ISSN 10248560, Atmospheric and Oceanic Optics, 2014, Vol. 27, No. 6, pp. 587–595. © Pleiades Publishing, Ltd., 2014. Original Russian Text © S.A. Lisenko, M.M. Kugeiko, 2014, published in Optika Atmosfery i Okeana.
OPTICAL INSTRUMENTATION
Nephelometric Method for Measuring Mass Concentrations of Urban Aerosols and their Respirable Fractions S. A. Lisenko and M. M. Kugeiko Belorussian State University, pr. Nezavisimosti 4, Minsk, 220030 Belarus email:
[email protected] Received September 27, 2013
Abstract—A method is suggested for determining the mass concentration of airborne particles with sizes ≤1, ≤2.5, ≤10, and >10 μm by measuring the light scattering coefficients of the investigated air at the wavelengths λ1 ≤ 0.55 and λ2 ≥ 1.0 μm for the scattering angles θ1 ≤ 5° and θ2 = 15–45°. Mass concentrations of airborne particles are calculated on the basis of their stable statistical relationships with measured coefficients. Analyt ical expressions for approximation of these statistical relationships have been derived on the basis of an opti calmicrophysical model of urban aerosol, adopted by the World Meteorological Organization, with variable concentrations, size distribution parameters, and complex refractive index of the particles of aerosol compo nents (soot, watersoluble, and dust). Statistical relationships derived in the modeling approach have been compared with independent numerical and experimental data. The errors of the method developed have been assessed under the overall variability of urban aerosol microphysical parameters. Keywords: urban aerosol, mass concentration, nephelometric method, multiple regressions DOI: 10.1134/S102485601406013X
Ecological problems are urgent for all large cities and industrial regions with high traffic. Numerous epi demiological studies unambiguously point to a rela tion between air pollution and the level of cardiovascu lar and respiratory disease of the population. Airborne aerosol particles are extremely dangerous for human health, first of all, fine (respirable) particles capable of penetrating deep into the respiratory organs and accu mulating in lungs (affecting influx of dangerous mate rials into the blood). According to American and European standards of the quality of atmospheric air, the level of air pollution with respirable particles is characterized by the mass concentrations PMX of particles with the aerodynamic diameter x ≤ X, where X = 1.0, 2.5, and 10 μm.
The principle of operation of measuring instru ments of the first type consists in sending laser radia tion with the wavelength λ into a measuring chamber and recording the scattered light by a photoreceiver arranged at an angle θ to the radiation source. These measuring instruments include industrially produced AEROKONP (λ = 0.67 μm, θ = 45°), AEROKON C (λ = 0.67 μm, θ = 20°), KANOMAX3431 (λ = 0.78 μm, θ = 70°), TMdata (λ = 0.88 μm, θ = 70°), and some others. Wavelengths and angles used in the known instruments determine the maximal sensitivity of measurement results to the mass concentration of fine aerosol [1–3]. This imposes fundamental restric tions on the use of these instruments for measure ments of small and large aerosol particles (PM1, PM10, and PM>10), since the contribution of the PM2.5 frac tion prevails in the measuring signal.
Common methods for controlling atmospheric air pollution by airborne particles include particle deposi tion to fiber filters and analysis of the deposit. Their advantage is that they allow direct measurements of the mass concentration of aerosol. Among disadvantages are the long time and laboriousness of the measure ments and the need for highly qualified staff. Optical measuring instruments are the most suitable for con tinuous and automated monitoring of air pollution by aerosols. The instruments can be divided into two types. The first one is based on the use of data on light scattering by the whole air volume, and the second one, on the analysis of light scattered by a single particle.
