Input data sources for water resources availability assessment
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",isbn:"978-1-80355-607-9",printIsbn:"978-1-80355-606-2",pdfIsbn:"978-1-80355-608-6",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"6cf0b844f6881c758c61cca10dc8b134",bookSignature:"Associate Prof. Gülşen Akın Evingür and Dr. Önder Pekcan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11830.jpg",keywords:"Elasticity, Toughness, Modulus, Compression, Extension, Optical Properties, Swelling, Drying, Diffusion, Release, Transmission Loss, Sound Absorption Coefficient",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 5th 2022",dateEndSecondStepPublish:"June 15th 2022",dateEndThirdStepPublish:"August 14th 2022",dateEndFourthStepPublish:"November 2nd 2022",dateEndFifthStepPublish:"January 1st 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"21 days",secondStepPassed:!1,areRegistrationsClosed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Evingür is a researcher in polymer composites and a lecturer at a maritime university. She has edited 2 books and has had 5 chapters published in international books, and 3 international and 5 national projects, respectively.",coeditorOneBiosketch:"Prof. Pekcan received their Ph.D. from the University of Wyoming, United States of America, in 1974. He has more than 362 SCI articles, 26 chapters, and 10 projects and is a member Science Academy in Turkey.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"180256",title:"Associate Prof.",name:"Gülşen",middleName:null,surname:"Akın Evingür",slug:"gulsen-akin-evingur",fullName:"Gülşen Akın Evingür",profilePictureURL:"https://mts.intechopen.com/storage/users/180256/images/system/180256.jpeg",biography:"Gülşen Akın Evingür graduated from Physics Department at the Yıldız Technical University (YTU, İstanbul, Turkey) in 1996. She completed her Master of Science degree in 2002 at the same department. The titled of her thesis was 'Electrical Properties of Polystyrene”. She received her PhD from Physics Engineering at İstanbul Technical University in 2011. The title of the thesis was 'Phase Transitions in Composite Gels”. She worked as an Assistant Professor between 2011 and 2018, and she is currently working as an Assosciate Professor at Pîrî Reis University, Istanbul, Turkey. She has been engaged in various academic studies in the fields of composites and their mechanical, optical, electrical, and acoustic properties. She has authored more than 60 SCI articles, 92 proceedings in national and international journals, respectively. She has edited \n 2 book, and has had 5 chapters published in international books, 3 international and 5 national projects, respectively.",institutionString:"Piri Reis University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Piri Reis University",institutionURL:null,country:{name:"Turkey"}}}],coeditorOne:{id:"27949",title:"Dr.",name:"Önder",middleName:null,surname:"Pekcan",slug:"onder-pekcan",fullName:"Önder Pekcan",profilePictureURL:"https://mts.intechopen.com/storage/users/27949/images/system/27949.jpeg",biography:"Prof. Pekcan received his MS Degree in Physics at the University of Chicago in June 1971, and then in May 1974 his PhD thesis on solid state physics was accepted at the University of Wyoming. \n\nHe started his career at Hacettepe University, Ankara, Turkey as Assistant Professor in 1974. Habilitation thesis on solid state physics was accepted in 1979. He became Associate Professor at Hacettepe University in 1979. \nHe visited ICTP Trieste, Italy as Visiting Scientist between June and August 1980. Between 1980 and 1981 he was a Visiting Scientist at the Technical University of Gdansk, Poland. \nHe worked as Visiting Professor at the Department of Chemistry, University of Toronto, Canada between 1981 and 1988. \nHe was appointed as full Professor at the Department of Physics, Istanbul Technical University, Turkey and worked there between 1988 and 2005. \nHe became an Elected Member of the Turkish Academy of Sciences (TÜBA) in January 1995. \nHe became the Dean of School of Arts and Sciences at the Istanbul Technical University in 1997. \nHe received the Science Award from the Scientific and Technological Research Council of Turkey (TÜBİTAK) in 1998. Prof. Pekcan was elected as Member of the Council of TÜBA in 2001 and Scientific Board of TÜBİTAK in 2003, respectively. \nHe was Head of the Department of Physics, and then became Dean of School of Arts and Sciences at the Işık University between 2005 and 2008.\nHe worked as Dean at the School of Art and Sciences, Kadir Has University (2008—2012). \nNow he is Professor at the Department of Bioinformatics and Genetics, Kadir Has University. Since 2012 he is a member of Science Academy. In the last few years Prof. Pekcan’s work covers mostly the area of biopolymers and nanocomposites.",institutionString:"Kadir Has University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Kadir Has University",institutionURL:null,country:{name:"Turkey"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"14",title:"Materials Science",slug:"materials-science"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"185543",firstName:"Maja",lastName:"Bozicevic",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/185543/images/4748_n.jpeg",email:"maja.b@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Churchill, Maja Dutour Sikirić, Božana Čolović and Helga Füredi Milhofer",coverURL:"https://cdn.intechopen.com/books/images_new/8812.jpg",editedByType:"Edited by",editors:[{id:"219335",title:"Dr.",name:"David",surname:"Churchill",slug:"david-churchill",fullName:"David Churchill"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6851",title:"New Uses of Micro and Nanomaterials",subtitle:null,isOpenForSubmission:!1,hash:"49e0ab8961c52c159da40dd3ec039be0",slug:"new-uses-of-micro-and-nanomaterials",bookSignature:"Marcelo Rubén Pagnola, Jairo Useche Vivero and Andres Guillermo Marrugo",coverURL:"https://cdn.intechopen.com/books/images_new/6851.jpg",editedByType:"Edited by",editors:[{id:"112233",title:"Dr.Ing.",name:"Marcelo Rubén",surname:"Pagnola",slug:"marcelo-ruben-pagnola",fullName:"Marcelo Rubén Pagnola"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"43182",title:"Geospatial Analysis of Water Resources for Sustainable Agricultural Water Use in Slovenia",doi:"10.5772/53528",slug:"geospatial-analysis-of-water-resources-for-sustainable-agricultural-water-use-in-slovenia",body:'Global population growth has greatly increased food demand. This, in turn, has intensified agricultural production, already the biggest consumer of water in the world [1]. Development of irrigation techniques has contributed to the global food production [2]. However, climate change simulations predict repeated droughts and deteriorating crop production, illustrating the critical need for sustainable irrigation [3]. Thus, a proactive water management strategy is a priority of any government in the world.
Globally, only 10% of estimated blue water (surface water, groundwater, and surface runoff) and 30% of estimated green water (evapotranspiration, soil water) resources are used for consumption. Nevertheless, water scarcity is a problem due to high variability of water resources availability in time and space [4]. Model results suggest that severe water scarcity occurs at least one month per year in almost one half of the world river basins [5]. One third of the water volume currently supplied to irrigated areas is supplied by locally stored runoff [6]. It is estimated that small reservoirs construction could increase global cereal production in low-yield regions (i.e. Africa, Asia) by approximately 35% [6]. Global water scarcity problems can now be, due to advances in hydrology science in the last decades, easily assessed on fine temporal and spatial scale [4].
Irrigation development and management in Slovenia have completely stagnated in the last decade due to financial shortages. In 1994 the Slovenian government adopted a strategy for agricultural land irrigation (i.e. National Irrigation Programme) [7]. In 1999, the World Bank prepared a feasibility study of this program. However, economic constraints and lack of political will limited the implementation of the program [8].
Slovenia is experiencing periodic droughts of varying intensities in different parts of the country. According to the Court of Audit, the total costs in the agricultural sector due to the droughts in 2000, 2001, 2003 and 2006 were 247 million euro (EUR) [9]. During the same period the government spent 85.9 million EUR for the elimination of the consequences of droughts, and only 3.3 million € on drought prevention measures. This figure is particularly worrisome, because Slovenia is relatively rich in water, with 800-3,000 mm of precipitation per year. With appropriate technical measures, water could be redistributed temporally and spatially, limiting water scarcity and drought effects. Recurring droughts and the results of global and regional climate scenarios [10] predict a tightening of crop production conditions in Slovenia, illustrating the urgent need to address the availability of water resources [11-17].
The Ministry of Agriculture and the Environment has identified the current lack of irrigation infrastructure as a serious obstacle to prevention of agricultural damage and improvement of crop production. Therefore, the Ministry called for two research projects of the Target Research Program, as preparation for the establishment of a new Irrigation Strategy. The first project, Water Perspectives of Slovenia and the Possibility of Water Use in Agriculture (V4-0487) [9, 18], had two objectives, (a) to determine the current water quantity of Slovenian water resources (ground and surface waters, wastewater and sewage treatment plants discharges, existing large reservoirs) potentially available for use, with emphasis on irrigation and (b) to determine the extent to which these water resource meet current irrigation needs.
In 2012 the second project, Projections of Water Quantities for Irrigation in Slovenia (V4-1066) was completed, with the objective to determine to what extent the surface runoff water retained in small water reservoirs along with the rest of the available water, from other water resources, covers irrigation needs. The project also took into account the irrigation norms for different crops, soils, climate zones and climate change scenarios [19]. Analyses of the available water quantities, potential irrigation areas, technical possibilities of construction of small reservoirs, legislation, irrigation norms for crops, climate change impacts were made as part of the agricultural drought risk assessment.
