Research on the Conservation of
Northwest Pacific Marine Environments
Water Quality Control Department
National Institute for Land and Infrastructure Management
Ministry of Land, Infrastructure, Transport and Tourism

1. Introduction
Recent years have brought remarkable economic growth in the Northwest Pacific region, leading to industrial
development and rapid population growth. At the same time, however, factory effluence and domestic wastewater
have caused progressive water pollution, and a deterioration in marine environments symbolized by the occurrence of
toxic red tide, among others, has become manifest in the Northwest Pacific (encompassing the Bohai Sea, Yellow Sea,
East China Sea and the Sea of Japan). To address this problem, various efforts are underway in countries of theNorthwest Pacific region to prevent water pollution in rivers and seas. However, while improvements to sewerage areyielding a degree of success in reducing pollution caused by urban effluence, there is still much to be desired, bearing
in mind the scale of economy and speed of economic growth in these countries.
Given this situation, the Wastewater System Division of the National Institute for Land and InfrastructureManagement (NILIM) of the Ministry of Land, Infrastructure, Transport and Tourism has, for three years since fiscal
2008, studied methods of conserving marine environments by reducing the discharge of pollutants from the mainland,
mainly by developing sewer systems in the countries concerned, with a view to conserving marine environments in
the Northwest Pacific. Fig. 1 shows the flow of this research over those three years, while Fig. 2 outlines the basin
areas subject to study in this research. As shown in Fig. 2, “the Northwest Pacific” refers to the Bohai Sea, Yellow Sea,
East China Sea and the Sea of Japan. Reducing pollutant emissions from countries facing these seas (Japan, China,
South Korea and Russia) is expected to contribute greatly to conserving marine environments.
As for the flow of this research, the first process was a preparatory stage with the aim of defining the behavior ofpollutants at sea and measures by the countries concerned (Japan, China, South Korea and Russia) to curb pollutant
emissions from land areas. In addition, existing research was defined and data on land and sea areas in the countries
concerned were gathered in fiscal 2008. Next, in fiscal 2009, we created a model of pollutant emissions from land
areas in the countries concerned, i.e. Japan, China, South Korea and Russia (“Pollution Load Model”) using various
data on topography, pollutant unit load, river flow rates, rainfall and others gathered in fiscal 2008 and 2009. On thisbasis, we established future scenarios up to the year 2030, taking account of economic growth (pollutant emissions)and the improvement of sewer systems, etc. (pollutant reduction). Moreover, volumes of pollutant discharge,
calculated from the Pollution Load Model and future growth scenario thus created, were used as input values in a
separately created Ocean Flow Model targeting the Bohai Sea, Yellow Sea, East China Sea and Sea of Japan. From
this, we ascertained changes in the volume of pollutants at sea. In fiscal 2010, the final year of the project, we
supplemented and corrected the results of simulation calculations conducted up to fiscal 2009, as well as studying
measures for conserving marine environments in the Northwest Pacific, taking account of the finally calculated
effects of measures to reduce pollutants.
The content of the research over the three years will now be described in the following sequence: 2. Results of data
gathering on pollutant emissions from land areas and marine environments in the countries concerned, 3. Method of
simulating land-based pollution loads and calculation results, 4. Method of simulating ocean flow and calculation
results, 5. Outline of international symposia held over the last three years, 6. Outline of research partnership between
the countries concerned, and 7. Summary.

1

FY2008• Define existing research• Define the current state of marine pollution• Gather data on pollutant unit load from landareas

Map showing basin areas in the Northwest Pacific region

Sea ofJapan

FY2009• Create a simulation model for land and sea areas• Study future scenarios taking account of
economic growth• Predict pollutant load using the model createdBohai Sea
Yellow Sea

LegendEast China Sea

FY2010• Supplement and correct the results of simulation
calculation• Study measures for conserving marine
environments in the Northwest PacificNational border
Basin area affecting the Sea ofJapan
Basin area affecting the East China
Sea
Basin area affecting the Yellow
Sea
Basin area affecting the Bohai Sea
Outside the scope of pollutant unit
load

Fig. 2 Area covered by the research

Fig. 1 Flow of research
2. Results of information gathering on marine environments and pollutant emissions from land areas in the
countries concerned
2.1 Information on pollutant emissions from land areas in the countries concerned
As stated in the previous section, simulating the emission of land-based pollution in neighboring countries,
ascertaining the current situation of pollutants discharged into the sea and predicting their future progression areimportant steps in this research. To create this Pollution Load Model, in fiscal 2008 we first gathered reference
literature and other information on the level of establishment or designation of water environment standards, thestatus of wastewater regulation, the level of sewer system development, water resources, pollutant volumes, pollution
analysis and water environment conservation measures in the countries concerned (Japan, China, South Korea andRussia). Although we succeeded in gathering basic reference material on each country, very little reference material
and data could be gathered on Russia; even when data could be gathered, not all of the latest data had been madepublic.
Meanwhile, as data for actual use in the Pollution Load Model, we gathered topographical and land use data,
population data, temperature and rainfall data, value of industrial production data, point source, nonpoint source andother pollutant unit loads, and monitoring data on water quality and water volume, etc., in major rivers. Basically, allof these data were gathered from materials published by the various countries. The data on China, for example, weregathered from the Chinese Statistical Yearbook, National Bureau of Statistics of the People’s Republic of China1), andautomatic monitoring data on water quality in China’s principal river basins, Ministry of Environmental Protection 2),among others.
In some cases, however, attempts to gather reference materials and data, etc., yielded no suitable information.
When it was not possible to gather survey data on pollutant unit load (e.g. unit load concerning nonpoint sources inforests, farmland, and built-up areas in China), we used average data from Japan, or otherwise substituted data fromcountries with similar data trends.
2.2 Information on marine environments in the countries concerned
The volume of pollutant discharge calculated using the “Land-based Pollution Load Model” built from data
gathered in 2.1 was incorporated into the separately built “Ocean Flow Model” as an input value. Making calculations
for the Ocean Flow Model enabled us to reproduce marine pollution and predict its future development. With a view
to building an Ocean Flow Model, we mainly surveyed three types of information in fiscal 2008. These were 1

2

survey information on Ocean Flow Models, 2 information on surveys of the applicability of impact assessment
models from neighboring countries, 3 information on surveys of marine environments in the Northwest Pacific.
2.2.1 Survey information on Ocean Flow Models
On investigating existing research and surveys on Ocean Flow Models, research results were seen incomparatively large quantities in the East China Sea near Japan, but there were few examples of calculation or
observation in the Bohai Sea, the Yellow Sea area, or the East China Sea near China. Moreover, it also became clearthat hardly any numerical simulations encompassing the whole area of the Bohai Sea, the Yellow Sea, the East China
Sea and the Sea of Japan have been published. From this, to build the Ocean Flow Model for the whole of theNorthwest Pacific, the most appropriate method was thought to be to divide sea areas at characteristic places like theTsushima Strait, study a simulation model that matches the characteristics of both the East China Sea and the Sea ofJapan, and continuously link the simulation research.
2.2.2 Information on surveys of the applicability of impact assessment models from neighboring countries
In parallel with the Ocean Flow Model, we also surveyed the applicability of impact assessment models ofpollutant emissions from neighboring countries (“water pollution models”). As a result of the survey, the “lowecosystem model” was invariably being applied to impacts on sea areas when the load from land areas changed, under
the Comprehensive Basin-wide Planning of Sewerage Systems (CBPSS) in Tokyo Bay3) and the 6th Total Pollutant
Load Control4). The main reason for application is that, in sea areas with advanced eutrophication, when the load ofnutrient salts (nitrogen (N) or phosphorus (P)) from land areas changes, it is known that, even when the COD load
itself does not change, an impact on COD concentrations in sea areas is caused by changes in the production ofphytoplankton. Taking these situations into account, it was considered desirable to opt for a “low ecosystem model”
in this research, just as in CBPSS in Tokyo Bay3). With this, we could assess the environmental impact on Japanaccompanying changes in load on sea areas due to economic activity in countries of the Northwest Pacific region as
well as changes in the development level of sewer systems and other social infrastructure.
2.2.3 Information on surveys of marine environments in the Northwest Pacific
In parallel with the survey in the previous subsection, we also gathered information concerning existing studies on
marine environments in the Northwest Pacific. In this survey, we gathered and organized data on water quality incountries along the coasts of the Northwest Pacific (Chinese Environmental Yearbook5), South Korea Statistical
Yearbook6), survey reports on water quality in public water areas7), etc.), remote sensing data, and data on marine
litter. From the data obtained, we were able to confirm, with respect to water quality data, the severity of pollution in
Chinese coastal regions, as well as increased nitrogen concentrations in South Korean coastal regions. In Russiancoastal regions, it became clear that, although the monitoring results of heavy metals are published, published figures
for monitoring results on eutrophication substances are almost non-existent. In Japanese coastal regions, meanwhile,an increase in COD concentrations in the Tsushima sea area was recognized, and it was suggested from the gathereddata that concentrations originating in the East China Sea could be rising.
On remote sensing data, as a result of gathering information, it was thought desirable to use the MODIS data
provided by the Japan Aerospace Exploration Agency (JAXA)8). The reasons for this were that wide-region remotesensing data could be obtained, even in districts where other data were difficult to obtain, and the data obtainablethrough MODIS, notably those on water temperature and chlorophyll-a, would be very useful when calculating an
Ocean Flow Model, as in this research. (Fig. 3, Fig. 4 (different MODIS data))

3

Fig. 3 Water temperature Oct. 2002 (℃)

Fig. 4 Chlorophyll-a Oct. 2002 (μg / l)We also comprehensively gathered and organized information on the migration routes of giant jellyfish, thesituation of marine litter, and sources of marine litter through reference to various data. In recent years, marine litterand other debris has been washed up on Japanese territory with increasing frequency, but we have also found, throughsimulation, that predictive calculations of the transit routes of jetsam are also possible.

