Guide to publishing Air Quality data on the World Air Quality Index project

Share: aqicn.org/publishingdata/jp/

Publishing data on the World Air Quality Index project is free for every one. But it is also simple and straightforward: All you need to add data on the World Air Quality Index map is to provide a feed URL with the real-time information about the monitoring stations (name and location), the pollutants being measured and the real-time readings (together with the units, for instance milligrams or ppb).


Qualification Criteria

Note that the data published on the World Air Quality Index map is only official data provided by each country respective Environmental Protection Agency (see the full EPA list). Those official data are monitored using professional BAM and TEOM-like Air Quality monitoring stations.

Those stations are not trivial, and do require constant maintenance and calibration by the the EPA professional field-engineering teams. Therefore, except from specific conditions (e.g. if there no coverage in a country or a given region / city), the World Air Quality Index project does not accept any form of data generated from non-professional Air Quality monitors.

If your contry or city does not have official monitoring, it is acceptable to report data from more affordable instant air particule counters (eg PMS, SDS,..). While we do recommend to use the semi-professional GAIA air quality monitoring stations for this purpose, we however accept data from other stations. Nevertheless, such particule counter-based stations need to report enhanced data feed with additional quality controls (see quality control section).

Feed format

Since almost each country has its own reporting format, the World Air Quality Index project can accept many kind of formats for the feeds: They can be in CSV, JSON or just plain text or HTML format. You can find at the bottom of this page 3 example for CSV, HTML and JSON.

You can also check, for reference, the official feeds for Singapore, Peru or Netherlands and notice that they are all different.

Data ingestion

The World Air Quality Index system will take care of regularly checking the data from the feed, and each time an update is available, it will be processed, converted to the US EPA scale AQI values, and publish on the World Air Quality Index website within minutes.

Also, although only PM2.5, PM10, Ozone, NO2, SO2 and CO Air Quality data is published, the system does collect more pollutants for forecasting purpose: Benzen, Toluen, Ethylbenzen, NOx, THC, NMHC, PM1, Formaldehyde, Mercury, Ammonia, Methan, Hydrogen sulfide, Nitrous acid, Phenol, Naphthalene, paraxylene (p-Xylen), metaxylene (m-Xylen), etc..

It is also possible to publish meteorological data: Temperature, Atmospheric Pressure, Humidity, Precipitation, Wind Speed, Wind Direction, Solar Radiation and UVI. If not provided, we will use other relevant meteorologic information sources.

Feed Example (CSV format)

 #ID: ID_BEI_DC
#City: Beijing
#Station: Dongcheng
#Name: 东城东四
#Latitude: 39.929
#Longitude: 116.417
#Timezone: +0800
Date,PM10,PM25,CO,Ozone,Sulphur Dioxide,Nitrogen Dioxide,AmbientTemperature,RelativeHumidity,WindDirection,WindSpeed,Pressure,RainGauge
Unit,ug/m3,ug/m3,ppm,µg/m3,µg/m3,µg/m3,°C,%,°,m/s,hPa,mm
10/29/2016 13:00,16,3,,58,10,3,32,66,200,3,1001,0
10/29/2016 14:00,19,8,,57,9,4,32,64,197,2,1001,0
10/29/2016 15:00,15,9,,52,47,17,30,72,190,2,1001,0
10/29/2016 16:00,31,19,,52,34,17,30,75,191,2,1001,0
10/29/2016 17:00,31,17,,49,49,19,29,75,194,1,1002,0
10/29/2016 18:00,37,18,,45,55,25,29,73,183,1,1003,0
10/29/2016 19:00,24,13,,40,21,19,29,80,65,1,1004,0
10/29/2016 20:00,39,22,,44,4,16,28,85,7,1,1005,0
10/29/2016 21:00,24,16,,43,3,7,28,85,10,1,1005,0

Feed Example (HTML format)

