Biochar Based Soil Amendments in West African Urban Agriculture

Biochar based soil amendments in West African urban agriculture:

Effects on crop yields, nutrient leaching and soil biological properties.

Dissertation zur Erlangung des Grades Doktor der Naturwissenschaften (Dr. rer. nat.)

an der Fakultät für Geowissenschaften der Ruhr-Universität Bochum

Vorgelegt von:

Steffen Werner M.Sc.

Bochum, den 21.2.2018

Erstbetreuer: Prof. Dr. Bernd Marschner

AG Bodenkunde und Bodenökologie, Geographisches Institut,

Fakultät für Geowissenschaften, Ruhr-Universität Bochum

Zweitbetreuer: Prof. Dr. Andreas Bürkert

Ökologischer Pflanzenbau und Agrarökosystemforschung in den Tropen und Subtropen,

Fakultät Ökologische Agrarwissenschaften, Universität Kassel

Table of Content

List of figures ...... i

List of tables ...... iii

List of Abbreviation ...... v

1. Introduction into urban agriculture in West African cities ...... 1

1.1 Soils in the West African Savanah and traditional / rural farming ...... 1

1.2 Nutrient management and balances in UA ...... 3

1.3 Biochar in soil: Concepts and effects on soil properties ...... 5

1.4 Effects of waste water irrigation on soil properties ...... 7

1.5 Hypothesis, objectives and outline of the thesis ...... 8

2. Agronomic benefits of biochar as a soil amendment after its use as waste water filtration medium ...... 17

3. Nutrient leaching and balances in urban agriculture in Northern Ghana: effects of waste water irrigation, mineral fertilization and biochar application...... 45

4. Effects of biochar and waste water irrigation on soil biological properties in urban agriculture in N-Ghana ...... 78

5. Summary discussion, conclusion and future research needs ...... 103

6. Acknowledgements ...... 111

7. Curriculum Vitae ...... 112

List of figures

Fig 1-1: Agroecological zones of Sub-Saharan West Africa. (Source: Bationo and

Buerkert (2001))……………………………………………………………... 2

Fig 2-1: Elimination of E.coli and Enterococci in water after filtration and influent

concentrations. Error bars show ± one standard deviation and asterisk indi-

cate significant difference between sand and biochar filter effluent (Whitney-

Mann U-Test, p<0.05, n=3)……………………………………….. 26

Fig 2-2: Total biomass production at the end of the experiment. Letters indicate signif-

icant differences of mean (ANOVA, p<0.05) and error bars ± one standard 28 deviation (n=5)………………………………………………………

Fig 2-3 Left: Mineral nitrogen content in soil after the experiment. Right: Bray 1 ex- and 2-4: tractable PO4-P in soil after the experiment. Letters indicate significant differ-

ences of mean (ANOVA, p<0.05) and error bars show standard deviation

(n=5)………………………………………………………………… 30

Fig 3-1: Schematic sketch of the wick-lysimeter used in this study…………………..... 51

Fig 3-2: Seasonal water flux (a) and the percentage of leaching to total water input (b)

of clean water (light gray bars) and waste water (dark grey) irrigated plots of

the multi-factorial field experiment in Tamale, northern Ghana. Error bars

represent + / - one standard deviation…………………………………………. 56

Fig 3-3: Seasonal leaching of NO3-N (a), PO4-P (b), K (c), Mg (d), Ca (e) and Na (f)

under clean water (light gray bars) and waste water (dark grey) irrigated plots

of the multi-factorial field experiment in Tamale, northern Ghana. Error bars

represent +/- one standard deviation, n=4…………………………………… 57

Fig 3-4: Seasonal balances of N (a), P (b), K (c), Mg (d), Ca (e), Na (f) under clean

water (light gray bars) and waste water (dark grey) irrigated plots of the mul-

ti-factorial field experiment in Tamale, northern Ghana. Error bars represent

+/- one standard deviation, n=4. The Na balance was calculated without up- 58 take by the crops……………………………………………………

Fig 3-5: Contribution of leaching and crop uptake to the total output of N (a), K (b),

Mg (c) and Ca (d) in the multi-factorial field experiment in Tamale, northern 60 Ghana…………………………………………………………………………

Fig 4-1: Basal respiration, soil microbial biomass carbon and metabolic quotient. Error bars represent one standard deviation, n=4. Stastical significant effects from

MANOVA are noted in the graphs. Basal respiration was squared to obtain 88 normal distribution…………………………………………………………….. Fig 4-2: Activity of extracellular enzymatic groups of C-cycle (α-glucosidase, β- glucosidase, β-xylosidase and β-cellobiosidase), N-cycle (leucine- aminopeptidase, tyrosine-aminopeptidase and arginine-aminopeptidase) and

P-cycle (acid phosphatase) in the different soil treatments under clean and 90 waste water irrigation………………………………………………………….. Fig 4-3: Score plot of principal component analysis with explained variance of com- 93 ponents in parantheses……………………………………………………

List of tables

Tab 1-1: Nutrient balances for urban and peri-urban vegetable production systems…... 4

Tab 2-1: Mean characteristics of the waste water used as influent in the filtration ex-

periment ± one standard deviation, n=9. The analyzed water samples were

collected throughout the whole experimental period of 3 months. COD =

Chemical oxygen demand; MPN = Most probable number; NTU = Nephelo-

metric turbidity unit………………………………………………… 22

Tab 2-2: Properties of biochar before and after filtration ± one standard deviation,

n=3. Letters indicate significant differences of mean (t-test, p<0.05)………... 27

Tab 2-3: Mean nutrient concentrations in biomass, pH of soil and standard deviation

(SD). Letters indicate significant differences (ANOVA, p<0.05, n=5) within

a fertilizer group. Differences between groups were assessed with Whitney-

Mann U test…………………………………………………………………… 29

Tab 2-4: Nutrient input, output and balances of the different treatments in the pot trial.

Input = nutrients in biochar + fertilizer; Output = total plant uptake………… 31

Tab 3-1: Seasonal water and nutrient inputs into the multi-factorial field experiment in

Tamale, northern Ghana…………………………………………...... 54

Tab 3-2: P-values from mixed model results for seasonal leaching amounts of the

multi-factorial field experiment in Tamale, northern Ghana. n.s. = not signif-

icant (P > 0.05), N.A. = no data available. 70

iii

…………………………………………..

Tab 3-3: P- values from mixed model results for seasonal nutrient balances of the

multi-factorial field experiment in Tamale, northern Ghana. n.s. = not signif-

icant (P > 0.05) , N.A. = no data available.…………………………………. 71

Tab 4-1: Physico-chemical soil parameters, dehydrogenase activity, substrate induced respiration and statistically significant (p≤0.05) effects and interactions. 86 Means ± one standard deviation, n=4…………………………………………

Tab 4-2: Enzyme activities and statistically significant (p≤0.05) effects and interac- 92 tions. Means ± one standard deviation, n=4…………………………..

Tab 4-3: Rotated component matrix of principal component analysis…………………. 96

List of Abbreviation

α-glu α-Glucosidase

AMC Amido-Methylcoumarin

ANOVA Analysis of variance arg Arginine-aminopeptidase

β-cello β-Ccellobiosidase

β-glu β-Glucosidase

β-xyl β-Xylosidase

BC Biochar

BET Brunauer-Emmett-Teller-Model

COD Chemical oxygen demand

EC Electrical conductivity

E.Coli Escherichia coli

FC Filter char (Biochar after use in filter)

FIB Fecal indicator bacteria

HWC Hot water extractable carbon

INT 2-p-Iodophenyl-3-p-nitrophenyl-5-phenyl-tetrazoliumchlorid

INTF Iodonitrotetrazolium-formazan leu Leucine-Aminopeptidase

MANOVA Multivariate analysis of variance

MBC Microbial biomass carbon

MPN Most probable number

MUF Methylumbelliferyl

N-acet N-Acetyl-Glucosidase

NAP Normal agricultural practice

Nmin Mineral Nitrogen (NO3-N + NH4-N)

NPK Mineral fertilizer (15-15-15)

NTU Nephelometric turbidity unit pH Negative 10 base logarithm of the activity of hydrogen ions pho Acid phosphatase

qCO2 Metabolic quotient of microbial respiration

SD Standard deviation

SOC Soil organic carbon

TOC Total organic carbon

TW Tap water tyr Tyrosine-aminopeptidase

UA Urban agriculture

WHC Water holding capacity of soil

WRB World reference base for soil resources

WW Waste water

vii

1. Introduction into urban agriculture in West African cities

Urban agriculture (UA) is a common phenomenon in West African cities. It has already become very important due to the continuing urbanization worldwide and especially in the West

African sub region. According to UN-HABITAT (2014), about 65% of the West African population will live in urban areas by the year 2050. Especially for the poorest part of the population, UA provides food, labor and income. As the study of Zezza and Tasciotti (2010) shows, the poorest quintile of households (based on expenditure) about 75% are involved in urban farming in Ghana (in 1998), while the share of income generated by UA in this part of the population was about 35%.

The spectrum of UA practices can vary widely, from backyard gardens with cropping only in rainy seasons and moderate fertilization, to all year round farming with high inputs of fertilizers and pesticides. Irrigation is typically done with untreated black and grey water (Keraita and Cofie 2014). Especially, the use of untreated waste water causes serious health risks, as shown for the case of the two biggest Ghanaian cities Accra and Kumasi, where Amoah et al.

(2007) found strong contamination of lettuce with fecal coliform bacteria.

1.1 Soils in the West African Savanah and traditional / rural farming

West African soils in general are less fertile compared to soils in temperate regions. The par- ent material is very old rock on which old and strongly leached soils have been developed. On the African continent in general, there are very few newly fold mountains, younger sediments or volcanic deposits rich in nutrients (Breman et al. 2001). In the past, low population densi- ties allowed the farmers to practice a shifting cultivation system with long fallow periods.

When a decline in soil fertility set in, the farmers moved to another place to let the soil natu-

rally recover. In the last decades, due to population growth, these fallow periods shortened and intensive cropping has reduced nutrient and carbon stocks of the soils (Bationo et al.

1998). The insufficient replacement of nutrients has been assessed by the means of nutrient mass balances. Stoorvogel and Smaling (1990) showed negative balances for the most important macronutrients N, P and K in Sub-Saharan Africa on a national scale. This means, nutrient exports are higher than the nutrient inputs. Furthermore, in a review of 57 nutrient balance studies on farm level all across Africa, 75% of the studies showed a negative N balance

(Cobo et al. 2010).

Figure 1-1: Agroecological zones of Sub-Saharan West Africa. (Source: Bationo and

Buerkert (2001))

Especially in the humid to semi-arid areas (Figure 1-1) where at least one intense rainfall period per year occurs and temperatures are relatively high compared to temperate regions, the turnover of organic matter is high and therefore, the depletion of soil organic matter pools are high (Breman et al. 2001). For instance, Tiessen et al. (1994) estimated a mean turnover time of less than 4 years for organic matter in an Amazonian rainforest soil. There are several man- 2

agement strategies to increase fertility of these soils to increase the organic carbon and nutrient pools. For instance, through intercropping with legumes, mulching, compost application and increased use of manure. However, the adaptation of these strategies is still low (Schlecht et al. 2007).

1.2 Nutrient management and balances in UA

Urban farming is very different compared to rural farming especially in terms of the type of crops grown and nutrient regime. In rural areas, mostly staple crops like maize (Zea mays L.), sorghum (Sorghum Moench), and rice (Oryza sativa) are cultivated. In urban agriculture vegetable crops like lettuce (Lactuca sativa L.), cabbage (Brassica oleracea L.) and tomatoes (So- lanum lycopersicum L.) are grown because of the close proximity to markets and the lag of cooling chains (Drechsel 2002). Rural farming is characterized by negative nutrient balances due to weak soil properties and insufficient nutrient inputs. In UA systems, the farmers use high amounts of mineral fertilizers (NPK and Urea) und manures. In addition, waste water used for irrigation is contributing to the overall nutrient input in UA. Quantitative studies of nutrient mass balances in irrigated urban vegetable production systems show tremendous nutrient surpluses (Table 1). For instance, in the case of the exceptional high balance of Graefe et al. (2008) 7312 kg N ha-1 a-1 waste water irrigation alone had an input of 7487 kg N ha-1 a-1.

However, the measurement of nutrient mass balances is not easy. Many of the studies reported in Table 1 are using a horizontal or partial approach where Balance = Input (fertilizer, nutrients in irrigation water, manure…) - Output (nutrient uptake with harvest). But there are more pathways through which nutrients can leave the agricultural system. The most promi- nent are leaching of nutrients with the water percolating through the soil and gaseous losses of nitrogen. 3

Table 1-1: Nutrient balances for urban and peri-urban vegetable production systems Balance [kg ha-1 a-1] Source Location Balance typ N P K Remarks Goenster et al. (2015) Nuba Mountains, Sudan Full -70 9 -117 Abdalla et al. (2012) Khartum, Sudan (four gardens) Horizontal 75 to 342 -3.4 to -45 -4 to -583 351 to Diogo et al. (2010) Niamey, Niger (ten gardens) Horizontal 290 to 1133 125 to 223 312 Drechsel (2002) Kumasi, Ghana full -176 642 -34 leaching estimated Khai et al. (2007) Bang B, Hanoi, Vietnam (two sites) horizontal 427 to 882 109 to 196 65 to 306 Phuc Ly, Hanoi, Vietnam (two sites) horizontal 85 to 131 160 to 193 20 to 127 Huang et al. (2006) Nanjing, Yangtze river region, China horizontal 814 288 268 Wuxi, Yangtze river region, China horizontal 786 606 -68 Graefe et al. (2008) Gountou, Niamey, Niger horizontal 7312 530 6827 Goudel, Niamey, Niger horizontal 780 260 -7 Safi et al. (2011) Kabul, Afghanistan full 80 75 -205 Lompo et al. (2012) Kodéni, Bobo-Dioulasso, Burkina Faso horizontal 2056 615 1864 Kuinima, Bobo-Dioulasso, Burkina Faso horizontal 1752 446 1643 recalculated on annual Siegfried et al. (2011) Sohar, Oman full 182 99.5 -6 basis

Unfortunately, the measurement of these pathways is not trivial, especially in developing countries. Some studies use ion exchange resins to measure nutrient leaching but this method seems to capture only a part of the real nutrient flux (Siemens and Kaupenjohann 2004). Nev- ertheless, these studies are marked as full balances in Table 1. The results of the mentioned studies show that in many cases in UA the input of nutrients exceeds by far the demand of the crops. Therefore, there is a risk of losing the nutrients either with gaseous emissions or via leaching in times when water flux in the soil profile occurs. This can have negative ecological impacts on other ecosystems and may cause an environmental problem.

1.3 Biochar in soil: Concepts and effects on soil properties

Biochar research in soil started with the work on Terra Preta soil in the Amazonia. In tropical

Ferrasols, which are mostly unfertile, researchers found fertile spots of land and connected this finding to charcoal particles present in the soil. These particles are related to human set- tlements in the past and may contribute to soil fertility until now. Terra Preta soil contains 2.7 times more organic carbon than the surrounding soil (Glaser et al. 2001). Since then, a lot of research has been focusing on the influence of charcoal on soil ecological processes.

The process of producing charcoal is called pyrolysis. Biomass is heated in the absence of oxygen or under limited oxygen conditions. This can be done with either modern technologies or with rather low technology biomass stoves. When the charcoal is intended to be used as a soil amendment it is called biochar (Gaunt and Lehmann 2008). Almost all types of biomass are suitable to produce biochar, for example abundant waste materials can be used. Due to its low production costs it is especially interesting for developing countries.

Biochar has been shown to be very recalcitrant against decomposition. In the Amazonian soils charcoal pieces were found to be up to 2460 years old (Glaser et al. 2001). For newly produced biochar, Zimmerman (2010) estimated half-life times by extrapolation of results from short term incubation studies from 102 to 107 years. However, the recalcitrance of biochar against biological decay varies strongly with different feedstock materials and pyrolysis temperature.

