Difference between revisions of "ISSS608 2018-19 T1 Assign Cao Xinjie"

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<font size = 6;text-align:center; color="#FFFFFF"> Group 6 - How is Beijing Air Quality? </font>
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<font size = 6;text-align:center; color="#FFFFFF">     Sofia Air Pollution - Be a Visual Detective </font>  
 
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<font size="5">'''To be a Visual Detective'''</font>
 +
 +
The assignments require you to put the concepts, methods and techniques you had learned in class to solve real world problem using visual analytics techniques.  Students should also use the assignments to gain hands-on experience on using the data visualisation toolkits I had shared with you to complate the assignment.
 +
 +
=Overview=
 +
 +
Air pollution is an important risk factor for health in Europe and worldwide. A recent review of the global burden of disease showed that it is one of the top ten risk factors for health globally.  Worldwide an estimated 7 million people died prematurely because of pollution; in the European Union (EU) 400,000 people suffer a premature death. The Organisation for Economic Cooperation and Development (OECD) predicts that in 2050 outdoor air pollution will be the top cause of environmentally related deaths worldwide. In addition, air pollution has also been classified as a leading environmental cause of cancer. 
 +
 +
Air quality in Bulgaria is a big concern: measurements show that citizens all over the country breathe in air that is considered harmful to health. For example, concentrations of PM2.5 and PM10 are much higher than what the EU and the World Health Organization (WHO) have set to protect health.
 +
 +
Bulgaria had the highest PM2.5 concentrations of all EU-28 member states in urban areas over a three-year average. For  PM10, Bulgaria is also leading on the top polluted countries with 77 μg/m3on the daily mean concentration (EU limit value is 50 μg/m3).
 +
 +
According to the WHO, 60 percent of the urban population in Bulgaria is exposed to dangerous (unhealthy) levels of particulate matter (PM10).
 +
[[File:WechatIMGd.png|thumb]]
 +
 +
=The Task=
 +
 +
In this assignment, you are required to use visual analytics approach to reveal spatio-temporal patterns of air quality in Sofia City and to identify issues of concern. 
 +
 +
==Task 1: Spatio-temporal Analysis of Official Air Quality==
 +
 +
Characterize the past and most recent situation with respect to air quality measures in Sofia City. What does a typical day look like for Sofia city? Do you see any trends of possible interest in this investigation?  What anomalies do you find in the official air quality dataset? How do these affect your analysis of potential problems to the environment? 
 +
 +
Your submission for this questions should contain no more than 10 images and 1000 words.
 +
 +
==Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements ==
 +
 +
Using appropriate data visualisation, you are required will be asked to answer the following types of questions:
 +
 +
* Characterize the sensors’ coverage, performance and operation. Are they well distributed over the entire city? Are they all working properly at all times? Can you detect any unexpected behaviors of the sensors through analyzing the readings they capture? Limit your response to no more than 4 images and 600 words.
 +
* Now turn your attention to the air pollution measurements themselves.  Which part of the city shows relatively higher readings than others?  Are these differences time dependent? Limit your response to no more than 6 images and 800 words.
 +
 +
==Task 3==
 +
 +
Urban air pollution is a complex issue.  There are many factors affecting the air quality of a city.  Some of the possible causes are:
 +
 +
* 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 third task, you are required to reveal the relationships between the factors mentioned above and the air quality measure detected in Task 1 and Task 2.  Limit your response to no more than 5 images and 600 words. 
 +
 +
 +
=The Data Sets=
 +
 +
Four major data sets in zipped file format are provided for this assignment, they are:
 +
 +
* Official air quality measurements (5 stations in the city)(EEA Data.zip) – as per EU guidelines on air quality monitoring see the data description [https://drive.google.com/file/d/1v5yCL-LdriDwa65qXPbFL7b0tydylDlb/view HERE…]
 +
* Citizen science air quality measurements (Air Tube.zip) , incl. temperature, humidity and pressure (many stations) and topography (gridded data).
 +
* Meteorological measurements (1 station)(METEO-data.zip): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility
 +
* Topography data (TOPO-DATA)
 +
 +
They can be download by click on this [https://storage.cloud.google.com/global-datathon-2018/sofia-air/air-sofia.zip link].
 +
 +
 +
=Visualisation Software=
 +
 +
To perform the visual analysis, students are encouraged to explore any one or a combination of the following software:
 +
*Tableau
 +
*JMP Pro
 +
*Qlik Sense
 +
*Microsoft Power BI
 +
 +
One of the goals of this assignment is for you to learn to use and evaluate the effectiveness of these visual analytics tools.
 +
 +
 +
=Submission details=
 +
 +
This is an individual assignment. You are required to work on the assignment and prepare submission individually. Your completed assignment is due on '''18th November 2018, by 11.59pm mid-night'''.
 +
 +
You need to edit your assignment in the appropriate wiki page of the Assignment Dropbox. The title of the wiki page should be in the form of: ISSS608_2018-19_T1_Assign_FullName.
 +
 +
The assignment wiki page should include the URL link to the web-based interactive data visualization system prepared.
  
