Selected data of composition and stable isotope ratio of CH4 and CO2.
\r\n\tCongenital hearing loss means hearing loss that is present at birth. I have managed children with hearing loss for many years, and the most touching thing is the light that blooms on the face while the hearing-impaired child heard his mother's voice at first time. The scene of "happy tears" impressed me so much. To hear the voice that has not been heard is so pleasant, as if this ordinary listening experience is a supreme listening enjoyment.
\r\n\r\n\tAge-related hearing loss means a progressive loss of ability to hear high frequencies with aging, also known as presbycusis. Among them are the influence of internal and external factors such as genes, drugs and noise exposure. The studies pointed out that the brain stimulation of the hearing-impaired person is greatly reduced compared with subjects with normal hearing. The connection of auditory cortex and other brain areas has declined a lot, which is probably one of the important causes of dementia or even depression in the elderly.
\r\n\r\n\tNoise-induced hearing loss is hearing impairment resulting from exposure to loud sound. There is actually continuous and endless noise in many workplaces, which may cause chronic and cumulative damage. Some young people often work hard but easily neglect to protect themselves. In addition, in recent years, entertainment noise (such as nightclubs, concerts, and personal listening devices) has caused hearing impairment in young people. These should be avoidable and preventable.
\r\n\r\n\tHearing Science is the study of impaired auditory perception, the technologies and other rehabilitation strategies for persons with hearing loss. Public health has been defined as "the science and art of preventing disease", improving quality of life through organized efforts. To avoid the “epidemic” of hearing loss, it is necessary to promote early screening, use hearing protection, and change public attitudes toward noise.
\r\n\r\n\tBased on these concepts, the book incorporates updated developments as well as future perspectives in the ever-expanding field of hearing loss. Besides, it is also a great reference for audiologists, otolaryngologists, neurologists, specialists in public health, basic and clinical researchers.
",isbn:"978-1-83968-678-8",printIsbn:"978-1-83968-677-1",pdfIsbn:"978-1-83968-679-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"a4b7dbb02ba00e7412422cd5dbffa029",bookSignature:"Dr. Tang-Chuan Wang",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10529.jpg",keywords:"Hidden Hearing Loss, Plasticity, Electrophysiology, Otoacoustic Emission, Newborn Hearing Screening, Genetics, Aging, Hearing Aids, Noise Exposure, Occupational Hearing Loss, Epidemiology, Prevention",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 3rd 2020",dateEndSecondStepPublish:"October 1st 2020",dateEndThirdStepPublish:"November 30th 2020",dateEndFourthStepPublish:"February 18th 2021",dateEndFifthStepPublish:"April 19th 2021",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Tang-Chuan Wang is an excellent otolaryngologist-head and neck surgeon in Taiwan; a research scholar of Harvard Medical School and University of Iowa Hospitals. He worked in the Hospital of the University of Pennsylvania, Boston Children's Hospital, and Massachusetts Eye and Ear. Due to his contribution to biomedical engineering, he was invited into the executive committee of HIWIN-CMU Joint R & D Center in Taiwan.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"201262",title:"Dr.",name:"Tang-Chuan",middleName:null,surname:"Wang",slug:"tang-chuan-wang",fullName:"Tang-Chuan Wang",profilePictureURL:"https://mts.intechopen.com/storage/users/201262/images/system/201262.gif",biography:'Dr. Tang-Chuan Wang is an excellent otolaryngologist – head and neck surgeon in Taiwan. He is also a research scholar of Harvard Medical School and University of Iowa Hospitals. During his substantial experience, he worked in Hospital of the University of Pennsylvania, Boston Children\'s Hospital and Massachusetts Eye and Ear. Besides, he is not only working hard on clinical & basic medicine but also launching out into public health in Taiwan. In recent years, he devotes himself to innovation. He always says that "in theoretical or practical aspects, no innovation is a step backward". 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"41882",title:"Thermogenic Methane with Secondary Alteration in Gases Released from Terrestrial Mud Volcanoes",doi:"10.5772/48232",slug:"thermogenic-methane-with-secondary-alteration-in-gases-released-from-terrestrial-mud-volcanoes",body:'Mud volcanoes are surface expressions of mud accompanied by water and gas originated from deep underground. They are found all over the world. The locations of mud volcanoes resemble magmatic volcanoes, that is, they are concentrated in areas of compressional tectonic settings such as accretionary complexes and subduction zones (Dimitrov, 2002, 2003; Kholodov, 2002; Kopf, 2002). Recent developments in seismic exploration and seafloor imaging have led to the discovery of mud volcanoes not only onshore, but also offshore. The fact that mud volcanoes are found along the compressional area suggests that eruptions are related to the occurrence of volcanic and earthquake activity. Mud extrusion is a phenomenon wherein fluid-rich, fine-grained sediments accompanying the gases ascend within a lithologic succession through conduits from pressurized reservoirs because of their buoyancy. The factors controlling the occurrence of mud volcanoes are considered to be (i) recent tectonic activity, particularly in a compressional regime; (ii) rapid loading of rocks due to fast sedimentation, accretion, or overthrusting; (iii) active hydrocarbon generation; and (iv) existence of thick, fine-grained, soft sediments deep in the sedimentary succession (Dimitrov, 2002). The main factor in mud volcano formation is considered to be a gravitative instability in low-density sediments below high-density rocks induced by fast sedimentation.
