Air Quality Management System Research Articles

МОНИТОРИНГ КАЧЕСТВА АТМОСФЕРНОГО ВОЗДУХА ЗАПАДНО-КАЗАХСТАНСКОГО РЕГИОНА: ПРИНЦИПЫ, МЕТОДЫ, ПОДХОДЫ

The main approaches and methods of studying the characteristics and conditions of atmospheric pollution on the example of Western Kazakhstan are considered. The classification and grouping of applied approaches by topics, methods, time intervals and other relevant criteria was conducted. An analysis of the available information on the sources and volumes of emissions into the atmosphere, as well as on the systems for monitoring the pollution of the air basin, was carried out. It is shown that to increase the effectiveness of the atmospheric air quality management system, it is expedient to use a complex approach taking into account the influence of meteorological factors and synoptic conditions that determine different levels of pollution. An analytical review of modern methods of modeling the spread of pollutants in atmospheric air showed the feasibility of using statistical methods integrated with deep machine learning and the Eulerian continuum model of turbulent diffusion. The obtained conclusions will allow further use of an integrated approach to improve the atmospheric air quality management system of the studied region.

Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil

Abstract. Developing air quality management systems to control the impacts of air pollution requires reliable data. However, current initiatives do not provide datasets with large spatial and temporal resolutions for developing air pollution policies in Brazil. Here, we introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database of air quality and its drivers in Brazil. BRAIN encompasses hourly datasets of meteorology, emissions, and air quality. The emissions dataset includes vehicular emissions derived from the Brazilian Vehicular Emissions Inventory Software (BRAVES), industrial emissions produced with local data from the Brazilian environmental agencies, biomass burning emissions from FINN – Fire INventory from the National Center for Atmospheric Research (NCAR), and biogenic emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (https://doi.org/10.57760/sciencedb.09858, Hoinaski et al., 2023a; https://doi.org/10.57760/sciencedb.09886, Hoinaski et al., 2023b). The meteorology dataset has been derived from the Weather Research and Forecasting Model (WRF) (https://doi.org/10.57760/sciencedb.09857, Hoinaski and Will, 2023a; https://doi.org/10.57760/sciencedb.09885, Hoinaski and Will, 2023c). The air quality dataset contains the surface concentration of 216 air pollutants produced from coupling meteorological and emissions datasets with the Community Multiscale Air Quality Modeling System (CMAQ) (https://doi.org/10.57760/sciencedb.09859, Hoinaski and Will, 2023b; https://doi.org/10.57760/sciencedb.09884, Hoinaski and Will, 2023d). We provide gridded data in two domains, one covering the Brazilian territory with 20×20 km spatial resolution and another covering southern Brazil with 4×4 km spatial resolution. This paper describes how the datasets were produced, their limitations, and their spatiotemporal features. To evaluate the quality of the database, we compare the air quality dataset with 244 air quality monitoring stations, providing the model's performance for each pollutant measured by the monitoring stations. We present a sample of the spatial variability of emissions, meteorology, and air quality in Brazil from 2019, revealing the hotspots of emissions and air pollution issues. By making BRAIN publicly available, we aim to provide the required data for developing air quality policies on municipal and state scales, especially for under-developed and data-scarce municipalities. We also envision that BRAIN has the potential to create new insights into and opportunities for air pollution research in Brazil.​​​​​​​

Prospects of the development and harmonization of hygienic standardization taking into account the risk of odour in the ambient air

