United States Department of Agriculture

Forest 

Service

Pacific Southwest 

Research Station

General Technical Report

PSW-GTR-257

March 

2018

Passive Monitoring Techniques for 

Evaluating Atmospheric Ozone and 

Nitrogen Exposure and Deposition to 

California Ecosystems

Mark E. Fenn, Andrzej Bytnerowicz, and Susan L. Schilling
This publication is available online at www.fs.fed.us/psw/. 

Pacific Southwest Research Station

800 Buchanan Street

Albany, CA 94710

Authors

Mark E. Fenn is a research plant pathologist, Andrzej Bytnerowicz is a research 

ecologist emeritus, and Susan L. Schilling is an information technology specialist, 

Pacific Southwest Research Station, 4955 Canyon Crest Dr., Riverside, CA 92507.

The use of trade or firm names in this publication is for reader information and 

does not imply endorsement by the U.S. Department of Agriculture of any product 

or service.

Cover Art: Top row from left to right: Passive sampler array installed in the White 

Mountains of California, change-out of passive samplers at Devils Postpile National 

Monument (the Granite Dome site), closeup view of a passive sampler array, 

collocation of ion exchange resin (IER) deposition samplers and passive samplers 

for monitoring gaseous pollutants in the Lake Tahoe Basin (All photographs in 

top row, and middle photo in bottom row by Andrzej Bytnerowicz, USDA Forest 

Service Pacific Southwest Research Station (PSW). Bottom row from left to right: 

IER throughfall collector in a forest clearing; IER throughfall collectors with snow 

tubes inserted into the sampling funnel, in the Lake Tahoe Basin; setup for filling 

the IER columns with IER beads (photos on the left and right hand side of bottom 

row are courtesy of USDA Forest Service, PSW Research Station). 
Abstract

Fenn, Mark E.; Bytnerowicz, Andrzej; Schilling, Susan L. 2018. Passive 

monitoring techniques for evaluating atmospheric ozone and nitrogen exposure 

and deposition to California ecosystems. Gen. Tech. Rep. PSW-GTR-257. 

Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station. 129 p.

Measuring the exposure of ecosystems to ecologically relevant pollutants is needed 

for evaluating ecosystem effects and to identify regions and resources at risk. 

In California, ozone (O ) and nitrogen (N) pollutants are of greatest concern for 3

ecological effects. “Passive” monitoring methods have been developed to obtain 

spatially extensive measurements of atmospheric pollutant concentrations and deposition flux inputs of N and other nutrient ions in California ecosystems. Two general types of passive samplers have been used: (1) passive samplers for determining 

time-averaged concentrations of gaseous pollutants in the atmosphere and (2) ion 

exchange resin (IER) collectors for measuring ionic deposition inputs. Common 

pollutants measured with passive samplers include nitrogen dioxide, nitric oxide, 

nitric acid vapor, ammonia, and O . Common ions measured with IER deposition 3

samplers include nitrate, ammonium, sulfate, phosphate, chloride, calcium, magnesium, potassium, and sodium. Laboratory and field methods, and the principles 

of use and appropriate applications for these atmospheric and deposition samplers, 

are described. Data from monitoring networks using these techniques help identify 

areas at risk and provide the foundation for describing pollution impacts to sensitive 

resources. In this report, several alternative approaches for estimating N deposition 

are also considered as a guide for selecting appropriate techniques in ecosystemeffects studies in California and elsewhere. We emphasized that measurements of N 

deposition in precipitation (wet deposition) alone are highly inadequate for characterizing deposition inputs under the climatic conditions of California and much of 

the arid West. Dry deposition of N must also be accounted for by using methods 

such as those described herein. 

Keywords: Nitrogen deposition, passive samplers, ozone, air pollution, dry 

deposition, ecosystem effects, atmospheric deposition.
Summary

The objective of this report is to provide practical guidance on the use of passive 

sampling techniques for measuring atmospheric concentrations of ecologically 

important pollutants and for measuring atmospheric deposition of nitrogen (N) 

and other pollutants with an emphasis on California ecosystems. Exposure to 

sulfur dioxide and atmospheric deposition of sulfate and other inorganic ions can 

also be measured with these techniques, but elevated exposure to these pollutants 

is not as common as to N compounds and ozone (O ) in California. We focus on 3

nitrogenous pollutants and O as these are the pollutants most affecting forests and 3

other ecosystems in California and throughout the Western United States. Passive 

sampling techniques greatly expand our capacity to estimate pollution exposure 

and atmospheric inputs across the landscape, thus accelerating our understanding of deposition impacts. Passive samplers are particularly important in defining 

pollution gradients, which can be used to study ecosystem response to air pollution 

across such spatial gradients.

Two major types of passive samplers are considered in this report—passive 

samplers for measuring atmospheric concentrations of gaseous pollutants and ion 

exchange resin (IER) samplers for measuring ionic deposition inputs from solutions 

(i.e., precipitation or throughfall solutions). Typical units of measure for pollutant 

concentrations are micrograms of pollutant per cubic meter, [μg pollutant m-3]; or 

part per billion [ppb], and common units for deposition are kilograms of pollutant 

per hectare per year [e.g., kg N ha-1 yr

-1]. Passive samplers are based on passive diffusion of a pollutant through barriers (filters, screens) or diffusion tubes, and onto 

the collection medium, the latter chosen on the basis of its affinity to the pollutant 

gas to be sampled. When exposed to the atmosphere, the pollutant or its reaction 

product accumulates within the sampler. The IER deposition samplers adsorb and 

accumulate ions from a solution as the solution percolates through the IER column. 

For both types of samplers, monitoring is done “passively”; that is, without the need 

for electronic or active monitors. 

The primary advantage of passive samplers over methods of active monitoring 

is the potential to monitor at a much greater number of sites, including at remote 

sites without electrical power. With sufficient sampling density using passive samplers, maps can be generated from the monitoring data that show spatial distributions of air pollutant concentrations or deposition across the monitoring network. 

Such widespread monitoring is not feasible with active collectors. 

The primary advantage 

of passive samplers 

over methods of active 

monitoring is the 

potential to monitor at 

a much greater number 

of sites, including at 

remote sites.

The IER samplers are placed under tree canopies to measure throughfall deposition or in open, canopy-free sites to collect “bulk deposition,” which is composed 
mainly of wet deposition with some background level of dry deposition that is 

collected by the funnel collectors during dry periods. Note that throughfall or bulk 

deposition fluxes measured with IER collectors are an equivalent measurement to 

throughfall or bulk deposition fluxes measured by conventional methods in which 

the throughfall or bulk deposition solutions are collected for analysis. The difference is that with the IER method, only the ions accumulated within the IER column 

are measured, following ionic extraction in the laboratory. No solutions are retained 

by the IER collectors in the field. 

As with any technique, passive sampling approaches have their limitations. 

For example, passive samplers for measuring atmospheric pollutant concentrations 

provide time-averaged values, typically over a 2-week period or sometimes longer. 

Diurnal or continuous (e.g., hourly) concentration values are generally needed to 

measure some biological responses, particularly with phytotoxic pollutants such 

as O . Such data require active sampling with an electronic monitor, although 3

statistical methods have been developed to estimate diurnal patterns or O exposure 3

indices from passive sampler data.

Likewise, there are situations where the ionic concentrations, pH values, or 

event-based inputs of throughfall or precipitation solutions are needed for some 

study objectives. In such cases, collection of the sample solution is required using 

the more conventional approach, because with IER samplers, deposition solutions 

are not collected. However, in most ecosystem-effects studies, the total input 

flux of N or of other compounds is the most important information. A primary 

advantage of throughfall deposition measurements, collected either in solution or 

as ions captured with IER collectors, is that throughfall is an integrated sample of 

the ions originating from precipitation, snowmelt, cloudwater, or dry deposition 

intercepted by the canopy and subsequently washed from it. In a real sense, the 

vegetative canopy functions as a passive sampler of dry-deposited particles and 

gases and cloudwater deposition that is collected as throughfall. One drawback of 

the throughfall method is that a fraction (typically 20 to 30 percent) of the atmospherically deposited N is retained by the canopy and not measured as throughfall. 

Particularly relevant in arid and semiarid regions such as California is that no 

throughfall samples are collected unless precipitation or fog events have occurred 

during the sampling period. Likewise, during droughty periods, throughfall deposition fluxes may be lower than normal for a given site. 

Data on average concentrations of N pollutants as measured by passive samplers can be used to calculate dry deposition fluxes to forests or shrublands using 

the so-called inferential approach when sufficient additional data are available for 
parameters such as leaf area index, deposition velocity for key pollutants, stomatal 

conductance, land cover, etc. These and other approaches for estimating N deposition, and under what circumstances they are most appropriately applied, are also 

described. Sometimes the use of several approaches for estimating atmospheric 

deposition are recommended because of the difficulty and uncertainty associated 

with estimates of dry deposition flux measurements obtained from any given 

approach. In recent years, models for simulating atmospheric N deposition have 

improved and are being widely used to estimate total N deposition for the continental United States. Empirical deposition and atmospheric concentration measurements are needed to evaluate these simulated deposition fluxes and to obtain 

local-scale deposition estimates. Empirical monitoring data are also being used as 

input to hybrid empirical/simulation models. 
Contents

1 Chapter 1: Nitrogen and Ozone Air Pollution in California: Sources, 

	 	 Chemical	Forms,	Monitoring,	and	Ecological	Effects

1 1.1―The Nitrogen Air Pollution Problem

2 1.2―Units Describing Air Pollution Exposure and Deposition

2 1.2.1—Passive Samplers for Gaseous Pollutants

2 1.2.2—Throughfall and Bulk Deposition Samplers

3 1.3―Nitrogen and Ozone Air Pollution in California

6 1.4―Ecological and Environmental Effects of Nitrogen Deposition

 in California

6 1.5―Monitoring Ozone and Nitrogenous Air Pollutants of

 Ecological Importance

11 1.6―National Atmospheric Deposition Networks

13 1.7―Throughfall Deposition Monitoring

15 Chapter 2: Passive Monitoring for Atmospheric Concentrations 

 of Gaseous Pollutants

15 2.1―Uses of Passive Samplers and Pollutants Commonly Measured

16 2.2―Design of Passive Samplers

18 2.3―Preparation and Assembly of Passive Samplers

18 2.4―Calibration of Passive Samplers

20 2.5―Field Deployment of Passive Samplers

23 2.6―Laboratory Methods of Analysis Following Field Exposure

24 2.7―Data Processing, Calculation of Atmospheric Concentrations,

 and Pollutant Mapping

27 Chapter 3: Deposition Monitoring With Ion Exchange Resin 

 (IER) Collectors

27 3.1―Uses of IER Collectors and Definition of Terms

28 3.2―Pollutants Measured With IER Collectors

29 3.3―Design and Construction of IER Collectors

36 3.4―Field Deployment of IER Collectors: Placement, Number of Replicates,

 and Open Vs. Throughfall Collectors 

45 3.5―Exposure Times, Changeout of IER Columns, and Use of Snow Tubes

46 3.6―Prevention of Animal Disturbance and Contamination
52 3.7―Laboratory Methods of Analysis Following Field Exposure

54 3.8―Data Processing and Calculation of Deposition Rates

57 Chapter 4: Selected Approaches for Estimating Atmospheric 

 Nitrogen Deposition

57 4.1―Rationale for Deciding on the Best Approach

57 4.2―Throughfall Nitrogen Deposition, Branch Rinsing, and Using

 Epiphytic Lichens as Passive Samplers

63 4.3―Inferential Method of Calculating Dry Deposition of Nitrogen

63 4.4―Simulated Nitrogen Deposition

65 4.5―High-Elevation Systems: IER Bulk Deposition in Summer Plus

 Snowpack Sampling

67 4.6—Conclusions

68 English Equivalents

69 Acknowledgments

69 References

81 Glossary

83 Appendix 1: Laboratory and Field Standard Operating 

 Procedures for Passive Monitoring of Gaseous Pollutants

105 Appendix 2: Standard Operating Procedures for Measuring 

 Atmospheric Deposition Using Ion Exchange Resin Collectors
1

Passive Monitoring Techniques for Evaluating Atmospheric Ozone and Nitrogen Exposure...

Chapter 1: Nitrogen and Ozone Air Pollution in California: 

Sources, Chemical Forms, Monitoring, and Ecological Effects

1.1―The Nitrogen Air Pollution Problem

Contamination of aquatic and terrestrial environments with reactive nitrogen (N) is 

a worldwide problem (Galloway et al. 2003). As one noted author has written: “In 

relative terms, human activities now perturb the global N cycle to a greater extent 

than they interfere in the cycles of the other two doubly mobile elements, carbon 

and sulfur (Smil 2001).” Nitrogen can be deposited to Earth surfaces in wet and dry 

forms. Wet forms may include N in precipitation, mist, snowfall and rime ice, and 

in fogwater or cloudwater―the latter often referred to as occult deposition in the 

literature. Dry deposition of N to surfaces such as plant canopies, rocks, litter, or 

mineral soil occurs in gaseous and particulate forms. Primary emissions sources 

are any process that burns fossil fuels, industrial operations, and agricultural 

activities, among others. The transportation sector is a major N emissions source. 

Once released to the environment, an atom of reactive N can cause multiple effects 

in the atmosphere, in terrestrial ecosystems, in freshwater and marine systems, and 

on human health. This sequence of effects is known as the N cascade (Galloway et 

al. 2003). The state of California, owing to its high population and associated large 

usage of fossil fuels and extensive agricultural activities, experiences among the 

highest levels of nitrogenous air pollution in the United States. 

When considering ecological effects of nitrogenous air pollution, two exposure 

or input metrics are important: (1) the atmospheric concentration of the various 

N pollutants and (2) the atmospheric deposition fluxes (also called loads or mass 

inputs) of N. The former describes atmospheric exposure, and the latter is based on 

mass deposition inputs of N compounds to the ecosystem. Thresholds have been 

established for N deposition loads (critical loads) above which adverse effects may 

occur for forests and other ecosystems (Bobbink and Hettelingh 2011, Pardo et al. 

2011). These thresholds are widely used as an ecosystem-risk evaluation, management, protection, and policy tool (Fenn et al. 2011a). In some cases (e.g., for ammonia [NH ]), thresholds have been estimated for ecosystem protection from exposure 3

to gaseous pollutants based on their atmospheric concentrations (critical levels) 

(Cape et al. 2009). However, critical levels of N pollutants are not widely used, 

while critical loads are increasingly being developed and used in many countries 

(Bobbink and Hettelingh 2011, Fenn et al. 2011a, Pardo et al. 2011). 
2

GENERAL TECHNICAL REPORT PSW-GTR-257

1.2―Units Describing Air Pollution Exposure and 

Deposition

1.2.1—Passive Samplers for Gaseous Pollutants

Atmospheric exposure to gaseous pollutants is described as mass or volume of the 

pollutant per volume of atmosphere. Common mass/volume units are micrograms 

per cubic meter (μg m-3), such as μg NH m-3. Nitrogenous gases can also be 3

expressed on an elemental N basis (i.e., μg NH -N m-3 or μg HNO -N m-3 [for nitric 3 3

acid vapor]) allowing for direct comparison between various N pollutants. Volume/

volume units are expressed as parts per million (ppm) or parts per billion (ppb), 

where ppb = μl m-3 and ppm = μl L-1 [liter] . 

The formula to convert the volume/volume units of a gaseous pollutant to its 

mass/volume units (at 25 o

C and 760 mm Hg) is:

1 ppm = M/0.02445 (μg m-3), 

where M is the molecular weight of the pollutant.

As such, data from passive samplers describe the average concentration in the 

atmosphere of the gaseous pollutant measured over the monitoring period (typically 

2 weeks, but can be longer or shorter). 

1.2.2—Throughfall and Bulk Deposition Samplers 

In contrast, deposition samplers, either as throughfall measured under vegetation 

canopies or as bulk deposition in canopy-free or open sites, measure deposition 

fluxes or mass inputs to the system on an areal basis. Typical deposition units are 

kilograms per hectare per year (kg ha-1 yr

-1) or milligrams per square meter per year 

(mg m-2 yr

-1; notice the time unit). As with gaseous nitrogenous pollutants, deposition fluxes can be expressed as N per se (i.e., NH -N or NO -N) or as the ion of 4 3

interest (i.e., NH + [ammonium] or NO - [nitrate]). We generally prefer to express 4 3

the deposition in units of N for simplicity and clarity in communicating deposition 

values. In terms of ecosystem effects, generally the total N input, with all forms 

combined, is most relevant and is most often used to evaluate and describe ecosystem responses to N deposition. The major atmospheric forms of N and sulfur (S) 

pollutants and their ionic forms that occur in throughfall, wet deposition, or bulk 

deposition samples are shown in table 1.1. In some cases, such as when considering 

soil or watershed acidification effects, it is necessary to express deposition inputs 

on a chemical-equivalent basis. In this case, typical deposition units include equivalents per hectare per year (eq ha-1

 yr

-1). Such units are used as deposition fluxes for 
3

acidifying ions (NO -, NH +, sulfate [SO 2-]) and acid-neutralizing base cations 3 4 4

(calcium [Ca2+], magnesium [Mg2+], sodium [Na+], potassium [K+]). 

Table 1-1―Atmospheric forms of major inorganic nitrogen and sulfur 

pollutants, their primary sources, and ionic forms measured in throughfall 

and bulk depositiona

Atmospheric 

form Major anthropogenic emissions sources

Ionic 

deposition form

NH3 Concentrated animal feeding operations, including dairies, feedlots, poultry farms, etc.; fertilizer 

use; vehicles equipped with three-way catalytic 

converters

NH +

4

NH +

4 Mostly emitted as NH3 (see above) and converted 

to NH4

+

. Some industrial operations can emit + particulate NH4

+ NH4

NO Fossil fuel burning; transportation sector is largest 

emissions source; industrial activities

NO -

3

NO2 Primarily from emitted NO, which is converted to 

NO2

NO -

3

HNO2 and HNO3 These are secondary compounds originating from 

NO and other atmospheric reaction products

- NO3

NO -

3 Mostly originating from the oxidized N gases 

shown above. Some industrial operations can - emit particulate NO3

NO -

3

SO2 Fossil fuel burning, especially ships and heavy 

freight vehicles and trains. In California, emissions of SO are much lower than N pollutants

2- SO4

SO 2-

4

2

Mostly emitted as SO2 (see above) and converted 

to SO4

2-. Some industrial operations can emit 

2- particulate SO4

SO 2-

4

NH = ammonia, NH +

 = ammonium, NO = nitric oxide, NO - = nitrate, NO = nitrogen dioxide, HNO = 3 4 3 2 2

nitrous acid, HNO = nitric acid, SO = sulfur dioxide, SO 2- = sulfate. 3 2 4 a

 All pollutants listed in the first column are gaseous pollutants, except NH +, NO -, and SO 2-, 4 3 4

which are particulates or aerosols. 

1.3―Nitrogen and Ozone Air Pollution in California

Ecosystems in 

California are exposed 

to the highest ozone 

(O3) and N pollutant 

levels in the United 

States, and these 

two pollutants (N 

species and O3) 

are the major ones 

affecting ecosystems in 

California.

Ecosystems in California are exposed to the highest ozone (O ) and N pollutant lev- 3

els in the United States, and these two pollutants (N species and O ) are the major 3

ones affecting ecosystems in California and throughout much of the world. The gaseous N pollutants of primary ecological importance in California include nitrogen 

oxides (NO ) such as nitric oxide (NO) and nitrogen dioxide (NO ), in addition to x 2

nitric acid (HNO ), and NH . Particulate air pollution is another important source 3 3

of NO - and NH + (Bytnerowicz and Fenn 1996). Ozone is a secondary pollutant 3 4
4

GENERAL TECHNICAL REPORT PSW-GTR-257

formed from precursor N oxides and hydrocarbons, primarily emitted from fossil 

fuel burning such as from the transportation and energy sectors (Bytnerowicz et 

al. 2016). Ozone is phytotoxic to sensitive plant species (Fenn et al. 2003, Miller 

and McBride 1999) while N is a plant nutrient that is commonly growth limiting 

(Fenn et al. 1998). However, chronic inputs of N can disrupt the normal functioning and resilience of various ecosystems or vegetation types as summarized in 

section 1.4 (Fenn et al. 2003, 2010, 2011b). Although O is a widespread pollutant 3

causing human and ecosystem health effects, the primary focus of this report will 

be monitoring methods for nitrogenous pollutants. However, because of similarity 

in monitoring methods among pollutants, approaches for passive monitoring of 

exposure to O and deposition of ions other than N will also be briefly considered. 3

Deposition of SO 2- can also be elevated in sites where S-rich fuels are consumed 4

(e.g., emissions from ships and heavy freight), although S deposition is not a widespread problem in California (Bytnerowicz et al. 2016, Cox et al. 2013).

Primary sources of N emissions in California are from fossil fuel burning, 

of which mobile sources are prominent, in addition to agricultural and industrial 

activities. Expressed on a per-N basis, emissions of N statewide are nearly evenly 

divided between reduced and oxidized forms, with NOx emissions only 9 percent 

higher than NH emissions. (Cox et al. 2013). In addition to agricultural emissions, 3

NH emissions from light-duty vehicles equipped with three-way catalytic convert- 3

ers are also an important source (Bishop et al. 2010, Bishop and Stedman 2015). 

With recent downward trends in emissions of NOx in California (Bytnerowicz et 

al. 2016, Cox et al. 2013) and many other regions, reduced N forms (e.g., NH and 3

NH +) have become an increasingly large fraction of total N deposition (Du et al. 4

2014b). 

Regions of highest N deposition in California are near highly urbanized areas 

and areas affected by intensive agriculture. Urban air pollution is prominent in 

southern California and the central coast, while agricultural emissions are concentrated in the Central Valley. Urban and agricultural emissions in central and southern California result in elevated N deposition to wildlands in southern California 

and along the southern and western portions of the Sierra Nevada. Nitrogen deposition in California is lowest in the northern and eastern portions of the state (fig. 1.1). 

A characteristic feature of spatial patterns of N deposition in California are the 

steep declines in N deposition with distance from the source area. For example, in 

the San Bernardino National Forest in southern California, N deposition declines 

dramatically along a 45-km west-to-east gradient, from 71 kg ha-1

 yr

-1 near the town 

of Crestline to 8 kg ha-1 yr

-1 near Barton Flats (Fenn et al. 2008). Such gradients are 

a function of high-deposition velocities of reactive N compounds such as HNO and 3
5

eicvret SseroA FDSU

Figure 1.1—Map of total annual nitrogen (N) deposition in California. Nitrogen deposition was calculated using the Community Multi-scale Air Quality Model for the most polluted two-thirds of the state on a 4-km resolution grid. The relatively 

unpolluted regions in northern and in the far southeastern corner of the state were simulated on a 36-km grid resolution 

(Fenn et al. 2010, Tonnesen et al. 2007). This was overlaid with vegetation cover data from the California Gap Analysis 

Project (Davis et al. 1998) to identify forested areas. Nitrogen deposition in mixed-conifer forest areas was adjusted based 

on the linear relationship with empirical throughfall data using the method previously described in Fenn et al. (2010).
6

GENERAL TECHNICAL REPORT PSW-GTR-257

NH , and because of effective scavenging of N deposition in cloudwater by large 3

tree canopies (Fenn and Poth 2004). However, long-range transport of N pollutants 

can occur as fine particulates and along river drainages such as the San Joaquin 

River drainage traversing the Sierra Nevada (Cisneros et al. 2010).

1.4―Ecological and Environmental Effects of Nitrogen 

Deposition in California

Ecological and environmental impacts of atmospheric N deposition reported in 

California (Fenn et al. 2003, 2008, 2010, 2011b, 2015b) include enhanced growth of 

invasive exotic grasses, local extirpation of N-sensitive epiphytic lichen species—

leading to changes in lichen functional groups, increased bark beetle attacks and 

pine mortality in mixed-conifer forests, acidification of soils in forests and chaparral ecosystems, and N enrichment of remote lakes and changes in diatom assemblages. Additional impacts include elevated nitrate concentrations in streamwater 

and groundwater from chaparral and forested watersheds, increased greenhouse gas 

emissions, impaired visibility, and human health effects (Bytnerowicz et al. 2016). 

Recent studies indicate that N deposition can exacerbate fuel buildup in shrublands 

and desert ecosystems as a result of increased growth of invasive grasses. This 

increases the risk of fire and possible vegetation type change in these habitats 

(Fenn et al. 2010, 2015b). Similarly, the combined effects of O and N deposition 3

contribute to increased aboveground growth, stand densification, and greater bark 

beetle activity and tree mortality in forests already stressed by periodic drought and 

long-term fire suppression. In summary, when chronic atmospheric N deposition, 

common in much of California, shifts ecosystems from a natural state of low N 

availability to a N-enriched condition, undesirable effects such as those listed above 

often ensue. 

The combined effects 

of O3 and N deposition 

contribute to increased 

aboveground growth, 

stand densification, 

and greater bark 

beetle activity and tree 

mortality in forests 

already stressed by 

periodic drought 

and long-term fire 

suppression.

1.5―Monitoring Ozone and Nitrogenous Air Pollutants 

of Ecological Importance

Air pollution monitoring can be done by way of “active monitoring.” As mentioned 

above, this involves the use of electronic equipment that is generally used to provide 

continuous measurements of pollutant concentrations in the atmosphere. In contrast, “passive monitoring” entails the deployment of samplers that do not require 

electrical power. Instead, passive samplers accumulate the pollutants of interest 

that diffuse onto a collection medium such as various types of filter disks, usually 

coated with a chemical chosen because of a selective affinity to the pollutant gas 
7

to be sampled. Such passive samplers, when exposed to the atmosphere for a given 

period, measure time-averaged atmospheric concentrations of key gaseous pollutants. The major reactive N gases (NO, NO , HNO , NH ) are routinely monitored 2 3 3

with passive samplers (Bytnerowicz et al. 2005, Fenn et al. 2009). Passive samplers 

for measuring deposition fluxes capture ionic pollutants in solution from precipitation or throughfall as the ions are adsorbed onto IER material (Fenn and Poth 2004, 

Fenn et al. 2009). 

The primary advantage of passive samplers over methods of active monitoring is the potential to monitor at a much greater number of sites, including remote 

sites without electrical power or easy access (fig. 1.2). With sufficient sampling 

density—using passive samplers, maps or graphs can be generated from the monitoring data that show spatial distributions of air pollutant concentrations (Bytnerowicz et al. 2010, 2016, Frączek et al. 2003) or deposition across the monitoring 

network (figs. 1.3 and 1.4). Such widespread monitoring is not feasible with active 

collectors. With sufficient spatial sampling intensity, maps of throughfall deposition eicvret SseroA FDSU

Figure 1.2—Passive sampling approaches are particularly useful for monitoring remote sites, such 

as in the boreal forest in the Athabasca Oil Sands Region in northern Alberta, Canada, where 

many of the study sites are accessible only by helicopter. 
8

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDSU A, Csdnalde, Retuittsnh Icraeses Rmetsyl Satnemnorivn, Ekezcąld FroitW

Figure 1.3—(A) Map of passive sampler network in southern California and (B) geographic information system mapping of average 

nitric acid (HNO ) concentrations across the sampler network for July 12–27, 2005. 3

A

B
9

eicvret SseroA FDSU

e 

c 

h

f 

ina

s t

) o

s

s

g

o

r

r

r

e

o

c

t

n

e

d i

d a

mo

e

e

l

r

v

i

l

u

k

o

s

s

ae

e (

si

s m

c

d d

nat

n

a

s

) ay

n w

ie d

l

o

h

e

it

v

i

t t

it

s

n

c

o

e

p

s

e

e

e

ps

. D

rp

e

e

, r

ad

e

s r

t

a

i

a

n

x

r

a

a

t

-

i

, C

d n

a

e x

n

t

h

.l

, a

r e

a

b

n t

v

m

l

s o

re

iu

eu

n

n A

tn

r

l

o

e

a

e i

m

ht

c

. V

n

m

r

s

e

o

, a

r

d

e

if

e

n

t

n n

lp

a

m

o

f

n i

l

a

o

u

i

s

g

n s

f = c

N (

e

o

n

it

o

-

i

3

s R

s

, c

O

d

o

n

d N

na

p

o

e

l S

i

n

i

F d

ge

, a

s R

N

a O

n T

d

i

-

c

s

n

4

s

e

a

H

aba

e r

l S

, N

i

h

g

S- 4

e At

nah

a O c

O

c

s

h

x

a

f S

n t

n e

ba

s o

r i

o

h

e

h i

t

e

t

x

n

t

e

i

e A

u

h

l

l c

f t

n f

a

4 w

i

1

oi

r

0

r o

t

t

y 2

e

is

s

t

u

n

o

d

a

e

p

n

e

l c

e i

) d

h

o M

a

F

8 t

i

m t

rts

T

0

u

l (

o

0

d

laf

r

n

e f

y 2a

e i

h

c

h

g

n

u

a

o

ts

m t

r

i

m M o

o

h

r

l t

h d

r

t

k f

e f

a

t

i

r

i

u

o

nn

, w

w

g s

)

t

n

A

N

e

i

—

r

I

o

D

g n

t

4

n (

i

n

e 1.

ir

no

e

o

r

g

ti

u

or

n

h m

g

t

o

c

i

i

a

Fnme
10

GENERAL TECHNICAL REPORT PSW-GTR-257

across the landscape can be developed based on statistical models using relationships between landscape characteristics (e.g., topographic exposure, elevation, 

intensity of fog deposition, and vegetation type) and throughfall deposition fluxes 

(Fenn et al. 2009, Weathers et al. 2006). 

