Annual and seasonal trends of wet deposition in Japan

ARTICLE IN PRESS AE International – Asia Atmospheric Environment 38 (2004) 3543–3556

Annual and seasonal trends of wet deposition in Japan Sinya Setoa,*, Hiroshi Harab, Manabu Satoc, Izumi Noguchid, Yutaka Tonookae a

Hiroshima Prefectural Institute for Public Health and Environmental Sciences, 1-6-29 Minami-machi, Minami-ku, Hiroshima 734-0007, Japan b Tokyo University of Agriculture and Technology, 3-5-8 Saiwaicho, Fuchu, Tokyo 183-8509, Japan c Hiroshima Prefectural College of Health Sciences, 1-1 Gakuen-machi, Mihara, Hiroshima 723-0053, Japan d Hokkaido Institute of Environmental Sciences, Kita-19 Nishi-12, Kita-ku, Sapporo, Hokkaido 060-0819, Japan e Faculty of Economics, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama 338-8570, Japan Received 5 November 2003; accepted 26 March 2004

Abstract In order to discuss temporal trends of the deposition of major ions, nonlinear least-squares regression analysis was applied to nation-wide wet deposition measurements in Japan. From the wet deposition database produced by Japan Environment Agency since 1983, the monitoring results at 17 sites over Japan from April 1989 through March 1998 were selected for the present study because of the data quality and current availability. These sites were further classified into four area groups in terms of the major sea of each area: the Pacific Ocean (PO), the Japan Sea (JS), the Seto Inland Sea (SI), and the East China Sea (EC) areas. The regression analysis elucidated temporal trends. The non-sea salt
1
+ sulfate (nss-SO2
4 ) deposition decreased on a national scale with a mean change rate of
3.5% a . The NO3 and NH4
1
1 deposition for the JS area showed increasing mean change rates of 3.4% a and 3.7% a , respectively; most of the sites, however, had no significant (p>0.05) annual trends in deposition of the two ions. Pronounced decreases in nonsea salt calcium (nss-Ca2+) deposition were recognized in northern Japan and some industrialized areas. For H+ deposition, negative change rates (
4 to
6% a
1) were estimated for the PO, EC, and SI areas. Annual trends of precipitation amount, however, made an only negligible contribution toward those of ionic deposition. Annual trends of the deposition were generally comparable with those of their domestic emissions and ionic concentrations, while the seasonality was attributed to the seasonal variation of precipitation amount. The decrease of the deposition sum of nss+ 2+ SO2
and NO
deposition sum will be responsible for the decreased 4 3 , and the increase of the NH4 and nss-Ca + deposition of H for some sites in the PO and SI areas. In consideration of microbial nitrification of ammonium in the soil, effective hydrogen ion deposition defined as the sum of H+ deposition and two times of NH+ 4 deposition for each site ranged from 50 to 119 meq m
2 a
1, which would be nearly equal to or less than their critical load estimates. r 2004 Elsevier Ltd. All rights reserved. Keywords: Temporal trend; Acidic deposition; Multiple regression; Sulfate; Nitrate; Japan

1. Introduction The deposition of acidifying substances is the major factor for evaluation of its potential effects on terrestrial and aquatic ecosystems. The reduction of acidifying *Corresponding author. Fax: +81-82-252-8642. E-mail address: [email protected] (S. Seto).

substances is needed for improvements of the adverse effects on the ecosystems. The assessment for the effects of their improvements requires temporal trend analyses of atmospheric deposition of acids and bases including sulfuric and nitric acids, and ammonia and calcium containing particles. Wet deposition of these substances has been extensively monitored whereas dry deposition is not measured on a routine basis like wet deposition

1352-2310/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2004.03.037

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because no practical monitoring method is developed yet. Long-term records of wet deposition monitoring were applied to temporal trend analyses for North America (Sisterson et al., 1990; Shannon, 1999; Lynch et al., 2000) and for Europe (Farmer et al., 1987; Clarke et al., 1990; Puxbaum et al., 1998). In Asia, Japanese Acid Deposition Survey (JADS) is likely to provide the longest record of wet deposition. The nation-wide monitoring has been conducted since September 1983 by Japan Environment Agency. Although several monitoring techniques have been modified in its history, the measurements are able to offer a reasonable database for trend analysis of wet deposition on a national scale. Long-range transport of acidic pollutants has been suggested to occur from Asian continent to Japan. For example, high atmospheric non-sea salt sulfate (nssSO2
4 ) concentrations observed at the Japan Sea site under the northeastern wind (Murano et al., 2000), and concentrations of anthropogenic sulfate and nitrate aerosol at the central North Pacific site almost doubled from 1981 to the mid-1990s, paralleling increased SO2 emissions from China (Prospero et al., 2003). These findings indicate that the precursor emissions in East Asia should also be taken into account for acidic deposition analysis in Japan. In the previous paper (Seto et al., 2002), temporal trend of ionic concentration was discussed by application of a regression model explicitly including precipitation amount to shed light on the wet deposition in terms of concentration. As its name implies, deposition should be emphasized in acid deposition study because deposition would be more significant with regard to potential impacts on ecosystems, and because trends of deposition could be different from those of the concentration. The present work therefore focuses on annual and seasonal trends of wet deposition in Japan. Data quality of the JADS database was evaluated to screen out data set of insufficient quality to discuss time trend for major
+ ions: nss-SO2
4 , nitrate (NO3 ), ammonium (NH4 ), non2+ + sea salt calcium (nss-Ca ) and hydrogen (H ) ions. To these data sets, a nonlinear least-squares regression model was applied to evaluate time trends of monthly deposition. Discussion was further extended to precipitation amount and their precursor emissions.

2. Experimental Monitoring techniques of JADS have been reported in the survey manuals (Japan Environment Agency, 1998; Second Interim Scientific Advisory Group Meeting of Acid Deposition Monitoring Network in East Asia, 2000). The database for the present series of analysis was the same measurements that were employed in the

previous paper (Seto et al., 2002). Although the sampling and chemical analysis have been already addressed in the paper, a brief description of the technique is provided in the following sections. As mentioned above, the monitoring techniques of the JADS operation have been changed in accordance with some technical developments on a trials-and-errors basis. The selected period is coincided with Phases II and III, April 1989 to March 1998 which have provided precipitation chemistry data of high quality. However, different kinds of sample collectors and sampling schedules were employed during the selected period, which will be detailed as below. 2.1. Monitoring methods From the data sets during Phases II and III, the measurements at the 17 sites among those of the 23 sites shown in Fig. 1 were selected on the basis of data completeness, quality of chemistry data and precipitation amounts (Seto et al., 2002). The sites have been administratively classified into two categories, urban and rural, according to a site and its surroundings on different spatial scales in consideration of local sources, potential obstacles and contaminations. For convenience, all sites were also grouped into four area groups in terms of the sea symbolizing the area of interest: the Pacific Ocean (PO), the Japan Sea (JS), the Seto Inland Sea (SI), and the East China Sea (EC) areas. Samples were collected with automated wet/dry samplers (Ogasawara US-420, US-750; DKK DRM200E, DRM-200K; Kimoto ARS-100, AR-102SNA). Precipitation amount was measured in the same site in parallel with the sample collection. If the precipitation gauge fails to record the precipitation amount, the precipitation amount was calculated based on the sample amount of the corresponding precipitation. It should be noted that two kinds of sampling duration were applied in this network because the measurements were designed to produce data not only for atmospheric processes but also for ecological impact surveys. For the 17 sites, samples were collected on a bimonthly and a week basis (Table 1). All data sets were compiled into monthly deposition. The pH and electric conductivity were determined with a pH electrode and an electric conductance meter,

+ respectively. Concentrations of SO2
4 , NO3 , Cl , NH4 + and K were determined by ion chromatography, and those of Ca2+ and Mg2+ by atomic absorption spectrometry. If not all of ionic concentrations were determined due to an insufficient precipitation amount, the sample was not used in the present statistical analysis. A fundamental data quality was assessed by the ratio R1 of anion sum to cation sum on an equivalent basis, and the ratio R2 of calculated to measured conductivity.

