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We use global airborne observations of propane (C3H8) and ethane (C2H6) from the Atmospheric Tomography (ATom) and HIAPER Pole-to-Pole Observations (HIPPO), as well as U.S.-based aircraft and tower observations by NOAA and from the NCAR FRAPPE campaign as tracers for emissions from oil and gas operations. To simulate global mole fraction fields for these gases, we update the default emissions' configuration of C3H8 used by the global chemical transport model, GEOS-Chem v13.0.0, using a scaled C2H6 spatial proxy. With the updated emissions, simulations of both C3H8 and C2H6 using GEOS-Chem are in reasonable agreement with ATom and HIPPO observations, though the updated emission fields underestimate C3H8 accumulation in the arctic wintertime, pointing to additional sources of this gas in the high latitudes (e.g., Europe). Using a Bayesian hierarchical model, we estimate global emissions of C2H6 and C3H8 from fossil fuel production in 2016-2018 to be 13.3 ± 0.7 (95% CI) and 14.7 ± 0.8 (95% CI) Tg/year, respectively. We calculate bottom-up hydrocarbon emission ratios using basin composition measurements weighted by gas production and find their magnitude is higher than expected and is similar to ratios informed by our revised alkane emissions. This suggests that emissions are dominated by pre-processing activities in oil-producing basins.

The role of anthropogenic NOx emissions in secondary organic aerosol (SOA) production is not fully understood but is important for understanding the contribution of emissions to air quality. Here, we examine the role of organic nitrates (RONO2) in SOA formation over the Korean Peninsula during the Korea-United States Air Quality field study in Spring 2016 as a model for RONO2 aerosol in cities worldwide. We use aircraft-based measurements of the particle phase and total (gas + particle) RONO2 to explore RONO2 phase partitioning. These measurements show that, on average, one-fourth of RONO2 are in the condensed phase, and we estimate that ≈15% of the organic aerosol (OA) mass can be attributed to RONO2. Furthermore, we observe that the fraction of RONO2 in the condensed phase increases with OA concentration, evidencing that equilibrium absorptive partitioning controls the RONO2 phase distribution. Lastly, we model RONO2 chemistry and phase partitioning in the Community Multiscale Air Quality modeling system. We find that known chemistry can account for one-third of the observed RONO2, but there is a large missing source of semivolatile, anthropogenically derived RONO2. We propose that this missing source may result from the oxidation of semi- and intermediate-volatility organic compounds and/or from anthropogenic molecules that undergo autoxidation or multiple generations of OH-initiated oxidation.

Oceans emit large quantities of dimethyl sulfide (DMS) to the marine atmosphere. The oxidation of DMS leads to the formation and growth of cloud condensation nuclei (CCN) with consequent effects on Earth's radiation balance and climate. The quantitative assessment of the impact of DMS emissions on CCN concentrations necessitates a detailed description of the oxidation of DMS in the presence of existing aerosol particles and clouds. In the unpolluted marine atmosphere, DMS is efficiently oxidized to hydroperoxymethyl thioformate (HPMTF), a stable intermediate in the chemical trajectory toward sulfur dioxide (SO2) and ultimately sulfate aerosol. Using direct airborne flux measurements, we demonstrate that the irreversible loss of HPMTF to clouds in the marine boundary layer determines the HPMTF lifetime (τHPMTF < 2 h) and terminates DMS oxidation to SO2 When accounting for HPMTF cloud loss in a global chemical transport model, we show that SO2 production from DMS is reduced by 35% globally and near-surface (0 to 3 km) SO2 concentrations over the ocean are lowered by 24%. This large, previously unconsidered loss process for volatile sulfur accelerates the timescale for the conversion of DMS to sulfate while limiting new particle formation in the marine atmosphere and changing the dynamics of aerosol growth. This loss process potentially reduces the spatial scale over which DMS emissions contribute to aerosol production and growth and weakens the link between DMS emission and marine CCN production with subsequent implications for cloud formation, radiative forcing, and climate.

Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Emissions and atmospheric concentrations of CH4 continue to increase, maintaining CH4 as the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the factors explaining the well-observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in-situ and greenhouse gas observing satellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land-surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full datasets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this edition benefits from important progress in estimating inland freshwater emissions, with better accounting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double accounting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double accounting that still exists (average of 23 Tg CH4 yr-1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr-1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr-1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr-1 or ~65 % are attributed to direct anthropogenic sources in the fossil, agriculture and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr-1or 63–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr-1 (range 9–40). Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr-1) larger global emissions (669 Tg CH4 yr-1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr-1 in Saunois et al. (2016, 2020), respectively), and for the first time uncertainty in bottom-up and top-down budgets overlap. The latitudinal distribution from atmospheric inversion-based emissions indicates a predominance of tropical and southern hemisphere emissions (~65 % of the global budget, <30° N) compared to mid (30° N–60° N, ~30 % of emissions) and high-northern latitudes (60° N–90° N, ~4 % of global emissions). This latitudinal distribution is similar in the bottom-up budget though the bottom-up budget estimates slightly larger contributions for the mid and high-northern latitudes, and slightly smaller contributions from the tropics and southern hemisphere than the inversions. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. We identify five major priorities for improving the CH4 budget: i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; ii) further development of process-based models for inland-water emissions; iii) intensification of CH4 observations at local (e.g., FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; iv) improvements of transport models and the representation of photochemical sinks in top-down inversions, and v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024). [ABSTRACT FROM AUTHOR]

Reactive halogens catalytically destroy O3 and therefore affect (1) stratospheric O3 depletion, and (2) the oxidative capacity of the troposphere. Reactive halogens also partition into the aerosol phase, but what governs halogen-aerosol partitioning is poorly constrained in models. In this work, we present global-scale measurements of non-sea-salt aerosol (nSSA) bromine and iodine taken during the NASA Atmospheric Tomography Mission (ATom). Using the Particle Analysis by Laser Mass Spectrometry instrument, we found that bromine and iodine are present in 8-26 % (interquartile range, IQR) and 12-44 % (IQR) of accumulation-mode nSSA, respectively. Despite being commonly found in nSSA, the mass concentrations of bromine and iodine in nSSA were low, 0.11-0.57 pmol mol-1 (IQR) and 0.04–0.24 pmol mol-1 (IQR), respectively. In the troposphere, we find two distinct sources of bromine and iodine to nSSA: (1) a primary source from biomass burning, and (2) a pervasive secondary source. In the stratosphere, nSSA bromine and iodine mass increased with increasing O3 concentrations; however, higher concentrations of stratospheric nSSA bromine and iodine were found in organic-rich particles that originated in the troposphere. Finally, we compared our ATom nSSA iodine measurements to the global chemical transport model GEOS-Chem; nSSA bromine concentrations could not be compared because they were not tracked in the model. We found that the model compared well to our ATom nSSA iodine measurements in the background atmosphere, but not in the marine boundary layer, biomass burning plumes, or in the stratosphere. [ABSTRACT FROM AUTHOR]

Proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) is a technique commonly used to measure ambient volatile organic compounds (VOCs) in urban, rural, and remote environments. PTR-ToF-MS is known to produce artifacts from ion fragmentation, which complicates the interpretation and quantification of key atmospheric VOCs. This study evaluates the extent to which fragmentation and other ionization processes impact urban measurements of the PTR-ToF-MS ions typically assigned to isoprene (m/z 69, C 5 H 8 H +), acetaldehyde (m/z 45, CH 3 CHO +), and benzene (m/z 79, C 6 H 6 H +). Interferences from fragmentation are identified using gas chromatography (GC) pre-separation, and the impact of these interferences is quantified using ground-based and airborne measurements in a number of US cities, including Las Vegas, Los Angeles, New York City, and Detroit. In urban regions with low biogenic isoprene emissions (e.g., Las Vegas), fragmentation from higher-carbon aldehydes and cycloalkanes emitted from anthropogenic sources may contribute to m/z 69 by as much as 50 % during the day, while the majority of the signal at m/z 69 is attributed to fragmentation during the night. Interferences are a higher fraction of m/z 69 during airborne studies, which likely results from differences in the reactivity between isoprene and the interfering species along with the subsequent changes to the VOC mixture at higher altitudes. For other PTR masses, including m/z 45 and m/z 79, interferences are observed due to fragmentation and O 2+ ionization of VOCs typically used in solvents, which are becoming a more important source of anthropogenic VOCs in urban areas. We present methods to correct these interferences, which provide better agreement with GC measurements of isomer-specific molecules. These observations show the utility of deploying GC pre-separation for the interpretation PTR-ToF-MS spectra. [ABSTRACT FROM AUTHOR]

Extensive airborne measurements of non-methane organic gases (NMOGs), methane, nitrogen oxides, reduced nitrogen species, and aerosol emissions from US wild and prescribed fires were conducted during the 2019 NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality campaign (FIREX-AQ). Here, we report the atmospheric enhancement ratios (ERs) and inferred emission factors (EFs) for compounds measured on board the NASA DC-8 research aircraft for nine wildfires and one prescribed fire, which encompass a range of vegetation types. We use photochemical proxies to identify young smoke and reduce the effects of chemical degradation on our emissions calculations. ERs and EFs calculated from FIREX-AQ observations agree within a factor of 2, with values reported from previous laboratory and field studies for more than 80 % of the carbon- and nitrogen-containing species. Wildfire emissions are parameterized based on correlations of the sum of NMOGs with reactive nitrogen oxides (NO y) to modified combustion efficiency (MCE) as well as other chemical signatures indicative of flaming/smoldering combustion, including carbon monoxide (CO), nitrogen dioxide (NO 2), and black carbon aerosol. The sum of primary NMOG EFs correlates to MCE with an R2 of 0.68 and a slope of - 296 ± 51 g kg -1 , consistent with previous studies. The sum of the NMOG mixing ratios correlates well with CO with an R2 of 0.98 and a slope of 137 ± 4 ppbv of NMOGs per parts per million by volume (ppmv) of CO, demonstrating that primary NMOG emissions can be estimated from CO. Individual nitrogen-containing species correlate better with NO 2 , NO y , and black carbon than with CO. More than half of the NO y in fresh plumes is NO 2 with an R2 of 0.95 and a ratio of NO 2 to NO y of 0.55 ± 0.05 ppbv ppbv -1 , highlighting that fast photochemistry had already occurred in the sampled fire plumes. The ratio of NO y to the sum of NMOGs follows trends observed in laboratory experiments and increases exponentially with MCE, due to increased emission of key nitrogen species and reduced emission of NMOGs at higher MCE during flaming combustion. These parameterizations will provide more accurate boundary conditions for modeling and satellite studies of fire plume chemistry and evolution to predict the downwind formation of secondary pollutants, including ozone and secondary organic aerosol. [ABSTRACT FROM AUTHOR]

