Assessing the value meteorological ensembles add to dispersion modelling using hypothetical releases

Atmospheric dispersion model output is frequently used to provide advice to decision makers, for example, about the likely location of volcanic ash erupted from a volcano or the location of deposits of radioactive material released during a nuclear accident. Increasingly, scientists and decision makers are requesting information on the uncertainty of these dispersion model predictions. One source of uncertainty is in the meteorology used to drive the dispersion model, and in this study ensemble meteorology from the Met Office ensemble prediction system is used to provide meteorological uncertainty to dispersion model predictions. Two hypothetical scenarios, one volcanological and one radiological, are repeated every 12 h over a period of 4 months. The scenarios are simulated using ensemble meteorology and deterministic forecast meteorology and compared to output from simulations using analysis meteorology using the Brier skill score. Adopting the practice commonly used in evaluating numerical weather prediction (NWP) models where observations are sparse or non-existent, we consider output from simulations using analysis NWP data to be truth. The results show that on average the ensemble simulations perform better than the deterministic simulations, although not all individual ensemble simulations outperform their deterministic counterpart. The results also show that greater skill scores are achieved by the ensemble simulation for later time steps rather than earlier time steps. In addition there is a greater increase in skill score over time for deposition than for air concentration. For the volcanic ash scenarios it is shown that the performance of the ensemble at one flight level can be different to that at a different flight level; e.g. a negative skill score might be obtained for FL350-550 and a positive skill score for FL200-350. This study does not take into account any source term uncertainty, but it does take the first steps towards demonstrating the value of ensemble dispersion model predictions.

An electromagnetic wave attenuation superposition structure for thin-layer plasma

This work proposes a new plasma super-phase gradient metasurfaces (PS-PGMs) structure, owing to the limitations of the thin-layer plasma for electromagnetic wave attenuation. Based on the cross-shaped surface unit configuration, we have designed the X-band absorbing structure through the dispersion control method. By setting up the Drude dispersion model in the computer simulation technology, the designed phase gradient metasurfaces structure is superposed over the plasma, and the PS-PGMs structure is constructed. The electromagnetic scattering characteristics of the new structure have been simulated, and the reflectance measurement has been carried out to verify the absorbing effect. The results demonstrate that the attenuation effect of the new structure is superior to that of the pure plasma structure, which invokes an improved attenuation effect from the thin layer plasma, thus enhancing the feasibility of applying the plasma stealth technology to the local stealth of the strong scattering part of a combat aircraft.

Vehicle Traffic as a Source of CO2, CO, HC and Particulate Polycyclic Aromatic Hydrocarbon in the Mingora City, District Swat, KP, Pakistan and Their Effect on Health, Temperature and Tourism

In this work we collected a large number of vehicular emission data of carbon dioxide (CO2), carbon monoxide (CO) and hydrocarbons (HC) from custom paid and non-custom paid vehicles in the Swat district, which are responsible for changing the climate and global warming. Swat valley is facing severe threats and impacts of the climate change as there is a record high increase in the temperature with flash floods and droughts becoming increasingly common. The main cause of the increasing warm weather is vehicle emissions along with the cutting of forest on a large scale in the valley. Hospital records for 2768 children aged 0 to 18 years (697 of whom had two encounters) were obtained for a main city area of two hospitals in Saidu Sharif, Swat. Residential addresses were geocoded. A line source dispersion model was used to estimate individual seasonal exposures to local traffic-generated pollutants (nitrogen oxides, carbon monoxide and hydroxide).

Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network

Given its abundant coal mining activities, the Upper Silesian Coal Basin (USCB) in southern Poland is one of the largest sources for anthropogenic methane (CH4) emissions in Europe. Here, we report on CH4 emission estimates for coal mine ventilation facilities in the USCB. Our estimates are driven by pair-wise upwind-downwind observations of the column-average dry-air mole fractions of CH4 (XCH4) by a network of four portable, ground-based, sun-viewing Fourier Transform Spectrometers of the type EM27/SUN operated during the CoMet campaign in May/June 2018. The EM27/SUN were deployed in the four cardinal directions around the USCB in approx. 50 km distance to the center of the basin. We report on six case studies for which we inferred emissions by evaluating the mismatch between the observed downwind enhancements and simulations based on trajectory calculations releasing particles out of the ventilation shafts using the Lagrangian particle dispersion model FLEXPART. The latter was driven by wind fields calculated by WRF (Weather Research and Forecasting model) under assimilation of vertical wind profile measurements of three co-deployed wind lidars. For emission estimation, we use a Phillips-Tikhonov regularization scheme with the L-curve criterion. Diagnosed by the averaging kernels, we find that, depending on the catchment area of the downwind measurements, our ad-hoc network can resolve individual facilities or groups of ventilation facilities but that inspecting the averaging kernels is essential to detected correlated estimates. Generally, our instantaneous emission estimates range between 80 and 133 kt CH4 a−1 for the south-eastern part of the USCB and between 414 and 790 kt CH4 a−1 for various larger parts of the basin, suggesting higher emissions than expected from the annual emissions reported by the E-PRTR (European Pollutant Release and Transfer Register). Uncertainties range between 23 and 36 % dominated by the error contribution from uncertain wind fields.

Time fractional advection-dispersion model to study transportation of particles with time-memory for unsteady nonequilibrium suspension in open-channel turbulent flows

In this study, the effects of time-memory on the mixing and nonequilibrium transportation of particles in an unsteady turbulent flow are investigated. The memory effect of particles is captured through a time-fractional advection-dispersion equation rather than a traditional advection-dispersion equation. The time-fractional derivative is considered in Caputo sense which includes a power-law memory kernel that captures the power-law jumps of particles. The time-fractional model is solved using the Chebyshev collocation method. To make the solution procedure more robust three different kinds of Chebyshev polynomials are considered. The time-fractional derivative is approximated using the finite difference method at small time intervals and numerical solutions are obtained in terms of Chebyshev polynomials. The model solutions are compared with existing experimental data of traditional conditions and satisfactory results are obtained. Apart from this, the effects of time-memory are analyzed for bottom concentration and transient concentration distribution of particles. The results show that for uniform initial conditions, bottom concentration increases with time as the order of fractional derivative decreases. In the case of transient concentration, the value of concentration initially decreases when $T<1$ and thereafter increases throughout the flow depth. The effects of time-memory \textcolor{green}{are} also analyzed under steady flow conditions. Results show that under steady conditions, transient concentration is more sensitive for linear, parabolic, and parabolic-constant models \textcolor{green}{of} sediment diffusivity rather than the constant model.

Employing Spectral Analysis to Obtain Dispersion Parameters in an Atmospheric Environment Driven by a Mesoscale Downslope Windstorm

Considering the influence of the downslope windstorm called “Vento Norte” (VNOR; Portuguese for “North Wind”) in planetary boundary layer turbulent features, a new set of turbulent parameterizations, which are to be used in atmospheric dispersion models, has been derived. Taylor’s statistical diffusion theory, velocity spectra obtained at four levels (3, 6, 14, and 30 m) in a micrometeorological tower, and the energy-containing eddy scales are used to calculate neutral planetary boundary layer turbulent parameters. Vertical profile formulations of the wind velocity variances and Lagrangian decorrelation time scales are proposed, and to validate this new parameterization, it is applied in a Lagrangian Stochastic Particle Dispersion Model to simulate the Prairie Grass concentration experiments. The simulated concentration results were shown to agree with those observed.