Monitoring throughfall, wet or bulk deposition, with conventional solution 

samplers requires that the samples be collected soon after a precipitation event to 

prevent microbial or other types of contamination (sometimes biocides are added to 

reduce this problem) or evaporation of the samples. Thus, frequent field sampling is 

needed. Consequently, a much greater number of samples are collected for laboratory analysis, although this is sometimes reduced by compositing samples from different precipitation events. In contrast, we generally use only two sampling periods 

per year for IER (passive) throughfall sampling. Another consideration is that if a 

large deposition network is needed to define deposition gradients or surfaces, collecting liquid samples on an event basis would require a number of field crews and 

greater logistical sampling complexity at unknown frequencies owing to the unpredictable timing of precipitation events. In addition, samples collected at remote 

sites are perishable and require storage at low temperatures during transit. In 

contrast, IER columns from passive deposition samplers are collected infrequently 

and are not time sensitive or perishable. We calculate that total annual deposition 

monitoring and analysis costs (for N and S) are six times higher with conventional 

throughfall samplers compared to a passive sampling approach in the first year 

when equipment must be purchased. In subsequent years, passive sampling is seven 

times less expensive. By comparison, active monitoring of O concentrations over 3

the growing season using portable solar-powered monitors is approximately 2.5 

times more expensive than monitoring with passive O samplers. 3

Although the use of passive samplers is now common for monitoring gaseous 

pollutants, passive samplers have also been used in California to collect fogwater 

and rime ice. Ionic concentrations of atmospheric pollutants are highly concentrated 

in fogwater and rime ice compared to precipitation or snowfall (Berg et al. 1991, 

Fenn et al. 2000). Active collectors are also available for collecting cloudwater 

(Daube et al. 1987, Fenn et al. 2000, Roman et al. 2013). In some montane areas of 

California, N inputs from cloudwater or fog can constitute as much as one-third 

of the total annual N deposition (Fenn et al. 2000, Waldman et al. 1985). Note, 

however, that trees function as natural cloudwater collectors, resulting in elevated 

fluxes of N to the forest floor in throughfall (Fenn and Poth 2004). Rime ice 

formation results when supercooled cloud droplets freeze on impact with natural or 

human-made surfaces. We have deployed passive samplers for cloudwater (Fenn et 
11

al. 2000) and rime ice (Berg et al. 1991) collection in California forests. Inasmuch 

as throughfall chemical flux measurements include estimates of the deposition of N 

and other pollutants to the canopy, including rime ice and cloudwater, we will not 

discuss rime ice or cloudwater samplers further in this report. 

1.6―National Atmospheric Deposition Networks

The largest atmospheric deposition network in the United States is the wet deposition monitoring program known as the National Atmospheric Deposition Program/

National Trends Nework (NADP/NTN) with 12 sites in California (http://nadp.

sws.uiuc.edu/data/sites/NTN/?net=NTN). Only deposition in precipitation, including snowfall, is measured. The NADP network has provided much useful data on 

spatial and temporal deposition trends in the United States because it is the most 

spatially extensive and longest running network (since the late 1970s at some sites) 

in the United States (fig. 1.5). At a subset of the NADP sites, the atmospheric concentrations of some N and S pollutants are measured by the Clean Air Status and 

Trends Network (CASTNET) program, with five sites in California (http://epa.gov/

castnet/javaweb/index.html). From these data, dry deposition fluxes are determined 

from model simulations. However, dry deposition fluxes estimated by CASTNET 

are frequently much lower than empirical measurements from the same sites (Fenn 

et al. 2009, Sparks et al. 2008, Weathers et al. 2006). 

The NADP also operates the Ammonia Monitoring Network (AMoN) a network of passive samplers for measuring atmospheric concentrations of NH . The 3

AMoN was officially established in 2010 and currently consists of 67 sites, with 

three in California (http://nadp.sws.uiuc.edu/amon/). Commercially available Radiello diffusive tube passive samplers for NH are used at the monitoring sites. The 3

intention is to continue expanding the network nationally. Empirical NH concen- 3

tration data from AMoN are used in the hybrid Total Deposition Science Committee 

(TDEP) model that is based on simulations from the model Community Multi-scale 

Air Quality (CMAQ) (Byun and Schere 2006, Tonnesen et al. 2007) that is adjusted 

with empirical monitoring data where available (Schwede and Lear 2014). 

Because of the 

prominence of dry 

deposition in California, 

which NADP does not 

measure, the NADP 

wet deposition maps 

show California as one 

of the lowest pollution 

regions in the country, 

notwithstanding the 

fact that the highest 

N deposition in North 

America occurs in 

southern California.

However, the NADP, CASTNET, and AMoN data are of limited use for ecosystem effects studies in California (Fenn et al. 2012). Because of the prominence 

of dry deposition in California, which NADP does not measure, the NADP wet 

deposition maps show California as one of the lowest pollution regions in the 

country (fig. 1.5), notwithstanding the fact that the highest N deposition in North 

America occurs in southern California. Likewise, cloud or fogwater deposition of 

N are important forms of N deposition inputs in coastal and montane regions of 

California that are influenced by atmospheric N emissions (Collett et al. 1990, Fenn 
12

GENERAL TECHNICAL REPORT PSW-GTR-257

ude.sionilli.swsi.pdan/:ptt, hkrowtes Ndnerl TanoitaN/margorn Poiitsopeic Drehpsomtl AanoitaN

y d betropes r4 a10n 2s ietad Stetinl Uatnenitnoe chn tn ioitisopet den w, i]N- 4 HNm [iunommd an] aN-3 ON

.

e [

kro

tar

wt

ti

e

f n

s N

m o

dne

u

r

s

l T

n (

a

oit

n

i

oi

s

t

o

a

pe

N/

) d

no

N

iti

n (

sop

egorti

e c D

c n

ire

i

h

n

p

a

so

gr o

mt

nI

l A

—

a

5

no

e 1.

ita

rugi

e Nh

Ft
13

et al. 2000, Fenn and Poth 2004, Templer et al. 2015), and the NADP wet deposition 

collectors do not effectively collect cloudwater. Furthermore, the sampling density 

for NADP (12 sites), and especially for AMoN (3 sites) and CASTNET (5 sites), 

are insufficient to describe N deposition in California. And, as mentioned above, 

CASTNET has been shown to underestimate dry deposition of N by a significant 

degree, including in California (Fenn et al. 2009, Sparks et al. 2008, Weathers et al. 

2006).

1.7―Throughfall Deposition Monitoring

Measuring throughfall deposition, the hydrologic flux of nutrients or pollutants 

washed from plant canopies during precipitation or snowmelt events, is a widely 

used method of estimating wet + dry deposition inputs of N or other compounds 

(Bleeker et al. 2003, Clarke et al. 2010, Draaijers et al. 1996, Hansen et al. 2013, 

Lovett and Lindberg 1993, Parker 1983, Thimonier 1998). The throughfall flux 

of nutrients from the canopy to the forest floor is an important part of ecosystem 

nutrient cycling. In polluted environments, the accumulation of dry-deposited 

compounds on canopy surfaces results in elevated nutrient fluxes to the forest floor. 

Many studies have related these increased throughfall fluxes of N or other pollutants to ecosystem effects.

Although throughfall N deposition includes both wet and dry deposition of 

N, a fraction of atmospherically deposited N is retained by the canopy, and as 

a result, throughfall N deposition is generally lower than total N deposition, as 

has been shown in many regions (Clarke et al. 2010, Fenn and Bytnerowicz 1997, 

Hansen et al. 2013, Lovett and Lindberg 1993). Thus, at best, throughfall N deposition is a lower bound estimate of total N deposition. Because of canopy uptake of 

atmospheric N, in relatively low pollution sites N deposition measured under tree 

canopies (throughfall) is often lower than in canopy-free or open areas (referred to 

as bulk deposition). In contrast, throughfall deposition of S has often been reported 

to be a good surrogate for total S deposition (Clarke et al. 2010, Granat and Hällgren 1992, Hansen et al. 2013, Lindberg and Lovett 1992), but there are exceptions. 

Stemflow refers to the hydrologic flux of nutrients in solution running down 

tree trunks (Clarke et al. 2010, Parker 1983). Stemflow is much less frequently 

measured than throughfall because it generally represents a small proportion of the 

total deposition to the forest floor and requires additional equipment and effort. 

Stemflow can be measured by attaching spiral cords or collars around the base of 

tree trunks. Generally, less than 10 percent of the total deposition to the forest floor 

is from stemflow, but this differs by tree species. In beech or dense pine stands, 

for example, when precipitation intensity and duration are sufficient, stemflow 
14

GENERAL TECHNICAL REPORT PSW-GTR-257

can constitute as much as 40 percent of the deposition (Draaijers et al. 1996). Ion 

exchange resin samplers have not been reported for measuring stemflow, but if the 

stemflow solutions were routed through IER columns, this could be accomplished. 

Notwithstanding the 

limitations of the 

throughfall technique, 

it is the most practical 

low-cost method for 

estimating deposition 

fluxes to forests and 

other ecosystems.

By definition, throughfall samples are only collected during precipitation 

events or as snow accumulated on tree canopies melts. This is problematic in arid 

climates such as mediterranean California where periods of little or no precipitation 

can span 3 to 6 months or longer (Fenn et al. 2000). Such long dry spells seem to 

result in greater underestimates of N deposition compared to throughfall measurements in more mesic climates or years with greater precipitation. This illustrates 

the need for including results from complementary approaches for estimating N 

deposition, especially during drought years. Notwithstanding the limitations of 

the throughfall technique, it is the most practical low-cost method for estimating 

deposition fluxes to forests and other ecosystems (fig. 1.6) (Clarke et al. 2010). This 

is why throughfall monitoring continues to be used in many studies, including large 

networks such as long-term regional, countrywide or continental-scale monitoring 

programs (Bleeker et al. 2003, Clarke et al. 2010, Fenn et al. 2008, Ferretti et al. 

2014, Hansen et al. 2013). 

eicvret SseroA FDSU

Figure 1.6—Some of the key benefits of using throughfall deposition monitoring for estimating atmospheric deposition inputs to forests 

and other ecosystems. N = nitrogen, N = inert dinitrogen, N O = nitrous oxide, NO = nitrogen oxide, NO - = nitrate, and NH + = 2 2 3 4

ammonium.
15

Chapter 2: Passive Monitoring for Atmospheric Concentrations 

of Gaseous Pollutants

2.1―Uses of Passive Samplers and Pollutants 

Commonly Measured

The primary use of passive samplers is to measure time-averaged concentrations 

(typically 2- to 4-week averages) of gaseous pollutants, thus providing summary 

information on pollutant exposure at each monitoring site. Passive samplers for 

gaseous pollutants measure pollutant concentrations based on passive diffusion 

of the pollutant through barriers (filters, screens) or diffusion tubes, and onto the 

collection medium. The collection medium is chosen on the basis of its affinity to 

the pollutant gas to be sampled (Krupa and Legge 2000). In contrast, an “active 

sampler” involves the active movement of air through the air pollution monitor by 

a pump. Following field exposure of passive samplers, pollutant concentrations are 

determined by extraction of the sampler medium and measurement of the pollutant 

of interest. Atmospheric concentrations are determined from previously established 

linear relationships between concentrations of the pollutant as determined from 

reference methods using active samplers and passive sampler extraction data (Calatayud and Schaub 2013, Krupa and Legge 2000). Using passive samplers is a highly 

useful approach as it allows monitoring over much larger networks than is feasible 

with active samplers. Pollutants for which passive samplers have been commonly 

used in ecological-effects studies include nitrogen oxides (NO ), nitrogen dioxide x

(NO ), ammonia (NH ), nitric acid vapor (HNO ), sulfur dioxide (SO ), ozone (O ), 2 3 3 2 3

and volatile organic compounds (VOCs) (see table 2.1). Concentrations of nitric 

oxide (NO) can be calculated as the difference between NO and NO . x 2

The key limitation of passive samplers is that the time-averaged data obtained 

do not describe diurnal patterns of pollutant exposure, which can be important 

when considering stomatal uptake and biological effects of pollutants (Krupa 

and Legge 2000). However, statistical procedures have been successfully used to 

estimate biologically relevant hourly O exposure indices from passive sampler 3

O concentration data (Ferretti et al. 2012). Furthermore, portable solar-powered 3

continuous O monitors are now available for real time O monitoring in remote 3 3

locations (Burley et al. 2015). 

Data from passive samplers deployed with sufficient density can be used to 

develop pollutant exposure maps using geostatistical techniques (Fraczek et al. 

2003), thus defining exposure to key pollutants across the landscape. Data on 

atmospheric concentrations of gaseous pollutants can be used to evaluate temporal 

trends in pollutant concentrations and to assess the potential for biological effects 

(Bytnerowicz et al. 2008, Cape et al. 2009). Concentration data for nitrogenous 
16

GENERAL TECHNICAL REPORT PSW-GTR-257

pollutants can also be used to calculate dry deposition fluxes to the ecosystem, 

an approach commonly known as the inferential method, which is summarized in 

section 4.3 (Bytnerowicz et al. 2015). Passive samplers used to monitor HNO have 3

also been used for stable nitrogen (N) isotope analysis of the collected HNO (Bell 3

et al. 2014, Elliott et al. 2009). 

Table 2.1―Characteristics of passive samplers for ozone and nitrogen and sulfur pollutants, including

common analytical methods

Pollutant Collection mediuma Ion measured in extract Analytical methoda Literature references

HNO3 + HNO2 Nylasorb (nylon filters) - NO3 Ion chromatography Bytnerowicz et al. 2005

NO2 Filters coated with triethanolamine (TEA)

- NO2 Colorimetrically Ogawa & Co., 

USA 2006

b

NOx TEA + an oxidizing agent - NO2 Colorimetrically As above

NO Calculated as the difference 

between NO and NO x 2

As above

NH3 Filters coated with citric acid + NH4

c Colorimetrically Roadman et al. 2003

O3 Pads coated with sodium nitrite - NO3 Ion chromatography Koutrakis et al. 1993

SO2 Filters coated with TEA 2- SO4 Ion chromatography Ogawa & Co., 

USA 2006

HNO = nitric acid, HNO = nitrous acid, NO - = nitrate, NO = nitrogen dioxide, NH = ammonia, NO = nitric oxide, O = ozone, NH + = 3 , 2 3 2 3 3 4 ammonium, SO = sulfur dioxide, SO 2- = sulfate. 2 4 a The analytical approaches and the collection media listed in the table are the ones used in our laboratory, but the ions mentioned in the table 

can all be analyzed with either colorimetric or chromatographic techniques.

b NO refers to the sum of concentrations of NO and NO .

x 2 c When atmospheric NH reacts with the citric acid, it forms diammonium citrate [(NH ) C H O ], which is extracted from the filters and 3 4 2 6 6 7

concentrations of NH + determined colorimetrically. 4

2.2―Design of Passive Samplers

Although there are various designs for passive samplers (Krupa and Legge 2000), 

we will focus on two types of passive samplers that we have commonly been used 

in field campaigns in California. The first is a widely used passive sampler generally referred to as the Ogawa sampler (fig. 2.1) (Koutrakis et al. 1993, Fenn et al. 

2009, Roadman et al. 2003). This sampler is used to measure NH , NO , NO , SO , 3 2 x 2

and O . The sampler is made of Teflon® with a Teflon end cap with precision- 3

drilled holes followed by a stainless steel mesh serving as the diffusion barrier. The 

sampler also requires the use of a shelter to protect the sampler from precipitation 

(fig. 2.1). The respective pollutant to be sampled is collected on cellulose filters (two 

per sampler) coated with reagents known to react to the pollutant of interest (Fenn 

et al. 2009, Roadman et al. 2003). Generally, one sampler per pollutant type (e.g., 

NH , NO ) is installed per site, yielding two replicate samples. 3 2
17

A

B

Figure 2.1—(A) An assembly of passive samplers for measuring average concentrations of gaseous pollutants in the atmosphere over the 

time of exposure. Ogawa samplers for measuring ozone (O ), ammonia 3

(NH ), nitrogen dioxide (NO ), and nitrogen oxides (NO ) are shown 3 2 x along with three replicate nitric acid (HNO ) vapor samplers. Typical 3

units of measure for gaseous pollutant concentrations in the atmosphere are micrograms per cubic meter (μg m-3; e.g., μg NH m-3 or μg 3

NH -N m-3). (B) Closeup view of an Ogawa passive sampler. 3 eicvret SseroA FDSU eicvret SseroA FDSU
18

GENERAL TECHNICAL REPORT PSW-GTR-257

The second sampler we have widely deployed in field studies is a passive 

sampler for measuring HNO + nitrous acid (HNO ) concentrations (fig. 2-1). This 3 2

nitric acid sampler is based on quantitative absorption of these gases to nylon filters 

(Bytnerowicz et al. 2001, 2005). The sampler uses a Teflon membrane for controlling airflow to the nylon filter (Bytnerowicz et al. 2005). Generally, three HNO 3

samplers are deployed at each site, yielding three replicate samples. Although 

HNO is generally the primary pollutant of interest when deploying these samplers, 3

as mentioned, both HNO and HNO are absorbed by the nylon filters. Ecologi- 3 2

cally, both of these gases can be important sources of atmospheric N, and, in this 

sense, the total of these two gases is important to measure. The ratio of HNO / 2

HNO in the atmosphere varies in time and space depending on ambient photo- 3

chemical processes (Finlayson-Pitts and Pitts 1986) but cannot be determined by 

this sampler. 

Collection media coated or impregnated with sodium chloride (NaCl) can 

be used to quantitatively capture HNO from air without also collecting HNO 3 2

(Allegrini and De Santis 1989, Allegrini et al. 1987). In preliminary trials at our 

lab, we coated cellulose, glass and quartz filters with 0.25 N NaCl and used these 

in the HNO + HNO sampler (Bytnerowicz et al. 2005) to measure atmospheric 3 2

concentrations of HNO only. Results were in agreement with HNO concentrations 3 3

as measured by a colocated annular denuder active sampling system (Koutrakis et 

al. 1988; Bytnerowicz, unpublished data). These results demonstrate conceptually 

that samplers with filters coated with NaCl may be useful in measuring only HNO , 3

while colocated samplers with nylon filter could be used to measure exposure to 

HNO + HNO . Average concentrations of HNO during the exposure period could 3 2 2

be determined by difference between the results of the two filter types. However, 

further field tests would be needed to further validate this approach.

2.3―Preparation and Assembly of Passive Samplers

Key in preparing passive samplers for field deployment is to handle them carefully 

to avoid contamination during assembly, transport to and from the field (Puchalski 

et al. 2011), storage, disassembly, and extraction of filter pads. Samplers should 

be prepared in a clean room or space, preferably in a clean air hood. Precautions 

include the use of gloves to avoid touching the samplers with bare hands, handling 

filters with forceps, covering tables or work benches with clean laboratory paper, 

and storing samplers in clean containers and storage bags to avoid atmospheric 

exposure prior to deployment. Unexposed blank or control filters stored in sealed 

containers are kept in the lab and later analyzed along with the field-exposed sampler filters; the ionic content from extracts of these filters are used to blank-correct 
19

the samplers exposed in the field. More detailed procedures for preparation and 

assembly of passive samplers are given in appendix 1. 

2.4―Calibration of Passive Samplers

The primary use of 

passive samplers is to 

measure time-averaged 

concentrations 

(typically 2- to 4-week 

averages) of gaseous 

pollutants, thus 

providing summary 

information on 

pollutant exposure at 

each monitoring site.

To derive atmospheric concentrations from the ionic content of the passive sampler filter extracts, a calibration curve relating the extract data with atmospheric 

exposures must be used. Such calibration curves are developed by measuring 

atmospheric concentrations with a reference method (active sampler) and collocated 

passive samplers (fig. 2.2). Then results from each of the two methods are plotted 

and tested for linearity in the relationship (fig. 2.3). Passive samplers should only be 

used in environments in which calibration curves have been established. Environmental conditions such as high winds, temperature, dust or other pollutants, or high 

humidity can potentially affect the performance of passive samplers (Bytnerowicz 

et al. 2005, Koutrakis et al. 1993, Krupa and Legge 2000). For these reasons, 

calibrations against reference methods are ideally obtained under field conditions 

in the areas of interest during the seasons of the year to be monitored. However, in 

practice, such calibrations are often not practical and must be done at least in locations with similar climatic conditions. 

2.5―Field Deployment of Passive Samplers

In selecting monitoring sites it is preferable to avoid steep slopes, and find sites 

located on plateaus if possible. In the Sierra Nevada of California, sites with a western aspect are preferred because the majority of the air pollution load originates 

in the California Central Valley to the west. If colocated with vegetation-effects 

study plots, the passive sampler location should be at the same elevation. When 

installing passive samplers in tall vegetation, such as forests or woodlands, choose 

a monitoring location that has an open fetch or corridor for air mass transport 

from the expected pollution source area so that pollution exposure in the broader 

study area is effectively characterized. At sites within or near a forest stand, locate 

passive monitors in an opening at a distance from the stand of at least two to three 

times the height of the tallest trees (fig. 2.4). Often it is difficult to find large stand 

openings across a monitoring network. Scarcely dispersed trees or shrubs, not 

directly obstructing airflow to the samplers should not be problematic. Exceptions 

to this rule could include studies in which the effects of canopy or stand position on 

pollution exposure also are being studied. 

Passive samplers should typically be placed about 2 m above ground level. 

At this height, pollutant concentrations represent ambient concentrations that are 

relatively unaffected by deposition to soil surfaces or short vegetation. At such a 
20

GENERAL TECHNICAL REPORT PSW-GTR-257

A

,

B

eicvret SseroA FDSU

eicvret SseroA FDSU

Figure 2.2—(A) Honeycomb denuder/filter pack system (active sampler unit strapped to the vertical post) used for calibration of 

ammonia and nitric acid passive samplers (mounted on the upper cross bars); and (B) a passive sampler calibration experiment at 

the Pacific Southwest Research Station Riverside Laboratory. Note that electricity is only required for the active samplers in the 

calibration, not the passive samplers.

A B

Figure 2.3—(A) Calibration curve for calculating average atmospheric concentrations of ammonia (NH ) from passive samplers exposed 3

in the field. To obtain NH concentrations in micrograms per cubic meter (μg m-3), the NH dose on the Y-axis (from the active sampler) 3 3

is divided by hours of exposure. The linear regression shows the correlation between concentrations of ammonium (NH +

) in the passive 4

sampler filter extracts and atmospheric concentration of NH as measured with an active sampler. (B) Calibration curve for calculating 3

average atmospheric nitric acid vapor (HNO ) concentrations from passive samplers exposed in the field. (Left figure for NH dose 3 3

courtesy of USDA Forest Service, Pacific Southwest Research Station. Figure on the right for HNO dose reprinted from Bytnerowicz et 3

al. (2005) with permission from Elsevier). 
21

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 2.4—Multiple passive samplers installed at a single field site in the White Mountains of California. Samplers are placed away from trees. 

height, it is also easy for operators to install and change the samplers (fig. 2.5). It is 

recommended that two to three replicate passive sampler media (i.e., filter disks) be 

deployed at each monitoring location. Frequently passive samplers for measuring 

several pollutants of interest are deployed simultaneously, depending on the aims of 

the study (fig. 2.6).

Passive samplers also can be placed on towers above the vegetative canopy 

(fig. 2.7), which allows for sampling of incoming air pollution to the site. Because 

vegetation takes up gaseous pollutants, passive samplers should be at least 1.5 m 

above the canopy to avoid canopy effects on atmospheric concentrations. However, 

samplers should be no more than 3 m above the canopy to ensure that exposure data 

are relevant to vegetative exposures in the sampling region. 

The most common exposure period for passive samplers is 2 weeks, although 

both shorter or longer periods can be sampled. In remote locations and where 

pollutant levels are low, exposure periods of 1 or 2 months have also been used 

(Hsu et al. 2016). With longer exposures, the resulting average pollutant concentration covers a longer period, with less time resolution. For some applications, this 

makes the data less useful because little is known about pollutant concentration 

dynamics over an extended period.

Passive samplers should be transported to and from field sites in clean, sealed 

air-tight containers and plastic bags to prevent contamination in transit. Containers 
22

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 2.5—A change-out of passive samplers at 

Devils Postpile National Monument California (the 

Granite Dome site). 

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 2.6—Closeup view of a setup for passive monitoring of multiple gaseous pollutants. The 

yellow housing unit contains passive samplers for volatile organic compounds (Burley et al. 

2015), illustrating an additional type of pollutant that can be passively sampled. 
23

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 2.7—A suite of passive samplers placed on a tower above the forest canopy in the 

Athabasca Oil Sands Region in northern Alberta, Canada, illustrating that the deployment of 

samplers can be in a variety of physical configurations. The passive samplers are deployed 

and accessed for change-out by a cable-and-pulley system. 

and procedures used to transport samplers and travel blanks to and from field sites 

should be carefully monitored for possible contamination. Travel blanks should be 

incorporated into monitoring plans to account for background levels and blank correction and to detect potential contamination problems during transit. For example, 

Puchalski et al. (2011) discovered that the plastic vials used to transport passive 

samplers for NH were emitting NH during warm weather. It was found that 3 3

transporting the NH samplers in all glass vials with Teflon-lined lids solved this 3

problem. Such contamination problems can occur with passive samplers for other 

pollutants as well. As another illustration of the use of inappropriate materials, we 

have found that Teflon tape from hardware stores is unsuitable for sealing travel 

containers in passive monitoring studies because of contamination issues. Use clean 

disposable gloves when placing the samplers on the mounting pole or stand and 

when collecting the sampler following the field exposure period (fig. 2.5). However, 

even “clean” disposable gloves can be a source of contamination, illustrating that 
24

GENERAL TECHNICAL REPORT PSW-GTR-257

all potential surfaces and supplies used should be evaluated as potential contamination sources. During all phases of preparing, deploying, and processing the passive 

samplers, use extreme care to prevent contamination. See appendix 1 for a sample 

protocol for field deployment of passive samplers.

2.6―Laboratory Methods of Analysis Following Field 

Exposure

During all phases of 

preparing, deploying, 

and processing the 

passive samplers, use 

extreme care to prevent 

contamination.

It is beyond the scope of this report to discuss chemical analysis methods in detail, 

particularly because details of such methods can be obtained from manufacturers 

of analytical equipment and elsewhere and because methods differ considerably 

among laboratories depending on the design, make, and model of instrumentation 

used. The Ogawa and HNO samplers discussed herein require extraction of the 3

collection medium and subsequent analysis of the pollutant of interest in the filter 

extracts. Table 2.1 lists the type of collection medium used, the ion measured in 

each extract solution, and suggested analytical techniques for passive samplers 

of O and each of the N pollutants considered here. For each of these passive 3,

samplers, the collection medium (filter) is extracted with deionized/distilled water. 

