Radiation dose rates and exposure associated to Technologically Enhanced Naturally Occurring Radioactive Materials (TENORM) at locations of a Portuguese coal-fired power plant

Coal contains trace quantities of natural radionuclides such as Th-232, U-235, U-238, as well as their radioactive decay products and 40K. These radionuclides can be released as fly ash in atmospheric emissions from coal-fired power plants, dispersed into the environment and deposited on the surrounding top soils. Therefore, the natural radiation background level is enhanced and consequently increase the total dose for the nearby population. A radiation monitoring programme was used to assess the external dose contribution to the natural radiation background, potentially resulting from the dispersion of coal ash in past atmospheric emissions. Radiation measurements were carried out by gamma spectrometry in the vicinity of a Portuguese coal-fired power plant. The radiation monitoring was achieved both on and off site, being the boundary delimited by a 20 km circle centered in the stacks of the coal plant. The measured radionuclides concentrations for the uranium and thorium series ranged from 7.7 to 41.3 Bq/kg for Ra-226 and from 4.7 to 71.6 Bq/kg for Th-232, while K-40 concentrations ranged from 62.3 to 795.1 Bq/kg. The highest values were registered near the power plant and at distances between 6 and 20 km from the stacks, mainly in the prevailing wind direction. The absorbed dose rates were calculated for each sampling location: 13.97-84.00 ηGy/h, while measurements from previous studies carried out in 1993 registered values in the range of 16.6-77.6 ηGy/h. The highest values were registered at locations in the prevailing wind direction (NW-SE). This study has been primarily done to assess the radiation dose rates and exposure to the nearby population in the surroundings of a coal-fired power plant. The results suggest an enhancement or at least an influence in the background radiation due to the coal plant past activities.

Radiological impact associated to Technologically Enhanced Naturally Occurring Radioactive Materials (TENORM) from coal-fired power plants emissions

Certain materials used and produced in a wide range of non-nuclear industries contain enhanced activity concentrations of natural radionuclides. In particular, electricity production from coal is one of the major sources of increased human exposure to naturally occurring radioactive materials. A methodology was developed to assess the radiological impact due to natural radiation background. The developed research was applied to a specific case study, the Sines coal-fired power plant, located in the southwest coastline of Portugal. Gamma radiation measurements were carried out with two different instruments: a sodium iodide scintillation detector counter (SPP2 NF, Saphymo) and a gamma ray spectrometer with energy discrimination (Falcon 5000, Canberra). Two circular survey areas were defined within 20 km of the power plant. Forty relevant measurements points were established within the sampling area: 15 urban and 25 suburban locations. Additionally, ten more measurements points were defined, mostly at the 20-km area. The registered gamma radiation varies from 20 to 98.33 counts per seconds (c.p.s.) corresponding to an external gamma exposure rate variable between 87.70 and 431.19 nGy/h. The highest values were measured at locations near the power plant and those located in an area within the 6 and 20 km from the stacks. In situ gamma radiation measurements with energy discrimination identified natural emitting nuclides as well as their decay products (Pb-212, Pb-2142, Ra-226, Th-232, Ac-228, Th-234, Pa-234, U- 235, etc.). According to the results, an influence from the stacks emissions has been identified both qualitatively and quantitatively. The developed methodology accomplished the lack of data in what concerns to radiation rate in the vicinity of Sines coal-fired power plant and consequently the resulting exposure to the nearby population.

Measurements of environmental background radiation in the surrounding area of a coal-fired power plant

