Search

This study aims to explore the mechanism of Tianhe Zhuifeng Ointment in treating rheumatoid arthritis(RA) with syndrome of internal obstruction and cold-dampness and the compatibility characteristics based on thequot;disease-syndrome-formulaquot; association network. A gene set associated with the clinical symptoms of RA was collected from Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine v2.0(TCMIP v2.0). The different expression gene set of RA with syndrome of internal obstruction and cold-dampness was screened out by transcriptomic expression profile detection and bioinformatics data mining of the comparison of RA patients with syndrome of internal obstruction and cold-dampness and healthy volunteers. The chemical composition information of 35 Chinese medicines from Tianhe Zhuifeng Ointment was collected from TCMIP v2.0 and Traditional Chinese Medicine Bank(TCMBank). The candidate targets were predicted based on the similarity principle of compounds structure. The interactive network ofquot;related gene of RA with syndrome of internal obstruction and cold-dampness-candidate target of Tianhe Zhuifeng Ointmentquot; was constructed. The core network targets were screened out by topological characteristics of calculating network, and the functional exploration was carried out based on Kyoto Encyclopedia of Genes and Genomes(KEGG) and Reactome Pathway Database. The compatibility mechanisms of various efficacy groups of Tianhe Zhuifeng Ointment were further explored. The results showed that the candidate targets of Tianhe Zhuifeng Ointment were mainly involved into the modules ofquot;immune-inflammationquot; regulation, nervous system function, cell function, and substance and energy metabolism, etc. The mechanisms of various efficacy groups emphasized on different aspects. The group of dispelling wind and removing dampness-dredging channels and activating collaterals, the group of extinguishing wind and stopping convulsions, and the group of pungent analgesia regulatedquot;immune-inflammationquot; system by warming meridians and dissipating cold. The group of activating blood and resolving stasis and the group of strengthening sinews and bones regulatedquot;immune-inflammationquot; system by activating blood and dredging channels. The group of dispelling wind and removing dampness-dredging channels and activating collaterals, the group of extinguishing wind and stopping convulsions, the group of activating blood and resolving stasis, the group of strengthening sinews and bones, and the group of clearing heat and draining water affected the nervous system by invigorating Qi-blood and benefiting spirit. The group of dispelling wind and removing dampness-dredging channels and activating collaterals and the group of extinguishing wind and stopping convulsions regulated cell function and substance and energy metabolism by dispelling wind and eliminating cold-dampness. The group of activating blood and resolving stasis and the group of strengthening sinews and bones regulated the cell function and substance and energy metabolism by activating blood and strengthening sinews and bones. The results showed that Tianhe Zhuifeng Ointment exerted the comprehensive efficacy of dispelling wind, removing dampness, activating blood, removing stasis, warming meridians, dredging channels, and strengthening sinews and bones through adjusting the imbalance ofquot;immune-inflammationquot;, regulating nervous system, cell function, and interfering with substance and energy metabolism, thus improving the syndrome of internal obstruction and cold-dampness. The findings of this study laid foundations for clarifying the therapeutic characteristics and clinical orientation of Tianhe Zhuifeng Ointment.

