Cyanobacterial Biomonitoring in Lake Avernus During the COVID-19 Pandemic: Integrating Remote Sensing and Field Data for Pollution Source Detection

In the context of environmental monitoring studies, the complex dynamics of environmental systems, constrained by the distribution, intensity and interaction of multiple sources, limits the ability to detect pollution phenomena and to identify their sources. The deployment of multidisciplinary, multilevel and multi-factorial strategies supports the identification of the links between the pollutants’ sources and targets. Our new biomonitoring strategy, based on the integration of remote (satellite) and proximal (drone) sensing monitoring data with field data (bio/chemical analyses) and focused on the use of cyanobacteria as bioindicators of pollution, was implemented and was validated through its application on a test-bed area, i.e., Lake Avernus (Campania Region, Southern Italy). A long-term analysis of multispectral remote sensing observations centred on the Lake Avernus area highlighted the periodicity and seasonality of cyanobacterial bloom events over the time interval 2019-2021. However, a sudden change of characteristics, observable through remotely sensed data, was evidenced during the first and major lockdown related to the COVID-19 pandemics, in year 2020. This sudden change depended on the drastic modification of human habits and a reduction in pollutant emissions, as widely reported by the scientific literature. During the same lockdown period, the opportunity to collect samples in the field allowed to identify an unusual progression of Microcystis' bloom, whose dynamics is triggered by the existing anthropogenic sources and the evolution of environmental parameters, that can stimulate the blooming events. This work shows and demonstrates how pollution attribution can be achieved using remote sensing of cyanobacteria, which are excellent bioindicators due to their sensitivity to multiple stressors and rapid response to habitat changes throughout the event.