Impacts

Authored by: Timothy J. Sullivan

Air Pollution and Its Impacts on U.S. National Parks

Print publication date:  January  2017
Online publication date:  February  2017

Print ISBN: 9781498765176
eBook ISBN: 9781315163703
Adobe ISBN:

10.1201/9781315163703-3

 

Abstract

Air pollutants, including gases, aerosols, and deposited materials, contribute to a range of environmental stressors in the national parks. Each pollutant has the potential to cause one or more effects on sensitive receptors (Table 3.1). Effects depend on both the type and amount of pollutant and the inherent sensitivity of the receptor or ecosystem. Background information on several types of air pollution–related ecosystem stress is presented here. Table 3.1 Matrix of Environmental Stressors and Selected Effects Caused by Air Pollutants

Pollutant

Stressor

Selected Effects

Acidic deposition

Soil acidification

Decreased soil base saturation, loss of plant nutrients, increased stress to sensitive plants, and loss of sensitive terrestrial species

Surface water acidification

Decreased surface water acid neutralizing capacity and pH, increased stress to sensitive aquatic biota, and loss of sensitive aquatic species.

Nutrient N deposition

Nutrient enrichment

Eutrophication, changes in species composition, loss of biodiversity

Ground-level ozone

Plant foliage exposure to ozone

Increased stress to ozone-sensitive plants, reduced growth, foliar injury

Toxic substances

Exposure to toxic conditions

Bioaccumulation of toxic materials, neurotoxicity, reproductive effects, etc.

Atmospheric concentrations of sulfate and nitrate

Formation of haze

Visibility degradation

Hydrocarbons

Formation of ozone

Increased stress to ozone-sensitive plants

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Impacts

Air pollutants, including gases, aerosols, and deposited materials, contribute to a range of environmental stressors in the national parks. Each pollutant has the potential to cause one or more effects on sensitive receptors (Table 3.1). Effects depend on both the type and amount of pollutant and the inherent sensitivity of the receptor or ecosystem. Background information on several types of air pollution–related ecosystem stress is presented here.

Table 3.1   Matrix of Environmental Stressors and Selected Effects Caused by Air Pollutants

Pollutant

Stressor

Selected Effects

Acidic deposition

Soil acidification

Decreased soil base saturation, loss of plant nutrients, increased stress to sensitive plants, and loss of sensitive terrestrial species

Surface water acidification

Decreased surface water acid neutralizing capacity and pH, increased stress to sensitive aquatic biota, and loss of sensitive aquatic species.

Nutrient N deposition

Nutrient enrichment

Eutrophication, changes in species composition, loss of biodiversity

Ground-level ozone

Plant foliage exposure to ozone

Increased stress to ozone-sensitive plants, reduced growth, foliar injury

Toxic substances

Exposure to toxic conditions

Bioaccumulation of toxic materials, neurotoxicity, reproductive effects, etc.

Atmospheric concentrations of sulfate and nitrate

Formation of haze

Visibility degradation

Hydrocarbons

Formation of ozone

Increased stress to ozone-sensitive plants

3.1  Acidification

Atmospheric deposition of S and/or N can cause acidification of soil, soil water, lakes, and streams. Soil and freshwaters can also be naturally acidified, largely by organic acids derived from wetlands and forest soils. Ocean acidification is different in that it is controlled primarily by increased carbon dioxide concentrations in the atmosphere and carbonic acid formation. It is not discussed in this book.

In most portions of the United States that have experienced soil and freshwater acidification attributable to air pollution, such effects have mainly been due to S inputs (Driscoll et al. 1998, 2007). There are, however, some regions, especially in the western United States, where resources are more threatened or have been more affected by the acidity of N inputs than by the acidity of S inputs. This is at least partially due to the low levels of S deposition received at most western locations. There are also regions where atmospheric S and N both contribute substantially to the observed acidification. These include portions of the Northeast, West Virginia, and high elevations in North Carolina, Tennessee, and Virginia. Historically, these areas received more S than N deposition but now receive about equal amounts.

The freshwater aquatic ecosystems within the national parks that are thought to be most sensitive to the effects of acidification from atmospheric S and N deposition include remote lakes that often occur at relatively high elevation and headwater (Strahler order 1–3) streams. Acid-sensitive waters most commonly occur in areas of steep terrain, on shallow soils, having shallow flow paths, and bedrock types that provide limited contribution of base cations that could, if present, buffer incoming acidity.

The soils that are thought to be most sensitive to acidification effects include shallow soils having low base saturation*

Base saturation reflects the percent of exchangeable cations adsorbed to soil that are base cations (Ca, Mg, Na, K) rather than acid cations (H, Al).

(less than about 12%–20%). These low base saturation soils generally exhibit low weathering rates and tend to have low clay content. They are often found at high elevation and are exposed to relatively high levels of precipitation, which can leach nutrient base cations to drainage water, reducing the soil’s ability to neutralize acidity from acidic deposition.

3.1.1  Terrestrial Effects

Acidification can affect soils and vegetation by depleting soil nutrients and releasing metals toxic to plant roots. Two tree species (red spruce [Picea rubens] and sugar maple [Acer saccharum]) are known to be highly susceptible to damage from acidic deposition (U.S. EPA 2008). This damage can take the form of reduced growth, canopy dieback, reduced regeneration, increased susceptibility of foliage to cold temperature, and other symptom manifestations. Some national parks have extensive coverage of vegetation types that include one or both of these sensitive tree species. Although soil acidification effects in the United States are expected to be especially pronounced in the plant communities that include these tree species, the same kinds of effects might also occur in other vegetation types but are poorly documented in this country.

Many lichen species are known to be especially sensitive to air pollution (Figure 3.1). To some extent, they represent the “canaries in the coal mine,” or early warning signals, because lichens may be impacted by air pollution before other species. Effects seem to be more clearly associated with N inputs than with S inputs (Bobbink et al. 2003, Geiser and Neitlich 2007, Glavich and Geiser 2008). These effects may be driven by nutrient enrichment processes more than, or in addition to, acidification processes. It is also likely, however, that S air pollution has impacted the distribution of lichens, especially in the eastern United States (U.S. EPA 2008).

Lichens are among the terrestrial receptors that are most sensitive to N inputs.

Figure 3.1   Lichens are among the terrestrial receptors that are most sensitive to N inputs.

(National Park Service photo.)

The release of base cations from soil to soil water through weathering, cation exchange, and mineralization contributes to neutralization of acidity derived both from acidic deposition and from natural processes (van Breemen et al. 1983). If the acidity is associated with anions that are mobile within the soil environment, such as sulfate or nitrate, cations can be leached to groundwaters and eventually to surface waters. Some loss of base cations from soil occurs naturally from the leaching of organic and carbonic acids. The limited mobility of anions associated with naturally derived organic acids and carbonic acid controls the rate of base cation leaching under conditions of low atmospheric deposition of S and N. Because inputs of S and N in acidic deposition supply anions that are often highly mobile in the soil, these mineral acid anions can accelerate base cation leaching (Cronan et al. 1978). In addition, depletion of nutrient base cations, especially Ca, can cause damage to acid-sensitive plants and those that require high Ca levels.

In regions of the eastern United States affected by acidic deposition, the total concentration of sulfate and nitrate in soil waters and surface waters has increased from historical conditions. In response to these changes in mineral acid anion concentrations, the concentrations of other ions in surface water must also have changed so that electroneutrality is maintained (the total cationic and anionic charges are balanced). The leaching of sulfate does not directly cause adverse environmental effects. Changes in other ions are responsible for environmental impacts caused by drainage water*

Drainage water is water derived from precipitation that drains through the soil and into groundwater or stream water.

acidification. As the sulfate concentration in drainage water has increased over time in the past, other anions (mainly bicarbonate or organic acid anions) have decreased and/or cations (e.g., base cations, hydrogen ion, or inorganic monomeric Al) must have increased in solution to maintain the charge balance (the sum of the cations equals the sum of the anions). Changes in the concentrations of these ions have affected the ability of soils to support acid-sensitive plant species and other biota.

Most acidification effects on plants are mediated through the soil and are governed by Al toxicity and nutrient base cation (Ca, Mg, K) deficiencies. Nitrogen saturation can also be involved. These three factors are often closely related.

3.1.1.1  Aluminum Mobilization

The key biogeochemical process impacting freshwaters that is altered by acidic deposition is the mobilization of Al from soils to drainage waters (Cronan and Schofield 1979, Mason and Seip 1985), potentially causing toxicity to both terrestrial and aquatic organisms. Aluminum becomes more soluble at pH values below about 5.5. As a consequence, Al concentrations in drainage waters having pH below about 5.0 are often substantially higher than in waters having pH above 6.0. At high concentration in soil water, Al is toxic to plant roots and causes reduced root growth. This limits the ability of the plant to take up water and nutrients, especially Ca (Parker et al. 1989).

Red spruce trees died over large portions of the eastern United States in the 1980s. This mortality was linked to the exposure of foliage to acidic cloud water and to an increase in the amount of dissolved Al compared with dissolved Ca in soil water (U.S. EPA 2008). Some of the red spruce decline occurred at high-elevation sites that frequently experience cloud cover and often receive high levels of occult deposition.

The leaching of atmospherically deposited sulfate into soil waters, and eventually to surface waters, controls soil acidification and Al toxicity to plants at most acid-impacted areas in the northeastern United States. At such locations, much of the deposited S is leached to surface waters as sulfate. This contributes to soil and surface water acidification and Al mobilization. In contrast, much of the deposited N is commonly taken up from watershed soils by plants and microbes, reducing its acidification potential. Thus, the mobilization and toxicity of Al are largely controlled by sulfate mobility in most affected ecosystems. Nitrate mobility is also important at some locations, but the dominant mobile strong acid anion in U.S. national parks is usually sulfate.

3.1.1.2  Depletion of Base Cations from Soil

Base cations, some of which are necessary plant nutrients, are common in rocks and soils, but largely in forms that are unavailable to plants. There is also a pool of bioavailable exchangeable base cations that are adsorbed to negatively charged surfaces on soil particles. Base cations in this pool are gradually leached from the soil in drainage water but are constantly resupplied through weathering and atmospheric deposition of base cations. Weathering slowly breaks down rocks and minerals, releasing base cations to join the pool of adsorbed exchangeable base cations on the soil. The base saturation is a soil metric that reflects the percentage of the adsorbed cations that are base cations rather than acid cations. The balance between base cation supply and base cation loss determines whether the pool of available soil base cations is increasing or decreasing in size over time. Enhanced leaching of base cations by acidic deposition in some cases can deplete the soil of exchangeable bases faster than they are resupplied (Cowling and Dochinger 1980). Nutrient base cations, including Ca, Mg, and K, are taken up through plant roots from soil water to satisfy plant nutritional needs. In soils having low base saturation, exchangeable Ca, Mg, or K can be depleted so much that nutrient deficiencies develop in vegetation.

The hardwood tree species most commonly associated with acidification effects due to base cation depletion is sugar maple. It is distributed throughout the northeastern United States, Upper Midwest, and Appalachian Mountain region as a component of the northern hardwood forest. Several studies, mainly in Pennsylvania and New York, have shown that sugar maple decline is linked to the occurrence of relatively high levels of acidic deposition and base-poor soils. Decline results, in part, from Ca depletion (Horsley et al. 1999).

The health of sugar maple trees is strongly influenced by the availability of Ca and other base cations in soil. Sugar maple trees that grow on soils having low base cation supply are stressed and consequently often become more susceptible to damage from defoliating insects, drought, and extreme weather. The overall response can include canopy damage or death of mature trees and poor regeneration of seedlings (Horsley et al. 1999, Sullivan et al. 2013).

Soil acidification and depletion of soil base cations may be contributing to sugar maple mortality in some of the eastern national parks, especially on sites having marginal (low-nutrient) soils. Sugar maple dieback at 19 sites in northwestern and northcentral Pennsylvania and southwestern New York was correlated with combined stress from defoliation and soil deficiencies of Mg and Ca (Horsley et al. 1999). Dieback occurred predominately on ridgetops and on upper slopes, where soil base cation availability was much lower than on middle and lower slopes (Bailey et al. 1999). Sugar maple in the Adirondack Mountains of New York exhibited essentially no regeneration on sites having an upper B soil horizon base saturation less than about 12% (Sullivan et al. 2013). This threshold may also be applicable to other areas.

3.1.2  Aquatic Effects

Surface water acidification produces chemical changes in lakes and streams, most notably a decrease in acid neutralizing capacity, usually a decrease in pH, and often an increase in the concentration of inorganic Al in lakes and streams (Driscoll et al. 2001b). Many species of aquatic biota are sensitive to water acidification.

Acid neutralizing capacity is the most widely used water chemistry indicator for both acidic deposition sensitivity and effects. It can be measured in the laboratory by Gran titration or defined as the difference between the measured base cation and mineral acid anion concentrations in water:

3.1() Acid neutralizing capacity = ( Ca 2+ + Mg 2+ + K + + Na + +NH 4 + ) ( SO 4 2 + NO 3 + Cl )

where

  • NH4+ is ammonium
  • SO42− is sulfate
  • NO3 is nitrate
  • Cl is chloride

Surface water acid neutralizing capacity integrates the chemical, physical, and biological interactions that occur as atmospheric deposition and precipitation move from the atmosphere into or over the soil and eventually become surface water in a stream or lake. If the sum of the base cation concentrations (in equivalent units*

Equivalent units are expressed in molar terms and then multiplied by the ionic charge.

) exceeds those of the strong acid anions, the water will have positive acid neutralizing capacity. Higher acid neutralizing capacity is generally associated with higher pH and Ca concentration; lower acid neutralizing capacity is generally associated with lower pH and higher inorganic Al concentrations and a greater likelihood of toxicity to aquatic biota.

Acid neutralizing capacity values were grouped by Cosby et al. (2006) into five major classes of biological concern: acute concern (less than 0 microequivalents per liter [µeq/L]), severe concern (0–20 µeq/L), elevated concern (20–50 µeq/L), moderate concern (50–100 µeq/L), and low concern (greater than 100 µeq/L), with each range representing a probability of ecological damage to the aquatic community. Biota are generally not harmed when acid neutralizing capacity values are above 100 µeq/L (U.S. EPA 2009c). In acid-sensitive regions, many surface waters commonly have acid neutralizing capacity below 100 µeq/L, and in some cases below 50 µeq/L, even in the absence of acidic deposition. Thus, although acidic deposition is responsible for the loss of acid neutralizing capacity in many sensitive water bodies, a relatively low acid neutralizing capacity value does not necessarily indicate that human-caused acidification has occurred if the acidic deposition levels are low.

