Beijing Air Quality Forecast

Forecast plotted using timezone +08:00
Sun 11th
31°C
19°C
Mon 12th
36°C
21°C
Tue 13th
35°C
24°C
Wed 14th
33°C
20°C
Thu 15th
35°C
20°C
Fri 16th
36°C
21°C
Sat 17th
29°C
19°C
PM2.5
98
88
127
105
138
138
138
138
138
138
138
89
68
68
72
68
94
74
124
105
137
134
138
138
138
138
138
115
103
94
89
88
117
88
153
134
158
158
163
159
171
164
174
174
174
174
216
174
250
246
252
181
159
159
159
159
159
159
159
152
145
142
155
141
159
159
159
159
159
159
159
159
159
154
151
109
89
89
89
89
116
89
136
132
138
138
138
138
138
138
138
104
89
89
120
89
166
138
220
174
252
252
252
243
242
238
249
243
252
252
252
252
PM10
39
28
46
45
55
46
58
55
54
50
46
34
28
28
39
28
46
45
46
46
54
46
57
57
58
57
68
58
73
63
58
51
68
46
118
78
147
138
167
152
174
174
197
174
341
223
396
389
392
385
396
198
159
135
123
123
123
90
73
63
58
58
68
58
73
73
73
73
73
73
73
67
64
56
52
48
46
46
46
45
46
45
55
46
58
53
56
51
58
58
58
51
55
46
102
58
195
123
360
287
396
396
396
396
396
396
396
396
396
396
396
396
UVI
1
4
6
4
1
1
4
5
4
1
1
5
6
4
1
1
4
7
5
1
1
5
7
5
1
Sunday 11thMonday 12thTuesday 13thWednesday 14thThursday 15thFriday 16thSaturday 17
hour
036912151821036912151821036912151821036912151821036912151821036912151821036912151821
Wind Speed (m/s)
22356412124662223223377786442332224565432586322133635543
























































Temp.
22°28°31°30°25°23°20°19°24°30°34°34°30°26°23°22°26°32°35°33°30°28°24°24°25°29°33°32°29°26°23°20°24°31°34°35°28°24°22°20°24°31°36°29°23°23°22°21°23°28°29°29°25°20°19°19°
UVI:
6


5:04 ~ 19:19
UVI:
5


5:03 ~ 19:20
UVI:
6


5:02 ~ 19:21
UVI:
7


5:01 ~ 19:22
UVI:
7


5:00 ~ 19:23


4:59 ~ 19:23


4:58 ~ 19:24
Share: aqicn.org/forecast/beijing/
Other Cities

The detailed forecast analysis is also available for other cities:

Or just select any of those cities:

Shanghai, Chengdu, Shenyang, Shenzhen, Guangzhou, Qingdao, Xian, Tianjin, Saitama, Kyoto, Osaka, Seoul, Busan, Bogota, Delhi, Jakarta, Ulaanbaatar, Hanoi, Chennai, Kolkata, Mumbai, Hyderabad, Santiago, Lima, Saopaulo, Quito, Singapore, Kuala-lumpur, Ipoh, Perai, Miri, New York, Seattle, Chicago, Boston, Atlanta

For other cities, countries or pollutants, please refer to world air quality forecast maps:

https://waqi.info/forecast/

Forecast Map

1Speed(FPS): 18
Sat 02Mon 04Wed 06Fri 08Jan 10Friday 1st, 0:00 (UTC)
Marker
500 km
300 mi
Leaflet Map Data: © OpenStreetMap contributors; Map render © Tracestrack

City Forecast

Model Comparison

This section is experimental. It provides the comparison for the prediction for several individual forecast models

For a full list of all Air Quality Forecast models being analyser, check the forecast models page: https://aqicn.org/forecast/models/

Forecast Analysis

How accurate are the forecasts?

Check the correlation graphs below for PM2.5, PM10 and Ozone for the past 30 days.

(Note that all values are based on the AQI, and that a maximum threshold of AQI 300 is used).

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Past month PM2.5 AQI short-term forecast analysis.

In the above graph, the forecast is data is the forecast one day in advance (i.e. the forecast computed today for tomorrow).

Do you know of any Air Quality stations in your area?
why not participate to the map with your own air quality station?

Our GAIA air quality monitors are very easy to set up: You only need a WIFI access point and a USB compatible power supply.

Once connected, your real time air pollution levels are instantaneously available on the maps and through the API.

The station comes with a 10-meter water-proof power cable, a USB power supply, mounting equipment and an optional solar panel.

Air Quality Forecasts Models

There are many forecast models, for different regions of the globe - below are few of them.

Just click on any of them to see the animated map for the given model.

For a full list of all Air Quality Forecast models being analyser, check the forecast models page: https://aqicn.org/forecast/models/



Please note that all above analysis are done on the World Air Quality Index (WAQI) project own budget.

We did not receive any subsidies from any of the intuitions publishing Air Quality forecast models.



Future Improvements

We need your help

Help is needed for keeping the world-wide Air Quality forecast model inventory up-to-date.

  • Do you know any model not listed below but for which gridded data is available?
  • Do you know better accuracy analysis solutions which should be used here?
  • Have you done a similar research and you would like to publish it here?
  • If yes, send us a message with the form below and we will contact you asap!

    Forecast Model Sources

    The above prediction is based on composite meta model, computed using several Air Quality Forecasting Systems (AQFS):

    The above map is based on the PM2.5 surface level modeling, and colors are following the US EPA AQI standard.

    Disclaimer

    This forecasting model, and all AQFS which it is based on, are research products intended to provide information related to Air Quality forecast. All reasonable measures have been taken to ensure its quality and accuracy. However:

    • We do not make warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, correctness, completeness of the information.
    • We do not assume any legal liability or responsibility for any damage or loss that may directly or indirectly result from any information contained on this website or any actions taken as a result of the content of this website;
    • We may change, delete, add to, or otherwise amend information contained on this website without notice

    For more information about the underlying concepts of Air Quality forecasting (or Atmospheric Dispersion Modeling), check the article on a visual study of wind impact of PM2.5 concentration.

    About the Air Quality and Pollution Measurement:

    About the Air Quality Levels

    AQI Air Pollution Level Health Implications Cautionary Statement (for PM2.5)
    0 - 50 Good Air quality is considered satisfactory, and air pollution poses little or no risk None
    51 -100 Moderate Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution. Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
    101-150 Unhealthy for Sensitive Groups Members of sensitive groups may experience health effects. The general public is not likely to be affected. Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
    151-200 Unhealthy Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects Active children and adults, and people with respiratory disease, such as asthma, should avoid prolonged outdoor exertion; everyone else, especially children, should limit prolonged outdoor exertion
    201-300 Very Unhealthy Health warnings of emergency conditions. The entire population is more likely to be affected. Active children and adults, and people with respiratory disease, such as asthma, should avoid all outdoor exertion; everyone else, especially children, should limit outdoor exertion.
    300+ Hazardous Health alert: everyone may experience more serious health effects Everyone should avoid all outdoor exertion

    To know more about Air Quality and Pollution, check the wikipedia Air Quality topic or the airnow guide to Air Quality and Your Health.

    For very useful health advices of Beijing Doctor Richard Saint Cyr MD, check www.myhealthbeijing.com blog.


    Usage Notice: All the Air Quality data are unvalidated at the time of publication, and due to quality assurance these data may be amended, without notice, at any time. The World Air Quality Index project has exercised all reasonable skill and care in compiling the contents of this information and under no circumstances will the World Air Quality Index project team or its agents be liable in contract, tort or otherwise for any loss, injury or damage arising directly or indirectly from the supply of this data.



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