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Optimal ventilation and filtering strategies Barcelona - May, 7 2015 - - PowerPoint PPT Presentation

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Optimal ventilation and filtering strategies Barcelona - May, 7 2015 for air quality in carriages P . Blondeau, M. O. Abadie University of La Rochelle, France Open Day on Air quality in rail subway systems, CSIC Expansion of the existing rail

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Optimal ventilation and filtering strategies for air quality in carriages

P . Blondeau, M. O. Abadie University of La Rochelle, France

Barcelona - May, 7 2015

Open Day on Air quality in rail subway systems, CSIC

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SLIDE 2

2

Frame of the study

Expansion of the existing rail public transport network of Paris 4 new lines and 2 expanded lines : 72 stations, 57 new

  • + 70 km of high speed metro
  • + 30 km of metro
  • +150 km of light rail

Underground

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SLIDE 3

3

Frame of the study

Define design guidelines for acceptable air quality in the underground indoor spaces from airflow and air quality simulations Construction and operation based on sustainable development principles French national plan on IAQ (2013): « Action S: undertake actions as a way to improve IAQ in subway systems »  Setup of mandatory monitoring of IAQ in subways Motivations of SGP for IAQ studies Objectives Literature review:

  • Pollutant concentrations

in metro areas

50 100 150 200 250 300 350 400 450 500 PM10 (µg/m³)

Underground train Underground platform Station Outdoor

1212

  • Technical data : ventilation (stations/tunnels/carriages), tyre/steel wheels,

braking system, platform equipments (e.g. window screens), … Target contaminants: PM10, PM2.5, NO2, benzene

2 1 Identify air quality main issues

and key parameters for IAQ

Coutdoor < Cstation < Cplatform < Ccarriage (except Taipei)

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4

Frame of the study

AIRFLOW IAQ Pressures on platform window screens Pollutant concentrations at platfom screen doors

Modelling strategy

System 3 : TUNNEL System 4 : STATION System 5: CARRIAGES System 1: TUNNEL System 2 : TUNNEL / STATION

IAQ AIRFLOW IAQ Airflows in tunnels and ventilation sinks Airflow rates between the compartments of the station Pollutant concentrations in tunnels

Cout

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5

  • Return air

Supply air

AHU « Fresh » air Exhaust air Recycled air Single zone model accounting for: Ventilation (including filters) Deposition onto surfaces Influence of passengers MP 05 train carriage: V = 73 m3, Max. load: 162 persons  Particle emission  Particle deposition on body  Particle sink by inhaled air  Particle resuspension due to movements (body, floor)  Volume reduction

  • Sbody = 340 m2 (1)
  • Vbody = 11 m3 (1)
  • PM10 emission rate = 100 mg/h (2)
  • Inhaled air flow rate = 68 m3/h (3)

(1) H = 1.65 m, W = 65 kg, winter clothes (2) 1.6 106 to 3 106 part/h/person, density =1000 kg/m3 (3) 0.42 m3/h/person

Deposition Inhaled air

Models and parameters

Design tool (steady-state) Exposure assesment (dynamic) 2 simulation tools :

Internal emissions Resuspension Resuspension

Cind Cout

Deposition

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SLIDE 6

6 Filter efficiencies for representative subway aerosol

9

M M

Ventilation filters are classified into 16 classes and 9 classes by international standards Filter class is determined based on the mean efficiency which is measured in standard test conditions using a specific aerosol  Not representative of the actual efficiency

Models and parameters

Protection of HVAC components IAQ improvement

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SLIDE 7

10 20 30 40 50 60 70 80 90 100 0.010 0.100 1.000 10.000

MERV 4 (G2) MERV 5 (G3) MERV 6 (G3) MERV 7 (G4) MERV 8 (G4) MERV 9 (M5) MERV 10 (M5) MERV 11 (M6) MERV 12 (M6) MERV 13 (F7) MERV 14 (F8) MERV 15 (F9) MERV 16 (F9) Exp

7 Computation of the initial efficiency

  • f filters as a function particle size

Particle size distribution of a typical subway aerosol (Midander et al, 2014)

