Increasing Pollution Levels Research Articles

Experimental Analysis of Ceramic Insulators with Different Profiles Under Very High Pollution Zone by Solid Layer Method

The outdoor insulators in service are exposed to marine, agricultural waste and industrial pollution. These pollutants get deposited on the insulator surface and lead to flashovers under fog conditions. There has been an abnormal increase in pollution levels due to rapid industrialization in the past two decades. This exponential increase in pollution levels causes frequent flashovers of insulators, leading to the tripping of transmission lines consecutively may result in blackouts, which severely affects the reliability of the power systems. The ESDD and NSDD measurement on the insulator surface are critical parameters for determining the pollution severity levels. This paper discusses ESDD and NSDD measurement procedures. In this paper, field pollution severity has been simulated in the Artificial Pollution Lab. In addition, the Non-Soluble Deposit Density (NSDD) component of pollutants for designing the creepage distance of ceramic insulators under heavy pollution conditions has been emphasized.

Irreversible and Large‐Scale Heavy Metal Pollution Arising From Increased Damming and Untreated Water Reuse in the Nile Delta

AbstractEgypt observes one of the highest water budget deficits in Africa that is mainly compensated by intensive reuse of untreated agricultural drainage water in the Nile Delta. The implications of untreated water reuse on increasing soil pollution levels remain poorly characterized; however, a large‐scale pollution can compromise crop production and water quality. To address this deficiency, we evaluate the level of heavy metal pollution in the Nile Delta, identify its sources and explore the implications of damming on heavy metal concentration using integrated pollution indicators and statistical modeling. Pollution indicators show moderate to very high contamination by Pb, Ni, Cr, Cd, Cu, and Zn, with unprecedented Cd levels in the sediments (up to 72.0 ppm) and a northward increase in pollution levels. Statistical modeling and historical datasets reveal the association of Cd and Fe on both Nile branches and the clustering of Pb, Ni, Cu, Zn and Cr, which attribute the heavy metal concentrations to the cumulative addition of untreated agricultural drainage water (9.5 BCM/yr) and wastewater. These processes introduced an accelerated pollution in the Nile Delta system. Though, conservation measures are crucial to reverse this degradation, yet the increasingly engineered Nile flow, the low gradient of the delta and the active silting impede heavy metal flushing causing irreversible pollution. Our findings alarm future increase in heavy metal pollution in response to increased untreated drainage water reuse to mitigate the impacts of ongoing upstream damming and call for implementing international cooperative agreements for integrated water management along the Nile River.

Biophysical, histological, and bioaccumulation properties of Tilapia muscle affected by water pollution with heavy elements and microbes at the El-Rahawy drain in Egypt

The leakage of sewage and agricultural drains has led to the contamination of freshwater branches with toxic heavy elements. This raises concerns about their toxic effects on aquatic ecosystems, especially on fish. Tilapia is regarded as an important protein source in Egypt and many other countries. The biophysical, nutritional, and histological aspects of water pollution in the El-Rahawy and Al-Qatta locations of the Nile on Nilotic tilapia muscle were evaluated by assessing the level of contamination of Nilotic tilapia fish. The current study showed that water of the Rosetta branch water was polluted with a very high level at El-Rahawy Drain discharge (RD) location, and with a high level at Al-Qatta (Q) location, while El-Rahawy (R) location was polluted with a lower level. The study traced the pollution effects on Tilapia (Nilotic) muscles in the previous locations. Bioaccumulation factor (BAF) showed a high value of all heavy metals in Tilapia muscle at the Q and R locations. Contrary to what was expected, discharge (RD) location contamination caused BAF increment of heavy metals in Tilapia muscles at upstream R location. All these results were compared with measured dielectric parameters of Tilapia muscle samples in the frequency range (0.02–1000) kHz. There was an increase in conductivity (σac), dielectric constant (ε′), dielectric loss (ε″), penetration depth (dp), and dissipated power (PD) values of Tilapia muscle, with increasing pollution level. The values of permittivity at low and high frequencies (ε′s & ε′∞) for Tilapia muscle decreased by increasing pollution. Finally, the variation of these parameters, based on that proportionality relationship, can be considered as a physical indicator for fish contamination affected by their environment pollution, although these parameters need further studies in a controlled (qualitatively and quantitatively) polluted media.

