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Modelling the contributions of major UK industrial sources to regional air quality with Models 3. Ye, Yu, Ranjeet Sokhi, Douglas R Middleton and Bernard Fisher Centre for Atmospheric and Instrumentation Research (CAIR) Met Office. Objectives.

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Modelling the contributions of major uk industrial sources to regional air quality with models 3

Modelling the contributions of major UK industrial sources to regional air quality with Models 3

Ye, Yu, Ranjeet Sokhi, Douglas R Middleton and Bernard Fisher

Centre for Atmospheric and Instrumentation Research (CAIR)

Met Office


Objectives
Objectives to regional air quality with Models 3

  • To examine the use of advanced 3D air quality models as a tool for assessing the potential of industrial emissions to create secondary pollutants under different meteorological conditions;

  • To give advice on the application of the Chemical Reactivity Index method in regulation.


Method
Method to regional air quality with Models 3

ECMWF Reanalysis (1 degree resolution, every 6 hour)

MM5

Meteorological Model

MCIP

Meteorology-Chemistry

Interface Processor

CORINE land cover data (100 m resolution)

CMAQ

Community Multiscale Air Quality Modelling System

SMOKE

Emission processor

Biogenic emission

Hourly 3-D Gridded Concentrations

EMEP (A,M)

NAEI (A,M,P)

EPER (P)

reformat

MM5/CMAQ Modelling System


Spatial distribution of nox emissions processed by smoke
Spatial distribution of NOx emissions processed by SMOKE to regional air quality with Models 3

Domain 1- 81 km

Domain 3- 9 km


Experiment design
Experiment design to regional air quality with Models 3

  • Simulation periods (three episodes):

  • a. 12 UTC 22 Jun -12 UTC 28 Jun 2001: Summer O3 and NO2 episode (T3)

  • b. 00 UTC 09 Dec – 00 UTC 15 Dec 2001: Winter NO2 episode (T1 &T2))

  • c. 00 UTC 31 Aug. – 00 UTC 04 Sept. 1998: SO2 episode (T1&T2)


Locations and indicative emissions of the 9 stacks
Locations and indicative emissions of the 9 stacks to regional air quality with Models 3

Annual emissions (tonne)


Cmaq model configuration
CMAQ Model Configuration to regional air quality with Models 3

Initial and boundary conditions:

Monthly averaged concentrations of species from global 3-D chemical-transport model STOCHEM

Chemical mechanism: CB-IV

26 vertical layers

For Sep. 1998 & Dec. 2001

For June 2001


Model evaluation june 2001 episode
Model evaluation to regional air quality with Models 3(June 2001 episode)


Observed concentrations june 2001
Observed concentrations (June 2001) to regional air quality with Models 3

Hourly NO2 (left) and O3 (right) concentrations during the June 2001 episode at selected sites.


Air quality stations
Air quality stations to regional air quality with Models 3


Temporal variations 23 jun 28 jun 01
Temporal variations (23 Jun –28 Jun 01) to regional air quality with Models 3


Scatter plots of observed vs modelled o 3 and no 2 concentrations for 3 km resolution
Scatter plots of Observed vs. Modelled O to regional air quality with Models 33 and NO2 concentrations for 3 km resolution

Fraction of predictions within a factor of 2 of observations

O3

NO2

53%

82 %


Estimating the contribution of industrial point sources to near surface pollutant concentrations
Estimating the contribution of industrial point sources to near surface pollutant concentrations


Contribution of industrial point sources to near surface o 3 june 2001
Contribution of industrial point sources to near surface near surface pollutant concentrationsO3 (June 2001)

daily maximum (top); daily maximum 8-h mean (bottom)


Contribution of industrial point sources to near surface no2 daily maximum no 2
Contribution of industrial point sources to near surface NO2 near surface pollutant concentrations (Daily maximum NO2)

June 2001 (top); Dec. 2001 (bottom)


Contribution of industrial point sources to ambient pollution levels daily maximum so 2
Contribution of industrial point sources to ambient pollution levels (Daily maximum SO2)

June 2001 (top); Sept. 1998 (bottom)


Percentage contribution of all uk point sources to near surface pollutant concentrations
Percentage contribution of all UK point sources to near surface pollutant concentrations

Percentage contribution=(Exp. A-Exp. B)/Exp. A


Conclusions
Conclusions surface pollutant concentrations

  • CMAQ is able to give information on the quantity of point source contributions to near surface pollutant concentrations and its spatial distribution. These information will help the Agency to identify the most affected areas and the most important pollutant to regulate.

