**2. Physiology of animal heart**

Circulation failure is absolutely a life-threatening event. Unpredictable cessation of blood flow is the worst-case scenario. For studying the problems, we need physiology, and it is necessary to record heartbeat data from freely moving animals.

**Figure 1** shows how to record electrocardiogram (EKG) from invertebrate animals. Two permanently implanted metallic electrodes (+ and −), touching the surface of the heart with extreme caution, were used to record EKG. We used DAM50 C-R coupled AC amplifier (World Precision Instruments, USA) and Power Lab (ADIntrument, Australia) for digital EKG data sampling at 1 kHz.

Nervous regulation of the crustacean heart is well documented by great scholars [1]: Carlson (1904), Alexandrowicz (1932), Maynard (1961), and so forth. The heart receives two kinds of nerve fibers. One is acceleratory nerve (CA) and the other is inhibitory nerve (CI) [3]. The nerves are always active and discharge frequency is ever-changing. Moreover, the brain releases slowly functioning cardio-active substances (peptide) via the nonneuronal hormonal method [6]. As a result, the heart never beats at a steady pace. Heart rate exhibits a dynamic change all through life. Heartbeat interval time is never stable, never regular, and is always fluctuating.

**Figure 1.** *Diagrammatic representation for EKG recording from insect (A), lobster (B), and isopod crustacean Ligia (C).*

#### **3. Analysis of heartbeat**

Mechanisms of cessation of heartbeat could be studied by mathematical methods. We believed that the method might be the frequency analysis because heartbeat is a cyclic behavior. The other candidate method is heartbeat-interval time series analysis. Whichever, we need natural data, EKG. We prepared two specimens,

**35**

*mDFA Detects Abnormality: From Heartbeat to Material Vibration*

carry hidden information that PSD might not capture.

heartbeat data exhibit the SI of around 0.5 (SI = ~0.5).

intact and isolated hearts. We tested two different analytical methods. One is the power spectral density analysis (PSD) and the other is mDFA [5, 6]. As a result, we found that PSD did not well distinguish the difference between the two heartbeats [5, 6]. In contrast, mDFA was powerful and quantitative to represent the inherent

PSD is well known worldwide. People who use PSD implicitly suppose that a complex-look signal is a sum of cosine waves at various frequencies such as 10, 20, 30, 40, and 50 Hz. Real world data, such as heartbeat and material-vibration signal,

With this consideration, the mDFA program was invented by a master-student, Tanaka (see [7]), and an author (TY) tested and verified it [1]. It is about 20 years

We repetitively confirmed [1, 4, 5] that freely moving animals' heartbeat exhibits the scaling exponent (SI, scaling index) of around 1 (SI = ~1.0). In turn, isolated

At a very early stage of the study, we learned that mDFA well distinguishes between intact and isolated hearts as aforementioned. We got an idea: mDFA can be a helpful tool in pathophysiology, because cardiac disease is one of the major causes

We began to record long-term EKGs from model animals. The recordings were started from fresh healthy specimens and were kept continued to the end of their life. Sometimes, the recording period length exceeded 2 years, which is extremely long and painstaking (**Figure 1B**, lobster). In turn, it was, at one time, only 2 h

**Figure 2** shows coconut crab EKG. This specimen was captured in March at a Japanese tropical island, south-west Okinawa. We transfer it to Tokyo in a handcarried baggage. Long-term EKG was recorded in Tokyo instead of the south, tropical zone. The animal eats apples and dry fish meat and lived longer than we expected. Climate in Tokyo got colder in autumn and the tropical crab ended its life in October: non-air-conditioned environment at natural room temperature. SI values in March were ~1.0 (data not shown). The SI values (around 0.9) continued

In **Figure 2**, one can see that SI values decrease when dying. It is of interest that after the cessation of pumping heartbeat, fibrillation remained (**Figure 2**), which

At the terminal condition, the brain is not likely to regulate the heart any longer,

If we look at dying crab specimens, our intuition tells that relevant specimen is

In the meantime, we encountered an unforgettable specimen that died unpredictably (**Figure 3**). At time zero in **Figure 3**, EKG trace looks normal. After checking EKG on PC screen, an author (TY) left Tokyo, setting out on a journey to see a hospitalized family. Two days later, TY returned and looked at PC and discovered that the crab

Many other specimens tested, including crayfish, crabs, insects, and clams, show a SI-decrease-phenomenon when dying (data not shown). We found it typical that when dying, animals show diminished movements and decremental SI-shift

although the heart is still pumping like the isolated heart. We consider that the

terminal condition accompanied by a low SI is a state of brain death.

likely to pass away soon. We define this as "natural death."

**Figures 2** and **3** show example EKGs at terminal conditions.

*DOI: http://dx.doi.org/10.5772/intechopen.85798*

state of the two hearts [4].

