MOF, Alm.del - 2020-21 - Endeligt svar på spørgsmål 598: Spm. om hvordan målbelastningen på 36.600 tons kvælstof er konstrueret, til miljøministeren og ministeren for fødevarer, landbrug og fiskeri

Miljø- og Fødevareudvalget 2020-21
MOF Alm.del
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Application of the Danish EPA’s Marine

Model Complex and Development of a

Method Applicable for the River Basin

Management Plans 2021-2027

Management Scenario 1

–

Regional Treaties and River

Basin Management Plans 2015-2021

Technical Note

November 2020

Technical Note

March 2020

MOF, Alm.del - 2020-21 - Endeligt svar på spørgsmål 598: Spm. om hvordan målbelastningen på 36.600 tons kvælstof er konstrueret, til miljøministeren og ministeren for fødevarer, landbrug og fiskeri MOF, Alm.del - 2020-21 - Endeligt svar på spørgsmål 598: Spm. om hvordan målbelastningen på 36.600 tons kvælstof er konstrueret, til miljøministeren og ministeren for fødevarer, landbrug og fiskeri

Application of the Danish EPA’s Marine Model

Complex and Development of a Method

Applicable for the River Basin Management

Plans 2021-2027

Management Scenario 1

–

Regional Treaties and RBMP 2015-2021

Prepared for

Represented by

Danish EPA (Miljøstyrelsen, Fyn)

Mr. Harley Bundgaard Madsen, Head of Section

Eelgrass in Kertinge Nor

Photo: Peter Bondo Christensen

Authors

Anders Chr. Erichsen (DHI), Trine Cecilie Larsen (DHI), Sophia Elisabeth Bardram Nielsen

(DHI), Karen Timmermann (AU), Jesper Christensen (AU) & Stiig Markager (AU)

Quality supervisor

Project number

Approval date

Classification

Mads Birkeland (DHI), XX (DHI), Nikolaj Reducha Andersen (AU) & xxx (DCE)

11822953

Xx 2020

Open

DHI

•

Agern Allé 5

•

DK-2970 Hørsholm

•

Denmark

Telephone: +45 4516 9200

• Telefax:

+45 4516 9292

•

[email protected]

•

www.dhigroup.com

Preface

This report is commissioned and funded by the Danish Environmental Protection Agency (EPA).

The data, methods and results included in the report are intended to be an integrated part of the

material behind the Danish River Basin Management Plans (RBMP) 2021-2027.

The work reported was managed and performed by DHI and AU/DCE. During the project, a

steering committee followed the development, and was involved through dialogue and follow-up

on progress, etc. The steering committee consisted of members from the Danish Ministry of

Environment and Food (MFVM), the Danish EPA (MST), DHI and AU.

In addition, a follow-up group consisting of members from

The Danish Agriculture & Food

Council,

SEGES, Sustainable Agriculture (BL), the Danish Society for Nature Conservation, the

Danish Sports Fishing Association, Danish Fishermen PO (DFPO), the Danish Ports, and

KL/municipalities was affiliated with the project. The follow-up group has been continuously

informed about the progress of the project at meetings convened by the MFVM.

Choice of methods, data processing, description and presentation of results have been solely

AU’s and DHI’s decision and responsibility.

managementscenario1_udkast2020.docx

CONTENTS

Preface

2.1

2.1.1

2.1.2

2.2

2.3

2.4

Introduction ................................................................................................................. 1

Preconditions for MAI Calculations ........................................................................... 2

Management Scenario Definitions ................................................................................................. 2

Management Scenario 1

–

Regional Treaties and RBMP 2015-2021........................................... 2

Scenario Loadings ......................................................................................................................... 2

Method for Calculating Danish N-MAI ........................................................................................... 5

Results ........................................................................................................................................... 6

Closing Remarks .......................................................................................................................... 14

References ................................................................................................................. 15

FIGURES

Figure 2-1

Figure 2-2

Distribution of reductions applied in scenario 1. ............................................................................ 4

Atmospheric N depositions summarised at overall water body level. ............................................ 5

TABLES

Table 2-1

Table 2-2

Overview of input data used to construct management scenario 1. .............................................. 5

Maximum Allowable Nitrogen Inputs (N-MAIs) for Danish water bodies given the

implementation of the Baltic Sea Action Plan, German nutrient reductions according to

WFD and reductions in atmospheric N deposition according to the NEC directive. ...................... 7

Water body-specific MAIs based on the two indicators chlorophyll-a (Chl-a) and light

penetration depth (light) estimated from either statistical models (STAT) or mechanistic

models (MEK). ............................................................................................................................. 18

Water body specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and

light penetration depth (light) estimated from either statistical models (STAT) or

mechanistic models (MEK). ......................................................................................................... 26

Water body-specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and

light penetration depth (light) estimated from either statistical models (STAT) or

mechanistic models (MEK). ......................................................................................................... 34

Water body-specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and

light penetration depth (light) estimated from either statistical models (STAT) or

mechanistic models (MEK). ......................................................................................................... 42

Water body-specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and

light penetration depth (light) estimated either statistical models (STAT) or mechanistic

models (MEK). ............................................................................................................................. 50

Table A- 1

Table B- 1

Table C- 1

Table D- 1

Table E- 1

APPENDICES

Appendix A Maximum Allowable Nitrogen Inputs (MAIs) based on management scenario 1 and

assuming 0% reduction in Danish land-based P loads ............................................................... 17

Appendix B Maximum Allowable Nitrogen Inputs (N-MAIs) based on management scenario 1 and

assuming 10% reduction in Danish land-based P loads ............................................................. 25

Appendix C Maximum Allowable Nitrogen Inputs (MAIs) based on management scenario 1 and

assuming 20% reduction in Danish land-based P loads ............................................................. 33

Appendix D Maximum Allowable Nitrogen Inputs (MAIs) based on management scenario 1 and

assuming 30% reduction in Danish land-based P loads ............................................................. 41

Appendix E Maximum Allowable Nitrogen Inputs (MAIs) based on management scenario 1 and

assuming 50% reduction in Danish land-based P loads ............................................................. 49

managementscenario1_udkast2020.docx

Introduction

When preparing the Danish River Basin Management Plans 2015-2021 (RMBP 2015-2021),

DHI and Aarhus University (AU) developed a number of mechanistic (DHI) and statistical (AU)

models that were used for calculating chlorophyll-a target values defining the threshold (GM)

between

‘Good

Ecological Status’ (GES) and

‘Moderate

Ecological Status’. The models were

also used for calculating Maximum Allowable Inputs (MAIs) of total nitrogen (N) from Danish

catchments based on chlorophyll-a threshold values and a proxy for eelgrass depth limit. Hence,

the development aimed at both the model development and the development of a method for

calculating the MAIs.

As part of the political, regulatory package

‘The

Food and Agriculture Package from 2015’ an

international evaluation of the procedures used in the RBMP 2015-2021 was conducted. The

evaluation was finalised autumn 2017 with a report (Herman

et al.

2017) including a number of

recommendations for improving the scientific background behind the RBMP 2021-2027.

To follow up on the international evaluation, the Danish EPA facilitated a range of R&D projects

with the overall aim to develop methods to calculate robust, transparent and differentiated

chlorophyll-a reference values (and corresponding target values) and MAIs in as many water

bodies as possible for incorporation into the RBMP 2021-2027.

Two central R&D projects relate to the continued model development in the assessment of

reference chlorophyll-a values (and corresponding target values) and final MAI calculations.

Other projects also support different aspects of the final MAI calculations, but here we focus on

those two central R&D projects:

•

‘Recommendations

for the continued development of models and methods for use in the

River Basin Management Plan 2021-2027. Follow-up on the international evaluation of

marine models behind the River Basin Management Plan 2015-2021’ (Erichsen &

Timmermann 2018)

‘Application

of the Danish EPA’s Marine Model Complex and Development of a Method

Applicable for the River Basin Management Plans 2021-2027’.

•

The outcome of the above research projects is a set of MAIs based on a range of different

assumptions regarding future developments in nutrient loading from neighbouring countries and

the atmosphere as described in Erichsen

et al.

2020. In the present technical note, the

assumptions and input data behind management scenario 1 and the corresponding results are

presented. In management scenario 1, it is assumed that all national and international adopted

treaties related to nutrient management, including BSAP (Baltic Sea Action Plan), RBMP 2015-

2021, OSPAR (Oslo/Paris

convention (for the Protection of the Marine Environment of the

North-East Atlantic)),

and the NEC-directive (National Emission Ceilings directive) have been

implemented.

Preconditions for MAI Calculations

The Danish MAIs will, among other things, also depend on future loadings from neighbouring

countries and atmospheric N-depositions as described in more detail in Erichsen

et al.

2020. In

addition, some water bodies may also respond to Danish land-based P loadings why one set of

Danish land-based N-MAIs corresponds to a set of Danish land-based P-MAIs.