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Fig. 1. Locations of precipitation chemistry sites in JADS Phases II and III. The symbols (K) and (J) represent an urban site and a rural site, respectively. The code of a site being selected in terms of data completeness criteria is enclosed with a square. The four areas: the Japan Sea (JS), the Pacific Ocean (PO), the Seto Inland Sea (SI), and the East China Sea (EC) areas, are also indicated. The codes correspond to the name of the sites as follows: SPR: Sapporo, NPR: Nopporo, NGT: Niigata, NIS: Niitsu, MTE: Matsue, NND: Nonodake, SDI: Sendai, TKB: Tsukuba, KSM: Kashima, TKO: Tokyo, ICH: Ichihara, KWS: Kawasaki, INY: Inuyama, NGY: Nagoya, KYT: Kyoto-yahata, AMG: Amagasaki, OSK: Osaka, KRS: Kurashiki, KHJ: Kurahashi-jima, UBE: Ube, KTK: Kita-kyusyu, CKG: Chikugo-ogori, OMT: Omuta.

If either R1 or R2 was different from unity by more than 20%, then the sample was re-analyzed to resolve the discrepancy. All questionable results that can be assigned to reasonable causes were removed from the data set for further analysis. Non-sea salt fractions for 2+ SO2
were calculated by assuming sodium to 4 and Ca be a conservative tracer for sea salt, and by estimating the sea salt contribution from the known ion ratios in seawater (p. 558 of Riley and Skirrow, 1975; Seto et al., 2000). Data completeness criteria for site selection are as follows: (1) A valid monthly volume-weighted mean (VWM) concentration calculated from ionic concentrations and precipitation amounts for samples must have at least 85% of percent TP (the percent of the total precipitation amount measured during the summary period that is associated with valid samples) defined by Olsen et al. (1990). (2) A valid annual VWM concentration must satisfy the two conditions such that the number of valid monthly VWM concentration is at least 11 of 12 (92%); and percent PCL (the percent of the summary period for which information on whether or not precipitation occurred is available) defined by Olsen et al. (1990), is at least 85% for 12 valid monthly VWM concentrations, or 93% for 11 valid monthly VWM

concentrations. (3) A valid whole study-period VWM concentration must have at least eight of nine years (89%) for each valid annual VWM concentration. 2.2. Acid–base chemistry Acidity, [H+], where the brackets denote equivalent concentration, is often discussed in precipitation chemistry in the form of pH. The pH of aqueous-solution is determined by the nature and relative proportion of acids and bases in solution, that is, ½Hþ  ¼ ½acids
½bases:

ð1Þ

In the light of current understanding of atmospheric chemistry, the dominant acids are sulfuric and nitric acids. Major bases involved are derived from gaseous ammonia and particulate basic calcium salts where calcium carbonate would be the most prevailing calcium species of interest. Under this assumption, Eq. (1) will be transformed into the following equation: ½Hþ  ¼ ð½H2 SO4  þ ½HNO3 Þ
ð½NH3  þ ½CaCO3 Þ:

ð2Þ

These acids and bases will be dissociated into the component ions to be subjected to the acid–base neutralization to form water. Throughout the

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3546

Table 1 Observed mean annual ionic deposition for each site from April 1989 to March 1998 Site (code)

Areaa

Categoryb

Deposition (meq m
2 a
1)

Sampling period Phase II

Phase III

nss-SO2
4

NO
3

NH+ 4

nss-Ca2+

H+

Sapporo (SPR) Niigata (NGT) Niitsu (NIS) Matsue (MTE)

JS JS JS JS

U U R R

Half Half Half Half

a a a a

month month month month

A week Half a month A week Half a month

33.7 56.1 56.2 51.5

10.8 19.3 27.1 22.7

18.5 28.4 28.2 23.1

13.1 9.2 13.6 15.3

12.6 31.8 42.6 28.3

Sendai (SDI) Ichihara (ICH) Kawasaki (KWS) Inuyama (INY) Nagoya (NGY)

PO PO PO PO PO

U U U R U

Half Half Half Half Half

a a a a a

month month month month month

Half Half Half Half Half

a a a a a

month month month month month

39.1 38.4 53.2 38.3 41.4

20.4 18.0 21.7 25.6 24.9

29.1 21.2 35.5 20.3 23.6

16.8 23.4 23.2 8.9 15.3

8.0 11.3 25.4 35.5 12.5

Kyoto-yahata (KYT) Osaka (OSK) Kurashiki (KRS) Kurahashi-jima (KHJ) Ube (UBE)

SI SI SI SI SI

R U U R U

Half Half Half Half Half

a a a a a

month month month month month

Half Half Half Half Half

a a a a a

month month month month month

33.9 38.3 32.6 45.4 76.0

19.1 16.2 15.4 18.9 24.7

18.8 23.4 13.2 20.5 46.0

11.8 9.3 7.4 5.9 46.0

23.4 28.9 26.2 38.1 2.5

Kita-kyusyu (KTK) Chikugo-ogori (CKG) Omuta (OMT)

EC EC EC

U R U

Half a month Half a month Half a month

Half a month Half a month Half a month

79.9 54.6 69.8

39.6 17.6 17.5

35.5 44.3 43.7

43.9 10.2 23.6

15.5 30.8 10.4

a b

JS: the Japan Sea area, PO: the Pacific Ocean area, SI: the Seto Inland Sea area, EC: the East China Sea area. U: Urban site, R: Rural site.

interaction, the initial concentration of acids and the concentrations of added bases will be conserved as the corresponding ionic concentrations. Eq. (2) will be then deduced numerically to Eq. (3) on the basis of the above chemical discussion þ
2þ ½Hþ  ¼ ð½nss-SO2
4  þ ½NO3 Þ
ð½NH4  þ ½nss-Ca Þ: ð3Þ

2.3. Trend model With regard to month-to-month variation of precipitation amount, both annual and semiannual patterns were generally observed in Japan. According to the precipitation measurements in Japan during the period from 1971 to 2000 (National Astronomical Observatory, 2001), one station in the monitoring network, Sendai, showed a sharp maximum in September whereas another station, Matsue, recorded the maximum and the second maximum in different seasons in the years. Hence, a temporal variation in ionic deposition should include a seasonal trend composed of both annual and semiannual cycles in addition to an annual trend representing long-term variation. The temporal variation in monthly ionic deposition was evaluated using a deposition-against-time regression

model as follows: i i i logðDi Þ ¼ a þ b þ g sinð2p þ fÞ þ l sin ð4p þ dÞ J J J ð4Þ þ ei ; i ¼ 1; 2; :::; J  N: Here Di is the deposition for the ith month and i denotes the lapse of time in months since 1 April 1989—a monthly deposition is located at its midpoint; J is the number of months in a year (=12), N the number of the years of interest (=9). Model parameter a represents the intercept, and b the slope of an annual trend; g and f are the amplitude and the phase-angle of an annual cycle, respectively; l and d are the amplitude and the phase-angle of a semiannual cycle, respectively. We assume that the error term ei obeys the normal distribution with mean zero and standard deviation se : The residuals were more fitted to normal distribution for logarithmically transformed deposition data than for the original deposition data. The measurements of precipitation amount showed fairly similar results. Hence logarithmically transformed deposition is used for the trend analysis. Estimates of the six parameters in Eq. (4) were obtained using SPSS statistical package (Norusˇ is and SPSS Inc., 1999) for a nonlinear least-squares regression model. At first, all samples were fitted to Eq. (4). When a sample has an absolute value of residual jlogðDobserved Þ
logðDestimated Þj being greater than 3se ;

