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IN PRESS
Reduced River Phosphorus Following Implementation of a Lawn Fertilizer
Ordinance
J. T. Lehman, D. W. Bell, and K. E. McDonald 2009. Reduced river phosphorus following
implementation of a lawn fertilizer ordinance, Lake and Reserv. Manage. 25: 00-00.
Key Words: temporal variation, sampling requirements, eutrophication, watershed
Abstract!!Statistical comparisons of 2008 surface water quality data with a historical data set
at weekly and sub-weekly resolution has revealed statistically significant reductions in total
phosphorus (TP) and a trend of reduction in dissolved phosphorus following implementation of a
municipal ordinance limiting the application of lawn fertilizers containing phosphorus. No
reductions were seen at an upstream control river site not affected by the ordinance. Non-target
analytes including nitrate, silica, and colored dissolved organic matter did not change
systematically as did P. The data were analyzed in the context of a statistical model that
characterized historical temporal variability and predicted the sampling effort needed to detect
changes of specified magnitude. Expected changes of ca. 25% in monthly mean value were
predicted to require weekly samples during the summer for only 1 or 2 years for TP, and
statistically significant reductions measured after 1 year averaged 28%, or about 5 kg P per day.
The lawn fertilizer ordinance was only one component of broader efforts to reduce non-point
source loading of P, however, so the magnitude of its role in the measured changes remains
uncertain.
Growing numbers of municipalities and state governments have adopted or are considering
the adoption of restrictions on the residential use of P-containing fertilizers. The actions are
based on awareness that P is often not a growth-limiting nutrient in many terrestrial soils, and
that excessive application of the element leads to runoff and eutrophication of surface waters
(e.g., Carpenter et al. 1998). Examples include the state of New Jersey, with over 100
municipalities affected (NJ 2007), Sarasota County, Florida (Sierra Club 2007), the state of
Maine (Maine 2008), and Dane County in Wisconsin (Dane County 2007).
Aside from the environmental consciousness of the actions, there has unfortunately been little
evidence yet that the bans are having a salutary effect. For example, the State of Minnesota
enacted a law to regulate the use of phosphorus lawn fertilizer with the intent of reducing
unnecessary phosphorus fertilizer use. The law prohibits use of phosphorus lawn fertilizer except
in prescribed instances. The prohibition went into effect in 2004 in the Twin Cities metropolitan
area and statewide in 2005. However, field studies to examine the efficacy of the ban for
improving surface water quality were inconclusive (MDA 2007), a fact attributed to excessive
variability in runoff data. The problem may indeed be the statistical power of available data sets.
Vlach et al. (2008) report reductions in phosphorus runoff from sub-watersheds in Minnesota
where the use of fertilizer containing P was restricted in 1999 compared to other sub-watersheds
where the ban was not imposed until 2004, based on analysis of more than 500 data points. The
study involved pair-wise comparisons of six sub-watersheds in the municipalities of Plymouth
and Maple Grove, MN. The sites differed in their regimens of fertilizer use, with the Plymouth
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sites using only phosphorus free fertilizer, and Maple Grove sites serving as controls, using P-
containing fertilizer. Concentrations of total P in runoff were virtually identical between the two
treatments, but soluble reactive P concentrations in runoff were 17% lower at the P-free sites.
As part of its efforts to comply with a state-imposed phosphorus TMDL (Total Maximum
Daily Load) that called for a 50% reduction in phosphorus discharges to the Huron River, the
city of Ann Arbor in southeast Michigan enacted an ordinance that went into effect in 2007 (Ann
Arbor 2006) to limit phosphorus application to lawns. Compliance with the lawn fertilizer
ordinance depends on point-of-sale restrictions and monitored compliance by lawn care services.
The estimated effect of full compliance was a 22% reduction in phosphorus entering the river.
The prediction was obtained by estimating the lawn fertilizer runoff from a creekshed within the
city and extrapolating that result to all other creeksheds. Ferris and Lehman (2008) used their
historical set of Huron River water quality data to predict the sampling effort that could detect
changes of roughly 25%. They concluded that a 25% reduction in total P (TP) would be
detectable after one or two years of sampling four times per month. Similar percentage
reductions in dissolved P (DP) would likely take two or three years, and for soluble reactive P
(SRP), the time could be as long as 8 years. This paper reports the test of the a priori predictions
after one year.