Certain materials used and produced in a wide range of non-nuclear industries contain enhanced activity concentrations of natural radionuclides. In particular, electricity production from coal is one of the major sources of increased exposure to man from enhanced naturally occurring materials. Over the past decades there has been some discussion about the elevated natural background radiation in the area near coal-fired power plants due to high uranium and thorium content present in coal. This work describes the methodology developed to assess the radiological impact due to natural radiation background increasing levels, potentially originated by a coal-fired power plant’s operation. Gamma radiation measurements have been done with two different instruments: a scintillometer (SPP2 NF, Saphymo) and a gamma ray spectrometer with energy discrimination (Falcon 5000, Canberra). A total of 40 relevant sampling points were established at locations within 20 km from the power plant: 15 urban and 25 suburban measured stations. The highest values were measured at the sampling points near to the power plant and those located in the area within the 6 and 20 km from the stacks. This may be explained by the presence of a huge coal pile (1.3 million tons) located near the stacks contributing to the dispersion of unburned coal and, on the other hand, the height of the stacks (225 m) which may influence ash’s dispersion up to a distance of 20 km. In situ gamma radiation measurements with energy discrimination identified natural emitting nuclides as well as their decay products (212Pb, 214Pb, 226Ra 232Th, 228Ac, 234Th 234Pa, 235U, etc.). This work has been primarily done to in order to assess the impact of a coal-fired power plant operation on the background radiation level in the surrounding area. According to the results, an increase or at least an influence has been identified both qualitatively and quantitatively.

Assessment of heavy metals in the surroundings of coal-fired power plant

This paper aims to survey metal concentrations in soils in the vicinity of a coal-firedpower plant located in southwest of Portugal. Two annual sampling campaigns were carried out to measure a hypothetical soil contamination around the coal plant. The sampling area was divided into two subareas, both centered in the emission source, delimited by two concentric circles with radius of 6 km and 20 km. About 40 samplings points were defined in the influence area. Metals measurements were performed with a portable analytical X-ray dispersive energy fluorescence spectrometer identifying about 20 different elements in each sampling point. The most relevant elements measured included As, Cu, Fe, Hg, Pb, Ti and Zn in both sampling areas. Considering the results obtained in the first sampling campaign, arsenic is predominantly higher within the 6-20 km sampling area. The second sampling campaign showed that both sampling areas presented relatively similar metal concentrations except for Fe, Mn, Sr and Zn which concentration is higher within the 6-20 km sampling area. Also, As, Fe, Mn and Ti concentrations decreased significantly from the first to the second sampling campaign and their concentration were predominately higher in the NE-E and E-SE directions.

Particulate matter flux deposition in the vicinity of a coal-fired power plant

This paper describes the methodology adopted to assess local air quality impact in the vicinity of a coal power plant located in the south of Portugal. Two sampling areas were selected to assess the deposition flux of dust fallout and its potential spatial heterogeneity. The sampling area was divided into two subareas: the inner, with higher sampling density and urban and suburban characteristics, inside a 6-km circle centered on the stacks, and an outer subarea, mainly rural, with lower sampling density within a radius of 20 km. Particulate matter deposition was studied in the vicinity of the coal fired power plant during three seasonal sampling campaigns. For the first one, the average annual flux of dust fallout was 22.51 g/(m2 yr), ranging from 4.20 to 65.94 g/(m2 yr); for the second one was 9.47 g/(m2 yr), ranging from 0.78 to 32.72 g/(m2 yr) and for the last one was 38.42 g/(m2 yr), ranging from 1.41 to 117.48 g/(m2 yr). The fallout during the second campaign turned out to be much lower than for others. This was in part due to meteorological local patterns but mostly due to the fact that the power plant was not working at full power during the second sampling campaign.155

Fast mobility support in low-power wireless networks: smart-HOP over RPL/6LoWPAN

With the emergence of low-power wireless hardware new ways of communication were needed. In order to standardize the communication between these low powered devices the Internet Engineering Task Force (IETF) released the 6LoWPAN stand- ard that acts as an additional layer for making the IPv6 link layer suitable for the lower-power and lossy networks. In the same way, IPv6 Routing Protocol for Low- Power and Lossy Networks (RPL) has been proposed by the IETF Routing Over Low power and Lossy networks (ROLL) Working Group as a standard routing protocol for IPv6 routing in low-power wireless sensor networks. The research performed in this thesis uses these technologies to implement a mobility process. Mobility management is a fundamental yet challenging area in low-power wireless networks. There are applications that require mobile nodes to exchange data with a xed infrastructure with quality-of-service guarantees. A prime example of these applications is the monitoring of patients in real-time. In these scenarios, broadcast- ing data to all access points (APs) within range may not be a valid option due to the energy consumption, data storage and complexity requirements. An alternative and e cient option is to allow mobile nodes to perform hand-o s. Hand-o mechanisms have been well studied in cellular and ad-hoc networks. However, low-power wireless networks pose a new set of challenges. On one hand, simpler radios and constrained resources ask for simpler hand-o schemes. On the other hand, the shorter coverage and higher variability of low-power links require a careful tuning of the hand-o parameters. In this work, we tackle the problem of integrating smart-HOP within a standard protocol, speci cally RPL. The simulation results in Cooja indicate that the pro- posed scheme minimizes the hand-o delay and the total network overhead. The standard RPL protocol is simply unable to provide a reliable mobility support sim- ilar to other COTS technologies. Instead, they support joining and leaving of nodes, with very low responsiveness in the existence of physical mobility.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Double power laws, fractals and self-similarity

Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.

Nanoparticles based Permeable Reactive Barriers as an Eco-efficient Technology for nitrate remediation in soil and groundwater

The need to increase agricultural yield led, among others, to an increase in the consumption of nitrogen based fertilizers. As a consequence, there are excessive concentrations of nitrates, the most abundant of the reactive nitrogen (Nr) species, in several areas of the world. The demographic changes and projected population growth for the next decades, and the economic shifts which are already shaping the near future are powerful drivers for a further intensification in the use of fertilizers, with a predicted increase of the nitrogen loads in soils. Nitrate easily diffuses in the subsurface environments, portraying high mobility in soils. Moreover, the presence of high nitrate loads in water has the potential to cause an array of health dysfunctions, such as methemoglobinemia and several cancers. Permeable Reactive Barriers (PRB) placed strategically relatively to the nitrate source constitute an effective technology to tackle nitrate pollution. Ergo, PRB avoid various adverse impacts resulting from the displacement of reactive nitrogen downstream along water bodies. A four stages literature review was carried out in 34 databases. Initially, a set of pertinent key words were identified to perform the initial databases searches. Then, the synonyms of those initial key words were used to carry out a second set of databases searches. The third stage comprised the identification of other additional relevant terms from the research papers identified in the previous two stages. Again, databases searches were performed with this third set of key words. The final step consisted of the identification of relevant papers from the bibliography of the relevant papers identified in the previous three stages of the literature review process. The set of papers identified as relevant for in-depth analysis were assessed considering a set of relevant characterization variables.

Permeable Reactive Barriers using nanoparticles to remediate nitrate pollution

Nitrat e (NO3 - ) i s per vasi ve i n t he bi ospher e[ 1, 2]. Cont emporar y agri cult ural pr acti ces are a mong t he maj or ant hr opogeni c sources of r eacti ve nitrogen speci es, wher e nitrat ei s t he most abundant of t hese [ 2]. Excessi ve a mount s of r eacti ve nitrogen i n soil s and gr oundwat er ar e creati ng si gnifi cant t hr eat s t o hu man healt h and saf et y [ 3] as well as a host of undesirabl e environment al i mpact s [ 2]; it i s curr ently consi der ed t he second most r el evant environment al i ssue, aft er car bon di oxide e mi ssi ons. Nowadays, a mong t he most r el evant and pr omi si ng appr oaches t o r educe nitrat e concentrati on i n wat er, na mel y gr oundwat er, ar e denitrifi cati on- based pr ocesses [ 4]. Per meabl e r eacti ve barri ers ( PRB) have been pr oven eff ecti ve i n r educi ng vari ous cont ami nant s i n copi ous a mount s, parti cul arl y i n shall ow gr oundwat er [ 5]. However t he possi bl e added eff ecti veness of usi ng nanoparti cl es i n t hese structur es t o obt ai n nitrogen gas from nitrat es requires f urt her i nvesti gati on.

