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The demand for cement has grown due to the rapid growth of the building sector. Cement manufacture, on the other hand, produces more greenhouse gases and carbon dioxide. As a result, different construction materials must be sought. Paper pulp is made from waste from the paper industry. Every year, the paper industry consumed a significant amount of land in the surrounding area. Some wastes are thrown on land as a disposal method, while some businesses burn their industrial waste in incinerators, causing serious air pollution issues. The impact of employing paper pulp and crushed stone dust as partial replacements in concrete is discussed in this study. The advantages of using paper pulp with crushed stone are explored in this study. Furthermore, this research presents the findings of an experimental inquiry for M35 grade concrete employing wastepaper as an extra ingredient in concrete mixes for housing projects. [ABSTRACT FROM AUTHOR]

Climate change has become an important issue since 196 countries in the world agreed to sign the Paris Agreement at COP21 in 2015. This is an important issue because Climate change has a wider impact in the long term such as rising air temperatures, increasing volume of sea water, extreme and unpredictable weather changes, shifting populations and wildlife habitats and affecting human health. One of the causes of climate change is air pollution produced by burning conventional vehicles or we can call Internal Combustion Engine (ICE). For this reason, various countries in the world are innovating by converting fossil-based vehicles into electric vehicles with the main raw material being batteries. As a result, several countries in the world such as Japan, Brazil, Germany, France and Sweden have succeeded in reducing their emission levels in the 2015-2018 period by starting to develop electric vehicles. This paper was conducted through literature study and in-depth analysis using qualitative research methods. This paper aims to analyze whether the transformation from an internal combustion engine-based vehicle to an electric vehicle is able to reduce the level of emissions in a country in order to overcome the problem of climate change. In addition, this paper also analyzes other supporting factors to find the right solution to overcome the problem of climate change. [ABSTRACT FROM AUTHOR]

The impact of construction activities on the environment has become a significant global concern due to the environmental degradation caused by the development of construction projects and activities. Noise pollution, water pollution, and air pollution are some of the types of pollution caused by construction activities, which can lead to serious health and environmental consequences. This review paper aims to examine the various types of pollution that occur during different construction activities in construction projects. In addition, this paper also focuses on the impact of concrete batching plant operations on the environment and the techniques that can be used to minimize these impacts. Concrete batching plants have been identified as one of the significant contributors to environmental pollution due to the dust, noise, and exhaust emissions generated during their operation. This paper highlights the importance of adopting appropriate pollution control measures to minimize the impact of concrete batching plant operations on the environment. Furthermore, the paper emphasizes the need to provide a better working environment for onsite workers and minimize the health impact on nearby communities. The use of advanced technologies and eco-friendly practices can contribute significantly to reducing the impact of construction activities on the environment. Overall, this paper provides valuable insights into the impact of construction activities on the environment and highlights the importance of adopting sustainable practices in the construction industry to protect the environment and promote a healthier and safer living environment. [ABSTRACT FROM AUTHOR]

This paper sheds light on the problems related database collection or selection in machine learning. It emphasizes on various aspects of database collection and issues one can get into while performing the collection procedure. It then discusses the second alternative method of using a premade database and how it could be an equally challenging issue, sometimes even worse. It concludes by a study of an air pollution database created in 2015 in.the state of Orissa, India which has over two thousand entries and applies different regression algorithms available analyzing the drawbacks of having data which is dense but limited to a particular location and time. This is followed by some methods through which the issues could be solved and emphasizes on the need for the issues to be solved and lack of databases in general. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic affected everyone's life in every aspect. World Health Organization declared it as global emergency in March 2020 which leads to halt all the human activity around the world. While this pandemic was hazardous for human beings the nature was nourishing itself and seems to be on reset as the Pollution decreased due to this pandemic. In countries like China, Italy, USA and many more which initiated the lockdown in their countries to avoid the spread of this deadly virus has shown the reduction of air pollution. The emission of air pollutants were reduced due the lockdowns in many countries. In the paper different types of environmental pollution, their reasons and effects on nature are discussed and also the impact of COVID-19 pandemic on environment is discussed. [ABSTRACT FROM AUTHOR]

Traditional automobiles utilize fossil fuels to ensure good performance and long reach. Here the major issue is the exhaustion of fossil fuels resources on the Earth, and the issue of atmospheric pollution due to motor vehicles, this motivates to look for replacement energy to propel the vehicle. One of the effective ways to propel the vehicles is by introducing the electric motor and battery to run the electric motor. An extensive database of passenger electric vehicles compiled by IDTechEx is further used to determine trends in battery packs and cell energy density, energy capacity, cell geometry, cell chemistry size, thermal management strategy, engine technology and power output, resulting in a comprehensive set of in-kind claims and market value projections. IDTechEx predicts more than 28 materials used in the construction of electric vehicle powertrains, each with varying market shares. Several material markets are seeing a rapid increase in demand after a small decline in 2020 due to the impact of COVID-19 on the automotive market. This paper thoroughly demonstrates the effective use of computer modelling and simulation software used in contemporary manufacturing industry at preliminary stage for evaluation of vehicle performance requirements about the design and techniques utilized. While most of the papers demonstrate the Electric vehicle simulation for four-wheelers, the two wheelers are not thoroughly researched for Indian market, this paper covers the primary parameters of two-wheeler electric vehicle simulation that uses the basic blocks from Simulink, Simscape, and electrical blocks available in the MATLAB. [ABSTRACT FROM AUTHOR]

