Sampling and physico-chemical analysis of precipitation: a review

Environmental Pollution 120 (2002) 565–594 www.elsevier.com/locate/envpol

Review

Sampling and physico-chemical analysis of precipitation: a review Sagar V. Krupa* Department of Plant Pathology, University of Minnesota, 495 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108, USA Received 20 December 2001; accepted 22 February 2002

‘‘Capsule’’: This is a comprehensive review of methods for sampling and physico-chemical analysis of rain, cloud and fog water and snow, as they relate to atmospheric processes and environmental impacts assessment. Abstract Wet deposition is one of two processes governing the transfer of beneficial and toxic chemicals from the atmosphere on to surfaces. Since the early 1970s, numerous investigators have sampled and analyzed precipitation for their chemical constituents, in the context of ‘‘acidic rain’’ and related atmospheric processes. Since then, significant advances have been made in our understanding of how to sample rain, cloud and fog water to preserve their physico-chemical integrity prior to analyses. Since the 1970s large-scale precipitation sampling networks have been in operation to broadly address regional and multi-regional issues. However, in examining the results from such efforts at a site-specific level, concerns have been raised about the accuracy and precision of the information gathered. There is mounting evidence to demonstrate the instability of precipitation samples (e.g. with N species) that have been subjected to prolonged ambient or field conditions. At the present time precipitation sampling procedures allow unrefrigerated or refrigerated collection of wet deposition from individual events, sequential fractions within events, in situ continuous chemical analyses in the field and even sampling of single or individual rain, cloud and fog droplets. Similarly analytical procedures of precipitation composition have advanced from time-consuming methods to rapid and simultaneous analyses of major anions and cations, from bulk samples to single droplets. For example, analytical techniques have evolved from colorimetry to ion chromatography to capillary electrophoresis. Overall, these advances allow a better understanding of heterogeneous reactions and atmospheric pollutant scavenging processes by precipitation. In addition, from an environmental perspective, these advances allow better quantification of semi-labile (e.g. NH+ 4 , frequently its deposition values are underestimated) or labile species [e.g. S (IV)] in precipitation and measurements of toxic chemicals such as Hg and PCBs (polychlorinated biphenyls). Similarly, methods now exist for source-receptor studies, using for example, the characterization of reduced elemental states and/or the use of stable isotopes in precipitation as tracers. Future studies on the relationship between atmospheric deposition and environmental impacts must exploit these advances. This review provides a comprehensive and comparative treatment of the state of the art sampling methods of precipitation and its physico-chemical analysis. # 2002 Elsevier Science Ltd. All rights reserved. Keywords: Precipitation; Rain; Cloud water; Fog water; Snow; Sampling; Composition; Chemistry; Analysis; Techniques

1. Introduction ‘‘Precipitation’’ can be defined as liquid or solid condensation products of water vapor that are deposited from the clouds or from the atmosphere onto surfaces. Within the scope of that definition, this review summarizes the state of our knowledge concerning issues relevant to the sampling and physico-chemical analysis of wet deposition (rain, cloud and fog water, and snow).

* Tel.: +1-612-625-8200; fax: +1-612-625-9728. E-mail address: [email protected] (S.V. Krupa).

Current worldwide sampling and physico-chemical analysis of precipitation have been stimulated mainly by Bolin et al. (1971). In their presentation at the United Nations Conference on Human Environment in Stockholm, Sweden, the authors provided evidence for the transport of air pollution across national boundaries and for the occurrence of acidic precipitation or rain in Sweden. Soon thereafter, Likens et al. (1972) described the prevalence of acidic rain as a regional-scale environmental problem in the northeast USA. In these and in virtually all other publications since that time, the term ‘‘acidic rain’’ has been used to describe rainfall with a pH value 5.65 or 5.62 (the pH value of distilled water at 25
C in equilibrium with air containing 300 or 365 parts

0269-7491/02/$ - see front matter # 2002 Elsevier Science Ltd. All rights reserved. PII: S0269-7491(02)00165-3

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per million (ppm) CO2, respectively at a total pressure of 1 atmosphere or 101.3 kPa). Whether acidic precipitation is a new or a newly discovered phenomenon is not an issue. Indeed, in 1692 Robert Boyle referred to ‘‘nitrous or salino-sulphureous spirits’’ in the air. Almost 200 years later, in 1872 a treatise on ‘‘Acid Rain’’ was published in England by Robert Angus Smith; 20 years earlier he had analyzed rain near Manchester and noted three types of areas as one moved from the city to the surrounding countryside: that with carbonate of ammonia in the fields at a distance, that with sulphate of ammonia in the suburbs and that with sulphuric acid or acid sulphate, in the town. Thus, the phenomenon of acidic ‘‘precipitation’’ is largely attributed to the prevalence of strong mineral acids (e.g. H2SO4) produced due to anthropogenic emissions of acid-forming gases (e.g. SO2). According to Cowling (1982): Some years ago the terms ‘acid precipitation’ and ‘acid rain’ were bits of esoteric jargon used almost exclusively by scientists in certain specialized fields of ecology and atmospheric chemistry. Recently these terms have become worrisome household words in many countries around the world. While they have inspired sensational and sometimes exaggerated headlines about ‘death from the sky’, they also have prompted a more deliberate and careful examination of the role of humans in the biogeochemistry and chemical climatology of the earth. It is most interesting to note that the widespread sampling and chemical analysis of precipitation that is prevalent today has been driven by concerns of adverse environmental impacts (crops, forests, soils, surface water and anthropogenic materials) of acidic precipitation, rather than by the need for a fundamental understanding of mechanisms transferring chemical constituents from the atmosphere to surfaces (US NAPAP, 1991). Nevertheless, these widespread studies have confirmed the significant spatial variabilities in precipitation composition observed more than some 100 years ago by Robert Angus Smith (1872). After the initial ‘‘acidic precipitation’’-driven thrust in establishing large geographic-scale precipitation monitoring and chemical analysis networks (e.g. US NADP; Canadian, CANSAP, see Section 3 for details) had subsided, many investigators began to examine the quality of data from such networks and also started to measure trace anthropogenic pollutants such as Hg, As, Se and PCBs (polychlorinated biphenyls) in wet deposition.

2. Sampling precipitation 2.1. Rain As with the measurement of any chemical constituent in the atmosphere, the method used to collect rain for chemical analysis and the duration used to collect a sample are governed by the application for which the data are intended (Table 1). Furthermore, any precipitation collector used must be considered as a surrogate surface and should reflect the properties (mechanical, electrostatic and chemical) it represents. Nevertheless, bulk precipitation samples have been collected in open containers, usually a plastic bucket or garbage can or even a conventional open rain gauge. Such samples do not represent rain per se, but a combination of dry+wet, total deposition. The dry component is mostly coarse particulate matter ( > 2.5 mm diameter), both natural and anthropogenic. The chemical composition of bulk samples provides a gross understanding of atmospheric deposition. Because of the frequent use of a long sampling duration (up to a month) to collect such samples, labor for sample collection and the subsequent chemical analysis costs are generally minimal compared to the other methods (Table 1). However, significant contamination of the samples by plant parts, insects, bird droppings and, as in Florida, even frogs and their excretions, lead to poor quality of data and inadequate understanding of the deposition of the chemical constituents in the atmosphere by rain. In contrast to collecting bulk samples, many precipitation monitoring networks (e.g. the US National Atmospheric Deposition Program, NADP; the Canadian Network for Sampling Precipitation, CANSAP, or the more recent Canadian Air Pollution Monitoring Network, CAPMoN) have used wet-only sampling protocols, although the sampler allows the collection of both wet and dry (dust) deposition as separate fractions (CANSAP, 1982; NADP, 1990). Here the rain sampler lid is either opened or closed as appropriate by a signal from a rain-sensing device (Fig. 1). Because the open and close positions are triggered by the rain sensor, individual rain events can be sampled. Here the rain sensor can be an electrical or an optical device that recognizes rain when it is already falling. Of the two types, electrical sensors are the ones in frequent use. These sensors keep the collector lid open whenever the flux of precipitation exceeds the evaporation from the heated sensor. Thus, the amounts of rain collected in the wet-only samplers are generally smaller than the bulk samplers (Stedman et al., 1990; Da¨mmgen et al., 1995). However, recently Marendic´-Miljkovic´ et al. (2000) developed an improved precipitation sensor with a response time of < 30 s at a minimum precipitation intensity of 0.1 mm h1. This sensor was also functional

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S.V. Krupa / Environmental Pollution 120 (2002) 565–594 Table 1 Various types of precipitation sampling protocols and their application Type of sampling

Application

Sampling duration

Comment(s)

(1) Bulk

To measure total deposition (dry+wet) of Variable, from a few days up chemical constituents from the atmosphere on to a month to surfaces.

Total deposition (both dry and wet); because the sampling device is continuously open, the sample is subject to contamination by reactive gases, fine particles, organic debris (plant and animal) and by crustal and other coarse particulate matter. Evaporative loss of water and change in chemical composition are a common problem.

(2) Wet only

To measure wet deposition of major ions as it relates to phenomena such as acidic precipitation.

Variable, from one day up to a month

Wet deposition only; however, since the sample is left under the ambient warming and cooling conditions, chemical composition will change where the sample retrieval is sufficiently long during the time interval after collection.

(3) Event/sub-event, wet only

(i) Event To understand physico-chemical mechanisms underlying specific events and to assess contributions from specific type(s) and location regions of emission sources to the composition of the precipitation.

(a) Grab

No time element involved

Samples are taken without respect to time or volume; samples are generally collected proportional to the precipitation intensity.

(b) Time related grab

Fixed time intervals

Samples of equal volume are collected at fixed time intervals and excess sample is discarded. Therefore, an incomplete sample of a given precipitation event will be collected.

(c) Time weighted sequential

Predetermined time intervals

Samples of unequal volume are collected consecutively from a predetermined time interval. The volume of each sample will vary depending on the intensity of precipitation during the collection interval. Samples are collected without a time break.

(d) Intensity weighted sequential

Unequal time intervals

Samples of equal volume are collected at unequal time intervals. Sampling frequency is proportional to the intensity or volume of precipitation. Samples are collected without a time break.

(ii) Sub-event To understand scavenging or air pollutants and chemical reaction mechanisms governing the dynamics of wet deposition and its relationships to the occurrence of other air pollutants.

(e) Continuous

Precipitation is routed through a sensor(s) as it is being collected. A continuous record of the sensor response is obtained.

(Table continued on next page)

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Table 1 (continued) Type of sampling

Application

(4) Individual droplets Cutting edge understanding of heterogeneous chemistry and dynamics of pollutant scavenging.

Sampling duration

Comment(s)

Rapid time intervals (seconds) Application of highly sophisticated chemical analysis technology for micro quantities of water. Samples of different individual droplet sizes are collected for analysis.

Modified from Robertson et al. (1980), Laquer (1990a), Ba¨chmann et al. (1992, 1993).

According to Robertson et al. (1980), sequential sampling produces a number of samples through the course of a storm, each sample representing the portion of the storm from which it was collected (Fig. 2A). A number of sequential sampling strategies have been used. An analysis of these methods shows five basic approaches:

Fig. 1. A schematic diagram showing a bucket type wet and dry deposition sampler. (A) Rain sensor; (B) dustfall collector; and (C) wet deposition collector. The rain sensor actuates the lid covering the wet deposition bucket to move over to the dustfall collector at the onset of a wet deposition event. After each event, the lid is actuated to move back to the wet deposition side.

at a snowfall intensity of 0.0012 mm h1. Nevertheless, because of the labor and chemical analysis costs, most major sampling networks have used weekly to monthly sampling durations. Consequently each rain sample can be the result of, from one to a composite number of rain events. Although contamination of the sample by dry deposition is virtually eliminated here, there is evidence to show aging and a change in the chemical composition of the rain sample when it is left for sufficiently long periods under ambient or field conditions during the summer season (see Section 4). To offset this problem and for more advanced applications, a number of investigators have used devices and sampling protocols to collect individual rain events and even sequential samples within an event (Table 2). Such methods provide not only high quality data on the chemical composition, but also an understanding of the stochasticity and mechanisms governing the dynamics of atmospheric deposition of chemical constituents by rain. At the present time, such sampling techniques have reached a level of sophistication where continuous in situ measurements of select chemical constituents in rain can be made (Table 2) and even individual raindrops can be sampled for chemical analysis (Ba¨chmann et al., 1992).

