•Dynamic time warping was used to cluster the concentration change pattern.•Geographical detector method was used to quantify the driving force.•Spatial correlation appears at the scale of urban ...agglomeration.•Temperature and air pressure are the most important meteorological driving factors.•Population density and road density are the most important anthropogenic driving factors.
Fine particulate matter (PM2.5) threatens public health severely, which, luckily, can be governed by referring to its spatiotemporal distribution and key driving factors. However, very few explored it in the long-term, broadly, and systematically. In this study, nine Chinese key urban agglomerations were targeted to explore the spatial distribution of PM2.5 and the evolution of its major driving factors from 2000 to 2017. Spatiotemporal distribution and change tendency were evaluated by spatial autocorrelation analysis and dynamic time warping (DTW), and the entire research period was divided into four stages according to the evaluation. Subsequently, the geographical detector method (GDM) was adopted to quantify the relationship between anthropogenic and meteorological factors with PM2.5 concentration in the entire period and sub-stages. As the findings indicate: 1) In 2000–2017, PM2.5 concentration increased firstly in all agglomerations and then declined by fluctuation; it was mainly gathered in the plain areas where the core cities of urban agglomerations were located, with the highest concentration in North China. 2) Variation of PM2.5 concentration appeared similar tendency and regional aggregation, e.g., five urban agglomerations around the central plains urban agglomeration (CPUA) had similar patterns. 3) The Driving factors of PM2.5 showed noticeable spatiotemporal differences. It is indicated that the critical meteorological factors refer to temperature and air pressure, while the key anthropogenic factors are population density (PD) and road density (RD). Except for the population density showing a relatively persistent high influence on urban agglomeration, especially significant in northern China, the rest of the anthropogenic factors represented different characteristics. Specifically, the proportion of secondary industry (PSP) and gross domestic product per capita (GDPP) showed relatively strong effects in the early stage but weakening dramatically in the later stage. Foreign direct investment (FI) increased in developed urban agglomerations in the entire stage while showed a downward trend in underdeveloped cities. Road density was enhanced dramatically in the early stage but weakened slowly in the later stage. The findings reveal the change tendency of PM2.5 concentration in urban agglomerations and the evolution of its driving factors, which help the Chinese government adopt effective strategies to cope with pollution.
In this study, a biosensor with a dual recognition system comprising a molecularly imprinted polymer (MIP) and aptamers selective for lincomycin was fabricated. The MIP was synthesized by ...electropolymerization of carbon dots (C-dots)-tagged DNA aptamers combined with lincomycin and o-aminophenol on the gold-nanoparticle-functionalized graphene oxide (Au-GO)-modified electrode. Electrogenerated chemiluminescence (ECL) resonance energy transfer was observed between Au-GO and C-dots. After the C-dots accepted the energy, they acted as a signal indicator and exhibited enhanced signal intensity in the presence of target lincomycin. When lincomycin was competitively bound to DNA aptamers and MIP, it blocked the transfer of energy, and a decreased ECL signal was observed. Hence, a dual recognition method for the detection of lincomycin is realized. Using this strategy, the sensor exhibited a linear ECL response to lincomycin at concentrations from 5.0 × 10 −12 mol/L to 1.0 × 10 −9 mol/L. The detection limit of this assay was found to be 1.6 × 10 −13 mol/L. This method was utilized to determine lincomycin residuals in meat samples with satisfactory results.
•A new aptamer-molecularly imprinted sensor for lincomycin detection was first reported.•The aptasensor presents a generic detection strategy for detecting pesticide residues.•A dual recognition system was obtained from the DNA aptamers and MIPs for the target molecule.
The presence of pesticide residues in cowpea raises serious health concerns. In this study, a novel, sensitive, high-performance method was developed to simultaneously analyze the residues of 35 ...pesticides in cowpea samples from growing areas in the Hainan province of China, from November 2018 to June 2021. The method employs modified QuEChERS sample pretreatment coupled with gas chromatography-tandem mass spectrometry. The limits of quantification of the 35 pesticides in the cowpea matrix ranged from 1.0 to 8.0 μg/kg. Twenty-seven of the 35 pesticides were detected, twelve of which are banned for use on legumes in China. Residues for ten pesticides in 17.1% of the samples exceeded their MRLs, with the highest exceedance of 380% observed in difenoconazole. Moreover, 80.8% of the samples contained one or more pesticide residues, with the most frequently detected pesticide being chlorfenapyr with a detection rate of 46.3%. In addition, the pesticide triazophos was detected through different years and regions. Notably, the chronic dietary exposure risk (%ADI) of the detected pesticides, evaluated from the national estimated acceptable daily intake, was lower than 100% in Chinese people of different age groups.