To be able to calculate a set of Danish land-based N-MAIs, we need to make assumptions on

future loadings and management strategies from neighbouring countries (management

scenarios) as well as assumptions regarding Danish land-based P loadings.

With respect to reductions in neighbouring countries, the Danish EPA has defined a set of

prerequisites to be used for constructing management scenarios defining potential

developments in future non-Danish land-based loadings and atmospheric deposition. For each

scenario, Danish land-based N-MAIs are calculated based on either 0%, 10%, 20%, 30% or

50% Danish land-based P reductions.

In this technical note, we have not assessed whether or not the scenarios defined by the Danish

EPA are realistic, or even possible, but solely provided N-MAIs that will ensure target reaching

given that the corresponding conditions related to nutrient loading from other countries,

atmospheric N deposition and P loading from Danish catchments are fulfilled.

2.1

Management Scenario Definitions

As mentioned above, the Danish EPA has defined a set of assumptions regarding nutrient

inputs from other countries and the atmosphere to be used as a precondition for the Danish

land-based N-MAI calculations. The assumptions are grouped into three management scenarios

and one scenario related to the interpretation of the Water Framework Directive (WFD-

scenario). The different assumptions are described in general terms in Erichsen

et al.

2020,

whereas the present technical note describes Management Scenario 1 in more details.

2.1.1

Management Scenario 1

–

Regional Treaties and RBMP 2015-2021

Management scenario 1 assumes that all national and international adopted treaties related to

nutrient management, including RBMP 2015-2021, have been implemented. This basically

corresponds to:

•

Full implementation of the BSAP (HELCOM) and similar reduction targets in the North Sea

(OSPAR)

Implementation of RBMP 2015-2021 in all relevant EU countries

Full implementation of the NEC-directive with respect to atmospheric N-deposition.

2.1.2

Scenario Loadings

The full overview of the nutrient reductions applied for management scenario 1, including

nutrient reductions in other countries than Denmark and atmospheric depositions, are

summarised in Table 2-1 and explained briefly in the following sections.

Baltic Sea Action Plan (BSAP)

With respect to Management scenario 1, the BSAP forms the foundation behind the land-based

nutrient loadings around the Baltic Sea. All countries around the Baltic Sea have adopted the

BSAP as the regional treaty that governs nutrient reductions to the Baltic Sea. Germany has,

however, adopted stricter reductions as part of the German RBMP 2015-2021, and these will be

described in the following section.

managementscenario1_udkast2020.docx

The BSAP consists of national MAIs including both land-based nutrient loadings and

atmospheric depositions. For the present calculation of Danish land-based nutrient MAIs, the

NEC directive will form the foundation for atmospheric depositions why we need to exclude the

atmospheric part of the BSAP in the present dataset. This is done by calculating the fraction of

atmospheric depositions in the baseline period (the BSAP baseline period corresponds to 1997-

2003) and assuming that the fractions are constant. Hence, the country specific MAIs is

determined by subtracting the atmospheric fraction of the total ceiling (CART). This is done for

both TN and TP, although P-depositions are relatively insignificant.

The present-day average loading (average of 2014-2018 loadings) is then compared to the land-

based MAIs within the two basins Baltic Proper (BAP) and Danish Straights (DS) and converted

into a need for reduction (in %). This estimation is done excluding Danish land-based loadings,

as they are the target of the present exercise.

RBMP 2015-2021

As mentioned above, Germany is the only country (besides Denmark), that has adopted N

reductions that are stricter than the targets defined in the BSAP.

According to the adopted German RBMP 2015-2021, nutrient targets for TN are defined as

average TN concentrations of 2.6 mg N/l in rivers discharging to the Baltic Sea and 2.8 mg N/l in

rivers discharging to the North Sea (COWI 2018). For TP no new targets have been defined in

the RBMP 2015-2021 why German TP concentrations in rivers discharging to the North Sea are

similar to present-day TP concentrations, and TP concentrations in rivers discharging to the

Baltic Sea follow the reductions determined by BSAP.

Based on Gadegast & Venohr (2015), the average concentration in the rivers discharging to the

North Sea was 4.04 mg N/l in 2005 why a change in concentrations to 2.8 mg N/l corresponds to

a 31% reduction. In COWI (2018), the need for reductions in German rivers is estimated at 30-

48% based on 2001-2005 loadings. Here we use the 31%, as the data reported in Gadegast &

Venohr (2015) also relates to the reductions used for defining reference loadings from German

and Dutch rivers discharging into the German Bight.

The reduction of 31% is inflicted on all German rivers discharging to the North Sea as well as

other North Sea rivers (due to lack of knowledge). Inflicting the same reduction on all North Sea

rivers is uncertain, but as the German rivers are the governing source of nutrients affecting

Danish waters, the uncertainty is regarded as less significant.

Concerning concentrations in rivers discharging to the Baltic Sea, COWI (2018) reports a target

of 2.6 mg N/l, and according to COWI (2018), this corresponds to a need for a reduction of 44%.

For management scenario 1, we adopt the 44% reduction from German rivers discharging to the

Baltic Sea.

Allocation of Reductions

When estimating the dose-response to nutrient reductions from neighbouring countries we

assumed a uniform reduction of 30% from all countries (except Danish loadings). Now we need

to transform local reductions to the Baltic Proper (BAP) and Danish Straits (DS) into an overall

reduction that can be applied with the estimated dose-responses.

According to HELCOM (2020), we can allocate reductions from BAP to DS and come up with an

estimate of the resulting reductions from the above scenarios. However, we will have to assume

that the impact from reductions differs between the Danish water bodies, as, e.g. German

reductions will have a profound impact on Flensburg Fjord, whereas the impact on the Sound is

regarded as less profound Hence, we operate with different reductions depending on the

individual water bodies.

Assuming no difference in impact from reductions in BAP and DS, the combination of BSAP and

German RBMP 2015-2021 equals a reduction of 4% for TN loadings and 27% for TP loadings.

Assuming difference in impacts as described in HELCOM (2020)

the corresponding TN

reductions equal a 35% reduction whereas a full impact from German RBMP 2015-2021 equals

a reduction of 44%.

As HELCOM (2020) defines a reduced impact from reductions as we move from one water body

to another (e.g. from BAP to DS), we need to distribute the above reductions from Germany and

other countries. This distribution is done according to Figure 2-1 and Table 2-1.

Figure 2-1

Distribution of reductions applied in scenario 1.

Nutrient reductions resulting from the German implementation of the RBMP (2015-2021) to

the North Sea and Baltic Sea are applied in water bodies marked with brown and yellow,

respectively. Nutrient reductions resulting from the implementation of the BSAP to the BAP

and DS are applied to water bodies marked in light blue. In dark blue areas, BSAP

reductions to BAP and DS are applied after taking into account the effect of transport

processes accounted for by the HELCOM (2020) allocation scheme.

NEC-Directive

According to Blicher-Mathiesen & Sørensen (2020), the reductions in atmospheric N deposition

after full implementation of the NEC-directive altogether amount to 16% or a 10% reduction, if

the different countries’ predictions are implemented. The full reduction of 16% is used for

management scenarios 1 and 2, whereas the predictions of 10% reduction are used for

management scenario 3a (see Erichsen

et al.

2020 for details).

Data are delivered by AU, and the reductions are resolved on an overall water body scale and

implemented in the Danish land-based N-MAIs calculations (see Figure 2-2 for data).

Here we assume that the difference in %-reductions can be translated into a %-reduction according to HELCOM (2020).

In HELCOM (2020) the effects, however, relate to tons of N and P why this is not entirely correct. As we operate in %-

reductions this assumption will likely overestimate the effects of the German reductions.

managementscenario1_udkast2020.docx

Figure 2-2

Atmospheric N depositions summarised at overall water body level.

‘2017’

and

‘2018’

represent present-day atmospheric N-depositions whereas

‘2027

NEC’

represents agreement behind the directive, and

‘2027

predictions’ represent the different

country prognosis.

Overview of input data used to construct management scenario 1.

N load reduction in

management scenario 1.

Reductions are in % of

current (2014-2018) load

P load reduction applied in

management scenario 1.

Reductions are in % of

current (2014-2018) load

27%

Adopted treaties

Table 2-1

Danish water areas

affected

Western Baltic Sea (light

blue area, Figure 2-1)

Great Belt and Kattegat

(dark blue area, Figure 2-1)

Effect of BSAP to DS

and BAP

Effect of BSAP and

German RBMP, using

HELCOM allocation

scheme

Effect of German RBMP

(2015-2021)

Effect of German RBMP

(2015-2021)

35%

27%

Southern Little Belt (yellow

area, Figure 2-1)

North Sea water bodies

and Limfjorden (brown

area, Figure 2-1)

Atmospheric deposition, all

Danish water bodies

44%

27%

31%

16%

NEC directive

2.2

Method for Calculating Danish N-MAI

Based on the assumed future load reductions from neighbouring countries and atmospheric

deposition as described above, maximum allowable input of nitrogen from Danish catchments to

each of the 109 water bodies is calculated as described in Erichsen

et al.