**4. Animal heart experiments**

(**Figure 1C**, isopod Crustacea).

indicates that heart muscles still try to contract.

of death worldwide.

to September.

toward 0.5.

since then.

*mDFA Detects Abnormality: From Heartbeat to Material Vibration DOI: http://dx.doi.org/10.5772/intechopen.85798*

intact and isolated hearts. We tested two different analytical methods. One is the power spectral density analysis (PSD) and the other is mDFA [5, 6]. As a result, we found that PSD did not well distinguish the difference between the two heartbeats [5, 6]. In contrast, mDFA was powerful and quantitative to represent the inherent state of the two hearts [4].

PSD is well known worldwide. People who use PSD implicitly suppose that a complex-look signal is a sum of cosine waves at various frequencies such as 10, 20, 30, 40, and 50 Hz. Real world data, such as heartbeat and material-vibration signal, carry hidden information that PSD might not capture.

With this consideration, the mDFA program was invented by a master-student, Tanaka (see [7]), and an author (TY) tested and verified it [1]. It is about 20 years since then.

We repetitively confirmed [1, 4, 5] that freely moving animals' heartbeat exhibits the scaling exponent (SI, scaling index) of around 1 (SI = ~1.0). In turn, isolated heartbeat data exhibit the SI of around 0.5 (SI = ~0.5).


**Abstract**

Forests play an irreplaceable role in linking the water cycle with the functions of soil. Soil water not only enhances the stability of forests, but also its run-off and evaporation affects the growth of plants in different ecosystems. The forest soil water balance is contextualized within the immediate and more global landscapes, in terms of relations of water to the soil environment and bedrock, participation in the local water cycle within a catchment basin and in the global cycle between ecosystems. Modifications by human civilization can have significant impacts, including erosion intensification, eutrophication, salinization, spreading of singlespecies plantations, and regime shifts. Forests regulate the movement of water in the soil environment by reducing the intensity of run-off. Such moderated run-off prevents the occurrence of flash floods, maintaining continuous availability of water for plant and human use. Participation of soil water in the cycling of elements in forests is modified by soil organic matter balance. The preservation of hydric functions in forest soils depends on prioritization of water balance restoration in every catchment basin enclosing the local element cycle. More fundamentally, the development of a synergistically interlinked system, centered around the soilforest-water-civilization nexus, must become an urgent priority.

**Keywords:** water potential, available water capacity, forest soil hydric potential, soil water communication, soil water and human society

#### **1. Introduction**

In this book section, we deal with four mutually coherent sub-sections which, according to the author teams should present the topic progressively from base soilwater interactions, properties and parameters on general level (Section 2.1); landscape and forest-horizontal water relations (Section 2.2); landscape and forest-vertical water relations (Section 2.3) and holistic soil-water-forest-landscape-civilization nexus (Section 2.4).

Soil water refers to any water contained in the soil in liquid, gaseous and solid states. From a forestry point of view, water can be considered as a key factor of production and its sustainability, while also contributing to the stability of the forest ecosystem, since water is essential, not only for nutrition (both as a reaction medium and as a substrate), but also for the growth and development of stands. Soil water in the liquid state acts by its deflocculating, dissolving, hydrolytic and

translocation effects. Soil water is irreplaceable in a wide range of Physico-chemical, biochemical and biological processes and de facto it conditions soil formation and the development of the pedosphere. Oxygen, upon which all anaerobic life depends, is generated from the water-splitting reaction. Entire photosynthetic physiological pathways, such as Crassulacean Acid Metabolism (CAM), are engineered around water conservation.


**3. Results**

#### *3.1. Properties of Dispersions*

#### 3.1.1. Product Concentration and Ion Content

The yield was measured gravimetrically. The gross yield of nanoparticles was corrected for the ion mass, determined by ion chromatography. Sulfuric acid hydrolysis followed by basic neutralization and successive centrifugation led to a gross yield of 41.4 ± 0.8 wt % of CNC from cotton linters. A gross yield of 32.2 ± 0.7 wt % of SNP was achieved from corn starch.

Redundant H2O and excess ions were mostly removed during precipitation and redispersion. The relative nanoparticle concentrations in the hydrolyzed products were 53.6 ± 1.0 g kg−1 of product and 125.2 ± 2.6 g kg−1 of product for cellulose and starch, respectively. The concentration of Na+ of 4.3 ± 0.1 mmol g−1 of CNC and 1.0 ± 0.3 mmol g−1 of SNP, and the concentration of SO4 2− of 2.3 ± 0.1 mmol g−1 of CNC and 0.6 ± 0.0 mmol g−1 of SNP, respectively, indicate an excess of free sulfate ions in both hydrolyzed products. This finding is confirmed by the acidic pH of 2.07 and 2.71 after centrifugation for CNC and SNP, respectively. No other ions were detected, pointing at the purity of the raw materials. Thereby, more than 99.8% of the ionic residuals were removed during the washing step.