Biochar application had been shown to increase the yields of various crops. For instance, the application of 10% biochar caused an increase in maize yield by 230% on a sandy soil in

Zambia (Martinsen et al. 2014). A recent meta-study on biochar effects on crop yields, with a total of 1125 cases, of which 527 were in tropical climates, revealed a 25% average increase in crop yields in tropical climate when biochar was applied but had no effect on yields in temperate climates. The increase was mainly attributed to a liming and nutrient fertilization effect of biochar on soils low in pH and nutrient poor, typical for the tropics (Jeffery et al.

2017). This is also in line with the findings of Major et al. (2010), who found an increase in maize yields by up to 140% accompanied by an increased soil pH and higher uptake of Ca and Mg.

Furthermore, biochar has been shown to retain nutrients in the soils and reduce the leaching of nitrogen. A charcoal treatment at a rate of 11 t ha-1 on a highly weathered Amazonian Fer- ralsol increased the N retention of soil by 15.6% (Steiner et al. 2008). In a field study with an

Colombian Oxisol mixed with biochar at 20 t ha-1, Major et al. (2012) also found a decrease in leaching of N, Ca and Mg. However, the downward movement of phosphorus was increased. In addition, there are several lab adsorption studies showing that biochar is able to

sorb and release nutrients at varying extend (Chintala et al. 2013, Hale et al. 2013, Yao et al.

2012).

Manifold effects of biochar on soil biological processes have been reported. In most cases the effects are quite different. For instance, several researchers reported an increase in soil microbial biomass when biochar was mixed into the soil (Ameloot et al. 2013, Kolb et al. 2009,

Liang et al. 2010). However, Dempster et al. (2012) found a decreasing microbial biomass when biochar was applied. Furthermore, alteration of enzyme activities, metabolic carbon efficiency, soil respiration and microbial community has been shown and reviewed by Lehmann et al. (2011).

1.4 Effects of waste water irrigation on soil properties

UA systems are often characterized by year round cultivation and irrigation. The only source of water is mostly from open sewage channels, as reported by Bellwood-Howard et al. (2015) for Tamale, Ghana. This waste water can have a huge impact on soil properties and functions due to high nutrient and organic matter loads (Heinze et al. 2014).

For instance, the irrigation with waste or treated waste water has effects on soil pH and EC

(Hernández-Martínez et al. 2016, Pinto et al. 2010). Due to carbon and nutrient contents of waste water, a change of SOC (Siebe et al. 2016) and available nutrients (Hernández-Martínez et al. 2016) has been reported. Furthermore, the soil biological processes like respiration and activities of enzymes can also be altered trough waste water irrigation (Filip et al. 1999,

González-Méndez et al. 2015, Heinze et al. 2014, Meli et al. 2002). Nevertheless, there is the risk of increased nutrient leaching and groundwater pollution when waste water with high nutrient contents is used for irrigation (Hernández-Martínez et al. 2016). Also soil physical 7

properties, such as hydraulic conductivity and water retention, can be affected due to organic compounds and salts commonly present in waste water (Arye et al. 2011, Gonçalves et al.

2007, Schacht and Marschner 2015).

1.5 Hypothesis, objectives and outline of the thesis

The main hypothesis of this thesis is: Biochar can be used as a soil amendment to increase soil fertility in UA.

Sub-hypotheses are:

 Biochar can be used to clean irrigation water from pathogens and becomes a valuable

fertilizer after filtration use.

 Biochar reduces the leaching of nutrients from soil in UA

 Biochar and waste water are improving biological properties of soil in West African

UA.

Therefore, the aim of the thesis is to test the use of biochar in a water filter and analyze its agronomic properties to increase yields. Furthermore, the effects of biochar and waste water on nutrient losses with leaching water were measured with wick lysimeters. Moreover, nutrient balances for an UA field trial were calculated. In addition, the effects of biochar and waste water on soil biological properties, like microbial activity and potential enzyme activities, were examined.

The first chapter gives a brief introduction on tropical soil and UA. It was shown that biochar can have many promising characteristics that may be beneficial in the UA context. Therefore,

in the second chapter biochar was used as a low cost filtration media for waste water treatment. The suitability of biochar filters to reduce pathogen contamination of irrigation water was assessed and the alteration of biochar, especially nutrient contents, in the filter was measured. The agronomic benefit of filterchar (biochar after use in filter) was examined in a greenhouse pot trial.

In chapter 3, the ability of biochar to reduce nutrient leaching from soil in an urban agricultural field trial in Tamale, Ghana was tested. In addition, the effects of fertilizer use and waste water on nutrient leaching were investigated using a multifactorial experimental design. A special emphasis was put on the calculation of nutrient mass balances and the contribution of leaching to the nutrient output of the system.

The aim of chapter 4 is to determine biological soil properties in the Tamale field trial, one year after the start of the experiment and incorporation of biochar into the soil. Therefore, biological soil properties like microbial activity and abundance were measured. Since enzymes in the soil are responsible for the breakdown of organic materials (i.e. organic fertilizer, biochar, particulate substances in waste water, animal manures or composts) and release of nutrients to the plants, the potential activities of selected enzymes important for the soil C, N, P, and S cycles were examined.

In conclusion, the objective of this work is to assess the use of biochar as part of a solution to environmental issues in UA. The suitability of biochar in low cost cleaning of irrigation water and improving crop yields in UA was tested, since no scientific research on biochar in UA is known so far. In addition, the impacts of biochar and waste water irrigation on nutrient leaching and the soil biological health are examined.

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2. Agronomic benefits of biochar as a soil amendment after its use as waste water filtration medium

Authors:

Steffen Werner1, Korbinian Kätzl2, Marc Wichern2, Andreas Buerkert3, Christoph Steiner3* and Bernd Marschner1

1 Ruhr-Universität Bochum, Institute of Geography, Soil Science and Soil Ecology, Universi- tätsstrasse 150, 44801 Bochum, Germany

2 Ruhr-Universität Bochum, Institute of Urban Water Management and Environmental Engi- neering, Universitätsstrasse 150, 44801 Bochum, Germany

3 Universität Kassel, Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics (OPATS), Steinstrasse 19, 37213 Witzenhausen, Germany

* Corresponding authors ([email protected] and [email protected])

Published in Environmental Pollution (2018), 233: 561-568

All authors developed the research idea, concept and gave feedback to the manuscript. KK conducted the filtration experiment. SW conducted the pot experiment, the statistical analysis and wrote the Manuscript.

Abstract

In many water-scarce countries, waste water is used for irrigation which poses a health risk to farmers and consumers. At the same time, it delivers nutrients to the farming systems. In this study, we tested the hypothesis that biochar can be used as a filter medium for waste water treatment to reduce pathogen loads. At the same time, the biochar is becoming enriched with nutrients and therefore can act as a fertilizer for soil amendment. We used biochar as a filter medium for the filtration of raw waste water and compared the agronomic effects of this "filterchar" (FC) and the untreated biochar (BC) in a greenhouse pot trial on spring wheat biomass production on an acidic sandy soil from Niger. The biochar filter showed the same removal of pathogens as a common sand filter (1.4 log units on average). We did not observe a nutrient accumulation in FC compared to untreated BC. Instead, P, Mg and K were reduced during filtration while N content remained unchanged. Nevertheless, higher biomass (Triti- cum L. Spp.) production in BC (+72%) and FC (+37%) treatments (20t ha-1), compared with the unamended control, were found. There were no significant differences in aboveground biomass production between BC and FC. Soil available P content was increased by BC

(+106%) and FC (+52%) application. Besides, mineral nitrogen content was reduced in BC treated soil and to a lesser extent when FC was used. This may be explained by reduced sorption affinity for mineral nitrogen compounds on FC surfaces. Although the nutrients provided by FC decreased, due to leaching in the filter, it still yielded higher biomass than the unamended control.

Introduction

During the next two decades, global population and corresponding food demand are projected to increase rapidly (United Nations Department of Economic and Social Affairs Population

Division 2015). As the cultivated land area can hardly be increased; this will lead to the need for further intensification of agricultural production. However, some agriculture practices; like poor water and nutrient management or shortened fallow periods, are already a major driver of environmental degradation (Tilman et al. 2002, Tilman et al. 2001), such as soil ero- sion and eutrophication of water bodies. Therefore, the development and use of more efficient soil fertility management practices that lead to a closing of nutrient cycles is needed (Tilman et al. 2013).

Biochar, the solid product of pyrolysis, received much attention during the last years for its potential to sequester carbon (C) in soils, to increase soil fertility (Biederman and Harpole

2013, Hussain et al. 2017, Jeffery et al. 2017a), to increase nutrient use efficiency (Steiner et al. 2008b), to reduce nutrient leaching losses (Laird et al. 2010b, Singh et al. 2010) and to immobilize contaminants in soil (Zhang and Ok 2014).

Another possible application of biochar could be its use for waste water treatment and nutrient recovery. Carbon materials are well known for their use in water filtration systems

(Tchobanoglous et al. 2003). Several researchers proposed to use biochar as a sorbent for contaminants, such as organic or inorganic compounds and microbial contamination from water

(Ahmad et al. 2014, Inyang and Dickenson 2015, Mohan et al. 2014, Yavari et al. 2017, Zama et al. 2017). Potential mechanisms are mainly sorption processes to the large surfaces and hy- drophobic interactions. Waste water treatment with biochar focusing on nutrient recovery has received much less attention (Ghezzehei et al. 2014). In many developing countries, urban 19

agriculture substantially contributes to food supply and may cover up to 90% of its perishable vegetable consumption (Drechsel and Dongus 2009). During dry periods, irrigation is common where water is available from open sewage channels. The irrigation with untreated waste water is a serious health risk to the farmer and the consumer (Abaidoo et al. 2010).

A simple sand filtration system can reduce Escherichia coli (E. coli) in wastewater by 2,6 log units and nitrate and phosphate (P) by 22% and 91%, respectively (Langenbach et al. 2009).

In another study, a biochar-sand filter removed up to 3 log units more E.coli from storm water than sand alone (Mohanty et al. 2014). Kätzl et al. (2014) reported the reduction of 2 log units of E.Coli from raw waste water with a slow biochar filter. This reduction can be explained by electrostatical attraction of bacteria to a biological film developing on the surface of the filter material (Stevik et al. 2004).

Only very few attempts have been made to use biochar for nutrient reclamation from waste water, so far. Streubel et al. (2012) tested the removal of P from an anaerobic digest lagoon and captured 1.9 g P kg-1 biochar. Sarkhot et al. (2013) used biochar to recover nutrients from

-1 -1 dairy manure effluent and absorbed 5.3 mg g NH4 and 0.24 g g PO4 from the solution with biochar. Therefore, an enrichment of various nutrients on the biochar is expected. When the enriched biochar would be applied to soil, a release of the nutrients to crops is expected.

Kammann et al. (2015) showed the slow fertilizer behavior and plant growth improvement through nutrients captured in biochar pores during composting.

We hypothesized, a simple biochar filtration system could work as an on-site water treatment system to remove harmful microorganism and thus produce safer water for crop irrigation.

Furthermore, we expected that a nutrient enriched biochar for soil fertility improvement is produced in the filter. Therefore, the objectives of this study were to i) test the retention of 20

pathogens with a slow through flow biochar filter; ii) measure the alteration of biochar properties during filtration and iii) evaluate the agronomic benefits of applied filterchar on crop yield and nutrient supply in a greenhouse pot trail.

Materials and Methods

Biochar production and waste water filtration

Biochar was produced from rice husks in a batch type custom made kiln at Kwame Nkrumah

University of Science and Technology (KNUST) in Kumasi, Ghana. We chose this feedstock since it is a waste material in Ghana and unlike wood there is no risk of fostering deforesta- tion. The feedstock was heated to a temperature of approximately 450°C under oxygen limited conditions. After pyrolysis, the biochar was quenched with water to avoid burning after removal from the kiln and subsequently air dried.

The detailed experimental setup of the slow filters was identical to our previous experiment

(Kätzl et al. 2014). Biochar was compared with sand as a commonly used filter material. As a water source we used pre-treated effluents of the grit chamber of a municipal waste water treatment plant (Ölbachtal, Bochum, Germany). The water was pre-treated with an anaerobic roughing filter to remove suspended solids and turbidity.

The beds of the biochar and sand filters were established in triplicates, had a depth of 55 cm and were covered by a 5 cm quartz sand layer, to prevent floating of the light biochar. The hydraulic loading rate of the slow biochar filters was adjusted to 50 mm h-1 and the run time of the filters was three months.

Samples for microbiological analysis of the fecal indicator bacteria (FIB) E. coli and intestinal enterococci were collected once per week and analyzed within 24 h, using standardized mi- croplates (Bio-Rad Laboratories GmbH, Munich, Germany) for determination of the most probable number (MPN) of bacteria (DIN EN ISO 7899-1 2000, DIN EN ISO 9308-3 1999).

Additionally, samples for physico-chemical analyses were taken and stored at – 20 °C for determination of chemical oxygen demand (COD), total nitrogen (Ntot) and total phosphorous

(Ptot). At each sampling interval ancillary data of pH, electrical conductivity (EC), redox potential and turbidity were also collected. Average characteristics of pre-treated wastewater used as the influent of the biofilters are given in Table 2.

Table 2-1: Mean characteristics of the waste water used as influent in the filtration experiment ± one standard deviation, n=9. The analyzed water samples were collected throughout the whole experimental period of 3 months. COD = Chemical oxygen demand; MPN = Most probable number; NTU = Nephelometric turbidity unit.

Parameter Unit Mean ± SD pH [-] 8.2 ± 0.24 EC [µS cm-1] 1005 ± 124 E. coli 4.87 ± 0.89 [log MPN 100ml-1 ] Enterococci 4.62 ± 0.98 COD 55 ± 41.7 -1 Ntot [mg l ] 57 ± 10.5

Ptot 2.24 ± 0.3 Turbidity [NTU] 11 ± 7.2

Experimental design of the pot experiment

A pot experiment was carried out in the greenhouse (Witzenhausen, Germany) to assess biochar and filterchar effects on plant growth and soil properties. The surface soil (0-20 cm) was taken from a Psammentic Paleustalf (Arenosol; FAO-WRB) in Sadoré, Republic of Niger

(13° 14´ N, 2° 17´ E). Texture was a sandy loam (FAO 2006) with 7 % clay, 22 % silt and 68

-1 % sand. The soil had 0.2 % Corg, 0.03 % nitrogen (N), P Bray 1 of 2.51 mg kg and a pH of

5.5. The soil was mixed with biochar or filterchar at a rate of 20 Mg ha-1 (7.14 g kg-1 soil) as- suming an incorporation depth of 20 cm and a mean bulk density of 1.4 g cm-³. Unamended soil was used as a control. The pots had a size of 9 x 9 x 9.5 cm (length x width x height) and were filled with two kg of soil or soil-biochar mixture.

Five seeds of spring wheat (Triticum L. Spp.) were planted in each pot. Both amended soils and the unamended control were tested with and without fertilizer addition of 85 mL from a

1.5 % fertilizer solution (8 % N, 8 % P2O5, 6 % K2O; Wuxal Universaldünger, Manna GmbH,

Düsseldorf, Germany). All treatments were replicated five times and their locations on the greenhouse table were completely randomized. The plants were harvested after eight weeks and their fresh weight was recorded. Subsequently, the samples were dried at 60 °C to con- stant weight for determination of dry weight and further analysis.

Analysis of biochar, plant and soil samples

The pH and electrical conductivity (EC) of bio- and filterchar were determined according to

Rajkovich et al. (2011). Briefly, 1 g of the materials was mixed with 20 mL deionized water and shaken on a horizontal shaker for 1.5 h. Readings were taken in supernatant with a gel electrode and a conductivity cell (Sentix 41 and TetraCon 325, Wissenschaftlich-Technische

Werkstätten (WTW) GmbH, Weilheim, Germany), respectively. The pH of soil was assessed using a 1:5 ratio of soil and 0.01 M CaCl2 solution. Ash and volatile matter of both materials were measured according to ASTM D1762-84 Rajkovich et al. (2011). To determine volatile matter by weight difference, a 1 g sample of the material was placed in a crucible covered with a lid in an oven at 950 °C for ten minutes. To measure the ash content, the sample was placed in the oven at 750 °C for six hours in an open crucible and subsequently weighed after cooling in a desiccator. For determination of biochar surface area a BET multipoint adsorption isotherm with N2 as adsorbent was prepared in a surface analyzer at 77 K (Autosorb 6,

Quantachrome Instruments, Boynton Beach, FL, USA).

