The fetus is prenatally exposed to a mixture of organochlorine pesticides (OCPs), mercury (Hg), docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and selenium (Se) through maternal seafood consumption in real-life scenario. Prenatal exposure to these contaminants and nutrients has been suggested to affect thyroid hormone (TH) status in newborns, but the potential relationships between them are unclear and the joint effects of the mixture are seldom analyzed. The aim of the study is to investigate the associations of prenatal exposure to a mixture of OCPs, Hg, DHA, EPA and Se with TH parameters in newborns. 228 mother-infant pairs in Shanghai, China were included. We measured 20 OCPs, total Hg, DHA, EPA and Se in cord blood samples as exposure variables. The total thyroxine (TT4), free thyroxine (FT4), total triiodothyronine (TT3), free triiodothyronine (FT3), and thyroid-stimulating hormone (TSH) levels and the FT3/FT4 ratio in cord serum were determined as outcomes. Using linear regression models, generalized additive models and Bayesian kernel machine regression, we found dose-response relationships of the mixture component with outcomes: among the contaminants, p,p'-DDE was the most important positive predictor of TT3, while HCB was predominantly positively associated with FT3 and the FT3/FT4 ratio, indicating different mechanisms underlying these relationships; among the nutrients, EPA was first found to be positively related to the FT3/FT4 ratio. Additionally, we found suggestive evidence of interactions between p,p'-DDE and HCB on both TT3 and FT3, and EPA by HCB interactions for TT3, FT3 and FT3/FT4 ratio. However, the overall effects of the mixture on thyroid hormone parameters were not significant. Our result suggests that prenatal exposure to p,p’-DDE, HCB and EPA as part of a mixture might affect thyroid function of newborns in independent and interactive ways. The potential biological mechanisms merit further investigation.

China is the largest CO₂ emitting country on Earth. During the COVID-19 pandemic, China implemented strict government control measures on both outdoor activity and industrial production. These control measures, therefore, were expected to significantly reduce anthropogenic CO₂ emissions. However, large discrepancies still exist in the estimated anthropogenic CO₂ emission reduction rate caused by COVID-19 restrictions, with values ranging from 10% to 40% among different approaches. Here, we selected Nanchang city, located in eastern China, to examine the impact of COVID-19 on CO₂ emissions. Continuous atmospheric CO₂ and ground-level CO observations from January 1st to April 30th, 2019 to 2021 were used with the WRF-STILT atmospheric transport model and a priori emissions. And a multiplicative scaling factor and Bayesian inversion method were applied to constrain anthropogenic CO₂ emissions before, during, and after the COVID-19 pandemic. We found a 37.1–40.2% emission reduction when compared to the COVID-19 pandemic in 2020 with the same period in 2019. Carbon dioxide emissions from the power industry and manufacturing industry decreased by 54.5% and 18.9% during the pandemic period. The power industry accounted for 73.9% of total CO₂ reductions during COVID-19. Further, emissions in 2021 were 14.3–14.9% larger than in 2019, indicating that economic activity quickly recovered to pre-pandemic conditions.

Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM₂.₅, PM₁₀, NO₂, SO₂, O₃ and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O₃ had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O₃-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O₃ in the future.

Adipokines, cytokines secreted by adipose tissue, may contribute to obesity-related metabolic disease. The role of environmental phenols and parabens in racial difference in metabolic disease burden has been suggested, but there is limited evidence. We examined the cross-sectional associations of urinary phenols and parabens with adipokines and effect modification by race. Urinary concentrations of 6 phenols (bisphenol-A, bisphenol-F, 2,4-diclorophenol, 2,5-diclorophenol, triclosan, benzophenone-3) and 4 parabens (methyl-paraben, ethyl-paraben, propyl-paraben, butyl-paraben) were measured in 2002–2003 among 1200 women (mean age = 52.6) enrolled in the Study of Women's Health Across the Nation Multi-Pollutant Study. Serum adipokines included adiponectin, high molecular weight (HMW)-adiponectin, leptin, soluble leptin receptor (sOB-R). Linear regression models were used to estimate the adjusted percentage change in adipokines per inter-quantile range (IQR) increase in standardized and log-transformed levels of individual urinary phenols and parabens. Bayesian kernel machine regression (BKMR) was used to evaluate the joint effect of urinary phenols and parabens as mixtures. Participants included white (52.5%), black (19.3%), and Asian (28.1%) women. Urinary 2,4-dichlorophenol was associated with 6.02% (95% CI: 1.20%, 10.83%) higher HMW-adiponectin and urinary bisphenol-F was associated with 2.60% (0.48%, 4.71%) higher sOB-R. Urinary methyl-paraben was associated with lower leptin in all women but this association differed by race: 8.58% (−13.99%, −3.18%) lower leptin in white women but 11.68% (3.52%, 19.84%) higher leptin in black women (P interaction = 0.001). No significant associations were observed in Asian women. Additionally, we observed a significant positive overall effect of urinary phenols and parabens mixtures in relation to leptin levels in black, but not in white or Asian women. Urinary bisphenol-F, 2,4-dichlorophenol and methyl-paraben may be associated with favorable profiles of adipokines, but methyl-paraben, widely used in hair and personal care products, was associated with unfavorable leptin levels in black women. Future studies are needed to confirm this racial difference.