3. Method of simulating land-based pollution and calculation results
3.1 Method of simulating land-based pollution
3.1.1 Basic rationale on constructing the Land-based Pollution Load Model
Using the information gathered in fiscal 2008, while supplementing missing information and making amendments,
we constructed a Land-based Pollution Load Model for Japan, China, South Korea and Russia to ascertain the volumeof pollutants released into the Northwest Pacific.
When constructing the Land-based Pollution Load Model, we focused on COD, nitrogen (N) and phosphorus (P)as target pollutants, taking account of the need to gather complete data for all countries. The method used to calculate
pollutant load, with reference to the rationale of the Comprehensive Basin-wide Planning of Sewerage Systems9) inJapan, followed the “unit load method”, as shown in Fig. 5. As for the procedure for calculating the Pollution Load
Model, as well as gathering the various data explained in the next subsection, we started by dividing into drainage
system blocks, as shown in Fig. 6. After setting frame values (such as population), the load arising and the unit load
for each block, we calculated the total generated load. After this, we made corrections for the rate of reduction due tomeasures and the volume of nonpoint sources. In China, we performed corrections taking account of the rate of loss
due to the withdrawal of water for commercial farming, the delivered ratio of rainfall into rivers, etc., and in Russia,
corrected the water quality of factory effluence, finally arriving at a calculation of the total delivered load to sea areas.
Divide into drainage system
blocks

水系のブロック分割

Blocks(breakdown: city / prefecture units)
ブロック(内訳：市･県単位)
Rivers
河川
Generate
発生排出Discharged

流達

Set frame values
フレーム値の設定(population, value of shipments,（人口、出荷額、箪産頭数等）_
livestock numbers, etc.)

Delivered

Man-made

Processed
処理

人
為
系

住居系
Residential

Set unit load factor
発生汚濁負荷量

Factory
工場系

畜産系
Livestock

Block
ブロック
(prefecture/ city)（県・市）

Calculate generated
load

発生負荷量の算定

Rate of reduction due
蚕策による削減率_
to measures

山林系
Forests
Natural自然系

of generated
pollution load

原単位の設定Farmland
農地系
Built-up
land
市街地系

降雨系
Rainfall

Sea海域
area
未処理
UnprocessedTakeaccount of reduction rate
施策による削減率(removalrate) due to measures(除去率)を考慮

Take
account of delivered ratio
排出経路の特質に応
in line with properties of
じた流達率を考慮
emission routeTakeaccount of the runoff ratio
河川流出特性に応じin line with properties of river
た流出率を考慮
runoffFig. 5 Image of calculation of the Land-based Pollution Load Model4

Calculatedischarged
排出負荷量の算定
load[Japan/ South Korea /【日暴・韓国・ロシア】_
Russia]・面源系負荷量の補正● Correct nonpoint
source load

[China]•【中国】
Rate of loss due towithdrawal
・利水による消失率• Delivered ratio of
・降水量の河川への流達率
precipitation
to rivers

Calculatetotal loaddelivered to sea
海域への総流達
負荷量の算定areas

Fig. 6 Calculation flow of theLand-based Pollution Load Model3.1.2 Various data used in the Land-based Pollution Load Model
To build the Land-based Pollution Load Model, since fiscal 2008 we have gathered data and reference materials
on the level of establishment or designation of water environment standards, the status of wastewater regulation, thelevel of sewer system development, water resources, pollutant volumes and water environment conservation
measures in the countries concerned (Japan, China, South Korea and Russia). Meanwhile, for topography, land use,
population, industry, pollutant unit load, water quality in major rivers, flow volumes and other data necessary to build
the Pollution Load Model, we have gathered data from published materials5)6)7), etc. When data on pollutant unit load
could not be gathered from published materials, etc. (e.g. unit load data on overseas forests, farmland and built-up
areas), we used Japan’s Guidelines and Explanation of the Comprehensive Basin-wide Planning of Sewerage
Systems 9), among others, to substitute with data from countries assumed to have similar situations in terms of unit
load.
3.1.3 On the segmentation of drainage system blocks
The segmentation of drainage system blocks was based on the basins of major rivers, with 7 sub-blocks for the
Chang Jiang River and Yellow River basins in China. For regions close to coasts, meanwhile, we set drainage system
blocks as direct discharge blocks, in which pollutants are directly discharged into sea areas (Fig. 7). We also set
drainage system blocks for Japan, South Korea and Russia, with 10 blocks, 5 blocks and 4 blocks, respectively, foreach of the sea areas of the Sea of Japan, the Yellow Sea and the East China Sea (Fig. 8).

Liao
River
Yalu
River

YellowRiver

Huai River

Chang Jiang River

LegendSub-block boundary
In blue Sub-block number
Yellow River basin
Huai River basin
Hai River basin
Liao River basin
Amur River basin
Other basin
Outside scope
Chang Jiang River observation points PC1-PC7

Yellow River observation points PK1-PK7
Liao River observation points PR1-PR2
Huai River observation points PW1-PW3

Fig. 7

Sea of Japan

Chang Jiang River basin

LegendCoastline (if on land:national frontier)Basin area affecting the
Sea of Japan
Basin area affecting theEast China Sea
Basin area affecting the
Yellow Sea
Basin area affecting theBohai Sea
Outside the scope ofpollutant unit load

Fig. 8 Segmentation of basin blocks inJapan, South Korea and Russia

Segmentation of basin blocks in China

3.1.4 Unit loads used in the Land-based Pollution Load Model
As the unit loads used in the Land-based Pollution Load Model, for China we mainly used the values in the “Water
Environment Restoration Pilot Project in Taihu Lake, People’s Republic of China (JICA)” 10), for Japan those of the“Guidelines and Explanation of the Comprehensive Basin-wide Planning of Sewerage Systems” 9), and for South
Korea those of the “Total Drainage System Pollution Management Technology Guidelines” 11). For Russia, since notenough data on unit loads could be obtained, we substituted figures from other countries (such as using the settings
for China, which has the most similar per capita GDP values of the other three countries). The pollutant unit loads
used in the constructed Pollution Load Model are tabulated below. (Table 1, Table 2, Table 3, Table 4)

5

項目

Item

中国、ロシアChina,
Russia
標準法除去率Removalrate by standard
COD

日本
Japan
T-N

標準法除去率Removal rateby standard method

T-P

80.0%
30.0%
下水道
Sewers80.0%
42.0%
合併浄化槽septic tanks
Combined
中国の除去率は、日本の除去率と同等とした。
China’sremoval rates were the same as those of Japan

Removal高度処理型除去率
rate by advanced treatment

除去率rateRemoval

COD

T-N

T-N

Removal rate標準法除去率
by standard method

T-P

COD

T-N

T-P

下水道
60.0% Sewers

④

80.0%

30.0%

60.0% Sewers
下水道

80.0%

30.0%

60.0%

農集等 etc.
38.0% Farm collection,

⑤

81.5%

44.5%

51.5% Combined
合併浄化槽septic tanks

80.0%

42.0%

38.0%

Combined
septic tanks
合併浄化槽

⑥

80.0%

42.0%

38.0%

Human
waste
し尿分

53.5%

34.4%

30.0%

Human
waste
し尿分

⑦

53.5%

34.4%

30.0%

Wastewater
雑排水

0.0%

0.0%

0.0%

0.0%

0.0%

0.0%

Separate
単独

下水道
Sewers
合併浄化槽septic tanks
Combined

韓国
South Korea

COD

Wastewater
雑排水⑧
Removal高度処理型除去率
rate by advanced treatment

T-P

COD

T-N

T-P

Separate
単独

Removal高度処理型除去率
rate by advanced treatment

COD

T-N

T-P

90.0%

75.0%

下水道
85.0% Sewers

④’

90.0%

75.0%

85.0% Sewers
下水道

90.0%

75.0%

85.0%

85.0%

67.0%

農集等 etc.
38.0% Farm collection,

⑤’

90.0%

75.0%

septic tanks
85.0% Combined
合併浄化槽

85.0%

67.0%

38.0%

Combined
septic tanks
合併浄化槽
85.0%
67.0%
38.0% Although the South Korean standards for sewer facilities (Korea⑥’
韓国における下水道施設基準（韓国上下水道協会、2005年【下水道の出典：設計指針（後編）】
Sourcefor sewers: Design Guidelines (Part II)
Water
and Wastewater Works Association, 2005, Ministry環境省）に
of theは、除去率の記載がないものの、韓国国内の処理方式として標準活性汚泥
標準活性汚泥法による家庭排水を対象にした一般的な除去率が記載
Thesestate general removal rates for domestic wastewater using the standard
do not specify removal rates, they were assumed to方が多いため、日本の除去率と同等とした。
されており、本調査では中間値を設定した。
activatedsludge method, the middle values being adopted for this survey. For the T-N Environment)same as those in Japan, since the standard activated sludge
andT-P removal rates, we adopted the secondary processing averages for sewage beなお、下水道区域外人口は「単独浄化槽」の除去率を採用した。
また、T-N、T-Pの除去率は下水の「高度処理技術（平成4年)」に示さ
indicatedin “Advanced Processing Technology (1992)”.
れている二次処理平均値を採用した。
method is commonly used as a method of treatment in South Korea.
*Figuresfor treatment plants operating within the scope of the Design Guidelines
韓国の下水道区域内普及率には、合併浄化槽等も含まれており、区分で※設計指針の範囲内で運転している処理場の数値
For
the population outside the sewerage area, the removal rates for
Sourcefor farm collection, combined septic tanks, etc.: CBPSS
きないため、下水道除去率を適応する。
【農集・合併浄化槽等の出典：流総指針】
The
removal rates for farm collection were based on the results of pollution volume “separate septic tanks” were adopted. The diffusion rate inside
農集除去率は排出量・負荷量原単位調査結果に基に、設定した
andunit load surveys.
合併浄化槽の除去率は、湖沼水質保全計画値（11箇所の平均値）をsewerage areas in South Korea includes combined septic tanks,The
removal rates set for combined septic tanks adopted the values in the Plan for
採用した
etc., and cannot be divided. Therefore, the sewerage removal rate isConservationof Lake Water Quality (average values in 11 locations).
単独浄化槽の除去率は、調査資料等を基に設定されている排出負荷The
removal rates for separate septic tanks were based on the pollutant unit load set applied.
量原単位をもとに設定

中国の除去率は、日本の除去率と同等とした。
China’sremoval rates were the same as those of Japanon the basis of survey materials, etc.

