*2.2. Procedures*

The first data collection (T1) was conducted in November 2019 (non-COVID time, hereinafter NoCoT). The patients were evaluated using the following clinical scales: the Mini Mental State Examination (MMSE), Brief Psychiatric Rating Scale (BPRS), and Kennedy Axis V (K Axis). The second data collection (T2) was conducted in April 2020 (COVID time, CoT). The patients were evaluated with the same scales as those at T1, but specific items were added on COVID-19 to investigate the psychiatric patients' knowledge and risk perception about the COVID-19 pandemic. Information on COVID-19 was collected through self-report items (i.e., "How did you become aware of the spread of COVID-19?"; "What is COVID-19?"; "Did you participate in community training sessions on this health emergency?").


*4.8. Statistical Analysis*

The results of the study were analyzed using Statistica 13.0 software (StatSoft, Cracow, Poland). The results are presented as arithmetic means (*x*) and standard deviations (SD). The statistical significance was set at *p* < 0.05. Prior to all statistical analyses, the normality of the distribution of variables was verified using the Shapiro-Wilk test. The paired sample t-test was used to determine the significance of differences in VO2max, WRmax between the two trials in different conditions. Furthermore, due to the lack of normality of distribution, the Wilcoxon test was used to determine the significance of differences in delta values in lactate concentrations (Delta LA) between the trials. The intergroup

differences between the research trials (condition × time of measurement) were determined using the two-way ANOVA for repeated measures. When significant differences were found, the post hoc Tukey's test was used. If the normality assumption was violated, the Friedman test was applied, whereas when significant differences were found, we used the post hoc Friedman test. The comparisons of repeated measurements (normoxia vs. hypoxia) were assessed by the Wilcoxon signed-rank test.


**2. Optical properties of the scatterer that influence polarization**

The scattering through soybean oil is the principle mechanism that modifies the initial polarization state of the incident light. The polarization state of light after a single scattering event depends on the direction of scattering and incident polarization state. [26-27] In many turbid media such as tissue, scattering structures have a large variance in size and are distributed or oriented in a complex and sometimes apparently random manner. Because each scattering event can modify the incident polarization state differently, until finally the polarization state is completely randomized. An important exception is when the media consists of organized linear structures, such as birefrengent soybean oil, and then the phase retardation between orthogonal polarization components is proportional to the distance traveled through the birefrengent medium. The phase retardation of the scattering medium is given as.

$$\delta = \frac{2\pi\Delta n\chi}{\lambda} \tag{1}$$

The phase retardation measurement through turbid media is aimed at retrieving useful information from such multiply scattered light. The behavior of light in random media is well-known from the extensive study of wave propagation. Light traveling in a random medium can be classified into three categories, the ballistic, the snake and the diffuse light. The ballistic light either remains unscattered, or undergoes coherent forward scattering in the medium. This light travels undeviated and has the shortest path length in the medium. The snake light is that which undergoes near-forward scattering, and follows path that undulate about the ballistic path.[28] The diffuse photons largely exceed the other two categories in number and undergoes multiple scattering. We considered all three kinds of photons in our study.

A large number of different experiments are possible if one wants to study the polarization dependent scattering properties of turbid media. The probing light may be linearly polarized at various angles, right and left-hand circularly, or elliptically polarized. Light coming from the scattering medium can be analyzed in the same numerous ways. However, only a few measurements are needed to completely characterize the optical properties of any material. The necessary procedure is elegantly demonstrated by the Stokes-vector Mueller matrix approach to polarization and light scattering.


Appendix

See Table A1.

#### Table A1.

Formulas for the three spatial covariance functions used in this analysis.

Process-Based Statistical Models Predict Dynamic Estuarine Salinity DOI: http://dx.doi.org/10.5772/intechopen.89911


2. Pathophysiology

The interface between the central and peripheral nervous systems is known as the transitional zone (TZ) [46], and the regenerating capacities are influenced by both of them. The first is rich in astrocytes that create channels through which motor fibers pass [15]. The latter has Schwann cells that secrete neurotrophic factors (NFs) with higher regeneration abilities [47].

NRA disconnects the transverse arch that exists at each spinal level between the posterior horn sensory, the lateral horn autonomic and anterior horn neurons [23] as well as disconnection of the DRG neurons from the bulbar and thalamic sensory nuclei [48]. NRA also induces loss of synapses and dendritic arborisation, fiber degeneration, neuronal death, posterior spinal column degeneration and glial proliferation [23, 48]. The synaptic and neuronal changes in the posterior horn produce neuropathic pain [24, 48, 49].

Soon after avulsion anterior horn motor neurons (MN) and sensory neurons at the dorsal root ganglion (DRG) undergo apoptosis [8–17]. Inside the avulsed NR itself, there is a Wallerian degeneration with axonal and myelin loss [18]. The muscles, devoid of nervous impulses, undergo atrophy and fibrous transformation [19, 20]. At the SC, the neurons suffer loss of synapses with destruction of previous neuronal networks and creation of new anomalous ones that will lead to abnormal nerve impulses which might induce chronic neuropathic

After complete NRA, spontaneous regeneration is impossible [9]. In case of a single NRA, recovery coming from nearby healthy ones can be expected in neonates but not in adult patients [25]. Ventral root surgical reimplantation has been attempted both in experimental

Axonal regeneration is stronger in direct ventral NR reimplantation [26, 28]. This is rarely possible [4, 7, 29, 30], so peripheral nerve grafts (NGs) are used to cover the gap between the SC and the remains of the avulsed NR [31–33]. These NGs are usually taken from a peripheral sensory nerve (medial antebrachial cutaneous, radial cutaneous, and saphenous), which is not the ideal situation as motor nerve regeneration is worse if sensory nerves are used as donors compared to mixed or pure motor nerves [34–36]. Acellular conduits have also been used, but

Surgical repair of spinal NRs after traumatic avulsion in live human beings was considered technically impossible until the pioneering work of Carlstedt et al. [39]. The first studies were done in rats [40], then in cats [41] and finally in primates [42, 43], before attempting NR reimplantation in humans [44]. Initially, the efforts were directed at repairing the ventral rootlets (motor), but in adult human beings, it provided only mild improvement in shoulder and elbow movements [45]. In children, some hand movement was recovered but with limited function [29]. In addition, it was found that the number of surviving MNs and the number of axons that regenerated after NR reimplantation had a direct relationship with the final functional recovery [7, 30]. Ever since, many research groups have focussed on understanding the underlying pathophysiology and to find surgical strategies and drugs that can enhance

The interface between the central and peripheral nervous systems is known as the transitional zone (TZ) [46], and the regenerating capacities are influenced by both of them. The first is rich in astrocytes that create channels through which motor fibers pass [15]. The latter has Schwann

NRA disconnects the transverse arch that exists at each spinal level between the posterior horn sensory, the lateral horn autonomic and anterior horn neurons [23] as well as disconnection of

cells that secrete neurotrophic factors (NFs) with higher regeneration abilities [47].

animals and in human beings with partial recovery [26, 27].

the regeneration does not grow further than 2 cm [37, 38].

pain [21–24].

46 Treatment of Brachial Plexus Injuries

1.1. Historical background

regenerating capacities.

2. Pathophysiology

NRA is followed by an intense inflammatory SC reaction [50] with microglia, macrophage and glial proliferations [51]. At the TZ a dense scar tissue and a neuroma from the avulsed MN develop [15, 46, 52–55]. In the normal situation, the central nervous system is rich in astrocytes that create channels through which the nerve fibers pass [15]. After NRA, astrocytes proliferate and rearrange, blocking those channels and making it difficult for the regenerating nerve fibers to grow [15, 46, 56]. Axonal and dendrite regeneration is inhibited by the secretion of some substances by the astrocytes (chondroitin sulphate proteoglycans or CSPGs) [57–59] and oligodendrocytes (myelin protein [60–62] and semaphorin-3 [63]). Additionally, the glia secrete neurotoxic products like glutamate [15] and free radicals [64] that induce massive neuronal death among motor [8], sympathetic [12], parasympathetic [12] and posterior horn sensory neurons [17].

About 80% of the MNs die in the following weeks [13, 65, 66], but this death does not happen immediately after NRA [13, 67, 68]. Instead, there is a 12-day period in which different treatment strategies can reduce this MN loss [65, 69]. The chemical compounds that counteract the glutamate toxic effects can reduce the MN loss by 70%, provided that they are administered in the first 2 weeks after the NRA [16, 65, 69].

The closer the axonal injury to the neuronal body [55], the smaller the regenerating capacity of the axon and the higher the chance that the neuron will die. Four millimeters is the minimum amount of peripheral nerve that should remain to avoid MN death [70].

The surviving MNs develop axonal sprouts within 1 month after the NRA [41], but to achieve a successful regeneration, the axons must cross the gliotic TZ, grow inside the distal peripheral nerves, and reach the motor end plates [71]. The long distance to cover is a big impediment to a successful functional recovery [72, 73].  The regeneration is not privative to the axon, and the dendrites can also regenerate as axon, creating what has been called a dendraxon. These also have the capacity to grow into the peripheral nerves and reinnervate muscles [75, 76].

Although the MN regenerating axon has a chance to cross the anterior SC white matter to reach its surface and then attempt to grow in a possible reimplanted NR [77, 78] for the DRG growing axon, the same is almost impossible as they have to cross a very hostile and gliotic posterior SC Dorsal Root Entry Zone (DREZ) [79–81].

In the human being, the avulsion damages more frequently the ventral NRts as they are more fragile than their posterior counterparts [15].

