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1. Introduction
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1.1 Is CRS directly caused by infectious agents?
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Our current state of knowledge indicates that chronic rhinosinusitis (CRS) is not directly caused by infectious agents [1]. Instead, the current paradigm states that CRS is a spectrum of “self-perpetuating” non-infectious inflammatory processes. If this is the case, that would mean that repetitive, long term, systemic antibiotic therapy has little to no role in the treatment of CRS, except in the event of an acute exacerbation. Furthermore, this would suggest that clinical improvement of CRS would be more appropriately explained by the reduction of inflammatory injury as a whole, and only secondarily by the amelioration of bacterial load and the resultant removal of super-antigens.
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Albeit this working theory pivots upon a non-infectious etiology it does raise many concerns in the direction of microbiology. The most paramount of which is that the misappropriate, frequent, and long term use of antibiotics actually selects for a pathological microflora, composed of microorganisms resistant to antibiotics, which may also form biofilms that may never be eradicated [1]. These biofilms may then act as the perfect stage for future acute exacerbations, functioning as a protective bunker for bacteria lying dormant within the film, and even create quasi-resistant bacteria. For example, a naturally antibiotic-sensitive bacterium contained within a biofilm may be out of reach of the action of an antibiotic, rendering it resistant-in-vivo.
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This idea is closely paralleled and supported by animal models of Pseudomonas-biofilm formation within sinus mucosa; where, Pseudomonas-biofilm required 400 times the concentration of tobramycin to be eradicated. Similarly, topical antibiotics are frequently ineffective at standard doses, which is often considered clinical proof of the non-bacterial etiology of CRS [2]. However, whether or not the proposed explanations are clinically valid for a non-bacterial mechanism of CRS remains a debatable issue and should be carefully evaluated in the context of published studies.
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Now, we will review these questions in a step-by-step fashion: physiology, sinus microflora, and recent discoveries on the role of punch biopsy in CRS and its detection of deep-tissue sinus infection.
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2. Is a healthy sinus cavity free of bacteria?
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So, now the question is, is sterility synonymous with well-being? By using microbiome technology to detect difficult to culture bacteria, it was observed that bacteria are present in both healthy and diseased sinuses [3]. However, a pilot study on CRS patients actually discovered a significantly lower taxa of bacteria than their healthy control. So, at first glance it may look like the opposite, a lower number of bacteria is correlated with a higher likelihood of CRS. Does this point to a non-infectious etiology, then?
\n
Importantly, these microbiome studies did not only reveal a difference in absolute number of bacteria, but in the content of the bacterial flora. Further analysis revealed that the bacterial taxa of the CRS patients was largely defined by relatively high numbers of unique single species, such as Corynebacterium tuberculostearicum, while microbiome analysis in the healthy control group showed a relative abundance of Lactobacillus spp., Enterococcus spp., and Pediococcus spp., but what does all of this mean in practice? These findings suggest that the etiology of CRS may hinge upon balance and equilibrium, and not at all upon bacterial load.
\n
To investigate this hypothesis further, a study was designed on a mouse model of inflammatory sinusitis. This study revealed something extremely interesting. Sinus infection by C. tuberculostearicum led to hyperplasia [3], but not by itself. This hyperplasia only occurred with the administration of antibiotics. It looks that the use of antibiotics backfired. Upon antibiotic treatment the commensal bacteria of the healthy sinus cavity were eliminated, selecting for an antibiotic resistant strain C. tuberculostearicum, which became opportunistically pathogenic without a commensal microflora to police its growth. But what would happen if we rebalanced our flora? Could this process be reversed?
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Interestingly enough, upon the addition of the Lactobacillus sakei the process reversed entirely, returning the sinus cavity to its natural state. The conclusion of this intriguing study was that antibiotic treatment of acute rhinosinusitis may be a “Catch-22”, and although it may rid the body of the archetypal bacteria of acute sinusitis, it may contribute to the future development of persistent sinusitis and/or CRS. These findings spark many questions and begin to steer the medical mind toward similar situations within different specialties.
\n
Taking these discoveries of bacterial imbalance into consideration, it may be appropriate to draw analogies across specialties, and explore the realm of microbiotic imbalance in the upper respiratory tract as it relates to the female urogenital tract. We may be able to draw important conclusions in the pathogenesis of floral-imbalance-induced-CRS through the data analysis of microbiome studies in bacterial vaginosis (BV). BV is an infection in which anaerobic bacteria overgrow vaginal mucosa as a direct result of the, often inadvertent, elimination of Lactobacillus species [4]. These species naturally secret bactericidal H2O2 that kills anaerobic species—protecting the delicate membranes of the vaginal mucosa. Just as CRS, BV is frequently a recurrent process. However, a very simple single treatment with Metronidazole and/or recolonization with Lactobacillus often restores the health of mucosal membranes. It may be an oversimplification of a complex disease state, but the possibility of a similar etiology and therefore similar non-invasive cost-effective treatment is tantalizing.
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2.1 Alternative thesis: CRS involves direct bacterial infection
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As much evidence as there may be for the noninfectious hypothesis of CRS, there is just as much supporting the opposite. So where does the truth lie? As with most things in life, most likely somewhere in the middle. Either way, here we will explore the possibility of infectious CRS, and some of the most recent discoveries and theories behind it.
\n
The noninfectious hypothesis of CRS is certainly a tantalizing one, but it is strongly challenged by the alternative hypothesis [5]. The authors of this chapter tend to lean toward the more active process of infection as the most common etiology, and we propose that the predominant progression of CRS directly involves bacterial infection. Furthermore, we believe that most of the theories and concepts pointing toward a noninfectious etiology, have been improperly evaluated and interpreted, and when reanalyzed tend to support an infectious cause of CRS.
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Many parallels can be drawn between the two main arguments, one of which is the selection of microflora and or pathogens by inadequate or improper antimicrobial treatment. Some pathogens, such as E. coli, are able to both actively and passively elude destruction and clearance through multiple mechanisms, and current studies are pointing toward the fact that we as clinicians are inadvertently selecting for them. Through mechanisms similar to those described in the previous sections, incomplete treatment of bacterial sinusitis looks to be inducing the escape of such organisms from the reach of the immune system as a whole, as well as antibiotics specifically, by driving these microorganisms into our body’s white cells or deep within the sinus mucosa. Simultaneously, the resultant disruption of the commensal bacterial community and mucosal integrity of the sinus leads to the formation of biofilm, which in our opinion is both a strong supplementary contributor and a direct cause of subacute and chronic infectious processes.
\n
As discussed previously, a weakened microflora may contribute to the dysfunction of the sinus mucosa and disruption of the general local immune state. This, in combination with a slew of other complex factors, creates the perfect platform for the formation of a biofilm. Once formed, biofilm contributes to the failure of the antibiotic treatment by preventing any significant antibiotic penetration. Bacteria hiding within the structure of the film, become effectively invulnerable, when in any other situation they would be easily eliminated. As an added layer to the issue, superficial swab and culture of the mucosal surface may be completely misleading. A positive bacterial culture of the biofilm showing in vitro antibiotic sensitivity may misdirect therapy entirely. Although you’ve confirmed in vitro effectiveness of therapy in regard to your surface culture, the chosen antimicrobial will most likely miss any pathogen lying deep within the film, interstitium, or intracellular space, rendering the chosen treatment clinically moot when used in-vivo.
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Now put yourself in the shoes of the clinician. You’ve swabbed properly and sent for culture and sensitivity, then treated accordingly, but there is no clinical improvement in your patient’s state of health. So, what do you do next? What conclusions may you draw? Such a cycle of negligible response to antibiotic therapy may inappropriately perpetuate the idea of pathogen independent CRS, when in reality it should raise questions of drug choice, administration, and adjunct therapy.
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This thought process brings one particular example to mind and into question. Recently Antunes et al. showed that a Pseudomonas containing biofilm required 400 times the concentration of tobramycin to be eradicated than its control counterpart. While this finding became a warning, heeded by many, against the “ineffective” antibiotic treatment of biofilm, and even further, considered by some as the disproval of a bacterial origin of CRS, this may be a grave misunderstanding. Looking back to our foundations in pharmacology we must remember that many antibiotics have near-no activity on intracellular pathogens hiding within white or epithelial cells [6]. A fantastic real-world example of this being the aminoglycosides, like tobramycin, in particular.
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In the world of microbiology the classic model for establishing intracellular infection in vitro is achieved by introducing an aminoglycoside to the infected epithelial cell culture. Once introduced the aminoglycoside does in fact eliminate the extracellular bacteria, however counterintuitively it actually positively selects for the intracellular pathogens. This pharmacological model is well established in many fields of microbiology and Infectious Disease research, often exploited in many classic experimental algorithms, across many specialties—except, it seems, for those in the area of ENT and CRS [6]. Such an oversight may have immensely detrimental effects on the validity of conclusions drawn from an otherwise extremely important finding.
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The current paradigm of thought, that chronic rhinosinusitis has no direct infectious etiology, is further challenged by the clinical efficacy of treatment with Mupirocin lavage in CRS patients who had positive endoscopically guided cultures for Staphylococcus aureus [7]. In one recent investigation of CRS, 15 of 16 patients treated with Mupirocin-saline nasal irrigation, twice daily for 3 weeks, saw significant clinical improvement followed by a negative repeat culture for S. aureus after treatment. A follow-up double-blinded, placebo-controlled, study on 22 patients with CRS non-responsive to surgery demonstrated infection clearance in 8 of 9 patients after 1 month of mupirocin treatment [8]. Although the clinical improvement could be explained by the resolution of an acute exacerbation or the elimination of Staphylococcus super-antigens, these studies clearly challenge the current dogma of noninfectious CRS, and furthermore may directly support a pathogenic etiology of chronic sinusitis.
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3. Finding E. coli in patients chronically ill with sinusitis
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There is much left to understand and discover about the pathogenesis of CRS, from both the infectious and non-infectious standpoints, and it will be many years before we have a full grasp on the matter, if ever. In the meantime, many groups are publishing some interesting studies with very exciting results, and conclusions.
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Recently, we have reported on the importance of proper biopsy in chronic sinusitis, and how such data may influence treatment and outcomes [5]. Interestingly, the predominance of specific pathogens differs in congruence with the method of sample collection. For instance, with swab and culture bacterial growth is most commonly dominated by the classic Gram-positives implicated in sinusitis. However, when samples are collected intraoperatively, by punch biopsy, the script is flipped and a predominance of Gram-negatives, including E. coli, is found [9, 10]. Therefore, logic dictates that if antibiotic therapy targets only the classic culprits of sinusitis, with Gram-negatives present, we may be achieving an incomplete or even inappropriate eradication of microflora and pathogens. This could explain and contribute to therapeutic failure in recurrent sinusitis, its transition into chronicity, and its interpretation as noninfectious [11, 12, 13, 14, 15, 16, 17, 18, 19].
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In general, the presence of nonclassical pathogens such as Gram-negatives, namely E. coli, has been poorly documented. However, more and more groups are finding E. coli in patients chronically ill with sinusitis, and the question remains, “Are these contaminants, or are they true pathogens?”. By definition if the latter is true, and these isolated E. coli are pathogenic, there should be evidence of their ability to produce disease, through the demonstration of various virulence factors [20, 21, 22]. Alternatively, if they are non-pathogenic and represent random contamination or commensal properties then there should be no evidence of genetic markers of virulence. So far, the nature of E. coli virulence and potential for cause of CRS remains largely unknown [23, 24, 25, 26]; and while numerous studies have explored the role of virulence genes in chronic and recurrent GI and Urinary Tract infections, no such data has been available in regard to chronic sinusitis, until recently [5, 23, 24, 25].
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We recently published the first report demonstrating an association between a highly pathogenic E. coli, chronic sinusitis, and the resolution of symptoms upon E. coli targeted therapy [5]. Our findings support the theory that a non-classical pathogen may lurk below the radar in non-pharmacologically-responsive CRS and would only be detected by the use of proper techniques. When we performed intraoperative biopsy and culture on our chronic sinusitis patients, followed by genetic analysis of virulence factors, we found the presence of a clearly non-random pathogenic E. coli. These E. coli carried genes encoding multiple virulence factors, granting them the ability to produce biofilm. Upon catering our antibiotic therapy to each patient’s biopsy and culture, we were able to obtain long term resolution of symptoms. These results, as a whole, lead us to believe that there very well may be genetic uniformity amongst E. coli isolated from patients suffering from CRS. These are not randomly occurring colonizers, or opportunistic colonizers.
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3.1 Genetic analysis discover highly pathogenic E. coli in CRS
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Generally, E. coli can be grouped genetically. Commonly, commensal E. coli are placed in phylogenetic groups A or B1, while pathogenic isolates are grouped in B2 or D [27, 28]. Upon in-depth genetic analysis of these patients, we found that 77% of isolated E. coli belonged to the pathogenic phylogenetic group B2, while only 23% belonged to the commensal B1 group [5]. This is concerning, not only due to shear pathogenicity, but the numerous dangerous traits associated with the bacteria in group B2. E. coli within this group are commonly capable of iron acquisition, granting them the ability to invade cells and multiply intracellularly and even within the blood stream. This makes members of the phylogenetic group B2 particularly toxic—contributing greatly to the inflammatory process and tissue injury of chronic infection.
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Diving deeper, we find that these E. coli share many attributes with extraintestinal-pathogenic-E. coli. However, other features suggest that they might be specifically pathogenic to sinus tissue [29, 30]. One example of this tissue specificity is the sfa adhesin gene, normally associated with meningitis [31]. It is no stretch of the imagination to think that two anatomical structures, in such close proximity as the sinuses and the meninges, may be invaded through similar cytophysiological pathways. Especially by multiple bacteria with a generally enigmatic local affinity, whom happen to share virulence factors. This association needs to be explored further, but for now it is exciting to think that we may be able to better explain local affinity (tropism) to the head and neck through such mechanisms.
