Process-based Methods Research Articles

THE INS AND OUTS OF WATER USE – A REVIEW OF MULTI-REGION INPUT–OUTPUT ANALYSIS AND WATER FOOTPRINTS FOR REGIONAL SUSTAINABILITY ANALYSIS AND POLICY

This paper reviews current knowledge about water footprints (WFs) and the role of input–output techniques. We first provide an overview of the prevailing ‘bottom-up’, process-based methods and their strengths and limitations. This overview leads to discussion of the benefits of combining process-based water footprints with information from input–output techniques. The central theme and proposition is that environmental multi-region input–output analysis (E-MRIO) has a powerful capacity to establish the geography of embodied water, and to complement process-based approaches to WF by expanding their supply-chain coverage. Combining process and input–output information provides valuable information for a diverse set of water planning and water policy objectives. A comprehensive and systematic outline of potential policy applications of E-MRIO (and process analysis methods) is presented.

Overview of Energy Consumption Model for Manufacturing Processes

The energy consumption for manufacturing processes is the largest impact contributor in various characterization categories, based on the assessment of environmental effects during the whole life cycle. It is necessary to investigate the manufacturing processes in depth to find out mechanism that can improve energy efficiency. This paper presents a comprehensive overview on two important aspects of energy consumption models for manufacturing processes: 1) two data collection methods: top-down and bottom-up; 2) two process-based analytical methods: thermodynamic model (including energy flow analysis and exergy analysis), and mechanical model. These models can improve energy efficiency.

Echo State Gaussian Process

Echo state networks (ESNs) constitute a novel approach to recurrent neural network (RNN) training, with an RNN (the reservoir) being generated randomly, and only a readout being trained using a simple computationally efficient algorithm. ESNs have greatly facilitated the practical application of RNNs, outperforming classical approaches on a number of benchmark tasks. In this paper, we introduce a novel Bayesian approach toward ESNs, the echo state Gaussian process (ESGP). The ESGP combines the merits of ESNs and Gaussian processes to provide a more robust alternative to conventional reservoir computing networks while also offering a measure of confidence on the generated predictions (in the form of a predictive distribution). We exhibit the merits of our approach in a number of applications, considering both benchmark datasets and real-world applications, where we show that our method offers a significant enhancement in the dynamical data modeling capabilities of ESNs. Additionally, we also show that our method is orders of magnitude more computationally efficient compared to existing Gaussian process-based methods for dynamical data modeling, without compromises in the obtained predictive performance.

Groundwater Vulnerability Assessment of Plant Protection Products: A Review

ABSTRACT Plant protection products (PPPs) pose a serious dilemma; although their application contributes to the fight against poverty and diseases, at the same time these agrochemicals represent a significant public health threat. As part of Ireland's commitment to the Water Framework Directive (WFD), the country's groundwater sources and resources have to be properly monitored and specific standards in groundwater quality need to be met. Vulnerability assessment is a methodology that evaluates the likelihood of an adverse event occurring and this information can be useful for pollution prevention and decision-making purposes. The objective of this article is to review and compare the most important vulnerability assessment methods and tools that have been used in catchment/regional scale studies. While the approach used is largely dependent on available data, user requirements, and local conditions, the evaluation showed that the COP and PI index-based methods and the MACRO and PRZM process-based methods represent the most advanced tools currently available for large-scale applications. Also discussed is the importance of statistical methods for uncertainty analysis and their usefulness in reducing the data requirements of the index and process-based methods.

Potential Species Distribution of Balsam Fir Based on the Integration of Biophysical Variables Derived with Remote Sensing and Process-Based Methods

In this paper we present a framework for modelling potential species distribution (PSD) of balsam fir [bF; Abies balsamea (L.) Mill.] as a function of landscape-level descriptions of: (i) growing degree days (GDD: a temperature related index), (ii) land-surface wetness, (iii) incident photosynthetically active radiation (PAR), and (iv) tree habitat suitability. GDD and land-surface wetness are derived primarily from remote sensing data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra satellite. PAR is calculated with an existing spatial model of solar radiation. Raster-based calculations of habitat suitability and PSD are obtained by multiplying normalized values of species environmental-response functions (one for each environmental variable) parameterized for balsam fir. As a demonstration of the procedure, we apply the calculations to a high bF-content area in northwest New Brunswick, Canada, at 250-m resolution. Location of medium-to-high habitat suitability values (i.e., >0.50) and actual forests, with >50% bF, matched on average 92% of the time.