The major differences between mud volcano and normal (magmatic) volcano are as follows: (i) mud volcano only releases, as suggested by its name, mud associated with water, whereas magmatic volcano releases ash and high-temperature lava; and (ii) most of the gases released from the former are methane (CH4), whereas the latter releases CO2 and N2, except for water vapor. With regard to difference (i), one may think that the mud volcano is not serious as a natural disaster. On the contrary, in Indonesia for example, more than 30,000 people lost their homes due to the eruption of mud (Mazzini et al., 2007). The eruption of an enormous amount of mud (170,000 m3 per day at the maximum) with the temperature close to 100 ºC buried the Sidoarjo village in Northeast Java (Mazzini et al., 2007). Thus, it is important to understand the eruption mechanism from the view of the disaster caused by the eruption. Difference (ii) is also important, considering that CH4 has a larger global warming potential than CO2 (IPCC, 2001). According to the IPCC report (2001), the global warming potential of CH4 is 62 times higher than that of CO2 in 20 years and 23 times higher in 100 years. The reported CH4 concentration released from mud volcanoes all over the world shows that CH4 dominates more than 90% for most mud volcanoes (Table 1). Furthermore, even if mud volcanoes are in the quiescent period, they constantly release gases into the atmosphere. Considering that magmatic volcanoes are not active in the quiescent period, the consecutive release of CH4 from mud volcanoes is potentially an important problem. Therefore, understanding the source, abundance, and cause of CH4 release from mud volcanoes is necessary to evaluate the global warming and potential resource as energy.
Both the concentration and CH4 flux from mud volcanoes to the atmosphere are important. Thus far, several estimates for global emission have been done, including 10.3 Tg y−1 to 12.6 Tg y−1 (Dimitrov, 2002), 5 Tg y−1 to 10 Tg y−1 (Etiope and Klusman, 2002), 5 Tg y−1 (Dimitrov, 2003), and 6 Tg y−1 to 9 Tg y−1 (Etiope and Milkov, 2004). The estimates include several assumptions that can have large uncertainty in their flux estimation because it is almost impossible to determine the quantity of CH4 released from each mud volcano on Earth. More recently, it has also been reported that gases from mud volcanoes not only originate from visible bubbling in the crater of mud volcanoes but also from soils around mud volcanoes. For example, Etiope et al. (2011) performed flux measurements from soils around mud volcanoes in Japan and showed that total output from soils is comparable with that from vents in the mud volcanoes. Their calculation suggests that global CH4 flux from mud volcanoes is between 10 and 20 Tg y−1 (Etiope et al., 2011). These estimates mean that mud volcanoes represent an important natural source of atmospheric CH4 considered in global greenhouse gas emission inventories.
Understanding the origin of CH4, namely, microbial origin from acetate fermentation, microbial from carbonate reduction, thermogenic, and inorganic, provides information on the process and environment responsible for its generation. The interpretation of the origins of gas is generally based on its stable carbon and hydrogen isotopes (δ13C and δD, respectively), and on the chemical composition of its gaseous alkanes (C1–C4; methane, ethane, propane, and butane). In particular, identifying the gas source is accomplished by plotting the stable carbon isotope ratio of C1 (δ13C1) versus the light gas composition (Bernard et al., 1978), and the δ13C1 versus δD1 (Schoell, 1983). Post-genetic alterations that can affect isotopic and molecular composition of gas should also be considered. The processes include (i) aerobic and anaerobic microbial oxidation of CH4, (ii) abiogenic oxidation, (iii) isotopic fractionation by diffusion, (iv) molecular fractionation by advection, (v) gas mixing, and (vi) anaerobic biodegradation of petroleum and secondary methanogenesis. In this respect, both the chemical and isotopic compositions of hydrocarbons and of CO2 can be useful. In this chapter, we attempt to improve our understanding of the origin of gases released from terrestrial mud volcanoes and seepages by summarizing published data. Further knowledge will allow researchers to use seepage gases as a tracer for hydrocarbon reservoirs and as an indicator of geodynamic processes, hazards, and importance in global changes.
The database used in this chapter includes all terrestrial mud volcanoes and other seeps for which all the following parameters are reported: CH4 stable isotopes (δ13C1 and δD1), compositional ratio of hydrocarbons [C1/(C2 + C3)], and concentration and stable carbon isotope ratio of CO2. The data which satisfy these restrictions are listed in Table 1. From more than 200 data, only 27 data from five countries consisted of all five parameters: 14 mud volcanoes from Azerbaijan, 7 from China, 1 from Georgia, 2 from Japan, and 3 from Turkmenistan; all other data lacked at least one parameter (Valyaev et al., 1985; Etiope et al., 2011; Nakada et al., 2011). Numerous studies have reported on at least one of the parameters above and/or the data of gases collected from the same mud volcanoes in different periods. However, the discussion should be performed using all the parameters above reported in one study, because (i) gases released from mud volcanoes have a complicated history, including secondary alterations, and (ii) compositions and stable isotope ratio can be fluctuated with time even in the same vent. Meanwhile, data from peats, recent sediments in freshwater environments, anthropogenically induced seeps from coal mines, coal-bed CH4 production, and submarine mud volcanoes are not considered.
All the data listed in Table 1 are plotted in the “Bernard” and “Schoell” diagrams, namely, δ13C1 versus C1/(C2 + C3) (Bernard et al., 1978; Faber and Stahl, 1984), and δ13C1 versus δD1 (Schoell, 1983). The former plot, which is widely used for the discrimination of thermogenic and microbial C1, was originally developed by Bernard et al. (1978) through their analysis of hydrocarbons from Texas shelf and slop sediments. In 1984, Faber and Stahl collected sediment samples from the North Sea and modified the Bernard plot by adding the maturation trends of type II and type III kerogen. Figure 1 shows that all the gases released from mud volcanoes in China and Japan fall within or close to the thermogenic field. One of three data in Turkmenistan also falls within the thermogenic field, while two data from Turkmenistan and Georgia are in the intermediate region of the thermogenic and microbial fields. The rest of the data, all from Azerbaijan and one-third from Turkmenistan, fall in the region A, an ambiguous sector above the thermogenic field and right to the microbial. Gases from mud volcanoes do not appear to originate from microbial activities. However, gases from mud volcanoes in Azerbaijan, Italy, Papua New Guinea, and Russia (Taman Peninsula) fall in the microbial area (Valyaev et al., 1985; Baylis et al., 1997; Etiope et al., 2007). The data listed in Table 1 are selected ones that show all five parameters described in the previous section. Hence, the data lacking in other parameters, such as δD1 or δ13CCO2, are not considered in the present work. Then, it should be noted that not all the gases released from mud volcanoes are of thermogenic origin.