NRA creates four problems that have to be addressed to achieve a successful repair. First, if the axon is torn closer than 4 mm to the cell body, motor and preganglionic parasympathetic neurons undergo apoptosis [10–13, 23, 67, 68, 70, 82–84]. Second, muscles are fibrotic by the time the regenerating axonal sprouts reach the motor end plates [72, 73]. In rats, functional recovery is seen only in cervical but not in lumbosacral avulsion models as the distance to cover is much shorter for the cervical NRs [9, 40, 85–87], and in any case only proximal limb muscle recovery is seen [86–89]. Third, the regenerating fibers may reach the wrong target due to misrouting [53], and in the absence of NG or conduit, the regenerating axons will grow along the surface of the SC [27, 43, 53, 83, 87]. The misrouting is responsible for simultaneous contractures in agonist and antagonist muscles leading to ineffective limb movements [30]. Fourth, there is severe muscular atrophy due to lack of use [74]. Hence, for a successful clinical result, MN survival must be improved, axonal regeneration has to be enhanced and accelerated, misrouting should be minimized and muscle atrophy should be prevented [15, 72].

always needed as torn NRts retract and undergo fibrosis with time, making direct reimplantation to the SC impossible unless the repair is done just a few days after the injury [74]. This is a further difficulty as regeneration is worse with NGs than with direct NRt

Nerve Root Reimplantation in Brachial Plexus Injuries http://dx.doi.org/10.5772/intechopen.82431 49

Several pharmacological aids have been introduced to improve MN survival and axonal regeneration after anterior spinal NRt reimplantation. They can be classified into NFs, drugs

NF administration improves MN survival as well as synaptic and axonal regrowth [87, 112–115] improving the NR reimplantation results. NFs enhance Schwann cell migration, axonal regeneration and myelination [8, 16, 69, 93, 105, 116–120] and delay MN apoptosis—by 6 weeks 80–90% of them are still alive [8, 69, 116, 118–121]. To be maximally effective, they must be administered locally at the SC-NR interface within the first 3 days and no later than 2 weeks post-avulsion [20, 87, 93, 116]. NFs ought to be applied with Gelfoam or fibrin glue to avoid dilution in the CSF [72], but free intrathecal application by means of an injecting pump is not recommended [122]. Their short half-life limits their use, particularly because NFs have to be applied directly to a surgically exposed SC [123]. Although NFs increase MN survival and axonal regeneration, their effect on muscle recovery and final functional results is very limited [4, 7, 18, 20, 27, 37, 93, 105]. It has been observed that in areas where the concentration of NFs is high, the regenerating axons get trapped and do not grow to reach their final distal targets [18, 102]. Some have cautioned against the possible adverse effects of using NFs in human clinical practice [124]. The currently used NFs are brain-derived neurotrophic factor (BDNF) [115], glial-derived neurotrophic factor (GDNF) [8, 18, 20, 37, 102, 105, 125], ciliary neurotrophic factor (CNTF) [87] and intracellular sigma peptide (ISP) [126]. GDNF shows the strongest action and a single direct application to the SC are enough, provided that they are applied within the first 2 weeks after NRA [18, 20, 37, 102, 116, 127]. GDNF delays MN cell death for 6 weeks, therefore broadening the window for avulsed NR reimplantation [20]. Similarly, the intracellular sigma peptide (ISP) blocks astrocytic inhibitory

Moreover, the distance to cover by the regenerating axons from the SC avulsion site to the muscular end plates is so long that by the time the axons reach their destination, the muscles are atrophic and fibrotic [20, 128]. To avoid and delay this muscle atrophy as much as possible, several strategies have been attempted: manipulating the molecular pathways involved in muscle atrophy [129–131], nerve transfers from neighboring functioning nerves [132–136], direct electrical stimulation of the affected muscles [137–139] and neuronal transplantation inside the denervated muscle [20, 140–142]. In rats, the combination of GDNF at the SC-NR injury site and embryonic spinal foetal neuron transplant inside the target muscles provided the best possible functional result [20]. These embryonic neurons reinnervate the muscle end plates just after the injury, preventing muscle atrophy while the regenerating axons arrived

3. Pharmacological aids to enhance regeneration after nerve root

reimplantation [26].

reimplantation

and cell-derived products (Table 1).

action, thus facilitating axonal regeneration [126].

Although the MN cell body can regenerate and grow a new axon after this is torn [69, 90], many MNs apoptose [13, 65, 69], and only 80% of the surviving MNs do finally project a regenerating axon in the reimplanted ventral root or NG [26, 27, 31, 86]. Reimplantation of avulsed NRs either directly or by means of a peripheral NG helps to reduce the number of MNs undergoing apoptosis, probably because of local NF production [69, 77, 89, 91–93]. Exogenous NFs can be administered to enhance the regenerating capacity of cells [47, 94, 95].

Historically, the first attempts were directed at motor recovery with ventral rootlet reimplantantion [96], but recently sensory recovery has been proved possible by reimplanting dorsal rootlets [97]. The results of dorsal rootlet repair are dismal because the SC glial proliferation creates barriers that prevent the regenerating DRG axons from reaching the posterior SC horn [81]. The lack of sensory recovery induces chronic neuropathic pain [49, 98], and the lack of proprioception causes limb clumsiness [30]. This has been partially avoided by direct implantation of the dorsal rootlets or their NGs' extensions inside the posterior horn itself rather than on the surface of the SC [81, 99]. The repair of both motor and sensory NRts leads to better functional results with more accurate movements and less muscular synkinesis [100]. Functional MRI studies have corroborated affected limb sensory cortex function recovery in the area corresponding to the reimplanted NR [100].

The timing of NR reimplantation is crucial, as a longer waiting period will correlate with a greater amount of MNs undergoing apoptosis [20, 27, 91, 93, 101–103]. The percentage of dead MNs increases from 20% by 10–12 days post-avulsion [13, 65, 69] to 50% by 4 weeks [104, 105], 85% by 6 weeks [106] and 90% by 20 weeks [27, 83, 93, 107]. Early NR reimplantation seems to have neuroprotective effects [27, 83, 89, 93, 108, 109], but some MN loss will happen even if repair occurs immediately after avulsion [93, 101]. In animal models, NRA followed by immediate reimplantation in the same surgical procedure minimizes MN apoptosis and achieves muscle reinnervation with some limited functional recovery, which is better in the brachial plexus than in the lumbosacral plexus [27, 69, 83, 110]. Ideally, the surgical repair must be performed no later than 10 days post-injury [65] as a delay over 2 weeks will lead to poor clinical results [20, 26, 27]. In clinical practice, patients suffering from brachial or lumbosacral plexus avulsions often experience other concomitant injuries, sometimes quite serious, that force delaying NR repair [111]. Another common scenario is that the precise diagnosis takes weeks or even months [3]. In any case, in human beings NRA repair has to occur no later than 1 month after the injury to allow any motor function recovery [45, 74, 97, 100]. NGs are almost always needed as torn NRts retract and undergo fibrosis with time, making direct reimplantation to the SC impossible unless the repair is done just a few days after the injury [74]. This is a further difficulty as regeneration is worse with NGs than with direct NRt reimplantation [26].


**Abstract**

In recent years, information and communication technology (ICT) and its impact on economic growth and CO2 emission has become a hot topic of debate; however, little research has been conducted regarding the impact of the interaction between ICT and economic growth on CO2 emission. The study tries to evaluate empirically the impact of ICT and economic growth on CO2 emissions of Tunisia and Morocco for the period 1980–2018, based on the Auto-Regressive Distributive Lag (ARDL) analysis. Findings demonstrate that ICT and economic growth affect positively and significantly the CO2 emissions in the short and long term in both Tunisia and Morocco; however, the direct and positive effect of economic growth on CO2 emissions can be ameliorated by introducing the interaction between ICT and economic growth. The Toda-Yamamoto Granger causality test reveals that bi-directional causality is running between economic growth and CO2 emissions in both countries. On the other hand, our obtained results express that there is a unidirectional causality running from ICT to CO2 emissions in both countries. So, the promotion of ICT can be considered one of the important strategies introduced to mitigate CO2 emissions. Then, introducing green ICT projects in various sectors of an economy is a better choice for policy makers to decrease the CO2 emissions.

**Keywords:** economic growth, ICT, CO2 emissions, Tunisia, Morocco, ARDL


**Proprioception ativity using swiss ball**

**INITIAL PHASE – The first 3 weeks FINAL PHASE – The last 3 weeks**

**EXERCISE 2**

10 times each limb

Final phase: The same performance but now each hand hold a 2 kg weight which increases 1.5 kg per week and the back leg is supported over the

**EXERCISE 3**

metatarsals.

30″ each limb

ankle.

Final phase: The same performance apart from each hand hold a 2 kg weight which increases 1.5 kg per week and a 3 kg ankle weight in each

**EXERCISE 2**

10 times each limb

Initial phase: From the position indicated in the picture, to do shoulder flexion – extension.

**EXERCISE 3**

30″ each limb

**125**

Initial phase: From the position of the picture, doing hip flexion – extension at the same time that moving the shoulder in flexion – extension.

*DOI: http://dx.doi.org/10.5772/intechopen.96236*

*Nomophobia Kids and Proprioception*

#### **INITIAL PHASE – The first 3 weeks FINAL PHASE – The last 3 weeks**

#### **EXERCISE 2**

Initial phase: From the position of the picture, doing hip flexion – extension at the same time that moving the shoulder in flexion – extension.

#### **EXERCISE 2**

Final phase: The same performance apart from each hand hold a 2 kg weight which increases 1.5 kg per week and a 3 kg ankle weight in each ankle.

10 times each limb

#### **EXERCISE 3**

Initial phase: From the position indicated in the picture, to do shoulder flexion – extension.

10 times each limb

#### **EXERCISE 3**

Final phase: The same performance but now each hand hold a 2 kg weight which increases 1.5 kg per week and the back leg is supported over the metatarsals.

30″ each limb

30″ each limb

#### **INITIAL PHASE – The first 3 weeks FINAL PHASE – The last 3 weeks**

#### **EXERCISE 4**

Initial phase: The free leg does a whole circulation which ends with the extension hip.

10 times each limb

#### **EXERCISE 5**

Initial phase: The free leg does hip, knee and ankle flexion synchronized with the high member which also moves in flexion – extension.

