While infants are developing, they are easily affected by toxic chemicals existing in their environments, such as semi-volatile organic compounds (SVOCs): phthalates, polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), and organophosphate esters (OPEs). However, the specific living environment of infants, including increased plastic products and foam floor mats, may increase the presence of these chemicals. In this study, 68 air, dust, and window film samples were collected from homes, with 3- to 6-month-old infant occupants, to analyze phthalates, PAHs, PBDEs, and OPEs. High detection rates and concentrations suggest that these SVOCs are widespread in infant environments and are associated with cooking methods, smoking habits, the period of time after decoration, and room floors. The partitioning behavior of SVOCs indicates that the logarithms of the dust/gas-phase air partition coefficient (logKD) and the window film/gas-phase air partition coefficient (logKF) in homes are not at an equilibrium state when the logarithm of the octanol/air partition coefficient (logKOA) is less than 8 or greater than 11. Considering the 3 exposure routes, ingestion and dermal absorption have become the main routes of infant exposure to phthalates and OPEs, and ingestion and inhalation have become the dominant routes of exposure to PAHs and PBDEs. The total carcinogenic risk of SVOCs, which have carcinogenic toxicities, via ingestion and dermal absorption for infants in homes exceeds the acceptable value, suggesting that the current levels of these SVOCs in homes might pose a risk to infant health.

Two hundred sixty-three fine particulate matter (PM₂.₅) samples were collected over fourteen months in Fresno and Bakersfield, California. Samples were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and 160 organic molecular markers. Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) source apportionment models were applied to the results in order to understand monthly and seasonal source contributions to PM₂.₅ OC. Similar source categories were found from the results of the CMB and PMF models to PM₂.₅ OC across the sites. Six source categories with reasonably stable profiles, including biomass burning, mobile, food cooking, two different secondary organic aerosols (SOAs) (i.e., winter and summer), and forest fires were investigated. Both the CMB and the PMF models showed a strong seasonality in contributions of some sources, as well as dependence on wind transport for both sites. The overall relative source contributions to OC were 24% CMB wood smoke, 19% CMB mobile sources, 5% PMF food cooking, 2% CMB vegetative detritus, 17% PMF SOA summer, 22% PMF SOA winter, and 12% PMF forest fire. Back-trajectories using the Weather Research and Forecasting model combined with the FLEXible PARTicle dispersion model (WRF-FLEXPART) were used to further characterize wind transport. Clustering of the trajectories revealed dominant wind patterns associated with varying concentrations of the different source categories. The Comprehensive Air Quality Model with eXtensions (CAMx) was used to simulate aerosol transport from forest fires and thus confirm the impacts of individual fires, such as the Rough Fire, at the measurement sites.

Selenium (Se) is an essential micronutrient for animals and humans with a relatively narrow margin between nutritional essentiality and potential toxicity. Even though our previous studies have demonstrated algae could efficiently remove Se, mainly through volatilization, concern is raised about eco-risks posed by the remaining Se in algae. Here, Sinanodonta woodiana was investigated as a biofilter for the removal of Se-containing Chlorella vulgaris and for its potential risk to human health. Our results suggest filtration rates of S. woodiana were independent of Se levels in algal biomass, with a removal efficiency of between 60 and 78%. However, Se concentrations accumulated in mussels were significantly correlated with algal-borne Se levels, with a dietary assimilation efficiency ranging from 12% to 46%. Thus, a pilot biofiltration system was set up to assess uptake and depuration processes. The system was found to efficiently remove Se laden algae through the uptake by mussels, while 21% of Se in mussels could be depurated in 6 days. Among tissues, gills accumulated the highest Se concentration after assimilating algal-borne Se but shed Se compounds in the fastest pace during depuration. Health risks posed by consumption of mussels exposed to different sources of Se were further assessed. S. woodiana accumulated the highest Se concentration after exposure to waterborne SeMet, followed by dietary Se, selenite and control. The relatively higher Se levels were found in gills for all the treatments. After boiling, the most common method of cooking mussels, the greatest reduction in Se concentration occurred in mantle for the control and dietary Se groups and in muscle for the SeMet and selenite treatments. Therefore, within the safe limits, Se-containing mussels can be consumed as a dietary supplement. Overall, our research suggests incorporation of mussels into an algal treatment system can improve Se removal efficiency and also provide financial incentives for practitioners.