Models and parameters

12% 23% 37% 45% 58% 63% 71% 74% 82% 86% 91% 93% 94% 9% 16% 27% 33% 42% 46% 52% 56% 64% 72% 83% 87% 88%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

G2 (MERV 4) G3 (MERV 5) G3 (MERV 6) G4 (MERV 7) G4 (MERV 8) M5 (MERV 9) M5 (MERV 10) M6 (MERV 11) M6 (MERV 12) F7 (MERV 13) F8 (MERV 14) F9 (MERV 15) F9 (MERV 16)

PM10 G2 (MERV 4) G4 (MERV 8)

Fresh air filter Supply / return air filter Fresh air filter Supply or return air filter Filtering efficiency as a function of particle size

0.001 0.01 0.1 1 10 100 1000 10000 1 10 100 1000 10000 100000

Dp (nm) dN/dlogDp (particles/cm3)

Modified particle size distribution

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8

Models and parameters

Deposition velocity of particles as a function of size (computed from Lai and Nazaroff model)

0.001 0.01 0.1 1 10

G2 (MERV 4) G3 (MERV 5) G3 (MERV 6) G4 (MERV 7) G4 (MERV 8) M5 (MERV 9) M5 (MERV 10) M6 (MERV 11) M6 (MERV 12) F7 (MERV 13) F8 (MERV 14) F9 (MERV 15) F9 (MERV 16)

Ceiling Walls Floor

0.000001 0.00001 0.0001 0.001 0.01 0.1 1 0.001 0.010 0.100 1.000 10.000

Deposition velocity (cm/s) Particle diameter (µm) Ceiling Walls Floor

Deposition velocity of PM10 (m/h) as a function of fresh air filter

Deposition velocities on surfaces

Friction velocity = 3 cm/s

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SLIDE 9

20 40 60 80 100 120 140 160 180 200 220

Indoor concentration (mg/m3) Supply air filter

MERV 4 (G2) MERV 5 (G3) MERV 6 (G3) MERV 7 (G4) MERV 8 (G4)

Fresh air filter

PM10

9

  • AHU

Applications : design tool

Train MP05, 1st configuration Cooled air mechanical ventilation: no recycled air, 11.5 kW cooling coil

  • Tunnel concentrations:

200 mg/m3 PM10, 75 mg/m3 PM2.5 1815 m3/h 1815 m3/h

  • 162 passengers (full load)

Cooling coil Fresh air filter Supply air filter

Simulation conditions:

24-hour mean WHO guidelines (2005) Annual mean 52 13

Internal emissions (passengers) Supply air T echnical specifications Paris Outdoor

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10

Applications : design tool

10 20 30 40 50 60 70 80 90 100

Indoor concentration (mg/m3) Supply air filter

MERV 4 (G2) MERV 5 (G3) MERV 6 (G3) MERV 7 (G4) MERV 8 (G4)

Fresh air filter

PM2.5

24-hour mean WHO guidelines (2005) Annual mean

  • Small influence of the fresh air filter on PM2.5 concentrations
  • MERV 14 (F8) needed to meet the WHO guideline for 24-hour mean

Train MP05, 1st configuration Cooled air mechanical ventilation: no recycled air, 11.5 kW cooling coil

  • Tunnel concentrations:

200 mg/m3 PM10, 75 mg/m3 PM2.5

  • 162 passengers (full load)

Simulation conditions:

Outdoor

  • Significant efficiency of filters from MERV 11 (M6)
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11

Applications : design tool

Air conditioning (recycled air)

  • Tunnel concentrations:

200 mg/m3 PM10, 75 mg/m3 PM2.5 7400 m3/h 5300 m3/h

  • 162 passengers

Simulation conditions:

20 40 60 80 100 120 140 160 180 200 220

Indoor concentration (mg/m3) Return air filter

MERV 4 (G2) MERV 5 (G3) MERV 6 (G3) MERV 7 (G4) MERV 8 (G4)

Fresh air filter

PM10

AHU Recycled air 2100 m3/h

24-hour mean WHO guidelines (2005) Annual mean Fresh air filter Return air filter

  • T

echnical specifications

Train MP05, 2nd configuration

Outdoor

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12

Applications : design tool

max max min norm

C C C C C   

Normalized IAQ index Operating conditions as the optimum between IAQ and energy

min min norm max

E E E E E   

Normalized energy index 0 (*) < Enorm < 1 0 < Cnorm < 1(*)

(*) best performance

 

v ducts filter fan

q P P E     

Fan power (W):

.