Biochar and plant N and C concentrations were measured by combustion in an elemental analyzer (Vario max cube, Elementar Analysesysteme GmbH, Hanau, Germany). Total Ca, Fe,

K, Mg, and P in biochar and plant samples were measured after microwave digestion with nitric acid in teflon tubes and subsequently elements were determined with an ICP-OES (Ci- ros CCD, SPECTRO Analytical Instruments GmbH, Kleve, Germany). The particle size distribution of the soil sample was assessed with a laser scattering method (Analysette 22;

Fritsch GmbH, Idar-Oberstein, Germany; Stumpe et al. (2011)).

Mineral N content and plant available P were determined after the harvest. For soil mineral N determination, the air-dry soil was pre-incubated at 60 % water holding capacity (WHC) for seven days in a refrigerator at 4°C. WHC was measured by adding 20 g of dry soil in a pre- weight funnel with moist filter paper. Soil was saturated with water and weighed after letting the water drain out of the soil by gravity. Afterwards, WHC was calculated by differences of weights. After incubation, 10 g of the soil was mixed with 100 mL of 0.01M K2SO4 and shaken for one hour to extract the mineral N compounds. Subsequently, nitrate (NO3) anions were

measured with an ion chromatograph (881 Compact IC Pro, Metrohm AG, Herisau, Switzer- land) and ammonium (NH4) cations were determined photometrically with sodium dichloroi- socyanurate and sodium salicylate (DIN 38406-E5-1 1985) in a Lambda 2 spectrophotometer

(Perkin Elmer Inc., Waltham, MA, USA). Available P in the soil was extracted by Bray 1 method from air-dried soil with an acid fluoride extractant in a 1:7 soil:solution ratio (w:vol;

(Bray and Kurtz 1945)). Orthophosphates in the solutions were determined by using the mo- lybdenum blue method (Murphy and Riley 1962).

Statistical analysis and calculations

All statistical tests were conducted with SPSS software version 22 (IBM, Armonk, New York,

USA). The data were tested for normality with the Kolmogorov-Smirnov test at p < 0.05.

Mineral N content and crop nutrient uptake data was normalized by root or square transfor- mations, respectively. Significant differences of means between biochar and filterchar properties were identified using a t-test (p < 0.05). Data from the pot experiment was analyzed by analysis of variance (ANOVA) and the Tukey test (p < 0.05) was used for post-hoc comparison. Because of lacking normality of data residuals between fertilization groups, a non- parametric Mann-Whitney U test was used to compare results of fertilized and unfertilized treatment groups. Another U test was employed to compare FIB removal between sand and biochar filters. In addition, partial N, P and K balances for all treatments were calculated by subtracting the elemental nutrient input (i.e. in biochar and fertilizer) from the total crop uptake.

Results

Pathogen removal from irrigation water

The mean removal rates of FIB in biochar filters over the entire experiment were 1.4 log10- units for both, E. coli and enterococci. In comparison, sand filters removed on average 1.2 log10-units of E. coli and 1.4 log10-units of enterococci. However, E. coli removal was only significantly higher in biochar filters on day 57 compared to the sand filters (Fig. 1).

5 6 5 8

]

Sand * Sand -1

]

-1 Biochar Biochar

-1 Influent 5 ] 4 -1 4 Influent 6 4 3 3

3 4

2 2

in influent [log MPN 100ml [log influent MPN in

elimination [log MPN 100ml [log MPN elimination 2

elimination [log MPN 100ml [log MPN elimination 2 1 1

1 E.coli

concentration in Influent [log MPN 100ml Influent in concentration [log MPN

Enterococci

E.coli 0 0 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Duration of Experiment [d] Duration of experiment [d]

Figure 2-1: Elimination of E.coli and Enterococci in water after filtration and influent concentrations. Error bars show ± one standard deviation and asterisk indicate significant difference between sand and biochar filter effluent (Whitney-Mann U-Test, p<0.05, n=3).

For enterococci no significant differences between biochar and sand filters were found. Meas- ured redox potential of filter influent and effluent was below – 300 mV and indicated strict anaerobic conditions in the filter columns. Therefore, N and P removal from wastewater is 26

mainly driven by incorporation in microbial biomass, but no removal could be measured. No significant change of pH and EC between influent and effluent was observed for both materials.

Biochar properties and alterations after filtration use

The rice husk biochar had an initial pH of 9.1 and an electrical conductivity of 21.7 mS m-1

(Tab. 2). The N and Corg contents were 0.78 % and 41.8 %, respectively. The use of biochar in the water filtration system reduced the pH and EC to 7.4 and 10.0 mS m-1, respectively. In addition, the K, Mg and P concentrations were reduced while the Ca concentration increased in the filterchar. All other biochar properties remained unchanged after filtration use.

Table 2-2: Properties of biochar before and after filtration ± one standard deviation, n=3. Letters indicate significant differences of means (t-test, p<0.05).

Biochar Filterchar pH [-] 9.08 a 7.41 b EC [mS m-1] 21.73 a 9.97 b Volatile matter 8.76 ±0.42 a 8.69 ±0.57 a Ash 52.27±0.77 a 52.12±1.31 a [%] N 0.78 ±0.03 a 0.80 ±0.06 a C 41.82 ±0.86 a 41.18 ±2.84 a Al 1.27 ±0.20 a 1.32 ±0.36 a Ca 1.78 ±0.11 b 3.27 ±0.24 a Fe 1.06 ±0.25 a 0.98 ±0.22 a K[g kg-1] 4.08±0.72 a 0.73±0.08 b Mg 1.26 ±0.11 a 0.82 ±0.04 b Na 0.65 ±0.05 a 0.66 ±0.08 a P 1.22±0.12 a 0.63±0.12 b BET Surface area [m2 g-1] 143.03 145.10

Plant growth, nutrient uptake and soil pH

Total biomass production in the pots treated with biochar or filterchar were significantly higher than in the respective unfertilized controls (72 % and 37 % increase, respectively) and fertilized controls (37 % and 23 % increase, respectively; Fig. 2). The difference between bio- 27

char and filterchar treatments and the control was smaller with fertilizer use, but still significant. Fertilization increased biomass yields. However, biochar addition without fertilization was equally effective as fertilization without biochar.

]

-1 a 4 ab

bc bc 3 c d

Total biomass production pot [g DM

Control biochar Filterchar

Control + NPK Biochar + NPK Filterchar + NPK

Figure 2-2: Total biomass production at the end of the experiment. Letters indicate significant differences of mean (ANOVA, p<0.05) and error bars ± one standard deviation

(n=5).

Tissue N concentration was higher in the control plants than in those of the FC and BC treatments without fertilization (Tab. 3). In the fertilized treatment group, the control also showed the highest N concentrations, while FC was higher than BC. Foliar P concentration was highest in BC and no differences could be observed between control and FC.

Table 2-3: Mean nutrient concentrations in biomass, pH of soil and standard deviation

(SD). Letters indicate significant differences (ANOVA, p<0.05, n=5) within a fertilizer group. Differences between groups were assessed with Whitney-Mann U test.

pH N Ca Mg K Fe P mean SD mean SD [g kg-1] no fertilizer Control 6.18 0.13 a 24.2 2.2 a 7.15 0.3 ab 4.63 0.32 a 15.31 0.42 a 0.11 0.02 a 1.11 0.12 b Biochar 6.11 0.11 a 19.2 1.3 b 6.43 0.69 b 4.34 0.31 a 14.76 1.32 a 0.09 0.04 a 1.46 0.11 a Filterchar 6.05 0.15 a 21.1 0.7 b 7.98 0.67 ab 4.76 0.34 a 13.64 0.83 a 0.11 0.03 a 1.18 0.08 b

with fertilizer Control 5.98 0.18 a 36.3 0.8 a 9.39 0.94 ab 5.36 0.41 a 15.51 0.15 a 0.12 0.04 a 4.32 0.32 a Biochar 5.79 0.67 a 30.9 2.2 c 7.37 1.53 b 4.75 0.56 a 16.26 0.68 a 0.11 0.02 a 4.51 0.89 a Filterchar 5.95 0.11 a 33.5 0.6 b 8.83 0.78 ab 5.33 0.43 a 14.71 0.38 b 0.11 0.03 a 4.29 0.31 a

U-test p= 0.105 0.000 0.003 0.004 0.041 0.561 0.000

When fertilizer was applied, the foliar P, Ca, Mg and Fe concentrations did not differ between the treatments. Plants from the FC treatment showed lower foliar K concentrations compared with the other treatments. The pH value remained unchanged by the addition of biochar or filterchar. The application of fertilizer reduced soil pH slightly but was found not to be significant (Tab.3).

Available N and P in soil after the experiment

The extractable mineral N (Nmin = NO3-N + NH4-N) analyzed in the soils after the experiment was highest in the untreated control soil (Fig. 3). In the unfertilized pots, biochar treatments had the lowest Nmin concentrations. The addition of FC resulted in an intermediate Nmin content. In the fertilized soil group, the control had the same Nmin as FC, but was significantly reduced in BC.

The Bray 1 extractable P concentrations were increased significantly by biochar in the unfertilized treatments and by both BC and FC in the fertilized treatments (Fig.4). The lowest P content was found in the untreated control soil. 29

16 16 a a 14 14

12 12 b

10 10 b c

8 b 8 c bc 6 6 d cd 4 d d 4

Nmin (NH4-N+NO3-N) [mg/kg DM] [mg/kg (NH4-N+NO3-N) Nmin 2 [mg/kg] PO4-P I extractable Bray 2

0 0

Control biochar Filterchar Control biochar Filterchar Control + NPK Biochar + NPK Filterchar + NPK Control + NPK Biochar + NPK Filterchar + NPK

Figure 2-3 and 2-4: Left: Mineral nitrogen content in soil after the experiment. Right:

Bray 1 extractable PO4-P in soil after the experiment. Letters indicate significant differences of mean (ANOVA, p<0.05) and error bars show standard deviation (n=5)

N, P and K balances

After harvest, N balances were positive for BC (20 mg N pot-1) and FC (10 mg N pot-1) treatments, but negative for the control (-2 mg N pot-1) in the unfertilized group (Tab. 4). When fertilizer was applied, all N-balances were positive and showed the same pattern as the unfertilized treatment group. More P remained in the soils with FC than in soils with BC. The K balances were only positive in the BC treatments.

Table 2-4: Nutrient input, output and balances of the different treatments in the pot trial. Input = nutrients in biochar + fertilizer; Output = total plant uptake.

Input Output Balance [mg pot-1] N no fertilizer Control 0 40 -40 Biochar 156 60 96 Filterchar 160 50 110

with fertilizer Control 102 100 2 Biochar 258 110 148 Filterchar 262 110 152 P no fertilizer Control 0 2 -2 Biochar 24 4 20 Filterchar 13 3 10

with fertilizer Control 449 12 437 Biochar 473 16 457 Filterchar 461 14 447 K no fertilizer Control 0 30 -30 Biochar 82 43 39 Filterchar 15 32 -17

with fertilizer Control 32 41 -9 Biochar 114 60 54 Filterchar 47 48 -1

Discussion

Filter efficiency and alterations of biochar

In comparison with commonly used sand as filter material, removal rates of FIB were slightly higher in BC filters. This can be explained by deeper formation of a biological active film in the biochar filter as reported by Kätzl et al. (2014). Overall, removal rates of FIB are in the same order of magnitude as reported in previous studies (Ellis 1987, Kätzl et al. 2014). A strong effect of BC on removal of FIB, as reported by Mohanty et. al (2014) or Lau et al.

(2017) for storm water, was not observed. Nevertheless, BC seems to be a suitable material 31

for biofiltration, since it showed similar FIB removal. It can be produced locally with inex- pensive methods and used as soil amendment after filtration. Since FC is likely carrying active pathogens, there is a need to control the further fate of these pathogens in the soil system.

Simple methods like sun drying and composting might be used to reduce the pathogens in FC.

There is a clear need to further evaluate this aspect, but this was not the scope of this research.

BC properties can vary widely depending on the type of feedstock and production temperature but our results of C and N content and pH value are similar to data published from the

UK Biochar Research Center (2014) for rice husk biochar produced at a slightly higher temperature of 550°C.

One of the hypotheses of this study was that BC can be loaded with nutrients by filtering waste water. When comparing the BC properties before and after filtration, we observed no increase in N content. Other element contents were even reduced: P by 48.4%, K by 82.11% and Mg by 34.92% or 0.59, 3.35 and 0.44 mg g-1, respectively. Results for P retention on BC reported elsewhere are inconsistent. For instance, Sarkhot et al. (2013) found an 0.24 mg P g-1 increase of total P after filtration of dairy effluent with BC. Streubel et al. (2012) reported an increase of 1.9 mg P g-1 BC after filtering an anaerobic digester effluent. In addition, Morales et al. (2013) and Chintala (2014) removed P from nutrient solution with BC. Other studies concluded that BC had no affinity or low ability to sorb P (Soinne et al. 2014, Xu et al. 2014,

Yao et al. 2012). Angst and Sohi (2012) showed the release of P from BC. However, it seems that P retention by BC is strongly related to BC properties and the nature of the waste water.

The same conclusion probably holds true for the data of Yao et al. (2012) and Hollister et al.

(2013) who reported low or no ability of BC to sorb NH4 or NO3 from solution. In contrast,

-1 Sarkhot et al. (2013) loaded BC with 5.3 mg NH4 g BC from diary effluent. In the same

study, basic cations leached and the pH value dropped during the filtration, as shown in our study.

The surface area of biochar did not change during the filtration. In general, both decrease and increase could be possible. Either the pores could be clogged with organic matter, such as a biofilm, or an increase of surface area through the removal of mineral ash components from the biochar pores could be expected. For example, Heitkoetter and Marschner (2015) reported an increased surface area for biochar aged in soil while Pignatello et al. (2006) found a decreased surface area after treating biochar with humic substances.

Effects on plant growth and soil nutrient uptake

Much work has already been done to demonstrate the effects of BC on plant productivity and crop yield. Jeffery et al. (2017a) reviewed data on this issue with a meta-analysis and found a mean increase in crop productivity by 25% in the tropics. In another meta-analysis from

Biedermann and Harpole (2013), the authors reviewed 371 studies and confirmed the higher mean above-ground productivity. Other studies with rice husk biochar found increases in crop yields for rice, lentil, spinach, cabbage, maize and lettuce (Abrishamkesh et al. 2015, Carter et al. 2013, Haefele et al. 2011, Nguyen et al. 2012, Sarkhot et al. 2013, Varela Milla et al.

2013). Our results also showed an increase in crop yield for BC and FC treatments compared with the control. This increase is higher in the unfertilized treatments than in the treatment group with fertilizer. Similarly, Carter et al. (2013) found the largest biomass increase in unfertilized soil (903%) while the fertilized soils showed a lower increase (403%). BC provided

P and K which also explains why FC treatments had a lower yield than biochar treated soil.

During the filtration, P, Mg and K were washed out from the biochar and therefore lead to lower biomass production. 33

This is also reflected in the nutrient uptake data. Increases in P uptake with rice husk BC has also been reported by Nguyen et al. (2012), which is in line with the plant available P in the experiment. BC clearly increased the available P compared with filterchar or control and P was most likely limiting plant growth. This is also confirmed by a correlation analysis. Pear- son correlation coefficients showed high correlation of biomass production with tissue P concentrations (R = 0.647; p<0.01). In addition, available P was positively correlated while mineral N content in soil after harvest was negatively correlated with biomass production. This clearly shows that P was the limiting factor for plant growth. In contrast, Abrishkamesh et al.