A number of factors influence the sensitivity of aquatic ecosystems to acidification in response to S and N deposition. Geologic composition of the watershed of a water body largely determines base cation availability and plays a dominant role in influencing the sensitivity of surface waters to the effects of acidic deposition. Bedrock geology formed the basis for maps of surface water sensitivity (Norton et al. 1982, Dise 1984, Bricker and Rice 1989, Sullivan et al. 2007). Most of the major concentrations of surface waters having low acid neutralizing capacity are located in areas of the United States that are underlain by bedrock resistant to weathering, with consequent low supply of base cations (U.S. EPA 2008). Soil chemistry, land use, watershed slope, and hydrologic flow path also contribute to the sensitivity of surface waters to acidic deposition. Land disturbance and consequent exposure of S-bearing minerals to oxidation,*

Oxidation of S-bearing minerals can release sulfuric acid to drainage waters.

loss of base cations through erosion and timber harvesting, and change in N status of the forest through insect infestation, disease, or timber management can all influence the relative availability of mobile mineral acid anions (sulfate, nitrate) and base cations (Ca, Mg, K, Na) in drainage water. This affects the acid neutralizing capacity of lakes and streams.

Most watersheds in the central and southeastern United States are no longer acidifying but also are not exhibiting much recovery of surface water pH or acid neutralizing capacity in response to recent large decreases in atmospheric S deposition (Burns et al. 2011). Recovery has been somewhat more pronounced in the northeastern United States but still relatively modest (Driscoll et al. 2001a, 2007). This limited recovery is partly due to previous leaching losses of base cations from soils in the watersheds draining to surface waters.

3.1.3  Spatial Patterns in Acidification Risk

High-elevation lakes and streams are of particular interest with respect to potential aquatic impacts attributable to acidic deposition in the national parks. Many waters located at high elevation tend to be dilute (low ionic concentrations) and have low acid neutralizing capacity levels, and this contributes to the increased risk of acidification and biological harm from acid input. Because soils at high elevation are often shallow and poorly developed, with much exposed bedrock, the supply of base cations with which to neutralize acidity can be low (U.S. EPA 2008).

Streams and lakes vary in their sensitivity to acidification from acidic deposition. The surface waters that tend to be most sensitive to acidification are located on geological formations that contribute minimal quantities of base cations to drainage water. Figure 3.2 shows the locations of lakes and streams in the United States known to have low acid neutralizing capacity. These maps were compiled from available datasets and include a total of 31,662 sampling locations. Surface waters having acid neutralizing capacity ≤50 µeq/L are considered to be especially sensitive to acidification.

(a) Surface water acid neutralizing capacity (ANC), based on data compiled from the data sources listed in Table 3.2. (b) Surface water acid neutralizing capacity, shown as a subset of data represented in (a), but only sites having median acid neutralizing capacity ≤100 µeq/L.

(a)

(a)  

(b)

(b)  

National and regional databases of measured water chemistry data were aggregated to generate a master database to represent surface water acid neutralizing capacity status throughout the National Park Service networks. Sources of data were mostly U.S. federal agencies (Table 3.2). Duplicate records among the data sources were identified and removed. An attempt was made to also remove samples expected to be affected by acid mine drainage, sea salt spray, and road salt application. This was performed by applying chemistry screens that removed samples with observed chloride or sulfate greater than 300 µeq/L or acid neutralizing capacity <–100 µeq/L.

Table 3.2   Data Sources for National Map of Surface Water Acid Neutralizing Capacity

Database

Source

Adirondack Lakes Survey

Adirondack Lakes Survey Corporation

Long-Term Monitoring Project

U.S. Environmental Protection Agency

Temporally Integrated Monitoring of Ecosystems

U.S. Environmental Protection Agency

Western Adirondack Stream Survey

U.S. Geological Survey

Eastern Lakes Survey

U.S. Environmental Protection Agency

Western Lakes Survey

U.S. Environmental Protection Agency

Environment Monitoring and Assessment Project

U.S. Environmental Protection Agency

Mid-Atlantic Streams Survey

U.S. Environmental Protection Agency

National Lakes Survey

U.S. Environmental Protection Agency

Wadeable Streams Assessment

U.S. Environmental Protection Agency

National Stream Survey

U.S. Environmental Protection Agency

STORET

U.S. Environmental Protection Agency

Regional Environmental Monitoring and Assessment Program

U.S. Environmental Protection Agency

High Elevation Lake Monitoring Program, Maine

Steve Kahl, Jason Lynch

Aquifer Lakes Project, Maine

Steve Kahl, Jason Lynch

Water Quality Monitoring in George Washington and Jefferson National Forests

U.S. Forest Service

Federal Land Manager Environmental Database

U.S. Forest Service

Monongahela National Forest Database

U.S. Forest Service

North Carolina National Forest Database

U.S. Forest Service

National Water Information System

U.S. Geological Survey

Alpine Hydrology Research Group

U.S. Geological Survey

Virginia Trout Stream Sensitivity Study

University of Virginia

These samples were considered to represent acid neutralizing capacity results that were likely confounded by disturbances other than acidic deposition. The final database contained 196,997 acid neutralizing capacity values from 19,808 spatially unique sites sampled between January 8, 1980, and May 25, 2011 (Figure 3.2a). There were 6,065 sites with low (<100 µeq/L) median acid neutralizing capacity derived from 69,649 samples (Figure 3.2b). The distribution of surface water acid neutralizing capacity across the National Park Service networks is shown in Table 3.3.

Table 3.3   Distribution of Measured Surface Water Acid Neutralizing Capacity (μeq/L) Values across the National Park Service Networksa

Network Name

Number of Sites

Minimum

5th Percentile

25th Percentile

Median

75th Percentile

95th Percentile

Maximum

Northeast Temperate

4300

−96.7

−23.1

12.8

80.0

199.0

853.6

6580.0

Northeast Coastal and Barrier

349

−71.4

−2.2

20.0

100.0

280.0

911.7

3600.0

Appalachian Highlands

1597

−22.0

2.0

43.0

106.0

228.7

1477.6

5602.2

Sierra Nevada

518

0.4

21.6

45.0

106.6

388.6

1380.5

4340.0

Eastern Rivers and Mountains

1636

−99.7

−23.7

64.5

194.9

500.0

1805.0

5792.2

Mid-Atlantic

834

−85.3

−10.4

77.7

220.0

539.0

1620.5

5020.0

Cumberland Piedmont

886

−20.4

16.8

132.8

340.0

1120.0

2754.9

4340.0

Gulf Coast

693

−58.7

0.0

120.0

368.0

910.0

2596.0

5200.0

Southeast Coast

1103

−87.0

20.0

200.0

370.0

550.0

1100.0

3810.0

National Capital Region

89

6.9

83.6

220.0

391.0

895.0

2455.4

3560.0

Great Lakes

1103

−48.6

7.0

81.5

391.5

1696.8

3738.0

6040.0

Southwest Alaska

64

140.0

147.5

260.0

410.0

560.0

797.0

940.0

Pacific Island

23

80.0

132.0

370.0

420.0

540.0

984.0

1040.0

North Coast and Cascades

815

−4.7

30.9

183.3

496.5

1005.0

2140.0

5844.9

Upper Columbia Basin

887

20.9

44.2

122.8

518.0

1320.0

3266.3

18720.0

Greater Yellowstone

495

12.0

35.4

88.8

518.2

1523.4

3860.0

6280.0

Klamath

599

0.0

26.7

219.1

654.6

1217.2

2862.0

8004.9

Rocky Mountain

1186

5.0

42.2

200.9

744.6

1817.5

4305.0

10700.0

Southeast Alaska

52

60.0

173.0

512.5

920.0

1375.0

3209.0

15180.0

Central Alaska

85

260.0

360.0

670.0

960.0

2360.0

3924.0

5200.0

Northern Colorado Plateau

788

−5.7

59.3

138.3

1173.7

3400.0

6012.5

12020.0

Arctic

40

310.0

716.0

985.0

1300.0

1625.0

2143.5

3300.0

Southern Colorado Plateau

216

10.0

48.7

484.6

1480.0

2810.0

4645.0

9847.1

Southern Plains

140

28.9

185.8

648.4

1500.0

2713.8

4790.0

14200.0

Heartland

637

0.0

100.0

524.5

1652.2

2860.0

4920.0

6520.0

Mojave Desert

86

126.9

476.4

955.0

2000.0

3775.0

4548.9

5940.0

South Florida/Caribbean

108

−46.1

29.9

542.5

2050.0

2805.0

4388.0

5400.0

San Francisco Bay Area

48

354.5

476.0

1374.6

2115.0

2535.0

3432.0

6860.0

Mediterranean Coast

40

300.0

579.0

1492.5

2242.5

3490.0

6628.0

9540.0

Sonoran Desert

82

115.4

540.0

1047.5

2260.0

3552.5

4619.0

5922.0

Northern Great Plains

263

20.0

786.0

2149.0

3040.0

4686.7

9798.0

14400.0

Chihuahuan Desert

9

740.0

1396.0

2480.0

3320.0

3840.0

8712.0

11920.0

Notes:

a  Data are based on samples mapped in Figure 3.2a, arranged in order of increasing median acid neutralizing capacity.

Although these data cannot be considered to be statistically representative of spatial distributions of surface water acid neutralizing capacity across the nation, there are clear patterns that emerge. Acidic lakes and streams are widely distributed but are mostly confined to upstate New York, the Appalachian Mountains, New England, the Upper Midwest, and Florida. Low acid neutralizing capacity lakes and streams (0–100 µeq/L) occur in these same areas plus portions of Arkansas, the Gulf states, and the Rocky, Cascade, and Sierra Nevada mountains. In other regions of the United States, available water quality data are generally indicative of well-buffered streams and lakes that are likely to be insensitive to acidic deposition.

3.2  Nutrient Nitrogen Enrichment

Nutrient enrichment describes a host of environmental changes that can occur when the availability of a key nutrient is increased as a consequence of air and/or water pollution. Nutrient enrichment effects can occur in terrestrial, wetland, and aquatic environments. In all cases, the addition of a key nutrient (typically N) from atmospheric deposition can contribute to changes in the species mix of the plant, lichen, and algal communities. Nutrient enrichment can cause some species to thrive, at the expense of others. Thus, the mix of species present in an ecosystem can change as a consequence of nutrient addition.

3.2.1  Terrestrial Effects

In many terrestrial ecosystems, N is the most important nutrient limiting the growth of plants under a plant’s natural water regime. If an appreciable amount of N is added from atmospheric deposition, plant growth rates may increase. Because some species are better able to take advantage of added N than others, some plant species grow well and others are crowded out. The species that benefit are often nonnative opportunistic species; those that are suppressed are sometimes rare native species (Sullivan 2015).

The extent to which ecosystems respond to nutrient addition depends in part on the extent to which the growth of plant communities is limited by N availability, as compared with the availability of light, water, phosphorus (P), or some other nutrient. Most north temperate terrestrial ecosystems are at least partially N-limited (U.S. EPA 2008). If the availability of N is increased, there can be a shift in competitive advantage to favor those species that grow faster. This can alter the species makeup of the plant community, decrease species diversity, and can eliminate some of the rare, or otherwise valued, species. In general, plant communities that are dominated by herbaceous plants appear to be more sensitive to N enrichment than plant communities dominated by woody plants. This may be partly because it takes a long time for scientists to document effects on trees that can grow for decades or centuries. Nutrient enrichment effects on plant communities in the United States have been most convincingly demonstrated for herbaceous arctic and alpine plant communities, grasslands, wetlands, and arid or semiarid lands (U.S. EPA 2009c). These are the primary plant community types that are discussed here. This does not mean that some of these same effects may not also be occurring in forest communities.

Alpine plant communities are known for their high diversity of vascular plant species (Bobbink et al. 2010) and have been shown to be especially sensitive to N enrichment. Some studies suggest that sedges benefit more from N addition to alpine herbaceous plant communities than do grasses or forbs (Bowman et al. 2006, Bobbink et al. 2010). Changes in the abundance of a species of alpine sedge (Carex rupestris) have been demonstrated at N deposition levels near 3 kg N/ha/yr (Bowman et al. 2012). More dramatic effects on alpine vascular plant community composition within a relatively short time period (a few years) probably require higher levels of N deposition, perhaps near 10 kg N/ha/yr (Bowman et al. 2006). Model simulations suggest that effects can develop over centuries in response to very low levels of N input (Sverdrup et al. 2012, McDonnell et al. 2014). There are a number of plant community characteristics in the alpine zone that appear to govern sensitivity to N input. These include low temperature, restricted growing season, low levels of primary production, and wide variation in moisture regimes from boggy meadows to the desiccating conditions of wind-swept ridges (Bowman et al. 1993, Bowman 1994, Bowman and Fisk 2001). Another contributing factor is the fact that soil formation is a slow process in the harsh alpine environment. Therefore, alpine plants have evolved under conditions of low nutrient supply (U.S. EPA 2008). In some alpine scrub habitats, ground-layer bryophytes and lichens are thought to be especially sensitive to N addition (Fremstad et al. 2005, Britton and Fisher 2007).

Arctic plants have not been well studied with regard to their sensitivity to modest levels of N enrichment that might correspond with potential future levels of atmospheric N deposition. Nevertheless, some arctic plant communities share many commonalities with alpine vegetation and are therefore thought to be highly sensitive. Arctic environmental conditions also contribute to slow soil development and low nutrient availability, thereby enhancing sensitivity to N deposition inputs. Low levels of N addition (1–5 kg/ha/yr) have been shown to change species composition and cover of grasses, forbs, and shrubs in some tundra ecosystems (Arens et al. 2008).

Increased N input has reduced plant biodiversity in grasslands in both Europe and North America (Bobbink et al. 2003, Stevens et al. 2004, Clark and Tilman 2008). Such effects have been documented across a range of soil conditions. Changes in species composition have been reported at N deposition levels as low as about 10 kg N/ha/yr (Bobbink et al. 2003). In the San Francisco Bay area, which receives total N deposition of about 10–15 kg N/ha/yr, nonnative nitrophilous (N loving) grasses have displaced native plant species. This effect has been attributed to greater N supply from the atmosphere combined with cessation of livestock grazing, which had previously removed some of the excess N from the ecosystem (Fenn et al. 2003, U.S. EPA 2008). A survey across acidic grasslands in the United Kingdom by Stevens et al. (2004) estimated a decrease of one plant species for every 2.5 kg N/ha/yr of deposition.

Experimental N fertilization studies have been conducted in arid and semiarid plant communities in southern California and the Colorado Plateau. Such vegetation communities are commonly dominated by shrubs but can also be dominated by grasses, forbs, and/or cacti. Results of the fertilization studies suggested increased biomass of some nonnative plant species and reduced biomass of some native species with sufficiently high levels of N input. There also appears to have been an increased fire risk where grasses replaced shrub cover. There are apparently multiple interactions involving N stimulation of nonnative grass species, competitive abilities of native forb and shrub species, and the incidence of fire (cf., Eliason and Allen 1997, Yoshida and Allen 2001). The coastal sage scrub plant community in California, in particular, has been declining for many decades. Current scientific understanding suggests that atmospheric N deposition plays a role in this decline and causes shrub replacement by Mediterranean annual grasses, which promote increased fire cycles (D’Antonio and Vitousek 1992, Minnich and Dezzani 1998, Padgett and Allen 1999, Padgett et al. 1999, Fenn et al. 2003).

