Spatial-temporal Variation Characteristics of Water Quality in the Lower Reaches of the Nenjiang River

As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.

Variational Quality Control of Non-Gaussian Innovations in the GRAPES m3DVAR System: Mass Field Evaluation of Assimilation Experiments

The existence of outliers can seriously influence the analysis of variational data assimilation.Quality control allows us to effectively eliminate or absorb these outliers to produce better analysis fields.In particular,variational quality control(VarQC) can process gray zone outliers and is thus broadly used in variational data assimilation systems.In this study,governing equations are derived for two VarQC algorithms that utilize different contaminated Gaussian distributions(CGDs): Gaussian plus flat distribution and Huber norm distribution.As such,these VarQC algorithms can handle outliers that have non-Gaussian innovations.Then,these VarQC algorithms are implemented in the Global/Regional Assimilation and PrEdiction System(GRAPES) model-level three-dimensional variational data assimilation(m3 DVAR) system.Tests using artificial observations indicate that the VarQC method using the Huber distribution has stronger robustness for including outliers to improve posterior analysis than the VarQC method using the Gaussian plus flat distribution.Furthermore,real observation experiments show that the distribution of observation analysis weights conform well with theory,indicating that the application of VarQC is effective in the GRAPES m3 DVAR system.Subsequent case study and longperiod data assimilation experiments show that the spatial distribution and amplitude of the observation analysis weights are related to the analysis increments of the mass field(geopotential height and temperature).Compared to the control experiment,VarQC experiments have noticeably better posterior mass fields.Finally,the VarQC method using the Huber distribution is superior to the VarQC method using the Gaussian plus flat distribution,especially at the middle and lower levels.

Spatiotemporal Variation Characteristics of Water Quality in the Yinma River

As an important river in the central part of Jilin Province, the Yinma River plays a crucial role in the daily lives of the people in Jilin Province. In this paper, 15 cross sections were selected in the Yinma River basin. Based on the water quality monitoring data from 2012 to 2021, referring to the Environmental Quality Standards for Surface Water (GB 3838-2002) and historical monitoring data of the river, dissolved oxygen (DO), five-day biochemical oxygen demand (BOD 5), permanganate index (COD Mn ), chemical oxygen demand (COD), ammonia nitrogen (NH 4-N), total phosphorus (TP), and total nitrogen (TN) were determined as 7 evaluation indicators, and the water quality of 15 cross sections in the Yinma River basin was comprehensively evaluated. A characteristic analysis was conducted on the water quality of the Yinma River, and its pollution sources were identified. Based on the conclusions, constructive control measures were proposed.

Variation and mechanisms of clastic reservoir quality in the Paleogene Shahejie Formation of the Dongying Sag, Bohai Bay Basin, China

Reservoir quality varies greatly in the Shahejie Formation in the Dongying Sag. It is essential to analyze the variation and mechanisms of reservoir quality for determining the controlling factors based on cores, porosity measurements and fluid inclusion techniques and so on. The sandstones in the fluvial, （fan） delta-front have the best reservoir quality due to the depositional conditions mechanically controlling the petrology configuration and the primary porosity, and chemically influencing the diagenesis and development of secondary pores. The activity of the boundary faults and the sedimentary facies dominate the variation of reservoir quality in different areas and intervals. The reservoir quality varies with the position of sandstone beds in different vertical models of sandstone and mudstone. This mainly arose from the strong cementation or strong dissolution in the sandstone caused by the diagenesis evolution of adjacent mudstone. With higher oil saturation reservoir quality is better because the hydrocarbon charge favors dissolution and restricts cementation. Diagenesis, depositional conditions and tectonic setting are the key controls of reservoir quality in the Shahejie Formation of the Dongying Sag.

