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The Michigan-Ontario Ozone Source Experiment (MOOSE)

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 27091

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Special Issue Editors

Dr. Eduardo (Jay) Olaguer

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Guest Editor

Michigan Department of Environment Great Lakes and Energy, Air Quality Division, Lansing, MI 48909, USA
Interests: meteorology; atmospheric chemistry; air quality; modeling; measurements

Dr. Yushan Su

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Guest Editor

Ontario Ministry of the Environment, Conservation and Parks, Toronto, ON M9P 3V6, Canada
Interests: ambient air monitoring; traffic-related air pollution; trend analysis; emerging monitoring techniques

Special Issue Information

Dear Colleagues,

Air quality in the border region between the state of Michigan and the province of Ontario is of great concern to both the United States and Canada. Southeast Michigan is currently designated as in nonattainment of the U.S. federal ozone standard, while many locations in southern Ontario frequently exceed the Canadian ozone standard. To ensure a viable ozone attainment strategy, both in the short and long term, regulatory and scientific agencies, including the Michigan Department of Environment, Great Lakes, and Energy (EGLE), the Ontario Ministry of the Environment, Conservation, and Parks (MECP), the U.S. Environmental Protection Agency (USEPA), Environment and Climate Change Canada (ECCC), and other partners, have decided to conduct a field study known as the Michigan-Ontario Ozone Source Experiment (MOOSE) in 2021 and 2022. This Special Issue is dedicated to scientific findings from the first year of MOOSE.

MOOSE has three components. The first component, the Great Lakes Meteorology and Ozone Recirculation (GLAMOR) sub-experiment, deals with the physics and chemistry of land–lake atmospheric circulations and their influence on regional oxidative capacity, including the role of reactive nitrogen reservoirs such as HONO. The second, called the Chemical Source Signatures (CHESS) sub-experiment, characterizes emissions of ozone precursors and air toxins (e.g., formaldehyde) from industrial point sources and their ambient concentration impacts on fine to regional scales. The third component, Methane Releases from Landfills and Gas Lines (MERLIN), examines the role of large methane leaks in enhancing the amount of ozone formed from surrounding emissions of more reactive Volatile Organic Compounds (VOCs) and nitrogen oxides (NOx).

The papers in this Special Issue are devoted to the experimental methods and data interpretation methods, including real-time measurements and advanced modeling approaches, used during MOOSE, and the latest scientific conclusions drawn from these that may enhance ozone attainment strategies in the border region.

Dr. Eduardo (Jay) Olaguer
Dr. Yushan Su
Guest Editors

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Keywords

ozone
air quality
monitoring
modeling
remote sensing
methane
VOCs
NOx
real-time measurements
land–lake breezes

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Published Papers (13 papers)

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Research

18 pages, 3501 KiB

Open AccessArticle

Mobile Laboratory Investigations of Industrial Point Source Emissions during the MOOSE Field Campaign

by Tara I. Yacovitch, Brian M. Lerner, Manjula R. Canagaratna, Conner Daube, Robert M. Healy, Jonathan M. Wang, Edward C. Fortner, Francesca Majluf, Megan S. Claflin, Joseph R. Roscioli, Elizabeth M. Lunny and Scott C. Herndon

Atmosphere 2023, 14(11), 1632; https://doi.org/10.3390/atmos14111632 - 30 Oct 2023

Cited by 4 | Viewed by 1217

Abstract

Industrial emissions of trace gases and VOCs can be an important contributor to air quality in cities. Disentangling different point sources from each other and characterizing their emissions can be particularly challenging in dense industrial areas, such as Detroit, Dearborn and surrounding areas in Southeast Michigan (SEMI). Here, we leverage mobile measurements of trace gases and speciated volatile organic compounds (VOCs) to identify emitting sites. We characterize their complicated emissions fingerprints based on a core set of chemical ratios. We report chemical ratios for 7 source types including automakers, steel manufacturers, chemical refineries, industrial chemical use (cleaning; coatings; etc.), chemical waste sites, compressor stations, and more. The source dataset includes visits to over 85 distinct point sources. As expected, we find similarities between the different types of facilities, but observe variability between them and even at individual facilities day-to-day. Certain larger sites are better thought of as a collection of individual point sources. These results demonstrate the power of mobile laboratories over stationary sampling in dense industrial areas. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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15 pages, 1014 KiB

