An Extended Self-Organizing Map Network for Modeling and Control of Pulse Jet Fabric Filters

ABSTRACT

Pulse jet fabric filters (PJFFs) have become an attractive option of particulate collection utilities, because they can meet stringent particulate emission limits regardless of variation in operating conditions. Despite their wide applications, the present control algorithm for PJFFs can best be described as rudimentary. In this paper, a modeling and control strategy based on the local model network (LMN) is proposed. An extended self-organizing map (ESOM) network is developed to construct the LMN model of the filtration process using the filter's input-output data. Subsequently, these ESOM local models are incorporated into the design of local generalized predictive controllers (GPC), and the proposed controller design is obtained as the weighted sum of these local controllers. Simulation results show that the proposed controller design yields a better performance than both conventional GPC and proportional plus integral (PI) controllers yield.     

An extended self-organizing map network for modeling and control of pulse jet fabric filters

Pulse jet fabric filters (PJFFs) have become an attractive option of particulate collection utilities, because they can meet stringent particulate emission limits regardless of variation in operating conditions. Despite their wide applications, the present control algorithm for PJFFs can best be described as rudimentary. In this paper, a modeling and control strategy based on the local model network (LMN) is proposed. An extended self-organizing map (ESOM) network is developed to construct the LMN model of the filtration process using the filter's input-output data. Subsequently, these ESOM local models are incorporated into the design of local generalized predictive controllers (GPC), and the proposed controller design is obtained as the weighted sum of these local controllers. Simulation results show that the proposed controller design yields a better performance than both conventional GPC and proportional plus integral (PI) controllers yield.     

Policy insight from renewable energy,foreign direct investment (FDI), and urbanization towards climate goal: insight from Indonesia

This study is premised on Indonesia’s climate goal amidst good economic performance. To test the environmental implication of this macroeconomic performance of Indonesia, we adopt Indonesian quarterly data of 1990Q1–2018Q4 for empirical analysis. Relevant instruments in the economic performance of Indonesia such as urbanization, foreign direct investment (FDI), and renewable energy source are all adopted for accurate estimations and analysis of this topic. Different approaches (structural break test, autoregressive distributed lag (ARDL)-bounds testing and Granger causality) are all adopted in this study. Our analysis and policy recommendations are based on the short-run and long-run ARDL dynamics and Granger causality. Findings from ARDL confirmed negative relationship between carbon emission and renewable energy source, FDI, and urbanization. Also, a U-shape instead of inverted U-shaped EKC is found confirming the impeding implication of Indonesian economic growth to its environmental performance if not checkmate. From Granger causality analysis, all the variables are seen transmitting to urbanization in a one-way causal relationship. Also, FDI and renewable energy prove to be essential determinants of the country’s environment development; hence, FDI is seen transmitting to both energy sources (fossil fuels and renewables) in a one-way causal relationship. Renewable energy is as well seen having two ways causal relationship with both carbon emission and fossil fuels. This result has equally exposed the significant position of the three instruments (urbanization, FDI, and renewable energy source) in Indonesian environment development.

     

Performance enhancement of solar photovoltaic system for roof top garden

Environmental Science and Pollution Research - The photovoltaic (PV) for irrigation system is an emerging technology to harness the solar energy. The performance of the PV modules depends on the...     

Some Basic Consideration in the Design of an Air Pollution Monitoring System

Quantified air quality and meteorological information provided by an air pollution monitoring system must be geared to the legally prescribed functions of the control agency. The network must be treated as a vital component of the total integrated data system that supports agency activities in air resources management and control. It should be closely interphased with data systems for emission inventory, registration and permits, violations and complaints, fuel use, emission reduction plans, land use, demographic projections, and urban planning. Compatibility with neighboring and statewide or regionwide data systems is essential for coordination of effort, especially under episode conditions.

The network should be planned on three levels, static, semi-automatic, and fully automatic, to provide monthly, daily, and up-to-the-minute measurements, respectively. Optimization of network specifications requires a three-way balance of hardware, control objectives, and agency resources (capital facilities, manpower, funding, etc.), of which the first two are realistically governed by the third.

A monitoring network could serve a wide range of functions, and there are pressures and temptations to cater to all possible users. A number of functions are listed; an order of priority should be determined. Experience shows that far more data tend to be generated than can be analyzed, assimilated, and utilized. Rapid data acquisition and on-line processing capabilities of present-day automatic networks could, without effective planning, result in mountainous backlogs of unassimilated information.