COVID-19 Pandemic: Impacts on Air Quality during Partial Lockdown in the Metropolitan Area of São Paulo

Air pollution has become one of the factors that most affect the quality of life, human health, and the environment. Gaseous pollutants from motor vehicles have a significantly harmful effect on air quality in the Metropolitan Area of São Paulo (MASP)—Brazil. Motor vehicles emit large amounts of particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and volatile organic compounds (VOCs), the last three acting as the main tropospheric ozone (O3) precursors. In this study, we evaluated the effects of these pollutants on air quality in the MASP during the partial lockdown that was imposed to ensure the social distancing necessitated by the COVID-19 pandemic. We compared the monthly data for nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) and CO, SO2, and BC from MERRA-2 for the period between April and May 2020 (during the pandemic) with the average for the same period for the (pre-pandemic) years 2017 to 2019 in the southeast region of Brazil. The meteorological and pollutant concentration data from the CETESB air quality monitoring stations for the MASP were compared with the diurnal cycle of three previous years, with regard to the monthly averages of April and May (2017, 2018, and 2019) and the same period in 2020, when the partial lockdown was first imposed in southeast Brazil. Our findings showed that there was a decrease in NO2 concentrations ranging from 10% to more than 60% in the MASP and the Metropolitan Area of Rio de Janeiro (MARJ), whereas in the Metropolitan Area of Belo Horizonte and Vitoria (MABH and MAV, respectively), there was a reduction of around 10%. In the case of the concentrations of CO and BC from MERRA-2, there was a considerable decrease (approx. 10%) during the period of partial lockdown caused by COVID-19 throughout almost the entire state of São Paulo, particularly in the region bordering the state of Rio de Janeiro. The concentration of SO2 from MERRA-2 was 5 to 10% lower in the MASP and MARJ and the west of the MABH, and there was a decrease of 30 to 50% on the border between the states of São Paulo and Rio de Janeiro, while in the MAV region, there was an increase in pollutant levels, as this region was not significantly affected by the COVID-19 pandemic. Sharp reductions in the average hourly concentrations of CO (38.8%), NO (44.9%), NO2 (38.7%), and PM2.5 (6%) were noted at the CETESB air quality monitoring stations in the MASP during the partial lockdown in 2020 compared with the hourly average rate in the pre-pandemic period. In contrast, there was an increase of approximately 16.0% in O3 concentrations in urban areas that are seriously affected by vehicular emissions, which is probably related to a decrease in NOx.

A sustainable vanadium bioremediation strategy from aqueous media by two potential green microalgae

Globally, environmental concerns are rapidly growing due to increasing pollution levels. Vanadium is a hazardous heavy metal that poses health issues with an exposure concentration of about 2 ppm. It is regularly discharged by some industries and poses an environmental challenge. There are no sustainable green treatment methods for discharged effluents to mitigate vanadium threats to humans and the environment. In this study, the goal was to develop a green, sustainable method for removing vanadium and to utilize the produced biomass for biofuels, thus offsetting the treatment cost. Microalgae Chlorella sorokiniana SU1 and Picochlorum oklahomensis were employed for vanadium (III) treatment. The maximum removal was 25.5 mg L−1 with biomass and lipid yields of 3.0 g L−1 and 884.4 mg L−1 respectively after 14 days of treatment. The vanadium removal capacity by microalgae was further enhanced up to 2–2.7 folds while optimizing the key parameters, pH, and temperature before removing biomass from the liquid phase. FTIR is used to analyse the reactive groups in algal cell walls to confirm vanadium adsorption and to understand the dominant and quantitative interactions. Zeta potential analysis helps to find out the most suitable pH range to facilitate the ionic bonding of biomass and thus maximum vanadium adsorption. This study addresses regulating external factors for enhancing the removal performance during microalgal biomass harvesting, which significantly enhances the removal of vanadium (III) from the aqueous phase. This strategy aims to improve the removal efficiency of microalgal treatment at an industrial scale for the bioremediation of vanadium and other inorganic pollutants.