To measure small dust concentrations in the atmo spheric air and in clear room air, optical measuring instruments of the second type are widely used (particle counters), where individual particles are passed through a focused laser beam and the light scattered by each par ticle is recorded. The light pulse intensity allows estima tion of a certain equivalent particle size, and the num ber of light pulses determines the number of aerosol particles. This principle is incorporated in commer cially available instruments AERO TRAK 9303, KANOMAX3887, Fluke 983, and AZ10. Disadvan tages of these instruments are high cost (mainly due to an inbuilt vacuum pump and a complicated optical
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scheme), effects of the shape and refractive index of particles on the measurement results, and unaccept able low counting efficiency of particles smaller than 0.3 µm (due to a high probability of several particles falling in an illuminated volume). There are also instruments that use optical measurements of these two types, e.g., GRIMM (model 180, EDM 107/165, and EDM365) and DUSTTRAK DRX. These devices allow measurements of air pollution with reference to different particle fractions (PM1, PM2.5, and PM10); however, they are too expensive to serve as a basis for urban automated air monitoring network. Thus, disadvantages of existing analyzers of aerosol air pollution necessitate the development of new, sim ple and reliable methods, which allow measurements of the aerosol mass concentration in a wide range of its physical and chemical properties with fractionation of PM1, PM2.5, PM10, and PM>10. TECHNIQUE FOR CALCULATING PMX It is well known that contributions of particles of different sizes to the overall intensity of light scattered by them differ depending on the scattering angle θ. Large particles determine scattering at small angles (θ ≤ 5°), while small particles mainly contribute into the lateral scattering (θ = 15–45°). Therefore, by recording light scattered at different angles, the aero sol particle size distribution can be analyzed. In addi tion, the precision of the analysis can be increased due to an optimal choice of light wavelengths, since the efficiency of light scattering is the highest by particles with sizes close to the wavelength of the incident radi ation. In view of this, we suggest the following scheme for measuring concentrations of aerosol fractions. The measuring volume is irradiated sequentially at the wave lengths λ1 ≤ 0.55 μm and λ2 ≥ 1.0 μm, which are highly informative of the fine and coarse aerosol fractions, respectively. The light scattered is captured by photoele ments mounted at angles θ1 ≤ 5° and 15° ≤ θ2 ≤ 45° to an incident beam. The coefficients of aerosol light scat tering β(λi, θj) (i = 1, 2 and j = 1, 2) are calculated according to the signals detected. The mass concentra tions PM1, PM2.5, PM10, and PM>10 are calculated by means of solution of the inverse problem of interpreta tion of the coefficients β(λi, θj). Considering a small volume of measurement data, the regression method is preferable for solution of the inverse problem [4, 5]; it allows calculation of desir able microphysical aerosol parameters on the basis of their multiple regression with optical aerosol parame ters measured experimentally. In our case, β(λi, θj) contains both spectral and spatial data and does not allow a simple onedimensional interpretation. Therefore, a more uniform data structure is required for convenience of their analysis. Values of lnβ(λi, θj) can be considered as components of the measurement
vector b. Let us expand b in eigenvectors vn (n = 1, …, 4) of its covariance matrix that form an orthogonal basis. The expansion coefficients ξn (linearly independent components) of any random realization of b are found from equation [6]:
ξ n = v n(b − b),
(1)
where b is the mean measurement vector with the components ln β(λ i , θ j ). To find the mass concentra tions PM1, PM2.5, PM10, and PM>10, the polynomial regression 4
