wetland pesticide monitoring in minnesota

Wetland Pesticide Monitoring in Minnesota

Matt Ribikawskis, Hydrologist, MDA

Bill VanRyswyk, MAU Supervisor, MDA

Dave Tollefson, Hydrologist, MDA

Pesticide Monitoring Program • 1985 – Groundwater Monitoring began

• 1987 – Revised Minnesota Pesticide Control Law

(MN Statute 18B)

• 1989 – Minnesota Comprehensive Ground Water Protection Act (MN Statute 103H)

• 1991 – Surface water pesticide monitoring began

• 2006 – Introduced tiered monitoring structure to SW monitoring

• 2007, 2012– Lake sampling (NLAP)

• 2008 – Began wet precipitation pesticide monitoring

• 2014 – Monitoring: Surface water (62 Sites, 1,034 samples); Groundwater monitoring (167 sites, 560 samples)

• One of the most comprehensive pesticide sampling programs in the country

Why Sample Wetlands?

• Compliments MDA surface water (rivers/streams, lakes) and groundwater monitoring

• Initiated in part by Canadian paper documenting frequent detection of neonicotinoid insecticides prairie pothole region (Main et al. 2014)

• Pilot wetland sampling in preparation for the National Wetland Condition Assessment (NWCA) in 2016

Wetland Pesticide Monitoring Locations

• 19 Wetlands targeting three wetland land use types: • Agriculture (8) • Reference / minimally

impacted (5) • Urban (6)

• Stratified sampling based on wetlands MPCA was currently sampling

Field methods

• Water column

– Surface grab, middle of wetland using MPCA standard monitoring protocols

– June 2-10, 2014

• Benthic substrate

– Sediment core, top 2 inches of consolidated sediment using MPCA standard monitoring protocols

– Sample collection: August 20-24, 2014

• Samples collected by MPCA personnel

Lab Methods

• Water column

– GC-MS/MS and LC-MS/MS methods

• 133 pesticide compounds (parent compounds and degradates)

• Benthic sediment

– New lab method developed by MDA laboratory

• 14 neonicotinoid insecticides – 7 Parent compounds

– 7 Degradate compounds (from 2 parent compounds)

MDA Water Column Results

• 27 compounds detected in at least one wetland

• Herbicide and herbicide degradates most commonly detected


• Dichlorvos detected above its USEPA OPP reference value

• Neonicotinoids detected • Thiamethoxam • Imidacloprid

• All other pesticides well below reference values


• Agriculture wetlands: • Herbicide and degradates • One insecticide

• Reference wetlands: • Generally fewest

detections

• Urban wetlands: • All pesticide

types


• Agriculture wetlands: • Highest total herbicide

degradate concentration

• Reference wetlands: • Lowest total

concentrations

• Urban wetlands: • Highest total median

concentration

Wetlands, Lakes and Rivers

• No fungicides or insecticides detected in lakes

• Similar detection frequencies with rivers and wetlands


• Rivers: Higher percent of reference value but still well below reference values

• Similar concentrations between lakes and wetlands for detected pesticides

Neonicotinoid Insecticides

• Class of insecticides that affect the central nervous system of insects.

• First registered neonicotinoid in 1994 (Imidicloprid)

• Used in agricultural and urban settings

• Primarily applied as seed treatments but also as foliar sprays, in-furrow treatments, tree injections, bait systems (ant, roach, flies), flea collars

Neonicotinoid Water Column Results

• Acetamiprid and clothiandin not detected in MN wetlands

• Canada wetlands had a higher detection frequency

Canada Minnesota

Acetamiprid 0.25 25.00

Clothianidin 0.60 25.00

Imidacloprid 0.55 20.00

Thiamethoxam 0.90 25.00

Analytical Method Reporting Limits (ng/L)

Neonicotinoid Water Column Results

• Canadian wetlands had much higher concentrations

• All MN wetland neonicotinoid insecticides well below USEPA OPP reference values

Benthic Sediment Results

• One pesticide compound detected in 2 urban wetlands

• No pesticide compounds detected in agricultural or reference wetlands

Benthic Sediment Results

• No parent insecticide compounds detected in MN wetland sediment

• Very low maximum concentrations observed

Conclusions - Water

• Pesticide compounds detected in wetland water are detected at low concentrations relative to reference values

• Reference wetlands contained the fewest number of compounds and the lowest total concentration (water)

• Fungicides only found in urban wetlands water

• Fewer detections and lower concentrations in wetlands than streams

• Higher detection frequencies and concentrations than lakes – most well below reference value

Sediment Conclusions and Future Work

• Low concentrations and detections of neonicotinoid insecticides in wetland sediment

• No neonicotinoid parent compounds detected in benthic sediment of Minnesota wetlands

• Future, potentially participating in the National Wetland Condition Assessment in (NWCA) 2016

Acknowledgements • Special thanks to Mark Gernes (MPCA), wetland site

selection and sample collection coordination

• Mary Knight (MPCA) sample collection

• MDA laboratory for analysis and method development

• Monitoring reports available at: http://www.mda.state.mn.us/monitoring

http://www.mda.state.mn.us/monitoring

References

– Main, AR, Headley JV, Peru KM, Michel NL, Cessna AJ, et al. (2014) Widespread Use and Frequent Detection of Neonicotinoid Insecticides in Wetlands of Canada's Prairie Pothole Region. PLoS ONE 9(3):e92821. doi:10.1371/journal.pone.0092821

Questions?

