[Applicability of odor analyzer based on study of processed ginger products and GC-MS validation]

Heracles Ⅱ rapid electronic odor analyzer has been gradually applied in the study on the "odor" of Chinese medicine because of its ability to associate volatile substances in the sample with "odor", but its applicability is not clear. In this article, processed ginger products--dried ginger, roasted ginger, and carbonized ginger were chosen as examples to study the volatile chemical components, and the applied scope and accuracy of Heracles Ⅱ rapid electronic odor analyzer were verified by gas chromatography-mass spectrometry(GC-MS). Components in ten batches of ginger from different producing places were detected by GC-MS and Heracles Ⅱ rapid electronic odor analyzer. Principal component analysis(PCA) and discriminant factor analysis(DFA) were performed to investigate the effects of producing place and processing degree on dried ginger, roasted ginger, and carbonized ginger. The results showed that the processing degree had significant impact on the processed ginger products, while producing place was not significant to the processed ginger products. At the same time, 42 and 45 compounds were detected by Heracles Ⅱ rapid electronic odor analyzer and GC-MS, respectively, of which 29 compounds were common detected, with a coincidence rate of 64.4%. This result indicated that compared with GC-MS, Heracles Ⅱ rapid electronic odor analyzer had certain referential value in the qualitative analysis. Heracles Ⅱ rapid electronic odor analyzer, with the characteristics of convenience, high efficiency, and accuracy in processing data, has certain advantages in the "odor" research aiming to comprehensively evaluate volatile substances, and has a good application prospect in the quality control of Chinese medicine and its processed products.

[Karst Hydrogeochemical Characteristics and Controlling Factors of Carlin-type Gold Mining Area Based on Hydrochemistry and Sulfur Isotope]

Mining activities change the groundwater level and flow conditions through pumping and drainage, which enhances the interaction between groundwater and aquifer rocks; mine drainage is discharged into the surface water system, which affects the whole karst water hydrogeochemical process. Based on hydrogeochemistry and the δ³⁴S isotope, the hydrogeochemical processes, characteristics, and main controlling factors for waste water, karst groundwater, and surface water in a typical Carlin gold mining area and its surrounding areas were revealed. The results showed that:chemical compositions of groundwater and surface water unaffected by gold mining activities were mainly controlled by the weathering of limestone and dolomitic limestone; Ca²⁺, Mg²⁺, and HCO₃^- were main ions; and the water chemical types were Ca-HCO₃. The mine wastewater and its downstream receiving water were affected by the dissolution of carbonate and silicate minerals, and cation exchange also played a role; the main ions were Ca²⁺, Mg²⁺, Na⁺, and SO₄^2-, and the hydrochemical type gradually evolved from Ca-HCO₃ to Ca-SO₄. SO₄^2- was the characteristic component in various water bodies affected by mining, and the concentration of SO₄^2- gradually decreased from top to bottom in the well. The values of δ³⁴S for unaffected groundwater and surface water were positive, and SO₄^2- was mainly derived from realgar oxidation. Conversely, mine wastewater and downstream water were negative, SO₄^2- was mainly influenced by the mixing action of realgar oxidation and meteoric precipitation, and pyrite also contributed to a certain extent. At the same time, NO₃^- came from agricultural fertilizer and rural domestic sewage discharge directly. Principal component analysis (PCA) further demonstrated:sulfide mineral oxidation and mining activities were the main controlling factors for the water chemical composition of mine wastewater and downstream water, whereas unaffected groundwater and surface water were mainly influenced by water-rock (carbonate rock) interactions. Agricultural fertilizer and rural sewage discharge also had a certain influence. Therefore, the study area should strengthen the interception of surface water, control-block-management of sulfide oxidation, rural domestic sewage treatment, and agricultural fertilizer.

