1
Introduction
1.1
The pollution loading inventory will be compiled for
the storm and sewage outfalls within the whole Hong Kong
waters for input into the Update Model and the detailed SEK Model for 2013 for
cumulative impact assessment. The
methodologies for compiling the pollution loading are given in this Appendix.
2
Storm Outfalls
2.1
The key sources of water pollution
in storm outfalls include:
l
Pollution
due to sewage from unsewered developments (dry weather load)
l
Pollution
due to expedient connections from trade and residential premises, and integrity
problems of aged drainage and sewerage systems (dry weather load)
l
Pollution
due to livestock waste (dry weather load)
l
Rainfall
related load.
2.2
The total pollution load discharged
via the storm system would cover the dry weather load and rainfall related load
Dry Weather Load
2.3
Domestic, commercial and
industrial activities are the principle sources of dry weather load in storm drains. Total pollution loads generated
from these activities were compiled by catchment areas as shown in Figure A5-3-1
below with reference to the projected population and employment data provided
by the Planning Department (PlanD). Details of these planning data and the
methodology for calculating the pollution loads from domestic commercial and
industrial activities are given in Section 4 of this Appendix.
2.4
It is assumed that a portion of
total pollution load generated within a catchment would be lost to the storm
system whilst the rest of the flow would be diverted to the sewerage
system. The assumed percentages of
pollution load discharged into the storm system for different catchments are
presented in Table A5-3-1.
Figure A5-3-1 Sewage Catchment
Boundaries
Table A5-3-1 Assumed % of Pollution Load in
the Storm System for 2013
|
Catchment
|
Catchment ID
|
Assumed % of Load Lost to Stom
|
Foul interception to
|
|
Sai Kung
|
1
|
10%
|
Sai Kung STW
|
|
Sai Kung
Country Park
|
1a
|
50%
|
|
Pak Sha Wan
|
1b
|
10%
|
|
Clear Water
Bay
|
1c
|
100%
|
-
|
|
Tseung Kwan O
|
2
|
5%
|
HATS
|
|
Yau Tong, East Kowloon
|
4
|
10%
|
|
North Kowloon, Central
Kowloon, South Kowloon
|
5
|
10%
|
|
Northwest
Kowloon
|
8
|
10%
|
|
Stonecutters
|
9a
|
10%
|
|
Kwai Chung and Tsuen Wan
East
|
10a
|
10%
|
|
Tsing Yi
|
10b
|
10%
|
|
Tsuen Wan West (Rural
Area)
|
11
|
10%
|
Sham Tseng STW
|
|
Tuen Mun
|
12
|
10%
|
Pillar Point STW
|
|
Yuen Long and Tin Shui
Wai and Deep Bay Streams
|
12a
|
10%
|
San Wan STW
|
|
Kam Tin and Yuen Long
New Town
|
12d
|
10%
|
Yuen Long STW
|
|
Discovery Bay
|
13
|
0%
|
Siu Ho Wan STW
|
|
North
Lantau
|
13a
|
10%
|
|
Chek Lap Kok
|
13b
|
0%
|
|
Peng Chau
|
14
|
30%
|
Peng Chau STW
|
|
Mui Wo
|
15
|
10%
|
Mui Wo STW
|
|
South
Lantau
|
15a
|
100%
|
-
|
|
Hei Ling Chau
|
16
|
0%
|
Hei Ling Chau STW
|
|
Cheung Chau
|
17
|
30%
|
Cheung Chau STW
|
|
Shek Kwu Chau
|
17a
|
100%
|
-
|
|
Tai A Chau
|
17b
|
0%
|
Tai A Chau PTW
|
|
Shek Pik
|
18
|
10%
|
Shek Pik STW
|
|
Tai O
|
18a
|
10%
|
Tai O STW
|
|
Lamma Island
|
19
|
30%
|
Yung Shue Wan STW and Sok Kwu Wan STW
|
|
Poi Toi
Islands
|
19a
|
100%
|
-
|
|
Tung Lung
|
19b
|
100%
|
-
|
|
Pokfulam Sandy
Bay
|
20a
|
10%
|
Sandy Bay PTW
|
|
Cyber Port
|
20b
|
10%
|
Cyber Port STW
|
|
Wah Fu Estates and Mt. Kellet
|
21
|
10%
|
Wah Fu PTW
|
|
Aberdeen, Shouson Hill and Repulse Bay,
South Bay
|
22
|
10%
|
Aberdeen PTW
|
|
Ap Lei Chau
|
23
|
10%
|
Ap Lei Chau PTW
|
|
Chung Hom Kok
|
26
|
10%
|
Stanley STW
|
|
Stanley
|
27
|
10%
|
|
Tai Lam
|
28
|
10%
|
|
Shek O
|
29
|
10%
|
Shek O STW
|
|
Chai Wan
|
30
|
10%
|
HATS
|
|
Shau Kei Wan
|
31
|
10%
|
|
North Point
|
32
|
10%
|
North Point PTW
|
|
Wan Chai East
|
33
|
10%
|
Wan Chai East PTW
|
|
Wan Chai West
|
34
|
10%
|
|
Western and Central, Green Island
|
35
|
10%
|
Central PTW
|
|
Tolo Harbour
|
37
|
10%
|
THEES
|
|
Sheung Shui and Fanling
|
38
|
10%
|
Shek Wo Hui STW
|
|
North New Territories
|
39
|
95%
|
|
Sha Tau Kok
|
40
|
10%
|
Sha Tau Kok STW
|
2.5
The percentage interceptions
assumed in Table A5-3-1 were based
on the implementation schedule for sewerage improvement projects as adopted
under the EPD Update (CE42/97) and the HATS EEFS (CE42/2001).