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Other highlights of this genetic analysis include the finding of both the hlyA and usp genes. These genes encode for the formation of bacterial toxins and are only present in highly virulent bacterial strains. In this patient group, they were present in over 70% of the E. coli isolates. By the other side of the same token, isolates were found to lack dra/afa adhesins, which are implicated in chronic and recurrent UTI and gestational pyelonephritis. Such a bold distinction may further support the idea that these isolates represent a novel subset of E. coli, with a unique genome, and possibly even tropism for the mucosa of the paranasal sinuses [32].
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Unexpectedly, there were three genes that were found in 100% of isolated E. coli from our patients. These genes were agn43, fimG/H, and fyuA [33, 34, 35, 36]. All of which are associated with UTI, and play a role in biofilm formation: agn43 assists in E. coli-E. coli self-adhesion, fimG/H codes for type 1 fimbriae allowing for E. coli to aggregate and adhere to mannose receptors on mucosal membranes, while fyuA assists in iron scavenging and is often implicated in septicemia.
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Possibly most shocking of all is that, when analyzed via a pseudo-phylogenetic tree, these genes had closely associated genetic loci, which signifies a very probable cooperation amongst them. This raises a very concerning question. Could these three genes, working together, code for some sort of “super biofilm”? This could explain how and why so many mono-therapies and empiric treatments fail to yield any improvement in patients who suffer from CRS. A biofilm of this nature would in essence be both a defensive and offensive fortification for the pathogen. A sort of moated fortress with large watch towers, never allowing antibiotics or the host immune system to penetrate it, creating an ideal environment for lingering infection and chronic inflammation.
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The resolution of CRS—following FESS, intra-operative biopsy, and antibiotic therapy targeted toward the resultant culture and sensitivity—is highly suggestive of E. coli’s strong contribution to the disease state of this patient population. Undoubtedly, this all hinges upon the genetic makeup of these bacteria, and the fact that their genetic code is set for pathogenesis by carrying the information necessary to express virulence factors, including the production of biofilm [37, 38]. Further deductive reasoning leads us to believe that, E. coli is a generally undermined and undetected etiologic factor of CRS and a major contributor of inflammation in these patients. Whether or not the presence of biofilm producing E. coli is directly responsible for the poor therapeutic response, after FESS alone, will continue to be explored in more detail [39, 40, 41, 42].
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As with all, there are limitations to this study that should be recognized. For example, the present investigation was a study of healthcare-seeking adults; only including those that were E. coli positive, raising a very important question. To what extent do these results apply to the general population? Next, due to the resolution of symptoms and subsequently negative cultures, along with consideration for cost and patient comfort, we did not perform a follow-up punch biopsy and analysis.
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4. Future studies
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Future studies should investigate the role of important factors in human health, such as the effects of hormones, like estrogen and progesterone, on chronic sinusitis [43, 44]. Which are known to control the immune system. We must also further explore the effects of obesity and diabetes mellitus on the risk of infection, as well as the relation of anatomical structure and function on the role of bacterial colonization. All of these factors change the expression of mucosal receptors, which is often exploited by various bacterial species, easing colonization and/or infection [32, 45].
\n
In regard to the possibility of hormonal control of the immune system of the upper respiratory tract, we speculate that the head and neck may be analogous to the female urogenital tract. Wherein sensitivity to infection rises during the secretory and proliferative phases of the menstrual cycle [44]. Exploring further in this direction, the anatomical structure of the upper respiratory system appears to resemble the urogenital tract in many ways. Within the urinary tract an ascending infection begins with the colonization of vaginal introitus, before migrating proximally [21]. Genital colonization with E. coli may progress to infection of the urethra, which then ascends to the bladder, and further up to the kidneys via the ureters. This is made possible through the exploitation of tissue specific receptors to which bacteria anchor via specialized adherence structures called fimbriae [46, 47]. This process of bacterial migration results in acute pyelonephritis, often followed by chronic kidney infection with even further spread to the blood stream and resultant urosepticemia [48, 49, 50]. Similarly, we implore the medical community to consider the oropharynx, nasal cavities and paranasal sinuses as another anatomical system conducive to similar ascending infections [21, 45]. Beginning with the colonization of the oral and nasal cavities, bacteria may migrate “upstream” to the maxillary and then frontal sinuses, as well as others along the way via similar receptor-ligand interaction. All of which may be complicated by anatomical variation, anomaly, and pathology, ranging from nasal polyps and turbinate hypertrophy to choanal atresia and structural issues of the sort. These problems may be caused by everything from allergy to genetic mutation—resulting in a slew of aggravating factors, expression of specialized epithelial cell types, and tissue receptors—all contributing to the risk of chronic rhinosinusitis.
\n
\n
\n
5. Considerations and conclusions
\n
All things considered, chronic sinusitis remains a bit of an enigma. However, the more we explore the better we will be able to understand the complex multifactorial etiology that’s sure to be lying below the surface. That being said, we’ve learned and discovered so much as a medical community in recent years, we believe there is no better time than now to begin making the most of it.
\n
Keeping in mind the most recent publications and studies, we urge physicians to consider intraoperative punch biopsy on all of their chronic sinusitis patients [5]. Biopsied samples should be homogenized, and host cells should be exposed to membrane destabilizing buffers, lysing them and releasing trapped intracellular bacteria, allowing for the most thorough culture and analysis. Considering that a direct culture of the sample on solid media may not always be fruitful, we recommend the use of liquid media which may better allow the growth and detection of bacteria, even at low numbers. Next, cultures should be tested individually for antibiotic sensitivity and a personalized therapy should be prescribed to each individual patient. Finally, we also urge you to consider sending bacterial isolates for genotyping [35, 48, 51, 52, 53, 54, 55, 56, 57]. Through doing so we can finally stop asking of ourselves if we’re fighting the right bug and know for certain that if it expresses virulence it is part of the problem.
\n
We believe that through the use of these methods we may be able to better differentiate between specific etiologies of CRS within our patients, and through doing so we hope that we can avoid inappropriate antibiotic use, repeat surgeries, and prolonged treatment. Giving our patients their health and quality of life back faster and more effectively than ever.
\n
In conclusion, we hope that personalized medicine may one day overshadow empiric treatment in chronic sinusitis, and all of our patients will be catered to with the utmost efficiency. With further testing and experimentation, we may be able to someday use vaccines or bacterial adhesion blockers to augment our therapies [30, 58]. Using genotyping to pick and choose what’s best for our patients, we may be able to target specific virulence factors that allow such abilities as iron binding or cellular adherence, effectively rendering those bacterial invaders non-pathogenic. Through interdisciplinary exploration we may be able to adopt and adapt what other specialties have learned and use it to restore mucosal and micro-floral balance, and band together to fight bacteria and biofilm together as a medical community.
\n
\n
Acknowledgments
\n
We thank you Nowicki Institute for Women’s Health Research, Nashville, Tennessee, USA for support.
\n
\n
Conflict of interest
\n
Authors declare no conflict of interest.
\n
\n',keywords:"chronic sinusitis, rhinosinusitis, E. coli, biofilm, genotype, virulence factors, antibiotic treatment, antibiotic resistance, biopsy",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/65465.pdf",chapterXML:"https://mts.intechopen.com/source/xml/65465.xml",downloadPdfUrl:"/chapter/pdf-download/65465",previewPdfUrl:"/chapter/pdf-preview/65465",totalDownloads:841,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:38,impactScoreQuartile:2,hasAltmetrics:0,dateSubmitted:"October 22nd 2018",dateReviewed:"January 9th 2019",datePrePublished:"February 11th 2019",datePublished:"December 4th 2019",dateFinished:"February 4th 2019",readingETA:"0",abstract:"Chronic sinusitis leads to unresolved infection and inflammation resulting in tissue remodeling, then further propagates the vicious cycle of deterioration and dysfunction of the sinuses’ natural defense mechanisms, and yet another cycle of infection and mucosal injury. Antibiotic therapy targeting pathogens classically implicated in sinusitis could augment the risk of therapeutic failure through the natural selection of resistant and/or virulent pathogens, especially in the presence of Gram-negative E. coli. Our recent demonstration of highly pathogenic E. coli, detected through intraoperative biopsy of sinus tissue, allowed the resolution of chronic sinusitis symptoms upon E. coli targeted therapy. The isolated E. coli carried three genes, each coding biofilm formation, which may, in part, account for the chronicity of E. coli sinusitis. We recommend that, patients with chronic sinusitis be considered for intraoperative biopsy for unusual pathogens, therefore allowing targeted therapy. In the future, use of vaccines and biofilm inhibitors might be an effective therapeutic consideration.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/65465",risUrl:"/chapter/ris/65465",book:{id:"7062",slug:"rhinosinusitis"},signatures:"Alexander Nowicki, Natalie Nowicki, Stella Nowicki, Alfred Samet, Michal Michalik, Roger Su, James K. Fortson and Bogdan Nowicki",authors:[{id:"281641",title:"Prof.",name:"Bogdan",middleName:null,surname:"Nowicki",fullName:"Bogdan Nowicki",slug:"bogdan-nowicki",email:"bnowicki1949@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"290331",title:"Dr.",name:"Alexander",middleName:null,surname:"Nowicki",fullName:"Alexander Nowicki",slug:"alexander-nowicki",email:"alexnowicki3@aim.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"290332",title:"Dr.",name:"Natalie",middleName:null,surname:"Nowicki",fullName:"Natalie Nowicki",slug:"natalie-nowicki",email:"natalie.nowicki@pop.belmont.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"290333",title:"Prof.",name:"Stella",middleName:null,surname:"Nowicki",fullName:"Stella Nowicki",slug:"stella-nowicki",email:"President@nowickiinstitute.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"290334",title:"Dr.",name:"Alfred",middleName:null,surname:"Samet",fullName:"Alfred Samet",slug:"alfred-samet",email:"dr.alfredsamet@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"290335",title:"Dr.",name:"Roger",middleName:null,surname:"Su",fullName:"Roger Su",slug:"roger-su",email:"rwsumd@acraef.org",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"290336",title:"Dr.",name:"James K.",middleName:null,surname:"Fortson",fullName:"James K. Fortson",slug:"james-k.-fortson",email:"jkfortson1@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"294104",title:"Dr.",name:"Michał",middleName:null,surname:"Michalik",fullName:"Michał Michalik",slug:"michal-michalik",email:"michalim@wp.pl",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 Is CRS directly caused by infectious agents?",level:"2"},{id:"sec_3",title:"2. Is a healthy sinus cavity free of bacteria?",level:"1"},{id:"sec_3_2",title:"2.1 Alternative thesis: CRS involves direct bacterial infection",level:"2"},{id:"sec_5",title:"3. Finding E. coli in patients chronically ill with sinusitis",level:"1"},{id:"sec_5_2",title:"3.1 Genetic analysis discover highly pathogenic E. coli in CRS",level:"2"},{id:"sec_7",title:"4. Future studies",level:"1"},{id:"sec_8",title:"5. Considerations and conclusions",level:"1"},{id:"sec_9",title:"Acknowledgments",level:"1"},{id:"sec_9",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Kennedy JL, Borish L. Chronic rhinosinusitis and antibiotics: The good, the bad, and the ugly. The American Journal of Rhinology and Allergy. 2013;27(6):467-472. DOI: 10.2500/ajra.2013.27.3960'},{id:"B2",body:'Antunes MB, Feldman MD, Cohen NA, Chiu AG. Dose-dependent effects of topical tobramycin in an animal model of Pseudomonas sinusitis. American Journal of Rhinology. 2007;21:423-427'},{id:"B3",body:'Abreu NA, Nagalingam NA, Song Y, Roediger FC, Pletcher SD, Goldberg AN, et al. Sinus microbiome diversity depletion and Corynebacterium tuberculostearicum enrichment mediates rhinosinusitis. Science Translational Medicine. 2012;4:151ra124'},{id:"B4",body:'Ma B, Forney LJ, Ravel J. Vaginal microbiome: Rethinking health and disease. Annual Review of Microbiology. 2012;66:371-389. DOI: 10.1146/annurev-micro-092611-150157'},{id:"B5",body:'Michalik M, Samet A, Marszałek A, Krawczyk B, Kotłowski R, Nowicki A, et al. Escherichia coli that carry fimG/H, fyuA and agn43 genes coding biofilm formation. 2018;13(3):e0192899. DOI: 10.1371/journal.pone.0192899.e. Collection 2018'},{id:"B6",body:'Rana T, Hasan RJ, Nowicki S, Venkatarajan MS, Singh R, Urvil PT, et al. Complement protective epitopes and CD55-microtubule complexes facilitate the invasion and intracellular persistence of uropathogenic Escherichia coli. Journal of Infectious Diseases. 2014;209(7):1066-1076'},{id:"B7",body:'Uren B, Psaltis A, Wormald PJ. Nasal lavage with mupirocin for the treatment of surgically recalcitrant chronic rhinosinusitis. Laryngoscope. 2008;118:1677-1680'},{id:"B8",body:'Jervis-Bardy J, Boase S, Psaltis A, et al. A randomized trial of mupirocin sinonasal rinses versus saline in surgically recalcitrant staphylococcal chronic rhinosinusitis. 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Familial risk of chronic rhinosinusitis with and without nasal polyposis: Genetics or environment. International Forum of Allergy and Rhinologyis. 2015;5(4):276-282'},{id:"B15",body:'Soler ZM, Mace JC, Litvack JR, Smith TL. Chronic rhinosinusitis, race, and ethnicity. American Journal of Rhinology and Allergy. 2012;26(2):110-116'},{id:"B16",body:'Lam K, Schleimer R, Kern RC. The etiology and pathogenesis of chronic rhinosinusitis: A review of current hypotheses. Current Allergy and Asthma Reports. 2015;15(7):41'},{id:"B17",body:'Stephenson MF, Mfuna L, Dowd SE. Molecular characterization of the polymicrobial flora in chronic rhinosinusitis. Journal of Otolaryngology–Head and Neck Surgery. 2010;39:182-187'},{id:"B18",body:'Stressmann FA, Rogers GB, Chan SW. Characterization of bacterial community diversity in chronic rhinosinusitis infections using novel culture-independent techniques. The American Journal of Rhinology and Allergy. 2011;25:e133e140'},{id:"B19",body:'Hamad WA, Matar N, Elias M. Bacterial flora in normal adult maxillary sinuses. American Journal of Rhinology and Allergy. 2009;23:261-263'},{id:"B20",body:'Nowicki B, Sledzinska A, Samet A, Nowicki S. Pathogenesis of gestational UTI: Urinary obstruction vs. immune adaptation and microbial virulence. BJOG: An International Journal of Obstetrics and Gynaecology. 