Michael P. Hannigan

Bio: Michael P. Hannigan is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Air quality index & Stove. The author has an hindex of 37, co-authored 121 publications receiving 4716 citations. Previous affiliations of Michael P. Hannigan include University of California, Davis & Kansas State University.

Characterization of Primary Organic Aerosol Emissions from Meat Cooking, Trash Burning, and Motor Vehicles with High-Resolution Aerosol Mass Spectrometry and Comparison with Ambient and Chamber Observations

Abstract: Organic aerosol (OA) emissions from motor vehicles, meat-cooking and trash burning are analyzed here using a high-resolution aerosol mass spectrometer (AMS). High resolution data show that aerosols emitted by combustion engines and plastic burning are dominated by hydrocarbon-like organic compounds. Meat cooking and especially paper burning emissions contain significant fractions of oxygenated organic compounds; however, their unit-resolution mass spectral signatures are very similar to those from ambient hydrocarbon-like OA, and very different from the mass spectra of ambient secondary or oxygenated OA (OOA). Thus, primary OA from these sources is unlikely to be a significant direct source of ambient OOA. There are significant differences in high-resolution tracer m/zs that may be useful for differentiating some of these sources. Unlike in most ambient spectra, all of these sources have low total m/z 44 and this signal is not dominated by the CO2+ ion. All sources have high m/z 57, which is low during hi...

Seasonal variability in bacterial and fungal diversity of the near-surface atmosphere.

Abstract: Bacteria and fungi are ubiquitous throughout the Earth's lower atmosphere where they often represent an important component of atmospheric aerosols with the potential to impact human health and atmospheric dynamics. However, the diversity, composition, and spatiotemporal dynamics of these airborne microbes remain poorly understood. We performed a comprehensive analysis of airborne microbes across two aerosol size fractions at urban and rural sites in the Colorado Front Range over a 14-month period. Coarse (PM10-2.5) and fine (PM2.5) particulate matter samples were collected at weekly intervals with both bacterial and fungal diversity assessed via high-throughput sequencing. The diversity and composition of the airborne communities varied across the sites, between the two size fractions, and over time. Bacteria were the dominant type of bioaerosol in the collected air samples, while fungi and plants (pollen) made up the remainder, with the relative abundances of fungi peaking during the spring and summer months. As bacteria made up the majority of bioaerosol particles, we analyzed the bacterial communities in greater detail using a bacterial-specific 16S rRNA gene sequencing approach. Overall, bacterial taxonomic richness and the relative abundances of specific bacterial taxa exhibited significant patterns of seasonality. Likewise, airborne bacterial communities varied significantly between sites and across aerosol size fractions. Source-tracking analyses indicate that soils and leaves represented important sources of bacteria to the near-surface atmosphere across all locations with cow fecal bacteria also representing an important source of bioaerosols at the more rural sites during early fall and early spring. Together, these data suggest that a complex set of environmental factors, including changes in atmospheric conditions and shifts in the relative importance of available microbial sources, act to control the composition of microbial bioaerosols in rural and urban environments.

The next generation of low-cost personal air quality sensors for quantitative exposure monitoring

