1 Challenge: multiple input pathways Challenge: multiple - - PDF document

SLIDE 1

Nitrogen sources to rivers & estuaries of New York

Elizabeth W. Boyer, State University of New York, Syracuse Robert W. Howarth, Cornell University, Ithaca, NY Richard B. Alexander, U.S. Geological Survey, Reston, VA

Collaborators

Rich Alexander, U.S. Geological Survey, VA Jim Galloway, University of Virginia Christy Goodale, Cornell University, NY Bob Howarth, Cornell University, NY Kate Lajtha, Oregon State University, OR Bernhard Mayer, University of Calgary, Canada Keith Paustian, Colorado State University, CO Greg Schwarz, U.S. Geological Survey, VA Sybil Seitzinger, Rutgers University, NJ Dick Smith, U.S. Geological Survey, VA Nico vanBreemen, Wageningen, the Netherlands

Outline

• Need to understand importance of atmospheric N in

terrestrial & aquatic ecosystems

• Challenges for estimating atmospheric N deposition
• Approaches for quantifying significance of

atmospheric N inputs & their fate

• Implications & Future Directions

The cascading effects of N pollution -- Significance of atmospheric N deposition?

Impacts table from Driscoll et al. 2003, Hubbard Brook Research Foundation

Challenges for understanding atmospheric N inputs to terrestrial & aquatic ecosystems

• Multiple reactive N species
• Multiple emissions sources
• Multiple transport pathways
• Quantifying atmospheric N deposition

NOx Emission Data from EPA National Air Pollution Emission Trends

Challenge: multiple sources of N emissions

1

SLIDE 2

Challenge: multiple atmospheric N species

• Reduced nitrogen, NH

x

Typically dominated by ammonia species (e.g., NH3 and NH4

+)

• Oxidized nitrogen, NOx

Composed primarily of nitrogen oxide species, representing primarily nitric oxides (NO3

­ and

HNO3) and nitrogen dioxide (NO2)

• Organic nitrogen, AON

Challenge: multiple input pathways

• Wet deposition is the fraction contained in precipitation—

predominantly rain and snow.

• Dry deposition is the fraction deposited in dry weather through

such processes as settling, impaction, and adsorption.

Quantifying Atmospheric Deposition

National Atmospheric Deposition Program National Trends Network (NADP­NTN): Wet deposition monitoring, designed to determine geographical patterns & long­term trends in precipitation chemistry. 9 active sites in NY; most since ~ 1980. Atmospheric Integrated Research Monitoring Network (AIRMoN): Wet deposition monitoring, designed to determine daily and storm­event trends. 1 site in NY since 1992. Clean Air Status and Trends Network (CASTNET): provides dry deposition & ground­level ozone monitoring data. 2+ active sites in NY since ~ 1990.

NADP­NTN AIRMoN CASTNET

How much N deposition does NY receive?

Inorganic nitrogen wet deposition at monitoring sites

Data from National Atmospheric Deposition Program ­ National Trends Network

2002 2 4 6 8 10 12 14 1980 1985 1990 1995 2000 N deposition, kg/ha

mean median ny08 ny10 ny20 ny22 ny52 ny65 ny68 ny98 ny99

How much N deposition does NY receive?

Inorganic nitrogen wet deposition at monitoring sites

Data from National Atmospheric Deposition Program ­ National Trends Network

How much N deposition does NY receive?

Inorganic nitrogen wet & dry deposition

Data from Clean Air Status and Trends Network, Monitoring station at Connecticut Hill, CTH110

2

SLIDE 3

t

Challenge: scaling up from monitoring sites

How to estimate dry deposition at wet­only sites? How to interpolate sparse data over space & time?

Boyer et al. 2002

2 4 6 8 10 12 14 Connecticut Hudson Mohawk Delaware Susquehanna Total inorganic N deposition, kg ha

• 1 yr
• 1

Ollinger et al. w/ Lovett & Rueth 1999 Ollinger et al. 1993 Lovett & Lindberg 1993 ATM3 model, Dentener 2000

( ( ( ( ( ( ( ( ( ( SUS C ON D E L K HU D ME R AN MOH S C H SA C B LA

Challenge: underestimating atmospheric N?

• Deposition in coastal, urban, &

agricultural areas? Monitoring in

in rural areas, to assess relationships between regional pollution and deposition patterns.

• Underestimating ammonium?

