Estimating ionospheric currents by inversion from ground-based geomagnetic data and calculating geoelectric fields for studies of geomagnetically induced currents

This research focuses on the inversion of geomagnetic variation field measurements to obtain the source currents in the ionosphere and magnetosphere, and to determine the geoelectric fields at the Earth’s surface. During geomagnetic storms, the geoelectric fields create geomagnetically induced currents (GIC) in power networks. These GIC may disturb the operation of power systems, cause damage to power transformers, and even result in power blackouts. In this model, line currents running east–west along given latitudes are postulated to exist at a certain height above the Earth’s surface. This physical arrangement results in the fields on the ground being composed of a zero magnetic east component and a nonzero electric east component. The line current parameters are estimated by inverting Fourier integrals (over wavenumber) of elementary geomagnetic fields using the Levenberg–Marquardt technique. The output parameters of the model are the ionospheric current strength and the geoelectric east component at the Earth’s surface. A conductivity profile of the Earth is adapted from a shallow layered-Earth model for one observatory, together with a deep-layer model derived from satellite observations. This profile is used to obtain the ground surface impedance and therefore the reflection coefficient in the integrals. The inputs for the model are a spectrum of the geomagnetic data for 31 May 2013. The output parameters of the model are spectrums of the ionospheric current strength and of the surface geoelectric field. The inverse Fourier transforms of these spectra provide the time variations on the same day. The geoelectric field data can be used as a proxy for GIC in the prediction of GIC for power utilities. The current strength data can assist in the interpretation of upstream solar wind behaviour

Seasonal and Diurnal Variation of Geomagnetic Activity: Revised \u3cem\u3eDst\u3c/em\u3e Versus External Drivers

Daily and seasonal variability of long time series of magnetometer data from Dst stations is examined. Each station separately shows a local minimum of horizontal magnetic component near 18 local time (LT) and weakest activity near 06 LT. The stations were found to have different baselines such that the average levels of activity differed by about 10 nT. This effect was corrected for by introducing a new “base method” for the elimination of the secular variation. This changed the seasonal variability of the Dst index by about 3 nT. The hemispheric differences between the annual variation (larger activity during local winter and autumn solstice) were demonstrated and eliminated from the Dst index by addition of two Southern Hemisphere stations to a new index termed Dst6. Three external drivers of geomagnetic activity were considered: the heliographic latitude, the equinoctial effect, and the Russell–McPherron effect. Using the newly created Dst6 index, it is demonstrated that these three effects account for only about 50% of the daily and seasonal variability of the index. It is not clear what drives the other 50% of the daily and seasonal variability, but it is suggested that the station distribution may play a role

Quantifying extreme behaviour in geomagnetic activity

Understanding the extremes in geomagnetic activity is an important component in understanding just how severe conditions can become in the terrestrial space environment. Extreme activity also has consequences for technological systems. On the ground, extreme geomagnetic behavior has an impact on navigation and position accuracy and the operation of power grids and pipeline networks. We therefore use a number of decades of one-minute mean magnetic data from magnetic observatories in Europe, together with the technique of extreme value statistics, to provide a preliminary exploration of the extremes in magnetic field variations and their one-minute rates of change. These extremes are expressed in terms of the variations that might be observed every 100 and 200 years in the horizontal strength and in the declination of the field. We find that both measured and extrapolated extreme values generally increase with geomagnetic latitude (as might be expected), though there is a marked maximum in estimated extreme levels between about 53 and 62 degrees north. At typical midlatitude European observatories (55–60 degrees geomagnetic latitude), compass variations may reach approximately 3–8 degrees/minute, and horizontal field changes may reach 1000–4000 nT/minute, in one magnetic storm once every 100 years. For storm return periods of 200 years the equivalent figures are 4–11 degrees/minute and 1000–6000 nT/minute

Variation of Absorption Angstrom Exponent in Aerosols From Different Emission Sources

The absorption Angstrom exponent (AAE) describes the spectral dependence of light absorption by aerosols. AAE is typically used to differentiate between different aerosol types for example., black carbon, brown carbon, and dust particles. In this study, the variation of AAE was investigated mainly in fresh aerosol emissions from different fuel and combustion types, including emissions from ships, buses, coal-fired power plants, and residential wood burning. The results were assembled to provide a compendium of AAE values from different emission sources. A dual-spot aethalometer (AE33) was used in all measurements to obtain the light absorption coefficients at seven wavelengths (370-950 nm). AAE(470/950) varied greatly between the different emission sources, ranging from -0.2 +/- 0.7 to 3.0 +/- 0.8. The correlation between the AAE(470/950) and AAE(370-950) results was good (R-2 = 0.95) and the mean bias error between these was 0.02. In the ship engine exhaust emissions, the highest AAE(470/950) values (up to 2.0 +/- 0.1) were observed when high sulfur content heavy fuel oil was used, whereas low sulfur content fuels had the lowest AAE(470/950) (0.9-1.1). In the diesel bus exhaust emissions, AAE(470/950) increased in the order of acceleration (0.8 +/- 0.1), deceleration (1.1 +/- 0.1), and steady driving (1.2 +/- 0.1). In the coal-fired power plant emissions, the variation of AAE(470/950) was substantial (from -0.1 +/- 2.1 to 0.9 +/- 1.6) due to the differences in the fuels and flue gas cleaning conditions. Fresh wood-burning derived aerosols had AAE(470/950) from 1.1 +/- 0.1 (modern masonry heater) to 1.4 +/- 0.1 (pellet boiler), lower than typically associated with wood burning, while the burn cycle phase affected AAE variation.Peer reviewe

Investigating the chemical species in submicron particles emitted by city buses

Detailed chemical characterization of exhaust particles from 23 individual city buses was performed in Helsinki, Finland. Investigated buses represented different technologies in terms of engines, exhaust after-treatment systems (e.g., diesel particulate filter, selective catalytic reduction, and three-way catalyst) and fuels (diesel, diesel-electric (hybrid), ethanol, and compressed natural gas). Regarding emission standards, the buses operated at EURO III, EURO IV, and EEV (enhanced environmentally friendly vehicle) emission levels. The chemical composition of exhaust particles was determined by using a soot particle aerosol mass spectrometer (SP-AMS). Based on the SP-AMS results, the bus emission particles were dominated by organics and refractory black carbon (rBC). The mass spectra of organics consisted mostly of hydrocarbon fragments (54-86% of total organics), the pattern of hydrocarbon fragments being rather similar regardless of the bus type. Regarding oxygenated organic fragments, ethanol-fueled buses had unique mass-to-charge ratios (m/z) of 45, 73, 87, and 89 (mass fragments of C2H5OC, C3H5O2+, C4H7O2+, and C4H9O2+, respectively) that were not detected for the other bus types at the same level. For rBC, there was a small difference in the ratio of C-4(+) and C-5(+) to C-3(+) for different bus types but also for the individual buses of the same type. In addition to organics and rBC, the presence of trace metals in the bus emission particles was investigated.Peer reviewe

Evaluation and modeling of the size fractionated aerosol number concentration measurements near a major road in Helsinki

Non peer reviewe

Evaluation and modeling of the size fractionated aerosol number concentration measurements near a major road in Helsinki

Non peer reviewe