AQ GEO Task - Unused Texts
A significant task of the AG is to assess, evaluate and comment on the proposed scope of the AQ SBA EO requirements. The initial scope proposed by the Analyst group is given below.
The composition of the atmosphere plays a significant role in at least three societal benefit areas defined by GEO: Climate, Disasters and Human Health. In Climate, atmospheric composition influences the energy budget of the Earth System, most notably through greenhouse gases and aerosols. The atmospheric observations, as they pertain to Climate, do influence air quality; however, they will be beyond the scope of this report as they are more directly addressed elsewhere. Among the Disasters, wild-land fires, dust storms, volcanic eruptions and severe pollution events have significant effect on atmospheric composition and through that on human health and well being. These causes will be considered within the scope of this EO needs assessment. The Human Health SBA will be the primary application of this EO needs assessment.
While the application is the protection of Human Health, the focus of this meta-analysis will be on the Earth Observations that are relevant to human health. Morbidity, mortality, and other human health observations will not be assessed. The EOs of particular interest will include the concentration of and population exposure to pollutants near the Earth surface, where people live. The spatial domain of primary interest will be the continents with emphasis on regions with highest population density. The vertical distribution will be considered as it relates to pollutant emission sources and transport. The temporal domain may extend over decades for the epidemiological studies, to short-term, hour-scale impacts of natural or anthropogenic pollution events. Geographic areas with high population densities will also be of high priority. Air pollutants over remote locations over land or ocean will be considered as they pertain to the identification of air pollutant sources and their transport.
The types of Earth observations will include ground-based in-situ monitoring of gases and aerosol particles, passive remote sensing (satellites), active remote sensing (lidar) and conceivably some aircraft sampling. Air quality models on local, regional and global scales will be considered as they contribute to the understanding and forecasting of air pollution that impact on human health. The focus on specific air pollutants will differ regionally: ozone and fine aerosols for the industrial countries and additional focus on biomass and waste-burn (urban and agriculture) smoke, traffic emissions and windblown dust in the developing countries (in addition to motor vehicle, industrial, and waste-combustion emissions [redundant?]). The above is not a prioritization per se, but guidance for the prioritization process. Note to AG: Feedback on this Scope from the AG will be particularly helpful, since it will guide both the selection of the relevant publicly available documents, as well as the subsequent prioritization of the required Earth observations. The suggestions regarding how to narrow the Scope wil be particularly welcome.
J. Fishman: One important website is the IGOS/IGACO report for the integrated observing of trace gases and aerosols: http://www.igospartners.org/Atmosphere.htm J. Meagher: I'm not sure I understand how you intend model products to factor into an analysis of earth observations. In my opinion there has been a disturbing trend to talk about model output as "data", or as a substitute for real observations. If the intent is to use models as a way to determine the adequacy of the current or proposed observational networks, I think that is appropriate. If the intent is to use models as another source of "observations" I think that is totally inappropriate. This section needs to be more clearly written so the use of models, in this context, can be clearly understood.
I don't quite know how to do it, but there needs to be more emphasis on observations whose quality are clearly quantified. You mentioned data quality as an important parameter earlier in the report. Is there some way we can be sure that more emphasis is placed on defining data quality (accuracy, precision, specificity, etc.)? Obviously this is a pet peeve. There are lots of data out there which are of very poor quality, including some of the US networks. The presence of these data actually, in my opinion, cause more ham than good.
The documents selected for this meta-analysis will include multiple sources, such as publicly available consensus reports and open publications by authoritative contributors including academic and other public research contributions (library-stored thesis or any other grey literature, especially in developing countries). The document identification will be performed by the Analyst Group, the Advisory Group as well as other experts. The Analyst Group will focus on the identification of consensus documents prepared by major national and international organizations, including the World Health Orgnization (WHO), US Environmental Protection Agency (EPA), European Monitoring and Evaluation Programme (EMEP), and Air Pollution Information Network Africa (APINA). The selection of journal and other publications will be focused on multi-author review articles relevant to EO needs. An expanding list of publications under consideration is given in the project website and a subset in the GEO Task Website.
