A method is developed to estimate global NO2 and SO2 dry deposition fluxes at high spatial resolution (0.1°×0.1°) using satellite measurements from the Ozone Monitoring Instrument (OMI) on the Aura ...satellite, in combination with simulations from the Goddard Earth Observing System chemical transport model (GEOS‐Chem). These global maps for 2005–2007 provide a data set for use in examining global and regional budgets of deposition. In order to properly assess SO2 on a global scale, a method is developed to account for the geospatial character of background offsets in retrieved satellite columns. Globally, annual dry deposition to land estimated from OMI as NO2 contributes 1.5 ± 0.5 Tg of nitrogen and as SO2 contributes 13.7 ± 4.0 Tg of sulfur. Differences between OMI‐inferred NO2 dry deposition fluxes and those of other models and observations vary from excellent agreement to an order of magnitude difference, with OMI typically on the low end of estimates. SO2 dry deposition fluxes compare well with in situ Clear Air Status and Trends Network‐inferred flux over North America (slope = 0.98, r = 0.71). The most significant NO2 dry deposition flux to land per area occurs in the Pearl River Delta, China, at 13.9 kg N ha−1 yr−1, while SO2 dry deposition has a global maximum rate of 72.0 kg S ha−1 yr−1 to the east of Jinan in China's Shandong province. Dry deposition fluxes are explored in several urban areas, where NO2 contributes on average 9–36% and as much as 85% of total NOy dry deposition.
Key PointsNO2 and SO2 dry deposition is derived from space‐based measurementsGlobal and regional budgets of dry deposition are determinedNO2 and SO2 deposition in urban areas is examined
Particulate organic matter is of interest for air quality and climate research, but the relationship between ambient organic mass (OM) and organic carbon (OC) remains ambiguous both in measurements ...and in modeling. We present a simple method to derive an estimate of the spatially and seasonally resolved global, lower tropospheric, ratio between OM and OC. We assume ambient NO2 concentrations as a surrogate for fresh emission which mostly determines the continental scale OM/OC ratio. For this, we first develop a parameterization for the OM/OC ratio using the primary organic aerosol (POA) fraction of total OM estimated globally from Aerosol Mass Spectrometer (AMS) measurements, and evaluate it with high mass resolution AMS data. Second, we explore the ability of ground-level NO2 concentrations derived from the OMI satellite sensor to serve as a proxy for fresh emissions that have a high POA fraction, and apply NO2 data to derive ambient POA fraction. The combination of these two methods yields an estimate of OM/OC from NO2 measurements. Although this method has inherent deficiencies over biomass burning, free-tropospheric, and marine environments, elsewhere it offers more information than the currently used global-mean OM/OC ratios. The OMI-derived global OM/OC ratio ranges from 1.3 to 2.1 (μg/μgC), with distinct spatial variation between urban and rural regions. The seasonal OM/OC ratio has a summer maximum and a winter minimum over regions dominated by combustion emissions. This dataset serves as a tool for interpreting organic carbon measurements, and for evaluating modeling of atmospheric organics. We also develop an additional parameterization for models to estimate the ratio of primary OM to OC from simulated NOx concentrations.
•Simple method to estimate spatially and seasonally resolved OM/OC.•The OM/OC ratio can be estimated from satellite-derived NO2 concentrations.•Parameterization developed from Aerosol Mass Spectrometer measurements.•OM/OC is lower in urban areas and higher in rural areas.•OM/OC is lower in winter and higher in summer.
