List of references of developed molecular identification assays for different anopheline species.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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Recent advances in Metformin research have provided new insights into how this drug could be utilized in numerous diseases. Metformin is one of the most widely used medicine to treat diabetes. The source of metformin, it’s availability and isolation plays an important role so that pure and precise medicine could be obtained. The analytical approaches to determine metformin in various bulk formulations is also a challenging task for the scientific community. The approaches in newer drug delivery of metformin may give further opportunities to the researcher so that an optimized preparation can be developed. Apart from its wide use in diabetes, Metformin has been frequently used in various cancer treatments along with side chemotherapeutic drugs. The objective of this book will be to provide a detailed insight on delivery systems of metformin, it’s multiple uses in numerous diseases, it’s safety and toxicity considerations.
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Despite the general acknowledge that traditional taxonomy is important, the decline in taxonomy and skills basis for identifying and describing biodiversity is a striking reality. Retiring taxonomists are leaving orphan reference collections - most often not digitalized - and associated catalogues or literature. Taxonomy being not considered as “big science”, few students are entering the field. This has particularly negative effects when dealing with arthropod pests, nuisances or vector species because the corollary is that taxonomic expertise is lost and would drastically be missing if the sanitary situation requires it. Meanwhile the development of molecular identification tools, recent mathematical developments motivated by the need for quantifying morphological characters [4], a new field has progressively emerged, called "modern" or "geometric" morphometrics, allowing to quantify and to visualize morphological differences between taxa.
Both these new tools reinforcing the taxonomic research are not only welcome, they are also highly needed. Entomological investigations for surveillance activities or research purposes collect usually large numbers of individuals (sometimes in bad shape) which means time-consuming identification process. The problem may become intractable when species diversity is high and, as in the
Before the development and use of molecular assays for the identification of individual specimens, cytogenetics technique was widely used for Anopheline species. This method has proved to be extremely informative, not only for species identification but also in the analysis of population structure and determining the existence of sibling species. However, the required expertise for cytogenetics has limited its large scale application. Allozymes have also widely been used but the need for individuals to be stored in liquid nitrogen constrained the collection. Since the 1990s, the development of techniques for DNA amplification primarily by Polymerase Chain Reaction (PCR) in research laboratories together with the analysis of DNA polymorphism has taken precedence over all other techniques of identification to the species level. The huge expansion of molecular identification assays is related to their sensitivity, reliability and speed to generate high number of identifications. Moreover, these assays can be applied to all stages of development, sex, and on whole specimen or parts (e.g. legs). The first complex for which biologists have designed and validate species specific probes is for the We follow the recommendations as stated in references (1, 2) for the naming of sibling species complex and species group.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t|
Afrotropical | \n\t\t\t\n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[5] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[6] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[7] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[8] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tSSCP PCR | \n\t\t\t[9] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[10] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[11] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[12, 13] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[14] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[15] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[15] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tAS PCR | \n\t\t\t[16] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tquantitative | \n\t\t\t[17] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tAS PCR | \n\t\t\t[18] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tquantitative | \n\t\t\t[19] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tquantitative | \n\t\t\t[20] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplexe AS PCR | \n\t\t\t[21] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tquantitative | \n\t\t\t[22] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tLAMP | \n\t\t\t[23] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[24] | \n\t\t
Palearctic | \n\t\t\t\n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[25] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\theteroduplex PCR | \n\t\t\t[26] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[27] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[28, 29] | \n\t\t
Oriental | \n\t\t\t\n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[30] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[31] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[32] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[33] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[34] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tMultiplex AS and SSCP PCR | \n\t\t\t[35] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[36] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[37] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[38] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[39, 40] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[41, 42] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[43] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tAS PCR | \n\t\t\t[44] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[45] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[46, 47] | \n\t\t
\n\t\t\t | \n\t\t\t\t ( | \n\t\t\tAS PCR | \n\t\t\t[48] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[49] | \n\t\t
Afrotropical and Oriental | \n\t\t\t\n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[50] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[51] | \n\t\t
Neotropical | \n\t\t\t\n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[52] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[53] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[54] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[55] | \n\t\t
Australasian | \n\t\t\t\n\t\t\t\t | \n\t\t\tRFLP PCR | \n\t\t\t[56] | \n\t\t
\n\t\t\t | \n\t\t\t\t | \n\t\t\tmultiplex AS PCR | \n\t\t\t[57, 58] | \n\t\t
List of references of developed molecular identification assays for different anopheline species.
RFLP-PCR (Restriction Fragment Length Polymorphism) assay is based on the amplification of a known locus of the genome and its subsequent digestion by a restriction enzyme (Fig. 1A).
Comparison of RFLP PCR (A) and AS PCR (B) methods and outputs.