Metals may affect adversely cardiovascular system, but epidemiological evidence on the associations of priority-controlled metals including antimony (Sb), arsenic (As), cadmium, lead, and thallium with children's blood pressure (BP) was scarce and inconsistent. We conducted two panel studies with 3 surveys across 3 seasons among 144 and 142 children aged 4–12 years in Guangzhou and Weinan, respectively. During each seasonal survey, urine samples were collected for 4 consecutive days and BP was measured on the 4th day. We obtained 786 BP values and urinary metals measurements at least once within 4 days, while 773, 596, 612, and 754 urinary metals measurements were effective on the health examination day (Lag 0), and the 1ˢᵗ, 2ⁿᵈ, and 3ʳᵈ day preceding BP measurement (Lag 1, lag 2 and lag 3), respectively. We used linear mixed-effect models, generalized estimating equations and multiple informant models to assess the associations of individual metal at each lag day and accumulated lag day (4 days averaged, lag 0–3) with BP and hypertension, and Bayesian Kernel Machine Regression to evaluate the relations of metals mixture at lag 0–3 and BP outcomes. We found Sb was positively and consistently related to systolic BP (SBP), mean arterial pressure (MAP), and odds of having hypertension within 4 days, which were the strongest at lag 0 and declined over time. And such relationships at lag 0–3 showed in a dose-response manner. Meanwhile, Sb was the only contributor to the relations of mixture with SBP, MAP, and odds of having hypertension. Also, synergistic interaction between Sb and As was significant. In addition, modification effect of passive smoking status on the association of Sb and SBP was more evident in passive smokers. Accordingly, urinary Sb was consistently and dose-responsively associated with increased BP and hypertension, of which Sb was the major contributor among children.

One of the best approaches for improving the assessment of metal toxicity in aquatic organisms is to study their organotropism (i.e., the distribution of metals among organs) through a dynamical approach (i.e., via kinetic experiments of metal bioaccumulation), to identify the tissues/organs that play a key role in metal regulation (e.g., storage or excretion). This study aims at comparing the organ-specific metal accumulation of a non-essential (Cd) and an essential metal (Zn), at their environmentally relevant exposure concentrations, in the gammarid Gammarus fossarum. Gammarids were exposed for 7 days to ¹⁰⁹Cd- or ⁶⁵Zn-radiolabeled water at a concentration of 52.1 and 416 ng.L⁻¹ (stable equivalent), respectively, and then placed in clean water for 21 days. At different time intervals, the target organs (i.e., caeca, cephalons, intestines, gills, and remaining tissues) were collected and ¹⁰⁹Cd or ⁶⁵Zn contents were quantified by gamma-spectrometry. A one-compartment toxicokinetic (TK) model was fitted by Bayesian inference to each organ/metal dataset in order to establish TK parameters. Our results indicate: i) a contrasting distribution pattern of concentrations at the end of the accumulation phase (7ᵗʰ day): gills > caeca ≈ intestines > cephalons > remaining tissues for Cd and intestines > caeca > gills > cephalons > remaining tissues for Zn; ii) a slower elimination of Cd than of Zn by all organs, especially in the gills in which the Cd concentration remained constant during the 21-day depuration phase, whereas Zn concentrations decreased sharply in all organs after 24 h in the depuration phase; iii) a major role of intestines in the uptake of waterborne Cd and Zn at environmentally relevant concentrations.

