Melt ponds have a strong impact on the Arctic surface energy balance and the ice-associated ecosystem because they transmit more solar radiation compared to bare ice. In the existing literature, melt ponds are considered as bright windows to the ocean, even during freeze-up in autumn. In the central Arctic during the summer-autumn transition in 2018, we encountered a situation where more snow accumulated on refrozen melt ponds compared to the adjacent bare ice, leading to a reduction in light transmittance of the ponds even below that of bare ice. Supporting results from a radiative transfer model suggest that melt ponds with a snow cover >0.04 m lead to lower light transmittance than adjacent bare ice. This scenario has not been described in the literature before, but has potentially strong implications for example on autumn ecosystem activity, oceanic heat budget and thermodynamic ice growth.

The difference between precipitation and evaporation has been extensively used to characterize the water cycle’s response to global warming. However, when it comes to the global scale, the information provided by this metric is inconclusive. Herein, we discuss how the sum of precipitation and evaporation could complement the assessment of global water cycle intensification. To support our argument, we present a brief yet robust correlation analysis of both metrics in four reanalysis data sets (20CR v3, ERA-20C, ERA5, and NCEP/NCAR R1). Additionally, by combining the two metrics, we investigate how well the global water cycle fluxes are represented in the four reanalyses. Among them, we observe four different responses to the temperature increase between 1950-2010, with ERA5 showing the best agreement with the intensification hypothesis. We argue that these discrepancies would remain elusive with the traditional approach, which makes the utilization of the sum of precipitation and evaporation a valuable addition to our methodological toolbox for the assessment of the global water cycle intensification.

Alkalinity, the excess of proton acceptors over donors, plays a major role in ocean chemistry, in buffering and in calcium carbonate precipitation and dissolution. Understanding alkalinity dynamics is pivotal to quantify ocean carbon dioxide uptake during times of global change. Here we review ocean alkalinity and its role in ocean buffering as well as the biogeochemical processes governing alkalinity and pH in the ocean. We show that it is important to distinguish between measurable titration alkalinity and charge-balance alkalinity that is used to quantify calcification and carbonate dissolution and needed to understand the impact of biogeochemical processes on components of the carbon dioxide system. A general treatment of ocean buffering and quantification via sensitivity factors is presented and used to link existing buffer and sensitivity factors. The impact of individual biogeochemical processes on ocean alkalinity and pH is discussed and quantified using these sensitivity factors. Processes governing ocean alkalinity on longer time scales such as carbonate compensation, (reversed) silicate weathering and anaerobic mineralization are discussed and used to derive a close-to-balance ocean alkalinity budget for the modern ocean.

The Pacific Meridional Mode (PMM) exhibits a marked seasonal variability, with the strongest (weakest) variance in northern spring (fall). Such a phase locking feature is investigated through a combined observational and modeling study. Given the PMM perturbation, the wind induced latent heat flux anomaly leads to a strongest (weakest) heating on local sea surface temperature anomaly (SSTA) in MAM (SON) through positive wind-evaporation-SST feedback. The difference between MAM and SON lies on the strength and area of mean northeasterly trades. Experiments with a simple air-sea coupled model further demonstrate that a PMM-like SSTA perturbation grows much faster in MAM than in SON. The difference is primarily attributed to the seasonal mean wind, not mean SST condition. It is greatest strength and area of the mean northeasterly trade in MAM that leads to most efficient wind-evaporation-SST feedback and thus fastest PMM growth rate.

