Gra

zEco

nomicsPapers

–GEP

GEP 2017–04

Identifying Phosphorus Hot Spots: A

spatial analysis of the phosphorus balance

as a result of manure application

Stefan Borsky and Alexej ParchomenkoJuly 2017

Department of Economics

Department of Public Economics

University of Graz

An electronic version of the paper may be downloaded

from the RePEc website: http://ideas.repec.org/s/grz/wpaper.html

Identifying Phosphorus Hot Spots:A spatial analysis of the phosphorus balance as a

result of manure application

Stefan Borsky† and Alexej Parchomenko*

†University of Graz, Wegener Center for Climate and Global Change, Brandhofgasse 5, A-8010

Graz, Austria.* Corresponding author. Vienna University of Technology, Institute for Water Quality, Resource

and Waste Management, Karlsplatz 13, 1040 Vienna, Austria and VITO, 200 Boeretang, 2400

Mol, Belgium, e-mail: alexej.parchomenko@tuwien.ac.at.

July 26, 2017

Abstract

In this paper, we analyze the phosphorus balance as a result of manure application

on the parish level for Denmark and investigate its local geographic distribution. For

our analysis, we determine phosphorus loads for the five main animal groups and the

phosphorus demand of the fifteen major crop categories. To identify statistical sig-

nificant local patterns of phosphorus over- and undersupply we apply Getis-Ord Gi*

hot spot analysis. Our results show that there is a large variability in the phosphorus

balance within Denmark. Statistically significant hot spots appear mainly along the

west coast, while cold spots are predominantly present on southern and eastern coasts

towards the Baltic Sea. The proximity of oversupply areas to water bodies and other

environmental sensitive areas reinforces the need for further phosphorus regulation.

These findings show the importance of a spatial targeted regulation, which allows

different levels of phosphorus application depending on local economic and environ-

mental circumstances, e.g., distance to an environmental sensitive region.

Keywords: Phosphorus, Spatial cluster detection, Nutrients balancing, Manure,

Phosphorus recycling.

JEL: Q15, Q19, Q52, Q53.

* This paper was written in part during an appointment at the Department of Environmentaland Business Economics, University of Southern Denmark. This research did not receive anyspecific grant from funding agencies in the public, commercial, or not-for-profit sectors.

1

1 Introduction

Animal manure is a side product of livestock rearing systems. It is derived from

animal feces and is mainly used as organic fertilizer in agriculture. It contains nu-

trients, such as nitrogen, phosphorus and potash. Today, the application of manure

is regulated on national level, e.g., Dutch Manure and Fertilizer Act (1999) or the

Danish Action Plans for the Aquatic Environment (APAEs), as well as international

level, e.g., European Nitrates Directive (EEC 1991), European Water Framework

Directive (EU WFD 2000) and the EU Rural Development Program (EC 2005).

The aim is to control the amount of nutrients entering the field and limit the corre-

sponding run-off to and pollution of adjacent rivers and other water bodies (Szogi,

Vanotti & Hunt 2015).

Despite thirty years of regulatory effort to reduce nutrient pollution from agri-

culture, improvements are still important to be made (Kaspersen, Jacobsen, Butts,

Jensen, Bøgh, Seaby, Muller & Kjær 2016). In general, regulation of manure faces

two problems. First, it is often applied uniformly on all agricultural land in a

country. This means that the level of regulation is not or only very coarsely spa-

tially targeted, which regularly ignores the varying capacity of a specific field and

crops to uptake nutrients. Second, the regulation regularly focuses on one nutrient,

namely nitrogen, thereby often ignoring the other nutrients, which are contained in

manure and which do not appear in fixed relations (Sharpley, Chapra, Wedepohl,

Sims, Daniel & Reddy 1994, Goetz & Zilberman 2000). Manure application rates

are based on the regulated animal units per ha, where one animal unit translates

in 100 kg nitrogen. This can potentially divert attention from balancing of other

nutrients. Additionally, nutrients in manure appear in opposite ratios as required

by most crops (Szogi et al. 2015). These problems can result in a severe imbal-

ance of nutrients on the agricultural fields with a significant local oversupply in

some fields, whereas others exhibit a nutrients deficit (Bateman, van der Horst,

Boardman, Kansal & Carliell-Marquet 2011). This makes the balance between nu-

trient inputs to the soil and nutrient removals from the soil critical for sustainable

agriculture and appropriate resource use (Goetz & Zilberman 2000, Kuosmanen &

Kuosmanen 2013, Kuosmanen 2014).

To illustrate such a case of nutrients imbalance, we show the example of phos-

phorus application stemming from manure in Danish livestock and crop systems.

Denmark is a country, which has a large livestock farming industry and therefore,

a large amount of manure, which has to be applied on agricultural land. In Den-

2

mark manure application is in general regulated by the ”Harmony rules”.1 This

regulation focuses on the amount of nitrogen in manure and therefore indirectly

affects the total phosphorus application rates per hectare. In particular, the regu-

lation specifies the livestock density on a farm through nitrogen limits of 140-170

kg nitrogen/ha and requires redistribution of excess manure based on written con-

tracts between farmers (Sommer, Christensen, Schmidt & Jensen 2013). Today, it

is estimated that, on average, fields in Denmark have an oversupply of phosphorus

(Sørensen & Møller 2006, Jacobsen 2011). Given the pattern of Danish livestock

production, with two thirds of all livestock units being located in Mid-Jutland and

Southern Denmark and only 11 per cent on Zealand (Klinglmair, Lemming, Jensen,

Rechberger, Astrup & Scheutz 2015), it is likely that on local level these values

are highly heterogeneous. This can have a strong influence on manure management

options and local redistribution possibilities.