(2015) found a lower available P concentration after biochar addition, which was attributed to precipitation reactions caused by the alkaline pH. In our experiment, the addition of biochar or filterchar had no effect on soil pH. The applied amount was obviously too low to have any effect.

Besides the positive effects of the treatment materials on plant growth and P uptake, the mineral N concentrations in soil were reduced in both biochar treatments compared with the control. In the study of Sarkhot et al. (2013) extractable Nmin was decreased if soil was amended with biochar and biochar enriched with dairy effluent as compared with the control. They explained this effect with decreased net N mineralization.

Generally, biochar effects on N immobilization and crop uptake are inconsistent in the literature as reviewed by Clough et al. (2013). These authors concluded that alterations of N dynamics by biochar are strongly related to specific soil and biochar combinations. Our results indicate that BC and FC are able to immobilize N in soil and make it at least partly unavaila- ble for plant uptake. The pre-treatment of biochar in a water filter reduces this effect, most likely through already occupied sorption sites.

Calculations of nutrient balances are useful to evaluate the sustainability of agricultural production systems but can also show limitations of crops to utilize nutrients from soil. BC treated soil had the most positive N balance, which means that the soil is accumulating N after the cropping cycle. This may be attributed to N immobilization, either through growing microbial biomass or due to sorption of organic or inorganic N compounds to the biochar surface, as found by different researchers (Clough et al. 2013, Steiner et al. 2008a, Zhang et al. 2014).

This may be desirable as long as crop yields are not decreased, as it was the case in our study.

When comparing the P balances, the highest residual P was found in the FC treatment although untreated biochar had the highest P content and thus the highest P input. In addition, biochar contributes to a positive K balance with its high K content.

Conclusions

This study showed similar pathogen retention of the slow biochar filter compared with sand filter media. An enrichment of biochar with nutrients during filtration was not observed but as long as the filtered water is used for irrigation the reduction of the biochar’s nutrient content during the filtration would be irrelevant. Instead, the relatively nutrient rich rice husk biochar lost nutrients during filtration. Filterchar application to soil leads to an increase in crop production compared with the untreated soil but did not show significant differences to the untreated biochar treatment. BC provided more readily available nutrients than FC, but reduced

N availability to a greater extent than FC.

The nutrient content in the waste water used for our study was probably not high enough to enrich FC with nutrients as shown in other studies. In addition, the properties of biochar are likely influencing adsorption of nutrients. The N immobilization needs further investigation.

Overall, biochar filtration of wastewater can be a good strategy to reduce pathogen loads, im- 35

prove crop yields and therefore contribute to food security and safety. However, using biochar for wastewater filtration does not increase its nutrient content compared to the fresh BC.

Acknowledgements

We are thankful for financial support by the BMBF founded Project UrbanFoodPlus under the initiative GlobE – Research for the Global Food Supply, grant number 031A242-B, -A. We also thank our colleague Kofi Atiah for provision of Biochar. Rainer Braukmann provided valuable assistance in the greenhouse. We are grateful for the support in the laboratory and thank Sabine Frölich, Katja Gonschorek, Heidrun Kerkhoff and Bettina Röhm from the Ruhr-

University of Bochum (Germany).

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3. Nutrient leaching and balances in urban agriculture in Northern Ghana: effects of waste water irrigation, mineral fertilization and biochar application.

Authors:

Steffen Werner1, Edmund Akoto-Danso2, Delphine Manka’busi2, Christoph Steiner2, Volker Haering1, George Nyarko3, Andreas Buerkert2 and Bernd Marschner1

1 Ruhr-Universität Bochum, Institute of Geography, Soil Science and Soil Ecology, Universi- tätsstrasse 150, D-44801 Bochum, Germany

2 Universität Kassel, Organic Plant Production and Agroecosystems Research in the Tropics and Subtropics (OPATS), Steinstrasse 19, D-37213 Witzenhausen, Germany

3 Faculty of Agriculture, University for Development Studies, Tamale, Ghana

*corresponding author ([email protected])

Submitted to Nutrient Cycling in Agroecosystems, Special issue: Urban agriculture

All authors contributed to the idea and concept of the field experiment and gave feedback on the manuscript. S.W., E. A.-K. and D.M. conducted the field work. In particular S.W. undertook the lysimeter study, statistical analysis and wrote the manuscript.

Abstract

Urban agriculture (UA) in developing countries may contribute to food diversity and security of the urban population. The importance of this contribution will increase in the future because of the fast growing urbanization especially in Sub-Saharan Africa. Little is known about nutrient fluxes and balances of these high input agricultural systems which are characterized by high fertilizer use, often combined with waste water irrigation. Adding biochar to soil has shown the potential to decrease nutrient leaching, increase yields and nutrient use efficiency.

Therefore, lysimeters were installed in a multi-factorial field experimental in Tamale, North- ern Ghana. The treatments with four replicates each included a control (without amendments), biochar at 20 t ha-1 (BC), mineral fertilization according to the normal farmers’ practice

(NAP) and a combination of BC+NAP. All treatments were either irrigated with tap water

(TW) or with waste water (WW). The results show generally lower water use efficiency (47-

82 %) and higher unproductive water losses under WW irrigation, most likely due to soil water repellency and resulting higher pore water velocity. Addition of biochar had no effects on nutrient leaching, balances and water flux. Waste water contributes significantly to the nutrient input and also induced higher leaching losses. Leaching losses of nitrogen (N) were around 200 kg N ha-1 season-1 when irrigation highly exceeded the demands. When irrigation was more appropriate the leaching rates were around 50-100 kg N ha-1. Strong increase of Mg and Ca leaching and negative mass balances under mineral fertilization is promoting soil acidification. Nutrient balances for N were found to be positive or negative depending on the season. While phosphorus (P) balances were always positive due to P immobilization, Potassium

(K), magnesium (Mg) and calcium (Ca) balances were always negative.

Introduction

Globally, 5.9 % of all crop land is located in urban areas (Thebo et al. 2014) and often substantially contributes to the food supply of urban populations, as shown for Kumasi, Ghana where urban agriculture (UA) produces 60-90 % of all perishable vegetables consumed in the city (Obuobie et al. 2006). Due to the relatively high revenues that can be achieved from these crops by the producers, year-round production with poorly adapted fertilizer inputs and irrigation with waste water from open channels are a common practice in many developing countries. For example, Lydecker and Drechsel (2010) estimated that from the 80 Mio l of waste water generated daily in Accra, Ghana, 11.3 Mio l are used for vegetable production.

As shown with national nutrient balances by Stoorvogel and Smaling (1990), crop production in rural Africa is often associated with nutrient mining resulting in negative soil nutrient balances. Cobo et al. (2010) reviewed 57 studies on the subject and found that more than 75 % of the field based studies reported negative nutrient balances (less nutrient input than output) for nitrogen (N) and potassium (K) and 57 % for phosphorus (P). In contrast, the few studies that examined nutrient dynamics in African UA show a very different picture. Sangare et al.

(2012) found that the annual nutrient supply in UA in Bobo Dioulasso, Burkina Faso exceeded crop demand by up to 2,012 kg ha-1 for N, 450 kg ha-1 for P and 393 kg ha-1 for K. Similar results were reported by Lompo et al. (2012), who found surpluses in annual partial balances

(partial balance = Nutrient inputs (Fertilizer and waste water) - crop uptake) in two urban gardens of 2056 and 1752 kg N ha-1, 615 and 446 kg P ha-1 and 1864 and 1643 kg K ha-1. Be- sides, Graefe et al. (2008) reported positive partial annual balances of up to 7312 kg N ha-1,

530 kg P ha-1 and 6827 kg K ha-1 in urban gardens of Niamey, Niger. In the same study, these authors also reported figures for rural millet fields being as low as -39 kg N ha-1, -9 kg P ha-1

and -33 kg K ha-1 per year. This underlines the differences between low input rural farming and very high input urban farming systems.

Such high surplus nutrient inputs have to be considered questionable in terms of fertilizer costs and unproductive gaseous or leaching losses of plant nutrients. The latter have rarely been examined in UA, so far. In one of the few studies, Predotova et al. (2011) estimated nutrient leaching in urban gardens of Niamey, Niger with ion exchange resins and found an on only negligible loss of up to 7.3 kg N ha-1 and 0.7 kg P ha-1. However, these data were collected in year with unusually low rainfall.

Since high nutrient losses are often related to the commonly low effective cation exchange capacities of Sub-Saharan African soils (Bationo et al. 1998) losses could be reduced by adding organic amendments, such as manures or composts (Gonçalves et al. 2007). But this may only be a short-term effect due to the high mineralization rates of organic materials under tropical conditions. More recently, the use of biochar (BC) has been proposed as a soil amendment to increase sorption capacities and thus reduce the leaching of nutrients from the soil (Biederman and Harpole 2013, Steiner et al. 2008b). BC can be produced from wood and organic wastes through heating in the absence of oxygen. Several efforts have been made to reduce nutrient leaching form soil with the addition of biochar. In a laboratory study, for example, Laird et al. (2010a) found a reduction of N, P and Mg leaching with biochar application to a soil fertilized with pig manure. Pereira et al. (2017) conducted a pot experiment in a greenhouse with biochar derived from pine chip and walnut shell. They found a decrease of N losses from the pots with leachate for pine chips biochar but not for walnut shell biochar. In another greenhouse experiment Borchard et al. (2012) observed an enhanced nitrate leaching by 41 % in a sandy soil and a decreased nitrate leaching by 17 % in a loamy soil with the

same biochar made from beech wood. These findings revealed that the impact of biochar on nutrient leaching from soil depend on the kind of biochar and soil type used.

We hypothesize a strong leaching of nutrients especially during rainy seasons as a conse- quence of waste water and fertilizer use. Biochar is expected to decrease nutrient losses via leaching and facilitate a more productive resource use. Therefore, the aims of this study were to (i) quantify the contribution of waste water to the total seasonal nutrient input, (ii) measure the extent of nutrient leaching in UA in a field study, (iii) determine the effect of waste water irrigation and biochar on nutrient loads in leaching water and (iv) calculate nutrient balances for major nutrients (N, P, K) and (v) asses the contribution of nutrient leaching to the total output of the system. For this purpose, we monitored water and nutrient fluxes with seepage water with lysimeters installed in an experimental UA field trial in Tamale, northern Ghana for two years or four consecutive climatic seasons.

Materials and methods

Field experiment set-up and biochar production

The field experiment was installed in the city of Tamale, northern Ghana in the semi-arid climate of the Guinea Savanna. Tamale has a long term mean annual rainfall of 1090 mm and a daily mean temperature of 27.9°C (DWD 2017). The soil type at the location is a Petroplin- thic Cambisol with a loamy silt texture (45.7 % sand, 47 % silt and 5.9 % clay) according to

WRB (FAO 2014) classification (Häring et al. 2017). Initial soil properties at 0 to 20 cm are

-3 0.41 % total C, 0.04 % total N, pH of 5.1 (in CaCl2), bulk density of 1.42 g cm and an effec-

-1 tive cation exchange capacity of 36.1 mmolc kg . Details about soil parameter and methods of measurement can be found in Häring et al. (2017). The treatments used in our study were:

Control (CON; without any treatment), a treatment fertilized according to normal agricultural practice of the local farmers (NAP), a biochar treatment (BC) with 20 t rice husk biochar ha-1 and a biochar with fertilization according to NAP (BCNAP) treatment. The quality of irrigation water was used as an additional factor, apart from fertilization and biochar application. the waste water effluent form a military base and tap water was used for irrigation. In order to avoid irrigation errors (wrong water quality) the plots with same irrigation were merged to main plots. Subplots with different biochar application and fertilization were randomly allo- cated inside the main plots.

The crops grown on the experimental field comprised in the first (rainy) season (April 2014-

September 2014, Wet 1), maize (Zea mays L.) (only four weeks), lettuce (Lactuca sativa L.) and cabbage (Brassica oleracea L.). In the second (dry) season (October 2014 – March 2015,

Dry 1), amaranth (Amaranthus cruentus L.), lettuce and again amaranth were grown. During the third (rainy) season (April 2015 – September 2015, Wet 2) nalta jute (Corchorus olitorius

L.) (two times), amaranth and again nalta jute were planted. During the last (dry) season (Oc- tober 2015 - March 2016, Dry 2), crops were roselle (Hibiscus sabdariffa L.), lettuce and car- rots (Daucus carota L.).

Fertilization was done with NPK 15-15-15 at rates of 200-563 kg ha-1 per crop except for two crop cycles of nalta jute in Wet 2 when urea was used at 247 and 256 kg ha-1.

The biochar used in this experiment was prepared from rice husks collected from waste heaps of a local rice mill in a custom made kiln at KNUST, Kumasi, Ghana. Highest treatment temperature was about 550 °C. Rice husk was chosen as feedstock material since it is an abundant waste product without alternative use in Ghana. The rice husk biochar had a total C content of

42.4 %, 0.4 % total N, a pH of 9.1 (in water) and 62.89 m² g-1 BET surface area. Further in- 50

formation and details about measurement procedures can be found in Atijah et al. (2017). Bi- ochar has been incorporated into the soil to a depth of 20 cm with manual ploughing using traditional hoes.

Lysimeters

In order to measure percolation rates and nutrient leaching passive wick lysimeters (Fig. 1) was constructed from PVC pipes with an inner diameter of 28 cm, adapted from descriptions of similar instruments in other studies (Brown et al. 1989, Holder et al. 1991, Siemens and

Kaupenjohann 2004). The lysimeters were filled with undisturbed soil cores taken to a depth of 40 cm. At the bottom of the cores, glass fiber wicks (Thermo E Glasstrickschnur ST1,

H.K.O. Oberhausen, Germany) of 40 cm length and 10 mm in diameter were installed to cre- ate a hanging water column and draw water from the soil.

Figure 3-1: Schematic sketch of the wick-lysimeter used in this study.

The leachate was collected in a bucket and extracted through a PVC tube at the sampling dates. In total, 36 such lysimeter were installed in the 2 x 4 m experimental plots of the field 51

experiment and received the same treatment (irrigation, fertilization, management) as the rest of the plot. The leachate was sampled weekly apart from times when no rain or irrigation took place. The amount of leachate was measured and a sample transported to the lab in an ice box.

All samples were acidified after pH and EC measurement and stored in a fridge until further analysis. Rain, tap and waste water were sampled weekly (when available or when used for irrigation) and treated similarly. Replication of the treatments was done in four blocks.

Water analysis

In all leachate, irrigation water and rain samples, pH (pH meter basic 20, Crison Instruments

S.A., Barcelona, Spain) and electrical conductivity (conductivity meter basic 20, Crison In- struments S.A., Barcelona, Spain) were recorded immediately after sampling. NO3-N

(Cataldo et al. 1975), NH4-N (Koroleff 1976) and PO4-P (Ohno and Zibilske 1991) were measured photometrically. Light absorption at the specific wavelengths was measured with an

UV/VIS spectrophotometer (Pharo 300 Spectroquant, Merck GmbH, Darmstadt, Germany).

Total amounts of K, Mg and Ca were determined in the acidified samples after transport to

Germany using an ICP-OES (Ciros CCD, SPECTRO Analytical Instruments GmbH, Kleve,

Germany). Details about measurement of nutrient concentrations in crops are reported in

Akoto-Danso et al. (2018)

Statistical data analysis and calculations

Testing of treatment effects on seasonal leachate volumes, cumulative element leaching and seasonal element balances were conducted using a mixed effects model in the package nlme of R software (R Development Core Team 2008) to account for the incomplete randomiza- tion. The fixed effects used in the analyses were irrigation water quality, fertilization and bio-

char application. In addition, we checked for statistically significant interactions between the factors. The full models were simplified stepwise until only significant factors (p ≤ 0.05) remained. We checked for normality (Shapiro-Wilk test) and heteroscedasticity in the data. If necessary, data were transformed by methods shown in the p-value tables (Supplementary material).. The calculation of nutrient balances was done by subtracting the outputs (nutrient leaching and crop uptake) from the inputs (from irrigation, rain and fertilization). Gaseous emissions of nitrogen have not been taken into account. Due to a lack of data for crop uptake of Na this was not incorporated in the balances. Furthermore, the Pearson correlation coeffi- cient was used to determine relationships between leaching components.