Spatial and temporal variations of water quality in Cao-E River of eastern China

Evaluation and analysis of water quality variations were performed with integrated consideration of water quality parameters, hydrological-meteorologic and anthropogenic factors in Cao-E River, Zhejiang Province of China. Cao-E River system has been polluted and the water quality of some reaches are inferior to Grade V according to National Surface Water Quality Standard of China （GB2002）. However, mainly polluted indices of each tributary and mainstream are different. Total nitrogen （TN） and total phosphorus （TP） in the water are the main polluted indices for mainstream that varies from 1.52 to 45.85 mg/L and 0.02 to 4.02 mg/L, respectively. TN is the main polluted indices for Sub-watershed Ⅰ, Ⅱ, Ⅳ and Ⅴ（0.76 to 18.27 mg/L）. BOD5 （0.36 to 289.5 mg/L）, CODMn （0.47 to 78.86 mg/L）, TN （0.74 to 31.09 mg/L） and TP （0 to 3.75 mg/L） are the main polluted indices for Sub-watershed Ⅲ. There are tow pollution types along the river including nonpoint source pollution and point source pollution types. Remarkably temporal variations with a few spatial variations occur in nonpoint pollution type reaches （including mainstream, Sub-watershed Ⅰ and Ⅱ） that mainly drained by arable field and/or dispersive rural dwelling district, and the maximum pollutant concentration appears in flooding seasons. It implied that the runoff increases the pollutant concentration of the water in the nonpoint pollution type reaches. On the other hand, remarkably spatial variations occur in the point pollution type reaches （include Sub-watershed Ⅲ, Ⅳ and Ⅴ） and the maximum pollutant concentration appears in urban reaches. The runoff always decreases the pollutant concentration of the river water in the seriously polluted reaches that drained by industrial point sewage. But for the point pollution reaches resulted from centralized town domestic sewage pipeline and from frequent shipping and digging sands, rainfall always increased the concentration of pollutant （TN） in the river water too. Pollution controls were respectively suggested for these tow types according to different pollution causes.

Impacts of water quality variation and rainfall runoff on Jinpen Reservoir,in Northwest China

The seasonal variation characteristics of the water quality of the Jinpen Reservoir and the impacts of rainfall runoff on the reservoir were investigated. Water quality monitoring results indicated that, during the stable stratification period, the maximum concentrations of total ni- trogen, total phosphorus, ammonia nitrogen, total organic carbon, iron ion, and manganese ion in the water at the reservoir bottom on September 6 reached 2.5 mg/L, 0.12 mg/L, 0.58 mg/L, 3.2 mg/L, 0.97 mg/L, and 0.32 rag/L, respectively. Only heavy storm runoff can affect the main reservoir and cause the water quality to seriously deteriorate. During heavy storms, the stratification of the reservoir was destroyed, and the reservoir water quality consequently deteriorated due to the high-turbidity particulate phosphorus and organic matter in runoff. The turbidity and concentrations of total phosphorus and total organic carbon in the main reservoir increased to 265 NTU, 0.224 mg/L, and 3.9 mg/L, respectively. Potential methods of dealing with the water problems in the Jinpen Reservoir are proposed. Both in stratification and in storm periods, the use of measures such as adjusting intake height, storing clean water, and releasing turbid flow can be helpful to safeguarding the quality of water supplied to the water treatment plants.

DYNAMIC VARIATIONS OF WATER QUALITY IN TAIHU LAKE AND MULTIVARIATE ANALYSIS OF ITS INFLUENTIAL FACTORS

Dynamic variation of water quality in Meiliang Bay and part of West Taihu Lake has been analysed based on data from 1991 to 1992. Principal Component Analysis is used to reveal the mutual relationships of various factors. It is shown that there existis an obvious spatial and temporal variation in the main factors of water quality. Annual values of TP, CON, TN, Chl-a and conductivity decrease evidently from inner Meiliang Bay to the outer from north to south. TP and TN fluctuate seasonally with much higher value in winter. This is particularly true for the mouth of Liangxi River. In addition, the Chl-1 has a synchronous variation with water temperature, although being lagged a little, and closely relates to TP and TN. Finally, the results from Principal Component Analysis show that TP, TN, SS (or SD), water temperature and Chl-a are the most influential factors to water qualuty in this area, and both suspensions and algae can contribute to transparency to Taihu Lake.