  • On average, point source emissions have the largest contribution to near surface SO2 concentrations, followed by NO2. The overall contribution of point source emissions to ground level O3 is very low and negative especially for the winter episode.

  • Weather and meteorological conditions can significantly affect the degree of contributions from point source emissions, suggesting that regulatory control of emissions from industrial sources is essential to abate pollution levels under particular meteorological conditions.


Plume chemistry
Plume Chemistry surface pollutant concentrations


Evolution of o 3 and no 2 in plumes from two point sources 3km resolution
Evolution of O surface pollutant concentrations3 and NO2 in plumes from two point sources (3km resolution)


Plume chemistry 3km resolution
Plume chemistry (3km resolution) surface pollutant concentrations


Plume chemistry 3km resolution1
Plume chemistry (3km resolution) surface pollutant concentrations


Plume chemistry 3km resolution2
Plume chemistry (3km resolution) surface pollutant concentrations


Plume chemistry 3km resolution3
Plume chemistry (3km resolution) surface pollutant concentrations


Plume chemistry 3km resolution4
Plume chemistry (3km resolution) surface pollutant concentrations


Voc nox and h2o2 noz 3km resolution
VOC/NOx and H2O2/NOz (3km resolution) surface pollutant concentrations

VOC= PAR+2OLE+2ETH+2ALD2+7TOL+8XYL+5ISOP+FORM

NOz = PAN + HONO + HNO3 + NO3 + N2O5


Conclusion
Conclusion surface pollutant concentrations

  • The O3 and NO2 concentrations in plumes simulated by CMAQ captured several qualitative behaviour of chemistry in the plume that is common in NAME III results. For example the formation of raised NO2 in the plume at night, the removal of ozone in the plume region by titration with NO, and the formation of ozone further downwind point sources if sufficient hydrocarbons are available.


Hourly no2 vs nox hourly no2 nox vs nox
Hourly [NO2] vs [NOx] surface pollutant concentrationsHourly [NO2]/[NOx] vs [NOx]


No2 versus nox hourly
[NO2] versus [NOx] (hourly) surface pollutant concentrations

June, 2001

Kingsnorth power station


No2 nox versus nox hourly

June, 2001 surface pollutant concentrations

[NO2]/[NOx] versus [NOx] (hourly)

Kingsnorth power station


No2 versus nox hourly1

Dec., 2001 surface pollutant concentrations

[NO2] versus NOx (hourly)

Lindsey oil refinery


No2 nox versus nox hourly1

Dec., 2001 surface pollutant concentrations

[NO2]/[NOx] versus [NOx] (hourly)

Lindsey oil refinery


No2 versus nox hourly2

Sept. 1998 surface pollutant concentrations

[NO2] versus NOx (hourly)

Lindsey oil refinery


No2 nox versus nox hourly2

Sept. 1998 surface pollutant concentrations

[NO2]/[NOx] versus [NOx] (hourly)

Lindsey oil refinery


Conclusions1
Conclusions surface pollutant concentrations

  • The CMAQ results confirm the sensitivity of [NO2] and [NO2]:[NOx] to day or night seen in NAME III results and extends it to include the dependence on weather and meteorological conditions

  • By selecting representative background [O3], the enclosing curves derived from NAME III encompass most of the data point of CMAQ results.

  • The results also show that different model runs all tend to suggest that the empirical curves from urban monitoring data are tending to underestimate the amount of NO2 presented in model simulations


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