[Assessment of soil fertility in Artemisia argyi planting areas in Qichun county based on minimum data set]

This study aims to explore the soil fertility in the main Artemisia argyi planting areas in Qichun county.To be specific, the soil physical and chemical properties in the main planting areas of A.argyi in Qichun county were analyzed.On this basis, 12 indexes were selected for principal component analysis(PCA) which was then combined with the norm value of each index and the correlation coefficients between the indexes to establish the minimum data set(MDS).The radar map was plotted to directly demonstrate the level of each index and the comprehensive level of the sampling sites.The comprehensive index model was used to calculate the soil fertility quality index(SFQI) of the total data set(TDS) and MDS(SFQI-TDS and SFQI-MDS, respectively), and linear regression of the two was performed.The results showed that the indexes that made up the MDS for soil fertility evaluation were pH, available potas-sium, available iron, available zinc, available manganese, available copper, and available magnesium.The radar map suggested the greatest difference in soil organic matter and smallest difference in available nitrogen among the 14 sampling sites.Moreover, the overall content of available phosphorus and available iron was high, while that of available nitrogen was the lowest.The SFQI-MDS which was yielded based on the weight of each index in MDS calculated with the norm value was more sensitive and the SFQI had stronger correlation with TDS-SFQI, which can better represent TDS-SFQI.SFQI-MDS was in the range of 0.298-0.784, with the average of 0.565 and variation coefficient of 18.38%.Caohe Town had the highest average SFQI-MDS.Clustering of SFQI-MDS value suggested that the soil fertility can be classified into 4 levels: level Ⅰ(SFQI ≥ 0.677) indicated excellent soil fertility, which accounted for 11.24%(mainly in Qingshi town, Balihu, and Zhangbang town); level Ⅱ(0.571≤SFQI≤0.680) meant good fertility, which made up 43.82%(mainly in Caohe town, Hengche town, and Pengsi town); level Ⅲ(0.466≤SFQI≤0.557) indicated average fertility, which took up 32.58%(mainly in Chidong town and Zhulin town); level Ⅳ(SFQI≤0.421) suggested poor fertility, which accounted for 12.36%(mainly in Guanyao town).It is recommended that nitrogen, potassium, magnesium, and calcium fertilizers should be increased and organic ferti-lizer should be applied for the cultivation of A.argyi in Qichun county to improve soil fertility and soil physical and chemical properties.

Dimensionality Reduction and Louvain Agglomerative Hierarchical Clustering for Cluster-Specified Frequent Biomarker Discovery in Single-Cell Sequencing Data

The major interest domains of single-cell RNA sequential analysis are identification of existing and novel types of cells, depiction of cells, cell fate prediction, classification of several types of tumor, and investigation of heterogeneity in different cells. Single-cell clustering plays an important role to solve the aforementioned questions of interest. Cluster identification in high dimensional single-cell sequencing data faces some challenges due to its nature. Dimensionality reduction models can solve the problem. Here, we introduce a potential cluster specified frequent biomarkers discovery framework using dimensionality reduction and hierarchical agglomerative clustering Louvain for single-cell RNA sequencing data analysis. First, we pre-filtered the features with fewer number of cells and the cells with fewer number of features. Then we created a Seurat object to store data and analysis together and used quality control metrics to discard low quality or dying cells. Afterwards we applied global-scaling normalization method "LogNormalize" for data normalization. Next, we computed cell-to-cell highly variable features from our dataset. Then, we applied a linear transformation and linear dimensionality reduction technique, Principal Component Analysis (PCA) to project high dimensional data to an optimal low-dimensional space. After identifying fifty "significant"principal components (PCs) based on strong enrichment of low p-value features, we implemented a graph-based clustering algorithm Louvain for the cell clustering of 10 top significant PCs. We applied our model to a single-cell RNA sequential dataset for a rare intestinal cell type in mice (NCBI accession ID:GSE62270, 23,630 features and 1872 samples (cells)). We obtained 10 cell clusters with a maximum modularity of 0.885 1. After detecting the cell clusters, we found 3871 cluster-specific biomarkers using an expression feature extraction statistical tool for single-cell sequencing data, Model-based Analysis of Single-cell Transcriptomics (MAST) with a   log ₂ FC threshold of 0.25 and a minimum feature detection of 25%. From these cluster-specific biomarkers, we found 1892 most frequent markers, i.e., overlapping biomarkers. We performed degree hub gene network analysis using Cytoscape and reported the five highest degree genes (Rps4x, Rps18, Rpl13a, Rps12 and Rpl18a). Subsequently, we performed KEGG pathway and Gene Ontology enrichment analysis of cluster markers using David 6.8 software tool. In summary, our proposed framework that integrated dimensionality reduction and agglomerative hierarchical clustering provides a robust approach to efficiently discover cluster-specific frequent biomarkers, i.e., overlapping biomarkers from single-cell RNA sequencing data.

