Volatile and Fixed Solids. Material that can be volatilized and burned off when ignited at 500 6 50°C is classified as volatile. In general, volatile solids (VS) are presumed to be organic matter, although some organic matter will not burn, and some inorganic solids break down at high temperatures. Fixed solids (FS) comprise the residue that remains after a sample has been ignited. Thus, TS, TSS, and TDS comprise both fixed solids and volatile solids. The ratio of the VS to FS is often used to characterize the wastewater with respect to amount of organic matter present.
Particle Size and Particle Size Measurement
As noted above, TSS is a lumped parameter. In an effort to understand more about the nature of the particles that comprise the TSS in wastewater, measurement of particle size is undertaken and an analysis of the distribution of particle sizes is conducted (Tchobano- glous, 1995). Information on particle size is of importance in assessing the effectiveness of treatment processes (e.g., secondary sedimentation, effluent filtration, and effluent disinfection). Because the effectiveness of both chlorine, ozone, and UV disinfection is dependent on particle size, the determination of particle size has become more important, especially with greater effluent reuse in the western United States.
Information on the size of the biodegradable organic particles is significant from a treatment standpoint, as the biological conversion rate of these particles is dependent on size (see discussion in Sec. 2–6, which deals with biochemical oxygen demand). Methods that have been used to determine particle size are summarized in Table 2–5. As reported in Table 2–5, the methods can be divided into two general categories: (1) methods based on observation and measurement and (2) methods based on separation and analysis tech- niques. The methods used most commonly to study and quantify the particles in wastewater
Table 2–5
Representative
2–3 Physical Properties
77
are (1) serial filtration, (2) electronic particle counting, and (3) direct microscopic observa- tion. The principal types of materials that comprise the filterable and non-filterable solids in treated wastewater and their approximate size range are reported on Fig. 2–7.
Serial Filtration. Serial filtration may be used to determine an approximate particle size distribution of suspended solids based on mass (Levine et al., 1985). In the serial filtration method, a wastewater sample is passed sequentially through a series of membrane filters (see Fig. 2–8) with circular openings of known diameter (typically 12, 8, 5, 3, 1, and 0.1 mm), and the amount of particulate material retained in each filter is measured. Typical results from such a measurement are shown on Fig. 2–9. What is interesting to note on Fig. 2–9 is that a significant amount of colloidal material will be found between 0.1 and 1.0 mm. Although some information is gained on the size and distribution of the particles in the wastewater sample, little information is gained on the nature of the individual particles.
Electronic Particle Size Analyzers. To understand more about the nature and dis- tribution of particles in wastewater, nondestructive measurement of particle size and particle size distribution is now quite common. However, it should be noted that electronic particle siz- ing and counting techniques cannot be used reliably for determining the source or type of par- ticle (e.g., distinguishing between a viable cyst, a nonviable cyst, or a similar size silt particle).
Figure 2–7
Size ranges of organic constituents in wastewater and size separation and measurement techniques used for their quantification.
0.01 0.1 1 10 100
Particle size, mm 101 102 103 104 105 106 107 108 109
Approximate molecular mass, amu
Particulate and dissolved matter found in treated wastewater
Electron microscopy
Light microscopy Colloidal material
Exocellular enzymes
Scanning tunneling microscopy
Silt particles Clay particles
RNA DNA
Bacteria
Cryptosporidium oocysts Proteins
Giardia lamblia cysts Humic acids Cell fragments
Fulvic acids Polysaccharides
Viruses Algae
Human vision
0.001 0.0001
Methods used to quantify particles found in treated wastewater
Laser light scattering
HiAC particle counter Coulter counter Range for TSS test
Settleable solids
Typical operating range of treatment processes
Reverse osmosis
Nanofiltration
Ultrafiltration
Microfiltration
Sedimentation Depth and surface filtration Activated carbon pores
Organic debris and bacterial flocs
Vitamins Fatty acids Carbohydrates
Chlorophyll
Synthetic organic compounds
Amino acids Nutrients
Aqueous salts
In electronic particle size counting, particles are counted by diluting a treated waste- water sample and then passing the diluted sample through a calibrated orifice or past a laser beam [see Figs. 2–10(a) and (b), respectively]. As the particles pass through the orifice, the conductivity of the fluid changes, due to the presence of the particle. The change in conductivity is correlated to the size of an equivalent sphere. In a similar fashion, as a particle passes by a laser beam, it reduces the intensity of the laser due to light scattering. The reduced intensity is correlated to the diameter of the particle.