The identification of different taxa is made through the polymorphism of the region targeted DNA, revealed by the endonuclease, and resulting in different digestion profiles. Each species is characterized by a digestion profile with bands of different sizes. The need for two steps (amplification and digestion) is time-consuming (digestion can take between 1-3 hours) and expensive. However, an identification assay based on this method is particularly appropriate in the case of entomological survey where anopheline fauna of a region is not known. Indeed, such assay is a priori non-selective and all species encountered give a digestion profile. Examples of RFLP-PCR assays include work on the M and S molecular forms of
PCR (SSCP PCR) is based on the nucleotide mutations in PCR products [59]. The SSCP-PCR (Single Strand Conformation Polymorphism) requires after the PCR amplification a step of heat denaturation of the PCR products, which are cooled very quickly to generate the formation of secondary structures of single stranded DNA. These formations migrate differentially based on their size and conformation, linked to polymorphism of the targeted region. Migration profile is species-specific and thus allows species identification. However, this method is also time-consuming (in particular with electrophoresis of several hours), and can pose problems of reproducibility. It requires special equipment and the use of polyacrylamide gel, more expensive than agarose gels. This kind of assay is not recommended for the identification of a large number of specimens. Some examples of SSCP-PCR tests include work on the
The generalization of partial or complete sequencing of many genomes allowed the development of identification assays based on a single step easier to implement and above all faster. These assays have been named allele-specific (AS-PCR) or PCR amplification of specific alleles (PASA) (Fig. 1B). This kind of assay is very specific and robust. It allows to quickly screen a large number of specimens, it is the most common technique currently being developed (Table 1). The basis of these assays is the identification of target amplification of a region of size known and specific to the different taxa studied. This assay therefore requires prior development of primers specific to each taxa and appropriate evaluation of the intraspecific variation of the targeted DNA region. Most recently developed identification tests are AS-PCR based focusing on the ITS2 differences [10, 15, 18, 25, 27-29, 31, 34, 38-40, 53, 58, 60, 61]; older assays targeted the IGS region (
Usually assays are developed to identify several species in a single PCR. When the primers are combined in a single amplification reaction, it is called "multiplex PCR". When developing a molecular identification assay, primers must first be checked for specificity. Moreover, an internal positive control is highly recommended; outcomes must be "amplification" rather than "no-amplification". Indeed, non-amplifications are indistinguishable from a technical problem such as false negative.
The choice of the locus of hybridization primers can be done either from a systematic sequencing of the regions of interest in the species studied, or from a random screening of regions not localized on the genome. In the first case, a prior sequencing of DNA regions studied is necessary. The choice of primers is then made on the basis of nucleotide differences observed between taxa on the target area in order to obtain fragments of specific sizes of each species (more than 25 bp difference). Thus, the identification is based on the length polymorphism amplified DNA fragments. In the second case, the selection of specific primers is made from screening random non-localized regions of the genome. Screening can highlight size of the amplified fragments specific taxa, and in this case be used for identification. Once bands of specific species are being recognized, they are cloned and sequenced. The fragment generated is called SCAR (Sequence Characterized Amplified Region). Of these nucleotide sequences are defined pairs of primers specific for the species to be identified. The combination of different primers may vary: 1) two pairs of primers for two different amplifications [62], 2) a pair of universal external primers and internal specific primers [63], 3) an universal primer and several species specific primers [10, 13, 15, 31], or 4) several amplifications with species specific pair of primers [37] (Fig. 2).
Different types of AS PCR.
The methods described above are qualitative and determine to which species a given individual belongs. However, despite their usefulness for species identification, they are not suitable for quantifying samples with large numbers of mixed species. Moreover, disadvantages of the conventional PCR approaches include the requirement for post-PCR processing (gel electrophoresis of PCR products) and manual scoring of test samples which can be prone to error due to the similar amplicon sizes generated by certain species. For
The initiative to barcode living forms was set out by [64] and since then the debate on “DNA taxonomy” has not ended with serious concerns about empirical approaches associated with DNA barcode data and their potential to impede rather than enhance the practice of taxonomy and the dissemination of reliable taxonomic information [65]. DNA barcoding is a new technique that uses the variations in short, standardized gene regions (Folmer region of the Cytochrome oxidase I, COI) can be used to identify known species and to discover new ones. This is possible because the variation within each species is low relative to the differences among species. Since its development in 2003, the application of this technology has grown from straightforward taxonomic identification to such fields as biodiversity monitoring and ecosystem reconstruction, with new uses emerging in public health, agriculture, economics and trade, and law enforcement. If a specimen is damaged or fragmented, at an immature stage of development, or part of an undiscovered cryptic species, even specialists may be unable to make identification. Barcoding solves these problems because non-specialists can obtain barcodes from tiny amounts of tissue, in many cases even when it has been digested. The principle relies on specimen identification using a partial sequence for COI. Investigators will identify specimen by first extracting its DNA, then amplifying and sequencing COI before comparing the sequence from the query with COI sequences for all known species. The use of DNA sequences in Diptera predates the formal proposal of DNA barcoding. Particularly extensive is the use of DNA sequences for
In modern morphometrics, size and shape are derived from a configuration of landmarks collected on a non-articulated part, often a single organ. Mosquito species diagnostic using geometric morphometrics generally makes use of the wings because these structures are almost bidimensional and relatively rigid, reducing digitizing error. The most common technique is the landmark-based approach. A few anatomical landmarks available on a wing (or any measurable part of the body) are submitted to specialized analyses to provide size and shape information, with the further possibility to visualize shape changes. A few landmarks do not completely describe the wing, nor do they describe the complete body. However, provided there is anatomical correspondence among individual landmarks, only a partial capture of shape is needed to allow valid comparisons among populations and species. There are also other technical approaches, in particular for those cases where landmarks are not conspicuous. The reader should refer to the following references for detailed information on morphometrics such as mathematical approaches and statistical procedures [4, 66-75].
Various arguments, not only related to cost/effectiveness, should convince most laboratories to apply modern morphometrics. The method is inexpensive. Modern morphometric techniques (at least 2D techniques) do not require more equipment than the one already present in any laboratory of entomology: optical devices (binocular microscope), computers and internet connection. They do not require from entomologists any new practice other than the usual dissecting and mounting, thus new personal is not necessary. The method is fast. While the dissection and sample preparation step might be time consuming, something which itself depends on the group of insects or the organ under study, the morphometric analysis is fast. Various hundreds of specimens can be measured (digitized) in one week, and the analytical steps can be performed in a few days or less. In spite of being fast, the method cannot pretend to quickly identify thousands of specimens. This could be improved with the progress of some specialized software aiming at the automatic digitization of mosquito wings [76]. Although some entomological knowledge is required, there is no need to be an expert in the insect group under study, a skill which is disappearing anyway since a few decades as stated above [77, 78]. The required skill in morphometrics is the same whatever the taxonomic group under study: it is mainly the ability to use specialized software. Morphometric study is a non-traumatic approach, in the sense that it does not impede the application on the same specimens of most other characterizing techniques, including molecular techniques. Actually, the technique could be applied in complement to almost any other kind of study. There are indeed many circumstances in which morphologically distinct species cannot be identified anymore because diagnostic characters were destroyed by the technique of capture or lost in the transport from field to laboratory. Some diagnostic morphologic characters are just a few scales on a given place of the body, and these precious scales are not visible any more on damaged specimens. As an example, the Asian anopheline species
In our experience, obstacles to adopt the strategy to use modern morphometrics in complement of other identification techniques - or as a main approach - are relatively easy to overcome. Modern morphometrics relies on sophisticated mathematical developments. They only require an intuitive understanding to allow a biological interpretation of the data. In the same way as molecular biologists have learned to use different specialized software, morphometricians have to assimilate the use of one or more dedicated software.
