",isbn:"978-1-80356-357-2",printIsbn:"978-1-80356-356-5",pdfIsbn:"978-1-80356-358-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"3aba1eb3600a8c9ff880c628f70b3298",bookSignature:"Ph.D. Delfín Ortega-Sánchez",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11481.jpg",keywords:"Integrated Curriculum, Transdisciplinarity, Integrated Active Learning, Educational Programs, Contemporary Social Problems, Critical Thinking, Creative Thinking, Social Thinking, Agenda 2030, Sustainable Development Goals, Educational Paradigm, Social Reality",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 18th 2022",dateEndSecondStepPublish:"March 18th 2022",dateEndThirdStepPublish:"May 17th 2022",dateEndFourthStepPublish:"August 5th 2022",dateEndFifthStepPublish:"October 4th 2022",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Internationally recognized researcher in the field of historical and social science education. Author of more than 100 publications, awarded three Doctorate degrees and the National End of Degree Award, granted by the Ministry of Education to the best academic records of Bachelor's degrees in Spain. Dr. Ortega-Sánchez has been Vice-Rector for Social Responsibility, Culture, and Sports at the University of Burgos since 2021.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"302925",title:"Ph.D.",name:"Delfín",middleName:null,surname:"Ortega-Sánchez",slug:"delfin-ortega-sanchez",fullName:"Delfín Ortega-Sánchez",profilePictureURL:"https://mts.intechopen.com/storage/users/302925/images/system/302925.jpg",biography:"I hold a PhD in Didactics of Social Sciences from the Autonomous University of Barcelona, a PhD in Educational Sciences from the University of Burgos, and a PhD in History from the University of Extremadura. 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1. Introduction
Leishmaniasis is an infection caused by a parasite from Leishmania genus, which can manifest itself through different forms: cutaneous (with skin ulcers) [1, 2], visceral (hepato and splenomegaly) [3], and diffuse integumentary form (injuries beyond the superficial skin barrier, hitting cartilages and deeper connective tissues) [4]. Leishmaniasis vectors are diptera from Psychodida family, which includes hematophagous from Phlebotomus genus (Old World) and Lutzomuyia genus (New World), with wide distribution in warm and temperate climates [5] (Figure 1).
In the New World, eight Leishmania species are responsible for men diseases: Leishmania braziliensis, Leishmania guyanensis, Leishmania panamensis, Leishmania lainsoni, Leishmania mexicana, Leishmania amazonensis, Leishmania venezuelensis and Leishmania chagasi [7]. Thus, leishmaniasis can be found in four continents, being considered endemic in 88 countries, of which 72 are in development [5].
Different protozoa species are able to live inside sand flies (insect vectors) from Phlebotominae subfamily and vertebrate hosts. This parasite lives between two different types of hosts due to its significant morphological changes. In vertebrate hosts, Leishmania is at amastigote form without flagella and inside the digestive tract of the sand flies, the parasite is flagellated and fusiform, and receives the name of promastigote, as shown in Figure 2.
Figure 1.
Distribution in Old World and New World of cutaneous (left, marked in orange) and visceral (right, marked in purple) leishmaniasis. Affected areas marked according to the World Health Organization [6].
Figure 2.
Leishmania sp (A) promastigote and (B) amastigote (right) forms.
In Figure 3, two important cellular structures used to identify the Leishmania parasites are highlited in the first image - the nucleus, indicated by the letter N and the kinetoplast, indicated by the letter K. These structures are kept in the distinct methacyclogenesis stages. After completing the cycle modifications, Leishmania becomes able to infect mammalian cells.
Figure 3.
Different transition stages between (a) promastigote and (f) amastigote forms of Leishmania braziliensis.
Different forms of leishmaniasis are transmitted through the bite of female sand flies. The transmission cycle begins when, during a bite, the mosquito ingests mammalian blood infected with amastigote forms. Once installed in the digestive tract of the host, Leishmania passes through the process of differentiation, methacyclogenesis, and the new form of the parasite, promastigote, can be inject in mammalian blood again during a bite, thus completing the disease transmission cycle (Figure 4).
Figure 4.
Life cycle of the parasite.
2. Current treatments
In 1912, Vianna [9] observed that the tartar emetic (an antimony compound) was effective in the treatment of American Integumentary Leishmaniasis. Due to toxicity and serious collateral damages associated to the tartar emetic use, i.e. gastrointestinal intolerance and cardiotoxic effects, the trivalent antimonials (Table 1) were replaced by quinquivalent compounds (Table 2). In 1936, Schmidt introduced in medical therapy antimony (V) sodium gluconate, commercially known as Solustibosan® (Bayer) or Pentostam® (Glaxo Wellcome) [10, 11].
Table 1.
Chemical structure of trivalent antimonials used in medical clinic, with their respective chemical and commercial names [5].
Table 2.
Chemical structure of quinquivalent antimonials used in medical clinic [5].
One of the most commonly used drugs is N-methylglucamine antimoniate, which are especially effective in the treatment of cutaneous and visceral leishmaniasis. This drug provokes fast regression of the clinical and hematological manifestations of the disease, as well as the dead of the parasite [5]. However, due to its low dosages and discontinuous treatments, some therapy failures, an increase of the resistant forms of the parasites started to show up [12-14].
The World Health Organization preconizes that antimonials dosages Should not trespass 20 mg/kg/day, and due to its elevated toxicity, the dosage of antimony ingested per day should not be higher than 850 mg [12]. However, the N-methylglucamine antimoniate is rapidly absorbed and about 90% of the antimony ingested is excreted through the kidneys in the firsts 48 hours [15]. Consequently, there is a necessity to administrate high doses of the drug, in continuous regimen, so an elevated dosage of antimony is assured in the tissues, and therefore the treatment efficacy is obtained.
High doses of N-methylglucamine antimoniate generate a various diversity of collateral effects, such as nephritis, gastrointestinal, cardiovascular and respiratory disturbances. In some cases, besides destroying the parasites, some patients are led to death [11]. The antimony can still be detected in the hair of the patients a year after the treatment is finished [16]. The toxicity of antimony can be explained by the fact that there are some evidences describing that a metabolic conversion happens inside the macrophages transforming antimony V (Sb5+) in antimony III (Sb3+) [13] and the antimony III is proved to be more lethal to the Leishmania species [5]. So the hypothesis is that the antimony V works as prodrug, and the conversion to antimony III is what guarantee its efficacy after administration [17], and the antimony III interferes in the β-oxidation process of fat acids of the parasites, as so in the glycolysis, taking the ATP to a low level inside the cell [12]. This way, the antimony III would be responsible for the toxicity of the drug as well as its therapeutic activity [18].
Besides antimonials, other medicines have been used in the treatment of the various forms of leishmaniasis, among them can be found pentamidine, amphotericin B, paromomycin, and miltefosine (Table 3) [5]. Pentamidine is also effective in the trypanosomiasis treatment [19] and this drug is also highly toxic, showing as collateral effects hypoglycemia, hypotension, cardiologic changes, nephrotoxicity and even death [12]. Amphotericin B is an antibiotic produced by Streptomyces nodosus and can produce nephrotoxicity, depleting the potassium and magnesium levels of the organism [20]. Paromomycin is an aminoglycoside antibiotic active against Leishmania species in in vitro and in vivo forms. It is been highly tested in India, where antimonial standard treatments are not effective [5]. Miltefosine is an alkyl phospholipidic anticancer drug and it is in intensive tests also in India. It is showing excellent results and may be the first oral treatment against visceral leishmaniasis [21].
Table 3.
Other chemicals used in leishmaniasis therapy, with their respective chemical and commercial names.
3. Alternative treatments
Association of some drugs used in leishmaniasis treatment within lipid vesicles called liposomes is one of the alternatives used to reduce the undesirable effects. This association increases the efficiency and the concentrations of these drugs in the tissues, reducing drastically their toxicity [22, 23]. The mechanism that could explain the effectiveness of liposomes is that they inhibit oxygen consumption by the parasite membrane [24].
One practical exemple of this association happens with Amphotericin B, a compound used for the treatment of calazar patients that are resistant to pentamidine. Amphotericin B can be toxic because they can associate with human cell cholesterol as they do to the ergosterol in the parasite plasmatic membrane [6]. To reduce this inappropriate recognition, there are some commercial formulations that associate the Amphotericin B to lipids (Ambisome, Abelcet, Amphotec). Besides their effectiveness in reducing this drug toxicity, they are very expensive and their use becomes basically impractical in poor countries [25].
However, there are some studies searching some low-cost methods of producing these drugs. One example is a formulation with a similar lipid composition to Abelcet, but with some different variables, such as conformation and molecular weight, that may influence the drug release and action in the organism [26]. This formulation was found to be much more effective and less toxic than Abelcet and, although it is less efficient than Ambisome, it is also less expensive for use in leishmaniasis treatment.
4. Vaccines against Leishmaniasis
Studies for the achievement of a vaccine for leishmaniasis immunization are accomplished since 1940 [27]. In the firsts vaccination process against this disease, scientists didn’t know that they were dealing with a microbian ill. This vaccine method was based in the injection of the active wound secretion from one patient to another that was not ill.
From this vaccine, other techniques were developed aiming the raise of the prophylactic efficiency and to avoid some troubles caused by the emergence of a wound. Thus, specialized literature reports four types of vaccines against different types of leishmaniasis: the vaccine based on dead parasites, the vaccine based on living but attenuated parasites, the vaccine with antigenic fragments, and the genic vaccine based on DNA [28].
In a few countries, some clinical trials were already performed but none of the vaccines showed a level of efficiency higher than 80%, a fact that makes unfeasible human tests. This lack of security may be associated to the differentiation between Leishmania species [29], and this differentiation hampers the accomplishment of a wide immunization field.
New investments to the manufacture of a vaccine against leishmaniasis depend on an active biomass of these protozoa. This way, when in contact with the target it may generate an immunological response without generating the disease. But nowadays, the methods for obtaining this biomass [30, 31] are very expensive with low profitability, since it generates a very small sample with an inefficient outcome.