Open AccessArticle

The Michigan–Ontario Ozone Source Experiment (MOOSE): An Overview

by Eduardo P. Olaguer, Yushan Su, Craig A. Stroud, Robert M. Healy, Stuart A. Batterman, Tara I. Yacovitch, Jiajue Chai, Yaoxian Huang and Matthew T. Parsons

Atmosphere 2023, 14(11), 1630; https://doi.org/10.3390/atmos14111630 - 30 Oct 2023

Viewed by 1341

Abstract

The Michigan–Ontario Ozone Source Experiment (MOOSE) is an international air quality field study that took place at the US–Canada Border region in the ozone seasons of 2021 and 2022. MOOSE addressed binational air quality issues stemming from lake breeze phenomena and transboundary transport, as well as local emissions in southeast Michigan and southern Ontario. State-of-the-art scientific techniques applied during MOOSE included the use of multiple advanced mobile laboratories equipped with real-time instrumentation; high-resolution meteorological and air quality models at regional, urban, and neighborhood scales; daily real-time meteorological and air quality forecasts; ground-based and airborne remote sensing; instrumented Unmanned Aerial Vehicles (UAVs); isotopic measurements of reactive nitrogen species; chemical fingerprinting; and fine-scale inverse modeling of emission sources. Major results include characterization of southeast Michigan as VOC-limited for local ozone formation; discovery of significant and unaccounted formaldehyde emissions from industrial sources; quantification of methane emissions from landfills and leaking natural gas pipelines; evaluation of solvent emission impacts on local and regional ozone; characterization of the sources of reactive nitrogen and PM_2.5; and improvements to modeling practices for meteorological, receptor, and chemical transport models. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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18 pages, 8220 KiB

Open AccessArticle

The Influence of Meteorology Initialization on Ozone Forecasting in the Great Lakes Region during MOOSE Study

by Rabab Mashayekhi, Craig A. Stroud, Junhua Zhang, Oumarou Nikiema and Sandrine Trotechaud

Atmosphere 2023, 14(9), 1383; https://doi.org/10.3390/atmos14091383 - 1 Sep 2023

Cited by 1 | Viewed by 980

Abstract

This study investigates the influence of meteorology initialization on surface ozone prediction in the Great Lakes region using Canada’s operational air quality model (GEM-MACH) at a 2.5 km horizontal resolution. Two different initialization techniques are compared, and it is found that the four-dimensional incremental analysis updating (IAU) method yields improved model performance for surface ozone prediction. The IAU run shows better ozone regression line statistics (y = 0.7x + 14.9, R² = 0.2) compared to the non-IAU run (y = 0.6x + 23.1, R² = 0.1), with improved MB and NMB values (3.9 ppb and 8.9%, respectively) compared to the non-IAU run (4.1 ppb and 9.3%). Furthermore, analyzing ozone prediction sensitivity to model initialization time reveals that the 18z initialization leads to enhanced performance, particularly during high ozone exceedance days, with an improved regression slope of 0.9 compared to 0.7 for the 00z and 12z runs. The MB also improves to −0.2 ppb in the 18z run compared to −2.8 ppb and −3.9 ppb for the 00z and 12z runs, respectively. The analysis of meteorological fields reveals that the improved ozone predictions at 18z are linked to a more accurate representation of afternoon wind speed. This improvement enhances the transport of ozone, contributing to the overall improvement in ozone predictions. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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20 pages, 3380 KiB

Open AccessArticle

Sensitivity of Source Apportionment of Ambient PM_2.5-Bound Elements to Input Concentration Data

by Tianchu Zhang, Yushan Su, Jerzy Debosz, Michael Noble, Anthony Munoz and Xiaohong Xu

Atmosphere 2023, 14(8), 1269; https://doi.org/10.3390/atmos14081269 - 10 Aug 2023