10 times each limb

#### **EXERCISE 4**

Final phase: The same performance apart from a 3 kg ankle weight in the free leg.

phone usage for extended period may change the brain activity, and postural

I would like to thank the authorities of Dr. MGR Educational and Research Institute, University, Honorable chairman Dr. AC. SHANMUGAM, Honorable president ACS. ARUNKUMAR, Honorable secretary Thiru A. RAVIKUMAR and our Principal, Faculty of Physiotherapy Dr. CV. SENTHIL NATHAN for providing facilities required to complete the chapter with their support and guidance. With great privilege I thank my husband Er. S Elangovan and my mother for their

Faculty of Physiotherapy, Dr. MGR Educational and Research Institute, Chennai,

© 2021 The Author(s). Licensee IntechOpen. 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,

\*Address all correspondence to<EMAIL_ADDRESS>
provided the original work is properly cited.

disturbance.

**Acknowledgements**

*Nomophobia Kids and Proprioception*

*DOI: http://dx.doi.org/10.5772/intechopen.96236*

support and motivation.

**Author details**

India

**127**

Giridharan Vaishnavi

10 times each limb

#### **EXERCISE 5**

Final phase: The same performance apart from each hand hold a 2 kg weight which increases 1.5 kg per week and also a 3 kg ankle weight in each ankle.

10 times each limb

### **11. Conclusions**

In line with King et al. [2], this study purports that nomophobia, or no mobile phone phobia, is thought of a contemporary age phobia introduced to our lives with the speedy proliferation and adoption of smartphone.

The proprioceptive system has an extensive influence at the protection of human fitness. When the proprioception is dysfunctional, the vital anxious device does no longer recognize the ideal fame of tonicity ofthe muscular tissues at rest or in motion, does no longer combine effectively the records that comes from sensory receptors, and has issue in modulating multi-sensory integration, with outcomes in motor behavior and cognitive function. This outcomes in a wide variety of proprioceptive abnormalities which are clinically related and are handled collectively termed as Postural Deficiency Syndrome (PDS). Kids using smart phones for a prolonged period of time lack attention, lack posture and motor control. Smart

phone usage for extended period may change the brain activity, and postural disturbance.


**8.1 Velocity streamlines**

Here, the velocity streamlines for various pitch angles (0,3,5, and 10 degrees) and TSR (5,6,7,8, and 9) are presented. Streamlines track the path of the wind as it flows across the blades. The least obtained velocity was 7.27 m/sec. This velocity (7.27 m/sec) is essential as it directly affects how much energy is extracted from the wind [10] shows some velocity streamlines for non-separated flow, as the turbine is optimized. Our results indicate non-separated flow at optimal TSR. **Figure 12** shows the velocity streamlines for various turbine blade configurations. The five rows of the image are the TSR 5, 6, 7, 8, and 9, and the four columns are pitch angles of 0, 3, 5, and 10 degrees. Every image at location {TSR, Pitch} corresponds to that particular input condition.

### **8.2 Pressure contours at root of the blade: CFD-Post**

The pressure contours are directly responsible for torque generation by the blade. Typically, the bottom portion should have high pressure, followed by the top side, which has low pressure. This net pressure difference creates lift at an angle. A portion of this lift will assist in blade rotation. One can note that as the pitch angle is high and TSR is increased, the low and high-pressure regions shift, and the blade will stop generating torque, or if pitching is increased further, it will generate reverse torque. This unique feature can make the blade stop rotating in stormy or very high TSR conditions by moving the blade to this appropriate zero torque angle. One can also note that the blade produces maximum torque when the angle of attack is close to 5 degrees, which depends on TSR and pitch angle. The two contours shown here are for the root (S815), **Figure 13** and tip (S826), and **Figure 14** of the blade. The five rows of the image are the TSR 5, 6, 7, 8, and 9, and the four columns are pitch angles of 0, 3, 5, and 10 degrees. Every image at location {TSR, Pitch} corresponds to that particular

**Figure 12.** *Velocity streamlines for varying pitch and TSR.*

input condition [10] shows pressure contours where the wake (region of low pressure) is visible at the tail end of the airfoil. However, the blade as a whole is not simulated, and this produces slightly differing pressure contours in our case but is still consistent with our results.


**2. Bringing blockchain into Industry 4.0**

After carrying out different proofs of concept, mainly associated with manufacturing companies, as well as analyzing other experiments carried out by third parties, we expose in a critical way which would be the main application scenarios of the blockchain technology and its benefit for industrial companies.

All the analyzed cases have been contrasted through a working meeting with several companies in order to analyze the real need and utility of them. The following are the use cases that have presented greatest utility in the experimentation process, responding to real needs not covered today in their ecosystems.

#### **2.1 Traceability**

The traceability of industrial goods throughout the entire supply chain, including even the life cycle of a product, is one of the applications that according to consulted experts in the experimentation, as well as the level of maturity of the technology in this field, is expected to have a greater impact on the short/medium term of the industry.

For any point in the chain, it is very valuable being able to have visibility of the destination and use of its components; thanks to this information the participant in the supply/value chain will be able to (i) analyze the impact of any change in the design/composition of their product, (ii) anticipate changes in consumption habits/ trends, (iii) avoid manually entering details of the products/components received by suppliers, (iv) automate complaints and warranties without the need for paperwork, or even (v) avoid reusing certificates of origin.

We are facing a known need that the big industrial players have wanted to solve on different occasions [4–7]. The large industries have designed and built traceability systems based on traditional (centralized) architectures and have made them available throughout their sectorial supply chain. However, these systems have not been widely accepted, and the only ones that continue to exist are those related to food safety that is mandatory.

The problem with the previous approaches is that the "giant" of the supply chain was the one that offered its system to the rest and was in charge of the custody and coherence of the common database.

**89**

equally.

point today.

*Blockchain: From Industry 4.0 to the Machine Economy DOI: http://dx.doi.org/10.5772/intechopen.88694*

This created great reticence because, even if industrial data visibility policies were implemented so that only agreed users/companies could consume certain information, there was a "demigod" in the supply chain which, due to the architecture of the system, could have visibility and exploit the information of the entire value chain. Furthermore, processing the information in a traditional system is very complicated to guarantee the sovereignty and protection of industrial data [8].

The alternative to create a similar system using traditional technologies is to create a clearing house in the supply chain, which has been done in areas such as food safety and is the only area where traceability is complete throughout the chain [9]. However, in this case the actors only submit information related to food safety and

Blockchain makes it possible to eliminate these barriers thanks to a distributed architecture in which there is no "agglutinator" of the contents. Guaranteeing through "contract" and cryptography the visibility and use of data (sovereignty of industrial data) and ensuring that all participants in the network are treated

However, we have detected that an important point in these projects is to maximize and automate as much as possible the capture of data, which is why industrial projects are considering that the Industrial Internet of Things (IIoT) should be the origin of most of the data that are dumped in the traceability chain. Moreover, this information should be signed by means of cryptographic hardware in these IIoT

Data and its exploitation are going to be the key in this new industrial paradigm in which we are entering, promoting even service models based on data [10]. That is why it is said that data is the new industrial raw material and its sovereignty is a key

For this reason, several initiatives have arisen that could be called industrial data platform and that aim to manage and share data of industrial processes, as well as create value-added services based on them. The most evolved platforms, such as the one from the international data space consortium, which arose in Germany but is currently the leading European experimental platform, even include application/

Perhaps predictive maintenance together with other cases of data analysis and prescription are the most common and tangible cases today [12], but it is expected that really these platforms are the basis for innovative proposals of business models and industrial services that today we cannot even imagine. However, there is currently a major barrier to the adoption of such platforms, and again it is the reliability

Firstly, there are models for selling information related to industrial processes, the value of which will depend on the reliability of such data. Therefore, it is one of the reasons why blockchain begins to be a buzzword in the deliberations on the future of these platforms, since the more reliable the data, the greater will be its

On the other hand, these platforms must guarantee the sovereignty of industrial data, for which blockchain architectures/platforms that natively allow confidentiality between parties seem the most promising [13]. Current developments include data encryption models specific to each recipient or set of recipients, such as chan-

However, blockchain and smart contracts will even allow to execute algorithms

and data processing independently, offering the recipient only the result of its

cannot consult/exploit the information, so the functionality is not full.

devices, so that the reliability of the data would be extraordinary.

**2.2 Interoperability and sovereignty of industrial data**

service marketplaces based on industrial data [11].

nels or private data collection in Hyperledger Fabric v1.4.

of the industrial data and its protection.

value in the market.

*Computer Security Threats*

its immutability. Blockchain allows us to operate our procedures and relationships in

The next few years will see a profound transformation of industrial processes, increasing the synchronization between different agents in the value chain, as well as extreme automation of decision-making, all thanks to the reliability offered by blockchain. It is even hoped that in the future, it will be able to transform its own business models, just as in recent decades the Internet has done, which has so far

In this chapter, we will explain the different use cases and scenarios that we consider to have greater potential in the future of Industry 4.0, starting first with generic industrial cases and then analyzing the specific cases of the energy industry. This selection has been made based on the experience of more than a dozen block-

Next, we will describe the four main generic values that we have discovered after different proofs of concept with several companies. Finally, we will discuss future lines of research linked to a new concept such as the machine economy and report

After carrying out different proofs of concept, mainly associated with manufacturing companies, as well as analyzing other experiments carried out by third parties, we expose in a critical way which would be the main application scenarios

All the analyzed cases have been contrasted through a working meeting with several companies in order to analyze the real need and utility of them. The following are the use cases that have presented greatest utility in the experimentation

The traceability of industrial goods throughout the entire supply chain, includ-

For any point in the chain, it is very valuable being able to have visibility of the destination and use of its components; thanks to this information the participant in the supply/value chain will be able to (i) analyze the impact of any change in the design/composition of their product, (ii) anticipate changes in consumption habits/ trends, (iii) avoid manually entering details of the products/components received by suppliers, (iv) automate complaints and warranties without the need for paper-

We are facing a known need that the big industrial players have wanted to solve on different occasions [4–7]. The large industries have designed and built traceability systems based on traditional (centralized) architectures and have made them available throughout their sectorial supply chain. However, these systems have not been widely accepted, and the only ones that continue to exist are those related to

The problem with the previous approaches is that the "giant" of the supply chain was the one that offered its system to the rest and was in charge of the custody and

ing even the life cycle of a product, is one of the applications that according to consulted experts in the experimentation, as well as the level of maturity of the technology in this field, is expected to have a greater impact on the short/medium

of the blockchain technology and its benefit for industrial companies.

process, responding to real needs not covered today in their ecosystems.

the digital environment in a much more safe and reliable way [3].

been the most disruptive technology in history.

chain projects in the domain of Industry 4.0.

