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Fluoride content in grass as related to atmospheric fluoride concentrations: a simplified predictive model
Agriculture, Ecosystems and Environment, 37 ( 1991 ) 257-273
257
Elsevier Science Publishers B.V., Amsterdam
Fluoride content in grass as related to atmospheric fluoride concentrations: a simplified predictive model L.J. van der Eerden Research Institute for Plant Protection, Department of Ecology, Binnenhaven 12, 6 700 G W Wageningen, Netherlands (Accepted 26 March ! 991 )
ABSTRACT Van der Eerden, L.J., 1991. Fluoride content in grass as related to atmospheric fluoride concentrations: a simplified predictive model. Agric. Ecosystems Environ., 37: 257-273.
A relatively simple model is presented that describes the increase and decrease of fluoride contents in pasture grass ( FG ) dependent on the atmospheric fluoride concentration (FA), season and rainfall. This model is useful to generalize the measured FG, tO give some insight into daily and seasonal fluctuations and to compare standards for FA with standards for F~. To prevent values in excess of 55/~g g- *for Fo, which is assumed to be a threshold for fluorosis (fluoride toxicity in cattle ), the maximum acceptable 24 h average of FA is 0.8/tg m -3 during the growing season and 0.3/tg m -3 for the rest of the year.
INTRODUCTION
Air-quality standards for fluorides are intended to protect human beings, animals, crops and natural ecosystems against fluoride toxicity. Effect thresholds are important criteria for standardization. Thresholds for plant injury have been estimated by various authors (McCune, 1969; National Academy of Sciences (NAS), 1971; Guderian, 1977; van Haut and Krause, 1982). Thresholds for human health are much higher than for plants, so that they are less relevant for setting standards. Fluoride effects on cattle have also been studied extensively. Fluorosis has been observed on a local scale (Quinche, 1974; Suttie, 1977; Debackere and Delbeke, 1978 ). Effects on natural fauna have hardly been studied at all (Walton, 1988). Fluoride effects on cattle are caused by the consumptiol~ of fodder and water containing fluorides; the effect of inhaling fluoride-contaminated air is negligible (Rao and Friedman, 1975 ). Fluoride causes several effects when consumed (Stoddard et al., 1963; NAS, 1971; Eckerlin et al., 1986): (a)it inhib0167-8809/91/$03.50
© 1991 Elsevier Science Publishers B.V. All rights reserved.
258
L.J. VAN DER EERDEN
its bone formation and stimulates the demolition ofb0.n,e ti.~sue, which results in increased fragility of the skeleton and r¢~luced mobility; (b) it inhibits the formation of enamel on growing teeth of young animals, which can reduce the fodder consumption; (c) it reduces fgrm0atation of fodder in the stomach and intestines. In most of the literature, the thr~hol~i for enamel injury is regarded as being the lowest of the three fluoride effects mentioned above. However, Eckerlin et al. (1986) conclude from a re-evaluation of data, published by Stoddard et al, (1963), that reduction in milk production can occur as a result of fluoride in grass at l¢vels below the threshold for impairment of teeth or skeleton. These results, based on limited experimental work, are in contrast to the findings ofothers (e.g. Suttie, 1969), and have not been verified in the field. To protect cattle it is necessary to have either a standard for the fluoride content in fodder, or a standard for atmospheric fluoride concentration that prevents excessive levels of fluoride accumulating in fodder. Accumulation of fluorides in the fodder via soil and roots is generally of minor importance (Garber et al., 1967). One exception apparently occurs when plants grow in more acid soil (that is also poor in organic matter). These plants tend to have a somewhat higher fluoride content. Some standards for atmospheric fluoride concentration with a 24 h average are: 8.5/~g m -3 (Canada), 7/~g m -3 (China, Montana and New York, USA), 5/zg m -3 (USSR), 4/~g m - J(Oermany, Belgium) and 2.8/~g m -3 (Netherlands). There are also standards for monthly growing season and x,oarl~, averages. In most cases, standards for fluoride content in pasture grass and fodder are not stated by law. Standards for maximum allowable fluoride contents are: 40~tgg -I (NAS, 1971 ), 50~tgg -~ (Hapke, 1977), 55/~g g-m (Gezondhe,.'dsraad, 1981 ) and 80/~g g - ' (Suttie, 1969), while standards for annual means are 40/~g g- ~ (Suttie, 1969) and 30/~g g- m(Brustier and Pitet, 1960; Wood, 1973; Prival and Fischer, 1973; Gezondheidsraad, 1981 ). Generally, in environmental policy a simple set of standards is preferred; for example, one standard that protects both plants and animals. However, the relation between atmospheric fluoride concentrations and fluoride contents in fodder does not appear to be very consistent. Therefore, use of a standard for atmospheric fluoride concentrations is not sufficient to protect cattle. Although fluoride-containing compounds differ in their toxicity, most standards involve all fluorides or those that are soluble in water at a neutral pH. With regard to plant injury, only soluble fluoride and particularly gaseous HF is relevant (Less et al., 1975). However, in the case of cattle, fluoride compounds soluble at a low pH are also important, because the pH of the stomach fluid of cattle is 1.5 (Sloof et al., 1989 ). In the following sections, the term 'fluoride' refers to the total fluoride compounds present in the atmosphere or plant. The following abbreviations will
FLUORIDE CONTENT IN GRASS
259
be used in this paper: FA, atmospheric fluoride concentration (gg m-3); FG, fluoride content in grass (/~g g-~, dry mass). Several research workers have described the relationship between the fluoride content in grass and the fluorides deposited in rain gauges or on limed papers (Miller et al., 1953; Adams, 1957; Garber, 1970; Israel, 1974; Davison et al., 1976; de Temmerman, 1984). By converting these deposition data into atmospheric concentrations, some insight can be obtained into the relation between atmospheric fluoride concentration and the fluoride content in grass. However, the direct relationship between these two parameters has also been described. In a fumigation experiment, Hitchcock et al. ( 1971 ) found the equation
FG= I.13 FAT+ I.17
(l)
where Fc is fluoride content in grass (/~g g-~), FA is atmospheric fluoride concentration (#g m - 3) and T is exposure time (days). McLean and Schneider ( 1973 ) quote a different regression
FG=4.12 FAT - 2.56
(2)
Besides this linear relation, Hitchcock et al. ( 1971 ) presented another formula in which a factor was introduced to describe the decrease in FG after exposure FG = 4.22 F ~ 821 '°'7°e- 0.032D ( 3) where the superscript D represents post-exposure time (days). De Temmerman (1984) considered a formula which incorporates the effect of rainfall FG= 128 F °A,3 ' I 3 . F 0"59"~0'45 -0.0043 NI,2 A,2 "~ A,I " e (4) Here, FA,~ is the average FA in the Xst week before grass sampling and N1,2 is the precipitation (ram) in the fortnight before the sampling date. This equation shows a relatively small effect of FA 3 weeks before the sampling date (FA.3). which is easy to understand. It is more of a problem to understand why b has a greater impact on FG than FA.~. Blakemore ( 1978, cited in Craggs and Davison, 1987a) produced a regression model, given by F~= - 31.1 +0.67 FG,t + 281 FA,g'[" 223 FA, p
(5)
F~ and FG,~ are the actual fluoride content in grass and the content 1 week earlier, respectively. FA,gand FA,p are atmospheric concentrations (averaged over 7 days preceding the grass sampling date) of gaseous and particulate fluorides, respectively. The model presented in eqn. (5) accounts for 72% of the total variation of FG. Measurements took place over a 2 year period at 7-day intervals. This
260
LJ. VAN DER EERDEN
equation suggests that gaseous and particulate fluorides contribute to FG in about equal proportions. However, it is difficult to prove this hypothesis under field conditions (Craggs and Davison, 1987a). Craggs and Davison (1987b) used the same data set, but induced more variables and made a non-linear model
F~=Fc,.~ exp (0.368 (rFA,a)g.t + 1.049 FA,to,--0.884 FA,tot, I +0.494 (rFA.b)tot.l--0.531 N°'25+0.701 +re)
(6)
The nomenclature of this equation is similar to that in the equations already mentioned. In addition, FA.to, is a variable representative of the total atmospheric fluoride concentration and is defined by the sum of the square root transformation of FA,g and the cubic root of FA.p. rFA,a, rFA.b and rc are random innovations (model residuals), according to the best fitting Box-Jenkins model (Box and Jenkins, 1976 ) for the univariate FA data set. The model presented in eqn. (6) is based on measurements from one particular experimental site. It accounts for 81% of the total variation, which is extraordinarily high for these kinds of field measurements. The authors themselves, however, warn that the model may be less accurate at other sites and in other periods. This point of criticism applies to all the equations mentioned above. All models mentioned here have in common the fact that they describe fairly well the conditions from which they originate (r--0.6-0.8) and that they are based on a relatively limited amount of data (n < 50). The first three equations are more useful for evaluating laboratory fumigations than field situations. Comparison of these regressions shows that, depending on the input data, the results can deviate by some hundreds of percentage points and that it is difficult to make the right choice between them. In this paper r a new model will be discussed. It integrates several factors that influence fluoride accumulation: rainfall, standing crop and dilution due to crop growth. This model is based on a concept of the causes of fluctuation of FG. Most elements of this concept have been evaluated in laboratory fumigations or measurements in the field. Regression analysis was performed only to quantify the coefficients in the equation. The first aim of this model is to relate standards for fluoride in fodder to atmospheric fluorides. This relation is of use in estimating environmental consequences of fluoride emissions. A second aim is that the model may be of use in evaluating the results of Fo monitoring programmes, e.g. to evaluate exceptional Fc values, to correct annual averages for missing values or unequal distribution of sampling data over the year. To be of use in practice, the model must not only be accurate, but must also be simple to use.
