Under Different Weather Conditions The Body Breathing Height Of PM₁₀, PM_2.5 Change Its Relationship With Meteorological Elements

In order to understand the human breathing height range of atmospheric particulate matter pollution situation in Beijing, we are on July 31, 2014- August 7 in Beijing Olympic Park View Avenue, one of the important flow distribution area established observation points, the use of E-BAM particle monitor, QUESTemp ° 36 integrated heat index monitor, ST20 infrared thermometer, for a week of real-time online monitoring, while the levels of atmospheric particulate matter and its variation with time of the study, and using correlation, regression analysis and other methods to analysis the human breathing height measured PM_2.5, PM₁₀ and temperature and humidity changes of vertical gradient, and the establishment of PM_2.5, PM₁₀ best univariate, multivariate predictive model to further investigate the case of no wind days PM_2.5, PM₁₀ levels of human exposure and diffusion process and mechanism. It concluded as follows:1. Flow distribution center Xidan Square, sunny PM_2.5 was negatively correlated with temperature, and the temperature at 0.1m correlation reached a very significant level（r=-0.442**）; and cloudy conditions, the correlation PM_2.5 and temperature are very small and did not reach significant levels. In short, under the premise of considering only the temperature factor, sunny day when the particle concentration is low and the height of each of the air temperature difference is small, diffusion capacity PM_2.5 mainly by the temperature close to the ground（ie 0.1m） control. In addition, when only consider the humidity factor, sunny PM_2.5 and 1.7 humidity maximum positive correlation（r=0.782**）, the most relevant cloudy with 1m humidity（r=0.656**）, shows that neither sunny or cloudy, PM_2.5 always top layer and relative humidity, most closely.2. Model Xidan Square PM_2.5 single factor established show, sunny, cloudy conditions, compared with the temperature, relative humidity is a major factor in controlling particulate matter concentration. The multi-factor model of PM_2.5 and created the show, regardless of sunny or cloudy days, in addition to major changes in PM_2.5 concentrations by humidity control, but also to some extent affected by humidity.3.Under sunny conditions, the basic performance of temperature from the surface up to is T0.0m> T0.1m> T1m> T1.7m, at the same time, the temperature of each layer than the ground temperature reached a peak lag time 1h. PM_2.5, PM₁₀ concentration change curve substantially "U" shaped, morning 9: 00-10: 00 when the temperature gradually increased to generate air convection, PM_2.5, PM₁₀ concentrations decreased by diffusion. Noon, 14: 00-15: 00 or so relative humidity reaches a minimum, the particle concentration is approaching correspondingly lower value. In the afternoon the air temperature began to decrease, convection weakened, PM_2.5, PM₁₀ diffusion capacity gradually suppressed and concentration. Compared with the sunny, rainy days PM（2.5,10） curve more peaks and valleys and undulating layers humidity, small temperature difference, the curve tends to coincide.4.Cloudy with sunny（or rainy） of ρ(PM_2.5) / ρ(PM₁₀) daily opposite trend. All the observed PM_2.5 and PM₁₀ daily average ratios were greater than 50%, indicating PM₁₀ mass concentration of PM_2.5 occupy most. Different atmospheric particulate matter concentration range, PM_2.5 and PM₁₀ ratio change rate is also different; one-level concentration range ρ(PM_2.5) / ρ(PM₁₀) changes in amplitude of 41.7%, 39.5% and two-level concentration range ρ(PM_2.5) / ρ(PM₁₀) changes in amplitude of 28.11%, 26.3%, three-level concentration range ρ(PM_2.5) / ρ(PM₁₀) variation margin 17.3%, 16.98%; ie the smaller the average daily mass concentration of PM_2.5 and PM₁₀, the larger the diurnal variation of the amplitude ratio between the two. PM_2.5 and PM₁₀ has a good positive correlation. Different concentrations of air quality range, the size of correlation of ρ(PM_2.5) /ρ(PM₁₀) performance: R2 three-level > R2 two-level > R2one-level, The performance of the PM_2.5 is PM₁₀ one of the important influencing factors of the content.5.EPA PM_2.5 monitoring values are basic greater than the near-surface（≤2 m） measured value. Observation period measured