Difference between revisions of "ISSS608 2017-19 T1 Assign HyderAli Conclusion"

From Visual Analytics and Applications
Jump to navigation Jump to search
(Created page with "<div style=background:#bdb0ab border:#A3BFB1> 165px <b><font size = 6; color="#3a2e29"> Air Pollution in Sofia City </font></b> </div> <!--Navigation--> {...")
 
 
(6 intermediate revisions by the same user not shown)
Line 1: Line 1:
 
<div style=background:#bdb0ab border:#A3BFB1>
 
<div style=background:#bdb0ab border:#A3BFB1>
 
[[Image:AP_HA.png|165px]]  
 
[[Image:AP_HA.png|165px]]  
−
<b><font size = 6; color="#3a2e29"> Air Pollution in Sofia City </font></b>
+
<b><font size = 6; color="#3a2e29"> A Visualization Approach to Air Pollution in Sofia </font></b>
 
</div>
 
</div>
 
<!--Navigation-->
 
<!--Navigation-->
Line 16: Line 16:
 
| style="font-family:Century Gothic; font-weight:bold; font-size:100%; text-align:center; background-color:#eae5e4; width=20%" |  
 
| style="font-family:Century Gothic; font-weight:bold; font-size:100%; text-align:center; background-color:#eae5e4; width=20%" |  
 
;
 
;
−
[[ISSS608_2017-19_T1_Assign_HyderAli_Conclusion|<font color="#000000">Conclusion</font>]]
+
[[ISSS608_2018-19_T1_Assign_HyderAli_Conclusion|<font color="#000000">Task 3 Insights</font>]]
 
|}
 
|}
 
<br>
 
<br>
−
<div style="border-style: solid; border-width:0; background: #c8bdb9; padding: 7px; font-weight: bold; text-align:left; line-height: wrap_content; text-indent: 20px; font-size:20px; font-family:Century Gothic;border-bottom:5px solid white; border-top:5px solid black"><font color= #000000>Conclusion (Task 3 Answer)</font></div>
+
<div style="border-style: solid; border-width:0; background: #c8bdb9; padding: 7px; font-weight: bold; text-align:left; line-height: wrap_content; text-indent: 20px; font-size:20px; font-family:Century Gothic;border-bottom:5px solid white; border-top:5px solid black"><font color= #000000>Insights</font></div>
 +
''In this third task, you are required to reveal the relationships between the factors mentioned below and the air quality measure detected in Task 1 and Task 2.  Limit your response to no more than 5 images and 600 words.
 +
* Local energy sources.  For example, according to [http://unmaskmycity.org/project/sofia/ Unmask My City], a global initiative by doctors, nurses, public health practitioners, and allied health professionals dedicated to improving air quality and reducing emissions in our cities, Bulgaria’s main sources of PM10, and fine particle pollution PM2.5 (particles 2.5 microns or smaller) are household burning of fossil fuels or biomass, and transport. 
 +
* Local meteorology such as temperature, pressure, rainfall, humidity, wind etc
 +
* Local topography
 +
* Complex interactions between local topography and meteorological characteristics.
 +
* Transboundary pollution for example the haze that intruded into Singapore from our neighbours.''
 +
In this section, we will proceed to investigate the relationship between pollutant levels and weather factors such as temperature, pressure, rainfall, humidity and wind speed during high pollutant periods between November and January.
 +
The correlation scatter in the Official and Citizen Science Air Quality shows that P1 (most likely PM 2.5) and P2 (most likely PM 10) are strongly positively correlated with a Pearson's r value = 0.934. The positive correlation between P1 and P2 pollutant concentration levels indicates that P1 and P2 may be emitted by the same sources, or one may be emitted by the transformation of another through some type of chemical mechanism. Thus, a combined physical and chemical analysis of pollutants is desirable to determine the specific reasons. The correlation among pollutant and weather factors such as Pressure, Humidity, Temperature, Wind, Precipitation and Dew Point Temperature is generally low (<0.20), which could be a strong indication that Air Quality is less likely to be linked to natural phenomenon. <br>
 +
[[File: corr_plot_1.png|600px]] [[File: corr_plot_2.png|600px]] <br>
 +
Incorporating time-series factor into the pollutant concentration trends, it is evident that the temperature inversion effect (low temperatures and stagnant air during cold seasons have a way of creating a build-up of particulate matter near the ground whereby cold air is trapped near the ground by a layer of warm air which then acts like a lid to hold these substances down) intensifies the air pollution levels in Sofia. As the temperature starts to fall from Nov-17 to Feb-18, P1 and P2 concentration levels starts to rise due to the temperature inversion effect.<br>
 +
[[File: corr_plot_3.png|800px]]
  