FLUORIDE CONTENT IN GRASS
261
MATERIALS AND METHODS
Field sampling Most of the field sampling was performed around three sources: two aluminium smelters and one glass factory. All sources emitted fluoride continuously. Grass was sampled monthly at eight to twelve sites around each of these sources. Additional measurements were made close to two brick factories, to estimate spatial and temporal variation of FG. To determine a background content of F6, containers of 301 with nutrientrich humus soil and a turf of Lolium multiflorum cv. 'Optima' were placed at three locations with no fluoride source closer than 30 kin. Every 14 days the grass was cut to just above soil level and the Fo was measured during the growing seasons of three successive years. All sites were located in The Netherlands. The Netherlands has an oceanic climate with an average summer temperature of 16 °C (June-September) and an average winter temperature of 5°C (December-February). Minimum temperatu.,'e is about - 12 oC and snow cover over pasture grass generally occurs two to three times per winter and lasts for less than 5 days. Precipitation is 7501 m-2 ( = 750 ram) per year and is equally spread over the whole year. Grass was cut from a pasture using a grass cutter, in a grid with 16 plots over an area of 9 m × 9 m. On each plot, about 200 c m 2 (one handful) was cut off. Areas within the sampling plots that had clearly been trampled by cattle were avoided. The grass was cut offjust above the leafbasis. This fixed height is important for two reasons. Firstly, fluoride is not equally distributed throughout the shoot: it accumulates in the leaf tips (Weinstein, 1977; van der Eerden, 1981 ). Secondly, there may be contamination of the grass by soil particles, this being greater towards the base of the stem. The percentage of soil in a grass sample has a seasonal fluctuation. Based on personal observations in earlier studies, this was approximately 2% (dry weight) in summer and 8% in winter using our sampling method. Cattle also consume soil when grazing: approximately 5% in summer and 20% in winter (Slooff et al., 1989). Soil fluoride is partly soluble in the gastric acid of the stomachs of cattle (pH 1.5-2.0). The percentage of fluoride in the soil that is soluble at a pH of 2.0 differs between soil types. Van den Berg et al. ( 1988 ) found a soluble fraction of 10% in clay and 45% in sandy soil. In winter, and on soil types with a high soluble fluoride content, the contamination of fodder with soil particles is important. If, for instance, the soil fluoride content is 400/~g g-! and half of it is soluble at a pH of 2.0, a maximum of 55/~g g- ~ in fodder means that in winter the fluoride content in grass without soil particles may be no higher than 30/zg g-i. In the rest of this paper, this point is ignored, because the fluoride content of the soil soluble at pH 2.0 in our field locations was 50 ~g g- 3 or less. In this paper, then, FG represents the fluoride content of cut grass,
262
LJ. VAN DER EERDEN
and the fact that a small proportion of the measured fluoride originates from the soil is not considered.
Fluoridefumigations The fumigation experiments were performed in climate-controlled chambers, ventilated with charcoal filtered air. The temperature was 8-14°C, relative humidity 40-..70% and light intensity 25-40 W m - 2 ( 12 h day- i ). Wind velocity was very low: 0.2-0.3 m s -I. The grass Lolium perenne cv. 'Pelo' was used in the fumigation experiments. The grass was growing on soil with a pH(CaCI2) of 6.5, rich in nutrients and humus and with a fluoride content of I l0 ~g g-i. Gaseous HF was produced by supplying an HF solution with a constant flow in a heating system. After evaporation, the vapour was supplied to the ventilation air of the chambers.
Fluoride ,malysis The grass was dried for 24 h at 105 °C, ground in an electric coffee grinder, and 0.5 g was ashed for 2 h at 520°C. After a melt in NaOH, the material was dissolved in water. The fluoride was then distilled from the solution by sulphuric acid at 180°C, condensed and mixed with a colour agent, lanthanum alizarin complexan, and measured colorimetrically at a wavelength of 620 nm (Weinstein et al., 1972 ). All the steps in sample preparation and analysis were checked thoroughly, using the standard addition approach: recovery was 100%. The standard deviation of a grass sample from a pasture with a FG of 40 ~tg g- ~was on average 10 ~g g- i. Thi~ includes all variations caused by sampling, drying and analysis. The fluoride concentration in the air was measured using soda-coated silver balls (Buck and Stratmann, 1965): air was sucked through a tube full of these balls. After 24 h the coating of the balls was washed off with water and measured in a similar way to that used for the fluoride analysis in grass samples. RESULTS
Field experiments In areas without fluoride sources, the FG fluctuates with growth and precipitation (Table l ). Probably soil particles (considered to be a source of natural "contamination" ) cause the fluctuation in this background level of F~. To obtain information on temporal fluctuation, grass was sampled from one site in the vicinity of two brick factories over a period of 75 days. The sampling frequency over 2 weeks was once per day and in the other weeks
263
FLUORIDE CONTENT IN GRASS
TABLE ! Average fluoride content in grass (FG) standard deViation (gD)arid minimum-maximum values (minmax) (~g g- ' ) for low and high dry matter production ove/f | d days, in relation to precipitation in the last week before sampling date .
Rainfall in the week before sampling (mm)
Low dry matter production (50-150 g m - ' ) FG
SD
Min-max
n
<0.5 0.5-5.0 5.1-25 >25
6.0 4.0 3.0 2.5
2.4 2.6 1.6 0.8
4-10 3-10 1.0-6 2.0-4
8 12 12 10
.
.
High dry matter production ( 150-400 g m - ' ) '-"" Fo ~1~ Min-max 3.5 2.5 2.0
l,~J
1.3 0.5 1.0 0.7
3-6 2.0-3 1.0-4 0.5-2.5
17 6 2! 12
Fg in ,ug.g"~ :tO0ISOhmxinlUtfl I00-
~ ~
Pgs (+)
So]
i
t~
a
m
i
i
a
s
o
n
cJ
month
overage
i
f
|
|
m m m
i
J
w
n
;
!
o
n
cl
month
Fig. 1. Frequency distribution of fluoride contents in grass (Fo) with an annual average of 3842 #g g-i. The percentiles (P95, P75 and P50) show the percentage of measurements above the indicated levels (e.g. a P75 of 100 gg g - ' indicates that 25% of the Fo measurements are higher than 100 gg g- I ). Grass samples were taken during a 5 year period from 12 sites in the vicinity of two continuously emitting fluoride sources, n = 23 per month. The lower figure shows the monthly averages.
once every 4-8 days. The average FG was 40 gg g-~. The correlation between the FG on one day and the FG 2 days afterwards was 0.66. After 4, 14 and 30 days, the correlation decreased to 0.35, 0.21 and 0.16, respectively. In this case study, very rainy days (more than 2 mm in 24 h) caused a decrease in FG of 80% of the initial level.
