Produce Air Pollution Research Articles

Battery Analysis in Off Grid Solar Power Plant as A Power Source for AC Motor Automatic Coffee Roaster Machine Capacity 20 Kg

Solar power plants that utilize solar energy to be converted into electrical energy have several advantages compared to other power plants, namely that they do not produce air pollution, are available continuously and are available everywhere. Coffee is a commodity in the world that is cultivated in more than 50 countries. Two species of coffee trees that are generally known are Robusta Coffee and Arabica Coffee. Processing coffee before consumption goes through a long process, namely from harvesting coffee beans that are ready to harvest. Then proceed with drying before roasting. Coffee roasting machine that uses an AC motor. The motor gets a DC power source from a solar power plant then the inverter changes the DC voltage to AC. This coffee roasting machine is equipped with IoT to control the motor rotation remotely and monitor the temperature. The battery has the function of storing electrical energy produced by solar panels in the form of direct current energy. The energy stored in the battery functions as a backup, which is usually used when the solar panels do not produce electrical energy. The greater the capacity of the battery used, the longer the battery can back up the load used.

Dispersion model of NOx emissions from a liquefied natural gas facility

Natural gas used widely in terms of energy production. Energy production is among the most prominent sectors of humankind. Combustion processes inevitably produces air pollutants. The major pollutant during a combustion process is nitrogen oxide emissions. The term of nitrogen oxides primarily include nitrogen monoxide and nitrogen dioxide. These pollutants are generated regardless of the fuel content since air composition itself is the major source for these pollutants. It is possible to calculate emissions through the activity data and emission factors. Calculation of emissions is not enough for an environmental assessment. The impact of pollutants on human health relies on their concentration in the atmosphere. In order to determine their concentrations several modelling practices are developed. In this study, AERMOD used for modelling purpose of NOx emissions from a liquefied natural gas facility. It was observed that the pollutants were dispersed mostly towards south-southwest of the facility, where Marmaraereğlisi district is located. Although the pollutants transported directly to the settlement, the concentrations remained limited. During operation conditions, the highest daily NOx concentration was 1.7 μg/m3 and the highest annual concentration was 0.1 μg/m3. At maximum operating conditions, the highest daily NOx concentration was 16.2 μg/m3 and the highest annual concentration was 2.5 μg/m3. At minimum operating conditions, the highest daily NOx concentration was 1.1 μg/m3 and the highest annual concentration was 0.2 μg/m3.

The Spatial–Temporal Emission of Air Pollutants from Biomass Burning during Haze Episodes in Northern Thailand

Air pollutants from biomass burning, including forest fires and agricultural trash burning, have contributed significantly to the pollution of the Asian atmosphere. Burned area estimates are variable, making it difficult to measure these emissions. Improving emission quantification of these critical air pollution sources requires refining methods and collecting thorough data. This study estimates air pollutants from biomass burning, including PMs, NOX, SO2, BC, and OC. Machine learning (ML) with the Random Forest (RF) method was used to assess burned areas in Google Earth Engine. Forest emissions were highest in the upper north and peaked in March and April 2019. Air pollutants from agricultural waste residue were found in the lower north, but harvesting seasons made timing less reliable. Biomass burning was compared to the MODIS aerosol optical depth (AOD) and Sentinel-5P air pollutants, with all comparisons made by the Pollution Control Department (PCD) Thailand air monitoring stations. Agro-industries, mainly sugar factories, produce air pollutants by burning bagasse as biomass fuel. Meanwhile, the emission inventory of agricultural operations in northern Thailand, including that of agro-industry and forest fires, was found to have a good relationship with the monthly average levels of ambient air pollutants. Overall, the information uncovered in this study is vital for air quality control and mitigation in northern Thailand and elsewhere.