Due to the increase in CO2 emissions as a pollutant, irreversible damages are inflicted on humans and environment. Therefore, policies must be implemented to control and reduce CO2 emissions. Analysis and forecasting of CO2 emission is a crucial subject for determining suitable policies. The aim of this paper is to use grey system theory for predicting the CO2 emissions. The factors oil, gas and coal burning are considered as the inputs that affect the CO2 emissions. The GM(1,4) model is used for predicting CO2 emissions. The effect of each item in the CO2 emissions is investigated. A fitting polynomial function with weighted data is proposed for evaluating CO2 emissions in different situations. This is essential for selecting the most appropriate policy scenario to reduce air pollution. Numerical results show that the method is robust and accurate. [ABSTRACT FROM AUTHOR]

The paper analyzes the meteorological conditions in the city of Krasnoyarsk during the period of unfavorable meteorological conditions from February 14 to 18, 2020. The relationship between the pollution of the city's atmosphere by suspended solid particles and the formation of a temperature inversion –an increase in temperature with altitude in the surface layer of the atmosphere is investigated. The paper uses data from the reanalysis of the NCEP GFS weather forecast model on the air temperature on 9 isobaric surfaces (1000-700 Mb) and the height of the atmospheric boundary layer. The regional air monitoring system provides measurements of suspended particulate matter PM2.5 concentrations and wind speed data. The results obtained allow us to conclude that there is a high degree of correlation between these parameters. The possibility of using GFS data in the analysis of meteorological conditions of the lower layer of the atmosphere and periods of its pollution, forecasting the aggravation of the environmental situation in the city is shown. [ABSTRACT FROM AUTHOR]

Solar power generation is most clean form of generation among all type of generation. Hence is gaining the first choice of the electricity generating authority all over the world. Still, it is under research and development stage. Solar cell has very low efficiency and due to above facts, these efficiency decreases which ultimately effects the power generation. Mono crystalline solar panels are made up of pure crystal silicon in which there are more mobility for electrons to move hence the efficiency of such panels are more as compared to poly crystalline panels. Moreover, the dimensions area for these panels is near about same. In this paper effect of pollution and incidence angle of solar panels along with temperature and fill factor on roof top systems by using mono crystalline panels are discussed. The panel has significantly reduction in cost since the year 2021. While calculating the power generation of solar roof top power plant, there are some points are to be considered. a) Total energy required or utilizes by load, b) Power Backup required for how many numbers of hours, c) Future expansion of load in coming few years. According to that technical analysis are done. While installing solar roof top system these points are also consider, p) Incident Angle, q) Pollution level of the area in last 5 to 10 year and other point like future expansion of load in coming next 20-year, Available space for roof top, Total shadow free area, Type of roof available at premise, longitude and latitude location of premises, Total sunny days available in that location, Air density and air pollution, Optimum temperature of location. [ABSTRACT FROM AUTHOR]

The current research intends Multiplication of pollution in the atmosphere and the limited amount of conventional fuels coined the topic of analysis and development in the field of clean and long-lasting alternative fuels like hydrogen (H2) for internal combustion engines. The favorable properties like its wide flammability, carbon free and fast flame speed make it the best option for IC engines. But due to its low density, there is a requirement for large space makes it impossible for transportation. This problem can be overcome by blending it with high density fuel. Today the blending biodiesel is trending in the research of alternative fuel. This paper gives the outline of current R&D on hydrogen and microalgae biodiesel fuel blend in IC engines and the scope of hydrogen fuel blending with third-generation biofuel microalgae biodiesel to overcome its unfavorable properties. This review focus on watching the characteristics of IC engine when microalgae biodiesel and hydrogen as fuel will be utilized independently. [ABSTRACT FROM AUTHOR]

Environmental and health issues have risen as living conditions and economic growth have improved. The haze weather phenomenon is becoming a serious problem as air quality continues to deteriorate. It has been discovered that there is a possible connection or causal relationship between exposure to air pollution and neurological diseases. The haze weather phenomenon is integrated into fog as an extreme weather warning in many geographical areas. The design and implementation of an embedded multisensory system for air pollution and air quality monitoring with disease prevention warnings and alarms is presented in this paper. This device is made up of a microcontroller and various sensors formeasuring gases in the atmosphere. This system also includes a model to predict diseases in a more efficient way other than the present conventional methods. More-over an immediate alert system is also included with display and enables data collection of these sensors for future machine learning and artificial intelligence systems. [ABSTRACT FROM AUTHOR]

Air pollution is the major level of environmental pollution which affects all the living beings health and atmospheric condition. In which it is a major challenging issue today's scenario. Air pollution leads to adverse effects on climate, ecosystem and living things including human, animals and plants etc,. The Atmospheric air is getting polluted by the industry, power plants, vehicle emission and many sources releasing the unwanted toxic, harmful gases and particulate matter into the atmosphere. This Particulate matter is one of the major sources for the contribution of increase in air pollution in the atmosphere. Such particulate matters create a serious requirement for monitoring, measuring and analysis of real-time air quality condition in order that appropriate resolutions are often taken during a period of time. This paper presents a real-time standalone solution for monitoring the air pollution level which includes various parameters: PM (Particulate Matters) 2.5, CO (Carbon Monoxide), CO2 (Carbon dioxide), air pressure, humidity and atmospheric temperature. The Internet of Things (IoT) is plays vital role in monitoring the pollution level in the atmosphere. IoT mingle with cloud computing gives a completely unique way for management of data from different sensors were collected and transmitted to the low power, a low-cost ARM Processor which act as a minicomputer based on Raspberry pi all the input from the various sensors are combined and compared to the standard level, when the variation is more than the standard it will inform the individual and also alert the user. Pollution in India has been increasing year by year and most of the states are suffering severely from it. So this system monitors pollution and updates pollution levels from all over the areas within the city in a real-time manner. [ABSTRACT FROM AUTHOR]

