Climate change mitigation strategies increasingly focus on negative emission technologies, including enhanced weathering. This study investigates the relationship between cation release in soil and climate factors such as rainfall and temperature, as a method of modeling the dissolution of rock from a enhanced rock weathering deployment. We conducted a field experiment comparing basalt-amended plots with a control plot, measuring cation concentrations in soil porewater over time. Concurrently, we recorded rainfall and temperature data to assess environmental influences on cation release dynamics. Results show significant differences in cation release between basalt-amended and control plots. Statistical modeling reveals strong correlations between cation concentrations and both rainfall and temperature. Our findings demonstrate strong correlations with climatic factors which underscores the importance of considering environmental conditions when implementing enhanced weathering techniques. This research contributes to our understanding of the efficacy and dynamics of enhanced weathering in real-world conditions, informing future large-scale applications of this climate change mitigation approach. The predictive model developed from this study offers a valuable tool for estimating the potential effectiveness of enhanced weathering across diverse environmental settings.

A document by Tasfia Tasnim. Click on the document to view its contents.

The enhanced severity and frequency of extreme weather events, such as combined heat waves and heavy rainfall, pose significant concerns due to their devastating regional impacts. This research quantifies the association between heatwaves and heavy rainfall events using Event Coincidence Analysis during 1951-2020. We compute both the Precursor Coincidence Rate (PCR) and the Trigger Coincidence Rate (TCR), which are key metrics in understanding the physical link between heatwaves and subsequent heavy rainfall events. The PCR indicates the proportion of heatwave events that precede heavy rainfall events, providing insight into the reliability of the precursor (heatwave events) as an indicator of the trigger event (heavy rainfall events). TCR represents the proportion of heavy rainfall events that follow heatwave events, useful for evaluating the predictive power of the precursor. Our results reveal TCR decreased in the recent period as compared to the base period for shorter time frame (temporal windows ΔT=2 and Delta ΔT=5), however, exhibited a notable rise (50%) observed in approximately 70% of the grid points for longer temporal windows ( ΔT=7). The observation is very well in congruence that the moisture holding capacity of the atmosphere has enhanced and convective activity and latent heat release (heatwave producing extreme rainfall) take longer than usual. Moreover, PCR increased for all temporal windows, indicating an increased probability of heatwaves triggering precipitation events within 7 days of their end and predictive potential in the recent period compared to the base period. Approximately 27% of grid points experienced one heat-wave event within 7 days prior to heavy rainfall occurrence in the recent period, compared to 13% in the base period, for every 5 precipitation events. Results indicate an increased coupling between the occurrence of heat waves and heavy rainfall within a very short period, attributed to moisture convergence and atmospheric convection.

Across various nations, a significant shift towards a sustainable and environmentally responsible economy is occurring. Nevertheless, this positive transition is marred by a rise in greenwashing, wherein organizations overstate their environmental commitments. To combat this issue and safeguard consumers, initiatives have been developed to authenticate green claims. Given the increasing prevalence of environmental and scientific assertions, there is a pressing need for automated methods capable of detecting and validating these claims on a large scale. Recent advancements in artificial intelligence, particularly large language models (LLMs), have revolutionized the processing of diverse textual data as these models are extensively trained on vast datasets spanning multiple domains. In this paper, we evaluate the ability of several open-source LLMs to detect claims within the environmental domain where we have used various prompt engineering techniques like zero-shot, few-shot and contextual learning. To enhance performance, we have also finetuned a lightweight Large Language Model, Mistral-7B, on domain-specific data for the claim detection task. This approach reduces hallucination while retaining the benefits of LLMs and can also be employed to discern the grounds of claims and the types of climate pollution they aim to address. Acknowledging the inherent challenge posed by LLMs’ tendency to generate false or misleading information, we introduce EnClaim—a transformer-based architecture augmented with stylistic features. EnClaim integrates various linguistic stylistic elements with language models to improve the accuracy of claim detection, providing a robust framework for evaluating environmental claims.

