Health Trend Analysis of In Orbit Satellite and Image Quality Monitoring of the Payload

This paper introduces the satellite system running status and key events.This satellite has been observing the Earth for six years after its launch into a 645 km sun-synchronous orbit.Through the health trend analysis of the platform and subsystems,the orbit,power supply,rotating parts status,temperature,fuel consumption and so on are introduced in detail.The cameras' status also are monitored and analyzed.

Evaluation of Groundwater Quality in the Deep Maastrichtian Aquifer of Senegal Using Multivariate Statistics and Water Quality Index-Based GIS

A regional groundwater quality evaluation was conducted in the deep Maastrichtian aquifer of Senegal through multivariate statistical analysis and a GIS-based water quality index using physicochemical data from 232 boreholes distributed over the whole country. The aim was to 1) identify the water types and likely factors influencing the hydrochemistry, and 2) determine the suitability of groundwater for drinking and irrigation. Results showed that sodium, chloride, and fluoride are highly correlated with electrical conductivity (EC) reflecting the significant contribution of these elements to groundwater mineralization. The principal component analysis evidenced: 1) salinization processes (loaded by Na+, K+, EC, Cl-, F- and HCO3-) controlled by water/rock interaction, seawater intrusion and cation exchange reactions;2) dolomite dissolution loaded by the couple Ca2+ and Mg2+ and 3) localized mixing with upper aquifers and gypsum dissolution respectively loaded by NO3- and SO42-. The hierarchical clustering analysis distinguished four clusters: 1) freshwater (EC = 594 μs/cm) with mixed-HCO3 water type and ionic contents below WHO standard;2) brackish (Na-mixed) water type with moderate mineralization content (1310 μs/cm), 3) brackish (Na-Cl) water type depicted by high EC values (3292 μs/cm) and ionic contents above WHO and 4) saline water with Na-Cl water type and very high mineralization contents (5953 μs/cm). The mapping of the groundwater quality index indicated suitable zones for drinking accounting for 54% of the entire area. The occurrence of a central brackish band and its vicinity, which were characterized by high mineralization, yielded unsuitable groundwater for drinking and agricultural uses. The approach used in this study was valuable for assessing groundwater quality for drinking and irrigation, and it can be used for regional studies in other locations, particularly in shallow and vulnerable aquifers.

Assessment of the Water Quality Index in the Semani River in Albania

Nowadays the human activity has increased the pressure on surface water quality. The purpose of this study is to assess the environmental quality of the Seman River water (in Southern part of Albania) through a 5-year monitoring program of 14 parameters (pH, DO, EC, TSS, Cl-, NO-3, Total-N, Total-P, BOD5, Cu2+, Ni2+, Pb2+, Cd2+ and Temp. °C), that determine the environmental status of this waterbody, as well as the application of WQI (CCME) through a multivariable approach. Based on the cluster dendogram results, it can be concluded that during wet seasons such as winter-spring, there are more sediments which influence other physic-chemical parameters, while during dry seasons (summer-autumn) there are more decomposition reactions of elements released by sediments and influenced by temperature. PCA analysis determines whether the groups of factors correlate strongly or not, depending on the internal structures of the groups and variables “heavy” or latent and vary from season to season with differentiated contributions to the water quality. All three factors influence WQI to the extent of 56% in the summer and spring season and 64% and 40% in the autumn and winter season, respectively.

Robust Soil Quality Index for Tropical Soils Influenced by Agricultural Activities

The knowledge of the soil quality plays a vital role in the agricultural sector. Despite its importance, there is scarce scientific information concerning this regard. The objective of this research is to develop a methodology to identify and select the most appropriate indicators of Soil Quality Index (SQI) in a region with high agricultural activity. For its conformation, a descriptive statistical analysis and a Pearson correlation matrix were performed and the indicators that showed greater variation were identified using a Principal Components Analysis (PCA). A sensitivity analysis was carried out and the most sensible soil indicators of?SQI?were identified. This statistical procedure was also used to specify the weights of the indicators in?SQI. The variables resulting from the multiparametric statistical analysis were pH, organic matter, sodium, calcium, iron, zinc, cation exchange capacity and electrical conductivity. The robustness of the?SQI?obtained in this study was demonstrated through simulations carried out by the numerical optimization through simplex method. The Soil Quality Index range obtained (0.54 - 0.75) locates Culiacan Valley soils as moderate/high quality.