Objective Knee osteoarthritis (KOA) is prevalent in middle-aged and elderly people. This condition negatively affects the quality of life of patients. Although non-steroidal anti-inflammatory drugs (NSAIDs) are often used to relieve symptoms associated with KOA, it is associated with many side effects. Acupuncture and moxibustion therapies have been applied in the treatment of KOA. However, the efficacy of various acupuncture and moxibustion treatments has not been compared. Methods Randomized controlled trials (RCTs) on the application of acupuncture and moxibustion in the treatment of KOA were searched in English databases and Chinese databases. Data were retrieved from establishment of the database to September 2020. Data analysis was performed using Stata14.0 and GeMTC 0.14.3 softwares. Results A total of 40 RCTs involving 3215 patients with KOA were retrieved. Network meta-analysis revealed that the fire needle was superior to western medicine, electro-acupuncture, conventional acupuncture, warm needle and sham acupuncture; warm needle was better than conventional acupuncture and western medicine whereas electro-acupuncture was better than conventional acupuncture in improving pain scores in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Moreover, we found that fire needle and warm needle more effectively improved WOMAC stiffness scores than western medicine and sham moxibustion, whereas electro-acupuncture was superior to western medicine and sham moxibustion in improving WOMAC stiffness scores. Further analysis revealed that fire needle, warm needle and electro-acupuncture were more effective in improving WOMAC joint function scores than conventional acupuncture and western medicine. The fire needle was superior to conventional acupuncture and sham acupuncture, whereas electro-acupuncture was better than western medicine, conventional acupuncture and sham acupuncture in improving visual analogue scale scores. Conclusion This study shows that fire needle is superior to warm needle and electro-acupuncture, whereas warm needle and electro-acupuncture are better than conventional acupuncture, western medicine, sham moxibustion and sham acupuncture.

Demand-side response (DSR), the incentivised time-shifting of energy use by consumers away from peak times, is regarded as a potentially effective measure to balance electricity supply and demand. This will be even more important in the low-carbon energy system of the future, with a high share of non-dispatchable power, such as variable renewable energy and nuclear power. Most DSR programmes require consumers’ active engagement in shifting end-use activities. Previous studies have, however, rarely revealed socio-demographic factors influential for consumers’ willingness-to-shift specific end-use activities. This study thus aims to fill this research gap and, using a multinomial logistic model to analyse a nationwide survey, identify factors influential for DSR-related decisions. The nationwide survey for 1004 respondents was carried out to collect data about consumers’ willingness-to-shift their daily activities. We focused on the activities that constitute the major part of domestic energy consumption, i.e. cooking, dish-washing, entertainment, heating, laundry and showering. According to the results, consumers’ original timing of the end-use activities, socio-demographic factors, ownership of specific appliances and level of concern for energy-saving are influential for their willingness-to-shift activities. These findings can not only help policymakers make more targeted DSR promotion plans but also help to improve broader modelling tools to better consider consumers’ willingness-to-shift their demand.

The present study explored the biological connotation of traditional Chinese medicine(TCM) syndromes of rheumatoid arthritis(RA) from thequot;disease-syndrome-symptomquot; association network. RA patients with four TCM syndromes(dampness-heat obstruction, phlegm-stasis obstruction, Qi-blood deficiency, and liver and kidney deficiency), three for each type, were assigned as the RA TCM syndrome group, and three healthy volunteers as the normal control group. The differential gene sets of four syndromes were screened out through transcriptome expression profiling and bioinformatics mining. The relevant gene sets of syndrome-related clinical symptoms were collected from TCMIP v2.0(http://www.tcmip.cn/). Thequot;disease-syndrome-symptomquot; association networks of four RA syndromes were established by using the intersection genes of syndrome-related differential genes and symptom-related genes, and the key network target genes of each syndrome were screened out and the corresponding biological functions were mined through topological feature calculation and enrichment analysis. The genes associated with clinical symptoms such as vasculitis, joint pain, and fever in the damp-heat obstruction syndrome ranked the top, and the key network target genes of this syndrome were most significantly enriched in the pathways related to material and energy metabolism and thermal reaction biological processes. The clinical symptom-related genes of the phlegm-stasis obstruction syndrome were most significantly enriched in the pathways related toquot;immunity-inflammationquot;, nervous system regulation, and sensory response. The clinical symptoms such as hypoglycemia, hypotension, weight loss, palpitation, and arrhythmia in Qi-blood deficiency syndrome were predominant, and its key network target genes were most significantly enriched in the pathways related to the nervous system andquot;immunity-inflammationquot; response. The abnormal symptoms in the liver and kidney in the liver and kidney deficiency syndrome were commonly seen, and its key network target genes were most significantly enriched in thequot;immunity-inflammationquot; regulatory pathways, and liver and kidney development and metabolic response. In conclusion, the differences and connections of the biological basis between different TCM syndromes of RA are in line with the theoretical interpretation of TCM on the etiology and pathogenesis of RA. This study summarized the objective essence of syndromes to a certain extent from thequot;disease-syndrome-symptomquot; association network and is expected to provide a theoretical basis for the discovery of serum biomarkers of RA syndromes.

