A Random Forest Approach to Estimate Daily Particulate Matter, Nitrogen Dioxide, and Ozone at Fine Spatial Resolution in Sweden

Stafoggia, M.; Johansson, C.; Glantz, P.; Renzi, M.; Shtein, A.; de Hoogh, K.; Kloog, I.; Davoli, M.; Michelozzi, P.; Bellander, T.
2020 | ATMOSPHERE | 11 (239) (1-19)

Air pollution is one of the leading causes of mortality worldwide. An accurate assessment
of its spatial and temporal distribution is mandatory to conduct epidemiological studies able to
estimate long-term (e.g., annual) and short-term (e.g., daily) health effects. While spatiotemporal
models for particulate matter (PM) have been developed in several countries, estimates of daily
nitrogen dioxide (NO2) and ozone (O3) concentrations at high spatial resolution are lacking, and no
such models have been developed in Sweden. We collected data on daily air pollutant
concentrations from routine monitoring networks over the period 2005–2016 and matched them
with satellite data, dispersion models, meteorological parameters, and land-use variables. We
developed a machine-learning approach, the random forest (RF), to estimate daily concentrations
of PM10 (PM<10 microns), PM2.5 (PM<2.5 microns), PM2.5–10 (PM between 2.5 and 10 microns), NO2,
and O3 for each squared kilometer of Sweden over the period 2005–2016. Our models were able to
describe between 64% (PM10) and 78% (O3) of air pollutant variability in held-out observations, and
between 37% (NO2) and 61% (O3) in held-out monitors, with no major differences across years and
seasons and better performance in larger cities such as Stockholm. These estimates will allow to
investigate air pollution effects across the whole of Sweden, including suburban and rural areas,
previously neglected by epidemiological investigations.

A simple field-based biodegradation test shows pH to be an inadequately controlled parameter in laboratory biodegradation testing

Goss, M.; Li, Z.; McLachlan, M.S.
2020 | Environ. Sci.: Processes Impacts | 22 (1006-1013)

Complex mixtures of chlorinated paraffins found in handwipes from a Norwegian cohort.

Yuan, B.; Tay, J.H.; Papadopoulou, E.; Haug, L.S.; Padilla-Sánchez, J.A.; de Wit, C.A.
2020 | Environ. Sci. Technol. Lett. | 7 (198-205)

Chlorinated paraffins in snakes from paddy fields in Yangtze River Delta: Occurrence, tissue distribution and biomagnification.

Du, X.; Yuan, B.; Zhou, Y.; de Wit, C.A.; Zheng, Z.; Yin, G.
2020 | Environ. Sci. Technol. | 54 (2753-2762)

DNA epigenetic marks are linked to embryo aberrations in amphipods

Gorokhova, E; Martella, G; Motwani, HN; Tretyakova, N; Sundelin, B; Motwani, HV
2020 | Sci Rep | 10:665

Serum albumin adducts, DNA adducts and micronuclei frequency measured in benzo[a]pyrene-exposed mice for estimation of genotoxic potency

Motwani, HV; Westberg, E, Lindh, C; Abramsson-Zetterberg, L; Törnqvist, M.
2020 | Mutat. Res. | 849

Radiometric Survey of the Tyaa River Sand Mine In Kitui, Kenya.

S. M. Matsitsi; J. M. Linturi; J. M. Kebwaro; Leonard Kirago
2020 | Radiat Prot Dosimetry | 188 (4) (405-412)

Severe thiamine deficiency in eastern Baltic cod (Gadus morhua)

Engelhardt J; Frisell O; Gustavsson H; Hansson T; Sjöberg R; Collier TK; Balk L
2020 | PLoS ONE

Evaluation of the OECD POV and LRTP screening tool for estimating the long-range transport of organophosphate esters

Sühring R, Scheringer M, Jantunen L, Diamond ML
2020 | Environ. Sci.-Process Impacts

Formation and mobilization of methylmercury across natural and experimental sulfur deposition gradients

Akerblom, S; Nilsson, MB; Skyllberg, U; Bjorn, E; Jonsson, S; Ranneby, B; Bishop, K
2020 | Environ. Pollut. | 263
accumulation , acid rain , boreal peatland , dissolved organic matter , global change , mercury , methyl mercury , methylation , nitrogen , peatland , sediments , sulfur , water , yellow perch
We investigated the influence of sulfate (SO42-) deposition and concentrations on the net formation and solubility of methylmercury (MeHg) in peat soils. We used data from a natural sulfate deposition gradient running 300 km across southern Sweden to test the hypothesis posed by results from an experimental field study in northern Sweden: that increased loading of SO42- both increases net MeHg formation and redistributes methylmercury (MeHg) from the peat soil to its porewater. Sulfur concentrations in peat soils correlated positively with MeHg concentrations in peat porewater, along the deposition gradient similar to the response to added SO42- in the experimental field study. The combined results from the experimental field study and deposition gradient accentuate the multiple, distinct and interacting roles of SO42- deposition in the formation and redistribution of MeHg in the environment. (c) 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Screening of halogenated phenolic compounds in plasma and serum from marine wildlife

