Search

Nitrogen oxides (NOx=NO+NO2) emissions are estimated in three regions in the Northern Hemisphere, generally located in North America, Europe, and East Asia, by calculating the directional derivatives of NO2 column amounts observed by the TROPOspheric Monitoring Instrument (TROPOMI) with respect to the horizontal wind vectors. We present monthly averaged emissions from 1 May 2018 to 31 January 2023 to capture variations before and after the COVID-19 pandemic. We focus on a diverse collection of 54 cities, 18 in each region. A spatial resolution of 0.04∘ resolves intracity emission variations and reveals NOx emission hotspots at city cores, industrial areas, and sea ports. For each selected city, post-COVID-19 changes in NOx emissions are estimated by comparing monthly and annually averaged values to the pre-COVID-19 year of 2019. While emission reductions are initially found during the first outbreak of COVID-19 in early 2020 in most cities, the cities' paths diverge afterwards. We group the selected cities into four clusters according to their normalized annual NOx emissions in 2019–2022 using an unsupervised learning algorithm. All but one of the selected North American cities fall into cluster 1 characterized by weak emission reduction in 2020 (−7 % relative to 2019) and an increase in 2022 by +5 %. Cluster 2 contains mostly European cities and is characterized by the largest reduction in 2020 (−31 %), whereas the selected East Asian cities generally fall into clusters 3 and 4, with the largest impacts in 2022 (−25 % and −37 %). This directional derivative approach has been implemented in object-oriented, open-source Python and is available publicly for high-resolution and low-latency emission estimation for different regions, atmospheric species, and satellite instruments.

Biomass burning emits vapors and aerosols into the atmosphere that can rapidly evolve as smoke plumes travel downwind and dilute, affecting climate- and health-relevant properties of the smoke. To date, theory has been unable to explain observed variability in smoke evolution. Here, we use observational data from the Biomass Burning Observation Project (BBOP) field campaign and show that initial smoke organic aerosol mass concentrations can help predict changes in smoke aerosol aging markers, number concentration, and number mean diameter between 40–262 nm. Because initial field measurements of plumes are generally >10 min downwind, smaller plumes will have already undergone substantial dilution relative to larger plumes and have lower concentrations of smoke species at these observations closest to the fire. The extent to which dilution has occurred prior to the first observation is not a directly measurable quantity. We show that initial observed plume concentrations can serve as a rough indicator of the extent of dilution prior to the first measurement, which impacts photochemistry, aerosol evaporation, and coagulation. Cores of plumes have higher concentrations than edges. By segregating the observed plumes into cores and edges, we find evidence that particle aging, evaporation, and coagulation occurred before the first measurement. We further find that on the plume edges, the organic aerosol is more oxygenated, while a marker for primary biomass burning aerosol emissions has decreased in relative abundance compared to the plume cores. Finally, we attempt to decouple the roles of the initial concentrations and physical age since emission by performing multivariate linear regression of various aerosol properties (composition, size) on these two factors.

Biomass burning is a major source of trace gases and aerosols that can ultimately impact health, air quality, and climate. Global and regional-scale three-dimensional Eulerian chemical transport models (CTMs) use estimates of the primary emissions from fires and can unphysically mix them across large-scale grid boxes, leading to incorrect estimates of the impact of biomass burning events. On the other hand, plume-scale process models allow for explicit simulation and examination of the chemical and physical transformations of trace gases and aerosols within biomass burning smoke plumes, and they may be used to develop parameterizations of this aging process for coarser grid-scale models. Here we describe the coupled SAM-ASP plume-scale process model, which consists of coupling the large-eddy simulation model, the System for Atmospheric Modelling (SAM), with the detailed gas and aerosol chemistry model, the Aerosol Simulation Program (ASP). We find that the SAM-ASP version 1.0 model is able to correctly simulate the dilution of CO in a California chaparral smoke plume, as well as the chemical loss of NOx, HONO, and NH3 within the plume, the formation of PAN and O3, the loss of OA, and the change in the size distribution of aerosols as compared to measurements and previous single-box model results. The newly coupled model is able to capture the cross-plume vertical and horizontal concentration gradients as the fire plume evolves downwind of the emission source. The integration and evaluation of SAM-ASP version 1.0 presented here will support the development of parameterizations of near-source biomass burning chemistry that can be used to more accurately simulate biomass burning chemical and physical transformations of trace gases and aerosols within coarser grid-scale CTMs.