1. Grab Sampling: samples are taken without respect to time or volume, but usually to provide at least a minimal amount for chemical analysis. Generally samples are collected proportional to rain intensity. 2. Time-Related Grab Sampling (Fig. 2B): samples of equal volume are collected at fixed time intervals. Once the set volume is collected the excess is allowed to spill until the next time interval. Only portions of the total storm are collected by this method. 3. Time-Weighted Sequential Sampling (Fig. 2C): samples of unequal volume are collected consecutively for a predetermined time interval. The volume of each sample will vary depending on the intensity of precipitation during the collection interval. The container volume is set large enough to collect from the most intense storm period expected. Samples are collected without time break during the whole storm. 4. Intensity Weighted Sequential Sampling (Fig. 2D): samples of equal volume are collected at unequal time intervals. Sampling frequency is proportional to the intensity of the storm or volume of the precipitation. Samples are collected consecutively without time break during the whole storm. 5. Continuous Monitoring (Fig. 2E): precipitation is routed through an appropriate measurement sensor or sensors as it is collected. A continuous record of the instantaneous response from the sensor is registered. Sequential rain samplers can be grouped into four basic categories: (1) manually segmented; (2) linked collection vessels; (3) automatically segmented; and (4) continuous (Robertson et al., 1980).

Table 2 Selected automatic, within-event, sequential precipitation collectors Covera opening method

Collectorb surface

Surface area m2

Sample volume

MAX # samples/ events

Rainfall resolution mm/sample

Rainfall rate measured by:

Substancesc measured and reported

Comment(s)

Linked collection vessels Manual-wash Lucite

0.80 &0.20

1 or 2 l

50

1.4–5.4

Weigh bucket

Runoff relationships

Auto-tissue Automatic Deploy@rain Auto-tissue

0.011 N/S 0.10 0.032

N/S 25 ml, 2 l 67 ml <60 ml

N/S 3; 5 9 5

N/S Varied 0.7 N/S

No No Weigh gauge No

Major ions& trace metals Major ions Major ions Major ions None reported

Intensity weighted segmenting samplers Always open PE Always open Plastic Always open Perspex Automatic PE Auto-open PE Automatic PE Automatic PTFE

1.00 0.07 0.16 0.029 0.64 0.19 0.19

0.5–1. l 20 ml 120 ml 14 ml 39 ml 20 ml 550 ml

70 N/S 40 200 250 250 8

0.5–1.0 0.27 0.75 0.5 0.05 0.1 2.92

Internal TB FC Adv. & CR FC Adv. & CR FC Adv. & CR FC Adv. & CR Digital Prn. FC Adv. Time

Automatic

PE

0.042

15 ml

48

0.36

FC Adv. Time

Manual Automatic Automatic Manual-wash

PE Plexiglas Polyane SS

0.053 0.06 1.00 0.13

12 ml 200 ml 100 ml 25 ml

>33 8 23 100

0.23 2.4–3.0 0.1 0.2

No No FC Adv. Time TB & computer

Time segmenting samplers Manual SS Automatic SS mixing bowl

0.20 0.13

27.5 ml 1.9 l max.

>74 30

0.5, 1, 2 min Hourly

Automatic Automatic

0.049 0.0346

400 ml 50 ml

12 100

1–6 h 3 or 5 min

N/S FC Adv.? TB 0.25 mm & weigh gauge No FC Adv. Time

0.049 0.07 est 0.054 3.84 0.28

– – – Variable –

– – – – –

0.02 – 0.5–1.0 Min 0.1 mm/h 0.1

Internal TB TB, 0.25 mm No Float gauge TB, 0.1 mm

Glass/PE N/S N/S N/S

Continuous monitors Automatic PE Automatic PE? Bucket When rain PP Automatic PP Manual-wash PP

Zn, Cu, Pb pH, SO2 4 Other ions Major ions Other ions Major ions Princ’ions& organics Other ions& trace metals Other ions  pH, SO2 4 , NO3 Other ions pH, Cond

Tracer experiments on precipitation systems 20 ml siphon, fraction collector Nonelectric, weight driven; catchment mass balance study Buchler Fractomette 200 Collector Gilson Anacol VF 30 collector; Second edition, scaled down collection Refrigerated

Princ’ions Major ions

Summer convective showers, washout Scavenging, only summary data available

Princ’ions pH, Cond

Source receptor, trajectory analysis Redirac Bromma LKB2112 Fraction Collector

pH, Cond pH, Cond, temp pH Major ions pH, Cond

Thermostatted apparatus at 25
C Acid rain, high altitude Real time pH, novel flow electrode Mobile lab, on-line assay with ISEd Compared with segmented sampling

Intra-event rain variability Electric valves; scavenging, aerosols ISCO cygnet fraction collector

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TB=tipping bucket; FC Adv.=fraction collector advance mechanism; CR=chart recording. Modified from Laquer (1990a). a Manual-wash=wash/rinse just prior to precipitation event. Auto-tissue=automatic open, manual close, includes ‘‘tissue’’ closures, polyvinyl alcohol paper. Automatic=automatic open and close. b Rain impact surface, funnels unless otherwise noted. PE, polyethylene; PTFE, Teflon; SS, stainless steel; PP, polypropylene; N/S, not stated; ?, educated guess.  2  c  + 2+ Major ions=H+, Na+, K+, Ca2+, Mg2+, NH+ , NH+ 4 , Cl , NO3 , SO4 . Other ions=other sets of ions, insufficient for ion balance calculation. Princ’ions=principal ions: H , Ca 4 , NO3 , SO2 4 . Cond, conductivity; Temp, temperature. d ISE, ion selective electrode.

S.V. Krupa / Environmental Pollution 120 (2002) 565–594

SS PE

Inverted siphon with check valves Below cloud scavenging, mountain/valley OSCAR experiment, cyclonic storms Installed in standard Canadian rain gauge

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Fig. 2. A schematic diagram showing different types of sampling strategies for rain. Robertson et al. (1980).

Each sampler type has its advantages and disadvantages based on the particular research need or based on the analyte to be measured and the analysis method used. Manual sampling methods are the least expensive in terms of equipment costs, but they require a person to change the collection vessel at the appropriate time. Manual methods can be used on a time weighted, intensity weighted, or grab sample basis. The simplest sampler is a funnel and bottle or an open widemouthed container. Gatz and Dingle (1971) used a 2.5

m2 funnel to collect 2–8 l rain samples. Dana et al. (1974, 1976) used a 1 m2 funnel mounted on the roof of an automobile for following convective storms at various distances. Perkins et al. (1970) used a large plastic sheet over a roof to direct rainwater to an ion exchange column that trapped the radionuclides of interest. In this case the ion exchange column was changed manually. It should be noted that the time of collection must be regulated and registered manually for all of the aforementioned methods.

S.V. Krupa / Environmental Pollution 120 (2002) 565–594

Three different research groups have employed linked collection vessels (Robertson et al., 1980). All these samplers consist of a series of bottles linked together by tubing. When one bottle is full, the rainwater flows into the next in line (Fig. 3). Bottle-filling time is proportional to precipitation intensity. The three research groups differ in their precautions taken to prevent mixing of incoming rain with that already in a bottle. Cooper et al. (1976) have the simplest device [Fig. 3 (a)] that relies on the narrow tubing leading to the bottle to prevent mixing. Kennedy et al. (1976) used air vents on the bottles as shown in Fig. 3(b) to prevent the process of siphoning between bottles. The most sophisticated one was that used in California by Liljestrand and Morgan [H. Liljestrand, University of Texas, personal communication, Fig. 3(c)] in which air vents and floating stoppers were used to prevent mixing. Although all three-sampler types will segment a storm unattended, if collection times are required they must be recorded manually or calculated from precipitation intensity data and the funnel area. In comparison with the manual samplers, the automated methods can be divided into timer or volume

Fig. 3. A schematic diagram showing three different types of linked bottle samplers: (a) Cooper et al. (1976); (b) Kennedy et al. (1976); (c) Liljestrand and Morgan, personal communication. Robertson et al. (1980).

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actuated, or actuated by a related parameter to segment the storm. The most widely used sampler is a tipping bucket (weight) actuated device developed by Gatz et al. (1971) and used by Adam et al. (1973) and Dingle (1977). Raynor and McNeil (1978) designed a timeractuated device. Time periods were preset but adjustable between sampling runs. Results reported by Raynor and Hayes (1978) were for one hour collection periods. Krupa and co-workers at the University of Minnesota (Coscio et al., 1982) have developed a sampler that senses when a bottle is full by means of a micro pressuresensor switch in the overflow port. The University of Minnesota sampler (Fig. 4), in addition to enabling the refrigeration of the samples in situ, is the only automated sampler that seals off the bottle from the atmosphere to prevent exchange of gases between the sample and the ambient environment after collection. The others utilize open bottles in a rack that remain open after collection. A sampler based on the Minnesota design is commercially available (Computer Controlled Machines of Minnesota, Northfield, MN, USA). This sampler has been used in the Minnesota-Wisconsin Power Suppliers Group Precipitation Sampling Network (Krupa et al., 1987) and in the Alberta Government-Industry Acidic Deposition Research Program (Legge and Krupa, 1990). In summary, the automated methods vary in complexity. Some require manual starting, but most are actuated by sensors. All have chart or electronic recorders to register sampling time and cover position (open or closed). An acid precipitation monitor was developed by USEPA scientists at Research Triangle Park, NC, USA, that collects fractions of rain events, measures the pH

Fig. 4. University of Minnesota Sequential Rain Sampler: a crosssectional view of the sample-distribution turret. The sample collection funnel is at the top, and incoming rain is channeled to the bottle at the extreme left. When the bottle is full, or alternately at the termination of a rain event the turret rotates. Rotation allows a new bottle to be filled and all bottles used for sampling are sealed against the turret. Coscio et al. (1982).