Unexpectedly, the picture step may be a problematic one. It is often the only financial investment needed in some laboratories to start applying modern morphometrics. No need however for a sophisticated optico-informatic device to capture the images. Current digital cameras applied to the binocular provide enough resolution and simpler use, even a simple scanner can provide reliable pictures [83]. The resolution, or size, of the picture, must be identical for each image. It should be as high as possible, but there is no rigid rule: the picture has to be taken with the idea to see the anatomical landmarks of interest. An important point is to keep an accurate information of size: size scale should be associated with the pictures. Unless a clear scale could be associated with each picture (Fig. 3), optical zooms should be avoided. And finally, there is no need for a complex imaging software: specialized and free software exists which only need the picture file as input.
A. Landmarks (LM) type I are the centers of the circles or squares. Circles indicate easily recognized LM, squares may be difficult to localize from one individual to another and are not often used. Landmark type II is the top of the curve making the transition between alula and posterior margin of the wing. The scales of the wing have been removed. B. Figure presented in [
Numerical data of shape are x,y coordinates of anatomical landmarks. Depending on the kind of landmarks, homologous landmarks or pseudo-landmarks, shape is the relative position of anatomical points (Fig. 3) or it is a sequence of points describing the contour of an organ (Fig. 4). Accordingly, different statistics apply, involving the Procrustes superimposition to the consensus configuration [72], or the elliptic Fourier analysis [85], respectively. In both approaches, shape changes can be visualized (Fig. 4).
Estimated contours of the male genital leaflet of
Size estimator in modern morphometrics is a single variable which is separate from the set of shape variables. It is thus possible to test for statistical relationship between size and shape (allometry). The landmark-based approach provides a global estimator of size using the totality of wing landmarks, which is called “centroid size” (Fig. 3). It provides information about size changes in as many directions as from the centroid to each landmarks. The centroid size of the wing is highly correlated to the traditional length and width of the wing [86], but not well correlated to smaller inter-landmark distances of the wing [66]. The size of an outline can be estimated in various ways, as for instance the perimeter of the outline or, better, the square root of its area.
In spite of providing many Type I landmarks, the mosquito wing is not easy to digitize because of the presence of scales on the veins. Scales can hide the area where two veins are crossing, so that the user has to guess the likely anatomical point of interest. One strategy is to make an estimation of the digitizing error and consider that with good scores the results can be submitted for publication. The digitizing error can be reduced by using the mean value of repeated measurements [87]; this can be performed also by taking the mean of left and right wings [88]. Phase contrast microscope can improve the relative transparency of the scales helping to localize the junction of two veins [89, 90]. Scales can be tentatively removed before digitizing the wings. Different techniques are used, from mechanical (Fig. 5) to chemical treatment [87, 91-93].
Mechanical scales removal on a
There is maybe a fourth response to that problem, which is to consider that the scale color could define landmarks. Indeed, especially in some groups of the
Taxonomists know of many species being consistently larger or smaller than others, giving size character an undisputed importance for species recognition. Moreover, the size of the wing acquired a renewed importance because of its likely association with wing beat frequencies mediating assortative matings [94, 95]: Stanford et al [96] found an agreement between size differences between incipient species of
For taxonomic use, it is not only necessary to adopt powerful tools exploring morphological similarities, it is also important to share the results. Whenever a piece of DNA is distinguishing two taxa, it can be published, stored as a sequence in the Gene Bank and shared with other biologists or taxonomists. When a morphological, qualitative character is discovered allowing to distinguish two taxa, it can be published and shared with other people. Unfortunately, shape variables are sample dependent and cannot be shared in the same way as genetic or morphologic characters [73]. As shape variables are derived from raw coordinates of landmarks, the temptation would be to use the raw coordinates as reference data. However, when the objective is to distinguish very similar or cryptic species, the measurement error (ME) may represent a significant obstacle. ME is always higher between two users than between two measurements from the same user, so that in any circumstance a one-user data set is the most reliable set of data [73]. Two solutions are presently developed to adapt modern morphometrics to a more acceptable taxonomic use: (i) to share machine-computed coordinates [76], or (ii) to share images instead of coordinates. The latter initiative is already running for bees (http://apiclass.mnhn.fr). It is in development for mosquitoes as a bank of reference images at http://mom-clic.com/clic-bank under the name CLIC (Collection of Landmarks for Identification and Characterization). The need for such a database is underestimated because, as it can be deduced from the low number of works on
While there have been sporadically traditional morphometric studies to help species diagnostic in the
Apparently, mosquito wings show very similar venation patterns among different species and higher taxa, including different tribes. However, Dujardin [66] showed that
Vincente et al [87] studied the intraspecific variation of
Five members of the
The taxonomy of the
We presented here the interest to take into account the modern morphometric alternative for its ability to separate morphologically indistinguishable species, as well as for its unbeatable speed and low cost. Despite promising outcomes, the recent morphometric techniques were not often applied to distinguish anopheline species, and other possibilities, for instance the ones making use of artificial intelligence, were even not considered.