The AG is requested to point out documents referring to EO needs for Air Quality. Of particular interest would be documents that discuss the EO needs in developing countries where the health impact may be dominated by non-industrial sources and the relevant observations are particularly scarce.
The identification of documents, the extraction of the relevant Earth observations and their prioritization is a highly subjective activity. Also, there are currently no generally accepted methods for conducting this process. For this reason, the leads for GEO Task US-09-01a have strongly encouraged the Analysts and the AGs to be inventive and resourceful in performing this delicate process.
Similar document analyzes and earth observation priority setting already conducted in other SBAs provide methods that will be considered in defining the method for AQ SBA, including:
J. Meagher: I didn't see any discussion of analytical methods or prioritization criteria so I assume that is something the group will work on.
This step of identifying, reading and analyzing the reports, documents and recommendations is in progress. Records of the activities are kept on the open project wiki website.
Interested members of the AG and others may examine the current state of the project including the project plan, chronological list of project events, interactions with the Analyst of other SBAs in this GEO task etc
Additional Comments from Kjetil – No comments. In the report need to include sections on each of the EO table columns, e.g. timeliness/latency
Moved from Report
The analysis used literature reviews, internet searches, and Advisory Group recommendations to identify documents with information related to observation requirements. International working groups and intergovernmental agencies have previously compiled information about global Earth observation requirements for climate, and their reports are included in the analysis. These include reports by the World Meteorological Organization (WMO) and experts working under the auspices of the Global Climate Observing System (GCOS). The documents also include assessments by the Intergovernmental Panel on Climate Change (IPCC) of the United Nations Framework Convention on Climate Change (UNFCCC). Reports by regional and national working groups and agencies provided information about regional requirements. Mission planning documents for future Earth observation systems were also a source of information about priority requirements.
Task US-09-01a methodology required examination of a wide range of sources for potentially relevant, publicly available documents, including:
- International, regional, and national documents focused on data sources, applications, or research priorities
- Project reports (e.g., findings from major regional/national projects)
- Surveys (e.g., of users of solar resource data)
- Workshop and conference summaries
- Individual peer-reviewed journal articles.
In order to identify as many publicly available documents as possible for consideration in the analysis of priority observations for the Disasters SBA, the Analyst and support team attempted to locate documents from various sources. The types of documents sought included international, regional, and national-level reports; workshop and conference proceedings, summaries and presentations; peer-reviewed journal articles; and other published documents. The Disasters SBA team used the following key methods in the document identification process:
- Requested document references for the three disasters subtopics directly from the Advisory Group.
- Searched the websites of large national and international working groups and government agencies. Examples of such working groups and agencies include the IGOS Geohazards Community of Practice, the US Subcommittee on Disaster Reduction (SDR), the Committee on Earth Observation Satellites (CEOS), USGS, and Bureau de Recherches Géologiques et Minières (BRGM- France).
- Performed web-based literature searches using standard search tools and databases. The Analyst used combinations of specific disasters and Earth observation keywords (e.g., earthquake, observation, priorities, spatial resolution, etc.) to perform the searches.
- Referred to the references listed in the documents identified through other methods to provide potential new sources of information.
For those documents that met the criteria described in Section 2.3.1, the Analyst first categorized the documents by renewable energy type(s) and region(s) represented (or global/international, if no specific geographic focus was noted).
Each document was evaluated for its usefulness based on the inclusion of specific observation requirements related to earthquakes, landslides, and/or floods. As a result, in order for a document to be included in the analysis, it had to explicitly identify required disasters-related Earth observations, and it had to contain information regarding the desired physical characteristics of the observation. The physical characteristics include the temporal resolution (frequency), spatial resolution, timeliness (how quickly the observation is available), accuracy/precision, and coverage or extent of the observation.
In addition to extracting as much information from the reports into the database as possible, each observation parameter was grouped into a broader category of observations.
The prioritization method involved two steps. The first step was documentation of an already-determined set of climate observation priorities,the essential climate variables (ECVs) identified by international teams of climate science and related experts convened under the auspices of the GCOS. The second step was review of documented requirements, both included among and in addition to the ECVs, to identify priorities of additional users. The analyst anticipated that the priorities of these users may overlap with the ECVs, but by taking account of their specific requirements, the needs of these users could provide a sense of relative priority, for these users, among the ECVs. As described further in Section 3.4, these users include regional and national governments.
