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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.

WRF-Chem and a modified version of the ECLIPSE 5a emission inventory were used to investigate the sources impacting black carbon (BC) deposition to the Himalaya, Karakoram, and Hindu Kush (HKHK) region. This work extends previous studies by simulating deposition to the HKHK region not only under current conditions, but also in the 2040-2050 period under two realistic emission scenarios and in three different phases of the El Nino-Southern Oscillation (ENSO). Under current conditions, sources from outside our South Asian modelling domain have a similar impact on total BC deposition to the HKHK region (35-87%, varying with month) as South Asian anthropogenic sources (13-62%). Industry (primarily brick kilns) and residential solid fuel burning combined account for 45-66% of the in-domain anthropogenic BC deposition to the HKHK region. Under a no further control emission scenario for 2040-2050, the relative contributions to BC deposition in the HKHK region are more skewed toward in-domain anthropogenic sources (45-65%) relative to sources outside the domain (26-52%). The in-domain anthropogenic BC deposition has significant contributions from industry (32-42%), solid fuel burning (17-28%), and diesel fuel burning (17-27%). Under a scenario in which emissions in South Asia are mitigated, the relative cotribution from South Asian anthropogenic sources is significantly reduced to 11-34%. The changes due to phase of ENSO do not seem to follow consistent patterns with ENSO. Future work will use the high-resolution deposition maps developed here to determine the impact of different sources of BC on glacier melt and water availability in the region.

We developed and evaluated three types of statistical forecasting models (quantitative, probabilistic, and classification) for predicting the maximum daily 8-hour average concentration of ozone based on meteorological and ozone monitoring data for six Texas urban areas from 2009 to 2015. The quantitative and probabilistic forecasting models were generalized additive models (GAMs), whereas the classification forecast used the random forest machine learning method. We found that for the quantitative forecasting models, five of the eight predictors (the day of week, day of the year, water vapor density, wind speed, and previous day’s ozone measurement) were significant at the α = 0.001 level for all urban areas, whereas the other three varied in significance according to the location. The quantitative forecasting for the 2016 ozone season agreed well with the associated measurements (R2 of ~0.70), but it tended to under-predict the ozone level for the days with the highest concentrations. By contrast, the probabilistic forecasting models showed little accuracy in determining the probability of concentrations exceeding policy-relevant thresholds during this season. The success rate for the random forest classification models typically exceeded 75% and would likely increase if the training data sets contained more extreme events.

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 variability in smoke evolution. Here, we use observational data from the BBOP field campaign and show that initial smoke concentrations can help predict changes in smoke aerosol aging markers, number, and diameter. Because initial field measurements of plumes are generally > 10 minutes downwind, smaller plumes will have already undergone substantial dilution relative to larger plumes. However, the extent to which dilution has occurred prior to the first observation is not a measurable quantity. Hence, initial observed concentrations can serve as an indicator of dilution, which impacts photochemistry and aerosol evaporation. Cores of plumes have higher concentrations than edges. By segregating the observed plumes into cores and edges, we infer that particle aging, evaporation, and coagulation occurred before the first measurement, and we find that edges generally undergo higher increases in oxidation tracers, more decreases in semivolatile compounds, and less coagulation than the cores.

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.

Simultaneous high-time-resolution measurements of atmospheric NH3 ,H NO3, soluble gas-phase chloride, and aerosol species were made in Houston, TX, from August 5, 2010 to August 9, 2010. Gaseous NH3 was measured using a 10.4-mm external cavity quantum cascade laser-based sensor employing conventional photo-acoustic spectroscopy, while gaseous HNO3 and HCl were sampled using a mist chambereion chromatograph (IC) system. Particle chemical composition was determined using a particle-into-liquidsamplereIC system. There was a large amount of variability in the gas phase mixing ratios of NH3 (3.0 � 2.5 ppb), HNO3 (287.4 � 291.6 ppt), and HCl (221.3 � 260.7 ppt). Elevated NH3 levels occurred around mid-day when NH4 þ (0.5 � 1.0 mgm � 3 ) andSO4 2� (4.5 � 4.3mgm � 3 ) alsoincreasedconsiderably,indicating that NH3 likely influenced aerosol particle mass. By contrast, the formation of NH4NO3 and NH4Cl was not observed during the measurements. Point sources (e.g., power plant and chemical plant) might be potential contributors to the enhancements in NH3 at the measurement site under favorable meteorological conditions. Increased particle number concentrations were predicted by the SAM-TOMAS model downwind of a large coal-fired power plant when NH3 emissions (based on these measurements) were included, highlighting the potential importance of NH3 with respect to particle number concentration. Separate measurements also indicate the role of NH3 in new particle formation in Houston under low-sulfur conditions.

NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are to used to evaluate modelled 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) CalNex emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.54. However, the surface observations at Bakersfield indicate a missing 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 the afternoon NH3 emissions in the CARB inventory are underestimated by at least a factor of two, while the night-time overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions, underestimated deposition, and insufficient vertical mixing in the WRF meteorological fields used to drive CMAQ. We used the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which night-time and midday emissions differed by about a factor of 4.5. Adding this diurnal profile to the CMAQ simulations while keeping the daily NH3 emissions constant at the CARB values significantly improved the model performance at night, but sizable errors (up to 15 ppbv) in night-time NH3 remain, likely due to remaining errors in vertical mixing at night. The model performance is slightly degraded during the afternoon when the diurnal cycle is adjusted, but this may reflect relatively small (~ 20 %) errors in the total NH3 emissions rather than remaining errors in the diurnal cycle. Running CMAQv5.0.2 with bi-directional NH3 flux also improves model performance on a similar scale, while combining bi-directional NH3 fluxes and adjusted emissions significantly reduces the model bias at night.

Within minutes after emission, rapid, complex photochemistry within a biomass burning smoke plume 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 burn 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 semi-volatile to extremely low volatility organic compounds (here collectively called "SVOCs") on the formation of OA (using the Volatility Basis Set) and O3 (using the concept of mechanistic reactivity). We show that this method can successfully simulate the observations of O3, OA, PAN, NOx, and C2H4 to within measurement uncertainty using reasonable assumptions about the chemistry of the unidentified SVOCs. These assumptions were: (1) a~reaction rate constant with OH of ~10−11cm3s−1, (2) a significant fraction (~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 SVOCs 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, which is consistent with our assumed fragmentation rate. 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. For the W.A. Parish power plant (near Houston, TX) during this time period, NOx emissions were reduced by ~90%, while SO2 emissions decreased by ~30%. Increases in plume OH (due to the reduced NOx) produced enhanced SO2 oxidation and particle nucleation despite the reduction in SO2 emissions. These results suggest that NOx emissions may strongly regulate particle nucleation and growth in power-plant plumes. Comparison of model results with airborne measurements made in the W.A. Parish power-plant plume in 2000 and 2006 confirm the importance of NOx emissions on new particle formation, yet also highlight the substantial effect of background aerosol loadings on this process. A wide range of NOx and SO2 emissions were modeled to understand how they affect particle formation in the plume. 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. Finally, we calculate emissions 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 ratesfrom 1997 to 2010 (whereas the W.A. Parish case study showed an increase). These results suggest that there may be important climate implications of power-plant controls due to changes in plume chemistry and microphysics. More extensive plume measurements for a range of emissions of SO2 and NOx and in varying background aerosol conditions are needed to better quantify these effects.

1. A primary growth crop of perennial ryegrass (Lolium perenneL., cv. S23) was partially wilted and ensiled after the application of eitherformic acid–water (1:3, w/v; 7.1 1/t fresh herbage; control diet C) or formic acid–formaldehyde (1:1, w/w; 8·81/t fresh herbage; formaldehyde treated diet F) which supplied 50gHCHO/kg crude protein (nitrogen (N) × 6·25). The two silages were fed separately and a third diet comprising formaldehyde-treated silage, supplemented with urea (20 g/kg dry matter dm) at the time of feeding was also examined (dietFU).2. The three diets were fed at a level of 16 g dm/kg live weight to six 3- to six-month-old cattle fitted with rumen and re-entrant duodenal cannulas in two 3 × 3 LatinSquare experiments, and measurements were made of the digestion of energy, carbohydrateand N.3. The formaldehyde-treated silage had a lower content of fermentation acids and ammoma-N and a higher content of water-soluble carbohydrate and total amino acids. The apparent digestibility of organic matter, energy and N were depressed (P < 0·05, P < 0·05 and P < 0·01 respectively) by treatment with formaldehyde, but cellulose and neutral-detergent fibre digestibility were unaffected.4. Within the rumen the digestion of organic matter, cellulose and neutral-detergent fibre were unaffected by formaldehyde treatment or supplementation with urea. Microbial protein synthesis in the rumen was similar for the three diets (average 131 g/kg apparently digested organic matter in the rumen).5. The application of formic acid-formaldehyde increased (P < 0·05) the amount of food protein escaping degradation in the rumen (4·76 diet C, 6·89 diet F; 7·07 diet FU g/kg protein intake). The contribution of amino acidsof dietary origin al the duodenum increased (P < 0·05) from 50 (diet C) to 80 (diet F) and 82 (diet FU) g/kg DM intake, and the flow of total amino acids at the duodenum was 33% higher (P < 0·001) in cattle fed formic acid–form aldehyde silage diets compared withthe control silage due to the reduction in degradation of protein at ensiling and in therumen.