In this study, 45 indoor dust samples and four particulate samples from air-conditioner filters were collected from four different indoor environments in Guangzhou, China, and the concentration and composition of organophosphate tri-esters (OPEs) and organophosphate di-esters (Di-OPs) were determined. Eight of the 10 target OPEs were detected in indoor dust at different detection frequencies (DFs), with tris(2-chloroisopropyl) phosphate and tris(2-chloroethyl) phosphate being the main components. Seven target Di-OPs were detected at different DFs, with diphenyl phosphate being the dominant compound. The total OPEs (∑8 OPEs) and total Di-OPs (∑7 Di-OPs) concentrations varied from 726 to 39,312 ng/g and 68.8–14,766 ng/g, respectively. The ∑8 OPEs concentrations in instrumental houses were significantly higher (p < 0.001) than in three other indoor environments. The varying strengths of the correlation between Di-OPs and their respective parent OPEs was suggestive of their emission sources (e.g., direct application, impurities in OPE formulas, and OPE degradation). The hazard index (HI) values of individual OPEs in residential house were lower than 1, the results suggested a limited human health risk from individual OPEs. However, the total HI value (∑HIs) of OPEs was approximately 1 based on a high exposure scenario and suggested a low risk for toddlers.

While the measurement of particulate matter (PM) with a diameter of less than 2.5 μm (PM₂.₅) has been conducted for personal exposure assessment, it remains unclear how models that integrate microenvironmental levels with resolved activity and location information predict personal exposure to PM. We comprehensively investigated PM₂.₅ concentrations in various microenvironments and estimated personal exposure stratified by the microenvironment. A variety of microenvironments (>200 places and locations, divided into 23 components according to indoor, outdoor, and transit modes) in a community were selected to characterize PM₂.₅ concentrations. Infiltration factors calculated from microenvironmental/central-site station (M/S) monitoring campaigns with time-activity patterns were used to estimate time-weighted exposure to PM₂.₅ for university students. We evaluated exposures using a four-stage modeling approach and quantified the performance of each component. It was found that the SidePak monitor overestimated the concentration by 3.5 times as compared with the filter-based measurements. Higher mean concentrations of PM₂.₅ were observed in the Taoist temple and night market microenvironments; in contrast, lower concentrations were observed in air-conditioned offices and car microenvironments. While the exposure model incorporating detailed time-location information and infiltration factors achieved the highest prediction (R² = 0.49) of personal exposure to PM₂.₅, the use of indoor, outdoor, and transit components for modeling also generated a consistent result (R² = 0.44).

Urban stormwater is a major source of chemical pollution to receiving waters. Anthropogenic materials in the built environment can be an important source of chemicals to stormwater runoff. Roofing materials can leach significant amounts of metals, which vary over the life of the roof. We report concentrations of three metals (As, Cu, Zn) leaching into runoff from experimental panels of 14 roofing materials over 4.5 years of weathering. Ten roofing materials leached metals. Several leached >10 ppb during one or more study periods. The most common correlate with metal concentration was panel age, followed by precipitation amount. Extrapolating from these observations, we estimated the loading of metals from each roofing material during the first 10 years following installation. Eight materials were predicted to leach metals above background at the end of the 10 years. In combination with information on the prevalence of different roofing materials in the Puget Sound region of the Pacific Northwest, we estimated the relative amount of metals contributed from roofing materials in this basin. Most arsenic and copper was estimated to be contributed by residential roofing; nearly all arsenic from wood shakes manufactured with copper chromated arsenic, and copper contributed mainly from treated wood shakes followed by copper granule-containing asphalt shingles. Most zinc was estimated to be contributed by commercial roofs, including Zincalume and painted metal roofs. Overall our data shows that roofing materials can be an important long-term source of As, Cu, and Zn to stormwater runoff. Compared with atmospheric deposition, roof materials were a significant source, particularly of As and Cu. To get a complete picture of metals sourced from buildings, there is a need to study whole roof systems, including gutters, downspouts, and HVAC systems, as well as metals contributed from homeowner-applied treatments to their roofs.