2.6
The pollution loading in the
storm system contributed from domestic, commercial and industrial activities is
compiled to the catchment levels shown in Figure
A5-3-1. The pollution loading compiled for each catchment is distributed to
appropriate discharge points (i.e. storm culverts / outfalls, rivers and
nullahs). It is assumed that these
storm pollutions would be evenly distributed amongst the major storm water
discharge points within the catchment.
2.7
The livestock waste load
discharged via rivers / streams adopted under the EPD Update Study (CE42/97) as
shown in Table A5-3-2 is directly
applied in this EIA for 2013.
Table A5-3-2 Livestock Waste Load
Assumed for 2013
|
Catchment
|
River Name
|
Flow (m3/d)
|
SS (kg/d)
|
TKN (kg/d)
|
NH3-N
(kg/d)
|
TP (kg/d)
|
E.coli (counts/d)
|
|
Tsueng Kwan O
|
Tseng Lan Shue River
|
2
|
0
|
0
|
0
|
0
|
6.98E+11
|
|
Sheung Shui and Fanling
|
Shenzhen River
|
3216
|
363
|
41
|
22
|
18
|
9.28E+14
|
|
Yuen Long, Tin Shui Wai and Kam Tin
|
Shan Pui Ho River
|
5034
|
568
|
65
|
34
|
28
|
1.45E+15
|
|
Tin Shui Wai Nullah
|
4190
|
473
|
54
|
28
|
24
|
1.21E+15
|
|
Deep Bay
|
Sheung Pak Nai Stream
|
97
|
11
|
1
|
1
|
1
|
2.79E+13
|
|
Ha Pak Nai Stream
|
677
|
76
|
9
|
5
|
4
|
1.95E+14
|
2.8
The total dry weather load in
the storm outfall would include the loading contributed from domestic,
commercial and industrial activities and the loading from livestock discharges
(if any) as shown in Table A5-3-2.
Rainfall Related Load
2.9
It is assumed that a rainfall
volume of greater than 10mm per day (and rainfall intensity greater than
2mm/hr) would give rise to runoff.
The runoff percentage was based on the average rainfall data between
1/01/74 and 31/10/05 from the Hong Kong Observatory. The calculation of the runoff percentage
is shown below:
Runoff percentage = (Sum of the rainfall volume for the days
with rainfall volume > 10mm and intensity > 2mm/hr within the season) ¸ Total rainfall volume for the
season x 100%
2.10
Rainfall data from May to
September represent the values for wet season, and those from November to March
represent the values for dry season. Accordingly, the runoff percentage was
calculated as 93% and 70% for wet and dry seasons respectively
2.11
The 30-year long term average
rainfall data were used to determine the daily runoff value as shown below:
Daily runoff value
(m/day) = 30year long term average daily rainfall data x runoff percentage
2.12
Thus, the runoff value was
calculated as 0.01104 m/day and 0.00102 m/day for wet and dry seasons
respectively.
2.13
The amount of rainfall related
load that would be discharged into the sea depends on the amount of impermeable
area within each catchment. It is assumed
that all urbanized/developed areas within the catchment would be
impermeable. The daily volume of
runoff generated within each catchment was estimated as shown below:
Daily volume of runoff in each catchment (m3/day)
= daily runoff value
(m/day) x impermeable area within each catchment (m2)
2.14
The daily volume of runoff
estimated for each catchment is multiplied with the runoff concentrations to
derive the rainfall related loading.
The assumed runoff concentrations are shown in Table A5-3-3.
Table A5-3-3 Event Mean
Concentrations for Stormwater Runoff
|
TSS
(g/m3)
|
BOD5
(g/m3)
|
NH3N
(g/m3)
|
Cu
(g/m3)
|
TP (g/m3)
|
OrthoP (g/m3)
|
Silicate (g/m3)
|
TON
(g/m3)
|
TKN
(g/m3)
|
|
43.25
|
22.48
|
0.20
|
0.01
|
0.20
|
0.04
|
3.28
|
0.40
|
1.40
|
(Source: EPD Pilot Study of Stormwater Pollution)
2.15
The rainfall related loading is
compiled to the catchment levels shown in Figure
A5-3-1. The pollution loading compiled for each catchment is distributed to
appropriate discharge points (i.e. culverts, outfalls, rivers and
nullahs). It is assumed that the
rainfall related loading is evenly distributed amongst the major storm water
discharge points within the catchment.
