Assessment using CFD of the wind direction on the air discharges caused by natural ventilation of a poultry house

Air inside poultry houses must be removed on a regular basis to prevent excess of heat, particles and noxious gases that can imperil animals. To cope with this issue, natural ventilation could be an effective method when assisted by accurate predictions. This study investigates air discharges caused by natural ventilation of a poultry house by means of a three-dimensional computational fluid dynamics (CFD) model. It solves the governing equations of momentum, heat and mass transport, radiative transfers and animal-generated heat. Wind directions of 0°, 36° and 56° (0° corresponds to a wind blowing perpendicular to the ridgeline) were investigated; the CFD model predictions achieved a RMSE of 1.2 °C and 0.6 g[H₂O] kg^?1 [dry air] for internal temperature and absolute humidity, respectively, when air blew with an angle of 36°. Air renewal rates (ARR) were 39.5 (±?1.9), 34.9 (±?2.2) and 33.6 (±?1.7) volumes of the building per hour, when air blew at 0°, 36° and 56°, respectively. Such ARR predictions served to know how the gases contained in air would likely spread downstream from the building in order to define regions of potentially high gas concentration that could endanger neighbouring habitable facilities.     

GPU Accelerated Lattice Boltzmann Simulation of a Cyanide-Release Accident in the Danjiangkou Reservoir

A graphics processing unit (GPU) accelerated two-dimensional contamination transport model is developed using the lattice Boltzmann method (LBM). The intrinsic parallel features of LBM make it particularly suitable for implementation on GPUs. After validation with two benchmarks, the model was applied to a cyanide-release accident in the Danjiangkou Reservoir, using a numerical combination of hydrodynamics and solute transport. The results show good agreement with an Environmental Fluid Dynamics Code (EFDC) model. A single GPU workstation speedup reaches 1.58 times that of a central processing unit (CPU) calculation alone. This speedup provides the opportunity for applying the model as a pollution accident information and decision support system for the Middle Route of the South to North Water Diversion Project in China.     

The Impact of Unilateral Commitment on Transboundary Pollution

To reach a common target of environmental quality, countries can choose to commit to a stream of pollution abatement right from the beginning of the game or decide upon abatement at each moment of time. Though most of the previous literature studies homogeneous strategies where no country or all countries commit to a (same) predefined policy, reality goes along a different way: some countries make more efforts than others to reduce pollutant emission. The main novelty of this paper resides in the introduction of this kind of heterogeneous strategic behavior currently observed among large pollution nations. We find that the pollution level can be lower under heterogeneous than under homogeneous strategies. A stringent environmental quality target will induce the committed player to produce an abatement effort that more than compensates the free-riding attitude of the non-committed player.     

Design,Modelling and Assessment of Emission Scenarios Resulting from a Network of Wood Biomass Boilers

The use of wood biomass as a fuel for domestic and industrial heating systems allows for a reduction of CO₂ emissions at a global scale, but it may also result in worse local air quality conditions, due to their emissions of particulate matter. The aim of this study is to assess the actual trend of atmospheric pollution in a study area, assuming that all heating systems are replaced by small size biomass boilers linked to the buildings through district heating network. Ground level concentrations of particulate matter, emitted by different heating systems, are therefore evaluated through numerical simulations performed by means of an atmospheric dispersion model (Sirane). As a first step, we have compared the environmental impact of a woodchip boilers network with that given by the use of traditional heating systems, i.e. wood stoves and natural gas boilers. As a second step, we have analysed the impact of such a network taking into account different emission scenarios, related to different boilers operating conditions. Results show that the environmental performances of a woodchip boilers network can be optimized by combining it with other renewable sources of energy devoted to the supply of hot water. The adopted analysis methodology can be applied to other real or hypothetic punctual sources on the territory.     

Natural Resource Use with Vague-Transferability in Property Right

The purpose of this paper is to study the impacts of the vagueness about the transfer of the harvest right on the use of a natural resource. We develop one-period non-cooperative game frameworks to examine whether the choice of the resource owner to be hazy about the transmission of the harvest contract is optimal. In the perfect information situation, we show that it is optimal for the resource owner to forbid the transfer of the harvest right instead of being hazy about it when the transfer fees are lesser than the collected net punishment fines of the monitoring costs even though the resource would be inefficiently used. In particular, we find in this case that the government’s announcement to forbid the transfer of the right should be public. We further show that there are subgame Nash equilibria in the perfect information context and a unique Nash equilibrium in the imperfect information setting. Specifically, we show that, when the transfer fees are greater or equal to the (net) punishment fines, there is a Nash equilibrium both in perfect and imperfect information situations, precisely when the owner chooses to allow the transfer of harvest title and the resource harvester transfers it.     

