dmug 2016 - alun roberts-jones, environment agency

Lagrangian particle modelling for long range ecological impacts

Presentation to DMUG Alun Roberts-Jones Environment Agency Air Quality Modelling and Assessment Unit 19th April 2016

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Outline of presentation Typical dispersion model types Long range Lagrangian model Case study – impact of ESI plant on habitat sites Results – modelling comparison to monitoring Case study conclusions Complex long range models future in regulation

New generation Gaussian plume models Models dispersion assuming a Gaussian distribution Skewed Gaussian distribution under convective conditions

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Schematic of the Gaussian plume (Schulze and Turner, 1996)

Emission rate constant over each hour Hourly sequential meteorological data Turbulent diffusivity

Boundary layer depth Monin-Obukov length

Wind speed and direction constant in space and time No change in wind direction over distance Accurate to 10 - 15 km 4

New generation Gaussian plume models

Gaussian Puff Models Lagrangian Particle Models Eulerian Advection and Dispersion Models Computational Fluid Dynamics (CFD)

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Other types of dispersion models

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NAME Lagrangian Model Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME) Stochastic Lagrangian Model Accounts for various atmospheric processes 3D model atmosphere

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NAME applications

Emergency response

Nuclear incidents

Volcanic Ash Services

Source: Met Office

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Case study part of ESI sector review Habitat Regulations assessment in 2007

Review of Consents for including Habitats Directive into IPPC

Concerns about deposition and ecological effects Opt-in installations given an improvement conditions to identify and monitor at certain sensitive Natura 2000 sites Ecological monitoring programme Linked to ESI sector permit reviews – Success? Continued monitoring required? Project to analyse data, and predict contribution from some of the ESI facilities

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Source and habitat locations

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Modelling assumptions Long range NAME modelling

NAME III version 6 Emissions of NOX and SO2 Emissions data – site specific hourly time varying emissions 2012 Efflux parameters – site specific Plume rise Dry deposition, includes plume depletion Meteorological data – NWP UM 4km resolution 2012 Receptors – gridded receptors over each habitat site Outputs – hourly and annual concentration and dry deposition outputs

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Sensitivity analysis Number of particles Sync time Near source scheme

Plume rise

Dry deposition Time varying emissions v Flat annual emissions

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Annual mean NOX results

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NOX PCs comparison

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Nutrient nitrogen deposition comparison

0.2 0.13 0.1 0.18

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Annual mean SO2 results

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SO2 PCs comparison

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Acid deposition comparison

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Case study conclusions NOX

Combined modelled contribution only represents a small proportion relative to measured concentration. NOX dominated by other sources, eg traffic and more localised small combustion plants

SO2 Combined modelled contribution similar to measured value. Power stations likely to be a more dominant contributor to SO2 at the habitat sites Modelled contribution and measured values well below critical level

Deposition Approximation using AQTAG06 method Nutrient nitrogen and acid (N + S) – combined contributions small relative to measured and APIS values Dominated by other sources of N deposition.

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Modelling helped underpin decision Can not confidently attribute changes in measured values to emissions from ESI facilities:

Small individual process contributions from each of the plant Modelling and monitoring uncertainties Inter-annual variation

Monitoring data Useful to determine current levels and status of habitat sites Useful to compare and confirm modelling conclusions

Continued monitoring Useful scientific exercise for reporting on site condition Unlikely to provided further insight on ESI emissions on the sites

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Long range models – future use? Not routinely used for regulation Useful tool in regulatory case studies, understanding impacts which can help underpin decision making Complex modelling provides valuable insight in situations where simpler Gaussian models are limited

Large sources with longer range of impact No change to current regulatory stance or modelling policy

The Environment Agency does not favour or prescribe the use of any particular model Gaussian models still widely applicable for regulatory purposes