Detection and Mapping of Water Quality Variation in the Godavari River Using Water Quality Index, Clustering and GIS Techniques

The objective of this research is to develop a tool for planning and managing the water quality of River Godavari. This is achieved by classifying the pollution levels of Godavari River into several categories using water quality index and a clustering approach that ensure simple but accurate information about the pollution levels and water characteristics at any point in Godavari River in Maharashtra. The derived water quality indices and clusters were then visualized by using a Geographical Information System to draw thematic maps of Godavari River, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Godavari River. This also provides an effective overview of those spots in the Godavari River where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment of the State’s water quality monitoring network. Three significant groups (less polluted, moderately and highly polluted sites) were detected by Cluster Analysis method. The results of Discriminant Analysis revealed that five parameters?i.e.?pH, Dissolved Oxygen (DO), Faecal Coliform (FC), Total Coliform (TC) and Ammonical Nitrogen (NH3-N) were necessary for analysis in spatial variation. Using discriminant function developed in the analysis, 100% of the original sites were correctly classified.

Exploring the Relationship between Spatiotemporal Variations in Air Quality and Meteorological Parameters before and during the COVID-19 Pandemic in Xi’an

The COVID-19 pandemic has significantly changed the air pollution of the world. The present study investigated the temporal and spatial variability in air quality in Xi’an, China, and its relationship with meteorological parameters during and before the COVID-19 pandemic. The outcomes of this study indicated that air pollutants, PM2.5, NO2, PM10, CO, and SO2 are likely to decrease during winter (25%, 50%, 30%, 40%, and 35%) to spring (30%, 55%, 38%, 50%, and 40%) and summer (40%, 58%, 60%, 55%, and 47%), respectively. However, the concentration of O3-8h increased by 40%, 55%, and 65% during winter, spring, and summer, respectively. The values of the air quality index decreased during the COVID-19 period. Furthermore, significant positive trends were reported in PM2.5, NO2, PM10, O3, and SO2, and no notable trends in CO during the COVID-19 pandemic. Both during and before the COVID-19 period, PM10, NO2, PM2.5, CO, and SO2 showed a negative correlation with the temperature and a moderately positive significant correlation between O3-8h and temperature. The findings of this study would help understand the air pollution circumstances in Xi’an before and during the COVID-19 period and offer helpful information regarding the implications of different air pollution control strategies.

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

Air quality is a critical concern for public health and environmental regulation. The Air Quality Index (AQI), a widely adopted index by the US Environmental Protection Agency (EPA), serves as a crucial metric for reporting site-specific air pollution levels. Accurately predicting air quality, as measured by the AQI, is essential for effective air pollution management. In this study, we aim to identify the most reliable regression model among linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression, and K-nearest neighbors (KNN). We conducted four different regression analyses using a machine learning approach to determine the model with the best performance. By employing the confusion matrix and error percentages, we selected the best-performing model, which yielded prediction error rates of 22%, 23%, 20%, and 27%, respectively, for LDA, QDA, logistic regression, and KNN models. The logistic regression model outperformed the other three statistical models in predicting AQI. Understanding these models' performance can help address an existing gap in air quality research and contribute to the integration of regression techniques in AQI studies, ultimately benefiting stakeholders like environmental regulators, healthcare professionals, urban planners, and researchers.

Spatiotemporal variations in ecological quality of Otindag Sandy Land based on a new modified remote sensing ecological index

Otindag Sandy Land in China is an important ecological barrier to Beijing;the changes in its ecological quality are major concerns for sustainable development and planning of this area.Based on principal component analysis and path analysis,we first generated a modified remote sensing ecological index(MRSEI)coupled with satellite and ground observational data during 2001–2020 that integrated four local indicators(greenness,wetness,and heatness that reflect vegetation status,water,and heat conditions,respectively,as well as soil erosion).Then,we assessed the ecological quality in Otindag Sandy Land during 2001–2020 based on the MRSEI at different time scales(i.e.,the whole year,growing season,and non-growing season).MRSEI generally increased with an upward rate of 0.006/a during 2001–2020,with clear seasonal and spatial variations.Ecological quality was significantly improved in most regions of Otindag Sandy Land but degraded in the southern part.Regions with ecological degradation expanded to 18.64%of the total area in the non-growing season.The area with the worst grade of MRSEI shrunk by 15.83%of the total area from 2001 to 2020,while the area with the best grade of MRSEI increased by 9.77%of the total area.The temporal heterogeneity of ecological conditions indicated that the improvement process of ecological quality in the growing season may be interrupted or deteriorated in the following non-growing season.The implementation of ecological restoration measures in Otindag Sandy Land should not ignore the seasonal characteristics and spatial heterogeneity of local ecological quality.The results can explore the effectiveness of ecological restoration and provide scientific guides on sustainable development measures for drylands.