On occasion, we have found that when monitoring at relatively unpolluted sites, 

particularly during seasons when pollutant concentrations are at their lowest, the 

ionic content of the filter extracts can be below the analytical detection limit. Such 

low pollution levels are below the thresholds expected to cause ecological harm. In 

these situations, exposure periods greater than 2 weeks may be more appropriate. 

2.7―Data Processing, Calculation of Atmospheric 

Concentrations, and Pollutant Mapping

Results from air 

pollution monitoring 

networks can be 

converted into maps 

of air pollution 

distribution that are 

useful for scientists, 

air resource and 

land managers, and 

decisionmakers. 

Raw data from chemical analysis of sampler extractions will provide ionic concentration data of the extract solutions, which based on extract volumes must then be 

converted to total ionic content extracted from the sampler. Using the example of 

the HNO samplers, the μg NO -

/filter can be converted to atmospheric concen- 3 3

trations of HNO + HNO based on the previously established calibration curve 3 2

(Bytnerowicz et al. 2005). Example calculations for O , NO , NO , NO, HNO and 3 x 2 3,

NH are shown in appendix 1. 3

Results from air pollution monitoring networks can be converted into maps 

of air pollution distribution (fig. 1.3) that are useful for scientists, air resource and 

land managers, and decisionmakers using geostatistics (Frączek et al. 2003). In our 

applications, we have used various versions of the Geostatistical Analyst software, 

which is an extension of ArcGIS software developed by the Environmental Systems 

Research Institute (ESRI, Redlands, California). Geostatistical Analyst uses values 
25

measured at monitoring network sites and interpolates them into a continuous 

surface of pollutant distribution using various techniques such as kriging, cokriging, or inverse distance weighing (Johnston et al. 2003). In addition to surfaces 

representing spatial changes in pollutant concentrations, uncertainty of predictions, called the prediction standard error, can also be calculated when the network 

density allows for using simple kriging (Bytnerowicz et al. 2010). 

Physiological measurements of foliar stomatal uptake of O is the most appro- 3

priate metric for evaluating plant responses to O . However, because of the lack 3

of stomatal conductance data for most of the tree species, simple O exposure 3

indices calculated from hourly ambient O concentrations are more often used to 3

evaluate potential responses of plants to O exposure (Musselman and Korfmacher 3

2014). Average O concentrations (e.g., 2-week averages) obtained from passive 3

O samplers can be used to estimate hourly O concentrations at passive sampler 3 3

monitoring sites using statistical models that couple O concentration data from 3

passive samplers with meteorological variables (Cisneros et al. 2010, Krupa et al. 

2003). Alternatively, portable, solar-powered active ozone monitors can be deployed 

in select locations (Burley et al. 2015).
26

GENERAL TECHNICAL REPORT PSW-GTR-257
27

Chapter 3: Deposition Monitoring With Ion Exchange

Resin (IER) Collectors

3.1―Uses of IER Collectors and Definition of Terms

Ion exchange resin (IER) samplers are used to measure deposition in precipitation 

and throughfall. Because these samplers use funnels constantly exposed to the 

atmosphere to capture the precipitation or throughfall solutions, such measurements 

are referred to as bulk deposition measurements. The term “bulk” refers to the fact 

that some level of dry deposition accumulates on the funnel sampler during dry 

periods and becomes part of the deposition measurement. This is in contrast to 

wet-only samplers that are closed by a lid during dry periods and only open during 

precipitation events (Fenn et al. 2009, Glaubig and Gomez 1994). 

In the atmospheric deposition literature, the term ”bulk deposition” has long 

been used specifically in reference to precipitation samples collected in open 

canopy-free areas with continuously exposed collectors. These are more commonly 

funnel- or cylindrical-shaped collectors, but trough collectors have also been used 

(Bleeker et al. 2003). However, with few exceptions (Fenn and Bytnerowicz 1997, 

Glaubig and Gomez 1994), throughfall samplers are continuously exposed to the 

atmosphere and thus collect dry deposition on the collector surfaces during dry 

periods. As such, these throughfall measurements are bulk throughfall collections, 

but usually are simply referred to as throughfall or throughfall deposition. However, 

such continuously exposed funnel, bucket, or trough collectors are not efficient dry 

deposition samplers, and the amount of dry deposition deposited directly to the collector from the atmosphere is considered minor compared to the interactions of dry 

deposition with plant and tree canopies and their much larger and reactive surface 

areas for dry deposition collection (Du et al. 2014a). 

Sometimes there has been a perception that throughfall deposition fluxes 

measured with IER throughfall collectors is a different flux measurement than 

fluxes measured with conventional throughfall solution samplers. In actuality, 

the throughfall input measurements are equivalent for both methods as has been 

demonstrated in field trials (Fenn and Poth 2004, Fenn et al. 2002). The ultimate 

flux measurements (i.e., kilograms per hectare per year [kg N ha-1

 yr

-1]) are identical. The principal difference between the two approaches is that with IER samplers, 

no liquid samples are collected in the field. Instead, ions in throughfall solutions 

are adsorbed and accumulated by the IER columns as the liquid percolates through 

the column by gravity flow. Typically, IER columns are left in the field for about 

6 months, accumulating ions from solution with each precipitation or snowmelt 

event. At the end of the sampling period, the IER columns are brought back to the 

laboratory for extraction of the adsorbed ions and chemical analysis of ions in the 

extractant solution. In contrast, with conventional throughfall samplers, solutions 
28

GENERAL TECHNICAL REPORT PSW-GTR-257

are collected repeatedly, either on an event or periodic basis. Total volumes of the 

collected solutions are measured and samples analysed for ionic concentrations. 

In the end, with both methods, the amount of ionic deposition to the throughfall collector is determined, ultimately resulting in data expressed as deposition of a given 

ion or element per land area over time (i.e., kg NO -N ha-1 yr

-1). 3

3.2―Pollutants Measured With IER Collectors

The most widespread use of IER collectors has been to measure deposition of 

nitrate (NO -), ammonium (NH +), and sulfate (SO 2-). Deposition of chloride (Cl-), 3 4 4

phosphate (PO 3-), and cations such as calcium (Ca2+), magnesium (Mg2+), sodium 4

(Na+), and potassium (K+) can also be measured (Fenn et al. 2015a, Simkin et al. 

2004). Typical extractants used to remove the ions of interest from IER columns 

prior to analysis and associated methods of ionic analysis are listed in table 3.1. 

The sum of NO -N and NH -N in solution is commonly referred to as dissolved 3 4

inorganic nitrogen or DIN, and this is what is typically measured in throughfall 

or bulk deposition. Dissolved organic nitrogen (DON) deposition fluxes are also 

a significant portion of the atmospheric input flux in many cases (Cornell 2011), 

although DON is much less frequently measured, largely because the analysis is 

less straightforward and because of the uncertain composition and sources of the 

mixture of organic N compounds. Dissolved organic nitrogen can be measured in 

the throughfall solutions collected in conventional samplers, but techniques have 

not been developed for quantitative extraction of DON from IER columns. Dissolved organic nitrogen is actually composed of many organic compounds that 

contain N, so this is a complex mixture of compounds and would likely require a 

different type of exchange resin than for inorganic N. The feasibility of measuring 

DON with a variety of IER types would need to be tested. 

Likewise, the pH or hydrogen ion (H+

) concentration of precipitation or throughfall solutions can be measured after sampling with conventional samplers. However, 

the acidity of precipitation or throughfall, and the concentrations in solution of any 

ions deposited, cannot be determined with IER samplers because throughfall or 

precipitation solutions per se are not collected. Instead, anions and cations are generally extracted from the IER columns with a strong salt solution, which precludes the 

possibility of measuring the pH or ionic concentration of the original solution.

In several studies, the natural abundance isotopic signatures of NO - (Clow et 3

al. 2015, Nanus et al. 2008, Proemse et al. 2013, Templer and Weathers 2011) and 

SO 2- (Proemse et al. 2012) in IER extracts have been determined. Isotopic signa- 4

tures of atmospheric deposition such as that determined with IER samples can help 

identify the emissions sources from which the N or sulfur (S) pollutants originated. 
29

Table 3.1―Ions commonly measured with ion exchange resin (IER) deposition samplersa

Ion Typical extractant Analytical methodb Literature references

- NO3 1N KI or 2N KCl Ion chromatography or colorimetrically

Fenn and Poth 2004; Fenn et 

al. 2013, 2015a; Simkin et 

al. 2004 - NO3 1N NaCl Colorimetrically Köhler et al. (2012) + NH4 1N KI or 2N KCl Ion chromatography or colorimetrically

Fenn and Poth 2004; Fenn et 

al. 2013, 2015a

2- SO4 1N KI Ion chromatography Fenn et al. 2013, 2015a

3- PO4 1N KI Ion chromatography Fenn et al. 2013, 2015a

Cl- 1N KI Ion chromatography Simkin et al. 2004

Na+

, Mg2+, Ca2+ 2N KClc ICP-AES (inductively 

coupled plasma-atomic 

emission spectroscopy)

Fenn et al. 2015a

K+

, Na+, Mg2+, Ca2+ 1N ammonium acetate 

(NH4C2H3O2); or 0.5N or 

1N HCld

ICP-AES Fenn, unpublished data; 

Yamashita et al. (2014) 

describe the HCl extraction.

K+

, Na+, Mg2+, Ca2+, 3- Al, Fe, Mn, PO4

2N H2SO4 ICP-OES Köhler et al. (2012)

NO - = nitrate, NH + = ammonium, SO 2- = sulfate, PO 3- = phosphate, Cl- = chloride, Na+ = sodium, Mg2+ = magnesium, Ca2+= calcium, K+ = 3 4 4 4 potassium, Al = aluminum, Fe = iron, Mn = manganese. 

a Negatively charged ions are captured from solution by anion exchange resin beads and positively charged ions by cation 

exchange resin beads. Mixed-bed resin (containing a mixture of cation and anion exchange resin beads) can be used to capture 

both cations and anions. 

b Analytical methods other than those listed can be used. Methods listed in the table are those described in the literature 

references given. 

c Note that in Fenn et al. (2015a), the IER columns were actually first extracted with 1N KI for analyzing the extracts for 

concentrations of NO -, NH +, SO 2-, and PO 3-. Then the same IER columns were further extracted with 2N KCl to extract 3 4 4 4

the remaining base cations. 

d Ammonium acetate is a stronger extractant than HCl, particularly for extraction of Ca2+ from the IER columns, although 

either extractant can be used. We use ammonium acetate routinely in our laboratory for extracting base cations. Other extractants such as BaCl should also work for extracting base cations, but barium is more toxic than the extractants listed. 2

3.3―Design and Construction of IER Collectors

Ion exchange resin throughfall or precipitation collectors are based on the same 

design as more conventional samplers except that in lieu of a bottle for collecting 

the solution from the funnel (or whatever type of recipient is deployed), an IER column is attached to the funnel to capture ions from the solution as it drains through 

the column (fig. 3.1). The deionized liquid is then allowed to drain onto the ground 

and is not saved for analysis. This is the key difference between IER collectors and 

conventional samplers (figs. 3.2 and 3.3).

The core components of an IER throughfall sampler consist of a funnel (fig. 

3.4) or cylindrical solution collecting device that is connected to a column filled 
30

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDSU

Figure 3.1—Photograph of an IER bulk deposition collector. Ion exchange resin collectors are 

used to collect precipitation (placed in open, canopy-free areas) or throughfall (placed under tree 

or other vegetation canopies) deposition samples. 
31

niap, Sdirda, Mnoitullor Pif Ay oglooicxotocr Eor fetne, CzemoG-aícrar GotcėH

Figure 3.2—Ion exchange resin (IER) throughfall collector on the left and 

conventional throughfall solution collector on the right—in a holm oak stand 

near Madrid Spain (García-Gómez et al. 2016). Both collectors are covered by a 

white tube designed to block direct solar radiation. For the collector on the left, 

the narrower shade tube covers the IER column. For the collector on the right, 

the shade tube is larger in diameter to accommodate a bottle connected to the 

funnel that collects the throughfall solution. Both collector types use the same 

funnel and bird rings. In this particular site, no snow tubes are needed.
32

GENERAL TECHNICAL REPORT PSW-GTR-257

y n

g

ia

lo

p

oic

, Sd

x

i

o

r

t

d

o

a

cr E

, M

o

n

r f

oit

et

ul

n

l

e

o

, C

r Pi

zem

f Ao

oG-aícrar GotcėH

Figure 3.3—Ion exchange resin (IER) throughfall collector. Photograph is similar to figure 3.2 

except that the shade tube covering the ion exchange resin (IER) column has been lowered to 

reveal the IER column. Also note the opaque cover over the liquid solution collector on the 

right to protect the sample from sunlight and reduce warming of the sampler.

eicvret SseroA FDSU

Figure 3.4—Inside view of a funnel used for monitoring throughfall or bulk deposition with ion 

exchange resin (IER) collectors. The disk in the center of the funnel is to keep coarse litter out 

of the IER columns. Polyester floss is also inserted on the top of the IER column as a fine filter. 
33

with IER beads. The bottom end of the IER column includes a cap with a threaded 

drainage hole or slit cut in the cap. A shade tube is sometimes used to cover the IER 

column and prevent direct solar radiation to the column (figs. 3.2 and 3.3). There 

are many permutations upon this design, including varying diameters and heights 

of funnels and different lengths of IER columns. For collecting throughfall under 

lower lying vegetation, such as chaparral or other shrubs, the IER collector design 

is modified to fit under low-lying shrubs. For example, we use IER columns of 

5 to 6 cm in length and shorter funnels so that the collector can easily be placed 

under low-lying shrub canopies (fig. 3.5). Particularly for samplers placed in open 

or canopy-free areas, it is recommended to use some type of protection against bird 

droppings by attaching a bird sitting ring (fig. 3.6) or bird rejection device above 

the funnel or snow tube to reduce the occurrence of sample contamination by bird 

droppings (see section 3.6). 

The IER collectors 

used in field 

monitoring studies 

can be constructed of 

simple components 

readily available at 

hardware or irrigation 

supply companies.

The IER collectors used in field monitoring studies can be constructed of 

simple components readily available at hardware or irrigation supply companies. 

Funnels of various sizes and designs can be obtained from auto, hardware, scientific, or general suppliers accessible via the Internet. The main requirement is that 

the funnels are made of inert materials that are not contaminated with the ions of 

interest and that the sample solution be efficiently collected and routed to the IER 

column so that the ions are adsorbed by the IER beads as the solution percolates 

through the column. Components of the IER collectors that come in contact with 

the sample solutions in the field should be tested in leaching studies in the laboratory to be sure they are not a source of the ions to be monitored in deposition. 

Nylon material should be avoided because of its known affinity for nitric acid vapor 

(HNO ) (see section 2.2), which could confound the results when monitoring for 3

NO -N deposition. 3

The main requirement 

is that the funnels 

are made of inert 

materials that are not 

contaminated with 

the ions of interest 

and that the sample 

solution be efficiently 

collected and routed to 

the IER column.

Here we give an example of a potentially problematic collector design (Klopatek et al. (2006) placed in short cylindrical (i.e., 5-cm) IER collectors along a 

vertical profile within tree canopies to measure throughfall deposition at different 

heights within the canopy. This study took place in south-central Washington state. 

When we used these same collectors for sampling throughfall under coastal sage 

scrub vegetation in the Los Angeles Air Basin, we found evidence of high levels of 

background contamination of NH +, NO -, and SO 2- in the field blanks exposed 4 3 4

only to the dry atmosphere for 7 months. In this collector design (Klopatek et al. 

2006), the exchange resin is sandwiched between two pieces of fine mesh nylon 

netting and otherwise directly exposed to the atmosphere in the cylinder. Tests in 

Riverside, California, showed that IER directly exposed to the atmosphere during 

the summer smog season in petri dishes, or placed in the cylindrical samplers in 
34

GENERAL TECHNICAL REPORT PSW-GTR-257

A

B

Figure 3.5—Two different designs of ion exchange resin throughfall collectors for monitoring nitrogen deposition under low-lying chaparral vegetation. The funnel in photo B (24 cm diameter) is larger than the funnel in 

photo A (11 cm diameter). The larger diameter is considered a more effective 

throughfall sampling size. Notice the yellow and orange colored nitrophilous lichen species (Xanthomendoza spp.) colonizing the woody chaparral 

branches in photo A.

eicvret SseroA FDSU
35

eicvret SseroA FDSU

Figure 3.6—An ion exchange resin bulk deposition 

sampler mounted on the fence of an air pollution monitoring station. A snow tube to allow for snow collection and 

accumulation and a bird sitting ring to prevent contamination of the sample by bird droppings are attached to the 

collector.

a fume hood with a steady airflow resulted in high levels of N in the IER extract 

solutions. We concluded that IER samplers with the IER directly exposed to pollutants and moisture in the atmosphere is an inappropriate design. Apparently, under 

these conditions, the IER can adsorb reactive N from the atmosphere and much of 

the background SO 2- may result from breakdown of the exposed resin, because 4

background levels of SO 2- were greater than for NH + or NO -. Furthermore, 4 4 3

the use of nylon mesh to contain the IER is also not advised because of the high 

affinity of nylon for HNO and HNO (Bytnerowicz et al. 2005, section 2.2, table 2 3

2.1). Thus, adsorption of HNO and HNO by the nylon mesh may explain why 2 3

background levels for NO -, although elevated, were less than for NH + in the IER 3 4

extracts, especially in the more polluted sites. 

Based on previous throughfall studies in forest ecosystems, it has been recommended that funnel openings be at least 20 cm in diameter and funnels with vertical 

sidewalls and beveled top edges are also preferred (Bleeker et al. 2003, Clarke et al. 

2010). Once the collector components are assembled, they should be washed, rinsed 
36

GENERAL TECHNICAL REPORT PSW-GTR-257

with distilled water, and dried. Place collectors in clean bags to keep them clean 

during storage and transport to the field. Do not touch the inner surfaces of the funnels or other parts of the collector with hands or anything that could contaminate 

the collectors. 

Different types and commercial varieties of IER beads can be used within the 

IER columns. Ion exchange resin beads are marketed by scientific suppliers, but 

the prices from such suppliers tend to be cost prohibitive if many samplers are to be 

deployed. We purchase analytical grade IER beads in bulk from a water purification company. Because both NO -

 (an anion) and NH + (a cation) deposition are 3 4

important to measure in N-deposition studies, mixed-bed IER, containing anion 

and cation exchange resin beads, are commonly used in IER collectors (Fenn and 

Poth 2004, Kjønaas 1999b). Furthermore, it is often useful to monitor deposition of 

N and S, and possibly base cations in the same study (Fenn et al. 2015a, Watmough 

et al. 2014). Alternatively, anion exchange resins can be used if only anions such as 

NO - and Cl- are being measured (Simkin et al. 2004). If only base cations are being 3

measured, one could use only cation exchange resin beads in the IER columns. 

Although any of various collector designs can be employed for collecting 

throughfall or bulk deposition, for our recent forest monitoring studies, the collector 

details are as follows: the IER columns (6 to 8 in [15.24 to 20.32 cm] in length) are 

filled with AmberliteTM IRN 150 mixed-bed analytical grade ion exchange resin 

beads prerinsed with distilled deionized water. Precipitation or throughfall samples 

are collected by a polyethylene funnel or snow tube and channeled through the resin 

column, where ions are retained by the IER. The inner diameter of the funnels used 

for the IER collectors is 21.1 cm, and the funnel collectors have a vertical wall 10 

cm in height. For winter collection in sites with significant snowfall, snow tubes 

with an inner diameter of 20.2 cm are inserted into the funnels to capture snow (see 

section 3.5 and fig. 3.7). 

3.4―Field Deployment of IER Collectors: Placement, 

Number of Replicates, and Open vs. Throughfall 

Collectors 

Field deployment of IER collectors is done the same as for conventional samplers. 

Details regarding the number of samplers to install, their placement in the field, exposure times or change-out frequency for the IER columns are largely dependent on 

the objectives of the study, statistical requirements, and available resources. Reviews 

of throughfall sampling methods have already been published (Bleeker et al. 2003, 

Clarke et al. 2010, Draaijers et al. 1996, Hansen et al. 2013, Thimonier 1998). 
37

Two types of deposition monitoring are used to measure inputs with IER collectors—bulk deposition in open areas (referred to simply as bulk deposition; figs. 3.8 

and 3.9) and throughfall sampling with collectors placed under tree canopies (fig. 

3.10). Bulk deposition is composed primarily of wet deposition with an unknown 

background level of dry deposition but can be considered as an approximation of 

eicvret SseroA FDSU

Figure 3.7—An ion exchange resin (IER) sampler with snow tube attached. Notice that the IER 

column is not yet attached to the bottom of the sampler. A new IER column is attached at the beginning of each new exposure period, typically for 5- to 6-month intervals. 

Two types of deposition 

monitoring are used to 

measure inputs with 

IER collectors—bulk 

deposition in open 

areas and throughfall 

sampling with 

collectors placed under 

tree canopies.
38

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 3.8—Installation of ion exchange resin bulk deposition samplers in a forest clearing 

in the Lake Tahoe basin. Passive samplers for gaseous pollutants and a battery/solar-powered 

active ozone monitor (Burley et al. 2015) were also installed at this study site.

eicvret SseroA FDS U

Figure 3.9—Bulk deposition ion exchange resin (IER) samplers being installed in a bog, a natural 

forest clearing, in a remote boreal forest site in northern Alberta, Canada. Notice the bird rings 

installed on the funnel collectors to discourage birds from perching on the funnels. The white 

tubes function as a shade covering over the IER columns, to prevent direct sun exposure of the 

IER columns.
39

eicvret SseroA FDSU

Figure 3.10—Ion exchange resin throughfall collectors, (left) with and (right) without snow tube attached.

wet deposition in most cases. Throughfall deposition in essence uses tree or other 

vegetation canopy as a collecting surface for dry-deposited pollutants and for fog or 

cloudwater-deposited pollutants (fig. 3.11). As such, throughfall deposition fluxes 

include estimates of wet, dry, and cloudwater deposition of N. However, throughfall generally underestimates total N deposition because of canopy retention of N 

(Lovett and Lindberg 1993). Bulk deposition collectors intended for bulk deposition 

need to be placed in stand openings large enough to avoid blowoff from adjacent 

canopies such as during windy storm events. 

The number of throughfall collectors needed for a particular degree of precision 

is specific to a given forest site and the ions to be measured. However, fewer collectors are needed for measuring deposition fluxes than for chemical concentration 

(i.e., when collecting liquid samples with conventional throughfall collectors). This 

is because ionic concentration data can differ widely between samples or sampling 

dates, while in comparison, ionic fluxes are moderated by the interaction between 

throughfall volume and ionic concentration. For example, ionic concentrations can 

vary by an order of magnitude between a low- and high-volume precipitation event, 

with lower concentrations from the high-volume event owing to a dilution effect. In 

contrast, the throughfall deposition flux could be similar between the two events 

because flux is a function of both volume and concentration (e.g., flux with high 

concentration x low volume may be similar to the flux with low concentration x 

high volume). 
40

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS U

Figure 3.11—Installation of ion exchange resin throughfall collectors with snow tubes at a forest 

site. The tree canopy serves as the atmospheric deposition collector surface for throughfall 

samples that are washed from the canopy by precipitation or snowmelt.

The number of replicate samplers needed decreases with longer collection 

periods (Hansen et al. 2013, Houle et al. 1999, Lawrence and Fernandez 1993, 

Thimonier 1998). Because IER throughfall collectors are typically used for cumulative deposition measurements over periods of many months, this tends to reduce the 

number of replicates needed compared to short-term throughfall measurements.

The following formula has frequently been used to calculate the number of 

collectors to use:

n = t2

 x CV2/E2

where n is the number of collectors needed to determine the mean throughfall 

deposition within a predetermined error and confidence level; t is the Student’s t

value for a given confidence level; CV is the coefficient of variation as a percentage; and E is the acceptable error (expressed as a percentage of the mean). 

For example, in a mixed-hardwood forest in Quebec, the number of collectors 

needed to estimate semiannual deposition with a confidence interval of 95 percent 

with a 10 percent error was 13, 14, and 25 for SO 2-, NO -

, and NH +, respectively 4 3 4

(Houle et al. 1999). Only five collectors were needed to estimate deposition of these 
41

same ions with a 20 percent error. Lawrence and Fernandez (1993) concluded that, 

for a spruce-fir (Picea-Abies spp.) forest in Maine, deposition of most ions on a 

seasonal or annual basis can be estimated within 20 percent, a level of precision 

that is generally adequate, using 20 to 30 collectors. In European International Cooperative Programme (ICP) forests, the number of replicate throughfall samplers 

per plot in the various countries was 8 to 20, with 10 being the most common number (Bleeker et al. 2003). For more intensive deposition studies, greater numbers of 

IER samplers can be deployed (Houle et al. 1999), with 20 to 40 samplers per site 

not being unusual (Fenn et al. 2013).

In some situations where deposition may be highly variable spatially, the 

number of collectors needed for statistical purposes could be greater than what 

is feasible. In practice, the number of IER samplers deployed in field studies or 

monitoring networks largely depends on study objectives, available resources, 

logistics, and characteristics of the vegetation. As a general guideline, in IER 

monitoring networks 8 to 15 replicate throughfall collectors are installed at each 

site. In most cases, five to six bulk deposition collectors are also deployed, but this 

requires that a sufficiently large clearing can be found at each or most monitoring 

sites. The replicate bulk deposition collectors are typically collocated within a small 

area, typically 25 to 40 m2. Sometimes IER collectors are used in remote locations, 

including wilderness areas. The number of collectors deployed per site in such 

studies is often dictated by practical considerations mainly related to transporting 

supplies to the remote sites, likely resulting in lower replication than otherwise 

recommended. Although when wilderness sites are above treeline only open-site 

collectors are used and lower replication is required.

Various approaches have also been used for field placement of the collectors. 

Again, this also depends largely on the design of the experiment and forest stand 

characteristics. The throughfall collectors can be placed under randomly selected 

trees at the monitoring sites or at preselected distances along transects (figs. 3.12 

and 3.13). If the objective is to estimate landscape-level deposition, a grid or multiple-transect design may be best. Alternatively, if comparing deposition to a dominant species or a plant species that is common to all sites in the network, sampling 

only under a given species may be required. In this case, bulk deposition can also 

be monitored by placing collectors in open areas such as a forest clearing (fig. 3.14). 

The number of replicates needed for bulk deposition samplers is theoretically less than that needed for throughfall collectors because of the high level of 

heterogeneity in canopy cover even within a single plant canopy. For example, in 

the National Atmospheric Deposition Program (NADP) wet deposition sampling 

network, only one sampler is used per site. However, these samplers are covered 
42

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 3.12—Ion exchange resin throughfall collectors with snow tubes attached, installed at a 

predetermined spacing along a transect at a forest site.
43

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 3.13—When measuring throughfall fluxes below a selected plant species that is common 

to all the sites within a monitoring network, more than one collector may be placed under each 

replicate tree or shrub. 

eicvret SseroA FDS, Uzicworentyj BezrdnA
44

GENERAL TECHNICAL REPORT PSW-GTR-257

with a lid over the bucket sampler except during precipitation events, thus preventing dry deposition collection or contamination by birds or other wildlife. Three 

replicate collectors in open areas would normally be sufficient for measuring bulk 

deposition, but contamination from bird droppings, and sometimes other animal 

disturbance, is common in forest clearings and can result in decreased usable 

replicates. Because of this, we generally install at least five to six replicate samplers 

in open areas. Even with this precaution, in areas with high bird activity, sometimes 

most or all of the replicates are lost to contamination during some exposure periods 

(see section 3.6). If possible, the clearing for installation of bulk deposition samplers 

should be of a diameter two to three times the height of the tallest adjacent trees 

or other obstacles (Clarke et al. 2010) to avoid contamination of blowoff from trees 

during storm events. 

Three replicate 

collectors in open 

areas would normally 

be sufficient for 

measuring bulk 

deposition, but 

contamination from 

bird droppings, and 

sometimes other 

animal disturbance, 

is common in forest 

clearings and can 

result in decreased 

usable replicates. 

Because of this, 

we generally install 

at least five to six 

replicate samplers in 

open areas.