Carbon isotope ratio of CH4 vs. hydrocarbon molecular composition diagram (Bernard plot; Bernard et al., 1978).
The “Schoell” plot, developed by Schoell (1983) through a summary of the genetic characterization of natural gases from several basins and areas including Gulf of Mexico, German Molasse, and Vienna (references therein), also shows that the data summarized here do not fall in the microbial field (Fig. 2). Likewise, no data are plotted in the dry thermogenic field (TD). Most of the data fall in the thermogenic field associated with oil or the mixed field. The gases collected in Japan were plotted in the thermogenic field with condensate. Similar to the discussion for the Bernard diagram, the data selected in this work do not cover all the reported data on gases released from mud volcanoes. Actually, gases released from mud volcanoes in Papua New Guinea and Italy fall in the microbial field (Baylis et al., 1997; Etiope et al., 2007). However, until now, any combination of δ13C1 and δD1 is not reported for the gas samples that fall on the dry thermogenic area released from mud volcano, though gases from water seeps and dry seeps sometimes fall on the dry thermogenic field (Etiope et al., 2006; 2007, Greber et al., 1997).
Carbon and hydrogen isotope diagram of CH4 (Schoell plot; Schoell, 1983); To: thermogenic with oil; Tc: thermogenic with condensate; TD: dry thermogenic.
The above figures suggest that thermogenic hydrocarbons are the main component of gases released from mud volcanoes. Considering that about half the gases from Azerbaijan fall in the thermogenic field in the Schoell plot, the reason gases plotted in region A in the Bernard diagram may be due to the fact that mixing between thermogenic and microbial or compositional ratio of hydrocarbons changed during post-genetic alteration. Considering δ13C1 values alone, gases from Azerbaijan can be regarded as thermogenic, whereas Bernard ratios, namely, C1/(C2 + C3), are in the range of microbial origin. Therefore, it can be natural to consider that the data indicate mixing of the gases with two origins. When combining the origins, however, both Bernard ratios and δ13C1 values are high enough to assume mixing between thermogenic and microbial, because the mixing trend generally tracks high δ13C1 value with low Bernard ratio to low δ13C1 value with high Bernard ratio and vise versa. This empirical rule suggests that gases from Georgia and one-third from Turkmenistan are regarded as tracking the mixing trend. On the other hand, gases from Azerbaijan and another one-third from Turkmenistan are not tracking the mixing trend, suggesting that the gases plotted in region A are not due to the mixing of thermogenic and microbial components. The data fall in region A in the Bernard diagram, therefore indicating post-genetic alteration such as (i) aerobic and anaerobic microbial oxidation of CH4, (ii) abiogenic oxidation, and (iii) anaerobic biodegradation of petroleum and secondary methanogenesis. In this respect, discussion using only isotope and compositional ratios of hydrocarbon is not sufficient; CO2 data provide useful information.
In contrast to the δ13C1 values, δ13CCO2 from mud volcanoes show a large variation, from -36.9‰ to +29.8‰ (Table 1). Furthermore, the δ13CCO2 values of the gases from Azerbaijan and China, which were plotted on a narrow range in the Bernard diagram, varied to a large degree. The δ13C1 values of Azerbaijan show a variation of 11.1‰ (from -52.2‰ to -41.1‰), whereas the variation of δ13CCO2 values is 51‰ (from -36.9‰ to +14.1‰). Similar to Azerbaijan, gases from seven mud volcanoes in China show a small variation in δ13C1 (7.3‰, from -45.9‰ to -38.6‰) and a large variation in δ13CCO2 (41.3‰, from -11.5‰ to +29.8‰). Besides the data selected there, similar characteristics also present in other reported data of gas released from mud volcanoes. Seven mud volcanoes in Georgia have a variation of 14.4‰ in δ13C1 values and a 28.7‰ variation of δ13CCO2 (Valyaev et al., 1985). Six vents of a mud volcano in Italy have a range of δ13C1 in 4.3‰ with 29.1‰ variation of δ13CCO2 values (Favara et al., 2001). Thirteen mud volcanoes with 20 reported isotopic ratios in Russia (Taman Peninsula) show a variation of 31.3‰ in δ13C1 and a variation of 41.9‰ in δ13CCO2 (Valyaev et al., 1985; Lavrushin et al., 1996). Twelve mud volcanoes with 15 vents in Trinidad display a variation of 21.6‰ in δ13C1 and a 32.4‰ variation in δ13CCO2 (Deville et al., 2003). Turkmenistan, with six available data of mud volcanoes, shows a variation of 12.5‰ in δ13C1 with 32.1‰ variation in δ13CCO2 (Valyaev et al., 1985). Eleven reported data from Ukraine show a 16.8‰ variation in δ13C1 and a 40.9‰ variation in δ13CCO2 (Valyaev et al., 1985). Seven mud volcanoes in Taiwan, in contrast, display a variation of 27.3‰ in δ13C1 with 17.3‰ in δ13CCO2 (Etiope et al., 2009). These facts clearly indicate that terrestrial mud volcanoes show a large variation in the isotopic ratio of CO2, though most of their δ13C1 values are within a thermogenic range.
In general, the δ13CCO2 value ranges from -25‰ to -5‰ for natural thermogenic and/or kerogen decarboxylation (Jenden et al., 1993; Kotarba, 2001; Hosgormez et al., 2008). In addition, Jenden et al. (1993) suggested that the upper limit of δ13CCO2 value due to the alteration of marine carbonates is +5‰. Therefore, CO2 released from mud volcanoes with δ13CCO2 value above that threshold can be called 13C-enriched CO2. Surprisingly, 14 mud volcanoes in the 28 listed in Table 1 release 13C-enriched CO2. Considering the 134 mud volcanoes described in the previous paragraph (data not shown), 66 (49%) of them show the 13C-enriched value.