The assessment of phosphorus levels on agricultural land is done in general on

global, national and regional scale (see, for example, Sheldrick, Syers & Lingard 2002,

OECD & Eurostat 2007, Bateman et al. 2011). For Denmark, phosphorus balance

assessments exist on the national and the local level. Sørensen & Møller (2006) and

Jacobsen (2011) assess the phosphorus balance on the national level and find that

on average Danish national oversupply of phosphorus is in the magnitude of 8-10

kg P/ha. Klinglmair et al. (2015), assess phosphorus balances for Denmark based

on three regions. Considering a wide spectrum of phosphorus flows, they find that

largest inflows occur in the form of feed imports and largest outflows are exported

in the form of food. Manure has the largest potential for mineral fertilizer substi-

tution, but availability of manure is highest in areas with lowest demand. Further,

they find large differences in manure application and phosphorus demand between

the three regions. On the local level, phosphorus budgets exist through farm-gate

(Nielsen & Kristensen 2005), soil surface and soil system approaches (Kuosmanen &

Kuosmanen 2013). The constructed budgets are usually based on case studies with

selected farms (Nielsen & Kristensen 2005, Spiess 2011), or for sensitive areas such

as lakes, specific catchments or fjords (Kaspersen et al. 2016). Based on those stud-

ies the phosphorus balance ranges between 7 to 42 kg phosphorus/ha oversupply in

Denmark and depends on the farm type, animal species, size and housing technology

(Nielsen & Kristensen 2005). However, for such detailed studies a full coverage on

a national level is not possible and not intended, even though farm-gate studies are

1 Ministry of Environment and Food in Denmark (2015): Vejledning om Gødsknings- og har-moniregler. Online available under http://www.naturerhverv.dk.

3

subsidized by the Danish Government to increase the availability of information in

the long run (Nielsen & Kristensen 2005).

Based on this setting, the aim of this study is, first, to determine the level of

phosphorus under- and oversupply stemming from animal manure on a local level

for the whole of Denmark. To do this we apply a soil surface approach, which ac-

counts for nutrients entering the soil via the surface and that leave the soil via crop

uptake. Thereby, we focus on animal manure and aggregate phosphorus loads of the

main animal manure categories and phosphorus demand of the fifteen major crop

categories on the level of the parish, which is the smallest census unit in Denmark.

This enables us to analyse spatial differences in the phosphorus balance on a very

detailed level for the whole country. Moreover, we analyze the balance not from the

perspective of permitted nutrient loads, but from the perspective of plant demand.

This shows that permitted levels of nutrient application can lead to large accumu-

lations of phosphorus over time. In a second step, we then use the local phosphorus

balance values and Getis-Ord Gi* statistics to identify statistical significant local

patterns, i.e., hot- and cold spots, of phosphorus over- and undersupply. This en-

ables us to describe how the phosphorus balance is geographically distributed and

gives us statistical evidence of spatial clustering.

Our results suggest that there is a large variability in phosphorus over- and un-

dersupply within Denmark. Whereas in the east of Denmark an undersupply can be

observed, the situation looks very different in the south, mid and northwestern parts

of Denmark. In these areas the parishes show an average oversupply of phosphorus

in the range between 23-28 kg/ha. The difference in the extent of phosphorus comes

from the imbalance in the amount of manure and agricultural production in the

individual parish and it shows the potential of inter-parish manure redistribution.

The outcome of the hot spot analysis shows several locally confined statistically

significant spatial clusters of parishes with a high level of phosphorus oversupply

along the west coast of Denmark. The proximity of oversupply areas to water bod-

ies and other environmental sensitive areas highlights the potential environmental

and economic impact of the local phosphorus balance in Denmark.

These results are of high environmental and economic relevance. Reducing the

degree of nutrient imbalance on agricultural farmland is essential to dampen the

nutrient run off into nearby water bodies. This reduces the resulting environmental

damage, like a high level of eutrophication or the contamination of groundwater

(e.g., Vitousek, Aber, Howarth, Likens, Matson, Schindler, Schlesinger & Tilman

1997, Tilman, Fargione, Wolff, D’Antonio, Dobson, Howarth, Schindler, Schlesinger,

Simberloff & Swackhamer 2001, Robertson, Paul & Harwood 2000).

4

Different regulative instruments, such as input controls of the animal feed and

technical barriers to limit the degree of run off in adjacent rivers and water bodies,

have been introduced to cope with the nutrients imbalance. Given that Denmark is

planning to better regulate the phosphorus application per hectare of agricultural

land (Willems, van Grinsven, Jacobsen, Jensen, Dalgaard, Westhoek & Kristensen

2016), information on nutrients balance hot spots on local level and their pattern

in space can improve the economic effectiveness of these instruments by allowing to

target them spatially across the regions (Kuosmanen & Kuosmanen 2013, Jacobsen

& Hansen 2016).

This article is structured as follows. Chapter 2 sets out the methodological

strategy to determine the phosphorus balance per parish and to identify areas with

a statistical significant spatial clustering of parishes with a phosphorus surplus or

deficit. In Chapter 3, the results of the spatial analysis are shown and potential

regulation options are discussed. Chapter 4 concludes.