The decision as to whether to monitor only bulk deposition, only throughfall 

deposition, or both, depends on the information needed or study objectives. In 

general, it is preferred to measure both bulk deposition and throughfall, assuming 

that both tree cover and open areas exist at the monitoring sites. This provides 

greater information regarding the relative importance of wet versus dry deposition 

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 3.14—Ion exchange resin bulk deposition samplers installed in a forest clearing and next to 

a pole containing a suite of passive samplers. Throughfall collectors are also being installed under 

trees in the adjacent forest stand.
45

and whether deposition is greater in open areas or under canopies. When deposition 

is much greater in throughfall than in bulk deposition, this indicates that cloudwater 

deposition or dry deposition (or both) are much greater than wet deposition alone. 

When throughfall deposition is less than bulk deposition, this usually suggests that 

dry deposition rates are relatively low and that a significant fraction of the drydeposited N, and possibly the wet-deposited N as well, is consumed by the canopy 

(Fenn et al. 2013). This illustrates the point that throughfall N fluxes generally 

underestimate total N deposition.

3.5―Exposure Times, Changeout of IER Columns, and 

Use of Snow Tubes

Once IER collectors are installed, continued monitoring only requires changeout 

of the IER columns at selected intervals. Generally, monitoring intervals for IER 

collectors are for about 6 months. This allows for collection of deposition data 

during fall/winter and spring/summer, for example. Deposition sampling periods 

for IER samplers have been shown to be effective from periods ranging from 3 to 

12 months (Fenn and Poth 2004) and possibly longer if needed. A key point is that 

deposition samples, either in open areas or under plant canopies, require collection 

of ions from aqueous solutions. If insufficient precipitation occurs, or if fog drip 

or snowmelt from the canopy is captured by the samplers in trivial amounts, little 

or no detectable deposition will be collected. This is true of conventional samplers 

as well—if there is no solution to be sampled, then bulk deposition or throughfall 

fluxes are zero and there is no sample to be collected, although dry deposition is 

occurring during precipitation-free periods. Therefore, an important consideration 

is to ensure that precipitation or snowmelt from tree canopies occurs during the 

monitoring period so that ionic deposition samples from aqueous solutions are 

collected. 

If collecting data on annual N deposition measurements is the objective of 

IER monitoring, we recommend changing out the IER columns about every 6 

months. Typical changeout dates are in April/May and again in October or early 

November. However, the objectives of some studies may dictate a different IER 

changeout frequency. Longer exposure times may reduce the level of uncertainty in 

the deposition estimates as ionic deposition accrues in the IER collectors. However, with longer exposure periods, if replicate samples are disturbed in the field, 

contaminated, or otherwise damaged, the amount of monitoring information lost 

is proportionally much greater, particularly in comparison to conventional liquid 

throughfall sampling that entails short sampling periods such as a few weeks or on 

a precipitation-event basis.
46

GENERAL TECHNICAL REPORT PSW-GTR-257

Such long IER sampler exposure times lead to questions as to whether microbial contamination occurs in the IER columns. We have found no evidence of this 

even in IER collectors left in the field for up to 12 months (Fenn and Poth 2004). 

Deposition fluxes from the IER samplers were highly comparable to those from 

colocated conventional solution samplers that were sampled on a precipitation-event 

basis. Also, no increases in NO - were found in the IER samplers compared to 3

conventional samplers, as might be expected if microbial nitrification was occurring in the IER columns (Fenn and Poth 2004). Furthermore, in the mixed-bed 

(anion + cation resin) IER collectors, the pH of the 1 N KI extracts is nearly always 

<2 or >10. These extreme pH values are similar to the pH values of KI extracts of 

the separate anion (ca. 13) and cation (ca. 0.6) resin, respectively (Fenn, unpublished 

data). The harsh chemical environment of the IER columns is not expected to foster 

microbial growth.

In forests or other monitoring sites where snowfall volumes may be larger than 

the capacity of the funnel collectors, snow tubes should be inserted into the funnels to increase the capacity for snow collection. Typical lengths of snow tubes are 

from 0.5 to 1.0 m, depending on the amount of snow accumulation that occurs in 

the study region (figs. 3.15 and 3.16). Snowfall is difficult to capture efficiently, and 

such snow tubes likely undersample snowfall, particularly in canopy-free areas during windy periods. Efficiency of snow collection is higher in throughfall collectors 

under forest canopy because of the wind-buffering effect of the tree canopies (Fenn 

et al. 2015a). Ideally, snow collectors in open sites should be ≥500 cm2 (i.d., of ≥25 

cm) (Hansen et al. 2013). The snow tubes we used (20.2 cm i.d.) are smaller than 

this recommendation. Large polyethelene cylinder buckets make good snow collectors. Theoretically, if snowmelt from such a bucket snow collector is channeled 

through an IER column, this could be an effective snow deposition sampler. 

3.6―Prevention of Animal Disturbance and 

Contamination

The single greatest problem with the IER bulk deposition collectors is contamination by birds. In some locations, disturbance by bears or other wildlife is a serious 

problem (Fenn et al. 2015a, Simkin et al. 2004) (fig. 3.17). In areas where bear 

activity is high, for example, electric fences (figs. 3.18 and 3.19) are needed to 

protect the samplers from disturbance (Fenn et al. 2015a). Extra rinsing of the IER 

beads prior to field deployment reduces the “fishy” odor and seems to reduce the 

attraction of bears to the collectors (Simkin et al. 2004). Deposition collectors 

placed in open areas are attractive perches for birds. For this reason, we recommend 

that bird sitting rings or bird rejection devices be placed on all collectors deployed 
47

eicvret SseroA FDSU

Figure 3.15—Ion exchange resin throughfall 

collector with snow tube inserted into the funnel. Snow tubes such as this one, about 1.0 m in 

length, are used in locations with high levels of 

winter snowfall. 

Figure 3.16—View of two ion exchange resin throughfall collectors in a jack pine (Pinus 

banksiana Lamb.) stand in northern Alberta, Canada, with shorter (0.5 m) snow tubes installed 

in a stand with low snowfall volumes.

USDA Forest Service
48

GENERAL TECHNICAL REPORT PSW-GTR-257

A

B

Figure 3.17—In areas of high bear activity, many or all the 

throughfall collectors installed may be damaged by bears 

if preventive measures are not taken. Bears reportedly 

have an affinity for chewing on plastic. Furthermore, the 

ion exchange resin (IER) beads have a strong fishy odor, 

which may further attract bears to the IER collectors. 

However, in IER monitoring campaigns in forests of California, the Rocky Mountains, or in the Pacific Northwest, 

bear damage has not been extensive.

onitavreson Clatnemonrivn Ef otnemtrape D,eatt Skor YewN eicvret SseroA FDSU
49

eicvret SseroA FDSU

Figure 3.18—In areas of high bear activity, the only effective solution to prevent disturbance of 

the ion exchange resin collectors is to install solar-powered electric fences around the area where 

the collectors are located.

Figure 3.19—Ion exchange resin throughfall collectors and snow tubes in an area protected from 

bear damage by an electric fence. The need to circumscribe the monitoring area with an electric 

fence restricts the size of the potential monitoring site.

eicvret SseroA FDSU
50

GENERAL TECHNICAL REPORT PSW-GTR-257

in clearings (Asman et al. 1982, Bleeker et al. 2003, Clarke et al. 2010, Dämmgen 

et al. 2005). The bird rings we have been using are similar to the design of Asman 

et al. (1982) and are simply a wire ring larger in diameter than the funnel collectors, fashioned from standard wire “cages” for tomato plants, that is attached to the 

collector (figs. 3.6 and 3.20) to deter birds from landing on the IER collectors, or if 

they do, to provide an alternative perch. Other designs for bird deterrents have been 

tried as well (see app. 2).

We have found that during seasons of high bird activity in some areas, the bird 

rings are not as effective as desired. To address this problem, we normally deploy 

at least five replicate collectors in open areas (fig. 3.21). Even so, in some cases, all 

five (or more) of the collectors may be contaminated with bird droppings. Additional 

strategies that have been recommended for managing the bird contamination problem in bulk deposition samplers include having two monitoring stations close to 

each other but with different bird populations or habitats, or installing more attractive perches nearby to keep birds away from the samplers (Dämmgen et al. 2005). 

Throughfall collectors are much less frequently contaminated by birds unless there 

eicvret SseroA FDSU

Figure 3.20—Example of a simple bird sitting ring made from a tomato cage prior to placement 

on a funnel or snow tube. Fishing line has been strung across the ring to further deter birds from 

perching on the collectors.
51

eicvret SseroA FDSU eicvret SseroA FDSU

Figure 3.21—Ion exchange resin bulk deposition collectors located in forest clearings. Because of 

potential bird contamination, it is recommended that five to six replicate samplers be used in most 

open-site locations.
52

GENERAL TECHNICAL REPORT PSW-GTR-257

is a large gap or open air space between the lower canopy and the collector opening. 

Consequently, bird rings are generally not essential when monitoring throughfall 

deposition.

We recommend 

measuring NH +

4 and 

PO 3-

4 in all samples 

to aid in identifying 

which samples are 

likely contaminated 

by bird droppings. 

Measuring PO 3-

4 in 

bulk deposition is 

particularly useful in 

detecting contaminated 

samples because 

PO 3-

4 deposition in 

bulk or wet deposition 

is generally near 

background levels.

In some areas, we are finding that animals, mainly birds and sometimes 

rodents, become trapped in some of the collectors when snow tubes are attached. 

Therefore, it is advisable to remove the snow tubes after the snow season is past. 

Note that the IER columns should also be changed out whenever snow tubes are 

installed or removed so that a constant collector opening surface area is maintained 

during the sample collection period so that deposition fluxes can be accurately 

calculated. In some locations, it may be worthwhile to install a coarse mesh screening (e.g., bird netting) over the snow tube openings to prevent animals from getting 

into the collectors. This may also reduce litter accumulation in the collectors. Any 

screen used for this purpose should first be tested in the laboratory to ensure that 

ions of interest are not leached from the screen. 

Identification of samples contaminated by bird droppings is important because 

bird droppings are high in ions such as NH +, PO 3-, and K+ (Asman et al. 1982, 4 4

Dämmgen et al. 2005). We recommend measuring NH + and PO 3- in all samples 4 4

to aid in identifying which samples are likely contaminated by bird droppings. 

Measuring PO 3- in bulk deposition is particularly useful in detecting contami- 4

nated samples because PO 3- deposition in bulk or wet deposition is generally near 4

background levels. Throughfall PO 3- deposition on the other hand is inherently 4

more variable, and levels are much greater because of foliar leaching of PO 3- and 4

presumably washoff of PO 3- from dust particles on plant surfaces. 4

3.7―Laboratory Methods of Analysis Following Field 

Exposure

Detailed analytical methods will not be described in this report because methods 

change over time and differ among laboratories based on the equipment available. 

Details of IER column extraction may also differ depending on column sizes, the 

particular IER used, etc. Following is a summary of our general extraction and 

analysis procedures. A more detailed description of the extraction procedures 

used in the Forest Service laboratory in Riverside are given in appendix 2. The 

extractant solutions used for ionic extraction from IER columns and the analytical 

procedures typically used for various anions and cations are given in table 3.1. After 

field exposure, the IER columns are routinely extracted with 75 ml of 1N KI, followed by a second extraction with 75 ml of 1N KI. The two extracts are combined 

and NO -

, SO 2- and PO 3- concentrations in the column extracts are analyzed by 3 4 , 4
53

ion chromatography (Dionex DX-1600, Sunnyvale, California) using a procedure 

modified from Simkin et al. (2004). Ammonium concentrations in the KI extracts 

are determined colorimetrically (Technicon TRAACS autoanalyzer). 

Quality control measures include a field blank IER tube that is capped and 

deployed with other tubes onsite for the same length of time. This is particularly 

important because of the potential release of quaternary amine groups from the 

anion resin, which could result in slightly elevated background levels of NH + when 4

using mixed-bed resins (Fenn and Poth 2004). Quality assurance and quality control procedures should also include analysis of laboratory standards and of random 

duplicate samples. Phosphate concentrations in the IER column extracts are also 

routinely measured using ion chromatography to aid in the detection of bird dropping contamination. Following a more rigorous extraction, the IER column extracts 

can also be analyzed for Ca+, Mg2+, and Na+ or other metals, such as by inductively 

coupled plasma atomic emission spectroscopy (ICP-AES) (Fenn et al. 2015a). If 

more complete base cation deposition data are desired (e.g., including data on K+

deposition), separate field-exposed IER columns can be extracted with an alternative extractant such as 1N ammonium acetate (NH C H O ) or 1N hydrochloric 4 2 3 2

acid (HCl) instead of extracting with a K+ salt (see table 3.1). Yamashita et al. (2014) 

used 0.5N HCl as an extractant for SO 2- and base cations, but we found better 4

recovery of base cations using 1N HCl. We recommend extraction with ammonium 

acetate, a widely used extractant for base cation analysis in soils (Chapman 1965), 

because the extractant can simply be percolated through the intact resin columns 

using the same procedures described for KCl or KI extractions in appendix 2. 

An important consideration is to know the extraction efficiency of the IER 

columns; that is, what percentage of the ions of interest are recovered during the 

extraction procedure. This can be determined by loading the columns with known 

amounts of the ions of interest at levels approximating or slightly greater than 

expected in the more polluted field sites, performing sequential extractions and 

measuring ion recovery. For commonly measured ions such as NO -

, NH +, and 3 4

SO 2-, recovery rates are within the range of 94 to 99 percent and 89 and 97 percent 4

for base cations extracted with 1N ammonium acetate. These percentage recovery 

values are used to adjust the calculated deposition rates from field samples. Another 

consideration in the use of IER is their durability and reliability under freeze-thaw 

and wet-dry cycles. Several studies have shown that IER perform well under such 

cycles (Fenn et al. 2004, Mamo et al. 2004). However, it is recommended that any 

IER used in long-term environmental monitoring be tested for reliability under the 

appropriate environmental conditions. 
54

GENERAL TECHNICAL REPORT PSW-GTR-257

3.8―Data Processing and Calculation of Deposition 

Rates

Most commonly, the ultimate objective for monitoring with IER samplers is to 

calculate annual deposition of the pollutants of interest. Thus, the most common 

units are kilograms per hectare per year (kg ha-1 yr

-1; e.g., for N, S, etc.). The most 

commonly measured pollutants for ecological-effects studies are NO -N, NH -N, 3 4

and SO -S. In this case, the sum of NO -N and NH -N equals total inorganic 4 3 4

N, also known as dissolved inorganic N. To determine deposition levels per unit 

of land area, the amount of each ion of interest that was extracted from the IER 

column must be extrapolated from the area of the IER collector opening (i.e., the 

funnel or snow tube opening; e.g., square centimeters) to the desired land area unit 

of measure (e.g., hectares). A sample calculation is given in appendix 2. We prefer 

to express the measured ions in terms of the primary element of interest (e.g., N or 

S) instead of as the ion measured. For example, we would give the final deposition 

of nitrate as nitrate-N (NO -N) instead of as NO , and as SO -S instead of as SO . 3 3 4 4

In any case, it should always be communicated clearly in which units of measure 

the ionic deposition is being expressed. For studies considering soil or watershed 

acidification effects, typical deposition units used for acidifying ions (NO -, 3

NH +, SO 2-) or acid-neutralizing compounds (Ca2+, Mg2+, Na+, K+) are generally 4 4

expressed as chemical equivalents (e.g., equivalent hectares per year [eq ha-1 yr

-1]) 

(Fenn et al. 2015a). 

One common strategy is to deploy IER collectors for two exposure periods of 

about 6-months duration, with IER column changeout in early spring and another in 

late fall; however, other seasonal exposure periods can be used. Summing the data 

from each exposure period yields annual deposition data, as long as the total monitoring period is about 12 months. To characterize deposition at a given site, it is 

much preferred to monitor for multiple years. Samplers deployed in open areas provide bulk deposition, which is similar to wet deposition, plus some dry deposition 

collected by the funnels during dry periods. Ion exchange samplers placed under 

tree or shrub canopies provide throughfall flux data. If landscape-level deposition 

data are desired, consideration must be made regarding percentage of canopy cover 
55

of the study area. Alternatively, if collectors are placed within transects of predetermined spacing with sufficient replication, this approach is designed to sample the 

general area and its various cover types. Deposition data from this sampling design 

provides an estimate of landscape-level deposition inputs for the study area. 

An important step in calculating deposition is to identify replicate samplers 

that are outliers, most commonly as a result of contamination from bird droppings, 

other animal disturbance, or other issues. Contamination from bird droppings is 

mainly a problem in collectors in open sites as a result of birds perching on the 

collectors. Contaminated samples will generally show elevated NH + and PO 3-

4 4

values. Because PO 3- deposition in bulk deposition is generally very low, PO 3- is a 4 4

good indicator of contamination. Sometimes bird droppings can be observed in the 

collectors and should be noted, but often such contamination is rinsed off in subsequent precipitation events. Values from any contaminated samples should be deleted 

from the analysis. 
56

GENERAL TECHNICAL REPORT PSW-GTR-257
57

Chapter 4: Selected Approaches for Estimating 

Atmospheric Nitrogen Deposition

4.1―Rationale for Deciding Upon the Best Approach

Table 4.1 summarizes the more commonly used approaches for estimating nitrogen 

(N) deposition and the advantages and disadvantages of these approaches. This is 

not an exhaustive list, but instead we focus on deposition monitoring methods that 

can be applied by using passive monitoring or simulated N-deposition approaches, 

and that can be used to estimate N deposition across the landscape or at a network 

of study sites. All of the methods listed include measures of both wet and dry deposition, thus allowing for estimates of total N deposition. The four best approaches 

we propose based on these criteria are (1) throughfall N deposition; (2) inferential 

for dry deposition + wet deposition measurements; (3) simulated N deposition; and 

(4) for high-elevation systems with a persistent winter snowpack, a hybrid approach 

consisting of ion exchange resin (IER) bulk deposition in summer and snowpack 

sampling in winter.

Although in a given situation one of these approaches may be best suited, 

because of uncertainty in all these measurements, when feasible, we recommend 

considering estimating N deposition with more than one approach. In the following subsections, we highlight the key considerations when deciding upon which 

approach(es) to use for measuring N deposition. 

We focus on deposition 

monitoring methods 

that can be applied 

by using passive 

monitoring or 

simulated N-deposition 

approaches, and that 

can be used to estimate 

N deposition across 

the landscape or at a 

network of study sites. 

All of the methods 

listed include measures 

of both wet and dry 

deposition, thus 

allowing for estimates 

of total N deposition.

4.2―Throughfall Nitrogen Deposition, Branch Rinsing, 

and Using Epiphytic Lichens as Passive Samplers

In forests or shrublands where there is sufficient canopy structure to capture dryand cloudwater-deposited pollutants, throughfall is considered the easiest method to 

estimate total N deposition to the ecosystem. This is particularly true if IER collectors are used with changeout times as infrequent as twice per year. As described in 

section 1.5, in throughfall, the flux of nutrients from the canopy to the forest floor 

is usually a lower bound estimate of total N deposition because of canopy retention 

of a portion of the atmospherically deposited pollutants. This underestimate of total 

N deposition is the largest uncertainty in the throughfall approach. On the other 

hand, the advantage of throughfall is that it is based on deposition to the natural 

surface receptor, the native vegetation at the monitoring site. One benefit of measuring throughfall N deposition is the large number of comparative studies from 

throughout the world reporting throughfall N deposition and associated ecosystem 

effects. This allows one to evaluate how polluted a study site is in comparison to 

previous studies of throughfall N deposition and what typical ecosystem responses 

can be expected at the measured N inputs in throughfall. 
58

GENERAL TECHNICAL REPORT PSW-GTR-257 Table 4.1―Factors to consider in selecting appropriate deposition monitoring approaches (continued) Technique Applications Advantages Disadvantages Throughfall Measuring deposition fluxes under vegetation. A simple method that integrates deposition to the native vegetative receptor canopy. 

Includes estimates of wet, fog, and dry deposition. Throughfall S and Na+ deposition is generally equivalent to total S and 

Na+ deposition.

For N deposition, throughfall underestimates total N deposition owing to 

canopy retention of N. Can only collect samples when sufficient precipitation occurs, which can be a limiting factor in arid or semiarid zones.

Branch rinsing Consists of washing tree or shrub branches 

with distilled water on a periodic basis to measure ions washed from branches. This approach could be considered a mini-throughfall technique. Can be used as a measure of dry deposition per branch surface area.

Do not need precipitation to collect branch 

rinse samples and thus estimate dry deposition fluxes. Is particularly useful to compare 

dry deposition across sites or over time.

If precipitation occurs during dry exposure period, this disrupts the branch 

rinse measurements; thus, the technique is only useful when dry periods occur (typically 2-week precipitation-free periods needed). To estimate total deposition requires scaling up to the leaf area of the entire tree or canopy, which entails uncertainty. 

Inferential modeling Calculation of dry deposition fluxes to surfaces and internal uptake of N gases. It is 

based on empirical atmospheric pollutant concentration measurements, empirically derived surface deposition velocities and literature-based stomatal conductance. For total deposition estimates, will need to also measure wet deposition.

Provides dry deposition input estimates 

and indicates the relative importance of various gaseous and particulate pollutants. Can use passive sampler data for inferential modeling. 

Much more data intensive than throughfall 

measurements. Atmospheric measurements and data used in calculations (i.e., deposition velocities for each pollutant) entail uncertainty.
59

Table 4.1―Factors to consider in selecting appropriate deposition monitoring approaches (continued)Technique Applications Advantages DisadvantagesSimulation modeling Simulation of dry and wet deposition to the 

ecosystem

Provides estimates of deposition fluxes for all 

major N forms, including organic N, in wet and dry deposition. Can provide simulated deposition from past and future years and under a variety of pollutant emissions scenarios. Provides such estimates across the landscape, whereas empirical measurements can be done at a limited number of sites. Provides broad-scale coverage, typically on a 12- by 12-km-grid scale. Models have limited capacity to simulate cloudwater deposition and orographic effects on deposition in montane regions.

Because of the complexity of simulating 

atmospheric deposition, estimates need to be confirmed with empirical data. In montane polluted sites in California, models generally underestimate N deposition fluxes. Models are better at providing broad-scale average deposition but are not reliable for site-specific deposition estimates, particularly when deposition is elevated. Hybrid models, such as TDEP, that incorporate empirical data give increased confidence in simulated deposition values.

IER bulk deposition in summer + snowpack sampling in winter

To estimate annual deposition in highelevation systems with winter snowpacks. Provides realistic estimates of total deposi- tion in remote sites with more difficult 

access; these areas are often sensitive to relatively low atmospheric inputs.

Expected to underestimate dry deposition 

in summer by an unknown amount, but still provides better estimates of annual deposition than other feasible methods.

Wet deposition To measure deposition in precipitation. Easier to measure than dry deposition; often 

measured as bulk deposition to continuously open collectors that include some background dry deposition.

Is usually the smaller component of total 

deposition, especially in more arid climates—thus not representative of total atmospheric deposition exposures and inputs. Even sites with very high total N deposition can appear as low-N deposition sites on national wet deposition maps.

Estimating throughfall N deposition from N levels in epiphytic lichens

To estimate throughfall N deposition in 

forests without deposition data, typically remote locations or protected areas where installation of samplers is discouraged.

Minimal disturbance of the site; installation 

of sampling equipment not needed. A good approach for remote sites. Requires some expertise in lichens—i.e., to identify and sample the appropriate species. 

Actual deposition measurements are not 

made; estimated deposition is based on established relationships at other sites between throughfall N deposition and concentrations of N in lichen tissue. 

S = sulfur, Na+ = sodium, N = nitrogen, IER = ion exchange resin, TDEP = total deposition.
60

GENERAL TECHNICAL REPORT PSW-GTR-257

Because of canopy retention of N, in low-deposition sites, bulk N deposition in 

forest clearings may be greater than throughfall N deposition. This is one reason 

why it is often more informative if both throughfall (under canopy) and bulk deposition (open areas) fluxes are measured. Another advantage is that in many cases, if 

both N and sulfur (S) deposition are measured in bulk deposition (or wet deposition) 

and throughfall, throughfall N deposition can often be converted to estimated total 

N deposition as described in Fenn et al. (2013). This is based on the following two 

assumptions supported by many previous literature reports. First, that S/N ratios 

in wet deposition (or bulk deposition) and total deposition are equal. Secondly, that 

throughfall S deposition equals total S deposition. Given these assumptions, total N 

deposition is calculated by using the following formula (Fenn et al. 2013):

Swet/Nwet = Stfall/x

where x = total inorganic N deposition, S = S in wet deposition, N = N in wet wet

wet deposition and S = S in throughfall deposition. tfall

Although this method worked very well in estimating total N deposition for 

15 forested sites from a number of regions (Fenn et al. 2013), mainly in the United 

States, the method should be verified for any given region and climate before being 

used to estimate N deposition fluxes. However, preliminary tests suggest this 

approach may not work well in arid or semiarid areas such as California. 

An important consideration when measuring throughfall deposition in regions 

that experience extended dry periods such as California is the lack of sample collection when no precipitation occurs. It appears that annual throughfall fluxes are lowest in unusually dry years, particularly in low-elevation regions such as chaparral 

or coastal sage scrub habitat that experience less precipitation than forested regions 

(Fenn, unpublished data). Dry deposition continues unabated in drought years, 

but low precipitation results in low throughfall volumes and less efficient washoff 

of pollutants from vegetative canopies. This is also an issue in forests at higher 

elevations, but less so because of infrequent summer thunder showers and cloudwater events and more frequent and higher amounts of precipitation that result in 

more efficient canopy washoff and throughfall collection than in low-elevation 

shrublands. 

A potential solution to the problem of infrequent precipitation is the branch 

rinsing technique, in which branches are manually washed at selected time intervals 

(typically 2 weeks) with distilled water using a hand sprayer (fig. 4.1) (Bytnerowicz 

et al. 1987, 1991). The branch rinse is collected and analyzed for ions of interest. 

This is, in essence, a mini-throughfall technique. Deposited ions washed from the 

branches are quantified and deposition fluxes expressed on a leaf-area basis (e.g., 
61

eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 4.1—Rinsing of foliage on tree branches to measure the ions in the collected rinse solution that were atmospherically deposited to the branches. From this, deposition fluxes since the 

time of the previous branch rinsing can be calculated.

μeq m

-2 h-1

 or mg m

-2). By scaling up from the leaf area of the branches that were 

rinsed to the leaf area of the stand, dry deposition to the canopy of a forest stand 

can be calculated. This technique requires data on leaf area of the washed branches, 

leaf area index of the stand, and stand density (Bytnerowicz et al. 1992)―information that is not required for traditional throughfall measurements. 

There is inherent uncertainty associated with the tree leaf area, stand leaf area 

index, and stand density estimates that all affect the final estimates of stand-level 

deposition based on branch rinsing. Another limitation of this approach is the difficulty or impracticality of obtaining branch rinse data year round in forests because 

of inclement weather in winter and because precipitation events can disrupt the dry 

exposure periods. In addition, it is not known how rinsing the branches on consis-
62

GENERAL TECHNICAL REPORT PSW-GTR-257

tent intervals, such as every two weeks, might give different deposition rates than 

random and less frequent precipitation events resulting in throughfall deposition. 

Measurements of N concentrations in epiphytic (tree-inhabiting) lichens (fig. 

4.2) have been calibrated with IER throughfall deposition data in the Western 

United States in order to predict throughfall deposition from N concentration in 

lichens (Root et al. 2013). Thus, lichens function as a type of passive N sampler. 

Lichens can be sampled and measured for N content, and from this throughfall N eicvret SseroA FDS, Uzicworentyj BezrdnA

Figure 4.2—An example of an epiphytic lichen (Letharia vulpina (L). Hue commonly 

known as the wolf lichen) for which nitrogen (N) concentrations in the lichen tissue 

have been calibrated with throughfall N deposition. Thus, N deposition fluxes can be 

estimated based on N concentrations measured in lichen samples collected from trees 

in forested areas (Root et al. 2013). 

Measurements of 

N concentrations 

in epiphytic (treeinhabiting) lichens 

have been calibrated 

with IER throughfall 

deposition data in the 

Western United States 

in order to predict 

throughfall deposition 

from N concentration 

in lichens. Thus, 

lichens function as 

a type of passive N 

sampler.
63

deposition can be estimated. This is particularly useful in remote locations where 

installing deposition samplers may be difficult or prohibited. Methods are described 

more fully in Root et al. (2013). 

