Future Green Energy: A Global Analysis

The main problem confronting the world is human-caused climate change, which is intrinsically linked to the need for energy both now and in the future. Renewable (green) energy has been proposed as a future solution, and many renewable energy technologies have been developed for different purposes. However, progress toward net zero carbon emissions by 2050 and the role of renewable energy in 2050 are not well known. This paper reviews different renewable energy technologies developed by different researchers and their potential and challenges to date, and it derives lessons for world and especially African policymakers. According to recent research results, the mean global capabilities for solar, wind, biogas, geothermal, hydrogen, and ocean power are 325 W, 900 W, 300 W, 434 W, 150 W, and 2.75 MWh, respectively, and their capacities for generating electricity are 1.5 KWh, 1182.5 KWh, 1.7 KWh, 1.5 KWh, 1.55 KWh, and 3.6 MWh, respectively. Securing global energy leads to strong hope for meeting the Sustainable Development Goals (SDGs), such as those for hunger, health, education, gender equality, climate change, and sustainable development. Therefore, renewable energy can be a considerable contributor to future fuels

Driving Cycles for Estimating Vehicle Emission Levels and Energy Consumption

Standard driving cycles (DCs) and real driving emissions (RDE) legislation developed by the European Commission contains significant gaps with regard to quantifying local area vehicle emission levels and fuel consumption (FC). The aim of this paper was to review local DCs for estimating emission levels and FC under laboratory and real-world conditions. This review article has three sections. First, the detailed steps and methodologies applied during the development of these DCs are examined to highlight weaknesses. Next, a comparison is presented of various recent local DCs using the Worldwide Harmonized Light-Duty Test Cycle (WLTC) and FTP75 (Federal Test Procedure) in terms of the main characteristic parameters. Finally, the gap between RDE with laboratory-based and real-world emissions is discussed. The use of a large sample of real data to develop a typical DC for the local area could better reflect vehicle driving patterns on actual roads and offer a better estimation of emissions and consumed energy. The main issue found with most of the local DCs reviewed was a small data sample collected from a small number of vehicles during a short period of time, the lack of separate phases for driving conditions, and the shifting strategy adopted with the chassis dynamometer. On-road emissions measured by the portable emissions measurement system (PEMS) were higher than the laboratory-based measurements. Driving situation outside the boundary conditions of RDE shows higher emissions due to cold temperatures, road grade, similar shares of route, drivers’ dynamic driving conditions, and uncertainty within the PEMS and RDE analysis tools

Assessment of knowledge, attitude and practices (KAP) of farmers about transmission of zoonotic diseases in Ada'a district, Oromia, Ethiopia

In developing countries like Ethiopia, zoonotic diseases pose a significant health and economic burden, with high exposure of farmers to zoonotic infection given the prevailing traditional husbandry practices. A cross-sectional survey involving 388 farmers in the Ada'a district central Ethiopia was conducted to investigate their knowledge, attitudes, and practices (KAP) regarding the transmission of zoonotic diseases. The respondents' mean age was 41.0 +/- 10.0 SD years. The majority of respondents (39.4%) were between the ages of 41 and 50, and 90.0% were married. Farmers claimed that conversations with family, colleagues, and friends were the primary sources of zoonoses information. Farmers stated that the primary sources of information on zoonotic diseases as community. They had a relatively low level (66.8%) of knowledge on zoonotic diseases and half of them (54.9%) did not have good information on zoonoses. Three-quarters (75.2%) of the farmers reported that they neither consume meat and milk nor use offal and hide/skin from sick or dead animals. Similarly, 71.1% of them stated that they do not eat meat from regularly aborting sheep/goats, and never consume raw meat and milk. Most of the respondents correctly answered that raw meat (82.7%) and raw milk (79.9%) are means of disease transmission from animals to humans. However, considerable proportions of them were unaware of zoonotic transmission of bovine tuberculosis (61.3%) and brucellosis (74.7%) transmission through raw milk intakes, and risk of taeniasis (71%) due to raw meat consumption. But, considerable proportions had never dewormed (48.7%), or tested their animals for brucellosis (82.7%) and bovine tuberculosis (83.3%), and more than three quarters (77.3%) did not used personal protective equipment when handling sick animals. Farmers who had a secondary education or above (OR = 6.8, CI = 2.4-18.0, p = 0.004), aged between 41 and 50 years (OR = 3.0, 95% CI: 1.2-7.2, p = 0.015), and those having good knowledge (OR = 2.1, CI = 1.3-3.5, p = 0.002), and positive attitude related to zoonotic diseases (OR = 7.8, CI = 4.7-12.9, p < 0.001) had better practices that reduce the risk of exposure to zoonotic infections than their counterparts. This study revealed a knowledge gaps, a low level of the desired attitude, and high -risk behavioral practices which call for awareness creation about zoonotic disease transmission