The purpose of this chapter is to present a novel and globally applicable approach for identification of agricultural lands that are at risk for drought. Spatial analysis of available water resources and their quantities for the sustainable irrigation of agricultural land is the key to an efficient integrated water management strategy. Knowing the spatial distribution, accessibility, abundance and availability of water resources is an important element of national security, with regards to the production of sufficient quantities of quality food. Assessing water resources is especially critical in the light of empirical meteorological data and climate model results showing clear changes in the allocation of precipitation and in seasonal patterns.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Surface watercourse | \n\t\t\tRiver network | \n\t\t\tPolyline layer | \n\t\t\tSlovenian Environmental Agency (SEA) | \n\t\t
River flow | \n\t\t\tGeo-referenced tabular data - river flow gauging stations (m3 s-1) | \n\t\t||
Water abstraction | \n\t\t\tGeo-referenced tabular data | \n\t\t||
Available water quantities | \n\t\t\tGeo-referenced tabular data - water available for irrigation and ecologically acceptable flow (m3 s-1) | \n\t\t\tInstitute of Water of the Republic of Slovenia (IWRS) | \n\t\t|
Large water reservoirs | \n\t\t\tReservoirs | \n\t\t\tPolygon layer | \n\t\t\tIWRS | \n\t\t
Reservoir characteristics | \n\t\t\tTabular data - reservoir type, volume, purpose of water use, share of water designated for use in agriculture | \n\t\t\tSlovenian National Committee on Large Dams (SNCLD), SEA | \n\t\t|
Groundwater | \n\t\t\tWater body | \n\t\t\tPolygon layer Hydrogeology, water availability | \n\t\t\tGeological Survey of Slovenia (GSS) | \n\t\t
Borehole | \n\t\t\tDrilling price | \n\t\t||
Water rights | \n\t\t\tGeo-referenced tabular data – water abstraction (m3 s-1) and % of all estimated water in groundwater body | \n\t\t\tSEA, GSS | \n\t\t|
Accumulated surface runoff | \n\t\t\tRunoff | \n\t\t\tRaster layers (mm year-1) | \n\t\t\tSEA | \n\t\t
Mean monthly flow | \n\t\t\tm3 s-1\n\t\t\t | \n\t\t||
Mean monthly specific runoff | \n\t\t\tl s-1 km2\n\t\t\t | \n\t\t\tIWRS | \n\t\t|
Soil data | \n\t\t\tPolygon layer Soil properties (texture, horizons, bedrock, hydraulic conductivity, soil water capacity, hydrological group) | \n\t\t\tUniversity of Ljubljana - Biotechnical Faculty (UL-BF) \n\t\t\t | \n\t\t|
Curve number | \n\t\t\tShare of precipitation as surface runoff defined by land use and soil hydrological group, slope | \n\t\t||
Surface runoff yield and abundance | \n\t\t\tQuantity of water in millimetres and m3 ha-1\n\t\t\t | \n\t\t\tIWRS UL-BF | \n\t\t|
DEM | \n\t\t\tRaster layer - Digital elevation model - 25m | \n\t\t\tThe Surveying and Mapping Authority of the Republic of Slovenia (SMARS) | \n\t\t|
Irrigation | \n\t\t\tIrrigation area | \n\t\t\tPolygon layer | \n\t\t\tUL-BF | \n\t\t
Irrigation norm | \n\t\t\tGross irrigation norm in millimetres, litres or m3 of water per hectare for defined crop and soils in one year for optimal growing conditions | \n\t\t\tIWRS, UL-BF | \n\t\t|
\n\t\t\t | Hydro-module | \n\t\t\tQualities of water used in litres per second per hectare of crop in one irrigation cycle | \n\t\t\tUL-BF | \n\t\t
\n\t\t\t | Irrigation systems | \n\t\t\tPolygon layer Total area and actually irrigated land | \n\t\t\tStatistical Office of Slovenia (SOS) | \n\t\t
Land use \n\t\t\t | \n\t\t\tGraphical Units of Agricultural Land - GERK | \n\t\t\tPolygon layer Land cover classification and spatial representation | \n\t\t\tMinistry of Agriculture and the Environment of the Republic of Slovenia (MAERS) | \n\t\t
Input data sources for water resources availability assessment
Table 1 provides an overview of the data used for spatial analysis (data type, name, source - location, description). If certain type of map was not available we created maps from tabular data provided from different sources. This type of spatial analysis requires a wide range of data starting with land use classes and soil types and their position in space as these have primary impact on surface runoff, percolation of water to groundwater and on soil water content.
Input data also includes river network, river flow, water abstraction and available water quantities for irrigation and ecologically acceptable flow to represent surface watercourses. Additional inputs include data on reservoir characteristics for spatial representation of large water reservoirs. Groundwater data includes hydrogeology and water availability layers, borehole drilling prices and water rights. The widest range of data was needed to spatially represent accumulated surface runoff. We included in the analysis runoff, mean monthly flow, mean monthly specific runoff, soil data, curve number and irrigation areas and norms which resulted in surface runoff yield and water abundance calculations. Geographic Information System ArcGIS software version 9.3 was used for all spatial analyses. Due to the characteristics of the spatial analysis with the raster layers (raster cells) we used extension build in the ArcGIS program toolbox called Spatial Analyst Tool.
The case study area is the Republic of Slovenia (2,020,318 ha), situated in central Europe between Italy, Austria, Hungary and Croatia. A land use analysis showed that agricultural land potentially suitable for irrigation covers 221,355 ha or 10.3 % (Figure 1, Table 2) of the country.
Based on a land use map, the following agricultural land use classes [20] were identified as suitable for irrigation:
fields and gardens, hops plantations, permanent crops on fields, greenhouses, nurseries, intensive orchards, extensive orchards, other permanent crops,
olive groves,
plantations of forest trees, uncultivated agricultural land.
Fields and gardens are the most suitable areas for irrigation, especially when crop production is being intensified. Irrigation in areas planted with hops, permanent crops on fields (asparagus, artichokes, rhubarb, etc.), intensive orchards (apple trees, pear trees, etc.), nurseries (fruit trees, vines, olive trees, etc.,) and in greenhouses, is particularly critical for sustainable crop production. Extensive orchards are potential areas where new intensive fruit plantations could be planted or old extensive orchards renewed, both could be irrigated to secure more reliable yield. Olive groves are not generally irrigated in Slovenia. An experimental irrigation system was installed within the project: Adapting technology of production to climatic conditions for achieving high quality yield of olives and olive oil (V4-0557). There are several reasons for the absence of olive grove irrigation in Slovenia: relatively high annual precipitation, grower’s belief in the relatively low sensitivity of olives trees to drought, lack of reliable water sources, and the terrain, which makes installation of irrigation equipment expensive. Plantations of forest trees with fast growing species like poplar are usually situated on agricultural land. The reasons for growing forest trees on agricultural land are different (paper industry, hydro-meliorations, land reclamations, ameliorations). However, after harvesting these areas could be allocated for agricultural production. Their suitability is even greater because these areas are usually near water resources. Uncultivated agricultural land is usually excluded from production, due to different types of construction sites, only for a certain time period. After completion of works these areas in the majority of cases return back to agricultural production.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t||
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t|
Fields and gardens | \n\t\t\t182,146.76 | \n\t\t\t82.29 | \n\t\t\t8.98 | \n\t\t
Hops | \n\t\t\t1,977.91 | \n\t\t\t0.89 | \n\t\t\t0.10 | \n\t\t
Permanent crops on fields | \n\t\t\t335.95 | \n\t\t\t0.15 | \n\t\t\t0.02 | \n\t\t
Greenhouses | \n\t\t\t130.01 | \n\t\t\t0.06 | \n\t\t\t0.01 | \n\t\t
Nurseries | \n\t\t\t47.84 | \n\t\t\t0.02 | \n\t\t\t0.00 | \n\t\t
Intensive orchards | \n\t\t\t4,385.30 | \n\t\t\t1.98 | \n\t\t\t0.22 | \n\t\t
Extensive orchards | \n\t\t\t23,929.25 | \n\t\t\t10.81 | \n\t\t\t1.18 | \n\t\t
Olive groves | \n\t\t\t1,810.83 | \n\t\t\t0.82 | \n\t\t\t0.09 | \n\t\t
Other permanent crops | \n\t\t\t416.53 | \n\t\t\t0.19 | \n\t\t\t0.02 | \n\t\t
Plantations of forest trees | \n\t\t\t271.39 | \n\t\t\t0.12 | \n\t\t\t0.01 | \n\t\t
Uncultivated agricultural land | \n\t\t\t5,903.37 | \n\t\t\t2.67 | \n\t\t\t0.29 | \n\t\t
Total | \n\t\t\t221,355.15 | \n\t\t\t100.00 | \n\t\t\t10.92 | \n\t\t
Agricultural land potentially suitable for irrigation in Slovenia
Geographic location of Slovenia, agricultural land potentially suitable for irrigation and locations of irrigation systems
In Slovenia in 2010, of 8,299 ha was prepared for irrigation and, only 3,851 ha was actually irrigated [21], accounting for less than 4 % and 2 % of total agricultural land potentially suitable for irrigation (221,355 ha), respectively (Table 3).
\n\t\t\t | \n\t\t\t\t | \n\t\t||||||||
\n\t\t\t | \n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Land prepared for irrigation (ha) | \n\t\t\t6,339 | \n\t\t\t5,303 | \n\t\t\t4,727 | \n\t\t\t5,395 | \n\t\t\t7,876 | \n\t\t\t7,732 | \n\t\t\t7,841 | \n\t\t\t7,604 | \n\t\t\t8,299 | \n\t\t
Actually irrigated land (ha) | \n\t\t\t2,741 | \n\t\t\t2,329 | \n\t\t\t1,812 | \n\t\t\t2,837 | \n\t\t\t3,759 | \n\t\t\t3,651 | \n\t\t\t3,732 | \n\t\t\t3,501 | \n\t\t\t3,851 | \n\t\t
Total area (ha) of agricultural land prepared for irrigation and actually irrigated in Slovenia
Water accessibility classes for surface watercourses or water reservoirs were spatially defined and created from the percentage (%) of defined agricultural land use areas suitable for irrigation (Figure 2 and 3). The project on water perspectives (V4-0487) [8, 18] defined the percentage of area that can be directly irrigated from existing water reservoirs. Dry water reservoirs were excluded from the analysis. The analysis was supported with field work (questionnaires) checking the status and operational management of reservoirs and with analysis of regulations on operation and maintenance of reservoirs.
Water accessibility classes for water reservoir in Slovenia
Water accessibility classes for surface watercourses in Slovenia
The project identified eighteen (18) water reservoirs, from which at least part of the accumulated water could be allocated for irrigation of agricultural land. In all of the large water reservoirs impact areas were determined, where water quantities are sufficient for direct irrigation of at least 30 % of the agricultural land potentially suitable for irrigation (Figure 2). It follows that the use of water from certain water reservoirs is quantitatively limited to water available for irrigation of agricultural land.
The percentage (%) of the area that can be directly irrigated from surface watercourses was determined on the basis of the available water quantity for irrigation at the last point downstream of individual surface watercourse water body. The project defined seventy (70) areas suitable for irrigation (Figure 3).
Area determination followed the criteria [18] below:
maintenance of ecologically acceptable flow (Official Gazette RS, No. 97/2009),
water abstraction within each catchment area must not be greater than the available water quantity at the last point downstream of individual catchment area of surface watercourse water body,
total water abstraction within a system of catchment areas must not be greater than the total capacity of a set of catchment areas, which is the same size as the availability of water quantity in the final (outflow) node of the concerned system of catchment areas;
irrigation area of each watercourse is located in the catchment area of the surface watercourse water body (some exceptions);
horizontal distance from the river to the border of agricultural land area potentially suitable for irrigation is not greater than 3 km (some exceptions);
difference in height between the watercourse and agricultural land suitable for irrigation does not exceed 100 m.
