Animal redundancy in phosphorus circularity

(1)

Abstract

The increasing human population and demand for animal-based food products drive agricultural intensification, causing climate disruption and biodiversity loss. One of the main drivers behind agricultural intensification is the growing animal husbandry sector. Vegetarianism is a popular trend that aims to increase the circularity and long-term sustainability of the food system. In the current food system, the flow of nutrients is mainly linear: from extraction in mines to application on land, to plant-uptake, to consumption and, finally, to waste. Using a substance flow analysis, this study researches the flow of phosphorus, because it poses the most imminent threats to food security and biodiversity loss. How does the presence of animal husbandry affect phosphorus circularity in the European Union 27 member states? A circular P flow requires no inorganic P import, no accumulation in soil and no losses. Two scenarios were designed: Scenario (i) Business as usual & Scenario (ii) No animal production. Scenario (ii), where animal production is reduced to zero, resulted in 58% less inorganic P import, 76% less accumulation in soil and 34% losses. Therefore, it can be concluded animal husbandry has a negative influence on phosphorus circularity.

Animal redundancy in phosphorus circularity

A scenario analysis describing the relationship between animal husbandry and a circular

phosphorus flow in the EU27.

Bas de Nijs

(2)

1. Introduction

1.1 The food system

The increasing human population and demand for animal-based food products drive agricultural intensification, causing climate disruption and biodiversity loss. The contemporary global population counts more than seven billion individuals – an all-time high. To sustain the increasing population’s demand for food throughout history, more than a third of the Earth’s forested area has been cleared to enable agricultural practises (Foley et al., 2005; Brown, 2002). Additionally, through transportation and enteric emissions, the food system currently accounts for approximately one-third of global greenhouse-gas emissions (Tubiello et al., 2014). It can be argued that agricultural productivity should decrease to promote sustainability. However, the United Nations Food and Agriculture Organisation predicts that in order to sustain the global demand for nutrition by 2050, agricultural productivity has to increase by 50% (FAO, 2017). This prediction is based on the expectation that the population will increase to 9.8 billion by 2050. Besides that, average life expectancy and the demand for a meat-based diet are predicted to rise due to economic growth.

One of the main drivers behind agricultural intensification is the growing animal husbandry sector, resulting from the increase in demand for land-based animal products (de Vries & de Boer, 2010). While land-based animal products provide approximately only 15% of calorie intake by humans, 80% of agricultural land is allocated for animal husbandry (Ranganathan et al., 2016). In contrast, plant-based products contribute approximately 85% of calorie intake and take up 20% of agricultural land. These statistics depict the considerable inefficieny of animal husbandry in the current food system. A decrease in consumption and corresponding production of land-based animal products would decrease emissions and significantly lower the demand for agricultural land use, thus eliminating the need for deforestation (Johnson & Ward, 1996).

1.2 Circularity and sustainability

The circular economy offers a solution to the wastefulness of the linear economy, promoting long-term sustainability through reduction of input and waste. The current ‘take, make, dispose’ production model of the linear economy starts with resource extraction and ends with waste. This linear approach is not sustainable for two reasons: 1) resource scarcity, 2) the disruptive impact of waste streams on ecosystems (Stahel, 2016). In a perfectly circular system, waste does not exist. Instead, ‘waste’ flows of the last cycle constitute the input for the production process of the new cycle, eliminating the need for extra-system input (Heshmati, 2015). Therefore, circularity eliminates resource scarcity and waste pollution, qualifying as the ultimate aim of sustainability.

Stoll-Kleemann & O’Riordan (2015) argue that vegetarianism increases the long-term sustainability of the food system, but this view is not undisputed. Louise Fresco, professor at Wageningen University & Research, discredits vegetarianism based on the assumption that animals are a requirement of the circular economy. In Dutch newspaper de Volkskrant (2018), she stated that ‘Animals are essential for the circular economy, they transform waste into proteins. If everyone becomes vegetarian, we will have a problem’. While circularity is the ultimate aim of sustainability, contemporary animal husbandry is the epitome of unsustainable agriculture. Therefore, defining animal husbandry as a requirement of the circular economy seems controversial and demands further investigation.

1.3 Circular food system

In the current food system, the flow of nutrients is mainly linear: from extraction in mines to application on land, to plant-uptake, to consumption and, finally, to waste (Van Dijk et al., 2015). During the last centuries, urbanization and globalisation drove the shift from subsistent to economic agriculture. Correspondingly, the priority of farmers shifted to generating surpluses that can be sold rather than feed the farm community (Brown, 2003). As a result, crops were removed from the farmed area, nutrients depleted from the system and soils degraded, making them less suitable for

(4)

crop production. In order to maintain high crop yield, farmers turned to inorganic fertilizers (Buckwell & Nadeu, 2016). Inorganic fertilizers mainly consist of the elements Nitrogen (N), Phosphorus (P) and Potassium (K), the three types of nutrients most abundantly required for plant growth (Marschner & Marschner, 2012). A circular food system requires a shift from linearity to circularity regarding the flow of nutrients.

This study focuses on the flow of P, because it poses the most imminent threats to food security and biodiversity loss. These threats can be attributed to the rapid depletion of natural P sources and the disruptive quality of excessive P in aquatic ecosystems (Vaccari, 2009). In Europe, 43% of P used in fertilizers is inorganic P extracted from phosphate rock (Buckwell & Nadeu, 2016). Because the natural P cycle acts on a geological timescale of 10-15 million years, phosphate rock is labelled as a non-renewable resource (Ruttenberg, 2003). There are several major reserves in the world and they are projected to run out in the next 30-300 years. The largest one, located in Morocco and the Western Sahara, accounts for 77% of presently known global phosphate rock (Van Dijk et al., 2015). A significant proportion of mined P ends up in oceans, where it takes millions of years to be buried in the sediment and tectonically uplifted as phosphate rock (Ruttenberg, 2003). In 2005, 17% of European P losses entered the hydrosphere, boosting algae growth and, to the detriment of biodiversity, causing ecosystem shifts from oligo- to eutrophic states in lakes and coastal areas (Van Dijk et al., 2015). Taking phosphate rock scarcity and aquatic ecosystem disruption into consideration, it becomes evident that P circularity is an absolute requirement of a circular food system and sustainable agriculture.

