Physiotyping of Plants and Modeling the Soil Plant Atmospheric Continuum (SPAC).

This chapter presents a holistic and quantitative approach to the carbon cycle in plant systems biology. It includes (rapid) phenotyping and monitoring of physiological key interactions of plants with its respective soil and atmospheric environment (soil plant atmospheric continuum-SPAC). The approach aims at qualifying and quantifying key components of this microhabitat as influenced by a single plant or a local group of plants in order to contribute to a flux-based modelling approach. The toolset consists of plant biometry, gas exchange, metabolomics, ionomics, root exudate characterization as well as soil biological and physical-chemical characterization. The results are presented as a basic interaction and input-output model aka conceptual system model employing H. T. Odum-style plots based on empirical data.

Ambient carbon dioxide concentration correlates with SARS-CoV-2 aerostability and infection risk.

An improved understanding of the underlying physicochemical properties of respiratory aerosol that influence viral infectivity may open new avenues to mitigate the transmission of respiratory diseases such as COVID-19. Previous studies have shown that an increase in the pH of respiratory aerosols following generation due to changes in the gas-particle partitioning of pH buffering bicarbonate ions and carbon dioxide is a significant factor in reducing SARS-CoV-2 infectivity. We show here that a significant increase in SARS-CoV-2 aerostability results from a moderate increase in the atmospheric carbon dioxide concentration (e.g. 800 ppm), an effect that is more marked than that observed for changes in relative humidity. We model the likelihood of COVID-19 transmission on the ambient concentration of CO2, concluding that even this moderate increase in CO2 concentration results in a significant increase in overall risk. These observations confirm the critical importance of ventilation and maintaining low CO2 concentrations in indoor environments for mitigating disease transmission. Moreover, the correlation of increased CO2 concentration with viral aerostability need to be better understood when considering the consequences of increases in ambient CO2 levels in our atmosphere.

Heterotic growth of hybrids of Arabidopsis thaliana is enhanced by elevated atmospheric CO2.

PREMISE: With the global atmospheric CO2 concentration on the rise, developing crops that can thrive in elevated CO2 has become paramount. We investigated the potential of hybridization as a strategy for creating crops with improved growth in predicted elevated atmospheric CO2. METHODS: We grew parent accessions and their F1 hybrids of Arabidopsis thaliana in ambient and elevated atmospheric CO2 and analyzed numerous growth traits to assess their productivity and underlying mechanisms. RESULTS: The heterotic increase in total dry mass, relative growth rate and leaf net assimilation rate was significantly greater in elevated CO2 than in ambient CO2. The CO2 response of net assimilation rate was positively correlated with the CO2 response of leaf nitrogen productivity and with that of leaf traits such as leaf size and thickness, suggesting that hybridization-induced changes in leaf traits greatly affected the improved performance in elevated CO2. CONCLUSIONS: Vegetative growth of hybrids seems to be enhanced in elevated CO2 due to improved photosynthetic nitrogen-use efficiency compared with parents. The results suggest that hybrid crops should be well-suited for future conditions, but hybrid weeds may also be more competitive.

HiMIC-Monthly: A 1 km high-resolution atmospheric moisture index collection over China, 2003-2020.

Near-surface atmospheric moisture is a key environmental and hydro-climatic variable that has significant implications for the natural and human systems. However, high-resolution moisture data are severely lacking for fine-scale studies. Here, we develop the first 1 km high spatial resolution dataset of monthly moisture index collection in China (HiMIC-Monthly) over a long period of 2003~2020. HiMIC-Monthly is generated by the light gradient boosting machine algorithm (LightGBM) based on observations at 2,419 weather stations and multiple covariates, including land surface temperature, vapor pressure, land cover, impervious surface proportion, population density, and topography. This collection includes six commonly used moisture indices, enabling fine-scale assessment of moisture conditions from different perspectives. Results show that the HiMIC-Monthly dataset has a good performance, with R2 values for all six moisture indices exceeding 0.96 and root mean square error and mean absolute error values within a reasonable range. The dataset exhibits high consistency with in situ observations over various spatial and temporal regimes, demonstrating broad applicability and strong reliability.