−
We hypothesize that the Rose-crested Blue Pipits may have been affected by certain activities at their old hangout location at the alleged dumping site. From Task 1 we see they had been found there in large concentrations pre-2014, had stopped singing in 2014 which shows they may have been under distress, and had moved away from there since 2015. These observations point to the high possibility that something bad had happened at that location in year 2014 which caused them to move away.
+
== Relationship between Air Quality Pattern and Local Topography ==
 +
The topography map of Sofia  city shows that it is situated in the bottom of a deep valley between high surrounding mountains. P1 and P2 pollutant concentration levels tend to rise and intensify towards the center of the city of lower elevation as indicated by the red hot-spots in the figures below. Although the air pollution in Sofia may be caused by human activity factors and further aggravated by temperature inversion factors, it's location in the Sofia valley by being surrounded by mountains also poses a serious problem because it also reduces the ability of the air to self-clean.<br>
 +
[[File: topo_1.png|400px]] [[File: topo_2.png|600px]] [[File: topo_3.png|600px]]
  
−
On top of these observations centered around the Pipit, it was also found that another 7 species of the 19 species had obvious changes in their numbers and/or their spatial distribution in years 2014 and 2015, and these 7 species do not live near the dumping site. It seems the problem is more than just the alleged dumping site and the Rose-crested Blue Pipits, as nearly half of the species had shown signs of moving away or reductions in numbers and spatially these effects are observed throughout the Preserve, not just at the alleged dumping site.
+
== Relationship between Air Quality Pattern and Local Energy Sources ==
−
 
+
Production of electricity by burning of coal in thermal power plants is also a major contributor to unhealthy air in Sofia. It is observed that the the pollutant level concentrations of Sofia, indicated by the red hot spots in the plot below, is high around Sofia Power Plant and Sofia Iztok Power Plant. This finding identifies the potential sources of pollutants and degree of air pollution contributed by the thermal power plants in Sofia city. As such, management strategies to move away from coal energy and relying on renewable energy sources should be suggested. <br>
−
From Task 2 we found that only two out of fifteen test files were recordings of the Rose-crested Blue Pipit, and both these files were recorded at locations far away from the usual hangout locations of the species. In addition, some of the fifteen test files do not appear to be recorded in the Preserve, as their spectrograms did not match any of the 19 species identified and provided by Mistford College. Overall, the set provided by Kasios did not support their claim that the Pipits are being found across the Preserve.
+
[[File: local_ener.png|800px]]
−
 
+
== Data Visualization Design ==
−
As many species started showing signs of change in 2014, we should investigate the movement of vehicles and visitors in the Preserve in the year 2014, considering the fact that in mini-challenge 1 2017 the dataset was only from May 1 2015 to May 1 2016. As the effects from negative externalities are not only constrained to around the dumping site but also observed throughout the Preserve, this may be related to the finding in mini-challenge 2 from 2017 that Methylosmolene was detected in their smokestack emissions, and if that was true, that could be causing the air in the Preserve to be undesirable for the birds to live in. Therefore investigations should also be carried out about the smokestack emissions and general air quality in the Preserve.
+
<big>'''[https://public.tableau.com/profile/hyder.ali#!/vizhome/Task3-1_0/CorrelationPlot Link 1]'''</big>
−
 
+
<big>'''[https://public.tableau.com/profile/hyder.ali#!/vizhome/Task3-2_1/Sheet23 Link 2]'''</big>
−
The current collection strategy does not ensure an equal number of recordings being collected each period, which makes it difficult to support or refute the claim that the Pipits or any species are still living happily in the Preserve because it is compounded by the fact that some years have more recordings than other years overall. What seems like a reduction in species numbers during spatial analysis could actually be due to the reduction in recordings for those years. Moving forward, a consistent methodology for bird recording collection should be adopted. Explore the possibility of replacing the human collectors with sensors, so that the sensors can be configured to collect recordings at equal time intervals of the day, month and year.
 