This is an example based on an HTML format (direct url: publishingdata/html/):
Station list:
Station IDCity or County NameStation NameLocal name (optional)Latitude/LongitudeTimezone (optional)
ID_BEI_DCBeijingDongcheng东城东四39.929/116.417+0800
ID_BEI_WPBeijingWest Park西城官园39.929/116.339+0800
ID_BEI_OPBeijingOlympic Park朝阳奥体中心39.982/116.397+0800
..................
  • The "Station ID" is the unique identifer for each station, and it can just be a number (eg ID8373), or the concatenation of station city and station name (eg. "Beijing/Dongcheng").
  • By default, the station will be available via the url /city/country-name/city-name/station-name.
  • The "Station Name" must use latin characters, so the optional "Local Name" can be provided to localize the webpage.

Real-time pollutant list:
Station IDPollutantUnitUpdate timeValueAveraging
ID_BEI_DCPM10mg/m32019/06/05 17:00:0027.81 hour
ID_BEI_DCPM25mg/m32019/06/05 17:00:0010.81 hour
ID_BEI_DCOzonemg/m32019/06/05 17:00:0015.21 hour
ID_BEI_DCOzonemg/m32019/06/05 17:00:0018.28 hours
ID_BEI_DCTemperatureCelcius2019/06/05 17:00:0022.31 hour
ID_BEI_WPPM10mg/m32019/06/05 17:00:0027.81 hour
ID_BEI_WPPM25mg/m32019/06/05 17:00:0010.81 hour
ID_BEI_WPSO2ppb2019/06/05 17:00:0015.21 hour
ID_BEI_WPHumidiy%2019/06/05 17:00:00881 hour
...............
  • The "Averaging" column is use to specify the duration of the value. The most common averaging is 1 hour. It is also the prefered one, as our backend system will automatically do the 8 hour averagin computation for the Ozone and Carbon Monoxyde.
  • In the case the readings are provided more freqently than every hour (for instance every 30 minutes or 10 minutes), you can either provide the raw readings for the given period, or just the hourly averaging: Our back-end system will anyway process data even between the hour.

Feed Example (JSON format)

This is an example based on JSON format (direct url: /publishingdata/json/)
..

Quality Control for particule counter sensors

For instant particule counters, such as the Plantower PMS or Nova SDS, which provide instantaneous (in few seconds) particulate matter readings, the data is usually reported every minute. This data is usually computed based on several "averaged" readings from a one or two minute period.

The use of averaging is however not good enough, especially for failing sensors (or sensor close of end-of-life). Therefore, for such sensors, it is required to provide additonal metrics, such as the median, min, max, and standard-deviation. See for example the readings object in the below JSON data feed.
..
You can use the following arduino-compatible code to collect those metrics:
class Accumulator 
{ 
    #define OUTPUT_BUFFER_SIZE 120 
    char buffer[OUTPUT_BUFFER_SIZE]; 
 
    #define MAXACCVALUES 120 
    int vals[MAXACCVALUES]; 
 
    int count = 0; 
 
public: 
    Accumulator() 
    { 
        reset(); 
    } 
 
    void reset() 
    { 
        count = 0; 
        for (int i=0;i< MAXACCVALUES;i++)  
        { 
            vals[i]=0; 
        } 
    } 
 
    bool hasData()  
    { 
        return count!=0; 
    } 
 
    std::string output()  
    { 
        if (!hasData()) return std::string("{}"); 
 
        sprintf(buffer, OUTPUT_BUFFER_SIZE, "{\"min\":%d,\"max\":%d,\"median\":%d,\"average\":%.1f,\"stddev\":%.1f,\"count\":%d}",  
            vmin(), vmax(), median(), average(), stddev(), count); 
 
        return std::string(buffer); 
 
