Ecological environmental quality evaluation and driving factor analysis of the Lijiang River Basin,based on Google Earth Engine

For regional ecological management,it is important to evaluate the quality of ecosystems and analyze the underlying causes of ecological changes.Using the Google Earth Engine(GEE)platform,the remote sensing ecological index(RSEI)was calculated for the Lijiang River Basin in Guangxi Zhuang Autonomous Region for 1991,2001,2011,and 2021.Spatial autocorrelation analysis was employed to investigate spatiotemporal variations in the ecological environmental quality of the Lijiang River Basin.Furthermore,geographic detectors were used to quantitatively analyze influencing factors and their interaction effects on ecological environmental quality.The results verified that:1)From 1991 to 2021,the ecological environmental quality of the Lijiang River Basin demonstrated significant improvement.The area with good and excellent ecological environmental quality in proportion increased by 19.69%(3406.57 km^(2)),while the area with fair and poor ecological environmental quality in proportion decreased by 10.76%(1860.36 km^(2)).2)Spatially,the ecological environmental quality of the Lijiang River Basin exhibited a pattern of low quality in the central region and high quality in the periphery.Specifically,poor ecological environmental quality characterized the Guilin urban area,Pingle County,and Lingchuan County.3)From 1991 to 2021,a significant positive spatial correlation was observed in ecological environmental quality of the Lijiang River Basin.Areas with high-high agglomeration were predominantly forests and grasslands,indicating good ecological environmental quality,whereas areas with low-low agglomeration were dominated by cultivated land and construction land,indicating poor ecological environmental quality.4)Annual average precipitation and temperature exerted the most significant influence on the ecological environmental quality of the basin,and their interactions with other factors had the great influence.This study aimed to enhance understanding of the evolution of the ecological environment in the Lijiang River Basin of Guangxi Zhuang Autonomous Region and provide scientific guidance for decision-making and management related to ecology in the region.

Marine environmental quality, pollution monitoring and environmental management

Chinese government has adopted a series of management measures to prevent and manage marine pollution and to protect ocean bio resources and ecosystem. The key points of Chinese marine environmental quality status, pollution monitoring and environmental management since 1980' were discussed in this paper. Those included the investigations of Chinese coast environmental quality, monitoring techniques and standards, as well as the marine environmental management measures. Recent status of marine environmental pollution and the monitoring network in China were also introduced.

On Environmental Quality Standards and Finding of Liability for Environmental Pollution Torts

Though bearing technical and legal attributes,environmental quality standards are neither rules nor regulatory documents.With the binding force coming from the legal norms where they are cited,environmental quality standards are designed and implemented as a yardstick for measuring environmental quality.They also play a role in the functions of goal setting,merit appraisals,inspiration,supervision and accountability in conjunction with the legal norms and administrative plans where they are cited.Characteristically,environmental quality standards adopt sort management in concept,take holistic values and methodologies,establish phased goals and accept the resulting policy choices.These standards are not applicable to determine tort liability caused by environmental pollution from the perspective of legal norms but provide limited evidence for finding the same in the view of factual analysis by delivering scientific support to prove negative effects on the environment.Hence,environmental quality standards do contribute to finding torts,thus making the production of evidence less difficult.Also,they can be used to prove the relevance between torts and damage.

Perception of the Residential Environmental Quality of Yenagoa Metropolis,Nigeria

Residential environmental quality(REQ)affects human health and quality of life(QoL).Therefore,this study as­sessed residents’perception of the REQ of the Yenagoa metropolis.Data for the study were sourced from the 400 ad­ministered questionnaires,which required respondents to rate their REQ based on seven selected indicators(air quality,drinking water quality,housing location,sanitation,waste management,housing accessibility and noise pollution).The respondents were sampled using the multistage sampling technique.The data were analyzed using frequency,percent­age,t-test,ANOVA and REQ model.The findings show that the overall calculated REQ of Yenagoa was classified as“good quality”.The best-rated indicator was drinking water quality,while the least-rated was noise pollution.Ratings based on respondents’sex,income and educational status recorded similar results.Also,the respondents’perception of the REQ across the four zones was similar as the calculated ratings of all the zones fell under the“good quality”classification.Furthermore,the hypotheses tested revealed that there were no significant differences in the perception of the REQ by sex and income status,while significant variation exists by education status.Despite the general“good quality”rating,there is still room for improvement,especially in the areas of noise pollution,sanitation and housing location,which received relatively low ratings.

