Overall quality of environmental statistics and possible improvements

Transcription

1 EUROPEAN COMMISSION EUROSTAT Directorate E: Sectoral and regional statistics Doc. ENV/DIMESA/5.4/01 Original in EN Agenda point 5.4 Overall quality of environmental statistics and possible improvements DIMESA Directors' Meeting on "Environmental statistics and accounts" 4 and 5 April 01, Luxembourg

2 Table of contents 1. Purpose of the document. 3. Problem statement Case Study: Review of quality aspects of water and waste statistics Water Statistics Waste statistics Waste Statistics: situation before the Regulation (EC) No 150/ Waste Statistics: situation after the Regulation (EC) No 150/ General conclusion: Quality improvement of waste statistics Proposals for quality improvement of environmental statistics Continue with gentlemen's agreement ('business as usual') Reinforcement of the gentlemen's agreement by a more formal commitment Legal base on environmental statistics.. 16 Annex I Availability of environmental statistics and accounts data...18

3 Overall quality of environmental statistics and possible improvements 1. Purpose of the document This document intends to highlight the need to enhance the completeness and overall quality of environmental statistics and to propose alternatives for such an improvement. The document presents aspects of the problem, a case study on water and waste statistics, and suggestions for measures to relief the problem (for the availability of environmental statistics and accounts data as of March 01 see Annex I). DIMESA is requested to give a first opinion on possible actions to improve the quality of environmental statistics and in particular on which specific environmental areas are to be covered by those actions.. Problem statement At current, the collection of European environmental statistics is partially based on a joint exercise between Eurostat and the OECD via their Joint Questionnaire which consists of the following sections: Air, Inland waters, Marine environment, Land, Forest, Wildlife, Waste, Noise, and Environment protection expenditures and revenues, while regional environment statistics are collected by means of a questionnaire operated by Eurostat alone. The main objective of the questionnaire is to provide a solid and relevant factual basis for work on environmental issues. It also provides a reference framework for the establishment of environmental information systems in individual countries. However, completing the questionnaire is not bound to any legal obligation but rather on a gentlemen's agreement. Unfortunately such a binding can not empower the national statistical institutes (NSIs) to put the necessary pressure to other national authorities for the collection of statistical data. Consequently, the NSIs, with reduced human and financial resources due to the economic crisis, give a low priority to the production of the requested statistics resulting to missing data and big gaps in the collections. A prominent example of such a case is the water statistics where there is a lack of complete data sets. Furthermore, the Member States have progressed heterogeneously in the production of environmental statistics resulting in non-harmonised concepts, methodologies and validation methods. The European Statistical System however should provide reliable and high-quality response to emerging user needs and new policy requirements (e.g Roadmap on resource efficiency). Only coordinated collections and data compilations, based on common methodological principles and definitions, can provide harmonised statistics of the level of detail and quality required to meet these needs. The development of a flexible system for environmental statistics must adapt to the need to reduce the statistical burden on respondents, the possible duplication of data collections at national level due to lack of coordination and the decrease of resources for the national statistical authorities. The Vision Paper (COM (009) 404) states that simplifying and improving the regulatory environment for the EU businesses and citizens is a long standing priority of the Commission. In the area of statistics, the strategic approach and work plan set out in the Commission s Communication on reduction of the response burden, simplification and priority-setting in the field of Community statistics was welcomed by the Council. Its 3

