**4. Comments**

At the 13th Sustainable Development of Energy, Water, and Environment Systems Conference held in 2018 in Palermo, Italy, interesting topics concerning sustainable development and energy efficiency were discussed and presented. This SI presents some of this work within the following main topics: energy efficiency and energy policy in urban areas, energy efficiency in industry and biomass and hydrogen. The editors of this SI of *Energies*, dedicated to 13th SDEWES Conference, believe that the above reported papers are focused on topics considered pivotal for the *Energies* journal. Such studies can be considered as fundamental and potentially practical tools to promote and disseminate the energy sustainability in different sectors: industries, metropolitan and urban areas, waste heat recovery, waste materials, water-energy nexus, etc.

Information on the future SDEWES Conferences and related activities are available on the website of the International Centre for Sustainable Development of Energy, Water, and Environment Systems (SDEWES Centre).

**Author Contributions:** F.C. and M.V. prepared an initial draft of the manuscript, which was completed, corrected and reviewed by M.C., N.D., Q.W. and P.A.Ø.

**Funding:** This research received no external funding.

**Acknowledgments:** The guest editors thank the authors of the papers that submitted their manuscripts to this special issue for the high quality of their work. We also thank all the reviewers who provided valuable and highly appreciated comments and advice, and the managing editors of *Energies* for their patience and excellent support.

**Conflicts of Interest:** The authors declare no conflict of interest.


The hydrodynamic model simulates the flow pattern in the Main Basin vicinity. All parameters and variables in the model have units according to the SI conventions. The coordinate system used for the model is in WGS‐84 Geographic UTM system Zone 35. All metric coordinates in this report will be given in this coordinate system. The depths and water level information in the flow model are defined relative to a levelling datum, which is equal to mean sea level (MSL). The following sections present the steps of development of Mariout hydrodynamic

The first step in the schematization process is the design and generation of the computational grid. The computational grid is a curvilinear grid to avoid the stair case problem which affects the numerical accuracy. In the design of a curvilinear grid, it is important to follow the land boundaries as good as possible. For the generation of a computational grid, the following items

analysis, the conclusions and recommendations are presented.

**4. Water quality model development**

section.

182 Lake Sciences and Climate Change

trations, etc. [20].

model.

*4.1.1. Grid generation*

are important:

**4.1. Setup of the hydrodynamic model**

**•** the areas which require the highest resolution;

**•** the orthogonality of individual cells;

The schematization of the land boundaries and the water depths have been derived from the hydrographic survey data. The bathymetric data have been mapped through an interpolation procedure on the computational grid of Mariout model. In this way, each coordinate of the computational grid of the model is given a depth value. The transition between the regions covered by different bathymetric data sources have been checked and smoothed where necessary.

#### *4.1.3. Boundary conditions*

In the flow simulations of a specific area with two open boundaries, it is preferable to set up one boundary as a discharge boundary and the other one as a water level boundary. In Lake Mariout model, the open boundary for Nubariya Canal and Omoum Drain were selected as a discharge boundary. The boundary at El‐Max Pumping station was selected as water level boundary, while other sources like Qalaa drain and the West Water Treatment Plant were

**Figure 3.** Model schematization with all boundaries and sources of discharge.

simulated as source point discharge. During the calibration phase, the discharges and water level measurements at the location of the open boundaries and at the other sources of water were used in the model. In the model scenarios (production simulations), the discharge data imposed in the discharge boundary is based on the dominant flow condition. The water levels associated with these discharges were used for each scenario as a water level boundary. The relevant water levels associated to these discharges were obtained from the historical data available about the Lake Mariout. **Figure 3** shows the model schematization with all bounda‐ ries and the source points of discharges.

#### *4.1.4. Parameter settings*

A uniform water density of 1025 kg/m3 was used, representing the salt water density. The acceleration of gravity was set to 9.81m/s2 . The value for the horizontal eddy viscosity is set to 1.0 m2 /s. The time step was selected for the model simulations based on the grid size and the Courant Number. Time step of 0.5 min (30 s) was used in the simulations. This time step fulfils the numerical criteria and the Courant Number requirements.

#### *4.1.5. Model calibration*

During the model calibration, the measured depth averaged flow velocities and water levels which were carried out by the National Institute of Oceanography and Fisheries (NIOF) were compared with the model results. Tuning of the roughness parameter in the model was carried

**Figure 4.** Flow velocity comparison at point fisheries hole in dam.

out to obtain the best match between the model and the field measurements. Manning roughness coefficient was varied between 0.02 at non‐vegetated area and 0.06 at the heavy vegetated area along the model area to give the best match between the measurements and the model computations. **Figure 4** shows the comparison between the measured and computed flow velocity values. The results for water level and currents were in good agreement with the measurements, which confirms that the model simulates the flow pattern in the main basin of Lake Mariout in the right way.

#### **4.2. Water quality model setup**

simulated as source point discharge. During the calibration phase, the discharges and water level measurements at the location of the open boundaries and at the other sources of water were used in the model. In the model scenarios (production simulations), the discharge data imposed in the discharge boundary is based on the dominant flow condition. The water levels associated with these discharges were used for each scenario as a water level boundary. The relevant water levels associated to these discharges were obtained from the historical data available about the Lake Mariout. **Figure 3** shows the model schematization with all bounda‐

/s. The time step was selected for the model simulations based on the grid size and the Courant Number. Time step of 0.5 min (30 s) was used in the simulations. This time step fulfils

During the model calibration, the measured depth averaged flow velocities and water levels which were carried out by the National Institute of Oceanography and Fisheries (NIOF) were compared with the model results. Tuning of the roughness parameter in the model was carried

was used, representing the salt water density. The

. The value for the horizontal eddy viscosity is set to

ries and the source points of discharges.

A uniform water density of 1025 kg/m3

acceleration of gravity was set to 9.81m/s2

the numerical criteria and the Courant Number requirements.

**Figure 4.** Flow velocity comparison at point fisheries hole in dam.

*4.1.4. Parameter settings*

184 Lake Sciences and Climate Change

*4.1.5. Model calibration*

1.0 m2

To apply the Delft3D‐WAQ module, the following steps must be followed:

#### *4.2.1. Selection of the processes involved in the water quality model*

In Delft3D‐WAQ module, the constituents of a water system are divided into functional groups. A functional group includes one or more substances that display similar physical and/ or (bio)chemical behaviour in a water system. Functional groups can interact with each other directly or indirectly. PLCT (Processes Library Configuration Tool) is used to choose the substances and water quality processes to be modelled. The selected substances groups and parameters are described in **Table 3**.

**Table 3.** Model parameters and associated processes.

#### *4.2.2. Model boundary conditions and observation locations*

Average historical monthly values have been selected for initial conditions of water quality parameters inside the lake. The continuity parameter which checks the mass balance of the model was set to 1 g/m3 . The model simulation period was selected as the same period for the hydrodynamic modelling, namely, for 1 month. Water quality model time step was set to 1 min. The default values were taken as input for some selected modelled substances, that they are by default constant in time and space. However, process parameters are changed in the process parameters data group because they can vary in time and/or space. Initially, process parameters will have the default value that is taken from the PLCT.

The water quality model boundary sections are selected to be the same boundary sections for the hydrodynamic model at the locations of the main input sources to the lake, where all discharges enter the lake shown in **Figure 3**. At the two sections for the Omoum drain outlet and Nubariya canal outlet, concentrations for different modelled parameters are defined as time‐varying boundary conditions. The concentrations used at the boundaries are time series average monthly concentrations for the modelling period.

#### *4.2.3. The water quality model calibration*

**Figure 5** shows the simulation of dissolved oxygen in Mariout Lake as an example of output from the model. In this study, the water quality model calibration is done on the conventional water quality parameters or oxygen group, nutrients group and coliform group (faecal and total) and process parameters are adjusted for of calibration. The model calibration was carried

**Figure 5.** Simulation of dissolved oxygen in Lake Mariout.

out by visual comparison of simulations and measurements in graphs, together with the calculation of the statistical error values such as mean relative error (MRE), the root mean square error (RMSE) to examine the performance of the model.

The simulated water quality parameters were plotted in graphs to make comparisons with respect to the observations in Lake Mariout during field survey, which were used to check how the simulations fit the observations. Besides, MRE was used to quantify the agreement of the model, by dividing the residuals by the observed values. In this study, the calculation of RE and MRE was based on the following equations:

> RE=(Csim- ) 100 *Cobs Cobs Sum RE n* ´ ¸ ¸

where Csim and Cobs are the simulated and observed values, respectively, and *n* is the number of cases. The MRE denotes the mean relative difference between simulations and observations.

**Table 4** shows the different values of RE and MRE for the modelled parameters at this level. **Figure 6** shows the calibration results of dissolved oxygen that shows good agreement with field measurements It is noted that at the entrance of the Qalaa drain to the lake, the DO has the lowest values; in general, the DO measurements are close to the simulated results with an RME value of 5.11%. **Figure 6** shows the calibration results of dissolved oxygen that shows good agreement with field measurements.

**Table 4.** Relative error for the calibrated model parameters.

*4.2.2. Model boundary conditions and observation locations*

parameters will have the default value that is taken from the PLCT.

average monthly concentrations for the modelling period.