(2020).

Since the Danish water bodies are all more or less connected, the reduction needed for a single

water body cannot be assessed in isolation. In addition, it is necessary to consider the load

reduction requirement estimated for nearby water bodies. To account for connected water

bodies, the following scheme was applied:

1) Catchments are assigned to each water body. Local catchments are assigned to the inner

part (sub-catchments) of estuaries (upstream water bodies), whereas two or more local

catchments (main-catchments) are assigned for downstream water bodies (e.g. the outer

part of estuaries) and more open water bodies.

2) Load reductions (in %) for each individual water body are calculated as described in

Erichsen

et al.

(2020) and transformed into a reduction requirement in tons using the load of

the assigned catchment.

3) For up-stream water bodies (with local catchments) the calculated reduction is a minimum

requirement.

4) Reduction requirements for downstream water bodies are corrected, considering any

minimum reduction handled by up-stream water bodies.

5) Reduction requirements are transformed into MAIs by subtracting load reduction from the

average annual load and aggregated to the corresponding local and/or regional catchment.

2.3

Results

Based on the above-described assumption (implementation of the Baltic Sea Action Plan,

German nutrient reductions according to RBMP 2015-2021 and reductions in atmospheric N

deposition according to the NEC directive) the different reduction requirements and

corresponding MAIs are calculated.

The different reduction requirements (%-wise and in actual tons) based on the different

indicators and different models are included in Appendices A-E, whereas the aggregated MAIs

are reported in Table 2-2.

managementscenario1_udkast2020.docx

Table 2-2

Maximum Allowable Nitrogen Inputs (N-MAIs) for Danish water bodies given the implementation of the BSAP, German nutrient reductions

according to RBMP 2015-2021 and reductions in atmospheric N deposition according to the NEC directive.

The table shows N-MAIs in tons N per year, where

‘main’

denotes main-catchment, and

‘sub’

denotes sub-catchments being part of a main-

catchment. The table shows average annual loads as well as N-MAIs calculated for 5 different phosphorus reduction scenarios designated P0,

P10, P20, P30 and P50, where phosphorus loadings from Danish catchments are reduced by 0%, 10%, 20%, 30% and 50%, respectively. The

column

‘aggregated’

denotes sub-catchments included in specific MAIs.

Aggregation

Average

annual

(main)

Average

annual

(sub)

764

388

1,098

899

164

523

1,272

238

419

164

523

1,007

186

419

1,098

573

164

523

1,036

188

419

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

No.

Name

Roskilde Fjord, ydre

Roskilde Fjord, indre

Nordlige Øresund

Korsør Nor

Basnæs Nor

Holsteinborg Nor

Isefjord, ydre

Skælskør Fjord and Nor

Sejerø Bugt

Kalundborg Fjord

Smålandsfarvandet, syd

Karrebæk Fjord

Dybsø Fjord

Avnø Fjord

Guldborgsund

Hjelm Bugt

1,2

24,165

541

380

1,098

543

381

1,098

578

164

523

545

382

1,098

578

164

523

1,065

191

419

547

382

1,098

578

164

523

1,092

193

419

550

384

578

1,143

198

No.

Name

Aggregation

Average

annual

(main)

278

509

Average

annual

(sub)

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

Grønsund

Fakse Bugt

Præstø Fjord

Stege Bugt

Stege Nor

Østersøen, Bornholm

Østersøen, Christiansø

Nærå Strand

Lillestrand

Lindelse Nor

Kløven

Bredningen

Gamborg Fjord

Aborg Minde Nor

Holckenhavn Fjord

Kerteminde Fjord

Kertinge Nor

Nyborg Fjord

Helnæs Bugt

46,47

48,49

84,85

83,86

207

435

208

133

251

522

128

152

290

308

216

101

119

141

207

438

137

251

522

109

128

141

207

442

140

251

522

121

140

141

207

445

144

251

522

132

151

141

207

452

151

251

522

156

174

141

259

860

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual

(main)

Average

annual

(sub)

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

101

102

103

104

105

106

107

108

109

110

111

113

114

Lunkebugten

Langelandssund

Odense Fjord, ydre

Odense Fjord, Seden Strand

Storebælt SV

Storebælt NV

Genner Bugt

Åbenrå Fjord

Als Fjord

Als Sund

Augustenborg Fjord

Haderslev Fjord

Juvre Dyb

Avnø Vig

Hejlsminde Nor

Nybøl Nor

Lister Dyb

Flensborg Fjord, indre

Flensborg Fjord, ydre

83,86,89,90

92,93

96, 84, 85

101

102

103,104,105

104

105

106

107

108

109

110

111

113

110,113,114

188

227

768

573

582

839

768

115

132

115

132

168

133

119

947

178

593

857

786

115

132

168

134

119

105

1,017

179

605

874

804

115

132

168

135

119

109

1,089

180

628

892

822

115

132

168

136

119

114

1,163

182

1,358

1,288

927

857

130

269

239

349

138

2,155

219

168

139

119

123

1,318

185

No.

Name

Aggregation

Average

annual

(main)

Average

annual

(sub)

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

119

120

121

122

123

124

125

127

128

129

130

131

132

Vesterhavet, syd

Knudedyb

Grådyb

Vejle Fjord, ydre

Vejle Fjord, indre

Kolding Fjord, indre

Kolding Fjord, ydre

Horsens Fjord, ydre

Horsens Fjord, indre

Nissum Fjord, ydre

Nissum Fjord, mellem

Nissum Fjord, Felsted Kog

Ringkøbing Fjord

119, 107,

111, 121,

120

121

122,123

123

124

124,125

127,128

128

129,131,130

130,131

131

132

133,129,130

,131, 132

136

136,137

138, 137,

136

8,538

2,910

2,920

968

561

493

528

833

782

2,412

2,083

1,938

4,748

2,952

841

842

724

498

226

262

477

426

1,080

750

1,300

2,467

3,022

841

842

728

505

236

271

480

429

1,199

869

1,309

2,587

3,095

841

842

731

513

251

286

483

431

1,345

1,015

1,361

2,707

3,257

841

930

735

517

268

303

485

434

1,504

1,225

1,474

2,826

3,934

1,433

1,576

743

524

309

344

491

440

1,925

1,682

1,727

4,030

133

136

137

Vesterhavet, nord

Randers Fjord, indre

Randers Fjord, ydre

7,237

2,925

3,078

3,624

2,201

2,137

3,863

2,201

2,235

4,128

2,256

2,332

4,407

2,346

2,429

6,032

2,525

2,619

138

Hevring Bugt

3,235

2,294

2,392

2,490

2,586

2,776

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual

(main)

856

Average

annual

(sub)

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

139

140

141

142

144

145

146

147

154

Anholt

Djursland Øst

Ebeltoft Vig

Stavns Fjord

Knebel Vig

Kalø Vig

Norsminde Fjord

Århus Bugt og Begtrup Vig

Kattegat Læsø

Bjørnholms Bugt, Riisgårde

Bredning, Skive Fjord og

Lovns Bredning

Hjarbæk Fjord

Mariager Fjord, indre

Mariager Fjord, ydre

Isefjord, indre

139

140

141

142

144

144,145

146

144,145,147

154

674

190

140

186

645

674

186

651

674

186

106

651

674

186

114

651

674

186

129

651

656

157

158

159

160

165

157,158

158

159

159,160

165

1,2,24,165,2

201

3,632

1,795

516

963

812

1,282

537

142

589

491

1,396

611

162

609

491

1,506

685

182

629

491

1,611

760

202

649

491

1,905

917

242

689

491

200

201

Kattegat Nordsjælland

Køge Bugt

Jammerland Bugt og Musholm

Bugt

1,857

1,109

1,243

843

1,243

859

1,243

875

1,243

891

1,243

923

204

1,327

929

931

932

934

936

No.