ARTICLE IN PRESS S. Seto et al. / Atmospheric Environment 38 (2004) 3543–3556

CR ¼

Dal ¼

1 Da9
Da1   100; N
1 1 P9 Da l 9 l¼1 12l X

ð% a
1 Þ; ð5Þ

logðDi Þ

10

;

l ¼ 1; 2; y; 9:

i¼12ðl
1Þþ1

Here Dal denotes the annual deposition estimate for the lth year. It should be noted that CR is calculated from deposition estimate by the model and not from observed deposition. Hence the deposition estimate has been derived from the whole data set of the monthly deposition throughout the study-period. Consequently, CR represents an annual trend relative to a mean annual deposition for the period. Temporal variation in monthly precipitation amount was also evaluated using a precipitation amountagainst-time regression model as follows: i i i logðPi Þ ¼ a þ b þ c sinð2p þ dÞ þ e sinð4p þ f Þ J J J þ gi ; i ¼ 1; 2; y; J  N:

ð6Þ

Here Pi is the precipitation amount for the ith month; the error term gi obeys the normal distribution with mean zero and standard deviation sg ; and the other model parameters in Eq. (6) are the same as the corresponding terms in Eq. (4). These parameters were estimated from precipitation measurements except the outliers. The significances of parameters were also evaluated by the same method as those of Eq. (4), and the normality assumption of gi was also checked by the same methods as testing ei : The above outlier removal was applied also to precipitation amount. For the 17 sites, the outliers have been eliminated from the monthly deposition data, where two monthly deposition data were screened out from a single-site database amounting some 2% of all the monthly deposition data. Using the valid deposition data, we discuss the characteristics of annual and seasonal trends of ionic deposition in Japan.

3. Results 3.1. Mean annual deposition of major ions In order to verify the validity of the above acid–base chemistry, the deposition sum of the three ions, H+, 2+ NH+ , was plotted against the sum of the 4 and nss-Ca two counterpart ions, nss-SO2
and NO
4 3 , on an equivalent basis in Fig. 2. The deposition of the three ions and that of the two generally agreed with each other except for a few sites. On the basis of the above discussion, the H+ deposition would be able to be quantitatively discussed in terms of those of the four 2+
+ ions: nss-SO2
. 4 , NO3 , NH4 and nss-Ca Table 1 shows observed mean annual ionic deposition for the rural and urban sites through the study-period.
2
1 a , For nss-SO2
4 , elevated deposition, 50–80 meq m was discernible for the EC area, most of the JS area, and two urban sites (UBE and KWS). For NO
3 , the highest deposition, 40 meq m
2 a
1, was observed at the KTK
2
1 site. High NH+ a was 4 deposition of 40–50 meq m recorded at the UBE, CKG and OMT sites. For nssCa2+, the two urban sites (UBE and KTK) had particularly pronounced deposition of about 45 meq m
2 a
1. With respect to H+ deposition, the highest deposition, 43 meq m
2 a
1, was recorded at the NIS site; on the other hand, the lowest deposition, 3 meq m
2 a
1, was found at the UBE site. In spite of the

160

(NH4+ + nss-Ca2+ + H+) deposition / meq m-2 a-1

the sample was eliminated from the data set. And the next stage, the remaining samples were fitted to Eq. (4). This outlier removal was applied to reduce the influence of potential anomalies in the present deposition data to the estimates of parameters. The significance of b# was evaluated by testing the null hypothesis H0: b ¼ 0; against the alternative hypothesis H1: ba0; the significance level used in this analysis is 5%. The significance of g# and l# were also evaluated by the same method. The normality assumption of ei was checked by plotting the frequency distribution of residuals, and also tested by Kolmogorov–Smirnov statistics. An annual change rate, CR of ionic deposition is calculated from

3547

140 1:1 120

100

80

60

40

20

0 0

20

40 2-

60

80 3

100

120

140 -2

160 -1

(nss-SO4 + NO ) deposition / meq m a


Fig. 2. Relations between the deposition of (nss-SO2
4 +NO3 ) 2+ + + and that of (NH4 +nss-Ca +H ) for each site from April 1989 to March 1998.

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log (Deposition/meq m-2 month-1)

2.0 1.5 1.0 0.5 0.0 -0.5 -1.0

0

1

2

3 4 5 6 7 Years since 1 April 1989

8

9

10

Fig. 4. Observed and predicted monthly deposition of nss-SO2
4 at the SDI site from April 1989 to March 1998. Open circles show observed values. Solid and broken lines represent estimates and the annual trend predicted by Eq. (4), respectively.

Fig. 3. Boxplots showing annual ionic deposition for the selected 17 sites in Japan and that for the 21 northeastern US sites located in NY, PA, and OH states in 2000. The deposition 2+ of nss-SO2
in Japan was compared with that of 4 and nss-Ca and Ca2+ in northeastern US (J): outlier, and (): SO2
4 extreme.

above characteristics of deposition for some areas and sites, we are unable to find obvious spatial patterns or urban-rural differences in deposition for the five ions. Ionic deposition records of the year 2000 were compared between Japan and northeastern US, the largest SO2 and NOx emissions region in the United States (Fig. 3). For northeastern US, the deposition of 2+ sulfate (SO2
) obtained by the 4 ) and calcium (Ca National Atmospheric Deposition Program database was used (National Atmospheric Deposition Program,
2001). The nss-SO2
4 and NO3 deposition in Japan was comparable to that in northeastern US. For NH+ 4 and nss-Ca2+, the deposition in Japan was higher than that in northeastern US. The H+ deposition in Japan, on the other hand, was half of that in northeastern US, which suggests that relatively low H+ deposition in Japan would be responsible for the high deposition of bases. 3.2. Annual and seasonal trends in deposition of major ions An example of the modeled results is presented in Fig. 4, where the observed and predicted monthly deposition of nss-SO2
4 at the SDI site was compared. It is evident that the deposition exhibited a discernible decreasing annual trend. Though a couple of values in the low deposition region would have been underestimated, the seasonal variation was characterized by a predominant annual cycle with a maximum in summer

Fig. 5. Frequency distribution of the residuals for monthly deposition of nss-SO2
at the SDI site from April 1989 to 4 March 1998. A solid curve represents a fitted normal distribution.

and a semiannual cycle was indiscernible. The residuals for nss-SO2
4 deposition at the SDI site are displayed as the frequency distribution in Fig. 5. No large departure from normality was discernible, which indicates that the residuals will fit a normal distribution. For all sites in this study, the estimates of parameters in Eq. (4) and annual change rates CRs of ionic deposition defined by Eq. (5) are shown in Tables 2 and 3, respectively, which enable us to evaluate area patterns of the annual and seasonal trends in the ionic deposition. In the present analysis, the normality of the residuals was not rejected at any sites for the five ions when Kolmogorov–Smirnov test was applied. For