Before assessing the relationship between 13C-enriched CO2 and composition and isotopes of carbon in hydrocarbon gas, it is necessary to note that a large variability of the δ13CCO2 value can be found within a mud volcano, both in space (gas samples from different vents) and in time (same vents analyzed in different time). For example, according to Nakada et al. (2011), four mud volcanoes (sites 1–4) are located very close to one another. The chemical compositions of mud and water, as well as relative abundances and stable isotopes of various hydrocarbons, are very similar. In particular, sites 2 to 4 are located within a 500 m distance, suggesting that their reservoir can be the same. Among these sites, however, only a gas released from site 2 has 13C-enriched CO2 (+16.2‰), whereas CO2 from sites 1 and 4 are within a range of kerogen decarboxylation, -8.0‰ and -11.5‰, respectively (gases from site 3 were not collected). Another example can be given by mud volcanoes in Japan. Kato et al. (2009) reported that the δ13CCO2 value of gas released from the Murono mud volcano in August 2004 was +30.8‰. Mizobe (2007) showed that the value of the same mud volcano in May 2005 was +19.2‰ and in June 2006 was +21.2‰. Etiope et al. (2011) reported the value of the same mud volcano was +28.32‰ in May 2010. In contrast, the variation observed in δ13C1 value of the Murono mud volcano reported in these papers was -33.1‰ to -36.2‰. These observations mean that the different vents of a mud volcano can be related to different circulation systems and/or post-genetic processes, and possibly different source pools or reservoirs. Some of the large Azerbaijan mud volcanoes show oil-saturated structures in some vents while others do not. This finding means that mud volcano systems may not be uniform, but can be structured in different systems and isolated blocks. However, the variation of δ13CCO2 with time for the same vent suggests that CO2 carbon isotopes are intrinsically unstable and can be affected by multiple gas–water–rock interactions. According to the estimation by Pallasser (2000), however, the dissolution effect is limited in the carbon isotope enrichments of up to 5‰, suggesting that the main enrichment is due to biochemical fractionation related to secondary methanogenesis.
Name | δ13C1 | δD1 | δ13CCO2 | CH4 (%) | CO2 (%) | C1/(C2+C3) | Reference |
Azerbaijan | |||||||
Airantekyan | –44.9 | –236 | +13.9 | 96.9 | 3.04 | 2423 | Valyaev et al. (1985) |
Akhtarma Pashaly | –47.9 | –159 | –7.2 | 99.1 | 0.68 | 825 | Valyaev et al. (1985) |
Chukhuroglybozy | –41.1 | –215 | +1.7 | 99.5 | 0.42 | 2488 | Valyaev et al. (1985) |
Dashgil | –42.2 | –200 | –6.4 | 99.0 | 0.93 | 2476 | Valyaev et al. (1985) |
Galmas | –47.7 | –167 | +13.7 | 97.4 | 2.06 | 2435 | Valyaev et al. (1985) |
Goturlyg | –42.7 | –198 | –15.4 | 98.9 | 0.99 | 989 | Valyaev et al. (1985) |
Gyrlykh | –49.3 | –204 | +0.6 | 98.4 | 1.54 | 3280 | Valyaev et al. (1985) |
Inchabel | –48.9 | –158 | –30.9 | 94.4 | 5.53 | 1573 | Valyaev et al. (1985) |
Kichik Kharami | –52.2 | –204 | +0.4 | 98.7 | 1.20 | 1646 | Valyaev et al. (1985) |
Shikhikaya | –47.3 | –170 | –36.9 | 98.9 | 0.99 | 989 | Valyaev et al. (1985) |
Shikhzagirli (Ilanly) | –42.5 | –194 | +0.1 | 99.1 | 0.81 | 3302 | Valyaev et al. (1985) |
Shokikhan | –42.0 | –228 | +13.8 | 96.7 | 3.30 | 3222 | Valyaev et al. (1985) |
Zayachya Gora (a) | –44.8 | –198 | +10.5 | 99.0 | 0.81 | 1647 | Valyaev et al. (1985) |
Zaakhtarma | –46.0 | –220 | +14.1 | 93.8 | 6.14 | 852 | Valyaev et al. (1985) |
China | |||||||
site 1 | –45.9 | –229 | –8.0 | 91.6 | 0.20 | 11 | Nakada et al. (2011) |
site 2 | –43.7 | –244 | +16.2 | 89.0 | 0.50 | 9 | Nakada et al. (2011) |
site 4 | –42.4 | –227 | –11.5 | 89.6 | 0.10 | 10 | Nakada et al. (2011) |
site 6 | –40.7 | –252 | +21.1 | 81.5 | 0.14 | 15 | Nakada et al. (2011) |
site 7 | –39.7 | –264 | +24.6 | 80.4 | 0.17 | 13 | Nakada et al. (2011) |
site 8 | –40.7 | –229 | +29.8 | 92.6 | 0.45 | 14 | Nakada et al. (2011) |
site 9 | –38.6 | –242 | –4.8 | 75.8 | 0.31 | 9 | Nakada et al. (2011) |
Georgia | |||||||
Tyulkitapa | –53.1 | –196 | +5.9 | 89.0 | 10.86 | 77 | Valyaev et al. (1985) |
Japan | |||||||
Kamou | –33.9 | –172 | +10.9 | 95.4 | 2.91 | 108 | Etiope et al. (2011) |
Murono vent2 | –36.2 | –175 | +28.3 | 93.7 | 5.62 | 144 | Etiope et al. (2011) |
Turkmenistan | |||||||
Keimir | –48.2 | –213 | –25.2 | 95.3 | 0.89 | 79 | Valyaev et al. (1985) |
Kipyashii Bugor | –43.8 | –176 | +6.9 | 96.8 | 2.79 | 968 | Valyaev et al. (1985) |
Ak-Patlauk | –55.7 | –199 | –16.2 | 94.2 | 3.67 | 44 | Valyaev et al. (1985) |
Selected data of composition and stable isotope ratio of CH4 and CO2.
