The role of micro-nano-scale stimulation of coalbed methane (CBM) reservoir is to open the fracture and pore channels, improve gas desorption and migration capabilities, and thereby increase CBM production capacity. Based on hydraulic fracturing simulation experiments, combined with liquid nitrogen absorption (LNA) and mercury intrusion porosity (MIP) measurements, the micro-nano-scale pore structure of coal before and after hydraulic fracturing stimulation in coal reservoirs was studied. It is found that significant changes in the number of pores in different pore sizes are the main reason for the changes in coal pore volume (PV) and pore specific surface area (PSSA) after hydraulic fracturing. the micro-nano-scale pore stimulation of hydraulic fracturing includes two forms of pore fragmentation and pore deformation, the coal with larger elastic modulus is mainly manifested as brittle crush. Moreover, larger in-situ stress will inhibit pore fracture and expansion, and even cause further compression of pores.

The uplift of the southern African Plateau is often attributed to mantle processes, but there are conflicting theories for the specific timing and drivers of topographic development. Evidence for most proposed plateau development histories is derived from continental erosion histories, marine stratigraphic architecture, or landscape morphology. Here we use a landscape evolution model to integrate these three types of data for southern Africa, including a large dataset of low temperature thermochronology, sediment flux rates to surrounding marine basins. We explore three main hypotheses for surface uplift: 1) southern Africa was already elevated at the time of Gondwana breakup, 2) uplift and continental tilting occurred in the mid-Cretaceous, or 3) uplift occurred in the mid to late Cenozoic. We test which of these three intervals of plateau development are plausible by using an inversion method to constrain the range in erosional and uplift model parameters that can best reproduce the observed data. Results indicate two families of uplift histories are most compatible with the data. Both have limited initial topography with some topographic uplift and continental tilting starting in the east at ~95 Ma. In one acceptable scenario, nearly all of the topography, ~1400 m, is created at this time with little Cenozoic uplift. In the other acceptable scenario, only ~500 m of uplift occurs in the mid-Cretaceous with another ~850 m of uplift in the mid-Cenozoic. The two model scenarios have different geodynamic implications, which in the future could be evaluated by direct comparison between geodynamic and landscape model predictions.

In contrast to most seagrass meadows where seawater carbonate chemistry generally shows strong diel variations with a higher pH during the daytime and a lower pH during nighttime due to the alternation in photosynthesis and respiration, the seagrass meadows of the inner lagoon on Dongsha Island had a unique diel pattern with an extremely high pH across a diel cycle. We suggest that this distinct diel pattern in pH was a result of a combination of total alkalinity (TA) production through the coupling of aerobic/anaerobic respiration and carbonate dissolution in the sediments and dissolved inorganic carbon consumption through the high productivity of seagrasses in overlying seawaters. The confinement of the semienclosed inner lagoon may hamper water exchange and seagrass detritus export to the adjacent open ocean, which may provide an ideal scenario for sedimentary TA production and accumulation, thereby forming a strong capacity for seagrass meadows to buffer ocean acidification.

The planetary boundary layer (PBL) is the main region for the exchange of matter, momentum, and energy between land and atmosphere. The transport processes in the PBL determine the distribution of temperature, water vapour, wind speed and other physical quantities and are very important for the simulation of the physical characteristics of the meteorology. Based on the two non-local (YSU, ACM2) and two local closure PBL schemes (MYJ, MYNN) in the Weather Research and Forecasting (WRF) model, seasonal and daily cycles of meteorological variables over the Yangtze River Delta (YRD) region are investigated. It is shown that all four PBL schemes overestimate 10-m wind speed and 2-m temperature, while underestimate relative humidity. Inter-comparisons among the different PBL schemes show that the MYNN scheme results in closer match of 2-m temperature and 10-m wind speed to surface observations in summer, while the MYJ scheme shows the smallest bias of 2-m temperature and relative humidity in winter. Compared to the observed PBL height obtained from a micro-pulse lidar system, the MYNN scheme exhibits lowest mean bias while the ACM2 scheme shows the highest correlation. It is also found that there is a varying degree of sensitivity of the PBL height in winter and summer, respectively; a best-performing PBL scheme should be chosen under different seasons to predict various meteorological conditions over complicated topography like the YRD region.