2011;118(2):109-112'},{id:"B21",body:'Nowicki B. In vitro models for the study of uropathogens. In: Mobley HLT, Warren JW, editors. Urinary Tract Infection: Molecular Pathogenesis to Clinical Management. Washington, DC: American Society for Microbiology; 1996. pp. 341-376'},{id:"B22",body:'Spaulding CN, Hultgren SJ. Adhesive pili in UTI pathogenesis and drug development. Pathogens. 2016;5(1):30. ASM Press. pp. 341-369'},{id:"B23",body:'Kremer B, Jacobs JA, Soudijn ER, Johannes A, van der Ven AM. Clinical value of bacteriological examinations of nasal and paranasal mucosa in patients with chronic sinusitis. European Archives of Oto-Rhino-Laryngology. 2001;258(5):220-225'},{id:"B24",body:'AlMutairi D, Kilty SJ. Bacterial biofilms and pathophysiology of chronic rhinosinusitis. Current Opinion in Allergy and Clinical Immunology. 2011;11:18-23'},{id:"B25",body:'Foreman A, Psalitis AJ, Tan LW, Wormald PJ. Characterization of bacterial and fungal biofilms in chronic rhinosinusitis. American Journal of Rhinology and Allergy. 2009;23(6):556-561'},{id:"B26",body:'Ferguson BJ, Stolz DB. Demonstration of biofilm in human bacterial chronic rhinosinusitis. American Journal of Rhinology. 2005;19(5):452-457'},{id:"B27",body:'Kotłowski R, Bernstein CN, Sepehri S, Krause DO. High prevalence of Escherichia coli belonging to the B2+D phylogenetic group in inflammatory bowel disease. Gut. 2007;56:669-675'},{id:"B28",body:'Johnson JR, Stell AL, Delavari P, Murray AC, Kuskowski M, Gaastra W. Phylogenetic and pathotypic similarities between Escherichia coli isolates from urinary tract infections in dogs and extraintestinal infections in humans. The Journal of Infectious Diseases. 2001;183:897-906'},{id:"B29",body:'Goluszko P, Moseley S, Truong LD, Kaul A, Nowicki S, Nowicki B. Development of experimental model of chronic pyelonephritis with Escherichia coli O75:K5:H—bearing Dr fimbriae: Mutation in the dra region prevented tubulointerstitial nephritis. The Journal of Clinical Investigation. 1997;99:1-11'},{id:"B30",body:'Kostakioti M, Hadjifrangiskou M, Hultgren SJ. Bacterial biofilms: Development, dispersal, and therapeutic strategies in the dawn of the postantibiotic era. Cold Spring Harbor Perspectives in Medicine. 2013;3(4):1-23'},{id:"B31",body:'Nowicki B, Vuopio-Varkila J, Viljanen P, Korhonen T, Makela PH. Fimbrial phase variation and systemic E. coli infection studied in mouse peritonitis model. 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Differences in the paranasal sinuses between germ-free and pathogen-free mice. International Forum of Allergy and Rhinologyis. 2016;6(6):631-637'},{id:"B41",body:'Radtsig EY, Selkova EP, Malygina LV, Lapitskaia AS. The role of respiratory viruses in etiology of rhinosinusitis in the children. Vestnik Otorinolaringologii. 2014;6:39-40'},{id:"B42",body:'Beule AG. Epidemiology of chronic rhinosinusitis, selected risk factors, comorbidities and economic burden. Laryngo-Rhino-Otologie. 2015;94(Suppl 1):S1-S23'},{id:"B43",body:'Kaul A, Goluszko PG, Hart A, Martens M, Pham T, Nowicki S, et al. Rapid cycle changes in density and accessibility of endometrial ligands for Escherichia coli Dr fimbriae. Infection and Immunity. 1996;64:611-615'},{id:"B44",body:'Nowicki B, Nowicki S. CD55 as a therapeutic target for steroid hormones: Implications for host pathogen interaction: In: Lambris JD, Holers VM, Ricklin D, editors. 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Evaluation of a PCR melting profile technique for bacterial strain differentiation. Journal of Clinical Microbiology. 2006;44:2327-2332'},{id:"B53",body:'Clermont O, Bonacorsi S, Bingen E. Rapid and simple determination of the Escherichia coli phylogenetic group. Applied and Environmental Microbiology. 2000;66:4555-4558'},{id:"B54",body:'Adamus-Białek W, Wojtasik A, Majchrzak M, Sosnowski M, Parniewski P. (CGG)4 based PCR as a novel tool for discrimination of uropathogenic Escherichia coli strains: Comparison with enterobacterial repetitive intergenic consensus PCR. Journal of Clinical Microbiology. 2009;47:3937-3944'},{id:"B55",body:'Johnson JR, Brown JJ, Carlino UB, Russo TA. Colonization with and acquisition of uropathogenic Escherichia coli as revealed by polymerase chain reaction-based detection. The Journal of Infectious Diseases. 1998;177:1120-1124'},{id:"B56",body:'Krawczyk B, Śledzińska A, Piekarska A, Hellmann A, Kur J. Recurrent bowel-blood translocations of Escherichia coli with the unique virulence characteristics over three-year period in the patient with acute myeloid leukaemia—Case report. Journal of Applied Genetics. 2017;58(3):415-418'},{id:"B57",body:'Nowak-Zaleska A, Wieczór M, Czub J, Nierzwicki Ł, Kotłowski R, Mikucka A, et al. Correlation between the number of Pro-Ala repeats in the EmrA homologue of Acinetobacter baumannii and resistance to netilmicin, tobramycin, imipenem and ceftazidime. Journal of Global Antimicrobial Resistance. 2016;7:145-149'},{id:"B58",body:'Mobley HLT, Alteri CJ. Development of a vaccine against Escherichia coli urinary tract infections. Pathogens. 2016;5(1):1'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Alexander Nowicki",address:null,affiliation:'
Washington University of Health and Science, Nowicki Institute for Women’s Health Research, USA
Nowicki Institute for Women’s Health Research, USA
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1. Introduction
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Life cycle assessment (LCA) is the quantification of potential environmental impacts and the resource use throughout a product’s life cycle: from raw material acquisition, via production and use phases, to waste management [1]. It has been frequently applied by consultants, researchers, industry, and authorities for the past 30 years. It has proven useful for gaining knowledge on the life cycle, for communication of environmental information, and for various kinds of decision-making.
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Meanwhile, it was clear almost from the start that results from different LCAs can contradict each other. This is still true, despite many attempts to harmonize, standardize, and regulate LCA. From history, we learn that it is not realistic to expect LCA to deliver a unique and objective result. It should not be regarded as a single unique method; it is more fruitful to consider it a family of methods.
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Attributional LCA (ALCA) and consequential LCA (CLCA) are important groups within this family of methods. The choice between ALCA and CLCA guides other methodological decisions in the LCA, such as the choice of input data and the modeling of processes with multiple products. However, within ALCA and CLCA, there are still many decisions to be made—many versions or members within each group in the LCA family.
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The purpose of this chapter is to discuss and clarify key concepts in relation to ALCA and CLCA and to guide the reader through the necessary and subjective methodological choices. The example used often relates to the supply of electricity in the life cycle, because much of the methodological debate has been on how to model electricity. The chapter is still relevant to all kinds of LCA, because energy supply is part of virtually all LCAs and because most of the discussion is valid also for modeling other parts of the life cycle. Furthermore, the chapter is relevant to other, similar types of quantitative environmental and sustainability assessments—for example, carbon footprint, which essentially is an LCA except that it is limited to emissions of greenhouse gases [2].
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To structure the discussion on the pros and cons of different methodological choices, I start by establishing a set of criteria for what an LCA, or a quantitative environmental systems analysis in general, should be and do (Section 2). The ALCA and CLCA approaches are outlined in Section 3, and their implications for the choice of data and allocation problems are discussed in some detail in Sections 4 and 5, respectively. Section 6 includes an assessment of the two approaches based on previous discussions. The chapter concludes with a few recommendations for the LCA practitioner.
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The LCA methodology is diverse, and the interpretation of the key concepts also varies between researchers. This chapter presents my view on the matter, which is subjective but based on knowledge gained from more than three decades of research in LCA and energy systems analysis. I present my arguments for this view but leave it to you, the reader, to accept my view or to choose another perspective.
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2. Criteria for methods in environmental systems analysis
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Environmental systems analysis is different from traditional science in that the aim is not just to systematically gather knowledge; it has the specific aim to gather and communicate knowledge that results in actions that reduce the negative environmental impacts of human activity in total or at least per functional unit, that is, per unit of utility that the studied system generates. The more a method for environmental assessments can be expected to contribute to this purpose, the better it is.
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For a method to benefit the environment, it must be possible to apply. The results need to be reasonably accurate, possible to communicate, and perceived as relevant by decision-makers (Figure 1). Furthermore, the method should be resistant against abuse. Each of these criteria is briefly discussed below.
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Figure 1.
Criteria for assessing methods for environmental assessment and their role in shaping decisions that are good for the environment (based on Ekvall et al. [3]).
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Different methods meet the criteria to varying degrees, but no method is ideal from all aspects. There will always be a trade-off between, for example, feasibility and accuracy. Hence, the set of criteria is not sufficient as a tool for objective selection of the best methods; however, it can be used for structured discussions on the pros and cons of available methods.
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2.1 Feasible
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To have any effect, the method must be used. The more often it is used, the more results it will generate. How often environmental assessments are made depends on how useful the results are (see Section 2.2–2.4). But it also depends on how easy the methods are to apply and how expensive the studies become. This in turn depends on how complex the methods are and on the extent to which the data and models needed are available. The method becomes more cost-efficient and can potentially have a greater impact if the results and conclusions it generates can be generalized and reused in multiple decision situations. Hence, the method should ideally be easy and cheap to apply and generate results and conclusions that can be generalized.
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2.2 Accurate
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An environmental assessment is sometimes designed to guide a specific decision. To have a positive effect, the results must guide such decisions in the right direction more often than not. The greater the chance that results will point in the right direction, the better. Hence, the method should ideally generate results that are as comprehensive, accurate, and precise as possible.
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2.3 Comprehensible
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Besides guiding specific decisions, an environmental assessment can contribute to increasing the knowledge of experts and decision-makers. If accurate, such knowledge not only contributes to deliberate immediate actions but can also have a positive impact on future decisions. To educate decision-makers and other stakeholders, the environmental assessment must be transparent and possible to understand. Decision-makers receive a large amount of information and have limited capacity for information processing. For this reason, the method and the results it generates should be easy to communicate and understand. Communication is easier when the concepts used in the method are clear and intuitively easy to understand. Communication is more challenging when the study is very comprehensive or conceptually complex. Hence, the method should ideally result in studies that are transparent, have a simple structure, and use intuitively clear concepts.
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2.4 Inspiring
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In order for environmental assessment to have a positive effect, the information and knowledge they generate must result in actions. Decision-makers often have conflicting goals, and decisions are often not rational in the sense that they are based on documented facts only. To convince and inspire decision-makers, the study should be perceived as relevant, legitimate, and credible and the recommendations clear. A study can be perceived as more relevant if it focuses on things that the decision-makers can influence and/or have a clear connection to. Legitimacy increases if the study is perceived as impartial and fair. Credibility can be obtained, for example, through sensitivity analyses. The conclusions and recommendations are clear when the uncertainties are not too great.
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Relevance and legitimacy are highly subjective. They both increase if the design of the study accounts for the need for knowledge as perceived by the decision-makers. This means that the choice of methods should ideally be adapted to the situation and may vary depending on the decision-makers involved.
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2.5 Robust
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Robustness here means that the method gives roughly the same results regardless of who applies it. This makes the method more difficult to abuse, that is, to apply in environmental assessments with the purpose to stop or delay decisions with positive consequences for the environment or to defend decisions with poor consequences. The method becomes more robust if it does not require the user to make assumptions or subjective choices that greatly affect the results. It is also more robust if there are detailed guidelines for how the method is to be applied and/or an established good practice for the application.
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3. Attributional and consequential LCA respond to different questions
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As clear from the Introduction, we can distinguish between ALCA and CLCA. The distinction between two types of LCA was suggested in the beginning of the 1990s [4, 5]. It was established toward the end of the decade [6] to resolve debates on what type of input data to use in LCAs (cf. Section 4) and on how to deal with the allocation problems that occur when, for example, a process produces more than one type of product (Section 5). Various names were used on the two types of LCA [7], but the terms attributional/consequential have been used since 2001 [8].
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Several different definitions of attributional and consequential LCA have been suggested [9, 10]. I prefer the definitions of Finnveden et al., in what is probably the most cited scientific paper on LCA [11]:
Attributional LCA: LCA aiming to describe the environmentally relevant physical flows to and from a life cycle and its subsystems
Consequential LCA: LCA aiming to describe how environmentally relevant flows will change in response to possible decisions
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These definitions clearly connect ALCA/CLCA not only to methodological choices but also to the goal of the study, because they respond to different questions (Figure 2). An ALCA gives an estimate of how much of the global environmental impact belongs to the product studied. A CLCA gives an estimate of how the global environmental impact is affected by the product being produced and used.
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Figure 2.
Illustration of accounting and consequence LCA (based on Weidema [12]). The large circles symbolize the total environmental burdens of the world.
