Spatial modelling of air pollution in urban areas with GIS: a case study on integrated database development

International audienceA wide range of data collected by monitoring systems and by mathematical and physical modelling can be managed in the frame of spatial models developed in GIS. In addition to data management and standard environmental analysis of air pollution, data from remote sensing (aerial and satellite images) can ehance all data sets. In spite of the fact that simulation of air pollutant distribution is carried out by standalone computer systems, the spatial database in the framework of the GIS is used to support decision-making processes in a more efficient way. Mostly, data are included in the map layers as attributes. Other map layers are carried out by the methods of spatial interpolation, raster algebra, and case oriented analysis. A series of extensions is built into the GIS to adapt its functionality. As examples, the spatial models of a flat urban area and a street canyon with extensive traffic polluted with NOx are constructed. Different scales of the spatial models require variable methods of construction, data management, and spatial data sources. The measurement of NOx and O3 by an automatic monitoring system and data from the differential absorption LIDAR are used for investigation of air pollution. Spatial data contain digital maps of both areas, complemented by digital elevation models. Environmental analyses represent spatial interpolations of air pollution that are displayed in horizontal and vertical planes. Case oriented analyses are mostly focused on risk assessment methods. Finally, the LIDAR monitoring results and the results obtained by modelling and spatial analyses are discussed in the context of environmental management of the urban areas. The spatial models and their extensions are developed in the framework of the ESRI's ArcGIS and ArcView programming tools. Aerial and satellite images preprocessed by the ERDAS Imagine represent areas of Prague

Eco-town: An integrated modeling framework for simulating the effects of urban morphology on sustainable development

Spatial structure of a city is a key determinant of its socioeconomic well-being and there is a growing interest in models that investigate the relation between spatial structure and sustainable urban development. This dissertation aims to examine the role of urban spatial structure on social, economic, and environmental dimensions of sustainability through developing an integrated modeling framework. In particular, this modeling framework bridges design of urban built environment and sustainable development at the city-region level through simulation and measuring the effect of changes in urban spatial structure on the stock of various asset forms including natural, human, and physical capital.;The proposed methodology consists of an integrated modeling framework through which various spatial configurations of the selected urban facilities are simulated and simulation outputs are evaluated in terms of sustainability. This framework consists of four components: i. a spatial database, ii. a land suitability analysis, iii. a spatial optimization model which is a combination of optimal facility location and optimal shopping frequency models and iv. a sustainability assessment. The sustainability metrics of Genuine Progress Indicator (GPI) is employed to evaluate simulation results and reveal the direction and magnitude of effects.;The modeling framework was applied to the study area of Morgantown, West Virginia for a case of locating food and beverage stores. The simulation results were generalized into a set of monocentric, polycentric and decentralized scenarios in order to measure the GPI level\u27s change due to the changes in the spatial configuration of food and beverage stores. The results show that even a modest change in the spatial configuration of an urban facility (food and beverage store) can significantly change the urban sustainability level as measured by GPI

Urban metabolism and land use modeling for urban designers and planners: A land use model for the Integrated Urban Metabolism Analysis Tool

Predicting the resource consumption in the built environment and its associated environmental consequences (urban metabolism analysis) is one of the core challenges facing policy-makers and planners seeking to increase the sustainability of urban areas. There is a critical need for a single integrated framework to analyze the consequences of urban growth and eventually predict the impacts of sustainable policies on the urbanscape. This dissertation presents the development of an Integrated Urban Metabolism Analysis Tool (IUMAT) – an analytical framework that simulates urban metabolism by integrating urban subsystems in a single comprehensive computational environment. It reviews the existing literature on urban sustainability, urban metabolism, as well as introducing the general framework for IUMAT. IUMAT uses three separate models for quantifying environmental impacts of land-use transition, consumption of resources, and transportation. This work outlines the development of IUMAT Land-Use Model that uses Remote Sensing, GIS, and Artificial Neural Networks (ANNs) to predict land use change patterns. By using Density-Based Spatial Clustering and normal equations, this dissertation introduces a method for generating building-form variables from Light Detection and Ranging (LIDAR) data, which can be used as a new determinant factor in land-use change modeling. The proposed Land-use Model, within IUMAT or other analytical models, can be useful to local planning officials in understanding the complexity of land-use change and developing enhanced land-use policies