Modelling the Contribution of 40K, 232Th and 226Ra to Radiation Dose and Risk from Airborne Discharges of Coal-Fired Power Plants

Coal contains trace elements and naturally occurring radionuclides such as 40K, 232Th, 238U. When coal is burned, minerals, including most of the radionuclides, do not burn and concentrate in the ash several times in comparison with their content in coal. Usually, a small fraction of the fly ash produced (2-5%) is released into the atmosphere. The activities released depend on many factors (concentration in coal, ash content and inorganic matter of the coal, combustion temperature, ratio between bottom and fly ash, filtering system). Therefore, marked differences should be expected between the by-products produced and the amount of activity discharged (per unit of energy produced) from different coal-fired power plants. In fact, the effects of these releases on the environment due to ground deposition have been received some attention but the results from these studies are not unanimous and cannot be understood as a generic conclusion for all coal-fired power plants. In this study, the dispersion modelling of natural radionuclides was carried out to assess the impact of continuous atmospheric releases from a selected coal plant. The natural radioactivity of the coal and the fly ash were measured and the dispersion was modelled by a Gaussian plume estimating the activity concentration at different heights up to a distance of 20 km in several wind directions. External and internal doses (inhalation and ingestion) and the resulting risk were calculated for the population living within 20 km from the coal plant. In average, the effective dose is lower than the ICRP’s limit and the risk is lower than the U.S. EPA’s limit. Therefore, in this situation, the considered exposure does not pose any risk. However, when considering the dispersion in the prevailing wind direction, these values are significant due to an increase of 232Th and 226Ra concentrations in 75% and 44%, respectively.

Radioactivity levels of 238U and 232Th decay series and related dose rates in the surroundings of a coal power plant using high resolution g-spectrometry

Gamma radiations measurements were carried out in the vicinity of a coal-fired power plant located in the southwest coastline of Portugal. Two different gamma detectors were used to assess the environmental radiation within a circular area of 20 km centred in the coal plant: a scintillometer (SPP2 NF, Saphymo) and a high purity germanium detector (HPGe, Canberra). Fifty urban and suburban measurements locations were established within the defined area and two measurements campaigns were carried out. The results of the total gamma radiation ranged from 20.83 to 98.33 counts per second (c.p.s.) for both measurement campaigns and outdoor doses rates ranged from 77.65 to 366.51 Gy/h. Natural emitting nuclides from the U-238 and Th-232 decay series were identified as well as the natural emitting nuclide K-40. The radionuclide concentration from the uranium and thorium series determined by gamma spectrometry ranged from 0.93 to 73.68 Bq/kg, while for K-40 the concentration ranged from 84.14 to 904.38 Bq/kg. The obtained results were used primarily to define the variability in measured environmental radiation and to determine the coal plant’s influence in the measured radiation levels. The highest values were measured at two locations near the power plant and at locations between the distance of 6 and 20 km away from the stacks, mainly in the prevailing wind direction. The results showed an increase or at least an influence from the coal-fired plant operations, both qualitatively and quantitatively.

Dispersion Modelling of Natural Radionuclides 238U, 232Th and 40K Released from Coal-fired Power Plants Operations

The aim of this work was to simulate the radionuclides dispersion in the surrounding area of a coal-fired power plant, operational during the last 25 years. The dispersion of natural radionuclides (236Ra, 232Th and 40K) was simulated by a Gaussian plume dispersion model with three different stability classes estimating the radionuclides concentration at ground level. Measurements of the environmen-tal activity concentrations were carried out by γ-spectrometry and compared with results from the air dispersion and deposition model which showed that the stabil-ity class D causes the dispersion to longer distances up to 20 km from the stacks.

Dynamic programming for a Markov-switching jump–diffusion

We consider an optimal control problem with a deterministic finite horizon and state variable dynamics given by a Markov-switching jump–diffusion stochastic differential equation. Our main results extend the dynamic programming technique to this larger family of stochastic optimal control problems. More specifically, we provide a detailed proof of Bellman’s optimality principle (or dynamic programming principle) and obtain the corresponding Hamilton–Jacobi–Belman equation, which turns out to be a partial integro-differential equation due to the extra terms arising from the Lévy process and the Markov process. As an application of our results, we study a finite horizon consumption– investment problem for a jump–diffusion financial market consisting of one risk-free asset and one risky asset whose coefficients are assumed to depend on the state of a continuous time finite state Markov process. We provide a detailed study of the optimal strategies for this problem, for the economically relevant families of power utilities and logarithmic utilities.