Prediction of air pollution from power generation using machine learning

Electrical energy is now widely recognized as an essential part of life for humans, as it powers many daily amenities and devices that people cannot function without. Examples of these include traffic signals, medical equipment in hospitals, electrical appliances used in homes and offices, and public transportation. The process that generates electricity can pollute the air. Even though natural gas used in power plants is derived from fossil fuels, it can nevertheless produce air pollutants involving particulate matter (PM), nitrogen oxides (NOx), and carbon monoxide (CO), which affect human health and cause environmental problems. Numerous researchers have devoted significant efforts to developing methods that not only facilitate the monitoring of current air quality but also possess the capability to predict the impacts of this increasing rise. The primary cause of air pollution issues associated with electricity generation is the combustion of fossil fuels. The objective of this study was to create three multiple linear regression models using artificial intelligence (AI) technology and data collected from sensors positioned around the energy generator. The objective was to precisely predict the amount of air pollution that electricity generation would produce. The highly accurate forecasted data proved valuable in determining operational parameters that resulted in minimal air pollution emissions. The predicted values were accurate with the mean squared error (MSE) of 0.008, the mean absolute error (MAE) of 0.071, and the mean absolute percentage error (MAPE) of 0.006 for the turbine energy yield (TEY). For the CO, the MSE was 2.029, the MAE was 0.791, and the MAPE was 0.934. For the NOx, the MSE was 69.479, the MAE was 6.148, and the MAPE was 0.096. The results demonstrate that the models developed have a high level of accuracy in identifying operational conditions that result in minimal air pollution emissions, with the exception of NOx. The accuracy of the NOx model is relatively lower, but it may still be used to estimate the pattern of NOx emissions

Experimental study on the performance of household electric cooking stoves: Locally made versus imported technologies

Biomass combustion produces air pollutants, causing high mortality rates, while electric cooking, which is efficient and eco-friendly, reduces mortality and maximizes socio-economic and ecological benefits. Thus, the primary purpose of this study is to compare the performance of domestic and imported household electric hotplate stoves via experimental investigation. For the study, 20 households have been purposively selected in Bahir Dar, Ethiopia from low- and middle-income groups. Following that, the researchers trained the participants and enumerators to record the energy consumption and time taken for each cooking event. The experiments have been conducted using medium-sized domestic and imported electric hotplate stoves for 15 days each. Digital energy meters have been used to record the daily cooking energy demand. Participants record the daily data using the developed Excel spreadsheet. Accordingly, the study disclosed that the average daily cooking energy consumption per household for locally-made and imported electric cookstoves is 3.55 kWh and 2.81 kWh, respectively. The result also reveals that local electric stoves are subjected to inferior efficiency and higher heat losses. On the other hand, the analysis of the average time required to cook a meal revealed that cooking with imported cookstoves took slightly longer than cooking with locally-made cookstoves. This is because as there is no power-control mechanism, locally-made electric stoves usually work at maximum power rate and cook faster than imported ones. Moreover, the average monthly energy expense per household using these stoves in their respective ways were $3.90 (213.33ETB), and $3.1(169.86ETB), suggesting that locally manufactured stoves have higher energy cost bills. An independent T-test results revealed a significant difference (p < 0.001) between the two types of stoves. However, most households use locally made electric cook stoves due to their low prices, easy maintenance, and low understanding of stove efficiency. Hence, further investigation is needed to improve the efficiency and standardization of local electric cook stoves and increase the supply chain of imported electric appliances.

Initial Design of Free energy magnetic generator (FEMG)

Nowadays, it is essential for some areas that there would be implemented such ways for electricity cost reductions in the areas, equipment durability and minimal technical labour demand maintenance. There are many type of generator that can help to generate the electricity such as steam turbines, gasoline turbines, electrical generators, solar or wind turbines, internal combustion engines, and biogas engines. However, there are many drawbacks of using these generators. One of the major drawbacks of these non-renewable generators are the released of hazardous exhausts into the environment such as carbon dioxide, nitrogen oxide, or any other dangerous exhaust. These will produce air pollution, although it imposes environmental costs through manufacture and construction. One of the well-known energy sufficient generator is the permanent magnet generator. The main aim for this project is to design a Free Energy Magnetic Generator (FEMG) using conventional induced voltage generating principle for industrial and residential appliances. The design will be used JMAG Designer Software from designing and observing the generator. It can be concluded that this generator can give a continuous output power supply due to the capability of the generator to produce high output power with low cogging torque which is 2.1Nm. Perhaps, the maximum value of magnetic flux between coil is 2.1066 while the minimum value is 0.0418.

