Iain R. Lake

Applying geographical information systems (GIS) to environmental and resource economics

Many of the analyses undertaken byenvironmental and resource economics areintimately concerned with spatial variations.This article examines the contribution whichGeographical Information Systems (GIS) mayprovide in incorporating the complexities ofthe spatial dimension within such analyses. Thepaper introduces the reader to the types ofdata handled by a GIS and overviews thepractical functionality offered by suchsystems. A brief literature review issupplemented by a number of more detailedapplications illustrating various GIStechniques which may be of use to the appliedenvironmental or resource economist.

Evaluating factors influencing groundwater vulnerability to nitrate pollution: developing the potential of GIS

The 1991 EU Nitrate Directive was designed to reduce water pollution from agriculturally derived nitrates. England and Wales implemented this Directive by controlling agricultural activities within their most vulnerable areas termed Nitrate Vulnerable Zones. These were designated by identifying drinking water catchments (surface and groundwater), at risk from nitrate pollution. However, this method contravened the Nitrate Directive because it only protected drinking water and not all waters. In this paper, a GIS was used to identify all areas of groundwater vulnerable to nitrate pollution. This was achieved by constructing a model containing data on four characteristics: the quality of the water leaving the root zone of a piece of land; soil information; presence of low permeability superficial (drift) material; and aquifer properties. These were combined in a GIS and the various combinations converted into a measure of vulnerability using expert knowledge. Several model variants were produced using different estimates of the quality of the water leaving the root zone and contrasting methods of weighting the input data. When the final models were assessed all produced similar spatial patterns and, when verified by comparison with trend data derived from monitored nitrate concentrations, all the models were statistically significant predictors of groundwater nitrate concentrations. The best predictive model contained a model of nitrate leaching but no land use information, implying that changes in land use will not affect designations based upon this model. The relationship between nitrate levels and borehole intake depths was investigated since there was concern that the observed contrasts in nitrate levels between vulnerability categories might be reflecting differences in borehole intake depths and not actual vulnerability. However, this was not found to be statistically important. Our preferred model provides the basis for developing a new set of groundwater Nitrate Vulnerable Zones that should help England and Wales to comply with the EU Nitrate Directive.

Modelling environmental influences on property prices in an urban environment

The aim of this research was to assign money values to the negative impacts associated with road development, more specifically noise and visual intrusion. These impacts do not have observable prices and so have to be calculated indirectly. One way of doing this is to examine their effect upon house prices. The valuations such a method produces can then be included alongside other costs and benefits in the appraisal of a road development. However in order to calculate these prices, one also has to control for the many other factors that affect house prices, in addition to specifying the two road variables. In previous research this has required much time and effort which has consequently limited the scope of such studies. The aim of this project was to use a geographical information system (GIS) and large-scale digital data to derive all the required variables in a quick and efficient manner. The flexibility of a GIS allows a large number of possible explanatory variables to be calculated, leading to a large and complex dataset. This paper describes how such a dataset was modelled and price estimates for road noise and the visual intrusion extracted. It concludes by commenting upon the benefits of using GIS in this type of study and considers the main limitations to their wider adoption.

Using GIS and large-scale digital data to implement hedonic pricing studies

This paper describes how a standard GIS package can be used to convert large-scale vector digital data (point, line and annotation features) into polygons using standardised and replicable methods. Building area, garden and land use polygons are all derived from such data (Ordnance Survey LandLine.Plus). These entities are then combined with further sources of digital data to derive more refined information such as property types. Finally, complex DEMs are developed for use in visibility studies. The variables calculated are subsequently employed in a property valuation study where many are found to be significant determinants of property price. The main exception is variables relating to viewsheds, although it is argued that this does not invalidate the techniques used in their deviation but highlights the difficulties involved in modelling a large number of variables in a property price analysis.

A re-evaluation of the impact of temperature and climate change on foodborne illness

The effects of temperature on reported cases of a number of foodborne illnesses in England and Wales were investigated. We also explored whether the impact of temperature had changed over time. Food poisoning, campylobacteriosis, salmonellosis, Salmonella Typhimurium infections and Salmonella Enteritidis infections were positively associated (P<0.01) with temperature in the current and previous week. Only food poisoning, salmonellosis and S. Typhimurium infections were associated with temperature 2-5 weeks previously (P<0.01). There were significant reductions also in the impact of temperature on foodborne illnesses over time. This applies to temperature in the current and previous week for all illness types (P<0.01) except S. Enteritidis infection (P=0.079). Temperature 2-5 weeks previously diminished in importance for food poisoning and S. Typhimurium infection (P<0.001). The results are consistent with reduced pathogen concentrations in food and improved food hygiene over time. These adaptations to temperature imply that current estimates of how climate change may alter foodborne illness burden are overly pessimistic.

