scholarly journals Atmospheric aerosols and their influence on air quality in urban areas

2006 ◽  
Vol 4 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Mirjana Tasic ◽  
Slavica Rajsic ◽  
Velibor Novakovic ◽  
Zoran Mijic
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Atmospheric Aerosols ◽  
Urban Areas ◽  
Ground Level ◽  
Urban Atmosphere ◽  
Basic Knowledge ◽  
Pm10 And Pm2.5 ◽  
Air Quality Assessment

The quality and pollution of air and its impact on the environment and particularly on human health, is an issue of significant public and governmental concern. The emission of the main air pollutants (sulfur dioxide, nitrogen oxides) has declined significantly but the trends in concentrations of a particulate matter are less clear and this pollutant still pose a risk to human health. The studies on the quality of air in urban atmosphere related to suspended particles PM10 and PM2.5, and first measurements of their mass concentrations have been initiated in our country in 2002, and are still in progress. The results of preliminary investigations revealed the need for the continuous and long-term systematical sampling measurements and analysis of interaction of the specific pollutants ? PM10 and PM2.5 as well as ozone, heavy metals in the ground level. Survey of some basic knowledge and features of atmospheric particles will be given and the results of air quality assessment in Belgrade will be presented as well.

Temporal patterns and trends of surface ozone concentrations over Portugal

2021 ◽  
Author(s):  
Carla Gama ◽  
Alexandra Monteiro ◽  
Myriam Lopes ◽  
Ana Isabel Miranda
Keyword(s):  
Air Quality ◽  
Iberian Peninsula ◽  
Human Health ◽  
Temporal Variability ◽  
Urban Areas ◽  
Surface Ozone ◽  
Quality Data ◽  
Ozone Concentrations ◽  
Long Term Study

<p>Tropospheric ozone (O<sub>3</sub>) is a critical pollutant over the Mediterranean countries, including Portugal, due to systematic exceedances to the thresholds for the protection of human health. Due to the location of Portugal, on the Atlantic coast at the south-west point of Europe, the observed O<sub>3</sub> concentrations are very much influenced not only by local and regional production but also by northern mid-latitudes background concentrations. Ozone trends in the Iberian Peninsula were previously analysed by Monteiro et al. (2012), based on 10-years of O<sub>3</sub> observations. Nevertheless, only two of the eleven background monitoring stations analysed in that study are located in Portugal and these two stations are located in Porto and Lisbon urban areas. Although during pollution events O<sub>3</sub> levels in urban areas may be high enough to affect human health, the highest concentrations are found in rural locations downwind from the urban and industrialized areas, rather than in cities. This happens because close to the sources (e.g., in urban areas) freshly emitted NO locally scavenges O<sub>3</sub>. A long-term study of the spatial and temporal variability and trends of the ozone concentrations over Portugal is missing, aiming to answer the following questions:</p><p>-           What is the temporal variability of ozone concentrations?</p><p>-           Which trends can we find in observations?</p><p>-           How were the ozone spring maxima concentrations affected by the COVID-19 lockdown during spring 2020?</p><p>In this presentation, these questions will be answered based on the statistical analysis of O<sub>3</sub> concentrations recorded within the national air quality monitoring network between 2005 and 2020 (16 years). The variability of the surface ozone concentrations over Portugal, on the timescales from diurnal to annual, will be presented and discussed, taking into account the physical and chemical processes that control that variability. Using the TheilSen function from the OpenAir package for R (Carslaw and Ropkins 2012), which quantifies monotonic trends and calculates the associated p-value through bootstrap simulations, O<sub>3</sub> concentration long-term trends will be estimated for the different regions and environments (e.g., rural, urban).  Moreover, taking advantage of the unique situation provided by the COVID-19 lockdown during spring 2020, when the government imposed mandatory confinement and citizens movement restriction, leading to a reduction in traffic-related atmospheric emissions, the role of these emissions on ozone levels during the spring period will be studied and presented.</p><p> </p><p>Carslaw and Ropkins, 2012. Openair—an R package for air quality data analysis. Environ. Model. Softw. 27-28,52-61. https://doi.org/10.1016/j.envsoft.2011.09.008</p><p>Monteiro et al., 2012. Trends in ozone concentrations in the Iberian Peninsula by quantile regression and clustering. Atmos. Environ. 56, 184-193. https://doi.org/10.1016/j.atmosenv.2012.03.069</p>

scholarly journals Atmospheric Aerosols: Air Quality and Climate Change Perspectives