264
L.J. VAN DER EERDEN
TABLE 2 Ratio of the fluoride content in grass, measured at half-monthly intervals and the corresponding annual average. The annual average is based on 12 measurements, equally spread over the year. The grass samples were taken during a 5 year period from several sites in the vicinity of two continuously ~'r~ittiag fluoride sources. To calculate this ratio, referred to as the seasons index, 130 sets of i 2 measuremelits with 2n annual average of 38-42/~g m - 3 were used Period
Seasons index
Period
Seasons index
First half of January Second half of January First half of February Second half of February First half of March Second half of March First half of April Second half of April First half of May Second half of May First half of June Second half of June
1.5 1,7 !.9 2.1 1.9 1.6 !. I 0.7 0.6 0,6 0.6 0.5
First half of July Second half of July First half of August Second haifofAugust First half of September Second halfofSeptember First haifofOctober Second half of October First half of November Second half of November First half of December Second half of December
0.5 0.6 0.6 0.6 0.6 0.7 0.8 0.8 0.9 1.0 l. 1 1.3
Besides daily fluctuations in F6, a seasonal pattern was also found. Figure l shows monthly averages of 32 sets of FG with an annual average of 38-42 /~g g-I. Each set consists of 12 Fc, sampled on the same plot: one for each month. Sampling was performed from 12 sites around two continuously emitting point sources. With an annual average FG of 40/~g g-l, monthly averages fluctuate from 70/~g g-I in February to 20/zg g- ~ in June. In February, 90/~g g-* is exceeded once every four measurements and 120/zg g-~ once every 20 measurements. Based on the same data set, an average pattern in seasonal fluctuations of Fo can be calculated. Twelve FG values, obtained from samples taken at monthly intervals from the same plot, give the annual average. The Fo measured on a certain date was divided by the corresponding annual average. This ratio is given in Table 2. These ratios are based on annual averages of 38-42/~g g-m. Lower average FG values also appear to follow these seasonal patterns, however: the lowest FG values, mentioned in Table l were found in the middle of the growing season. Information concerning annual average FG values of more than 50/~g g- ~ is very limited. The level of correlation between FA and Fc measured during four subsequent growing seasons on a site close to an aluminium smelter appeared to depend on the definition of FA. If FA was averaged over the period before the sampling date, beginning after the last rainy day (more than 2 mm rain in 24 h), the linear regression was FG = -- 1.8 + 72.3 FA
265
FLUORIDE CONTENT IN GRASS
400 A
To,
(a) 300
(n
5.3 ug.m-3 c_
3.7 ug.m-3
200
0 . 8 3 ug.m-3 100
t
0 0
5
10
15
20
exposure period (days)
400 A
I ol
(b)
--~ 300 m
C_
200
§ .~
100
.9..
@
17 days
[]
6 days
&
1 day
T
0 0
2
4
6
atmosphertc I-IF concentration (ug,m-3)
Fig. 2. (a) Relation between fluoride content in grass (FG, Lolium perenne, cv. 'Pelo') and atmospheric hydrogen fluoride concentration (F^). Plants were exposed in controlled environment chambers to three concentrations: 0.83 #g m -3, 3.7 #g m -3 or 5.3 #g m -3 for 0.5 day, 1 day, 3 days, 6 days, 9 days, 13 days or 17 days. The vertical bars show one standard deviation at each side of the mean. n=4. (b) Relation between fluoride content in grass (Fo, Lolium perenne, cv. 'Pelo') and atmospheric hydrogen fluoride concentration (FA). Data are similar to those in (a) at exposure periods of I, 6 or 17 days, but are presented in relation to FA concentration.
The explained variance in this regression is 39% (n=22). If, instead of the average, the highest FA during that same period is used (indicated by F~, ), the regression takes the form F6=3.8+31.0 F~ Here, the explained variance has increased considerably to 68%. This sup-
266
L.J. VAN DER EERDEN
ports the supposition that a peak in FA is more important to FG than the average FA. After an exposure period, FG decreases as a result of growth, senescence, wind and precipitation. In field measurements, an average "half-life" of fluorides in grass of 4 days in summer and 12 days in winter was found in periods with background levels of FA and no precipitation. Fumigation experiments In a fumigation experiment, grasses were exposed for 0.5, 1, 3, 6, 9, 13 and 17 days to three FA levels. Biomass increase was not affected by the fumigations. With a constant FA, FG tends to reach equilibrium. This level is linearly related to FA, SOit is not a real saturation level. In the fumigation experiments presented here, at an FA of 0.83/~g m - 3, equilibrium was reached after 2 days, but it lasted longer with higher FA values (Fig. 2 (a)). In the same experiment, a linear relation between FA and FG was found. The slope of this relation increases with longer exposures (Fig. 2 (b) ). In another fumigation experiment lasting for 5 days with an FA value of 2 /~g m - 3, the influence on FG of wind velocity was examined between 0.25 and 5.0 m s -~. The relation between wind velocity (V) and FG was FG=81.7+12.1 V
(n=53, r=0.83)
(7)
Modelling the relation between F,~ and F~; Based on the above conclusions, a relation between FA and FG has been defined. This relation is composed of the following elements. ( l ) Fo is linearly related to FA. Therefore, FG = k FA (Fig. 2 ). (2) The increase in FG during exposure is faster than the decrease after exposure. (3) An exposure period can be considered to start after a day with more than 2 mm rainfall (FG has become very low then) and ends on the sampling date. The highest FA in that period (indicated as F~ ) determines FG. Th~refore, FG ffi KF ~,. (4) After the day that F~ has occurred, FG decreases. The velocity of decrease is dependent on the season. To describe the decrease of FG, a seasons index can be introduced in a negative exponential function: e x p - (K2Si- ~T). Si is the seasons index as mentioned in Table 2 and T is the number of days between the day F~ occurred and the sampling date. From regression analysis it was concluded that K2 is 0.1. (5) In the formula: K Si F~, e x p - (0.1 Si -~ T), K can be estimated by relating measured and calculated values of FG. This has been done with 127
FLUORIDE CONTENT IN GRASS
267
measurements around two fluoride sources in southwest Netherlands. K was estimated as 90. Thus the total model becomes
FG=9OSiF~,exp ( - 0 . 1 S i -~ T)
(9)
Si is the seasons index (Table 2), F~ is the highest (24 h average) FA between a day with more than 2 mm rain and the grass sampling date. T is the number of days between the day that F~ occurred and the sampling date. DISCUSSION
Many research workers mention a background FG level of 10-22 ~tg g(Benedict et al., 1964; Guderian et al., 1969; NAS, 1971, Less et al., 1975 ). De Temmerman et al. ( 1978 ) found background level~ in 12 grass species of between 2 and 6/~g g-~. However, Table 1 suggests that completely uncontaminated grass of the species Lolium multiflorum probably contains only 1 or 2/zgg -~. A significant (P<0.05) but low correlation was found between Fc values measured on the same site with an interval of I day (0.66). This correlation decreased considerably with longer time intervals. This indicates that an FG value on a certain day provides limited information about FG values which existed on the days before and after that sampling date. In other words, a sampling frequency of once a month (which is normally used in monitoring programmes) does not represent an average over the total month, but is only a random sample out of a population of some 15-30 values. These results on temporal variation of FG are in agreement with the findings of de Temmerman (1984). Davison et al. ( 1979 ) found somewhat larger fluctuations. The observation that rainfall can decrease FG is in agreement with most literature data. A negative correlation between FG and rainfall was also found by Davison and Blakemore (1976) and de Temmerman (1984), although the slope of this regression differs considerably between the authors. It must be attributed to the fact that the relation between F6 and rainfall is much more complicated than only a relation between the volume of precipitation and FG. Figure 2 (a) shows an equilibrium level for Fc after a certain exposure period. The length of this period was longer with higher FA levels: 2 days at 0.8 gg m-a and more than 15 days at 5.3 gg m-3. These results are from a fumigation experiment in which boundary layer resistance probably dominates over stomatal resistance owing to the very low wind velocity (0.2-0.3 m s-m ). In another experiment, a linear relation between fluoride accumulation in grasses and wind velocity was found up to 5 m s-~, the maximum velocity used in this experiment (eqn. (7) ). Above 1 m s- ~, stomatal resistance dominates over boundary layer resistance. In the field, with wind velocities of more than 1 m s -~, most of the time an equilibrium between FA and FG will
268
L.J. V A N D E R E E R D E N
(a)
Ill
FG
~1
FG calculated
measured 400
" f,g.3-a
( 1976-1981)
300 A
I
200
0 U. 100
5678910
5678910
5567810
5678910
567B910
445678910 month
(b)
I
FG measured
I---I
FG calculated
150 fig 3-b
1982- 1989) ]
100 I
0
U.
50
6
12
6
12
6
12
6
12
6
12
6
12
6
12
6
month
Fig. 3. Fluoride content in pasture grass (Fa, ~g m -s), measured in a sample (solid bars) and calculated with the FA/FG model (dotted bars), using local measurements of rainfall and atmospheric fluorides. The pasture consisted mainly of Lolium perenne. (a) Course of fluoride content in pasture grass at 1.5 km from an aluminium factory. Grass sampling was done once every 4 weeks and only during the grazing season. (b) Like (a), but in this case grass sampling was usually done over the whole year. (c) Fluoride content in pasture grass, measured I km from a glass factory. Grass sampling was done once every 14 days in the period from June to October and every day in the first week of November.