Figure 3 shows that 13C-enriched CO2 has no relation with CO2 concentrations. Hypothetical end-members were assumed in the figure at 30% CO2 with a carbon isotope ratio of 10‰ and 25% CO2 with δ13CCO2 of 30‰ for fermentation of hydrocarbon oxidation products, and 0% CO2 with carbon isotope ratio of -20‰ and 0.5% CO2 with δ13CCO2 of 0‰ for thermogenic (Jeffrey et al., 1991). The observed data are distributed following the mixing trend between CO2-rich gas produced by fermentation and CO2-poor thermogenic gas. The two trend lines appear compatible with a mixing model and, therefore, with the presence of a residual CO2 related to secondary methanogenesis and anaerobic biodegradation.
Relationship between δ13CCO2 and CO2 concentration. The 2 lines refer to a mixing trend similar to the model by Jeffrey et al. (1991).
The relationship between δ13C of CH4 and CO2 is shown in Fig. 4. The 13C-enriched CO2 seems to occur preferentially in thermogenic CH4, where δ13C1 values are within a range of -50‰ to -30‰. In other words, this relationship seems to have a correlation; the gases showing a low δ13C1 value have a low δ13CCO2 value while a high δ13C1 value corresponds to a high δ13CCO2 value. This observation can imply that the light δ13C1 in the few mud volcanoes (although data are not shown here, gases from Azerbaijan, Italy, Papua New Guinea, and Taman Peninsula fall in the microbial area in the Bernard diagram) with microbial gas is not due to secondary methanogenesis, but simply to primary methanogenesis. On the other hand, thermogenic gas with 13C-enriched CO2 maintains its high δ13C1 value, indicating that δ13C1 value is not perturbed by the secondary microbial gas. The δ13C1 value does not vary to a large degree by post-genetic alteration because the amount of secondary microbial CH4 is small compared with that of the pre-existing thermogenic gas.
Relationship between carbon isotopes of CH4 and CO2.
However, the post-genetic alteration can lead to a significant change in their concentration and isotopic composition for CO2. Oil biodegradation, one of the post-genetic alterations followed by CO2 reduction, is described as follows:
\n\t\t\t\tThis reaction is associated with a large kinetic isotope effect, meaning that the more the reaction proceeds with decreasing CO2 concentration, the more 13C is enriched in residual CO2. Considering that CO2 is a minor component of gases released from mud volcanoes, the concentration and isotopic composition of CO2 can largely be affected by the reaction. The isotope effect of oil biodegradation results in the increase in δ13C of residual CO2, which can easily exceed +10‰ (Pallasser, 2000; Waseda and Iwano, 2008). Occurrence of oil biodegradation is suggested by the high C2/C3 and i-C4/n-C4 ratios (Pallasser, 2000; Waseda and Iwano, 2008) and/or by the presence of H2 gas. For example, all these characteristics are identified in the gases released from mud volcanoes in China, which show a large variation in δ13CCO2 as described above (Nakada et al., 2011). The increase of C2/C3 ratio due to oil biodegradation also leads to an increase of Bernard ratio, meaning that a gas sample plotted on the Bernard diagram will move in an upward direction. Thus, gases that fall in region A, which is geometrically above the thermogenic field in the Bernard diagram (Fig. 1), can be subject to the post-genetic alteration including biodegradation.
The anaerobic biodegradation of oil and natural gas has been document to be mostly limited to shallow reservoirs, generally shallower than 2000 m with temperature below 60 ºC to 80 ºC (Pallasser, 2000; Feyzullayev and Movsumova, 2001). For example, the depth of petroleum reservoirs in the South Caspian Basin is shallower than 2000 m if the data are confined to the gas showing 13C-enriched CO2 (Fig. 5; after Etiope et al., 2009). This observation suggests that mud volcanoes showing anaerobic biodegradation signals will be linked with shallow reservoirs, while mud volcanoes without anaerobic biodegradation will more likely be produced by deeper reservoirs. Anaerobic biodegradation of petroleum and subsequent secondary methanogenesis, however, can also take place at shallower depths even above the deep reservoir along the seepage channels of the mud volcano system.
Carbon isotopic ratios of CO2 vs. reservoir depth in the South Caspian Basin and China.
Recently, Nakada et al. (2011) showed that the reservoir depth of mud volcanoes in Xinjiang Province, China, is deeper than 3600 m, though some of the volcanoes release 13C-enriched CO2. The province hosts a large abundance of petroleum; therefore, many oil-testing wells are made in the province, leading to the knowledge of geothermal gradient and depth of oil reservoir. Nakada et al. (2011) calculated the equilibrium temperature of oxygen isotope fractionation between water and calcite in mud, indicating that the temperature where the water–rock interaction is occurring is 81 ºC for mud volcanoes located close to the Dushanzi oil field. Assuming the mean geothermal gradient of the area is 18 ±1 ºC/km (Nansheng et al., 2008) and that the surface temperature is 15 ºC, the depth of the chamber with the temperature of 81 ºC is calculated to be 3670 ±200 m. The calculated depth is slightly deeper than the oil reservoir at the Dushanzi field (3644 m–3656 m; Clayton et al., 1997). However, considering that the reservoir of saline fossil waters related to petroleum is generally deeper than that of oil and gas due to the difference in density, the calculation by Nakada et al. (2011) was surprisingly well consistent with the observation by Calyton et al. (1997). Then, Nakada et al. (2011) estimated the depth of gas reservoir at about 3600 m by considering that (i) the gases released from the mud volcanoes in the area were thermogenic gas associated with oil and (ii) the gas reservoir is generally located above the petroleum reservoir. The depth of 3600 m is greater than those previously reported for mud volcanoes releasing 13C-enriched CO2, such as those in South Caspian Basin. Thus, the secondary microbial effect that can occur at a relatively shallower depth must be considered separately from the initial thermogenic source in the field in China. Therefore, Nakada et al. (2011) clearly showed that the anaerobic biodegradation of petroleum can take place at a shallower depth. This result strengthens the model that considers a deep reservoir with thermogenic gas and secondary microbial activity occurring along the seepage system above the main deep reservoir.