2

init final filter

P P P     

(Pa)

PM2.5 concentration – Fresh air filter = MERV 6 (G3) Fan energy – Fresh air filter = MERV 6 (G3)

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13

Applications : design tool

MERV 11 (M6) MERV 13 (F7) MERV 14 (F8) MERV 16 (F9)

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 1500 2000 2500 3000 3500 4000

Optimum

3000 4000 5000 6000 7000 8000

Fresh air filter = MERV 6 (G3)

PM2.5

Technical specifications Optimum

norm norm

C I E 

0 < I <  (best performance) Performance index

Performance index Fan efficiency : fan = 0.54

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SLIDE 14

20 40 60 80 100 120 140 20 40 60 80 100 120 140 160 180 200 220

15:34:14 15:35:11 15:36:08 15:37:05 15:38:02 15:38:59 15:39:56 15:40:53 15:41:50 15:42:47 15:43:44 15:44:41 15:45:38 15:46:35 15:47:32 15:48:29 15:49:26 15:50:23 15:51:20 15:52:17 15:53:14 15:54:11 15:55:08 15:56:05 15:57:02 15:57:59 15:58:56 15:59:53

Number of passengers Concentration (mg/m3) 14

Applications : dynamic tool

Cooling with fresh air only Fresh Air : MERV6 (G3) Supply : No filter

PM10

Passengers On ground section 45 mg/m3: Mean 2013 Roosevelt station Mean : 100 mg/m3 Mean : 30 mg/m3

Paris Train : MP05

Tunnel : 200 mg/m3

WHO 24-hour mean

A/C with recycled air Fresh Air : MERV6 (G3) Return : MERV14 (F8)

WHO annual mean

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SLIDE 15

15 Possible developments

  • Modeling the increase of filter efficiency with particle load
  • Modeling the influence of airflow rate upon filter efficiency

Easy to use models / friendly environment  Engineers and designers  System owner or subway operator  Health authorities Optimal ventilation / air conditioning strategies Assessment of exposure Acknowledgements Thanks to Klara Midander and Karine Elihn (Stockholm), Costas Sioutas and Winnie Kam (Los Angeles), Yu-Hsiang Cheng (Taipei)

  • Improve accuracy of the energy index from information about cross

sectional areas of air outlets / return duct in metro trains

  • Additional criteria for optimization : filter lifetimes, replacement costs, …

Conclusion

Technical specifications in the frame

  • f call for tenders

Model improvement

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16

Selected bibliography

Particle concentrations and size distribution in subways

  • K. Midander, K. Elihn, A. Wallén, L. Belova, A-K. Borg Karlsson, I. Odnevall Wallinder (2012)

Characterisation of nano- and micron-sized airborne and collected subway particles, a multi- analytical approach. Science of the Total Environment 427–428 (2012) 390–400

Filter efficiency as a function of particle size Deposition velocities of particles onto surfaces

Kowalski W, Bahnfleth W. (2002) MERV filter models for aerobiological applications. Air Media, Summer Issue, pp. 13-17. Lai ACK, Nazaroff W. (2000) Modeling indoor particle deposition from turbulent flow onto smooth

  • surfaces. Journal of Aerosol Science, 4, pp. 463-476

Human emissions of particles

  • S. Bhangar, R. I. Adams, W. Pasut, J. A. Huffman, E. A. Arens, J. W. Taylor, T. D. Bruns, W. W. Nazaroff (2015)

Chamber bioaerosol study: human emissions of size-resolved fluorescent biological aerosol particles. Indoor Air (published online Mars 2015)

Particle ressupension from clothes

  • A. Mc Donagh and M.A. Byrne (2014) A study of the size distribution of aerosol particles

resuspended from clothing surfaces. Journal of Aerosol Science 75(2014), 94–103

Particle resupension from the floor

  • Z. Mana (2014) Etude de la remise en suspension de particules due à la marche d’un opérateur.

Thèse de doctorat de l’Université Paris Sud