2015 ◽  
Vol 10 (3) ◽  
pp. 738-746 ◽  
Author(s):  
Shabana Manzoor ◽  
Umesh Kulshrestha
Keyword(s):  
Air Quality ◽  
Atmospheric Aerosols ◽  
Urban Areas ◽  
Ambient Air ◽  
Quality Standard ◽  
Vital Role ◽  
Cloud Formation ◽  
Pm10 And Pm2.5 ◽  
Suspended Particulate ◽  
Ambient Air Quality Standard

Recently, air quality has become a matter of concern of everyone. According to the reports, atmospheric aerosols play very crucial role in air quality. PM10 and PM2.5 aerosols are integral parts of total suspended particulate matter which affect our health. Often air quality has been reported very poor due to violation of National Ambient Air Quality Standard (NAAQS) limits. PM10 and PM2.5 limits are crossed for both residential as well as sensitive sites. This is one of the major reasons of increasing cases of respiratory diseases in urban areas. However, aerosol loadings alone are not the factor for deciding or predicting toxic and harmful effects of aerosols. Chemical composition and size ranges do matter. Aerosol loadings can be due to three major source categories viz. marine, crustal and anthropogenic. Since, marine and crustal content of aerosols are generally non-toxic and hence, degree of toxicity of air needs to be decided on the basis of anthropogenic fraction having metals, PAHs and other harmful content. Apart from air quality and health, atmospheric aerosols play vital role in other atmospheric processes such as cloud formation, radiative transfer and monsoon etc. Though there are several studies reported on different aspects of atmospheric aerosols, but most of the findings are sort of data reporting based on short term observations. Hence, there is need to investigate the atmospheric aerosols in order to demonstrate local and regional phenomenon on the basis of long term datasets.

The Long Term Spatial-temporal Distribution of Aerosol Optical Depth and Its Associated Atmospheric Circulation Over Southeast Africa.

2021 ◽  
Author(s):  
Matthews Nyasulu ◽  
Md. Mozammel Haque ◽  
Bathsheba Musonda ◽  
Cao Fang
Keyword(s):  
Human Health ◽  
Atmospheric Circulation ◽  
Atmospheric Aerosols ◽  
Crop Residues ◽  
Temporal Distribution ◽  
Western Coast ◽  
High Concentration ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol

Abstract Recent studies have revealed significant impacts of increased concentration of anthropogenic aerosols in the atmosphere to both climate and human health. Southeast Africa is one of the regions where studies related to atmospheric aerosols remain scant, causing high uncertainty in predicting and understanding the impacts of these aerosols to both climate and human health. The present study therefore has investigated the long term spatial-temporal distribution of atmospheric aerosols, trends, its relationship with cloud properties and the associated atmospheric circulation over the region. High concentration of aerosol has been detected during the dry months of September to November (SON) while low during March to May (MAM) and June-July (JJA) seasons in most areas. Highest 550 was recorded in areas with low elevation such as over Lake Malawi, Zambezi valley and along the western coast of the Indian Ocean. The average of the detected concentration is however low as compared to highly polluted regions of the globe. Statistical analyses revealed insignificant change of AOD550 in most areas between 2002 and 2020 time period. The study has also revealed seasonality of aerosol distribution highly influenced by changes in atmospheric circulation. Burning of biomass during dry months such bush fires and burning of crop residues remain the major source of anthropogenic aerosol concentration over Southeast Africa hence needs to be controlled.

Air Quality Modeling in Dense Urban Areas at Ground Level—CFD, OSM or Gauss?

2021 ◽  
pp. 265-270
Author(s):  
Marie Haeger-Eugensson ◽  
Christine Achberger ◽  
Helen Nygren ◽  
Erik Bäck ◽  
Anna Bjurbäck ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Ground Level ◽  
Air Quality Modeling ◽  
Quality Modeling

scholarly journals Emission of fine particles (PM2.5) from residential biomass combustion in Croatia and how to reduce it

2020 ◽  
Vol 7 (2) ◽  
pp. 84-94
Author(s):  
Mirela Poljanac
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Urban Areas ◽  
Fine Particles ◽  
Biomass Combustion ◽  
Rural And Urban Areas ◽  
Wood Burning ◽  
Rural And Urban ◽  
The Impact ◽  
Pm2.5 Emissions