The absence of up-to-date emissions has been a major impediment to accurately simulating aspects of atmospheric chemistry and to precisely quantifying the impact of changes in emissions on air ...pollution. Hence, a nonlinear joint analytical inversion (Gauss–Newton method) of both volatile organic compounds (VOCs) and nitrogen oxide (NOx) emissions is made by exploiting the Smithsonian Astrophysical Observatory (SAO) Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) formaldehyde (HCHO) and the National Aeronautics and Space Administration (NASA) Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) columns during the Korea–United States Air Quality (KORUS-AQ) campaign over East Asia in May–June 2016. Effects of the chemical feedback of NOx and VOCs on bothNO2 and HCHO are implicitly included by iteratively optimizing the inversion. Emission uncertainties are greatly narrowed (averaging kernels >0.8, which is the mathematical presentation of the partition of information gained from the satellite observations with respect to the prior knowledge) over medium- to high-emitting areas such as cities and dense vegetation. The prior amount of total NOx emissions is mainly dictated by values reported in the MIX-Asia 2010 inventory. After the inversion we conclude that there is a decline in emissions (before, after, change) for China (87.94±44.09 Gg d-1, 68.00±15.94 Gg d-1, -23 %), North China Plain (NCP) (27.96±13.49 Gg d-1, 19.05±2.50 Gg d-1,-32 %), Pearl River Delta (PRD) (4.23±1.78 Gg d-1, 2.70±0.32 Gg d-1, -36 %), Yangtze River Delta (YRD) (9.84±4.68 Gg d-1,5.77±0.51 Gg d-1, -41 %), Taiwan (1.26±0.57 Gg d-1,0.97±0.33 Gg d-1, -23 %), and Malaysia (2.89±2.77 Gg d-1,2.25±1.34 Gg d-1, -22 %), all of which have effectively implemented various stringent regulations. In contrast, South Korea (2.71±1.34 Gg d-1, 2.95±0.58 Gg d-1, +9 %) and Japan (3.53±1.71 Gg d-1, 3.96±1.04 Gg d-1, +12 %) are experiencing an increase inNOx emissions, potentially due to an increased number of diesel vehicles and new thermal power plants. We revisit the well-documented positive bias (by a factor of 2 to 3) of MEGAN v2.1 (Model of Emissions of Gases and Aerosols from Nature) in terms of biogenic VOC emissions in the tropics. The inversion, however, suggests a larger growth of VOCs (mainly anthropogenic) over NCP (25 %) than previously reported (6 %) relative to 2010. The spatial variation in both the magnitude and sign of NOx and VOC emissions results in nonlinear responses of ozone production and loss. Due to a simultaneous decrease and increase in NOx/VOC over NCP and YRD, we observe a ∼53 % reduction in the ratio of the chemical loss of NOx (LNOx) to the chemical loss of ROx (RO2+HO2) over the surface transitioning toward NOx-sensitive regimes, which in turn reduces and increases the afternoon chemical loss and production of ozone through NO2+OH (-0.42 ppbv h-1)/HO2 (and RO2)+NO (+0.31 ppbv h-1). Conversely, a combined decrease in NOx and VOC emissions in Taiwan, Malaysia, and southern China suppresses the formation of ozone. Simulations using the updated emissions indicate increases in maximum daily 8 h average (MDA8) surface ozone over China (0.62 ppbv), NCP (4.56 ppbv), and YRD (5.25 ppbv), suggesting that emission control strategies on VOCs should be prioritized to curb ozone production rates in these regions. Taiwan, Malaysia, and PRD stand out as regions undergoing lower MDA8 ozone levels resulting from the NOx reductions occurring predominantly in NOx-sensitive regimes.
Airborne and ground-based Pandora spectrometer NO2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound ...region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2= 0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2=0.96) than Pandora measurements are with TROPOMI (r2=0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5∘) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4 %–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19 %–33 % during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12 %–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7 %–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.
Retrievals of sulfur dioxide (SO2) from space‐based spectrometers are in a relatively early stage of development. Factors such as interference between ozone and SO2 in the retrieval algorithms often ...lead to errors in the retrieved values. Measurements from the Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Global Ozone Monitoring Experiment‐2 (GOME‐2) satellite sensors, averaged over a period of several years, were used to identify locations with elevated SO2 values and estimate their emission levels. About 30 such locations, detectable by all three sensors and linked to volcanic and anthropogenic sources, were found after applying low and high spatial frequency filtration designed to reduce noise and bias and to enhance weak signals to SO2 data from each instrument. Quantitatively, the mean amount of SO2 in the vicinity of the sources, estimated from the three instruments, is in general agreement. However, its better spatial resolution makes it possible for OMI to detect smaller sources and with additional detail as compared to the other two instruments. Over some regions of China, SCIAMACHY and GOME‐2 data show mean SO2 values that are almost 1.5 times higher than those from OMI, but the suggested spatial filtration technique largely reconciles these differences.
Key Points
Available satellite SO2 data can be used to monitor large emission sources
SO2 data from different satellites agree when spatial filtration is applied
Instruments with higher spatial resolution can detect smaller emission sources
We apply an optimal estimation algorithm originally developed for retrieving ozone profiles from the Global Ozone Monitoring Experiment (GOME) and the Ozone Monitoring Instrument (OMI) to make global ...observations of sulfur dioxide from the Global Ozone Monitoring Experiment 2 (GOME‐2) on the MetOp‐A satellite. Our approach combines a full radiative transfer calculation, retrieval algorithm, and trace gas climatologies to implicitly include the effects of albedo, clouds, ozone, and SO2 profiles in the retrieval. Under volcanic conditions, the algorithm may also be used to directly retrieve SO2 plume altitude. Retrieved SO2 columns over heavy anthropogenic pollution typically agree with those calculated using a two‐step slant column and air mass factor approach to within 10%. Retrieval uncertainties are quantified for GOME‐2 SO2 amounts; these are dominated by uncertainty contributions from noise, surface albedo, profile shape, correlations with other retrieved parameters, atmospheric temperature, choice of wavelength fitting window, and aerosols. When plume altitudes are also simultaneously retrieved, additional significant uncertainties result from uncertainties in the a priori altitude, the model's vertical layer resolution, and instrument calibration. Retrieved plume height information content is examined using the Mount Kasatochi volcanic plume on 9 August 2008. An a priori altitude of 10 km and uncertainty of 2 km produce degrees of freedom for signal of at least 0.9 for columns >30 Dobson units. GOME‐2 estimates of surface SO2 are compared with in situ annual means over North America in 2008 from the Clear Air Status and Trends Network (CASTNET; r = 0.85, N = 65) and Air Quality System (AQS) and National Air Pollution Surveillance (NAPS; r = 0.40, N = 438) networks.