#### 3.1.2. Particle Size

Both cellulose and starch feed stocks had a bimodal particle size distribution with a volume-weighted mean equivalent diameter of 50.1 ± 0.4 μm and 7.7 ± 0.0 μm, respectively, while the spans were 5.16 ± 0.1 μm and 1.1 ± 0.0 μm. After the sulfuric acid treatment, microscale hydrolyzed residues or agglomerates due to high salt concentrations with a diameter of 7.4 ± 0.1 μm and 4.3 ± 0.0 μm for cellulose and starch, respectively, were still present. The spans corresponding to the mean diameters were 2.7 ± 0.1 μm and 1.9 ± 0.0 μm, respectively.

The apparent mean size of the nanoparticles was 113.4 ± 0.6 nm for cellulose and 248.7 ± 15.7 nm for starch. Accordingly, the polydispersity indices were 0.225 ± 0.007 and 0.369 ± 0.015. Thus, both nanoscale and microscale particles coexist in the hydrolyzed product [49]. An overview of the dispersion properties and the nanoparticle sizes of CNC and SNP is given in Table 2.

**Table 2.** Properties of nanoparticle dispersions as prepared from cotton linters and corn starch.


**2. Overview of current knowledge and practice**

Given its origin in the financial sector, where the economic approach is prevalent, the first significant developments in the field of infrastructure asset management were led by ac‐ countants and economists. In the late 1980s, the South Australia Public Accountants Com‐ mittee published a series of eight reports alerting all Australian governments for the need to seriously consider the management of their infrastructure if deterioration of valuable public services were to be avoided (Burns *et al*., 1999). Following these reports, Prof. Penny Burns, at the University of Adelaide (Australia), played an crucial role in bringing to attention the importance of the subject and formalizing key concepts and principles (e.g., Burns, 1990; Burns *et al*., 1999). Australian leadership in this field endures to the present day, through both industry practice and initiatives by organizations such as the Institute of Public Works Engineering Australia (IPWEA, www.ipea.org.au), the National Asset Management Steering Group (NAMS, www.nams.au.com), the Australian National Audit Office (ANAO, www.anao.gov.au), the Asset Management Quarterly International (AMQI, www.am‐ qi.com), ACORN Inc. (www.acorninc.org) and the Water Services Association Australia (WSAA, www.wsaa.asn.au).

The Australian and New Zealand AM school is synthesized in the International Infrastruc‐ ture Management Manual, revised and updated periodically (current edition: IIMM, 2011), which addresses different types of public infrastructures and promotes the Total Asset Man‐ agement Process.

IAM has equally seen significant advances in many other countries, such as in the US (e.g. Clark *et al*. 2010; US EPA, 2012), the UK (e.g. IAM/BSI, 2008; UKWIR, 2003) and Portugal (Alegre and Covas, 2010; Coelho and Vitorino, 2011; Alegre *et al*., 2011). From a practical standpoint, very good examples of leading-edge utility practice can be found in Asia (e.g., Singapore PUB), and in Central and Northern Europe, such as in the Netherlands (e.g. PWN - North Holland), Germany (e.g. Munich, Berlin), Norway (e.g. Oslo) or Sweden (e.g. Stock‐ holm, Malmo).

IAM has also registered scientific developments, particularly with regard to algorithms and tools aiming at supporting pipe rehabilitation prioritization and decision-making. Whole-life costing (e.g. Skipworth *et al*., 2002), as well as life time assessment and failure forecasting, are among the most researched topics (e.g., Sægrov ed., 2005; Sægrov ed., 2006; Malm *et al*., 2012; Renaud *et al*., 2011). From 2005, the biannual LESAM (Leading-Edge Strategic Asset Manage‐ ment) conferences of the International Water Association have clearly demonstrated the in‐ creasing interest and recognition of this field of knowledge (e.g. Alegre and Almeida ed., 2009).

Effective decision-making requires a comprehensive approach that ensures the desired per‐ formance at an acceptable risk level, taking into consideration the costs of building, operat‐ ing, maintaining and disposing capital assets over their life cycles. Brown and Humphrey (2005) summarize these concepts by defining IAM as "the art of balancing performance, cost and risk in the long-term".