Results

Rainfall and irrigation amounts

During the first wet season rainfall was 614 mm and irrigation 743 mm, resulting in total water input of 1357 mm (Table 1). In the following dry season we recorded 48 mm of rainfall and 850 mm irrigation, amounting to a total input of 898 mm. The following wet season

(Wet3) was rather dry with only 409 mm rainfall and only 408 mm of irrigation water was applied, amounting to a total input of 817 mm. In the last dry season, 140 and 1046 mm of rain and irrigation water were recorded, respectively, yielding total water input of 1186 mm.

Nutrient inputs with rainfall, irrigation water and fertilizer application

Mean pH values for waste water were slightly higher in the wet seasons (8.15 and 7.46) compared to the dry seasons (7.31 and 7.13; Tab. 1). The same pattern was observed for clean water with pH values from 7.1 to 8.1.

Table 3-1: Seasonal water and nutrient inputs into the multi-factorial field experiment in Tamale, northern Ghana.

water input Waste water Clean water rainfall irrigation total pH EC NPK Mg Ca Na pH EC NPK Mg Ca Na [mm] [mm] [mm] [-] [mS/cm] [kg/ha] [-] [mS/cm] [kg/ha] Wet season 14 614,2 742,5 1356,7 8,15 405,32 103,06 15,98 25,81 39,83 146,49 114,72 7,35 190,55 1,88 0,07 7,67 17,33 69,60 15,34 Dry seaon 14/15 47,7 849,8 897,5 7,31 563,33 259,67 94,82 36,47 49,42 221,18 160,54 7,10 104,57 5,86 0,38 9,51 22,10 84,05 18,36 Wet season 15 408,5 408,5 817 7,46 511,25 195,47 30,06 20,89 25,77 117,08 75,68 8,10 89,01 1,75 0,07 4,34 10,31 40,20 6,75 Dry season 14/15 139,7 1046,4 1186,1 7,13 471,51 396,70 165,46 153,70 65,53 356,81 248,04 7,10 97,79 5,02 0,91 22,88 28,30 112,58 31,59

Rainwater Fertilizer pH EC NPK Mg Ca Na NPK Mg Ca Na [-] [mS/cm] [kg/ha] [kg/ha] Wet season 14 7,39 17,19 1,46 0,15 0,38 0,43 3,51 1,23 228,65 97,71 141,76 0,30 41,92 8,54 Dry seaon 14/15 117,87 50,37 73,08 0,16 21,61 4,40 Wet season 15 7,52 28,43 1,17 0,45 1,85 1,70 8,09 1,34 310,57 28,82 37,33 0,11 13,95 2,84 Dry season 14/15 6,90 27,60 0,20 0,13 1,29 0,89 9,02 0,87 148,55 56,35 72,99 0,20 27,23 5,55

Rain water had a pH between 6.9 and 7.5. Electrical conductivity was between 405 and 563 mS cm-1 in waste water for all seasons with no clear pattern between wet and dry seasons. N inputs with waste water were higher in the dry seasons (259.67 and 396.7 kg ha-1) compared to the wet seasons (103.06 and 195.47 kg ha-1), mainly due to the higher irrigation rates. N inputs with clean irrigation water (1.75 – 5.86 kg ha-1) and with rainfall (0.2-1.46 kg ha-1) were much lower. The same seasonal patterns were observed for P, K, Mg, Ca and Na inputs with waste water irrigation and clean water and rain also showed smaller values for these parameters. Seasonal nutrient inputs into the system under NAP treatments varied with crops and were between 117.87 to 310.57 kg N ha-1, 28.82 to 97.71 kg P ha-1, 37.33 to 141.76 kg K ha-1, 0.11 to 0.3 kg Mg ha-1and 13.95 to 41.92 kg Ca ha-1 and Na inputs were 2.84 to 8.54 kg ha-1 (Table 1).

Leachate amounts

During Wet1, leached water reached a mean of 770 mm, which was the highest of all seasons

(Fig. 2), amounting to about 57 % of the total water inputs. No significant effects of the treatments were found. Starting in Dry1, leaching amounts were significantly higher with waste water irrigation than with clean water (p < 0.001), with 274 and 173 mm, respectively, corresponding to 30 and 19 % of the water inputs.

Similar differences were observed for Wet2 with 318mm of leaching under clean water and

419 mm under waste water irrigation, corresponding to 36 and 51 % of the water inputs. Due to a loss of irrigation protocols, leaching rates under waste water irrigation during Dry2 could not be calculated. Under clean water irrigation there was 239 mm leachate in Dry 2, corresponding to 19 % of the water inputs.

Figure 3-2: Seasonal water flux (a) and the percentage of leaching to total water input

(b) of clean water (light gray bars) and waste water (dark grey) irrigated plots of the multi-factorial field experiment in Tamale, northern Ghana. Error bars represent + / - one standard deviation.

Seasonal leaching of NO3-N, NH4-N, PO4-P, K, Ca, Mg and Na

During the first wet season (Wet 1), nitrate leaching was very high in the fertilized plots

-1 reaching up to 222 kg NO3-N ha (Fig. 3). Similar significant treatment patterns were also observed during the following seasons but with lower NO3-N leaching rates (Tab. 2). In addition, during Dry 1 and Wet 2 irrigation with waste water increased NO3-N leaching compared to clean water irrigation. A significant influence of the biochar applications on NO3-N leach-

+ ing was not observed. N-leaching as NH4 -N was much lower compared to NO3-N and generally below one kg per ha (data not shown). Furthermore, PO4-P leaching was also very low

-1 (<1 kg ha ) except during Wet 2, when PO4-P leaching under waste water irrigation reached up to 2 kg ha-1 and was significantly higher than under clean water irrigation. Seasonal K leaching was significantly higher under waste water irrigation and ranged from 2 to 4 kg ha-1 with much lower values during Dry1. The highest leaching rates were observed for Ca with up to 375 kg Ca ha-1 in Wet 1 and between 20 and 200 kg Ca ha -1 in the following seasons, 56

with generally highest values in the NAP treatments with mineral NPK fertilization. In Dry 1 waste water irrigation also significantly increased the Ca leaching. Magnesium showed a very similar pattern like Ca but with lower values (Fig. 3).

Figure 3-3: Seasonal leaching of NO3-N (a), PO4-P (b), K (c), Mg (d), Ca (e) and Na (f) under clean water (light gray bars) and waste water (dark grey) irrigated plots of the multi-factorial field experiment in Tamale, northern Ghana. Error bars represent +/- one standard deviation, n=4.

Sodium leaching was higher in the wet seasons with 13 to 140 kg Na ha-1 than in the dry season with 4 to 48 kg Na ha-1. In seasons one to three a significant increase of Na leaching under waste water irrigation was found (Fig. 3 and supplementary material).

Seasonal nutrient balances and contribution of leaching to total system output

Figure 3-4: Seasonal balances of N (a), P (b), K (c), Mg (d), Ca (e), Na (f) under clean water (light gray bars) and waste water (dark grey) irrigated plots of the multi-factorial field experiment in Tamale, northern Ghana. Error bars represent +/- one standard deviation, n=4. The Na balance was calculated without uptake by the crops. 58

Nitrogen balances for the first wet season were negative to neutral and the data showed a significant effect of water quality to more negative balances under clean water irrigation (Fig. 4 and Table 3).

Only during this season, leaching was the dominant N output from the soil system (53 % to 83

% of total N output) and exceeded the N uptake of plants (Fig. 5). In the following seasons N uptake by plants was more dominant and leaching accounted for 11 to 32 % of the total N removal form the system. In Dry 1 clean water irrigated treatments also showed negative balances up to to -100 kg N ha-1 in the fertilized treatments. Under waste water irrigation with its associated higher N-inputs (Supplementary material), N balances were positive with a surplus of up to +65 kg N ha-1 in the unfertilized treatments while fertilized treatments showed neutral

N balances. The data shows increasing N balances through fertilization and the different water qualities for irrigation. During Wet 2, the N balances for all the fertilized plots, especially under waste water irrigation were the highest with values between 166 and 209 kg N ha-1, thus showing that much of the N inputs from fertilization (310 kg ha-1) and waste water (195 kg ha-1) were neither leached nor taken up by the crops. In Dry 2, N balances are only available for the clean water irrigated treatments and are negative to neutral (-46 to 14 kg N ha-1) with a significant higher surplus on fertilized plots (Table 3). In the first season leaching was the dominant N output from the system and exceeded the N uptake of plants (Fig. 5). Leaching was responsible for 53 % to 83 % of total N output. In the following seasons, with less irrigation, N uptake by plants was more dominant and leaching accounted for 11 to 32 % of the total N removal form the system.

Figure 3-5: Contribution of leaching and crop uptake to the total output of N (a), K (b),

Mg (c) and Ca (d) in the multi-factorial field experiment in Tamale, northern Ghana.

Phosphorus balances of plots with clean water irrigation without mineral fertilizer application were generally slightly negative with values between -1.76 and -5.49 kg P ha-1(Fig. 4), largely due to crop uptake (Fig. 5). With fertilizer application, balances were positive reaching up to

103 kg P ha-1 (Fig. 4). In Dry 1 and Wet 2 waste water application without fertilizer caused positive balances of 78 and 13 kg ha-1, respectively. In all seasons, P balances were significantly increased by fertilizer application and during the first three seasons a significant effect of waste water irrigation was determined (Table 3). The contribution of leaching to total P output was generally low (Fig. 5). Even during the elevated P leaching under waste water irrigation in Wet 2 leaching accounted only for 2 % of total P output.

Potassium balances were generally negative, except in the NAP treatments during the Wet1 season (Fig. 4) when K fertilizer application was highest (Table 1). Similar to P, K removal occurred mainly with crop biomass and leaching losses were negligible (Fig. 5). Interestingly, during Dry1 and Wet2, K balances were more negative under waste water irrigation, likely because of increased uptake of K by the crops, although inputs were higher by about 36 and

21 kg ha-1 compared to those under clean water irrigation (Table 1).

Magnesium balances were negative in all seasons and treatments, with highest losses in the

NAP treatments where NPK fertilizer was applied (Fig. 4). Here, the higher outputs were generally due to both increased leaching and higher crop uptake (Fig. 5). Interestingly, the contribution of Mg leaching to total system output was higher under clean water than under waste water irrigation.

Calcium balances were also mostly negative except in the unfertilized plots during the two dry seasons (Fig. 4). Outputs were dominated by leaching and this was greatly enhanced by fertilizer application (Fig. 5). In the first season Ca leaching accounted for 87 to 94 % of total

Ca output. In the following season this contribution was lower but still dominant. The lowest contribution was recorded in Dry 1 with 37 to 55 %. In addition, in the first season waste water improved Ca balances due to higher Ca input with waste water irrigation.

Sodium balances in Wet 1 were between -35 and 12 kg Na ha-1 and showed a significant increase by waste water irrigation. This is in line with the higher Na input (100 kg Na ha-1) with waste water. During Dry 2 waste water irrigation showed the biggest effect and increased balances to 127 kg Na ha-1. Surprisingly, during Wet 2 waste water irrigation decreased Na balances to –61 kg Na ha-1, while clean water irrigated plot exhibited almost neutral balances.

This is likely connected to the increased Na leaching rates and water flux under waste water 61

irrigation. When compiling a total Na balance for Wet 1 to Wet 2 we found a negative mass balance under clean water irrigation with -15 to -30 kg Na ha-1 and under waste water irrigation, a positive balance of 66 to 95 kg Na ha-1.

Discussion

Range of nutrient inputs

Comparing N inputs of this study (702-1051 kg N ha-1 yr-1 in fertilized and waste water irrigated plots) with data from other studies on high input UA shows a relatively low nutrient input in our case. Diogo et al. (2010) reported inputs up to ~1,400 kg N ha-1 yr-1. In studies from

Vietnam and China N inputs were up to 1,643 and 1,565 kg N ha-1 yr-1, respectively (Huang et al. 2006, Khai et al. 2007). Graefe et al. (2008) reported even annual inputs of up to 7,519 kg

N ha-1. However, the N inputs in our study were higher than the reported up to 165 kg N ha-1 yr-1 from Goenster et al. (2015) for home gardens in the Nuba Mountains of Sudan or 800 kg

N ha-1 yr-1 reported by Abdalla et al. (2012) also for a study in River Nile flooded gardens of

Khartoum, Sudan.

The P inputs in this study are between 159 and 279 kg P ha-1 yr-1 with fertilizer and waste water use. As in the case of N inputs, this is lower than 500, 261, 736 and 543 kg P ha-1 yr-1 reported by Graefe et al. (2008), Diogo et al. (2010), Khai et al. (2007) and Huang et al. (2006), respectively. However, the P applied in this study is higher than the inputs reported by

Abdalla et al. (2012) and Goenster et al. (2015) with 4.5 and 29 kg P ha-1 yr-1, respectively.

K inputs in this study were as high as 276 and 284 kg K ha-1 yr-1 and the comparison with other reported amounts show the same picture as for N and P. K inputs were much lower than values reported by Diogo et al. (2010), Khai et al. (2007) or Huang et al. (2006) of 700, 903 62

or 690 kg K ha-1 yr-1, respectively. Interestingly, Graefe et al. (2008) reported a K input of up to 7,081 kg K ha-1 yr-1. However, Abdalla et al. (2012) and Goenster et al. (2015) reported lower values with 90 and 149 kg K ha-1 yr-1.

Water use efficiency and effects of waste water on drainage

The percentage of leached water was very high in the first season although it was a wet season, the irrigation was high with a total water input of 1356 mm and 56 % of the total water input remained unused. During the following season the total amount of irrigation and rainfall was lower and therefore the leaching rates were reduced and the water use efficiency was improved. In another study, Sangare et al. (2012) measured water lost by drainage of about 3-8

% of total water input in urban farm in Bobo Dioulasso, Burkina Faso. These amounts were exceeded in our study in all seasons, indicating a need for better farmer training on irrigation quantities.

Furthermore, during Dry 1 and Wet 2 we observed increased water flux under waste water irrigated plots. This could maybe be explained by high loads of humic matter, polysaccharides and fatty acids in waste water causing increasing soil water repellency, resulting in higher infiltration rates as shown by Arye et al. (2011). However, Schacht and Marschner (2015) reported lower hydraulic conductivity when soil was irrigated with treated waste water compared to fresh water in fruit orchards in Israel. The irrigation with waste water and the resulting soil water repellency can cause finger flow paths in soil with higher water flux in these areas (Wallach et al. 2005). In addition, damage of macro and micro pore structure under irrigation with treated sewage effluent has been observed and the losses of Ca may further increase this effect (Gonçalves et al. 2007). The thereby reduced pore space may reduce the wa-

ter holding capacity of the soil. This may explain the increased leachate amounts under waste water irrigation.

An effect of biochar on leachate amounts was not found in our study. A literature review re- veals inconsistent effects of biochar on soil physical parameters. Biochar showed decreasing and increasing effects on saturated hydraulic conductivity depending on biochar particle size and soil texture (Lim et al. 2016). However, biochar additions had no effect in loamy soils. In other studies, biochar increased the water holding capacity of soil (Abel et al. 2013, Sun and

Lu 2014). In a study of Ojeda et al (2015), biochar had no effect on water storage in soil. In general, biochar properties and their effect on soil can vary widely depending on feedstock material and pyrolysis method.

Seasonal nutrient leaching effected by biochar

In our study we could not find any significant effects of biochar on leaching of nutrients.

There are some field studies on nutrient leaching and biochar application in the literature. In an Colombian Oxisol, N, Ca, Mg and K leaching decreased after the addition of 20 t ha-1 wood biochar (Major et al. 2012). Also N leaching was reduced by 82 % in a field trial in

New York with the application of biochar produced from maize stover under full fertilization but not with half fertilization (Güereña et al. 2013). Hardie et al. (2015) conducted a wick lysimeter campaign in a young apple orchard in New Zealand with 47 t ha-1 wood biochar which had no effect on nitrate leaching but increased K losses. The lack of effects in our study may be explained with the high inputs of nutrients through fertilizer application and waste water in this vegetable production system and a relatively low sorption capacity of the biochar. The surface area of the used rice husk char is small compared to other biochars

(Mukherjee et al. 2011), therefore the interface of biochar to interact with soil water is lim- 64

ited. Furthermore, the application rate of 20 t ha-1 incorporated to a depth of 20 cm or about

0.5 wt. % was relatively low. Many other biochar studies used biochar additions which were ten times higher or more to observe significant effects of biochar on leaching.