The sulfur cycle plays a key role in atmospheric air quality, climate, and ecosystems. In this study, we compare the spatial and temporal distribution of four sulfur-containing species, dimethyl sulfide (DMS), sulfur dioxide (SO2), particulate methanesulfonate (MSA), and particulate sulfate (SO4), that were measured during the airborne NASA Atmospheric Tomography (ATom) mission and simulated by five AeroCom-III models to analyze the budget of sulfur cycle from the models. This study focuses on remote regions over the Pacific, Atlantic, and Southern Oceans from near the ocean surface to ~12-km altitude range, and covers all four seasons. These regions provide us with highly heterogeneous natural and anthropogenic source environments, which is not usually the case for traditional continental studies. We examine the vertical and seasonal variations of these sulfur species over tropical, mid-, and high-latitude regions in both hemispheres. We identify their origins from land versus ocean and from anthropogenic versus natural sources with sensitivity studies by applying tagged tracers linking to emission types and regions. In general, the differences among model results can be greater than one-order of magnitude. Comparing with observations, simulated SO2 is generally low while SO4 is high, and the model-observation agreement is much better in ATom-4 (April-May, 2018). There are much larger DMS concentrations simulated close to the sea surface than observed, indicating that the DMS emissions may be too high from all models. Anthropogenic emissions are the dominant source (40-60% of the total amount) for atmospheric sulfate simulated at locations and times along the ATom flight tracks at almost every altitude, followed by volcanic emissions (18-32%) and oceanic sources (16-32%). Similar source contributions can also be derived at broad ocean basin and monthly scales, indicating that any reductions of anthropogenic sulfur emissions would have global impacts in modern times. [ABSTRACT FROM AUTHOR]

In this study, the WRF-Chem v4.4 model was utilized to evaluate three bottom-up emission inventories (EDGAR-HTAP v2, v3, and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8-hour average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30°N over China. All simulations underestimated the observed CO by 50-60% over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2, v3, and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO and HCHO concentrations. Notably, the model aromatic VOCs were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local emission dominant case, but led to the model O3 overestimations for the transport dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

Proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) is a technique commonly used to measure ambient volatile organic compounds (VOCs) in urban, rural, and remote environments. PTR-ToF-MS is known to produce artifacts from ion fragmentation, which complicates the interpretation and quantification of key atmospheric VOCs. This study evaluates the extent to which fragmentation and other ionization processes impacts urban measurements of the PTR-ToF-MS ions typically assigned to isoprene (m/z 69, C5H8H+), acetaldehyde (m/z 45, CH3CHO+), and benzene (m/z 79, C6H6H+). Interferences from fragmentation are identified using gas-chromatography (GC) pre-separation and the impact of these interferences are quantified using ground-based and airborne measurements in a number of US cities, including Las Vegas, Los Angeles, New York City, and Detroit. In urban regions with low biogenic isoprene emissions (e.g., Las Vegas), fragmentation from higher carbon aldehydes and cycloalkanes emitted from anthropogenic sources may contribute to m/z 69 by as much as 50% during the day, while the majority of the signal at m/z 69 is attributed to fragmentation during the night. Interferences are a higher fraction of m/z 69 during airborne studies, which likely results from differences in the reactivity between isoprene and the interfering species along with the subsequent changes to the VOC mixture at higher altitudes. For other PTR masses, including m/z 45 and m/z 79, interferences are observed due to the fragmentation and secondary ionization of VOCs typically used in solvents, which are becoming a more important source of anthropogenic VOCs in urban areas. We present methods to correct these interferences, which provide better agreement with GC measurements of isomer specific molecules. These observations show the utility of deploying GC pre-separation for the interpretation PTR-ToF-MS spectra. [ABSTRACT FROM AUTHOR]

The Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf of Mexico was conducted in May 2019 by NASA and the Bureau of Ocean Energy Management to determine the feasibility of using satellite data to measure air quality in a region of concentrated oil and natural gas (ONG) operations. SCOAPE addressed both technological and scientific issues related to measuring NO2 columns over the outer continental shelf. Featured were nitrogen dioxide (NO2) instruments (Pandora, Teledyne API analyzer) at Cocodrie, LA (29.26°, −90.66°), and on the Research Vessel Point Sur operating off the Louisiana coast with measurements of ozone, carbon monoxide, and volatile organic compounds (VOCs). The findings: (a) all NO2 observations revealed two atmospheric regimes over the Gulf, the first influenced by tropical air in 10–14 May, the second influenced by flow from urban areas on 15–17 May; (b) comparisons of OMI v4 and TROPOMI v1.3 TC (total column) NO2 data with shipboard Pandora NO2 column observations averaged 13% agreement with the largest difference during 15–17 May (∼20%). At Cocodrie, the satellite–Pandora agreement was ∼5%. (c) Three new‐model Pandora instruments displayed a TC NO2 precision of 0.01 Dobson Units (∼5%); (d) regions of smaller, older natural gas operations showed high methane readings from leakage; elevated VOCs were also detected. Neither satellite nor spectrometer captured the magnitude of ambient NO2 variability near ONG platforms. Given an absence of regular air quality monitoring over the Gulf of Mexico, SCOAPE data constitute a baseline against which future observations can be compared. Plain Language Summary: The Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf of Mexico (GOM) conducted on the Research Vessel Point Sur in May 2019 investigated the feasibility of using satellite data to measure air quality in a region of concentrated oil and natural gas (ONG) operations. SCOAPE addressed both technological and scientific issues related to measuring NO2 columns in a prototypical coastal environment. The results are as follows. First, measurements from SCOAPE demonstrated that satellite NO2 data can be used to monitor ONG activity over the GOM. Second, during SCOAPE both OMI and TROPOMI TC (total column) NO2 amounts were higher over land and sometimes the near‐shore ONG‐rich Gulf, than over deepwater regions farther offshore. This was confirmed by Pandora spectrometer "ground truth" TC NO2 data measured throughout SCOAPE on shore and on ship. Third, SCOAPE established the reliability and precision of a new generation of Pandora spectrometers. Fourth, comparisons of satellite and Pandora TC NO2 data in SCOAPE confirm previous land–water interface studies that point to limitations in satellite NO2 in coastal regions. Finally, neither satellite nor spectrometer captures the magnitude of ambient ("nose‐level") NO2 variability in a region dotted with hundreds of ONG platforms. Key Points: Shipboard Pandora NO2 columns and surface O3, NO2, CO, and volatile organic compounds (VOCs) over the Gulf of Mexico (GOM), May 2019, displayed two air quality (AQ) regimesGOM AQ was dominated by continental NO2 sources and near‐shore VOC; deepwater oil platforms were in a clean marine regimePandora and satellite total column NO2 over GOM agreed overall within 5% in clean, clear‐sky conditions along the coast and 13% over water [ABSTRACT FROM AUTHOR]

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LROx) to the chemical loss of NO x (LNOx). Subsequently, we challenge the predictive power of HCHO/NO2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LROx/LNOx. FNRs show a strongly linear (R2=0.94) relationship with LROx/LNOx , but only on the logarithmic scale. Following the baseline (i.e., ln(LROx/LNOx) = - 1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NOx -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the ROx – HOx cycle. We calculate high ozone production rates (PO 3) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NOx -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm -2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric. [ABSTRACT FROM AUTHOR]

