Environ. Sci. Technol. 2011, 45, 1028–1033
Predicting National Exposure to a Point Source Chemical: Japan and Endocrine Disruption as an Example A N D R E W C . J O H N S O N , * ,† JUNICHI YOSHITANI,‡ HIROAKI TANAKA,§ AND YUTAKA SUZUKI| CEH Wallingford, Wallingford, Oxfordshire, OX10 8BB, United Kingdom; National Institute for Land and Infrastructure Management, 1 Asahi, Tsukuba, Ibaraki Prefecture, 305-0804, Japan; Research Center for Environmental Quality Management, Kyoto University, 1-2 Yumihama, Otsu, Shiga 520-0811, Japan; and Public Works Research Institute, 1-6 Mnamihara, Tsukuba, Ibaraki 305-8516, Japan
Received October 4, 2010. Revised manuscript received November 25, 2010. Accepted November 29, 2010.
The predicted aquatic estrogen concentrations for the whole of England and Japan were determined and compared using population and flow data. The overall value for English surface waters was 0.9 ng/L estradiol equivalents (EEQ) compared to 0.1 ng/L overall for Japan. Available dilution of sewage effluent was considered to be more important than contraceptive pill usage in this relative risk. A national survey of Japanese rivers using the yeast estrogen assay (YES) gave a median value of 0.27 ng/L EEQ which, while higher than that predicted, confirmed an overall low endocrine disruption risk. Using local population and flow data for 27 separate catchments, the predicted EEQ and measured EEQ (YES) values compared well, confirming the national picture that endocrine disruption would not be a widespread phenomena in Japan. Simple predictions based on population and flow can give an appropriate “ball park” value for catchments and even nations for concentrations of polar organic contaminants which have a majority human origin.
Introduction Historically much of our concern surrounding organic pollutants that contaminate the aquatic environment has focused on diffuse sources such as pesticides from agriculture, and specific industrial point sources. Assessing the level of national risk required considerable geographic information such as where pesticides were applied, soil type, and amount of runoff (1), or the location of specific industries (2). The contamination of the aquatic environment with point source chemicals such as pharmaceuticals from the human population has introduced a new and unwelcome dimension. While farming practices may be changed, pesticides banned and industries curbed, pharmaceuticals and other natural human excretion products cannot be so easily controlled. The synthetic estrogen 17R-ethinylestradiol (EE2) is a classic example of a chemical that is not likely to be banned any * Corresponding author e-mail:
[email protected]. † CEH Wallingford. ‡ National Institute for Land and Infrastructure Management. § Research Center for Environmental Quality Management, Kyoto University. | Public Works Research Institute. 1028
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time soon due to its societal benefits yet it has clear harmful effects on fish (3, 4). In the light of this new threat of endocrine disruption with an organic contaminant originating directly from the human population, many nations instituted survey programmes either to measure the chemicals, or assess their effects on wildlife. That endocrine disruption proved to be a worldwide issue was unsurprising, since estrogen excretion is common to human beings and EE2 together with sewerage systems are common to developed nations. While sewage effluent concentrations of estrogens tended to be fairly similar, concentrations and endocrine disruption effects in receiving waters were very different both within and between nations. Thus, it was unclear just how serious the threat of endocrine disruption actually was across a nation. This prompted countries like the U.K., Japan, Holland, Switzerland, Austria, and Ireland to institute very broad chemical and fish monitoring studies (5-11). Such surveys are extremely demanding both in the technical and logistical sphere and consequently very expensive. Not every nation is in a position to commission such large surveys to allay the fears of their environmental and wider public communities. However, unlike pesticide, or industrial chemical issues, the concentration and hence risk associated with a point source chemical emanating from the human population should be