**3.1 Number size distribution of raindrops**

The number size distribution of raindrops collected at two different rainfall intensities was estimated by the volume of melted raindrops and that of calculated single raindrop from its average size. **Figure 3** shows the raindrop number size distribution at the beginning (0.2 mm h<sup>−</sup><sup>1</sup> ) and subsequent (1.2 mm h<sup>−</sup><sup>1</sup> ) rainfalls. The raindrop concentration Nr (m<sup>−</sup><sup>2</sup> h<sup>−</sup><sup>1</sup> ) is the total number of drops falling per square meter of surface per hour. Raindrop number tended to drastically decrease as the drop size goes up at both hourly rain rates (i.e., rain intensity). Needless to say, it showed higher number concentration when the higher rainfall intensity. This result indicates that the increase in the rain rate stemmed mainly from the increase in the number concentration of raindrops with drop diameter < 0.94 mm.

### **3.2 Calculation of particle scavenging efficiency of size-resolved raindrops**

Prior to the interpretation of the actual measurement data about particle scavenging properties of size-resolved rain drops, the collection efficiency of ambient particles as a function of raindrop size was theoretically calculated.

Slinn and Hales [13] proposed three particle collection efficiencies (*E*), that is, *E* by Brownian diffusion (*Edif.*), *E* by interception (*Eint.*), and *E* by inertial impaction processes (*Eimp.*). Subsequently, Strauss [14] suggested a more advanced equation for particle collection efficiency (*Einteg.*) of raindrops that integrated three kinds of efficiencies as follows:

**Figure 3.** *Raindrop number size distribution at the beginning (0.2 mm h<sup>−</sup><sup>1</sup> ) and subsequent (1.2 mm h<sup>−</sup><sup>1</sup> ) rainfalls.*

$$E\_{\rm integral} = \mathbf{1} - \left\langle \mathbf{1} - E\_{\rm df.} \right\rangle \left\langle \mathbf{1} - E\_{\rm int.} \right\rangle \left\langle \mathbf{1} - E\_{\rm imp.} \right\rangle \tag{1}$$

In this study, the collection efficiency of ambient particles for three kinds of raindrop sizes (i.e., 0.09, 0.94, and 2.60 mm diameter) was theoretically computed using this integrated *Einteg*. Details for calculation like variable settings and computation processes were already described in our earlier articles [6, 15]. **Figure 4** shows the below-cloud scavenging coefficients of ambient particles by falling raindrops as a function of aerosol radius and collector rain drop size. There are several features that appear in the particle capturing efficiency curves. As the first outstanding feature, the smaller raindrop can scavenge particles more efficiently. Another peculiarity for particle scavenging efficiency curves is that the efficiency is rapidly degraded in the central part of each curve. This is well-known phenomenon as the term of "Greenfield gap" [13]. Although, the margin is varied from 0.01 to 2 μm [16], this gap has been reported in various studies.

#### **3.3 Particle scavenging properties of size-resolved raindrops**

**Figure 5** shows time series variation of relative humidity and four-size resolved (0.3–0.5, 0.5–1.0, 1.0–2.0, and 2.0–5.0 μm) particle number concentration throughout a whole rainfall duration. As previously mentioned, it was a relatively weak rainfall with the rainfall intensity varied from 0.2 to 1.2 mm h<sup>−</sup><sup>1</sup> .

Particles of all sizes exhibit lower concentrations when the rain started. Although this was the expected result, an unusual thing was that particle number concentration was temporarily increased immediately after the rain.

Decreasing relative humidity increases scavenging in the Greenfield gap since the evaporating raindrops are cooler at the surface, and this sets up a thermal gradient that induces motion of the aerosols towards the cooler raindrop surface [17]. In the condition of initial rainfall, falling raindrops can be exposed to the dry air of near the surface. According to Croft et al. [17], this situation will reduce the levels

**Figure 4.** *Theoretically calculated collection efficiency of ambient particles as a function of raindrop size.*

**101**

*The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles…*

of atmospheric particles because the particle removal efficiency can be improved by increasing scavenging in the Greenfield gap. Nevertheless, the reason for a temporarily increasing of particle concentration might be that new particles were created in the early stage of precipitation because small size rain droplets cloud be easily

