Second Workshop on Regional Climate Modeling and Extreme ...€¦ · Bruna Segalin, doutoranda...
Transcript of Second Workshop on Regional Climate Modeling and Extreme ...€¦ · Bruna Segalin, doutoranda...
Second Workshop on Regional Climate Modeling and Extreme
Events over South America"Modeling Air Quality in São Paulo
with WRF-CHEMEmission Processing and Modeling
Rita YnoueLAPAt (Laboratório de Análise dos Processos Atmosféricos)
DCA – IAG – USP Nov 8th 2018
Departamento de Ciências Atmosféricas
LAPAt – Laboratório de Análises dos Processos Atmosféricos
Website: http://www.lapat.iag.usp.br/Maria de Fátima Andrade ([email protected])
Fabio L. T. Gonçalves ([email protected])
Adalgiza Fornaro ([email protected])
Rita Yuri Ynoue ([email protected])
O grupo estuda os processos associados à poluição atmosférica, com destaque para estudos da região metropolitana de São Paulo. Os projetos
concentram-se nas seguintes áreas:➢ Caracterização física e química de aerossóis atmosféricos; Caracterização química de deposição úmida (águas de chuva, nevoeiro).
➢ Gases atmosféricos: hidrocarbonetos (C2-C11), etanol, carbonilas, amônia, metano, dióxido de carbono, etc
➢Modelagem de remoção de matéria particulada e gases: deposição úmida e seca.
➢Modelagem da dispersão e formação de poluentes atmosféricos (smog fotoquímico).
➢ Quantificação e classificação de bioaerossóis.
Micro-Orifice Uniform
Deposit Impactor (MOUDI)
Dichotomous Sequential Air Sampler,
Partisol®-Plus 2025-D (www.thermo.com)MiniVol
Composição elementar e iônica do material particulado
Sondagens de ozônio
EDX (Energy Dispersive X-ray Fluorescence)Cromatografia iônica
CG-FID (Cromatografia gasosa )
Hidrocarbonetos (C2-C11)
Personal cascate impactor (PCIS)Amostrador automático de
águas de chuva
Experimentos em túneis
Modelagem da qualidade
do ar:
Emissão, dispersão e
formação de poluentes
Emissão de NOx
Bruna Segalin, doutoranda
Sergio Ibarra, doutorando
Atmospheric emissions, transport, transformation, and deposition of trace gases
(Source: Aneja et al., 2003, 2006b)
Good emissions estimates are the start
of any environmental assessment
Emissions: natural and anthrop. sources
Calculating emissions
• Emissions = Emission Factor x activity data• Emission Factors: mass of polutant produced per
unit of activity– Vary by pollutant, equipment/source– Found in models, national tables, source tests
• Example: How much CO does a light duty vehicleemit in one day?
• Emission fator (MOBILE)=2g of CO/km• Activity level (Transportation Agency)=30 km/day• Emission = 60 g CO/day
Alicia Edwards & Clint Farr-ADEQ-Air non point & mobile source program
Brazilian Environmental ProtectionAgency
• IBAMA (Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis): Federal Environmental Protection Agency
• CETESB (Companhia Ambiental do Estado de São Paulo): Local EPA
CETESB, 2016
CETESB´s emissions inventory
CETESB, 2016
Emissions Processing toAir Quality Models
Air quality models needs good quality emission input, which should...
describe all (anthropogenic) sourcesbe consistent in time and spaceprovide the best (scientific) estimate for the emission
Top-down x Bottom-up approaches
https://vito.be/sites/vito.be/files/styles/image_full_width/public/media/land_s8_topic-air_emission_inventorying-2-eng.jpg?itok=DqGIlrN1
Emissions Terminology
• Inventory: estimate of pollutant emissions at a given spatial unit
• Model Grid: 3-d representation of the earths surface based on discrete and uniform spatial units, i.e. grid cells
• Speciation: conversion of inventory pollutant species to model pollutant species
• Gridding: conversion of inventory spatial units to model grid cells
• Temporalization: conversion of inventory temporal units to those requires by an air quality model
Zac Adelman and Craig MattocksCarolina Environmental Program
Emissions Processing
Area Mobile Point Biogenic
Emissions Processing Steps
AQM-ready Emissions:
Zac Adelman and Craig MattocksCarolina Environmental Program
Emissions Processing
• Purpose: convert emissions data to formats required by air quality model
• Primary functions– Import data into system
– Spatial allocation (gridding)
– Chemical allocation (speciation)
– Temporal allocation
– Merge
– Quality assurance
Zac Adelman and Craig MattocksCarolina Environmental Program
Emissions Processing Steps
• Data Import– Inventory categories
• Area
• Point
• Mobile
• Biogenic
• Gridded
– ASCII or gridded binary
– Country/state/county estimates
– Annual estimates
– Pollutants include bulk VOC and PM2.5
• Spatial Allocation– Inventory spatial units →model grid
– Requires spatial surrogates
Zac Adelman and Craig MattocksCarolina Environmental Program
Emissions Processing Steps
• Chemical Allocation– Tons →Moles
– Converts inventory pollutants to air quality model species
– Model-dependent speciation profiles
– NOx → NO + NO2
– VOC → PAR, OLE, etc.