Cited by 1 | Viewed by 1018

Abstract

This study investigated the sensitivity of the positive matrix factorization (PMF) model using concentrations of PM_2.5-bound elements in Windsor, Ontario, Canada. Five scenarios were devised to assess impacts of input data on source identification, source contributions, and model performance. The study found that the model outcomes and performance were not sensitive to data below method detection limits (MDLs) being replaced with ½ MDLs, nor whether brown carbons (BrCs) data were excluded. By analyzing two episodic events individually, unique factors of fireworks and mineral dust were identified for each of the two episodes. Moreover, PMF model performance was improved greatly for event markers of the episodes and elements with less variability in concentration when compared with the base case scenario. Excluding the two episodes from the entire dataset had little impact on factor identification and source contributions but improved the model performance for three out of twelve elements unique to the two episodes. Overall, the PMF model outcomes and performance were sensitive to percentages of concentrations below MDLs and element concentrations with large variability due to high concentrations observed in episodes. Our findings are useful for dealing with data below MDLs and episodic events in conducting future PMF source apportionment of PM_2.5-bound elements. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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22 pages, 5895 KiB

Open AccessArticle

Impact of Solvent Emissions on Reactive Aromatics and Ozone in the Great Lakes Region

by Craig A. Stroud, Junhua Zhang, Elisa I. Boutzis, Tianchu Zhang, Rabab Mashayekhi, Oumarou Nikiema, Mahtab Majdzadeh, Sumi N. Wren, Xiaohong Xu and Yushan Su

Atmosphere 2023, 14(7), 1094; https://doi.org/10.3390/atmos14071094 - 30 Jun 2023

Cited by 2 | Viewed by 1351

Abstract

While transportation emissions have declined over the past several decades, volatile organic compound (VOC) emissions from solvent use applications have increased as urban areas expand. In this work, the Canadian air quality model (GEM-MACH-TEB) is used to assess the importance of solvent emissions during the Michigan Ontario Ozone Source Experiment (MOOSE). Model predictions are compared to ozone and total mono-substituted aromatics (TOLU) observations collected in Windsor, Ontario. For summer 2018, model estimates of TOLU from solvent emissions are smaller (30% for an 8 h daytime average) in Windsor than estimates from positive matrix factorization (44% for a 24 h average). The use of updated U.S. solvent emissions from the EPA’s VCPy (Volatile Chemical Product framework) for summer 2021 simulations increases the solvent use source contribution over Detroit/Windsor (30–50% for an 8 h daytime average). This also provides a more uniform spatial distribution across the U.S./Canada border (30–50% for an 8 h daytime average). Long-chain alkanes are the dominant speciation in the model’s air pollutant emission inventory and in the observation-derived solvent use factor. Summertime 8 h daytime ozone decreased by 0.4% over Windsor for a 10% solvent use VOC emission reduction scenario. A 10% mobile NO_x emission reduction scenario resulted in a 0.6% O₃ decrease over Windsor and more widespread changes over the study region. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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19 pages, 4785 KiB

Open AccessEditor’s ChoiceArticle

Inverse Modeling of Formaldehyde Emissions and Assessment of Associated Cumulative Ambient Air Exposures at Fine Scale

by Eduardo P. Olaguer

Atmosphere 2023, 14(6), 931; https://doi.org/10.3390/atmos14060931 - 26 May 2023

Cited by 2 | Viewed by 1801

Abstract

Among air toxics, formaldehyde (HCHO) is an important contributor to urban cancer risk. Emissions of HCHO in the United States are systematically under-reported and may enhance atmospheric ozone and particulate matter, intensifying their impacts on human health. During the 2021 Michigan-Ontario Ozone Source Experiment (MOOSE), mobile real-time (~1 s frequency) measurements of ozone, nitrogen oxides, and organic compounds were conducted in an industrialized area in metropolitan Detroit. The measured concentrations were used to infer ground-level and elevated emissions of HCHO, CO, and NO from multiple sources at a fine scale (400 m horizontal resolution) based on the 4D variational data assimilation technique and the MicroFACT air quality model. Cumulative exposure to HCHO from multiple sources of both primary (directly emitted) and secondary (atmospherically formed) HCHO was then simulated assuming emissions inferred from inverse modeling. Model-inferred HCHO emissions from larger industrial facilities were greater than 1 US ton per year while corresponding emission ratios of HCHO to CO in combustion sources were roughly 2 to 5%. Moreover, simulated ambient HCHO concentrations depended significantly on wind direction relative to the largest sources. The model helped to explain the observed HCHO concentration gradient between monitoring stations at Dearborn and River Rouge in 2021. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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20 pages, 3416 KiB