Water quality changing trends of the Miyun Reservoir

In order to simulate changes in the water quality of the Miyun Reservoir dueto continuous descent of surface water level, a 3-D ecological hydrodynamic model was developedthrough coupling the water quality analysis simulation program (WASP) with the environmental fluiddynamics code (EFDC). The model was then calibrated and verified. Four scenarios (S1, S21, S22 andS23) were simulated using the model. Results show that the water quality of the Miyun Reservoirunder conditions of low surface water level is apparently affected by different amounts of inflowand different total phosphorus (TP) loadings. The chlorophyll-a concentration might exceed 10 μg/Lin many areas of the Miyun Reservoir (This limitative value is seen as a critical value ofeutrophication) when large loadings of TP enter due to the amount of inflow increasing. Results ofscenario S23 indicate that control of TP loadings can decrease chlorophyll-a concentrationeffectively, and the water quality of the Miyun Reservoir will improve or retain its status quo.

Trend Impact Analysis of Dissolved Nutrients Released From Soil on Water Quality in Qinglongshan Reservoir

During the storage of water and the initial running of a reservoir, part of the dissolved nutrients released from the soil in water will effect water quality. Taking Qinglongshan Reservoir as an example, estimating the value of the contribution of dissolved nutrients to the water quality and analyzing the trend or level of the dissolved nutrients effecting on the water quality under the soil nutrient inquiring, the soil nutrient monitoring, and the dissolving experiment of nutrients released from soil, also according to the capacity curve of Qinglongshan Reservoir.

GROUNDWATER QUALITY AND CONTAMINATION INDEX MAPPING IN CHANGCHUN CITY,CHINA

Groundwater in Changchun City, Jilin Province of China tends to be influenced by human activities. Chemical types of groundwater were detected in both shallow and deep groundwater were: HCO3--Ca2+ and HCO3--Ca2+·Mg2+ or HCO3--Mg2+·Ca2+; SO42--Ca2+ and SO42--Ca2+·Mg2+; Cl--Ca2+; and CO32--Na+. The deteriorations of groundwater quality due to the increase of TDS, NO3-+ NO2-(as Nitrogen) and TH contents have been observed from 1991 to 1998. Scatter analyses showed strong positive correlations between Ca2+, Cl-and NO3-ions and weak negative correlations between the depth of water table and Ca2+, SO42-, Cl-and NO3-ions. A mapping of contaminant index based on Chinese standard of groundwater showed that a large proportion of the groundwater in 1998 was deteriorated by human process. Despite their low values of sodium adsorption ratio (SAR), the most of the sampled wells were not suitable for drinking and agriculture purposes due to higher contents of NO3-, NO2-and Mn2+ ions.

Spatiotemporal changes of eco-environmental quality based on remote sensing-based ecological index in the Hotan Oasis,Xinjiang

The rapid economic development that the Hotan Oasis in Xinjiang Uygur Autonomous Region,China has undergone in recent years may face some challenges in its ecological environment.Therefore,an analysis of the spatiotemporal changes in ecological environment of the Hotan Oasis is important for its sustainable development.First,we constructed an improved remote sensing-based ecological index(RSEI)in 1990,1995,2000,2005,2010,2015 and 2020 on the Google Earth Engine(GEE)platform and implemented change detection for their spatial distribution.Second,we performed a spatial autocorrelation analysis on RSEI distribution map and used land-use and land-cover change(LUCC)data to analyze the reasons of RSEI changes.Finally,we investigated the applicability of improved RSEI to arid area.The results showed that mean of RSEI rose from 0.41 to 0.50,showing a slight upward trend.During the 30-a period,2.66% of the regions improved significantly,10.74% improved moderately and 32.21% improved slightly,respectively.The global Moran's I were 0.891,0.889,0.847 and 0.777 for 1990,2000,2010 and 2020,respectively,and the local indicators of spatial autocorrelation(LISA)distribution map showed that the high-high cluster was mainly distributed in the central part of the Hotan Oasis,and the low-low cluster was mainly distributed in the outer edge of the oasis.RSEI at the periphery of the oasis changes from low to high with time,with the fragmentation of RSEI distribution within the oasis increasing.Its distribution and changes are predominantly driven by anthropologic factors,including the expansion of artificial oasis into the desert,the replacement of desert ecosystems by farmland ecosystems,and the increase in the distribution of impervious surfaces.The improved RSEI can reflect the eco-environmental quality effectively of the oasis in arid area with relatively high applicability.The high efficiency exhibited with this approach makes it convenient for rapid,high frequency and macroscopic monitoring of eco-environmental quality in study area.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