The stability, structure, and elastic properties of pyrite-type (FeS2 structured) FeO2H were determined using density functional theory-based computations with a self-consistent Coulombic self-interaction term (Ueff). The properties of pyrite-type FeO2H are compared to that of pyrite-type AlO2H with which it likely forms a solid solution at high temperature, as well as the respective lower pressure CaCl2-type polymorphs of both endmembers: e-FeOOH and d-AlOOH. Due to substantial differences in the CaCl2-type to pyrite-type structural transition pressures of these endmembers, the stabilities of the (Al,Fe)O2H solid solution polymorphs are anticipated to be compositionally driven at lower mantle pressures. As the geophysical properties of (Al,Fe)OOH are structurally dependant, interpretations regarding the contribution of pyrite-type FeO2H to seismically observed features must take into account the importance of this broad phase loop. With this in mind, Fe-rich pyrite-type (Al,Fe)OOH may coexist with Al-dominant CaCl2-type d-(Al,Fe)OOH in the deep Earth. Furthermore, pyrite-type (Al0.5-0.6,Fe0.4-0.5)O2H can reproduce the reduced compressional and shear velocities characteristic of seismically observed Ultra Low Velocity Zones (ULVZs) in the Earth’s lowermost mantle while Al-dominant but Fe-bearing CaCl2-type d-(Al,Fe)OOH may contribute to Large Low Shear Velocity Provinces (LLSPs).

Observations of the spatio-temporal structure of turbulent mixing in a large, energetic strait were used to examine the interactions between wind- and tidally-forced boundary layers in a coastal environment. Te Moana-o-Raukawa (Cook Strait) of Aotearoa (New Zealand) is a relatively wide, energetic strait, known to experience substantial tidal currents and wind stress. A turbulence-enabled ocean glider mission measured O(40,000) turbulence samples that passed QAQC including the use of a vehicle-mounted speed through water sensor. The observations were compared to one-dimensional models of turbulence to understand the mechanisms that regulates the vertical structure of mixing. Tidal flows of O(1 m/s) and wind speeds of O(10 m/s) enhance dissipation to ε=O(10^{-5} W/kg) through boundary drag, shear-driven production of turbulent kinetic energy (P) and to a minor extent buoyancy flux (G). The benthic and wind-driven boundary layers behaved reasonably predictably when considering a 1D perspective. The interaction between the two boundary layers depended on mid-water column stratification which is to a large degree an externally-prescribed condition. Transient stratification can stabilize the mean flow (median Ri_g=0.6(>1/4)) and reduce both turbulence intensity (Re_b) and diapycnal diffusivity (K_z) by up to two orders of magnitude in the middle of the water column, insulating bottom and surface mixing-layers. Mid-water dissipation rate levels tend to be associated with marginal dynamical stability (median Ri_g=0.22(~1/4)) and canonical mixing efficiency (median R_f=0.17), while elevated levels are connected to unstable mean flow conditions (median Ri_g=0.14(<1/4)) and reduced mixing efficiency (median R_f=0.1(<0.17)) that promotes turbulence growth.

We investigate if the commonly neglected riverine detrital carbonate fluxes might balance several chemical mass balances of the global ocean. Particulate inorganic carbon (PIC) concentrations in riverine suspended sediments, i.e., carbon contained by these detrital carbonate minerals, was quantified at the basin and global scale. Our approach is based on globally representative datasets of riverine suspended sediment composition, catchment properties and a two-step regression procedure. The present day global riverine PIC flux is estimated at 3.1 ± 0.3 Tmol C/y (13% of total inorganic carbon export and 4 % of total carbon export), with a flux-weighted mean concentration of 0.26 ± 0.03 wt%. The flux prior to damming was 4.1 ± 0.5 Tmol C/y. PIC fluxes are concentrated in limestone-rich, rather dry and mountainous catchments of large rivers in Arabia, South East Asia and Europe with 2.2 Tmol C/y (67.6 %) discharged between 15 °N and 45 °N. Greenlandic and Antarctic meltwater discharge and ice-rafting additionally contribute 0.8 ± 0.3 Tmol C/y. This amount of detrital carbonate minerals annually discharged into the ocean implies a significant contribution of calcium (~ 4.75 Tmol Ca/y) and alkalinity fluxes (~ 10 Tmol(eq)/y) to marine mass balances and moderate inputs of strontium (~ 5 Gmol Sr/y), based on undisturbed riverine and cryospheric inputs and a dolomite/calcite ratio of 0.1. Magnesium fluxes (~ 0.25 Tmol Mg/y), mostly hosted by less-soluble dolomite, are rather negligible. These unaccounted fluxes help elucidating respective marine mass balances and potentially alter conclusions based on these budgets.