Impact of COVID-19 lockdown on the water quality of the Damodar River, a tributary of the Ganga River in West Bengal.

The online version contains supplementary material available at 10.1007/s40899-022-00790-2.

Seismic Data Denoising Based on Wavelet Transform and the Residual Neural Network

The neural network denoising technique has achieved impressive results by being able to automatically learn the effective signal from the data without any assumptions. However, it has been found experimentally that the performance of the method using neural networks gradually decreases with increasing pollution levels when processing contaminated seismic data, and how to improve the performance will become the direction of further development of the method. As a traditional method widely used for tainted seismic data, the wavelet transform can effectively separate the signal from the noise. Thus, we propose a method combining wavelet transform and a residual neural network that achieves good results in suppressing random noise data.

Investigations on exhaust emissions of aninsulated diesel engine with alternative fuels

In the context of depletion of fossil fuels, ever increase of pollution levels with fossil fuels and escalating prices of crude petroleum in International market, the search for alternative fuels has become pertinent. Alcohols (ethanol, methanol and butanol) and vegetable oils are important substitutes for diesel fuel. Alcohols renewable in nature, have low C/H (C=Number of carbon atoms and H=Number of hydrogen atoms in fuel composition and highly volatile. Butanol has higher calorific value than ethanol and methanol. Vegetable oils comparable cetane number and energy content when compared to diesel fuel. However, the drawbacks of vegetable oils (high viscosity and low volatility) and alcohols (low cetane number and low energy content) to be used as fuels in diesel engine call for semi adiabatic diesel engine (SADE) with its significance characteristics of higher operating temperature, maximum heat release, high brake thermal efficiency and ability to handle the low calorific value fuel.Exhaust emissions from diesel engine cause severe health hazards once they are inhaled in. They also cause environmental disorders. Hence control of these emissions is immediate step and urgent. In order to take advantages from both vegetable oils and alcohols, it is proposed to use the vegetable oil along with carbureted butanol in semi adiabatic diesel engine. Butanol was inducted into the engine through a variable jet carburetor, installed at the inlet manifold of the engine at different percentages of crude vegetable oil at full load operation on mass basis. Crude vegetable oil was injected at near end of compression stroke in conventional manner. Exhaust emissions were determined with semi adiabatic engine consisting of air gap (3 mm) insulated piston with superni (an alloy of nickel) crown, air gap (3 mm) insulated liner with superni insert and ceramic coated cylinder head with mixture of carbureted butanol and crude vegetable oil with varied injector opening pressure and injection timing. Comparative studies were made with data of conventional engine (CE) with maximum induction of Butanol at similar operating conditions. Aldehydes were measured by wet method. The maximum induction of butanol was 60% at recommended injection timing of 27obTDC (before top dead center), while it was 55% at optimum injection timing of 29obTDC.

Investigations on Pollution Levels of Four Stroke Copper Coated Spark Ignition Engine with Alcohol blended Gasoline

Alcohols are renewable fuels. They can be conveniently used in spark ignition engines. They have octane number (a measure of combustion quality in spark ignition engine) higher than gasoline. Alcohols are important substitutes for gasoline, in the context of fast depletion of fossil fuels, ever increase of pollution levels with fossil fuels and increase of economic burden due to import of crude petroleum the search for alternative fuels has become pertinent. Investigations were carried out to determine pollution levels of variable speed, variable compression ratio, four- stroke, single cylinder, spark ignition (SI) engine having copper coated engine [CCE, copper-(thickness, 250 ìm) coated on piston crown and inner side of cylinder head] provided with catalytic converter with sponge iron/manganese ore as catalyst with different test fuels of neat gasoline, gasohol (85% gasoline and 15% ethanol by volume) and methanol blended gasoline (85% gasoline and 15% methanol by volume) and compared with conventional engine (CE) with neat gasoline operation. Exhaust emissions of carbon mono oxide (CO), un-burnt hydro carbons (UBHC) and nitrogen oxide (NOx) were varied with different values of brake mean effective pressure (BMEP) of the engine with different versions of the engine with test fuels with and without provision of the catalytic converter with sponge iron or manganese ore as catalyst. The engine was provided with catalytic converter with sponge iron and manganese ore as catalysts. There was provision for injection of air into the catalytic converter. The performance of the catalyst was compared with one over the other. Methanol blended gasoline decreased exhaust emissions effectively in comparison with gasohol with both versions of the engine. Catalytic converter with air injection significantly reduced pollutants with different test fuels on both configurations of the engine.

