Mould growth results from a complex interaction between environmental factors, material properties, and mould fungi characteristics. These interactions must be considered during the design, construction and maintenance of a building to prevent growth. Mould prediction models aim to predict whether mould will grow on a specific material in a part of building with a known, or simulated, relative humidity and temperature. They are often used in the design phase. Several models are available. There is limited research on the performance of the models in real buildings. This study aimed to evaluate six different models, using data from five building parts. The predictions on whether mould growth was expected or not were compared to actual mould growth observations on five building materials. The study was performed as a round-robin. Most models underestimated the possibility for mould when humidity and temperature varied a lot by time. The outcome also depended on the end-user, who needs to make assumptions and parameter values choices on, for example, material susceptibility for mould growth. Therefore, using the same climate data, mould growth prediction may differ depending on who makes the prediction. One model, MOGLI model, where input data comes from laboratory tests and no such assumptions must be made, predicted correct in most cases. One conclusion of the study is that when predictions are made in practice, the results must be used cautiously. More knowledge is needed to understand, and more accurately model, the relationships between the moisture and temperature variations in buildings and the risk for mould growth. 

The IRIS project has defined goals and targets in the project proposal, and the monitoring and evaluation work package (WP) 9 will analyse to what extent the project reaches these goals and objectives. The monitoring and evaluation will also provide information concerning the performance of the different solutions demonstrated in the Lighthouse (LH) cities in IRIS which is important for the replication of the solutions both in the LH cities and in other cities. This is of importance for the replicability of the solutions, both in the LH cities (Utrecht, Nice and Gothenburg) and in other cities. The project consists of several demonstration projects which are divided by 5 transition tracks (TTs): TT1; Smart renewables and closed- loop energy positive districts, TT2; Smart Energy Management and Storage for Grid Flexibility, TT3; Smart e-Mobility Sector, TT4; City Innovation Platform (CIP) Use Cases, TT5; Citizen engagement and co-creation.

D9.5 is the result of 2 years of work with several iterative processes involving the LH cities and their partners with the ultimate goal to:

Define a set of Key Performance Indicators (KPIs) which evaluate the effectiveness and impact of the cities proposed measures.Setup monitoring plans for each IS to define how each parameter is being measured to ensure that the KPIs can be calculated.Define how the baseline and the targets are defined and measured.This work started as described in D9.2 (Report on monitoring and evaluation schemes for integrated solutions) [1] with:The definition of the initial list of KPIs and how to calculate them, based on Smart Cities Information System (SCIS) [2], the CITYKeys Project [3] and the IRIS project itself .The assignment of KPIs to relevant measures within the project.An evaluation plan to measure performance on project level, including aggregation of KPIs.

The process has continued with D9.3 (Report on data model and management plan for integrated solutions) [4] and D9.4 (Report on unified framework for harmonized data gathering, analysis and reporting) [5], which define the basis of the methodologies used to come to the results written in this report.

Feedback from several workshops on this topic has led to a guideline that supports the partners responsible for implementation of the demonstrators in setting up their projects such that:KPIs that are being measured are well understood.KPIs give a meaningful result.The right data is being measured to calculate the required KPIs during the implementation of the measures.

An important part of this process is to have a close look at the KPIs that are projected for each demonstrator, the calculation method of the KPIs, and the expected results. By means of KPI interpretation forms. By doing so:

• KPIs are defined and calculated such that only one way of interpretation is possible. This way results from different projects and cities are homogenized.

• It is well understood what result the measurement of a KPI leads to.The method and results of this process are described in this report, which is a revised KPI list where KPIs are added, removed or adapted.

In addition to this, the KPI interpretation forms created the basis for the formulation of detailed monitoring plans for all measures within the project. Together with template forms for reporting these plans and a common data structure, which were provided to the affiliated partners, these plans are obtained and described for all measures per Transition Track and per Lighthouse city in this report.

Another essential part of measuring the performance of the IRIS project is the establishment of the baseline measurements and review if targets are met. Tables with KPI data requirements, consisting of the associated parameters, data sources, baseline and (possible) targets for all measures are incorporated.

An important part of the monitoring strategy of the IRIS project is the KPI tool, which is described in detail in report D9.4 [5]. This tool is established to collect all relevant monitoring data from the IRIS project in order to calculate and visualize the performance of the project. The tool partly obtains it’s data by means of the City Information Platforms (CIP). The monitoring details combined with the updated KPIs, result in an inventory containing an overview of all data sources with as main objective:

• To make sure that all data sources are known and will be measured by the responsible partners.

• To know what kind of data needs to be collected by the KPI tool.

• To know when monitoring in each demonstrator starts and data can be expected.

• To have a clear overview for all responsible partners what to deliver.

Besides setting up the collection of the indicators data, D9.5 also continues the work on aggregation of KPIs. For each city a revised list is made that indicates which KPIs will be aggregated to Transition Track-, City- and IRIS-level.

In the conclusion the challenges that where met during the process of setting up the monitoring framework are described. Because of delays within the IRIS project, not all monitoring plans have been obtained yet. Therefore, a future update of this report will be submitted as soon as this information is available. Further on a perspective is described for future work to start gathering the data and visualize results of the IRIS project.

The target group for this report is mainly people who:

-  Are interested in how to apply a unified monitoring and evaluation scheme into a large Smart City project with many different partners and stakeholders. For example, people working on comparable (Smart City) projects, or the follower cities within the IRIS project.

-  Are interested in how the performance of several different Smart city projects can be evaluated.

-  Are interested in the implementation of KPIs from projects such as SCIS and CITYkeys.

