Volatilisation processes in wastewater treatment plants as a source of potential exposure to vocs

Ann. occup. Hyg., Vol. 41, No. 4, pp. 437454, 1997 $3 1997 British Occupational Hygiene Soaety. All rights reserved Published by Elsevier Science Ltd Printed in Great Britain ooo3s4878/97 s17.00+0.00

Pergamon

PII: s00034878(97)0000~7

VOLATILISATION PROCESSES IN WASTEWATER TREATMENT PLANTS AS A SOURCE OF POTENTIAL EXPOSURE TO VOCs Alexander P. Bianchi*$ and Mark S. Varneyt *Industrial Hygiene Department, Exxon Chemical Co., Cadland Rd, Hythe, Southampton SO45 6NP, U.K.; and tDepartment of Oceanographic Sciences, Oceanography Centre, University of Southampton, Empress Dock, Southampton SO40 4WH, U.K. (Received

17 Ocmber

1996)

Abstract-The results of a survey estimating volatilisation rates (as gas exchange constants and flux rates) of a range of hazardous alkane, aromatic, organohalogen, organosulphide, ketone and alcohol volatile organic compounds (VOCs) from a water bay are presented. More than 73 experimental test runs were carried out over a year under varying seasonal conditions to measure the simultaneous concentrations of VOCs in air and water phases. The data were processed employing new advances in ‘surface renewal’ volatilisation models. Based on the experimental data, estimates of theoretical equilibrium constants, gas exchange constants and flux rates for each VOC were made. Within the ranges of concentration which may reasonably be encountered by process workers, the fluxes for a broad range of VOCs ranged from approximately 0.04x 1O-8 to 9.0x IO-’ g cm -* h-l. The results were used to make predictions about the relationship between volatilisation processes and their implications for occupational hygiene risk assessment. 0 1997 British Occupational Hygiene Society. Published by Elsevier Science Ltd

INTRODUCTION

Emissions of volatile organic compounds (VOCs) from wastewaters in municipal sewage treatment plants, surface impoundments, waste lagoons, industrial wastewaters and drainage systems are often overlooked as sources of exposure to hazardous substances. In many cases,the toxic effects of a broad range of VOCs arising from such sources may have significant adverse consequences for public health (Pellizzari, 1982; Namkung and Rittman, 1987; Ciccioli, 1993; Wallace, 1993) and for wastewater plant workers within an industrial setting (de Mik, 1993). The range of volatile chemical substancespassing through wastewater treatment plants are often unknown, which creates problems when attempting to measure the VOC contribution to airborne environments or assessexposure implications for operating personnel (Deacon, 1977; Dix, 1981; Berrafato and Wadden, 1986; Maugh, 1987; GESAMP, 1991; Haz. Sub., 1993; de Mik, 1993). Up to 40% of the organic loading within an industrial or municipal wastewater plant may be volatile (for example VOCs with boiling point: < 350°C; vapour pressure, 0.1-500 mm Hg at 20°C) depending on the nature of materials flushed to sewer (Knap et al., 1979; Clark, 1986). Ecotoxicological impacts within the immediate receiving environment are also closely associated with the effects of toxic vapour and liquid-phase VOCs in effluent (Verscheuren, 1983; Stagg, 1986). $Author

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Volatilisation has long been recognised as a mechanism whereby organic compounds with appropriate physicochemical characteristics (that is aqueous solubility and concentration, vapour pressure and Henry’s Law constant) transfer across the water/air interface from the ‘aqueous’ compartment to the ‘atmosphere’ compartment (Kotzias and Sparta, 1993). Within wastewater and treatment plants, volatilisation processes have, in the past, been viewed as a legitimate means for reducing the total organic load at the discharge point. Moreover, these so-called ‘evaporative losses’ were incorporated into basic models employed to perform crude estimates of volatile hydrocarbons emissions from oil/water separator bays (Litchfield, 1971) and of volatile organohalogens from general wastewaters (Dilling et al., 1975; Dilling, 1977). Within the last lo-15 years, the limitations of engineering controls over volatilisation processes have been recognised as an undesirable feature of public and industrial sector wastewater management (Dix, 1981). In the U.S.A. uncontrolled emissions were identified as an ongoing problem in municipal water treatment plants, with unknown consequences for exposure (Pellizzari, 1982). Similar problems have arisen in British municipal plants with respect to the reduction of VOC emissions, particularly concerning odour control. For example, despite the usage of a variety of ‘chemical’ controls on malodorous sewage streams (including scrubbing, oxidation and ozonolysis), the release of volatile compounds, including sulphur-containing organic thiols, polysulphides and hydrogen sulphide persisted as a source of concern and complaint (Slater and Harling-Brown, 1986). Selective improvements in industrial emission control have, however, been made within the last l&20 years. In the U.S.A., the petrochemical industry has steadily developed new technology to reduce VOC emissions. In the early design and use of primary wastewater treatment bays for industrial oil-water separation (for example the API Separator; Litchfield, 1971) volatile hydrocarbon emissions arising from wastewater treatment processes were not subject to control until the use of fixedroof ‘vapour-encapsulating’ structures and closed-loop vents were mandated by the USEPA (Vincent, 1979). Within the last decade or so, VOC losses to atmosphere from large-scale wastewater treatment plants have been the subject of heightened concern with respect to environmental control and public health, especially in the U.S.A. Today, the uncontrolled release of VOCs (termed ‘secondary fugitive emissions’) are increasingly subject to legislative controls by USEPA and other regulatory bodies (Springer et al., 1986). Perhaps one of the most challenging problems encountered by air quality scientists and occupational hygienists is the lack of suitable, consistent and scientifically enduring models for estimating emission rates of VOCs from wastewaters to the local airborne environment. Within the field of environmental control, appropriate models are needed for estimating transfer of VOCs from water to airborne compartments as part of emission loss assessments. Reliable models are also needed for performing residence time calculations on anthropogenically-derived VOCs as part of ecotoxicological risk assessments (Rogers et al., 1992). Accounting for VOC losses from water-based processes in the manufacturing industry (for example paint and dyestuffs) is also required by pollution control legislation. From an occupational health perspective, predicting volatilisation behaviour allows evaluation of personal exposure to hazardous VOCs, thus enabling adequate

