Longitudinal assessment of personal air pollution clouds in ten home and office environments

Sources, levels, and determinants of indoor air pollutants in Europe: A systematic review

Clean air is a requirement for life, and the quality of indoor air is a health determinant since people spend most of their daily time indoors. The aim of this study was to systematically review the available evidence regarding the sources, determinants and concentrations of indoor air pollutants in a set of scenarios under study in K-HEALTHinAIR project. To this end, a systematic review was performed to review the available studies published between the years 2013-2023, for several settings (schools, homes, hospitals, lecture halls, retirement homes, public transports and canteens), conducted in Europe, where sources and determinants of the indoor pollutants concentrations was assessed. After a two-stage screening in abstract and full-text, 148 papers were included for data extraction. For particulate matter, carbon dioxide and volatile organic compounds, several emission sources were identified (occupancy, human activities, resuspension, cleaning products, disinfectants, craft activities, cooking, smoking), with ventilation, number of occupants, building characteristics, being considered as important determinants. This review made also possible to discuss some of the actions that are already in place or should be implemented in the future to prevent and control the presence of pollutants indoors.

Influence of Ventilation on Formation and Growth of 1-20 nm Particles via Ozone-Human Chemistry

Ozone reaction with human surfaces is an important source of ultrafine particles indoors. However, 1-20 nm particles generated from ozone-human chemistry, which mark the first step of particle formation and growth, remain understudied. Ventilation and indoor air movement could have important implications for these processes. Therefore, in a controlled-climate chamber, we measured ultrafine particles initiated from ozone-human chemistry and their dependence on the air change rate (ACR, 0.5, 1.5, and 3 h-1) and operation of mixing fans (on and off). Concurrently, we measured volatile organic compounds (VOCs) and explored the correlation between particles and gas-phase products. At 25-30 ppb ozone levels, humans generated 0.2-7.7 × 1012 of 1-3 nm, 0-7.2 × 1012 of 3-10 nm, and 0-1.3 × 1012 of 10-20 nm particles per person per hour depending on the ACR and mixing fan operation. Size-dependent particle growth and formation rates increased with higher ACR. The operation of mixing fans suppressed the particle formation and growth, owing to enhanced surface deposition of the newly formed particles and their precursors. Correlation analyses revealed complex interactions between the particles and VOCs initiated by ozone-human chemistry. The results imply that ventilation and indoor air movement may have a more significant influence on particle dynamics and fate relative to indoor chemistry.

Physiology or Psychology: What Drives Human Emissions of Carbon Dioxide and Ammonia?

Humans are the primary sources of CO2 and NH3 indoors. Their emission rates may be influenced by human physiological and psychological status. This study investigated the impact of physiological and psychological engagements on the human emissions of CO2 and NH3. In a climate chamber, we measured CO2 and NH3 emissions from participants performing physical activities (walking and running at metabolic rates of 2.5 and 5 met, respectively) and psychological stimuli (meditation and cognitive tasks). Participants' physiological responses were recorded, including the skin temperature, electrodermal activity (EDA), and heart rate, and then analyzed for their relationship with CO2 and NH3 emissions. The results showed that physiological engagement considerably elevated per-person CO2 emission rates from 19.6 (seated) to 46.9 (2.5 met) and 115.4 L/h (5 met) and NH3 emission rates from 2.7 to 5.1 and 8.3 mg/h, respectively. CO2 emissions reduced when participants stopped running, whereas NH3 emissions continued to increase owing to their distinct emission mechanisms. Psychological engagement did not significantly alter participants' emissions of CO2 and NH3. Regression analysis revealed that CO2 emissions were predominantly correlated with heart rate, whereas NH3 emissions were mainly associated with skin temperature and EDA. These findings contribute to a deeper understanding of human metabolic emissions of CO2 and NH3.

Adequacy of stationary measurements as proxies for residential personal exposure to gaseous and particle air pollutants

People are exposed to myriad of airborne pollutants in their homes. Owing to diverse potential sources of air pollution and human activity patterns, accurate assessment of residential exposures is complex. In this study, we explored the relationship between personal and stationary air pollutant measurements in residences of 37 participants working from home during the heating season. Stationary environmental monitors (SEMs) were located in the bedroom, living room or home office and personal exposure monitors (PEMs) were worn by the participants. SEMs and PEMs included both real-time sensors and passive samplers. During three consecutive weekdays, continuous data were obtained for particle number concentration (size range 0.3-10 μm), carbon dioxide (CO2), and total volatile organic compounds (TVOC), while passive samplers collected integrated measures of 36 volatile organic compounds (VOCs) and semi volatile organic compounds (SVOCs). The personal cloud effect was detected in >80% of the participants for CO2 and >50% participants for PM10. Multiple linear regression analysis showed that a single CO2 monitor placed in the bedroom efficiently represented personal exposure to CO2 (R2 = 0.90) and moderately so for PM10 (R2 = 0.55). Adding a second or third sensor in a residence did not lead to improved exposure estimates for CO2, with only 6-9% improvement for particles. Selecting data from SEMs when participants were in the same room improved personal exposure estimates by 33% for CO2 and 5% for particles. Out of 36 detected VOCs and SVOCs, 13 had at least 50% higher concentrations in personal versus stationary samples. Findings from this study aid improved understanding of the complex dynamics of gaseous and particle pollutants and their sources in residences, and could support the development of refined procedures for residential air quality monitoring and inhalation exposure assessment.

Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic

Personal cloud, termed as the difference in air pollutant concentrations between breathing zone and room sites, represents the bias in approximating personal inhalation exposure that is linked to accuracy of health risk assessment. This study performed a two-week field experiment in a naturally ventilated office during the COVID-19 pandemic to assess occupants' exposure to common air pollutants and to determine factors contributing to the personal cloud effect. During occupied periods, indoor average concentrations of endotoxin (0.09 EU/m³), TVOC (231 μg/m³), CO₂ (630 ppm), and PM₁₀ (14 μg/m³) were below the recommended limits, except for formaldehyde (58 μg/m³). Personal exposure concentrations, however, were significantly different from, and mostly higher than, concentrations measured at room stationary sampling sites. Although three participants shared the same office, their personal air pollution clouds were mutually distinct. The mean personal cloud magnitude ranged within 0-0.05 EU/m³, 35-192 μg/m³, 32-120 ppm, and 4-9 μg/m³ for endotoxin, TVOC, CO₂, and PM₁₀, respectively, and was independent from room concentrations. The use of hand sanitizer was strongly associated with an elevated personal cloud of endotoxin and alcohol-based VOCs. Reduced occupancy density in the office resulted in more pronounced personal CO₂ clouds. The representativeness of room stationary sampling for capturing dynamic personal exposures was as low as 28% and 5% for CO₂ and PM₁₀, respectively. The findings of our study highlight the necessity of considering the personal cloud effect when assessing personal exposure in offices.

Proxy methods for detection of inhalation exposure in simulated office environments

BACKGROUND

Modern health concerns related to air pollutant exposure in buildings have been exacerbated owing to several factors. Methods for assessing inhalation exposures indoors have been restricted to stationary air pollution measurements, typically assuming steady-state conditions.

OBJECTIVE

We aimed to examine the feasibility of several proxy methods for estimating inhalation exposure to CO2, PM2.5, and PM10 in simulated office environments.

METHODS

In a controlled climate chamber mimicking four different office setups, human participants performed a set of scripted sitting and standing office activities. Three proxy sensing techniques were examined: stationary indoor air quality (IAQ) monitoring, individual monitoring of physiological status by wearable wristband, human presence detection by Passive Infrared (PIR) sensors. A ground-truth of occupancy was obtained from video recordings of network cameras. The results were compared with the concurrent IAQ measurements in the breathing zone of a reference participant by means of multiple linear regression (MLR) analysis with a combination of different input parameters.

RESULTS

Segregating data onto sitting and standing activities could lead to improved accuracy of exposure estimation model for CO2 and PM by 9-60% during sitting activities, relative to combined activities. Stationary PM2.5 and PM10 monitors positioned at the ceiling-mounted ventilation exhaust in vicinity of the seated reference participant accurately estimated inhalation exposure (adjusted R² = 0.91 and R² = 0.87). Measurement at the front edge of the desk near abdomen showed a moderate accuracy (adjusted R² = 0.58) in estimating exposure to CO2. Combining different sensing techniques improved the CO2 exposure detection by twofold, whereas the improvement for PM exposure detection was small (~10%).

SIGNIFICANCE

This study contributes to broadening the knowledge of proxy methods for personal exposure estimation under dynamic occupancy profiles. The study recommendations on optimal monitor combination and placement could help stakeholders better understand spatial air pollutant gradients indoors which can ultimately improve control of IAQ.

Quantifying the dynamic characteristics of indoor air pollution using real-time sensors: Current status and future implication

People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM_2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.

Lung Effects of Household Air Pollution

Biomass fuel smoke, secondhand smoke, and oxides of nitrogen are common causes of household air pollution (HAP). Almost 2.4 billion people worldwide use solid fuels for cooking and heating, mostly in low- and middle-income countries. Wood combustion for household heating is also common in many areas of high-income countries, and minorities are particularly vulnerable. HAP in low- and middle-income countries is associated with asthma, acute respiratory tract infections in adults and children, chronic obstructive pulmonary disease, lung cancer, tuberculosis, and respiratory mortality. Although wood smoke exposure levels in high-income countries are typically lower than in lower-income countries, it is similarly associated with accelerated lung function decline, higher prevalence of airflow obstruction and chronic bronchitis, and higher all-cause and respiratory cause-specific mortality. Household air cleaners with high-efficiency particle filters have mixed effects on asthma and chronic obstructive pulmonary disease outcomes. Biomass fuel interventions in low-income countries include adding chimneys to cookstoves, improving biomass fuel combustion stoves, and switching fuel to liquid petroleum gas. Still, the impact on health outcomes is inconsistent. In high-income countries, strategies for reducing biomass fuel-related HAP are centered on community-level woodstove changeout programs, although the results are again inconsistent. In addition, initiatives to encourage home smoking bans have mixed success in households with children. Environmental solutions to reduce HAP have varying success in reducing pollutants and health problems. Improved understanding of indoor air quality factors and actions that prevent degradation or improve polluted indoor air may lead to enhanced environmental health policies, but health outcomes must be rigorously examined.