Geographical information system and environmental epidemiology: a cross-sectional spatial analysis of the effects of traffic-related air pollution on population respiratory health

<p>Abstract</p> <p>Background</p> <p>Traffic-related air pollution is a potential risk factor for human respiratory health. A Geographical Information System (GIS) approach was used to examine whether distance from a main road (the Tosco-Romagnola road) affected respiratory health status.</p> <p>Methods</p> <p>We used data collected during an epidemiological survey performed in the Pisa-Cascina area (central Italy) in the period 1991-93. A total of 2841 subjects participated in the survey and filled out a standardized questionnaire on health status, socio-demographic information, and personal habits. A variable proportion of subjects performed lung function and allergy tests. Highly exposed subjects were defined as those living within 100 m of the main road, moderately exposed as those living between 100 and 250 m from the road, and unexposed as those living between 250 and 800 m from the road. Statistical analyses were conducted to compare the risks for respiratory symptoms and diseases between exposed and unexposed. All analyses were stratified by gender.</p> <p>Results</p> <p>The study comprised 2062 subjects: mean age was 45.9 years for men and 48.9 years for women. Compared to subjects living between 250 m and 800 m from the main road, subjects living within 100 m of the main road had increased adjusted risks for persistent wheeze (OR = 1.76, 95% CI = 1.08-2.87), COPD diagnosis (OR = 1.80, 95% CI = 1.03-3.08), and reduced FEV₁/FVC ratio (OR = 2.07, 95% CI = 1.11-3.87) among males, and for dyspnea (OR = 1.61, 95% CI = 1.13-2.27), positivity to skin prick test (OR = 1.83, 95% CI = 1.11-3.00), asthma diagnosis (OR = 1.68, 95% CI = 0.97-2.88) and attacks of shortness of breath with wheeze (OR = 1.67, 95% CI = 0.98-2.84) among females.</p> <p>Conclusion</p> <p>This study points out the potential effects of traffic-related air pollution on respiratory health status, including lung function impairment. It also highlights the added value of GIS in environmental health research.</p