eminently predictable. This is because most of the important information to assess the risk is readily at hand. These include the size and location of the human population and flow in the rivers receiving the chemicals. Assessing the per capita discharge of the chemical requires more research, but often, as with estrogens, research in this area has already been published (12). In recent years, such information has been fed into sophisticated GIS water quality models, which predict concentrations over each and every reach in a catchment, taking into account natural attenuation (13-15). This is something of a specialist skill and requires the existence of established GIS water quality models. However, before getting into such detail, a much more simple procedure can be attempted. At a national level, the entire runoff water volume can be used to dilute the products of the national population, thus giving a national predicted aquatic environmental concentration (PEC). Alternatively, the PEC for a range of representative catchments can be calculated. In this case, a suitable downstream location in a catchment such as a flow gauging point is selected. The recorded flow values from the gauging station can be used to dilute the products of the upstream human population to give a catchment PEC. The absence of subtleties such as in stream attenuation and natural flow variations will limit their precision. But a suitable range of PECs can be calculated based on the available flow statistics such as the 25th percentile and 75th percentile flow values. As a first tier assessment of local, or national, risk the attraction of such an approach is obvious as it can provide an answer relatively quickly and at negligible cost. As a densely populated series of islands, with relatively short rivers, Japan has been concerned for over a decade by the threat posed by endocrine disruption to its aquatic wildlife. Like many developed nations, this concern has now spread to other pharmaceuticals and personal care products discharged to water bodies by its human population. Both fish surveys and chemical surveys have been carried out over the years to assess the level of the endocrine disruption threat. To some peoples’ surprise, the extent of endocrine disruption and level of endocrine disrupting chemicals in rivers did not seem to be as high, or as widespread as in other similarly 10.1021/es103358t
2011 American Chemical Society
Published on Web 12/17/2010
TABLE 1. Comparison of English and Japanese National Populations, Geography and Predicted Average Water Estrogen Concentrationa factor
England
Human population in 2004 Land surface area % Population connected to sewer system Inland population connected to sewers (discounting those discharging to sea) Contraceptive pill take up Excretion of normalized national person (µg/d) Estrogenicity generated from a normalized person post activated sludge treatment (µg/d) (14)
Inland natural mean flow
Inland available dilution/inland population Average estrogenic potency of inland water Japanese population adopts contraceptive pill at English level English population stops taking contraceptive pill a
NA, not applicable.
b
Japan
50.1 million (36) 129 009 km2
127 million (37) 374 744 km2
96% (17)
68% in 2004 (38)
28.6 million (14)
57 million (18)
17% total female population (12)
not included
13.8 E1 + 3.3 E2 + 0.89 EE2 ) 16.8 EEQ
b
13.8 E1 + 3.3 E2 ) 7.9 EEQ
4.3 E1 + 0.6 E2 + 0.15 EE2 ) 3.53 EEQ
4.3 E1 + 0.6 E2 ) 2.03 EEQ
109 million m3/d average natural flow in inland catchments (14)
Japan receives 1690 mm rain a year,(39) this translates to 1735 million m3/d of rainfall given the area of Japan. With runoff 1090 mm (39, 40) this gives 1119 million m3/d flow for Japan
3.8 m3/d/cap
19.6 m3/d/cap
0.93 ng/L EEQ
0.10 ng/L EEQ
NA
0.18 ng/L EEQ
0.53 ng/L EEQ
NA
Estradiol equivalent, or EEQ ) E2 + E1/3 + 10(EE2) (16).
developed countries such as England (5-7). Perhaps this was predictable? The objectives of this work were to predict estrogen exposures on a national basis for England and Japan and compare the relative risks of endocrine disruption faced by the two countries. Second, to compare predicted catchment aquatic estrogen concentrations using flow and population data for 27 Japanese catchments against a large data set of existing yeast estrogen screen (YES) measurements.