Water Quality Analysis of Fuping Section of the Shichuan River Based on Different Evaluation Methods

In order to study the water quality of the Shichuan River basin in Fuping,Shaanxi Province,based on improved Nemerow index method,comprehensive pollution index method and principal component analysis method,eight water quality indexes such as pH,dissolved oxygen(DO),total dissolved solids(TDS),COD,total hardness,total phosphorus,total nitrogen and Zn in three monitoring sections of Fuping section of the Shichuan River in Shaanxi Province were detected and analyzed.The results show that the water quality of the surface water in the Shichuan River basin is gradeⅢorⅣwater,that is,the water is slightly polluted and moderately polluted.It is necessary to monitor the water quality after regulation and clarify the main factors causing the water pollution.

A Comprehensive Assessment of Water Quality at the Rosetta Branch of the Nile River, Egypt

The aim of the present study is to assess the water quality along the Rosetta branch of the Nile River, Egypt. The study area extends from upstream of the EI-Rahawy drain to the end of the branch. The correlation matrix was performed to help identify the nature of correlations between the different parameters. The WQI （water quality index） was calculated seasonally at different points along the Rosetta branch to provide a simple indicator of water quality at these points. The results of WQI calculations showed that the fecal coliform is the main cause of poor water quality along the Rosetta branch. A statistical analysis was also performed using a two-way ANOVA （analysis of variance） to identify the significant sources of water pollution and to determine the impact of the parameters on a mass loading. A significant difference was observed between the impacts of the pollution sources on the water quality. Also, a significant difference was observed between the impacts of each parameter in the mass loading. The results showed that the E1-Rahawy, Tala and Sabal drains are the major sources for water quality degradation along the Rosetta branch and that the effect of the EI-Tahrir and the Zawyet El-Baher drains on the water quality is not significant.

Assessment and mapping of environmental quality in agricultural soils of Zhejiang Province, China

Heavy metal concentrations in agricultural soils of Zhejiang Province were monitored to indicate the status of heavy metal contamination and assess environmental quality of agricultural soils. A total of 908 soil samples were collected from 38 counties in Zbejiang Province and eight heavy metal （Cd, Cr, Pb, Hg, Cu, Zn, Ni and As） concentrations had been evaluated in agricultural soil. It was found 775 samples were unpolluted and 133 samples were slightly polluted and more respectively, that is approximately 14.65% agricultural soil samples had the heavy metal concentration above the threshold level in this province by means of Nemerow＇s synthetical pollution index method according to the second grade of Standards for Soil Environmental Quality of China （GB15618- 1995）. Contamination of Cd was the highest, followed by Ni, As and Zn were lower correspondingly. Moreover, Inverse Distance Weighted （IDW） interpolation method was used to make an assessment map of soil environmental quality based on the Nemerow＇s pollution index and the soil environmental quality was categorized into five grades. Moreover, ten indices were calculated as input parameters for principal component analysis （PCA） and the principal components （PCs） were created to compare environmental quality of different soils and regions. The results revealed that environmental quality of tea soils was better than that of paddy soils, vegetable soils and fruit soils. This study indicated that GIS combined with multivariate statistical approaches proved to be effective and powerful tool in the mapping of soil contamination distribution and the assessment of soil environmental quality on provincial scale, which is beneficial to environmental protection and management decision-making by local government.

