Difference between revisions of "ISSS608 2018-19 T1 Assign Cao Xinjie"
| Line 26: | Line 26: | ||
; | ; | ||
|} | |} | ||
| + | <!--MAIN HEADER--> | ||
| + | <big><big><big>'''Air Pollution in Sofia, Bulgaria - An Investigative Journey'''</big></big></big> | ||
| − | = | + | =Background= |
| − | + | Air pollution is a recurring problem and one of the most important risk factors for health in major cities all over the world. Worldwide an estimated 9 million people died prematurely because of pollution annually. In addition, air pollution has also been classified as the leading environmental cause of cancer. | |
| − | + | Sofia is no exception to this. Bulgaria’s issue with air pollution is not new. Prior to the early 90s, there had been a big issue with sulphur oxides emissions from industry in the city contribution to air pollution. With the die-down of large industry since then, focus shifted towards particulate matter (PM). The issue has gained public attention in recent years. | |
| − | |||
| − | |||
| − | |||
| − | + | <span style=text-align:center;">[[File:Particulate Matter.jpg|thumb|right|220px|Particulate Matter]]</span> | |
| − | < | + | Particulate matter (PM) is a complex mixture of extremely small airborne particles and liquid droplets. Once inhaled, these particles can affect the heart and lungs and cause serious health effects. Some particles, such as dust, dirt, soot, or smoke, are large or dark enough to be seen with the naked eye. Others are so small they can only be detected using an electron microscope. |
| − | |||
| − | |||
| − | [[ | ||
| − | |||
| − | == | + | Particulate pollution includes: <br> |
| − | < | + | • PM10: inhalable particles, with diameters that are generally 10 micrometers and smaller; and <br> |
| − | < | + | • PM2.5: fine inhalable particles, with diameters that are generally 2.5 micrometers and smaller. |
| − | < | + | |
| − | < | + | Visual analytics approach will be used for this project to reveal spatio-temporal patterns of air quality in Sofia City and to identify issues of concern. |
| + | |||
| + | =Tasks= | ||
| + | ===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? | ||
| + | |||
| + | ===Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements=== | ||
| + | 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? | ||
| + | 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? | ||
| + | |||
| + | ===Task 3: Spatio-temporal Analysis of Meteorological & Environmental Factors=== | ||
| + | Urban air pollution is a complex issue. There are many factors affecting the air quality of a city. Some of the possible causes are: <br> | ||
| + | • 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. <br> | ||
| + | • Local meteorology such as temperature, pressure, rainfall, humidity, wind etc <br> | ||
| + | • Local topography <br> | ||
| + | • Complex interactions between local topography and meteorological characteristics. <br> | ||
| + | • 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. | ||
| + | |||
| + | =The Data Sets= | ||
| + | Four major data sets provided for this assignment are: <br> | ||
| + | • Official air quality measurements (5 stations in the city) (EEA Data.zip) – as per EU guidelines on air quality monitoring <br> | ||
| + | • Citizen science air quality measurements (Air Tube.zip) , incl. temperature, humidity and pressure (many stations) and topography (gridded data).<br> | ||
| + | • Meteorological measurements (1 station) (METEO-data.zip): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility<br> | ||
| + | • Topography data (TOPO-DATA) | ||
| + | |||
| + | =Visualization Software= | ||
| + | To perform the visual analysis, a combination of the following software has been used: <br> | ||
| + | • Tableau Desktop 2018.3 <br> | ||
| + | • SAS JMP Pro 14 <br> | ||
| + | • R Studio (Packages: Tidyverse, Geohash) | ||
| + | |||
| + | =References= | ||
| + | [http://advancom.com.my/?product=particle-counter Particulate Matter Diagram] <br> | ||
| + | [https://www.epa.gov/pm-pollution/particulate-matter-pm-basics#PM Particulate Matter Basics] <br> | ||
| + | [https://airtube.info/index.php?pos=42.70438894943289,23.356933593750004,11 Airtube Citizen Science Air Quality Data] <br> | ||
| + | [https://www.washingtonpost.com/news/energy-environment/wp/2017/10/19/pollution-kills-9-million-people-each-year-new-study-finds/?noredirect=on&utm_term=.01d6d75d3d5a Air pollution kills 9 million people each year] | ||
Revision as of 20:47, 17 November 2018
Sofia Air Pollution - Be a Visual Detective
|
|
|
|
|
|
Air Pollution in Sofia, Bulgaria - An Investigative Journey
Contents
Background
Air pollution is a recurring problem and one of the most important risk factors for health in major cities all over the world. Worldwide an estimated 9 million people died prematurely because of pollution annually. In addition, air pollution has also been classified as the leading environmental cause of cancer. Sofia is no exception to this. Bulgaria’s issue with air pollution is not new. Prior to the early 90s, there had been a big issue with sulphur oxides emissions from industry in the city contribution to air pollution. With the die-down of large industry since then, focus shifted towards particulate matter (PM). The issue has gained public attention in recent years.
Particulate matter (PM) is a complex mixture of extremely small airborne particles and liquid droplets. Once inhaled, these particles can affect the heart and lungs and cause serious health effects. Some particles, such as dust, dirt, soot, or smoke, are large or dark enough to be seen with the naked eye. Others are so small they can only be detected using an electron microscope.
Particulate pollution includes:
• PM10: inhalable particles, with diameters that are generally 10 micrometers and smaller; and
• PM2.5: fine inhalable particles, with diameters that are generally 2.5 micrometers and smaller.
Visual analytics approach will be used for this project to reveal spatio-temporal patterns of air quality in Sofia City and to identify issues of concern.
Tasks
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?
Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements
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? 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?
Task 3: Spatio-temporal Analysis of Meteorological & Environmental Factors
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.
The Data Sets
Four major data sets provided for this assignment are:
• Official air quality measurements (5 stations in the city) (EEA Data.zip) – as per EU guidelines on air quality monitoring
• 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)
Visualization Software
To perform the visual analysis, a combination of the following software has been used:
• Tableau Desktop 2018.3
• SAS JMP Pro 14
• R Studio (Packages: Tidyverse, Geohash)
References
Particulate Matter Diagram
Particulate Matter Basics
Airtube Citizen Science Air Quality Data
Air pollution kills 9 million people each year
