#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
 

This is an example based on an HTML format (direct url: publishingdata/html/):

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

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; 
    } 
};

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", ..

대기질 지수 단계에 대하여

AQI	지수구분	구간의미
0 - 50	좋음	대기오염 관련 질환자군에서도 영향이 유발되지 않을 수준
51 -100	보통	환자군에게 만성 노출시 경미한 영향이 유발될 수 있는 수준
101-150	민감군영향	환자군 및 민감군에게 유해한 영향이 유발될 수 있는 수준
151-200	나쁨	환자군 및 민감군(어린이, 노약자 등)에게 유해한 영향 유발, 일반인도 건강상 불쾌감을 경험할 수 있는 수준
201-300	매우나쁨	환자군 및 민감군에게 급성 노출시 심각한 영향 유발, 일반인도 약한 영향이 유발될 수 있는 수준
300+	위험	환자군 및 민감군에게 응급 조치가 발생되거나, 일반인에게 유해한 영향이 유발될 수 있는 수준

(Reference: see airkorea.or.kr)

대기질과 오염에 대해 더 많은 것을 알아보려면 위키피디아의 대기질 문서(영어)을 보거나 대기질과 건강에 대한 AirNow 가이드(영어)를 참조해보세요.

매우 유용한 베이징의 의학박사 Richard Saint Cyr MD의 건강 관련 팁을 보려면 www.myhealthbeijing.com 의 블로그를 확인하세요.