ln PM X = a00, X +
K
∑∑a
nk, X (ξ n )
k
(2)
n =1 k =1
can be used, where K is the polynomial power; a00,X and a nk, X are the regression coefficients found on the basis of a “training” ensemble of random realizations of PMX and β(λi, θj). OPTICALMICROPHYSICAL MODEL OF URBAN AEROSOL A set of training data required for finding vectors vn and b and regression coefficients in Eq. (2) has been formed on the basis of the urban (or industrial) aerosol model adopted by the World Meteorological Organi zation (WMO) [7]. In this model, aerosol particles are considered as spherical and of a homogeneous internal structure. This, on the one hand, is connected with known difficulties in the solution of problems of elec tromagnetic radiation diffraction on inhomogeneous and nonspherical particles and a restricted region of applicability of solutions found. On the other hand, as shown below, to calculate the concentrations of the aerosol fractions under study, one can limit oneself to measurements of scattered light intensity in the angle range θ ≤ 20°, where the aerosol light scattering phase function weakly depends on the structure and shape of scattering particles [8, 9]. According to the WMO model [7], urban aerosol consists of three components: soot (1), water soluble (2), and dust (3). Each component corresponds to a particle size distribution function
⎡ ln 2(x x f )⎤ dV f = A f exp ⎢− ⎥, 2 d ln x ⎣ 2 ln σ f ⎦
(3)
where subscript f corresponds to different aerosol components, x is the particle diameter, dV f is the frac tion of particle volume of the fth component in the size range [ln x, ln x + d ln x], xf and σf are the median size
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Table 1. Ranges of variations in microphysical parameters of urban aerosol and boundaries of the spectrum of particle sizes of aerosol fractions f
xf, μm
σf
μf
x f , min , μm
1
0.042–0.066
1.8
1
0.002
0.4
2
0.48–0.84
1.61–2.09
μ1 (1–10)
0.020
5.0
3
12–36
2.5–3.7
μ2 (0.1–200)
0.020
and halfwidth parameter for each mode, Af is the nor malization constant chosen from the condition x f ,max
γa
dV f Mμ d ln x = 3 f , d ln x x f ,min μf
∫
∑ f =1
M is the total mass concentration of all the aerosol components, μf is the relative mass concentration of particles of the fth component, [x f ,min, x f ,max ] is the size range of particles of the fth component, and γa is the mean density of aerosol matter equal 1.0 g/cm3 in the calculations. Ranges of variations in the parameters μf, xf, and σf are given in Table 1 according to the results of work [10]. The parameters xf and σf of all the aerosol compo nents varied independently of each other. The concen tration μf varied in the following sequence: μ1 = 1, μ2 = μ1(1–10), lnμ3 = ln(0.1μ2) – ln(200μ2). The range 1–800 μg/cm3 is used for the aerosol mass con centration M, which corresponds to a wide range of air pollution (from the background level to extremely dusty). We should note that the range of variations in M is not important, since this parameter linearly enters in all calculation equations. Spectra of complex refractive indices (CRI) for the components of urban aerosol are considered constant in the WMO model. However, there are several differ ent spectral dependencies of CRI for soot and dust particles in the literature [7, 11–16]. The CRI spec trum of soluble particles can change with air moisture. In view of this, CRI spectra of soot and dust particles (f = 1 and 3, respectively) have been modeled as linear combinations
m f (λ) =
∑ p m* (λ) ∑ p , i
i
i, f
i
i
where mi*, f is the CRI of the particle material from [7, 11–16], pi is the weight coefficient varying in the range 0–1. The CRI of water soluble particles m2(λ) has been calculated as wmw(λ) + mws(λ)(1 – w) (mws is the CRI of water soluble particles corresponding to the ATMOSPHERIC AND OCEANIC OPTICS
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x f , max , μm
30
