Characterization of VOC emissions and health risk assessment in the plastic manufacturing industry.

Volatile organic compounds (VOCs) significantly contribute to ozone pollution formation, and many VOCs are known to be harmful to human health. Plastic has become an indispensable material in various industries and daily use scenarios, yet the VOC emissions and associated health risks in the plastic manufacturing industry have received limited attention. In this study, we conducted sampling in three typical plastic manufacturing factories to analyze the emission characteristics of VOCs, ozone formation potential (OFP), and health risks for workers. Isopropanol was detected at relatively high concentrations in all three factories, with concentrations in organized emissions reaching 322.3 µg/m3, 344.8 µg/m3, and 22.6 µg/m3, respectively. Alkanes are the most emitted category of VOCs in plastic factories. However, alkenes and oxygenated volatile organic compounds (OVOCs) exhibit higher OFP. In organized emissions of different types of VOCs in the three factories, alkenes and OVOCs contributed 22.8%, 67%, and 37.8% to the OFP, respectively, highlighting the necessity of controlling them. The hazard index (HI) for all three factories was less than 1, indicating a low non-carcinogenic toxic risk; however, there is still a possibility of non-cancerous health risks in two of the factories, and a potential lifetime cancer risk in all of the three factories. For workers with job tenures exceeding 5 years, there may be potential health risks, hence wearing masks with protective capabilities is necessary. This study provides evidence for reducing VOC emissions and improving management measures to ensure the health protection of workers in the plastic manufacturing industry.

PM2.5 pollution modulates the response of ozone formation to VOC emitted from various sources: Insights from machine learning.

Numerous studies have linked ozone (O3) production to its precursors and fine particulate matter (PM2.5), while the complex interaction effects of PM2.5 and volatile organic compounds (VOCs) on O3 remain poorly understood. A systematic approach based on an interpretable machine learning (ML) model was utilized to evaluate the primary driving factors that impact O3 and to elucidate how changes in PM2.5, VOCs from different sources, NOx, and meteorological conditions either promote or inhibit O3 formation through their individual and synergistic effects in a tropical coastal city, Haikou, from 2019 to 2020. The results suggest that under low PM2.5 levels, alongside the linear O3-PM2.5 relationship observed, O3 formation is suppressed by PM2.5 with higher proportions of traffic-derived aerosol. Vehicle VOC emissions contributed maximally to O3 formation at midday, despite the lowest concentration. VOCs from fossil fuel combustion and industry emissions, which have opposing effects on O3, act as inhibitors and promoters by inducing diverse photochemical regimes. As PM2.5 pollution escalates, the impact of these VOCs reverses, becoming more pronounced in shaping O3 variation. Sensitivity analysis reveals that the O3 formation regime is VOC-limited, and effective regional O3 mitigation requires prioritizing substantial VOC reductions to offset enhanced VOC sensitivity induced by the co-reduction in PM2.5, with a focus on industrial and vehicular emissions, and subsequently, fossil fuel combustion once PM2.5 is effectively controlled. This study underscores the potential of the SHAP-based ML approach to decode the intricate O3-NOx-VOCs-PM2.5 interplay, considering both meteorological and atmospheric compositional variations.

Significant spatiotemporal changes in atmospheric particulate mercury pollution in China: Insights from meta-analysis and machine-learning.

PM2.5 bound mercury (PBM2.5) in the atmosphere is a major component of total mercury, which is a pollutant of global concern and a potent neurotoxicant when converted to methylmercury. Despite its importance, comprehensive macroanalyses of PBM2.5 on large scales are still lacking. To explore the driving factors, spatiotemporal pollution distribution, and associated health risks, we compiled a comprehensive dataset consisting of PBM2.5 concentrations and spatiotemporal information across China from 2000 to 2023 that was collected from the published scientific literature with valid data. By incorporating corresponding multidimensional predicting variables, the best-fitted random forest model was applied to predict PBM2.5 concentrations with a high spatial resolution of 0.25°â€¯× 0.25°, and the health risk assessment model was used for subsequent health risk assessment. Our results indicated that population density and PM2.5 emissions from power generation were the main contributors to PBM2.5 concentrations. In 2020, the pollution was primarily concentrated in northern, central, and eastern China, with the highest annual average concentration of 815.91 pg/m3 in Shanghai. Beijing experienced the most significant seasonal increase, with PBM2.5 concentrations rising by 146.92 % from summer to winter. Nationally, the annual average PBM2.5 pollution decreased extensively and markedly from 2015 to 2020. The non-carcinogenic risk of PBM2.5 alone was negligible in 2020, with HQ values generally <0.02 in winter. This study may provide an important assessment of the effectiveness of China's measures against mercury pollution and offer valuable insights for future prevention and control of PBM2.5 pollution.