4 implementation has progressed well, in particular in the area of business and trade statistics, and it will have to be extended to other statistical domains. 3. Case Study: Review of quality aspects of water and waste statistics In this chapter two different domains of environmental statistics, the water and the waste statistics, are described in terms of specific criteria as they are defined in the European Statistics Code of Practice: Completeness, Comparability, Punctuality and Timeliness, and Accuracy. The two domains are selected to demonstrate the imbalance of quality among the different sections of environmental statistics. Moreover, good practices from the field of waste statistics can be identified in order to be applied in other fields and eventually lead to quality improvement. 3.1 Water Statistics Completeness The OECD/Eurostat Joint Questionnaire on Inland Water 010, comprised 10 tables and 648 variables per year (inflow/outflow tables excluded). Forty questionnaires (including EU Member States, UK-E/W (UK-England/Wales), UK-S (UK-Scotland), UK-N (UK-Northern Ireland) and candidate and Balkan countries) were sent and 33 replies were received: 3 from EU7 countries, 3 candidate countries, EFTA and other countries. Year 008 is used as reference year for the following graphs as only about half of the respondents were able to provide data for year 009. The response rate for year 008 was on average 18.9% for all tables. The following table indicates the response rate per country: RESPONSE RATES 008: ALL TABLES 100% 90% 80% 70% 60% 50% 40% 30% 0% 10% 0% MT RO SI NL LT CZ AT BG PL ES FYROM TR EE CY HU NO UK-E/W SRB PT HR BE UK-NIE LU DK SE UK-SC BIH UK-TOT FR CH IT DE EL AL FI IE KO LV MNE SK 4

5 In the following graph we see that the average increases to 3% if table 7 ("Generation and Discharge of Wastewater", quite heavy with its 440 variables) is not taken into account. RESPONSE RATES 008: TABLES % 90% 80% 70% 60% 50% 40% 30% 0% 10% 0% MT LT NL BG SI CZ PL ES FYROM RO TR CY HU EE SRB NO UK-E/W AT BE UK-NIE PT LU HR DK UK-SC UK-TOT SE BIH FR CH IT DE EL AL FI IE In general, EU1 countries provide more complete responses than EU15 countries. The 4 most populous EU15 countries, counting for half of the total population, provided less complete responses. The situation in the previous data collection (IW JQ 008) is slightly better if we take all tables into account, but if we consider only tables 1-6 it seems that the response rate did not change significantly (increased by 0.6% on average) with the latest data collection. The comparison between the two data collections can be summarized in the tables below: KO LV MNE SK For all tables Data Collection 008 (006/007) Data Collection 010 (008) Average: 1.4% 18.9% Average EU15: 14.5% 9.4% Average EU1: 40.0% 3.8% Average CC: 6.7% 10.3% Average EFTA: 4.6% 6.% For tables 1-6 Data Collection 008 (006/007) Data Collection 010 (008) Average: 31.4% 3.0% Average EU15: 0.1% 16.% Average EU1: 55.8% 48.4% Average CC: 15.6% 33.5% Average EFTA: 1.5% 16.9% Comparability Comparability between countries and regions can be very good provided the reporters in different countries use the same methods and interpret the definitions in the same way. 5

6 However, this ideal situation does not always translate into practice: Methods: The use of different models/estimation methods by different countries (e.g. for evapotranspiration) limits comparability; Systematic issues: precipitation over flat land is much easier to measure than in a mountainous area, so comparability is better between countries/regions of like nature; similarly, non-point emissions of pollutants are easier to compare between area of similar density of population/settlements than across such classes; Definitions and methodological instructions are not always 100% respected, and/or interpreted in different ways, which automatically reduces comparability; Specific circumstances detailing the way a dataset was established (e.g. assumptions, sources for raw data used, data coverage etc.) can limit comparability as well; such circumstances are often, but not necessarily documented in footnotes to the respective tables. As a rule, more accurate figures are also better comparable than less accurate ones. The 'mixed' nature of both accuracy and comparability is reflected in the fact that in cases/countries where different networks (statistical system, environment ministries/agencies, NGOs) work in parallel and come up with data sets for identical variables, we observe concord as well as marked discrepancies; case wise, the latter can be explained when looking into the detail, or remain without obvious reason. Punctuality and timeliness As we can see in the graph below, in the JQ-IW 008 data collection only nine countries (out of 31 final replies) replied on time. Another 14 countries replied in the next two months after the deadline but still before the first data release. Five countries sent their replies during the two months after the first data release and before the second data release. Finally another three countries delivered their replies during the three month period after the second data release, expanding the period of delivery to eight months after the initial deadline for replies. The situation was significantly improved in the JQ-IW 010 data collection. Twelve countries (out of 33 final replies) replied on time while another 14 countries replied in the next month after the deadline. The remaining seven replies were delivered in the next trimester. Only one reply was delivered after the first data release and none after the second data release. The overall period of late replies was four months, only half of the corresponding period for the 008 data collection. 6