Phytoarchitecture Design for Public Roads to Combat Air Pollution Resulting from Transport Operations

Public roads and all their activities interact with the environment outside. The interaction was related to transportation pollutants and their recipient bodies, plants, air, and soil. The interaction of these environmental components can produce air pollution and requires prevention solutions. Plants are considered capable of weakening pollution; thus, this study aims to design a novel phytoarchitecture for public roads where roadside plants reduce air pollutants. The method for achieving this goal was based on selected empirical research, which was searched, collected, and selected using the Mendeley reference manager platform with the search phrase: roadside plants, heavy metals, and gaseous pollutants. The selection of hundreds of literatures was carried out in three screening stages. The organisation of this literature review used the ecological approach of transportation pollutants and roadside plants. With the intended methodology, the results of this study indicate that gaseous pollutants and heavy metals arise from public road transportation activities. Traces of pollutants can be measured on the surrounding land and especially on plants. There are five functional characteristics of plants, including phytotreatment, which reduces air pollution; phytoaccumulation to store pollutants; phytoindicators to indicate the presence of excessive concentrations; phytotoxicity in response to toxic levels; and phytomonitoring, which can provide early warning system. Finally, an ecological design is proposed for new roads and improving, operating, and maintaining existing roadside plants. In conclusion, the plant roles can be applied as criteria in the architectural design of public roads.

Comparative Study of Thermodynamic Performance and System Characteristics of Solid Oxide Fuel Cell System with Three Different Fuels

The global demand for hydrogen is increasing as the global warming problem emerges. Hydrogen, which does not produce air pollutants, is attracting attention in various fields such as transportation and power generation. However, there are drawbacks in storing and transporting hydrogen in its own form. Hydrogen must be stored in the form of low-temperature and high-pressure liquefied hydrogen, which requires a lot of energy, and transportation costs are also high due to the low mass energy density of hydrogen. Therefore, there is a need to store and transport hydrogen in different forms, and a means to convert and use these different forms of hydrogen is needed.Solid oxide fuel cell (SOFC) is one of the energy conversion devices capable of using various types of hydrogen with high efficiency. Due to the high operating temperature of SOFC, fuel can receive adequate heat for reforming process from high temperature SOFC exhaust gas. Therefore, SOFC can use various types of fuels, such as methane and ammonia.Due to the fuel flexibility of SOFC, many SOFC system study using various fuels have been conducted. However, the SOFC operating conditions and system layout used in each study are all different. Also, most of studies lacked parasitic power consideration due to the pressure drop in system components. These limitations make it difficult to compare each SOFC system and find out effect of fuel on SOFC system.In this study, a quantitative comparison of SOFC using three different fuels, methane, ammonia, and hydrogen, was conducted. Thermodynamic models of a SOFC stack and balance of plant components developed from the previous study are used for the system simulations. Two system layouts, non-recirculation, and anode recirculation were chosen, and thermodynamic feasibility test was conducted based on T-Q diagram analysis at heat exchanger and reformer. With these system layouts, thermodynamic performance of the system and the design characteristics of the system components were compared. Boundary conditions, such as SOFC operating temperature, air and fuel utilization remains the same to compare each system result quantitatively. Also, most of design variables of system components are fixed to find out the effect of fuel on system components.Among three non-recirculation systems, ammonia fed non-recirculation system showed the highest electrical efficiency, while methane fed anode recirculation system showed the highest electrical efficiency among the anode recirculation systems. With the anode recirculation, SOFC power drop occurs due to the lower hydrogen concentration in the SOFC. However, fuel input drop due to anode recirculation is greater than the SOFC power drop, which positively affects system performance. But parasitic power is also increased due to recycle blower and higher mass flow rate of anode recirculation flow. In the case of ammonia fueled system, this increase in parasitic power leads to decrease in electrical efficiency.In this study, there are many constraints in operating conditions and BoPs designs to compare each system with different fuel. Therefore, operating conditions and BoPs designs are not optimized, so each system performance for each fuel may increase with appropriate system design. This optimization will be done in further study. Figure 1

Design of air conditioner (AC) system simulator on cars to improve student competence

The purpose of this study is to design a simulator for a car air conditioning system as a learning medium, so that the learning objectives can be achieved properly and in accordance with the expected competencies. This design uses an electric motor drive to drive the AC system compressor so that it is easier to operate and does not produce air pollution and is made with a design that can be moved easily by having sturdy wheels. The electric motor is also equipped with an inverter that can adjust the rotation of the motor as in the conditions of a real car engine. This research model uses Research and Development which includes the stages: problem analysis, seeking information, designing a model, validating the design, evaluating the model, testing the model, revising the model, wider testing, finalizing the design. The results obtained are the creation of an AC simulator that has been validated by experts in terms of media and material in the very feasible category, then from the user side with 25 respondents giving a value in the very feasible category for use in learning. The increase in competency occurred by 23.90% with a comparison of the pretest value with the posttest value.

