Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads

The design of a water quality monitoring network (WQMN) is a complicated decision-making process because each sampling involves high installation, operational, and maintenance costs. Therefore, data with the highest information content should be collected. The effect of seasonal variation in point and diffuse pollution loadings on river water quality may have a significant impact on the optimal selection of sampling locations, but this possible effect has never been addressed in the evaluation and design of monitoring networks. The present study proposes a systematic approach for siting an optimal number and location of river water quality sampling stations based on seasonal or monsoonal variations in both point and diffuse pollution loadings. The proposed approach conceptualizes water quality monitoring as a two-stage process; the first stage of which is to consider all potential water quality sampling sites, selected based on the existing guidelines or frameworks, and the locations of both point and diffuse pollution sources. The monitoring at all sampling sites thus identified should be continued for an adequate period of time to account for the effect of the monsoon season. In the second stage, the monitoring network is then designed separately for monsoon and non-monsoon periods by optimizing the number and locations of sampling sites, using a modified Sanders approach. The impacts of human interventions on the design of the sampling net are quantified geospatially by estimating diffuse pollution loads and verified with land use map. To demonstrate the proposed methodology, the Kali River basin in the western Uttar Pradesh state of India was selected as a study area. The final design suggests consequential pre- and post-monsoonal changes in the location and priority of water quality monitoring stations based on the seasonal variation of point and diffuse pollution loadings.     

Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

Mathematical Modeling and Numerical Algorithms for Simulation of Oil Pollution

This paper deals with the mathematical modeling and algorithms for the problem of oil pollution. For solving this task, we derive the adjoint problem for the advection–diffusion equation describing the propagation of oil slick after an accident, which we call the main problem. We prove a fundamental equality between the solutions of the main and the adjoint problems. Based on this equality, we propose a novel method for the identification of the pollution source location and the accident time of oil emission. This approach is illustrated on an example for an accident in the offshore of the central part of the Vietnamese coast. Numerical simulations demonstrate the effectiveness of the proposed method. Besides, the method is verified for 1D model of substance propagation.     

Site location optimization of regional air quality monitoring network in China: methodology and case study

Regional air quality monitoring networks (RAQMN) are urgently needed in China due to increasing regional air pollution in city clusters, arising from rapid economic development in recent decades. This paper proposes a methodological framework for site location optimization in designing a RAQMN adapting to air quality management practice in China. The framework utilizes synthetic assessment concentrations developed from simulated data from a regional air quality model in order to simplify the optimal process and to reduce costs. On the basis of analyzing various constraints such as cost and budget, terrain conditions, administrative district, population density and spatial coverage, the framework takes the maximum approximate degree as an optimization objective to achieve site location optimization of a RAQMN. An expert judgment approach was incorporated into the framework to help adjust initial optimization results in order to make the network more practical and representative. A case study was used to demonstrate the application of the framework, indicating that it is feasible to conduct site optimization for a RAQMN design in China. The effects of different combinations of primary and secondary pollutants on site location optimization were investigated. It is suggested that the network design considering both primary and secondary pollutants could better represent regional pollution characteristics and more extensively reflect temporal and spatial variations of regional air quality. The work shown in this study can be used as a reference to guide site location optimization of a RAQMN design in China or other regions of the world.     

The significance of structural power in Strategic Environmental Assessment

This article presents a study of how power dynamics enables and constrains the influence of actors upon decision-making and Strategic Environmental Assessment (SEA). Based on structuration theory, a model for studying power dynamics in strategic decision-making processes is developed. The model is used to map and analyse key decision arenas in the decision process of aluminium production in Greenland. The analysis shows that communication lines are an important resource through which actors exercise power and influence decision-making on the location of the aluminium production. The SEA process involved not only reproduction of formal communication and decision competence but also production of alternative informal communication structures in which the SEA had capability to influence.It is concluded, that actors influence strategic decision making, and attention needs to be on not only the formal interactions between SEA process and strategic decision-making process but also on informal interaction and communication between actors as the informal structures, which can be crucial to the outcome of the decision-making process. This article is meant as a supplement to the understanding of power dynamics influence in IA processes and as a contribution to the IA research field with a method to analyse power dynamics in strategic decision-making processes. The article also brings reflections of strengths and weaknesses of using the structuration theory as an approach to power analysis.     