Introduction. The presence of a specific odour in the ambient air in the areas where various enterprises are located with formal compliance with environmental legislation indicates the need to update the methodology of hygienic standardization of odourous substances.
 The purpose of the work is to analyze modern methods of the establishment of standards for odourous complex multicomponent mixtures of substances in the atmospheric air and substantiate ways to harmonize them in this field of knowledge.
 Materials and methods. The paper systematizes existing approaches to regulating the quality of atmospheric air in areas where odourous emissions sources are located, taking into account certain provisions of regulatory and methodological documents, publications on approaches, and criteria for quantitative sanitary and hygienic assessment of the quality of the environment and public health, as well as the authors’ long-term experience in this field.
 Results. The basic principles of hygienic standardization of the permissible content of odorous mixtures of substances in the atmospheric air taking into account their odour are formulated. The substantiation of hygienic standards is carried out with the allocation of substances identified as priority (indicator), based on the results of studying the production technology and the formation of emissions, olfactory properties of the mixture under experimental conditions, with the possibility of monitoring the established standard in atmospheric air by certified instrumental methods of analysis.
 Limitations. The limitations of the study are due to the fact that this article does not fully reflect the issues of the development of the entire atmospheric air quality management system taking into account the risk of odour outside the focus of this work, which will be covered in the preparation of the following articles.
 Conclusion. The ongoing process of harmonization of domestic and foreign approaches used in hygienic standardization including the field of regulation of atmospheric air pollution by specific odours makes it necessary to significantly expand approaches to the issues of rationing and assessment of environmental pollution by complex multicomponent emissions of odour-source enterprises taking into account modern experience.

DEVELOPMENT AND RESEARCH OF THE FUNCTIONAL POSSIBILITIES OF THE AUTOMATED FUZZY INDOOR AIR QUALITY MANAGEMENT SYSTEM OF PRODUCTION PREMISES

Purpose. Development of a fuzzy indoor air quality control system and research of the efficiency of an automated complex for increasing the concentration of air ions, namely a small-sized ultrasonic generator of air ions and a pump unit in the conditions of a complex ventilated air environment of work premises. Design/methodology/approach. The comprehensive research carried out is important in the context of the development of measures and means and the research of their effectiveness in maintaining the aeroionic regime of industrial premises at the regulatory level. Conclusions. The structure of an intelligent indoor air quality control system is proposed, which implements a combined change in the rotation speed of the fan and pump and the power of the ultrasonic aeroion generator. For the first time, a formalized criterion for the optimality of the indoor air quality management system is proposed, which depends on individual preferences of people regarding the comfort of the production environment and standardized parameters of temperature, relative humidity, and concentration of air ions in the working space. The task of the intelligent control system is to minimize the proposed criterion. Limitations/consequences of research. The proposed recommendations are universal and can be used in various areas of business to create safe and harmless working conditions in production. Practical consequences. The use of the developed small-sized ultrasonic aeroion generator not only significantly increases the concentration of aeroions in the working area, but also due to the baloelectric effect minimizes the negative impact inherent in most existing ionizers, namely the generation of ozone and nitrogen oxide, which significantly improves indoor air quality and thereby increases the level of industrial safety and labor protection. Originality/meaning. The existing control systems assume that standard ionizers (corona discharges) are inserted in the room, so there was a need to develop and research a modern intelligent system for controlling the quality of the indoor air in the working area of industrial premises using an aeroion generator and automated displacement ventilation.

Roles of Artificial Intelligence and Machine Learning in Enhancing Construction Processes and Sustainable Communities

Machine Learning (ML), a subset of Artificial Intelligence (AI), is gaining popularity in the architectural, engineering, and construction (AEC) sector. This systematic study aims to investigate the roles of AI and ML in improving construction processes and developing more sustainable communities. This study intends to determine the various roles played by AI and ML in the development of sustainable communities and construction practices via an in-depth assessment of the current literature. Furthermore, it intends to predict future research trends and practical applications of AI and ML in the built environment. Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, this study highlights the roles that AI and ML technologies play in building sustainable communities, both indoors and out. In the interior environment, they contribute to energy management by optimizing energy usage, finding inefficiencies, and recommending modifications to minimize consumption. This contributes to reducing the environmental effect of energy generation. Similarly, AI and ML technologies aid in addressing environmental challenges. They can monitor air quality, noise levels, and waste management systems to quickly discover and minimize pollution sources. Likewise, AI and ML applications in construction processes enhance planning, scheduling, and facility management.