**2. Bringing blockchain into Industry 4.0**

work, or even (v) avoid reusing certificates of origin.

the final conclusions of the chapter.

**2.1 Traceability**

term of the industry.

food safety that is mandatory.

coherence of the common database.

**88**

This created great reticence because, even if industrial data visibility policies were implemented so that only agreed users/companies could consume certain information, there was a "demigod" in the supply chain which, due to the architecture of the system, could have visibility and exploit the information of the entire value chain. Furthermore, processing the information in a traditional system is very complicated to guarantee the sovereignty and protection of industrial data [8].

The alternative to create a similar system using traditional technologies is to create a clearing house in the supply chain, which has been done in areas such as food safety and is the only area where traceability is complete throughout the chain [9]. However, in this case the actors only submit information related to food safety and cannot consult/exploit the information, so the functionality is not full.

Blockchain makes it possible to eliminate these barriers thanks to a distributed architecture in which there is no "agglutinator" of the contents. Guaranteeing through "contract" and cryptography the visibility and use of data (sovereignty of industrial data) and ensuring that all participants in the network are treated equally.

However, we have detected that an important point in these projects is to maximize and automate as much as possible the capture of data, which is why industrial projects are considering that the Industrial Internet of Things (IIoT) should be the origin of most of the data that are dumped in the traceability chain. Moreover, this information should be signed by means of cryptographic hardware in these IIoT devices, so that the reliability of the data would be extraordinary.

## **2.2 Interoperability and sovereignty of industrial data**

Data and its exploitation are going to be the key in this new industrial paradigm in which we are entering, promoting even service models based on data [10]. That is why it is said that data is the new industrial raw material and its sovereignty is a key point today.

For this reason, several initiatives have arisen that could be called industrial data platform and that aim to manage and share data of industrial processes, as well as create value-added services based on them. The most evolved platforms, such as the one from the international data space consortium, which arose in Germany but is currently the leading European experimental platform, even include application/ service marketplaces based on industrial data [11].

Perhaps predictive maintenance together with other cases of data analysis and prescription are the most common and tangible cases today [12], but it is expected that really these platforms are the basis for innovative proposals of business models and industrial services that today we cannot even imagine. However, there is currently a major barrier to the adoption of such platforms, and again it is the reliability of the industrial data and its protection.

Firstly, there are models for selling information related to industrial processes, the value of which will depend on the reliability of such data. Therefore, it is one of the reasons why blockchain begins to be a buzzword in the deliberations on the future of these platforms, since the more reliable the data, the greater will be its value in the market.

On the other hand, these platforms must guarantee the sovereignty of industrial data, for which blockchain architectures/platforms that natively allow confidentiality between parties seem the most promising [13]. Current developments include data encryption models specific to each recipient or set of recipients, such as channels or private data collection in Hyperledger Fabric v1.4.

However, blockchain and smart contracts will even allow to execute algorithms and data processing independently, offering the recipient only the result of its

execution [14]. In the future the algorithms can be encoded in a native blockchain program—the smart contract—in such a way that the owner of the algorithms can allow the smart contract to access and process their data and generate insights about them. However, the smart contract provider will not have access to the user's RAW data; this will allow them to offer a service based on the data without the customer having to make a disclosure of such information [15].

After all, it will allow us to put in value the industrial data even without having to expose them to a third party, allowing them nevertheless to execute certain processes on them. This can even be very useful to test/train prediction models of all kinds without endangering the source data, the result of which can then be a high-value algorithm for a specific industry.

### **2.3 IIoT reliability**

One of the main benefits of the blockchain application to IIoT in which all the interviewed experts agree is precisely the decentralized architecture that blockchain can offer to IoT in general and especially to the industrial ecosystem whose requirements are more severe [16].

Currently the architecture of these systems is a classic client/server, which has a series of barriers and deficiencies for an environment such as IoT/IIoT. It is expected that the client/server architecture will not be able to respond to the exponential growth of IIoT and IoT in general; we must bear in mind that we will face an immense number of devices generating and consuming information from third parties. To get an idea of this figure, an industrial control machine or device generates hundreds of millions of data/parameters annually, and inside a mediumsized factory, we can find tens or hundreds of devices.

The cost of centralized processing and even network equipment and connectivity to support such cross traffic between different industrial systems (clients) with dependencies between them would be exponential if all these communications had to pass through a central system (server). In addition, this central system (server) would be a major bottleneck for all connected devices and a single point of failure (SPOF) which, if compromised, could generate a production shutdown of millions of euros in a single factory.

The trend is also that connected machines and factories interact outside their business environment with partners, suppliers, and customers. This brings another set of challenges at the level of identity management and device authentication. Currently within a factory, existing systems have multiple limitations because vendors deploy centralized systems that cannot interact safely and reliably with third parties, even rely on costly and complex in-house or manufacturer-controlled PKI architectures. In a global economy and in an ecosystem relationship, the problem and complexity multiply. Thus, blockchain technology has demonstrated that distributed authentication and identity management are highly efficient and feasible [17] and can solve identity management problems.

For all these reasons, we are dealing with a new paradigm in which, after moving from the traditional server model to an elastic cloud server architecture, we must evolve toward a network of devices in which blockchain is postulated as the main technological enabler. This paradigm shift would lead us toward decentralized registers that could become sectorial or even universal.

But the adoption of blockchain in the IIoT ecosystem, and IoT in general, offers another series of advantages, which although perhaps less disruptive also resolves some of the challenges and barriers to adoption of IIoT and IoT discussed above.

Blockchain offers us a decentralized record of information, which is also reliable and unalterable. That is why besides avoiding the single point of failure

**91**

*Blockchain: From Industry 4.0 to the Machine Economy DOI: http://dx.doi.org/10.5772/intechopen.88694*

unknown devices or different organizations.

based on third party information sources.

logical attack) for forensic analysis.

able to erase any trace once the cyberattack is executed.

the machine code of our industrial devices.

**3. A new energy industry**

record [18].

in the data.

of traditional systems, it offers us a more resilient system, not only in terms of system availability, which increases exponentially by avoiding the single point of failure, but also in terms of information, since it provides us with a reliable

Offering a reliable record of information due to its immutability and ensuring non-repudiation of operations are an enabling factor for transactions between

As we have mentioned before, one of the biggest barriers to adopting a higher level of automation in the industrial environment is precisely the mistrust of data, especially data from third parties. Although the industries themselves in many cases do not rely on automating some critical processes based on their own information due to potential sabotages or failures, it is impossible to think that they will do it

Blockchain offers reliability over our own information—thanks to the integrity and strong authentication of our issuers—as well as over information provided by third parties. Such reliability will allow greater automation and avoid many of today's low value-added manual processes that are provoked by a lack of confidence

The decentralization of information and its immutability are also a major advantage for critical industrial infrastructures (chemical, energy, etc.). According to the latest recommendations for critical infrastructure protection like the European Critical Infrastructure Protection (ECIP) or NIST Cybersecurity Framework, they should be able to guarantee the custody of their data in the case of any fortuitous incident (natural disaster, system failure) or deliberate incident (physical and/or

Nowadays, this custody of information in case of cyber incidents is practically impossible to achieve since the attacker usually stays inside the system 146 days before executing the attack or being detected [19], and one of its objectives is to meticulously study the infrastructure not only to maximize its impact but also to be

This is why traditional backup systems and data replicas are usually eliminated during the attack; however, if the infrastructure was connected to a blockchain network, the attacker would have to completely erase each and every one of the nodes of the distributed blockchain network to make their footprints disappear, something totally unthinkable. In fact, during all the time that the attacker remains investigating, the infrastructure is erasing his trail, so a simple periodic comparison of the logs of the infrastructure itself against its unalterable copy in blockchain could alert us of the existence of an intruder in the network or detect any change in

However, although blockchain is postulated as the solution to IIoT's architectural design problems, it must be kept in mind that current solutions and ledgers must evolve in order to respond to the needs of IIoT devices in real time (low latency, bandwidth, message size). That is why in the blockchain, ecosystem begins to emerge new developments and technologies aimed at overcoming this barrier [20–22]. If this is achieved, the potential market and technological impact could

In the last years, the energy sector has initiated a major transformation of the electricity grid, the industrial infrastructure responsible for transporting and distribution electricity from the generation plants to the consumer. The smart grid

lead to the long-awaited paradigm shift we were talking about earlier.