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•This study presents a coupled numerical model for the ore-forming processes of the Maoping Pb-Zn deposit. This approach furthers understanding of the processes that led to the ...formation of this deposit and enables the identification of areas prospective for future exploration.•Our modeling reveals the controlling factors which causes the difference of the distribution of mineralization, which can be used in future mineral exploration.•Our numerical modeling identifies the key controlling factors of the ore-forming processes of the Maoping Pb-Zn deposit.
The Maoping large Pb-Zn deposit is located in the Sichuan-Yunnan-Guizhou Metallogenic Province (SYGMP), southwestern China, hosting more than 3 mt Pb and Zn minerals, with 140 t associated Ge. This study uses numerical simulation methods to explore the key factors of the mineralizing system that formed the Maoping deposit which traditional analytical methods cannot easily identify, answering questions about the spatial distribution of galena and giving information for future resource exploration within the Maoping district. This Study reveals and highlights the practical value of numerical modeling in quantitatively researching the ore-forming processes of mineral deposits and how this knowledge can be used in future geological research and mineral exploration. Our model interlinks heat transfer, pressure (without deformation process), fluid-flow, and material migration during the mineralizing processes and indicates the presence of a temperature anomaly, location of fluid convergence and the spatial distribution of Pb2+ that match the known distribution of mineralization. We also analyze the whole process and find the key factors which control the spatial distribution of galena, answering the question why there is mineralization with economic value in the northwest limb and none in the southeast limb of the Maoping anticline. All these data can be used in future geological research to gain insights into the ore-forming system that formed the Maoping Pb-Zn deposit as well as other hydrothermal mineralizing systems in the SYGMP.
Alkaline humic acid fertiliser amendment (HAFA) can significantly enhance the microstructural stability of soils, as well as alleviate Al toxicity. Thus, the potential effects of HAFA on soil have ...attracted increased attention. A soil incubation experiment was conducted to evaluate the effects of HAFA. A typical acidic latosol was cultured for 51 days with five fertiliser treatments—unfertilised (CK), 0.32 g of inorganic fertiliser (IF), 0.32 g of inorganic fertiliser combined with 1.00 g lime (IF.CaO), 0.32 g of HAFA (HAFA0.32), and 0.42 g of HAFA (HAFA0.42)—to investigate the effects of HAFA on the microstructural stability and Al toxicity of soils. The results indicate that HAFA increased the number of aggregates and their honeycomb structures in latosol, as well as enhanced the adsorption capacity of the aggregates. HAFA not only increased latosol pH by 0.72–0.92, but also reduced the exchangeable acid content by 39.49–43.03% as compared with CK, which was similar to the lime treatment; it also significantly increased the soil organic matter content and the availability of N, P, and K, and improved the cation exchange capacity. However, HAFA decreased the effect of increasing the amount of exchangeable Ca when compared to the lime treatment. Additionally, the total amounts of reactive and exchangeable Al in the HAFA treatments were reduced by 45.84–54.59% and 56.67–67.53%, respectively. Both HAFA and lime applications effectively decreased the concentrations of phytotoxic Al species in latosols when compared to the application of inorganic fertiliser alone, with the HAFA0.42 treatment being more effective than lime application in decreasing the amount of dissolved and exchangeable Al. The HAFA0.42 treatment was also the best amendment for stabilising the microstructure, increasing the nutrient content, and mitigating Al toxicity in the potted acidic latosol.
Risks from combined exposure to multiple chemicals in food have prompted a growing concern for their effect on human health. Risk management of chemical mixtures should be based on developing and ...harmonizing methodologies to scientifically evaluate their cumulative adverse effects. In this study, a simplified tiered approach of cumulative exposure assessment is described along with a case study of vegetables in China’s Hainan province during 2012–2014. This case study could be a reference for the Chinese National Risk Assessment Programs for vegetable and fruit products. In the proposed assessment approach,
Tier 1
acts as a screening tier to categorize and evaluate chemicals under a conservative scenario, and it prioritizes the pesticides of most concern.
Tier 2
refines the grouping of substances from
Tier 1
and normalizes the toxic potency of the chemicals to sum the exposure of chemical mixtures in a given assessment group.
Tier 3
applies the refined exposure model and the input parameter distribution to create probabilistic models using Monte Carlo simulation. This approach will be helpful in the cumulative exposure assessment where data on pesticide residues are sufficient, but the individual dietary consumption is inadequate.