Illustrating the multi-stakeholder perceptions of environmental pollution based on big data:Lessons from China

The relationship between stakeholders and the environment influences sustainable development and human wellbeing.To illustrate the multi-stakeholder perceptions of environmental pollution in China,we interpreted a feedback loop in the perception-behavior-environment nexus from the perspective of the coupled human-environment system,measured the differences of environmental perceptions among five stakeholders(the public,government,media,companies,and scientists)and regions(including 31 provinces,autonomous regions,and municipalities in China,with exceptions of Taiwan of China,Hong Kong of China,and Macao of China due to a lack of data)using big data,and made a comparison between the perceptions and the actual pollution situation.The results showed that the five stakeholders exhibited similar perceptions of environmental pollution at the national scale,with air pollution being of most concern,followed by water pollution and soil pollution.There were significant spatial differences in environmental perceptions.All stakeholders in the developed regions in eastern China paid relatively high attention to environmental issues,while those in the northwestern regions paid much less attention.There existed a mutual influence and interaction among the different stakeholders.More attention should be paid to air pollution in Xinjiang Uygur Autonomous Region and Ningxia Hui Autonomous Region,water pollution in Hainan Province,Inner Mongolia Autonomous Region,Heilongjiang Province,and Jilin Province,and soil pollution in Hainan Province,Fujian Province,and Jilin Province.This paper provides a research paradigm on multi-stakeholder environmental perceptions based on big data,and the results provide a background reference for regional environmental governance.

Big Data Analytics with Artificial Intelligence Enabled Environmental Air Pollution Monitoring Framework

Environmental sustainability is the rate of renewable resourceharvesting, pollution control, and non-renewable resource exhaustion. Airpollution is a significant issue confronted by the environment particularlyby highly populated countries like India. Due to increased population, thenumber of vehicles also continues to increase. Each vehicle has its individualemission rate;however, the issue arises when the emission rate crosses thestandard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop predictionapproaches to monitor and control pollution using real time data. With thedevelopment of the Internet of Things (IoT) and Big Data Analytics (BDA),there is a huge paradigm shift in how environmental data are employed forsustainable cities and societies, especially by applying intelligent algorithms.In this view, this study develops an optimal AI based air quality prediction andclassification (OAI-AQPC) model in big data environment. For handling bigdata from environmental monitoring, Hadoop MapReduce tool is employed.In addition, a predictive model is built using the hybridization of ARIMAand neural network (NN) called ARIMA-NN to predict the pollution level.For improving the performance of the ARIMA-NN algorithm, the parametertuning process takes place using oppositional swallow swarm optimization(OSSO) algorithm. Finally, Adaptive neuro-fuzzy inference system (ANFIS)classifier is used to classify the air quality into pollutant and non-pollutant.A detailed experimental analysis is performed for highlighting the betterprediction performance of the proposed ARIMA-NN method. The obtainedoutcomes pointed out the enhanced outcomes of the proposed OAI-AQPCtechnique over the recent state of art techniques.

The impact of foreign trade and FDI on environmental pollution

Over the past 30 years China＇s economy has made tremendous development and going on the road of opening-up is an important aspect of the successful experience, which should be unswervingly adhered to in the further. However, rationally looking at how different the impact of foreign economic activities on China＇s economy and society is economic workers＇ main task. From 1982 to 2006, based on six categories of China＇s environmental indicators, the paper improves the entropy method to calculate the environmental pollution index which can represent China＇s overall environmental situation, uses the VAR model of the impulse response function and variance decomposition method to study the impact of foreign trade, FDI on China＇s environmental pollution in the long-term. The results show that, FDI and import trade is conducive to the improvement of the quality of our environment and export trade is the deterioration of our environment, ＂pollution haven＂ hypothesis is proved in China. Export trade is an important variable that aggravates environmental pollution.

R/S method for evaluation of pollutant time series in environmental quality assessment

The significance of the fluctuation and randomness of the time series of each pollutant in environmental quality assessment is described for the first time in this paper. A comparative study was made of three different computing methods： the same starting point method, the striding averaging method, and the stagger phase averaging method. All of them can be used to calculate the Hurst index, which quantifies fluctuation and randomness. This study used real water quality data from Shazhu monitoring station on Taihu Lake in Wuxi, Jiangsu Province. The results show that, of the three methods, the stagger phase averaging method is best for calculating the Hurst index of a pollutant time series from the perspective of statistical regularity.