Nowadays, it is so important in saving our economic activity and evading the disasters caused by terrestrial electromagnetic effects to predict both temporal and spatial scales of the geomagnetic disturbances based on in-situ solar wind observations. Recently, Neural Network (NN) is one of the notable techniques for the predictions of the magnetospheric activities. However, NN has a problem referred to as ‘black box’, which is difficult to extract which solar wind parameters are the most important for prediction. In this study, we examine a significant relationship between Kp index, which represents the magnetospheric activity, and the solar wind conditions based on an interpretable neural network: ‘Potential Learning (PL)’. A feature of the PL is to make a network that can understand the input variables by learning the “input potentialities”, which are indices calculated using the variances of the solar wind parameters as input variables. In this study, we investigate the magnetospheric activity profile when the Interplanetary Magnetic Field (IMF) oriented southward (Bz < 0). As the input solar wind data, we utilize the two components of the magnetic field (Bx, By) in GSE, and solar wind flow speed, and number density during 20 years between 1999 and 2018. Furthermore, we divide the associated values of Kp into two groups (targets): ‘Kp = 6- to 9 (positive target)’ and ‘Kp = 0 to 1+ (negative target)’. Because the data number of positive target was smaller than that of negative target, the negative target samples are randomly selected so that the data numbers of both targets become equal. Based on the PL neural network, we obtain two important results; 1) the solar wind plasma flow speed might have the most influential in the increase of the Kp index, and 2) as the secondary influential parameter for the Kp increase, the solar wind proton density is considered. In the presentation, we will discuss feasibility of the application to the prediction of the magnetospheric activity based on the solar wind parameters.

Application of apatite (U-Th)/He thermochronology has been hindered by incomplete understanding of single-grain age dispersion often displayed by samples, particularly those from older, slowly cooled settings. To assess the capability of continuous ramped heating (CRH) to explain dispersion, we performed a study on an apatite suite from Cathedral Rocks in the Transantarctic Mountains (TAM) that have high age dispersion. Examining 132 apatite grains from a total of six samples, we confirmed earlier apatite (U-Th)/He results showing that measured AHe ages have at least three-fold intra-sample dispersion with no obvious relationships between ages and effective uranium concentration (eU) or grain size. CRH results on these apatites yielded two groups. Those with younger ages, characterized by single-peak incremental 4He gas-release curves, displayed simple volume diffusion behavior. In contrast, grains with older ages generally show anomalous gas release in the form of sharp spikes and / or extended gas-release at high temperatures (i.e., >= 800 °C). Well-behaved apatites still show considerable age dispersion that exceeds what grain size, radiation damage, and analytical uncertainty can explain, but this dispersion appears to be related to variations in 4He diffusion kinetics. The screened AHe ages from well-behaved younger apatite grains together with kinetic information from these grains suggest that the sampled region experienced slow cooling prior to rapid cooling (rock exhumation) beginning ca. 35 Ma. This interpretation is consistent with other studies indicative of an increase in exhumation rates at this time, possibly related to the initiation of glaciation at the Eocene-Oligocene climate transition. An attempt to correct anomalous older apatite ages by simply removing extraneous gas-release components is proposed yielded some ages that are too young for the samples’ geologic setting, suggesting that the factors that lead to anomalous laboratory release behavior can impact both the expected radiogenic component as well as those that are extraneous. From our observations we conclude that: (1) CRH analysis can serve as a routine screening tool for AHe dating and offers opportunities to reveal first-order kinetic variations; (2) model-dependent age correction may be possible but would require some means of estimating the broad proportions of 4He components incorporated into grains before and after closure to diffusion, and (3) interpretation of highly dispersed AHe ages requires assessment of individual-grain diffusion kinetics beyond that predicted by radiation-damage models. We also infer that many apatite grains contain imperfections of varying kinds that contribute significantly to kinetic variability beyond that associated with radiation damage.

The impacts of solar eclipses on the ionosphere-thermosphere system particularly the composition, density, and transport are studied using numerical simulation and subsequent model-data comparison. We introduce a model of a solar eclipse mask (shadow) at Extreme Ultra Violet (EUV) wavelengths that computes the corresponding shadowing as a function of space, time, and wavelength of the input solar image. The current model includes interfaces for Solar Dynamics Observatory (SDO) and Geostationary Operational Environmental Satellites (GOES) EUV telescopes providing solar images at nine different wavelengths. We show the significance of the EUV eclipse shadow spatial variability and that it varies significantly with wavelength owing to the highly variable solar coronal emissions. We demonstrate geometrical differences between the EUV eclipse shadow compared to a geometrically symmetric simplification revealing changes in occultation vary $\pm$20\%. The EUV eclipse mask is validated with in-situ solar flux measurements by the PROBA2/LYRA instrument suite showing the model captures the morphology and amplitudes of transient variability while the modeled gradients are slower. The effects of spatially EUV eclipse masks are investigated with Global Ionosphere Thermosphere Model (GITM) for the 21 August 2017 eclipse. The results reveal that the modeled EUV eclipse mask, in comparison with the geometrically symmetric approximation, causes changes in the Total Electron Content (TEC) in order of $\pm$20\%, 5-20\% in F-region plasma drift, and 20-30\% in F-region neutral winds.