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Table 2 Estimates of the regression parameters in Eq. (4) based on monthly ionic deposition for each site from April 1989 to March 1998 Area

Site

Category

na

Regression parameters a#

b# b

g# b

# f

l# b

d#

Maxc

s# logðDÞ

r2 d

Normalitye

JS

SPR NGT NIS MTE

U U R R

102 105 102 105

0.499 0.529 0.569 0.700


0.016 0.009 0.014
0.033

0.090 0.117 0.183 0.212

3.70 3.79 2.62 2.80

0.053 0.068 0.107 0.057

1.29 2.67 2.53 2.72

WI AU WI WI

0.189 0.317 0.206 0.270

0.160 0.091 0.370 0.283

0.849 0.853 0.808 0.858

PO

SDI ICH KWS INY NGY

U U U R U

99 97 96 104 99

0.533 0.527 0.773 0.494 0.592


0.028
0.009
0.045
0.022
0.027

0.335 0.062 0.300 0.299 0.226

6.24 6.08 6.24 0.03 6.12

0.069 0.096 0.090 0.021 0.062

1.93 1.15 1.03 0.90 1.14

SU SP SP SU SU

0.264 0.214 0.236 0.233 0.262

0.482 0.130 0.532 0.476 0.345

0.876 0.892 0.205 0.890 0.207

SI

KYT OSK KRS KHJ UBE

R U U R U

101 105 103 98 105

0.462 0.444 0.391 0.662 0.839


0.023
0.005
0.018
0.036
0.025

0.251 0.230 0.311 0.208 0.203

0.27 6.22 0.13 0.54 0.52

0.013 0.024 0.063 0.060 0.100

1.27 3.03 3.09 0.31 2.94

SU SU SU SP SU

0.278 0.237 0.272 0.271 0.225

0.332 0.334 0.427 0.329 0.376

0.444 0.549 0.888 0.789 0.495

EC

KTK CKG OMT

U R U

103 106 96

0.848 0.544 0.847


0.015 0.011
0.027

0.109 0.210 0.196

0.36 0.79 0.58

0.016 0.065 0.039

1.73 2.95 2.35

SU SP SU

0.209 0.202 0.236

0.144 0.379 0.316

0.604 0.574 0.594

SPR NGT NIS MTE

U U R R

102 106 102 103


0.076 0.039 0.160 0.197

0.002 0.021 0.037 0.005

0.067 0.059 0.094 0.184

4.12 4.17 2.28 2.76

0.038 0.088 0.075 0.082

1.34 3.00 2.59 2.89

AU AU WI WI

0.196 0.263 0.191 0.229

0.075 0.110 0.327 0.285

0.720 0.924 0.666 0.947

PO

SDI ICH KWS INY NGY

U U U R U

99 97 95 106 100

0.170 0.165 0.247 0.213 0.271


0.014
0.008
0.010 0.002
0.008

0.406 0.123 0.255 0.277 0.271

6.14 6.24 0.21 6.20 6.17

0.068 0.074 0.079 0.058 0.042

1.66 0.94 1.57 1.17 1.43

SU SP SP SU SU

0.253 0.262 0.278 0.266 0.275

0.571 0.130 0.308 0.364 0.344

0.606 0.594 0.285 0.532 0.300

SI

KYT OSK KRS KHJ UBE

R U U R U

101 105 102 98 105

0.088
0.073 0.039 0.094 0.291

0.011 0.028
0.007 0.013
0.008

0.237 0.242 0.295 0.148 0.201

0.18 6.13 0.18 0.72 0.33

0.015 0.027 0.128 0.100 0.053

0.63 0.45 0.47 0.49 3.13

SU SU SP SP SU

0.244 0.238 0.245 0.253 0.209

0.326 0.367 0.468 0.216 0.341

0.782 0.294 0.853 0.730 0.933

EC

KTK CKG OMT

U R U

104 106 96

0.456
0.069 0.174

0.007 0.038
0.010

0.099 0.189 0.246

0.56 0.82 0.21

0.029 0.056 0.017

2.37 0.55 2.04

SU SU SU

0.192 0.194 0.224

0.131 0.427 0.382

0.947 0.995 0.979

SPR NGT NIS MTE

U U R R

103 106 102 103

0.178 0.132 0.213
0.012


0.004 0.033 0.026 0.024

0.086 0.064 0.142 0.359

4.10 4.80 2.06 2.28

0.048 0.073 0.094 0.110

2.58 2.88 2.61 0.47

AU AU WI WI

0.194 0.296 0.223 0.435

0.117 0.119 0.289 0.284

0.175 0.948 0.969 0.410

PO

SDI ICH KWS INY NGY

U U U R U

100 97 96 106 101

0.285 0.191 0.468
0.084 0.118

0.000 0.002
0.017 0.036 0.012

0.367 0.062 0.319 0.376 0.225

6.15 0.32 0.01 6.21 6.27

0.039 0.145 0.096 0.047 0.030

1.44 0.80 1.22 2.59 0.17

SU SP SP SU SU

0.246 0.265 0.250 0.272 0.331

0.521 0.145 0.470 0.511 0.195

0.331 0.282 0.174 0.844 0.916

SI

KYT OSK

R U

100 105

0.044 0.156

0.010 0.012

0.216 0.270

0.25 6.19

0.034 0.035

2.67 2.33

SU SU

0.272 0.221

0.251 0.436

0.375 0.832

log (NO
3) JS

log (NH+ 4 ) JS

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3550 Table 2 (continued) Area