Review of Delay Analysis Methods: A Process-Based Comparison

Schedule delays frequently occur in construction projects. Many methods have been developed and used to analyze and measure the schedule delay of construction projects. Selecting a suitable analysis methodology is a major task for resolving the schedule delay claims encountered. This study reviews 18 delay analysis methods, and compares in detail three process-based dynamic analysis methods, namely, the snapshot analysis method, the windows analysis method and the isolated delay type method. A dynamic method is ideal for resolving a delay claim, since it provides accurate analysis. The differences among the dynamic methods in terms of the capabilities, required documents, timing and analysis process are discussed to help delay analysts to select an appropriate method. Finally, this study attempts to propose six suggestions on developing an ideal analysis method.

A geostatistical algorithm to reproduce lateral gradual facies transitions: Description and implementation

Valid representations of geological heterogeneity are fundamental inputs for quantitative models used in managing subsurface activities. Consequently, the simulation of realistic facies distributions is a significant aim. Realistic facies distributions are typically obtained by pixel-based, object-based or process-based methods. This work presents a pixel-based geostatistical algorithm suitable for reproducing lateral gradual facies transitions (LGFT) between two adjacent sedimentary bodies. Lateral contact (i.e. interfingering) between distinct depositional facies is a widespread geometric relationship that occurs at different scales in any depositional system. The algorithm is based on the truncation of the sum of a linear expectation trend and a random Gaussian field, and can be conditioned to well data. The implementation introduced herein also includes subroutines to clean and geometrically characterize the obtained LGFT. The cleaned sedimentary body transition provides a more appropriate and realistic facies distribution for some depositional settings. The geometric measures of the LGFT yield an intuitive measure of the morphology of the sedimentary body boundary, which can be compared to analogue data. An example of a LGFT obtained by the algorithm presented herein is also flow simulated, quantitatively demonstrating the importance of realistically reproducing them in subsurface models, if further flow-related accurate predictions are to be made.

Chemical, biological, and ecotoxicological assessment of pesticides and persistent organic pollutants in the Bahlui River, Romania

Background, aim, and scope Current knowledge on environmental impacts of industrial activities in Romania, particularly persistent organic pollutants (POPs), indicates that environmental standards of the European Union are not systematically met. In our study area, additional sources of POPs are agriculture and domestic wastes. Very scarce information is available upon environmental contaminations and effects. In the present study, we investigated the chemical pollution and their eventual impact on the ecosystem by measuring POPs and by using biological indicators of pollution.

A hybrid process-based and stochastic reconstruction method of porous media

In the present study we have developed a hybrid method that combines statistical with process-based reconstruction methods to recreate the three dimensional morphology of a given porous medium. The method starts with the generation of unconsolidated porous media, made from a process-based method such as the random packing of equal or unequal sized hard spheres and proceeds with a statistical method, the simulated annealing algorithm that matches the original image statistics obtained from two-dimensional SEM micrographs. We have determined the Darcy permeability in the reconstructed 3D domains and compared it with the Kozeny–Carman formula and experimental data obtained from in-house measurements of a sintered porous ceramic and from reported values for the anode cermet of a solid oxide fuel cell. The hybrid method simulation results are in very good agreement with the experimental permeability values and slightly better than those obtained by using simulated annealing alone.

Comportamento hidrológico de bacias hidrográficas: integração de métodos e aplicação a um estudo de caso

O tempo de concentração é uma variável que assume um papel fulcral na determinação do caudal e hidrograma do escoamento numa bacia hidrográfica. Esse trabalho pretende constituir uma fonte exaustiva de informação sobre os diferentes métodos de cálculo do tempo de concentração e vazão de ponta na bacia hidrográfica. Subdividem-se os métodos em estritamente empíricos e semi-empiricos, evidenciando-se as vantagens e constrangimentos de aplicação de cada um deles a partir dos resultados obtidos para a bacia hidrográfica da ribeira do Livramento na região de Setúbal (Portugal). Os tempos de concentração obtidos pelos métodos empíricos e semi-empíricos são depois utilizados no cálculo da vazão de ponta pelos métodos Racional e de Soil Conservation Service (SCS) para ilustrar o impacto nos resultados bem como a vantagem de aplicação de cada um dos métodos. Os resultados demonstram que os métodos semi-empíricos possibilitam a avaliação do impacto das intervenções de engenharia no comportamento hidrológico da bacia, visto que permitem considerar a variabilidade espacial e espácio-temporal das características biofísicas da bacia hidrográfica.

Epistemic Verification of Anonymity

Anonymity is not a trace-based property, therefore traditional model checkers are not directly able to express it and verify it. However, by using epistemic logic (logic of knowledge) to model the protocols, anonymity becomes an easily verifiable epistemic formula. We propose using Dynamic Epistemic Logic to model security protocols and properties, in particular anonymity properties. We have built tool support for DEL verification which reuses state-of-the-art tool support for automata-based verification. We illustrate this approach by analyzing an anonymous broadcast protocol and an electronic voting protocol. By comparison with a process-based analysis of the same protocols, we also discuss the relative (dis)advantages of the process-based and epistemic-based verification methods in general.