Pan-cancer mutational signature surveys correlated mutational signature with geospatial environmental exposures and viral infections

BackgroundCancer has been disproportionally affecting minorities. Genomic-based cancer disparity analyses have been less common than conventional epidemiological studies. In the past decade, mutational signatures have been established as characteristic footprints of endogenous or exogenous carcinogens. MethodsIntegrating datasets of diverse cancer types from The Cancer Genome Atlas and geospatial environmental risks of the registry hospitals from the United States Environmental Protection Agency, we explored mutational signatures from the aspect of racial disparity concerning pollutant exposures. The raw geospatial environmental exposure data were refined to 449 air pollutants archived and modeled from 2007 to 2017 and aggregated to the census county level. Additionally, hepatitis B and C viruses and human papillomavirus infection statuses were incorporated into analyses for skin cancer, cervical cancer, and liver cancer. ResultsMutation frequencies of key oncogenic genes varied substantially between different races. These differences were further translated into differences in mutational signatures. Survival analysis revealed that the increased pollution level is associated with worse survival. The analysis of the oncogenic virus revealed that aflatoxin, an affirmed carcinogen for liver cancer, was higher in Asian liver cancer patients than in White patients. The aflatoxin mutational signature was exacerbated by hepatitis infection for Asian patients but not for White patients, suggesting a predisposed genetic or genomic disadvantage for Asians concerning aflatoxin. ConclusionsEnvironmental pollutant exposures increase a mutational signature level and worsen cancer prognosis, presenting a definite adverse risk factor for cancer patients.

Unraveling Water Quality Degradation in Ramgarh Tal, Gorakhpur: A Geographical Study

The rising anthropogenic activities in the area have raised concerns about the quality of water in Ramgarh Tal of Gorakhpur, Uttar Pradesh. The objective of this research was to determine Ramgarh Tal's water quality index (WQI) by a thorough evaluation of several physicochemical factors. A variety of parameters, such as pH, dissolved oxygen (DO), total dissolved solids (TDS), biochemical oxygen demand (BOD), sulfate, nitrate, alkalinity, magnesium, calcium, chloride, and microbiological pollutants, were measured on water samples that were taken from various locations. The findings showed a considerable deterioration in the quality of the water, with increasing pollution levels above allowable limits established by ICMR/BIS guidelines. High nutrient levels, turbidity, and microbiological burdens in the water body have been attributed to the main causes of contamination and eutrophication, which have been identified as industrial discharge, home sewage, and agricultural runoff. A quantitative assessment of the total water quality was obtained by calculating the WQI using accepted techniques, which showed low to bad conditions at the sampled site.

Construction of the comprehensive evaluation system of waterbody pollution degree and the response of sedimentary microbial community

This study proposed and established a comprehensive evaluation system for the pollution degree of the waterbody by taking overlying water and sediment as a whole. By dividing different sampling points into three gradients according to the pollution degree, the changes in sedimentary microbes under various pollution gradients were compared. The results showed that microbial diversity, abundance and specific OTUs decreased significantly with the increase in pollution degree. Meanwhile, Firmicutes, Bacteroidota and Caldiseriota increased in the severely polluted group, while Chloroflexi and Acidobacteriota decreased. Spearman correlation analysis and co-occurrence network revealed that COD, pH in overlying water, and Mn, Fe in sediments were the most significant pollution degree evaluation indicators affecting sedimentary microorganisms, which drove the sedimentary microbial communities dominated by Proteobacteria and Firmicutes. FAPROTAX functional prediction indicated that increased pollution levels led to the weakening of functional genes related to nitrogen metabolism and sulfur metabolism and the increase of functional genes related to carbon metabolism in sediment microorganisms. This study not only provided new insights into waterbody pollution evaluation but also verified the feasibility of this evaluation method by the response of sedimentary microbial communities to different pollution degrees.