A machine learning-based study on the impact of COVID-19 on three kinds of pollution in Beijing-Tianjin-Hebei region.

Large-scale restrictions on anthropogenic activities in China in 2020 due to the Corona Virus Disease 2019 (COVID-19) indirectly led to improvements in air quality. Previous studies have paid little attention to the changes in nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3) concentrations at different levels of anthropogenic activity limitation and their interactions. In this study, machine learning models were used to simulate the concentrations of three pollutants during periods of different levels of lockdown, and compare them with observations during the same period. The results show that the difference between the simulated and observed values of NO2 concentrations varies at different stages of the lockdown. Variation between simulated and observed O3 and PM2.5 concentrations were less distinct at different stages of lockdowns. During the most severe period of the lockdowns, NO2 concentrations decreased significantly with a maximum decrease of 65.28 %, and O3 concentrations increased with a maximum increase of 75.69 %. During the first two weeks of the lockdown, the titration reaction in the atmosphere was disrupted due to the rapid decrease in NO2 concentrations, leading to the redistribution of Ox (NO2 + O3) in the atmosphere and eventually to the production of O3 and secondary PM2.5. The effect of traffic restrictions on the reduction of NO2 concentrations is significant. However, it is also important to consider the increase in O3 due to the constant volatile organic compounds (VOCs) and the decrease in NOx (NO+NO2). Traffic restrictions had a limited effect on improving PM2.5 pollution, so other beneficial measures were needed to sustainably reduce particulate matter pollution. Research on COVID-19 could provide new insights into future clean air action.

The sweet potato B-box transcription factor gene IbBBX28 negatively regulates drought tolerance in transgenic Arabidopsis.

B-box (BBX) which are a class of zinc finger transcription factors, play an important role in regulating of photoperiod, photomorphogenesis, and biotic and abiotic stresses in plants. However, there are few studies on the involvement of BBX transcription factors in response to abiotic stresses in sweet potato. In this paper, we cloned the DNA and promoter sequences of IbBBX28. There was one B-box conserved domain in IbBBX28, and the expression of IbBBX28 was induced under drought stress. Under drought stress, compared to wild type Arabidopsis, the protective enzyme activities (SOD, POD, and CAT) were all decreased in IbBBX28-overexpression Arabidopsis but increased in the mutant line bbx28, while the MDA content was increased in the IbBBX28-overexpression Arabidopsis and decreased in the bbx28. Moreover, the expression levels of the resistance-related genes showed the same trend as the protective enzyme activities. These results showed that IbBBX28 negatively regulates drought tolerance in transgenic Arabidopsis. Additionally, the yeast two-hybrid and BiFC assays verified that IbBBX28 interacted with IbHOX11 and IbZMAT2. The above results provide important clues for further studies on the role of IbBBX28 in regulating the stress response in sweet potato.

Expression level of fibroblast growth factor 5 (FGF5) in the peripheral blood of primary hypertension and its clinical significance.

