Eighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud-resolved simulation of the 29-30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly-developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model-simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model-simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor-based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

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 (NOy) to modified combustion efficiency (MCE) as well as other chemical signatures indicative of flaming/smoldering combustion, including carbon monoxide (CO), nitrogen dioxide (NO2), 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 NO2, NOy, and black carbon than with CO. More than half of the NOy in fresh plumes is NO2 with an R2 of 0.95 and a ratio of NO2 to NOy of 0.55 ± 0.05 ppbv ppbv−1, highlighting that fast photochemistry had already occurred in the sampled fire plumes. The ratio of NOy 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.

Convective clouds are important for both the vertical redistribution of tropospheric trace gases and the removal, via microphysical scavenging, of soluble trace gas precursors of ozone. We investigate wet scavenging of formaldehyde (CH2O), hydrogen peroxide (H2O2), and methyl hydrogen peroxide (CH3OOH) in quasi-marine and land convective storms over Texas, USA observed on 18 September 2013 during the 2013 SEAC(4)RS campaign. Cloud-resolving simulations using the Weather Research and Forecasting model with Chemistry (WRF-Chem) were performed to understand the effect of entrainment, scavenging efficiency (SE), and ice physics processes on these trace gases with varying solubility. While marine and land convection can have distinctly different microphysical properties, we did not find significant differences in the SEs of CH2O, H2O2, or CH3OOH. The SEs of 44%-53% for CH2O and 85%-90% for H2O2 are consistent with our previous studies from SEAC(4)RS and the 2012 DC3 field experiment storms. Using WRF-Chem simulations, the ice retention factor (r(f)) for CH2O was determined to be 0.5-0.9, which is higher than found in previous studies. We show that the CH2O r(f) is higher in airmass and multicell storms than in severe storms and hypothesize that ice shattering may affect CH2O r(f) values. The CH3OOH SEs (39%-73%) were higher than expected from Henry's Law equilibrium. While recent studies suggest that CH3OOH measurements have interference due to methane diol, we find that this interference cannot fully explain the higher-than-expected CH3OOH SEs determined here and during DC3, suggesting further research is needed to understand CH3OOH vertical redistribution.

The University of Colorado Airborne Solar Occultation Flux (CU AirSOF) instrument conducted the first suborbital carbon monoxide (CO) mass flux measurements on the scale of large wildfires, showing that the destructive fires in northern California in October 2017 emitted 2,040 ± 316 tonnes CO hr −1 . Pyrogenic estimates from seven satellite‐based emission inventories bracket the observed flux, but their range spans a factor of 83. The simulated air quality impacts in the form of ozone and fine particulate matter scale primarily with these uncertain emission amounts, and range from insignificant to very severe. This uncertainty in predicting emissions is reduced to a factor of ∼2 by the CU AirSOF flux measurements, with potential for future improvements. The uncertainty is primarily the result of uncertain vegetation types and sources of radiative power measurements, and to a lesser extent uncertain emission factors and fire diurnal cycles.

The Amazon rainforest suffers increasing pressure from anthropogenic activities. A key aspect not fully understood is how anthropogenic atmospheric emissions within the basin interact with biogenic emissions and impact the forest's atmosphere and biosphere. We combine a high-resolution atmospheric chemical transport model with an improved emissions inventory and in-situ measurements to investigate a surprisingly high concentration of ozone (O3) and secondary organic aerosol (SOA) 150-200 km downwind of Manaus city in an otherwise pristine forested region. We show that atmospheric dynamics and photochemistry determine a gross production of secondary pollutants seen in the simulation. After sunrise, the erosion of the nocturnal boundary layer mixes natural forest emissions, rich in biogenic volatile organic compounds, with a lofted pollution layer transported overnight, rich in nitrogen oxides and formaldehyde. As a result, O3 and SOA concentrations greater than ∼47 ppbv and 1.8 μg m-3, respectively, were found, with maximum concentrations occurring at 2 pm LT, 150-200 km downwind of Manaus city. These high concentrations affect a large primary forested area of about 11,250 km2. These oxidative areas are under a NOx-limited regime so that changes in NOx emissions from Manaus have a significant impact on O3 and SOA production.

The effect of food texture on the development of schedule-induced polydipsia was examined in six groups of rats (n = 8), each receiving one of six grades of food granulation. A seventh group received pellets. By the end of 15 sessions of FT 60-sec food delivery, rats receiving pellets and the coarser granulations had developed polydipsia. The volume of water drunk at asymptote by the remaining groups declined with decreased coarseness of the food. Ethological analyses of the behavioral repertoire of the rats during the fifteenth session showed that the polydipsic groups sustained their drinking throughout the session, rather than turning from ingestive to exploratory behaviors near the end of the session, as was the case with animals receiving finer granulations. The enhanced drinking induced by the coarser food texture was reciprocally related to the amount of time the animal spent with its head in the feeder hole during the period of maximum drinking. The results support the conclusion that the schedule-induced polydipsia traditionally demonstrated with pellets as the reinforcer is critically dependent on the fact that pellets are coarse in texture.