A systems engineering approach to planning will ascertain that preliminary requirements are critically scrutinized, and only genuine requirements that meet the test of constraints (natural environment, economic, legal, social, political constraints, and manpower resources) will be translated into performance specifications. By means of this approach, design characteristics that are extraneous or peripheral to the principal network functions can be identified as low priority luxuries, whereas seemingly expensive items may be justified on the basis of data reliability or long-range savings in operation and maintenance requirements.     

AERCOARE: An overwater meteorological preprocessor for AERMOD

AERCOARE is a meteorological data preprocessor for the American Meteorological Society and U.S Environmental Protection Agency (EPA) Regulatory Model (AERMOD). AERCOARE includes algorithms developed during the Coupled-Ocean Atmosphere Response Experiment (COARE) to predict surface energy fluxes and stability from routine overwater measurements. The COARE algorithm is described and the implementation in AERCOARE is presented. Model performance for the combined AERCOARE-AERMOD modeling approach was evaluated against tracer measurements from four overwater field studies. Relatively better model performance was found when lateral turbulence measurements were available and when several key input variables to AERMOD were constrained. Namely, requiring the mixed layer height to be greater than 25 m and not allowing the Monin Obukhov length to be less than 5 m improved model performance in low wind speed stable conditions. Several options for low wind speed dispersion in AERMOD also affected the model performance results. Model performance for the combined AERCOARE-AERMOD modeling approach was found to be comparable to the current EPA regulatory Offshore Coastal Model (OCD) for the same tracer studies. AERCOARE-AERMOD predictions were also compared to simulations using the California Puff-Advection Model (CALPUFF) that also includes the COARE algorithm. Many model performance measures were found to be similar, but CALPUFF had significantly less scatter and better performance for one of the four field studies. For many offshore regulatory applications, the combined AERCOARE-AERMOD modeling approach was found to be a viable alternative to OCD the currently recommended model.

Implications: A new meteorological preprocessor called AERCOARE was developed for offshore source dispersion modeling using the U.S. Environmental Protection Agency (EPA) regulatory model AERMOD. The combined AERCOARE-AERMOD modeling approach allows stakeholders to use the same dispersion model for both offshore and onshore applications. This approach could replace current regulatory practices involving two completely different modeling systems. As improvements and features are added to the dispersion model component, AERMOD, such techniques can now also be applied to offshore air quality permitting.     

Performance Evaluation of Integral and Analytical Plume Rise Algorithms

The purpose of this study was to evaluate the performance of current regulatory algorithms for predicting plume rise for refinerytype sources (short stacks and a wide range of source conditions) and the performance of new or alternate algorithms which may provide better estimates. To meet the objectives, five plume rise algorithms were statistically evaluated against ten field and laboratory plume rise data bases. Two forms of the Briggs plume rise equations were tested because they are almost exclusively used in current EPA regulatory models. Two modified Briggs equations were tested to assess how simple modifications can Improve the accuracy of the estimates. The fifth algorithm was a numerical solution to the basic equations for conservation of mass, momentum, and energy often referred to as an Integral plume rise algorithm. This algorithm was selected because It handles the wide range of source and atmospheric boundary-layer conditions that affect trajectories of plumes from refinery stacks.

Ten independent plume rise data bases were assembled that covered a wide range of source and meteorological conditions. From the data bases, a total of 107 different data sets were obtained and each data set included plume rise observations versus downwind distance for one source and meteorological condition. Each model was run for each data set and the root-mean-square and mean error between model and observation was computed for use in statistically evaluating model performance.

The statistical evaluation of the algorithms showed that the rms error (considering all data bases) for the Integral plume rise algorithm was approximately 30 percent less than the errors for all other algorithms tested. This difference was significant at the 95 percent confidence level. The results suggest that improved plume rise estimates in regulatory models applied to refineries and other appropriate sources could be achieved to reduce costs and improve ambient air quality estimates through the use of an integral plume rise algorithm.     

Recovering valuable metals from recycled photovoltaic modules

Recovering valuable metals such as Si, Ag, Cu, and Al has become a pressing issue as end-of-life photovoltaic modules need to be recycled in the near future to meet legislative requirements in most countries. Of major interest is the recovery and recycling of high-purity silicon (>99.9%) for the production of wafers and semiconductors. The value of Si in crystalline-type photovoltaic modules is estimated to be ?$95/kW at the 2012 metal price. At the current installed capacity of 30 GW/yr, the metal value in the PV modules represents valuable resources that should be recovered in the future. The recycling of end-of-life photovoltaic modules would supply >88,000 and 207,000 tpa Si by 2040 and 2050, respectively. This represents more than 50% of the required Si for module fabrication. Experimental testwork on crystalline Si modules could recover a >99.98%-grade Si product by HNO₃/NaOH leaching to remove Al, Ag, and Ti and other metal ions from the doped Si. A further pyrometallurgical smelting at 1520ºC using CaO–CaF₂–SiO₂ slag mixture to scavenge the residual metals after acid leaching could finally produce >99.998%-grade Si. A process based on HNO₃/NaOH leaching and subsequent smelting is proposed for recycling Si from rejected or recycled photovoltaic modules.