OBJECTIVE: To explore the expression level of FGF5 in the peripheral blood of primary hypertension patients and its clinical significance. METHODS: The 34 patients with primary hypertension treated in this hospital from June 2012 to June 2014 were selected as the observation group, while the 25 patients at this hospital who had physical exam with heathy results were selected as control group. Venous blood was drawn early in the morning after an overnight fast. FGF5, mRNA and protein level changes in the peripheral blood cells and peripheral blood serum were analyzed by real-time fluorescence based quantitative PCR (RT-PCR) and enzyme-linked immunosorbent assay (ELISA). FGF5 gene SNP (rs16998073) were amplified by PCR and inserted into T vector, and its genetic variation were analyzed by sequencing. The relationship of FGF5 protein levels and genetic variation with diastolic/systolic blood pressure was also analyzed. RESULTS: Comparing with the control group, the observation group's FGF5 mRNA and protein levels significantly increased in the peripheral blood cells and peripheral blood. The difference was statistically significant (P < .05). Correlation analysis showed that FGF5 protein level and systolic/diastolic blood pressure were positively correlated (P < .05). T/A genetic variation of FGF5 gene SNP (rs16998073) and diastolic/systolic blood pressure were positively correlated (P < .05). CONCLUSION: The FGF5 mRNA and protein expression levels of the patients with primary hypertension were abnormal and had genetic variation, which were associated with blood pressure of the patients with primary hypertension.

Comparative pharmacokinetic analysis of extracts of crude and wine-processed Dipsacus asper in rats by a sensitive ultra performance liquid chromatography-tandem mass spectrometry approach.

The purpose of this study is to establish and validate an UPLC-MS/MS approach to determine 4-caffeoylquinic acid, chlorogenic acid, 3,5-dicaffeoylquinic acid, loganic acid, loganin, sweroside, dipsacoside B and asperosaponin VI from extracts of crude and wine-processed Dipsacus asper in biological samples and apply the approach to a comparative pharmacokinetic study. A Waters BEH C18 UPLC column was employed with acetonitrile/0.2% formic acid-water as mobile phases. The mass analysis was carried out in a triple quadrupole mass spectrometer using multiple reaction monitoring (MRM) with negative scan mode. A one-step protein precipitation by acetonitrile was performed to extract the eight analytes from plasma. Our results revealed that all of the calibration curves displayed good linear regression (r2>0.9990). The lower limits of quantification (LLOQ) were determined as 10.0, 9.6, 8.9, 9.1, 9.2, 9.8, 10.1 and 9.8ng/mL. The intra-day and inter-day precisions (RSD) of the eight compounds at high, medium and low levels were less than 4.94% and the bias of the accuracies ranged from -3.89% to 3.95%.The extraction recoveries of the eight compounds were from 90.4% to 100.2% and the matrix effects ranged from 89.3% to 100.1%. The stabilities of these compounds were investigated by analyzing six replicates of QC samples at three different concentrations following storage at 25°C for 4h, -80°C for 30days, three-freeze-thaw cycles, and 4°C for 24h. All the samples showed satisfactory precision and accuracy after various stability tests. Pharmacokinetic parameters were estimated using a non-compartment model. Compared with the crude group, the parameters of Cmax and AUC0-t of 4-caffeoylquinic acid, loganic acid, loganin and asperosaponin VI increased remarkably (p<0.05) after oral administration of the aqueous extract of wine-processed Dipsacus asper, indicating that wine-processing could enhance bioavailability of 4-caffeoylquinic acid, loganic acid, loganin and asperosaponin VI.

[Seasonal and Spatial Variations of Carbon Fractions in PM2.5 in Ningbo and the Estimation of Secondary Organic Carbon].

To investigate the seasonal and spatial variations of carbon fractions in PM2.5 in Ningbo, PM2.5 samples were collected at 5 sites in typical periods of 4 seasons from December 2012 to October 2013. The concentrations of organic carbon (OC) and elemental carbon (EC) were determined and the contribution of secondary organic carbon (SOC) was estimated. The result shows that: (1)the annual average of PM2.5 in Ningbo is 51. 6 µm.m-3. OC and EC account for 17% and 6% respectively. According to the result of the backward trajectory model, the concentrations of PM2.5 in winter and spring are higher mainly because of regional transport from inland China. (2) the OC/EC ratio and the correlation between OC and EC indicate that in summer a large sum of SOC is generated while in winter the influence of coal burning emission for heating in North China may be the main reason for high OC/EC ratio. (3) the contribution of SOC was estimated using an EC tracer method. The result shows that this method is not suitable for both winter and spring because of significant regional transport. The average concentrations of SOC in summer and autumn are 2. 5 µg.m-3 and 2. 3 µg.m-3, accounting for 42% and 28% of total OC respectively.