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controls to be established (for example engineering design, use of respiratory protective equipment). Inevitably, because programmes of continuous air and water VOCs monitoring in wastewater plants will be limited in practical terms by constraints on time and resources, it is clearly desirable to have reliable models for predicting emission rates of toxic VOCs. Air/water

volatilisation

processes

In general, volatilisation models describing air/water interface transfer processes have not enjoyed widespread use by environmental scientists nor occupational hygienists in the study of environment and related health effects. Various commentators have suggested that this may be because such models and the implied processes are considered too theoretical, mathematically complex or requiring significant amounts of input data which are not readily available (Ciccioli, 1993; Bianchi, 1994). As with many predictive models which utilise differing input parameters and incur major assumptions about natural processes, they may yield variable and often conflicting results (Wadden and Berrafato-Triemer, 1989). Importantly, the status of volatilisation models has undergone much change since the early 1990s following major reappraisals of our understanding of physicochemical and meteorological parameters which control air-water exchange. In the late 1980s the principal models in common use to describe volatilisation processes from water bodies were of the (1) ‘stagnant film’, (2) ‘surface renewal’ and (3) ‘turbulent boundary layer’ type. Many of the commoner so-called ‘box’ variants are in fact variants of stagnant film and earlier surface renewal models. Although it is beyond the scope of this paper to go into these in greater detail, the interested reader can find a summary of each in Liss and Merlivat (1986). In particular, the stagnant film model, developed and refined by Broecker and Peng (1974), was widely applied in the U.S.A. Used throughout the 1970s and 1980s it also formed the basis of many commercial computer packages for VOC flux estimating. However, in the early 1990s further development and complementary fieldwork on surface renewal and turbulent boundary layer volatilisation processes significantly advanced the validity and effectiveness of models describing volatilisation processes from water (Upstill-Goddard et al., 1990; Watson et al., 1991). Simultaneously this new work also highlighted fundamental difficulties in the stagnant film models. Crucially, the stagnant film model did not accurately predict the correct dependence of gas transfer on molecular diffusivity nor account for significant non-linear response in the effects of wind-induced turbulence on volatilisation rates. The extent to which the model deviated from real situations varied according to meteorological conditions and the physicochemical properties of The literature also indicated that the organic compounds under examination. previous calculations of emission rates based on the stagnant film model may significantly underestimate actual flux levels, creating major implications for the reliability of environmental databases founded upon it (Nightingale, 1991). Some of the key findings of Upstill-Goddard et al. (1990) and Watson et al. (1991) were later examined and validated through extensive field measurements (Wanninkhof, 1992). Throughout 1992-93, in one of the first field studies intended to estimate fluxes of low-level VOCs between environmental (that is estuarine and

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riverine) waters and air under typical environmental conditions, contemporary VOC emission databases were reprocessed using the new surface renewal models and found to be up to 10 times higher than predicted by the stagnant film model (Bianchi and Varney, 1993; Bianchi, 1994). Given that concentrations of VOCs in wastewater plants are usually much higher than in marine environments, the consequences for emission rate estimates and their interpretation in terms of environmental and occupational health are potentially of greater relevance. Moreover, in this paper we present what we believe to be one of the first attempts at applying advances in the development of surface renewal and, where relevant, turbulent boundary layer models to a wastewater treatment bay under simulated conditions, in the context of an environmental hygiene study. SURFACE

RENEWAL

VOLATILISATION

PROCESSES-KEY

PRINCIPLES

In the study of gas exchange between air and water, the interface between the two phases is considered as a two-layer (film) system; the main resistance to gas transport arises from the gas and liquid phase interfacial layers across which exchanging phases transfer by molecular processes (Liss and Slater, 1974). Since transfer through the layer system is by molecular diffusion, Fick’s first law in the one-dimensional form (with z as the vertical direction) is applicable, that is F = -D dc/dz (where F is the flux of gas through the layer, D is the coefficient of molecular diffusion of gas in the layer material, and c is the gas concentration. The flux of an organic compound across the water-air interface is a product of the overall transfer velocity, k, and the extent of the disequilibrium between air and surface water concentrations (Preston, 1992). The transfer velocity for any given compound is dependent inter alia on factors such as Henry’s Law constant, the Schmidt number, windspeed and water temperature (Upstill-Goddard et al., 1990; Watson et al., 1991). Additional parameters which influence the rate of volatilisation of VOCs across the water-air boundary include aqueous solubility, vapour pressure, diffusivity, wave action and bubble penetration (Mackay and Yeun, 1983; Liss and Merlivat, 1986; Wadden and Berrafato-Triemer, 1989). Some of the most important relationships governing exchange processes can be summarised as: F = k(r),AC

(1)

where AC is the concentration difference driving the flux (fl and k(T),,, is the total transfer velocity (that is the gas exchange constant). The concentration difference is the difference between the observed aqueous concentration and the calculated concentration assuming the gas is in equilibrium with the atmosphere and obeys Henry’s law. It can be specifically expressed as: AC = C,H-’

- C,

(2)

where C, and C, are the gas concentrations in air and water, respectively, and H is the dimensionless and temperature-dependent Henry’s Law constant. The total transfer velocity can therefore be described as: I/‘+T)w = 1/ak, + 1/Hk,

(3)

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where k, and k, are the individual transfer velocities for chemically unreactive gases in air and water phases, respectively, and a is a factor which quantifies any enhancement of gas transfer in the water due to chemical reaction. Equation (3) can be expressed in terms of resistancesas: R(T)w = rw + ra