Implications:The photovoltaic industry is considering options of recycling PV modules to recover metals such as Si, Ag, Cu, Al, and others used in the manufacturing of the PV cells. This is to retain its “green” image and to comply with current legislations in several countries. An evaluation of potential resources made available from PV wastes and the technologies used for processing these materials is therefore of significant importance to the industry. Of interest are the costs of processing and the potential revenues gained from recycling, which should determine the viability of economic recycling of PV modules in the future.     

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

A Qualitative Approach to Evaluating the Anticipated Reliability of a Photochemical Air Quality Simulation Model for a Selected Application

ABSTRACT

Photochemical air quality simulation models are now used widely in evaluating the merits of alternative emissions control strategies on spatial scales from metropolitan to sub-continental. Greatly varying levels of resources have been available to support modeling, from relatively comprehensive databases and evaluation of performance to a paucity of aerometric data for developing model inputs. Where data are sparse, many alternative outcomes are consistent with the knowledge at hand. Where performance evaluation is inadequately supported, the probability of error may be high. In each instance, uncertainties may be large when compared with the signal of interest, and thus confidence in the reliability of the model as an estimator of future air quality may come into question.

This paper proposes a qualitative procedure for assessing whether a particular application of a modeling system is likely to be potentially unreliable, suggesting that either (1) modification and further evaluation is needed, if supportable, prior to adoption for regulatory application; or (2) the model should not be used if improvement is not supportable. The procedure is proposed for use by policy-makers, staffs of public agencies, air quality managers, environmental staffs of industrial organizations, and other interested parties. The proposed use of the procedure is (1) to assess, a priori, whether a proposed application is likely to be judged questionable or unacceptably uncertain in outcome; and (2) to provide, a posteriori, a basis for judging quickly the likely quality of model performance. The procedure is presented with tropospheric ozone as the pollutant of concern. With adjustments, however, the procedure should be applicable for particu-late matter and other pollutants of interest.     

Design of control strategies for nutrient removal in a biological wastewater treatment process

Wastewater treatment plants (WWTP) are highly non-linear operations concerned with huge disturbances in flow rate and concentration of pollutants with uncertainties in the composition of influent wastewater. In this work, the activated sludge process model with seven reactor configuration in the ASM3bioP framework is used to achieve simultaneous removal of nitrogen and phosphorus. A total of 8 control approaches are designed and implemented in the advanced simulation framework for assessment of the performance. The performance of the WWTP (effluent quality index and global plant performance) and the operational costs are also evaluated to compare the control approaches. Additionally, this paper reports a comparison among proportional integral (PI) control, fuzzy logic control, and model-based predictive control (MPC) configurations framework. The simulation outcomes indicated that all three control approaches were able to enhance the performance of WWTP when compared with open loop operation.

     

Techno-economic assessment of coconut biodiesel as a potential alternative fuel for compression ignition engines

Over the past years, there were dramatic improvements in identifying and assessing various feedstocks for the production of biodiesel fuels. To promote a particular feedstock as a renewable source of energy, it is important to analyze their energy, economic, and engine performance characteristics. The current work attempts to evaluate the net energy and economic indices for both fossil diesel and coconut-blended diesel (B20) considering the diesel consumption by the Indian railways. Further, we present the experimental results of a multi-cylinder diesel engine operated with neat coconut biodiesel (B100) and fossil diesel at various load and speed conditions. The engine experiments reveal that the coconut biodiesel exhibits leaner combustion and shorter ignition delay than fossil diesel. Lower amount of carbon monoxide, hydrocarbon, and smoke emission is observed in the case of coconut biodiesel, with higher levels of nitric oxide (14%) and fuel consumption than diesel. The coefficient of variation in indicated mean effective pressure is within the range of better driveability zone for both the fuels at all test conditions. Overall the engine performance, emission and combustion results with neat coconut biodiesel are favorable with a penalty in NO emission at high load conditions. The techno-economical study highlights higher production cost per liter of B20 than the cost of fossil diesel. However, the net energy ratio (NER) for B20 is 1.021, favoring higher output than diesel and thus lowers the dependency on crude oil.

