Browsing by Subject "Atmospheric chemistry"

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Anthropogenic influence on the fate of secondary organic aerosol : chlorine chemistry and alkane oxidation
(2022-10-06) Wang, Dongyu; Hildebrandt Ruiz, Lea; Allen, David T; Donahue, Neil M; Rochelle, Gary T; Xu, Ying
Oxidation of volatile organic compounds (VOC) in the atmosphere leads to the formation of secondary organic aerosol (SOA), which can have extensive impacts on air quality, health, and climate. Existing air quality models used to describe the fate of ambient organic aerosol tend to underpredict the aerosol oxidation state. In addition, modeled concentrations of nitrogen oxides (NO [subscript x]) and other reactive nitrogen compounds (NO [subscript y]), including alkyl nitrates, often deviate from field observations. Certain SOA formation pathways, SOA ageing mechanisms, and alkyl nitrate decay mechanisms may be missing. Recent field studies show that NO [subscript x]-mediated heterogeneous production of nitryl chloride, ClNO₂, could provide a ubiquitous source for chlorine atoms. Little is known about the role of chlorine atoms in SOA formation and ageing, or their interaction with other anthropogenic emissions found in polluted environments, where alkane oxidation chemistry is important. Environmental chamber experiments are carried out to address knowledge gaps in atmospheric chlorine and alkane oxidation chemistry. Results show that chlorine-initiated oxidation of isoprene leads to SOA formation, organic chloride formation, and possibly secondary HO [subscript x] chemistry. Alkane-derived alkyl nitrate compounds are found not to hydrolyze appreciably in humid environments or in the presence of acidic aerosol. Uptake of inorganic nitrate and inorganic chloride are observed in the presence of deliquescent particles. Chlorine-initiated oxidation of linear alkanes is shown to result in prompt SOA formation and delayed organic chloride formation, which is enabled by the addition of chlorine radical to dihydrofuran, a heterogeneously produced multi-generational oxidation product. Improvements are made for the detection of organic chloride using aerosol mass spectrometry, and for aerosol volatility measurements using temperature programmed thermal desorption techniques. A two-dimensional thermogram framework is developed to visualize aerosol composition, aerosol volatility, and thermal fragmentation simultaneously.
Factors influencing ambient particulate matter : from Texas to New Delhi
(2022-05-03) Patel, Kanan; Hildebrandt Ruiz, Lea; Allen, David T; Apte, Joshua S; Sharma, Mukul M
Long term exposure to particulate matter (PM) has been linked to an increase in mortality and cardiorespiratory diseases. In addition, PM affects Earth’s radiative balance, and is one of the main sources of uncertainty in climate change predictions. Hence, it is imperative to understand PM composition and concentrations and the factors contributing to their variability. Different parts of the world experience different levels of air pollution, due to an interplay between various factors including sources, meteorological factors, and chemical transformations. PM can either be directly emitted into the atmosphere (primary) or can be generated as result of oxidation of gas-phase precursors leading to the formation and partitioning of low volatility products to the particle phase (secondary). The nature, sources and dynamics of PM can be estimated by combining ambient field measurements with receptor modeling, machine learning and statistical analysis tools. The objective of my thesis is to understand the factors influencing PM concentration and composition in different environments. In chapter 2, I have reported the results of the measurements in Austin, Texas, one of the fastest growing metropolitan cities in the U.S. I used several modeling and data analysis tools to understand the sources and formation of particulate matter in Austin including positive matrix factorization (PMF), the Extended Aerosol Thermodynamics Model (E-AIM) and air back trajectory analysis using HYSPLIT. Through my analysis, I demonstrated that photochemistry is an important factor in governing PM composition in Austin. We observed rapid photochemical processing of traffic emissions, H₂SO₄-driven new particle formation (NPF) events, production of organic nitrate, and daytime peaks in the locally formed oxidized organic aerosol during the summer period. My analysis also suggested that SO₂ emissions from cement kilns may be the main source of particulate sulfate observed at this receptor site, pointing toward the need for measurements at the source to investigate this further. This chapter has been published in ACS Earth and Space Chemistry. Meanwhile, Delhi (India) is the most polluted megacity in the world and routinely experiences extreme pollution episodes. Our group is one of the first in the world to measure long term PM composition at high time resolution in the city. As part of the Delhi Aerosol Supersite (DAS) study, we have recorded over five years of near-continuous PM composition to understand inter-seasonal as well as inter-annual variability in the PM concentrations and the factors influencing them. I have studied specific “special” events which have implications for policy decisions. In chapter 3, I have investigated the factors influencing high PM concentrations observed during the autumn (~Sep – Nov) season which experiences some of the most extreme pollution episodes observed anywhere in the world. I combined our measurements with data obtained from regulatory monitoring sites (CO, NOₓ, PM₂.