Key Points
The GOME and OMI ozone profile algorithm is extended to retrieve SO2 from GOME‐2
Error analysis is performed for SO2 anthropogenic and volcanic retrievals
Surface SO2 from GOME‐2 is validated with in situ data over North America
The northern high latitudes (50–90° N, mostly including boreal-forest and tundra ecosystems) have been undergoing rapid climate and ecological changes over recent decades, leading to significant ...variations in volatile organic compounds (VOC) emissions from biogenic and biomass burning sources. Formaldehyde (HCHO) is an indicator of VOC emissions, but the interannual variability of HCHO and its main drivers over the region remains unclear. In this study, we use the GEOS-Chem chemical transport model and satellite retrievals from the Ozone Monitoring Instrument (OMI) and the Ozone Mapping and Profiler Suite (OMPS) to examine the interannual variability of HCHO vertical column density (VCD) during the summer seasons spanning from 2005 to 2019. Our results show that, in 2005–2019 summers, wildfires contributed 75 %–90 % of the interannual variability of HCHO VCD over Siberia, Alaska and northern Canada, while biogenic emissions and background methane oxidation account for ∼ 90 % of HCHO interannual variability over eastern Europe. We find that monthly solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2), an efficient proxy for plant photosynthesis, shows a good linear relationship (R= 0.6–0.7) with the modeled biogenic HCHO column (dVCDBio,GC) in eastern Europe, Siberia, Alaska and northern Canada, indicating the coupling between SIF and biogenic VOC emissions over the four domains on a monthly scale. In Alaska, Siberia and northern Canada, SIF and dVCDBio,GC both show relatively lower interannual variabilities (SIF: CV = 1 %–9 %, dVCDBio,GC: CV = 1 %–2 %; note that CV stands for coefficient of variation) in comparison to wildfire-induced HCHO (CV = 8 %–13 %), suggesting that the high interannual variabilities of OMI HCHO VCD (CV = 10 %–16 %) in these domains are likely driven by wildfires instead of biogenic emissions.
Many patients with hematological neoplasms fail to mobilize sufficient numbers of hematopoietic stem cells (HSCs) in response to granulocyte colony-stimulating factor (G-CSF) precluding subsequent ...autologous HSC transplantation. Plerixafor, a specific antagonist of the chemokine receptor CXCR4, can rescue some but not all patients who failed to mobilize with G-CSF alone. These refractory poor mobilizers cannot currently benefit from autologous transplantation. To discover alternative targetable pathways to enhance HSC mobilization, we studied the role of hypoxia-inducible factor-1α (HIF-1α) and the effect of HIF-1α pharmacological stabilization on HSC mobilization in mice. We demonstrate in mice with HSC-specific conditional deletion of the Hif1a gene that the oxygen-labile transcription factor HIF-1α is essential for HSC mobilization in response to G-CSF and Plerixafor. Conversely, pharmacological stabilization of HIF-1α with the 4-prolyl hydroxylase inhibitor FG-4497 synergizes with G-CSF and Plerixafor increasing mobilization of reconstituting HSCs 20-fold compared with G-CSF plus Plerixafor, currently the most potent mobilizing combination used in the clinic.
Formaldehyde (HCHO) has been measured from space for more
than 2 decades. Owing to its short atmospheric lifetime, satellite HCHO
data are used widely as a proxy of volatile organic compounds (VOCs; ...please
refer to Appendix A for abbreviations and acronyms), providing constraints
on underlying emissions and chemistry. However, satellite HCHO products from
different satellite sensors using different algorithms have received little
validation so far. The accuracy and consistency of HCHO retrievals remain
largely unclear. Here we develop a validation platform for satellite HCHO
retrievals using in situ observations from 12 aircraft campaigns with a chemical
transport model (GEOS-Chem) as the intercomparison method. Application to
the NASA operational OMI HCHO product indicates negative biases (−44.5 %
to −21.7 %) under high-HCHO conditions, while it indicates high biases (+66.1 % to
+112.1 %) under low-HCHO conditions. Under both conditions, HCHO a priori
vertical profiles are likely not the main driver of the biases. By providing
quick assessment of systematic biases in satellite products over large
domains, the platform facilitates, in an iterative process, optimization of
retrieval settings and the minimization of retrieval biases. It is also
complementary to localized validation efforts based on ground observations
and aircraft spirals.
Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes ...in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO
and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO
columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO
emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO
emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO
. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO
reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (
= 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative
become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.
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