On Nucleation Pathways and Particle Size Distribution Evolutions in Stratospheric Aircraft Exhaust Plumes with H2SO4 Enhancement.

Stratospheric aerosol injection (SAI) is proposed as a means of reducing global warming and climate change impacts. Similar to aerosol enhancements produced by volcanic eruptions, introducing particles into the stratosphere would reflect sunlight and reduce the level of warming. However, uncertainties remain about the roles of nucleation mechanisms, ionized molecules, impurities (unevaporated residuals of injected precursors), and ambient conditions in the generation of SAI particles optimally sized to reflect sunlight. Here, we use a kinetic ion-mediated and homogeneous nucleation model to study the formation of H2SO4 particles in aircraft exhaust plumes with direct injection of H2SO4 vapor. We find that under the conditions that produce particles of desired sizes (diameter ∼200-300 nm), nucleation occurs in the nascent (t < 0.01 s), hot (T = 360-445 K), and dry (RH = 0.01-0.1%) plume and is predominantly unary. Nucleation on chemiions occurs first, followed by neutral new particle formation, which converts most of the injected H2SO4 vapor to particles. Coagulation in the aging and diluting plumes governs the subsequent evolution to a narrow (σg = 1.3) particle size distribution. Scavenging by exhaust soot is negligible, but scavenging by acid impurities or incomplete H2SO4 evaporation in the hot exhaust plume and enhanced background aerosols can matter. This research highlights the need to obtain laboratory and/or real-world experiment data to verify the model prediction.

Shedding light on the increased carbon uptake by a boreal forest under diffuse solar radiation across multiple scales.

Solar radiation is scattered by cloud cover, aerosols and other particles in the atmosphere, all of which are affected by global changes. Furthermore, the diffuse fraction of solar radiation is increased by more frequent forest fires and likewise would be if climate interventions such as stratospheric aerosol injection were adopted. Forest ecosystem studies predict that an increase in diffuse radiation would result in higher productivity, but ecophysiological data are required to identify the processes responsible within the forest canopy. In our study, the response of a boreal forest to direct, diffuse and heterogeneous solar radiation conditions was examined during the daytime in the growing season to determine how carbon uptake is affected by radiation conditions at different scales. A 10-year data set of ecosystem, shoot and forest floor vegetation carbon and water-flux data was examined. Ecosystem-level carbon assimilation was higher under diffuse radiation conditions in comparison with direct radiation conditions at equivalent total photosynthetically active radiation (PAR). This was driven by both an increase in shoot and forest floor vegetation photosynthetic rate. Most notably, ecosystem-scale productivity was strongly related to the absolute amount of diffuse PAR, since it integrates both changes in total PAR and diffuse fraction. This finding provides a gateway to explore the processes by which absolute diffuse PAR enhances productivity, and the long-term persistence of this effect under scenarios of higher global diffuse radiation.

Plastic footprint deteriorates dryland carbon footprint across soil-plant-atmosphere continuum.

Plastic fragments are widely found in the soil profile of terrestrial ecosystems, forming plastic footprint and posing increasing threat to soil functionality and carbon (C) footprint. It is unclear how plastic footprint affects C cycling, and in particularly permanent C sequestration. Integrated field observations (including 13C labelling) were made using polyethylene and polylactic acid plastic fragments (low-, medium- and high-concentrations as intensifying footprint) landfilling in soil, to track C flow along soil-plant-atmosphere continuum (SPAC). The result indicated that increased plastic fragments substantially reduced photosynthetic C assimilation (p < 0.05), regardless of fragment degradability. Besides reducing C sink strength, relative intensity of C emission increased significantly, displaying elevated C source. Moreover, root C fixation declined significantly from 21.95 to 19.2 mg m-2, and simultaneously root length density, root weight density, specific root length and root diameter and surface area were clearly reduced. Similar trends were observed in the two types of plastic fragments (p > 0.05). Particularly, soil aggregate stability was significantly lowered as affected by plastic fragments, which accelerated the decomposition rate of newly sequestered C (p < 0.05). More importantly, net C rhizodeposition declined averagely from 39.77 to 29.41 mg m-2, which directly led to significant decline of permanent C sequestration in soil. Therefore, increasing plastic footprint considerably worsened C footprint regardless of polythene and biodegradable fragments. The findings unveiled the serious effects of plastic residues on permanent C sequestration across SPAC, implying that current C assessment methods clearly overlook plastic footprint and their global impact effects.