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Note that the latter can include both increases and reductions in the environmental impact. It is not unusual that an increase in the production of a product leads to increases in emissions as well as to environmental benefits. The production of district heating in a combined heat-and-power (CHP) plant in Sweden, for example, generates emissions from the CHP plant but reduces emissions in other parts of the electricity system, when electricity from the power plant replaces other electricity production.
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There are thus two types of LCAs, carbon footprints, etc.:
Attributional assessments, which give an estimate of what part of the global environmental burdens belongs to the study object
Consequential assessments, which give an estimate of how the production and use of the study object affect the global environmental burdens
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The choice between ALCA and CLCA affects system boundaries. In the example of district heating from a CHP plant, a CLCA includes both the emissions from the CHP plant and the reduction in emissions from the electricity production displaced by electricity from the CHP plant. In general, when a production process delivers more than one type of products, the CLCA should take into account how the process is affected by a change in the of the product investigated. If it affects the production of other products from the process, the system should be expanded to include the effect of that change.
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A more advanced CLCA can also include other types of consequences. An increased use of a material in the studied system can, for example, lead to less material being used in other systems. This reduction can be quantified with a partial equilibrium model of the market [13]. The alternative use most likely to be affected can be identified through an econometric analysis [14].
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An investment in a relatively new energy technology can contribute to improvements in that technology and thus to more such investments being made in the future. Such an indirect effect can in some cases be very large [15]. In an advanced CLCA, the effect could be roughly estimated using an energy system model with so-called experience curves [16].
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An ALCA, in contrast, does not include environmental benefits or other indirect consequences that arise outside the life cycle of the investigated product. Instead, the raw material use and emissions of a co-production process are partitioned between the products of that process. In the cogeneration example above, the environmental burdens of the CHP plant are divided between the electricity and the heat. Such a partitioning is called allocation and can be done in several different ways (see Section 5.1).
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The choice between attributional and consequential LCA also affects the choice of input data to the calculations. An ALCA estimates how much of the world’s environmental impact belongs to a product. If electricity is used in the product’s life cycle, the calculations must include the product’s share of the environmental burdens of the electricity production system. This is calculated by multiplying the product’s electricity consumption by the average environmental burden of the electricity system per unit of electricity delivered. The figures describing the average environmental burdens are called average data. The electricity described by these average data is called average electricity.
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Average data is used not only to model electricity production in ALCA. If the product investigated contains steel, average data is used to model steel production. The same applies to other input goods. In order to calculate the average environmental impact of a production system, the boundaries of the production system must be defined. This can also be done in different ways (see Section 4.1).
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A CLCA aims to generate information on how the study object affects the environmental burdens of the world. If electricity is used in the system investigated, the CLCA should include data that reflects how the environmental burdens of the electricity production system are affected by this electricity use. In a few cases, the system investigated has a significant impact on the electricity production—for example, in a study of a future electric car fleet. In such cases, the CLCA should ideally be based on input data that reflects how such a large change in production volume would affect the production system’s environmental burdens. Such data are called incremental data. With incremental data, the environmental burdens per kWh electricity often depend on the size of the change in power generation (compare the slope of the two lines representing incremental data in Figure 3).
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Figure 3.
Illustration of average data, incremental data, and marginal data (based on Azapagic and Clift [17]).
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In most cases, however, the electricity use in the system investigated is so small it has only a marginal impact on the electricity system. A change can be described as marginal when it occurs within a range where the environmental burdens as a function of the production interval can be approximated with a straight line (see Figure 3). Within this range, the slope of the line represents the approximate increase in environmental burdens per unit increase of electricity produced. Since the line is straight, the environmental impact per kWh is approximately constant, and the environmental impact of an additional electricity demand is proportional to the size of this demand. Data that reflects the environmental impact per kWh change within this range is called marginal data. The electricity described by marginal data is called marginal electricity.
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A CLCA should, if possible, include marginal data not only on electricity production but also on the production of other inputs where the study object only has a marginal impact on the total production volume. There are different types of marginal effects and different ways of identifying marginal production. This is further discussed in Section 4.2.
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A CLCA can be made to describe and estimate the consequences of a given decision but also to investigate what a specific decision-maker can influence. If this decision-maker can completely shut down or replace a production system, the CLCA should include the entire production system. The environmental burdens per unit produced in this system are then the total burdens of the system divided by the total product output. This is identical to the average data.
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4. The choice of average and marginal data
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If marginal or average data are to be used in the LCA depends on whether the study is attributional or consequential, as discussed above. However, there are several types of average and marginal data. The next question to ask is therefore what average or marginal values should be used as input in the calculations.
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4.1 The average of what?
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An ALCA is based on average data on the production systems in the product life cycle. In order to calculate the average environmental impact of the production systems, they must be identified, and their boundaries must be defined.
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When the supplier of a material or component is known, this supplier is linked to the product through contracts and through the economic and physical flows resulting from the contracts. Established good ALCA practice is then to use as specific data as possible. These are data representing the average environmental performance of the supplier or, when possible, of the individual processes in the production plant.
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In many cases the supplier is unknown, for example, because the product is not yet being produced or because the material or component is bought on a market where the actual supplier shifts over time. Here, established ALCA practice is to use average data for the relevant geographical area. Ideally, this is the area from where the good is bought and/or the area covered by the market, which might be global or regional.
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Energy carriers like electricity, gas, or district heat are distributed in networks. When the suppliers are known, there are contractual links and economic flows to the supplier, but there is no clear physical flow from the production process to the user. If the contract specifies the producer, it is rather uncontroversial to use data representing a weighted average over the production plants that the supplier has in the network.
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Contracts might also specify that the electricity bought is produced with a specific technology, such as wind power. In such cases, it is reasonable to use data for wind power in the ALCA. To be more specific, it is reasonable to use average data for the wind power of the producer or supplier to which the contract applies. If the deal is on wind power from a specific plant or site, average values for that plant/site should ideally be used. Of course, similar rules apply if the contract specifies that the electricity is hydro or some other specific technology, or green electricity in general.
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When the electricity supplier is unknown, many influential LCA guidelines (e.g., [18, 19, 20]) recommend the use of national average data or, for very large countries, average data for regional electricity grids. This might be because electricity supply has traditionally been a responsibility of national authorities. For the past decades, electricity production has been privatized in many countries, power producers have become international companies (e.g., EDF, Vattenfall, E.ON), electricity grids have become more integrated nationally and between countries, and electricity trade and transfer between countries have increased. This means that most electricity systems are no longer isolated national or regional grids. There are strong arguments for using average data for a larger geographical area instead. However, there are various ways to define this area. I here discuss them with a focus on Northern Europe, where I have my expertise:
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Although production of electricity is increasingly privatized, the electricity sector is still to a large extent regulated by national authorities. One way to defend the use of national average data is to define the electricity system by the geographical scope of regulating authorities. Note, though, that electricity production is affected not only by national authorities but also by local authorities and by international cooperation, for example, within the European Union (EU).
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Another approach is to define the geographical area by the electricity market. Since the establishment of the Nordic electricity exchange, NordPool, there is a well-established Nordic market, and the corresponding electricity system is often perceived as Nordic, including Sweden, Norway, Denmark, and Finland. As NordPool expands and the transmission capacity to other parts of northern Europe increases, it becomes increasingly relevant to regard the market as North European. There is also an EU directive aiming toward a common European electricity market, with provisions to remove bottlenecks in the electricity transfer between countries. In the future, the electricity market may be described as pan-European.
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The electricity system can also be defined based on physical facts, for example, the transmission capacity between or within countries. This can be insufficient at times when a lot of electricity is produced at one place and used elsewhere. As a result, there will often be a difference in electricity price, for example, between North and South Sweden and between North and South Germany. The boundaries of the system can be defined where the transfer of electricity is limited by the transfer capacity in the grid, for example, between northern and southern Germany.
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Alternatively, the electricity system can be defined as the area where the electricity network is synchronized, allowing for transfer of electricity without conversion to direct current. Conversion of electricity is a bottleneck because it is associated with energy loss. Based on this physical bottleneck, a system boundary is between Jutland and Zealand in Denmark, where the former is synchronized with continental Europe but the latter with the rest of Scandinavia.
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Regardless of the geographical boundaries of the electricity system, the question remains as to whether data should apply to the average of the electricity produced in this area or whether they should apply to the average of the energy used in the area. In the latter case, imports and exports of electricity must be accounted for in the calculation of the average.
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4.2 What marginal impacts?
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The difference between short- and long-term marginal effects is important in a CLCA [13]. The distinction between short and long term is well-established within economic theory. Short-term effects in economics are effects on the utilization of existing production capacity that occurs before the production capacity has been able to adapt to, for example, a change in demand. The capacity itself is thus assumed to be unaffected in a short-term perspective.
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When long-term effects are examined, the production capacity is assumed to completely adapt to the change in demand, to the extent that the risk of capacity shortage is the same as before the change. For the production of most goods, this means that the utilization rate of the capacity is assumed not to change. However, for electricity the long-term marginal effect of increased electricity use may include the construction of, for example, new wind turbines that have lower utilization rates than other power plants. This reduces the total utilization rate in the electricity system, although the risk of capacity shortage is unchanged.
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If the electricity use in the life cycle is small, the probability is very small that it will affect the energy system’s production capacity. Electricity for lighting in a single house is, for example, a drop in the sea, compared to the total production capacity of the electricity system. The sea, on the other hand, does not consist of much else than drops. If a change in the lighting of a house happens to be what triggers an investment in a new power plant, the effect of the lighting becomes much greater than the electricity demand of the lighting. The long-term marginal effect is calculated as the expected value, i.e., the small probability times the large outcome. This expected value is 1 kWh/year changed production capacity per kWh/year change in the consumption of electricity.
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The short- and long-term marginal effects can be difficult to communicate, as they are easily confused with the effects of changes made in the near or far future. However, short-term effects can arise far into the future, and long-term effects can occur in the coming decades. As an example, the long-term marginal technologies in 2020 are the technologies whose production capacity is affected by energy use in 2020. These effects may occur in 2025–2035. Meanwhile, the short-term marginal effects in 2050 relate to how a change in energy use in 2050 affects the utilization of the production facilities that exist in 2050. These effects occur during that same year and the years immediately thereafter. Short-term marginal effects of a disruption in 2050 thus arise later than the long-term effects of a disruption in 2020.
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To make communication easier, the concepts short- and long-term marginal effects are sometimes replaced by “operating” and “built” margins. A draw-back of this terminology is that the term built margin is somewhat misleading: changes in production capacity are not always the construction of new facilities; it may instead be the closure of existing production facilities. The long-term marginal effects of a change in energy use in the year 2020 can include technologies in energy plants that are constructed during the period 2025–2035, but they can also include technologies in energy plants that are shut down during the years 2020–2030.
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Which concepts to use depends on the context. In communication with the general public, the rough meaning of the concepts should be easily understood. Operating and built margin are good terms to use in this context. In communication with researchers in the field, however, the precision of the concepts is important. Then it is probably better to talk about short- and long-term effects. In communication with policy-makers and professional actors in the industry, the appropriate choice of words may depend on the situation and the level of knowledge of the audience.
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Changing demand for a product often gives rise to both short- and long-term marginal effects: the utilization rate is affected first, and after a while the change also contributes to new power plants being built or old ones being shut down. Changing demand can also affect investments in several different technologies, and these investments can in turn affect both the utilization rate of existing plants and other, future investments. This means that the full marginal effect is complex. The complex margin in an energy system can be estimated in an optimizing, dynamic model that can account for both the short-term and long-term margin changes [21]. The complex marginal effect is then defined as the difference between the results of two model runs: one with the change in energy demand and one without it.
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The complex margin is, in theory, the most correct to use for CLCAs whether the possible decisions involve changes in the short term (e.g., putting out a lamp) or the long term (e.g., changing the heating system in the house). This is because even short-term changes can produce long-term marginal effects. Investment decisions are based on assessments of the future demand and price of the product. These assessments are, in turn, affected by the current market situation. If we increase electricity consumption this year, we might contribute to investment decisions being taken next year or the year after that.
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In practice, the complex marginal effects are very difficult to estimate. It requires model calculations over the relevant time period. Model runs suggest that this time period never ends, because indirect effects occur when new production plants must be replaced far into the future [21]. Unfortunately, the uncertainty very far into the future is too great for modeling to be meaningful. The choice of time horizon in the model is subjective and depends on the time resolution in the model. If each year is modeled as a single or a handful of time slots, the model usually extends a couple or a few decades into the future [21, 22, 23, 24]. An hour-by-hour model is more likely to cover just a single year [25], although it can still be possible to model a few years where each model year represents, for example, a decade [26].
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Identifying marginal effects with an energy system model requires special expertise. There are rarely resources to develop an energy system model within the framework of a specific LCA. With the right expertise, the marginal effects can be studied in an existing model. It is, of course, even easier to use results from published model runs as a basis for assumptions about the marginal effects. Assumptions about marginal effects of electricity use in Sweden can be based on results from, for example, Hagberg et al. [26]. However, the simpler the method used to generate complex marginal data, the greater the risk that they do not reflect the marginal effects caused by the specific electricity use being studied.
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Perhaps the biggest problem is that the uncertainty in complex marginal data is extremely large. Optimizing dynamic energy systems models indicate that the complex marginal effects of Swedish electricity use vary greatly depending on assumptions on, for example, investment costs, future fuel prices and policy instruments—where the two latter are highly uncertain [21]. Completely different marginal effects can occur in a single electricity scenario, depending on whether the expansion of wind power in the scenario is assumed to be driven by an increased electricity demand or by other motives [26]. A small change in the use of district heating can change the optimum development of an entire district heating system completely [24]. This illustrates that the actual effects of a small change in demand are and will remain basically unknown. An optimizing dynamic systems model can remind us of the great uncertainty, but not give much knowledge of the actual marginal effects.
