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The Lagrangian particle dispersion model FLEXPART version 10.4
The Lagrangian particle dispersion model FLEXPART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as those released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to global. In particular, inverse modeling based on source–receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, the temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing for more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing FLEXPART output data, and we briefly report on alternative FLEXPART versions.
2019
Trends in measured NO2 and PM. Discounting the effect of meteorology.
This report documents a study on long-term trends in observed atmospheric levels of NO2, PM10 and PM2.5 based on data from the European Environmental Agency (EEA) Airbase v8 (EEA, 2018). The main aim is to evaluate to what extent the observed time series could be simulated as a function of various local meteorological data plus a time-trend by a Generalized Additive Model (GAM). The GAM could be regarded an advanced multiple regression model. If successful, such a model could be used for several purposes; to estimate the long-term trends in NO2 and PM when the effect of the inter-annual variations in meteorology is removed, and secondly, to “explain” the concentration levels in one specific year in terms of meteorological anomalies and long-term trends. The GAM method was based on a methodology developed during a similar project in 2017 looking at the links between surface ozone and meteorology.
The input to the study consisted of gridded model meteorological data provided through the EURODELTA Trends project (Colette et al., 2017) for the 1990-2010 period as well as measured data on NO2, PM10 and PM2.5 extracted from Airbase v8. The measurement data was given for urban, suburban and rural stations, respectively. The analysis was split into two time periods, 1990-2000 and 2000-2010 since the number of stations differ substantially for these periods and since there is reason to believe that the trends differ considerably between these two periods.
The study was focused on the 4-months winter period (Nov-Feb) since it was important to assure a period of the year with consistent and homogeneous relationships between the input explanatory data (local meteorology) and the levels of NO2 and PM. For NO2, this period will likely cover the season with the highest concentration levels whereas for PM high levels could be expected outside this period due to processes such as secondary formation, transport of Saharan dust and sea spray.
When measured by the R2 statistic, the GAM method performed best for NO2 in Belgium, the Netherlands, NW Germany and the UK. Significantly poorer performance was found for Austria and areas in the south. For PM10 there were less clear geographical patterns in the GAM performance.
Based on a comparison between the meteorologically adjusted trends and plain linear regression, our results indicate that for the 1990-2000 period meteorology caused an increase in NO2 concentrations that counteracted the effect of reduced emissions. For the period 2000-2010 we find that meteorology lead to reduced NO2 levels in the northwest and a slight increase in the south.
The amount of observational data is much less for PM than for NO2. For the 1990-2000 period the number of sites with sufficient length of time series is too small to apply the GAM method on a European scale. For the 2000-2010 period, we find that the general performance of the GAM method is poorer for PM10 than for NO2. With respect to the link between PM10 and temperature, the results indicate a marked geographical pattern with a negative relationship in central Europe and a positive relationship in Spain, southern France and northern Italy.
For PM10 during 2000-2010, the vast majority of the estimated trends are found to be negative. The difference between the GAM trend and the plain linear regression, indicates that meteorology lead to increased PM10 levels in the southern and central parts and decreased levels in the north.
For PM2.5 it turned out that the amount of data in the entire period 1990-2010 was too small to use the GAM method in a meaningful way on a European scale. Only a few sites had sufficient time series and thus more recent data are required.
ETC/ACM
2019
Land cover and traffic data inclusion in PM mapping
Annual European-wide air quality maps have been produced using geostatistical techniques for many years and is based primarily on air quality measurements. The mapping method follows in principle the sequence of regression – interpolation – merging. It combines monitoring data, chemical transport model outputs and other supplementary data (such as altitude and meteorology) using a linear regression model followed by kriging of its residuals (‘residual kriging’), applied separately for rural and urban background areas. The rural and urban background map layers are
subsequently merged on basis of population densities into one final concentration map for Europe.
Inclusion of land cover and road type data among the set of the supplementary data demonstrated to improve the quality of urban and rural background layers in the NO2 map and is currently routinely applied in the NO2 mapping. In addition, an urban traffic map layer based on the measurement data from traffic stations is constructed and takes art in the merging process with the rural and urban background map layers to reach a final NO2 map.
This report examines now – due to its proved added value in the NO2 mapping – whether for PM10 and PM2.5 the similar method provides also sufficient added value to include it on a routinely basis in the production of the final concentration map and population exposure estimates.. It concerns the inclusion of land cover data and road type data in the background map layers, as well as the inclusion of the urban traffic layer based on traffic measurement stations. The analysis is done based on 2015 data, being the most recent year with all data needed available when this study started.
ETC/ACM
2019
Low cost sensor systems for air quality assessment. Possibilities and challenges.
Air quality is enjoying popular interest in the last years, with numerous projects initiated by civil society or individuals that aim to assess the quality of air locally, aided by new, low-cost monitoring technologies that can be used by “everyone”. Such initiatives are very welcome, but in this highly technical and (in the western world) thoroughly regulated area, the professional community seems to struggle with communication with these initiatives, trying to reconcile the often highly technical aspects with the social ones. The technical issues include subjects such as monitoring techniques, air quality assessment methods, or quality control of measurements, and disciplines such as metrology, atmospheric science or informatics.