IDENTIFICATION OF LEAD (Pb) IN WATER SPINACH (Ipomoea aquatica forsk) IN PALLEKO SUB-DISTRICT NORTH POLONGBANGKENG TAKALAR REGENCY

The sugar factory located in Palleko Village can produce air pollution and waste which is suspected to pollute the environment and waters. Environmental pollution in the form of lead metal can contaminate water and soil around industrial plants. Environmental pollution in water is thought to be higher than on land because it is polluted from mining processes and industrial waste. Lead metal is thought to be able to contaminate plants in water, for example kale, which is a mediator of the spread of heavy metals in living things due to the entry of these metals into plants through roots and leaf mouths (stomata). Water spinach that grows around industrial factories is at risk of being exposed to pollutant substances such as lead (Pb). Lead consumed can cause symptoms of chronic poisoning, paralysis, can affect the circulatory system, nervous system, urinary system. This study aims to identify lead (Pb) in water spinach (Ipomoea aquatica forsk) in Palleko Village, North Polongbangkeng District, Takalar Regency. This research was conducted by laboratory observation with purposive sampling technique using the color reaction test as many as 9 samples. The results showed that of the 9 samples of water spinach (Ipomoea aquatica forsk) examined, the results were all negative for lead metal. it was concluded that water spinach does not contain lead so it is safe for consumption according to the Decree of the Director General of Drug and Food Control Number 03725/B/SK/VII/89 concerning the maximum limit of metal contamination in food is 2.0 mg/kg.

Analisis Kualitas Udara Pada Rumah Warga Terhadap Parameter Bakteri dan Jamur

The final processing and disposal the waste occurs at the Final Disposal Facility (TPA). Because the rubbish heaps include a variety of contaminants and produce air pollution, landfills can have an impact on the environment's quality. This study intends to identify and contrast the outcomes of the analysis of the air quality in residents' homes near the Piyungan TPA location, which is 50 m, 350 m, 650 m, and 1000 m from the TPA, with quality standards according to the Decision of the Minister of Health No. 1077 of 2011 based on bacterial and fungal parameters. The ideal distance between residential areas and the TPA location is another goal of this study. Air sampling at each location used the air sampling method directly with NA media and PDA media in petri dishes. The results showed that the number of bacterial colonies at a distance of 50 m was 4,485.6 CFU m-3 and the fungal colonies were 2,306.4 CFU m-3. At a distance of 350 m, the number of bacterial colonies was 3,355.4 CFU m-3 and fungal colonies were 2,130.9 CFU m-3. The number of bacterial colonies at a distance of 650 m was 2,919.7 CFU m-3 and the number of fungal colonies was 2,001.3 CFU m-3. The number of bacterial colonies at a distance of 1000 m was 1,353.2 CFU m-3 and the number of fungal colonies was 765.2 CFU m-3. Air quality in residents' homes with a distance of 50 m to 1000 m does not meet the healthy air quality requirements based on Minister of Health Regulation No. 1077 of 2011 concerning Indoor Air Conditioning at Home with maximum levels of airborne microbes &lt;700 CFU m-3.

Pemilihan Pemasok Baterai Forklift Elektrik dengan Menggunakan Metode AHP dan TOPSIS di Industri Manufaktur Otomotif

The activity of the automotive manufacturing industry continues to increase. The selection of electric forklift battery suppliers needs to be done because they are environmentally friendly and do not produce air pollution. Supplier selection is very important in determining the speed of delivery and the quality of raw materials to be able to meet consumer demands quickly and with quality. The purpose of this research is to select the best battery supplier and in accordance with the company's qualifications. The method used in completing this research is the Analytical Hierarchy Process (AHP) and Technique for Others Reference by Similarity to Ideal Solution (TOPSIS) in assisting decision-making. The AHP method is used to determine the most dominant criterion with a pairwise comparison matrix to determine the weight. Then the weight value is used as input in the calculation of the TOPSIS method to determine the ranking. The contribution of this research can be applied in the automotive manufacturing industry in selecting electric forklift battery suppliers. Based on the calculation results, it is known that the price criterion is the most dominant criterion with a weight of 0.463. Price is a parameter that is often used by every company. In addition to price criteria, there are also important criteria, including service life 0.270, quality 0.144, service 0.079, and flexibility 0.044. Based on TOPSIS calculations, it is known that the Rocket supplier is ranked 1st and is a priority to become a supplier in the selection of forklift batteries in the automotive manufacturing industry.

