To explore high-resolution temporal variation characteristics of atmospheric metal elements concentration and more accurate pollution sources apportionment, online monitoring of metal elements in PM₂.₅ with 1-h time resolution was conducted in Beijing from August 22, 2018 to August 21, 2019. Concentration of 18 elements varied between detection limit (ranging from 0.1 to 100 ng/m³) and nearly 25 μg/m³. Si, Fe, Ca, K and Al represented major elements and accounted for 93.47% of total concentration during the study period. Compared with previous studies, airborne metal pollution in Beijing has improved significantly which thanks to strict comprehensive control measures under the Clean Air Action Plan since 2013. Almost all elements present higher concentrations on weekdays than weekends, while concentrations of elements associated with dust sources during holidays are higher than those in working days after the morning peak, and there is almost no concentration difference in the evening peak period. Soil and dust, vehicle non-exhaust emissions, biomass, industrial processes and fuel combustion were apportioned as main sources of atmospheric metal pollution, accounting for 63.6%, 18.4%, 16.8%, 1.0% and 0.18%, respectively. Furthermore, main occurrence season of metal pollution is judged by characteristic radar chart of varied metal elements proposed for the first time in this study, for example, fuel combustion type pollution mainly occurs in winter and spring. Results of 72-h backward trajectory analysis of air masses showed that, except for local emissions, atmospheric metal pollution in Beijing is also affected by regional transport from Inner Mongolia, Hebei, the Bohai Sea and Heilongjiang.

In China, rural chemical SMEs are often believed to still largely operate below the sustainability radar. This paper investigates to what extent and how chemical SMEs are already experiencing pressure to improve their environmental performance, using an in-depth case study in Jasmine County, Hebei province. The results show that local residents had rather low trust in the environmental improvement promises made by the enterprises and the local government, and disagreed with the proposed improvement plans. Although the power of local residents to influence decision making remained limited, the chemical SMEs started to feel increasing pressures to clean up their business, from governments, local communities and civil society, and international value chain stakeholders. Notwithstanding these mounting pressures chemical SME's environmental behavior and performance has not changed radically for the better. The strong economic ties between local county governments and chemical SMEs continue to be a major barrier for stringent environmental regulation.

This paper presents a novel operational oil spill modelling system based on HF radar currents, implemented in a northwest European shelf sea. The system integrates Open Modal Analysis (OMA), Short Term Prediction algorithms (STPS) and an oil spill model to simulate oil spill trajectories. A set of 18 buoys was used to assess the accuracy of the system for trajectory forecast and to evaluate the benefits of HF radar data compared to the use of currents from a hydrodynamic model (HDM). The results showed that simulated trajectories using OMA currents were more accurate than those obtained using a HDM. After 48h the mean error was reduced by 40%. The forecast skill of the STPS method was valid up to 6h ahead. The analysis performed shows the benefits of HF radar data for operational oil spill modelling, which could be easily implemented in other regions with HF radar coverage.

Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3–8K above ambient, this is detectable by infrared (IR) cameras.Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing.

At-sea detection of marine debris presents a difficult problem, as the debris items are often relatively small and partially submerged. However, they may accumulate in water parcel boundaries or eddy lines. The application of models, satellite radar and multispectral data, and airborne remote sensing (particularly radar) to focus the search on eddies and convergence zones in the open ocean appear to be a productive avenue of investigation. A multistage modeling and remote sensing approach is proposed for the identification of areas of the open ocean where debris items are more likely to congregate. A path forward may best be achieved through the refinement of the Ghost Net procedures with the addition of a final search stage using airborne radar from an UAS simulator aircraft to detect zones of potential accumulation for direct search. Sampling strategies, direct versus indirect measurements, remote sensing resolution, sensor/platform considerations, and future state are addressed.