*4.2.3. The water quality model calibration*

**Figure 5.** Simulation of dissolved oxygen in Lake Mariout.

model was set to 1 g/m3

186 Lake Sciences and Climate Change

Average historical monthly values have been selected for initial conditions of water quality parameters inside the lake. The continuity parameter which checks the mass balance of the

hydrodynamic modelling, namely, for 1 month. Water quality model time step was set to 1 min. The default values were taken as input for some selected modelled substances, that they are by default constant in time and space. However, process parameters are changed in the process parameters data group because they can vary in time and/or space. Initially, process

The water quality model boundary sections are selected to be the same boundary sections for the hydrodynamic model at the locations of the main input sources to the lake, where all discharges enter the lake shown in **Figure 3**. At the two sections for the Omoum drain outlet and Nubariya canal outlet, concentrations for different modelled parameters are defined as time‐varying boundary conditions. The concentrations used at the boundaries are time series

**Figure 5** shows the simulation of dissolved oxygen in Mariout Lake as an example of output from the model. In this study, the water quality model calibration is done on the conventional water quality parameters or oxygen group, nutrients group and coliform group (faecal and total) and process parameters are adjusted for of calibration. The model calibration was carried

. The model simulation period was selected as the same period for the

The simulated BOD and COD results are very close to the measured values at most locations within the lake, and the MRE value is around 5% for BOD5 and 5.6% for COD. For eutrophi‐ cation parameters group, the values show agreement between measured and modelled parameters with mean relative error 4.7% for DetN, 5% for NH4 values and 5.7% for PO4 values that are considered acceptable for this kind of water quality modelling. For bacterial parame‐ ters, the faecal coliform values show a difference between simulated and observed values at locations in the Omoum drain outlet station, with a relative error of 27%. This could be due to the low‐velocity distributions at these locations around the lake edges; but the overall MRE for all measurement locations is within an acceptable range of 9% for faecal coliform and 4.2% for total coliform.

**Figure 6.** Comparison between measured and modelled DO.

#### **5. Conclusions**

Unfortunately, Lake Mariout, one of the Egyptian coastal lakes, suffers from almost all possible environmental problems. In order to evaluate the environmental condition of the Lake Mariout, a 3D hydrodynamic and water quality model that simulates the lake response to pollution loading from the watershed has been developed using the Delft3D hydrodynamic module coupled with the DWAQ module. The model refers to the lake's Main Basin model including watershed simulation scenarios.

First, the 2D hydrodynamic model was developed to simulate the hydrodynamic behaviour of the lake through simulating the water velocity, current and flow within the lake basin. The developed, well‐structured hydrodynamic model was also capable of describing the physical and hydrodynamic processes of the water system. Second, a reliable water quality model lake system in this research work is coupled with the developed and calibrated hydrodynamic 2D model. The basic water quality modelling component simulates the main water quality parameters including the oxygen compounds (BOD, COD, DO), nutrients compounds (NH4, TN, TP) and finally the temperature, salinity and inorganic matter.

The calibration was conducted to compare the model results with the observed data at the different locations for both the hydrodynamic and the water quality models. The model results and calculations are in reasonable agreement with the measured concentrations. This devel‐ oped calibrated model is able to predict the basic water quality indicators of the lake system and ready to conduct any scenarios for watershed water quality management.

#### **Acknowledgements**

locations in the Omoum drain outlet station, with a relative error of 27%. This could be due to the low‐velocity distributions at these locations around the lake edges; but the overall MRE for all measurement locations is within an acceptable range of 9% for faecal coliform and 4.2%

Unfortunately, Lake Mariout, one of the Egyptian coastal lakes, suffers from almost all possible environmental problems. In order to evaluate the environmental condition of the Lake Mariout, a 3D hydrodynamic and water quality model that simulates the lake response to pollution loading from the watershed has been developed using the Delft3D hydrodynamic module coupled with the DWAQ module. The model refers to the lake's Main Basin model

First, the 2D hydrodynamic model was developed to simulate the hydrodynamic behaviour of the lake through simulating the water velocity, current and flow within the lake basin. The developed, well‐structured hydrodynamic model was also capable of describing the physical and hydrodynamic processes of the water system. Second, a reliable water quality model lake system in this research work is coupled with the developed and calibrated hydrodynamic 2D model. The basic water quality modelling component simulates the main water quality parameters including the oxygen compounds (BOD, COD, DO), nutrients compounds (NH4,

The calibration was conducted to compare the model results with the observed data at the different locations for both the hydrodynamic and the water quality models. The model results

TN, TP) and finally the temperature, salinity and inorganic matter.

for total coliform.

188 Lake Sciences and Climate Change

**5. Conclusions**

**Figure 6.** Comparison between measured and modelled DO.

including watershed simulation scenarios.

Special thanks to the Alexandria Coastal Zone Management Project (2010–2015) financed by the Global Environment Facility (GEF) managed through the World Bank in coordination with the Egyptian Environmental Affairs Agency (EEAA) for providing the data required to accomplish this work.

#### **Author details**

Noha Donia

Address all correspondence to<EMAIL_ADDRESS>
Institute of Environmental studies and Researches, Ain Shams University, Cairo

#### **References**

[7] Sagehashi M., Sakoda A., Suzuki, M. A mathematical model of a shallow and eutrophic lake (the Keszthely Basin, Lake Balaton) and simulation of restorative manipulations.

[8] Buttcher D., Approaches for Nutrient Management in the Lake Okeechobee Watershed, Symposium Handbook, Practical Management for Good Lake Water Quality. 2003;

[9] Zacharias I., Gianni A., Hydrodynamic and dispersion modeling as a tool for restora‐ tion of coastal ecosystems. Application to a re‐flooded. Environmental Modelling and

[10] EEAA (The Egyptian Environmental Affairs Agency), Annual Report for the Environ‐ mental Monitoring Program for the Northern Lakes, 2012; Ministry of Environment,

[11] ALAMIM (Alexandria Lake Mariout Integrated Management), Integrated Action Plan,

[12] Hossam M. N., Salem A. A. S., Evaluation of drainage water quality for reuse: a case study of the Omoum drain in Egypt. Lowland Technology International, 2003; Vol. 5(2):

[13] Mateo M. Á., Lake Mariout: An Ecological Assessment, Laura Serrano and Oscar Serrano (CEAB‐CSIC), WADI Project (Water Demand Integration; INCOCT‐ 2005‐ 015226) and CEDARE (Centre for the Development of the Arabic Region), 2009. [14] SOGREAH, Alexandria Integrated Coastal Zone Management AICZM, Egyptian

[15] Mahlis A. M., El‐Wakeel S. K., Morcos S. A., The major cations in Lake Mariout waters.

[16] Allen R. G., Pereira L. S., Raes D., Smith M., Crop Evapotranspiration Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage, Paper 56. 1998;

[17] Fermor P. M., Gilbert J. C., Gowing D. J. G., Reedbed evapotranspiration rates in

[18] NIOF (National Institute of Oceanography and fisheries). Lake Mariout Data Acquis‐

[19] Delft3D‐FLOW, Simulation of Multi‐Dimensional Hydrodynamic and Transport

[20] D‐Water Quality, Water Quality and Aquatic Ecology Modelling Suite. 2015; Delaters,

Pollution Abatement Project EPAP II,). Base line Conditions, 2008.

England. Hydrological Processes, 2001; Vol. 15(4): pp. 621–631.

Phenomena, Including Sediments. 2015; Delaters, The Netherlands.

Water Research, 2001; Vol. 35(7): pp. 1675–1686.

EC‐SMAP III, March 2009; American Public Health.

Hydrobiologica, 1970; Vol. 36(2): pp. 253–274.

Software, 2008; Vol. 23(6): pp. 751–767.

New Zealand.

190 Lake Sciences and Climate Change

Egypt.

pp. 27–38.

FAO, Rome.

ition. 2008.

The Netherlands.

### *Edited by M.Nageeb Rashed*

Lakes are highly essential for their water quality, habitat suitability, and water supply. Lakes constitute important source for aquatic life, fish, wildlife, and human, but can undergo rapid environmental changes. Most important factors that affect lake ecosystem are climate, atmospheric inputs, land use, morphology, and physiography. Several environmental problems can affect a lake's water quality, and habitat suitability. The book "Lake Sciences and Climate Change" deals with several aspects of lake sciences (botany, zoology, geology, chemistry, models, morphology, and physiography) ,as well as the effect of climatic changes on lake body ecosystem. The book is divided into three sections and structured into 10 chapters. The first section discusses the relationship between lake and climatic change; the second section explains lake biology and health; and the third section focuses on water quality, management, and modeling. Scientists from different fields of lake sciences reported in this book their findings.

Lake Sciences and Climate Change

Lake Sciences

and Climate Change

*Edited by M.Nageeb Rashed*

Photo by valio84sl / iStock


**1. Introduction**

Energy is an integral part of today's modern life, but the way most the energy is produced around the world creates several environmental and sustainability issues. Environmental sustainability is the core issue that needs to be addressed for development to focus on human well-being and yet stay within the limitations of the planet's capacity. Environmentally sound waste management is one of the key elements for sustainable development. The idea of sustainability developed in the early 1980s as reported in the International Geosphere-Biosphere Program can be defined as "meeting fundamental human needs while preserving the earth natural environment" [1]. Since the earth's population is increasing, it is putting pressure on the earth's resources. According to the World Economic Forum, it is estimated that food production will need to double by 2050 to feed 10 billion people on the earth [2]. Today, sustainability has three essential pillars, including environmental protection, social development, and economic growth; sustainable development can be been defined as a development that meets the needs of the present without compromising the ability of future generations to meet their own needs [3]. The need for sustainable development is truly recognized by all countries, and thus in 2015, the United Nations (UN) was able to introduce 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [4]. The UN under Goal 12 (Responsible Consumption and Production) of its SDGs aims to substantially reduce waste generation through prevention, reduction, recycling, and reuse. Data from 214 cities or municipalities in 103 countries show that about three quarters of MSW generated is collected (**Figure 1**). In sub-Saharan Africa, less than half of all MSW generated is collected, with adverse effects on the health of residents. Moreover, even when waste is collected, it is often not treated and disposed of in a sustainable and environmentally sound manner. Managing such wastes continues to be a major challenge facing urban areas in several regions. Appropriate waste management is important for conserving local and global environments. Improvement of waste management in developing countries is directly related to preventing environmental pollution and expanding public health services. Appropriate waste management contributes to reducing not only the emission of water/atmospheric pollutants and odors but also the emission of greenhouse gases. In this regard, some studies reported that Green House Gases (GHG) emissions from the waste sector contribute to 3–4% of total global GHG emissions [7]. The rapidly increasing amount of municipal waste in cities around the globe is connected with economic development, as an increase in the city population creates many major challenges associated with economic development [8].