To evaluate the curative effect of integrated Traditional Chinese and Western Medicine on gout, and to investigate the therapy timing and exact treatment options of integrated medicine.Totally 860 patients were enrolled, including 460 patients with intermittent gout, 200 patients with active Traditional Chinese Medicine (TCM) syndrome (TCM syndrome score ≥ 6) and 200 patients with stable TCM syndrome (score6). They were randomly divided into intervention and control groups. The control group was treated according to Western Medicine guidelines. The intervention group was treated with integrated Traditional Chinese and Western Medicine. The efficacy of TCM syndrome, joint pain score, joint swelling score, ESR, C-reactive protein, serum uric acid, liver and kidney function, and the duration of remission of TCM syndrome were compared between the two groups before and after treatments.For the patients with stable TCM syndrome, there was no significant difference in the effective rate and inefficiency between the intervention group and the control group. For the active type, the effective rate of the intervention group is better than the control group significantly. For the stable type, there was no significant difference between the intervention group and the control group in improving the scores of joint pain and swelling, reducing the level of ESR, C-reactive protein, serum uric acid and improving liver and kidney function. For the active type, the differences between the two groups were significant. The stable stage of gout in the intervention group was longer than the control group.For the gout patients with stable TCM syndrome in the acute stage of gout, we can use TCM treatment or Western Medicine alternatively; for the patients with active TCM syndrome, the scheme of combination of Traditional Chinese and Western Medicine can be applied, with the better curative effect than any medicine alone.

New contingency policy plans are expected to be published by the United Kingdom government to set out urgent actions, such as carbon capture and storage, greenhouse gas removal and the use of sustainable bioenergy to meet the greenhouse gas reduction targets of the 4th and 5th Carbon Budgets. In this study, we identify two plausible bioenergy production pathways for bioenergy with carbon capture and storage (BECCS) based on centralized and distributed energy systems to show what BECCS could look like if deployed by 2050 in Great Britain. The extent of agricultural land available to sustainably produce biomass feedstock in the centralized and distributed energy systems is about 0.39 and 0.5 Mha, providing approximately 5.7 and 7.3 MtDM/year of biomass respectively. If this land‐use change occurred, bioenergy crops would contribute to reduced agricultural soil GHG emission by 9 and 11 urn:x-wiley:17571693:media:gcbb12630:gcbb12630-math-0001/year in the centralized and distributed energy systems respectively. In addition, bioenergy crops can contribute to reduce agricultural soil ammonia emissions and water pollution from soil nitrate leaching, and to increase soil organic carbon stocks. The technical mitigation potentials from BECCS lead to projected CO2 reductions of approximately 18 and 23 urn:x-wiley:17571693:media:gcbb12630:gcbb12630-math-0002/year from the centralized and distributed energy systems respectively. This suggests that the domestic supply of sustainable biomass would not allow the emission reduction target of 50 urn:x-wiley:17571693:media:gcbb12630:gcbb12630-math-0003/year from BECCS to be met. To meet that target, it would be necessary to produce solid biomass from forest systems on 0.59 or 0.49 Mha, or alternatively to import 8 or 6.6 MtDM/year of biomass for the centralized and distributed energy system respectively. The spatially explicit results of this study can serve to identify the regional differences in the potential capture of CO2 from BECCS, providing the basis for the development of onshore CO2 transport infrastructures.