*Computer Security Threats*

**2.3 IIoT reliability**

ments are more severe [16].

of euros in a single factory.

execution [14]. In the future the algorithms can be encoded in a native blockchain program—the smart contract—in such a way that the owner of the algorithms can allow the smart contract to access and process their data and generate insights about them. However, the smart contract provider will not have access to the user's RAW data; this will allow them to offer a service based on the data without the customer

After all, it will allow us to put in value the industrial data even without having to expose them to a third party, allowing them nevertheless to execute certain processes on them. This can even be very useful to test/train prediction models of all kinds without endangering the source data, the result of which can then be a

One of the main benefits of the blockchain application to IIoT in which all the interviewed experts agree is precisely the decentralized architecture that blockchain can offer to IoT in general and especially to the industrial ecosystem whose require-

Currently the architecture of these systems is a classic client/server, which has a series of barriers and deficiencies for an environment such as IoT/IIoT. It is expected that the client/server architecture will not be able to respond to the exponential growth of IIoT and IoT in general; we must bear in mind that we will face an immense number of devices generating and consuming information from third parties. To get an idea of this figure, an industrial control machine or device generates hundreds of millions of data/parameters annually, and inside a medium-

The cost of centralized processing and even network equipment and connectivity to support such cross traffic between different industrial systems (clients) with dependencies between them would be exponential if all these communications had to pass through a central system (server). In addition, this central system (server) would be a major bottleneck for all connected devices and a single point of failure (SPOF) which, if compromised, could generate a production shutdown of millions

The trend is also that connected machines and factories interact outside their business environment with partners, suppliers, and customers. This brings another set of challenges at the level of identity management and device authentication. Currently within a factory, existing systems have multiple limitations because vendors deploy centralized systems that cannot interact safely and reliably with third parties, even rely on costly and complex in-house or manufacturer-controlled PKI architectures. In a global economy and in an ecosystem relationship, the problem and complexity multiply. Thus, blockchain technology has demonstrated that distributed authentication and identity management are highly efficient and

For all these reasons, we are dealing with a new paradigm in which, after moving from the traditional server model to an elastic cloud server architecture, we must evolve toward a network of devices in which blockchain is postulated as the main technological enabler. This paradigm shift would lead us toward decentralized

But the adoption of blockchain in the IIoT ecosystem, and IoT in general, offers another series of advantages, which although perhaps less disruptive also resolves some of the challenges and barriers to adoption of IIoT and IoT discussed above. Blockchain offers us a decentralized record of information, which is also reliable and unalterable. That is why besides avoiding the single point of failure

having to make a disclosure of such information [15].

sized factory, we can find tens or hundreds of devices.

feasible [17] and can solve identity management problems.

registers that could become sectorial or even universal.

high-value algorithm for a specific industry.

**90**

of traditional systems, it offers us a more resilient system, not only in terms of system availability, which increases exponentially by avoiding the single point of failure, but also in terms of information, since it provides us with a reliable record [18].

Offering a reliable record of information due to its immutability and ensuring non-repudiation of operations are an enabling factor for transactions between unknown devices or different organizations.

As we have mentioned before, one of the biggest barriers to adopting a higher level of automation in the industrial environment is precisely the mistrust of data, especially data from third parties. Although the industries themselves in many cases do not rely on automating some critical processes based on their own information due to potential sabotages or failures, it is impossible to think that they will do it based on third party information sources.

Blockchain offers reliability over our own information—thanks to the integrity and strong authentication of our issuers—as well as over information provided by third parties. Such reliability will allow greater automation and avoid many of today's low value-added manual processes that are provoked by a lack of confidence in the data.

The decentralization of information and its immutability are also a major advantage for critical industrial infrastructures (chemical, energy, etc.). According to the latest recommendations for critical infrastructure protection like the European Critical Infrastructure Protection (ECIP) or NIST Cybersecurity Framework, they should be able to guarantee the custody of their data in the case of any fortuitous incident (natural disaster, system failure) or deliberate incident (physical and/or logical attack) for forensic analysis.

Nowadays, this custody of information in case of cyber incidents is practically impossible to achieve since the attacker usually stays inside the system 146 days before executing the attack or being detected [19], and one of its objectives is to meticulously study the infrastructure not only to maximize its impact but also to be able to erase any trace once the cyberattack is executed.

This is why traditional backup systems and data replicas are usually eliminated during the attack; however, if the infrastructure was connected to a blockchain network, the attacker would have to completely erase each and every one of the nodes of the distributed blockchain network to make their footprints disappear, something totally unthinkable. In fact, during all the time that the attacker remains investigating, the infrastructure is erasing his trail, so a simple periodic comparison of the logs of the infrastructure itself against its unalterable copy in blockchain could alert us of the existence of an intruder in the network or detect any change in the machine code of our industrial devices.

However, although blockchain is postulated as the solution to IIoT's architectural design problems, it must be kept in mind that current solutions and ledgers must evolve in order to respond to the needs of IIoT devices in real time (low latency, bandwidth, message size). That is why in the blockchain, ecosystem begins to emerge new developments and technologies aimed at overcoming this barrier [20–22]. If this is achieved, the potential market and technological impact could lead to the long-awaited paradigm shift we were talking about earlier.


**4.4 System fabrication**

478 Solar Radiation

The thermocouple wires (Type E) made of different metal alloys (Nickel-Chromium copperconstantan) is joined together by soldering. The number of thermocouples required to generate an output voltage of 15V is required. Knowing the output voltage of one thermocouple (type E) given as 153mv (0.153v), dividing 15 by 0.153 to give 98.04 = 98 junctions. There are six modules with 15 junctions each (Fig 9). These thermocouples were joined together in series to form cascaded thermopile consisting of a number of

The construction of the solar power module was simple and convenient employing modular approach in which the entire system is divided into modules. The design is to generate high voltage, thus the cells are connected in series in the module. The voltage is a function of the cell's physical composition, while the amperage is affected not only by the area of the cell,

**4.3 Construction of thermocouple circuit**

thermocouples.

Fig. 9. Thermocouple solar panel

but also by the amount and intensity of light falling upon it.

The entire system is divided into modules as shown in Figure 11. Vero board is used as the circuit boards for the solar panel and the charge control system.

Fig. 11. Block diagram of the system

The charge control system uses the LED control charging system to charge a 12v lead Acid battery. An electrical diode, D1 ensures unidirectional voltage flow when battery is under charge (Fig 10). For simplicity of construction and convenience the modular approach of constructing solar energy harvest modalities is used. Photovoltaic conversion provides the highest power density, which makes it the modality of choice to power an embedded system using reasonably small harvesting module.

Fig. 11. Circuit Diagram of the solar power supply

The components of the electrical circuit and ratings are as follows:

D1, D2 = Diode (MA2J728 or MA3x704), Q1, Q2 = FET transistor (IRFZ44), R1 = Resistor =220k, R2 = Resistor = 12k, R3 = Resistor = 2.7k, R4 = Resistor = 4.5k, R5 = Variable Resistor = 1000k, LED (Green/Red), Battery = 12V Rechargeable Lead Acid.

Since the thermocouple array is expected to charge the battery on sunny days when output exceeds the load, but on cloudy days or at night, the load is expected to exceed the array output and drain the battery- Hence the array must be sized to ensure that the balance is positive and the battery is recharged when discharged. The array delivered an average daily output equal to the average daily system load (including all losses) plus approximately 10% to ensure that the battery is recharged.

#### **5. System test result**

#### **5.1 Collector surface temperature**

The daily total solar energy Qt received per unit surface area of the absorber at the location (Ishiagu, South East Nigeria) as evaluated by Bello and Odey (2009) is 747.67 W/m2. The useful components of the global solar radiation at the location are: direct solar radiation qD = 680.67 W/m2, diffuse solar radiation qd = 64.21 W/m2 and ground reflected radiation qr = 2.34 W/m2. The collector heat transfer coefficient between the absorber and cover expressed as the heat loss per unit area of the collector surface per temperature change is 3.06 W/m2 oC. Total absorbed heat energy per unit surface area of absorber qu = 592.43 W/m2

Fig. 11. Circuit Diagram of the solar power supply

to ensure that the battery is recharged.

**5.1 Collector surface temperature**

**5. System test result**

LED (Green/Red), Battery = 12V Rechargeable Lead Acid.

heat energy per unit surface area of absorber qu = 592.43 W/m2

The components of the electrical circuit and ratings are as follows:

D1, D2 = Diode (MA2J728 or MA3x704), Q1, Q2 = FET transistor (IRFZ44), R1 = Resistor =220k, R2 = Resistor = 12k, R3 = Resistor = 2.7k, R4 = Resistor = 4.5k, R5 = Variable Resistor = 1000k,

Since the thermocouple array is expected to charge the battery on sunny days when output exceeds the load, but on cloudy days or at night, the load is expected to exceed the array output and drain the battery- Hence the array must be sized to ensure that the balance is positive and the battery is recharged when discharged. The array delivered an average daily output equal to the average daily system load (including all losses) plus approximately 10%

The daily total solar energy Qt received per unit surface area of the absorber at the location (Ishiagu, South East Nigeria) as evaluated by Bello and Odey (2009) is 747.67 W/m2. The useful components of the global solar radiation at the location are: direct solar radiation qD = 680.67 W/m2, diffuse solar radiation qd = 64.21 W/m2 and ground reflected radiation qr = 2.34 W/m2. The collector heat transfer coefficient between the absorber and cover expressed as the heat loss per unit area of the collector surface per temperature change is 3.06 W/m2 oC. Total absorbed Measurements were taken on a clear day without cloud cover and surface temperatures were measured at five different spots every hour. According to measured temperature data, the average daily surface temperature increases with increase in sunshine hour reaching its peak between 1300hr and 1400hr (Fig 12) and then decline. On the average, 10hrs of sunshine hours is available per day, but for useful solar harvest, 8hrs of sunshine may is assumed because of difference in temperature between the collector surface and the ambient. The full sun (peak sun) hour value monitored at the site during raining season and dry season were found to be 4hrs and 5hrs respectively, agreeing with Onojo *et al.,* (2004).

Fig. 12. Average daily temperature in collector

Three surface areas were used for the test as follows 0.6m2, 1.0m2 and 1.5m2. There appeared to be no significant difference in spot temperatures in each of the surfaces per hour (Fig 12), it can be concluded that the surface temperature is independent of surface area. There appeared to be no significant difference in spot temperatures measured in each of the collectors per hour (TAV1, TAV2, TAV3), hence, it can be concluded that the surface temperature is independent of surface area. The average cell surface area used in computation is 1.03 m2 and the total surface area of the module is 6.2 m2.

Material density constitutes to heat retention within the system and hence increases in surface temperature and higher potential difference. The collector compaction test shows that a densely packed material retains more heat and hence increases surface temperature, which obviously will produce higher potential difference.