4.3―Inferential Method of Calculating Dry Deposition 

of Nitrogen

The inferential method is used to calculate dry deposition and thus can provide useful 

data for the situations described above when, during long dry periods, little or no 

throughfall deposition can be collected. With the inferential method, dry deposition 

fluxes are calculated from data on atmospheric concentrations of nitrogenous pollutants, the deposition velocities of each pollutant, and leaf area index. Total deposition 

can then be determined by summing wet N deposition fluxes and dry deposition from 

the inferential approach. Wet deposition can be determined from precipitation samplers, or bulk deposition measurements from IER collectors can be used. 

As can be seen from the preceding paragraph, the data and level of expertise 

required for the inferential approach are much greater than for simple throughfall 

measurements, and each additional variable potentially introduces greater uncertainty in the deposition estimates. However, recent comparisons of throughfall 

deposition and inferential estimates in California have resulted in similar deposition 

fluxes (Bytnerowicz et al. 2015, Fenn et al. 2011b). We have recently described a 

geographic information system-based inferential approach demonstrated with a 

case study that mapped N deposition across a major portion of the San Bernardino 

Mountains in southern California (Bytnerowicz et al. 2015). The air pollution data 

for this study was from a network of passive samplers for gaseous N air pollutants (nitric oxide [NO], nitrogen dioxide [NO ], ammonia [NH ] and nitric acid 2 3 ,

[HNO ]. Branch rinse data for NO - and NH + were used for determining their 3 3 4

surface deposition velocity to key tree species. Literature-based values of stomatal 

conductance were used to calculate internal uptake of nitrogenous compounds. 

Using this approach, meteorological data are not required (Bytnerowicz et al. 2015). 

Without the use of passive samplers, such a study would be impractical as it would 

require a network of electronic samplers to be installed across the mountain range 

that includes many sites without electric power. 

4.4―Simulated Nitrogen Deposition

In recent years, comprehensive air quality models have provided reasonable broadscale estimates of N deposition in the United States. The most common models are 

Community Multi-scale Air Quality (CMAQ) and more recently the total deposition 

(TDEP) models, both providing output at 12- by 12-km-grid scales for the conti-
64

GENERAL TECHNICAL REPORT PSW-GTR-257

nental United States (fig. 4.3). Nitrogen deposition for two-thirds of California has 

also been simulated at a 4- by 4-km-grid scale with the CMAQ model (Tonnesen 

et al. 2007). Simulated deposition by CMAQ to montane regions of California have 

been adjusted by empirical throughfall deposition data collected with IER samplers 

(fig. 1.1) (adjustment method described in Fenn et al. 2010). The TDEP is a hybrid 

model based on CMAQ but adjusted for empirical air pollution data where available 

(Schwede and Lear 2014). Advantages of these models are that they provide complete areal coverage of N deposition, and all forms of N air pollutants are included 

in the model, including trace and organic forms of N, not commonly analyzed in 

empirical measurements. Furthermore, provided with retrospective or projected N 

emissions, air quality models can simulate historical and future N deposition and 

estimated deposition under varying emissions scenarios or regulatory policies. 

Currently, simulated N deposition for the United States based on TDEP simulations 

are available for the years 2000 to 2014 (http://nadp.sws.uiuc.edu/committees/tdep/

tdepmaps/). Modelled deposition has also been used to extrapolate seasonal deposition estimates from empirical data to annual deposition (Bytnerowicz et al. 2015). 

Simulated N deposition is best at providing broad-scale N deposition estimates. 

Hotspots of local-scale elevated N deposition are often missed, which is of particular concern in California. Thus, when deposition data are needed for site-specific 

studies, such as looking for thresholds of ecosystem effects or specific biological 

responses, local empirical N deposition measurements should be used whenever 

possible. We have found that CMAQ N deposition estimates in montane sites in 

California are underestimated in sites with N deposition greater than approximately 

6 kg ha-1 yr

-1. Complex chemical and atmospheric processes are not perfectly simulated by models. For example, orographic effects and cloud-water deposition are not 

well accounted for in CMAQ outputs, and emissions inventories, particularly for 

NH , are also uncertain, resulting in underestimates of NH -N deposition (Fenn 3 4

et al. 2010). For this reason, we adjusted CMAQ N deposition in montane forested 

regions of California based on the linear relationship with empirical throughfall 

data from the Sierra Nevada and San Bernardino Mountains (Fenn et al. 2010). This 

produced a more reasonable N deposition map for California (fig. 1.1).

Simulated N deposition 

is best at providing 

broad-scale N 

deposition estimates. 

Hotspots of local-scale 

elevated N deposition 

are often missed, 

which is of particular 

concern in California. 

Thus, when deposition 

data are needed for 

site-specific studies, 

such as looking 

for thresholds of 

ecosystem effects 

or specific biological 

responses, local 

empirical N deposition 

measurements should 

be used whenever 

possible.

The TDEP model, particularly in the most recent years, has improved estimates 

of N deposition for California because where possible, empirical NH data are 3

used to adjust the simulated deposition of reduced N. Because of uncertainty in 

simulated deposition, it is important to evaluate modeled deposition with empirical 

measurements when possible. This again reiterates the point that because of uncertainty in all deposition measurements or simulations, there is value in applying 

more than one approach. 
65

Figure 4.3—Total nitrogen (N) deposition for the continental United States in 2014 based on the total deposition hybrid model at a 12- by 

12-km-grid scale (ftp://ftp.epa.gov/castnet/tdep/images/n_tw/n_tw-2014.png). This simulation model is adjusted with empirical air quality data where available (Schwede and Lear 2014). (Map figure courtesy of National Atmospheric Deposition Program, Total Deposition 

Science Committee (TDEP), http:/nadp.isws.illinois.edu.)

4.5―High-Elevation Systems: IER Bulk Deposition in 

Summer Plus Snowpack Sampling

Clow et al. (2015) described an effective hybrid approach for estimating total N 

deposition in high-elevation systems characterized by a persistent snowpack during 

winter. If rain-on-snow events occur in the monitoring region, such as at lower 

elevation sites, then this method is not appropriate. Sampling and chemical analysis 

of the persistent snowpack during winter and early spring provides an effective 

integrator of wet-plus-dry deposition over the winter (Fenn et al. 2009). In the 

study by Clow et al. (2015), the IER collectors were placed near ground level in an 

attempt to sample the snowmelt from the snowpack in the spring, but this proved 
66

GENERAL TECHNICAL REPORT PSW-GTR-257

ineffective, presumably as a result of preferential flow through the snowpack during 

snowmelt. It was concluded that annual N deposition was best estimated as the sum 

of bulk deposition measured with the IER collectors in the summer and snowpack 

sampling in winter (Clow et al. 2015, Wasiuta et al. 2015) (fig. 4.4). 

decre, Mainrofilaf Cy oitsreivn, Usorenso CidraicR edisreiv, Rainrofilaf Cy oitsreivn, Unamkics SemaJ

Figure 4.4—Annual deposition to high-elevation sites with winter snowpack can be 

estimated as the sum of summertime ion exchange resin bulk deposition (top panel) 

plus wintertime deposition (bottom panel) in the snowpack (Clow et al. 2015).
67

4.6―Conclusions

To evaluate ecosystem responses to air pollution, ecosystem exposure to biologically important pollutants must be determined. In California, the use of passive 

sampling methods for characterizing spatial patterns of air pollution exposure and 

atmospheric deposition of N has enabled major advances in our understanding of 

ecosystem-response thresholds (e.g., N deposition critical loads) (Fenn et al. 2010). 

This was possible because of the use of passive sampling approaches that are 

relatively simple to use and do not require electric power or frequent field visits, 

thus allowing for extensive pollution and deposition monitoring in remote areas. 

Sometimes a combination of air quality or deposition monitoring approaches may 

be needed depending on the uncertainties, circumstances, and objectives within a 

given study. In this report, we focus on passive sampling methods, particularly for 

nitrogenous pollutants and ozone (O ), but these are discussed within the context of 3

alternative air pollution monitoring approaches appropriate for remote regions, each 

with their particular advantages and limitations as discussed herein. 

The two principal passive sampling approaches described in this report are 

(1) passive samplers for measuring time-averaged atmospheric concentrations of 

gaseous pollutants (N and S compounds and O ), and (2) IER deposition samplers 3

for measuring ionic deposition fluxes in throughfall (under tree canopies) or as 

bulk deposition (in canopy-free areas). The first approach provides data on average 

atmospheric concentrations of pollutants, from which deposition fluxes of these 

pollutants can be calculated if the appropriate supportive data are available. The 

second approach, when used to measure throughfall N deposition fluxes, provides 

a lower bound estimate of total (wet-plus-dry) N deposition. For broad-scale (i.e., 

regional to national) estimates of N deposition, atmospheric simulation models have 

improved and become more widely available. However, caution is warranted in 

applying simulation model results to site-specific studies or at fine scale in California because of steep dry deposition gradients and cloud water N deposition that are 

not captured by such models. In summary, a variety of empirical, simulation, and 

hybrid deposition approaches are available, and when judiciously applied, can each 

provide useful estimates of atmospheric deposition inputs for ecosystem-effects 

studies.
68

GENERAL TECHNICAL REPORT PSW-GTR-257

English Equivalents

When you know: Multiply by: To find:

Millimeter (mm) 25.4 Inch

Centimeters (cm) 2.54 Inch

Kilometers (km) 1.609 Mile

Meters (m) 0.305 Foot

Hectare (ha) 0.405 Acre

2 Square meters (m ) 0.093 Square foot

2 Square centimeters (cm ) 929 Square foot

Liters (L) 28.317 Cubic foot

Liters (L) 3.785 Gallon

Milliliters (ml or cubic 

 centimeters cc) 29.574 Ounce (fluid; oz)

Kilograms (kg) 0.454 Pound

Grams (g) 453.592 Pound

-1 Kilograms per hectare (kg ha ) 0.892 Pound per acre

Micrograms per cubic meter (μg m-3)*:

 NH3 1.437 part per billion

 HNO3 0.388 part per billion

 NO2 0.531 part per billion

 NO 0.813 part per billion

 O3 0.510 part per billion

 SO2 0.381 part per billion

Milligrams (mg) 2.835 x 104 Ounce (oz)

Degrees Celsius (°C) 1.8 °C + 32 Degrees Fahrenheit

*at 25 °C; 760 mm Hg
69

Acknowledgments

The authors thank Beatriz Vindiola, Madeline Blua, Diane Alexander, and Tony 

Davila for help in editing laboratory protocol descriptions and in providing updated 

laboratory photographs. The vital contributions of Tim Blubaugh, Drew Farr, and 

Chris Ross in the development of laboratory and field techniques for monitoring 

deposition with IER samplers is gratefully acknowledged. The authors acknowledge the invaluable assistance of Dave Jones, Tony Davila, and Tony Gomez in 

developing the original ion exchange collectors and installing and maintaining the 

collectors in the field. The efforts of Enrique Jimenez, Joe Decruyenaere, and Diane 

Alexander in developing laboratory extraction and chemical analysis procedures are 

also acknowledged.

References

Allegrini, I.; De Santis, F. 1989. Measurement of atmospheric pollutants relevant 

to dry acid deposition. Critical Reviews in Analytical Chemistry. 21: 237–255.

Allegrini, I.; De Santis, F.; Di Palo, V.; Febo, A.; Perrino, C.; Possanzini, M. 

1987. Annular denuder method for sampling reactive gases and aerosols in the 

atmosphere. The Science of the Total Environment. 67: 1–16.

Asman, W.A.H.; Ridder, T.B.; Reijnders, H.F.R.; Slanina, J. 1982. Influence 

and prevention of bird-droppings in precipitation chemistry experiments. Water, 

Air and Soil Pollution. 17: 415–420.

Bell, M.D.; Sickman, J.O.; Bytnerowicz, A.; Padgett, P.E.; Allen, E.B. 2014.

Variation in isotopologues of atmospheric nitric acid in passively collected 

samples along an air pollution gradient in southern California. Atmospheric 

Environment. 94: 287–296.

Berg, N.; Dunn, P.; Fenn, M. 1991. Spatial and temporal variability of rime ice 

and snow chemistry at five sites in California. Atmospheric Environment. 25A: 

915–926.

Bishop, G.A.; Peddle, A.M.; Stedman, D.H. 2010. On-road emission 

measurements of reactive nitrogen compounds from three California cities. 

Environmental Science and Technology. 44: 3616–3620.

Bishop, G.A.; Stedman, D.H. 2015. Reactive nitrogen species emission trends 

in three light-/medium-duty United States fleets. Environmental Science and 

Technology. 49: 11234–11240.
70

GENERAL TECHNICAL REPORT PSW-GTR-257

Bleeker, A.; Draaijers, G.; van der Veen, D.; Erisman, J.W.; Mols, H.; Fonteijn, 

P.; Geusebroek, M. 2003. Field intercomparison of throughfall measurements 

performed within the framework of the Pan European intensive monitoring 

program of EU/ICP Forest. Environmental Pollution. 125: 123–138.

Bobbink, R.; Hettelingh, J.-P., eds. 2011. Review and revision of empirical 

critical loads and dose response relationships. RIVM report 680359002, ISBN 

978-90-6960-251-6. Bilthoven, The Netherlands: Coordination Centre for 

Effects, National Institute for Public Health and the Environment. 244 p.

Burley, J.D.; Theiss, S.; Bytnerowicz, A.; Gertler, A.; Schilling, S.; Zielinska, 

B. 2015. Surface ozone in the Lake Tahoe basin. Atmospheric Environment. 

109: 351–369.

Bytnerowicz, A.; Arbaugh, M.; Schilling, S.; Fraczek, W.; Alexander, D. 2008.

Ozone distribution and phytotoxic potential in mixed conifer forests of the San 

Bernardino Mountains, southern California. Environmental Pollution. 155: 

398–408. 

Bytnerowicz, A.; Dawson, P.J.; Morrison, C.L.; Poe, M.P. 1991. Deposition 

of atmospheric ions to pine branches and surrogate surfaces in the vicinity of 

Emerald Lake Watershed, Sequoia National Park. Atmospheric Environment. 

25A: 2203–2210.

Bytnerowicz, A.; Dawson, P.J.; Morrison, C.L.; Poe, M.P. 1992. Atmospheric 

dry deposition on pines in the Eastern Brook Lake Watershed, Sierra Nevada, 

California. Atmospheric Environment. 26A: 3195–3201.

Bytnerowicz, A.; Fenn, M.E. 1996. Nitrogen deposition in California forests: a 

review. Environmental Pollution. 92: 127–146.

Bytnerowicz, A.; Fenn, M.; Allen, E.B.; Cisneros, R. 2016. Atmospheric 

chemistry. In: Mooney, H.; Zavaleta, E., eds. Ecosystems of California. Oakland, 

CA: University of California Press: 107–128. Chapter 7. 

Bytnerowicz, A.; Fraczek, W.; Schilling, S.; Alexander, D. 2010. Spatial 

and temporal distribution of ambient nitric acid and ammonia in the 

Athabasca Oil Sands Region, Alberta. Journal of Limnology. 69(Suppl. 1): 

11–21.
71

Bytnerowicz, A.; Johnson, R.F.; Zhang, L.; Jenerette, G.D.; Fenn, M.E.;

Schilling, S.L.; Gonzalez-Fernandez, I. 2015. An empirical inferential 

method of estimating nitrogen deposition to Mediterranean-type 

ecosystems: the San Bernardino Mountains case study. Environmental 

Pollution. 203: 69–88. 

Bytnerowicz, A.; Miller, P.R.; Olszyk, D.M. 1987. Dry deposition of 

nitrate, ammonium and sulfate to a Ceanothus crassifolius canopy and 

surrogate surfaces. Atmospheric Environment. 21: 1749–1757.

Bytnerowicz, A.; Padgett, P.E.; Arbaugh, M.J.; Parker, D.R.; Jones, D.P. 

2001. Passive sampler for measurement of atmospheric nitric acid vapor 

(HNO ) concentrations. TheScientificWorldJOURNAL. 1: 815–822. 3

Bytnerowicz, A.; Sanz, M.J.; Arbaugh, M.J.; Padgett, P.E.; Jones, 

D.P.; Davila, A. 2005. Passive sampler for monitoring ambient nitric 

acid (HNO ) and nitrous acid (HNO ) concentrations. Atmospheric 3 2

Environment. 39: 2655–2660.

Byun, D.; Schere, K.L. 2006. Review of the governing equations, 

computational algorithms, and other components of the Models-3 

Community Multiscale Air Quality (CMAQ) modeling system. Applied 

Mechanics Reviews. 59: 51–77.

Calatayud, V.; Schaub, M. 2013. Methods for measuring gaseous air 

pollutants in forests. In: Ferretti, M.; Fischer, R., eds. Developments 

in environmental science, volume 12: Forest monitoring: methods for 

terrestrial investigations in Europe with an overview of North America 

and Asia. Amsterdam: Elsevier: 375–384. Chapter 19. 

Cape, J.N.; van der Eerden, L.J.; Sheppard, L.J.; Leith, I.D.; Sutton, 

M.A. 2009. Evidence for changing the critical level for ammonia. 

Environmental Pollution. 157: 1033–1037.

Chapman, H.D. 1965. Cation exchange capacity. In: Black, C.A., ed. 

Methods of soil analysis. Part 2. Madison, WI: American Society of 

Agronomy, Inc. Agronomy. 9: 891–901. 

Cisneros, R.; Bytnerowicz, A.; Schweizer, D.; Zhong, S.R.; Traina, 

S.; Bennett, D.H. 2010. Ozone, nitric acid, and ammonia air pollution 

is unhealthy for people and ecosystems in southern Sierra Nevada, 

California. Environmental Pollution. 158: 3261–3271. 
72

GENERAL TECHNICAL REPORT PSW-GTR-257

Clarke, N.; Zlindra, D.; Ulrich, E.; Mosello, R.; Derome, J.; Derome, 

K.; König, N.; Lövblad, G.; Draaijers, G.P.J.; Hansen, K.; Thimonier, 

A.; Waldner, P. 2010. Sampling and analysis of deposition. Part XIV. In: 

Manual on methods and criteria for harmonized sampling, assessment, 

monitoring and analysis of the effects of air pollution on forests. UNECE, 

ICP Forests, Hamburg. ISBN: 978-3-926301-03-1. http://www.icp-forests.

org/Manual.htm. (14 November 2017). 66 p. 

Clow, D.W.; Roop, H.A.; Nanus, L.; Fenn, M.E.; Sexstone, G.A. 2015.

Spatial patterns of atmospheric deposition of nitrogen and sulfur using 

ion-exchange resin collectors in Rocky Mountain National Park, USA. 

Atmospheric Environment. 101: 149–157.

Collett,	J.L.,	Jr.;	Daube,	B.C.,	Jr.;	Hoffmann,	M.R.	1990. The chemical 

composition of intercepted cloudwater in the Sierra Nevada. Atmospheric 

Environment. 24A: 959–972.

Cornell, S.E. 2011. Atmospheric nitrogen deposition: revisiting the question of the 

importance of the organic component. Environmental Pollution. 159: 2214–2222.

Cox, P.; Delao, A.; Komorniczak, A. 2013. The California almanac of emissions 

and air quality, 2013 edition. Sacramento, CA: California Environmental 

Protection Agency, Air Resources Board. 

Dämmgen, U.; Erisman, J.W.; Cape, J.N.; Grünhage, L.; Fowler, D. 2005.

Practical considerations for addressing uncertainties in monitoring bulk 

deposition. Environmental Pollution. 134: 535–548. 

Daube, B., Jr.; Kimball, K.D.; Lamar, P.A.; Weathers, K.C. 1987. Two new 

ground-level cloud water sampler designs which reduce rain contamination. 

Atmospheric Environment. 21: 893–900.

Davis, F.W.; Stoms, D.M.; Hollander, A.D.; Thomas, K.A.; Stine, P.A.; Odion, 

D.; Borchert, M.I.; Thorne, J.H.; Gray, M.V.; Walker, R.E.; Warner, K.; 

Graae, J. 1998. The California gap analysis project; final report. University of 

California, Santa Barbara, CA. http://www.biogeog.ucsb.edu/projects/gap/gap_

rep.html. (31 August 2016).

Draaijers, G.P.J.; Erisman, J.W.; Spranger, T.; Wyers, G.P. 1996. The 

application of throughfall measurements for atmospheric deposition monitoring. 

Atmospheric Environment. 30: 3349–3361.
73

Du, E.; Jiang, Y.; Fang, J.Y.; De Vries, W. 2014a. Inorganic nitrogen deposition 

in China’s forests: status and characteristics. Atmospheric Environment. 98: 

474–482.

Du, E.Z.; De Vries, W.; Galloway, J.N.; Hu, X.Y.; Fang, J.Y. 2014b. Changes 

in wet nitrogen deposition in the United States between 1985 and 2012. 

Environmental Research Letters 9: 95004. 

Elliott, E.M.; Kendall, C.; Boyer, E.W.; Burns, D.A.; Lear, G.G.; Golden, 

H.E.; Harlin, K.; Bytnerowicz, A.; Butler, T.J.; Glatz, R. 2009. Dual nitrate 

isotopes in dry deposition: utility for partitioning NOx source contributions to 

landscape nitrogen deposition. Journal of Geophysical Research. Biogeosciences. 

114: G04020, doi:10.1029/2008JG000889.

Fenn, M.E.; Allen, E.B.; Geiser, L.H. 2011b. Mediterranean California. In: Pardo, 

L.H.; Robin-Abbott, M.J.; Driscoll, C.T., eds. Assessment of nitrogen deposition 

effects and empirical critical loads of nitrogen for ecoregions of the United 

States. Gen. Tech. Rep. NRS-80. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station: 143–169. Chapter 13.

Fenn, M.E.; Allen, E.B.; Weiss, S.B.; Jovan, S.; Geiser, L.; Tonnesen, G.S.; 

Johnson, R.F.; Rao, L.E.; Gimeno, B.S.; Yuan, F.; Meixner, T.; Bytnerowicz, 

A. 2010. Nitrogen critical loads and management alternatives for N-impacted 

ecosystems in California. Journal of Environmental Management. 91: 

2404–2423.

Fenn, M.E.; Bytnerowicz, A. 1997. Summer throughfall and winter deposition 

in the San Bernardino Mountains in southern California. Atmospheric 

Environment. 31: 673–683.

Fenn, M.E.; Bytnerowicz, A.; Liptzin, D. 2012. Nationwide maps of atmospheric 

deposition are highly skewed when based solely on wet deposition. BioScience. 

62: 621.

Fenn, M.E.; Bytnerowicz, A.; Schilling, S.L.; Ross, C.S. 2015a. Atmospheric 

deposition of nitrogen, sulfur and base cations in jack pine stands in the 

Athabasca Oil Sands Region, Alberta, Canada. Environmental Pollution. 

196: 497–510. 
74

GENERAL TECHNICAL REPORT PSW-GTR-257

Fenn, M.E.; Driscoll, C.T.; Zhou, Q.; Rao, L.E.; Meixner, T.; Allen, E.B.; 

Yuan, F.; Sullivan, T.J. 2015b. Use of combined biogeochemical model 

approaches and empirical data to assess critical loads of nitrogen. In: de Vries, 

W.; Hettelingh, J.-P.; Posch, M., eds. Critical loads and dynamic risk assessments: 

nitrogen, acidity and metals in terrestrial and aquatic ecosystems. Environmental 

Pollution book series. The Netherlands: Springer. Dordrecht: 269–295. Chapter 

10. Vol. 25.

Fenn, M.E.; Jovan, S.; Yuan, F.; Geiser, L.; Meixner, T.; Gimeno, B.S. 2008.

Empirical and simulated critical loads for nitrogen deposition in California 

mixed conifer forests. Environmental Pollution. 155: 492–511.

Fenn, M.E.; Lambert, K.F.; Blett, T.F.; Burns, D.A.; Pardo, L.H.; Lovett, 

G.M.;	Haeuber,	R.A.;	Evers,	D.C.;	Driscoll,	C.T.;	Jeffries,	D.S.	2011a. Setting 

limits: using air pollution thresholds to protect and restore U.S. ecosystems. 

Issues in Ecology, report number 14. Baron, J.S., editor-in-chief. Washington, 

DC: Ecological Society of America. 21 p. 

Fenn, M.E.; Poth, M.A. 2004. Monitoring nitrogen deposition in throughfall 

using ion exchange resin columns: a field test in the San Bernardino Mountains. 

Journal of Environmental Quality. 33: 2007–2014.

Fenn, M.E.; Poth, M.A.; Aber, J.D.; Baron, J.S.; Bormann, B.T.; Johnson, 

D.W.; Lemly, A.D.; McNulty, S.G.; Ryan, D.F.; Stottlemyer, R. 1998.

Nitrogen excess in North American ecosystems: predisposing factors, ecosystem 

responses, and management strategies. Ecological Applications. 8: 706–733.

Fenn, M.E.; Poth, M.A.; Arbaugh, M.J. 2002. A throughfall collection method 

using mixed bed ion exchange resin columns. TheScientificWorldJOURNAL.

2: 122–130. 

Fenn, M.E.; Poth, M.A.; Bytnerowicz, A.; Sickman, J.O.; Takemoto, B.K. 

2003. Effects of ozone, nitrogen deposition, and other stressors on montane 

ecosystems in the Sierra Nevada. In: Bytnerowicz, A.; Arbaugh, M.J.; Alonso, 

R., eds. Developments in environmental science, volume 2: ozone air pollution 

in the Sierra Nevada: distribution and effects on forests. Amsterdam: Elsevier: 

111–155. Chapter 5.

Fenn, M.E.; Poth, M.A.; Schilling, S.L.; Grainger, D.B. 2000. Throughfall and 

fog deposition of nitrogen and sulfur at an N-limited and N-saturated site in the 

San Bernardino Mountains, southern California. Canadian Journal of Forest 

Research. 30: 1476–1488.
75

Fenn, M.E.; Ross, C.S.; Schilling, S.L.; Baccus, W.D.; Larrabee, M.A.; 

Lofgren, R.A. 2013. Atmospheric deposition of nitrogen and sulfur and 

preferential canopy consumption of nitrate in forests of the Pacific Northwest, 

USA. Forest Ecology and Management. 302: 240–253.

Fenn, M.E.; Sickman, J.O.; Bytnerowicz, A.; Clow, D.W.; Molotch, N.P.; 

Pleim, J.E.; Tonnesen, G.S.; Weathers, K.C.; Padgett, P.E.; Campbell, 

D.H. 2009. Methods for measuring atmospheric nitrogen deposition inputs in 

arid and montane ecosystems of western North America. In: Legge, A.H., ed. 

Developments in environmental science, volume 9: air quality and ecological 

impacts: relating sources to effects. Amsterdam: Elsevier: 179–228. Chapter 8. 

Ferretti, M.; Cristofolini, F.; Cristofori, A.; Gerosa, G.; Gottardini, E. 2012. A 

simple linear model for estimating ozone AOT40 at forest sites from raw passive 

sampling data. Journal of Environmental Monitoring. 14: 2238–2244.

Ferretti, M.; Marchetto, A.; Arisci, S.; Bussotti, F.; Calderisi, M.; Carnicelli, 

S.; Cecchini, G.; Fabbio, G.; Bertini, G.; Matteucci, G.; De Cinti, B.; 

Salvati, L.; Pompei, E. 2014. On the tracks of nitrogen deposition effects on 

temperate forests at their southern European range—an observational study from 

Italy. Global Change Biology. 11: 3423–3438.

Finlayson-Pitts, B.J.; Pitts, J.N., Jr., 1986. Atmospheric chemistry: fundamentals 

and experimental techniques. New York: John Wiley & Sons. 1098 p.

Frączek,	W.;	Bytnerowicz,	A.;	Arbaugh,	M.J.	2003. Use of geostatistics to 

estimate surface ozone patterns. In: Bytnerowicz, A.; Arbaugh, M.J.; Alonso, 

R., eds. Developments in environmental science, volume 2: ozone air pollution 

in the Sierra Nevada: distribution and effects on forests. Amsterdam: Elsevier: 

215–247. Chapter 9.