The Effects of Weather and Climate Change on Dengue

Background There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors. Methods and Findings Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5°C, but Tmin values above 18°C showed a rapidly increasing effect. Maximum temperature above 20°C also showed an increasing effect on dengue incidence with a peak around 32°C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant. Conclusions Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather–health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue.

The Axford Debate Revisited: A Case Study Illustrating Different Approaches to the Aggregation of Benefits Data

Recent debate following the rejection of the Environment Agency case regarding an application for water abstraction at Axford on the River Kennet has focused upon the benefits procedure employed for aggregating non-user benefits which underpinned the economic case put forward by the Agency (although this was not the reason cited by the inquiry for rejection of the case). Commentators have seen this case as setting an unfortunate precedent for the use of economic assessments in such resource management issues. The paper presents a number of highly tractable alternative methods for the aggregation of benefits estimates designed to address the central problems of the definition of a relevant aggregation population and a potential decay of values with increasing distance from a given valuation site. These methods are tested using data obtained from a national survey of non-users of a specific natural area. Results from this application indicate that simpler approaches such as that used at the Axford inquiry may result in aggregate benefits estimates which are very substantially larger than those produced by our proposed alternative approaches to aggregation.

Climate Variability and Dengue Fever in Warm and Humid Mexico

Multiple linear regression models were fitted to look for associations between changes in the incidence rate of dengue fever and climate variability in the warm and humid region of Mexico. Data were collected for 12 Mexican provinces over a 23-year period (January 1985 to December 2007). Our results show that the incidence rate or risk of infection is higher during El Niño events and in the warm and wet season. We provide evidence to show that dengue fever incidence was positively associated with the strength of El Niño and the minimum temperature, especially during the cool and dry season. Our study complements the understanding of dengue fever dynamics in the region and may be useful for the development of early warning systems.

Microbiological surveillance of private water supplies in England - the impact of environmental and climate factors on water quality.

A passive surveillance system captured information on 34,904 microbiological samples from 11,233 private drinking water supplies within England as well as the associated constructional, climatic and environmental variables. Escherichia coli was detected in 6588 (18.87%) of samples and at least one positive sample was detected from 3638 (32.39%) of sites. However, this estimate of supplies failing to meet the European drinking water E. coli standard was probably an underestimate as the more samples taken per supply, the more likely the supply was to fail. A multivariable model of private water supplies data showed a strong seasonal impact, with samples between January and May being significantly less contaminated with E. coli than samples between June and December. Samples from springs (OR 2.5, CI 2.0-3.1) or surface waters (OR 2.4, CI 0.8-7.0) were more likely to fail than groundwater sources, as were supplies with no effective treatment (OR1.8, CI 1.5-2.3). Commercial supplies were less likely to fail than domestic supplies (OR 0.63, CI 0.48-0.83) and the probability of failure was linearly associated with the density of sheep in the area and rainfall on the previous day. A Monte Carlo modelling approach was used to estimate that, had sufficient samples been taken, 54% (95% confidence intervals 49-59%) of all private water supplies in England were likely to be unsatisfactory. These findings will be able to inform risk assessments of private water supplies prior to microbiological results being available.

A systematic review of analytical observational studies investigating the association between cardiovascular disease and drinking water hardness.

The aim of this study is to systematically review and critically assess analytical observational epidemiology studies investigating the association between levels of drinking water hardness and cardiovascular disease. We searched electronic databases and used standardised forms to extract data and assess study quality. Of 2,906 papers identified, 14 met the inclusion criteria (nine case control and five cohort studies). Of the nine case control studies, seven examined both drinking water magnesium and calcium and risk of death from cardiovascular disease. A pooled odds ratio showed a statistically significant inverse association between magnesium and cardiovascular mortality (OR 0.75 (95%CI 0.68, 0.82), p < 0.001). Only two studies reported a statistically significant effect for calcium. Substantial heterogeneity between studies made calculation of a summary estimate for drinking water calcium inappropriate. Of three cohort studies reviewed, two were of good quality. A weak suggestion that soft water was harmful in females and possibly associated with a slightly greater risk of sudden death was reported, but there was no association between water hardness and mortality from stroke or cardiovascular disease. This study found significant evidence of an inverse association between magnesium levels in drinking water and cardiovascular mortality following a meta-analysis of case control studies. Evidence for calcium remains unclear.