PM_2.5 and EPA PM_2.5 showed a significant positive correlation; one-level air pollution concentration range, its correlation coefficient was the highest（r=0.943**）, and the trend is basically the same; two-level pollution concentration range, the minimum correlation coefficient（r= 0.741**）; contamination when three-level of its relevance to 0.802**, range in size between these two types of pollution levels.6.The correlation overall performance of PM_2.5, PM₁₀ and temperature is: Sunny best, followed by cloudy, rainy day minimum. High concentrations of atmospheric particles and the air low transparency of August 2, the layers of air temperature difference is small, negative correlation between PM_2.5, PM₁₀ and the ground temperature is best; and low air density and air quality high transparency 8 May 6, the best correlation PM（2.5,10） between 1.0m and air temperature; between the two contamination of August 7, PM_2.5, PM₁₀ and temperature of the air close to the ground（0.1m） related highest. Cloudy day, when the weather conditions are relatively stable（July 31）, PM（2.5,10） and human breathing height（1.7m） of temperature is best correlation, respectively r=-0.638*, r=-0.687**; contrast with meteorological conditions（August 5）, the correlation is poor.7.Vertical temperature gradient is one of the important factors affecting the PM（2.5,10） diffusion rates. Each sunny vertical temperature gradient amplitude decreasing order of August 6 is 1.47℃⁷.52℃, August 7 is 1.53℃⁷.12℃, August 2 is 0.94℃⁵.38℃, Correspondingly, the maximum percentage of PM（2.5, 10） changes were August 6 is 1025%, 317%, August 7 is 255%, 169%, the smallest for the August 2 is 73%, 80%, that is, the temperature change in the vertical direction the more intense, the stronger the air flow, the faster the diffusion of atmospheric particles, in addition, in the same period of PM_2.5 ascending, descending rate is mostly higher than PM₁₀. Cloudy or rainy day on the vertical temperature difference is small, the air tends to be stable, PM（2.5,10） proliferation was inhibited.8.Under different weather conditions, PM（2.5,10） and relative humidity correlated differences. Sunny, high concentrations of atmospheric particulate matter（August 2）, the closer to the ground（0.1m） a large at a relative humidity, which associated with PM_2.5 and PM₁₀ is the best. Transparent better air August 6 and August 7, human breathing height（1.7m） of relative humidity is large, PM_2.5, PM₁₀ associated with it better. Thereby obtained, sunny PM_2.5, PM₁₀ are always most closely relationship with the highest level of relative humidity.9.Sunny layers of relative humidity is another important factor in affect the rate of change of PM（2.5,10） diffusion rates. Air good transparency August 6, the temperature increase（decrease） rapidly, resulting in a faster rate of change of the relative humidity, atmospheric particles due to moisture absorption effect rapidly reduced（or increased）; poor the transparency of the air（August 2）, it is the opposite; August 7 is the transition of the first and two types. In short, PM（2.5,10） concentration variation rate are corresponding to the rate of change of the relative humidity.10.Sunny PM（2.5,10） univariate regression models have reached a very significant level（P <0.01）, and an accuracy of greater than 0.75. August 6, transparent air, ground heat quickly, the temperature rose faster rate, the model of the highest precision was established by PM（2.5,10） and temperature at 1m; and poor transparency of air August 2, as well as between these two meteorological conditions in August 7, PM（2.5,10） respectively with 0.1m or 1.7m humidity to establish the model of optimal, described by its mainly controlled by humidity. PM（2.5,10） model of cloudy is less precise than the sunny and determination coefficients were less than 0.5.11.PM（2.5,10） multivariate regression model showed that under different weather conditions: sunny transparent air, temperature as the main factors affecting the diffusion of particles, and vice versa is controlled mainly by humidity; between both pollution, PM_2.5 and PM₁₀ concentration change not only controlled by relative humidity of each layer, is also affected by temperature. Cloudy PM_2.5, PM₁₀ model accuracy is unsatisfactory than sunny day, and the equation is more complicated.