Modeling and Optimal Control of Atmospheric Pollution Hazard in Nuclear and Chemical Disasters

AbstractNuclear and chemical disasters can cause heavy atmospheric pollution hazard and threat people's lives and health. In this paper, theory and application for modeling and optimal control of such hazard is studied. The modeling is based on the simulation and visualization of atmospheric dispersion of pollutants, the source term estimation of nuclear and chemical disasters, and the risk evaluation of hazardous substances. The optimal control is based on Natural Cybernetics theory, effective and economic cost evaluation of control techniques, and optimization methods. Some applications and illustrations of modeling and optimal control are reported

Smaller, Closer, Dirtier: Diesel Backup Generators in California

Quantifies the threat to air quality and human health by backup generators, and examines air quality in Los Angeles, San Diego, Sacramento, and Fresno, with some analysis of San Francisco as well

Environmental Parameter Effects on the Fate of a Chemical Slick

International audienc

Establishing National Ocean Service Priorities for Estuarine, Coastal, and Ocean Modeling: Capabilities, Gaps, and Preliminary Prioritization Factors

This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages

A SIMPLIFIED APPROACH FOR SOLUTION OF TIME UPDATE PROBLEM DURING TOXIC WASTE PLUME SPREADING IN THE ATMOSPHERE

Reliable and up to date information represents principal prerequisite for effective management of intervention operations targeted on emergency situations during accidental releases of harmful substances into the atmosphere. Promising way of this trend insists in development of assimilation techniques for improvement of model prognosis reliability on basis of optimal blending of predictions with observations incoming from terrain. In this paper we are concentrating on the forecast procedure which generates the new state predictions from the initial conditions standing for previous time. Two problems are encountered here. At first, the resulting predictions from the previous time step can be assimilated with incoming data before the next time predictions are evaluated. The initial conditions for the next time are then modified in advance and trajectory information accumulated from the same beginning can become fuzzy. So, the trajectory models can have troubles how to propagate plume in the next time. At second, reliable and up to date information at medium distances from the source of pollution represents basic inevitable conditions for effective management of intervention operations targeted on consequence mitigation during emergency situations. But justifiability of Gaussian plume model application in medium range distances is questionable. A simplified solution offers segmented Gaussian plume model (SGPM) which can account stepwise for the time dynamics of the admixture release and hourly changes of meteorological conditions. The extension of modelling to medium distances is facilitated by availability of the new quality of gridded spatial short-term meteorological forecasts. The Czech meteorological service provides 3-D data in ALADIN format for medium domain 160 km × 160 km around each nuclear power plant (NPP) in the Czech Republic. In the following text we are describing the SGPM application in longer distances taking into account the new gridded meteorological predictions. The comparison with former methodology is illustrated on one real meteorological situation from June 25, 2008

Planning the petrochemical industry in Kuwait using economic and safety objectives

Kuwait, one of the major oil producing countries in the Middle East, is in the process of globalizing its operation in petroleum and petrochemical production. Kuwaiti officials have expressedin terest in acceleratingd evelopmento f the country's relatively small petrochemical industry. The development is to produce new valuable chemicals from the available basic feedstock chemicals. Two of the important planning objectives for a petrochemical industry are the economic gain and the industrial safety involved in the development. For the economic evaluation of the industry, and for the proposed final product chemicals in the development, a long-range plan is needed to identify trends in chemical prices. The chemical prices are related to the oil price, which is considered an important motivator for the whole petrochemical industry. Price trend modelling is performed to be able to forecast these prices for the planning horizon. Safety, as the second objective, is considered in this study as the risk of chemical plant accidents. Risk, when used as an objective fimction, has to have a simple quantitative form to be easily evaluated for a large number of possible plants in the petrochemical network. The simple quantitative form adopted is a risk index that enables the number of people affected by accidents resulting in chemical releases to be estimated. The two objectives, when combined with constraints describing the desired or the possible structure of the industry, will form an optimization model. For this study, the petrochemical planning model consists of a Mixed Integer Linear Programming (MILP) model to select the best routes from the basic feedstocks available in Kuwait to the desired final products with multiple objective functions. The economic and risk objectives usually have conflicting needs. The presence of several conflicting objectives is typical when planning. In many cases, where optimization techniques are utilized, the multiple objectives are simply aggregated into one single objective function. Optimization is then conducted to get one optimal result. However, many results are obtained for different aggregations of the objectives and eventually a set of solutions is obtained. Other tools, such as strategic tools, are used to select the best solution from the set. This study, which is concerned with economic and risk objectives, leads to the identification of important factors that affect the petrochemical industry. Moreover, the procedure, of modelling and model solution, can be used to simplify the decisionmaking for complex or large systems such as the petrochemical industry. It presents the use of simple multiple objective optimization tools within a petrochemical planning tool formulated as a mixed integer linear programming model. Such a tool is particularly useful when the decision-making task must be discussed and approved by officials who often have little experience with optimization theories