標準法 method
Standard

COD

Released into
Domestic
Urban
areas 下水道放流
生活排水A
都市部
A
wastewater
sewersDirectly
Urban
areas 直接排水
都市部
discharged

Rural
areas
農村部
Rural
areas
農村部

Domestic
生活排水B
wastewater
B
Domestic
Combined
生活排水C
合併浄化槽
C
septic tanks wastewater
Directly
Domestic
生活排水D
直接排水
discharged
wastewater
D

Rural
areas
農村部
Rural
areas
農村部

Domestic
Combined
生活排水C
合併浄化槽
septic tanks wastewater C
Directly
Domestic
生活排水DD
直接排水discharged
wastewater

標準法（シナリオ1,2,3）
Standard
method (scenarios 1, 2, 3)

T-P

Sewers
下水道

COD

T-N

T-P

標準法（シナリオ1,2,3）
Standard
method (scenarios 1, 2, 3)
Released into7

0.4

③×(1-④)

5.4

7.7

areas 下水道放流
生活排水AA
0.5 Urban
都市部
wastewater
sewers16.5

25

農集等 etc. ③×(1-⑤)
0.5 Farm collection,
Combined
septic③×(1-⑥)
合併浄化槽
0.5
tanks
Human
waste ①×(1-⑦)+②×(1-⑧)
0.4 Separate
単独
し尿分

5.0

6.1

areas
0.6 Urban
都市部

4.0

5

12.5

2

T-N

高度処理（シナリオ2’、3’）
Advancedtreatment (scenarios 2', 3')

T-P

Sewers
下水道

2.8

3

0.2

16.5

25

農集等 etc.
0.5 Farm collection,
Combined
septic
合併浄化槽
0.5
tanks
Vault汲取等
toilets, etc.
0.4

3.0

3

12.5

2

5.4

6.4

areas
0.8 Rural
農村部

21.7

7.9

areas
1.0 Rural
農村部

COD

T-N

T-P

③×(1-④’)

2.7

0.3③×(1-⑤’)

2.7

0.4

COD

Domestic

5.6

Pollutantunit load
排出負荷量原単位※高度処理除去率を用いた場合*If
using the advanced treatment removal rate
［発生×（1-除去率）］(generated
load x (1 –高度処理
Advancedtreatment
CODremoval rate))
Released into
Domestic
Urban
areas 下水道放流
生活排水A
都市部
sewersA
wastewater
Directly
Domestic
Urban
areas 直接排水
生活排水BB
都市部
discharged wastewater

T-N

Domestic
Untreated
未処理（単独） 生活排水B(separate) wastewater B
Combined septic Domestic
生活排水CC
合併浄化槽
wastewater
tanks
Untreated
Domestic
未処理（単独）生活排水CD(separate)
wastewater

高度処理（シナリオ2’、3’）
Advancedtreatment (scenarios 2', 3')
Released into

③×(1-⑥’)

4.1

0.4

areas
0.4 Rural
農村部①×(1-⑦)+②×(1-⑧)

21.7

7.9

areas
1.0 Rural
農村部

wastewater B
Domestic
Combined
septic 生活排水C
合併浄化槽
wastewater C
tanks
Domestic
Untreated
未処理（単独） 生活排水C
wastewater D(separate)

T-P
7.4

0.5

21.7

7.7

0.9

5.4

7.5

0.9

21.7

9.4

1.1

COD

Domestic

areas 下水道放流
生活排水AA
0.6 Urban
都市部
wastewater
sewers
Untreated
Domestic
areas 未処理（単独）
生活排水B
0.5 Urban
都市部(separate)

T-N

5.4

T-N

T-P

2.7

2.7

0.2

21.7

7.7

0.9

4.1

4.3

0.9

21.7

9.4

1.1

Table 1 Setting of pollutant removal rates and generated pollutant unit loads in domestic wastewater inthe countries concerned
中国、ロシアChina,
RussiaItem
項目
Calculation
method
算定方法

日本
Japan

工場系排出負荷量＝フレーム値（工業総生産額）×排水量原単位×工場排
To be calculated as [Factory-related pollution load = Frame value (Gross industrial To
be calculated as [Industrial shipments value x Pollution unit load].
工業出荷額×負荷量原単位にて算定する方針とする。
水水質にて算定する方針とする
output value) x Effluence unit load x Water quality of factory effluence]
Effluencemeeting water quality standards: Factory effluence A【供用開始区域外】【水質基準達成排水：工場排水A】
Outside the service start areaGrossindustrial output value x Factory effluence unit load x Factory effluence standards x Water quality Industrial
工業出荷額×工場排水負荷量原単位A
工業総生産額×工場排水量原単位×工場排水基準×水質基準達成率
shipments value x Factory effluence pollution unit load A
standards
achievement rate
【供用開始区域内】【水質基準達成排水：工場排水B】
Inside the service start area
Effluence meeting water quality standards: Factory effluence B
工業出荷額×工場排水負荷量原単位B×（1-下水道除去率）
工業総生産額×工場排水量原単位×工場排水水質×（1-水質基準達成 Industrial
shipments value x Factory effluence pollution unit load B x (1-sewer
Gross industrial output value x Factory effluence unit load x Water quality of factory effluence x (1-Water率） standards achievement rate)
removal rate)quality

韓国
South
Korea

To
be calculated as [Factory-related pollution load = Frame value (Gross
工場系排出負荷量＝フレーム値（工業総生産額）×排水量原単位×工場
排水水質にて算定する方針とする
industrial
output value) x Effluence unit load x Water quality of factory effluence]

Water qualityof factory effluence (mg /出荷額当たり負荷量原単位（ｇ/日/百万円）
工場排水水質（ｍｇ/L)
COD
T-N
T-P
COD
T-N
T-P
COD
T-N
T-P
(g
/ day / million yen)L)
Unpolluted river regions (less than 2000m3 /Effluencemeeting water
Factory
the service start
Factory
effluence A 66.7
工場排水A
工場排水A
水質基準達成排水25
0.3 Outside
20～120
10～50
2～8
50
30.0
4.0
供用開始区域外
清流地域の場合（2000m3/日未満）
qualitystandards
day)
effluence A
area
Effluence not meeting water Factory effluence B
Industrial effluence unit
the service start area Factory
regions (less than 2000m3 / day)
水質基準未達成排水
工場排水B
工場排水B
200.0
26
3.0 Inside
280～51020～90
2～13 AA地域の場合（2000m3/日未満）
90
60.0
8.0
供用開始区域内
effluenceBload (mg / L) or (g / day / quality standards
For
Japan, pollution unit load inside and outside the sewer service start area BB地域の場合（2000m3/日未満）【水質基準達成排水：工場排水基準】
日本は下水道供用開始区域内・外の汚濁負荷量原単位を都道府県別
Effluencemeeting water quality standards: Factory effluence standards
regions (less than 2000m3 / day)
工場排水負荷量原単位
130
60.0
8.0
million
yen)
is
set
per
prefecture
中国環境基準二級基準濃度（CODCｒ）を基に設定した。
に設定
Set
on
the
basis
of
the
Grade
2
standard
concentrationinChineseEnvironmental（mg/L）又は（ｇ/日/百万
Regions subject to special orders (less than
特例地域の場合（2000m3/日未満）
Outsidethe service start area
40
60.0
8.0
3 / day)
ただし、CODMnへの変換は、JICA資料を基にCODCr÷3にて想定した。
【供用開始区域外】
2000m
Standards(CODCr).
円）
Setbased on more stringent prefectural standards on effluence【水質基準未達成排水：工場排水水質】
都道府県別の上乗せ排水基準をもとに設定
Effluence
regulation values in South Korea are determined in accordance with韓国における排水規制値は、地域区分（清流地域、A地域、B地域、特例
Theconversion to CODMn was assumed to be CODCr ÷ 3, based on JICA
Insidethe service start area
JICA資料（太湖流域調査）を基に200mg/lと想定した。
【供用開始区域内】
regional
divisions(unpolluted
river
regions,Aregions,B
regions,
Regions
subject
to地域）に応じて定められており、その地域区分は行政区単位に設定されてmaterials.
Set
based on sewer abatement standards
下水道の除害施設基準をもとに設定
specialいる。 orders), and these regional divisions reflect units of administrative areas.
Effluence not meeting water quality standards: Water quality of factory effluence The water quality shown above is assumed from the volume of effluence and In
this survey, we surveyed and set representative regional divisions for each
本調査では、行政区ごとの代表的な地域区分を調査し、設定した。
thepollutant load.
Assumed to be 200mg / l based on JICA materials (Taihu Lake Project).
administrative area.
上記水質は、排水量と負荷量から想定した水質を示す。
Water qualityof factory effluence(mg/ L)
工場排水水質（ｍｇ/L)