7 JQ-IW 008 Data Collection Launch of questionnaire 9 Deadline for replies 8 First data release Second data release Replies received MAIN PERIOD OF VALIDATION JULY (008) AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER JANUARY FEBRUARY MARCH APRIL MAY JUNE (009) JQ-IW 010 Data Collection Launch of questionnaire 1 14 Deadline for replies Replies received First data release Second data release 0 JULY (010) AUGUST SEPTEMBER OCTOBER NOVEMBER MAIN PERIOD OF VALIDATION DECEMBER JANUARY FEBRUARY MARCH APRIL Accuracy The accuracy of the water statistics data varies widely by variable but in general is difficult to be assessed, as there are hardly any objective means: Across the domain, the nature/character of the variables is quite different: from elements of the water cycle (e.g. evapotranspiration) via water management items (e.g. water use by the 7

8 chemical industry) and systematic items (e.g. water losses) to built infrastructure (e.g. treatment capacity of wastewater treatment plants (WWTP)) and the methods used to obtain the data are likewise different and encompass measurements, estimations, models, administrative registers etc. While it should be easily possible to correctly specify the number of WWTPs in a country and their cumulative design capacity, loads of e.g. cadmium originating from the textile industry or from non-point sources will inevitably have a margin of error as they are typically not measured but estimated by e.g. using emission factors (industry branches) or models (nonpoint sources). The accuracy of these estimates in turn is not precisely known but can only be estimated. 3. Waste statistics 3..1 Waste Statistics: situation before the Regulation (EC) No 150/00 Completeness The availability of data for waste statistics after the Joint OECD/Eurostat Questionnaire 000 was low. In all cases response rates for priority waste data (main aggregates for waste generated by economic activities and for important waste categories) was higher than for nonpriority data (individual waste streams by economic activity). However, response rates even on priority indicators, such as municipal waste generation, were considered far too low in most cases, especially if we consider that in order to produce meaningful EU totals or time series, figures close to 100% were needed. The following table indicates for how many variables and countries data had been delivered for at least one year between 1990 and 000. Waste Questionnaire Number Total Avail. Avail. as a % of total Total Priority Avail. Priority Avail. as a % of total Waq1_000 Generation of waste by sector % % Waqa_000 Generation, recovery and recycling of selected % % waste streams Waqb_000 Generation of waste by selected waste streams % % Waq3_000 Generation, treatment and disposal of nonhazardous % % industrial waste Waq4a_000 Generation, treatment and disposal of hazardous % % industrial waste Waq4b_000 Generation of hazardous waste by category % % Waq5a_000 Generation and collection of municipal waste % % Waq5b_000 Composition of municipal waste % % Waq5c_000 Treatment and disposal of municipal waste % % Waq6_000 Waste treatment and disposal installations % % Availability for non priority data ranged from 14% to 45% whereas for priority data from 0% to 77%. Even for priority indicators the availability was more than 50% only for out of 10 tables. The graph below indicates data availability of priority indicators for waste statistics after data collection

9 Availability of priority data for Waste Statistics (JQ 000) 90% 80% 70% 60% 50% 40% 30% 0% 10% 0% Waq1 Waqa Waqb Waq3 Waq4a Waq4b Waq5a Waq5b Waq5c Waq6 Average The situation improved slightly during the Joint OECD/Eurostat Questionnaire 00 but the results were not considered satisfactory. Data availability varied greatly among different countries. Comparability In the evaluation of country replies to the Joint OECD/Eurostat Questionnaire 00, statistical data on waste at Community level where considered to suffer from a number of shortcomings, including incomplete coverage and lack of harmonisation. Although most of the data used in this policy field used to come from the JQ, compilation of waste statistics at Community level had shown that the sets of data produced by the countries are very heterogeneous. For example: For industrial waste generated by economic sectors, data availability was not satisfactory and varied from country to country. Accordingly, comparisons of data between countries were difficult. For municipal waste and household waste, data availability was much better but comparison between countries had some limitations. Municipal waste, which is waste collected by or on behalf of municipalities, included waste from households, commercial activities, office buildings and institutions, as well as waste with similar properties from businesses and from municipal services. Household waste included bulky (mixed) waste and separately collected (by the private sector) fractions of waste materials such as paper, clothes, etc. The differences between municipal waste and household waste were the result of the different collection systems in countries: in Belgium, Denmark, the UK and Poland municipal waste used to come mainly from households; in France, Luxembourg, the Netherlands, Austria and Finland, it included considerable amounts of waste from commercial and industrial activities. 9

