Air pollution modelling: an overview

Mihaela Mircea

UTVALAMB-AIR, National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Via Martiri di Monte Sole 4,

40129, Bologna, Italy

Outlines

Air pollution history, sources, effects

Measurements and air quality models

Air quality models types

Air quality assessment with models in Europe (FAIRMODE)

Eulerian air quality models (main characteristics, input data, validation)

Air quality study with AMS-MINNI over Italy: an example

Conclusions

Air pollution history

Air Pollution Has Been a Problem Since the Days of Ancient Rome “bubbles trapped in Greenland’s ice revealed that we began emitting greenhouse gases at least 2,000 years ago. …. The ice core data show that as far back as the time of the Roman Empire, human [activities] emitted enough methane gas to have had an impact on the methane signature of the entire atmosphere.” http://www.smithsonianmag.com/history-archaeology/Air-Pollution-Has-Been-a-Problem-Since-the-Days-of-Ancient-Rome-187936271.html#ixzz2lGiIqcac

What is the history of air pollution in London? “It is often assumed that air pollution in London is a recent phenomenon, however, legislation attempting to control air pollution was enacted as early as 1306. Coal smoke and its associated problems remained a matter of concern in London up until the late 20th century with the famous smogs of the 1950s and 60s.” http://www.londonair.org.uk/LondonAir/guide/LondonHistory.aspx

1273 Use of coal prohibited in London as being "prejudicial to health". 1306 - Royal Proclamation: Prohibiting artificers (craftsmen) from using sea-coal (a soft coal) in their furnaces. http://www.air-quality.org.uk

1272 - King Edward I of England bans use of “sea coal” 1377 – 1399 - Richard II restricts use of coal 1413 – 1422 - Henry V regulates/restricts use of coal

Air pollution sources: anthropogenic and natural

Air pollution effects: acid rain

Acid deposition occurs all the time, even on sunny days. Sulphur dioxide and nitrogen oxides combine with water in the atmosphere to create acid rain. Acid rain acidifies the soils and waters where it falls, killing off plants. Many industrial processes produce large quantities of pollutants including sulphur dioxide and nitrous oxide.

EUTROFIZZAZIONE

Eutrophication is when the environment becomes enriched with nutrients.

This can be a problem in marine habitats such as lakes as it can cause algal blooms.

The algae may use up all the oxygen in the water, leaving none for other marine life.

This results in the death of many aquatic organisms such as fish, which need the oxygen in the water to live.

The bloom of algae may also block sunlight from photosynthetic marine plants under the water surface.

Some algae even produce toxins that are harmful to higher forms of life.

Air pollution effects: eutrophication

Air pollution effects: global warming

Air pollution effects: human health

Atmospheric processes in air quality models

“The spatial and temporal coverage of model data typically far exceeds that of measurement data; the cost of simulating air pollution concentrations with a model is low compared with the equipment and personnel costs to operate a network of measurement stations; and models permit analysis of future projections and implications of air quality management policy.”

(Holloway et al., Energy for Sustainable Development, 2005 )

Why to use models?

“The spatial coverage of monitoring is usually limited. Modelling can potentially provide complete spatial coverage of air quality. Modelling can be applied prognostically. I.e. it can be used to predict the air quality as a result of changes in emissions or meteorological conditions. Modelling provides an improved understanding of the sources, causes and processes that determine air quality. Modelling is an important tool on which to base action plans, both short and long term.”

(Guidance on the use of models for the European Air Quality Directive , ETC/ACC report)

Air pollution: measurements and models

What is a model?

It is a simple representation of the world.

This is achieved via application of the processes like:

Generalization:

The process of treating different entities as if they were the same for the sake of simplifying the description.

Distortion:

The process of changing the representation for the sake of simplifying the description, e.g., treat two serial reactions as if they were one.

Deletion:

The process where by entities or processes are omitted from the description to simplify the description.

Nescience:

The unintended process whereby entities or processes are omitted from the system because of lack of knowledge.

