scholarly journals Meteorological parameters and pollution caused by Sulfur dioxide and their influence on construction materials and heritage

2011 ◽  
Vol 24 (1) ◽  
pp. 9-20 ◽  
Author(s):  
Ljubisa Preradovic ◽  
Predrag Ilic ◽  
Svetlana Markovic ◽  
Zoran Janjus
Keyword(s):  
Air Pollution ◽  
Sulfur Dioxide ◽  
Population Density ◽  
Meteorological Parameters ◽  
Statistical Data ◽  
Construction Materials ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Statistical Tool ◽  
Automatic Station

In work is presented research of presence Sulfur dioxide (SO2) on sample place where is intensive traffic and population density is high. Air quality monitoring was done with an automatic station. For the interpretation of the results are used monthly and annual patterns. On the basis of the detected pollutants during the air monitoring show the state of environmental conditions in terms of air pollution with Sulfur dioxide and influence of them on aero-pollution, structural materials and building heritage. Also is given evaluation of influence polluted air on building heritage. For statistical data processing and modeling of pollution along with meteorological parameters was used decision tree implementation of the analytical and statistical tool SPSS 17.

scholarly journals Evaluating the Influence of Meteorological Parameters on Ozone Concentration Levels

2018 ◽  
Vol 7 (3.7) ◽  
pp. 65
Author(s):  
Amina Nazif ◽  
Nurul Izma Mohammed ◽  
Amirhossein Malakahmad ◽  
Motasem S. Abualqumboz
Keyword(s):  
Air Pollution ◽  
Air Pollutants ◽  
Stepwise Regression ◽  
Meteorological Parameters ◽  
Anthropogenic Activities ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Pollution Levels ◽  
Air Quality Monitoring Stations ◽  
Concentration Levels

Over the years, anthropogenic activities have led to the increase in air pollution concentration levels in the atmosphere, this persistent increase in pollution levels can be influenced by meteorological parameters. These parameters assist in the formation and transportation of air pollutants in the atmosphere. Hence, this study aims at evaluating the association between meteorological parameters and air pollutants. The analysis was carried out using Ozone (O3), Particulate matter (PM10), Nitrogen dioxide (NO2), temperature, humidity, wind speed, and wind direction data from 2006 to 2010, from two industrial air quality monitoring stations. Stepwise regression (SR) analysis was used to assess the influence of meteorological parameters in accounting for the variability of O3 concentration levels. The SR analysis showed that meteorological parameters accounted for more than 50 % of O3 variability. It can be concluded that different relationship between meteorological parameters and O3 can exist in different locations in the same region.  

scholarly journals ANALYSIS OF THE RESULTS OF AIR QUALITY MONITORING IN THE AREA OF THE CITY OF ZENICA

2021 ◽  
Vol 9 (12) ◽  
pp. 453-461
Author(s):  
Mirnes Durakovic ◽  
◽  
Azrudin Husika ◽  
Halim Prcanovic ◽  
Sanela Beganovic ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Sulfur Dioxide ◽  
Sampling Period ◽  
Ambient Air ◽  
Quality Monitoring ◽  
World Health ◽  
Air Quality Monitoring ◽  
Short Period ◽  
The City

According to the World Health Organization (WHO), air pollution is the largest single environmental risk to public health. According to the latest estimate of this organization, 9 out of 10 people on the planet breathe polluted air. The development of industry in the relatively small Zenica valley reflected on air quality in the city of Zenica. The problem of high air pollution due to emissions of pollutants from industrial sources, traffic, and individual furnaces, burning of environmentally unsuitable fuels containing high sulfur and ash content has been present in the City of Zenica for a long time. In addition, the low wind speed during the year, which ranges up to 1.5 m/s, with unfavorable temperature inversions, causes the concentrations of pollutants in the air to reach alarmingly high values in a short period. In the wider area of the City of Zenica, air quality has been monitored since 1978 in the network of stationary stations. The paper presents results of air quality monitoring which are analyzed at the Institute Kemal Kapetanovic in Zenica for the sampling period from 01.01.2019. to 31.12.2020. years. Air quality monitoring included sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter (PM10) at three locations in the wider area of the city of Zenica. In the wider area of the City of Zenica, air quality has been monitored since 1978 in the network of stationary stations. The paper presents the processed results of air quality monitoring which are analyzed at the Institute Kemal Kapetanovic in Zenica for the sampling period from 01.01.2019 to 31.12.2020. The measured concentrations of pollutants in the ambient air indicate that during the heating season, i.e. the winter months, the air quality in the urban and suburban areas of the city of Zenica is very poor. The data show that the highest hourly concentration of sulfur dioxide was recorded in December at the measuring station AMS Tetovo in the amount of 1100.59 µg/m3, which is located in the settlement next to the metallurgical facilities of the industrial zone Zenica.