269
FLUORIDE CONTENT IN GRASS
~
(c)
Iml
FG measured
FG calculated
200
Iflg. 3-c I A
I 100 L9 LL
j 0
6
7
7
8
8
9
9
•7m-i 1o
lO
1o
lO
11
11
1
11
11
11 11
month
Fig. 3. Cont.
probably be reached much faster. A negative correlation with wind velocity was found by de Temmerman (1984), but his measurements were not made during fumigation with HF, but directly afterwards: higher wind velocities caused considerable loss of fluorides from the grass. Seasonal fluctuations in FG as shown in Table 2 were also reported by Guderian et al. (1969), NAS (1971 ), de Temmerman (1984) and Slooff et al. (1989). Craggs et al. ( 1985 ) conclude that this seasonality does not always Occur and is not due to dilution of fluoride in the case of dry matter production. Growth dilution is often of minor importance, which can be concluded from the observation that FG can decrease drastically within I or 2 days. This rapid decrease cannot be caused by growth dilution only. Standing crop and the effect of surface roughness on deposition velocity is probably of more importance. The absence of seasonality in FG, as found by Craggs et al. (1985) may be caused by an abundance of influential factors, such as rainfall and wind which are discussed in this paper. One consequence of the large seasonal fluctuation is that for an accurate calculation of an annual average based on monthly sampling, no monthly value can be missed. If, for example, the February value is not used, an annual average of 40/lg g-i becomes 34/~g g-~. The seasons index (Table 2 ) can help to estimate a missing value, using the rest of the measurements. The reliability of the FA/FGmodel, presented above, has been tested at two locations. The results are illustrated in Fig. 3. One location was 1.5 km from an aluminium factory. The ratio of gaseous and particulate fluoride emission was estimated to be 4: I. No other fluoride sources were present in that area.
270
L.J. VAN DER EERDEN
Close to the site where grass was sampled, FA and rainfall were measured at 24-h intervals. The sampling frequency for grass was once a month. In the first 6 years, measurements were performed only during the growing season (Fig. 3(a) ). In the following 7.5 years, sampling took place in almost every month of the year (Fig. 3(b) ). In winter during the following years, no grass sampling occurred when the pasture was covered in snow. The correlation between calculated and measured values of Fc was 0.82. The explained variance in this case was 67%. On another site, l km from a glass factory which only emitted HF, another check on the reliability of the FA/FG model was done (Fig. 3 (c)). The data set was much smaller and the grass sampling frequency was higher in this case. A correlation between measured FG and FG calculated with the FA/FGmodel was 0.82. It must be concluded that the model does not have sufficient accuracy to predict (or substitute) FG measurements. Certainly, the model would gain in accuracy if the actual biomass (as a result of growth, grazing or mowing), the duration and intensity of rain showers and the fluctuation of FA concentrations within 24 h were taken into account. But this would require enormous measuring facilities and effort to collect all the required data. The model is suitable, however, for simulating the behaviour and fluctuations of FG and to relate standards for FG tO standards for FA and also to 'generalize' measured FG levels. Some examples will illustrate these uses. The model gives some insight into the possible daily fluctuations of FG and explains why a sampling frequency of once a month only gives very limited information on the monthly average FG because the fluctuations can be considerable. The model also offers the possibility to standardize. If, for instance, sampling has taken place during an exceptionally long dry period, it can be estimated from the model what the Fc would have been in a dry period ofaverage length. The FG at a given FA in a certain period of the year can also be calculated. For example, a 24 h average of FA of 2.8/~g m - a (a recommended standard in The Netherlands) causes an FG of 50 ~g g - ' in summer (June) and 180~ugg- ' in winter (February). After 4 dry days, FG is 24/~g g- ' in summer and 147 ~g g - ' in winter. The model can calculate thresholds for FA, given a maximum permissible FG. For an FG of 55/~g g-~, FA (24 h average) must be 0.3/~g m - a. If only the grazing season (April-October) is taken into account, FA can be 0.8 ~ g m - 3. Nevertheless, the model indicates that to prevent values of FG in excess of 55 /~g g-~, FA must be considerably lower than the FA thresholds that are assumed to protect plants. If an FG of 55/~g g-~ is not considered to be an absolute maximum, but a maximum for a monthly average, it depends on the frequency distribution of FA as to which levels are tolerable. The reliability of the FA/FG model was tested on data sets other than the one used to parameterize the model. In this respect, it is an exception: the
FLUORID[~ CONTENT IN GRASS
271
models presented in the introduction (eqns. ( 1-6 ) ) only describe the FA/Fc relation under conditions from which the data originate. A quantitative comparison between the models is only possible with some assumpti~ms (on preand post-exposure perinds, seasonal effects, rainfall and the ratio of gaseous and particulate fluorides). In the very simple situation of background levels of FA, followed by a few days with elevated HF concentrations in a dry period, the FA/Fc model presented in this paper gives about the same results as eqn. (5), but only in ~he range of FA of 0.2-2/~g m - 3. Other equations predict considerably lower FG values. For an accurate comparison, however, more detailed information on the local situation is necessary. The FA/F6 model presented here is based on measurements in a moderate oceanic climate, but it may also be useful under other climatic conditions. In that case, the seasons index (Table 2) and the definition of F~ must be adapted. ACKNOWLEDGEMENTS
The author wishes to thank G. Laurens who did the chemical analyses and J. van Achterberg for assistance in the field experiments.
REFERENCES Adams, D,F,, 1957. Further applications of the limed paper technique in fluorine air pollution studies, J. Air Pollut. Control Assoc., 7: 81-91. Benedict, H.M., Ross, J.M. and Wade, R.W., 1964. The disposition of atmospheric fluorides by vegetation. Int. J. Air. Water Pollut., 8: 279-289. Box, G.E.P. and Jenkins, G.M., 1976. Time series analysis forecasting and control. Holden Day, San Francisco, CA, 576 pp. Brustier, V. and Pitet, G., 1960. Sur la pollution de l'atmosph~re par des poussi~res fluor~es. Arch. Mal. Prof., 21:71-72. Buck, M. and Stratmann, H., 1965. Ein Verfahren zur Bestimmung sehr geringer Konzentrationen yon Fluorionen in der Atmosphiire. BrennstoffChemie, 46 (8): 3-7. Craggs, C. and Davison, A.W., 1987a. Autocorrelation and univariate time series modelling for grass fuoride and airborne fluoride concentrations. Environ. Pollut., 43:115-128. Craggs, C. and Davison, A.W., 1987b. Multivariate stochastic modelling of grass fluoride and airborne fluoride. Environ. Pollut., 44: 279-296. Craggs, C., Blakemore, J. and Davison, A.W., 1985. Seasonality in the fluoride concentration of pasture grass subject to ambient airborne fluorides. Environ. Pollut. Ser. B., 9: 163-177. Davison, A.W. and Blakemore, J., 1976. Factors determining fluoride accumulation in forage. In: T.A. Mansfield (Editor), Effects of Air Pollutants on Plants, Cambridge University Press, Cambridge, pp. 17-20, Davison, A.W., Blakemore, J. and Wright, D.A., 1976. A re-examination of published data on the fluoride content of pastures. Environ. Pollut., 10:209-215. Davison, A.W., Blakemore, J. and Craggs, C., 1979. The fluoride content of forage as an environmental quality standard for the protection of livestock. Environ. Pollut., 20: 279-296.