Due to the lower ionospheric thermal pressure and existence of the crustal magnetism at Mars, the Martian ionopause is expected to behave differently from the ionopause at Venus. We study the solar wind interaction and pressure balance at the ionopause of Mars using both in situ and remote sounding measurements from the MARSIS (Mars Advanced Radar for Subsurface and Ionosphere Sounding) instrument on the Mars Express orbiter. We show that the magnetic pressure usually dominates the thermal pressure to hold off the solar wind in the ionopause at Mars, with only 13% unmagnetized ionopauses observed over a 11-year period. We also find that the ionopause altitude decreases as the normal component of the solar wind dynamic pressure increases. Moreover, our results show that the ionopause thickness at Mars is mainly determined by the ion gyromotion and equivalent to about 5.7 ion gyroradii.

The observation that individual volcanic centres have their own eruption frequencies has been known for a long time but is as yet poorly understood. The key to a better understanding of the mechanisms controlling the eruption frequency comes from integrating accurate geochronology and geochemical data with numerical models. In many silicic volcanic systems, the eruption frequency is studied for short timescales of <1 Ma. Here, we combine two published numerical models to improve our understanding of the eruption frequency in a long-lived (>3 Ma) felsic magmatic system, the Milos volcanic field. From these two models, we interpret the time intervals between magma pulses into the subvolcanic reservoir (ti), the rates of magma supply (Qav) and chamber growth rates (Gmc) as the key parameters controlling the eruption frequency. During the time intervals of 1.5-1.04 Ma and 0.97-0.63 Ma the ti is longer than 500 years and the volcanic quiescence periods are longer than 350 ka. Furthermore, these periods are characterized by low values for Qav (≤ 0.001 km3·yr-1) and for Gmc (<0.0008 km3·yr-1). In contrast, during the time intervals of 3.3-1.5 Ma and 0.60-0.06 Ma, the ti is shorter (<0.5 ka) and the values for Qav (> 0.001 km3·yr-1) and for Gmc (> 0.001 km3·yr-1) are higher corresponding to frequent eruptions. The parameters ti, Qav, and Gmc appear to determine the eruption frequency of a volcanic system. Changes in one or more of these three parameters of the Milos volcanic field correlate with changes in the tectonic stress field.

While liquid environments with high salt content are of broad interest to the Earth and Planetary Science communities, instruments face challenges in detecting organics in hypersaline samples due to the effects of salts. Therefore, technology to desalt samples before analysis by these instruments would be enabling for liquid sampling on missions to Mars or ocean worlds. Electrodialysis (ED) removes salt from aqueous solutions by applying an electric potential across a series of ion-selective membranes, and is demonstrated to retain a significant percentage of dissolved organic molecules (DOM) in marine samples. However, current electrodialysis systems used for DOM recovery are too large for deployment on missions or for use in terrestrial fieldwork. Here we present the design and evaluation of the Minature Robotic Electrodialysis (MR ED) system, which is approximately 1/20th the size of heritage instruments and processes as little as 50 mL of sample at a time. We present tests of the instrument efficiency and DOM recovery using lab-created solutions as well as natural samples taken from an estuary of the Skidaway River (Savannah, GA) and from South Bay Saltworks (San Diego, CA). Our results show that the MR ED system removed 97-99% of the salts in most samples, with an average DOC recovery range from 53 to 77%, achieving similar capability to tabletop instruments. This work both demonstrates MR ED as a possible field instrument and increases the technology readiness level of miniaturized electrodialysis systems for future missions.

Geostationary satellites observe the earth surface and atmosphere with a short repeat time which can thus provide aerosol parameters with high temporal resolution. Due to the limited information content in satellite data, and the coupling between the signals received from the surface and the atmosphere, the accurate retrieval of multiple aerosol parameters over land is difficult. Here we propose a Neural Network AEROsol retrieval framework for Geostationary satellite (NNAeroG) which can potentially be applied to different instruments to retrieve various aerosol parameters. NNAeroG was applied for aerosol retrieval using data from the Advanced Himawari Imager on Himawari-8 and the results were evaluated versus independent ground-based sun photometer reference data. The retrieved Aerosol Optical Depth, Ångström Exponent and Fine Mode Fraction are significantly better than the official JAXA aerosol products. The use of thermal infrared bands is meaningful for aerosol retrieval.

