Saturday, April 12, 2014

Last Chinese Air Quality Index (AQI) showing persistent Air pollution during Jan & Feb 2014 with high level of Particulate Matter pollution in Northern regions

Shijiazhuang is struggling to contain a dense smog because of its heavy reliance on coal; both Xingtai and Shijiazhuang cities- located in Hebei 300 km South of Beijing- had the worst AQI throughout China during Jan & Feb 2014. From CCTV reporter Ning Hong - 16 Oct 2013

In the first two months of 2014, the 190 most important Chinese cities sample were recorded with an Air Quality Index (AQI) value around 130. Most affected areas were the industrial North region including Harbin, Beijing and Tianjin.

Particulate Matters (PM2.5 and PM10) were almost always the principal pollutants determining the value of Air Quality Index, PM2.5 with 68% of the city-month records being mostly concerned with PM10 only 29%. As a consequence, the PM2.5 inclusion in the new AQI definition has dramatically changed the Air quality perception.  

During Jan. & Feb. 2014, on a 59 days' period: the 76 most polluted cities (40% of 190 sample) had largely exceeded the yearly budget of "exceedance" days (with AQI>50 or PM2.5> 35μg/m3) normally permitted in the WHO, the US or the UE for instance.

This means that based on the first two months and for 40% of major urban areas China is more or less six times more polluted as compared with Western standards! 

The new Air Quality Index publications, concerning China’s major urban areas, are being speeding up gradually by the Ministry of Environmental Protection (MEP).

However every month already published AQIs ​​are modified retrospectively due to errors found after publication.

But we believe that many errors are still present: from a test performed by computing the highest values ​​of all pollutant sub-indices, we found that at least 181 cities indications already published - or 16% of all published city-month records- should still be corrected, including: Harbin (Oct & Dec), Xi’an (Dec & Jan) and Beijing (Feb).

What are the main information resulting from last AQI data released on the most important Chinese cities?

After 76 cities recorded from May 2013, then 144 cities from Sep 2013, we have now 190 cities- all among the largest urban areas- recorded from Jan 2014 with the new Air Quality Index (AQI) format that incorporates the finest Particulate Matter (PM2.5).

As explained in our previous blog dated 12 Nov 2013, we may establish average per capita pollution over specific region or on an overall national basis only after urban population weighting the results of each city inside the concerned area.

In the first two months Jan. & Feb. 2014, the population weighted average AQI value is 129 for an overall urban population of 408 Mil of the 190 concerned cities.

The most affected areas were the industrial North regions including Harbin, Beijing and Tianjin. The list of the top 76 most polluted cities is given in the following Figures 1 (a) and 1 (b):

Figure 1 (a)38 most polluted cities or first quintile (1/5 of  the 190 cities) from mean Jan & Feb 2014

Figure 1 (b): 39th to 76th most polluted cities or second  quintile from mean Jan & Feb 2014

The first 40% - or 2 fifths (quintile) - of the ranked 190 Chinese cities are located mostly in the Northern (60%) or in the Middle (37%) regions.

These cities were classified with an Air Quality Index- following US denominations- either "Very polluted" (11 cities including Xi'an), or "Unhealthy" (40 cities including Beijing and Harbin), or "Unhealthy for sensitive groups" (25 cities including Chongqing).

Xi'an (ranking n°11), Harbin (n°40), Beijing (n°45), Chongqing (n°53), Tianjin (n°56) and Nanjing (n°64) are among the greatest Chinese cities but are also those which air is the most heavily polluted by Particulate Matter. 

The G06 Northern region (Beijing, Tianjin, Hebei Provinces & Dalian City) plus being the People's Republic of China capital location were certainly the most polluted during the period.

With 10 cities ranking respectively n°1 (Xingtai), n°2 (Shijiazhuang), n°3 (Baoding), n°5 (Handan), n°7 (Hengshui), n°16 (Langfang), n°25 (Tangshan), n°37 (Cangzhou), n°45 (Beijing) &  n°56 (Tianjin) and a population totaling 48 Mil: the population-weighted AQI value is around 162  with only  4.8 "good days" over the 59 days period. 

Most of the pollution is coming from the surrounding Hebei Province which burned over 300 million tons of coal in 2011, more than all of Germany!

The number of "good " days - where AQI <50 or PM2.5 <35μg/m3- during Jan. & Feb. 2014 where nil for Xi'an, Harbin and Tianjin, 3 for Chongking and Nanjing and -quite unexpectedly- 10 for Beijing with 5 in Jan. and again 5 in Feb.. 
As a result, after over the first two months of the year all these cities have largely exceeded the yearly budget of "exceedance" days such as defined for instance in the UE . This means that based on these first two months China is more of less six times more polluted following normal western standards.

Figure 2 : Most polluted 78 Chinese Cities from mean Jan & Feb 2014

 What are the most important pollutants concerned?

For a specific day the AQI value is the value reached by the highest underlying sub-index of each of the 7 main different pollutants recorded: PM2.5, PM10, CO, NO2, SO2 , O3-1h & O3-8h.