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==PROJECT OVERVIEW==
 
−
<p align="justify">On Nov 4th, Beijing Environmental Protection Agency released the news, owing to the adverse weather conditions and early winter heating as well as other factors, it is expected that there will be a continuous 4-day regional heavily polluted air quality in Beijing-Tianjin-Hebei and surrounding areas on November 4th, in addition, the air quality in some cities may reach serious pollution level….</p>
 
−
<p align="justify">“Why is China’s smog so bad now?”, a lot of people from overseas want to explore. With the rapid development of economy in China, news from China is more frequently commented in the globe. China’s air pollution has been a serious issue for more than 10 years, with the problem appealing more attention worldwide, the Chinese government has make big efforts to solve it.</p>
 
−
<p align="justify">China's capital Beijing is under pressure to bring average PM2.5 readings to 60 micrograms per cubic meter this year, which has decreased from 73 micrograms since last year. Nonetheless, the index is still higher than the official air quality standard value in China Mainland.</p>
 
−
<p align="justify">Along with the increasing escalation of air pollution, most people who are working and living in Beijing are faced with the tracheitis, pneumoconiosis, asthma, to name just a few. Nowadays, current air quality fails to meet people's expectation. Gradually, a lot of people are terrified with living and working in Beijing.</p>
 
−
<p align="justify">In our project, we mean to apply the visual analytics tools to better visualize the changes of air quality according its existing indicators. We will show the fluctuation of the historical AQI (Air Quality Index), the pollutant concentrations and trend charts by pollutants in the different view point in Beijing. We hope that we can try our best to show the weather condition, make people clearly know more about the surroundings they are living in as well as raise the public awareness of environmental protection.</p>
 
  
−
==DATASET DESCRIPTION==
+
=Reference=
−
<p align="justify">This dataset is provided by Beijing Municipal Environmental Monitoring Center. We only select the data in 2017 to do the further analysis in our project, which contains 87,361 records for the Beijing air quality each hour, which starts from 2017-01-01 to 2017-11-01. The dataset includes the columns: City, Date, Hour, View point, AQI, Air Quality Descriptor, 1-hr PM2.5, 24-hr PM2.5, 1-hr PM10, 24-hr PM10, 1-hr SO2, 24-hr SO2, 1-hr NO2, 24-hr NO2, 1-hr CO,
 
−
24-hr CO, 1-hr O3, 8-hr O3 and Primary pollutant.</p>
 
−
<p align="justify">The following header shows part of the dataset:</p>
 
−
[[image:Air5.PNG|1100px|center]]
 
−
<p align="justify"></p>
 
  
−
==TOOLS==
+
* [https://wiki.smu.edu.sg/1617t1ISSS608g1/ISSS608_2016-17_T1_Assign3_Ong_Han_Ying Dino Holmes Series]
−
<p align="justify">ggplot2</p>
+
* [https://wiki.smu.edu.sg/1617t3isss608g1/ISSS608_2016-17_T3_Assign_GUAN_YIFEI Mystery at the Wildlife Preserve]
−
<p align="justify">tidyverse</p>
+
* [https://wiki.smu.edu.sg/1718t1isss608g1/ISSS608_2017-18_T1_Assign_RACHEL_TONG Sickness in SmartPolis]
−
<p align="justify">zoo</p>
+
* [https://wiki.smu.edu.sg/1718t3isss608/ISSS608_2017-18_T3_Assign_Tan_Yong_Ying Suspense at the Wildlife Preserve]
−
<p align="justify">shiny</p>
 

Latest revision as of 00:15, 18 November 2018

WechatIMG8.png Sofia Air Pollution - Be a Visual Detective

Overview

Data Preparation

Task1

Task2

Task3

Dashboard


To be a Visual Detective

The assignments require you to put the concepts, methods and techniques you had learned in class to solve real world problem using visual analytics techniques. Students should also use the assignments to gain hands-on experience on using the data visualisation toolkits I had shared with you to complate the assignment.

