Limiting global warming to close to 1.5°C by 2100 requires deep and rapidgreenhouse gas emission reductions and carbon dioxide removals (CDR) on amassive scale, presenting a remarkable scaling challenge. This paper focuses onthe financing of bioenergy with carbon capture and storage (BECCS) in Sweden.BECCS is one of the most prominent CDR methods in 1.5°C-compatible globalemission scenarios and has been assigned a specific role in Swedish policy fornet-zero. A Swedish state support system for BECCS based on results-basedpayments is planned. Furthermore, demand for CDR-based carbon credits is onthe rise on the voluntary carbon markets (VCM) for use towards voluntarymitigation targets. Risks involved with the current Swedish policies areanalysed, specifically for the co-financing of BECCS by the planned statesupport and revenues from the VCM.
We find that with the current policies,state support systems will subsidise carbon credit prices on the VCM. We arguethat such subsidisation can lower decarbonisation efforts by lowering the internalcarbon price set by actors, thus undermining environmental integrity. It isconcluded that proportional attribution should be applied, i.e., attributingmitigation outcomes to the state support and VCM revenue in proportion totheir financial contribution to the CDR achieved.
The attribution analysis shouldbe accompanied by adjustments in national greenhouse gas accounting so thatmitigation outcomes that are issued as carbon credits and used for offsetting arenot double claimed (i.e., not used by both a nation and a non-state actor on theVCM towards their respective mitigation targets). If proportional attribution andadjustments in national GHG accounting are not implemented, the credibility andenvironmental integrity of offsetting claims made by carbon credit users areeroded. We recommend that action is taken to operationalise and implementproportional attribution to allow for co-financing of BECCS projects whilemaintaining environmental integrity. Wider implications for ourrecommendations beyond the case of Swedish BECCS are also analysed.
Atmospheric nitrogen and sulfur deposition is an important effect of atmospheric pollution and may affect forest ecosystems positively, for example enhancing tree growth, or negatively, for example causing acidification, eutrophication, cation depletion in soil or nutritional imbalances in trees. To assess and design measures to reduce the negative impacts of deposition, a good estimate of the deposition amount is needed, either by direct measurement or by modeling.
In order to evaluate the precision of both approaches and to identify possible improvements, we compared the deposition estimates obtained using an Eulerian model with the measurements performed by two large independent networks covering most of Europe. The results are in good agreement (bias <25%) for sulfate and nitrate open field deposition, while larger differences are more evident for ammonium deposition, likely due to the greater influence of local ammonia sources. Modeled sulfur total deposition compares well with throughfall deposition measured in forest plots, while the estimate of nitrogen deposition is affected by the tree canopy. The geographical distribution of pollutant deposition and of outlier sites where model and measurements show larger differences are discussed.
Urban sources, wastewater treatment plants (WWTPs), untreated wastewater (not connected to WWTPs), and especially combined sewer overflow systems (CSS) including stormwater are major pathways for microplastics in the aquatic environment. We compile microplastics emission data for the Baltic Sea region, calculate emissions for each pathway and develop emission scenarios for selected polymer types, namely polyethylene (PE)/polypropylene (PP) and the polyester polyethylene terephthalate (PET). PE/PP and PET differ with respect to their density and can be regarded as representative for large groups of polymers. We consider particles between 20–500 μm with varying shapes. The emission scenarios serve as input for 3D-model simulations, which allow us to estimate transport, behavior, and deposition in the Baltic Sea environment.
According to our model results, the average residence time of PET and PE/PP in the Baltic Sea water body is about 14 days. Microplastics from urban sources cause average concentrations of 1.4 PE/PP (0.7 PET) particles/m2 sea surface (20–500 μm size range) in the Baltic Sea during summer. Average concentrations of PET, resulting from urban sources, at the sea floor are 4 particles/m2 sediment surface during summer. Our model approach suggests that accumulation at the shoreline is the major sink for microplastic with annual coastal PE/PP and PET accumulation rates of up to 108 particles/m each near emission hot-spots and in enclosed and semi-closed systems. All concentrations show strong spatial and temporal variability and are linked to high uncertainties.
The seasonality of CSS (including stormwater) emissions is assessed in detail. In the south-eastern Baltic, emissions during July and August can be up to 50% of the annual CSS and above 1/3 of the total annual microplastic emissions. The practical consequences especially for monitoring, which should focus on beaches, are discussed. Further, it seems that PET, PE/PP can serve as indicators to assess the state of pollution.
Using low-cost air quality sensors (LCS) in citizen science projects opens many possibilities.LCS can provide an opportunity for the citizens to collect and contributewith their own air qualitydata. However, low data quality is often an issue when using LCS and with it a risk of unrealisticexpectations of a higher degree of empowerment than what is possible. If the data quality andintended use of the data is not harmonized, conclusionsmay be drawn on the wrong basis anddata can be rendered unusable.
Ensuring high data quality is demanding in terms of labor andresources. The expertise, sensor performance assessment, post-processing, as well as thegeneral workload required will depend strongly on the purpose and intended use of the airquality data. It is therefore a balancing act to ensure that the data quality is high enough for thespecific purpose, while minimizing the validation effort. The aim of this perspective paper is toincrease awareness of data quality issues and provide strategies to minimizing labor intensityand expenses while maintaining adequate QA/QC for robust applications of LCS in citizenscience projects.
We believe that air quality measurements performed by citizens can be betterutilized with increased awareness about data quality and measurement requirements, incombination with improved metadata collection. Well-documented metadata can not onlyincrease the value and usefulness for the actors collecting the data, but it also the foundation forassessment of potential integration of the data collected by citizens in a broader perspective.