The Contradictions Between District and Individual Heating Towards Green Deal Targets

The blind spot can be defined as the area around the vehicle where the driver cannot see through the mirrors without turning their head or taking their eyes off the road. Similar blind spots occur in energy policy. Blind spots can occur in forecasting economic development and creating policy documents. This study uncovers potential blind spots and controversies in the sustainability assessment of energy supply technologies. A composite sustainability index was constructed to compare district heating with four individual heating technologies—wood pellet boilers, natural gas boilers, solar collectors, and heat pumps. A total of 19 indicators were selected and grouped into four dimensions of sustainability—technical, environmental, economic, and social. The results reveal that district heating can compete with individual heating technologies in all dimensions of sustainability;however, a possible blind spot lies in evaluating environmental performance indicators of the different heating technologies. This study provides a novel decision-making tool that policy-makers could use to identify and avoid potential blind spots and uncertainties in energy policy at an early stage.


Introduction
Over the last decade, numerous strategies, regulations, and policies have been enforced to drive decarbonization.
The policies pursued and the enforcement mechanisms used are not always highly effective and often fall short of the necessary climate targets set by policymakers.
There are situations when the government can not overlook existing blind spots in policymaking. The blind spot can be defined as the area around the vehicle where the driver cannot see through the mirrors without turning their head or taking their eyes off the road. Similar blind spots occur in energy policy.
Heat supply is the most carbon and energy-intensive sector in the European Union, accounting for about 50% of total demand European Union.
Most studies comparing district heating and individual heating focus on one perspective, analysing either the cost-effectiveness, technical performance, or environmental impact of the different heating technologies. Looking at only one dimension and neglecting other sustainability dimensions can create unexpected blind spots in energy policy.
it is necessary to develop a comprehensive methodology that allows for a full-fledged sustainability assessment that includes a unified consideration of all aspects together. 2

Objectives
The aim of this study is to design a methodology to analyze contradictions and validate the methodology by revealing some of the controversies of the energy sector.
This study's main objective is to compare the sustainability of district heating with different individual heating solutions.
The subject of the study is not individual heating and district heating solutions in a particular country, but the study aimed to highlight the existing trends in the sustainability of heating solutions.
Sustainability is assessed in terms of the compatibility of the technology with the goals of a low-carbon economy.
Model for sustainability index construction and decisionmaking algorithm 4 The core element for sustainability assessment is the construction of the composite sustainability index. In this study composite sustainability index is calculated for district heating (based on the natural gas) and four different technological solutions of decentralized (individual) heating wood pellet boiler; natural gas boiler; solar collectors; and (4); heat pump. The selection of individual heat supply solutions was based 1) on a Danish study on individual heat supply solutions 2) on the availability of data to create a complex index 3) on the sustainability of the heat supply solution.
• Determination of Sustainability Dimensions and selection of Indicators Model includes four main dimensions -technical, environmental, economic, and social. Each dimension is composed of various descriptive indicators. In total, 19 indicators were selected and grouped into representative dimensions.

• Data collection and expert evaluation
Quantitative indicator values for each technology were determined based on two main approaches -quantitative and qualitative assessment. For the indicators where the specific values could be found from publicly available databases, scientific papers, researches and reports, legislation, and technology data sheets. Technology efficiency (tech1), specific CO 2 emissions (env1), specific capital investments (econ1), specific service and maintenance costs (econ2), technology lifetime (econ3), specific energy costs (econ4).

Weighting and indicator aggregation into sustainability index
Weighting is performed in order to proceed with indicator aggregation into representative sub-indices and final composite sustainability index. After data normalization, weights are assessed by a two-step procedure. At first, equal weighting is applied to calculate sustainability dimension sub-index scores using: is impact weight of indicators on dimension sub-index (application of equal weighting) is number of indicators in dimension.
Then AHP method is utilized to account for different impact scales of each dimension to the overall sustainability index: is composite sustainability index, is impact weight of dimension sub-index on composite sustainability index (determined from AHP).
AHP method was used to collect expert opinion on each dimension's impact on the overall sustainability.

Summary
Composite sustainability index was constructed to compare sustainability levels of district heating with four different individual heating solutionswood pellet boiler, natural gas boilers, solar collectors, and heat pumps.
Wide range of indicators were selected including both quantitative and qualitative assessment methods. The sustainability index was composed of 19 different indicators that were grouped in four sustainability dimensions -technical, environmental, economic, and social.
Indicators were normalized using a min-max normalisation technique that scaled sub-indices and index values in a range [0;1], allowing comprehensively interpreting the obtained results.