To investigate the impacts of an energy efficiency retrofit, indoor air quality and resident health were evaluated at a low-income senior housing apartment complex in Phoenix, Arizona, before and after a green energy building renovation. Indoor and outdoor air quality sampling was carried out simultaneously with a questionnaire to characterize personal habits and general health of residents. Measured indoor formaldehyde levels before the building retrofit routinely exceeded reference exposure limits, but in the long-term follow-up sampling, indoor formaldehyde decreased for the entire study population by a statistically significant margin. Indoor PM levels were dominated by fine particles and showed a statistically significant decrease in the long-term follow-up sampling within certain resident subpopulations (i.e. residents who report smoking and residents who had lived longer at the apartment complex).

Low-cost air quality sensors (LCSs) have become more widespread due to their low cost and increased capabilities; however, to supplement more traditional air quality networks, the performance of these LCSs needs to be validated. This study focused on NO₂ measurements from eight Clarity Node-S sensors and used various environmental factors to calibrate the LCSs. To validate the calibration performance, we calculated the root-mean-square error (RMSE), mean absolute error (MAE), R², and slope compared to reference measurements. Raw results from six of these sensors were comparable to those reported for other NO₂ LCSs; however, two of the evaluated LCSs had RMSE values ~20 ppb higher than the other six LCSs. By applying a sensor-specific calibration that corrects for relative humidity, temperature, and ozone, this discrepancy was mitigated. In addition, this calibration improved the RMSE, MAE, R², and slope of all eight LCS compared to the raw data. It should be noted that relatively stable environmental conditions over the course of the LCS deployment period benefited calibration performance over time. These results demonstrate the importance of developing LCS calibration models for individual sensors that consider pertinent environmental factors.

A survey of key indoor air quality (IAQ) parameters and resident health was carried out in 72 apartments within a single low-income senior housing building in Phoenix, Arizona. Air sampling was carried out simultaneously with a questionnaire on personal habits and general health of residents. Mean PM₁₀ concentrations are 66±16, 58±13, and 24±3 μg/m³ and mean PM_2.5 concentrations are 62±16, 53±13, and 20±2 μg/m³ for the living room, kitchen, and outdoor balcony, respectively. Median PM₁₀ concentrations are 17, 18 and 17 μg/m³ and median PM_2.5 concentrations are 13, 14, and 13 μg/m³, respectively. The initial results indicate that increased indoor particle concentrations coincide with residents who report smoking cigarettes. Indoor formaldehyde concentrations revealed median levels of 36.9, 38.8, and 4.3 ppb in the living room, kitchen, and balcony, respectively. Results show that 36% of living room samples and 44% of kitchen samples exceeded the Health Canada REL for chronic exposure to formaldehyde (40 ppb). Associations between occupants’ behavior, self-reported health conditions, and IAQ are evaluated.

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NO_x) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO₂ monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O₃ values at the downwind sites were significantly correlated, ~0.27, to the morning NO₂ × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O₃ on smoke days was approximately 20% higher than on non-smoke days, however, the average NO₂ concentration multiplied by estimated photolysis rate (NO₂ × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO₂ ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO₂ ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O₃ production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O₃ attainment in the county.