Name

Aggregation

Average

annual

(main)

Average

annual

(sub)

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

206

207

208

209

212

Smålandsfarvandet, åbne del

Nakskov Fjord

Femerbælt

Rødsand og Bredningen

Fåborg Fjord

16,17,18,25,

35,36,37,20

207

207,208,209

209

212

68,72,212,2

87,101,102,

103,104,105

,110,113,11

4,216

74,82,106,1

08,109,217

59,62,92,93,

127,128,142

,146,219

221

222,159,160

122,123,224

225

231,124,125

,80

2,014

454

1,530

521

1,663

405

1,283

322

1,697

408

1,285

322

1,729

410

1,288

322

1,760

411

1,289

322

1,819

414

1,292

322

214

Det sydfynske Øhav

633

333

334

335

336

337

216

Lillebælt, syd

1,309

885

217

Lillebælt Bredningen

956

469

219

221

222

224

225

Århus Bugt, syd, Samsø og

Nordlige Bælthav

Skagerrak

Kattegat Ålborg Bugt

Nordlige Lillebælt

Nordlige Kattegat Ålbæk Bugt

2,810

1,423

2,026

1,588

706

1,718

1,423

1,652

988

706

1,718

1,423

1,672

988

706

1,718

1,423

1,692

988

706

1,718

1,423

1,712

988

706

1,718

1,423

1,752

988

706

231

Lillebælt Snævringen

789

266

285

304

323

360

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual

(main)

880

Average

annual

(sub)

(main)

(sub)

P10

(main)

P10

(sub)

P20

(main)

P20

(sub)

P30

(main)

P30

(sub)

P50

(main)

P50

(sub)

232

233

Nissum Bredning

Kaas Bredning og Venø Bugt

232

232,233

157,158,234

, 233, 236

157, 158,

233, 234,

235, 236,

238

236

238

490

1,955

1,129

526

1,239

545

1,350

561

1,463

595

1,670

234

Løgstør Bredning

4,336

2,811

2,923

3,035

3,147

3,369

235

236

238

Nibe Bredning og Langerak

Thisted Bredning

Halkær Bredning

Danish N-load

(National MAI)

11,064

1,091

620

6,867

379

114

6,982

388

117

7,139

398

161

7,295

408

206

7,707

428

396

58,100

36,624

37,294

38,014

38,832

41,982

Truncated at land-based reference N-load for one indicator

Truncated at land-based reference N-load for two indicators

Chlorophyll-a and light

‘good-moderate’ target obtained based on measurement (and not dependent on reductions from neighbouring

countries or

atmospheric depositions

2.4

Closing Remarks

The estimated maximum allowable nitrogen input (N-MAI) to Danish water bodies presented in

this report is based on the preconditions that the BSAP, the RBMP 2015-2021, and the NEC

directive will be fully implemented. These treaties have been adopted but not yet fully

implemented. We have not assessed whether the implementations of the treaties are realistic or

even possible.

If the preconditions are fulfilled, and the MAI for Danish water bodies is reached by the end of

2027, all Danish water bodies will most likely not have reached Good Ecological Status (GES)

as defined in the WFD. This is because

•

The MAI estimation is based on the depth of light as a proxy for the indicator eelgrass

depth limit. Hence, even if light has reached the target value, recovery for eelgrass is

expected to take several years (and even decades). In addition, other barriers than light

availability, such as sediment suitability, lack of seedlings, etc., may delay or even prevent

eelgrass recovery.

With the given preconditions in management scenario 1, one or both of the indicators

(chlorophyll-a and light) may not reach the target value despite reductions from Danish

catchments. In these situations, the reduction requirement for that indicator is cut

off/truncated using the reference loading. A cut-off at reference loading indicates that the

method applied cannot provide a specific MAI for that water body that ensures GES, and

some administrative choices have to be made, like applying an average reduction from

neighbouring water bodies, reductions like down-stream water bodies or a general MAI

(kg/ha) for those water bodies. However, the implication is that GES for both indicators

cannot be expected in these water bodies, not even if MAI is obtained.

The method is not based on the one-out-all-out principle as required in the WFD, but on an

average of two indicators. Hence, it is expected that both indicators will be as close to the

target value as possible, but one will, in some cases be above and one below the target

value.

In this scenario, we are using the boundary between good and moderate status as the

target value. Due to uncertainties, there is a 50% chance that the water body will end in

good status and a 50% chance that the water body will end in moderate status, once MAI

has been reached.

As some ecosystems respond with significant time-lags to changes in loadings, it will take

years before the full environmental effects of nutrient reductions can be observed. Hence,

reaching MAI will provide the conditions for obtaining GES but the achievement of GES will

likely be delayed.

•

managementscenario1_udkast2020.docx

References

/1/

Blicher-Mathiesen G & Sørensen P (red) (2020). Baseline 2027 for udvalgte elementer.

Aarhus Universitet, DCE

–

Nationalt Center for Miljø og Energi, 120 s. - Teknisk rapport

nr. 184

http://dce2.au.dk/pub/TR184.pdf

COWI (2018). Nabotjek af EU-landes fremgangsmåder ved planlægning for marine

vandområder i henhold til Vandrammedirektivet. Komparativ rapport. COWI rapport.

Erichsen AC (Ed.), Timmermann K (Ed.), Birkeland M, Christensen JPA, Markager S,

Møhlenberg F. (2018) Recommendations for continued development of models and

methods for use in the River Basin Management Plan 2021-2027. Follow-up on the

international evaluation of marine models behind the River Basin Management Plan 2015-

2021. Technical report. DHI.

Erichsen AC, Birkeland M, Timmermann K, Christensen J & Markager S (2020).

Application of the Danish EPA’s Marine Model Complex and Development of a Method

Applicable for the River Basin Management Plans 2021-2027. Conceptual Method for

Estimating Maximum Allowable Inputs. Technical report. DHI.

Gadegast M & Venohr M (2015). Modellierung Historischer Nährstoffeinträge und -

Frachten zur Ableitung von Nährstoffreferenz

–

und Orientierungswerten für

Mitteleuropäische Flussgebiete. Technical Report

Herman P, Newton A, Schernewski G, Gustafsson B, Malve O (2017) International

Evaluation of the Danish Marine Models, Danish EPA.

/2/

/3/

/4/

/5/

/6/

Appe nd i x A

–

Ma ximum Allo wa b le Ni t rogen

I nput s ( N- M AI s) based o n mana gem ent scen ario

1 and assu ming a 0 % reduct i on i n Dan ish la nd -

base d P loa ds

Table A- 1

Water body-specific MAIs based on the two indicators chlorophyll-a (Chl-a) and light penetration depth (light) estimated from either statistical

models (STAT) or mechanistic models (MEK).

The table shows both the individual calculations and the averaged water-specific MAIs (without any aggregation) and the corresponding need for

reduction in %. The data in this table are based on management scenario 1 and Danish land-based P-reductions set at 0%.

Aggregation

Average

annual N-

load

764

388

1,098

899

164

523

1,272

238

419

278

504

606

388

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

No.

Name

Roskilde Fjord, ydre

Roskilde Fjord, indre

Nordlige Øresund

Korsør Nor

Basnæs Nor

Holsteinborg Nor

Isefjord, ydre

Skælskør Fjord and Nor

Sejerø Bugt

Kalundborg Fjord

Smålandsfarvandet, syd

Karrebæk Fjord

Dybsø Fjord

Avnø Fjord

Guldborgsund

Hjelm Bugt

Grønsund

1,2

24,165

651

388

1,098

545

164

523

1,272

238

419

278

431

354

1,098

636

164

523

742

134

419

136

555

388

541

371

1,098

591

164

523

1,007

186

419

207

541

380

1,098

573

164

523

1,007

186

419

207

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

510

208

259

859

128

152

290

308

216

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

Fakse Bugt

Præstø Fjord

Stege Bugt

Stege Nor

Østersøen, Bornholm

Østersøen, Christiansø

Nærå Strand

Lillestrand

Lindelse Nor

Kløven

Bredningen

Gamborg Fjord

Aborg Minde Nor

Holckenhavn Fjord

Kerteminde Fjord

Kertinge Nor

Nyborg Fjord

Helnæs Bugt

Lunkebugten

46,47

48,49

84,85

83,86

438

144

259

184

154

509

123

259

860

121

277

216

474

133

259

522

101

215

141

474

133

259

522

101

215

141

No.

Name

Aggregation

Average

annual N-

load

768

1,358

1,288

188

227

130

269

239

349

138

2,155

219

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

101

102

103

104

105

106

107

108

109

110

111

113

114

Langelandssund

Odense Fjord, ydre

Odense Fjord, Seden Strand

Storebælt SV

Storebælt NV

Genner Bugt

Åbenrå Fjord

Als Fjord

Als Sund

Augustenborg Fjord

Haderslev Fjord

Juvre Dyb

Avnø Vig

Hejlsminde Nor

Nybøl Nor

Lister Dyb

Flensborg Fjord, indre

Flensborg Fjord, ydre

83,86,89,90

92,93

96, 84, 85

101

102

103,104,105

104

105

106

107

108

109

110

111

113

110,113,114

581

836

1,223

690

986

1,288

107

119

127

947

219

768

1,127

406

188

227

106

269

160

1,030

690

674

1,057

847

115

132

168

133

119

674

1,043

768

115

132

168

133

119

947

219

947

219

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

119

120

121

122

123

124

125

127

128

129

130

131

132

Vesterhavet, syd

Knudedyb

Grådyb

Vejle Fjord, ydre

Vejle Fjord, indre

Kolding Fjord, indre

Kolding Fjord, ydre

Horsens Fjord, ydre

Horsens Fjord, indre

Nissum Fjord, ydre

Nissum Fjord, mellem

Nissum Fjord, Felsted Kog

Ringkøbing Fjord

119, 107,

111, 121,

120

121

122,123

123

124

124,125

127,128

128

129,131,130

130,131

131

132

133,129,130

,131, 132

136

136,137

138, 137,

136

8,538

2,910

2,920

968

561

493

528

833

782

2,412

2,083

1,938

4,747

1,938

1,679

532

188

451

841

3,934

841

842

480

530

246

278

508

405

1,357

898

662

4,748

968

479

283

400

449

447

1,018

602

662

1,761

1,938

1,679

491

188

841

3,934

841

842

724

505

265

339

478

426

1,187

750

662

3,254

3,934

841

842

724

498

226

339

478

426

1,187

750

1,300

2,467

133

136

137

Vesterhavet, nord

Randers Fjord, indre

Randers Fjord, ydre

7,237

2,925

3,078

2,925

3,078

1,477

1,196

7,237

2,925

3,078

1,477

1,196

2,201

2,137

7,237

2,201

2,137

7,237

2,201

2,137

138

Hevring Bugt

3,235

No.