Due to the effects of heightened warming in the Arctic, there has been an urgency to develop methods for detecting oil in (or under) sea ice, owing to increasing potential for oil exploration and ship traffic in the more accessible Arctic regions. To test the potential for radar utilizing the normalized radar cross section (NRCS) of the sea ice, an oil-in-ice mesocosm experiment was performed. Throughout the experiment, corn oil was used as a surrogate for medium crude oil, to assess oil movement tendencies in sea ice, and the resultant impact on the complex permittivity through measurement and modelling techniques. We performed a modelling study to establish the effects of corn oil on the NRCS of sea ice. The oil presence in the sea ice increased the temperature and reduced the salinity of the sea ice, thereby lowering its complex permittivity and modeled NRCS when compared to control sea ice.

Loud sound emitted during offshore industrial activities can impact marine mammals. Regulations typically prescribe marine mammal monitoring before and/or during these activities to implement mitigation measures that minimise potential acoustic impacts. Using seismic surveys under low visibility conditions as a case study, we review which monitoring methods are suitable and compare their relative strengths and weaknesses. Passive acoustic monitoring has been implemented as either a complementary or alternative method to visual monitoring in low visibility conditions. Other methods such as RADAR, active sonar and thermal infrared have also been tested, but are rarely recommended by regulatory bodies. The efficiency of the monitoring method(s) will depend on the animal behaviour and environmental conditions, however, using a combination of complementary systems generally improves the overall detection performance. We recommend that the performance of monitoring systems, over a range of conditions, is explored in a modelling framework for a variety of species.

Fishing gears are marked to establish and inform origin, ownership and position. More recently, fishing gears are marked to aid in capacity control, reduce marine litter due to abandoned, lost or otherwise discarded fishing gear (ALDFG) and assist in its recovery, and to combat illegal, unreported and unregulated (IUU) fishing. Traditionally, physical marking, inscription, writing, color, shape, and tags have been used for ownership and capacity purposes. Buoys, lights, flags, and radar reflectors are used for marking of position. More recently, electronic devices have been installed on marker buoys to enable easier relocation of the gear by owner vessels. This paper reviews gear marking technologies with focus on coded wire tags, radio frequency identification tags, Automatic Identification Systems, advanced electronic buoys for pelagic longlines and fish aggregating devices, and re-location technology if the gear becomes lost.

Intensive anthropogenic activities have a serious negative effect on the Jiangsu coastal area of China, especially on the distinctive intertidal zone. Humans are trying to eliminate this effect by taking protection and eco-compensation measures. However, when trying to determine the ecological status and quantify the anthropogenic impact for this area, the complex relationship between ecosystems and environmental stress leads to difficulties in reflecting general environmental quality. This study assessed the benthic ecological status of 10 transects (three stations/transect) across six different typologies over six years (2007, 2009–2013) in the Jiangsu intertidal zone. A unitary assessment of each transect was conducted using the multivariate AZTI Marine Biotic Index (M-AMBI), along with a radar chart (and its parameters). In the Jiangsu intertidal zone, the ecological status was noted as good or moderate at most sampling stations. Among the six assessed years, 2010 had the highest ecological status, while 2007 had the lowest. As for transects, transect 1 had the highest ratings, and transect 3 had the lowest ratings. Various stresses and advantageous human intervention and contributed to the ecological status for the different areas. The M-AMBI could be used in the future as a suitable index to assess the benthic ecological status of the Jiangsu intertidal zone. In addition, the new unitary method validated in this study could be used to assess ecosystems with several small biotopes, while accurately reflecting environmental quality.

The dominant source of coastal pollution adversely affecting the regional coastal water quality is the seasonally variable urban runoff discharged via southern California’s rivers. Here, we use a surface transport model of coastal circulation driven by current maps from high frequency radar to compute two-year hindcasts to assess the temporal and spatial statistics of 20 southern California stormwater discharges. These models provide a quantitative, statistical measure of the spatial extent of the discharge plumes in the coastal receiving waters, defined here as a discharge’s “exposure”. We use these exposure maps from this synthesis effort to (1) assess the probability of stormwater connectivity to nearby Marine Protected Areas, and (2) develop a methodology to estimate the mass transport of stormwater discharges. The results of the spatial and temporal analysis are found to be relevant to the hindcast assessment of coastal discharges and for use in forecasting transport of southern California discharges.