District Scale Research Articles

Multi-objective optimization algorithms applied to residential building retrofitting at district scale: BRIOTOOL

The design of district and urban energy efficient retrofitting projects is a major challenge if contrasted solutions want to be implemented. From the establishment of the criteria to the calculation of indicators, there are several aspects to be considered, such as evaluating a series of refurbishment solutions or establishing an adequate method to select the optimal solution. Apart from this process requiring a high number of time and resources, it can result in a number of inaccuracies, leading to inadequate decisions or designs. The main achievement of the BRIOTOOL solution proposed is the transformation of a subjective problem (what the best combination of energy conservation measures to implement is) into a mathematical problem, which ensures a more robust decision-making process. In particular, by analysing which multi-objective optimization method (NSGA-II, IHS, MHACO or NSPSO) is the most appropriate, based on execution time, number of different and optimal solutions, and hypervolume of the Pareto front generated. As a result, the time reduction and the increase in the accuracy of the process compared to business as usual practices shows the benefits of the solution in designing energy efficient retrofitting projects at district level.

Modeling Actual Water Use Under Different Irrigation Regimes at District Scale: Application to the FAO-56 Dual Crop Coefficient Method

Modeling Actual Water Use Under Different Irrigation Regimes at District Scale: Application to the FAO-56 Dual Crop Coefficient Method

Decomposition Strategy for Districts as Renewable Energy Hubs

In light of the energy transition, it becomes a widespread solution to decentralize and to decarbonize energy systems. However, limited transformer capacities are a hurdle for large-scale integration of solar energy in the electricity grid. The aim of this paper is to define a novel concept of renewable energy hubs and to optimize its design strategy at the district scale in an appropriate computational time. To overcome runtime issues, the Dantzig–Wolfe decomposition method is applied to a mixed-integer linear programming framework of the renewable energy hub. Distributed energy units as well as centralized district units are considered. In addition, a method to perform multi-objective optimization as well as respecting district grid constraints in the decomposition algorithm is presented. The decomposed formulation leads to a convergence below 20 min for 31 buildings and a mip gap lower than 0.2%. The centralized design enhances the photovoltaic penetration in the energy mix and reduces the global warming potential and necessary curtailment in order to respect transformer capacity constraints.

A New Approach for Modelling Techno-Economic Performance of Integrated Energy Systems on District Scale for Informed Decision-Making in a Multi-Stakeholder Context

A New Approach for Modelling Techno-Economic Performance of Integrated Energy Systems on District Scale for Informed Decision-Making in a Multi-Stakeholder Context

Perbandingan Peta Percepatan Tanah di Permukaan sebagai Dasar Perencanaan Tata Ruang Berbasis Mitigasi Bencana di Provinsi Riau

Spatial planning has an important role in disaster mitigation efforts. The availability of earthquake maps is very useful in spatial planning. The need for spatial planning today is micro spatial planning. Therefore, the 2017 national earthquake map needs to be detailed into a micro zonation map at the district or city scale. The ground acceleration presented in the national earthquake map was the acceleration at bedrock, while in spatial planning it is the necessary acceleration at the surface. Therefore, the purpose of this research was to obtain a map of the earthquake at the surface with a micro-scale. Determination of the acceleration value at the surface was carried out by two models. Model-1, the surface acceleration was obtained by multiplying the results of the PSHA analysis at bedrock by the amplification factor based on SNI-1726. While Model-2, the acceleration value at the surface was directly obtained from the results of PSHA analysis using the average surface shear wave velocity (Vs30) based on data from the USGS. The result of this study showed that from the 2 analytical models used, Model-2 has a higher surface acceleration value than Model-1. Riau Province has 12 districts. in general, the 12 districts were included in the low to moderate risk index class, but there was one district that was close to the high index class, namely Rokan Hulu district.