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Debackere, M. and Delbeke, F.T., 1978. Fluoride pollution caused by a brickworks in the Flemish countryside of Belgium. J. Environ. Stud., I I: 245-252. De Temmerman, L.O., 1984. Invloed van atmosferische fluorideverontreiniging op kulturen van Engels Raaigras (Lolium perenne L. ) en op artifici~le graslandassociaties. Dissertation, University of Ghent, Belgium, 297 pp. De Temmerman, L.O., Istas, J.R., Rakelboom, E.L. and Baten, H., 1978. Fluor in grassoorten en bodem van een agrarisch gebied en een industriezone. Landbouwtijdschrift, 31: 515-524. Eckerlin, R.H., Maylin, G.A. and Krook, L., 1986. Milk production of cows fed fluoride contaminated commercial feed. Cornell Vet., 79: 403-414. Gather, K., 1970. Fluoride in rainwater and vegetation. Fluoride, 3: 22-26. Gather, K., Guderian, R. and Stratmann, H., 1967. Untersuchungen fiber die Aufnahme von Fluff aus dem Boden durch Pflanzen. Qual. Plant. Mater. Veg., 14: 223-236. Gezondheidsraad, 1981. Advieswaarden voor anorganische fluoriden in de buitenlucht. Rep. no. VAR 50, Ministry of Environmental Affairs, Leidschendam, the Netherlands, 99 pp. Guderian, R., 1977. Air Pollution: Phytotoxicity of acidic gases and its significance in air pollution control. Ecological Studies, 22. Springer, Berlin, 127 pp. Guderian, R., van Haut, R.H. and Stratmann, H., 1969. Experimentelle Untersuchungen fiber Pflanzen schadigende Fluorwasserstofkonzentrationen. Forschungsber. Landes NordrheinWestfalen No. 02017. Westdeutscher, K61n, pp. 3-54. Hapke, H.J., 1977. Immissionswirkungen bei Tieren. Umschau, 15:517. Hitchcock, A.E., McCune, D.C., Weinstein, L.H. and Mandle, R.H., 1971. Effects of hydrogen fluoride fumigation on alfalfa and orchard grass: A summary of experiments from 1952 through 1965. Contrib. Boyce Thompson Inst., 14: 363-386. Israel, G.W., 1974. A field study ofthe correlation ofstatic lime paper sampler with forage and cattle urine. Atmos Environ., 8:169- 18 I. Less, L.M., McGregor, A., Jones, L.N.P., Cowling, D.W. and Leafe, E.L., 1975. Fluorine uptake by grass from aluminium smelter fume. Int. J. Environ. Stud., 7:153-160. McCune, D.C., 1969. On the establishment of air quality criteria, with reference to the effects of atmospheric fluorine on vegetation. Air Qual. Monogr. 69-3, Am. Petrol. Inst., New York, 33 pp. McLean, D.C. and Schneider, R.E., 1973. Fluoride accumulation in forage: continuous vs. intermittent exposures to hydrogen fluoride. J. Environ. Qual., 2: 501-503. Miller, V.L., Allmendinger, D.F., Johnson, F. and Policy, D., 1953. Lime papers and indicator plants in fluorine air pollution investigations. Agric. Food Chem., I: 526-529. National Academy of Sciences, 1971. Fluorides. NAS, Washington, DC, 295 pp. Prival, MJ. and Fischer, F., 1973. Fluorides in the air. Environment, 3: 25-32. Quinche, J.P., 1974. La pollution des herbages du valais par le fluor et ses effets sur les bovins. Rev. Suisse Agric., VI-3:81-85. Rao, G.S. and Friedman, E.A., 1975. Fluoride and bone disease in uremia. Kidney Int., 7: 125129. Slooff, W., Eerens, H.C., Janus, J.A. and Ross, J.P., 1989. Integrated criteria document fluorides. Rep, No. 758474010, Nat. Inst. Public Health Environ. Prot., Bilthoven, the Netherlands, ! 71 pp. Stoddard, G.E., Bateman, G.Q., Harris, L.E,, Shupe, L.J. and Greenwood, D.A., 1963. Effects of fluorine in dairy cattle. IV, milk production. J. Dairy Sci., 46: 720-726. Suttie, J.W., 1969. Air quality for the protection of farm animals from fluorides. J. Air. Pollut. Control Assoc., 4: 239-242. Suttie, J.W., 1977. Effects of fluoride on livestock. J. Occup. Med., 19: 40-48. Van den Berg, R., Mesters-Bakhuis, H., van Staden, J.J. and van den Berg, S., 1988. Extractie fluoriden uit rivierklei. Simulatie van de beschikbaarheid in de koemaag. Rep. No. 758474006, Natl. lnst, Public Health Environ. Prot., Bilthoven, Netherlands, 27 pp. Van der Eerden, L.J., 1981. Fluoride-accumulatie in gras; voortgangsverslag, no. I. Rep. No. R 256, Res. Inst. Plat Prof., Wageningen, the Netherlands, 36 pp.
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Van Haut, H. and Krause, G.K.H., 1982. Fluorwasserstofwirkungen aufPflanzen. LIS-berichte, 25. Landesanstalt Ffir Immissionsschutz, Essen, Germany, 60 pp. Walton, K.C., 1988. Environmental fluoride and fluorosis in mammals. Mammal Rev., 2: 7790. Weinstein, L.H., 1977. Fluoride and plant life. J. Occup. Med., 19( 1 ): 49-78. Weinstein, L.H., Jacobsen, J.S. and Mandi, R.H., 1972. Fluorine: semi-automated method. J. Assoc. Off. Anal. Chem., 5: 998-1003. Wood, R., 1973. Fluorine as a pollutant. Trans. J. Br. Ceram. Soc., 1: 35-37.
257
Elsevier Science Publishers B.V., Amsterdam
Fluoride content in grass as related to atmospheric fluoride concentrations: a simplified predictive model L.J. van der Eerden Research Institute for Plant Protection, Department of Ecology, Binnenhaven 12, 6 700 G W Wageningen, Netherlands (Accepted 26 March ! 991 )
ABSTRACT Van der Eerden, L.J., 1991. Fluoride content in grass as related to atmospheric fluoride concentrations: a simplified predictive model. Agric. Ecosystems Environ., 37: 257-273.
A relatively simple model is presented that describes the increase and decrease of fluoride contents in pasture grass ( FG ) dependent on the atmospheric fluoride concentration (FA), season and rainfall. This model is useful to generalize the measured FG, tO give some insight into daily and seasonal fluctuations and to compare standards for FA with standards for F~. To prevent values in excess of 55/~g g- *for Fo, which is assumed to be a threshold for fluorosis (fluoride toxicity in cattle ), the maximum acceptable 24 h average of FA is 0.8/tg m -3 during the growing season and 0.3/tg m -3 for the rest of the year.
INTRODUCTION
Air-quality standards for fluorides are intended to protect human beings, animals, crops and natural ecosystems against fluoride toxicity. Effect thresholds are important criteria for standardization. Thresholds for plant injury have been estimated by various authors (McCune, 1969; National Academy of Sciences (NAS), 1971; Guderian, 1977; van Haut and Krause, 1982). Thresholds for human health are much higher than for plants, so that they are less relevant for setting standards. Fluoride effects on cattle have also been studied extensively. Fluorosis has been observed on a local scale (Quinche, 1974; Suttie, 1977; Debackere and Delbeke, 1978 ). Effects on natural fauna have hardly been studied at all (Walton, 1988). Fluoride effects on cattle are caused by the consumptiol~ of fodder and water containing fluorides; the effect of inhaling fluoride-contaminated air is negligible (Rao and Friedman, 1975 ). Fluoride causes several effects when consumed (Stoddard et al., 1963; NAS, 1971; Eckerlin et al., 1986): (a)it inhib0167-8809/91/$03.50
© 1991 Elsevier Science Publishers B.V. All rights reserved.
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L.J. VAN DER EERDEN
its bone formation and stimulates the demolition ofb0.n,e ti.~sue, which results in increased fragility of the skeleton and r¢~luced mobility; (b) it inhibits the formation of enamel on growing teeth of young animals, which can reduce the fodder consumption; (c) it reduces fgrm0atation of fodder in the stomach and intestines. In most of the literature, the thr~hol~i for enamel injury is regarded as being the lowest of the three fluoride effects mentioned above. However, Eckerlin et al. (1986) conclude from a re-evaluation of data, published by Stoddard et al, (1963), that reduction in milk production can occur as a result of fluoride in grass at l¢vels below the threshold for impairment of teeth or skeleton. These results, based on limited experimental work, are in contrast to the findings ofothers (e.g. Suttie, 1969), and have not been verified in the field. To protect cattle it is necessary to have either a standard for the fluoride content in fodder, or a standard for atmospheric fluoride concentration that prevents excessive levels of fluoride accumulating in fodder. Accumulation of fluorides in the fodder via soil and roots is generally of minor importance (Garber et al., 1967). One exception apparently occurs when plants grow in more acid soil (that is also poor in organic matter). These plants tend to have a somewhat higher fluoride content. Some standards for atmospheric fluoride concentration with a 24 h average are: 8.5/~g m -3 (Canada), 7/~g m -3 (China, Montana and New York, USA), 5/zg m -3 (USSR), 4/~g m - J(Oermany, Belgium) and 2.8/~g m -3 (Netherlands). There are also standards for monthly growing season and x,oarl~, averages. In most cases, standards for fluoride content in pasture grass and fodder are not stated by law. Standards for maximum allowable fluoride contents are: 40~tgg -I (NAS, 1971 ), 50~tgg -~ (Hapke, 1977), 55/~g g-m (Gezondhe,.'dsraad, 1981 ) and 80/~g g - ' (Suttie, 1969), while standards for annual means are 40/~g g- ~ (Suttie, 1969) and 30/~g g- m(Brustier and Pitet, 1960; Wood, 1973; Prival and Fischer, 1973; Gezondheidsraad, 1981 ). Generally, in environmental policy a simple set of standards is preferred; for example, one standard that protects both plants and animals. However, the relation between atmospheric fluoride concentrations and fluoride contents in fodder does not appear to be very consistent. Therefore, use of a standard for atmospheric fluoride concentrations is not sufficient to protect cattle. Although fluoride-containing compounds differ in their toxicity, most standards involve all fluorides or those that are soluble in water at a neutral pH. With regard to plant injury, only soluble fluoride and particularly gaseous HF is relevant (Less et al., 1975). However, in the case of cattle, fluoride compounds soluble at a low pH are also important, because the pH of the stomach fluid of cattle is 1.5 (Sloof et al., 1989 ). In the following sections, the term 'fluoride' refers to the total fluoride compounds present in the atmosphere or plant. The following abbreviations will
FLUORIDE CONTENT IN GRASS
259