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Referring to the criteria in Section 2, input data on complex marginal effects make the CLCA results more accurate, but just a little—particularly if these data are from previously published model runs. Generating case-specific complex marginal data leads to a method that is difficult to use. The use of complex marginal data also makes the study less comprehensible: it is a challenge to explain marginal results from an energy system model. This makes it more difficult for decision-makers to assess the relevance and validity of the results.
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If complex marginal effects are to be introduced at all in a CLCA depends on the context. In many cases, it is probably better to use a method that is easier to use and explain. The LCA practitioner and the decision-makers should then be aware that the method used is simplified and that the actual marginal effects remain unknown.
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A simplified method can be limited to focusing on short- or long-term marginal effects only. Since investment and closure decisions have consequences for the environment during a long time, such effects are typically more important for the environment than changes in the use of existing production capacity. In other words, the long-term marginal effects are typically more important for the environment than the short-term marginal effects [13].
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In some cases, however, a change in demand cannot be expected to have any effect at all on the production capacity. This applies if the existing production system has a significant overcapacity and closure of existing plants is not a reasonable option. It also applies if the production capacity is expanded for political or other strategic reasons, rather than to cover an expected demand for the product. A change in current Swedish electricity use might, for example, not have any effect on new investment decisions, because there is an overcapacity in the North European electricity system and because wind and solar power is still being expanded for policy and strategic business reasons. On the other hand, a change in electricity use can contribute to keeping electricity prices up or down, which can make decisions on continued investments more or less difficult. There is also a long-term political ambition to phase out coal and nuclear power. A change in electricity demand can contribute to a quicker or slower closure of such power plants. This discussion reminds us that the actual marginal effects are difficult to foresee. Different assumptions are possible, even if the environmental assessment is limited to long-term marginal effects.
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Another way to simplify things is to use the five-step procedure presented by Weidema et al. [27] to identify the production technology that is affected by a marginal change in demand. This procedure involves responding to five questions:
Is short or long term the relevant time perspective?
What market is affected? Here, both a geographical delimitation and a delimitation in different market segments may be required, for example, in base- and peak-load electricity or in eco-labeled and non-ecolabel products.
What is the trend in demand in this market? If demand declines faster than the natural turnover rate in production capacity, long-term marginal effects are assumed to consist of closure of existing plants; otherwise they are assumed to consist of investments in new facilities.
Which production techniques are flexible, that is, can vary their production volume in response to market demand?
Which technology will be affected? If the marginal effect is an investment, it is assumed to be in the technology that is cheapest to expand. If the marginal effect is a closure, it is assumed that it is in the technology that is most expensive to utilize.
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This five-step procedure can be used in CLCAs of a wide range of products. The procedure points at a single technology where the marginal effect occurs. This contributes to making the CLCA approach feasible and comprehensible—but at the cost of simplifying assumptions: that the relevant effects are either short-term or long-term rather than both, that markets and market segments can be clearly distinguished and do not affect each other, that the production volume of a technology is either completely flexible or not at all flexible, and that decisions are based solely on economic rationality. Each of these simplifications reduces the accuracy of the CLCA results. The LCA practitioner and the user of the LCA results should both be aware of this. The five-step procedure can be described as a structured way to arrive at an assumption of the marginal effects, rather than a method of identifying the actual marginal effects.
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Another approach is to collect information on plans to close and/or expand the production capacity and assume that the built margin is the mix of technologies in these plans. This is also an assumption, because plans do not always come true [28] and because some of the closure and investment decisions might be driven by policy or business strategies rather than by the demand for the product.
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Assumptions about the marginal effects can, of course, be made even without a structured or formal procedure. Long-term marginal effects in the electricity system can, as the first approximation, be assumed to be electricity production in new natural gas-fired power plants, as they have an environmental performance that is better than some possible marginal techniques but worse than others. A possible sensitivity analysis can be based on data from old coal power or old nuclear power, as the closure of such power plants can be included in the long-term marginal effects and because they are near opposite ends of the scale for several important environmental impacts. Similarly, a first approximation and the extreme values can be identified for marginal production of other products.
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To simply make an assumption is likely to be the easiest method to produce marginal data for the environmental assessment. On the other hand, pure assumptions make the study less accurate. They can also make the study less comprehensible in the sense that the basis for the assumptions can be difficult to communicate. If the assumptions appear arbitrary, the study also becomes less credible, which reduces the likelihood that the results inspire decisions and actions.
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5. Dealing with allocation
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A single production process often serves many different life cycles: diesel from a single refinery and steel from a steel mill can be used in almost any life cycle. If the production process generates a single type of product (e.g., steel), this is not considered a problem in LCA. We obtain input data to the calculations by simply dividing the total environmental burdens of the process by the total production, the functional output, of the process. The resulting input data are an average for that process and, hence, most suited for an ALCA. In a thorough CLCA we should ideally instead use input data that reflect how the environmental burdens of the process change as a result of a change in the total functional output. This is still a straightforward process, at least in theory.
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A methodological problem occurs when the process generates more than one type of product or function, which are used in different life cycles. A refinery, for example, produces many different fuels and materials. A steel mill might produce residual heat besides the steel. A CHP plant produces electricity and heat. Waste incineration serves the function of treating many different waste flows and might, at the same time, generate electricity, residential heating, and/or process steam. The problem is to decide on how quantify the total functional output of the multifunctional process and, hence, how to allocate the environmental burdens of the process to the various life cycles it serves. The approach to this problem depends on whether the LCA is an ALCA or a CLCA.
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5.1 Partitioning in attributional LCA
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An ALCA aims to estimate what share of the global environmental burdens belongs to the product investigated. Faced with the allocation problem, the task is to estimate what share of the burdens of the multifunctional process belongs to the product investigated and also what share of input materials, energy, etc. The basis for this allocation has to be a property that the products and/or functions of the process have in common: mass, energy content, economic value, etc. The total output of the process can be quantified in terms of this property, and the burdens of the process can be partitioned and allocated to the different products/functions in proportion to this property.
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What properties the products and functions have in common varies between multifunctional processes:
A refinery: mass, energy, exergy, and price
A CHP plant producing electricity and heat: energy, exergy, and price
A steel mill with residual heat: price
Waste incineration with energy recovery: price
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As indicated from this short list, the price is sometimes the only possible basis for allocation. In many ALCAs, it is the only allocation key that can be consistently used throughout the life cycle. Economic value can also be considered a valid basis for the allocation, since the economic value of the products is a proxy for their contribution to the expected profit from the process. The expected profit is typically the reason for investing and running the process and, hence, the cause of its impacts on the environment [12, 29].
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Economic allocation is often criticized because it will make the LCA results vary as prices change over time. However, the LCA results can be made more stable by using the average price over a period of several years as basis for the allocation. This will also more precisely reflect the causality, because the expected profit is more likely to depend on the average price than on the price at a specific point in time.
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There are cases where the economic value does not reflect a causality, because the processes are not driven by the expected profit but by concern for, e.g., the environment. These include noncommercial processes such as municipal wastewater treatment plants [30] and landfills. In these cases, the economic value is less valid and might not even be possible to use as basis for the allocation.
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When we choose an allocation key, we might account for what the intended audience considers to be fair. This increases the legitimacy of the study in their eyes, which increases the chance of the LCA leading to decisions.
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The choice of allocation method also depends on how feasible it is. If the allocation problem is not important for the results and conclusions of the ALCA, the easiest methods can be used to keep the cost of the study down. This can include allocating all burdens to the main product of the process—for example, to the steel from the steel mill with residual heat.
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5.2 System expansion in consequential LCA
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A CLCA aims to estimate how the global environmental burdens are affected by the production and use of the product investigated. Faced with a multifunctional process, the task is to estimate how the flows of the process are affected: the flows of input materials and energy, the emissions and waste flows, and the output of each product and function. When the output of products and functions for use in other life cycles are affected, the CLCA system should ideally be expanded to include the processes that are affected by this change in flows.
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A change in the demand for one of the products from a multifunctional process can affect decision-makers running the process and other actors in various ways that are difficult to predict and model. To make the CLCA approach feasible, we can choose to divide the multifunctional processes into three idealized cases [13]:
Independent production: a change in the demand for the product investigated affects the output of this product but not the flow of other products and functions from the process.
Use of main product in joint production: an increase in the demand for the product investigated drives the process and increases the output of all its products and functions proportionally.
Use of by-product in joint production: a change in the demand for the product investigated does not affect the process or any of its outputs; instead it affects the alternative use of the by-product.
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The idealized cases are simplifications of reality: products from a multifunctional process are rarely produced completely independent of each other [31], and the process is rarely driven by only one of the functional outputs.
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If the products of the multifunctional process are independently produced, the input data for each of the products should reflect how the environmental burdens of the process change when the production of this product changes while the production volume is constant for the other products.
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If the CLCA includes the use of the main product from a joint multifunctional process, the LCA model should include this process and also the processes affected by a change in the volume of by-products. The latter are typically assumed to be the production of products that compete with and are substituted by by-products from the multifunctional process (see Figure 4). Since the study is a CLCA, the competing production should ideally be modeled based on marginal data (cf. Sections 3 and 4.2).
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Figure 4.
System expansion at a joint multifunctional process where the product investigated is the main product (based on Ekvall and Weidema [13]).
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If the CLCA instead includes the use of a by-product, the operation of the multifunctional process is assumed to be unaffected by the demand for this product. The use of such a by-product does not affect its production; instead, it affects how much of the by-product is available for other purposes. The CLCA model should include affected processes only, which means it should not include the multifunctional process. Instead, the model ideally includes the marginal, alternative use of the by-product. This is the use affected by a (usually marginal) change in supply of the by-product (Figure 5).
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Figure 5.
System expansion at a joint multifunctional process where the product investigated is a by-product (based on Ekvall and Weidema [13]).
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In some cases, the by-products are not fully utilized: for example, part of the residual heat from a steel mill might be cooled off, and part of a residual material might be disposed as waste. In such cases, a change in the use of the by-product is not likely to affect the alternative use but instead how much of the by-product needs to be cooled off or disposed of in some other way. The CLCA should include the affected disposal process.
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Note that the “expanded” system in Figure 5 is not necessarily larger than the original system. It does not include the multifunctional process or the production of fuel and other raw materials for that process. Instead, it includes the disposal or alternative use of the by-product and any foreseeable consequences thereof.
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The easiest method, such as ignoring the production of by-products, can be applied in the CLCA if the choice of approach is not important for the results and conclusions of the study. However, more information is required to decide on such a cut-off in a CLCA, compared to an ALCA. Even if a multifunctional process has little environmental burdens, making it unimportant in an ALCA, a change in this process might have environmentally important consequences elsewhere, hence making it significant for the CLCA.
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6. The pros and cons of attributional and consequential LCA
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Attributional and consequential LCA have both advantages and disadvantages [9, 32]. This section discusses the choice between ALCA and CLCA using the criteria described in Section 2. The intention is not to determine what kind of LCA is superior but to discuss and explain their strong and weak aspects. The intention is also to show how the criteria in Section 2 can be used systematically to structure a discussion and assessment of methodological options.
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6.1 Feasible
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In a CLCA, the system model often needs to be expanded (Section 5.2), which requires environmental data on more processes and also economic data on the markets affected by the production and use of the product investigated (cf. Section 4.2). The databases that exist today usually include average data, but few include marginal data—Ecoinvent 3 is a notable exception, although its marginal data are rough. All of this means that a CLCA risks becoming unfeasible or at least significantly more expensive than an ALCA. On the other hand, the CLCA can exclude parts of the life cycle that are not affected by the production of by-products (cf. Section 5.2). The cost of CLCAs can also be reduced by limiting the study to the consequences expected to be the most important for the conclusions.
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With time, CLCAs may become easier to carry through if future databases include more of marginal data.
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6.2 Accurate
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A CLCA generates information on the environmental impact of a specific decision or information on how a decision-maker can affect the environment. This is just the accurate information to have as a basis for decisions that contribute to reducing the total negative environmental impacts or, at least, the impact per functional unit.
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An ALCA might be more precise and comprehensive, because a detailed and comprehensive CLCA might be too expensive or even unfeasible to carry through (see Section 6.1). As an ALCA is refined, it becomes more detailed, and the results converge toward an exact response to the attributional question: how much of the world’s environmental impact belongs to the product studied? However, even a very precise answer to this question will in some cases guide decisions in the wrong direction, because the impacts belonging to a product are not the same as the consequences of producing and using this product (see Figure 2).
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Refining a CLCA can involve accounting for more causal relationships. This makes the CLCA more comprehensive, but it does not necessarily mean that the results converge toward a final answer. On the contrary, as an additional causal relationship is included in the calculations, the results might shift completely and point in another direction.
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The CLCA provides, by definition, more information on how decisions affect the environment; however, if the CLCA results are highly uncertain and do not converge toward a final, true result, the CLCA might not guide decisions in the right direction more often than an ALCA.
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6.3 Comprehensible
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An ALCA is based on the concepts “life cycle” and “value chain” which are intuitively clear and easy to communicate. The system model in an ALCA usually has a simple structure, which means that it can easily be presented in a way that is transparent, at least in principle. The high level of detail that can be achieved, however, makes the study bulky and can make it a challenge in practice to communicate to decision-makers and other stakeholders.
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The basic concept in a CLCA is “consequences.” This is also intuitively easy to understand. However, other concepts required to understand the study (marginal production, partial equilibrium, etc.) are more difficult to grasp. The system model is also more complex with environmental burdens, avoided burdens, and additional, indirect burdens and with models of markets between the models of production processes. Making such a study comprehensible to decision-makers and stakeholders can be very difficult.
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6.4 Inspiring
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An ALCA can be interpreted to distribute responsibility and guilt for environmental impact, and recognition and goodwill for environmental improvements in the value chain, a part of the technological system that is linked to the production and use of the product through contracts and/or physical flows. An LCA model based on such clear links can be perceived as a relevant basis for choosing between products and for decisions on changes in the product. If the choice of allocation methods and system boundaries is accepted by the decision-maker, the results will also be perceived as fair and legitimate. However, they can be questioned by actors who have other, subjective perspectives on what is fair and right.