     

Rapid immobilization of viable Bacillus pseudomycoides in polyvinyl alcohol/glutaraldehyde hydrogel for biological treatment of municipal wastewater

A new approach for easy synthesis of Bacillus pseudomycoides immobilized polyvinyl alcohol (PVA)/glutaraldehyde (GA) hydrogel for application in a wastewater treatment system is reported. Optimization studies revealed that GA/PVA mass ratio of 0.03 and acidic pH of 2 were required for hydrogel synthesis and eventually for bacterial cell immobilization. The synthesized crosslinked matrix possessed a pore size suitable for microbial cell entrapment while maintaining cell accessibility to external environment for bioremediation. Possible crosslinking and bacterial cell immobilization in the hydrogel were evidenced by FTIR, XRD, and SEM studies, respectively. Further, the extent of crosslinking of GA with PVA was investigated and confirmed by transmittance and permeability experiments. The viability and proliferation of hydrogel embedded cells (after 25 days) was confirmed by confocal fluorescence microscopy which also indicated that acidic pH of polymer solution did not affect the immobilized live cells. B. pseudomycoides immobilized hydrogel were demonstrated to be effective for treatment of municipal wastewater and reduced biochemical oxygen demand (BOD), chemical oxygen demand (COD), and protein content below the recommended levels. Overall, the results from this bench-scale work show that employing bacteria-embedded PVA/GA hydrogel for the treatment of municipal wastewater yield promising results which should be further explored in pilot/field-scale studies.

     

Application of Genetic Algorithms for the Design of Ozone Control Strategies

ABSTRACT

Designing air quality management strategies is complicated by the difficulty in simultaneously considering large amounts of relevant data, sophisticated air quality models, competing design objectives, and unquantifiable issues. For many problems, mathematical optimization can be used to simplify the design process by identifying cost-effective solutions. Optimization applications for controlling nonlinearly reactive pollutants such as tropospheric ozone, however, have been lacking because of the difficulty in representing nonlinear chemistry in mathematical programming models.

We discuss the use of genetic algorithms (GAs) as an alternative optimization approach for developing ozone control strategies. A GA formulation is described and demonstrated for an urban-scale ozone control problem in which controls are considered for thousands of pollutant sources simultaneously. A simple air quality model is integrated into the GA to represent ozone transport and chemistry. Variations of the GA formulation for multiobjective and chance-constrained optimization are also presented. The paper concludes with a discussion of the practicality of using more sophisticated, regulatory-scale air quality models with the GA. We anticipate that such an approach will be practical in the near term for supporting regulatory decision-making.     

Modeling a periodic electric vehicle–routing problem considering delivery due date and mixed charging rates using metaheuristic method

The coupling of ever-increasing consumption of fossil fuels around the globe with the decrease in the availability of fossil fuel supplies has led to an increased cost of energy commodities, which together with ever-expanding requirements for reducing the level of environmental pollutions has resulted in an ever-increasing deal of attention to alternative transportation schemes such as electric vehicles (EVs). Since decades ago, national governments and environmental activists have initiated various efforts towards reducing atmospheric pollutions. A part of such effort has been focused on reducing the use of internal combustion vehicles and rather replacing them with EVs. In this research, we attempt to fill in this research gap by presenting a mathematical model for minimizing the sum of traveled distance and recharging cost of EVs per a given period and then solving it by simulated annealing (SA) algorithm. Results of the proposed algorithm were then compared to those of coding in GAMS for 30 different sample problems with different counts of customers, EVs, and charging stations. Numerical results indicated good efficiency of the metaheuristic algorithm in terms of processing time and solution quality. Indeed, with the SA algorithm, the processing time was seen to increase gradually with increasing the problem complexity, while the rate of increase in processing time was much steeper with the GAMS.

     

活性污泥微型动物群落结构优化的可控途径研究

优化活性污泥微型动物群落的结构实际就是从根本上优化活性污泥的运转效能。优化作用可从以下几个方面着手 :为活性污泥中的微型动物提供适合其生长繁殖的运行参数 ;优化这些生物所需的营养 ;向活性污泥曝气池中投放微型动物。     

Green finance,technological progress,and ecological performance—evidence from 30 Provinces in China

