Air pollution: a study of citizen's attitudes and behaviors using different information sources

Background: From November 2015 to January 2016, the routine air monitoring showed a peak of air pollution (in particular of PM10) that caused alarm in many Italian cities and was widely reported by mass media. After some weeks from this alarm, we tried to evaluate the citizen awareness and interest towards air pollution together with their positive behaviors, using different information sources. Methods: From September 2015 to March 2016, in parallel with the number of exceedances of the PM10 in Italy we evaluated the press coverage, the average monthly searches on Google and the interest on Twitter. Moreover, a qualitative content analysis on daily newspapers was conducted and a self-compiled questionnaire on the attitudes and behaviors about environmental issues and their determinants was administered to 598 parents involved in the project MAPEC_LIFE (LIFE12 ENV/IT/00614). Results: The media coverage of the theme of air pollution was very high from the end of 2015 to the beginning of 2016, as well as internet searches and twitter messages. Our qualitative analysis highlighted that only a small portion of articles included information about positive behaviors and environmental awareness. Despite the high media coverage and the satisfactory self-perceived knowledge, the majority of respondents judged negatively the received information (as untrue and incomplete) and declared a limited adoption of pro-environmental behaviors.  Conclusion: The parallel study of mass media information and people’s attitudes and behaviors seem to indicate that the high media coverage was not followed by a very high motivation towards pro-environmental behaviors

Linking geosocial sensing with the socio-demographic fabric of smart cities

Technological advances have enabled new sources of geoinformation, such as geosocial media, and have supported the propagation of the concept of smart cities. This paper argues that a city cannot be smart without citizens in the loop, and that a geosocial sensor might be one component to achieve that. First, we need to better understand which facets of urban life could be detected by a geosocial sensor, and how to calibrate it. This requires replicable studies that foster longitudinal and comparative research. Consequently, this paper examines the relationship between geosocial media content and socio-demographic census data for a global city, London, at two administrative levels. It aims for a transparent study design to encourage replication, using Term Frequency—Inverse Document Frequency of keywords, rule-based and word-embedding sentiment analysis, and local cluster analysis. The findings of limited links between geosocial media content and socio-demographic characteristics support earlier critiques on the utility of geosocial media for smart city planning purposes. The paper concludes that passive listening to publicly available geosocial media, in contrast to pro-active engagement with citizens, seems of limited use to understand and improve urban quality of life

A SMART AIR POLLUTION MONITORING SYSTEM

Air pollution affects our day to day activities and quality of life. It poses a threat to the ecosystem and the quality of life on the planet. The dire need to monitor air quality is very glaring, owing to increased industrial activities over the past years. People need to know the extent to which their activities affect air quality. This project proposes an air pollution monitoring system. The system was developed using the Arduino microcontroller. The air pollution monitoring system was designed to monitor and analyze air quality in real-time and log data to a remote server, keeping the data updated over the internet. Air quality measurements were taken based on the Parts per Million (PPM) metrics and analyzed using Microsoft Excel. The air quality measurements taken by the designed system was accurate. The result was displayed on the designed hardware’s display interface and could be accessed via the cloud on any smart mobile device

Right to the map? Counter-mapping practices of smog alerts and urban greenery movements in Poland

Data production is becoming an emerging trend in critical urban activism. Precise and reliable public information, including spatial and environmental information, serves individual and collective ‘right to the city’ beliefs. One of the common strategies adopted by contemporary urban movements to ensure the accuracy and inclusiveness of urban data production processes are various forms of counter-mapping, which we introduce in this paper as a perspective aimed in critical evaluation of urban environmental conditions in Polish cities. By process tracing of smog alerts and urban greenery movements, we investigate the main strategies of using such tools and their effects for both particular social actors, and general urban environmental policy. We argue that the core idea of a citizen-driven collection of geographical data is strongly supported by its other features - social involvement and collective production of visualizations illustrating the scale and dynamics of particular environmental problems. In this sense, counter-mapping is aimed rather at repoliticizing urban environmental data in order to critically evaluate existing urban policy, than just to ensure greater citizen involvement in environmental decision-making