Wood burning in residential appliances is very represented in the Republic of Croatia. It is a main or an additional form of heating for many households in rural and urban areas and is therefore an important source of air pollution. The choice of energy and the combustion appliance used in home have a significant impact on PM2.5 emissions. The paper informs the reader about PM2.5 emissions, their main sources and impacts on human health, environment, climate, air quality, and the reason why PM2.5 emissions from residential wood burning are harmful. Paper also gives an overview of spatial PM2.5 emission distribution in Croatia, their five air quality zones and four agglomerations. The paper analyses the sources and their contribution to PM2.5 emissions with the relevance of PM2.5 emissions from residential plants, the use of fuels in residential plants and their contribution to PM2.5 emissions and PM2.5 emissions by fuel combustion technologies in residential sector. Appropriate strategies, policies, and actions to reduce the impact of residential biomass (wood) burning on the environment, air quality and human health are considered.

scholarly journals A Machine Learning Approach to Predict Air Quality in California

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Mauro Castelli ◽  
Fabiana Martins Clemente ◽  
Aleš Popovič ◽  
Sara Silva ◽  
Leonardo Vanneschi
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Environmental Protection Agency ◽  
Urban Areas ◽  
Principal Component ◽  
Ground Level ◽  
Support Vector ◽  
Validation Data ◽  
Pollutant Concentrations ◽  
Rbf Kernel

Predicting air quality is a complex task due to the dynamic nature, volatility, and high variability in time and space of pollutants and particulates. At the same time, being able to model, predict, and monitor air quality is becoming more and more relevant, especially in urban areas, due to the observed critical impact of air pollution on citizens’ health and the environment. In this paper, we employ a popular machine learning method, support vector regression (SVR), to forecast pollutant and particulate levels and to predict the air quality index (AQI). Among the various tested alternatives, radial basis function (RBF) was the type of kernel that allowed SVR to obtain the most accurate predictions. Using the whole set of available variables revealed a more successful strategy than selecting features using principal component analysis. The presented results demonstrate that SVR with RBF kernel allows us to accurately predict hourly pollutant concentrations, like carbon monoxide, sulfur dioxide, nitrogen dioxide, ground-level ozone, and particulate matter 2.5, as well as the hourly AQI for the state of California. Classification into six AQI categories defined by the US Environmental Protection Agency was performed with an accuracy of 94.1% on unseen validation data.

scholarly journals Ambient air quality in an urban area and its effects on plants and human beings: a case study of Tiruchirappalli, India

1970 ◽  
Vol 6 (2) ◽  
pp. 13-19 ◽  
Author(s):  
Sirajuddin M Horaginamani ◽  
M Ravichandran
Keyword(s):  
Air Pollution ◽  
Developing Countries ◽  
Air Quality ◽  
Human Health ◽  
Urban Area ◽  
Urban Areas ◽  
Ambient Air ◽  
Control Measures ◽  
Human Beings ◽  
Ambient Air Quality

Though water and land pollution is very dangerous, air pollution has its own peculiarities, due to its transboundary dispersion of pollutants over the entire world. In any well planned urban set up, industrial pollution takes a back seat and vehicular emissions take precedence as the major cause of urban air pollution. Air pollution is one of the serious problems faced by the people globally, especially in urban areas of developing countries like India. All these in turn lead to an increase in the air pollution levels and have adverse effects on the health of people and plants. Western countries have conducted several studies in this area, but there are only a few studies in developing countries like India. A study on ambient air quality in Tiruchirappalli urban area and its possible effects selected plants and human health has been undertaken, which may be helpful to bring out possible control measures. Keywords: ambient air quality; respiratory disorders; APTI; human health DOI: 10.3126/kuset.v6i2.4007Kathmandu University Journal of Science, Engineering and Technology Vol.6. No II, November, 2010, pp.13-19

scholarly journals Urban Air Quality Assessment Using Integrated Artificial Intelligence Algorithms and Geographic Information System Modeling in a Highly Congested Area, Iraq

2020 ◽  
Vol 55 (1) ◽  
Author(s):  
Oday Zakariya Jasim ◽  
Noor Hashim Hamed ◽  
Mohammed Abdullah Abid
Keyword(s):  
Information System ◽  
Air Quality ◽  
Geographic Information System ◽  
Regression Model ◽  
Quality Assessment ◽  
Urban Areas ◽  
Geographic Information ◽  
Urban Air ◽  
Congested Area ◽  
Air Quality Assessment

