An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China
Abstract
:1. Introduction
2. Method and Data
2.1. Air Quality Mapping Technologies and Framework
2.2. Time Series Map Symbol Encoding: timezoom.js
- is the time hierarchy structure that will be calculated;
- is the time series values’ array, such as the 365 days of one year data value array, {};
- is the time system for hierarchy construction, such as {}. This can be decided by users and can be extended to hours, minutes and seconds levels, as shown in Figure 2;
- is the operation for the value aggregation from the lower time level to the higher time level. This can be any statistical method for aggregation, such as average, median, quantile, etc.
2.3. Adaptive Map Symbol Control: symadaptive.js
2.4. Data Sources and Processing
- is the individual Air Quality Index of pollutant P,
- is the concentration of pollutant P,
- is the the concentration division point of pollution P that is ,
- is the concentration breakpoint of pollution P that is ,
- is the index division point (Table 3) corresponding to ,
- is the index division point (Table 3) corresponding to .
3. Results and Discussion
3.1. Air Quality Data Map Visualization Design
3.1.1. Spatial Navigation
3.1.2. Temporal Navigation
3.1.3. Thematic Navigation
3.2. Results and Analysis
3.3. Nationwide Air Quality Condition of China
3.4. Spatio-Temporal Pattern of Air Pollutants
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A. Mapping and Visualization Technologies Used
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Name | Description and Unit |
---|---|
AQI | Air Quality Index, value without unit, range 0–500 |
SO | Sulfur Dioxide, g/m |
NO | Nitrogen Dioxide, g/m |
CO | Carbon Monoxide, |
O | Ozone, g/m |
O_8H | 8-h average concentration of Ozone, g/m |
PM2.5 | Particulate Matter, diameter less than 2.5 m, g/m |
PM10 | Particulate Matter, diameter less than 10 m, g/m |
Divisions | Health Influences | Color Coding |
---|---|---|
0–50 | Good: Satisfactory | Green (0,228,0) |
51–100 | Moderate: Acceptable, but influential for very sensitive groups. | Yellow (255,255,0) |
101–150 | Slightly Unhealthy: Influential for sensitive groups. | Orange (255,126,0) |
151–200 | Unhealthy | Red (255,0,0) |
200–300 | Very Unhealthy | Purple (153,76,0) |
>300 | Hazardous | Maroon (126,0,35) |
IAQI Ranges | SO g/m | NO g/m | PM10 g/m | PM2_5 g/m | CO mg/m | O g /m | O_8H g /m |
---|---|---|---|---|---|---|---|
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
50 | 50 | 40 | 50 | 35 | 2 | 160 | 100 |
100 | 150 | 80 | 150 | 75 | 4 | 200 | 160 |
150 | 475 | 180 | 250 | 115 | 14 | 300 | 215 |
200 | 800 | 280 | 350 | 150 | 24 | 400 | 265 |
300 | 1600 | 565 | 420 | 250 | 36 | 800 | 800 |
400 | 2100 | 750 | 500 | 350 | 48 | 1000 | - |
500 | 2620 | 940 | 600 | 500 | 60 | 1200 | - |
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Lu, W.; Ai, T.; Zhang, X.; He, Y. An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China. Atmosphere 2017, 8, 148. https://doi.org/10.3390/atmos8080148
Lu W, Ai T, Zhang X, He Y. An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China. Atmosphere. 2017; 8(8):148. https://doi.org/10.3390/atmos8080148
Chicago/Turabian StyleLu, Wei, Tinghua Ai, Xiang Zhang, and Yakun He. 2017. "An Interactive Web Mapping Visualization of Urban Air Quality Monitoring Data of China" Atmosphere 8, no. 8: 148. https://doi.org/10.3390/atmos8080148