*Time series variation of relative humidity and size-resolved particle number concentration.*

A continuous decrease of the particle number concentration over most of the range of particle diameter during a whole precipitation was not seen. There was a modest increase in particle number concentration from 07:00 to 09:30 (see **Figure 5**). Such increases might be caused by a decline of rainfall intensity and the influx of

Scavenging rate, *Rsca*.(%), of three-size resolved (0.3–0.5, 0.5–1.0, and 1.0– 2.0 μm) particles showing an obvious reduction was calculated by below equation:

(%) <sup>=</sup> *Np*max. <sup>−</sup> *Np*min. \_\_\_\_\_\_\_\_\_\_ *Np*max.

where *Npmax*. and *Npmin*. are the maximum and minimum particle number

Calculated *Rsca*. based on the actual measurement values were 38.7, 69.5, and 80.8% for the particles with 0.3–0.5, 0.5–1.0, and 1.0–2.0 μm diameter, respectively. The results show a good match to that of model calculation shown in **Figure 4**.

Meanwhile, there was a very high rain washing efficiency for PM2.5. This result should be welcomed by people, particularly living in East Asia, who suffer from PM2.5.

**Figure 6** shows the time series variation of PM2.5, sulfate in PM2.5, their *Rsca*., and relative humidity in the first half of rainfall. Here, let us pay attention to the *Rsca*. for PM2.5 and sulfate in PM2.5. *Rsca*. shows a gradual increase in both. However, that of PM2.5 (63.1%) was overwhelmingly high compared to sulfate in PM2.5 (33.0%). Despite sulfate particles being water soluble, unexpectedly they have a low *Rsca*. Most of the sulfate in fine particles are forming (NH4)2SO4 or NH4HSO4 and they are generally appearing in the fine mode at 0.5–0.6 μm [18]. Therefore, Greenfield

× 100 (2)

*DOI: http://dx.doi.org/10.5772/intechopen.84227*

evaporated in the dried low altitude air.

**Figure 5.**

pollutants to our measurement site.

*Rsca*.

concentration for target particle size, respectably.

gap is the reason for the low *Rsca*. of sulfate in PM2.5.

*The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles… DOI: http://dx.doi.org/10.5772/intechopen.84227*

#### **Figure 5.**

*Rainfall - Extremes, Distribution and Properties*

gap has been reported in various studies.

**3.3 Particle scavenging properties of size-resolved raindrops**

rainfall with the rainfall intensity varied from 0.2 to 1.2 mm h<sup>−</sup><sup>1</sup>

concentration was temporarily increased immediately after the rain.

*Theoretically calculated collection efficiency of ambient particles as a function of raindrop size.*

*Einteg*. = 1 − (1 − *Edif*.) (1 − *Eint*.) (1 − *Eimp*.) (1)

**Figure 5** shows time series variation of relative humidity and four-size resolved (0.3–0.5, 0.5–1.0, 1.0–2.0, and 2.0–5.0 μm) particle number concentration throughout a whole rainfall duration. As previously mentioned, it was a relatively weak

Decreasing relative humidity increases scavenging in the Greenfield gap since the evaporating raindrops are cooler at the surface, and this sets up a thermal gradient that induces motion of the aerosols towards the cooler raindrop surface [17]. In the condition of initial rainfall, falling raindrops can be exposed to the dry air of near the surface. According to Croft et al. [17], this situation will reduce the levels

Particles of all sizes exhibit lower concentrations when the rain started. Although this was the expected result, an unusual thing was that particle number

.

In this study, the collection efficiency of ambient particles for three kinds of raindrop sizes (i.e., 0.09, 0.94, and 2.60 mm diameter) was theoretically computed using this integrated *Einteg*. Details for calculation like variable settings and computation processes were already described in our earlier articles [6, 15]. **Figure 4** shows the below-cloud scavenging coefficients of ambient particles by falling raindrops as a function of aerosol radius and collector rain drop size. There are several features that appear in the particle capturing efficiency curves. As the first outstanding feature, the smaller raindrop can scavenge particles more efficiently. Another peculiarity for particle scavenging efficiency curves is that the efficiency is rapidly degraded in the central part of each curve. This is well-known phenomenon as the term of "Greenfield gap" [13]. Although, the margin is varied from 0.01 to 2 μm [16], this

**100**

**Figure 4.**

*Time series variation of relative humidity and size-resolved particle number concentration.*

of atmospheric particles because the particle removal efficiency can be improved by increasing scavenging in the Greenfield gap. Nevertheless, the reason for a temporarily increasing of particle concentration might be that new particles were created in the early stage of precipitation because small size rain droplets cloud be easily evaporated in the dried low altitude air.

