (World Health Organization, 2013). Long-term exposure to the PM2.5 pollution can lead to reduced lung function, chronic bronchitis and premature death or reduced life expectancy. Such consistent exposure is estimated to reduce the life expectancy by approximately 8.6 months on average in the European region (World Health Organization, 2013). There is a clear association of airborne PM2.5 2 and adverse cardiovascular and respiratory effect on human health (Brook et al., 2010). Even small 3 increases in daily averaged PM2.5 levels, like 10 μg/m can inflate the risk of all-cause mortality by 0.8% (Janssen, Fischer, Marra, Ameling, & Cassee, 2013). PM also contributes to haze and visibility deterioration and can harm the environment by changing the chemical composition of soil (National Center for Environmental Assessment (Research Triangle Park N.C.), 2009). Air suspended particles are the overwhelming source for scattering and absorption of light, leading directly to visibility impairment. When it comes to scattering, leading to the light extinction, larger aerosols scatter more light than smaller particles of the same composition and similar shape. However the amount of light scattered in relation to mass is greatest for aerosol particles with size diameters between 0.3 and 1.0 μm (National Center for Environmental Assessment (Research Triangle Park N.C.), 2009). It is also important to look at another aspect of aerosols - their
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