Statistical and Geospatial Assessment of Groundwater Quality in the Megacity of Karachi

Inserting Groundwater quality variability and sources potentially contributing to aquifer recharge was evaluated in metropolitan Karachi. Selected sampling sites were characterized by large waste dumping sites, industrial zones, and the presence of open streams receiving heavy loads of industrial and domestic wastes. Levels of pH, electrical conductivity (EC), fluoride (F-), chloride (Cl-), bromide (Br-), nitrate-N (NO-3-N), sulfate (SO2-4), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), and ammonium (NH+4) were determined and compared with the WHO permissible limits. Concentrations of the measured ions were in the order of Cl- > Na+ > SO2-4 > Mg2+ > Ca2+ > NO-3-N > K+ > F- > Br-. EC values were above the WHO guidelines, representing the presence of high ionic concentration in the groundwater. The health risk index (HRI) for indicated that inhabitants of Karachi are at risk of high exposure. Ingestion of high concentrations of NO-3-N in water can cause methemoglobinemia and birth defects. Results of multivariate statistical analysis, principal component analysis (PCA), cluster analysis (CA), and geographic information system (GIS) map analysis revealed that human activities are leading to adverse effects on the existing groundwater quality in Karachi.

Clusterization of Surface Water Quality and Its Relation to Climate and Land Use/Cover

The quality of surface water is rapidly changing due to climatic variations, natural processes, and anthropogenic activities. The objectives of this study were to classify and analyze the surface water quality of 12 major rivers of Alberta on the basis of 17 parameters during the period of five years (i.e., 2004-2008) using principal component analysis (PCA), total exceedance model and clustering technique. Seven major principal components (PCs) with variability of about 89% were identified. These PCs were the indicators of watershed geology, mineralization and anthropogenic activities related to land use/cover. The seven dominant parameters revealed from the seven PCs were total dissolved solids (TDS), true color (TC), pH, iron (Fe), fecal coliform (FC), dissolved oxygen (DO), and turbidity (TUR). The normalized data of dominant parameters were used to develop a model for obtaining total exceedance. The exceedance values acquired from the total exceedance model were used to determine the patterns for the development of five clusters. The performance of the clusters was compared with the classes obtained in Canadian Water Quality Index (CWQI). Cluster 1, cluster 2, cluster 3, cluster 4 and cluster 5 showed agreements of 85.71%, 83.54%, 90.22%, 80.74%, and 83.40% with their respective CWQI classes on the basis of the data for all rivers during 2004-2008. The water quality was deteriorated in growing season due to snow melting. This methodology could be applied to classify the raw surface water quality, analyze the spatio-temporal trends and study the impacts of the factors affecting the water quality anywhere in the world.

Water Quality Assessment of Dachangshan ArtificialHabitat Development Demonstration Area

[Objective] The paper was to evaluate the water quality environment in Dachangshan artificial habitat development demonstration area.[Method] From 2013 to 2015, an environmental survey was conducted for eight voyages in Dachangshan artificial habitat development demonstration area of Changhai County, Dalian City, and 20 hydrochemical indexes including salinity, pH, and COD were monitored. The water quality of thesea area was analyzed by principal component analysis and single factor index method. [Result] Except for that the control area of the August 2014voyage belonged to IIclass sea water standard, the water quality in other stations of all voyages conformed toIclass sea water standard. Totally 20water quality indicators were synthesized into six principal components using principal component analysis, which explained 79.165% of the results;the principal component score was ranged from -1.536 to 3.706; the score in August 2014 was the highest, and the evaluation results were basicallyconsistent with the results of single factor index analysis. [Conclusion] The overall water quality is good in Dachangshan artificial habitat development demonstration area.

Water and Sediment Quality Assessment of a Multipurpose Reservoir in India

Malampuzha reservoir is a multipurpose reservoir in south India. Seven water samples and four sediment samples were studied for the physico-chemical and bacteriological nature of the Malampuzha reservoir water and sediments. Bacteriological analysis indicated the microbial contamination of the reservoir and the physico-chemical characteristics indicated that the water is non potable directly. Analysis of irrigational water quality by SAR, Kelly＇s ratio and SSP indicates that the reservoir water is suitable for irrigation. Heavy metal pollution of the sediments was evaluated based on Sediment Quality Guidelines （SQG）, Pollution Load Index （PLI） and degree of contamination （Cd） of soil in four stations. Principal Component Analysis （PCA） was done to find out the possible linear combination of the original variables of trace metals. Results of PCA showed that no collinearity existed among the studied metals. However, emphasis on the monitoring of Cu and Ni should be preferred because of its alarmingly higher contamination value.