Pollution unit load per shipment value

Table 2 Methods of calculating factory effluence load and the water quality of factory effluence6中国、ロシア
日本
China,
RussiaJapan
To be calculated as [Livestock-related pollution
load = Frame value (livestock numbers) x Pollution unit load x Discharge rate]
家畜系排出負荷量＝フレーム値（家畜頭数）×発生負荷量原単位×排出率にて算定する方針とする

項目
Item
算定方法
Calculation
method
フレーム値
Frame
value

For Japan, we surveyed the following frame values (livestock). 韓国は以下のフレーム値（家畜）を調査した。
For South Korea, we surveyed the following frame values (livestock).
日本は以下のフレーム値（家畜）を調査した。
Dairy
cattle, beef cattle, horses, pigs, deer, poultry
Cattle,牛、豚 pigs
乳牛、韓牛、馬、豚、鹿、家檎For China, we surveyed the following frame values (livestock).
中国は以下のフレーム値（家畜）を調査した。
大牧畜（牛、馬）、豚、羊
Large
pasturing livestock (cattle, horses), pigs, sheep
COD

T-N

T-P

COD

T-N

T-P

Livestock
A (large pasturing livestock)
畜産A（大牧畜）

65.06

108.770.30 Cattle
牛

畜産B（豚）
Livestock
B (pigs)

8.38

14.06

3.00 Pigs
130
40
豚【出典：流総指針】
Survey Guidelines and Explanation of the CBPSS
25.00 Source:「流総指針」では農林省畜産局資料等をもとに設定している。

530

290

COD

161.8

56.7

25 Beef
韓牛 Cattle

530.0

116.8

36.1

馬
Horses
豚
Pigs
鹿
Deer
家檎
Poultry

Discharge rate

T-P

4.2%

3.8%

COD

1.3% Cattle
牛

2.9%

T-N

T-P

4.2%

77.6

24.0

27.7

12.2

10.0

5.8

0.9

3.0

1.1

0.4

COD

1.3% Dairy
乳牛 Cattle

6.0%

Quality (cattle: average value for 13 locations, pigs: averagevalue for 12 locations) was adopted

pigs for sheep)

530.0
130.0

Source:Total Drainage System Pollution Control Guidelines (National Office of【出典：水系汚染総量管理指針（国立環境研究室）】
Environmental
Research)
ただし、CODは日本の原単位を採用
For COD, Japan’s unit load was adopted

3.7% Pigs
3.8%
6.0%
3.7% Beef
豚
韓牛 Cattle【出典：流総指針】
Livestock
C (sheep)
3.8%
6.0%
3.7% Source:
畜産C（羊）馬
CBPSS
Horses
排出率は、湖沼水質保全計画（牛：13箇所の平均値、豚：12箇所の平中国の排出率は、日本と同等とした（羊は豚を採用）
the discharge rate, the Plan for Conservation of Lake Water Pigs
China’sdischarge rate was taken to be the same as Japan’s (using For
豚均値）を採用Livestock
B (pigs)
畜産B（豚）

排出率

T-N

2.9%

T-P

530.0

In the Water Environment Restoration Pilot Project in Taihu Lake,
PRC (JICA), unit load was set on the basis of Chinese data.

COD

T-N

50 Dairy
乳牛 Cattle

3.28
6.25
Livestock
C (sheep)
畜産C（羊）
Pollution unit load 【出典：中華人民共和国太湖水環境管理計画調査 （JICA)】
発生汚濁負荷量原単位
Source: Water Environment Restoration Pilot Project in Taihu Lake, In the “Comprehensive Plan”, these are set on the basis of(g /（g/頭･日）
head / day)
中華人民共和国太湖水環境管理計画調査 （JICA)では、中国の資料に materials from the Livestock Bureau, MAFF, among others.
PRC(JICA)
基づき、原単位を設定している。

Livestock
A (large pasturing livestock)
畜産A（大牧畜）

South韓国
Korea

鹿
Deer
家檎
Poultry

T-N

T-P

2.9%

4.2%

1.3%

2.9%

4.2%

1.3%

1.0%

1.9%

2.9%

3.8%

6.0%

3.7%

1.0%

1.9%

2.9%

10.0%

10.0%

1.3%

Source:CBPSS【出典：流総指針】
日本の排出率を採用（鹿は馬を採用）
Japan’sdischarge rate adopted (using horses for deer)

Table 3

Livestock effluence unit load and discharge rates

中国、ロシアChina,
Russia

項目
Item
算定方法
Calculation method
フレーム値
Frame value

日本
China, Japan
RussiaTo be calculated
as [Nonpoint pollution load = Frame value (land use area) x Generated pollution unit load]
面源系排出負荷量＝フレーム値（土地利用面積）×発生負荷量原単位にて算定する方針とするSouth韓国
Korea

For Japan, we surveyed the following frame values (land use area). For
South Korea, we surveyed the following frame values (land use area).
For
China, we surveyed the following frame values (land use area). 日本は以下のフレーム値（土地利用面積）を調査した。
中国は以下のフレーム値（土地利用面積）を調査した。
韓国は以下のフレーム値（土地利用面積）を調査した。
Forests,
paddy fields, dry fields, built-up areas
Forests,
paddy fields, dry fields, built-up areas
山林、水田、畑、市街地
山林、水田、畑、市街地
山林、水田、畑、市街地
Forests,
paddy fields, dry fields, built-up areas
COD

Forests 山林
水田
Paddy Fields
Discharged pollution
排出汚濁負荷量原単位
畑地（kg/ha･年）
unit load(kg / ha / year) Dry Fields
Built-Up市街地
Areas

T-N

T-P

20.7

4.2

0.17

42.9

11.0

1.30

19.1

32.2

0.36

51.1

12.1

0.81

中国の原単位は、日本と同等とした。
China’sunit load was taken to be the same as Japan’s.

Table 4COD
山林
Forests
Paddy水田
Fields
畑地
Dry Fields
市街地
Built-Up
Areas

T-N

T-P

20.7

4.2

0.17

42.9

11.0

1.30

19.1

32.2

0.36

51.1

12.1

0.81

Source: CBPSS【出典：流総指針】
Adoptedthe Plan for Conservation of Lake Water Quality (average of 11
湖沼水質保全計画（11箇所の平均値）を採用
locations)

COD

Forests山林
水田
Paddy Fields
畑地
Dry Fields
市街地
Built-Up
Areas

T-N

T-P

41.4

8.0

0.50

128.7

34.5

0.90

19.1

23.9

2.20

204.4

50.0

7.70

Source:Total Drainage System Pollution Control Guidelines (National Office of【出典：水系汚染総量管理指針（国立環境研究室）】
Environmental Research)
Forただし、CODは次頁参照
COD, see the next section

Nonpoint source pollutant unit load

3.1.5 Method of calculating load using Land-based Pollution Load Model calculations, and method of
calculating corrections
With the constructed Pollution Load Model, we calculated discharged load by multiplying the frame values(population, etc.) of the various discharge sources by the unit load factor of each discharge source, in accordance withthe unit load factor calculation method. We then calculated the total discharged load by adding together thedischarged loads from each discharge source (e.g. point source, factory-related, etc.). For example, when calculating
man-made load, the process was[Point source load] = [Population (divided into urban and rural areas)] x [Unit load factor].
For nonpoint sources, for example in the case of forests, the calculation took the form
[Nonpoint source volume (forests) ] = [Land use area (forests) ] x [Unit load factor].
As the rationale on annual delivered load from land to sea areas, meanwhile, in Japan, South Korea and Russia, we
calculated the annual delivered load to sea areas as if the entire load discharged to land areas runs off to sea areas
throughout the year, following the rationale of examples that deal with Japan’s enclosed sea areas. In other words,
annual delivered ratio = 1.0. In China, on the other hand, basin areas are vast, and meteorological conditions, water
use situations and other factors differ from those in other countries. Therefore, we did not apply the hypotheticalannual delivered ratio = 1.0 set for Japan, South Korea and Russia, but took account of the rate of loss of pollution
load through river withdrawal for agricultural and other uses, and the runoff ratio of rainfall to rivers, whencalculating delivered load to sea areas (Fig. 9, Fig. 10).
The estimated annual delivered load was used for analysis of the Ocean Flow Model (discussed later). When
doing so, however, the annual delivered load needed to be redistributed for each season. In this research, we
calculated seasonal delivered load by multiplying annual delivered load by the ratio of seasonal rainfall to annual
rainfall in the target area (Fig. 10, Fig. 11).
As other corrective calculations, in Japan, South Korea and Russia, we made corrective calculations for nonpoint
source pollutant volume according to annual rainfall in each basin. When making corrective calculations, we used the7following correlation equation between the runoff ratio from nonpoint sources (forests, paddy fields, dry fields,
built-up areas) and annual rainfall volume, created in this research (Fig. 12).