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and conductivity in real time, and stores the remaining samples under refrigeration conditions. A Z-80 microprocessor controls all operations of the monitor, including sample collection, sample analysis, quality control analysis, and data recording (Kronmiller et al., 1990). A similar system has been constructed by Beverland et al. (1996). These samplers represent a transition in technology between sequential samplers (Coscio et al., 1982) and continuous monitors. In contrast to the sequential samplers, in the past most continuous monitors have been used to examine nuclei in air samples during rain and snowstorms. Radke et al. (1970) used an integrating nephelometer and Graedel and Franey (1977) used a cloud nucleus counter and an optical particle counter for this purpose. However, in the recent years the technology has become sufficiently sophisticated to allow continuous in situ measurements of several major inorganic ions in rain. For example, Ames et al. (1987) developed an instrument capable of collecting rainwater and analyzing it + 2+  continuously for H+, NH+ , NO 4 , Na , Ca 3 , and Cl (Fig. 5). This sampler is based on an inverted V-array arrangement mounted on the roof of a small moving caravan. While an indirect colorimetric method is used for SO2 4 and a chemiluminescent method for H2O2, the other species are determined by ion-selective electrodes. The onset of rain is sensed by a simple conductivity plate or by a modified float gauge. Laquer (1990b) compared the results from two precipitation intensity or volume weighted collection

Fig. 5. A schematic diagram of the rainwater analysis system. (M), mixing coils; (B), ionic strength adjustment buffers; (P), pinch valves; and (C), calibration solution. The pump flow rates are 1 ml min1 for the rainwater samples and 0.1 ml min1 for the electrode calibration buffers. Ames et al. (1987).

methods (Table 3). A continuous flow measurement of conductivity and pH was compared to the corresponding data for samples collected by a sequential fraction collection system. Conductivity data from summer thunderstorms in Omaha, Nebraska, USA, collected by the two systems were comparable to each other and with an integrated, wet-only event sampler. The flow system pH measurement exhibited bias with respect to the sequential fraction collection system due to insufficient electrode equilibration time, especially when the precipitation conductivity was low, < 10 mS cm1. As opposed to the development of technologies for the continuous measurements of major inorganic ions in rainfall, some investigators have been developing methods for examining the chemical composition of individual raindrops. Esmen and Fergus (1976) were the first to measure the pH of individual raindrops by using a manual filter paper collection system treated with various acid-base pH indicator reagents. Ba¨chmann et al. (1993) have developed a method for the sampling of individual raindrops and to quantify free and total acidity and the concentrations of the main anions and cations. The Guttalgor (Latin: guttare=to catch; Greek: algor=frost) method of Ba¨chmann et al. (1992, 1993) mainly consists of a modified Dewar flask filled with liquid nitrogen (Fig. 6). The collection system is enclosed in an inert box to avoid contamination from the outside environment. The box is opened for up to 3 s each time. Raindrops fall into the liquid nitrogen and remain at the surface for several seconds due to the evaporating nitrogen and until they reach the temperature of that vapor. Then they sink, since their density will be higher than that of the liquid nitrogen. Raindrops do not change their spherical shape during this process. Consequently, it is possible to separate individual raindrops of different sizes using sieves of different mesh sizes. The following mesh sizes were used in the Guttalgor: 0.2, 0.3, 0.4, 0.5, 0.6, 0.8, and 1.0 mm. The sample volumes usually range from  1 ml for the 0.2 mm size fraction to several milliliters for the size fraction > 1 mm. The short opening intervals prevent drops from coalescing at the surface of the liquid nitrogen. A change in the ion concentration of the drops does not occur because, first the evaporating nitrogen creates a higher pressure within the box compared with the ambient atmosphere. Therefore, a small gas stream is generated out of the box when open and no ambient air gets into the box. Second, the drops are frozen in less than 1 s and no evaporative loss in the drops takes place. The numerical results of standard drops made of distilled water showed ion concentrations below their detection limits (see Section 5.2.4. for the details of the chemical analysis). For size classification of the raindrops, it was found necessary to add a known volume of a standard Li+

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S.V. Krupa / Environmental Pollution 120 (2002) 565–594 Table 3 Summary comparison of conductivity and H+ data collected by continuous flow versus a sub-event precipitation sampler Statistic

Rainfall rate, mm/h

Arithmetic mean S.D. Median Geometric mean Log geometric mean Log geometric S.D. Number of samples

17.00 22.00 5.50 6.00 0.79 0.72 434.00

H+105, mol l1

Conductivity, mS cm1 Flow

Sub-event

Flow

Sub-event

19.00 17.00 13.00 13.00 1.12 0.37 416.00

22.00 25.00 13.00 15.00 1.17 0.36 431.00

1.54 1.38 1.30 0.89 5.05 0.60 360.00

1.63 3.51 0.79 0.63 5.20 0.64 436.00

Modified from Laquer (1990b).

Fig. 6. A schematic diagram of the sampler used for collecting individual raindrops. Ba¨chmann et al. (1993).

solution to an individual raindrop or a size fraction and to determine the change of the Li+ concentration as an indirect measure of droplet size. The sieves of various mesh sizes are only used for pre-separation (Ba¨chmann et al., 1993). The frozen raindrops are removed from the sieves with a pair of Teflon tweezers and transferred into a closable receptacle filled with 10 ml of the Li+ standard. Raindrops having a volume > 500 nl can be analyzed as single drops, while drops with a smaller volume can only be analyzed as size fractions (Ba¨chmann et al., 1993). 2.2. Cloud and fog water In recent years there has been an increase in the interest to collect and characterize the chemistry of cloud and fogwater. This is due to: (1) the scientific importance of understanding the droplet (heterogeneous) chemistry

of sulfur and nitrogen oxides in the context of acidic precipitation, and (2) the ecological concern for the interception of cloud and fog water by high elevation forests and its role in forest health in North America and in Europe (US NAPAP, 1987; 1990). Chemical processes within cloud droplets are most commonly studied by collecting a sample of water from the cloud and analyzing its chemical composition. This approach has a number of drawbacks, among the most serious of which is the averaging that occurs during sample collection (Ogren et al., 1988). One type of averaging relates to droplet size, where the collected sample contains contributions from droplets of widely varying sizes. The collection efficiency as a function of droplet size varies widely with the principle and manufacturer design of the sampler (Table 4). In many cases this information is unknown. Another type of averaging is over time and space, since all collectors require a finite

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Table 4 Some examples of cloud and fog water collectors Collector type

Comment(s)

Reference

Passive vertical string collector

Uses the natural relative velocity between the fog droplet and a stationary surface. Less expensive than most other methods.

Schmitt (1988)

Occult deposition collector

Simple, inexpensive, passive sampler, excludes precipitation. Allows for long-term sampling at remote locations.

Spink and Parsons (1990)

Active strand collector

Cloudwater droplet collection by inertial impaction. Fifty percent collection at a droplet size of 14 mm for example.

Kins et al. (1986), Daube et al. (1987)

Slotted rod cloud water collector

Used in aircraft based measurements. However, the rods themselves and the distortion of airflow around the aircraft are likely to cause a fractionation of the droplets during collection.

Winters et al. (1979)

Rotating arm collector

Fifty percent collection efficiency at droplet sizes of 8 to 20 mm.

Hileman (1983), Jacob et al. (1984)

Automated rotating string collector/optical fog detector

Automatic system using an optical fog detector. Unattended sampling of several fog events.

Fuzzi et al. (1990)

Mesh impaction sampler

Simple, rugged, portable active sampler. Fifty percent collection efficiency at a droplet size of 2.4 mm.

Huang et al. (1986)

Counterflow virtual impactor

Allows estimation of mass concentration of non-volatile materials dissolved or suspended in cloud droplets, the average size of the sampled cloud droplets, and the average size of aerosol particles that result from evaporation of the sampled cloud droplets.

Ogren et al. (1985, 1988)

Electrostatic precipitator

Allows the sampling of single cloud or fog water droplets as small as 2 pl or bulk phase water. Allows the study of the relationships between droplet size and solute concentrations.

Tenberken and Ba¨chmann (1998)

amount of time to obtain sufficient volume of sample for chemical analysis. Thus, virtually all of the cloud and fog water samplers currently in use do not permit a study of droplet-size-dependent physico-chemical processes of the atmosphere. Nevertheless, a number of investigators have used passive samplers to collect cloud and fog water (see Unsworth and Fowler, 1988). Fig. 7 provides an example of a passive sampler. The collector consists of a Teflon support structure and 0.3 mm diameter Teflon strings, mounted 3.0 mm apart in a cylindrical configuration. Under appropriate air flow conditions, fog droplets are impacted on these strings, grow to larger drops, run down the strings and are collected in a sampling bottle. At normal wind speeds, all droplets > 5.0 mm diameter are impacted (Georgii and Schmitt, 1985). In general, a sampling time of 2 h is required to collect a volume of 15–25 ml. This string collector is exposed only during the fog events. At other times, it is kept inside a metal cylinder to prevent contamination by rain and dry deposition. The sampler actuation–deactuation modes are regulated by a temperature-dew point-based fog sensor and a separate rain sensor. Modified dynamic versions of the passive sampler are also available, Fig. 8 (Kins et al., 1986) and the CalTech Active Strand Cloud

Water Collector [Fig. 9(A) Daube et al., 1987]. In the latter, a fan is installed to draw air across six angled banks of 508 mm Teflon strands at a velocity of 8.5 m s1. Cloud water droplets in the air parcel are collected on the strands by inertial impaction. The collected droplets run down the strands, aided by gravity and aerodynamic drag, through a Teflon sample trough into a high density polyethylene collection bottle. This instrument has a theoretical lower collection size-cut of 3.5 mm, based on droplet diameter, and has collected cloud water at rates of up to 8.5 ml min1. Fog water can also be collected by the use of a rotating device consisting of a stainless steel arm (63 cm long) with slits along each side to collect the water. The arm rotates at 1700 rpm, picking up fog water droplets larger than  8 mm with good efficiency (Hileman, 1983). The water droplets are pushed by centrifugal force into collection bottles inserted in each end of the arm. Collett et al. (1990) compared the performance of a rotating arm collector [Fig. 9(B)] with the CalTech Active Strand Collector placed side-by-side. There were significantly higher concentrations of Na+, Ca2+, Mg2+ and Cl in the samples collected by the rotating arm compared with the CalTech sampler. This may be due to the differences in the droplet size collected by the

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Fig. 7. A schematic diagram of a passive fog water sampling system. A fog sensor, comparing the actual temperature and the dewpoint, gives a signal to a motor (M), which moves the collector (C) out of a shelter (G) for sampling the fog water. Schmitt (1988).

Fig. 9. A schematic diagram showing the: (A) CalTech active strand cloudwater collector. Air flow is from right to left through the collector as viewed in the figure; and (B) CalTech rotating arm collector. Collette et al. (1990).

Fig. 8. A schematic diagram of a ground-based active collector for cloud and fog water. Kins et al. (1988).

two samplers or due to differences in the collection efficiency of suspended coarse particles (> 5.0 mm) in the atmosphere by the rotating impactor surface. However, no significant differences were observed in the con2 + centrations of NO 3 , SO4 or NH4 in the samples collected by the two samplers. Fuzzi et al. (1990) developed an automatic system for fog water collection. This system uses an optical fog detector that senses the backscatter of light by the fog droplets, a rotating string collector, a sample storage or fractionation unit and a computer that regulates

the operation of the sampler and stores information relative to the sampling periods. This system was designed for the unattended sampling of several fog events. When this sampler is activated, the string collector rotates at 100 rpm, volume of air continuously moved through the collector is 6.5 m3 min1 and the mean collection efficiency is 90% for droplets > 8 mm in size and 20% for droplets=5 mm in size. Huang et al. (1986) have used a Mesh Impaction Fog Sampler (MIFS). The MIFS (Fig. 10) collects fog water drawing an airflow of approximately 1.5 m3 min1 into the sampler inlet and through a polypropylene mesh using a vacuum-cleaner blower downstream. The mesh is made of interlaced filaments (410 mm diameter) and has a void volume of 96%. The fog water intercepted by the 10 cm diameter, 4 cm thick mesh drains down a Teflon-lined 10 cm polyvinyl chloride pipe into a polyethylene bottle. Since the air sampling flow rate is clearly defined, fog water chemistry may be related back to ambient fog chemistry. The MIFS can effectively

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Fig. 10. A schematic diagram of the mesh impaction fog sampler; the polypropylene mesh is 10 cm in diameter and 4 cm thick, installed inside the PTFE (Teflon)-lined 10 cm diameter PVC down tube. Huang et al. (1986).