Figure 1. Study site, with sampling stations identified.
Study site!!Our field site (Fig. 1) was a portion of the Huron River catchment in southeastern
Michigan (United States Geological Survey, USGS Cataloging Unit 04090005). Four stations
were established (Table 1) on the basis of an existing historical data set at weekly and sub-
weekly intervals (Ferris and Lehman 2008). The station designated Control (CTL) corresponded
to station 1 of Ferris and Lehman (2008). It was upstream from Ann Arbor and outside the
jurisdiction affected by the city ordinance. Stations A and B corresponded with Ferris and
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Lehman’s stations 5 and 6. Station A represents about 29 km2 of catchment attributable to Ann
Arbor, and station B has about 94 km2. A fourth station, designated F, was downstream at the
site where the Huron River discharges into Ford Lake, a eutrophic impoundment. Station F was
downstream from the outfall of the wastewater treatment facility that serves Ann Arbor
(AAWWTP); stations A and B were upstream of the outfall. Water quality data at station F have
been reported by Ferris and Lehman (2007), and include four years (2003 to 2006) prior to
implementation of Ann Arbor’s fertilizer ordinance.
Table 1. Locations and approximate catchment areas of four Huron River stations that are attributable to
Ann Arbor. Coordinates are specified as eastings and northings for UTM Zone 17.
___________________________________________________________________________
Station E N Catchment Area attributable to Ann Arbor (km2)
CTL 262796 4691655 0
A 275285 4685262 29
B 279744 4683268 94
F 284834 4679126 94 + AAWWTP outfall
___________________________________________________________________________
Field sampling!!Water was collected at weekly intervals from May to Sep 2008. Raw water
was filtered on site for nutrient analysis using Millipore™ disposable filter capsules of nominal
0.45 "m pore size.
Nutrient analyses!!Analyses included soluble reactive phosphorus (SRP), dissolved
phosphorus (DP), total phosphorus (TP), soluble reactive Si (SRSi), pH, and nitrate (NO3). SRP
was measured as molybdate-reactive phosphate in filtrate. DP and TP were measured as SRP
after first oxidizing filtrate (DP) or unfiltered water (TP) with potassium persulfate at 105 C for 1
h. Specific conductance at 25 C (K25, "S) was measured with samples at 25 C in a water bath.
Colored dissolved organic matter (CDOM) was measured as UV absorbance at 254 nm. Ferris
and Lehman (2008) showed that CDOM correlates strongly with both dissolved organic carbon
(DOC) and dissolved organic nitrogen (DON) in the Huron River. All nutrient analyses were
performed according to Ferris and Lehman (2007). For SRP and TP, three replicates were
measured at each site. For DP, two replicates were measured at CTL and station A, and 3
replicates were measured at stations B and F. Sample means and standard error of the mean (SE)
were calculated for each determination and additional replicates were added if the ratio of SE to
mean exceeded 0.05.
Daily volumetric discharge and mean daily TP concentrations in the effluent of the
AAWWTP were supplied by the city of Ann Arbor from the operator’s logs.
Statistical methods!!The primary response variables of interest were SRP, DP, and TP.
However, NO3, CDOM, SRSi, pH, and K25 were included as non-target or quasi-control
variables because we reasoned that they should be unaffected by a nutrient reduction strategy
specifically targeted at P. We adopted the statistical model developed by Ferris and Lehman
(2008) with the aim of testing the efficacy of the new ordinance; it balanced type I error against
type II error such that #$= 0.1 and % = 0.75. The object was to hold type I error reasonably low
while seeking a credible level of power to detect environmental changes if they indeed occur.
Because we wished to test the model predictions, we set #$= 0.1 for significance testing. Our a
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priori expectation was that P concentrations would decrease, and so we applied one-tailed tests
to the P data. We had no a priori expectations regarding the non-target variables, and so we
applied two-tailed tests to them and set #$= 0.1 in order to mimic the threshold probability
applied to P variables.
