*Edited by Lakshmanan Elango*

There are several books on broad aspects of hydrogeology, groundwater hydrology and geohydrology, which do not discuss in detail on the intrigues of hydraulic conductivity elaborately. However, this book on Hydraulic Conductivity presents comprehensive reviews of new measurements and numerical techniques for estimating hydraulic conductivity. This is achieved by the chapters written by various experts in this field of research into a number of clustered themes covering different aspects of hydraulic conductivity. The sections in the book are: Hydraulic conductivity and its importance, Hydraulic conductivity and plant systems, Determination by mathematical and laboratory methods, Determination by field techniques and Modelling and hydraulic conductivity. Each of these sections of the book includes chapters highlighting the salient aspects and most of these chapters explain the facts with the help of some case studies. Thus this book has a good mix of chapters dealing with various and vital aspects of hydraulic conductivity from various authors of different countries.

ISBN 978-953-307-288-3

Hydraulic Conductivity - Issues, Determination and Applications

Photo by reisegraf / iStock

## Hydraulic Conductivity Issues, Determination and Applications

*Edited by Lakshmanan Elango*

**HYDRAULIC CONDUCTIVITY**

**– ISSUES, DETERMINATION**

**AND APPLICATIONS**

Edited by **Lakshmanan Elango**

**INTECHOPEN.COM**


**5. Hot spot mapping**

A hot spot map was produced to demonstrate locations with high, moderate, and low potentials for installing an EV charging station for the study area (**Figure 4**). High suitable areas were highlighted in red on the map. The areas have an index demand score of 50 or greater, and contain the highest mixture of input demand factors. These are driving public frequently visited areas and are ideal for installing EV charging

stations. Downtown business districts, shopping districts, employment hubs, public facilities, health care centers, park and ride lots, parking garages, and major roads and intersections, attractions, recreational areas etc., are all hot spots for EV charging stations. The yellow areas represented moderate suitable areas. This class displayed an uneven mixture of input demand factors. Moderate demand areas are secondary choices for charging station when prime areas cannot be located in surrounding areas.

**Figure 4.** *Optimal locations to install EV charging stations.*

*Using Geospatial Analysis to Assist with Clean Vehicle Infrastructure DOI: http://dx.doi.org/10.5772/intechopen.110864*

#### **Table 3.**

*Influence of the demand factors.*

Examples are small business parks near larger residential neighborhoods, and areas that are seeing population and employment growth. Low suitability areas were colored green, where showed a low mixture of influential factors and surrounded by low suitability factors such as residential neighborhoods, open space, and agricultural areas.

The multi-factor modeling system developed in this research classifies the hierarchical importance of each input demand factor, and identifies suitability of locations for installing EV charging stations. The ranking for each input demand factor was tested against the total number of input grids. The testing showed that the majority of the input demand factors had an average influential percentage of 80%, as listed in **Table 3**, indicating the model's ability to produce reliable results [29].


*2.6.3 Biology*

Life span of *Sesamia inferens* lasts in 40–50 days under favorable conditions [37]. Adults lay globular and creamy white eggs at the base of the wheat plant [38] which may range from 120 to 348 [39]. Egg color changes from creamy white to brown before hatching [40]. Larvae emerge from the fertilized eggs within a week. The newly hatched larvae are pinkish in color with a reddish-brown head [41]. Six instars of larvae take 23–39 days for entering into pupal stage [42]. Full grown larvae measure 30 mm in length [37] and pupate in stem galleries. Adults have straw-colored forewings with a trivial dark brown streak. Males have Pectinate antennae while females have filiform [43]. Under tropical conditions *Sesamia inferens* completes 4–5 generations in a year.