Additional studies have been conducted in desert plant communities, suggesting that N additions in the range of 10 kg N/ha/yr or higher can cause invasion of nonnative plant species, including grasses (U.S. EPA 2008). Effects appear to be more pronounced at higher elevations, perhaps because the increased precipitation that occurs at higher elevation in arid lands can contribute to increased grass production. Increased grass biomass in desert plant communities is associated with increased fire frequency (Brooks 1999, Brooks and Esque 2002, Brooks et al. 2004). The effects of N deposition on arid and semiarid plant communities may vary with moisture levels. In Joshua Tree National Park, California, N loadings of 3–4 kg/ha/yr were estimated to significantly increase the cover of nonnative grasses, with subsequent increases in fire risk (Rao et al. 2010). In some cases, N may be limiting during wet seasons or years, whereas water may be limiting during dry seasons or years.

Lichens are typically among the most N-sensitive terrestrial receptors (Figure 3.1; Bobbink et al. 2003, Fenn et al. 2003, Vitt et al. 2003, Geiser et al. 2010). Most lichens can be classified into groups based on N requirements. Some additional lichen taxa exhibit broad tolerance to N supply. Lichens that inhabit trees are called epiphytes. They tend to be highly sensitive to N inputs and are widely recognized as good early warning indicators of terrestrial ecosystem effects from atmospheric N input (Fenn et al. 2011). Epiphytic lichens vary in their N requirements. Montane species tend to be adapted to low N availability and are classified as oligotrophic (low nutrient availability). They are commonly found on coniferous trees. Valley species tend to be adapted to more mesotrophic (moderate nutrient availability) conditions and often occur on hardwood trees. Eutrophic (high nutrient availability) species are adapted to high N supply, often in association with animal nesting or roosting sites. Atmospheric N deposition results in a shift from more oligotrophic toward more eutrophic conditions; this shift is typically accompanied by a change in the lichen community to favor the mesotrophic and eutrophic forms, with a decrease in the oligotrophic species (Geiser et al. 2010). Many lichen species that are prevalent in the western United States have relatively well-known N requirements. Critical loads of N have been well established, especially in the West (Pardo et al. 2011, Cleavitt et al. 2015). A change in lichen species distribution and abundance in response to a change in N supply can have broad ecosystem-level effects. This is due to the importance of various oligotrophic lichen species as forage, for nutrient cycling, and as nesting materials for wildlife.

3.2.2  Aquatic Effects

Estuaries and coastal marine waters are generally susceptible to nutrient enrichment effects from atmospheric N deposition because N tends to be the main growth-limiting nutrient in such environments. Growth of plants and algae in freshwaters, in contrast, is often limited by the availability of P, which is typically not an important component of air pollution and atmospheric deposition at most locations. There are some freshwaters, however, that are limited in their algal growth by N or by a combination of both N and P. Many of these occur at high elevation.

High-elevation lakes are of particular concern, among aquatic ecosystems, with respect to potential impacts attributable to atmospheric nutrient N enrichment. There are several reasons. Many high-elevation lakes tend to be dilute to ultradilute (low ionic concentrations) and nutrient-poor, contributing to increased risk of biological change from nutrient addition, even in relatively low quantities. Many high-elevation lakes have been shown to be N-limited. Diatom communities in several high-elevation lakes in Colorado and Wyoming have been shown to have been impacted by relatively low levels of atmospheric N deposition (Wolfe et al. 2001, Saros et al. 2003, Baron et al. 2011, Nanus et al. 2012). Because soils in the watersheds of high-elevation lakes are often poorly developed, with much exposed bedrock, the transport of N from atmospheric deposition to lake water can be quick and direct.

Research by Elser et al. (2009a,b) suggested that atmospheric inputs of N in some high-elevation areas have altered the relative proportional availability of N and P to phytoplankton. These changes in nutrient availability may have shifted lakes from N limitation toward P limitation, with consequent alterations to plankton community structure, species diversity, and trophic interactions (Elser et al. 2009b).

3.2.3  Nitrogen Saturation

An undisturbed forest commonly uses and incorporates, mostly through the soil, almost all of the small amounts of N that it receives from atmospheric deposition. This N is cycled between soil and vegetation, but the cycle can be disrupted by increased atmospheric N deposition (Aber et al. 1989). Forests have a maximum capacity to store N that they receive from outside the watershed. This capacity is determined by the plant species present on the site and the history of logging and other disturbances that removed some of the N previously stored on site. When N inputs exceed this storage capacity, the site becomes N-saturated, and an appreciable percentage of the incoming N leaches as nitrate to soil water and to streams and lakes. Leaching of nitrate can contribute to soil acidification. As N saturation progresses, tree health deteriorates and the forest may release to drainage water more N than is coming into the watershed from atmospheric deposition. Under conditions of advanced N saturation, tree growth declines and sensitive tree species die in response to acidification, Al toxicity, and/or base cation depletion (U.S. EPA 2008).

Atmospheric deposition of N has increased N availability in soils at some locations, which has led to increased nitrification and acidification of soil and soil water. Because the N retention capacity of soils is strongly dependent on land-use history, the relationships between N deposition and ecosystem N status are variable. In general, atmospheric deposition of about 8–10 kg N/ha/yr or higher is required in order for appreciable amounts of nitrate to leach from forest soils to surface waters in the eastern United States (U.S. EPA 2008). At high elevations in the West, the scarcity of soil and the dynamics of snowmelt contribute to substantial N leaching at lower levels of atmospheric N deposition (Williams et al. 1996, Nanus et al. 2012).

Many studies in the southern Appalachian Mountains (cf., Joslin et al. 1992, Van Miegroet et al. 1992a,b, Joslin and Wolfe 1994, Nodvin et al. 1995) have found high concentrations of nitrate in soil water and stream water at high-elevation, old-growth spruce-fir forest locations. This nitrate leaching is believed to have been caused by high N deposition, low N uptake by forest vegetation, and inherently high N release from soils. Forest age also affects N uptake by vegetation. Mature trees take up relatively small amounts of N for new growth and often show higher nitrate leaching than younger, faster growing stands (Goodale and Aber 2001).

3.3  Critical Load and Exceedance

The critical load is defined as the threshold of acid or nutrient pollutant deposition below which specified harmful ecological effects do not occur according to present knowledge (Nilsson and Grennfelt 1988, Porter et al. 2005). The critical load allows evaluation of relative resource sensitivity. Critical loads can be developed for any pollutant but are most often applied to N and S deposition and acidity or to N enrichment. Critical loads are commonly expressed as kg/ha of N or S or as equivalents per hectare (eq/ha) of combined acidity from N and S per unit time (usually per year). The critical load is generally determined for a specified indicator and endpoint for that indicator. For example, a critical load for S can be calculated that will prevent acid neutralizing capacity from decreasing to a level below 50 or 100 µeq/L in a lake, levels considered safe for most aquatic biota. A critical load for N can be calculated that will prevent loss of a certain amount of plant species diversity in a grassland or alpine meadow. Critical loads can be calculated using dose-response functions, ecological models, or empirical observations (Sullivan and Jenkins 2014). The critical load is assumed to be sustainable under long-term steady-state mass balance conditions (Henriksen and Posch 2001). In other words, the critical load specifies the pollutant load which, when applied to the ecosystem in question for a period of years to centuries, will eventually trigger a change in a chemical or ecological indicator of harm at the time that the ecosystem comes into steady state with respect to that particular pollutant input level.

A dynamic, as opposed to steady-state, pollutant load can also be defined, which is specific to a particular point in time. This dynamic pollutant load will specify, for example, the deposition load that can be tolerated in a certain lake or stream until the year 2100 without loss of brook trout populations. If a stream is already acidified, it can identify how much S or N loading should be reduced in order to restore the stream to a healthy acid neutralizing capacity by the year 2100, for example. This dynamic load, which includes consideration of the temporal component of ecosystem damage or recovery, is called a target load or a dynamic critical load. The target load concept can be used to describe not only the effects of time but also the inclusion of various management actions or scenarios (Sullivan and Jenkins 2014).

There is no single “definitive” critical load for a natural resource. The critical load depends on what is to be protected, to what level of protection, what indicator is used, and what is specified as the critical or threshold tipping point level of that indicator. Critical load estimates reflect the current state of knowledge and policy priorities, both of which can change. This process typically results in the calculation of multiple critical loads for a given pollutant at a given location, and those values can change over time. Multiple critical load values may also arise from an inability to agree on a single definition of significant harm (Sullivan and Jenkins 2014).

The critical load is affected by the heterogeneity of natural ecosystems. Because of high spatial and temporal variability of soils and surface waters, there may be a continuum of sensitivity and critical load values for a given sensitive indicator.

The critical load or target load provides an indication of the point at which the ecosystem may begin losing ecosystem services and transitioning from a sustainable functioning ecosystem for those services to one that is not functioning properly and is no longer considered sustainable. The critical load concept provides a tool that enables the implementation of decision-making based on ecosystem services (Sullivan 2012).

On its own, the critical load does not predict whether the ecosystem experiences, or will experience, biological harm. The ambient pollutant load must also be considered. If the ambient deposition is higher than the critical load or target load that the ecosystem can tolerate, the ecosystem is in exceedance, which suggests an increased likelihood of biological harm. Transitioning between a condition of nonexceedance to a condition of exceedance does not mean a change in whether the ecosystem is currently experiencing damage. The transition from nonexceedance to exceedance, or vice versa, indicates a change in the probability that ecosystem services will be reduced, lost, or recovered, depending on whether the starting point is an undamaged or a damaged state (Sullivan 2012). For undamaged systems, exceedance signifies that if deposition is continued at the current exceedance level, damage will likely occur at the time point specified for the analysis (e.g., 2100, eventual steady-state condition). Transitioning from exceedance to nonexceedance suggests that recovery will occur at the future time specified in the analysis (Sullivan and Jenkins 2014).

In a watershed that receives a loading of acidic deposition that is lower than the critical load, a target load might be selected that is higher than or lower than the critical load. A higher target load might be justified if the damage projected to occur under the critical load will not be manifested for a very long time, allowing future opportunity to further mitigate pollution levels before the damage is realized. A lower target load might be justified to err on the side of resource protection or to protect against short-term damage prior to attaining a long-term steady-state protected condition. For a watershed that receives an acidic deposition loading that is higher than the critical load, an interim target load might be selected that is higher than the critical load in order to allow for partial resource recovery within a management timeline. For an already damaged watershed, a target load might be selected that is lower than the critical load if resource managers are unwilling to wait the decades or centuries that it might take to achieve full resource recovery under sustained loading at the level of the critical load (Porter et al. 2005, Sullivan 2012).

Pardo et al. (2011) compiled empirical data on nutrient N critical loads in ecoregions throughout the United States for a variety of N-sensitive resources, including lichens, mycorrhizal fungi, herbaceous plants and shrubs, and forests. These critical loads were generally reported by Pardo et al. (2011) as ranges for a given ecoregion, rather than absolute values. Because ecosystems vary, sometimes substantially, within an ecoregion, the critical load range for a given receptor (species or group of species) may not apply to all plant communities or all portions of the ecoregion. Some are more sensitive than others.

Sullivan and McDonnell (2014) evaluated empirical critical load estimates for ecoregions developed by Pardo et al. (2011) and analyzed available vegetation distribution data to estimate the appropriate critical load range for 12 selected national parks in the intermountain West. They also examined oxidized N emissions by county and total (oxidized and reduced) N deposition estimates in and near the selected parks. Deposition estimates for 2008 were compared to park nutrient N empirical critical loads to evaluate the likelihood that critical loads were exceeded in the national parks considered, given the presence of the sensitive element. The parks selected for study included many of those in the western United States that have been identified as having N-sensitive ecosystems. Some of the parks have been experiencing, in recent years, increasing levels of nearby energy, agricultural, mineral extraction, and/or transportation development, with associated increasing N emissions.

The critical load and exceedance estimates developed by Sullivan and McDonnell (2014) were based on the lower limits of the ranges of critical load, by ecoregion, reported by Pardo et al. (2011). This was done to conform with the Congressional mandate when considering critical loads for national parks and other protected areas, to err on the side of resource protection. Based on these lower limits of the critical load ranges reported by Pardo et al. (2011), terrestrial resources in most of the parks evaluated by Sullivan and McDonnell (2014) were either in exceedance of the nutrient N critical load or received ambient (year 2008) total wet plus dry N deposition that was below, but within 1 or 2 kg N/ha/yr of, the critical load. Thus, nutrient-sensitive terrestrial resources in some of these parks may be experiencing adverse impacts associated with critical load exceedance. In other cases, appreciable increases in oxidized N or ammonia emissions and deposition in the future may trigger exceedances.

Of the 12 parks that were evaluated in the study of Sullivan and McDonnell (2014), estimated nutrient N critical load exceedances were most pronounced in Voyageurs, Mesa Verde, Black Canyon of the Gunnison, and Saguaro national parks. Large portions of Grand Canyon, Arches, Badlands, Theodore Roosevelt, and Wind Cave national parks and Colorado and Dinosaur national monuments received N deposition in 2008 that was within 1 kg N/ha/yr or less below the nutrient N critical load. Much of Canyonlands National Park received N deposition in 2008 that was below, but within 2 kg N/ha/yr of, the nutrient N critical load. These results provide estimates of relative risk of nutrient enrichment to sensitive vegetative receptors among the parks selected for study.

Baron (2006) recommended a critical load of 1.5 kg N/ha/yr (wet deposition) to protect alpine lakes in Rocky Mountain National Park against eutrophication. Similarly, Saros et al. (2011) found that 1.4 kg N/ha/yr (wet deposition) caused nutrient enrichment effects (i.e., changes in diatom diversity) in high-elevation lakes in the eastern Sierra Nevada and the Greater Yellowstone ecosystems. Similar thresholds have been identified by Baron et al. (2011) and Nanus et al. (2012).

Nitrogen deposition to wetlands can alter competitive relationships among species, sometimes increasing the establishment of nonnative species at the expense of rare species. Such changes are thought to occur in Europe at N deposition levels in the range of 5–10 kg N/ha/yr for raised and blanket bogs, 10–20 kg N/ha/yr for poor fens, and at higher deposition levels for rich fens and salt marshes (Achermann and Bobbink 2003). Pardo et al. (2011) suggested a critical load range of 2.7–13 kg N/ha/yr to protect wetlands in the northeastern United States.

3.4  Ozone Exposure and Effects

The challenge in assessing ozone effects is to quantify the spatial distribution of ozone exposure relative to the location of sensitive plant receptors and the environmental conditions that promote ozone uptake by plants into the stomata. The fact that ozone concentrations are higher downwind from urban areas, and that concentrations tend to increase with elevation, suggests that some national parklands can be particularly vulnerable.

Despite known general relationships between regional sources of ozone (and its precursors) and wildland receptors, it has been difficult to estimate ozone exposure in those wildlands because of high variability. Ozone is monitored at about 40 national parks, although about twice that many urban national park units have nearby ozone monitors. The National Park Service-Air Resources Division also provides estimates of ozone concentrations and exposures at over 200 park units in the continental United States, using all available monitoring data to derive interpolated estimates (http://www.nature.nps.gov/air/Maps/AirAtlas/index.cfm). Trends are highlighted at http://www.nature.nps.gov/air/data/products/parks/index.cfm.