Vast areas of boreal peatlands are impacted by linear disturbances known as seismic lines. Tree removal and ground disturbance alter vegetation communities and are expected to change ecosystem functioning. We investigate seismic line disturbances on peatland plant community composition and phenological patterns using readily available digital photography at a bog and a fen in Alberta, Canada. Our objectives were to: 1) compare the understory vegetation on seismic lines with those in adjacent undisturbed peatlands using two phenological metrics (green and red chromatic coordinates); 2) evaluate if vegetation greenness is directly related to vegetation community composition, and 3) determine whether plot-scale greenness predicts plant productivity. We found that disturbed peatlands have an earlier seasonal peak (maximum greenness) compared to undisturbed areas, and vegetation communities had a stronger relationship to greenness and gross primary production (GPP) at disturbed sites relative to undisturbed sites. This change in understory vegetation results in greater CO2; uptake in disturbed sites. We demonstrate an easy-to-use application of digital photography that successfully quantifies phenological changes in boreal peatland vegetation. This non-destructive method for understanding vegetation phenology eliminated the need for fixed infrastructure and allowed us to sample more plots and study sites while allowing for repeated measures in the future. As boreal landscapes continue to be disturbed by linear disturbances, understanding the magnitude and mechanisms of vegetation and phenology changes is the first step toward predicting carbon cycling changes across broad spatial scales.

Air pollution levels are uneven within cities, contributing to persistent health disparities between neighborhoods and population sub-groups. Highly spatially resolved information on pollution levels and disease rates is necessary to characterize inequities in air pollution exposure and related health We leverage recent advances in deriving surface pollution levels from satellite remote sensing and granular data in disease rates for one city, Washington, DC, to assess intra-urban heterogeneity in fine particulate matter (PM5)- attributable mortality and We estimate PM2.5-attributable cases of all-cause mortality, chronic obstructive pulmonary disease, ischaemic heart disease, lung cancer, stroke, and asthma emergency department (ED) visits using epidemiologically-derived health impact Data inputs include satellite-derived annual mean surface PM5 concentrations; age-resolved population estimates; and statistical neighborhood-, zip code- and ward-scale disease counts. We find that PM5 concentrations and associated health burdens have decreased in DC between 2000 and 2018, from approximately 240 to 120 cause-specific deaths and from 40 to 30 asthma ED visits per year (between 2014 and 2018). However, remaining PM5-attributable health risks are unevenly and inequitably distributed across the Higher PM2.5-attributable disease burdens were found in neighborhoods with larger proportions of people of color, lower household income, and lower educational Our study adds to the growing body of literature documenting the inequity in air pollution exposure levels and pollution health risks between population sub-groups, and highlights the need for both high-resolution disease rates and concentration estimates for understanding intra-urban disparities in air pollution-related health risks.

Clouds over tropical oceans are an important factor in Earth’s response to increased greenhouse gas concentrations, but their representation in climate models is challenging due to the small-scale nature of the involved convective processes. We perform two 4-year-long simulations at kilometer-resolution (3.3 km horizontal grid spacing) with the limited-area model COSMO over the tropical Atlantic on a 9000x7000 km2 domain: A control simulation under current climate conditions driven by the ERA5 reanalysis, and a climate change scenario simulation using the Pseudo-Global Warming (PGW) approach. We compare these results to the changes projected in the CMIP6 scenario ensemble. We find a good representation of the annual cycle of albedo, in particular for trade-wind clouds, even compared to the ERA5 reanalysis. Also, the vertical structure and annual cycle of the marine intertropical convergence zone (ITCZ) is accurately simulated, and the simulation does not suffer from the double ITCZ problem commonly present in global climate models (GCMs). The ITCZ responds to warming through a vertical extension and intensification primarily at high levels, as well as a slight southward extension of the annual mean ITCZ, while the narrowing typically seen in GCMs is not visible.