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO2) (a proxy for nitrogen oxides) tropospheric columns from Ultraviolet-Visible (UV-Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near to the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to carefully quantify those errors. Concerning the chemistry error, a well-characterized box model constrained by more than 500 hours of aircraft data from NASA’s air quality campaigns is used to simulate the ratio of the chemical loss of HO2+RO2 (LROx) to the chemical loss of NOx (LNOx). Subsequently, we challenge the predictive power of HCHO / NO2 ratios (FNRs), which are commonly applied in current research, at detecting the underlying ozone regimes by comparing them to LROx / LNOx. FNRs show a strongly linear (R²=0.94) relationship to LROx / LNOx in the log-log scale. Following the baseline (i.e., ln(LROx / LNOx) = -1.0±0.2) with the model and mechanism (CB06, r2) used for segregating NOx-sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that FNR has an inherent 20 % standard error (1-sigma) resulting from not being able to fully describe the ROx-HOx cycle. We calculate high ozone production rates (PO3) dominated by large HCHO×NO2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO3 and HCHO×NO2 becomes more pronounced when moving towards NOx-sensitive regions due to non-linear chemistry; our results indicate that there is fruitful information in the HCHO×NO2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO2 concentration from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns to the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. With respect to a high-resolution sensor like TROPOspheric Monitoring Instrument (TROPOMI) (>5.5×3.5 km²), Ozone Monitoring Instrument (OMI) loses 12 % of spatial information at its native resolution. A pixel with a grid size of 216 km² fails at capturing ~65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in-situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO2 and HCHO columns. At 68 % confidence interval (1 sigma) errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO2 columns should be above 1.2–1.5×1016 molec.cm-2 to attain 20–30 % standard error in the ratio. This level of error is almost non-achievable with OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (<50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., Rocky Mountains) are markedly uncertain (>100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric. The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO2) (a proxy for nitrogen oxides) tropospheric columns from Ultraviolet-Visible (UV-Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near to the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to carefully quantify those errors. Concerning the chemistry error, a well-characterized box model constrained by more than 500 hours of aircraft data from NASA’s air quality campaigns is used to simulate the ratio of the chemical loss of HO2+RO2 (LROx) to the chemical loss of NOx (LNOx). Subsequently, we challenge the predictive power of HCHO / NO2 ratios (FNRs), which are commonly applied in current research, at detecting the underlying ozone regimes by comparing them to LROx / LNOx. FNRs show a strongly linear (R²=0.94) relationship to LROx / LNOx in the log-log scale. Following the baseline (i.e., ln(LROx / LNOx) = -1.0±0.2) with the model and mechanism (CB06, r2) used for segregating NOx-sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that FNR has an inherent 20 % standard error (1-sigma) resulting from not being able to fully describe the ROx-HOx cycle. We calculate high ozone production rates (PO3) dominated by large HCHO×NO2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO3 and HCHO×NO2 becomes more pronounced when moving towards NOx-sensitive regions due to non-linear chemistry; our results indicate that there is fruitful information in the HCHO×NO2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO2 concentration from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns to the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. With respect to a high-resolution sensor like TROPOspheric Monitoring Instrument (TROPOMI) (>5.5×3.5 km²), Ozone Monitoring Instrument (OMI) loses 12 % of spatial information at its native resolution. A pixel with a grid size of 216 km² fails at capturing ~65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in-situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO2 and HCHO columns. At 68 % confidence interval (1 sigma) errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO2 columns should be above 1.2–1.5×1016 molec.cm-2 to attain 20–30 % standard error in the ratio. This level of error is almost non-achievable with OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (<50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., Rocky Mountains) are markedly uncertain (>100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric. [ABSTRACT FROM AUTHOR]

Bromine released from the decomposition of short-lived brominated source gases contributes as a sink of ozone in the lower stratosphere. The two major contributors are CH2Br2 and CHBr3. In this study, we investigate the global seasonal distribution of these two substances, based on four High Altitude and Long Range Research Aircraft (HALO) missions, the HIAPER Pole-to-Pole Observations (HIPPO) mission, and the Atmospheric Tomography (ATom) mission. Observations of CH2Br2 in the free and upper troposphere indicate a pronounced seasonality in both hemispheres, with slightly larger mixing ratios in the Northern Hemisphere (NH). Compared to CH2Br2, CHBr3 in these regions shows larger variability and less clear seasonality, presenting larger mixing ratios in winter and autumn in NH mid to high latitudes. A clear CH2Br2 maximum is observed in the NH during autumn with a less pronounced similar feature in the Southern Hemisphere (SH). This suggests that transport processes may be different in both hemispheric autumn seasons, which implies that the influx of tropospheric air ("flushing") into the NH lowermost stratosphere is more efficient than in the SH. However, the SH database is insufficient to quantify this difference. We further compare the observations to model estimates of TOMCAT and CAM-Chem, both using the same emission inventory. The pronounced tropospheric seasonality of CH2Br2 in the SH is not reproduced by the models, presumably due to erroneous seasonal emissions or atmospheric photochemical decomposition efficiencies. In contrast, model simulations of CHBr3 show a pronounced seasonality in both hemispheres, which are not confirmed by observations. The distributions of both species in the lowermost stratosphere of the Northern and Southern Hemispheres are overall well captured by the models with the exception of southern hemispheric autumn, where both models present a bias that maximizes in the lowest 40 K above the tropopause, with considerably lower mixing ratios in the observations. Thus, both models reproduce equivalent "flushing" in both hemispheres, which is not confirmed by the available observations. Our study emphasises the need for more extensive 20 observations in the SH to fully understand the impact of CH2Br2and CHBr3 on lowermost stratospheric ozone loss and to help constraining emissions. [ABSTRACT FROM AUTHOR]