Among the many challenges the Arctic region faces as shifting climate conditions threaten the frozen landscape, the collapse of its terrestrial transportation infrastructure is one of the most prominent. This research builds upon the Community Arctic Transportation Accessibility Model (CATAM) to find key areas of vulnerability for permanent roads and railroads as well as seasonal winter and ice roads. The latest version of CATAM uses CMIP6 data from NCAR’s Community Earth System Model (CESM) under moderate (SSP245) and extreme (SSP585) projected climate scenarios to create a comprehensive analysis of future terrestrial hazards. Changes in transportation and the accessibility of infrastructure networks are simulated across the Arctic states – the US (Alaska), Canada, Denmark (Greenland), Iceland, Norway, Sweden, Finland, and Russia. Preliminary results indicate a widespread decline in overland accessibility by mid-century, with Finland, western Russia, Nunavut and the Northwest Territories in Canada, and the North Slope Borough in Alaska particularly affected. The results of this research can help to inform policymakers and infrastructure planners in order to support sustainable transportation strategies and infrastructure development in the Arctic regions.

Since the dawn of civilization water reservoirs have been used to support irrigation and livestock in many arid regions of the world [1]. Evaporative losses diminish reservoir storage efficiency; hence, different means such as floating covers have been proposed to reduce losses. While laboratory and field studies have evaluated effects of cover properties (e.g., geometry, thermal, and radiative characteristics) on Evaporation Suppression Efficiency (ESE) [2-4], the influence of seasonal climate variability on ESE remains understudied. We conducted long-term field measurements in two identical water reservoirs (area: 25 m2, depth: 2 m) in a dry region to investigate how seasonal variations in atmospheric conditions affect ESE. We compared the evaporation rate and water temperature profile in a reservoir covered with Styrofoam discs (D: 50 cm, H: 5 cm) with those in an uncovered reservoir. For 90% surface coverage, measurements indicate that ESE varied from nearly 80% in summer to about 60% in winter. Temperature variations and radiative energy storage within the reservoirs show that the opaque and thermal insulating characteristics of the Styrofoam discs and their effects on wind-induced mixing lead to thermal stratification and formation of a seasonal thermocline in the covered reservoir. These affect the exchange of accumulated summer heat with overlying air resulting in a slower reduction in evaporation rate compared to the uncovered reservoir in cold seasons. The study sheds new light on thermal regimes and ESE in partially covered multiuse reservoirs under different climatic conditions. References [1] M. Aminzadeh, N. Friedrich, S. Narayanaswamy, K. Madani, and N. Shokri, Evaporation Loss from Small Agricultural Reservoirs in a Warming Climate: An Overlooked Component of Water Accounting, Earth’s Future, 12(1), 2024. [2] M. Aminzadeh, P. Lehmann, and D. Or, Evaporation suppression and energy balance of water reservoirs covered with self-assembling floating elements, Hydrology and Earth System Sciences, 22(7), 2018. [3] M. Bakhtiar, M. Aminzadeh, M. Taheriyoun, D. Or, and E. Mashayekh, Effects of floating covers used for evaporation suppression on reservoir physical, chemical and biological water quality parameters, Ecohydrology, 15(8), 2022. [4] P. Lehmann, M. Aminzadeh, and D. Or, Evaporation Suppression from Water Bodies Using Floating Covers: Laboratory Studies of Cover Type, Wind, and Radiation Effects, Water Resources Research, 55(6), 2019.