Value and Quality in the Dialectics between Human and Urban Capital of the City Networks on the Land District Scale

This contribution proposes an inter-scalar and multi-polar analysis evaluation model of the territory of the Enna district, aimed at providing a robust axiological representation of the salient aspects of the general issue of internal areas, and therefore of the set of criticalities affecting them from the perspective of the human and urban capital they express. In the prospect of investigating the relations between urban and life quality—corresponding to the “city effect”—in the territorial context of each of the 20 municipalities of the Enna district, a hierarchical descriptive-valuation model was created, which coordinates a relevant amount of information units (data) and the corresponding attributes, indicators and indices that have been turned in aggregate value judgments attributed to each administrative land unit, from the perspectives of the criteria referred to as the main forms of the territorial capital. This is a multi-dimensional valuation model based on the Multi-Attribute Value Theory. Each survey and processing is mapped with different levels of detail at the scale of municipalities, census sections and cadastral land units. The outcome of this complex process of analysis and assessment provides multiple comparisons, revealing unexpected and sometimes counter-intuitive aspects in several municipalities, some of which are characterised by innovative prospects and opportunities for redevelopment of their historic centers. Correlations between information units at the different levels of the dendrogram have also indicated interesting trends and attitudes, whose comparisons can address territorial policies on both a local and provincial scale. Furthermore, the focus on the “cities network” is here assumed and proposed as the privileged point of observation of territory and the related aspects of the quality of life.

Intelligent IoT-multiagent precision irrigation approach for improving water use efficiency in irrigation systems at farm and district scales

The fourth industrial revolution in agriculture seeks the automation of traditional practices, using modern smart technologies. Advances in electronics, computation and the internet of things are integrated for improving field inputs management. The aim of this paper is to present the design and implementation of an intelligent IoT-multiagent precision irrigation approach for improving water use efficiency in irrigation systems. The study site was the large-scale irrigation and drainage district of Chicamocha and Firavitoba (Usochicamocha) located in Boyacá - Colombia, where water is distributed from the Chicamocha riverbed. In the proposed system, irrigation is supervised and controlled in each field by an intelligent irrigation agent that autonomously prescribes and applies water amounts with agronomical criteria. The methodology was applied with real (cyber-physical) and virtual (simulated) intelligent agents and was extended to eleven pump stations that supply water to 5911 fields. Using a MQTT protocol, hundreds of irrigation intelligent agents report water prescriptions and crop characteristics to a master agent in each pump station, who creates a regional irrigation map to manage georeferenced field information and performs negotiation of water resources between agents according to supply availability. Field maps and intelligent irrigation agents can be visualized using devices with internet access. Results demonstrated that irrigation amounts were correctly applied on the fields, thus improving the water use efficiency. This technology is a novel support to decision-making in water resources management applications at field and district scales.

Improving Thermoeconomic and Environmental Performance of District Heating via Demand Pooling and Upscaling

This study evaluates the effects of pooling heat demands in a district for the purpose of upscaling heat production units by means of energy, exergy, economic, exergoeconomic, and environmental indicators, as well as the sensitivity to investment and fuel costs. The following production systems to satisfy the heat demands (domestic hot water production and space heating) of a mixed district composed of office (80%), residential (15%), and commercial (5%) buildings are considered: gas- and biomass-fired boilers, electric boilers and heat pumps (grid-powered or photovoltaic -powered), and solar thermal collectors. For comparison, three system sizing approaches are examined: at building scale, at sector scale (residential, office, and commerce), or at district scale. For the configurations studied, the upscaling benefits were up to 5% higher efficiency (energy and exergy), there was lower levelized cost of heat for all systems (between 20% and 54%), up to 55% lower exergy destruction costs, and up to 5% greater CO2 mitigations. In conclusion, upscaling and demand pooling tend to improve specific efficiencies, reduce specific costs, reduce total investment through the peak power sizing method, and mitigate temporal mismatch in solar-driven systems. Possible drawbacks are additional heat losses due to the distribution network and reduced performance in heat pumps due to the higher temperatures required. Nevertheless, the advantages outweigh the drawbacks in most cases.