(4)

where Rp,,( = l/k(r),) is the total resistance, with r,( = I/ak,) and r,( = l/Hk,) the resistancesof water and air phasesrespectively. By substitution of appropriate values for k,, k, and a in Equation (3) it can be demonstrated that for many gaseseither rw or ra is dominant. Gases for which r, is the dominant resistance to transfer mostly have high Henry’s Law constants (that is low solubility) and a is roughly equal to 1.0 [for example CH4, C02, CH31, (CH&S)]. This category includes VOCs such as methane and dimethylsulphide which are often found in industrial and municipal wastewaters, and for these compounds, k, is the transfer velocity which controls their air/water exchange. In this study, most attention was focused on examining the effects of continuous air movement over the surface of a body of water releasing VOCs to its local environment using surface renewal concepts, typical of the environment in which wastewater plants operate. Models of these transfer processesindicate that k, is proportional to friction velocities in air (U*) and also to windspeed (U). Similarly, k, is also proportional to the ratio of the transfer coefficients for momentum (kinematic viscosity, v) and mass(molecular diffusivity, 0) to the power -2/3 (that is k,aSc-2’3 at U= < 5 m s- ’ or U* = < 0.3 m s-’ (that is, a ‘smooth surface’ regime) according to the definition of Liss and Merlivat (1986)). SC is the Schmidt number, v/D, a dimensionless ratio which is typically in the range of 0.5-2.0 for gasesand 500-2000 for liquids. A useful feature of the Schmidt number is that it also expresses temperature dependence, notably for liquids in which case SC decreasesrapidly with increasing temperature, as diffusivity rises and viscosity falls. To estimate k, it is assumed the surface is smooth and that continuity of stress across the interface is attained in order to convert the velocity profile in air to an equivalent profile in water, that is: k, = 0.082Scezi3(r,/rw)1’2 U*

(5)

where ra and r, are the densities of air and water. For this model, k, is proportional to D213.Wind tunnel experiments have shown that the relationship between k, and SC is not constant, and that under unsteady-state penetration mass-transfer conditions, a lower dependence is indicated (that is k, is proportional to SC-~‘*) for a ‘rough surface regime’ where the actual value of U=4-13 m s-‘, and U* ~0.3% 0.7 m s-’ (which represents a considerable increase in the slope of k, versus windspeed). Here, the Schmidt number gives the transfer velocity (that is gas exchange constant) as proportional to approximately D”.5. At windspeeds much above U= 10 m s-i (that is which corresponds to the breaking-wave ‘bubble’ regime associated with high winds over the water surface) gas transfer rates are considerably enhanced, as confirmed by the application of dual-tracer experiments in rough water environments (Watson et al., 1991).

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Assuming the gas exchange constant (koJ dependent on the wind speed, three relationships using carbon dioxide as the model gas, are:

is strongly and non-linearly which describe such variation

k(T)w = 0.17U (where U < 3.6 m s-‘)

k(qw =

2.85U - 9.65 (where 3.6 < U < 13 m s-l)

kcTJw = 5.9U-

49.3 (where c! > 13 m s-l)

(6) (7) (8)

where kcTjw is in cm hh’, and CTis in m s-r. This model has been successfully used to describe air-sea exchange fluxes ranging from low energy water bodies to large scale open-ocean air-sea exchange associated with high wind speed and significant surface turbulence (Wallace and Wirick, 1992).

EXPERIMENTAL

DETAIL

AND

MONITORING

SURVEYS

Volatilisation measurements were carried out over a 1Cmonth period using a redundant wastewater holding bay in the eastern Southampton dockland area (that is an outdoor setting) access to which was made available by a commercial marine engineering company. Meteorological variables and water temperature were monitored continuously in addition to the aqueous and airborne concentrations of selected VOCs, representative of those compounds frequently reported in municipal and industrial waste streams (Aggazzotti and Predieri, 1986; Lawrence and Foster, 1987; Thomas et al., 1987; Hazard et al., 1991; Rogers et al., 1992). Samples were collected over 8-h intervals under a variety of weather conditions spanning spring through to winter. Under circumstances intended to model severe water contamination, samples were taken over 15-min periods to estimate the possible consequences for short-term exposure. Average air temperatures ranged through the periods of sampling from -21” to 32.2”C. Experimental

methods

The wastewater holding bay was an embedded, fined concrete structure of approximate dimensions 18x 10 m with depth 6.5 m, of which a ‘lip’ 1.4 m high protruded above a ground-level concrete apron. The bay was gated at either end so as to allow small vessels (and estuarine water from the Itchen sub-estuary) to enter at one end and leave at the other. Contaminated water (post-experiment) was rerouted to a dirty water holding bay. The basic layout shared many similarities in structure and physical dimensions with municipal or industrial wastewater holdingbays or oil/water separators. Water depth was recorded during each sampling period allowing total water volume (and where necessary, residence time) to be calculated. Water temperature was measured using mercury-in-glass thermometers. Meterological factors such as relative humidity (Oh) and air temperature (dry bulb) were measured using a portable thermohygrograph (Casella Ltd, Bedford, U.K.). Wind velocity profiles were measured at various locations across the bay using a rotatingvane anemometer (Casella). Meteorological data were checked daily with the Southampton Weather Centre. Sampling was avoided during times of prolonged

