Development of Hourly Indoor PM2.5 Concentration Prediction Model: The Role of Outdoor Air, Ventilation, Building Characteristic, and Human Activity

Investigation of source and infiltration of toxic metals in indoor PM2.5 using Pb isotopes during a season of high pollution in an urban area

Lead (Pb) isotope ratio has been applied in source investigation for particulate matter in size < 2.5 μm. However, arsenic (As) and cadmium (Cd) are carcinogenic to human and their isotope analysis is difficult. This study investigated whether the Pb isotope ratio was a useful indicator in identifying the sources of As and Cd indoors and investigating its influencing factors. This study also calculated the infiltration factor (Finf) for metals to assess the influences of indoor- and outdoor-generated metals to indoor air. The As and Cd concentrations in indoor air were 0.87 ± 0.69 and 0.19 ± 0.15 ng/m3, respectively; the corresponding values for outdoor air were 1.44 ± 0.80 and 0.33 ± 0.19 ng/m3. The Finf of As and Cd were 0.60 ± 0.37 and 0.58 ± 0.39, and outdoor was a predominant contributor to indoor As and Cd. The Pb isotopes ratio indicated that traffic-related emission was a major contributor to Pb. The Pb concentration was associated with those of As and Cd in indoor or outdoor air, as was the 208Pb/207Pb ratio in outdoor air. Significant correlations between indoor 208Pb/207Pb values and As and Cd concentrations in indoor air were found only in study houses with air change rate > 1.5 h-1. These findings suggested that traffic-related emission was identified as a major source of As and Cr. The 208Pb/207Pb is a useful indicator in investigating the source of As and Cd; however, the air change rate influences the applicability of this approach on source identification.

LASSO and attention-TCN: a concurrent method for indoor particulate matter prediction

Long time exposure to indoor air pollution environments can increase the risk of cardiovascular and respiratory system damage. Most previous studies focus on outdoor air quality, while few studies on indoor air quality. Current neural network-based methods for indoor air quality prediction ignore the optimization of input variables, process input features serially, and still suffer from loss of information during model training, which may lead to the problems of memory-intensive, time-consuming and low-precision. We present a novel concurrent indoor PM prediction model based on the fusion model of Least Absolute Shrinkage and Selection Operator (LASSO) and an Attention Temporal Convolutional Network (ATCN), together called LATCN. First, a LASSO regression algorithm is used to select features from PM1, PM2.5, PM10 and PM (>10) datasets and environmental factors to optimize the inputs for indoor PM prediction model. Then an Attention Mechanism (AM) is applied to reduce the redundant temporal information to extract key features in inputs. Finally, a TCN is used to forecast indoor particulate concentration in parallel with inputting the extracted features, and it reduces information loss by residual connections. The results show that the main environmental factors affecting indoor PM concentration are the indoor heat index, indoor wind chill, wet bulb temperature and relative humidity. Comparing with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) approaches, LATCN systematically reduced the prediction error rate (19.7% ~ 28.1% for the NAE, and 16.4% ~ 21.5% for the RMSE) and improved the model running speed (30.4% ~ 81.2%) over these classical sequence prediction models. Our study can inform the active prevention of indoor air pollution, and provides a theoretical basis for indoor environmental standards, while laying the foundations for developing novel air pollution prevention equipment in the future.

Trends in elemental Pb concentrations within atmospheric PM2.5 and associated risk to human health in major cities of China

High concentrations of elemental lead (Pb) in the atmosphere pose a serious threat to human health. This study presents and summarizes data obtained from relevant literature on Pb concentrations within fine particulate matter (PM_2.5) recorded in major cities in China from 2008 to 2019. An environmental health risk assessment model was then used to evaluate the health hazards of inhaling Pb among adults and children in China. Owing to the promulgation and implementation of a series of air pollution control measures, the Pb concentrations within PM_2.5 measured in major cities in China showed a downward trend after peaking in 2013. The concentrations were higher in winter than in summer, and higher in northern cities than in southern cities. Although the Pb concentrations in most cities did not exceed the limit (500 ng/m³) set by China, they remained much higher than concentrations recorded in developed countries. The results of the environmental health risk analysis showed that the non-carcinogenic risk from atmospheric Pb exposure was higher in children than in adults (adult females > adult males), while the carcinogenic risk was higher in adults than in children. This study shows that even if the health risk of Pb in PM_2.5 does not exceed the acceptable limit, stricter Pb pollution control measures are required to safeguard population health due to the dangers of Pb.