scholarly journals Domain adaptation based deep calibration of low-cost PM2.5 sensors

2021 ◽  
Author(s):  
Sonu Kumar Jha ◽  
Mohit Kumar ◽  
Vipul Arora ◽  
Sachchida Nand Tripathi ◽  
Vidyanand Motiram Motghare ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Domain Adaptation ◽  
Low Cost ◽  
Monitoring Network ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Proposed Model ◽  
Temperature And Humidity ◽  
Calibration Approach

<div>Air pollution is a severe problem growing over time. A dense air-quality monitoring network is needed to update the people regarding the air pollution status in cities. A low-cost sensor device (LCSD) based dense air-quality monitoring network is more viable than continuous ambient air quality monitoring stations (CAAQMS). An in-field calibration approach is needed to improve agreements of the LCSDs to CAAQMS. The present work aims to propose a calibration method for PM2.5 using domain adaptation technique to reduce the collocation duration of LCSDs and CAAQMS. A novel calibration approach is proposed in this work for the measured PM2.5 levels of LCSDs. The dataset used for the experimentation consists of PM2.5 values and other parameters (PM10, temperature, and humidity) at hourly duration over a period of three months data. We propose new features, by combining PM2.5, PM10, temperature, and humidity, that significantly improved the performance of calibration. Further, the calibration model is adapted to the target location for a new LCSD with a collocation time of two days. The proposed model shows high correlation coefficient values (R2) and significantly low mean absolute percentage error (MAPE) than that of other baseline models. Thus, the proposed model helps in reducing the collocation time while maintaining high calibration performance.</div>

An assessment of ambient air quality using AQI and exceedance factor for Udaipur City, Rajasthan (India)

2021 ◽  
pp. 94-106
Author(s):  
Porush Kumar ◽  
Kuldeep ◽  
Nilima Gautam
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Urban Air Pollution ◽  
Ambient Air ◽  
Quality Monitoring ◽  
Urban Air ◽  
Air Quality Monitoring ◽  
Ambient Air Quality ◽  
Control Board

Air pollution is a severe issue of concern worldwide due to its most significant environmental risk to human health today. All substances that appear in excessive amounts in the environment, such as PM10, NO2, or SO2, may be associated with severe health problems. Anthropogenic sources of these pollutants are mainly responsible for the deterioration of urban air quality. These sources include stationary point sources, mobile sources, waste disposal landfills, open burning, and similar others. Due to these pollutants, people are at increased risk of various serious diseases like breathing problems and heart disease, and the death rate due to these diseases can also increase. Hence, air quality monitoring is essential in urban areas to control and regulate the emission of these pollutants to reduce the health impacts on human beings. Udaipur has been selected for the assessment of air quality with monitored air quality data. Air quality monitoring stations in Udaipur city are operated by the CPCB (Central Pollution Control Board) and RSPCB (Rajasthan State Pollution Control Board). The purpose of this study is to characterize the level of urban air pollution through the measurement of PM10, NO2, or SO2 in Udaipur city, Rajasthan (India). Four sampling locations were selected for Udaipur city to assess the effect of urban air pollution and ambient air quality, and it was monitored for a year from 1st January 2019 to 31st December 2019. The air quality index has been calculated with measured values of PM10, NO2, and SO2. The concentration of PM10 is at a critical level of pollution and primarily responsible for bad air quality and high air quality Index in Udaipur city.

scholarly journals Healthier breath for all and everywhere – Urban air quality monitoring experience

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Gajic ◽  
D Dimovski ◽  
B Vukajlovic ◽  
M Jevtic
Keyword(s):  
Public Health ◽  
Air Pollution ◽  
Air Quality ◽  
Health Risk ◽  
Urban Health ◽  
Urban Areas ◽  
Danube River ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Residential Areas