The interaction between green finance and other factors, such as ecological environment, has been a research hotspot nowadays. Especially, the reasonable guiding of capital into energy conservation and environmental protection industries would greatly affect those factors, so as to the relation between them. This paper aimed to analyze the relationships between green finance, technological progress, and ecological performance quantitatively. The entropy method was used to respectively construct the system of index for green finance and technological progress, and index for ecological performance was measured by the super-SBM model. The panel vector autoregressive (PVAR) model was selected to empirically analyze dynamic relationships based on datasets from 30 provinces in China during 2008–2019 period. The results told that (1) from 2008 to 2019, China’s overall level of green finance, technological progress and ecological performance increased to varying degrees. Spatially, the areas with high-developed green finance greatly coincided with those such as large cities or the eastern coast that had good financial development. The distribution of technological progress index were similar, except some underdeveloped areas with relatively advanced scientific research institutes. The ecological performance, however, was high in the South and low in the north. (2) In the lag for 3 years, the influence of green finance on ecological performance in different regions was all positive for that all the coefficient symbols that passed the significance test were above 0, while that on technological progress was negative first and then positive. And the effects of technological progress on ecological performance were positive in ecological regions and negative in low ecological regions (0.0893 and -0.1211 in the case of three-stage lag respectively). (3) The contribution of green finance to ecological performance was high according to the results of variance decomposition, maintained at about 30%, and that of technological progress increased year by year (from 0.000 to 0.039). Therefore, we proposed to strengthen the development of green finance in underdeveloped regions. The emphasis should be laid on the researches and applications of green technology, the formulation of financing policies in innovation compensation and the establishment of a dynamic monitoring system for the ecological environment.

     

Human Visual Sensitivity to Plumes with a Gaussian

This paper discusses results of a research project designed to develop an empirical model that could be used as a tool to predict human visual sensitivity to plumes. The resultant probability of detection algorithm (PROBDET) allows one to estimate the probability of a plume of known size, shape and contrast being detected visually. As a basis for the algorithm, a series of laboratory experiments using a high threshold signal detection procedure and computer generated images of plumes with Gaussian luminance distributions was conducted to measure human visual sensitivity to plumes. Results of the laboratory experiments are compared with results of contrast sensitivity experiments that examined visual sensitivity to stimuli with square and sine wave luminance distributions. An example of the PROBDET algorithm is presented to demonstrate its potential

usefulness for assessing how probability of detection estimates change as plume size and contrast parameters vary. Since this research was designed to build on existing knowledge, a discussion of that knowledge and how it relates to the research conducted is also presented. The focus of this discussion is on the human visual system (HVS) and on how visual sensitivity is affected by factors such as the luminance of the stimulus and the surround, the luminance distribution of the stimulus, the size of the surround, and the size and spatial frequency characteristics of the stimulus.     

利用太阳能驱动的一体化氧化沟的运行方式

污水处理的高能耗和新能源利用已引起人们的关注,本文根据太阳光照强度的周期变化和农村污水昼夜排放量悬殊的特征,提出了一种新型的利用无蓄电池太阳能光伏系统驱动的污水生物处理系统,可有效降低太阳能光伏系统的成本。生物反应器是一个双沟式一体化氧化沟。按照启动的用电设备的数量,一体化氧化沟具有5种运行方式。在不同的运行方式下,一体化氧化沟的内沟和外沟具有不同的功能,其中运行方式3到运行方式5对污染物去除效率最高。采用阶梯型电量输出模式,可以充分利用太阳能,并保障一体化氧化沟的高效运行时间。在160 d的连续运行实验中,COD、氨氮、总氮和总磷的平均去除率分别为87.8%、98.4%、68.7%和80.3%。证明无蓄电池太阳能光伏系统驱动污水生物反应器处理农村分散污水是可行的。     

Decomposition of Gas Phase 1,3-Butadiene by Ultraviolet/Ozone Process

Abstract

A pilot-scale plug-flow reactor was built to investigate its performance in treating airborne 1,3-butadiene (BD) via ozonation (O₃) and ultraviolet (UV)/O₃ technologies. Governing factors, such as the initial molar ratio of ozone to BD, UV volumetric electric input power, and moisture content in the influent airstream, were investigated. Experiments were conducted at an influent BD concentration of ～50 ppm, an ambient temperature of 26 °C, and a gas retention time of 85 sec. Results show that an initial molar ratio of ozone to BD of 3.5 and 2 sufficed to obtain BD decompositions of >90% for ozonation and UV/O₃, respectively. The UV irradiance did not directly promote the decomposition of BD, rather, it played a role in promoting the production of secondary oxidants, such as hydroxyl radicals. Kinetic analyses indicate that both types of BD decomposition are peudo–first-order with respect to BD concentrations. Moisture content (relative humidity = 40–99%) and UV volumetric electric input power (0.147 and 0.294 W/L) are both factors that weakly affect the rate of BD decomposition. Economic evaluation factors, including both energy of ozone production and UV electric input power, were also estimated.