Biomass burning is a significant global source of aerosol number and mass. In fresh biomass burning plumes, aerosol coagulation reduces aerosol number and increases the median size of aerosol size distributions, impacting aerosol radiative effects. Near-source biomass burning aerosol coagulation occurs at spatial scales much smaller than the grid boxes of global and many regional models. To date, these models have ignored sub-grid coagulation and instantly mixed fresh biomass burning emissions into coarse grid boxes. A previous study found that the rate of particle growth by coagulation within an individual smoke plume can be approximated using the aerosol mass emissions rate, initial size distribution median diameter and modal width, plume mixing depth, and wind speed. In this paper, we use this parameterization of sub-grid coagulation in the GEOS-Chem–TOMAS (TwO-Moment Aerosol Sectional) global aerosol microphysics model to quantify the impacts on global aerosol size distributions, the direct radiative effect, and the cloud-albedo aerosol indirect effect. We find that inclusion of biomass burning sub-grid coagulation reduces the biomass burning impact on the number concentration of particles larger than 80 nm (a proxy for CCN-sized particles) by 37 % globally. This cloud condensation nuclei (CCN) reduction causes our estimated global biomass burning cloud-albedo aerosol indirect effect to decrease from −76 to −43 mW m−2. Further, as sub-grid coagulation moves mass to sizes with more efficient scattering, including it increases our estimated biomass burning all-sky direct effect from −224 to −231 mW m−2, with assumed external mixing of black carbon and from −188 to −197 mW m−2 and with assumed internal mixing of black carbon with core-shell morphology. However, due to differences in fire and meteorological conditions across regions, the impact of sub-grid coagulation is not globally uniform. We also test the sensitivity of the impact of sub-grid coagulation to two different biomass burning emission inventories to various assumptions about the fresh biomass burning aerosol size distribution and to two different timescales of sub-grid coagulation. The impacts of sub-grid coagulation are qualitatively the same regardless of these assumptions.

NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are used to evaluate modeled concentrations of NH3(g) and NH4(p) from the Community Multiscale Air Quality (CMAQ) model in the San Joaquin Valley (SJV) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) campaign. We find that simulations of NH3 driven with the California Air Resources Board (CARB) emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.64. However, the surface observations at Bakersfield indicate a diurnal cycle in the model bias, with CMAQ overestimating surface NH3 at night and underestimating it during the day. The surface, satellite, and aircraft observations all suggest that daytime NH3 emissions in the CARB inventory are underestimated by at least a factor of 2, while the nighttime overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions and underestimated deposition.Running CMAQ v5.0.2 with the bi-directional NH3 scheme reduces NH3 concentrations at night and increases them during the day. This reduces the model bias when compared to the surface and satellite observations, but the increased concentrations aloft significantly increase the bias relative to the aircraft observations. We attempt to further reduce model bias by using the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which nighttime and midday emissions differ by about a factor of 4.5. Running CMAQv5.0.2 with a bi-directional NH3 scheme together with this emissions diurnal profile further reduces model bias relative to the surface observations. Comparison of these simulations with the vertical profile retrieved by TES shows little bias except for the lowest retrieved level, but the model bias relative to flight data aloft increases slightly. Our results indicate that both diurnally varying emissions and a bi-directional NH3 scheme should be applied when modeling NH3(g) and NH4(p) in this region. The remaining model errors suggest that the bi-directional NH3 scheme in CMAQ v5.0.2 needs further improvements to shift the peak NH3 land–atmosphere flux to earlier in the day. We recommend that future work include updates to the current CARB NH3 inventory to account for NH3 from fertilizer application, livestock, and other farming practices separately; adding revised information on crop management practices specific to the SJV region to the bi-directional NH3 scheme; and top-down studies focused on determining the diurnally varying biases in the canopy compensation point that determines the net land–atmosphere NH3 fluxes.

Accurate modeling of the scattering and absorption of ultraviolet and visible radiation by aerosols is essential for accurate simulations of atmospheric chemistry and climate. Closure studies using in situ measurements of aerosol scattering and absorption can be used to evaluate and improve models of aerosol optical properties without interference from model errors in aerosol emissions, transport, chemistry, or deposition rates. Here we evaluate the ability of four externally mixed, fixed size distribution parameterizations used in global models to simulate submicron aerosol scattering and absorption at three wavelengths using in situ data gathered during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. The four models are the NASA Global Modeling Initiative (GMI) Combo model, GEOS-Chem v9-02, the baseline configuration of a version of GEOS-Chem with online radiative transfer calculations (called GC-RT), and the Optical Properties of Aerosol and Clouds (OPAC v3.1) package. We also use the ARCTAS data to perform the first evaluation of the ability of the Aerosol Simulation Program (ASP v2.1) to simulate submicron aerosol scattering and absorption when in situ data on the aerosol size distribution are used, and examine the impact of different mixing rules for black carbon (BC) on the results. We find that the GMI model tends to overestimate submicron scattering and absorption at shorter wavelengths by 10–23 %, and that GMI has smaller absolute mean biases for submicron absorption than OPAC v3.1, GEOS-Chem v9-02, or GC-RT. However, the changes to the density and refractive index of BC in GC-RT improve the simulation of submicron aerosol absorption at all wavelengths relative to GEOS-Chem v9-02. Adding a variable size distribution, as in ASP v2.1, improves model performance for scattering but not for absorption, likely due to the assumption in ASP v2.1 that BC is present at a constant mass fraction throughout the aerosol size distribution. Using a core-shell mixing rule in ASP overestimates aerosol absorption, especially for the fresh biomass burning aerosol measured in ARCTAS-B, suggesting the need for modeling the time-varying mixing states of aerosols in future versions of ASP.