5. New treatment proposals
Due to intense collateral effects, lots of people who are infected with leishmaniases refuse treatment, and there is the need to new alternative treatments. One of the new possibilities in study nowadays uses natural rubber (NR) membranes with metallic nanoparticles (MNPs) such as silver and gold (SNPs and GNPs, respectively). NR membranes are used as an active support to the MNPs reduction process using precursor salts to obtain metallic particles, and that means that the NR membrane works as a reducing agent as well as a stabilizer for MNPs.
When a promastigote population of Leishmania braziliensis is in the presence of pure natural rubber membranes, there is a significant increase in the log phase of the cells, constituted by a large number of cells at the division process. In the 27th hour after inoculation, the parasite colony remains stable, without large variations in the population cells. In this phase, called stationary phase, the promastigote cells start morphophysiological transformations known as metacyclogenesis. With the end of the stationary phase, an environmental saturation happens with cell waste and lack of nutrients, resulting in the death of cells, phase known as fall.
This decrease could be explained by the natural dynamics of promastigotes in the culture medium. It is expected that after 150 hours, this decrease in the population number occurs because of nutritional deficit and saturation of the cellular environment with cellular excreta generated during the period of growth log and stationary phase, but the presence of nanoparticles anticipates the drop in the number of the parasites, probably because these metal components stop the absorption of nutrients of the environment through permeases and transplasmalema transport channels.
However, when promastigotes interact with natural rubber membranes impregnated with silver nanoparticles, a stretch of the first metabolic phase is seen, only with a non-significant growth. In figure 5 is possible to see that the decrease in L. braziliensis is proportional to the increase of silver concentrations in the NR membrane.
Silver nanoparticles toxicity is well known, and although death of the promastigotes may occur, it is believed that changes in the physiological maturation process, such as drastic changes in the surface glycoproteins, happen to the microorganism cell. In that way, the NR membranes with silver nanoparticles when put in the protozoa medium is capable of separating the cells without killing the whole population, eliminating only the ones which did not finalized their metacyclogenesis and are highly infective to the hosts (Figure 6). Immature cells that are not able to generate a disease are kept intact, and this process is what generates an important biomass to a future study focus a vaccine against this disease.
Figure 5.
Populational growth of Leishmania braziliensis promastigotes in contact with natural rubber membranes and natural rubber membranes impregnated with silver nanoparticles using in situ reduction.
Figure 6.
Separation Process of Leishmania in contact with NR membranes with silver (Ag) nanoparticles; (a) and (b) NR/Ag membranas in culture medium; (c) Leishmania braziliensis in contact to NR/Ag membranes; (d) Separated protozoa attached to NR/Ag membranes.
Natural rubber membranes containing GNPs (NR/Au) also decrease the population growth rate, showing a lower index of living promastigotes (attached to the membrane surface) depending on the amount of nanoparticles deposited in the membrane surface. Formation and growth of the GNPs within the NR membranes, by reduction of Au3+, was monitored following the Plasmon absorption band. Reducing agents for GNPs formation are likely to be the carboxylic functional groups present in the NR. Nanoparticle, which produces an increase of the intensity of the distinctive plasmon absorption band of GNPs centered at approximately 560 nm, as shown in Figure 7 [33].
Figure 7.
UV-Vis spectroscopy of natural rubber/gold nanoparticles prepared at different gold reduction times, compared to raw natural rubber membrane (preparation of the membrane annealed at 65 °C).
Analyses by scanning electron microscopy (ESEM) were performed for natural rubber membranes with gold nanoparticles, obtained at a reduction time of 30 min (Figure 8). Apparently, there is a homogenous distribution of nanoparticle occupying the entire surface of the membrane, but by amplifying the images, one can observe the formation of many nanoparticles in sites, and among them, nanoparticles dispersed on the surface of the polymeric matrix. In Figure 8 (d) the small spherical nanoparticles can be seen agglomerated over reduction sites, forming aggregates at an exorbitant amount. Nanoparticles sizes were measured and are very similar, with an average of approximately 48 nm. These results are in agreement with the analysis by UV-Vis spectroscopy.
Figure 8.
SEM analysis of NR/Au membrane obtained at 30 minutes of reduction. Magnification of (a) 200 times; (b) 1,000 times; (c) 20,000 times; (d) 100,000 times.
Natural rubber membranes, with colloidal incorporation of gold nanoparticles, were synthesized by in situ method (NR/Au) at different reduction times, in order to evaluate the physiological behavior of L. braziliensis promastigotes cultured in axenic medium, in a colony of seven weeks old, evaluating the increase kinetics in relation to the permanence time of the membranes in the culture medium as a function of reduction time and temperature of preparation of natural rubber membranes.
It was observed that the inclusion of NR/Au membrane in culture generates a delayed onset of growth in culture until about 24 hours, with a reduction in the development population proportional to the time reduction of the gold nanoparticles. It is also noted that the NR/Au 120 min. membrane presents the best results with regard to growth inhibition of promastigote population in culture medium. NR/Au 30 min membrane has a sharper decline in curve kinetics attributable to death of promastigotes from 120 hours. Upon analysis completion of growth medium, the membranes prepared for times of 30, 60 and 120 minutes showed similar results, with the number of promastigotes in solution smaller than inserted into the initial population.
According to the results the best allowed reduction time is 120 minutes, due to its greater population growth inhibition, and was then assessed the influence of the thermal treatment by the casting preparation method of membrane natural rubber annealed at 60, 80 and 120 °C, and then used as substrates for the reduction of nanoparticles. Results obtained for the kinetics of increase in solution are shown in Figure 9.
Figure 9.
Analysis of the kinetics of increase of promastigotes in solution in the presence of natural rubber membranes prepared by the casting method, at temperatures of 65, 80 and 120 °C, and then incorporated gold nanoparticles to the time reduction of 120 minutes.
It is observed that with increasing of thermal treatment temperature in the preparation of NR membranes the population growth factor in culture decreases, reaching scores lower than 2x105 promastigotes (less than half of the inoculum) to membranes prepared at 120 °C at a reduced nanoparticles to 120 minutes. It is known from promastigotes reactivity with carboxylic and nitrogenated groups, the same reactive groups and assigned to the reduction of nanoparticles. Higher the temperature of thermal treatment used in the preparation of NR membranes, smaller the amount of nanoparticles embedded in the membrane surface, attributed to the fact that there is further degradation of the active components of the membrane with increasing temperature. Thus, it is attributed the decrease in population growth in solution to generate more reactive nanoparticles or selective proteins contained in the culture medium, inhibiting the development of promastigotes, and may also be linked to decreasing of active cores on the membrane surface, or even liberation of radicals in the culture medium attributed to membrane preparation temperature, but the level of promastigotes in culture medium still remains considerable, so that in an attempt to develop a smart skin bandage incorporated into methylene blue molecules on Au particles to photodynamic treatment, due to the drug photosensitivity.
Membranes of pure natural rubber and with incorporation of gold nanoparticles and methylene blue were inserted in the culture medium and the behavior of L. braziliensis promastigotes were evaluated through the population growth kinetics and morphophysiological analysis. Results regarding to population growth obtained for protozoan eluted to membranes prepared at 120 °C of thermal treatment are presented in Figure 10.
Figure 10.
Molecular spectroscopy in UV-Vis region of natural rubber membranes with gold nanoparticles for reduction time of 120 min and functionalization with methylene blue molecules, compared to pure natural rubber membranes.
To improve the studies, blue methylene was incorporated to the NR membrane. This incorporation does not show toxic interaction with promastigotes, since the population growth usually develops when inserted NR/MB membranes. Moreover, when irradiated culture media containing BM molecules, a deficit in the population growth is observed. For NR/MB membranes irradiated with blue light total elimination of promastigotes is observed in about 120 hours, whereas when MB molecules deposited on gold nanoparticles this time decreases to about 60 hours. This fact is attributed to the amplification effect of surface commonly evaluated by micro-Raman spectroscopy, so that the metallic particles act as sites for amplification of energy absorbed by the anchored molecules.
The electrons assume an excited energy state, and during the release of the absorbed energy active radicals are generated, with interaction with the environment where are MB molecules. In the first instance, electrons from MB molecules, when returning to the ground state emit enough energy to excite the oxygen present in the medium converting to superoxides or peroxides radials. This transfer may occur also by interaction with hydrogen atoms present in other molecules to form radicals, e.g. hydroxyl, also with potential toxic to cells, or as in this case, the promastigotes. If the emission energy is derived from a transition to a triplet state of the photosensitizer, one can obtain the formation of a singlet oxygen molecule and an oxidizing agent more toxic to cells [34-38].
6. Conclusion
Membranes with metal nanoparticles significantly influences the development of the protozoan L. braziliensis, thus they can be used for different applications.
Membranes with SNPs can separate the cells at different stages of maturation. In this case, we obtain a biomass feasible to manufacture a vaccine for the purpose of immunization against leishmaniasis.
