Low-cost measurement techniques to characterize the influence of home heating fuel on carbon monoxide in Navajo homes.

A large fraction of the global population relies on the inefficient combustion of solid fuels for cooking and home heating, resulting in household exposure to combustion byproducts. In the southwestern United States, unhealthy air quality has been observed in some homes that use solid fuels as a primary source of heat on the Navajo Nation. In order to better understand how home heating fuel choice can influence indoor air quality in this region, we used recently developed low-cost electrochemical sensors to measure carbon monoxide (CO) air mole fractions continuously inside and outside 41 homes in two communities on the Navajo Nation. Using low-cost sensors in this study, which don't require extensive training to operate, enabled collaboration with local Diné College students and faculty in the planning and implementation of home deployments. Households used natural gas, propane, pellets, wood, and/or coal for heating. We developed quantification methods that included uncertainty estimation for Alphasense CO-B4 sensors, for measurements both inside and outside homes. CO concentrations elevated above background were observed in homes in each heating fuel group, but the highest hourly concentrations were observed in wood and coal burning homes, some of which exceeded World Health Organization Guidelines on both an hourly and eight-hourly basis. In order to probe the many factors that can influence indoor pollutant concentrations, we developed and implemented methods that employ CO emission and decay time periods observed in homes during everyday activities to estimate air exchange rates as well as CO emission rates on the basis of a given well-mixed volume of air. The air quality measurement tools and methods demonstrated in this study can be readily extended to indoor air quality studies in other communities around the world to inform how home heating and cooking practices are influencing indoor air quality during normal daily activities.

Assessing a low-cost methane sensor quantification system for use in complex rural and urban environments.

Low-cost sensors have the potential to facilitate the exploration of air quality issues on new temporal and spatial scales. Here we evaluate a low-cost sensor quantification system for methane through its use in two different deployments. The first was a one-month deployment along the Colorado Front Range and included sites near active oil and gas operations in the Denver-Julesberg basin. The second deployment was in an urban Los Angeles neighborhood, subject to complex mixtures of air pollution sources including oil operations. Given its role as a potent greenhouse gas, new low-cost methods for detecting and monitoring methane may aid in protecting human and environmental health. In this paper, we assess a number of linear calibration models used to convert raw sensor signals into ppm concentration values. We also examine different choices that can be made during calibration and data processing, and explore cross-sensitivities that impact this sensor type. The results illustrate the accuracy of the Figaro TGS 2600 sensor when methane is quantified from raw signals using the techniques described. The results also demonstrate the value of these tools for examining air quality trends and events on small spatial and temporal scales as well as their ability to characterize an area - highlighting their potential to provide preliminary data that can inform more targeted measurements or supplement existing monitoring networks.