Open AccessArticle

Mobile Measurements of Atmospheric Methane at Eight Large Landfills: An Assessment of Temporal and Spatial Variability

by Tian Xia, Sachraa G. Borjigin, Julia Raneses, Craig A. Stroud and Stuart A. Batterman

Atmosphere 2023, 14(6), 906; https://doi.org/10.3390/atmos14060906 - 23 May 2023

Cited by 3 | Viewed by 1492

Abstract

Municipal solid waste landfills are major contributors to anthropogenic emissions of methane (CH₄), which is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. The development of sensitive, selective, and fast-response instrumentation allows the deployment of mobile measurement platforms for CH₄ measurements at landfills. The objectives of this study are to use mobile monitoring to measure ambient levels of CH₄ at eight large operating landfills in southeast Michigan, USA; to characterize diurnal, daily and spatial variation in CH₄ levels; and to demonstrate the influence of meteorological factors. Elevated CH₄ levels were typically found along the downwind side or corner of the landfill. Levels peaked in the morning, reaching 38 ppm, and dropped to near-baseline levels during midday. Repeat visits showed that concentrations were highly variable. Some variation was attributable to the landfill size, but both mechanistically-based dilution-type models and multivariate models identified that wind speed, boundary layer height, barometric pressure changes, and landfill temperature were key determinants of CH₄ levels. Collectively, these four factors explained most (r² = 0.89) of the variation in the maximum CH₄ levels at the landfill visited most frequently. The study demonstrates the ability to assess spatial and temporal variation in CH₄ levels at landfills using mobile monitoring along perimeter roads. Such monitoring can identify the location of leaks and the best locations for long-term emission monitoring using fixed site monitors. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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22 pages, 4551 KiB

Open AccessArticle

Apportionment of PM_2.5 Sources across Sites and Time Periods: An Application and Update for Detroit, Michigan

by Zhiyi Yang, Md Kamrul Islam, Tian Xia and Stuart Batterman

Atmosphere 2023, 14(3), 592; https://doi.org/10.3390/atmos14030592 - 20 Mar 2023

Cited by 4 | Viewed by 2914

Abstract

Identifying sources of air pollutants is essential for informing actions to reduce emissions, exposures, and adverse health impacts. This study updates and extends apportionments of particulate matter (PM_2.5) in Detroit, MI, USA, an area with extensive industrial, vehicular, and construction activity interspersed among vulnerable communities. We demonstrate an approach that uses positive matrix factorization models with combined spatially and temporally diverse datasets to assess source contributions, trend seasonal levels, and examine pandemic-related effects. The approach consolidates measurements from 2016 to 2021 collected at three sites. Most PM_2.5 was due to mobile sources, secondary sulfate, and secondary nitrate; smaller contributions arose from soil/dust, ferrous and non-ferrous metals, and road salt sources. Several sources varied significantly by season and site. Pandemic-related changes were generally modest. Results of the consolidated models were more consistent with respect to trends and known sources, and the larger sample size should improve representativeness and stability. Compared to earlier apportionments, contributions of secondary sulfate and nitrate were lower, and mobile sources now represent the dominant PM_2.5 contributor. We show the growing contribution of mobile sources, the need to update apportionments performed just 5–10 years ago, and that apportionments at a single site may not apply elsewhere in the same urban area, especially for local sources. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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16 pages, 5019 KiB

Open AccessArticle

Is There a Formaldehyde Deficit in Emissions Inventories for Southeast Michigan?

by Eduardo P. Olaguer, Yongtao Hu, Susan Kilmer, Zachariah E. Adelman, Petros Vasilakos, M. Talat Odman, Marissa Vaerten, Tracey McDonald, David Gregory, Bryan Lomerson and Armistead G. Russell