Segregation in US linked with pollution toxicity

Exposure to fine particulate air pollution (PM 2.5 ) is a leading cause of death and disease around the world . In the US, race and ethnicity are associated with disparities in people’s exposures. Now, researchers have shown that these disparities are tied not just to demographic differences but to racial segregation. Non-Hispanic Black people living in the most highly segregated places are exposed to more total air pollution than non-Hispanic White people in nearby neighborhoods. What’s more, the PM 2.5 they breathe contains 10 times the concentrations of toxic and carcinogenic metals, including lead ( Nat. Commun. 2022, DOI: 10.1038/s41467-022-33372-z ). Due to a history of racist laws and housing development practices, many US cities are segregated. Highways and factories that produce air pollution are more likely to be located in predominantly Black neighborhoods , says Colorado State University engineer John K. Kodros. He and his team drew on

Assessment of the Spatial Distribution of Carbondioxide Pollution Emitted by Cement Industry Located in Sagamu, Nigeria

Cement factory produces air pollutants that contaminate and cause adverse effects on the health of dwellers of the affected environment. These pollutants enter the body and become injurious by initiating or aggravating problems in the respiratory, circulatory and nervous systems. During the production of cement, many processes like crushing, raw milling, calcining, burning and cements milling, release pollutants to the immediate environment. This study aimed at estimating the discharge rate of carbon dioxide (CO2) pollutant emitted from the production/combustion unit of Lafarge Cement Factory Sagamu Ogun State. Six points on each of the three major routes that lead to the factory were used as the sampling points for the study. Gaussian plume model method was applied in developing the model equation. Raw data obtained from the field was used to determine the spread of CO2 concentration. The study showed that there were emissions of CO2 within the study area, with an average monthly highest discharge rate of 773.333 ppm on Ikorodu route, and the lowest discharge rate on Abeokuta route (689.875 ppm). Consequently, the findings can be used to formulate and validate models as well as develop co-correlation among the three routes in the study area.

IOT Based Air Pollution Monitoring System using Raspberry Pi

IOT which means Internet of Things is a highly distributed network of smart devices. Every smart device is embedded with an electronic sensors, softwares and other technologies. The word “Things” means the one who is able to connect as well as exchange the data with other devices and systems over an internet, which are embedded with sensors, softwares and other technologies. Now a days air pollution is increasing day by day. The factors which produce air pollution are industrialization, increase in population, urbanization and so on. As the air pollution is increasing rapidly, it has become a major concern to work on. So we have tried to design and implement this project to detect the amount of gases present in air to reduce air pollution.

Prediction of Carbon Monoxide Concentration with Variation of Support Vector Regression Kernel Parameter Value

Human and industrial activities produce air pollutants that can cause a decline in air quality. In urban areas, transportation activities are the main source of air pollution. One of the emitted air pollutants produced by transportation is carbon monoxide (CO). The understanding of CO concentration is crucial since its overabundance beyond a certain limit will have a negative impact on human health and the environment. In this study, the support vector regression (SVR) method was used to predict CO concentration. The purpose of this study was to predict the hourly CO concentration in the Ujung Berung district, Bandung City, West Java, Indonesia with optimal prediction accuracy. An experiment was carried out by modeling the CO concentration with varying kernel parameter values to obtain accurate prediction results. The suitability of the values between error (ɛ), a trade-off constant (C), and variation mismatch (γ) is vital to obtain optimal prediction results. The results showed that the best prediction accuracy value was 97.68% with kernel parameter values ɛ = 0.02, γ = 30, and C = 0.006. These results may lead to proper decision making on environmental issues and can improve air pollution control strategies.