The typical size ranges quantifiable with different types of particle size counters were reported previously in Table 2–5. Most particle counters used in wastewater treat- ment facilities to assess performance have sensors available in different size ranges, such as 1.0 to 60 mm or 1 to 350 mm, depending on the manufacturer and application.
Figure 2–8
Definition sketch for the determination of the particle size distribution (by mass) using serial filtration with membrane filters.
12 mm
8 mm
5 mm
3 mm
1 mm 0.1 mm Relative pore size Water
sample
Filtrate processed using subsequent filters with smaller
pore size
Figure 2–9
Typical data on the distribution of filterable solids obtained in two different tests by serial filtration in trickling filter effluent. Note: the large fraction of unmeasured solids between 0.1 and 1.0 mm using conventional TSS test.
0 5 10 15 20 25
0.1 to 1.0 1.0 to
3.0 3.0 to 5.0 5.0 to
8.0 8.0 to 12.0 >12.0 TSS (1 mm) = 17.7 mg/L TSS (0.1 mm) = 39.9 mg/L TSS (1 mm) = 17.0 mg/L TSS (0.1 mm) = 38.3 mg/L Size range captured on standard filter used for TSS test
Particle mass concentration within indicated size range, mg/L
Particle size range as determined by filter pore diameter, mm
2–3 Physical Properties
79
Particle counters that do not measure particles smaller than 1 mm may be a limitation in some cases. Particle counts are typically measured and recorded in about 10 to 20 size ranges (e.g., 2 to 5 mm) called channels (or bins) of the chosen sensor range. One com- monly used particle counter utilizes 128 channels. Channel sizes can be arithmetic, logarithmic, or arbitrary, depending on the measurement objective. Using a logarithmic scale, the upper channel limit is equal to the lower channel limit times a scaling factor.
A typical particle size analysis with a laser type counter with 128 channels is shown on Fig. 2–11(a).
For disinfection studies, channel sizes are often selected that correspond to the size ranges of interest, for example, Cryptosporidium (2 to 5 mm) and Giardia (5 to 15 mm).
With particle size counters that use large numbers of small channel sizes, the interpretation of the resulting data is more difficult. Where extremely small channel sizes are used, it is recommended that the data be aggregated into appropriate bin sizes [see Fig. 2–11(b)]. In addition to reporting particle number by size, the data can be reported in terms of surface area and volume; the volume fraction corresponding to each particle size range can also be computed, if needed (Standard Methods, 2012).
Direct Observation. For visualization of particles that are smaller than those visible to the unaided eye, microscopic techniques may be used. The use of microscopic observa- tion allows for the determination of particle size counts and in some cases for more rigor- ous identification of a particle’s origin than is possible with other analysis techniques. In microscopic observation, a measured volume of sample is placed in a particle counting cell, and the individual particles may be counted, often with the use of a stain to enhance the particle contrast. The size range quantifiable using a variety of microscopic tech- niques is reported in Table 2–5. In general, microscopic counting of particles is impracti- cal on a routine basis, given the number of particles per mL of wastewater. Nevertheless, this method can be used to qualitatively assess the nature and size of the particles in wastewater.
Figure 2–10
Determination of particle size distribution: (a) coulter counter, voltage difference as particle passes through the orifice is used to determine the size of an equivalent spherical particle and (b) laser particle size counter, size of equivalent spherical particle is based on reduced intensity and light scattering as particle passes through light beam.