intercept droplets > 5.0 mm, with a 50% collection efficiency at 2.4 mm. Huang et al. (1986) compared their MIFS with the performance of four other types of fog collectors in a common study. The four collector types were: (1) rotating arm with slotted end; (2) rotating rods; (3) two interconnected rotating plates with strings mounted between them; and (4) three rectangular jets for drawing the air, followed by rotating drums for droplet impaction. In this inter-comparison, results from the collocated five sampler types showed a data precision 16% for total, strong and free acidity, SO2 4 , + NO 3 , and NH4 , and 14–46% for the major cations. The results from non-collocated samplers showed an agreement of 17–22% for the acids, 8–12% for SO2 4 , + NO 3 , and NH4 and 30–70% for the major cations. The combined data from all the samplers in this case exhibited an agreement of 21–23% for the acids, 24–33% for  + SO2 4 , NO3 , and NH4 and 34–80% for the major cations. The authors concluded that when examining fog chemistry data, one should recognize the data variation due to sampler precision (collocated samplers), fog heterogeneity (non-collocated samplers), and the use of different sampler types. An important consideration relevant to most cloud and fog water samplers is their inability to separate the water molecules being collected from the influence of the surrounding air. Ogren et al. (1985) used a Counterflow Virtual Impactor, CVI (Fig. 11) to separate cloud droplets from the surrounding air. Warm, dry, particle-free air flows through the annular region of two concentric tubes to the tip of the impactor. The wall of the inner tube at the tip is constructed of porous stainless steel, which allows the dry air to flow into the inner tube. A fraction of the air entering the inner tube is sucked back into the sampler, while the rest blows out the tip. A consequence of this flow scheme is that somewhere along the length of the porous tube there is a stagnation plane where there is no net axial flow. Tipward of this plane the air flows towards the tip, while

inward of this plane the air flows back into the sampler. The distance from the stagnation plane to the tip can be varied by adjusting the air flow rates to the tip and back into the sampler. Cloud droplets approaching the CVI can either be deflected around the inlet or swept into the inner tube. Gas molecules and sub-micrometer aerosol particles follow the air streamlines around the tip of the impactor, while larger particles (or droplets) diverge from the streamlines due to their higher inertia. Those droplets that enter the inner tube are either blown back out the tip or sucked into the sample flow, depending on whether they have sufficient inertia to pass through the region off tipward-flowing air. The parameter controlling droplet collection is the stop distance of the droplets, which is the distance a droplet with a given initial velocity travels in motionless air before coming to rest (Fuchs, 1964). The minimum radius of droplets that can be sampled is determined by the radius of the outer tube of the sampler (1 cm); droplets with stop distances less than about 1 cm will follow the air streamlines around the tip of the probe. The length of the porous inner tube in the CVI (8 cm) determines the maximum size of droplets that can be rejected. The lower size limit of droplets that are sampled can be varied from  4 mm to  15 mm. Large droplets that enter the CVI are removed by impaction on a 90
bend in the tubing located 75 cm downstream of the tip. This bend has a radius of curvature of 2.5 cm, and the sample air velocity is typically 3 m s1. A first-order analysis based on the Stokes number of the droplets (Fuchs, 1964) shows that droplets with radii larger than  50 mm will be removed at this bend. The flow rate of air swept out by the sampler is equal to the cross-sectional area of the inlet multiplied by the velocity of the air flowing past the tip; this was  130 l min1. Those droplets with sufficient inertia to enter the sampler become trapped at a flow rate of  10 l min1.

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Fig. 11. A schematic diagram of the internal geometry of counterflow virtual impactor. Ogren et al. (1988).

As a result, droplet number concentrations, liquid water content, and the concentrations of material dissolved or suspended in the cloud droplets are enhanced inside the sampler by a factor of  13 relative to ambient air. The results can be corrected for this pre-concentration effect, and thus referred to ambient conditions. The sampled cloud droplets evaporate quickly in the warm, dry air inside the CVI. As a first-order estimate, the time required to evaporate a droplet has been calculated by Ogren et al. (1988) by neglecting the effects of ventilation, curvature, and solute concentration, and by assuming that the temperature of the surface film of the droplet is constant. Although any rigorous calculation would have to include the effects of evaporation on the stop distance, the first-order estimates indicate that the maximum droplet radius that can be sampled is between 50 and 100 mm. Ambient gases and sub-micron aerosol particles are rejected in the CVI with almost 100% effectiveness. A measure of this effectiveness is the rejection ratio, defined as the ratio of the concentration of a species in ambient, cloud-free air to the concentration within the CVI. Measurements of the rejection ratio for condensation nuclei resulted in values of 102 and 105, depending on the wind speed and the distance from the sampler inlet to the stagnation plane. For the worst-case combination of a rejection ratio of 102, a cloud droplet number concentration of 50 cm3, and an ambient (within cloud) condensation nucleus concentration of 103 cm3, contamination by sub-micron aerosol particles would result in a surplus of 10 cm3, amounting to a 17% error in the measured droplet number concentration. In reality, under the experimental conditions, the actual contamination was much less, as the baseline of the droplet number concentration trace was under 1 cm3 (Ogren et al., 1988). Overall, surrogate surfaces provide an inadequate approach to the precise measurement of deposition by cloud and fog water. Due to the generally unknown

Fig. 12. A schematic diagram of an electrostatic precipitator for sampling single cloud or fog water droplets. (a) High-voltage power supply; (b) corona discharge electrode; (c) collection or precipitation electrode; and (d) Petri dish. Tenberken and Ba¨chmann (1998).

influences of electrostatic forces, the settling velocities of the droplets can be very small and thus, cannot be accurately determined by using data on size distribution and ‘‘normal’’ settling velocities. Tenberken and Ba¨chmann (1998) developed a electrostatic precipitation method capable of sampling single cloud or fog drops as small as 2 pl (Fig. 12). The precipitator is based on the corona discharge principle. A copper electrode serving as the discharge electrode is positioned at a distance of 10 cm above an aluminum precipitation electrode. A 25–30 kV voltage is applied to the discharge electrode for 1 s to produce a spray of electrons or negative charge and the charge is transferred to the droplets by action of the electric field. After the charged droplets move to the precipitator electrode, they are collected in a petri dish. They are covered immediately by paraffin oil to prevent evaporation and contamination. The chemical analysis of the single drops is accomplished through capillary electrophoresis, after introducing a single droplet directly from the paraffin oil into the capillary by vacuum suction (Tenberken and Ba¨chmann, 1996, 1997). The authors used their method to study the relationships between cloud and fog water droplet size and solute concentration. The same sampler can also be used for collecting bulk phase cloud or fog water, by increasing the time for the application of the voltage to the discharge electrode from 1 s to 5–15 min, depending on the density of the fog. 2.3. Ice crystals Ehrman et al. (2001) used a modified Guttalgor method of Ba¨chmann et al. (1992, 1993, see Fig. 6 and the corresponding text in Section 2 of this review) to

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sample size-classified ice crystals at Jungfraujoch, Switzerland. The chemical composition of the crystals was analyzed by ion chromatography. Ions associated with coarse mode aerosol (e.g. K+, Ca2+, Mg2+, and Cl) increased with decreasing ice crystal size, suggesting scavenging by nucleation. A mixed behavior was observed for the remaining ions, suggesting a combination of gas phase scavenging and scavenging via riming. 2.4. Snow In comparison to the development of sophisticated techniques for the sampling of rain and cloud and fog water, very little effort has been directed to the advancement of methods for collecting snow. It is widely accepted that rain samplers are not very efficient in collecting snow (USEPA, 1986). As opposed to raindrops, snow is transported horizontally and its sedimentation is slow. In addition to the difficulty caused by the angle of the impaction of snowflakes, snowstorms are frequently associated with highly turbulent crosswinds at the ground level. In this context, although some investigators have used windvanes coupled with bucket type rain samplers, such modifications have not produced satisfactory results. Many scientists have collected falling snow by simply placing acid washed plastic sheets on the ground and held in place by plastic frames. Others have used various types of coring devices for obtaining composite samples after several snowfalls. Johannessen and Henriksen (1978) used lysimeters placed below the ground for collecting snowmelt water. Independent of which approach is used, it should be noted that when collecting composite snowfall samples, such samples will be subject to contamination between individual snow events by dry deposition and by fugitive particulate matter. Colin et al. (1987) developed a sampler for rain and snow. This collector consists of a square funnel obtained by fusing four sheets of Polyane (a proprietary name for low density polyethylene) together at an angle of 60
. It rests on a collapsible metal frame, and this is supported by four telescopic feet that set the opening at 1.50 m from the ground. The funnel has Polyane flanges that completely cover the metal part, thus avoiding contamination by the armature (Galloway and Likens, 1976; Asman, 1980). The second feature is the protection of the sample against any significant contamination by dry deposition. For this purpose the funnel is covered with a tightly fitting sheet of Polyane. The collector is manually uncovered when precipitation is expected. Samples are collected manually in pre-weighed bottles of polyethylene. The time is recorded whenever the bottle is changed so that the precipitation intensity can be calculated. To collect snow a heating device is attached to melt the snowflakes by circulating warm air over the outer walls of the funnel.

3. Some major sampling networks of precipitation During the second half of the 1970s, the occurrence of acidic precipitation became a major international issue of environmental concern. By that time networks of precipitation sampling and analysis had already been in operation in Sweden and Norway. The results from those studies and the consequent socio-political pressure led to the establishment of major networks for precipitation sampling in many countries throughout the world. Examples of some of these are the US National Atmospheric Deposition Program (NADP), the Canadian Network for Sampling Precipitation (CANSAP) and the Precipitation Composition Monitoring Networks in the UK and FRG. The most sophisticated national network for precipitation sampling is in Japan, consisting of more than some 29 sampling locations (K. Tanaka, National Industrial Research Institute of Nagoya, personal communication). In this program precipitation samples are collected on a daily basis with a refrigerated, wet-only rain collector (Fig. 13). This sampler is commercially available (DKK Corporation, Tokyo, Japan).

Fig. 13. A schematic diagram of the automated, refrigerated precipitation sampler used in the Japanese Acid Rain Monitoring Network. (1) Top cover operating mechanism; (2) collection vessel; (3) cleaning water reservoir; (4) refrigerator; (5) dustfall collection vessel; (6) rain sensor; (7) rain sample dispensing section; (8) control panel; (9) recorder; and (10) ground cable. DKK Corporation, Tokyo, Japan.

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Table 5 provides a summary of the number of sampling sites and precipitation collection protocols used in some of the networks. Because of the labor and chemical analysis costs involved, most of the networks continue to collect composite weekly, bi-weekly or monthly samples. Results from such studies have led to the mapping of the geographic and temporal patterns of wet deposition of major anions (SO2 and NO 4 3 ) and + + 2+ cations (H , NH4 , and Ca ). However, the composite sampling protocols used can lead to an underestimation of the deposition of certain ions such as NH+ 4 (see Section 4 for details). In addition, composite precipitation sampling does not permit an understanding of the dynamics of heterogeneous air chemistry and wet deposition nor a satisfactory resolution of source–receptor relationships.