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rainfall due to the difficulties foreseen in quantitatively accounting for its potential effects (for example temporary dilution of VOCs in surface water, VOCs ‘washout’ effects of wet precipitation). Water sampling. Replicate water samples (1 1.) were drawn from the top 0.5 m depth for analysis at 15-min and hourly intervals for storage in sealed, insulated boxes cooled to 4°C. The majority of water samples were taken from the mid-point of the bay (approximately 1 m towards the centre) where natural mixing conditions were found to be relatively stable and free from internal turbulence (as previously determined by observation of fluoroscein (BDH-Merck, Eastleigh, U.K.) dye spiking experiments and water flow measurements using a current meter (Vector Instruments, Oxford, U.K.). Water samples were taken to the laboratory in sealed glass vessels (with no headspace) and analysed within 12 h of sampling. Analysis for VOC content was conducted using a dynamic headspace open-loop multi-sorbent bed ‘purge-and-trap’ method with automated thermal desorption (Perkin-Elmer ATD-50, Beaconsfield, U.K.) and BP-l capillary column-CC with simultaneous FID/mass-spectral detection. A fuller description of the analytical details and conditions employed, including calibration procedures, method performance and quality assurance details, are published in Bianchi et al. (1989) Varney and Bianchi (1990) and Bianchi et al. (1991) and will not be repeated. Air sampling. Air samples were collected at a height of 2.0f0.5 m above the water surface using sampling pumps (low-flow Accuhaler 808 model, MDA, Lincolnshire, Illinois, U.S.A.; and Flo-Lite pumps, MSA, Pittsburgh, PA, U.S.A.) connected to Perkin-Elmer ATD-50 sampling tubes packed to the Supelco ‘Carbotrap 300 specification’ [that is Carbotrap C (250 mg) 20/40 mesh; Carbotrap B (175 mg) 20140 mesh; Carbosieve S-III (105 mg) 60180 mesh] supplied by Supelco Inc (Supelco, Bellefonte, PA, U.S.A.). Air sampling was carried out by suspending sampling pumps on tripods to which short aluminium ‘poles’ were attached so as to ensure that the sampling tubes were correctly positioned within the body of air immediately above the water surface. Air samples were taken to coincide with water sampling events at 15-min (Flo-Lite pump; pump flow rate = 500 ml min-‘) and 8-hr intervals (MDA Accuhaler pump; pump flow rate = 50 ml min-‘). Air sampling tubes were capped with Swageloka end-caps and sealed in glass-jars which were then stored in separate boxes at 4°C for analysis within 12 h of sampling. Analysis was carried out on the sampling tubes using Perkin-Elmer ATD-50 thermal desorption and cGC-FID/MS techniques, very similar to methods used for water samples. Fuller details of the sampling and analytical methods employed here, including calibration and quality assurance steps used for airborne VOC samples were based on the outline protocols given in CONCAWE (1986) and HSE (1989) and further developed for environmental air sampling by Bianchi and Varney (1993). Spiking experiments

Sampling measurements were carried out ‘background’ VOCs in estuarine water from airspace above it. Aqueous solutions of the prepared by dissolving the pure compounds

to determine the concentrations of which the bay was filled, and the VOC compounds of interest were (AnalaR and HPLC spectrophoto-

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metric grade, Aldrich Ltd, Blandford Forum, U.K.) in water and injecting them into the bay at a depth of 1 m using a motorised pump and braided steel-mesh hose. For compounds that were slightly soluble and denser than water, saturated solutions were prepared, diluted to an appropriate concentration and then injected into the bay. In further experiments, drums of heavily contaminated water (for example marine diesel, fuel oil and gasoline-contaminated wastewater) were added in order to study the variation in volatilisation fluxes arising from the increased levels of contamination.

RESULTS AND DISCUSSION A summary of the air and water concentration data for the VOC substances of interest is shown in Table 1. The data presented in Table 1 are representative of the ‘low concentration’ spiking experiments carried out by adding relatively low-tomoderate concentrations of each of the VOCs of interest where the concentrated aqueous solutions added to the bay were typically 5 1. of spike solution (1000 mg I.-’ of each compound), yielding final aqueous concentrations in the approximate range of 5-15000 ng 1.-l per component over the experimental duration (that is N=73, over 14 months). These concentrations were intended to represent relatively low levels of contamination found in many typical influent waters to wastewater bays and their discharge points. Table

1. Typical

air and water

concentration ranges of selected VOCs in air (C,) from wastewater bay spiking experiments G

voc n-Hexane n-Decane Methylcyclohexane 2,2,4-Trimethylpentane Benzene Toluene Ethylbenzene o-Xylene 1,2,4-Trimethylbenzene Naphthalene Carbon tetrachloride Chloroform Trichlorofluoromethane 1,1,1 -Trichloroethane Trichloroethylene Methyl mercaptan Dimethyl sulphide Dimethyl disulphide Butanone-2 Butanol-2

(Min-Max)* 0.05-33.2 0.07-13.6 0.02-20.2 0.05-24.3 0.10118.5 0.34-65.7 0.29-60.3 0.36-58.3 0.40-50.0 0.44-28.3 0.23-27.3 0.77-99.3 0.01-20.2 0.75-47.5 1.21-59.4 O.Od95.3 0.05-99.2 0.10-93.3 0.35-8.5 0.28-7.4

and water

(C,)

derived

cw

(Mean)? 12.3 8.4 7.6 11.0 25.3 33.7 30.3 28.4 26.7 13.4 15.6 47.0 9.3 25.3 30.3 44.5 55.3 50.3 4.5 3.5

GMf 6.0 3.3 3.0 5.6 11.9 15.9 14.1 13.3 12.3 6.5 7.3 23.5 4.5 12.2 14.3 20.4 27.5 25.6 2.3 1.8

The data shown are based on a pool of N= 73 ‘low concentration’ weighted average concentrations. Concentration data are expressed *Arithmetic range shown as Min-Max values obtained. tArithmetic mean. IGeometric mean.

(Min-Max)* 8.84400 2.7-2203 3.3-1920 2.1-2504 lo.68320 17.410 122 15.2-10001 12.8-11030 10.2-8684 5.3-3686 12.3-6478 93.42 I 300 15.6-3647 10.2-8500 20.3-9403 27.3-l 1020 18.2-16304 29.3-13000 15.66900 18.8-7530 experiments as ng I.-‘.