Gulf Cooperation Council (GCC) member countries (Saudi Arabia, Oman, United Arab Emirates, Kuwait, and Qatar) are considered as major consumers of the natural resources, which results in a huge amount of emissions [9, 10]. Similarly, the annual solid waste generation in the GCC region has exceeded 150 million tons. GCC countries feature among the world's top 10 per capita waste generators (**Figure 2**). Similarly, the annual solid waste generation in the GCC region has exceeded 150 million tons. Comparatively, this is lower than the waste generated in the UK, as GCC has a lower population (=54 million) than the UK (66 million); however, at the same time; the UK recycles more than 45% of its waste [12]. The recycling of waste in the GCC is almost zero. Lack of legal and institutional frameworks has been a major stumbling block in the progress of the waste management sector [11]. The per capita production of municipal waste in top GCC cities, such as Riyadh, Doha, Abu Dhabi, and Dubai, is more than 1.5 kg per day which is among the highest worldwide [13]. Some recent studies which considered situations of waste in the whole gulf region indicate that the recycling sector is underdeveloped and hardly 10–15% of the waste is recycled [14]. This chapter considers the MSW in Oman to produce electricity. Currently, the MSW

**257**

**Figure 2.**

**2. Literature review**

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

of the MSW in Oman goes to landfills [17].

*GCC population versus municipal waste generation [6, 11].*

consumption, and the types of waste-to-energy plants.

in Oman is deposited in more than 300 landfills/dumpsites managed by municipalities. Overall, most of the solid waste is sent to authorized and unauthorized dumpsites for disposal, which is creating environmental and health issues. There are several dumpsites which are located in the midst of residential areas or close to catchment areas of private and public drinking water bodies. Similarly, these landfill stations occupied a large area of land which can be utilized for some other purposes. For instance, as per the Ministry of Housing regulations, each Omani is eligible to get a plot of 500 sqm for the house after reaching a certain age [15]. Of course, this is a non-sustainable approach, but this is the current policy of the government, and thus the reduction in landfills will help Oman to fulfill such commitment in a more appropriate manner. Similarly, a survey conducted by the Be'ah, a company established under the Royal Decree 46/2009, shows that solid waste in Oman is characterized by a very high percentage of recyclables, primarily paper and cardboard (15%), plastics (20.9%), metals (1.8%), and glass (4%) [16]. Some of the newspaper reports show that currently 100%

To reduce GHG emissions from MSW and to reduce the burden of landfills on the earth, proper disposal and recycling of MSW are important. One of the modern methods that are recently adopted by many countries is to use MSW in a plant to produce energy. This type of plant is commonly known as waste-to-energy plants. The aim of this research is therefore to explore the opportunities to use MSW for electricity production in Oman. Such opportunities, however, cannot be understood well without knowing the composition of the MSW, public participation, and cooperation in activities related to recycling. This research, therefore, incorporates both quantitative and qualitative approaches, commonly known as mixed method, were adopted to accomplish the aims and objectives set for the research. The next section provides a literature review, covering Oman energy situation, electricity

Although energy has become an integral requirement of today's modern life and it is considered as a fundamental element for social and economic growth, however,

#### **Figure 1.**

*Proportion of the municipal solid waste generated that is collected, 2001–2015 (data from 214 cities/ municipalities in 103 countries) [5, 6].*

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

#### **Figure 2.**

*Biotechnological Applications of Biomass*

challenges associated with economic development [8].

development is truly recognized by all countries, and thus in 2015, the United Nations (UN) was able to introduce 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [4]. The UN under Goal 12 (Responsible Consumption and Production) of its SDGs aims to substantially reduce waste generation through prevention, reduction, recycling, and reuse. Data from 214 cities or municipalities in 103 countries show that about three quarters of MSW generated is collected (**Figure 1**). In sub-Saharan Africa, less than half of all MSW generated is collected, with adverse effects on the health of residents. Moreover, even when waste is collected, it is often not treated and disposed of in a sustainable and environmentally sound manner. Managing such wastes continues to be a major challenge facing urban areas in several regions. Appropriate waste management is important for conserving local and global environments. Improvement of waste management in developing countries is directly related to preventing environmental pollution and expanding public health services. Appropriate waste management contributes to reducing not only the emission of water/atmospheric pollutants and odors but also the emission of greenhouse gases. In this regard, some studies reported that Green House Gases (GHG) emissions from the waste sector contribute to 3–4% of total global GHG emissions [7]. The rapidly increasing amount of municipal waste in cities around the globe is connected with economic development, as an increase in the city population creates many major

Gulf Cooperation Council (GCC) member countries (Saudi Arabia, Oman, United Arab Emirates, Kuwait, and Qatar) are considered as major consumers of the natural resources, which results in a huge amount of emissions [9, 10]. Similarly, the annual solid waste generation in the GCC region has exceeded 150 million tons. GCC countries feature among the world's top 10 per capita waste generators (**Figure 2**). Similarly, the annual solid waste generation in the GCC region has exceeded 150 million tons. Comparatively, this is lower than the waste generated in the UK, as GCC has a lower population (=54 million) than the UK (66 million); however, at the same time; the UK recycles more than 45% of its waste [12]. The recycling of waste in the GCC is almost zero. Lack of legal and institutional frameworks has been a major stumbling block in the progress of the waste management sector [11]. The per capita production of municipal waste in top GCC cities, such as Riyadh, Doha, Abu Dhabi, and Dubai, is more than 1.5 kg per day which is among the highest worldwide [13]. Some recent studies which considered situations of waste in the whole gulf region indicate that the recycling sector is underdeveloped and hardly 10–15% of the waste is recycled [14]. This chapter considers the MSW in Oman to produce electricity. Currently, the MSW

*Proportion of the municipal solid waste generated that is collected, 2001–2015 (data from 214 cities/*

**256**

**Figure 1.**

*municipalities in 103 countries) [5, 6].*

*GCC population versus municipal waste generation [6, 11].*

in Oman is deposited in more than 300 landfills/dumpsites managed by municipalities. Overall, most of the solid waste is sent to authorized and unauthorized dumpsites for disposal, which is creating environmental and health issues. There are several dumpsites which are located in the midst of residential areas or close to catchment areas of private and public drinking water bodies. Similarly, these landfill stations occupied a large area of land which can be utilized for some other purposes. For instance, as per the Ministry of Housing regulations, each Omani is eligible to get a plot of 500 sqm for the house after reaching a certain age [15]. Of course, this is a non-sustainable approach, but this is the current policy of the government, and thus the reduction in landfills will help Oman to fulfill such commitment in a more appropriate manner. Similarly, a survey conducted by the Be'ah, a company established under the Royal Decree 46/2009, shows that solid waste in Oman is characterized by a very high percentage of recyclables, primarily paper and cardboard (15%), plastics (20.9%), metals (1.8%), and glass (4%) [16]. Some of the newspaper reports show that currently 100% of the MSW in Oman goes to landfills [17].

To reduce GHG emissions from MSW and to reduce the burden of landfills on the earth, proper disposal and recycling of MSW are important. One of the modern methods that are recently adopted by many countries is to use MSW in a plant to produce energy. This type of plant is commonly known as waste-to-energy plants. The aim of this research is therefore to explore the opportunities to use MSW for electricity production in Oman. Such opportunities, however, cannot be understood well without knowing the composition of the MSW, public participation, and cooperation in activities related to recycling. This research, therefore, incorporates both quantitative and qualitative approaches, commonly known as mixed method, were adopted to accomplish the aims and objectives set for the research. The next section provides a literature review, covering Oman energy situation, electricity consumption, and the types of waste-to-energy plants.

#### **2. Literature review**

Although energy has become an integral requirement of today's modern life and it is considered as a fundamental element for social and economic growth, however, the United Nations report indicated that 13% of the earth's populations still have no access to modern electricity. Similarly, more than 3 billion people are still using wood, coal, charcoal, or animal waste for cooking their food and heating purposes. Energy is considered as the dominant contributor to climate change, which is estimated to be around 60% of total global greenhouse gas emissions. Similarly, it is estimated that in 2012, the indoor air pollution from using combustible fuels for household energy caused 4.3 million deaths around the world [18]. Overall, most of the current energy production is based on conventional resources such as oil, gas, and coal which, on the one hand, are non-sustainable but also, on the other hand, these resources produce greenhouse gases. These gases are considered a threat to the earth due to its contribution to global warming and climate change. The main gas which highly contributes to global warming and climate change is CO2. The emission of the CO2 to the earth's atmosphere has been significantly increased since 1950 which has reached a level of 400 parts per million (ppm). The CO2 emission during the past 800,000 years until 1950 was below the level of 300 ppm [19].

Majority of the greenhouse gases are regarded as manmade gases in which the major role has been played by the recent industrialization. Although, the issue of global warming and climate change is well regarded as a threat to human life on the earth and there have been several efforts to control the emissions which cause global warming and climate change, the data from different sources reflect that these emissions are still increasing. For instance, the global CO2 emission from fossil fuels in 2010 was 33.1 gigatons which have increased to 37.1 gigatons in 2018, representing a total increase of 12.08%. This emission quite alarming and if not tackled properly, and if it is increased at the same level, it would reach 41.58 gigatons by 2028 [20].

Goal 7 of the UN SDGs is "Affordable and Sustainable Energy" under which the member countries agreed to ensure access to affordable, reliable, sustainable, and modern energy. This goal is further supported by five global targets as mentioned below:

Target 1: By 2030, ensure universal access to affordable, reliable, and modern energy services.

Target 2: By 2030, increase substantially the share of renewable energy in the global energy mix.

Target 3: By 2030, double the global rate of improvement in energy efficiency.

Target 4: By 2030, enhance international cooperation to facilitate access to clean energy research and technology, including renewable energy, energy efficiency, and advanced and cleaner fossil-fuel technology, and promote investment in energy infrastructure and clean energy technology.