4. Stability of the chemical composition of rain Compared with the composition of seawater, rain can be considered as a poorly buffered, highly dilute mixture of chemical constituents (Whitfield, 1979). Because of this nature, there is evidence to show that rain sample

chemical composition can change under certain conditions between the time of collection and the chemical analysis. There are a number of plausible reasons for such changes: (1) adsorption and absorption of certain chemical constituents on to the surface of the sampling device; (2) changes in the chemical equilibrium between the insoluble and the soluble fractions; (3) evaporative loss of water in the sample; (4) loss of certain dissolved constituents by volatilization; (5) oxidation of ionic species initially collected in their reduced state; and (6) microbial immobilization or consumption of essential elements for growth. Rain sampler collection surfaces include: stainless steel, Lucite, plastic, polyethylene, glass and Teflon (Table 2). Although the differences in the adsorption, absorption and desorption properties of these various surfaces may not be critical if the objective is simply to calculate the annual or seasonal rain deposition values of a major ion such as SO2 4 , clearly this aspect should be addressed a priori if the goal is to quantify trace constituents such as Hg (Vermette et al., 1995a) or PCBs (Murray and Andren, 1992a). The selection of the proper collection surface will depend on the nature of the surface itself and on the physico-chemical properties

Table 5 Selected examples of USA, Canadian, European and Japanese wet deposition collection networks Network abbreviation

Name

Operator(s)

MAP3S/RAINE

Multistate Atmospheric Power Production Pollution Study/Regional Acidity of Industrial Emissions National Atmospheric Deposition Program/National Trends Network

Battelle Pacific Northwest Laboratories, USA Consortium of government agencies, universities and private sector, USA NADP, see the previous row

NADP/NTN

AIRMon UAPSP

Atmospheric Integrated Research Monitoring Network Utility Acid Precipitation Study Program

Edison Electric Institute, Electric Power Research Institute, USA TVA Tennessee Valley Authority Tennessee Valley Authority, USA CANSAP Canadian Network for Sampling Acid Precipitation Environment Canada CAPMoN Canadian Air and Precipitation Monitoring Network Environment Canada APN Air and Precipitation Monitoring Network Environment Canada ROC Reseau Quebec Vois de Collectre des Precipitations Quebec Ministry of the Environment APIOS Acidic Precipitation in Ontario Study Ontario Ministry of the Environment GLAD Great Lakes Atmospheric Deposition Network EPA Region V, USA WMO/BAPMoN World Meteorological Organization/Background EPA, NOAA, WMO Air Pollution Monitoring Network UK/PCMoN United Kingdom Precipitation Composition AEA Technology Monitoring Network Hessen/FRG FRG UBA/FRG Japan

Province of Hessen Precipitation Sampling and Analysis Network Umweltprobenbank Umweltbundesamt Acid Rain Monitoring Network

Hessische Landesanstalt fu¨r Umwelt KFA Ju¨lich, Inst. Physical Chemistry Umweltbundesamt Ministry of Environment

Collection frequency No. of stationsa 9

By event

10

Weekly, some cases daily Daily

19

Daily

>200

11 59 20 6 45 34 41 10

Bi-weekly Monthly Daily Daily Weekly Monthly Weekly Weekly

32 5

Bulk/weekly Wet only/daily

6

Bulk/bi-weekly

12 31 29

Bulk/bi-weekly Bulk/bi-weekly Daily (refrigerated)

Modified from Wisniewski and Kinsman (1982). a In many of the networks, the number of sampling stations has changed over the years. Some networks are no longer in operation and some others have been merged.

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of the analyte. These types of preliminary, but essential studies are frequently omitted in measuring uncommon, trace chemical constituents in rain (see Section 5.2.3.). In major rain sampling networks, precipitation samples are filtered to remove the insoluble particulate fraction prior to the chemical analysis of major inorganic ions in the dissolved fraction. While this is desirable, the time lapse between the collection of the first rain sample and the sample filtration in these networks can be as low as 8 or 9 days to as high as more than a month, depending on the sampling duration of the composite sample (CANSAP, 1982; NADP, 1990). Although it is generally believed that the stated time lapse is not large enough to influence the concentrations of the major inorganic ions in the dissolved fraction, there are few detailed investigations on the influence of sample collection–filtration conditions and their influence on insoluble and soluble rain sample fraction dynamics of chemical equilibrium (Peden and Skowron, 1978). The pH of rain samples may change significantly in storage, depending on the conditions of storage and the composition of the sample. Guiang et al. (1984) provided a pH time series for rain samples under two different sets of storage conditions. These samples were initially collected with the University of Minnesota refrigerated, sequential, sealed precipitation sampler (Coscio et al., 1982). For the pH time series shown in Fig. 14(A), the samples were maintained in the sealed bottles under refrigeration. Periodically, 25 ml aliquots were withdrawn and the pH measured. The pH of nearly all samples increased in storage. The increase was often greatest just after the bottle was initially unsealed and the first aliquot withdrawn. This was the first time sufficient gas exchange between the sealed sample and outside air was allowed to occur. In addition, larger changes in pH occurred in samples with a pH > 4.5. The change in pH was not significantly correlated with any of the measured inorganic or organic ions. For the time series shown in Fig. 14(B), a different storage method was employed. A second set of aliquots were withdrawn from the sealed bottles and maintained under refrigeration, but were left in open beakers loosely sealed with parafilm. This procedure allowed free gas exchange with the laboratory air. Thus, in Fig. 14(B) the first two pH values for each sample were identical to those in Fig. 14(A). However, subsequent pH values were different and generally were higher, suggesting that gas exchange may be involved in the rise of the pH. Other explanations include low-level microbial activity or dissolution of some constituents of the insoluble fraction. With the exception of the University of Minnesota collector (Coscio et al., 1982), the rain samplers currently in use (continuous samplers not included) do not provide a complete seal between the collected sample

Fig. 14. (A) Time series measurements of the pH of 15 rain samples selected to represent the range of values observed in the Minnesota rain chemistry data. The samples were maintained in sealed bottles under refrigeration, and periodically aliquots were withdrawn for the pH analysis. (B) Time series measurements of the 15 rain samples used in (A). In this case the second aliquot withdrawn for a pH measurement was preserved under refrigeration in an open beaker sealed loosely with parafilm to allow gas exchange prior to the pH measurement. The first two values for each sample are identical to the first two values shown in (A). Subsequently, changes were observed between the two storage methods (A & B). Guiang et al. (1984).

and the ambient environment. In addition, with bucket type collectors, frequently there will be a significant headspace volume between the sample surface and the lid. Under these conditions, absorption and desorption of water-soluble gases such as CO2 should be expected, particularly when the samples are allowed to remain in the field, from days to a month alternately warming and cooling. Although this aspect is generally ignored in most networks, sampling duration has an important influence on the data obtained on the chemical composition of rain (Sisterson et al., 1985; Lamb and Comrie, 1993).

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The loss of water molecules by evaporation from composite samples during the summer months can be important. This issue is considered to be site-specific and has not been fully examined, because it is believed by many that it is not an important factor. It is generally accepted that any differences in the measured precipitation depth between a standard rain gauge and a rain sampler is strictly due to the difference in the collection efficiency of the sampler. Any measurable loss of water from the sample would result in higher concentrations of some of the measured ions (mass to volume ratio). However, as shown in Table 6, this is not the case. Several independent studies have shown similar results (de Pena et al., 1985; Sisterson et al., 1985). In these studies the precipitation volume-weighted concentrations of several major inorganic ions were all higher when daily rain sample data were appropriately converted for comparison with composite weekly samples and such an effect was pronouncedly more so, when the daily rain samples were refrigerated in situ (Table 6). de Pena et al. (1985) were unable to offer a specific reason for the lower concentrations of all the ions quantified in weekly precipitation compared to event samples at a Pennsylvania site. In comparison, Sisterson et al. (1985) observed at their Illinois site significantly less NH+ 4 and higher laboratory pH during all seasons and

Table 6 An example comparison of volume weighted precipitation chemistry between co-sampled unrefrigerated weekly and in situ refrigerated event samples cumulatively converted to weekly valuesa Variable Unrefrigerated weekly samples Refrigerated event samples pH

5.49b (4.92–6.87)c

5.28 (4.32–8.02)

Ca2+

11.62 (4.99–57.88)

18.83 (1.7–90.8)

Mg2+

3.53 (1.40–30.77)

4.92 (0.3–35.9)

K+

0.83 (0.33–9.41)

1.32 (0.3–13.8)

Na+

1.64 (0.52–17.05)

2.33 (0.4–21.0)

NH+ 4

24.92 (0.56–78.90)

38.03 (0.6–220.6)

NO 3

15.07 (6.29–50.33)

78.61 (2.3–79.1)

Cl

1.49 (0.28–16.08)

4.74 (0.1–23.2)

22.83 (3.12–54.94)

29.32 (5.7–163.5)

SO2 4

Krupa and Pratt (1982), Krupa and Nosal (1999). a All values except pH in meq l1. Samples were collected during warm months only, at Lamberton, MN, USA. Range of long-term average daily air temperatures at Lamberton, MN, USA (between 1961 and 1995), during May–September: daytime: 17.1–30.2
C; nighttime: 3.7–17.5
C (M.W. Seeley, University of Minnesota, personal communication). b Average value. c Range.

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more SO2 4 during fall, winter and spring in the weekly composite compared with event samples. Weekly samples had significantly more Ca2+ and Mg2+ during seasons with little precipitation, while weekly and event NO 3 concentrations were never significantly different. Sisterson et al. (1985) attributed the observed differences to chemical degradation of the weekly samples while waiting in the field for retrieval and during shipment between the field site and the analysis laboratory. They also suggested possible biological conversion of  NH+ 4 to NO3 . It is equally possible that the dissolution 2+ of Ca and Mg2+ from the insoluble particulate fraction into the soluble fraction and the consequent increase in pH could have contributed to some conversion of NH+ 4 to NH3 and its volatilization. Chen et al. (2001) observed in Taipei (Taiwan) that with increasing time after sampling, there were comparable increases in + NO 3 and decreases in NH4 concentrations, using three different storage methods (filtration, refrigeration and the presence of light). The three storage methods used, respectively result in three different consequences: filtration—removal of the insoluble fraction, refrigeration—prevention or retardation of microbial activity and light—occurrence of possible aqueous phase photochemical reactions (e.g. photo-destruction of dissolved organic N; Anastasio and McGregor, 2000 or photoformation of CO from dissolved carbon, thus affecting the redox; Zuo and Jones, 1996). Thus, it is difficult to find a common mechanistic explanation for the observations of Chen et al. (2001), although changes in the solution acid-base equilibrium appears to be important, as indicated by differences in the sample pH between the three types of storage methods. Vesely´ (1990) found in Czechoslovakia that the concentration of free H+ was affected after deposition by several processes, the most important being bio+ consumption of NH+ 4 leading to an increase in the H level depending on the length of the sampling interval, the time of the year and the way the samples were stored prior to their analysis. Similarly in Kansas, Ramundo and Seastedt (1990) compared NH+ 4 concentrations in weekly composite rain samples split for analysis between two independent laboratories (Kansas State University and the Central Analytical Laboratory of the National Atmospheric Deposition Program, NADP, in Illinois, USA) and found that the NH+ 4 concentrations were lower in the NADP analysis, exhibiting a strong seasonally dependent difference from the Kansas State University laboratory. According to the authors the losses were not likely due to volatilization; microbial immobilization of NH+ 4 likely occurred during transport of the samples from the collection site to the NADP analysis laboratory. Precipitation chemistry data derived from more than six years of concurrent sampling involving weekly composite versus daily samples were analyzed by Lamb and

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Comrie (1993). The most notable bias occurred for NH+ 4 concentration in the weekly samples, a finding consistent with all the other studies. The authors concluded that this bias may be related to the relatively long time that the weekly samples remained in the field, thus strengthening the arguments in favor of the use of daily sampling protocols. The studies of Krupa and Pratt (1982) and Krupa and Nosal (1999) at an agricultural site in Minnesota provide a strong site-specific argument for the role of microbes. In this study, comparisons were made between in situ refrigerated event samples and weekly non-refrigerated, composite samples (Table 6). According to Ridder et al. (1985), in the Netherlands, storage of rainwater samples in the dark at 4
C resulted in a satisfactory sample preservation in comparison to samples left at room temperature. Almost all of the elements included in Table 6 are essential for microbial growth. In general, microbes do not grow at any measurable rate at refrigeration (  +5
C) temperatures and most microorganisms parasitic on vegetation are normally grown in the laboratory at 20–25
C (Ainsworth and Sussman, 1965). Overall, microbial populations in the atmosphere are known to be high in agricultural regions during the crop growth season (Agrios, 1997) and there are unpublished reports that composite rain samples can be turbid and slimy at some agricultural sites during the summer months. Turbidity, light scattering or absorption can be used as measures of microbial growth in dilute solutions (Ainsworth and Sussman, 1965). However, this author does not know of any precipitation sampling network where these types of variables are measured prior to the sample filtration to exclude the insoluble fraction. Nevertheless, such measurements should be made in the future to determine the importance of microbial activity in any observed changes in rain composition. In the past some investigators have used biocides such as very high purity thymol to prevent microbial activity (Gillett and Ayres, 1991). Although the approach appears to be desirable, great care must be used in adding an extraneous chemical constituent to the rain sampler. Therefore, use of biocides has neither been widely implemented in major precipitation sampling networks nor their use tested extensively for any modifications of the chemistry of the highly dilute and poorly buffered rain samples. In addition, the selection and use of a biocide will depend on the analyte(s) to be measured, without interference.