IAM is most often approached based on partial views: e.g., for business managers and account‐ ants, IAM means financial planning and the control of business risk exposure (Harlow and Young, 2001); for water engineers, IAM is focused on network analysis and design, master planning, construction, optimal operation and hydraulic reliability (Alegre and Almeida ed., 2009); for asset maintenance managers, the infrastructure is mostly an inventory of individual assets and IAM tends to be the sum of asset-by-asset plans, established based on condition and criticality assessment; for many elected officials, since water infrastructures are mostly buried, low visibility assets, IAM tends to be driven by service coverage, quality and affordability in the short run. Common misconceptions include reducing IAM to a one-size-fits-all set of prin‐ ciples and solutions, mistaking it for a piece of software, substituting it for engineering technol‐ ogy, or believing that it can be altogether outsourced. In practical terms, many existing implementations tend to be biased by one or several of these perspectives.


**Physicochemical Properties and Catalytic Applications of Iron Porphyrazines and Phthalocyanines**

Tomasz Koczorowski, Wojciech Szczolko and Tomasz Goslinski

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/68071

#### **Abstract**

Porphyrazines and phthalocyanines belong to porphyrinoids, which are macrocyclic compounds consisting of four pyrrole or indole rings, respectively. The aromatic rings of porphyrazines and phthalocyanines are fused together by azamethine bridges (meso nitrogen atoms) in place of methine bridges present in porphyrins. The physicochemical properties of these macrocycles can be modified in two ways. The first is by substitu‐ tion of metal cation in the core, whereas the second relies on peripheral modification with various substituents. Porphyrazines and phthalocyanines can be modified inside the macrocyclic core with various transition metal cations, including iron(II/III), which impacts their electrochemical properties and influences potential applications in redox reactions. Due to their unique optical and electrochemical properties, porphyrazines and phthalocyanines found many potential and practical applications in medicine and technology. They were mainly researched as photosensitizers in photodynamic therapy, as sensors in biomedical and analytical applications or as building blocks for materials chemistry. This chapter presents physicochemical properties and catalytic applications of iron porphyrazines and phthalocyanines. The first part summarizes the influence of peripheral and axial substituents of iron(II/III) porphyrazines and phthalocyanines on their spectral properties, whereas the second focuses on the electrochemical properties of these molecules. The third part covers the activity of selected iron(II/III) porphyr‐ azines and phthalocyanines of potential value for diverse applications including cata‐ lytic reactions.

**Keywords:** catalytic properties, electrochemistry, iron, porphyrazines, phthalocyanines

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## **1. Introduction to porphyrinoids**

Porphyrinoids are macrocyclic compounds consisting of four pyrrole rings usually linked together through methine or azamethine bridges. Porphyrins (Ps) are planar and aromatic with nominally 22π‐electrons of which 18π‐electrons are engaged in a conjugative path. Porphyrins can be substituted at the peripheral β and methine meso positions. Chlorins and bacterichlorins possess similar structure to porphyrins, and they are defined as dihydro or tetrahydro derivatives of porphyrins. Corrole macrocycle constitutes an 18π‐electron system with the characteristic feature being the lack of a methine bridge between the A and D pyr‐ role rings. In addition, corolles carry inside the macrocyclic core three NH protons, which is different from porphyrins and chlorins, which carry two NH protons. It is worth noting that structurally related corrins with the key natural product cobalamine (vitamin B12) are not aromatic and contain only one NH proton inside the macrocyclic core. Porphyrazines (Pzs) and phthalocyanines (Pcs) commonly known as tetraazaporphyrins belong to synthetic por‐ phyrinoids. Methine bridges are replaced by azamethine (with nitrogen atoms) as the most notable feature of their structure. In addition, Pcs are tetrabenzo tetraazaporphyrins, which have annulated benzene rings in comparison with the Pz core. Formally, in phthalocyanines, unlike in porphyrazines, the azamethine bridges combine four indole instead of pyrrole rings, respectively (**Figure 1**). The derivatives of Pcs can be obtained by substitution of fused benzo‐ rings at peripheral (2,3 or β) and nonperipheral positions (1,4 or α). The tetraazaporphyrins possess unique physicochemical properties due to the presence of a conjugated system of

**Figure 1.** Structures of porphyrins (a), chlorins (b), corroles (c), porphyrazines (d), and phthalocyanines (e).

π electrons, bulky periphery and an ability to coordinate various metal cations inside macro‐ cyclic core. The chelation reaction of the inner NH protons with various metal ions leads to metal chelates, which is a common feature for all porphyrinoids [1–6].