Membranes with GNPs can used for a possible treatment of cutaneous leishmaniasis, once the cell death is cause due to interaction between the gold and protozoan. NR/MB membranes can be direct to the photosensitive treatment of lesions and so accelerate the closing of the same. Thus, membranes with metallic nanoparticles are a viable and the low cost for both the immunization procedure and in the treatment process because the disease is already established. In addition, treatment with the application of membranes with MNPs dramatically reduces the side effects caused by conventional treatment.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/46055.pdf",chapterXML:"https://mts.intechopen.com/source/xml/46055.xml",downloadPdfUrl:"/chapter/pdf-download/46055",previewPdfUrl:"/chapter/pdf-preview/46055",totalDownloads:2252,totalViews:235,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:11,impactScoreQuartile:1,hasAltmetrics:0,dateSubmitted:"September 19th 2013",dateReviewed:"October 18th 2013",datePrePublished:null,datePublished:"March 19th 2014",dateFinished:"December 25th 2013",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/46055",risUrl:"/chapter/ris/46055",book:{id:"3842",slug:"leishmaniasis-trends-in-epidemiology-diagnosis-and-treatment"},signatures:"Aldo Eloizo Job, Alexandre Fioravante de Siqueira, Caroline Silva\nDanna, Felipe Silva Bellucci, Flávio Camargo Cabrera, Leandra Ernst\nKerche Silva and Pedro Henrique Benites Aoki",authors:[{id:"169579",title:"Dr.",name:"Aldo",middleName:null,surname:"Job",fullName:"Aldo Job",slug:"aldo-job",email:"job@fct.unesp.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169797",title:"Dr.",name:"Alexandre",middleName:"Fioravante",surname:"De Siqueira",fullName:"Alexandre De Siqueira",slug:"alexandre-de-siqueira",email:"siqueiraaf@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169797/images/4469_n.png",institution:null},{id:"169798",title:"Dr.",name:"Caroline",middleName:null,surname:"Silva Danna",fullName:"Caroline Silva Danna",slug:"caroline-silva-danna",email:"caroldanna@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169799",title:"Dr.",name:"Felipe",middleName:null,surname:"Bellucci",fullName:"Felipe Bellucci",slug:"felipe-bellucci",email:"felipe_bellucci@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169800",title:"Dr.",name:"Flavio",middleName:null,surname:"Camargo Cabrera",fullName:"Flavio Camargo Cabrera",slug:"flavio-camargo-cabrera",email:"flavioccabrera@yahoo.com.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169802",title:"Dr.",name:"Leandra Ernst",middleName:null,surname:"Kerche Silva",fullName:"Leandra Ernst Kerche Silva",slug:"leandra-ernst-kerche-silva",email:"leakerche@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169803",title:"Dr.",name:"Pedro Henrique",middleName:null,surname:"Benites Aoki",fullName:"Pedro Henrique Benites Aoki",slug:"pedro-henrique-benites-aoki",email:"pedroaoki@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"169804",title:"Dr.",name:"Carlos Jose",middleName:null,surname:"Leopoldo Constantino",fullName:"Carlos Jose Leopoldo Constantino",slug:"carlos-jose-leopoldo-constantino",email:"case@fct.unesp.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Current treatments",level:"1"},{id:"sec_3",title:"3. Alternative treatments",level:"1"},{id:"sec_4",title:"4. Vaccines against Leishmaniasis",level:"1"},{id:"sec_5",title:"5. New treatment proposals",level:"1"},{id:"sec_6",title:"6. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Tato Lmp Et Al. Colloids And Surfaces B: Biointerfaces. 2009;68: 55-60.'},{id:"B2",body:'Ministério Da Saúde, Secretaria De Vigilância Em Saúde. Manual De Vigilância Da Leishmaniose Tegumentar Americana. Brasília: Editora Do Ministério Da Saúde; 2007.'},{id:"B3",body:'Goto H, Lindoso Jal. Expert Review Of Anti-Infective Therapy. 2010; 8(4): 419-433.'},{id:"B4",body:'Späth Gf Et Al. Proceedings Of The National Academy Of Sciences (Usa). 2000; 97: 9258-9263.'},{id:"B5",body:'Rath S Et Al. Química Nova. 2003;26(4): 550-555.'},{id:"B6",body:'Santos Od. Parasitology Research. 2008;103: 1-10.'},{id:"B7",body:'Grimaldi, G.; Tesh, A. B.; Mcmahon, P. D. 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Department of Physics, Chemistry and Biology, Univ Estadual Paulista, Presidente Prudente, Sao Paulo, Brazil
'},{corresp:null,contributorFullName:"Alexandre Fioravante de Siqueira",address:null,affiliation:'
Department of Physics, Chemistry and Biology, Univ Estadual Paulista, Presidente Prudente, Sao Paulo, Brazil
Department of Physics, Chemistry and Biology, Univ Estadual Paulista, Presidente Prudente, Sao Paulo, Brazil
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1. Introduction
Uruguay is a small country located in South America. According to the 2010 Strategic Energy Development Plan for Uruguay, the diversifying of the energy matrix should be prioritized. Alternative and renewable energy sources rose to be exploited at a major scale. Because of its windy climate, wind energy is now one of the most important sources in our country: currently, Uruguay has more than 1500 MW of installed power lying on this green energy source.
The fast growing development of wind power in Uruguay has encouraged research on many environmental issues, especially those related to wind turbines operation. In many countries—Uruguay included—the method of ISO Standard 9613-2 is the preferred tool for predicting environmental sound pressure levels due to stationary noise sources. However, it is well known that it can incur on great underestimations when sources are large wind turbines, especially under certain atmospheric conditions [1].
This paper is focused on the prediction of environmental sound pressure levels due to the operation of large wind turbines, emphasizing in the prediction model developed by the Research Group on Noise Pollution at the Faculty of Engineering (UdelaR). For its development, the theoretical analysis of the phenomena involved on noise emissions was complemented with tests at the University wind tunnel and, of course, with sound pressure levels measurements at some wind farms in Uruguay. The aerodynamic phenomena involved in acoustic emissions were analyzed with the Research Group on Wind Energy at the Faculty, which has been working on wind energy for nearly 30 years.
The application of the prediction model allows obtaining the expected sound pressure levels at different points. Only airborne sound propagation is considered, as the importance of ground propagation does not involve an important amount of acoustic energy for onshore wind farms.
2. Some limitations of the usual prediction methods to represent wind turbines noise generation and propagation
Environmental sound pressure levels related to stationary sources are usually predicted as prescribed by the ISO Standard 9613-2. It is not only a standardized method of calculation, but it has been for a long time the recommended one in the European Union [2]. This is a strong argument at some developing countries. Convincing the decision-makers about the need of developing another prediction method to achieve more reliable results in the case of wind turbines is not an easy task.
This section aims to point out the main hypothesis of the ISO Standard 9613-2 [3] and to discuss their applicability to wind turbine noise.
2.1 The origin of the calculation method
In 1981, CONCAWE (a group of oil companies, aiming toward the research on the conservation of water and air quality in Europe) hired C. J. Manning for developing a prediction model of environmental sound pressure levels [4]. Some novel prediction methods were inspired on it, as the ISO Standard 9613-2 was.
According to CONCAWE, the environmental sound pressure levels at remote places due to a noise source can be obtained by solving the following expression:
Lp=LW+D−KE1
Where Lp is the sound pressure level in the short time for the octave band i, LW is the acoustic power level for the octave band i, D is the correction due to directivity of the source, and K is the sum of the attenuation terms.
The ISO Standard 9613-2 general expression is just the same:
Lpi=LWi+D−AiE2
The definitions of Eq. (1) are valid for Eq. (2). Ai are the attenuation terms (atmosphere absorption, ground absorption, presence of obstacles or noise barriers, etc.). The subscript i refers to the values for the octave band i.
Both calculation methods assume the divergence law to be quadratics, thus the emitter is supposed to be a point source. Also, both calculation methods promote their application by frequency octave bands. Nevertheless, if there is not enough information to work by bands, ISO Standard 9613-2 will accept calculating in A-weighted sound pressure levels using all formulae and coefficients corresponding to the octave band centered at 500 Hz. If the acoustic emissions have high energy content in low frequencies, this way of calculating will cause a great underestimation of immission sound pressure levels.
CONCAWE’s model uses the meteorological categories proposed by Parkin and Scholes instead of the currently preferred Pasquill-Gifford ones. ISO Standard 9613-2 does not consider calculating differences due to different meteorological conditions when the main calculation hypothesis is satisfied: wind speed between 1 and 5 m/s at a height between 3 and 11 m above the ground and averaged over a short period of time or moderate temperature inversion with its base at ground level. These conditions are not always met when the source is a wind turbine.
In this century, it has been verified that the differences between environmental sound pressure levels predicted by ISO Standard 9613-2 and those that do occur due to the operation of wind turbines would be very important: underestimations of 15 dB or more have been reported during the occurrence of certain combination of environmental conditions [5, 6].
Then, ISO Standard 9613-2 calculation method has been submitted to a deeper analysis.
2.2 Understanding the ISO Standard 9613-2 limitations
Aerodynamic noise generation during operation of wind turbines is inherent to them in nature: the major acoustic emissions from large wind turbines are caused by the interaction between the air flow and the blades. The acoustic emissions occur all along each blade, most of them at low frequencies. Then, the height of the noise source is from about 40–130 m above the ground. The incident wind speed largely varies between these two heights, so that the wind turbine becomes a heterogeneous and complex sound emission source.
There are some limitations for the use of ISO Standard 9613-2 to predict environmental sound pressure levels due to large size wind turbines [1]. Some of the general ones are the following:
The hypothesis about wind speed and atmospheric stability is not always fulfilled.
Atmospheric conditions (neutral, instability, or under an inversion layer) have a great incidence both on generation and on propagation of noise [6].
At the typical distances of interest, a wind turbine cannot be supposed to be a point source [7].
The Standard supposes the distance from source to receiver to be between 100 and 1000 m.
The average height of source and receiver should be between 0 and 30 m (then, the maximum height of the source will not exceed 60 m if the receiver is at 0 m height).
Source and receiver should be placed over a plain surface (a surface with a continuous slope, i.e., the method is not valid for complex terrain).
If the calculations are done based on A-weighted sound pressure levels (as it is allowed by the Standard), a greater underestimation should be done at low frequencies.
Some experimental findings also refer to better results when not considering ground attenuation effects during propagation [8].
But there are also two of the major assumptions that are at the very beginning of the conceptual framework of environmental acoustics that are not fulfilled by the physic/fluid mechanic phenomena involved in the aerodynamic sound generation from wind turbines [9]:
The hypothesis that acoustic processes are adiabatic, because they occur very fast and involve only very small amounts of energy. Most of vibration phenomena can be well described as adiabatic ones, but this is not the case of the aerodynamic noise related to wind turbines’ operation. Noise generation is related to turbulent phenomena, which are not adiabatic but very dissipative ones.
The hypothesis of ideal fluid, which is opposite to the main phenomena that are related to release of eddies from a boundary layer; these phenomena only can occur if the air is considered as a viscous or real fluid.
These are thought to be the root causes for both CONCAWE and ISO methods not to being appropriate for predicting the environmental sound pressure levels related to wind turbines’ operation, as they cannot describe the main involved phenomena on a right way [1, 9, 10, 11].
3. Improving the prediction method
In order to improve the current prediction method, we have proposed several modifications. We have focused on the noise generation phenomena, but we have also worked on two other points: the explicit consideration of the atmospheric stability condition and the dissipative nature of the main phenomena during propagation.