SRP, DP, TP, NO3, SRSi and CDOM were log-transformed prior to statistical comparison.
K25 and pH were used in statistical tests without transformation Based on previous work we
expected values from the different sampling stations to differ and that there would be significant
differences in mean monthly concentrations. In order to partition variability contributed by these
factors while testing differences between the control and treatment sites and between the pre-
ordinance and post-ordinance years, a MANOVA (SAS) was used to assess overall changes in
concentrations of the three P variables simultaneously, using station, month, and year (reference
period vs 2008) as categorical factors. All three factors proved statistically significant (P< 0.02
for both SRP and DP, and P< 0.0001 for TP). We subsequently explored the data with attention
to detailed response by station, particularly control vs experimental as well as the direction of
change.
All original data used in these analyses are archived for public access at
http://www.umich.edu/~hrstudy/dataarchive.htm.
Hydrology!!Fluvial discharge of the Huron River at Ann Arbor (USGS 04174500) during
2008 was qualitatively similar to discharges recorded during the reference years, with the
exceptions of unusually high discharges during late May 2004 and late Sep 2008 (Fig. 2).
Figure 2. Fluvial discharge of the Huron River at Ann Arbor (USGS 04174500) from May to
September for three reference years (2003 to 2005) and the post-ordinance test year 2008.
Non-target variables!Analysis of variance (AOV, SYSTAT version 10) revealed that SRSi
concentrations varied significantly by month (P< 0.0001) but not by station or year (P > 0.19).
Nitrate varied significantly by station and month (P < 0.0001) but not by year (P = 0.49).
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CDOM, on the other hand, varied by month (P < 0.0001) and by year (P = 0.007) but not by
station (P > 0.6). Across all stations, including CTL, CDOM was on average about 8% higher in
2008 compared with the reference period, suggesting that DON or DOC levels were elevated.
Specific conductance was similarly on average about 9% higher in 2008 than the reference
period across all stations including CTL (P < 0.0001), and pH was significantly higher by about
0.1 unit (P < 0.0001). Temporal patterns in CDOM, specific conductance and pH seemed to
correspond with the seasonal pattern of river flow variation in 2008. As flow slackened in Jul
and Aug, these properties increased at all stations, including CTL.
Phosphorus variables!!As anticipated from past sampling experience, SRP was more
variable than DP or TP (Fig. 3) and there was no indication that concentrations for the months of
May to Sep in 2008 were significantly lower than reference values at any site other than station F
in Aug. For DP, there was a trend of decreasing mean concentrations at the experimental
stations, particularly stations B and F (Fig. 3). TP concentrations, however, were repeatedly
lower than reference at the 90% probability level, particularly at stations B and F (Fig. 3).
The magnitude of the concentration decreases observed at station F downstream of the
AAWWTP outfall were indistinguishable from the decreases observed at upstream station B.
Paired t-tests of the concentration differences by month for 2008 compared to the reference
period differed neither for TP (P= 0.83) nor for DP (P= 0.13). Analysis of TP discharge records
for the AAWWTP (Fig. 4) revealed that 2008 discharge levels were within the range observed
during the previous five years.
Discussion!!Ferris and Lehman’s (2008) median estimate of the effort needed to detect a
25% change was 8 years of weekly samples for SRP but only 2 years for TP and 3 years for DP.
The results of this study after one year are consistent with those predictions. A reduction in SRP
was detected at only one site on one date, whereas reductions were detected for both DP and TP
at experimental sites with greater regularity. A summary of key findings follows:
&$Decreases in TP concentration at 90% confidence were noted in 10 cases out of 15 at the
experimental sites (A, B and F) during the main growing period from May to Sep (Fig.
3). Moreover, there is a trend of reduced (mean) TP concentrations at the experimental
sites in 14 cases out of 15. Reductions at station B, just upstream from the AAWWTP
outfall, were more regular than at station A. Station B receives considerably more
cumulative drainage from Ann Arbor than does station A, and may therefore be more
responsive. The average reduction in concentration for the 10 statistically significant
cases was 28%.