Terrestrial mud volcanoes release a dominant abundance of thermogenic CH4 related to the activities in relatively deep reservoirs, most of which are in petroleum seepage systems. Maturated petroleum associated with gas and water pressurizes the reservoir, causing gas and water to ascend preferentially through faults (Nakada et al., 2011). Some post-genetic secondary processes can alter the chemical and isotopic composition of the gases. Among these processes, some mixing, molecular fractionation, and particularly, secondary methanogenesis related to subsurface biodegradation of petroleum seem to be significant in changing the chemical and isotopic composition of gases released from mud volcanoes. Mud volcanoes show highly variable δ13CCO2 values even within the same mud volcanoes, such that 13C-enriched CO2 can be found in some vents and not in others nearby, or not systematically changed in the same vent, meaning that 13C-enriched CO2 is, therefore, not an uncommon characteristic. The association of anaerobic biodegradation can depend on the type of microbial communities and physicochemical conditions of the reservoir.
Dengue fever is a mosquito-borne disease caused by any one of four closely related dengue viruses (DenV-1, DenV-2, DenV-3, and DenV-4). Dengue fever is transmitted by the bite of an Aedes mosquito infected with a dengue virus. The female mosquito becomes infected when it bites a person with dengue virus in their blood both indoors and outdoors during the daytime (from dawn to dusk). Aedes aegypti is particularly involved, as it prefers to lay its eggs in artificial water containers, to live in close proximity to humans, and to feed on people rather than other vertebrates.
\nDengue infection is the most rapidly spreading mosquito-borne viral disease in the world. Infections are most commonly acquired in the urban environment. In recent decades, the expansion of villages, towns, and cities in the areas in which it is common and the increased mobility of people have increased the number of epidemics and circulating viruses. Dengue fever, which was once confined to Southeast Asia, has now spread to Southern China, countries in the Pacific Ocean and America, and might pose a threat to Europe. In the last 50 years, dengue virus infections had expanded to many other countries with significant increasing cases [1] up to 2.5 billion people living in endemic countries where about 1.8 billion (more than 70%) in Southeast Asia and the Western Pacific Region [1, 2, 3, 4]. About 50 million dengue infections occur every year [2, 3], and approximately 500,000 patients are hospitalized of whom dominated by children [2, 3, 4, 5, 6, 7]. The increasing incidence and geographical spread of dengue virus were more likely driven by demographic and societal changes such as population growth, urbanization, and modern transportation [8]. The traveler movement also contributed to the risk of contracting dengue disease from nonendemic countries to endemic dengue areas to nonendemic regions where competent mosquito vectors are currently found [9, 10, 11, 12].
\nIndonesia, with 257.5 million inhabitants and 17,500 islands spread across the equator, poses as the largest archipelago country in the world [13], comprising 3.1 million km2 of ocean (62% of the total area) with a coastline of 81,000 km and approximately 2 million km2 of land (38% of the total area). Its tropical climate and subsequent relative high humidity makes Indonesia favorable conditions for vector-borne disease transmission. The increasing trend of dengue infections over the current decades putting Indonesia as one of endemic area for dengue fever and tread both the people as well as travelers visiting the archipelago [14]. Its burden is a result of a constant ground of established infections in the past period, combined with epidemics of emerging infectious diseases (EID) [15]. This chapter describes the dengue fever status or situation in Indonesia, its vulnerability among population, the future challenges, and the disease prevention and control.
\nIndonesia is reported as the second largest with dengue fever cases among 30 endemic countries. The number of cases of dengue fever is most prevalent in the provinces of East Java, West Java, and Central Java. However, there are a number of provinces that are vulnerable with its high incidence rate of dengue fever. In 1968, the first 58 dengue cases were reported in Indonesia from the city of Jakarta (DKI Jakarta) and Surabaya (East Java) [16, 17, 18, 19]. Since then, the sharp increasing numbers of cases and spreading to many other geographical locations have been reported [16, 17, 20, 21, 22, 23, 24, 25]. The epidemiology of dengue fever in Indonesia has been described mostly in the form of case series, reporting on single outbreaks, or clinical and virological studies in confined geographical locations and selected years [26].
\nA study in 2014 reported that the annual dengue fever incidence increased from 0.05/100,000 in 1968 to ~35–40/100,000 in 2013. The highest epidemic occurred in 2010 with the incidence of 85.7/100,000 population. The data revealed declining of case fatality rate (CFR) from 41% in 1968 to 0.73% in 2013. Dengue cases increased among ages during the observation period up to 1998 with the highest incidence of aged 5–14 years. From 1999 onward, the trend of dengue incidence increased among those aged 15 years or over. This study indicates incidence of dengue fever increased rapidly over the past 45 years in Indonesia with peak incidence shifting from young children to older age groups [27].
\nThe threat of dengue fever among children was emphasized clearly on a recently published study among 3194 children aged 1 through 18 years who lived in 30 different urban neighborhoods. Children blood samples were drawn for antibodies to dengue, an indication that someone has been infected with the virus in the past, and found that 69.4% of all children tested positive for dengue antibodies. Among the age groups, positive antibodies found 33.8% at the group of 1–4 year olds, 65.4% at the group of 5–9 year olds, 83.1% at the group of 10–14 year olds, and 89% at the group of 15–18 year olds. The first time to become infected with dengue was at the age of 4.8 years as the median, and in addition, 13.1% of children on average get their first dengue infection each year. It was also found that the more people in a household who had been diagnosed with dengue since a child’s birth, the more likely the child were to test positive for dengue antibodies [28].
\nThe incidence rate (IR) for every 100,000 population in seven provinces were found over 100 or are prone to dengue cases. The seven provinces are Bali (484), East Kalimantan (306), DKI Jakarta (198.7), DI Yogyakarta (167.9), North Kalimantan (158.3), Southeast Sulawesi (123.3), and South Kalimantan (101.1). The lowest IR is achieved by Papua province (11.8) and West Kalimantan (12.1) (Figure 1). The whole of Indonesia is high (IR is 78.0). In general, the increasing number of dengue fever cases is more likely followed by the spread of the cities and districts infected in all of 34 provinces in Indonesia (Figure 2). From the total of 497 cities and districts in Indonesia, about 80% have reported the dengue fever cases in 2017.