A novel deep learning framework with variational auto-encoder for indoor air quality prediction

Exposure to poor indoor air conditions poses significant risks to human health, increasing morbidity and mortality rates. Soft measurement modeling is suitable for stable and accurate monitoring of air pollutants and improving air quality. Based on partial least squares (PLS), we propose an indoor air quality prediction model that utilizes variational auto-encoder regression (VAER) algorithm. To reduce the negative effects of noise, latent variables in the original data are extracted by PLS in the first step. Then, the extracted variables are used as inputs to VAER, which improve the accuracy and robustness of the model. Through comparative analysis with traditional methods, we demonstrate the superior performance of our PLS-VAER model, which exhibits improved prediction performance and stability. The root mean square error (RMSE) of PLS-VAER is reduced by 14.71%, 26.47%, and 12.50% compared to single VAER, PLS-SVR, and PLS-ANN, respectively. Additionally, the coefficient of determination (R2) of PLS-VAER improves by 13.70%, 30.09%, and 11.25% compared to single VAER, PLS-SVR, and PLS-ANN, respectively. This research offers an innovative and environmentally-friendly approach to monitor and improve indoor air quality.

Application of Projection Pursuit Evaluation Model Based on Real-Coded Accelerating Genetic Algorithm in Evaluating Wetland Soil Quality Variations in the Sanjiang Plain, China

A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.

DYNAMIC VARIATIONS OF WATER QUALITY IN TAIHU LAKE AND MULTIVARIATE ANALYSIS OF ITS INFLUENTIAL FACTORS

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WATER RESOURCES TRANSFORMATION AND WATER QUALITY VARIATION IN THE URUMQI RIVER BASIN

Like other inland basins in arid regions, the natural vertical zones create special conditions for water resources transformation in the Urumqi River Basin. In the course of water resources transformation and utilization, the chemical composition and degree of mineralization are influenced by both geographic conditions and human activities. Although the Urumqi River is rather small in runoff and rather short in flow distance, the water quality changes substantially along the river. However, ion concentrations of surface and ground water in the whole basin are relatively low, generally less than 1 g/L. Therefore, the basin is good at providing low-mineralized water. The pollution is not so serious and the water impurity does not surpass the national standard for drinking. As long as people are conscious with protecting water quality and reducing the further water pollution, it is possible for harm of the slight pollution to be eliminated.

Spatial and Temporal Variation of Urban Air Quality: A GIS Approach

This study investigated the seasonal variation of ambient air quality status of Burdwan town using GIS approach. Concentration of SOR2R (sulphur dioxide), NOR2R (nitrogen dioxide) and RSPM (respiratory suspended particulate matter) were measured once a week for 24 hour in both premonsoon and postmonsoon season. The seasonal average concentration of the RSPM, SOR2R and NOR2R in premonsoon season was observed to be 188.56 ± 88.63, 5.12 ± 6.27 and 92.51 ± 64.78 mg/mP3P respectively whereas in postmonsoon it was 53.03 ± 38.27, 8.51 ± 7.11 and 162.85 ± 184.80 mg/mP3P respectively. Statistical analysis showed the significant monsoonal effect on mean difference of RSPM, SOR2R and NOR2R concentration. Postmonsoon concentration of ambient SOR2R and NOR2R were observed to be higher than premonsoon, suggesting longer residence times of these pollutants in the atmosphere due to stagnant conditions and low mixing height. Spatial distribution of pollutants throughout the town in both the season was represented by digital elevation model (DEM). On the basis of Air Quality Index (AQI) a GIS based air pollution surface models were generated in both the seasons by means of Inverse Distance Interpolation (IDINT) technique. From the output surface model it was found that in comparison to premonsoon there was a significant increase of clean and fairly clean area and decrease of moderately polluted area of the town during postmonsoon.

Water quality variation of mining-subsidence lake during the initial stage： cases study of Zhangji and Guqiao Mines

Four quarters＇ water collecting and monitoring samples were done in the mining subsidence lakes of different water storing periods （ 2 to 7 years）, considering the water storing time and pollution sources state of the subsidence lakes. The following indexes were discussed such as organic indexes （TOC, CODM,, BOD, COD）, nutrient salts （TN, NH4^＋, NO3, NO,, Kjeldahl Nitrogen, TP, PO4^3- ）, etc. It is shown that water quality of the mining subsidence lake during the initial stage （ 2 years to 7 years） can stay relatively stable with a fluctuation during different quarters in a year, which can reach class Ill or IV of the Surthcc Water Environmental Quality Standard.

