scholarly journals Monitoring and Forecasting Air Pollution Levels by Exploiting Satellite, Ground-Based, and Synoptic Data, Elaborated with Regression Models

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Silas Michaelides ◽  
Dimitris Paronis ◽  
Adrianos Retalis ◽  
Filippos Tymvios
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Regression Models ◽  
Eastern Mediterranean ◽  
Anthropogenic Sources ◽  
Spatial And Temporal Variability ◽  
Pollution Levels ◽  
Synoptic Conditions

This paper presents some of the results of a project that aimed at the design and implementation of a system for the spatial mapping and forecasting the temporal evolution of air pollution from dust transport from the Sahara Desert into the eastern Mediterranean and secondarily from anthropogenic sources, focusing over Cyprus. Monitoring air pollution (aerosols) in near real-time is accomplished by using spaceborne and in situ platforms. The results of the development of a system for forecasting pollution levels in terms of particulate matter concentrations are presented. The aim of the present study is to utilize the recorded PM10 (particulate matter with aerodynamic diameter less than 10 μm) ground measurements, Aerosol Optical Depth retrievals from satellite, and the prevailing synoptic conditions established by Artificial Neural Networks, in order to develop regression models that will be able to predict the spatial and temporal variability of PM10 in Cyprus. The core of the forecasting system comprises an appropriately designed neural classification system which clusters synoptic maps, Aerosol Optical Depth data from the Aqua satellite, and ground measurements of particulate matter. By exploiting the above resources, statistical models for forecasting pollution levels were developed.

scholarly journals Fine particulate matter predictions using high resolution Aerosol Optical Depth (AOD) retrievals

2014 ◽  
Vol 89 ◽  
pp. 189-198 ◽  
Author(s):  
Alexandra A. Chudnovsky ◽  
Petros Koutrakis ◽  
Itai Kloog ◽  
Steven Melly ◽  
Francesco Nordio ◽  
...  
Keyword(s):  
Particulate Matter ◽  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Fine Particulate Matter ◽  
Fine Particulate

scholarly journals Aerosol optical depth in the European Brewer Network

2017 ◽  
Author(s):  
Javier López-Solano ◽  
Alberto Redondas ◽  
Thomas Carlund ◽  
Juan J. Rodriguez-Franco ◽  
Henri Diémoz ◽  
...  
Keyword(s):  
Real Time ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Temporal Variability ◽  
Input Data ◽  
Spatial And Temporal Variability ◽  
Ultraviolet Range ◽  
Using Data ◽  
Better Than

Abstract. The high spatial and temporal variability of aerosols make networks capable of measuring their properties in near real time of high scientific interest. In this work we present and discuss results of an aerosol optical depth algorithm to be used in the European Brewer Network, which provides data in near real time of more than 30 spectrophotometers located from Tamanrasset (Algeria) to Kangerlussuaq (Greenland). Using data from the Brewer Intercomparison Campaigns in the years 2013 and 2015, and the period in between, plus comparisons with Cimel sunphotometers and UVPFR instruments, we check the precision, stability, and uncertainty of the Brewer AOD in the ultraviolet range from 300 to 320 nm. Our results show a precision better than 0.01, an uncertainty of less than 0.05, and a stability similar to that of the ozone measurements for well-maintained instruments. We also discuss future improvements to our algorithm with respect to the input data, their processing, and the characterization of the Brewer instruments for the measurement of aerosols.

Validation of Aerosol Optical Depth from HJ-1 CCD Retrievals

2014 ◽  
Vol 955-959 ◽  
pp. 1591-1594
Author(s):  
Dan Li ◽  
Chang Kui Sun ◽  
Kun Yu ◽  
Lin Sun ◽  
Lei Du
Keyword(s):  
Air Pollution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Validation Study ◽  
Ccd Cameras ◽  
Vegetation Region

This study compares the aerosol optical depth (AOD) from the HJ-1 CCD cameras with ground-based measurements of AEROSOL ROBOTIC NETWORK (AERONET). The results indicate that the HJ-1 CCD AOD retrievals at 550 nm have good correlations with the ground-based measurements. This validation study indicates that the HJ-1 CCD AOD retrievals can adequately characterize the AOD distributions over the dense dark vegetation region of China. This AOD product can act an important role to study air pollution.

