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The use of environmental data at The use of environmental data at EU levelEU level

David StannersDavid Stanners

Ecoinformatics 12th Joint MeetingResearch Triangle ParkNorth Carolina, U.S.A

8 April 2008

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Why do we need scientific data, information & statistics?

•To understand what is going on in the physical world (driving forces, pressures, state and impacts) in a way that is meaningful to policy development, evaluation and decision/action taking.

•To measure progress towards policy targets.

•To understand the linkages between the environmental, social and economic dimensions of sustainable development and to measure changes.

Role of statistical offices becoming marginalised

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The Bricks, Big Boys or Doorstops!

•SOER2005 story

•SOER2010/Signals challenge

•We give up SOERs at out peril !

•Statistical offices partnership does not encourage innovation & responsiveness....

•...but can strengthen rigour and regularity.

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Statistics for the 21st century - Six challenges

1. The need for a range of statistics across the social, economic and environmental domains increasing demands for integration between the domains.

2. The need for improved timeliness in support of climate change, natural resource use and environment and health policy objectives

3. The importance of having socio-economic statistics at the same spatial resolution as environmental data e.g. water catchments, cities, ecosystems.

4. The relevance of seasonal data and not only annual statistics to support policies for example around water resources and climate change.

5. The significance of the “Beyond GDP” process as the political opportunity to make rapid progress across all of the above four challenges

6. The opportunity of making three ongoing processes - SEIS, INSPIRE and GMES – work together to support our goals by providing respectively improved access to data, harmonised standards for their use & funds to underpin work with countries.

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1. Integration - Range of statistics needed

The DPSIR framework for analysingsector/environment interactions

e.g. causes

e.g. pollutants

e.g. quality

e.g. health,ecosystems,materials

e.g. policiesand targets

pressureses

responses

impact

state

drivingforces

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Range of statistics needed

– Environmental statistics on waste generation and disposal, use of natural resources such as water and land and environmental taxes, subsidies and expenditures,

– Social statistics to understand threats to health (such as noise and air pollution), benefits of policies, well-being, behavioural patterns etc. by social groups. Could the house budget surveys be extended in this respect?

– Economic statistics for the main sectors that impact on the environment and people’s health such as land use, energy consumption, transport demand, industrial production, and tourism. Also the integration of environmental variables into macro-economic modelling, for example Input-Output analysis and NAMEA.

e.g. causes

e.g. pollutants

e.g. quality

e.g. health,ecosystems,materials

e.g. policiesand targets

pressureses

responses

impact

state

drivingforces

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2. Timeliness - more timely statistics needed for:

•Fast changing policy developments

•Measure up-to-date policy performance against targets

–For example, under current procedures European citizens and decision makers will not know until 2014 whether they have met their obligations under the Kyoto protocol for the period 2008-2012!

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Quality data means ”fit for purpose”

•Unofficial estimates fulfil a real need

•Timely data

– an estimate now, instead of acccurate figures tomorrow, can be a lot more useful for decision makers

– this allows them to adjust policies rather than just being told two years on that they got it wrong!

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Examples of timeliness

• Quicker access to data already collected in countries so that timely European analysis can be produced to influence global discussions

• Now-casting models that extrapolate available trends to the current year in which decisions are likely to be taken on possible new targets

• Accurate forecasts of socio-economic developments that greatly influence our performance towards longer term environmental targets out to 2020 and beyond

• Near-real time data on human activities and their impacts on people’s health.

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EU-27 emissions projected to be 6% below 1990 by 2020 with all measures (target is -

20%)

93.4 90.7 92.5

8088.9

92.1 94

0

20

40

60

80

100

120

1990 1995 2000 2005 2010 2015 2020

Inde

x 1

00 =

1990

leve

l

EU-27 greenhouse gas emissions EU-27 with existing measures projections

EU-27 with additional measures projections EU-27 projected 2020

European Council 2020 reduction target

`

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3. Spatial resolution

•‘One number per country’ is no longer fit for purpose

•Increasing demand for spatially resolved statistics and analysis across DPSIR to know WHERE things are happening

•Examples: use of CAP and Structural funds against environmental objectives including issues on cross/compliance between environmental legislation and expenditure programmes e.g. nitrates directives and CAP.

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External nr of downloads/year (EEA)

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

2003 2004 2005

Tabular data

Geospatial data

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EEA Spatial data infrastructure Data volume / storage capacity

160800

5000

8000

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

2003 2004 2005 2006

Diskspace available (GB) Diskspace used (GB)

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More spatial socio-economic statistics

• Wide needs - population, GDP, expenditures, energy use & road transport - to tackle the 6EAP priorities

– climate change impacts and adaptation at all scales, from local administrative regions to environmental regions such as water catchment areas

– loss of biodiversity, habitats and ecosystem services within Europe and globally,

– the sustainable use of natural resources such as water and land within Europe and beyond, the latter to support understanding of our footprint on the rest of the world

– environmental health impacts especially in urban areas where 70% of Europe’s citizens currently live.

