This is a visualization of the US AQI pollution levels over all the years of
data collection for the station named "Pai Overall Average."
We align each year by month so that you can compare seasonal pollution levels. The dim vertical lines are weeks
of each month (7 day intervals).
Within the colorful horizontal strip for a given year, each vertical column represents one day.
Here is an example where we highlight one day with a blue box:
คำอธิบาย
นี่คือการแสดงภาพระดับมลพิษ US AQI ในช่วงหลายปีที่ผ่านมาของการรวบรวมข้อมูลสำหรับสถานีที่มีชื่อ "ค่าเฉลี่ยทั่วอำเภอปาย"
As you move up the column for that day from bottom to top, you move
from early morning, through noon (12:00), to midnight. So the example
day above had red pollution level until about 04:00 (4am), then went
to yellow level until about 14:00 (2pm), then went to green level for
most of the evening and night.
You can use this visualization to see what time of day pollution is
typically better or worse.
Here is a slightly different visualization that helps you get a sense of what
percent of each day has different levels of pollution (rather than what time of day).
To help you see this, we sort the pollution levels seen on each day from the
cleanest levels (bottom) to the dirtiest levels (top):
You see green that takes up about 30% of the vertical range. So that means that pollution was at green level for about 30% of that day (not necessarily all in one period: the day might have had many short periods of green that added up to 30%).
You see yellow that takes up about 50% of the vertical range, so that means pollution was at yellow level for about 50% of that day (again, not necessarily all in one period).
You see red that takes up about 20% of the vertical range, telling you that pollution was at red level for about 20% of that day (again, not necessarily all in one period).
This visualization was inspired by the yearly charts from aqicn.org,
which show three levels per day (quartile 1-3, aka 25%, 50%, 75%)
diagonally in each square. Here we have expanded on that idea by
showing up to 24 levels per day and displaying in a vertical format
that makes it easier to see day-to-day patterns. And we have made the
visualization more useful by merging together years of data from 25+
Pai stations into the Pai Overall
Average virtual station.
If you incorporate, or are inspired by, this visualization idea in
your website or app, please give credit and link to: https://allaboutpai.com/weather/.
Thank you.
This is a visualization of Pollution, Rain, Wind Speed and Temperature over all the years of
data collection for the station named "Pai Overall Average."
Like the first pollution chart above, each column represents one day
and goes from early morning (bottom) to noon (middle) to late night
(top).
The color scale for Temperature (Celsius) looks like:
ระดับสีสำหรับอุณหภูมิ (เซลเซียส) ลักษณะดังนี้:
No data
ไม่มี ข้อมูล
0°C
25°C
50°C
Note: rain and wind data comes from the "Wiang Nuea: Vimarnkiri Resort Rain and Wind" station,
which might not be near the place where pollution and temperature data were measured.
This is a visualization of Pollution, Rain, Wind Speed and Temperature over all the years of
data collection for the station named "Pai Overall Average."
Like the second pollution chart above, each column
represents one day and goes from lowest measurement level (on the bottom) to the highest measurement level
(on the top).
Taking temperature as an example, each column represents one day
and goes from the coldest temperature (on the bottom) to the
hottest temperature (on the top). So you can use this visualization
to see what percent of the day you will spend at different
temperatures.
The color scale for Temperature (Celsius) looks like:
ระดับสีสำหรับอุณหภูมิ (เซลเซียส) ลักษณะดังนี้:
No data
ไม่มี ข้อมูล
0°C
25°C
50°C
Note: rain and wind data comes from the "Wiang Nuea: Vimarnkiri Resort Rain and Wind" station,
which might not be near the place where pollution and temperature data were measured.