3
Sewage Outfalls
3.1
A portion of the total loads
from domestic, commercial and industrial activities generated in each catchment
is allocated to the sewerage system according to the percentage of storm
interception shown in Table A5-3-1. The remaining portion of the total
load in each catchment is distributed to the storm system.
3.2
Besides the pollution loads
from domestic, commercial and industrial activities, the sewerage system would
also receive pollution loads from landfills and beaches as most of the landfill
sites and beach facilities would be connected to the sewerage system. Table
A5-3-4 and Table A5-3-5 show the pollution load of relevant
landfills and beaches adopted under the EPD Update Study. These loading data are
directly adopted in this EIA for 2013. The beach loading is included for the
wet season simulations only. Loading
from landfills and beaches that would not be connected to the STW is given in
Section 5 of this Appendix. It is
considered that the effect of this point source pollution loading would be
localized. Contributions of these
point source pollution loads would be insignificant as compared to the overall
pollution loading that would be discharged into the sea. Possible change of these point source
loads would unlikely affect the overall modelling results. Thus, the broad
assumption of using the same amount of point source pollution loads for all the
assessment years is considered acceptable.
Table A5-3-4 Pollution Flows and
Loads from Landfills
|
|
Discharge
Location
|
Flow (m3/d)
|
BOD
(kg/d)
|
SS
(kg/d)
|
Org-N (kg/d)
|
NH3-N
(kg/d)
|
E-Coli (no./d)
|
Cu
(g/d)
|
|
Shuen Wan Landfill
|
|
Shuen Wan Landfill
|
Foul sewer to Tai Po STW
|
110
|
8
|
28
|
13
|
76
|
7.65E+05
|
2
|
|
NEW Strategic Landfills
|
|
WENT
|
Foul sewer to NWNT sewage outfall
|
714
|
2648
|
288
|
190
|
1690
|
4.97E+06
|
14
|
|
SENT
|
Foul sewer to HATS
|
523
|
30
|
131
|
26
|
1
|
3.64E+06
|
10
|
|
NENT
|
Foul sewer to Shek Wu Hui STW
|
541
|
11
|
53
|
22
|
1
|
3.76E+06
|
11
|
|
NWNT Landfills
|
|
Pillar Point
Valley
|
Foul sewer to Pillar Point STW
|
3283
|
3165
|
822
|
389
|
2511
|
2.28E+07
|
66
|
|
Ngau Tam Mei
|
Foul sewer to HATS
|
200
|
193
|
50
|
24
|
153
|
1.39E+06
|
4
|
|
Siu Lang Shui
|
|
Gin Drinkers
Bay
|
|
Ma Tso Lung
|
|
Urban Landfills
|
|
Jordan Valley
|
Foul sewer to HATS
|
638
|
615
|
160
|
76
|
488
|
4.44E+06
|
13
|
|
Ma Yau Tong Central
|
|
Sai Tso Wan
|
|
Ma Yau Tong West
|
|
Ngau Chi Wan
|
|
TKO Landfills
|
|
TKO I
|
Foul sewer to HATS
|
69
|
66
|
32
|
8
|
52
|
4.77E+05
|
1
|
Table A5-3-5
Pollution Loads from Beach Users in Bathing Season
|
Gazetted Beach
|
Discharge Location
|
Flow
(m3/day)
|
BOD
(g/day)
|
SS
(g/day)
|
Org-N
(g/day)
|
NH3-N
(g/day)
|
E.coli.
(no./day)
|
TP
(g/day)
|
OrthoP
(g/day)
|
|
Big Wave Bay
|
Shek O STW
|
3
|
788
|
657
|
432
|
985
|
1.04E+13
|
224
|
133
|
|
Hairpin
|
1
|
334
|
278
|
183
|
417
|
4.41E+12
|
95
|
57
|
|
Shek
O
|
20
|
4895
|
4079
|
2685
|
6118
|
6.46E+13
|
1393
|
829
|
|
Deep Water Bay
|
Aberdeen STW
|
22
|
5436
|
4530
|
2982
|
6795
|
7.17E+13
|
1547
|
921
|
|
Middle Bay
|
3
|
667
|
556
|
366
|
833
|
8.80E+12
|
190
|
113
|
|
Repulse Bay
|
44
|
10968
|
9140
|
6017
|
13710
|
1.45E+14
|
3121
|
1858
|
|
South Bay
|
2
|
584
|
487
|
321
|
730
|
7.71E+12
|
166
|
99
|
|
Chung
Hom Kok
|
Stanley STW
|
1
|
225
|
187
|
123
|
281
|
2.96E+12
|
64
|
38
|
|
St.