10 The Waste Statistics Regulation was expected to remedy this situation by establishing a framework for the production of statistics on generation, recovery and disposal of waste by all economic sectors and households. Punctuality and timeliness For the Joint OECD/Eurostat Questionnaire 000 the timeliness of the Waste data ranged from zero months of delay to seven months for two countries. Out of 31 participating countries (15 EU members, EFTA and candidate countries) only 11 reported data in June 000 (the deadline was 9 th of June 000). In a period of 5 months after the initial deadline, another 11 questionnaires were delivered, while 7 months after the initial deadline all 5 replies were sent to Eurostat. Five countries did not report waste data. The following graph indicates the number of replies per month after the initial deadline. Number of replies per month (JQ 000) Number of countries Deadline Deadline + 1 Deadline + Deadline + 3 Deadline + 4 Deadline + 5 Deadline + 6 Deadline + 7 Months after deadline For the Joint OECD/Eurostat Questionnaire 00 the situation was considerably improved compared to previous years but still the number of countries who delivered their data on time was slightly over 50%. More precisely out of 3 participating countries, more than half, ie 17 countries, reported before the set deadline. Another seven countries sent their data in the following two months, four countries in the following two months and finally four countries during the next six months. The following graph indicates the number of replies per month after the initial deadline. 10

11 Number of countries Deadline Number of replies per month (JQ 00) 17 Deadline Deadline + 4 Deadline + 3 Deadline + 4 Deadline Deadline Deadline + 7 Months after deadline Deadline Deadline Deadline Waste Statistics: situation after the Regulation (EC) No 150/00 Article 8(1) of Regulation (EC) No 150/00 of the European Parliament and of the Council of 5 November 00 on waste statistics 1 requires the Commission to submit a report on the implementation of the Regulation every three years to the European Parliament and the Council. The first report was published in 008 while the second report was published in March 011. Based on this last report, the progress being made in the areas of the four mentioned criteria since the first data collection in 006 will be presented, covering the 7 Member States and considering the results of the latest data delivery in June 010. Completeness In the first reporting round for the reference year 004, 6 of the 7 EU Member States were able to provide complete data sets on waste generation covering all waste categories and all sectors. Twenty-one Member States delivered data sets with some gaps. Most data gaps related either to waste generated in agriculture, forestry, hunting (NACE A 01, A 0) and fishery (NACE A 03) or to the reporting on sludges (in weight and dry weight). Overall, the share of missing values on waste generation amounted to about 9 % of the required data. For the reference year 006, the completeness of data improved considerably. The share of missing values on waste generation fell to.1 %. Missing data were reported by only 7 countries whereas 0 Member States provided complete data sets. The share of missing data is highest for the sectors already mentioned above (NACE A 01 03). The highest shares of missing values in 006 were reported by Ireland, Italy and Latvia. With regard to the data on waste treatment, the number of countries with incomplete data sets at national level also decreased significantly between 004 and 006. In 004, 15 countries reported incomplete data sets. The share of missing data for the EU7 accounted for.5 % of the required data. In 006, only five countries delivered incomplete data on the amounts of waste treated. The share of the missing values fell to 1.5 %. More than 70 % of the missing 1 OJ L 33, , p. 1, as amended by Regulation (EC) No 849/010 (OJ L 53, , p. ). COM(008) 355 final,

