Research on deep integration of application of artificial intelligence in environmental monitoring system and real economy

Environmental monitoring, modeling, and managing allow a better understanding of major processing and techniques for managing environmental changes. The pollution level has risen over time due to many factors such as a rise in population and the use of the vehicle, industrialization, and urbanization that have a direct impact on people ‘s health. Hence, in this paper, Artificial intelligence assisted Semantic Internet of Things (AI-SIoT) has been proposed using a wireless sensor network (WSN) for the environmental monitoring system and the real economy. The Artificial Intelligence technique can very effectively analyze data and make precise decisions on the provision of services in different types. This study provides a mathematical framework for the analysis of interdependent aspects of the WSN protocol for communication and design of signal processing. The Internet of Things (IoT) based framework comprises the complete information system from the sensor level to data management about the environment. The experimental results show that the proposed method provides an effective way to analyze the long-term monitoring of environmental data. The proposed AI-SIoT method using the WSN method enhances accuracy(95.6%), performance(98.7%) increase efficiency (93.7%) with reliability (97.4%) when compared to other existing methods.     

Urban water resource management for sustainable environment planning using artificial intelligence techniques

In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.     

Environmental planning based on reduce,reuse, recycle and recover using artificial intelligence

Waste disposal was a significant challenge faced by the community and government. Customers buy and use goods that produce a considerable amount of waste. Waste management is a major problem since the number of consumers increased due to high waste generation. This has resulted in a huge amount of waste, which calls for enormous waste-management policies. Reduce; Reuse, Recycle, and Recover are the tools to reduce the adverse implications of retailing and manufacturing on the environment. In this paper, Artificial Intelligence based Hybridized Intelligent Framework (AIHIF) has been proposed for automated recycling to optimizing the waste management process. The system will optimize waste collection with a short distance by utilizing machine learning and graph theory. AI design technology, which helps different approaches adapted to interest groups, collecting their specific information and greatly improving environmental planning and urban management performance, accuracy, and efficiency. The experimental results show that the proposed method enhances performance and accuracy when compared to other existing methods.     

Short-range transport of contaminants released from e-waste recycling site in South China

The transport behaviors of a suite of contaminants released from electronic waste (e-waste) recycling operations, including polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), and heavy metals, were evaluated by analyzing the contaminant residues in surface soils sampled in the surrounding area of an e-waste recycling site in South China. Concentrations of PBDEs and PCBs in the soil samples ranged from 0.565 to 2908 ng g(-1) dw and from 0.267 to 1891 ng g(-1) dw, respectively, while soil residues were 0.082-2.56, 3.22-287, and 16.3-162 μg g(-1) dw for Cd, Cu, and Pb, respectively. Concentrations of PBDEs and PCBs in soil decreased with increasing distance from the source of pollution, indicating possible PBDE and PCB contamination in the surrounding areas due to the short-range transport of these compounds from the e-waste recycling site. Although no significant difference in the short-range transport potential among PBDE and PCB congeners was observed, reductions in concentrations of the highly-brominated-BDEs and highly-chlorinated-CBs were slightly quicker than those of their less-halogen-substituted counterparts. Conversely, heavy metals showed the lowest transport potential due to their low vapor pressure, and results showed metals would remain near the pollution source instead of diffusing into the surrounding areas. Finally, mass inventories in areas near the e-waste site were 0.920, 0.134, 0.860, 4.68, 757, and 673 tons for BDE209, PBDEs (excluding BDE209), PCBs, Cd, Cu, and Pb, respectively.     

Integrated studies for automobile wastes management in developing countries; in the concept of environmentally friendly mechanic village