−
 
 
−
 
 
−
Banner image credit to: [https://www.flickr.com/photos/23660854@N07/24385545393 Marshal Hedin]
 

Latest revision as of 09:20, 18 November 2018

AP HA.png A Visualization Approach to Air Pollution in Sofia

Overview

Task 1 Insights

Task 2 Insights

Task 3 Insights


Insights

In this third task, you are required to reveal the relationships between the factors mentioned below and the air quality measure detected in Task 1 and Task 2. Limit your response to no more than 5 images and 600 words.

  • Local energy sources. For example, according to Unmask My City, a global initiative by doctors, nurses, public health practitioners, and allied health professionals dedicated to improving air quality and reducing emissions in our cities, Bulgaria’s main sources of PM10, and fine particle pollution PM2.5 (particles 2.5 microns or smaller) are household burning of fossil fuels or biomass, and transport.
  • Local meteorology such as temperature, pressure, rainfall, humidity, wind etc
  • Local topography
  • Complex interactions between local topography and meteorological characteristics.
  • Transboundary pollution for example the haze that intruded into Singapore from our neighbours.

In this section, we will proceed to investigate the relationship between pollutant levels and weather factors such as temperature, pressure, rainfall, humidity and wind speed during high pollutant periods between November and January. The correlation scatter in the Official and Citizen Science Air Quality shows that P1 (most likely PM 2.5) and P2 (most likely PM 10) are strongly positively correlated with a Pearson's r value = 0.934. The positive correlation between P1 and P2 pollutant concentration levels indicates that P1 and P2 may be emitted by the same sources, or one may be emitted by the transformation of another through some type of chemical mechanism. Thus, a combined physical and chemical analysis of pollutants is desirable to determine the specific reasons. The correlation among pollutant and weather factors such as Pressure, Humidity, Temperature, Wind, Precipitation and Dew Point Temperature is generally low (<0.20), which could be a strong indication that Air Quality is less likely to be linked to natural phenomenon.
Corr plot 1.png Corr plot 2.png
Incorporating time-series factor into the pollutant concentration trends, it is evident that the temperature inversion effect (low temperatures and stagnant air during cold seasons have a way of creating a build-up of particulate matter near the ground whereby cold air is trapped near the ground by a layer of warm air which then acts like a lid to hold these substances down) intensifies the air pollution levels in Sofia. As the temperature starts to fall from Nov-17 to Feb-18, P1 and P2 concentration levels starts to rise due to the temperature inversion effect.
Corr plot 3.png

Relationship between Air Quality Pattern and Local Topography

The topography map of Sofia city shows that it is situated in the bottom of a deep valley between high surrounding mountains. P1 and P2 pollutant concentration levels tend to rise and intensify towards the center of the city of lower elevation as indicated by the red hot-spots in the figures below. Although the air pollution in Sofia may be caused by human activity factors and further aggravated by temperature inversion factors, it's location in the Sofia valley by being surrounded by mountains also poses a serious problem because it also reduces the ability of the air to self-clean.
Topo 1.png Topo 2.png Topo 3.png

Relationship between Air Quality Pattern and Local Energy Sources

Production of electricity by burning of coal in thermal power plants is also a major contributor to unhealthy air in Sofia. It is observed that the the pollutant level concentrations of Sofia, indicated by the red hot spots in the plot below, is high around Sofia Power Plant and Sofia Iztok Power Plant. This finding identifies the potential sources of pollutants and degree of air pollution contributed by the thermal power plants in Sofia city. As such, management strategies to move away from coal energy and relying on renewable energy sources should be suggested.
Local ener.png

Data Visualization Design

Link 1 Link 2

Retrieved from ‘https://wiki.smu.edu.sg/18191isss608g1/index.php?title=ISSS608_2017-19_T1_Assign_HyderAli_Conclusion&oldid=3016’