Sample with particles
Laser Lens
Sample out
Detector Signal output, mV
Intensity Electrodes used to
measure voltage differences as particles pass through orifice
Fluid containing particles to be counted flows through orifice
Particles
Ruby orifice embedded in glass Vacuum to pull solution
through the orifice
(a) (b)
Particle Size Distribution
In wastewater, it has been observed that the number of particles increases with decreasing particle diameter and that the frequency distribution typically follows a power law distribution of the form:
dN
d(dp) 5A(dp)2b. ≤N
≤(dpi) (2–16) where dN 5 the particle number concentration with respect to the incremental change in
particle diameter d(dp), number/mL?mm d(dp) 5 incremental change in particle diameter, mm
A 5 power law density coefficient, unitless
dp5 arithmetic (or geometric) mean particle diameter, depending on counter channel configuration, mm
Figure 2–11
Effect the use of chemicals on filter particle size removal performance (a) original data as collected (courtesy of K. Bourgeous, 2005), (b) original data aggregated into selected channel (bin) sizes, and, (c) the original data, plotted functionally according to the power law (see Example 2–4).
Secondary effluent Filtered secondary effluent Coagulated, flocculated, and filtered secondary effluent
100 101 102 103 104
100 101 102 103 104
105 106
1 10 100
1 10 100
-1 0 1 2 3 4 5 6
0 0.5 1 1.5 2
log (dp) log[(DN/D(dpi)]
Particle count per size channel, DN, number/mL
Mean particle size, dp, mm
Particle count per size channel, DN, number/mL
Mean particle size, dp, mm Size range of
interest for Cryptosporidium
Size range of interest for Giardia
(a)
(c)
(b)
b = 2.6
b = 3.2 b = 2.5
2 5 15
2–3 Physical Properties
81
b5 power law slope coefficient
≤N 5 the particle number concentration in given channel, number/mL
≤(dpi) 5 incremental channel size, mm
In effect the right-hand term in Eq. (2–16) is used to normalize the data and allows for comparison between particle size distributions. Taking the log of both sides of Eq. (2–16) results in the following expression, which can be plotted to determine the unknown coefficients A and b:
log c ≤N
≤(dpi)d5logA2blog(dp) (2–17)
The value of A is determined when dp51 mm. As the value of A increases, the total number of particles in each size classification increases. The slope b is a measure of the relative number of particles in each size range. Thus, if b is less than one the particle size distribution is dominated by large particles, if b is equal to one all particle sizes are represented equally, and if b is greater than one the particle size distribution is dominated by small particles (Trussell and Tate, 1979). Because different slope values will be obtained, depending on the selection of the bin sizes, care must be exercised in interpreting the results. The analysis of data obtained from a particle size counter is shown on Fig. 2–11(c); the necessary computational steps are illustrated in Example 2–4.
EXAMPLE 2–4 Analysis of Particle Size Information Determine the coefficients A and b in Eq. (2–16) for the following particle size data obtained using a particle counter with arithmetic channel settings.
Channel
size, mm Number
1–2 20,000
2–5 6688
5–10 3000
10–15 1050
15–20 300
20–30 150
30–40 27
40–60 12
60–80 6
80–100 4
100–140 2
Channel size, mm
Mean diametera
dp, mm DN, number/
mL
Channel size interval,
D(dpi) log(dp) log[DN/D(dpi)]
1–2 1.50 20,000 1 0.18 4.30
2–5 3.50 6688 3 0.54 3.35
5–10 7.5 3000 5 0.88 2.78
10–15 12.5 1050 5 1.10 2.32
15–20 17.5 300 5 1.24 1.78
20–30 25.0 150 10 1.40 1.18
30–40 35.0 27 10 1.54 0.43
40–60 50.0 12 20 1.70 20.22
60–80 70.0 6 20 1.85 20.52
80–100 90.0 4 20 1.95 20.70
100–140 120.0 2 40 2.08 21.12
a Arithmetic mean diameter, 1.5 5 [(1 1 2)/2].
2. Prepare a plot of the log of the geometric mean particle diameter, dp, versus the normalized number of particles for the corresponding bin size, log[DN/D(dpi)].