As long as a phenetic approach provides satisfactory scores of species classification, and when the objective is to identify species, its combination with molecular methods could help reducing costs. An integrative approach would not only be less expensive, it would preserve the interest of biologists for the morphological interaction with environmental changes and speciation events.
Climate change occurs because of both natural and human causes. A geographic area that has a particular prevailing weather condition is said to have a particular climate [1, 2]. Over the course of time, earth has gone through several global climate changes, including the asteroid that killed the dinosaurs [3], the ice ages, and the warm period that we are in now [4]. Specific regions of the earth have also gone through local climate changes due to large storms, earthquakes, and volcanic eruptions that mostly only affect the target locations [5, 6]. Since human civilizations started intelligently designing ecosystems by channeling water, doing agriculture, building cities, and so on—we have been intentionally, and sometimes unintentionally, changing climates as well.
\nCivilization arguably did not start contributing to climate change at a global scale until after the industrial revolution with the proliferation of coal-powered steam engines and the burning of fossil fuels into the air [7]. The portable energy transformation device was revolutionary; the abundance with which humans lived and moved increased dramatically. Then, in 1896, Swedish chemist Svante Arrhenius estimated that the long-term effects of coal burning would enhance the natural greenhouse effect, and that a doubling of carbon dioxide in the atmosphere would warm the earth a few degrees Celsius. Modern-day climate models have maintained Arrhenius’s conclusion, and only added more specifics to the predictions, with details such as less average freezing at the earth’s poles, higher sea level, more forceful storms, and various different weather patterns in particular geographies [8, 9]. Oil spills, trash barges, mass pavement, deforestation, various air-borne pollutants, and so on have also affected earth’s ecosystems and climates [10].
\nClimate change is now affecting infrastructure systems by changing the weather conditions in which they must operate. The United States Department of Homeland Security has defined 16 critical infrastructure sectors that are considered vital to the “security, national economic security, and national public health or safety” of the country [11]. These critical infrastructure sectors are: chemicals, commercial facilities, communications, critical manufacturing, dams, defense, emergency services, energy, financial services, food and agriculture, government facilities, healthcare and public health, information technology, nuclear, transportation, and water and wastewater systems [11]. Across these infrastructure sectors, climate change will impact physical assets, operations, and use [12, 13]. As public awareness of the risks of climate change has risen, vulnerability assessments and adaption planning studies have been rapidly emerging in recent years too [13, 14, 15, 16].
\nClimate is typically considered in infrastructure system designs by using several years’ recent weather conditions to specify tolerances. This can be problematic for two reasons. First, because weather is not exactly the same every year, and more robust hardware is typically costlier, investors are often faced with tough risk management problems for low-probability high-impact events. Second, climates are changing. Thanks to advancements in global climate modeling, researchers are now able to forecast changes in future climate conditions and plan for extreme weather conditions with higher confidence. Climate change assessments generally rely on scenarios standardized by the Intergovernmental Panel on Climate Change (IPCC) [17]; however other considerations are made as well for factors such as the anthropogenic change in urban environments [18, 19]. The IPCC standard scenarios are referred to as Representative Concentration Pathways (RCPs), and are numbered corresponding to the amount of radiation forcing increase from the sun associated with the greenhouse gas effect relative to pre-industrial times, for example, RCP 4.5 and RCP 8.5 (4.5 and 8.5 W/m2) [20, 21].
\nThe newest technological advancements in climate change modeling and long-term weather forecasting include high-resolution spatial projections based on “downscaling” techniques. These downscaling techniques aim to improve the geographic and temporal resolution of specific weather projections, including air temperature, wind speed, solar radiation, precipitation, snowpack, and hydrology for specific geographic regions [22, 23, 24, 25, 26, 27]. However, challenges still exist in incorporating climate change data into practice [28, 29, 30]. These challenges range from a lack of understanding of what parameters to use in complex models, to the methods used in the models, to what to do about the results. Significant literature is emerging to disentangle the contribution of different mechanisms to the response patterns, yielding more transparent models and results [31]. Further solutions to these challenges are expected to be met through ongoing collaboration between climate scientists and engineers, which we have included examples for in this chapter for electricity infrastructure and heat waves.
\nElectric power infrastructure broadly consists of three systems: generation, delivery, and demand. In terms of the physical processes, electrical power is created by generators to meet demand via delivery hardware. In terms of functionality however, it is the demand for electric power that drives the development of the other two systems. Reliable electric power is central to urban development, and is a critical service in modern cities as almost all other major infrastructure and services rely on it: commerce, communication, manufacturing, defense, emergency, finance, agriculture, healthcare, information technology, transportation, and water [32]. Climate change can affect energy trade over time in ways that are significant to economics and natural resource consumption. For example, more extreme summer and winter temperatures necessarily result in more demand for cooling and heating, respectively. Climate change can also affect electric service reliability. A shortage of electric power generation, or sequence of faults in the delivery network, can result in an interruption in service at any second. This is why generation and delivery systems are built with multiple redundancies, such that individual component outages can occur safely. Unless there are multiple simultaneous outages, the infrastructure system can still deliver power to buildings and other loads without an interruption in service. Table 1 provides a summary of major climate variables and their associated impacts on the power sector, adapted from [33].
\nClimate hazard | \nKey impacts | \nImpacted segment | \nAdaptation strategies | \n
---|---|---|---|
Increased air temperatures | \n\n
| \nGeneration | \n\n
| \n
\n
| \nDelivery-Transmission & Distribution | \n\n
| \n|
\n
| \nDemand-End Use | \n\n
| \n|
Increase in precipitation | \n\n
| \nGeneration | \n\n
| \n
\n
| \nDelivery-Transmission & Distribution | \n\n
| \n|
Decrease in precipitation | \n\n
| \nGeneration | \n\n
| \n
Sea level rise/increased storm surge during hurricanes and tropical storms/increased nuisance flooding during high tides | \n\n
| \nGeneration/delivery-Transmission and Distribution Demand-End use | \n\n
| \n
More frequent/severe extreme events (floods, typhoons, drought, high winds, etc.) | \n\n
| \nGeneration Delivery-Transmission and Distribution | \n\n
| \n
Summary of key climate drivers and possible impacts to power systems.
