Treating drinking water, municipal wastewater, and industrial wastewater in the United States (U.S.) consumes energy and chemicals (1-3). Generating energy and manufacturing chemicals produces emissions of criteria air pollutants (e.g., nitrous oxides, sulfur dioxide, and particulate matter) and greenhouse gasses (e.g., CO<sub>2</sub>). These emissions have their own risks and human health, environmental, and climate (HEC) damages associated with them, and so water treatment sets up a risk-risk trade-off. The Water Associated Health and Environmental Air Damages (Water AHEAD) Tool is designed to quantify these trade-offs. An overview of the Water AHEAD Tool is shown in Figure [1] below.
![Fig 1. Water AHEAD Model Overview][1]
Fig 1. Water AHEAD Model Overview
To build this tool, we created an inventory of energy (thermal and electrical) and chemical inputs into water treatment processes from a variety of literature sources. To see our literature sources, see the references in (1-3) or check the Mendeley folder associated with this OSF project. The model takes information on a specified treatment train or new unit process and builds an inventory of energy & chemical usage. Using information on the electricity and chemical manufacturing sectors, the model converts this inventory of energy & chemical inputs into information on the embedded air emissions and emission locations. The model then calculates the total HEC damages using AP2 (4) and the Social Cost of Carbon (5).
After the model was developed and applied to understand air-water risk trade-offs in drinking water (1) and industrial wastewater (3) and opportunities to mitigate these risk trade-offs in municipal wastewater (2), the WE3 Lab developed a graphical user interface for the Water AHEAD Tool. The tool allows the users to use our model without having to run the Python code. To use the model, the user needs to enter basic information about the water treatment facility, where the facility sources its electricity and chemicals, and what processes are installed to treat water. Finally, the model outputs the energy and chemical consumed, the embedded air emissions associated with generating that energy and manufacturing those chemicals, and the HEC damages.
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### References ###
1. Gingerich, D. B.; Mauter, M. S. Air Emissions Damages from Municipal Drinking Water Treatment under Current and Proposed Regulatory Standards. Environ. Sci. Technol. 2017, 51 (18), 10299–10306.
2. Gingerich, D. B.; Mauter, M. S. Air Emission Reduction Benefits of Biogas Electricity Generation at Municipal Wastewater Treatment Plants. Environ. Sci. Technol. 2018, 52 (3), 1633–1643.
3. Gingerich, D.; Sun, X.; Behrer, A. P.; Azevedo, I. M. L.; Mauter, M. S. Spatially resolved air-water emissions tradeoffs improve regulatory impact analyses for electricity generation. Proc. Natl. Acad. Sci. 2017.
4. Muller, N. Z. Using index numbers for deflation in environmental accounting. Environ. Dev. Econ. 2014, 19 (4), 466–486.
5. Interagency Working Group on Social Cost of Carbon. Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis; Washington, D.C., 2015.
[1]: https://ndownloader.figshare.com/files/19699181/preview/19699181/preview.jpg