Water accessibility points for water reservoirs and watercourses were determined by the extent of agricultural land (ha, %), which may be irrigated with the water assigned for the agricultural use from both sources. It is important that the use of water from a reservoir is quantitatively limited to the water available for agricultural land irrigation, and water from watercourses is limited to ecologically acceptable flows.
Large water reservoirs and surface waters are attributed with 100 points of availability if the water resource supplies sufficient quantities of water for irrigation of all potentially suitable agricultural land for irrigation in the defined area of the water body (Table 4). If water quantities are insufficient (0 to 99%) for irrigation of a whole defined area of water body adequate for irrigation, the water resource is attributed with availability points between 0 and 99.
Water accessibility classes for groundwater were determined based on a hydrogeological map [22] which defines three classes of groundwater availability (hard, medium and easy) which were linked with three classes of average cost for borehole (well) drilling. The areas with easily accessible groundwater and the lowest price for borehole drilling were attributed with 100% availability of water (Table 4). The other two accessibility classes have smaller or higher number of percentages (Figure 4), in proportion to the price of borehole drilling and the accessibility of groundwater.
It is important to note that groundwater is priority reserved for drinking water. A relatively small percentage of groundwater is actually abstracted; with the highest rate (35%) in the Savska kotlina with Ljubljansko barje in central Slovenia. However, the analysis of the officially assigned abstraction rates from granted water rights showed that three groundwater bodies are 100% utilized (Savska kotlina with Ljubljansko barje. Kamniško-Savinjske Alpe in central Slovenia and Vzhodne Slovenske gorice in eastern Slovenia).
Water accessibility classes for groundwater in Slovenia
The average price for borehole drilling in 2010 in an area with easily accessible groundwater (diameter 100 mm, the average rate of flow of 5.5 l s-1, depth 50 m) was estimated to be 11,000 EUR. The average price for borehole drilling in an area with medium accessible groundwater (diameter 100 mm, yield up to 5.5 l s-1, depth of 70 m to 150 m) was estimated to be 15,000 and 30,000 EUR. The average price for borehole drilling in areas with hard accessible groundwater (diameter 100 mm, the average yield of 1 l s-1, at least 200 m depth) was estimated to be 44,300 EUR. Accessibility of groundwater and price of borehole drilling is highly dependent on geology, groundwater levels, aquifer layer thickness and type of aquifer.
\n\t\t\t\t | \n\t\t\t|||||||||
\n\t\t\t\t | \n\t\t|||||||||
\n\t\t\t | unrestricted (irrigation of 100% of area | \n\t\t\t100 | \n\t\t|||||||
\n\t\t\t | restricted (irrigation of 0 to 99% of area) | \n\t\t\t0-99 | \n\t\t|||||||
\n\t\t\t\t | \n\t\t|||||||||
\n\t\t\t | unrestricted (irrigation of 100% of area) | \n\t\t\t100 | \n\t\t|||||||
\n\t\t\t | restricted (irrigation of 0 to 99% of area) | \n\t\t\t0-99 | \n\t\t|||||||
\n\t\t\t\t | \n\t\t|||||||||
\n\t\t\t | easy | \n\t\t\t100 | \n\t\t|||||||
\n\t\t\t | medium | \n\t\t\t50 | \n\t\t|||||||
\n\t\t\t | hard | \n\t\t\t25 | \n\t\t|||||||
\n\t\t\t\t | \n\t\t|||||||||
\n\t\t\t | abundance (m3 ha-1) | \n\t\t\t1 MED | \n\t\t\t2 PAN | \n\t\t\t3 SMED | \n\t\t\t4 SPAN | \n\t\t\t5 CENT | \n\t\t\t6 ALPS | \n\t\t||
\n\t\t\t | > 6000 | \n\t- | \n\t- | \n\t100 | \n\t- | \n\t100 | \n\t100 | \n||
\n\t | 4000-6000 | \n\t75 | \n\t- | \n\t100 | \n\t100 | \n\t100 | \n\t100 | \n||
\n\t | 2000-4000 | \n\t50 | \n\t75 | \n\t75 | \n\t75 | \n\t100 | \n\t100 | \n||
\n\t | 1000-2000 | \n\t25 | \n\t50 | \n\t50 | \n\t50 | \n\t75 | \n\t100 | \n||
\n\t | 500-1000 | \n\t25 | \n\t25 | \n\t25 | \n\t25 | \n\t50 | \n\t100 | \n||
\n\t | < 500 | \n\t25 | \n\t25 | \n\t- | \n\t25 | \n\t- | \n\t- | \n||
\n\t | Relative slope < 6 % | \n\t0 | \n\t0 | \n\t0 | \n\t0 | \n\t0 | \n\t0 | \n||
\n | |||||||||
\n\t\t | \n\t0 | \n
Determination of potential availability of water resources for irrigation based on water direct accessibility from (1) water reservoirs, (2) surface watercourses, (3) groundwater and (4) abundance of surface runoff yield as small water reservoirs
MED – Mediterranean irrigation area; PAN – Pannonian irrigation area; SMED – Sub-Mediterranean irrigation area; SPAN – Sub-Pannonian irrigation area; CENT – Central Slovenian irrigation area; ALPE – Alpine-Dinaric irrigation area
1 irrigation of x% of area identified as suitable for irrigation from large water reservoir and surface watercourses
Areas with easily accessible groundwater and therefore with the lowest price of borehole drilling are attributed with 100 points of availability (Table 4). Medium and hard accessible groundwater areas are attributed with 50 and 25 availability points, respectively. The price of borehole drilling for those two classes is two or four times higher than for easily accessible groundwater.
To create classes of potential abundance of surface runoff for accumulation in small reservoirs, we had to gather information on the maximum irrigation norm for drip irrigation on light soils for several groups of plants per one hectare (vegetables - low norm, vegetables – high norm, strawberries and permanent crops). This was for all irrigation areas and based on the average quantity of water available for irrigation (Table 4 and 5) [6, 23]. The definition was also based on the optimum volume of a small reservoir for the irrigation of one hectare (of accumulated surface runoff) defined by agro-meteorological stations in different irrigation areas for a dry year with a five-year return period (Table 4). Classes of potential winter yield of surface runoff (mm) (1971 - 2000) (Figure 5) were merged with a map of irrigation areas creating classes with assigned attributed points of surface runoff yield abundance [24].
\n\t\t\t | \n\t\t\n\t\t\t | \n\t\t\n\t\t\t | \n\t\t\n\t\t\t | \n\t|||
\n\t\t\t | \n\t\t\n\t\t\t | \n\t\t\n\t\t\t | \n\t||||
1500 | \n\t\t531,8 | \n\t\t968,2 | \n\t\tstrawberries | \n\t\t878 | \n\t\t25 | \n\t|
2000 | \n\t\t692,4 | \n\t\t1307,6 | \n\t\tvegetables – low norm | \n\t\t1292 | \n\t\t50 | \n\t|
4500 | \n\t\t1477,4 | \n\t\t3022,6 | \n\t\tvegetables – high norm | \n\t\t2871 | \n\t\t75 | \n\t|
6000 | \n\t\t1941,2 | \n\t\t4058,8 | \n\t\tpermanent crops | \n\t\t3720 | \n\t\t100 | \n\t|
1500 | \n\t\t219,5 | \n\t\t1280,5 | \n\t\tstrawberries | \n\t\t1125 | \n\t\t25 | \n\t|
2000 | \n\t\t284,2 | \n\t\t1715,8 | \n\t\tvegetables – low norm | \n\t\t1625 | \n\t\t50 | \n\t|
4000 | \n\t\t536,7 | \n\t\t3463,3 | \n\t\tvegetables – high norm | \n\t\t3097 | \n\t\t75 | \n\t|
4500 | \n\t\t598,9 | \n\t\t3901,1 | \n\t\tpermanent crops | \n\t\t3482 | \n\t\t100 | \n\t|
1000 | \n\t\t131,1 | \n\t\t868,9 | \n\t\tstrawberries | \n\t\t588 | \n\t\t25 | \n\t|
1500 | \n\t\t187,3 | \n\t\t1312,7 | \n\t\tvegetables – low norm | \n\t\t1031 | \n\t\t50 | \n\t|
2500 | \n\t\t296,8 | \n\t\t2203,2 | \n\t\tvegetables – high norm | \n\t\t2271 | \n\t\t75 | \n\t|
3000 | \n\t\t350,7 | \n\t\t2649,3 | \n\t\tpermanent crops | \n\t\t2359 | \n\t\t100 | \n\t|
1000 | \n\t\t168,4 | \n\t\t831,6 | \n\t\tstrawberries | \n\t\t951 | \n\t\t25 | \n\t|
1500 | \n\t\t241,0 | \n\t\t1259,0 | \n\t\tvegetables – low norm | \n\t\t1299 | \n\t\t50 | \n\t|
3000 | \n\t\t452,1 | \n\t\t2547,9 | \n\t\tvegetables – high norm | \n\t\t2568 | \n\t\t75 | \n\t|
3500 | \n\t\t521,3 | \n\t\t2978,7 | \n\t\tpermanent crops | \n\t\t3024 | \n\t\t100 | \n\t|
500 | \n\t\t45,0 | \n\t\t455,0 | \n\t\t/ | \n\t\t/ | \n\t\t25 | \n\t|
1000 | \n\t\t80,8 | \n\t\t919,2 | \n\t\tstrawberries vegetables – low norm | \n\t\t552 848 | \n\t\t50 | \n\t|
1500 | \n\t\t115,3 | \n\t\t1384,7 | \n\t\tvegetables – high norm | \n\t\t1697 | \n\t\t75 | \n\t|
2500 | \n\t\t182,3 | \n\t\t2317,7 | \n\t\tpermanent crops | \n\t\t2157 | \n\t\t100 | \n\t
Determination of availability points for accumulated surface runoff water in small water reservoirs based on average available water for irrigation in reservoir and maximal irrigation norm for drip irrigation and light soils
MED – Mediterranean irrigation area; PAN – Pannonian irrigation area; SMED – Sub-Mediterranean irrigation area; SPAN – Sub-Pannonian irrigation area; CENT – Central Slovenian irrigation area; ALPE – Alpine-Dinaric irrigation area
The magnitude of the abundance points was based on the maximum irrigation norm (drip irrigation) for one hectare of permanent crops (orchards) on light soils and its corresponding optimal reservoir volume for irrigation. If there was enough water for the irrigation of this type of crop (orchard, light soils, drip irrigation, maximum irrigation norm) in an irrigation area it was given 100 availability points (Table 4). Each subsequent class was determined by 25 availability points less, as it does not facilitate sufficient quantities of surface runoff water for irrigation of all groups of agricultural plants.