In recent times, due to the increase in air pollution and its impact on the everyone's health and environment; it has become a very tedious task to monitor and check the air quality. Predicting the air quality is a highly tangled task due to the volatility, particle nature and variables constituting the pollutants. It has become pertinent to check the air quality in rural/urban areas due to the impact it has on people's health and the environment. In this paper, we first do comparative analysis of popular ML(machine learning) method, linear regression, random forest, XGBoost decision tree, k-nearest neighbors (KNN), and L1 and L2 regularization for forecasting pollutant and particulate levels and also the air quality index (AQI) is predicted. Then we apply cross validation and grid search to optimize our random forest model. Finally, we predict the model with Long short-term memory (LSTM). [ABSTRACT FROM AUTHOR]

This paper hypothesizes on how Hulhumale' and its citizens can be encouraged to develop healthier lifestyles and environment by incorporating bicycle culture via bicycle sharing system throughout the city. The environment of Hulhumale' is pleasant and green, with some flaws including increasing noise and air pollution which could be potentially reduced through the implementation of a bicycle system. A study showed that the citizens there were not particularly unhealthy. However, city life revolves so much around sedentary work, causing extreme limitation of daily physical activity. Further ideas are also explored about how a bicycle system can be a practical and efficient way of increasing health levels. While the current most commonly used method of travel is by motorcycle, concepts revolving around bicycle sharing systems and the usage of bicycles in general were taken excellently by the community. [ABSTRACT FROM AUTHOR]

The palm oil industry is one of the most important agro-based industries in Malaysia, with more than 400 palm oil mills nationwide. These mills are generally self-sustained in energy by converting empty fruit bunch (EFB), palm mesocarp fibre (PMF) and palm kernel shell (PKS), into energy. However, palm fuel burned in boilers have caused severe air pollution problems due to improper boiler operation and inefficient air pollution control systems. This results in emission of bottom ash particulates from multicyclone and electrostatic precipitator (ESP) hopper after combustion. This paper discusses the characteristics of palm fuel, namely PMF, PKS and EFB, based on proximate analysis, gross calorific value, ultimate analysis and element composition. Morphology of bottom ash emitted from multicyclone and ESP was also examined using scanning electron microscope (SEM). EFB was found to have the ' highest moisture content of 63.1% among others, while mixture of PMF and PKS had the highest volatile matter of 54.5% and fixed carbon of 18.5%. PMF has the highest calorific value of 2993 kcals/kg among others. The bottom ash from multicyclone and ESP exhibited particulate sizes ranging from 18.4 to 68 µm and 10.9 to 44.6 µm, respectively. These were considered as preliminary results which require further future research. The outcomes of this study are useful for mitigation of fine particulate emission from air pollution control system in the palm oil mill. [ABSTRACT FROM AUTHOR]

Construction industry as one of the sectors that causes climate change must start paying attention to environmental impacts. Through the provision of numerous ecosystem services, Green infrastructure (GI) is one of the essential strategies for achieving sustainable development since it can effectively coordinate social, economic, and environmental growth. Thus, GI has been highlighted as a promising strategy to aid cities in adapting to climate change. 197 papers published between 2016 and 2021 were organized and classified using the 7th version of Publish or Perish software as part of this study's literature review methodology. Results show that there has been a significant growth in research on green infrastructure in recent years, with Sustainability Journal dominating the field. The initial top three cited journals that cover GI research are China Earth Sciences, Construction & Building Materials, and Cities. Another set of findings reveals that issues with water, materials, heat, air pollution, and policies-regulation & cost have been particularly focused on. Future research is needed and quite promising, such as: green materials, solutions to water & flood problems, urban heat, and GI regulation are topics that need further research, especially in Indonesia. [ABSTRACT FROM AUTHOR]

Emission-free economy is an achievable target with the formulation of policies by the Governments around the globe. A major contribution is made by the transport industry. Delhi is one of the examples among the cities in India which is polluting the air by transportation which is about 20 percent. Towards achieving the Sustainable Development Goals, the nation has to take a different trajectory from concentrating on the technical aspect of reducing the hazardous emissions to refining the regulatory awareness. The research study is based on the statistical inputs provided by the government agencies and the judicial verdicts seeking a pollution free atmosphere. The Judiciary has been proactively recommending and directing the respective government to take necessary action towards controlling the pollution caused due to road transport. Nevertheless, the use of Artificial Intelligence has been an area which has not been strongly recommended by the apex court. The regulatory and judicial control over the emissions is towards a penalizing perspective and the technological assistance has not been resorted to. Though a one hundred percent emission-free economy is not a possibility, the areas which are still not explored or have not been brought under the purview of consideration have been the scope of study in the research paper. [ABSTRACT FROM AUTHOR]