Abstract Issue/problem Increasing attention is being paid to air pollution as one of the greatest threats to public and urban health. The WHO’s Urban Health Initiative points out the importance of collecting data and mapping the present state of air quality in urban areas. For citizens, such engagement is enabled by the appearance of personal air quality measurement devices that use crowd-sourcing to make measurement results publicly accessible in real time. Description of the problem As a way of contributing to air pollution monitoring in their town, three PhD Public health students conducted over 40 measurements between the start of June and end of August 2018 on various locations in the city of Novi Sad, Serbia. Measurements were performed using AirBeam personal air quality monitoring devices and their results presented as μg/m3 of Particulate Matter 2.5 (PM2.5) and automatically uploaded to the internet using the Air-casting app. Results Measurements conducted in public transportation vehicles returned the rather high average value of 40 μg/m3, where coffee shops and restaurants scored an even higher value of 48,67 μg/m3. The lowest average air pollution levels were registered near the Danube river bank (5.67) and in the parks (6), while the sites near crossroads or in the street showed average air pollution of 8.33 μg/m3. Residential areas where smoking is present during the day reported 2.5 times higher PM2.5 values than those without smokers (33.8 and 12.78 μg/m3). Lessons Bearing in mind that the air quality is considered as a serious health risk in urban areas, results of this pilot investigation suggest potential health risk for citizens living in urban areas. The negative effects of combustion and smoking on air quality are strongly highlighted, as well as the positive impact of green areas and parks near residential areas. Key messages Air pollution exposure as a serious health risk in urban areas. Crowdsourcing as a way of air quality monitoring has great potential for contributing to public health.

scholarly journals One-Year Simulation of Ozone and Particulate Matter in China Using WRF/CMAQ Modeling System

2016 ◽  
Author(s):  
Jianlin Hu ◽  
Jianjun Chen ◽  
Qi Ying ◽  
Hongliang Zhang
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Model Performance ◽  
Monitoring Network ◽  
Organic Aerosol ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Low Concentration ◽  
Temporal And Spatial

Abstract. China has been experiencing severe air pollution in recent decades. Although ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research &amp; Forecasting model (WRF) and the Community Multi-scale Air Quality model (CMAQ) was conducted to provide detailed temporal and spatial information of ozone (O3), PM2.5 total and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, over-prediction of O3 generally occurs at low concentration range while under-prediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in Southern China than in Northern, Central and Sichuan basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of CMAQ model in reproducing severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

A Cluster Analysis of PM2.5 Using CMAQ Model Results for Representativeness of Air Quality Monitoring Networks in Busan, Korea

2020 ◽  
Author(s):  
Woo-Sik Jung ◽  
Woo-Gon Do
Keyword(s):  
Air Pollution ◽  
Cluster Analysis ◽  
Air Quality ◽  
Monitoring Network ◽  
Hierarchical Cluster ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Monitoring Networks ◽  
Monitoring Stations

&lt;p&gt;&lt;strong&gt;With increasing interest in air pollution, the installation of air quality monitoring networks for regular measurement is considered a very important task in many countries. However, operation of air quality monitoring networks requires much time and money. Therefore, the representativeness of the locations of air quality monitoring networks is an important issue that has been studied by many groups worldwide. Most such studies are based on statistical analysis or the use of geographic information systems (GIS) in existing air quality monitoring network data. These methods are useful for identifying the representativeness of existing measuring networks, but they cannot verify the need to add new monitoring stations. With the development of computer technology, numerical air quality models such as CMAQ have become increasingly important in analyzing and diagnosing air pollution. In this study, PM2.5 distributions in Busan were reproduced with 1-km grid spacing by the CMAQ model. The model results reflected actual PM2.5 changes relatively well. A cluster analysis, which is a statistical method that groups similar objects together, was then applied to the hourly PM2.5 concentration for all grids in the model domain. Similarities and differences between objects can be measured in several ways. K-means clustering uses a non-hierarchical cluster analysis method featuring an advantageously low calculation time for the fast processing of large amounts of data. K-means clustering was highly prevalent in existing studies that grouped air quality data according to the same characteristics. As a result of the cluster analysis, PM2.5 pollution in Busan was successfully divided into groups with the same concentration change characteristics. Finally, the redundancy of the monitoring stations and the need for additional sites were analyzed by comparing the clusters of PM2.5 with the locations of the air quality monitoring networks currently in operation.&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(2017R1D1A3B03036152).&lt;/strong&gt;&lt;/p&gt;

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