Journal articles: 'Air pollution modelling and control'

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Colette, A., B. Bessagnet, F. Meleux, and L. Rouïl. "Frontiers in air quality modelling." Geoscientific Model Development Discussions 6, no. 3 (August 2, 2013): 4189–205. http://dx.doi.org/10.5194/gmdd-6-4189-2013.

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Abstract. The first pan-European kilometre-scale atmospheric chemistry simulation is introduced. The continental-scale air pollution episode of January 2009 is modelled with the CHIMERE offline chemistry-transport model with a massive grid of 2 million horizontal points, performed on 2000 CPU of a high performance computing system hosted by the Research and Technology Computing Center at the French Alternative Energies and Atomic Energy Commission (CCRT/CEA). Besides the technical challenge, we find that model biases are significantly reduced, especially over urban areas. The high resolution grid also allows revisiting the contribution of individual city plumes to the European burden of pollution, providing new insights for designing air pollution control strategies.

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Finzi, G., and G. Guariso. "Optimal air pollution control strategies: a case study." Ecological Modelling 64, no. 2-3 (October 1992): 221–39. http://dx.doi.org/10.1016/0304-3800(92)90116-v.

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Chaulya, S. K., A. K. Singh, T. B. Singh, G. C. Mondal, S. Singh, S. K. Singh, and R. S. Singh. "Modelling for Air Quality Estimation for a Planned Coal Washery to Control Air Pollution." Environmental Modeling & Assessment 25, no. 6 (June 16, 2020): 775–91. http://dx.doi.org/10.1007/s10666-020-09721-x.

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Zhu, Wei, Shaonan Shan, Xiaohui Shi, and Hui Li. "Research on the Establishment and Stability of the Beijing-Tianjin-Hebei Region Air Pollution Cooperative Control Alliance: An Evolutionary Game Approach." Discrete Dynamics in Nature and Society 2021 (September 2, 2021): 1–18. http://dx.doi.org/10.1155/2021/1179351.

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Air pollution control refers to a vital issue in the integrated and coordinated development of the Beijing-Tianjin-Hebei region. As impacted by the fluidity of air pollution, air pollution control cannot be achieved independently by a single local government in the Beijing-Tianjin-Hebei region, and a long-term mechanism should be established for regional coordination and cooperative control. However, in the pursuit of maximising benefits by the participating parties, difficulties in effective coordination between the various control bodies occurred and a dilemma was created in the cooperative control of air pollution in the Beijing-Tianjin-Hebei region. Based on the existing research, this study first builds an evolutionary game model to analyse the evolutionary path and stability of cooperative alliance of air pollution control behaviour in the Beijing-Tianjin-Hebei region. Second, this study explores the core elements of reaching alliances and consolidating cooperative control among cities in the Beijing-Tianjin-Hebei region. Last, in combination with the simulation results, this study compares the feasibility of cooperative control among cities in the Beijing-Tianjin-Hebei region with and without central government constraints. As indicated from the results, without the constraints of the central government, intergovernmental cooperative control is correlated with intercity public benefits, cities’ own benefits, and air pollution losses, whereas it is not effective since it cannot control the phenomenon of “free-riding” by cities in the Beijing-Tianjin-Hebei region. Under the control of the central government, a stable strategy among cities can evolve toward a fast and efficient cooperative management. To achieve air pollution control effectively, the air pollution control alliance should be formed in the Beijing-Tianjin-Hebei region, and the benefits of cooperation lay the basis for reaching cooperative control. The mentioned findings highlight that (1) the benefits of cooperation lay the basis for cooperative control, (2) punitive policies of central government increase the evolutionary rate of cooperative control, and (3) cooperation costs determine the long-term stability of the alliance.

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Mohamed, Ghada Osama, Maher Elsayed Saleh, Elsayed Ahmed Shalaby, and Ahmed Samir Elsafty. "Using biochar to control nitric oxide air pollution." Journal of Physics: Conference Series 2305, no. 1 (August 1, 2022): 012029. http://dx.doi.org/10.1088/1742-6596/2305/1/012029.

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Abstract This study deals with the ability of Rice Husk Biochar (RHB) to adsorb and reduce the concentration of 90 ppm Nitric Oxide (NO) gas which passed through it with a 1.2 liter/min flow rate within 8 minutes. The characteristics of biochar before and after adsorption were studied by SEM, EDAX, and FTIR analyses. To study the effect of different factors on adsorption the effect of manufacturing temperatures of biochar was studied by using two degrees 450 °C and 500 °C. It has also been measured the effect of biochar particles size using two types of size, coarse (C) and fine (F). The effect of the shape of the measurement system on the adsorption was also measured using two types of systems A and B. In general, the RHB450C A gives the best adsorption capacity for NO (95.7 mg/g) followed by RHB450F A (41.9 mg/g) followed by RHB500C A (24.8 mg/g). Both Langmuir and Freundlich isothermal models were applied to mathematical modelling of NO adsorption, and based on the coefficient of determination (r2) Langmuir’s model provided a perfect fit to the experimental data. It was also found that the pseudo-first-order model is suitable for studying adsorption kinetics.

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Cocks, A. T., I. R. Rodgers, R. A. Skeffington, and A. H. Webb. "The limitations of integrated assessment modelling in developing air pollution control policies." Environmental Pollution 102, no. 1 (1998): 635–39. http://dx.doi.org/10.1016/s0269-7491(98)80092-4.

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Das, Sukanya, MN Murty, and Kavita Sardana. "Using Economic Instruments to Fix the Liability of Polluters in India." Ecology, Economy and Society–the INSEE Journal 4, no. 2 (July 31, 2021): 45–64. http://dx.doi.org/10.37773/ees.v4i2.363.

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This review paper highlights the informational requirements for the effective use of environmental policy instruments to achieve ambient standards of pollution in India. A section on the Integrated Urban Air Pollution Assessment Model is attempted to identify data requirements for, and information gaps associated with, using these instruments. We review the available information and identify informational gaps that thwart the realization of ambient standards of environmental quality. In India, command-and-control instruments are arbitrarily used to assign liability without taking cognizance of economic estimates. The available cost–benefit estimates of air and water pollution, combined with air quality modelling for urban areas and water quality modelling, are essential inputs for using environmental policy instruments to ensure compliance with ambient standards. We discuss how to use economic estimates while designing and using economic instruments such as pollution taxes and pollution permits, in addition to command and control.

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Issakhov, Alibek, and Aiymzhan R. Baitureyeva. "Numerical modelling of a passive scalar transport from thermal power plants to air environment." Advances in Mechanical Engineering 10, no. 10 (October 2018): 168781401879954. http://dx.doi.org/10.1177/1687814018799544.