Social Space and Social Media: Analyzing Urban Space with Big Data

This dissertation focuses on the key role that big data can play in minimizing the perceived disconnect between social theory and quantitative methods in the discipline of geography. It takes as its starting point the geographic concept of space, which is conceptualized very differently in social theory versus quantitative methodology. Contrary to this disparity, an examination of the disciplinary history reveals a number of historic precedents and potential pathways for a rapprochement, especially when combined with some of the new possibilities of big data. This dissertation also proposes solutions to two common barriers to the adoption of big data in the social sciences: accessing and collecting such data and, subsequently, meaningful analysis. These methods and the theoretical foundation are combined in three case studies that show the successful integration of a quantitative research methodology with social theories on space. The case studies demonstrate how such an approach can create new and alternative understandings of urban space. In doing so it answers three specific research questions: (1) How can big data facilitate the integration of social theory on space with quantitative research methodology? (2) What are the practical challenges and solutions to moving “beyond the geotag” when utilizing big data in geographical research? (3) How can the quantitative analysis of big data provide new and useful insight in the complex character of social space? More specifically, what insights does such an analysis of relational social space provide about urban mobility and cognitive neighborhoods

A Densely-Deployed, High Sampling Rate, Open-Source Air Pollution Monitoring WSN

Air quality, especially particulate matter, has recently attracted a lot of attention from governments, industry, and academia, motivating the use of denser air quality monitoring networks based on low-cost sensing strategies. However, low-cost sensors are frequently sensitive to aging, environmental conditions, and pollutant cross-sensitivities. These issues have been only partially addressed, limiting their usage. In this study, we develop a low-cost particulate matter monitoring system based on special-purpose acquisition boards, deployed for monitoring air quality on both stationary and mobile sensor platforms. We explore the influence of all model variables, the quality of different calibration strategies, the accuracy across different concentration ranges, and the usefulness of redundant sensors placed in each station. The collected sensor data amounts to about 50GB of data, gathered in six months during the winter season. Tests of statically immovable stations include an analysis of accuracy and sensors’ reliability made by comparing our results with more accurate and expensive standard β radiation sensors. Tests on mobile stations have been designed to analyze the reactivity of our system to unexpected and abrupt events. These experiments embrace traffic analysis, pollution investigation using different means of transport and pollution analysis during peculiar events. With respect to other approaches, our methodology has been proved to be extremely easy to calibrate, to offer a very high sample rate (one sample per second), and to be based on an open-source software architecture. Database and software are available as open source in [1]

Public participation in the Geoweb era: Geosocial media use in local government

Advances in spatially enabled information and communication technologies (ICTs) have provided governments with the potential to enhance public participation and to collaborate with citizens. This dissertation critically assesses this potential and identifies the opportunities and challenges for local governments to embark on emerging geo-enabled practices. This dissertation first proposes a new typology for classifying geo-enabled practices related to public participation (termed here as geo-participation) and demonstrates the emerging opportunities presented by geo-participation to improve government-citizen collaboration and government operations. This dissertation then provides in-depth examinations of geosocial media as an exemplar geo-participation practice. The first empirical study assesses the potential of repurposing geosocial media data to gauge public opinions. The study suggests that geosocial media can help identify geographies of public perceptions concerning public facilities and services and have the potential to complement other methods of gauging public sentiment. The second empirical study assesses the usefulness of geosocial media for sharing non-emergency issues and identifies an important opportunity of enabling citizen collaboration for reporting and sharing non-emergency issues. Altogether, this dissertation makes several conceptual, empirical, and practical contributions to local government adoption of geo-participation. Conceptually, the proposed typology lays the foundation for researching and implementing geo-participation practices. Empirically, this dissertation tells a story of opportunities and challenges that sheds light on how local governments may adopt geosocial media to solicit citizen input and enable new forms of government-citizen interaction. Practically, this dissertation develops a tool for processing text-based citizen input and models of implementing geosocial media reporting that can help local government develop proper strategies of adopting geosocial media