Atmosphere 2023, 14(3), 461; https://doi.org/10.3390/atmos14030461 - 25 Feb 2023

Cited by 2 | Viewed by 1977

Abstract

Formaldehyde is a key Volatile Organic Compound (VOC) and ozone precursor that plays a vital role in the urban atmospheric radical budget on par with water vapor, ozone, and nitrous acid. In addition to modulating radical and ozone production, ambient formaldehyde has both carcinogenic and non-carcinogenic inhalation health effects. This study concludes that ambient formaldehyde in the Southeast Michigan (SEMI) ozone nonattainment area may be underestimated up to a factor of two or more by regional air quality models. The addition of plausible amounts of primary formaldehyde to the U.S. National Emissions Inventory based on estimated formaldehyde-to-CO emission ratios partially alleviates this modeling deficit and indicates the presence of formaldehyde concentrations above 5 ppb at a previously unsuspected location northeast of Detroit. Standard 24-h formaldehyde samples obtained during the Michigan-Ontario Ozone Source Experiment (MOOSE) verified the presence of high ambient formaldehyde concentrations at this location. Moreover, the addition of plausible amounts of primary formaldehyde to VOC emissions inventories may add more than 1 ppb of ozone to ambient air in the SEMI nonattainment area, where ozone design values exceeded the U.S. National Ambient Air Quality Standard (NAAQS) by 1–2 ppb for the 2018–2020 design value period. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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18 pages, 2590 KiB

Open AccessEditor’s ChoiceArticle

Continuous Measurements and Source Apportionment of Ambient PM_2.5-Bound Elements in Windsor, Canada

by Tianchu Zhang, Yushan Su, Jerzy Debosz, Michael Noble, Anthony Munoz and Xiaohong Xu

Atmosphere 2023, 14(2), 374; https://doi.org/10.3390/atmos14020374 - 14 Feb 2023

Cited by 7 | Viewed by 2152

Abstract

Ambient fine particulate matter (PM_2.5) levels in Windsor, Ontario, Canada, are impacted by local emissions and regional/transboundary transport input and also attributable to secondary formation. PM_2.5-bound elements were monitored hourly in Windsor from April to October 2021. Observed concentrations of the elements were generally comparable to historical measurements at urban sites in Ontario. A clear diurnal pattern was observed for most of the elements, i.e., high in the morning and low in the afternoon, mostly related to evolution of atmospheric mixing heights and local anthropogenic activities. Conversely, sulfur showed elevated levels in the afternoon, suggesting conversion of gaseous sulfur dioxide to particulate sulphate was enhanced by increased ambient temperatures. Five source factors were resolved using the US EPA positive matrix factorization model, including three traffic-related sources (i.e., vehicular exhaust, crustal dust, and vehicle tire and brake wear factors) and two industrial sources (i.e., coal/heavy oil burning and metal processing factors). Overall, the three traffic-related sources were mostly local and contributed to 47% of the total elemental concentrations, while the two industrial sources may originate from regional/transboundary sources and contributed to 53%. Measures to control both local traffic emissions and regional/transboundary industrial sources would help reduce levels of PM_2.5-bound elements in Windsor. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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18 pages, 6816 KiB

Open AccessArticle

Spatially Resolved Source Apportionment of Industrial VOCs Using a Mobile Monitoring Platform

by Robert M. Healy, Uwayemi M. Sofowote, Jonathan M. Wang, Qingfeng Chen and Aaron Todd

Atmosphere 2022, 13(10), 1722; https://doi.org/10.3390/atmos13101722 - 20 Oct 2022