**1. Introduction to porphyrinoids**

102 Recent Progress in Organometallic Chemistry

Porphyrinoids are macrocyclic compounds consisting of four pyrrole rings usually linked together through methine or azamethine bridges. Porphyrins (Ps) are planar and aromatic with nominally 22π‐electrons of which 18π‐electrons are engaged in a conjugative path. Porphyrins can be substituted at the peripheral β and methine meso positions. Chlorins and bacterichlorins possess similar structure to porphyrins, and they are defined as dihydro or tetrahydro derivatives of porphyrins. Corrole macrocycle constitutes an 18π‐electron system with the characteristic feature being the lack of a methine bridge between the A and D pyr‐ role rings. In addition, corolles carry inside the macrocyclic core three NH protons, which is different from porphyrins and chlorins, which carry two NH protons. It is worth noting that structurally related corrins with the key natural product cobalamine (vitamin B12) are not aromatic and contain only one NH proton inside the macrocyclic core. Porphyrazines (Pzs) and phthalocyanines (Pcs) commonly known as tetraazaporphyrins belong to synthetic por‐ phyrinoids. Methine bridges are replaced by azamethine (with nitrogen atoms) as the most notable feature of their structure. In addition, Pcs are tetrabenzo tetraazaporphyrins, which have annulated benzene rings in comparison with the Pz core. Formally, in phthalocyanines, unlike in porphyrazines, the azamethine bridges combine four indole instead of pyrrole rings, respectively (**Figure 1**). The derivatives of Pcs can be obtained by substitution of fused benzo‐ rings at peripheral (2,3 or β) and nonperipheral positions (1,4 or α). The tetraazaporphyrins possess unique physicochemical properties due to the presence of a conjugated system of

**Figure 1.** Structures of porphyrins (a), chlorins (b), corroles (c), porphyrazines (d), and phthalocyanines (e).

Many natural porphyrins and chlorins, for example, heme in hemoglobin and chlorophyll, reveal various vital functions and are responsible for many biochemical processes. Nowadays, porphyrinoids possess potential applications in science and technology, for example, syn‐ thetic derivatives of porphyrins as well as phthalocyanines found many applications in the dye industry and revealed potential for medicine (photodynamic therapy and photodynamic diagnosis) and technology (artificial enzymes, catalysts). Many tetraazaporphyrins have also been studied as analytical indicators, structural elements in materials chemistry, in optical data drivers and microchips, as well as photovoltaic cells. In addition, there is a possibility to utilize porphyrazines and phthalocyanines as catalysts in various organic synthesis reac‐ tions due to their ability to coordinate transition metal cations inside macrocyclic core or in the periphery. Lately, tetraazaporphyrins have also been considered as building blocks in nanotechnology due to their self‐assembly and self‐organization ability (**Figure 2**) [3, 6–19].

Tetraazaporphyrins can be modified using two approaches. The first relies on the introduc‐ tion of various alkyl and/or aryl substituents with sulfur, nitrogen or oxygen atoms into por‐ phyrazine β peripheral positions of pyrrole rings and phthalocyanine α nonperipheral and/ or β peripheral positions of indole rings. The second concerns removal or exchange of cen‐ tral metal cation present in macrocyclic core. By using all of these modification approaches, there is a possibility to obtain macrocyclic compounds of altered physicochemical properties, for example, extended thermal and photochemical stability, increased solubility in organic solvents, improved luminescence and spectroscopic, magnetic, electrochemical properties, photoconductivity and surface activity [1, 2]. Incorporation of iron(II/III) cations into the por‐ phyrinoid core allowed the application of these compounds as catalysts in redox reactions. There is a great interest in the catalytic properties of iron(II/III) tetraazaporphyrins, which dates back to the 1980s. These macrocyclic systems were considered as potential electron

**Figure 2.** The main practical and potential applications of tetraazaporphyrins, M—metal ion.

and/or molecule carriers. For example, iron(III) octaphenylporphyrazine pyridine adduct developed by Stuzhin was found to be a molecular oxygen carrier [20]. Theoretical calcula‐ tions using density functional theory (DFT) and experimental studies indicated that there are significant differences between metalated tetraazaporphyrins and porphyrins. The dif‐ ference in the core size and shape of the macrocycle has a substantial effect on the electronic structure and properties of the overall system. DFT calculations indicated on differences in bond lengths between pyrrole/indole nitrogen atoms and coordinated iron(II) cation in por‐ phyrins, phthalocyanines and porphyrazines, which were 1.98; 1.93 and 1.90 Å, respectively. The smaller coordination cavity results in a stronger ligand field in Pzs than in porphyrins. However, the benzo annulation in phthalocyanines produces a surprisingly strong destabiliz‐ ing effect on the metal‐macrocycle bonding [21, 22]. The calculations also showed how the dif‐ ferences in porphyrinoid (Ps, Pcs and Pzs) structures influence the axial ligand coordination of pyridine and CO to the iron(II) complexes [22].


**1. Introduction**

The Mekong Subregion is linked by common energy challenges. There are challenges in maintaining economic growth and ensuring energy security, while curbing climate change and reducing air pollution. At the intersection of these challenges is the corresponding need to rapidly develop and deploy energy efficiency, low-emissions coal technology, and double the share of renewables in the energy mix towards more inclusive and sustainable growth, as the region's energy demand is expected to rise significantly over the next 30 years [1]. Such an increase is bringing both opportunities and challenges, including climate change, which is a result of fossil fuels. Despite significant progress in recent decades in terms of energy poverty alleviation, countries such as Cambodia and Myanmar are still struggling to provide energy access to their rural populations.