2 Method

In this paper, the phosphorus balance is analysed on the parish level, which repre-

sents former church administration units and is the smallest census unit in Denmark

(Schullehner & Hansen 2014). The study covers fifteen crop categories and five an-

imal manure categories. As a trade-off due to the high degree of disaggregation,

not all potential phosphorus flows, like compost, sewage sludge, crop residues and

mineral fertilizers, are considered. We focus our analysis on animal manure based

on following two reasons: Due to its large livestock farming industry, manure is the

largest source of non-mineral fertilizer in Denmark. Nielsen & Kristensen (2005)

show that compared to the soil type animal stock per land area has a high im-

pact on the nutrient surplus. Further, manure contains multiple types of nutrients,

whereas the focus of the regulation is mainly on nitrogen. This can lead to large

imbalances of applied nutrients.

The analysis is performed in the following steps: First, phosphorus supply based

on animal manure production is calculated on parish level. Second, the demand for

phosphorus depending on the crop type is determined per field and aggregated on

the parish level. Third, based on phosphorus supply and demand the phosphorus

balance per parish is calculated. And, fourth, a hot spot analysis is performed by

employing the Getis Ord Gi* statistical method (Ord & Getis 1995) to identify

statistical significant local patterns of spatial clustering.

5

2.1 Animal phosphorus supply

Five animal groups, including cattle, pig, poultry, mink and a category ”other”,

which summarises smaller groups of animals like sheep, are the contributors to the

phosphorus supply in Denmark. The phosphorus values are calculated for the animal

stock, which is published in the central animal register. The data is provided by the

Danish online GIS service of the Ministry of Environment and Food2. The nutrient

load is reported in animal units (Table 1). Each animal unit represents the yearly

manure load of a milking cow, but more precisely, it stands for a yearly manure load

of 100 kg nitrogen.

To calculate the phosphorus supply for each parish, animal numbers per animal

group are averaged over five years from 2011 to 2015.3 The sum of the phosphorus

load in manure, pl, over all animal categories, a, constitutes the supply side for each

parish, j, and is given by:

PSj =A∑

a=1

pla. (1)

From the data in Table 1, one can see that on average 39 slaughter pigs, 170 laying

hens, or 4.4 sows contribute the same nitrogen load over one year. This measure

complies with the procedure presented in the handbook for constructing phosphorus

balances jointly published by the OECD and Eurostat (OECD & Eurostat 2007).

They propose to use animal numbers for multiplication with the specific manure

coefficient of that animal.

We derive our nitrogen/phosphorus ratios based on the calculation of Christensen

& Sommer (2013), who determine the nutrient load for the dry matter of different

types of animal manure. Additionally, information on the nitrogen/phosphorus ratio

for mink, the largest fur animal group in Denmark, is provided by Newell (1999).

The manure nitrogen/phosphorus ratio varies between the animal groups as specified

in Table 2.

For cattle the average of slurry and farmyard manure is calculated to take into

account the contaminants from bedding material in farmyard manure. This results

in one animal unit of cattle supplying 21.8 kg phosphorus. For pigs we take the

nutrient content for sows, which is a lower bound estimate for that animal group,

which results in one animal unit of pigs supplying 25.5 kg phosphorus per year.

2 www.jordbrugsanalyser.dk3 An average over 5 years is taken to smooth out cyclical variation in animal stock. Averaging

the animal numbers over five years smooths yearly fluctuations, which mainly exist due to the highspatial resolution of the data.

6

Table 1: Animal groups and animal unit values

Animal Group Animal Unit Comments

Cattle 1.00 0.75 animal unit equivalent of one dairy cow

Pig

of which sows 4.40 with piglets up to 7.4 kg

of which slaughter pigs 39.00 32-107 kg

Poultry

of which laying hens 170.00

of which slaughter chicken 3, 020.00

Mink 29.00

Notes: Animal units based on a manure load of 100 kg nitrogen. Based on Danish ”Harmonization rules for

agriculture, notice of authorisation and approval of livestock” (Bekendtgørelse om tilladelse og godkendelse m.v.

af husdyrbrug) and (Newell 1999).

Table 2: Phosphorus/nitrogen ratios

Animal category Mean P Mean N P/N ratio

Cattle - - 0.218

Pig 42.0 165.0 0.255

Poultry 21.0 39.0 0.538

Mink - - 0.300

Other - - 0.160

Notes: Phosphorus (P) and nitrogen (N) values are given in

gramm/kg drymatter and are based on Christensen & Sommer

(2013). The ratio for mink stems from Newell (1999). The value

for cattle is the average of the phosphorus/nitrogen ratios for

slurry (0.262) and dry matter (0.173). For pigs the phosphorus

and nitrogen values of sows are taken. For the category ”other”

the lowest phosphorus/nitrogen level for an animal in this group

is taken.

For poultry, the ratio is 53.8 kg phosphorus per animal unit, which represents a

much larger phosphorus content per mass unit. Even though other fur animals,

like fox, fin raccoon and fitchew are bred in Denmark, mink, with over 19 million

harvested skins per year4, is by large the dominant fur animal and other subgroups

can be neglected. Based on Newell (1999) one animal unit of mink produces 30

kg of phosphorus per year. For the animal category ”other”, which has a rather

small fraction in the overall animal stock, a phosphorus/nitrogen ratio of 16 kg per

4 Danish Agriculture and Food Council, http://www.agricultureandfood.dk/

danish-agriculture-and-food/mink-and-fur

7

animal unit is used, which is the lowest phosphorus/nitrogen ratio available for any

animal and represents a lower bound estimate for this category. This should avoid

overestimation of animal phosphorus supply.