Modeling the Distribution of Radionuclides in the Air and on the Soil Surface

Mathematical and numerical methods are used to simulate physical and chemical processes when building models of pollutants dispersion in the air and on the soil surface. Based on meteorological data and information on the source of emissions, these models characterize both the primary pollutants entering the atmosphere directly and the secondary ones formed as the result of complex chemical reactions. These models are important for the air quality management system, as they allow monitoring emissions into the atmosphere, predicting their distribution, as well as developing effective strategies intended for reducing harmful substances in the atmosphere. The article presents an overview of computational methods used to simulate the pollutants dispersion in atmospheric air and on the soil surface, such as the Gaussian torch model, the Lagrangian dispersion stochastic model, and the Eulerian model of atmospheric diffusion. The practical application of the considered models showed sufficient reliability and validity of the air and soil pollution levels forecast. The simulation uses computer programs that include algorithms for solving the mathematical equations that control pollutant dispersion. The dispersion models are used to estimate the concentration of air pollutants or toxins. They can also be used to predict future concentrations under certain scenarios. They are useful for studying the pollutants that disperse over long distances and can initiate reactions in the atmosphere. Such software products are as follows: AEROPOL, AERMOD, GRAL, TAPM CSIRO, CALPUFF, HYSPLIT, etc. A method of processing information about the pollution sources and the environmental parameters, based on the HYSPLIT program, is proposed to form maps of the volume and surface activity of radionuclides. This method was applied to analyze the process of the plutonium isotopes dispersion as a result of the movement of air masses in the places of fires in April 2020 in the exclusion zone of the Chornobyl NPP, as well as the associated hazard for the population health and the environment.

Indoor Air Pollution Monitoring System

This work presents an investigation of indoor air pollution using a combination of biomedical engineering (BME) sensors and indoor air sensors. Indoor air quality is a significant factor affecting human health, and monitoring and controlling indoor air pollution have become essential for indoor environ- mental quality management. In this study, BME techniques are employed to analyze indoor air pollutants, and an indoor air sensor is used to measure and monitor the indoor air quality in real-time. The study involves the deployment of a network of sensors in an indoor environment, data collection, and analysis using machine learning algorithms. The results show that the combination of BME and indoor air sensors is an effective approach for detecting and mitigating indoor air pollution, and provides valuable insights for the development of indoor air quality management systems. This study contributes to the growing body of research on indoor air quality and provides new strategies for improving indoor air quality and safeguarding human health.

Indoor Air Quality Management under Button Up Conditions

Abstract: Maintaining the desired Indoor Air Quality under the Button Up Conditions, has always been a challanging task. The present invention provides Indoor Air Quality Management System Under Button Up Conditions[1]. The system is operated in a Normal, Button Up or Filtration mode. The invention comprises computer based fully automated system which include six sub systems i.e., CO2 Removal System, Odour/ TVOC Removal System, Oxygen Replenishment System, Compressed Air System, NBC Filtration System and Facility Management System that operate in coordination with one another to maintain the desired CO2, Oxygen and Positive Pressure levels in facility. CO2 adsorbents which adsorb CO2 from the air by way of not only their chemical reactions but also or only by way of their molecular structure and other properties. Activation of CO2 Removal System is based on the signal from the CO2 sensor that is located in the return air duct of the air handling units serving the buildings. The CO2 Removal System does not depend only on one type of absorbent/adsorbent material. All the six sub systems are fully integrated with one another to always maintain the desired levels of CO2, Oxygen and positive pressure in the facility and filter away any hazardous contaminants from the air under all three modes of operation i.e., Normal Mode, Button Up Mode or Filtration Mode as felt necessary. The Bunkerman absorbents used in the system, showed CO2 absorbent capacity of about 35% to 42% by weight. The adsorbent capacity of the Bunkerman Adsorbents and molecular sieves were observed to be between 15 to 18. An absorbent capacity of 30% and adsorbent capacity of 12% can be safely adopted for CO2 removal filters in the systems. The proposed Bunkerman Indoor Air Quality Management System was effectively able to ensure the recommended levels of CO2 and TVOC [2,3] in the facility tested during Real Button Up Mode.