Quiet paths for people : developing routing analysis and Web GIS application

Altistuminen saasteille saattaa vähentää merkittävästi aktiivisten liikkumismuotojen, kuten kävelyn ja pyöräilyn terveyshyötyjä. Yksi liikenteestä johtuvista saasteista on melu, joka voi aiheuttaa terveyshaittoja, kuten kohonnutta verenpainetta ja stressiä. Aikaisemmissa tutkimuksissa ja selvityksissä melulle altistumista on arvioutu yleensä kotipaikan suhteen ja liikkumisen aikana tapahtuva altistus on jäänyt vähemmälle huomiolle. Koska liikkumisen aikainen (dynaaminen) melualtistus saattaa muodostaa merkittävän oan kaupunkilaisten päivittäisestä kokonaismelualtistuksesta, tarvitaan kehittyneempiä menetelmiä dynaamisen melualtistuksen arvioimiseen ja vähentämiseen. Tässä tutkielmassa kehitin kävelyn reititysmenetelmän ja sovelluksen, jolla voi 1) etsiä lyhimmän reitin, 2) mallintaa kävelyn aikaisen melualtistuksen ja 3) löytää vaihtoehtoisia, hiljaisempia reittejä. Sovellus hyödyntää OpenStreetMap-tieverkostoaineistoa ja mallinnettua aineistoa tieliikenteen tyypillisistä päiväajan melutasoista. Reitinetsintä perustuu kehittämääni melukustannusfunktioon ja alhaisimman kustannuksen reititysanalyysiin. Melukustannukset lasketaan sovelluksessa lukuisilla eri meluherkkyyskertoimilla, minkä ansiosta sovellus löytää useita vaihtoehtoisia (hiljaisempia) reittejä. Jotta eri reittien meluisuutta (melualtistuksia) voidaan vertailla, kehitin sarjan melualtistusindeksejä. Tapaustutkimuksessa tutkin Helsingistä tehtävien työmatkojen aikaisia melualtistuksia; selvitin rekistereihin perustuvien työmatkojen mukaiset joukkoliikennereitit ja tutkin reittien kävelyosuuksien aikaisia melualtistuksia reitittämällä kävelyreitit uudestaan kehittämälläni reitityssovelluksella. Lisäksi tutkin hiljaisempien reittivaihtoehtojen mahdollistamia vähennyksiä melualtistuksissa tapaustutkimuksessa mallinnetuilla kävelyreiteillä. Tapaustutkimuksen tulokset indikoivat, että tyypilliset dynaamiset melualtistukset vaihtelevat huomattavasti eri asuinpaikkojen välillä. Toisaalta merkittävä osa melulle altistumisesta on mahdollista välttää hiljaisemmilla reittivaihtoehdoilla; tilanteesta riippuen, hiljaisemmat reitit tarjoavat keskimäärin 12–57 % vähennyksen altistuksessa yli 65 dB melutasoille ja 1.6–9.6 dB keskimääräisen vähennyksen reittien keskimääräisessä melutasossa. Altistuksen mahdolliseen vähennykseen näyttäisivät vaikuttavan ainakin 1) melualtistuksen suuruus lyhimmällä (ts. verrokki) reitillä, 2) lyhimmän reitin pituus, eli etäisyys lähtö- ja kohdepisteen välillä reititysgraafissa ja 3) hiljaisemman reitin pituus lyhimpään reittiin verrattuna. Julkaisin hiljaisten kävelyreittien reitityssovelluksen avoimena web-rajapintapalveluna (API - Application Programming Interface) ja kehitin hiljaisten kävelyreittien reittioppaan mobiilioptimoituna web-karttasovelluksena. Kaikki tutkielmassa kehitetyt menetelmät ja lähdekoodit ovat avoimesti saatavilla GitHub-palvelussa. Yksilöiden ja kaupunkisuunnittelijoiden tietoutta dynaamisesta altistuksesta melulle (ja muille saasteille) tulisi lisätä kehittämällä altistusten arviointiin ja vähentämiseen kehittyneempiä analyyseja ja sovelluksia. Tässä tutkielmassa kehitetty web-karttasovellus havainnollistaa hiljaisten reittien reititysmenetelmän toimivuutta tosielämän tilanteissa ja voi näin ollen auttaa jalankulkijoita löytämään hiljaisempia, ja siten terveellisempiä, reittivaihtoehtoja. Kun ympäristöllisiin altistuksiin perustuvaa reitinetsintää kehitetään pidemmälle, tulisi pyrkiä huomioimaan useampia erillisiä altistuksia samanaikaisesti ja siten reitittämään yleisesti ottaen terveellisempiä reittejä.It is likely that journey-time exposure to pollutants limit the positive health effects of active transport modes (e.g. walking and cycling). One of the pollutants caused by vehicular traffic is traffic noise, which is likely to cause various negative health effects such as increased stress levels and blood pressure. In prior studies, individuals’ exposure to community noise has usually been assessed only with respect to home location, as required by national and international policies. However, these static exposure assessments most likely ignore a substantial share of individuals’ total daily noise exposure that occurs while they are on the move. Hence, new methods are needed for both assessing and reducing journey-time exposure to traffic noise as well as to other pollutants. In this study, I developed a multifunctional routing application for 1) finding shortest paths, 2) assessing dynamic exposure to noise on the paths and 3) finding alternative, quieter paths for walking. The application uses street network data from OpenStreetMap and modeled traffic noise data of typical daytime traffic noise levels. The underlying least cost path (LCP) analysis employs a custom-designed environmental impedance function for noise and a set of (various) noise sensitivity coefficients. I defined a set of indices for quantifying and comparing dynamic (i.e. journey-time) exposure to high noise levels. I applied the developed routing application in a case study of pedestrians’ dynamic exposure to noise on commuting related walks in Helsinki. The walks were projected by carrying out an extensive public transport itinerary planning on census based commuting flow data. In addition, I assessed achievable reductions in exposure to traffic noise by taking quieter paths with statistical means by a subset of 18446 commuting related walks (OD pairs). The results show significant spatial variation in average dynamic noise exposure between neighborhoods but also significant achievable reductions in noise exposure by quieter paths; depending on the situation, quieter paths provide 12–57 % mean reduction in exposure to noise levels higher than 65 dB and 1.6–9.6 dB mean reduction in mean dB (compared to the shortest paths). At least three factors seem to affect the achievable reduction in noise exposure on alternative paths: 1) exposure to noise on the shortest path, 2) length of the shortest path and 3) length of the quiet path compared to the shortest path. I have published the quiet path routing application as a web-based quiet path routing API (application programming interface) and developed an accompanying quiet path route planner as a mobile-friendly web map application. The online quiet path route planner demonstrates the applicability of the quiet path routing method in real-life situations and can thus help pedestrians to choose quieter paths. Since the quiet path routing API is open, anyone can query short and quiet paths equipped with attributes on journey-time exposure to noise. All methods and source codes developed in the study are openly available via GitHub. Individuals’ and urban planners’ awareness of dynamic exposure to noise and other pollutants should be further increased with advanced exposure assessments and routing applications. Web-based exposure-aware route planner applications have the potential to help individuals to choose alternative, healthier paths. When developing exposure-based routing analysis further, attempts should be made to enable simultaneously considering multiple environmental exposures in order to find overall healthier paths