–2 –1 0 1 2 3 4 5 6
0 0.5 1 1.5 2 2.5
log[^N/^(dpi)]
log (dp) Intercept = 5.16
3. Determine A and b in Eq. (2–16) a. Determine A
When log (dp) 5 0, dp5 1, and A 5 105.16 b. Determine b
2b5 3.652(21.15)
0.522 5 23.2 b53.2
Solution
1. Set up a table to determine the information needed to plot the data
2–3 Physical Properties
83
Nanoparticles and Nanocomposites
Nanoparticles, originating from natural and anthropogenic processes, are small objects or particles, ranging in size from 1 to 100 nm, which behave as an entire unit with respect to their properties and transport. Because nanoparticles can form a variety of structures, such as nanospheres, nanotubes, or nanosheets, at least two of the three dimensions must be between 1 and 100 nm. Nanoparticles have also been referred to as ultrafine particles.
Nanoparticles form a bridge between bulk materials and molecular or atomic structures.
Nanocomposites, formed from two or more dissimilar materials, are developed to produce new structures with differing but controllable properties. For nanocomposites, at lease one of the materials (phases) must have a dimension in the nanoscale.
Common materials used for the production of nanoparticles, arranged alphabetically, include aluminum oxide, cerium oxide, cobalt, gold, iron, iron oxide, nickel, platinum, silica (SiO2), silver, titanium dioxide (TiO2), and zinc oxide. In addition to the constituents just mentioned, nanocomposites can include citrate, polyvinyl acetates (PVA), polyvinylpyrrol- idone (PVP), tannic acid, and an ever expanding list of compounds. Nanoparticles are formed through natural processes and human industrial (anthropogenic) means. Natural processes include the oxidation of volatile compounds of biogenic origin. Industrially, nanoparticles are formed in the liquid and gas phase through a series of controlled chemical reactions.
Interest in nanoparticles and nanocomposites stems from the fact that they are now used extensively in the manufacture of a wide variety of consumer products such as self- cleaning glasses, clothing, scratch-resistant coatings, swimming pool cleaners, personal care products, and food production. Because of their widespread use, nanoparticles released from different household products and industrial activities are now being found in ever increasing concentrations in untreated and treated wastewater and biosolids.
At this time, little is known about the long-term effects of nanoparticles on public health and their impacts when discharged to the environment. Also, there is some concern that nanoparticles may accumulate and that such accumulations may have health implica- tions. In a recently completed study, it was found that the accumulation of silver nanopar- ticles may have a detrimental effect on nitrification and nutrient removal (Hu, 2010).
Because the field of nanotechnology is evolving so rapidly, the current literature should be consulted for the latest developments including production, patterns of utilization, and the potential presence of nanoparticles in wastewater and their implications for treatment, public health, and environment. A comprehensive review of nanotechnology has been prepared by SCENIHR (2006).
Turbidity
Turbidity is a measure of the light scattering properties of a solution containing suspended and colloidal particles. Turbidity measurements require a light source (incandescent or Comment As the value of b is greater than one, the distribution is dominated by small particles, which is consistent with the actual data. It is important to note that the slope of the line of best fit through the plotted data will vary depending on the bin sizes selected for analysis.
Also, it should be noted that the line used to define b may not be linear depending on the characteristics of the suspension and the minimum and maximum particle sizes measured, a characteristic of the specific instrument used in the analysis. The channel sizes of 2–5 and 5–15 mm were selected to determine if the number of Cryptosporidium or Giardia determined analytically can be correlated with particle size measurements.
light-emitting diode) and a sensor to measure the scattered light. As shown on Fig. 2–12(a), the scattered light sensor is located at 90 degrees to the light source. The measured turbid- ity increases as the intensity of the scattered light increases. Turbidity is expressed in nephelometric turbidity units (NTU). The spatial distribution and intensity of the scattered light, illustrated on Fig. 2–12(b), will depend on the size of the particle relative to the wavelength of the light source (Hach, 1997). For particles less than one-tenth of the wave- length of the incident light, the scattering of light is fairly symmetrical [see Fig. 2–12(b)(i)].
Limitations of Turbidity Measurements. As the particle size increases relative to the wave length of the incident light, the light reflected from different parts of the particle create interference patterns that are additive in the forward direction [see Figs. 2–12(b)(ii) and (iii)]. Also, the intensity of the scattered light varies with the wave- length of the incident light. For example, the turbidity of a solution of lamp black will essentially be equal to zero. Based on these considerations, turbidity measurements tend to be more sensitive to particles in the size range of the incident light wavelength (0.3 to 0.7 mm for visible light).