Changes in Water Quality of Origin Flows of Hotan River Based on Nemorow Pollution Index

[Objective] The study aimed to analyze water quality of origin flows of Hctan River using Nemorow pollution index method. [Method] Based on data monitored at four monitoring sections of Yorungkash River and Karakash River dudng 2001 -2005, water quality of Hotan River was assessed by using Nemorow pollution index method. [ Result] During 2001 -2005, Yorungkash River and Karakash River had clean water reaching the first standard. Nemorow pollution index was 0.15 -0.69 at the first section of Yorungkash River, and it was 0.23 -0.46 at its last section; there were few changes in water quality at the last section, while Nemorow pollution index showed a downward trend at the first section. Nemorow pollu- tion index was 0.23 -0.65 at the first section of Karakash River, and it was 0.23 -0.47 at its last section, showing a downward trend at its last section. [Condusion] Water quality of Hotan River belonged to first-class clean water.

Socio-Environmental Impact of Water Pollution on the Mid-canal (<i>Meda Ela</i>), Sri Lanka

Unplanned urban population growth in developing countries such as Sri Lanka exert pressures on the sectors of water supply, sewage disposal, waste management, and surface drainage in the cities as well as their surrounding areas. The Mid-canal is considered the most polluted surface water body in the Kandy district of Sri Lanka and contributes significantly to pollution of the Mahaweli River. Health problems in the nearby population may well be associated with environmental degradation and related to deteriorated water quality. The overall objectives of this study were to identify the socio-economic status of the community settled along the Meda Ela banks, and to examine the current water quality status of the Meda Ela and possible impacts of the nearby residents on water quality. Additionally, we propose remedial measures concerning wastewater and solid waste disposal to improve environmental conditions in this area.

Universal Index Formula of Parameterized Combination Operator for Eco-environmental Quality Evaluation

[Objective] The aim was to evaluate the regional eco-environmental quality by using the universal index formula of parameterization combination operator based normalized index values.[Method] Through setting reference values and normalized transformation formulae for typical ecological environmental indexes appropriately,the difference among the standard normalized values would become very small after normalized transformation,and the ecological environmental indices expressed by normalized values can be equivalent to normalized indices.Under certain optimization conditions,shuffled frog leaping based on immune evolutionary particle swarm optimization algorithm was applied to optimize the parameters in parameterization combination operator formula,and the universal index formula suited to eco-environmental quality assessment was established finally.[Result] The universal index formula of parameterization combination operator,appropriate for any m(1≤m≤23) ecological environmental indices,was used to assess the eco-environmental quality of towns surrounding Headland Reservoir,and the results were in full accordance with those of unascertained measure method,that is,the eco-environmental quality of five towns around Headland Reservoir was the fourth grade.[Conclusion]The universal index formula of parameterization combination operator,suited to eco-environmental quality evaluation,is simple and intuitive in form,easy in computation and universal in application.

Eco-environmental Quality Evaluation of Manasi River Basin in Recent 30 Years

Taking the Technical Specifications of Eco-environmental Quality Assessment enacted by the State Environmental Protection Administration in 2006 as the conceptual framework model and improving some indices and weights in the regulation,the eco-environmental assessment index system for Manas River Basin was established,and the eco-environmental quality index (EQI) of this basin from 1976 to 2005 was assessed based on the related data.The results indicated that the ecological quality index increased to 48.26 from 34.44 during 1976-2005.The biologic abundance index,vegetation coverage index and land deterioration index decreased,while there was an increase in water reticulation density index,environmental quality index and pollution load index,so the improvement and deterioration of the ecological environment coexisted in the basin.On the whole,the poor state of the basin ecological environment had turned into a general state,and the eco-environmental quality was developed towards favorable circle.The results also showed that the improved calculating method of EQI accorded with the actual situation of the research area.