Iran (Persian: ایران‎ Irān [ʔiːˈɾɒːn] (About this soundlisten)), also called Persia,[11] and officially the Islamic Republic of Iran,[a] is a country in Western Asia. It is bordered to the northwest by Armenia and Azerbaijan,[b] to the north by the Caspian Sea, to the northeast by Turkmenistan, to the east by Afghanistan, to the southeast by Pakistan, to the south by the Persian Gulf and the Gulf of Oman, and to the west by Turkey and Iraq. Iran covers an area of 1,648,195 km2 (636,372 sq mi), with a population of 85 million.[12] It is the second-largest country in the Middle East (after Saudi Arabia), the sixth-largest entirely in Asia, and its capital and largest city is Tehran.

Studies on the molecular mechanisms of microbial adaptation in chaotropic and low water activity (aw) environments are poorly understood. Chaotropic environments are characterized as salt rich, MgCl2 and CaCl2, which lowers the availability of water for biological processes. PATRIC, an integrated genomic browsing tool containing vast libraries of sequenced genomes, can help us identify unique genetic markers in chaophilic and xerophilic microbes. Halophilic microbes are characterized as obligate hypersaline with the ability to tolerate exposure to chaotropic agents. Microbes with the greatest tolerance in these extreme environments must have advanced adaptive methods. Halobacterium salinarum and Haloquadratum walsbyi are chaotolerant and well adapted to low water activity. Haloquadratum walsbyi is unique among the halophilics as having the highest tolerance for chaotropes and its square shape. Performing comparative genomics using fully sequenced halophilic archaea such as Halobacterium salinarum NRC-1, a model halophile, and Haloquadratum walsbyi C23, we were able to identify genes that confer adaptation to chaotropic and low aw environments, as well as individual adaptations that may be responsible for the varying levels of tolerance in chaotropic environments . Characterizing genes associated with chaotolerance and low aw adaptations can help elucidate the cellular functions that make these microbes unique. Chaotropic brines may be used as analogs to study the origin of life and the possibility of suitable environments hosting extremophilic microbes on other planets like the Martian brines and the icy moons of Europa; therefore, studying the microbiome of chaotropic environments are essential in the field of astrobiology.

Debate abounds regarding the composition of the deep (middle + lower) continental crust. Studies of medium and high grade metamorphic lithologies guide us but encompass mafic (< 52 wt.%) to felsic (> 68 wt.%) compositions. This study presents a global compilation of geochemical data on amphibolite (n = 6500), granulite (n = 4000), and eclogite (n = 200) facies lithologies and quantifies systematic trends, uncertainties, and sources of bias in the deep crust sampling. The continental crust’s Daly Gap is well documented in amphibolite and most granulite facies lithologies, with eclogite facies lithologies and granulite facies xenoliths having mostly mafic compositions. Al2O3, Lu, and Yb vary little from the top to bottom of the crust. In contrast, SiO2 and incompatible elements show a wider range of abundances. Because of oversampling of mafic lithologies, our predictions are a lower bound on middle crustal composition. The distinction between granulite facies terrains (intermediate SiO2, high heat production, high incompatibles) or granulite facies xenoliths (low SiO2, low heat production, low incompatibles) as being the best analogs of the deep crust remains disputable. We incorporated both, along with amphibolite facies lithologies, to define a deep crustal composition that approaches 57.6 wt.% SiO2. This number, however, represents a compositional middle ground, as seismological studies indicate a general increase in density and seismic velocity with increasing depth. Future studies should analyze more closely the depth dependent trends in deep crustal composition so that we may develop compositional models that are not limited to a three-layer crust.

Iodine-initiated new particle formation (I-NPF) has long been recognized in coastal hotspot regions. However, no prior work has studied the exact chemical composition of organic compounds and their role in the coastal I-NPF. Here we present an important complementary study to the ongoing laboratory and field researches of iodine nucleation in coastal atmosphere. Oxidation and NPF experiments with vapor emissions from real-world coastal macroalgae were simulated in a bag reactor. On the basis of comprehensive mass spectrometry measurements, we reported for the first time a series of volatile precursors and their oxidation products in gas and particle phases in such a highly complex system. Organic compounds overwhelmingly dominated over iodine in the new particle growth initiated by iodine species. The identity and transformation mechanisms of organic compounds were identified in this study to provide a more complete story of coastal NPF from low-tide macroalgal emission.