Pollution source

Generated load

Load reduction through measures

Block downstream flow andwater quality monitoring
pointsBlock upstream flow and water Discharged loadquality monitoring points

Flowdown load

Runoff load

Load reduction due towithdrawal (rate of loss)

Runoff load

Runoff ratio• Generated load: Load generated from pollution sources (man-made, nonpoint)• Discharged load: Of the generated load, load actually discharged• Flowdown load: Load taking account of loss rate
Discharged load x (1 – loss rate)• Runoff load: Load reaching water quality datum points (= observed load)• Runoff ratio: (Upstream block runoff load + Target block flowdown load) ÷ Block downstream
observed value

Fig. 9Rationale on load calculations[Rationale on annual delivered load]
Japan, South Korea and Russia:
Annual delivered load = Annual discharged load x Delivered ratio (1.0)
China:
Annual delivered load = Annual discharged load x {1 – (Load loss rate due to withdrawal
upstream of observation point (e.g. use of surface water for
agriculture)) x Precipitation runoff to rivers[Rationale on seasonal delivered load]
Seasonal delivered load = Annual delivered load x Seasonal rainfall / Annual rainfall
Fig. 10

Rationale on annual delivered ratio and seasonal delivered load8

7,000,000
6,000,000
5,000,000Sea
日本海
of Japan

4,000,000

東シナ海
East
China Sea

3,000,000

黄海 SeaYellow

2,000,000

渤海 SeaBohai

1,000,000
0SpringFig. 11

Summer Autumn

WinterAnnualRationale on seasonal delivered load

Nonpoint load runoff ratio.

Rainfall volume (mm)0.0031x{y = 0.0262e(x = basin annual rainfall volume (mm), y = nonpoint load runoff ratio)}(correlation coefficient R2 = 0.681)
Fig. 12

Relationship between nonpoint source load runoff ratio and rainfall volume

3.2 Result of calculation of pollutant volume using the Land-based Pollution Load Model
Using the calculation method and corrective calculations outlined above, we calculated land-based pollution loads
in Japan, China, South Korea and Russia in the base year (2005) and tabulated the delivered load for each sea area, as
shown in Fig. 13.
Meanwhile, in China, South Korea and Japan, where observation point data on the flow rate and water quality(COD concentrations) of major rivers are published throughout the year, we compared the observed load at
most-downstream observation points (flow rate x water quality (COD)) with the delivered pollutant volume at thesame most-downstream points, as calculated with the Pollution Load Model. Fig. 14 shows the results of thecomparison.
The estimated load ratio, defined as [Load ratio] = [Observed value] / [Estimated value], ranged from around 0.8(0.81) to 1.3 (1.29) for the Chang Jiang River and all rivers in Japan and South Korea. The exception was the Yellow
River, with a load ratio of 0.28. The ratio between observed and estimated values for the Yellow River showed anearly four-fold discrepancy, even after corrective calculations. Although the Chinese calculation results tookaccount of loss rates due to withdrawals from rivers and corrective calculations of nonpoint sources, the specificity ofbasin characteristics are thought to have been the main cause of this.

9

3,000COD
delivered load (t / year)
COD流達負荷量（ｔ/年）

4,500,000
4,000,000
3,500,000
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000

計算負荷量（面源系）
Estimated load (nonpoint)
計算負荷量（人為系）
Estimated load (man-made)実測負荷
Observed load

2,500
COD
load (thousand t / year)
COD負荷量（千ｔ/年間）

Russia
ロシア
Japan
日本
South
韓国
Korea
中国
China

2,000

Load
ratio = Observed load /流達率＝実測値/計算値
Estimated load

1,500
1,000

0.28

500

500,000-

渤海 SeaBohai

黄海 SeaYellow

東シナ海
East
China Sea

0.92

0

日本海
Sea
of Japan

Yellow River

Chang Jiang River

黄河

長江

China
100

T-N流達負荷量（ｔ/年）
T-N
delivered load (t / year)

1,600,000
1,400,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000-

Estimated
load
計算負荷量（面源系）(nonpoint)
Estimated
load
計算負荷量（人為系）(man-made)
実測負荷load
Observed

80
70
60
50
40

1.10

30
20
10
0
Ishikari
River
石狩川

渤海 SeaBohai

黄海 SeaYellow

東シナ海
East
China Sea

日本海
Sea of Japan

90,00080,00070,00060,00050,00040,00030,00020,000140
COD
load (thousand t / year)
COD負荷量（千ｔ/年間）

Russia
ロシア
Japan
日本
South
韓国
Korea
中国
China

100,000

Chikugo
River
筑後川

Japan
160

T-PT-P流達負荷量（ｔ/年）
delivered load (t / year)

1.29

90
CODCOD負荷量（千ｔ/年間）
load (thousand t / year)

Russia
ロシア
Japan
日本
South
韓国
Korea
中国
China

120
100

Estimatedload (nonpoint)
計算負荷量（面源系）
Estimated load
計算負荷量（人為系）(man-made)
実測負荷 load
Observed

1.06
1.23

0.85

80
60
40

1.03

0.81

20

10,000-0
渤海 SeaBohai

黄海 SeaYellow

東シナ海
East
China Sea

Nakdong
洛東江River Seomjin
蟾津江 River Geum
錦江River Yeongsan
栄山江River Hang
漢江River日本海
Seaof JapanSouth Korea(left) Fig. 13
Volumes of pollutant discharge by sea area in the base year (2005)(right) Fig. 14 Ratio between observed and estimated load by river (COD)
3.3 Setting future scenarios taking account of economic growth, etc., and pollutant emission volumes in the
future scenarios
3.3.1 Setting future scenarios taking account of economic growth, etc.
To ascertain the future volume of pollutant discharge in each country, we established future scenarios taking
account of economic growth (increase in pollutant emissions) and development of sewer systems, etc. (reduction ofpollutants), as shown in Table 5.
Taking 2005 as the base year, we set the target year of the future scenarios at 2030. Meanwhile, we adopted thefigures given in World Statistics (Statistics Bureau, Ministry of Internal Affairs and Communications)12) and GDP
figures forecast by the Japan Center for Economic Research 13) as future values of the various frame values (such as
population and gross industrial output). As for China’s population and the GDP of China and South Korea, we
assumed significant increases until 2030.
We also assumed that values for livestock numbers, land use area and other nonpoint sources in future would be
the same as in the base year (2005).

10Future scenarios

Urban areas
Standard Advanced
methodtreatment

Scenario content

Scenario 1

Current status maintained

Scenario 2

If measures for sewers, etc. (standard method) are deployedin urban areas(Coverage by the standard method to be expanded to 100% by
FY2030)(Regulations on factory effluence achieved at the same time)
If measures for sewers, etc. (advanced treatment) are
deployed in urban areas
If measures for sewers, etc., are deployed in urban andrural areas(Wastewater treatment coverage in urban and rural areas to be
expanded to 100% by FY2030)
If measures for sewers, etc. (advanced treatment) are
deployed in urban and rural areas

Scenario 2'
Scenario 3

Scenario 3'-

Rural areas
Standard Advanced
methodtreatment

-

-

-

-

-

-

-

-

-

-

Table 5 Future scenarios taking account of economic growth, etc.
Table 6 expresses the diffusion rates of sewer systems and others in each future scenario in Japan, China, South
Korea and Russia as of 2030. “Advanced treatment” in Table 6 indicates the diffusion of sewer systems and others
capable of advanced treatment. Advanced treatment in rural areas assumes the development of advanced treatment
for farm village effluence in Japan, and the development of combined septic tanks capable of advanced treatment inother countries.
In connection with measures for factory effluence, meanwhile, we assumed a high satisfaction rate of factory
effluence regulations in all countries, with most factories lying within sewer system areas. We therefore thought itpossible to reduce load along with improvements to the sewer system diffusion ratio, and as such, decided not to set a
scenario accompanying progress in measures. We also decided not to take account of the reduction of nonpoint
sources and measures to reduce pollutants in sea areas.
Scenario 1

Scenario 2

Scenario 2'(Advanced treatment)
100%

Scenario 3

Urban areas

63%

100%

Rural areas

0%

0%

0%

100%

Urban areas

81%

100%

(Advanced treatment)
100%

100%

Rural areas

61%

61%

61%

100%

Urban areas

95%

100%

(Advanced treatment)
100%

100%

Rural areas

0%

0%

0%

100%

Urban areas

15%

100%

(Advanced treatment)
100%

100%

Rural areas

15%

15%

15%

100%

China

Japan

South Korea

Russia100%

Scenario 3'(Advanced treatment)
100%(Advanced treatment)
100%(Advanced treatment)
100%(Advanced treatment)
100%(Advanced treatment)
100%(Advanced treatment)
100%(Advanced treatment)
100%(Advanced treatment)
100%

Table 6 Diffusion ratios of sewer systems, etc., in each country and future scenario
3.3.2 Pollutant emission volumes taking account of future scenarios
The volume of pollutant discharge (COD, T-N, T-P) in each country at present and in future scenarios, ascalculated using the Pollution Load Model, is as shown in Fig. 15 through Fig. 18. The calculation results in eachscenario are those of 2030.