Name

Aggregation

Average

annual N-

load

856

190

140

656

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

139

140

141

142

144

145

146

147

154

Anholt

Djursland Øst

Ebeltoft Vig

Stavns Fjord

Knebel Vig

Kalø Vig

Norsminde Fjord

Århus Bugt og Begtrup Vig

Kattegat Læsø

Bjørnholms Bugt, Riisgårde

Bredning, Skive Fjord og

Lovns Bredning

Hjarbæk Fjord

Mariager Fjord, indre

Mariager Fjord, ydre

Isefjord, indre

139

140

141

142

144

144,145

146

144,145,147

154

493

190

140

631

656

636

856

190

656

644

190

674

190

646

674

190

645

157

158

159

160

165

157,158

158

159

159,160

165

1,2,24,165,2

201

3,632

1,795

516

963

812

379

992

426

784

396

1,572

649

201

516

812

379

1,282

537

142

650

604

1,282

537

142

650

491

200

201

Kattegat Nordsjælland

Køge Bugt

Jammerland Bugt og Musholm

Bugt

1,857

1,109

836

1,857

973

629

729

836

1,243

851

1,243

843

204

1,327

532

929

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

206

207

208

209

212

Smålandsfarvandet, åbne del

Nakskov Fjord

Femerbælt

Rødsand og Bredningen

Fåborg Fjord

16,17,18,25,

35,36,37,20

207

207,208,209

209

212

68,72,212,2

87,101,102,

103,104,105

,110,113,11

4,216

74,82,106,1

08,109,217

59,62,92,93,

127,128,142

,146,219

221

222,159,160

122,123,224

225

231,124,125

,80

2,014

454

1,530

521

2,014

450

1,468

284

1,699

360

1,530

359

1,856

405

1,499

322

1,856

405

1,499

322

214

Det sydfynske Øhav

633

176

451

176

529

314

352

333

216

Lillebælt, syd

1,309

462

1,309

885

217

Lillebælt Bredningen

956

276

371

956

276

663

469

219

221

222

224

225

Århus Bugt, syd, Samsø og

Nordlige Bælthav

Skagerrak

Kattegat Ålborg Bugt

Nordlige Lillebælt

Nordlige Kattegat Ålbæk Bugt

2,810

1,423

2,026

1,588

706

626

1,423

2,026

389

706

2,810

1,718

1,423

1,718

1,423

2,026

988

706

2,026

1,588

706

2,026

988

706

231

Lillebælt Snævringen

789

222

182

439

222

311

266

No.

Name

Aggregation

Average

annual N-

load

880

1,955

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

232

233

Nissum Bredning

Kaas Bredning og Venø Bugt

232

232,233

157,158,234

, 233, 236

157, 158,

233, 234,

235, 236,

238

236

238

297

604

297

1,457

762

802

451

530

1,129

490

1,129

234

Løgstør Bredning

6,502

1,980

3,642

2,811

235

236

238

Nibe Bredning og Langerak

Thisted Bredning

Halkær Bredning

11,064

1,091

620

9,773

2,984

269

114

9,774

488

114

9,773

6,379

379

114

8,076

379

114

managementscenario1_udkast2020.docx

Appe nd i x B

–

Ma ximum Allo wa b le Ni t rogen

I nput s ( N- M AI s) based o n mana gem ent scen ario

1 and assu ming a 1 0% reduct i on i n Dan ish

lan d - bas ed P loads

Table B- 1

Water body specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and light penetration depth (light) estimated from either

statistical models (STAT) or mechanistic models (MEK).

The table shows both the individual calculations and the averaged water-specific MAIs (without any aggregation) and the corresponding need for

a reduction in %. The data in this table are based on management scenario 1 and Danish land-based P-reductions set at 10%.

Aggregation

Average

annual N-

load

764

388

1,098

899

164

523

1,272

238

419

278

525

623

388

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

No.

Name

Roskilde Fjord, ydre

Roskilde Fjord, indre

Nordlige Øresund

Korsør Nor

Basnæs Nor

Holsteinborg Nor

Isefjord, ydre

Skælskør Fjord and Nor

Sejerø Bugt

Kalundborg Fjord

Smålandsfarvandet, syd

Karrebæk Fjord

Dybsø Fjord

Avnø Fjord

Guldborgsund

Hjelm Bugt

Grønsund

1,2

24,165

651

388

1,098

545

164

523

1,272

238

419

278

435

358

1,098

637

164

523

800

139

419

136

574

388

543

373

1,098

591

164

523

1,036

188

419

207

543

381

1,098

583

164

523

1,036

188

419

207

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

509

208

259

859

128

152

289

308

216

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

Fakse Bugt

Præstø Fjord

Stege Bugt

Stege Nor

Østersøen, Bornholm

Østersøen, Christiansø

Nærå Strand

Lillestrand

Lindelse Nor

Kløven

Bredningen

Gamborg Fjord

Aborg Minde Nor

Holckenhavn Fjord

Kerteminde Fjord

Kertinge Nor

Nyborg Fjord

Helnæs Bugt

Lunkebugten

46,47

48,49

84,85

83,86

439

146

259

184

159

509

127

259

860

132

280

216

474

137

259

522

109

219

141

474

137

259

522

109

219

141

No.

Name

Aggregation

Average

annual N-

load

768

1,358

1,288

188

227

130

269

239

349

138

2,155

219

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

101

102

103

104

105

106

107

108

109

110

111

113

114

Langelandssund

Odense Fjord, ydre

Odense Fjord, Seden Strand

Storebælt SV

Storebælt NV

Genner Bugt

Åbenrå Fjord

Als Fjord

Als Sund

Augustenborg Fjord

Haderslev Fjord

Juvre Dyb

Avnø Vig

Hejlsminde Nor

Nybøl Nor

Lister Dyb

Flensborg Fjord, indre

Flensborg Fjord, ydre

83,86,89,90

92,93

96, 84, 85

101

102

103,104,105

104

105

106

107

108

109

110

111

113

110,113,114

581

836

1,223

690

996

1,288

108

119

138

1,017

219

768

1,162

478

188

227

106

269

161

1,030

690

674

1,079

883

115

132

168

134

119

674

1,054

786

115

132

168

134

119

105

1,017

219

105

1,017

219

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

119

120

121

122

123

124

125

127

128

129

130

131

132

Vesterhavet, syd

Knudedyb

Grådyb

Vejle Fjord, ydre

Vejle Fjord, indre

Kolding Fjord, indre

Kolding Fjord, ydre

Horsens Fjord, ydre

Horsens Fjord, indre

Nissum Fjord, ydre

Nissum Fjord, mellem

Nissum Fjord, Felsted Kog

Ringkøbing Fjord

119, 107,

111, 121,

120

121

122,123

123

124

124,125

127,128

128

129,131,130

130,131

131

132

133,129,130

,131, 132

136

136,137

138, 137,

136

8,538

2,910

2,920

968

561

493

528

833

782

2,413

2,083

1,938

4,748

1,938

1,679

546

200

465

841

3,934

841

842

487

531

251

278

516

407

1,444

993

662

4,748

968

480

294

406

454

450

1,103

745

698

2,242

1,938

1,679

506

200

841

3,934

841

842

727

505

272

342

485

429

1,273

869

680

3,495

3,934

841

842

727

505

236

342

485

429

1,273

869

1,309

2,587

133

136

137

Vesterhavet, nord

Randers Fjord, indre

Randers Fjord, ydre

7,237

2,925

3,078

2,925

3,078

1,477

1,392

7,237

2,925

3,078

1,477

1,392

2,201

2,235

7,237

2,201

2,235

7,237

2,201

2,235

138

Hevring Bugt

3,235

No.