Commercial areas consider a center of attraction for large numbers of citizens for the purpose of shopping and trade exchange, and thus traffic increases in commercial areas. The commercial areas are among the most places in city centers that suffer from traffic congestion, and consequently, the burning of motor fuels. In this paper, air pollution resulting from crowded and irregular traffic in the main commercial center of Al-Diwaniyah city in southern Iraq was studied. It covered an area of 4 km2 for the emission and spread of air pollutants resulting from traffic movement. Air pollution tests for particle matter, gases, and atmospheric measurements were conducted during the year 2021 using the air pollution monitoring system. Field measurements of air pollutants were compared with a mathematical model for the purpose of calibrating and adopting it in the future prediction of the spread of pollutants according to traffic movement and according to geometry designs for roads, and the change in the vehicles number, vehicles types and speed of different transportation. the results of air pollution was compared with WHO limitation. The results showed a significant increase in the air pollution quality index (AQI), reaching 300, and it is considered among the dangerous areas for this indicator. The results showed a match of up to 98% between the results of the mathematical model and the field measurements. [ABSTRACT FROM AUTHOR]

The utilization of bio-briquette fuel for rural kitchens would reduce dependence on firewood and, subsequently, air pollution. To fabricate bio-briquettes from biomass, it is necessary to pay attention to the basic properties of the materials used in order to understand their potential as a fuel. This paper particularly examines the basic characteristics of rice husk biomass waste in terms of its physical and chemical properties as a first step to determine its potential as a bio-briquette material. The results showed that the physical properties of rice husks are dominated by volatile matter 61.18 wt.%, indicating an excellent fuel reactivity during devolatilization. The calorific value of 14.63 MJ/kg was observed, indicating that the energy that would be released during the combustion process would be sufficient. The chemical characteristics of rice husk showed that the carbon, oxygen, sulfur, nitrogen, and hydrogen content were 35.85; 31.22; 0.12; 0.98, and 5.75 wt.%, respectively. Rice husk is dominated by C and O elements that are believed to be able to effectively contribute to increasing fuel volatility. [ABSTRACT FROM AUTHOR]

Air pollution is one of the main factors causing adverse health effects, such as cardiovascular disease, morbidity, and even mortality to humans. In the urban environment, transport is known to be the primary source of air pollution. This paper aims to assess people awareness of air pollution in open public spaces by investigating the relationship between people's dwell time and traffic-induced pollution at sidewalk café/restaurant. First, air pollution was analysed by descriptive statistics. Next, correlation and multivariate analysis were used to seek the relations between traffic, air pollution, and dwell time. The results show that pollution level doesn't significantly influence people duration of stay, but traffic does. It portrays the unawareness of people towards air quality in their surroundings. Furthermore, the unexpected result found in this study is that there are other significant pollution sources such as from cooking and smoking activities. Therefore, policies to improve air quality in urban areas are highly needed from the transport sector and eventually beyond it. [ABSTRACT FROM AUTHOR]

Sustainability issues are the primary concern of the Padang City nowadays. With an annual traffic growth reaching 10% at some main roads, Padang should be aware of the air pollution and congestion problems. Therefore, the "Cycle to Work" policy would be promoted to enhance the sustainability of the city. "Cycle to Work" was chosen because, many informal cycling enthusiast groups were voluntarily established in the society, recently. With many towns people getting used to cycling, it is expected that the "Cycle to Work" Policy will work well in Padang. This paper assesses the requirement for infrastructure to support the "Cycle to Work" policy based on Bicyclist Enthusiasts in Padang. A Likert-type questionnaire was distributed to 300 members of cycling enthusiast groups around the city. The respondents were asked to show their preferences about "Cycle to Work" policy concerning situation and condition when the cycling about to conduct, including the weather, number of luggage, body fit, security, the existence of cycle line infrastructures. Data were analysed using structural equation model (SEM). The study found that most of the respondents are happy with the policy and will support it and encourage more people to do it. [ABSTRACT FROM AUTHOR]

Lung disease refers to a disorder of the lungs that affects the organs to breathe. Respiratory problems caused by lung disease can prevent the body from getting the oxygen it needs. Some lung diseases can lead to respiratory failure. Respiratory diseases can be caused by infections, tobacco smoking, air pollution, and more. Recently, the deadly corona virus was added to this list. Respiratory problems caused by lung disease can be severe enough to require hospital treatment, even with oxygen or a ventilator and sometimes even causing death. This paper analyzes different approaches to image-based machine learning technique with different classifiers to predict various diseases and their effectiveness. [ABSTRACT FROM AUTHOR]

Sustainability, environmental sustainability, and sustainable transportation are all attracting attention currently, and the importance of sustainable transportation due to its effects on both the environment and society are now well acknowledged. However, although there has been an increasing number of projects and measures addressing sustainable mobility issues emerging in recent years, it can be difficult to compare outcomes, as there is not yet a set of globally applicable tools and indicators to guarantee comprehensive evaluation and to ensure the reliability of best practices. Maintaining sustainability is always a challenge, leading to this paper examining previous studies in detail to create a systematic overview of relevant and scientifically sound indicators for various aspects of sustainable mobility applicable in a range of social and economic contexts globally, particularly in terms of sustainability indicators for urban roads such as degree of congestion, traffic noise pollution, and traffic air pollution. This is important, as identifying such sustainability indicators is a significant factor in developing appropriate transport plans for any city. [ABSTRACT FROM AUTHOR]