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The fact that a CLCA provides information on how possible decisions affect the environment can also be perceived as very relevant to the decision-maker. Rational decision-making requires information on the consequences of the decision. However, the CLCA typically include indirect consequences occurring in processes to which the product is not linked through physical flows or contractual obligations. The decision-maker might not want to be held responsible for such consequences. In order to account for them anyway, the decision-maker probably needs to be driven by the desire to actually improve the environment, rather than simply getting recognition for good environmental performance.
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6.5 Robust
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The ALCA practice is more well-established than CLCA. Environmental product declarations, a specific application of ALCA, also have detailed guidelines specifying the method [19]. In other applications, ALCA requires subjective choices of system boundaries (Section 4.1) and allocation methods (Section 5.1). However, the ALCA results are somewhat less sensitive to subjective choices than CLCA where the results might shift from positive to negative depending on system boundaries and assumptions. All this implies that ALCA is more robust and more resistant to abuse in the sense that the results depend less on who is doing the study.
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The actual consequences of a decision are almost always highly uncertain. If the sensitivity analysis of a CLCA takes full account of the great uncertainty, the study will rarely reach clear conclusions. This increases the risk of decisions and actions not being taken, especially if the actions are expensive or undesirable in other ways. The large uncertainty in the actual consequences makes it easy to misuse CLCA results to cast in doubt environmentally desirable decisions.
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However, when the ALCA is completed, the results can be abused if presented as a basis for decisions. This is because the ALCA does not aim to investigate the consequences of the decision on the environment. In a country with little fossil-based power production, such as Norway or Sweden, an ALCA can, for example, conclude that energy efficiency is not important for electric appliances. It can also indicate that residential heating should be provided through heat pumps rather than district heating from CHP plants fired with natural gas and perhaps even biofuel. A CLCA would not be likely to produce such results. If and when CLCA practice becomes more established, it will also become somewhat more difficult to abuse.
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7. Conclusions
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Attributional and consequential LCA respond to different questions: what part of the global environmental impacts is associated with the product investigated, and how does the product affect the global environmental impacts? In most applications and for most study objects, the choice between ALCA and CLCA is open. Since the two types of LCA have different advantages and disadvantages, it cannot be unequivocally stated that one is better than the other [32]. Roughly stated, the CLCA is more accurate, while ALCA have advantages when it comes to all other criteria. However, what kind of study is easiest to understand and most inspiring will vary between different decision-makers.
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To ensure that the study is perceived as relevant, it is a good idea to, if possible, discuss the goal and scope of the study with the client before deciding on what type of LCA to carry through. To make the study as legitimate as possible, it might also be useful to discuss with other stakeholders. In such a discussion, it is important to carefully explain what type of information is provided by an ALCA and a CLCA. Figure 2 can be used in that explanation. It is also important to make clear the limitations of the different methods. Only then can the client and other stakeholders decide on the type of study they want.
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As should be clear from this chapter, the actual effects of a decision on the global environmental impacts are in most cases highly uncertain. We will never know how close the CLCA results are to reflect the actual consequences. For this reason, CLCA should probably not be presented as a method to estimate the actual consequences. Instead the results are the consequences foreseeable within the methodological framework we choose to use in the study.
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The risk that the study will be abused will also vary from case to case. Here, it does not help to consult the client. The LCA practitioners must instead use their own judgment and decide what kind of LCA is the most appropriate. In this decision, it may be good to consult with colleagues and/or to discuss with other stakeholders. The decision to make an ALCA or a CLCA should therefore be taken by the LCA practitioner after discussions with the client and possibly with other stakeholders and colleagues.
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Acknowledgments
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This chapter was completed with financial support through the EU ERA-Net Sumforest project BenchValue (Formas Grant Number 2016-02113). It is based on translated parts of a report in Swedish, “Miljöbedömning av energibärare – vägledning för livscykelanalyser,” produced within the framework of the North European Energy Perspectives Project (NEPP). Jenny Gode, Mathias Gustavsson, Erik Dotzauer, and Lisa Hallberg contributed valuable input to this report. The methods and concepts presented in this chapter were to a large extent developed by or in collaboration with Bo Weidema, Göran Finnveden, and other international LCA experts. However, the author is solely responsible for the final content of the chapter.
\n
\n',keywords:"life cycle inventory analysis, methodology, attributional LCA, consequential LCA, allocation, marginal data, electricity",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/69212.pdf",chapterXML:"https://mts.intechopen.com/source/xml/69212.xml",downloadPdfUrl:"/chapter/pdf-download/69212",previewPdfUrl:"/chapter/pdf-preview/69212",totalDownloads:2334,totalViews:0,totalCrossrefCites:16,dateSubmitted:"January 25th 2019",dateReviewed:"August 16th 2019",datePrePublished:"September 24th 2019",datePublished:"February 12th 2020",dateFinished:"September 23rd 2019",readingETA:"0",abstract:"An attributional life cycle assessment (ALCA) estimates what share of the global environmental burdens belongs to a product. A consequential LCA (CLCA) gives an estimate of how the global environmental burdens are affected by the production and use of the product. The distinction arose to resolve debates on what input data to use in an LCA and how to deal with allocation problems. An ALCA is based on average data, and allocation is performed by partitioning environmental burdens of a process between the life cycles served by this process. A CLCA ideally uses marginal data in many parts of the life cycle and avoids allocation through system expansion. This chapter aims to discuss and clarify the key concepts. It also discusses pros and cons of different methodological options, based on criteria derived from the starting point that environmental systems analysis should contribute to reducing the negative environmental impacts of humankind or at least reduce the impacts per functional unit: the method should be feasible and generate results that are accurate, comprehensible, inspiring, and robust. The CLCA is more accurate, but ALCA has other advantages. The decision to make an ALCA or a CLCA should ideally be taken by the LCA practitioner after discussions with the client and possibly with other stakeholders and colleagues.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/69212",risUrl:"/chapter/ris/69212",signatures:"Tomas Ekvall",book:{id:"8156",type:"book",title:"Sustainability Assessment at the 21st century",subtitle:null,fullTitle:"Sustainability Assessment at the 21st century",slug:"sustainability-assessment-at-the-21st-century",publishedDate:"February 12th 2020",bookSignature:"María José Bastante-Ceca, Jose Luis Fuentes-Bargues, Levente Hufnagel, Florin-Constantin Mihai and Corneliu Iatu",coverURL:"https://cdn.intechopen.com/books/images_new/8156.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78984-977-6",printIsbn:"978-1-78984-976-9",pdfIsbn:"978-1-83880-079-6",isAvailableForWebshopOrdering:!0,editors:[{id:"210968",title:"Dr.",name:"María José",middleName:null,surname:"Bastante-Ceca",slug:"maria-jose-bastante-ceca",fullName:"María José Bastante-Ceca"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"293149",title:"Prof.",name:"Tomas",middleName:null,surname:"Ekvall",fullName:"Tomas Ekvall",slug:"tomas-ekvall",email:"tomas.ekvall@ivl.se",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. Criteria for methods in environmental systems analysis",level:"1"},{id:"sec_2_2",title:"2.1 Feasible",level:"2"},{id:"sec_3_2",title:"2.2 Accurate",level:"2"},{id:"sec_4_2",title:"2.3 Comprehensible",level:"2"},{id:"sec_5_2",title:"2.4 Inspiring",level:"2"},{id:"sec_6_2",title:"2.5 Robust",level:"2"},{id:"sec_8",title:"3. Attributional and consequential LCA respond to different questions",level:"1"},{id:"sec_9",title:"4. The choice of average and marginal data",level:"1"},{id:"sec_9_2",title:"4.1 The average of what?",level:"2"},{id:"sec_10_2",title:"4.2 What marginal impacts?",level:"2"},{id:"sec_12",title:"5. Dealing with allocation",level:"1"},{id:"sec_12_2",title:"5.1 Partitioning in attributional LCA",level:"2"},{id:"sec_13_2",title:"5.2 System expansion in consequential LCA",level:"2"},{id:"sec_15",title:"6. The pros and cons of attributional and consequential LCA",level:"1"},{id:"sec_15_2",title:"6.1 Feasible",level:"2"},{id:"sec_16_2",title:"6.2 Accurate",level:"2"},{id:"sec_17_2",title:"6.3 Comprehensible",level:"2"},{id:"sec_18_2",title:"6.4 Inspiring",level:"2"},{id:"sec_19_2",title:"6.5 Robust",level:"2"},{id:"sec_21",title:"7. Conclusions",level:"1"},{id:"sec_22",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'ISO 14040:2006. Environmental Management – Life Cycle Assessment – Principles and Framework. Geneva: International Organisation for Standardization; 2006\n'},{id:"B2",body:'ISO 14067:2018. Greenhouse Gases — Carbon Footprint of Products — Requirements and Guidelines for Quantification. Geneva: International Organisation for Standardization; 2018\n'},{id:"B3",body:'Ekvall T, Ciroth A, Hofstetter P, Norris G. Comparative assessment of attributional and consequential methods for LCA. Poster and handout. In: Abstracts 14th Annual Meeting of SETAC-Europe; April 2004. Prague. Brussels: SETAC-Europe; 2004. p. 197\n'},{id:"B4",body:'Heintz B, Baisnée P-F. System boundaries. In: Life Cycle Assessment. Workshop Report: 2-3 December 1991; Leiden. Brussels: SETAC-Europe; 1992. pp. 35-52\n'},{id:"B5",body:'Weidema BP. Development of a method for product life cycle assessment with special references to food products [PhD thesis summary]. Lyngby: Technical University of Denmark; 1993\n'},{id:"B6",body:'Tillman A-M. Significance of decision-making for LCA methodology. Environmental Impact Assessment Review. 2000;20:113-123. DOI: 10.1016/S0195-9255(99)00035-9\n'},{id:"B7",body:'Ekvall T. System expansion and allocation in life cycle assessment – With applications for wastepaper management [PhD thesis]. Gothenburg: Chalmers University of Technology; 1999\n'},{id:"B8",body:'Curran MA, Mann M, Norris G. The international workshop on electricity data for life cycle inventories. Journal of Cleaner Production. 2005;13(8):853-862. DOI: 10.1016/j.jclepro.2002.03.001\n'},{id:"B9",body:'Zamagni A, Guinée J, Heijungs R, Masoni P, Raggi A. Lights and shadows in consequential LCA. International Journal of Life Cycle Assessment. 2012;17:904-918. DOI: 10.1007/s11367-012-0423-x\n'},{id:"B10",body:'Ekvall T, Azapagic A, Finnveden G, Rydberg T, Weidema BP, Zamagni A. Attributional and consequential LCA in the ILCD handbook. International Journal of Life Cycle Assessment. 2016;21:293-296. DOI: 10.1007/s11367-015-1026-0\n'},{id:"B11",body:'Finnveden G, Hauschild MZ, Ekvall T, Guinée J, Heijungs R, Hellweg S, et al. Recent developments in life cycle assessment. Journal of Environmental Management. 2009;91(1):1-21. DOI: 10.1016/j.jenvman.2009.06.018\n'},{id:"B12",body:'Weidema BP. Market Information in Life Cycle Assessment. Environmental Project no. 863. Copenhagen: Danish Environmental Protection Agency; 2003. 147 p. Available from: https://www2.mst.dk/Udgiv/publications/2003/87-7972-991-6/pdf/87-7972-992-4.pdf [Accessed: 2019-08-11]\n'},{id:"B13",body:'Ekvall T, Weidema BP. System boundaries and input data in consequential life cycle inventory analysis. International Journal of Life Cycle Assessment. 2004;9(3):161-171. DOI: 10.1007/BF02994190\n'},{id:"B14",body:'Ekvall T, Andrae A. Attributional and consequential environmental assessment of the shift to lead-free solders. International Journal of Life Cycle Assessment. 2006;11(5):344-353. DOI: 10.1065/lca2005.05.208\n'},{id:"B15",body:'Sandén BA, Karlström M. Positive and negative feedback in consequential life-cycle assessment. Journal of Cleaner Production. 2007;15(15):1469-1481. DOI: 10.1016/j.jclepro.2006.03.005\n'},{id:"B16",body:'Mattsson N. Internalizing technological development in energy systems models [LicEng thesis]. Gothenburg: Chalmers University of Technology; 1997\n'},{id:"B17",body:'Azapagic A, Clift R. Allocation of environmental burdens in multiple-function systems. Journal of Cleaner Production. 1999;7(2):101-119. DOI: 10.1016/S0959-6526(98)00046-8\n'},{id:"B18",body:'Greenhouse Gas Protocol. Product Life Cycle Accounting and Reporting Standard. Washington, DC, Geneva: World Resources Institute, World Business Council for Sustainable Development; 2011. 