Current methods for assessing exposure to extreme heat and air pollution depend mostly on readings from regulatory monitoring stations. We hypothesize that this does not accurately represent the different conditions people encounter in various microenvironments. This study integrates distributed outdoor networks, indoor monitors, and wearable personal devices to characterize exposures to heat and fine particulate matter (PM2.5) experienced by residents of low-income public housing in Elizabeth, New Jersey. We apply exceedance-based metrics to measure both the intensity and duration of exposures across different participant groups (youth, seniors, staff working for the housing authority and researchers). The results show clear heterogeneity: Seniors face the highest PM2.5 exposures, and youth show widely varying and often higher thermal exposures. Comparisons of wearable devices and local monitors with regulatory monitors show congruent thermal conditions but high local variation in PM2.5 values. These findings highlight major discrepancies between existing design assumptions and actual living conditions. The study concludes that HVAC engineering efforts, urban design methods, and public health measures should be guided by personal monitoring data to tackle differences in risk. Future research should connect personal sensor data with health outcomes and consider the combined health effects of extreme heat and air pollution.

Personal exposures to environmental stressors including extreme heat and air pollution vary widely depending on schedules and activities. This paper shares results of a city-scale project to build fixed indoor and outdoor sensor networks while also deploying mobile sensors. The network helps building occupants, building operators, and public officials to safely manage extreme heat and air pollution. The Exposure Duration Curve (EDC) concept is introduced to facilitate comparisons.

Heatwaves are known to result in negative health effects in general and especially in vulnerable populations. At the same time, the effect of high outdoor temperatures on indoor air quality is largely unknown. To start filling this knowledge gap, we recruited 24 seniors from 3 low-income housing sites in Elizabeth, NJ, to participate in a study, during which we deployed consumer-grade sensors in their apartments to monitor airborne particulate matter (PM2.5) and air temperature. Additionally, one empty apartment, used as a control, and an outdoor station were set up with the same type of sensors. Measurements were performed from July to September 2017. During this period, there were seven days when outdoor temperatures exceeded 90 degrees F (32 degrees C), our criterion for heatwave days.First, we found that the average hourly indoor PM2.5 levels varied among apartments and were greatly affected by the presence of smokers. During non-heatwave days, in apartments without smokers, the hourly median PM2.5 concentrations ranged from 4 mu g/m3 to 12 mu g/m3, while in apartments with smokers, the hourly median PM2.5 concentrations ranged from 14 mu g/m3 to 90 mu g/m3. More importantly, the indoor PM2.5 levels were higher (p < 0.05) during heatwave days. A statistically significant increase was observed for all apartments, regardless of the building site, presence of smokers, or type of air conditioning. Moreover, since human activity contributes to indoor PM2.5, we separated the data into an active period (6:00 a.m. to 10:00 p.m.) and the rest period (10:00 p. m. to the next day 6:00 a.m.); the PM2.5 increase during heatwaves was statistically significantly higher for both periods.Overall, our data suggest that higher ambient temperatures could be an important factor for indoor PM2.5 exposures. Future investigations should consider several exposure-modifying factors, such as the use of windows and AC, for a more accurate assessment of outdoor conditions affecting indoor exposures.

Exposure to bioaerosols has been implicated in adverse respiratory symptoms, infectious diseases, and bioterrorism. Although these particles have been measured within residential and occupational settings in multiple studies, the deposition of bioaerosol particles within the human respiratory system has been only minimally explored. This paper uses real-world environmental measurement data of total fungal spores using Air-o-Cell cassettes in 16 different apartments and residents' physiological data in those apartments to predict respiratory deposition of the spores. The airborne spore concentrations were measured during the spring, summer, and fall. The respiratory deposition of five most prevalent spore genera-Ascospores, Aspergillus, Basidiospores, Cladosporium, and Myxomycetes-was predicted using three empirical models: the Multiple Path Particle Dosimetry model, using both the Yeh and age-specific versions, and the Bioaerosol Adaptation of the International Committee on Radiological Protection's Lung deposition model. The predicted total deposited number of spores was highest for Ascospores and Cladosporium. While the majority of spores deposit were in the extrathoracic region, there is a significant deposition for both Aspergillus and Cladosporium in the alveolar region, potentially leading to the development of aspergillosis or allergic asthma. Although the dose-response relationship is unknown, the estimate of the actual spore deposition could be the first step in determining such a relationship.