1.4 Phosphorus Flow Analysis

To verify Prof. Fresco’s statement in relation to P circularity, this study researched the impact of animal husbandry on the P flow using a Substance Flow Analysis (SFA). An SFA is a research method that quantifies flows and stocks in a system (Brunner & Rechberge, 2004). SFA’s can provide guidelines for policy making concerning sustainable substance management. Generally, SFA’s are applied in the field of industrial ecology to unveil all the links in the supply chain of a product (Ayers & Ayers, 2002). The method focuses on how a substance is used, reused and lost in a system. In order to maintain efficacy, the boundaries of the system under investigation have to be well-defined. The European Union 27 member states (EU27) offer not only well-defined geographical boundaries, but also has abundant availability of data that can be used to define the boundaries of the anthroposphere. Therefore, Van Dijk et al. (2015) was able to agglomerate various national data sources to quantify the P flow and stocks in the EU27 (Fig 1). This study analysed and adapted the P flow model put forth by Van Dijk et al. (2015) to answer the following research question: How does animal husbandry affect P circularity in the EU27? If Prof. Fresco’s statement is correct, then it can be expected that a food system without animals does not support P circularity.

2. Methods

2.1 Approach

The flow model put forth by Van Dijk et al. (2015) was used as a starting point for this research, because it contains elaborate data on P flow through the system in the EU27. Details of the original model can be found in Appendix A. Van Dijk’s model was based on an agglomeration of raw data. Because the data involved a wide variety of sources and collection methods, it needed to be balanced to equalize input and output. Subsequently, the data was subjected to an iterative balancing method using programming software General Algebraic Modelling System (GAMS). Van Dijk et al. (2015) quantified P flows and provided insight into efficiency for each of the following sectors: Crop Production (CP), Animal Production (AP), Food Processing (FP), Non-Food production (NF) and Human Consumption (HC). For each sector, input and output flows of P are quantified on a

(5)

subflow level, adding up to a total of 96 subflows. However, the model was not designed for alteration of parameters in order to predict system response to changing circumstances. Therefore, two scenarios were designed to investigate the impact of animal production on system behaviour: Scenario (i) Business as usual & Scenario (ii) No animal production. Scenario (i) is based on the original model shown in Fig. 1 and Scenario (ii) required adaptation of the original model to reflect a P flow system that excludes animal production. Scenario (ii) was visualized in a fashion similar to the original model using diagramming software Lucid Chart (www.lucidchart.com). The difference in P flow quantities between Scenario (i) and (ii) can be used as a measure of the impact of the presence animal production on the system.

The analysis of both scenarios was based on three measurements that are related to the circular economy: (1) total inorganic P import, (2) P accumulation in soil, (3) total losses. Because inorganic P extracted from phosphate rock is a non-renewable resource, it is – similar to waste and losses – inherently incompatible with circularity. In addition, although accumulated P in the soil is not eternally lost from the system, it does not support a circular economy considering in-and output. With intra-system accumulating P stocks, during each cycle the output will be smaller than the input, repeatedly requiring extra input and defeating the purpose of circularity. The impact of the gradual decline of animal production on the three measurements for circularity was depicted in a line chart using Microsoft Excel.

In Van Dijk et al. (2015), the origin and destination of, respectively, the import and export are insufficiently defined to be labelled as circular. However, eliminating import and export is not essential for investigating the impact of animal production on the system. Including them would significantly increase the complexity of the research and corresponding assumptions, because it would entail mapping extra-system P flows. Therefore, this study excluded both flows in the measurements for circularity. Nevertheless, it must be noted that, in a perfectly circular system, the input is derived from the output and does not require extra-system input.

2.2 Adaptations

Describing the P flow system excluding animal production required adaptation of the original model put forth by Van Dijk et al. (2015). The substance flow analysis does not describe how the input flows are proportionally divided over the output flows per sector. For instance, which quantity of P imported into sector ‘food processing’ constitutes for which quantity of P in output flows is uncertain. Therefore, this study used a set of assumptions (Table 1) to determine system behaviour as a response to the decline of animal production. This paragraph summarizes the model adaptations and underlying assumptions per sector. An extensive overview of all adaptations including calculations can be found in Appendix B.

Animal Production

Initially, to design the model described by scenario (ii), all flows directly going in and out of sector animal production (AP) were linked to ‘AP productivity’, a parameter with values ranging from 1 (100%) to 0 (0%). Each subflow value was multiplied with the AP productivity value. The 100% and 0% boundaries reflect scenarios (i) and (ii), respectively. Subsequently, all subflows indirectly related to AP were recalculated or redirected on the basis of the original data and the assumption that the demand for P in ‘Human Consumption’ (HC) will remain constant.

Food Processing

To determine the impact of the already implemented decrease in value of subflows to- and from AP, all input and output subflows in FP were divided into three categories: animal-based products (AbP), plant-based products (PbP) and others. Category ‘others’ include flows such as subflow(3.5) ‘Food additives raw material’ and subflow(19.1) ‘Food processing pet food ingredients’ (Table 4.1 & 4.2, Appendix B). Subsequently, they were defined in terms of proportions to calculate their response to the changing inflow and outflow of P from and to AP (Table 4.3, Appendix B). The amount of P that

(6)

reached HC from FP (594 Gg P/year) was kept constant by compensating for the decrease in P from AbP with an increase in P from PbP. This was done based on the assumption that the demand for P in society would remain constant throughout the shift to no AP (Table 1).

“Fig. 1. Phosphorus (P) use for the EU-27 in 2005 [Gg P/year]; aggregated at the food and non-food production–consumption–waste chain based on 96 sub-flows; showing the imports (blue), exports (purple), losses (red) and internal upward/downward flows (black) for crop production (CP), animal production (AP), food processing (FP), non-food production (NF) and consumption (HC) sectors (indicated with square blocks); the arrow thickness shows the relative flow sizes; the positive balance of +924 in CP represents annual net accumulation of P in agricultural soils in 2005.” (Van Dijk et al., 2015)

Crop Production

The changes made in AP and FP required a response from the import into CP, as the other input flows remained unchanged. To define the response, the CP efficiency was calculated by defining the effective output, i.e. output minus losses and accumulation, as a proportion of the input. Because the effective output required from CP to sustain the demand in HC was already calculated before, the response of the import subflows could now be calculated. Finally, the accumulation and losses were defined as a proportion of the crop production input.