Name

Aggregation

Average

annual N-

load

856

190

140

656

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

139

140

141

142

144

145

146

147

154

Anholt

Djursland Øst

Ebeltoft Vig

Stavns Fjord

Knebel Vig

Kalø Vig

Norsminde Fjord

Århus Bugt og Begtrup Vig

Kattegat Læsø

Bjørnholms Bugt, Riisgårde

Bredning, Skive Fjord og

Lovns Bredning

Hjarbæk Fjord

Mariager Fjord, indre

Mariager Fjord, ydre

Isefjord, indre

139

140

141

142

144

144,145

146

144,145,147

154

493

190

140

656

636

856

190

656

190

674

190

646

674

190

651

157

158

159

160

165

157,158

158

159

159,160

165

1,2,24,165,2

201

3,632

1,795

516

963

812

379

992

465

823

396

1,801

756

237

597

812

379

1,396

611

163

710

604

1,396

611

163

710

491

200

201

Kattegat Nordsjælland

Køge Bugt

Jammerland Bugt og Musholm

Bugt

1,857

1,109

853

1,857

991

629

740

853

1,243

866

1,243

859

204

1,327

535

931

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

206

207

208

209

212

Smålandsfarvandet, åbne del

Nakskov Fjord

Femerbælt

Rødsand og Bredningen

Fåborg Fjord

16,17,18,25,

35,36,37,20

207

207,208,209

209

212

68,72,212,2

87,101,102,

103,104,105

,110,113,11

4,216

74,82,106,1

08,109,217

59,62,92,93,

127,128,142

,146,219

221

222,159,160

122,123,224

225

231,124,125

,80

2,014

454

1,530

521

2,014

452

1,468

284

1,699

363

1,530

359

1,856

408

1,499

322

1,856

408

1,499

322

214

Det sydfynske Øhav

633

176

454

176

529

315

352

334

216

Lillebælt, syd

1,309

462

1,309

885

217

Lillebælt Bredningen

956

276

371

956

276

663

469

219

221

222

224

225

Århus Bugt, syd, Samsø og

Nordlige Bælthav

Skagerrak

Kattegat Ålborg Bugt

Nordlige Lillebælt

Nordlige Kattegat Ålbæk Bugt

2,810

1,423

2,026

1,588

706

626

1,423

2,026

389

706

2,810

1,718

1,423

1,718

1,423

2,026

988

706

2,026

1,588

706

2,026

988

706

231

Lillebælt Snævringen

789

260

182

439

260

311

285

No.

Name

Aggregation

Average

annual N-

load

880

1,955

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

232

233

Nissum Bredning

Kaas Bredning og Venø Bugt

232

232,233

157,158,234

, 233, 236

157, 158,

233, 234,

235, 236,

238

236

238

302

639

297

1,519

866

960

470

582

1,239

526

1,239

234

Løgstør Bredning

6,503

1,980

3,866

2,923

235

236

238

Nibe Bredning og Langerak

Thisted Bredning

Halkær Bredning

11,064

1,091

620

9,987

3,574

269

114

10,441

508

119

9,987

7,008

389

117

8,497

389

117

managementscenario1_udkast2020.docx

Appe nd i x C

–

Ma ximum Allo wa b le Ni t rogen

I nput s ( N- M AI s) based o n mana gem ent scen ario

1 and assu ming a 2 0% reduct i on i n Dan ish

lan d - bas ed P loads

Table C- 1

Water body-specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and light penetration depth (light) estimated from either

statistical models (STAT) or mechanistic models (MEK).

The table shows both the individual calculations and the averaged water-specific MAIs (without any aggregation) and the corresponding need for

a reduction in %. The data in this table are based on management scenario 1 and Danish land-based P-reductions set at 20%.

Aggregation

Average

annual N-

load

764

388

1,098

899

164

523

1,272

238

419

278

546

638

388

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

No.

Name

Roskilde Fjord, ydre

Roskilde Fjord, indre

Nordlige Øresund

Korsør Nor

Basnæs Nor

Holsteinborg Nor

Isefjord, ydre

Skælskør Fjord and Nor

Sejerø Bugt

Kalundborg Fjord

Smålandsfarvandet, syd

Karrebæk Fjord

Dybsø Fjord

Avnø Fjord

Guldborgsund

Hjelm Bugt

Grønsund

1,2

24,165

651

388

1,098

545

164

523

1,272

238

419

278

438

361

1,098

637

164

523

857

144

419

136

592

388

545

375

1,098

591

164

523

1,065

191

419

207

545

381

1,098

592

164

523

1,065

191

419

207

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

510

208

259

859

128

152

290

308

216

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

Fakse Bugt

Præstø Fjord

Stege Bugt

Stege Nor

Østersøen, Bornholm

Østersøen, Christiansø

Nærå Strand

Lillestrand

Lindelse Nor

Kløven

Bredningen

Gamborg Fjord

Aborg Minde Nor

Holckenhavn Fjord

Kerteminde Fjord

Kertinge Nor

Nyborg Fjord

Helnæs Bugt

Lunkebugten

46,47

48,49

84,85

83,86

441

149

259

184

164

509

131

259

860

143

285

216

475

140

259

522

121

224

141

475

140

259

522

121

224

141

No.

Name

Aggregation

Average

annual N-

load

768

1,358

1,288

188

227

130

269

239

349

138

2,155

219

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

101

102

103

104

105

106

107

108

109

110

111

113

114

Langelandssund

Odense Fjord, ydre

Odense Fjord, Seden Strand

Storebælt SV

Storebælt NV

Genner Bugt

Åbenrå Fjord

Als Fjord

Als Sund

Augustenborg Fjord

Haderslev Fjord

Juvre Dyb

Avnø Vig

Hejlsminde Nor

Nybøl Nor

Lister Dyb

Flensborg Fjord, indre

Flensborg Fjord, ydre

83,86,89,90

92,93

96, 84, 85

101

102

103,104,105

104

105

106

107

108

109

110

111

113

110,113,114

581

836

1,223

690

1,006

1,288

109

119

138

1,089

219

768

1,196

549

188

227

106

269

162

1,030

690

674

1,101

918

115

132

168

135

119

674

1,065

804

115

132

168

135

119

109

1,089

219

109

1,089

219

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

119

120

121

122

123

124

125

127

128

129

130

131

132

Vesterhavet, syd

Knudedyb

Grådyb

Vejle Fjord, ydre

Vejle Fjord, indre

Kolding Fjord, indre

Kolding Fjord, ydre

Horsens Fjord, ydre

Horsens Fjord, indre

Nissum Fjord, ydre

Nissum Fjord, mellem

Nissum Fjord, Felsted Kog

Ringkøbing Fjord

119, 107,

111, 121,

120

121

122,123

123

124

124,125

127,128

128

129,131,130

130,131

131

132

133,129,130

,131, 132

136

136,137

138, 137,

136

8,538

2,910

2,920

968

561

493

528

833

782

2,412

2,083

1,938

4,748

1,938

1,679

561

222

478

841

3,934

841

842

495

532

256

278

525

409

1,562

1,146

662

4,748

968

481

304

414

457

454

1,187

884

908

2,721

1,938

1,679

520

222

841

3,934

841

842

731

506

280

346

491

431

1,375

1,015

785

3,734

3,934

841

842

731

513

251

346

491

431

1,375

1,015

1,361

2,707

133

136

137

Vesterhavet, nord

Randers Fjord, indre

Randers Fjord, ydre

7,237

2,925

3,078

2,925

3,078

1,588

1,587

7,237

2,925

3,078

1,588

1,587

2,256

2,332

7,237

2,256

2,332

7,237

2,256

2,332

138

Hevring Bugt

3,235

No.

Name

Aggregation

Average

annual N-

load

856

190

140

656

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

139

140

141

142

144

145

146

147

154

Anholt

Djursland Øst

Ebeltoft Vig

Stavns Fjord

Knebel Vig

Kalø Vig

Norsminde Fjord

Århus Bugt og Begtrup Vig

Kattegat Læsø

Bjørnholms Bugt, Riisgårde

Bredning, Skive Fjord og

Lovns Bredning

Hjarbæk Fjord

Mariager Fjord, indre

Mariager Fjord, ydre

Isefjord, indre

139

140

141

142

144

144,145

146

144,145,147

154

493

190

140

656

636

856

190

656

190

674

190

106

646

674

190

106

651

157

158

159

160

165

157,158

158

159

159,160

165

1,2,24,165,2

201

3,632

1,795

516

963

812

379

992

508

870

396

2,019

862

271

672

812

379

1,506

685

182

771

604

1,506

685

182

771

491

200

201

Kattegat Nordsjælland

Køge Bugt

Jammerland Bugt og Musholm

Bugt

1,857

1,109

870

1,857

1,009

629

751

870

1,243

880

1,243

875

204

1,327

537

932

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

206

207

208

209

212

Smålandsfarvandet, åbne del

Nakskov Fjord

Femerbælt

Rødsand og Bredningen

Fåborg Fjord

16,17,18,25,

35,36,37,20

207

207,208,209

209

212

68,72,212,2

87,101,102,

103,104,105

,110,113,11

4,216

74,82,106,1

08,109,217

59,62,92,93,

127,128,142

,146,219

221

222,159,160

122,123,224

225

231,124,125

,80

2,014

454

1,530

521

2,014

454

1,468

284

1,699

366

1,530

359

1,856

410

1,499

322

1,856

410

1,499

322

214

Det sydfynske Øhav

633

176

458

176

529

317

352

335

216

Lillebælt, syd

1,309

462

1,309

885

217

Lillebælt Bredningen

956

276

371

956

276

663

469

219

221

222

224

225

Århus Bugt, syd, Samsø og

Nordlige Bælthav

Skagerrak

Kattegat Ålborg Bugt

Nordlige Lillebælt

Nordlige Kattegat Ålbæk Bugt

2,810

1,423

2,026

1,588

706

626

1,423

2,026

389

706

2,810

1,718

1,423

1,718

1,423

2,026

988

706

2,026

1,588

706

2,026

988

706

231

Lillebælt Snævringen

789

298

182

439

298

311

304

No.