Nowadays the world is largely dependent on conventional energy sources which are non-renewable and its demand is increasing day by day. The emission due to utilization of these energy resources causes air pollution and human disease. So researchers are focusing their attention on biodiesel as an alternative to diesel. Biodiesel while being renewable, environment friendly, has poor performance and higher NOx emission. To eliminate these problems up to some extent, blending with diesel can be done but increasing blending percentage again causes the same problem. To eliminate these demerits of biodiesel researchers are using nano sized particles as additives to biodiesel. A large number of nanoparticles are used as additives and resulted in improved performance and emissions, viz. increased "brake thermal efficiency", reduced "brake specific fuel consumption" (bsfc), lower release of Hydrocarbon (HC) and Carbon monoxide (CO) etc. Apart from poor performance, higher NOx release is the main concern with the use of biodiesel. Some nanoparticles reduce NOx emission while use of some other nanoparticles result in increased NOx emission. NOx emission varies with the concentration of nano particle as well. This paper reviews the research work in which nanoparticles such as CeO2, TiO2, GO, CaO, Al2O3, Bi2O3, SiO2, ZnO, NiO, Ag-O, CNT, MWCNT, nano water emulsion as well as combination of these nano sized particles have been used as additives to biodiesel or biodiesel blends. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are developing rapidly due to various factors, such as the climate and envi-ronment changes, reduction in prices comparing with conventional vehicles, due to the problems caused by gas-oline engines on the people as well as the environment. The automotive industry has changed to the EVs. EVs play a major role in reducing the emissions caused by the greenhouse gases which automatically leads to the reduction of air pollution. However, to enable the change from the traditional source of energy to fully EV powered motors, a new problem has emerged in society. The method of using electricity as a source of fuel is not a cheap task. It falls out of technology and infrastructure to support it as a primary source, infrastructure that is not available even in developed countries. EVs offer many benefits such as reducing pollution levels and oil imports bills etc. This paper offers reviews on electric vehicle mileage compiles and threats in promot-ing EVs. It also describes opportunities and challenges ahead in electric vehicles. [ABSTRACT FROM AUTHOR]

Traffic congestion increase on highways (especially at intersections) represents one of the main problems causing situation hazards, traffic problems, and air pollution, these issues generally lead to failure or approximately to, in traffic structures and other infrastructures. This research is a part of a study trail to enhance and assess the level of service and traffic efficiency of a signalized intersection, named Al-Salam intersection, which is the only signalized one in Najaf city. Traffic volume had been collected for through, left, and right movements within morning and evening peak hours, that classified into passenger cars, heavy vehicles, buses, and motorcycles. Data were collected by video recording technique. SIDRA program had been dependent on evaluating Al-Salam intersection. SIDRA also can be utilized available development options and select suitable alternative. The primary analysis process results showed the intersection level of service (LOS E). This paper explains some strategies for enhancing the traffic flow and increasing the level of service, such as change No. of lanes in each approach, optimizing the cycle length, and eliminating some traffic directions by constructing over-bass or under bass. [ABSTRACT FROM AUTHOR]

In recent times, due to the increase in air pollution and its impact on the everyone's health and environment; it has become a very tedious task to monitor and check the quality of air. Predicting the quality of air is a highly tangled task due to the volatility, particle nature and variables constituting the pollutants. It has become pertinent to check the quality of air in rural/ urban areas due to the impact it has on people's well-being and the environment. In this paper, we first do comparative analysis of popular machine learning method, decision tree, linear regression, k-nearest neighbors (KNN), random forest, XGBoost and L1 and L2 regularization to forewarning pollutant and particulate levels and to forecast the air quality index (AQI). Then we apply cross validation and grid search to optimize our random forest model. Finally, we predict the model with Long short-term memory (LSTM). [ABSTRACT FROM AUTHOR]

The quality of air is very important to living beings on the earth. In this research paper, a model is developed for the ealuation of air quality called Adaptive Neuro-Fuzzy Inference System (ANFIS). The four air pollution variables: SO2, NO2, RSPM, and TSPM of Chennai city from 2006 to 2008 are used in the development of the ANFIS model. The implied model is reciprocated alongside the Indian air quality index (IAQI), and it is ascertained such so the implicate model resulted with acknowledging the legitimate prevision of air quality. [ABSTRACT FROM AUTHOR]

In this paper a study the sensitivity of concentration variations of some of the most dangerous air pollutants with respect to the anthropogenic emissions levels and with respect to some chemical reactions rates has been performed. Quasi-Monte Carlo algorithms based on Sobol, Faure, and different lattice rules are used in our sensitivity study of the Unified Danish Eulerian model. Different parts of the large amount of output data, produced by Unified Danish Eulerian model, were used in various practical applications, where the reliability of this data should be properly estimated. Another reason to choose this model as a case study here is its sophisticated chemical scheme, where all relevant chemical processes in the atmosphere are accurately represented. The numerical tests show that the stochastic algorithms under consideration, and especially the optimal lattice rule, are efficient for the multidimensional integrals under consideration and especially for computing small by value sensitivity indices. Clearly, the progress in the area of air pollution modeling, is closely connected with the progress in reliable algorithms for multidimensional integration. [ABSTRACT FROM AUTHOR]

The control object is the urban traffic of network of eight crossroad sections as a part of density populated area in Sofia. The goal is minimization of vehicle queue lengths in front of the junctions, which leads to faster driving, reducing the air and noise pollution and better ecological picture. The paper analyzes two types of modeling and optimizations, applied for the traffic control: classical optimization (one-level) and bi-level one. The bi-level optimization has the priority to co-ordinate the two-level hierarchical problem and to take into account the interconnections between the crossroad sections. It contains two goal functions, which are considered for the control process. The bi-level and classical one-level linear-quadratic optimizations are numerically applied for the traffic light control of urban network. The comparison gives preferences to the bi-level optimization, confirmed by numerical simulations. [ABSTRACT FROM AUTHOR]