Waste water effects on seasonal nutrient leaching

The seasonal N leaching was effected by waste water irrigation. This is mainly explained by the increased N input through waste water. In the first season, due to the high rainwater input and therefore high water flux, the effect of waste water irrigation on N leaching was less pro- nounced compared to the later seasons. Also Barton et al. (2005) found an increase of N leaching when soils were irrigated with secondary treated domestic effluent. The leaching of

NH4 showed only an effect of waste water irrigation in Wet 2. Although, the main form of N in the waste water is in the form of NH4-N almost all N leaching is in the form of NO3-N which was also observed by Goenster et al. (2015).

In our study, P leaching was generally very low with less than 0.5 kg ha-1 per seasons because the soil exhibits many bonding sides for P like Al and Fe hydrous oxides and clay (Parfitt

1979). Nevertheless, in Wet 2 an increase of P leaching under waste water irrigated plots has been observed. This could be explained by competitive sorption of waste water borne dissolved organic carbon with phosphorus as shown by Kang et al. (2011) or more specifically organic anions (Kafkafi et al. 1988). This mechanism in combination with an increase of soil pore water velocity, due to above mentioned effects of waste water irrigation on soil water repellency and physical soil properties could likely cause the measured increment in P leaching in Wet 2.

Furthermore, K leaching was only in Dry 1 increased by waste water irrigation, which is explained by the negative K balances of the systems. Also in the literature K leaching is negligible in these savannah soils (Piéri 1989). Ca and Mg leaching was also observed to be increased by waste water irrigation. This is attributed to the increased nitrate leaching because an equivalent amount of cations is needed to obtain electrical neutrality of the leachate. This is also supported by higher Pearson correlation coefficients of leached Ca and Mg to leached

NO3 (0.65 and 0.73, p < 0.05) than to the water flux (0.55 and 0.6, p < 0.05).

When compared to other studies, N leaching was found to be much higher in the first season under fertilizer application than reported 2.2-7.3 kg ha-1 yr-1 by Predotova et al. (2011) or Safi et al. (2011) who found an average N leaching of 140 kg N ha-1 yr-1 in two vegetable gardens in Kabul, Afghanistan and the reported 53-45 kg N ha-1 yr-1 by Goenster et al. (2015). In season two to three, the reported values are close to ours with the exemptions of Predotova et al.

(2011), who reported much lower leaching rates which, however, are likely reflecting the par- ticularities of a below average rainfall year. Our findings indicate that apart from the effects of soil properties and input quantities, leaching is largely controlled by the water flux. The aforementioned studies were done by using ion exchange resins cups and therefore water fluxes could not been measured (Weihermüller et al. 2007). The leaching of P was as low as reported in other studies (Goenster et al. 2015, Predotova et al. 2011) but lower than the 6.5 kg ha-1 yr-1 from the study of Safi et al. (2011) which was conducted in a garden soil with a pH higher than 8 and therefore higher P mobility. Furthermore, K leaching was far lower than

33-34 kg ha-1 yr-1 reported by Goenster et al. (2015).

When we compare the N output from the system by crop uptake with leaching, especially when water fluxes are high like in Wet 1, leaching can be the major output pathway. In later

seasons with are more adjusted irrigation and therefore less water flux, the contribution of leaching to the total output was about 25 % (Fig.5). In the case of P and K which are less prone to leaching, the leaching losses are almost negligible.

Nutrient balances in urban agriculture

Nitrogen mass balances were negative in the first two seasons but positive in the third season.

Generally, the results are comparable to those reported by Cobo et al. (2010) in their meta- analysis. Waste water borne N contributed strongly to a positive balance although higher water fluxes were observed in the later seasons. A general conclusion whether N balances are negative or positive cannot be given. However, the N balances in this study were far lower than the extremely high horizontal balances of 7,312 (Graefe et al. 2008), 1,133 (Diogo et al.

2010), 2,056 (Lompo et al. 2012) or 814 kg N ha-1 yr-1 (Huang et al. 2006). Nevertheless, they are comparable to N balances reported by (Goenster et al. 2015) of -70 or Abdalla et al.

(2012) with 342 kg N ha-1 yr-1. The loss of N from the soil during the experiment was also measured in the soil parameters. The initial low soil N of 0.04 % (0-20 cm) and 0.03 % (20-

40 cm) was further reduced by 3.5 to 10.1 % (Häring et al. 2017).

Strongly positive balances for P were observed in this study, which was comparable to the balances calculated by other researchers (Diogo et al. 2010, Graefe et al. 2008, Huang et al.

2006, Khai et al. 2007). Negative balances as reported by Goenster et al. (2015) or Abdalla et al. (2012) seems to be impossible with the soil in this study when fertilizer is applied to soil and / or waste water is used for irrigation. A completely different situation was found for K with negative balances. The use of waste water was decreasing the balances although higher

K inputs occurred. This is explained by higher K plant uptake as measured by Akoto et al.

(2018). Mg and Ca showed negative balances and are therefore strongly removed from the 67

soil. In addition, fertilization caused a significant reduction of Mg and Ca balances. The leaching of these basic cations decreases the buffering capacity of the soil and thus indicates soil acidification. This was confirmed by the observed significantly lower soil pH values in treatments where fertilizer was used (Häring et al. 2017). Furthermore, effects of waste water irrigation can be observed in positive Na balances, while negative balances were found under clean water irrigation. Therefore, Na was accumulating in soils under waste water irrigation which might have increased soil salinity and the exchangeable sodium percentage (Levy et al.

2014). Interestingly, Na balances under waste water irrigation were not always positive. Dur- ing wet seasons balances close to zero or even negative were found so that salinization may be reversed during the rainy season.

Conclusions

Unlike rural agricultural systems, African UA systems are typically highly intensive input- output systems which show large positive nutrient balances for N and P. Waste water contributes significantly to the nutrient inputs as shown in this field trial. Nutrient leaching and nutrient mass balances are also affected by waste water irrigation, the amount of fertilizer applied and strongly by the appropriate amount of irrigation. In our case, K fertilization was not high enough to replace K losses by plant uptake. There also were high losses of basic cations that indicate a strong tendency of acidification when mineral fertilizer is used. This needs to be compensated by inputs, possibly from organic amendments such as composts. In our study, nutrient leaching losses were not as high as in the horizontal balance studies reported from other studies.

Our results and field observations show that there is scope for better fertilizer management taking waste water contribution into account and adjusting irrigation quantities. Apart from 68

the nutrient contribution of waste water there are also negative effects on soil physical parameters that result in a decreased water use efficiency and accumulation of Na in soils that may lead to salinization in the long term.

Acknowledgements

We thank the German Federal Ministry of Education and Research (BMBF) and the German

Federal Ministry for Economic Cooperation and Development (BMZ) for funding the research of the UrbanFoodPlus project under the GlobE-initiative (FKZ: 031A242-A,B). We also thank Sabine Frölich, Katja Gonschorek, Heidrun Kerkhoff and Bettina Röhm at Ruhr-

Universität Bochum for technical support. We also acknowledge the help of our field techni- cians Isaac K. Assirifi and Isaac Assirifi, supporting farmers and the University for Develop- ment Studies (UDS) in Tamale for their effective support.

Supporting information

Table 3-2: P-values from mixed model results for seasonal leaching amounts of the multi- factorial field experiment in Tamale, northern Ghana. n.s. = not significant (P > 0.05), N.A. = no data available.

Wet season '14 Dry season '14/15

Factor NO3-N P log(K) log(Ca) Mg Na NO3-N log(P) log(K) log(Ca) Mg Na Fertilizer <0.01 n.s. n.s. <0.01 <0.01 0.02 <0.01 n.s. n.s. <0.01 <0.01 n.s. Water quality n.s. n.s. n.s. n.s. n.s. 0.00 <0.01 n.s. n.s. <0.01 n.s. <0.01 Biochar n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. Interactions Bc:Fert:Bc Bc:Fert 0.01 <0.01

Wet season '15 Dry season '15/16

Factor NO3-N log(P) log(K) Ca Mg Na NO3-N log(P) K Ca Mg Na Fertilizer <0.01 n.s. n.s. 0.02 n.s. n.s. <0.01 n.s. n.s. <0.01 <0.01 n.s. Water quality n.s. <0.01 n.s. n.s. 0.02 <0.01 N.A. N.A. N.A. N.A.N.A.N.A. Biochar n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. Interactions WatQu:Fert WatQu:Fert 0.04 0.04

Table 3-3: P- values from mixed model results for seasonal nutrient balances of the multi- factorial field experiment in Tamale, northern Ghana. n.s. = not significant (P > 0.05) , N.A. = no data available.

Wet season '14 Dry season '14/15 2 Factor N P K (Ca+600) Mg NPK Ca Mg Fertilizer 0.04 <0.01 n.s. n.s. <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 Water quality n.s. <0.01 <0.01 n.s. n.s. <0.01 <0.01 <0.01 n.s. n.s. Biochar n.s. 0.01 0.01 n.s. 0.01 n.s. n.s. n.s. n.s. <0.01 Interactions Bc:Fert Bc:Fert Bc:Fert Bc:Fert WatQu:Fert WatQu:Fert 0.01 0.02 0.02 <0.01 <0.01 0.03

Wet season '15 Dry season '15/16 Factor N P K Ca Mg NPK Ca Mg Fertilizer <0.01 <0.01 n.s. <0.01 <0.01 n.s. <0.01 n.s. <0.01 <0.01 Water quality <0.01 <0.01 <0.01 n.s. 0.01 N.A. N.A. N.A. N.A. N.A. Biochar n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. Interactions WatQu:Fert <0.01

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4. Effects of biochar and waste water irrigation on soil biological properties in urban agriculture of N-Ghana

Co-authors:

Steffen Werner1, Isaac K. Assirifi2, Stephanie Heinze1, Saba Courage2, Innocent Y.D. Law- son3 and Bernd Marschner1

1 Department of Soil Science and Soil Ecology, Faculty of Geosciences, Ruhr-University Bo- chum, Universitätsstr. 104, 44801 Bochum, Germany

2 University for Development Studies, Tamale, Ghana

3 Soil Science Department, School of Agriculture, University of Ghana, Box LG 245, Legon-

Accra, Ghana

*Corresponding author ([email protected])

To be submitted to Biology and Fertility of Soils

All authors contributed to the idea and concept of the experiment and gave feedback to the manuscript. S.W. and I. A. conducted the analysis. S.W. undertook the statistical analysis and wrote the manuscript

Abstract

Urban agriculture (UA) in West African developing countries contributes to urban economy and health of the urban population. It is often characterized by high nutrient inputs compared to rural areas and the use of mostly untreated waste water for irrigation. Biochar has been proposed to increase crop yield and improve soil properties. In this paper we assessed microbial respiration, microbial biomass carbon and enzyme activities of soil from a field experiment in UA in northern Ghana treated with fertilizer and/or biochar under clean and waste water irrigation. Our results show a strong increase of SOC by biochar application by up to

141%. Hot water extractable carbon (HWC) was increased by biochar by about 11 to 26% and microbial biomass carbon (MBC) by 34%. Waste water irrigation increased HWC significantly by 4%. Basal respiration was significantly increased in mineral fertilized soil by up to 46% and decreased by 12-45% under waste water irrigation. Overall, the metabolic quotient

(qCO2) indicated less stress for the microbial community and increased carbon use efficiency with biochar application and waste water irrigation. Furthermore, waste water irrigation increased total enzyme activities and biochar treated soils exhibit a more diverse C-cycling community and a higher activity of aminopeptidases. Therefore, biochar and waste water showed positive effects on biological soil properties and contributed to soil fertility. Our results also suggest beneficial effects of biochar on non-biochar SOC stocks in the long term.

Introduction

Urban agriculture is a common phenomenon in African cities and can contribute to 60-100% of the fresh vegetable supply (Drechsel et al. 2006). It makes use of every free space, provides income for the farmer housholds and contributes to more diverse diets (Cofie et al. 2003). It is often characterized by excessive use of mineral or organic fertilizer, intensive continuous cropping cycles without fallow periods, production of cash crops and irrigation with untreated sewage water (Keraita and Cofie 2014). Soils fertility in these systems is often very poor. For instance, Häring et al. (2017) reported very low soil carbon, nitrogen, cation exchange capacities and pH values for an UA soil in Tamale, Ghana. In UA systems nutrient leaching can be very high due to high nutrient inputs and poor soil properties (Werner et al. in Preperation).

Little is known about soil biological properties in these agroecosystems. Soil biological activities are an important part of soil quality, since microorganisms and their associated enzymes in soil are responsible for the breakdown of organic matter and release of nutrients

(Burns et al. 2013). Especially irrigation with waste water or treated water can have a strong impact on soil microbial activities and abundance due to the input of carbon or mineral and organic bound nutrients (Durán–Álvarez and Jiménez–Cisneros 2014, Friedel et al. 2000,

Jueschke et al. 2008). Furthermore, irrigation with raw or treated waste water has been shown to have effects on soil enzyme activities and thus turnover of nutrient and organic carbon

(Chen et al. 2008, Heinze et al. 2014). In the West African savanna soils, organic matter content is generally low (Bationo and Buerkert 2001). Many studies propose the application of biochar as a soil conditioner. A recent meta-analysis of 109 studies by Jeffery et al. (2017b) revealed an 25% average increase in yield through biochar application in tropical climates.

This effect was mainly explained by a liming and fertilization effect of ash content of biochar

(Jeffery et al. 2017b). Other authors suggest that biochar may increase microbial activity, pro- 80

vide habitat for microorganisms and hence alter microbial mediated processes in soil

(Lehmann et al. 2011). Especially, soil enzymes activities are affected by biochar. For instance, (Paz-Ferreiro et al. 2014) found increase in activities of soil enzymes catalyzing important reactions in soil when biochar was added to a tropical soil. However, (Lammirato et al. 2011) reported a decrease in β-glucosidase activities with biochar application. Further- more, biochar carbon has shown to be very recalcitrant in soil with turnover times of more than a millennia (Zimmerman et al. 2011) and thus provide a long term improvement. This paper is based on the hypothesis, that waste water and biochar stimulate and improve the microbial community and soil enzyme activities. Therefore, we incubated soil from an UA field experiment and measured parameters related to microbial abundance and activity. In addition we assessed soil enzyme activities from C, N, S and P cycles.

Materials and Methods

Experimental design and site description

Samples were taken from an experimental field trial in Tamale, Northern Ghana. The city is located in the guinea savanna zone and has a semi-arid climate with a monomodal rainfall pattern from May to mid-October. The mean annual precipitation is 1090 mm and the daily mean temperature is 27.9°C (DWD o.J.). The soil at the experimental site is a Petroplinthic Cambi- sol (FAO 2014) with a loamy silt texture (45.7 % sand, 47 % silt and 5.9 % clay) . Initial soil properties were tested before the start of the experiment to a depth of 20 cm and showed

0.41% SOC, 0.04 % total nitrogen, pH 5.1, bulk density of 1.42 g cm-3 and an effective cation

-1 exchange capacity of 36.1 mmolc kg (Häring et al. 2017). Treatments in the field experiment include a control (with no amendments), a biochar treatment (20 t ha-1), a treatment fertilized according to the normal agricultural practices (NAP) of the farmers and a treatment with bio-

char and NAP. All the treatments were either irrigated with clean tap water or with untreated waste water. The fertilizer used in the NAP treatment was a commercial NPK 15-15-15 blend.