148 p. ISBN 978-1-56973-773-6. Available from: https://ghgprotocol.org/sites/default/files/standards/Product-Life-Cycle-Accounting-Reporting-Standard_041613.pdf [Accessed: 2019-08-11]\n'},{id:"B19",body:'General Programme Instructions for the International EPD® System. Version 3.0. Stockholm: EPD International AB; 2017. 77 p. Available from: https://www.environdec.com/contentassets/95ee9211a9614f1faa7461ff32cecc91/general-programme-instructions-v3.0.pdf [Accessed: 2019-08-11]\n'},{id:"B20",body:'Product Environmental Footprint Category Rules Guidance: Version 6.3 – May 2018. Brussels: European Commission; 2018. 238 p. Available from: http://ec.europa.eu/environment/eussd/smgp/pdf/PEFCR_guidance_v6.3.pdf [Accessed: 2019-08-11]\n'},{id:"B21",body:'Mattsson N, Unger T, Ekvall T. Effects of perturbations in a dynamic system – The case of Nordic power production. In: Unger T, editor. Common energy and climate strategies for the Nordic countries – A model analysis [PhD thesis]. Gothenburg: Chalmers University of Technology; 2003\n'},{id:"B22",body:'Sköldberg H, Unger T. Effekter av förändrad elanvändning/elproduktion – Modellberäkningar. Elforsk Rapport 08:30. Elforsk: Stockholm; 2008. 68 p\n'},{id:"B23",body:'Sandvall AF, Börjesson M, Ekvall T, Ahlgren EO. Modelling environmental and energy system impacts of large-scale excess heat utilization – A regional study. Energy. 2015;79:68-79. DOI: 10.1016/j.energy.2014.10.049\n'},{id:"B24",body:'Sandvall AF, Ahlgren EO, Ekvall T. Low-energy buildings heat supply – Modelling of energy systems and carbon emissions impacts. Energy Policy. 2017;111:371-382. DOI: 10.1016/j.enpol.2017.09.007\n'},{id:"B25",body:'Lund H, Mathiesen BV, Christensen P, Schmidt JH. Energy system analysis of marginal electricity supply in consequential LCA. International Journal of Life Cycle Assessment. 2010;15(3):260-271. DOI: 10.1007/s11367-010-0164-7\n'},{id:"B26",body:'Hagberg M, Gode J, Lätt A, Ekvall T, Adolfsson I, Martinsson F. Miljövärdering av energilösningar i byggnader etapp 2: Metod för konsekvensanalys. Rapport 2017:409. Stockholm: Energiforsk; 2017. 75 p\n'},{id:"B27",body:'Weidema BP, Frees N, Nielsen P. Marginal production technologies for life cycle inventories. International Journal of Life Cycle Assessment. 1999;4(1):48-56. DOI: 10.1007/BF02979395\n'},{id:"B28",body:'Mathiesen BV, Münster M, Fruergaard T. Uncertainties related to the identification of the marginal energy technology in consequential life cycle assessments. Journal of Cleaner Production. 2009;17:1331-1338. DOI: 10.1016/j.jclepro.2009.04.009\n'},{id:"B29",body:'Huppes G. A general method for allocation in LCA. In: Huppes G, Schneider F, editors. Proceedings of the European Workshop on Allocation in LCA.; February 1994; Leiden. Brussels: SETAC-Europe; 1994. pp. 74-90\n'},{id:"B30",body:'Heimersson S, Svanström M, Ekvall T. Opportunities of consequential and attributional modelling in life cycle assessment of wastewater and sludge management. Journal of Cleaner Production. 2019;222:242-251. DOI: 10.1016/j.jclepro.2019.02.248\n'},{id:"B31",body:'Ekvall T, Finnveden G. Allocation in ISO 14041 – A critical review. Journal of Cleaner Production. 2001;9(3):197-208. DOI: 10.1016/S0959-6526(00)00052-4\n'},{id:"B32",body:'Ekvall T, Tillman A-M, Molander S. Normative ethics and methodology for life cycle assessment. Journal of Cleaner Production. 2005;13(13-14):1225-1234. DOI: 10.1016/j.jclepro.2005.05.010\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Tomas Ekvall",address:"tomas.ekvall@ivl.se",affiliation:'
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Applications",isOpenForSubmission:!1,hash:"a3479e76c6ac538aac76409c9efb7e41",slug:"neuroimaging-neurobiology-multimodal-and-network-applications",bookSignature:"Yongxia Zhou",coverURL:"https://cdn.intechopen.com/books/images_new/9347.jpg",editedByType:"Edited by",editors:[{id:"259308",title:"Dr.",name:"Yongxia",middleName:null,surname:"Zhou",slug:"yongxia-zhou",fullName:"Yongxia Zhou"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8938",title:"Inhibitory Control Training",subtitle:"A Multidisciplinary Approach",isOpenForSubmission:!1,hash:"bd82354f3bba4af5421337cd42052f86",slug:"inhibitory-control-training-a-multidisciplinary-approach",bookSignature:"Sara Palermo and Massimo Bartoli",coverURL:"https://cdn.intechopen.com/books/images_new/8938.jpg",editedByType:"Edited by",editors:[{id:"233998",title:"Ph.D.",name:"Sara",middleName:null,surname:"Palermo",slug:"sara-palermo",fullName:"Sara Palermo"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6998",title:"Synucleins",subtitle:"Biochemistry and Role in Diseases",isOpenForSubmission:!1,hash:"2b4b802fec508928ce8ab9deebd1375f",slug:"synucleins-biochemistry-and-role-in-diseases",bookSignature:"Andrei Surguchov",coverURL:"https://cdn.intechopen.com/books/images_new/6998.jpg",editedByType:"Edited by",editors:[{id:"266540",title:"Dr.",name:"Andrei",middleName:null,surname:"Surguchov",slug:"andrei-surguchov",fullName:"Andrei Surguchov"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:65,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"46296",doi:"10.5772/57398",title:"Physiological Role of Amyloid Beta in Neural Cells: The Cellular Trophic Activity",slug:"physiological-role-of-amyloid-beta-in-neural-cells-the-cellular-trophic-activity",totalDownloads:5886,totalCrossrefCites:18,totalDimensionsCites:31,abstract:null,book:{id:"3846",slug:"neurochemistry",title:"Neurochemistry",fullTitle:"Neurochemistry"},signatures:"M. del C. Cárdenas-Aguayo, M. del C. Silva-Lucero, M. Cortes-Ortiz,\nB. Jiménez-Ramos, L. Gómez-Virgilio, G. Ramírez-Rodríguez, E. Vera-\nArroyo, R. Fiorentino-Pérez, U. García, J. Luna-Muñoz and M.A.\nMeraz-Ríos",authors:[{id:"42225",title:"Dr.",name:"Jose",middleName:null,surname:"Luna-Muñoz",slug:"jose-luna-munoz",fullName:"Jose Luna-Muñoz"},{id:"114746",title:"Dr.",name:"Marco",middleName:null,surname:"Meraz-Ríos",slug:"marco-meraz-rios",fullName:"Marco Meraz-Ríos"},{id:"169616",title:"Dr.",name:"Maria del Carmen",middleName:null,surname:"Cardenas-Aguayo",slug:"maria-del-carmen-cardenas-aguayo",fullName:"Maria del Carmen Cardenas-Aguayo"},{id:"169857",title:"Dr.",name:"Maria del Carmen",middleName:null,surname:"Silva-Lucero",slug:"maria-del-carmen-silva-lucero",fullName:"Maria del Carmen Silva-Lucero"},{id:"169858",title:"Dr.",name:"Maribel",middleName:null,surname:"Cortes-Ortiz",slug:"maribel-cortes-ortiz",fullName:"Maribel Cortes-Ortiz"},{id:"169859",title:"Dr.",name:"Berenice",middleName:null,surname:"Jimenez-Ramos",slug:"berenice-jimenez-ramos",fullName:"Berenice Jimenez-Ramos"},{id:"169860",title:"Dr.",name:"Laura",middleName:null,surname:"Gomez-Virgilio",slug:"laura-gomez-virgilio",fullName:"Laura Gomez-Virgilio"},{id:"169861",title:"Dr.",name:"Gerardo",middleName:null,surname:"Ramirez-Rodriguez",slug:"gerardo-ramirez-rodriguez",fullName:"Gerardo Ramirez-Rodriguez"},{id:"169862",title:"Dr.",name:"Eduardo",middleName:null,surname:"Vera-Arroyo",slug:"eduardo-vera-arroyo",fullName:"Eduardo Vera-Arroyo"},{id:"169863",title:"Dr.",name:"Rosana Sofia",middleName:null,surname:"Fiorentino-Perez",slug:"rosana-sofia-fiorentino-perez",fullName:"Rosana Sofia Fiorentino-Perez"},{id:"169864",title:"Dr.",name:"Ubaldo",middleName:null,surname:"Garcia",slug:"ubaldo-garcia",fullName:"Ubaldo Garcia"}]},{id:"58070",doi:"10.5772/intechopen.72427",title:"MRI Medical Image Denoising by Fundamental Filters",slug:"mri-medical-image-denoising-by-fundamental-filters",totalDownloads:2564,totalCrossrefCites:17,totalDimensionsCites:30,abstract:"Nowadays Medical imaging technique Magnetic Resonance Imaging (MRI) plays an important role in medical setting to form high standard images contained in the human brain. MRI is commonly used once treating brain, prostate cancers, ankle and foot. The Magnetic Resonance Imaging (MRI) images are usually liable to suffer from noises such as Gaussian noise, salt and pepper noise and speckle noise. So getting of brain image with accuracy is very extremely task. An accurate brain image is very necessary for further diagnosis process. During this chapter, a median filter algorithm will be modified. Gaussian noise and Salt and pepper noise will be added to MRI image. A proposed Median filter (MF), Adaptive Median filter (AMF) and Adaptive Wiener filter (AWF) will be implemented. The filters will be used to remove the additive noises present in the MRI images. The noise density will be added gradually to MRI image to compare performance of the filters evaluation. The performance of these filters will be compared exploitation the applied mathematics parameter Peak Signal-to-Noise Ratio (PSNR).",book:{id:"6144",slug:"high-resolution-neuroimaging-basic-physical-principles-and-clinical-applications",title:"High-Resolution Neuroimaging",fullTitle:"High-Resolution Neuroimaging - Basic Physical Principles and Clinical Applications"},signatures:"Hanafy M. Ali",authors:[{id:"213318",title:"Dr.",name:"Hanafy",middleName:"M.",surname:"Ali",slug:"hanafy-ali",fullName:"Hanafy Ali"}]},{id:"41589",doi:"10.5772/50323",title:"The Role of the Amygdala in Anxiety Disorders",slug:"the-role-of-the-amygdala-in-anxiety-disorders",totalDownloads:9671,totalCrossrefCites:4,totalDimensionsCites:28,abstract:null,book:{id:"2599",slug:"the-amygdala-a-discrete-multitasking-manager",title:"The Amygdala",fullTitle:"The Amygdala - A Discrete Multitasking Manager"},signatures:"Gina L. Forster, Andrew M. Novick, Jamie L. Scholl and Michael J. Watt",authors:[{id:"145620",title:"Dr.",name:"Gina",middleName:null,surname:"Forster",slug:"gina-forster",fullName:"Gina Forster"},{id:"146553",title:"BSc.",name:"Andrew",middleName:null,surname:"Novick",slug:"andrew-novick",fullName:"Andrew Novick"},{id:"146554",title:"MSc.",name:"Jamie",middleName:null,surname:"Scholl",slug:"jamie-scholl",fullName:"Jamie Scholl"},{id:"146555",title:"Dr.",name:"Michael",middleName:null,surname:"Watt",slug:"michael-watt",fullName:"Michael Watt"}]},{id:"26258",doi:"10.5772/28300",title:"Excitotoxicity and Oxidative Stress in Acute Ischemic Stroke",slug:"excitotoxicity-and-oxidative-stress-in-acute-ischemic-stroke",totalDownloads:7157,totalCrossrefCites:6,totalDimensionsCites:25,abstract:null,book:{id:"931",slug:"acute-ischemic-stroke",title:"Acute Ischemic Stroke",fullTitle:"Acute Ischemic Stroke"},signatures:"Ramón Rama Bretón and Julio César García Rodríguez",authors:[{id:"73430",title:"Prof.",name:"Ramon",middleName:null,surname:"Rama",slug:"ramon-rama",fullName:"Ramon Rama"},{id:"124643",title:"Prof.",name:"Julio Cesar",middleName:null,surname:"García",slug:"julio-cesar-garcia",fullName:"Julio Cesar García"}]},{id:"62072",doi:"10.5772/intechopen.78695",title:"Brain-Computer Interface and Motor Imagery Training: The Role of Visual Feedback and Embodiment",slug:"brain-computer-interface-and-motor-imagery-training-the-role-of-visual-feedback-and-embodiment",totalDownloads:1439,totalCrossrefCites:13,totalDimensionsCites:23,abstract:"Controlling a brain-computer interface (BCI) is a difficult task that requires extensive training. Particularly in the case of motor imagery BCIs, users may need several training sessions before they learn how to generate desired brain activity and reach an acceptable performance. A typical training protocol for such BCIs includes execution of a motor imagery task by the user, followed by presentation of an extending bar or a moving object on a computer screen. In this chapter, we discuss the importance of a visual feedback that resembles human actions, the effect of human factors such as confidence and motivation, and the role of embodiment in the learning process of a motor imagery task. Our results from a series of experiments in which users BCI-operated a humanlike android robot confirm that realistic visual feedback can induce a sense of embodiment, which promotes a significant learning of the motor imagery task in a short amount of time. We review the impact of humanlike visual feedback in optimized modulation of brain activity by the BCI users.",book:{id:"6610",slug:"evolving-bci-therapy-engaging-brain-state-dynamics",title:"Evolving BCI Therapy",fullTitle:"Evolving BCI Therapy - Engaging Brain State Dynamics"},signatures:"Maryam Alimardani, Shuichi Nishio and Hiroshi Ishiguro",authors:[{id:"11981",title:"Prof.",name:"Hiroshi",middleName:null,surname:"Ishiguro",slug:"hiroshi-ishiguro",fullName:"Hiroshi Ishiguro"},{id:"231131",title:"Dr.",name:"Maryam",middleName:null,surname:"Alimardani",slug:"maryam-alimardani",fullName:"Maryam Alimardani"},{id:"231134",title:"Dr.",name:"Shuichi",middleName:null,surname:"Nishio",slug:"shuichi-nishio",fullName:"Shuichi Nishio"}]}],mostDownloadedChaptersLast30Days:[{id:"29764",title:"Underlying Causes of Paresthesia",slug:"underlying-causes-of-paresthesia",totalDownloads:192666,totalCrossrefCites:3,totalDimensionsCites:7,abstract:null,book:{id:"1069",slug:"paresthesia",title:"Paresthesia",fullTitle:"Paresthesia"},signatures:"Mahdi Sharif-Alhoseini, Vafa Rahimi-Movaghar and Alexander R. Vaccaro",authors:[{id:"91165",title:"Prof.",name:"Vafa",middleName:null,surname:"Rahimi-Movaghar",slug:"vafa-rahimi-movaghar",fullName:"Vafa Rahimi-Movaghar"}]},{id:"63258",title:"Anatomy and Function of the Hypothalamus",slug:"anatomy-and-function-of-the-hypothalamus",totalDownloads:4558,totalCrossrefCites:6,totalDimensionsCites:12,abstract:"The hypothalamus is a small but important area of the brain formed by various nucleus and nervous fibers. Through its neuronal connections, it is involved in many complex functions of the organism such as vegetative system control, homeostasis of the organism, thermoregulation, and also in adjusting the emotional behavior. The hypothalamus is involved in different daily activities like eating or drinking, in the control of the body’s temperature and energy maintenance, and in the process of memorizing. It also modulates the endocrine system through its connections with the pituitary gland. Precise anatomical description