**3.1 Use of ozone in denim washing**

The denim garments are very popular, and they are preferred by people of all ages, classes, and genders. Depending on the desired effect, denim garments are treated with different substances [28, 29]. A lot of dry and wet processing techniques are used for desired effects [30]. Wet processes in denim washing are not environment friendly. High water and energy consumption, large amount of wastewater, and solid waste like pumice stones are generally environmental problem in denim washing [29, 30]. Sodium hypochlorite is a very common bleaching agent in denim washing. Especially AOXs (adsorbable halogenated organic compounds) are the most important environmental problem. Therefore, chlorine-free bleaching technologies are a good solution for AOX. Ozonation is an alternative bleaching method [28]. Ozonation is a simple and "green" process because it does not require steam and water. Therefore, it greatly reduces process time, water, chemical and energy consumption, and amount of wastewater [31, 32]. Ozone decomposes indigo and other dyes because of high oxidation potential. In addition to denim washing, it is generally applicable to treatment of other textiles like T-shirts, shirts, chinos, and casual wear. In ozonation, the ozone generated in the equipment can commercially provide bleaching effect. It is like washing machine without water for fading of color [31]. And ozone is generally applied to whole of the garment in this ozonation

machine. However, local bleached spots on the fabric can also be created by ozone. Ozone gas is scattered onto the denim fabric at a controlled velocity [32].

Özdemir et al. studied on ozonation parameters of denim fabric. They used prewashed denim fabric for ozonation. They inform that water content of the denim fabric is very important for efficiency of ozonation, and 50–60% water pick up value (W.P.V.) is the best for bleaching efficiency. The higher W.P.V. affects the bleaching efficiency of ozonation negatively. For ozonation, acidic and neutral pH values are better than basic pH value. Temperature is one of the most important parameters because higher temperatures decrease the half-life of ozone. Ozonation of wet denim is especially for bleaching [28].

Hmida and Ladhari studied the parameters affecting dry and wet ozone bleaching of denim fabric. Their results about the effect of W.P.A. on bleaching efficiency are also compatible with Özdemir's results. They claim that water film covers the surface of the fabric and swelling of the fibers is achieved. Then, ozone can penetrate into fibers, and bleaching efficiency on wet denim is better than that of dry denim. On the other hand, backstaining problem is solved by ozonation of dry denim [31, 33].

In the other study, denim fabric was treated with the combination of ozonated water, ultrasound, and hydrogen peroxide. According to the results, ozone is more effective with the aid of ultrasonic energy because the ultrasonic cavitations improve the penetration of ozone into the fabric, and then, ozone decomposes indigo [5, 32].

Bağıran et al. compared ozone to other bleaching agents in denim washing. According to results, ozone is one of the strong agents. It follows potassium permanganate and benzoyl peroxide. But, the most important advantage of ozone is environment friendly, and it is a good alternative to the others. Benzoyl peroxide and ozone are the causes of gray tint in bleached denim fabric. The others are the reason for blue tint of bleached denim. After ozonation, loss of strength is not too high because ozone is unstable, and it decomposes indigo primarily [34].

In practice, ozone is applied to garments. However, there are a few studies on ozonation of yarn [35, 36]. Beşen and Balcı try to fade indigo-dyed yarn before weaving and garment processes. The indigo-dyed yarn is ozonated in hank form. Their results about the effect of the ozonation condition on bleaching efficiency are generally compatible with Özdemir's results. On the other hand, the origin of the raw material directly affects the fading degree of the yarn. According to the results, the count of the yarn is the most important parameter on the decrease in strength of the yarns depending on the ozonation process. However, strength loss is not so important. As a conclusion, the ozonation condition can be determined according to desired effect from the yarns. They claim that different fading effects can be achieved by ozonation before weaving process [35].

He et al. investigated effect of ozone on three typical denim yarns (cotton, lyocell, and polyethylene terephthalate (PET)) during the color-fading process. They claim that ozone only smoothly impacts the crystalline structures of these yarns. PET is not affected by ozone because of its aggregate structure. This structure prevents the oxidation and decomposition of PET. They suggest that ozonation for cotton, lyocell, or other cellulosic yarns should be limited within 10 min at the pH > 7 with a careful selection of water content [36].

#### **3.2 Ozonation of cellulosic fibers**

A lot of researchers study on ozonation of cellulosic fibers, especially cotton. Perinçek et al. studied on the use of ozone gas in bleaching cotton fabrics. Cotton fabric containing 60% water at pH 7 can be bleached in a short time with ozonation treatment. Room temperature is the optimum for ozonation. After ozonation in a

**21**

**Figure 4.**

*Use of Ozone in the Textile Industry*

so important [5, 10].

*DOI: http://dx.doi.org/10.5772/intechopen.81774*

and rinsing the fabric after ozonation [39].

philicity values have to be considered carefully [3].