In this report, we would like to provide the reader with a practically oriented overview indicating the position of these new technologies in the ecosystem of air quality monitoring and measurement activities. Sensing techniques are rapidly evolving. This ‘ever’ improving capability implies among other, that there is currently no traceable method of evaluation of data quality. Despite the efforts of numerous groups, including within the European standardization system, a certification system will take some time to develop. This has important implications for example, when comparing measurements taken in time, by different devices (or different versions of the same sensor system device). Fitness for purpose – why are we measuring or monitoring and how do we intend to use the information we obtain – should always be the main criterion for the technological choice.
The report starts with an overview of elements of a monitoring system and proceed to describe the new technologies. Then, we give examples of how low-cost sensor technologies are being used by citizens. These examples are followed by reflections upon providing actionable information. Having learned from practical applications of sensor systems, we also discuss how the data from citizen activities can be used to develop new information, and provide some reflections on developing sensor systems monitoring on a larger scale.
We feel that the new technologies, while a disruptive change, provide many exciting opportunities, and we hope that this report will contribute to promote their use alongside with other assessment methods. We believe that increased understanding of technical issues we discuss will ultimately lead to better communication on air quality, and in its consequence, will enable further improvements in this domain.
ETC/ACM
2019
Diurnal cycle of iodine, bromine, and mercury concentrations in Svalbard surface snow
Sunlit snow is highly photochemically active and plays a key role in the exchange of gas phase species between the cryosphere and the atmosphere. Here, we investigate the behaviour of two selected species in surface snow: mercury (Hg) and iodine (I). Hg can deposit year-round and accumulate in the snowpack. However, photo-induced re-emission of gas phase Hg from the surface has been widely reported. Iodine is active in atmospheric new particle formation, especially in the marine boundary layer, and in the destruction of atmospheric ozone. It can also undergo photochemical re-emission. Although previous studies indicate possible post-depositional processes, little is known about the diurnal behaviour of these two species and their interaction in surface snow. The mechanisms are still poorly constrained, and no field experiments have been performed in different seasons to investigate the magnitude of re-emission processes Three sampling campaigns conducted at an hourly resolution for 3 d each were carried out near Ny-Ålesund (Svalbard) to study the behaviour of mercury and iodine in surface snow under different sunlight and environmental conditions (24 h darkness, 24 h sunlight and day–night cycles). Our results indicate a different behaviour of mercury and iodine in surface snow during the different campaigns. The day–night experiments demonstrate the existence of a diurnal cycle in surface snow for Hg and iodine, indicating that these species are indeed influenced by the daily solar radiation cycle. Differently, bromine did not show any diurnal cycle. The diurnal cycle also disappeared for Hg and iodine during the 24 h sunlight period and during 24 h darkness experiments supporting the idea of the occurrence (absence) of a continuous recycling or exchange at the snow–air interface. These results demonstrate that this surface snow recycling is seasonally dependent, through sunlight. They also highlight the non-negligible role that snowpack emissions have on ambient air concentrations and potentially on iodine-induced atmospheric nucleation processes.
2019
Frequency of extreme precipitation increases extensively with event rareness under global warming
The intensity of the heaviest extreme precipitation events is known to increase with global warming. How often such events occur in a warmer world is however less well established, and the combined effect of changes in frequency and intensity on the total amount of rain falling as extreme precipitation is much less explored, in spite of potentially large societal impacts. Here, we employ observations and climate model simulations to document strong increases in the frequencies of extreme precipitation events occurring on decadal timescales. Based on observations we find that the total precipitation from these intense events almost doubles per degree of warming, mainly due to changes in frequency, while the intensity changes are relatively weak, in accordance to previous studies. This shift towards stronger total precipitation from extreme events is seen in observations and climate models, and increases with the strength – and hence the rareness – of the event. Based on these results, we project that if historical trends continue, the most intense precipitation events observed today are likely to almost double in occurrence for each degree of further global warming. Changes to extreme precipitation of this magnitude are dramatically stronger than the more widely communicated changes to global mean precipitation.
Nature Portfolio
2019
2019
Screening new PFAS compounds 2018
This screening project has focused on the occurrence of conventional and emerging PFASs in terrestrial and marine environments, including the Arctic. Conventional PFASs were found to be wide-spread in the environment and for the first time in Norway reported in wolf, a top predator from the terrestrial environment. Otters living in close proximity to human settlements and preying on the marine food chain, are heavily contaminated with PFASs. Areas where ski-testing activities are common are a potential “hotspot” where PFASs can enter the food chain. The difference in PFAS-profile between the samples indicates that the diversity in samples are necessary to reveal the complete picture of PFASs in the environment.
NILU
2019