Model and Measurement Approach National Predicted Estrogen Concentration. Although this exercise was focused on predicting estrogen concentrations in Japan, a prediction for England was also made by way of comparison. England was selected because studies on the extent of endocrine disruption in wild roach have revealed up to a third of the male fish in the surveys to be affected, thus, implying a high river estrogen content (5, 16). England represents 54% of the land surface of the UK but holds 84% of its population. Output from the geographic based hydrological model LF2000-WQX model was used for the assessment of the population in England discharging their waste inland (14). In this case, all sewage outfalls (and their associated populations) discharging to sea, or within 1 km of the coast were excluded. Thus, several population centers such as most of London were largely excluded. The proportion of population connected to sewers was reported as 96% (17). Information was also directly available for Japan on the inland excreting population connected to sewers (18). As Japan has a mountainous backbone which runs for most of the length of the home islands (19), many of the major cities, such as Tokyo and Osaka, are located by the sea, so much of their waste does not enter the freshwater environment. The amount of flow, or dilution available to these inland populations in England and Japan was taken to be the mean annual runoff (Table 1). For England, the predicted runoff
provided by the LF2000-WQX model was used which is based on rainfall data from 1960-1991 (14). In terms of the natural estrogens, it was assumed that both English and Japanese populations would excrete the same quantity of 17b-estradiol (E2) and estrone (E1) per capita (14). Although there is some evidence that Asians and Western Europeans are slightly different in their excretion profile (20), in terms of estrogens observed in sewage effluents these differences are not large (21). For England, a predicted discharge of EE2 from the contraceptive pill was used (12). These predicted per capita discharges of estrogens following sewage treatment have been found to compare well with field observations (16, 22). The evidence suggests that despite being approved in Japan as a contraceptive in 1999, the pill remains unpopular and has rarely been detected in sewage effluent (21, 23). Therefore, in this assessment EE2 was discounted from the estrogen discharge calculations for Japan. The significance of omitting EE2 from the Japanese calculations is considered in more detail later in this work. Following discharge from sewage treatment, no further estrogen processing was assumed other than dilution. The approach can be summarized as an equation: EEQave ) (EPi × EEQ_outpc) ÷ r where EEQave is the national E2 equivalent concentration for the country (ng/L), EPi is the inland human population connected to sewers, EEQ_outpc is the per capita excretion amount after sewage treatment (µg EEQ/cap/d), and r is the national runoff (m3/d) based on a mean annual value. Predicting Estrogen Concentrations for 27 Selected Japanese Catchments and Comparing against Observed Yeast Estrogen Screen (YES) Data. For 27 selected Japanese rivers, comprehensive information was available from an MLIT database, including their resident population and their connection to sewers and to STPs. For these catchments, their most downstream gauging stations that were above the VOL. 45, NO. 3, 2011 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Map of Japan showing the main stem of the rivers, the gauging stations (filled circles), and their proximity to the sampling locations for the YES assay study (arrows). tidal limit were identified. At these locations, their mean, 25 percentile and 75 percentile flow values from the period 1993-2003 were collected (24). Using these flow and population values, the catchment EEQ values could be calculated based on a per capita estrogen discharge as before. In this case, a range of possible EEQ values were calculated from a high flow 25 percentile value, a mean flow and lower 75 percentile flow value. A widespread survey program of Japanese rivers using the YES was carried out in the years 1998 to 2001 (6, 25, 26). The method involved rinsing the sample bottle, taking a 1-L river water sample, filtration (1 µm), and then concentration on a C-18 solid phase extraction cartridge. Following methanol extraction, the eluate was dried down and redisolved in dimethylsulfoxide (DMSO). The extract in DMSO was diluted in series with 5:1 (distilled water to concentrate) for the YES assay. Incubation was for 7 d at 28 °C before the 96-microtiter wells were read for absorbance. In this survey, over 200 locations on 40 rivers were sampled resulting in 179 determinations. The majority of these locations were toward the bottom of their respective rivers but above the tidal limits. Fortunately, the locations where the YES samples were taken included the selected rivers near the 27 gauging stations, thus, enabling comparisons of predicted and measured EEQs to be made (Figure 1). All of these locations were sampled in autumn 2001, with some of the rivers being previously sampled in autumn 1998, spring, summer, and autumn 1999, and also in autumn 2000. Sampling avoided very high flow events in these rivers.