The coronavirus disease (COVID-19) pandemic is another major challenge of our time. It has caused a global economic downturn, with economic output set to contract by 2.5% in 2020. This economic impact has also brought about low energy demand in all sectors. As a result, daily global emission levels fell by 17% in the first quarter of 2020 [2]. However, as governments begin lifting restrictions and business activities resume, so too will the demand for energy. Economic recovery could see levels of carbon dioxide (CO2) emissions bounce back very quickly. Indeed, global data from late May 2020 show record levels of CO2 as countries started reopening their economies [3]. The post-COVID-19 economic recovery will drive increased energy demand, which emphasises the need to secure investment to fill infrastructure gaps.

**Citation:** Phoumin, H.; Meas, S.; An, H.P. Sustainable Energy-Related Infrastructure Development in the Mekong Subregion: Key Drivers and Policy Implications. *Sustainability* **2021**, *13*, 5720. https://doi.org/ 10.3390/su13105720

Academic Editor: Carlos Oliveira Cruz

Received: 13 March 2021 Accepted: 11 May 2021 Published: 20 May 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Quality infrastructure, connectivity, and innovation are considered key for the region to ensure prosperity and sustainable development. In fact, fast connectivity—along with high-quality infrastructure and human resources development in the Southeast Asian region—has already resulted in opportunities for growth. These developments have also lifted living standards through income generation and employment opportunities. They have enabled the region to participate in the production network at different degrees and made it ready to benefit from the global value chain in the near future as improved connectivity attracts more investment, cuts logistics costs, and creates synergies and location advantages [4]. The region is arguably fortunate to have different stakeholders supporting infrastructure improvement that has bridged the missing links in Southeast Asia. However, the influx of investment, particularly in energy infrastructure development, has raised questions about both sustainability and quality, and the identification of partners the region should prioritize working with to promote long-term development sustainability, quality, and innovation in the Mekong Subregion. This report aims to review and analyze major initiatives that drive energy-related infrastructure development in the subregion; conducts energy modeling and estimation for energy demand and supply in the subregion during 2017–2050; and, from there, draws key policy implications that guide high-quality, energy-related infrastructure development.

This paper comprises seven sections. The second section discusses the study's approaches. The third section reviews regional platforms and initiatives for infrastructure development related to the Mekong Subregion by engaging relevant literature. The fourth section examines economic impacts brought by connectivity. The region's energy landscape, the required investment to meet the rising energy demand in the region for the foreseeable future, and the region's energy transition are discussed in the fifth and sixth sections. The final section concludes with policy implications.

#### **2. The Study's Approach**

This study employs several approaches to gathering data and information. Data on economic investment, in particular energy for the Mekong Subregion, are available in different forms and for time periods. The study relies on several past studies conducted by the Economic Research Institute for ASEAN and East Asia (ERIA) for the economic impacts brought by infrastructure connectivity in the Mekong Subregion. For project infrastructure investment, the study uses data and information from past projects and studies conducted by the Asian Development Bank (ADB). For the energy data and analysis, we conducted our own energy modeling and estimation for energy demand and supply for the Mekong Subregion. We also reviewed key regional initiatives for infrastructure investment and development platforms, such as quality infrastructure initiated by Japan at the G20 in Osaka; China's Belt and Road Initiative; the United States (US) Blue Dot Network (BDN); the Free and Open Indo-Pacific (FOIP); and other subregional initiatives, such as the Mekong River Commission, Lancang–Mekong Cooperation, and Mekong– Japan Cooperation.

Our analysis of the economic impacts brought by Mekong Subregion connectivity involves the quantitative assessment of existing and proposed infrastructure development up to 2030. The ERIA study on economic impact assessment employed a geographical simulation model (GSM), which was developed to track the progress on quality infrastructure development in the Association of Southeast Asian Nations (ASEAN) and East Asia. Jointly developed by the ERIA and the Institute of Developing Economies in 2007, the model calculates the proposed infrastructure-related projects for connectivity and innovation and includes a sophisticated level of information on infrastructure development status to facilitate any assessment.