be used in this paper: FA, atmospheric fluoride concentration (gg m-3); FG, fluoride content in grass (/~g g-~, dry mass). Several research workers have described the relationship between the fluoride content in grass and the fluorides deposited in rain gauges or on limed papers (Miller et al., 1953; Adams, 1957; Garber, 1970; Israel, 1974; Davison et al., 1976; de Temmerman, 1984). By converting these deposition data into atmospheric concentrations, some insight can be obtained into the relation between atmospheric fluoride concentration and the fluoride content in grass. However, the direct relationship between these two parameters has also been described. In a fumigation experiment, Hitchcock et al. ( 1971 ) found the equation
FG= I.13 FAT+ I.17
(l)
where Fc is fluoride content in grass (/~g g-~), FA is atmospheric fluoride concentration (#g m - 3) and T is exposure time (days). McLean and Schneider ( 1973 ) quote a different regression
FG=4.12 FAT - 2.56
(2)
Besides this linear relation, Hitchcock et al. ( 1971 ) presented another formula in which a factor was introduced to describe the decrease in FG after exposure FG = 4.22 F ~ 821 '°'7°e- 0.032D ( 3) where the superscript D represents post-exposure time (days). De Temmerman (1984) considered a formula which incorporates the effect of rainfall FG= 128 F °A,3 ' I 3 . F 0"59"~0'45 -0.0043 NI,2 A,2 "~ A,I " e (4) Here, FA,~ is the average FA in the Xst week before grass sampling and N1,2 is the precipitation (ram) in the fortnight before the sampling date. This equation shows a relatively small effect of FA 3 weeks before the sampling date (FA.3). which is easy to understand. It is more of a problem to understand why b has a greater impact on FG than FA.~. Blakemore ( 1978, cited in Craggs and Davison, 1987a) produced a regression model, given by F~= - 31.1 +0.67 FG,t + 281 FA,g'[" 223 FA, p
(5)
F~ and FG,~ are the actual fluoride content in grass and the content 1 week earlier, respectively. FA,gand FA,p are atmospheric concentrations (averaged over 7 days preceding the grass sampling date) of gaseous and particulate fluorides, respectively. The model presented in eqn. (5) accounts for 72% of the total variation of FG. Measurements took place over a 2 year period at 7-day intervals. This
260
LJ. VAN DER EERDEN
equation suggests that gaseous and particulate fluorides contribute to FG in about equal proportions. However, it is difficult to prove this hypothesis under field conditions (Craggs and Davison, 1987a). Craggs and Davison (1987b) used the same data set, but induced more variables and made a non-linear model
F~=Fc,.~ exp (0.368 (rFA,a)g.t + 1.049 FA,to,--0.884 FA,tot, I +0.494 (rFA.b)tot.l--0.531 N°'25+0.701 +re)
(6)
The nomenclature of this equation is similar to that in the equations already mentioned. In addition, FA.to, is a variable representative of the total atmospheric fluoride concentration and is defined by the sum of the square root transformation of FA,g and the cubic root of FA.p. rFA,a, rFA.b and rc are random innovations (model residuals), according to the best fitting Box-Jenkins model (Box and Jenkins, 1976 ) for the univariate FA data set. The model presented in eqn. (6) is based on measurements from one particular experimental site. It accounts for 81% of the total variation, which is extraordinarily high for these kinds of field measurements. The authors themselves, however, warn that the model may be less accurate at other sites and in other periods. This point of criticism applies to all the equations mentioned above. All models mentioned here have in common the fact that they describe fairly well the conditions from which they originate (r--0.6-0.8) and that they are based on a relatively limited amount of data (n < 50). The first three equations are more useful for evaluating laboratory fumigations than field situations. Comparison of these regressions shows that, depending on the input data, the results can deviate by some hundreds of percentage points and that it is difficult to make the right choice between them. In this paper r a new model will be discussed. It integrates several factors that influence fluoride accumulation: rainfall, standing crop and dilution due to crop growth. This model is based on a concept of the causes of fluctuation of FG. Most elements of this concept have been evaluated in laboratory fumigations or measurements in the field. Regression analysis was performed only to quantify the coefficients in the equation. The first aim of this model is to relate standards for fluoride in fodder to atmospheric fluorides. This relation is of use in estimating environmental consequences of fluoride emissions. A second aim is that the model may be of use in evaluating the results of Fo monitoring programmes, e.g. to evaluate exceptional Fc values, to correct annual averages for missing values or unequal distribution of sampling data over the year. To be of use in practice, the model must not only be accurate, but must also be simple to use.
FLUORIDE CONTENT IN GRASS
261
MATERIALS AND METHODS
Field sampling Most of the field sampling was performed around three sources: two aluminium smelters and one glass factory. All sources emitted fluoride continuously. Grass was sampled monthly at eight to twelve sites around each of these sources. Additional measurements were made close to two brick factories, to estimate spatial and temporal variation of FG. To determine a background content of F6, containers of 301 with nutrientrich humus soil and a turf of Lolium multiflorum cv. 'Optima' were placed at three locations with no fluoride source closer than 30 kin. Every 14 days the grass was cut to just above soil level and the Fo was measured during the growing seasons of three successive years. All sites were located in The Netherlands. The Netherlands has an oceanic climate with an average summer temperature of 16 °C (June-September) and an average winter temperature of 5°C (December-February). Minimum temperatu.,'e is about - 12 oC and snow cover over pasture grass generally occurs two to three times per winter and lasts for less than 5 days. Precipitation is 7501 m-2 ( = 750 ram) per year and is equally spread over the whole year. Grass was cut from a pasture using a grass cutter, in a grid with 16 plots over an area of 9 m × 9 m. On each plot, about 200 c m 2 (one handful) was cut off. Areas within the sampling plots that had clearly been trampled by cattle were avoided. The grass was cut offjust above the leafbasis. This fixed height is important for two reasons. Firstly, fluoride is not equally distributed throughout the shoot: it accumulates in the leaf tips (Weinstein, 1977; van der Eerden, 1981 ). Secondly, there may be contamination of the grass by soil particles, this being greater towards the base of the stem. The percentage of soil in a grass sample has a seasonal fluctuation. Based on personal observations in earlier studies, this was approximately 2% (dry weight) in summer and 8% in winter using our sampling method. Cattle also consume soil when grazing: approximately 5% in summer and 20% in winter (Slooff et al., 1989). Soil fluoride is partly soluble in the gastric acid of the stomachs of cattle (pH 1.5-2.0). The percentage of fluoride in the soil that is soluble at a pH of 2.0 differs between soil types. Van den Berg et al. ( 1988 ) found a soluble fraction of 10% in clay and 45% in sandy soil. In winter, and on soil types with a high soluble fluoride content, the contamination of fodder with soil particles is important. If, for instance, the soil fluoride content is 400/~g g-! and half of it is soluble at a pH of 2.0, a maximum of 55/~g g- ~ in fodder means that in winter the fluoride content in grass without soil particles may be no higher than 30/zg g-i. In the rest of this paper, this point is ignored, because the fluoride content of the soil soluble at pH 2.0 in our field locations was 50 ~g g- 3 or less. In this paper, then, FG represents the fluoride content of cut grass,
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LJ. VAN DER EERDEN
and the fact that a small proportion of the measured fluoride originates from the soil is not considered.
Fluoridefumigations The fumigation experiments were performed in climate-controlled chambers, ventilated with charcoal filtered air. The temperature was 8-14°C, relative humidity 40-..70% and light intensity 25-40 W m - 2 ( 12 h day- i ). Wind velocity was very low: 0.2-0.3 m s -I. The grass Lolium perenne cv. 'Pelo' was used in the fumigation experiments. The grass was growing on soil with a pH(CaCI2) of 6.5, rich in nutrients and humus and with a fluoride content of I l0 ~g g-i. Gaseous HF was produced by supplying an HF solution with a constant flow in a heating system. After evaporation, the vapour was supplied to the ventilation air of the chambers.
Fluoride ,malysis The grass was dried for 24 h at 105 °C, ground in an electric coffee grinder, and 0.5 g was ashed for 2 h at 520°C. After a melt in NaOH, the material was dissolved in water. The fluoride was then distilled from the solution by sulphuric acid at 180°C, condensed and mixed with a colour agent, lanthanum alizarin complexan, and measured colorimetrically at a wavelength of 620 nm (Weinstein et al., 1972 ). All the steps in sample preparation and analysis were checked thoroughly, using the standard addition approach: recovery was 100%. The standard deviation of a grass sample from a pasture with a FG of 40 ~tg g- ~was on average 10 ~g g- i. Thi~ includes all variations caused by sampling, drying and analysis. The fluoride concentration in the air was measured using soda-coated silver balls (Buck and Stratmann, 1965): air was sucked through a tube full of these balls. After 24 h the coating of the balls was washed off with water and measured in a similar way to that used for the fluoride analysis in grass samples. RESULTS
Field experiments In areas without fluoride sources, the FG fluctuates with growth and precipitation (Table l ). Probably soil particles (considered to be a source of natural "contamination" ) cause the fluctuation in this background level of F~. To obtain information on temporal fluctuation, grass was sampled from one site in the vicinity of two brick factories over a period of 75 days. The sampling frequency over 2 weeks was once per day and in the other weeks
263
FLUORIDE CONTENT IN GRASS
TABLE ! Average fluoride content in grass (FG) standard deViation (gD)arid minimum-maximum values (minmax) (~g g- ' ) for low and high dry matter production ove/f | d days, in relation to precipitation in the last week before sampling date .