Spatial contaminant heterogeneity: quantification with scale of measurement at contrasting sites

Material within the terrestrial environment is rarely homogeneously distributed, either spatially or temporally. One consequence of heterogeneity is that uncertainty is usually generated in measurements that are taken with the aim of characterising the environment. For example, a measurement of analyte concentration within soil taken from one sampling location on contaminated land can vary substantially when compared against another sample taken at effectively the same nominal location. The measurement uncertainty arising from the heterogeneity can substantially limit the reliability of the interpretations made upon environmental investigations. The sampling uncertainty usually outweighs the analytical uncertainty from the laboratory, often by a factor of 20 or more. One approach to reducing the uncertainty is to design a more suitable sampling strategy. This might be achieved by predicting the degree of heterogeneity prior to the investigation, but this is often difficult to achieve accurately. Another approach, which was investigated here, is to actually characterise the heterogeneity prior to the main investigation using rapid and inexpensive technology, such as in situ measurement techniques. In situ portable X-ray fluorescence (PXRF) and X-ray microprobe (XMP) techniques were employed to test the feasibility of this approach. Two contrasting contaminated land sites were chosen to characterise the two-dimensional spatial heterogeneity of heavy metal contamination in topsoil at a range of scales (50 m to 0.001 m). The spatial heterogeneity of contaminants, expressed as relative standard deviations, was found to differ between the two sites by a factor of two, largely due to the mode of deposition of pollution. The study also indicated that the heterogeneity did not change systematically with the scale of measurement between sampling locations at either site.     

Source Release-Rate Estimation of Atmospheric Pollution from a Non-Steady Point Source at a Known Location

The goal is to build up an inverse model capable of finding the release history of atmospheric pollution by using measured gas concentration data at just one location on the ground and identify the factors which affects the accuracy of the model predictions. The problem involves a non-steady point source of pollution at a known location in the atmosphere. This problem of finding the release rate is an ill-posed inverse problem and its solution is extremely sensitive to errors in the measurement data. Special regularisation methods, which stabilise the process of the solution, must be used to solve the problem. The method described in this paper is based on linear least-squares regression and Tikhonov regularisation, coupled with the solution of an advection-diffusion equation for a non-steady point source. The accuracy of the method is examined by imposing normally-distributed relative noise into the concentration data generated by the forward model as well as some real experimental data.     

Economic perspective-based analysis on urban infrastructures carrying capacity — A China study

Urban Infrastructure Economic Capacity (UIEC) is one of the most important capacities of urban infrastructure carrying capacity, which is an essential determinant of sustainable urban development. However, it appears that UIEC is not properly investigated during the urban development process, for which establishing an appropriate method is imperative to examine whether the urban infrastructure has achieved ideal economic capacity. This paper introduces an instrumental approach named UIEC model to investigate urban infrastructure economic capacity. The UIEC model adopts Coupling-Coordination Degree Model, Mean-Variance Analysis Method, Support-Pressure Model, and Super-efficiency Slack-based-measure Window model jointly. By employing the UIEC model, the economic capacity of urban infrastructure carrying capacity is appreciated by investigating the economic carrying efficiency of urban infrastructures. A China study is conducted during 2008–2017 for demonstrating the application of the introduced UIEC model. The research findings suggest that: 1) Economic location and self-governance authority have significant impact on UIEC; 2) the overall economic carrying efficiency of urban infrastructure in surveyed cities is decreasing; 3) there lies in an exponential relationship between economic carrying efficiency of urban infrastructure and GDP value in surveyed cities. High utilization efficiency of urban infrastructures is an essential prerequisite for carrying large volume of urban economic development.     

Optimization of pressure gauge locations for water distribution systems using entropy theory

It is essential to select the optimal pressure gauge location for effective management and maintenance of water distribution systems. This study proposes an objective and quantified standard for selecting the optimal pressure gauge location by defining the pressure change at other nodes as a result of demand change at a specific node using entropy theory. Two cases are considered in terms of demand change: that in which demand at all nodes shows peak load by using a peak factor and that comprising the demand change of the normal distribution whose average is the base demand. The actual pressure change pattern is determined by using the emitter function of EPANET to reflect the pressure that changes practically at each node. The optimal pressure gauge location is determined by prioritizing the node that processes the largest amount of information it gives to (giving entropy) and receives from (receiving entropy) the whole system according to the entropy standard. The suggested model is applied to one virtual and one real pipe network, and the optimal pressure gauge location combination is calculated by implementing the sensitivity analysis based on the study results. These analysis results support the following two conclusions. Firstly, the installation priority of the pressure gauge in water distribution networks can be determined with a more objective standard through the entropy theory. Secondly, the model can be used as an efficient decision-making guide for gauge installation in water distribution systems.     

