Understanding core tungsten (W) transport and control in an improved high-performance fully non-inductive discharge on EAST

The behavior of heavy/high-Z impurity tungsten (W) in an improved high-performance fully non-inductive discharge on EAST with ITER-like divertor (ILD) is analyzed. It is found that W could be well controlled. The causes of no W accumulation are clarified by analyzing the background plasma parameters and modeling the W transport. It turns out that the electron temperature (T_e) and its gradient are usually high while the toroidal rotation and density peaking of the bulk plasma are small. In this condition, the modeled W turbulent diffusion coefficient is big enough to offset the total turbulent and neoclassical pinch, so that W density profile for zero particle flux will not be very peaked. Combining NEO and TGLF for the W transport coefficient and the impurity transport code STRAHL, not only the core W density profile is predicted but also the radiated information mainly produced by W in the experiment can be closely reconstructed. At last, the physics of controlling W accumulation by electron cyclotron resonance heating (ECRH) is illustrated considering the effects of changed T_e by ECRH on ionization balance and transport of W. It shows that the change of ionization and recombination balance by changed T_e is not enough to explain the experimental observation of W behavior, which should be attributed to the changed W transport. By comparing the W transport coefficients in two kinds of plasmas with different T_e profiles, it is shown that high T_e and its gradient play a key role to generate large turbulent diffusion through increasing the growth rate of linear instability so that W accumulation is prevented.

Impact of modified turbulent diffusion of PM_2.5 aerosol in WRF-Chem simulations in eastern China

Correct description of the boundary layer mixing process of particle is an important prerequisite for understanding the formation mechanism of pollutants, especially during heavy pollution episodes. Turbulent vertical mixing determines the distribution of momentum, heat, water vapor and pollutants within the planetary boundary layer (PBL). However, what is questionable is that the turbulent mixing process of particles is usually denoted by turbulent diffusion of heat in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). With mixing-length theory, the turbulent diffusion relationship of particle is established, embedded into the WRF-Chem and verified based on long-term simulations from 2013 to 2017. The new turbulent diffusion coefficient is used to represent the turbulent mixing process of pollutants separately, without deteriorating the simulation results of meteorological parameters. The new turbulent diffusion improves the simulation of pollutant concentration to varying degrees, and the simulated results of PM2.5 concentration are improved by 8.3 % (2013), 17 % (2014), 11 % (2015) and 11.7 % (2017) in eastern China, respectively. Furthermore, the pollutant concentration is expected to increase due to the reduction of turbulent diffusion in mountainous areas, but the pollutant concentration did not change as expected. Therefore, under the influence of complex topography, the turbulent diffusion process is insensitive to the simulation of the pollutant concentration. For mountainous areas, the evolution of pollutants is more susceptible to advection transport because of the simulation of obvious wind speed gradient and pollutant concentration gradient. In addition to the PM2.5 concentration, the concentration of CO as a primary pollutant has also been improved, which shows that the turbulent diffusion process is extremely critical for variation of the various aerosol pollutants. Additional joint research on other processes (e.g., dry deposition, chemical and emission processes) may be necessary to promote the development of the model in the future.

Simulating Diurnal Variations of Water Temperature and Dissolved Oxygen in Shallow Minnesota Lakes

In shallow lakes, water quality is mostly affected by weather conditions and some ecological processes which vary throughout the day. To understand and model diurnal-nocturnal variations, a deterministic, one-dimensional hourly lake water quality model MINLAKE2018 was modified from daily MINLAKE2012, and applied to five shallow lakes in Minnesota to simulate water temperature and dissolved oxygen (DO) over multiple years. A maximum diurnal water temperature variation of 11.40 °C and DO variation of 5.63 mg/L were simulated. The root-mean-square errors (RMSEs) of simulated hourly surface temperatures in five lakes range from 1.19 to 1.95 °C when compared with hourly data over 4–8 years. The RMSEs of temperature and DO simulations from MINLAKE2018 decreased by 17.3% and 18.2%, respectively, and Nash-Sutcliffe efficiency increased by 10.3% and 66.7%, respectively; indicating the hourly model performs better in comparison to daily MINLAKE2012. The hourly model uses variable hourly wind speeds to determine the turbulent diffusion coefficient in the epilimnion and produces more hours of temperature and DO stratification including stratification that lasted several hours on some of the days. The hourly model includes direct solar radiation heating to the bottom sediment that decreases magnitude of heat flux from or to the sediment.