During the first year of the experiment, the NAP treatments received 228.7 kg N ha-1, 97.7 kg

P ha-1 and 141.8 kg K ha-1 in the form of NPK (15-15-15) fertilizer. The biochar was produced from rice husks which are an abundant organic waste in Ghana. Briefly, the rice husks were heated in a custom pyrolysis oven under oxygen limited conditions to about 550°C. The rice husk biochar had a total C content of 42.4%, 0.4% total N, a pH of 9.1 (in water) and

-1 62.89 m² g BET (N2) surface area. Further information and details about measurement procedures of biochar properties can be found in Atijah and Marschner (submitted). Soil samples were taken from each of the four replicate plots from each treatment one year after establish- ment of the field experiment. A composite sample from six randomly distributed points of the plot was taken to a depth of 20 cm. After sampling, the soils were air dried, sieved to 2 mm and shipped to Germany.

Assessment of soil respiration, microbial biomass and enzyme activity

Prior to the measurement of soil biological parameters, the samples were rewetted to 50% water holding capacities and pre-incubated for seven days at 25°C. Total water holding capacity was determined by placing 10 g of soil in a funnel with prewetted filterpaper. The soil was wetted several times with deionized water and excess water was allowed to drain from the soil. The maximum water holding capacity was subsequently determined by weighing. Basal and substrate induced respiration were measured with the Microresp method developed by

Campbell et al. (2003). Briefly, a pre-incubated samples (0.3 g) of soil were placed into deep- well microtiter plates and water (for basal respiration) or substrate (glucose, alanine or citric acid) was added to reach 60% WHK. Afterwards, the plate is covered and sealed with another

plate filled with agar containing an indicator dye (cresol red). The evolved CO2 was captured in the agar and causes a color change. After six hours of incubation the color change is measured with a microplate reader (Infinite F200, TECAN Deutschland GmbH, Crailsheim, Ger- many) at 590 nm. Microbial biomass carbon (MBC) was measured with the chloroform fumigation extraction method according to Vance et al. (1987). Ten grams of preincubated soil sample were exposed to chloroform vapor for 22 hours in a desiccator and extracted afterwards with 40 ml 0.5 M K2SO4. TOC of the extract were measured with a TOC analyzer

(Dimatoc 2000, Dimatec Analysentechnik GmbH, Essen, Germany). In addition, an unfumigated sample was extracted the same way and microbial biomass carbon was then calculated as the difference in TOC of fumigated and unfumigated sample by using a conversion factor of 0.45 (Joergensen 1996). Dehydrogenase activities was determined by measuring the reduction of 2-p-Iodophenyl-3-p-nitrophenyl-5-phenyl-tetrazoliumchlorid (INT) to Iodonitro- tetrazolium-formazan (INTF) after 24 hours (Trevors 1984). One gram of soil was mixed with

50µl glucose solution (1%) and 1ml INT solution (0.4%) and incubated for 24h in the dark at

23°C. Then, 10 ml methanol was added and after filtration the extinction of the extract was measured at 485nm and INTF content was calculated by means of a calibration curve. Extra- cellular enzyme activities of C, N, P and S cycle were measured after Marx et al. (2001) with fluorescent substrates. The following extracellular enzyme activities were measured for C- cycling enzymes: α-glucosidase (α-glu), β-xylosidase (β-xyl), β-glucosidase (β-glu), N-acetyl- glucosidase (N-acet) and β-cellobiosidase (β-cello) were measured with methylumbelliferyl

(MUF)-labelled substrates. Also acid phosphatase (pho) involved in the P cycle and sulfatase

(sul) from the S cycle were measured with MUF labelled substrates. Activities of enzymes from the N cycle, such as leucine-aminopeptidase (leu), tyrosine-aminopeptidase (tyr) and arginine-aminopeptidase (arg) were determined with amido-methylcoumarin (AMC) labeled 83

substrates. The respective substrate (1 mM) was dissolved in dimethyl sulfoxide and diluted with sterile water and 0.1 M MES buffer for MUF substrates or 0.05 M TRIZMA buffer for

AMC substrates. A soil suspension was produced by mixing one gram of soil with 50 ml sterile water and treated with ultrasound probe at 150 W to release the enzymes from the soil particles. Soil suspension and substrates in the respective buffer solutions were pipetted into mi- crotiterplates and incubated for 10 min at 30°C. Subsequently, enzyme activities were measured by detecting florescence of released enzymatic products every 30 min during 3 h with a multiplate reader (Infinite F200, TECAN Deutschland GmbH, Crailsheim, Germany) at

360nm excitation and emissions at 465 nm. The enzyme activities were calculated from the slopes of the resulting utilization curves.

General soil parameter

Total carbon and nitrogen contents of the samples were determined by using a C/N-Analyzer

(Vario max cube, Elementar Analysesysteme GmbH, Hanau, Germany). The pH was measured by mixing soils with 0.1 M CaCl2 at a 1:5 soil : solution ratio (vol. : vol.). Readings were taken with a pH meter equipped with a gel electrode (Sentix 41, Wissenschaftlich-Technische

Werkstätten (WTW) GmbH, Weilheim, Germany). Hot water extractable carbon (HWC) was measured with a method adapted from Haynes and Francis (1993). Briefly, 2 g pre-incubated soil was mixed with 20 ml deionized water in centrifuge tubes. After 16 h in a 80 °C water bath the tubes were centrifuged and carefully decanted. The supernatants were filtered (0.45

µm membrane) and then analyzed with a TOC-Analyzer (Dimatoc 2000, Dimatec, Essen,

Germany).

Statistical analysis

Significant differences of mean were assessed by using multi factorial analysis of variance

(MANOVA). P values <0.05 are considered to be significantly different. Data was checked for normal distribution with Shapiro-Wilk test. If necessary, data were transformed to archive normal distribution. Details of the respective transformation can be found in Tab. 2. Principal component analysis (PCA) was used for reduction of parameters to two main factors. Vari- max rotated factor loadings are given in Tab. 4. MANOVA was done using R (R

Development Core Team 2008) and PCA was conducted with SPSS Statistics 22 (IBM, Ar- monk, New York, USA).

Results and Discussion

Treatment effects on soil parameters

Biochar application increased SOC due to its high C content (42.4% C) by 84-86% in the

NAP treatments and by even 97-123% in unfertilized treatments. Despite C inputs with waste water, a significant increase of C after one year of waste water irrigation could not be observed. After long-term irrigation with waste water or treated waste water, other researchers found increases of SOC (Jueschke et al. 2008, Lal et al. 2015, Siebe et al. 2016). Fertilizer use decreased pH of the soil by up 0.7 units. This can be explained by the release of protons during nitrification of the fertilizer and by the negative mass balances of base cations like Ca, K and Mg due to nitrate leaching (Werner et al. in preperation). Total P in soil is significantly increased by 45-50% with fertilizer use in the NAP treatments compared to the control (Tab.

1). In the biochar treatments, no significant effect on total P in soil was found. Similar values were also reported after two years in the same experiment (Häring et al. 2017).

Table 4-1: Physico-chemical soil parameters, dehydrogenase activity, substrate induced respiration and statistically significant (p≤0.05) effects and interactions. Means ± one standard deviation, n=4.

C N P pH HWC Dehydrogenase Substrate induced respiration activity Glucose Citirc acid Alanin

[%]±SD [%]±SD [g/kg]±SD [-]±SD [g/kg]±SD [nmol product [µg CO2-C/g]±SD /g] ±SD clean water Control 0.35 ±0.07 0.04 0.01 0.14 0.01 5.20 0.24 166.49 10.90 15.03 2.96 1.11 0.25 1.59 0.18 0.43 0.15 irrigation Biochar 0.69 ±0.08 0.05 0.01 0.17 0.02 5.23 0.32 210.20 7.95 14.58 3.32 1.22 0.25 1.78 0.20 0.38 0.22 NAP 0.43 ±0.04 0.05 0.00 0.20 0.01 4.51 0.16 191.69 4.23 15.50 2.98 0.67 0.21 1.85 0.10 0.19 0.16 NAP/Biochar 0.80 ±0.2 0.06 0.01 0.20 0.01 4.54 0.18 212.37 16.75 18.21 2.86 0.89 0.38 1.75 0.53 0.23 0.08

waste water Control 0.35 ±0.1 0.04 0.01 0.16 0.02 5.04 0.19 173.08 7.16 16.50 1.93 1.16 0.22 1.80 0.26 0.41 0.13 irrigation Biochar 0.78 ±0.12 0.05 0.01 0.17 0.02 5.25 0.25 218.10 2.19 18.27 2.76 1.18 0.06 1.81 0.11 0.45 0.10 NAP 0.45 ±0.03 0.05 0.01 0.23 0.02 4.67 0.12 197.94 8.44 14.18 2.28 0.82 0.15 1.92 0.10 0.34 0.11 NAP/Biochar 0.83 ±0.09 0.05 0.00 0.18 0.01 4.58 0.07 223.43 4.00 12.04 2.17 0.71 0.02 1.86 0.09 0.29 0.08 Transformation log log P values from MANOVA Block Biochar <0.05 <0.05 Fertilizer <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 Water quality <0.05 Sig. Interactions p≤0.05) Bc:Fert Bc:Fert Fert:Watqual BC:Watqual

In this study, biochar significantly increased hot water extractable carbon (HWC, Tab.1) by

11-13% in fertilized soil and by 26% in the unfertilized soils. The fertilization with NPK was also found to significantly increase the HWC in soil. This could be related to a decreased decomposition of labile SOC due to lower pH values in fertilizer treated soil. However, higher basal respiration rates in NAP treatments are contradictory to this hypothesis. HWC has been attributed to the biological available carbon pool (Körschens et al. 1998). In the study of

Haynes and Francis (1993), they suggest that HWC is mainly from microbial origin. In this study, increased HWC in the biochar treatments could be explained by soluble biochar compounds or by the sorption of soluble SOC compounds that would have otherwise been miner- alized or leached. Zimmerman et al. (2011) found a suppression of carbon mineralization when biochar was added to soil. This was explained by physical protection or sorption of organic matter by biochar. In addition, Lu et al. (2014) found a negative priming effect with up to 68% reduced decomposition of native soil organic matter due to biochar addition. In their study, the stimulatory effect of N amendments on CO2 emissions from soil was reduced by biochar addition. This was also the case in our experiment (see below).

Basal respiration, metabolic quotient (qCO2) and substrate induced respiration

Basal respiration of the samples from clean water irrigation was up to 34% higher in fertilizer treated soils in comparison to the respective control (Fig. 1). This can largely be attributed to the much higher biomass production and an accompanied higher input of labile carbon into the soil of the fertilized plots (Häring et al. 2017). In contrast, waste water irrigation had a significant decreasing effect on basal respiration with a 8-30% reduction, as shown in Fig. 1.

This comes quite unexpectedly, since waste water irrigation supplies high loads of easily de- composable carbon compounds and nutrients to the soil. Therefore, other authors like Siebe et

al. (2016) and Meli et al. (2002) found an increase in basal respiration from soil irrigated with lagooned waste water. Possibly, the nutrient loads with the waste water irrigated treatments change the microbial community towards bacteria. Sakamoto and Oba (1994) showed the positive relationship between fungal:bacterial biomass ratio and soil respiration.

Figure 4-1: Basal respiration, soil microbial biomass carbon and metabolic quotient. Er- ror bars represent one standard deviation, n=4. Stastical significant effects from MANOVA are noted in the graphs. Basal respiration was squared to obtain normal distribution.

The incorporation of biochar had no effect on basal respiration in our study. However, when basal respiration was normalized to SOC content, biochar decreased the SOC-specific basal respiration significantly (data not shown). This suggests, that biochar cannot be utilized as an

energy substrate in the same way as the native SOC. This is in line with studies showing that biochar is very recalcitrant in soil and cannot be easily decomposed by microorganisms

(Wang et al. 2016).

The metabolic quotient qCO2 calculated from the basal respiration per unit of microbial biomass carbon was significantly lower by 12-45% in soil samples from waste water irrigated plots (Fig. 1), thus indicating a more efficient use of organic substrates for microbial catabo- lism and anabolism (Anderson and Domsch 1990). Also Heinze et al. (2014) and Meli et al.

(2002) found a lower qCO2 when soil was irrigated with treated or lagooned waste water, respectively. Biochar also had a decreasing effect on the qCO2 (Fig.1), suggesting that microbial efficiency is also higher in these treatments. A decreasing effect of biochar on qCO2 was also found in other studies (Liang et al. 2010, Zheng et al. 2016). This may be explained with the porous nature of the biochar material providing a habitat of the microorganisms (Warnock et al. 2007) and the more diverse microbial community (Anderson et al. 2011). In the NAP treatments, the qCO2 values were elevated under both irrigation water qualities, indicating some form of stress, most likely from increased soil acidity. Interestingly, this stress is not observed in combination with biochar although pH of the samples was similar.

Citric acid induced respiration did not show any effects of the soil treatments. However, glucose and alanine induced respiration were significantly decreased in all fertilized soils (Tab.

1). For glucose, this is explained by the lower pH and therefore generally lower microbial activity in the soil as seen in basal respiration. However, this finding is contradictory to the increased basal respiration in fertilized treatments. Lower alanine induced respiration in fertilized soil compared to unfertilized soil may show a less N limited microbial community. The addition of biochar had no effect on the decomposition of any substrate.

Table 4-2: Enzyme activities and statistically significant (p≤0.05) effects and interactions. Means ± one standard deviation, n=4.

α-glucosidase β-losidase β-glucosidase β- N -Acetl-β- sulfatase acid leucine- tyrosine- arginine- cellobiosidase glucosaminidase phosphatase aminopeptidase aminopeptidase aminopeptidase

[µmol product / g soil /h]±SD clean water Control 16,98 ± 10,98 19,00 ± 1,54 235,61 ± 39,50 1,66 ± 0,47 6,74 ± 1,89 7,18 ± 1,32 15,95 ± 2,18 3,42 ± 1,58 44,50 ± 15,02 38,72 ± 8,84 irrigation Biochar 15,11 ± 7,31 13,76 ± 1,41 132,84 ± 28,77 130,18 ± 22,72 60,86 ± 60,01 564,33 ± 646,15 34,32 ± 9,28 140,52 ± 30,41 84,86 ± 9,07 426,92 ± 510,04 NAP 6,42 ± 2,87 8,04 ± 3,06 2,10 ± 1,98 29,44 ± 6,00 15,99 ± 3,55 272,66 ± 41,61 1,63 ± 0,60 24,60 ± 5,45 13,42 ± 4,33 496,91 ± 270,09 NAP/Biochar 8,22 ± 2,88 8,13 ± 1,84 3,43 ± 2,67 4,53 ± 2,76 14,53 ± 6,98 279,96 ± 58,88 5,68 ± 6,91 38,69 ± 7,54 47,06 ± 9,75 706,57 ± 96,40

waste water Control 33,85 ± 6,41 25,58 ± 2,73 254,07 ± 54,42 9,31 ± 7,67 10,23 ± 4,16 9,10 ± 2,44 17,39 ± 4,89 6,29 ± 0,99 179,16 ± 86,57 322,66 ± 351,08 irrigation Biochar 14,96 ± 2,36 12,11 ± 3,25 101,55 ± 9,69 144,82 ± 37,61 134,02 ± 38,36 1142,65 ± 185,56 39,05 ± 2,26 227,28 ± 23,50 80,86 ± 11,48 1657,55 ± 897,59 NAP 11,68 ± 5,28 10,11 ± 2,20 95,78 ± 5,41 65,88 ± 51,77 119,59 ± 14,03 1218,51 ± 130,32 38,73 ± 2,20 208,80 ± 17,67 68,78 ± 3,60 1216,10 ± 194,27 NAP/Biochar 36,97 ± 17,77 19,95 ± 2,52 1180,33 ± 26,78 33,75 ± 9,44 8,91 ± 2,26 295,24 ± 573,56 114,97 ± 3,37 92,50 ± 4,29 108,78 ± 9,28 1111,36 ± 28,80 Transformation log sqrt log log n.d. sqrt sqrt P values from MANOVA Block <0.05 Biochar <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 Fertilizer <0.05 <0.05 <0.05 <0.05 Water quality <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 Sig. Interactions (p≤0.05 Bc:Fert BC:Fert BC:Fert BC:Fert BC:Fert BC:Fert BC:Fert BC:Fert:Watqu Fert:Watqu BC:Watqu BC:Fert:Watqual BC:Fert:Watqu BC:Watqu BC:Watqu BC:Fert:Watqu Fert:Watqu Fert:Watqu Fert:Watqu BC:Fert:Watqu BC:Fert:Watqu BC:Fert:Watqu

This supports findings from Jones et al. (2012) where biochar had no effect on the decomposition of glucose, organic acids or amino acids.