Comparison of hydrological and vegetation remote sensing datasets as proxies for rainfed maize yield in Malawi

Weather Index-based Insurances (WIIs) have emerged as a promising risk coping mechanism to compensate for weather-induced damage to rainfed agriculture. Remote sensing may provide cost-effective information capable of discriminating the weather spatial variability thus reducing the spatial basis risk, i.e., the mismatch between the weather-based index triggering the insurance payout and the actual damage experienced by the farmers, which is often one of the causes hindering the wide implementation of WIIs. In this work we assess which indices based on remote sensing datasets are the best proxy indicators for rainfed maize yield in Malawi. We analyse the spatial (district scale) and temporal (monthly) correlations of historical maize yield data and several remote sensing datasets including the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset, the ESA CCI Soil Moisture combined dataset (version 4.2), the Evaporative Stress Index (ESI) from the Atmosphere-Land Exchange Inversion model (ALEXI), the MOD13Q1 Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). With respect to the previous literature, this work exploits a historical crop yield dataset at the sub-national level which allows us to analyse the correlation of the hydro-meteorological and vegetation variables at a higher spatial resolution than what is commonly done (i.e., at the national level using FAO national yield statistics) and ultimately explore the issues related to WII spatial basis risk. Results show that the correlations between crop yield and satellite datasets show high spatial and temporal variability, making it difficult to identify a unique WII index that is at the same time simple and effective for the entire country. Precipitation, particularly the standardized March precipitation anomaly, has the highest correlations with maize yield (with Pearson correlation values higher than 0.55), in Central and South Malawi. Soil moisture and NDVI do not add much value to precipitation in anticipating historical maize yield at the district scale. From a methodological perspective, our work shows that WII indexes are best identified by: i) considering datasets with fine spatial resolution, whenever possible; ii) accounting for the vulnerability of the different crop growing stages to water-stress; iii) distinguishing between water scarce and water abundant events.

Green infrastructure-based hydrological modelling, a comparison between different urban districts, through the case of Szeged, Hungary

Because of the climate uncertainties caused by climate change and the growing urban areas, today’s cities face new environmental challenges. The impervious artificial elements change the urban water cycle. Urban districts with inadequate water infrastructure and treatment can be a major source of environmental risks, like urban flash floods. Modern cities need to be prepared for the changing environment in a sustainable way, which can be realised with the help of green infrastructure. The primary role of the green infrastructure is mitigation, such as surface runoff reduction and retainment. The aim of our research is to examine urban district scale data about the role of green infrastructure in urban water management. Hydrological models can provide adequate data about the surface runoff, infiltration and the mitigating effect of vegetation (interception and evaporation). We compared two significantly different urban districts (downtown and housing estate area), based on land cover and vegetation data. The analysis of the districts of Szeged (Hungary) suggests that the vegetation can significantly contribute to the reduction of surface runoff. Differences between these urban districts can be quantified, thus, these data can serve as a basis for urban water management planning processes.

Remote sensing and GIS application for monitoring drought vulnerability in Indonesia: a review

Agricultural drought is one of the hydrometeorological disasters that cause significant losses because it affects food stocks. In addition, agricultural droughts, impact the physical and socio-economic development of the community. Remote sensing technology is used to monitor agricultural droughts spatially and temporally for minimizing losses. This study reviewed the literatures related to remote sensing and GIS for monitoring drought vulnerability in Indonesia. The study was conducted on an island-scale on Java Island, a provincial-scale in East Java and Bali, and a district-scale in Indramayu and Kebumen. The dominant method was the drought index, which involves variable land surface temperature (LST), vegetation index, land cover, wetness index, and rainfall. Each study has a strong point and a weak point. Low-resolution satellite imagery has been used to assess drought vulnerability. At the island scale, it provides an overview of drought conditions, while at the provincial scale, it focuses on paddy fields and has little detailed information. In-situ measurements at the district scale detect meteorological drought accurately, but there were limitations in the mapping unit's detailed information. Drought mapping using GIS and remote sensing at the district scale has detailed spatial information on climate and physiographic aspects, but it needs temporal data monitoring.