Results and Discussion National Predictions. In the U.K., a precautionary value of fish endocrine disruption effects starting at 1 ng/L EEQ has been suggested (14), and with Japanese medaka, a lowest observable effect value of 5 ng/L EEQ has recently been reported (27). Thus, where predicted, or measured, EEQ values exceed 1 ng/L then some endocrine disruption effects might be expected, and this concern rises particularly where levels exceed 5 ng/L EEQ. The national predictions here 1030
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indicate an overall EEQ of 0.9 ng/L for English rivers and only 0.1 ng/L for Japanese rivers based on mean flow (Table 1). This suggests endocrine disruption effects might occur much more frequently in England than Japan. In fact, the median YES value for the Japanese rivers survey was reported as 0.27 ng/L EEQ (26) which was higher than the prediction made here perhaps because the latter study included many tributaries receiving higher percentages of STP discharges in the river flows than those in the major rivers. Nevertheless, the prediction of EEQ concentrations being largely below effect levels in Japanese rivers appears to have been born out. Why is the risk of endocrine disruption in fish in England apparently 3-9 times greater than in Japan? Due to the popularity of the contraceptive pill in England compared to Japan, it is predicted that the normalized per capita estrogenic discharge will be greater in England than in Japan (Table 1). Although Japan is assessed as having a greater inland population than England, its greater mean flow, and hence available dilution per capita (five times more), suggests its combined steroid estrogen potency will be less across its rivers. If the Japanese population were to take up the contraceptive pill to the extent of that in England, then the national PEC would rise from 0.10 to 0.18 ng/L EEQ. Thus, widespread endocrine disruption would still not be predicted because of the large amount of available dilution. However, if the English population were to stop using the contraceptive pill, then all other things being equal, the national PEC would drop from 0.93 to 0.53 ng/L EEQ, i.e., below effect levels. Predictions for 27 Catchments. A weakness of a national mean estrogen value is that it does not give an impression of the variation between catchments around a country, nor the impact of natural seasonal variation in the flow on the concentration (28). The catchments studied here were spread over each of the main Japanese home islands of Hokkaido, Honshu, Shikoku, and Kyushu and contained 10.5 million people covering an area of 55 810 km2 (Table 2) which represents 8% of the population and 15% of the land area of Japan. Some of the catchments were very small, such as the Kiku with 34 km2 and others very large, such as the Ishikari
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area (km2)
