01 Establish a modelling and ecosystem impact assessment plan

Stage 3 builds upon the work conducted in Stage 2, which evaluated the "potential" for risk. In this stage, methodologies are applied to assess actual impacts or damages, including an analysis of economic losses where applicable. Additionally, more in-depth evaluations of sensitivity can be performed using an extended time series of pollution data and a better understanding of the ecosystems present in your jurisdiction, particularly focusing on their characteristics that influence sensitivity. 
To conduct a national-scale ecosystem services assessment based on patterns of deposition and concentration, it is essential to utilize regional-scale (full airshed) chemical transport modeling results, which are being developed simultaneously (See Source Attribution Guidance Stage 3, Steps 6-9). Therefore, establishing partnerships with air quality modelers and those conducting modeling in Stage 3 under the "Source Attribution" guidelines is vital. By working collaboratively, you can ensure that the relevant outputs are integrated into post-processing routines, thereby enhancing the accuracy and comprehensiveness of your assessments.  

02 Identify comprehensive Ambient Air Pollution input data

Building on the assessments from Stage 2, compile a list of critical natural capital and ecosystem services that are likely to be impacted by air pollution. Gather the additional input data necessary for conducting damage assessments, supplementing the ecosystem data already collected in Stage 2. This may include national-level statistics on arable agricultural production, timber harvest data from forestry, as well as data on semi-natural and natural biodiversity, including habitat types, species composition, and distribution, along with surface water distribution information. Furthermore, specify the air pollution concentration and deposition data required for assessments, such as hourly ozone (O3) levels, hourly meteorological data, annual nitrogen (N) and sulfur (S) deposition figures, and information on wet and dry deposition, nitrogen oxides (NOx), ammonia (NH3) and ammonium (NH4+), and nitrogen deposition rates. 

03 Identify Ozone and Crop Data

Identify the input data necessary to estimate ozone-induced crop yield losses. This should encompass the spatial distribution of dominant arable crop species, along with their specific growing seasons and national-level production statistics. Collect ozone concentration data, which can be sourced from site-specific monitoring or, preferably, modeled data. Additionally, identify concentration-based and flux-based response functions for the primary crop types in the country, referencing Mills et al. (2007) and the upcoming update by Hayes et al. (in submission), as well as the UNECE Air Convention Coordination Centre for Effects’ Mapping Manual. Determine relevant ozone metrics employed in dose-response relationships, such as M7, AOT40, and Phytotoxic Ozone Dose (PODy), which is defined as the accumulated amount of ozone that enters plant leaves through stomata over a certain threshold of Y. You may also consider utilizing tools like the TOAR Data Portal and webDO3SE or the DO3SE model to calculate PODy values for use in conjunction with flux response relationships. 

04 Ambient Air Pollution and Forest Data

Identify the input data needed to estimate either AOT40 or stomatal ozone flux for key forest species within your jurisdiction, as well as the exceedance of critical loads for acidification and eutrophication. Collect data on forest distribution, including the spatial distribution of dominant tree species—deciduous, coniferous, and tropical—as well as their growth periods. Convert ozone concentration data into AOT40 and/or PODy metrics to facilitate analysis. Gather information on timber harvest and net annual increment to determine whether sufficient data is available for estimating net annual biomass loss, as referenced in Karlsson et al. (2025). Additionally, identify the nitrogen (N) and sulfur (S) critical loads for key forest species in your jurisdiction to support exceedance mapping. Finally, develop maps illustrating the exceedance of nitrogen and sulfur deposition, overlaying them with forest distribution maps. This should extend to additional species and include a time series analysis from the past five to ten years, building on work conducted in Stage 2. 

05 Ambient Air Pollution and Biodiversity Data

Identify the input data necessary to estimate the exceedance of air quality limits aimed at protecting biodiversity from ozone, acidification, and eutrophication. Collect extended land cover and land use distribution data related to biodiversity, supplementing any existing data described in Stage 2. Convert ozone concentration data into the AOT40 metric for more accurate assessments. Identify critical load values for nitrogen (N) and sulfur (S) deposition, along with ozone critical levels, for a broader range of key ecosystems within your jurisdiction. Finally, develop maps that illustrate the exceedance of nitrogen and sulfur deposition, as well as ozone concentrations, incorporating a time series of 5 to 10 years alongside biodiversity maps to provide a comprehensive understanding of the impacts on ecosystems.

06 Ambient Air Pollution and Aquatic Data

Identify the tools and input data required to estimate the exceedance of air quality limits that protect aquatic ecosystems from acidification and eutrophication. Begin by collecting data on surface water distribution within your jurisdiction. Next, determine the critical loads for nitrogen (N) and sulfur (S) deposition specific to aquatic environments. Finally, develop exceedance maps that illustrate nitrogen and sulfur deposition alongside surface water distribution, ensuring that these maps incorporate an extended time series to provide a comprehensive overview of trends and potential impacts on aquatic ecosystems over time (5 to 10 years). 

07 Document visibility impairment attributable to air pollution

To assess air pollution impacts on visual range and visibility, begin by gathering relevant data on particulate matter (PM2.5) concentrations -- if possible, consider speciated fine particle concentrations (See Source Attribution Guidance Stage 3, Step 2 and 3) to enable calculation of visibility impacts for species with different scattering cross sections (See IMPROVE algorithm linked below). Aerosol optical depth may be available through global networks or as measured at airports. Utilize monitoring tools like visibility sensors and AERONET for ground-based measurements. Incorporate satellite data from resources like MODIS to analyze regional air quality trends. Additionally, employ models such as the AERMOD dispersion model to simulate local visibility impacts. Ensure your datasets include historical information to evaluate trends over time. By combining these tools and data sources, identify acceptable levels of aerosol pollution that maintain appropriate levels of visibility for your jurisdiction. Develop exceedance maps of aerosol pollution that will limit visibility to the defined thresholds. 

08 Monetize losses of ecosystem services

Estimating monetized losses of ecosystem services can be effectively approached using simple spreadsheets and mapping techniques. Begin by quantifying economic losses from ozone-induced crop losses by applying either the AOT40 or PODy metrics, leveraging established dose-response relationships for key agricultural crops. Collect data on affected crop yields and market prices to calculate overall economic impacts.
Consider expanding your assessment to include other ecosystem impacts suitable for monetization, such as declines in timber productivity, losses in fish populations, and damage to recreational resources, as suggested by Jones et al. (2012). For each impact, gather relevant data on ecological changes, economic value, and potential mitigation costs. Visualizing this information through mapping can enhance the understanding of spatial distributions and highlight areas most affected. Ultimately, this holistic approach will provide a clearer picture of the overall economic implications of air pollution on ecosystem services and inform effective policy decisions.

09 Prepare for Stage 4

To prepare for the next stage of analysis, begin by outlining the research methods necessary for validating modeled air pollution concentrations and deposition results in rural locations. This involves comparing model outputs with data from additional air quality monitoring stations strategically placed in these areas. Ensure that you gather comprehensive ecosystem service and natural capital data to assess the potential impacts accurately.
Next, develop a detailed definition of the impacted ecosystem services, focusing on key areas such as crop yields and timber harvests. This may include identifying specific crops and tree species affected by air pollution. Consider exploring various methodologies for quantifying impacts on natural capital accounting, which may involve monetary valuation, changes in biodiversity, and ecosystem functionality. By integrating these elements into your analysis, you will create a robust framework that not only assesses air pollution impacts but also informs management and policy decisions aimed at protecting valuable ecosystem services and natural capital.