Southeast Asia’s extensive tropical peatlands account for a significant proportion of the global riverine dissolved organic carbon (DOC) flux to the ocean. Peat-derived DOC is rich in polyphenolic compounds, the microbial degradation of which is thought to rely on extracellular phenol oxidases. Despite substantial interest in the biogeochemical fate of terrigenous DOC (tDOC), few studies have quantified phenol oxidase activity in aquatic environments, and microbial remineralization rates of tDOC have never been measured in Southeast Asia. Here, we assess the potential for using phenol oxidase assays as a proxy of tDOC biodegradation across peat-draining rivers and coastal waters of Sarawak, Borneo, and report experimental measurements of microbial tDOC remineralization rates from this region. We show first that phenol oxidase assays in aquatic samples are problematic because of the rapid, pH-dependent auto-oxidation of the assay substrate. Our field measurements of phenol oxidase activity detected only substrate auto-oxidation, suggesting that real phenol oxidase activity was low or absent. Second, we report that peatland tDOC, collected from one of the few remaining intact peatlands on Borneo, showed at most very limited biodegradation (0–6% loss of DOC, and 0–12% loss of coloured dissolved organic matter) during several 56-day incubation experiments at in-situ temperature of ~30°C, even when diluted with seawater or amended with nutrients. Our results suggest that direct microbial respiration is perhaps not a major pathway for peatland tDOC remineralization in Southeast Asia, and that photo-oxidation is more likely to control the fate of this carbon.

Traditional crop irrigation relies on farmers’ knowledge on plant, soil, and weather. Irrigation system is one of the key facilities in Nebraska to supply sufficient water resource to farming activities. However, in large scale farming, it is not rare to see plant get over irrigated while the marginal economic benefit of irrigation decreases significantly. The WaterSmart system combines various data sources to provide irrigation guidance to help farmers making better irrigation decision. To support the WaterSmart system, a semantic irrigation ontology is developed to understand these Agro-Geoinformatics data with local planting knowledge such as water usage during different crop stages. Local knowledge on crop irrigation has already been studied and published by Institute of Agriculture and Natural Resources, Nebraska Extension at the University of Nebraska-Lincoln. The ontology is built using Webprotégé with using HermiT as the reasoner. The ontology focuses on two main crops in Nebraska: corn and soybean. Final product is released on GitHub repository and registered with w3id thru persistent uniform resource locator (PURL). All software and tools were used to develop the ontology are open source. The ontology is used to represent irrigation knowledge and host concepts in the irrigation decision making portal.

Afforestation has been suggested as an effective ecological engineering approach for carbon sequestration and environmental benefits. However, the impact of afforestation on soil inorganic carbon (SIC) is less clear and sometimes controversial. Here, we conducted a field campaign, with 2346 soil profiles from 619 afforested plots and 163 control plots, to investigate the relative and absolute changes of SIC between afforested and corresponding control plots in northern China. We found positive responses of SIC to afforestation in acidic soils, where afforestation increased soil pH. In contrast, in alkaline soil, afforestation caused soil acidification and thus negative SIC responses. Fitting a structure equation model (SEM) confirmed that afforestation-induced soil pH change (ΔpH) was the most significant factor regulated SIC responses to afforestation. In particular, we observed stronger SIC sensitivity to pH change in arid areas, where both soil pH and SIC stocks were high. Other factors indirectly affected SIC responses to afforestation through modulating soil pH and soil organic carbon (SOC) dynamics. Afforestation-induced SIC changes also varied considerably among different planted tree species and across different soil depths. Specifically, in Pinus sylvestris var. mongholica, Pinus tabuliformis and Populus spp. plantations, changes of SIC were large enough to be comparable to that of SOC. Our finding provides a data-based comprehensive understanding on the impact of afforestation on SIC and its underlying mechanisms. With increased uses of afforestation and reforestation as potential nature-based climate solutions, decisions need to consider potential associated SIC changes, especially in SIC-rich areas.

Sea Surface Salinity (SSS) can change as a result of surface freshwater forcing (FWF), or internal ocean processes such as upwelling or advection. At the seasonal scale, SSS should follow FWF by ¼ cycle, or 3 months, if FWF is the primary process controlling it at the seasonal scale. In this paper we compare the phase relationship between SSS and FWF (i.e. evaporation minus precipitation over mixed layer depth) over the global (non-Arctic) ocean using in situ SSS and satellite evaporation and precipitation. We find that instead of the expected 3 month delay between SSS and FWF, the delay is mostly closer to 1-2 months, with SSS peaking too soon relative to FWF. We then compute monthly vertical entrainment and horizontal advection terms of the upper ocean salinity balance equation and add their contributions to the phase of the FWF. The addition of these processes to the seasonal upper ocean salinity balance brings the phase difference between SSS and the forcing processes closer to the expected value. We do a similar computation with the amplitude of the seasonal SSS and the forcing terms, with less definitive results. The results of this study highlight the important role that ocean processes play in the global freshwater cycle at the seasonal scale.