Comparisons of AIRMON and NADP data suggest loss of wet NHx species due to biological activity in collection buckets during week­long

• storage. Underestimated >15%,

Meyers et al. 2001

• Underestimating atmospheric

Organic N? ~30% of total in

northeast, Neff et al. 2003

Challenge: quantifying agricultural volatilization

Boyer et al. 2002

2 4 6 8 10 Connecticut Hudson Mohawk Delaware Susquehanna NHx-N volatilization, kg ha

• 1 y r
• 1

animal waste, Cass et al. 1982 animal waste, Asman 1990 animal waste, van der Hoek 1998 animal waste, Krus et al. 1989 animal waste, Moller & Schieferdecker 1989 animal waste, Buijsman et al. 1987 animal waste, ApSimon et al. 1987 animal waste, Bouwman et al. 1997 animal waste, Lee 1994 animal waste, Battye et al. 1994 fertilizer, Battye et al. 1994

How much is transported long­range versus re­deposited locally?

( ( ( ( ( ( ( ( S U S CON DEL H UD MER AN MOH SCH SAC BLA

Approaches to quantifying significance & fate of atmospheric N in terrestrial & aquatic ecosystems

• Mass balance model: TNNI
• Empirical model: SPARROW

Major Watersheds of NY Mass balance model: total net N inputs

• Quantify new inputs of N (N that is newly fixed

within, or newly transported into, each region)

– atmospheric deposition – application of nitrogenous fertilizers – biological N fixation by crops – net import or export of N in food & feed

• Quantify outputs of N in streamflow
• Quantify fate of remainder…

Howarth et al. 1996, Boyer et al.2002

3

SLIDE 4

Mass balance model: fate of N inputs?

• Uptake by vegetation
• Storage in soils or groundwater
• Conversion and loss to atmospheric forms

through denitrification & volatilization

• Export in streamflow

Quantified N inputs, storages, and losses for 16 coastal watersheds in the northeast USA

Boyer et al. 2002 0% 20% 40% 60% 80% 100%

PEN KEN AND SAC MER CHA BLA CON HUD MOH DEL SCH SUS POT RAP JAM Total

Watershed Land Use

forest agricultural urban water & wetl.

• ther

Watershed land use, from north to south

Boyer et al.2002

Primary data sources

• Topography & catchment boundariesdelineated from USGS 1°

DEMs

• National Land Cover Database of the Multi­Resolution Land

Characteristics Interagency Consortium (MRLC).

• Population data & characteristics from the Census Bureau, 1990
• Discharge and N concentration data from USGS (Alexander et al. 1998)
• Atmospheric depositionfrom the National Atmospheric Deposition

Program

• Nitrogenous fertilizer use from USGS spatial database on agricultural

chemical use in the US (Battaglin & Goolsby 1994)

• Livestock and cropinformation, for calculating agricultural transfers of N

in food and feedstocks, from the 1992 USDA Census of Agriculture

• Forest growth data from USDA Forest Service’s Forest Inventory and

Analysis (FIA) program

• River reach characteristics from USGS national hydrologic dataset
• 1000

1000 2000 3000 4000 5000 6000

Nitrogen, kg/km

2

/yr

PEN KEN AND SAC MER CHA BLA CON HUD MOH DEL SCH SUS POT RAP JAM Net import in feed Net import in food Fertilizer use Agricultural N2 fixation Net atmospheric deposition Forest N2 fixation

Mass balance model

Total N inputs in 16 northeastern catchments

Boyer et al.2002

Mass balance model

Total N inputs to catchments are related to riverine export

4

N export in streamflow, kg/km

2/yr

2000 1600 1200 800 400

y =0.26x; R

2=0.62

Northeastern USA

Howarth et al. 1996: NE USA

2000 4000 6000 Total N inputs, kg N/km

2/yr

Boyer et al.2002

SLIDE 5

5

fertilizer net feed import fixation fixation net food import net deposition net NH3 vol.

waste

AGRICULTURE

• ther

forest pools

Harvest Export FOREST

? wood ? ? soils

SUB/ URBAN

? soils ? soils

denit. Riverine Export WATER

? groundwater

denit.

leaching

denit. denit.

leaching sewage & septic

denit.

Mass Balance Model

Nitrogen Sources, Storages, & Losses

(2002: Boyer et al., Goodale et al., Mayer et al., Neff et al., Seitzinger et al., VanBreemen et al.)