Stephen’s
|
4
|
875
|
729
|
480
|
1094
|
1.15E+13
|
249
|
148
|
|
Stanley Main
|
6
|
1504
|
1254
|
825
|
1880
|
1.98E+13
|
428
|
255
|
|
Turtle
Cove
|
1
|
268
|
223
|
147
|
334
|
3.53E+12
|
76
|
45
|
|
Silvermine Bay
|
Mui Wo STW
|
0
|
112
|
93
|
61
|
140
|
1.47E+12
|
32
|
19
|
|
Hung
Shing Yeh
|
Yung
Shue Wan STW
|
1
|
308
|
256
|
169
|
384
|
4.06E+12
|
88
|
52
|
|
Lo
So Shing
|
0
|
68
|
57
|
37
|
85
|
8.99E+11
|
19
|
12
|
|
Kwun
Yau Wan
|
Cheung
Chau STW
|
0
|
94
|
78
|
52
|
117
|
1.24E+12
|
27
|
16
|
|
Tung
Wan, Cheung Chau
|
4
|
1089
|
908
|
598
|
1362
|
1.44E+13
|
310
|
185
|
|
Silverstrand
|
Sai
Kung STW
|
18
|
4556
|
3797
|
2500
|
5695
|
6.01E+13
|
1297
|
772
|
|
Trio
(Hebe Haven)
|
3
|
632
|
527
|
347
|
790
|
8.34E+12
|
180
|
107
|
|
Anglers’
|
Sham Tseng STW
|
0
|
87
|
73
|
48
|
109
|
1.15E+12
|
25
|
15
|
|
Approach
|
Sham Tseng STW
|
0
|
77
|
64
|
42
|
96
|
1.02E+12
|
22
|
13
|
|
Casam
|
Sham Tseng STW
|
0
|
63
|
53
|
35
|
79
|
8.36E+11
|
18
|
11
|
|
Gemini
|
Sham Tseng STW
|
0
|
41
|
34
|
23
|
52
|
5.44E+11
|
12
|
7
|
|
Hoi Mei Wan
|
Sham Tseng STW
|
0
|
85
|
71
|
47
|
107
|
1.13E+12
|
24
|
14
|
|
Lido
|
Sham Tseng STW
|
3
|
662
|
552
|
363
|
828
|
8.74E+12
|
188
|
112
|
|
Ting Kau
|
Sham Tseng STW
|
0
|
26
|
22
|
14
|
32
|
3.42E+11
|
7
|
4
|
|
Butterfly
|
Pillar Point STW
|
17
|
4248
|
3540
|
2331
|
5310
|
5.61E+13
|
1209
|
720
|
|
Castle Peak
|
2
|
605
|
504
|
332
|
756
|
7.98E+12
|
172
|
102
|
|
Kadoorie
|
22
|
5561
|
4634
|
3051
|
6951
|
7.34E+13
|
1582
|
942
|
|
New Cafeteria
|
8
|
2045
|
1704
|
1122
|
2556
|
2.70E+13
|
582
|
346
|
|
Old Cafeteria
|
3
|
732
|
610
|
401
|
915
|
9.65E+12
|
208
|
124
|
|
Golden Beach
|
22
|
5505
|
4587
|
3020
|
6881
|
7.26E+13
|
1566
|
932
|
3.3
The total load generated in the
sewerage system would be reduced after the treatment processes. Table A5-3-6
shows the treatment processes for major STW. HATS loading is calculated separately as
mentioned in the main text of this Working Paper. The treatment efficiencies
for different treatment processes are given in Table A5-3-7 for
reference.