(7)

Human Consumption & Non-food Production

In HC and NF, there are relatively little adaptations besides the ones already defined before. The total input and output don’t change with the decrease in AP. The downwards flow from HC to AP is added to losses, as the former decreases the latter increases. This flow supports Prof. Fresco’s claim that animals can recycle human waste. However, it constitutes merely 0.5% of sector input. In a similar fashion, the upwards flow from AP to NF is added to NF’s import flows.

Table 1

List of assumptions per sector. Animal production

Nr Flow Description

1 All The decline of animal production is proportionally the same for every subflow.

Food processing Nr Flow Description

1 20 The quantity of P that flows to human consumption will not change as a response to the decline in animal production and the decrease in quantity of P that flows to human consumption from animal-based products can be substituted for by an increase in quantity of P from plant-based products with a ratio of 1:1.

2 All All subflows can be divided into categories ‘plant-based products’, ‘animal-based products’ and ‘others’, and calculated as proportions.

Crop production Nr Flow Description

1 1 Import subflows can be calculated in proportion to effective sector output. 2 9 Losses can be calculated as a constant proportion of sector input.

3 32 Accumulation in soil can be calculated as a constant proportion of sector input.

Human consumption Nr Flow Description

1 23.1 Food residues for animal feeding will be lost from the system in proportion to the decline of food residues for animal going to animal production.

Non-food production Nr Flow Description

(8)

Fig. 2. Phosphorus (P) use for the EU-27 in 2005 [Gg P/year depicting Scenario (ii) No animal production; showing the imports (blue), exports (purple), losses (red) and internal upward/downward flows (black) for crop production (CP), animal production (AP), food processing (FP), non-food production (NF) and consumption (HC) sectors (indicated with square blocks); the arrow thickness shows the relative flow sizes; the positive balance of +222 in CP represents annual net accumulation of P in agricultural soils.

3. Results

3.1 Scenario (ii)

Scenario (ii) is displayed in Fig. 2. Comparing Scenario (ii) to Scenario (i), overall input and output decreased significantly. The largest discrepancies were detectable in sectors Food Processing and Crop Production. By excluding Animal Production from the system, nearly all flows going in and out of Food Processing and Crop Production decreased, including inorganic P import, accumulation in soil and losses. Logically, with the decrease in AP productivity decreased the demand for crops. Lower productivity requires less input, i.e. less import, and decline in Crop Production input resulted in a decline in P losses and accumulation in soil. Naturally, all flows, including inorganic P import and losses, directly linked to AP decreased to zero in correspondence with AP productivity. All flows connected to Human Consumption and Non-food Production stayed relatively stable. ‘Losses Human Consumption’ and ‘Import Non-food Production’ increased a little, as a result of the elimination of the outflows originally destined for Animal Production.

(9)

3.2 Circularity

For Scenario (i) and (ii), Table 2 shows the values related to the three measurements for circularity: (1) total inorganic P import, (2) P accumulation in soil, (3) total losses. In Scenario (ii), total inorganic P import, accumulation in soil and total losses decreased by 58%, 76% and 34%, respectively, when compared to Scenario (i) (Fig. 3). Overall losses decreased despite adding the HC flow, originally flowing downwards to AP, to losses.

Table 2

Evaluation of Scenario (i) and (ii) on the basis of the three measurements for circularity: (1) total inorganic P import, (2) P accumulation in soil, (3) total losses. The values are expressed in [tonnes P / year].

Scenario (i)

Measurement Value [tonnes P / year]

1. Total inorganic P import 1,776,109 2. Accumulation in soil 924,285 3. Total losses 1,216,886

Scenario (ii)

Measurement Value [tonnes P / year]

1. Total inorganic P import 750,071 2. Accumulation in soil 222,053 3. Total losses 803,973

Fig. 3. Influence of Animal Production on system measurements for circularity. 100% and 0% describing Scenario (i) ‘Business as usual’ and Scenario (ii) ‘No Animal Production’, respectively. All three variables decrease at different rates in response to the decline in AP productivity.

0 200000 400000 600000 800000 1000000 1200000 1400000 1600000 1800000 2000000 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Tonnes P / y ear AP productivity

Influence of Animal Production on P circularity

(10)

4. Discussion

4.1 Interpretation of results

Scenario (ii) required 58% less use of inorganic P, mined from finite phosphate rock reserves. A decrease in use of the finite resource entails mitigating the adverse effects of resource scarcity. Furthermore, P accumulation in soil was 76% lower for Scenario (ii) than for Scenario (i). The decrease in accumulating P in soils causes a decrease in the difference between input and output. Would the output be equal to the input, circularity becomes possible through P recovery from waste flows. However, with P accumulating in the soil, no matter the efficiency of the recovery methods, a perfectly circular P flow is unattainable. Finally, with the decline in animal production, total losses decreased by 34%. As a result, less P will enter water bodies and pollute aquatic ecosystems through eutrophication (Buckwell & Nadeu, 2016).

4.2 Focus on Phosphorus

This study is limited by the focus on one substance. A substance flow analysis, like the one performed in Van Dijk et al. (2015), can provide guidelines for policy making concerning sustainable substance management. However, it should be noted that only one substance was focused on: Phosphorus. To adequately judge sustainable management, all substances related to the product of focus – in this case mainly food products – have to be taken into consideration (Brunner & Rechberge, 2016). For instance, this study compensated for the decline in consumption of animal-based food products by an increase in consumption of plant-animal-based food products. While the P content may have been adequately substituted for, the nitrogen (N) ratio of plant-based products vs animal-based products might be different than the phosphorus ratio. To sum up, compensation on the basis of P content might create a deficit of N content in the consumption sector. Combining SFAs of each nutritional component of food products requires significantly more effort, but provides a more effective compass for policy makers (Brunner & Rechberge, 2016). Therefore, we suggest mapping the nutritional components of food products and their origin for future research on a circular food system.

