Integrated System and Predictive Model to Assess Air Quality and Rapidly Pinpoint Emerging Sources

Natural and anthropogenic sources of pollution, according to several studies, contribute to in excess of 6 million premature deaths per year worldwide, with more than 200,000 in the US alone. The high number of deaths caused by air pollution shows the importance of making people aware of air quality at their location. Five of the components of greatest concern are listed on the National Ambient Air Quality Standard as part of the Clean Air Act by EPA: CO, NO2, O3, SO2 and PM2.5. In addition to contributing to climate change, these gases and particulate are harmful for humans and attack the respiratory system, penetrating deep into the respiratory system and damages lung tissue and the bronchial system causing pulmonary edema. Satellites are not able, on their own, to detect how high above the ground air pollution is. These systems provide an integrated measurement through the column of troposphere being measured, not readings at ground level. It is difficult to model the vertical distribution of gases and dust. Satellites are therefore often not very accurate in giving estimations for the concentrations of pollutants in the actual air humans breathe. AQ models and existing networks lack local resolution since air quality values are highly dependent on local topography and wind direction. The air quality can vary significantly over a few hundred meters in urban areas and around roads and industrial areas. Hyper-local monitoring would improve accuracy of exposure assessments and improve models. Therefore, we offer this proposal for a truly low-cost, reliable air quality system with integrated data from remote monitors and local sensor nodes.

The proposed data assimilation and predicitve mapping system directly support NASA's strategy for building the tools that humankind can use to meet new and emerging challenges. The proposed data analysis system will reduce NASA Earth Science and other remote and local data into an intuitive dashboard, or App, that provides health agencies and residents themselves to make aware decisions. The immediate focus is on improved resolution of the air quality data and readily accessible access to information to minimize exposure and health hazards. The model will be data source agnostic, however, so it can be readily adapted to other atmospheric modeling and source detection concerns including greenhouse gas emissions, wildfire detection and response. We expect initial markets to be primarily government agencies such as NASA, EPA and NOAA, larger community air quality groups as well as “early adopters”. Once the Model and AQ mapping are established, the market will expand to include small communities and suburbs, rural towns and even residential end users.

This is early/mid-stage (TRL 5) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.