ETC

Gaussian plume model: This model was applied for the main purpose of calculating the maximum ground level impact of plumes and the distance of maximum impact from the source. Lagrangian model: an air parcel (or “puff”) is followed along a trajectory, and it is assumed to keep its identity during its path. Eulerian model: the area under investigation is divided into grid cells, both in vertical and horizontal directions.

Types of air quality models

Air quality model components and input

Model components Transport and dispersion Removal Chemical and physical transformations

Model input

Emissions Meteorology

Boundary conditions

Gaussian plume model

Gaussian plume model: puff models

Gaussian models

NO2 guidance document

http://fairmode.ew.eea.europa.eu/guidance-use-models-wg1

Limitations in the use of Gaussian models:

- they are intended for use where there are no

obstacles, e.g. buildings, surrounding the road.

- they are suitable for chemically inactive species,

otherwise parameterised chemistry must be

implemented separately.

- they perform optimally when the stability is in

the range of stable to unstable. Highly stable or

highly unstable conditions may not be well

modelled using the standard slender plume

approximation

Lagrangian particles models

STILT ( Lin et al., 2003)

ATTILA (Reithmeier and Sausen, 2002)

STOCHEM (Collins et al., 1997)

NO2 guidance document

http://fairmode.ew.eea.europa.eu/guidance-use-models-wg1

an air parcel (particle or “puff”) is followed along a trajectory, and

is assumed to keep its identity during its path.

each particle represents a particular mass of one or several

pollutants emitted from a given source.

the concentration is computed by counting particles in a user

defined volume (e.g. the cell of a regular grid).

a large number of particles are necessary to derive concentration

values with a high statistical accuracy and this implies that

computation time is usually significantly higher than for the

Gaussian models.

flow and turbulence fields have to be provided either by Eulerian

models (e.g. CFD models in built-up areas) or by meteorological

pre-processors (e.g. in flat terrain without significant influence of

buildings).

chemical conversions of first order (exponential decay of the

particle mass) can be modelled directly, likewise wet and dry

deposition and sedimentation processes. More general chemical

reactions cannot be carried out directly with these models but

some of these models may also be used for odour calculations.

Eulerian model

The Eulerian grid model uses a fixed coordinate system with respect to the ground while Lagrangian trajectory model employs a moving frame of reference . The three-dimensional Eulerian grid modeling has the ability to better and more fully characterize physical and chemical processes in the atmosphere. These models often are referred to by other names, including chemical transport models (CTM), air quality models, photochemical air quality models, air pollution models, emission-based models, source-based models, source-oriented models, source models, first-principles models, and comprehensive models.

Eulerian models in use in Europe

(Kukkonen et al., 2012)

http://www.mi.uni-hamburg.de/Model-Inventory.5554.0.html

Detailed description of an Eulerian model structure

Radiation

Gas phase chemistry

Jiminez et al. (2003)

Luecken et al. (2008)

Aerosols

Aerosol model structure: an example

FARM

Modal

Ni, Dpgi, i

Gas precursors: HNO3, NH3, H2SO4

toluene, xylene

isoprene, monoterpene

condensation/evaporation

coagulation

n

u

cl

e

a

ti

o

n

AERO3 (Binkowski and Roselle, 2003)

ISORROPIA (Nenes et al., 1998)

SORGAM (Schell et al., 2001)

Aerosol models

Aerosol dynamics

MADE -Ackerman, Atm Env 1998, ECHAM4

MADRID -Zhang, JGR 2004, CMAQ

M7 -Vignati, JGR 2004, ECHAM5, Stier, ACP 2005

GLOMAP -Spracklen, ACP 2005

MAM -Sartelet, Sportise, AerSciTechn 2006

HYDN -Feng, JGR 2007

ORISAM -Guillaume, Tellus B 2007

MOSAIC -Zaveri, JGR 2008

MATRIX -Bauer, ACP 2008

AERO3 – Binkowski et al. (, 1995, 2003)

Thermodynamic equilibrium models

ISORROPIA - Nenes et al. (1998)

AIM http://www.aim.env.uea.ac.uk

MARS Saxena et al., (1986)

