Seasonality of the levels of particulate matter PM10 air pollutant in the city of Ruse, Bulgaria

2020 ◽  
Author(s):  
E. Veleva ◽  
I. R. Georgiev
Keyword(s):  
Particulate Matter ◽  
Air Pollutant ◽  
The City

scholarly journals Assessment of PM10 in Aurangabad City of Central India

2016 ◽  
Vol 5 (2) ◽  
pp. 61-74 ◽  
Author(s):  
Geetanjali Kaushik ◽  
Arvind Chel ◽  
Sangeeta Shinde ◽  
Ashish Gadekar
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Tall Buildings ◽  
Central India ◽  
Air Pollutant ◽  
Traffic Density ◽  
High Pollution ◽  
High Concentrations ◽  
The City

Almost 670 million people comprising 54.5% of our population reside in regions that do not meet the Indian NAAQS for fine particulate matter. Numerous studies have revealed a consistent correlation for particulate matter concentration with health than any other air pollutant. Aurangabad city a rapidly growing city with population of 1.5 million is home to five major industrial areas, the city is also known for its historical monuments which might also be adversely affected from air pollution. Therefore, this research aims at estimating PM10 concentrations at several locations across Aurangabad. The concentration of PM10 was highest at the Railway Station followed by Waluj (an industrial zone) and City chowk is the centre of the city which has high population, tall buildings, few open spaces which causes high congestion and does not allow the particulates to disperse. Other locations with high concentrations of PM are Mill corner, Harsul T-point, Kranti Chowk, Seven Hill, TV centre and Beed Bye pass. All these locations have narrow roads, high traffic density, poor road condition with pot holes and few crossing points which cause congestion and vehicle idling which are responsible for high pollution. Therefore, it is evident that air pollution is a serious issue in the city which may be further aggravated if it is not brought under control. Hence, strategies have to be adopted for combating the menace of air pollution.INTERNATIONAL JOURNAL OF ENVIRONMENTVolume-5, Issue-2, March-May 2016, Page :61-74

scholarly journals Magnetic Properties and Size of Microscopic Pollutant Particles in the Urban Area of Coimbra

2008 ◽  
Vol 14 (S3) ◽  
pp. 144-145 ◽  
Author(s):  
C.R. Gomes ◽  
A.M. Dinis ◽  
A.F. Rocha ◽  
E.M.C. Gomes ◽  
L.F. Neves
Keyword(s):  
Magnetic Properties ◽  
Particulate Matter ◽  
Human Health ◽  
Urban Area ◽  
Motor Vehicle ◽  
Air Pollutant ◽  
Nerium Oleander ◽  
Vehicle Traffic ◽  
Pollution Levels ◽  
The City

Pollutant particles of small size are produced and resuspended every day as a result of traffic. These particles, identified as particulate matter (PM10, PM2.5), can affect human health when inhaled, mostly the respiratory and cardiopulmonary systems. Some of these particles are ferromagnetic (s.l.) and their magnetic properties indicate their sources, composition and size. Coimbra is an inland city situated in the center of Portugal at a distance of 40 km from the coast. Coimbra has a total area of 320 km2 and a population of about 168.000. Motor vehicle traffic is the main source of air pollutant in the city. The main goal of this research is to assess pollution levels in the urban area of Coimbra using the magnetic properties of microscopic pollutant particles on Nerium oleander leaves.

scholarly journals Development of a Mobile Edge Device and an Information System to Analyze Particulate Matter Distribution as a mHealth Service

2021 ◽  
Vol 11 (6) ◽  
pp. 48-58
Author(s):  
Franz Frederik Walter Viktor Walter Tscharf ◽  
Keyword(s):  
Information System ◽  
Particulate Matter ◽  
Field Trials ◽  
Air Pollutant ◽  
Engineering Requirement ◽  
New Year’S Eve ◽  
The University ◽  
Particulate Matter Distribution ◽  
The City ◽  
Particulate Matter Pollution

Particulate matter is an air pollutant consistent of very small particles that are suspended in the air. Shortterm exposure may result in respiratory symptoms such as shortness of breath, throat and nose irritation, chest tightness, coughing, in addition to eye irritation. The research aimes at creating a prototype of a mobile sensor system that can be used to analyze the particulate matter pollution on a location and on a time scale to measure the degree of pollution in the city. The engineering requirement to construct the edge device includes temperature (humidity) sensor, particulate matter sensor, GPS module, and an LCD for displaying the current sensor values. The health data of the mobile edge device can be analyzed through a developed analytics system, which allows the user to identify and avoid pollution sources. For the implementation of the web service the framework ReactJS, NodeJS with Express.js, and the database MongoDB are being used. The mHelath service is evaluated through field trials: New Year’s Eve, various source identifications, and a demonstration through a journey from the subway station to the university. The paper outlines a mHealth service, which can collect data records of the surroundings and analyze the particulate matter in an information system to visualize risk locations of a user.