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The number of thermal power plants is growing due to the industry development and the growth of energy consumption. This leads to an increase in harmful emissions in the atmosphere. There is a necessity to control the emission concentration level in the areas of power plants location. The aim of this work was to study the level of pollution concentration at different distances from the source. The mathematical model and the numerical algorithm were verified by solving test problems and comparing them with the experimental data and numerical results of other authors. Furthermore, the pollution distribution in three-dimensional case was investigated in a real physical scale. CO2 was considered as polluting gas. As a real example, the Ekibastuz SDPP-1 coal-fired thermal power plant was simulated. The remarkable feature of this thermal power plant is that the pollution emits from two chimneys of different heights (330 and 300 m). The results showed that due to the difference between chimney heights (30 m), the pollution concentration from the higher chimney dropped far away from source, than from the lower one (2160 and 1970 m, respectively). Obviously, building higher chimneys helps to reduce the harmful impact of emissions on the environment. Also, it can be used to control the emissions level at already existing power plants.

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Bekesiene, Svajone, and Ieva Meidute-Kavaliauskiene. "Artificial Neural Networks for Modelling and Predicting Urban Air Pollutants: Case of Lithuania." Sustainability 14, no. 4 (February 21, 2022): 2470. http://dx.doi.org/10.3390/su14042470.

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This study focuses on the Vilnius (capital of Lithuania) agglomeration, which is facing the issue of air pollution resulting from the city’s physical expansion. The increased number of industries and vehicles caused an increase in the rate of fuel consumption and pollution in Vilnius, which has rendered air pollution control policies and air pollution management more significant. In this study, the differences in the pollutants’ means were tested using two-sided t-tests. Additionally, a 2-layer artificial neural network and a pollution data were both used as tools for predicting and warning air pollution after loop traffic has taken effect in Vilnius Old Town from July of 2020. Highly accurate data analysis methods provide reliable data for predicting air pollution. According to the validation, the multilayer perceptron network (MLPN1), with a hyperbolic tangent activation function with a 4-4-2 partition, produced valuable results and identified the main pollutants affecting and predicting air quality in the Old Town: maximum concentration of sulphur dioxide per 1 hour (SO2_1 h, normalized importance = 100%); carbon monoxide (CO) was the second pollutant with the highest indication of normalized importance, equalling 59.0%.

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Croitoru, Cristiana, and Ilinca Nastase. "A state of the art regarding urban air quality prediction models." E3S Web of Conferences 32 (2018): 01010. http://dx.doi.org/10.1051/e3sconf/20183201010.

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Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

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Raos, Miomir, Ljiljana Zivkovic, Amelija Djordjevic, and Branislav Todorovic. "Modelling of the filter-adsorber type air cleaner by using neural network." Facta universitatis - series: Physics, Chemistry and Technology 7, no. 1 (2009): 23–31. http://dx.doi.org/10.2298/fupct0901023r.

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It is well known that most air purifying methods imply the passing of air flow, as a pollutant carrier, through a control unit which retains impurities. Properties of the air control unit and the purifying process itself therefore differ depending on the nature of present impurities, as well as on flow-thermal properties of air as the carrier of those impurities. For the assumed conditions, in terms of production of a pollution source and presence of different polluting substances in the form of dust, aerosols, gas, vapor in the exhaust gas, etc., an integrated gas purifier has been designed and tested, comprising a module for purification of mechanical impurities and a module for purification of gaseous impurities. The purifier is compact and has a universal application while simultaneously retaining several different pollutants. These requirements were met through application of the filtration and adsorption methods. On the formed experimental line with an adequate system of acquisition, filter-adsorber type gas cleaners in the function of flow-thermal parameters of gas mixture were tested simultaneously. Experimental data were used for training the radial basis function neural network, which was then used to model properties of the process and gas cleaner.

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Budianu, Mihaela, Valeriu Nagacevschi, and Matei Macoveanu. "MODELLING AND SIMULATION OF DISPERSIONS OF POWDER EMISSIONS FROM MULTIPLE SOURCES WITH THE MATHEMATICAL MODEL POL 15SM." JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT 22, no. 2 (June 20, 2014): 151–60. http://dx.doi.org/10.3846/16486897.2013.821068.

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Over the last decades, air pollution has become one of the greatest challenges negatively affecting human health and the entire environment, including air, water, soil, vegetation, and urban areas. Lately, special attention has been given to mathematical modelling for diffusion of pollutants in the atmosphere as a particularly effective and efficient method that can be used to study, control and reduce air pollution. The diversity of models developed by different research groups imposed a rigorous understanding of model types in order to apply them correctly according to local or regional problems of air pollution phenomenon. Tus the authors have developed and improved two mathematical models for dispersion of air pollutants. Tis paper presents a case study of dispersion of powders in suspension originating from 14 point sources that correspond to 5 economic agents in the agroindustrial area of Vaslui city using a computer simulation based on the mathematical model Pol 15sm, for multiple point sources of pollution, designed by the authors.

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Todorov, Venelin, and Ivan Dimov. "Innovative Digital Stochastic Methods for Multidimensional Sensitivity Analysis in Air Pollution Modelling." Mathematics 10, no. 12 (June 20, 2022): 2146. http://dx.doi.org/10.3390/math10122146.

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Nowadays, much of the world has a regional air pollution strategy to limit and decrease the pollution levels across governmental borders and control their impact on human health and ecological systems. Environmental protection is among the leading priorities worldwide. Many challenges in this research area exist since it is a painful subject for society and a fundamental topic for the healthcare system. Sensitivity analysis has a fundamental role during the process of validating a large-scale air pollution computational models to ensure their accuracy and reliability. We apply the best available stochastic algorithms for multidimensional sensitivity analysis of the UNI-DEM model, which plays a key role in the management of the many self-governed systems and data that form the basis for forecasting and analyzing the consequences of possible climate change. We develop two new highly convergent digital sequences with special generating matrices, which show significant improvement over the best available existing stochastic methods for measuring the sensitivity indices of the digital ecosystem. The results obtained through sensitivity analysis will play an extremely important multi-sided role.

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Panagi, Marios, Zoë L. Fleming, Paul S. Monks, Matthew J. Ashfold, Oliver Wild, Michael Hollaway, Qiang Zhang, Freya A. Squires, and Joshua D. Vande Hey. "Investigating the regional contributions to air pollution in Beijing: a dispersion modelling study using CO as a tracer." Atmospheric Chemistry and Physics 20, no. 5 (March 6, 2020): 2825–38. http://dx.doi.org/10.5194/acp-20-2825-2020.