    } 
 
    void add(int val) 
    { 
        if (count==MAXACCVALUES-1) { 
          for (int i = 0; i < MAXACCVALUES - 1; i++) { 
            vals[i] = vals[i + 1]; 
            } 
            count --; 
        } 
        vals[count++]=val; 
    } 
 
    float stddev()  
    { 
        if (!hasData()) return -1; 
        int u  =avg(); 
        int t = 0; 
        for (int i=0;ivals[j]) { 
                    float t = vals[j]; 
                    vals[j]=vals[i]; 
                    vals[i]=t; 
                } 
  
            } 
        } 
        return vals[count/2]; 
    } 
 
    float avg()  
    { 
        if (!hasData()) return -1; 
        float t = 0; 
        for (int i=0;ivals[i]) { 
                t=vals[i]; 
            } 
        } 
        return t; 
    } 
 
    float vmax()  
    { 
        if (!hasData()) return -1; 
        float t = vals[0]; 
        for (int i=0;it) { 
                t=vals[i]; 
            } 
        } 
        return t; 
    } 
};

Inquiry Form

Data Feed Inquiry form
Enter your name - eg "John Doe"
Enter your email address - eg "john.doe@mail.com"
Enter your country or city - eg Tbilisi, Georgia
Enter your data-feed URL - eg "https://airnow.gov/"
Write few words about your request - eg: "A feed for Tbilisi, Georgia is available at ..", "The feed for Sofia, Bulgaria has been updated", "I need help to setup the feed for Dakar, Senegal", "The location of the station Patumahoe in Auckland is incorrect. It's lat,lon is -37.204,174.864", ..


大気汚染指数の測定方法:

大気汚染レベルについて

指数 大気質指数の分類(米国) 健康影響 / カテゴリ 粒子状物質(PM10,PM2.5)
0 - 50 良い - Good 通常の活動が可能 なし
51 -100 並 - Moderate 特に敏感な者は、長時間又は激しい屋外活動の減少を検討 非常に敏感な人は、長時間または激しい活動を減らすよう検討する必要がある。
101-150 敏感なグループにとっては健康に良くない - Unhealthy for Sensitive Groups 心臓・肺疾患患者、高齢者及び子供は、長時間又は激しい屋外活動を減少 心疾患や肺疾患を持つ人、高齢者、子供は、長時間または激しい活動を減らす必要がある。
151-200 健康に良くない - Unhealthy 上記の者は、長時間又は激しい屋外活動を中止
すべての者は、長時間又は激しい屋外活動を減少
心疾患や肺疾患を持つ人、高齢者、子供は、長時間または激しい活動を中止する必要がある。それ以外の人でも、長時間または激しい活動を減らす必要がある。
201-300 極めて健康に良くない - Very Unhealthy 上記の者は、すべての屋外活動を中止
すべての者は、長時間又は激しい屋外活動を中止
心疾患や肺疾患を持つ人、高齢者、子供は、全ての屋外活動を中止する必要がある。それ以外の人でも、長時間または激しい活動を中止する必要がある。
300+ 危険 - Hazardous 上記の者は、屋内に留まり、体力消耗を避ける
すべての者は、屋外活動を中止
全ての人が屋外活動を中止する必要がある。特に、心疾患や肺疾患を持つ人、高齢者、子供は、屋内に留まって激しい活動を避け静かに過ごす必要がある。
(Reference: see wikipedia, and cn.emb-japan.go.jp/)

大気汚染についての更なる詳細をお知りになりたい方は、WikipediaAirNowを参照してください。

北京在住の医師Richard Saint Cyr氏による大変役に立つ健康上のアドバイスは、 www.myhealthbeijing.com をご覧ください。


使用上の注意: すべての大気質データは公開時点では妥当性が担保されていないため、これらのデータは予告なしに修正することがあります。 世界大気質指数プロジェクトは、この情報の内容を編集に最善の注意を尽くしておりますが、いかなる状況においても World Air Quality Index プロジェクトチームまたはそのエージェントは、このデータの供給によって直接的または間接的に生じる損失や損害について責任を負いません。



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Temperature unit:
Celcius