The role of different technologies in a future low carbon energy system is determined by numerous factors, many of which are highly uncertain. Their deployment may be a function of dependency on other technologies, or competition, or wider system effects. In this paper, using a UK example, we explore patterns of interdependency between technologies using a hierarchical clustering approach across multiple scenarios. We find that technologies compete in some instances, often on costs, cluster because they co-depend on each other, or emerge under all conditions, as robust options. Crucially, the broader scenario framing around carbon capture and storage (CCS) availability and climate policy stringency strongly influences these interdependencies. Keywords: Energy system models, Scenario clustering, Technology interdependency, Low carbon pathways

The design of cost-effective power systems with high shares of variable renewable energy (VRE) technologies requires a modelling approach that simultaneously represents the whole energy system combined with the spatiotemporal and inter-annual variability of VRE. Here, we soft-link a long-term energy system model, which explores new energy system configurations from years to decades, with a high spatial and temporal resolution power system model that captures VRE variability from hours to years. Applying this methodology to Great Britain for 2050, we find that VRE-focused power system design is highly sensitive to the inter-annual variability of weather and that planning based on a single year can lead to operational inadequacy and failure to meet long-term decarbonization objectives. However, some insights do emerge that are relatively stable to weather-year. Reinforcement of the transmission system consistently leads to a decrease in system costs while electricity storage and flexible generation, needed to integrate VRE into the system, are generally deployed close to demand centres. The rising share of variable renewable energy sources in the grid makes planning future power systems more complex. Zeyringer et al. present an approach that uses multiple weather-years of data and highlights the need to incorporate inter-annual weather variability into planning decisions.

While many governments rely on oil production and exports for fiscal revenues, the global energy transition driven by climate policy and technological change makes future demand and prices uncertain. We propose a framework to explore prospects for oil production, public revenues from oil, and unexploited oil reserves under hundreds of future energy transitions scenarios, following robust decision making principles. We apply it to Latin American and the Caribbean, a developing region that exports half its oil production and faces fiscal constraints. We use the BUEGO (Bottom-Up Economic and Geological Oil field production) model to simulate field development and production decisions globally. We find that oil production in the region over the next 15 years is highly sensitive to the impact of global climate action on oil prices and to the strategies of large global producers, while choices around oil fiscal regimes have limited impact. Also, 66 to 81% of proved, probable and possible reserves will remain unused by 2035. Finally, cumulative fiscal and nonfiscal revenues from oil would be $1.3-2.6 trillion under strong global climate action, compared to $2.7-6.8 trillion if reserves were strongly exploited. Our findings confirm that governments need to diversify their fiscal revenues away from dependency on oil production.

Bioenergy with carbon capture and storage (BECCS) is envisaged as a critical element of most deep decarbonisation pathways compatible with the Paris Agreement. Such a transformational upscaling—to 3–7 Gt CO2/yr by 2050—requires an unprecedented technological, economic, socio-cultural and political effort, along with, crucially, transparent communication between all stakeholders. Integrated Assessment Models (IAMs) that underpin the 1.5 °C scenarios assessed by IPCC have played a critical role in building and assessing deep decarbonisation narratives. However, their high-level aggregation and their complexity can cause them to be perceived as non-transparent by stakeholders outside of the IAM community. This paper bridges this gap by offering a comprehensive assessment of BECCS assumptions as used in IAMs so as to open them to a wider audience. We focus on key assumptions that underpin five aspects of BECCS: biomass availability, BECCS technologies, CO2 transport and storage infrastructure, BECCS costs, and wider system conditions which favour the deployment of BECCS. Through a structured review, we find that all IAMs communicate wider system assumptions and major cost assumptions transparently. This quality however fades as we dig deeper into modelling details. This is particularly true for sets of technological elements such as CO2 transport and storage infrastructure, for which we found the least transparent assumptions. We also found that IAMs are less transparent on the completeness of their treatment of the five BECCS aspects we investigated, and not transparent regarding the inclusion and treatment of socio-cultural and institutional-regulatory dimensions of feasibility which are key BECCS elements as suggested by the IPCC. We conclude with a practical discussion around ways of increasing IAM transparency as a bridge between this community and stakeholders from other disciplines, policy decision makers, financiers, and the public.

