Feng Jiang Professor, School of Chemistry and Environment South - PowerPoint PPT Presentation

Study of the Septicity Problem throughout the Tunnel Systems under the Harbour Area Treatment Scheme (HATS) Feng Jiang Professor, School of Chemistry and Environment South China Normal University Email: jiang.feng@foxmail.com / jiangfeng@scnu.edu.cn Mobile / Tel: +86-13760612488

Contents 1 General introduction 2 Assess the sulfide generation in HATS SCS 3 Simulation of HATS SCS by SPMM 4 Summary

1. General introduction As the water quality in Victoria Harbour affects many people in Hong Kong, the Government initiated the Harbour Area Treatment Scheme(HATS). It improves the water quality of Victoria Harbour through the collection, treatment and disposal of sewage from both sides of Harbour. Stage 1: • commissioned in December 2001; • upgrading 7 PTWs, construction of 23km -long and -70 to -140 m deep tunnel system; • treats 75% of the sewage, the capacity to move up to 1.7 million m 3 /d . Stage 2A: • commissioning in December 2015; • upgrading 8 PTWs, construction of 21km - long and -70 to -160 m deep tunnel system; • treats the remaining 25% of sewage long-distance long-time of sewage conveyance obnoxious gas(H 2 S) and corrosion

Mechanism of H 2 S production in sewers sulfide is generally bio-generated in sewer biofilm, due to the growth of the SRB colonized in biofilm (Ito et al. , Sulfate reduction and sulfide production ： 2002). 𝑇𝑆𝐶 𝑇 2− + 𝐷𝑃 2 2− + 𝐷 𝑇𝑃 4 Sewer atmosphere Anoxic sulfide oxidation ： Sulfur Oxidizing Bacteria 𝑇 2− + 𝑃 2 /𝑂𝑃 3 2− + 𝑂 2 − 𝑇 0 /𝑇𝑃 4 H 2 SO 4 Hydrogen sulfide dissociation ： 𝑇 2− ↔ 𝐼𝑇 − ↔ 𝐼 2 𝑇 H 2 S Hydrogen sulfide emission: 𝐼 2 𝑇 (aq) ↔ 𝐼 2 𝑇 (𝑕) H 2 S H 2 S 2- SO 4 2- SO 4 H 2 S (g) Harmful effects Sulfate Reducing Bacteria conc.(ppm) Min concentration can be smelt 0.13 Bulk sewage … … Biofilm average Continuous exposure after one hour, there was a noticeable 200-300 conjunctivitis, and respiratory irritation HATS peak Loss of consciousness, apnea, and even death 500-700 Loses consciousness immediately, breathes stops and died in 1000~ several minutes

25000 How to control H 2 S (g) in sewer ? CW Flowrate (m 3 /h) 20000 SKW 15000 TKO Forced Ventilation 10000 KT End-of-pipe TKW 5000 treatment Deodourization KC 0 Unit TY 4/10/2015 9:00 5/10/2015 21:00 7/10/2015 9:00 Time To transform - , H 2 O 2 , O 2 , NO 3 Control H 2 S - dissolved sulfide NO 2 To inhibit sulfide FNA, Molybdate formation Chemical Dosing In-pipe To precipitate Fe 2+ , Fe 3+ treatment dissolved sulfide Hydraulic flushing To suppress H 2 S g NaOH, Ca(OH) 2 emission • High Cost Over • Chemical pollution dosage • Risk to downstream WWTP and ecosystem A sewer processes math model is essential to cost-effective H 2 S control in • Ineffective H 2 S control Insufficient HATS • Infrastructure corrosion dosage • Human health risk