Personal PM2.5 Elemental Components, Decline of Lung Function, and the Role of DNA Methylation on Inflammation-Related Genes in Older Adults: Results and Implications of the BAPE Study

Epidemiological evidence of the effects of PM_2.5 elements on lung function and DNA methylation is limited. We conducted a longitudinal panel study of 76 healthy older adults aged 60-69 years in Jinan, China, from September 2018 to January 2019. We periodically measured individual 72 h PM_2.5 and element concentrations, lung function, and DNA methylation levels of eight inflammation-related genes. We used linear mixed-effect models to investigate the effects of exposure to personal PM_2.5 elements on the lung function and DNA methylation. Mediation analysis was used to investigate the underlying effect mechanism. Negative changes in the ratio of forced expiratory volume in 1 s to forced vital capacity, ranging from -1.23% [95% confidence interval (CI): -2.11%, -0.35%] to -0.77% (95% CI: -1.49%, -0.04%), were significantly associated with interquartile range (IQR) increases in personal PM_2.5 at different lag periods (7-12, 13-24, 25-48, 0-24, 0-48, and 0-72 h). Arsenic (As), nickel, rubidium (Rb), selenium, and vanadium were significantly associated with at least three lung function parameters, and IQR increases in these elements led to 0.12-5.66% reductions in these parameters. PM_2.5 elements were significantly associated with DNA methylation levels. DNA methylation mediated 7.28-13.02% of the As- and Rb-related reduced lung function. The findings indicate that exposure to elements in personal PM_2.5 contributes to reduced lung function through DNA methylation.

Early pregnancy PM2.5 exposure and its inorganic constituents affect fetal growth by interrupting maternal thyroid function

Early pregnancy is crucial for fetal growth. Maternal thyroid hormone is critical for fetal growth and can be disturbed under exogenous exposure. However, it's uncertain whether exposure to PM_2.5 and inorganic constituents during early pregnancy can affect TH and fetal growth. We focused on the associations of early-pregnancy PM_2.5 and inorganic constituents with fetal growth and maternal THs. PM_2.5 concentration was estimated using a satellite-based spatiotemporal model. Fetal biparietal diameter (BPD), head circumference (HC), femur length (FL), and humerus length (HL) were measured by ultrasonography at median 15.6, 22.2, and 33.1 gestational weeks. Levels of 28 PM_2.5 constituents were measured in a sub-group of 329 pregnancies. Maternal serum free thyroxine (fT4), free triiodothyronine, and thyroid-stimulating hormone levels were measured at 14 weeks of gestation. Mixed-effect models and multiple linear regression were applied to evaluate the associations of PM_2.5 and its constituents with fetal growth measures. Mediation analysis was used to examine the mediating role of the THs. Results showed that each 10 μg/m³ increase in PM_2.5 was associated with 0.20 mm reductions in BPD (95%CI: 0.33, -0.01), 0.27 mm decreases in FL (95%CI: 0.40, -0.13), and 0.36 decreases in HL (95%CI: 0.49, -0.23). Per 10 μg/m³ increment in PM_2.5 was correlated with 5.82% decreases in the fT4 level (95% CI: 8.61%, -2.96%). FT4 accounted for 14.3% of PM_2.5 exposure-induced change in BPD at first follow-up. Al (β = -2.91, 95%CI: 5.17, -0.66), Si (β = -1.20, 95%CI: 2.22, -0.19), K (β = -3.09, 95%CI: 5.41, -0.77), Mn (β = -47.20, 95%CI: 83.68, -10.79) and Zn (β = -3.02, 95%CI: 5.55, -0.49) were associated with decreased fetal BPD, especially in first follow-up. Zn (β = -38.12%, 95% CI: 58.52%, -8.61%) was also associated with decreased fT4 levels. Overall, early pregnancy exposure to PM_2.5 and its constituents was associated with fetal growth restriction and decreased maternal fT4 levels might mediate the effect of PM_2.5.

Long-Term Exposure to Fine Particulate Matter and the Deterioration of Estimated Glomerular Filtration Rate: A Cohort Study in Patients With Pre-End-Stage Renal Disease

Limited literature has explored the effect of air pollutants on chronic kidney disease (CKD) progression, especially for patients with pre-end-stage renal disease (pre-ESRD). In this study, we reported the linear and nonlinear relationships of air pollutants of particles with diameter <2.5 μm (PM2.5) and nitrogen dioxide (NO2) with estimated glomerular filtration rate (eGFR) deterioration after adjusting for smoking status and other traditional clinical factors. This study adopted a retrospective cohort of patients with stage 3b to stage 5 CKD (N = 11,479) from Taichung Veterans General Hospital during January 2006 to December 2020. The eGFR deterioration was defined as a decline in eGFR > 5 ml/min/1.73 m2/year. Hybrid kriging/land-use regression models were used to estimate the individual exposure levels of PM2.5 and NO2. The relationships of air pollutants with eGFR deterioration were evaluated using Cox proportional hazard models. After adjusting for smoking status, baseline eGFR stages, and other traditional clinical factors, the risk of eGFR deterioration was found to increase with increasing PM2.5 and NO2 level (p < 0.0001 and p = 0.041, respectively), especially for those exposed to PM2.5 ≥ 31.44 μg/m3 or NO2 ≥ 15.00 ppb. Similar results were also found in the two-pollutant models. Nonlinear dose-response relationships of eGFR deterioration were observed for concentrations of 26.11 μg/m3 for PM2.5 and 15.06 ppb for NO2. In conclusion, linear and nonlinear associations between PM2.5 and NO2 levels and the incidence risk of eGFR deterioration were observed in patients with pre-ESRD.