Satellite-based soil moisture retrieval (SSMR) is crucial for various applications such as crop yield estimation, land surface-climate interactions, drought monitoring, irrigation management, and urban water management. SSMR covers two key areas: surface soil moisture (SSM) analysis, which focuses on the top 3–5 cm of soil, and root-zone soil moisture (RZSM) estimation, which extends to depths of 30–110 cm. While remote sensing has been widely utilized for large-scale SSM estimation, its application for farm-scale RZSM retrieval and soil hydraulic parameter estimation remains underexplored and previous studies have primarily assimilated either land surface temperature (LST) or SSM separately. This research, thus, emphasizes the interdependency between soil moisture and temperature and proposes a new method using a reduced-order variational approach to simultaneously assimilate LST and SSM data from thermal and microwave satellite remote sensing into the HYDRUS-1D model. Our framework aims to estimate soil hydraulic parameters and RZSM profiles at the farm scale (~30m-1km) using data from MODIS, LANDSAT-8, and SMAP, by combining the horizontal coverage and spatial resolution of remote sensing with the vertical coverage and temporal continuity of the soil moisture simulation models. We have designed an Observing System Simulation Experiment (OSSE) to evaluate this framework. Preliminary results indicate that coupling soil temperature and moisture models enhances the accuracy of surface energy and water flux predictions. Additionally, it enables more precise estimation of soil hydraulic parameters compared to models that assimilate only LST or SSM data. These findings highlight the potential of using freely available satellite data to estimate RZSM profiles and soil hydraulic parameters globally, thereby reducing the reliance on costly ground-based measurements. This research advances hydrological modeling capabilities and demonstrates how integrated satellite observations can improve water resource management, particularly in underserved communities.

This study delves into the present-day seismotectonic conditions beneath the intracontinental High Atlas Mountains, Morocco, with a focus on the region of the significant Al Haouz earthquake on September 8, 2023. the analysis encompasses over twenty moderate seismic events recorded since 2009, utilizing a database of high-resolution seismic recordings (magnitudes ranging from 3.5 to 7) collected by networks established between 2008 and 2024. The primary objective is to refine preliminary earthquake relocation, initially based on P-wave arrival times, by incorporating residual travel-time data from each hypocenter pair to seismic stations. Results from these methods are nearly identical, with the double-difference method yielding the most accurate outcomes. Seismic activity in the region, with depths not exceeding 30 km, appears Skin-Deep, consistent with observations from the latesst Al Haouz earthquake, occurring at a depth of 31 km. The present-day tectonic regimes along the High Atlas system (western and central parts) are determined through inversion of regional seismic moment and tectonic stress tensors. Focal mechanism solutions for well-located earthquakes are calculated using P-wave first motion polarities and regional moment tensor inversion. Subsequently, tectonic stress tensor properties are derived through inversion of focal mechanism parameters. Most seismic events analyzed exhibit focal mechanisms characterized by pure reverse faulting or reverse faulting with a strike-slip faulting component. The orientation of P, B & T axes is 16/189, 39/036, and 08/104 respectively. Estimated stress tensor parameters suggest σ1 axes trend N-S in the Western High Atlas and NW-SE to NNW-NNE in the Central High Atlas. These tectonic regimes align well with GPS velocities and neotectonic data, elucidating the tectonic deformation process observed in the High Atlas, particularly in concordance with characteristics of the Al Haouz earthquake beneath the Western High Atlas area. Keywords: Double Difference Location, First Motion Polarity, Focal Mechanism, Tectonic Stress, Inversion, Western High Atlas, Central High Atlas, Morocco.

The Southern Ocean (SO) provides a unique natural laboratory for studying cloud formation and cloud-aerosol interactions with minimal anthropogenic influence. The Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES), was an aircraft-based campaign conducted from Jan 15 to Feb 28, 2018, off the coast of Hobart, Tasmania, utilizing the NSF/NCAR GV research aircraft. The aircraft was equipped with in-situ probes and remote sensors to observe precipitation, cloud particles, and aerosols, providing detailed vertical profiles to characterize the marine boundary layer (MBL) and free troposphere.

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Wildfire poses an increasing risk to forested and urban areas. Combustion related to fire has been shown to generate low frequency acoustic waves and infrasound (sound below 20 Hz). Here, acoustic waves from a semi-realistic linear fire source are modeled in a 3x3km simulated forest medium using infraFDTD, a 3-D numerical solver for the acoustic wave equation using Finite-Difference Time-Domain (FDTD) method (Kim and Lees, GRL 2011). The model is validated by comparing it to acoustic observations from a prescribed burn at Eglin Air Force Base in March 2023. Model parameters are altered to constrain the source dimensions, geometry, and source time function necessary to create an observable and distinct acoustic signal from a plume during a fire. Results show that the dimensions, intensity, and source function of firelines have a significant effect on signal strength and frequency. All frequencies are constrained from 0-25 Hz. Longer firelines produce prolonged high amplitude, lower frequency signals, with dominant signals in the 0-4 Hz range. More intense fires produce fewer low amplitude, high frequency signals (6-14 Hz) and stronger, longer-lasting signals in the 0-4 Hz range. Dominant frequencies of a semi-realistic fire signal range from 0-5 Hz, with weaker signals in the 5-15 Hz range, and higher frequencies (15-25 Hz) produced by noise. Additionally, inverse modeling using the Reverse Time Migration (RTM) (Kim and Lees, GJI 2015) technique demonstrates the potential for imaging the acoustic source of fires from observation stations below 15 Hz (Figure 1).