-  Want to learn from project partners from within the IRIS project who work on similar projectsabout their monitoring. For example, partners from different cities affiliated with the same transition track or transition track leaders.

- Want to find out what kind of data can be expected from the IRIS project. For example, external researchers interested in the results of Smart City projects, but also partners working on WP4 (CIP) and WP9 (monitoring and evaluation).Want to learn what the current state is of the monitoring and evaluation of the IRIS project.

The susceptibility for mould growth varies among different building materials. One way to describe the susceptibility is the lowest RH at which mould can grow on a specific material, the critical moisture level (RHcrit). Determining RHcrit for materials provide the basis for material choice in designs where moisture and temperature conditions are known. In this study, RHcrit of 21different products were determined according to SIS-TS 41:2014/SPMet 4927. This test method is developed based on the results of a variety of laboratory studies and validated by field studies. Test specimens were inoculated with a suspension containing spores from six different mould fungi and were then incubated in moisture chambers at four levels of RH at 22 °C. After 12 weeks specimens were analysed for mould growth. RHcrit was determined based on the lowest RH at which mould grew on the specimens. RHcrit varied among different products, even between product belonging to a similar group of material, for example, calcium silicate boards or gypsum boards. The results show, and confirm, previous findings that it is not possible to estimate RHcrit for a specific product based on material group. Instead, each product must be tested. © The Authors

The IRIS project has defined goals and targets in the project proposal and the monitoring and evaluation work package (WP) 9 will analyse to what extent the project reaches these goals and objectives. The monitoring and evaluation will also provide information concerning the performance of the different solutions demonstrated in the LH cities in IRIS which is important for the replication of the solutions both in the LH cities and in other cities.

The deliverable particularly addresses the IRIS Lighthouse Cities partners responsible for specific solutions and the leaders from the five Transition Tracks. The main objective of D9.2 is to present an all- embracing evaluation plan and monitoring program. A set of Key Performance Indicators (KPIs) has been selected to evaluate the effectiveness and impact of the cities proposed integrated solutions. Deliverable D9.2 sets out the requirements and objectives for the monitoring and evaluation to be carried out in the lighthouse cities and their integrated solutions and is a significant step towards the establishment of the unified monitoring infrastructure of the IRIS project.

The selection of the KPI set was carried out in collaboration with key representatives from the lighthouse cities and involved their partners responsible for specific solutions and the leaders from the five Transition Tracks. The final selection of KPIs fulfil the ambitions of the Grant Agreement and set targets, as well as specific input from partners wishing to assess more accurately the success level of each solution or methodology tested by the demonstrators.

The definition of Key Performance Indicators has been harmonized with other European projects working on energy smartification of European cities. The main initiatives that have been consulted for the definition of the key performance indicators (KPIs) are SCIS and CITYkeys, although some new indicators originate from the work conducted within the IRIS project. The use of SCIS and CITYkeys KPIs in IRIS will facilitate incorporation of all performance data into the SCIS throughout the project.

The work done in D9.2 will be used in D9.3 that is due in month 14 (M14). D9.3 will create the data model and the management plan for the integrated solutions and forms the basis for the establishment of a unified framework for harmonized data gathering, analysis and reporting which will be concluded in deliverable D9.4 which is due M18. Deliverable D9.2 will also provide input for WPs 3, 5-7 and 8.

Eco-neighborhoods with gardens on concrete decks are for several reasons increasingly being prescribed today in major Swedish cities. However, there is a lack of knowledge, experience, standards and guidelines as well as collaboration between parties and stakeholders when installing such systems. It is incredibly important to avoid any leakage during the lifetime of a green roof garden but this cannot be completely guaranteed with today’s installation practice and project management. At Sustainable City 2014 in Siena, we presented a paper about a new project aiming at bringing together researchers, government and industry to collaborative development of new and attractive solutions for green roof gardens with consideration to the environment and high requirements for durability, materials, construction and energy efficiency. This paper is a continuation of the paper presented in Siena and reports on the most recent results from the collaborative project which will finalize in November 2016. After that, the project will be further evaluated in a proposed continuation project for another couple of years.

En slutrapport från ett projektet vars syfte var att lyfta och utvärdera möjligheterna med utvändigt lufttäta klimatskal, både vid nyproduktion och vid ombyggnad där klimatskalet skall uppgraderas.

Discolouration of building facades. A knowledge survey

Microorganisms that grow on facades can cause extensive discoloration, which often poses a problem for home owners as it can provide an aesthetically unfavourable impression of the building. Fouling occurs as a result of a complex process that involves several parameters, including biological factors, climatic factors and factors related to the building. This report describes and discusses these factors and their implications for the incidence of fouling, based on scientifically published research. One chapter of the report deals with cleaning and maintenance of facades. Based on the knowledge available in the literature suggestions are given for further research that can contribute to decreased problems with discoloured facades. Finally, the report provides references to a number of scientific articles categorized by keywords in order to make it easier for those who want to read more on the topic.

I Sverige ser vi ett ökat intresse bland byggherrar och fastighetsägare att bygga och förvalta byggnader som har gröna ytor på tak, och även väggar. Med det ökande intresset ökar behovet av att bygga kunskap kring de gröna klimatskalens inverkan på bl a fukt- och temperaturförhållanden i konstruktioner samt energianvändning för byggnaden. Inom ramen för detta projekt har mätningar, simuleringar utförts där kunskapen byggts vidare bland annat för ventilerade gröna väggar och tak. Även intervjuer har utförs, framförallt vad gäller gröna tak där erfarenheter från genomförda projekt har samlats.