Now a days, air pollution is a critical environmental issue in developing countries due to urbanization and industrialization. The pollution in air causes severe health issues for human beings, affects plants and animals due to acid rain, creates loss in economy, agricultural production and commercial production. In order to prevent or control it, the air quality forecasting necessitates. Accurate air quality prediction is a prominent task to be done to control the pollution level and to take countermeasures for securing the human life. The complex, uncertain and non-linear nature of the air quality pollutants impose complications in achieving accurate forecasting. The advent of artificial intelligence techniques helps to improve the air pollution forecasting results compared to traditional statistical methods at the great extent. This paper focuses the complications of air pollution, significance of air quality prediction, air quality index, and reviews the applications of machine learning and deep learning methods in air quality prediction. Literature shows that the machine learning and deep learning methods along with feature engineering and optimization techniques guarantees a promising air quality prediction. [ABSTRACT FROM AUTHOR]

Air pollution is a modern problem of high importance due to its negative impact on human health. The Organization for Economic Co-operation and Development (OECD) predicts that in 2050, air pollution will be the leading cause of environmental deaths worldwide. In addition, air pollution is classified as a major cause of cancer, related to the environment. In recent years, machine learning techniques have been used extensively to predict future values of time series. They can model nonlinear dependencies, allow the inclusion of large number of features and have weaker requirements than those of classical statistical methods. Fine particulate matter (PM) is the most common and major air pollutant in the city of Ruse, Bulgaria and is a serious problem for air quality. The paper examines the possibilities of the XGBoost method for forecasting the future values of the air pollutant PM10 in.the city of Ruse, Bulgaria. Data for the period 01.01.2015–31.03.2022 are used. The model includes the minimum and maximum daily air temperatures in Ruse for the period considered. The calculations are performed with the R programming language. [ABSTRACT FROM AUTHOR]

In December 2019, the outbreak of Covid-19 does cause a lot of serious issues, fatality, economic crisis, the rise of the unemployment rate, air pollution, and so on. This paper focuses on the impact of Covid-19 that relates to the long-lasting issue of air quality. The scope of this study is focused on the changing of air quality that occurred within the Movement Control Order (MCO) which was launched by the Malaysian government against Covid-19 spreading in Malaysia. Multiple reports suggest during the MCO period, the overall air quality in Malaysia was improved. However, when we just look into the history of air quality index (AQI) value without doing any further analysis, we can see there is no significant difference between the AQI value since the MCO was executed. Therefore, we need to understand how AQI value is obtained and compare available data before MCO is launched to the first three phases of MCO. This paper estimates the impact of MCO towards reduction of moving vehicles which can give impact to air quality in terms of 24-hours PM2.5 concentrations. Air quality index data have been analyzed by developed code using MATLAB. From the investigating and analyzing the data conducted, we found out the impact of MCO on the air quality in Malaysia is positive. [ABSTRACT FROM AUTHOR]

Jakarta is one of the world's cities with unhealthy air quality, even during a pandemic. Unhealthy air quality is caused by air pollution from various activities, including industry, transportation, offices, and housing. Unhealthy air quality can cause many problems such as health problems, decreased productivity, financial losses, family economic problems, and social problems. The public can obtain many benefits by knowing the daily air quality prediction. Among them is that they can make preparations to protect themselves when the air quality is unhealthy. This paper aims to predict monthly air quality categories based on five indicators, namely Particulate Matter 10 µg (PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Ozone (O3), and Carbon Monoxide (C.O.) using quadratic discriminant analysis. The model validation performance shows that discriminant analysis can predict the daily air quality category in Jakarta well. Performance measures the accuracy of 93.84%, the specificity of 96.80 %, the sensitivity of 90.41 %, the F1 score of 90.41 %, and the precision of 90.41 %. [ABSTRACT FROM AUTHOR]

The increase in construction density and disproportionate development in recent years of Moscow spurred the development of urban heat islands (UHI) and urban pollution islands (UPI). The impact of air pollution by hazardous substances from industries, transport, and utilities is currently the most dangerous form of natural environmental degradation in Moscow. Human activities inside the city cause urban pollution and heat gain on the urban surface layer. Since UHI and UPI can interact, exploring the synergism between urban heat and pollution is critical. This paper conducts a systematic review of the existing knowledge on the link between urban heat island (UHI) and urban pollution island (UPI). The results of determining the urban pollution island of Moscow by remote sensing image analysis are presented. The research results will contribute to developing an urban environmental assessment methodology based on the relationship of UHI and UPI and propose optimal solutions to reduce urban heat island (UHI) and urban pollution island (UPI) to improve the living environment within the city. The plan to develop a smart city should be focused on green space inside the city, playing a vital role in minimizing dust dispersion, contributing to air pollution reduction, and playing an active role in reducing urban surface temperature. [ABSTRACT FROM AUTHOR]