Automated control and control system of emissions into the atmospheric air of thermoelectric-power industries

The article describes new approaches to the systems of automated monitoring and control of emissions into the atmospheric air of thermoelectric-power industries. The purpose of creating such systems is to reduce the level of impact on the air of residential areas and control its quality. The basis of this air quality management system is the continuous measurement and registration of pollutant concentrations both at emission sources and in the air of residential areas. Due to the analysis of meteorological conditions in combination with the use of the method of marker compounds, statistical processing of the obtained analytical data, a decision is made not only about the degree of impact on the environment, but also the determination of the specific polluter of this contamination. The complexity of this goal lies in the need to maintain a large fleet of analytical measuring instruments with varying degrees of sensitivity. The article proposes methods to reduce the diversity of the instrument base, which leads to an improvement in the performance of automated air quality control devices and to simplify the maintenance of such systems. The use of such systems allows for the optimization and digitalization of air quality management systems in the residential area as a whole through the use of various controllers and soft hardware.

Population Health Risk and Harm Indicators in the System of New Mechanisms for Air Quality Monitoring and Management

Introduction: The article dwells on major legislative and methodical aspects related to the latest update of the system for air quality management in the country. Objective: To summarize the experience in applying the health risk assessment procedure to the system of new mechanisms for ambient air quality monitoring and management. Materials and methods: The study relied on the results obtained by summary estimates of dispersion of emissions from 1.5 to 6.5 thousand sources per city and health risk assessment in twelve cities included in the Federal Clean Air Project. We also analyzed the results of biomedical studies (about two thousand chemical, immunological, and clinical tests done in 2020–2022) in and outside the zones of influence of mining and chemical industries. Results: Health risks were estimated as unacceptable in the cities included in the experiment on introducing new emission control technologies. In some cases, risks were rated as “very high” for diseases of the respiratory system, blood and blood-forming organs, musculoskeletal system, etc. We substantiated the lists of priority pollutants for emission monitoring and quoting and the lists of priority objects generating unacceptable risks. We demonstrate that the evaluation of health damage as an indicator of realized risks under certain circumstances can serve as yet another evidence of adverse health effects of environmental pollution. We suggest a fundamental algorithm for including the assessment of human health risks and damages into the system of air quality management for elaboration of the existing regulatory and methodological framework of monitoring and standardization. Conclusions: The procedures of assessing health risks and damages are a significant component of air quality management. Their results ensure adequacy of the monitoring programs to the current situation, make managerial actions more targeted and precise, and guarantee optimal achievement of the major goal to preserve public health through safe and comfortable environment.

Air pollution in Delhi, India: It's status and association with respiratory diseases.

The policymakers need research studies indicating the role of different pollutants with morbidity for polluted cities to install a strategic air quality management system. This study critically assessed the air pollution of Delhi for 2016–18 to found out the role of air pollutants in respiratory morbidity under the ICD-10, J00-J99. The critical assessment of Delhi air pollution was done using various approaches. The mean PM2.5 and PM10 concentrations during the measurement period exceeded both national and international standards by a wide margin. Time series charts indicated the interdependence of PM2.5 and PM10 and connection with hospital visits due to respiratory diseases. Violin plots showed that daily respiratory disease hospital visits increased during the winter and autumn seasons. The winter season was the worst from the city’s air pollution point of view, as revealed by frequency analyses. The single and multi-pollutant GAM models indicated that short-term exposure to PM10 and SO2 led to increased hospital visits due to respiratory diseases. Per 10 units increase in concentrations of PM10 brought the highest increase in hospital visits of 0.21% (RR: 1.00, 95% CI: 1.001, 1.002) at lag0-6 days. This study found the robust effect of SO2 persisted in Delhi from lag0 to lag4 days and lag01 to lag06 days for single and cumulative lag day effects, respectively. While every 10 μg m-3 increase of SO2 concentrations on the same day (lag0) led to 32.59% (RR: 1.33, 95% CI: 1.09, 1.61) rise of hospital visits, the cumulative concentration of lag0-1 led to 37.21% (RR: 1.37, 95% CI:1.11, 1.70) rise in hospital visits which further increased to even 83.33% (RR: 1.83, 95% CI:1.35, 2.49) rise at a lag0-6 cumulative concentration in Delhi. The role of SO2 in inducing respiratory diseases is worrying as India is now the largest anthropogenic SO2 emitter in the world.