Estimation of the Vertical Turbulent Exchange Intensity in the Main Pycnocline Layer in the Prikerchensky Area of the Black Sea Shelf

The paper investigates the seasonal variability of the vertical turbulent exchange coefficient in the upper stratified layer of the Black Sea. The expedition data used in this work containing information on the microstructure of physical fields were obtained in different hydrological seasons covering the northeastern part of the Black Sea in the Prikerchensky area of the shelf slope. The data were collected during cruises of r/v “Professor Vodyanitsky” in 2016–2019 using “Sigma-1” sounding complex. Based on the semi-empirical methods of assessment of vertical turbulent exchange in the deep-water area of the Black Sea, the dependence of the vertical turbulent diffusion coefficient K on the buoyancy frequency N in the studied layer was established from the flow fluctuation characteristics, with the corresponding graphs and their approximating power-law dependences K  A  N  plotting. In addition, the vertical distribution of the K coefficient with depth was analyzed. Comparative analysis of the obtained dependences with the results of the 1.5D model was carried out. The analysis of the measurement data showed that the results obtained in this work do not contradict the original model. The results can also be used to assess the vertical fluxes of heat, salt and other dissolved chemical and biological substances depending on stratification in the studied part of the Black Sea for different seasons.

Mean velocity, spreading and entrainment characteristics of weak bubble plumes in unstratified and stationary water

In this paper we present an experimental and theoretical study of weak bubble plumes in unstratified and stationary water. We define a weak bubble plume as one that spreads slower than the linear rate of a classic plume. This work focuses on the characteristics of the mean flow in the plume, including centreline velocity, plume spreading and entrainment of ambient water. A new theory based on diffusive spreading instead of an entrainment hypothesis is used to describe the lateral spreading of the bubbles and the associated plume. The new theory is supported by the experimental data. With the measured data of liquid volume fluxes and the new theory, we conclude that the weak bubble plume is a decreasing entrainment process, with the entrainment coefficient $\unicode[STIX]{x1D6FC}$ in the weak bubble plume decreasing with height $z$, following $\unicode[STIX]{x1D6FC}\sim z^{-1/2}$, and taking on values much smaller than those in a classic bubble plume. An additional non-dimensional diffusion coefficient, $\hat{E_{t}}\sim E_{t}U_{s}^{2}/B_{0}$, is also needed to describe the evolution of the volume and kinematic momentum fluxes for the mean flow in the weak bubble plume. Here, $E_{t}$ is the effective turbulent diffusion coefficient, $U_{s}$ is the terminal rise velocity of the bubbles, and $B_{0}$ is the kinematic buoyancy flux of the source. Finally, we provide a unified framework for the mean flow characteristics, including volume flux, momentum flux and plume spreading for the classic and weak bubble plumes, which also provides insight on the transition from classic to weak bubble plume behaviour.

Tunable diffusion in wave-driven two-dimensional turbulence

We report an abrupt change in the diffusive transport of inertial objects in wave-driven turbulence as a function of the object size. In these non-equilibrium two-dimensional flows, the turbulent diffusion coefficient $D$ of finite-size objects undergoes a sharp change for values of the object size $r_{p}$ close to the flow forcing scale $L_{f}$. For objects larger than the forcing scale ($r_{p}>L_{f}$), the diffusion coefficient is proportional to the flow energy $U^{2}$ and inversely proportional to the size $r_{p}$. This behaviour, $D\sim U^{2}/r_{p}$ , observed in a chaotic macroscopic system is reminiscent of a fluctuation–dissipation relation. In contrast, the diffusion coefficient of smaller objects ($r_{p}<L_{f}$) follows $D\sim U/r_{p}^{0.35}$. This result does not allow simple analogies to be drawn but instead it reflects strong coupling of the small objects with the fabric and memory of the out-of-equilibrium flow. In these turbulent flows, the flow structure is dominated by transient but long-living bundles of fluid particle trajectories executing random walk. The characteristic widths of the bundles are close to $L_{f}$. We propose a simple phenomenology in which large objects interact with many bundles. This interaction with many degrees of freedom is the source of the fluctuation–dissipation-like relation. In contrast, smaller objects are advected within coherent bundles, resulting in diffusion properties closely related to those of fluid tracers.