Use of Bayesian Inference Method to Model Vehicular Air Pollution in Local Urban Areas

The file attached to this record is the author's final peer reviewed version.Traffic Related Air Pollution (TRAP) studies are usually investigated using different categories such as air pollution exposure for health impacts, urban transportation network design to mitigate pollution, environmental impacts of pollution, etc. All of these subfields often rely on a robust air pollution model, which also necessitates an accurate prediction of future pollutants. As is widely accepted by the heath authorities, TRAP is considered to be the major health issue in urban areas, and it is difficult to keep pollution at harmless levels if the time sequenced dynamic pollution and traffic parameters are not identified and modelled efficiently. In our work here, artificial intelligence techniques, such as Bayesian Networks with an optimized configuration, are used to deliver a probabilistic traffic data analysis and predictive modelling for air pollution (SO2, NO2 and CO) at very local scale of an urban region with up to 85% accuracy. The main challenge for traditional data analysis is a lack of capability to reveal the hidden links between distant data attributes (e.g. pollution sources, dynamic traffic parameters, etc.), whereas some subtle effects of these parameters or events may play an important role in pollution on a long-term basis. This study focuses on the optimisation of Bayesian Networks to unveil hidden links and to increase the prediction accuracy of TRAP considering its further association with a predictive GIS syste

MANAGING CO2 EMISSIONS REGIONALLY USING GEOGRAPHICAL INFORMATION SYSTEM (GIS) SPATIAL MODELING AND PINCH ANALYSIS

Climate change has become the major global challenge of sustainability; among various anthropogenic sources of carbon dioxide (CO2) emissions, the burning of fossil fuels for energy to support commercial, residential, municipal and industrial sectors is considered to be the primary cause of increasing levels of carbon dioxide emissions. However, because climate change is regionally driven with global consequences, to analyze emissions data, energy planning techniques must be developed which are simple, replicable and optimized for maximum benefit. Climate scenarios are continually derived from global models despite these models containing little to no regional or local specificity. Place-based research, well grounded in local experience, offers a more tractable alternative for defining complex interactions among the environmental, economic, and social processes that drive greenhouse gas emissions. The focus of this study involves the development of a balanced energy supply and demand model under carbon constraints for the Southern Illinois energy sector; this sector represents the local specificity desired to build a carbon emissions pinch analysis model at the local level. This project is intended to formulate a robust methodology for constructing a Geographic Data Base Management System by employing a bottom/up approach to CO2 emissions modeling; the resulting data base can serve as the foundation for an environmental applications model employing pinch analysis techniques to address the allocation of energy resources and technologies to reduce CO2 emissions

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Engenharia de sistemas baseada em modelos: um sistema para o tráfego & ambiente

