Improved atmospheric constraints on Southern Ocean CO2 exchange.

We present improved estimates of air-sea CO2 exchange over three latitude bands of the Southern Ocean using atmospheric CO2 measurements from global airborne campaigns and an atmospheric 4-box inverse model based on a mass-indexed isentropic coordinate (Mθe). These flux estimates show two features not clearly resolved in previous estimates based on inverting surface CO2 measurements: a weak winter-time outgassing in the polar region and a sharp phase transition of the seasonal flux cycles between polar/subpolar and subtropical regions. The estimates suggest much stronger summer-time uptake in the polar/subpolar regions than estimates derived through neural-network interpolation of pCO2 data obtained with profiling floats but somewhat weaker uptake than a recent study by Long et al. [Science 374, 1275-1280 (2021)], who used the same airborne data and multiple atmospheric transport models (ATMs) to constrain surface fluxes. Our study also uses moist static energy (MSE) budgets from reanalyses to show that most ATMs tend to have excessive diabatic mixing (transport across moist isentrope, θe, or Mθe surfaces) at high southern latitudes in the austral summer, which leads to biases in estimates of air-sea CO2 exchange. Furthermore, we show that the MSE-based constraint is consistent with an independent constraint on atmospheric mixing based on combining airborne and surface CO2 observations.

Global Gridded Emission Inventory of Organophosphate Flame Retardants from 2010 to 2020.

As a substitute for brominated flame retardants, organophosphate flame retardants (OPFRs) have become a global concern due to their high toxicity and bioaccumulation. To paint an overall picture of OPFRs in the global environment, the present study develops a gridded global emission inventory of OPFRs on a spatial resolution of 1 × 1° from 2010 to 2020. Revealing a 3.31% average annual increase in emissions, totaling 21,324.42 tons. The production process is the primary source, accounting for 55.43% of emissions, with consumption processes making up the rest. Major sources are in Asia, North America, and Europe. The inventory is verified by implementing emission data into a global atmospheric transport model to predict OPFR concentrations in the global environment and comparing modeled concentrations with field sampled data. The results indicate that the inventory is reliable except for the pristine polar region, where the emission inventory and modeled concentrations underestimate OPFR levels in the atmosphere, likely resulting from ignorance of chemical reactions and the secondary derivative of parent OPFRs during their global long-distance atmospheric transport in the model. This comprehensive data set aids in formulating OPFR emission control policies and assessing health risks.

Bacterial Emission Factors: A Foundation for the Terrestrial-Atmospheric Modeling of Bacteria Aerosolized by Wildland Fires.

Wildland fire is a major global driver in the exchange of aerosols between terrestrial environments and the atmosphere. This exchange is commonly quantified using emission factors or the mass of a pollutant emitted per mass of fuel burned. However, emission factors for microbes aerosolized by fire have yet to be determined. Using bacterial cell concentrations collected on unmanned aircraft systems over forest fires in Utah, USA, we determine bacterial emission factors (BEFs) for the first time. We estimate that 1.39 × 1010 and 7.68 × 1011 microbes are emitted for each Mg of biomass consumed in fires burning thinning residues and intact forests, respectively. These emissions exceed estimates of background bacterial emissions in other studies by 3-4 orders of magnitude. For the ∼2631 ha of similar forests in the Fishlake National Forest that burn each year on average, an estimated 1.35 × 1017 cells or 8.1 kg of bacterial biomass were emitted. BEFs were then used to parametrize a computationally scalable particle transport model that predicted over 99% of the emitted cells were transported beyond the 17.25 x 17.25 km model domain. BEFs can be used to expand understanding of global wildfire microbial emissions and their potential consequences to ecosystems, the atmosphere, and humans.

Modeling long-distance seed dispersal of the invasive tree Spathodea campanulata in the Society Islands.