WMO model and mw is the water CRI [17]) account ing for the volume fraction of water (w = 0–1) in their composition. The polydisperse coefficient of aerosol light scat tering is calculated by the known Mie equations [18] under the specified m f (λ) spectra and parameters of distribution function (3). The mass concentration PMX of the aerosol fractions are calculated via integra tion of function (3), accounting for restrictions on the upper particle size: 3
PM X =
X
∑ ∫
f =1 x f ,min
dV f d ln x. d ln x
OPTICALMICROPHYSICAL CORRELATIONS An ensemble of 103 random realizations of PMX and β(λ, θ), where θ = 1–180° and λ = 0.355, 0.532, 1.064, 1.25, 1.56, 1.67, and 2.14 μm has been formed on the basis of the model described above. This set of wavelengths is caused by a need in nephelometric measurements of aerosol in the atmospheric transpar ency windows that correspond to the minimum absorption of light by atmospheric gases [4]. In addi tion, the values λ = 0.355, 0.532, and 1.064 μm corre spond to commercially available and highly effective laser radiation sources. Let us consider correlations between PMX and β(λ, θ) to optimize measurements of aerosol light scattering. The analysis of the spectralangular dependence of the coefficient of pair correlation ρ1(λ, θ) between the mass concentration of fine particles PM1 and β(λ, θ) shown in Fig. 1a shows that ρ1(λ, θ) increases as λ decreases, and the angle θ that corresponds to the ρ1(λ, θ) maximum is 15° at λ = 0.355 μm, 20° at λ = 0.532 μm, and 40° at λ = 1.064 μm. The analogous correlation coefficient ρ >10(λ, θ) for coarse particles (PM>10), in contrast, rapidly decreases with λ (Fig. 1b), and the values of θ that cor respond to the strongest correlation between PM>10 and β(λ, θ) are localized in a progressively narrower
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ρ1(λ, θ) 1.00
with an increase in δ. One should also take into account that scattering angles less than 5° are of no practical interest because of the technical difficulty of measure ments of scattered radiation and in view of a significant effect of diffraction on optical elements of a radiator. However, as follows from Fig. 1b, it is possible to increase the accuracy of the PM> 10 calculation from measurements of aerosol light scattering in a region of practically acceptable angles by means of an increase in the wavelength of the sounding radiation. Thus, increasing λ from 1.064 to 2.14 μm the correlation coef ficients between PM>10 and β(λ, 5°) increase from 0.80 to 0.97.
(a)
1
0.98
2 0.96 0.94
3
0.92 0.90 0
20
40
Thus, to calculate concentrations of fine and coarse aerosols simultaneously, the aerosol light scat tering should be measured at angles θ1 = 5° and θ2 = 15° at wavelengths λ1 = 0.355 and λ2 = 2.14 μm, since the coefficients β(λ1, θ2) and β(λ2, θ1) are almost unambiguously connected with the concentrations PM1 and PM> 10. At the same time, the coefficients β(λ1, θ1) and β(λ2, θ2) tightly correlate with the mass concentrations of other aerosol fractions, i.e., with PM1–2.5 = PM2.5 – PM1 and PM2.5–10 = PM10 – PM2.5. The calculation results of the correlation coefficients ρ1–2.5(λ, θ) and ρ2.5–10(λ, θ) that answer these frac tions show that ρ1–2.5 and ρ2.5–10 maxima approxi mately correspond to the above values of λi and θj. In this case, it is evident that joint processing of all the four coefficients β(λi, θj) by Eqs. (1) and (2) allows an increase in the accuracy of concentration of each frac tion as compared to the pair correlations. The vectors vn and b and regression coefficients in Eq. (2) that answer the optimal scheme of PMX nephelometric measuring instrument are given in Tables 2 and 3 (in [μg/m3] and [km–1 sr–1] for PMX and β, respectively).
θ, deg
60 (b)
ρ>10(λ, θ) 1.0
3 0.8 2
0.6
0.4
1
0.2 0
5
10
15
θ, deg
Fig. 1. Coefficients of correlation between the aerosol directional scattering coefficient and mass concentrations (a) PM1 and (b) PM>10 as functions of the scattering angle: (a) λ = 0.355 (1), 0.532 (2), and 1.064 μm (3); (b) λ = 1.064 (1), 1.56 (2), and 2.14 μm (3).