(Mean)t 1020 964 873 1285 4672 5602 4975 5204 4664 1405 3692 10203 1502 4633 4304 6422 8377 7002 3500 3790

GMf 945 467 420 640 2202 2829 2704 2474 2645 693 1578 4365 745 2403 2102 3404 4355 3680 1200 1540

and relate to 8-h time-

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The highest recorded concentration was for chloroform (C,=99.3 ng 1.-l, corresponding to C, = 21300 ng 1.- ‘), a major contribution of which came from the influent estuarine water used to flood the bay. This is consistent with the results of Aggazzotti and Predieri (1986) who identified comparable levels of chloroform in municipal water streams where it also represented the most ubiquitous compound found in the highest concentration. Elevated levels of chloroform had previously been reported by Bianchi (1994) and Dawes and Waldock (1994) in the Itchen subestuary to Southampton Water, mainly as a by-product of water chlorination and industrial processes. Organosulphide levels in ‘background’ water (and in air samples) were also higher than anticipated. Up to 25% of the total amount of methyl mercaptan, dimethylsulphide (DMS) and dimethyldisulphide (DMDS) measured in the bay were also derived from surface water in the Itchen. Water quality varies significantly within the estuary (Soulsby et al., 1985) highlighting the need to account for extranneous sources of VOCs. The sources of the organosulphides were traced to a nearby sewage outfall and unrelated biological decay processes of plankton such as the photosynthetic ciliate (Mesodinium rubrum). Among the alkylbenzenes, for example, toluene was also found in the highest concentrations, particularly in air. The lowest airborne concentrations recorded were for butanone-2 and butanol-2, which may be expected given their hydrophilic, polar nature. Theoretical equilibrium concentrations Given the analytical data set made available by the air and water concentration surveys, it was possible to estimate concentration differences (AC) across the airwater interface. By using the theoretical Henry’s Law constants for each compound (Equation 2), theoretical equilibrium concentrations were calculated (that is the aqueous concentration in theoretical equilibrium with the concentration measured in air) using the Henry’s constant protocol described by Nightingale (1991). A summary of the theoretical equilibrium concentration values are shown in Table 2. For all compounds studied, the actual aqueous concentration significantly exceeded the theoretical air-water equilibrium concentration predicted by achievement of interphase equilibrium, showing that, despite the relatively low range of aqueous concentrations, the water was supersaturated with respect to atmospheric transfer. Thus, in terms of Equation (2) C, is mainly > > C&-l. At these aqueous concentrations, VOC movement would therefore be highly unidirectional (that is from water to air), with the atmospheric ‘compartment’ representing the major sink. This is an important finding, since under different environmental conditions the direction of transfer may be reversed (that is from air to water). For example it was previously shown by Bianchi and Varney (1993) that under certain conditions following episodes of elevated airborne pollution, vapour-phase toluene may cross the ‘air-water’ interface, representing a source of toluene to surface waters (that is where C,H- ’ > C,. VOCjux

calculations

Fluxes were derived by calculating the respective C, and C, data for each component, allowing for maximum and minimum recorded wind speed across the surface of the water body. Using this data, gas exchange constants k(r),) were

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Table 2. Equilibrium

concentration values for representative air and water VOC concentration data

voc n-Hexane n-Decane Methylcyclohexane 2,2,4-Trimethylpentane Benzene Toluene Ethylbenzene o-Xylene 1,2,4-Trimethylbenzene Naphthalene Carbon tetrachloride Chloroform Trichlorofluoromethane I ,I,]-Trichloroethane Trichloroethylene Methyl mercaptan Dimethylsulphide Dimethyldisulphide Butanone-2 Butanol-2

Estimated equilibrium concentration 0.26 0.03 0.66 0.12 210.8 187.2 121.2 118.3 133.5 1595.2 14.4 522.2 1.86 105.4 101.0 Ill.3 1843.3 251.5 225.0 3500.0

Measured aqueous concentration*

Calculated Henry’s Law constant?

1020 964 873 1285 4672 5602 4975 5204 4664 1405 3692 10232 1502 4633 4304 6422 8377 7002 350 379

47 252 11.4 91.2 0.12 0.18 0.25 0.24 0.20 0.0084 1.08 0.09 5 0.24 0.3 0.4 0.3 0.2 0.02 0.01

Values are estimated from arithmetic mean data for air (C,) and water (C,) for the data set (N= 73). Concentration data are expressed as ng 1.-l. *Measured aqueous concentration ng I.-‘. tHenry’s Law constants calculated according to Liss and Slater (1974), Sauer (1978) and Nightingale (1991) corrected for temperature and pressure.

calculated for each component under the prevailing conditions. As these values relate to the model gas CO*, a correction must be applied for other volatile compounds to compensate for differences in molecular diffusivities. There are two ways of accomplishing this. Firstly, by using the ratio of the square roots of the molecular weights of CO* and the organic compound, as detailed by Liss and Slater (1974) and Nightingale (1991); or secondly, by examining the variation of the gas exchange constant with both the compound of interest and temperature, which can be described by a power dependence on the Schmidt number as KI/K2= (SC&~)” (Watson et al. (1991). For a windspeed of more than 3.6 m s-l, the power dependence (n) is approximately l/2. As there are few predetermined values available for molecular diffusivities, the molecular mass correction was applied to values of KcTjw in this body of work. Flux transfer rates were significantly a function of wind speed and VOC concentration differences between air and water phases. In the Southampton Dock area, wind direction is usually from the south-west for more than 75% of the year, and normally exceeds 2.3 m s-l for more than 80% of the time (Bianchi, 1994). During winter months (that is which we classed as December through to March), wind speeds during sampling exercises ranged from 3.613.9 m s-i. In summer months (that is classedas May to September) wind speedswere much lower, from 1.9-4.8 m s-i. Within the ranges of concentration tabulated in Table 1, fluxes for a broad range of VOCs ranged from approximately 0.04x IOh to 9.0x lop8 g cm-* h-‘. A range

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Table 3. Flux estimates for typical winter (5/2/95) and summer (23/7/95) weather conditions

(W/95)*

voc n-Hexane n-Decane Methylcyclohexane 2,2,4-Trimethylpentane Benzene Toluene Ethylbenzene o-Xylene 1.2.4-Trimethvlbenzene Naphthalene Carbon tetrachloride Chloroform Trichlorofluoromethane 1, 1, 1-Trichloroethane Trichloroethylene Methyl mercaptan Dimethylsulphide Dimethyldisulphide Butanone-2 Butanol-2

c,

Gv

18.9 11.4 17.1 20.1 41.9 60.7 58.3 53.7 45.6 20.3 15.1 80.0 15.1 36.9 44.5 58.3 69.7 67.4 4.2 4.9