Galloway, J.N.; Aber, J.D.; Erisman, J.W.; Seitzinger, S.P.; Howarth, R.W.; 

Cowling, E.B.; Cosby, B.J. 2003. The nitrogen cascade. BioScience. 53: 

341–356.

García-Gómez, H.; Izquieta-Rojano, S.; Aguillaume, L.; González-Fernández, 

I.; Valiño, F.; Elustondo, D.; Santamaría, J.M.; Àvila, A.; Fenn, M.E.; 

Alonso, R. 2016. Atmospheric deposition of inorganic nitrogen in Spanish 

forests of Quercus ilex measured with ion‐exchange resins and conventional 

collectors. Environmental Pollution. 216: 653–661.
76

GENERAL TECHNICAL REPORT PSW-GTR-257

Glaubig, R.; Gomez, A. 1994. A simple, inexpensive rain and canopy throughfall 

collector. Journal of Environmental Quality. 23: 1103–1107.

Granat, L.; Hällgren, J.E. 1992. Relation between estimated dry deposition and 

throughfall in a coniferous forest exposed to controlled levels of SO and NO . 2 2

Environmental Pollution. 75: 237–242.

Hansen,	K.;	Thimonier,	A.;	Clarke,	N.;	Staelens,	J.;	Žlindra,	D.;	Waldner,	P.;	

Marchetto, A. 2013. Atmospheric deposition to forest ecosystems. In: Ferretti, 

M.; Fischer, R., eds. Developments in Environmental Science. Volume 12: forest 

monitoring: methods for terrestrial investigations in Europe with an overview of 

North America and Asia. Amsterdam: Elsevier: 337–374.

Houle,	D.;	Ouimet,	R.;	Paquin,	R.;	Laflamme,	J.G.	1999. Determination of 

sample size for estimating ion throughfall deposition under a mixed hardwood 

forest at the Lake Clair Watershed (Duchesnay, Quebec). Canadian Journal of 

Forest Research. 29: 1935–1943.

Hsu, Y.-M.; Bytnerowicz, A.; Fenn, M.E.; Percy, K.E. 2016. Nitrogenous and 

sulfurous air pollution and atmospheric dry deposition in the Athabasca Oil 

Sands Region, Alberta, Canada. Science of the Total Environment. 568: 285–295.

Johnston, K.; Ver Hoef, J.M.; Krivoruchko, K.; Lucas, N. 2003. ArcGIS9: Using 

ArcGIS Geostatistical Analyst. Redlands, CA: Environmental Systems Research 

Institute. 300 p.

Kjønaas, O.J. 1999a. Factors affecting stability and efficiency of ion exchange 

resins in studies of soil nitrogen transformation. Communications in Soil Science 

and Plant Analysis. 30: 2377–2397.

Kjønaas, O.J. 1999b. In situ efficiency of ion exchange resins in studies of nitrogen 

transformation. Soil Science Society of America Journal. 63: 399–409.

Klopatek, J.M.; Barry, M.J.; Johnson, D.W. 2006. Potential canopy interception 

of nitrogen in the Pacific Northwest, USA. Forest Ecology and Management.

234: 344–354.

Köhler, S.; Jungkunst, H.F.; Gutzler, C.; Herrera, R.; Gerold, G. 2012.

Atmospheric ionic deposition in tropical sites of central Sulawesi determined 

by ion exchange resin collectors and bulk water collector. Water, Air and Soil 

Pollution. 223: 4485–4494.
77

Koutrakis, P.; Wolfson, J.M.; Bunyaviroch, A.; Froehlich, S.E.; Hirano, K.; 

Mulik, J.D. 1993. Measurement of ambient ozone using a nitrite-coated filter. 

Analytical Chemistry. 65: 209–214.

Koutrakis, P.; Wolfson, J.M.; Slater, J.L.; Brauer, M.; Spengler, J.D.; Stevens, 

R.K. 1988. Evaluation of an annular denuder/filter pack system to collect acidic 

aerosols and gases. Environmental Science and Technology. 22: 1463–1468.

Krupa, S.; Nosal, M.; Ferdinand, J.A.; Stevenson, R.E.; Skelly, J.M. 2003.

A multi-variate statistical model integrating passive sampler and meteorology 

data to predict the frequency distributions of hourly ambient ozone (O ) 3

concentrations. Environmental Pollution. 124: 173–178.

Krupa, S.V.; Legge, A.H. 2000. Passive sampling of ambient, gaseous air 

pollutants: an assessment from an ecological perspective. Environmental 

Pollution. 107: 31–45.

Lawrence, G.B.; Fernandez, I.J. 1993. A reassessment of areal variability of 

throughfall deposition measurements. Ecological Applications. 3: 473–480.

Lindberg, S.E.; Lovett, G.M. 1992. Deposition and forest canopy interactions 

of airborne sulfur—results from the Integrated Forest Study. Atmospheric 

Environment. 26: 1477–1492.

Lovett, G.M.; Lindberg, S.E. 1993. Atmospheric deposition and canopy 

interactions of nitrogen in forests. Canadian Journal of Forest Research. 23: 

1603–1616.

Mamo, M.; Ginting, D.; Renken, R.; Eghball, B. 2004. Stability of ion exchange 

resin under freeze-thaw or dry-wet environment. Soil Science Society of 

America Journal. 68: 677–681. 

Miller, P.R.; McBride, J.R. 1999. Oxidant air pollution impacts in the montane 

forests of southern California: a case study of the San Bernardino Mountains. 

Ecological Studies 134. New York: Springer-Verlag

Musselman, R.C.; Korfmacher, J.L. 2014. Ozone in remote areas of the southern 

Rocky Mountains. Atmospheric Environment. 82: 383–390.

Nanus, L.; Williams, M.W.; Campbell, D.H.; Elliott, E.M.; Kendall, C. 2008.

Evaluating regional patterns in nitrate sources to watersheds in national parks 

of the Rocky Mountains using nitrate isotopes. Environmental Science and 

Technology. 42: 6487–6493.
78

GENERAL TECHNICAL REPORT PSW-GTR-257

Ogawa & Co., USA, Inc. 2006. NO, NO , NOx and SO sampling protocol using 2 2

the Ogawa Sampler. 6th ed. Pompano Beach, FL. 30 p. http://ogawausa.com/wpcontent/uploads/2014/04/prono-noxno2so206.pdf. (14 November 2016).

Pardo, L.H.; Robin-Abbott, M.J.; Driscoll, C.T., eds. 2011. Assessment of 

nitrogen deposition effects and empirical critical loads of nitrogen for ecoregions 

of the United States. Gen. Tech. Rep. NRS-80. Newtown Square, PA: U.S. 

Department of Agriculture, Forest Service, Northern Research Station. 291 p.

Parker, G.G. 1983. Throughfall and stemflow in the forest nutrient cycle. Advances 

in Ecological Research. 13: 57–133.

Proemse, B.C.; Mayer, B.; Fenn, M.E. 2012. Tracing industrial sulfur emissions 

in atmospheric sulfate deposition in the Athabasca oil sands region, Alberta, 

Canada. Applied Geochemistry. 27: 2425–2434.

Proemse, B.C.; Mayer, B.; Fenn, M.E.; Ross, C.S. 2013. A multi-isotope 

approach for assessing industrial contributions to atmospheric nitrogen 

deposition in the Athabasca oil sands region in Alberta, Canada. Environmental 

Pollution. 182: 80–91. 

Puchalski, M.A.; Sather, M.E.; Walker, J.T.; Lehmann, C.M.B.; Gay, D.A.; 

Mathew, J.; Robarge, W.P. 2011. Passive ammonia monitoring in the United 

States: comparing three different sampling devices. Journal of Environmental 

Monitoring. 13: 3156–3167.

Roadman, M.J.; Scudlark, J.R.; Meisinger, J.J.; Ullman, W.J. 2003.

Validation of Ogawa passive samplers for the determinations of gaseous 

ammonia concentrations in agricultural settings. Atmospheric Environment. 

37: 2317–2325.

Roman, P.; Polkowska, Z.; Namiesnik, J. 2013. Sampling procedures in studies 

of cloud water composition: a review. Critical Reviews in Environmental Science 

and Technology. 43: 1517–1555.

Root, H.T.; Geiser, L.H.; Fenn, M.E.; Jovan, S.; Hutten, M.A.; Ahuja, S.; 

Dillman, K.; Schirokauer, D.; Berryman, S.; McMurray, J.A. 2013. A simple 

tool for estimating throughfall nitrogen deposition in forests of western North 

America using lichens. Forest Ecology and Management. 306: 1–8.

Schwede, D.B.; Lear, G.G. 2014. A novel hybrid approach for estimating total 

deposition in the United States. Atmospheric Environment. 92: 207–220.
79

Simkin, S.M.; Lewis, D.N.; Weathers, K.C.; Lovett, G.M.; Schwarz, K. 2004.

Determination of sulfate, nitrate, and chloride in throughfall using ion-exchange 

resins. Water, Air, and Soil Pollution. 153: 343–354.

Smil, V. 2001. Enriching the Earth: Fritz Haber, Carl Bosch, and the transformation of world food production. Cambridge, MA: The MIT Press. 338 p. 

Sparks, J.P.; Walker, J.; Turnipseed, A.; Guenther, A. 2008. Dry nitrogen 

deposition estimates over a forest experiencing free air CO enrichment. Global 2

Change Biology. 14: 768–781.

Templer, P.H.; Weathers, K.C. 2011. Use of mixed ion exchange resin and 

the denitrifier method to determine isotopic values of nitrate in atmospheric 

deposition and canopy throughfall. Atmospheric Environment. 45: 2017–2020. 

Templer, P.H.; Weathers, K.C.; Ewing, H.A.; Dawson, T.E.; Mambelli, S.; 

Lindsey, A.M.; Webb, J.; Boukili, V.K.; Firestone, M.K. 2015. Fog as a 

source of nitrogen for redwood trees: evidence from fluxes and stable isotopes. 

Journal of Ecology. 103: 1397–1407.

Thimonier, A. 1998. Measurement of atmospheric deposition under forest 

canopies: some recommendations for equipment and sampling design. 

Environmental Monitoring and Assessment. 52: 353–387.

Tonnesen, G.; Wang, Z.; Omary, M.; Chien, C.-J. 2007. Assessment of nitrogen 

deposition: modeling and habitat assessment. CEC-500-2006-032. Sacramento, 

CA: California Energy Commission, Public Interest Energy Research (PIER) 

Energy-Related Environmental Research. 

Waldman,	J.M.;	Munger,	J.W.;	Jacob,	D.J.;	Hoffmann,	M.R.	1985. Chemical 

characterization of stratus cloudwater and its role as a vector for pollutant 

deposition in a Los Angeles pine forest. Tellus. 37B: 91–108.

Wasiuta, V.; Lafrenière, M.J.; Norman, A.L. 2015. Atmospheric deposition of 

sulfur and inorganic nitrogen in the Southern Canadian Rocky Mountains from 

seasonal snowpacks and bulk summer precipitation. Journal of Hydrology. 523: 

563–573.

Watmough,	S.A.;	Whitfield,	C.J.;	Fenn,	M.E.	2014. The importance of 

atmospheric base cation deposition for preventing soil acidification in the 

Athabasca Oil Sands Region of Canada. Science of the Total Environment. 

493: 1–11.
80

GENERAL TECHNICAL REPORT PSW-GTR-257

Weathers, K.C.; Simkin, S.M.; Lovett, G.M.; Lindberg, S.E. 2006. Empirical 

modeling of atmospheric deposition in mountainous landscapes. Ecological 

Applications. 16: 1590–1607.

Yamashita, N.; Sase, H.; Kobayashi, R.; Leong, K. P.; Hanapi, J.M.; Uchiyama, 

S.; Urban, S.; Toh, Y.Y.; Muhamad, M.; Gidiman, J.; Chappell, N.A. 2014.

Atmospheric deposition versus rock weathering in the control of streamwater 

chemistry in a tropical rain forest catchment in Malaysian Borneo. Journal of 

Tropical Ecology. 30: 481–492.
81

Glossary

atmospheric deposition―The transfer of air pollutants from the atmosphere to the 

Earth’s surface. Atmospheric deposition occurs in both wet and dry forms.

bulk deposition―Wet-deposited atmospheric deposition collected by a sampler 

that is continuously exposed to the atmosphere resulting in unquantified, but generally low, levels of dry-deposited pollutants accumulating on the collector; thus the 

sample collected is generally primarily wet deposition plus some amount of drydeposited material. Bulk deposition collectors can be deployed under vegetation to 

collect bulk throughfall or in open areas. In the latter case, samples collected during 

precipitation events are specifically referred to as bulk deposition. 

critical level―The concentration, cumulative exposure, or cumulative stomatal 

flux of atmospheric pollutants above which direct adverse effects on sensitive 

vegetation may occur according to present knowledge. 

critical load―The quantitative estimate of a deposition input or exposure to one 

or more pollutants below which significant harmful effects on specified sensitive 

elements of the environment do not occur according to present knowledge.

dissolved inorganic nitrogen (DIN) deposition―Atmospheric deposition of 

inorganic N deposition in solution, either as throughfall under vegetation canopies 

or as precipitation in open areas. DIN is the sum of the two inorganic ions nitrate 

(NO -

) and ammonium (NH +). 3 4

dissolved organic nitrogen (DON) deposition―Atmospheric deposition of 

organic forms of N in solution, either as throughfall under vegetation canopies or as 

precipitation in open areas. DON consists of the sum of organic N compounds that 

can occur in precipitation or throughfall (i.e., peptides, free amino acids, urea, etc.). 

Although DON is generally considered to be an important component of atmospheric deposition, it is not routinely measured in monitoring networks or studies.

dry deposition―Atmospherically deposited pollutants or compounds that are 

deposited to plant, soil, litter, water or geologic surfaces in dry forms, which can 

include gaseous or particulate pollutants.

net	throughfall―An estimate of dry + cloud/fog deposition; calculated as throughfall deposition (of nitrogen [N], for example), minus wet N deposition (that in 

precipitation).
82

GENERAL TECHNICAL REPORT PSW-GTR-257

occult deposition―Refers to deposition occuring as mist, cloud water, or fog water. 

Precipitation samplers collect very little occult deposition. Cloud water or fog is 

normally collected on string collectors as the liquid collected on the strings drips 

into a recipient.

throughfall deposition―Hydrologic flux to the forest floor of ions and other 

compounds contained within the throughfall solution.

total N deposition―The sum of atmospheric nitrogen (N) deposition, including all 

major N pollutants being deposited in both wet and dry forms.

wet deposition―Atmospheric deposition occurring in wet forms; or in other words, 

as precipitation, most commonly as rain or snow. 
83

Appendix 1: Laboratory and Field

Standard Operating Procedures for 

Passive Monitoring of Gaseous Pollutants

General Requirements

Passive samplers and filters (collecting media) should be handled in a dedicated 

clean laboratory room equipped with a clean-air chamber. The working surfaces 

of laboratory benches and inside of the clean-air chamber are to be covered with a 

clean sheet of laboratory paper or clean laboratory tissue. Use powder-free laboratory gloves for loading, installing, removing, and unloading the samplers. Handle 

filters only with tweezers. Tweezers should be rinsed with deionized, distilled, or 

preferably, Nanopure water and dried with disposable laboratory wipes.

For field convenience, we put all the containers and bags for a monitoring site 

in one large zip bag labeled with the site name. Record the site name, pollutant, and 

date/time of sampler changeout. We include a small form in each sampler jar or bag 

for this. Note: any problems with the samplers during their installation, exposure, or 

removal (e.g., samplers found on the ground, samplers wet or dirty, perforated ends 

of Ogawa samplers were touched, nitric acid (HNO ) filter was touched or dam- 3

aged, missing samplers, insect activity) should be recorded on the data form. Short 

comments about field weather conditions (smoke, clear air, rain) can also be helpful.

Containers and procedures used to transport samplers and travel blanks to and 

from field sites should be carefully monitored for possible contamination. Travel 

blanks should be incorporated into monitoring plans to account for background 

levels and blank correction and to detect potential contamination problems during transit. For example, Puchalski et al. (2011) reported that the plastic vials used 

to transport ammonia (NH ) samplers in their study emitted NH during warm 3 3

weather, leading them to switch to glass vials and Teflon-lined lids. All containers, 

surfaces, and supplies used should be evaluated as potential contamination sources. 

During all phases of preparing, deploying, transporting, and processing the passive 

samplers, use extreme care to prevent contamination of the samplers.
84

GENERAL TECHNICAL REPORT PSW-GTR-257

Remark: In the event of rain, avoid any contact of the samplers with moisture.

Construction of Stand and Shelters

Items needed:

1. Aluminum sheet

2. Solid PVC (polyvinyl chloride) 7/8-in (2.2-cm) rod 

3. 3-in (7.6-cm) PVC pipe end caps

4. 4-oz (125-ml) 70-mm polypropylene jar (Fisher 02-891C)

5. Hook-and-loop material (self-adhesive)

6. Fence post

7. 2- by 2-in (5.1- by 5.1-cm) wood post at least 8 ft (20.3 cm) long

8. Double 90-degree brackets (USP TTB22-TZ/ SIMPSON STRONGTIE 

RTB22)

9. Hose clamps 

10. Ogawa shelters

11. HNO (nitric acid) protective caps 3

12. Remark: all outside parts of the sampler shelters and stand may be painted 

to make it less visible while in the field. Avoid getting paint on the inside 

of the shelters, and allow the paint to thoroughly dry before installing 

samplers.

Passive sampler stand— 

Passive sampler stand consists of one fence post, one 8-ft 2- by 2-in wood post and 

two 2- by 2-in wood cross arms. Fasten the 8-ft 2- by 2-in (20.3 cm 5.1- by 5.1-cm) 

wooden post to the fence post with hose clamps. The cross arms are fastened to the 

post using two double 90-degree brackets (see figure A1.1).

Cross-Arm Construction

Cut two pieces of 2- by 2-in (5.08- by 5.08-cm) wood posts, each 30 in (76.2 cm) long. 

Drill four 15/16-in (2.38-cm) holes, 1 in (2.54 cm) deep at interval shown 

in figure A1.2.

Drill a second small hole, perpendicular to the large hole for the small screw 

to hold shelter knob in place (fig. A1.3). This will provide a total of eight holes for 

installing sampler shelters in the two cross arms.

Ogawa sampler shelter and support bracket 

The shelter and bracket can be purchased from Ogawa or constructed from inexpensive materials. Cut a 1-in piece of 7/8-in (0.88-cm) solid PVC rod. Drill a pilot hole 

through the center of the rod. Drill a pilot hole through the top of a 3-in (7.62-cm) 
85

eicvret SseroA FDS, Uzicworentyj Bezrdns Aotohh ptoB

Figure A1.1—Sampler stand and crossarms.
86

GENERAL TECHNICAL REPORT PSW-GTR-257

A 

eic

DS, U

vre

g

t S

n

s

i

e

l

r

li

o

h

F

cn SasuS

Figure A1.2—Diagram of holes to be drilled in 2- by 2-in crossarm.

eicvret SseroA FDSU

Figure A1.3—Drilling set-screw hole.

PVC end cap. Screw the rod to the top of the cap on the outside (fig. A1.4). Optionally, sanding the cap top flat and gluing the rod piece will help secure the knob. 

For the support bracket, cut a 0.5- x 7-in (1.27- x 17.78-cm) strip from a piece of 

aluminum sheet. Carefully file sharp edges and corners. Bend strip into shape as in 

fig. A1.5. It should fit snugly on the PVC cap (fig A1.6). To hang the shelter, insert 

rod piece (knob) into any of the large holes in the crossarm and fasten with a set 

screw from the side (fig. A1.7).
87

eicvret SseroA FDSU

Figure A1.4—Ogawa shelter with knob attached. 

eicvret SseroA FDSU

Figure A1.5—Shelter bracket (left) and sampler clip (right). 
88

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS, Ugnillihcn SasuS

Figure A1.6—Ogawa shelter with bracket.

noitah StcraeseW RS, Peicvret SseroA FDSU

Figure A1.7—Ogawa shelter (right) and nitric acid protective cap (left) mounted on crossarm. 
89

HNO3 Protective Cap 

The schematic of an HNO sampler is shown in figure A1.8. Mark a line 10 mm 3

below the threads of a 4-oz (125-ml) polypropylene jar. Cut the bottom of jar off at 

this line. The jar top without cap should measure 22 mm in height (fig. A1.9). The 

jar bottom can be discarded. 

Cut a 1 inch piece of the PVC solid rod and drill a pilot hole in center. Screw 

the rod to outside of jar lid to form a knob (fig. A1.9). 

Apply a 1 inch piece of hook and loop material to the inside of the jar lid 

(fig. A1.9). 

To hang the shelter, insert knob into any of the large holes and fasten it with 

a set screw from the side (fig. A1.7). The jar top can be temporarily removed after 

hanging to facilitate the installation or removal of the sampler, but it should be 

installed during exposure.

Ogawa Samplers for Ozone (O3), Ammonia (NH3), 

Nitrogen Dioxide (NO2), and Nitrogen Oxides (NOx)

These are available for purchase from Ogawa USA. Typically one sampler per pollutant is deployed at each site (each sampler holds two replicate samples).

Items needed:

1. Clean-air chamber

2. Wrist-action shaker

3. 25-ml HDPE opaque (light-blocking) screw top vials for sampler storage

4. Laboratory paper or disposable laboratory paper towels for covering work 

surfaces

5. 8-ml Nalgene bottles for storage of exposed filters

6. Paper tape and pen for labeling

7. Tweezers

8. Powder-free laboratory gloves (latex or latex-free)

9. Polyethylene reclosable zip bags (small and large)

10. Ogawa passive sampler (PS-100)

a. Sampler body, screens, rings, and endcaps 

b. Precoated Ogawa filters 

c. Ogawa sampler clip

Storage of unexposed filters: 

In general, filters in Ogawa original unopened packages can be stored up to 6 

to 8 months in a freezer (-18 o

C). Two days before the expected loading of samplers, 

the filters should be moved to a refrigerator (where they can be kept up to 3 months 
90

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS, Ugnillihcn SasuS

Figure A1.8—Schematic of passive sampler, including the protective cap, for measuring 

atmospheric concentrations of nitric acid + HNO = nitrous acid. A 47-mm diameter 1-μm 2

pore-size Nylasorb nylon filter collecting HNO and HNO is held between two Teflon rings 3 2

in the base of a Millipore petri dish. Airflow is controlled by a 47-mm-diameter Zefluor 

Teflon filter of 2-μm pore-size held in place by a polyvinyl chloride ring. The passive sampler 

is attached with hook-and-loop tape inside of a cap protecting the sampler from wind and rain 

(for details of the sampler design, see Bytnerowicz et al. 2005).
91

in unopened original vials). After opening, the filters can be kept refrigerated up to 

4 to 6 weeks in tightly closed original vials placed in zip bags. Allow vials to warm 

to room temperature before opening.

Loading Filters Into Passive Samplers (Same Procedure for O3, 

NH3, NO2 and NOx):

Use only clean tweezers and never allow filter to touch any other surfaces. Clean 

the tweezers with Nanopure water and carefully dry each time before touching a 

filter. Insert Teflon disk and ring into sampler body in the order shown in figure 

A1.10. Place a filter between two stainless steel mesh screens and insert filter in 

one end of the sampler body. Close that end of the sampler body with the perforated eicvret SseroA FDS, Ugnillihcn SasuS

Figure A1.9—Upper: nitric acid protective cap after painting (hook and loop attached to inside 

center of cap is partially visible). Lower right: jar cap before painting with attached knob. Lower 

left: cut portion of the threaded jar top (ring).
92

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDS, Ugnillihcn SasuS

Figure A1.10—Schematic of an Ogawa type passive sampler. These can be used for measuring 

atmospheric concentrations of ammonia, nitrogen dioxide, nitrogen oxides, sulfur dioxide, and 

ozone, depending on which chemical reagent the cellulose filter is coated with.

Teflon endcap. Similarly load the second side of the sampler. Label the outside of 

the sampler body with the pollutant being measured using a permanent marker. 

Snap the assembled sampler into sampler clip and place it into a small zip bag. 

Close the zip bag and place it in a labeled opaque vial with a blank data form (fig. 

A1.11). Samplers are ready for deployment. Storage time of prepared samplers prior 

to deployment should be minimized to avoid possible background contamination of 

samplers.

Blank (control) filters:

As each exposure is being loaded, label and date three 8-ml Nalgene bottles. Place 

one unexposed filter in each bottle. Close the bottles tightly and place them in 

a small zip bag. Keep the blank filters at room temperature until the end of the 

exposure period.

Unloading and Storing of Exposed Filters From 

Samplers: 

After exposure in the field, samplers should be returned in sealed zip bags inside 

properly labeled opaque vials. Wearing clean laboratory gloves, open one side of the 

sampler and remove exposed filter from between the stainless steel mesh screens 

with tweezers. Place filter in an 8-ml Nalgene bottle and close tightly. Clean tweezers and repeat with the other side of the sampler. Label the Nalgene bottle with the 

site name, pollutant, and exposure start and end dates and times. Assign laboratory 

ID to the samples and log into laboratory database. Store bottles with exposed and 

blank filters in a freezer (-18 o

C) until they are to be extracted. Disassemble sampler 

and wash thoroughly before reusing.
93

eicvret SseroA FDS, Ugnillihcn SasuS

Figure A1.11—A sampler in a zip bag, data form, and opaque jar. 

Remark: The exposed samplers should be kept at room temperature before their 

disassembly (not longer than 3 days following the field exposure). Samplers should 

always be disassembled before being stored in a refrigerator or a freezer to avoid 

condensation buildup on the filters. 

Extraction and Chemical Analysis of Filters:

O —add 5 ml of Nanopure water to 8-ml Nalgene bottles containing exposed 3

filters. Shake bottles for 15 min on a wrist action shaker at level “2.” Transfer a 0.5 

ml aliquot into an ion chromatograph vial. Close the vial with a Dionex vial cap. 

Sample is ready for NO - analysis with ion chromatography. 3

Remark: Extraction of O filters can be done several days before the analyses if the 3

extracts are kept in a refrigerator prior to analysis. 

NH , NO , and NO – add 8 ml of ultrapure water to 8 ml bottles containing 3 2 x

exposed filters. Shake bottles for 15 minutes on a wrist action shaker. The filter 

extracts are analyzed colorimetrically. NH sampler extracts are analyzed for NH +

3 4

while the NO and NO sampler extracts are analyzed for NO -. 2 x 2

Remark: analyses of NH , NO , and NO extracts should be performed on the day 3 2 x

of extraction. If this is not possible, the extracts should be kept in a refrigerator and 

analyzed within 24 hours.
94

GENERAL TECHNICAL REPORT PSW-GTR-257

HNO3 Samplers

These samplers are not commercially available and must be fabricated. A machine 

shop may be able to cut the PVC and Polytetrafluoroethylene (also known as PTFE 

or Teflon) pipe into rings to the specifications in figure A1.8. Typically three 

samplers are deployed at each site to be monitored.

Items needed:

1. Adhesive-back hook-and-loop fastener material

2. 47-mm diameter petri dish (Millipore PD2004705)

3. 1 7⁄8-in O.D. (4.71-cm) × 1 1⁄2-in I.D. (3.81-cm) PTFE tube (McMaster-Carr 

part #8547K36) sliced into 1/16 in (0.16) rings

4. 1.5 in (3.81-cm) diameter Gray Sch40 PVC pipe sliced into 0.165 in (0.42-

cm) rings

5. 47-mm 1.0-μm Nylasorb nylon filters (p/n 66509)

6. 47-mm 2.0-μm Zefluor PTFE filters (p/n P5PJ047)

7. 50- or 60-mm Petri dish (Fisher 08-757-100B)

8. Laboratory paper or disposable laboratory paper towels for covering work 

surface area

9. Paper tape for labeling of vials

10. Tweezers

11. Powder-free laboratory gloves (latex or latex-free)

12. Plastic zip-lock bags (small and large) 

13. Clean-air chamber

14. Wrist-action shaker

15. 250-ml Erlenmeyer flasks

Construction of samplers: 

One 47-mm Petri dish is needed for each sampler. Peel backing from hook-and-loop 

and apply approximately 1-inch piece to outside bottom of Petri dish. Allow to set 

for at least 24 hours. Two white PTFE rings and one gray PVC ring are needed for 

each sampler. See figure A1.12.

