Characterization of cooking-related ultrafine particles in a US residence and impacts of various intervention strategies.

Interventions that improve air exchange or filter the air have the potential to reduce particle exposures from residential cooking. In this study, we evaluated the effect of using a range hood, opening kitchen windows, and using portable air cleaners (PACs) in various home locations on the concentrations of ultrafine particles (UFPs) at different times and in different rooms during and after cooking. All experiments were conducted using a standardized cooking protocol in a real-world naturally-ventilated apartment located in the northwest United States. Real-time UFP measurements collected from the kitchen, living room, and bedroom locations were used to estimate parameters of a dynamic model, which included time-varying particle emission rates from cooking and particle decay. We found that 1-min mean UFP number concentrations in the kitchen and living room mostly peaked within 0-10 min after cooking ended at levels of 150,000-500,000 particles/cm3. In contrast, the bedroom UFP concentrations were consistently low except for the window-open scenario. While varying considerably with time, the 1-min UFP emission rates were comparable during and within 5-min after cooking, with means (standard deviations) of 0.8 (1.1) × 1012 and 1.1 (1.2) × 1012 particles/min, respectively. Compared with the no-intervention scenario, keeping the kitchen windows open and using a kitchen range hood reduced the mean indoor average UFP concentrations during and 1 h after cooking by ~70% and ~35%, respectively. Along with the range hood on, utilizing a PAC in the kitchen during and after cooking further reduced the mean indoor average UFP levels during and 1 h after cooking by an additional 53%. In contrast, placing the PAC in the living room or bedroom resulted in worse efficacy, with additional 2-13% reductions. These findings provide useful information on how to reduce cooking-related UFP exposure via readily accessible intervention strategies.

Residential cooking-related PM2.5: Spatial-temporal variations under various intervention scenarios.

Some cooking events can generate high levels of hazardous PM2.5. This study assesses the dispersion of cooking-related PM2.5 throughout a naturally-ventilated apartment in the US, examines the dynamic process of cooking-related emissions, and demonstrates the impact of different indoor PM2.5 mitigating strategies. We conducted experiments with a standardized pan-frying cooking procedure under seven scenarios, involving opening kitchen windows, using a range hood, and utilizing a portable air cleaner (PAC) in various indoor locations. Real-time PM2.5 concentrations were measured in the open kitchen, living room, bedroom (door closed), and outdoor environments. Decay-related parameters were estimated, and time-resolved PM2.5 emission rates for each experiment were determined using a dynamic model. Results show that the 1-min mean PM2.5 concentrations in the kitchen and living room peaked 1-7 min after cooking at levels of 200-1400 µg/m3, which were more than 9 times higher than the peak bedroom levels. Mean (standard deviation) kt for the kitchen, ranging from 0.58 (0.02) to 6.62 (0.34) h-1, was generally comparable to that of the living room (relative difference < 20%), but was 1-5 times larger than that of the bedroom. The range of PM2.5 full-decay time was between 1-10 h for the kitchen and living room, and from 0 to > 6 h for the bedroom. The PM2.5 emission rates during and 5 min after cooking were 2.3 (3.4) and 5.1 (3.9) mg/min, respectively. Intervention strategies, including opening kitchen windows and using PACs either in the kitchen or living room, can substantially reduce indoor PM2.5 levels and the related full-decay time. For scenarios involving a PAC, placing it in the kitchen (closer to the source) resulted in better efficacy.

Energy consumption of using HEPA-based portable air cleaner in residences: A monitoring study in Seattle, US.

Portable air cleaners (PACs), offering both auto and manual (adjustable) operation modes, are commonly used in residences. Compared with adjustable mode, auto mode's advantage of reducing indoor PM2.5 has been previously demonstrated. This study examines the energy consumption of such PACs in six residences recruited in Seattle, United States, and compares the power consumption between auto and adjustable modes. Each residence went through a one-week-long PAC filtration session under auto and adjustable modes, respectively. PAC power consumption, indoor PM2.5, temperature, and relative humidity (RH) were measured at 10-second intervals in each residence. A linear mixed-effects regression (LMER) model was used to compare the PAC power consumption between the two modes after adjusting for indoor PM2.5, temperature, and RH. Results show that the mean (standard deviation) PAC power consumption under adjustable and auto modes were 7.0 (3.5) and 6.8 (2.6) W, respectively. The average monthly energy consumption of continuous PAC operation was estimated to be ~5 kWh for both modes. Based on the LEMR model, PAC power consumption under auto mode was approximately 3% larger than that under adjustable mode, after adjusting for living-room PM2.5, temperature, and RH levels. The implications for PAC operation mode selection in residential environments were discussed.