ANALYSIS ON THE SPATIAL DISTRIBUTION VARIATION CHARACTERISTIC OF URBAN HEAT ENVIRONMENTAL QUALITY AND ITS MECHANISM——A Case Study of Hangzhou City

Urban heat environmental quality (UHEQ) is affected by the interacting of weather condition and underlying surface framework of urban area. In the last two decades, many researchers from domestic and overseas have studied many problems at the aspect of urban heat environment such as urban heat islands, urban air temperature and their relation with urban land cover, city population, air pollution etc. In the recent years, Hangzhou, acting as a center city of Zhejiang Province in China, its urbanization quantum and quantity have both changed greatly, in particular, representing as business affairs building, resident real property and all kinds of specialty market having arisen in built-up zone. Based on Landsat TM images data in 1991 and 1999, urban underlying surface temperature value and Normalized Difference Vegetation Index (NDVI) were calculated using image interpreting and supervised classification technique by remote sensing software ERDAS image 8.4. The relation model between urban underlying surface temperature (UUST) and urban air temperature was setup according to the certain correlation pattern. Reference to the relational standard of assessing human comfort and other meteorology data of Hangzhou City in summer, the spatial distribution characteristic and the spatial variation degree of human comfort of heat environmental quality are estimated and mapped on a middle scale, that is, in six districts of Hangzhou City . Then the paper reveals the main characteristic of spatial variation from 1991 to 1999. Lastly, the change mechanism is analyzed and discussed from the viewpoint of city planning, construction and environmental protection.

Spatial and Temporal Variation in Water Quality of River Benue, Nigeria

The study investigates the spatial and temporal variation in water quality parameters at ten different locations along River Benue for twelve consecutive months. In order to explore the spatial variation among different stations and seasonal changes, multivariate analysis of variance (MANOVA) was used to group these on the basis of spatial similarities. MANOVA on season and station shows that there is no significant difference between the stations investigated while there is for the seasons. This could be viewed as a resulting from the narrow spatial sampling interval (12 km at 0.7% total length of River Benue). However, discriminate analysis identified all the parameters to discriminate between the three seasons with 99.2% correct assignations. Two discriminate functions were found and the total variance cumulative was 100% between seasons. The first function explained 64.8% of the total variance between the seasons while the second function explained 35.2%. Total solids (TS) were the highest contributor in discriminate functions 1 and 2. Therefore, discriminate function analysis would enable us to predict the likely season a water sample from metropolitan Makurdi was collected given the values of the water quality parameters. It also enables us to conclude that all the parameters were responsible for significant seasonal variations in River Benue water quality.

Assessment of Spatio-Temporal Variations in Water Quality of Shailmari River, Khulna (Bangladesh) Using Multivariate Statistical Techniques

Surface water has become one of the most vulnerable resources on the earth due to deterioration of its quality from diverse sources of pollution. Understanding of the spatiotemporal distribution of pollutants and identification of the sources in the river systems is a prerequisite for the protection and sustainable utilization of the water resources. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA) were applied in this study to investigate the temporal and spatial variations of water quality and appoint the major factors of pollution in the Shailmari River system. Water quality data for 14 physicochemical parameters from 11 monitoring sites over the year of 2014 in three sampling seasons were collected and analyzed for this study. Kruskal-Wallis test showed significant (p < 0.01) temporal and spatial variations in all of the water quality parameters of the river water. Principal component analysis (PCA) allowed extracting the contributing parameters affecting the seasonal water quality in the river system. Scatter plots of the PCs showed the tidal and spatial variation within river system and identified parameters controlling the behavior in each case. Factor analysis (FA) further reduced the data and extracted factors which are significantly responsible for water quality variation in the river. The results indicate that the parameters controlling the water quality in different seasons are related with salinity, anthropogenic pollution (sewage disposal, effluents) and agricultural runoff in pre-monsoon;precipitation induced surface runoff in monsoon;and erosion, oxidation or organic pollution (point and non-point sources) in post-monsoon. Therefore, the study reveals the applicability and usefulness of the multivariate statistical methods in assessing water quality of river by identifying the potential environmental factors controlling the water quality in different seasons which might help to better understand, monitor and manage the quality of the water resources.