3.1 Wind velocity at the hub height: Considering atmospheric stability class
The wind velocity is usually measured at 10 m height above the ground. One of the main causes of underestimating the environmental sound pressure levels is related to calculating the wind speed at the hub height using a neutral atmospheric profile with basis on its value at 10 m. To avoid this problem, the atmospheric stability class (according to Pasquill-Gifford) has to be explicitly taken into account for this calculation. The atmospheric stability does not only influence the wind speed profile but also the turbulence intensity and, therefore, the acoustic energy depletion law.
If a stable or thermal inversion atmospheric condition occurs, not including it in the prediction method will conduct to:
A great underestimation of the wind speed at the hub height, which would result in the underestimation of the emitted acoustic power level.
A great overestimation of the sound pressure levels depletion, due to the lower atmospheric turbulence and hence, the lower energy dissipation during propagation.
If the atmospheric thermic profile is not known, the wind speed at the hub height should be obtained by supposing a strong atmospheric stability profile (class F according to Pasquill-Gifford), to be in the most demanding hypothesis for protecting the health of noise receivers.
Then, the wind speed at the hub height should be met by converting the measured wind speed data—that are usually taken at 10 m over the ground—using a proper method.
Using the logarithmic profile approach for wind velocity (Eq. (3)) is better than using the potential profile approach (Eq. (4)), even though there are good experimental values for the potential approach. Indeed, since several authors refer that the usual values of m may lead to underestimation of the acoustic power, using the experimental values met by Van den Berg [6] is strongly recommended when using the potential approach, in order to remain on the safe side (see Table 1).
Pasquill stability class
m
Class
Description
Usual bibliography values
Van den Berg experimental values [from 6]
A
Highly unstable
0.09
0.15
D
Neutral
0.28
0.40
F
Highly stable
0.41
0.65
Table 1.
Values of m according to Pasquill-Gifford stability class.
Logarithmic profile approach:
uhhub=u∗klnhhubz0−ψmhhubL∗E3
Where:
u(hhub) wind velocity at hub height
u* friction velocity
k von Karman’s constant
z0 roughness length
ψm thermal stratification function
L* Monin-Obukhov length
Potential profile approach:
uhhub=urefhhubhrefmE4
Where:
uhub wind velocity at hub height hhub
uref measured wind velocity at a reference height href
m coefficient depending on Pasquill-Gifford class of atmospheric stability (see Table 1)
The calculation procedure that we recommend to meet the wind velocity at hhub height, taking into account its value at any other height href, is as follows [10, 11, 12]:
If the stability class to which uref corresponds is known, the velocity at the hub height can be met by applying either Eqs. (3) or (4).
If the stability class to which uref corresponds is not known, a stable atmospheric profile should be assumed for calculating the velocity at hub height with basis on the wind velocity at a reference height (usually 10 m above the ground).
Once the wind velocity at the hub height (uhub) has been obtained, a “corrected” wind velocity at 10 m in height should be calculated. This is the 10 m height wind velocity to be used for meeting the acoustic power level of the wind turbine from tables or charts provided by the manufacturer. Figure 1 sketches the procedure.
Figure 1.
How to reach the wind speed at 10 m height to obtain LW,A (redrawn from [10]).
Please note:
If the wind speed at the hub height is known, the wind velocity at 10 m must always be obtained assuming a neutral atmosphere (even when the stability class is known not to be neutral).
For obtaining the sound pressure level resulting from a wind velocity value measured at a height “H” (other from hhub) in any given atmospheric condition “X”: uhub should be calculated assuming the class of stability “X”; then, the “corrected” wind speed at 10 m in height should also be calculated by assuming neutral atmosphere (class D). The acoustic power shall be read from the datasheet provided by the manufacturer; it will also be associated with that atmospheric stability class: LW"X".
Wind turbine manufacturers often provide tables or graphs relating the wind velocity at 10 m in height (u10) to the acoustic power level (in dBA) emitted by the wind turbine in neutral atmosphere conditions. However, providing emission spectra in frequency bands is not so common. If this information is not available, a reference spectrum should be used, e.g., spectrum in Table 2.
f (Hz)
16
31.5
63
125
250
500
1000
2000
4000
8000
Add to LWA (dB)
−44
−26
−21
−14
−7
−6
−6
−9
−12
−22
Table 2.
Reference spectrum of acoustic power of 2 MW wind turbines in octave bands (based on [13]).
Table 2 (based on [13]) presents the values to be added arithmetically to the acoustic power level of the wind turbine (LWA) to obtain the acoustic power levels in each octave band, also in dBA (LW,f,A).
3.2 Modeling noise generation phenomena
We aim to obtain the sound pressure levels due to the operation of a typical three-blade wind turbine, at a generic receiver point located downwind at a distance d.
Aerodynamic noise is generated by the interaction of wind with the blades of the machine. Most of the acoustic emissions occur in low frequencies, so the acoustic print of wind turbines can be found at large distances from the sources, making the problem more complex to manage.
3.1.1 General background
There are three main processes causing the fluctuation of the pressure field and then the acoustic emissions [14]:
The turbulence of the incoming wind, which causes pressure fluctuations around the blades; it is variable over time and it is called “incoming flow noise.”
The viscous forces in the boundary layer over the solid surfaces of the turbine, such as blades, tower, and hub. Viscous forces in this layer are not negligible compared with the inertial forces (related to the medium air flow). The release of eddies with negative gauge pressure at their cores, developed on solid surfaces such as blades, tower, and hub due to viscous stresses, causes a continuous noise called “trailing edge noise.”
The power exchange between the wind and the machine that produces the release of two families of eddies linked to each blade; one of them has helical motion and the other one is centered on the rotation axis, and its length scale is about the length of the diameter of the rotor.
These phenomena are related to three different geometric scales [14, 15]:
Macroscale: it is the scale related to the largest eddies. If U, L, and T are the scales of velocity, length, and time associated to these eddies, the Reynolds number of the biggest eddies is the same as for the main flow.
Intermediate scale: it includes lower scales than the macroscale ones; there is still no power dissipation. The range of scales included here is called “inertial range.”
Microscale: it is the lowest scale, in which the energy dissipation occurs. Unlike what happens in the macroscale, the smallest eddies are isotropic, as if the flow has “forgotten” where it comes from.
The turbulent cascade hypothesis is then to be considered. According to it, the larger eddies are dissipating into smaller scale eddies with increased kinetic energy. However, there is a length scale at which the power transfer to a smaller eddies scale is not possible. At this point, the turbulent cascade ends and the energy from the last eddies is finally dissipated. The smallest eddies scale is the Kolmogorov scale; the so-called Kolmogorov frequency or dissipation frequency is the generation frequency of these smallest eddies [15]. According to their frequency and energy, the released eddies are able to produce audible phenomena, i.e., they can become noise sources (Figure 2).
Figure 2.
Atmospheric conditions for propagation. From: [15].
The passage of the blades ahead the tower imposes a fluctuation of the sound level pressures emitted by the abovementioned phenomena. It results in an amplitude-modulated noise, called the “blade passage noise.” It has a double nature, one related to the flow and one related to the geometry of the source. The modulation is the most related process to annoyance in wind turbine noise. This process is not modeled in detail: the informed sound pressure levels are the highest of those corresponding to the fluctuation.
3.1.2 Basic concepts concerning wind turbines
A first approach to describe the wind turbines operation is to model the rotor as an active disk, which absorbs kinetic energy from the incoming wind, resulting in a reduction in the flow speed downstream of the turbine.
If v1 is the incoming velocity and v2 is the outcoming velocity, the velocity induction coefficient “a” is defined according to Eq. (5):
v2=v11–2aE5
Applying mass and energy balances to the incoming flow, and supposing an adiabatic and incompressible flow, the maximum amount of power absorbed by the disk is:
W=14ρAv1+v2v12−v22E6
In Eq. (6), ρ is the air mass density, and A is the swept area or rotor area.
The power absorbed is maximized when a = 1/3. Then, Eq. (7) is the expression of the so-called “Betz power”:
WMáx=1627∙12ρAv13E7
The wind turbine operates at its maximum power for each wind velocity, while the wind velocity is under the rate value. As consequence of the power exchange process between the wind and the machine, the flow downwind the rotor rotates around the turbine axis.
The force over the blade, consequence of the interaction between the flow and the blade, is split in two components: the drag effort (D) and the lift one (L) (Figure 3). The magnitude of these components strongly depends on the angle of attack (α), which is the angle between the chord of the blade and the incoming flow relative to the blade. When the drag component increases, the noise generation increases too. This usually occurs when the angle of attack α increases.
Figure 3.
Drag FD and lift FL efforts over the blade (from [15]).
3.1.3 Theory of turbulence
There are several analytical expressions to describe the universal shape of the turbulence spectrum. One of that, the Von Karman’s spectrum, expresses the spectrum as function of a nondimensional ratio built with turbulence integral length scale Lu and the main flow speed v (Eq. (8)):
X=LufvE8
According to Von Karman spectrum, we propose to estimate the energy content in a third-octave band centered at a frequency f according to Eq. (9), in which σ is the standard deviation of the flow speed:
S=4X21/6−2−1/6σ21+708X25/6E9
3.1.4 Emitted acoustic power level
To meet the acoustic power level, we accept that each blade is composed of a group of discrete thin elements or slices. Each one would be sufficiently thin to be thought as a noise point source. Then, the total acoustic power emitted by one blade element should be obtained as the superposition of the acoustic power emitted by the incoming flow (LW,IF) and the trailing edge (LW,TE) as following (Eq. (10)):
LW=10log10LW,IF10+10LW,TE10E10
The incoming flow noise is the result of the fluctuation of the lift effort on the blade, which makes the drag effort to fluctuate. We propose estimate of the pressure field fluctuation using McLaurin series, where first-order terms are related to the turbulent fluctuation.
The length scale of interest, for the incoming turbulence, is similar to the length of the blade chord, which corresponds to the length scale of the eddies that produce the greatest amplitude fluctuation on the pressure field. Van den Berg proposes to use a length scale equal to 60% of the blade chord for this length [8]. Smaller eddies would produce lower fluctuations on the pressure field. Then, the shape of the spectrum of the incoming edge noise, associated to eddies with length scale larger than the blade chord, will be the same as Von Karman’s spectrum.
