Airborne Emission Rate Measurements Validate Remote Sensing Observations and Emission Inventories of Western U.S. Wildfires

Carbonaceous emissions from wildfires are a dynamic mixture of gases and particles that have important impacts on air quality and climate. Emissions that feed atmospheric models are estimated using burned area and fire radiative power (FRP) methods that rely on satellite products. These approaches show wide variability and have large uncertainties, and their accuracy is challenging to evaluate due to limited aircraft and ground measurements. Here, we present a novel method to estimate fire plume-integrated total carbon and speciated emission rates using a unique combination of lidar remote sensing aerosol extinction profiles and in situ measured carbon constituents. We show strong agreement between these aircraft-derived emission rates of total carbon and a detailed burned area-based inventory that distributes carbon emissions in time using Geostationary Operational Environmental Satellite FRP observations (Fuel2Fire inventory, slope = 1.33 ± 0.04, r² = 0.93, and RMSE = 0.27). Other more commonly used inventories strongly correlate with aircraft-derived emissions but have wide-ranging over- and under-predictions. A strong correlation is found between carbon monoxide emissions estimated in situ with those derived from the TROPOspheric Monitoring Instrument (TROPOMI) for five wildfires with coincident sampling windows (slope = 0.99 ± 0.18; bias = 28.5%). Smoke emission coefficients (g MJ^-1) enable direct estimations of primary gas and aerosol emissions from satellite FRP observations, and we derive these values for many compounds emitted by temperate forest fuels, including several previously unreported species.

Robust Evidence of 14C, 13C, and 15N Analyses Indicating Fossil Fuel Sources for Total Carbon and Ammonium in Fine Aerosols in Seoul Megacity

Carbon- and nitrogen-containing aerosols are ubiquitous in urban atmospheres and play important roles in air quality and climate change. We determined the ¹⁴C fraction modern (f_M) and δ¹³C of total carbon (TC) and δ¹⁵N of NH₄⁺ in the PM_2.5 collected in Seoul megacity during April 2018 to December 2019. The seasonal mean δ¹³C values were similar to -25.1‰ ± 2.0‰ in warm and -24.2‰ ± 0.82‰ in cold seasons. Mean δ¹⁵N values were higher in warm (16.4‰ ± 2.8‰) than in cold seasons (4.0‰ ± 6.1‰), highlighting the temperature effects on atmospheric NH₃ levels and phase-equilibrium isotopic exchange during the conversion of NH₃ to NH₄⁺. While 37% ± 10% of TC was apportioned to fossil-fuel sources on the basis of f_M values, δ¹⁵N indicated a higher contribution of emissions from vehicle exhausts and electricity generating units (power-plant NH₃ slip) to NH₃: 60% ± 26% in warm season and 66% ± 22% in cold season, based on a Bayesian isotope-mixing model. The collective evidence of multiple isotope analysis reasonably supports the major contribution of fossil-fuel-combustion sources to NH₄⁺, in conjunction with TC, and an increased contribution from vehicle emissions during the severe PM_2.5 pollution episodes. These findings demonstrate the efficacy of a multiple-isotope approach in providing better insight into the major sources of PM_2.5 in the urban atmosphere.

Urbanization minimizes the effects of plant traits on soil provisioned ecosystem services across climatic regions

An increasingly urbanized world is one of the most prominent examples of global environmental change. Across the globe, urban parks are designed and managed in a similar way, resulting in visually pleasing expansions of lawn interspersed with individually planted trees of varying appearances and functional traits. These large urban greenspaces have the capacity to provide various ecosystem services, including those associated with soil physicochemical properties. Our aim was to explore whether soil properties in urban parks diverge underneath vegetation producing labile or recalcitrant litter, and whether the impact is affected by climatic zone (from a boreal to temperate to tropical city). We also compared these properties to those in (semi)natural forests outside the cities to assess the influence of urbanization on plant-trait effects. We showed that vegetation type affected percentage soil organic matter (OM), total carbon (C) and total nitrogen (N), but inconsistently across climatic zones. Plant-trait effects were particularly weak in old parks in the boreal and temperate zones, whereas in young parks in these zones, soils underneath the two tree types accumulated significantly more OM, C and N compared to lawns. Within climatic zones, anthropogenic drivers dominated natural ones, with consistently lower values of organic-matter-related soil properties under trees producing labile or recalcitrant litter in parks compared to forests. The dominating effect of urbanization is also reflected in its ability to homogenize soil properties in parks across the three cities, especially in lawn soils and soils under trees irrespective of functional trait. Our study demonstrates that soil functions that relate to carbon and nitrogen dynamics-even in old urban greenspaces where plant-soil interactions have a long history-clearly diverged from those in natural ecosystems, implying a long-lasting influence of anthropogenic drivers on soil ecosystem services.