Microbial biomass carbon and dehydrogenase activity

Soil microbial biomass carbon was found to be significantly increased by biochar application from 41.5 to 55.8 mg kg-1 (means of all treatments with or without biochar, respectively) while waste water or fertilizer application had no effect (Fig. 1; Tab. 2). Other studies, also found an increase in MBC when biochar was mixed into soil (Ameloot et al. 2013, Kolb et al.

2009, Liang et al. 2010). However, Dempster et al. (2012) found a decrease in MBC with eucalyptus char. There are some concerns about the reliability of soil biological standard methods, i.e. Lehmann et al. (2011) discussed the suitability of common methods to determine soil microbial biomass. Due to sorption of carbon compounds to the biochar surface the chloroform fumigation method could be biased. Liang et al. (2010) corrected the measurements with a sorption isotherm for DOC on biochar and reported 21-41% higher values for MBC compared to the standard method. Therefore, the true increase of MBC in our study might even be higher.

The activity of dehydrogenase did not show any effects from the treatments and was not related to our MBC data although other studies generally show a close relationship of dehydrogenase activity and the microbial biomass (Beyer et al. 1992). The use of soil enzyme assays in the presence of biochar are in discussion since this may alter extraction efficiency of products from enzymatic processes or the protection of substrates due to sorption on the biochar surface (Bailey et al. 2011, Swaine et al. 2013). However, there is no consensus how to adjust methods for measuring enzyme activities in biochar amended soil.

Extracellular enzyme activities

The total enzymatic activities determined by the fluorimetric assay were approximately two to three times higher in waste water than in clean water irrigated soil (Fig. 2). This microbial activity parameter therefore stands in contrast to the observed reduced basal respiration rates in the WW samples (Fig. 1). Especially the enzymes involved in the cycling of N are more active in WW irrigated soil. We attribute this to the input of proteins and other labile N-rich carbon substrates with waste water irrigation. This finding is confirming reports from Filip et al. (1999) and Chen et al. (2008). They also found higher activities of various enzymes due to long term waste water irrigation, while Heinze et al. (2014) found lower enzyme activities in the top 2 cm of soil irrigated with treated waste water compared to a fresh water control.

Figure 4-2: Activity of extracellular enzymatic groups of C-cycle (α-glucosidase, β- glucosidase, β-xylosidase and β-cellobiosidase), N-cycle (leucine-aminopeptidase, tyrosine-aminopeptidase and arginine-aminopeptidase) and P-cycle (acid phosphatase) in the different soil treatments under clean and waste water irrigation 92

By adding biochar to the unfertilized soil treatments, a more diverse activity of enzyme involved in carbon cycling was observed. Without biochar addition beta-glu was the main active C cycling enzyme. When biochar is added, the total activities of C cycling enzymes are still the same but more diversely distributed among the five measured enzymes. Also,

Lammirato et al. (2011) found a decrease of beta-glu in soil mixed with chestnut biochar and linked this finding to sorption of this enzyme to the biochar surface. They found an adsorption of 99 % beta-glu to the surface and 30 % reduction in activity. A reduction in beta-glu activity was also found by other researchers (Foster et al. 2016, Zheng et al. 2016).

Table 4-3: Rotated component matrix of principal component analysis

Component 1 2 α-glucosidase -.005 .895 β-xylosidase -.327 .877 N-Acetyl. .588 -.330 Acid phosphatase .623 .677 β-glucosidase .208 .892 β-cellobiosidase .757 -.080 Leucine-aminopep. .873 -.108 Arginine-aminopep. .770 -.104 Tyrosine-aminopep. -.067 .674 pH -.113 .312 Dehydrogenase -.074 -.426 N .612 .195 C .791 -.011 Basal-Resp. -.021 -.622 HWC .864 -.026 Cmik .465 .269

In addition, the activities of N cycling enzymes are increased in the unfertilized treatments with biochar addition. We explain these observations with a more diverse microbial commu-

nity when biochar is applied to soil. For instance, Anderson et al. (2011) found a change in abundance of different N cycling bacterial groups and also Zheng et al. (2016) showed a higher diversity of the bacterial community in rice paddy with biochar addition. Under fertilizer application, this observation is less clear. Furthermore, the total enzymatic activities were found to be lower when fertilizer was applied compared to the unfertilized treatments.

Figure 4-3: Score plot of principal component analysis with explained variance of components in parantheses

This is likely a result of the lower pH values of the treatments fertilized with mineral fertilizer. The findings of Paz-Ferreiro et al. (2014) suggesting that enzymatic activities are influ-

enced by pH and effects of biochar on soil enzymatic activities are both biochar and soil de- pended. The effects of the measured parameters are reduced to two main factors by means of a principal component analysis. Factor loadings (Tab.3) of the components suggest Factor 1 is influenced by the nutrient availability and labile carbon because of two aminopeptidases and

HWC. Factor 2 is affected by high factor loadings of C cycling enzymes and showing a negative connection to the basal respiration. Therefore it may represent treatments with low available carbon contents. However, both factors explain only 56% of total variance. In the score plot (Fig.3.) we found a fairly strong differentiation between waste water and clean water irrigated samples on both factors. Waste water irrigates samples are more located in the upper right corner of the plot showing more nutrients and available carbon The control treatments lying close together and are clearly differentiated on factor 1 from the other treatments. The

BCNAP treatment under waste water irrigation has a unique position most likely reflecting the very high C cycling enzymes.

Conclusions

Biochar and waste water irrigation reduced microbial stress and facilitated a more efficient use of carbon. In contrast, the use of fertilizer increased microbial activity but not abundance and increased carbon losses from soil, most likely due to acidity-induced stress. Biochar may protect carbon in soil from decomposing and therefore sequester SOC as evident by decreasing basal respiration and increasing HWC. Waste water irrigation and biochar application both increased total enzyme activity. In addition, biochar treated soil showed higher diversity of enzymes involved in C and N cycling. This suggests a more diverse microbial community.

Biochar and waste water irrigation both were found to be beneficial for soil microorganisms, therefore having positive effects on soil fertility.

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5. Summary discussion, conclusion and future research needs

One of the main hypotheses of this thesis was that biochar can reduce pathogens from water in a filter system and later be used as fertilizer because of its large surface area and reactivity.

It was concluded that waste water treatments with a biochar filter is possible. The mean pathogen reduction in the filter was 1.8 log units for E.Coli and enterococci but a loading of biochar with nutrients was not found. Especially Mg, K and P contents of biochar were reduced.

However, when the treated water is used for irrigation the loss of nutrients from biochar into the water is not problematic. Despite the lower nutrient content of the filterchar, the crop yields were still significantly higher than the control treatments and not statistically different from the yields obtained when untreated biochar was used. The analysis of plant tissue showed that a direct P fertilizing effect of biochar was mainly responsible for the increases in crop yields. Other authors reported the loading of biochar with diary effluent or effluent from an anaerobic digester (Ghezzehei et al. 2014, Sarkhot et al. 2012, Streubel et al. 2012). It seems that the ability to recover nutrients with biochar from water is controlled by the nature and properties of the waste stream (form of nutrients) and the properties of biochar (sorption properties, surface area, etc.). Especially the properties of biochar can be very specific depending mainly on feedstock for pyrolysis, the production method, degree of oxygen exclu- sion and pyrolysis temperature (Enders et al. 2012, Rajkovich et al. 2011, Steiner 2016). Es- pecially the rice husk biochar used in this study was produced at KNUST in Kumasi, Ghana.

The custom made pyrolysis reactor allows only little monitoring and produces a very ash rich biochar (Atijah 2017). In addition, rice husk is a very unique feed stock because of its relatively low carbon and high silica content (Yalçin und Sevinç 2001).

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Also in the lysimeter study, the rice husk biochar was not able to reduce nutrient leaching and has a low surface area compared to other biochars (Atijah 2017). This may explain why this biochar was not loaded with nutrients. Nevertheless, the hypothesis that biochar can be used in waste water filtration holds true. Although, biochar was not enriched with nutrients it still showed a significant beneficial effect on crop yields.

The hypothesis that biochar can reduce nutrient leaching form soil in UA was tested in chapter 3. In general, the monitoring of nutrient leaching in the UA field trial showed tremendous losses of nitrate and basic cation from the soil, especially when irrigation was above the plant needs. Waste water had a high contribution to the overall nutrient input but showed also negative effects on the soil water retention leading to a more inefficient water use. This was mainly attributed to the potential development of preferential flow paths under waste water irrigation. The reduction of water use efficiency is a novel result and, to our knowledge, has not been shown on the field scale. However, the application of biochar had no effect on the measured parameters. However, several other researchers found a decreasing effect of biochar on nutrient leaching (see discussion in chapter 3). The main reason for our results could also be related to the properties of the rice husk biochar, as already discussed. Furthermore, the high nutrient loads in UA may exceed the retention capacities of biochar. Therefore, the hypothesis that biochar can reduce nutrient leaching cannot be confirmed.

The study on soil biological properties deals with the hypothesis, that biochar and waste water improve the biological properties of soil in UA. Beneficial effects of both, biochar and waste water, on the carbon use efficiency of soil microorganism were reported. A tendency of biochar to sequester carbon in the form of bioavailable organic matter and a more diverse activity

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of enzymes, especially from the cycling of nitrogen and carbon was reported. Therefore, the hypothesis of beneficial impact of the substance soil biology can be verified.

Furthermore, the leading hypothesis that biochar increase the overall soil fertility was mainly confirmed. The use of biochar as soil amendment increased the soil carbon stocks (Häring et al. 2017). In the Tamale field trial biochar increased fresh matter yields during the first five crop cycles by 15% and by 9% after two years. Furthermore, soil moisture was increased by

9% when biochar was applied under clean water irrigation (Akoto-Danso et al. 2018). This result is also in line with the increases in crop yield reported in chapter 2. However, biochar did not increase or decrease gaseous nitrogen emissions from soil (Manka'busi et al. 2018).

Apart from the effects on nutrient leaching biochar increased soil fertility in the Tamale UA field trial.

The greenhouse trial in chapter 2 also gives an explanation for the increases in crop yields.

Most likely the release of phosphorus from the ash fraction of the biochar caused the better crop performance. This effect was declining after the first few crop cycles.

Unfortunately, the results are less clear than expected. However, beneficial effects of biochar mainly on the crop yields could be shown. This is from a farmer perspective definitely the most important aspect. But there are still remaining questions. Can rice husk biochar have further positive effects at higher application rates or with repeated applications, like often reported in the literature?

Also the treatment of waste water with a biochar filter may reduce substances that cause alteration of hydrological properties of soil. These are mostly related to lipids, humic substances and other organic compounds (Arye et al. 2011). Therefore, a systematic examination of bio-

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char properties related to filter use is needed. In addition, the influence of filterchar on the biological soil properties compared to untreated biochar is not comprehensively assessed. The term biochar is used for a wide range of material made from different feedstocks like wood, leafy biomass, manure, bones and many more. The production conditions are likewise showing a great degree of variation (e.g. slow or fast pyrolysis, hydrothermal carbonization)

(Steiner 2016). A comprehensive tool is needed to predict biochar properties and the effect on soil properties.

Furthermore, some standard methods of soil biology like the chloroform fumigation method to explore microbial bound carbon and methods to measure enzymatic activities are giving doubtful results. Due to sorption properties of biochar, these methods might be biased. An evaluation and possible adjustments of the methods are essential (Lehmann et al. 2011).

In conclusion, there are still a lot of open questions in biochar research. A high potential to improve soils could be shown in this thesis as well as in the literature. Biochar was able to increase crop yields and reduce pathogen concentration in irrigation water with a simple low cost filter.

Further systematical research on biochar properties, their agronomic potentials and filter abili- ties to reduce pathogens and mineral and organic compounds from water is still needed.

Apart from biochar related effects, the use of waste water in UA showed potentials to improve soil health, increase the nutrient input and therefore reduce the fertilizer amounts needed. Alt- hough negative impacts on hydrological properties of the soil have been observed in this thesis and can be found in the literature. In the future, when fresh water will become more scare

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as predicted (Burgess et al. 2015), the reuse of polluted water with sustainable filter systems in agriculture will become even more important.

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6. Acknowledgements

First of all, I want to thank my parents Christel and Jürgen Werner for their support and patience all my life. I want to say “Thank you” to all the friends who helped me along the way.

Especially, Linda.

I want to thank my supervisor Prof. Dr. Bernd Marschner, who gave me so much freedom, guidance and support in my work. I like to thank my second supervisor Prof. Dr. Andreas

Bürkert. Furthermore, the team of the working group Soil Science and Soil Ecology Dr.

Stephanie Heinze, Julian Heitkötter and Michael Herre.

I am grateful for the wonderful help and friendship of Isaac K. Asirifi and Isaac Asirifi in the field and in the laboratory of the University for Development Studies in Tamale.

Last but not least, I want to thank the team of the laboratory of Physical Geography at the In- stitute for Geography at the Ruhr-University Bochum, Sabine Fröhlich, Heidrun Kerkhoff,

Bettina Röhm and Katja Gonschorek for their support and patience.

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7. Curriculum Vitae

Steffen Werner [email protected]

Born 31.07.1982 in Unna, Germany

Education:

 2010 - 02/2012: M.Sc. in Geography (City- and Landscape Ecology) Ruhr-Universität Bochum

 2007 - 2010: B.Sc. in Geography, Ruhr-Universität Bochum

 2004 - 2007: Abitur Westfalen-Kolleg, Dortmund

Work Experience:

 Since 05/2013: Research assistant in the BMBF project “Urban Food Plus - African- German partnership to enhance resource use efficiency and improve food security in urban and peri-urban agriculture of West African cities”

 01/2012 - 04/2012: Internship at Max-Plank Institute for Biogeochemistry, Jena. Topic: Biochar as a soil amendment. Assistance in green house experiment and measuring of PAH in soil water from biochar field plots.

 02/2011 – 04/2013: Student assistant for Prof. Dr. Marschner in the working group “Soil Science /Soil Ecology” at the Institute for Geography Ruhr-Universität Bochum.

 02/2010 - 01/2011: Student assistant in the M.Sc. Program” Interdisciplinary Environmental Science” at the FernUniversität Hagen.

 07 - 08/2009 Internship at Kuhlmann & Stucht Environmental Planning, Bochum. Environmental impact assessment and compensation.

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Erklärung

Ich versichere an Eides statt, dass ich die eingereichte Dissertation selbstständig und ohne un- zulässige fremde Hilfe verfasst, andere als in ihr angegebene Literatur nicht benutzt und dass ich alle ganz oder annähernd übernommenen Textstellen sowie verwendete Grafiken, Tabel- len und Auswertungsprogramme kenntlich gemacht habe. Außerdem versichere ich, dass die vorgelegte elektronische mit der schriftlichen Version der Dissertation übereinstimmt und die

Abhandlung in dieser oder ähnlicher Form noch nicht anderweitig als Promotionsleistung vorgelegt und bewertet wurde.

Bochum, den 20.2.2018

Steffen Werner

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Vorabveröffentlichung

Das Kapitel: “2. Agronomic benefits of biochar as a soil amendment after its use as waste water filtration medium” wurde bereits in der Zeitschrift “Environmental Pollution” (2018), 233

Seiten: 561-568 veröffentlicht. Der Hauptautor hatte die Idee zum gesamten Experiment. Er führte das Gewächshausexperiment durch, wertete die Daten aus und verfasste das Manu- skript. Korbinian Kätzel führte das Filtrationsexperiment durch. Alle anderen Co-Autoren ga- ben Kommentare zum Konzept und Manuskript.

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