Generation is vulnerable to flooding, reduced streamflow, warmer water, and warmer air temperatures, which can all cause a shortage of power supply in the system [34]. There are many ways to physically generate electric power, but to evaluate the effects of climate change we have chosen to broadly categorize them as those that use water, and those that do not as follows. Conventional hydroelectric and water-cooled turbine generators (e.g., nuclear, coal-fired, and some natural gas) use water, and so are vulnerable to changes in three ways. First, flooding can damage physical hardware of above and below ground equipment if that hardware is not sufficiently shielded [35]. For example, sea level is projected to rise by 1–1.4 m by the end of the century, and if that is the case, then 25 coastal plants in California will be at risk of flooding during 1-in-100 year high-tide events [36]. Second, if the water levels in natural sources are too low (e.g., low river flow during droughts), then production capacity can be dependent upon priority level in access rights or reduced to zero if the water level physically goes below the intake pipe [37]. Third, some once-through generators are vulnerable to increases in water temperature in coastal plants, as a certain amount of temperature rise is necessary to cool the generators. Environmental regulations prevent expelling of water that is too hot to be safe for the ecosystem [38]. In August of 2015, the Pilgrim Nuclear Power Station in Massachusetts cut its power because the temperature of sea water used as influent was too high [39]. Power generators that do not use water include dry combustion natural gas and solar photovoltaics. These types of “dry” power generators are generally inland and could be at risk of flooding if they are located in a basin-like landscape that would collect water from a storm. Dry power generators also operate less efficiently under higher ambient air temperatures, which mean they also have lower production capacity to meet peak demand [40]. Dry generators are also vulnerable to changes in humidity that can affect their air circulation systems, as well as flooding and storm-gusty winds in general [33].
\nDelivery systems can be affected by climate change due to higher temperatures causing higher demand, reduced capacity, and congestion; wildfires that can render power lines inoperable due to ionized air; and large storms that can cause physical damage via flooding and high winds that make trees fall on lines [41]. Delivery systems physically consist of various types of power lines that transport energy, transformers which convert the power to different voltage levels, quality devices for efficiency and reliability, and protection devices that interrupt power flows during hazardous conditions. Climate change can cause failures via physical hardware damage or create operational conditions that exceed hardware tolerances. Higher temperatures can cause individual components to become inoperable because protection devices will cut them off if power flow is too high for the weather conditions [42]. Additionally, higher temperatures can result in reduced capacity for above ground power lines to safely carry electricity. If too many components are offline or the capacity of the system is significantly reduced, then power may not be available when it is needed causing cascading failures and blackouts as happened in the US in 2003 and 2011 [43, 44]. Alternatively, if protection devices are not properly calibrated, then components can overheat. This has happened to hundreds of distribution-level transformers during recent record breaking heat waves in the US southwest [45]. Moreover, lines can sag to the point that they permanently deform. Not coincidentally, during these record-breaking heat waves, the air is very dry, and the risk of wildfires is high. If wildfires burn under power lines, then those components can fail as well due to air ionization. Like generators, substations are vulnerable to rising sea levels and storm floods near the coast and in basin-like land areas [36]. Flooding can erode or short the hardware in substations and underground power lines [33]. Lastly, severe storms can blow trees, and other things, into power lines and cause outages.
\nElectric power demand is primarily susceptible to higher air temperatures, which can increase both total energy consumption and the peak demand in regions with significant electric air conditioning [40, 46, 47]. Demand is typically planned for at city- and state-level geographies based on seasonal weather usage patterns, daily weather usage patterns, and local use patterns. In warm to hot climates, the peak electricity demand is usually in the late afternoon during the summer when businesses are still operating and people are coming home and turning on air conditioners [48]. Historically, preparing for higher peak demand means building additional generation and delivery capacity, but policies aimed at natural resource conservation have targeted building and appliance energy efficiency standards which also offset increases in peak demand [40]. In terms of climate change, higher average temperatures and higher maximum temperatures mean more demand for AC usage, which could mean more energy usage over time, higher power demand for ACs to operate at hotter temperatures, and more installations of ACs total in moderately warm climates. The combined effects could be a significant increase in per capita demand [40]. This may be more than local delivery infrastructure are capable of supporting without systemic or network-wide investments [49].
\nThe fault tree in Figure 1 shows the terminal event of a service interruption on the right, and the power- and material/hardware-based-failures that can lead to a service interruption logically proceeding from the left [50]. Hardware failures feedback into the event triggers as their loss of functionality results in a loss of power-flow that could cause an interruption. System operators generally maintain an n − 1 redundancy standard in design at the high-voltage transmission level meaning that the single largest generator, transmission line branch, or substation can fail at any time without any interruption in service [51]. These n − 1 redundancies are represented by octagon boxes and logical AND gates in the figure. Service interruptions due to major component failures only occur when more than one individual component fails at the same time. Such events can lead to cascading failures including blackouts as in the 2011 Arizona-California blackout [52]. The pathway for high demand is colored red because it is a critical condition for a service interruption in a system protected with multiple redundancies.
\nFault tree from heat wave to service interruption.
The two ways that a service interruption can occur as a function of purely rising air temperatures are that there is either not enough total generation to meet total demand, or particular power lines and substations do not have sufficient capacity to deliver power to loads. The following list explains how increases in ambient air temperatures can trigger failures leading to service interruptions consistent with the lettering in Figure 1.