Lindqvist, D
2020 | Int. J. Environ. Sci. Technol. | 17 (4) (2177-2184)
analysis , bde-47 , bioaccumulation , biotransformation , blood , fate , food , hydroxylated polychlorinated-biphenyls , mass spectral library , pbdes , phenols , polybrominated diphenyl ethers , retention index
The growing knowledge of the impact of halogenated phenolic compounds on hormonal and metabolic systems has led to an increased interest in the exposure and potential effects of these compounds in wildlife. In the present study, a screening procedure was developed to detect and quantify halogenated phenolic compounds in serum and plasma from marine wildlife. A mass spectral library containing selective ion monitoring data was created using gas chromatography electron capture negative ionization mass spectrometry. The selective ion monitoring data in the library were accompanied with retention indices to increase the specificity of each entry in the library. The library together with the developed extraction procedure and optimized instrumental settings can be used for the detection of 52 different halogenated phenolic compounds of environmental concern, including 23 hydroxylated polychlorinated biphenyls and 24 hydroxylated polybrominated diphenyl ethers. The instrument limit of detection for the compounds included in the library ranged from 30 to 320 fg/injection, with a median detection limit of 90 fg/injection. The average recovery of 11 different halogenated phenolic compounds, from four species of marine wildlife, was 66 +/- 14%. A full-scan mass spectral library was also created containing an additional seven compounds. Gray seals, long-tailed ducks, and two species of fish from the Baltic Sea were screened for halogenated phenolic compounds using the developed procedure. A total of 33 compounds included in the library were detected and quantified.

Deconvolution of FIGAERO-CIMS thermal desorption profiles using positive matrix factorisation to identify chemical and physical processes during particle evaporation

Buchholz, A; Ylisirnio, A; Huang, W; Mohr, C; Canagaratna, M; Worsnop, D; Schobesberger, S; Virtanen, A
2020 | Atmos. Chem. Phys. | 20 (13) (7693-7716)
absorption-model , alpha-pinene ozonolysis , components , gas , insights , mass-spectrometer , oxidation , secondary organic aerosol , semivolatile , volatility
The measurements of aerosol particles with a filter inlet for gases and aerosols (FIGAERO) together with a chemical ionisation mass spectrometer (CIMS) yield the overall chemical composition of the particle phase. In addition, the thermal desorption profiles obtained for each detected ion composition contain information about the volatility of the detected compounds, which is an important property for understanding many physical properties like gas-particle partitioning. We coupled this thermal desorption method with isothermal evaporation prior to the sample collection to investigate the chemical composition changes during isothermal particle evaporation and particulate-water-driven chemical reactions in alpha-pinene secondary organic aerosol (SOA) of three different oxidative states. The thermal desorption profiles of all detected elemental compositions were then analysed with positive matrix factorisation (PMF) to identify the drivers of the chemical composition changes observed during isothermal evaporation. The keys to this analysis were to use the error matrix as a tool to weight the parts of the data carrying most information (i.e. the peak area of each thermogram) and to run PMF on a combined data set of multiple thermograms from different experiments to enable a direct comparison of the individual factors between separate measurements. The PMF was able to identify instrument background factors and separate them from the part of the data containing particle desorption information. Additionally, PMF allowed us to separate the direct desorption of compounds detected at a specific elemental composition from other signals with the same composition that stem from the thermal decomposition of thermally instable compounds with lower volatility. For each SOA type, 7-9 factors were needed to explain the observed thermogram behaviour. The contribution of the factors depended on the prior isothermal evaporation. Decreased contributions from the factors with the lowest desorption temperatures were observed with increasing isothermal evaporation time. Thus, the factors identified by PMF could be interpreted as volatility classes. The composition changes in the particles due to isothermal evaporation could be attributed to the removal of volatile factors with very little change in the desorption profiles of the individual factors (i.e. in the respective temperatures of peak desorption, T-max). When aqueous-phase reactions took place, PMF was able to identify a new factor that directly identified the ions affected by the chemical processes. We conducted a PMF analysis of the FIGAERO-CIMS thermal desorption data for the first time using laboratory-generated SOA particles. But this method can be applied to, for example, ambient FIGAERO-CIMS measurements as well. There, the PMF analysis of the thermal desorption data identifies organic aerosol (OA) sources (such as biomass burning or oxidation of different precursors) and types, e.g. hydrocarbon-like (HOA) or oxygenated organic aerosol (OOA). This information could also be obtained with the traditional approach, namely the PMF analysis of the mass spectra data integrated for each thermogram. But only our method can also obtain the volatility information for each OA source and type. Additionally, we can identify the contribution of thermal decomposition to the overall signal.

Contact information

Visiting addresses:

Geovetenskapens Hus,
Svante Arrhenius väg 8, Stockholm

Arrheniuslaboratoriet, Svante Arrhenius väg 16, Stockholm (Unit for Toxicological Chemistry)

Mailing address:
Department of Environmental Science
Stockholm University
106 91 Stockholm

Press enquiries should be directed to:

Stella Papadopoulou
Science Communicator
Phone +46 (0)8 674 70 11
stella.papadopoulou@aces.su.se