₅) to gain insights from the temporal trends of the pollutants and to demonstrate the differences between autumn and winter, which also experiences high concentrations. I incorporated receptor models and non-parametric wind regression to understand the nature and sources of PM during this period. Further, I used meteorological data such as temperature, planetary boundary layer height, wind speed/direction and relative humidity to understand their impact on PM using statistical hypothesis testing. Using these tools, I demonstrated the influence of regional agricultural burning (from the neighboring states) and fireworks during the festival of Diwali on PM during this season. Overall, my analysis provided detailed insights into the sources and dynamics of PM during one of the most polluted seasons in Delhi (and in the world) and provided a direction for future studies in the region. This chapter has also been published in ACS Earth and Space Chemistry. In chapter 4, I have investigated the impact of COVID-19 lock-down on Delhi's air quality by combining PM and gas phase data of over four years with robust statistical analysis, including the method of “robust differences” to account for seasonal variability in the pollutant concentrations. My analysis suggests that future large-scale modification of activity restrictions in Delhi may impact the primary pollutants (NOₓ, CO, black carbon) more than the secondary pollutants, emphasizing the fundamental importance of secondary or regional pollutants on air quality in Delhi. I showed that overall, future strict activity reductions may lead to only a moderate reduction in PM₁, reflective of complex PM₁ chemistry and the need for integrative, multiscale, and multisectoral policies to address the major air pollution challenge in Delhi. This chapter has been published in ACS Environmental Science & Technology Letters. Because of the interplay between sources and meteorology in Delhi, in chapter 5 I have developed machine learning models incorporating random forest regression that estimate the concentrations of PM₁ and its constituents by using meteorology and emission proxies. I have demonstrated the applicability of these models to capture temporal variability of the PM₁ species, to understand the influence of individual factors via sensitivity analyses, and to separate impacts of the COVID-19 lockdowns and associated activity restrictions from impacts of other factors. Overall, these models provide new insights into the factors influencing ambient PM₁ in New Delhi, India, demonstrating the power of machine learning models in atmospheric science applications. This chapter will be submitted to Aerosol Science and Technology. My research has advanced our understanding about PM formation and processing in different environments. These novel measurements and analyses will help guide future studies aimed at understanding and improving ambient air quality in these regions. Furthermore, the results of my scientific analyses may help guide policy decisions aimed at reducing PM levels in the atmosphere, thus helping improve the lives of millions of people.
Photochemistry of atmospherically relevant association reaction products
(2005) Flowers, Bradley Alan; Stanton, John (John F.)
The work described herein relates to the long and short lived products of association reactions. These reactions are defined most generally as A + B AB . Specifically in Earth’s atmosphere the rates of such reactions and the subsequent chemistry of AB are defined by local conditions. In this work we are specifically interested in two such reactions. The first is the combination of acetyl peroxy radical with NO2 to form peroxyacetyl nitrate (PAN), viz CH3C(O)OO + NO2 + M = CH3C(O)OONO2 + M PAN is a uniquely stable molecule and its formation allows the transport of NO2 to regions far from its source. The subsequent decomposition of PAN releases NO2 which can effect regional ozone levels. Nitrate radical quantum yield measurements for PAN have been performed. The nitrate radical quantum yield is measured relative to N2O5 photolysis, detecting NO3 via cavity ring-down absorption measurements. Additionally, ab initio electronic structure calculations have been performed on PAN and peroxynitric acid (PNA, HO2NO2) to investigate salient aspects of electronic excitation in these related peroxy nitrate species. The theoretical and experimental results are used to understand (1.) PAN photochemistry in the atmosphere and (2.) general properties of ROONO2 photo-excitation. The second reaction is the formation of a hydrogen-bound complex. HO2 + HOOH HO2-HOOH The formation of these types of complexes can effect both reaction kinetics and photochemical properties of both species. In this case, the complex is formed via two hydrogen bonding interactions between HO2 and HOOH. We use theoretical methods to predict the binding energy, thermochemistry, vibrational frequencies and associated shifts, and excitation energies for an HO2-HOOH hydrogen bonded complex. The effects of complex formation are discussed in terms of both laboratory and atmospheric effects. The final chapter deals with our continued work in calculations of highly accurate thermochemical properties for both closed and open shell species. We have developed a theoretical model chemistry capable of sub-kcal mol−1 accuracy for thermochemical properties of closed and open shell species. We named the method High Accuracy Extrapolated Ab Initio Thermochemisry, or HEAT. The development of the method and its performance on a test