3.4.1  Effects of Ozone on Plants

Ozone injury to plants is determined primarily by three things: (1) the plant and its inherent sensitivity to ozone, (2) the level of ozone in the atmosphere at the location of the plant, and (3) site-specific environmental conditions (Kohut 2007b). In general terms, ozone injury will only occur if the plant is genetically predisposed to ozone injury, the level of atmospheric ozone exposure exceeds the threshold for injuring that plant, and the environmental conditions at the site facilitate the uptake of ozone through the stomata into plant leaves.

Injury occurs when all three key elements are satisfied. First, the plant must be predisposed to ozone sensitivity. Differences in sensitivity are often pronounced at the species level. For example, ponderosa pine (Pinus ponderosa) and quaking (also called trembling) aspen (Populus tremuloides) are two common tree species found in many national parks in the western United States that are known to be sensitive to ozone. However, differences in plant sensitivity can also be observed among clonal lines, subspecies, or individual plants. The reasons for such differences are not well understood (Kohut 2007b). Second, the threshold level of atmospheric ozone exposure that can produce injury on a plant must be exceeded at the location of the plant. Peak levels of exposure can produce acute effects; lower but sustained levels of exposure can produce chronic effects. Exposure indices that consider both atmospheric ozone peak levels and sustained exposure are used to evaluate the likelihood of the plant experiencing a high ozone exposure. Third, the plant must experience environmental conditions that facilitate ozone uptake into the leaf through the stomata. The environmental conditions that inhibit stomatal opening, and therefore also inhibit ozone uptake into the leaf, include mainly low soil moisture and high temperature. Conditions of optimum moisture availability, humidity, illumination, and temperature facilitate both photosynthesis and uptake of ozone into the leaf. Such conditions can be highly variable spatially. For example, low soil moisture and high temperature can limit stomatal opening broadly across a vegetative community, yet more favorable conditions for ozone uptake may occur at the microsite level, for example, in riparian zones or other areas that retain soil moisture. Thus, plants on favorable microsites may exhibit physiological responses, such as foliar ozone symptoms, whereas adjacent plants under water stress may not. Similarly, an ecosystem may express ozone symptoms during one year, but not the next, due entirely to differences in ozone exposures, soil moisture, and/or temperature. Foliar symptoms are most pronounced when all variables of the response triad are satisfied (Kohut 2007b).

Visible foliar symptoms provide an easily identified (with training) indicator of ozone injury to vegetation. Ozone injury of cells and tissues is essentially the same in woody and herbaceous plants (Bytnerowicz and Grulke 1992). Injury generally occurs first in the most photosynthetically active tissues, with disruption of chloroplasts in the palisade and mesophyll tissue. The loss of photosynthetic tissue results in visible chlorosis (bleaching) and necrosis (death of tissue). Visible symptoms do not constitute an early warning signal indicating damage to the plant; physiological impacts may have occurred prior to the production of foliar symptoms. Various effects may have occurred inside the plant before visible symptoms are evident. Furthermore, the presence of visible symptoms does not necessarily indicate that effects on growth, health, or reproduction have, or will, also occur.

3.4.2  Standards and Cumulative Exposure Indices

Evaluation of plant response to ozone exposure requires the use of an appropriate ozone exposure summary statistic. Exposure reflects the atmospheric concentration of ozone to which a plant is exposed; dose reflects the amount of ozone that is actually taken up by the plant. Factors that influence plant response are complex and vary with environmental conditions and the physiology of ozone-sensitive plants (Musselman et al. 2006). The degree of pollutant injury depends on the effective dose, which is a function of concentration, length of exposure, and stomatal aperture, as well as plant biochemical defense response to the ozone dose received (Kozlowski and Constantinidou 1986). Exposure indices are unable to consider the full range of processes that control ozone transport from the atmosphere into the leaf or the physiological response, including detoxification mechanisms, of the plant. As a consequence, there is no appropriate dose-based index for use in evaluating the effects of ozone on plants (Musselman et al. 2006). Rather, exposure-based indices are used.

In order to protect human health and welfare, the EPA has established primary (to protect human health) and secondary (to protect welfare and the environment) National Ambient Air Quality Standards for maximum allowable atmospheric ozone concentration levels. Prior to 1997, these standards were based upon 1-hour average ozone measurements. They were revised in 1997, when the EPA promulgated new standards, both primary and secondary, based upon an 8-hour average value. The standards were both set at 0.08 parts per million (ppm; or rounded to 85 ppb), a value that represented the annual fourth highest daily maximum 8-hour ozone concentration, averaged over three years for the protection of both human health (primary National Ambient Air Quality Standard) and vegetation (secondary National Ambient Air Quality Standard). The standards were strengthened in 2008 to 0.075 ppm and in 2015 to 0.070 ppm. This average is computed by first determining the highest 8-hour average ozone value for each day of the year at a site and then identifying the fourth highest of all daily maximum 8-hour ozone values that occurred during the year. These fourth highest values are then averaged over three successive years to determine the final concentration value that is compared to the standard.

The decision by the EPA to transition from an ozone standard based upon a 1-hour average to a standard based upon an 8-hour average was prompted by research indicating that prolonged exposure to ozone at concentrations lower than the 1-hour standard can have significant impacts. The agency has also recognized the potential importance of an exposure index in setting the secondary ozone standard to protect native vegetation and ecosystems. The EPA proposed a new secondary ozone standard in January 2010 (Federal Register Vol. 75, No. 11, 40 CFR Parts 50 and 58, National Ambient Air Quality Standards for Ozone, Proposed Rules, January 19, 2010, p. 2938). It was based on an index, called the W126, of the total plant ozone exposure during the daytime (8:00 am–8:00 pm), whereby hourly values were weighted according to magnitude and then summed. Higher concentrations are weighted more heavily, as they are more likely to induce ozone injury. The W126-3-mo statistic is calculated as the three-month period having the highest cumulative exposure. The proposed standard was based on a three-year average of the annual W126-3-mo metric; nevertheless, the EPA administrator judged that the primary standard at that time was sufficient to protect sensitive vegetation.

In addition to the W126, another metric, the SUM06, is used to express ozone exposures (Heck and Cowling 1997). This index is calculated as a 90-day maximum sum of the hourly concentrations of ozone during daylight hours that are higher than or equal to 60 ppb (0.06 ppm). It is calculated over a running 90-day period. The maximum value can occur at any time of year during the ozone monitoring season but usually occurs during the summer months.

The W126 index (Lefohn et al. 1997) can be calculated as the weighted sum of the 24 one-hour ozone concentrations measured daily for seven months from April through October as originally proposed by Lefohn or calculated for daylight hours over a three-month period as modified by the EPA. When originally developed, the W126 was expressed in conjunction with the number of hours (called the N100) during which the ozone exposure is ≥0.100 ppm. This was because the N100 was associated with foliar effects noted in chamber studies.

It is important to note that calculated values of the W126 index differ depending on whether they are calculated over a seven-month period (W126-7-mo; original Lefohn version) or a three-month period (W126-3-mo; modified by the EPA in 2010). The ozone assessments of Kohut (2007a,b) used the Lefohn version; the assessment presented here uses the EPA version. The National Park Service has adopted the EPA version for assessing ozone exposure in parks with respect to potential injury to vegetation (NPS 2011).

3.4.3  Mode of Action

In the context of impacts of air pollutants on plants, damage and injury terminology is rather precise, as applied by Federal Land Managers (cf., Guderian 1977, Musselman et al. 2006, U.S. Forest Service et al. 2010). Injury refers to all physical and biological responses to air pollutants, including effects on processes and cycles. Damage is a reduction in the intended use or value of the resource, including reduction in aesthetic value, plant diversity, or other ecosystem services.

Ozone can cause injury to various plant tissues, including direct effects on leaves and indirect effects on stems and roots. Manifestation of foliar symptoms is the most visible indication of ozone injury, although without proper field training, one can sometimes confuse ozone symptoms with other biophysical injuries, including abrasion, desiccation, insect herbivory, and effects of fungal pathogens. It is difficult to equate visible ozone-induced foliar symptoms with other effects on vegetation, such as on growth or reproduction. The significance of foliar symptoms appears to depend on how much of the total leaf area is affected and also plant age, size, and developmental stage. Nevertheless, visible foliar symptoms have been shown in some studies to correlate with decreased plant growth (cf., Benoit et al. 1982, Peterson et al. 1987, Karnosky et al. 1996) and, in some cases, decreased reproduction (cf., Black et al. 2000, Chappelka 2002).

Ozone enters plant leaves as a gas and dissolves in the presence of water. The resulting free radicals oxidize proteins of cell membranes, including those of the thylakoid membranes where photosynthesis takes place. Injury includes leaf discoloration, reduced photosynthetic rates, and lowered sugar production.

Ozone exposure is believed to inhibit plant stomatal responses. This may explain the finding of McLaughlin et al. (2007a,b) that peak hourly ozone exposure increased water loss from several tree species and reduced late-season modeled streamflow in forested watersheds in eastern Tennessee. Ozone exposure was also found to decrease the net primary productivity of most forest types in the Mid-Atlantic region by 7%–8% but had a much smaller effect (~1%) on the net primary productivity of high-elevation spruce-fir forests (Pan et al. 2009).

The timing of ozone exposure relative to the life cycle of the affected plant is important in determining response. For instance, exposure to ozone may reduce the growth of the root system in an annual plant; as the plant repairs leaf injury and maintains photosynthesis, there is less carbon (C) available to grow roots (U.S. EPA 1996b). In fact, root systems may be reduced in growth long before deleterious effects are manifested on aboveground portions of the plant. In perennial plants, the process is more complex, as stored reserves are usually available for growth and the effect of an exposure may not be manifested for several growing seasons (Hogsett et al. 1989, Andersen et al. 1991, Laurence et al. 1994). However, in the most sensitive perennial species, a single season of exposure can be sufficient to reduce growth significantly (Wang et al. 1986, Woodbury et al. 1994). The EPA estimated that under ambient ozone exposures, biomass loss in quaking aspen could exceed 10% in some areas of the East; biomass loss in black cherry (Prunus serotina) seedlings could exceed 20% in many areas (U.S. EPA 2007). Impacts to seedlings may decrease long-term growth and survival, ultimately affecting both individuals and populations of sensitive species.

Because ozone enters the plant through stomata, the duration of stomatal opening greatly affects the pollutant dose assimilated. Once ozone enters a plant cell, there are many biochemical processes that can be affected (Wellburn 1988, Heath and Taylor 1997). Ozone increases the potential for the formation of free radicals, which are highly reactive and disrupt various metabolic processes through oxidation and toxicity.

The most common visible effects of ozone exposure on vegetation are stipple (pigmentation on leaves), fleck (tiny light colored markings on upper layers of leaves), mottle (blotchy appearance), and necrosis (Miller et al. 1983, Thompson et al. 1984a,b, Hogsett et al. 1989, Treshow and Anderson 1989, Stolte 1996, Brace et al. 1999). Oxidant stipple is highly specific to ozone injury. Other types of injury may also occur in response to ozone exposure, including chlorosis, premature senescence, and growth reduction. However, these types of injury are not specific to ozone and can be caused by a variety of stressors. Documentation of stipple between the veins on the upper leaf surface of older sun exposed leaves provides a strong indication of ozone injury; changes in growth, species composition, and diversity in response to ozone exposure are much more difficult to document and quantify in the field.

Visible symptoms on leaves usually occur after acute exposure to high concentrations of ozone. Exposure to moderate concentrations of ozone for periods of several days to several months can also cause chronic injury, accelerated aging, premature casting of foliage, or reduced growth (Pell et al. 1994a,b, U.S. EPA 1996a,b). Accelerated aging may result in premature color change and loss of foliage, an effect of considerable importance at some national parks where park visitation levels are relatively high during the fall color season. Growth reductions at ambient levels of ozone are often difficult to measure, although a cumulative stress over multiple growing seasons may significantly reduce the growth and productivity of trees and understory vegetation (Reich and Amundson 1985, U.S. EPA 1996b).

Ozone exposure typically does not kill plants outright. Rather, it weakens them by disrupting their C budgets. Exposure to ozone contributes to reduced C fixation. In addition, because C is needed to repair ozone injury to membranes and organelles, there is less C available in ozone-stressed plants for growth, reproduction, or responding to other stressors such as low temperature, insects, and disease. Plants must expend energy to counteract the effects of ozone. This energy might otherwise be used for growth or health maintenance. Injured plant cells may die if detoxification and cellular repair are outpaced by ozone uptake into plant tissue.

There is considerable genetic variability, both within and among plant species, in the amount of damage that occurs in response to ozone exposure (Miller et al. 1982). The most sensitive plants are injured by exposure to concentrations of 60 ppb by volume or less for several days. These species are often used as biological indicators of ozone exposure (U.S. EPA 1996b). Conversely, some plants are very tolerant of ozone and are unaffected, even with severe exposures. Stomatal responses to ozone are complex. There can be pronounced differences in stomatal response due to differences in species sensitivities, exposure levels, and duration of exposure (McAinish et al. 2002, McLaughlin et al. 2007a).

Oxidant stipple can occur on sensitive plant species at ozone concentrations considered to be near or at background levels (Singh et al. 1978), sometimes in response to naturally occurring stratospheric ozone intrusions. However, such intrusions typically occur during spring, and not during the major part of the growing season when the leaf uptake of ozone is more pronounced (Singh et al. 1980, Wooldridge et al. 1997).

3.4.4  Field Observations

Smith (2012) reported the results of ozone exposure and effects biomonitoring across the northeastern and northcentral United States, with data collected over a period of 16 years at some locations (biosites). Ozone-sensitive plants were evaluated for ozone-induced foliar symptoms. However, regression models were generally not successful in predicting the presence of foliar symptoms based on ozone exposure (SUM06 and N100), site moisture (Palmer Drought Severity Index), and a plant moisture availability index (r2 > 0.1). She did, however, generate plausible clustering of the data that supported the following weak associations:

  • Biosites showing no symptoms occurred across all SUM06 and N100 exposures.
  • Biosites showing symptoms occurred across all SUM06 and N100 exposures.
  • When the Palmer Drought Severity Index and plant moisture availability index indicated that moisture was limiting, the percent of sites not showing symptoms was much greater than the percentage showing symptoms.

Generally, similar results were reported by Campbell et al. (2007) for western forests. They found an association between foliar symptoms and exposure, but high symptom expression could occur with low ozone exposure, and vice versa.