Cited by 7 | Viewed by 2343

Abstract

Industrial emissions of volatile organic compounds (VOCs) directly impact air quality downwind of facilities and contribute to regional ozone and secondary organic aerosol production. Positive matrix factorization (PMF) is often used to apportion VOCs to their respective sources using measurement data collected at fixed sites, for example air quality monitoring stations. Here, we apply PMF analysis to high time-resolution VOC measurement data collected both while stationary and while moving using a mobile monitoring platform. The stationary monitoring periods facilitated the extraction of representative industrial VOC source profiles while the mobile monitoring periods were critical for the spatial identification of VOC hotspots. Data were collected over five days in a heavily industrialized region of southwestern Ontario containing several refineries, petrochemical production facilities and a chemical waste disposal facility. Factors associated with petroleum, chemical waste and rubber production were identified and ambient mixing ratios of selected aromatic, unsaturated and oxygenated VOCs were apportioned to local and background sources. Fugitive emissions of benzene, highly localized and predominantly associated with storage, were found to be the dominant local contributor to ambient benzene mixing ratios measured while mobile. Toluene and substituted aromatics were predominantly associated with refining and traffic, while methyl ethyl ketone was linked to chemical waste handling. The approach described here facilitates the apportionment of VOCs to their respective local industrial sources at high spatial and temporal resolution. This information can be used to identify problematic source locations and to inform VOC emission abatement strategies. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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19 pages, 4973 KiB

Open AccessArticle

Improving the Performance of Pipeline Leak Detection Algorithms for the Mobile Monitoring of Methane Leaks

by Tian Xia, Julia Raneses and Stuart Batterman

Atmosphere 2022, 13(7), 1043; https://doi.org/10.3390/atmos13071043 - 29 Jun 2022

Cited by 5 | Viewed by 2084

Abstract

Methane (CH₄) is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. Sizable CH₄ releases can occur during gas extraction, distribution, and use, thus, the detection and the control of leaks can help to reduce emissions. This study develops, refines, and tests algorithms for detecting CH₄ peaks and estimating the background levels of CH₄ using mobile monitoring, an approach that has been used to determine the location and the magnitude of pipeline leaks in a number of cities. The algorithm uses four passes of the data to provide initial and refined estimates of baseline levels, peak excursions above baseline, peak locations, peak start and stop times, and indicators of potential issues, such as a baseline shift. Peaks that are adjacent in time or in space are merged using explicit criteria. The algorithm is refined and tested using 1-s near-ground CH₄ measurements collected on 20 days while driving about 1100 km on surface streets in Detroit, Michigan by the Michigan Pollution Assessment Laboratory (MPAL). Sensitivity and other analyses are used to evaluate the effects of each parameter and to recommend a parameter set for general applications. The new algorithm improves the baseline estimates, increases sensitivity, and more consistently merges nearby peaks. Comparisons of two data subsets show that results are repeatable and reliable. In the field study application, we detected 534 distinct CH₄ peaks, equivalent to ~0.5 peaks per km traveled; larger peaks detected at nine locations on multiple occasions suggested sizable pipeline leaks or possibly other CH₄ sources. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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19 pages, 6465 KiB

Open AccessArticle

Landfill Emissions of Methane Inferred from Unmanned Aerial Vehicle and Mobile Ground Measurements

by Eduardo P. Olaguer, Shelley Jeltema, Thomas Gauthier, Dustin Jermalowicz, Arthur Ostaszewski, Stuart Batterman, Tian Xia, Julia Raneses, Michael Kovalchick, Scott Miller, Jorge Acevedo, Jonathan Lamb, Jeff Benya, April Wendling and Joyce Zhu

Atmosphere 2022, 13(6), 983; https://doi.org/10.3390/atmos13060983 - 18 Jun 2022

Cited by 6 | Viewed by 4110

Abstract

Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of radical chain lengths in atmospheric reactions of volatile organic compounds and nitrogen oxides. Several advanced techniques were deployed to measure methane emissions from two landfills in the Southeast Michigan ozone nonattainment area during the Michigan–Ontario Ozone Source Experiment (MOOSE). These techniques included mobile infrared cavity ringdown spectrometry, drone-mounted meteorological sensors and tunable diode laser spectrometry, estimation of total landfill emissions of methane based on flux plane measurements, and Gaussian plume inverse modeling of distributed methane emissions in the presence of complex landfill terrain. The total methane emissions measured at the two landfills were of the order of 500 kg/h, with an uncertainty of around 50%. The results indicate that both landfill active faces and leaking gas collection systems are important sources of methane emissions. Full article

(This article belongs to the Special Issue The Michigan-Ontario Ozone Source Experiment (MOOSE))

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