Coalbed methane (CBM) is high-quality clean energy and accurate prediction of daily gas production of CBM is critical for CBM engineering. However, the production process of CBM is a non-stable ...dynamic with significant fluctuation, and it is hard to predict by traditional statistical methods. This study processes a deep learning model T-DGCN considering time, space, and geological features for predicting complex long gas production sequences. T-DGCN innovatively measures the similarity of geological features between wells with Dynamic Time Warping (DTW), and merges geological and spatial features to dynamically correct the weight matrix in a multilayer neural network with multiple aggregations. Then, the model uses the Gated Recurrent Unit (GRU) to extract the temporal features of gas production and predict the daily gas production sequence. The experiments with the data set from Shanxi Province showed that T-DGCN achieves an accuracy of 0.9298 in short-term production prediction, which is higher than the baseline models. In addition, the geological similarity calculated by DTW in T-DGCN significantly improves the performance of the model. And T-DGCN can still have better performance in long-term prediction tasks with accuracy above 0.9. This study provides a new method for the theoretical guidance for adjusting development schemes of CBM and the prediction of long-time series in geoscience.
•A multi-feature deep learning model T-DGCN for coalbed methane production prediction.•T-DGCN integrates time, space and geological features for increasing accuracy.•The inter-well interference caused by space proximity was integrated into T-DGCN.•The similarity of geological features was measured by the Dynamic Time Warping.•T-DGCN's accuracy exceeds the baseline models' on unstable long-time series.
Considering the limitations associated with existing methods for the detection of trace amounts of trichlorfon, this paper proposes a novel molecularly imprinted electrochemiluminescence (ECL) sensor ...for the detection of trichlorfon by utilizing the double enhancement effect of trichlorfon and Ag nanoparticles supported by multi-walled carbon nanotubes (MWCNTs/Ag NPs) in a luminol–H
2
O
2
ECL system. Here, trichlorfon was electropolymerized on the surface of the MWCNT/Ag NP–modified gold nanoelectrode with
o
-phenylenediamine to prepare the molecularly imprinted polymer-based sensor. After eluting the trichlorfon, imprinted holes for the identification of trichlorfon were retained on the sensor, which were used as signal switches to obtain different ECL intensities through the adsorption of different concentrations of trichlorfon. The ECL signal of the sensitized luminol–H
2
O
2
was doubly enhanced by the MWCNTs/Ag and trichlorfon, improving the sensitivity of the sensor. The trichlorfon concentration was positively correlated with the enhanced ECL intensity of the sensor in the range 5.0 × 10
−8
–5.0 × 10
−11
mol L
−1
, and the detection limit of trichlorfon was 3.9 × 10
−12
mol L
−1
. Moreover, the proposed sensor was successfully applied to the detection of trichlorfon residues in real samples, and the recovery ranged between 91.8 and 109%.
Graphical abstract
A molecularly imprinted electrochemiluminescence sensor for trichlorfon detection by utilizing the double enhancement effect of trichlorfon and Ag nanoparticles supported by multi-walled carbon nanotubes in a luminol–H
2
O
2
ECL system. The dual enhancement of the ECL signal improved the sensitivity of the sensor.
The structure of hapten determines the performance of the antibody and the corresponding detection method. A new type of antigen was designed and synthesized to expose the spatial and characteristic ...structure of dinotefuran molecule, and a type of high-quality antibody was obtained. The IC
value of the monoclonal antibody was 5.30 ng/mL and its cross-reactivity (CRs) was less than 2% when reacting with other structurally related analytes. The effects of spatial configurations of hapten on the antibody were visually analyzed while using the appropriate software according to the quality of the antibodies, which showed that the specificity of the antibody is closely related with the exposed structure of hapten. An ELISA assay with an IC
of 5.66 ng/mL and a linear range of 1.95 to 16.29 ng/mL was developed. The results that were obtained from the ELISA and HPLC methods were equivalent. The results showed that spatial simulation is a crucial method that is used in the designing of hapten to obtain a sensitive and specific antibody. The application of this method will highlight the potential aim and improve the detection efficiency of ELISA.
A novel supramolecular imprinted electrochemical sensor was developed for carbofuran (CBF) determination based on a multiwalled carbon nanotube-supported Pd-Ir nanocomposite catalyst (MWCNT/Pd-Ir) ...with methylene blue (MB) signal amplification. First, MWCNT/Pd-Ir composite nanoparticles were synthesized and used to modify the surface of a glassy carbon electrode; then, a molecular imprinted polymer for CBF was prepared by electropolymerization, with MB-doped o-phenylenediamine as the functional monomer and a 4-tert-butylcalix8arene-CBF (4TB8A-CBF) supramolecular complex as the template. The electrical signals were controlled though the elution and re-adsorption of CBF. Due to the double catalysis by the MWCNT/Pd-Ir and MB, the current intensity for CBF was obviously amplified. Additionally, because of the double recognition by the 4TB8A and MIP, the sensors showed outstanding CBF identification properties. The method was applied to detect CBF in agricultural products, and the satisfactory results were obtained.
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