Impact of aircraft on the atmosphere studied specifically their effect as a source of air and water pollution and how they contribute to the transmission or spread of diseases such as Covid 19. Aircraft engines generate various gases like carbon dioxide (CO2), including around 70% of the exhaust, and water vapor (H2O), which provides about 30%. Lower than 1% of this exhaust is consists of pollutants such as oxides of nitrogen (NOx), sulfur oxides (SOx), monoxide of carbon (CO), and especially combusted or unburned hydrocarbons (HC), particulate matter (PM), and other components. In addition, many pollutants formed in combustion convert when they are emitted into the atmosphere. All these emissions are a significant source that contributes to environmental pollution. Also, in our current days, we notice the spread of Coronavirus significantly with the increasing cases of travel and movement between governorates and countries, which makes transportation in general one of the causes of its spread as this virus travels through the air and thus affects human health in a very negative way. Statistical analysis of the impact of aircraft on air and water pollution and the problems of COVID 19 have been investigated. With the rapid development of equipment and technologies used in airplanes, and therefore current-days, airport transmission has been widespread attention with a focus on social and economic well-being, environmental activity, and protection towards sustainability. [ABSTRACT FROM AUTHOR]

The article considers environmental innovations, defines their importance not only in terms of commercial effect, but also from the perspective of human values. Today environmental issues are the most acute. Pollution of the atmosphere, water resources, destruction of forests – all this speaks of the acute relevance of issues of conservation of natural resources, the irreparable loss of which may threaten the very existence of human civilization. Undoubtedly, everything new that science offers to solve this most important problem requires large financial resources, which are needed for the development of innovative products, their testing and large-scale implementation. Commercialization of investment goals is quite justified from the position of investors' interests, who determine the financial results of any realized projects as a priority. At the same time it should not be forgotten that today mankind, having embarked on the technocratic path of development and making technological breakthroughs in various production sectors, may face an insoluble problem of lack of clean air and potable water. This point of no return can be passed at any moment. To prevent such a development, the authors propose a methodology for evaluating innovations in the field of ecology in order to reorient the purely commercial investment interests on environmental issues, without prejudice to the financial aspects of the implementation of environmental projects. The work considers the methodology that will allow the investor to determine a more acceptable direction of investment, while respecting their financial interests. Eco-innovations are evaluated in terms of environmental, financial and social effects. The paper assesses their compliance with various criteria. For the analysis of factor weights, the method of hierarchy analysis was used, which in the conditions of this statement of the problem allows to determine the degree of importance of each type of environmental innovation from the position of the maximum cumulative effect. The method makes it possible to rank the priority of both individual types of environmental innovations and the criteria for their assessment. [ABSTRACT FROM AUTHOR]

An important way to protect public health is to forecast air quality by giving early warnings about air pollution. Management of air quality is highly dependent on data from time series collected at air monitoring stations. However, data input must be processed first in time series observations for several reasons, such as measurement errors, to prevent misleading results during forecast analysis. Data obtained from different measurements brings a degree of uncertainty that contributes to uncertainty in the data. Therefore, by constructing the Fuzzy Symmetry Triangular Fuzzy number data using the standard deviation and percentage error methods, the procedure for preparing data containing uncertain information is presented in this paper. ARIMA then uses the pre-processed data to create a predictive model. The findings of this study suggest that smaller prediction errors have resulted in the use of the proposed method to create fuzzy numbers for ARIMA. This implies that, with fewer prediction errors, the accuracy of the prediction model is higher. [ABSTRACT FROM AUTHOR]

The pollution of the atmosphere and the subsequent dire ramifications of emissions on the planet are prominent issues that the vast majority of people do not dispute, and a problem the scientific community is trying to mitigate. This paper presents a review of the regulations that the International Maritime Organization (IMO) has imposed for the reduction of air pollution and the various methods that have been developed for measuring the emissions of ships. Besides we propose an Internet of Ships concept that suggests the creation of a shipping network with the use of LPWAN technologies like LoRa for communications that operate automatically and collect data on air and marine pollution as well as marine geophysical measurements. Subsequently, we will examine how such a concept can be developed and what benefits can be procured in the process of environmental improvement by collecting such data. [ABSTRACT FROM AUTHOR]

The article discusses a JavaScript library for constructing isolines and isosurfaces based on the calculation of spatial interpolation using the inverse distance weighting method. It is intended for use as part of the geospatial web system client software. The structure of the software implementation of the library and its main modules are presented, and data on the speed of its operation is provided. The practical application of the development is primarily focused on solving the problems of building interactive web maps within the framework of software tools for operational environmental monitoring. A model for constructing maps of atmospheric air pollution with an adjustment for a digital terrain model is proposed. [ABSTRACT FROM AUTHOR]

A method for estimating the intensity of intermittent emissions of an atmospheric air pollutant from a point source is presented. Intensity parameters are calculated using time series (data) of pollutant concentrations recorded at the monitoring site. To estimate the transfer of pollutants from the source, a well-posed model of atmospheric dispersion and a model adjoint to it are formulated. Such dispersion models are used to establish relationships between intermittent emissions from the source and data. The parameter estimation method is formulated as a quadratic programming problem depending on the regularization parameter. The existence and uniqueness of a solution to this optimization problem are proved. Particular solutions of the dispersion model are used to establish the constraints of the quadratic programming problem. We emphasize the computational advantage of using adjoint functions to compute such solutions. One-dimensional synthetic numerical examples demonstrate the possibilities of the method for estimating the intensity of intermittent emissions. [ABSTRACT FROM AUTHOR]