More cities in developing countries now consider mechanic village (MV) as superior to the city wide auto-workshop practice following the increasing influx of used or waste automobile from industrialized nations. This is because of the numerous advantages of the mechanic village concept as a capacity building, and in poverty alleviation. Nevertheless, mechanic villages are poorly developed with no waste management plan. They are now identified with severe to excessive heavy metal soil pollution, causing ecological and public health hazards. This paper has a wider explanation of what it takes for a mechanic village to be environmentally friendly based on spectroscopic analysis and physical measurements conducted in three MVs. Heavy metal concentrations (mg kg(?-1)) above background levels in the upper 100 cm soil profiles of the Okigwe, the Orji, and the Nekede MVs in the Imo River basin collectively range 748-70,606 for Fe; 99-1,090 for Pb; 186-600 for Mn; 102-1,001 for Cu; 8-23 for Cd; 4-27 for Cr; and 3-10 for Ni. The most abundant metals of environmental concerns are Pb, Mn, and Cu, in the order of Pb > Mn > Cu. Three-phase storm water treatment, emission testing, minimum safe farming distance (350 m), extended producer responsibility for disposal or recycling of used motor oil, phyto-remediation using local plants, groundwater monitoring wells, and continuous education of mechanics are recommended. Exporters of waste automobiles to developing countries and the United Nations may assist developing countries in establishing environmentally friendly MVs.     

Assessment of cadmium exposure for neonates in Guiyu, an electronic waste pollution site of China

This study aimed to determine the levels of placental cadmium (PCd) and cord blood cadmium (CBCd) and the resulting expression of placental metallothionein (MT) in neonates and to investigate cadmium (Cd) exposure levels in neonates and mothers who live in Guiyu, China, an electronic waste (e-waste) pollution site. Among the 423 mothers included in the study from 2004/2005 to 2007, 289 lived in Guiyu (exposed group) and 134 lived in Chaonan, located 10 km away from Guiyu (controls) and had never been exposed to e-waste pollution. CBCd and PCd levels were measured by atomic absorption spectrometry. Placental MT was examined by immunohistochemistry. Information on maternal and neonatal characteristics and exposure conditions was obtained from hospital records and by personal interviews. For the 3 years, the median CBCd was higher for Guiyu neonates than for controls (3.61 vs. 1.25 ??g/L), with 25.61% of Guiyu subjects exhibiting a median CBCd that exceeded the safety limit defined by the World Health Organization (5 ??g/L), as compared with 14.18% of control neonates (p < 0.01). In Guiyu, the mean PCd was higher than that for controls (0.17 ± 0.48 vs. 0.10 ± 0.11 ??g/g, p ?? 0.01). The high levels of CBCd and PCd were significantly associated with parents?? occupational and environmental exposure to e-waste recycling pollutants. Staining for MT was positive and dense for 67.00% (67/100) of Guiyu neonates as compared with 32.69% (17/52) of controls (p < 0.01). Exposure to e-waste recycling pollutants increased Cd exposure in neonates, which was accompanied by increased placental MT expression.     

国内外优先评估化学品筛选方法与清单概述

优先评估化学品名录对推进有毒有害化学品的管控、保护环境和人类健康具有重要意义。综述了国内外优先评估化学品筛选方法的发展、原则和步骤,总结了筛选评估流程中重点关注的多种危害特性,比较了各国优先评估化学品名录及其在各国/组织的禁止/限制情况,并分析其在我国的生产状况。结果表明,各国家/组织共筛选出1 146种优先评估化学品,有239种在至少2个国家/组织中被列为优先评估化学物质,有208种在我国生产使用,但其中164种尚未列入我国优控化学品名录,可作为下一步风险评估的对象。邻苯二甲酸二（2-乙基己基）酯（DEHP）被所有国家/组织列为优先关注化学品,接下来应严格管控塑料制品中的DEHP,或寻找合适的替代物。研究可为我国优先评估化学品的筛选与环境管理提供参考。     

Development of an Expert System for the Remediation of Petroleum-Contaminated Sites

Groundwater and soil contamination caused by light nonaqueous phase liquids (LNAPLs) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies, generally classified as ex situ and in situ remediation techniques, have been developed and implemented to clean up the contaminated sites in the last two decades. One of the problems associated with ex situ remediation is the cost of operation. In recent years, in situ techniques have acquired popularity. However, the selection process of the desired techniques needs a large amount of knowledge. Insufficient expertise in the process may result in unnecessary inflation of expenses. In this study, petroleum waste management experts and Artificial Intelligence (AI) researchers worked together to develop an expert system (ES) for the management of petroleum contaminated sites. Various AI techniques were used to construct a useful tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation in the project. The expert system was applied to a real-world case study and the results show that the expert system can generate desired remediation alternatives to assist decision-makers. The application case study constitutes partial validation of the prototype expert system.     