High air temperatures can result in loss of generation capacity and loss of efficiency in the transmission and distribution (T&D) network [36, 53]. If the system is also in high demand, (B), then load can exceed generation. If there are insufficient generation reserves, then there will be a service interruption.
High air temperatures can result in higher demand, especially during the already hot summer months due to increased burden on building air conditioning systems [53].
High air temperatures result in less capacity in T&D lines and transformers [36, 53]. If a circuit is in high demand, then power flow can result in components’ temperatures exceeding safe operating temperatures [52].
If protection devices function correctly, then they will trip (open) the circuit under excessive loading and power flow will be instantaneously redistributed to parallel T&D components [52]. If there is insufficient capacity in parallel branches to deliver power to the load, then there will be a service interruption [52].
If a protection device fails to trip and a circuit is over loaded, then excess heat accelerates the chemical degradation rate of sensitive materials and can result in mechanical failure (E) [54, 55]. Protection devices can fail because they are not accurately designed or calibrated for local climate conditions or other reasons [56]. Depending on the type and location of overload failure, a generator, transmission line, substation, quality device, or other protection device can fail. If a generator fails, then the system state goes to (A) as the system now has less generation. If a line or transformer fails, then the system goes to (C) as the T&D network operates at lower efficiency and or has less power flow capacity. If a power quality device fails, then it goes to (A) or (C) again or directly to excessive loading depending on the circumstances. If another redundant protection device fails, then the cycle of potential failures repeats for additional components on connected circuits.
High air temperatures can result in a protection device failing to trip [56]. The device could be calibrated to a certain power rating that should be lower for the actual air temperature. If that occurs during high loading, then a component can become overloaded and fail as in (ii).
High air temperatures can result in an accelerated physical material degradation rate, which can result in accelerated failures for any electrical devices [57]. The same failure scenarios can occur as described above, with the addition of an undesired trip of a protection device. If a protection device fails with an undesired trip, and there is no redundant power flow, then a service interruption occurs.
How can we know how much electricity demand there will be if weather conditions are more severe than they have ever been in the past? With no past records, how can we know what the future will be? How do we know if there will be sufficient generation resources to meet the demand? These are not straightforward questions to answer as demand and generation are, at the city scale, rather complicated with millions of moving parts. In this case study, adapted from Burillo et al. [40], we show how analysts can produce a reasonable city-scale predictive model using basic computational tools, and simple publicly available data for buildings, electricity demand, and air temperature.
\nWe will consider Phoenix, Arizona and Los Angeles, California as regions because they have summertime peak demands with significant air conditioner (AC) penetration, and are expected to have higher air temperatures in the future with climate change [58, 59, 60]. A simple approach to predicting peak demand for future temperatures would be to plot daily peak electricity demand against daily maximum air temperatures,
A full explanation of the theory and equations are in [40], but the concept in brief has two main parts as follows. First, at a micro-scale, as outdoor thermal forces (sunlight and air temperature) increase, the work that individual ACs do increases and so does their electrical load. In our prior study, we found that the most common AC units (split indoor-outdoor dry air-cooled) have an increase in active load of 1.33% kW per 1°C ± 0.35%. Second, at a macro scale, AC duty cycles increase proportional to the ratio of incoming and outgoing building thermal energy at the thermostat set point. At higher
The results for the peak demand SEM are shown in Figure 2 compared to a straight-line approach. Peak demand in Phoenix is more sensitive to average historical seasonal changes in air temperatures than Los Angeles, but results show that
(a) Peak demand. (b) Peak demand SEM factors. (a) Shows SEM approach results in solids. Straight-line approach shown in dotted lines. (b) Shows the two s-curved lines are expected values.
While city-scale blackouts often make for bigger headlines in the news, neighborhood-scale outages are much more common. In the last case study, we saw how forecasting peak electricity demand was critical for planning generation resource capacity, and how those efforts could be enhanced with better quantitative understanding of climate change. In this case study, based on [61], we incorporate climate change projections at the next level in electricity infrastructure planning and consider the highly complex problem of siting and sizing delivery component capacities.
\nIt is not enough to simply have generation resources in the same city as loads. There must also be lines, substations, and transformers to get the power from the generators to the users, and each of those have their own capacities which are a function of how hot the devices can safely operate at. Where and how should we build immovable field assets with 30–70-year useable life spans? How do we know what the urban landscape, the buildings, the appliance technology, the population, and so on will look like that far into the future? Doing this well is a highly coordinated effort with many steps and iterations across multiple planning departments, as we shall get a taste for below.
\nIf we are going to attempt to model a map of the future infrastructure requirements with any accuracy, then first we need a model that produces an accurate map of current conditions. The full details of our approach are described in Ref. [61], and the concept at brief is as follows. We used high-resolution (2 km2) data for daily maximum ambient air temperatures (
Map of Los Angeles County, California. (a) Peak demand and (b) substation loading in base period.
With a reasonably accurate and verified model of base period electricity demand, and initial loading on delivery hardware, we can use historical climate data to estimate overloading risks in the base period. We do this by re-running our models with the composite image of the highest temperature values that historically occurred in any location at any historical period in time. We also use that temperature image to estimate the reduced capacity on infrastructure hardware. Combining the two together, we can compute the thermally de-rated load factors on hardware as shown in Figure 4 for substations with corresponding definitions in Table 2.
\nMap of Los Angeles County, California substation risks in base period.