To illustrate chemical characteristic of PM2.5 emission and assess inhalational carcinogenic risk of domestic Chinese cooking, 5 sets of duplicate cooking samples were collected, using the most used 5 types of oil. The mass abundance of 14 elements, 5 water-soluble ions, organic carbon (OC), elemental carbon (EC) and 11 polycyclic aromatic hydrocarbons (PAHs) were calculated; the signature and diagnostic ratio of cooking in the domestic kitchen were analyzed; and carcinogenic risks of heavy metals and PAHs via inhalation were assessed in two scenarios. The analysis showed that OC was the primary composition in the chemical profile; Na was the most abundant element that might be due to the usage of salt; Cr and Pb, NO3− and SO42-, Phe, FL and Pyr were the main heavy metals/water-soluble ions/PAHs, respectively. Phe and FL could be used to separate cooking and stationary sources, while diagnostic ratios of BaA/(BaA + CHR), BaA/CHR, BaP/BghiP and BaP/BeP should be applied with caution, as they were influenced by various cooking conditions. Carcinogenic risks of heavy metals and PAHs were evaluated in two scenarios, simulating the condition of cooking with no ventilation and with the range hood on, respectively. The integrated risk of heavy metals and PAHs was 2.7 × 10−3 and 5.8 × 10−6, respectively, during cooking with no ventilation. While with the usage of range hood, only Cr(VI), As and Ni might induce potential carcinogenic risk. The difference in the chemical abundance in cooking sources found between this and other studies underlined the necessity of constructing locally representative source profiles under real conditions. The comparison of carcinogenic risk suggested that the potentially adverse health effects induced by inorganic compositions from cooking sources should not be ignored. Meanwhile, intervention methods, such as the operation of range hood, should be applied during cooking for health protection.

Because people spend most of their time indoors, the characterization of indoor air quality is important for exposure assessment. Unfortunately, indoor air data are scarce, leading to a major data gap in risk assessment. In this study, PM2.5 concentrations in both indoor and outdoor air were simultaneously measured using on-line particulate counters in 13 households in Haidian, Beijing for both heating and non-heating seasons. A bimodal distribution of PM2.5 concentrations suggests rapid transitions between polluted and non-polluted situations. The PM2.5 concentrations in indoor and outdoor air varied synchronously, with the indoor variation lagging. The lag time in the heating season was longer than that in the non-heating season. The particle sizes in indoor air were smaller than those in ambient air in the heating season and vice versa in the non-heating season. PM2.5 concentrations in indoor air were generally lower than those in ambient air except when ambient concentrations dropped sharply to very low levels or there were internal emissions from cooking or other activities. The effectiveness of an air cleaner to reduce indoor PM2.5 concentrations was demonstrated. Non-linear regression models were developed to predict indoor air PM2.5 concentrations based on ambient data with lag time incorporated. The models were applied to estimate the overall population exposure to PM2.5 and the health consequences in Haidian. The health impacts would be significantly overestimated without the indoor exposure being taken into consideration, and this bias would increase as the ambient air quality improved in the future.

Human exposure to polycyclic aromatic hydrocarbons (PAHs) in indoor environments can be particularly relevant because people spend most of their time inside buildings, especially in homes. This study aimed to investigate the most important particle-bound PAH sources and exposure determinants in PM2.5 samples collected in 19 homes located in northern Italy. Complementary information about ion content in PM10 was also collected in 12 of these homes. Three methods were used for the identification of PAH sources and determinants: diagnostic ratios with principal component and hierarchical cluster analyses (PCA and HCA), chemical mass balance (CMB) and linear mixed models (LMMs). This combined and tiered approach allowed the infiltration of outdoor PAHs into indoor environments to be identified as the most important source in winter, with a relevant role played by biomass burning and traffic exhausts to be identified as a general source of PAHs in both seasons. Tobacco smoke exhibited an important impact on PAH levels in smokers' homes, whereas in the whole sample, cooking food and natural gas sources played a minor or negligible role. Nitrate, sulfate and ammonium were the main inorganic constituents of indoor PM10 owing to the secondary formation of ammonium sulfates and nitrates.

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.