Activity of low-molecular weight components of Larix sibirica antioxidant system under exposure to technogenic pollution.

Changes in the antioxidant protection system of Larix sibirica Ledeb at different pollution levels caused by emissions from a large aluminum smelter (BrAS) have been studied. We revealed that the content of peroxide (H2O2) in the needles is a reliable marker of oxidative stress in the trees under pollution. The crucial role of non-enzymatic components, in particular, proline, phenolic compounds, ascorbic acid, glutathione, in reducing the level of free radicals in the needles cells was found. Proline concentration in the needles significantly rises with the increase in pollution levels from low to high. Under critical level pollution, it decreases by 40% compared to the background. The total content of ascorbic acid (ASC) in the needles of polluted trees varies slightly; however, there are significant changes in its various forms. With an increase in pollution to a high level, the content of the reduced form of ASC in the needles increases by 1.5-2.9 times compared to the background content. At a critical level of pollution, the total level of ascorbic acid and its reduced form falls, the content of the oxidized form reaches minimum values. The total content of phenolic compounds in the needles increased by 50-55%, concentration of flavonoids by 1.5-1.8 times, catechins by 1.9-2.5 times, proanthocyanidins by 45% compared to the background level under low, moderate, high pollution, whereas under critical pollution their content decreased. The absolute concentration of the reduced form glutathione in the needles falls by 1.9-3.0 times, the oxidized form increases by 1.5-2.0 times compared to the background. The ratio of reduced glutathione to oxidized glutathione decreased, especially during critical pollution. The data obtained show significant activation of Siberian larch biochemical protection at low, moderate and high levels of pollution by the aluminum smelter emissions. At a critical levels of contamination, a significant depletion of the pool of low-molecular antioxidants was observed.

Investigating the Role of Information and Communication Technologies, Economic Growth, and Foreign Direct Investment in the Mitigation of Ecological Damages for Achieving Sustainable Development Goals.

At the present time, information and communication technology (ICT) has played a vital role in socio-economic development such as economic growth, literacy, life expectancy, and employment levels in societies, however, such development has come with various environmental damages perspectives. This study scrutinizes the impact of ICT, economic growth, and foreign direct investment (FDI) on carbon dioxide (CO2) emissions in the 44 One Belt and Road Initiative (OBRI) countries split into sub-region from 1991 to 2019. This study applied various econometrics approaches such as cross-sectional dependence, second-generation unit root, and Westerlund panel cointegration techniques are executed to analyze the panel data set. The full modified ordinary lease square and dynamic ordinary lease square estimators are applied to investigate the long-term influence of ICT development, GDP (economic growth), and FDI on CO2 emissions. The empirical analysis was performed at a disaggregated level to assess the possible environmental influences across the OBRI countries. Overall, the results reported that broadband and mobile development have an adverse effect on CO2 emissions. The finding further reveals that the broadband indicator negatively affects CO2 emissions in all OBRI regions except South Asia. Similarly, the mobile use indicator protects the environmental quality in all OBRI regions except MENA (Middle East and North Africa) and Central Asia. Regarding country-wise analysis, broadband has alleviated the pollution level in 21 countries, while mobile has alleviated it in 15 countries. Moreover, economic growth is responsible to increase pollution levels in all panels and regions except Europe. Besides, the results highlight that higher FDI reduces environmental pollution whereby, the pollution halo hypothesis is supported to hold for all OBRI panels and regions except MENA countries. Based on the empirical findings, the policymakers and governments of these economies should design policies to grow smarter cities, transportation systems, electrical grids, industrial processes, and energy-saving production through ICT development on a macro level.