Exposure to metals has been linked with the risk of hypertensive disorders of pregnancy (HDP), but little is known about the potential effects of exposure to metal mixtures. Thus, our study aimed to investigated the impact of a complex mixture of metals on HDP, especially the interactions among metal mixtures. We did a population-based nested case-control study from October 2013 to October 2016 in Wuhan, China, including 146 HDP cases and 292 controls. Plasma concentrations of Aluminum (Al), Barium (Ba), Cobalt (Co), Copper (Cu), Lead (Pb), Mercury (Hg), Molybdenum (Mo), Nickel (Ni), Selenium (Se), Strontium (Sr), Thallium (Tl), and Vanadium (V) were measured and collected between 10 and 16 gestational weeks. We employed quantile g-computation, conditional logistic regression models, and Bayesian Kernel Machine Regression (BKMR) to assess the association of individual metals and metal mixtures with HDP risk. In the quantile g-computation, the OR for a joint tertile increase in plasma concentrations was 3.67 (95% CI: 1.70, 7.91). Hg contributed the largest positive weights and followed by Al, Ni, and V. In conditional logistic regression models, concentrations of Hg, Al, Ni, and V were significantly associated with the risk of HDP (p-FDR < 0.05). Compared to the lowest tertiles, the ORs (95% CI) for the highest tertiles of these four metals were 2.67 (1.44, 4.95), 3.09 (1.70, 5.64), 5.31 (2.68, 10.53), and 4.52 (2.26, 9.01), respectively. In the BKMR analysis, we observed a linear positive association between Hg, Al, V, and HDP, and a nonlinear relationship between Ni and HDP. A potential interaction between Al and V was also identified. We found that exposure to metal mixtures in early pregnancy, both individually and as a mixture, was associated with the risk of HDP. Potential interaction effects of Al and V on the risk of HDP may exist.

The association of co-exposure to polycyclic aromatic hydrocarbons (PAHs) and phthalates (PAEs) with blood cell-based inflammatory biomarkers is largely unknown. We conducted a panel study of 144 children aged 4–12 years, with up to 3 repeated visits across 3 seasons. For each visit, we collected the first-morning urine for 4 consecutive days and fasting blood on the day of physical examination. We developed a gas chromatography/tandem mass spectrometry method to detect the metabolites of 10 PAHs (OH-PAHs) and 10 PAEs (mPAEs) in urine samples. We employed linear mixed-effects models to evaluate the individual associations of each OH-PAH and mPAE with blood cell-based inflammatory biomarkers over different lag times. Bayesian kernel machine regression (BKMR) and quantile g-computation were used to evaluate the overall associations of OH-PAHs and mPAEs mixtures with blood cell-based inflammatory biomarkers. After multiple adjustments, we found positive associations of summed hydroxylphenanthrene (∑OHPHE), summed OH-PAHs, and mono-n-butyl phthalate with inflammatory biomarkers such as neutrophil count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and the systemic immune-inflammation index (SII) at lag 0 (the day of physical examination). Each 1% increase in ∑OHPHE was related to a 0.18% (95% confidence interval: 0.10%, 0.25%) increase in SII, which was the strongest among the above associations. The results of BKMR and quantile g-computation suggested that co-exposure to PAHs and PAEs mixture was associated with an elevated white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and SII, to which ∑OHPHE and 1-hydroxypyrene (1-OHPYR) might be the major contributors. In addition, gender and age modified the associations of ∑OHPHE and 1-OHPYR with inflammatory biomarkers, where girls and younger children were more susceptible. In conclusion, co-exposure to PAHs and PAEs was associated with elevated inflammation in children, in which ∑OHPHE and 1-OHPYR might play important roles.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Applying mineral phosphorus (P) fertilizers introduces a considerable input of the toxic heavy metal cadmium (Cd) into arable soils. This study investigates the fate of P fertilizer derived Cd (Cddff) in soil-wheat systems using a novel combination of enriched stable Cd isotope mass balances, sequential extractions, and Bayesian isotope mixing models. We applied an enriched ¹¹¹Cd labeled mineral P fertilizer to arable soils from two long-term field trials with distinct soil properties (a strongly acidic pH and a neutral pH) and distinct past mineral P fertilizer application rates. We then cultivated wheat in a pot trial on these two soils. In the neutral soil, Cd concentrations in the soil and the wheat increased with increasing past mineral P fertilizer application rates. This was not the case in the strongly acidic soil. Less than 2.3% of freshly applied Cddff was taken up by the whole wheat plant. Most of the Cddff remained in the soil and was predominantly (>95% of freshly applied Cddff) partitioned into the easily mobilizable acetic acid soluble fraction (F1) and the potentially mobile reducible fraction (F2). Soil pH was the determining factor for the partitioning of Cddff into F1, as revealed through a recovery of about 40% of freshly applied Cddff in F1 in the neutral pH soil compared with about 60% in the strongly acidic soil. Isotope mixing models showed that F1 was the predominant source of Cd for wheat on both soils and that it contributed to over 80% of the Cd that was taken up by wheat. By tracing the fate of Cddff in entire soil-plant systems using different isotope source tracing approaches, we show that the majority of Cddff remains mobilizable and is potentially plant available in the subsequent crop cycle.