Translating genetic findings to epigenetics: identifying the mechanisms associated with aging after high-radiation exposure on earth and in space.

Purpose: Exposure to radiation is a health concern within and beyond the Earth's atmosphere for aircrew and astronauts in their respective austere environments. The biological effects of radiation exposure from a multiomics standpoint are relatively unexplored and stand to shed light on tailored monitoring and treatment for those in these career fields. To establish a reference variable for genetic damage, biological age seems to be closely associated with the effect of radiation. Following a genetic-based study, this study explores the epigenetic landscape of radiation exposure along with its associative effects on aging processes. Methods: We imported the results of the genetics-based study that was a secondary analysis of five publicly available datasets (noted as Data1). The overlap of these genes with new data involving methylation data from two datasets (noted as Data2) following similar secondary analysis procedures is the basis of this study. We performed the standard statistical analysis on these datasets along with supervised and unsupervised learning to create preranked gene lists used for functional analysis in Ingenuity Pathway Analysis (IPA). Results: There were 664 genes of interest from Data1 and 577 genes from Data2. There were 40 statistically significant methylation probes within 500 base pairs of the gene's transcription start site and 10 probes within 100 base pairs, which are discussed in depth. IPA yielded 21 significant pathways involving metabolism, cellular development, cell death, and diseases. Compared to gold standards for gestational age, we observed relatively low error and standard deviation using newly identified biomarkers. Conclusion: We have identified 17 methylated genes that exhibited particular interest and potential in future studies. This study suggests that there are common trends in oxidative stress, cell development, and metabolism that indicate an association between aging processes and the effects of ionizing radiation exposure.

Transcutaneous oximetry values in chronic ulcer patients during Hyperbaric treatment at 1.4 ATA compared to 2 ATA.

Chronic wounds have a significant impact on a patient's quality of life. Different pathologies, such as poor blood supply and tissue breakdown, may lead to inadequate oxygenation of the wound. Hyperbaric oxygen (HBO2) is a widely used treatment for an increasing number of medical practices. A new so-called "hyperbaric treatment" trend has emerged. The use of low-pressure, soft-sided, or inflatable chambers represents a growing trend in hyperbaric medicine. Used in professional settings as well as directly marketed to individuals for home use, they are promoted as equivalent to clinical hyperbaric treatments provided in medical centers. However, these chambers are pressurized to 1.3 atmospheres absolute (ATA) on either air or with an oxygen concentrator, both generate oxygen partial pressures well below those used in approved hyperbaric centers for UHMS-approved indications. A total of 130 consecutive patients with chronic ulcers where tested. TcPO2 was measured near the ulcer area while the patient was breathing 100% O2 at 1.4 ATA for five and 10 minutes. The average TcPO2 at 1.4 ATA after 10 minutes of O2 breathing was 161 mmHg (1-601 mmHg, standard deviation 137.91), compared to 333 mmHg in 2 ATA (1-914±232.56), p < 0.001. Each electrode tested was also statistically significant, both after five minutes of O2 breathing and after 10 minutes. We have not found evidence supporting the claim that 1.4 ATA treatment can benefit a chronic ulcer patient. The field of HBO2 is constantly evolving. We have discovered new ways to treat previously incurable ailments. Nevertheless, it is important to note that new horizons must be examined scientifically, supported by evidence-based data. The actual effect of 1.4 ATA on many ailments is yet to be determined.