11Factories
工場系
下水道
Sewers

3,500

Livestock
畜産系

160

3,000

140

5,000

2,500

120

4,000
3,000
2,000

T-P (thousandt / year)T-P（千t/年）

6,000

T-N (thousandt / year)T-N（千t/年）

CODCOD（千t/年）(thousand t / year)

Domestic–
生活系農村部rural

Domestic–
生活系都市部
urban

自然系
Natural

7,000

2,000
1,500
1,000

100
80
60
40

500

1,000
0

Fig. 150Base year Scenario 1 Scenario
2 Scenario
2' Scenario
3 Scenario3'
現況（2005） シナリオ1
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'(2005)

Base year Scenario
1
シナリオ1(2005)

現況（2005）

Scenario
2 Scenario
2' Scenario
3 Scenario
3'
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'

Pollutant volume (COD, T-N, T-P) in China at present and in each scenario(bar graph: from below, nonpoint sources – livestock)

生活系都市部
Domestic– urban l
Sewers
下水道

自然系
NaturalFactories(except sewers)
工場系（下水道以外）

800

20

0

Base year Scenario 1 Scenario
2 Scenario
2' Scenario
3 Scenario3'
現況（2005） シナリオ1
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'(2005)

生活系農村部
Domestic– rural
畜産系
Livestock

350

700

20
18

300

16

500
400
300
200

250

T-P (thousandt / year)T-P（千t/年）

T-N T-N（千t/年）(thousand t / year)

COD（thousands t/yr）

600

200
150
100

14
12
10
8
6
4

50

100

Scenario
1
シナリオ1

自然系
Natural

900

工場系
Factories

0

Scenario
2 Scenario
2' Scenario
3 Scenario
3'
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'

生活系都市部
Domestic– urban
下水道
Sewers

生活系農村部
Domestic– rural
畜産系
Livestock

700
600
500
400
300

450

40

400

35

350

30

300
250
200
150
100

200

25
20
15
10
5

50

100
0

Base year
現況（2005）(2005)

Scenario 1
シナリオ1

900

0

Scenario 2 Scenario 2' Scenario 3 Scenario 3'
シナリオ2

Fig. 17

シナリオ2'

シナリオ3

Base year(2005)

現況（2005）

シナリオ3'

0

Scenario
1 Scenario
2 Scenario
2' Scenario
3 Scenario
3'
シナリオ1
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'

Base year Scenario
1 Scenario
2 Scenario
2' Scenario
3 Scenario
3'
シナリオ1
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'(2005)

現況（2005）

Pollutant volume (COD, T-N, T-P) in South Korea at present and in each scenario(bar graph: from below, nonpoint sources – livestock)

自然系
NaturalDomestic– urban
生活系都市部

Domestic – rural
生活系農村部

Factories
工場系

Sewers
下水道

Livestock
畜産系

180

T-N (thousand
T-N（百t/年）t / year)

700
600
500
400
300
200

12

200

800

160
140
120
100
80

10
8
6
4

60
40

100
0

Base year Scenario
1 Scenario
2 Scenario
2' Scenario
3 Scenario
3'
シナリオ1
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'(2005)

現況（2005）

Pollutant volume (COD, T-N, T-P) in Japan at present and in each scenario(bar graph: from below, nonpoint sources – livestock)800

COD (thousandt / year)
COD（百t/年）

Base year Scenario
1
シナリオ1(2005)

現況（2005）

T-NT-N（千t/年）(thousand t / year)

CODCOD（千t/年）(thousand t / year)

Fig. 16

1,000

2

0

Scenario 2 Scenario
2' Scenario
3 Scenario3'
シナリオ2'
シナリオ3
シナリオ3'

シナリオ2

T-P (thousand
T-P（千t/年）
t / year)

Base year(2005)

現況（2005）

T-P（百t/年）
T-P(thousand t / year)

0

2

20

Base
year Scenario1
現況（2005）
シナリオ1(2005)

Scenario
2' Scenario3'
シナリオ22 Scenario
シナリオ2'
シナリオ33 Scenario
シナリオ3'

Fig. 18

0

Base
year
現況（2005）(2005)

Scenario
1 Scenario
2 Scenario
2' Scenario
3 Scenario
3'
シナリオ1
シナリオ2
シナリオ2'
シナリオ3
シナリオ3'

0Base year Scenario
現況（2005）
シナリオ11(2005)

Scenario
シナリオ22 Scenario
シナリオ2'2' Scenario
シナリオ33 Scenario
シナリオ3'3'

Pollutant volume (COD, T-N, T-P) in Russia at present and in each scenario(bar graph: from below, nonpoint sources – livestock)

In each country, the introduction of advanced treatment will make it possible to inhibit increases in T-N and T-P. In
China and South Korea, in particular, it will be possible to inhibit increases in T-N, T-P compared to the present
situation, in spite of population increase and economic growth.
Viewing China in isolation, in scenario 3 and 3', it has been suggested that COD discharge can be reduced to12below the present level, and that an increase in the sewerage diffusion ratio will be effective in reducing COD. As for
T-N and T-P, the result was that the discharge volume in scenario 3 would be greater than those of scenario 1 and 2.
The main cause of this is that, while the discharge pollutant volume will increase because not all human waste will becollected due to the diffusion of flush toilets in rural areas (based on the unit load factor used this time), the removal
rate of T-N and T-P in septic tanks will be only 42% and 38%, respectively.
Meanwhile, from the results of Pollution Load Models calculated for individual future scenarios, it was suggested
that an effective measure for reducing load in Japan and South Korea would be to promote advanced sewage
treatment as well as nonpoint source pollutant measures, etc., while in Russia it would be to promote the developmentof wastewater treatment facilities in urban areas, respectively.

4. Method of constructing the Ocean Flow Model and calculation results
4.1 Creation of the “water quality model” and “hydrodynamic model”
As mentioned above, we also constructed a separate Ocean Flow Model to reproduce and predict future changes
in marine pollution on the Northwest Pacific, using the calculated volume of land-based pollution loads. In thisresearch, we have built two different types of Ocean Flow Model, namely a water quality model and a hydrodynamic
model. Based on information gathered in fiscal 2008, we decided to adopt a “low ecosystem model” for the water
quality model, in that it can appropriately express changes in load delivered to sea areas due to economic activity andsewer systems or other social infrastructure in the respective countries. Increased reproduction of phytoplankton due
to photosynthesis is also included in the model.
Fig. 19 shows a conceptual diagram of the low ecosystem model.

Load inflow
Exchange with air

Dissolved oxygen (DO)Respiration

Photosynthesis

Mortality, secretion
Phytoplankton
Respiration,
excretion

Photosynthesis
Inorganic nitrogen(IN)

DO consumption
accompanying
mineralization
Organic nitrogen(PON + DON)
Organic phosphorus(POP + DOP)

Mineralization

溶沈

Inorganic
phosphorus (IP)
Sedimentation

ElutionFig. 19

COD(PCOD+DCOD)
Dispersal (DO consumption
in bottom mud)
Sedimentation

Concept diagram of the water quality model (low ecosystem model)

13

For the hydrodynamic model, we decided to select a model that could take into account the following four
elements, bearing in mind the characteristics and flow mechanisms of the sea areas targeted by this research (Bohai
Sea, Yellow Sea, East China Sea, Sea of Japan).
1 Tidal current (induced by raising and lowering of water level by tides)
2 Density current (induced by density difference between freshwater (low) and seawater (high))
3 Wind-driven current (induced by ocean surface winds)
4 Ocean current (large-scale circulation of seawater, such as the Kuroshio or the Oyashio)
In bay areas such as Japan’s representative Tokyo Bay, Osaka Bay and Ise Bay, tidal current, density current,
wind-driven current and others play an important role in the long-term propagation of water quality. On the other
hand, the sea areas targeted by this research are far greater in spatial scale than these domestic bays. As a result,compared to the role of tidal current, the principal hydrodynamic factors used were ocean current caused by the
Kuroshio, density current caused by the introduction of freshwater from the Chang Jiang River, and wind-driven
current.
From the above, we decided to use the model with coordinates converted vertically, researched and developed by
Mellor, et al. (2002)14) and Ezer and Mellor (2004)15), as a hydrodynamic model that can take into account the effectof density current, wind driven current and ocean current.
While detailed explanation will be omitted here, the grid partitioning arising vertically when coordinates areconverted is similar to that shown in Fig. 20.
The same vertical coordinate conversion model is used in the water quality model mentioned above.
0

Depth(m)

-5

-10

-15

-20
0

5000

10000

15000

20000

Horizontal Distance(m)Fig. 20

Example of vertical grid partitioning in a general vertical coordinate model

Meanwhile, the intervals in the horizontal grid were set at 40km, over the range shown in Fig. 21. In the verticaldirection, theσ (sigma) coordinate system was used, dividing vertically into a total of 20 layers from the sea surface
downwards. (Fig. 23)
The boundary conditions used with the hydrodynamic model were ocean current velocity, water level, salinity andwater temperature. We used the ocean assimilation data supplied by the company Forecast Ocean Plus (FO) 16) asboundary conditions.

14

km

5500

5000

4500

4000

3500

83
83
82
82
81
81
80
80
79
79
78
78
77
77
76
76
75
75
74
74
73
73
72
72
71
71
70
70
69
69
68
68
67
67
66
66
65
65
64
64
63
63
62
62
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6611 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 61
1
2
3
4
5
60
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33
33
32
32
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
311 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 31
1
2
3
4
5
30
30
29
29
28
28
27
27
26
26
25
25
24
24
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8
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6
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4
3
3
2
2
11 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 011 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
1
2
3
4
5

5500

5000

4500

4000

3500

J=21

3000

2500

0

500

1000

3000

2500

Depth(m)02000 km

1500

83
83
82
82
81
81
80
80
79
79
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62
62
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6611 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 61
1
2
3
4
5
60
60
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32
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
311 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 31
1
2
3
4
5
30
30
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2
2
11 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 011 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
1
2
3
4
5

Fig. 21 Horizontal grid partitioning adopted
for the hydrodynamic model

1000

0
-3
-5
-10
-20
-30
-40
-50
-60
-70
-80
-90
-100
-200
-300
-400
-500
-600
-700
-800
-900
-1000
-2000
-3000
-4000
-5000
-6000
-7000

2000

Fig. 22 Water depth data used in the calculations

0

J=21 section
-500

0

-1000

-20

-1500

-2000

depth

depth

-40

-60

-80

-2500
-100

-3000
-120

-3500

400000600000800000

1E+06

horizontal distance-4000
500000

1E+06

horizontal distanceFig. 23

Vertical grid partitioning adopted in the hydrodynamic model (shows position J21 in Fig. 21)