Associations between residential proximity to oil and gas extraction and hypertensive conditions during pregnancy: a difference-in-differences analysis in Texas, 1996-2009.

Oil and gas extraction produces air pollutants that are associated with increased risks of hypertension. To date, no study has examined residential proximity to oil and gas extraction and hypertensive conditions during pregnancy. This study quantifies associations between residential proximity to oil and gas development on gestational hypertension and eclampsia. We utilized a population-based retrospective birth cohort in Texas (1996-2009), where mothers reside <10 km from an active or future drilling site (n = 2 845 144.) Using full-address data, we linked each maternal residence at delivery to assign exposure and evaluate this exposure with respect to gestational hypertension and eclampsia. In a difference-in-differences framework, we model the interaction between maternal health before (unexposed) or after (exposed) the start of drilling activity (exposed) and residential proximity near (0-1, >1-2 or >2-3 km) or far (≥3-10 km) from an active or future drilling site. Among pregnant women residing 0-1 km from an active oil or gas extraction site, we estimate 5% increased odds of gestational hypertension [95% confidence interval (CI): 1.00, 1.10] and 26% increased odds of eclampsia (95% CI: 1.05, 1.51) in adjusted models. This association dissipates in the 1- to 3-km buffer zones. In restricted models, we find elevated odds ratios among maternal ages ≤35 years at delivery, maternal non-Hispanic White race, ≥30 lbs gained during pregnancy, nulliparous mothers and maternal educational attainment beyond high school. Living within 1 km of an oil or gas extraction site during pregnancy is associated with increased odds of hypertensive conditions during pregnancy.

THE IMPACT OF FINANCIAL DEVELOPMENT ON DECARBONIZATION FACTORS OF CARBON EMISSIONS: A GLOBAL PERSPECTIVE

In order to limit the adverse effects of climate change, the carbon dioxide emissions should be controlled. These toxic emissions are associated with the energy sector like coal, oil, natural gas, which produce air pollution and it has to be reduced. Reductions can be brought about by using appropriate technologies and policy initiatives. Financial development has been an important factor, which influences the decision on carbon emissions. This study attempts to study the relationship between financial development and carbon emissions, based on the least square of NLS and ARMA method and the data, based on 10 developed countries and five developing countries, during the study period of 10 years from 1st April 2010 to 31st March 2019. The study employed the Kaya identity IPAT model, unit root test and co-integration test. The variables of GDP per capita and carbon dioxide (CO2) emissions were used as a measure of economic financial development and the status of environmental degradation.Keywords: Carbon dioxide emissions, Financial development, Urbanization, GDP per capita, Climate change, STIRPAT model.JEL Classifications: P44, Q40, Q48, Q54DOI: https://doi.org/10.32479/ijeep.11872

Economic, environmental and grid-resilience benefits of converting diesel trains to battery-electric

Nearly all US locomotives are propelled by diesel-electric drives, which emit 35 million tonnes of CO2 and produce air pollution causing about 1,000 premature deaths annually, accounting for approximately US$6.5 billion in annual health damage costs. Improved battery technology plus access to cheap renewable electricity open the possibility of battery-electric rail. Here we show that a 241-km range can be achieved using a single standard boxcar equipped with a 14-MWh battery and inverter, while consuming half the energy consumed by diesel trains. At near-future battery prices, battery-electric trains can achieve parity with diesel-electric trains if environmental costs are included or if rail companies can access wholesale electricity prices and achieve 40% use of fast-charging infrastructure. Accounting for reduced criteria air pollutants and CO2 emissions, switching to battery-electric propulsion would save the US freight rail sector US$94 billion over 20 years.

A CRITICALITY OF THORIUM FUEL IN FAST REACTORS NUCLEAR POWER PLANT

Nuclear energy is an alternative energy that has advantages in the amount of energy it produces, the fuel it uses, and does not produce air pollution. Thorium is one of the fertile nuclear fuels which is abundant, which is four times more than the amount of uranium. Calculation of criticality of fast reactor design using thorium nitride (ThN) fuel using a set of SRAC programs that produce critical conditions for the enrichment of uranium-233 by 5% with excess reactivity value of 0.044% in volume fraction of 65% fuel, 10% cladding and 25% coolant. Thorium fuel can be used as nuclear fuel for nuclear power plants with a burnup time of 50 years.