The PMX errors in the method suggested have been estimated on the basis of a test ensemble of PMX and β(λi, θj) realizations formed by superposition of random deviations on the coefficients β(λi, θj) from the training ensemble within δβ limits. PMX has been retrieved by Eqs. (1) and (2) for each β(λi, θj) realization from the test ensemble. The retrieved mass concentrations PM*X have been compared with their exact values corre sponding to the inverse coefficients β(λi, θj). After a search of all realizations, the absolute (ΔPMX) and rel
angle range near θ = 0°. This qualitative behavior of the coefficients ρ1(λ, θ) and ρ> 10(λ, θ) is quite predict able and is explained by the dependence of β(λ, θ) on the parameter δ = πx/λ and an increase in the forward elongation of the scattering phase function of particles
Table 2. Mean values and eigenvectors of the covariance matrix lnβ(λ, θ) λ, μm
θ, deg
ln β(λ, θ)
v1
v2
v3
v4
0.355
5 15
–2.3420 –3.5399
0.5145 0.4840
–0.3677 –0.6111
–0.4636 0.4742
0.6206 –0.4091
2.14
5 15
–3.5678 –4.9681
0.4887 0.5120
0.5801 0.3936
0.5501 –0.5075
0.3494 –0.5704
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Table 3. Coefficients ank, X of regression equation (2) X, μm
n, k 1.0
2.5
10
>10
0, 0
1.4155
1.9910
2.6219
2.2536
1, 1
0.4790
0.5133
0.5051
0.4657
1, 2
0.0000
–0.0002
–0.0002
0.0005
1, 3
–0.0002
–0.0001
–0.0001
0.0000
2, 1
–0.6672
–0.5072
0.0089
0.6720
2, 2
–0.0099
–0.0366
0.0988
0.0141
2, 3
–0.0033
–0.0062
0.0007
0.0024
3, 1
0.6164
–0.3890
–0.0825
1.6109
3, 2
–0.0125
0.2876
0.0981
–0.2215
3, 3
0.4131
0.0348
0.0729
–0.0783
4, 1
–1.2784
0.1001
–0.1774
1.4384
4, 2
–1.0618
–0.2407
–0.2002
–2.0067
4, 3
3.8264
2.9235
2.1516
8.4568
ative (δPMX) errors of PMX retrieval were calculated, as well as the correlation coefficient between the spec ified and retrieved values PMX(ρ*X ). The PM*X calcu lated by Eqs. (1) and (2) at δβ = 10% are shown in Fig. 2 versus the corresponding known PMX values. These results show the accuracy of PMX calculation by the method suggested under conditions of overall variabil ity of the microphysical parameter of urban aerosol. Quantitative assessments of the accuracy of PMX retrieval at δβ = 0 and 10% are given in Table 4. It is seen that data found from optical measurements are of a high information content relative to all ecologically valuable aerosol fractions, and the solution of the inverse problem by Eqs. (1) and (2) is stable to optical measurement errors. We should note that the scheme suggested of a PMX nephelometric measuring instrument have two significant disadvantages that concern optical sound ing wavelengths used in it. First, the molecular scatter ing will noticeably contribute to an optical signal detected at λ1 = 0.355 μm in a weakly turbulized atmosphere. This circumstance is not difficult to con sider; however, this requires the use of additional a pri ori data on the air temperature and pressure at the measurement site. Second, there are no effective semiconductor and laser sources of radiation with λ2 = 2.14 μm at present. Many scientific works devoted to the design of IR radiation laser sources with practically suitable parameters allows one to hope for the appear ance of industrially produced sources. However, to use the method suggested for PMX calculation just now, the possibility of its implementations on the basis of ATMOSPHERIC AND OCEANIC OPTICS
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currently available elemental basis should be consid ered. Let us also take into account that the molecular scattering effect on detectable signals can be signifi cantly weakened by a shift of λ1 toward longer wave lengths (according to the Rayleigh law, the molecular scattering coefficient decreases as λ–4 with an increase in λ). Let us consider a scheme of nephelometric mea surements where the air volume under study is irradi ated at λ1 = 0.532 and λ2 = 1.064 μm, and the radia tion scattered is recorded at the angles θ1 = 5° and θ2 = 20° to the sounding beam. The angle θ2 = 20° Table 4. Assessments of the PMX accuracy, corresponding to the scheme of nephelometric measurements with λ1 = 0.355 μm and λ2 = 2.14 μm and θ1 = 5° and θ2 = 15° with errors of β(λi, θj) measurements equal to δβ
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X, μm 1.0
2.5
10
>10
2014
δβ, %
ρ*X
ΔPMX, μg/m3 δPMX, %
0
0.9883
4.13
10.8
10
0.9823
4.98
13.3
0
0.9919
4.34
7.9
10
0.9914
4.66
9.2
0
0.9947
4.58
5.3
10
0.9940
5.13
6.1
0
0.9965
2.96
7.6
10
0.9835
6.59
14.7
592
LISENKO, KUGEIKO PM*1 , µg/m3
(a)
PM*2.5 , µg/m3
103
103
101
101
10–1
10–1
10–1 PM*1 0, µg/m3
101
103 PM1, µg/m3
10–1 PM*>10, µg/m3
(c)
103
103
101
101
10–1
10–1
10–1
101
103 PM10, µg/m3
(b)
10–1
101
103 PM2.5, µg/m3
(d)
101
103 PM>10, µg/m3
Fig. 2. Results of closed numerical experiments on retrieval of mass concentrations of particles with sizes (a) ≤ 1, (b) ≤ 2.5, (c) ≤ 10, and (d) > 10 μm from coefficients β(λi, θj) under superposition of random distortions in the 10% limit.