Hybridized Renewable Energy for Smart Vehicle-to-Grid (V2G) Systems

Wind and sunlight are increasingly being exploited as energy supplies that never run out. Additionally, renewable energy resources, including sun, wind, and geothermal heat, are being used for different technologies. It was considered the use of hybridized wind-solar energy resources in smart vehicle technology. A thorough understanding of an integrated framework of the hybridized renewable energy for smart vehicle-to-grid (V2G) systems is essential and required to further identify and perhaps maximize existing opportunities. Aiming to develop a vehicle-to-grid (V2G) system where the smart vehicle runs on stored sunshine and wind energy, and vehicle batteries store energy and release it to the electricity grid in peak demand periods. To achieve this aim, mathematical models for solar and wind systems were created and entire 24-h simulations were run for case studies of three smart vehicles, which were assessed for different scenarios and circumstances, using the MATLAB/SIMULINK environment. The estimated values obtained were home load 10 MW, power factor 0.15 MVA, industrial load 0.16 MVA, and smart car-to-grid, solar panel farm, and wind farm power of 4 MW, 8 MW, and 4.5 MW, respectively. Therefore, the hybridized wind-solar energy sources were applicable for all three smart vehicles considered

Performance prediction of a pump as a turbine using energy loss analysis

As interest in renewable energy sources grows, interest in small-scale hydropower development and utilization increases. The development of micro- and small-scale hydropower plants is challenging, mainly due to the high cost of hydraulic turbines. If the turbine mode performance can be predicted accurately before installation, pumps as turbines (PATs) are an excellent alternative for small-scale hydropower generation. In this study, a theoretical procedure using a detailed energy loss analysis to determine PAT's energy losses is developed, and a non-dimensional performance prediction model is presented. The models were implemented to determine the pressure, head, torque, power, and efficiency across a wide range of flow rates. This work clearly characterizes the effects of individual losses, thereby acknowledging their influence. The prediction results were tested at ten different flow rates, ranging from 50 % to 180 %. The model result was validated through experiments using a hydro-pump test rig developed at the Bahir Dar Institute of Technology at Bahir Dar University. The numerical and model results have good agreement with the experimental results. at BEP The experimental result gives a 1.6 flow rate, 1.72 head ratios, and an efficiency of 76.53 %, 78.09 %, and 74.04 % using analytical, numerical, and experimental methods, respectively. The PAT off-design efficiency decreases sharply below BEP and smoothly above BEP. At BEP, the CFD and analytical results deviated by -2.04 % and 3.08 %, respectively, from the experimental results. Further, the detailed energy loss analysis revealed that the volute frictional (12.1 %), the throat frictional (11.9 %), the inlet pipe frictional (11.2 %), the impeller frictional (9.4 %), and the volute diffusion (8.9 %) losses take the major energy losses sequentially. This provides full insight for applying performance optimization measures

Optimizing the performance of a wheeled mobile robots for use in agriculture using a linear-quadratic regulator

Use of wheeled mobile robot systems could be crucial in addressing some of the future issues facing agriculture. However, robot systems on wheels are currently unstable and require a control mechanism to increase stability, resulting in much research requirement to develop an appropriate controller algorithm for wheeled mobile robot systems. Proportional, integral, derivative (PID) controllers are currently widely used for this purpose, but the PID approach is frequently inappropriate due to disruptions or fluctuations in parameters. Other control approaches, such as linear-quadratic regulator (LQR) control, can be used to address some of the issues associated with PID controllers. In this study, a kinematic model of a four-wheel skid-steering mobile robot was developed to test the functionality of LQR control. Three scenarios (control cheap, non -zero state expensive; control expensive, non -zero state cheap; only non -zero state expensive) were examined using the characteristics of the wheeled mobile robot. Peak time, settling time, and rising time for cheap control based on these scenarios was found to be 0.1 s, 7.82 s, and 4.39 s, respectively

Knowledge, Attitude and Practice Towards Exclusive Breast Feeding Among Inhabitants of Ginjo Guduru Kebele, Jimma Town, Oromia Region, Ethiopia

Appropriate feeding practices are fundamental importance for the survival, growth, development and health of the infant and young children. However; exclusive breastfeeding remains a challenge because of many factors. It was suggested that mother's knowledge, attitude and practice determines the effectiveness of exclusive breastfeeding. This research is a cross-sectional study aimed to assesses mother's knowledge, attitude and practice towards optimal breastfeeding among Ginjo Guduru kebele. The survey was conducted from June 29-July30, 2018, from a total of 315 mothers who had children under one (1) year age, 190 mothers were selected using simple random sampling. Structured pre-tested questionnaires, as well as the in-depth interview, was used to collect the data on the socio-economic, demographic characteristics, knowledge attitude and practice towards exclusive breastfeeding. Among mothers studied about 73.94% had good knowledge of effective breastfeeding, 63.99% of mothers had a positive attitude on effective breastfeeding, and 69.69% had a good practice of effective breastfeeding. About 24.06% of mothers had poor knowledge of effective breastfeeding, approximately 36.11% of mothers had a poor level of attitude on effective breastfeeding, and about 31.31% of mothers had a poor practice of effective breastfeeding. Health service delivery staffs Policymakers, administrators and Non-governmental organisation collaborates to draw strategies to enhance the awareness of mothers about effective breastfeeding