5. Physico-chemical analysis of precipitation 5.1. Insoluble fraction The physical and chemical properties of the insoluble fraction in precipitation have attracted very little

attention from scientists studying the phenomenon of acidic precipitation (Krupa et al., 1976a; Colin et al., 1987). However, it is widely recognized that prolonged lagtime between sample collection and analysis can result in the solubilization of certain components of the insoluble fraction, resulting in higher concentrations of ions such as Ca2+ (Peden and Skowron, 1978; Vesely´, 1990). Therefore, precipitation samples are routinely filtered prior to the quantitation of major ions, but no analysis is performed on the material gathered on the filter. In contrast, Georgii et al. (1982) described a wet combustion procedure of the filter and combining the extract with the soluble fraction to analyze total concentrations. The insoluble fraction in precipitation can be both biogenic (pollen, microbial spores, unicellular microorganisms and fragments of other organisms) and anthropogenic (agriculture- and industry-related particulate matter). In addition to its influence on the chemical equilibrium of the soluble component of precipitation, study of the insoluble fraction can provide insights regarding the human influence on precipitation scavenging and composition. In the field of aerosol science a number of multielement analysis techniques have been developed (Stevens, 1986). These include X-ray fluorescence (XRF); proton induced X-ray emission (PIXE) and instrumental neutron activation (INA) analyses (FinlaysonPitts and Pitts, 1999). All these techniques can be applied for the study of the insoluble fraction in precipitation. In addition, when sufficient mass of insoluble material is available, atomic absorption or emission spectrometry methods (see Section 5.2.2.2.) can be applied for cations and ion chromatographic methods for both anions and cations (see Sections 5.2.2.1 and 5.2.2.3). More recently application of capillary electrophoresis has come into vogue. In contrast to all the aforementioned methods, the approach that allows both morphological and semiquantitative characterization of the composition of the insoluble fraction is the combined scanning electron microscopy (SEM) and energy dispersive X-ray microanalysis (EDXM; Krupa et al., 1976a) or electron probe X-ray microanalysis (EPXMA; Jambers et al., 2000). 5.2. Soluble fraction 5.2.1. Speciation of acids pH is a measure of free H+ activity in a solution. Here the acidity of precipitation due to strong acids is of specific interest. However, the measured pH might not correspond to the true concentration of a strong acid, in the presence of weak acids and at precipitation pH > 4.0. To avoid this problem, a number of investigators have used direct alkalimetric (externally added OH) (Askne and Brosset, 1972; McQuaker et al., 1983;

S.V. Krupa / Environmental Pollution 120 (2002) 565–594

Sisterson and Wurfel, 1984) or coulometric (internally generated OH; Liberti et al., 1972; Krupa et al., 1976b) titration procedures based on the theory of Gran (1952) to determine the concentrations of strong and weak acids in precipitation. Although both direct alkalimetry and coulometry perform equally well for strong acids, alkalimetry has poor accuracy with precipitation samples containing low H+ concentrations (Liberti et al., 1972) and produces an overestimation of H+ concentrations in samples containing high NH+ levels 4 (Keene and Galloway, 1985). Thus, coulometry has certain desirable features over direct alkalimetry. 5.2.1.1. Theory of coulometry. An acidic rainwater sample is titrated by cathodic generation of hydroxyl ions at a constant current in a galvanic cell of the type: ðÞ reference electrodejtest solutionjglass electrode ðþÞ Hydroxyl ions are liberated at a platinum electrode: H2 O þ e  !

1 2

H2 þ OH

whereas at the anode (a silver–silver bromide electrode) silver bromide is formed: Ag þ Br ! AgBr þ e The e.m.f. (electro motive force) of the cell (E ) is given by: E ¼ E 0o þ

  2 3 RT log Hþ H þ Ej F

ð1Þ

583

As the ionic strength is kept almost constant by the addition of potassium bromide and the initial hydrogenion concentration of the sample is generally lower than 104 mol l1, gH and Ej do not change appreciably during the titration. F By plotting the function ¼ 10E2 3 RT versus t, a straight line is obtained. This line intercepts the abscissa at a value te that corresponds to the end-point of the titration (Fig. 15). The initial hydrogen-ion concentration, [H]o, from strong acids, is obtained from the relationship: ½H o ¼

ite FVo

ð4Þ

Continued generation of OH beyond the equivalence point can supply additional information if the function F 0 ¼ 10E2 3RT is plotted versus the generation time. By drawing a line through the experimental points a new intercept, te0 , is obtained (Fig. 15), from which an [H]o0 value is calculated; this value represents the acidity caused by strong and weak non-volatile acids that may be present in the rain sample [e.g. HSO 3 and hydrolyzable cations such as in NH4HSO4, Fe(H2O)3+ 6 , Al(H2O)3+ 6 , etc.]. Regarding SO2, it should be pointed out that if the initial pH of the sample is > 4.0, the SO2, which will be present as HSO 3 , will be titrated as a monoprotic weak acid. Pena et al. (1982) have reported up to 12% SO2 3 , of the total S ion measured normally as SO2 4 concentrations. The [H]o value will coincide with that of [H]o0 in the absence of weak acids. In this instance the graphs of

where Eo0 includes the potential of the reference half of the cell and the normal potential of the probe half of the cell, Ej is the liquid junction potential and gH is the activity coefficient of the hydrogen ion. For any value of time t, corresponding to the generation of it F1 equivalents of hydroxyl ion before the equivalence point, the following equation holds: 

Hþ

 Vo ½Ho itF 1 Vo

ð2Þ

were Vo ml is the volume of solution that is titrated, [H]o is the initial molar hydrogen-ion concentration from strong acids, i mA is the current, t is the time (seconds) and F is Faraday’s constant. From equations (1) and (2) the following is obtained:   2 3 RT Vo Ho  it F1 E ¼ Eo þ log F Vo 2 3 RT log H þ Ej þ F 0

ð3Þ

Fig. 15. Results of the application of Gran’s theory for c versus time (line 1) and c0 versus time (line 2) for the detection of the end-point of the coulometric titration of a rainwater sample. Liberti et al. (1972).

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the two functions will give straight lines that intercept each other on the abscissa (Fig. 15). When the solution contains a weak non-volatile acid, the graphs of the two functions will be curved; the extrapolations of the straight portions of these curves will not give the same intercept on the abscissa and the difference between the two intercepts will give a value for the acidity from weak acids. The average standard deviation for this measurement method is  5% and the limit of sensitivity is 0.1 mg ml1 (calculated as H2SO4). 5.2.1.2. Apparatus for coulometry. A measured sample of rainwater (50–75 ml) is transferred to a five-necked cell (Fig. 16). One neck holds the working electrode, polarized to act as a cathode, which is made of a platinum sheet (1.250.65 cm2); the anode, a coiled silver wire, is set in another neck. The glass indicator electrode and the reference electrode are placed in two other necks of the flask, the last available neck being used as an entry port for the nitrogen that is bubbled through the solution to render it free of carbon dioxide. A coulometric microtitrator is used as a constant-current generator operating in the range 0–10 mA. Subsequently potentiometric measurements are made with a glass electrode and a conventional fiber-type reference electrode. 5.2.1.3. Procedure for coulometry. The titration is carried out as follows: the solution is stirred magnetically and 0.02 mol l1 potassium bromide is added as a constant current carrier and to maintain the ionic strength. Nitrogen is then bubbled through the sample and the e.m.f. of the cell is measured. The potential becomes constant after a certain period, the exact length of which

Fig. 16. A schematic diagram of a measurement cell for coulometric titration. Liberti et al. (1972).

depends on the carbon dioxide concentration. When the electrolysis current (1–5 mA) is started, the e.m.f. of the cell is read at intervals of 20–30 s and the results are used to construct graphs by the use of Gran’s theory (Fig. 15). 5.2.1.4. Strong and weak acids in rain. As an example, Table 7 provides summary results on the concentrations of strong and weak acids in rain at six sites in Minnesota, USA. All these sites can be characterized as rural agricultural or as forested areas (Krupa et al., 1987). The weak acids are considered to be monoprotic inorganic or organic acids (Liberti et al., 1972; Guiang et al., 1984; Chapman et al., 1986; Kawamura and Kaplan, 1986). 5.2.2. Commonly measured constituents Commonly measured chemical constituents in pre cipitation are: anions—SO2 and Cl and 4 , NO3 + + 2+ 2+ + cations—H , NH4 , Ca , Mg , Na , and K+. 5.2.2.1. Anions. Whereas in the field of cation analysis both fast and sensitive analytical methods are available (atomic absorption spectrometry, inductively coupled plasma atomic absorption spectrometry, polarography and others), the lack of corresponding highly sensitive methods for anion analysis until now is noteworthy (Weiss, 1995). The conventional wet chemical methods such as titration, photometry, gravimetry, turbidimetry and colorimetry are all labor intensive, time consuming and occasionally troublesome. But with the introduction of ion chromatography in 1975, it quickly became the most widely used analytical method for quantifying the major inorganic anions in rain and other forms of precipitation (Fig. 17). According to Weiss (1995), ion chromatographic methods offer several advantages over conventional methods: (1) speed or short time needed for the analysis (10 min or less); (2) sensitivity (simple inorganic anions can be detected at a 10 mg l1 concentration in a 50 ml sample); (3) selectivity (this is ensured by selecting a combination of suitable analyte separation and detection systems); (4) simultaneous detection of multiple ions; and (5) availability of stable ion separator columns. Modern day ion chromatography is based on three different separation mechanisms. Ion-exchange chromatography. This separation method is based on an ion-exchange process with surface agglomerated latex that is oppositely charged to the surface functionality of the base particle. In ions with high polarizibility, additional non-ionic adsorption processes contribute to the separation mechanism. The stationary phase consists of a polystyrene resin copolymerized with divinylbenzene and modified with ion-exchange groups. Ion-exchange

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585

Table 7 Volume weighted mean concentrations of strong and weak acids in daily in situ refrigerated rain samples in Minnesota Sampling location

Weak acid (W) meq l

Lamberton Wright Sherburne Sandstone Grand Rapids Ely

Strong acid (S)

W/S

7.40 17.10 17.60 17.20 14.60 19.70

3.27 2.22 1.81 1.81 3.12 1.39

1

24.20 37.90 31.90 31.10 45.50 27.40

Krupa et al. (1987).