Doutoramento em Gestão IndustrialThe contemporary world is crowded of large, interdisciplinary, complex systems made of other systems, personnel, hardware, software, information, processes, and facilities. The Systems Engineering (SE) field proposes an integrated holistic approach to tackle these socio-technical systems that is crucial to take proper account of their multifaceted nature and numerous interrelationships, providing the means to enable their successful realization. Model-Based Systems Engineering (MBSE) is an emerging paradigm in the SE field and can be described as the formalized application of modelling principles, methods, languages, and tools to the entire lifecycle of those systems, enhancing communications and knowledge capture, shared understanding, improved design precision and integrity, better development traceability, and reduced development risks. This thesis is devoted to the application of the novel MBSE paradigm to the Urban Traffic & Environment domain. The proposed system, the GUILTE (Guiding Urban Intelligent Traffic & Environment), deals with a present-day real challenging problem “at the agenda” of world leaders, national governors, local authorities, research agencies, academia, and general public. The main purposes of the system are to provide an integrated development framework for the municipalities, and to support the (short-time and real-time) operations of the urban traffic through Intelligent Transportation Systems, highlighting two fundamental aspects: the evaluation of the related environmental impacts (in particular, the air pollution and the noise), and the dissemination of information to the citizens, endorsing their involvement and participation. These objectives are related with the high-level complex challenge of developing sustainable urban transportation networks. The development process of the GUILTE system is supported by a new methodology, the LITHE (Agile Systems Modelling Engineering), which aims to lightening the complexity and burdensome of the existing methodologies by emphasizing agile principles such as continuous communication, feedback, stakeholders involvement, short iterations and rapid response. These principles are accomplished through a universal and intuitive SE process, the SIMILAR process model (which was redefined at the light of the modern international standards), a lean MBSE method, and a coherent System Model developed through the benchmark graphical modeling languages SysML and OPDs/OPL. The main contributions of the work are, in their essence, models and can be settled as: a revised process model for the SE field, an agile methodology for MBSE development environments, a graphical tool to support the proposed methodology, and a System Model for the GUILTE system. The comprehensive literature reviews provided for the main scientific field of this research (SE/MBSE) and for the application domain (Traffic & Environment) can also be seen as a relevant contribution.O mundo contemporâneo é caracterizado por sistemas de grande dimensão e de natureza marcadamente complexa, sócio-técnica e interdisciplinar. A Engenharia de Sistemas (ES) propõe uma abordagem holística e integrada para desenvolver tais sistemas, tendo em consideração a sua natureza multifacetada e as numerosas inter-relações que advêm de uma quantidade significativa de diferentes pontos de vista, competências, responsabilidades e interesses. A Engenharia de Sistemas Baseada em Modelos (ESBM) é um paradigma emergente na área da ES e pode ser descrito como a aplicação formal de princípios, métodos, linguagens e ferramentas de modelação ao ciclo de vida dos sistemas descritos. Espera-se que, na próxima década, a ESBM desempenhe um papel fundamental na prática da moderna Engenharia de Sistemas. Esta tese é dedicada à aplicação da ESBM a um desafio real que constitui uma preocupação do mundo actual, estando “na agenda” dos líderes mundiais, governantes nacionais, autoridades locais, agências de investigação, universidades e público em geral. O domínio de aplicação, o Tráfego & Ambiente, caracteriza-se por uma considerável complexidade e interdisciplinaridade, sendo representativo das áreas de interesse para a ES. Propõe-se um sistema (GUILTE) que visa dotar os municípios de um quadro de desenvolvimento integrado para adopção de Sistemas de Transporte Inteligentes e apoiar as suas operações de tráfego urbano, destacando dois aspectos fundamentais: a avaliação dos impactos ambientais associados (em especial, a poluição atmosférica e o ruído) e a divulgação de informação aos cidadãos, motivando o seu envolvimento e participação. Estes objectivos relacionam-se com o desafio mais abrangente de desenvolver redes de transporte urbano sustentáveis. O processo de desenvolvimento do sistema apoia-se numa nova metodologia (LITHE), mais ágil, que enfatiza os princípios de comunicação contínua, feedback, participação e envolvimento dos stakeholders, iterações curtas e resposta rápida. Estes princípios são concretizados através de um processo de ES universal e intuitivo (redefinido à luz dos padrões internacionais), de um método simples e de linguagens gráficas de modelação de referência (SysML e OPDs/OPL). As principais contribuições deste trabalho são, na sua essência, modelos: um modelo revisto para o processo da ES, uma metodologia ágil para ambientes de desenvolvimento baseados em modelos, uma ferramenta gráfica para suportar a metodologia proposta e o modelo de um sistema para as operações de tráfego & ambiente num contexto urbano. Contribui-se ainda com uma cuidada revisão bibliográfica para a principal área de investigação (ES/ESBM) e para o domínio de aplicação (Tráfego & Ambiente)