Urban air pollution is rapidly becoming a major environmental problem of public concern in several developing countries of the world. Jeddah, the second-largest city in Saudi Arabia, is subject to high air pollution that has severe implications for the health of the exposed population. Fine particulate matter (PM2.5) samples were collected for 24 h daily, during a 1-year campaign from 2013 to 2014. This study presents a detailed investigation of PM2.5 mass, chemical composition, and sources covering all four seasons of the year. Samples were analyzed for black carbon (BC), trace elements (TEs), and water-soluble ionic species (IS). The chemical compositions were statistically examined, and the temporal and seasonal patterns were characterized using descriptive analysis, correlation matrices, and elemental enrichment factor (EF). Source apportionment and source locations were performed on PM2.5 samples using the positive matrix factorization (PMF) model, elemental enrichment factor, and air-mass back trajectory analysis. The 24-h mean PM2.5 and BC concentrations ranged from 33.9 ± 9.1–58.8 ± 25 µg/m3 and 1.8 ± 0.4–2.4 ± 0.6 µg/m3, respectively. Atmospheric PM2.5 concentrations were well above the 24-h WHO guideline of 15 µg/m3, with overall results showing significant temporal and seasonal variability. EF defined two broad categories of TEs: anthropogenic (Ni, V, Cu, Zn, Cl, Pb, S, Lu, and Br), and earth-crust derived (Al, Si, Mg, K, Ca, Ti, Cr, Mn, Fe, and Sr). The five identified factors resulting from PMF were (1) fossil-fuels/oil combustion (45.3%), (2) vehicular emissions (19.1%), (3) soil/dust resuspension (15.6%), (4) industrial mixed dust (13.5%), and (5) sea-spray (6.5%). This study highlights the importance of focusing control strategies, not only on reducing PM concentration but also on the reduction of components of the PM as well, to effectively protect human health and the environment. [ABSTRACT FROM AUTHOR]

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by -64% but overestimates nitrate aerosol by 36%. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 46% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements. [ABSTRACT FROM AUTHOR]

Large wildfires markedly alter regional atmospheric composition, but chemical complexity challenges model predictions of downwind impacts. Here, we elucidate key facets of gas-phase photochemistry and assess novel chemical processes via a case study of the 2013 California Rim Fire plume. Airborne in situ observations, acquired during the NASA Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) mission, illustrate the evolution of volatile organic compounds (VOC), oxidants, and reactive nitrogen over 12 hours of atmospheric aging. Measurements show rapid formation of ozone and peroxyacyl nitrates (PNs), sustained peroxide production, and prolonged enhancements in oxygenated VOC and nitrogen oxides (NO[sub x]). Measurements and Lagrangian trajectories constrain a 0-D puff model that approximates plume photochemical history and provides a framework for evaluating key processes. Simulations examine the effects of 1) previously -unmeasured reactive VOC identified in recent laboratory studies, and 2) emissions and secondary production of nitrous acid (HONO). Inclusion of estimated unmeasured VOC leads to a 250% increase in OH reactivity and a 70% increase in radical production via oxygenated VOC photolysis. HONO amplifies radical cycling and serves as a downwind NO[sub x] source, although two different HONO production mechanisms (particulate nitrate photolysis and heterogeneous NO[sub 2] conversion) exhibit markedly different effects on ozone, NO[sub x], and PNs. Analysis of radical initiation rates suggests that oxygenated VOC photolysis is a major radical source, exceeding HONO photolysis when averaged over the first 2 hours of aging. Ozone production chemistry transitions from VOC-sensitive to NO[sub x]-sensitive within the first hour of plume aging, with both peroxide and organic nitrate formation contributing significantly to radical termination. To simulate smoke plume chemistry accurately, models should simultaneously account for the full reactive VOC pool and all relevant oxidant sources. [ABSTRACT FROM AUTHOR]