With the increase in the population density, portability and industrial pursuit maintain at a stimulating rate, in the recent years, air pollution has acquired the surveillance of policy makers in both the urban and metropolitan areas. There is a frequent review in highly polluted cities concerning the growing mortality correlated with acute diseases whose consequences may be incensed owing to exposure to air contaminants. Forecasting environmental pollution is contemplated as an indispensable lead for timely warning and control management of environmental pollution, specifically in emergency circumstances, where large proportions of pollutants are immediately liberated in the air, bringing about substantial destructions. Predicting environmental pollution in such circumstances is distinctly demanding owing to numerous spatial aspects influencing environmental pollution. In this study, we propose a method called Bivariate Gibbs and Spatial Correlated Deep Prediction (BG-SCDP). The proposed BG-SCDC based on Bivariate Gibbs Aggregated Feature Selection algorithm and Spatial Correlated Deep Prediction for highly dynamic environmental prediction mining. First, meteorological big data dataset is provided as input to the Bivariate Gibbs Aggregated Feature Selection model. Here, data points that include missing value are eliminated therefore obtaining computationally efficient features for further reference. Furthermore, if uncertain spatial big data analytic estimates of prediction make the forecasting more reliable, a Convoluted Long and Short-Term Memory for highly dynamic environment quality prediction is designed that allows in mining spatial data features in a precise and accurate manner. We conduct extensive experimental evaluations using meteorological dataset. The results demonstrate the efficiency of our proposed BG-SCDC method in comparison to state-of-the-art methods in terms of execution time, true positive rate and prediction accuracy. [ABSTRACT FROM AUTHOR]

Quasi-Monte Carlo algorithms based on modified Sobol sequences, modified van der Corput sequnces and modified lattice sequences are used in our sensitivity study of the Unified Danish Eulerian model. A highly efficient lattice reflection rule is developed and applied to the model. Our experiments show that the optimal algorithms under consideration, and especially the new lattice reflection rule, are efficient for the multidimensional integrals under consideration and especially for computing small by value sensitivity indices. Clearly, the progress in the area of air pollution modelling, is closely connected with the progress in reliable algorithms for multidimensional integration. [ABSTRACT FROM AUTHOR]

Air pollution modeling has attracted experts in the field of the atmospheric environment due to its priority in future studies. In general, many studies conducted to model air pollutants such as proximity models, geostatistical interpolation, dispersion models, land use regression models, remote sensing, and artificial intelligence models. In this study, we review studies that are relevant to the modeling of air pollutants. We qualitatively and quantitatively evaluated these studies. Proximity models are considered the most basic methods to assess the quantitative, temporal, and spatial variation of air pollutants in a specific area. The main drawbacks of this technique, proximity models often use a limited number of parameters like traffic and roads neglecting important parameters such as weather information, and topography. In addition, these models neglect the type of vehicles like trucks and vehicles. Moreover, these models need self-reported approaches that represent the exposure to pollutants emitted from traffic, which may have been affected by biased information. On the other hand, this approach is usually performed based on the geostatistical interpolation techniques or GIS modeling, the main advantage of this method is; the precision of maps mainly relies on the accuracy of the used dataset and the interpolation algorithm used in GIS. Land use regression models are well-known models that use multiple linear regression algorithms to model the relationship between the dependent variable and independent variables. The main constraint of these models that they are difficult to be generalize for other study areas that include different natures. Dispersion models are important models that used various kinds of parameters such as emission data, topography, and meteorological data to model pollutants emissions in ambient air. The most recent approaches are the remote sensing methods that are used to detect and monitor air pollutants concentrations over large areas. The main drawbacks of remote sensing methods are that they are not suitable for high-resolution predictions in urban scales such as micro-scales studies. The most advanced techniques are artificial intelligence algorithms due to their ability to allow computer applications through learning from experience based on algorithmic training and iterative processing. This study can be a good guideline for researchers who are interested in the modeling of air pollutants. [ABSTRACT FROM AUTHOR]

Various environment affairs are affected by the increasing infrastructural frameworks and industries. One of the affecting affairs is air pollution, which cause various health issues. This undertaking means to develop an environmental observing framework to screen the environmental polluting gases, temperature, humidity and dust present in the particular area by using Universal Object Interaction or IoT. Knowing the current data of these factors helps one to take immediate measures at that place and lead a healthy life. These data are collected using different sensors connected to the Arduino UNO board and then the observations are passed to the Thing Speak cloud to view the measures of the area and alert mail will be sent when the situation worse. [ABSTRACT FROM AUTHOR]

This article deals with the problem of artificial ventilation of urban intersections. The need to find solutions to this problem is caused by the growth of urban air pollution due to the ever-increasing emissions from industry and transport in the presence of inversions in the atmosphere over the city. As a result of the analysis of existing methods of local influence on weather conditions, a method was chosen to create an upward flow of heated air. A basic design of the meteotron is proposed in the form of a high chimney, for heating which solar heaters are used to create a temperature gradient. Preliminary calculations showed that with a specific power of solar heaters of 250 W/m2, the total power of the meteotron will be 375,000 W, which will create a temperature difference of 4.1 °C. The city meteotron will improve air circulation and reduce the concentration of harmful substances at urban intersections. [ABSTRACT FROM AUTHOR]

Particulate matter, chemical pollutants, and biological contaminants all contribute to air pollution. People getting aware of harmful effects in their health from breathing in polluted air during short-and long-term exposure. Following the results of recent researches, it has been observed that the rick of respiratory and cardiovascular diseases such as chronic, asthma, myocardial infarction, lung cancer, failure of heart and accidents related to cerebrovascular etc. have increased from traffic air pollution. Air pollution makes people more vulnerable especially pregnant women, new-borns. This narrative overview summarizes the most common diseases linked to air pollution exposure. [ABSTRACT FROM AUTHOR]