Relationship between the incidence of socially significant diseases and sanitary and ecological parameters of the environment throughout municipal entities in the Mari El Republic

BACKGROUND: There is a formal contradiction in the Republic of Mari El between the favorable ecological situation in localities of the Republic and the above-limit morbidity rates caused by the negative impact of habitat factors. As such, there is a need to conduct a specified quantitative examination using modern econometric approaches.
 AIM: By using panel data, to identify and substantiate statistical relations between the morbidity rate of the population in municipal entities of the Mari El Republic and ecological parameters of the environment (physical and chemical and bioindication indicators).
 MATERIAL AND METHODS: This study used the panel data on morbidity rates of the population, including children, adolescents, and adults, and environmental pollution across 15 municipal entities within the Mari El Republic from 20092019, as well as spatial data on fluctuating asymmetry for 2019 that were based on a field study and integrally reflect the environmental quality. Statistical analysis for dynamic panel data involved cointegration and modeling with a mechanism of balance adjustment, whereas that for spatial data involved nonparametric correlation analysis. All statistical analyses were conducted using the statistics packages EViews 11 and Stata 16 IC.
 RESULTS: It was established that over the long term the increasing pollution level of drinking water from the distribution network and the atmosphere has a statistically significant effect (2=79.79; p 0.001) on the increase in figures of congenital abnormalities (malformation), deformations and chromosome breakages in children aged 0 to 14 years. Adjustment of the indicator of congenital abnormalities (malformation), deformations and chromosome breakages in children aged 0 to 14 years with a deviation from the equilibrium trajectory occurs in about 2 years. It is required to develop measures to systematically provide the population with good-quality drinking water and reduce emissions of pollutants into the atmosphere. Stable positive correlations of long-term average annual morbidity rate of the whole population and the adult population aged 18 and older being ill with malignant tumors are associated with the change in environmental quality (indicators of the fluctuating asymmetry in the impact zone).
 CONCLUSION: A panel regression model was designed that explains the change in time of the indicator of congenital abnormalities (malformation), deformations and chromosome breakages in children aged 0 to 14 years within one municipal entity with the increasing pollution level of the atmosphere and drinking water. Being ill with malignant tumors is related to a complex of various stress factors (varying between the human impact and climate change).

Estimating the heavy metal contents in farmland soil from hyperspectral images based on Stacked AdaBoost ensemble learning

• Assessment of heavy metal pollution in soil base on hyperspectral image. • Estimating the soil heavy metal content by constructing ensemble learning model. • The estimation accuracy of heavy metal content in soil is improved. • Mapping the distribution trend of heavy metals in farmland soil. • The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Heavy metal pollution poses a huge challenge to the soil environment. With the increasing pollution level, the traditional monitoring methods cannot quickly obtain information on large-area pollution. Therefore, a large-scale mapping method with high precision is urgently needed to effectively control heavy metal pollution. This study explored a method for mapping soil heavy metal concentrations through hyperspectral images. On this basis, a new Stacked AdaBoost ensemble learning algorithm was constructed to construct the inversion model of soil heavy metal contents. The characteristic spectral bands of heavy metals were extracted as model input variables using Pearson’s correlation coefficient and successive projections algorithm. With three sets of heavy metal content data, the prediction accuracy and mapping outcomes of various machine learning methods were compared. Furthermore, the potential sources of heavy metal pollution in the study area were analyzed based on the Moran’s index. The results showed that the Stacked AdaBoost model was relatively stable with higher accuracy than traditional machine learning models. For Cr, Cu, and As, the determination coefficients ( R 2 ) of the verification set were 0.66, 0.61, and 0.74, respectively. Afterward, the results of this model were used to map the heavy metal concentration over the study area. The mapping results suggested that the heavy metal conditions of soils in the Ganhetan area were caused by nature and human activities. The As pollution in agricultural soils was the most serious, with an exceedance rate of 38.66%. Industrial areas were potential sources of soil heavy metal pollution in the study area. In summary, the Stacked AdaBoost ensemble learning model provides detailed and reliable data for agricultural ecological protection and industrial pollution control, allowing the effective management of heavy metal pollution sources.