\nIncidence rate (IR) of dengue fever per 100,000 population by province in Indonesia 2016 (source: DG of CDC MOH 2017).
Incidence rate (IR) of dengue disease per 100,000 population and number of cities/districts infected in Indonesia 1968–2016.
In the context of dengue fever mortality, as many as 1229 people died in 2015 from the disease caused by this dengue virus. Throughout the history of dengue fever in Indonesia, the highest death rate occurred when first time the disease was discovered in 1968 in Surabaya. Of the 58 people infected, 24 lives were lost. In 2016, the highest percentage of CFR was obtained in Maluku Province (6.0%), Gorontalo (6.1%), and West Papua (4.6%). Provinces with the lowest CFR were achieved by Papua (0%), DKI Jakarta (0.1%), and NTT (0.2%). In some provinces, dengue disease was an outbreak in 1998 and 2004 that caused 79,480 people and 800 more deaths. In subsequent years, there has been reported a decrease in the case of death but note that the number of cases continues to increase. In 2008, there were 137,469 cases and 1187 deaths. In 2009, there were 154,855 cases and 1384 deaths [29].
\nStudies on Indonesian vulnerability to climate change were mostly focused on mitigation aspects, such as water scarcity, reduction emission from deforestation and degradation (REDD), the forest conservations, disasters, land drought, floods, and others. Meanwhile, the vulnerability study on adaptation is still rare, especially to human health. In 2013, Research Center for Climate Change—University of Indonesia (RCCC-UI) initiated a study on vulnerability of dengue disease to climate change/variability in collaboration with the Directorate of Environmental Health of the Ministry of Health and supported by Indonesia Climate Change Trust Fund (ICCTF). The study involved 20 districts/cities in 5 provinces namely West Sumatra, Jakarta, East Java, Bali, and Central Kalimantan which were selected based on the availability of monitoring station of the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG). The dengue disease vulnerability components were generated based on bionomic mosquito and habitat, pathology dengue disease, and factors related to dengue disease occurrence. The exposure variables include land use (settlement, offices, business, schools, etc.) and population density. The sensitivity variables include breeding places and resting areas of Aedes mosquitoes, pupa and adult density, incidence of dengue fever, and population mobility. The adaptive capacity variables include availability of health services (number of hospitals, clinics, and public health centers), treatment management and skilled providers, implementation of dengue fever intervention program, community participation and involvement on dengue fever prevention program, and personal protection behavior. The Intergovernmental Panel Convention for Climate Change (IPCC) vulnerability analysis was implemented to gain the coping range index of DF for each city/district [31]. The coping range index (CRI) = 1 (blue) indicates the people vulnerability of having dengue fever is very low and located at quadrant between low exposure and sensitivity index and high adaptive capacity index; CRI = 2 (green) indicates the people vulnerability of having dengue fever is low and located at quadrant between high exposure and sensitivity index and high adaptive capacity index; CRI = 3 (yellow) indicates the people vulnerability of having dengue fever is medium and located at quadrant between medium exposure and sensitivity index and medium adaptive capacity index; CRI = 4 (brown) indicates the people vulnerability of having dengue fever is high and located at quadrant between low exposure and sensitivity index and low adaptive capacity index; and CRI = 5 (red) indicates the people vulnerability of having DF is very high and located at quadrant between high exposure and sensitivity index and low adaptive capacity index (Figure 3) [30].
\nThe coping range index (CRI) of dengue disease vulnerability.
A study of Research Center for Climate Change—Universitas Indonesia 2013–2014 reported that in almost all districts/municipalities under study (in 17 out of 20 regencies/cities) indicated a very serious vulnerability condition of very high coping range index (CRI) (red = 5) since 2005. Very high CRI was found in 75% of regencies/cities in West Sumatra province (City of Padang in 2005, 2007, 2008, 2009, and 2012; Padang Pariaman Regency in 2008, 2011, and 2012; and City of Padang Panjang in 2007 and 2008), all of regencies/cities in Bali province (City of Denpasar in 2006, 2009, and 2010; Jembrana Regency in 2007; City of Badung in 2007, 2009, and 2010), 80% of regencies/cities in East Java province (City of Surabaya in 2007, 2008, 2009, 2011, and 2012; Malang Regency in 2007, 2008, 2009, 2011, and 2012; City of Pasuruan in 2007, 2008, 2009, 2010, and 2011; Sumenep Regency in 2007, 2008, 2009, 2011, and 2012), all of cities in Jakarta province (City of Central Jakarta in 2005, 2006, 2007, 2008, 2009, and 2012; City of North Jakarta in the year 2006–2012), half of cities in Banten province (City of Tangerang in 2007–2012), all of regencies/cities in Central Kalimantan province (City of Palangkaraya in 2006, 2008, and 2012; Kotawaringin Barat Regency in 2005–2008 and in 2012; Kotawaringin Timur Regency in 2008, 2010, and 2011; Barito Utara Regency in 2008). High CRI (brown = 4) was also happened more often before and following the years of the very high CRIs occurrences in the regencies/cities [30]. Thus, this concluded that dengue fever is in the level of seriously vulnerable to people living in the regencies/cities under study in Indonesia. Figures 4 and 5 show the dengue fever vulnerability among cities/districts in 2012 in the provinces of Jakarta/Banten, Bali, Central Kalimantan, and East Java.
\nMap of CRI of dengue fever vulnerability in Jakarta/Banten and West Sumatra in 2012.
Map of CRI of dengue fever vulnerability in Bali, Central Kalimantan, and East Java in 2012.
Dengue emerged as a public health burden and has become increasingly important, with progressively longer and more cyclical epidemics of dengue including cases of dengue with alarm signs and severe dengue. In Indonesia, although some programs and control efforts have been performed, both the incidence and case fatality rate are still high and not showing significant changes. There are still some challenges that need to be handled, such as surveillance system, availability adequate laboratory, community knowledge, awareness, and involvement against dengue, many new cases reported from new city or district, high mobility of dengue fever’s carrier, density of community in the city/district central, access to health centers, and the availability of drugs and vaccines.