Site

Category

na

Regression parameters

Maxc

s# logðDÞ

r2 d

Normalitye

a#

b# b

g# b

# f

l# b

d#

0.25 0.82 0.36

0.052 0.089 0.125

2.97 0.16 2.92

SU SP SU

0.280 0.271 0.230

0.486 0.294 0.393

0.326 0.925 0.863

KRS KHJ UBE

U R U

103 97 104


0.006 0.267 0.486


0.022
0.023 0.004

0.364 0.203 0.231

KTK CKG OMT

U R U

103 107 97

0.405 0.386 0.567


0.001 0.022
0.013

0.149 0.247 0.233

0.11 0.78 0.76

0.102 0.084 0.055

2.72 2.67 2.57

SU SP SU

0.244 0.208 0.262

0.217 0.456 0.308

0.735 0.948 0.819

SPR NGT NIS MTE

U U R R

103 104 100 102

0.262
0.336
0.214 0.121


0.067 0.023 0.033
0.035

0.149 0.188 0.294 0.382

2.14 2.46 2.28 2.58

0.065 0.221 0.234 0.020

1.06 0.37 0.33 1.59

SP SP SP WI

0.249 0.282 0.273 0.324

0.401 0.372 0.513 0.415

0.780 0.799 0.761 0.692

PO

SDI ICH KWS INY NGY

U U U R U

99 97 94 105 99

0.149 0.093 0.321
0.226 0.126


0.020 0.032
0.032
0.010
0.018

0.207 0.086 0.339 0.262 0.211

0.50 1.59 0.00 0.53 0.33

0.105 0.101 0.085 0.172 0.123

1.39 0.96 1.40 0.36 1.33

SP SP SU SP SP

0.225 0.271 0.316 0.314 0.243

0.374 0.172 0.404 0.346 0.364

0.746 0.733 0.861 0.708 0.935

SI

KYT OSK KRS KHJ UBE

R U U R U

100 105 102 84 105


0.254
0.216
0.339
0.503 0.625

0.033 0.008 0.001 0.013
0.027

0.207 0.218 0.266 0.338 0.104

0.80 0.52 0.31 1.19 1.14

0.074 0.078 0.023 0.140 0.068

0.70 0.97 1.43 1.73 0.64

SP SP SU SP SP

0.313 0.214 0.314 0.388 0.288

0.239 0.373 0.260 0.324 0.136

0.635 0.445 0.753 0.660 0.127

EC

KTK CKG OMT

U R U

103 106 95

0.506
0.214 0.488


0.001 0.009
0.052

0.116 0.257 0.194

0.44 1.43 1.68

0.023 0.034 0.061

2.00 1.48 0.19

SP SP SP

0.183 0.263 0.222

0.171 0.332 0.441

0.565 0.832 0.356

SPR NGT NIS MTE

U U R R

102 103 102 103


0.904 0.281 0.479 0.273

0.139 0.008 0.008
0.007

0.374 0.179 0.159 0.230

3.92 4.09 3.26 3.44

0.207 0.110 0.099 0.081

0.18 0.22 0.02 2.71

WI WI WI WI

0.374 0.324 0.212 0.388

0.626 0.178 0.290 0.165

0.705 0.843 0.084 0.225

PO

SDI ICH KWS INY NGY

U U U R U

101 95 97 106 100


0.359 0.134 0.486 0.487
0.599


0.041
0.093
0.069
0.039 0.066

0.659 0.465 0.189 0.217 0.454

5.92 6.06 6.05 6.15 5.89

0.037 0.075 0.139 0.020 0.053

2.81 1.45 1.49 0.75 3.02

SU SU AU SU SU

0.495 0.470 0.365 0.377 0.501

0.484 0.444 0.312 0.207 0.337

0.544 0.482 0.134 0.088 0.629

SI

KYT OSK KRS KHJ UBE

R U U R U

99 106 102 97 102

0.351 0.419 0.309 0.471
1.104


0.042
0.040
0.030
0.005 0.023

0.201 0.228 0.223 0.158 0.460

6.26 6.03 6.20 0.56 0.06

0.069 0.008 0.105 0.095 0.123

2.54 1.40 0.08 0.59 2.21

SU SU SU SP SU

0.343 0.323 0.389 0.289 0.476

0.240 0.278 0.209 0.180 0.337

0.367 0.154 0.398 0.608 0.753

EC

KTK CKG OMT

U R U

102 107 97


0.073 0.378
0.156


0.006
0.017
0.071

0.192 0.125 0.600

1.43 0.45 6.25

0.004 0.082 0.109

2.89 0.11 3.01

SP SP SU

0.448 0.312 0.510

0.085 0.128 0.464

0.998 0.740 0.568

EC

log (nss-Ca2+) JS

log (H+) JS

a

The number of months with valid data. Significant at the 5%-level. c The season of the predicted maximum deposition occurred (SP: spring, SU: summer, AU: autumn, WI: winter). d The fraction of total variance explained by the regression model. e The probability value of the null hypothesis that the residuals obey a normal distribution estimated by Kolmogorov–Smirnov test statistics. b

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3551

Table 3 Annual change rates of ionic deposition for each site from April 1989 to March 1998 Area

Site

Category

Annual change ratea (% a
1) nss-SO2
4

NO
3

NH+ 4

nss-Ca2+

H+

JS

SPR NGT NIS MTE Area meanb

U U R R


3.47 1.68 3.05
6.64
1.34

0.43 4.03 7.87 1.13 3.37


0.77 6.18 5.37 4.14 3.73


13.62 4.32 6.46
6.90
2.44

25.41 1.50 1.75
1.23 6.86

PO

SDI ICH KWS INY NGY Area meanb

U U U R U


5.57
1.91
9.20
4.49
5.47
5.33


2.81
1.47
2.09 0.30
1.51
1.52

0.05 0.41
3.36 6.95 2.13 1.24


3.80 6.03
6.10
1.99
3.66
1.90


6.67
15.98
11.77
6.77 9.23
6.39

SI

KYT OSK KRS KHJ UBE Area meanb

R U U R U


4.45
1.01
3.49
6.97
5.22
4.23

2.14 5.78
1.38 2.61
1.75 1.48

1.81 2.40
4.25
4.53 0.74
0.77

6.20 1.59 0.16 2.54
5.24 1.05


7.43
7.18
4.99
1.01 3.14
3.49

EC

KTK CKG OMT Area meanb

U R U


3.08 2.38
5.50
2.07

1.43 8.13
2.09 2.49


0.22 4.51
2.60 0.56


0.16 1.84
11.05
3.12


0.92
3.23
9.92
4.69

(All)

Rural mean Urban mean (Rural+Urban) mean


2.85
3.84
3.49

3.70
0.13 1.22

3.04 0.06 1.11

1.36
2.87
1.38


2.98
1.65
2.12

a b

See Eq. (5) in the text. An arithmetic mean of deposition for rural and urban sites in an area.

# nss-SO2
4 , the bs significantly decreased at 10 sites out of 17 (Table 2); nss-SO2
4 deposition has been decreasing throughout Japan, in fact, area mean CRs (arithmetic means of deposition change rate at the sites regardless of the site attribute whether rural or urban) ranged from
1.3% a
1 to
5.3% a
1, with a mean of
3.5% a
1 for all sites (Table 3). The other ions, however, are not the # for NO
case. Though the bs 3 significantly increased at the four sites (NGT, NIS, OSK and CKG), no significant trends were recognized for the other sites;
1 area mean CRs of NO
in the JS 3 increased by 3.4% a area, and by 2.5% a
1 in the EC area. For NH+ 4 , # increased various trends were confirmed. The bs significantly at the four sites (NGT, NIS, INY and CKG) whereas decreased at the KRS and KHJ sites. No significant trends were observed for the other sites; as for area mean, the highest CR of 3.7% a
1 was recorded in # significantly increased the JS area. For nss-Ca2+, the bs at the four sites (NGT, NIS, ICH and KYT), and decreased at the six sites (SPR, MTE, SDI, KWS, UBE and OMT); the CRs for this ion seem to differ from site

to site. A pronounced decreasing CR of 14% a
1 for the SPR site would be due mainly to the reduction of road dust generated by vehicle-studded tires (Noguchi et al., # significantly 1995; Seto et al., 2002). For H+, the bs increased only at the SPR and NGY sites. In particular, the SPR site had a notable CR of 25.4% a
1, which would be due to the decreased composition of basic substances including road dust as discussed above; in contrast, all the PO area sites except the NGY site had # as well as the CRs ranging significantly decreasing bs
1 from
6 to
16% a . Area mean CRs of H+ also decreased by 3–6% a
1 for the PO, EC and SI areas. Rural and urban mean CRs seem to vary from ion to ion. Consequently, nss-SO2
4 deposition decreased on a + national scale, whereas NO
3 and NH4 deposition had indiscernible trend for most of the sites. The annual trend in nss-Ca2+ varied with sites. The H+ trend, on the other hand, is likely to decrease for the three areas, PO, EC and SI. Amplitudes and phase-angles in the annual and semiannual cycles were discussed in terms of their