respirable total carbon

In the mining industry, personal measurements of elemental and total carbon are frequently used as surrogates of diesel particulate matter (DPM) exposure, and the respirable or submicron fractions are usually measured. However, vapor-phase organic carbon (OC) can be adsorbed in the filters, interfering with total carbon results. This study presents a comparative evaluation between the submicron fraction of DPM concentrations corrected for the adsorption of the vapor-phase OC (dynamic blank), and the respirable fraction of DPM corrected for a field blank. Respirable and submicron fractions of total carbon (TC_R and TC₁) and elemental carbon (EC_R and EC₁) concentrations were sampled in parallel, in the workers' breathing zone, in an underground gold mine. A total of 20 full-shift personal samples were taken for each size fraction. Field blanks were collected each day for both the submicron and respirable fractions, while dynamic blank correction was also applied for the submicron fraction. TC_R presented a larger and statistically different geometric mean concentration compared to TC₁ (98 µg/m³ vs. 72 µg/m³; p = 0.01), while the concentrations of EC_R and EC₁ were not statistically different (58 µg/m³ vs. 54 µg/m³; p = 0.74). Average TC_R/EC_R ratio was 1.7, while the TC₁/EC₁ ratio was 1.3. In addition, 93% of EC had an aerodynamic size lower than 1 µm, while the proportion of TC particles in the submicron fraction was lower (73%). Finally, a similar quantity of OC was found when analyzing the dynamic and field blanks of the filters with the submicron fraction selective size (24 µg and 22 µg, respectively). In conclusion, the correction for the vapor phase OC by the dynamic blank was not a significant correction in our study design compared to the field blank samples. This study suggests that the differences in TC may be explained by the different aerodynamic fractions of DPM collected. In addition, elemental carbon measurements did not seem to be extensively affected by the aerodynamic size of the particles collected.

Comparison between Random Forests, Artificial Neural Networks and Gradient Boosted Machines Methods of On-Line Vis-NIR Spectroscopy Measurements of Soil Total Nitrogen and Total Carbon

Accurate and detailed spatial soil information about within-field variability is essential for variable-rate applications of farm resources. Soil total nitrogen (TN) and total carbon (TC) are important fertility parameters that can be measured with on-line (mobile) visible and near infrared (vis-NIR) spectroscopy. This study compares the performance of local farm scale calibrations with those based on the spiking of selected local samples from both fields into an European dataset for TN and TC estimation using three modelling techniques, namely gradient boosted machines (GBM), artificial neural networks (ANNs) and random forests (RF). The on-line measurements were carried out using a mobile, fiber type, vis-NIR spectrophotometer (305-2200 nm) (AgroSpec from tec5, Germany), during which soil spectra were recorded in diffuse reflectance mode from two fields in the UK. After spectra pre-processing, the entire datasets were then divided into calibration (75%) and prediction (25%) sets, and calibration models for TN and TC were developed using GBM, ANN and RF with leave-one-out cross-validation. Results of cross-validation showed that the effect of spiking of local samples collected from a field into an European dataset when combined with RF has resulted in the highest coefficients of determination (R²) values of 0.97 and 0.98, the lowest root mean square error (RMSE) of 0.01% and 0.10%, and the highest residual prediction deviations (RPD) of 5.58 and 7.54, for TN and TC, respectively. Results for laboratory and on-line predictions generally followed the same trend as for cross-validation in one field, where the spiked European dataset-based RF calibration models outperformed the corresponding GBM and ANN models. In the second field ANN has replaced RF in being the best performing. However, the local field calibrations provided lower R² and RPD in most cases. Therefore, from a cost-effective point of view, it is recommended to adopt the spiked European dataset-based RF/ANN calibration models for successful prediction of TN and TC under on-line measurement conditions.

Enhancement of Taihu blue algae anaerobic digestion efficiency by natural storage

Taihu blue algae after different storage time from 0 to 60 d were anaerobic fermented to evaluate their digestibility and process stability. Results showed that anaerobic digestion (AD) of blue algae under 15 d natural storage led to the highest CH4 production of 287.6 mL g(-1) VS at inoculum substrate ratio 2.0, demonstrating 36.69% improvement comparing with that from fresh algae. Storage of blue algae led to cell death, microcystins (MCs) release and VS reduction by spontaneous fermentation. However, it also played an important role in removing algal cell wall barrier, pre-hydrolysis and pre-acidification, leading to the improvement in CH4 yield. Closer examination of volatile fatty acids (VFA) variation, VS removal rates and key enzymes change during AD proved short storage time (≤ 15 d) of blue algae had higher efficiencies in biodegradation and methanation. Furthermore, AD presented significant biodegradation potential for MCs released from Taihu blue algae.