This folder contains the input data for the WaterTAP3 model that was used for the eight NAWI (National Alliance for Water Innovation) source water baselines studies published in the Environmental Science and Technology special issue: Technology Baselines and Innovation Priorities for Water Treatment and Supply. There are also eight other separate DAMS submissions, one per source water, that include the model results for the published studies. In this data submission, all model inputs across the eight baselines are included. The data structure and content are described in a README.txt file. For more details on how to use the data in WaterTAP3 please refer to the model documentation and GitHub site found at "WaterTAP3 Github" linked in the submission resources.
Description: This folder contains the results for the WaterTAP3 model that was used for the eight NAWI (National Alliance for Water Innovation) baseline studies published in the Environmental Science and Technology special issue: Technology Baselines and Innovation Priorities for Water Treatment and Supply. The data structure and content are described in a README.txt file. For more details on how to use the data and interpret the results please refer to the model documentation and GitHub site linked in the submission.
COMBINE_CONC_A0_2016_without_DMS_AVG.tar – annual average model predicted concentrations without DMS chemistry COMBINE_CONC_A_2016_annual_AVG.tar – annual average model predicted concentrations with DMS chemistry GRIDCRO2D.108NHEMI2.44L.20060101.tar - file containing latitude and longitude of model grid-cell Model: The Community Multiscale Air Quality (CMAQv53) was used. It is available at https://www.epa.gov/cmaq. This dataset is associated with the following publication: Gantt, B., K. Foley, B. Henderson, H. Pye, K. Fahey, D. Kang, R. Mathur, J. Zhao, Y. Zhang, Q. Li, A. Saiz-Lopez, and G. Sarwar. Impact of dimethylsulfide chemistry on air quality over the Northern Hemisphere. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 244: 117961, (2020).