chromatography is used for the separation of both organic and inorganic anions and cations, respectively. Separation of anions is accomplished with quaternary ammonium groups attached to the polymer, whereas sulfonate groups are used as ionexchange sites for the separation of cations. Ion-exclusion chromatography. The separation mechanism in ion-exclusion chromatography is governed by Donnan exclusion, steric exclusion and sorption processes. A totally sulfonated polystyrene/ divinylbenzene-based cation exchange material with high capacity is employed as the stationary phase. Specific to the present context, ion-exclusion chromatography is particularly useful for the separation of weak inorganic and organic acids from those acids that are completely dissociated at the eluent pH. All acids with high acid strengths are not retained and elute unresolved within the void volume. Ion-pair chromatography. The dominating separation mechanism in ion-pair chromatography is adsorption. The stationary phase consists of a neutral porous divinylbenzene resin of low polarity and high specific surface area. Alternatively, chemically bonded silica phases of the octyl or octadecyl type with an even lower polarity can be used. The selectivity of the separator column is determined solely by the mobile phase. Besides an organic modifier, an ion-pair reagent is added to the eluent (water, aqueous buffer solution, etc.) depending on the chemical nature of the analytes. Ion-pair chromatography is particularly suited for the separation of surface-active anions and cations as well as transition metal complexes. After separation and post-column derivatization if required, analyte detection systems include: (1) conductimetry; (2) amperometry; (3) UV–visible wavelength photometry; and (4) fluorescence photometry. For details of these systems, the reader is referred to Weiss (1995) and Fritz and Gjerde (2000). A proper combination of the separation and detection methods can allow the quantification of numerous chemical constituents in precipitation (Tables 8 and 9). However, at the present time ion chromato-

Fig. 17. Chromatogram of a synthetic mixture of inorganic anions. Separator column: IonPac AS4A; eluent: 0.0017 mol l1 NaHCO3+0.0018 mol l1 Na2CO3; flow rate: 2 ml min1; detection: suppressed conductivity; injection: 50 ml; solute concentrations: 3 mg 1 l1 F, 4 mg l1 Cl, 10 mg l1 NO Br, 20 mg l1 NO 2 , 10 mg l 3, 1 10 mg l1 HPO2 SO2 4 and 25 mg l 4 . It is important to note that in rain many of these ion concentrations will be lower than in the standard mixture. If refrigeration and proper chemical fixation procedures are used in sampling rain and measurable concentrations of SO2 3 are 2 found, its elution peak will appear between those of NO 3 and HPO4 in the chromatogram. Modified from Weiss (1995).

graphy is being used primarily in the major networks (e.g. US National Atmospheric Deposition Program, NADP) to quantify inorganic anions in precipitation. In this context, Butler et al. (1978) compared results of automated colorimetric procedures for the quanti2 fication of NO 3 and SO4 against the corresponding data from ion chromatography. While the results between the two methods are comparable, the simplicity and speed of simultaneous multiple ion detection by ion chromatography leads to its clear preference where many samples must be analyzed. Capillary electrophoresis. In the past decade, beyond the application of ion chromatography (IC), significant progress has been made in the use of capillary electrophoresis (CE) for quantifying anions, cations (alkaline, alkaline earth and transition metals) and

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Table 8 Overview of the ion chromatographic separation methods Separation methoda

Functionality of resin

Recommended eluents

Analyzable species

þ

Ion exchange (Anions)

 N R3

Na2CO3/NaHCO3

2 2 F, Cl, Br, I, SCN, CN, H2PO 2 , HPO3 , HPO4 , 5   2 2 2 2 2 P2O4 7 , P3O10 , NO2 , NO3 ,S , SO3 , SO4 , S2O3 , S2O6 ,    2 2 2  S2O2 , OCl , ClO , ClO , ClO , SeO , SeO , HAsO 8 2 3 4 3 4 3 , 2 2 WO2 4 , MoO4 , CrO4 , carbohydrates, peptides, proteins, etc.

Ion exchange (Cations)

–SO 3

HCl/HCl/DAPa

+ + + 2+ Li+, Na+, NH+ , Ca2+, Sr2+, 4 , K , Rb , Cs , Mg Ba2+, small aliphatic amines.

–SO 3 /  N R3 +

Oxalic acid PDCAb

Fe2+, Fe3+, Cu2+, Ni2+, Zn2+, Co2+, Pb2+, Mn2+, Cd2+, Al3+, Ga3+, V5+, UO2+ 2 , lanthanides.

Ion exclusion

–SO 3

HCl Octane–sulfonic acid

Aliphatic carboxylic acids, borate, silicate, carbonate, alcohols, aldehydes.

Ion pair formation (Anions)

Neutral

NH4OH TMAOHc TPAOHd TBAOHe

In addition to the anions listed under HPIC: anionic surfactants, metal-cyano complexes, aromatic carboxylic acids.

Ion pair formation (Cations)

Neutral

HCl Hexane–sulfonic acid Octane–sulfonic acid

In addition to the cations listed under HPlC: alkylamines, alkanolamines, quaternary ammonium compounds, cationic surfactants, sulfonium compounds, phosphonium compounds.

þ

Modified from Weiss (1995). a DAP=2,3-diaminopropionic acid. b PDCA=pyridine-2,6-dicarboxylic acid. c TMAOH=tetramethylammonium hydroxide. d TPAOH=tetrapropylammonium hydroxide. e TBAOH=tetrabutylammonium hydroxide.

organic acids in aqueous solutions (Fritz and Gjerde, 2000). As opposed to IC that requires a liquid mobile phase and a column with a stationary phase, CE depends on ion mobility when placed in an aqueous or background electrolyte (BGE) buffer in a capillary column (e.g. fused silica) and subjected to high voltage (0–30 kV power supply) across the capillary. While the appropriate form of voltage (positive or negative power source) is applied at one end of the capillary, detection of the separated ions occurs at the opposite end. Ions are separated based on their differences in mobility in the buffer when the electric field is applied. When an electric field is applied through narrow capillaries, it induces a flow within the capillary known as ElectroOsmotic Flow (EOF), considered to be the pump in CE. Ions eluting from the capillary are detected for example by the use of UV sensors through direct (absorbance) or indirect (by adding an absorption reagent to the BGE, such as chromate) methods. The capillary length varies from 20 to 100 cm and the diameter from 10 to 100 mm. Thus, the main advantages of EC are the need for very small sample volumes (nl) and rapid detection of the ion(s) of interest. Therefore, the throughput of samples is dramatically increased. Kuchida et al. (1992) quantified the con-

 centrations of Cl, NO 3 , and SO4 in rainwater in less than 3 min, in comparison to roughly double that time for IC. The correlation coefficient between the results from the two methods was > 0.99. Minimum detection limit for the ions was < 0.1 mg l1. Tenberken and Ba¨chmann (1996, 1997) used CE to characterize the chemical composition of single cloud and fog water droplets. CE instruments are commercially available from several different manufacturers. Perhaps the most desirable method for separation of ions would be one that combines the principles of IC and CE into a single technique (Kar and Dasgupta, 1996). One easy way to separate ions on the basis of both their electrophoretic and ion exchange behavior is simply to add a water soluble ion exchange polymer to the BGE in a conventional CE method (Fritz and Gjerde, 2000). This approach is rapidly evolving and represents the state of the art.

5.2.2.2. Cations. Most scientists and precipitation sampling and chemical analysis networks use spectrometric techniques to quantify cations other than H+ and NH+ 4 (Table 10). While the free H+ concentration is measured by the use of a pH electrode, precautions must be taken in such an approach (McQuaker et al., 1983; Sis-

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587

Table 9 Overview of the ion chromatographic detection methods Detection method

Principle

Application

Conductometry

Electrical conductance

Anions and cations with pKa or pKb <7.

Amperometry

Oxidation and reduction at Ag-/Pt-/Auand glassy carbon electrodes

Anions and cations with pKa or pKb >7.

UV/V is detection with or without post-column derivatization

UV/V is light absorption

UV active anions and cations, heavy metals after reaction with PARa and Tironb, polyvalent anions after reaction with iron(III), silicate and phosphate after reaction with molybdate, alkaline-earth metals after reaction with Arsenazo I.

Fluorescence in combination with post-column derivatization

Excitation and emission

Ammonium, amino acids, and polyamines after reaction with s-phthaldialdehyde.

Weiss (1995). a PAR=4-(2-Pyridylazo)resorcinol. b Tiron=4,5-Dihydroxy-1,3-benzenedisulfonic acid-disodium salt.

terson and Wurfel, 1984; Midgley, 1987). Conventional electrodes measure free H+ activity instead of the actual H+ concentration or free acidity. Correction from activity to concentration is a function of ionic strength and can be large for the low ionic strengths typical of precipitation samples. In addition, differences between the sample and standard calibration buffer solution ionic strengths can result in liquid-electrode junction potentials that affect the electrode readings. Streaming potentials due to the stirring of precipitation samples can cause the single, largest error in pH measurements. Sisterson and Wurfel (1984) have described procedures to reduce individual types of errors in pH measurements. In addition, the reader is referred to a previous section of this review on the speciation of acids in precipitation. In the past most scientists have quantified NH+ 4 concentrations by colorimetry or by an ion selective electrode. Currently most investigators use segmented flow or flow injection techniques (see Table 10), excluding ion chromatography. Frequently spectrometric techniques are used to measure major as well as trace metals (e.g. Table 10). Here, the three popular approaches are: atomic absorption; atomic emission and inductively coupled plasma atomic emission. Table 11 provides a comparison of the minimum detection limits for the three methods. Depending on the element to be analyzed, each method has its strengths and weaknesses. At the end, in a broadspectrum elemental analysis, all three methods are comparable. In addition to these, capillary electrophoresis can be used to quantify cation (alkaline, alkaline earth and transition metals) concentrations in aqueous samples (Fritz and Gjerde, 2000). 5.2.2.3. Simultaneous measurement of anions and cations. Tanaka et al. (1994) have developed a simple,

selective and sensitive method for simultaneously deter2 mining major anions (Cl, NO 3 , SO4 ) and cations + + + 2+ 2+ (Na , NH4 , K , Mg , Ca ) in acidic precipitation (Table 12). The method involves combined ion-exclusion and cation-exchange chromatography with conductimetric detection, using a polyacrylate weakly acidic cation-exchange resin column and a weak acid eluent. Owing to the presence of H+ ions in the eluent, the detector response will be positive for the anions and negative for the cations. With a 5 mM tartaric acid— 7.5% methanol–water eluent, good simultaneous separation and detection of anions and cations were achieved in about 30 min. The results from central Japan indicated an ion balance of about 100% between the anions (including HCO 3 ) and the cations (including H+) in precipitation. Following the development of a second formulation for ion separation (Tanaka et al., 2000), recently Tanaka et al. (2001) have reduced the time required for the simultaneous determination of anions and cations from  30 to  14 min using high-performance ionexclusion/cation exchange chromatography with conductimetric detection. The separator column was packed with polymethacrylate-based weakly acidic cation-exchange resin in the hydrogen-form and the eluent was 1.5 mM sulfosalicylic acid-6 mM 18-crown-6 at pH 2.6, operated at 1.5 ml min1. 5.2.3. Uncommonly measured constituents Table 13 provides a listing of some uncommonly measured constituents in precipitation and the analysis methods used. It is beyond the scope of this review to provide details regarding each of these and therefore, the reader is referred to the specific references provided in the table. Nevertheless, such measurements have a broad spectrum of applications in our understanding of: (1) changes or trends in mobile source emissions (ionic

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Table 10 Commonly measured variables in precipitation and methods of their determination (The US National Atmospheric Deposition Program/ National Trends Network)

Table 12 Simultaneous measurement of anions and cations by combined ionexclusion and cation-exchange chromatography: retention volumes (VR) and detection limits for the major ions

Variable

Measurement method

Method number

Lower limit of detection, mg l1

Ion

Na+ K+ Ca2+ Mg2+ NH+ 4 SO2 4  NO3 PO3 4 Cl

AAS AAS AAS AAS AC IC IC IC IC

200.6 200.6 200.6 200.6 N/Aa 300.6 300.6 300.6 300.6

3.0 3.0 9.0 3.0 20.0 30.0 30.0 20.0 30.0

Specific conductance pH

EL EL

SO2 4 (S) S2O2 3 (S) Cl (S) PO3 4 (W) Br (S) NO 3 (S) I (W) NO 2 (W) F (W) HCOO (W) CH3COO (W) Li+ Na+ NH+ 4 K+ Rb+ Cs+ Mg2+ Ca2+ Sr2+ Ba2+

120.6 150.6

0.1 mS cm1 0.01 unitsb

b

AAS, atomic absorption spectrometry; AC, automated colorimetry; IC, ion chromatography; EL, electrometry. Malo (1990). a NH+ 4 analysis methodology was switched from segmented flow (SFA) to flow injection (FIA). Though equivalency has been established for these two implementations of the same chemistry, no separate method designation number has been established. b Not the lowest value measured, but rather the lowest difference detected between two measurements; a measure of sensitivity.