Field measurements of PM2.5 infiltration factor and portable air cleaner effectiveness during wildfire episodes in US residences.

Wildfires have frequently occurred in the western United States (US) during the summer and fall seasons in recent years. This study measures the PM2.5 infiltration factor in seven residences recruited from five dense communities in Seattle, Washington, during a 2020 wildfire episode and evaluates the impacts of HEPA-based portable air cleaner (PAC) use on reducing indoor PM2.5 levels. All residences with windows closed went through an 18-to-24-h no filtration session, with five of seven following that period with an 18-to-24-h filtration session. Auto-mode PACs, which automatically adjust the fan speed based on the surrounding PM2.5 levels, were used for the filtration session. 10-s resolved indoor PM2.5 levels were measured in each residence's living room, while hourly outdoor levels were collected from the nearest governmental air quality monitoring station to each residence. Additionally, a time-activity diary in minute resolution was collected from each household. With the impacts of indoor sources excluded, indoor PM2.5 mass balance models were developed to estimate the PM2.5 indoor/outdoor (I/O) ratios, PAC effectiveness, and decay-related parameters. Among the seven residences, the mean infiltration factor ranged from 0.33 (standard deviation [SD]: 0.06) to 0.76 (SD: 0.05). The use of auto-mode PAC led to a 48%-78% decrease of indoor PM2.5 levels after adjusting for outdoor PM2.5 levels and indoor sources. The mean (SD) air exchange rates ranged from 0.30 (0.13) h-1 to 1.41 (3.18) h-1 while the PM2.5 deposition rate ranged from 0.10 (0.54) h-1 to 0.49 (0.47) h-1. These findings suggest that staying indoors, a common protective measure during wildfire episodes, is insufficient to prevent people's excess exposure to wildfire smoke, and provides quantitative evidence to support the utilization of auto-mode PACs during wildfire events in the US.

Exposures to Air Pollution and Noise from Multi-Modal Commuting in a Chinese City.

BACKGROUND: Modern urban travel includes mixtures of transit options, which potentially impact individual pollution exposures and health. This study aims to investigate variations in traffic-related air pollution and noise levels experienced in traffic in Chengdu, China. METHODS: Real-time PM2.5, black carbon (BC), and noise levels were measured for four transportation modes (car, bus, subway, and shared bike) on scripted routes in three types of neighborhoods (urban core, developing neighborhood, and suburb). Each mode of transportation in each neighborhood was sampled five times in summer and winter, respectively. After quality control, mixed effect models were built for the three pollutants separately. RESULTS: Air pollutants had much higher concentrations in winter. Urban Core had the highest PM2.5 and BC concentrations across seasons compared to the other neighborhoods. The mixed effect model indicated that car commutes were associated with lower PM2.5 (-34.4 µg/m3; 95% CI: -47.5, -21.3), BC (-2016.4 ng/m3; 95% CI: -3383.8, -648.6), and noise (-9.3 dBA; 95% CI: -10.5, -8.0) levels compared with other modes; subway commutes had lower PM2.5 (-11.9 µg/m3; 95% CI: 47.5, -21.3), but higher BC (2349.6 ng/m3; 95% CI: 978.1, 3722.1) and noise (3.0 dBA; 95% CI: 1.7, 4.3) levels than the other three modes of transportation. CONCLUSION: Personal exposure to air pollution and noise vary by season, neighborhood, and transportation modes. Exposure models accounting for environmental, meteorological, and behavioral factors, and duration of mixed mode commuting may be useful for health studies of urban traffic microenvironments.