In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux.

Rivers are key pathways for transporting microplastics from land to the oceans, yet microplastic flux estimates remain uncertain. Remote sensing allows repeated broad-scale measurements and can be used to extrapolate limited in situ observations. This study investigated the relationship between suspended particulate matter (SPM), a satellite-observable water quality parameter, and microplastic concentration in a partially mixed estuary (Tamar, UK). Microplastic concentrations ranged from 0.04 to 0.99 microplastics/m3, decreasing downstream. A significant correlation was found between SPM and microplastic concentration over two seasons. This relationship was used to compute a multiyear timeseries of proxy microplastic concentration from satellite imagery and produce estimates of annual proxy microplastic flux. This approach could be applied to investigate microplastic flux in other major rivers worldwide where such a relationship between microplastics and SPM exists. To apply this workflow elsewhere, the establishment of local SPM-to-microplastic relationships from in situ observations and local validation of remote sensing SPM algorithms are essential.

Abundance and distribution of large microplastics (1-5 mm) within beach sediments at the Po River Delta, northeast Italy.

Coastal areas are especially prone to plastic debris, being subjected to various land- and sea-based sources. Nevertheless, knowledge about microplastic distribution on beaches is limited, as studies focused either on high tide lines, specific items, or relied on visual identification. Beaches exhibit several accumulation zones and microplastic deposition depends on particle properties. We thus studied microplastic distribution (1-5 mm), including various types and shapes, among three driftlines at three beaches within the Po River Delta. Particles were analyzed using ATR-FTIR spectroscopy. Abundances ranged from 2.92 (± 4.86 SD) to 23.30 (± 45.43 SD) microplastics per kilogram dry weight between the beaches. The accumulation of microplastics among driftlines showed no consistent pattern, besides expanded polystyrene tending to accumulate backshore. We observed that accumulation hotspots within a single driftline can disrupt a general observed accumulation pattern. Thus, microplastic monitoring guidelines should further include protocols for the handling of accumulation hotspots within datasets.

Coastal accumulation of microplastic particles emitted from the Po River, Northern Italy: Comparing remote sensing and hydrodynamic modelling with in situ sample collections.

Microplastic research has mainly concentrated on open seas, while riverine plumes remain largely unexplored despite their hypothesized importance as a microplastic source to coastal waters. This work aimed to model coastal accumulation of microplastic particles (1-5 mm) emitted by the Po River over 1.5 years. We posit that river-induced microplastic accumulation on adjacent coasts can be predicted using (1) hydrodynamic-based and (2) remote sensing-based modelling. Model accumulation maps were validated against sampling at nine beaches, with sediment microplastic concentrations up to 78 particles/kg (dry weight). Hydrodynamic modelling revealed that discharged particle amount is only semi-coupled to beaching rates, which are strongly mouth dependent and occur within the first ten days. Remote sensing modelling was found to better capture river mouth relative strength, and accumulation patterns were found consistent with hydrodynamic modelling. This methodology lays groundwork for developing an operational monitoring system to assess microplastic pollution emitted by a major river.

Spatial evaluation of Indonesia's 2015 fire-affected area and estimated carbon emissions using Sentinel-1.

Fires raged once again across Indonesia in the latter half of 2015, creating a state of emergency due to poisonous smoke and haze across Southeast Asia as well as incurring great financial costs to the government. A strong El Niño-Southern Oscillation (ENSO) led to drought in many parts of Indonesia, resulting in elevated fire occurrence comparable with the previous catastrophic event in 1997/1998. Synthetic Aperture Radar (SAR) data promise to provide improved detection of land use and land cover changes in the tropics as compared to methodologies dependent upon cloud- and haze-free images. This study presents the first spatially explicit estimates of burned area across Sumatra, Kalimantan, and West Papua based on high-resolution Sentinel-1A SAR imagery. Here, we show that 4,604,569 hectares (ha) were burned during the 2015 fire season (overall accuracy 84%), and compare this with other existing operational burned area products (MCD64, GFED4.0, GFED4.1s). Intersection of burned area with fine-scale land cover and peat layer maps indicates that 0.89 gigatons carbon dioxide equivalents (Gt CO2 e) were released through the fire event. This result is compared to other estimates based on nonspatially explicit thermal anomaly measurements or atmospheric monitoring. Using freely available SAR C-band data from the Sentinel mission, we argue that the presented methodology is able to quickly and precisely detect burned areas, supporting improvement in fire control management as well as enhancing accuracy of emissions estimation.

Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird).

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.