Table 11 Minimum detection limits (MDL, mg l1) attainable with three different types of methods used for the analysis of cations Element

FAASa

FAESb

ICP–AESc

Al Ba Ca Cr Cs Cu In K Li Mg Mn Na Rb Sr V

10.00 10.00 1.00 2.00 – 1.00 20.00 1.00 3.00 0.10 2.00 0.50 2.00 2.00 40.00

10.00 1.00 0.10 5.00 8.00 10.00 5.00 3.00 0.03 5.00 5.00 0.10 0.30 0.10 10.00

20.00 0.50 0.10 5.00 – 3.00 20.00 15.00 3.00 0.20 1.00 0.20 15.00 0.20 2.00

Modified from Lajunen (1992). a FAAS, flame atomic absorption spectrometry. b FAES, flame atomic emission spectrometry. c ICP–AES, inductively coupled plasma–atomic spectrometry.

emission

alkyllead); (2) heterogeneous atmospheric liquid phase S chemistry (H2O2); (3) biogenic versus anthropogenic influences on wet deposition (stable isotopes); (4) local emission source contributions versus long range trans-

VR (ml)

6.77 6.80 7.43 7.62 7.75 7.98 9.12 11.02 11.26 12.67 13.26 20.76 21.12 22.07 22.43 22.23 22.37 44.40 47.47 48.20 67.80

Detection limita mM

ppb

0.16 – 0.10 – – 0.14 – – – – – – 0.20 0.30 0.32 – – 0.28 0.28 – –

15 – 3.6 – – 9 – – – – – – 4.6 5.4 12.5 – – 6.8 11.2 – –

S, strong acid anion; W, weak acid anion. Modified from Tanaka et al. (1994). a Signal-to-noise ratio=3.

port to precipitation composition (reduced S and N species, stable isotopes); and (5) environmental impacts of select toxic chemicals (Hg, PCBs). Clearly there are many other examples of these types of studies that are beyond the scope of large scale network type efforts. 5.2.4. Analysis of the chemistry of individual raindrops Ba¨chmann et al. (1993) used chromatographic methods for the chemical analysis of individual raindrops. The main problem with such methods relates to the fact that a single raindrop will provide only a small volume of water for analysis. In addition, the concentration of the analyte will be very low. Compared with high pressure liquid chromatography (HPLC), micro-HPLC methods have the advantage of lower detection limits. Consequently, present day analytical methods based on HPLC were improved and adapted to micro-HPLC. Table 14 compares the absolute detection limits of HPLC and micro-HPLC. Compared with HPLC, in micro-HPLC the absolute detection limits are improved by a factor of 5–50. Normally, Gran titration (Section 5.2.1.) is used to measure the free and total acidity. The volume needed for this is much larger than the volume of individual drops; Ba¨chmann et al. (1993) used a flow injection analysis (FIA) system with an injection volume of 4.5 ml.

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S.V. Krupa / Environmental Pollution 120 (2002) 565–594 Table 13 Examples of some uncommonly measured precipitation constituents Chemical constituent used (abbreviation)

Analysis method

Reference

Hydrogen peroxide (H2O2)

Chemiluminescence/luminol+hemin

Yoshizumi et al. (1984)

Ionic alkyllead (IAL)

Differential pulse anodic stripping voltametry/ diethyldithiocarbamate complex followed by acid water extraction

Mikac and Branica (1994)

Mercury (Hg)

Atomic fluorescence spectrometry Atomic fluorescence spectrometry

Ferrara et al. (1986) Vermette et al. (1995a)

Methane sulfonic acid (MSA)

Ion chromatography/Dionex AG4A anion guard column+AS4A anion separator column+AMMS1 anion fiber suppressor column

Mihalopoulos et al. (1993)

Nitrogen (15N/14N), oxygen (18O/16O), strontium (87Sr/86Sr) sulfur (34S/32S) Isotope ratios

Mass spectrometry/extraction—precipitate formation

Heaton (1987), Andersson et al. (1990), Herut et al. (1995), Jamieson and Wadleigh (2000)

Organic acids (COOHs)/organic matter (polyaromatic hydrocarbons, PAHs, etc.)

Ion chromatography/Dionex ICE 30888 HPICE suppressor column+ICE 30891 ISC separator column Ion exclusion chromatography or gas chromatography– mass spectrometry/chloroform extracts Gas chromatography–mass spectrometry/ methylchloride extraction at pH 1.0

Chapman et al. (1986)

Pesticides (PEs) (e.g. fenobucarb, propyzamide)

Gas chromatography–mass spectrometry–selective anion monitoring/dichloromethane extraction

Haraguchi et al. (1995)

Polychlorinated biphenyl congeners (PCBs)

Gas chromatography/electron capture detector

Murray and Andren (1992b)

Reduced sulfur (S(IV)) and nitrogen (NO 2 ) species

Colorimetry/pararosaniline reaction of fixed S(IV) with tetrachloromercurate Ion chromatography subtraction/total SO2 4 with and without S(IV) oxidation with Br For NO 2 , spectrophotometry/British Standard Method No. 2690, 1968 (reagents: Sulphanilic and Cleve’s acid solutions)

Hara and Okita (1990)

Guiang et al. (1984) Kawamura and Kaplan (1986)

Guiang et al. (1984) Radojevic´ (1986)

Total amine nitrogen (TAN)

High pressure liquid chromatography/derivatization with s-phthaldialdehyde-2-mercaptoethanol reagent

Gorzelska et al. (1992)

Trace metals (Tms)

Inductively coupled plasma–mass spectrometry Atomic absorption spectrometry/deuterium arc

Vermette et al. (1995b) Ba¨chmann et al. (1995)

Quality control was tested by comparing bulk measurements and size fractions weighted by volume fraction (Ba¨chmann et al., 1993). The size distribution of raindrops as a function of time was measured by optical spectrometry. Good agreement was found between the raindrop size measured by the Guttalgor and by the optical spectrometer. 1. The analysis of alkaline and alkaline earth metals was performed with cerium (III) as the eluent (Shermann and Danielson, 1987) on two cation exchange columns of different capacity [ION-210

metals column (ICT) and Fast Cation 1 (Dionex Corp., Sunnyvale, CA, USA)]. With column + 2+ switching, Na+, NH+ , and Ca2+ 4 , K , Mg were separated in one run (Ba¨chmann et al., 1989). 2 2. The anions, Cl, NO 3 , and SO4 were separated by a PRP X-100 column (Hamilton Co., Reno, NV, USA). A 3 mmol l1 Na2CO3-buffer with 6% acetonitrile and 0.17 mmol l1 of p-cyanophenol was used as the eluent and a suppressor system was employed with a conductivity detector. The limits of detection for the simultaneous

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stand the fundamental, but complex aspects of the human influence on atmospheric deposition of beneficial and toxic chemical constituents onto surfaces; and (2) to determine the extent of wet deposition, its ionic concentrations and their adverse environmental impacts. Significant advances have been made during the last decade for sampling and physico-chemical analysis of rain, cloud and fog water. In contrast, very little progress has been made with the collection of snow samples to preserve their initial integrity from the time of deposition. Present-day technology allows continuous measurements of major ions in rain as it is falling. There are also methods for sampling and analyzing individual rain, cloud and fog water droplets. Such levels of deposition data resolution are not matched, to a large degree, by the state of ecological effects research. Biological receptor responses have not been shown to match the dynamics of wet deposition. Scientists investigating biological effects have continued to view single causeand-effect relationships. Future research must view the atmosphere in its dynamic and stochastic interactive components of dry and wet deposition and consequently, they must include these considerations in the assessment of any ecological effects. This is largely a problem related to the inadequate coupling of information between physical and biological sciences.

measurements of the anions are between 2 and 10 pg ml1 (Table 15). 3. The free and total acidity were determined with FIA associated with a gradient mixing technique and UV/V is wavelength detection. In this system free acidity and the sum of free and bonded hydrogen ions can be determined in a few microliters (4.5 ml) of the sample by reaction with suitable acid/base indicators (detection limits: 2.4 pmol (free acidity), 110.0 pmol (total acidity; Sprenger and Ba¨chmann, 1991). More recently, Tenberken and Ba¨chmann (1996, 1997) have used capillary electrophoresis to analyze the chemical composition of single cloud and fog water droplets.

6. Conclusions Sampling and physico-chemical analysis of precipitation are based on two major objectives: (1) to under-

Table 14 Comparison of the absolute detection limits of high pressure liquid chromatography (HPLC) and micro-HPLC Ion

Conventional systema LOD (pg)b

Micro-bore systemc LOD (pg)

Li+ Na+ NH+ 4 K+ Mg2+ Ca2+

12.50 25.00 50.00 50.00 50.00 100.00

0.35 1.00 8.00 10.00 5.00 25.00

7. Addendum Since the preparation of this review, Moore et al. (2002) and Straub and Collett (2002) have developed and calibrated a 5-stage cloud water collector based on the principles of cascade inertial impaction. Sampled cloud water is separated into 5 classes based on the droplet size.

Ba¨chmann et al. (1993). a Column: length 100 mm  diameter 3.2 mm. b LOD, lower limit of detection. c Column: length 130 mm  diameter 0.25 mm.

Table 15 Element/species concentration detection requirements for individual raindrop analysis Element/species

LODa rain (pg)

LODb(pg)

Volume(mg l1)

Method

Na+ NH+ 4 K+ Mg2+ Ca2+ Cl NO 3 SO2 4 H+ Total acid

30.0 30.0 30.0 5.0 30.0 10.0 50.0 80.0 5.0 10.0

1.0 8.0 10.0 5.0 25.0 20.0 10.0 50.0 3.0 110.0

1.0 1.0 1.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5

Micro-ICa Micro-IC Micro-IC Micro-IC HPLC HPLC HPLC HPLC FIA FIA

IC, ion chromatography; HPLC, high pressure liquid chromatography; FIA, flow injection analysis. Ba¨chmann et al. (1993). a Requirement of LOD (lower limit of detection) for the analysis of individual drops without any enrichment procedure. b LOD that has actually been achieved for the analysis of individual drops.

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Acknowledgements The author is grateful to J.P. Lodge, Jr. (Boulder, CO, USA), R.K. Stevens (formerly of the USEPA), U. Da¨mmgen (Federal Agricultural Research Institute, Germany), T. Kommedahl (University of Minnesota) and two anonymous scientists for their very valuable peer review comments on an earlier version of this manuscript. Thanks are due to Leslie Johnson (word processing) and Charlie Barnes and Sid Simms (graphic art production) for their critical help in the preparation of this manuscript. The author acknowledges the support-in-kind by the University of Minnesota Agricultural Experiment Station in the preparation of this review.

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