Exposure to air pollution has been linked to elevated blood pressure (BP) and hypertension, but most research has focused on short-term (hours, days, or months) exposures at relatively low concentrations. We examined the associations between long-term (3-year average) concentrations of outdoor PM₂.₅ and household air pollution (HAP) from cooking with solid fuels with BP and hypertension in the Prospective Urban and Rural Epidemiology (PURE) study. Outdoor PM₂.₅ exposures were estimated at year of enrollment for 137,809 adults aged 35–70 years from 640 urban and rural communities in 21 countries using satellite and ground-based methods. Primary use of solid fuel for cooking was used as an indicator of HAP exposure, with analyses restricted to rural participants (n = 43,313) in 27 study centers in 10 countries. BP was measured following a standardized procedure and associations with air pollution examined with mixed-effect regression models, after adjustment for a comprehensive set of potential confounding factors. Baseline outdoor PM₂.₅ exposure ranged from 3 to 97 μg/m³ across study communities and was associated with an increased odds ratio (OR) of 1.04 (95% CI: 1.01, 1.07) for hypertension, per 10 μg/m³ increase in concentration. This association demonstrated non-linearity and was strongest for the fourth (PM₂.₅ > 62 μg/m³) compared to the first (PM₂.₅ < 14 μg/m³) quartiles (OR = 1.36, 95% CI: 1.10, 1.69). Similar non-linear patterns were observed for systolic BP (β = 2.15 mmHg, 95% CI: −0.59, 4.89) and diastolic BP (β = 1.35, 95% CI: −0.20, 2.89), while there was no overall increase in ORs across the full exposure distribution. Individuals who used solid fuels for cooking had lower BP measures compared to clean fuel users (e.g. 34% of solid fuels users compared to 42% of clean fuel users had hypertension), and even in fully adjusted models had slightly decreased odds of hypertension (OR = 0.93; 95% CI: 0.88, 0.99) and reductions in systolic (−0.51 mmHg; 95% CI: −0.99, −0.03) and diastolic (−0.46 mmHg; 95% CI: −0.75, −0.18) BP. In this large international multi-center study, chronic exposures to outdoor PM₂.₅ was associated with increased BP and hypertension while there were small inverse associations with HAP.

Indoor air contributes significantly to overall exposure, particularly for rural Chinese who often use solid fuels for cooking and/or heating. Unfortunately, overlooked rural indoor air leads to a critical knowledge gap. Simultaneous measurements in the kitchen, living room, and immediately outside of houses using six-channel particle counters were carried out in 18 biomass-burning rural and 3 non-biomass-burning urban households (as a comparison) in winter to characterize dynamic change patterns indoor air pollution and indoor-outdoor relationship. The rural households mainly used wood or crop residues for cooking and heating, while the urban households used pipelined natural gas for cooking and air conditioners for heating. In rural households with significant solid-fuel burning internal sources, the highest concentration was found in the kitchen (101 ± 56 μg/m³), with comparable levels in the living room (99 ± 46 μg/m³) and low levels in outdoor air (91 ± 39 μg/m³). A generally opposite direction of indoor-outdoor exchange was found between the rural and urban households. PM in kitchen air is smaller than that in living rooms and outdoors because solid fuel burning (mainly in rural households) and cooking oil heating (in rural and urban households). Indoor and outdoor PM concentration changed synchronously, with a slight delay in indoor air in urban households but a slight delay in outdoor air in rural households. Cooking, heating, and smoking elevated indoor PM significantly, but different from the cooking activity that produced peaks lasting for about 30 min, emissions from heating created a series of peaks due to frequent disturbance and fuel-feeding and had more significant impacts on the daily average concentration. Distinct indoor-outdoor relationships and dynamic change patterns between the two household categories w/o strong internal biomass burning sources imply that totally different model schemes are needed to quantitatively address indoor air pollution and inhalation exposure.

Smoky coal burning is a predominant manner for heating and cooking in most rural areas, China. Air pollution is associated with the risk of atherosclerosis, however, the link between indoor air pollution induced by smoky coal burning and atherosclerosis is not very clear. Therefore, we designed a cross-sectional study to evaluate the association of long-term exposure to smoky coal burning pollutants with the risk of atherosclerosis. 426 and 326 participants were recruited from Nangong, China and assigned as the coal exposure and control group according to their heating and cooking way, respectively. The indoor air quality (PM2.5, CO, SO₂) was monitored. The association between coal burning exposure and the prevalence of atherosclerosis was evaluated by unconditional logistic regression analysis, adjusted for confounding factors. The inflammatory cytokines mRNAs (IL-8, SAA1, TNF-α, CRP) expression in whole blood were examined by qPCR. People in the coal exposure group had a higher risk of carotid atherosclerosis compared with the control (risk ratio [RR], 1.434; 95% confidence interval [95%CI], 1.063 to 1.934; P = 0.018). The association was stronger in smokers, drinkers and younger (<45 years old) individuals. The elevation of IL-8 (0.24, 95%CI, 0.06–0.58; P < 0.05), CRP (0.37, 95%CI, 0.05–0.70; P < 0.05), TNF-α (0.41, 95%CI, 0.14–0.67; P < 0.01) mRNAs expression in whole blood were positively related to coal exposure. Our results suggested long-term exposure to smoky coal burning emissions could increase the risk of carotid atherosclerosis. The potential mechanism might relate that coal burning emissions exposure induced inflammatory cytokines elevation which had adverse effects on atherosclerotic plaque, and then promoted the development of atherosclerosis.