Atmospheric element mercury concentration prediction method based on site monitoring data construction
A technology for monitoring data and concentration prediction, which is applied in the field of atmospheric element mercury concentration prediction based on site monitoring data. , the effect of promoting convenience
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Embodiment 1
[0033] In order to solve the problems of high cost, difficult popularization and complicated operation of existing gaseous elemental mercury detection, the present invention proposes a method for predicting atmospheric elemental mercury concentration based on site monitoring data, including steps:
[0034] S1: Obtain air quality data, water-soluble ion concentration and GEM data to establish a database, air quality data includes PM 2.5 , O 3 , PM 10 , SO 2 , CO, NO X , the water-soluble ions include the cation K + , Ca 2+ 、Na + , Mg 2+ , NH 4 + and anion SO 4 2- , NO 3 - and Cl - ;
[0035] S2: Use stepwise multiple linear regression to obtain the main influencing parameters on GEM, mainly PM 2.5 , CO, NO X ;
[0036] S3: Perform multiple linear regression according to the main influencing parameters to obtain the linear relationship between the main influencing parameters and GEM;
[0037] S4: Determine the exponential relationship between the characteristic...
Embodiment 2
[0054] In order to further understand and prove the present invention better, the present embodiment uses the form of actual data to verify, a method for predicting the concentration of atmospheric element mercury based on site monitoring data, such as Figure 4 shown.
[0055] PM for verification 2.5 , CO, NO x and Na + +Mg 2+ The accuracy of the model for predicting the change of GEM constructed by the four independent variables of the ratio of cation equivalent concentration, the data of the observation site from January to April 2018 (1334 sets of valid data) were substituted into the model to calculate the simulated GEM concentration. The average concentration of GEM measured from January to April 2018 was 2.28ng / m 3 , the average concentration predicted by the model is 2.16ng / m 3 , which turned out to be 5.1 percent lower. The time series comparison between the predicted results and the actual observed concentration is as follows: Figure 4 shown. It can be seen ...
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