The overall phosphorus supply is calculated for each group by multiplying the

animal units and the phosphorus to nitrogen ratio for each animal group and is laid

out in Table 3.

Table 3: Phosphorus supply by animal group and total number of animalsin animal units.

Cattle Pig Poultry Mink Other

Animals (in million animal units) 1,190.0 1,114.0 0.086 0.097 0.018

Phosphorus supply (in tons) 25,942.0 28,407.0 4,626.8 2,910.0 288.0

Notes: An animal unit represents the yearly manure load of a milking cow, but more precisely, it stands

for a manure load of 100 kg nitrogen.

The data shows that around 87 percent of phosphorus are supplied by cattle

and pigs, with nearly equal fractions, even though the real number of pigs is much

larger. Poultry contributes with 7.5 percent to the yearly phosphorus supply, while

the remaining 5 percent stems from fur animals and the category ”other” animals.

2.2 Plant demand

Most modern crops remove between 5 and 35 kg phosphorus/ha, with some high

yielding maize, removing more than 45 kg phosphorus/ha (Scholz, Roy & Hellums

2014). To analyse the distribution of phosphorus demand of different crops locally,

a five-step procedure is performed (see Figure 1).

First, we preselect the most relevant crops grown in Denmark. The selection is

based on the total crop area in ha as laid out in Table 4, which is provided by the

Danish Agriculture and Food Council.5 The 15 selected crop categories represent

94 per cent of all crops produced during the year 2014. Second, the phosphorus

demand is assigned to each preselected crop category. The phosphorus demand

values are based on the Danish fertilizer manual, which refers to each crop category

and is published by the Danish Ministry of Environment and Food. Third, the

phosphorus demand values (see Table 4) are assigned to field polygons within a GIS

5Danish Agriculture and Food Council (2015); http://www.agricultureandfood.

dk/~/media/lf/tal-og-analyser/fakta-om-erhvervet/fakta-om-erhvervet/2014/

facts-and-figures/facts-and-figures-2015.pdf.

8

Preselection of crop categories

Assigning phosphorus demand to crops

Assigning crop phosphorus demand

to GIS field polygon data set

Calculating phosphorus de-

mand per field polygon

Aggregating field poly-

gons at each parish polygon

Figure 1: Procedure to calculate phosphorus demand on parish level

field polygon data set.6 In most cases, multiple sub-categories, which are represented

by the specific crop code within the GIS data set (see Table 4), must be assigned to

one crop category. For example, the phosphorus demand of 19 kg P/ha for winter

wheat is assigned to winter wheat types with crop codes 2, 8, 9 within the GIS data

set. These multiple crop codes, refer to subcategories of winter wheat types grown

in Denmark. Fourth, the phosphorus demand values of each field are multiplied by

the field area in ha. This results in phosphorus demand values at field level. Fifth,

the field polygons are aggregated for each parish, based on a parish polygon data

set provided by the Danish Environment and Food Council’s online-GIS service.7

The calculation is performed with one harvest per year. Before the next main

crop is planted, catch crops accommodate the nutrients and avoid leaching of nutri-

ents during the wet and non-growing period of the year. Even though two harvests

may be possible under certain circumstances, i.e. in the combination of main crop

and feed crops for animals, it is assumed that either winter or summer crops are

grown, followed by catch crops or a fallow period.

6 ftp://131.165.57.138/Jordbrugsanalyseportal/Afgr%F8der/Afgroede_2012/7 http://miljoegis.mim.dk/cbkort?profile=jordbrugsanalyse

9

Tab

le4:

Agr

icu

ltu

ral

ph

osp

hor

us

dem

and

dat

afo

rco

nsi

der

edcr

opca

tego

ries

Tot

alcu

ltiv

ate

dar

eakg

P/h

aA

rea

Are

aas

fract

ion

Cum

ula

tive

are

aC

rop

code

(in

ha)

(dem

and)

in10

00ha

ofto

tal

are

aas

fract

ion

Win

ter

whea

t19

646

0.24

650.2

465

2,8,9

Spri

ng

bar

ley

21

483

0.1843

0.4

308

1

Gra

ssou

tsid

ero

tati

on13

200

0.0763

0.5

071

82-

89,1

08,2

61

Cor

nan

dsi

lage

mai

ze45

190

0.07

250.5

795

5,72

Rap

ese

edto

tal

24

166

0.06

330.6

429

15

Win

ter

bar

ley

18

119

0.04

540.6

883

7

Rye

20

106

0.04

040.7

287

10,1

1

See

ds

for

sow

ing

15

76

0.0290

0.7

577

27-4

9,2

59

Cer

eal

for

gree

nfo

dder

22

62

0.0237

0.7

814

66,7

0,7

2,78,

80

Pot

atoes

42

42

0.01

600.7

974

50-5

3

Oat

s20

36

0.01

370.8

111

3

Suga

rb

eet

44

36

0.01

370.8

249

54

Tri

tica

le22

34

0.01

300.8

378

12

Oth

ers

22

260

0.0992

0.9

370

4,13

Uncu

ltiv

ated

land

0-

--

120

Notes:

Valu

esfo

rgra

ssou

tsid

ero

tati

on

refe

rto

norm

al

yie

ldin

the

fert

iliz

erm

anu

al.

Valu

esfo

rp

ota

toes

base

don

aver

age

yie

ldof

fou

rd

iffer

ent

pota

toca

tegori

es.