**1. Introduction**

Engineering is an imperfect science. Noisy measurements from sensors in state estimation [1,2], a constantly changing environment in guidance [3–5], and improperly actuated controls [6] are all major sources of error. The more these sources of error are understood, the better the final product will be. Ideally, every variable with some sort of uncertainty associated with it would be completely and analytically described with its probability density function (pdf). Unfortunately, even if this is feasible for the initialization of a random variable, its evolution through time rarely yields a pdf with an analytic form. If the pdf cannot be given in analytic form, then approximations and assumptions must be made.

In many cases, a random variable is quantified using only its first two moments—as with the unscented transform [7]—and a further assumption is that the distribution is Gaussian. In cases where the variable's uncertainty is relatively small and the dynamics governing its evolution are not highly nonlinear, this is not necessarily a poor assumption. In these cases, the higher order moments are highly dependent on the first two moments; i.e., there is a minimal amount of unique information in the higher order moments. In contrast, if either the uncertainty is large or the dynamics become highly nonlinear, the higher order moments become less dependent on the first two moments and contain larger amounts of unique information. In this case, the error associated with using only the first two moments becomes significant [8,9].

One method of quantifying uncertainty that does not require an assumption of the random variable's pdf is polynomial chaos expansion (PCE) [10–14]. PCE characterizes a random variable as a coordinate in a polynomial vector space. Useful deterministic information about the random variable lies in this coordinate, including the moments of the random variable [15]. The expression of the coordinate depends on the basis in which it is expressed. In the case of PCE, the bases are made up of polynomials that are chosen based on the assumed density of the random variable; however, any random variable can be represented using any basis [16]. It is strongly noted that assuming the density of the random variable simply eases computation; with enough computing power, any random variable can be quantified with any basis [17]. The most common basis polynomials are those that are orthogonal with respect to common pdfs, such as the Hermite-Gaussian and Jacobi-beta polynomial-pdf pairs.

Polynomial chaos has been used to quantify and propagate the uncertainty in nonlinear systems including fluid dynamics [18–21], orbital mechanics in multiple element spaces [22], and has been expanded to facilitate Gaussian mixture models [23]. While polynomial chaos has been well-studied for variables that exist in the *n*-dimensional space of real numbers ( R*n*), many variables do not lie in this field. The variables that are of concern in this paper are angular variables. When estimating an angular random variable, such as the true anomaly of a body in orbit or vehicle attitude, a common approach is to assume that the variable is approximately equal to its projection on R*n* and use methods designed for variables on that space. When the uncertainty is very small, this approximation is relatively effective; however, as the uncertainty increases, this approximation becomes invalid. Recently, work on directional statistics has been incorporated into state estimation, providing a method for estimating angular random variables directly on the *n*-dimensional special orthogonal group (S*n*) [24–26]. Recent work [27] has shown that polynomial chaos can be used to estimate the mean and variance of one-dimensional angular random variables and the set of equinoctial orbital elements elements [28]. In neither case was a correlation estimated that included an angular state.

The sections of this paper include a detailed discussion of orthogonal polynomials in Section 2, including those that are orthogonal on the unit circle and two of the more common circular pdfs. In Section 3 an overview of polynomial chaos is given as well as the extension that has been made to include angular random variables, including the correlation between two angles. Finally, in Section 4, numerical results are presented comparing the correlation between two angular random variables calculated using Monte Carlo and PCE.


**7. Conclusion**

The structural and metabolic diversity of various pest control chemicals shown above demonstrates the usefulness of the "Trojan horse" principle of chemical formulation. Future research efforts, either capitalizing on known pesticide design practices or discovering new ones based on differences between the xenobiotic metabolisms of various organisms, will lead to new and selective agrochemicals that find and hit the target enzyme or receptor of the pest as "magic bullets."


*<IP_ADDRESS>. Adjuvant treatment*

Knowing that the wild-type astrocytomas have a worse prognosis, a low-dose radiotherapy regimen in the immediate postoperative period is recommended instead of close clinical imagistic observation. There are arguments in favor of radiotherapy in terms of prolonged PFS but not necessarily the OS [59]. Due to the fact that the patients receiving associated radiotherapy and chemotherapy have an improved long-term survival [60], a combined radio-chemotherapy regimen seems to be recommendable. Further studies will have to determine whether temozolomide, which was historically preferred by neuro-oncologists due to its lower toxicity and oral administration, is superior or not to PCV [61].


**5.5. Conclusion**

The design and measurements of the high-speed data capturing device for the M-sequence sensor are described in this chapter. The data capturing device utilizes the "stroboscopic feedback loop" for achieving high dynamic range together with high sampling rate.

**a) b)**

A number of different techniques are used to achieve the desired performance of the separate components.

To achieve a high effective resolution bandwidth of the analog-to-digital converter, the new segmented reference network was proposed. The new network, implemented in the ADC [46] allows increasing the effective resolution bandwidth several times compared to the similar conventional one [47], while the power dissipation is only slightly increased.

The high-speed predictor was described in VHDL and implemented using a high-speed ECL library. Despite the disadvantage of the power dissipation, the ECL implementation allows speeds of up to 10 GS/s to be achieved. Furthermore, it is simple to modify the predictor to comply with different system parameters, such as the M-sequence length or averaging factor.

An off-chip calibration was implemented for the high-speed digital-to-analog converter. The calibration is implemented on an FPGA-board. After having been modified slightly, it could be integrated into the DAC. The static errors of the DAC after calibration are lower than 0.15 % which allows the use of a converter in the data capturing device with a target resolution of 9 bits.


3.2.3. Damping Loss Factor

The loss factor which is also called damping factor, tan δ = G"/G', represents the ratio of G' to loss modulus (G") and the degree of energy dissipation during the deformation of the material. It is adopted to measure the damping e fficiency of MREs [113,114]. Dissipation occurs mainly at the interface between the matrix and the particles, that is, higher interfacial adhesion results in loss factor reduction. Hapipi et al. [115] examined plate-like CI-based MREs (MRE-P) and spherical type CI-based MREs (MRE-S). The field-dependent rheological properties were studied. Figure 5 shows the loss factor according to the frequency of both MRE-P and MRE-S. In all samples, the loss factor tends to increase with an increased frequency, whereas the loss factor of the MRE-P sample is lower than that of MRE-S. Since the primary factor of the loss factor is related to the interface interaction between the particle and the elastomer, the following results indicate that the relative motion between the particles is increased due to the weak interface bonding between the particles and the medium, which results in energy dissipation. The stronger the interfacial interaction between particles and the medium, the smaller the degree of loss factor. As a result, it confirmed that plate-like CI has stronger interfacial bonds with matrix than spherical CI particles.

**Figure 5.** Frequency dependence of loss factor with di fferent curing magnetic fields and particle shapes [115].


**3. Resources**

statistical model for the estimating PM mass concentrations using AOT measured from remote sensing techniques and meteorological parameters. Furthermore, the ground truth observa‐ tions collected within AIRSPACE project were used to assess qualitative and quantitative

daily average concentrations there was a 0.9% (95%CI: 0.6%, 1.2%) increase in all-cause and 1.2% (95%CI: -0.0%, 2.4%) increase in cardiovascular admissions. A recent study regarding dust storm events in Nicosia, Cyprus, found a 2.43% (95% CI: 0.53, 4.37) increase in daily

Air pollution in large cities is one of the major issues to be addressed by local and global communities due to its widespread presence, and deleterious impact on human life (Hadji‐ mitsis, 2009). As air pollution is a major environmental health risk, by reducing the levels of air pollutants, countries will reduce the incidence of disease from respiratory infections, heart disease and lung cancer (WHO, 2011). Actions by policy makers and public authorities at the national, regional and international levels are required in order to control the exposure to air pollutants (EEA, Air Quality in Europe, 2012 - Report). Transboundary domestic air pollution is of high concern among the EU member states. In 2010, about 21% of the EU urban population was exposed to concentrations of PM10 above the limit value established by the European Environmental Agency (EEA, Air Quality in Europe, 2012 - Report). The WHO, USEPA (U.S. Environmental Protection Agency) and EEA have established an extensive body of legislation which establishes standards and objectives for a number of air pollutants such as PM10 (coarse particles), PM2.5 (fine particles) and O3 (WHO, Fact sheet No 313, 2011; USEPA, NAAQS, 2012;

Current research focused on the study of regional and intercontinental transport of air pollutants, such as particulate matter (PM10, 2.5), points to a need for additional data sources to monitor air pollution in multiple dimensions, both spatially and temporally. To address this issue, earth observations from satellite sensors can be a valuable tool for monitoring air

Although air quality monitoring stations have been established in major cities, there is an increased need to establish mobile stations for additional coverage, as such stations provide a means for alerting the public regarding air quality. However, measuring stations are localised and do not provide sufficient geographic coverage, since air quality is highly variable spatially. The use of earth observations to monitor air pollution in different geographical areas, espe‐ cially cities, has received considerable attention from researchers (see Wald et al., 1999; Grosso and Paronis, 2012; Hadjimitsis, 2009; Hadjimitsis et al., 2010; Jones and Christopher, 2007; Michaelides et al., 2011; Nisantzi et al., 2012; Retalis and Sifakis, 2010; Retalis et al., 2003; Retalis et al., 1999; Vidot et al., 2007). Several researchers (Chudnovsky et al., 2013; Gupta et al., 2006; Koelemeijer et al., 2006; van Donkelaar et al., 2010) have focused on the use of satellite sensors on air pollution studies, especially their ability for systematic monitoring and synoptic coverage. The use of sunphotometers and LIDAR systems are found to be suitable tools for

pollution due to their ability to provide complete and synoptic views of large areas.

increase in PM10

increase in PM10 concentrations on

performance of a chemical model forecast of PM concentrations throughout Cyprus.