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Abstract. The rapid urbanization and industrialization of northern China in recent decades has resulted in poor air quality in major cities like Beijing. Transport of air pollution plays a key role in determining the relative influence of local emissions and regional contributions to observed air pollution. In this paper, dispersion modelling (Numerical Atmospheric Modelling Environment, NAME model) is used with emission inventories and in situ ground measurement data to track the pathways of air masses arriving in Beijing. The percentage of time the air masses spent over specific regions during their travel to Beijing is used to assess the effects of regional meteorology on carbon monoxide (CO), a good tracer of anthropogenic emissions. The NAME model is used with the MEIC (Multi-resolution Emission Inventory for China) emission inventories to determine the amount of pollution that is transported to Beijing from the immediate surrounding areas and regions further away. This approach captures the magnitude and variability of CO over Beijing and reveals that CO is strongly driven by transport processes. This study provides a more detailed understanding of relative contributions to air pollution in Beijing under different regional airflow conditions. Approximately 45 % over a 4-year average (2013–2016) of the total CO pollution that affects Beijing is transported from other regions, and about half of this contribution comes from beyond the Hebei and Tianjin regions that immediately surround Beijing. The industrial sector is the dominant emission source from the surrounding regions and contributes over 20 % of the total CO in Beijing. Finally, using PM2.5 to determine high-pollution days, three pollution classification types of pollution were identified and used to analyse the APHH winter campaign and the 4-year period. The results can inform targeted control measures to be implemented by Beijing and the surrounding provinces to tackle air quality problems that affect Beijing and China.

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Manco-Perdomo, L. A., L. A. Pérez-Padilla, and C. A. Zafra-Mejía. "Intervention analysis with autoregressive integrated moving average models for time series of urban air pollutants." Journal of Physics: Conference Series 2139, no. 1 (December 1, 2021): 012002. http://dx.doi.org/10.1088/1742-6596/2139/1/012002.

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Abstract The objective of this paper is to show an intervention analysis with autoregressive integrated moving average models for time series of air pollutants in a Latin American megacity. The interventions considered in this study correspond to public regulations for the control of urban air quality. The study period comprised 10 years. Information from 10 monitoring stations distributed throughout the megacity was used. Modelling showed that setting maximum emission limits for different pollution sources and improving fuel were the most appropriate regulatory interventions to reduce air pollutant concentrations. Modelling results also suggested that these interventions began to be effective between the first 4 days-15 days after their publication. The models developed on a monthly timescale had a short autoregressive memory. The air pollutant concentrations at a given time were influenced by the concentrations of up to three months immediately preceding. Moving average term of the models showed fluctuations in time of the air pollutant concentrations (3 months - 14 months). Within the framework of the applications of physics for the air pollution control, this study is relevant for the following findings: the usefulness of autoregressive integrated moving average models to temporal simulate air pollutants, and for its suitable performance to detect and quantify regulatory interventions.

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LIU, Gang-jun, Er-jiang FU, Yun-jia WANG, Ke-fei ZHANG, Bao-ping HAN, and Colin ARROWSMITH. "A Framework of Environmental Modelling and Information Sharing for Urban Air Pollution Control and Management." Journal of China University of Mining and Technology 17, no. 2 (June 2007): 172–78. http://dx.doi.org/10.1016/s1006-1266(07)60066-2.

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Schmitt, Laetitia Helene Marie. "QALY gain and health care resource impacts of air pollution control: A Markov modelling approach." Environmental Science & Policy 63 (September 2016): 35–43. http://dx.doi.org/10.1016/j.envsci.2016.05.015.

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Zundel, T., O. Rentz, R. Dorn, A. Jattke, and M. Wietschel. "Control techniques and strategies for regional air pollution control from energy and industrial sectors." Water, Air, & Soil Pollution 85, no. 1 (1995): 213–24. http://dx.doi.org/10.1007/bf00483702.

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Remmers, J., Th Morgenstern, G. Schons, H. D. Haasis, and O. Rentz. "Integration of air pollution control technologies in linear energy—environmental models." European Journal of Operational Research 47, no. 3 (August 1990): 306–16. http://dx.doi.org/10.1016/0377-2217(90)90217-y.

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Hamzelo, M., A. Gharagozlou, S. Sadeghian, S. H. Baikpour, and A. Rajabi. "MODELLING OF CARBON MONOXIDE AIR POLLUTION IN LARG CITIES BY EVALUETION OF SPECTRAL LANDSAT8 IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (December 11, 2015): 281–85. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-281-2015.

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Air pollution in large cities is one of the major problems that resolve and reduce it need multiple applications and environmental management. Of The main sources of this pollution is industrial activities, urban and transport that enter large amounts of contaminants into the air and reduces its quality. With Variety of pollutants and high volume manufacturing, local distribution of manufacturing centers, Testing and measuring emissions is difficult. Substances such as carbon monoxide, sulfur dioxide, and unburned hydrocarbons and lead compounds are substances that cause air pollution and carbon monoxide is most important. Today, data exchange systems, processing, analysis and modeling is of important pillars of management system and air quality control. In this study, using the spectral signature of carbon monoxide gas as the most efficient gas pollution LANDSAT8 images in order that have better spatial resolution than appropriate spectral bands and weather meters،SAM classification algorithm and Geographic Information System (GIS ), spatial distribution of carbon monoxide gas in Tehran over a period of one year from the beginning of 2014 until the beginning of 2015 at 11 map have modeled and then to the model valuation ،created maps were compared with the map provided by the Tehran quality comparison air company. Compare involved plans did with the error matrix and results in 4 types of care; overall, producer, user and kappa coefficient was investigated. Results of average accuracy were about than 80%, which indicates the fit method and data used for modeling.

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Rode, Carsten, John Grunewald, Zhenlei Liu, Menghao Qin, and Jianshun Zhang. "Models for residential indoor pollution loads due to material emissions under dynamic temperature and humidity conditions." E3S Web of Conferences 172 (2020): 11002. http://dx.doi.org/10.1051/e3sconf/202017211002.

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The IEA EBC Annex 68 project on “Indoor Air Quality Design and Control in Low Energy Residential Buildings” has been recently completed. The project considered indoor air pollution loads in dwellings, particularly how such pollutants are emitted in dependency of the hygrothermal conditions: temperature, moisture and air flows. Thus, a proper understanding of the mutual interactions between hygrothermal conditions and pollutants was needed to obtain optimal paradigms for demand-controlled ventilation. The project adopted a similarity approach for modelling the transports of moisture and volatile organic compounds (VOCs) in materials, and thereby it was possible to provide a comprehensive set of data and tools whereby the indoor atmospheric conditions of buildings can be optimized, e.g. with respect to the need for ventilation. The paper explains the experimental and modelling approach and presents a summary of the results.

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Sendow, Theo Kurniawan. "Modelling of Air Pollution Caused by Traffic Flows in Manado City, Indonesia." Journal of Sustainable Engineering: Proceedings Series 1, no. 1 (June 30, 2019): 84–95. http://dx.doi.org/10.35793/joseps.v1i1.11.