Evaluation on Soil Heavy Metal Pollution of Agricultural Habitat Environment in Xi'an City

[Objective] This study aimed to understand and grasp the soil heavy metal pollution status of agricultural habitat environment in Xi＇an City. [Method] The soil heavy metal pollution status of pollution-free agricultural products-producing areas in 9 counties （districts） of Xi＇an City was investigated. A total of 609 soil samples were collected, and their Cd, Hg, As, Pb and Cr contents were determined. In addition, the heavy metal pollution status of the collected soil samples was evaluated by Nemerow index method. [Result] The pollution in Baqiao, Chang＇an; Gaoling, Lan- tian, Lintong and Yanliang was of grade I, belonging to clean level; the pollution in Hu County, Weiyang and Zhouzhi was of grade II, near the warning line, belong to relatively clean level. There was no large-area soil heavy metal pollution overall. The investigated areas could be used as production bases of pollution-free agricultural products and even high-quality agricultural products. However, the heavy met- als contents in some individual areas exceeded relevant soil environmental quality standards, and they should be avoided or forbidden during regional planning and selection of production area. [Conclusion] Soil heavy metal pollution of agricultural habitat environment in Xi＇an City is generally at good status. Targeting at the future development plan of Xi＇an City, feasible and scientific suggestions are put forward.

Analysis and Evaluation of Heavy Metal Environmental Quality of Irrigation Water in Vegetable Farmlands of Shandong Province

[Objective] The aim was to evaluate heavy metal environmental quality of irrigation water in vegetable farmlands of Shandong Province. [Method] Heavy metal contents including Hg,Cd,As,Cr (+6),Pb,Cu and Zn in irrigation water of main vegetable farmlands of Shandong Province were investigated by randomly sampling,and the environmental quality conditions of these heavy metals were evaluated by methods of single quality index and complex quality index. [Result] The results showed that the average contents of heavy metals in irrigation water of Shouguang,Laiyang,Jinxiang and Zhangqiu were all far lower than the limit values prescribed by 'Farmland Environmental Quality Evaluation Standards for Edible Agricultural Products' (HJ332-2006),and no heavy metal was found beyond the limit value in every sample. The single quality indices of the 7 elements in the studied 4 places were all lower than 0.5. The comprehensive quality index of the seven elements was 0.317 8 in Shouguang,0.320 4 in Laiyang,0.232 6 in Jinxiang,and 0.260 7 in Zhangqiu. The environmental quality of irrigation water in the studied four places were all set at the first class. [Conclusion] The environmental quality of irrigation water in the 4 places belonged to clean level and were fit for the plantation of no pollution vegetables.

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.

A Comparative Analysis of Environmental Quality Assessment Methods for Heavy Metal-Contaminated Soils

Four assessment methods （two pollution indexes and two fuzzy mathematical models） were employed to investigate the environmental quality of four soils around a ferroalloy plant in Nanjing City. Environmental quality was assessed as class Ⅳ （moderately polluted） for each soil with single-factor index method, and was identified to be classes Ⅳ, Ⅲ （slightly polluted）, Ⅲ, and Ⅲ for soils A, B, C, and D, respectively, with the comprehensive index model. In comparison with the single-factor index method, the comprehensive index model concerned both dominant parameter and average contribution of all factors to the integrated environmental quality. Using the two fuzzy mathematical methods （single-factor deciding and weighted average models）, the environmental risks were determined to be classes Ⅳ, Ⅲ, Ⅱ （clean）, and Ⅱ for soils A, B, C, and D, respectively. However, divergence of the membership degree to each pollution class still occurred between the two methods. In fuzzy mathematical methods, membership functions were used to describe the limits between different pollution degrees, and different weights were allocated for the factors according to pollution contribution. Introduction of membership degree and weight of each factor to fuzzy mathematical models made the methods more reasonable in the field of environmental risk assessment.