A continuous decrease of the particle number concentration over most of the range of particle diameter during a whole precipitation was not seen. There was a modest increase in particle number concentration from 07:00 to 09:30 (see **Figure 5**). Such increases might be caused by a decline of rainfall intensity and the influx of pollutants to our measurement site.

Scavenging rate, *Rsca*.(%), of three-size resolved (0.3–0.5, 0.5–1.0, and 1.0– 2.0 μm) particles showing an obvious reduction was calculated by below equation:

$$R\_{\text{car.}}\left(\text{96}\right) = \frac{N\_{p\_{\text{max}}} - N\_{p\_{\text{min}}}}{N\_{p\_{\text{max}}}} \times \mathbf{100} \tag{2}$$

where *Npmax*. and *Npmin*. are the maximum and minimum particle number concentration for target particle size, respectably.

Calculated *Rsca*. based on the actual measurement values were 38.7, 69.5, and 80.8% for the particles with 0.3–0.5, 0.5–1.0, and 1.0–2.0 μm diameter, respectively. The results show a good match to that of model calculation shown in **Figure 4**.

**Figure 6** shows the time series variation of PM2.5, sulfate in PM2.5, their *Rsca*., and relative humidity in the first half of rainfall. Here, let us pay attention to the *Rsca*. for PM2.5 and sulfate in PM2.5. *Rsca*. shows a gradual increase in both. However, that of PM2.5 (63.1%) was overwhelmingly high compared to sulfate in PM2.5 (33.0%).

Despite sulfate particles being water soluble, unexpectedly they have a low *Rsca*. Most of the sulfate in fine particles are forming (NH4)2SO4 or NH4HSO4 and they are generally appearing in the fine mode at 0.5–0.6 μm [18]. Therefore, Greenfield gap is the reason for the low *Rsca*. of sulfate in PM2.5.

Meanwhile, there was a very high rain washing efficiency for PM2.5. This result should be welcomed by people, particularly living in East Asia, who suffer from PM2.5.

**Figure 6.** *Time series variation of PM2.5 (μg m<sup>−</sup><sup>3</sup> ), sulfate in PM2.5 (μg m<sup>−</sup><sup>3</sup> ), their Rsca. (%), and relative humidity (%).*

## **3.4 Chemical properties of the residuals in size-classified raindrops**

**Figure 7** shows the elemental concentration of individual raindrops classified in three steps (i.e., 0.09, 0.94, and 2.6 mm) in order of size. The data were the elemental concentration in the raindrops at the beginning (0.2 mm h<sup>−</sup><sup>1</sup> ) rainfall and they were determined by PIXE analysis. S, Ca, Si, and Al ranked relatively high concentration in raindrops, especially small ones. Most of the element showed a continuous decrease in concentration with increasing raindrop diameter. Especially, there was a marked decrease in the range of between 0.09 and 0.94 mm raindrop diameter. Although little is known at present, it is expected that smaller raindrops should have higher elemental concentration because they have lower falling velocities and consequently they can effectively remove pollutants during longer lifetimes than larger ones. On the other hand, in some of the elements (e.g., Cl, Ca, Cu, and Zn), a slight increase was found between 0.94 and 2.6 mm raindrop diameter. If the elemental constituent were originated from large size particle (>4 mm in diameter), it has some possibility of the increasing for elemental concentration between 0.94 and 2.6 mm raindrops in diameter. Among many elements determined from individual raindrops, sulfur that showed the highest concentration was probably derived from gaseous SO2 and particulate sulfur taken up by falling raindrops. As another remarkable thing, unexpectedly, relatively high levels of lead were detected. Their concentrations were 0.83, 0.28, and 0.088 ppm in 0.09, 0.94, and 2.6 mm raindrops, respectively. In dealing with the health hazards of lead like neurologic and behavioral disorders, it is something that we ought to be talking about. In general, major sources of ambient lead are piston-engine aircraft operating on leaded aviation fuel, metals processing, waste incinerators, and lead-acid battery manufacturers. Although, because of its serious impacts on public health, leaded gasoline was permanently banned in Japan long time ago, the metal contaminations of roadside soils were included in ambient particles until now [19, 20].