The potential commonality of prebiotic chemical processes on Titan and the primitive Earth makes Titan a prime body of astrobiological interest. Amino acid synthesis can occur if the abundant simple organics on Titan’s surface can mix with liquid water. Because events that melt surface ice, such as impacts, are rare, it is essential to recognize how long the synthesized molecules remain intact on Titan’s surface. The degradation of biomolecules in extraterrestrial environments can be estimated by combining theoretical work about energy deposition on the surface with experimental results from irradiation of organic molecules. We modelled the destruction of amino acids on the surface of Titan, something absent in current literature. We chose Glycine, Alanine, and Phenylalanine as our molecules of interest due to relevant experimental results for their radiation stability at Titan temperatures. Titan’s thick atmosphere prevents solar radiation and energetic particles trapped in Saturn’s magnetosphere from reaching the surface. The dominant source of energetic radiation at the surface of Titan is the diminished flux of Galactic Cosmic Rays (GCR’s) that penetrate the atmosphere. Sittler Jr et al. (Icarus, 2019) modeled surface GCR flux to be ~10^-9 ergs/cm^3/s. Using the GCR flux, in conjunction with the half-life doses at T=100 K from Gerakines et al. (Icarus, 2012), we estimate the half-lives to be 7.69 x 10^12;, 5.07 x 10^12, and 5.82 x 10^12 years for Glycine, Alanine and Phenylalanine, respectively. These extraordinarily long half-lives on Titan’s surface, as compared to similar calculations for amino acids on Mars, Europa, or Pluto, are directly the result of reduced energy deposition due to the atmosphere. We thus conclude that the degradation of these three amino acids by GCR flux is insignificant over geological time, and will not be an essential factor in interpreting the chemistry from Titan’s surface samples from future missions, such as Dragonfly.

Lead (Pb) is a neurotoxicant that particularly harms young children. Urban environments are often plagued with elevated Pb in soils and dusts, posing a health exposure risk from inhalation and ingestion of these contaminated media. Thus, a better understanding of where to prioritize risk screening and intervention is paramount from a public health perspective. We have synthesized a large national dataset of Pb concentrations in household dusts from across the United States (U.S.), part of a community science initiative called “DustSafe.” Using these results, we have developed a straightforward logistic regression model that correctly predicts whether Pb is elevated (> 80 ppm) or low (< 80 ppm) in household dusts 75% of the time. Additionally, our model estimated 18% false negatives for elevated Pb, displaying that there was a low probability of elevated Pb in homes being misclassified. Our model uses only variables of approximate housing age and whether there is peeling paint in the interior of the home, illustrating how a simple and successful Pb predictive model can be generated if researchers ask the right screening questions. Scanning electron microscopy supports a common presence of Pb paint in several dust samples with elevated bulk Pb concentrations, which explains the predictive power of housing age and peeling paint in the model. This model was also implemented into an interactive mobile app that aims to increase community-wide participation with Pb household screening. The app will hopefully provide greater awareness of Pb risks and a highly efficient way to begin mitigation.

Agricultural emissions of ammonia (NH3) impact air quality, human health, and the vitality of aquatic and terrestrial ecosystems. In the UK, there are few direct policies regulating anthropogenic NH3 emissions and development of sustainable mitigation measures necessitates reliable emissions estimates. Here we use observations of column densities of NH3 from two space-based sensors (IASI and CrIS) with the GEOS-Chem model to derive top-down NH3 emissions for the UK at fine spatial (~10 km) and time (monthly) scales. We focus on March-September when there is adequate spectral signal to reliably retrieve NH3. We estimate total emissions of 272 Gg from IASI and 389 Gg from CrIS. Bottom-up emissions are 27% less than IASI and 49% less than CrIS. There are also differences in seasonality. Top-down and bottom-up emissions agree on a spring April peak due to fertilizer and manure application, but there is also a comparable summer July peak in the top-down emissions that is not in the bottom-up emissions and appears to be associated with dairy cattle farming. We estimate relative errors in the top-down emissions of 11-36% for IASI and 9-27% for CrIS, dominated by column density retrieval errors. The bottom-up versus top-down emissions discrepancies estimated in this work impact model predictions of the environmental damage caused by NH3 emissions and warrant further investigation.

