In this paper, based on the traditional grey multivariate convolutional model, the concept of a buffer operator is introduced to construct a single-indicator buffered grey multivariate convolutional model applicable to air quality prediction research. The construction steps of the model are described in detail in this paper, and the stability of the model is analyzed based on perturbation theory. Furthermore, the model was applied to predict the air quality composite index of the “2 + 26” Chinese air pollution transmission corridor cities based on different socioeconomic development scenarios in a multidimensional manner. The results show that the single-indicator buffered grey multivariate convolutional model constructed in this paper has better stability in predicting with a small amount of sample data. From 2020 to 2025, the air quality of the target cities selected in this paper follows an improving trend. The population density, secondary industry, and urbanization will not have a significant negative impact on the improvement of air quality if they are kept stable. In the case of steady development of secondary industry, air quality maintained a stable improvement in 96.4% of the “2 + 26” cities. The growth rate of population density will have an inverted U-shaped relationship with the decline in the city air quality composite index. In addition, with the steady development of urbanization, air quality would keep improving steadily in 71.4% of the “2 + 26” cities.
Background and study aim The klotho protein, a multifunctional protein, has been shown to be associated with a wide range of endocrine diseases and has been linked to thyroid tumourigenesis. However, the relationship between serum klotho levels and thyroid hormones remains poorly understood. This study aimed to explore the correlation between serum klotho levels and thyroid hormones. Methods Data was obtained from the NHANES cycles 2007–2008, 2009–2010, and 2011–2012. A total of 4674 participants were recruited for this study. Statistical analysis was using multiple linear regression analyses, and restricted cubic spline plots (RCS) to investigate the association between serum klotho levels and serum levels of thyroid hormones. Results In the unadjusted covariate model, ln(klotho) significantly positively correlated with tT3, tT4, fT3, tT4/fT4, and tT3/fT3 (all P<0.01) and negatively correlated with TSH, tT4/tT3, and fT4/fT3 (all P<0.05). Furthermore, tT3, tT4, fT3and tT3/fT3 (P < 0.05) were still significant in the adjusted model. And it is worth noting that there is an approximately L-shaped nonlinear relationship between ln(klotho) and fT3,tT3 with a cut-off point of 6.697 (P-non-linear < 0.05). The stratification analysis showed gender and iodine level differences in the relationship between serum Klotho levels and thyroid hormones. Conclusion There is an L-shaped nonlinear relationship between ln(klotho) and fT3, tT3, suggesting that klotho could be involved in the physiological regulation of thyroid function.
Northern China has 12 main deserts that range from extremely arid regions in the west to semi-arid or semi-humid regions in the east. Based on their geographical locations, we divided these deserts into western, central, and eastern deserts. We investigated the geochemical elements in their surface sediments and found that the concentration of the major element SiO 2 gradually increased from west to east, whereas the other major elements tended to decrease; however, the CaO concentration was unusually high in the Taklimakan and Qaidam Basin deserts. The spatial distribution of geochemical elements was more homogeneous in the western and central deserts than in the eastern. Unlike the eastern deserts, the western and central deserts show greater physical than chemical weathering and lower mineral maturity due to the extremely low precipitation and a continuous supply of younger materials. Most major trace elements in the eastern deserts were more depleted relative to the upper continental crust than in the western deserts, but were moderately depleted in the central deserts. The spatial distribution of geochemical elements showed similar provenances of aeolian material in the Taklimakan Desert and Kumtag Desert, and similar provenances of aeolian material in the Badain Jaran, Tengger, Ulan Buh, and Hobq deserts. There were no obvious provenance relationships for the Otindag, Horqin, and Hulun Buir sandy lands in the central and western deserts
Particulate matter (PM) emissions from anthropogenic sources contribute substantially to air pollution. The unequal adverse health effects caused by source-emitted PM emphasize the need to consider the discrepancy of PM-bound chemicals rather than solely focusing on the mass concentration of PM when making air pollution control strategies. Here, we present a dataset about chemical compositions of real-world PM emissions from typical anthropogenic sources in China, including industrial (power, industrial boiler, iron & steel, cement, and other industrial process), residential (coal/biomass burning, and cooking), and transportation sectors (on-road vehicle, ship, and non-exhaust emission). The data was obtained under the same strict quality control condition on field measurements and chemical analysis, minimizing the uncertainty caused by different study approaches. The concentrations of PM-bound chemical components, including toxic elements and PAHs, exhibit substantial discrepancies among different emission sectors. This dataset provides experimental data with informative inputs to emission inventories, air quality simulation models, and health risk estimation. The obtained results can gain insight into understanding on source-specific PMs and tailoring effective control strategies.
Abstract. Haze pollution is a severe environmental problem, caused by elevation of fine particles (aerodynamic diameter < 2.5 μm, PM2.5), which is related to secondary aerosol formation, unfavourable synoptic conditions, regional transport, etc. The regional haze formation in basin areas, along with intensive emission of precursors, high relative humidity and poor dispersion conditions, is still limitedly understood.In this study, a field campaign was conducted to investigate the factors resulting in haze formation in Sichuan Basin (SCB) during winter in 2021. The fine aerosol chemical composition was characterised by using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) with the aim of inorganic and organic aerosol characterisation and source apportionment. The average concentration of non-refractory fine particles (NR-PM2.5) was 98.5 ± 38.7 μg/m3, and organics aerosols (OA), nitrate, sulphate, ammonium, and chloride occupied 40.3, 28.8, 10.6, 15.3 and 5.1 % of PM2.5. Three factors, including a hydrocarbon-like OA (HOA), a biomass burning OA (BBOA), and an oxygenated OA (OOA), were identified by applying the positive matrix factorisation (PMF) analysis, and they constituted 24.2, 24.2 and 51.6 % of OA on average, respectively. Nitrate formation was promoted by gas-phase and aqueous-phase oxidation, while sulphate was mainly formed through aqueous-phase. OOA showed strong dependence on Ox, demonstrating the contribution of photooxidation to OOA formation. OOA concentration increased as aerosol liquid water content (ALWC) increased within 200 μg/m3 and kept relatively constant when ALWC > 200 μg/m3, suggesting the insignificant effect of aqueous-phase reactions on OOA formation. Among the three haze episodes identified during the whole campaign, the driving factors were different: the first haze episode (H1) was driven by nitrate formation through photochemical and aqueous-phase reactions, and the second haze episode (H2) was mainly driven by the intense emission of primary organic aerosols from biomass burning and vehicle exhaust, while the third haze episode (H3) was mainly driven by reactions involving nitrate formation and biomass burning emission. HOA and BBOA were scavenged, while OOA, nitrate, and sulphate formation were enhanced by aqueous-phase reactions during fog periods, which resulted in the increase of O:C from pre-fog to post-fog periods. This study revealed the factors driving severe haze formation in SCB, and implied the benefit of controlling nitrate as well as intense biomass burning and vehicle exhaust emission to the mitigation of heavy aerosol pollution in this region.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)