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This study was aimed to determine the level of CO concentration due to traffic flows, know the traffic (vehicle) volume, traffic (vehicle) speed and wind speed, find out the relationship between traffic (vehicle) volume, traffic (vehicle) speed, wind speed and CO concentration using a regression model as well as examine the parameters influencing air pollution due to traffic flows. The primary data used in this study were the sample data of CO tested directly in the field and the sampling was done using Ecoline 6000 Gas Analyzer tool. The research sites covered 1) the segment of Sam Ratulangi Street in Manado representing the street locations with many multi-rise buildings and high building density, 2) the segment of Ahmad Yani Street in Manado representing the street locations with many trees, and 3) the segment of Pierre Tendean Street in Manado representing the street locations with open areas (beachsides). In this modeling, the independent variables were the total traffic volume, the average traffic speed as well as the wind speed and direction. The dependent variable was Carbon Monoxide (CO) with increased concentrations. Using the three independent variables, there were total 7 (seven) variable combinations used. Then, the obtained model was validated using the surveyed data. The maximum vehicle volume was 4,281.60 pcu/hour (pcu = passenger car unit) and the maximum vehicle speed was 32 km/hour. Meanwhile, the maximum wind speed generated was 7.5 km/hour and the maximum level of air pollution (CO) was 12.86 ppm (ppm = part per million). In this study, it was obtained the best model for each of the three locations. The results showed that the air pollution (CO) level of street locations with low wind speed, such as Sam Ratulangi street which is a closed area with many multi-rise buildings and high building density, was much higher than that of street locations with many trees growing in the median of streets with a distance of 1 meter from the edge of street pavement and also higher than that of street locations with open areas (beachsides). This is because a higher wind speed can disseminate or divide the concentration level of air pollution (CO) to various places. Air pollution control covers three stages namely the prevention, countermeasure, and recovery of air quality.

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Abulude, Francis Olawale, Moez Bahloul, Smart Olubayode, and Ebenezer Alaba Adeoya. "A review on top-down and bottom-up approach for air pollution studies." World Journal of Environmental Research 7, no. 2 (May 14, 2018): 52–60. http://dx.doi.org/10.18844/wjer.v7i2.3427.

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AbstractIt is a well-known fa ct that pollution is a global problem and mus t be holis ticall y ta ckled. In doing this, a dequa te knowledge of the sources of pollution is i mporta nt; therefore, the ai m of this paper is to review source a pportionment wi th reference to top-down and bottom-up methods . In this paper, dispersion modelling, emissions inventory and sa mpling methods are dis cussed. Also, anal yti cal methods invol ved in top -down source apportionment a re mentioned. The two techniques are needed to evalua te pollutants and their sources . Based on these two approa ches , pollution control s tra tegy is developed and decisions can be made on deci ding the ri ght approach to sol ve or reduce the pollution problems .

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Kaya, İhsan, and Cengiz Kahraman. "Air Pollution Control Using Fuzzy Process Capability Indices in the Six-Sigma Approach." Human and Ecological Risk Assessment: An International Journal 15, no. 4 (August 5, 2009): 689–713. http://dx.doi.org/10.1080/10807030903050897.

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Papaleonidas, Antonios, and Lazaros Iliadis. "Neurocomputing techniques to dynamically forecast spatiotemporal air pollution data." Evolving Systems 4, no. 4 (April 23, 2013): 221–33. http://dx.doi.org/10.1007/s12530-013-9078-5.

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Dave, Neha M., Rupesh P. Vasani, and Parmit Chhasiya. "Modelling the impact of Urban Heat Island mitigation strategies on Urban Air Quality." Current World Environment 17, no. 2 (September 10, 2022): 393–409. http://dx.doi.org/10.12944/cwe.17.2.11.

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Increasing urban sprawl has caused many severe problems like surge in pollution, rapid climatical variations, and the intensification of temperature in the urban areas, termed Urban Heat Islands (UHI). Population density has caused theconversion of most land areas into cities, and cities have expanded vastly. UHI phenomenon has caused temperature rise in the cities. Most of the metropolitan regions of India are experiencing consequences of UHI and the severity of pollution formation, which is a crucial research area. Since the rising temperature has a direct linkage with urban air pollution; the mitigation measures for UHI are also linked with urban air pollution mitigation; efficacy of mitigation measures of UHI phenomenon in correlation with urban air quality is being studied extensively, which emphasizesthescientific approach and planning concerns of implementation agency to consider the same into urban design and planning aspects. Ahmedabad is one of the growing metropolitan regions of India. The city has grown economically and physically by expanding its boundaries in a radial pattern. This study has attempted temporal assessment of remote sensing data to derive the UHI and the city's growth, and its changing land uses. Assessment has been performed from2008 to 2018 from Landsat data for temperature profile at surface level and type of usage of land of the study area. The spatial profile of Particulate Matter (PM2.5 and PM10) has been generated based on data from the state pollution control board. Four variables, LST, PM2.5, PM10, and LULC, are taken to establish the relationship between all variables present in different layers withthehelp of regression statistical analysis. A strong positive correlation between PM2.5, PM10, and LST has been discovered, which was eventually used to assess the impact of mitigation strategies of UHI, specifically urban greening and a white roof to particulate matter concentrations.

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Ho, Quoc Bang. "APPLICATION MONTE-CARLO METHOD TO ESTIMATE UNCERTAINTIES IN THE RESULTS OF AIR QUALITY MODELLING: THE CASE OF HO CHI MINH CITY." Science and Technology Development Journal 14, no. 1 (March 30, 2011): 78–91. http://dx.doi.org/10.32508/stdj.v14i1.1869.

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Air pollution has deteriorated considerably the health of millions of people in Ho Chi Minh City (HCMC) due to high levels emissions. It has been showed that more than 90% of children under the age of 5 years old suffered from different respiratory illnesses in the city. The objectives of this research include: (1) studying the formation of the pollution plume over the city during a 3-day episode in February 2006 and (2) estimating uncertainties in the results of air quality simulations for HCMC. Research results show evidence of the development of a Ozone (O3) pollution plume in the north-western part of the city. A scenario for reduction of air pollution is studied in this work to help the local government to make decisions for managing air quality in HCMC. For making a better-informed decision, the probabilistic estimate for the photochemical model is carried out in this research. The Monte-Carlo method that is applied in this research for the uncertainty analyses is an efficient method of producing a probabilistic output from the photochemical model. The results of abatement strategy showed that if the local government follows the emission control plan: by 2020, the O3 concentration will be decreased by 30% compared to the recent O3 concentration.

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Xu, Wen, Wei Song, Yangyang Zhang, Xuejun Liu, Lin Zhang, Yuanhong Zhao, Duanyang Liu, et al. "Air quality improvement in a megacity: implications from 2015 Beijing Parade Blue pollution control actions." Atmospheric Chemistry and Physics 17, no. 1 (January 2, 2017): 31–46. http://dx.doi.org/10.5194/acp-17-31-2017.