corresponds to the maximal correlation between PM1 and β(λ, θ) at λ = 0.532 μm (Fig. 1a). Proceeding from a similar correlation for PM>10, the angle θ1 should be decreased as compared to the case consid ered above; however, as has been already noted, this is connected with several technical difficulties. Assess ments of the accuracy of PMX calculation with the use of the measurement scheme considered found on the basis of closed numerical experiments on PMX retrieval from β(λi, θj) are given in Table 5. It is seen that the results of PM1, PM2.5, and PM10 retrieval almost coincide with similar results for the optimal scheme of nephelometric measurements. At the same time, the accuracy of PM>10 retrieval for optimal measurements is significantly higher. How
ever, a standard for atmospheric air for PM>10 (and for PM1) has not been introduced yet in any country due to the lack of reliable data on the effect of these aerosol fractions on the air quality and conditions of life for the people. COMPARISON OF MODEL CALCULATIONS WITH EXPERIMENTAL DATA The ranges of variations in model parameters are chosen arbitrary to some extent in the abovedescribed statistical simulation. Therefore, it is important to estimate the reliability of opticalmicrostructural cor relations derived on the basis of the model used. For this, let us compare them with known statistical corre
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lations between optical and microphysical parameters of aerosol found from experimental data. Stable statistical relationships between the aerosol light scattering coefficients at λ = 0.51 μm at an angle of 45° (β1) and at λ = 1.2 μm at an angle of 3° (β2) and the volume concentrations of fine H0.1–1.2 (particles with diameters of 0.1–1.2 μm) and coarse H>2 (diam eters of 2–20 μm) aerosol fractions, respectively, have been found in [2, 19]. The regression equations that describe these relationships are [2, 19]: H0.1–1.2 = 0.92 1.0β1.0 1 and H> 2 = 0.23β 2 , where H2–20 and H0.1–1.2 are measured in mm3/m3, and β1 and β2, in km–1 sr–1. Similar regressions can be derived on the basis of a data set modeled, i.e., within the model used with a specified variability of its parameters. A set of points (β1, H0.1–1.2) and (β2, H>2), which correspond to differ ent combinations of model parameters (103 in the total amount) is shown in Fig. 3. A logarithmic approxima tion of these points result in the following regression equations: H0.1–1..2 = 1.29β1.04 and H> 2 = 0.25β1.00 1 2 . Coefficients of the equations derived are quite close to similar coefficients that correspond to independent experimental ensembles. Small differences between theoretical and experimental dependencies are easily explained physically. First, experimental ensembles correspond to much narrower ranges of variations in microphysical param eters of aerosol than the data set modeled. As seen from Fig. 3a, the experimental equation describes well a statistical correlation between H0.1–1.2 and β1 in the range H0.1–1.2 = 0.001–0.06 mm3/m3, which corre sponds to the experimental ensemble [2]. At the same time, the theoretical regression is valid for a much wider range H0.1–1.2 = 10–5–0.5 mm3/m3. Second, it should be noted that H0.1–1.2 and H> 2 concentrations were not measured directly in [2, 19], but were calculated through reversion of optical mea surement data. In this case, the particle size distribu tion was used in the range of diameters 0.4–20 μm of spheres equivalent in volume. In our calculations, we use the range 0.002–30 μm, and the total volume of particles of 2–30 μm in size is taken as the concentra tion H>2. According to an empirical model of atmospheric hazes developed at the Institute of Atmospheric Phys ics, Russian Academy of Sciences, the mass concen tration of fine aerosol Ma [μm/m3] for the aerosol par ticle matter density γa = 1.5 g/cm3 can be calculated by the equation Ma = 2400β(0.52 μm, 45°) [20]. Accord ing to data of our statistical modeling, the proportion ality factor between the mass concentration of parti cles 0.2–2.0 μm in size and β at the same density of aerosol matter is 2100 mg sr/m2, which agrees quite well with the above value given the uncertainty range of particle sizes corresponding to the fine aerosol frac ATMOSPHERIC AND OCEANIC OPTICS
