Vertically-resolved indoor measurements of air pollution during Chinese cooking

Household air pollution disparities between socioeconomic groups in Chicago

Purpose: To assess household air pollution levels in urban Chicago households and examine how socioeconomic factors influence these levels. Methods: We deployed wireless air monitoring devices to 244 households in a diverse population in Chicago to continuously record household fine particulate matter (PM2.5) concentration. We calculated hourly average PM2.5 concentration in a 24-hour cycle. Four factors-race, household income, area deprivation, and exposure to smoking-were considered in this study. Results: A total of 93085 h of exposure data were recorded. The average household PM2.5 concentration was 43.8 μg m-3. We observed a significant difference in the average household PM2.5 concentrations between Black/African American and non-Black/African American households (46.3 versus 31.6 μg m-3), between high-income and low-income households (18.2 versus 52.5 μg m-3), and between smoking and non-smoking households (69.7 versus 29.0 μg m-3). However, no significant difference was observed between households in less and more deprived areas (43.7 versus 43.0 μg m-3). Implications: Household air pollution levels in Chicago households are much higher than the recommended level, challenging the hypothesis that household air quality is adequate for populations in high income nations. Our results indicate that it is the personal characteristics of participants, rather than the macro environments, that lead to observed differences in household air pollution.

Appraising the characteristics of particulate matter from leather tanning micro-environments, their respirational risks, and dysfunctions amid exposed working cohorts

Leather tanneries are known for chemical laden work environments and pulmonic complaints among workers. This study presents an analysis of tannery micro-environments emphasizing on size-based variation in composition of particulate matter and consequent respiratory dysfunctions. Qualitative (FTIR, SEM-EDX) and quantitative assessment (elemental composition, carbon forms) of PM10 and 2.5 has been employed. For lung function evaluation of workforce, spirometry with ATS proprieties was used. The peak concentrations of both PM10 and 2.5 have been found at PU, FU, and B&S. The LTCR for only Cr is high for both PM2.5 and PM10. HQ was high for Al, Cr, and Mn for both PM sizes. The maximum organic and secondary organic carbon in PM10 was found at FU and in PM2.5 at PU. The varied PM composition included carbohydrate (B&S, WMO), ether (S&S, P&S) and hydroxyl (B&S, S&S, P&S), proteins, polyenes, vinyl groups (S&S, P&S, FU), alcohols (PU and FU), and aldehyde present at PU. These results were armored by high organic and total carbon concentrations for the same sites. Therefore, PM are classified into biogenic (carbonaceous: microbial and animal remains) from PU and WMO, incidental (industrial, mixt physico-chemical character) from PU, FU, WMO, B&S and P&S, and geogenic (crustal mineral dust) from RHT, B&S, PU, and P&S. Furthermore, increase in metal concentrations in PM10 (Cr, Mn, Co, Ni, V, As, Be, Ba, and Cd) and PM2.5 (As, Pb) while TC, OC, and SOC in PM2.5 caused depreciation overall lung function. The exposure to biogenic and incidental PM nature are key cause of pulmonic dysfunction.

Indoor air pollution from the household combustion of coal: Tempo-spatial distribution of gaseous pollutants and semi-quantification of source contribution

Coal is a widely used solid fuel for cooking and heating activities in rural households, whose incomplete combustion in inefficient household stoves releases a range of gaseous pollutants. To evaluate the impact of coal combustion on indoor air quality, this study comprehensively investigated the indoor air pollution of typical gaseous pollutants, including formaldehyde (HCHO), carbon dioxide (CO₂), carbon monoxide (CO), total volatile organic compounds (TVOC), and methane (CH₄), during coal combustion process in rural households using online monitoring with high tempo-spatial resolution. The indoor concentrations of gaseous pollutants were considerably elevated during the coal combustion period, with the indoor concentrations being significantly higher than those in courtyard air. The levels of several gaseous pollutants (CO₂, CO, TVOC, and CH₄) in indoor air were much higher during the flaming phase than the de-volatilization and smoldering phases, while HCHO peaked in the de-volatilization phase. The gaseous pollutant concentrations mostly decreased from the room ceiling to the ground level, while their horizontal distribution was relatively uniform within the room. It was estimated that coal combustion accounted for about 71 %, 92 %, 63 %, 59 %, and 21 % of total exposure to indoor CO₂, CO, TVOC, CH₄, and HCHO, respectively. Improved stove combined with clean fuel could effectively lower the concentrations of CO₂, CO, TVOC, and CH₄ in indoor air and reduce the contributions of coal combustion to these gaseous pollutants by about 21-68 %. These findings help better understand the indoor air pollution resulting from residential coal combustion and could guide the development of intervention programs to improve indoor air quality in rural households of northern China.

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.