Pollutant emissions are considered to be a major threat to air quality and human health in urban areas. Therefore, accurate modeling and assessment tools are required. In this study, a model was done by the integration of machine learning algorithms and a geographic information system model. This model included the optimization of the support vector regression model by using the principal component analysis algorithm. Then, the integration of the regression model with spatial analysis modeling via a grid (100 x 100 m) was done in order to generate prediction maps during holidays and workdays in the daytime and at nighttime in a highly congested area in Baghdad city, Iraq. The data used in this study categorized into two categories. The first category is the data acquired through field surveying that includes temperature, humidity, wind speed, wind direction, and traffic flow data (e.g., the number of light and heavy vehicles), as well as carbon monoxide samples by using mobile equipment. The second category is the information derived from geographic information system data, such as land use, road network, and building height. The accuracy of the proposed model is 81%, and the lowest value of root mean square error was 0.067 ppm. The integration between air pollution models and geographic information system techniques could be a promising tool for urban air quality assessment and urban planning. These tools effectively utilized by stakeholders and decision-makers to outline proper plans and strategies to mitigate air pollutants in urban areas.

scholarly journals Application of Photo Texture Analysis and Weather Data in Assessment of Air Quality in Terms of Airborne PM10 and PM2.5 Particulate Matter

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5483
Author(s):  
Monika Chuchro ◽  
Wojciech Sarlej ◽  
Marta Grzegorczyk ◽  
Karolina Nurzyńska
Keyword(s):  
Air Quality ◽  
Texture Analysis ◽  
Regression Models ◽  
Quality Measurement ◽  
Classification Model ◽  
Weather Data ◽  
Classification Models ◽  
Pm10 And Pm2.5 ◽  
Air Quality Assessment ◽  
Short Video

The study was undertaken in Krakow, which is situated in Lesser Poland Voivodeship, where bad PM10 air-quality indicators occurred on more than 100 days in the years 2010–2019. Krakow has continuous air quality measurement in seven locations that are run by the Province Environmental Protection Inspectorate. The research aimed to create regression and classification models for PM10 and PM2.5 estimation based on sky photos and basic weather data. For this research, one short video with a resolution of 1920 × 1080 px was captured each day. From each film, only five frames were used, the information from which was averaged. Then, texture analysis was performed on each averaged photo frame. The results of the texture analysis were used in the regression and classification models. The regression models’ quality for the test datasets equals 0.85 and 0.73 for PM10 and 0.63 for PM2.5. The quality of each classification model differs (0.86 and 0.73 for PM10, and 0.80 for PM2.5). The obtained results show that the created classification models could be used in PM10 and PM2.5 air quality assessment. Moreover, the character of the obtained regression models indicates that their quality could be enhanced; thus, improved results could be obtained.

scholarly journals AIR QUALITY MONITORING AND DATA MANAGEMENT IN GERMANY – STATUS QUO AND SUGGESTIONS FOR IMPROVEMENT

2020 ◽  
Vol XLIV-4/W2-2020 ◽  
pp. 37-43
Author(s):  
L. Petry ◽  
H. Herold ◽  
G. Meinel ◽  
T. Meiers ◽  
I. Müller ◽  
...  
Keyword(s):  
Decision Making ◽  
Air Quality ◽  
Management Practices ◽  
System Development ◽  
Ground Level ◽  
Ground Level Ozone ◽  
Novel Approach ◽  
Depth Analysis ◽  
New Generation

Abstract. This paper proposes a novel approach to facilitate air quality aware decision making and to support planning actors to take effective measures for improving the air quality in cities and regions. Despite many improvements over the past decades, air pollutants such as particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3) pose still one of the major risks to human health and the environment. Based on both a general analysis of the air quality situation and regulations in the EU and Germany as well as an in-depth analysis of local management practices requirements for better decision making are identified. The requirements are used to outline a system architecture following a co-design approach, i.e., besides scientific and industry partners, local experts and administrative actors are actively involved in the system development. Additionally, the outlined system incorporates two novel methodological strands: (1) it employs a deep neural network (DNN) based data analytics approach and (2) makes use of a new generation of satellite data, namely Sentinel-5 Precursor (Sentinel-5P). Hence, the system allows for providing areal and high-resolution (e.g., street-level) real-time and forecast (up to 48 hours) data to inform decision makers for taking appropriate short-term measures, and secondly, to simulate air quality under different planning options and long-term actions such as modified traffic flows and various urban layouts.

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