Long-term decarbonisation pathways to achieve ambitious low-carbon targets involve a range of uncertainties. Different energy system modelling approaches can be used to systematically evaluate the influence of the uncertainties, but this often leads to an unmanageable number of pathways. Summarising the large ensemble through a more limited number of representative pathways, to inform stakeholders, can be challenging. This study thus explores how to identify representative decarbonisation pathways using clustering algorithms, which can assist in grouping similar data points in uncategorised datasets, such as pathway ensembles. However, the suitability of clustering algorithms for pathway characterisation has not been investigated to date. Hence, k-means, hierarchical clustering, Gaussian mixture model, spectral clustering, and density-based clustering are adopted for comparisons. An illustrative pathway ensemble for the United Kingdom is applied to evaluate their performance based on cluster validity indices. Three metric transformations, including power, standardisation and sectoral standardisation, are also applied to create three additional sets of pathways for testing. The k-means algorithm is found to outperform others consistently, although hierarchical clustering might also be applicable if the distribution of pathway proximity is uneven. The results also highlight the utility of the approach in revealing distinctive trade-offs between technologies among the identified representative pathways. For instance, the electrification of heating can be replaced by district heating in the residential sector. The described, novel approach can be applied to characterise other sets of pathways, with greater technological details generated by any energy system models, to reveal insights for long-term decarbonisation.

To reduce the amount of water wastage caused by leakage, the utilities have to monitor and detect leakage of water distribution networks periodically. In order to identify leaking pipelines efficiently when limited resources are available, a cluster identification method (CIM) is proposed to establish a priority for leakage detection and to assess whether spatial clusters of high failure-prone areas exist. The proposed CIM evaluates the difference between the observed data and simulated trials to determine the statistical significance of each cluster; a method previously applied only in epidemiology studies to assess the occurrence probabilities of rare diseases for spatial clusters. The CIM suggested in this study is the overlapping local case proportions (OLCP) that uses grids to scope the entire area and then to simulate the number of failures in the neighborhood of each grid. The simulated failure ratios are then compared with the existing records to determine the statistical significance. The statistical significance represents the potential of the grid requiring further leakage detection. Three failure probability estimation methods, including local average, global average, and empirical equation, are utilized to analyze the suitability of the OLCP for use with various probability inputs. A case study in the central region of Taiwan was implemented to demonstrate the applicability of the proposed method. The results indicate that the rate of failure in the following year found within the spatial clusters determined by the OLCP was twice the average amount and thus provided valuable information used to prioritize the pipelines for further inspection.

Chloride diffusuion is regarded as the dominant chloride transport process in concrete and the main cause of the corrosion of steel in concrete structures exposed to chloride-rich environments. Surface biodeposition can be applied to both new and existing concrete structures to restrain this deterioration. To gain comprehensive overview to the protective mechanism of surface biodeposition, a theoretical study of chloride diffusion through surface-biodeposited concrete is required. This paper proposes a physical model for surface biodeposited concrete, and develops a theoretical model to predict chloride diffusion of surface-biodeposited concrete structures. The model describes movement and retention of moisture and chloride by means of balance equations and diffusion laws. The influences of biodeposition and substrate properties on chloride diffusion are studied by a finite difference model. Results indicate that chloride diffusion is controlled by both the biodeposition and the substrate.

