Assessment of Indoor Air Quality in Residential Buildings of New England through Actual Data

The impact of short-term exposure to meteorological factors on the risk of death from hypertension and its major complications: a time series analysis based on Hefei, China

OBJECTIVES

This study aimed to reveal the short-term impact of meteorological factors on the mortality risk in hypertensive patients, providing a scientific foundation for formulating pertinent prevention and control policies.

METHODS

In this research, meteorological factor data and daily death data of hypertensive patients in Hefei City from 2015 to 2018 were integrated. Time series analysis was performed using distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Furthermore, we conducted stratified analysis based on gender and age. Relative risk (RR) combined with 95% confidence interval (95% CI) was used to represent the mortality risk of single day and cumulative day in hypertensive patients.

RESULTS

Single-day lag results indicated that high daily mean temperature (T mean) (75th percentile, 24.9 °C) and low diurnal temperature range (DTR) (25th percentile, 4.20 °C) levels were identified as risk factors for death in hypertensive patients (maximum effective RR values were 1.144 and 1.122, respectively). Extremely high levels of relative humidity (RH) (95th percentile, 94.29%) reduced the risk of death (RR value was 0.893). The stratified results showed that the elderly and female populations are more susceptible to low DTR levels, whereas extremely high levels of RH have a more significant protective effect on both populations.

CONCLUSION

Overall, we found that exposure to low DTR and high T mean environments increases the risk of death for hypertensive patients, while exposure to extremely high RH environments significantly reduces the risk of death for hypertensive patients. These findings contribute valuable insights for shaping targeted prevention and control strategies.

Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing

With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM2.5) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM2.5 concentration with population distribution to provide the personal daily PM2.5 internal dose considering the indoor/outdoor exposure difference. A 30-m PM2.5 assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R2 = 0.78-0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R2 = 0.31-0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM2.5 concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM2.5 concentration was 26.5 μg/m3. The internal dose based on the assimilated indoor/outdoor PM2.5 concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.

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.

Assessment of indoor air quality and comfort by comparing an energy simulation and actual data in Native American shelters

Introduction: This research will determine if a native American shelter (wigwam) can create comfort and if while doing so can provide healthy indoor air quality (IAQ) levels as defined by current standards. Concurrent to this research a technique to digitally model the outcomes of comfort created within the shelter was developed.

Methods: A fullsize example of a wigwam was built and data from inside and outside the wigwam monitored for comparison. Data collected both inside and outside was temperature and relative humidity of the air, collected inside the wigwam were CO2, VOC, and PM2.5 levels. The wigwam allowed us to compare the accuracy of a digital model created in Design Builder. The Design Builder model was made to the specific size, materials, and location of the actual wigwam. This allowed an accurate comparison of temperature and relative humidity levels. Design-Builder accurately recreated the attributes of the full-size wigwam.

Results and Discussion: It was found that comfort can be achieved to modern standards in this native shelter; as temperature, relative humidity, and rainfall exposure can all be controlled to acceptable levels. Indoor air quality is always at an acceptable level when a fire isn’t active. When an open fire is introduced, the particulates and VOC released into the interior of the wigwam are at dangerous levels. A woodstove with flue pipe allowed for comfort to be maintained at healthier air quality levels but did not reach acceptable levels for particulate matter.

A review of critical residential buildings parameters and activities when investigating indoor air quality and pollutants

Indoor air in residential dwellings can contain a variety of chemicals, sometimes present at concentrations or in combinations which can have a negative impact on human health. Indoor Air Quality (IAQ) surveys are often required to characterize human exposure or to investigate IAQ concerns and complaints. Such surveys should include sufficient contextual information to elucidate sources, pathways, and the magnitude of exposures. The aim of this review was to investigate and describe the parameters that affect IAQ in residential dwellings: building location, layout, and ventilation, finishing materials, occupant activities, and occupant demography. About 180 peer-reviewed articles, published from 01/2013 to 09/2021 (plus some important earlier publications), were reviewed. The importance of the building parameters largely depends on the study objectives and whether the focus is on a specific pollutant or to assess health risk. When considering classical pollutants such as particulate matter (PM) or volatile organic compounds (VOCs), the building parameters can have a significant impact on IAQ, and detailed information of these parameters needs to be reported in each study. Research gaps and suggestions for the future studies together with recommendation of where measurements should be done are also provided.

Assessing the indoor air quality and their predictor variable in 21 home offices during the Covid-19 pandemic in Norway

In this study, concentrations of pollutants: formaldehyde, carbon dioxide (CO₂), and total volatile organic compounds (TVOC) and parameters: indoor room temperature and relative humidity (RH) were measured in 21 home offices for at least one week in winter in Trondheim, Norway. Eleven of these were measured again for the same duration in summer. Potentially explanatory variables of these parameters were collected, including building and renovation year, house type, building location, trickle vent status, occupancy, wood stove, floor material, pets, RH, and air temperature. The association between indoor air pollutants and their potential predictor variables was analyzed using generalized estimation equations to determine the significant parameters to control pollutants. Significantly seasonal differences in concentrations were observed for CO₂ and formaldehyde, while no significant seasonal difference was observed for TVOC. For TVOC and formaldehyde, trickle vent, RH, and air temperature were among the most important predictor variables. Although higher concentrations of CO₂ were measured in cases where the trickle vent was closed, the most important predictor variables for CO₂ were season, RH, and indoor air temperature. The formaldehyde concentrations were higher outside working hours but mostly below health thresholds recommendations; for CO₂, 11 of the measured cases had indoor concentrations exceeding 1000 ppm in 10% of the measured time. For TVOC, the concentrations were above the recommended values by WHO in 73% of the cases. RH was generally low in winter. The temperature was generally kept over the recommended level of 22-24 °C during working hours.