Oth

ers

incl

ud

eall

oth

ercr

op

typ

esan

dvalu

eis

base

don

the

aver

age

of

all

main

crop

sw

eighte

dby

are

a.

Th

eto

tal

lan

dare

asu

ms

up

to25,0

86,0

00.0

0h

a.

Acc

ord

ing

toth

eD

an

ish

fert

iliz

erru

les,

pla

nts

for

gro

win

gse

eds

have

the

sam

ep

hosp

horu

sd

eman

dvalu

esas

pla

nts

gro

wn

as

crop

s.

10

The area size of each agricultural field polygon and the distribution of crop

categories within each parish allows to assign phosphorus values to each hectare and

to calculate the crop specific demand per parish as laid out in Figure 1. The sum

determines the absolute demand of phosphorus per parish, j, and is given by:

PDj =H∑

h=1

cdh (2)

where cd is the phosphorus demand of the crop in field, h, and H is the total number

of fields in parish, j.

2.3 Phosphorus balance

To calculate the final phosphorus balance per parish, we exclude polygons with a

large degree of build-up land, i.e. urban dwellings. They have a low proportion of

animals to agricultural land, which makes these parishes appear extreme in their

phosphorus balance.8 Selection of such parishes is undertaken through a classifi-

cation of Corine data, a land use classification data set of the European Union

countries.9 Parishes are excluded, if more than 50 percent of the overall parish area

is covered by build-up land.10 This results in 343 parishes being classified as urban

dwellings, which are excluded from our analysis. For the remaining 1837 parishes

the phosphorus balance, PB, per parish, j, is constructed by the subtraction of

phosphorus crop demand from the phosphorus load.

2.4 Hot spot analysis

To describe how the phosphorus balance is geographically distributed and to identify

phosphorus hot spots in Denmark, we apply the Getis-Ord Gi* statistical method

as laid out in Ord & Getis (1995). A phosphorus hot spot is defined as an area with

a statistical significant spatial clustering of parishes with high levels of phosphorus

oversupply. Phosphorus cold spots are areas, in which parishes with an undersup-

ply of phosphorus are spatially clustered. The knowledge of the spatial pattern

of the phosphorus balance enables to determine potential priority areas for future

phosphorus regulation.

8 The impact of the exclusion of these extreme values on the overall phosphorus balance willbe discussed in more detail in Section 3.

9 EEA (2016) - Corine land cover 2012 raster data; http://www.eea.europa.eu/

data-and-maps/data/clc-2012-raster10 Validation of this exercise is performed for selected parishes via aerial photo interpretation

for major agglomerations, using Google Earth.

11

The Getis-Ord Gi* statistical method is given as

G∗i =

∑nj=1 wijPBj − X

∑nj=1 wij

S

√n∑n

j=1 w2ij−(

∑nj=1 wij)2

n−1

(3)

where PBj is the level of phosphorus balance in parish, j, as calculated in Section 2.3,

n is the total number of parishes and S denotes the standard deviation of the sample.

The spatial weight, wij, which determines the degree of connectivity between parish

i and j, is based on the Queen’s case method with 8 contiguous neighbors.

The Getis-Ord Gi∗ statistic calculates a z-score with a respective p-value for

each parish and evaluates it in respect to neighboring parishes. Thereby, statisti-

cally significant high or low value parishes are identified and checked whether they

are surrounded by similar parishes. If a parish is not surrounded by statistically

significant high or low values, it does not appear as a hot spot or cold spot on the

map, even though it can have an extreme value itself. To be a significant hot spot

or cold spot at a 5% significance level, the z-values must be located outside the in-

terval of −1.96 and 1.96 (Harris, Goldman, Gabris, Nordling, Minnemeyer, Ansari,

Lippmann, Bennett, Raad, Hansen et al. 2017).

3 Results and Discussion

3.1 Results of the phosphorus balance calculation

The results of the phosphorus balance analysis as laid out in Section 2 is pictured in

Figure 2. The general pattern is an east-west gradient of surplus phosphorus, with

fewest oversupply values on Zealand in the east of Denmark, and largest oversupply

values in Jutland, in the west of the country. In Jutland, the oversupply areas are

mainly concentrated in the centre-northern part. Funen acts as a bridge by linking

the two different parts of Denmark.11

The resulting pattern reflects the influence of historically developed production

patterns and regional specialization of Danish agriculture. Historically, crop pro-

duction was concentrated in the east of Denmark, where higher yields were possible

11 It is important to note that the supply and demand values do not account for cross-parishdistribution. This sometimes results in having parishes with low phosphorus concentration andhigh phosphorus concentration values neighbouring each other. Although, it may exaggerate theover- and undersupply of phosphorus it gives a clear picture of the potential for interregional redis-tribution of manure. Further, phosphorus is much less dissolvable in water than other nutrients,which makes the leaching of phosphorus into adjacent parishes generally to be limited (Kuosmanen& Kuosmanen 2013).

12

Figure 2: Phosphorus balance in kg/ha of agricultural land on parish basis for Denmark

13

due to better soil conditions, while livestock production became more dominant in

Jutland (Klinglmair et al. 2015). It is indicated that some of the development can

be attributed to the availability of low cost protein in the form of cereal substitutes

and soybeans, and that high-density livestock areas developed close to harbours

(Neumann, Elbersen, Verburg, Staritsky, Perez-Soba, de Vries & Rienks 2009). To

a large degree, this pattern persists until today (Oelofse, Jensen & Magid 2013).