Long-distance dispersal is a key factor explaining the success of invasive alien species, particularly across oceanic islands. However, it is often not feasible to reliably measure long-distance seed dispersal (LDD) over many kilometers in the field. Here, we used a three-dimensional kinematic trajectory model (Computing Atmospheric Trajectory tool [CAT]) initiated on the basis of regional wind field data to assess the potential for LDD of a wind-dispersed invasive tree, Spathodea campanulata (African tulip tree), across the Society Islands (French Polynesia, South Pacific Ocean) following its initial planting and spread on the island of Tahiti. The main objective of our study was to determine whether S. campanulata could be expected to spread naturally among islands. Atmospheric dynamics, seed terminal velocity, precipitation, and temperature of air masses were considered to assess the potential for LDD between oceanic islands, with the island of Tahiti serving as the island source for multiple, geographically distant invasions. Aerial trajectories of modeled S. campanulata seeds indicated that wind-dispersed seeds originating from trees on the island of Tahiti could reach most of the Society Islands and disperse as far as 1364 km. This result suggests that Spathodea can be expected to spread naturally among the Society Islands. When rainfall events were modeled as causal agents of seed settlement, fewer seeds reached distant islands, but more seeds settled on the closest island (20 km away). Including effects of island topography ("barrier effects") also resulted in more seeds settling on the closest island and fewer seeds reaching the most distant islands. Overall, our findings suggest that recent atmospheric models can provide valuable insights into LDD and invasion patterns of wind-dispersed invasive species.

AP Shadow Net: A Remote Sensing Shadow Removal Network Based on Atmospheric Transport and Poisson's Equation.

Shadow is one of the fundamental indicators of remote sensing image which could cause loss or interference of the target data. As a result, the detection and removal of shadow has already been the hotspot of current study because of the complicated background information. In the following passage, a model combining the Atmospheric Transport Model (hereinafter abbreviated as ATM) with the Poisson Equation, AP ShadowNet, is proposed for the shadow detection and removal of remote sensing images by unsupervised learning. This network based on a preprocessing network based on ATM, A Net, and a network based on the Poisson Equation, P Net. Firstly, corresponding mapping between shadow and unshaded area is generated by the ATM. The brightened image will then enter the Confrontation identification in the P Net. Lastly, the reconstructed image is optimized on color consistency and edge transition by Poisson Equation. At present, most shadow removal models based on neural networks are significantly data-driven. Fortunately, by the model in this passage, the unsupervised shadow detection and removal could be released from the data source restrictions from the remote sensing images themselves. By verifying the shadow removal on our model, the result shows a satisfying effect from a both qualitative and quantitative angle. From a qualitative point of view, our results have a prominent effect on tone consistency and removal of detailed shadows. From the quantitative point of view, we adopt the non-reference evaluation indicators: gradient structure similarity (NRSS) and Natural Image Quality Evaluator (NIQE). Combining various evaluation factors such as reasoning speed and memory occupation, it shows that it is outstanding among other current algorithms.

Spatiotemporal distribution and dynamic modeling of atmospheric gaseous polycyclic aromatic hydrocarbons in a rapidly urbanizing city: Nanjing, China.

Multiple studies have evaluated the concentration and lung cancer risk of polycyclic aromatic hydrocarbons (PAHs). However, the monitoring and dynamic modeling of PAHs with a high resolution were relatively insufficient. We investigated the spatiotemporal distribution of gaseous PAH concentrations using passive air samplers with high sampling density in an industrial city of Nanjing, China (January and October 2015) and found that the gaseous PAH concentrations in western Nanjing were higher than those in eastern Nanjing, mainly because of emission source distribution and wind action. There were notable seasonal changes in PAH concentrations: winter > autumn > spring > summer. We developed an atmospheric PAH dynamic model with a high resolution of 1 km2 based on the advection-diffusion equation and coupled with an emissions inventory and atmospheric transportation processes. Acenaphthene was selected as a proxy for gaseous PAHs. The modeled acenaphthene concentrations were similar to the concentrations measured. Moreover, we used the model to identify the impact of meteorological factors on gaseous PAHs via scenario analysis and found that a narrow-range temperature change and even heavy rainfall may not significantly affect atmospheric gaseous PAH concentrations, whereas the wind played an important part in transferring PAHs and changing their geographic distribution.

Enabling probabilistic retrospective transport modeling for accurate source detection.

Predicting source or background radionuclide emissions is limited by the effort needed to run gas/aerosol atmospheric transport models (ATMs). A high-performance surrogate model is developed for the HYSPLIT4 (NOAA) ATM to accelerate transport simulation through model reduction, code optimization, and improved scaling on high performance computing systems. The surrogate model parameters are a grid of short-duration transport simulations stored offline. The surrogate model then predicts the path of a plume of radionuclide particles emitted from a source, or the field of sources which may have contributed to a detected signal, more efficiently than direct simulation by HYSPLIT4. Termed the Atmospheric Transport Model Surrogate (ATaMS), this suite of capabilities forms a basis to accelerate workflows for probabilistic source prediction and estimation of the radionuclide atmospheric background.