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Abstract. The implementation of strict emission control measures in Beijing and surrounding regions during the 2015 China Victory Day Parade provided a valuable opportunity to investigate related air quality improvements in a megacity. We measured NH3, NO2 and PM2.5 at multiple sites in and outside Beijing and summarized concentrations of PM2.5, PM10, NO2, SO2 and CO in 291 cities across China from a national urban air quality monitoring network between August and September 2015. Consistently significant reductions of 12–35 % for NH3 and 33–59 % for NO2 in different areas of Beijing during the emission control period (referred to as the Parade Blue period) were observed compared with measurements in the pre- and post-Parade Blue periods without emission controls. Average NH3 and NO2 concentrations at sites near traffic were strongly correlated and showed positive and significant responses to traffic reduction measures, suggesting that traffic is an important source of both NH3 and NOx in urban Beijing. Daily concentrations of PM2.5 and secondary inorganic aerosol (sulfate, ammonium and nitrate) at the urban and rural sites both decreased during the Parade Blue period. During (after) the emission control period, concentrations of PM2.5, PM10, NO2, SO2 and CO from the national city-monitoring network showed the largest decrease (increase) of 34–72 % (50–214 %) in Beijing, a smaller decrease (a moderate increase) of 1–32 % (16–44 %) in emission control regions outside Beijing and an increase (decrease) of 6–16 % (−2–7 %) in non-emission-control regions of China. Integrated analysis of modelling and monitoring results demonstrated that emission control measures made a major contribution to air quality improvement in Beijing compared with a minor contribution from favourable meteorological conditions during the Parade Blue period. These results show that controls of secondary aerosol precursors (NH3, SO2 and NOx) locally and regionally are key to curbing air pollution in Beijing and probably in other mega cities worldwide.

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Guo, Jiaqi, and Zhongke Feng. "Study on Spatial Temporal Distribution Characteristics of Air Quality Index in Beijing and Its Correlation with Local Meteorological Conditions." Discrete Dynamics in Nature and Society 2019 (December 18, 2019): 1–15. http://dx.doi.org/10.1155/2019/1462034.

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The changing of AQI presented by historical observations has significant meaning to the urban air pollution prevention. In order to explore the correlation between air quality and meteorological condition in Beijing from 2014 to 2017, researchers processed 52165 sample data from 35 air monitor stations by means of R statistical software, analyzed the spatial temporal distribution characteristics of air quality index (AQI) with Kriging and mathematical statistics and did the research on correlation between spatial temporal distribution characteristics of AQI and meteorological condition. The results showed that (1) the spatial increasing trend of AQI is obvious from the north to the south in Beijing zone, representing that the air quality is getting worse from the north to the south; (2) the diurnal variation of daily AQI value reveals interannual periodic trend and a relatively great fluctuating range from 485 to 0. (3) The correlation coefficients of daily AQI mean with average temperature, specific humidity and wind speed are −0.116, −0.073 and −0.192 respectively, displaying that all of the three factors are negatively correlated with AQI and average temperature and wind speed are significantly negatively correlated. The results provide a reference for regional environmental management and pollution prevention and control.

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Rahman, Md Masudur, Wang Shuo, Weixiong Zhao, Xuezhe Xu, Weijun Zhang, and Arfan Arshad. "Investigating the Relationship between Air Pollutants and Meteorological Parameters Using Satellite Data over Bangladesh." Remote Sensing 14, no. 12 (June 8, 2022): 2757. http://dx.doi.org/10.3390/rs14122757.

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Understanding of the relationship between air pollutants and meteorological parameters on the regional scale is a prerequisite for setting up air pollution prevention and control strategies; however, there is a lack of methodical investigations, particularly in the context of Bangladesh’s deficiency of information on air pollution. This study represents the first attempt to investigate the relationship between air pollutants (NO2, O3, SO2, and CO) and meteorological parameters over Bangladesh using satellite data (OMI and MOPITT) during the period from 2015 to 2020. Geographically weighted regression (GWR) modelling was utilized to assess the relationship between air pollutants and weather variables. The spatial representation and average values of geographically varying coefficients showed that the column densities of air pollutants were affected by the meteorological parameters. For example, NO2 was positively associated with temperature in most of the studied regions, with an average geographically varying coefficient value of 0.12 Dobson units (DU, 1 DU = 2.687 × 1016 molecules/cm2), indicating that NO2 concentrations increase by 0.12 DU/year with every unit increase in temperature. The sources of NO2 and SO2 in Dhaka were identified through emission inventory analysis, and transportation and industry emissions were the most significant influencing factors for NO2 and SO2, respectively. Temperature and pressure showed a higher degree of relationship with all four air pollutants compared with other parameters. The results and discussion presented in this study can be of benefit for policy makers in developing air pollution control strategies in Bangladesh.

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Gallagher, J., L. W. Gill, and A. McNabola. "The passive control of air pollution exposure in Dublin, Ireland: A combined measurement and modelling case study." Science of The Total Environment 458-460 (August 2013): 331–43. http://dx.doi.org/10.1016/j.scitotenv.2013.03.079.

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Costabile, F., and I. Allegrini. "A new approach to link transport emissions and air quality: An intelligent transport system based on the control of traffic air pollution." Environmental Modelling & Software 23, no. 3 (March 2008): 258–67. http://dx.doi.org/10.1016/j.envsoft.2007.03.001.

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Wen, Youyue, Jianneng Xiao, Jian Yang, Saoman Cai, Minxuan Liang, and Peng Zhou. "Quantitatively Disentangling the Geographical Impacts of Topography on PM2.5 Pollution in China." Remote Sensing 14, no. 24 (December 13, 2022): 6309. http://dx.doi.org/10.3390/rs14246309.

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Fine particulate matter (PM2.5) pollution’s passive effects on public health have attracted a great deal of attention. Extensive studies have tried to uncover the impacts of external drivers on PM2.5 pollution variation; however, the topography’s effects on PM2.5 pollution remain poorly understood. Using annual high-resolution concentration estimates for PM2.5, this paper quantitatively disentangled the geographical impacts of topography on the PM2.5 pollution in China and quantified the mountain blocking effects on the PM2.5 pollution dispersion on a macro scale. The results show that, in China, the plains and surrounding platforms and hills tend to suffer from long-term severe PM2.5 pollution. The most polluted topography type is the plains. In comparison, regions such as high-altitude mountains and plateaus are less affected by PM2.5 pollution. Mountains have significant and evident blocking effects on the cross-regional spread of PM2.5 pollution. Generally, Level I mountains (high elevation, density and coverage mountains) provide better blocking effects than Level II (middle elevation, density and coverage mountains) mountains and Level III mountains (low elevation, density and coverage mountains). The mountains’ blocking effects begin to play an efficient role when their altitudes reach a certain value; however, the exact altitude values vary by different mountains with a value of 163 m for all typical mountains with absolute PM2.5 concentration differences between their two sides greater than 10 μg/m3. In heavily polluted areas, PM2.5 pollution may overflow where the surrounding mountains are not high enough or the mountains’ stretch breaks. This study can provide key theoretical support for air pollution modelling and regional air pollution joint prevention and control.

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K, Dr Vijayakumar, Rahul M M, Dhamodara Prasath G, and Aravinth V. "Adaptive Air Quality Sensing using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 423–30. http://dx.doi.org/10.22214/ijraset.2022.42186.