ARTICLE IN PRESS S. Seto et al. / Atmospheric Environment 38 (2004) 3543–3556

3552

# l# and d: # The g# s of the five ions parameter estimates, g# ; f; were significant for most sites, whereas the correspond# were significant for 5–8 sites (Table 2). In the JS ing ls area, the predicted seasonal maximum deposition of nss
+ + SO2
took place in the period of 4 , NO3 , NH4 and H autumn to winter, while the maximum deposition in the other areas was predicted to occur mostly in summer. In contrast, nss-Ca2+ had its maximum in spring throughout the country, which strongly suggests that long-range transported Asian dust enriched in calcium salts is associated with wet deposition (Ichikuni, 1978; Dokiya et al., 1995). In the JS area, the season of predicted maximum of nss-SO2
4 was consistent with the observational result that reaches its maximum in the cold season (October–March) (Fujita et al., 2000a); and the deposi+ tion of NO
3 and NH4 was also the case (Fujita et al., 2000b).

estimated annual and seasonal trends of precipitation amount in terms of the parameters in Eq. (6) (Table 4). The normality of the residuals was not rejected at any sites. The slopes of annual trend in precipitation amount ˆ showed no significance for 14 sites. For the sites bs 2+ # of nss-SO2
exhibiting significant bs and H+ 4 , nss-Ca ˆ deposition, the corresponding bs were found not to be significant for 9 sites out of 10, 8 sites out of 10, and 8 sites out of 9, respectively. Annual trends of precipitation amount are therefore concluded to have negligible contributions to those of ionic deposition. In the JS area, predicted precipitation amounts reach their maximum in autumn and winter. In the other areas, on the other hand, the maximum is calculated to occur mostly in summer including the rainy season, Baiu, (Table 4). This seasonality is similar to the deposition +
+ trends of nss-SO2
(Table 2). 4 , NO3 , NH4 and H Accordingly, the seasonal pattern of precipitation amount would be concluded to be responsible for that +
+ of ionic deposition of nss-SO2
4 , NO3 , NH4 and H , except nss-Ca2+ to which Asian dust will greatly contribute in spring.

3.3. Annual and seasonal trends in precipitation amount In order to explore the relationship between two trends, deposition and precipitation amounts, we

Table 4 Estimates of the regression parameters in Eq. (6) based on monthly precipitation amount for each site from April 1989 to March 1998 Area

log (precipitation amount) JS

Site

Category

na

Regression parameters aˆ

bˆ b

cˆ b

dˆ

eˆ b

fˆ

Maxc

s# logðPÞ

r2 d

Normalitye

SPR NGT NIS MTE

U U R R

103 105 102 105

1.76 1.89 2.02 2.09

0.006 0.010 0.023
0.011

0.232 0.173 0.094 0.084

4.33 4.57 3.92 5.14

0.115 0.066 0.106 0.085

2.86 0.19 0.45 2.56

AU AU WI SU

0.204 0.288 0.186 0.261

0.450 0.174 0.292 0.106

0.970 0.315 0.693 0.791

PO

SDI ICH KWS INY NGY

U U U R U

101 97 96 105 100

1.92 2.06 2.18 2.02 2.01


0.021
0.018
0.037
0.004
0.013

0.379 0.177 0.213 0.194 0.267

5.88 5.53 5.68 6.15 5.94

0.061 0.088 0.136 0.090 0.056

1.55 1.07 1.19 2.99 0.75

SU AU AU SU SU

0.344 0.253 0.257 0.286 0.325

0.389 0.250 0.383 0.227 0.279

0.421 0.756 0.923 0.647 0.096

SI

KYT OSK KRS KHJ UBE

R U U R U

101 106 103 98 105

1.93 1.90 1.89 1.92 1.97


0.014
0.002
0.022 0.005
0.004

0.243 0.226 0.289 0.291 0.368

0.12 6.05 6.15 0.13 0.16

0.043 0.047 0.065 0.028 0.044

1.24 0.72 0.12 1.57 1.94

SU SU SU SU SU

0.291 0.306 0.310 0.283 0.302

0.289 0.223 0.343 0.345 0.433

0.939 0.257 0.862 0.740 0.933

EC

KTK CKG OMT

U R U

104 106 97

1.99 1.86 1.95

0.254 0.328 0.400

0.05 0.28 0.10

0.076 0.049 0.082

2.31 0.17 2.42

SU SU SU

0.287 0.293 0.342

0.295 0.402 0.400

0.971 0.938 0.476

a

0.001 0.028 0.006

The number of months with valid data. Significant at the 5%-level. c The season of the predicted maximum precipitation amount occurred (SU: summer, AU: autumn, WI: winter). d The fraction of total variance explained by the regression model. e The probability value of the null hypothesis that the residuals obey a normal distribution estimated by Kolmogorov–Smirnov test statistics. b

ARTICLE IN PRESS S. Seto et al. / Atmospheric Environment 38 (2004) 3543–3556

3.4. Relation between annual trends in deposition and in concentration

3553 10 Group 1

8

4. Discussion Annual change rates of the equivalent sum of nss
+ SO2
4 and NO3 deposition (AD), and those of NH4 and 2+ nss-Ca deposition (BD) were compared for each site by Eqs. (4) and (5) as depicted in Fig. 6. Cluster analysis by group average method using squared Euclidean distance was applied to this result to divide the sites into the three groups in terms of CRs for AD and BD. Degrees of CR for H+ deposition was also considered. In Group 1, both AD and BD increased with a small changes of H+ deposition (|CR|p5% a
1). Group 2 is characterized by the decrease in AD and increase in BD, and a large decrease in H+ deposition (CRp
5% a
1). For the ICH, KYT and INY sites in the PO and SI areas, decreased deposition of H+ took place with decreased deposition of acids and increased deposition of bases. Group 3 has generally decreasing rates of both AD and BD. The sites in this group can hardly characterized in terms of the change rate, because this group includes sites in all of the three categories according to the range of H+ change rates. It can be noted that all the sites (KRS, KHJ and UBE) in the SI area had small change rates of H+ deposition, (|CR|p5% a
1), and that the CRs of H+ deposition were fairly large: 25% a
1 for the SPR and 9% a
1 for the NGY sites. The marked increase in H+ for the SPR

NIS NGT Group 2

6 CKG

ICH

Change rate in base / % a-1

Seto et al. (2002) have summarized the principal characteristics of temporal trends of concentrations of
+ 2+ nss-SO2
from the same data 4 , NO3 , NH4 and nss-Ca set as the present paper. We are able to compare the trends in the deposition with those of concentrations. The nss-SO2
concentration exhibited on a national 4 scale decreasing trends with a mean change rate of
3.0% a
1, comparable to that of deposition of
3.5% a
1. For the change rates of NO
3 concentration, the rural sites showed an increasing mean change rate of 3.0% a
1, while indiscernible for the urban sites. These urban and rural change rates would be applicable to concentration, the those of deposition. For NH+ 4 maximum area mean change rate of 3.8% a
1, a little higher than that of deposition, 1.2% a
1, was recorded in the PO area. For nss-Ca2+ concentration, the two urban sites, SPR and OMT, exhibited pronounced decreasing change rates of about 10% a
1, closely parallel to those of deposition. The above comparison of trends in deposition with those of concentration would lead to the conclusion that the annual trends in
+ 2+ wet deposition of nss-SO2
4 , NO3 , NH4 and nss-Ca were generally consistent with those of concentrations in Japan.