The phosphorus balance ranges mostly between 0 to 50 kg of phosphorus/ha,

while it is important to note that around 10 percent of the considered parishes have

an undersupply of phosphorus up to -13.4 kg phosphorus/ha. Regionally, the phos-

phorus balance is rather heterogeneous. The northern region close to the Limfjord

has the highest local phosphorus concentration, while Zealand in the east of the

country has the lowest concentration. As shown in Table 5 on average the phospho-

rus balance ranges from 5.47 kg phosphorus/ha in the capital region and Bornholm

to 28.14 kg phosphorus/ha in the northern region of Jutland. The spread between

the extreme values is in tendency larger in regions with higher mean oversupply

values.

Table 5: Phosphorus values for Denmark and its five regions

Min 1st Quart. Median Mean 3rd Quart. Max

Denmark -13.40 6.70 18.00 19.78 30.00 324.80

North-Jutland -10.20 16.55 27.15 28.14 37.75 124.00

Mid-Jutland -7.70 11.60 21.70 23.56 32.00 324.80

Southern Denmark -8.00 12.60 23.10 23.03 32.00 103.30

Zealand excl. capital region -5.50 -0.70 4.50 6.63 11.40 86.80

Capital region and Bornholm -13.40 -2.50 1.20 5.47 11.60 44.60

Taking the sum of all positive and negative values, the national phosphorus

balance results in an oversupply of 51,224 Mg. Compared to other studies the

phosphorus balance of this study is higher. Sørensen & Møller (2006) report a gen-

eral phosphorus balance of around 10 kg/ha. Heckrath, Bechmann, Ekholm, Ulen,

Djodjic & Andersen (2008) report a value of 13 kg P/ha. Whereas, Jacobsen (2011)

reports a diminished oversupply value due to change in feeding practices, especially

on pig farms, which led to a phosphorus oversupply value of 7-8 kg/ha. The larger

values in this study stems from the fact that we, due to the high disaggregation of

our study, are able to distinguish between build-up land like urban dwellings and

agricultural land. Build-up land often has a low proportion of animal to agricultural

land, which results in extremely low values in their phosphorus balance. Excluding

14

this mainly negative values results in a larger average value of the phosphorus bal-

ance.12 Additionally, it has to be noted that we base our calculation of phosphorus

demand of crops assuming one harvest per year. Increasing the amount of harvests

per year would increase the demand but would have no significant impact on the

pattern of the phosphorus balance.

3.2 Identifying phosphorus hot- and cold spots

Figure 3 shows the outcome of the spatial cluster analysis based on the Getis-Ord

Gi* statistics considering 8 neighbors as described in Section 2.4.13

Compared to the fractured picture of the phosphorus balance laid out in Figure 2,

we are now able to clearly identify various clusters of spatially autocorrelated high

values of phosphorus mostly along the west coast of Jutland. Whereas, some clus-

ters with an undersupply of phosphorus are located on Zealand and around major

agglomerations around the cities of Odense, Aarhus, Randers and Aalborg. Further,

phosphorus hot spots in the middle and north of Jutland are often adjacent to larger

waterbodies, which can be negatively affected by potential phosphorus run off from

the agricultural fields.

In a further step, in Figure 4 and Figure 5, the spatial pattern of phosphorus

hot- and cold spots is combined with information on environmental sensitive areas.

This gives a better insight in the potential environmental impact of these spatial

clusters. In Figure 4 phosphorus hot spots in relation with nature protection areas

and in Figure 5 with nitrate sensitive areas are plotted. Nature protection areas

are represented by Natura 2000 areas. Nitrate sensitive areas are regions, which are

sensitive to nitrate leakage. It can be seen that clusters of phosphorus oversupply

can be found adjacent to these environmental sensitive areas. In particular, nature

protection areas at the west coast of Denmark are potentially affected by phosphorus

12 Table A1 in the Appendix shows the results of the phosphorus balance analysis based on thefull sample, exclusion of the two largest and lowest values and the exclusion of the five largestand lowest values. Based on the full sample the average phosphorus balance in Denmark is 13.11kg phosphorus per ha. Excluding the 5 largest and 5 lowest values in our sample results in aphosphorus balance of 16.26 kg/ha.

13 Results of a hot spot analysis are sensitive to neighbourhood size. With increasing neigh-bourhood size hot spots will become larger and fewer. Whereas with smaller neighbourhood sizethey will capture more localized trends (Harris et al. 2017). With eight neighbours, we base ouranalysis on a local level, which supports the idea of a low degree of phosphorus leakage in spaceand the building up of local phosphorus stocks. In a robustness exercise, we increase the amountof relevant neighbors to 16 - again based on Queen’s case contiguity. Although, the outcome ofthe Getis-Ord Gi∗ statistics is sensitive to the chosen spatial weight structure, we are still able tosee a similar pattern of spatial clusters of phosphorus in Denmark. The results of this robustnessexercise are plotted in Figure A1 in the appendix.

15

Figure 3: Hot spots and cold spots for phosphorus balance values for Denmark. Based on GetisOrd Gi∗ z-score with consideration of 8 neighbours.

16

hot spots. In case of nitrate sensitive areas, our results show that these areas are

close to the phosphorus hot spots in particular in Northern and Southern Jutland.

These environmental sensitive areas could be first targeted to protect watersheds

from excessive phosphorus pollution.

