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Abstract This study examines the role of human dynamics within Geospatial Artificial Intelligence (GeoAI), highlighting its potential to reshape the geospatial research field. GeoAI, emerging from the confluence of geospatial technologies and artificial intelligence, is revolutionizing our comprehension of human-environmental interactions. This revolution is powered by large-scale models trained on extensive geospatial datasets, employing deep learning to analyze complex geospatial phenomena. Our findings highlight the synergy between human intelligence and AI. Particularly, the humans-as-sensors approach enhances the accuracy of geospatial data analysis by leveraging human-centric AI, while the evolving GeoAI landscape underscores the significance of human–robot interaction and the customization of GeoAI services to meet individual needs. The concept of mixed-experts GeoAI, integrating human expertise with AI, plays a crucial role in conducting sophisticated data analyses, ensuring that human insights remain at the forefront of this field. This paper also tackles ethical issues such as privacy and bias, which are pivotal for the ethical application of GeoAI. By exploring these human-centric considerations, we discuss how the collaborations between humans and AI transform the future of work at the human-technology frontier and redefine the role of AI in geospatial contexts. 

The ocean has absorbed anthropogenic carbon dioxide (C_anthro) from the atmosphere and played an important role in mitigating global warming. However, how much C_anthrois accumulated in coastal oceans and where it comes from have rarely been addressed with observational data. Here, we use a high-quality carbonate dataset (1996–2018) in the U.S. East Coast to address these questions. Our work shows that the offshore slope waters have the highest C_anthroaccumulation changes (ΔC_anthro) consistent with water mass age and properties. From offshore to nearshore, ΔC_anthrodecreases with salinity to near zero in the subsurface, indicating no net increase in the export of C_anthrofrom estuaries and wetlands. Excesses over the conservative mixing baseline also reveal an uptake of C_anthrofrom the atmosphere within the shelf. Our analysis suggests that the continental shelf exports most of its absorbed C_anthrofrom the atmosphere to the open ocean and acts as an essential pathway for global ocean C_anthrostorage and acidification. 

Abstract Dissolved inorganic carbon (DIC) and its stable carbon isotope (δ¹³C‐DIC) are valuable parameters for studying the aquatic carbon cycle and quantifying ocean anthropogenic carbon accumulation rates. However, the potential of this coupled pair is underexploited as only 15% or less of cruise samples have been analyzed forδ¹³C‐DIC because the traditional isotope analysis is labor‐intensive and restricted to onshore laboratories. Here, we improved the analytical precision and reported the protocol of an automated, efficient, and high‐precision method for ship‐based DIC andδ¹³C‐DIC analysis based on cavity ring‐down spectroscopy (CRDS). We also introduced a set of stable in‐house standards to ensure accurate and consistent DIC andδ¹³C‐DIC measurements, especially on prolonged cruises. With this method, we analyzed over 1600 discrete seawater samples over a 40‐d cruise along the North American eastern ocean margin in summer 2022, representing the first effort to collect a large dataset ofδ¹³C‐DIC onboard of any oceanographic expedition. We evaluated the method's uncertainty, which was 1.2 μmol kg⁻¹for the DIC concentration and 0.03‰ for theδ¹³C‐DIC value (1σ). An interlaboratory comparison of onboard DIC concentration analysis revealed an average offset of 2.0 ± 3.8 μmol kg⁻¹between CRDS and the coulometry‐based results. The cross‐validation ofδ¹³C‐DIC in the deep‐ocean data exhibited a mean difference of only −0.03‰ ± 0.07‰, emphasizing the consistency with historical data. Potential applications in aquatic biogeochemistry are discussed. 

Renewable 1,3-butadiene (1,3-BD, C4H6) was synthesized from the tandem decyclization and dehydration of biomass-derived tetrahydrofuran (THF) on weak Brønsted acid zeolite catalysts. 1,3-BD is a highly solicited monomer for the synthesis of rubbers and elastomers. Selective conversion of THF to 1,3-BD was recently measured on phosphorus-modified siliceous zeolites (P-zeosils) at both high and low space velocities, albeit with low per-site catalytic activity. In this work, we combined kinetic analyses and QM/MM calculations to evaluate the interaction of THF with the various Brønsted acid sites (BAS) of Boric (B), Phosphoric (P), and Sulfuric (S) acid modified silicalite-1 catalysts toward a dehydra-decyclization pathway to form 1,3-BD. Detailed kinetic measurements revealed that all three catalysts exhibited high selectivity to 1,3-BD ca. 64–96% in the order of S-MFI > P-MFI > B-MFI at a given temperature (360 °C). Notably, the S-MFI maintained a selectivity >90% for all evaluated process conditions. The computational results suggested that the nature of the Brønsted acid sites and the adsorption energetics (relative THF-acid site interaction energies) are distinct in each catalyst. Additionally, the protonation of THF can be improved with the addition of a water molecule acting as a proton shuttle, particularly in S-MFI. Overall, S-containing zeosils exhibited the ability to control reaction pathways and product distribution in dehydra-decyclization chemistry optimization within microporous zeolites, providing another alternative weak-acid catalytic material. 

Here, we explicitly define a half-cell reaction approach for pH calculation using the electrode couple comprised of the solid-state chloride ion-selective electrode (Cl-ISE) as the reference electrode and the hydrogen ionselective ion-sensitive field effect transistor (ISFET) of the Honeywell Durafet as the hydrogen ion (H+)-sensitive measuring or working electrode. This new approach splits and isolates the independent responses of the Cl-ISE to the chloride ion (Cl−) (and salinity) and the ISFET to H+ (and pH), and calculates pH directly on the total scale (pHEXT total) in molinity (mol (kg-soln)−1) concentration units. We further apply and compare pHEXT total calculated using the half-cell and the existing complete cell reaction (defined by Martz et al. (2010)) approaches using measurements from two SeapHOx sensors deployed in a test tank. Salinity (on the Practical Salinity Scale) and pH oscillated between 1 and 31 and 6.9 and 8.1, respectively, over a six-day period. In contrast to established Sensor Best Practices, we employ a new calibration method where the calibration of raw pH sensor timeseries are split out as needed according to salinity. When doing this, pHEXT total had root-mean squared errors ranging between ±0.0026 and ±0.0168 pH calculated using both reaction approaches relative to pHtotal of the discrete bottle samples (pHdisc total). Our results further demonstrate the rapid response of the Cl-ISE reference to variable salinity with changes up to ±12 (30 min)−1. Final calculated pHEXT total were ≤±0.012 pH when compared to pHdisc total following salinity dilution or concentration. These results are notably in contrast to those of the few in situ field deployments over similar environmental conditions that demonstrated pHEXT total calculated using the Cl-ISE as the reference electrode had larger uncertainty in nearshore waters. Therefore, additional work beyond the correction of variable temperature and salinity conditions in pH calculation using the Cl-ISE is needed to examine the effects of other external stimuli on in situ electrode response. Furthermore, whereas past work has focused on in situ reference electrode response, greater scrutiny of the ISFET as the H+-sensitive measuring electrode for pH measurement in natural waters is also needed.