Air path of antimicrobial resistance related genes from layer farms: Emission inventory, atmospheric transport, and human exposure.

Animal husbandry is a significant contributor to increased environmental antimicrobial resistance (AMR), but little is known regarding the dissemination of AMR from animal farms via airborne transmission. Here, we connected the air path of AMR related genes tailored to layer poultry farms from source of escape to end of sedimentation. The emission inventories of 8 AMR related genes from all 163-layer poultry farms around Beijing city were quantified. We developed the atmospheric transport model with a gene degradation module to estimate the spatiotemporal distribution of airborne AMR, and also assessed their corresponding regional exposure and sedimentation. Total emissions of 16 S rDNA and AMR related genes from layer houses ranged from 1015 to 1016 copies year-1. Those layer-sourced genes contributed 1-14.6% of antimicrobial resistant genes, 4.9% of Staphylococcus spp. and 2.2% of CintI1 to the corresponding annual genetic burden of Beijing's urban air. The average exposure of the Beijing residents to layer-sourced airborne 16 S rDNA was 1.39 × 104 copies year-1 person-1, approximately 87% of them would be deposited in the upper respiratory tract. The findings highlight that air medium represents an important dissemination pathway of animal-sourced genes to AMR burden in humans and environment.

Sensitivity study to select the wet deposition scheme in an operational atmospheric transport model.

The ability of operational atmospheric transport models to simulate the soil contamination caused by deposition processes is important in the response to a nuclear crisis. The Fukushima accident was characterized by wet deposition of Cs-137, which is difficult to simulate accurately based on observations. A sensitivity study investigated seven wet deposition schemes integrated into operational atmospheric transport models. Deposition maps produced from the multiple simulations are compared with each other and with the observed deposition. Similarities and discrepancies in average behavior are presented for a number of modeling cases on the basis of criteria representing soil contamination crisis management needs. This study confirms the importance of the wet deposition scheme in a crisis management context. None of the schemes used in the study are the best option to satisfy all the comparison criteria. This study suggests that crisis managers must not exclusively trust a single model for selecting responses. At the current time, it is preferable to use several wet deposition schemes in the modelling tools for emergency responses.

Monitoring atmospheric 85Kr by atom counting.

Radioactive 85Kr is a major gaseous fission product emitted into the air by the nuclear fuel reprocessing industry. Measuring atmospheric 85Kr has applications in environmental monitoring, atmospheric transport model validation and dating of environmental water samples, including groundwater, sea water and glacier ice. We present an ultra-sensitive method for fast analysis of atmospheric 85Kr at 10-5 parts per trillion level. This method is based on laser cooling and trapping and is capable of counting individual 85Kr atoms. Measurements at the 3% precision level can be made on krypton extracted from 1L STP of air with a turnaround time of 1.5 h. Moreover, we have realized a system for continuous air sampling over days to weeks. Based on this atom-counting technology and a portable air sample integrator we have realized atmospheric 85Kr baseline monitoring in Hefei, China, for over 20 months. The technological advances presented in this work lay the ground for a global atmospheric 85Kr monitoring network.

RECONSTRUCTION OF THE RADIOACTIVE CONTAMINATION OF THE TERRITORY OF UKRAINE BY IODINE-131 DURING INITIAL PERIOD OF THE CHORNOBYL ACCIDENT USING THE RESULTS FROM NUMERICAL MODEL WRF. / REKONSTRUKTsIIa RADIOAKTYVNOGO ZABRUDNENNIa TERYTORIÏ UKRAÏNY IODOM-131 V POChATKOVYI PERIOD ChORNOBYL'S'KOÏ AVARIÏ Z VYKORYSTANNIaM ChYSEL'NOÏ MODELI WRF.