4.3 Scenario (ii) and circularity

It should be noted that the P flow system according to Scenario (ii) is still linear, defeating the purpose of long-term sustainability. It is more sustainable than Scenario(i), but it is not circular. Although the system requires smaller quantities of inorganic P import and causes less P accumulation in soil and extra-system losses, these flows are still present. To make the system truly circular the P content of losses subflows should be recovered and reapplied to the soil or used in other sectors, eliminating the need for inorganic P import (Buckwell & Nadeu, 2016). In addition, fertilization has to become more efficient and soil or crop specific to prevent accumulation, runoff and leaching (Cordell et al., 2009). The orginal model put forth by Van Dijk et al. (2015) included one flow that exemplified recycling by animals: food residues for animal feeding. This flow involves food leftovers from human consumption, that in Scenario (ii) end up as losses, and constitutes for 0.5% of P consumed by humans. Alternatively, Buckwell & Nadeu (2016) suggest various methods to recover P from solid organic and waste wastewater, the largest waste stream, including: anaerobic digestion, composting and pyrolysis. Non of these techniques include the use of animals. Furthermore, Cordell & White (2015) argue that a vegetable based diet requires 2-3 times less P fertilizer than a meat-based diet.

(11)

4.4 Computer modelling

To gain useful insight into system functioning, it is preferable to have knowledge of how proportions of input subflows in a sector are divided over output subflows. Whereas this study used assumptions to determine the effect of a decline in value for subflows flowing in and out of sector Animal Production, initial programming of proportional distribution could prove a more reliable method. For instance, knowing exactly how input subflow ‘slaughtered animals’ into sector Food Processing is divided over output subflows concerning animal-based food products for human consumption, pet food and waste flows, allows for reliable computation of the effect of said subflow. If the whole model was programmed in such a fashion, it could be used more aptly for predicting potential future scenarios. Therefore, we suggest designing a model that includes proportional distribution of substance per flow for future research concerning flow system functioning.

4.5 Conclusion

This study found that animal husbandry negatively influences P circularity in the EU27. The amount of P consumed in society in food and non-food products was kept constant for both Scenario (i) ‘Business as Usual’ and Scenario (ii) ‘No Animal Production’. Nevertheless, inorganic P import, accumulation in soil and losses dropped drastically when comparing Scenario (i) to Scenario (ii). Therefore, it can be concluded that when animal production was reduced to zero, circularity increased. The contribution of animal production to total inorganic P import, accumulation in soil and total losses was disproportional, as animal-based products contributed relatively little to human consumption.

(12)

Appendix A – System description

“Fig. 1. Phosphorus (P) use for the EU-27 in 2005 [Gg P/year]; aggregated at the food and non-food production–consumption–waste chain based on 96 sub-flows; showing the imports (blue), exports (purple), losses (red) and internal upward/downward flows (black) for crop production (CP), animal production (AP), food processing (FP), non-food production (NF) and consumption (HC) sectors (indicated with square blocks); the arrowthickness shows the relative flowsizes; the positive balance of +924 in CP represents annual net accumulation of P in agricultural soils in 2005.” (Van Dijk et al., 2015)

“Our system includes crop production (CP), animal production (AP), food processing (FP), non-food production (NF) and consumption (HC) sectors (Fig. 1). We used the food system approach with anthroposphere system boundaries as described by Ma et al. (2010), but also included production of petfood, forestry products, inorganic feed and food P additives, and detergents in the NF sector. The CP sector includes arable and grass land production as well as the seed industry. The AP sector includes livestock production, fish culture (aquaculture), and the feed processing industry. The FP sector includes the processing of crops, milk and eggs, the slaughtering process of livestock, and catches of fish and other wild animals from nature as an external input from outside the system

(13)

boundary. The NF sector includes the fibre, forestry (wood, paper, etc.), petfood and detergent industries. The HC sector includes the societal consumption of plant and animal based food products and non-food products, such as fibres, tobacco, skins/hides, pet food, detergents, wood and paper. This consumption can take place via households, wholesale, retail, food service, restaurants and offices, etc. On the output side, this HC sector includes the handling of related communal liquid and solid waste flows such as wastewater, municipal solid waste, bio and green waste, pet excreta, and wood and paper wastes. All other non-communal waste flows are situated in the concerning sector such as stable manure losses in AP, liquid and solid industrial wastes including meat and bone meal in FP and biomass incineration for bio-energy production in NF. The input (import) and output (export +loss) flows connect the systems anthroposphere with the other compartments of the total environment, including the hydrosphere (e.g. emissions), biosphere (e.g. fish catches, wood harvest), atmosphere (e.g. small amounts of deposition), and lithosphere (e.g. P-rock mining, soils). The geographical boundary included the 27 Member States of the European Union (EU-27). The base year was 2005, but our estimates also include the period 1961 to 2009.” (Van Dijk et al., 2015)

Appendix B – Flow adaptations and calculations

Per sector, Appendix B elaborates on the adaptations and corresponding calculations used for Scenario (ii). Table 3 displays all balanced flow- and subflow values as originally put forth by Van Dijk et al. (2015). All tables show values for Scenario (i). The capital letters under ‘Abbreviations’ stand for: Import (I), Export (E), Losses (L), Upwards (U) and Downwards (D). The capital letters are followed by the sector abbreviations described in Appendix A. The Microsoft Excel file used to execute all calculations can be found in: https://drive.google.com/drive/folders/1sm-GkEizJsF1aYqvIUaCOUEoFCheEYY2?usp=sharing.

Concerning sector animal production, all subflows were subjected to the calculation shown below:

1) Flow value = original data * AP productivity

For sectors food processing and crop production all input and output subflows are displayed as total input and output changed in response to the decline in AP productivity. Because there were relatively few adaptations, the analysis for sectors human consumption and non-food production shows only the subflows that were affected by the decline in AP productivity and not defined in any of the other sectors.

Table 3

Phosphorus flows and subflows in the EU27 in 2005.