4.2 Hydrodynamic and water quality calculations used in the constructed modelFig. 24 (right) shows the water temperature actually calculated using the constructed hydrodynamic calculation
model. On comparing the monthly average values for 2005 obtained from a satellite (MODIS data obtained from
JAXA) with the average of the calculation results, the characteristics of the calculation results and the satellite data
can be said to resemble each other in general. Again, in the water quality calculations, we compared chlorophyll-awith satellite data (MODIS). Since the satellite data included data such as agitation of colored dissolved organic
matter derived from rivers and bottom mud, their consistency in relation to concentrations of chlorophyll adeteriorates particularly in summer, when rainfall and river flow rates increase. This sometimes made it difficult tomake direct comparisons of concentration with the calculation results. Besides this, however, it could be said that the15

calculation results generally reflected the characteristics of the satellite data (Fig. 25)
Satellite data (MODIS)

Fig. 24

Calculation results

Example of comparison between satellite data and estimated values using the model (watertemperature) (January 2005)

Satellite data (JAXA MODIS)

Fig. 25

Calculation results

Example of comparison between satellite data and estimated values using the model(chlorophyll-a) (January 2005)

16

4.3 Changes in marine pollutant volume in line with the volume of pollutant discharge from land areas basedon future scenarios
When reproducing marine pollution, we added the volume of land-based pollution loads calculated in the previous
section as input values in the horizontal grid near the estuaries of major rivers, or in major urban areas in coastal
regions, and then made calculations for hydrodynamic and water quality models. For future scenarios (for economic
growth and development of sewer systems, etc.), similarly, we made calculations using the 5 future scenarios
explained above.
To evaluate changes in load from land areas, we summarized changes in water quality concentrations at theestuaries of principal rivers in each country. The pickup points for concentration were the nine locations shown in Fig.
26.

5500

83
83
82
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62
611 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 61
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
1
2
3
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5
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311 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 31
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
1
2
3
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5
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1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 01 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6
1
2
3
4
5

Ishikari-Riv.

5000

4500

石狩川
● Depth(m)Yalu Riv.

●黄河

●鴨緑江

Yellow Riv.

4000

●漢江

Nakdong-gang●准河 洛東江●

Shinano-Riv.

●江の川

Gou-no-Riv.

Huai Riv.

3500

●
信濃川

Hang-gang●長江

Chang Riv.

3000

2500

0
Fig. 26

1000
2000
Locations for comparison of concentrations to evaluate scenarios

17

0
-3
-5
-10
-20
-30
-40
-50
-60
-70
-80
-90
-100
-200
-300
-400
-500
-600
-700
-800
-900
-1000
-2000
-3000
-4000
-5000
-6000
-7000

At the points shown in Fig. 26, Fig. 27 shows changes in annual average concentrations in coastal regions used to
calculate each scenario in 2030. In the chart, “-01” indicates the results for the surface layer (the uppermost of the 20
segmented vertical layers) and “-05” those of the 5th layer (of the 20 segmented vertical layers, the 5th from the top)(around 10m deep).

Fig. 27 Changes in concentration in coastal regions used to calculate each scenario in 2030
(annual averages) (COD, T-N, T-P)

18

Figs. 28 to 30 show the distribution of water quality concentrations (COD) in layer 1 (the surface layer) used to
calculate each scenario in 2005 and 2030. When comparing scenario 1 with scenario 2' and scenario 3' in Figs. 28, 29
and 30, for example, we see that the effects of measures in different scenarios are particularly pronounced in the
Bohai Sea area.
Winter
3000

Summer2005-02

3000

COD
0

1

2

3

4

COD

[mg/L]

0

1

2

3

4

[mg/L]

2500

2500

2000

North - South Distance [km]North - South Distance [km]

2000

2005

2005-08

1500

1500

1000

1000

500

500

0

0

0

500

1000

1500

0

500

1000

1500

2000

1500

2000

East - West Distance [km]2000

East - West Distance [km]3000

2030-02

3000

COD
1

2

3

4

COD

[mg/L]

0
2500

2000

2000

1500

1500

2

3

4

[mg/L]

1000

1000

500

500

0

1

North - South Distance [km]2500North - South Distance [km]Scenario 1

02030-08

00

Fig. 28

500

1000
1500
East - West Distance [km]

2000

0

500

1000
East - West Distance [km]Distribution of water quality concentration (layer 1) (2005, 2030 scenario 1, COD)

19

Winter
3000

2030-02

3000

COD
0

1

2

3

4

0

2500

2500

2000

2000

1500

1500

0

500

1000

1500

0

2000

2030-02

3000

COD
1

2

3

4

0

500

1000
1500
East - West Distance [km]

2

3

0
2500

2000

2000

1500

1500

1000

1000

1

4

[mg/L]

North - South Distance [km]

2500

2000

2030-08
COD[mg/L]

North - South Distance [km]Scenario 2’

0

500

500

0

500

1000

1500

0

2000

East - West Distance [km]Fig. 293500

East - West Distance [km]04[mg/L]

2

1000

500

3000

1

North - South Distance [km]

1000

0

2030-08
COD[mg/L]

North - South Distance [km]Scenario 2

Summer

0

500

1000

1500

2000

East - West Distance [km]Distribution of water quality concentration (layer 1) (2030 scenario 2, scenario 2', COD)

20

Winter
3000

2030-02
0

1

3000

2

3

4

0

2500

2500

2000

2000

1500

1500

1000

1000

500

500

0

3000

500

1000
1500
East - West Distance [km]

0

2000

2030-02
0

3000

1

2

3

4

0

4

[mg/L]

2

3

500

1000
1500
East - West Distance [km]

2

3

2000

2000

1500

1500

1000

1000

500

500

0

1

500

1000
1500
East - West Distance [km]4[mg/L]

North - South Distance [km]North - South Distance [km]

2500

2000

2030-08
COD[mg/L]

2500

0

500

1000

1500

0

2000

East - West Distance [km]Fig. 30

1

North - South Distance [km]

0

COD

0

2030-08
COD[mg/L]

North - South Distance [km]Scenario 3

COD

Scenario 3’

Summer0

2000

Distribution of water quality concentration (layer 1) (2030 scenario 3, scenario 3', COD)

21

The Ocean Flow Model calculations involve various analyses besides those given in Fig. 27 through Fig. 30. The
results of study on the Ocean Flow Model are outlined below.
① Coastal parts of China and South Korea where load is particularly large are susceptible to the impact ofpollutant inflow, and a pronounced trend for deterioration in water quality was seen. Meanwhile, in scenarios
involving advanced measures, a tendency was seen for the deterioration of water quality in coastal areas to be
reduced, particularly in the case of COD.
② Because we constructed a model taking account of internal production by phytoplankton in sea areas (lowecosystem model), even when the COD load is reduced as a result of developing sewer systems and othermeasures for conserving the water quality environment, the effects do not appear clearly in sea areas.
Depending on the load balance between nitrogen and phosphorus, internal production became activated, and
COD concentrations rose in sea areas in some cases.
③ Because we took account of internal production in sea areas, a big difference was seen in COD concentrations
between scenarios in spring-summer, when phytoplankton production is lively, while in winter the differencein water quality concentrations between scenarios showed a smaller tendency.
④ Even within the same country, depending on factors such as the state of upstream land use, the level ofurbanization and the state sea areas in which river estuaries are located, the water quality environment and its
mechanism will differ between rivers and estuaries. As a result, even when the pollutant volume is reduced in
the same way, there are different trends in changes of water quality concentrations in estuaries. Consequently,
the status of each river needs to be taken into account when studying water quality conservation measures.
As can be seen from the results of the Ocean Flow Model, this survey has made it clear that cases such as scenario
3', which adopt more advanced water quality conservation measures, inhibit the deterioration in water quality in the
Northwest Pacific more than scenario 1, which maintains current water quality conservation measures.
However, the problem for the Ocean Flow Model, which predicts the impact of increases or decreases in thevolume of land-based pollution loads on the water quality environment of the Northwest Pacific, is that it wasdifficult to gather data on water quality for verification of the target year in calculations to ascertain the current status.

5. Outline of international symposia held over the last three years
In promoting this research, we have confirmed the relevance of our methods of constructing the Land-based
Pollution Load Model and the Ocean Flow Model through regular exchanges of views with researchers from Japan,
China, South Korea and Russia on the details of the methods, etc. At the same time, we have also taken theopportunity to gather information such as pollutant emissions in other countries, amend our model calculation
method based on the views of overseas academics, and so on.
The principal researchers and others from Japan, China and South Korea involved in this research are, specifically,
Professor Tetsuya Kusuda of Graduate school, The University of Kitakyushu (Japan), former Senior Researcher Kim
Kap-Soo of the Seoul Development Institute (South Korea), Associate Professor Du Pengfei of Tsinghua University(China), Professor Li Guangming of Tongji University (China), and Dr Vladimir Shulkin, Head of the Geochemical
Laboratory in the Pacific Geographical Institute (Russia).
Once a year in each of fiscal 2008, fiscal 2009 and fiscal 2010, we invited these researchers and others to Japan for
an international conference, when we discussed each country’s measures against land-based pollution loads, etc., andexchanged views. At these international conferences, we also received numerous useful comments on our methods ofproceeding with this research.
In fiscal 2008, we held an international conference in the Clock Tower Centennial Hall of Kyoto University,
which jointly hosted the event. This first conference was attended by about 120 people. In fiscal 2009, the venue forthe conference was moved to the Shiba Park Hotel in Tokyo. And in fiscal 2010, the final conference was held in theTokyo Bay Ariake Washington Hotel.
Fig. 31 and Fig. 32 show scenes from the most recent conference held in the Tokyo Bay Ariake Washington Hotelon February 9th, 2011.
At the conference venue on February 9th, 2011, we presented an outline of our survey results over the three yearsof our research to the assembled academics. Specifically, we explained the method of constructing a model ofpollutant emissions from land areas in the countries concerned and the calculation results, the method of constructing
ocean flow simulation and the calculation results, and others from the Japanese perspective. At the conference venue,

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we pointed out to the overseas academics that our survey methods and calculation results had been amended since theprevious fiscal year, and received comments that, within the range of data obtained in the survey, they wereappropriate analytical methods and calculation results.