A Novel Abiotic Pathway for Phosphine Synthesis over Acidic Dust in Venus' Atmosphere.

Recent ground-based observations of Venus have detected a single spectral feature consistent with phosphine (PH3) in the middle atmosphere, a gas which has been suggested as a biosignature on rocky planets. The presence of PH3 in the oxidized atmosphere of Venus has not yet been explained by any abiotic process. However, state-of-the-art experimental and theoretical research published in previous works demonstrated a photochemical origin of another potential biosignature-the hydride methane-from carbon dioxide over acidic mineral surfaces on Mars. The production of methane includes formation of the HC · O radical. Our density functional theory (DFT) calculations predict an energetically plausible reaction network leading to PH3, involving either HC · O or H· radicals. We suggest that, similarly to the photochemical formation of methane over acidic minerals already discussed for Mars, the origin of PH3 in Venus' atmosphere could be explained by radical chemistry starting with the reaction of ·PO with HC·O, the latter being produced by reduction of CO2 over acidic dust in upper atmospheric layers of Venus by ultraviolet radiation. HPO, H2P·O, and H3P·OH have been identified as key intermediate species in our model pathway for phosphine synthesis.

Integrated Portable and Stationary Health Impact-Monitoring System for Firefighters.

The multi-layered negative effects caused by pollutants released into the atmosphere as a result of fires served as the stimulus for the development of a system that protects the health of firefighters operating in the affected area. A collaborative network comprising mobile and stationary Internet of Things (IoT) devices that are furnished with gas sensors, along with a remote server, constructs a resilient framework that monitors the concentrations of harmful emissions, characterizes the ambient air quality of the vicinity where the fire transpires, adopting European Air Quality levels, and communicates the outcomes via suitable applications (RESTful APIs and visualizations) to the stakeholders responsible for fire management decision making. Different experimental evaluations adopting separate contexts illustrate the operation of the infrastructure.

Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits.

Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and WorldView-2 same-day paired satellite imagery and handheld multispectral proximal sensors on two days during the 2012-2013 winter cover crop season. We compared two processing levels from three satellites with spatially aggregated proximal data for red and green spectral bands as well as the normalized difference vegetation index (NDVI). We then compared NDVI estimated fractional green cover to in-situ photographs, and we derived cover crop biomass estimates from NDVI using existing calibration equations. We used slope and intercept contrasts to test whether estimates of biomass and fractional green cover differed statistically between sensors and processing levels. Compared to top-of-atmosphere imagery, surface reflectance imagery were more closely correlated with proximal sensors, with intercepts closer to zero, regression slopes nearer to the 1:1 line, and less variance between measured values. Additionally, surface reflectance NDVI derived from satellites showed strong agreement with passive handheld multispectral proximal sensor-sensor estimated fractional green cover and biomass (adj. R2 = 0.96 and 0.95; RMSE = 4.76% and 259 kg ha-1, respectively). Although active handheld multispectral proximal sensor-sensor derived fractional green cover and biomass estimates showed high accuracies (R2 = 0.96 and 0.96, respectively), they also demonstrated large intercept offsets (-25.5 and 4.51, respectively). Our results suggest that many passive multispectral remote sensing platforms may be used interchangeably to assess cover crop biophysical traits whereas SPOT 5 required an adjustment in NDVI intercept. Active sensors may require separate calibrations or intercept correction prior to combination with passive sensor data. Although surface reflectance products were highly correlated with proximal sensors, the standardized cloud mask failed to completely capture cloud shadows in Landsat 7, which dampened the signal of NIR and red bands in shadowed pixels.

Land surface conductance linked to precipitation: Co-evolution of vegetation and climate in Earth system models.