Target 5: By 2030, expand infrastructure and upgrade technology for supplying modern and sustainable energy services for all in developing countries, in particular, least developed countries, Small Island, developing States, and land-locked developing countries, in accordance with their respective programs of support.

To effectively understand the energy requirement of GCC countries, the electricity consumption and CO2 emission in these countries are considered in the first instance. As the gulf region is rich in oil and gas reserves, therefore this region is considered as the main producer and supplier of the energy. The oil and gas revenue constitutes a major portion of the gross domestic product (GDP) in most of the GCC countries and remained support for the government and industrial sectors [21]. At the same time, the region is also a main consumer of energy as compared with other countries around the world. Similarly, due to the high rate of electricity consumption in these countries, the CO2 emission is also high as presented in **Figure 3**. High electricity consumption and CO2 emission could be justified due to the climatic condition of the region where the temperature in summer reaches 50°C as reported by Umar and Egbu [24], however, such

**259**

**Figure 3.**

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

consumption and emissions are more than the double when compared with other countries. For instance, the average electricity consumption in GCC countries [=12,896.058 kilowatt-hours (kWh)] as of 2014, is more than three times greater than the electricity consumption in China (=3927 kWh) [22]. Similarly, the GCC electricity consumption per capita is more than double the consumption in the United Kingdom (=5130 kWh). It is very difficult to justify so high consumption of electricity in the GCC region based on the argument that it has a hot climatic condition. if this argument is considered to be true, then a high consumption is to be expected from the United Kingdom as well, as it has a cold climatic condition, however, the consumption in the united kingdom is far low than the average consumption of the GCC. Similarly, the average CO2 emission is GCC countries (=25.36 tons) is more than three times greater than the CO2 emission per capita in China (=7.5 tons) and almost four times greater than the CO2 emission per capita in the United Kingdom (=6.5 tons) [23]. The main reason for this high CO2 emission in GCC countries is that most of the electricity in these countries is produced by oil and gas. For instance, in Saudi Arabia, a total of 330.5 billion kWh of electricity was generated in 2016. 40.30% of this electricity was produced from oil, 59.6% was produced by gas, and only 1% was produced from renewable resources [25]. Similarly, according to the British Petroleum report, 68% of the electricity in Oman is produced by gas while the remaining 32% is produced by oil. Overall, the share of GCC countries in the renewable section is almost negligible. At the same, in other parts of the world, research is in progress to explore how to meet the full energy requirement of cities through renewable sources [26, 27]. Thus, it is obviously clear that a huge emission could be expected from these countries when all of

*Electricity consumption and CO2 emission per capita in GCC countries [22, 23].*

Different estimates show that 0.0016 barrels of oil is required to produce 1 kWh

of electricity and one barrel of oil produces 0.43 tons of CO2 [28, 29]. To clarify the situation more effectively, the total electricity consumption per capita in the GCC region is 77376.349 kWh and the total CO2 emission in this region is 152.2 ton (=152,200 kg). In other words, the CO2 production per capita per kWh in the GCC region stands at 1.97 kg (1.97 kg/kWh). This further reveals that the CO2 production

its energy requirements will be met from fossil fuels.

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

#### **Figure 3.**

*Biotechnological Applications of Biomass*

the United Nations report indicated that 13% of the earth's populations still have no access to modern electricity. Similarly, more than 3 billion people are still using wood, coal, charcoal, or animal waste for cooking their food and heating purposes. Energy is considered as the dominant contributor to climate change, which is estimated to be around 60% of total global greenhouse gas emissions. Similarly, it is estimated that in 2012, the indoor air pollution from using combustible fuels for household energy caused 4.3 million deaths around the world [18]. Overall, most of the current energy production is based on conventional resources such as oil, gas, and coal which, on the one hand, are non-sustainable but also, on the other hand, these resources produce greenhouse gases. These gases are considered a threat to the earth due to its contribution to global warming and climate change. The main gas which highly contributes to global warming and climate change is CO2. The emission of the CO2 to the earth's atmosphere has been significantly increased since 1950 which has reached a level of 400 parts per million (ppm). The CO2 emission during

the past 800,000 years until 1950 was below the level of 300 ppm [19].

Majority of the greenhouse gases are regarded as manmade gases in which the major role has been played by the recent industrialization. Although, the issue of global warming and climate change is well regarded as a threat to human life on the earth and there have been several efforts to control the emissions which cause global warming and climate change, the data from different sources reflect that these emissions are still increasing. For instance, the global CO2 emission from fossil fuels in 2010 was 33.1 gigatons which have increased to 37.1 gigatons in 2018, representing a total increase of 12.08%. This emission quite alarming and if not tackled properly, and if it is increased at the same level, it would reach 41.58 gigatons by 2028 [20]. Goal 7 of the UN SDGs is "Affordable and Sustainable Energy" under which the member countries agreed to ensure access to affordable, reliable, sustainable, and modern energy. This goal is further supported by five global targets as men-

Target 1: By 2030, ensure universal access to affordable, reliable, and modern

Target 2: By 2030, increase substantially the share of renewable energy in the

Target 3: By 2030, double the global rate of improvement in energy efficiency. Target 4: By 2030, enhance international cooperation to facilitate access to clean energy research and technology, including renewable energy, energy efficiency, and advanced and cleaner fossil-fuel technology, and promote investment in energy

Target 5: By 2030, expand infrastructure and upgrade technology for supplying modern and sustainable energy services for all in developing countries, in particular, least developed countries, Small Island, developing States, and land-locked developing

To effectively understand the energy requirement of GCC countries, the electricity consumption and CO2 emission in these countries are considered in the first instance. As the gulf region is rich in oil and gas reserves, therefore this region is considered as the main producer and supplier of the energy. The oil and gas revenue constitutes a major portion of the gross domestic product (GDP) in most of the GCC countries and remained support for the government and industrial sectors [21]. At the same time, the region is also a main consumer of energy as compared with other countries around the world. Similarly, due to the high rate of electricity consumption in these countries, the CO2 emission is also high as presented in **Figure 3**. High electricity consumption and CO2 emission could be justified due to the climatic condition of the region where the temperature in summer reaches 50°C as reported by Umar and Egbu [24], however, such

countries, in accordance with their respective programs of support.

**258**

tioned below:

energy services.

global energy mix.

infrastructure and clean energy technology.

*Electricity consumption and CO2 emission per capita in GCC countries [22, 23].*

consumption and emissions are more than the double when compared with other countries. For instance, the average electricity consumption in GCC countries [=12,896.058 kilowatt-hours (kWh)] as of 2014, is more than three times greater than the electricity consumption in China (=3927 kWh) [22]. Similarly, the GCC electricity consumption per capita is more than double the consumption in the United Kingdom (=5130 kWh). It is very difficult to justify so high consumption of electricity in the GCC region based on the argument that it has a hot climatic condition. if this argument is considered to be true, then a high consumption is to be expected from the United Kingdom as well, as it has a cold climatic condition, however, the consumption in the united kingdom is far low than the average consumption of the GCC. Similarly, the average CO2 emission is GCC countries (=25.36 tons) is more than three times greater than the CO2 emission per capita in China (=7.5 tons) and almost four times greater than the CO2 emission per capita in the United Kingdom (=6.5 tons) [23]. The main reason for this high CO2 emission in GCC countries is that most of the electricity in these countries is produced by oil and gas. For instance, in Saudi Arabia, a total of 330.5 billion kWh of electricity was generated in 2016. 40.30% of this electricity was produced from oil, 59.6% was produced by gas, and only 1% was produced from renewable resources [25]. Similarly, according to the British Petroleum report, 68% of the electricity in Oman is produced by gas while the remaining 32% is produced by oil. Overall, the share of GCC countries in the renewable section is almost negligible. At the same, in other parts of the world, research is in progress to explore how to meet the full energy requirement of cities through renewable sources [26, 27]. Thus, it is obviously clear that a huge emission could be expected from these countries when all of its energy requirements will be met from fossil fuels.

Different estimates show that 0.0016 barrels of oil is required to produce 1 kWh of electricity and one barrel of oil produces 0.43 tons of CO2 [28, 29]. To clarify the situation more effectively, the total electricity consumption per capita in the GCC region is 77376.349 kWh and the total CO2 emission in this region is 152.2 ton (=152,200 kg). In other words, the CO2 production per capita per kWh in the GCC region stands at 1.97 kg (1.97 kg/kWh). This further reveals that the CO2 production for China (=1.90 kg/kWh) and United Kingdom (1.26 kg/kWh) is lower than the GCC region. As shown in **Figure 4**, the high consumption of natural resources has derailed the progress of both the relevant goals of UN SDGs, Goal 12 (Responsible Consumption and Production) and Goal 13 (Climate Action). On the other hand, Denmark which is ranked first in terms of progress toward UN SDGs has achieved a score of 90.20 (out of 100) in Goal 13 [30].

The move of the GCC region toward renewable energy may change these figures and could enable the region to reduce its emission per kWh. Oman has particularly low oil and gas reserves, therefore, it is important for the country to take advantages from other resources that are available and can be used for electricity production so that that the pressure on its oil and gas reserves can be reduced and as such can stay for long [31]. Despite the fact that Oman has comparatively low oil and gas reserves, its progress toward renewable recourses is low [32]. Similarly, both the Omani visions 2020 and 2040 stress to reduce the dependency on the oil and gas revenue and on the action plan mentions that improve MSW collection service. These visions also emphasize that improved MSW collection and disposal system are mandatory to reduce the impact on the natural environment [33, 34].

One of the resources that have been used by many countries to produce electricity is waste. For instance, Japan is using 72% of its waste to produce energy, while the United States is using approximately 13% of the waste for the same purpose. The top leading countries around the world which are using waste for energy production along with the percentage of the waste they are using for such purpose as shown in **Figure 5**. There is an opportunity for Oman to take advantage of the waste-to-energy technique and produce a share of its energy requirement from the MSW as other countries are doing. This will not only help to reduce the burden of the Oman oil and gas reserves but will also help to minimize MSW impact on the natural environment.