Matt Ribikawskis

[email protected]


Percent of Detections by Pesticide Type

Sources, Transport, and Distribution of Contaminants of

Emerging Concern in a Mixed Land Use Watershed

David Fairbairn (U of M), Ekrem Karpuzcu (U of M), Bill Arnold (U of M), Brian Barber (U of M), Liz Kaufenberg (U of M), Bill

Koskinen (U of M, USDA-ARS), Paige Novak (U of M), Pam Rice (U of M, USDA-ARS), Deb Swackhamer (U of M)

University of MinnesotaWater Resources Center

Research Team• U of M Faculty

• Deb Swackhamer• Pam Rice (USDA-ARS)• Bill Arnold• Paige Novak• Bill Koskinen (USDA-ARS)

• UM Staff• Brian Barber• Ekrem Karpuzcu

• Graduate Students• Liz Kaufenberg• Megan Kelly

• Undergraduate Students• Anthony, Stephanie,

Brendan, Goeun, Khanhtram, Dan

• Environmental Consultants• McGhie Betts, Inc.

CEC Background• Multitude of different types of chemicals• Not typically monitored or subject to WQ standards• May cause adverse human or ecological effects

– E.g., Endocrine disruption, antibiotic resistance

• May be candidates for future regulation

Image credit: WHO/UNEP

Food Additives

Personal Care Products

Pesticides

Pharmaceuticals -Human and Veterinary

Natural and Synthetic

HormonesIndustrial/Commercial Chemicals

CECs

Many Sources and Pathways

Image credits: U.S. EPA, USGS

CEC Knowledge Gaps

• Sources• Transport • Fate• Spatial and temporal

factors and variability• Effects

– What, where, when, and how

In-stream Occurrence

WWTP

Agricultural Runoff

Urban Runoff

Research Goals• Characterize, track CEC sources

in complex mixtures• Identify CEC markers• Help understand occurrences

and mitigate impacts

In-stream Occurrence

WWTP

Agricultural Runoff

Urban Runoff

Agricultural Runoff WWTP

Urban Runoff

ChemicalA, B, C

ChemicalA, B, C, D

ChemicalB, D, E

Objectives

Investigate:• Well-delineated, mixed land use area

– South Fork of the Zumbro River (SFZR), Zumbro River Watershed

• Diverse CECs• Spatiotemporal patternsRelate to CEC sources

Study Area – SFZR

Bear CreekSFZR-US2 SFZR-DSWillow Creek

Populations (Est.) • 108k People• 101k Poultry• 73k Swine• 22k Cattle• 13k Mink

Sampling Seasons/Events

2011-2012 Hydrograph and Sampling Events: SFZR-DS Example

Sampling Event

2012 Hydrograph and Sampling Events: Instream and Effluent

Field and Laboratory Methods

Compounds of InterestUrban/Residential Agricultural Mixed Uses

AcetaminophenCarbamazepine

IbuprofenCaffeineCotinine

DEETCarbaryl

IprodioneMecoprop

TylosinMonensin

VirginiamycinAcetochlor

AtrazineMetolachlor

FormononetinTrenbolone

Zeranol

ErythromycinOxytetracycline

SulfamethoxazoleTrimethoprimChlorpyrifos

DaidzeinGenistein

4-Nonylphenol

Text Color Key:PharmaceuticalsPersonal Care ProductsPesticides

Hormones & PhytoestrogensCommercial/Industrial

Compounds of InterestUrban/Residential Agricultural Mixed Uses

AcetaminophenCarbamazepine

CaffeineCotinine

DEETCarbaryl

Mecoprop

Tylosin

AcetochlorAtrazine

Metolachlor

Erythromycin

SulfamethoxazoleTrimethoprim

Daidzein

4-Nonylphenol

Text Color Key:PharmaceuticalsPersonal Care ProductsPesticides


Concentrations in 68 Water Samples

Method Reporting Limit

Text Color Key:Pesticides

PharmaceuticalsPersonal Care Products


Concentrations and Loading by Site

*significant differences among sites by ranked ANOVA

Met

olac

hlor

*

Mass Loading (g/d)Ca

rbam

azep

ine*

Met

olac

hlor

*

Concentration (ng/L)

red line = Method Reporting Limit (MRL)

Carbamazepine*Acetaminophen*

Carbamazepine*

Metolachlor*

Acetaminophen*Metolachlor*

Site

Site

Acet

amin

ophe

n*

Mass Loading (g/d)

CarbamazepineAcetaminophen*

Concentrations and Loading by Season

*significant differences among seasons by ranked ANOVA

Carbamazepine

Metolachlor*

Concentration (ng/L)

Acetaminophen*

Met

olac

hlor

*

Metolachlor*

Met

olac

hlor

*

Met

olac

hlor

*

Met

or*

Met

or*

Met

or*

Seas

onSe

ason

red line = Method Reporting Limit (MRL)

For Mass Balance: Comparing Concentrations in Streams and WWTP Effluent (n=35)

• WWTP effluent, downstream, and upstream samples collected at 7 times.