The Analyst developed a linear method of prioritization of the Earth observation parameters identified through the document meta-analysis described in Section 2.3.2 above. The Advisory Group reviewed the method of prioritization. Only two Advisory Group members made minor comments on the method.3 The three consecutive steps of this prioritization are as follows:
- Cross-Cutting Parameters: The first step in identifying Earth observation priorities was for the Analyst to assess which observation parameters are required, with similar scales and characteristics, across several of the six sub-areas of renewable energy. The Analyst deemed that parameters that are required for multiple types of renewable energy would have an “economy of scale” that provides a multi-faceted return on investment. To ensure that these parameters are required with similar scales and characteristics, the Analyst checked the original literature and noted where required characteristics between renewable energy sub-areas varied significantly. However, in many cases, although the ideally required scales varied, meeting the finer scale requirement (e.g., hourly data) for one renewable energy sub-area would also allow averaging to meet a coarser scale requirement (e.g., monthly averages) for a different renewable energy sub-area.
- Key Parameters for Priority Renewable Energy Types: The second step was for the Analyst to identify the renewable energy types that are projected by experts to gain prominence over the next 20 plus years. For this, the Analyst relied on the International Energy Agency’s (IEA) World Energy Outlook 2008 (IEA, 2008b). The World Energy Outlook draws on a worldwide body of experts to identify required actions in the energy realm for a sustainable future. The Reference Scenario presented in the World Energy Outlook projects the energy mix out to 2030. The Analyst deemed that the top four renewable energy types by Terawatt-hours generated in the 2030 Reference Scenario should be considered “priority” types in this US-09-01a analysis. These were hydropower, onshore/land-based wind, bioenergy, and offshore wind.
- Advisory Group Refinement: The third step was oversight and review from the Task US-09-01a Energy SBA Advisory Group of the observation priorities identified by one or both of the first prioritization steps. This also served as a final check, should one of the above two methods fail to identify or properly categorize an observation. When combined with additional analysis by the Analyst, this allowed for ordering the parameters identified by the two methods above into a single tiered set of parameters.
Using the data from the observation database generated during the document review process, a weighted index was computed in order to generate a list of priority disasters observations that is as objective as possible given the information and resources available. The index value for each of the observation categories takes into account how frequently the observation category is mentioned in the documents as a priority, as well as document -specific weighting factors based on the cross-cutting applicability of the observation category and a report weight based on the type of document.
The cross-cutting applicability weight for each document is an integer value from 1 to 3 that is equal to the number of disaster types (earthquakes, landslides and/or floods) to which a single observation applies, as identified by the document. This weight did not rely on the Analyst’s judgment; rather it was assigned based only on the disaster types identified as applicable by the document.
The document weight is also an integer value from 1 to 3. International working group or consensus documents carry the highest weight with a value of 3, since they typically represent the viewpoints of scientists from a broad range of geographic locations and technical specialties. National-level government or working group documents have a weight of 2. The national-level documents are weighted slightly lower due to the narrowed geographic focus of the documents. Journal articles, conference presentations, conference proceedings, and unpublished studies have a weight of 1, as they typically represent the viewpoint of one or a few scientists, have a narrow geographic focus, and are not always subject to the peer-review process. Table 2 summarizes the weighting factors and gives examples of each document category.
The document-specific index value for each observation category, do i , is calculated by taking the product of the weighting factor for the number of disaster types applicable for the observation category in the document, no w , and the weighting factor for the document type, d w , as seen in Equation 1.
The final aggregated weighted index for each observation category, Io, is calculated for all documents by taking the sum of the document-specific index values for the observation category over all of the documents (Equation 2).
By taking the sum of the index values over all of the documents, the aggregated index value takes into account how frequently the observation categories are identified as priorities. Those that are identified more frequently will have higher aggregated index values. The final aggregated index values are then used to rank the observation priorities across all three hazard types and all documents.