Spatiotemporal variations and driving factors of habitat quality in the loess hilly area of the Yellow River Basin:A case study of Lanzhou City,China

Rapid industrialization and urbanization have led to the most serious habitat degradation in China,especially in the loess hilly area of the Yellow River Basin,where the ecological environment is relatively fragile.The contradiction between economic development and ecological environment protection has aroused widespread concern.In this study,we used the habitat quality of Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST-HQ)model at different scales to evaluate the dynamic evolution characteristics of habitat quality in Lanzhou City,Gansu Province of China.The spatiotemporal variations of habitat quality were analyzed by spatial autocorrelation.A Geographical Detector(Geodetector)model was used to explore the driving factors that influencing the spatial differentiation of habitat quality,including natural factors,socio-economic factors,and ecological protection factors.The results showed that the habitat quality index of Lanzhou City decreased from 0.4638 to 0.4548 during 2000-2018.The areas with reduced the habitat quality index were mainly located in the Yellow River Basin and Qinwangchuan Basin,where are the main urban areas and the new economic development areas,respectively.The spatial distribution of habitat quality presented a trend of high in the surrounding areas and low in the middle,and showed a significant positive spatial autocorrelation.With the increase of study scale,the spatial distribution of habitat quality changed from concentrated to dispersed.The spatial differentiation of habitat quality in the study area was the result of multiple factors.Among them,topographic relief and slope were the key factors.The synergistic enhancement among these driving factors intensified the spatial differentiation of habitat quality.The findings of this study can provide a scientific basis for land resources utilization and ecosystem restoration in the arid and semi-arid land.

Variation in Parameters of Ambient Air Quality in National Capital Territory (NCT) of Delhi (India)

Air Pollution is an escalating problem worldwide fuelled by increasing anthropogenic activities, speedy development, rapid industrialization, transportation, superfluous use of fossil fuel consumption, increasing global power needs, etc. Also the diverse meteorological factors influence our environment to a great extent. Population explosion has led to remarkable increase in vehicular population. The use solely depends upon the lifestyle of the citizen. Any change in the lifestyle has a remarkable effect on the air we breathe. A comprehensive database for pollution levels from the year 2006 to 2010 was analyzed for a main traffic intersection and a non-traffic area in Delhi (India). The paper asserts that pollutant concentration levels on weekend are lower than those on weekdays (increase on Sundays with respect to weekdays is CO 2.98 times, PM2.5 1.18 times, NO 1.62 times, NO2 5.76 times, SO2 1.27 times and O3 1.15 times). The pollution levels have been found to attenuate on public holidays and weekends. Pollution can hence be related to the weekly cycle of human activities. Pollutions due to vehicular emissions on roads, rails, air or water all serve as major sources of pollution. Hence, viably possible solutions for pollution control can also be achieved by controlling the magnitude of traffic flow on roads.

Seasonal and Spatial Variations in Water Physicochemical Quality of Coastal Potou Lagoon (Côte d’Ivoire, Western Africa)

The study investigates the seasonal and spatial variations in water quality parameters at four different locations along Potou lagoon for seventeen consecutive months. In order to explore spatial variation among different stations and seasonal changes, no parametric test of ANOVA was used to compare the mean values of the tested parameters for all the different sampling sites and seasons. Seasonal observations on water quality parameters and chlorophyll-a in Potou coastal lagoon revealed that the coastal water was significantly influenced by freshwater during the long and short rainy seasons. The seasonal significant variation (p a increased during the long dry season, whereas, the concentration of nutrients (nitrite, nitrate, ammonium and soluble reactive phosphorus) increased in the rainy periods. Contrary to the seasonal variation, a spatial homogeneity (horizontal) was registered for all variables, a condition related to the low human occupation in the lagoon watershed. Comparing this study with others conducted in Potou lagoon in 2008, no critical differences that evidence alteration in the water quality were found.

Effects of PHC on Water Quality of Jiaozhou Bay Ⅰ. Annual Variation of PHC Content

Based on investigation data on PHC in Jiaozhou Bay, China from 1979 to 1983, the monthly, seasonal and annual variations of PHC content in Jiaozhou Bay were studied. The results showed that from 1979 to 1983, Jiaozhou Bay was polluted by PHC seriously and then slightly in spring and summer, while Jiaozhou Bay was polluted by PHC slightly in autumn. During 1979 -1983, PHC content in the water body of Jiaozhou Bay decreased year by year, and it was close to the background value gradually. Moreover, the reduction was obvious in spring and summer but very slight in autumn. Therefore, the water quality of Jiaozhou Bay became better.