OBJECTIVE: To reconstruct the 131I activity concentrations in air and 131I ground deposition densities from 26 April to7 May 1986 from the radioactivity release after the Chornobyl accident in the settlements of Ukraine using themesoscale radionuclides atmospheric transport model LEDI and meteorological information from the numericalweather forecast model WRF and to compare the obtained results with those calculated previously as well as withavailable measurements of 131I activity in soil.Object of research: the near-ground layer of the atmosphere and the surface of the territory of Ukraine radioactively contaminated as a result of the Chornobyl accident.Materials and methods of research. The dispersion of 131I in the atmosphere and deposition on the ground surfacein Ukraine were calculated using the Lagrangian-Eulerian diffusion model LEDI. The detailed fields of meteorological parameters calculated using the mesoscale weather forecast model WRF, which was adapted for the territory ofUkraine, were used as input data for the LEDI model. RESULTS: The 131I daily-average activity concentrations in the surface air and 131I daily ground deposition densitiesfrom 26 April to 7 May 1986 were calculated using the up-to-date mesoscale model of numerical weather forecastWRF for 30,352 settlements in entire Ukraine, including 1,263 settlements in Kyiv, 1,717 - in Zhytomyr and 1,570 -in Chernihiv Oblasts. CONCLUSIONS: The method of mathematical modeling of the atmospheric transport of the radionuclides is combination with the up-to-date mesoscale model of numerical weather forecast WRF is a useful tool for reconstruction ofradioactive contamination of the air and the ground surface after the Chornobyl accident. Calculated in this study131I activity concentrations in air and 131I ground deposition densities were used to reconstruct the thyroid doses dueto 131I intake to the population of Ukraine.

JMA's regional atmospheric transport model calculations for the WMO technical task team on meteorological analyses for Fukushima Daiichi Nuclear Power Plant accident.

The World Meteorological Organization (WMO) convened a small technical task team of experts to produce a set of meteorological analyses to drive atmospheric transport, dispersion and deposition models (ATDMs) for the United Nations Scientific Committee on the Effects of Atomic Radiation's assessment of the Fukushima Daiichi Nuclear Power Plant (DNPP) accident. The Japan Meteorological Agency (JMA) collaborated with the WMO task team as the regional specialized meteorological center of the country where the accident occurred, and provided its operational 5-km resolution mesoscale (MESO) analysis and its 1-km resolution radar/rain gauge-analyzed precipitation (RAP) data. The JMA's mesoscale tracer transport model was modified to a regional ATDM for radionuclides (RATM), which included newly implemented algorithms for dry deposition, wet scavenging, and gravitational settling of radionuclide aerosol particles. Preliminary and revised calculations of the JMA-RATM were conducted according to the task team's protocol. Verification against Cesium 137 ((137)Cs) deposition measurements and observed air concentration time series showed that the performance of RATM with MESO data was significantly improved by the revisions to the model. The use of RAP data improved the (137)Cs deposition pattern but not the time series of air concentrations at Tokai-mura compared with calculations just using the MESO data. Sensitivity tests of some of the more uncertain parameters were conducted to determine their impacts on ATDM calculations, and the dispersion and deposition of radionuclides on 15 March 2011, the period of some of the largest emissions and deposition to the land areas of Japan. The area with high deposition in the northwest of Fukushima DNPP and the hotspot in the central part of Fukushima prefecture were primarily formed by wet scavenging influenced by the orographic effect of the mountainous area in the west of the Fukushima prefecture.

Quantifying missing annual emission sources of heavy metals in the United Kingdom with an atmospheric transport model.

An atmospheric chemical transport model was adapted to simulate the concentration and deposition of heavy metals (arsenic, cadmium, chromium, copper, lead, nickel, selenium, vanadium, and zinc) in the United Kingdom. The model showed that wet deposition was the most important process for the transfer of metals from the atmosphere to the land surface. The model achieved a good correlation with annually averaged measurements of metal concentrations in air. The correlation with measurements of wet deposition was less strong due to the complexity of the atmospheric processes involved in the washout of particulate matter which were not fully captured by the model. The measured wet deposition and air concentration of heavy metals were significantly underestimated by the model for all metals (except vanadium) by factors between 2 and 10. These results suggest major missing sources of annual heavy metal emissions which are currently not included in the official inventory. Primary emissions were able to account for only 9%, 21%, 29%, 21%, 36%, 7% and 23% of the measured concentrations for As, Cd, Cr, Cu, Ni, Pb and Zn. A likely additional contribution to atmospheric heavy metal concentrations is the wind driven re-suspension of surface dust still present in the environment from the legacy of much higher historic emissions. Inclusion of two independent estimates of emissions from re-suspension in the model was found to give an improved agreement with measurements. However, an accurate estimate of the magnitude of re-suspended emissions is restricted by the lack of measurements of metal concentrations in the re-suspended surface dust layer.