Main Flows Subflows

Nr Abbreviations Description Flow

[tonnes P/year]

Nr Name Flow

[tonnes P/year]

1 Icp Import into crop production 1,399,207 1.1 Seeds & planting material

import

2,787

1.2 Mineral fertilizer 1,389,431

1.3 Pesticides 1,269

1.4 Atmospheric deposition 5,720

2 Iap Import into animal

production

439,945 2.1 Plant-based processed feed import

189,124

2.2 Animal-based processed feed

import

652

2.3 Live animals import 259

2.4 Inorganic feed additives 249,910

3 Ifp Import into food processing 338,132 3.1 Crops & processed products

import

(14)

3.2 Livestock slaughtered &

processed products import 74,941

3.3 Fish catches 22,741

3.4 Wild products 595

3.5 Food additives raw materials 26,599

4 Inf Import into non-food

production

215,040 4.1 Plant-based materials import 5,155

4.2 Animal-based materials import 1,524

4.3 Forestry products import 5,745

4.4 Detergent raw materials 110,169

4.5 Harvested wood 92,447

5 Ecp Export from crop production 3,618 5.1 Seeds & planting materials

export

3,618

6 Eap Export from animal

production

21,453 6.1 Plant-based processed feed

export

11,085

6.2 Animal-based processed feed

export 5,156

6.3 Live animals export 5,212

6.4 Manure export 0

7 Efp Export from food processing 215,557 7.1 Crops & processed products

export

134,375

7.2 Livestock slaughtered &

processed products export

81,182

8 Enf Export from non-food

production

10,526 8.1 Plant-based materials export 2,389

8.2 Animal-based materials export 2,216

8.3 Exported forestry products 5,921

9 Lcp Losses from crop production 84,488 9.1 Leaching & drainage 39,602

9.2 Run-off & erosion 44,886

10 Lap Losses from animal

production 62,027 10.1 Losses from stables 61,985

10.2 Feed waste 42

11 Lfp Losses from food processing 338,970 11.1 Slaughter waste 293,837

11.2 Food processing solid waste 35,945

11.3 Food processing wastewater 9,188

12 Lnf Losses from non-food

production 76,875 12.1 Incinerated fuelwood 9,841

12.2 Paper industry waste 1,662

12.3 Wood industry waste 65,372

13 Lhc Losses from human

consumption

654,526 13.1 Communal sewage sludge 226,680

13.2 Urban WWTP effluent 37,553 13.3 Centralized untreated wastewater 16,311 13.4 Decentralized treated wastewater 35,730 13.5 Decentralized untreated wastewater 10,637 13.6 Uncollected wastewater 31,815

13.7 Compost non-agricultural use 9,444

13.8 Deceased humans 3,576

13.9 Paper waste 20,918

13.10 Wood waste 8,780

13.11 Food waste households 79,325

13.12 Food waste retail 16,071

13.13 Food waste food service 80,045

13.14 Pet food waste 7,306

13.15 Pet excreta 69,255

13.16 Deceased pets 1,080

14 Ucp-ap Flow from crop production

to animal production 1,459,884 14.1 Feed crops 437,175

14.2 Roughages 1,022,709

15 Ucp-fp Flow from crop production

to food processing

841,546 15.1 Food crops 841,546

16 Ucp-nf Flow from crop production

to non-food production 12,332 16.1 Non-food crops 12,332

17 Uap-fp Flow from animal

production to food processing

552,602 17.1 Slaughtered animals 388,841

17.2 Milk & eggs 158,883

(15)

18 Uap-nf Flow from animal production to non-food production

559 18.1 Wool & hair 559

19 Ufp-nf Flow from food processing

to non-food production 85,510 19.1 Food processing pet food ingredients 44,807

19.2 Slaughter by-products for pet

food

34,096

19.3 Food processing residues other

utilization

6,607

20 Ufp-hc Flow from food processing

to human consumption

594,119 20.1 Plant-based food products 368,373

20.2 Animal-based food products 198,160

20.3 Inorganic food additives 27,586

21 Unf-hc Flow from non-food to

human consumption

238,194 21.1 Plant-based materials 5,805

21.2 Animal-based materials 523

21.3 Other utilization food & feed 6,232

21.4 Pet food 75,428

21.5 Household detergent 109,128

21.6 Forestry products 41,078

22 Dhc-cp Flow from human

consumption to crop production

161,603 22.1 Communal sewage sludge

applied 147,107

22.2 Communal compost applied 14,496

22.3 Recycled compounds (Hc-Cp)

for fertilizers 0

23 Dhc-ap Flow from human

consumption to animal production

4,031 23.1 Food residues for animal

feeding

4,031

23.2 Recycled compounds (Hc-Ap)

for feed additives 0

24 Dhc-fp Flow from human

consumption to food processing

0 24.1 Food residues for food

production

0

24.2 Recycled compounds (Hc-Fp)

for food additives

0

25 Dhc-nf Flow from human

consumption to non-food production

12,154 25.1 Recycled paper 10,746

25.2 Recycled wood 1,408

25.3 Recycled compounds (Hc-Nf)

for non-food use

0

26 Dnf-cp Flow from non-food

production to crop production

0 26.1 Recycle organic materials 0

26.2 Recycled compounds 0

27 Dnf-ap Flow from non-food

production to animal production

0 27.1 Non-food materials for animal

feed

0

27.2 Recycled compounds (Nf-Ap)

for fertilizers 0

28 Dnf-fp Flow from non-food

0 28.1 Food & beverage ingredients 0

28.2 Recycled compounds (Nf-Fp)

fod feed additives

0

29 Dfp-cp Flow from food processing

to crop production 16,670 29.1 Slaughter by-product fertilizer 16,670

29.2 Recycled compounds (Fp-Cp)

fod feed additives

0

30 Dfp-ap Flow from food processing

to animal production

481,454 30.1 Feed crops & ingredients 480,363

30.2 Slaughter by-product feed 1,091

30.3 Recycled compounds (Fp-Ap)

for feed additives

31 Dap-cp Flow from animal

production to crop production

1,748,673 31.1 Manure 1,748,673

(16)

