A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.

The widespread diffusion of sensors, mobile devices, social media and open data are reconfiguring the way data underpinning policy and science are being produced and consumed. This in turn is creating both opportunities and challenges for policy-making and science. There can be major benefits from the deployment of the IoT in smart cities and environmental monitoring, but to realize such benefits, and reduce potential risks, there is an urgent need to address current limitations, including the interoperability of sensors, data quality, security of access and new methods for spatio-temporal analysis. Within this context, the manuscript provides an overview of the AirSensEUR project, which establishes an affordable open software/hardware multi-sensor platform, which is nonetheless able to monitor air pollution at low concentration levels. AirSensEUR is described from the perspective of interoperable data management with emphasis on possible use case scenarios, where reliable and timely air quality data would be essential.

The availability of timely, accessible and well documented data plays a central role in the process of digital transformation in our societies and businesses. Considering this, the European Commission has established an ambitious agenda that aims to leverage on the favourable technological and political context and build a society that is empowered by data-driven innovation. Within this context, geospatial data remains critically important for many businesses and public services. The process of establishing Spatial Data Infrastructures (SDIs) in response to the legal provisions of the European Union INSPIRE Directive has a long history. While INSPIRE focuses mainly on ’unlocking’ data from the public sector, there is need to address emerging technological trends, and consider the role of other actors such as the private sector and citizen science initiatives. The objective of this paper, given those bounding conditions is twofold. Firstly, we position SDI-related developments in Europe within the broader context of the current political and technological scenery. In doing so, we pay particular attention to relevant technological developments and emerging trends that we see as enablers for the evolution of European SDIs. Secondly, we propose a high level concept of a pan-European (geo)data space with a 10-year horizon in mind. We do this by considering today’s technology while trying to adopt an evolutionary approach with developments that are incremental to contemporary SDIs.

Much research on human mobility patterns and accessibility to date has been conducted largely in Western European and North American countries, where the private vehicle is the main means for commuting. As a result, most studies focused largely on car‐based mobility (automobility) and accessibility, and relatively little is known about countries in other regions of the world. Based on an activity‐travel dataset collected in Sofia, Bulgaria and using 3D geovisualisation, this study attempts to fill this gap through examining gender differences in commute time and potential access to urban opportunities. The results reveal important gender differences in commute time and individual accessibility. Among the surveyed participants, women tend to spend more time on their commute trips and have more restrictive spatial reach to urban opportunities compared with men, largely as a result of their reliance on public transit as their primary mode of transport. Further, women have lower accessibility compared with men who used the same travel mode. This case study adds important new knowledge about a geographical area that has been under‐studied by Anglophone geographers. It also shows that GIS‐based geovisualisation and analysis are powerful tools for uncovering gender differences in the geographical distribution of commute time, which conventional quantitative methods cannot reveal.

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