Abstract: Advances in embedded systems and low-cost gas sensors are enabling a new wave of low-cost air quality monitoring tools Our team has been engaged in the development of low-cost, wearable, air quality monitors (M-Pods) using the Arduino platform These M-Pods house two types of sensors – commercially available metal oxide semiconductor (MOx) sensors used to measure CO, O3, NO2, and total VOCs, and NDIR sensors used to measure CO2 The MOx sensors are low in cost and show high sensitivity near ambient levels; however they display non-linear output signals and have cross-sensitivity effects Thus, a quantification system was developed to convert the MOx sensor signals into concentrations We conducted two types of validation studies – first, deployments at a regulatory monitoring station in Denver, Colorado, and second, a user study In the two deployments (at the regulatory monitoring station), M-Pod concentrations were determined using collocation calibrations and laboratory calibration techniques M-Pods were placed near regulatory monitors to derive calibration function coefficients using the regulatory monitors as the standard The form of the calibration function was derived based on laboratory experiments We discuss various techniques used to estimate measurement uncertainties The deployments revealed that collocation calibrations provide more accurate concentration estimates than laboratory calibrations During collocation calibrations, median standard errors ranged between 40–61 ppb for O3, 64–84 ppb for NO2, 028–044 ppm for CO, and 168 ppm for CO2 Median signal to noise (S / N) ratios for the M-Pod sensors were higher than the regulatory instruments: for NO2, 36 compared to 234; for O3, 14 compared to 16; for CO, 11 compared to 100; and for CO2, 422 compared to 300–500 By contrast, lab calibrations added bias and made it difficult to cover the necessary range of environmental conditions to obtain a good calibration A separate user study was also conducted to assess uncertainty estimates and sensor variability In this study, 9 M-Pods were calibrated via collocation multiple times over 4 weeks, and sensor drift was analyzed, with the result being a calibration function that included baseline drift Three pairs of M-Pods were deployed, while users individually carried the other three The user study suggested that inter-M-Pod variability between paired units was on the same order as calibration uncertainty; however, it is difficult to make conclusions about the actual personal exposure levels due to the level of user engagement The user study provided real-world sensor drift data, showing limited CO drift (under −005 ppm day−1), and higher for O3 (−26 to 20 ppb day−1), NO2 (−156 to 051 ppb day−1), and CO2 (−42 to 31 ppm day−1) Overall, the user study confirmed the utility of the M-Pod as a low-cost tool to assess personal exposure

Respeciation of organic gas emissions and the detection of excess unburned gasoline in the atmosphere

Abstract: The development of a set of organic gas composition profiles for key source categories is described. This information is used to recompute the organic gas emission inventory for the Los Angeles area. Comparisons are made between the revised emission inventory and ambient concentration measurements in southern California. Respeciation of the organic gas emissions results in large changes in the basinwide emissions estimates for many individual organic species, including l,3-butadiene, ethylene glycol, methanol, and cyclohexane. Significant changes are observed in the reactivity of the chemical composition profiles for individual source categories, especially for surface-coating activities and associated thinning solvent use. Receptor-modeling methods are used to identify the relative importance of major sources that contribute to atmospheric organic gas concentrations in southern California. The receptor modeling results indicate a key discrepancy between the emission inventory and ambient data: there is much more unburned gasoline in the atmosphere than is indicated in the emission inventory. These excess unburned gasoline emissions may be coming from a combination of sources including tailpipe emissions, hot-soak evaporative emissions, and fuel spillage.

ARIEL: automatic wi-fi based room fingerprinting for indoor localization

Abstract: People spend the majority of their time indoors, and human indoor activities are strongly correlated with the rooms they are in. Room localization, which identifies the room a person or mobile phone is in, provides a powerful tool for characterizing human indoor activities and helping address challenges in public health, productivity, building management, etc. Existing room localization methods, however, require labor-intensive manual annotation of individual rooms. We present ARIEL, a room localization system that automatically learns room fingerprints based on occupants' indoor movements. ARIEL consists of (1) a zone-based clustering algorithm that accurately identifies in-room occupancy "hotspot(s)" using Wi-Fi signatures; (2) a motion-based clustering algorithm to identify inter-zone correlation, thereby distinguishing different rooms; and (3) an energy-efficient motion detection algorithm to minimize the noise of Wi-Fi signatures. ARIEL has been implemented and deployed for real-world testing with 21 users over a 10-month period. Our studies show that it supports room localization with higher than 95% accuracy without requiring labor-intensive manual annotation.

Bounding the role of black carbon in the climate system: A scientific assessment

Abstract: Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg yr−1 in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W m−2 with 90% uncertainty bounds of (+0.08, +1.27) W m−2. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W m−2. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W m−2 with 90% uncertainty bounds of +0.17 to +2.1 W m−2. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W m−2, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (−0.50 to +1.08) W m−2 during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (−0.06 W m−2 with 90% uncertainty bounds of −1.45 to +1.29 W m−2). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

An inventory of gaseous and primary aerosol emissions in Asia in the year 2000 : NASA global tropospheric experiment transport and chemical evolution over the pacific (TRACE-P): Measurements and analysis (TRACEP1)

