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Dataset results
4 results for “Atlanta, Georgia”
Dissolved organic carbon concentrations for seasonal synoptic sampling of 93 urban streams in Atlanta, Georgia (USA) from 2021-2022
This dataset contains dissolved organic carbon concentrations from surface water samples collected at 93 first- to fifth-order streams in the Altamaha, Chattahoochee, and Flint Watersheds draining a gradient of urban land use in the greater Atlanta, Georgia metropolitan area. Samples were collected four times (September 2021, December 2021, March 2022, and July 2022) to capture spatial and seasonal variation in DOC concentrations. Filtered stream samples were analyzed for dissolved organic carbon concentration. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Dissolved organic matter characterization for seasonal synoptic sampling of 93 urban streams in Atlanta, Georgia (USA) from 2021-2022
This dataset contains dissolved organic matter (DOM) characteristics from surface water samples collected at 93 first- to fifth-order streams in the Altamaha, Chattahoochee, and Flint Watersheds draining a gradient of urban land use in the greater Atlanta, Georgia metropolitan area. Samples were collected four times (September 2021, December 2021, March 2022, and July 2022) to capture spatial and seasonal variation in DOM characteristics. Fluorescent optical properties were measured on filtered water samples to understand the chemical composition of DOM. Excitation-Emission Matrices (EEMs) were measured using a Horiba Aqualog spectrometer. DOM characteristics were quantified using both standard fluorescence and absorbance metrics as well as through parallel factor (PARAFAC) analysis. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Field data for seasonal synoptic sampling of 93 urban streams in Atlanta, Georgia (USA), 2021-2022
This dataset contains field measurements taken during water sampling from 93 first- to fifth-order streams in the Altamaha, Chattahoochee, and Flint Watersheds draining a gradient of urban land use in the greater Atlanta, Georgia metropolitan area. Field collection took place during four synoptic sampling events(September 2021, December 2021, March 2022, and July 2022) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH, ORP). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in separate datasets. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
A Modeling Framework for Near-Road Population Exposure to Traffic-Related PM2.5 and Environmental Equity Analysis: A Case Study in Atlanta, Georgia
<p>This is the dataset for the NCST project <em>"A Modeling Framework for Near-Road Population Exposure to Traffic-Related PM2.5 and Environmental Equity Analysis: A Case Study in Atlanta, Georgia"</em> by the Georgia Tech research team.</p> <p> </p> <p>Here is the abstract of the research: </p> <p>In this study, a modeling framework for population exposure to traffic-related PM2.5 with high spatiotemporal resolution is proposed and applied to the I-575/I-75 Northwest Corridor (NWC) in Atlanta, GA, for environmental equity analysis. The analyses retrieved trip data from the Atlanta Regional Commission’s (ARC) Activity-Based Model 2020 (ABM2020), after implementing path retention algorithms (Zhao, et al., 2019) to generate individual travel paths for more than 20 million predicted vehicle trips. Emission rates for each link were retrieved from MOVES-Matrix given the ABM link speed and facility type, the ARC’s county-level fleet composition data, and regional fuel properties and I&M program parameters. High-resolution downwind concentration profiles were predicted using EPA’s AERMOD microscale dispersion model with AERMET meteorology profiles for a huge array of receptors. Trip-end locations were derived from the ABM trip data, and the on-road trajectories for each person-trip (vehicle trace data) were derived from the travel paths through network. ABM synthetic household and person data were used in demographic assessment, and linked to representative household latitude and longitude locations in the Epsilon 2019 household demographic dataset. Individual exposure to traffic-related PM2.5 in time and space (average hourly concentration) was assessed by overlaying the second-by-second person location profiles (for 24 hours) against the hourly predicted PM2.5 concentration profiles. The analyses summarize the results across 16 demographic groups and the aggregate population exposure are compared to assess potential impact differences across demographics. High-income households in the corridor were exposed to less traffic-related air pollution as they tended to live further from the freeways. The analyses did not reveal large disproportionate negative impacts on low income groups along this specific corridor, but lager disproportionate negative impacts are expected elsewhere in the metro area due to the spatial clustering of income groups along other corridors. Overall, the research demonstrates the applicability of the modeling framework and describes how the various elements (e.g., link screening, dispersion modeling, path tracing, etc.) are optimized on the supercomputing cluster.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.