12 data relate to the disposal of waste through land treatment and release into water bodies, which is mainly applied for non-hazardous sludges. A further improvement of data completeness for waste generation and treatment is noticed for the reference year 008. However, due to the late data delivery of three countries the evaluation was still ongoing by the time this report was drafted. Comparability Comparability over time With the third reporting round having been accomplished, a first assessment of the comparability of the data over time is possible. The evaluation of the countries quality reports shows that considerable adjustments to national waste statistics approaches were made by nearly all Member States. Most countries are now further improving their data collection with regard to data quality (e.g. closing of data gaps; improvement of coverage) and with regard to the efficiency of their methods. However, the comparison of data for 008 with the previous years, which indicates a decrease in waste generation of about 309 million tonnes or 10.9 %, shows that methodological modifications in individual countries may still have significant impacts on the EU aggregates. This is best illustrated by the fact that this development can be attributed to methodological changes in three Member States. Whereas the reductions in Poland and Sweden are due to adjustments of data coverage, France reported considerably lower amounts of waste from the construction sector (NACE Rev. 1.1, section F) as a result of a newly introduced, more accurate survey of the construction sector. The data validation system by Eurostat ensures that breaks in time series are identified and either corrected or explained. In addition, the countries quality reports have proven to be a useful tool to monitor methodological changes and their impacts in Member States. To ensure a consistent time series at the level of economic sectors, the data for 004 and 006 were adjusted for the changes in the breakdown by sectors that result from the transition to NACE Rev.. In addition, the data for 004 that were missing on account of derogations for 11 countries were imputed retrospectively on the basis of the data for 006. Comparability across countries Thanks to the common definitions and classifications the comparability of the data across countries is fairly high. Differences between countries with regard to the generated and treated totals become more and more explainable. Some problems remain where countries have not used statistical units to link to the economic activities that generate the waste. This does not affect the total amounts of waste reported but hampers the comparability by economic sectors. The thorough data analysis, inter alia by means of sector-specific statistics, as well as the framework of statistical waste categories (EWC-STAT) and of waste treatment operations defined by the Regulation ensures a continuous improvement of comparability across countries. Punctuality and timeliness Data and quality reports are to be submitted within 18 months after the reference year, i.e. the delivery deadline for reference year 008 was 30 June 010. The countries were asked, in the 1

13 event of incomplete data or missing quality reports, to provide the missing information as soon as possible. At the time of this report, compliance with the reporting deadline for the reference year 008 can be summarised as follows: 19 countries delivered their data sets in time; 4 Member States submitted data within 3 weeks after the deadline so that they could be considered in the first evaluation round (Portugal, Austria, France, Cyprus); 1 Member State (Romania) delivered data on 0 September 010; 3 Member States submitted data more than 3 months after the deadline: Italy delivered on 11 November, Greece on 1 December and Ireland on 1 December 010. Greece and Ireland incurred serious delays in reporting already in the previous reporting years. In summary, compliance with the reporting deadline for 008 was satisfactory. In all, 3 of the 7 Member States submitted their deliveries timely or with a delay of not more than three weeks. A compliance monitoring routine is established at Eurostat and reminders are sent to Member States at short intervals according to a defined schedule. Hence, punctuality has improved compared to the reference year 006 when 18 countries delivered data within the same period. Overall quality Data quality in a multi-method environment Regulation (EC) 150/00 defines the data to be submitted and the required quality but does not prescribe a specific method of drawing up waste statistics, which are thus compiled in a multi-method environment. This enables Member States to keep their data collection systems and to minimise the changes needed to comply with the Regulation. However, the multi-method approach may result in methodological differences from one country to another, between different data sets from the same country, and even within individual data sets. This makes it difficult to safeguard data comparability and ensure high data quality. The way in which data quality can be measured depends on the methods used. For different methods, there are different quality parameters (e.g. coefficient of variation for sample surveys, sensitivity analysis for modelling, etc.). In particular, the combination of methods within data sets makes it difficult to define indicators for overall data quality. As a consequence the Regulation s multi-method approach hampers the assessment and communication of data quality. In their quality reports, the Member States describe the data by reference to quality elements commonly used in the European Statistical System 3 and set out in Regulation (EC) 1445/005 on the quality of waste statistics 4. Quality control Since the first data delivery in 006, Eurostat has set up an efficient quality control system consisting of two steps. The first step is a quick evaluation of the data and quality reports, and 3 4 Eurostat website on Quality: 73_ &_dad=portal&_schema= PORTAL. OJ L 9, , p