E141,42,02, N43,54,30 E141,43,00, N43,53,16 234 14 548 E143,54,47, N 43,47,57 E143,58,20, N43,55,06 1394 89 331 E141,20,36, N43,13,53 E141,31,30, N43,08,06 12 687 955 315 E139,48,55, N, 38,50,28 E139,48,55, N38,50,25 695 73 314 E141,17,11, N38,39,31 E141,17,07, N38,39,44 7869 750 529 E139,36,32, N35,30,54 E139,36,28, N35,30,53 134 925 139 E140,34,03, N36,29,42 E140,33,16, N36,29,47 1 422 114 200 E140,19,45, N36,32,49 E140,25,53, N36,25,17 2181 272 814 E136,31,00, N36,24,02 E136,26,14, N36,24,39 167 62 330 E137,35,21, N36,48,52 E137,26,00, N36,54,51 637 78 476 E139,27,40, N38,08,06 E139,25,30, N38,08,54 1127 19 317 E138,48,04, N37,18,31 E138,48,09, N37,18,38 9719 2 144 530 E138, 05,19, N34,44,19 E138,14,50, N34,42,50 34 1346 E138,21,54, N34,57,37 E138,22,02, N34,57,35 537 218 998 E136,52,41, N35,11,59 E136,52,03, N35,11,32 705 1 112 519 E136,52,41, N35,24,02 E136,44,06, N35,18,42 4684 612 207 E135,36,59, N34,34,52 E135,29,24, N34,35,36 962 1 605 462 E135,07,28, N35,18,16 E135,13,10, N35,25,30 1344 184 524 E133,20,23, N34,29,24 E133,22,30, N34,27,27 817 240 856 E133,53,23, N34,10,23 E133,48,47, N34,17,15 90 20 227 E133,41,03, N33,33,54 E133,40,57, N33,34,02 468 19 947 E133,24,59, N33,32,57 E133,26,53, N33,29,38 1463 31 809 E134,20,52, N34,05,25 E134,25,38, N34,05,45 3044 301 643 E130,02,42, N32,51,08 E130,03,31, N32,50,44 36 12 470 E130,58,32, N,31,21,47 E130,58,26, N31,21,40 450 36 710 E131,30,31, N33,11,42 E131,36,20, N33,12,05 412 86 668 E130,29,42, N33,19,10 E130,29,25, N33,18,41 2295 557 429 55 810 10 562 485
grid ref of gauging stat. (first) and nearest water sampling location (second) 1.97 10.6 255.6 41.4 179.7 5.4 14.9 36.1 5.9 6.7 51.0 284.6 0.6 5.3 10.3 108.1 9.4 22.5 1.6 0.4 3.7 24.5 39.5 0.8 17.4 9.8 43.0
9.21 24.3 511.0 107.9 374.1 8.7 30.4 85.5 22.0 22.7 162.2 579.1 2.1 23.7 24.7 256.8 21.9 57.8 7.3 1.3 22.7 80.6 91.8 1.5 28.0 18.8 90.8
11.1 22.9 478.5 86.6 322.4 9.2 37.7 78.2 16.5 25.1 125.2 485.7 2.1 27.4 25.3 241.1 24.1 50.7 9.1 1.7 26.5 94.0 117.6 2.2 29.8 18.7 104.9
65.7 22.1 43.3 101 37.1 0.9 28.0 24.8 22.9 27.7 560.1 19.6 134.1 10.3 2.0 34.0 1.3 23.8 3.3 7.3 114.9 255.2 35.2 15.2 70.1 18.6 16.3
0.03 0.09 0.05 0.02 0.05 2.3 0.07 0.08 0.09 0.05 0.0 0.10 0.01 0.19 1.01 0.06 1.54 0.08 0.61 0.27 0.02 0.01 0.04 0.13 0.03 0.11 0.12
0.37 1.04 0.26 0.29 0.23 13.5 0.30 0.66 0.53 0.19 0.21 0.24 0.07 0.1 4.1 0.19 2.07 0.27 0.19 0.48 0.08 0.06 0.20 0.17 0.52 0.26 0.22
2001 2001 1999, 2001 2001 1998, 1999, 1999, 2001 2001 1999, 1999, 2001 2001 1999, 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 1999,
location 16 line Bgde Chushi Bridge 2001 IshikariOhashi Hamanaka Tome 1999, 2001 Kamenoko Bridge 2001 Sakakibashi 2001 Noguchi Tsurugashima Bridge Shimokurobe Bridge 2000 Asahibashi 2001 Asahibashi Takada Bridge Abekawa Bridge 2000, 2001 Biwajima Noubi Bridge Kashiwara Yuragawa Bridge Komizunomi Bridge Marugame Bridge Fukabuchi Nakajima Takase Bridge Asahimachi Matase Hunai Bridge 2000, 2001 Senoshita
year sampled
Where reported values are for a single year this reflects a single determination. Multiple years have up to a maximum of five observations and here the mean is given.
Owada Kitami Ishikariohashi Hamanaka Tome Kamenoko Bridge Sakakibashi Noguchi Haneda Unazuki Tsuzurayama Ojiya Kamo Tegoshi Biwajima Inuyama Kashiwara Fukuchiyama Yamate Tsunekaneba Fukabuchi Ino Chuobashi Urayama Matase Dojiri Senoshita
Rumoi Tokoro Ishikari Aka Kitakami Tsurumi Kuji Naka Kakehashi Kurobe Ara Shinano Kiku Abe Syounai Kiso Yamato Yura Ashida Doki Monobe Niyodo Yoshino Honmyo Kimotsuki Ooita Chikugo totals
a
gauging sta.