Profiles,sources, and transport of polycyclic aromatic hydrocarbons in soils affected by electronic waste recycling in Longtang,south China

We studied the profiles, possible sources, and transport of polycyclic aromatic hydrocarbons (PAHs) in soils from the Longtang area, which is an electronic waste (e-waste) recycling center in south China. The sum of 16 PAH concentrations ranged from 25 to 4,300 ng/g (dry weight basis) in the following order: pond sediment sites (77 ng/g), vegetable fields (129 ng/g), paddy fields (180 ng/g), wastelands (258 ng/g), dismantling sites (678 ng/g), and former open burning sites (2,340 ng/g). Naphthalene, phenanthrene, fluoranthene, pyrene, chrysene, and benzo[b]fluoranthene were the dominant PAHs and accounted for approximately 75 % of the total PAHs. The similar composition characteristics of PAHs and the significant correlations among individual, low molecular weight, high molecular weight, and total PAHs were found in all six sampling site types, thus indicating that PAHs originated from similar sources. The results of both isomeric ratios and principal component analyses confirmed that PAHs were mainly derived from the incomplete combustion of e-waste. The former open burning sites and dismantling sites were the main sources of PAHs. Soil samples that were taken closer to the point sources had high PAH concentrations. PAHs are transported via different soil profiles, including those in agricultural fields, and have been detected not only in 0- to 40-cm-deep soil but also in 40 cm to 80 cm-deep soil. PAH concentrations in soils in Longtang have been strongly affected by primitive e-waste recycling, particularly by former open burning activities.     

The European eel quality database: towards a pan-European monitoring of eel quality

The stocks of the European eel Anguilla anguilla are in decline and there is an increasing awareness that poor health status due to contaminants and/or diseases might be a key element in this decline and might be a hindrance to recovery. Many countries have started compiling data on the health status of eels in their water bodies. Objectives for these monitoring actions are diverse and there is a large amount of information collected by EU member countries. However, this information is widely scattered over Europe in agencies, institutes or universities. As there is a growing need to collect and report on data on the health status of the eel on international level, the Joint EIFAC/ICES Working Group on Eels initiated in September 2007 the set up of an European Eel Quality Database to collect recent data of contaminants and diseases over the distribution area of the eel. This paper describes the aim, the set up and future development of the database in order to give it greater publicity and to call on scientists or managers to submit data on eel health status. The database represents now the first comprehensive pan-European compilation of eel health data, including data from over 10,000 eels from approximately 1,200 sites over 14 countries. Preliminary work has indicated a number of shortcomings and future developments will be needed. Guaranteeing further development of the database, harmonisation of methods, quality assurance, and setting up harmonised eel monitoring strategies over Europe will be a great challenge and will need pan-European cooperative work.     

Artificial Reefs of Southeast Asia - Do They Enhance or Degrade the Marine Environment?

Artificial reefs are seen as effective tools to enhance the marine environment and increase productivity, particularly fish biomass and abundance. Many Southeast Asian countries have implemented artificial reef programmes. When effectively managed, artificial reefs enhance habitats and biological productivity. Management includes proper planning on the use and configuration of materials, site selection, and regulatory control of fisheries harvest. Without planning and long-term management, artificial reefs fail and become nothing more than pollutants that contribute to the further degradation of the marine environment.     

Health,safety and environmental unit performance assessment model under uncertainty (case study: steel industry)

Performance assessment is a critical objective of management systems. As a result of the non-deterministic and qualitative nature of performance indicators, assessments are likely to be influenced by evaluators’ personal judgments. Furthermore, in developing countries, performance assessments by the Health, Safety and Environment (HSE) department are based solely on the number of accidents. A questionnaire is used to conduct the study in one of the largest steel production companies in Iran. With respect to health, safety, and environment, the results revealed that control of disease, fire hazards, and air pollution are of paramount importance, with coefficients of 0.057, 0.062, and 0.054, respectively. Furthermore, health and environment indicators were found to be the most common causes of poor performance. Finally, it was shown that HSE management systems can affect the majority of performance safety indicators in the short run, whereas health and environment indicators require longer periods of time. The objective of this study is to present an HSE-MS unit performance assessment model in steel industries. Moreover, we seek to answer the following question: what are the factors that affect HSE unit system in the steel industry? Also, for each factor, the extent of impact on the performance of the HSE management system in the organization is determined.     

Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed

Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.     