Metal-organic framework-based materials for the abatement of air pollution and decontamination of wastewater.

Developing new and efficient technologies for environmental remediation is becoming significant due to the increase in global concerns such as climate change, severe epidemics, and energy crises. Air pollution, primarily due to increased levels of H2S, SOx, NH3, NOx, CO, volatile organic compounds (VOC), and particulate matter (PM) in the atmosphere, has a significant impact on public health, and exhaust gases harm the natural sulfur, nitrogen, and carbon cycles. Similarly, wastewater discharged to the environment with metal ions, herbicides, pharmaceuticals, personal care products, dyes, and aromatics/organic compounds is a risk for health since it may lead to an outbreak of waterborne pathogens and increase the exposure to endocrine-disrupting agents. Therefore, developing new and efficient air and water quality management systems is critical. Metal-organic frameworks (MOFs) are novel materials for which the main application areas include gas storage and separation, water harvesting from the atmosphere, chemical sensing, power storage, drug delivery, and food preservation. Due to their versatile structural motifs that can be modified during synthesis, MOFs also have a great promise for green applications including air and water pollution remediation. The motivation to use MOFs for environmental applications prompted the modification of their structures via the addition of metal and functional groups, as well as the creation of heterostructures by mixing MOFs with other nanomaterials, to effectively remove hazardous contaminants from wastewater and the atmosphere. In this review, we focus on the state-of-the-art environmental applications of MOFs, particularly for water treatment and air pollution, by highlighting the groundbreaking studies in which MOFs have been used as adsorbents, membranes, and photocatalysts for the abatement of air and water pollution. We finally address the opportunities and challenges for the environmental applications of MOFs.

Air quality monitoring and management system model of vehicles based on the internet of things

The design of an air quality monitoring system is a recent trend and emerging research topic using IoT and wireless sensor technology. The massive number of automobiles entering metropolitan areas contributes to increased air pollution and lower air quality, which leads to serious health problems. The paper’s primary goal is to introduce a vehicular pollution monitoring system model that can detect and measure pollutants like carbon monoxide and smoke produced by automobiles. The proposed module consists of sensors that can detect the pollutants, carbon monoxide, and smoke released by a vehicle. A Node Micro-Controller Unit (NodeMCU) will work as the brain of the sensor node and communicator with the server through wireless fidelity. The suggested system model can monitor automobile pollution, and if any vehicle exceeds a certain threshold value, it will be reported to the traffic department and the owner of the vehicle. The proposed system model is straightforward and simple, and it is predicted to be inexpensive.

Multilevel RNN-Based PM10 Air Quality Prediction for Industrial Internet of Things Applications in Cleanroom Environment

Adequate air ventilation systems and maintaining environmental air quality are essential things that need to be considered to create an excellent industrial environment in a company. Operating or maintaining ecological air quality is a challenge for companies to optimize the existing work environment. Especially at the economic and business level in the company are facing the main problems. In this case, monitoring and predicting future air quality are needed to maintain air quality conditions. PM10 concentration, humidity, and temperature were used to predict annual and seasonal indoor air quality using a recurrent neural network (RNN) and long short-term memory (LSTM). In this paper, we propose the IAQP method for air quality management systems that combines indoor air quality forecasting based on real-time data. To measure indoor air quality, we predict the outcome from the IIoT sensor and LoRa sensor. The result of prediction is that the multilevel RNN model outperformed the LSTM, as the model demonstrated excellent results and feasibility.