Comparative analysis of converter topologies used in switched reluctance motor for high torque electric vehicle application

Electric Vehicles (EVs) are gaining interest because of the sky rocketing oil prices and increased pollution level in major cities across the world. Almost all EV motors need rare earth magnet which are in limited supply. In order to reduce this dependency, EVs are looking for magnet free motors. One of the alternatives gaining significant mindshare across industry is Switched Reluctance motor (SRM). SRM largely satisfies all the requirements of EV. However, its performance is mainly dependent on converter and controller topology. This paper critically analyses the various parameter of SRM during dynamic loading condition like speed, torque ripple and current, using various converter topologies. Analysis of 60 kW, 4 phase SRM for EV application has been presented with mid-point converter and asymmetric bridge converters along with the proportional plus integral (PI) hysteresis controller. Results shows that asymmetric bridge converter provides enhanced performance for EV application.

Oxyhydrogen Gas Production by Alkaline Water Electrolysis and the Effectiveness on the Engine Performance and Gas Emissions in an ICEs: A Mini-Review

The excessive use of fossil fuels and the resultant dramatic increase in pollution levels have highlighted the need for a new sustainable and environmentally friendly fuel. Hence, it is necessary to research alternatives to reduce the use of fossil fuels and the emission of greenhouse gases. Utilising oxyhydrogen (HHO) gas has been proven to achieve high engine power output and efficiency with low emissions for spark-ignited internal combustion engines. HHO gas is generated from the electrolysis of water. This paper reviews the recent research findings related to the influencing factors on the production of HHO gas using alkaline water electrolysis involving electrolyte properties, electrolyte concentration, the distance between electrolytes, and the effects of HHO gas on the engine performance and gas emissions. Using an HHO gas blend in a diesel/gasoline engine could be a viable option for lowering GHG emissions and increasing engine efficiency.

Design and Fabrication of Chairless-Chair using Pressure Cylinder and Flow Control Valves

Today the world is now going to be compact. For suitability to the world, things are also going to be made of compact and smaller in size. Now the battle is also done between machines instead of man to man. Machine, which is fighting, are operated and driven by man sitting instead the vehicle or being in touch with the machines. Also, the human has to win the war against the increasing oil prizes and tremendously increasing pollution level in the air. To win this war and to thought regarding another parallel motive force to the auto- mobile, we have thought of manufacturing “CHAIRLESS CHAIR” through the mission of project. Project is a mission of creating something new, which is innovative i.e. manufacturing of a new product.

FACTORS AFFECTING E-SCOOTER SHARING PURCHASE INTENTION TO COMBAT CLIMATE CHANGE: AN ANALYSIS USING UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY

Transportation uses a significant amount of energy and burns most of the world's petroleum. As a result, it gives effect to the environment, such as air pollution in the forms of carbon dioxide, nitrous oxide, and particulates. Those compounds create a phenomenon called global warming. Within the transportation sector, road transport is the largest contributor to global warming. To cope with global warming, environmental regulations in developed countries are trying to reduce the individual vehicle's emissions. However, this has been counterbalanced by an increase in the number of vehicles and increased use of each vehicle. Therefore, micro-mobility may alleviate several challenges facing big cities today and offer more sustainable urban transportation. In the next ten years, e-scooter sharing is predicted to become an international business as its potential to become a multi-billion dollar industry (Purnomo Yusgiantoro, 2019). E-scooter sharing has seen a massive leap in popularity within the last few years because, on the surface, it appears to be a business model that is here to stay and, most importantly, has become a solution in creating a greener environment and economy. This research utilizes the framework of the UTAUT2 to identify and build a quantitative approach to identify factors related to the purchase intention factors of e-scooter sharing. The 200 respondents' field data were collected in Jakarta Metropolitan Area (Jabodetabek) as a rapid increase in pollution level and a considerable number of essentials of the central business district and many high-rises stores and universities. The linear regression study revealed that the consumers' purchase intention of e-scooter sharing is shaped by seven main factors: performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value, and habit. Those factors can explain 83 percent of the field data. Moreover, a brief recommendation for related stakeholders based on the Research results are proposed to increase the adoption of e-scooter sharing. The practical implications resulting from this analysis are suggested policy measures, e-scooter sharing, environmentally impact potency and strengthening green economy achievement in the communities. Keywords : E-Scooter Sharing, Green Economy, Linear Regression, Purchase Intention