UHAERO (Amundson et al., 2006)

Secondary organic aerosol models

SORGAM (Schell et al., 2001)

SOAP (Strader et al., 1998)

VBS based models in North America

(Robinson et al., 2007; Lane et al.,

2008; Shrivastava et al., 2008; Murphy

and Pandis, 2009),

and very recently in Europe (Simpson et

al., 2009; Fountoukis et al., 2011)

Sea salt models

Dust models

M7: size-resolved aerosol microphysical model

Vignati et al. (2004); Stier et al. (2005)

Dry deposition of gases and aerosols

(Zhang et al., 2003)

Ra - the aerodynamic resistance

Rb - the quasi-laminar sublayer resistance above the

canopy

Rc - the overall canopy resistance (Rc).

Rc= Rst+ Rns

Rst - stomatal resistance with its associated mesophyll

resistance (Rm)

Rns - non-stomatal resistance.

Rns can be further decomposed into resistance to soil

uptake, which includes in-canopy aerodynamic

resistance (Rac) and the subsequent soil resistance (Rg),

as well as resistance to cuticle uptake (Rcut).

Dry deposition velocity

Wet removal of gases and aerosols in- and below-cloud

Wet deposition refers to processes by which pollutants are scavenged by atmospheric hydrometeors (cloud and fog drops, rains).

(Zhang et al., 2004)

C/ t=- C

C – concentration

t – time

– scavenging coefficient

MINNI - AMS: preprocessore emissivo

Emissioni Inventario Nazionale per provincia e settore + puntuali

Esempio: Emissioni NOx

Macrosettore 7 (traffico stradale)

Tutti i settori

Model evaluation

Operational evaluation

● How do the predicted concentrations compare to observed concentration data: determine errors and biases?

Diagnostic evaluation

● Are error/biases due to model input or

modelled processes?

● Can the responsible process(es) be

isolated?

Dynamical evaluation

● Can the model capture changes related to

meteorological events or variations?

● Can the model capture changes related to

emission reductions?

Credits: Massimo D’Isidoro

Operational Evaluation

Correlation coefficient Root Mean Square Error Index Of Agreement

Determine errors and biases by means of statistical scores From FAIRMODE: http://fairmode.ew.eea.europa.eu/

Relative Directive Error Relative Percentile Error

Mean Fractional Error Mean Fractional Bias

Credits: Massimo D’Isidoro

Operational Evaluation

NO2 Highly variability (space/time). Maxima valuated on hourly basis

depends on pollutant, legislation, measurement methodology,...

Particulate Matter (PM10) Evaluated on daily average basis

O3 Defined seasonal/diurnal cycle 8h running mean daily maxima

CO Almost Passive tracer 8h running mean daily maxima

Credits: Massimo D’Isidoro

2D validation:

- meteorological statistics ISPRA-SCIA

- meteorological data from Basilicata region

Validation of meteorology: AMS-MINNI

Meteorological data from Trisaia

campaign:

- data from VAISALAMAWS00

- humidity and temperature profiler

HATPRO

Credits: Lina Vitali

What types of models can be used for air quality studies?

The model has the appropriate spatial and temporal resolution for the intended application. The model is adequately validated for the particular application and well documented. The model contains the relevant physical and chemical processes suitable for the type of application, the scale and the pollutant for which it is applied. The relevant emission sources for the application are adequately represented. Suitable meteorological data is available.

Model guidance (v6.2, FAIRMODE –WG1) in support to application of the European Air Quality Directive (50/2008)

Model guidance (v6.2, FAIRMODE –WG1) in support to application of the European Air Quality Directive (50/2008)

Model guidance (v6.2, FAIRMODE –WG1) in support to application of the European Air Quality Directive (50/2008)

Model guidance (v6.2, FAIRMODE –WG1) in support to application of the European Air Quality Directive (50/2008)

Italian case study in the framework of MINNI project

Sistema modellistico AMS-MINNI Atmospheric Modelling System of MINNI project (AMS-MINNI)

www.minni.org

RAMS, LAPS

Emission Manager

SURFPRO Meteo

Parametri di turbolenza

FARM

Emissioni

Campi ECMWF Dati Locali Inventari

(ISPRA ed EMEP)