Моніторинг довкілля

1. Monitoring dovkillya: Моніторинг довкілля: підручник / В. М. Боголюбов, М. О. Клименко, В. Б. Мокін [та ін.]; за ред. проф. В. М. Боголюбова. Вид. 2-ге, переробл. і доповн. Київ: НУБіПУ, 2018. 435 с. 2. Navchalnyj posibnyk dlya vyvchennya dystsypliny “Monitoring dovkillya”: навч. посібник для вивчення дисципліни «Моніторинг довкілля» для студентів напряму підготовки 6.040106 «Екологія, охорона навколишнього середовища та збалансоване природокористування» освітньокваліфікаційного рівня «Бакалавр». Полтава: ПолтНТУ, 2016. 117 с. 3. Положення про деякі питання здійснення державного моніторингу в галузі охорони атмосферного повітря. Постанова Кабінету Міністрів України від 14.08.2019 р. № 827. 4. Законодавство України / [Електронний ресурс]. – Режим доступу https://zakon.rada.gov.ua/laws/show/960-2020-%D0%BF#Text 5. Міністерство захисту довкілля та природних ресурсів України / [Електронний ресурс]. – Режим доступу: https://mepr.gov.ua/ 6. International journal on environmental monitoring and analysis. [Електронний ресурс]. – Режим доступу: http://journalseeker.researchbib.com/view/issn/2328-7667The course “Environmental Monitoring” introduces students to the basics of monitoring of environmental components through lectures, laboratory exercises, and self-study. Topics ranging from the concept and general ideas about the system, hierarchical levels and regulatory support for environmental monitoring to quality control of the environmental components are explored. It is intended for students specializing in Ecology and Environmental Protection doing their courses in English.Курс «Моніторинг довкілля» знайомить студентів з основами екологічного моніторингу за допомогою лекцій, лабораторних вправ та самостійного вивчення. Досліджуються теми від загальних уявлень про систему, ієрархічні рівні та нормативно-правове забезпечення здійснення моніторингу довкілля до контролю якості компонентів навколишнього середовища. Для студентів вищих навчальних закладів, що навчаються англійською мовою за освітньо-професійною програмою «Екологія та охорона навколишнього середовища»

Improved Source-Reconstruction Through the Exploitation of Dose-Response Models

The emergency actions following an accidental or intentional release of a hazardous material (HazMat) are strongly influenced by what is known of the HazMat event and its evolution (e.g. mass flowrate of the release, location of the release, and the duration of the release). Thus, the availability of such information in a timely and accurate manner is of great importance for emergency crews both on-site and in the areas in the proximity of the site. This information aids in predicting the fate of the release and mitigating the possible threats imposed by it on human health. Characterizing the source of an atmospheric contaminant is typically regarded as an inverse problem, where one has to infer the source characteristics of the released HazMat from concentration or deposition measurements. The inverse solution is obtained by combining atmospheric dispersion models and concentration measurements in an optimal way, where dispersion models are used to produce concentration predictions in space and time using as input initial guesses of the source information. Furthermore, estimating the source parameters needed for atmospheric transport and dispersion modeling requires the application of deterministic and stochastic inversion techniques, such as the Bayesian frames employing Monte Carlo methods. Locating the source and determining its release rate based on downwind concentration measurements, however, is only viable for some cases like industrial accidents, where measurement data from monitoring stations are typically obtained on-site. For other release cases, such as transport accidents or malevolent attacks, there is a lack of input data (i.e. immediate concentration measurements). Hence, there is a necessity to develop new approaches for real cases where this information is probably not available to the required extent or at all. This work presents the development, application and assessment of computational algorithms used in reconstructing the source characteristics following an accidental release of an airborne hazard. A promising methodology is the utilization of the resulting health symptoms from exposure as indirect input for emergency response systems. In this work, a total of six scenarios were constructed and analyzed in terms of their ability to reconstruct the source rate in addition to the source location. The results revealed that the source term information can be identified with good agreement with the true source parameters when using the new scheme. However, the complexity of the information used as input was reflected on the minimum requirement of input data needed to reconstruct the source term. The results also revealed the necessity to explore other sophisticated sampling and inversion techniques