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Abstract A limitation in fine-tuned tree-ring radiocarbon (¹⁴C) data is normally associated with overall data uncertainty. Tree-ring¹⁴C data variance as a result of sample heterogeneity can be reduced by adopting best practices at the time of sample collection and subsequent preparation and analysis. Variance-reduction of¹⁴C data was achieved by meticulous sample handling during increment core or cross-sectional cuttings, in-laboratory wood reductions, and cellulose fiber homogenization of whole rings. To demonstrate the performance of those procedures to final¹⁴C results, we took advantage of the replicated data from assigned calendar years of two Pantropical post-1950 AD tree-ring¹⁴C reconstructions. TwoCedrela fissilisVell. trees spaced 22.5 km apart, and two trees of this species together with onePeltogyne paniculataBenth tree spaced 0.2 to 5 km apart were sampled in a tropical dry and moist forest, respectively. Replicate¹⁴C data were then obtained from grouped tree-ring samples from each site. A total of 88% of the replicated¹⁴C results fell into a remarkably consistent precision/accuracy range of 0.3% or less, even though multiple tree species were used as pairs/sets. This finding illustrates how adopting a few simple strategies, in tandem with already established chemical extraction procedures and high-precision¹⁴C analysis, can improve¹⁴C data results of tropical trees. 

To ensure unbiased tree-ring radiocarbon (14C) results, traditional pretreatments carefully isolate wood cellulose from extractives using organic solvents, among other chemicals. The addition of solvents is laborious, time ­consuming, and can increase the risk of carbon contamination. Tropical woods show a high diversity in wood­ anatomical and extractive composition, but the necessity of organic-solvent extraction for the 14C dating of these diverse woods remains untested. We applied a chemical treatment that excludes the solvent step on the wood of 8 tropical tree species sampled in South-America and Africa, with different wood-anatomical and extractive properties. We analyzed the success of the extractive removal along with several steps of the a-cel­lulose extraction procedure using Fourier Transform Infrared (FTIR) spectroscopy and further confirmed the quality of 14C measurements after extraction. The ex-cellulose extracts obtained here showed FTIR-spectra free of signals from various extractives and the 14C results on these samples showed reliable results. The chemical method evaluated reduces the technical complexity required to prepare a-cellulose samples for 14C dating, and therefore can bolster global atmospheric 14C applications, especially in the tropics. 

Tree-ring width chronologies of cedro (Cedrela fissilis Vell.) (1875 to 2018), jatobá (Hymenaea courbaril L.) (1840 to 2018) and roxinho Peltogyne paniculata Benth.) (1910 to 2018) were developed by dendrochronological techniques in the southern Amazon Basin. Acceptable statistics for the tree-ring chronologies were obtained, and annual calendar dates were assigned. Due to the lack of long-term chronologies for use in paleoclimate reconstructions in degraded forest areas, dendrochronological dating was validated by 14C analysis. Tree-rings selected for analysis corresponded to 1957, 1958, 1962, 1963, 1965, 1971, and 1972. Those are critical calendar years in which atmospheric 14C changes were the highest, and therefore their tree-ring cellulose extracts 14C signatures when in alignment with existing post-AD 1950 atmospheric 14C atmospheric curves would indicate annual periodicity. Throughout our correlated calendar years and post-AD 1950 14C signatures, we indicate that H. courbaril shows an erratic sequence of wood ages. The other two tree species, C. fissilis and P. paniculata, are annual in nature and can be used successfully as paleoclimate proxies. Moreover, due to the sampling site’s strategic location in relation to the Tropical Low-Pressure Belt over South America, these trees can be used to enhance the limited amount of observational data in Southern Hemisphere atmospheric 14C calibration curves. 

Abstract Injections of wildfire smoke plumes into the free troposphere impact air quality, yet model forecasts of injections are poor. Here, we use aircraft observations obtained during the 2019 western US wildfires (FIREX-AQ) to evaluate a commonly used smoke plume rise parameterization in two atmospheric chemistry-transport models (WRF-Chem and HRRR-Smoke). Observations show that smoke injections into the free troposphere occur in 35% of plumes, whereas the models forecast 59–95% indicating false injections in the simulations. False injections were associated with both models overestimating fire heat flux and terrain height, and with WRF-Chem underestimating planetary boundary layer height. We estimate that the radiant fraction of heat flux is 0.5 to 25 times larger in models than in observations, depending on fuel type. Model performance was substantially improved by using observed heat flux and boundary layer heights, confirming that models need accurate heat fluxes and boundary layer heights to correctly forecast plume injections. 

With deforestation and associated fires ongoing at high rates, and amidst urgent need to preserve Amazonia, improving the understanding of biomass burning emissions drivers is essential. The use of orbital remote sensing data enables the estimate of both biomass burning emissions and deforestation. In this study, we have estimated emissions of particulate matter with diameter less than 2.5 µm (PM2.5) associated with biomass burning, a primary human health risk, using the Brazilian Biomass Burning emission model with Fire Radiative Power (3BEM_FRP), and estimated deforestation based on the MapBiomas dataset. Using these estimates, we have assessed for the first time how deforestation drove biomass burning emissions in Amazonia over the last two decades at three scales of analysis: Amazonia-wide, country/state and pixel. Amazonia accounted for 48% of PM2.5 emitted from biomass burning in South America and current deforestation rates have reached values on par with those of the early 21st Century. Emissions and deforestation were concentrated in the Eastern and Central-Southern portions of Amazonia. Amazonia-wide deforestation and emissions were linked through time (R = 0.65). Countries/states with the widest spread agriculture were less likely to be correlated at this scale, likely because of the importance of biomass burning in agricultural practices. Concentrated in regions of ongoing deforestation, in 18% of Amazonia grid cells PM2.5 emissions associated with biomass burning and deforestation were significantly positively correlated. Deforestation is an important driver of emissions in Amazonia but does not explain biomass burning alone. Therefore, future work must link climate and other non-deforestation drivers to completely understand biomass burning emissions in Amazonia. The advance of anthropogenic activities over forested areas, which ultimately leads to more fires and deforestation, is expected to continue, worsening a crisis of dangerous emissions.