Vicious Cycle of Economic Growth, Pm2.5 and COVID-19 Case of G7 Countries

2020 ◽  
Author(s):  
Rıdvan Karacan
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Particulate Matter ◽  
Fossil Fuels ◽  
Fine Particulate Matter ◽  
Panel Cointegration ◽  
Air Pollutant ◽  
Population Exposure ◽  
Causality Analysis ◽  
G7 Countries

<p>Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases.</p><p><br></p><p><br></p><p>[1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).</p>

scholarly journals GIS-Based Approach to Spatio-Temporal Interpolation of Atmospheric CO2 Concentrations in Limited Monitoring Dataset

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 384
Author(s):  
Yaroslav Bezyk ◽  
Izabela Sówka ◽  
Maciej Górka ◽  
Jan Blachowski
Keyword(s):  
Seasonal Variability ◽  
Sampling Strategy ◽  
Climate Impacts ◽  
Air Pollutant ◽  
Urban Atmosphere ◽  
Atmospheric Co2 ◽  
Spatial Characteristic ◽  
Interpolation Methods ◽  
Co2 Levels ◽  
The City

Understanding the magnitude and distribution of the mixes of the near-ground carbon dioxide (CO2) components spatially (related to the surface characteristics) and temporally (over seasonal timescales) is critical to evaluating present and future climate impacts. Thus, the application of in situ measurement approaches, combined with the spatial interpolation methods, will help to explore variations in source contribution to the total CO2 mixing ratios in the urban atmosphere. This study presents the spatial characteristic and temporal trend of atmospheric CO2 levels observed within the city of Wroclaw, Poland for the July 2017–August 2018 period. The seasonal variability of atmospheric CO2 around the city was directly measured at the selected sites using flask sampling with a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. The current work aimed at determining the accuracy of the interpolation techniques and adjusting the interpolation parameters for estimating the magnitude of CO2 time series/seasonal variability in terms of limited observations during the vegetation and non-vegetation periods. The objective was to evaluate how different interpolation methods will affect the assessment of air pollutant levels in the urban environment and identify the optimal sampling strategy. The study discusses the schemes for optimization of the interpolation results that may be adopted in areas where no observations are available, which is based on the kriging error predictions for an appropriate spatial density of measurement locations. Finally, the interpolation results were extended regarding the average prediction bias by exploring additional experimental configurations and introducing the limitation of the future sampling strategy on the seasonal representation of the CO2 levels in the urban area.

scholarly journals Urban influence on the concentration and composition of submicron particulate matter in central Amazonia

2018 ◽  
Author(s):  
Suzane S. de Sá ◽  
Brett B. Palm ◽  
Pedro Campuzano-Jost ◽  
Douglas A. Day ◽  
Weiwei Hu ◽  
...  
Keyword(s):  
Time Series ◽  
Particulate Matter ◽  
Air Quality ◽  
Nitrogen Oxides ◽  
Mass Concentration ◽  
Critical Role ◽  
Metropolitan Region ◽  
Anthropogenic Emissions ◽  
Organic Mass ◽  
The City

Abstract. Fundamental to quantifying the influence of human activities on climate and air quality is an understanding of how anthropogenic emissions affect the concentrations and composition of airborne particulate matter (PM). The central Amazon basin, especially around the city of Manaus, Brazil, has experienced rapid changes in the past decades due to ongoing urbanization. Herein, changes in the concentration and composition of submicron PM due to pollution downwind of the Manaus metropolitan region are reported as part of the GoAmazon2014/5 experiment. A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and a suite of other gas- and particle-phase instruments were deployed at the T3 research site, 70 km downwind of Manaus, during the wet season. At this site, organic components represented on average 79 ± 7 % of the non-refractory PM1 mass concentration, which was in the same range as several upwind sites. The organic PM1 was, however, considerably more oxidized at T3 compared to upwind measurements. Positive-matrix factorization (PMF) was applied to the time series of organic mass spectra collected at the T3 site, yielding three factors representing secondary processes (73 ± 15 % of total organic mass concentration) and three factors representing primary anthropogenic emissions (27 ± 15 %). Fuzzy c-means clustering (FCM) was applied to the afternoon time series of concentrations of NOy, ozone, total particle number, black carbon, and sulfate. Four clusters were identified and characterized by distinct airmass origins and particle compositions. Two clusters, Bkgd-1 and Bkgd-2, were associated with background conditions. Bkgd-1 appeared to represent near-field atmospheric PM production and oxidation of a day or less. Bkgd-2 appeared to represent material transported and oxidized for two or more days, often with out-of-basin contributions. Two other clusters, Pol-1 and Pol-2, represented the Manaus influence, one apparently associated with the northern region of Manaus and the other with the southern region of the city. A composite of the PMF and FCM analyses provided insights into the anthropogenic effects on PM concentration and composition. The increase in mass concentration of submicron PM ranged from 25 % to 200 % under polluted compared to background conditions, including contributions from both primary and secondary PM. Furthermore, a comparison of PMF factor loadings for different clusters suggested a shift in the pathways of PM production under polluted conditions. Nitrogen oxides may have played a critical role in these shifts. Increased concentrations of nitrogen oxides can shift pathways of PM production from HO2-dominant to NO-dominant as well as increase the concentrations of oxidants in the atmosphere. Consequently, the oxidation of biogenic and anthropogenic precursor gases as well as the oxidative processing of pre-existing atmospheric PM can be accelerated. The combined set of results demonstrates the susceptibility of atmospheric chemistry, air quality, and associated climate forcing to anthropogenic perturbations over tropical forests.

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