For energy demand and supply in the Mekong Subregion, we employ energy modeling using the Long-Range Energy Alternative Planning System (LEAP) software, an accounting system used to develop projections of energy balance tables based on final energy consumption and energy input and output in the transformation sector. Final

energy consumption is forecast using energy demand equations by energy and sector and future macroeconomic assumptions. For consistency, the historical energy data in the Mekong Subregion used in this analysis came from the energy balances of the International Energy Agency (IEA) for the Organization for Economic Cooperation and Development (OECD) and non-OECD countries [5]. Energy demand and supply has two scenarios: the business-as-usual (BAU) scenario, reflecting each country's current goals, action plans, and policies; and the alternative policy scenario (APS), which includes additional goals, action plans, and policies that countries could achieve with their best efforts given energy policy reforms and technological development. The APS consists of assumptions such as more efficient final energy consumption, more efficient thermal power generation, and higher consumption of new and renewable energy and biofuels.

The study also quantifies the required investment for power generation demand from 2017 to 2050, using the following formula:

$$Investment(i) = GenCapacity(i) \times Unit\ Cost\ (\\$/GW)$$

$$GenCapacity\ (i) = \frac{GWh(i)}{[24\ hours \times 365\ days \times CapF(i)]}$$

where (*i*) is the fuel type, such as coal, gas, hydropower, and renewables; *investment* (*i*) is the required investment amount of fuel type (*i*); *GenCapacity* (*i*) is the generation capacity of fuel type (*i*) in gigawatts; and *CapF*(*i*) is the capacity factor of fuel type (*i*).

The study does not consider other required investments in the power grid or connectivity costs. It only estimates the required generation to meet the growing demand from 2017 to 2050.


**5. Flood risk assessment**

### **5.1 Vulnerability module**

The on-site and remote surveys allowed for the classification of the parameters affecting flood vulnerability, according to the methodology described in Section 2. **Figures 6a, b** and **7a, b** show the frequency distribution and the spatial distribution concerning, respectively, two of the most relevant parameters that compose the flood vulnerability index: the wall orientation, which determines the exposure component of the vulnerability, and the condition of the building, which falls under the sensitivity *Flood Risk Assessment in Urban Areas: The Historic City Centre of Aveiro as a Case Study DOI: http://dx.doi.org/10.5772/intechopen.109867*

**Figure 6.**

*Frequency distribution of (a) wall orientation and (b) building condition parameters.*

**Figure 7.** *Spatial distribution of (a) wall orientation and (b) building condition parameters.*

component. Regarding the former, all the investigated buildings fall into two categories, namely, "partial exposure with openings" or "full exposure with openings", with most of the buildings that present high level of exposure (class D) being located closer to the canal.

For what concerns the buildings' condition, their conservation state can be deemed as satisfactory. Almost 86% of the buildings assessed either are in a good condition (about 45%) or present minor conservation issues, mainly related with small cracks and moisture issues. The remaining 13% of structures face more serious degradation such as significant cracking, material loss, or settlement.

Regarding the heritage status, even though a great amount of the present building complexes are of architectural interest, only 3% of them are listed heritage with local/ municipal interest. To consider the intangible value of such assets, the methodology was modified, without altering its underpinning rationale, to include within category B the status of significant local heritage that was not included in the original formulation.

However, uncertainties arose for several buildings in the assessment of the remaining parameters, namely, construction material and age. This is due to the recent finishing that does not expose the original construction materials beneath and a lack of documentary evidence on the evolution of the building stock in the neighborhood. To address these uncertainties, several assumptions were made. Most of the

buildings with uncertain age were assumed to be built between 15th and 19th centuries, that is, category C. This option not only corresponds to the largest time range and, consequently, the highest probability for a building to be built during it but also is in accordance with the period of evolution of the Beira Mar neighborhood, completed during the 20th century (category B), which would be a less conservative assumption. On the other hand, buildings dating back to before the 15th century (category D) as well as to the 21st century (category A) were easily identifiable, due to their morphological and structural characteristics. Based on the aforementioned assumption, 81% of the buildings were classified as being built between the fifteenth and twentieth centuries.

Regarding the material, masonry and earthen constructions were often hardly distinguishable. Therefore, two cases were conceived. Case 1 has all uncertain construction materials classified as B (Masonry), while Case 2 has all uncertain construction materials graded as D (Earth). For the flood vulnerability assessment, Case 1 is selected, as it is more realistic based on the results obtained from the on-site survey.

Upon the classification, a clear predominance of masonry buildings emerged, accounting for 67% of the assets, assuming them as made of stone or bricks in the first scenario and of adobe in the second one. Nineteen percent of the buildings made of reinforced concrete are newer constructions.

Following this, the geographical distribution of the index is presented in **Figure 8**. The highest FVI value obtained for both the scenarios is 64.6. While this value is not negligible, in both cases, a very small percentage of buildings present a medium or high vulnerability.

Comparing the assessment of two different scenarios, it can be observed that Case 2, as expected, results in a higher vulnerability. Nonetheless, the overall vulnerability is slightly sensitive to the uncertainty in the classification of the material, as demonstrated by the very similar results both in terms of FVI values and distribution. Therefore, only Case 1 is considered for the risk assessment hereafter. The vulnerability is rather affected by the exposure component, with the most concerning buildings located along the canals.