[Seasonal Variation and Source Apportionment of Carbonaceous Species in PM2.5 in Chengde]

In order to study the seasonal variations and pollution sources of carbonaceous species in PM_2.5 in Chengde, the concentration of these components was determined in atmospheric PM_2.5 samples collected in January, April, July, and October 2019. The change in carbonaceous species were analyzed based on the estimation of the ratio of organic carbon(OC) to elemental carbon(EC), total carbonaceous aerosol(TCA), and secondary organic carbon(SOC). The source of these pollutants was determined by means of the backward trajectory and principal component analysis(PCA). The results showed that the mean mass concentrations of PM_2.5, OC, and EC during the sampling period were(31.26±21.39) μg·m^-3,(13.27±8.68) μg·m^-3, and(2.80±1.95) μg·m^-3, respectively. The seasonal variations of PM_2.5 were:winter[(47.68±30.37) μg·m^-3]>autumn[(28.72±17.12) μg·m^-3]>spring[(26.59±15.32) μg·m^-3]>summer[(23.17±8.38) μg·m^-3], consistent with the trend of total carbon(TC), OC, and EC. The source of OC and EC during winter(R²=0.85) was similar. Based on the ratio of OC/EC, all four seasons were affected by traffic and coal-burning source emissions, and the most affected season by bituminous coal emissions was winter. The average concentration of TCA was(21.38±13.68) μg·m^-3, which accounted for 68.39% of PM_2.5. The order of secondary conversion rate(SOC/OC) was:spring(54.09%) >autumn(37.64%) >summer(32.91%) >winter(25.43%). The results of the backward trajectory simulation show that the pollutant concentrations carried by air masses are relatively low in spring and summer, and the transport channels of pollutants are southwest in autumn and northwest in winter. The results of the PCA showed that the key to reducing PM_2.5 in Chengde is to control emissions from vehicle exhausts, and coal and biomass combustion sources.

[O3 Source Characteristics of an Industrial Area in the Yangtze River Delta Based on Boundary Observations]

To study the characteristics of ozone sources in a petrochemical industrial park in Shanghai, O₃ and its precursors were synchronously and continuously measured for 3 months(June-August 2020) alongside meteorological parameters using an online monitoring system. The Texas Commission on Environmental Quality(TCEQ) method and principal component analysis(PCA) were used to study the contribution of regional background and local O₃ concentrations in the industrial zone, the results of which were compared. The results indicated that:① During the observation period, the dominant wind directions in the park were southeast and east, and the average temperature was 27.12℃. The daily average ρ(VOCs-36), ρ(NO_x), and ρ(O₃) was 32.05-240.51, 10.15-47.51, and 31.81-144.43μg·m^-3, respectively. Alkanes are the most abundant of 36 VOCs; ② The regional background concentrations based on the TCEQ method ranged from 32.63 to 191.13μg·m^-3, and the local concentrations ranged from 16.08 to 134.25 μg·m^-3. The percentage contribution of the regional background ranged from 32.6% to 87.7%. The PCA analysis showed that the regional background concentrations ranged from 66.3 to 219.83μg·m^-3; ③ The variations in local O₃ concentrations based on the TCEQ analysis broadly correspond to the variations in ozone formation potential in the park. The two analysis methods were consistent, verifying that the results are reliable; and ④ After eliminating the calculation error caused by the abnormal concentrations recorded at some stations, the proportion of background O₃ in the region was generally within the range 75%-95% during the observation period. Overall, regional transport was the main source of O₃ in the industrial park, and O₃ pollution in the surrounding cities should be the focus of pollution control alongside joint prevention and control measures in the Yangtze River Delta region.