The trailing edge noise is due to the turbulent boundary layer separation over the blade. The length scale of interest in this case is about the boundary layer thickness.
We built a routine for obtaining the emitted acoustic power level by third-band octave. Its aim is to obtain the predicted sound pressure levels at a point placed at 100 m downwind of the wind turbine tower. We discretize the blade in infinitesimal length blade elements. The coordinates of each slice in every moment could be thought as [x(t), y(t), z (t)]. Then, the propagation into the first 100 m from the tower axis is done assuming that each one of the blade elements is a nonstationary noise point source (Figure 4).
Figure 4.
Sketch of calculation of sound pressure levels in the first 100 m (from [10]).
For the propagation from each blade element to the receiver location, our routine only considers the geometrical divergence and the atmospheric sound absorption as indicated at ISO Standard 9613-1 [16]. The output of this routine is the input for the propagation module [10, 11].
3.3 Modeling noise propagation
For computing sound propagation, the input data are the results of the computing at 100 m far from the tower of the wind turbine. Not only geometric divergence but also atmospheric absorption and turbulent dissipation are considered; both phenomena depend on the frequency. The final sound pressure levels at a given reception point are obtained by superposing the sound pressure levels due to different wind turbines operation. All computations are done in octave bands, and the final results are expressed as LAeq values [11].
3.3.1 Atmospheric conditions and audibility of acoustic emissions
The analysis of the evolution of eddies generated due to wind turbine operation requires the use of the cascade process as it is usual in turbulent flow studies. According to it, the larger eddies are melting into smaller ones, increasing its kinetic energy. At some point, small eddies cannot continue to transfer power to smaller ones; so, they dissipate their remaining energy, thus ending the cascade process. The scale of these last eddies is the order of the Kolmogorov’s scale.
Under atmospheric instability condition, the turbulence is very high and the eddies scale interval is broad; the cascade process is very efficient to dissipate the produced turbulence. For distances greater than the one at which that dissipation occurs, it shall be assumed that the flow conditions are the same as upstream the wind turbine. The ratio between the current wind velocity up and downstream the machine tends to 1 for greater distances, and the difference between them is practically negligible at a distance of about 6 or 7 rotor diameters downstream of the wind turbine (i.e., about 600 m).
In strong atmospheric instability conditions, the prior distance is the shortest one to fully carry out the whole energy cascade process. For any other atmospheric conditions, the dissipation process occurs in greater distances.
Under strong atmospheric stability conditions (i.e., class “F” according to Pasquill-Gilfford stability classes), the effect of turbulence should be negligible. The only mechanism that affects the energy depletion process in any frequency band—in addition to the geometric divergence or attenuation by distance—is the atmospheric absorption.
3.3.2 The atmospheric absorption
The effect of atmospheric absorption can be considered as the depletion of the acoustic energy of a wave over a given distance, due to energy loss caused by the viscosity of the propagation medium (currently, the atmosphere). To estimate the effect of the atmospheric absorption, the computation method of the ISO Standard 9613-1 was used [16].
The attenuation due to atmospheric absorption in dB of a pure tone with frequency f, from its initial level at a distance d = 0 to its level at d, can be obtained according to Eq. (11):
Abs=Γif·d1000E11
Where Γi is the atmospheric absorption in the i-th frequency band in dB/km, and d is the distance from the base in m. The absorption coefficient Γi is a function of the relaxation frequencies from oxygen and nitrogen [16].
The generation and propagation phenomena of eddies can be described from a wave approach. Then, close to the source, the sound pressure levels should be estimated considering energy depletion by geometric divergence (Div) and by atmospheric absorption as shown in Eq. (12).
Lp=LW−Div−Γif·d1000E12
The threshold of perception at each frequency band should be another criterion for determining the distance upon which the sound is still audible. Hearing threshold levels were retrieved from ISO Standard 226 [17].
3.3.3 Geometric divergence
For the depletion of sound pressure levels due to distance, the adjustment is focused on the exponent (n) of the divergence law, which is neither squared nor linear as many measured sound pressure levels close to operating wind farms have shown.
As one of the main hypotheses of linear acoustics was broken (nonviscous effect), we intend not to be mandatory for n to be constant across every one of the considered third-octave bands: the exponents may be related to the distance scale at which eddies are expected to dissipate all their turbulence energy. Then:
Div=10logdd0nfiE13
Here, n = n(fi, d, u) depends on the central frequency fi of each octave band.
For the calculations of geometric divergence, the turbulent cascade approach is taken into account (Figure 2). The released eddies can propagate along great distances while the turbulent cascade occurs [15]. These distances are related to a certain energy level and a length scale. They are also closely related to atmospheric stability.
We calculated the length scale where the turbulent cascade is expected to end by considering it to depend on the incoming wind velocity and the frequency of the released eddies. This is based on prior consideration of the atmospheric stability during the calculation of noise emissions [10, 11].
Different sets of n values were achieved by fitting measured data. At first, we consider only the dependence of n related to the frequency. Then, we explored the dependences on the distance d, the wind speed u, and the atmospheric stability. The best set of n values was selected by the application of the statistic Friedman test and the comparison of residues (differences) between measured to predicted sound pressure levels expressed as A-weighted broadband levels.
Field data were taken at a height of 1.2 m with class 1 sound pressure meters, close to three different wind farms over plain terrain; the distances of measurements covered from 100 m to about 2000 m.
The best set of values was found to be the one obtained for n = n(f, d, u). The explicit consideration of atmospheric stability in the propagation term did not result in an improvement in the simulated sound pressure levels.
The values of n(f, d, u) are given in octave bands according to whether the calculation distances are closer or further than 750 m and that the wind speed at the hub height is less or greater or equal to than 6.5 m/s (Table 3).
f (Hz)
16
31.5
63
125
250
500
1000
2000
4000
8000
Closer than 750 m, less than 6.5 m/s
0.37
0.01
0.05
0.66
1.60
1.67
1.94
1.61
0.85
0.43
Closer than 750 m, 6.5 m/s or more
0.52
0.02
0.01
0.22
0.93
0.79
1.04
1.07
1.06
0.65
Further than 750 m
0.45
0.01
0.06
0.72
1.58
1.71
2.03
1.60
0.67
0.34
Table 3.
Divergence coefficient “n” values for octave bands, according to the wind speed u and the distance d.
4. Validation of the model
4.1 Field measurements
Several sound pressure level measurement campaigns were conducted at three different wind farms with large wind turbines (rate power of 1.8 MW), covering several operating conditions.
Sound pressure level records were taken at 1.2 m height, simultaneously with records of wind speed and direction at 10 m height. In addition, the records of wind speed and direction were obtained from the wind farm anemometer, located at 66 m high and close to the turbines. To carry out the measurements, we used two sound level meters class 1 (Brüel and Kjaer 2250 and Casella 633C), an anemometer (Extech EN-300), a GPS, and two computers.
The measurement points covered four different geographical locations:
A hilly zone, far from external sources such as houses or roads, to avoid introducing disturbances to the data obtained.
A flat zone close to the sea, where 10 large wind turbines are installed.
Another flat zone where two 1.8 MW wind turbines are installed.
A location in the countryside close to a private company, which has only one wind turbine. This location was particularly interesting for this study, since the records are not affected by other turbines or any external sources.
A set of 59 measurements was used during the calibration and validation processes. The main findings showed that the model gave a good approach for the environmental sound pressure levels related to the operation of wind turbines for wind speeds over 5 m/s at the hub height.
In order to validate the model, another set of field data was used. It was another set of data of 49 cases from 10 wind farms in different locations in Uruguay:
The four abovementioned places.
A flat zone in the northern of the country, where 35 wind turbines are installed.
Two hilly wind farms placed on the Southern part of the country, each one with around 25 wind turbines
Three rather flat zones in the center/south-western part of the country, having from 20 to 35 wind turbines each one.
Some adjustments were needed for improving the prediction of noise propagation from wind farms built on uneven terrain.
4.2 Accuracy of predictions
The results obtained in the verification of the performance of the model are presented in Tables 4–6. Almost 80% of the cases are reproduced within ±3 dB range.
Number of cases
Cases in ±3 dB
Number
%
d closer than 750 m
30
24
80
d further than 750 m
18
14
78
Total
48
38
79
Table 4.
Quality of results according to distance to the wind turbine.
Number of cases
Cases in ±3 dB
Number
%
u lower than 6.5 m/s
12
10
83
u higher than 6.5 m/s
36
28
78
Total
48
38
79
Table 5.
Quality of results according to wind velocity at the hub height.
Number of cases
Cases in ±3 dB
Number
%
d closer than 750 m, u lower than 6.5 m
8
7
88
d closer than 750 m, u higher than 6.5 m
22
17
77
d further than 750 m, u lower than 6.5 m
4
3
75
d further than 750 m, u higher than 6.5 m
14
11
79
Total
48
38
79
Table 6.
Quality of results according to distance to the wind turbine and wind velocity at the hub height.
5. Further discussion
5.1 Computed spectra
As important as the percentage of accurate predictions is to state that not only the levels in scale A are predicted in a reasonably adjusted way, but particularly that the spectra obtained with the proposed model are also rightly adjusted to the measured ones [10].
Figure 5 shows some results for short and long distances. The blue bar is the measured sound pressure level; the pink bar is the computed sound pressure level using ISO 9613-2 with attenuation only due to geometric divergence and atmospheric absorption; and the dark red bar is the result of our prediction proposal. As it can be seen, our model achieves a good performance as a prediction tool.
Figure 5.
Comparison of results; left bar: Measured sound pressure levels; center bar: ISO 9613-2 predicted sound pressure levels; left bar: Our prediction proposal. All sound pressure levels are in dBZ. (Adapted from [10]).
5.2 Comparison with a nonnegative matrix factorization (NMF) estimation [18]
It is not usual to find references that use a variable depletion law according to the frequency.
We compared our attenuation curves with those presented in a paper published in 2021 [18]. The authors estimate the sound pressure level related to wind turbines with a nonnegative matrix factorization (NMF), a machine learning technique.