Table A5-3-6 Summary of Major Sewage
Treatment Works and the Corresponding Treatment Levels
|
STW
|
Treatment Level
|
|
2013
|
|
Stanley
|
|
|
Shek O
|
Preliminary treatment
|
|
Tai O
|
Primary treatment
|
|
Cheung Chau
|
Primary treatment
|
|
Mui Wo
|
Secondary treatment with disinfection
|
|
Peng Chau
|
Secondary treatment with disinfection
|
|
Shek Wu Hui
|
Secondary treatment with disinfection
|
|
Sha Tau Kok
|
Secondary treatment with disinfection
|
|
Sai Kung
|
Secondary treatment with disinfection
|
|
Yung Shue Wan
|
Secondary treatment with disinfection
|
|
Sok Kwu Wan
|
Secondary treatment with disinfection
|
|
Hei Ling Chau
|
Secondary treatment with disinfection
|
|
Shek Pik
|
Secondary treatment with disinfection
|
|
Cyber Port
|
Chemically enhanced primary treatment
|
|
Pillar Point
|
Chemically enhanced primary treatment with disinfection
|
|
Siu Ho Wan
|
Chemically enhanced primary treatment with disinfection
|
|
THEES
|
Secondary treatment with disinfection
|
|
San Wan
|
Chemically enhanced primary treatment with disinfection
|
|
Sham Tseng
|
Chemically enhanced primary treatment with disinfection
|
Table A5-3-7 Treatment Efficiency for Treatment Works
|
Types of Treatment Plant
|
BOD5
|
TSS
|
NH3-N
|
Org-N
|
OrthoP
|
TP
|
Cu
|
E.coli
|
|
Screening PlantsA
|
0%
|
0%
|
0%
|
0%
|
0%
|
0%
|
0%
|
0%
|
|
Primary Treatment (no
disinfection)
|
32.5%
|
55%
|
0%
|
15%
|
0%
|
15%
|
26%
|
50%
|
|
Primary Treatment (with
disinfection)
|
32.5%
|
55%
|
0%
|
15%
|
0%
|
15%
|
26%
|
99.95%
|
|
Chemical Enhanced
Primary Treatment (with no disinfection)B
|
55%
|
70%
|
10%
|
45%C
|
60%
|
60%
|
80%
|
50%
|
|
Chemical Enhanced
Primary Treatment (with disinfection)B
|
55%
|
70%
|
10%
|
45%C
|
60%
|
60%
|
80%
|
99.95%
|
|
Secondary Treatment (no
disinfection)
|
85%
|
90%
|
75%
|
80%
|
35%
|
50%
|
74%
|
94%
|
|
Secondary Treatment
(with disinfection)
|
85%
|
90%
|
75%
|
80%
|
35%
|
50%
|
74%
|
99.97%
|
Note
A. It is assumed that the reduction of
the pollution parameters is insignificant in screening plants. Therefore, the
removal rates for these parameters are all assumed zero.
B.
Based on estimation from the
SSDS EIA Study: Technical Note 1 (Revised) Wastewater Flows and Loads and
Effluent Characteristics.
C. The
removal rate of org-N is calculated from the removal rates of NH3-N
and total N (10% and 25% respectively) assuming that NH3-N
contributes about 57% of total N in raw sewage.
Population
and Employment Statistics
Time Aspect
4.1
The 2003-based Territorial
Population and Employment Data Matrices (TPEDM), which are the latest planning
information released by PlanD at the time when this assessment is conducted, are
used to compile the pollution loads from domestic, commercial and industrial
activities. The TPEDM provides the
projected population breakdown by Planning Vision and Strategy (PVS) zones for
2006, 2011 and 2016. For strategic planning purposes, two different scenarios
of growth rate are postulated for future population (2011 and 2016) under the
2003-based TPEPM. Scenario I assumed
a total population of 7.57 million by 2016. Scenario II assumed a total population
of 7.94 million by 2016, which represents about 5% increase in population on
top of Scenario I. The population
and employment projections for 2006 are only available for Scenario I.
4.2
Territorial population
projections given by the Census & Statistics Department (C&SD) are used
as the control totals for the TPEDM Scenario I. The TPEDM Scenario II was compiled for
long-term planning purposes with no given territorial population as the control
totals and is used in this EIA for conservative assessment.
4.3
The projected population data
provided by PlanD at PVS zones are also available for 2011 and 2016. Linear interpolation will be used to
determine the population for 2013 based on the TPEDM Scenario II for 2011 and
2016.
Spatial Aspect
4.4
To facilitate the estimation of
pollution loading, the population and employment data are required to be
presented at the level of catchment areas shown in Figure A5-3-1 of this Appendix. However, the
projected population from PlanD is provided in a much smaller scale at PVS
zones. Population and
employment data for each sewage catchment area are estimated by overlaying the
PVS zones on top of the layout of the sewage catchment area for allocating the
appropriate PVS zones to the sewage catchment area.
Data Manipulation
4.5
The TPEDM provides the number
of usual residents, mobile residents and school places within the territory at
PVS zones.
4.6
Employment population is
divided by 12 job types under the TPEDM as listed below:
l
J1 Manufacture
l
J2 Electricity, gas & water
l
J3 Transport, storage &
communication
l
J4 Wholesale and retail
l
J5 Import & export
l
J6 Financial, insurance, real estate
& business services
l
J7 Agriculture & fishery
l
J8 Mining & quarrying
l
J9 Construction
l
J10 Restaurants, hotels & boarding houses
l
J11 Community, social & personal services
l
J12 Public administration
4.7
The population data from the
TPEDM are manipulated and presented at the following categories:
l
Residential
population (by usual residents and mobile residents)
l
Transient
Population (by total employment number and total school places), where total
employment =J1+J2+J3+J4+J5+J6+J7+J8+J9+J10+J11+J12
l
Number of
employees in commercial sector (by J2, J3, J4, J9, J10 & J11)
l
Number of
employees in manufacturing sector (=J1) by 6 sub-categories, namely food,
textiles, leather, paper, manufacturing and machinery respectively.
4.8
The domestic pollution load to
be generated from a catchment would be affected by the number of resident
population and transient population within the catchment. The total employee number comprises 12
job types listed above. It is considered that commercial effluents are
contributed from job J2 to J4 and J9 to J11. Industrial effluents are
contributed from job type J1.