Using benthic macrofauna to assess environmental quality of four intertidal mudflats in Hong Kong and Shenzhen Coast

Intertidal zone is a significant wetland between land and ocean. It plays an important rolein maintaining local ecological balance. Both Mai Po and Futian intertidal mudflats are located in Shenzhen Bay and are important 'refueling' point along the East Asian/Australian flyway of migratory birds. The environmental quality of Mai Po and Futian mudflats have aroused great concern due to rapid economic developments in Hong Kong and Shenzhen in recent decades. Macroinfauna of Mai Po and Futian mudflats was investigated in December 2000 and the faunal data were used to assess their environmental quality. Two other mudflats, namely Ma Wan Typhoon Shelter (a more disturbed area) and Luk Keng intertidal mudflat (a place with relatively less human disturbance), were also sampled for macroinfauna and used as reference mudflats. Shannon - Weaver species diversity index (Isd), biotic coefficient (Cb) and macrofaunal pollution index (Imp) of the macrofauna community on four intertidal mudflats were used to determine their environmental quality. The results showed that Luk Keng intertidal mudflat was unpolluted, Mai Po and Futian mudflats were slightly polluted, and Ma Wan was moderately polluted. The pollution in Ma Wan Typhoon Shelter mainly came from various types of rubbish and fishing boats that disturbed the sediment, while pollution sources in Mai Po and Futian mudflats were discharges of industrial water, municipal sewage and from nearby rivers.

Development and Application of Water Quality Index (WQI) for the Evaluation of the Physico-Chemical Quality of Groundwater in Gold Mining Areas of Southeastern Senegal

Water is the most essential requirement for life. It provides a variety of purposes such as a source of water supply for drinking, domestic and industrial use, irrigated agriculture, livestock, and mining activities. Evaluating the status of water quality from traditional approaches does not guarantee the whole overview of the water quality situation. Therefore, developing a tool that can convert multiple parameters data into information that is understandable by both technical and non-technical personnel is vital. In this context, the purpose of this paper was to develop, calculate, and apply a water quality index for assessing the suitability (for drinking purposes) of groundwater in the gold mining areas in south-eastern Senegal. The development of this index based on WHO water quality guidelines followed the five standards steps i.e., parameters selection, sub-index formation, parameters weighting and sub-index aggregation and evaluation. Finally, the WQI summarized twelve key water quality parameters into 05 simple terms (excellent, good, medium, poor, and very poor) which is more relevant for reporting to managers and the public in a consistent manner. Thus, it was observed in the study area, that the water quality indexes in artisanal and industrial mining areas are either poor or very poor while in the reference stations (where there are no mining activities) WQI are either good or excellent. This situation was attributed to the effects of mining activities in such zones which contribute to the pollution of groundwater with heavy metals, nitrates, and suspended solids.

Air Pollution Exposure Based on Nighttime Light Remote Sensing and Multi-source Geographic Data in Beijing

Air pollution is a problem that directly affects human health,the global environment and the climate.The air quality index(AQI)indicates the degree of air pollution and effect on human health;however,when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored.In the present study,multi-source data were combined to map the distribution of the AQI and population data,and the analyze their pollution population exposure of Beijing in 2018 was analyzed.Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018.Using Luojia-1 nighttime light remote sensing data,population statistics data,the population of Beijing in 2018 and point of interest data,the distribution of the permanent population in Beijing was estimated with a high precision of 200 m×200 m.Based on the spatialization results of the AQI and population of Beijing,the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level(PWEL)formula.The results show that the southern region of Beijing had a more serious level of air pollution,while the northern region was less polluted.At the same time,the population was found to agglomerate mainly in the central city and the peripheric areas thereof.In the present study,the exposure of different districts and towns in Beijing to pollution was analyzed,based on high resolution population spatialization data,it could take the pollution exposure issue down to each individual town.And we found that towns with higher exposure such as Yongshun Town,Shahe Town and Liyuan Town were all found to have a population of over 200000 which was much higher than the median population of townships of51741 in Beijing.Additionally,the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same,with the peak value being in winter and the lowest value being in summer.The exposure intensity in population clusters was relatively high.To reduce the level and intensity of pollution exposure,relevant departments should strengthen the governance of areas with high AQI,and pay particular attention to population clusters.

Assessment of a Precaution Index for Environmental Evaluation: An Example of Application to the Cow’s Milk Production

The paper presents a Precaution Index (P) developed to create an instrument to assess the potential risk related to the presence of pollution sources next to milk production farms. The methodology starts from the inventory and geo-referencing of all pollution sources in an area, with the help of the multi-criteria decision analysis. Results are represented in a map of P, which highlights which areas are most at risk and need monitoring, and which pollutants may be involved. This may help in the early identification of emerging hazards to food safety. P was calculated for the milk production in an Italian region. Results show that 97% of the area is in a condition of minimum precaution that would be needed in controlling the safety of dairy products.