Food Processing

To understand the impact of a decrease in all flows going in and out of AP on input and output subflows in FP, three categories were designed in which the subflows could be divided: animal-based products (AbP, red), plant-based products (PbP, green) and others (gray). All subflow details, calculations and adaptations can be found in Table 4.1, 4.2 and 4.3. Concerning the input, AbP comprise all subflows going from AP to FP, PbP include crops & processed products import and food crops from CP, and the remaining import subflows were assigned to ‘others’. The output subflows proved more difficult to categorize as the origin of the P content is undefined. The P content of e.g. output subflow(11.2) 'Food processing solid waste' could possibly be derived from input subflows from all three categories. Therefore, the subflows that were going to be directly affected by the decline in AP needed to be defined first. The three major output subflows directly linked to the input flow from AP are export subflow(7.2) 'Livestock slaughtered & processed products export', losses subflow(11.1) 'Slaughter waste' and subflow(20.2) 'Animal-based food products' destined for HC. Though proportions of these three subflows might find their origin in any of the import subflows assigned to category others, this research prioritised a vegetarian human population, i.e. no AbP flow to HC. Besides that, the discrepancies were insignificant and irrelevant to discovering system functioning on a general scale. Comparing the P content in input and output subflows in category AbP resulted in a difference of 20,577 tonnes P, or 3.7%. As Van Dijk et al. used an iterative method to balance the raw data, resulting in calculated flows deviating up to 15% from the original data, this study allowed differences of relatively small proportions, i.e. smaller than 5%. While proportions of output subflows concerning pet food and useful slaughter by-products might have been derived from AbP input flows, they were kept constant throughout the dissolution of AP. Logically, pets will not switch to a vegan diet and, practically, it is more effective to maintain a clear view and not make the adaptions unecessarily complex, especially when it concerns minor subflows of 1% of sector input or less. The subflows that involved AbP, but are still a requirement in Scenario (ii), were allocated to ‘others’ and remained unchanged - with the exception of subflow(30.2) 'Slaughter by-product feed' (0.1% of sector input), as it is directly connected to AP. Theoretically, in a system with no AP, their P content would be derived from import. Besides subflow(30.2), they include subflow(19.1) 'Food processing pet food ingredients', subflow(19.2) 'Slaughter by-product feed' and subflow(29.1) 'Slaughter by-product fertilizer', but also subflow(20.3) 'Inorganic food additives', which can be directly connected to input subflow(3.5) 'Food additives raw material'. The PbP output subflows that logically followed, include subflow(7.1) 'Crops & processed products export', subflow(11.2) 'Food processing solid waste', subflow(11.3) 'Food processing wastewater', subflow(19.3) 'Food processing residues other utilization', subflow(20.1) 'Plant-based food products' and subflow(30.1) 'Feed crops & ingredients'.

With all the subflows categorized, the calculations could start. For all output subflows in category AbP, a constant 'C' was calculated, describing their proportion of the sum of AbP input subflows - all calculations are shown in Table 4.3. With this constant, the values of AbP output subflows could be calculated as a proportion of AbP input subflows, resulting in values of 0 tonnes P at the 0% AP productivity mark of Scenario (ii). Subsequently, as the amount of P flowing to HC now declines in proportion to AP productivity due to calculation subflow(20.2) ‘Animal-based food products’ , output subflow(20.1) 'Plant-based food products' is subjected to a formula using the sum of P reaching HC in food products in Scenario (i) as a constant, but substituting P from AbP with P from PbP. To keep the system in balance, the changing PbP output subflow(20.1) and subflow(30.1), the latter decreasing in correlation with AP, require a response from PbP input subflows. Hence the PbP efficiency coefficient was designed. The PbP output subflows were divided into two groups: effective and ineffective, with two losses subflows constituting the ineffective group and the other subflows the effective group. This way, the amount of P in PbP input subflows required to sustain the changing demand of the PbP output subflows could be calculated. To illustrate the impact on CP, the import of crops was kept constant. Finally, the two PbP losses subflows were defined as a

(17)

proportion of the PbP input subflows, both with a particular constant 'C', and changed in proportion to the changing PbP input.

Table 4.1

Food processing input

Nr Abbreviations Description Flow

[tonnes P/year] Nr Name Flow [tonnes P/year] Percentage of total sector input Calculations

3 Ifp Import into food

processing

338,132 3.1 Crops & processed products import

213,256 12.3%

3.2 Livestock slaughtered

& processed products import

74,941 4.3%

3.3 Fish catches 22,741 1.3%

3.4 Wild products 595 0.0%

3.5 Food additives raw

materials 26,599 1.5%

15 Ucp-fp Flow from crop

841,546 15.1 Food crops 841,546 48.6% SUM(effective PbP

out) / PbP efficiency - subflow(3.1)

17 Uap-fp Flow from animal

552,602 17.1 Slaughtered animals 388,841 22.4% Defined by AP productivity

17.2 Milk & eggs 158,883 9.2% Defined by AP

productivity

17.3 Aquaculture products 4,878 0.3% Defined by AP

productivity

Total 1,732,280 100%

Table 4.2

Food processing output

Nr Abbreviations Description Flow

[tonnes P/year] Nr Name Flow [tonnes P/year] Percentage of total sector input Calculations

7 Efp Export from food

processing

215,557 7.1 Crops & processed products export

134,375 7.8%

7.2 Livestock slaughtered

& processed products export

81,182 4.7% C7.2 * SUM(AbP in)

11 Lfp Losses from food

processing

338,970 11.1 Slaughter waste 293,837 17.0% C11.1 * SUM(AbP in)

11.2 Food processing solid

waste 35,945 2.1% C11.2 / SUM(PbP in)

11.3 Food processing

wastewater

9,188 0.5% C11.3 / SUM(PbP in)

11.4 System imbalance

insecurity

0 0.0% Total input - total output

19 Ufp-nf Flow from food

processing to non-food production

85,510 19.1 Food processing pet food ingredients

44,807 2.6%

19.2 Slaughter

by-products for pet food

34,096 2.0%

19.3 Food processing

residues other utilization

6,607 0.4%

20 Ufp-hc Flow from food

processing to human consumption 594,119 20.1 Plant-based food products 368,373 21.3% Original data subflow(20.1) + original data subflow(20.2) – calculated subflow(20.2)

(18)

20.2 Animal-based food

products 198,160 11.4% C20.2 * SUM(AbP in)

20.3 Inorganic food

additives

27,586 1.6%

29 Dfp-cp Flow from food

processing to crop production 16,670 29.1 Slaughter by-product fertilizer 16,670 1.0% 29.2 Recycled compounds (Fp-Cp) fod feed additives 0