– PM2.5→ NO3, SO4, etc.
• Temporal allocation– Inventory units → hourly
emissions
– Requires temporal profiles
0
0.02
0.04
0.06
0.08
0.1
0.12
J F M A M J J A S O N D
% E
mis
sio
ns
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
M T W Th F Sa Su
% E
mis
sio
ns
0
0.01
0.02
0.03
0.04
0.05
0.06
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
% E
mis
sio
ns
Monthly Weekly
DiurnalZac Adelman and Craig MattocksCarolina Environmental Program
Available gridded emissions database
Air quality forecasting withWRF-CHEM in MASP
WRF-CHEM in MASP
• Academic and Operational simulations• GFS (FNL) 1º x 1º analysis and forecasts for
meteorological IC and BC• Operational run:
– GFS 00UTC– 48 hours– 1 grid, 9x9 km2 horizontal resolution– Meteorological outputs: intercomparison with other
models(http://www.master.iag.usp.br/ind.php?inic=00&pos=1&prod=previsao_glob)
Emissions
• CETESB emissions inventory for mobilesources (annual value for MASP): CO, NOx, VOCs, SOx, PM10
• Emission Factors: CETESB, Tunnel Experiments(LAPAt)
• VOC´s speciation: Tunnel Experiments (LAPAt)
• Vehicular activities: CETESB
• Spatial distribution: Night lights, IED, SMOKE, Street density
Vehicular emissions
• Daily pollutant emission (pol) by type of vehicle(veic):
• Emission (pol,veic) = activity (veic) * emissionfactor (pol,veic)*N(veic)
– Emission = [mass/time] (g/hour)– Activity = [length/time] (km/day)– Emission factor = [mass/length] (g/km)– N = number of type of vehicle
Vehicular Fleet – Denatran e CETESB, 2012
Estado Capital Cap/Estado
SP 23286890 6795228 29,2
RJ 5212996 2326286 44,6
MG 8295192 1519438 18,3
ES 1481976 178463 12,0
PR 5954243 1371431 23,0
SC 3940467 290566 7,4
48171764 12481412 25,9
VEICULOS MOVIDOS A GASOLINA (VEIC 1)
42%
VEICULOS MOVIDOS A ETANOL (VEIC 2)
3%
VEICULOS MOVIDOS A FLEX (VEIC 3)
36%
CAMINHOES (DIESEL -VEIC 4A)
3%
ONIBUS URBANO (DIESEL - VEIC 4B)
3%
ONIBUS RODOVIARIO (DIESEL - VEIC 4C)
0%
TAXIS (GAS - VEIC 5)0%
MOTOS MOVIDOS A GASOLINA (VEIC
6A)12%
MOTOS FLEX (VEIC 6B)1%
TIPOS
Activity (source: SPTRANS)
Activity (km/day)
VEICULOS MOVIDOS A GASOLINA (VEIC 1) 41,09
VEICULOS MOVIDOS A ETANOL (VEIC 2) 41,09
VEICULOS FLEX (VEIC 3) 41,09
CAMINHOES (DIESEL - VEIC 4A) 109,58
ONIBUS URBANO (DIESEL - VEIC 4B) 164,38
ONIBUS RODOVIARIO (DIESEL - VEIC 4C) 164,38
TAXIS (GAS - VEIC 5) 0
MOTOS MOVIDOS A GASOLINA (VEIC 6A) 136,98
MOTOS FLEX (VEIC 6B) 136,98
Emission factors (g/km)
GAS ETA FLEX CAMINHOESMOTOS
GASMOTOS
FLEX
exa_co 5,43 12 5,13 4,95 9,15 9,02
exa_nox 0,34 1,12 0,32 9,81 0,132 0,129
exa_so2 0,029 0,014 0,021 0,61 0,0097 0,0093
exa_c2h5oh 0,079 0,253 0,166 0,61 0,079 0,305
exa_hcho 0,0089 0,011 0,0098 0,61 0,0152 0,0155
exa_ald 0,014 0,03 0,022 0,61 0,0164 0,0188
exa_pm 0,15 0,15 0,15 0,44 0,05 0,05
exa_voc 0,425 1,3 0,434 2,05 1,08 1,08
vap_voc 0,23 0,25 0,24 0 0 0
liq_voc 2 1,5 1,75 0 1,2 1,2
Cetesb (2010)IAG
VOC splitting (mol/100g)
VAPORS LIQUID EXHAUST VAPORS LIQUID EXHAUST VAPORS LIQUID EXHAUST
1 e_eth 0.025000 0.000000 0.282625 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
2 e_hc3 0.240000 0.213150 0.435206 0.000000 0.000000 0.000000 0.000000 0.000000 0.048995
3 e_hc5 0.450000 0.157299 0.158620 0.000000 0.000000 0.977799 0.000000 0.000000 0.057741