This study delves into the present-day seismotectonic conditions beneath the intracontinental High Atlas Mountains, Morocco, with a focus on the region of the significant Al Haouz earthquake on September 8, 2023. the analysis encompasses over twenty moderate seismic events recorded since 2009, utilizing a database of high-resolution seismic recordings (magnitudes ranging from 3.5 to 7) collected by networks established between 2008 and 2024. The primary objective is to refine preliminary earthquake relocation, initially based on P-wave arrival times, by incorporating residual travel-time data from each hypocenter pair to seismic stations. Results from these methods are nearly identical, with the double-difference method yielding the most accurate outcomes. Seismic activity in the region, with depths not exceeding 30 km, appears Skin-Deep, consistent with observations from the latesst Al Haouz earthquake, occurring at a depth of 31 km. The present-day tectonic regimes along the High Atlas system (western and central parts) are determined through inversion of regional seismic moment and tectonic stress tensors. Focal mechanism solutions for well-located earthquakes are calculated using P-wave first motion polarities and regional moment tensor inversion. Subsequently, tectonic stress tensor properties are derived through inversion of focal mechanism parameters. Most seismic events analyzed exhibit focal mechanisms characterized by pure reverse faulting or reverse faulting with a strike-slip faulting component. The orientation of P, B & T axes is 16/189, 39/036, and 08/104 respectively. Estimated stress tensor parameters suggest σ1 axes trend N-S in the Western High Atlas and NW-SE to NNW-NNE in the Central High Atlas. These tectonic regimes align well with GPS velocities and neotectonic data, elucidating the tectonic deformation process observed in the High Atlas, particularly in concordance with characteristics of the Al Haouz earthquake beneath the Western High Atlas area.

A document by Rosaria Tondi. Click on the document to view its contents.

A document by Anurag Sharma. Click on the document to view its contents.

Diamonds are primary records of carbon transport in the deep mantle. Their growth is mediated by carbon-bearing fluids, but this process is challenging to study, due both to the rarity of fluid inclusions and limitations in imaging crystal growth structures and trace element abundances. We overcome some of these limitations in two ways: 1) by careful sample selection of twinned diamonds, which tend to incorporate remnants of their growth fluids in the regions next to the twinning plane; and 2) by using a custom 3D fluorescence-lifetime imaging system to map the concentration of A-center N aggregates in the diamonds using the quenching of N3 lifetime. The mapping reveals the 3D internal growth structure in high resolution, offering a marked advantage over current popular techniques such as cathodoluminescence imaging that can only image 2D diamond surfaces.The 3D analysis shows growth initially from a central nucleation site, and then subsequently in concentric layers. The layers are periodic in their A-center concentrations but are crosscut by sinuous linear features with elevated A-center concentrations oriented roughly perpendicular to the (111) twin plane. These features have a triangular cross section aligned with the (111) face’s triangular morphology, interpreted as growth spirals centered on screw dislocations, which act as nucleation sites during periods of crystal growth. Initial crystal growth is often rapid due to supersaturation of reactants in the fluid. Rapid growth tends to incorporate more incompatible elements which may explain the relatively high N (as A-centers) concentrations along these linear features. The periodic banding suggests a pulsed fluid supply and either a change in growth rate (growth starts fast, then slows and stops at the end of each pulse); or a change in fluid composition over the course of a pulse (fluid reacts, diamond precipitates, and fluid matures).Twinned diamonds often entrap clusters of micro fluid-inclusions at the twin plane during growth. Raman mapping of these inclusions reveals the presence of hydrous-silicic fluids, N-bearing phases, hydrocarbons, as well as olivine and enstatite. These inclusions clusters are likely remnants of the primary growth fluid and will help connect our observations of growth with fluid compositions over time.Plain-Language SummaryWe studied the growth of diamonds because they are one of the primary records of carbon transport deep in earth’s mantle. This study demonstrates that diamonds grow due to periodic pulses of carbon rich-fluid moving through, and then reacting with the solid rock of the mantle. We show that a new imaging method, 3D fluorescence-lifetime mapping, is a powerful tool to add to the suite of methods available for studying the growth of diamonds. By imaging diamond growth bands, we learn about trends in the episodic nature of crystallization. It helps distinguish changes in diamond composition over time and provides context for growth around inclusions. We looked at a specific type of sample that contains remnants of the diamond forming fluid, trapped in clusters of very small inclusions. The 3D fluorescence-lifetime mapping helps us determine that the inclusions were trapped early in diamond growth. Using another method, Raman spectroscopy mapping, we identify that individual micro-inclusions within the clusters have different compositions. We find fluid inclusions rich in hydrated-silica, in nitrogen and others in hydrocarbons. This work helps us to determine more about the composition and transport of the carbon-rich diamond forming fluids deep in the earth.