KYT

4

INY

OSK

2

Group 3 NGY

-10

-8

-6 MTE-4 KTK -2 SDI

UBE

KRS

0

0

2

4

-4 OMT

SPR

8

10

-2

KHJ

KWS

6

-6

+

-1

Change rate of H > 5 % a + -1 Change rate of H < -5 % a Change rate of H+ ≤ 5 % a-1

-8 -10 Change rate in acid / % a-1

Fig. 6. Relations between the change rate of the deposition of 2+
+ ) for each site (nss-SO2
4 +NO3 ) and that of (NH4 +nss-Ca
from April 1989 to March 1998. Acid: nss-SO2
4 +NO3 , base: 2+ NH+ +nss-Ca . 4

site would be due to a larger decrease of BD than that of AD. For the NGY site, an increase in H+ in spite of a decrease (
6% a
1) in AD can be due to possible decreasing deposition of bases other than NH3 and CaCO3. Accordingly, the decrease of AD and the increase of BD will be responsible for the decreased deposition of H+ for some sites in the PO and SI areas. With respect to soil acidification, a bacteriological process should be included in addition to hydrogen ion deposition. Nitrification eventually converts one ammonium ion into two hydrogen ions and one nitrate ion: +
NH+ (Erisman, 1993). In 4 +2O2-NO3 +H2O+2H the present work, the wet deposition of effective hydrogen ions H+ eff defined as the equivalent sum of + H+ and doubled NH+ and 2NH+ 4 deposition, H 4 , would be an appropriate measure of the potential effects on soil acidification. Table 5 gives annual deposition and change rate of H+ eff estimated from the same method as those of AD and BD. The annual deposition of H+ eff for each site ranged from 50 to 119 meq m
2 a
1, and its area mean varied from approximately 70 meq m
2 a
1 (the PO and SI areas) to about 100 meq m
2 a
1 (the EC area). It is meaningful to compare these H+ eff deposition with the critical load estimates based on the BC/Al criterion, (the sum of Ca2+, Mg2+, Na+ and K+ concentrations)/ (aluminum concentration)>1.0 mol mol
1, using the steady-state mass balance model by Shindo and Fumoto

ARTICLE IN PRESS S. Seto et al. / Atmospheric Environment 38 (2004) 3543–3556

3554

Table 5 Annual deposition and change rate of effective hydrogen ions for each site from April 1989 to March 1998

2.0

Area Site

1.6

PO

SI

EC

SPR NGT NIS MTE Area meanb

U U R R

49.5 88.6 99.0 74.5 77.9

4.47 4.51 4.40 0.48 3.47

SDI ICH KWS INY NGY Area meanb

U U U R U

66.3 53.7 96.3 76.2 59.7 70.4


0.73
3.96
6.85
0.26 5.07
1.34

KYT OSK KRS KHJ UBE Area meanb

R U U R U

61.0 75.7 52.6 79.2 94.6 72.6


2.33
1.62
5.13
3.51 0.89
2.34

KTK CKG OMT Area meanb

U R U

86.4 119.4 97.8 101.2


0.43 2.47
4.31
0.76

84.9 74.7 78.3

0.21
0.73
0.40

(All) Rural mean Urban mean (Rural+Urban) mean a

See Eq. (5) in the text. An arithmetic mean of deposition for rural and urban sites in an area. b

(1998). For all areas over Japan in their work, the critical loads were estimated to range from 500 to 2000 eq ha
1 a
1 (50–200 meq m
2 a
1). Hence, the H+ eff deposition would be nearly equal to or less than their critical load estimates for the sites. The annual change
1 rate of H+ eff at each site ranged from
6.9 to 5.1% a .
1 The area mean change rate increased by some 3% a in the JS area, and decreased by some 2% a
1 in the SI area, whereas those for the other areas are likely to differ from site to site. A mean increase in anthropogenic SO2 emissions of 2.2% a
1 over the whole Asia has been estimated during 1990–1997 (Streets et al., 2001). As discussed above, the mean nss-SO2
wet deposition throughout Japan, 4 however, decreased of 3.5% a
1 during 1989–1998. This change rate is comparable to a negative rate of domestic anthropogenic SO2 emissions, a slope/

Annual emissions (Tg a-1)

JS

Category Annual Annual change deposition ratea (% a
1) (meq m
2 a
1)

NOx

1.8

SO2

1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 1989

1991

1993 Year

1995

1997

Fig. 7. Emissions of SO2 and NOx from all anthropogenic sources in Japan from 1989 to 1998. Linear emission-time regression lines are also shown. Solid line: SO2, broken line: NOx.

(an arithmetic mean of annual SO2 emissionsÞ 100 ¼
0:0152 Tg a
1 =0:858 Tg a
1 100 ¼
1:8% a
1 ; from 1989 to 1998 (Fig. 7). In terms of only change rate, the decrease in domestic anthropogenic SO2 emissions would be responsible for the decrease in nss-SO2
4 wet deposition in the country. Volcanic SO2 emissions should also be taken into account in the country. However, more detailed discussion on the temporal nssSO2
4 deposition trend is beyond the scope of this paper, because no high quality continuous measurements of volcanic sulfur emissions are available for the period of interest. A mean increase in NOx emissions of 6.2% a
1 over the whole Asia has been estimated during 1990– 1997 (Streets et al., 2001). This is much larger than an increase in domestic NOx emissions, a slope/(an arithmetic mean of annual NOx emissions)  100=0.0217 Tg a
1/1.70 Tg a
1  100=1.3% a
1, from 1989 to 1998 (Fig. 7). The increase rate could be qualitatively interpreted to be consistent with the mean
1 increase rate of NO
3 wet deposition, 1.2% a , on a national scale. For ammonia (NH3), total emissions in East Asia were estimated to be 10.6 Mt a
1 in 1990 and 12.6 Mt a
1 in 1995, suggesting the increase rate of 3.4% a
1; and in Japan, a total of NH3 emissions was 0.4 Mt a
1 for both the two years (Klimont et al., 2001). No change for domestic NH3 emissions during the period estimated by them would be comparable with the mean increase rate
1 of NH+ on a national scale 4 wet deposition 1.1% a from 1989 to 1998 (Table 3). As for the NH3 emissions

ARTICLE IN PRESS S. Seto et al. / Atmospheric Environment 38 (2004) 3543–3556

in Japan, the greatest contribution was estimated to be 3.4 Mt a
1 from the agricultural sector (livestock & poultry and fertilizer application) in 1994 (Kannari et al., 2001). In summary, the above relationship between annual
+ trends of nss-SO2
4 , NO3 and NH4 deposition and those of their domestic precursor emissions suggests that both trends are generally comparable each other. For further discussion on temporal trends of ionic deposition, modeling studies on a basis of more elaborated emission data will be necessary in Asia.