The determination of abundance points in the case of irrigated land for the Mediterranean and central Slovenian irrigation areas was as follows.
For the drip irrigation of one hectare of permanent crop with maximum irrigation norm on light soils (3,720 m3 ha-1 per year) and water balance for a dry year with a five-year return period we need a small reservoir with optimal volume of 6,000 m3 of water (Table 5). This means that in the Mediterranean area, where potential accumulated surface runoff yield is more than 6,000 m3 ha-1, it is possible to irrigate most of the crops. Therefore this abundance class was attributed with 100 availability points (Table 4). If it is possible to accumulate only up to 1000 m³ ha-1 of surface runoff yield in the Mediterranean irrigation area in ‘dry year with five-year return period’, then only a small share of crops can be irrigated. This means that the water quantity is insufficient to meet the water needs of the majority of crops in this area. Irrigation of strawberries in the Mediterranean area requires 1,500 m3 of water. Accordingly, this abundance class was attributed with 25 availability points (Table 4 and 5). In central Slovenia, for the drip irrigation of one hectare of permanent crop with maximum irrigation norm on light soil, 2,157 m3 ha-1 per year of water (dry year with five-year return period) is needed. If we include the water balance of the area, a small reservoir with volume of 2,500 m3 would be needed. This means that in central Slovenia where potentially accumulated surface runoff yield exceeds 2,000 m3 ha, the abundance classes were attributed with 100 availability points (Table 4 and 5).
Potential surface runoff yield (mm) for dry winter period with five year return period in Slovenia
The final product of assembly and reclassification of individual data resulted in a map of abundance classes of potential surface runoff yield for the dry winter period and irrigation norm by irrigation areas (Figure 6). Also excluded from further analysis was data with a relative slope of less than 6%, and undefined areas (urban, rocky, surface waters). These areas were attributed with 0 availability points.
Water abundance classes for potential surface runoff yield for dry winter period in Slovenia
The determination of drought risk classes of agricultural land suitable for irrigation is the sum of the attributed availability points of each individual water resource suitable for irrigation of agricultural land (Table 6). Water resources (large water reservoirs, surface watercourses, groundwater and surface runoff yield) are spatially defined and interrelated (Figures 2 - 6). The analysis was conducted with raster layers whose spatial resolution was 100×100 m (1 ha) for the entire study area.
Drought risk assessment for agricultural land suitable for irrigation is divided into 6 classes (Table 6). Class 1 is attributed with zero points and indicates areas with potential absence of available water resources for irrigation and is defined as an area with \'distinct drought risk\'. Class 6 is attributed with 400 availability points, as all water resources (included in the research) are potentiality available for irrigation and is defined as area with virtually no drought risk if proper measures are undertaken. Intermediate classes between 2 and 5 have one or more restricted water resources and/or one or more of the unlimited water resources suitable for irrigation.
\n\t\t\t | \n\t\t\n\t\t\t | \n\t\t\n\t\t\t | \n\t|
\n\t\t\t | \n\t\t\n\t\t\t | \n\t||
1 | \n\t\tDistinct | \n\t\t0 | \n\t\tNo available water resources | \n\t
2 | \n\t\tVery high | \n\t\t1 - 99 | \n\t\tOnly water resources with limited availability | \n\t
3 | \n\t\tHigh | \n\t\t100 - 199 | \n\t\tOne water resource with unlimited availability and/or more with limited availability | \n\t
4 | \n\t\tMedium | \n\t\t200 - 299 | \n\t\tTwo water resources with unlimited availability and/or more with limited availability | \n\t
5 | \n\t\tLow | \n\t\t300 - 399 | \n\t\tThree water resources with unlimited availability and/or more with limited availability | \n\t
6 | \n\t\tNone | \n\t\t400 | \n\t\tAll water resources with unlimited availability | \n\t
Determination of risk classes of agricultural land suitable for irrigation in case of drought from the sum of availability points of water resources for irrigation
Due to the characteristics of the spatial analysis of the raster layers (raster cells) with the ArcGIS program tool (Spatial Analyst Tools), areas of certain land use classes and total area of agricultural land suitable for irrigation were slightly lower in comparison with the real situation. However, in the results section we primarily operate with shares of areas, describing availability points of water resources and drought risk classes.
Slovenia has unevenly distributed water resources suitable for irrigation as can be seen from the spatial analysis of availability points (Figure 7) in terms of the dry year with five-year return period.
We detected high availability (151-399 points) of water resources for irrigation in river valleys with alluvial soils (rivers Sava, Drava, Mura, Krka and Vipava), where there is, in addition to surface watercourses, also an easily accessible groundwater and in certain areas (river Vipava) large reservoirs (10 % of case study area) (Table 7). In more than 69 % of the case studies water resources for irrigation is rather poorly available (only 100-151 points), which are mostly a combination of groundwater and surface runoff. On more than 17 % of case study areas, available water resources are extremely low (25 - 99 points), with nearly 3 % of area having only low available groundwater (less than 25 points), whose availability for irrigation is in question due to the high costs associated with borehole drilling.
\n\t\t\t | \n\t\t\n\t\t\t | \n\t|
\n\t\t\t | \n\t\t\n\t\t\t | \n\t|
Undefined (urban, rocks, water) | \n\t\t60.896,5 | \n\t\t3,01 | \n\t
0 | \n\t\t0 | \n\t\t0,00 | \n\t
1 - 25 | \n\t\t54.137,5 | \n\t\t2,68 | \n\t
26 - 50 | \n\t\t173.185,7 | \n\t\t8,57 | \n\t
51 - 99 | \n\t\t122.795,3 | \n\t\t6,08 | \n\t
100 - 150 | \n\t\t1.406.312,6 | \n\t\t69,61 | \n\t
151 - 199 | \n\t\t34.017,6 | \n\t\t1,68 | \n\t
200 - 250 | \n\t\t154.698,3 | \n\t\t7,66 | \n\t
251 - 299 | \n\t\t7.758,8 | \n\t\t0,38 | \n\t
300 - 350 | \n\t\t6.401,5 | \n\t\t0,32 | \n\t
351 - 399 | \n\t\t114,3 | \n\t\t0,01 | \n\t
400 | \n\t\t0 | \n\t\t0,00 | \n\t
\n\t\t\t | \n\t\t\n\t\t\t | \n\t\t\n\t\t\t | \n\t
Areas (%, ha) classes of availability of water resources for irrigation based on figure 7 for total area of Slovenia
Points of potential availability of water resources for irrigation (based on
The map of potential availability of water resources for irrigation was further adjusted and classified in accordance to the potential drought risk (Table 6), thus creating a map of agricultural land suitable for irrigation yet exposed to drought risk at the dry year with five year return period (Figure 8).
We conducted a spatial analysis of agricultural land suitable for irrigation in the case study area to define the availability of water resources for irrigation, and to define potential areas of drought risk. We identified areas of agricultural land at none, low, medium, high, very high and distinct drought risk. Analysis of the potential drought risks of agricultural land suitable for irrigation showed that more than 34 % (75,868 ha) of the case study agricultural land suitable for irrigation is located in areas of very high drought risk (1 - 99 points). Nearly 50 % of agricultural land (109,231 ha) is located in areas of high drought risk (100-199 points) and almost 15 % (33,010 ha) in areas of medium drought risk (200 - 299). Low drought risk (300 - 399) is present in only 0.2 % of agricultural land (442 ha) and is therefore negligible at the macro scale. Based on this analysis we argue that areas of medium and low drought risk should not suffer from water scarcity or drought causing damage in crops production and limiting crop yield, if appropriate infrastructure and systems for water transport and irrigation are installed, maintained and used in these areas. Research analysis did not detect any areas of agricultural land use suitable for irrigation at either absolute extremity of drought risk (0 points and 400 points).
Agricultural land potentially suitable for irrigation and exposed to drought risk at dry year with five year return period in Slovenia at 1 ha resolution (100×100 m) (based on
This chapter presents a novel methodological approach and findings which substantially contribute to the understanding of spatial water resources availability and drought risk assessment of agricultural land. The methodology is clear, practical and therefore generally applicable in any region or on a global level. Methodology is open to adding other water resources, not presented here (e.g. waste water), in to the water resources availability assessment.
When the spatial analysis of available water quantities for irrigation from water resources is prepared for a certain area (region, state, catchment), it is essential to cooperate with all organizations engaged in regulating water management (e.g. environmental agencies, water and geological institutes and responsible governmental bodies). Water quantities available for irrigation from different water resources are usually regulated by state legislation defining minimal water quantities in the surface watercourses or reservoirs to sustain ecological acceptable flows, for the survival of the organisms in the water bodies. Legislation should also include consideration of the share of total water quantity in the water body which can be abstracted for irrigation of agricultural land, and the share of the water quantity in the water body at ecological acceptable flow that is especially reserved for agriculture and can be abstracted for irrigational purposes. Water reservoirs usually have, in addition, operational regulations defining the share of water reserved for agriculture, recreational activities, or for the conservation of wildlife habitats. Legislation and regulation are key factors to preventing over exploitation of water resources.
Spatial analysis of potentially needed water quantities for irrigation should be based on land use classes, types of crops and crop management. This is especially important in the case of crops with high water demand. Furthermore, spatial analysis should include physical and hydrological properties of soils in the area. This is important if soils in the area are light, with a high share of sand, high hydraulic conductivity and low available water capacity. Finally, it is crucial to define the irrigation norm (maximum, average and minimum) for all types of soils and crops grown in the area. This kind of analysis has to be done in cooperation with soil hydrologists, plant physiologists, agro-meteorologists and specialist technicians in irrigation systems.
To define accessibility or abundance of water resources in this study, we choose to use availability points as a number from 0 to 100. Water accessibility points for water reservoirs and watercourses were determined by the extent of agricultural land (%), which may be irrigated with the water assigned for agricultural use from both sources (0 to 100 points). Water accessibility classes for groundwater were determined on the basis of the hydrogeological map and average cost for borehole drilling, and put into three classes: hard (25 points), medium (50 points) and easy (100 points), defining the availability of groundwater. The determination of abundance points was based on the maximum irrigation norm (drip irrigation) for one hectare of permanent crops (orchards) on light soils and its corresponding optimal reservoir volume for irrigation. If in irrigation area was enough of water for irrigation of orchard on light soils with drip irrigation and maximum irrigation norm, it was given 100 availability points (Table 4). Each subsequent class was determined by 25 availability points less, as it does not facilitate sufficient quantities of surface runoff water for irrigation of all groups of agricultural plants.