A document by Lindsay Fitzpatrick. Click on the document to view its contents.

Intra-city buses are crucial for urban transportation, providing essential mobility services. However, in India, the public sector's total bus fleet expanded from 1.89 million units in 2014 to its current size in 2023, reflecting a compound annual growth rate of 2.19%. This growth has led to significant emissions and impacts on air quality in urban areas. This study evaluates the real-world fuel efficiency and emission characteristics of gaseous pollutants from urban transit diesel buses under heterogeneous traffic conditions using a portable emissions measurement system. Fuel consumption rates were determined in real-time using a carbon balance method based on the emission rates of major carbonaceous pollutants. Under typical real-world driving conditions, the average distance-specific fuel consumption for diesel buses is 29.3 L/100 km with the air conditioning off and 42.7 L/100 km with the air conditioning on. The average emission rates (g/s) for CO, HC, CO2, and NO gases from transit buses were measured at 0.092 ± 0.057, 0.054 ± 0.032, 0.436 ± 0.186, and 0.089 ± 0.058, respectively. The maximum emission factors observed were 17.98 g/km for CO and 12.93 g/km for HC+NO, which exceed the BS emission standards by 10.3 to 15.2 times (BS III: CO = 0.95 g/km, HC+NO = 0.86 g/km; BS IV: CO = 0.74 g/km, HC+NO = 0.46 g/km). Fuel efficiency in buses is influenced by operating conditions such as land use, ridership, speed, and accessibility. These insights underscore the need for enhanced transit management strategies to optimize fuel use and limit emissions.

Superposed Epoch Analysis: • Analyzes data around 286 geomagnetic disturbance events (SYM-H ⩽-50 nT). • Aligns data around a 'zero epoch' (minimum SYM-H). • Averages data across events to find common patterns. • Parameters: SYM-H measures the intensity of the geomagnetic storm by monitoring the horizontal component of the Earth's magnetic field near the equator. • Ey, dawn-to-dusk Interplanetary Electric Field • Bz, North-South component of the interplanetary magnetic field (IMF) • SME Index (SuperMAG Electrojet Index), measures the strength of the auroral electrojets. Equatorial plasma bubbles (EPBs) disrupt trans-ionospheric communication, especially Global Navigation Satellite System (GNSS) signals, adversely affecting navigation accuracy. Understanding how geomagnetic activity influences EPBs is crucial. This study uses superposed epoch analysis on geomagnetic indices, zonal and meridional winds, and the σ index (an EPB indicator) with data from the ICON satellite (2020-2022, 18:00-23:00 SLT). Results show that in South America, EPBs decrease as geomagnetic activity declines, while in Africa, they increase with geomagnetic disturbances. Additionally, a westward shift in zonal winds aligns with peak geomagnetic activity, underscoring regional differences in EPB behavior.