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Is nitrate harmful to humans? Are the current limits for nitrate concentration in drinking water justified by science? There is substantial disagreement among scientists over the interpretation of evidence on the issue. There are two main health issues: the linkage between nitrate and (i) infant methaemoglobinaemia, also known as blue baby syndrome, and (ii) cancers of the digestive tract. The evidence for nitrate as a cause of these serious diseases remains controversial. On one hand there is evidence that shows there is no clear association between nitrate in drinking water and the two main health issues with which it has been linked, and there is even evidence emerging of a possible benefit of nitrate in cardiovascular health. There is also evidence of nitrate intake giving protection against infections such as gastroenteritis. Some scientists suggest that there is sufficient evidence for increasing the permitted concentration of nitrate in drinking water without increasing risks to human health. However, subgroups within a population may be more susceptible than others to the adverse health effects of nitrate. Moreover, individuals with increased rates of endogenous formation of carcinogenic N‐nitroso compounds are likely to be susceptible to the development of cancers in the digestive system. Given the lack of consensus, there is an urgent need for a comprehensive, independent study to determine whether the current nitrate limit for drinking water is scientifically justified or whether it could safely be raised.

The computer model described simulates changes in soil mineral nitrogen and crop uptake of nitrogen by computing on a daily basis the amounts of N leached, mineralized, nitrified and taken up by the crop. Denitrification is not included at present. The leaching submodel divides the soil into layers, each of which contains mobile and immobile water. It needs points from the soil moisture characteristic, measured directly or derived from soil survey data; it also needs daily rainfall and evaporation. The mineralization and nitrification submodel assumes pseudo-zero order kinetics and depends on the net mineralization rate in the topsoil and the daily soil temperature and moisture content, the latter being computed in the leaching submodel. The crop N uptake and dry-matter production submodel is a simple function driven by degree days of soil temperature and needs in addition only the sowing date and the date the soil returns to field capacity, the latter again being computed in the leaching submodel. A sensitivity analysis was made, showing the effects of 30% changes in the input variables on the simulated amounts of soil mineral N and crop N present in spring when decisions on N fertilizer rates have to be made. Soil mineral N was influenced most by changes in rainfall, soil water content, mineralization rate and soil temperature, whilst crop N was affected most by changes in soil temperature, rainfall and sowing date. The model has so far been applied only to winter wheat growing through autumn, winter and spring but it should be adaptable to other crops and to a full season.The model was validated by comparing its simulations with measurements of soil mineral N, dry matter and the amounts of N taken up by winter wheat in experiments made at seven sites during 5 years. The simulations were assessed graphically and with the aid of several statistical summaries of the goodness of fit. The agreement was generally very good; over all years 72 % of all simulations of soil mineral N to 90 cm depth were within 20 kg N/ha of the soil measurements; also 78 % of the simulations of crop nitrogen uptake were within 15 kg N/ha and 63% of the simulated yields of dry matter were within 25 g/m 2 of the amounts measured. All correlation coefficients were large, positive, and highly significant, and on average no statistically significant differences were found between simulation and measurement either for soil mineral N or for crop N uptake. c r o P t o w n i°n '* w a s applied seems very variable. Powlson et al. (1983) found it to range from 51 to In 1985 farmers in England and Wales used nearly 84% in field experiments on winter wheat spread 1-3 million tonnes of fertilizer nitrogen, of which over 3 years. With spring barley, Dowdell et al. roughly 350000, worth over £100 million, went to (1984) found values between 46 and 54% in lysimeter winter wheat (C. D. Kershaw, private communica-experiments. Quite a lot of the unused N will be tion). Although cereals are relatively efficient users immobilized in soil organic matter an...

This paper shows how the wavelet transform can be used to analyse the complex spatial covariation of the rate of nitrous oxide (N 2 O) emissions from the soil with soil properties that are expected to control the evolution of N 2 O. We use data on N 2 O emission rates from soil cores collected at 4-m intervals on a 1024-m transect across arable land at Silsoe in England. Various soil properties, particularly those expected to influence N 2 O production in the soil, were also determined on these cores.We used the adapted maximal overlap discrete wavelet transform (AMODWT) coefficients for the N 2 O emissions and soil variables to compute their wavelet covariances and correlations. These showed that, over the transect as a whole, some soil properties were significantly correlated with N 2 O emissions at fine spatial scales (soil carbon content), others at intermediate scales (soil water content) and others at coarse spatial scales (soil pH). Ammonium did not appear to be correlated with N 2 O emissions at any scale, suggesting that nitrification was not a significant source of N 2 O from these soils in the conditions that pertained at sampling.We used a procedure to detect changes in the wavelet correlations at several spatial scales. This showed that certain soil properties were correlated with N 2 O emissions only under certain conditions of topography or parent material. This is not unexpected given that N 2 O is generated by biological processes in the soil, so the rate of emission may be subject to one limiting factor in one environment and a different factor elsewhere. Such changes in the relationship between variables from one part of the landscape to another is not consistent with the geostatistical assumption that our data are realizations of coregionalized random variables.

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A number of conceptual models for solute leaching in soil are reviewed, quantitatively compared and classified as far as possible within a framework that makes distinction between deterministic and stochastic, mechanistic and functional and rate and capacity models. They are also discussed with reference to their purpose (viz research or management), complexity, flexibility, transferability and usefulness for field soils. The basic assumptions and structures of the models impose definite limits on the ways in which they can be used. The spatial variability of soil properties caused problems for deterministic models using rate parameters, but stochastic elements can be incorporated in these models. Simpler capacity-type models and non-mechanistic stochastic models offer other answers to this problem. Few data sets are available for testing a range of models and few models have been tested on a range of soil types, and very few models have much demonstrable ability to simulate transient field leaching conditions. Examples of a models of field solute transport. Journal of an approximate analytic method of computing solute profiles with dispersion in soils. Journal of Environmental Qualit-v 11, 151-155. ROUSELLE, V. 1913. Le mouvement des nitrates dans le sol et ses consequences relative a I'emploi du nitrate de soude. Annales de la Science Agronomique, 4th Series, pp. 97-1 15. 379-388. 35, 1358-1364. 9-76015. July I976 pp. 235-242. US/EPA:

Mineralization of soil organic nitrogen measured in laboratory incubation experiments on Rothamsted soils with contrasting histories was most appropriately expressed by the simple zero-order relationship NI= kf in which Nl is the amount of N mineralized in time t. The rate constants ( k ) were well related to the absolute temperature by the Arrhenius equation. The approach in which 'potentially mineralizable N' (No) is mineralized with first-order kinetics could not be applied to these data.When the soils were incubated with added ammonium chloride, the increase in nitrate-N and the decline in ammonium-N were both linear with time, but were equal to each other in only one of the soils. These linear relationships did not reflect true zero-order kinetics because the rates of ammonium-N decline and nitrate-N production both depended on the initial ammonium concentration. The Arrhenius relationships showed no significant difference between mineralization and nitrification in their sensitivity to temperature.

Abstract. The model described divides the soil into layers and considers two categories of water, mobile and immobile, in each layer. It has two main parameters, one a measure of the soil's capacity to hold water and thence to retain solutes against leaching, and the other a measure of the ease with which water can pass through the soil and carry solutes with it. These are, in effect, capacity and rate parameters, and the model is unusual in having both. They can be estimated from the percentages of clay and other soil components. The rate parameter varied appreciably between plots in the field but in a consistent manner. The model has been validated against field experiments following the vertical movement of solute applied to the soil surface and allowed to leach, and the paper includes one such test.