Analysis of the concentration of heavy metals in soil, vegetables and water around the bole Lemi industry park, Ethiopia

Irrigation water contaminated with industrial waste could pollute the soil and vegetables with heavy metals. The objective of this study was to analyze the concentration of heavy metals in soil and vegetables after irrigation practices with wastewater emanating from industrial parks. 24 samples were collected from 8 sampling stations for vegetable, soil and water samples separately, following APHA procedures. Samples were collected using a composite sampling method in May and June 2021. Water samples were collected using clean polyethylene plastic bottles while soil and vegetables were sampled using clean plastic bags. Analysis was done for heavy metal concentrations such as Pb, Cr, Cd, and Zn for each sample using descriptive statistics of changes in concentrations, one-way analysis of variance (ANOVA), Principal Component Analysis and Pearson Correlation Coefficient. The mean concentration of heavy metals in soil, vegetables, and water samples was analyzed. Unlike the rest of the heavy metal concentrations, the result showed the highest levels for Zn, i.e., 7.82 mg/kg and 5.12 mg/kg for vegetables and soil samples, respectively. The maximum value of the bioconcentration factor (BCF), the highest value of Estimated Daily Intake (EDI), and the maximum Target Cancer Risk (TCR) value recorded were 19.39, 0.001, and 8.09 x 10(-5) for Cd, Zn, and Cr, respectively. But, Hazard Index (HI) indicated no potential health effects. On the other hand, the concentration of heavy metals in the soil sample showed that Cr and Cd were strongly positively correlated with the concentration of Pb in vegetables during May. Cd concentration in the water sample was also strongly positively correlated with the concentration of Pb during May. The application of proper management for the reduction of contaminants, and suitable irrigation methods with treated wastewater is essential. The study can provide a basis for the City Administration of Addis Ababa to properly protect the water quality of rivers and provide a reference for river management around the industry parks across the country

An experimental assessment of simultaneous reduction in vehicle tailpipe emissions employing desirability function analysis

In vehicles powered by fuel, the effort to minimize CO and HC emissions through various strategies leads to an increase in CO2, contributing to global warming. This study aimed to experimentally assess the simultaneous reduction of vehicle tailpipe emissions of CO, HC, and CO2 using desirability function analysis (DFA). On predetermined routes in Addis Ababa city, two vehicles were tested for on-road emissions at five various speeds and on five various road slopes using a portable emissions tester. Surface plots were used to display how the tailpipe emissions of CO2, CO, and HC vary with changes in vehicle speed and road gradient. The DFA results revealed that the optimal speed for simultaneous reduction of CO, HC, and CO2 emissions was 40 km/h on a flat route and 30 km/h on a 2-degree uphill, with composite desirability of 0.83 and 0.72, respectively. This study found that a speed of 30 km/h on a flat road increased CO2 by 2.82%, CO by 18.97%, and HC by 5.28% compared to an optimized vehicle speed of 40 km/h. On a 2-degree gradient, a vehicle traveling at 20 km/h exhibited a 4% increase in CO2 emissions, a 23.92% increase in CO emissions, and a 1.26% decrease in HC emissions compared to the optimized speed of 30 km/h. Adjusting speed limits according to road gradients is recommended to minimize vehicle tailpipe emissions simultaneously using DFA. This approach contributes to lowering air pollution by reducing pollutant emissions from vehicles through optimized speeds

Utilizing an Internet of Things (IoT) Device, Intelligent Control Design, and Simulation for an Agricultural System

In an agricultural system, finding suitable watering, pesticides, and soil content to provide the right nutrients for the right plant remains challenging. Plants cannot speak and cannot ask for the food they require. These problems can be addressed by applying intelligent (fuzzy logic) controllers to IoT devices in order to enhance communication between crops, ground mobile robots, aerial robots, and the entire farm system. The application of fuzzy logic in agriculture is a promising technology that can be used to optimize crop yields and reduce water usage. It was developed based on language and the air properties in agricultural fields. The entire system was simulated in the MATLAB/SIMULINK environment with Cisco Packet Tracer integration. The inputs for the system were soil moisture sensors, temperature sensors, and humidity sensors, and the outputs were pump flow, valve opening, water level, and moisture in the sounding. The obtained results were the output of the valve opening, moisture in the sounding, pump flow rate, outflow, water level, and ADH values, which are 10.00000013 rad/s, 34.72%, 4.494%, 0.025 m3/s, 73.31 cm3, and 750 values, respectively. The outflow rate increase indicates that water is being released from the tanks, and the control signal fluctuates, indicating that the valve is opening