3.3 Regulation of phosphorus oversupply

Historically, the regulation of manure in Denmark is based mainly on a uniformly

applied direct regulative approach, which is in general focused on the level of nitro-

gen. Thereby, it ignores the phosphorus content in manure, which does not appear

in fixed relations. Moreover, livestock rearing systems are not equally distributed

over space in Denmark. As shown in Figure 2 and Figure 3 this can result in a severe

imbalance of nutrients on the agricultural fields with a significant local oversupply

of phosphorus in some areas, whereas others exhibit a phosphorus deficit.

This geographical heterogeneity will lead a uniform regulation to economic inef-

ficient and cost-ineffective outcomes (Jacobsen & Hansen 2016). In many cases, the

damage from phosphorus pollution depends more on spatial concentration than on

total emission. Therefore, location matters and a regulative approach, which consid-

ers the individual location in space, would be more cost-effective and economic effi-

cient (Van der Straeten, Buysse, Nolte, Lauwers, Claeys & Van Huylenbroeck 2011).

A tradeable concentration permit system or a phosphorus tax system, which the-

oretically will provide an economic efficient outcome, is difficult to administer in

situations, in which the marginal damage and marginal benefits differ significantly

in space and time (Goetz & Zilberman 2000, Van der Straeten et al. 2011). A system

of spatial limitations, like zoning, can be additionally introduced, which, determines

the level of allowed phosphorus concentration in the case of the permit trading sys-

tem or the level of the tax in case of a price regulation system locally. Additionally,

buffer zones14, riparian zones, zero-phosphorus application areas, strip cropping,

drainage ditches and others can be implemented, which hold back phosphorus by

reducing erosion and take up of nutrients (Rao, Easton, Schneiderman, Zion, Lee

& Steenhuis 2009). Depending on the definition of the zone, these approaches can

lead to outcomes, which are close to economic efficient. The identification of the

spatial pattern of phosphorus oversupply, as introduced in this paper, can assist in

determining different phosphorus zones.

14 It is indicated that even this option is challenging to be applied in the long term, because bufferzones accumulate phosphorus over time and become phosphorus sources instead of phosphorus sinks(Dodd & Sharpley 2016).

17

Fig

ure

4:P

hos

ph

oru

sh

otsp

ots

and

Nat

ura

2000

area

sF

igu

re5:

Ph

osp

hor

us

hot

spot

san

dn

itra

tese

nsi

tive

area

s

18

Depending on the spatial location, endowments and relative prices, farmers will

react differently to such a regulation. They can reduce the inputs of phosphorus,

e.g., by a change in feed or reduction of animals. Or they can reduce the negative

externality from the output, for example by transporting the manure to other farms

(Polman & Thijssen 2002) or other adjacent environmental areas. One option could

be the application of manure on adjacent nutrient poor forest areas as suggested

by Vejre, Ingerslev & Raulund-Rasmussen (2001), Tong & Chen (2002) and Zhang,

Liu, Pan & Yu (2013). A potential tightening of phosphorus levels in the future

as well as an increase in organic farming will lead to limitations in the degree of

regional redistribution of manure.15 Moreover, our analysis has shown that parishes

of undersupply and parishes of oversupply are often spread far in space. Due to its

bulkiness and high transportation costs long distance transport, i.e., interregional

redistribution of manure, is economically often not feasible. Therefore, another way

of reducing the negative externality from the output, which could become more

important in the future, is the processing of the manure. For example, manure

separation technologies, which enable the restructuring of the nutrients balance in

the manure, can potentially reduce the phosphorus pollution in the parish. Knowl-

edge of areas with high levels of phosphorus oversupply, as provided by the hot spot

analysis in this paper, could give valuable information to plan manure processing

facilities more cost effectively.

4 Conclusion

In this study, we have determined phosphorus hot spots based on manure application

for Denmark. To do this we rely on a soil surface approach to derive the phosphorus

balance for manure application on the parish level. The small-scale analysis of the

phosphorus balance in Denmark reveals a clear pattern. Statistically significant hot

spots appear mainly along the west coast, while cold spots are predominantly present

on eastern coasts. The proximity of oversupply areas to water bodies and other

environmental sensitive areas opens another perspective of the local phosphorus

balance distribution in Denmark, while making regional balancing of phosphorus

more difficult.

15 The organic farming association of Denmark agreed to phase out conventional manure applica-tions until 2022, to become input independent from conventional agriculture (Oelofse et al. 2013).This would mean that conventional farmers may have further difficulties in areas with larger organicfarm concentration to release their manures.

19

A regulation on maximum phosphorus application per ha will be implemented in

Denmark in the near future (Willems et al. 2016). Based on the findings of this study

we argue not to apply a uniform maximum level on all agricultural fields in Denmark,

but for a spatial targeted regulation, which allows for different levels of phosphorus

application depending on local economic and environmental circumstances, e.g.,

distance to an environmental sensitive region.16 In combination with an incentive

based regulative approach, like a tradeable concentration permit system (Van der

Straeten et al. 2011) or a phosphorus tax (Goetz & Zilberman 2000) it can lead to

economic efficient outcomes.

It has to be noted that this study faces some limitations. First, phosphorus is

forced artificially to stay inside the parish boundaries, which in reality can be re-

distributed between parishes. Although, this may overstate the phosphorus values

in some parishes, it helps to illustrate the potential for intraregional redistribution.