They present some attenuation filters in third-octave bands from 31.3 to 2000 Hz, for attenuation only and for attenuation considering three kinds of residual noise designed by the authors with basis on real noise samples. The filters were published in graphic format for three distances: 500, 1000, and 1500 m. We read the graphs and compared the attenuations proposed in [18] with the attenuation achieved for our prediction model in the same frequencies range.
The comparison was done using the Wilcoxon’s test for differences between pairs. H0 was the equivalence of the compared curves; accepting H0 at 95% confidence means that our attenuation curves are equivalent to those from [18]. Test results are summarized in Table 7. We conclude that each one of our attenuation curves reasonably fit at least one case of the filters suggested by [18], the filter with residual noise 1 being the most similar to our proposal.
Only attenuation
With residual noise 1
With residual noise 2
With residual noise 3
500 m, u less than 6.5 m/s
Accept H0
Reject H0
Reject H0
Reject H0
500 m, u 6.5 m/s or higher
Reject H0
Accept H0
Reject H0
Reject H0
500 m (all together)
Reject H0
Accept H0
Reject H0
Reject H0
1000 m
Reject H0
Accept H0
Accept H0
Accept H0
1500 m
Reject H0
Accept H0
Accept H0
Accept H0
Table 7.
Comparison between our attenuation curves and those from [18].
6. Summarizing our proposal for predicting sound pressure levels related to the operation of large wind turbines
Our proposed calculation process has two steps: at first, modeling the noise generation and its propagation in the short scale (less than 100 m); and propagating the output of the first step from short to large distances far away from the source. At the beginning of the process, the atmospheric stability class is to be taken into account by a correction to the wind velocity; this is very important, to avoid underestimations.
The first step of the calculation process divides the blade in infinitesimal length slices that behave as point sources, and for them the sound pressure level associated to the three mentioned generation processes for each source is calculated and summed logarithmically.
The propagation model takes into account the geometric divergence and the atmospheric absorption, considering n as n(fi, d u). Our proposed “n” values have been presented in Section 3. The fact of not working under the usual hypothesis of environmental acoustics allows considering the coefficient “n” as variable.
Calculation process of this prediction proposal (adapted from [10]).
7. Final remarks
We presented an alternative proposal for predicting sound pressure levels from wind turbines. It is a simple method that has shown very good results, it is easy to build, and it does not need special hardware or software requirements.
The whole model was calibrated, validated, and verified, with field measurements made in different wind farms located in Uruguay. Field data for calibration and validation were taken at distances between 300 and 2000 m from the tower of the wind turbine.
Although this method can be used for different turbines, our results were obtained for 2 MW power rate turbines with between 80 and 90 m of hub height.
More, our prediction model seems to be a good one to be used in noise impact studies related to environmental impact assessments for getting the environmental license of wind farms before their construction.
We presented the accuracy of the predicted A-weighted sound pressure levels, which are good or very good in most of the cases; we also showed the obtained spectra fit accurately to the measured ones.
This fitting is more noticeable at low frequencies, the most problematic ones for noise phenomena in wind turbine, because the energetic content in those frequencies is potentially related to people’s annoyance.
Acknowledgments
This chapter is the result of many years of research. It has been supported by funds from cooperation with the National Program of Wind Energy (National Energy Directory of the Ministry of Industry, Energy and Mining of Uruguay, DNE – MIEM), by the Sectorial Energy Fund of the National Agency of Research and Innovation (Project ANII_FSE_1_2013_1_10942) and the Research Commission of the Universidad de la República through their Fund for Research and Development Groups (CSIC I + D Groups 2014).
Many people have been involved in our team along the years. Here they are, in alphabetical order: Fabiana Bianchi Falco, Pablo Bonilla Medina (in memoriam), Nicolás Cunha Apatie, Matteo Deambrosi Papini, Pablo Gianoli Kovar, Matías Hernández Castellani, Marcos Raúl Lisboa, Joaquín Montero Croucciée, Luciana Olazábal Barrios, Juan Ignacio Pais, Martín Paz Urban, Nicolás Rezzano Tizze, Felipe Silva Rodríguez, and Guillermo Sugasti Sánchez. We thank all of them for taking part in this research.
Conflict of interest
The authors declare they have no conflict of interest.
\n',keywords:"wind turbines noise, wind farms noise, wind energy, noise prediction model, aerodynamic noise",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80973.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80973.xml",downloadPdfUrl:"/chapter/pdf-download/80973",previewPdfUrl:"/chapter/pdf-preview/80973",totalDownloads:14,totalViews:0,totalCrossrefCites:0,dateSubmitted:"January 22nd 2022",dateReviewed:"February 10th 2022",datePrePublished:"March 25th 2022",datePublished:null,dateFinished:"March 25th 2022",readingETA:"0",abstract:"The prediction of the environmental sound pressure levels of wind farms does not yet have a global consensus on how to achieve an easy-to-build model with accurate results. This chapter aims to present the sound pressure level prediction model developed at Universidad de la República (Uruguay). Its main characteristics are: taking into account atmospheric stability to determine the acoustic power of the machines; describing the generation of noise along the blades due to turbulent phenomena; and calculating the noise propagation at different distances from the tower taking into account atmospheric absorption, turbulence energy dissipation, and geometric divergence. It does not have any special IT requirements. A new approach to calculating geometric divergence is considered. The results show more than 80% of the cases within the range of ±3 dB, for wind farms throughout our country. The need to use not only A-weighted sound pressure levels but also octave frequency band levels is indicated.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80973",risUrl:"/chapter/ris/80973",signatures:"Alice Elizabeth González and José Cataldo Ottieri",book:{id:"11176",type:"book",title:"Wind Turbines - Advances and Challenges in Design, Manufacture and Operation",subtitle:null,fullTitle:"Wind Turbines - Advances and Challenges in Design, Manufacture and Operation",slug:null,publishedDate:null,bookSignature:"Prof. Karam Youssef Maalawi",coverURL:"https://cdn.intechopen.com/books/images_new/11176.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80355-493-8",printIsbn:"978-1-80355-492-1",pdfIsbn:"978-1-80355-494-5",isAvailableForWebshopOrdering:!0,editors:[{id:"18593",title:"Prof.",name:"Karam",middleName:"Youssef",surname:"Maalawi",slug:"karam-maalawi",fullName:"Karam Maalawi"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Some limitations of the usual prediction methods to represent wind turbines noise generation and propagation",level:"1"},{id:"sec_2_2",title:"2.1 The origin of the calculation method",level:"2"},{id:"sec_3_2",title:"2.2 Understanding the ISO Standard 9613-2 limitations",level:"2"},{id:"sec_5",title:"3. Improving the prediction method",level:"1"},{id:"sec_5_2",title:"3.1 Wind velocity at the hub height: Considering atmospheric stability class",level:"2"},{id:"sec_6_2",title:"3.2 Modeling noise generation phenomena",level:"2"},{id:"sec_6_3",title:"3.1.1 General background",level:"3"},{id:"sec_7_3",title:"3.1.2 Basic concepts concerning wind turbines",level:"3"},{id:"sec_8_3",title:"3.1.3 Theory of turbulence",level:"3"},{id:"sec_9_3",title:"3.1.4 Emitted acoustic power level",level:"3"},{id:"sec_11_2",title:"3.3 Modeling noise propagation",level:"2"},{id:"sec_11_3",title:"3.3.1 Atmospheric conditions and audibility of acoustic emissions",level:"3"},{id:"sec_12_3",title:"3.3.2 The atmospheric absorption",level:"3"},{id:"sec_13_3",title:"Table 3.",level:"3"},{id:"sec_16",title:"4. Validation of the model",level:"1"},{id:"sec_16_2",title:"4.1 Field measurements",level:"2"},{id:"sec_17_2",title:"4.2 Accuracy of predictions",level:"2"},{id:"sec_19",title:"5. Further discussion",level:"1"},{id:"sec_19_2",title:"5.1 Computed spectra",level:"2"},{id:"sec_20_2",title:"5.2 Comparison with a nonnegative matrix factorization (NMF) estimation [18]",level:"2"},{id:"sec_22",title:"6. Summarizing our proposal for predicting sound pressure levels related to the operation of large wind turbines",level:"1"},{id:"sec_23",title:"7. Final remarks",level:"1"},{id:"sec_24",title:"Acknowledgments",level:"1"},{id:"sec_27",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'González AE, Rezzano Tizze N, Bianchi Falco F. Algunas limitaciones de la Norma ISO 9613—Parte 2 para el estudio de propagación de ruido de aerogeneradores de gran porte (Some limitations of ISO 9613-Part 2 for studying noise propagation from big wind turbines). In: Reunión Regional de Acústica, 11–12 October 2011; Montevideo, Uruguay. Montevideo: Asociación Uruguaya de Acústica–Departamento de Ingeniería Ambiental; 2011. p. 54. ISBN: 978-9974-0-0785-7'},{id:"B2",body:'Official European Union Journal. Directive 2002/49/EC of the European Parliament and of the Council relating to the assessment and management of environmental noise. 25 June 2002'},{id:"B3",body:'International Standard Organization. International Standard 9613. Attenuation of sound during propagation outdoors—Part 2: General method of calculation. 1996'},{id:"B4",body:'Manning CJ. The Propagation of Noise from Petroleum and Petrochemical Complexes to Neighbouring Communities. Report 4/81, CONCAWE. 1981'},{id:"B5",body:'IMFIA. Impacto acústico de aerogeneradores. Subproyecto A. Informe Final (Acoustic Impact of Wind Turbines. Subproject A. Final Report). Specific Agreement between the Universidad de la República–Faculty of Engineering and the Ministry of Industry, Energy and Mining–National Energy Directorate. December 2012'},{id:"B6",body:'Van den Berg GP. The sound of high winds: the effect of atmospheric stability on wind turbine sound and microphone noise [doctoral thesis]. Netherlands: University of Groningen; 2006'},{id:"B7",body:'Martín B, María Á, Tarrero AI, Bravo D, Copete M, González J, Machimbarrena M, García L. Impacto acústico de los parques eólicos y su evolución (Acoustic impact of wind parks and their evolving). In: Acústica 2008. Coimbra, Portugal. 