3295 2105 1763 2209 7095 8654 7920 7562 6827 3057 4929 15300 3005 6250 8133 8745 14321 11450 5880 5956

GW/Wt

KCr)WFlUX$ 10.21 7.95 9.58 8.87 10.34 9.87 8.79 9.19 8.64 8.36 7.64 8.63 8.08 8.20 8.27 13.66 12.03 9.76 11.16 11.01

336.4 167.3 168.8 195.9 692.8 820.9 675.7 674.4 570.2 76.2 375.4 1243.8 242.6 499.9 660.4 1181.5 1694.9 1084.6 632.8 116.3

‘A

9.8 4.7 5.0 6.1 15.0 22.3 23.5 20.4 19.3 11.1 12.0 39.3 8.1 20.0 24.3 30.1 50.2 42.3 2.1 1.8

G

560 420 440 620 2150 2720 2000 1950 1920 1700 1495 5500 655 2350 2090 3605 4107 3595 1190 1904

&qw

0.40 0.31 0.38 0.35 0.40 0.39 0.35 0.36 0.34 0.33 0.30 0.34 0.32 0.32 0.33 0.54 0.47 0.38 0.44 0.43

FW

2.24 1.30 1.67 2.17 8.10 10.12 6.67 6.71 6.20 1.07 4.45 16.87 2.09 7.25 6.63 19.06 18.52 12.86 4.77 0.44

Air and water concentration ranges of selected VOCs are shown for air (C,) and water (C,) concentrations derived from sampling and analysis. Experimental data are based on 8-h time-weighted average concentrations. &,,, are expressed as cm h-r. Concentration data are expressed as ng I.-‘. *Data gathered on 5/2/95. Mean wind speed (S-h)=8.4 m s-r, mean air temp (8-h) =2.5”C, mean water temperature = 5.3”C. tData gathered on 23/7/95. Mean wind speed (8-h) = 3.3 m s-‘, mean air temp (8-h) = 30.3”C, mean water temperature = 18.2”C. SAlI flux data are expressed x10-r’ (g cm-* h-t).

of flux data spanning a typical summer and winter day are shown in Table 3. The flux data reflect and reinforce marked concentration differences which were observed between seasons, and support the premise that volatilisation in a relatively narrow open body of water (such as a wastewater bay) may still occur at a relatively fast rates, even during colder winter months when water temperatures are low and surface evaporative mechanisms are hindered. As a general observation, volatile contaminants entering and leaving wastewater systems tend to be proportionally higher in winter months due to increased usage of fossil fuels for space heating, reduced levels of in situ biodegradation (which removes VOCs), and increases in general runoff (Gschwend et al., 1982; Leaderer, 1982; Bianchi, 1994). Given the greater concentrations of VOCs in wastewaters (and in the relative values of AC, - C,) during winter, in tandem with enhanced rates of surface renewal immediately above the air-water interphase, values of K(r), were found to be 2&30 times higher in winter than in summer. This is not necessarily an obvious finding as intuitively many observers might assume that the higher air and water temperatures associated with summer months also result in higher removal rates from water. Although water temperature correlates directly with volatilisation potential for most VOCs, the effect of temperature can be shown to be lower in relative magnitude than the effect of wind speed over the surface of a water surface. Inherently, the work of

448

A. P. Bianchi and M. S. Varney

Upstill-Goddard et al. (1990) and Watson et al. (1991) demonstrates that volatilisation is a ‘faster’ process than evaporation alone, with the Schmidt number exerting a major influence on the transfer rate. The relationship between temperature and the transfer coefficient can be usefully explained by employing a modified variant of the Mackay and Yeun (1983) mass-transfer equation which incorporates the Schmidt number directly, that is K(T)w = 1.0 x 1o-6 + 34.1 x Io-4u*sc,0.s (where U* (friction velocity)>0.3

(9)

m SK’)

and U* = (6.1 + 0.63Ui0)~.~Uio. (where Uio is the wind speed at a nominal height of 10 m). Benzene, for example has a SCL= 1021 (at 20°C). By employing a typical value of 0.42 (of V*) for winter, a flux rate of 16.5 cm h-’ is obtained. The ScL value increases with increasing alkylation of the benzene ring (for example SC= toluene = 1155) and hence flux rates are progressively lower for Cs- and C4alkylbenzenes. ScL increases with decreasing water temperature and hence broad estimates can be made of the variation of flux rate with water temperature. The precise quantitative relationship between Schmidt number, temperature and related environmental variables is not yet fully understood but it can be shown, for example that if SCLincreasesby 2.8% per degree Centigrade decrease, the Schmidt number for benzene at typical winter temperatures of about 70°C is predicted to be about 1650. At this theoretical value, the magnitude of Kcr,w (benzene) decreasesfrom 16.5 cm h-’ (at 2O’C) to 13.0 cm hh’. Individual flux rates are also highly dependent on the absolute concentration of contaminant in the water phase. This may be illustrated by comparing net fluxes from water bodies which contain moderate concentrations of VOCs with those from relatively pristine water bodies such as open sea water. For example, Nightingale (1991) performed identical estimates for volatile organohalogens in the southern North Sea, and estimated a net daily flux of 0.11 x lo-” g cm-’ hh’ for chloroform. By way of comparison, the net daily fluxes obtained for chloroform in our study were up to 1244x lo- i” g cm-* hh ‘, between 150 and 12 000 times higher for summer and winter months respectively, highlighting the significant differences in rate and total mass of transfer which is theoretically possible for the same compound. In terms of occupational health and environmental issues, these results also suggest that volatilisation processeswithin wastewater bays may, under conditions determined by AC= C,H-l-C,, their respective concentrations, KcTjw, and air and water temperatures, represent important factors which may determine personal exposure to individual (or total) VOCs. For example, crude estimates based on the experimental data from this study suggest that where XC,>, 5 mg l.- ‘, (as total VOCs) in water (that is levels commonly encountered in wastewater plants), CC, may reasonably be expected to reach or exceed 50 mg m-’ (as total VOCs) in air within the activity zone of workers, under moderate wind speed conditions (for example 3-6 m s-l). More precise estimates of exposure to individual compounds