Midletton et al. (2008) reported that in Nicosia, Cyprus for every 10-μg/m3

dust days in comparison with non-dust days (Neophytou et al., 2013).

cardiovascular mortality associated with each 10-μg/m3

182 Remote Sensing of Environment: Integrated Approaches

**2. Background**

EEA, AAS, 2012).

### **3.1. CIMEL Sunphotometer**

At the main study site in Limassol, the sunphotometer observations were performed by a CIMEL sun-sky radiometer, which is part of the AERONET Global Network (http://aero‐ net.gsfc.nasa.gov). The CIMEL sunphotometer allows for measurements of direct solar irradiance and sky radiance at 8 wavelengths; 340, 380, 440, 500, 670, 870, 1020 and 1640 nm. The technical specifications of the instrument are given in detail by Holben et al. (1998).

**Figure 1.** CUT-TEPAK AERONET station

The instrument is located on the roof of the building of the Department of Civil Engineering and Geomatics of Cyprus University of Technology (CUT) (34.675ºN, 33.043ºE elevation: 10 m). The CUT\_TEPAK AERONET station is located in the center of Limassol, 500m away from the sea. The sunphotometric station has been in operation since April 2010. Figure 1 features the CUT-TEPAK AERONET Cimel sun-photometer.

#### **3.2. MICROTOPS Sunphotometer**

At the study sites in Nicosia, Larnaka and Paphos where CIMEL's data were not available a handheld MICROTOPS II sunphotometer was used in order to retrieve AOT measurements. The sun-photometer is equipped with five accurately aligned optical collimators and internal baffles to eliminate internal reflections. Microtops II provides AOT and water vapor retrievals at five channels, which are determined using the Bouguer-Lambert-Beer law. In order to achieve measurements with great accuracy, the sunphotometer was mounted on a tripod at the same location each time. To avoid cloud contamination, measurements were taken during cloud-free daylight hours. Figure 2 shows the MICROTOPS II handheld sunphotometer used.

**Figure 2.** MICROTOPS II handheld sunphotometer

#### **3.3. CUT LIDAR System**

For the vertical distribution of aerosols, the LIDAR system located at CUT, in Limassol, Cyprus (34.675ºN, 33.043ºE, 10 m above sea level) was used. The LIDAR records daily measurements between 08:00 UTC and 09:00 UTC (consistent with MODIS overpass) and provides continuous measurements for the retrieval of the aerosol optical properties over Limassol, Cyprus inside the Planetary Boundary Layer (PBL) and the lower free troposphere, thus providing informa‐ tion for the load, the size and the sphericity of the aerosols.

whole range starting at the full overlap of the LIDAR (~300 m) up to tropopause level. Three channels are detected, one for the wavelength 1064 nm and two for 532 nm. The two polari‐ zation components at 532nm are separated in the receiver by means of polarizing beamsplitter cubes (PBC). A special optomechanical design allows the manual ±45°-rotation of the whole depolarization detector module with respect to the laser polarization for evaluating the depolarization calibration constant of the system. The CUT depolarization LIDAR operates at 532nm and it is possible to rotate the detection box including the polarization beam-splitter cube in order to calibrate the instrument (Freudenthaler et al., 2009). Firstly, the backscattered LIDAR signals (P and S) were recorded using the normal orientation of the LIDAR detection box. For the next two steps, the LIDAR detection box is rotated by ±45º, and the P and S signals are recorded. The operation principal of this method is based on the fact that same amount of energy is sent to P and S channels, at "opposite" directions (Freudenthaler et al., 2009). Photomultiplier tubes (PMTs) are used as detectors at all wavelengths except for the signals at 1064 nm (avalanche photodiode, APD). A transient recorder that combines a powerful A/D converter (12 bit at 20 MHz) with a 250 MHz fast photon counting system (Licel, Berlin) is used for the detection of 532 nm radiation, while only analog detection is used at 1064nm. The raw

Air Pollution from Space http://dx.doi.org/10.5772/39310 185

**Figure 3.** CUT's Depolarization Lidar System

signal spatial resolution is 7.5 meters. The CUT LIDAR system is featured in Figure 3.

The LIDAR transmits laser pulses at 532 and 1064 nm simultaneously and collinear with a repetition rate of 20 Hz. This system is based on a small, rugged, flashlamp-pumped Nd-YAG laser with pulse energies around 25 and 56 mJ at 1064 and 532 nm, respectively. An achromatic beam expander reduces the divergence to less than 0.15 mrad. Elastically backscatter signals at two wavelengths (532nm, 1064nm) are collected with a Newtonian telescope with primary mirror diameter of 200 mm and an overall focal length of 1000 mm. The field of view (FOV) of the telescope is 2 mrad. The mirror and cover plate coatings are optimized for the wavelength range from 532 nm to 1064 nm. A plain cover plate protects the mirrors. Behind the field stop two plano-convex with a focal length of 80 mm output parallel rays. The LIDAR covers the

**Figure 3.** CUT's Depolarization Lidar System

The sun-photometer is equipped with five accurately aligned optical collimators and internal baffles to eliminate internal reflections. Microtops II provides AOT and water vapor retrievals at five channels, which are determined using the Bouguer-Lambert-Beer law. In order to achieve measurements with great accuracy, the sunphotometer was mounted on a tripod at the same location each time. To avoid cloud contamination, measurements were taken during cloud-free daylight hours. Figure 2 shows the MICROTOPS II handheld sunphotometer used.

For the vertical distribution of aerosols, the LIDAR system located at CUT, in Limassol, Cyprus (34.675ºN, 33.043ºE, 10 m above sea level) was used. The LIDAR records daily measurements between 08:00 UTC and 09:00 UTC (consistent with MODIS overpass) and provides continuous measurements for the retrieval of the aerosol optical properties over Limassol, Cyprus inside the Planetary Boundary Layer (PBL) and the lower free troposphere, thus providing informa‐

The LIDAR transmits laser pulses at 532 and 1064 nm simultaneously and collinear with a repetition rate of 20 Hz. This system is based on a small, rugged, flashlamp-pumped Nd-YAG laser with pulse energies around 25 and 56 mJ at 1064 and 532 nm, respectively. An achromatic beam expander reduces the divergence to less than 0.15 mrad. Elastically backscatter signals at two wavelengths (532nm, 1064nm) are collected with a Newtonian telescope with primary mirror diameter of 200 mm and an overall focal length of 1000 mm. The field of view (FOV) of the telescope is 2 mrad. The mirror and cover plate coatings are optimized for the wavelength range from 532 nm to 1064 nm. A plain cover plate protects the mirrors. Behind the field stop two plano-convex with a focal length of 80 mm output parallel rays. The LIDAR covers the

**Figure 2.** MICROTOPS II handheld sunphotometer

184 Remote Sensing of Environment: Integrated Approaches

tion for the load, the size and the sphericity of the aerosols.

**3.3. CUT LIDAR System**

whole range starting at the full overlap of the LIDAR (~300 m) up to tropopause level. Three channels are detected, one for the wavelength 1064 nm and two for 532 nm. The two polari‐ zation components at 532nm are separated in the receiver by means of polarizing beamsplitter cubes (PBC). A special optomechanical design allows the manual ±45°-rotation of the whole depolarization detector module with respect to the laser polarization for evaluating the depolarization calibration constant of the system. The CUT depolarization LIDAR operates at 532nm and it is possible to rotate the detection box including the polarization beam-splitter cube in order to calibrate the instrument (Freudenthaler et al., 2009). Firstly, the backscattered LIDAR signals (P and S) were recorded using the normal orientation of the LIDAR detection box. For the next two steps, the LIDAR detection box is rotated by ±45º, and the P and S signals are recorded. The operation principal of this method is based on the fact that same amount of energy is sent to P and S channels, at "opposite" directions (Freudenthaler et al., 2009). Photomultiplier tubes (PMTs) are used as detectors at all wavelengths except for the signals at 1064 nm (avalanche photodiode, APD). A transient recorder that combines a powerful A/D converter (12 bit at 20 MHz) with a 250 MHz fast photon counting system (Licel, Berlin) is used for the detection of 532 nm radiation, while only analog detection is used at 1064nm. The raw signal spatial resolution is 7.5 meters. The CUT LIDAR system is featured in Figure 3.

#### **3.4. Surface monitoring**

#### *3.4.1. PM10 concentration monitoring*

Two approached were used to monitor near-surface levels of particulate matter. DustTrack monitors were used at all sites to provide continuous monitoring of PM10. Harvard Impac‐ tors were usedto collect 24 hour samples ofPM10 andPM2.5 which couldbe analyzedfor mass, elemental composition, and other physical-chemical properties of the aerosol. The surface monitoringofparticulatematter(PM)concentrations,TheDustTrack(TSI,Model8533)monitors were located in each of the four sampling sites and were selected to provide weekly monitor‐ ing of PM10 concentrations during morning hours from 08:00 to 13:00 UTC. It records the PM temporal variability with satisfactory time resolution.DustTrak's nominalflow rate of 1.7 l/min is obtainedby an internalpumpintegralto the sampler.The monitoris factory calibratedforthe respirable fraction of standard ISO12103-1, A1 test dust (Arizona Test Dust), which is represen‐ tative of a wide variety of aerosols. It measures concentrations in the range of 0.001– 100 mg/m3 , with a resolution of 0.1% of the reading or 0.001 mg/m3 . Before each measurement, the instru‐ mentis zeroedandits flowrate is checked.PM10 concentrationshavebeenrecordedcontinuous‐ ly since March 2011. The instrument is located, on the roof of the Cyprus International Institute (CII) in Limassol, at 10 m above ground level in order to avoid the measurements being affected by localized pollution such as passing cars. PM10 concentrations were also recorded by Dust‐ Trak (TSI, Model 8520) at Nicosia, Larnaca and Paphos. One TSI DustTrack has been operated by Frederick University since July 2011 and is located at the top of the Frederick University librarybuildinginNicosia,at10mabovegroundlevel.The secondDustTrackhasbeenoperated by CUT's scientific team during 15-day campaigns at Larnaca and Paphos. All sampling points were selected to ensure exposure to wind and to be free of other obstacles. Figure 4 features the TSI Dust Trak. Harvard Impactors were operated each third day at the primary sampling site in Limassol and every sixth day at the other sampling sites.

providing comprehensive and reliable data on the air pollution throughout Cyprus based on

Air Pollution from Space http://dx.doi.org/10.5772/39310 187

Air pollution near ground level measurement sites were established in the four cities of Cyprus: Nicosia, Larnaca, Limassol and Paphos. These sites were located at positions thought to be representative of air pollution in each city. In Nicosia, the site is located on the roof of the Frederick University library building, on the same site where the DustTrak and sunphotometer were operated. The Larnaca site is located in the center of the city, on the roof of the tax agency building. The Limassol site is located on the roof of the CII building in the center of the city and Paphos site is on the roof of the economics department of Paphos Municipality. In Figure

The Moderate Resolution Imaging Spectro-Radiometer (MODIS) observations from the TERRA and AQUA satellites both measuring spectral radiance in 36 channels (412–14200 nm), in with resolutions between 250 m and 1 km (at nadir) were used to provide a climatology for Cyprus. In polar orbit, approximately 700 km above the Earth, MODIS views a swath of approximately 2300 km resulting in near daily global coverage of Earth's land/ocean/atmos‐ phere system. The swath is broken into 5-min ''granules'', each approximately 2,030 km long.

ground level measurements.