4.9
In order to provide a better
estimation of pollution loads from industrial processes, the number of
employees in manufacturing sector (J1) was further broken down into 6
sub-categories, namely food, textiles, leather, paper, manufacturing and
machinery. Projected employment
statistics are not available for these 6 sub-categories. It is noted that the size for each of
these 6 sub-categories is estimated under the EPD Update Study. To estimate the
size of these 6 sub-categories for this EIA, it is assumed that the share of
each sub-category in the manufacturing sector provided in the Update Study would be the same
as that for 2013.
4.10
Relevant per head flow and load
are assigned to residential, transient, commercial and industrial population to
obtain the quantity and quality of total untreated wastewater by individual
catchment areas. Table A5-3-8 to
Table A5-3-12 shows the flow and load factors.
Table A5-3-8
Domestic Flow and Load Factors for Resident Population
|
Description
|
Flow 1 (m3/d/head)
|
SS 2
|
BOD52
|
TKN 2
|
NH3-N 2
|
TP 3
|
Cu3
|
E. coli 2
|
|
|
(all in g/d/head except E.coli in no./d/head)
|
|
|
2013
|
|
|
Usual residents
|
|
|
Sandy Bay
|
0.35
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Stanley, Discovery Bay
|
0.29
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Shek O
|
0.35
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Outlying Island, Sai Kung
|
0.27
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Yuen Long, Mui Wo
|
0.25
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Aberdeen, Wan Chai, North Lantau
|
0.23
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Sha Tin, Tai Po
|
0.22
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
San Wai
|
0.23
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Wah Fu, Shek Wu Hui, N
|
0.21
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Northwest
Kowloon, Tuen Mun, Central, North Point
|
0.2
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Ap Lei Chau, Chai Wan,
Shau Kei Wan, Central Kowloon, East Kowloon, Kwai Chung, Tsing Yi, Tseung
Kwan O
|
0.19
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
|
Mobile residents
|
0.19
|
40
|
42
|
8.5
|
5.0
|
1.33
|
0.0065
|
4.3E+10
|
|
Source of reference:
1.
Guidelines for Estimating Sewage
Flows for Sewage Infrastructure Planning (Version 1.0), EPD, March 2005
2.
DSD Sewerage Manual
3.
EPD Update Study
Table A5-3-9 Domestic Flow and Load
Factors for Transient Population
|
Description
|
Flow 1 (m3/d/head)
|
SS 2
|
BOD52
|
TKN 2
|
NH3-N 2
|
TP 3
|
Cu3
|
E. coli 2
|
|
(all in g/d/head except E.coli in no./d/head)
|
|
Employed population
|
0.08
|
34
|
34
|
6.7
|
4.0
|
1.06
|
0.0052
|
3.5E+10
|
|
Students
|
0.04
|
34
|
34
|
6.7
|
4.0
|
1.06
|
0.0052
|
3.5E+10
|
Source of reference:
1.
Guidelines for Estimating Sewage
Flows for Sewage Infrastructure Planning (Version 1.0), EPD, March 2005
2.
DSD Sewerage Manual
3.
EPD Update Study
Table A5-3-10 Flow and Load Factors
for Commercial Activities
|
Description
|
Flow 1 (m3/d/employee)
|
SS 2
|
BOD52
|
TKN 2
|
NH3-N 2
|
TP 3
|
E.coli 2
|
|
(all in g/d/head except
E.coli in no./d/head)
|
|
J2 Electricity Gas & Water
|
0.25
|
25
|
53
|
2.5
|
0.8
|
0.53
|
0
|
|
J3 Transport, Storage & Communication
|
0.1
|
25
|
53
|
2.5
|
0.8
|
0.53
|
0
|
|
J4 Wholesale & Retail
|
0.2
|
25
|
53
|
2.5
|
0.8
|
0.53
|
0
|
|
J9 Construction
|
0.15
|
25
|
53
|
2.5
|
0.8
|
0.53
|
0
|
|
J10 Restaurants & Hotels
|
1.5
|
25
|
53
|
2.5
|
0.8
|
0.53
|
0
|
|
J11 Community, Social & Personal Services
|
0.2
|
25
|
53
|
2.5
|
0.8
|
0.53
|
0
|
Source of reference:
1.
Guidelines for Estimating Sewage
Flows for Sewage Infrastructure Planning (Version 1.0), EPD, March 2005
2.
DSD Sewerage Manual
3.