4 e_hc8 0.000000 0.192629 0.076538 0.000000 0.000000 0.000000 0.000000 0.000000 0.296627
5 e_ol2 0.038240 0.000000 0.341600 0.000000 0.000000 0.948944 0.000000 0.000000 0.318889
6 e_olt 0.200000 0.082045 0.143212 0.000000 0.000000 0.076220 0.000000 0.000000 0.385318
7 e_oli 0.460000 0.179849 0.161406 0.000000 0.000000 0.076220 0.000000 0.000000 0.000000
8 e_iso 0.000000 0.001146 0.004554 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
9 e_tol 0.085000 0.058353 0.140506 0.000000 0.000000 0.015079 0.000000 0.000000 0.235115
10 e_xyl 0.000000 0.119330 0.157456 0.000000 0.000000 0.039490 0.000000 0.000000 0.008360
11 e_ket 0.000000 0.000000 0.000083 0.000066 0.000066 0.016767 0.000000 0.000000 0.000012
12 e_ch3oh 0.000000 0.000000 0.001841 0.002200 0.002200 0.005539 0.000000 0.000000 0.000003
13 e_c2h5oh * 0.350000 0.605079 0.000000 2.170.610 2.170.610 0.000000 0.000000 0.000000 0.000000
14 e_hcho * 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.322544
15 e_ald * 0.000000 0.059507 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.075100
ETANOLGASOLINA DIESEL
Air quality model domain
Satellite view of earth at night
Night lights for horizontal distribution
Imagem e processamento de dados pela
NOAA's National Geophysical Data Center.
MASP
Horizontal distribution of emission
MASP
SMOKE - Sparse Matrix OperatorKernel Emissions
3 x 3 km2. Albuquerque, 2010
The International Environmental Database System (IED): 1 x 1 km2
The International Sustainable Systems Research Center (ISSRC) 2012
Com relação às emissões veiculares, está sendo utilizado um esquema de inclusão de fontes móveis para S. Paulo e Rio de Janeiro baseado nas seguintes informações:• dados de contagem veicular e velocidade dos veículos da Companhia de Engenharia de Tráfego (CET), (Desempenho do Sistema Viário Principal, Volume e Velocidade, 2012);• Contagem de veículos realizada no estudo de Túnel – IAG• Informações de inventário de fontes móveis CETESB e Estatísticas da Associação Nacional dos Fabricantes de Veículos Automotores –ANFAVEA• Fator de emissão calculado em experimentos de túneis• Fator de emissão COPERT 4 (Nziachristos y Samaras, 2009)• Informação Maplink• Dados Rede de Ruas (www.openstreetmap.org). Sistema de informação geográfica aberta. Contém uma descrição do tipo de rua segundo sua importância e função.
•
Vehicular sources – spatial distribution
Road net fromwww.openstreetmap.org
9km x 9km Horizontal Grid
Density (total road length/cell) Hypothesis: no. vehicles proportional to density
Temporal distribution
0
0,01
0,02
0,03
0,04
0,05
0,06
0,07
0,08
0,09
0,1
0 1 2 3 4 5 6 7 8 9 10 11 12 17 18 19 20 21 22 23
hrsplt_co hrsplt_no
CO e COVs
NO, NO2, SO2 e MP
Atmospheric emissions, transport, transformation, and deposition of trace gases
(Source: Aneja et al., 2003, 2006b)
Good emissions estimates are the start
of any environmental assessment
Operational WRF-CHEM
• 9 x 9 km2, 100 x 100 grid points, 27 vert levels• Timestep: 45 s• http://www.lapat.iag.usp.br/aerossol/wrf9/index.php
VEIN MODELSergio Ibarra PhD Thesis
CO Emissions (g at peak hour)
http://jornal.usp.br/wp-content/uploads/gCO.html
PM Emissions (g at peak hour)
http://jornal.usp.br/wp-content/uploads/gPM.html
• Thank you!