Field studies and controlled exposure experiments continue to identify ozone-sensitive plant species (cf., Kline et al. 2008, 2009). The U.S. Forest Service’s Forest Inventory Analysis program previously surveyed the incidence and severity of ozone-induced foliar symptoms on multiple sensitive species using standardized procedures at biosites throughout the United States (Coulston et al. 2003, Smith et al. 2003, USDA FS 2011). These monitoring data have confirmed the applicability of several species as effective biomonitors in the eastern United States, including sweetgum (Liquidambar styraciflua), black cherry, blackberry (Rubus spp.), and milkweed (Asclepias spp.). A more extensive list of bioindicator species is available in a National Park Service report (Porter 2003), and lists of both sensitive and bioindicator species, by park, are available through the National Park Service Data Store (https://irma.nps.gov/App/Portal).

Early studies of ozone foliar injury to conifers focused on ponderosa pine and eastern white pine (Pinus strobus; Miller and Millecan 1971, Pronos and Vogler 1981, Peterson et al. 1991, Peterson and Arbaugh 1992). Applicability to other coniferous species may vary considerably with respect to specific symptoms and pollutant exposure. Numerous studies have documented the sensitivity of quaking aspen to ozone under field and experimental conditions (Wang et al. 1986, Karnosky et al. 1992, Coleman et al. 1996), although there is considerable variability in sensitivity among different genotypes (Berrang et al. 1986).

Available plant symptom data do not suggest a broadly applicable ozone injury threshold. In general, there may be adverse effects with prolonged exposure to ozone concentrations greater than about 60 ppb, and there are likely effects with prolonged exposure to concentrations greater than about 80 ppb (Sullivan et al. 2003).

Efforts to take results of seedling ozone exposure studies and scale them up to whole trees have generally not been very successful (Samuelson and Kelly 2001). Trees and seedlings differ in energy budgets, canopy-to-root balance, and P allocation and cannot be assumed to exhibit similar levels of ozone sensitivity.

Kohut (2007c) evaluated the risk of ozone-induced foliar injury on sensitive plant species in 244 national park units as part of the Vital Signs Monitoring Network. The analysis examined plant response related to ozone exposure level and environmental conditions. He concluded that 27% of the parks had high risk of foliar injury, 19% moderate risk, and 54% low risk. Parks determined to have high risk included Gettysburg, Valley Forge, Delaware Gap, Cape Cod, Fire Island, Antietam, Harper’s Ferry, Manassas, Wolf Trap Farm, Mammoth Cave, Shiloh, Sleeping Bear Dunes, Great Smoky Mountains, Joshua Tree, Sequoia and Kings Canyon, and Yosemite.

Because ozone exposure is both chronic and episodic and is difficult to predict, plant responses may be controlled in large part by the capacity of plants to maintain leaf antioxidant systems throughout the growing season. Burkey et al. (2006) assessed seasonal patterns in ascorbate pool size and redox status in leaves from natural populations of three wildflower species (cutleaf coneflower [Rudbeckia laciniata L.], tall milkweed [Asclepias exaltata L.], and crown-beard [Verbesina occidentalis Walt.]) in Great Smoky Mountains National Park to determine relationships between foliar injury and ozone exposure. Ascorbic acid is an important metabolite that protects plant leaves from ozone injury (Conklin and Barth 2004). This was perhaps the first study to characterize leaf ascorbate in natural wildflower populations under field conditions. The three species showed differences in the content of leaf ascorbic acid and oxidation state that corresponded with differences among the three species in foliar symptoms in response to ozone exposure. The aspects of ascorbic acid metabolism that contributed to plant defense against ozone injury were identified.

Evans et al. (1996) found that the percent of dead palisade parenchyma cells in plant leaves was positively correlated with the percent of leaf area showing visible ozone injury. This was found for sassafras (Sassafras albidum), cutleaf coneflower, and smooth blackberry (Rubus canadenis). Also, the percent of dead cells was positively correlated with cumulative ozone exposure for sassafras and smooth blackberry.

Research at the Aspen Free-Air Carbon Dioxide Enrichment site in Rhinelander, Wisconsin, demonstrated that exposure to ozone can change the composition of plant communities. Aspen clones with high ozone tolerance were dominant over more ozone-sensitive clones, which showed reduced growth and increased mortality as a result of ozone exposure. Additionally, ozone exposure resulted in a competitive advantage for birch and maple over aspen in mixed aspen-birch and aspen-maple communities (Kubiske et al. 2007) with aspen biomass decreasing by 13%–23% in response to elevated ozone over a seven-year study (King et al. 2005). Biomass (above- and belowground) and net primary productivity were measured at the Aspen Free-Air Carbon Dioxide Enrichment site after seven years of ozone exposure. Relative to biomass at the control plot, total biomass at the ozone-enriched sites decreased by 23%, 13%, and 14% in the aspen, aspen-birch, and aspen-maple plant communities, respectively (King et al. 2005). Ozone exposure reduced growth and increased the mortality of an ozone-sensitive aspen clone; as a consequence, the tolerant clone became dominant. In mixed aspen-birch and aspen-maple communities, ozone exposure decreased the competitive ability of aspen compared to birch and maple (Kubiske et al. 2007).

3.4.5  Environmental Interactions

Chappelka et al. (1996) judged that the influences of microsite factors are important in controlling responses to ozone-induced injury. Available soil moisture appeared to be the most important environmental factor regulating ozone uptake into foliage, and subsequently effects on plants, through the influence of ozone on stomatal function. Kohut et al. (2012) found significant ozone injury on coneflowers in Rocky Mountain National Park in surveys conducted from 2006 to 2010. Risk to vegetation at the park had been rated as low because higher ozone concentrations that occur during the summer often coincided with dry soil conditions (Kohut 2007c). However, the 2006–2010 surveys were conducted in riparian areas, where soil moisture was sufficient to allow the plants to remain physiologically active and to promote ozone uptake. Kohut recommended that ozone surveys in western parks that often experience dry conditions be conducted in riparian or moist areas (Kohut et al. 2012). These riparian areas are also some of the most important areas ecologically in arid regions, supporting high levels of biodiversity.

Ozone may also affect the growth of plants indirectly through interactions with pests and pathogens (Laurence 1981), or by altering the symbiotic relations between plants and associated organisms (McCool 1988, Stroo et al. 1988, Andersen and Rygiewicz 1991, Rygiewicz and Andersen 1994, Andersen and Rygiewicz 1995). The resulting changes in nutrient availability or uptake may also result in altered plant growth, mediated by ozone exposure (Weinstein et al. 1991, Weinstein and Yanai 1994, Andersen and Scagel 1997). Increased atmospheric concentration of carbon dioxide and N deposition may increase plant productivity; ozone exposure may reduce or counteract these effects (Ollinger et al. 2002, Felzer et al. 2004).

Interactions with insects, pathogens, and other pollutants (Bytnerowicz and Grulke 1992) can accentuate the stress complex for plants exposed to ozone. This has been well documented for the effects of ozone on ponderosa pine. The most common stress complex includes ozone exposure, drought stress, and bark beetle injury (especially mountain pine beetle [Dendroctonus ponderosae] and western pine beetle [D. brevicomis]; Stolte 1996, Pronos et al. 1999). This interaction is particularly prominent in the mixed conifer forests of southern California and the southern Sierra Nevada. For example, during the late 1980s and early 1990s, ozone-stressed trees were subjected to several years of low precipitation. This reduced xylem pressure, and many trees were sufficiently weakened that they were susceptible to bark beetles, which proliferated through local and regional outbreaks, resulting in high levels of tree mortality in many areas.

Because lack of adequate soil moisture contributes to decreased stomatal conductance and consequently limits ozone entry into the leaf tissues (Panek and Goldstein 2001, Grulke et al. 2003, Panek 2004, Matyssek et al. 2006), dry periods exhibit decreased incidence and severity of symptoms of foliar ozone injury. Such symptoms are therefore not always higher during years having higher atmospheric ozone concentrations (Smith et al. 2003). The relationship of pollutant exposure to seasonal variation in physiological activity can have a significant influence on ozone injury in plants (Grulke 1999). The potential for pollutant uptake is higher during periods when plants are most metabolically active. However, biological defense mechanisms may be less at night when some remote locations receive peak exposures. Therefore, at some locations, exposure may contribute disproportionately to injury during the spring when soil moisture and gaseous uptake are higher, and there may be stratospheric intrusions of ozone.

3.4.6  Spatial Patterns in Ozone Effects

Most (244 parks) of the Inventory and Monitoring national parks in the conterminous United States, plus one in Alaska, were ranked by Kohut (2007a) with respect to overall risk from exposure of vegetation to ozone. This risk assessment was based on the presence of bioindicator plant species, estimated levels of ozone exposure, and estimated soil moisture conditions during periods of exposure over five years in each park. Each park was assigned a risk ranking of low, moderate, or high. These estimated park risk levels are shown in Figure 3.3 and are used in this book as an important part of the basis for estimating spatial patterns in ecological risk in the Inventory and Monitoring parks from ozone exposure. Most of the parks that were classified by Kohut (2007a) as having high risk are located in the eastern United States or in California. The former group includes Mammoth Cave, Delaware Water Gap, and Great Smoky Mountains. The latter includes Joshua Tree, Sequoia/Kings Canyon, and Yosemite. The process used by Kohut (2007a) for assigning relative risk was based on

  1. The extent and consistency by which the SUM06, W126, and N100 ozone exposure thresholds were exceeded
  2. The nature of the relationship between ozone exposure and soil moisture
  3. The extent to which soil moisture levels constrained the vegetative uptake of ozone during high exposure years
Risk ranking for exposure of vegetation in Inventory and Monitoring parks throughout the United States to ground-level ozone.

Figure 3.3   Risk ranking for exposure of vegetation in Inventory and Monitoring parks throughout the United States to ground-level ozone.

(From Kohut, R., Environ. Pollut., 149, 348, 2007.)

Kohut (2007a) judged that parks ranked as high were likely to experience foliar symptoms due to ozone exposure in most years. A ranking of moderate suggested that injury was likely to occur at some point during a five-year period. Parks ranked as low were judged to be unlikely to experience injury during any year.

Kohut’s analysis represented an examination of the major factors known to influence ozone uptake and injury and provided the best information to date on risk to plants in parks. However, it was based on data available at the time of the study, from the period 1995 to 1999. But to provide more updated information, the National Park Service-Air Resources Division developed a method for rating more recent ozone condition, based on exposure thresholds. This method does not take into account environmental factors like soil moisture. For this book, ozone data from 2005 to 2009, compiled by the National Park Service, were examined. These data were used to generate interpolated surfaces of SUM06 and W126-3-mo indices at 10 km resolution (D. Bingham, National Park Service, unpublished data, 2010). The SUM06 and W126-3-mo index values were determined for each Inventory and Monitoring park as a spatially weighted average of all the values that occurred within a park. Each was calculated as a three-month average of exposure during the 12 daytime hours. Thresholds for rating condition were based on information from the EPA’s review of the ozone standards (2007). The review considered the recommendations of an expert working group (Heck and Cowling 1997) who suggested ozone thresholds for protecting natural vegetation against foliar injury. Based on these recommendations, the National Park Service determined that a W126-3-mo ≤7 ppm-h could be considered “good” condition, with impact unlikely, and a W126-3-mo > 13 ppm-h would warrant significant concern (NPS 2010). Exposure of W126-3-mo between 7 and 13 ppm-h would warrant moderate concern. Equivalent thresholds for the SUM06 index are 8 and 15 ppm-h, respectively (NPS 2010). Thus, the breakdown is as follows:

  • W126-3-mo:
    • Good < 7 ppm-h
    • Moderate Concern 7–13 ppm-h
    • Significant Concern > 13 ppm-h
  • SUM06:
    • Good < 8 ppm-h
    • Moderate Concern 8–15 ppm-h
    • Significant Concern > 15 ppm-h

Spatial patterns in estimated cumulative ozone exposure were similar between the W126-3-mo and SUM06 indices (Figures 3.4 and 3.5). However, the areas classified as having high ozone exposure were somewhat more extensive for the SUM06 index as compared with the W126-3-mo index. Areas classified as having low ozone exposure were nearly identical using the two indices and included most of the Pacific Northwest, southern Texas, southern Florida, and the northern tier of states except around the eastern Great Lakes region.

Interpolated values of cumulative ozone exposure during the five-year period 2005–2009 using the W126-3-mo exposure index.

Figure 3.4   Interpolated values of cumulative ozone exposure during the five-year period 2005–2009 using the W126-3-mo exposure index.

Interpolated values of cumulative ozone exposure during the five-year period 2005–2009 using the SUM06 exposure index.

Figure 3.5   Interpolated values of cumulative ozone exposure during the five-year period 2005–2009 using the SUM06 exposure index.

Note that there are differences between Kohut’s (2007a) risk ranking (Figure 3.3) and the more recent National Park Service estimates (Figures 3.4 and 3.5). In particular, many parks in the arid west were estimated by Kohut to be at relatively low risk even though the exposure indices were relatively high. This difference reflects the low soil moisture conditions in these parks. Thus, there is not always a clear relationship between exposure and risk; low soil moisture limits ozone uptake, thereby reducing risk. Nevertheless, it is important to recognize that riparian vegetation communities in these arid western parks may, in fact, have sufficiently high soil moisture that risk is enhanced in locally moist areas.

3.5  Visibility Impairment

Atmospheric pollutants derived from both natural and human sources can degrade visibility and produce regional haze. In many national parks, this haze impairs the scenic vistas that are integral to a park or wilderness experience. Visibility degradation results from the scattering and absorption of visible light by gases and particles in the atmosphere. If there are no suspended particles in the air, the natural visibility is determined by the amount of light scattered by air molecules. Scattering of visible light from air molecules is called Rayleigh scattering. The light is scattered evenly in both the forward and backward direction, with a preferential scattering of shorter wavelengths; this scattering is responsible for the blueness of the sky. The value of the Raleigh scattering is a function of air density and elevation.

Visibility is a key air quality indicator. Haze can affect how far and how well we can see. National Park Service management policies prohibit the impairment of visibility in all national park units. The Clean Air Act set a specific goal for visibility protection in Class I areas:

the prevention of any future, and the remedying of any existing, impairment of visibility in mandatory Class I federal areas which impairment results from manmade air pollution (42 U.S.C. 7491).

Federal regulations require each state to develop a plan to improve visibility in Class I areas, with the goal of returning visibility to natural conditions in 2064. Natural background visibility assumes no human-caused pollution but varies with natural processes such as windblown dust, fire, volcanic activity, and biogenic emissions. Visibility is monitored by the Interagency Monitoring of Protected Visual Environments (IMPROVE) network and typically reported using the haze index measured in deciviews.*

The deciview visibility metric expresses uniform changes in haziness in terms of common increments across the entire range of visibility conditions, from pristine to extremely hazy conditions. Because each unit change in deciview represents a common change in perception, the deciview scale is like the decibel scale for sound. A one deciview change in haziness is a small but noticeable change in haziness under most circumstances when viewing scenes in Class I areas.

Current visibility estimates reflect current pollution levels and also include natural background conditions, that is, conditions that would exist in the absence of human-caused pollution. Estimates were used to rank conditions at parks discussed in this book in order to provide park managers with information on spatial differences in visibility and air pollution. Rankings range from very low haze (very good visibility) to very high haze (very poor visibility). Only parks with on-site or representative IMPROVE monitors were used in generating the visibility ranking.

