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Health risk assessment associated with the reuse of compost, urine and greywater in agricultural field in sahelian climate.

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par Alexis Loukou BROU
Fondation 2iE - Master Environnement option Eau et Assainissement 2014
  

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Abbreviations

Ameli-EAUR Amélioration de l'accès à l'Eau potable et à l'Assainissement en milieu Urbain et Rural

C+TW Compost and Top Water

C+U+GW Compost, Urine and Greywater

DALY Disability Adjusted Life Years

DW Dry weight

EPA Environment Protection Agency

FAO Food and Agriculture Organization of United Nations

FW Fresh weight

GW Greywater

JICA Japanese International Cooperation Agency

NoF Non Fertilizer

Pinf Probability of infection

PPPY Per Person Per Year

Pyr Annual Probability risk infection

QMRA Quantitative Microbial Risks Analysis

UNICEF United Nations Organization for Child and Education Found

U+TW Urine and Top Water

W/V Weight/Volume

List of tables

Table 1: Different routes of exposure of farmers by irrigation with greywater 2

Table 2: Different parameters which are analyzed in the matrix 15

Table 3: Different exposure scenarios and pathways which farmers and consumers can be exposed in different cases 21

Table 4: Summary of dose-response parameters for exponential and beta-Poisson models from various enteric pathogen ingestion studies 23

Table 5: Annual probabilities of Salmonella and Ascaris infection associated with the ingestion of soil combined with compost and consumption of lettuce 25

Table 6: Annual probabilities of Salmonella infection associated with the ingestion of soil combined with urine and consumption of lettuce 26

Table 7: Annual probabilities of Salmonella infection associated with the soil and greywater ingestion combined with greywater and lettuce consumption 27

Table 8: Annual probabilities of Salmonella and Ascaris infection associated with the soil and greywater ingestion combined with compost, urine and greywater and lettuce consumption 28

Table 9 : Probabilistic values of different treatments compared with the WHO guideline values of the risk. 29

Table 10: Probabilistic values of Greywater and Compost, Urine and Greywater treatments compared with the WHO guideline values of the risk. 30

Table 11: Probabilistic values of different treatments compared with the WHO guideline values of the risk. 31

List of figures

Figure 1: Experimental site of Kamboinsé (source Google earth) 2

Figure 2: Experimental design in the site 14

Figure 3: Illustration of step of Salmonella analysis 18

Figure 4: Steps of calculation of Monte Carlo Method 23

Figure 5: Annual infection risks of Salmonella and Ascaris in function of scenarios compared with WHO guideline value. 25

Figure 6 : Annual infection risks of Salmonella in function of scenarios compared with WHO guideline value. 26

Figure 7 : Annual infection risks of Salmonella in function of scenarios compared with WHO guideline value. 27

Figure 8: Annual infection risks of Salmonella and Ascaris in function of scenarios compared with WHO guideline value. 28

Figure 9 : Probabilistic values of all treatments compared with the WHO guideline values of risk for soil ingestion scenario 29

Figure 10 : Probabilistic values of Greywater and Compost, Urine and Greywater treatments compared with the WHO guideline values 30

Figure 11: Probabilistic values of all treatments compared with the WHO guideline values of risk for lettuce consumption scenario 31

Table of contains

Dedication i

Acknowledgements ii

Abstract iii

Résumé iv

Abbreviations vi

List of tables vii

List of figures viii

I. Introduction 1

II. LITERATURE REVIEW 3

1. Generalities on health risk assessment 4

1.1. Health risk assessment 4

1.2. Steps of health risk assessment 5

1.3. Microbial risk assessment 6

2. Health risk assessment for farmers 6

2.1. Spreading compost 6

2.2. Spreading urine 7

2.3. Watering greywater 8

3. Health risk assessment for consumers 10

III. MATERIAL AND METHODS 12

1. Experimental site 13

2. Sampling and data collection 15

2.1. Initial statement of the experimental site 15

2.2. Microbiological analysis of matrix (soil, compost, urine, and greywater) 15

2.3. Following up indicators of pathogen on lettuce leave 19

3. Quantitative Microbial Risk Analysis (QMRA) methods 19

3.1. Hazard identification 19

3.2. Exposure assessment 19

3.3. Dose-response assessment 21

3.4. Risk characterization 23

IV. RESULTS AND DISCUSSION 24

1. Results 25

1.1. Quantitative Microbial Risk Assessment from different treatments 25

1.2. Comparison of the probabilistic values of different treatments related with the scenarios 29

2. Discussion 32

2.1. Quantitative Microbial Risk Assessment from each treatment. 32

2.2. Comparison of the probabilistic values of different treatments related with the scenarios 35

IV. Conclusion and perspectives 38

V. References 39

Annex i

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