Drought risk classes have to be developed in a careful manner with a clear distinction between classes. A maximum of six classes is recommended, to maintain comprehensibility and transparency for the reader. Aggregation of classes is useful, but must include sufficient information for the reader to understand the data. The scale needs to have extreme classes which represent areas without potentially available water resources for irrigation and areas with all potential water resources fully available.
Practical applications of the geospatial analysis of water resources for sustainable agricultural water use are numerous. The results are important for identifying areas on regional and global level which are best suited for irrigation development in terms of water resources availability. Results are important as they help areas suffering from periodic droughts to draw governmental attention. This is important as these areas require financial investment in irrigation equipment and irrigation technologies. It helps small growers in remote hilly or karst areas to identify reliable water resources. The results define areas suitable for building small water reservoirs for accumulated surface runoff water, which can help small farm businesses with vegetable or fruit production to be water independent in the drought periods. This is especially important for the population and agriculture businesses in dry, temperate and continental climates with high seasonal differences in precipitation and evapotranspiration.
Human activities over time have left a legacy of contaminated soils around the world. The intense exploitation of soil and the inadequate disposal of hazardous wastes by urban expansion, industrial and transport activities, mining, military activities and armed conflicts, and even unsustainable agricultural practices are the main sources of soil pollution. These anthropogenic activities release various chemicals into the environment that are often found to form a complex mixture of numerous contaminants. The different contaminants produce adverse effects on the health of ecosystems and all living beings that inhabit there. Moreover, the frequency and severity of extreme climatic events (droughts, floods, dust storms, and wildfires incidents) caused by climate change exacerbate soil contamination. Anthropogenic activities contribute to changes in the moisture and temperature regimes of soils and groundwater and can increase rates of movement of contaminants
Element | Essential | Natural sources | Anthropogenic sourses | Uses |
---|---|---|---|---|
Arseni | No | Dust storms Volcanic eruptions Geothermal/hydrothermal activity Forest fires Arsenic-rich minerals | Metal mining and smelting. Coal mining and burning of arsenic-rich coals. Pesticide. Timber industry. Pyrotechnics. | Wood preservatives. Additive to veterinarian drugs (poultry). Doping agent in semiconductors. |
Cadmium | No | Zinc and lead minerals. Phosphates rocks. | Electroplating. Metal industry (non-ferrous metals and steel). Automobile exhaust. Phosphate mineral fertilizer. | Pigments in paints, ceramics, plastics, etc. Cd impurities in Zn coatings used on metal structures. |
Chromium | Yes | Chromium minerals | Metal industry Electroplating. Industrial sewage. | Electroplating. Metal alloys. Anticorrosive products. Pesticides, detergents. |
Copper | Yes | Sulfides, oxides, carbonates | Domestic and industrial waste, mining waste, animal manure (pig and poultry). Car breaks. Metal industry. Copper-based fungicides. | Electric supplies, electric conductor. Electroplating. Fungicides. Plant residues treated with fungicides are used as soil amendments. Timber treatment chemicals. Copper piping and guttering. Vehicle brake linings. |
Lead | No | Lead minerals | Battery manufacturing facilities. Private and industrial waste. Rifle ranges and military facilities. Leaded paints and leaded fuel addition. Insecticides. | Batteries. Alloys, bullets and other munitions. |
Mercury | No | Mercury sulfide ores. Volcanoes. Forest fires. Ocean emissions. | Artisanal and small-scale gold mining. Chemical industry. Fossil fuels (coal and petroleum) combustion. Nonferrous metals production. | Catalysts, electrical switches. Batteries, fluorescent lights, felt production, thermometers and barometers. Alloys for dental fillings. Bright-red paint pigments. |
Nickel | Yes | Nickel minerals | Metal works, battery plants, electronics. Industrial waste. | Metal alloys, batteries, electronics. |
Zinc | Yes | Minerals | Battery plants. Metal industry. Phosphate fertilizers. | Batteries. Alloys. Construction anticorrosive planting. Tire rubber. Additives in veterinary drugs and pesticides. |
Natural and anthropic sources of some elements and their industrial use (Source [1]).
The insufficient registration of contaminated areas in many regions of the world and the lack of regulations for their remediation accentuate this environmental conflict. About 3.5 million sites in the European Union (EU) were estimated to be potentially contaminated, with 0.5 million sites being highly contaminated and needing urgent remediation. There are 400,000 polluted sites in European countries, including Germany, England, Denmark, Spain, Italy, Netherlands, and Finland. Sweden, France, Hungary, Slovakia, and Austria count up to 200,000 contaminated sites. Greece and Poland reported 10,000 contaminated land areas, while Ireland and Portugal reported less than 10,000 contaminated sites. In America, approximately 600,000-ha brownfield sites are polluted with heavy metals [2]. Identification and assessment of potentially polluted sites are the essential first step in the management of soil pollution.
Among the persistent and potentially (eco)toxic heavy metal(loids)s (HMs) ubiquitous around polluted soils are arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb), manganese (Mn), nickel (Ni), zinc (Zn), and radionuclides. Many of them are considered trace elements. The concentration of these HMs in soil has increased drastically over the last three decades, thus posing a risk to the environment and human health. A detailed description of the above-mentioned trace elements, including the natural and anthropogenic sources and uses, is given in Table 1. Identifying the sources of trace elements in the environment is of key importance to understanding the pollution patterns and natural global cycles, in addition to making decisions concerning soil pollution remediation.
The remediation methods are generally based on physical, chemical, and biological approaches, which may be used in combination with one another to clean-up HMs to an acceptable and safe level [3, 4, 5]. The physical and chemical conventional methods are usually expensive and can irreversibly affect the properties of soil, water and the living beings that inhabit them [6]. Figure 1 resumes the soil remediation techniques based on chemical, physical, and biological processes developed during the last two decades [4, 7, 8, 9].
Comparison of physical, chemical and biological methods of remediation for polluted soils or contaminated substrate. Physical remediation methods include (1) soil replacement, (2) soil isolation, (3) vitrification, and (4) electrokinetic; biological methods generally include (5) phytovolatilization, (6) phytoextraction and (7) phytostabilization; chemical methods contain (8) immobilization and (9) soil washing. Biological and chemical methods can be applied jointly depending on the type of contaminant, soil, plant and chemical reagent. Moreover, the effectiveness of different phytoremediation techniques can be enhanced by microbial-, chelate- and genetic-assisted remediation. Modified from [
These methods consist of removing or reducing contaminants by physical methods such as dilution, heating, and solidification of contaminated soil. Some of the technologies involve the soil replacement or isolation, the thermal analytical method, vitrification, and the electric repair technique, which does not change the chemical properties of the pollutants.
Phytoremediation technology:
Phytoremediation involves the use of plants to extract and remove chemical pollutants or to decrease their bioavailability in soil [12, 13]. In general, plants used to carry out phytoremediation are known as metallophytes. The main benefits reported for phytoremediation include less secondary waste generation and minimal-associated environmental disturbance
These methods include soil washing and immobilization technologies. Different chemicals or solvents (metallic oxides, clays, or biomaterials) are added into the soils to stabilize the pollutants and convert them into less toxic forms to living organisms, thus reducing their bioavailability, adsorption, or transformation [27]. The remediation chemical methods are faster than biological ones and could also be applied
As it was previously mentioned, the bioavailability and mobility of HMs in soil substrate are greatly influenced by the soil physicochemical properties (pH, Eh, electrical conductivity, cation exchange capacity, and soil mineralogy), the biological conditions, and the presence of soil inorganic and organic ligands. Careful risk assessments should be undertaken to select the appropriate hyperaccumulating plant species and determine safe and acceptable use of the aboveground plant biomass. As this aerial plant biomass gradually accumulates trace elements and other contaminants and its toxicity is likely to increase, it is important to select those hyperaccumulating species that are unlikely to enter the food chain or implement a protection system to avoid this important issue. There are several post-harvest management options for crops including energy generation, biofuel production, gasification, composting, recovery of critical and secondary raw material recovery, and phytomining.
Microbial-assisted phytomining of HMs also represents a promising method for the remediation of contaminated soil [30]. Microbial-assisted phytomining of HMs involves several mechanisms such as biosorption, intracellular accumulation, enzyme-catalyzed transformation, bioleaching and biomineralization, and redox reactions [31]. In many cases, plant-microbe associations are highly efficient in absorbing, accumulating, translocating, and tolerating HMs because of their capacity to produce various substances that participate in stimulating growth and HMs accumulation (monocyclopropane-1-carboxylate deaminase, siderophores, indole acetic acid) [30]. In microbial-assisted phytomining, the exudates of mycorrhizal roots play a significant role in the efficiency of phytoextraction of the elements in the soil. For instance, concentrations of amino acids (glutamine, glutamic acid, valine, and methionine) and organic acids (citric acid, malic acid, and oxalic acid) in the root exudate of
Several authors have reported the operating costs related to different remediation technologies, normalized per unit (m3) of contaminated soil (Table 2).
Applied technology | Cost/ m3contaminated soil | Observations | Source |
---|---|---|---|
Phytoremediation (phytoextraction) | US$ 37,7 | Biological (20 cm soil depth, 2 years), initial capital included in the cost. | [36] |
US$ 50–200 | Biological (density 2 tn/m3) | [37] | |
US$ 10–35 | Biological | [3] | |
Plant extraction | US$ 19–78 | Physical-biological | [38] |
Phytostabilization | US$ 1.3 | Biological | [1] |
Turnover and attenuation | US$ 4.7–5.6 | Physical | [38] |
Extraction | US$ 240–290 | Physico-chemical | [36] |
Solidification | US$ 87–190 | Physico-chemical | [36] |
US$ 480–813 | Physical | [39] | |
US$ 81–252 | Physical | [40] | |
US$ 130–260 | Chemical-Biological | [36] | |
US$ 100 | Biological, initial capital included in the cost | [41] | |
Unlined repositories | US$ 9.52 | Physical | [42] |
Lined repositories | US$ 34.44 | ||
Soil replacement—excavation | US$ 540–920 | Physical ( | [43] |
Excavation and treatment | US$ 145 | Physical-chemical, initial capital included in the cost | [1] |
Vitrification | US$ 600–1000 | Physical, initial capital included in the cost | [37] |
Flushing | US$ 150–420 | Physical | [37] |
US$ 50–150 | Biological | [3] | |
Bioremediation | US$ 50 | Biological | [1] |
Stabilization/solidification | US$ 240–340 | Chemical | [3] |
Soil venting | US$ 20–220 | Chemical | [3] |
Solvent extraction | US$ 360–440 | Chemical | [3] |
Soil washing | US$ 80–200 | Chemical | [3] |
Incineration | US$ 200–1500 | Chemical | [3] |
Phytoextraction+ Chelation | US$ 15 | Chemical-biological | [44] |
Economical costs of some technologies for remediation of contaminated soils.