Sources Sinks

denitrification in landscape (39%) ? soil storage (9%)

• denitr. in

river (11%) riverine export (19%) ? wood & biomass storage (8%) wood export(5%) NH3 vol. (3%) food export (6%) net import in food & feed (24%) atmospheric deposition (33%) fertilizer use (15%) forest fixation (5%) agricultural fixation (23%)

VanBreemen et al. 2002, Boyer et al. 2002

Mass Balance Model

N Sources, Storages, & Losses in 16 NE catchments

• 500

500 1000 1500 2000 2500 3000 3500 4000 Upper Hudson & Mohawk Hudson Hudson & Raritan Net anthropogenic N inputs, kg N km -2 yr

• 1

Net N imports in food Net N imports in feed N fixation in agricultural lands N fertilizer use Atmospheric N deposition

36% 22% 16% 13% 8% 18% 13% 27% 11% 33% 23% 31% 14% 38%

Mass balance model

N inputs from uplands to the coastal zone

SPARROW (SPAtially Referenced Regression on Watershed Attributes)

Terrestrial Landscape Aquatic Landscape Monitoring Data

N LCD 1K

Wa t e r I c e , s n o w H i g h i n t e n s i t y r e s i d e n t i a l L

• w i

n t e n s i t y r e s i d e n t i a l Q u a r i e s , s t r i p mi n e s , g r a v e l p i t s T r a n s i t i

• n a

l B a r e r o c k , s a n d , c l a y C o mme r c i a l , i n d u s t r i a l , t r a n s p

• r

t a t i

• n

D e c i d u

• u

s f o r e s t Mi x e d f

• r

e s t E v e r g r e e n f

• r

e s t G r a s s l a n d s , h e r b a c e o u s P a s t u r e , h a y O r c h a r d s , v i n e y a r d s , o t h e r S h r u b l a n d R o w c r o p s S ma l g r a i n s U r b a n , r e c r e a t i o n a l g r a s e s F a l

• w

E me r g e n t h e r b a c e

• u

s w e t l a n d s Wo o d y w e t l a n d s

• Statistically estimates origin & fate of contaminants
• Model predictions include: flux, yield, concentration and

sources in streams; stream & reservoir losses; uncertainty measures

Smith et al. 1997

SPARROW water quality model

Monitored Stream Load Sources Land-to-water transport Aquatic transport Error

) exp( ) 1 /( 1 ) exp( ) exp(

1 , , , , 1 , ) ( i l l j i r m m j i s m N n j n j n i J j i

q T Z S LOAD ε λ δ α β       + −       ′ − =

∏ ∏ ∑ ∑

− = ∈

Smith et al. 1997, Alexander et al. 2000

SPARROW water quality model prediction of N fluxes in NY stream reaches

Data based on Alexander et al. 2000

TN Flux (metric tons/yr) < 100 100 to 250 250 to 1,000 > 1,000

SLIDE 6

5 10 15 20 25 30 35 SENECA 23 19 4 4 10 22 17 MOHAWK 31 23 8 7 6 8 17 atmos. dep. urban land forest land sewer. pop.

• rganic

matter synth. fertilizer animal waste

SPARROW water quality model

prediction of N source shares (%) in NY catchments

Seneca 8919 km

2

Mohawk 8,935 km

2

Data based on Alexander et al. 2000

Quantifying Atmospheric Nitrogen Source with New Stable Isotope Techniques

w/ colleagues: Carol Kendall Beth Boyer Doug Burns Greg Michalski Rick Carleton & contributions from: Tom Butler Greg Lawrence Pat Phillips

Are isotopic approaches the panacea for elucidating atmospheric N sources? Considering δ17O δ18O and δ1 5N of nitrate

s

in water and air samples)

Thanks, NYSERDA! Implications for the changing future At The End of the Day

• Do we have a broad understanding of the N Cycle? Yes.
• Do we know the source of new nitrogen? Yes.
• Do we know the rate of N accumulation

– In the atmosphere? Yes – In forests? Yes – In soils and groundwater? No. – In rivers and coastal waters? Not well.

• What are the big uncertainties? Storage & Denitrification
• Is knowledge on the consequences of N accumulation

adequate to begin to make policy decisions? – In the atmosphere? Yes. – In the terrestrial landscape? Yes. – In rivers and coastal waters? Yes.

Priorities for research on N sources

• 1. Accounting & improved, long­term

monitoring of nutrient sources.

• 2. Quantify nutrient inputs and fates

under different land­use scenarios.

• 3. Watershed­scale analyses of the role
• f groundwaters, surface waters,

riparian zones, and wetlands as sinks, sources, and transformers of nutrients.

• 4. Improved models for managers of

nutrient fluxes from the landscape under current and future conditions.

• 5. Determine most effective policy and management approaches

for nutrient reduction, and quantification of the costs, trade­offs, and benefits of controlling nutrient pollution.

After Howarth et al. 2003

Questions?

ewboyer@syr.edu

6