Contamination by perfluorinated compounds in water near waste recycling and disposal sites in Vietnam

There are very few reports on the contamination by perfluorinated chemicals (PFCs) in the environment of developing countries, especially regarding their emission from waste recycling and disposal sites. This is the first study on the occurrence of a wide range of PFCs (17 compounds) in ambient water in Vietnam, including samples collected from a municipal dumping site (MD), an e-waste recycling site (ER), a battery recycling site (BR) and a rural control site. The highest PFC concentration was found in a leachate sample from MD (360 ng/L). The PFC concentrations in ER and BR (mean, 57 and 16 ng/L, respectively) were also significantly higher than those detected in the rural control site (mean, 9.4 ng/L), suggesting that municipal solid waste and waste electrical and electronic equipment are potential contamination sources of PFCs in Vietnam. In general, the most abundant PFCs were perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluoroundecanoic acid (PFUDA; <1.4–100, <1.2–100, and <0.5–20 ng/L, respectively). Interestingly, there were specific PFC profiles: perfluoroheptanoic acid and perfluorohexanoic acid (88 and 77 ng/L, respectively) were almost as abundant as PFOA in MD leachate (100 ng/L), whereas PFNA was prevalent in ER and BR (mean, 17 and 6.2 ng/L, respectively) and PFUDA was the most abundant in municipal wastewater (mean, 5.6 ng/L), indicating differences in PFC contents in different waste materials.     

Intelligent comprehensive evaluation system using artificial intelligence for environmental evaluation

Environmental evaluation plays a significant role in the development of the culture and economy in modern times. When the environmental condition becomes degraded, the complete evaluation of ecological analysis is highly necessary to evaluate the environment. Hence, the development of a scientific assessment system of environmental assessment is highly significant in the development of the culture and economy. In this research, the present state of environmental evaluation is discussed, and the evaluation system is integrated through a computational process. Secondly, an environmental evaluation system is presented to establish the model in the evaluation process. Further, in this research, Advanced Artificial Intelligence Framework (AIF) for environmental development and protection has been proposed to improve the culture and economy in modern times. Studies reports indicate clear connections between the criteria of environmental assessment, the protection and development of the environment. The practical application of study findings involves establishing specific proposals for reducing pollution and improving the protection of the environment in China.     

Groundwater stress and vulnerability in rural coastal aquifers under competing demands: a case study from Sri Lanka

Rural coastal aquifers are undergoing rapid changes due to increasing population, high water demand with expanding agricultural and domestic uses, and seawater intrusion due to unmanaged water pumping. The combined impact of these activities is the deterioration of groundwater quality, public health concerns, and unsustainable water demands. The Kalpitiya peninsula located northwest of Sri Lanka is one area undergoing such changes. This land area is limited and surrounded almost completely by sea and lagoon. This study consists of groundwater sampling and analysis, and vulnerability assessment using the DRASTIC method. The results reveal that the peninsula is experiencing multiple threats due to population growth, seawater intrusion, land use exploitation for intensive agriculture, groundwater vulnerability from agricultural and domestic uses, and potential public health impacts. Results show that nitrate is a prevalent and serious contaminant occurring in large concentrations (up to 128 mg/l NO₃?CN), while salinity from seawater intrusion produces high chloride content (up to 471 mg/l), affecting freshwater sources. High nitrate levels may have already affected public health based on limited sampling for methemoglobin. The two main sources of nitrogen loadings in the area are fertilizer and human excreta. The major source of nitrogen results from the use of fertilizers and poor management of intense agricultural systems where a maximum application rate of up to 11.21 metric tons N/km² per season is typical. These findings suggest that management of coastal aquifers requires an integrated approach to address both the prevalence of agriculture as an economic livelihood, and increasing population growth.     