MODERN APROACH TO MICROCLIMATE CONTROL ON BOARD SHIPS

Ambient and indoor air pollution have high impact on public health. Safety of indoor air is crucial for well-being and stress tolerance of seafarers due to their prolonged stay in the environment characterized by adjacency of work and leisure premises. Flaws in ventilation and air distribution systems may lead to infiltration and accumulation of pollutants in air of living and recreation premises. However, available onboard HVAC systems designs are not fit to ensure cleanliness and quality of the indoor air of ships accommodation. In this study a new approach for indoor air quality management on board merchant ships is proposed. Air quality standards and requirements analyzed and formal representation formulated. Approximation techniques for thermal comfort index PMV reviewed and computationally efficient polynomial representation proposed. Unified dynamic model of microclimate, thermal comfort and gas composition of air is developed. Model performance was studied in simulation environment with superstructure microclimate model of a real ship. As a proof of the hypothesis a preliminary prototype developed and tested on board of gas carrier vessel. A proposed control optimization problem statement allows implementation of a wide range of indoor air quality and comfort management systems at scale. Prototype multiparameter controller based on microprocessor technology showed potential of performance improvement and scalability for development of distributed control systems.

The quality of the first and second Vaal Triangle Airshed Priority Area (VTAPA) Air Quality Management Plans

In response to deteriorating air quality, South Africa implemented national programmes that aim to manage and regulate ambient air quality and air pollution. Air Quality Management Plans (AQMPs) are clear outlines of measures and resources needed to achieve air quality objectives in a given geographical area and require support from government, business, industry, non-governmental organisations (NGOs) and the public. The success of the AQMPs depends primarily on the support of all stakeholders and the quality of the management plan. The Vaal Triangle Airshed Priority Area (VTAPA) was declared in 2006 as an area where ambient air quality standards are exceeded or may cause adverse air quality impacts. This research study focused on the VTAPA to evaluate the quality of the first and second-generation AQMPs for the VTAPA. Quality evaluation includes an analysis of procedures, processes, methods and documents. Effectiveness refers to the results of individual activities; therefore, the extent to which the AQMP met the expected outcomes of the review package defined the quality of the AQMP report. Both the first and draft second-generation AQMPs were considered to be of good quality. The first-generation AQMP was found to be of better quality than that of the draft second-generation AQMP. Funding mechanisms need to be investigated to assist in implementing intervention strategies in the AQMP as both the first and draft second-generation AQMPs were found to lack the potential to secure funds. Though the draft second-generation AQMP was found to be of lesser quality, the source apportionment study for identification of all sources as well as a better-outlined air quality management system was found to be good improvements to the AQMP.

Impact of local air quality management policies on emergency hospitalisations for respiratory conditions in the North West Coast region of England: a longitudinal controlled ecological study

BackgroundAir quality is monitored at a local level in the UK as part of the Local Air Quality Management (LAQM) system. If air quality objectives within an area are not achieved an Air Quality Management Area (AQMA) is declared and action plan developed. The efficacy of this system in reducing air pollution has increasingly come into question, however very little is known about its impact on health or health inequalities. We therefore investigated the effect of declaring an AQMA on emergency hospitalisations for respiratory conditions in the North West Coast region of England, and examined whether the effect differed between more compared to less deprived neighbourhoods.MethodsThis longitudinal controlled ecological study analysed neighbourhoods located within or touching the boundaries of AQMAs declared in the North West Coast region between 2006 and 2016. Each of these intervention neighbourhoods were matched with five control neighbourhoods which had never been located within/touching an AQMA boundary. Difference-in-differences methods were used to compare the change in hospitalisation rates in the intervention neighbourhoods to the change in hospitalisation rates in the matched control neighbourhoods, before and after the declaration of an AQMA.ResultsIn total, 108 intervention neighbourhoods and 540 control neighbourhoods were analysed over the period 2005–2017, giving a total sample size of 8424 neighbourhood-years. Emergency hospitalisations for respiratory conditions decreased in the intervention neighbourhoods by 158 per 100,000 per year [95% CI 90 to 227] after an AQMA was declared relative to the control neighbourhoods. There was a larger decrease in hospitalisation rates following the declaration of an AQMA in more compared to less income deprived neighbourhoods.ConclusionsOur results suggest the LAQM system has contributed to a reduction in emergency hospitalisations for respiratory conditions, and may represent an effective strategy to reduce inequalities in health. These findings highlight the importance of measuring the success of air quality policies not just in terms of air pollution but also in terms of population health.