Finally, the buildings are divided into three categories, namely, low, moderate, and high vulnerability (**Figure 9**). Index values of 20 and 40 are set as thresholds [14].

**Figure 8.** *Flood vulnerability index results: Distribution over the study area Case 1 (a) and Case 2 (b).*

*Flood Risk Assessment in Urban Areas: The Historic City Centre of Aveiro as a Case Study DOI: http://dx.doi.org/10.5772/intechopen.109867*

**Figure 9.**

*Distribution of flood vulnerability levels over the study area (a) and histogram with respect to the number of buildings (b).*

#### **5.2 Hazard levels**

The hazard component of the flood risk assessment was analyzed in collaboration with the University of the West of England, which provided flood extents, velocities, and water depth maps associated with return periods of 20 and 100 years—that is, frequent and rare flooding events, as per the Portuguese Decreelaw no. 115/2010 of 22 October. From these maps, the flood depth and velocity affecting each building were estimated, transforming the overlaid data (**Figure 10a**) into building-specific data (**Figure 10b** and **c**).

Within the investigated area, the estimated flood extent for 20- and 100-year return period is the same. Similarly, the flood velocity is equal in both cases, corresponding to 0.05 m/s. The flood depth, instead, significantly changes in the two scenarios. Indeed, for the 20-year return period, the buildings will be exposed to an average depth of 0.93 m and for the 100-year scenario, to an average depth of 0.98 m. Out of the 228 buildings affected by the flood in the two scenarios, a water height between 1.5 and 2.5 m is expected for 26 building under the 20-year return period and 28 under the 100-year return period. This is a significant value, but it represents a low percentage of buildings (5%) in comparison to the total amount.

Water height (y) and velocity (v) are used to calculate a single hazard indicator as follows:

$$\mathbf{H} = \mathbf{y}(\mathbf{v} + \mathbf{0}.5) \tag{2}$$

Based on the classes of hazard, defined in the Portuguese Floods Directive, five hazard levels are considered, namely, negligible, low, moderate, high, and extreme as shown in **Table 1**.

According to the criterion adopted in this matrix-based analysis, the level of flood hazard throughout the study area does not alter much passing from the 20-year to the 100-year peak flow scenario. By observing the distribution of percentages, the results can be deemed as satisfactory, portraying a low level of danger. In terms of spatial distribution (**Figure 11a** and **b**), it is possible to identify two blocks that can be particularly affected: one in the northern part of the city center and one in the southern, always in the flood-prone areas near the canal.

#### **Figure 10.**

*Hazard levels: (a) flood depth hazard map for 100 years return period; (b) flood depth per building for 20 years return period; (c) flood depth per building for 100 years return period.*

#### **5.3 Risk analysis**

By deploying the aforementioned levels of vulnerability and hazard, the flood risk matrix is obtained, as reported in **Table 2**, where the numbers represent the level of risk on a four-point scale.

*Flood Risk Assessment in Urban Areas: The Historic City Centre of Aveiro as a Case Study DOI: http://dx.doi.org/10.5772/intechopen.109867*

#### **Table 1.**

*Distribution of hazard levels for Aveiro.*

#### **Figure 11.**

*Spatial distribution of flood hazard levels (a) and values for the adopted 20-year peak flow scenario (b).*

**Figure 12** shows the risk maps for the two return periods. The flood risks for the 20-year return period (**Figure 12a**) and 100-year return period (**Figure 12b**) are remarkably similar. In a total of 495 surveyed buildings, 77.37% of them present low flood risk; 12.53 and 12.73% for 100 and 20 years, respectively, moderate; and 10.10 and 9.90% for 100 and 20 years, respectively, high. It is noted that for the 20-year return period, the moderate risk is slightly higher, raising more alarm for a dangerous situation in the near future.

It is observed that the buildings with a significant risk are located closer to the canal; they can be again distinguished into two blocks, and also, a significant number of them are located along one of the main streets, R. João Mendonça. Indeed, the

**Table 2.** *Flood risk matrix.*

**Figure 12.** *Spatial distribution of the flood risk results for 20 years (a) and 100 years (b).*

**Figure 13.** *Flood risk per building for a 20-year return period.*

buildings likely affected by the flood hazard, in the two return-period scenarios, are also the most vulnerable within the investigated area (**Figure 13**).

Overall, even though a percentage of about 10% of the buildings can be identified as being at high risk in the next decades, it is concluded that the flood risk for the Beira Mar neighborhood is relatively low, and in view of future mitigation strategies, the effort can be concentrated on the buildings located within the identified flood-prone area.