EPD Update Study
Table
A5-3-11 Flow Factors for Industrial Activities
|
Catchment
|
Flow 1 (m3/d/employee)
|
|
J1 Manufacturing
|
|
Hong
Kong Island
(except Aberdeen & Ap Lei Chau), San Po
Kong
|
0.25
|
|
North
West Kowloon
|
0.45
|
|
East Kowloon, Sha Tin, Lantau Island (except Mui Wo)
|
0.45
|
|
Central Kowloon, North District,
Aberdeen, Ap
Lei Chau
|
0.55
|
|
Tsuen Wan, Kwai Chung
|
0.65
|
|
Tai Po
|
0.75
|
|
Tuen Mun, Tseung Kwan O, Yau
Tong, Cheung Chau, Mui Wo
|
1
|
|
Tsing Yi
|
1.5
|
|
Sai Kung, Yuen Long
|
2
|
Source of
reference:
1.
Guidelines for Estimating Sewage
Flows for Sewage Infrastructure Planning (Version 1.0), EPD, March 2005
Table
A5-3-12 Load Factors for Industrial Activities
|
Category
|
SS
1
|
BOD5
1
|
TKN
1
|
NH3-N
1
|
Cu
1
|
E.coli 1
|
|
(all
in g/d/employee except E.coli in
no./d/employee)
|
|
J1 Manufacturing
|
|
Food
|
502
|
713
|
39
|
0
|
0
|
0
|
|
Textiles
|
2095
|
3680
|
67
|
0
|
4.4
|
0
|
|
Leather
|
115
|
115
|
29
|
7
|
0.1
|
0
|
|
Paper
|
2228
|
2150
|
33
|
0
|
0
|
0
|
|
Manufacturing
|
355
|
931
|
0
|
0
|
2.4
|
0
|
|
Machinery
|
40
|
90
|
29
|
22
|
0.9
|
0
|
Source of reference:
1.
EPD Update Study
4.11
Pollution load generation
factors for OrthoP and silica are not available. The following assumptions are
adopted for calculating OrthoP and silica loading in raw sewage.
l
TP to
OrthoP is 1.68 based on the actual measurements of raw sewage at Sha Tin STW
and Yuen Long STW.
l
The silica
content is approximately 9 mg/l based on the actual measurements of raw sewage
at Sha Tin STW.
5.1
The pollution loads from
typhoon shelters, marine culture zones adopted in the EEFS are summarized in Table A5-3-13 and Table A5-3-14. These pollution loads are included in
the water quality model under 2013 for cumulative assessment. Loading from landfills and beaches that
would not be connected to the STW is summarized in Table A5-3-15 and Table A5-3-16.
Table A5-3-13 Pollution Flows
and Loads from Typhoon Shelter
|
Typhoon shelters
|
Flow (m3/d)
|
BOD (g/d)
|
SS
(g/d)
|
Org-N (g/d)
|
NH3-N (g/d)
|
E.coli (no./d)
|
Copper (g/d)
|
TP
(g/d)
|
OrthoP (g/d)
|
Silicate (g/d)
|
|
Shau
Kei Wan
|
149
|
41670
|
39686
|
3473
|
4961
|
4.27E+14
|
6
|
1320
|
785
|
1279
|
|
Sam
Ka Tsuen
|
39
|
10803
|
10289
|
900
|
1286
|
1.11E+13
|
2
|
342
|
204
|
332
|
|
Kwun
Tong
|
22
|
6055
|
5766
|
505
|
721
|
6.20E+12
|
1
|
192
|
114
|
186
|
|
Causeway Bay
|
179
|
50099
|
47714
|
4175
|
5964
|
5.13E+13
|
8
|
1586
|
944
|
1538
|
|
Yau
Ma Tei
|
184
|
51643
|
49183
|
4304
|
6148
|
5.29E+13
|
8
|
1635
|
973
|
1586
|
|
Rambler
Channel
|
36
|
10032
|
9554
|
836
|
1194
|
1.03E+13
|
2
|
318
|
189
|
308
|
|
Aberdeen
|
388
|
108746
|
103568
|
9062
|
12946
|
1.11E+14
|
17
|
3444
|
2050
|
3339
|
|
Tuen
Mun
|
138
|
38643
|
36803
|
3220
|
4600
|
3.96E+13
|
6
|
1224
|
728
|
1186
|
|
Cheung
Chau
|
166
|
46597
|
44378
|
3883
|
5547
|
4.77E+13
|
7
|
1476
|
878
|
1431
|
|
Shuen
Wan (Yim Tin Tsai)
|
49
|
13712
|
13059
|
1143
|
1632
|
1.40E+13
|
2
|
434
|
258
|