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Ozone web – near real-time spatial Ozone web – near real-time spatial datadata

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Water Information System for Europe (WISE)

First prototype of a public website for map viewing and ecosystem analysis

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4. Seasonal Data

•‘One number per year’ is no longer a viable approach to issues such as energy use, water resource use and climate change.

•Imagine:

– river water flow– variable water needs for irrigation and tourism

– climate change exacerbating seasonal changes increasing this need

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Seasonal temperature scenarios for Europe (1961-1990 to 2071-2100)

Source: PRUDENCE, HIRHAM model

WinterSummer

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How to do this?

•The new energy statistics regulation, with tight deadlines for reporting by the Member States, provides a good basis for developing fast within year estimates…

•…provided that the frequent delivery of statistics is matched by an equally quick compilation and publication of energy data and greenhouse gas emissions.

•Can we replicate this for other statistics?

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5. Beyond GDP

• “Beyond GDP” is looking for other credible and timely measures to put alongside GDP.

This brings two challenges to the environment community:

• First is to consider well-recognised trends such as greenhouse gas emissions, water use, and waste that could be presented alongside GDP for the same time period (latest year) and frequency (annual or even quarterly).

• Second is to consider aggregate measures of welfare that take better account of environmental considerations than GDP.

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Ecosystem accounting

• For both challenges, we need to account for ecosystem goods and services on which human welfare depend

• But no transparent accounts, physical or monetary • Many ecosystem services are not factored into market

considerations and hence GDP• Ecosystem accounting focuses on integration

across the three domains of SD and on spatial analysis of physical and monetary stocks and flows of ecosystem services

• The aggregates generated from ecosystem accounts can supplement GDP, not replace or adjust it.

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LEAC Query Tool(Land & Ecosystem Accounts)

An element of the EEA services

From local to European curiosity…

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LEAC

•Data base of statistical changes based on the CLC 90 and CLC2000

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Time lags and uneven development

Anticipate urban sprawl in new EU…

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6. SEIS, INSPIRE & GMES

•Three initiatives that could help us make substantial progress quickly on the actions outlined above

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SEIS (Shared Environment Information System)

•Commission Communication published Feb 2008

•Enhancing the benefits we can derive from the investments made by Member States and the EU in expensive data collection activities through streamlining unwanted demands and focusing demands around integration

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Emissionsdata

Emissionsdata

UserUser

Internet(Geonetwork Inspire)

Internet(Geonetwork Inspire)

EEA-nodeinformation

services

EEA-nodeinformation

services

EIONETEIONET

Data fromother

Directives

Data fromother

DirectivesMappingAgenciesMappingAgencies

InternationalConventionsInternationalConventions

NationalData

centres

NationalData

centres

InternetInternet

Sub-nationalData

centres

Sub-nationalData

centres

GMESGMES

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Principles underpinning SEISData and information should be• managed as close as possible to its source• collected once and shared with others for many

purposes• readily available to public authorities and enable them to

easily fulfil reporting obligations• accesible to enable end-users to make comparisons at the

appropriate geographic scale and to participate meaningfully in the development and implementation of environmental policy

• available to the general public after due consideration of the appropriate level of aggregation, given possible confidentiality constraints, and at national level in the national language(s)

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INSPIRE

•INSPIRE now in place and offers the prospect within the SEIS umbrella to substantially enhance the availability, usability and integration of spatial statistics and scientific data to support policy needs.

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GMES

• Provides funding possibilities to build capacities in needed areas.• €2.2 billion from now to 2013• €600 million earmarked for in-situ monitoring (including

atmospheric and marine monitoring and statistics on land use and water resources).

• High potential if we compared with the EEA’s operational budget of €14 million a year !!

• GMES is the EU’s contribution to a wider global process trying to improve the delivery of 21st century data for 21st century problems.

• Statistical challenge is not confined within the EU’s borders but is a global challenge.

• Should give serious consideration to all of the above working with our Eastern and North African Mediterranean colleagues as a contribution to the European Neighbourhood Policy.

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Conclusions

• We need to recruit better the statistical offices into the information game…

• Need to break down barriers to change - joining forces in ways that reward innovation and risk-taking (not the opposite!)

• Better define decision/policy user needs – responsively!

• Better organizing existing resources and networks

• EEA strategy 2009-2013 - intensify data exchange locally & globally.

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Thank you!