Name

Aggregation

Average

annual N-

load

880

1,955

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

232

233

Nissum Bredning

Kaas Bredning og Venø Bugt

232

232,233

157,158,234

, 233, 236

157, 158,

233, 234,

235, 236,

238

236

238

331

673

297

1,583

880

1,118

502

589

1,350

545

1,350

234

Løgstør Bredning

6,502

1,980

4,091

3,035

235

236

238

Nibe Bredning og Langerak

Thisted Bredning

Halkær Bredning

11,064

1,091

620

10,199

4,200

269

114

11,064

528

209

10,199

7,632

398

161

8,916

398

161

managementscenario1_udkast2020.docx

Appe nd i x D

–

Ma ximum Allo wa b le Ni t rogen

I nput s ( N- M AI s) based o n mana gem ent scen ario

1 and assu ming a 3 0% reduct i on i n Dan ish

lan d - bas ed P loads

Table D- 1

Water body-specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and light penetration depth (light) estimated from either

statistical models (STAT) or mechanistic models (MEK).

The table shows both the individual calculations and the averaged water-specific MAIs (without any aggregation) and the corresponding need for

a reduction in %. The data in this table are based on management scenario 1 and Danish land-based P-reductions set at 30%.

Aggregation

Average

annual N-

load

764

388

1,098

899

164

523

1,272

238

419

278

569

654

388

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

No.

Name

Roskilde Fjord, ydre

Roskilde Fjord, indre

Nordlige Øresund

Korsør Nor

Basnæs Nor

Holsteinborg Nor

Isefjord, ydre

Skælskør Fjord and Nor

Sejerø Bugt

Kalundborg Fjord

Smålandsfarvandet, syd

Karrebæk Fjord

Dybsø Fjord

Avnø Fjord

Guldborgsund

Hjelm Bugt

Grønsund

1,2

24,165

651

388

1,098

545

164

523

1,272

238

419

278

442

365

1,098

638

164

523

912

149

419

136

612

388

547

377

1,098

592

164

523

1,092

193

419

207

547

382

1,098

602

164

523

1,092

193

419

207

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

509

208

259

859

128

152

290

308

216

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

Fakse Bugt

Præstø Fjord

Stege Bugt

Stege Nor

Østersøen, Bornholm

Østersøen, Christiansø

Nærå Strand

Lillestrand

Lindelse Nor

Kløven

Bredningen

Gamborg Fjord

Aborg Minde Nor

Holckenhavn Fjord

Kerteminde Fjord

Kertinge Nor

Nyborg Fjord

Helnæs Bugt

Lunkebugten

46,47

48,49

84,85

83,86

442

151

259

184

110

169

509

136

259

860

155

288

216

476

144

259

522

132

228

141

476

144

259

522

132

228

141

No.

Name

Aggregation

Average

annual N-

load

768

1,358

1,288

188

227

130

269

239

349

138

2,155

219

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

101

102

103

104

105

106

107

108

109

110

111

113

114

Langelandssund

Odense Fjord, ydre

Odense Fjord, Seden Strand

Storebælt SV

Storebælt NV

Genner Bugt

Åbenrå Fjord

Als Fjord

Als Sund

Augustenborg Fjord

Haderslev Fjord

Juvre Dyb

Avnø Vig

Hejlsminde Nor

Nybøl Nor

Lister Dyb

Flensborg Fjord, indre

Flensborg Fjord, ydre

83,86,89,90

92,93

96, 84, 85

101

102

103,104,105

104

105

106

107

108

109

110

111

113

110,113,114

581

836

1,223

690

1,015

1,288

110

119

138

1,163

219

768

1,231

620

188

227

106

269

163

1,030

690

674

1,123

954

115

132

168

136

119

674

1,076

822

115

132

168

136

119

114

1,163

219

114

1,163

219

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

119

120

121

122

123

124

125

127

128

129

130

131

132

Vesterhavet, syd

Knudedyb

Grådyb

Vejle Fjord, ydre

Vejle Fjord, indre

Kolding Fjord, indre

Kolding Fjord, ydre

Horsens Fjord, ydre

Horsens Fjord, indre

Nissum Fjord, ydre

Nissum Fjord, mellem

Nissum Fjord, Felsted Kog

Ringkøbing Fjord

119, 107,

111, 121,

120

121

122,123

123

124

124,125

127,128

128

129,131,130

130,131

131

132

133,129,130

,131, 132

136

136,137

138, 137,

136

8,538

2,910

2,920

968

561

493

528

833

782

2,412

2,083

1,938

4,748

1,938

1,679

561

248

492

841

3,934

841

930

503

533

261

278

535

411

1,736

1,430

906

4,748

968

481

315

420

462

458

1,272

1,019

1,115

3,197

1,938

1,679

527

248

841

3,934

841

930

735

507

288

349

499

434

1,504

1,225

1,010

3,972

3,934

841

930

735

517

268

349

499

434

1,504

1,225

1,474

2,826

133

136

137

Vesterhavet, nord

Randers Fjord, indre

Randers Fjord, ydre

7,237

2,925

3,078

2,925

3,078

1,768

1,779

7,237

2,925

3,078

1,768

1,779

2,346

2,429

7,237

2,346

2,429

7,237

2,346

2,429

138

Hevring Bugt

3,235

No.

Name

Aggregation

Average

annual N-

load

856

190

140

656

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

139

140

141

142

144

145

146

147

154

Anholt

Djursland Øst

Ebeltoft Vig

Stavns Fjord

Knebel Vig

Kalø Vig

Norsminde Fjord

Århus Bugt og Begtrup Vig

Kattegat Læsø

Bjørnholms Bugt, Riisgårde

Bredning, Skive Fjord og

Lovns Bredning

Hjarbæk Fjord

Mariager Fjord, indre

Mariager Fjord, ydre

Isefjord, indre

139

140

141

142

144

144,145

146

144,145,147

154

493

190

140

656

636

856

190

656

190

674

190

114

646

674

190

114

651

157

158

159

160

165

157,158

158

159

159,160

165

1,2,24,165,2

201

3,632

1,795

516

963

812

379

992

555

100

926

396

2,230

966

305

741

812

379

1,611

760

202

834

604

1,611

760

202

834

491

200

201

Kattegat Nordsjælland

Køge Bugt

Jammerland Bugt og Musholm

Bugt

1,857

1,109

888

1,857

1,027

629

762

888

1,243

895

1,243

891

204

1,327

540

934

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

206

207

208

209

212

Smålandsfarvandet, åbne del

Nakskov Fjord

Femerbælt

Rødsand og Bredningen

Fåborg Fjord

16,17,18,25,

35,36,37,20

207

207,208,209

209

212

68,72,212,2

87,101,102,

103,104,105

,110,113,11

4,216

74,82,106,1

08,109,217

59,62,92,93,

127,128,142

,146,219

221

222,159,160

122,123,224

225

231,124,125

,80

2,014

454

1,530

521

2,014

454

1,468

284

1,699

369

1,530

359

1,856

411

1,499

322

1,856

411

1,499

322

214

Det sydfynske Øhav

633

176

461

176

529

319

352

336

216

Lillebælt, syd

1,309

462

1,309

885

217

Lillebælt Bredningen

956

276

371

956

276

663

469

219

221

222

224

225

Århus Bugt, syd, Samsø og

Nordlige Bælthav

Skagerrak

Kattegat Ålborg Bugt

Nordlige Lillebælt

Nordlige Kattegat Ålbæk Bugt

2,810

1,423

2,026

1,588

706

626

1,423

2,026

389

706

2,810

1,718

1,423

1,718

1,423

2,026

988

706

2,026

1,588

706

2,026

988

706

231

Lillebælt Snævringen

789

335

182

439

335

311

323

No.