Volatilisation

processes

in wastewater

treatment

plants

449

should be readily available when performing finer estimates. In theory, it should also be possible for occupational hygiene personnel to make sufficiently useful predictions of likely airborne concentrations based on measurements (or good estimates) of aqueous VOC concentration and windspeed alone. Contamination

(spill)

events

Importantly, increased loadings of contaminant material (including hydrocarbon or solvent-based fluids) are relatively common occurrences in municipal and industrial wastewater plants and can take place at any time, particularly after a spill event. Such circumstances may arise after a process plant upset or following a civil, traffic-related or industrial incident (for example fire, emergency release). Depending on the nature of the VOCs in the influent water and prevailing weather conditions, these factors will have a major impact on volatilisation rates. Further experiments were carried out by injecting large volumes (200-300 1.) of contaminated effluent water from local shipping activities (for example marine fuel oil, gasoline and dieselcontaining ballast water) into the bay from large steel drums using drum pumps. Sampling was carried out within 15min time ‘windows’ within 5 min of charging the bay, and for longer periods of time extending up to 8 h. Representative results of a sample ‘injection’ of a mixture of ballast water severely contaminated by kerosine and raw gasoline are shown in Table 4. The results indicate that at relatively moderate values of Kc-r,W (that is 2.33.7 cm h-i) proportionally high flux rates can be achieved ‘driven’ mainly to the significant gradient (high AC) between air and water-phase concentrations (in AC = C,H-’ - C,), especially in the first 15 min. Moreover, as the results suggest, personnel working within the immediate zone would probably require respiratory protection or limited work periods to prevent or reduce the risk of high single- and Table

4. Flux

estimates

voc n-Hexane n-Decane Benzene Toluene Ethylbenzene o-Xylene 1,2,4-Trimethylbenzene Naphthalene

for a simulated contamination event following taminated by petroleum-fluids (15min

period)*

Cal

Cd

KCYW

111 52 1.56 242 219 215 127 I

124 183 137 106 105 104 84 48

2.86 2.26 2.91 2.78 2.50 2.58 2.42 2.36

discharge

of wastewater

con-

(8-h period)t Flux7

Cal

Cd

Kmw

35 41 40 43 26 21 26 11

2.0 0.9 3.9 4.7 3.5 4.1 0.9 0.1

3.5 4.7 5.1 6.7 1.5 2.1 0.7 0.3

3.67 2.90 3.12 3.57 3.21 3.31 3.10 3.03

FIN 1.3 1.4 1.9 2.4 0.5 0.7 0.5 0.1

Air and water concentration ranges of principal VOC are shown for air (C,) and water (C,) concentrations derived from sampling and analysis. Experimental data are based on 15-min and 8-h sampling periods. Kcnw are expressed as cm hh’ corrected according to mean wind speed. Concentration data are expressed as ng I.-‘. mean air temp 15-min= 17.5”C, mean water *Mean wind speed (15-min period)=4.8 m s-l, temperature = 10.2”C. tMean wind speed (8-h)= 5.2 m s-‘, mean air temp (8-h) = 18.2”C, mean water temperature= 10.7”C. SC, expressed as x lo3 ng I.-‘. SC,,, expressed as x106 ng I.-‘. TAXI flux data are expressed x IO-’ (g cm-* h-l).

450

A. P. Bianchi and M. S. Varney

mixed-substance exposures on both a 15-min and full-shift basis. Fluxes during contamination events are likely to exceed normal operating conditions by several orders of magnitude. For example, during the first 15 min of the spill event, flux rates ranged from 1143x 10K5 g cmU2 h-l, falling to an overall average of O.l2.4x 10m5g cmW2 h- ’ after 8 h. Interestingly, even after 8 h of volatilisation, flux rates were still significantly higher in the bay than for ‘low contamination’ conditions (as shown in Table 3) by magnitudes ranging from lx lop5 to 100x 10e5 g cme2 h-i. This is a noteworthy feature of the volatilisation behaviour since it suggests that a high inhalation risk may persist for some time after a contamination event, perhaps long after the point at which exposure controls are removed. In assessingthe data as a whole, a further key factor requiring consideration concerns the relative differences in QrjW between different VOCs, and the effect this has when making predictions about ‘volatility rates’ and subsequent potential risk. For example, among the alkylbenzenes, benzene exhibits the highest value of K~r),,,, a feature which enhances its transfer from water to air under most practicable situations (that is where C, is mainly > > C,H- ‘). For all alkylbenzenes, values of KcrjW reduce with increasing alkylation of the benzene ring. Given the relatively greater chronic health risks associated with benzene compared to its alkylbenzene counterparts, this feature would need to be adequately addressedduring exposure risk assessment. Among the volatile organosulphides, values of K(r),+. are highest for most low molecular compounds with high vapour pressures(for example methyl mercaptan, DMS). In particular, these factors may help to explain the labile nature of highly malodorous methyl mercaptan (including ethyl and propyl mercaptans) within municipal sewage works and waste transfer and recycling stations where these compounds are frequently found, enhancing the probability of public odour nuisance complaints (Slater and Harling-Brown, 1986; Bianchi, 1994). Taken together, the foregoing discussion points suggest that a valid exposure risk assessmentwould require the occupational hygienist to obtain a sound database of aqueous concentration data in addition to airborne data, the latter activity being the ‘normal’ premise of the practising hygienist. From our experience in assessing volatilisation behaviour in open waters, wastewater lagoons, waste treatment plants and industrial oil-water separators, it seemsa valid and achievable precaution to develop local predictive models which describe volatilisation fluxes and anticipated airborne concentrations of commonly encountered VOCs under a range of operating conditions regarded as ‘routine’ for the plant in question. Furthermore, these results reinforce the necessity in considering the use of controlled encapsulation, venting and filtration systems as a management strategy for VOCs in wastewaters, as opposed to a dilute-and-disperse approach which calculations indicate may exacerbate an already existing inhalation risk or enhance a nuisance odour risk for certain types of VOCs. Research carried out as part of this and earlier studies indicates that these volatilisation models should also usefully apply to indoor water bays, tanks or receptacles as much as they do to outdoor water bodies. New work on indoor paint spraying tasks (unpublished at the time of writing) indicates that the surface renewal model predicts airborne concentrations of VOCs (at levels of approximately 20-