Evaluation of methods for quantifying agricultural emissions of air, water and soil pollutants

Integrated assessments that analyze global warming, acidification, eutrophication and ozone related problems simultaneously, need complete, detailed and consistent emission estimates that consider possible interrelations between different pollutants. We discuss three types of emission estimation methods: emission factor, regression analyses and process-based methods. Selected examples of these are reviewed to illustrate the large variety in methods available. We present an approach for the evaluation of emission estimation methods which follows three steps: (1) Comparison, (2) Scoring and (3) Multi-Criteria Analysis (MCA). We demonstrate the usefulness of this approach by applying it to a case study for the Czech Republic. Firstly we compare selected methods with respect to characteristics which we consider as requirements to quantify emissions of air, water and soil pollutants in an integrated way. We observe that none of the selected methods fully meet our defined characteristics. Secondly, we score the methods with respect to three types of criteria. This evaluation reveals large differences between the methods. We conclude that the following methods best meet our criteria: the IPCC Guidelines, methods from INITIATOR, and the detailed method of the EMEP/CORINAIR Guidebook. Finally, we perform a Multi-Criteria Analysis to analyze how our conclusions change if one considers certain criteria as more important than others. Based on this analysis we suggest that combining parts of each of the three methods forms a sound basis for a new emission estimation method for quantifying agricultural emissions of air, water and soil pollution simultaneously.

Empirical Comparison of Process and Economic Input-Output Life Cycle Assessment in Service Industries

The study fills a gap in existing literature by comparing process-based and E10-based life cycle assessment (LCA) methods empirically in service industries. Despite the numerous methodological differences, the methods were found mostly to produce the same environmentally significant processes for the case organization: the use of electricity in the premises, the construction of the premises, the business travel by cars, the heating of the premises, and the business flights. However, the process-based LCA could not be used to assess the environmental impacts of purchased services properly. The study also recognized most of the theoretical differences listed in the literature, and found the ones related to the cut-offs in purchased services, the price inhomogeneity, and the industry-atypical electricity production have the greatest influence on results.

Two-dimensional equilibrium morphological modelling of a tidal inlet: an entropy based approach

The management of tidal inlets requires the accurate prediction of equilibrium morphologies. In areas where the flow from rivers is highly regulated, it is important to give decision makers the ability to determine optimal flow management schemes, in order to allow tidal inlets to function as naturally as possible, and minimise the risk of inlet closure. The River Murray Mouth in South Australia is one such problem area. Drought and the retention of water for irrigation and urban water consumption have limited the amount of water entering the estuary. As a result, sediment from the coastal environment is being deposited in the mouth of the estuary, reducing the effect of further coastal interactions. Currently, situations such as this are modelled using traditional process-based methods, where wave, current, sediment transport and sediment balance modules are linked together in a time-stepping process. The modules are reapplied and assessed until a stable morphology is formed. In this paper, new options for modelling equilibrium morphologies of tidal inlets are detailed, which alleviate some of the shortfalls of traditional process-based models, such as the amplification of small errors and reliance on initial conditions. The modelling problem is approached in this paper from a different angle and involves the use of entropy based objective functions, which are optimised in order to find equilibrium morphologies. In this way, characteristics of a system at equilibrium can be recognised and a stable system predicted without having to step through time. This paper also details the use of self-organisation based modelling methods, another non-traditional model application, where local laws and feedback result in the formation of a global stable equilibrium morphology. These methods represent a different approach to traditional models, without some of the characteristics that may add to their limitations.

Simultaneous examination of nitrous oxide emissions in grazed pastures using paddock-scale measurements and process-based models

In-situ farm-scale measurements are a prerequisite to improve the accuracy of the greenhouse gas inventory and to assess the viability of mitigation options. These measurements are also important in developing and verifying the empirical, as well as process-based, modelling approaches to emission estimates at farm-scales and beyond. Here, we assess the practicalities of implementing process-based modelling methods of quantifying nitrous oxide (N2O) emissions through validation and testing at the farm-scale, using environmental inputs and N2O emissions data from an emissions measurement campaign on dairy-grazed pastures in New Zealand. The median emissions measured with an atmospheric technique gave an emission factor (EF) of about 0.01, similar to the EF currently used by New Zealand inventory reporting for animal excreta (0.01) or for N fertiliser (0.0125). Emissions were simulated at the farm scale using two process-based models: NZ-DNDC and DayCent. The NZ-DNDC and DayCent models predicted EFs of 0.022 and 0.015, respectively for non-irrigated conditions and 0.041 and 0.032, respectively with irrigation. Lack of information on the grazing (excretal N inputs) and irrigation schedules before the campaign, and on soil ammonium and nitrate levels, was the main limitation in these validations. Identification of these shortcomings has been useful for the design of further integrated work on model development with farm-scale validation.