Drought analysis and management for Tamil Nadu: Science-stakeholder-policy linkage

The complex and multi-dimensional nature of droughts in Tamil Nadu state and its impact on agricultural sector and farming community requires a thorough analysis for developing short and long– term adaptation and mitigation measures with institutional arrangement and policy support. In the present investigation, drought analysis was made for Tamil Nadu state using 148 years (1871 – 2018) monthly rainfall data obtained at district scale from India Meteorological Department (IMD) and Tamil Nadu Agricultural University by employing various drought indices. Larger co-efficient of variation (139 and 149 %) during the major growing seasons (Southwest and Northeast monsoon)evidenced high undependability of rainfall over Tamil Nadu. Drought Index (DI) analysis indicated a 51 per cent drought years in SWM and 48 per cent in NEM season, while Standardized Precipitation Index (SPI) exhibited 43 and 48 per cent of drought years in SWM and NEM respectively, indicating occurrence of drought once in every four years. More number of Consecutive Drought years (CDY) posed serious impacts on food production and livelihoods. Drought management framework as well as input for designing drought policy for Tamil Nadu.

Difficulties in the energy renovation processes of district heating buildings. Two case studies in a temperate climate

• The maintenance and update of old District Heating contribute to net zero districts. • Post-occupational studies are essential to control energy rehabilitation processes. • Distribution of payments according to consumption but maintaining a fixed cost. • Neighbours must understand what to expect in each step of the rehabilitation process. • Indoor overheating in winter is an issue if Heating District isn´t regulated. Renovation at district scale is a key strategy to reduce CO 2 emissions and energy consumptions by optimising the implementation of renewable energy sources and taking advantage of economies of scale. In this context, this paper focuses on assessing the positive impacts and difficulties after the energy rehabilitation of thermal envelopes in two buildings that belong to two different District Heating systems. The methodology is based on the comparative analysis of indoor temperatures data and energy consumption data of 17 monitored dwellings. The results showed a significant association between the improvement of envelopes and the increase of indoor temperatures in winter (β=0,644). Due to some technical and social barriers, the heating system was not regulated after the rehabilitation, so energy consumption was unnecessarily high, there were situations of indoor overheating in winter (maximum average indoor temperatures between 24-26°C) and these issues produced dissatisfaction on neighbours. In order to avoid these negative consequences, some recommendations are provided, such as informing neighbours about expectations in each step of the long rehabilitation process, reconsidering payments to promote the envelope rehabilitation but maintaining a fixed cost to protect vulnerable groups, and promoting post-occupational studies that contribute to the viability and up-date of this kind of District Heating systems.

COVID-19 pandemic hazard–risk–vulnerability analysis: a framework for an effective Pan-India response

This study evaluated the COVID-19 risk considering positive cases (as a hazard) and the demographic structure (as a socio-economic vulnerability) at districts scale across India using fuzzy analytical hierarchical process and geospatial modelling. Despite the fact that the high and very high COVID-19 hazard was observed in a limited area (14.2%, 233 districts), the proportion of high to very high COVID-19 risk was evident in larger regions (42.5%, 575 districts). A moderate to very high socio-economic vulnerability was recorded in major parts of the country (60.0%, 557 districts), while the districts with megacities had been severely affected due to the more complex urban and social systems. The study highlights the zones under high COVID-19 hazard and its possible linkages with vulnerability and risk at district scales in India that may effectively support emergency preparedness and response mechanisms during the different waves of the pandemic.