\nSurveillance for this vector-borne viral disease remains largely passive and based on the hospital report which is the estimation of real cases still underreported. It was also reported that many health centers and clinics were without adequate laboratory support. This will lead increasing of referral activities to hospitals with the consequences of time spent and transportation challenges in rural areas. Some studies found about one-third adult population with sufficient knowledge about dengue fever and its fast spreading to other people. However, only about 17% of them aware and clearly know the way for prevention [31, 32]. In addition, the high number of dengue fever incidence can also be caused by increasing Aedes aegypti mosquito breeding places, mosquito habitat, more effective mode of transmission, more frequent dengue fever course, shorten dengue fever symptoms, access for dengue fever treatment. Home conditions such as governance and the layout of goods at home can also affect the high number of dengue fever incidence.
\nIndonesia is a country with a vast region, varied geographic and biodiversity, populated density, and characteristics of various populations. In the last decade, several new administration districts developed with the newly reporting and recording management systems. This will lead underreporting of dengue fever both from the passive surveillance and the number of real cases estimation. The increasing number of people and the area of dengue fever spread in Indonesia is due to the high population mobility, the development of urban areas, climate change, increasing population density, and changes in population distribution. Climate change causes changes in rainfall, temperature, humidity, and air direction thus affecting the breeding of Aedes aegypti mosquitoes.
\nThe last and most important thing of the challenges is community participation. The participation of the community to participate consistently to keep the environment from dengue is still difficult. Various breakthroughs by government such as 3 M plus (draining, covering, burying or utilizing/recycling and all forms of prevention, such as to apply powder of larvae-killers in water tanks, to use mosquito repellents, to keep fish predators to consume mosquito larvae, etc.) movement, Jumantik (volunteer or student who periodically monitor Aedes larvae on water storages at home) and so have long been circulated. But people who forget and bored easily become a problem. For example, after some time, there was no extraordinary incident, the community considered it safe and careless, consequently when the case exploded, people just reacted [33].
\nAmong other challenges, passive surveillance systems tend to underestimate the burden of communicable diseases such as dengue. By utilizing the data from the Indonesian surveillance system and associated health system parameters, a study to estimate the proportion of dengue was conducted by Delphi panel in 2017. The iterative estimation was generated by calculating the expansion factors (EF), the ratio of total and reported cases during the presentation of medical and epidemiological data and subsequent discussions. The data revealed that from all of symptomatic Indonesian dengue episodes, 57.8% enter healthcare facilities to seek treatment but only 39.3% of them are diagnosed as dengue. Furthermore, only 20.3% of them are subsequently reported in the surveillance system. Public sector found dominating occurrence of hospitalizations and followed by private sector for ambulatory episodes (∼55%). Therefore, estimations gave an overall EF of 5.00; hospitalized EF of 1.66; and ambulatory EF of 34.01 which, when combined with passive surveillance data, equates to an annual average (2006–2015) of 612,005 dengue cases, and 183,297 hospitalizations (Figure 6.). The findings are lower than those similar estimations published elsewhere, perhaps due to case definitions, local clinical perceptions, and treatment-seeking behavior [34].
\nEstimated annual number of dengue cases and hospitalizations in Indonesia following adjustment of surveillance reports with EFs, and their 95% confidence intervals (CIs), 2006–2015.
The goal of WHO Global Strategy is to reduce the burden of dengue. Its specific objectives are: (1) to reduce dengue mortality by at least 50% by 2020, (2) to reduce dengue morbidity by at least 25% by 2020, and (3) to estimate true burden of the disease by 2015 (the year 2010 is used as the baseline). The implementing strategy is expected to pave the way for reducing dengue morbidity and mortality nationwide through strengthening local and national capabilities, as well as regional coordination. National Dengue Control Program in Indonesia is currently implementing WHO Global Strategy 2012–2020 that promotes coordination and collaboration among multisectoral partners, an integrated vector management approach and sustained control measures at all levels. Dengue is an ecological disease, therefore coordination and collaboration by all sectors within the government, communities, civil societies, private sectors, and media need to be strengthened. All sectors should harmonize the prevention, surveillance (entomological and epidemiological), and case management with the existing health systems, in order to make the program sustainable, cost-effective, and ecologically sound.
\nIt has long been believed that preventing and reducing dengue virus transmission was very depended upon vectors control (Aedes sp.) or interrupt the human-vector contact. Activities to control transmission should target Ae. aegypti (the main vector) in the habitats of its adult stages as well as the immature. The high death toll from dengue fever demands people to stay alert to possible outbreaks of this disease in their neighborhoods [35]. Therefore, it is important for the community to collectively jointly create a healthy environment free of larvae to suppress the incidence of dengue disease. The prevention and control programs need to be undertaken with specific commitments from stakeholders from the top to the bottom levels. Currently, the Ministry of Health has launched a program of Nest Mosquito Eradication Program (PSN) through 3 M plus way.
\nGiven the wide area in the tropical temperature, high population density in urban area, and various geographic and biodiversity, putting Indonesia as a natural potential for the habitat of dengue viruses. The number of dengue fever cases reported dramatically increases since it was firstly found in 1968 and spread out almost in 80% cities and districts in Indonesia in 2016. Many of those cities and districts were very vulnerable and putting million people at risk to the disease in 2012. Some challenges are still heading in the front of the prevention and control implementation actions. However, keeping spirit for struggling to combat dengue fever in Indonesia along with full commitment and involvement of community are urgently needed as well as to revitalize dengue disease eradication programs at every stage with close monitoring implementation.
\nIn addition, technical guidance and increased skills of health officers are indispensable. Socialization of a hands-on program activities in particular and increased capacity and active participation of community on the action could be a joint action in preventing the increase in dengue disease associated to climate change.
\nThe author declares no competing financial interests.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. 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