There are three types of combustion technologies that can be used to produce energy from MSW [36]. The mass-burn facilities are the most common type of waste-to-energy plants installed in the United States [37]. In some types of plants, it is necessary to segregate the MSW before it is moved to the combustion chamber while in other it is not necessary. The segregation of waste before entering the burn unit allows extracting the recyclable materials from the waste [38]. In most cases, the mass-burn facilities are made to burn the waste in one burning chamber allowing excess air. In the combustion process, excess air must be allowed to promote turbulence and mixing so that air can reach all waste. This process is important due to the inconsistent composition of MSW. In a common mass-burn plant, the MSW is

**261**

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

conventional boiler system [40, 41].

Agency (JICA) in Hanoi [42–44].

**3. Research approach**

**Figure 5.**

burned in a sloping and moving grate. The vibration allows the blending of MSW and helps it to mix with air. Similarly, the modular systems are made to combust the unprocessed and mixed waste. Such plants are quite smaller when compared with the mass-burn unit and therefore can be moved from one site to another site easily [39]. The third type of waste-to-energy plants are known as "Refuse Derived Fuel Systems." Such plants apply mechanical systems to segregate the MSW and allow only combustible materials and mixtures to be used in the furnace or in a

*Percentage of waste that is used for energy production in different countries [35].*

The research methodology used in this research is explained in the next section.

Both the qualitative and quantitative research strategies were employed to obtain the aims and objectives set for this research. Since the quantity and the composition of the MSW are important to know energy content and emissions, therefore, the samples of MSW were collected from different households. To know the composition of the MSW in Oman, a total of 238 samples collected from 25 residential houses (175 samples), four restaurants (28 samples), three shopping markets (21 samples), and two hotels (14 samples) as shown in **Table 1**. The houses were selected in a way so that the reliability could be achieved. Thus, the houses with the family members of 2, 3, 4, 5, and 6 were considered for data collection. Samples of waste were collected from each house on a 24-hour basis. The same approach was adopted to collect the samples from restaurants (four numbers), shopping markets (three numbers), and hotels (two numbers). The samples were collected on each day of the week. The samples were deposed in the municipality collection point after recording the required data. Every morning the samples were collected, segregated, and measured. The data collection was completed in 2 months, from June 27, 2019 to August 26, 2019. The segregation method adopted was according to the criteria followed in the 3R projects implemented by Japan International Cooperation

Additionally, the residents' willingness and participation in recycling activities were captured through an interview conducted at the time of sample collection. A total of 34 interviews, 25 from residential houses, four from restaurants, three from shopping markets, and two from hotels were conducted. The sample used to know

**Figure 4.** *Goals 12 and 13 score of different GCC countries.*

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

#### **Figure 5.**

*Biotechnological Applications of Biomass*

score of 90.20 (out of 100) in Goal 13 [30].

mize MSW impact on the natural environment.

for China (=1.90 kg/kWh) and United Kingdom (1.26 kg/kWh) is lower than the GCC region. As shown in **Figure 4**, the high consumption of natural resources has derailed the progress of both the relevant goals of UN SDGs, Goal 12 (Responsible Consumption and Production) and Goal 13 (Climate Action). On the other hand, Denmark which is ranked first in terms of progress toward UN SDGs has achieved a

The move of the GCC region toward renewable energy may change these figures and could enable the region to reduce its emission per kWh. Oman has particularly low oil and gas reserves, therefore, it is important for the country to take advantages from other resources that are available and can be used for electricity production so that that the pressure on its oil and gas reserves can be reduced and as such can stay for long [31]. Despite the fact that Oman has comparatively low oil and gas reserves, its progress toward renewable recourses is low [32]. Similarly, both the Omani visions 2020 and 2040 stress to reduce the dependency on the oil and gas revenue and on the action plan mentions that improve MSW collection service. These visions also emphasize that improved MSW collection and disposal system

are mandatory to reduce the impact on the natural environment [33, 34]. One of the resources that have been used by many countries to produce electricity is waste. For instance, Japan is using 72% of its waste to produce energy, while the United States is using approximately 13% of the waste for the same purpose. The top leading countries around the world which are using waste for energy production along with the percentage of the waste they are using for such purpose as shown in **Figure 5**. There is an opportunity for Oman to take advantage of the waste-to-energy technique and produce a share of its energy requirement from the MSW as other countries are doing. This will not only help to reduce the burden of the Oman oil and gas reserves but will also help to mini-

There are three types of combustion technologies that can be used to produce energy from MSW [36]. The mass-burn facilities are the most common type of waste-to-energy plants installed in the United States [37]. In some types of plants, it is necessary to segregate the MSW before it is moved to the combustion chamber while in other it is not necessary. The segregation of waste before entering the burn unit allows extracting the recyclable materials from the waste [38]. In most cases, the mass-burn facilities are made to burn the waste in one burning chamber allowing excess air. In the combustion process, excess air must be allowed to promote turbulence and mixing so that air can reach all waste. This process is important due to the inconsistent composition of MSW. In a common mass-burn plant, the MSW is

**260**

**Figure 4.**

*Goals 12 and 13 score of different GCC countries.*

*Percentage of waste that is used for energy production in different countries [35].*

burned in a sloping and moving grate. The vibration allows the blending of MSW and helps it to mix with air. Similarly, the modular systems are made to combust the unprocessed and mixed waste. Such plants are quite smaller when compared with the mass-burn unit and therefore can be moved from one site to another site easily [39]. The third type of waste-to-energy plants are known as "Refuse Derived Fuel Systems." Such plants apply mechanical systems to segregate the MSW and allow only combustible materials and mixtures to be used in the furnace or in a conventional boiler system [40, 41].

The research methodology used in this research is explained in the next section.

### **3. Research approach**

Both the qualitative and quantitative research strategies were employed to obtain the aims and objectives set for this research. Since the quantity and the composition of the MSW are important to know energy content and emissions, therefore, the samples of MSW were collected from different households. To know the composition of the MSW in Oman, a total of 238 samples collected from 25 residential houses (175 samples), four restaurants (28 samples), three shopping markets (21 samples), and two hotels (14 samples) as shown in **Table 1**. The houses were selected in a way so that the reliability could be achieved. Thus, the houses with the family members of 2, 3, 4, 5, and 6 were considered for data collection. Samples of waste were collected from each house on a 24-hour basis. The same approach was adopted to collect the samples from restaurants (four numbers), shopping markets (three numbers), and hotels (two numbers). The samples were collected on each day of the week. The samples were deposed in the municipality collection point after recording the required data. Every morning the samples were collected, segregated, and measured. The data collection was completed in 2 months, from June 27, 2019 to August 26, 2019. The segregation method adopted was according to the criteria followed in the 3R projects implemented by Japan International Cooperation Agency (JICA) in Hanoi [42–44].

Additionally, the residents' willingness and participation in recycling activities were captured through an interview conducted at the time of sample collection. A total of 34 interviews, 25 from residential houses, four from restaurants, three from shopping markets, and two from hotels were conducted. The sample used to know

#### **Table 1.**

*MSW samples collection approach.*

the residents' willingness and participation was considered appropriate as there is evidence in the existing literature that similar studies were conducted with much smaller samples. For instance, Mason [45], in his research entitled "Sample Size and Saturation in Ph.D. Studies Using Qualitative Interviews," reported the result of 560 studies and noted that the most common size of the sample in these studies was 20. Similarly, Umar [46], while developing an integrated approach to promote sustainability in university campuses, used a sample of 20 respondents. Although the questionnaire used for this purpose was prepared in English, due to the diversity of the respondents, the interview process was deemed fit to the respondents. Overall, 45% of the residents in Oman are expatriates and the majority of them belong to some Asian countries [47]. The participants in the data collection were therefore interviewed in the local language so that there could be no communication barriers.

The environmental performance of the current approach of MSW management was measured through the emissions produced by landfills. The Intergovernmental Panel on Climate Change (IPCC) 2006 model is used to calculate GHG emissions from landfills [48]. IPCC model is an international model used by The United Nations Framework Convention on Climate Change (UNFCCC) member countries to report the national GHG inventory. Eq. (1) is used to calculate the CH4 emission from landfills. Similarly, for the environmental performance of waste-to-energy approach, different parameters such as emissions per tons, reduction in landfills, and energy production and social indicators such as employment were considered. For instance, Eq. (2) was used to determine the emissions from crude oil when used in electricity production. In the comparison of emissions from both scenarios, landfilling and waste-to-energy approach, the emissions produced from the transportation of waste were ignored. Such emissions include the GHG emission from the transportation of waste from the collection point to the recycling facility for which trucks are commonly used [49].

$$\mathbf{CH}\_4 = \left[ \left( \mathbf{MSW}\_{\text{(Land-III)}} \times \mathbf{MCF} \times \mathbf{DOC} \times \mathbf{DOC}\_{\text{f}} \times \mathbf{F} \times \left( \mathbf{16/12} \right) \cdot \mathbf{R} \right) \times \left( \mathbf{1-OX} \right) \right] \tag{1}$$

where CH4 = methane emission in Gg/year (1 Gg = 109 g; 1 Gg = 1000 ton), MSW(Land Fill) = total amount of MSW in the landfill in wet weight basis (Gg/year), MCF = CH4 correction factor—value used in the calculation = 0.6, DOC = the

**263**

*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

oxidation factor—value used in the calculation = 0.

of carbon dioxide to the carbon (=44 kg CO2/12 kg C) [9, 50].

plant as proposed in this research.

into 0.175 kg CO2 per kWh.

fraction of degradable organic carbon in MSW (Gg C/Gg MSW)—value used in the calculation = 0.2455, DOCf = the fraction of DOC that can decompose (fraction) value used in the calculation = 0.77, F = the fraction of CH4 in generated landfill gas—value used in the calculation = 0.5, R = the recovered CH4 (Gg/year), 16/12 is the molecular weight ratio CH4/C—value used in the calculation = 0, and OX = the

where *E* = CO2 emission per barrel (tons), *A* = the average heat content of the crude oil (=5.80 mmbtu per barrel; mmbtu = one million British Thermal Units), *B* = the average carbon coefficient of crude oil (=20.31 kg carbon per mmbtu), *C* = the fraction oxidized (=100% [48]), and *D* = the ratio of the molecular weight