Sewer Process Mathematical Model • The Sewer Process Mathematical Model (SPMM) – Developed by Dr. Feng Jiang (SCNU) and Prof. G H Chen (HKUST) since 2007 – To simulate all the physical, chemical, and biological processes related to sewage quality changing in sewers. H 2 S (g) Gas phase H 2 SO 4 Corrosion Substance concentrations emission in biofilm S 2- //HS - /H 2 S (ag) SO 4 2- Biomass / particulate Water phase - NO 3 Attachment /Detachment Diffusion Changes in S 2- biofiom Biofilm/sediment biofilm-process composition Schematic diagram of the main reaction related to sulfide in sewer

SPMM can be used to simulate the biochemical process of biofilm and wastewater, and also can predict the sulfide production and H 2 S releases, e.g. the previous Applications of this SPMM (1) Agreement No. DEMP09/06 - Sewer Biofilm Modeling for sulfide Formation in Sewers • Tung Chung pressured main sewer (TCS) and Tuen Mun gravity sewer (TMS) (2) HKIA Sewer Network Study • The sewer networks in the Hong Kong International Airport (HKIA) H 2 S (g) sulfide

2. Assess the sulfide generation in HATS SCS  Sampling Locations: SCISTW and 7 PTWs  Analyzing parameter: 20 parameters include TS, DS, VSS, H2S(g), flowrate etc. HATS 1  Sampling time: Every 2 or 12h for 7 days • Data (2015.10.4 9:00 to 2015.10.7 9:00) for model calibration • Date (2015.10.7 9:00 to 2015.10.11 9:00) for model verification  Sampling Locations: SCISTW and 8 PTWs  Analyzing parameter: 20 parameters include TS, DS, VSS, H2S(g), flowrate etc. HATS 2A  Sampling time: Every 2 or 12h for 2 days • (2015.12.7 14:00 to 2015.12.9 14:00)

Field experiment and data analysis HATS Stage 1 Inverted Syphon KC Pressured Main PTW 43 Both (KT Riser Shaft) TY 2089 kgS 2- /d SCI PTW kgS 2- /d STW 18 TKW kgS 2- /d PTW KT KT PTW TUNNEL G PS 108 191 TKO kgS 2- /d kgS 2- /d PTW TUNNEL F 228 kgS 2- /d TUNNEL E TUNNEL C SKW PTW TUNNEL D CW 27 PTW kgS 2- /d 48 TUNNEL B kgS 2- /d CW input KC input KT input SKW input TKO input TKW input TY input SCISTW output PTWs input ~70% DS were generated in the HATS 1 TUNNEL A SCISTW output 0 500 1000 1500 2000 Net sulfide input or output (kgS/d)

H 2 S (g) conc. in HATS 1 outlet H 2 S g monitoring at SCISTW MPS No.1 H 2 S (g) Conc. at MPS No.1 Average: 219 ppm Maximum: 720 ppm Wet well Liquid sampling

7 PTWs input (10/4-10/7) SCISTW output (10/4-10/7) pH 3.5 3 DS Dissolved sulfide (mgS/L) 2.5 CW SKW 2 TKO H 2 S (g) 1.5 KT TKW 1 KC 0.5 TY 0 4/10/2015 9:00 5/10/2015 9:00 6/10/2015 9:00 7/10/2015 9:00 Time Strong fluctuation DS 25000 Flowrate 20000 CW Flowrate (m 3 /h) SKW 15000 TKO Flowrat 10000 KT e TKW 5000 KC TY 0 4/10/2015 9:00 5/10/2015 9:00 6/10/2015 9:00 7/10/2015 9:00 Time Based on the different sewer with different water quality and hydraulic conditions (e.g. pH, flowrate, and dissolved sulfide ), model should be used to predict and effective control H 2 S (g).