Thus, two filtered wastewater samples with nearly identical turbidity values could have very different particle size distributions. A further complication with turbidity measurements is that some particles will essentially adsorb most of the light and only scatter a minimal amount of the incident light. Also, because of the light scattering characteristics of large particles, a few large particles would not be detected in the presence of many smaller particles. Also, some online turbidity meters used to moni- tor the performance of microfiltration units are affected by the air used to clean the membranes.
Thus, there is no fundamental relationship between turbidity and the concentration of total suspended solids, and turbidity alone is not a good measure of whether wastewater can be disinfected effectively. As a result, it is almost impossible to compare turbidity values reported in the literature. However, turbidity readings at a given facility can be used for process control.
Figure 2–12
Determination of turbidity by light scattering: (a) schematic of turbidity apparatus and
(b) typical light scattering patterns for small (i), intermediate (ii), and large (iii) particles.
Incident light
Light source
Photodetector at 90 degrees for measuring turbidity
Inline photodetector for measuring transmittance
Water sample in glass cell
Scattered light Transmitted light Aperture
Lens
(a)
(b) Incident light
(i) (ii) (iii)
Pattern of light scatter Suspended
particle
2–3 Physical Properties
85
Relationship Between Turbidity and TSS
In general, there is no relationship between turbidity and the concentration of total sus- pended solids in untreated wastewater. There is, however, a reasonable relationship between turbidity and total suspended solids for the settled and filtered secondary effluent from the activated sludge process. The general form of the relationship is as follows:
TSS, mg/L<(TSSf)(T) (2–18)
where TSS 5 total suspended solids, mg/L
TSSf5 factor used to convert turbidity readings to total suspended solids, (mg TSS/L)/NTU
T 5 turbidity, NTU
The specific value of the conversion factor will vary for each treatment plant, depending primarily on the operation of the biological treatment process. The conversion factors for settled secondary effluent and for secondary effluent filtered with a granular-medium depth filter will typically vary from 2.3 to 2.4 and 1.3 to 1.6, respectively.
Color
Historically, the term condition was used along with composition and concentration to describe wastewater. Condition refers to the age of the wastewater which is determined qualitatively by its color and odor. Fresh wastewater is usually a light brownish-gray color. However, as the travel time in the collection system increases, and more anaerobic conditions develop, the color of the wastewater changes sequentially from gray to dark gray, and ultimately to black. When the color of the wastewater is black, the wastewater is often described as septic. Some indus- trial wastewaters may also add color to domestic wastewater. In most cases, the gray, dark gray, and black color of the wastewater is due to the formation of metallic sulfides, which form as the sulfide produced under anaerobic conditions reacts with the metals in the wastewater.
Absorption/Transmittance
The absorbance of a solution is a measure of the amount of light, of a specified wave- length, that is absorbed by the constituents in a solution. Absorbance is measured using a spectrophotometer with a fixed path length (usually 1.0 cm) at a wavelength of 254 nm.
Absorbance follows the Beers-Lambert Law as given by Eq. (2–19):
logaI Io
b 5e(l)Cx (2–19) Where I 5 light intensity at distance x from the light source, mW/cm2
Io5 light intensity at light source, mW/cm2
e(l) 5 molar absorptivity (also known as the extinction coefficient) of the light- absorbing solute at wavelength l, L/mole?cm
C 5 concentration of light-absorbing solute, mole/L x 5 light path-length, cm
When the left-hand side of Eq. (2–19) is expressed as a natural logarithm, the right-hand side of the equation must be multiplied by 2.303 because the absorbance coefficient is determined in base 10. The term on the right-hand side of Eq. (2–19) is defined as the absorbance, A(l), which is unitless but is often reported in units of cm21, which corresponds to absorptivity k(l).
If the length of the light path is 1 cm, absorptivity is equal to the absorbance.
k(l) 5e(l)C 5 A(l)
x (2–20)
where k(l) 5 the absorptivity, cm21 A(l) 5 absorbance, dimensionless