A remediation technique of cracked concrete by bacterial mediated carbronate deposition i.e. bio-deposition is discussed. Bio-deposition is a technique that comes from a broader category of biomineralization. The aim of this study was to investigate the plugging of artificially cracked concrete using bacteria Sporosarcina pasteurii and combined with sand as a filling material in artificially made cuts in concrete specimens which was cured in urea and Ca2+ medium and to research the effects on the compressive strength and flexural load of healing of concrete specimens by bio-deposition. The remediation efficacy of cracks in concrete was studied through compressive strength test and flexural failure test. Experimental results show that bio-deposition is able to make the improvement in concrete compressive strength and flexural load. The technique can be used to improve the compressive strength and flexural load of cracked concrete specimens and the remediation of cracks.

Bio-deposition has led to the exploration of remediation and improvement technique in the field of cementitious materials. The aim of this study was to investigate the effects of bio-deposited carbonate on parameters affecting concrete properties and the effects of bio-deposition on the durability of concrete specimens. The remediation efficacy of cracks in concrete was studied through compressive strength test and flexural failure test. Water absorption and the resistance towards carbonation of concrete were analyzed by water absorptivity test and concrete accelerated carbonation test, respectively. Experimental results show that bio-deposition is able to make the improvement in concrete compressive strength and the remediation of cracks. Bacterial deposition of calcite on the surface of the concrete specimens results in a decrease of capillary water uptake and carbonation rate constant, and an increase in resistance towards degradation processes.

To gain an insight into the protective mechanism of surface biodeposition, a theoretical study of carbon dioxide diffusion through surface-biodeposited concrete is required. The present paper proposes a physical model for surface biodeposition and the concept of water-percolated porosity, and develops a theoretical model to predict carbonation of surface-biodeposited concrete structures. The model describes movement and retention of heat, moisture and carbon dioxide by means of balance equations and diffusion laws. The influences of biodeposition and substrate properties on carbon dioxide diffusion are studied by a finite difference model. Results indicate that carbon dioxide diffusion is controlled by both the biodeposition and the substrate. Biodeposition can significantly reduce carbon dioxide concentration at the concrete surface, but this interfacial concentration increases with time.

Biodeposition treatment had been proposed as alternative techniques for improvement in the durability of concrete structures. Laboratory experiments were conducted by bacterially mediated carbonate precipitation on the surface and subsurface of specimens of concrete. Some properties of specimens and crystal, such as the crystal phase, morphology and growth of the crystal deposited on specimens, water penetration, the resistance towards carbonation of concrete and so on, were analyzed by XRD, SEM, water absorptivity test and concrete accelerated carbonation test. Some efficiencies of biodeposition treatment for were investigated by experiment. Results show that the mineral crystal deposits uniformly on the surface and subsurface of specimens, phases of crystal are calcite and vaterite. Biodeposition effectively reduces capillary water uptake and leading to carbonation rate constant decreased by 25~40%. Bacterially mediated carbonate mineralization can be an ecological and novel alternative for improvement in the durability of concrete structures.

Microbial carbonate precipitation had been proposed as alternative technique for improvement in concrete materials. Laboratory experiments were conducted by bacterially mediated carbonate deposition on the surface and subsurface of concrete specimens. The crystal phase, morphology and growth of the crystal deposited on specimens as well as the efficiency of bonding and protection were analyzed by means of X-ray diffraction (XRD), scanning electron microscope (SEM), and ultrasonic test. Water absorption and the resistance of carbonation of concrete were analyzed by water absorptivity test and concrete accelerated carbonation test, respectively. Results show that phases of crystal are calcite and vaterite. The crystals are deposited uniformly on the surface of specimens. Biodeposotion effectively reduces capillary water uptake and carbonation rate constant.

Laboratory experiments were conducted to protect and consolidate historic architectural heritages by bacterially induced carbonate mineralization on the surface of samples of marble and concrete. Some properties of samples and mineral, such as the composition and growth of the mineral deposited on samples, porosity or pore size distribution of samples, the efficiency of protection, the bond behavior between the deposited mineral and substratum, were analyzed by X-ray diffraction, scanning electron microscopy, mercury intrusion porosimetry and ultrasonic test. The results show that the phases of mineral crystal are calcite and vaterite, and the calcium source has an effect on the phase of calcium carbonate mineralization and precipitation. Bacteria act as nucleation sites in the course of precipitation of the mineral crystallization, and the crystal is deposited uniformly on the surface and subsurface of the matrix. The precipitation has no significant effect on the pore size distribution of the matrix, but results in a decrease of porosity, and mineral crystals are strongly attached to the substratum. Bacterial mineralization for remediation of historic buildings can be an ecological and novel alternative to traditional techniques.