Abstract: [i] An inventory of air pollutant emissions in Asia in the year 2000 is developed to support atmospheric modeling and analysis of observations taken during the TRACE-P experiment funded by the National Aeronautics and Space Administration (NASA) and the ACE-Asia experiment funded by the National Science Foundation (NSF) and the National Oceanic and Atmospheric Administration (NOAA). Emissions are estimated for all major anthropogenic sources, including biomass burning, in 64 regions of Asia. We estimate total Asian emissions as follows: 34.3 Tg SO 2 , 26.8 Tg NO x , 9870 Tg CO 2 , 279 Tg CO, 107 Tg CH 4 , 52.2 Tg NMVOC, 2.54 Tg black carbon (BC), 10.4 Tg organic carbon (OC), and 27.5 Tg NH 3 . In addition, NMVOC are speciated into 19 subcategories according to functional groups and reactivity. Thus we are able to identify the major source regions and types for many of the significant gaseous and particle emissions that influence pollutant concentrations in the vicinity of the TRACE-P and ACE-Asia field measurements. Emissions in China dominate the signature of pollutant concentrations in this region, so special emphasis has been placed on the development of emission estimates for China. China's emissions are determined to be as follows: 20.4 Tg SO 2 , 11.4 Tg NO x , 3820 Tg CO 2 , 116 Tg CO, 38.4 Tg CH 4 , 17.4 Tg NMVOC, 1.05 Tg BC, 3.4 Tg OC, and 13.6 Tg NH 3 . Emissions are gridded at a variety of spatial resolutions from 1° × 1° to 30 s x 30 s, using the exact locations of large point sources and surrogate GIS distributions of urban and rural population, road networks, landcover, ship lanes, etc. The gridded emission estimates have been used as inputs to atmospheric simulation models and have proven to be generally robust in comparison with field observations, though there is reason to think that emissions of CO and possibly BC may be underestimated. Monthly emission estimates for China are developed for each species to aid TRACE-P and ACE-Asia data interpretation. During the observation period of March/ April, emissions are roughly at their average values (one twelfth of annual). Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of ±16% for SO 2 to a high of ±450% for OC.

Chemical and microphysical characterization of ambient aerosols with the aerodyne aerosol mass spectrometer

Abstract: The application of mass spectrometric techniques to the realtime measurement and characterization of aerosols represents a significant advance in the field of atmospheric science. This review focuses on the aerosol mass spectrometer (AMS), an instrument designed and developed at Aerodyne Research, Inc. (ARI) that is the most widely used thermal vaporization AMS. The AMS uses aerodynamic lens inlet technology together with thermal vaporization and electron-impact mass spectrometry to measure the real-time non-refractory (NR) chemical speciation and mass loading as a function of particle size of fine aerosol particles with aerodynamic diameters between similar to 50 and 1,000 nm. The original AMS utilizes a quadrupole mass spectrometer (Q) with electron impact (EI) ionization and produces ensemble average data of particle properties. Later versions employ time-of-flight (ToF) mass spectrometers and can produce full mass spectral data for single particles. This manuscript presents a detailed discussion of the strengths and limitations of the AMS measurement approach and reviews how the measurements are used to characterize particle properties. Results from selected laboratory experiments and field measurement campaigns are also presented to highlight the different applications of this instrument. Recent instrumental developments, such as the incorporation of softer ionization techniques (vacuum ultraviolet (VUV) photo-ionization, Li(+) ion, and electron attachment) and high-resolution ToF mass spectrometers, that yield more detailed information about the organic aerosol component are also described. (c) 2007 Wiley Periodicals, Inc.

A Survey of Indoor Localization Systems and Technologies

Abstract: Indoor localization has recently witnessed an increase in interest, due to the potential wide range of services it can provide by leveraging Internet of Things (IoT), and ubiquitous connectivity. Different techniques, wireless technologies and mechanisms have been proposed in the literature to provide indoor localization services in order to improve the services provided to the users. However, there is a lack of an up-to-date survey paper that incorporates some of the recently proposed accurate and reliable localization systems. In this paper, we aim to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time of flight (RTOF), and received signal strength (RSS); based on technologies, such as WiFi, radio frequency identification device (RFID), ultra wideband (UWB), Bluetooth, and systems that have been proposed in the literature. This paper primarily discusses localization and positioning of human users and their devices. We highlight the strengths of the existing systems proposed in the literature. In contrast with the existing surveys, we also evaluate different systems from the perspective of energy efficiency, availability, cost, reception range, latency, scalability, and tracking accuracy. Rather than comparing the technologies or techniques, we compare the localization systems and summarize their working principle. We also discuss remaining challenges to accurate indoor localization.