along with a correct characterization of the component structures is essential for understanding its functions.",book:{id:"6331",slug:"hypothalamus-in-health-and-diseases",title:"Hypothalamus in Health and Diseases",fullTitle:"Hypothalamus in Health and Diseases"},signatures:"Miana Gabriela Pop, Carmen Crivii and Iulian Opincariu",authors:null},{id:"57103",title:"GABA and Glutamate: Their Transmitter Role in the CNS and Pancreatic Islets",slug:"gaba-and-glutamate-their-transmitter-role-in-the-cns-and-pancreatic-islets",totalDownloads:3478,totalCrossrefCites:3,totalDimensionsCites:9,abstract:"Glutamate and gamma-aminobutyric acid (GABA) are the major neurotransmitters in the mammalian brain. Inhibitory GABA and excitatory glutamate work together to control many processes, including the brain’s overall level of excitation. The contributions of GABA and glutamate in extra-neuronal signaling are by far less widely recognized. In this chapter, we first discuss the role of both neurotransmitters during development, emphasizing the importance of the shift from excitatory to inhibitory GABAergic neurotransmission. The second part summarizes the biosynthesis and role of GABA and glutamate in neurotransmission in the mature brain, and major neurological disorders associated with glutamate and GABA receptors and GABA release mechanisms. The final part focuses on extra-neuronal glutamatergic and GABAergic signaling in pancreatic islets of Langerhans, and possible associations with type 1 diabetes mellitus.",book:{id:"6237",slug:"gaba-and-glutamate-new-developments-in-neurotransmission-research",title:"GABA And Glutamate",fullTitle:"GABA And Glutamate - New Developments In Neurotransmission Research"},signatures:"Christiane S. Hampe, Hiroshi Mitoma and Mario Manto",authors:[{id:"210220",title:"Prof.",name:"Christiane",middleName:null,surname:"Hampe",slug:"christiane-hampe",fullName:"Christiane Hampe"},{id:"210485",title:"Prof.",name:"Mario",middleName:null,surname:"Manto",slug:"mario-manto",fullName:"Mario Manto"},{id:"210486",title:"Prof.",name:"Hiroshi",middleName:null,surname:"Mitoma",slug:"hiroshi-mitoma",fullName:"Hiroshi Mitoma"}]},{id:"35802",title:"Cross-Cultural/Linguistic Differences in the Prevalence of Developmental Dyslexia and the Hypothesis of Granularity and Transparency",slug:"cross-cultural-linguistic-differences-in-the-prevalence-of-developmental-dyslexia-and-the-hypothesis",totalDownloads:3601,totalCrossrefCites:2,totalDimensionsCites:7,abstract:null,book:{id:"673",slug:"dyslexia-a-comprehensive-and-international-approach",title:"Dyslexia",fullTitle:"Dyslexia - A Comprehensive and International Approach"},signatures:"Taeko N. Wydell",authors:[{id:"87489",title:"Prof.",name:"Taeko",middleName:"N.",surname:"Wydell",slug:"taeko-wydell",fullName:"Taeko Wydell"}]},{id:"58597",title:"Testosterone and Erectile Function: A Review of Evidence from Basic Research",slug:"testosterone-and-erectile-function-a-review-of-evidence-from-basic-research",totalDownloads:1331,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Androgens are essential for male physical activity and normal erectile function. Hence, age-related testosterone deficiency, known as late-onset hypogonadism (LOH), is considered a risk factor for erectile dysfunction (ED). This chapter summarizes relevant basic research reports examining the effects of testosterone on erectile function. Testosterone affects several organs and is especially active on the erectile tissue. The mechanism of testosterone deficiency effects on erectile function and the results of testosterone replacement therapy (TRT) have been well studied. Testosterone affects nitric oxide (NO) production and phosphodiesterase type 5 (PDE-5) expression in the corpus cavernosum through molecular pathways, preserves smooth muscle contractility by regulating both contraction and relaxation, and maintains the structure of the corpus cavernosum. Interestingly, testosterone deficiency has relationship to neurological diseases, which leads to ED. Testosterone replacement therapy is widely used to treat patients with testosterone deficiency; however, this treatment might also induce some problems. Basic research suggests that PDE-5 inhibitors, L-citrulline, and/or resveratrol therapy might be effective therapeutic options for testosterone deficiency-induced ED. Future research should confirm these findings through more specific experiments using molecular tools and may shed more light on endocrine-related ED and its possible treatments.",book:{id:"5994",slug:"sex-hormones-in-neurodegenerative-processes-and-diseases",title:"Sex Hormones in Neurodegenerative Processes and Diseases",fullTitle:"Sex Hormones in Neurodegenerative Processes and Diseases"},signatures:"Tomoya Kataoka and Kazunori Kimura",authors:[{id:"219042",title:"Ph.D.",name:"Tomoya",middleName:null,surname:"Kataoka",slug:"tomoya-kataoka",fullName:"Tomoya Kataoka"},{id:"229066",title:"Prof.",name:"Kazunori",middleName:null,surname:"Kimura",slug:"kazunori-kimura",fullName:"Kazunori Kimura"}]}],onlineFirstChaptersFilter:{topicId:"18",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81646",title:"Cortical Plasticity under Ketamine: From Synapse to Map",slug:"cortical-plasticity-under-ketamine-from-synapse-to-map",totalDownloads:14,totalDimensionsCites:0,doi:"10.5772/intechopen.104787",abstract:"Sensory systems need to process signals in a highly dynamic way to efficiently respond to variations in the animal’s environment. For instance, several studies showed that the visual system is subject to neuroplasticity since the neurons’ firing changes according to stimulus properties. This dynamic information processing might be supported by a network reorganization. Since antidepressants influence neurotransmission, they can be used to explore synaptic plasticity sustaining cortical map reorganization. To this goal, we investigated in the primary visual cortex (V1 of mouse and cat), the impact of ketamine on neuroplasticity through changes in neuronal orientation selectivity and the functional connectivity between V1 cells, using cross correlation analyses. We found that ketamine affects cortical orientation selectivity and alters the functional connectivity within an assembly. These data clearly highlight the role of the antidepressant drugs in inducing or modeling short-term plasticity in V1 which suggests that cortical processing is optimized and adapted to the properties of the stimulus.",book:{id:"11374",title:"Sensory Nervous System - Computational Neuroimaging Investigations of Topographical Organization in Human Sensory Cortex",coverURL:"https://cdn.intechopen.com/books/images_new/11374.jpg"},signatures:"Ouelhazi Afef, Rudy Lussiez and Molotchnikoff Stephane"},{id:"81582",title:"The Role of Cognitive Reserve in Executive Functioning and Its Relationship to Cognitive Decline and Dementia",slug:"the-role-of-cognitive-reserve-in-executive-functioning-and-its-relationship-to-cognitive-decline-and",totalDownloads:22,totalDimensionsCites:0,doi:"10.5772/intechopen.104646",abstract:"In this chapter, we explore how cognitive reserve is implicated in coping with the negative consequences of brain pathology and age-related cognitive decline. Individual differences in cognitive performance are based on different brain mechanisms (neural reserve and neural compensation), and reflect, among others, the effect of education, occupational attainment, leisure activities, and social involvement. These cognitive reserve proxies have been extensively associated with efficient executive functioning. We discuss and focus particularly on the compensation mechanisms related to the frontal lobe and its protective role, in maintaining cognitive performance in old age or even mitigating the clinical expression of dementia.",book:{id:"11742",title:"Neurophysiology",coverURL:"https://cdn.intechopen.com/books/images_new/11742.jpg"},signatures:"Gabriela Álvares-Pereira, Carolina Maruta and Maria Vânia Silva-Nunes"},{id:"81488",title:"Aggression and Sexual Behavior: Overlapping or Distinct Roles of 5-HT1A and 5-HT1B Receptors",slug:"aggression-and-sexual-behavior-overlapping-or-distinct-roles-of-5-ht1a-and-5-ht1b-receptors",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.104872",abstract:"Distinct brain mechanisms for male aggressive and sexual behavior are present in mammalian species, including man. However, recent evidence suggests a strong connection and even overlap in the central nervous system (CNS) circuitry involved in aggressive and sexual behavior. The serotonergic system in the CNS is strongly involved in male aggressive and sexual behavior. In particular, 5-HT1A and 5-HT1B receptors seem to play a critical role in the modulation of these behaviors. The present chapter focuses on the effects of 5-HT1A- and 5-HT1B-receptor ligands in male rodent aggression and sexual behavior. Results indicate that 5-HT1B-heteroreceptors play a critical role in the modulation of male offensive behavior, although a definite role of 5-HT1A-auto- or heteroreceptors cannot be ruled out. 5-HT1A receptors are clearly involved in male sexual behavior, although it has to be yet unraveled whether 5-HT1A-auto- or heteroreceptors are important. Although several key nodes in the complex circuitry of aggression and sexual behavior are known, in particular in the medial hypothalamus, a clear link or connection to these critical structures and the serotonergic key receptors is yet to be determined. This information is urgently needed to detect and develop new selective anti-aggressive (serenic) and pro-sexual drugs for human applications.",book:{id:"10195",title:"Serotonin and the CNS - New Developments in Pharmacology and Therapeutics",coverURL:"https://cdn.intechopen.com/books/images_new/10195.jpg"},signatures:"Berend Olivier and Jocelien D.A. Olivier"},{id:"81093",title:"Prehospital and Emergency Room Airway Management in Traumatic Brain Injury",slug:"prehospital-and-emergency-room-airway-management-in-traumatic-brain-injury",totalDownloads:49,totalDimensionsCites:0,doi:"10.5772/intechopen.104173",abstract:"Airway management in trauma is critical and may impact patient outcomes. Particularly in traumatic brain injury (TBI), depressed level of consciousness may be associated with compromised protective airway reflexes or apnea, which can increase the risk of aspiration or result in hypoxemia and worsen the secondary brain damage. Therefore, patients with TBI and Glasgow Coma Scale (GCS) ≤ 8 have been traditionally managed by prehospital or emergency room (ER) endotracheal intubation. However, recent evidence challenged this practice and even suggested that routine intubation may be harmful. This chapter will address the indications and optimal method of securing the airway, prehospital and in the ER, in patients with traumatic brain injury.",book:{id:"11367",title:"Traumatic Brain Injury",coverURL:"https://cdn.intechopen.com/books/images_new/11367.jpg"},signatures:"Dominik A. Jakob, Jean-Cyrille Pitteloud and Demetrios Demetriades"},{id:"81011",title:"Amino Acids as Neurotransmitters. The Balance between Excitation and Inhibition as a Background for Future Clinical Applications",slug:"amino-acids-as-neurotransmitters-the-balance-between-excitation-and-inhibition-as-a-background-for-f",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.103760",abstract:"For more than 30 years, amino acids have been well-known (and essential) participants in neurotransmission. They act as both neuromediators and metabolites in nervous tissue. Glycine and glutamic acid (glutamate) are prominent examples. These amino acids are agonists of inhibitory and excitatory membrane receptors, respectively. Moreover, they play essential roles in metabolic pathways and energy transformation in neurons and astrocytes. Despite their obvious effects on the brain, their potential role in therapeutic methods remains uncertain in clinical practice. In the current chapter, a comparison of the crosstalk between these two systems, which are responsible for excitation and inhibition in neurons, is presented. The interactions are discussed at the metabolic, receptor, and transport levels. Reaction-diffusion and a convectional flow into the interstitial fluid create a balanced distribution of glycine and glutamate. Indeed, the neurons’ final physiological state is a result of a balance between the excitatory and inhibitory influences. However, changes to the glycine and/or glutamate pools under pathological conditions can alter the state of nervous tissue. Thus, new therapies for various diseases may be developed on the basis of amino acid medication.",book:{id:"10890",title:"Recent Advances in Neurochemistry",coverURL:"https://cdn.intechopen.com/books/images_new/10890.jpg"},signatures:"Yaroslav R. Nartsissov"},{id:"80821",title:"Neuroimmunology and Neurological Manifestations of COVID-19",slug:"neuroimmunology-and-neurological-manifestations-of-covid-19",totalDownloads:41,totalDimensionsCites:0,doi:"10.5772/intechopen.103026",abstract:"Infection with SARS-CoV-2 is causing coronavirus disease in 2019 (COVID-19). Besides respiratory symptoms due to an attack on the broncho-alveolar system, COVID-19, among others, can be accompanied by neurological symptoms because of the affection of the nervous system. These can be caused by intrusion by SARS-CoV-2 of the central nervous system (CNS) and peripheral nervous system (PNS) and direct infection of local cells. In addition, neurological deterioration mediated by molecular mimicry to virus antigens or bystander activation in the context of immunological anti-virus defense can lead to tissue damage in the CNS and PNS. In addition, cytokine storm caused by SARS-CoV-2 infection in COVID-19 can lead to nervous system related symptoms. Endotheliitis of CNS vessels can lead to vessel occlusion and stroke. COVID-19 can also result in cerebral hemorrhage and sinus thrombosis possibly related to changes in clotting behavior. Vaccination is most important to prevent COVID-19 in the nervous system. 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