Since the publication of the new monthly AQI values, we have 1102 city-month records of monthly average AQI and associated pollutants over a period of 10 months from May 2013 to Feb 2014.

It is possible to compute monthly sub index values from each monthly recorded pollutant average concentration. In the vast majority of city-month records, PM2.5 or PM10 were almost always the most important pollutants as defined by the value of the various sub-index (see Figures 3 (a) & 3 (b)).

Under this approach we found that PM2.5 was the most important pollutant for 750 city-month records (68%), then PM10 for 325 (29%), NO2 for 17 (1.5%) and O3-8h then SO2 respectively for 6 (0.5%) & 3 (0.25%) city-month records only.

Figure 3 (a) : Beijing, Canton and Chongqing 10 month records from May 2013 to Feb 2014 

Figure 3 (b) : Beijing, Canton and Chongqing 10 month sub indexes as derived from May 2013 to Feb 2014 detailed AQI and associated pollutant records

As explained above, each new AQI monthly issue from China’s MEP might is bringing corrections to several of the preceding issued city-month records.

And nevertheless lots of mistakes are still uncorrected! We found that for 181 city-month records, the value of the month was less than the value of the sub highest index computed from the monthly average of the corresponding pollution (See Harbin in Oct. and Dec., in Beijing in Feb in following Figure 4).

These are certainly errors since the highest sub index including the daily volatility during the specific month is certainly higher than the sub index without volatility!  

181 errors on 1102 values is a level of mistakes around 16% with lots of errors still concerning Oct., Nov. and Dec..

Figure 4 : 40 among 181 errors found in the last AQI issues where the sub index is higher than the recorded AQI

These values ​​are average monthly which might hide severe daily pollution

As we have not for each city the detailed daily value of each of 7 main pollutants we can only assess the most severe daily pollution from the monthly average issued each month.    

Figure 5: Existing correlation between monthly  AQI or PM2.5 sub-index and PM2.5 monthly average PM2.5 for all 1102 city-month records; a large number of PM2.5 sub-index higher than that recorded AQI necessarily corresponds to an error

Figure 6: Correlation between overall AQI and calculated monthly Sub Index PM10 for all monthly-cities 1102 records

But in each of the 1102 city-month records we have the number of days during the month period where AQI was "good" (AQI<50) which permits an estimation of the size of population exposed over long periods to unhealthy air quality.

Figure 7: Number of days where AQIcity is "good" or <50

The Figure 7 above is showing that "good air quality" had only 22-29 "good" days during each last month; when "moderate air quality" had only 5-10 "good days"; and "unhealthy air quality" only 1-5 "good days"!   

These performances are more than extremely 
exceeding the health limitations put forward by WHO, EU or US regulations which are -in the EU-  90.4 percentiles with PM10 < 50μg/m3  or less than 35 exceedance days (9.6%) over one year and - in the US- 98 percentiles  for PM2.5 < 35 μg/m3 or less than 7 exceedance days (2%) over one year (see my last blog dated 22 Sep 2013)

During Jan & Feb 2014 the population-weighted "good days" (AQI<50 
or PM2.5<35μg/m3) were around 5.5 days for all the 190 cities. 

This mean as exposed above that on the overall 190 cities during Jan. to Feb. 2014 there were 53 (=59-5.5) unhealthy days (with AQI>50 or PM2.5>35
μg/m3)  or 1.5 times the 35 days exceedance yearly period accepted by WHO, the US or the UE!

Finally is it possible to know whether air pollution is on an upward or downward trend during the last years?

As we did in our last post dated  10 Nov. 2013, we may use the benchmark of air pollution introduced by W. J. Qu et al. in their 2010 study "Spatial distribution and inter-annual variation of PM10 concentrations over 86 Chinese cities" as established  from Jun. 2000 to Feb. 2007 daily API data available.

As during that period the finest particulate matter were not recorded, we might only compare PM10 pollution using this 86 cities bench mark which are the biggest cities inside the 190 cities recorded by MEP.

On the overall 86 cities the total population weighted PM10 is +2.17% higher than the 2000-2007 bench-mark (see Figure 8 and 9 below):

Figure 8: Monotonous curve comparison with the bench-mark

Figure 9 : Comparison for 2000-2007 86 cities benchmark ; in blue the 2000-2007 population weighted 10 months PM10 value ; in red the last 10 month values from same 86 cities recorded completed progressively with small missing cities deducted from previous seasonal factors; for each cluster the number of cities and the overall population are given

On the 16 city’s clusters (see Figure 9 & 10):

There are reduction for Northern G01 (-21.76%); Northern G03 (-23.35%); Northern G05 (-17.87%); Southern G12 (-13%) & West GX1 (-10.14%). 

But also we note a huge increase for Northern G07 (37%); Northern G08 (34%); Southern G13 (30%); Northern G02 (11%) & Middle G11   (8.8%).      

Figure 10 : The 16 clusters of correlated cities used as a bench-mark