#### **3.5 Chemical properties of the residual particles in size-classified raindrops**

When melt and evaporation of frozen raindrops were completed, it was possible to maintain residual materials on the Ag thin film. These retained matters could be the targets of SEM–EDX analysis. An example of EDX spectrum and elemental Weight% of a single residual particle in a raindrop (Dr = 2.5 mm) was drawn in **Figure 8**.

**103**

**Figure 7.**

*The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles…*

**Figure 9** illustrates the SEM image (top left) of a single residual particle in a raindrop (Dr = 2.5 mm) and its elemental maps. These visualized elemental maps for several elements including oxygen enable us not only to presume the chemical mixing state of raindrop residual particles, but also to estimate their source profiles. To obtain the source profile information for aerosol components, factor analysis, which is one of the multivariate statistical techniques, was carried out. It was possible to construct the matrix of 450-set of 13 components by the result of SEM–EDX analysis for residual particles in a total of 150 individual raindrops. The factor loadings (Varimax with Kaiser normalization) are shown in **Table 1**. The data matrix (450 variables × 13 cases) constructed in the present study was successfully classified into four factors. The first factor (34% of the variance) shows high loadings for S, P, Cu, Ca, and Cr. Although typical soil component like Al and Si were excluded because of their missing data, the first factor was associated with soil components (Ca and other minors). The second factor, which explains 26% of the variance, seemed to express the sources of fossil fuel combustion. The third factor grouped F and Fe were the components originated from biomass burning (or volcanoes) [21] and iron industry. The fourth factor dominantly made up of typical marine components. The cumulative variance of these three factors was 85.2%. This

*Elemental concentration of size-resolved raindrops determined by PIXE analysis.*

*DOI: http://dx.doi.org/10.5772/intechopen.84227*

*The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles… DOI: http://dx.doi.org/10.5772/intechopen.84227*

**Figure 7.** *Elemental concentration of size-resolved raindrops determined by PIXE analysis.*

**Figure 9** illustrates the SEM image (top left) of a single residual particle in a raindrop (Dr = 2.5 mm) and its elemental maps. These visualized elemental maps for several elements including oxygen enable us not only to presume the chemical mixing state of raindrop residual particles, but also to estimate their source profiles.

To obtain the source profile information for aerosol components, factor analysis, which is one of the multivariate statistical techniques, was carried out. It was possible to construct the matrix of 450-set of 13 components by the result of SEM–EDX analysis for residual particles in a total of 150 individual raindrops. The factor loadings (Varimax with Kaiser normalization) are shown in **Table 1**. The data matrix (450 variables × 13 cases) constructed in the present study was successfully classified into four factors. The first factor (34% of the variance) shows high loadings for S, P, Cu, Ca, and Cr. Although typical soil component like Al and Si were excluded because of their missing data, the first factor was associated with soil components (Ca and other minors). The second factor, which explains 26% of the variance, seemed to express the sources of fossil fuel combustion. The third factor grouped F and Fe were the components originated from biomass burning (or volcanoes) [21] and iron industry. The fourth factor dominantly made up of typical marine components. The cumulative variance of these three factors was 85.2%. This

*Rainfall - Extremes, Distribution and Properties*

**3.4 Chemical properties of the residuals in size-classified raindrops**

*), sulfate in PM2.5 (μg m<sup>−</sup><sup>3</sup>*

concentration in the raindrops at the beginning (0.2 mm h<sup>−</sup><sup>1</sup>