30 Dfp-ap Flow from food

processing to animal production

481,454 30.1 Feed crops &

ingredients 480,363 27.7% Defined by AP productivity

30.2 Slaughter by-product

feed

1,091 0.1% Defined by AP

productivity

30.3 Recycled compounds

(Fp-Ap) for feed additives

0

Total 1,732,280 100%

Table 4.3

Food Processing adaptations

Name Description Value Calculation

Sum AbP in Sum of P input from animal-based products 552,602 SUM(subflow(17.1); subflow(17.2); subflow(17.3))

Sum PbP in Sum of P input from plant-based products 1,054,802 SUM(flow(3.1); flow(15.1))

PbP efficiency Plant-based products efficiency coefficient 0.938297425 1_{SUM(effective PbP out) / SUM (PbP in)}

C7.2 Constant used to calculate subflow(7.2) 0.146908625 1_{subflow(7.2) / SUM(AbP in)}

C11.1 Constant used to calculate subflow(11.1) 0.531733508 1_{subflow(11.1) / SUM(AbP in)}

C11.2 Constant used to calculate subflow(11.2) 0.034077486 1_{subflow(11.2) / SUM(PbP in)}

C11.3 Constant used to calculate subflow(11.3) 0.00871064 1_{subflow(11.3) / SUM(PbP in)}

C20.2 Constant used to calculate subflow(20.2) 0.358594431 1_{subflow(20.2) / SUM(AbP in)} 1_{these calculations only used the original data displayed in table 3 to calculate a constant.}

Crop Production

As CP only comprises plant-based products, this sector was more easily subjected to adaptations. All subflow details, calculations and adaptations can be found in Table 5.1, 5.2 and 5.3.The sector input and output decline in correlation with AP, but the output changes further with the in FP defined subflow(15.1) 'Food crops', requiring an input response. As downward subflow(29.1) 'Slaughter by-product fertilizer' from FP to CP remains constant and the downward flow from HC to CP is not subjected to change, the response has to come from the import flows. Subflow(1.1) 'Seeds & planting material import', subflow(1.2) 'Mineral fertilizer' and subflow(1.3) 'Pesticides' were each assigned a constant that described their proportion in respect of one another. Subflow(1.4) 'Atmospheric deposition' was not taken into account, as it was expected to remain constant regardless of any changes related to AP. To calculate the required input response the CP efficiency coefficient was designed, describing the relationship between the input and effective output, i.e. output minus losses. With the use of constants and the CP efficiency, defined in Table 5.3, the import subflows were defined as described by the calculations in Table 5.1. ‘SUM(effective out)’ comprises the sum all output subflows minus the two losses subflows and ‘SUM(other in)’ includes all input subflows except the three import subflows under calculation. Subsequently, the losses subflows and accumulation were subjected to a calculation, using a constant that described the subflows as a proportion of the sector input (Table 5.2).

(19)

Table 5.1

Crop Production input

Nr Abbreviations Description Value

[tonnes P/year] Nr Name Value [tonnes P/year] Percentage of total sector input Calculations

1 Icp Import into crop

production 1,399,207 1.1 Seeds & planting material import 2,787 0.08% SUM(effective out) / CP efficiency - SUM(other in) * C1.1

1.2 Mineral fertilizer 1,389,431 41.77% SUM(effective out) /

CP efficiency - SUM(other in) * C1.2

1.3 Pesticides 1,269 0.04% SUM(effective out) /

CP efficiency - SUM(other in) * C1.3

1.4 Atmospheric

deposition

5,720 0.17%

22 Dhc-cp Flow from human

consumption to crop production 161,603 22.1 Communal sewage sludge applied 147,107 4.42% 22.2 Communal compost applied 14,496 0.44% 22.3 Recycled compounds (Hc-Cp) for fertilizers

26 Dnf-cp Flow from

non-food production to crop production 0 26.1 Recycle organic materials 26.2 Recycled compounds

29 Dfp-cp Flow from food

processing to crop production 16,670 29.1 Slaughter by-product fertilizer 16,670 0.50% 29.2 Recycled compounds (Fp-Cp) fod feed additives

31 Dap-cp Flow from animal

production to crop production 1,748,673 31.1 Manure 1,748,673 52.57% Defined by AP productivity Total 3.326.153 100% Table 5.2

Crop Production output

5 Ecp Export from crop

production

3,618 5.1 Seeds & planting materials export

3,618 0.11%

9 Lcp Losses from crop

production

84,488 9.1 Leaching & drainage

39,602 1.19% C9.1 * input

9.2 Run-off & erosion 44,886 1.35% C9.2 * input

14 Ucp-ap Flow from crop

production to animal production

1,459,884 14.1 Feed crops 437,175 13.14% Defined by AP

productivity

14.2 Roughages 1,022,709 30.75% Defined by AP

productivity

15 Ucp-fp Flow from crop

841,546 15.1 Food crops 841,546 25.30% Defined in FP

16 Ucp-nf Flow from crop

production to non-food production 12,332 16.1 Non-food crops 12,332 0.37% 32 - Accumulation in soil 924,285 - - - 27.79% C32 * input Total 3.326.153 100%

(20)

Table 5.3

Crop Production adaptations

Name Description Value Calculation

C1.1 Constant used to calculate subflow(1.1) 0.00200002 subflow(1.1) / SUM(flow(1.1); flow(1.2) ; flow(1.3))

C1.2 Constant used to calculate subflow(1.2) 0.997089316 subflow(1.2) / SUM(flow(1.1) ; flow(1.2) ; flow(1.3))

C1.3 Constant used to calculate subflow(1.3) 0.000910665 subflow(1.3) / SUM(flow(1.1) ; flow(1.2) ; flow(1.3))

C9.1 Constant used to calculate subflow(9.1) 0.011906247 subflow(9.1) / CP input

C9.2 Constant used to calculate subflow(9.2) 0.013494869 subflow(9.2) / CP input

C32 Constant used to calculate flow(32) 0.27788409 accumulation / CP input

CP efficiency Crop production efficiency coefficient 0.696714793 effective output / input

*All of the calculations above used the original data displayed in Table 3 to calculate a constant.

Human Consumption & Non-food Production

In HC, there are relatively few adaptations besides the ones already defined before. The total input and output don’t change with the decrease in AP. The decline in subflow(23.1) 'Food residues for animal feeding', originally destined for AP, is now attributed to losses as subflow(13.17) (Table 6.1). Sector NF stays untouched throughout the process, but for one tiny subflow. Subflow(18.1) ‘Wool & hair’, 0.2% of sector input, has to gradually be imported as subflow(4.6), following the shift to Scenario (ii), instead of flowing directly from AP to NF (Table 6.2).