Here we use satellite observations of HCHO vertical column densities (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI), ground-based and aircraft measurements, combined with a nested regional chemical transport model (GEOS-Chem at 0.5°×0.625° resolution), to understand the variability and sources of summertime HCHO better in Alaska. We first evaluate GEOSChem with in-situ airborne measurements during Atmospheric Tomography Mission 1 (ATom-1) aircraft campaign and ground-based measurements from Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS). We show reasonable agreement between observed and modeled HCHO, isoprene and monoterpenes. In particular, HCHO profiles show spatial homogeneity in Alaska, suggesting a minor contribution of biogenic emissions to HCHO VCD. We further examine the TROPOMI HCHO product in Alaska during boreal summer, which is in good agreement with GEOSChem model results. We find that HCHO VCDs are dominated by free-tropospheric background in wildfire-free regions. During the summer of 2018, the model suggests that the background HCHO column, resulting from methane oxidation, contributes to 66 to 80% of the HCHO VCD, while wildfires contribute to 14% and biogenic VOC contributes to 5 to 9% respectively. For the summer of 2019, which had intense wildfires, the model suggests that wildfires contribute to 40 to 65%, and the background column accounts for 30 to 50% of HCHO VCD in June and July. In particular, the model indicates a major contribution of wildfires from direct emissions of HCHO, instead of secondary production of HCHO from oxidation of larger VOCs. We find that the column contributed by biogenic VOC is often small and below the TROPOMI detection limit. The source and variability of HCHO VCD above Alaska during summer is mainly driven by background methane oxidation and wildfires. This work discusses challenges for quantifying HCHO and its precursors in remote pristine regions. [ABSTRACT FROM AUTHOR]

Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway as well as the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden, as well as the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg-S (+29%) and 582 Gg-S (+8.8%), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is -0.11 W m-2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (-2.2 W m-2 in standard versus -1.7 W m-2 with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (-2.3 W m-2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading, as well as the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes. [ABSTRACT FROM AUTHOR]

Glyoxal (CHOCHO), the simplest dicarbonyl in the troposphere, is an important precursor for secondary organic aerosol (SOA) and brown carbon (BrC) affecting air-quality and climate. The airborne measurement of CHOCHO concentrations during the KORUS-AQ (KORea-US Air Quality study) campaign in 2016 enables detailed quantification of loss mechanisms, pertaining to SOA formation in the real atmosphere. The production of this molecule was mainly from oxidation of aromatics (59%) initiated by hydroxyl radical (OH), of which glyoxal forming mechanisms are relatively well constrained. CHOCHO loss to aerosol was found to be the most important removal path (69 %) and contributed to roughly ~20 % (3.7 μg sm-3 ppmv-1 hr-1, normalized with excess CO) of SOA growth in the first 6 hours in Seoul Metropolitan Area. To our knowledge, we show the first field observation of aerosol surface-area (4smf)-dependent CHOCHO uptake, which diverges from the simple surface uptake assumption as ^surf increases in ambient condition. Specifically, under the low (high) aerosol loading, the CHOCHO effective uptake rate coefficient, ^uptake, linearly increases (levels off) with ^uf thus, the irreversible surface uptake is a reasonable (unreasonable) approximation for simulating CHOCHO loss to aerosol. [ABSTRACT FROM AUTHOR]