This project transforms the air pollution index into visible poles to demonstrate the PM2.5 (Fine Particulate Matter) air pollution vividly for ordinary people. We got inspiration from an artist who made a brick of PM2.5 particles after collecting them for 100 days with a vacuum in Beijing. Therefore, we determined to calculate if we compress PM2.5 particles in several cities to make poles, how tall will the buildings be? In this way, people can have a clear vision of how severe PM2.5 pollutions in some cities are, and how the comparison of air quality between countries and regions can be dramatically evident.

# STEP 1

## Definitions & Formulations

The ultimate goal of these definitions and formulation is to figure out how tall a pillar can be with the PM2.5 in a city for an average day. So we defined the mainly required statistics and created formulas before collecting data and further calculation.

PM2.5: Fine particles with a diameter of 2.5μm or less

We choose PM2.5 because they do greater damage than larger particles like PM10 since PM2.5 can penetrate deeply into the respiratory system and therefore entail a risk for health by increasing mortality from respiratory infections and diseases, lung cancer, and certain cardiovascular diseases.

The Concentration of PM2.5 (CPM2.5)：Annual means (μg/m3)

We use the annual mean of with a unit of “ μg/m3” because this indicator depicts the yearly condition of each city and is feasible to make a comparison.

The Density of PM2.5(ρPM2.5): 1g/cm3

As PM2.5 consists of different components in terms of time and space, the density of these particulates varies a lot. In practice, however, if the aerosol characteristics exhibited by the particles are consistent with spherical particles having a diameter of 2.5 m or less and a density of 1g/cm3, we called them PM2.5. Therefore, we assume that the density of PM2.5 is 1 g/cm3.

The Height of PM2.5 Polluted Atmosphere (HUrban Atmosphere): 100m

We define that the PM2.5 which has a negative influence on human spreads 0m to 100m above ground.

Urban Area (SUrban Area): Built-up land area (km3)

When determining the PM2.5 index, we consider the built-up land area of each city, so that the non-built-up suburban area will not be counted in the following calculation.

The Bottom Area of the PM2.5 Poles (SBottom): 491cm2

We use the bottom area of a regular utility pole (with a diagram of 25cm) as the bottom of the PM2.5 poles so that people can better understand the size of the poles.

In accordance with the terms mentioned above, we can get formulas about:

• The volume of PM2.5 polluted atmospheres in urban areas (VUrban Atmosphere)
• The mass of PM2.5 in urban areas (MPM2.5)
• The volume of PM2.5 in urban areas (VPM2.5)
• And ultimately, the height of the PM2.5 poles (HPM2.5) is as follows:

$∵ \ V_{Urban~Atmosphere} = \ S_{Urban~Area} * \ H_{Urban~Atmosphere}$

$∵ \ H_{Urban~Atmosphere} = {100m}, \ ρ_{PM2.5} = {1g/cm^3}, \ S_{Bottom} = {491cm^2}$

$∴ \ H_{PM2.5} = \frac{ 100m }{ 491cm^2 * 1g/cm^3} * S_{Urban~Area} * C_{PM2.5}$

# STEP 2

## Collecting, Filtering, and Calculating Data

### Data Collecting

Basing on the definitions and formulations mentioned above, we found relevant data are the annual average PM2.5 index and urban area of major cities around the world.

We got the Ambient Air Pollution Database released from World Health Organization in May 2016, containing almost 3, 000 cities’ recently available annual average PM2.5. Meanwhile, we acquired the built-up land area of the top 1, 000 largest cities globally from the 12th Annual Edition of Demographia World Urban Areas published in April 2016.

Ambient Air Pollution Database (2016)

Demographia World Urban Areas (12th Annual Edition)

### Data Filtering

We determined to overlap the two databases and extract the top 100 cities sorted out by land mass for further visualization since the effect and efficiency will not be ideal if including thousands of cities.

First, we import the databases of land area and PM2.5 index into MySQL and conducted fuzzy search via the following code to match the objects in two databases.

We got the statistics within minutes after running the code mentioned above.

Then we scrutinized the result since there were a few matching errors and sorted out the top 100 cities.

### Data Calculation

Finally, we use the formula $\ H_{PM2.5} = \frac{ 100m }{ 491cm^2 * 1g/cm^3} * S_{Urban~Area} * C_{PM2.5}$ mentioned above to calculate the outcome of the top 100 cities in Excel.

The Height of PM2.5 Poles in Largest 100 Cities

# STEP 3

## Design

In the beginning, we sketched out different ways to visualize the statistics and asked many people to see if they can understand the prototype. Later we determined to put the 100 poles together and align them with six famous buildings around the world together.

##### Sketches

Based on the sketch work, we made the digital version and repeatedly modified it with feedback from several people before moving to the final display.

# REFLECTIONS

In this project, I learned more about data processing and design and came up with some reflections.

• The height of PM2.5 poles is influenced by both the air pollution index and the urban area of these cities. So the dramatic height does not imply that the severity of PM2.5 pollution is huge and vice versa. So later we will make a set of visualization works to show the air pollution comprehensively.

• However, the height did warn many people who saw this work how air pollution is becoming a huge problem in their cities – even a relatively low PM2.5 pollution index can lead to an enormous amount of toxic particles in urban areas, which is the case in New York and Tokyo.

• Good data visualization requires the ability to collect and process the data properly. The outcome would have been better if the way we deal with was more accurate. I have to learn more to improve my related skills.

• Good data visualization also requires user-centered design thinking. The criterion of an excellent work comes from the experience of audience – can they understand what it is about and are they influenced by the work?

I love Beijing, the capital of China where I have been living for years. But the unbearable air pollution has choked the air in winter. Residents have to wear masks frequently whenever the air pollution index rises. I really hope that this work could contribute to some changes. And one day, the PM2.5 pillar of Beijing is not the highest one anymore.