2008'},{id:"B8",body:'Kaliski K, Duncan E. Propagation Modelling Parameters for Wind Power Projects. (Based on a paper presented at Noise-Con 2007. Reno, NV: Institute of Noise Control Engineering; 2008'},{id:"B9",body:'Nuñez Pereira I. Elementos de Acústica, Environmental Engineering Magister Program. Montevideo: Faculty of Engineering, Universidad de la República; 2013'},{id:"B10",body:'González AE, Gianoli Kovar P, Deambrosi Papini M, Hernández Castellani M, Paz Urban M. Síntesis de Resultados del Proyecto ANII FSE_2013_1_10942 “Impacto Acústico de Aerogeneradores de Gran Porte”: Modelo predictivo de niveles ambientales de presión sonora. [Summary of Outcomes from the Research Project ANII FSE_2013_1_10942 “Acoustic Impact of Large Wind Turbines”: Prediction Model for Environmental Sound Pressure Levels.]. September 2016. p. 23'},{id:"B11",body:'González AE, Gianoli-Kovar P, Deambrosi-Papini M, Hernández-Castellani M, Paz-Urban M. Environmental noise due to large wind turbines: What we have learnt. In: International Congress on Acoustics ICA 2016. Buenos Aires, Argentina. 2016'},{id:"B12",body:'González AE, Rezzano Tizze N, Lisboa MR, Gianoli Kovar P. Environmental noise from wind farms: a prediction proposal for flat areas. In: International Congress of Sound and Vibration ICSV22, Florence, Italy. 2015'},{id:"B13",body:'Jørgen, Kragh Birger Plovsing, DELTA, Acoustics & Vibration; Svein Å. Storeheier, SINTEF, Telecom and Informatics; Hans G. Jonasson, SP Swedish National Testing and Research Institute, Acoustics. Nordic environmental noise prediction methods, Nord 2000. Summary report. General Nordic sound propagation model and applications in source-related prediction methods. Client: Nordic Noise Group; 2002'},{id:"B14",body:'Van den Berg GP. Effects of the wind profile at night on wind turbine sound. Journal of Sound and Vibration. 2004;277:955–970. DOI: 10.1016/j.jsv.2003.09.050'},{id:"B15",body:'Cataldo J. Introducción a la Turbulencia” (Introduction to turbulence) [postgraduate course notes]. Uruguay: Universidad de la República; 2016'},{id:"B16",body:'International Standard Organization. International Standard 9613. Attenuation of sound during propagation outdoors—Part 1: Calculation of the absorption of sound by the atmosphere. 1993'},{id:"B17",body:'International Standard Organization. ISO 226. Acoustics – Normal Equal-Loudness-Level Contours. 2nd ed. 2003'},{id:"B18",body:'Gloaguen J-R, Ecotière D, Gauvreau B, Finez A, Petit A, Le Bourdat C. Automatic estimation of the sound emergence of wind turbine noise with nonnegative matrix factorization. Journal of the Acoustical Society of America. October 2021;150(4):3127-3138'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Alice Elizabeth González",address:"elizabet@fing.edu.uy",affiliation:'
IMFIA, Faculty of Engineering, Universidad de la República UdelaR (University of the Republic), Montevideo, Uruguay
IMFIA, Faculty of Engineering, Universidad de la República UdelaR (University of the Republic), Montevideo, Uruguay
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The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.
",metaTitle:"Our story",metaDescription:"The company was founded in Vienna in 2004 by Alex Lazinica and Vedran Kordic, two PhD students researching robotics. While completing our PhDs, we found it difficult to access the research we needed. So, we decided to create a new Open Access publisher. A better one, where researchers like us could find the information they needed easily. The result is IntechOpen, an Open Access publisher that puts the academic needs of the researchers before the business interests of publishers.",metaKeywords:null,canonicalURL:"/page/our-story",contentRaw:'[{"type":"htmlEditorComponent","content":"
We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
\\n\\n
In the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
\\n\\n
The IntechOpen timeline
\\n\\n
2004
\\n\\n
\\n\\t
Intech Open is founded in Vienna, Austria, by Alex Lazinica and Vedran Kordic, two PhD students, and their first Open Access journals and books are published.
\\n\\t
Alex and Vedran launch the first Open Access, peer-reviewed robotics journal and IntechOpen’s flagship publication, the International Journal of Advanced Robotic Systems (IJARS).
\\n
\\n\\n
2005
\\n\\n
\\n\\t
IntechOpen publishes its first Open Access book: Cutting Edge Robotics.
\\n
\\n\\n
2006
\\n\\n
\\n\\t
IntechOpen publishes a special issue of IJARS, featuring contributions from NASA scientists regarding the Mars Exploration Rover missions.
\\n
\\n\\n
2008
\\n\\n
\\n\\t
Downloads milestone: 200,000 downloads reached
\\n
\\n\\n
2009
\\n\\n
\\n\\t
Publishing milestone: the first 100 Open Access STM books are published
\\n
\\n\\n
2010
\\n\\n
\\n\\t
Downloads milestone: one million downloads reached
\\n\\t
IntechOpen expands its book publishing into a new field: medicine.
\\n
\\n\\n
2011
\\n\\n
\\n\\t
Publishing milestone: More than five million downloads reached
\\n\\t
IntechOpen publishes 1996 Nobel Prize in Chemistry winner Harold W. Kroto’s “Strategies to Successfully Cross-Link Carbon Nanotubes”. Find it here.
\\n\\t
IntechOpen and TBI collaborate on a project to explore the changing needs of researchers and the evolving ways that they discover, publish and exchange information. The result is the survey “Author Attitudes Towards Open Access Publishing: A Market Research Program”.
\\n\\t
IntechOpen hosts SHOW - Share Open Access Worldwide; a series of lectures, debates, round-tables and events to bring people together in discussion of open source principles, intellectual property, content licensing innovations, remixed and shared culture and free knowledge.
\\n
\\n\\n
2012
\\n\\n
\\n\\t
Publishing milestone: 10 million downloads reached
\\n\\t
IntechOpen holds Interact2012, a free series of workshops held by figureheads of the scientific community including Professor Hiroshi Ishiguro, director of the Intelligent Robotics Laboratory, who took the audience through some of the most impressive human-robot interactions observed in his lab.
\\n
\\n\\n
2013
\\n\\n
\\n\\t
IntechOpen joins the Committee on Publication Ethics (COPE) as part of a commitment to guaranteeing the highest standards of publishing.
\\n
\\n\\n
2014
\\n\\n
\\n\\t
IntechOpen turns 10, with more than 30 million downloads to date.
\\n\\t
IntechOpen appoints its first Regional Representatives - members of the team situated around the world dedicated to increasing the visibility of our authors’ published work within their local scientific communities.
\\n
\\n\\n
2015
\\n\\n
\\n\\t
Downloads milestone: More than 70 million downloads reached, more than doubling since the previous year.
\\n\\t
Publishing milestone: IntechOpen publishes its 2,500th book and 40,000th Open Access chapter, reaching 20,000 citations in Thomson Reuters ISI Web of Science.
\\n\\t
40 IntechOpen authors are included in the top one per cent of the world’s most-cited researchers.
\\n\\t
Thomson Reuters’ ISI Web of Science Book Citation Index begins indexing IntechOpen’s books in its database.
\\n
\\n\\n
2016
\\n\\n
\\n\\t
IntechOpen is identified as a world leader in Simba Information’s Open Access Book Publishing 2016-2020 report and forecast. IntechOpen came in as the world’s largest Open Access book publisher by title count.
\\n
\\n\\n
2017
\\n\\n
\\n\\t
Downloads milestone: IntechOpen reaches more than 100 million downloads
\\n\\t
Publishing milestone: IntechOpen publishes its 3,000th Open Access book, making it the largest Open Access book collection in the world
We started by publishing journals and books from the fields of science we were most familiar with - AI, robotics, manufacturing and operations research. Through our growing network of institutions and authors, we soon expanded into related fields like environmental engineering, nanotechnology, computer science, renewable energy and electrical engineering, Today, we are the world’s largest Open Access publisher of scientific research, with over 4,200 books and 54,000 scientific works including peer-reviewed content from more than 116,000 scientists spanning 161 countries. Our authors range from globally-renowned Nobel Prize winners to up-and-coming researchers at the cutting edge of scientific discovery.
\n\n
In the same year that IntechOpen was founded, we launched what was at the time the first ever Open Access, peer-reviewed journal in its field: the International Journal of Advanced Robotic Systems (IJARS).
\n\n
The IntechOpen timeline
\n\n
2004
\n\n
\n\t
Intech Open is founded in Vienna, Austria, by Alex Lazinica and Vedran Kordic, two PhD students, and their first Open Access journals and books are published.
\n\t
Alex and Vedran launch the first Open Access, peer-reviewed robotics journal and IntechOpen’s flagship publication, the International Journal of Advanced Robotic Systems (IJARS).
\n
\n\n
2005
\n\n
\n\t
IntechOpen publishes its first Open Access book: Cutting Edge Robotics.
\n
\n\n
2006
\n\n
\n\t
IntechOpen publishes a special issue of IJARS, featuring contributions from NASA scientists regarding the Mars Exploration Rover missions.
\n
\n\n
2008
\n\n
\n\t
Downloads milestone: 200,000 downloads reached
\n
\n\n
2009
\n\n
\n\t
Publishing milestone: the first 100 Open Access STM books are published
\n
\n\n
2010
\n\n
\n\t
Downloads milestone: one million downloads reached
\n\t
IntechOpen expands its book publishing into a new field: medicine.
\n
\n\n
2011
\n\n
\n\t
Publishing milestone: More than five million downloads reached
\n\t
IntechOpen publishes 1996 Nobel Prize in Chemistry winner Harold W. Kroto’s “Strategies to Successfully Cross-Link Carbon Nanotubes”. Find it here.
\n\t
IntechOpen and TBI collaborate on a project to explore the changing needs of researchers and the evolving ways that they discover, publish and exchange information. The result is the survey “Author Attitudes Towards Open Access Publishing: A Market Research Program”.
\n\t
IntechOpen hosts SHOW - Share Open Access Worldwide; a series of lectures, debates, round-tables and events to bring people together in discussion of open source principles, intellectual property, content licensing innovations, remixed and shared culture and free knowledge.