3. Simulation of HATS SCS by SPMM Model Calibration of HATS stage 1 (10/4-10/7) Average sulfide Concentration: DS H 2 S(g) measured: 219 ppm simulated: 221 ppm DS measured: 1.82 mgS/L simulated: 1.94 mgS/L Simulated well Flowrate H 2 S (g) Model Verification of HATS stage 1 (10/7-10/11) Average sulfide Concentration: DS H 2 S(g) measured: 207 ppm simulated: 214 ppm DS measured: 1.89 mgS/L Predicted simulated: 1.79 mgS/L well Flowrate H 2 S (g)

Model Application of HAST Stage 1 Overview 1. Locate the position of sulfide generation 2. Case study  Case 1: Ultimate Flow Simulation  Case 2: Temperature effect  Case 3: Water Flushing 3. H 2 S control by chemical dosing  Case 4: Super-oxygenation system(TKO) ;  Case 5: Nitrate dosing(TKW) ;  Case 6: NaOH (TKW) ;  Case 7: Nitrate + NaOH (TKW) ;  Case 8: Nitrate + NaOH (TKW) + Forced Ventilation (MPS1)

HATS Stage 1 The position of sulfide generation Long HRT result in high sulfide concentration Largest Short HRT and high DO result in very Due to 35,390m 3 /h wastewater low sulfide concentration Net sulfide Average flowrate Hydraulic Calculated DS-in Calculated DS-out production Tunnel Lengh (km) (m 3 /h) retention time(h) (average mgS/L) (average mgS/L) (kgS/d) A CW 2446 1.1 2300 0.81 2.35 90 B CW SKW 5357 0.7 2500 1.29 2.02 94 1.64 2.93 180 C TKO 5812 2.6 5300 25754 0.8 1.36 1.57 130 D CW SKW TKO KT 3300 E CW SKW TKO KT TKW 35390 1.5 5500 1.27 2.04 654 F KC TY 12210 1.3 3600 0.18 1.70 445 0.19 0.15 -8 G KC 9643 0.3 800

HATS 1 Case Study 1 Ultimate Flow Simulation • The ultimate flow is predicted to be 1.4 times of current flow (average); • sulfide production in Tunnels decreased by 12% , DS concentration decreased by 27% (drop from 1.94 mgS/L to 1.42 mgS/L). Current flow Ultimate peak flow Net sulfide Net sulfide Flowrate Average Simulated DS-out Flowrate Average Simulated DS-out Tunnel production production (m 3 /h) (m 3 /h) HRT(h) (mgS/L) HRT(h) (average mgS/L) （ kgS/d ） （ kgS/d ） A 2,446 1.1 2.35 90 2,556 1.0 2.13 81 B 5,357 0.7 2.02 94 7,083 0.5 1.69 87 C 5,812 1.3 2.93 180 6,869 1.1 2.78 188 D 25,754 0.8 1.57 130 34,560 0.6 1.28 50 E 35,390 1.5 2.04 654 52,201 1.0 1.44 539 F 12,210 1.3 1.70 445 16,066 1.0 1.38 463 G 9,643 0.3 0.15 -8 12,789 0.2 0.14 -15 1,585 1,393 HATS 1 47,599 1.94 68,267 1.42

HATS 1 Case Study 2 SCISTW Net sulfide production Temperature Effect DS variation(%) （ kgS/d ） DS (mgS/L) 28.7 ° C- 1.94 0% 1,585 Winter: 18 ° C simulated 32.0 ° C- Spring-Autumn: 25 ° C 2.16 1,837 11% simulated Summer: 32 ° C 25.0 ° C- 1.61 -17% 1,207 simulated Field experiment: 28.7 ° C 18.0 ° C- 1.16 -40% 692 simulated  Temperature Bioactivity sulfide generation Case Study 3 Water Flushing F E Flushing  Unsatisfactory control effects - Enormous flow requirement: 10 to 20 times of the average Tunnel E Tunnel F flow, and increase with tunnel size; Length (km) 5.5 3.6 - Flushing frequency: every 3~4 days, lasting for 1h;  Negative impact Flowrate (m 3 /h) 35,390 12,210 (10/4-10/7) - Stress the downstream treatment capacity HRT (hour) 1.5 1.3 - High energy consumption