Second, this analysis is static in so far as it ignores the temporal development of

the phosphorus balance. An interesting research area would be to analyze land

use changes, animal stock changes, and their simultaneous influence on the phos-

phorus balance. Third, we do not account for the present phosphorus soil stock,

which would mean we would need detailed data on phosphorus leaching, which de-

pends on climatic, soil and topography conditions and is difficult to obtain on such

detailed level (Kuosmanen & Kuosmanen 2013). Nevertheless, our analysis would

allow to target areas for more detailed risk evaluation of phosphorus loss, like the

incorporation of transport factors and erosion (Drewry, Newham & Greene 2011).

And fourth, we solely concentrate our analysis on phosphorus from manure. Other

organic sources, like wastewater sludge, atmospheric deposition, planting material,

such as seeds and household waste, that can enter the cycle through biogas slurry,

and mineral fertilizers are not considered in our analysis.

An additional benefit in increasing the nutrients balance and reducing the run-

off lies in the context of food-security and resource scarcity. Nutrient reserves in

general and phosphor reserves in specific, which are essential for plant growth, are

scarce and concentrated in only a few supplier countries. For the European Union,

for example, more than 90% of phosphate fertilizers are imported from Morocco,

Tunesia and Russia (European Commission 2016). Therefore, better matching of

phosphorus supply and crop demand has been identified as one of the key strategies

for closing the phosphorus cycle (Bateman et al. 2011, Kuosmanen & Kuosmanen

16 It has to be noted that some spatial targeting is already taking place in Denmark. Farms,which want to increase their level of production and are close to environmental sensitive areas arefacing restrictions in the phosphorus surplus due to manure application.

20

2013, Kuosmanen 2014, Schoumans, Bouraoui, Kabbe, Oenema & van Dijk 2015,

European Commission 2016, Bicket, Guilcher, Hestin, Hudson, Razzini, Tan, ten

Brink, van Dijl, Vanner & Watkins 2014).

21

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25

Appendix

Figure A1: Hot spots and cold spots for phosphorus balance values for Denmark. Based onGetis Ord Gi∗ z-score with consideration of 16 neighbours.

26

Table A1: Phosphorus values for Denmark and its five regions - Build up landexclusion

Min 1st Quart. Median Mean 3rd Quart. Max

(a) Full sample

Denmark -7200.00 1.10 14.60 13.11 28.00 712.70

North-Jutland -14.20 14.45 26.20 28.37 37.15 712.70

Mid-Jutland -150.00 8.30 19.30 20.16 30.40 324.80

Southern Denmark -957.90 8.35 20.45 17.79 31.15 103.30

Zealand excl. capital reg. -27.00 -1.20 3.95 6.28 11.38 97.80

Capital region and Bornh. -7200.00 -1.58 0.00 -27.93 0.00 420.50

(b) Exclusion of two largest and two smallest values

Denmark -957.90 1.10 14.60 15.91 27.92 324.80

North-Jutland -14.20 14.45 26.15 26.44 37.05 124.00

Mid-Jutland -150.00 8.30 19.30 20.16 30.40 324.80

Southern Denmark -957.90 8.35 20.45 17.79 31.15 103.30

Zealand excl. capital reg. -27.00 -1.20 3.95 6.28 11.38 97.80

Capital region and Bornh. -54.50 -1.53 0.00 1.05 0.00 44.60

(c) Exclusion of five largest and five smallest values

Denmark -93.80 1.20 14.60 16.26 27.80 103.30

North-Jutland -14.20 14.30 26.10 26.16 36.90 99.60

Mid-Jutland -54.60 8.30 19.30 19.82 30.40 98.20

Southern Denmark -93.80 8.50 20.70 19.91 31.20 103.30

Zealand excl. capital reg. -27.00 -1.20 3.95 6.28 11.38 97.80

Capital region and Bornh. -54.50 -1.53 0.00 1.05 0.00 44.60

Notes: (b) −24400.00,−7200.00, 712.70 and 420.50 excluded. (c) −24400.00,−7200.00,

−957.90,−150.00,−98.60, 712.70, 420.50, 324.80, 124.00 and 106.10 excluded.

27

Graz Economics PapersFor full list see:

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Address: Department of Economics, University of Graz,

Universitatsstraße 15/F4, A-8010 Graz

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prediction of stock returns with generated bond yields

09–2012 Jorn Kleinert, Nico Zorell: The export-magnification effect of offshoring

08–2012 Robert J. Hill, Iqbal A. Syed: Hedonic Price-Rent Ratios, User Cost, and

Departures from Equilibrium in the Housing Market

07–2012 Robert J. Hill, Iqbal A. Syed: Accounting for Unrepresentative Products and

Urban-Rural Price Differences in International Comparisons of Real Income: An

Application to the Asia-Pacific Region

06–2012 Karl Steininger, Christian Lininger, Susanne Droege, Dominic Roser,

Luke Tomlinson: Towards a Just and Cost-Effective Climate Policy: On the

relevance and implications of deciding between a Production versus Consumption

Based Approach

05–2012 Miriam Steurer, Robert J. Hill, Markus Zahrnhofer, Christian Hartmann:

Modelling the Emergence of New Technologies using S-Curve Diffusion Models

04–2012 Christian Groth, Ronald Wendner: Embodied learning by investing and speed

of convergence

03–2012 Bettina Bruggemann, Jorn Kleinert, Esteban Prieto: The Ideal Loan and the

Patterns of Cross-Border Bank Lending

02–2012 Michael Scholz, Jens Perch Nielsen, Stefan Sperlich: Nonparametric

prediction of stock returns guided by prior knowledge

01–2012 Ronald Wendner: Ramsey, Pigou, heterogenous agents, and non-atmospheric

consumption externalities