[Water Chemical Characteristics and Influence of Exogenous Acids in the Yangtze River Basin]

To explore the influence of human activities on the Yangtze River water chemistry, water samples were obtained from a representative section the main river stem/branch in wet and normal seasons in 2016. Ion ratio analysis, principal component analysis(PCA), and chemical ion balance calculations were performed, and carbonate rock dissolution rates were determined based on carbonate and exogenous acids. The result show that HCO₃-Ca is the dominant hydrochemistry type, indicating that the dissolution of carbonate rocks in the basin is the main process affecting hydrochemistry, and carbonate acid is significant in the weathering of carbonate rocks. In addition, the proportion of carbonate acid dissolution in the wet and normal seasons accounted for 60.33% and 59.14% of the total dissolution, respectively. The dissolution ratio among the different sampling points was notable, which indicates that the carbon sink effect of exogenous acid cannot be ignored. In addition, cation exchange some influence on hydrochemistry but was not the main reaction process. Compared with hydrological monitoring data for the last few years, the weathering of rocks by sulfuric and nitrate acids has strengthened, and the negative effects of anthropogenic pollution in the Yangtze River have increased.

[Seasonal Characteristics and Source Analysis of Water-soluble Inorganic Ions in PM2.5 in Suqian City]

To study the seasonal pollution characteristics and sources of water-soluble inorganic ions in atmospheric PM_2.5 in Suqian City, 171 samples were collected at three monitoring points, which were in the water vapor channel, from May 2017 to January 2018. The mass concentrations of PM_2.5 and nine water-soluble inorganic ions were analyzed. The results showed that the annual average concentration of water-soluble inorganic ions in PM_2.5 in Suqian City was (44.08±34.61) μg ·m^-3, accounting for 41.8% of PM_2.5. The concentrations of these species were in the order of ρ(NO₃^-) > ρ(SO₄^2-) > ρ(NH₄⁺) > ρ(ρl^-) > ρ(Na⁺) > ρ(Ca²⁺) > ρ(K⁺) > ρ(F^-) > ρ(Mg²⁺); NO₃^-, SO₄^2-, and NH₄⁺ accounted for 75.6% of the total water-soluble ions. The annual average ratio of ρ(NO₃^-) to ρ(SO₄^2-) was 1.53±0.88, indicating that mobile sources contributed more to PM_2.5 pollution. Based on the correlation analysis of NH₄⁺ and SO₄^2-, NO₃^- may exist in the form of (NH₄)₂ SO₄, NH₄HSO₄, or NH₄NO₃. According to the principal component analysis, secondary transformation, industrial pollution, biomass burning, and dust were the major sources of water-soluble inorganic ions. PM_2.5concentrations were positively related to relative humidity in winter. Water vapor transmission is more likely to promote PM_2.5 accumulation in winter.

[Heavy Metal Pollution Characteristics and Ecological and Health Risk Assessment of Atmospheric PM2.5 in a Living Area of Zhengzhou City]

To study the pollution characteristics of atmospheric heavy metal elements in a living area of Zhengzhou City, assess the potential ecological risks, and determine risks to resident health in this city, the Wuhan Tianhong TH-16A Airborne Particles Intelligent Sampler was used to collect atmospheric PM_2.5 in Zhengzhou City. The mass concentrations of 17 metal elements were analyzed by ambient air determination of inorganic elements by ambient particle matter wavelength dispersive X-ray fluorescence spectrometry. The source of heavy metals was analyzed by the enrichment factor method and principal component analysis. The ecological risk index method and the US Environmental Protection Agency's health risk assessment method were used to evaluate the potential ecological risks and residents' health risks from Cr, Cd, Cu, Zn, Ni, Pb, As, and other elements. The results showed that metals with higher enrichment factor values were Cd, Sb, Pb, and As, and Cd had the highest enrichment factor value. The sources of metal elements in a living area of Zhengzhou City were mainly crust/burning coal, fuel, garbage burning, metallurgical dust, and vehicle emission. The single factor potential ecological hazard index values of Cd, Pb, Zn, As, Cu, Ni, and Cr were 70420.2, 255.3, 204.6, 71.5, 36.9, 24.0, and 5.1, respectively. Cd, As, and Cr in a living area of Zhengzhou City posed a cancer risk, and Cd was the most harmful. Mn had a non-carcinogenic risk.