**Figure 5.** Harvard Samplers

*3.4.3. Satellite observations*

5 the setup of the Harvard samplers is presented.

**Figure 4.** TSI DUST-Track

#### *3.4.2. PM10 sampling and elemental composition determinations*

Under the AIRSPACE project, the Harvard School of Public Health (HSPH) and Cyprus International Institute for Environmental and Public Health (CII) were responsible for providing comprehensive and reliable data on the air pollution throughout Cyprus based on ground level measurements.

Air pollution near ground level measurement sites were established in the four cities of Cyprus: Nicosia, Larnaca, Limassol and Paphos. These sites were located at positions thought to be representative of air pollution in each city. In Nicosia, the site is located on the roof of the Frederick University library building, on the same site where the DustTrak and sunphotometer were operated. The Larnaca site is located in the center of the city, on the roof of the tax agency building. The Limassol site is located on the roof of the CII building in the center of the city and Paphos site is on the roof of the economics department of Paphos Municipality. In Figure 5 the setup of the Harvard samplers is presented.

**Figure 5.** Harvard Samplers

**3.4. Surface monitoring**

**Figure 4.** TSI DUST-Track

*3.4.1. PM10 concentration monitoring*

186 Remote Sensing of Environment: Integrated Approaches

with a resolution of 0.1% of the reading or 0.001 mg/m3

in Limassol and every sixth day at the other sampling sites.

*3.4.2. PM10 sampling and elemental composition determinations*

Two approached were used to monitor near-surface levels of particulate matter. DustTrack monitors were used at all sites to provide continuous monitoring of PM10. Harvard Impac‐ tors were usedto collect 24 hour samples ofPM10 andPM2.5 which couldbe analyzedfor mass, elemental composition, and other physical-chemical properties of the aerosol. The surface monitoringofparticulatematter(PM)concentrations,TheDustTrack(TSI,Model8533)monitors were located in each of the four sampling sites and were selected to provide weekly monitor‐ ing of PM10 concentrations during morning hours from 08:00 to 13:00 UTC. It records the PM temporal variability with satisfactory time resolution.DustTrak's nominalflow rate of 1.7 l/min is obtainedby an internalpumpintegralto the sampler.The monitoris factory calibratedforthe respirable fraction of standard ISO12103-1, A1 test dust (Arizona Test Dust), which is represen‐ tative of a wide variety of aerosols. It measures concentrations in the range of 0.001– 100 mg/m3

mentis zeroedandits flowrate is checked.PM10 concentrationshavebeenrecordedcontinuous‐ ly since March 2011. The instrument is located, on the roof of the Cyprus International Institute (CII) in Limassol, at 10 m above ground level in order to avoid the measurements being affected by localized pollution such as passing cars. PM10 concentrations were also recorded by Dust‐ Trak (TSI, Model 8520) at Nicosia, Larnaca and Paphos. One TSI DustTrack has been operated by Frederick University since July 2011 and is located at the top of the Frederick University librarybuildinginNicosia,at10mabovegroundlevel.The secondDustTrackhasbeenoperated by CUT's scientific team during 15-day campaigns at Larnaca and Paphos. All sampling points were selected to ensure exposure to wind and to be free of other obstacles. Figure 4 features the TSI Dust Trak. Harvard Impactors were operated each third day at the primary sampling site

Under the AIRSPACE project, the Harvard School of Public Health (HSPH) and Cyprus International Institute for Environmental and Public Health (CII) were responsible for

,

. Before each measurement, the instru‐

#### *3.4.3. Satellite observations*

The Moderate Resolution Imaging Spectro-Radiometer (MODIS) observations from the TERRA and AQUA satellites both measuring spectral radiance in 36 channels (412–14200 nm), in with resolutions between 250 m and 1 km (at nadir) were used to provide a climatology for Cyprus. In polar orbit, approximately 700 km above the Earth, MODIS views a swath of approximately 2300 km resulting in near daily global coverage of Earth's land/ocean/atmos‐ phere system. The swath is broken into 5-min ''granules'', each approximately 2,030 km long. Aerosol products are reported at 10 km resolution (at nadir). Details of file specification of MODIS L2 aerosol products can be found at the website http://modis.gsfc.nasa.gov/.

**2. Vertical profile of the aerosol backscatter:** A light detection and ranging (LIDAR) system was established in Limassol in April 2010, consisting of a laser capable of measuring aerosol backscatter and aerosol depolarization ratio in the atmosphere as a function of height. This allows the AOT, and hence the scaling to aerosol concentration, to be quantified below the boundary layer since this fraction best represents the PM measure‐

1) **Satellite data products from the MODIS sensor**: Aerosol optical thickness (AOT) and

**Figure 7 :** Overall Methodology of the Airspace project

**LIDAR data [aerosol vertical distribution]**

size distribution DAILY

Backscatter coefficient and particle depolarization ratio profiles

**TSI Dust track PM10 concentration**

> PM10 concentration

**Meteo data Surface T, P, RH and wind**

> **Chemical Model PM estimation**

**AIRSPACE Outputs Instrumentation Retrievals**

**Statistical Model PM estimation**

Air Pollution from Space http://dx.doi.org/10.5772/39310 189

**CIMEL/Microtops II Columnar aerosol parameters**

AOT, AE

**Climatology Natural-Anthropogenic**

**MODIS VALIDATION**

**Figure 7.** Overall Methodology of the Airspace project

2) **Vertical profile of the aerosol backscatter**: A light detection and ranging (LIDAR) system was established in Limassol in April 2010, consisting of a laser capable of measuring aerosol backscatter and aerosol depolarization ratio in the atmosphere as a function of height. This allows the AOT, and hence the scaling to aerosol concentration, to be quantified below the boundary layer since this fraction best represents the PM measurements in a well-mixed

**3. Integrated aerosol optical thickness for the entire atmospheric column:** A sunphotom‐ eter station was installed in the centre of Limassol (at the CUT premises), where pollution from both industrial and urban sources exist. This further assists in the calibration and verification of satellite derived AOT data. Moreover, two hand-held sunphotometers were

3) **Integrated aerosol optical thickness for the entire atmospheric column**: A sunphotometer station was installed in the centre of Limassol (at the CUT premises), where pollution from both industrial and urban sources exist. This will further assist calibration and verification of satellite derived AOT data. Moreover, two hand-held sunphotometers

4) **Measurements of particulate matter (PM) concentration levels**: PM10 and PM2.5 hourly concentration values were collected using portable PM samplers available from the CUT Remote Sensing Laboratory and the Harvard University. Additionally, the HARVARD samplers used and located in Limassol, Nicosia, Larnaca and Paphos regions were used to

5) **Meteorological data from the entire area of Cyprus:** Relative humidity measurements combined with the AOT fraction below the boundary layer derived by the LIDAR were incorporated into the statistical PM-AOT models, for improving the PM concentration estimation. Classification of the synoptic situations in Cyprus was also taken into account.

**4. Measurements of particulate matter (PM) concentration levels:** Ground level PM was monitored using two methods. Continuous measurements of PM10 were taken using portable monitors (DustTrack model 8533). These continuous measurements were supplemented with measurements of PM10 and PM2.5 taken using Harvard Impactors. The material collected by the Harvard Impactor was analyzed for chemical composition.

**5. Meteorological data from the entire area of Cyprus:** Relative humidity measurements combined with the AOT fraction below the boundary layers, derived by the LIDAR, were incorporated into the statistical PM-AOT models, for improving the PM concentration estimation. Classification of the synoptic situations in Cyprus was also taken into account.

**6. Simulation results from dispersion/air pollution model:** A modeling system that incorporates a fully interactive coupling between the chemistry-aerosol and meteorology (radiation and cloud-physics) portions of the model was created, allowing real-time

ments in a well-mixed boundary layer.

boundary layer.

**4.1 Method**

**Satellite aerosol Products [AOT, AE]**

AOT & AE

**10 years Aerosol**

used to measure urban, industrial and dust pollution.

were used to measure urban, industrial and dust pollution.

provide chemical characterization of the collected aerosols.

The overall methodology is described in the following (see Fig. 7):

aerosol size/type data were collected for the years 2002-2010 over Cyprus.

**Aerosol separation**

**Figure 6.** MODIS image for Eastern Mediterranean region


# **Oscillator-Amplifier Free Electron Lasers an Outlook to Their Feasibility and Performances**

Edited by Giuseppe Dattoli, Alessandro Curcio and Danilo Giulietti Printed Edition of the Special Issue Published in *Applied Sciences*

www.mdpi.com/journal/applsci