A quantitative methodology for indexing environmental sensitivity and pollution potential

A methodology for rating the suitability of sites forthe location of industrial facilities is formulated and appliedto the case of a coal-fired power plant location. The methodologycomprises two major interlinked components: the environmentalplant location indexing component, which involves theidentification, scaling and weighting of environmentalsensitivity factors; and the impact analysis component, whichinvolves the superimposition of the pollution generation impactsof an industrial facility on spatially gridded zones of variousenvironmental sensitivities. For each rectangular areal unitdefined by a square grid, the Unit Pollution Potential Index isdetermined by the severity and distribution of key environmentalsensitivity factors and the coverage of superimposed pollutanteffects as determined by contaminant fate and transport models.For any alternative site of a planned facility, the summation ofthe unit indices over the area of influence of the facilityprovides the quantitative Pollution Index, which can be used as abasis for comparison of alternative sites for planned facilities.For this paper, this methodology is applied to the hypotheticalcase of the siting of a coal-fired power plant in thenortheastern region of the United States, in which threealternative sites are considered. The three sites: A, B and Cyielded indices of 47.83, 47.91 and 47.6, respectively, indicatingthat site C is the most suitable for siting the power plant.     

Locating pollutant emission sources with optical remote sensing measurements and an improved one-dimensional radial plume mapping technique

Previous studies have shown that there was a relatively large amount of uncertainty along the major wind direction in the results of locating emission sources using the one-dimensional radial plume mapping (RPM(1D)) technique based on optical remote sensing measurements. This paper proposes setting up an additional monitoring line that is perpendicular to the original scanning beam geometry to reduce this uncertainty. We first conducted a computer simulation study using the Gaussian dispersion model to generate the downwind concentrations of plumes from 400 source locations in a 201 m × 201 m spatial domain under various wind directions (n = 181). The optical remote sensing instrument was assumed to be at (0, 0) with two perpendicular monitoring lines, each of which had three beam segments of equal length. Each pair of the reconstructed downwind concentration profiles was then used to trace back to the source locations. The results showed that the accuracy of the method and its uncertainty were improved by using the proposed two-line RPM(1D) approach rather than the original one-line RPM(1D) approach at most simulated source locations. In a follow-up field experiment, a tracer gas was released at the coordinate of (100, 100). The release location was covered within the 0.25- to 0.5-probability area of the estimated results, and the distance between the actual and estimated source locations was 18.4 m (9.2% of the longest beam path).     

A multi-scale metrics approach to forest fragmentation for Strategic Environmental Impact Assessment

Forests are becoming severely fragmented as a result of land development. South Korea has responded to changing community concerns about environmental issues. The nation has developed and is extending a broad range of tools for use in environmental management. Although legally mandated environmental compliance requirements in South Korea have been implemented to predict and evaluate the impacts of land-development projects, these legal instruments are often insufficient to assess the subsequent impact of development on the surrounding forests. It is especially difficult to examine impacts on multiple (e.g., regional and local) scales in detail. Forest configuration and size, including forest fragmentation by land development, are considered on a regional scale. Moreover, forest structure and composition, including biodiversity, are considered on a local scale in the Environmental Impact Assessment process. Recently, the government amended the Environmental Impact Assessment Act, including the SEA, EIA, and small-scale EIA, to require an integrated approach. Therefore, the purpose of this study was to establish an impact assessment system that minimizes the impacts of land development using an approach that is integrated across multiple scales.This study focused on forest fragmentation due to residential development and road construction sites in selected Congestion Restraint Zones (CRZs) in the Greater Seoul Area of South Korea. Based on a review of multiple-scale impacts, this paper integrates models that assess the impacts of land development on forest ecosystems. The applicability of the integrated model for assessing impacts on forest ecosystems through the SEIA process is considered.On a regional scale, it is possible to evaluate the location and size of a land-development project by considering aspects of forest fragmentation, such as the stability of the forest structure and the degree of fragmentation. On a local scale, land-development projects should consider the distances at which impacts occur in the vicinity of the forest ecosystem, and these considerations should include the impacts on forest vegetation and bird species. Impacts can be mitigated by considering the distances at which these influences occur. In particular, this paper presents an integrated environmental impact assessment system to be applied in the SEIA process. The integrated assessment system permits the assessment of the cumulative impacts of land development on multiple scales.     

Open-source methods for estimating health risks of fine particulate matter from coal-fired power plants: A demonstration from Karachi,Pakistan

Environmental impact assessments (EIAs) effectiveness and accessibility by the public is determined by local environmental enforcement and regulation. Massive energy infrastructure projects like China's Belt and Road initiative (BRI) could accentuate social and economic costs, as regulation is deferred to host countries with varying levels of domestic enforcement. To fill major gaps in the public evaluation of EIA practices and results, our objective here is to present an open-source approach for evaluating localized air pollution health impacts for BRI-financed coal-fired power plants. This analysis focuses on one specific problem, additional attributable mortality from stroke, ischemic heart disease, and chronic obstructive pulmonary disease for adults ages 25–84 from fine particulate matter (PM_2.5), known to be major risk factor for premature deaths globally. As a concrete example, we examine the case of the Port Qasim power plant located near Karachi, Sindh Province, Pakistan. We present results for two main scenarios: a base case, assuming fully operational pollution control technologies, in particular electrostatic precipitators (ESP); and an alternative case without ESPs. All material and methods for replicating this analysis for the case study and for other projects are available in our institutional open repository. Our approach can be applied immediately to virtually any source location in the world, due to the public and global availability of input data.SynopsisWe present an open-source approach for evaluating localized health impacts due to fine particulate matter emitted from coal-fired power plants.     