5. Conclusion Annual and seasonal trends in wet deposition of major ions were discussed for JADS results on the basis of a nonlinear least-squares regression model. On a national scale, nss-SO2
4 deposition exhibited significant (po0.05) decreasing trends with a mean change rate of +
3.5% a
1. The NO
3 and NH4 deposition for the JS area showed increasing mean change rate of 3.4% a
1 and that of 3.7% a
1, respectively; however, most of the sites had no significant annual trends in the two ions. Pronounced decreases in nss-Ca2+ deposition were recognized in northern Japan and some industrialized areas. Mean change rates of H+ also decreased by 4–6% a
1 for the Pacific Ocean, East China Sea, and Seto Inland Sea areas. Annual trends of precipitation amount are concluded to have only negligible contributions to those of ionic deposition in Japan. Annual trends of the deposition were generally comparable with those of their domestic emissions and ionic concentrations, while the seasonality was attributed to the seasonal variation of precipitation amount. The predicted maximum deposition of seasonal
+ components for nss-SO2
and H+ 4 , NO3 , NH4 occurred for the Japan Sea area from autumn to winter, while for most sites in the other areas in summer. However, nss-Ca2+ had its maximum in spring throughout the country. This seasonality would be a reflection of strong impacts of Asian dust transported from the continent. The decrease of the deposition sum of nss-SO2
4 and + NO
and nss-Ca2+ 3 , and the increase of the NH4 deposition sum will be responsible for the decreased deposition of H+ for some sites in the Pacific Ocean and Seto Inland Sea areas. The estimates of annual deposition of effective hydrogen ions, sum of H+ deposition and two times of NH+ 4 deposition, for each site ranged from 50 to 119 meq m
2 a
1, which would be nearly equal to or less than their critical load estimates. The annual mean change rate of effective hydrogen ions increased by some 3% a
1 for the Japan Sea area, and decreased by some 2% a
1 for the Seto Inland Sea area.

3555

Acknowledgements The authors wish to thank anonymous reviewers for their helpful comments. This work was supported in part by funds from the Grant-in-Aid for Scientific Research in Priority Areas under Grant No. 14048213 from Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.

References Clarke, A.G., Lambert, D.R., Willison, M.J., 1990. Trends in particulate deposition and precipitation chemistry at Leeds (UK) 1907–1987. Atmospheric Environment 24B, 159–169. Dokiya, Y., Miyakoshi, N., Hirooka, T., Yamashita, J., Ishikawa, S., Ohya, M., Sugaya, J., 1995. Long range transport of sulfur compounds over the western North Pacific: deposition samples obtained on islands. Journal of the Meteorological Society of Japan 73, 873–881. Erisman, J.W., 1993. Acid deposition to nature areas in the Netherlands: Part I. Methods and results. Water, Air, and Soil Pollution 71, 51–80. Farmer, G., Barthelmie, R.J., Davies, T.D., Brimblecombe, P., Kelly, P.M., 1987. Relationships between concentration and deposition of nitrate and sulphate in precipitation. Nature 328, 787–789. Fujita, S., Takahashi, A., Weng, J.H., Huang, L.F., Kim, H.K., Li, C.K., Huang, F.T.C., Jeng, F.T., 2000a. Precipitation chemistry in East Asia. Atmospheric Environment 34, 525–537. Fujita, S., Takahashi, A., Hayami, H., Sakurai, T., 2000b. Wet deposition of nitrate and ammonium over the Japanese Archipelago. Kankyo Kagakkai-shi (Environmental Science) 13, 491–501 (in Japanese with English abstract). Ichikuni, M., 1978. Calcite as a source of excess calcium in rainwater. Journal of Geophysical Research 83 (C12), 6249–6252. Japan Environment Agency, 1998. Guideline for Wet Deposition Monitoring, 61pp. (in Japanese). Kannari, A., Baba, T., Hayami, H., 2001. Estimation of ammonia emissions in Japan. Taiki Kankyo Gakkai-shi (Journal of Japan Society for Atmospheric Environment) 36, 29–38 (in Japanese with English abstract). Klimont, Z., Cofala, J., Scho¨pp, W., Amann, M., Streets, D.G., Ichikawa, Y., Fujita, S., 2001. Projections of SO2, NOx, NH3 and VOC emissions in East Asia up to 2030. Water, Air, and Soil Pollution 130, 193–198. Lynch, J.A., Bowersox, V.C., Grimm, J.W., 2000. Changes in sulfate deposition in eastern USA following implementation of Phase I of Title IV of the Clean Air Act Amendments of 1990. Atmospheric Environment 34, 1665–1680. Murano, K., Mukai, H., Hatakeyama, S., Jang, E.S., Uno, I., 2000. Trans-boundary air pollution over remote islands in Japan: observed data and estimates from a numerical model. Atmospheric Environment 34, 5139–5149. National Astronomical Observatory (Ed.), 2001. Chronological Scientific Tables 2002, Maruzen, Tokyo, pp. 200–201 (in Japanese).

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S. Seto et al. / Atmospheric Environment 38 (2004) 3543–3556

National Atmospheric Deposition Program, 2001. National Atmospheric Deposition Program 2000 Annual Summary, NADP Data Report 2001–01, Illinois State Water Survey, Champaign, Illinois, pp. 3–11. Noguchi, I., Kato, T., Akiyama, M., Otsuka, H., Matsumoto, Y., 1995. The effect of alkaline dust decline on the precipitation chemistry in northern Japan. Water, Air, and Soil Pollution 85, 2357–2362. Norusˇ is, M.J., and SPSS Inc., 1999. SPSS Regression Modelst 10.0, Chicago, pp. 19–26. Olsen, A.R., Voldner, E.C., Bigelow, D.S., Chan, W.H., Clark, T.L., Lusis, M.A., Misra, P.K., Vet, R.J., 1990. Unified wet deposition data summaries for North America: data summary procedures and results for 1980–1986. Atmospheric Environment 24A, 661–672. Prospero, J.M., Savoie, D.L., Arimoto, R., 2003. Long-term record of nss-sulfate and nitrate in aerosols on Midway Island, 1981–2000: Evidence of increased (now decreasing?) anthropogenic emissions from Asia. Journal of Geophysical Research, 108 (D1), AAC10-1–AAC10-11. Puxbaum, H., Simeonov, V., Kalina, M.F., 1998. Ten years trends (1984–1993) in the precipitation chemistry in central Austria. Atmospheric Environment 32, 193–202. Riley, J.P., Skirrow, G. (Eds.), 1975. Chemical Oceanography, 2nd Edition. Vol. 1. Academic Press, London. Second Interim Scientific Advisory Group Meeting of Acid Deposition Monitoring Network in East Asia, 2000.

Technical Manual for Wet Deposition Monitoring in East Asia, pp. 18–36. Seto, S., Oohara, M., Ikeda, Y., 2000. Analysis of precipitation chemistry at a rural site in Hiroshima Prefecture, Japan. Atmospheric Environment 34, 621–628. Seto, S., Nakamura, A., Noguchi, I., Ohizumi, T., Fukuzaki, N., Toyama, S., Maeda, M., Hayashi, K., Hara, H., 2002. Annual and seasonal trends in chemical composition of precipitation in Japan during 1989–1998. Atmospheric Environment 36, 3505–3517. Shannon, J.D., 1999. Regional trends in wet deposition of sulfate in the United States and SO2 emissions from 1980 through 1995. Atmospheric Environment 33, 807–816. Shindo, J., Fumoto, T., 1998. Estimation of acid buffering capacity of soils and its modeling for evaluation of soil acidification. Global Environmental Research 2, 95–102. Sisterson, D.L., Bowersox, V.C., Olsen, A.R., 1990. Wet deposition of atmospheric pollutants. In: Sisterson, D.L. (Principal author), Deposition Monitoring: Methods and Results, National Acid Precipitation Assessment Program, Acidic Deposition: State of Science and Technology Report 6. NAPAP Office, Washington, DC, pp. 6-145–6-174. Streets, D.G., Tsai, N.Y., Akimoto, H., Oka, K., 2001. Trends in emissions of acidifying species in Asia, 1985–1997. Water, Air, and Soil Pollution 130, 187–192.