(**Figure 4**) like batik or tie-dyed cloths [40].

short time, the whiteness of the fabric is acceptable for dyeing and DP losses are not

Eren and Öztürk also investigated ozonation of cotton fabrics. According to their results, the starch size removal of the greige cotton samples and the water absorbency of the greige and desized cotton samples are increased by ozonation. But ozonation does not remove the motes successfully. Bleaching effect of ozonation

Maqsood et al. suggest ozonation of cotton fiber for medical textiles and produc-

Turhan and Soydaş discussed ozonation of cotton terry fabrics. As the results of the study, ozone cannot sufficiently remove impurities like sizing agents, natural waxes, and oils. Therefore, they suggest desizing the terry fabric before ozonation

Perinçek et al. also investigated the effects of new advanced processes on cotton woven fabric. The new advanced processes contain ozonation, ultrasound, and ultraviolet. In this study, cotton fabrics are bleached by combining ozone with ultrasound and ultraviolet. According to results, advanced processes can be used in pretreatment of cotton fabrics. However, advanced processes at 63–65°C are not sufficient for desizing the cotton fabrics and need desizing agents. After ultrasonic treatment followed by ozonation, whiteness and hydrophilicity of the fabric are sufficient for dyeing. The combination of ozone and ultraviolet processes for high whiteness of the fabric is recommended. However, breaking strengths and hydro-

Perinçek recommended a removing method of optical brightener from cotton fabric in her paper. It is difficult to remove optical brightener efficiently from the fabric when any problem is seen on the fabric due to high stability of optical brightener. Hazardous chemicals are generally used to remove it. Therefore, ozonation process has ecological advantage. The results show that ozonation can be used for decolorizing the optical bleached samples. Increasing ozonation time increases the efficiency. However, bursting strength loss of fabric should be taken into consideration due to the oxidation of cellulose. Meanwhile, a new patterning method for optical bleached fabrics is proposed in the paper. It provides fashionable products

*The photographs of fabrics treated by developed method (I: optical bleached fabric is tied in knots, tightly bound with thread; II: a = optical bleached fabric before ozonation; II: b/c = optical bleached fabric after ozonation in accordance with developed method [40]). (*Thanks to Textile and Apparel for copyright*).*

tion of nanocrystalline cellulose or nanofibrils of cellulose in their paper [38].

is successful because of high oxidation potential of ozone [37].


*3.3. Variable Measurement*

**Dependent Variables.** To measure firm innovation, we followed common practices in the innovation literature and constructed the metrics, e.g., in [11,13,14,16]. First, we used the patent-based measure to capture the corporate innovation output, that is, the natural logarithm of one plus the number of patents that the firm has filed (*LnPatents*). More precisely, this variable only counts the annual number of filed patent applications that were eventually granted. As China's State Intellectual Property Office (SIPO) does not require the citation of all related patents when applying for a patent, Chinese patent filing has a well-known problem, that is, a lack of patent citation information [27,34,43], Accordingly, we used the natural logarithm of one plus the number of invention patents (*LnInventions*), which are more innovative and original, to reflect the quality of the innovation output.

Following the practices used in previous innovation research [27,34,43], we combined the number of invention and utility patents as the firm's innovation output. We collected the number of patents for all public firms from the CSMAR database. In total, 108,969 patents were filed in the sample period including 48,663 invention patents and 60,306 utility patents.

**Control Variables**. In our regression model, we referred to prior research to control for a vector of firm-level characteristics that may influence innovation [11,16]. All control variables were collected from the CSMAR database. Specifically, we controlled for*firm size*, *firm age*, *return on assets (ROA)*, *leverage*, *cash holdings*, and *R&D intensity*. Firm size is the natural logarithm of total assets. Firm age is the natural logarithm of the number of years since the firm's inception. ROA is the ratio of net income to total assets. The leverage ratio is the total liabilities divided by the total assets. Cash holdings is the ratio of cash to total assets. R&D intensity is calculated as the R&D investment, which is collected from the annual report of each firm, scaled by the total assets. To control for outliers, we winsorize all continuous control variables at the 1st and 99th percentiles of their empirical distributions, i.e., data above (below) the 99th (1st) percentile are set to the 99th (1st) percentile. The definitions of all variables used in this paper are presented in Table A1.