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Abstract: Air pollution is a worldwide problem having impacts on both local and global scales. According to the World Health Organization (WHO), air pollution causes 7 million deaths every year, with 4.2 million attributed to exposure to outdoor air pollution. Compared to the reference methods defined in the Air Quality Directive, the use of low-cost air quality sensors for monitoring ambient air pollution would reduce air pollution monitoring costs and would also allow larger spatial coverage especially in remote areas where monitoring with traditional facilities is uneasy. Theses multi-sensors were either calibrated against standard gas mixtures or using artificial neural network under field conditions. The later method resulted in mixed results either satisfactory for short periods or generally weak for longer data series. This project mainly focuses on the adaptive calibration of the low-cost sensors using the trained machine learning model. The performances of several field calibration methods for low-cost sensors, including linear/multi linear regression and supervised learning techniques will be compared. A cluster of ozone, nitrogen dioxide, nitrogen monoxide, carbon monoxide and carbon dioxide sensors will be operated. Subsequently, the accuracy of the predicted values will be evaluated for about a period. These predicted values are fed through the training model and the model will run accordingly and it will adapt all the error situations. This will be useful to the automobile industry in the current situation for smoke emission control and also for many refinery industries in which low-cost sensors can be used with the following modelling for the higher accuracy. This would reduce the cost and also yields more accuracy beyond the varying situation. Keywords: 1) Low-Cost Sensors (LCS) 2) Internet of Things (IoT)

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V. Dhandapani, N., R. Manimaran, and R. Velmurugan. "A Study on seismic load characteristics and modelling of chimney structure using fem approach." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 622. http://dx.doi.org/10.14419/ijet.v7i2.8.10545.

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Chimneys are landmarks for power plants and industrial setups for modelling them using FEM approach. Chimneys are vertically and discharge, gaseous products of combustion, chemical wastes gases and exhaust air from and industry to the atmosphere. Rapid growth of industrialisation and increasing need for air pollution control as made RC chimneys as common structure in modern scenarios. With large scale industrialisation number of chimneys and stacks being constructed is increasing year by year. Here the chimney structure can be analysed by finite element analysis using FEM approach. Based on ANSYS Software, the structure can be meshed (discretized into several parts are called elements). At last, we can apply the boundary conditions and calculate its design by applying various loads.

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Kajewska-Szkudlarek, Joanna, Jan Bylicki, Justyna Stańczyk, and Paweł Licznar. "Neural Approach in Short-Term Outdoor Temperature Prediction for Application in HVAC Systems." Energies 14, no. 22 (November 10, 2021): 7512. http://dx.doi.org/10.3390/en14227512.

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An accurate air-temperature prediction can provide the energy consumption and system load in advance, both of which are crucial in HVAC (heating, ventilation, air conditioning) system operation optimisation as a way of reducing energy losses, operating costs, as well as pollution and dust emissions while maintaining residents’ thermal comfort. This article presents the results of an outdoor air-temperature time-series prediction for a multifamily building with the use of artificial neural networks during the heating period (October–May). The aim of the research was to analyse in detail the created neural models with a view to select the best combination of predictors and the optimal number of neurons in a hidden layer. To meet that task, the Akaike information criterion was used. The most accurate results were obtained by MLP 3-3-1 (r = 0.986, AIC = 1300.098, SSE = 4467.109), with the ambient-air-temperature time series observed 1, 2, and 24 h before the prognostic temperature as predictors. The AIC proved to be a useful method for the optimum model selection in a machine-learning modelling. What is more, neural network models provide the most accurate prediction, when compared with LR and SVR. Additionally, the obtained temperature predictions were used in HVAC applications: entering-water temperature and indoor temperature modelling.

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Lumley, Thomas, and Lianne Sheppard. "Assessing seasonal confounding and model selection bias in air pollution epidemiology using positive and negative control analyses." Environmetrics 11, no. 6 (2000): 705–17. http://dx.doi.org/10.1002/1099-095x(200011/12)11:6<705::aid-env444>3.0.co;2-h.

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Gupta, Medhavi, Manju Mohan, and Shweta Bhati. "Assessment of Air Pollution Mitigation Measures on Secondary Pollutants PM10 and Ozone Using Chemical Transport Modelling over Megacity Delhi, India." Urban Science 6, no. 2 (April 6, 2022): 27. http://dx.doi.org/10.3390/urbansci6020027.

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Sporadic efforts have been introduced to control emissions in Delhi, but the air quality has declined further due to the rapid development of different sectors. In this study, the impact of various mitigation scenarios on air quality for PM10, ozone, and its precursors are studied using a chemical transport model, namely WRF-Chem. The Emission Database for Global Atmospheric Research emission inventory was modified and introduced into the WRF-Chem model to assess the impact of selected emission control scenarios on different sectors. The simulations were conducted with reduced emissions for these sectors over the study domain: (a) implementation of Bharat Stage—VI norms in the transport sector, (b) conversion of fuel from coal to natural gas in the energy sector, and (c) fuel shift to LPG in the residential sector. The transport sector noted a decrease of 4.9% in PM10, 44.1% in ozone, and 18.9% in NOx concentrations with emission reduction measures. In the energy sector, a marginal reduction of 3.9% in NOx concentrations was noted, and no change was observed in PM10 and ozone concentrations. In the residential sector, a decrease of 8% in PM-10, 47.7% in ozone, and 49.8% in NOx concentrations were noted. The VOC-to-NOx ratios were also studied, revealing the ozone production over the study domain was mostly VOC-limited. As the inclusion of control measures resulted in varying levels of reduction in pollutant concentrations, it was also studied in the context of improving the air quality index. The WRF-Chem model can be successfully implemented to study the effectiveness of any regulated control measures.

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Madhav Sai, N., S. Lekshmi, and P. V. Manitha. "Modelling of an Electric Vehicle." Journal of Physics: Conference Series 2312, no. 1 (August 1, 2022): 012055. http://dx.doi.org/10.1088/1742-6596/2312/1/012055.

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Abstract Electric Vehicles (EVs) are considered to be as an essential aspect in the immediate term to reduce global emissions and to improve local air quality. The automobile industry will have a substantial transformation in the upcoming five to ten years than it has in the last few decades. The development of technologies promoted a better eco-friendly version of EVs. Electric cars in short are the thought of batteries on wheels and are the future of motoring. Growing concerns over the limited supply of fossil fuels led to the invention of electric cars which truly rely upon the use of an electric drive system rather upon the Internal Combustion Engines. In addition, electric cars diminished the pressure of massive carbon emissions, urban pollution, greenhouse gases, and city noises. This paper proposes an investigative study on electric vehicle modelling, simulation, and step-by-step control design for an effective environment. For the purpose of modelling and simulation of an electric vehicle MATLAB/SIMULINK software is used.

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Vicente, Ana Belen, Pablo Juan, Sergi Meseguer, Laura Serra, and Sergio Trilles. "Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies." Sustainability 11, no. 20 (October 22, 2019): 5857. http://dx.doi.org/10.3390/su11205857.