Name

Aggregation

Average

annual N-

load

880

1,955

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

232

233

Nissum Bredning

Kaas Bredning og Venø Bugt

232

232,233

157,158,234

, 233, 236

157, 158,

233, 234,

235, 236,

238

236

238

361

707

297

1,650

880

1,276

534

589

1,463

561

1,463

234

Løgstør Bredning

6,501

1,980

4,314

3,147

235

236

238

Nibe Bredning og Langerak

Thisted Bredning

Halkær Bredning

11,064

1,091

620

10,410

4,865

269

114

11,064

547

298

10,410

7,965

408

206

9,188

408

206

managementscenario1_udkast2020.docx

Appe nd i x E

–

Ma ximum Allo wa b le Ni t rogen

I nput s ( N- M AI s) based o n mana gem ent scen ario

1 and assu ming a 5 0% reduct i on i n Dan ish

lan d - bas ed P loads

Table E- 1

Water body-specific MAIs based on the two individual indicators chlorophyll-a (Chl-a) and light penetration depth (light) estimated either statistical

models (STAT) or mechanistic models (MEK).

The table shows both the individual calculations as well as the averaged water-specific MAIs (without any aggregation) and the corresponding

need for a reduction in %. The data in this table are based on management scenario 1 and Danish land-based P-reductions set at 50%.

Aggregation

Average

annual N-

load

764

388

1,098

899

164

523

1,272

238

419

278

614

685

388

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

No.

Name

Roskilde Fjord, ydre

Roskilde Fjord, indre

Nordlige Øresund

Korsør Nor

Basnæs Nor

Holsteinborg Nor

Isefjord, ydre

Skælskør Fjord and Nor

Sejerø Bugt

Kalundborg Fjord

Smålandsfarvandet, syd

Karrebæk Fjord

Dybsø Fjord

Avnø Fjord

Guldborgsund

Hjelm Bugt

Grønsund

1,2

24,165

651

388

1,098

545

164

523

1,272

238

419

278

450

373

1,098

639

164

523

1,015

158

419

136

649

388

550

380

1,098

592

164

523

1,143

198

419

207

550

384

1,098

621

164

523

1,143

198

419

207

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

509

208

259

859

128

152

289

308

216

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

Fakse Bugt

Præstø Fjord

Stege Bugt

Stege Nor

Østersøen, Bornholm

Østersøen, Christiansø

Nærå Strand

Lillestrand

Lindelse Nor

Kløven

Bredningen

Gamborg Fjord

Aborg Minde Nor

Holckenhavn Fjord

Kerteminde Fjord

Kertinge Nor

Nyborg Fjord

Helnæs Bugt

Lunkebugten

46,47

48,49

84,85

83,86

445

157

259

184

134

179

509

144

259

860

177

296

216

477

151

259

522

156

237

141

477

151

259

522

156

237

141

No.

Name

Aggregation

Average

annual N-

load

768

1,358

1,288

188

227

130

269

239

349

138

2,155

219

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

101

102

103

104

105

106

107

108

109

110

111

113

114

Langelandssund

Odense Fjord, ydre

Odense Fjord, Seden Strand

Storebælt SV

Storebælt NV

Genner Bugt

Åbenrå Fjord

Als Fjord

Als Sund

Augustenborg Fjord

Haderslev Fjord

Juvre Dyb

Avnø Vig

Hejlsminde Nor

Nybøl Nor

Lister Dyb

Flensborg Fjord, indre

Flensborg Fjord, ydre

83,86,89,90

92,93

96, 84, 85

101

102

103,104,105

104

105

106

107

108

109

110

111

113

110,113,114

581

836

1,223

690

1,036

1,288

112

119

138

1,318

219

768

1,300

761

188

227

106

269

166

1,030

690

674

1,168

1,024

115

132

168

139

119

674

1,099

857

115

132

168

139

119

123

1,318

219

108

123

1,318

219

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

119

120

121

122

123

124

125

127

128

129

130

131

132

Vesterhavet, syd

Knudedyb

Grådyb

Vejle Fjord, ydre

Vejle Fjord, indre

Kolding Fjord, indre

Kolding Fjord, ydre

Horsens Fjord, ydre

Horsens Fjord, indre

Nissum Fjord, ydre

Nissum Fjord, mellem

Nissum Fjord, Felsted Kog

Ringkøbing Fjord

119, 107,

111, 121,

120

121

122,123

123

124

124,125

127,128

128

129,131,130

130,131

131

132

133,129,130

,131, 132

136

136,137

138, 137,

136

8,538

2,910

2,920

968

561

493

528

833

782

2,413

2,083

1,938

4,748

1,938

3,616

561

314

519

2,026

3,934

841

1,576

519

535

271

278

553

414

2,412

2,083

968

483

335

433

468

466

1,437

1,281

1,516

4,748

4,142

1,938

3,616

540

314

2,026

3,934

841

1,576

743

509

303

356

511

440

1,925

1,682

1,516

4,445

3,934

1,433

1,576

743

524

309

356

511

440

1,925

1,682

1,727

4,030

133

136

137

Vesterhavet, nord

Randers Fjord, indre

Randers Fjord, ydre

7,237

2,925

3,078

2,925

3,078

2,126

2,160

7,237

2,925

3,078

2,126

2,160

2,525

2,619

7,237

2,525

2,619

7,237

2,525

2,619

138

Hevring Bugt

3,235

No.

Name

Aggregation

Average

annual N-

load

856

190

140

656

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

139

140

141

142

144

145

146

147

154

Anholt

Djursland Øst

Ebeltoft Vig

Stavns Fjord

Knebel Vig

Kalø Vig

Norsminde Fjord

Århus Bugt og Begtrup Vig

Kattegat Læsø

Bjørnholms Bugt, Riisgårde

Bredning, Skive Fjord og

Lovns Bredning

Hjarbæk Fjord

Mariager Fjord, indre

Mariager Fjord, ydre

Isefjord, indre

139

140

141

142

144

144,145

146

144,145,147

154

493

190

140

656

636

856

190

118

656

190

674

190

129

646

674

190

129

651

157

158

159

160

165

157,158

158

159

159,160

165

1,2,24,165,2

201

3,633

1,795

516

963

812

379

1,185

666

115

963

396

2,626

1,168

369

866

812

379

1,905

917

242

914

604

1,905

917

242

914

491

200

201

Kattegat Nordsjælland

Køge Bugt

Jammerland Bugt og Musholm

Bugt

1,857

1,109

923

1,857

1,064

629

784

923

1,243

924

1,243

923

204

1,327

546

936

managementscenario1_udkast2020.docx

No.

Name

Aggregation

Average

annual N-

load

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

206

207

208

209

212

Smålandsfarvandet, åbne del

Nakskov Fjord

Femerbælt

Rødsand og Bredningen

Fåborg Fjord

16,17,18,25,

35,36,37,20

207

207,208,209

209

212

68,72,212,2

87,101,102,

103,104,105

,110,113,11

4,216

74,82,106,1

08,109,217

59,62,92,93,

127,128,142

,146,219

221

222,159,160

122,123,224

225

231,124,125

,80

2,014

454

1,530

521

2,014

454

1,468

284

1,699

375

1,530

359

1,856

414

1,499

322

1,856

414

1,499

322

214

Det sydfynske Øhav

633

176

468

176

529

322

352

337

216

Lillebælt, syd

1,309

462

1,309

885

217

Lillebælt Bredningen

956

276

371

956

276

663

469

219

221

222

224

225

Århus Bugt, syd, Samsø og

Nordlige Bælthav

Skagerrak

Kattegat Ålborg Bugt

Nordlige Lillebælt

Nordlige Kattegat Ålbæk Bugt

2,810

1,423

2,026

1,588

706

626

1,423

2,026

389

706

2,810

1,718

1,423

1,718

1,423

2,026

988

706

2,026

1,588

706

2,026

988

706

231

Lillebælt Snævringen

789

409

182

439

409

311

360

No.

Name

Aggregation

Average

annual N-

load

880

1,955

Chl-a (STAT)

Light (STAT)

Chl-a (MEK)

Light (MEK)

N-MAI

(STAT)

N-MAI (MEK)

Avg. MAI

Avg.

reduction [%]

232

233

Nissum Bredning

Kaas Bredning og Venø Bugt

232

232,233

157,158,234

, 233, 236

157, 158,

233, 234,

235, 236,

238

236

238

427

775

297

1,791

880

1,591

601

589

1,691

595

1,691

234

Løgstør Bredning

6,503

1,980

4,758

3,369

235

236

238

Nibe Bredning og Langerak

Thisted Bredning

Halkær Bredning

11,064

1,091

620

10,827

6,332

271

316

11,064

586

475

10,827

8,698

428

396

9,763

428

396

managementscenario1_udkast2020.docx