Vegetation and precipitation are known to fundamentally influence each other. However, this interdependence is not fully represented in climate models because the characteristics of land surface (canopy) conductance to water vapor and CO2 are determined independently of precipitation. Working within a coupled atmosphere and land modelling framework (CAM6/CLM5; coupled Community Atmosphere Model v6/Community Land Model v5), we have developed a new theoretical approach to characterizing land surface conductance by explicitly linking its dynamic properties to local precipitation, a robust proxy for moisture available to vegetation. This will enable regional surface conductance characteristics to shift fluidly with climate change in simulations, consistent with general principles of co-evolution of vegetation and climate. Testing within the CAM6/CLM5 framework shows that climate simulations incorporating the new theory outperform current default configurations across several error metrics for core output variables when measured against observational data. In climate simulations for the end of this century the new, adaptive stomatal conductance scheme provides a revised prognosis for average and extreme temperatures over several large regions, with increased primary productivity through central and east Asia, and higher rainfall through North Africa and the Middle East. The new projections also reveal more frequent heatwaves than originally estimated for the south-eastern US and sub-Saharan Africa but less frequent heatwaves across east Europe and northeast Asia. These developments have implications for evaluating food security and risks from extreme temperatures in areas that are vulnerable to climate change.

Digital economy and green total factor productivity in China.

The development of information technology has created conducive conditions for the digital economy. The digital economy is regarded as a critical pathway for transforming traditional economic models. Green total factor productivity serves as an indicator for assessing the quality of economic development. During pivotal periods of economic transition, the digital economy and green total factor productivity have emerged as two prominent themes for achieving sustainable economic development. But the impact of digital economy on green total factor productivity is less discussed. Innovation environment refers to a confluence of conditions shaped by factors such as talent, funding, cultural atmosphere and government policies, all of which collectively support innovative activities within a region. The institutional environment encompasses the aggregate of economic, political, social, and legal rules. Currently, there is little discussion on bringing innovation environment and institutional environment into the impact of digital economy on green total factor productivity. To fill the research gap, this paper adopts the Slack based measure-Directional distance function model and Malmquist-Luenberger productivity index to measure green total factor productivity in each region based on the panel data collected from 30 provinces in China from 2004 to 2019. Generalized Method of Moments method is constructed to carry out an empirical study on the impact of digital economy on green total factor productivity. This paper constructs a panel threshold model with innovation environment and institutional environment as threshold variables. In further analysis, this paper employs panel quantile regression for the empirical analysis of the impact of the digital economy on green total factor productivity. Further analysis elucidates the evident disparities in the influence of the digital economy on green total factor productivity at various levels. The research results can provide a guide for discussing the green value of the digital economy and its role in fostering the development of a green economy.

Stability of 20 Biogenic Amino Acids in Concentrated Sulfuric Acid: Implications for the Habitability of Venus' Clouds.

Scientists have long speculated about the potential habitability of Venus, not at the 700K surface, but in the cloud layers located at 48-60 km altitudes, where temperatures match those found on Earth's surface. However, the prevailing belief has been that Venus' clouds cannot support life due to the cloud chemical composition of concentrated sulfuric acid-a highly aggressive solvent. In this work, we study 20 biogenic amino acids at the range of Venus' cloud sulfuric acid concentrations (81% and 98% w/w, the rest water) and temperatures. We find 19 of the biogenic amino acids we tested are either unreactive (13 in 98% w/w and 12 in 81% w/w) or chemically modified in the side chain only, after 4 weeks. Our major finding, therefore, is that the amino acid backbone remains intact in concentrated sulfuric acid. These findings significantly broaden the range of biologically relevant molecules that could be components of a biochemistry based on a concentrated sulfuric acid solvent.

Comparative analysis of CAMS aerosol optical depth data and AERONET observations in the Eastern Mediterranean over 19 years.