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A statistical modelling of PM10 concentration (2006–2015) is applied to understand the behaviour, to know the influence of the variables to exposure risk, to treat the missing data to evaluate air quality, and to estimate data for those sites where they are not available. The study area, Castellón region (Spain), is a strategic area in the framework of EU pollution control. A decrease of PM10 is observed for industrial and urban stations. In the case of rural stations, the levels remain constant throughout the study period. The contribution of anthropogenic sources has been estimated through the PM10 background of the study area. The behaviour of PM10 annual trend is tri-modal for industrial and urban stations and bi-modal in the case of rural stations. The EU Normative suggests that 90% of the data per year are necessary to control air quality. Thus, interpolation statistical methods are presented to fill missing data: Linear Interpolation, Exponential Interpolation, and Kalman Smoothing. This study also focuses on testing the goodness of these methods in order to find the ones that better approach the gaps. After analyzing graphically and using the RMSE the last method is confirmed to be the best option.

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Gong, Jiyoung, Changsub Shim, Ki-Chul Choi, and Sungyong Gong. "The Characteristics of PM2.5 Pollution and Policy Implications in Chungcheong Region." Journal of Korean Society of Environmental Engineers 43, no. 6 (June 30, 2021): 407–18. http://dx.doi.org/10.4491/ksee.2021.43.6.407.

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Objectives : This study aims to discuss air quality policy improvement that reflect regional characteristics through analyzing recent PM2.5 concentration, air pollutant emission sources and those contributions to annual PM2.5 concentration in Chungcheong region (Daejeon Metropolitan City, Sejong Metropolitan Autonomous City, the Province of Chungcheongnam-do, and Chungcheongbuk-do) in South Korea. In addition, we identified the characteristics of the PM2.5 pollution at the level of fundamental local government, and demonstrated the number of vulnerable population exposed to high level of PM2.5 concentration in order to propose policy implications in Chungcheong region.Methods : Based on the national emissions estimates (CAPSS: Clean Air Policy Support System) and air quality modelling system, major sectors/sources of air pollutants emission and national contributions of PM2.5 concentrations in Chungcheong region were analyzed. Furthermore, the study identified the number of people exposed to the higher PM2.5 concentrations (>25 µg/m3) by the measurement data and demographics available in 2019.Results and Discussion : The national air pollutants emissions in Chungcheong region were emitted from Chungnam (about 59% of NOx emission volume, 89% of SOx, 70% of NH3, 54% of VOCs, 79% of PM2.5, and 68% of TSP respectively), mainly from industry, domestic, energy, and road sector. According to the results of the air quality modelling, Chungcheong region also had the largest contribution on the average annual PM2.5 concentration in South Korea (27%). Chungnam emitted the largest emission volume of air pollutants, mainly from industry and power generation sectors (especially in Dangjin, Seosan, and Boryeong), while Asan, Yesan, Hongseong, and Cheongyang were classified as the areas with higher PM2.5 concentrations (>25 µg/m3), showing a gap between the areas with large emission volume and high concentration. Chungbuk and Sejong had higher annual PM2.5 concentration due to the influence of external sources and their geographical characteristics. The largest vulnerable population (over 65 years old and under 18 years old) exposed to high PM2.5 concentrations annually lived in Cheongju. Chungbuk had about 40% more air pollutant emission volume than Chungnam, but about 17% more vulnerable population.Conclusions : At the current stage of “master plan” in Chungcheong region, it is important to mitigate air pollutants emissions on the basis of the local emissions characteristic at the level of fundamental local government (such as industry sector in Dangjin, Seosan, and Danyang/ Domestic buring in Cheongju, Cheonan, and Daejeon/power generation in Boryeong, Taean and Dangjin/ road in Daejeon, Cheongju, and Cheoan). In addition, Chungbuk requires management of the areas with higher PM2.5 concentration such as Goesan, Boeun, Okcheon, and Yeongdong located outside “air control zone”. To reduce high level of PM2.5 concentration in Chungcheong region, cooperation with neighboring local governments such as Gyeonggi Province is crucial, and policy solutions are needed between the stakeholders to resolve the disparity issues between areas with larger emission volume and higher PM2.5 concentration.

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Gallagher, J., L. W. Gill, and A. McNabola. "Numerical modelling of the passive control of air pollution in asymmetrical urban street canyons using refined mesh discretization schemes." Building and Environment 56 (October 2012): 232–40. http://dx.doi.org/10.1016/j.buildenv.2012.03.013.

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K�geson, P. "Control techniques and strategies for regional air pollution from the transport sector the European case." Water, Air, & Soil Pollution 85, no. 1 (1995): 225–36. http://dx.doi.org/10.1007/bf00483703.

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Bai, Jiayu, Feng Liu, Xiaodai Xue, Wei Wei, Laijun Chen, Guohua Wang, and Shengwei Mei. "Modelling and control of advanced adiabatic compressed air energy storage under power tracking mode considering off-design generating conditions." Energy 218 (March 2021): 119525. http://dx.doi.org/10.1016/j.energy.2020.119525.

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Wojnar, Sławomir, Tomáš Polóni, Peter Šimončič, Boris Rohal̓-Ilkiv, Marek Honek, and Jozef Csambál. "Real-time implementation of multiple model based predictive control strategy to air/fuel ratio of a gasoline engine." Archives of Control Sciences 23, no. 1 (March 1, 2013): 93–106. http://dx.doi.org/10.2478/v10170-011-0044-9.

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Abstract Growing safety, pollution and comfort requirements influence automotive industry ever more. The use of three-way catalysts in exhaust aftertreatment systems of combustion engines is essential in reducing engine emissions to levels demanded by environmental legislation. However, the key to the optimal catalytic conversion level is to keep the engine air/fuel ratio (AFR) at a desired level. Thus, for this purposes more and more sophisticated AFR control algorithms are intensively investigated and tested in the literature. The goal of this paper is to present for a case of a gasoline engine the model predictive AFR controller based on the multiple-model approach to the engine modeling. The idea is to identify the engine in particular working points and then to create a global engine's model using Sugeno fuzzy logic. Opposite to traditional control approaches which lose their quality beside steady state, it enables to work with satisfactory quality mainly in transient regimes. Presented results of the multiple-model predictive air/fuel ratio control are acquired from the first experimental real-time implementation on the VW Polo $1390 cm^3$ gasoline engine, at which the original electronic control unit (ECU) has been fully replaced by a dSpace prototyping system which execute the predictive controller. Required control performance has been proven and is presented in the paper.

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Brandt, J., J. D. Silver, J. H. Christensen, M. S. Andersen, J. H. Bønløkke, T. Sigsgaard, C. Geels, et al. "Contribution from the ten major emission sectors in Europe and Denmark to the health-cost externalities of air pollution using the EVA model system – an integrated modelling approach." Atmospheric Chemistry and Physics 13, no. 15 (August 12, 2013): 7725–46. http://dx.doi.org/10.5194/acp-13-7725-2013.