CVOR在山区河道整治植被恢复综合评价中的应用研究

以石葵河生态河道治理为例,将工程扰动区划分为河道工程区（Q1）、临时施工道路区（Q2）、弃渣场区（Q3）、取土区（Q4）、临时表土堆场区（Q5）等5个分区。采用层次分析法和CVOR模型,构建山区河道整治工程扰动区植被恢复综合评价模型。结果表明：Q1区植被恢复潜力最强,生态健康等级为健康,属容易恢复区,Q4区、Q5区、Q2区生态健康等级为不健康,植被恢复潜力较弱,生态修复中须加大投资;植被恢复潜力与生态系统健康评价结果基本保持一致,基况条件对植被恢复潜力影响较大,可通过人工干扰提高扰动区植被恢复潜力,提升植被恢复效果。     

Long-term ecosystem monitoring and assessment of the Detroit River and Western Lake Erie

Over 35 years of US and Canadian pollution prevention and control efforts have led to substantial improvements in environmental quality of the Detroit River and western Lake Erie. However, the available information also shows that much remains to be done. Improvements in environmental quality have resulted in significant ecological recovery, including increasing populations of bald eagles (Haliaeetus leucocephalus), peregrine falcons (Falco columbarius), lake sturgeon (Acipenser fulvescens), lake whitefish (Coregonus clupeaformis), walleye (Sander vitreus), and burrowing mayflies (Hexagenia spp.). Although this recovery is remarkable, many challenges remain, including population growth, transportation expansion, and land use changes; nonpoint source pollution; toxic substances contamination; habitat loss and degradation; introduction of exotic species; and greenhouse gases and global warming. Research/monitoring must be sustained for effective management. Priority research and monitoring needs include: demonstrating and quantifying cause-effect relationships; establishing quantitative endpoints and desired future states; determining cumulative impacts and how indicators relate; improving modeling and prediction; prioritizing geographic areas for protection and restoration; and fostering long-term monitoring for adaptive management. Key management agencies, universities, and environmental and conservation organizations should pool resources and undertake comprehensive and integrative assessments of the health of the Detroit River and western Lake Erie at least every 5 years to practice adaptive management for long-term sustainability.     

Environmental Specimen Bank in Ehime University (es-BANK), Japan for global monitoring

During the last 40 years, The Center for Marine Environmental Studies (CMES), Ehime University collected a variety of environmental and biological material comprising about 1000 species and 100,000 samples from many developing and developed countries and also open seas and oceans all over the world. They were categorically archived, catalogued and stocked in our Environment Specimen Bank (es-BANK) facility equipped with a -25 degrees C cold room. We have already exchanged specimens with many scientific institutions and are also eager to widen our collaboration with other specimen banks. In our survey using the air, water, wildlife and human samples, we found that the major emission sources for the industrial chemicals like polychlorinated biphenyls (PCBs) are in the developed nations while those of organochlorine (OC) pesticides like dichlorodiphenyltrichloroethane and its metabolites (DDTs), hexachlorocyclohexane isomers (HCHs), etc. are located in developing countries. However, significant emission of modern environmental contaminants such as polybrominated diphenyl ethers (PBDEs) also seems to occur predominantly in countries with high economic growth rates. Apart from the modern incinerators and other industrial installations in developed nations, the compounds, like dioxins and related compounds (DRCs), were also found to be released in significant levels from the municipal solid waste dumping sites of developing countries. By evaluating the distribution patterns of various persistent toxic substances (PTSs) in our studies, we could conclude that DRCs and DDTs are regional contaminants, while PCBs, PBDEs, HCHs and hexachlorobenzene (HCB) are global contaminants. We also found that the pollution by PBDEs has been increasing in the last two decades while that of the legacy OCs has been decreasing.     

Seasonal analysis of the generation and composition of solid waste: potential use—a case study

Ensenada health officials lack pertinent information on the sustainable management of solid waste, as do health officials from other developing countries. The aims of this research are: (a) to quantify and analyze the household solid wastes generated in the city of Ensenada, Mexico, and (b) to project biogas production and estimate generation of electrical energy. The characterization study was conducted by socioeconomic stratification in two seasonal periods, and the biogas and electrical energy projections were performed using the version 2.0 Mexico Biogas Model. Per capita solid waste generation was 0.779?±?0.019 kg per person per day within a 98 % confidence interval. Waste composition is composed mainly of food scraps at 36.25 %, followed by paper and cardboard at 21.85 %, plastic at 12.30 %, disposable diapers at 6.26 %, and textiles at 6.28 %. The maximum capacity for power generation is projected to be 1.90 MW in 2019. Waste generated could be used as an intermediate in different processes such as recycling (41.04 %) and energy recovery (46.63 %). The electrical energy that could be obtained using the biogas generated at the Ensenada sanitary landfill would provide roughly 60 % of the energy needed for street lighting.