&$For DP, reductions in concentration were rarely significant at 90% confidence level at the
experimental sites (Fig. 3), although there is a trend of reduced monthly mean
concentrations at the experimental stations, with the mean reduction being 13% overall.
&$The magnitudes of the DP and TP reductions at station F, downstream from the
AAWWTP outfall, are indistinguishable from DP and TP reductions measured at station
B, upstream of the outfall. Combined with absence of any systematic trend in point
source discharge of TP (Fig. 4), this suggests that the detectable effect traces to non-point
source loading.
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Figure 3. Concentration anomalies of SRP, DP, and TP at control and experimental sites
in 2008 expressed as percent of reference values. Error bars represent upper 90%
confidence intervals of the means.
&$The upstream site CTL appeared to function well as a control site, in that no reductions in
SRP, DP or TP were noted there.
&$The non-target variables showed no evidence of the station-specific response seen in TP
and to a lesser degree in DP. Departures of specific conductance, pH, and CDOM from
historical conditions appeared to originate upstream of the experimental unit because they
were in evidence at the control site. Consistent changes in nutrient concentrations only
within the experimental unit were confined to P.
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&$Based on the median daily TP load carried by the Huron River at station B during May to
September 2003 to 2005 (data from Ferris and Lehman 2008), the magnitude of the load
reduction is about 5 kg P per day.
Figure 3. Monthly discharge of TP from the Ann Arbor wastewater treatment facility
from 2003 to 2008. = 2003 to 2007; & = 2008.
After the first year of data collection and analysis detectable reductions have been
documented for TP and, to some degree, for DP for every month from May to Sep. Percentage
reductions are of the magnitude that was predicted to be detectable at the applied level of
sampling effort. We can state objectively within the context of our statistical model that
phosphorus concentrations were lower in 2008 compared with the reference period (2003 to
2005) at experimental sites upstream from the AAWWTP outfall and therefore independent from
treatment or discharge practices. These reductions were coincident with a city ordinance
restricting use of lawn fertilizers containing phosphorus. In fact, the magnitudes of DP and TP
reductions downstream of the outfall are not statistically different from those measured
upstream, meaning that the two are highly correlated and traceable to non-point source loading.
The magnitudes of the TP reductions are generally greater than DP reductions, even though
DP accounted for 56% (SE= 3%) of TP at all sites during the reference period and 60% (SE=
3%) of TP in 2008. This suggests that the main effect has been reduction in the particulate P load
of the river. We have not tried to determine the relative contributions of biogenic or mineral
particles to the total, nor whether phosphate in particulate matter is biologically absorbed or
physically adsorbed.
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It would be tempting to conclude that the phosphorus reductions were caused by
implementation of the ordinance, and that may indeed be the case. However, the ordinance was
enacted in the context of public education efforts that encourage citizens to be more mindful of
yard waste discharges into storm drains, to exert more diligence regarding buffer strips of
vegetation along stream banks, and to exhibit more environmental awareness in general. These
multi-faceted efforts make it difficult to isolate a single cause for the changes, but the changes
appear to be real and of the predicted magnitude and direction. Continued measurements are
certainly in order in this watershed as well as others, but the initial results suggest that with good
baseline data even relatively modest (25%) changes in nutrient load can be detected against
background variation on time scales fast enough to help inform policy decisions.
John T. Lehman
Douglas W. Bell
Kahli E. McDonald
Department of Ecology and Evolutionary Biology
Natural Science Building
University of Michigan, Ann Arbor 48109-1048
USA
Correspondence: John T. Lehman, Natural Science Building, University of Michigan, Ann
Arbor, Michigan 48109-1048 USA. Email: jtlehman@umich.edu
References
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Michigan, January 2006.
http://www.a2gov.org/government/publicservices/systems_planning/Environment/Docu
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MDA 2007. Report to the Minnesota Legislature: Effectiveness of the Minnesota Phosphorus
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Acknowledgements
This study was funded in part by U.S. EPA STAR grant R830653-010, USDA CSREES 2006-
02523, and the city of Ann Arbor. We thank E. Kenzie for providing daily discharge data for the
AAWWTP.