Fig. 31

Fig. 32

Scene from the “International Conference: Research on the Conservation of the Northwest
Pacific Marine Environment” on Feb. 9th, 2011

Participants in the “International Conference: Research on the Conservation of the Northwest
Pacific Marine Environment” on Feb. 9th, 2011

6. Outline of research partnership between the countries concerned
In this research, we used the Land-based Pollution Load Model and the Ocean Flow Model to predict the volume
and behavior of pollutants flowing into the Northwest Pacific, and obtained the required outcome. However,something that was always a problem when conducting surveys was gathering and ensuring the reliability ofmonitoring data on the quality and flow of water, essential elements for analysis.
Each country has different methods of gathering monitoring and other data on water quality, and different times
for doing so. This made it very difficult to use data uniformly for analysis in the four countries of Japan, China, South
Korea and Russia.

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To promote the conservation of marine environments in the Northwest Pacific using the methods developed in thisresearch, it will of course be important for the four countries of Japan, China, South Korea and Russia to continuously
gather monitoring data on water flow and water quality, but also for each of the four countries to share their respective
monitoring data. This has also been pointed out by the overseas academics attending our international conferences.
Based on this problem awareness, at the international conference held on Feb. 9th, 2011, we discussed the idea ofcontinuously sharing water quality monitoring data on the Northwest Pacific possessed by each country, as a concrete
plan of action for a research partnership aimed at the conservation of marine environments in the Northwest Pacificbetween fellow researchers in Japan, China, South Korea and Russia. We gained the approval of the invitedacademics of this principle, leading to the signing of the agreement shown in Fig. 35 (Fig. 33, Fig. 34).
The text set out in the agreement is as follows.

RESEARCH PARTNERSHIPONCONSERVATION OF THE NORTHWEST PACIFIC MARINE ENVIRONMENTTokyo, 9th February, 2011
So far, we have held an international symposium in 2009 and international workshops in 2010 and 2011, and haveworked to accumulate knowledge on the conservation of marine environments in the Northwest Pacific.
As a result of this research, we shared analytical tools for conserving marine environments in the Northwest
Pacific by implementing the Ocean Flow Model based on estimation of land-based pollution loads from each country
and future predictions. Furthermore, we have clarified the effects of measures to reduce pollutants in different futurescenarios by utilizing these tools.
In future, for the conservation of marine environments in the Northwest Pacific, we will continuously carry out
survey research, while continuing exchanges of information on water quality data in the Northwest Pacific, etc., until
the end of March 2014.
(China) Li Guangming, Tongji University(China) Du Pengfei, Tsinghua University(South Korea) Kim Kap-Soo, Seoul Development Institute(Russia) Vladimir Shulkin, Geochemical Laboratory in the Pacific Geographical Institute(Japan) Tetsuya Kusuda, Graduate school, The University of Kitakyushu(Japan) Takashi Sakakaibara, National Institute for Land and Infrastructure Management (NILIM), Ministry of Land,
Infrastructure, Transport and Tourism

Fig. 33 Signing the Agreement Document

Fig. 34 Signing the Agreement Document24

Fig. 35

Copy of the Agreement on Research Partnerships without signatures25

7. Summary
As has already been stated up to the previous section, to study methods of conserving marine environments in the
Northwest Pacific, we have attempted to ascertain pollutant emissions from land areas in Japan, China, South Korea
and Russia, predict their future increases or decreases, and predict the behavior of pollutants at sea in the Northwest
Pacific. For land-based pollution simulation, we constructed a calculation model based on the rationale used inJapan’s Comprehensive Basin-wide Planning of Sewerage Systems (CBPSS)9), and made calculations while using
the data gathered. Meanwhile, we investigated various reference materials and others concerning future predictionsof GDP, etc., set scenarios for economic growth (pollutant increase) and development of sewer systems, etc.
(reduction of pollutants), and attempted to ascertain future increases or decreases in pollutants by the year 2030. In
the Northwest Pacific Ocean Flow Model, moreover, we specifically constructed a hydrodynamic model and a water
quality model (low ecosystem model), and attempted to predict the behavior of pollutants at sea based on thecalculation results of the Land-based Pollution Load Model.
As a result, we demonstrated that, if each country were to take appropriate steps such as developing sewer systems,
a reduction in pollutants could be expected in the Northwest Pacific, particularly in the Bohai Sea and other enclosed
sea areas or the coastal regions of each country. Meanwhile, in a prediction of water quality in the Northwest Pacificusing the Ocean Flow Model, we found that deterioration in water quality can be inhibited by reducing pollutants.
Again, researchers from Japan, China, South Korea and Russia shared the perception that it is important toenhance water quality monitoring data on major rivers and the Northwest Pacific Ocean possessed by each country,
and for each country to share those data, with a view to ascertaining the improvement of marine environments in the
Northwest Pacific Ocean and promoting pollutant emission countermeasures.
In response to this problem awareness, in an international conference held with invited researchers from Japan,
China, South Korea and Russia on Feb. 9th, 2011, we prepared an agreement stating that “In future, we willcontinuously carry out survey research on the Northwest Pacific, while continuing exchanges of information on water
quality data, etc., between our four countries.” (Fig. 32, Fig. 33, Fig. 34).
In future, we aim to enhance information and others related to water quality monitoring data and the pollutant unitload in each country by holding exchanges of information with the other countries. We will actively provide theobtained data to research institutes and others that need them. By enhancing water quality monitoring data, etc., itshould become possible to identify issues related to conserving marine environments in the Northwest Pacific, and toprepare draft environmental conservation measures in greater detail than in the study undertaken in this research.
Based on the survey results accumulated in this research and the research partnerships forged between Japan,
China, South Korea and Russia, we intend to continue lobbying from Japan through frameworks such as JICA and the
Global Centre for Urban Sanitation (GCUS) , so that measures to reduce pollutants may be steadily implemented bycountries in the Northwest Pacific.

Acknowledgement
In conducting this research, we were fortunate to receive assistance from a large number of sources, not only inJapan but also in China, South Korea and Russia. In particular, Professor Tetsuya Kusuda of Graduate school, The
University of Kitakyushu, Professor Li Guangming of Tongji University, Associate Professor Du Pengfei of Tsinghua
University, former Senior Researcher Kim Kap-Soo of the Seoul Development Institute, and Dr Vladimir Shulkin,
Head of the Geochemical Laboratory in the Pacific Geographical Institute (Russia), took part in our international
workshops over three years from 2008 and provided tremendous assistance. We also received many useful opinionsfrom members of the “Review Subcommittee for Promoting Joint Research by Japan, China, South Korea and Russia
on Environmental Problems of the Northwest Pacific”, set up within the Committee of Environmental Engineering of
the Japan Society of Civil Engineers. Besides the parties cited above, we have received information in the form ofhearings, etc., from many academics both within Japan and overseas. We would like to express our gratitude to all ofthese parties, as well as the relevant personnel in Nippon Jogesuido Sekkei Co., Ltd. and IDEA Consultants , Inc.,
who shared in implementing this research.

Reference materials, etc.
1) National Bureau of Statistics, People’s Republic of China: China Statistical Yearbook 1996-2007
2) Ministry of Environmental Protection, PRC: Automatic monitoring data on water quality in China’s principal river
basins, 2005
3) Ministry of Land, Infrastructure, Transport and Tourism, Kanto Regional Development Bureau: Comprehensive

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Basin-wide Planning of Sewerage Systems in Tokyo Bay, Sept. 2007
4) Ministry of the Environment: Total emission reduction policy concerning chemical oxygen demand, nitrogencontent and phosphorus Nov. 2006
5) Chinese Environmental Yearbook 1997-2006
6) South Korea Statistical Yearbook 1996-2005
7) Public water area water quality survey results 1990-2006
8) MODIS data http://www.eorc.jaxa.jp/hatoyama/satellite/sendata/modis_j.html
9) Japan Sewerage Works Association: Survey Guidelines and Explanation of the Comprehensive Basin-wide
Planning of Sewerage Systems, September 2008
10) JICA: Water Environment Restoration Pilot Project in Taihu Lake, People’s Republic of China – Final Report
June 1998
11) South Korean National Institute of Environmental Research: Total Drainage System Pollution Management
Technology Guidelines Nov. 2002
12) Statistics Bureau, Ministry of Internal Affairs and Communications: World Statistics, March 200913) Japan Center for Economic Research: Long-term economic forecast, website:
http://www.jcer.or.jp/research/long/detail3532.html
14) Mellor, G. L., S. Hakkinen, T. Ezer and R. Patchen (2002): A generalization of a sigma coordinate ocean modeland an intercomparison of model vertical grids, In: Ocean Forecasting: Conceptual Basis and Applications, N.
Pinardi and J. D. Woods (Eds.), Springer, Berlin, 55-72.
15) Ezer, T. and G. L. Mellor(2004): A generalized coordinate ocean model and a comparison of the bottom boundary
layer dynamics in terrain-following and in z-level grids, Ocean Modelling, 6, 379-403
16) Forecast Ocean Plus http://www.forecastocean.com/e/index.html

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