Loading HNO3

 passive samplers: 

Working inside the clean-air chamber use tweezers to place a white PTFE ring in 

the Petri dish bottom (fig. A1.12). Using clean tweezers, place a Nylasorb nylon 

filter on the white PTFE ring in the Petri dish. Place another white PTFE ring 

over the Nylasorb nylon filter. Using tweezers, place a Zefluor PTFE filter on the 

second white PTFE ring. Place a grey PVC ring over the Zefluor filter. Cover the 

loaded sampler with Petri dish lid. Assemble two more samplers and place the three 
95

eicvret SseroA FDS, Ugnillihcn SasuS

Figure A1.12—A schematic of nitric acid sampler loading order. 

eicvret SseroA FDSU

Figure A1.13—A zip sampler bag with three nitric acid samplers.
96

GENERAL TECHNICAL REPORT PSW-GTR-257

samplers and a blank data form in a small zip bag (fig. A1.13). Samplers are ready 

for deployment and should be kept at room temperature.

Blanks (control filters): 

Each group (exposure) of field-exposed filters should have three to six blanks. Label 

and date three 60-mm-diameter petri dishes. Place one unexposed Nylasorb nylon 

filter in each petri dish bottom and cover with petri dish lid. Seal petri dishes in a 

labeled zip bag and keep at room temperature until the end of the exposure period. 

Unloading and storing exposed HNO3 filters from samplers: 

Clean tweezers after handling each filter. Working in the clean-air chamber, remove 

the grey PVC ring with tweezers. Remove and discard the top Zefluor PTFE filter. 

Remove white PTFE ring. Remove the Nylasorb nylon filter and place it in a clean 

50- or 60-mm-diameter petri dish. Label the petri dish indicating the site name and 

exposure start and end dates and times, and place it in a small zip bag. Assign a 

lab ID for each sample and record in laboratory database. Store exposed and blank 

filters together in a freezer (-18 o

C) until they are to be extracted. Disassemble 

sampler and wash thoroughly before reusing.

Extraction and chemical analysis of HNO3 filters: 

Place filter and 20 ml of Nanopure water into 250-ml acid-washed Erlenmeyer flask. 

Label the flask. Cover the flask with parafilm and shake on wrist-action shaker for 

15 minutes. Decant into 15-ml red-capped centrifuge vial. Analyze for NO -

 immedi- 3

ately or within 24 hours (if kept refrigerated) with ion chromatography.

Passive Samplers Field Installation/Removal 

Ogawa samplers installation: 

1. Remove the support bracket from the shelter cap. 

2. Wearing clean gloves, remove the sampler from its opaque vial and bag, 

handling it by the clip (fig. A1.14).

3. Clip the sampler to the bracket, making sure that it will be parallel with the 

ground (fig. A1.15). 

4. Slide the bracket back onto the protective cap. If needed, adjust the bracket 

so it fits snugly on the cap. 

5. Record installation data on the form (fig A1.11). 

6. Store the small plastic bag and the form in the opaque vial and place vial 

back in large site bag while the sampler is in field. Be sure to bring this vial 

back for sampler removal after exposure.
97

eicvret SseroA FDSU

Figure A1.14—How to hold the Ogawa sampler by the clip.

eicvret SseroA FDSU

Figure A1.15—A sampler clipped to the bracket, showing proper 

orientation.
98

GENERAL TECHNICAL REPORT PSW-GTR-257

7. Before leaving the site, check that all Ogawa samplers are positioned parallel to the ground (fig. A1.16). 

Ogawa sampler removal: 

1. Wearing clean gloves, remove the Ogawa sampler by pulling the bracket off 

the shelter cap.

2. Handling the sampler by the clip, unclip the sampler and place it in the correct small zip bag and opaque vial (same bag and vial used when sampler 

was installed). 

3. Record removal data on form and return it to the vial with the sampler.

4. Be sure to seal the zip bag before placing it in the opaque vial. Tighten the 

lid of the vial and place it in the large site bag.

eicvret SseroA FDSU

Figure A1.16—Ogawa sampler positioned correctly in the shelter. 
99

Remark: Always handle the samplers by the clip. Never touch the perforated ends 

of the sampler cylinder. 

HNO3

 sampler installation: 

1. Remove a HNO sampler from the small zip bag (fig. A1.13). 3

2. The protective cap ring may be removed to facilitate installation or removal 

of the sampler (fig. A1.17)

3. With the lid of the sampler still in place, press the sampler onto the cap, 

making sure that the hook and loop will hold the sampler in place inside of 

the cap (figs. A1.18 and A1.19). 

4. Remove the sampler lid (fig. A1.20). Repeat for the other two samplers.

5. Record install the data on the form in the sampler bag. 

6. Check that the cap ring is back in place before leaving the site.

7. Place the sampler lids and data form back into the small zip bag, making 

sure to seal it.

8. Return the small HNO sampler bag to the large site bag. 3

HNO3

 sampler removal:

1. Wearing clean gloves, remove the small HNO sampler bag containing the 3

three sampler lids and data form from the large site bag. 

2. The cap ring may be removed to facilitate removal of sampler (fig. A1.17)

3. Place a sampler lid firmly on the exposed sampler. Remove the sampler by 

pulling it down from the cap. Repeat the procedure for the two remaining 

samplers. 

Remark: the hook-and-loop connection may be hard to detach. Replace the shelter cap promptly if the hook-and-loop material comes loose while removing the 

sampler.

4. Place the closed samplers back in the small sampler bag. 

5. Record removal data on the form and return it to the sampler bag.

6. Seal and place the sampler bag in the large site bag for return to lab. 
100

GENERAL TECHNICAL REPORT PSW-GTR-257

eicvret SseroA FDSU

Figure A1.17—Ring from protective cap removed for ease of nitric acid 

sampler install/removal.

eicvret SseroA FDSU

Figure A1.18—Nitric acid sampler with hook-and-loop material.
101

eicvret SseroA FDSU

Figure A1.19—A nitric acid sampler before removal of the lid.

eicvret SseroA FDSU

Figure A1.20—A nitric acid sampler with the lid removed.
102

GENERAL TECHNICAL REPORT PSW-GTR-257

Calculations of Atmospheric Concentrations of Air 

Pollutants from Passive Samplers:

Ozone (O3)

Data needed:

a. Passive sampler exposure time (t) in (h)

b. Concentration of NO -

 in exposed filter extracts (c ) in (mg/L) 3 e

c. Concentration of NO - in blank filter extracts (c ) in (mg/L) 3 b

d. Sample dilution – 5x

e. Volume of deionized water used for extraction of a filter (v) in (L)

f. Conversion factors to transform NO -

 formation rate (μg NO -/h) into 3 3

O ambient concentrations (ppb) based on a comparison with colocated 3

passive samplers with real-time electronic ozone monitors. 

Formulas for O3 calculations:

NO3 /filter (μg) = (ce

 - cb) × v × 5 × 10 - 3

NO3

-

 formation rate (μg/h) = (NO3

-

/filter)/t

O3 ambient concentration (ppb) = NO3 formation rate × conversion factor -

Example (for sample #14.107295):

NO3

-

/filter = (0.2717 mg/L – 0.0116 mg/L) × 0.005 L × 5 × 1000 = 6.505 μg

NO3 formation rate = 6.505 μg / 120.25 h = 0.0540 μg/h -

O3 ambient concentration = 0.0540 × 571 = 30.8 ppb

Ammonia (NH3

) and nitric acid (HNO3) 

Data needed:

a. Passive sampler exposure time: (h)

b. Concentration of NH +

 or NO - in exposed filter extracts (mg/L) 4 3

c. Concentration of NH + or NO - in blank filter extracts (mg/L) 4 3

d. Volume of deionized water used for extraction of a filter (L)

e. Conversion factors to transform amount of ion extracted from passive 

sampler (μg/filter) into ambient pollutant dose (μg/m3 × h) and subsequently ambient concentration (μg/m3

) based on a comparison of passive samplers with honeycomb denuder systems. 
103

Formulas for NH3 calculations:

NH4

+

/filter (μg) = (ce - cb) × v × 103

NH4

+

 formation rate (μg/h) = (NH4

+

/filter)/t

NH3 ambient concentration (μg m-3) = NH4

+

 formation rate × conversion factor

Example (for sample #15.108998):

NH4

+

/filter = (0.1704 mg/L – 0.0000 mg/L) × 0.008 L × 103 = 1.3632 μg

NH4

+

 formation rate = 1.3632 μg / 337.83 h = 0.0040 μg/h

NH3 ambient concentration = 0.0040 × 858.79 = 3.43 μg m-3

Remark: NH ambient concentrations can also be calculated using the Ogawa & 3

Co., USA, Inc. manual “NH Sampling Protocol Using the Ogawa Sampler,” 2010, 3

Pompano Beach, FL, 9 p.

Formulas for HNO3 calculations:

NO3

-

/filter (μg) = (ce - cb) × v × 103

NO3

-

 formation rate (μg/h) = (NO3

-

/filter)/t

HNO3 ambient concentration (μg m-3) = NO3

-

 formation rate × conversion factor

Example (for sample #15.109148):

NO3

-

/filter = (0.3207 mg/L – 0.0340 mg/L) × 0.020 L × 103 = 5.734 μg

NO3

-

 formation rate = 5.734 μg / 337.83 h = 0.0170 μg/h

HNO3 ambient concentration = 0.0170 × 93.079 = 1.58 μg m-3

Remark: For more information see A. Bytnerowicz et al. (2005). 

Nitrogen oxides (NOx

), nitrogen dioxide (NO2) and nitric oxide (NO)

Data needed:

a. Passive sampler exposure time (t) in (h)

b. Concentration of NO -

 in exposed NO and NO filter extracts (c ) in 2 x 2 e

(mg/L)

c. Concentration of NO - in blank NO and NO filter extracts (c ) in 2 x 2 b

(mg/L) 

d. Volume of deionized water used for extraction of a filter (v) in (L)

e. Conversion factors we use for transforming NO - formation rate (ng 2

NO -/h) to ambient concentrations (ppb) from comparison of passive 3

samplers with colocated real-time electronic monitors are as follows: 

1.301 for NO and 1.152 for NO . However, conversion factors can vary x 2

depending on ambient conditions, and should be determined under 

conditions similar to where the passive samplers will be deployed. 
104

GENERAL TECHNICAL REPORT PSW-GTR-257

Formulas for NOx concentration calculations: 

NO2

-

/filter (ng) = (ce - cb) × v × 106 

NO2

-

 formation rate (ng/h) = (NO2

-

/filter)/t

NOx ambient concentration (ppb) = NO2

-

 formation rate (ng/h) × conversion factor 

Example (for sample #15.109098)

NO2

-

/filter = (0.1835 mg/L – 0.0362 mg/L) × 0.008 L × 106 = 1178.4 ng

NO2

-

 formation rate = 1178.4 ng / 337.83 h = 3.488 ng/h

NOx ambient concentration = 3.488 × 1.301 = 4.54 ppb

Formulas for NO2

 concentration calculations:

NO2

-

/filter (ng) = (ce - cb) × v × 106 

NO2

-

 formation rate (ng/h) = (NO2

-

/filter)/t

NO2 ambient concentration (ppb) = NO2

-

 formation rate (ng/h) x conversion factor 

Example (for sample #15.109048):

NO2

-

/filter = (0.0605 mg/L - 0.0307 mg/L) × 0.008 L × 106 = 238.4 ng

NO2

-

 formation rate = 238.4 ng / 337.83 h = 0.706 ng/h

NO2 ambient concentration = 0.706 × 1.152 = 0.813 ppb

Formula for NO concentration calculation

NO ambient concentration (cNO) = NOx ambient concentration (cNOx) – NO2

ambient concentration (cNO2)

Example for samples #15.109098 and #15.109048

NO ambient concentration = 4.538 ppb – 0.813 ppb = 3.725 ppb

Remark: NO and NO ambient concentrations can also be calculated using the x 2

Ogawa & Co., USA, Inc. manual “NO, NO , NO , and SO Sampling Protocol 2 x 2

Using the Ogawa Sampler”, 1998, Pompano Beach, FL, 30 p.
105

Appendix 2: Standard Operating Procedures 

for Measuring Atmospheric Deposition Using 

Ion Exchange Resin Collectors

Preparation of Ion Exchange Resin Columns and 

Funnel Collectors

This appendix includes descriptions of how to build the collectors and deploy them 

in the field, the processing and extraction of the resin columns after field exposure, 

laboratory analyses, and atmospheric deposition flux calculations from the raw 

data. 

The first ion exchange resin (IER) throughfall collectors we used are described 

in Fenn and Poth (2004). This collector used a 10-cm-diameter rain gauge funnel 

to collect precipitation or throughfall. In 2005, we began using a modified collector 

with a 20-cm-diameter funnel that has vertical side walls that are 10 cm in height. 

This size and type of funnel is recommended by the European International Cooperative Programme (ICP) forests monitoring program (Bleeker et al. 2003). A list 

of the parts used to build these collectors are given in table A2.1. The parts listed 

provide an example of how IER collectors can be constructed from readily available 

inexpensive hardware, in addition to analytical grade IER beads. The collectors 

can be modified using products from other suppliers and according to the needs 

of a particular study. Instructions for building IER throughfall collectors are given 

below.

Ion Exchange Resin Used in These Studies

Originally, we used Rohm and Haas AmberliteTM MB150 mixed-bed IER as 

described by Kjønaas (1999a). Mixed bed refers to the fact that the resin contains 

both anion and cation exchange resin beads. Currently, we are using Amberlite 

IRN 150 Mixed Bed IER. This resin is similar to the MB150, but of a higher grade 

(referred to as nuclear grade) or purity. The cation exchange resin in this mixed-bed 

resin is AmberliteTM IRN77, and the anion exchange resin is AmberliteTM IRN78 

resin. The cation resin is highly basic with an hydroxy ionogenic group and H+ 

(hydrogen ion) as counterion. The anion exchange resin is highly acidic with a 

quaternary amine ionogenic group and OH- (hydroxide) as counterion.

We purchase the resin in bulk quantities (generally one or two tubs; 1 ft3/tub 

[28.3 l/tub]). Other sources or brand names of mixed-bed resin can also be used. 

Regardless of what IER is used, we recommend that every new batch of resin 

should be tested in the laboratory prior to being used in the field. The lab tests 

should include an evaluation of ionic background levels of the resin for the ions to 
106

GENERAL TECHNICAL REPORT PSW-GTR-257

Table A2.1―List of components used to construct the ion exchange resin throughfall collectors described 

above (presented as an example only; other designs based on different parts also can be used)

Collector part Material Source

Snow tube N-12 Plain End Drainage Pipe 8 in I.D. ADS Pipe; www.ads-pipe.com

Funnel Wirthco Polyethylene Funnel Product #90092 Wirthco Engineering; www.wirthco.com (can 

be purchased from other suppliers also)

Funnel filter 2-in PVC round rod sliced 4 mm thick with 

honeycomb of holes

Harrington Plastics; www.harrington 

plastics.com

Coupling 1-in PVC coupling with both ends threaded Hardware or irrigation supply store

Reducer bushing 1 x .05 in; both ends threaded Hardware or irrigation supply store

connection Weld-On 600 Adhesive from IPS Corporation Irrigation supply store or contact IPS 

For distributor; www.ipscorp.com

Coupling to bushing 

connection

Teflon thread tape Hardware or irrigation supply store

Mounting posts Two 6-ft posts and one 3- or 4-ft post Hardware or agricultural supply store

Snowtube to funnel and to 

post connection

Three 10-in-diameter stainless steel hose 

clamps

Hardware or irrigation supply store

Funnel to post connection 

(no snowtube)

Two 2.75-in diameter stainless steel hose 

clamps

Hardware or irrigation supply store

Resin tube 0.5- x 8-in PVC schedule 80 riser (length 

can vary depending on vegetation type or 

deposition level expected)

Hardware or irrigation supply store

Filter fiber Polyester fish tank filter or pillowstuffing Pet store or crafts store

Ion exchange resin Rohm and Haas Amberlite IRN 1501

 mixed 

bed ion-exchange resin

Can buy in bulk from water treatment 

companies. More expensive from 

scientific suppliers.

Resin tube top cap 0.5-in threaded PVC cap Hardware or irrigation supply store

Resin tube drain cap 0.5-in by 10-32 thread adapter for 

drip irrigation

Hardware or irrigation supply store

Shade tube 1.25-in-diameter PVC pipe; length depends 

on length of resin tube it is to cover

Hardware or irrigation supply store
107

be measured, the efficiency of ion capture, and the percentage of ion recovery following extraction of the IER. Tests of ionic background levels are done by extracting IER columns that have not been preloaded with ionic solutions. Tests of IER ion 

capture and efficiency of ionic recovery are done by loading the columns with ionic 

solutions resulting in an ionic load similar to loading rates expected at field monitoring sites. Ion capture efficiency of the IER column is determined by collecting 

and analyzing ionic concentrations in the loading solution draining from the bottom 

of the column when loading the ionic solutions. 

Extraction efficiency is calculated as the percentage of the ions loaded on 

the columns that is recovered in sequential extractions. We typically load an IER 

column with 1 to 5 mg of ammonium (NH +), nitrate (NO -), or sulfate (SO 2-) in 4 3 4

100 ml of loading solution (10 to 50 mg/l concentrations applied in 100-ml volumes) 

when performing these laboratory tests. In some tests, we have used a range of 

solution loading concentrations (e.g., 5 to 300 mg/l). Percentage ionic recovery is 

determined by extracting ions from the loaded IER columns with three 200-ml 

extractions as described below. Each 200-ml aliquot is collected, weighed, and analyzed separately. We have found that the small percentage of nitrogen (N) removed 

in the third extraction is insignificant and thus normally only two extractions are 

performed for field samples. From these two extractions, 98 to 100 percent of the 

N ions on the IER are recovered and >94 percent of the SO 2- ions (Fenn and Poth 4

2004; Fenn et al. 2002; Fenn, unpublished data).

Throughfall funnel collector construction:

1. If applicable, remove any factory-installed fine mesh screen. Such screens 

are not used because they are likely to become clogged under field 

conditions.

2. If applicable, peel off any labels.

3. If applicable, cut off all tabs from the outer rim of the funnel.

4. Scuff the outside of the funnel using sandpaper if you wish to reduce the 

shiny appearance of the funnels. Wipe away any dust from the tip of the 

funnel.

5. Apply Weld-On 600 to the first 3 cm of the outside of the funnel tip. 

6. Also apply cement inside one half of the 1-in (2.54-cm) threaded coupling. 

7. Screw the coupling onto the tip of the funnel until the tip of the funnel is 

half way through the coupling. Use pliers, wrench, or vise grips if needed. 

Immediately wipe away excess cement and allow to dry for 24 hours.

8. Note: Enough cement should be applied to fill all gaps but not so much as 

to cause drips to form when connecting coupling to funnel.
108

GENERAL TECHNICAL REPORT PSW-GTR-257

9. Apply Teflon tape to 1- by 1⁄2-in (2.54- by 1.26-cm) reducer bushing 

threads.

10. Screw the bushing onto funnel coupling with pliers, a wrench, or vise grips.

11. Scrub all parts of funnel thoroughly with Liqui-Nox (or other laboratory 

soap) and water. Rinse with tap water first, followed by thorough rinsing 

with deionized water and thorough rinsing with Nanopure water. Allow to 

dry in a clean dust-free area.

12. Store double-bagged in thick plastic bags until ready for installation.

Throughfall Snow Tube Construction

1. For 1-m-long snow tubes, count 41 ridges from the end of the piece of corrugated drain pipe (ADS 8-in (20.32-cm) plain end N-12 drain pipe) and cut 

between the 41st and 42nd ridges using a reciprocating saw. Each 1-m snow 

tube should have 41 ridges. Six snow tubes can be cut from each full (6.1-

m) piece of drain pipe. Note: the use of corrugated pipe is not essential for 

the snow tubes. We used this particular corrugated pipe because it is highly 

durable and the diameter was an appropriate fit for the funnel collectors.

2. The corrugation needs to be removed at one end of the tubes so the snow 

tube can fit inside the funnel.

3. Lay the tube on the ground against a wall or other vertical surface and 

remove the corrugations with a hand grinder using coarse 24-grit sanding 

disks. 

4. Repeat step 3, removing only one corrugation ring on the other end of the 

tube (fig. A2.1). This will ensure that the top lip of the tube is thin, minimizing snow accumulation, which could fall into the collector.

5. After making all cuts, the outer surface of the tube on both ends will need 

to be deburred with a wire brush attached to a hand drill. 

6. Before a snow tube is used, it must be thoroughly washed, rinsed, and dried. 

The first step in washing is to wet the entire inside and outside of the tube. 

Next submerge (or partially submerge) in a large sink or clean garbage can 

full of warm soapy (lab soap) water. Scrub all of the inside and the cut parts 

of the snow tube very well using a long-handled brush and a sponge or rag. 

Brush and wipe all parts multiple times to ensure all residue is removed. 

After scrubbing, immediately rinse off the soap with tap water followed by a 

thorough rinsing with deionized water and with Nanopure. Dry upright with 

the funnel side down on a paper towel in a clean dust-free room.

7. When dry, wrap both ends with two thick garbage bags or sheets of plastic 

until installation.
109

Figure A2.1—Side view of the top (upper end) of a snow tube. The top outer corrugated ring has 

been ground off from the tube to provide a thinner wall at the snow tube opening.

eicvret SseroA FDS, Ualivaio DnotnA

IER tube filling procedure:

1. Take a clean empty 1⁄2- by 8-in (1.27- by 20.3-cm) resin tube and tightly 

wrap each threaded end three and four times with Teflon thread tape.

2. Wearing lab gloves, pull off a piece of polyester fiber. The piece should be 

compacted into an approximately 1.5-cm long plug to be stuffed into one 

end of the resin tube. Plug should be about 1⁄2 cm into the tube. This will be 

the bottom of the tube.

3. Take a drain cap and thread it onto the bottom end of the resin tube (hand 

tight).

4. Place the resin tube in a rack (drain cap down) with a tray underneath to 

catch drippings.

5. Insert a 300- to 400-ml capacity funnel into the top of tube.

6. Using a scoop or a 50-ml beaker, take 25 to 30 ml of IER from the resin 

container (wearing gloves). 

7. Place resin into a clean 400-ml beaker. 
110

GENERAL TECHNICAL REPORT PSW-GTR-257

8. Put 200 ml of Nanopure (distilled and deionized) water into the beaker and 

swirl or stir into a slurry. 

9. Let the resin settle and pour off the most water possible without pouring off 

the resin.

10. Repeat steps 8 and 9 two more times for a total of three rinses.

11. Put 200 ml of Nanopure into the beaker again, swirl or stir into a slurry and 

immediately pour the resin and water into the funnel.

12. Allow water to drain and remove funnel. The resin should reach to 2 cm 

from the top of the tube. 

13. If there is too much resin in a tube, use a clean spatula or scoop to remove 

some resin. Place this excess resin back into the 400-ml beaker for reuse or 

put it directly into another resin tube.

14. If there is resin backed up into the funnel, move the funnel to another tube 

or use a squirt bottle to put the resin back into the 400-ml beaker for reuse.

15. Once resin is in the tube and drained, put a slightly smaller fiber filter plug 

1 cm into the top of the tube.

16. Wipe any water or resin off the threads and screw on the cap. The top cap 

should only be threaded tightly enough so that it will not fall off.

17. The resin tube can now be removed from the rack and stored upright in a 

bucket. The bottom of the bucket should be lined with paper towels to soak 

excess water dripping from the tubes.

Multiple funnels and 400-ml beakers can be used to fill more than one tube 

at a time.

It is important to pour the resin into the tubes in a well-mixed slurry to provide 

the proper ratio of cation and anion resin from the mixed-bed exchange resin 

(fig. A2.2).

Cleaning Collectors and Preparing for Transport to 

the Field

All parts of the throughfall collectors that will come in contact with throughfall 

solutions must be thoroughly cleaned and sealed in clean bags for transport to the 

field. Parts should be initially washed with laboratory-grade detergent (i.e., sodium 

dodecyl benzene sulfonate) and tap water. Parts should then be thoroughly rinsed 

with distilled or distilled/deionized water. Allow parts to dry on a countertop lined 

with paper in a clean room. After parts dry, double-bag them in thick-walled bags for 

transport to the field. For long-distance transport, place bagged parts in cardboard 

boxes for further protection. Be certain to keep the bags sealed and intact to prevent 
111

aliav DionotnA

eicvret SseroA FDSU

Figure A2.2—Ion exchange resin (IER) column and hardware used 

to fill the columns (top). Setup for filling the columns with IER 

beads (bottom). 
112

GENERAL TECHNICAL REPORT PSW-GTR-257

contamination of the collectors during storage or transit. When bagging the collectors and during field installation, take care to not touch inner surfaces of the 

collectors. 

Field Installation of Throughfall Collectors: General 

Guidelines

See section 3.4 for more details on number of replicate samplers needed and experimental designs for placement of the collectors in the field. In areas where much of 

the winter precipitation occurs as snow, snow tubes, typically 0.3 to 1.0 m in length 

depending on amount of winter precipitation expected, are installed over the funnel 

openings prior to the first snowfall. Our default protocol is to leave IER columns in 

the field for about 6 months. So for monitoring sites where snow tubes are needed, 

a typical schedule is to install the snow tubes and a new resin column in the fall 

and then 6 months later in spring, the resin columns can be exchanged for columns 

with new resin and the snow tubes removed. The snow tubes are slightly smaller in 

diameter than the funnels, so it is important for a given set of IER columns to know 

whether a snow tube was attached to the funnel or not during the field exposure 

period. The surface area (and thus the diameter) of the collector opening must be 

known in order to calculate deposition fluxes (e.g., kg N ha-1). Note that a “shade 

tube” made of polyvinyl chloride (PVC) pipe can also be installed over the resin 

tube year-round to protect the tube from solar radiation. Field blank resin columns, 

generally one to two per site, are collocated with throughfall collectors in the field, 

extracted at the same time as the sample resin columns, and used to blank correct 

the data. 

Example of a Specific Field IER Collector Installation 

Protocol

Site selection for samplers:

1. Canvas area to choose exact locations for the 5 bulk and 12 throughfall 

samplers.

2. Locate the five bulk samplers in an open area where they will not collect 

drip from the canopy. This is usually two to three tree heights from the tallest of the nearest trees.

3. Locate the 12 throughfall samplers in adjacent forest under mature trees where 

they will collect canopy drip. Ideally two samplers will be placed under each 

of six trees. If necessary, place some samplers under individual trees. 

4. Target tree species are Pinus ponderosa (Lawson & C. Lawson) and 
113

Pseudotsuga menziesii (Mirb.) Franco. If neither is available, choose a different Pinus spp., or if no other pines are present, then choose an Abies spp. 

Put all throughfall samplers under the same tree species.

Installation of samplers:

1. Use post driver to pound in two large stakes. Place the stakes close enough 

together to suspend a snow tube or funnel between them using the large 

size (30.5-cm) hose clamp (fig. A2.3).

2. Pound in small stake at halfway point between two large stakes, off-centering slightly to leave room for white PVC pipe cover that is sometimes used 

to shade the IER column (fig. A2.3).

3. Attach the white PVC cover to the small stake using a small hose clamp, 

leaving at least 15.2 cm of ground space. If herb layer is high, leave more 

space.

4. Connect funnel to snow tube and secure with a large hose clamp.

5. If installing resin tubes, take off the top cap of the resin tube (the one with 

no drainage hole) and screw it into the coupler at the end of the funnel until 

tight. It is usually a good idea to tap the resin tube downward a few times 

on something solid so that cotton and resin beads do not fall out when 

unscrewing the top cap.

6. Hold the snow tube-funnel (or snow tube-funnel-resin tube) between stakes 

to determine height above ground when the white PVC cover is in place 

below funnel.

7. Attach the snow tube-funnel between the two large stakes using a large hose 

clamp to go around both stakes and the snow tube. Tighten the hose clamp.

8. Loop the second small hose clamp around the white PVC pipe, unfastened, 

so that it is easy to find when it is time to install the resin tubes. The second hose clamp will hold the funnel coupler to the small stake after the 

resin tube has been screwed in. If installing resin tubes, then the resin tube 

should be sitting inside the white PVC cover and the funnel coupler can be 

secured to the small stake using a small hose clamp.