Info spaziali e temporali

Concentrazioni e Deposizioni

Campi EMEP

IC e BC

Sottosistema METEO

Sottosistema EMISSIVO

Sottosistema CHIMICO-FISICO

Flexible Air quality Regional Model (Farm) http://air-climate.eionet.europa.eu/databases/MDS/

Transport +

diffusion

Meteorology

Dry and wet gas deposition

Initial and boundary conditions:(aerosol)

AEROSOL MODELS:

AERO3 ISORROPIA SORGAM

GAS CHEMISTRY MECHANISM:

SAPRC90

Aerosol emissions

Gas emissions

Heterogeneous chemistry

Emission model: sea salt

Initial and boundary conditions (gas)

Emission model: BVOC

Land use and

orography

Dry and wet aerosol deposition

Configurazione simulazioni: 2003, 2005, 2007

METEOROLOGIA: 20 e 4 km risoluzione spaziale orizzontale ic/bc da ECMWF: 50km ogni 6hrs

QUALITA DELL’ ARIA: 20 e 4 km risoluzione spaziale orizzontale ic/bc from EMEP/MSC-W: 50km ogni 3h

EMISSIONI: -antropiche: ISPRA inventario nazionale “top-down” + EMEP -biogeniche: ISPRA2005 per Italia e Guenther et al. (2005) per gli altri paesi comprese nel

Ozono (O3): stazioni rurali 2003 2005 2007

g/m3

aumento numero stazioni

20 km

4 km

Ozono (O3): stazioni urbane 2003 2005 2007

g/m3

20 km

4 km

Ozono (O3)

Media annuale del valore medio massimo giornaliero su 8 ore sulla base delle medie consecutive di 8 ore.

Materiale particolato (PM10): stazioni rurali

2003 2005 2007

g/m3

20 km

4 km

Materiale particolato (PM10): stazioni urbane

2003 2005 2007

g/m3

20 km

4 km

Materiale particolato (PM10)

Media annuale del valore medio giornaliero.

Diossido di azoto (NO2): stazioni rurali

2003 2005 2007

g/m3

20 km

4 km

Diossido di azoto (NO2): stazioni urbane

2003 2005 2007

g/m3

20 km

4 km

Diossido di azoto (NO2)

Media annuale del valore medio orario.

O3: correlazione

2003

Simon et al., 2012 (Atmos. Environ)

2005

2007

PM10: diagramma di Taylor

Chemel et al., 2010 (Atmos.Environ)

Cerchi: stazioni rurali Crocette : stazioni urbane Quadrati: stazioni suburbane

EURODELTA III: European AQ models intercomparison

NO2: diagramma di Taylor

Cerchi: stazioni rurali Crocette : stazioni urbane Quadrati: stazioni suburbane

EURODELTA III: European AQ models intercomparison

Conclusioni caso test

Il sistema modellistico AMS-MINNI riproduce relativamente bene:

- la distribuzione spaziale delle concentrazioni di O3, PM10, NO2

- la variabilità interannuale osservata in tutte le stazioni di fondo (rurale, suburbano, urbano)

L’aumento della risoluzione spaziale delle simulazioni migliora l’accordo tra le concentrazioni simulate e osservate alle stazioni di monitoraggio, e produce mappe di concentrazione più accurate per stimare l’esposizione della popolazione agli inquinanti atmosferici nocivi.

I risultati del modello sono in linea con i risultati degli altri modelli utilizzati in Europa, USA e Canada.

http://www.va.minambiente.it/condivisione/datiminni.aspx

Conclusions

Only an air quality/atmospheric scientist may offer problem-specific advice on how to best incorporate model output into the health problems and what model structure/model input may be suited to a specific research initiative.

Only an air quality model can describe the chemical and physical state of the whole atmosphere at any time.

Only an air quality model can predict the effect of emissions changes on future pollution.

Air quality forecast in Italy and Europe

Thank you for your attention!