Rainfall in the week before sampling (mm)
Low dry matter production (50-150 g m - ' ) FG
SD
Min-max
n
<0.5 0.5-5.0 5.1-25 >25
6.0 4.0 3.0 2.5
2.4 2.6 1.6 0.8
4-10 3-10 1.0-6 2.0-4
8 12 12 10
.
.
High dry matter production ( 150-400 g m - ' ) '-"" Fo ~1~ Min-max 3.5 2.5 2.0
l,~J
1.3 0.5 1.0 0.7
3-6 2.0-3 1.0-4 0.5-2.5
17 6 2! 12
Fg in ,ug.g"~ :tO0ISOhmxinlUtfl I00-
~ ~
Pgs (+)
So]
i
t~
a
m
i
i
a
s
o
n
cJ
month
overage
i
f
|
|
m m m
i
J
w
n
;
!
o
n
cl
month
Fig. 1. Frequency distribution of fluoride contents in grass (Fo) with an annual average of 3842 #g g-i. The percentiles (P95, P75 and P50) show the percentage of measurements above the indicated levels (e.g. a P75 of 100 gg g - ' indicates that 25% of the Fo measurements are higher than 100 gg g- I ). Grass samples were taken during a 5 year period from 12 sites in the vicinity of two continuously emitting fluoride sources, n = 23 per month. The lower figure shows the monthly averages.
once every 4-8 days. The average FG was 40 gg g-~. The correlation between the FG on one day and the FG 2 days afterwards was 0.66. After 4, 14 and 30 days, the correlation decreased to 0.35, 0.21 and 0.16, respectively. In this case study, very rainy days (more than 2 mm in 24 h) caused a decrease in FG of 80% of the initial level.
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L.J. VAN DER EERDEN
TABLE 2 Ratio of the fluoride content in grass, measured at half-monthly intervals and the corresponding annual average. The annual average is based on 12 measurements, equally spread over the year. The grass samples were taken during a 5 year period from several sites in the vicinity of two continuously ~'r~ittiag fluoride sources. To calculate this ratio, referred to as the seasons index, 130 sets of i 2 measuremelits with 2n annual average of 38-42/~g m - 3 were used Period
Seasons index
Period
Seasons index
First half of January Second half of January First half of February Second half of February First half of March Second half of March First half of April Second half of April First half of May Second half of May First half of June Second half of June
1.5 1,7 !.9 2.1 1.9 1.6 !. I 0.7 0.6 0,6 0.6 0.5
First half of July Second half of July First half of August Second haifofAugust First half of September Second halfofSeptember First haifofOctober Second half of October First half of November Second half of November First half of December Second half of December
0.5 0.6 0.6 0.6 0.6 0.7 0.8 0.8 0.9 1.0 l. 1 1.3
Besides daily fluctuations in F6, a seasonal pattern was also found. Figure l shows monthly averages of 32 sets of FG with an annual average of 38-42 /~g g-I. Each set consists of 12 Fc, sampled on the same plot: one for each month. Sampling was performed from 12 sites around two continuously emitting point sources. With an annual average FG of 40/~g g-l, monthly averages fluctuate from 70/~g g-I in February to 20/zg g- ~ in June. In February, 90/~g g-* is exceeded once every four measurements and 120/zg g-~ once every 20 measurements. Based on the same data set, an average pattern in seasonal fluctuations of Fo can be calculated. Twelve FG values, obtained from samples taken at monthly intervals from the same plot, give the annual average. The Fo measured on a certain date was divided by the corresponding annual average. This ratio is given in Table 2. These ratios are based on annual averages of 38-42/~g g-m. Lower average FG values also appear to follow these seasonal patterns, however: the lowest FG values, mentioned in Table l were found in the middle of the growing season. Information concerning annual average FG values of more than 50/~g g- ~ is very limited. The level of correlation between FA and Fc measured during four subsequent growing seasons on a site close to an aluminium smelter appeared to depend on the definition of FA. If FA was averaged over the period before the sampling date, beginning after the last rainy day (more than 2 mm rain in 24 h), the linear regression was FG = -- 1.8 + 72.3 FA
265
FLUORIDE CONTENT IN GRASS
400 A
To,
(a) 300
(n
5.3 ug.m-3 c_
3.7 ug.m-3
200
0 . 8 3 ug.m-3 100
t
0 0
5
10
15
20
exposure period (days)
400 A
I ol
(b)
--~ 300 m
C_
200
§ .~
100
.9..
@
17 days
[]
6 days
&
1 day
T
0 0
2
4
6
atmosphertc I-IF concentration (ug,m-3)
Fig. 2. (a) Relation between fluoride content in grass (FG, Lolium perenne, cv. 'Pelo') and atmospheric hydrogen fluoride concentration (F^). Plants were exposed in controlled environment chambers to three concentrations: 0.83 #g m -3, 3.7 #g m -3 or 5.3 #g m -3 for 0.5 day, 1 day, 3 days, 6 days, 9 days, 13 days or 17 days. The vertical bars show one standard deviation at each side of the mean. n=4. (b) Relation between fluoride content in grass (Fo, Lolium perenne, cv. 'Pelo') and atmospheric hydrogen fluoride concentration (FA). Data are similar to those in (a) at exposure periods of I, 6 or 17 days, but are presented in relation to FA concentration.
The explained variance in this regression is 39% (n=22). If, instead of the average, the highest FA during that same period is used (indicated by F~, ), the regression takes the form F6=3.8+31.0 F~ Here, the explained variance has increased considerably to 68%. This sup-
266
L.J. VAN DER EERDEN
ports the supposition that a peak in FA is more important to FG than the average FA. After an exposure period, FG decreases as a result of growth, senescence, wind and precipitation. In field measurements, an average "half-life" of fluorides in grass of 4 days in summer and 12 days in winter was found in periods with background levels of FA and no precipitation. Fumigation experiments In a fumigation experiment, grasses were exposed for 0.5, 1, 3, 6, 9, 13 and 17 days to three FA levels. Biomass increase was not affected by the fumigations. With a constant FA, FG tends to reach equilibrium. This level is linearly related to FA, SOit is not a real saturation level. In the fumigation experiments presented here, at an FA of 0.83/~g m - 3, equilibrium was reached after 2 days, but it lasted longer with higher FA values (Fig. 2 (a)). In the same experiment, a linear relation between FA and FG was found. The slope of this relation increases with longer exposures (Fig. 2 (b) ). In another fumigation experiment lasting for 5 days with an FA value of 2 /~g m - 3, the influence on FG of wind velocity was examined between 0.25 and 5.0 m s -~. The relation between wind velocity (V) and FG was FG=81.7+12.1 V
(n=53, r=0.83)
(7)
Modelling the relation between F,~ and F~; Based on the above conclusions, a relation between FA and FG has been defined. This relation is composed of the following elements. ( l ) Fo is linearly related to FA. Therefore, FG = k FA (Fig. 2 ). (2) The increase in FG during exposure is faster than the decrease after exposure. (3) An exposure period can be considered to start after a day with more than 2 mm rainfall (FG has become very low then) and ends on the sampling date. The highest FA in that period (indicated as F~ ) determines FG. Th~refore, FG ffi KF ~,. (4) After the day that F~ has occurred, FG decreases. The velocity of decrease is dependent on the season. To describe the decrease of FG, a seasons index can be introduced in a negative exponential function: e x p - (K2Si- ~T). Si is the seasons index as mentioned in Table 2 and T is the number of days between the day F~ occurred and the sampling date. From regression analysis it was concluded that K2 is 0.1. (5) In the formula: K Si F~, e x p - (0.1 Si -~ T), K can be estimated by relating measured and calculated values of FG. This has been done with 127
FLUORIDE CONTENT IN GRASS
267
measurements around two fluoride sources in southwest Netherlands. K was estimated as 90. Thus the total model becomes
FG=9OSiF~,exp ( - 0 . 1 S i -~ T)
(9)
Si is the seasons index (Table 2), F~ is the highest (24 h average) FA between a day with more than 2 mm rain and the grass sampling date. T is the number of days between the day that F~ occurred and the sampling date. DISCUSSION
Many research workers mention a background FG level of 10-22 ~tg g(Benedict et al., 1964; Guderian et al., 1969; NAS, 1971, Less et al., 1975 ). De Temmerman et al. ( 1978 ) found background level~ in 12 grass species of between 2 and 6/~g g-~. However, Table 1 suggests that completely uncontaminated grass of the species Lolium multiflorum probably contains only 1 or 2/zgg -~. A significant (P<0.05) but low correlation was found between Fc values measured on the same site with an interval of I day (0.66). This correlation decreased considerably with longer time intervals. This indicates that an FG value on a certain day provides limited information about FG values which existed on the days before and after that sampling date. In other words, a sampling frequency of once a month (which is normally used in monitoring programmes) does not represent an average over the total month, but is only a random sample out of a population of some 15-30 values. These results on temporal variation of FG are in agreement with the findings of de Temmerman (1984). Davison et al. ( 1979 ) found somewhat larger fluctuations. The observation that rainfall can decrease FG is in agreement with most literature data. A negative correlation between FG and rainfall was also found by Davison and Blakemore (1976) and de Temmerman (1984), although the slope of this regression differs considerably between the authors. It must be attributed to the fact that the relation between F6 and rainfall is much more complicated than only a relation between the volume of precipitation and FG. Figure 2 (a) shows an equilibrium level for Fc after a certain exposure period. The length of this period was longer with higher FA levels: 2 days at 0.8 gg m-a and more than 15 days at 5.3 gg m-3. These results are from a fumigation experiment in which boundary layer resistance probably dominates over stomatal resistance owing to the very low wind velocity (0.2-0.3 m s-m ). In another experiment, a linear relation between fluoride accumulation in grasses and wind velocity was found up to 5 m s-~, the maximum velocity used in this experiment (eqn. (7) ). Above 1 m s- ~, stomatal resistance dominates over boundary layer resistance. In the field, with wind velocities of more than 1 m s -~, most of the time an equilibrium between FA and FG will
268
L.J. V A N D E R E E R D E N
(a)
Ill
FG
~1
FG calculated
measured 400
" f,g.3-a
( 1976-1981)
300 A
I
200
0 U. 100
5678910
5678910
5567810
5678910
567B910
445678910 month
(b)
I
FG measured
I---I
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150 fig 3-b
1982- 1989) ]
100 I
0
U.