9. Controls: At one of the bulk samplers and one of the forest samplers, fasten 

a white PVC cover pipe at least 15.2 cm from the ground to one of the large 

stakes. Control resin tubes will be inserted in these. Leave a second small 

hose clamp looped around the PVC cover so that the top of the control resin 

tube can be fastened just above the PVC cover to the large stake. If installing resin tubes, then, leaving the top caps on, fasten the top of the resin 

tube just below the cap to the small stake. The top caps are left on so that 

precipitation will not enter controls, and these caps should not have holes, 
114

GENERAL TECHNICAL REPORT PSW-GTR-257

,eicvret SseroA FDS, Uresiea GdnLi

Figure A2.3—Ion exchange resin collectors installed in the field, showing the 

snow tubes as mounted onto fence posts and with a bird deterrent attached.

but the control, like all the other resin tubes, will still have a bottom cap 

with a hole in it so that water may drain out. 

10. Attach bird deterrents to tops of the four bulk samplers in the open area 

(fig. A2.4). Tighten the deterrent to itself using pliers to bend the ends 

around. If necessary, create longer ends using wirecutters to snip the wire 

at the grid points. Notice that the deterrent is clipped in four places so that 

four wires can be bent slightly and placed on the inside of the snow tube, 

most of the deterrent is attached to the outside of the snow tube, or, if there 

is no snow tube, to the funnel. Secure the bottom of the deterrent to the 

snow tube or funnel using three large white plastic ties joined together into 

one long tie; pull tight and trim (fig. A2.4).
115

eicvret SseroA FDS, Uresiea GdnLi

Figure A2.4—Closeup side view of a bird deterrent attached to a snow tube. Note that this bird 

deterrent is different than the bird sitting ring shown in figures 3.7 and 3.20. 

Collection of IER Columns at the end of the Field 

Exposure

At the end of the field exposure period, each IER column is unscrewed from the 

throughfall collector assembly and the top of the resin tube is capped off with a 

PVC cap. Do not remove the polyester fiber material that is on top of the IER beads. 

This will be done later in the laboratory prior to extraction. The IER columns are 

then transported or shipped to the laboratory for extraction. If throughfall monitoring is to be continued, after the IER columns have been removed, clear the funnels 

of accumulated litter. Any obvious contamination (e.g., bird droppings, etc.) should 

be cleaned with distilled water and tissue paper. Newly filled IER columns can 

then be attached to the collector funnels. The clean polyester fiber material located 

above the IER beads is to be left in place to protect the IER from contaminants 

during the field exposure. In many instances, snow tubes will need to be removed 

(for snow-free periods) or added for winter monitoring at the same time that the IER 

tubes are exchanged. However, in some remote sites, the snow tubes may be left on 

year-round. However, they will need to be loosened and raised up enough to inspect 
116

GENERAL TECHNICAL REPORT PSW-GTR-257

and clean the funnel periodically. Typically, this is done when exchanging the resin 

columns.

Field notes should also be made of any unusual observations, documenting such 

things as dates when the resin tubes were installed and dates when the tubes were 

removed, whether snow tubes were installed or not, observations of animal disturbance of the collectors, contamination, missing or damaged collectors, etc. Please 

send a copy (preferably electronically) of these notes to the principal investigator.
117

EXAMPLE OF A FIELD INSTALLATION DATA CARD

Site Name (< 8 letters) ________________ Date(s) __________________________

Installers (write full names) _____________________________________________

Were snow tubes installed? (circle one) YES / NO

Location description __________________________________________________

_________________________________________________________________

_________________________________________________________________

GPS coordinates of site center (mapping datum NAD27, record in DD.DDDDo)

Bulk samplers Latitude __________, Longitude __________

Throughfall samplers Latitude __________, Longitude __________

GPS elevation (m) ________________ GPS mapping accuracy (m) _________

Topo map elevation (m) _________

Throughfall sampler tree species (choose Douglas fir or ponderosa pine, if these are not 

available choose a different pine or a true fir) ________________________________

Habitat descripton ___________________________________________________

_________________________________________________________________

_________________________________________________________________

_________________________________________________________________

Actions taken while on site _____________________________________________

_________________________________________________________________

_________________________________________________________________

_________________________________________________________________

Deviations from standard operating procedure _______________________________

_________________________________________________________________

_________________________________________________________________

_________________________________________________________________

Special notes about samplers or relocation of samplers __________________________

_________________________________________________________________

_________________________________________________________________

_________________________________________________________________

Other notes ________________________________________________________

_________________________________________________________________

_________________________________________________________________

_________________________________________________________________
118

GENERAL TECHNICAL REPORT PSW-GTR-257

Notes on IER Column Extraction Procedures

The IER beads can also be extracted by removing the resin from the column and 

placing the resin and extractant in a beaker and agitating on a shaker, but for routine 

analyses, we extract the resin within the column. Percolating the extractant through 

the resin column is reportedly more efficient than batch extractions on a shaker 

(Kjønaas 1999b). Note that with some IER sources or batches, the extractant sample 

is very acidic (e.g., less than pH 3) after passing through the resin column. In our 

experience, for the colorimetric analysis of NO -, the pH of the extractant sample 3

should be 3.0 or higher. When the samples are below pH 3, prior to analyzing the 

sample, six to eight drops of 6M potassium hydroxide (KOH) are added to 60 to 

85 ml of extractant to increase the pH. However, when analyzing NO -

 with ion 3

chromatography, which is our routine method for NO -, pH of the extract is not 3

an issue. 

Extractants Used for Analysis of NO -, NH + 2-

3 4 , SO4

and PO 3-

4 (Phosphate)

Previously, we used potassium chloride (KCl) (2 N) for NO - and NH + extraction, 3 4

followed by colorimetric analysis with an autoanalyzer. In the case of SO 2-, the 4

IER columns are extracted with 1N KI, followed by analysis with ion chromatography. In this case, NO -

 is also analyzed by ion chromatography in the same analyti- 3

cal run as SO 2-, but NH + in KI extracts are analyzed colorimetrically. When 4 4

SO 2- analysis is needed, KI is used as the extractant instead of KCl because the 4

chloride peaks from the KCl solution overwhelm the analysis on the ion chromatograph. In this case, we also analyze the KI extracts for PO 3- along with NO -

 and 4 3

SO 2- using ion chromatography. As mentioned in this report, PO 3- analysis is for 4 4

detection of potential contamination, particularly from bird droppings. The latter is 

more common for field samplers located in clearings. 

KI extractions can be successfully ran on an ion chromatograph after a 1:10 

dilution, but run times per sample are long (about 30 minutes per sample in our lab). 
119

Because of the greater run times and cost, 2N KCl can be used as the extractant if 

only NO - and NH + are being monitored. Potassium iodide is more expensive than 3 4

KCl and two separate instruments are needed for the analysis. We do not analyze 

for NH + in KI extracts using ion chromatography, because the K+ peak is very 4

large and overwhelms the NH + peak. Furthermore, if open-site samples are being 4

analyzed, it is very useful to also analyze for PO 3- with ion chromatography. 4

KCl Resin Extraction Procedure for Analysis of NO -

3

and NH +

4

Note: The instructions below assume that a black drain cap reducer (with a 10-32 

thread (0.8-cm) drain hole) was installed at the bottom of the resin tube when 

filling the tube with resin (prior to field deployment). If, however, the bottom of 

the resin tube was instead fitted with a PVC cap into which a hole was drilled or 

slits were cut for drainage, then this cap will need to be removed in the laboratory and replaced with a black drain cap threaded reducer so that a drip valve can 

be attached. In this case, we replace the drain cap with a PVC drain cap reducer 

to which the petcock or thread valve is permanently sealed to the drain cap with 

silicone. This avoids breakage and is also useful because often Teflon thread tape 

used to attach the valve to the drain cap does not completely prevent leakage. 

However, caution must be exercised in removing the original bottom cap from the 

tube because resin beads may spill out; therefore, the resin tube should be held over 

a large clean disposable weigh boat container (or similar container) while removing 

the bottom cap (one with a drain hole or slits). After the cap is removed, make sure 

the polyester floss plug is in place before screwing a black drain reducer cap to the 

bottom of the tube. If any resin beads spilled into the weigh boat, remove the top 

cap of the resin tube, discard fiber filter using tweezers and pour the spilled resin 

back into the tube. Proceed beginning with step 2 below.

1. If loose, hand tighten black drain cap on the bottom of the resin tube. If the 

drain hole is dirty, clean it with moistened laboratory tissue paper.

2. Using labelling tape, place two labels on each tube with lab identification. 

Record this information into the lab book along with all field information. 

Place 1.3-cm-width Teflon thread tape on one end of drip valve and carefully thread the valve into the resin tube drain hole. Note: the valve tip will 

break if over-tightened.

3. Remove the top cap over the large clean disposable weigh boat container 

and discard the fiber filter using tweezers. If needed, place Teflon tape on 
120

GENERAL TECHNICAL REPORT PSW-GTR-257

the threads and thread on a white reservoir (fig. A2.5). Be sure to tighten 

both ends and make sure the valve is in the closed position.

4. Place all columns vertically in a rack. (We use a wrist action shaker to hold 

the tubes in place during the extraction procedure). Then place a plastic 

tray under the resin tubes (fig. A2.6).

5. Pour 100 ml of Nanopure (deionized/distilled) water in the reservoir and 

wait 20 minutes. While waiting, inspect all threaded joints for leakage. If 

leakage occurs, tighten and wipe with a paper towel. If leakage continues, 

reapply thread tape after step 7.

6. Open valve slightly so that the drip rate is about two drops/second. Let the 

column drip like this for 10 minutes. 

7. Then open the valve wide to let the remainder of the water out of the column. Allow 5 minutes for complete drainage. 

8. Repeat steps 5 through 7. Using a handheld air pump with rubber stopper, make a seal on top of the reservoir and pump out the remaining water. 

Remove tray and discard water.

9. Remove one of the tape labels with the lab ID# and transfer it to a 250-ml 

sample bottle for each resin tube (preweigh bottles without caps or label 

and write the weight on the bottle). Place a bottle under the corresponding 

resin tube (fig. A2.7).

10. Make sure the valve is closed and place 100 ml of 2N KCl solution in reservoir and wait 20 minutes.

11. Open valve slightly so that the drip rate is about two drops/second. Let the 

column drip like this for 10 minutes.

12. Then open the valve wide to let the remainder of the 2N KCl solution out of 

the column. Allow 5 minutes for complete drainage.

13. Repeat steps 10 to 12 once again and pump the remaining solution out. The 

total volume should be approximately 200 ml in each bottle.

14. Weigh bottles without caps and labels. Record weight of bottle/solution and 

record the weight of the empty bottle with corresponding sample ID in a 

spreadsheet.

15. Shake capped sample bottle to mix solution and decant a subsample into 

a 60-ml sample bottle with the label transferred from original bottle. The 

remaining extractant may be discarded.

16. Repeat steps 9 through 15 using new preweighed 250-ml bottles.

17. Samples can be frozen and stored if not analyzed within 48 hours. Analyze 

samples for NH +

 and NO - colorimetrically. Short-term storage (less than 4 3

48 hours) is under refrigeration.
121

,eicvret SseroA FDS, Ualivaio DnotnA

Figure A2.5—Hardware and supplies used to extract the ion exchange resin columns. eicvret SseroA FDS, Ualoidnz ViirtaeB

Figure A2.6—Setup for extracting the ion 

exchange resin (IER) columns. Tray under the 

IER columns is used to collect Nanopure water 

during the prerinse step, prior to extraction.
122

GENERAL TECHNICAL REPORT PSW-GTR-257

Notes:

Each resin tube will result in two, 200-ml samples. Each will be analyzed 

separately.

In initial tests, three 200-ml extractions are done to estimate the percentage of 

yield of the first two extractions.

Ammonium Acetate Resin Extraction Procedure for 

Analysis of Base Cations (Ca2+, Mg2+, K+, Na+ [calcium, 

magnesium, potassium, sodium]) 

The extraction procedure for base cations is the same as for KCl extraction except 

that 1N ammonium acetate (NH C H O ) is used as the extractant. Extraction with 4 2 3 2

ammonium acetate can be done under a fume hood because of the odor given off 

from the ammonium acetate during the IER extraction. Analysis of the extracted 

cations can then be analyzed with inductively coupled plasma atomic emission 

spectroscopy, atomic absorption spectroscopy or any analytical method appropriate 

for metals. 

KI Resin Extraction Procedure for Analysis of NO -

3 , 

NH +

4 , SO 2-4 , PO 3-4 , and Cl-

.

Note: See the above Introductory Note and steps. Procedures are the same except 

for the extracting solution and sample volumes.

1. If loose, hand tighten the black drain cap on the bottom of the resin tube. If 

the drain hole is dirty, clean it with moistened laboratory tissue paper.

2. Using labelling tape, place two labels on each tube with lab identification. 

Record this information into the lab book along with all field information. 

If necessary, place 1.3-cm width Teflon thread tape on one end of the drip 

valve and carefully thread valve into the resin tube drain hole. Note: The 

valve tip will break if over-tightened. Alternatively, we now use a PVC 

drain cap reducer that threads on to the bottom of the column and to which 

the petcock or thread valve is permanently sealed with silicone. This avoids 

breakage and is also useful because often the Teflon thread tape does not 

completely prevent leakage.

3. Remove the top cap a over large clean disposable weigh boat container and 

discard fiber filter using tweezers. If needed, place Teflon tape on threads 

and thread on white reservoir (fig. A2.5). Be sure to tighten both ends and 

make sure the valve is in the closed position.
123

eicvret SseroA FDS, Ualivao DinotnA

Figure A2.7—Setup for extracting the ion exchange resin columns. 
124

GENERAL TECHNICAL REPORT PSW-GTR-257

4. Place all columns vertically in a rack. (We use a wrist action shaker to hold 

the tubes in place during the extraction procedure). Then place a plastic 

tray under the resin tubes (fig. A2.6).

5. Pour 100 ml of Nanopure (deionized/distilled) water in the reservoir and 

wait 20 minutes. While waiting inspect all threaded joints for leakage. If 

leakage occurs, tighten and wipe with a paper towel. If leakage continues, 

reapply thread tape after step 7.

6. Open valve slightly so that the drip rate is about two drops/second. Let the 

column drip like this for 10 minutes. 

7. Then open the valve wide to let the remainder of the water out of the column. Allow 5 minutes for complete drainage. 

8. Repeat steps 5 through 7 and then pump the remaining liquid out using a 

handheld air pump. Remove the tray and discard water.

9. Remove one of the tape labels with the lab ID# and transfer it to a 250-ml 

sample bottle for each resin tube (preweigh bottles without caps or label 

and write the weight on the bottle). Place the bottle the under corresponding 

resin tube (fig. A2.7).

10. Make sure the valve is closed and place 75-ml of 1N KI solution in reservoir and wait 20 minutes.

11. Open the valve slightly so that the drip rate is about two drops/second. Let 

the column drip like this for 10 minutes.

12. Then open the valve wide to let the remainder of the 1N KI solution out of 

the column. Allow 5 minutes for complete drainage.

13. Repeat steps 10 through 12 once again. Use the handheld air pump to push 

out the remaining solution, the total volume should be about 150 ml in each 

bottle.

14. Weigh bottles without caps and labels. Record weight of bottle/solution and 

record the weight of the empty bottle with corresponding sample ID in a 

spreadsheet.

15. Shake capped sample bottle to mix solution and decant a subsample into a 

15-ml centrifuge tube (parent vial) with the label transferred from the original bottle. The remaining extractant may be discarded.

16. Samples are diluted 1:10 with Nanopure water before analysis, by placing 1 

ml from the parent vial and 9 ml of Nanopure in a clean 15-ml centrifuge 

tube. The 1:10 diluted sample can be stored in the refrigerator to be analyzed within 48 hours. Parent vials should be stored in a freezer and thawed 
125

out whenever dilutions are made. Analyze samples for ammonium colorimetrically and for nitrate, sulfate, phosphate, or chloride using high-performance ion chromatography.

Notes:

The 1N KI extractant solution should be made up fresh daily as it is light sensitive. 

Each resin tube will result in one 150-ml sample. In initial tests, an additional 100-

ml extraction is done to estimate the percentage of yield of the first two extractions.

Calculating Deposition Fluxes

Following the extraction of the IER columns, the extractant is weighed and the 

weight of the extractant solution is converted to volume based on its specific 

density (2N KCl = 1.085 g/ml; 1N KI = 1.118 g/ml). After ionic concentrations in 

the extracts have been determined and quality assurance/quality control QA/QC 

procedures completed, the mass amount (i.e., mg) of each ion collected on a given 

column is determined as the factor of extractant volume x ionic concentration. If 

two separate extractions were done on the IER columns, each of the two extraction 

solutions for each column is analyzed separately and the ions extracted from the 

two columns are summed to calculate the total deposition to that collector. We recommend converting deposition expressed on an ion basis (i.e., NO -

, SO 2-, etc.) to 3 4

an elemental basis (i.e., NO -N, SO -S, etc.). Then if total inorganic N (also called 3 4

dissolved inorganic N or DIN) is to be reported (i.e., kg N ha-1yr

-1), this is simply 

calculated as the total of NO -N + NH -N. And total inorganic sulfur (S) deposition 3 4

is reported as SO -S. Following are the elemental percentages for four common 4

ions measured: NH + = 77.7 percent N; NO - = 22.6 percent N; SO 2- = 33.4 percent 4 3 4

S; PO 3- = 32.6 percent P. 4

The surface area of the funnel opening is then used to determine deposition 

per collector opening area (e.g., mg N m-2). It is generally recommended that the 

diameter measurement for the collector opening be taken from midpoint to midpoint of the opposite sides or walls (i.e., to add half of the rim area to the collecting 

area) of the funnel based on the assumption that droplets will splash or run into the 

funnel 50 times out of 100 (Dämmgen et al. 2005). However, this depends on the 

thickness and shape of the rim, which can influence the windspeed increase owing 

to flow distortion. Dämmgen et al. (2005) reported that in one study testing 20-cm 
126

GENERAL TECHNICAL REPORT PSW-GTR-257

polyethylene funnels used for water capture, including the full rim area (21 cm) was 

more comparable to standard ground-level rain gauges. 

Here is a sample calculation for determining atmospheric deposition to a given 

IER collector. We begin with NO - concentration data for the IER extract and our 3

final units will be kg NO -N deposition per hectare. 3

First the weight of the KI extract is converted to volume using the specific 

density of 1N KI as given above.

226.03 g × ml/1.118 g × L/1000 ml = 0.202 L of KI extract

Then, we convert the NO - concentration value to NO -N (expressed as N 3 3

content) by multiplying by the proportion of N in NO - which is 0.226. 3

211.61 mg NO3/L × 0.226 = 47.82 mg NO3-N/L

Next, we multiply the volume by the NO - concentration to determine the total 3

amount of NO - extracted from the IER column. 3

0.202 L × 47.82 mg NO3-N/L = 9.66 mg NO3-N

Lastly, we determine the deposition rate per land area, using the surface area 

of the snow tube (320.47 cm2) that was inserted into the funnel for a wintertime 

monitoring period.

9.66 mg NO3-N × kg/106mg × 1/320.47 cm2 × cm2/10-4 m

2

 × 104m

2

/ha = 

3.01 kg NO3-N ha-1

If a 6-month fall and winter exposure yields a deposition of 3.01 kg NO -N ha-1

3

and the deposition for the 6 months of the spring and summer season were 5.24 kg 

NO -N ha-1, then these two values can be summed to yield an annual deposition 3

flux of 8.25 kg NO -N ha-1 yr

-1. If annual deposition of NH -N was equal to 7.32 3 4

kg NH -N ha-1 yr

-1, the deposition of NO -N and NH -N could then be summed 4 3 4

(because both are expressed in units of N) to obtain the annual DIN flux, which in 

this case would be 15.57 kg N ha-1 yr

-1. However, the second decimal place is not 

considered significant because of uncertainty in the measurements, and the DIN 

value can be appropriately rounded to 15.6 kg N ha-1

 yr

-1.

In addition to the above calculations, for each of the extractions of fieldexposed IER columns, the data is blank-corrected using the average results from 

all the field blank IER columns. The calculated deposition fluxes should also be 

adjusted for the efficiency of extraction; that is, the percentage of each ion that is 

recovered by the extraction process. This is determined previously by loading IER 

columns with a known amount of each ion and following extraction and analysis 

determining the percentage of recovery of the loaded ions. 

Deposition flux units also include a time unit, the most common of which is an 

annual time step (e.g., kg N ha-1 

yr

-1). In our IER deposition monitoring, the default 

exposure period is about 6 months, after which the IER columns are collected 
127

and new ones installed. Deposition totals from the two exposure periods are then 

summed to arrive at annual deposition flux numbers. An additional benefit of this 

approach is that deposition values are obtained for two different seasons of the year.

In reporting deposition fluxes, it is important to accurately describe the type of 

deposition measured or calculated. If the collectors were placed in open sites, this is 

traditionally referred to as bulk deposition and is mostly wet deposition with some 

unknown amount of “bulk” dry deposition occurring to the collectors during dry 

periods. For collectors placed under trees or shrubs, this is referred to as throughfall 

and describes the flux of pollutants or nutrients to the forest floor. However, unless 

it is a closed-canopy forest, such throughfall measurements will likely overestimate 

deposition across the landscape if the landscape includes areas without significant 

canopy cover―sites where deposition will be much lower because of less receptor 

surface area to collect deposited pollutants from the atmosphere. 

When vegetation cover is incomplete or highly variable across the landscape, 

estimates of deposition to the landscape must account for the variable land cover. This 

can be done by measuring deposition in throughfall under the main vegetation types 

and in open areas, and then weighting each deposition flux proportionally based on 

the land cover types in the area. Alternatively, deposition samplers can be placed at 

predetermined spacing across transects or a grid sampling design so that deposition 

measurements give integrated deposition fluxes that account for land cover. 

Data Analysis

An initial coarse-scale evaluation of the deposition data can be made by comparing the deposition results to expected values based on previous monitoring data 

or based on the location of the site across known spatial deposition gradients. An 

important step in evaluating the results from the throughfall or bulk deposition 

monitoring is to identify outlier data, such as samples that may have been contaminated by bird droppings or other types of field disturbance. Bears or other animals 

can also disturb the samplers, although bird contamination is the most common 

problem, especially with samplers located in open areas. Field crews collecting the 

IER columns at the monitoring sites should look for any signs of disturbance in the 

field and make note of this or any other disturbances or abnormalities in the field 

notes. These observations can then be noted in the laboratory reports or data sheets 

so that when laboratory data are evaluated, unusual results may be attributed to 

possible field disturbance or contamination. 

Variability in deposition fluxes should vary relatively little among collectors 

placed in open, canopy-free areas compared to throughfall collectors that are placed 

under vegetative canopies. Canopy cover can be highly heterogenous over distances 
128

GENERAL TECHNICAL REPORT PSW-GTR-257

as small as 1 to 2 m, which can greatly affect throughfall deposition flux rates, even 

at the same monitoring site, and particularly so at more polluted sites. Thus, when 

deposition fluxes vary more than expected among replicate samplers located in 

open areas, the higher values may be contaminated. As a general guideline, when 

bulk deposition values for a given N or S ion are less than 1 kg ha-1 yr-1, values that 

are more than 20 percent higher than the lowest replicates have a high likelihood of 

being contaminated and should be excluded. For bulk deposition values greater than 

1 kg ha-1 yr

-1, values more than 10 percent higher may be considered as outliers. 

Once any outliers have been identified, the remaining replicate values can be used 

to calculate average deposition values for the site and standard errors or standard 

deviation values calculated. 

Bird droppings contain elevated levels of NH +, PO 3- and K+. However, K+

4 4 ,

analysis cannot be used for identification of bird contamination when the IER 

columns are extracted with strong K+ salts such as KCl or KI. When a given bulk 

deposition sample contains elevated NH + and PO 3-, this is strong evidence of bird 4 4

contamination. Throughfall samples usually have much higher concentrations of 

PO 3- than in bulk deposition samples because of leaching of PO 3- from the canopy 4 4

and possibly resulting from washoff of low levels of dry-deposited PO 3-. As a 4

result, PO 3- levels in throughfall samples are not a good indication of bird contami- 4

nation, except when the contamination levels are sufficiently high to cause a clear 

increase in PO 3- deposition. 4

Occasionally, a rodent, bird or other small animal gets trapped in snow tubes 

and this will result in NH + values that are many fold higher than expected, leaving 4

no doubt this is an outlier result. Often in bird-contaminated samples, NH + and 4

PO 3- are elevated, but NO - and SO 2- values appear unaffected. Nonetheless, con- 4 3 4

taminated replicates are generally excluded for all ionic deposition measurements. 

When bird contamination in a given sample is slight, it can sometimes be difficult 

to ascertain if a sample is contaminated or not. 

Fortunately, PO 3- deposition is very low in wet or bulk deposition samples. 4

Thus, if PO 3- deposition to open areas is greater than the normal background depo- 4

sition, this is a good indication of contamination from bird droppings. Background 

bulk deposition of PO -P is usually less than 0.06 to 0.1 kg PO -P ha for a 6-month 4 4

exposure, although this can vary slightly from site to site. Deposition of all ions to 

bulk deposition collectors can also show excessive variation among the replicates if 

the collectors are not placed in a sufficiently large forest clearing and blowoff from 

tree canopies during wet storms contaminates the samples. 
129

In more rare instances, other potential sources of deposition can also interfere 

with measurements of N or S deposition from anthropogenic sources. Prominent 

among these are pollen “rain,” forest fire emissions, or dust storms. These can 

be noted from observations made in the field during the monitoring period, or 

deposits of smoke, dust, or pollen may accumulate in the collectors and be observed 

at the end of the monitoring period when the IER columns are exchanged. In 

rare instances, such deposits may impede drainage through the IER columns and 

result in water accumulation in the collectors. Again, such occurrences should be 

recorded in field notes and also recorded in the laboratory data report worksheets. 

As mentioned above, it is not unusual that throughfall deposition fluxes vary 

among replicate samples, particularly when canopy cover above the throughfall 

collectors varies greatly. Such variability is generally greater in more polluted sites. 

When higher deposition is a result of higher leaf area cover above a given replicate 

sampler, this usually results in higher deposition for most or all of the ions measured. If only one ion shows increased deposition, this could possibly be a contamination or analysis error. Another useful consideration when evaluating individual 

replicate values is to see if nutrient ratios for that replicate are typical for the study 

region, and for the particular monitoring site in question. For example, if the NH -4

N:NO -N ratio is unusually high in a sample or at a site, this is further evidence of 3

bird contamination, or of contamination from some other NH + source. 4
In accordance with Federal civil rights law and U.S. Department of Agriculture 

(USDA) civil rights regulations and policies, the USDA, its Agencies, offices, and 

employees, and institutions participating in or administering USDA programs are 

prohibited from discriminating based on race, color, national origin, religion, sex, 

gender identity (including gender expression), sexual orientation, disability, age, 

marital status, family/parental status, income derived from a public assistance program, political beliefs, or reprisal or retaliation for prior civil rights activity, in any program or activity conducted or funded by USDA (not all bases apply to all programs). 

Remedies and complaint filing deadlines vary by program or incident. 

Persons with disabilities who require alternative means of communication for 

program information (e.g., Braille, large print, audiotape, American Sign Language, 

etc.) should contact the responsible Agency or USDA’s TARGET Center at (202) 

720-2600 (voice and TTY) or contact USDA through the Federal Relay Service at

(800) 877-8339. Additionally, program information may be made available in languages other than English.

To file a program discrimination complaint, complete the USDA Program Discrimination Complaint Form, AD-3027, found online at http://www.ascr.usda.gov/complaint_

filing_cust.html and at any USDA office or write a letter addressed to USDA and 

provide in the letter all of the information requested in the form. To request a copy 

of the complaint form, call (866) 632-9992. Submit your completed form or letter to 

USDA by: (1) mail: U.S. Department of Agriculture, Office of the Assistant Secretary 

for Civil Rights, 1400 Independence Avenue, SW, Washington, D.C. 20250-9410; 

(2) fax: (202) 690-7442; or (3) email: program.intake@usda.gov.

USDA is an equal opportunity provider, employer, and lender.