As Table 2 shows, phytoremediation represents a sustainable and low-cost alternative for the rehabilitation of environments affected by natural and anthropogenic pollutants [45, 46]. The differential costs reported among similar methodologies are concerned with the type of chemical elements and their concentration to be extracted, the technical procedures, the type and amount of soil to be remediated, the area to be treated, and the ideal nontoxic concentration value of pollutants to be achieved, among others. For some instances, only high-costing operations are considered, and it is frequently that a plus initial capital has been added for carrying out remediation.
Based on economic implications, the aim of phytoremediation can be three-layered: (1) phytomining (plant-based extraction of metals with a financial benefit, i.e., in the perspective of critical and secondary raw materials recovery from plant biomass [47]); (2) minimization of the risks of bioaugmentation of contaminants in the food chain, for example, by stabilization of Cd in cocoa plantations (https://www.fontagro.org/new/proyectos/bioproceso-cd/en); and (3) sustainable soil management by steadily increases soil fertility allowing for follow-up cultivation of crops with added economic value [48, 49, 50]. In concordance, the chelate-assisted and microbial-assisted phytoextraction and use of genetically engineered plants can further reduce the cost of remediation by enhancing metal accumulation and decreasing remediation time. Moreover, the operational costs remain the same as for phytoextraction alone. The implementation of phytoremediation as an effective methodology that guarantees the recovery of elements of interest and the rehabilitation of the soil must contemplate, in the long term, a period greater than 4 months for continuous monitoring, to ensure not having negative impacts due to external and internal variables (e.g., climatic variables, man, animals, changes in pH, Eh) that may affect the efficiency of the process [34, 36, 47].
—Constructed wetland systems:
From the remediation conceptual tests at the laboratory corresponding to technology readiness level (TRL) 1–2 to their applications in the territory (TRL 7), a long way of calibration and adjustments must be executed. Generally, a significant economic loss is given by poor evidence of adaptation and adjustment when technology proceeds from TRL 3 to TRL 7 [51].
In the study by Scotti et al. [34], a constructed wetland system called vegetable depuration module (VDM) is proposed as a calibrator of variables in MAP tests (Figure 2A). The use of VDM allows to determining the balance mass and the metal(loid) partition between soil, fungal structures, mycorrhizal roots, and aboveground plant tissues. The VDM allows the leaching of different HMs under particular conditions of pH-Eh, organic matter and other amendments and co-enzymatic factors (among other elements) taking to account the hydraulic variables such as type of irrigation (vertical, horizontal, continuous, interrupted, laminar, or turbulent), dynamics flow, and constant of hydraulic retention (Kh physical constant dependent on filling). Partitioning among different media usually relies on an equilibrium between the contaminant adsorbed on solid surfaces and the contaminant dissolved in a liquid (or gaseous) phases, controlled by the chemical characteristics of the contaminant (e.g., hydrophobicity, volatility). Several distribution coefficients have been developed over the years (e.g., partitioning coefficient between soil and water: Kd, organic carbon and water: Koc, or octanol-water partition coefficient: Kow) to elucidate processes in nature, but these are usually simple models that do not consider the specificity of sorption sites or competition among molecules and elements [1]. Thermodynamic processes that determine the bioavailability of trace elements are complex, and VDM allows to calibrate some of these processes. Once the calibration of these parameters has been obtained, the system can be scaled up to territory by adapting the engineering practices. The description of the VDM [34] shows it as a modified subsurface constructed wetland that allows designing the type and quantity of underground filter, its granulometry, type of substrate, and amendments besides the hydraulic system.
A: The Vegetable Depuration Module (VDM) under construction, B: Vertical flow beds (VFB) under construction in Lima, Peru; C: VFB under construction in Bayawan City, Philippines; D: From left to right: three VFBs (filters) for pre-treatment and two VFBs for secondary treatment in Albondón, Spain (photos by (photos from [
The VDM (located at
The VDM is a technological development adaptable to different designs and methodologies with a scale of TRL 6 as a simulated environment. The output of the VDM calibration corresponds to the first engineering cycle of a design to be taken to field scale. Under the experimental conditions in the VDM, the HMs in multi-contaminated soils with high leaching properties pass to the collecting chamber to be recycled and treated in another VDM with different physical-chemical and biological conditions. Consequently, those HMs translocated to plant biomass are considered bio-extracted and the elements retained in the substrate without entering biomass are considered stabilized. Furthermore, the VDM allows calibration of the capacity of phytoextraction or phytostabilization of a given system under certain conditions. The differential behavior between phytoextraction and phytostabilization is mainly given by the soil conditions and the plant-microorganism association. The mycorrhizal plants can retain HMs in soil substrate by physical-chemical fixation, redox reactions, absorption and adsorption in the extra-radical mycelium and spores, and by releasing glomalin, a complex of glycoproteins that acts as a carbon reservoir in soils and is involved in the sequestration of HMs [53]. Recent studies have demonstrated that AM symbiosis performance can fluctuate between phytostabilization and/or phytoextraction depending on certain HMs, the environmental conditions, and the types of plant and fungal partners [54]. As it is known, the bioavailability of HMs is related to the solubility of these elements, which intimately depends on the temperature, pH, and Eh parameters (Pourbaix) [55], among other factors. The VDM allows modifying the retention capacity in the substrate or the leaching rates of HMs by controlling the pH-Eh values according to the soil-plant-microorganisms system applied.
Recently, different modular constructed wetland systems in series were designed with different numbers of vertical flow bed (VFB). In the system designed in Figure 2B, the entire surface is used as an inlet area to greywater influents through connected pipes with uniform holes that later are covered with gravel to complete the testing performances. In Figure 2C, another example of a VFB is constructed for the treatment of wastewater from a landfill. Figure 2D shows modular constructed wetland systems in series without electricity supply as it is built on a slope. It consists of three VFBs for pre-treatment as a filtration step and two VFBs for secondary treatment.
In Scotti et al. [47], we estimated the calibration for an efficient extraction of CRM and SRM per m3 of mining soil treated in the VDM with the MAP system. Estimated bio-extracting potential (BP) was in the range 2.417 g (K) > BP > 0.14 g (As) per m3 of contaminated soil, suggesting the eventual subsequent recovery of SRMs and CRMs by hydrometallurgical techniques, with final purification by selective electrodeposition, as a viable and cost-effective option. In this work, the costs of a projection to TRL 7 (real environment) of the BP results reached by using the MAP and the VDM were determined. For that, an economic model used by Wan et al. [36] was followed, separating initial capital costs and operating costs. Also, repositories and constructed wetland costs were considered (Table 3). For the operating costs, various models of repositories and constructed wetlands were taken into account depending on the objective to be achieved [34, 52]. The costs of the projection to the territory for the application of MAP using designed models of the VDM are shown in Table 3. The costs of the MAP system were divided into initial capital and operational costs. The initial capital includes the following items: investigation about pollution, selection of remediation strategy, soil preparation, construction of modules repositories, pipes and collector chambers, equipment, temporary store, irrigation system, and incineration equipment. Construction of adequate accesses is required.
Items | Cost (USD)/ha | ||
---|---|---|---|
Strategy selection | 824.8 | ||
Modules, collector chambers, repositories | 5770.3 | ||
Equipment | 5893.6 | ||
Irrigation system | 5986.8 | ||
Possible accesses required | 4548.4 | ||
Incineration equipment | 7216.5 | ||
Others | 3812.4 | ||
Cost of labor | Seedling | 0.082 | |
AM fungal inocula production | 0,390 | ||
Transplant | 0.103 | ||
Fertilize | 0.062 | ||
Insect control | 0.062 | ||
Irrigation and recycled | 0.062 | ||
Weed control | 0.206 | ||
Harvest | 0.093 | ||
Module filling, placement of stones, amendments, chelates, others | 0.329 | ||
Cost of materials | Seedling tray | 0.041 | |
Hyperaccumulator seedlings | 0.082 | ||
Crops seedlings | 1.261 | ||
Farm chemicals | 0.021 | ||
Fertilizer | 7.446 | ||
Stone filter, amendments, chelates, others | 0.461 | ||
Cost for usage of large machines | Harvest machines | 0.148 | |
Incineration machine | 0.161 | ||
Disposal of dangerous wastes | 0.103 | ||
Other direct cost | Production compensation | 0.178 | |
Rent of land | 0.155 | ||
Fuel and power cost | 0.974 | ||
Construction supervision | 0.037 | ||
Environment supervision | 2.006 | ||
Regular monitor | 1.650 | ||
Indirect cost | Staff wage | 0.495 | |
Administrative expenses | 0.412 | ||
Travel expenses | 1.944 | ||
Cost of water and electricity | 1.003 | ||
Others (amortizations, taxes) | 3.782 | ||
17.026 | |||
Costs of projection to the territory for the application of MAP using designed models of the VDM.
Regarding the operational costs, they include the cost of labor and materials, large machines, and other direct or indirect costs. The cost of labor involves seedling, production of AM fungal inocula, transplantation, fertilizer application, insect control, irrigation and recycled, weed control, harvesting, module filling, placement of stones, amendments and chelates, and some other less significant items. The cost of materials includes the purchase of seedling tray, hyperaccumulator seedling production, crop seedlings, farm chemicals, inorganic and organic fertilizer, stones filter, amendments, chelates, and some other less significant items. The cost of using large machines includes rent for machines during harvest, incineration, and disposal of dangerous wastes. The direct cost is the production compensation and rent of land, which are paid to the local farmer; fuel and power cost during the phytoremediation project; construction and environmental supervision, amortization for the initial capital to 10 years. When the land is fiscal (government), the compensation is included in the indirect costs at the level of tax rates. A conversion from ha to m3 was carried out taking into account 0.2 m of soil depth. The total estimated cost of MAP was US$ 40.775 with initial capital and operational costs accounting for 41.76% and 58.24%, respectively. On the other hand, the operational cost in total was US$ 23.75. It is highlighting that the cost for labor is low compared to total operating costs. This could indicate that the system is simple to be managed, and no extreme technical skills are required to handle it.
In Table 4, the commercial value of each chemical element established by the global market was linked to the quantities of each bioextracted element in the VDM corresponding to 1 m3 of treated soil substrate. Although the commercialization value corresponds to the last prize quote, we observed that there are elements (Mn, Fe, P, Rb Sr., Al, Ba, K, S, and K) that are highly remunerative, and their cost of bioextraction is very low (US$ 40.75/m3), disregarding the cost of hydrometallurgy to recover metal with high purity. Therefore, an important aspect in applying bioextraction processes is the appropriate selection of the experimental conditions, the combination of chemical elements, the adding of amendments and enzymatic co-factors, and an efficient mycorrhizal hyperaccumulating plant.