Within minutes after emission, complex photochemistry in biomass burning smoke plumes can cause large changes in the concentrations of ozone (O3) and organic aerosol (OA). Being able to understand and simulate this rapid chemical evolution under a wide variety of conditions is a critical part of forecasting the impact of these fires on air quality, atmospheric composition, and climate. Here we use version 2.1 of the Aerosol Simulation Program (ASP) to simulate the evolution of O3 and secondary organic aerosol (SOA) within a young biomass burning smoke plume from the Williams prescribed fire in chaparral, which was sampled over California in November 2009. We demonstrate the use of a method for simultaneously accounting for the impact of the unidentified intermediate volatility, semi-volatile, and extremely low volatility organic compounds (here collectively called "SVOCs") on the formation of OA (using the Volatility Basis Set – VBS) and O3 (using the concept of mechanistic reactivity). We show that this method can successfully simulate the observations of O3, OA, NOx, ethylene (C2H4), and OH to within measurement uncertainty using reasonable assumptions about the average chemistry of the unidentified SVOCs. These assumptions were (1) a reaction rate constant with OH of ~ 10-11 cm3 s−1; (2) a significant fraction (up to ~ 50 %) of the RO2 + NO reaction resulted in fragmentation, rather than functionalization, of the parent SVOC; (3) ~ 1.1 molecules of O3 were formed for every molecule of SVOC that reacted; (4) ~ 60 % of the OH that reacted with the unidentified non-methane organic compounds (NMOC) was regenerated as HO2; and (5) that ~ 50 % of the NO that reacted with the SVOC peroxy radicals was lost, presumably to organic nitrate formation. Additional evidence for the fragmentation pathway is provided by the observed rate of formation of acetic acid (CH3COOH), which is consistent with our assumed fragmentation rate. However, the model overestimates peroxyacetyl nitrate (PAN) formation downwind by about 50 %, suggesting the need for further refinements to the chemistry. This method could provide a way for classifying different smoke plume observations in terms of the average chemistry of their SVOCs, and could be used to study how the chemistry of these compounds (and the O3 and OA they form) varies between plumes.

Nucleation in coal-fired power-plant plumes can greatly contribute to particle number concentrations near source regions. The changing emissions rates of SO2 and NOx due to pollution-control technologies over recent decades may have had a significant effect on aerosol formation and growth in the plumes with ultimate implications for climate and human health. We use the System for Atmospheric Modeling (SAM) large-eddy simulation model with the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm to model the nucleation in plumes of coal-fired plants. We test a range of cases with varying emissions to simulate the implementation of emissions-control technologies between 1997 and 2010. We start by simulating the W. A. Parish power plant (near Houston, TX) during this time period, when NOx emissions were reduced by ~90% and SO2 emissions decreased by ~30%. Increases in plume OH (due to the reduced NOx) produced enhanced SO2 oxidation and an order-of-magnitude increase in particle nucleation in the plume despite the reduction in SO2 emissions. These results suggest that NOx emissions could strongly regulate particle nucleation and growth in power-plant plumes. Next, we test a range of cases with varying emissions to simulate the implementation of SO2 and NOx emissions-control technologies. Particle formation generally increases with SO2 emission, while NOx shows two different regimes: increasing particle formation with increasing NOx under low-NOx emissions and decreasing particle formation with increasing NOx under high-NOx emissions. Next, we compare model results with airborne measurements made in the W. A. Parish power-plant plume in 2000 and 2006, confirming the importance of NOx emissions on new particle formation and highlighting the substantial effect of background aerosol loadings on this process (the more polluted background of the 2006 case caused more than an order-of-magnitude reduction in particle formation in the plume compared to the cleaner test day in 2000). Finally, we calculate particle-formation statistics of 330 coal-fired power plants in the US in 1997 and 2010, and the model results show a median decrease of 19% in particle formation rates from 1997 to 2010 (whereas the W. A. Parish case study showed an increase). Thus, the US power plants, on average, show a different result than was found for the W. A. Parish plant specifically, and it shows that the strong NOx controls (90% reduction) implemented at the W. A. Parish plant (with relatively weak SO2 emissions reductions, 30%) are not representative of most power plants in the US during the past 15 yr. These results suggest that there may be important climate implications of power-plant controls due to changes in plume chemistry and microphysics, but the magnitude and sign of the aerosol changes depend greatly on the relative reductions in NOx and SO2 emissions in each plant. More extensive plume measurements for a range of emissions of SO2 and NOx and in varying background aerosol conditions are needed, however, to better quantify these effects.