scholarly journals Visualization of Correlation for Air Pollution Time Series using TAQMN Data

2019 ◽  
Vol 8 (3) ◽  
pp. 7922-7927
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Particulate Matter ◽  
Pearson Correlation ◽  
Fine Particulate Matter ◽  
Correlation Method ◽  
Well Being ◽  
Pollution Levels ◽  
Fine Particulate ◽  
Pm2.5 Concentration

In Taiwan country Annan, Chiayi, Giran, and Puzi cities are facing a serious fine particulate matter (PM2.5) issue. To date the impressive advance has been made toward understanding the PM2.5 issue, counting special temporal characterization, driving variables and well-being impacted. However, notable research as has been done on the interaction of the content between the selected cities of Taiwan country for particulate matter (PM2.5) concentration. In this paper, we purposed a visualization technique based on this principle of the visualization, cross-correlation method and also the time-series concentration with particulate matter (PM2.5) for different cities in Taiwan. The visualization also shows that the correlation between the different meteorological factors as well as the different air pollution pollutants for particular cities in Taiwan. This visualization approach helps to determine the concentration of the air pollution levels in different cities and also determine the Pearson correlation, r values of selected cities are Annan, Puzi, Giran, and Wugu.

Empirical relationship between particulate matter and aerosol optical depth over Northern Tien-Shan, Central Asia

2012 ◽  
Vol 6 (2) ◽  
pp. 385-396 ◽  
Author(s):  
Boris B. Chen ◽  
Leonid G. Sverdlik ◽  
Sanjar A. Imashev ◽  
Paul A. Solomon ◽  
Jeffrey Lantz ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Central Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Empirical Relationship ◽  
Tien Shan ◽  
Northern Tien Shan

Relationship between the concentration of fine particulate matter and aerosol optical depth in the Middle Urals

2021 ◽  
Author(s):  
Anna P. Luzhetskaya ◽  
Ekaterina S. Nagovitsyna ◽  
Elena V. Omelkova ◽  
Vasiliy A. Poddubny ◽  
Alexey A. Shchelkanov ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Fine Particulate Matter ◽  
Middle Urals ◽  
The Middle Urals ◽  
Fine Particulate

scholarly journals Novel Coronavirus: How Atmospheric Particulate Affects Our Environment and Health

Challenges ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 6 ◽  
Author(s):  
Luigi Sanità di Toppi ◽  
Lorenzo Sanità di Toppi ◽  
Erika Bellini
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Atmospheric Particulate Matter ◽  
The Novel ◽  
Atmospheric Particulate ◽  
Po Valley ◽  
Pollution Levels ◽  
Syncytial Virus ◽  
Novel Coronavirus ◽  
Prompt Action

It is well-known that atmospheric pollution, first and foremost the particulate matter (PM), causes serious diseases in humans. China’s metropolises and Italy’s Po Valley have in fact achieved a concerning degree of notoriety thanks to runaway air pollution problems. The spread of viral respiratory diseases is facilitated in polluted environments, an example of which is the respiratory syncytial virus bronchiolitis. In this opinion paper, we consider the possible relationship between air pollution, primarily airborne PM10–2.5, and the spread of the novel coronavirus in Northern Italy. If it is true that the novel coronavirus remains active from some hours to several days on various surfaces, it is logical to postulate that the same can occur when it is adsorbed or absorbed by the atmospheric particulate matter, which may also help carry the virus into the human respiratory system. As the Earth presents us with a very high bill to pay, governments and other authorities need to take prompt action to counter excessive pollution levels, both in Italy and in other countries.

scholarly journals A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado

2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Aerosol Optical Depth ◽  
Citizen Science ◽  
Optical Depth ◽  
Spatial Scales ◽  
Fine Particulate Matter ◽  
Optical Measurements ◽  
Fine Particulate ◽  
Northern Colorado

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.

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