3.5.1  Sources of Visibility Degradation

Ambient visibility in the national parks is typically evaluated in the context of the natural background visibility at that location. The natural visibility condition is affected by wild-land fire, volcanic emissions, wind, soil conditions, biogenic emissions from vegetation, and sea salt aerosols. Research is ongoing to further refine scientific understanding of these natural contributions to visibility impairment.

Particulate matter in the atmosphere, derived from both natural and human sources, scatters light. The amount of particle light scattering depends on the size and concentration of the particles, which are affected by their physical and chemical properties. Fine particles (particles less than 2.5 micrometers [µm] in diameter) have a greater scattering efficiency on a per mass basis than coarse particles (particles between 2.5 and 10.0 µm in diameter). Particles with sizes near the wavelength of visible light (0.4–0.7 µm) scatter light most efficiently. The chemical composition of particles in the air also plays a role in their relative light scattering efficiencies. The major categories of particulate chemical composition generally used to differentiate among fine particles that scatter light are sulfate, nitrate, organics, and soil. Sulfate and nitrate aerosols are hygroscopic. The growth of these aerosols at higher relative humidity conditions can dramatically enhance their effect on light scattering. Coarse particles are generally not speciated and are lumped together in terms of their scattering efficiency.

Sulfate and nitrate are secondary particulate matter species produced in the atmosphere, primarily from gaseous precursors. At sufficiently high humidity levels (relative humidity >85%), they are typically the most efficient particulate species contributing to haze (U.S. EPA 2009a). Particulate sulfate, as ammonium sulfate, is the dominant source of regional haze in the eastern United States and is an important contributor to haze elsewhere in the country. Most atmospheric sulfate forms from gaseous emissions of sulfur dioxide from coal-fired power plants. In coastal areas, some sulfate is derived from sea spray.

Particulate nitrate is only a minor component of remote-area regional haze in the eastern United States and in the western United States outside California. It is, however, an important contributor to haze throughout most of California and in the upper midwestern United States, especially during winter. Both nitric acid (a reaction product of oxidized N emissions) and ammonia are needed to form ammonium nitrate. Urban particulate nitrate concentrations are significantly higher than remote-area background concentrations. Particulate ammonium nitrate concentrations in California and the Midwest are commonly an order of magnitude higher than estimated natural levels. Particulate nitrate concentrations are sensitive to changes in either oxidized N emissions (from a combination of human-caused mobile and point emissions sources) or ammonia emissions (principally from agricultural sources).

Elemental C and organic carbonaceous components of particulate matter are responsible for a large fraction of the haze that occurs in many western parks. This is especially the case in the northwestern United States (U.S. EPA 2009a). Both elemental C and organics are products of incomplete combustion of fuels, including gasoline and diesel emissions and smoke from wildland fire (Figure 3.6). Organic particulate matter is also produced by the atmospheric transformation of some precursor gaseous emissions. Smoke plume particulates from large wildfires dominate many of the worst haze periods in the western United States. Particulate matter from elemental and organic C is generally the largest component of urban excess fine particulate matter. Western urban areas have more than twice the average concentrations of carbonaceous particulate matter compared with remote areas in the same region. In eastern urban areas, fine particulate matter is dominated by sulfate and organic C components, though the usually high relative humidity in the East causes the hydrated sulfate particles to contribute about twice as much of the urban haze as that caused by the carbonaceous particulate matter (U.S. EPA 2009a).

Fire (prescribed, accidental, natural) is an important source of air pollutants, including coarse particulate matter, N oxides, and revolatilized Hg.

Figure 3.6   Fire (prescribed, accidental, natural) is an important source of air pollutants, including coarse particulate matter, N oxides, and revolatilized Hg.

This photo was taken of the 1988 fire in Yellowstone National Park. (National Park Service photo by Jim Peaco, 1988.)

Both fine soil and coarse particles are significant contributors to haze in the arid southwestern United States where they typically contribute a quarter to a third of the haze. Coarse mass elements usually contribute twice as much haze as fine soil in this region. Coarse mass concentrations are also high in the central Great Plains. The relative contribution to haze by the high coarse mass in the Great Plains is smaller, however, because of the relatively high concentrations of sulfate and nitrate particulate matter in that region.

Dust is an important contributor to haze in the West. A comprehensive assessment (U.S. EPA 2009a) of the 610 worst sampled haze episodes over a three-year period in the western United States, where dust was the major contributor, categorized each site/sample period into four causal groups: Asian dust, local windblown dust, transported regional windblown dust, and undetermined dust (i.e., not in one of the three other groups). Most dust days occurred at sites in Arizona, New Mexico, Colorado, western Texas, and southern California, and these were dominated by local and regionally transported windblown dust (U.S. EPA 2009a). Asian dust caused only a few of the worst dust days during the three-year assessment period, though it was an important source of dust for the more northern regions of the West and was responsible for 10%–40% of their worst dust periods.

Organic particulates in the atmosphere are diverse in their makeup and sources. Vegetation itself is an important source of hydrocarbon aerosols. Terpenes, released from tree foliage, may react in the atmosphere to form submicron particles. These naturally generated organic particles contribute significantly to the blue haze aerosols formed naturally over some forested areas (Geron et al. 2000, U.S. EPA 2004).

Some gases can also absorb light. Nitrogen dioxide is the only major visible light-absorbing gas in the lower atmosphere. It usually does not occur in sufficient concentrations in remote areas to make a major contribution to the total light absorption. Elemental C is the dominant light-absorbing particle in the lower atmosphere.

3.5.2  Visibility Metrics

To quantify visibility conditions and estimate the degree of degradation caused by various air pollutants, several visibility scales/metrics can be employed. Depending on the application, metrics may include a contrast and color difference index, light extinction coefficient, visual range, or degree of haziness.

The light extinction coefficient, often called extinction, represents the attenuation of light per unit distance of travel in some medium, such as air. It is commonly measured in inverse length (e.g., inverse kilometers [km−1] or inverse mega meters [Mm−1]). The extinction reflects attenuation of light due to scattering and absorption of light by aerosols/particles or gases. The best possible visibility (extinction-free, or Rayleigh conditions) corresponds to an extinction of approximately 10 Mm−1, although this value is spatially variable.

The extinction is not linear with respect to increases or decreases in perceived visual air quality. For example, a given change in extinction can result in a scene change either unnoticeably small or very apparent depending on the baseline visibility conditions. Therefore, another visibility metric, the haziness index (expressed as deciviews), was defined to index a constant fractional change in the extinction to visual perception (Pitchford and Malm 1994). The haze value in deciviews is a log-transformation of extinction that provides a perceptually uniform haze metric. The advantage of this characterization is that equal changes in deciview are equally perceptible to the human eye across different baseline conditions. Higher haziness index values signify poorer visibility. The EPA has adopted the deciview metric for determining progress in improving visibility under the Regional Haze Rule described in the following text. The deciview is often used in describing overall visibility condition or haze and in tracking changes in visibility. A 1-deciview change would be a small but likely perceptible change in uniform haze conditions, regardless of the baseline visibility level (Pitchford and Malm 1994).

Although the deciview value is widely used to describe haze conditions and monitor trends in visibility, extinction is the characterization most used by scientists concerned with the assessment of the causes of visibility degradation. Extinction can be directly calculated from light transmittance measurements (measured extinction) or derived from measured atmospheric particle concentrations using linear relationships between the concentrations of particles and gases and their contribution to the extinction coefficient (calculated extinction). Understanding these relationships provides a method of estimating how visibility would change with changes in the concentrations of each of these atmospheric constituents. This methodology, known as “extinction budget analysis,” is important for assessing the visibility consequences of proposed pollutant emissions sources or for determining the extent of pollution control required to meet a desired visibility condition (Sullivan et al. 2003). Each haze-causing species in the atmosphere can be measured, and the amount of light extinction that it causes can be calculated at a given location and time.

Uptake of water by fine aerosol particles in the atmosphere has been investigated at remote natural settings, including within three national parks: Great Smoky Mountains, Grand Canyon, and Big Bend (Day and Malm 2001). Inorganic sulfate and ammonium salts can absorb considerable water in moist atmospheres. This uptake and release of atmospheric water in response to changes in relative humidity can influence the light scattering properties of aerosols (Horvath 1996, Tang 1996, Day et al. 2000). Light scattering can increase twofold or more at relative humidity above 80% (Rood et al. 1986, Day et al. 2000). Organic C is also an important vehicle for water uptake by atmospheric aerosols (Day and Malm 2001).

3.5.3  Visibility Monitoring

The IMPROVE Program is a cooperative monitoring effort that is governed by a steering committee comprising representatives from federal and regional-state organizations. It was established in 1985 to aid in the creation of federal and state implementation plans for the protection of visibility in mandatory Class I areas, as stipulated in the 1977 Clean Air Act Amendments. A complete IMPROVE monitoring station includes fine and coarse particle monitoring and optical monitoring and may have previously also included view monitoring with photography.

There are 187 sites included in the IMPROVE database (downloaded from http://vista.cira.colostate.edu/IMPROVE/Default.htm). Fifty-five of these sites are located in national park units, representing 53 individual Inventory and Monitoring parks. Average deciview values were calculated for some analyses presented in this book over a five-year period (2004–2008) for those IMPROVE sites that are located in or near the Inventory and Monitoring parks.

Effects on visibility vary spatially across the United States. Most impairment occurs as regional haze, which is generally most pronounced in the eastern United States and southern California. In the East, ammonium sulfate contributes at least half of the visibility impairment at most Class I areas, and ammonium sulfate is a major contributor to visibility impairment throughout the United States (Hand et al. 2011). The contribution from ammonium nitrate is highest in central and southern California and in parts of the Midwest. The contribution from organic C is highest in the Southeast. The contributions from coarse particles and fine soil are highest in the arid southwest (Debell et al. 2006, U.S. Forest Service et al. 2010, Hand et al. 2011).

Since the early 1990s, visibility throughout most remote areas in the conterminous United States has improved substantially. Hand et al. (2014) computed extinction on the haziest 20% of days following Regional Haze Rule guidelines for three major regions: East, Intermountain/Southwest, and West Coast. During the two-decade period, 1992–2011, the haze level on the regional mean 20% haziest days decreased by 52% in the East and 20% in the West Coast region and remained unchanged in the Intermountain/Southwest region. Improvements for the West Coast region accelerated to a −3.5%/yr decrease in extinction during the second decade of the monitoring period. Park-specific visibility condition and trends are available at http://www.nature.nps.gov/air/data/products/parks/index.cfm.

3.5.3.1  Particle Monitoring

Particle monitoring provides concentration measurements of atmospheric particles that contribute to visibility impairment. Four independent IMPROVE sampling modules are used to automatically collect 24-hour samples of suspended particles every three days by drawing in air and collecting suspended particles on filters. The filters are later analyzed to determine the chemical makeup of the suspended particles. Three of the four samplers (modules A, B, and C) collect fine particles with diameters <2.5 µm. The fourth sampler (module D) collects particles with diameters up to 10 µm. Module A filters are analyzed to determine the gravimetric mass and elemental composition of the collected particles. Module B filters are analyzed specifically for sulfate, nitrate, and chloride ions. Module C filters are analyzed for organic material and light absorbing C. The gravimetric mass of coarse particles (2.5–10.0 µm) is determined by subtracting the module A gravimetric mass from the module D gravimetric mass.

3.5.3.2  Optical Monitoring

Optical monitoring provides a direct quantitative measure of extinction that represents overall visibility conditions. Because water vapor in combination with suspended particles can affect visibility, optical stations also record temperature and relative humidity. Optical monitoring uses ambient long-path transmissometers or ambient nephelometers to collect hourly averaged data. Transmissometers measure the amount of light transmitted through the atmosphere over a known distance (between 0.5 and 10.0 km) between a light source of known intensity (transmitter) and a light measurement device (receiver). The transmission measurements are electronically converted to hourly averaged extinction (scattering plus absorption). Ambient nephelometers draw air into a chamber and measure the scattering component of light extinction. Optical measurements of extinction and scattering include meteorological events such as cloud cover and rain, but the data are filtered by flagging as invalid those data points collected under conditions of high relative humidity (>90%). This filtering process is assumed to remove the largest effects of weather from the dataset. Optical data also provide concurrent, independent measurement of extinction to compare with calculations made using particle data. Transmissometers have gradually been phased out of the IMPROVE program, due to their relatively high expense compared to nephelometers.

3.5.3.3  View Monitoring

View, or scenic, monitoring was formerly accomplished with automated camera systems. Cameras typically took three photographs a day (9:00, 12:00, and 15:00) of selected scenes, which formed a photographic record of characteristic visibility conditions. These photographs reveal how differences in visibility affect vistas in a particular park. Based on April 1995 recommendations of the IMPROVE Steering Committee, view monitoring was discontinued at all National Park Service Class I areas that had a five-year or greater photographic monitoring record. Webcams have been installed at about 20 parks and are linked to air quality monitoring stations (http://www.nature.nps.gov/air/WebCams/index.cfm).

Photos of vistas within many of the Inventory and Monitoring parks were downloaded for this book from http://vista.cira.colostate.edu/IMPROVE/Data/IMPROVE/Data_IMPRPhot.htm. A series of photos representing the best 20%, worst 20%, and annual average visibility were selected and are included as plates associated with some of the case study chapters. If a photo was not available for the exact deciview value needed to correspond with average haze measurements over the period 2004–2008 within a given park, the closest deciview photo was selected. All photos in the series were taken at the same time of day.

3.5.3.4  Regional Haze Rule

In 1977, Congress established a national goal of no human-caused visibility impairment in Class I areas by 2064 and in 1999 promulgated a rule requiring states to develop and implement plans to make continuous progress toward that goal. The EPA provided detailed guidance for assessing regional haze (U.S. EPA 2001a). The assessment of progress toward the national goal requires long-term particle monitoring on which to base estimates of natural*

“Natural condition” is a term used in the Clean Air Act, which means that no human-caused pollution can impair visibility.

and current visibility conditions. This long-term monitoring is provided by the IMPROVE Program.

The Regional Haze Rule requires states (and tribes who choose to participate) to review how pollution emissions within the state affect visibility in Class I areas. The Regional Haze Rule also requires states to make “reasonable progress” in reducing any effect that air pollution has on visibility conditions in Class I areas and to prevent future impairment of visibility. The states are required by the rule to analyze a linear pathway that takes the Class I areas from current conditions to “natural conditions.” The response to these regulations, while aimed at Class I areas, is expected to improve regional visibility conditions throughout the country.