Developing machine-learning meta-models for high-rise residential district cooling in hot and humid climate

Cooling accounts for a significant amount of energy consumption in hot and humid climates, and district cooling is an energy-efficient solution. During its planning stage, an accurate and fast prediction of district cooling loads is required to assist decision-making. This study investigated the development of machine-learning-based meta-models to predict the cooling load of high-rise residential buildings at a district scale. Four machine-learning models have been evaluated, including Multiple Linear Regression, Support Vector Regression, Artificial Neural Networks (ANN), and eXtreme Gradient Boosting. The meta-model development starts with the sensitivity analysis to determine the critical parameters as independent variables. The results show that the ANN model with 30 neurons of the hidden layer, trained by eight epochs with 20% sample data, manifested superior performance when predicting monthly energy use intensity for the testing cases. A minimum of eight independent variables for the meta-model was also shown to be acceptable.

Trace-element imaging at macroscopic scale in a Belgian sphalerite-galena ore using Laser-Induced Breakdown Spectroscopy (LIBS)

Laser-Induced Breakdown Spectroscopy (LIBS) is a fast in-situ analytical technique based on spectroscopic analysis of atomic emission in laser-induced plasmas. Geochemical mapping at macroscopic scale using LIBS was applied to a decimetric Zn-Pb ore sample from east Belgium, which consists of alternating sphalerite and galena bands. A range of elements was detected with no or minimal spectral correction, including elements of interest for beneficiation such as Ge, Ag and Ga (although the detection of gallium could not be confirmed), and remediation, especially As and Tl. The comparison between LIBS and Energy Dispersive Spectroscopy (EDS) analyses showed that LIBS intensities reliably relate to elemental concentration although differences in spot size and detection limits exist between both techniques. The elemental images of minor and trace elements (Fe, Cu, Ag, Cd, Sb, As, Tl, Ge, Ni and Ba) obtained with LIBS revealed with great detail the compositional heterogeneity of the ore, including growth zones that were not visible on the specimen. In addition, each mineral generation has a distinct trace-element composition, reflecting a geochemical sequence whose potential metallogenic significance at the district scale should be addressed in further work. Although qualitative and preliminary, the obtained LIBS dataset already produced a wealth of information that allowed to initiate discussion on some genetical and crystallochemical aspects. Above all, LIBS appears as a powerful tool for screening geochemically large samples for the selection of zones of particular interest for further analysis.

Enhancing resilience in a post-industrial city through the urban regeneration of the downtown district. A case study of part of downtown Lodz called Nowa Dzielnica

Lodz is a post-industrial city in central Poland, the third largest in terms of population and with the largest area of downtown districts in the country. The regeneration of historical districts is one of the main challenges of the local urban policy here, as in many other post-industrial cities. Urban regeneration is understood as cohesive changes implemented in terms of social, economic and spatial conditions on degraded areas, according to mechanisms introduced by the Urban Renewal Act. Another consideration is climate change, which requires an in-depth approach to design objectives so that they include certain solutions increasing the city’s resilience to climatic events. In accordance with the European Union’s policy, in 2013, the Polish Council of Ministers adopted the Strategic Adaptation Plan for sectors and areas sensitive to climate changes until 2020, looking forward to 2030. The implementation of this plan was entrusted to the Ministry of the Environment, in partnership with 44 cities with a population of over 100,000 residents, including Lodz. The city’s adaptation plan to climate changes until 2030 indicates that the most vulnerable areas of the city are those of high-intensity residential development. These areas are particularly vulnerable to the phenomena of urban heat islands, urban flooding, storms, and smog. The article shows the planning assumptions for the part of the centre called Nowa Dzielnica (New District). It is an interesting example of implementing local spatial policy at district scale, but also on a much larger scale than usually adopted in local plans. The Nowa Dzielnica downtown section was described in a sequence of four local land use plans. This constitutes an example of spatial management at local government level, which may define the direction of changes for downtown districts in other post-industrial cities. It serves as a good example of implementing changes for centres where both urban regeneration and resilience urban planning constitute important elements of urban policy.