Understanding mechanical processes occurring on faults requires detailed information on the microseismicity that can be enhanced today by advanced techniques for earthquake detection. This problem is challenging when the seismicity rate is low and most of the earthquakes occur at depth. In this study, we compare three detection techniques, the autocorrelation FAST, the machine learning EQTransformer, and the template matching EQCorrScan, to assess their ability to improve catalogs associated with seismic sequences in the normal fault system of Southern Apennines (Italy) using data from the Irpinia Near Fault Observatory (INFO). We found that the integration of the machine learning and template matching detectors, the former providing templates for the cross-correlation, largely outperforms techniques based on autocorrelation and machine learning alone, featuring an enrichment of the automatic and manual catalogs of factors 21 and 7 respectively. Since output catalogs can be polluted by many false positives, we applied refined event selection based on the cumulative distribution of their similarity level. We can thus clean up the detection lists and analyze final subsets dominated by real events. The magnitude of completeness decreases by more than one unit compared to the reference value for the network. We report b-values associated with sequences smaller than the average, likely corresponding to larger differential stresses than for the background seismicity of the area. For all the analyzed sequences, we found that main events are anticipated by foreshocks, indicating a possible preparation process for mainshocks at sub-kilometric scales.

Climate mitigation can bring health co-benefits by improving air quality. Yet, whether mitigation will widen or narrow current health disparities remains unclear. Here we use a coupled climate-energy-health model to assess the effects of a global carbon price on the distribution of ambient fine particulate matter (PM2.5) exposure and associated health risks across an ensemble of nearly 30,000 future scenarios. We find that pricing carbon consistently lowers the PM2.5-attributable death rates in lower-income countries by reducing fossil fuel burning (e.g., China and India). Since these countries are projected to have large ageing populations, the greatest reduction in global average PM2.5-attributable death rate is found in elderly populations, which are more vulnerable to air pollution than the other age groups. In contrast, the health effects in higher-income countries are more complex, because pricing carbon can increase the emissions from bioenergy use and land-use changes, counteracting the mortality decrease from reduced fossil fuel burning. Mitigation technology choices and complex interactions between age structures, energy use, and land use all influence the distribution of health effects. Our results highlight the importance of an improved understanding of regional characteristics and cross-sector dynamics for addressing the interconnected challenges of climate, health, and social inequalities.

It is generally accepted that modeling Farley-Buneman instabilities require resolving ion Landau damping to reproduce experimentally observed nonlinear features. Particle in cell (PIC) simulations have been able to reproduce most of these, but at a computational cost that severely affects its scalability. This limitation hinders the study of non-local phenomena that require three dimensions or coupling with larger-scale processes. We argue that a form of the five-moment fluid system can recreate several aspects of Farley-Buneman dynamics such as density and phase speed saturation, wave turning, and heating. A comparison between the proposed fluid and a kinetic model shows good qualitative agreement.

This article is composed of three independent commentaries about the state of ICON principles (Goldman et al. 2021) in the AGU Biogeosciences section and discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: Global collaboration, technology transfer and application (Section 2), Community engagement, citizen science, education, and stakeholder involvement (Section 3), and Field, experimental, remote sensing, and real-time data research and application (Section 4). We discuss needs and strategies for implementing ICON and outline short- and long-term goals. The inclusion of global data and international community engagement are key to tackle grand challenges in biogeosciences. Although recent technological advances and growing open-access information across the world have enabled global collaborations to some extent, several barriers ranging from technical to organizational to cultural have remained in advancing interoperability and tangible scientific progress in biogeosciences. Overcoming these hurdles is necessary to address pressing large-scale research questions and applications in the biogeosciences, where ICON principles are essential. Here, we list several opportunities for ICON, including coordinated experimentation and field observations across global sites, that are ripe for implementation in biogeosciences as a means to scientific advancements and social progress.