The Regional Haze Rule requires emissions reductions that will reduce the human-caused contributors to regional haze at 156 of the largest national parks, wilderness areas, and national wildlife refuges in the United States. The long-term goal is to achieve visibility that represents natural conditions, unimpacted by human-caused emissions, by the year 2064. In order to comply with requirements of the Regional Haze Rule, multistate planning organizations were established to conduct the technical analysis used by state air agencies, as follows:

  • Western Regional Air Partnership
  • Central Regional Air Planning Association
  • Midwest Regional Planning Organization
  • Mid-Atlantic/Northeast Visibility Union
  • Visibility Improvement State and Tribal Association of the Southeast

Each state must describe ambient visibility conditions, based on the best and worst visibility days for the five baseline years 2000–2004. Because the IMPROVE sampler operates every 3 days, there are data for about 121 days/yr at each site. The 20% highest haze days (approximately 24 haziest days during each year) and the 20% lowest haze days (24 clearest days) are averaged for each baseline year. Each state also must demonstrate that the 20% least impaired days do not degrade from the baseline on days when visibility is mainly affected by natural emissions sources.

Under the Regional Haze Rule, states must estimate the uniform rate of haze reduction that would allow them to progress from the current conditions to the required natural haze level in 2064. Haze conditions for this requirement are expressed as the five-year mean of the annual 20% most impaired visibility conditions at each protected Class I area. States also must document that the five-year mean of the annual 20% clearest days does not deteriorate over time at the protected areas.

In order for states to comply with the Regional Haze Rule, they must estimate haze levels at Class I areas that represent the average of the 20% haziest days so that the 60-year uniform rate of progress can be specified. A default approach was described by the EPA (2001a) to accomplish that. It was based on the original IMPROVE algorithm (Sisler 1996) for estimating extinction. Thus, the EPA provided default estimates of natural background visibility for the mean, clearest, and haziest days for each of the protected areas. States could choose to use these default values or choose to use a refined approach.

The default approach specified by the EPA for estimating natural haze conditions was subsequently reviewed and found to be flawed in multiple respects (Ryan et al. 2005, Pitchford et al. 2007). Problems were identified in the method used to calculate percentiles, and the default approach did not adequately adjust for light scattering by sea salt at coastal locations or the effects of elevation.

The IMPROVE algorithm was revised in 2005 to address some of these problem areas. The use of the revised algorithm for estimating ambient haze also requires the use of the same algorithm for estimating natural conditions in order to avoid biasing the calculation of the required uniform rate of progress glide path needed to accomplish the visibility improvements mandated in the Regional Haze Rule. The revised approach is not without problems, however. For example, it assumes two estimates of natural haze-causing atmospheric species concentrations, one for the East and one for the West. As a consequence, there is a rather steep line of demarcation between the East and the West in the background haze estimates. There may not be sufficient data to justify breaking down the country into smaller units at this time. Additional research may be needed to further improve the approach for specifying natural visibility conditions.

Trend analyses show that over short (2000–2008) and long (1989–2008) time periods, the mass concentrations of major aerosol species have decreased at many IMPROVE sites. These decreasing trends (improving visibility) were largest for the lowest concentrations and during winter seasons and may not be typical of all sites and species (Hand et al. 2011). However, these results are consistent with 1999–2008 trends at National Park Service sites, which showed larger decreasing trends in deciview on the clearest days compared to the haziest days (NPS 2010).

3.5.3.5  Spatial Patterns in Visibility Impairment

A regional haze dataset was downloaded for the analysis provided in this book from http://vista.cira.colostate.edu/IMPROVE/Default.htm, based on the revised IMPROVE algorithm. Out of this dataset, measured haze values for the years 2004–2008 were extracted. Five-year means of the clearest, haziest, and average 20% visibility days were summarized for the following light extinctions: ammonium sulfate, ammonium nitrate, organic mass, light absorbing C, fine soil, coarse mass, and sea salt.

Relative ranking of haze measurement values, expressed in deciviews, from the IMPROVE sites is provided in Figures 3.7 through 3.9 as five-year averages over the period 2004–2008. Only sites having monitoring data during the period 2004–2008 are included. Results are presented for the 20% of the monitored days having the lowest haze (clearest visibility) at each site (Figure 3.7), the 20% of the days having highest haze (Figure 3.8), and the average 20% days (Figure 3.9). Ambient haze measurements must be interpreted within the context of estimated natural haze levels. In general, parks that exhibited high levels of ambient haze were also estimated to have relatively high natural haze levels.

Relative ranking of haze measurements (in deciviews [dv]) at IMPROVE sites for the 20% clearest days during the five-year period 2004–2008.

Figure 3.7   Relative ranking of haze measurements (in deciviews [dv]) at IMPROVE sites for the 20% clearest days during the five-year period 2004–2008.

Low deciview values correspond to better visibility; as deciview increases, visibility decreases.
Relative ranking of haze measurements (in deciviews [dv]) at IMPROVE sites for the 20% haziest days during the five-year period 2004–2008.

Figure 3.8   Relative ranking of haze measurements (in deciviews [dv]) at IMPROVE sites for the 20% haziest days during the five-year period 2004–2008.

Low deciview values correspond to better visibility; as deciview increases, visibility decreases.
Relative ranking of haze measurements (in deciviews [dv]) at IMPROVE sites, based on the average days at each site.

Figure 3.9   Relative ranking of haze measurements (in deciviews [dv]) at IMPROVE sites, based on the average days at each site.

Low deciview values correspond to better visibility; as deciview increases, visibility decreases.

In order to rank measured haze values into five classes ranging from very low to very high, deciview values for each group were divided using a geometrical interval. This classification scheme is useful for ranking continuous datasets that are not normally distributed. It creates intervals by minimizing the variance among values within each class and results in classes that contain approximately the same number of parks. The ranking for most sites was based on five years of data.

Extinction budgets are provided in the case study chapters of this analysis for each of the park units that contains an IMPROVE monitoring site or has a nearby representative site having data for the time period 2004–2008. The contribution of each aerosol type to extinction is shown relative to particulate light extinction, excluding Rayleigh (blue sky) scattering. This approach was taken because the focus of this book is on the components of haze, rather than on all contributors to extinction.

3.6  Effects of Exposure to Airborne Toxics

Just as for acid precursors and nutrients, atmospheric emissions of toxic substances can affect resources in parks that are downwind of emission sources. Researchers have become increasingly concerned about the potential susceptibility of resources in the national parks to airborne toxic contaminants. These chemical pollutants can be transported by the wind and deposited on land far from where they originate. Relevant toxic chemicals include Hg, various pesticides, and industrial contaminants. Some have the potential to bioaccumulate to relatively high concentrations at upper trophic levels of the food web. Combustion products, including metals and polycyclic aromatic hydrocarbons, may also be important atmospherically deposited toxic and/or carcinogenic (cancer-causing) compounds. Adverse effects on sensitive animal species can include reproductive impairment, reduced growth and health, neurological damage, and behavioral changes. Humans consuming contaminated fish and wildlife may also be affected.

3.6.1  Toxic Substances of Concern for This Book

The most thoroughly studied airborne toxin that affects national parklands is Hg. It is a heavy metal that occurs naturally in several forms. Elemental Hg is released from sources in the earth’s crust into the global environment through volcanic and geothermal activity and the weathering of rocks. It is also being emitted by human emissions sources, primarily coal-fired power plants and incinerators. The most important route of entry of Hg into remote national park ecosystems is atmospheric deposition of inorganic Hg (Fitzgerald et al. 1998).

Once released into the atmosphere, Hg can be deposited to the earth’s surface and transformed through natural processes into a toxic form, methyl Hg (Ullrich et al. 2001), that can bioaccumulate in food webs. Contamination of aquatic ecosystems by Hg has prompted many states to issue fish consumption advisories and has reduced the benefits provided by fisheries resources in many inland and coastal waters throughout the United States.

A variety of factors influence Hg deposition, fate, and transport. Such factors relate in particular to speciation of the Hg that is emitted, the forms in which it is deposited from the atmosphere, and transformations that occur within the atmosphere and within the aquatic, transitional, and terrestrial compartments of the receiving watersheds (http://www3.epa.gov/mats/actions.html).

Persistent organic pollutants constitute another class of potentially toxic contaminants. Many are semivolatile and therefore are readily emitted into the atmosphere and subsequently deposited from the atmosphere to the ground surface. They are not efficiently degraded in the environment and can be concentrated in the food web toward higher trophic levels. They can accumulate to toxic levels in piscivorous fish and wildlife, wading birds, and humans. Results of persistent organic pollutant biomagnification can include reproductive disruption, neurological disorders, and mortality.

Many persistent organic pollutants have high toxicity, are relatively insoluble in water, and tend to concentrate at each level of the food web (Landers et al. 2010). These compounds include PCBs, dioxins, dichlorodiphenyltrichloroethane (DDT) and its breakdown products, chlordane, dieldrin, endosulfan, polycyclic aromatic hydrocarbons, and others. Although the use of many of these compounds is now restricted, their presence in the environment has human health, environmental, and economic impacts (Clair et al. 2011). Flame retardants (particularly for household goods), developed and deployed to respond to stricter fire regulations, are also of increasing concern. For example, levels of polybrominated diphenylether flame retardants have increased dramatically in smelt in the Great Lakes (Chernyak et al. 2005).

3.6.2  Biomagnification

Biomagnification is the progressive accumulation of chemicals with increasing trophic level (LeBlanc 1995). It describes the process of chemical accumulation in the food web. Pollutants that biomagnify accumulate in body fat or muscle tissue. Organic (methylated) Hg is the most likely metal to biomagnify, in part because organisms can efficiently assimilate methyl Hg and it is slowly eliminated (Reinfelder et al. 1998, Croteau et al. 2005).

Atmospheric emissions of semivolatile organic compounds and metals are of interest primarily because of their detrimental effects on biota, particularly the more sensitive species that can be found in remote national parks. The WACAP study (Landers et al. 2008) showed significant biomagnification of these pollutants in all parks studied; fish showed semivolatile organic compound concentrations that were five to seven orders of magnitude higher than concentrations in abiotic components sampled (air, snow, and water). Concentrations of polycyclic aromatic hydrocarbons, current-use pesticides, and hexachlorocyclohexanes tended to be highest in vegetation, whereas fish tissue accumulated mostly PCBs, chlordanes, DDT, and dieldrin.

The bioavailability of methyl Hg in the environment is also of particular importance to humans who can accumulate high levels of methyl Hg from eating contaminated fish. Avoiding exposure to Hg is particularly important for pregnant women and nursing mothers. Mercury poisoning can cause neurological impairment in children, leading to effects on memory, visual and spatial ability, information processing, and general intelligence (Mahaffey 2005).

Because atmospheric Hg must be methylated in order to bioaccumulate in the food web, significant efforts have been made to understand the bacteria responsible for this chemical transformation. Sulfate-reducing bacteria have been shown to be the main agents of Hg methylation in sediments (Gilmour et al. 1992) and wetlands (St. Louis et al. 1994, Branfireun et al. 1999), although Fe-reducing bacteria can also be important. In ecosystems that are sulfate-poor, the total amount of biologically available S controls the activity of these bacteria and thereby in part the rate of methyl Hg production. Atmospheric sulfate deposition, leading to the stimulation of sulfate-reducing bacteria and increased Hg methylation, may have caused or contributed to the observed postindustrial amplification of methyl Hg concentrations in fish (Jeremiason et al. 2006). Studies have demonstrated increased levels of methyl Hg production with experimental addition of sulfate (Gilmour and Henry 1991, Gilmour et al. 1992, Branfireun et al. 1999, Jeremiason et al. 2006). In addition, fish have shown increased methyl Hg burdens in acidified lakes as compared with nonacidified lakes receiving similar atmospheric Hg deposition (Gilmour and Henry 1991). Therefore, reduced sulfate emissions and deposition may be expected to cause a corresponding reduction in Hg methylation and bioavailability (Jeremiason et al. 2006).

The WACAP analyzed salmonid fish tissue for contaminants and biomarkers to assess fish condition. Vitellogenin concentration was also analyzed as a biomarker indicating exposure to estrogen and estrogen-mimicking chemicals. Many semivolatile organic compound contaminants have been shown to be endocrine-disrupting compounds that interfere with natural hormonal regulation (e.g., dieldrin, PCBs, endosulfan, DDT, polycyclic aromatic hydrocarbons, etc.). The levels of vitellogenin in male fish can constitute a helpful biomarker that indicates exposure to these contaminants.

In order to evaluate possible human health concerns due to biomagnified contaminant concentrations in fish, the WACAP study measured contaminant concentrations in 136 fish from 14 lakes in the eight core parks included in the study and compared their findings with the EPA’s Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisories. They found that over half of study fish (77) in 11 of the lakes exceeded subsistence fishing human health concentration thresholds for the contaminants dieldrin and/or the DDT breakdown product p,p-dichlorodiphenyldichloroethylene (DDE). Nine of the lakes demonstrated mean fish dieldrin and p,p-DDE that exceeded human contaminant health thresholds for subsistence fishing. These EPA thresholds were not exceeded by any other semivolatile organic compound contaminant concentrations in fish.

High concentrations of contaminants in fish can be detrimental to piscivorous wildlife. The Hg burdens in fish at many WACAP sites exceeded published health thresholds for mink (Mustela vison), river otter (Lutra canadensis), and belted kingfisher (Megaceryle alcyon). Although the production of DDT was banned in the United States in 1972, concentrations of the DDT and its by-products in fish remained above the health threshold for kingfisher at two sites in Sequoia/Kings Canyon National Park and one in Glacier National Park. Dieldrin concentrations in fish did not exceed the wildlife health thresholds in any of the parks. Dieldrin production in the United States was banned in 1987, following a 1974 ban of the pesticide for agricultural use. Rocky Mountain National Park contained fish with the highest dieldrin concentrations of any park. This may have resulted from industrial production of dieldrin in Denver between 1952 and 1982 (Landers et al. 2010).

For lakes studied in WACAP, fish in Burial Lake in the arctic Noatak National Preserve bioaccumulated the highest concentration of Hg. The other arctic lake sampled (Matcharak Lake) also contained fish with comparatively high Hg concentrations. Snow, sediments, and vegetation in these parks showed low Hg concentrations, suggesting that the high Hg concentrations found in fish were a result of other characteristics of the watershed, such as efficient transformation of atmospheric Hg into methyl Hg. These two arctic lakes both showed fish with Hg concentrations that exceeded the EPA consumption criteria.

Plant foliage can accumulate elemental Hg over time in response to air and soil exposure (Ericksen et al. 2003, Frescholtz et al. 2003). Although this Hg does not harm the plants, it does affect Hg cycling and bioavailability. Foliar/air Hg exchange has been shown to be dynamic and bidirectional (Millhollen et al. 2006). These investigators compared foliar Hg accumulation over time in three tree species with fluxes measured using a plant gas-exchange system subsequent to soil amendment with mercury chloride. Root tissue Hg concentrations were strongly correlated with soil Hg concentrations, suggesting that below-ground accumulation of Hg by roots may be an important process in the biogeo-chemical cycling of Hg in soil systems. Nevertheless, measured foliar Hg fluxes indicated that the deposition of atmospheric Hg constituted the dominant flux of Hg to the leaf surface (Millhollen et al. 2006).

