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A FRAMEWORK FOR VALUING THE HEALTH BENEFITS OF IMPROVED BATHING WATER QUALITY IN THE RIVER IRVINE CATCHMENT EK Johnson 1 , D Moran 2 and AJA Vinten 3 1 592 Quail Court Kingston, Ontario, K7M 8Z3, Canada, E-mail: elaine_k_johnson@ hotmail.com; 2 Land Economy and Environment Research Group, SAC, West Mains Road, Edinburgh EH6 5AT, UK; 3 Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen, AB15 8QH, UK SUMMARY A model predicting bathing water concentrations of Escherichia coli from livestock in the Irvine catchment has been adapted for faecal streptococci (FS). This has been used to predict risk of bather illness by extrapolation of published data on bather FS exposure vs. incidence of gastro-enteritis. Simulated reduction in the risk of illness by reduced faecal loading was multiplied by a willingness to pay for risk reduction to estimate the annual benefits of mitigation. Benefits of reducing loading by 95% at Irvine Beach were about £600 k pa. Estimated annualised costs of best management practises (BMPs) across the catchment were higher (> £1 m), and it is very unlikely that 95% mitigation is achievable with current stocking rates. However, more work on calibration and validation of this framework is needed. INTRODUCTION Current research is exploring applications of BMPs which reduce agriculture’s contribution of faecal bacteria to coastal bathing waters. An economic incentive is required for implementation of these measures. This paper presents a draft framework for valuing the health benefits to society of reducing faecal loading to bathing waters which may be achieved through BMP implementation. By relating a BMP-induced reduction in faecal loading to a decrease in risk of illness, benefits can be calculated using an estimate of society’s willingness to pay for reduction in swimming-associated illness. MODEL FRAMEWORK Three components were involved in evaluating reduced faecal loading in the Irvine catchment in Ayrshire (Figure 1). These will subsequently be linked to cost/ effectiveness of mitigation. Predict Bathing Water Quality Relate Bathing Water Quality to Risk of Illness Determine Value of Reduced Faecal Loading Justification of BMPs??? Figure 1: Steps involved in determining the value of faecal loading reductions in the Irvine catchment 211
Predicting Bathing Water Quality Vinten et al. (2004) devised a spreadsheet model to predict E. coli in bathing water by accounting for inactivation, sedimentation, transport and mixing in the Irvine Beach/River Irvine catchment system for various loading in the catchment. We have modified this model so FS levels in bathing waters could be predicted rather than E. coli, using changes to key parameter values, summarised in Table 1. The relative levels in animal faeces and inactivation factors show considerable variation in the literature, so these figures should only be considered indicative at this stage. Table 1: Correction factors used with the model of Vinten et al. (2004) to predict FS concentrations in bathing water instead of E. coli Parameter Correction factor for FS/E. coli References Levels in animal faeces 5.6 Sinton et al., 1993 Reddy et al., 1981 Half lives in soil and water 0.7 Sherer et al., 1992 in Merrilees, 2004 Bathing water quality predictions were made for current and 25–95% reduction in livestock loadings. Summer discharge percentiles were calculated using 14 years (1989-2002) of River Irvine data. Bathing Water Quality and Risk of Illness A dose–response function between the concentration of FS in bathing water and the probability of contracting gastro-enteritis was determined by Kay et al. (1994) and Wyer et al. (1999), based on risk of contracting illness from bathing water quality determined by the World Health Organization using a probability density function of bathing water quality throughout Europe (WHO, 2001). This relationship has data for up to 12% probability of infection, and these data were fitted to an exponential function (eq. 1) to predict risk of illness, including extrapolation where necessary beyond the data range. - Risk of illness = 1- e 0. 000218c (1) Where c = concentration of FS in bathing water (cfu/100mL). This equation was linked to model simulations of FS in bathing water to give the risk of contracting gastro-enteritis as a function of faecal loading and river discharge (Step 2 in Figure 1). Economic Valuation of Reduced Risk of Illness Consumer willingness to pay (WTP) for a reduction in risk of illness resulting from swimming in contaminated waters was determined using a benefit transfer of a contingent valuation used in a previous study in England and Wales (EFTEC, 2002). The EFTEC study determined consumers’ WTP for a reduction in risk of illness from swimming in contaminated bathing water. Valuations from the study indicate that respondents are willing to pay between £1.10 and £2.00 per household per year 212
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International Water Association AGR
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2006 Conference Organising Committe
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Theme 2: Cost-effectiveness of Best
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Poster Presentations The Farm Soils
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viii
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managers need support in understand
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During the past 20 years, it became
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infiltration); and (4) capture, sto
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DOMINATING PARAMETERS OF IMPAIRMENT
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Using the results of the unsupervis
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Kohonen T (2001). Self-Organizing M
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WATER FRAMEWORK DIRECTIVE IMPLEMENT
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Table 1: Modelled total annual loss
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• It should be possible to apply
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Scottish Executive against 18 measu
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REFERENCES Anthony S, Betson M, Lor
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ased on the ‘drainage basin’ in
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management practices’ (BMPs) toge
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It is envisaged that these data wil
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testing (including climate change)
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Council of the European Communities
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DECREASING THE NITROGEN SOIL SURFAC
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Table 1: Overview of the measures c
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Table 2: Costs (C), effects (E) and
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Figure 2: Combination of ‘best av
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MATERIALS AND METHODS At the 5-km 2
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REFERENCES Jordan P, Menary W, Daly
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Although the TMDL programme origina
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grassland and heather moorland, sup
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Given that the release of P from th
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to the underlying causes, and thus
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All water body use attainment infor
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indicate the possible presence of p
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DEVELOPMENT AND IMPLEMENTATION OF M
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BMP is being implemented and the ap
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THE USE OF PONDS TO REDUCE POLLUTIO
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established pond/wetland for nutrie
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Table 1: Hydraulic load, mean water
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Comparable SS removals have been re
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Reddy GB, Hunt PG, Phillips R, Ston
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In general, the combinations of mea
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final word on the POMs selection an
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CONCLUSIONS The ERBD project team i
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Table 1: A summary of the measures
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Table 3: A summary of the represent
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cost (£'000/farm) or reduction in
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ECONOMIC IMPLICATIONS OF MINIMISING
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spread cattle slurry in the autumn
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£25,000. The investment in trailin
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Studies on a drained clay soil at B
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REFERENCES Anon (2000). Fertiliser
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(Haygarth and Jarvis, 1999). The vo
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Application Representative farm sys
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Table 2: Modelled cost-curve for th
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ASSESSING THE SIGNIFICANCE OF DIFFU
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In the absence of data on the sourc
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Magnitude of Impacts The magnitude
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D. Use relative area of farm and wh
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ADAS has developed a matrix for Def
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Dickson JW, Edwards T, Jeffrey WA,
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60% phosphorus and 50% nitrogen of
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RESULTS AND DISCUSSION Landscape St
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was contributed to the low vegetati
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iological uptake in a grassed area.