Overview

Air pollution is an important risk factor for health in Europe and worldwide. A recent review of the global burden of disease showed that it is one of the top ten risk factors for health globally. Worldwide an estimated 7 million people died prematurely because of pollution; in the European Union (EU) 400,000 people suffer a premature death. The Organisation for Economic Cooperation and Development (OECD) predicts that in 2050 outdoor air pollution will be the top cause of environmentally related deaths worldwide. In addition, air pollution has also been classified as a leading environmental cause of cancer.

Air quality in Bulgaria is a big concern: measurements show that citizens all over the country breathe in air that is considered harmful to health. For example, concentrations of PM2.5 and PM10 are much higher than what the EU and the World Health Organization (WHO) have set to protect health.

Bulgaria had the highest PM2.5 concentrations of all EU-28 member states in urban areas over a three-year average. For PM10, Bulgaria is also leading on the top polluted countries with 77 μg/m3on the daily mean concentration (EU limit value is 50 μg/m3).

According to the WHO, 60 percent of the urban population in Bulgaria is exposed to dangerous (unhealthy) levels of particulate matter (PM10).

WechatIMGd.png

The Task

In this assignment, you are required to use visual analytics approach to reveal spatio-temporal patterns of air quality in Sofia City and to identify issues of concern.

Task 1: Spatio-temporal Analysis of Official Air Quality

Characterize the past and most recent situation with respect to air quality measures in Sofia City. What does a typical day look like for Sofia city? Do you see any trends of possible interest in this investigation? What anomalies do you find in the official air quality dataset? How do these affect your analysis of potential problems to the environment?

Your submission for this questions should contain no more than 10 images and 1000 words.

Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements

Using appropriate data visualisation, you are required will be asked to answer the following types of questions:

  • Characterize the sensors’ coverage, performance and operation. Are they well distributed over the entire city? Are they all working properly at all times? Can you detect any unexpected behaviors of the sensors through analyzing the readings they capture? Limit your response to no more than 4 images and 600 words.
  • Now turn your attention to the air pollution measurements themselves. Which part of the city shows relatively higher readings than others? Are these differences time dependent? Limit your response to no more than 6 images and 800 words.

Task 3

Urban air pollution is a complex issue. There are many factors affecting the air quality of a city. Some of the possible causes are:

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


The Data Sets

Four major data sets in zipped file format are provided for this assignment, they are:

  • Official air quality measurements (5 stations in the city)(EEA Data.zip) – as per EU guidelines on air quality monitoring see the data description HERE…
  • Citizen science air quality measurements (Air Tube.zip) , incl. temperature, humidity and pressure (many stations) and topography (gridded data).
  • Meteorological measurements (1 station)(METEO-data.zip): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility
  • Topography data (TOPO-DATA)

They can be download by click on this link.


Visualisation Software

To perform the visual analysis, students are encouraged to explore any one or a combination of the following software:

  • Tableau
  • JMP Pro
  • Qlik Sense
  • Microsoft Power BI

One of the goals of this assignment is for you to learn to use and evaluate the effectiveness of these visual analytics tools.


Submission details

This is an individual assignment. You are required to work on the assignment and prepare submission individually. Your completed assignment is due on 18th November 2018, by 11.59pm mid-night.

You need to edit your assignment in the appropriate wiki page of the Assignment Dropbox. The title of the wiki page should be in the form of: ISSS608_2018-19_T1_Assign_FullName.

The assignment wiki page should include the URL link to the web-based interactive data visualization system prepared.


Reference

Retrieved from ‘https://wiki.smu.edu.sg/18191isss608g1/index.php?title=ISSS608_2018-19_T1_Assign_Cao_Xinjie&oldid=2831’