Persistent organic pollutants can move in successive steps of evaporation, atmospheric transport, and deposition toward colder areas. This is called cold condensation; it can be responsible for high concentrations of persistent organic pollutants in remote arctic and alpine regions (Simonich and Hites 1995, Blais et al. 1998), including in some western national parks. These persistent organic pollutants can then accumulate and biomagnify at higher levels of the food web, eventually potentially impacting fish and wildlife reproduction, behavior, growth, and mortality.

3.6.3  Effects of Atmospherically Deposited Toxic Substances

3.6.3.1  Effects on Fish

Increased body burdens of Hg in fish can lead to decreased reproductive success and behavioral alterations. Yellow perch (Perca flavescens) are widely distributed and are often studied as a primary indicator species for Hg contamination in the environment. Ecological effects thresholds for Hg concentration in fish prey have been proposed at levels lower than human health thresholds.

Mercury concentrations in fish were generally lower at WACAP sites in the western United States than in fish from lakes previously sampled in the midwestern and northeastern United States. Nevertheless, concentrations in fish from some WACAP lakes exceeded the EPA thresholds for human consumption.

Histopathological biomarkers provide evidence regarding the effects of toxins on individual organisms. One such biomarker is the macrophage aggregate, a focal accumulation of macrophages in the spleen, kidney, or liver of fish that indicates an immune system response to environmental conditions. The macrophage aggregates are formed in response to tissue damage (Schwindt et al. 2008). Significant correlations have been found between increased macrophage aggregates in fish from polluted waters and fish exposed to Hg or other metals (Handy and Penrice 1993, Meinelt et al. 1997, Manera et al. 2000, Fournie et al. 2001, Khan 2003, Capps et al. 2004). Schwindt et al. (2008) demonstrated an association between Hg and trout kidney and spleen tissue damage, as indicated by increased macrophage aggregate occurrence. This research was conducted on four species of trout collected from 14 lakes in the WACAP national parks or preserves in the western United States. This result suggests that Hg and/or other contaminants might adversely impact fish that inhabit remote and protected lakes in western national parks. Some “intersex” fish (male and female reproductive structures in the same fish) were found in Rocky Mountain National Park and Glacier National Park, but not in any of the other six parks sampled in the WACAP study. The causes and consequences of this reproductive disruption remain to be determined (Schwindt et al. 2009).

3.6.3.2  Effects on Humans

The EPA conducted the National Study of Chemical Residues in Lake Fish Tissue, a screening-level survey of chemical residues in fish throughout the conterminous United States (U.S. EPA 2009b). Sampling sites were selected using a random approach, and results are therefore applicable to numbers and percentages of lakes regionally and nationally. The focus was on identifying chemical concentrations in fish that were above levels of potential concern for humans and piscivorous wildlife (Table 3.4). Fish tissues were analyzed for 268 persistent, bioaccumulative, and toxic chemicals, including Hg, PCB congeners, dioxins and furans, and a variety of pesticides and other semivolatile organic compounds (U.S. EPA 2009b). These pollutants have been delivered to fish in the sampled lakes from both atmospheric and nonatmospheric sources. Over a sampling period of four years, 486 predator fish (fillets) and 395 bottom dwellers (whole body analysis) were analyzed from 500 sampling locations. Results were extrapolated to an estimated 76,559 lakes for predators and 46,190 lakes for bottom dwellers.

Table 3.4   Estimated Numbers and Percentages of Lakes, from among 76,559 Target Lakes in the Conterminous United States That Had Predator Fish Species Having Chemical Concentrations above Screening Values for Protecting Human Health, Based on a Survey by the EPA of Fish in 500 Lakes

Lakes above Human Health Screening Values

Chemical

Screening Value

Percent of Population

Number of Lakes

Mercury

0.3 ppm

48.8

36,422

PCBs

12 ppb

16.8

12,886

Dioxins and Furans

0.15 parts per trillion

7.6

5,356

DDT

69 ppb

1.7

1,329

Chlordane

67 ppb

0.3

235

Mercury and PCBs were detected in fish collected from all sampled lakes; dioxins and furans were detected in 81% of the predator fish samples and 99% of the bottom-dweller samples. Other contaminants in fish were not as widely distributed. Analyses of predator fish fillets indicated that nearly half (36,422 lakes) of the sampled population had Hg tissue concentrations that exceeded the Hg human health screening value of 0.3 ppm. Nearly 17% of the sampled population had PCB compounds tissue concentrations above the 12 ppb human health screening value. Smaller percentages of the sampled lakes exceeded screening values of dioxin and furan concentrations, DDT, and chlordane.

Flanagan-Pritz et al. (2014) analyzed fish pesticide data collected in 14 national parks in Alaska and the western United States. The analysis found that concentrations of some historic-use pesticides exceeded the EPA guidelines for human subsistence fish consumers at 13 of 14 parks. Eagles-Smith et al. (2014) examined over 1400 fish across 21 national parks in the western United States. They found that total Hg concentrations in 68% of the fish sampled were above exposure levels recommended by the Great Lakes Advisory Group as being unsuitable for unlimited consumption by humans.

All 50 states issued Hg advisories for human fish consumption in 2008 (Fenn et al. 2011). The U.S. Environmental Protection Agency (2001b) recommended a human health criterion of 0.3 ppm in fish and shellfish tissue to protect the general population. More stringent restrictions may be appropriate for women of child-bearing age and children. Some states, including Maine and Minnesota, use a more restrictive human health standard of 0.2 ppm in fish.

3.6.3.3  Effects on Piscivorous Wildlife

Methyl Hg causes damage to the vertebrate central nervous system. In addition, low-level dietary Hg exposures that cause no measureable effects on adult birds can impair egg fertility, hatchling survival, and reproductive success (Scheuhammer 1991). In reproducing females of fish, birds, and piscivorous mammals, methyl Hg passes directly to developing egg or embryo (Evers et al. 2003, Hammerschmidt and Sandheinrich 2005, Heinz et al. 2010). These early life stages are more sensitive than adults to the adverse effects of methyl Hg exposure (Evers et al. 2003, Wiener et al. 2003, Scheuhammer et al. 2007).

Eagles-Smith et al. (2014) found that in 21 western U.S. national parks, total Hg concentrations in 35% of sampled fish exceeded a benchmark for risk to highly sensitive fish-consuming birds. Flanagan-Pritz et al. (2014) found that historic-use pesticides exceeded the EPA’s guidelines for wildlife (kingfisher) health thresholds at 13 of 14 parks in the western United States and Alaska.

Reproductive effects on fish-eating birds have been reported at fish Hg levels of 0.16 ppm (Fenn et al. 2011). In piscivorous birds, including loons (Gavia spp.) and bald eagles (Haliaeetus leucocephalus), Hg poisoning can lead to brain lesions, reduced reproductive success, increased chick mortality, spinal cord collapse, and neuromuscular problems. The common loon (Gavia immer) has been widely used as a Hg bioaccumulation indicator for risk to piscivorous birds (Evers et al. 2008, 2011a). It is listed as threatened in Michigan and as a species of special concern in New York and Wisconsin. Because loons feed almost exclusively on fish and crayfish and are relatively long-lived, they can bioaccumulate a substantial amount of Hg (Evers et al. 2011b). Nevertheless, common loons are considered less sensitive to Hg than some other piscivorous birds. They do, however, concentrate Hg in their blood to levels that are high enough to impair the reproduction at some locations (Burgess and Meyer 2008, Evers et al. 2011a). Belted kingfisher has also been used as an indicator of Hg pollution. Kingfishers are piscivorous and widely distributed, occurring in many national parks, including many of the WACAP parks. Lazorchak et al. (2003) developed fish Hg contaminant thresholds for kingfishers; these thresholds were exceeded in nearly all fish in all WACAP lakes (Landers et al. 2010). Average concentrations of Hg in fish in many parks studied by WACAP exceeded risk thresholds for health impacts to fish-eating birds and mammals (Landers et al. 2010).

Mink has been proposed as a sentinel species indicating toxic contaminant exposure (Basu et al. 2007, Martin et al. 2011). This species constitutes a good candidate for biomonitoring due to its wide distribution and abundance, upper level trophic status, and availability of tissue samples from trappers (Mason and Wren 2001). River otter is also widely distributed and a good indicator of Hg contamination. Hg levels in fish from WACAP lakes often exceeded the health thresholds (Lazorchak et al. 2003) for both mink and river otter (Landers et al. 2010).

As more research has been conducted during the last few decades, high concentrations of Hg have been increasingly documented in more species of wildlife, especially across the Great Lakes region and into the northeastern United States. Recent research has also decreased the estimates of effects levels, suggesting sublethal effects on wildlife (including effects on reproduction and biochemical processes) at whole-fish concentrations of 0.2–0.3 ppm (Beckvar et al. 2005, Dillon et al. 2010, Sandheinrich and Wiener 2011).

3.6.4  Spatial Patterns in Exposure to Toxic Substances

3.6.4.1  Mercury

Spatial patterns in Inventory and Monitoring park sensitivity to potential damage from Hg exposure across the United States can be evaluated, in part, using maps of interpolated wet Hg deposition. Wet deposition data are currently available from the Mercury Deposition Network at monitoring sites across the United States. The spatial coverage of the monitoring data is too sparse in some regions to allow rigorous interpolation of site-specific measurements, but the Mercury Deposition Network does provide interpolations for much of the United States. These data reflect only wet deposition. Dry Hg deposition data are not available regionally. To evaluate likely patterns in atmospheric Hg deposition across the Inventory and Monitoring parks, wet Hg deposition estimates are presented in Figure 2.4 for the year 2013 from the Mercury Deposition Network. In general, wet deposition of Hg is highest in Florida, the Gulf States, and north into the Heartland. High deposition also occurs in mountainous areas, including the Rockies, Sierra Nevada, and Cascades, reflecting the higher levels of precipitation in those areas. Wet Hg deposition tends to be lower in the West (at lower elevations), Upper Midwest, Northeast, and Mid-Atlantic regions. Although dry deposition estimates are not available for most areas, limited research indicates that dry Hg deposition can equal or exceed wet deposition, especially in arid regions. In areas of New Mexico, estimated dry Hg deposition was about 60% of total (wet + dry) deposition (Caldwell et al. 2006).

The U.S. Geological Survey (last modified February 20, 2015) predicted surface water methyl Hg concentrations for all hydrologic units included in a National Park Service Inventory and Monitoring Program unit where sufficient empirical data were available to generate a prediction. Predictions were generated using a partial least squares regression model, with input parameters selected based on literature consensus. Partial least squares is a shrinkage method in which a continuous portion of the information contained in linear combinations of the variables (components) is used for regression. Twelve datasets representing water-quality sampling sites from across the conterminous United States were compiled representing various projects having surface water data for pH, sulfate, and organic C together with methyl Hg. Methyl Hg analyses for all data were performed by the Wisconsin Mercury Research Laboratory. Predictions of methyl Hg were made using regression on four selected independent variables: pH, sulfate, total organic C, and watershed percent wetland. Leverage calculations indicated that total organic C was most important relative to the other parameters in describing the variability of methyl Hg concentration. Predicted methyl Hg concentrations were obtained by applying the prediction dataset to the partial least squares model. Total Hg concentrations were not included in the calibration of the model. Therefore, this model represents only the potential sensitivities of ecosystems to surface water methyl Hg contamination providing that sufficient quantities of inorganic Hg are available for methylation.

Predicted methyl Hg concentrations in surface waters varied across the conterminous United States, based on U.S. Geological Survey (2015) estimates for eight-digit hydrologic unit codes containing Inventory and Monitoring parklands (Figure 3.10). Geographic hot spots containing relatively high estimates of methyl Hg occurred throughout the southeast coastal region, upper midwest, intermountain and desert southwest, and northern New England. Estimated methyl Hg concentrations tended to be lower in the interior Mid-Atlantic region, northern Rocky Mountains and Great Plains, and Pacific Northwest. The results of this analysis should be considered a first approximation of risk. Sampling of biota in areas of high predicted methyl Hg can confirm whether bioaccumulation in the food web is occurring.

Predicted methylmercury (MeHg) in nanograms per liter (ng/L) concentrations in surface waters throughout the United States by hydrologic unit codes that contain national parklands.

Figure 3.10   Predicted methylmercury (MeHg) in nanograms per liter (ng/L) concentrations in surface waters throughout the United States by hydrologic unit codes that contain national parklands.

Estimates were generated by the U.S. Geological Survey (last modified February 20, 2015). Rankings are based on quintile distributions across all Inventory and Monitoring parks having estimates by the U.S. Geological Survey.

3.6.4.2  Semivolatile Organic Compounds

The WACAP study focused on semivolatile organic compounds and metals, largely because of their capacity for atmospheric transport over long distances. Semivolatile organic compounds can undergo repeated volatilization on surfaces, such as plant foliage, in response to daily changes in temperature. As a consequence, such compounds can be deposited, reemitted, and redeposited multiple times. This behavior can cause these compounds to move large distances in a leap-frog fashion. The semivolatile organic compounds were classified into four groups: current-use pesticides, North American historic-use pesticides, industrial/urban-use compounds, and combustion by-products. WACAP identified and analyzed over 100 semivolatile organic compounds representing various levels of volatility, solubility in water, hydrophobocity, and persistence in the environment. In each of the core parks studied, a variety of ecosystem compartments were sampled, including air, snow, water, sediments, lichens, conifer needles, and fish, to identify concentrations and potential biological impacts of contaminants. Air, lichens, and conifer needles were analyzed in 12 secondary parks. WACAP also used back-trajectory cluster analysis in the core parks to spatially model atmospheric transport of these air pollutants (Landers et al. 2010).

Within the WACAP monitoring effort, the highest pesticide concentrations in snow were found in the Rocky Mountains and the California Sierra Nevada Mountains. Pesticide concentrations in vegetation were highest in California and in the Rocky Mountains; for other ecosystem components, including fish, these same areas often exhibited the highest measured total pesticide concentrations (Landers et al. 2010).

At the WACAP parks having high vegetation contamination, the major semivolatile organic compound pollutants were the current-use pesticides endosulfan and dacthal. Contaminant concentrations generally increased with elevation, so high-elevation areas in parks may be at extra risk for contamination; polycyclic aromatic hydrocarbons were an exception, decreasing at higher elevation. This may have been a result of increased wildfires and human activity at lower elevation. Dieldrin, an acutely toxic pesticide that causes reproductive impairment in fish, was measured at significantly higher concentrations in fish at some WACAP sites than in comparable ecosystems in Canada. Proximity of cropland was a statistically significant indicator of the presence of pesticides in WACAP parks. In parks in the contiguous United States, current-use pesticide concentrations in snow and vegetation were strongly correlated with percent of cropland within 150 km (93 mi) of the park. In Alaska, there are no croplands within 150 km of the WACAP sample sites; therefore, presence of pesticides was assumed to result from long-range atmospheric transport and deposition (Landers et al. 2010).

Historic-use pesticides that are now prohibited in the United States were found at higher concentrations in the lower 48 states than in Alaska, suggesting continued persistence, despite the fact that they are no longer used in this country. Regulations on emissions appear to have been effective in reducing contamination from some of these airborne pollutants.

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