A Matter of Metals: Copper but Not Cadmium Affects the Microbial Alpha-Diversity of Soils and Sediments - a Meta-analysis.

Heavy metal (HM) accumulation in soil affects plants and soil fauna, yet the effect on microbial alpha-diversity remains unclear, mainly due to the absence of dedicated research synthesis (e.g. meta-analysis). Here, we report the first meta-analysis of the response of soil microbial alpha-diversity to the experimental addition of cadmium (Cd) and copper (Cu). We considered studies conducted between 2013 and 2022 using DNA metabarcoding of bacterial and fungal communities to overcome limitations of other cultivation- and electrophoresis-based techniques. Fungi were discarded due to the limited study number (i.e. 6 studies). Bacterial studies resulted in 66 independent experiments reported in 32 primary papers from four continents. We found a negative dose-dependent response for Cu but not for Cd for bacterial alpha-diversity in the environments, only for Cu additions exceeding 29.6 mg kg-1 (first loss of - 0.06% at 30 mg kg-1). The maximal loss of bacterial alpha-diversity registered was 13.89% at 3837 mg kg-1. Our results first highlight that bacterial communities behave differently to soil pollution depending on the metal. Secondly, our study suggests that even extreme doses of Cu do not cause a dramatic loss in alpha-diversity, highlighting how the behaviour of bacterial communities diverges from soil macro-organisms.

Next Generation Air Quality Platform: Openness and Interoperability for the Internet of Things.

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.

SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems.

Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor data of quality-controlled sensor networks along with co-located reference data sets. Sensor data are collected using the AirSensEUR sensor system, including sensors to monitor NO, NO2, O3, CO, PM2.5, PM10, PM1, CO2 and meteorological parameters. In total, 85 sensor systems were deployed throughout a year in three European cities (Antwerp, Oslo and Zagreb), resulting in a dataset comprising different meteorological and ambient conditions. The main data collection included two co-location campaigns in different seasons at an Air Quality Monitoring Station (AQMS) in each city and a deployment at various locations in each city (also including locations at other AQMSs). The dataset consists of data files with sensor and reference data, and metadata files with description of locations, deployment dates and description of sensors and reference instruments.