river
mean population mean dilution predicted observed connected 75 percentile 25 percentile flow flow/cap/d mean YES EEQ to STP flow (m3/s) flow (m3/s) (m3/s) (m3) EEQ (ng/L)a
TABLE 2. Comparison of the Selected Japanese Rivers Catchments, Predicted Mean Catchment EEQ and Observed Mean YES EEQ Data
FIGURE 2. Predicted mean (bow tie symbol) and range (columns) of EEQ (ng/L) based on 25 percentile and 75 percentile flow values for 27 Japanese rivers compared against measured YES values. Note Tsurumi in 1998 and Syounai in 1999 also recorded single off scale values of 31 and 18 ng/L EEQ, respectively. of 12 687 km2, therefore there is both a geographic and size diversity in the selection (Figure 1). The location of the YES sampling points were mostly very close to the downstream gauging station of the catchment used for the prediction making comparison possible (Figure 1). By predicting estrogen values for both the 25 percentile and 75 percentile flows, it was expected that half of possible EEQ values would fall between these points (Figure 2). It may seem surprising that the mean predicted value was often lower than the 25%ile predicted flow value (lowest point on the bars) but this is related to the disproportionate effect occasional very high storm flows has on the mean. The YES assay has been successfully used to demonstrate the combined estrogenic potency of a range of endocrine disrupting chemicals in water for well over a decade (29). In countries such as the U.K. and Japan the major estrogenic component (98%) as detected by YES in sewage effluent have been identified as the steroid estrogens (23, 30). Thus, it might reasonably be expected that the estrogenic signal picked up by the YES assay in river water would reflect the combined steroid estrogen content (31-33). Where three to five measurements were made for the same river location, the typical variation was no more than 5-fold (Figure 2). The greatest variation was for the Syounai river which was 9-fold. Thus, the hydrological conditions when samples taken were, in most cases, not extreme, either by virtue of very low, or very high flows. The prediction method indicated that high catchment PECs could be expected in the Tsurumi, Syounai, Yamato, Ashida, and Doki rivers (Figure 2). The YES data did indeed report high YES values for these rivers (>1 ng/L EEQ). However, the majority of the rivers were predicted to have values well below 1 ng/L EEQ and this also was corroborated by the measured YES data (median value 0.24 ng/L EEQ). As a check for the YES survey, additional direct E1 and E2 measurements were also made at many of the sampling locations using liquid chromatography tandem mass spectrometry (6). At these times and locations it was found that the combined E1 and E2 concentrations had an estrogenic potential comparable to that found in the YES assay. Thus, the catchment predictions, while not a perfect match to the YES values (Table 2), were giving the same overall message of a low estrogen presence in most rivers. Implications. The predictive calculations, which were largely corroborated by the field YES measurements, suggest estrogens in most river water would be below effect concentrations and so widespread endocrine disruption would not be expected throughout Japan. It should be acknowledged 1032
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that other factors will moderate the actual endocrine disruption outcome, such as the fish species sensitivity. But, with some exceptions, the field studies would appear to corroborate this low endocrine disruption impact (7). Of course there will be “hot spots” and unfortunately there remain large and important catchments, such as the Yodo and Tone (not explicitly examined here) where high population densities compared to their diluting capacity would yield much higher estrogen concentrations and the possibility of endocrine disruption (34, 35). Overall, this work suggests simple predictions based on population and flow can give an appropriate “ball park” value for catchments and even nations for concentrations of polar organic contaminants which have an exclusively human origin. For such chemicals, we recommend these simple calculations be carried out before starting catchment, regional, or national monitoring/ biological surveys.
Acknowledgments The authors are very grateful for funding from the UK-J programme managed by Defra (U.K.) and the Ministry of the Environment (Japan) together with the Japan Society for the Promotion of Science (JSPS). The authors are also grateful to Helen Davies, Monika Ju ¨ rgens, and Richard Williams of CEH for technical support and John Sumpter for his advice.
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