421
|
|
Sai
Kung
|
81
|
22794
|
21709
|
1899
|
2714
|
2.33E+13
|
4
|
722
|
430
|
700
|
|
Chai
Wan
|
44
|
12347
|
11759
|
1029
|
1470
|
1.26E+13
|
2
|
391
|
233
|
379
|
|
To
Kwa Wan
|
53
|
14840
|
14133
|
1237
|
1767
|
1.52E+13
|
2
|
470
|
280
|
456
|
Table A5-3-14 Pollution Flows
and Loads from Marine Culture Zone
|
Marine Culture Zone
|
BOD (g/d)
|
SS (g/d)
|
Org-N (g/d)
|
NH3-N (g/d)
|
TP (g/d)
|
OrthoP (g/d)
|
|
Sha
Tau Kok
|
42806
|
124916
|
10569
|
38075
|
2038
|
1595
|
|
Ap
Chau
|
999
|
2915
|
247
|
888
|
48
|
37
|
|
Kat
O
|
7705
|
22485
|
1902
|
6854
|
367
|
287
|
|
O
Pui Tong
|
25113
|
73284
|
6200
|
22338
|
1196
|
936
|
|
Sai
Lau Kong
|
1712
|
4997
|
423
|
1523
|
82
|
64
|
|
Wong
Wan
|
5351
|
15615
|
1321
|
4759
|
255
|
199
|
|
Tap
Mun
|
17217
|
50244
|
4251
|
15315
|
820
|
642
|
|
Kau
Lau Wan
|
2663
|
7773
|
658
|
2369
|
127
|
99
|
|
Sham
Wan
|
42948
|
125333
|
10604
|
38202
|
2045
|
1600
|
|
Lo
Fu Wat
|
1284
|
3747
|
317
|
1142
|
61
|
48
|
|
Yung
Shue Au
|
81330
|
237341
|
20081
|
72343
|
3872
|
3031
|
|
Leung
Shuen Wan
|
4114
|
12006
|
1016
|
3659
|
196
|
153
|
|
Tiu
Cham Wan
|
4043
|
11798
|
998
|
3596
|
192
|
151
|
|
Tai
Tau Chau
|
14934
|
43582
|
3687
|
13284
|
711
|
557
|
|
Kai
Lung Wan
|
6432
|
18769
|
1588
|
5721
|
306
|
240
|
|
Kau
Sai
|
10987
|
32062
|
2713
|
9773
|
523
|
409
|
|
Ma
Nam
Wat
|
9536
|
27829
|
2355
|
8482
|
454
|
355
|
|
Po Toi O
|
9084
|
26510
|
2243
|
8080
|
432
|
339
|
|
Po Toi
|
33579
|
97990
|
8291
|
29868
|
1599
|
1251
|
|
Sok
Kwu Wan
|
25969
|
75783
|
6412
|
23099
|
1236
|
968
|
|
Lo
Tik Wan
|
11011
|
32131
|
2719
|
9794
|
524
|
410
|
|
Ma
Wan
|
50939
|
148650
|
12577
|
45310
|
2425
|
1898
|
|
Yim
Tin Tsai
|
35552
|
103750
|
8778
|
31624
|
1693
|
1325
|
|
Cheung
Sha Wan
|
19025
|
55518
|
4697
|
16922
|
906
|
709
|
|
Yim
Tin Tsai (East)
|
35499
|
103750
|
4406
|
31754
|
1197
|
1051
|
|
Tung
Lung Chau
|
18996
|
55518
|
2358
|
16992
|
640
|
562
|
Table A5-3-15 Pollution Flows and
Loads from Landfills
|
Landfill
|
Flow (m3/d)
|
BOD
(kg/d)
|
SS
(kg/d)
|
Org-N (kg/d)
|
NH3-N
(kg/d)
|
E-Coli (no./d)
|
Cu
(g/d)
|
|
Shuen Wan
Landfill Leachate seepage into coastal waters
|
50
|
10
|
10
|
10
|
90
|
3.48E+05
|
1
|
Table A5-3-16 Pollution Flows and
Loads from Beaches
|
Gazetted
Beach
|
Flow
(m3/d)
|
BOD
(g/d)
|
SS
(g/d)
|
Org-N
(g/d)
|
NH3-N
(g/d)
|
E.coli.
(no./d)
|
TP
(g/d)
|
OrthoP
(g/d)
|
|
Cheung Sha Lower
|
1
|
245
|
204
|
135
|
307
|
3.24E+12
|
70
|
42
|
|
Cheung Sha Upper
|
0
|
95
|
79
|
52
|
118
|
1.25E+12
|
27
|
16
|
|
Pui O
|
1
|
152
|
126
|
83
|
190
|
2.00E+12
|
43
|
26
|
|
Tong Fuk
|
1
|
188
|
156
|
103
|
234
|
2.48E+12
|
53
|
32
|
|
Hap Mun Bay
|
13
|
3204
|
2670
|
1757
|
4004
|
4.23E+13
|
912
|
543
|
|
Kiu Tsui
|
1
|
353
|
294
|
194
|
441
|
4.66E+12
|
100
|
60
|
|
Tung Wan, Ma Wan
|
2
|
485
|
404
|
266
|
607
|
6.40E+12
|
138
|
82
|
|
Clear Water Bay 1st
|
5
|
1340
|
1117
|
735
|
1675
|
1.77E+13
|
381
|
227
|
|
Clear Water Bay 2nd
|
46
|
11385
|
9487
|
6246
|
14231
|
1.50E+14
|
3240
|
1928
|