Volatilisation

processes

in wastewater

treatment

plants

451

500 mg rnp3 + 25%) associated with ‘wet collection’ drainage sluices used in manual spraying activities adjacent to spray booths. Perhaps one of the main factors which detracts from the validity of the model lies in the existence of competing ‘sinks’ for VOCs. For example, the presence of high concentrations of waterborne suspended solids in treatment plant bays (inorganic flocculant, sand particles, organic sewage particles) may act as selective adsorbent sites for hydrophobic VOCs, reducing the solute fugacity or partial pressure, and so reducing the volatilisation rate. Adsorption to sediments results in removal from the liquid phase and incorporation into a solid phase. Exchange may also take place with and between resuspended particles at varying rates, depending upon a variety of parameters. However, in a series of field measurements and modelling experiments examining the extent of adsorption within water treatment plant effluents, Bianchi (1994) demonstrated that even under conditions of high suspended solids (that is 1200 mg l.- ‘) with correspondingly high fractional organic contents (that is approaching lOO%), the maximum amount of VOCs removed by adsorption was 10% (of total mass) for chloroform, and 5% (of total mass) for most volatile aromatics (for example including benzene, toluene and C2-alkylbenzenes) and organohalogens (for example including chloroform and carbon tetrachloride), where actual aqueous concentrations were between 1 and 10 pg 1.-l. It is therefore unlikely that adsorption would represent an important competing sink nor significantly reduce volatilisation rates under conditions in which inhalation exposure represented a potential risk. Photo-oxidation processes have also been considered as a potential ‘sink’ for VOCs. It is, however, unlikely that photo-oxidation reactions would occur at fast enough rates to remove VOCs. Many of the final photo-oxidised products of anthropogenic volatile hydrocarbons are aldehydes (Grosjean et al., 1978; Howard et al., 1991). In particular some alkanes and alkenes oxidise to saturated aldehydes (Cox et al., 1980) none of which were identified during this study.

SUMMARY

AND

CONCLUSIONS

This study has provided new and quantitative experimental data describing the variation in gas exchange constants and water-to-air fluxes for a broad range of hazardous VOCs commonly encountered in municipal and industrial wastewaters under varying environmental conditions. The data were derived using a relatively new volatilisation model which representatively accounts for the effect of physicochemical characteristics and meteorological factors exerting major controlling influences on volatilisation behaviour. With hindsight, the value of obtaining a broad experimental data set over a year under changing climate conditions and in an environment which closely resembled a real wastewater bay (as opposed to laboratory simulations) cannot be underestimated. We believe that, despite potential gaps in the experimental protocol, the data provide a useful platform from which to examine the relationship between gas transfer velocities and wind speed as predicted by Upstill-Goddard et al. (1990) Watson et al. (1991) and Wanninkhof (1992). Further confirmation or comparison of the experimental findings was made difficult by the apparent lack of data in the literature concerning similar studies of this

452

A. P. Bianchi

and M. S. Vamey

nature, which may indicate that this topic remains a new and still emerging field in the discipline of occupational hygiene. For all compounds we studied, the aqueous concentrations used to model typical wastewater bay conditions significantly exceeded the theoretical air-water equilibrium concentration predicted by achievement of interphase equilibrium. Despite what we considered to be quite low absolute aqueous concentrations of VOCs, it seems likely that most wastewaters will be supersaturated with respect to atmospheric transfer. In most cases, aqueous concentrations of VOCs in wastewater bays would probably exceed their theoretical air-water equilibrium concentrations. The total set of VOCs data, including concentration differences (AC) between air (C,) and water (C,) phases, gas exchange constants (kcrjw), and fluxes were calculated using the most up-to-date ‘surface renewal’ equations. To the best of our knowledge, these models have been proven to be reliable although new work is needed to examine their applicability to occupational environments and in particular to a wide range of waterborne compounds used by industry. Within the ranges of concentration commonly encountered in this study, fluxes for most VOCs ranged from approximately 0.04x10K8 to 9.0x lop8 g cm-* hh’, the highest values usually being observed with alkylbenzene and organosulphide compounds. Furthermore, given the higher concentrations of VOCs in wastewaters during winter associated with greater windspeeds immediately above the air-water interphase, values of Kcr,w were 20-30 times higher than in summer. These findings reinforce general conclusions that programmes designed to minimise VOC emissions to air must account for mechanisms which enhance volatilisation and incorporate precautionary strategies around organic vapour control. The results of our basic experiments intended to represent ‘contamination spill events’ indicated that at relatively moderate values of Kc-~-,~(that is 2.3-3.7 cm hh’) high flux rates are observed due to the significant gradient (high AC) between air and water-phase concentrations (that is where AC = C,H- I - C,), especially in the first 15 min. Moreover, as our results highlight, personnel working within the immediate vicinity may be at risk of higher levels of exposure than anticipated during such occurrences. We believe that these data should serve as a useful platform from which to encourage the use of volatilisation modelling by occupational hygienists carrying out risk assessments in a variety of wastewater treatment operations. Through appropriate application of the theoretical models described, reasonable predictions and estimates can be made of potential VOC exposure scenarios to workplace personnel employed in wastewater storage and treatment activities. Acknowledgemenrs-The authors would like to thank Mr J. Leach and Mr A. Chidwick (Condive Marine Co., Southampton) for access to and use of the water bay utihsed for the field experiments, for assistance in operating the equipment and arranging supply of the contaminated wastewater materials. The authors would also like to thank Prof. P. Liss and Dr P. Nightingale (School of Environmental Sciences, University of East Angha) for helpful comments on the use of the volatihsation models.

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