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Tim US, Jolly R and Liao HH (1995).
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to control SS and P loads from agri
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Total P inputs in fertilisers and m
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Within the Teme catchment, largest
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A RISK ASSESSMENT AND MITIGATION ST
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Environmental Monitoring The primar
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BMP measure 1 (exclusion of stock f
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(a) With reference to the increase
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ACKNOWLEDGEMENTS SAC acknowledges f
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The Environment Sensitive Farming (
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improved further as a result of att
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to do more to reduce pesticide impa
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MANAGING DIFFUSE POLLUTION FROM A F
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turbulent air mixing. The effect th
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Although nitrate leaching can be re
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infiltration of water sheeting off
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Nisbet TR, Orr H and Broadmeadow S
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anthropogenic activities are pollut
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monitoring is determined up front b
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(USEPA). Nevertheless, by applying
Page 169 and 170: • Sampling equipment •Laborator
Page 171 and 172: Reinert RE, Knuth BA, Kamrin MA and
Page 173 and 174: Tier 3 - Tier 3 of LMCs is planned
Page 175 and 176: policy literature, although this is
Page 177 and 178: Figure 1: Individual-collective spe
Page 179 and 180: • tailoring activities to local c
Page 181 and 182: ACKNOWLEDGEMENTS The support of the
Page 183 and 184: THE EFFECT OF DIFFUSE POLLUTION FRO
Page 185 and 186: equires the Minister to designate a
Page 187 and 188: protection and restoration, sustain
Page 189 and 190: expensive. One-to-one contact becom
Page 191 and 192: farmers. In England, recent policy
Page 193 and 194: practices but, hopefully, the chang
Page 195 and 196: A CASE STUDY: ADOPTION OF BEST MANA
Page 197 and 198: The approaches taken by Brittany to
Page 199 and 200: MANURE TREATMENT By January 2005, t
Page 201 and 202: REGULATORY OPTIONS FOR THE MANAGEME
Page 203 and 204: There are also measures that contro
Page 205 and 206: widely recognised as needing much a
Page 207 and 208: ploughed, of rivers and streams tha
Page 209 and 210: is the only mechanism identified fo
Page 211 and 212: PHOSPHORUS STORAGE IN FINE CHANNEL
Page 213 and 214: structure and minimum level of main
Page 215 and 216: REFERENCES May L, Place C, O’Hea
Page 217 and 218: LOUND CATCHMENT PROJECT: WORKING WI
Page 219: MINIMISING THE PRESSURES AND IMPACT
Page 223 and 224: Risk of illness percentages were ca
Page 225 and 226: Table 4: Expected lifetime benefits
Page 227 and 228: DETERMINATION OF THE VETERINARY ANT
Page 229 and 230: Thin Layer Chromatography The sampl
Page 231 and 232: Table 2: Regression functions and c
Page 233 and 234: OPPORTUNITIES AND CONSTRAINTS FOR U
Page 235 and 236: to land managers and agency staff t
Page 237 and 238: stakeholders, together with their i
Page 239 and 240: REFERENCES EC (2000). Directive 200
Page 241 and 242: A third scenario was applied to Clu
Page 243 and 244: Based on a detailed distribution of
Page 245 and 246: could be misleading. The results of
Page 247 and 248: TACKLING DIFFUSE NITRATE POLLUTION:
Page 249 and 250: AMMONIA VOLATILISATION FROM CATTLE
Page 251 and 252: and 27% of the soil surface at 80 m
Page 253 and 254: FIELD TESTING OF MITIGATION OPTIONS
Page 255 and 256: techniques can significantly reduce
Page 257 and 258: NITRATE CONTAMINATION OF GROUNDWATE
Page 259 and 260: MATERIALS AND METHODS At two UK sit
Page 261 and 262: ACKNOWLEDGEMENTS Funding of this wo
Page 263 and 264: y standard methods and fresh, end o
Page 265 and 266: comparable to those in water draini
Page 267 and 268: Results may be influential in deter
Page 269 and 270: • numbers and distribution of liv
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Using this method of classification
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Table 5: Results of land use scenar
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CONCLUSIONS As a decision support t
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types. This paper reports results f
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N Losses in Drainage Water Mean nit
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SOIL AND CROP MANAGEMENT EFFECTS ON
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treatments, typically 10 storm even
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Tramline Effects In both years, obs
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Notes 278
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