14 an evaluation report is sent out to the countries within two months after the reporting deadline. The second step is a more in-depth validation with no strict deadline. The quick evaluation is made on the basis of five criteria: completeness of data sets; completeness of quality report; timeliness; proper application of definitions and classifications; application of sound statistical methods. In this phase, the data validation concerns mainly the internal coherence of the new data and the developments over time. The analysis is made at a highly aggregate level and aims to detect important breaks in series. The quick evaluation is appreciated by the countries, which is reflected in the immediate feedback to the questions raised in the evaluation reports, and ensures timely publication of the data. The country data are published in the Eurostat dissemination database three months after delivery deadline. The in-depth validation analyses the data at a more detailed level (e.g. by economic sectors and by waste categories) and compares patterns and developments across countries. The validation checks include: intra-country comparisons of waste generation with values from previous years for each economic activity using appropriate indicators; cross-country comparisons of the data for each economic activity; cross-checks with waste data from other reporting obligations such as compliance monitoring pursuant to other waste-related legislation. Potential questions are checked against the countries quality reports and the feedback to the quick evaluation and may result in a second set of questions being sent to the countries concerned General conclusion: Quality improvement of waste statistics Significant progress has been achieved with regard to the compilation of waste statistics since the first reporting in 006. The punctuality and completeness of data delivery by Member States as well as the timeliness of data publication have steadily improved. Waste statistics have reached a fairly high degree of comparability across countries and considerable progress is being made towards full data coverage. Overall, the data are of appropriate quality for most countries. The harmonisation of data is furthered by a set of methodological guidance documents that are available from the website of the Environmental Data Centre on Waste. Errors and methodological deficits are identified by the quality control system. With the data delivery for 008, data on waste generation and treatment are now available for the period from 004 to 008. With the extension of the time series the data become increasingly useful, e.g. for building indicators and for use in the field of environmental accounts. At the same time, it has to be mentioned that methodological changes in individual countries may still have a significant impact on the time series, at national level but also at the level of the EU7 aggregate. Developments over time should thus still be interpreted with caution and after careful analysis of the underlying data. Also, the effect of new concepts introduced by the revised Waste Framework Directive, i.e. end-of-waste criteria, on waste statistics has to be observed. 14

15 A considerable improvement with regard to the usability and interpretability of waste statistics is expected from the revision of the Regulation. Among other improvements, a major step is the harmonisation of the breakdown of waste categories for waste generation and treatment. Member States will deliver the data under the new structure by 30 June 01 for reference year Proposals for quality improvement of environmental statistics In this section, possible actions for improving the quality of environmental statistics data collections will be presented. Each one of the proposals has advantages and disadvantages and further discussions with all involved parties are encouraged to identify and implement the most appropriate approach. 4.1 Continue with gentlemen's agreement ('business as usual') The first approach would be to carry on with gentlemen's agreements for the domains where no legal base is in force. This means that the replies will be delivered on voluntary basis as until now and the situation in terms of overall quality (completeness of data sets, timeliness, proper application of definition, application of common methodology etc) could not be improved significantly in the coming years. Effects and consequences for Member States Under the current situation which is based on gentlemen's agreement without any legal base, in the best case scenario the data quality and availability will continue to be at the current less-than-adequate level or, even more likely, data availability will decrease. There is a general tendency among Member States to focus almost exclusively on legally required reporting and thus data compiled and reported under gentlemen's agreements would cease to be compiled due to a lack of legal requirement. This could also be the case for environmental statistics due to budgetary constraints. Effects and consequences for policies at European Union level There are increasing needs for environmental statistics in Europe. More and more environmental data are needed in several EU action plans and strategies. The assessment of the environmental strategies can be done only if reliable data are available. The current situation based on the gentlemen s agreement does not guarantee data of adequate quality, timeliness and coverage to properly perform this assessment. By remaining under the gentlemen s agreement there is a risk that missing data will be estimated and collected elsewhere on an ad hoc basis. Thus the possibilities to build up a knowledge base and adequate data to answer the policy demands will be limited under the current conditions. 4. Reinforcement of the gentlemen's agreement by a more formal commitment Another approach to the problem could be to strengthen the validity of the current gentlemen's agreement by formal commitments from the Member States regarding the implementation of these agreements (soft law approach). So far no gentlemen's agreement has been formalised. The structure, content and scope of such agreements have to be discussed in each specific case, but one could imagine a commitment at ESSC level. As in a regulation, follow up of the compliance to the legal base will be ensured. 15