Similarly, the electricity content and emissions from the MSW was established considering the existing literature. Different keywords such as "electricity content in MSW," "energy production from MSW," "waste-to-energy plant," and "emissions from energy to waste" were used in the main search engines. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were adhered to during the review process [51]. Different results associated with the electricity content and emissions from waste-to-energy plants were obtained from the systematic review. For instance, in the United States, there are 68 wasteto-energy power plants that produce about 14 billion kilowatt-hours (kWh) of electricity using 26.76 tons of combustible MSW [52]. In other words, the energy or electricity content per tons of MSW in the United States is approximately 586 kWh. The waste-to-energy plant installed in Qatar which has a capacity of 2300 tons per day produces 50 Mega Volt Amp (MVA) which is equal to 40,000 kWh per day [53]. Similarly, the statistics issued by Waste Management World indicates that electricity production from MSW can be up to 875 kWh per ton of MSW processed in a waste-to-energy plant [54]. The calculation presented in this chapter, however, considers a value of 586 kWh per MSW used in a waste-to-energy plant, keeping in mind that this value is from the United States which uses the same types of waste to

The total waste which is burned for energy recovery in the United States currently

stood at 12.70% of the total waste. Apart from producing energy, the burning of waste can reduce the volume of waste by 90%. Similarly, a recent waste-to-energy plant constructed in Ethiopia uses the same approach of burning waste to produce electricity. The collected waste is kept for 5 days to allow the moisture to seep out and then burning the waste at 1000°C to turn it to heat energy to run the steam turbine [55]. The latest and modern waste-to-energy plant can reduce the emissions (CO2) ranging from 100 to 350 kg CO2 equivalent per ton of the MSW used [56]. An average emission reduction value of 225 kg CO2 equivalent to per ton of MSW can be used to measure such reduction in emission; however, the Environmental Protection Agency (EPA) of the United States reveals that the burning of 1 ton MSW in a wasteto-energy plant results in 1 ton of less CO2 when compared to the common practice of landfilling [57]. The potential reduction in emissions between landfilling and wasteto-energy plants investigated by Wang et al. [58] in China noted that such reduction can be more than 1000 kg per ton. Similarly, the study conducted by Obermoser et al. [59] to establish a reliable CO2 value from waste-to-energy plant noted that CO2 emission can be in the range of 30–67 kg CO2 per Giga Joule which can be translated

*E AxBxC xD* = (2)

*Biotechnological Applications of Biomass*

**Number of samples per day (24 hours)**

**Type of entity**

Residential houses

Shopping markets

*MSW samples collection approach.*

**Table 1.**

the residents' willingness and participation was considered appropriate as there is evidence in the existing literature that similar studies were conducted with much smaller samples. For instance, Mason [45], in his research entitled "Sample Size and Saturation in Ph.D. Studies Using Qualitative Interviews," reported the result of 560 studies and noted that the most common size of the sample in these studies was 20. Similarly, Umar [46], while developing an integrated approach to promote sustainability in university campuses, used a sample of 20 respondents. Although the questionnaire used for this purpose was prepared in English, due to the diversity of the respondents, the interview process was deemed fit to the respondents. Overall, 45% of the residents in Oman are expatriates and the majority of them belong to some Asian countries [47]. The participants in the data collection were therefore interviewed in the local language so that there could be no communication barriers. The environmental performance of the current approach of MSW management was measured through the emissions produced by landfills. The Intergovernmental Panel on Climate Change (IPCC) 2006 model is used to calculate GHG emissions from landfills [48]. IPCC model is an international model used by The United Nations Framework Convention on Climate Change (UNFCCC) member countries to report the national GHG inventory. Eq. (1) is used to calculate the CH4 emission from landfills. Similarly, for the environmental performance of waste-to-energy approach, different parameters such as emissions per tons, reduction in landfills, and energy production and social indicators such as employment were considered. For instance, Eq. (2) was used to determine the emissions from crude oil when used in electricity production. In the comparison of emissions from both scenarios, landfilling and waste-to-energy approach, the emissions produced from the transportation of waste were ignored. Such emissions include the GHG emission from the transportation of waste from the collection point to the recycling facility for which

Restaurants 1 7 4 28

Hotels 1 7 2 14 Total: 34 238

**Number of days samples were collected**

1 7 25 (one sample from each houses

1 7 3 21

**Number of entitles used for sample collection/interview**

with family members of 2, 3, 4, 5, and 6)

**Total samples**

175

( ) ( ( ) ) ( ) CH = MSW ×MCF×DOC×DOC ×F× 16 /12 - R × 1-OX 4 f Land Fill (1)

MSW(Land Fill) = total amount of MSW in the landfill in wet weight basis (Gg/year), MCF = CH4 correction factor—value used in the calculation = 0.6, DOC = the

g; 1 Gg = 1000 ton),

where CH4 = methane emission in Gg/year (1 Gg = 109

**262**

trucks are commonly used [49].

fraction of degradable organic carbon in MSW (Gg C/Gg MSW)—value used in the calculation = 0.2455, DOCf = the fraction of DOC that can decompose (fraction) value used in the calculation = 0.77, F = the fraction of CH4 in generated landfill gas—value used in the calculation = 0.5, R = the recovered CH4 (Gg/year), 16/12 is the molecular weight ratio CH4/C—value used in the calculation = 0, and OX = the oxidation factor—value used in the calculation = 0.

$$E = A \propto B \propto C \propto D \tag{2}$$

where *E* = CO2 emission per barrel (tons), *A* = the average heat content of the crude oil (=5.80 mmbtu per barrel; mmbtu = one million British Thermal Units), *B* = the average carbon coefficient of crude oil (=20.31 kg carbon per mmbtu), *C* = the fraction oxidized (=100% [48]), and *D* = the ratio of the molecular weight of carbon dioxide to the carbon (=44 kg CO2/12 kg C) [9, 50].

Similarly, the electricity content and emissions from the MSW was established considering the existing literature. Different keywords such as "electricity content in MSW," "energy production from MSW," "waste-to-energy plant," and "emissions from energy to waste" were used in the main search engines. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were adhered to during the review process [51]. Different results associated with the electricity content and emissions from waste-to-energy plants were obtained from the systematic review. For instance, in the United States, there are 68 wasteto-energy power plants that produce about 14 billion kilowatt-hours (kWh) of electricity using 26.76 tons of combustible MSW [52]. In other words, the energy or electricity content per tons of MSW in the United States is approximately 586 kWh. The waste-to-energy plant installed in Qatar which has a capacity of 2300 tons per day produces 50 Mega Volt Amp (MVA) which is equal to 40,000 kWh per day [53]. Similarly, the statistics issued by Waste Management World indicates that electricity production from MSW can be up to 875 kWh per ton of MSW processed in a waste-to-energy plant [54]. The calculation presented in this chapter, however, considers a value of 586 kWh per MSW used in a waste-to-energy plant, keeping in mind that this value is from the United States which uses the same types of waste to plant as proposed in this research.

The total waste which is burned for energy recovery in the United States currently stood at 12.70% of the total waste. Apart from producing energy, the burning of waste can reduce the volume of waste by 90%. Similarly, a recent waste-to-energy plant constructed in Ethiopia uses the same approach of burning waste to produce electricity. The collected waste is kept for 5 days to allow the moisture to seep out and then burning the waste at 1000°C to turn it to heat energy to run the steam turbine [55]. The latest and modern waste-to-energy plant can reduce the emissions (CO2) ranging from 100 to 350 kg CO2 equivalent per ton of the MSW used [56]. An average emission reduction value of 225 kg CO2 equivalent to per ton of MSW can be used to measure such reduction in emission; however, the Environmental Protection Agency (EPA) of the United States reveals that the burning of 1 ton MSW in a wasteto-energy plant results in 1 ton of less CO2 when compared to the common practice of landfilling [57]. The potential reduction in emissions between landfilling and wasteto-energy plants investigated by Wang et al. [58] in China noted that such reduction can be more than 1000 kg per ton. Similarly, the study conducted by Obermoser et al. [59] to establish a reliable CO2 value from waste-to-energy plant noted that CO2 emission can be in the range of 30–67 kg CO2 per Giga Joule which can be translated into 0.175 kg CO2 per kWh.

The next section describes the results and analysis made from the data collected in Section 3.

## **4. Results and analysis**

Considering the different aspects of the results and analysis, this section is divided into different subsections. The first subsection describes the results and analysis of the MSW composition and the public participation in the MSW segregation.

#### **4.1 MSW composition and public willingness**

As noted in Section 3, a total of 175 samples were collected from the residential houses. These samples were used to determine the MSW generation per capita. The results show that the mean weight of the MSW samples was 1.3 ± 0.28 kg/per capita. Currently, as of May 2020, the total Oman population stands at 4,613,726, which can be translated into a total of 5998 tons MSW generation per day in Oman [60]. Similarly, the whole samples collected from the residential houses, restaurants, shopping markets, and hotels were used to determine the MSW composition in Oman. This composition is reported in **Figure 6**. Overall, the composition of the MSW represents a good percentage of waste that can be combustible and suitable to be used in a waste-to-energy plant to produce electricity.

During the MSW sample collection process, the inhabitants were asked about their cooperation and participation in the waste segregation activities. The willingness of the residents was considered important as this may be helpful to transfer only the MSW that is suitable to be used in the waste-to-energy plant. In other words, when the residents will segregate the waste at their own, the process at the waste-to-energy plant will become more straightforward as it will receive only the waste which could be used in the plant. A total of 34, consisting of 67.64% male and 32.35% female face-to-face interviews were conducted during this stage. All the participants appraised the idea of using MSW for electricity generation. A large number of the interviewees (70.58%) agreed that they are willing to participate in the segregation of the MSW at their doorsteps. The remaining participants did not answer as no but they were somehow not sure how they can do such segregation.

