Despite dramatic reductions in the 1990s of N and P emissions in the drainage basin, Lake Peipsi/Chudskoe (Estonia/Russia) is still suffering from algal blooms, probably caused by low N:P ratios of the lake water. To quantify the sources and changes of N and P inputs to the lake as a result of economic changes, we modelled emissions, transfer and in-stream retention using a GIS model. The model was calibrated using river monitoring data from the 1985-1989 period, and used to simulate emissions and loads for five future scenarios for 2015-2019. During the 1985-1999 period, diffuse P emissions decreased relatively more than N diffuse emissions, but this was not reflected in the loads to the lake. P loads decreased relatively less than N loads, which caused a decrease in the N:P ratio of the rivers. About 30-45% of diffuse N emissions and only 3-10% of diffuse P emissions reaches the river network. In-stream retention reduces N and P loads to the lake by about 62% and 72%, respectively. Point sources contribute negligibly to the N load to the lake, but form about one-third of the P load. A target/fast development scenario is the most likely scenario for the 2015-2019 period, resulting in higher nutrient loads than in recent years. We conclude that effective load reductions can be achieved by focussing on diffuse N and P emissions close (< 50 km2) to the lake and by upgrading P removal capacity in wastewater treatment plants of towns.

This study aims at the quantification of possible future nutrient loads into Lake Peipsi/Chudskoe under different economic development scenarios. This drainage basin is on the borders of Russia, Estonia and Latvia. The sudden disintegration of the Soviet Union in 1991 caused a collapse of agricultural economy, and consequently, a substantial decrease of diffuse and point-source nutrient emissions. For the future, uncertainties about economic development and the priorities that will be set for this region make it difficult to assess the consequences for river water quality and nutrient loads into the lake. We applied five integrated scenarios of future development of this transboundary region for the next twelve to fifteen years. Each scenario consists of a qualitative story line, which was translated into quantitative changes in the input variables for a geographical information system based nutrient transport model. This model calculates nutrient emissions, as well as transport and retention and the resulting nutrient loads into the lake. The model results show that the effects of the different development scenarios on nutrient loads are relatively limited over a time span of about 15 years. In general, a further reduction of nutrient loads is expected, except for a fast economic development scenario.

PurposeThis paper aims to assess the current waste management situation in Estonian municipalities and outlines the main constraints hindering the implementation of the Pay‐As‐You‐Throw (PAYT) system into the existing waste management model.Design/methodology/approachData pertaining to the treatment methods of municipal solid waste (MSW) and the ability to implement the PAYT system were gathered from 150 of the 226 local municipalities, whilst statistical data related to the amounts of MSW generated and separately collected at a municipal level were obtained from the Estonian Environmental Information Centre.FindingsThe results of the study showed that 39 per cent of the municipalities sort waste before landfilling. To increase the sorting ability of inhabitants, 43 per cent of those municipalities that responded to the questionnaire suggested enhancing awareness among people in regard to waste handling. It was found that people are not economically motivated to sort their waste due to the fact that differences in charges between separately collected and unsorted waste are negligible. It was estimated that implementing the PAYT system in one rural municipality would increase the cost of emptying containers by approximately 20‐45 per cent.Practical implicationsResults of the study can be used in countries with a comparable economic situation to improve their current economic and legislative context in the field of sustainable waste management.Originality/valueThe novelty is that the authors aimed to assess the possibility of implementation of the Pay‐As‐You‐Throw system in practice, using Estonian municipalities as a case area, including economic feasibility and willingness of stakeholders to apply the system.

A method for environmental planning (MEP) was adapted for use in water management in large drainage basins. Using a semi-dynamic method, Fuzzy Cognitive Mapping, an expert system divided the studied Narva River basin into three distinct environmental zones. Consequences were calculated based on environmental effects on and significances of waterbodies. In the DPSIR (referring to driving forces, pressures, state, impacts, and responses) framework, the expert system quantified the effects of large-scale spatial plans into impacts and consequences. Also, several existing concepts were integrated to define environmental sensitivity, which comprises two components: (1) strength of links between components in the DPSIR framework and (2) significance of the feature of interest. The results revealed environmentally cost-effective principles for localizing various driving forces such as wastewater treatment, oil shale mining, and agricultural activities.

This chapter draws on results from previous chapters, in some cases creating new syntheses by combining information across chapters and including findings of previous projects. Its specific objective is to consolidate all these findings in the design of a system to support transaction of information for environmental assessments and decision support at central and local levels, by local managers of land and species as well as by policymakers. It recognises the need not merely to provide a technological tool, but also to consider demand and supply for information in that tool, the ease of use of the tool, motivation to use the tool and cost of maintaining the tool long-term: a tool that is not desirable, practical, and durable will not last. The chapter therefore first addresses who makes the most decisions, finding not only that local managers of land and species have high need of support, but also that their demand is least met by model-based decision support despite their high capacity to generate data. For this reason a system was designed primarily to accommodate needs of knowledge transfer at local level. Consideration of data quality, ownership, and confidentiality was important, together with scale, uncertainty (and resulting liability) of resulting decision support. All these considerations can be addressed by developing trust in operation of such a system, for which a basis in the civic sector (rather than in private business or government) was recommended. A portal was launched to continue informing all interests of the scope for building and opportunities from use of such a system.