The uncertainty of the availability of water resources during the boreal winter has led to significant economic losses in recent years in Taiwan. A modified support vector machine (SVM) based prediction framework is thus proposed to improve the predictability of the inflow to Shihmen reservoir in December and January, using climate data from the prior period. Highly correlated climate precursors are first identified and adopted to predict water availability in North Taiwan. A genetic algorithm based parameter determination procedure is implemented to the SVM parameters to learn the non-linear pattern underlying climate systems more flexibly. Bagging is then applied to construct various SVM models to reduce the variance in the prediction by the median of forecasts from the constructed models. The enhanced prediction ability of the proposed modified SVM-based model with respect to a bagged multiple linear regression (MLR), simple SVM, and simple MLR model is also demonstrated. The results show that the proposed modified SVM-based model outperforms the prediction ability of the other models in all of the adopted evaluation scores. Copyright © 2009 Royal Meteorological Society

A segment-based analysis system is developed to analyse the vulnerability of a water distribution network (WDN). Valve-enclosed segments of a WDN can be efficiently identified by the system using a proposed depth-first search-based algorithm and are illustrated by a Web-based geographic information system. Critical segments, whose failures can significantly impact downstream water supply, are identified by another proposed identification algorithm. With the auxiliary network established from the identified segments, the impact of pipe failures could be assessed and the area affected by a failure event can be effectively delineated. A simulation program using the EPANET2 toolkit is also developed for estimating the impact of failure events. Two case studies are implemented to demonstrate the applicability of the developed system. The developed system can efficiently assess the segment-based vulnerability of a WDN and improve management and response for single or multiple segment failures.

A water quality monitoring network (WQMN) must be designed so as to adequately protect the water quality in a catchment. Although a simulated annealing (SA) method was previously applied to design a WQMN, the SA method cannot ensure the solution it obtained is the global optimum. Therefore, two new linear optimization models are proposed in this study to minimize the deviation of the cost values expected to identify the possible pollution sources based on uniform cost (UC) and coverage elimination uniform cost (CEUC) schemes. The UC model determines the expected cost values by considering each sub-catchment being covered by which station, while the CEUC model determines the coverage of each station by eliminating the area covered by any upstream station. The proposed models are applied to the Derchi reservoir catchment in Taiwan. Results show that the global optimal WQMN can be effectively determined by using the UC or CEUC model, for which both results are better than those from the SA method, especially when the number of stations becomes large.

Pollution loads discharged from upstream development or human activities significantly degrade the water quality of a reservoir. The design of an appropriate water quality sampling network is therefore important for detecting potential pollution events and monitoring pollution trends. However, under a limited budgetary constraint, how to site an appropriate number of sampling stations is a challenging task. A previous study proposed a method applying the simulated annealing algorithm to design the sampling network based on three cost factors including the number of reaches, bank length, and subcatchment area. However, these factors are not directly related to the distribution of possible pollution. Thus, this study modified the method by considering three additional factors, i.e. total phosphorus, nitrogen, and sediment loads. The larger the possible load, the higher the probability of a pollution event may occur. The study area was the Derchi reservoir catchment in Taiwan. Pollution loads were derived from the AGNPS model with rainfall intensity estimated using the Thiessen method. Analyses for a network with various numbers of sampling sites were implemented. The results obtained based on varied cost factors were compared and discussed. With the three additional factors, the chosen sampling network is expected to properly detect pollution events and monitor pollution distribution and temporal trends.