Aerosol optical depth (AOD) is an essential metric for evaluating the atmospheric aerosol load and its impacts on climate, air quality, and public health. In this study, the AOD data from the Copernicus Atmosphere Monitoring Service (CAMS) were validated against ground-based measurements from the Aerosol Robotic Network (AERONET) throughout the Eastern Mediterranean, a region characterized by diverse aerosol types and sources. A comparative analysis was performed on 3-hourly CAMS AOD values at 550 nm against observations from 20 AERONET stations across Cyprus, Greece, Israel, Egypt, and Turkey from 2003 to 2021. The CAMS AOD data exhibited a good overall agreement with AERONET AOD data, demonstrated by a Pearson correlation coefficient of 0.77, a mean absolute error (MAE) of 0.08, and a root mean square error (RMSE) of 0.11. Nonetheless, spatial and temporal variations were observed in the CAMS AOD data performance, with site-specific correlation coefficients ranging from 0.57 to 0.85, the lowest correlations occurring in Egypt and the highest in Greece. An underestimation of CAMS AOD was noted at inland sites with high AOD levels, while a better agreement was observed at coastal sites with lower AOD levels. The diurnal variation analysis indicated improved CAMS reanalysis performance during the afternoon and evening hours. Seasonally, CAMS reanalysis showed better agreement with AERONET AODs in spring and autumn, with lower correlation coefficients noted in summer and winter. This study marks the first comprehensive validation of CAMS AOD performance in the Eastern Mediterranean, offering significant enhancements for regional air quality and climate modeling, and underscores the essential role of consistent validation in refining aerosol estimations within this complex and dynamic geographic setting.

Rapid fiber-detection technique by artificial intelligence in phase-contrast microscope images of simulated atmospheric samples.

Since the manufacture, import, and use of asbestos products have been completely abolished in Japan, the main cause of asbestos emissions into the atmosphere is the demolition and removal of buildings built with asbestos-containing materials. To detect and correct asbestos emissions from inappropriate demolition and removal operations at an early stage, a rapid method to measure atmospheric asbestos fibers is required. The current rapid measurement method is a combination of short-term atmospheric sampling and phase-contrast microscopy counting. However, visual counting takes a considerable amount of time and is not sufficiently fast. Using artificial intelligence (AI) to analyze microscope images to detect fibers may greatly reduce the time required for counting. Therefore, in this study, we investigated the use of AI image analysis for detecting fibers in phase-contrast microscope images. A series of simulated atmospheric samples prepared from standard samples of amosite and chrysotile were observed using a phase-contrast microscope. Images were captured, and training datasets were created from the counting results of expert analysts. We adopted 2 types of AI models-an instance segmentation model, namely the mask region-based convolutional neural network (Mask R-CNN), and a semantic segmentation model, namely the multi-level aggregation network (MA-Net)-that were trained to detect asbestos fibers. The accuracy of fiber detection achieved with the Mask R-CNN model was 57% for recall and 46% for precision, whereas the accuracy achieved with the MA-Net model was 95% for recall and 91% for precision. Therefore, satisfactory results were obtained with the MA-Net model. The time required for fiber detection was less than 1 s per image in both AI models, which was faster than the time required for counting by an expert analyst.

Clothing Textiles as Carriers of Biological Ice Nucleation Active Particles.

Microplastics have littered the globe, with synthetic fibers being the largest source of atmospheric microplastics. Many atmospheric particles can act as ice nucleators, thereby affecting the microphysical and radiative properties of clouds and, hence, the radiative balance of the Earth. The present study focused on the ice-nucleating ability of fibers from clothing textiles (CTs), which are commonly shed from the normal wear of apparel items. Results from immersion ice nucleation experiments showed that CTs were effective ice nucleators active from -6 to -12 °C, similar to common biological ice nucleators. However, subsequent lysozyme and hydrogen peroxide digestion stripped the ice nucleation properties of CTs, indicating that ice nucleation was biological in origin. Microscopy confirmed the presence of biofilms (i.e., microbial cells attached to a surface and enclosed in an extracellular polysaccharide matrix) on CTs. If present in sufficient quantities in the atmosphere, biological particles (biofilms) attached to fibrous materials could contribute significantly to atmospheric ice nucleation.