Harvesting project knowledge: a review of project learning methods and success factors

This article presents an overview of proven methods to record experiences from projects and discusses their use in project management. We distinguish between process-based and documentation-based debriefing methods. Process-based methods focus on a procedural approach to capture key learnings from a project. Documentation-based methods serve as appropriate representation formats or structures for project insights. The article bridges the current gap between theoretical insights into this topic and the managerial reality today. It discusses central project debriefing problems such as the lacking willingness to learn from mistakes or the lacking discipline in the use of project management manuals. We conclude the article with recommendations on how debriefing processes can be integrated successfully into project procedures.

Using Corporate-Based Methods to Assess Technical Communication Programs

Assessment continues to be an important issue for technical communicators in both practitioner and academic contexts. In this article, we investigate methods of program assessment used by corporate learning sites and we profile value add methods as a new way to both construct and evaluate academic programs in technical communication. Our goal is to introduce value added assessment methods as one way to supplement and expand current methods of program assessment. The article initially reviews Return on Investment (ROI) indicators as a widely used model for assessing programs. However, we are critical of these indicators, suggesting that they are biased against technical communication in both practitioner and academic contexts. The article then examines and critiques assessment methods from corporate training environments. These include methods employed by corporate universities and value added process-based assessment methods. The second half of the article profiles value added methods by applying them in a brief assessment of a technical communications certificate program. We conclude that while the program uses ROI indicators as a marketing device, the value the program brings and adds to its university is the “portal” it creates for university and business community collaboration. This value cannot be fully demonstrated solely through the use of ROI indicators. The article then discusses the kinds of programmatic negotiations value added processes require within university contexts that may impose non-value added activities on departments and programs. The article concludes by critically examining the appropriateness of corporate assessment methods for academic contexts.

Developing a usage-based software certification process

The author proposes an alternative to process-based methods of assuring software quality: a certification process that will provide product-based and trustworthy quality guarantees for commercial software packages. I call the agencies that perform such certification "software certification laboratories" (SCLs). The beauty of establishing independent SCLs is that they provide a fair playing field for each publisher, assuming that each product under review receives equal treatment.

Assessing groundwater vulnerability to agrichemical contamination in the Midwest US

Agrichemicals (herbicides and nitrate) are significant sources of diffuse pollution to groundwater. Indirect methods are needed to assess the potential for groundwater contamination by diffuse sources because groundwater monitoring is too costly to adequately define the geographic extent of contamination at a regional or national scale. This paper presents examples of the application of statistical, overlay and index, and process-based modeling methods for groundwater vulnerability assessments to a variety of data from the Midwest U.S. The principles for vulnerability assessment include both intrinsic (pedologic, climatologic, and hydrogeologic factors) and specific (contaminant and other anthropogenic factors) vulnerability of a location. Statistical methods use the frequency of contaminant occurrence, contaminant concentration, or contamination probability as a response variable. Statistical assessments are useful for defining the relations among explanatory and response variables whether they define intrinsic or specific vulnerability. Multivariate statistical analyses are useful for ranking variables critical to estimating water quality responses of interest. Overlay and index methods involve intersecting maps of intrinsic and specific vulnerability properties and indexing the variables by applying appropriate weights. Deterministic models use process-based equations to simulate contaminant transport and are distinguished from the other methods in their potential to predict contaminant transport in both space and time. An example of a one-dimensional leaching model linked to a geographic information system (GIS) to define a regional metamodel for contamination in the Midwest is included.

Assessing groundwater vulnerability to agrichemical contamination in the Midwest US

Agrichemicals (herbicides and nitrate) are significant sources of diffuse pollution to groundwater. Indirect methods are needed to assess the potential for groundwater contamination by diffuse sources because groundwater monitoring is too costly to adequately define the geographic extent of contamination at a regional or national scale. This paper presents examples of the application of statistical, overlay and index, and process-based modeling methods for groundwater vulnerability assessments to a variety of data from the Midwest U.S. The principles for vulnerability assessment include both intrinsic (pedologic, climatologic, and hydrogeologic factors) and specific (contaminant and other anthropogenic factors) vulnerability of a location. Statistical methods use the frequency of contaminant occurrence, contaminant concentration, or contamination probability as a response variable. Statistical assessments are useful for defining the relations among explanatory and response variables whether they define intrinsic or specific vulnerability. Multivariate statistical analyses are useful for ranking variables critical to estimating water quality responses of interest. Overlay and index methods involve intersecting maps of intrinsic and specific vulnerability properties and indexing the variables by applying appropriate weights. Deterministic models use process-based equations to simulate contaminant transport and are distinguished from the other methods in their potential to predict contaminant transport in both space and time. An example of a one-dimensional leaching model linked to a geographic information system (GIS) to define a regional metamodel for contamination in the Midwest is included.