Ambient concentrations of fine particulate matter (PM₂.₅) concentration is often used as an exposure surrogate to estimate PM₂.₅ health effects in epidemiological studies. Ignoring the potential variations in the amount of outdoor PM₂.₅ infiltrating into indoor environments will cause exposure misclassification, especially when people spend most of their time indoors. As it is not feasible to measure the PM₂.₅ infiltration factor (Fᵢₙf) for each individual residence, we aimed to build models for residential PM₂.₅Fᵢₙf prediction and to evaluate seasonal Fᵢₙf variations among residences. We repeated collected paired indoor and outdoor PM₂.₅ filter samples for 7 continuous days in each of the three seasons (hot, cold and transitional seasons) from 48 typical homes of Shanghai, China. PM₂.₅-bound sulfur on the filters was measured by X-ray fluorescence for PM₂.₅Fᵢₙf calculation. We then used stepwise-multiple linear regression to construct season-specific models with climatic variables and questionnaire-based predictors. All models were evaluated by the coefficient of determination (R²) and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV). The 7-day mean (±SD) of PM₂.₅Fᵢₙf across all observations was 0.83 (±0.18). Fᵢₙf was found higher and more varied in transitional season (12–25 °C) than hot (>25 °C) and cold (<12 °C) seasons. Air conditioning use and meteorological factors were the most important predictors during hot and cold seasons; Floor of residence and building age were the best transitional season predictors. The models predicted 60.0%–68.4% of the variance in 7-day averages of Fᵢₙf, The LOOCV analysis showed an R² of 0.52 and an RMSE of 0.11. Our finding of large variation in residential PM₂.₅Fᵢₙf between seasons and across residences within season indicated the important source of outdoor-generated PM₂.₅ exposure heterogeneity in epidemiologic studies. Our models based on readily available data may potentially improve the accuracy of estimates of the health effects of PM₂.₅ exposure.

Exposure to fine and ultrafine particles as well as particulate polycyclic aromatic hydrocarbons (PAHs) by commuters in three transportation modes (walking, subway and bus) were examined in December 2011 in Beijing, China. During the study period, real-time measured median PM2.5 mass concentration (PMC) for walking, riding buses and taking the subway were 26.7, 32.9 and 56.9 μg m−3, respectively, and particle number concentrations (PNC) were 1.1 × 104, 1.0 × 104 and 2.2 × 104 cm−3. Commuters were exposed to higher PNC in air-conditioned buses and aboveground-railway, but higher PMC in underground-subway compared to aboveground-railway. PNC in roadway modes (bus and walking) peaked at noon, but was lower during traffic rush hours, negatively correlated with PMC. Toxic potential of particulate-PAHs estimated based on benzo(a)pyrene toxic equivalents (BaP TEQs) showed that walking pedestrians were subjected to higher BaP TEQs than bus (2.7-fold) and subway (3.6-fold) commuters, though the highest PMC and PNC were observed in subway.

Speciation of inorganic trivalent arsenicals (iAsIII), inorganic pentavalent arsenicals (iAsV), monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) in total arsenic (As) content and its bioaccessible fractions contained in road dust, household air-conditioning (AC) filter dust and PM2.5 was investigated. Inorganic As, especially iAsV, was observed as the dominant species. Physiologically based extraction test (PBET), an in-vitro gastrointestinal method, was used to estimate the oral As bioaccessibility in coarse particles and the species present in the oral bioaccessible fraction. A composite lung simulating serum was used to mimic the pulmonary condition to extract the respiratory bioaccessible As and its species in PM2.5. Reduction of iAsV to iAsIII occurred in both in-vitro gastrointestinal and lung simulating extraction models. The inorganic As species was the exclusive species for absorption through ingestion and inhalation of atmospheric particles, which was an important exposure route to inorganic As, in addition to drinking water and food consumption.