Load factor | \nRisk level | \nReference | \nDescription | \n
---|---|---|---|
n/a | \nUnknown | \nn/a | \nSubstation(s) exists in this space according to national database [1], but not shown in SCE DERiM [2], so load factor data were unavailable | \n
0.01–0.5 | \nVery safe | \nAssumption | \nNegligible thermal wear, probably n − 2 reliable if in parallel/redundant configuration | \n
0.51–0.85 | \nSafe | \n15% rule | \nVery low thermal wear, probably n − 1 reliable if in parallel/redundant configuration | \n
0.86–1.00 | \nCaution | \n15% rule | \nSome thermal wear, probably not n − 1 reliable | \n
1.01–1.20 | \nWarning | \n[3, 4] | \nModerate thermal wear, component overloaded, automatic switching may occur within 24 h to 30 days if loading continues at this level depending upon switch gear settings | \n
1.21–2.00 | \nEmergency | \n[3, 4] | \nSignificant thermal wear, component very overloaded, automatic switching may occur within 30 min depending upon switch gear settings | \n
>2 | \nOutage | \n[4] | \nExtreme thermal wear, switchgear will automatically trip to prevent combustion and permanent hardware damage | \n
Substation derated load factor risk metrics.
We can now forecast into the future for a variety of factors. In this case, we considered rising air temperatures, population growth, building stock turnover, housing densification, air conditioning penetration, and air conditioning efficiency. All of these factors were technically specified in either the building energy models or at the census block group in making spatial allocations to the maps. The results are shown for two population growth scenarios, and two energy efficiency scenarios for substation loading in Figure 5. This is what the peak hour could look like during a heat wave in 2060 with the same infrastructure as in the base period. Specific cities and neighborhoods are identified as being at risk of overloading and outages as shown in Figure 5.
\nMap of Substation Risks by 2060.
There are many ways to maintain stability in electric power systems in light of climate change. Several mitigation and adaptation options are listed in Figure 6 for our case studies of insufficient supply-side resources during rising air temperatures, with effects on stability and other factors important for consideration as well. We categorically consider several options in the form of technology implementations, market incentives, and building stock. We consider load variance as an effect explicitly because less variance means more consistent load, more capacity for contingencies, and lower operations and maintenance costs [49]. We also identified effects of those options on several other complex interdependent factors that are priorities for stakeholders too. This discussion should not be considered exhaustive nor advocate any particular option, but simply present several options as we have identified so far in a structured manner.
\nClimate change risk mitigation and adaptation options and effects.
The major tradeoffs between generation technologies—distributed solar PV (with storage and power quality controls) and centralized systems—in meeting demand are: land space requirements, delivery congestion relief, water usage, air emissions, and marginal capital costs. Solar PV can be installed on building roofs, whereas centralized systems require their own dedicated land footprint and delivery infrastructure [62, 63, 64, 65]. When implemented at the distribution level, solar PV can power load directly without going through delivery components that are necessary for central systems. The net effect is a relative decrease in load from the perspective of the grid relative to demand. Yet these distributed systems beg the question of storage given peak demand occurs once the PV systems decline in production of power. At the same time, this will be an important metric to monitor for reliability purposes going forward—if storage is included—as those two values have historically been one and the same. The most prominent fast-ramping central generation technology is combined cycle natural gas plants, which both consume water and emit various gasses into the atmosphere. Combustion-only natural gas plants could be implemented, which would not use water, but would be more sensitive to rising air temperatures, as well as less fuel-efficient, and therefore more costly and emissions intensive per kWh. While levelized costs of solar PV are now at or below parity with bulk generation plants on a per kWh basis, the combined costs of solar PV with storage to provide 24/7 dispatchable energy and regulation services are still higher than traditional central generation plants [66]. Thus, the best options for new resource procurement across competing objectives, will be those that consider the current and future state of the delivery infrastructure.
\nImplementing DER with new buildings may be the most cost-effective way to meet demand associated with growth in areas where delivery infrastructure are already over capacity during extreme heat waves. In such areas, some substations may be able to be adapted with improved heat sinks, forced air, or water cooling systems to increase capacity. But some may not, and overhead power line capacity will still be limited to convective cooling. The cost of increasing delivery infrastructure capacity necessary to meet demand through central generation, or long-distance imported power could be quite significant at $10–130 million USD per substation and $1–3 million USD per mile of line length leading all the way out of the urban center [67, 68].
\nFuture work for vulnerable neighborhoods should consider implementation of adaptation options by considering 24-h load profiles on distribution-level circuits, the total Watt-hours of necessary storage capacity to complement solar PV capacity, and opportunity for network aggregation in supplying ancillary grid services. Circuits with higher portion of commercial and industrial loads may be preferable for the installation of DERs, as their load profiles may more closely match the PV generation profile (peaking at mid-day) allowing for more storage efficiency. Effective implementation of energy storage would reduce load variance by charging during off-peak hours and discharging during peak hours, resulting in a more consistent load, which is more readily manageable by system operators, and therefore has lower operations and maintenance costs [49]. This could occur through some kind of automated and networked market incentives that are available for wholesale markets as of February 2018 [69].
\nImplementation of new bulk generation systems and delivery infrastructure may be more valuable in the northern areas of San Fernando and Antelope Valley. The areas are relatively less developed there and so land should be more readily available for construction. Future studies should consider the reliability and security benefits of redundant central and distributed energy systems, and determine what amount of each, including storage, is optimal for different outage risk tolerances.
\nMore energy efficient appliances can reduce use-phase load, load variance, and thus provide benefits to power systems’ stability. To mitigate risks from heat waves however, focus should be directed towards air conditioner units. Differences in lighting and other appliance efficiencies only affected peak demand in the models by 2% in California, but that state already has aggressive energy efficiency policies, so other areas around the world could benefit more. AC units generally accounted for 60–70% of summertime peak demand within residential buildings, and higher air temperatures resulted in a 3–7% increase in demand per 1°C (1.8°F). Los Angeles County currently has only 45% AC penetration in its residential buildings, meaning that peak demand in just over half of the current building stock does not increase with air temperature. By 2060 almost all buildings could have AC.
