Comparison of dynamic subgrid-scale models for simulations of neutrally buoyant shear-driven atmospheric boundary layer flows

Several non-dynamic, scale-invariant, and scale-dependent dynamic subgrid-scale (SGS) models are utilized in large-eddy simulations of shear-driven neutral atmospheric boundary layer (ABL) flows. The popular Smagorinsky closure and an alternative closure based on Kolmogorov’s scaling hypothesis are used as SGS base models. Our results show that, in the context of neutral ABL regime, the dynamic modeling approach is extremely useful, and reproduces several establised results (e.g., the surface layer similarity theory) with fidelity. The scale-dependence framework, in general, improves the near-surface statistics from the Smagorinsky model-based simulations. We also note that the local averaging-based dynamic SGS models perform significantly better than their planar averaging-based counterparts. Lastly, we find more or less consistent superiority of the Smagorinsky-based SGS models (over the corresponding Kolmogorov’s scaling hypothesis-based SGS models) for predicting the inertial range scaling of spectra.     

Development of similarity relationships for energy dissipation rate and temperature structure parameter in stably stratified flows: a direct numerical simulation approach

In this study, a newly developed direct numerical simulation (DNS) solver is utilized for the simulations of numerous stably stratified open-channel flows with bulk Reynolds number (Re _b ) spanning 3400–16,900. Overall, the simulated bulk Richardson number (\(Ri_b\)) ranges from 0.08 (weakly stable) to 0.49 (very stable). Thus, both continuously turbulent and (globally) intermittently turbulent cases are represented in the DNS database. Using this comprehensive database, various flux-based and gradient-based similarity relationships for energy dissipation rate (ε) and temperature structure parameter (\(C_T^2\)) are developed. Interestingly, these relationships exhibit only minor dependency on Re _b . In order to further probe into this Re _b -effect, similarity relationships are also estimated from a large-eddy simulation (LES) run of an idealized atmospheric boundary layer (very high Re _b ) case study. Despite the fundamental differences in the estimation of ε and \(C_T^2\) from the DNS- and the LES-generated data, the resulting similarity relationships, especially the gradient-based ones, from these numerical approaches are found to be remarkably similar. More importantly, these simulated relationships are also comparable, at least qualitatively, to the traditional observational data-based ones. Since these simulated similarity relationships do not require Taylor’s hypothesis and do not suffer from mesoscale disturbances and/or measurement noise, they have the potential to complement the existing similarity relationships.     

Air quality analysis and indexing of Kolkata city with respect to vertical floor heights and seasonal variation

Air pollution is one of the most important global environmental issues. Urban air quality is generally becoming vulnerable especially in the developing countries due to various developmental activities. Several national and international studies prove that air pollution is harmful to human health and its long term exposure contributes to even mortality. Current study has been designed to determine the vertical floor wise air quality status of the city of Kolkata and the seasonal variation of the pollutants during two consecutive years. Particulate matter (PM₁₀ and suspended particulate matter), oxides of nitrogen, sulfur dioxide and carbon monoxide were analyzed for a total number of 135 air quality samples throughout the study area and period. Pollutants were found positively correlated with each other and with the floor heights. According to the air quality indexing, all the places were found affected from moderate to severe air pollution irrespective of the vertical floor heights, seasons and places. Although, no such seasonal trend has been emerged from the study but the number of samples beyond standard is found highest during the winter season followed by pre-monsoon.     

Species-level study on arsenic availability from dietary components

Arsenic (As) contaminated water and foodstuffs are of major concern. Samples of drinking–cooking water (n = 50), raw rice (n = 50), common vegetables (eight types), and common pulses (three types) were collected from households in the endemic region. The study found up to 70% As reduction by using safe water for cooking of rice and vegetables. Speciation study reflected more arsenate than arsenite and other organic arsenicals in all the types of samples. Male intake of 293 μg As through drinking water contained 38 μg arsenite and 246 μg arsenate, and female intake of 199 μg As contained 167 μg arsenate and 25 μg arsenite. In cooked rice, 108 μg As contained 69 μg arsenate and 17 μg arsenite with 9 μg dimethylarsonic acid (DMA). Total As consumption from cooked vegetables was 45 μg with 34 and 4 μg of arsenite and arsenate, respectively, and 5 μg of DMA. Data indicate that cooking with As-free water removes arsenic in already contaminated foodstuffs but without interconversion of the As species, from toxic inorganic to less toxic organic forms.     

An ecotoxicological view on neurotoxicity assessment

The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.     

Predicting climate change and its impact on future occurrences of vector-borne diseases in West Bengal,India

Environment, Development and Sustainability - Climate change is a concerning matter nowadays. It has a long-term effect on human health by spreading vector-borne diseases throughout the world, and...     

Revisiting and revising Tatarskii’s formulation for the temperature structure parameter ( $$C_T^2$$ C T 2 ) in atmospheric flows

Environmental Fluid Mechanics - In this paper, we revisit a well-known formulation of temperature structure parameter ( $$C_T^2$$ ), originally proposed by V. I. Tatarskii. We point out its...