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

The Green Ocean Amazon experiment – GoAmazon 2014–2015 – explored the interactions between natural biogenic forest emissions from central Amazonia and urban air pollution from Manaus. Previous GoAmazon 2014–2015 studies showed that nitrogen oxide (NOx = NO + NO2) and sulfur oxide (SOx) emissions from Manaus strongly interact with biogenic volatile organic compounds (BVOCs), affecting secondary organic aerosol (SOA) formation. In previous studies, ground-based and aircraft measurements provided evidence of SOA formation and strong changes in aerosol composition and properties. Aerosol optical properties also evolve, and their impacts on the Amazonian ecosystem can be significant. As particles age, some processes, such as SOA production, black carbon (BC) deposition, particle growth and the BC lensing effect change the aerosol optical properties, affecting the solar radiation flux at the surface. This study analyzes data and models SOA formation using the Weather Research and Forecasting with Chemistry (WRF-Chem) model to assess the spatial variability in aerosol optical properties as the Manaus plumes interact with the natural atmosphere. The following aerosol optical properties are investigated: single scattering albedo (SSA), asymmetry parameter (gaer), absorption Ångström exponent (AAE) and scattering Ångström exponent (SAE). These simulations were validated using ground-based measurements at three experimental sites, namely the Amazon Tall Tower Observatory – ATTO (T0a), downtown Manaus (T1), Tiwa Hotel (T2) and Manacapuru (T3), as well as the U.S. Department of Energy (DOE) Gulfstream 1 (G-1) aircraft flights. WRF-Chem simulations were performed over 7 d during March 2014. Results show a mean biogenic SOA (BSOA) mass enrichment of 512 % at the T1 site, 450 % in regions downwind of Manaus, such as the T3 site, and 850 % in areas north of the T3 site in simulations with anthropogenic emissions. The SOA formation is rather fast, with about 80 % of the SOA mass produced in 3–4 h. Comparing the plume from simulations with and without anthropogenic emissions, SSA shows a downwind reduction of approximately 10 %, 11 % and 6 % at the T1, T2 and T3 sites, respectively. Other regions, such as those further downwind of the T3 site, are also affected. The gaer values increased from 0.62 to 0.74 at the T1 site and from 0.67 to 0.72 at the T3 site when anthropogenic emissions are active. During the Manaus plume-aging process, a plume tracking analysis shows an increase in SSA from 0.91 close to Manaus to 0.98 160 km downwind of Manaus as a result of SOA production and BC deposition.

Nitrogen oxides (NO x ) are air pollutants critical to ozone and fine particle production in the troposphere. Here, we present fuel‐based emission inventories updated to 2018, including for mobile source engines using the Fuel‐based Inventory of Vehicle Emissions (FIVEs) and oil and gas production using the Fuel‐based Oil and Gas (FOG) inventory. The updated FIVE emissions are now consistent with the NEI17 estimates differing within 2% across the contiguous US (CONUS). Tropospheric NO 2 columns modeled by the Weather Research and Forecasting with Chemistry model (WRF‐Chem) are compared with those observed by TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI) during the summer of 2018. Modeled NO 2 columns show strong temporal and spatial correlations with TROPOMI (OMI), identified with biases of −3% (−21%) over CONUS, and +8% (−6%) over point sources plus urban regions. Taking account of the negative bias (∼20%) in early version of TROPOMI over polluted regions, WRF‐Chem shows good performance with updated FIVE and FOG emissions. Our model tends to under‐predict the tropospheric NO 2 columns over background and rural regions (bias of −21% to −3%). Through model sensitivity analyses, we demonstrate the important roles of emissions from soils (11.7% average over CONUS), oil and gas production (4.1%), wildfires (10.6%), and lightning (2.3%) with greater contributions at regional scales. This work provides a roadmap for satellite‐based evaluations for emission updates from various sources.

Wildland fires involve complicated processes that are challenging to represent in chemical transport models. Recent airborne measurements reveal remarkable chemical tomography in fresh wildland fire plumes, which remain yet to be fully explored using models. Here, we present a high‐resolution large eddy simulation model coupled to chemistry to study the chemical evolution in fresh wildland fire plume. The model is configured for a large fire heavily sampled during the Fire Influence on Regional to Global Environments and Air Quality field campaign, and a variety of airborne measurements are used to evaluate the chemical heterogeneity revealed by the model. We show that the model captures the observed cross‐transect variations of a number of compounds quite well, including ozone (O3), nitrous acid (HONO), and peroxyacetyl nitrate. The combined observational and modeling results suggest that the top and edges of fresh plume drive the photochemistry, while dark chemistry is also present but in the lower part of the plume. The model spatial resolution is shown to be very important as it may shift the chemical regime, leading to biases in O3 and NOx chemistry. Based on findings in this work, we speculate that the impact of small fires on air quality may be largely underestimated in models with coarse spatial resolutions.

Abstract Anthropogenic factors, such as ignitions, climate, and land use changes, are the primary reason why the wildfire season today is three times longer than only twenty years ago, with fires now burning year-round in the continental United States1. The quantities of fuel that go up as smoke in the form of trace gases and aerosols affect public health2,3,4 and ecosystems5, but are highly uncertain6,7,8,9 due to a lack of measurement techniques to directly quantify wildfire emissions. Uncertain emissions contribute to errors in air quality models10,11 used to forecast smoke impacts on public health in affected communities, and to inform firefighting efforts. Here we show that destructive fires in northern California during October 2017 emitted 2040 ± 316 tonnes hr-1 carbon monoxide (CO), which is more than ten times larger than the emissions from all other anthropogenic CO pollution sources in the entire state of California combined. An assessment of satellite-based emission inventories reveals that the uncertainty in predicting pyrogenic CO emissions spans a factor of 83. Air quality impacts in the form of ozone and fine particulate matter range from insignificant to very severe (vary by two orders of magnitude), and scale with uncertain emissions caused primarily by the different ecosystem classification among emission inventories. This uncertainty is reduced to a factor of ~2 by our first CO mass flux measurements on the scale of actual wildfires. We derive the conversion factor of satellite fire radiative energy to CO emissions (α = 73 ± 11 to 149 ± 23 g CO MJ-1) for savannah and extratropical forest fuels of these fires, which is higher (+30 to +230%) than tabulated for these fuel types. Our results help to improve future model predictions, and suggest an additional organic soil contribution to emissions from wildfires in northern California.