50
6
12
6
12
6
12
6
12
6
12
6
12
6
12
6
month
Fig. 3. Fluoride content in pasture grass (Fa, ~g m -s), measured in a sample (solid bars) and calculated with the FA/FG model (dotted bars), using local measurements of rainfall and atmospheric fluorides. The pasture consisted mainly of Lolium perenne. (a) Course of fluoride content in pasture grass at 1.5 km from an aluminium factory. Grass sampling was done once every 4 weeks and only during the grazing season. (b) Like (a), but in this case grass sampling was usually done over the whole year. (c) Fluoride content in pasture grass, measured I km from a glass factory. Grass sampling was done once every 14 days in the period from June to October and every day in the first week of November.
269
FLUORIDE CONTENT IN GRASS
~
(c)
Iml
FG measured
FG calculated
200
Iflg. 3-c I A
I 100 L9 LL
j 0
6
7
7
8
8
9
9
•7m-i 1o
lO
1o
lO
11
11
1
11
11
11 11
month
Fig. 3. Cont.
probably be reached much faster. A negative correlation with wind velocity was found by de Temmerman (1984), but his measurements were not made during fumigation with HF, but directly afterwards: higher wind velocities caused considerable loss of fluorides from the grass. Seasonal fluctuations in FG as shown in Table 2 were also reported by Guderian et al. (1969), NAS (1971 ), de Temmerman (1984) and Slooff et al. (1989). Craggs et al. ( 1985 ) conclude that this seasonality does not always Occur and is not due to dilution of fluoride in the case of dry matter production. Growth dilution is often of minor importance, which can be concluded from the observation that FG can decrease drastically within I or 2 days. This rapid decrease cannot be caused by growth dilution only. Standing crop and the effect of surface roughness on deposition velocity is probably of more importance. The absence of seasonality in FG, as found by Craggs et al. (1985) may be caused by an abundance of influential factors, such as rainfall and wind which are discussed in this paper. One consequence of the large seasonal fluctuation is that for an accurate calculation of an annual average based on monthly sampling, no monthly value can be missed. If, for example, the February value is not used, an annual average of 40/lg g-i becomes 34/~g g-~. The seasons index (Table 2 ) can help to estimate a missing value, using the rest of the measurements. The reliability of the FA/FGmodel, presented above, has been tested at two locations. The results are illustrated in Fig. 3. One location was 1.5 km from an aluminium factory. The ratio of gaseous and particulate fluoride emission was estimated to be 4: I. No other fluoride sources were present in that area.
270
L.J. VAN DER EERDEN
Close to the site where grass was sampled, FA and rainfall were measured at 24-h intervals. The sampling frequency for grass was once a month. In the first 6 years, measurements were performed only during the growing season (Fig. 3(a) ). In the following 7.5 years, sampling took place in almost every month of the year (Fig. 3(b) ). In winter during the following years, no grass sampling occurred when the pasture was covered in snow. The correlation between calculated and measured values of Fc was 0.82. The explained variance in this case was 67%. On another site, l km from a glass factory which only emitted HF, another check on the reliability of the FA/FG model was done (Fig. 3 (c)). The data set was much smaller and the grass sampling frequency was higher in this case. A correlation between measured FG and FG calculated with the FA/FGmodel was 0.82. It must be concluded that the model does not have sufficient accuracy to predict (or substitute) FG measurements. Certainly, the model would gain in accuracy if the actual biomass (as a result of growth, grazing or mowing), the duration and intensity of rain showers and the fluctuation of FA concentrations within 24 h were taken into account. But this would require enormous measuring facilities and effort to collect all the required data. The model is suitable, however, for simulating the behaviour and fluctuations of FG and to relate standards for FG tO standards for FA and also to 'generalize' measured FG levels. Some examples will illustrate these uses. The model gives some insight into the possible daily fluctuations of FG and explains why a sampling frequency of once a month only gives very limited information on the monthly average FG because the fluctuations can be considerable. The model also offers the possibility to standardize. If, for instance, sampling has taken place during an exceptionally long dry period, it can be estimated from the model what the Fc would have been in a dry period ofaverage length. The FG at a given FA in a certain period of the year can also be calculated. For example, a 24 h average of FA of 2.8/~g m - a (a recommended standard in The Netherlands) causes an FG of 50 ~g g - ' in summer (June) and 180~ugg- ' in winter (February). After 4 dry days, FG is 24/~g g- ' in summer and 147 ~g g - ' in winter. The model can calculate thresholds for FA, given a maximum permissible FG. For an FG of 55/~g g-~, FA (24 h average) must be 0.3/~g m - a. If only the grazing season (April-October) is taken into account, FA can be 0.8 ~ g m - 3. Nevertheless, the model indicates that to prevent values of FG in excess of 55 /~g g-~, FA must be considerably lower than the FA thresholds that are assumed to protect plants. If an FG of 55/~g g-~ is not considered to be an absolute maximum, but a maximum for a monthly average, it depends on the frequency distribution of FA as to which levels are tolerable. The reliability of the FA/FG model was tested on data sets other than the one used to parameterize the model. In this respect, it is an exception: the
FLUORID[~ CONTENT IN GRASS
271
models presented in the introduction (eqns. ( 1-6 ) ) only describe the FA/Fc relation under conditions from which the data originate. A quantitative comparison between the models is only possible with some assumpti~ms (on preand post-exposure perinds, seasonal effects, rainfall and the ratio of gaseous and particulate fluorides). In the very simple situation of background levels of FA, followed by a few days with elevated HF concentrations in a dry period, the FA/Fc model presented in this paper gives about the same results as eqn. (5), but only in ~he range of FA of 0.2-2/~g m - 3. Other equations predict considerably lower FG values. For an accurate comparison, however, more detailed information on the local situation is necessary. The FA/F6 model presented here is based on measurements in a moderate oceanic climate, but it may also be useful under other climatic conditions. In that case, the seasons index (Table 2) and the definition of F~ must be adapted. ACKNOWLEDGEMENTS
The author wishes to thank G. Laurens who did the chemical analyses and J. van Achterberg for assistance in the field experiments.
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Van Haut, H. and Krause, G.K.H., 1982. Fluorwasserstofwirkungen aufPflanzen. LIS-berichte, 25. Landesanstalt Ffir Immissionsschutz, Essen, Germany, 60 pp. Walton, K.C., 1988. Environmental fluoride and fluorosis in mammals. Mammal Rev., 2: 7790. Weinstein, L.H., 1977. Fluoride and plant life. J. Occup. Med., 19( 1 ): 49-78. Weinstein, L.H., Jacobsen, J.S. and Mandi, R.H., 1972. Fluorine: semi-automated method. J. Assoc. Off. Anal. Chem., 5: 998-1003. Wood, R., 1973. Fluorine as a pollutant. Trans. J. Br. Ceram. Soc., 1: 35-37.