Bioaerosol concentrations in residential buildings located in the Northeastern US have not been widely studied. Here, in 2011-2015, we studied the presence and seasonal variability of culturable fungi and bacteria in three multi-family apartment buildings and correlated the bioaerosol concentrations with building ventilation system types and environmental parameters. A total of 409 indoor and 86 outdoor samples were taken. Eighty-five percent of investigated apartments had indoor-outdoor (I/O) ratios of culturable fungi below 1, suggesting minimal indoor sources of fungi. In contrast, 56% of the apartments had I/O ratios for culturable bacteria above 1, indicating the prominence of indoor sources of bacteria. Culturable fungi I/O ratios in apartments serviced by central heating, ventilation, and air-conditioning (HVAC) system were lower than those in apartments with window AC. The type of ventilation system did not have a significant effect on the presence of indoor culturable bacteria. A significant positive association was determined between indoor dew point (DP) levels and indoor culturable fungi (P < .001) and bacteria (P < .001), regardless of ventilation type. Also, residents in apartments with central HVAC did not experience extreme DP values. We conclude that building ventilation systems, seasonality, and indoor sources are major factors affecting indoor bioaerosol levels in residential buildings.

Indoor air quality (IAQ) is determined by indoor and outdoor sources and conditions, building characteristics, and occupant behavior. In the field study context where the researcher lacks full control of observational conditions, it is difficult to compare and integrate these determinants because they require such different types and sources of data. This pilot-level project investigated the potential to overcome these limitations by integrating traditional IAQ measurement techniques with questionnaires and analysis of building deficiencies using 3D infrared thermography imaging in two residential multi-apartment buildings. Of the building deficiencies detected by the 3D thermography, missing insulation (MI) correlated best with the IAQ measurements and questionnaire data. Apartments missing more than 5% of insulation in their exterior wall (n=6) had a significantly higher number concentration of ultrafine airborne particles (diameter < 300 nm) (p=0.013) and their indoor/outdoor ratio (p=0.029) compared to apartments where less than 5% of insulation was missing (n=14). The correlation was driven by apartments where no smoking or use candles or incense was reported. Ultrafine particle concentrations in apartments with combustion sources were higher regardless of the levels of MI. Corner apartments had a higher fraction of MI compared to non-corner apartments (p=0.002); higher levels of MI were detected in apartments where a resident had an asthma attack in the past 12 months. Our data suggest that integration of different data streams produces a more informative IAQ investigation. This pilot-level study should be performed on a larger scale to examine its wider applicability in the IAQ field.

There are limited data on air quality parameters, including airborne particulate matter (PM) in residential green buildings, which are increasing in prevalence. Exposure to PM is associated with cardiovascular and pulmonary diseases, and since Americans spend almost 90% of their time indoors, residential exposures may substantially contribute to overall airborne PM exposure. Our objectives were to: (1) measure various PM fractions longitudinally in apartments in multi-family green buildings with natural (Building E) and mechanical (Building L) ventilation; (2) compare indoor and outdoor PM mass concentrations and their ratios (I/O) in these buildings, taking into account the effects of occupant behavior; and (3) evaluate the effect of green building designs and operations on indoor PM. We evaluated effects of ventilation, occupant behaviors, and overall building design on PM mass concentrations and I/O. Median PMTOTAL was higher in Building E (56 µg/m3) than in Building L (37 µg/m3); I/O was higher in Building E (1.3–2.0) than in Building L (0.5–0.8) for all particle size fractions. Our data show that the building design and occupant behaviors that either produce or dilute indoor PM (e.g., ventilation systems, combustion sources, and window operation) are important factors affecting residents’ exposure to PM in residential green buildings.

Rutgers, The State University of New Jersey, Dept. of Environmental Sciences, New Brunswick, NJ, USA Rutgers, The State University of New Jersey, Dept. of Civil & Environ. Engineering, Piscataway, NJ, USA Rutgers, The State University of New Jersey, Edward J. Bloustein School of Planning and Public Policy, New Brunswick, NJ, USA