Environmental monitoring
Objective well-being level (OWL) composite indicator for sustainable and resilient cities
Well-being is a critical element of the 2030 Agenda for Sustainable Development Goals. Given the complexity of the concept of well-being, it follows that its measurement requires complex, multivariate methods that can characterize the physical, economic, social and environmental aspects along with the mental state of a city. Although it is not sufficient to carry out settlement-level analyses to make cities inclusive, safe, resilient and sustainable. It is necessary to understand patterns within settlements. This work aims to present how the urban macrostructure of urban well-being indicators can be estimated based on GIS-based multilayer analysis. Open-source data, e.g. road networks, points of interest, green spaces and vegetation, are used to estimate urban well-being parameters such as noise levels, air quality and health-related impacts supplemented by climate models to assess urban resilience and sustainability. The proposed methodology integrates 24 models into six categories, namely walkability, environment, health, society, climate change and safety, which are weighted based on a multilevel Principal Component Analysis to minimize information loss for aggregated composite indicators. The study revealed two main components of the macrostructure related to well-being in the studied city: one related to the geometrical features and the other can be derived from the structure of the natural environment. In Veszprém a natural restoration of the detached house area, industrial area and downtown is recommended including developments with green and blue infrastructural elements and nature-based solutions.
Post date: 09 January 2024
Surface Water Monitoring Systems—The Importance of Integrating Information Sources for Sustainable Watershed Management
The complex interactions from anthropogenic activities, climate change, sedimentation and the input of wastewater has significantly affected the aquatic environment and entire ecosystem. Over the years, the researchers have investigated water monitoring approaches in terms of traditional monitoring or even integrated systems to handle such an environmental assessment and predictions based on warning systems. However, research into the selection and optimization of water monitoring systems by the combination of parallel approach in terms of sampling techniques, process analysis and results is limited. The research objectives of the present study are to evaluate the existing water monitoring systems based on the latest approach and then provide insights into factors affecting sensor implementation at sampling locations. Here we summarize the advancement and trends of various water monitoring systems as well as the suitability of sensor placement in the area by reviewing more than 300 papers published between 2011 and 2022. The research highlights the urgency of an integrative approach with regard to water monitoring systems including water quality model and water quantity model. A framework is proposed to incorporate all water monitoring approaches, sampling techniques, and predictive models to provide comprehensive information about environmental assessment. It was observed that the urgency of model-based approaches as verification and fusion of data assemble has the ability to improve the performances of the systems. Furthermore, integrated systems with the inclusion of a separate modeling approach through integrated, semi-mechanistic models, data science and artificial intelligence are recommended in the future. Overall, this study provides guidelines for achieving standardized water management by implementing integrated water monitoring systems.
Post date: 31 March 2023
Indicators for climate change-driven urban health impact assessment
Climate change can cause multiply potential health issues in urban areas, which is the most susceptible environment in terms of the presently increasing climate volatility. Urban greening strategies make an important part of the adaptation strategies which can ameliorate the negative impacts of climate change. It was aimed to study the potential impacts of different kinds of greenings against the adverse effects of climate change, including waterborne, vector-borne diseases, heat-related mortality, and surface ozone concentration in a medium-sized Hungarian city. As greening strategies, large and pocket parks were considered, based on our novel location identifier algorithm for climate risk minimization.
A method based on publicly available data sources including satellite pictures, climate scenarios and urban macrostructure has been developed to evaluate the health-related indicator patterns in cities. The modelled future- and current patterns of the indicators have been compared. The results can help the understanding of the possible future state of the studied indicators and the development of adequate greening strategies.
Another outcome of the study is that it is not the type of health indicator but its climate sensitivity that determines the extent to which it responds to temperature rises and how effective greening strategies are in addressing the expected problem posed by the factor.
Post date: 16 September 2022
Trájer, Attila J., Sebestyén, V.., Domokos, E., Abonyi, J. (2022). Indicators for climate change-driven urban health impact assessment. Journal of Environmental Management, 323, 116165.
Network-Based Topological Exploration of the Impact of Pollution Sources on Surface Water Bodies
We developed a digital water management toolkit to evaluate the importance of the connections between water bodies and the impacts caused by pollution sources. By representing water bodies in a topological network, the relationship between point loads and basic water quality parameters is examined as a labelled network. The labels are defined based on the classification of the water bodies and pollution sources. The analysis of the topology of the network can provide information on how the possible paths of the surface water network influence the water quality. The extracted information can be used to develop a monitoring- and evidence-based decision support system. The methodological development is presented through the analysis of the physical-chemical parameters of all surface water bodies in Hungary, using the emissions of industrial plants and wastewater treatment plants. Changes in water quality are comprehensively assessed based on the water quality data recorded over the past 10 years. The results illustrate that the developed method can identify critical surface water bodies where the impact of local pollution sources is more significant. One hundred six critical water bodies have been identified, where special attention should be given to water quality improvement.
Identification of sampling points for the detection of SARS-CoV-2 in the sewage system
A suitable tool for monitoring the spread of SARS-CoV-2 is to identify potential sampling points in the wastewater collection system that can be used to monitor the distribution of COVID-19 disease affected clusters within a city. The applicability of the developed methodology is presented through the description of the 72,837 population equivalent wastewater collection system of the city of Nagykanizsa, Hungary and the results of the analytical and epidemiological measurements of the wastewater samples. The wastewater sampling was conducted during the 3rd wave of the COVID-19 epidemic. It was found that the overlap between the road system and the wastewater network is high, it is 82 %. It was showed that the proposed methodological approach, using the tools of network science, determines confidently the zones of the wastewater collection system and provides the ideal monitoring points in order to provide the best sampling resolution in urban areas. The strength of the presented approach is that it estimates the network based on publicly available information. It was concluded that the number of zones or sampling points can be chosen based on relevant epidemiological intervention and mitigation strategies. The algorithm allows for continuous effective monitoring of the population infected by SARS-CoV-2 in small-sized cities.