A phased city air quality management approach for faster clean air progress

Clean air is a basic human right, yet over 90% of people are exposed to unhealthy levels of pollution, resulting in over 5 million deaths each year. The burden of air pollution is the greatest in densely populated cities; and will continue to grow without rapid and aggressive action to reduce pollution emissions. Air pollution is associated with chronic illnesses, including diabetes and heart and lung diseases, which can make people more susceptible to COVID-19. Local governments must prioritise feasible and scalable proven solutions and innovations in their jurisdictions to control local emissions in the near term while engaging advocacy and cooperation for regional and national actions to improve air quality over the long term. Vital Strategies' Accelerating City Progress on Clean Air: Innovation and Action Guide (the Guide) is an evidence-based, pragmatic playbook for helping city governments develop comprehensive air quality management systems to rapidly promote clean air for health. This talk will summarise the pragmatic step-by-step approach laid out in the Guide, and describe progress underway in Jakarta, Indonesia, where this guidance is being implemented to strengthen the city's clean air plan. Strategies to be discussed will include: innovations to improve data on air pollution levels and sources, health impact analyses using local data and policy implications; improved data transparency and communication on air quality issues; and the intersectoral approach and coordination being undertaken to accelerate and sustain clean air action.

Use of Satellite Data for Air Pollution Modeling in Bulgaria

Air pollution continues to be of concern for Bulgarian cities, mainly due to particulate matter of aerodynamic diameter smaller than 10 μm (PM10). There is public and expert interest in the improvement of two operational air quality modeling systems: the Bulgarian Chemical Weather Forecast System (BgCWFS) and the Local Air Quality Management System (LAQMS) for the city of Plovdiv. The aim of the study is to investigate the effects of satellite data assimilation in BgCWFS on surface concentrations over Bulgaria (resolution 9 km), to downscale BgCWFS output to LAQMS (resolution 250 m), and to examine effects on PM10 in Plovdiv. Data from the Global Ozone Monitoring Experiment-2 (GOME-2) (MetOP satellites) for aerosols, nitrogen dioxide (NO2), and sulfur dioxide (SO2) were assimilated in BgCWFS using objective analysis. Simulation experiments with and without satellite data were conducted for a summer and a winter month. The comparison to surface observations in the country showed improvement of results when using satellite data, especially in the summer due to mineral dust events captured by satellites. The decrease in the normalized mean bias (NMB) over the two months was 43% (PM10) and 73% (SO2). The LAQMS estimated background contributions to PM10 in the city as 32%. The absolute NMB by LAQMS decreased by 38%.

Using of summary calculations for assessment of air pollution in the urban habitat in the Arctic region

This article discusses the possibility of using summary calculations as a standard for assessing the quality of the city air. Murmansk, like many industrialized Arctic cities, has its own specifics of development, which leads to an increase in the concentration of pollutants in the urban atmosphere, which negatively affects the health of the population and the urban environment quality. There is an air quality management system In Russia, but for many reasons it is imperfect. At the same time, along with it, there is a practice of applying summary calculations to assess air pollution by emissions from road transport and industrial facilities, which allows getting a more detailed picture of the atmospheric air quality. The authors of this article compared the results of assessing of pollutants distribution in the atmosphere of Murmansk city, obtained by using of summary calculations and actual indicators of hazardous components content in the air. The objectivity of summary calculations maps and the possibility of their use for predicting the distribution of air pollution in Murmansk are determined.