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Table 5. Assessments of the PMX, corresponding to the scheme of nephelometric measurements with λ1 = 0.532 μm and λ2 = 1.064 μm, θ1 = 5° and θ2 = 20° X, μm
δβ, %
ρ*X
ΔPMX, μg/m3 δPMX, %
0
0.9825
4.86
12.4
10
0.9768
5.75
15.0
0
0.9888
5.08
9.0
10
0.9850
5.94
11.0
0
0.9930
4.96
5.4
10
0.9918
6.07
7.3
0
0.9679
8.83
23.2
10
0.9414
1.0
2.5
10
>10 12.8
31.5
tion. We should note that the value of γa should be spec ified a priori when comparing the model and experi mental statistical relationships between aerosol optical parameters and mass concentrations of aerosol frac tions. The analysis of experimental data from different literature sources shows that their best correspondence to model calculations is attained under the assumption of a matter density of particles with sizes x ≤ 2.5 and x > 2.5 μm is 1.5 and 1.0 g/cm3, respectively. Thus, mean values of 3.3 and 3.4 m2/g are given in [1, 3], respectively, for the ratio of aerosol scattering coeffi cient at λ = 0.55 μm and the concentration PM2.5, which are quite close to the model assessment of this ratio (3.5 m2/g) at γa = 1.5 g/cm3. A similar ratio for the aerosol attenuation coefficient is 4.93 m2/g according to the experimental data [21] and 4.87 m2/g according to model calculations. A correlation between the scat tering coefficient βsca and the mass concentration of coarse particles PM10 and the total concentration of all the aerosol fractions M is shown with a low correlation coefficient (0.5–0.7); however, the mean values of the ratios βsca(0.55 μm)/PM10 and βsca(0.53 μm)/M, equal to 2.5 and 1.1 m2/g, respectively, from data [3, 22], also agree well with the results of our statistical modeling at γa = 1.0 g/cm3 equal to 2.1 and 1.2 m2/g, respectively. Thus, the model used and the statistical modeling allow us to derive statistical relationships between optical and microphysical aerosol parameters, which correlate well with data from independent measure ments. The method developed on this basis can be effectively used for continuous monitoring of concen trations of respirable aerosol fractions in urban air at automated air monitoring stations [23].
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REFERENCES
(a)
H0.1–0.2, mm3/m3 100
1 2
10–2
10–4
10–5
H>2, mm3/m3 100
10–3 10–1 –1 –1 β(0.51 μm, 45°), km sr (b)
10–2 2
1 10–4
10–3
10–1 β(1.2 μm, 3°), km–1 sr–1
101
Fig. 3. Model ensembles of points (a) β(0.51 μm, 45°), H0.1–1.2 and (b) β(1.2 μm, 3°), H> 2, corresponding to dif ferent values of model parameters, their logarithmic approximations (1), and experimental dependencies (2) from [2, 19].
CONCLUSIONS The results of the study allow the conclusion that there is a possibility of designing an air pollution nephelometric measuring instrument with divisions of mass concentrations of aerosol fractions PM1, PM2.5, PM10, and PM>10, which satisfies the requirements of sanitation and epidemiological services. Industrial production of this instrument will allow building an automated monitoring network of urban air with transmission of all data to a central control board or on the Internet.
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