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Abstract. We have developed an integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain, to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors, which can be used to support policy-making with respect to emission control. Central for the system is a newly developed tagging method capable of calculating the contribution from a specific emission source or sector to the overall air pollution levels, taking into account the non-linear atmospheric chemistry. The main objective of this work is to identify the anthropogenic emission sources in Europe and Denmark that contribute the most to human health impacts. In this study, we applied the EVA system to Europe and Denmark, with a detailed analysis of health-related external costs from the ten major emission sectors and their relative contributions. The paper contains a thorough description of the EVA system, the main results from the assessment of the main contributors and a discussion of the most important atmospheric chemical reactions relevant for interpreting the results. The main conclusion from the analysis is that the major contributors to health-related external costs are major power production, agriculture, road traffic, and non-industrial domestic combustion, including wood combustion. We conclude that when regulating the emissions of ammonia from the agricultural sector, both the impacts on nature and on human health should be taken into account. This study confirms that air pollution constitutes a serious problem for human health and that the related external costs are considerable. The results in this work emphasize the importance of defining the right questions in the decision-making process. The results from assessing the impacts from each emission sector depend clearly on the assumption that the other emission sectors are not changed, especially emissions changing concentrations of atmospheric OH and therefore lifetimes of other chemical species.

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Jairam, Karthick, Feroskhan Mohammed Musthafa, Kishorre Annanth Vijayan, and Manimaran Renganathan. "Computational investigations on port injected DEE in a biogas inducted HCCI engine." International Journal for Simulation and Multidisciplinary Design Optimization 12 (2021): 9. http://dx.doi.org/10.1051/smdo/2021010.

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Owing to global climate change and atmospheric pollution, several automobile manufacturing companies look for homogeneously charged engines to satisfy strict emission levels. In the present work, computational fluid dynamics (CFD) investigations have been carried out to showcase the homogeneity of air-fuel mixture formation by port fuel injection and manifold fuel injection of a Biogas-Diethyl Ether (DEE) homogeneous charge compression engine (HCCI). The distributions of equivalence ratio based on fuel and the total air-fuel mixture is formulated and found to be in close agreement with the literature. Earlier investigations have shown that the use of biogas as a single fuel causes lower power output compared to other alternative fuels. Hence the present study is planned to use biogas with DEE as an ignition improver via fuel injection systems to find the best suitable fuel injection system. In the mesh independent study, port injection mode is found to perform better against the manifold injection mode when compared with the homogeneity factor. Iso-volumes of excess-air ratio based on biogas, diethyl ether and other variables such as the density, turbulent kinetic energy, turbulent dissipation rate of air-fuel mixture influencing the homogeneity and equivalence ratio are studied for better in-cylinder distribution under the port injection mode.

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Liu, Baoshuang, Yanyang Wang, He Meng, Qili Dai, Liuli Diao, Jianhui Wu, Laiyuan Shi, Jing Wang, Yufen Zhang, and Yinchang Feng. "Dramatic changes in atmospheric pollution source contributions for a coastal megacity in northern China from 2011 to 2020." Atmospheric Chemistry and Physics 22, no. 13 (July 5, 2022): 8597–615. http://dx.doi.org/10.5194/acp-22-8597-2022.

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Abstract. Understanding the effectiveness of long-term air pollution regulatory measures is important for control policy formulation. Efforts have been made using chemical transport modelling and statistical approaches to evaluate the efficacy of the Clean Air Action Plan (CAAP; 2013–2017) and the Blue Sky Protection Campaign (BSPC; 2018–2020) enacted in China. Changes in air quality due to reduction in emissions can be masked by meteorology, making it highly challenging to reveal the real effects of control measures. A knowledge gap still existed with respect to how sources changed before and after the CAAP and BSPC were implemented, respectively, particularly in coastal areas where anthropogenic emissions mixed with additional natural sources (e.g. marine aerosol). This work applied a machine-learning-based meteorological normalization approach to decouple the meteorological effects from air quality trend in a coastal city in northern China (Qingdao). Secondly, the relative changes in source contributions to ambient PM2.5 with a ∼ 10-year observation interval (2011–2012, 2016, and 2019) were also investigated. We discovered that the largest emission reduction section was likely from coal combustion as the meteorologically normalized SO2 dropped by ∼ 15.5 % yr−1, and the annual average dispersion-normalized SO42- decreased by ∼ 41.5 %. Change in the meteorologically normalized NO2 was relatively stable (∼ 1.0 % yr−1), and NO3- changed inappreciably in 2016–2019 but was significantly higher than that prior to the CAAP. Crustal dust decreased remarkably after the CAAP began. Industrial emissions, for example, steel-related smelting, decreased after 2016 due to the relocation of steel-making enterprises. Note that vehicle emissions were increased in importance as opposed to the other primary sources. Similar to other megacities, Qingdao is also at risk of increased ozone pollution that in turn facilitates secondary-particle formation in the future. The policy assessment approaches applied in this work also work for other places where air quality management is highly in demand to reduce air pollution.

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Benítez, Ángel, Jefferson Medina, Cristina Vásquez, Talía Loaiza, Yesenia Luzuriaga, and James Calva. "Lichens and Bromeliads as Bioindicators of Heavy Metal Deposition in Ecuador." Diversity 11, no. 2 (February 25, 2019): 28. http://dx.doi.org/10.3390/d11020028.

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We evaluated heavy metal deposition in Parmotrema arnoldii and Tillandsia usneoides in response to air pollution in Loja city, Ecuador. We assessed heavy metal (cadmium, copper, manganese, lead and zinc) content in these organisms at nine study sites inside Loja city and three control sites in nearby forests. Concentrations of all studied heavy metals (i.e., cadmium (Cd), copper (Cu), lead (Pb), manganese (Mn) and zinc (Zn)) were highest in downtown Loja. Our study confirms that passive monitoring using lichens and/or bromeliads can be an efficient tool to evaluate heavy metal deposition related to urbanization (e.g., vehicle emissions). We recommend these organisms to be used in cost-effective monitoring of air pollution in tropical countries.

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Vishnevetskiy, Vyacheslav, and Vladislav Popruzhniy. "Open access system of life quality management on the basis of spatial modelling of pollution in the coastal areas." E3S Web of Conferences 140 (2019): 09004. http://dx.doi.org/10.1051/e3sconf/201914009004.

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The quality of human life consists of many parameters: physical, psychological, level of independence, social life and the environment. The latter, in turn, includes safety, ecology, security, availability and quality of medical care, information, training opportunities, and life. The system of life quality evaluation, combining an objective component (indicators of water and air quality, morbidity) and subjective (the degree of satisfaction of residents with water quality) was developed. “Crowd survey” data block realizes the function of “Open access”. The system of life comfort includes information on people morbidity and the main consumed water and air parameters that affect the satisfaction with natural resources and health. Such system units as «Input Interface» and «Interaction Interface» have been developed as a mobile application. In addition, system includes geographic information system that allows visualizing, analyzing and predicting the state of the object. Thematic maps of spatial pollution of the Taganrog Bay at control points were simulated. The main features of the system are shown and recommendations for its application are offered.

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Journal articles on the topic 'Air pollution modelling and control'

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