A Study on the potential of branding aspect in Balikpapan Kota District, Balikpapan City, Indonesia

Balikpapan is experiencing urbanization quite rapidly and has a role in residential development to accommodate the needs of its citizen. One of the strategic issues of settlements in Balikpapan is the settlements that have decreased in quality in settlement area. Based on the City Service Center System Plan of the Balikpapan Spatial Plan, Balikpapan Kota District functions as a Government Service Center, Trade and Service Center, Health Service Center, and Education Center in a City-wide Scale. Balikpapan Kota District Settlement Area is included in the area with a mild level of slum. Naturally, this will result in a shift in public perception of the area and, thus, undermines the image of the area or, arguably, the area does not have the essence of city branding value. Thus, it is necessary to study the potential in the aspect of branding in the Balikpapan Kota District Settlement Area. In achieving these objectives, an analysis related to the city’s branding aspects was carried out. The branding aspect approach in this study used the City Branding Hexagon approach. The analysis was conducted by means of quantitative descriptive method (scoring method). The results of this study provided a score from the branding aspect of the settlement area. The results of the branding aspects analysis in the Balikpapan Kota District have been identified from the neighbourhood, sub-district, and district scale. Balikpapan Kota District Settlement Area has the most substantial potential in the dimensions of Potential (2.90) and Prerequisite (2.76). There are two branding potentials but they are quite weak compared to the other aspects, which are the Presence (1.75) and Pulse (1.67) dimensions. Moreover, there are dimensions of Place (2.03) and People (2.50), which have potential that can be developed.

Smart District and Circular Economy: The Role of ICT Solutions in Promoting Circular Cities

Cities will have a decisive role in reducing the consumption of resources and greenhouse gas emissions by 2050. Various experiences of urban regeneration have exploited Information and Communication Technology (ICT) potentialities to optimize the management of complex systems and to encourage sustainable development models. This paper investigates the role of ICT technologies in favouring emerging design for Circular Economy (CE) in the urban context. The paper starts by defining the theoretical background and subsequently presents the goal and methodology of investigation. Through a scoping review, the authors identify case studies and analyse them within the Ellen MacArthur Foundation classification framework that splits the urban context into three urban systems: buildings, mobility and products. The research focuses on nine case studies where the ICT solutions were able to promote the principles of CE. The results show, on the one hand, how data management appears to be a central issue in the optimization of urban processes and, on the other hand, how the district scale is the most appropriate to test innovative solutions. This paper identifies physical and virtual infrastructures, stakeholders and tools for user engagement as key elements for the pursuit of CE adoption in the urban context.

Demand-side flexibility in a residential district: What are the main sources of uncertainty?

With the increasing share of intermittent renewable energy sources in the energy mix, demand-side flexibility is likely to play a key role in the future. For buildings, flexibility is defined as the ability to shift their energy consumption away from “peak periods” i.e. high-demand periods of the electrical network. In France, these episodes occur mainly during the wintertime due to the significant demand for space heating. To achieve flexibility objectives, we explore an indirect control strategy at district scale by adjusting the dwelling thermostat during peak periods. The study is conducted over 337 dwellings in order to better predict the load curve by taking advantage of the aggregation effect. Three main research questions are addressed in relation to the assessment of flexibility potential: (i) the effect of aggregation, (ii) the identification of the most influencing factors, including occupant behavior, and (iii) the quantification of uncertainties. Using an urban building energy modeling tool populated with various national data sources (building envelope, energy class of equipment, etc), we perform a sensitivity analysis on 22 parameters representing the geometry, the appliances, the building characteristics, the occupants, and the grid. The output indicator is the average power shifted during the flexibility (or demand response) event. From this analysis, 7 parameters appear as being the most influential. A regression analysis on these parameters is performed, depending on both the duration of the event and the typology of district. The results show that the duration of the flexibility event and the occupant pre-selected temperature change are the most influential parameters. It results to approximately ± 90 W of uncertainty on an average potential of 290 W of shiftable power per household in a recent district. Furthermore, the occupants are highlighted as making a significant contribution to flexibility. Finally, we observed that the thermal properties investigated with the study of an old fabric district play a key role. Low thermal performance means high heating consumption and increased flexibility potential, but a similar relative uncertainty.