• Mass balances tested across events– Predicted vs. Observed– Wilcoxon signed-rank test

• Mass balances yielded information on CEC sources and transport to SFZR-DS

*significant differences among sites

Conc

entr

atio

n (n

g/L)

Mass Balance: Predicted vs. Observed Loading in Different Flow Types

Low FlowHigh and Low Flow

Mass Loadings By Site Over Time

Mass Loading: Transport and temporal patterns varied by CEC class, contributing land use, and instream flow.

Site/Seasonal AnalysisObserved source and seasonal patterns:• Upstream sources, season and runoff influenced:

– Agricultural herbicides and daidzein (phytoestrogen)

• Mixed sources and (moderate) seasonal-runoff influences:– Certain PPCPs, e.g., acetaminophen, DEET, caffeine– Mecoprop (urban/residential herbicide)

• Primarily WWTP source and little seasonality:– Certain pharmaceuticals, e.g., erythromycin, carbamazepine– 4-Nonylphenol– Carbaryl (insecticide)

• Method utility:– The “whole” (downstream loads) was well-explained by the sum

of the measured parts (WWTP plus upstream loads)– Good, quick way to compare loads from various subwatersheds

and WWTP for different events– Can enhance tracking of CEC sources and transport

• Results confirm observed CEC sources, temporal, and group patterns:– Agricultural/runoff dominated CECs: >90% of loading from

upstream areas, large temporal variability– Mixed sources-transport CECs:

• 20%-80% of load from each source (upstream areas vs. WWTP)• Upstream inputs greater during periods of increased precipitation and flow

– Effluent-dominated CECs: >90% of load via WWTP, little variability

Mass Balance Analysis

Principal Component Analysis

• More samples, fewer analytes

• Similar groupings identified

• Reinforces conclusions made via other methods

• Demonstrates utility of PCA to broadly identify patterns in complex environmental datasets

Sediment-Water Distributions: Predicted (log Kow) vs. Observed (log Kd-obs)

Acetaminophen

Caffeine

Acetochlor

CarbamazepineAtrazine

DEETDaidzein

Kd-obs (L/kg) = [C]sed / [C]H20 * (1000 g/kg)

Sediment-Water Distributions

• CEC concentrations in sediments showed:– Insignificant seasonality– Variation by land use, year, and event

• Hydrophobic and hydrophilic interactions affected the observed distributions– Hydrophilic CECs detected most frequently in sediment

• River sediments: small organic carbon content (<2%)

• CEC persistence affected the range of distributions

Project Synthesis: Overall Goals

• Characterize and track CEC sources in complex mixtures

• Determine predictability and variability of occurrences

• Help understand and mitigate impacts

Contaminants in Water Sample

40%

Outcomes

• Improved knowledge of CEC sources, transport, and behavior

• Improved study designs• Sampling and data analysis• Identifying problem areas• Identifying sources

• Information for decision-making

Research Articles

• Karpuzcu, M. E., Fairbairn, D. J., Arnold, W. A., Barber, B. L., Kaufenberg, E. F., Koskinen, W. C., Novak, P. J., Rice, P. J., and Swackhamer, D. L., Identifying sources of emerging organic contaminants in a mixed use watershed using principal components analysis. Environmental Science: Processes & Impacts 2014, 16, 2390-2399.

• Fairbairn, D. J., Karpuzcu, M. E., Arnold, W. A., Barber, B. L., Kaufenberg, E. F., Koskinen, W. C., Novak, P. J., Rice, P. J., and Swackhamer, D. L., Sediment–water distribution of contaminants of emerging concern in a mixed use watershed. Sci. Total Environ. 2015, 505, 896-904.

• Fairbairn, D. J., Karpuzcu, M. E., Arnold, W. A., Barber, B. L., Kaufenberg, E. F., Koskinen, W. C., Novak, P. J., Rice, P. J., and Swackhamer, D. L., Contaminants of emerging concern in a mixed land use watershed: a two year study of fluvial occurrence and spatiotemporal variation. Environ. Toxicol. Chem. In review.

• Fairbairn, D. J., Arnold, W. A., Barber, B. L., Kaufenberg, E. F., Koskinen, W. C., Novak, P. J., Rice, P. J., and Swackhamer, D. L., Contaminants of emerging concern: mass balance and comparison of wastewater effluent and upstream sources in a mixed-use watershed. Environ. Sci. Technol. In review.

AcknowledgementsFunding for this project was provided by the Minnesota

Environment and Natural Resources Trust Fund as recommended by the Legislative-Citizen Commission on

Minnesota Resources (LCCMR).

wetland pesticide monitoring in minnesota

Documents