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*A Comparative Study of MSW to Emery in Oman DOI: http://dx.doi.org/10.5772/intechopen.93745*

scenario.

**4.2 Emissions from MSW**

year CO2 equivalent per ton of MSW.

**4.3 Electricity production and emissions**

oil and gas are therefore calculated as follows:

kg = **123.414 million tons CO2 per year.**

kg = **38.367 million tons CO2 per year.**

Emissions for 29.31 kWh from oil = 73.16 kg CO2.

Emissions for 29.31 kWh from gas = 53.07 kg CO2.

Emission for 49,443.35 million kWh = 49,443.35 73.16

Emission for 21,190.01 million kWh = 21,190.01 53.07

million kWh per year.

million kWh per year.

sort of training and tools to do such tasks in their homes.

Overall, the majority of the respondents (79.94%) noted that they required some

The next section outlines the emission from MSW considering the landfilling

To calculate the emissions from MSW using Eq. (1), DOC for different waste

materials was obtained from the IPCC and the Atmospheric Brown Clouds Emission Inventory Manual (ABC EIM). Based on these two documents, the DOC paper = 0.25, DOC food = 0.4, DOC textile = 0.25, and the DOC rubber = 0.39 were considered. The average DOC value was calculated based on the above values and waste fraction as shown in **Figure 6**. The final DOC value used in the calculation, therefore, stands at 0.2455. The total MSW waste considered in this calculation was equal to 2,159,219 tons per year or 2159 Gg per year. This MSW produces a total of 163,060 Gg/year CH4 which is equal to 3,424,247 tons/year CO2 equivalent. This can be translated into the emissions produced 1 ton, which can be equal to 1.58 ton per

The next section describes the electricity consumption, production, and

In terms of electricity production, Oman is using both oil and gas to meet its electricity requirement. As noted in **Figure 3**, the current consumption of electricity per capita in Oman is 15,309.4 kWh per year that can be translated into total energy consumption by multiplying this figure with the total population of Oman (15,309.4 × 4,613,726), which gives a total consumption of 70,633.37 million kWh per year. To calculate the emissions from electricity production through oil and gas, 70% of the electricity production is considered to be from oil, and 30% is considered to be from natural gas. These percentages were taken from the study conducted by the Authority of Electricity Regulation in Oman [61]. The EIA guidelines were used to establish the emissions both from oil and gas when used for electricity production. As per these guidelines, to produce 1 million British thermal units (btu) energy which is equal to 29.31 kWh from oil, a total of 161.30 pounds (=73.16 kg) of CO2 is produced. Similarly, if the same amount of energy is produced from gas, then the total emissions will be equal to 117.0 pounds (53.07 kg). The emissions from electricity production in Oman considering both

**Emissions from oil:** Electricity produced from oil = total electricity consumption × percentage produced from oil = 70,633.37 million kWh × 70% = 49,443.35

**Emission from gas:** Electricity produced from oil = total electricity consumption × percentage produced from oil = 70,633.37 million kWh × 30% = 21,190.01

29.31 *x*

29.31

= 1.234 × 1011

*<sup>x</sup>* = 3.836 × 1010

emissions produced by such consumption and production.

**Figure 6.** *Composition of MSW in Oman.*

Overall, the majority of the respondents (79.94%) noted that they required some sort of training and tools to do such tasks in their homes.

The next section outlines the emission from MSW considering the landfilling scenario.


4. Conclusion

This chapter explained the conventional voltage regulation schemes used in smart grids with inverter-based DGs and PEVs. High penetration levels of PEVs and DGs may lead to negative impacts on the conventional voltage control devices such as tap-changing transformers and capacitor banks. The main reason behind these negative impacts is the stochastic power profiles of PEVs and renewable-based DGs that stimulate chronological overvoltage and undervoltage and make load forecasting erroneous. In the literature, there are two approaches to mitigating the voltage


*3.1.2 58S bioglass*

Ceramic 58S bioactive glass is a great bioactive, biodegradable glass with the capability of bone bonding. This bioactive glass, having 33% calcium oxide, 58% silicon dioxide 9% phosphorus pentoxide, is able to receive specific attention as scaffold substance [94–96]. The reaction of 58S bioactive glass with physiological fluids occurs after implantation quickly and makes bond to the tissue of bone. This

**Figure 11.** *The typical surface structure of 45S5 bioglass coatings sprayed [90].*

happens without inflammatory, toxicity and foreign-body reaction. The fast ionic dissolution as well as the hydroxyl-carbonated apatite layer formation was seen after the rapid in-vivo surface reactions. With the release of calcium, silicon and phosphorous ions, the gene expression and the proliferation of osteoblast happens to form the bone quickly. This produced hydroxyapatite layer was as the bioactivity evidence of prepared bioglass, which both X-ray diffraction and scanning electron microscope images can confirm.


**Abbreviations**

The following abbreviations are used in this manuscript:

#### ISPRS International Society for Photogrammetry and Remote Sensing

## **Appendix A**

**Table A1.** Experiment Environment.


**2.4.1 Flow-rate**

The flow-rate has a significant effect on the jet diameter and stability of the jet in cone-jet transition. It is the main parameters to control the jet diameter for the patterning process. The flow-rate also affects the applied potential requirement for development of cone-jet (operating envelop) and the resulting the shape of the cone-jet. In electrohydrodynamic jetting, flow-rate also affect the stability of the jet, at low flow-rate the jet is stable, whereas the high flow-rate in cone-jet region destabilize the jet resulting in shorter jet length. This is due to amount of charge carrying at high flow-rate which destabilizes the jet. The typical effects of the flow-rate on stable cone-jet mode are shown in figure 3.

Fig. 3. Effect of flow rate on the cone-jet transition, as shown the jet diameter increases with increase in flow-rate. The red arrow indicates the jet break-up point.

#### **2.4.2 Electric field (applied voltage)**

Electric field affects the morphology of the cone, by increasing the electric field strength in steady cone-jet mode, the cone-jet recedes towards the nozzle. However, there is less effect on the jet diameter by increasing the applied voltage. At relatively low flow-rate and high electric field, the jet disintegrated into mist of small droplets also known as electrospray atomization, this behavior is used for the thin film deposition of functional material. The typical shape of the come at different applied voltage is shown in figure 4.


Sum of Glucose and Fructose

The determination of reducing sugars (the sum of glucose and fructose) in honey is also a quality criterion used to indicate honey freshness. Of the total number of nonconforming samples (n = 276), 113 (40.9%) did not meet the UAE criterion for acceptable total sugar content. While all 20 forest honey samples met the UAE standard, blended honey, honeycomb and acacia honey did not. Honey showed the highest percentage of non-conformities at 40.2%. The mean total reducing sugar content of these samples was 52.5%, with a range of 19.6 to 59.1%. An amount of fructose and glucose below 60% is taken to indicate honey adulteration. It should be noted that the ratio of fructose to glucose in any particular honey depends largely on the source of the nectar [37]. The mean total glucose and fructose content obtained in the present study for non-conforming honey samples at 52.5% was similar to the 54.3% obtained for 29 samples of Sidr honey collected from Oman. The acceptable total glucose and fructose content as per GSO honey standards is a minimum of 45% [6]; however, the UAE legislation is more strict and accepts a minimum value of only 60%.

The sugar composition results found during the current study are not in accordance with the values reported in a study by Geană, Ciucure, Costinel, and Ionete (2020) [40] where the total amount of fructose and glucose in 48 honey samples that originated in Romania was higher than the 60% specified in the EU standards [4]. Another study conducted in Turkey showed that the mean combined glucose and fructose content of 68 honey samples ranged from 62.6 to 77.3%, with a mean concentration of 71.0% [26].


**Author details**

Lisa R. Warner, Olga Mass, Nancy Donnelly Lenn, Briana R. Grantham and Julia Thom Oxford\* Biomolecular Research Center, Boise State University, Boise, Idaho, USA

\*Address all correspondence to<EMAIL_ADDRESS>
© 2018 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, provided the original work is properly cited.


**1. Introduction**

Interest in renewable energy sources has increased considerably, mainly due to concerns related to the climate change caused by the atmospheric accumulation of greenhouse gases resulting from fossil fuel use [1]. A promising alternative to the fossil fuels used in the transportation sector is the production of biofuels—e.g., biodiesel, green diesel, and biokerosene—from renewable feedstocks, including vegetable oils and animal fats [2,3]. Moreover, to improve the economics of these biofuels and avoid disrupting the food supply, attention has shifted to low-cost inedible feedstocks, including used cooking oil (UCO), which is also known as yellow grease (YG) [4–6]. This particular waste stream is both abundant and inexpensive (~\$463/ton), with ca. one million tons being produced annually in the U.S. alone [7].

Of the biofuels mentioned above, biodiesel is the name given to the fatty acid methyl esters (FAMEs) resulting from the catalytic transesterification of fat, oil, or greases (FOG) with methanol. Biodiesel has several advantages over petroleum-based diesel, such as being biodegradable and producing less harmful gas emissions and particulate matter upon combustion [8,9]; however, it also displays several drawbacks, including poor cold flow properties as well as relatively low thermal and oxidative stability, mostly arising from its oxygen content [10]. The catalytic deoxygenation of FOG to fuel-like hydrocarbons o ffers advantages over biodiesel in terms of fuel quality and feedstock flexibility. Indeed, deoxygenation processes are able to handle FOG feeds with significantly higher free fatty acid concentrations relative to those typically required for biodiesel synthesis [11].