Contributions to the explosive growth of PM_2.5 mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China

The explosive growth of PM2.5 mass usually results in extreme PM2.5 levels and severe haze pollution in eastern China, and is generally underestimated by current atmospheric chemistry models. Based on one such model, GRAPES_CUACE, three sensitivity experiments – a “background” experiment (EXP1), an “online aerosol feedback” experiment (EXP2), and an “80 % decrease in the turbulent diffusion coefficient of chemical tracers” experiment, based on EXP2 (EXP3) – were designed to study the contributions of the aerosol–radiation feedback (AF) and the decrease in the turbulent diffusion coefficient to the explosive growth of PM2.5 during a “red alert” heavy haze event in China's Jing–Jin–Ji (Beijing–Tianjin–Hebei) region. The results showed that the turbulent diffusion coefficient calculated by EXP1 was about 60–70 m−2 s−1 on a clear day and 30–35 m−2 s−1 on a haze day. This difference in the diffusion coefficient was not enough to distinguish between the unstable atmosphere on the clear day and the extremely stable atmosphere during the PM2.5 explosive growth stage. Furthermore, the inversion calculated by EXP1 was obviously weaker than the actual inversion from sounding observations on the haze day. This led to a 40 %–51 % underestimation of PM2.5 by EXP1; the AF decreased the diffusion coefficient by about 43 %–57 % during the PM2.5 explosive growth stage, which obviously strengthened the local inversion. In addition, the local inversion indicated by EXP2 was much closer to the sounding observations than that indicated by EXP1. This resulted in a 20 %–25 % reduction of PM2.5 negative errors in the model, with errors as low as −16 % to −11 % in EXP2. However, the inversion produced by EXP2 was still weaker than the actual observations, and the AF alone could not completely explain the PM2.5 underestimation. Based on EXP2, the 80 % decrease in the turbulent diffusion coefficient of chemical tracers in EXP3 resulted in near-zero turbulent diffusion, referred to as a “turbulent intermittence” atmospheric state, which subsequently resulted in a further 14 %–20 % reduction of the PM2.5 underestimation; moreover, the negative PM2.5 errors were reduced to −11 % to 2 %. The combined effects of the AF and the decrease in the turbulent diffusion coefficient explained over 79 % of the underestimation of the explosive growth of PM2.5 in this study. The results show that online calculation of the AF is essential for the prediction of PM2.5 explosive growth and peaks during severe haze in China's Jing–Jin–Ji region. Furthermore, an improvement in the planetary boundary layer scheme with respect to extremely stable atmospheric stratification is essential for a reasonable description of local “turbulent intermittence” and a more accurate prediction of PM2.5 explosive growth during severe haze in this region of China.

Impact of urban canopy meteorological forcing on aerosol concentrations

The regional climate model RegCM4 extended with the land surface model CLM4.5 was coupled to the chemistry transport model CAMx to analyze the impact of urban meteorological forcing on surface fine aerosol (PM2.5) concentrations for summer conditions over the 2001–2005 period, focusing on the area of Europe. Starting with the analysis of the meteorological modifications caused by urban canopy forcing, we found a significant increase in urban surface temperatures (up to 2–3 K), a decrease of specific humidity (by up to 0.4–0.6 gkg−1), a reduction of wind speed (up to −1 ms−1) and an enhancement of vertical turbulent diffusion coefficient (up to 60–70 m2s−1). These modifications translated into significant changes in surface aerosol concentrations that were calculated by a “cascading” experimental approach. First, none of the urban meteorological effects were considered. Then, the temperature effect was added, then the humidity and the wind, and finally, the enhanced turbulence was considered in the chemical runs. This facilitated the understanding of the underlying processes acting to modify urban aerosol concentrations. Moreover, we looked at the impact of the individual aerosol components as well. The urbanization-induced temperature changes resulted in a decrease of PM2.5 by −1.5 to −2 µg m−3, while decreased urban winds resulted in increases by 1–2 µg m−3. The enhanced turbulence over urban areas resulted in decreases of PM2.5 by −2 µg m−3. The combined effect of all individual impact depends on the competition between the partial impacts and can reach up to −3 µg m−3 for some cities, especially when the temperature impact was stronger in magnitude than the wind impact. The effect of changed humidity was found to be minor. The main contributor to the temperature impact is the modification of secondary inorganic aerosols, mainly nitrates, while the wind and turbulence impact is most pronounced in the case of primary aerosol (primary black and organic carbon and other fine particle matter). The overall as well as individual impacts on secondary organic aerosol are very small, with the increased turbulence acting as the main driver. The analysis of the vertical extent of the aerosol changes showed that the perturbations caused by urban canopy forcing, besides being large near the surface, have a secondary maximum for turbulence and wind impact over higher model levels, which is attributed to the vertical extent of the changes in turbulence over urban areas. The validation of model data with measurements showed good agreement, and we could detect a clear model improvement in some areas when including the urban canopy meteorological effects in our chemistry simulations.