Geospatial strategy for sustainable management of municipal solid waste for growing urban environment

This paper presents the implementation of a Geospatial approach for improving the Municipal Solid Waste (MSW) disposal suitability site assessment in growing urban environment. The increasing trend of population growth and the absolute amounts of waste disposed of worldwide have increased substantially reflecting changes in consumption patterns, consequently worldwide. MSW is now a bigger problem than ever. Despite an increase in alternative techniques for disposing of waste, land-filling remains the primary means. In this context, the pressures and requirements placed on decision makers dealing with land-filling by government and society have increased, as they now have to make decisions taking into considerations environmental safety and economic practicality. The waste disposed by the municipal corporation in the Bhagalpur City (India) is thought to be different from the landfill waste where clearly scientific criterion for locating suitable disposal sites does not seem to exist. The location of disposal sites of Bhagalpur City represents the unconsciousness about the environmental and public health hazards arising from disposing of waste in improper location. Concerning about urban environment and health aspects of people, a good method of waste management and appropriate technologies needed for urban area of Bhagalpur city to improve this trend using Multi Criteria Geographical Information System and Remote Sensing for selection of suitable disposal sites. The purpose of GIS was to perform process to part restricted to highly suitable land followed by using chosen criteria. GIS modeling with overlay operation has been used to find the suitability site for MSW.     

A data-based model to locate mass movements triggered by seismic events in Sichuan, China

Earthquakes affect the entire world and have catastrophic consequences. On May 12, 2008, an earthquake of magnitude 7.9 on the Richter scale occurred in the Wenchuan area of Sichuan province in China. This event, together with subsequent aftershocks, caused many avalanches, landslides, debris flows, collapses, and quake lakes and induced numerous unstable slopes. This work proposes a methodology that uses a data mining approach and geographic information systems to predict these mass movements based on their association with the main and aftershock epicenters, geologic faults, riverbeds, and topography. A dataset comprising 3,883 mass movements is analyzed, and some models to predict the location of these mass movements are developed. These predictive models could be used by the Chinese authorities as an important tool for identifying risk areas and rescuing survivors during similar events in the future.     

Investigation of Building - Influenced Atmospheric Dispersion Using a Dual Source Technique

Dispersion of atmospheric contaminants in the vicinity of an isolated cubical model building was investigated in the field. A dual source/receptor technique was used in the experiments, which was proved to be very useful for the investigation of pollution dispersion. This experimental technique involved the simultaneous release of two different tracer gases from two different point sources, and the deployment of a FID (Flame Ionization Detector) co-located with a UVIC®(Ultra-Violet Ion Collector) detector. Both mean concentrations and concentration fluctuation statistics were examined. In this paper concentration fluctuation statistics are presented. The effect of the upwind source location on intermittency values and on the cumulative density function (cdf) is examined. The exact location of a source placed upwind of an obstacle has a very significant and complex effect on both mean concentrations and concentration fluctuations. As the lateral or vertical displacement between the two sources is increased, cross-correlation values between data taken simultaneously by two co-located detectors decrease rapidly.     

Optimal Expansion of Water Quality Monitoring Network by Fuzzy Optimization Approach

River reaches are frequently classified with respect to various mode of water utilization depending on the quantity and quality of water resources available at different location. Monitoring of water quality in a river system must collect both temporal and spatial information for comparison with respect to the preferred situation of a water body based on different scenarios. Designing a technically sound monitoring network, however, needs to identify a suite of significant planning objectives and consider a series of inherent limitations simultaneously. It would rely on applying an advanced systems analysis technique via an integrated simulation-optimization approach to meet the ultimate goal. This article presents an optimal expansion strategy of water quality monitoring stations for fulfilling a long-term monitoring mission under an uncertain environment. The planning objectives considered in this analysis are to increase the protection degree in the proximity of the river system with higher population density, to enhance the detection capability for lower compliance areas, to promote the detection sensitivity by better deployment and installation of monitoring stations, to reflect the levels of utilization potential of water body at different locations, and to monitor the essential water quality in the upper stream areas of all water intakes. The constraint set contains the limitations of budget, equity implication, and the detection sensitivity in the water environment. A fuzzy multi-objective evaluation framework that reflects the uncertainty embedded in decision making is designed for postulating and analyzing the underlying principles of optimal expansion strategy of monitoring network. The case study being organized in South Taiwan demonstrates a set of more robust and flexible expansion alternatives in terms of spatial priority. Such an approach uniquely indicates the preference order of each candidate site to be expanded step-wise whenever the budget limitation is sensitive in the government agencies.