As shown in Scheme 1, FOG deoxygenation can proceed via hydrodeoxygenation (HDO) and decarboxylation/decarbonylation (deCOx). In HDO, oxygen is removed as H2O, and the alkanes produced have the same number of carbon atoms as the corresponding fatty acid chains comprising the FOG. In decarboxylation, oxygen is removed in the form of CO2, and in decarbonylation, oxygen is removed as H2O and CO. In both cases, the resulting alkanes have one carbon atom less than the corresponding fatty acid bound in the triglyceride. Depending on the catalyst and the experimental conditions employed, the CO and CO2 produced in the gas phase may react with hydrogen to form CH4. In fact, because of the number of confounding reactions, which include not only methanation but also the water gas shift (WGS) and the Boudouard reaction, these routes cannot be easily distinguished from each other based solely on the amounts of H2O, CO2, and CO produced [12,13].

**Scheme 1.** Deoxygenation routes for tristearin as a model compound representing triglycerides (blue shading) and concomitant reactions confounding oxygen-bearing deoxygenation products (red shading).

In recent years, the production of fuel-like hydrocarbons via deCOx has been intensively investigated as a way to avoid the large amounts and pressures of hydrogen, as well as the problematic sulfide catalysts required by HDO, since the hydrogen requirements of deCOx are lower and these reactions proceed over simple supported metal catalysts [14]. Although the majority of deCOx studies have focused on Pd and Pt catalysts, the high price of these metals has spurred the search for alternatives. Saliently, inexpensive Ni-based catalysts can provide comparable results to Pd and Pt formulations in the deCOx of FOG to hydrocarbons [15,16].

Since the high activity of Ni in C–C hydrogenolysis can decrease the carbon yield and the hydrogen e fficiency of deCOx processes, the incorporation of a second metal has been investigated as a means to modify the electronic and geometric properties of Ni to ultimately improve its activity and selectivity [17]. Indeed, Ni/Al2O3 promoted with Cu or Pt can a fford near quantitative diesel yields in the conversion of both model and realistic lipid feeds to fuel-like hydrocarbons [13,18]. The promotion effect displayed by these bimetallic catalysts is in large part attributed to the ability of Cu and Pt to facilitate NiO reduction at relatively low temperatures since metallic Ni sites constitute the active site for the deCOx reaction. Moreover, Pt addition also curbs the adsorption of CO on the catalyst surface, helping to avoid catalyst inhibition by any CO evolved via decarbonylation and the catalyst coking resulting from the disproportionation of CO via the Boudouard reaction [13].

Supported Ni catalysts promoted with Fe have also a fforded promising results in the conversion of model and realistic lipid feeds to hydrocarbons [17], the promoting e ffect of Fe being attributed to the synergy between nickel sites possessing the ability to activate hydrogen and iron sites with strong oxophilicity [17,19]. Indeed, since Fe has a higher oxygen a ffinity than Ni, oxygen vacancies within iron oxide species can facilitate the adsorption and subsequent activation of oxygenates. Specifically, H2 activated through its facile dissociative adsorption on Ni sites can spill over to neighboring Fe sites onto which the oxygen atoms of C=O groups are adsorbed, subsequent hydrogenation leading to deoxygenation products. In addition, the formation of Ni-Fe alloys with Fe-rich surfaces disrupts the adjacency of Ni atoms, a geometric e ffect known to suppress C–C hydrogenolysis, which requires Ni ensembles. Cu is also known to decrease the C–C hydrogenolysis activity of Ni through the same geometric e ffect [20].

In order to develop practicable catalytic deCOx technology for the conversion of FOG to fuel-like hydrocarbons, it is necessary to study the most promising catalysts using industrially relevant feeds and reaction conditions. In addition, in order to make meaningful comparisons between the performance of di fferent catalysts, measurements must be made at a steady state. Against this backdrop, the present work investigated the conversion of UCO to renewable diesel via deCOx over supported Ni catalysts promoted with Cu, Fe or Pt. The performance of these formulations was tested in a fixed bed reactor using industrially-relevant reaction conditions for 76 h of time on stream (TOS), as previous work has shown that catalysts of this type require >48 h of TOS to attain a steady state [11]. In addition, the analysis of the fresh, spent, and regenerated catalysts was undertaken in an e ffort to understand the distinct performance displayed by these formulations.


**7. Future prospects for nanopharmaceuticals delivery**

Another targeted approach to the brain for delivering drugs is through the ocular route. The ocular route has so many advantages like reduced peripheral toxicity and

**131**

provided the original work is properly cited.

*Nanopharmaceuticals: A Boon to the Brain-Targeted Drug Delivery*

direct delivery of therapeutic moiety in the target site [76]. Ocular and intranasal drug delivery for the brain was compared by a group, in which nerve growth factor (NGF) was used for treating Alzheimer's disease. However, it was found out that intranasal drug administration was more effective and potent for brain disorders and ocular route did not perform well. However, many scientists are working for making the ocular route a success because of it being the compliant and non-invasive route [77]. There has been a huge room for the administration of nanocarrier through ocular route to the brain. Nanocarrier can facilitate drug delivery to the brain because of their size, site-retention properties and enhanced adhesion to the lacrimal fluid. The route can be exploited for the delivery of drugs and genes to CNS by avoiding

Brain-targeted drug delivery is a difficult matter due to anatomic and pathophysiological brain barriers. The current advances in nanotechnology provide a solution in the form of nanopharmaceuticals, drug containing nanocarriers, to cross the CNS barriers and to target the brain tissue in various disorders.

Nanopharmaceuticals' mode of administration into the body is an important aspect, which ultimately effects drug concentration in the brain and drug therapeutic effect. Current chapter highlighted the routes of administration through which nanopharmaceuticals can be delivered to reach the brain. Every route has pros and cons, nanopharmaceuticals overcome the route associated limitations in the delivery of drug to the brain due to their peculiar physicochemical properties and surface modulation. Translation this research area into the clinic still require investigations, as safety is the foremost concern and distribution to other body organs must be eradicated. Moreover, there is a need to control the drug delivery rate when

*DOI: http://dx.doi.org/10.5772/intechopen.83040*

systemic exposure via nanopharmaceuticals [78].

nanopharmaceuticals reach the brain for safer action.

The authors declared no conflict of interest.

\*Address all correspondence to<EMAIL_ADDRESS>
**8. Conclusion**

**Conflict of interest**

**Author details**

© 2019 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,

Mahira Zeeshan, Mahwash Mukhtar, Qurat Ul Ain, Salman Khan and Hussain Ali\*

Department of Pharmacy, Quaid-i-Azam University, Islamabad, Pakistan

*Nanopharmaceuticals: A Boon to the Brain-Targeted Drug Delivery DOI: http://dx.doi.org/10.5772/intechopen.83040*

direct delivery of therapeutic moiety in the target site [76]. Ocular and intranasal drug delivery for the brain was compared by a group, in which nerve growth factor (NGF) was used for treating Alzheimer's disease. However, it was found out that intranasal drug administration was more effective and potent for brain disorders and ocular route did not perform well. However, many scientists are working for making the ocular route a success because of it being the compliant and non-invasive route [77]. There has been a huge room for the administration of nanocarrier through ocular route to the brain. Nanocarrier can facilitate drug delivery to the brain because of their size, site-retention properties and enhanced adhesion to the lacrimal fluid. The route can be exploited for the delivery of drugs and genes to CNS by avoiding systemic exposure via nanopharmaceuticals [78].


*3.3. Distribution of Publications by Countries*

If the results obtained are analyzed by country, a total of 159 countries have published on this topic. Figure 4 shows the countries that have published on the subject and the intensity with which they published has been shown. It is observed that China and India stand out over the rest of the countries with more than 10,000 publications, perhaps influenced by traditional medicine, although their most cited works are related to antioxidant activity, both for China [45], and for India [46,47], and in this last country also antidiabetic potential [4]. The third place is the USA followed by Brazil, both with more than 5000 publications. The most frequently cited publications from these countries focus on antioxidant activity [48], and antimicrobial activity [49] for the USA and anti-inflammatory activity for Brazil [50,51].

As mentioned, the list of countries is very long, but those with more than 2000 publications are included: Japan, South Korea, Germany, Iran, United Kingdom, Pakistan, Italy, and France. If the overall results obtained are analyzed in their evolution by years, for this list of countries with more than 2000 publications, Figure 5 is obtained. From this point onwards, three groups of countries can be identified.

**Figure 4.** Worldwide research on medical plants.

**Figure 5.** Temporal evolution on medical plants publications for Top 12 countries.

The first group is the leaders of this research, China and India, with between 800 and 1100 publications per year. China led the research from 1996 to 2010, and from this year to 2016, the leader was India, after which it returned to China. The second group of five countries is formed in order in the last year of the study: Iran, Brazil, USA, South Korea and Pakistan. This group of countries has a sustained growth over time, with a rate of publications between 200 and 400 per year. It should be noted that Brazil led the third place for a decade, from 2007 to 2016, since then that position is for Iran. The third group of five countries is made up of: Japan, Germany, United Kingdom, Italy, and France. They are keeping the publications around 100 a year, with an upward trend, but at a very slight rate.

If the analysis of the publications by country is made according to the categories in which they publish, Figure 6 is obtained, which shows the relative effort between the different themes or categories is shown. At first look, it might seem that they have a similar distribution. However, in relative terms the category of Pharmacology, Toxicology and Pharmaceutics is led by Brazil with 35% of its own publications followed by India with 33%. For the Medicine category, in relative terms it is led by China with 29 %, followed by Germany with 27 %. The category of Biochemistry, Genetics and Molecular

Biology always takes second or third place for this ranking of countries, standing out especially for Japan and South Korea with 23% and for France with 22%. The fourth category for many countries is Agricultural and Biological Sciences, with Pakistan standing out with 20%, followed by Italy with 16%. The category of Chemistry occupies the fourth category for countries such as Japan with 20% or Iran with 14%. The other categories: Chemical Engineering, Immunology and Microbiology, Environmental Science, Multidisciplinary, or Engineering, are below 5 % in all countries.

**Figure 6.** Distribution by scientific categories according to countries.

According to these results, it can be seen the relative lack of relevance of the category of Agricultural and Biological Sciences for medicinal plants, compared to the categories of Pharmacology, Toxicology and Pharmaceutics, Medicine, or Biochemistry, Genetics and Molecular Biology.