The prevalence of asthma and allergic diseases has increased rapidly in urban China since 2000. There has been limited study of associations between home environmental and lifestyle factors with asthma and symptoms of allergic disease in China.In a cross-sectional analysis of 2214 children in Beijing, we applied a two-step hybrid Least Absolute Shrinkage and Selection Operator (LASSO) algorithm to identify environmental and lifestyle-related factors associated with asthma, rhinitis and wheeze from a wide range of candidates. We used group LASSO to select variables, using cross-validation as the criterion. Effect estimates were then calculated using adaptive LASSO. Model performance was assessed using Area Under the Curve (AUC) values.We found a number of environmental and lifestyle-related factors significantly associated with asthma, rhinitis or wheeze, which changed the probability of asthma, rhinitis or wheeze from −5.76% (95%CI: −7.74%, −3.79%) to 27.4% (95%CI: 16.6%, 38.3%). The three factors associated with the largest change in probability of asthma were short birth length, carpeted floor and paternal allergy; for rhinitis they were maternal smoking during pregnancy, paternal allergy and living close to industrial area; and for wheeze they were carpeted floor, short birth length and maternal allergy. Other home environmental risk factors identified were living close to a highway, industrial area or river, sharing bedroom, cooking with gas, furry pets, cockroaches, incense, printer/photocopier, TV, damp, and window condensation in winter. Lifestyle-related risk factors were child caretakers other than parents, and age<3 for the day-care. Other risk factors included use of antibiotics, and mother’s occupation. Major protective factors for wheeze were living in a rural/suburban region, air conditioner use, and mother’s occupation in healthcare.Our findings suggest that changes in lifestyle and indoor environments associated with the urbanization and industrialization of China are associated with asthma, rhinitis, and wheeze in children.

Metals in indoor dust pose potential health risks to humans. Dust deposition on air conditioner filters can represent the resuspended particulate matter in indoor air. However, few studies have examined this until now. This study investigated the total concentrations and different chemical fractionations of Cd, Cr, Mn, Ni, Pb, Sb, V, and Zn in indoor dust from three different functional zones (the Chief District, Commercial District (CmD), and Industrial District) in Hefei. The mean metal concentrations in indoor dust decreased in the following order: Zn > Mn > Pb > Cr > Ni > V > Cd > Sb. Cd, Pb, and Zn mainly existed in the mobile fraction. Cr and V mainly existed in the residual fraction. The enrichment factor and geo-accumulation index values of heavy metals were all ranked in the order of Cd > Zn > Pb > Sb > Ni > Cr > V, and these values in indoor dust were larger than those in outdoor dust. In addition, the enrichment patterns of these elements were similar in the three functional areas. The orders of non-carcinogenic risk (hazard index; HI) for the different functional areas for children were roughly the same, but there were clear differences for adults. In general, all the HIs were less than 1, which were within the internationally recognized safe range. The total carcinogenic risk (TR) was in the order of Cr > Pb > Cd for both children and adults in the three functional zones. The TRs from Cr exposure were not negligible. The TRs were significantly higher in the CmD.

Concentrations of nine organophosphate flame retardants (OPFRs) and eight polybrominated diphenyl ethers (PBDEs) were measured in samples of indoor dust (n = 85) and air (n = 45) from Australian houses, offices, hotels, and transportation (buses, trains, and aircraft). All target compounds were detected in indoor dust and air samples. Median ∑₉OPFRs concentrations were 40 μg/g in dust and 44 ng/m³ in indoor air, while median ∑₈PBDEs concentrations were 2.1 μg/g and 0.049 ng/m³. Concentrations of FRs were higher in rooms that contained carpet, air conditioners, and various electronic items. Estimated daily intakes in adults are 14000 pg/kg body weight/day and 330 pg/kg body weight/day for ∑₉OPFRs and ∑₈PBDEs, respectively. Our results suggest that for the volatile FRs such as tris(2-chloroethyl) phosphate (TCEP) and TCIPP, inhalation is expected to be the more important intake pathway compared to dust ingestion and dermal contact.

In indoor air, terpene-ozone reactions can form secondary organic aerosols (SOA) in a transient process. ‘Real world’ measurements conducted in a furnished room without air conditioning were modelled involving the indoor background of airborne particulate matter, outdoor ozone infiltrated by natural ventilation, repeated transient limonene evaporations, and different subsequent ventilation regimes. For the given setup, we disentangled the development of nucleated, coagulated, and condensed SOA fractions in the indoor air and calculated the time dependence of the aerosol mass fraction (AMF) by means of a process model. The AMF varied significantly between 0.3 and 5.0 and was influenced by the ozone limonene ratio and the background particles which existed prior to SOA formation. Both influencing factors determine whether nucleation or adsorption processes are preferred; condensation is strongly intensified by particulate background. The results provide evidence that SOA levels in natural indoor environments can surpass those known from chamber measurements. An indicator for the SOA forming potential of limonene was found to be limona ketone. Multiplying its concentration (in μg/m³) by 450(±100) provides an estimate of the concentration of the reacted limonene. This can be used to detect a high particle formation potential due to limonene pollution, e.g. in epidemiological studies considering adverse health effects of indoor air pollutants.