Element | Purity (%) | BP g/VDM (m3) | State | Price USD/g (Market) | Recovery (USD) in VDM (m3) | Source |
---|---|---|---|---|---|---|
Mn | 99.7 | 34.82 | scales | 0.15 | 5.223 | [56] |
Fe | 99.99 | 60.01 | powder 450 μ | 1.19 | 71.4119 | [57] |
Ga | 99.99 | 1.02 | spheres | 30.97 | 31.5894 | [58] |
P | 99.5 | 114.7 | red | 91.72 | 10,520 | [59] |
As | 99.99 | 0.145 | lump | 40.78 | 5.91 | [60] |
Zn | 99.5 | 43.22 | Ingot | 0.023 | 0.99 | [61] |
Ti | 99.95 | 2.2 | Ingot | 0.16 | 0.352 | [62] |
Cr | 99.5 | 0.21 | Ingot | 1.2 | 0.252 | [63] |
Ni | 99.99 | 0.22 | spheres | 0.14 | 0.0308 | [64] |
Cu | 99.99 | 0.55 | tabs | 0.12 | 0.066 | [65] |
Rb | 99.99 | 3.39 | tabs | 421 | 1.427 | [66] |
Sr | 99.8 | 12.14 | dendritic pieces | 9 | 109.26 | [67] |
Al | 99.99 | 23.99 | granules | 1.8 | 43.182 | [68] |
Ba | 99 | 0.65 | lump | 348.4 | 226.46 | [69] |
K | 99.97 | 2,417 | lump | 8.47 | 20471.99 | [70] |
S | 99.8 | 243.9 | powder | 11.29 | 2.754 | [71] |
Ca | 99 | 690 | lump | 29.76 | 20.534 | [72] |
The commercial value of each chemical element established by the global market linked to the quantities of each bioextracted element in the VDM corresponding to 1 m3 of the treated soil substrate.
Sustainable remediation is now covered by the International Organization for Standardization with the ISO standard 18504:2017 “Soil quality – Sustainable remediation” [73]. In the United States of America, the international American Society for Testing and Materials (ASTM) has developed the “Standard Guide for Greener Clean-ups ASTM E2893 - 16e1” [74]. Australia has developed a National Remediation Framework and technical guidance to support its legislation on polluted sites [75]. In this regard, ISO Technical Committee on Soil Quality has developed a valuable catalog of standard methods for the analyses of soil contaminants, as well as the design and implementation of soil sampling from contaminated sites. ISO also includes methods to assess the toxicity of contaminated soils to plants, microorganisms, earthworms, insects, and other biota [56]. However, this extensive catalog is only available on a standard purchase basis, making it difficult to access, especially in developing countries. To facilitate universal access to internationally developed and agreed standards, the Global Soil Partnership works in collaboration with experts from around the world to identify, agree, and make harmonized sampling and analytical procedures available worldwide through the global networks of soil laboratories (GLOSOLAN1, http://www.fao.org/global-soil-partnership/glosolan/en/) and soil information institutions (INSII2, http://www.fao.org/global-soil-partnership/insii/en/).
Phytoextraction is a safe, least destructive, eco-friendly, and cost-efficient remediation technique that allows soil clean-up over a large scale. The cost of phytoremediation of HMs contaminated soils can be minimized by better understanding the mechanisms and processes involved in bioremediation, and the many options at the different remediation steps.
Phytomining is an incipient methodology for both remediation and recovery of chemical elements of interest. The UE in its 4th list [76] declares 20 critical raw materials due to their availability in nature and the increasing demand in the industry. Many of these elements can be recovered in toxicity-tolerant hyperaccumulators plants.
This methodology can be improved by modulating the physical-chemical and biological variables and their dynamism. For instance, amendments, enzymatic co-factors, and chelators could be incorporated by both artificially and naturally ways to set physical-chemical variables. But results about biological exudates are not constant and reproducible because they depend on an elapsed time, nutrients, and microorganisms present in soils.
Variables on phytomining techniques are currently under study, and many of these have not been elucidated yet, leading to failures when the technology is scaled up. To carry out this calibration, we propose the application of the VDM at a TRL 6 scale (1 to 10 m3 of soil) before taking it to the territory (TRL 7). Through the controlled experiences in the VDM, it is possible to obtain information on phytoextraction, phytostabilization, and leaching of the elements under study.
In this sense, to successfully transfer this methodology to territory, we can generalize the knowledge about the partition of a certain chemical element: a) root and aerial biomass (translocation factor), b) root and soil biomass (bioconcentration), and c) solid-liquid matrix phases. These partition compartments are dependent on various physical-chemical and biological factors.
Regarding the economic aspect, phytoremediation is a very convenient option compared to other techniques of remediation used. In turn, the possibility of recovering valuable chemical elements for the global market, this methodology becomes even more convenient.
Finally, the social license for phytoremediation, under recovery of commercially important chemical elements and minimization of wastes in the environment, makes this methodology a good option toward a circular economy.
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\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\n\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\n\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\n\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\n\nPolicy last updated: 2016-06-09
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Mertens, Brian T. Kress, Michael Wiltberger, W. Kent Tobiska, Barbara Grajewski and Xiaojing Xu",authors:[{id:"92275",title:"Dr.",name:"Christopher",middleName:null,surname:"Mertens",slug:"christopher-mertens",fullName:"Christopher Mertens"}]},{id:"32084",doi:"10.5772/33257",title:"Measurement of H2AX Phosphorylation as a Marker of Ionizing Radiation Induced Cell Damage",slug:"measurement-of-h2ax-phosphorylation-as-a-marker-of-ionizing-radiation-induced-cell-damage",totalDownloads:8953,totalCrossrefCites:5,totalDimensionsCites:14,abstract:null,book:{id:"1562",slug:"current-topics-in-ionizing-radiation-research",title:"Current Topics in Ionizing Radiation Research",fullTitle:"Current Topics in Ionizing Radiation Research"},signatures:"Aida Muslimovic, Pegah Johansson and Ola Hammarsten",authors:[{id:"94660",title:"Dr.",name:"Ola",middleName:null,surname:"Hammarsten",slug:"ola-hammarsten",fullName:"Ola Hammarsten"},{id:"106943",title:"Dr.",name:"Aida",middleName:null,surname:"Muslimovic",slug:"aida-muslimovic",fullName:"Aida Muslimovic"},{id:"108167",title:"Dr.",name:"Pegah",middleName:null,surname:"Johansson",slug:"pegah-johansson",fullName:"Pegah Johansson"}]},{id:"62269",doi:"10.5772/intechopen.79227",title:"An Overview of PET Radiopharmaceuticals in Clinical Use: Regulatory, Quality and Pharmacopeia Monographs of the United States and Europe",slug:"an-overview-of-pet-radiopharmaceuticals-in-clinical-use-regulatory-quality-and-pharmacopeia-monograp",totalDownloads:2344,totalCrossrefCites:8,totalDimensionsCites:11,abstract:"Since 1976, more and more PET radiopharmaceuticals have been developed as the clinical introduction of [18F]FDG for various medical applications. However, few of them could be involved in routinely clinical use in hospitals partly because of restrictions in regulatory and facilities. This chapter aims to provide an overview of PET radiopharmaceuticals that are common manufactured (or prepared) in industry (or hospitals) about regulatory and quality aspects, and further summarize pharmacopeia-listed PET radiopharmaceuticals and their clinical usefulness herein. Particularly, PET radiopharmaceuticals listed in latest United States Pharmacopeia (USP) and/or European Pharmacopeia (EP) are included for this chapter. Finally, this chapter would be helpful in the basic understanding of clinical PET radiopharmaceuticals for physicians or technologists.",book:{id:"7373",slug:"nuclear-medicine-physics",title:"Nuclear Medicine Physics",fullTitle:"Nuclear Medicine Physics"},signatures:"Ya-Yao Huang",authors:[{id:"247754",title:"Prof.",name:"Ya-Yao",middleName:null,surname:"Huang",slug:"ya-yao-huang",fullName:"Ya-Yao Huang"}]},{id:"48894",doi:"10.5772/60435",title:"Gamma Radiation as a Recycling Tool for Waste Materials Used in Concrete",slug:"gamma-radiation-as-a-recycling-tool-for-waste-materials-used-in-concrete",totalDownloads:2292,totalCrossrefCites:4,totalDimensionsCites:8,abstract:"Over the course of the last 50 years, a large number of major technological advances have contributed to the development of higher-strength, high-performance materials that provide excellent benefits. Nevertheless, in most cases, after a very short useful life, these products become waste material and contribute to environmental degradation. This situation has created an environmental crisis that has reached global proportions. In efforts to combat this issue and to promote sustainable development and reduce environmental pollution, some investigations have focused on recycling using innovative and clean technologies, such as gamma radiation, as an alternative to conventional mechanical and chemical recycling procedures. In this context, the reuse and recycling of waste materials and the use of gamma radiation are useful tools for improving the mechanical properties of concrete; for example, the compressive strength and modulus of elasticity are improved by the addition of waste particles and application of gamma radiation. In this chapter, we propose the use of gamma radiation as a method for modifying waste materials; for instance, polyethylene terephthalate plastic bottles, automotive tire rubber, and the cellulose in Tetra Pak containers, and their reuse to enhance the properties of concrete.",book:{id:"4604",slug:"evolution-of-ionizing-radiation-research",title:"Evolution of Ionizing Radiation Research",fullTitle:"Evolution of Ionizing Radiation Research"},signatures:"Gonzalo Martínez-Barrera, Liliana Ivette Ávila-Córdoba, Miguel\nMartínez-López, Eduardo Sadot Herrera-Sosa, Enrique Vigueras-\nSantiago, Carlos Eduardo Barrera-Díaz, Fernando Ureña-Nuñez and\nNelly González-Rivas",authors:[{id:"102080",title:"Dr.",name:"Gonzalo",middleName:null,surname:"Martínez-Barrera",slug:"gonzalo-martinez-barrera",fullName:"Gonzalo Martínez-Barrera"},{id:"110214",title:"Dr.",name:"Fernando",middleName:null,surname:"Ureña-Nuñez",slug:"fernando-urena-nunez",fullName:"Fernando Ureña-Nuñez"},{id:"177864",title:"Dr.",name:"Liliana Ivette",middleName:null,surname:"Ávila-Córdoba",slug:"liliana-ivette-avila-cordoba",fullName:"Liliana Ivette Ávila-Córdoba"},{id:"177865",title:"Dr.",name:"Miguel",middleName:null,surname:"Martínez-López",slug:"miguel-martinez-lopez",fullName:"Miguel