\n
\n\n
2012
\n\n
\n\t
Publishing milestone: 10 million downloads reached
\n\t
IntechOpen holds Interact2012, a free series of workshops held by figureheads of the scientific community including Professor Hiroshi Ishiguro, director of the Intelligent Robotics Laboratory, who took the audience through some of the most impressive human-robot interactions observed in his lab.
\n
\n\n
2013
\n\n
\n\t
IntechOpen joins the Committee on Publication Ethics (COPE) as part of a commitment to guaranteeing the highest standards of publishing.
\n
\n\n
2014
\n\n
\n\t
IntechOpen turns 10, with more than 30 million downloads to date.
\n\t
IntechOpen appoints its first Regional Representatives - members of the team situated around the world dedicated to increasing the visibility of our authors’ published work within their local scientific communities.
\n
\n\n
2015
\n\n
\n\t
Downloads milestone: More than 70 million downloads reached, more than doubling since the previous year.
\n\t
Publishing milestone: IntechOpen publishes its 2,500th book and 40,000th Open Access chapter, reaching 20,000 citations in Thomson Reuters ISI Web of Science.
\n\t
40 IntechOpen authors are included in the top one per cent of the world’s most-cited researchers.
\n\t
Thomson Reuters’ ISI Web of Science Book Citation Index begins indexing IntechOpen’s books in its database.
\n
\n\n
2016
\n\n
\n\t
IntechOpen is identified as a world leader in Simba Information’s Open Access Book Publishing 2016-2020 report and forecast. IntechOpen came in as the world’s largest Open Access book publisher by title count.
\n
\n\n
2017
\n\n
\n\t
Downloads milestone: IntechOpen reaches more than 100 million downloads
\n\t
Publishing milestone: IntechOpen publishes its 3,000th Open Access book, making it the largest Open Access book collection in the world
\n
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The oxidative polymerization of catecholamines can be triggered by light, chemical and physical methods, thus representing one of the widely explored surface coating methods. The overall objectives of this chapter are to compile the various methods of accomplishing surface coatings and compare the structural diversity of catecholamines. The progress achieved so far on polydopamine (pDA) coatings on electrospun polymers will be discussed. Finally, we will summarize the research efforts on catecholamine coatings for biomedical applications as well as their potential as a high definition coating method.",book:{id:"7256",slug:"dopamine-health-and-disease",title:"Dopamine",fullTitle:"Dopamine - Health and Disease"},signatures:"Rajamani Lakshminarayanan, Srinivasan Madhavi and Christina Poh\nChoo Sim",authors:[{id:"256023",title:"Associate Prof.",name:"Lakshminarayanan",middleName:null,surname:"Rajamani",slug:"lakshminarayanan-rajamani",fullName:"Lakshminarayanan Rajamani"},{id:"270706",title:"Prof.",name:"Madhavi",middleName:null,surname:"Srinivasan",slug:"madhavi-srinivasan",fullName:"Madhavi Srinivasan"},{id:"270707",title:"Dr.",name:"Christina Poh Choo",middleName:null,surname:"Sim",slug:"christina-poh-choo-sim",fullName:"Christina Poh Choo Sim"}]},{id:"47285",doi:"10.5772/58851",title:"Spinal Additives in Subarachnoid Anaesthesia for Cesarean Section",slug:"spinal-additives-in-subarachnoid-anaesthesia-for-cesarean-section",totalDownloads:5764,totalCrossrefCites:2,totalDimensionsCites:7,abstract:null,book:{id:"3819",slug:"topics-in-spinal-anaesthesia",title:"Topics in Spinal Anaesthesia",fullTitle:"Topics in Spinal Anaesthesia"},signatures:"Hala M. 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Other human and animal studies indicate that fluoride is a developmental neurotoxicant and that it operates in utero. Economic impacts of IQ loss have been quantified. The objective was to use data from the meta-analysis and other studies to estimate a daily dose of fluoride that would protect all children from lowered IQ, and to estimate economic impacts. We used two methods: traditional lowest-observed-adverse-effect (LOAEL)/no-observed-adverse-effect level (NOAEL); and benchmark dose (BMD). We used 3 mg/L in drinking water as an “adverse effect concentration,” with reported fluoride intakes from food, in the LOAEL/NOAEL method. We used the available dose–response data for the BMD analysis. Arsenic, iodine, and lead levels were controlled for in studies we used. BMD analysis shows the possible safe dose to protect against a five-point IQ loss is between 0.0014 and 0.050 mg/day. The LOAEL/NOAEL safe dose range estimate is 0.0042–0.16 mg/day. The economic impact for IQ loss among US children is loss of tens of billions of dollars.",book:{id:"5894",slug:"neurotoxins",title:"Neurotoxins",fullTitle:"Neurotoxins"},signatures:"John William Hirzy, Paul Connett, Quanyong Xiang, Bruce Spittle\nand David Kennedy",authors:[{id:"215103",title:"Dr.",name:"J. William",middleName:null,surname:"Hirzy",slug:"j.-william-hirzy",fullName:"J. 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The oxidative polymerization of catecholamines can be triggered by light, chemical and physical methods, thus representing one of the widely explored surface coating methods. The overall objectives of this chapter are to compile the various methods of accomplishing surface coatings and compare the structural diversity of catecholamines. The progress achieved so far on polydopamine (pDA) coatings on electrospun polymers will be discussed. Finally, we will summarize the research efforts on catecholamine coatings for biomedical applications as well as their potential as a high definition coating method.",book:{id:"7256",slug:"dopamine-health-and-disease",title:"Dopamine",fullTitle:"Dopamine - Health and Disease"},signatures:"Rajamani Lakshminarayanan, Srinivasan Madhavi and Christina Poh\nChoo Sim",authors:[{id:"256023",title:"Associate Prof.",name:"Lakshminarayanan",middleName:null,surname:"Rajamani",slug:"lakshminarayanan-rajamani",fullName:"Lakshminarayanan Rajamani"},{id:"270706",title:"Prof.",name:"Madhavi",middleName:null,surname:"Srinivasan",slug:"madhavi-srinivasan",fullName:"Madhavi Srinivasan"},{id:"270707",title:"Dr.",name:"Christina Poh Choo",middleName:null,surname:"Sim",slug:"christina-poh-choo-sim",fullName:"Christina Poh Choo Sim"}]},{id:"59036",title:"Nursing Care for Persons with Drug Addiction",slug:"nursing-care-for-persons-with-drug-addiction",totalDownloads:2150,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Persons with drug addiction (PDDs) may exhibit symptoms affecting the central nervous system. Multidisciplinary treatment teams may offer the most updated treatment and care. Pharmacotherapy is one standard treatment, effective in managing psychotic symptoms with supportive psychosocial interventions. As part of the health-care team, nurses deal with PDD on a 24-hour basis. Quality nursing care is essential for improving quality of life, health status, and continued abuse-free status of PDD.",book:{id:"6404",slug:"drug-addiction",title:"Drug Addiction",fullTitle:"Drug Addiction"},signatures:"Ek-uma Imkome",authors:[{id:"219235",title:"Associate Prof.",name:"Ek-Uma",middleName:null,surname:"Imkome",slug:"ek-uma-imkome",fullName:"Ek-Uma Imkome"}]},{id:"59317",title:"Effect of Alcohol on Brain Development",slug:"effect-of-alcohol-on-brain-development",totalDownloads:1208,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In the world, 3.3 million deaths occur every year due to harmful use of alcohol; this represents 5.9% of all deaths. Ethanol metabolites’ production and their post-translation modification are one of the proposed mechanisms that lead to neuronal toxicity. The projected neurochemical changes in chronic alcohol drinkers may be due to an imbalance between excitatory and inhibitory neurotransmitters. Interaction of alcohol with GABA and glutamate receptors (NMDA and AMPA) resulted in diverse adaptive changes in gene expression through neuronal pathways leading to alcohol toxicity. Alcohol consumption in an individual leads to biochemical changes that are correlated with complex inflammatory signaling pathways such as phosphorylation of proteins, synthesis of nitric oxide (NO), NF-kappaB and MAP kinase pathways in certain regions of the brain. Ethanol exposure activates neurons and microglial cells that lead to release of neuroimmune factors like high-mobility group box 1 (HMGB1), toll-like receptor 4 (TLR4) and certain cytokines involved in immune responses leading to neuroimmune signaling in the brain. Epigenetic modification of DNA and histones may lead to neuronal gene expression, thus regulating ethanol toxicity. Researchers attempt to modulate therapies that can help to foil alcohol toxicity and support the development of original neuronal cells that have been injured or degenerated by alcohol exposure.",book:{id:"6404",slug:"drug-addiction",title:"Drug Addiction",fullTitle:"Drug Addiction"},signatures:"Farhin Patel and Palash Mandal",authors:[{id:"217215",title:"Dr.",name:"Palash",middleName:null,surname:"Mandal",slug:"palash-mandal",fullName:"Palash Mandal"},{id:"219333",title:"Ms.",name:"Farhin",middleName:null,surname:"Patel",slug:"farhin-patel",fullName:"Farhin Patel"}]},{id:"61035",title:"Induced Pluripotent Stem Cell-Derived Human Glutamatergic Neurons as a Platform for Mechanistic Assessment of Inducible Excitotoxicity in Drug Discovery",slug:"induced-pluripotent-stem-cell-derived-human-glutamatergic-neurons-as-a-platform-for-mechanistic-asse",totalDownloads:1251,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Since the guiding principles of Replace, Reduce, and Refine were published, wider context-of-use for alternatives to animal testing have emerged. Induced pluripotent stem cell-derived human glutamatergic-enriched cortical neurons can be leveraged as 2- and 3-dimensional platforms to enable candidate drug screening. Uniquely so, 2-dimensional models are useful considering that they exhibit spontaneous firing, while, 3-dimensional models show spontaneous synchronized calcium transient oscillations. Here, the limitations of selected induced acute seizure models as well as the early utilization of fully differentiated glutamatergic neuron models for interrogation of inducible excitotoxicity following exposure to neuromodulators will be described. 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The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. 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The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. 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We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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