\nPolicies that would guide new or replacement ACs based on different performance constraints or different technologies would aid in reducing the risk of excessive peak demand during extreme heat events. It is possible to design AC units that are more efficient under the hottest conditions or that utilize thermal storage to achieve ‘flat’ efficiency curves that do not degrade at the hottest temperatures [70, 71]. For example, developing a new ‘peak performance rating’ for ACs at 50°C (122°F) could be useful to mitigate peak load during extreme heat waves. Doing so could provide incentive for ACs to be optimally engineered for more efficient performance at or near such extreme temperatures. Current standards, SEER and EER [72], are primarily for temperatures at or below 35°C (95°F). The current SEER standard, SEER 13, is already optimized to the point that improvements in SEER ratings in the model up to SEER 21 only affected peak demand by a few percent and were slightly counter-effective in some instances where temperatures exceeded 45°C (113°F) due to tradeoffs in engineering design optimization. Water-based evaporative cooling systems are another option that uses much less electric power, but requires water to operate, and are often not accepted by users as the sole-source of air conditioning due to insufficient comfort levels when the weather is both hot and humid [73, 74]. Further study may be useful to identify the practicality of hybrid designs.
\nSome studies suggest that the traditional utility business model, that couples energy sales to profits, is not compatible with certain energy efficiency goals or large amounts of DER [85]. The former issue is because utility revenues are primarily dependent on total energy sales, but the costs of providing reliable infrastructure are primarily dependent on capital expenditures, operations, and maintenance [75]. Profits increase with volumetric energy sales, and costs are relatively flat. Therefore, financial incentives must exist to be relatively inefficient in some processes. Hence, public regulatory commissions exist to oversee the prices set for ratepayers. The alternative business model is referred to as a “decoupled” market, where “excess” profits are carried forward and accounted for in adjusting the following years’ prices [76, 77]. When utility profits are decoupled from energy sales, load serving entities can implement effective conservation programs without violating fiduciary responsibility to shareholders [78]. This structure has been implemented in several states with positive effects on energy efficiency. For example, California’s per-capita annual energy consumption has remained relatively flat since decoupling was implemented in the 1980s, whereas many other states’ has steadily risen [79]. Market design determines rules by which participants must play [80]. If utilities’ profits were a function of key reliability precursors, such as smaller load variance, then utilities would have a direct incentive to reduce peak load (including shifting it to off-peak hours), resulting in less congestion, higher utilization of lower-cost base-load bulk generation resources, and more contingency capacity for non-stationary extreme heat events.
\nOne philosophy for evaluating public policy is to consider whether the rules are equitable, efficient, transparent, administratively simple, and support achieving greater policy goals [81]. Current retail electricity rate schedules in Los Angeles and Phoenix generally meet these criteria via monthly energy billing with tiered and time of use rates [82, 83, 84, 85]. Charging residential ratepayers monthly based on total energy use is simple, transparent, equitable, and promotes energy efficiency. Higher electricity prices during peak hours helps to reduce peak load by incentivizing ratepayers to take action to shift flexible or non-critical usage to off-peak hours when electricity can be generated at lower cost [86]. Incentivizing ratepayers to turn off loads in the form of demand response relieves congestion on the grid; however, the majority of that relief comes from industrial customers who often switch to onsite diesel power or natural gas combined heat and power units [87]. Rebates are available in some localities for ratepayers to obtain solar PV, storage, or demand management technologies [88]. One-time rebates for building energy efficiency enhancements have also been found to reduce demand and peak load [89]. Overall, these incentives generally reflect the philosophy that electricity is both a critical infrastructure necessity and a non-critical commodity. Electricity is critical for powering infrastructure systems such as water, transportation, food, fuel, communications, and finance [32]. It is also critical in residential buildings for lighting, cooking, cleaning, and climate control.
\nPopulation growth will increase peak demand, but where and by how much will be significantly influenced by decisions relating to the management of urban systems. Housing demand in less developed areas can be met through either single family or multi-family dwelling units. To meet population growth through densification however, most housing demand would need to be met through new multi-family dwelling. In addition to conserving land space, the benefits of building new multi-family unit residential housing can be as much as a 50% lower peak demand per capita than single-family detached units. Those benefits are due to reduced volume and shared walls, which significantly reduce exposure to extreme heat. In addition, street albedo and widths should be considered for urban heat island impacts.
\nClimate change is a broad term used to describe ecosystem disruptions that result in long-term changes in weather patterns. Industrial processes have had various impacts on ecosystems over time, and for the most part business peace treaties have been effective in the form of government regulations to limit climate-altering emissions that are harmful to human health. While electric power generation is not the only contributor to climate change, it has historically been a major one with various emissions regulations developed for the solid, liquid, and air-borne wastes of different processes. Carbon-dioxide emissions, once thought relatively harmless, are now understood to be the primary contributor to higher solar energy retention by the earth’s atmosphere, and thus lower average annual ice formation, higher sea-levels, warmer air temperatures, and various related effects around the globe. As public understanding of the risks of climate change have increased in recent years, several advancements in technology, analytics, and regulations have been piloted to reduce carbon emissions as well. Through advancements in weather forecasting tools, analysts are better able to characterize extreme weather conditions, and support electric power systems planning to forecast peak demand, resource adequacy requirements, delivery infrastructure capacity, and avoid outages during heat waves. While public understanding of the risks of climate change has increased, little knowledge exists of the value of low-cost energy available to the public nor the public risk of unstable power systems. As power systems around the world undergo transformation to lower-emissions technology standards, analysts can use the techniques demonstrated in this chapter to clearly define other risky climate conditions and support development of tools, regulations, and implementations that manage risks of other power stability issues in conjunction with climate change.
\nThe content in this chapter was adapted from the published PhD dissertation of its author [90], which was supported by the California Energy Commission under grant number CEC EPC-15-007, Climate Change in Los Angeles County: Grid Vulnerability to Extreme Events, and the National Science Foundation under grant number 1360509, 2014-2017, Advancing Infrastructure and Institutional Resilience to Climate Change for Coupled Water-Energy Systems. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the California Energy Commission.
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