Table 6.1

Human Consumption input

[tonnes P/year] Nr Name Value [tonnes P/year] Percentage of total sector input Calculations 13 Lhc Losses from human consumption - 13.17 Food residues for animal feeding 0 0% Original data subflow (23.1) – calculated subflow(23.1)

23 Dhc-ap Flow from

human consumption to animal production 4,031 23.1 Food residues for animal feeding 4,031 0,48% Defined by AP productivity Table 6.2

Non-food production input

4 Inf Import into

non-food production - 4.6 Wool & hair 0 0% Original data subflow(18.1) – calculated subflow(18.1)

18 Uap-nf Flow from

animal production to non-food production

559 18.1 Wool & hair 559 0,002% Defined by AP

(21)

References

Ayres, R., & Ayres, L. (2002). A Handbook of Industrial Ecology, Edward Elgar Publishing Limited, Cheltenham (UK).

Battaglia Richi, E., Baumer, B., Conrad, B., Darioli, R., Schmid, A. & Keller, U. (2015). Health risks associated with meat consumption: a review of epidemiological studies. Int J Vitam Nutr

Res, 85, 1–2.

Buckwell, A. & Nadeu, E. (2016). Nutrient Recovery and Reuse (NRR) in European agriculture. A review of the issues, opportunities, and actions., RISE Foundation, Brussels.

Brown, A. D. (2003). Feed or Feedback: Agriculture, Population Dynamics and the State of the Planet.

International Books, Utrecht.

Brunner, P.H., & Rechberge, H. (2004). Practical Handbook of Material Flow Analysis, Lewis

Publishers, Boca Raton.

Brunner, P.H., & Rechberge, H. (2016). Handbook of material flow analysis: For environmental, resource and waste engineers, CRC Press, Boca Raton.

Carter, S., Herold, M., Avitable, V., de Bruin, S., De Sy, V., Kooistra, L. & Rufino, M. C. (2017). Agriculture-driven deforestation in the tropics from 1990-2015: emissions, trends and uncertainties, Environmental Research Letters, 13(1).

Cordell, D., Drangert, J., & White, S. (2009). The story of phosphorus: Global food security and food for thought, Global Environmental Change, 19, 292-305.

Cordell, D., Rosemarin, A., Schröder, J. & Smit, A. (2011) Towards global phosphorus security: a systemic framework for phosphorus recovery and reuse options. Special Issue on the

phosphorus cycle, Chemosphere, 84, 747-758.

Cordell, D., & White, S. (2015). Tracking phosphorus security: idicators of phosphorus vulnerability in the global food system, Food Security, 7, 337-350.

De Ridder, M., De Jong, S., Polchar, J. & Lingemann, S. (2012). Risks and opportunities in the global phosphate rock market: Robust strategies in times of uncertainty, The Hague Centre for

Strategic Studies (HCSS) Report, The Hague.

Speksnijder, C. (2018). Zoals het klimaatakkoord van Parijs moet er een groot voedselakkoord komen, De Volkskrant.

De Vries, M. & de Boer, I. J. M. (2010). Comparing environmental impacts for livestock products: a review of life cycle assessments. Livest. Sci., 128, 1–11.

FAO. (2017). The future of food and agriculture – Trends and challenges, Rome.

Foley, J. A. et al. (2005). Global consequences of land use. Science, 309, 570–574.

Heshmati, A. (2015). A Review of the Circular Economy and its Implementation, IZA Discussion

(22)

Johnson, D.E. & Ward, G.M. (1996). Estimates of animal methane emissions, Environmental

Monitoring and Assessment, 42, 133–141.

Marschner, H., Marschner, P. (2012). Marschner’s mineral nutrition of higher plants,

Elsevier/Academic Press, London; Waltham, MA, 3rd_ed.

Matson, P. A., Parton, W. J., Power, A. G. & Swift, M. J. (1997). Agricultural intensification and ecosystem properties,Science, 277, 504

Montgomery, D. R. (2007). Soil erosion and agricultural sustainability, Proceedings of the National

Academy of Sciences, USA, 104, 13268–13272.

Ranganathan, J., Vennard, D., Waite, R., Dumas, P., Lipinski, B. & Searchinger, T. (2016). Shifting Diets for a Sustainable Food Future, Working Paper, Installment 11 of Creating a Sustainable Food

Future. World Resources Institute: Washington DC.

Ruttenberg, K.C. (2003). The Global Phosphorus Cycle, Treatise on Geochemistry, Elsevier, 9, 585– 643.

Song, K., Xue, Y., Zheng, X., Lu, W., Qiao, H., Qin, Q., & Yang, J. (2017). Effects of the continuous use of organic manure and chemical fertilizer on soil inorganic phosphorus fractions in calcareous soil, Scientific Reports, 7.

Stahel, W. (2016). The circular economy, Nature, 531(7595)

Stoll-Kleemann, S. & O’Riordan, T. (2015). The Sustainability Challenges of Our Meat and Dairy Diets, Environment: Science and Policy for Sustainable Development, 57(3), 34-48.

Tubiello, F. N., Salvatore, M., Cóndor Golec, R. D., Ferrara, A., Rossi, S., Biancalani, R., Federici, S., Jacobs, H. & Flammini, A. (2014). Agriculture, Forestry and Other Land Use Emissions by Sources and Removals by Sinks, Food and Agriculture Organization of the United Nations,

Rome.

United Nations. (2018). World Urbanization Prospects: The 2018 Revision, ‘https://esa.un.org/unpd/wup/’.

Vaccari, D. (2009). Phosphorus, a looming crisis, Scientific American, 2009, 42–47.

Van Dijk, K. C., Lesschen, J. P. & Oenema, O. (2016). Phosphorus flows and balances of the European Union Member States, Science of The Total Environment, 542, 1078–1093.

Wilkins, R. J. (2007). Eco-efficient approaches to land management: a case for increased integration of crop and animal production systems, Philos Trans R Soc B, 12, 517–525.

Animal redundancy in phosphorus circularity

Abstract