Martínez-López"},{id:"177866",title:"Dr.",name:"Eduardo",middleName:null,surname:"Sadot Herrera-Sosa",slug:"eduardo-sadot-herrera-sosa",fullName:"Eduardo Sadot Herrera-Sosa"},{id:"177867",title:"Dr.",name:"Enrique",middleName:null,surname:"Vigueras-Santiago",slug:"enrique-vigueras-santiago",fullName:"Enrique Vigueras-Santiago"},{id:"177868",title:"Dr.",name:"Carlos Eduardo",middleName:null,surname:"Barrera-Díaz",slug:"carlos-eduardo-barrera-diaz",fullName:"Carlos Eduardo Barrera-Díaz"},{id:"177869",title:"Dr.",name:"Nelly",middleName:null,surname:"González-Rivas",slug:"nelly-gonzalez-rivas",fullName:"Nelly González-Rivas"}]},{id:"49039",doi:"10.5772/60846",title:"Physical and Radiobiological Evaluation of Radiotherapy Treatment Plan",slug:"physical-and-radiobiological-evaluation-of-radiotherapy-treatment-plan",totalDownloads:4389,totalCrossrefCites:5,totalDimensionsCites:8,abstract:"Radiation treatment planning plays an important role in modern radiation therapy; it could simulate to plan the geometric, radiobiological, and dosimetric aspects of the therapy using radiation transport simulations and optimization. In this chapter, we have reviewed several quantitative methods used for evaluating radiation treatment plans and discussed some important considering points. For the purpose of quantitative plan evaluation, we reviewed dosimetrical indexes like PITV, CI, TCI, HI, MHI, CN, COSI, and QF. Furthermore, radiobiological indexes like Niemierko’s EUD-based TCP and NTCP were included for the purpose of radiobiological outcome modeling. Additionally, we have reviewed dose tolerance for critical organs including RTOG clinical trial results, QUENTEC data, Emami data, and Milano clinical trial results. For the purpose of clinical evaluation of radiation-induced organ toxicity, we have reviewed RTOG and EORTC toxicity criteria. Several programs could help for the easy calculation and analysis of dosimetrical plan indexes and biological results. We have reviewed the recent trend in this field and proposed further clinical use of such programs. Along this line, we have proposed clinically optimized plan comparison protocols and indicated further directions of such studies.",book:{id:"4604",slug:"evolution-of-ionizing-radiation-research",title:"Evolution of Ionizing Radiation Research",fullTitle:"Evolution of Ionizing Radiation Research"},signatures:"Suk Lee, Yuan Jie Cao and Chul Yong Kim",authors:[{id:"96630",title:"Prof.",name:"Suk",middleName:null,surname:"Lee",slug:"suk-lee",fullName:"Suk Lee"},{id:"175104",title:"Prof.",name:"Chul Yong",middleName:null,surname:"Kim",slug:"chul-yong-kim",fullName:"Chul Yong Kim"},{id:"175234",title:"Dr.",name:"Yuan Jie",middleName:null,surname:"Cao",slug:"yuan-jie-cao",fullName:"Yuan Jie Cao"}]}],mostDownloadedChaptersLast30Days:[{id:"48796",title:"Ionizing Radiation Detectors",slug:"ionizing-radiation-detectors",totalDownloads:3890,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"Ionizing radiation has always been present in the natural environment. However, this radiation is not easily detected and since it also possesses high ionizing power and penetration strength, it constitutes a risk to human health when it is found outside of its acceptable limits. The adverse effects of ionizing radiation on human health need to be systematically monitored in order to prevent damage, overexposure, or even death. The detection of the radiation depends on its particular interaction with a sensitive material, and different types of detectors, in different physical states (solid, liquid or gas), are used to measure selective types of ionizing radiation. New materials such as organic semiconductors, for instance, are being targeted for research and as potential candidates for new perspectives on ionizing radiation sensing.",book:{id:"4604",slug:"evolution-of-ionizing-radiation-research",title:"Evolution of Ionizing Radiation Research",fullTitle:"Evolution of Ionizing Radiation Research"},signatures:"Marcia Dutra R. Silva",authors:[{id:"173533",title:"Dr.",name:"Marcia",middleName:"Dutra",surname:"Silva",slug:"marcia-silva",fullName:"Marcia Silva"}]},{id:"73661",title:"Localization Mechanisms of Radiopharmaceuticals",slug:"localization-mechanisms-of-radiopharmaceuticals",totalDownloads:961,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Scintigraphic techniques have opened a new era of developments in the localization of infectious and cancerous foci. Diseases area targeting mechanisms of radiopharmaceuticals encompasses visualization, characterization, and measurement of physiological and biological functioning at targeted sites in addition to measure the area and density of the disease. The accumulation of a radiopharmaceutical at specific organ is based upon numerous processes such as enzymatic interactions, receptor binding site, transport of chemical species and elimination of damaged cells from circulation by a normal metabolic process. PET and SPECT are developing scanning techniques that provides effective diagnostic tool to identify pathophysiology of diseased cells. In this chapter, we are exploring and explaining different mechanisms of radiopharmaceutical localization for imaging and therapeutic processes. The knowledge of these mechanisms will help to develop target based new radiopharmaceuticals using variety of medically used radioisotopes either for imaging or therapy of diseased cells.",book:{id:"7769",slug:"medical-isotopes",title:"Medical Isotopes",fullTitle:"Medical Isotopes"},signatures:"Sana Komal, Sana Nadeem, Zahra Faheem, Arouma Raza, Komal Sarwer, Hijab Umer, Samina Roohi and Syed Ali Raza Naqvi",authors:null},{id:"49039",title:"Physical and Radiobiological Evaluation of Radiotherapy Treatment Plan",slug:"physical-and-radiobiological-evaluation-of-radiotherapy-treatment-plan",totalDownloads:4390,totalCrossrefCites:5,totalDimensionsCites:8,abstract:"Radiation treatment planning plays an important role in modern radiation therapy; it could simulate to plan the geometric, radiobiological, and dosimetric aspects of the therapy using radiation transport simulations and optimization. In this chapter, we have reviewed several quantitative methods used for evaluating radiation treatment plans and discussed some important considering points. For the purpose of quantitative plan evaluation, we reviewed dosimetrical indexes like PITV, CI, TCI, HI, MHI, CN, COSI, and QF. Furthermore, radiobiological indexes like Niemierko’s EUD-based TCP and NTCP were included for the purpose of radiobiological outcome modeling. Additionally, we have reviewed dose tolerance for critical organs including RTOG clinical trial results, QUENTEC data, Emami data, and Milano clinical trial results. For the purpose of clinical evaluation of radiation-induced organ toxicity, we have reviewed RTOG and EORTC toxicity criteria. Several programs could help for the easy calculation and analysis of dosimetrical plan indexes and biological results. We have reviewed the recent trend in this field and proposed further clinical use of such programs. Along this line, we have proposed clinically optimized plan comparison protocols and indicated further directions of such studies.",book:{id:"4604",slug:"evolution-of-ionizing-radiation-research",title:"Evolution of Ionizing Radiation Research",fullTitle:"Evolution of Ionizing Radiation Research"},signatures:"Suk Lee, Yuan Jie Cao and Chul Yong Kim",authors:[{id:"96630",title:"Prof.",name:"Suk",middleName:null,surname:"Lee",slug:"suk-lee",fullName:"Suk Lee"},{id:"175104",title:"Prof.",name:"Chul Yong",middleName:null,surname:"Kim",slug:"chul-yong-kim",fullName:"Chul Yong Kim"},{id:"175234",title:"Dr.",name:"Yuan Jie",middleName:null,surname:"Cao",slug:"yuan-jie-cao",fullName:"Yuan Jie Cao"}]},{id:"70286",title:"Parathyroid Scintigraphy",slug:"parathyroid-scintigraphy",totalDownloads:615,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The visualization of abnormal parathyroid glands is difficult due to their variations in number and localization. Noninvasive parathyroid imaging studies include 99mTc-sestamibi scintigraphy, ultrasonography, computed tomography scanning, magnetic resonance imaging, and positron emission tomography. There is a general consensus that the most sensitive and specific imaging modality, especially when it is combined with single-photon emission CT is the scintigraphy with 99mTc-sestamibi or 99mTc-tetrofosmin. 99mTc-sestamibi scintigraphy significantly increases the role of preoperative scintigraphy in patients with hyperparathyroidism and allows unilateral surgical approach with minimally invasive parathyroidectomy to be used. Generally, three protocols with the use of two radiopharmaceuticals, 99mTc-sestamibi or 99mTc-tetrofosmin, are most widely applied: single-phase dual-isotope subtraction, dual-phase single-isotope and combination of both. Each one of them has specific advantages and disadvantages. While single parathyroid adenomas are localized with greater precision, hyperfunctioning parathyroid hyperplastic cells represent a real challenge to the imaging modalities. Several factors can influence the radionuclide uptake in pathologically changed parathyroid cells, like the size, the level of their functional activity, the quantity of oxyphilic cells, mitochondria, P glycoprotein and other MDR gene products.",book:{id:"7769",slug:"medical-isotopes",title:"Medical Isotopes",fullTitle:"Medical Isotopes"},signatures:"Albena Dimitrova Botushanova and Nikolay Petrov Botushanov",authors:null},{id:"70578",title:"Gallium-68: Radiolabeling of Radiopharmaceuticals for PET Imaging - A Lot to Consider",slug:"gallium-68-radiolabeling-of-radiopharmaceuticals-for-pet-imaging-a-lot-to-consider",totalDownloads:1684,totalCrossrefCites:4,totalDimensionsCites:5,abstract:"Gallium-68 was applied for positron emission tomography (PET) imaging already in the early beginnings of PET imaging. Today, with the introduction of PSMA-targeting tracers (e.g. PSMA-11, PSMA-617, and PSMA-I&T), the number of clinical applications of 68Ga-radiopharmaceuticals for diagnostic imaging has grown considerably. This development was initiated and supported already in the mid-2000s by the commercial availability of 68Ge/68Ga generators designed for clinical usage. This progression was accompanied by the development of several purification methods to generator eluate as well as sophisticated 68Ga-radiopharmaceuticals. Due to the 68Ga-rush, the need for implementation of gallium-68 (depending on production route) and its certain tracers into the pharmacopeia increased. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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