**Figure 7** shows the elemental concentration of individual raindrops classified in three steps (i.e., 0.09, 0.94, and 2.6 mm) in order of size. The data were the elemental

determined by PIXE analysis. S, Ca, Si, and Al ranked relatively high concentration in raindrops, especially small ones. Most of the element showed a continuous decrease in concentration with increasing raindrop diameter. Especially, there was a marked decrease in the range of between 0.09 and 0.94 mm raindrop diameter. Although little is known at present, it is expected that smaller raindrops should have higher elemental concentration because they have lower falling velocities and consequently they can effectively remove pollutants during longer lifetimes than larger ones. On the other hand, in some of the elements (e.g., Cl, Ca, Cu, and Zn), a slight increase was found between 0.94 and 2.6 mm raindrop diameter. If the elemental constituent were originated from large size particle (>4 mm in diameter), it has some possibility of the increasing for elemental concentration between 0.94 and 2.6 mm raindrops in diameter. Among many elements determined from individual raindrops, sulfur that showed the highest concentration was probably derived from gaseous SO2 and particulate sulfur taken up by falling raindrops. As another remarkable thing, unexpectedly, relatively high levels of lead were detected. Their concentrations were 0.83, 0.28, and 0.088 ppm in 0.09, 0.94, and 2.6 mm raindrops, respectively. In dealing with the health hazards of lead like neurologic and behavioral disorders, it is something that we ought to be talking about. In general, major sources of ambient lead are piston-engine aircraft operating on leaded aviation fuel, metals processing, waste incinerators, and lead-acid battery manufacturers. Although, because of its serious impacts on public health, leaded gasoline was permanently banned in Japan long time ago, the metal contaminations of roadside soils were included in ambient particles until now [19, 20].

**3.5 Chemical properties of the residual particles in size-classified raindrops**

When melt and evaporation of frozen raindrops were completed, it was possible to maintain residual materials on the Ag thin film. These retained matters could be the targets of SEM–EDX analysis. An example of EDX spectrum and elemental Weight% of a single residual particle in a raindrop (Dr = 2.5 mm) was drawn in **Figure 8**.

) rainfall and they were

*), their Rsca. (%), and relative humidity (%).*

**102**

**Figure 6.**

*Time series variation of PM2.5 (μg m<sup>−</sup><sup>3</sup>*

**Figure 8.** *EDX spectrum and elemental weight% of a single residual particle in a raindrop (Dr = 2.5 mm).*

**Figure 9.** *SEM image (top left) of a single residual particle in a raindrop (Dr = 2.5 mm) and its elemental maps*

**105**

*The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles…*

result indicates that the rainfall plays a valuable role in scavenging natural as well as

*Result of factor analysis for the elements detected from individual residues in raindrops with diameters between* 

Ambient particles are ultimately removed from the atmosphere by the natural processes generally referred to as wet precipitation and dry deposition. The former is the most important natural removal mechanism of ambient air pollutants including PM2.5. The clear landscapes after the rain is a good proof of this wet precipitation. In this study, the scavenging properties of ambient particles were investigated by collection of raindrops as a function of their size and clarifying their chemical nature. Particle scavenging rates based on both the actual measurement and the theoretically calculated values indicated that raindrops, especially small raindrops, played a great role to remove ambient particles including both naturally and artificially formed ones. On the other hand, through the PIXE analytical technique for the residuals in and/or on individual raindrops, it was obvious that several hazard components like Pb, Cr, and Mn had meaningful amount. Therefore, we must be thankful for the role of the rain, at the same time, we should avoid getting wet to protect our health from heavy metals. Further study on a comparison of the real measured data with the calculated result for the particle scavenging by raindrops is being planned in the near future.

artificial particles from the dirty atmosphere.

**4. Conclusions**

**Table 1.**

*1.17 and 3.5 mm.*

*DOI: http://dx.doi.org/10.5772/intechopen.84227*


*The Chemical Nature of Individual Size-Resolved Raindrops and Their Residual Particles… DOI: http://dx.doi.org/10.5772/intechopen.84227*

#### **Table 1.**

*Rainfall - Extremes, Distribution and Properties*

*EDX spectrum and elemental weight% of a single residual particle in a raindrop (Dr = 2.5 mm).*

*SEM image (top left) of a single residual particle in a raindrop (Dr = 2.5 mm) and its elemental maps*

**104**

**Figure 9.**

**Figure 8.**

*Result of factor analysis for the elements detected from individual residues in raindrops with diameters between 1.17 and 3.5 mm.*

result indicates that the rainfall plays a valuable role in scavenging natural as well as artificial particles from the dirty atmosphere.