16 In both cases 4.1 and 4. possible measures could be taken to help improve the data collection situation. A few options are presented below: Intensify the grants and/or training programme More grants and/or trainings for the Member States could be offered as incentives for improved participation and of course improved quality. The drawback of this approach is that previous experience has shown that when more grants and more training was offered in the area of water statistics the impact on participation and quality was only limited. The likelihood to run effective grant-supported projects is also depending on the administrative and managerial 'absorption capacity' which is often limited in countries with already weak statistics. While the very good training provided to candidate countries and new Member States in the framework of the PHARE and Transition Facility Programmes certainly is one of the reasons for their relatively good performance e.g. in water statistics, demand is rather poor for participation in an ESTP offered to countries in 01. Concentrate on geographical areas Depending on the domain of environmental statistics concerned, another option for improvement would be to focus the demand for statistics on certain geographical areas. To give some examples, it is a fact that in the Mediterranean countries the imbalance of water demand and availability makes the need of solid water statistics more important than in some northern parts of Europe. Also within some countries the situation differs significantly among regions. 4.3 Legal base on environmental statistics Last but not least, a possible solution would be to establish a legal base to ensure the availability and increased quality of environmental statistics data. Effects and consequences for Member States Environmental statistics would only require limited additional resources from the Member States side. Examples of good practice have shown that small teams can organise and deliver solid replies. A legal base would establish a clear mandate for the national statistical institutes and justify the right to claim the necessary resources. The focus on a limited number of key variables and the flexibility to take into account national specificities will further reduce the Member States' impact. Effects and consequences for policies at European Union level The assessment of the European Environmental Policy and its Thematic Strategies can only seriously be done if reliable data are available. The Thematic Strategy on the Sustainable Use of Natural Resources requires data from the area of environmental statistics. These data are currently being collected in many cases through gentlemen s agreements. The required consistent and regular production and reporting of environmental data would improve the quality of the statistics. Moreover, other EU policies (e.g. Sustainable Development Indicator on natural resources) would be much better monitored if data of good quality would exist. These data can be collected through a framework of environmental statistics, but it is necessary that every 16

17 country participates and that harmonisation is fully guaranteed. An appropriate legal base for this data collection could ensure these requirements. A common framework regulation for the collection, compilation, transmission and evaluation of environmental statistics would help: integrate the dispersed production of environmental statistics in the European Statistical System; reduce respondent fatigue due to the avoidance of multiple reporting requirements to various EU and international bodies. Moreover, a flexible approach can help avoid unnecessary burden on data collection from the countries with fewer and less severe environment-related problems (e.g. different reporting needs on water from Spain and Finland); create a solid infrastructure of statistical information to be used widely and intensively for various applications. The European statistical programme has defined this infrastructure as the three-level pyramid 'Primary and secondary data Accounting systems Indicators'. In order to build reliable indicators and meet statistical needs for EU policies, a rigid and well-developed base of the pyramid is required. Good quality primary and secondary data collected with harmonised methodologies will ensure such a stable base. There are fundamental issues to be analyzed concerning a legal base for environmental statistics such as the form it could take (e.g. regulation, directive, etc.), its scope and flexibility, its structure and variables. Modular structure: A modular structure of the legal base should start by areas where the need for a regulation due to data scarcity is more evident. Water, basic regional environmental statistics and perhaps forestry could form a first set of modules to be considered. Any additional module will require full legislative process (EP and Council). Variables: A start could be made with a limited set of variables comprising the most important data. More details are left for gentlemen's agreements. Adaptation to national needs: The legal base should provide the possibility of setting up thresholds in order reduce the data to be reported for those countries where the impact on the environment is not important. 17

18 Annex I Availability of Environmental Statistics and Accounts (situation as of March 01)