Groundwater Modeling in Agricultural Watershed under Different Recharge and Discharge Scenarios for Quaternary Aquifer Eastern Nile Delta,Egypt

Different scenarios of recharge and discharge were assessed for sustainable management of groundwater in Quaternary aquifer east of Nile Delta. MODFLOW was utilized to investigate the effect of land use change and damming construction in the upstream of the Nile River on the current and short-term groundwater management strategies. The interpretive transient simulation was performed between 2004 and 2016 after steady-state calibration in 2004, and transient state from 2004 to 2013 with different irrigation recharges associated with land use change in this period. Sensitivity analysis was performed for hydraulic conductivities, recharge, and conductance parameters. The predictive transient simulation was run till 2023 under three scenarios of increasing pumping rates by 15, 30, and 50% for agriculture expansion and specified head reduction of Port Said Canal by 0.2, 0.4, and 0.6 m associated with the reduction of Nile water levels after Grand Ethiopian Residence Dam, GERD operation in 2017. Results from the in- and out-flow budgets showed that groundwater aquifer is stable at the current rate of pumping till 2023. Groundwater heads decreased by 0.2 and 0.42 m in the southern section, and a slight increase in the northern part was noticed for the first and second scenarios, respectively. When additional pumping stress is applied (50% increase), groundwater head dropped by 0.66 m, and the storage is no longer able to maintain the aquifer capacity after 2020 (worst-case scenario).     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

A Mathematical Model for the Effects of Fertilization on Nitrogen Concentrations in Unsaturated Soil on Blueberry Farms in Southern New Jersey

Nitrogen is commonly known as a food source for crops. However, the nitrogen compounds used in crop fertilizers, most commonly nitrate (NO₃) and ammonium (NH₄), are not widely understood. Blueberry plants do not take up these compounds as efficiently as organic nitrogen so varying amounts of leaching into the soil and groundwater will occur. A biogeochemical model consisting of ordinary and partial differential equations is implemented to computationally predict the concentrations of nitrate and ammonium in unsaturated soil of blueberry plants, specifically in the southern region of New Jersey. The model takes into account the type of soil of the region, the nitrate uptake of the plant, the water content in the roots region, the pressure heads in the soil pores, and the application rates of fertilizers containing nitrate, ammonium, and organic nitrogen. Computational simulations demonstrate that the model accounts for natural processes and, in addition, show that commonly used fertilizer application rates cause unnecessarily high concentrations of both nitrate and ammonium in the unsaturated soil level. Further, simulations show that decreasing nitrate fertilizer applications by 85.7% in annual and 91.8% in bi-annual schedules provides an optimal system for safe reapplication.     

Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations

We introduce robust procedures for analyzing water quality data collected over time. One challenging task in analyzing such data is how to achieve robustness in presence of outliers while maintaining high estimation efficiency so that we can draw valid conclusions and provide useful advices in water management. The robust approach requires specification of a loss function such as the Huber, Tukey’s bisquare and the exponential loss function, and an associated tuning parameter determining the extent of robustness needed. High robustness is at the cost of efficiency loss in parameter loss. To this end, we propose a data-driven method which leads to more efficient parameter estimation. This data-dependent approach allows us to choose a regularization (tuning) parameter that depends on the proportion of “outliers” in the data so that estimation efficiency is maximized. We illustrate the proposed methods using a study on ammonium nitrogen concentrations from two sites in the Huaihe River in China, where the interest is in quantifying the trend in the most recent years while accounting for possible temporal correlations and “irregular” observations in earlier years.     

Multivariate analyses of the effect of an urban wastewater treatment plant on spatial and temporal variation of water quality and nutrient distribution of a tropical mid-order river

Freshwater resources are increasingly scarce due to human activities, and the understanding of water quality variations at different spatial and temporal scales is necessary for adequate management. Here, we analyze the hypotheses that (1) the presence of a wastewater treatment plant (WWTP) and (2) a polluted tributary that drains downstream from the WWTP change the spatial patterns of physicochemical variables (pH, turbidity, dissolved oxygen, and electrical conductivity) and nutrient concentrations (reactive soluble phosphorus, total phosphorus, nitrogen series, total nitrogen, and total dissolved carbon) along a mid-order river in SE Brazil and that these effects depend on rainfall regime. Six study sites were sampled along almost 4 years to evaluate the impacts of human activities, including sites upstream (1–3) and downstream (5–6) from the WWTP. The impacts were observed presenting an increasing trend from the source (site 1) towards Água Quente stream (site 4, the polluted tributary), with signs of attenuation at site 5 (downstream from both WWTP and site 4) and the river mouth (site 6). Input of nutrients by rural and urban runoff was observed mainly at sites 2 and 3, respectively. At sites 4 and 5, the inputs of both untreated and treated wastewaters increased nutrient concentrations and changed physicochemical variables, with significant impacts to Monjolinho River. Seasonal variations in the measured values were also observed, in agreement with the pluviometric indexes of the region. Univariate analyses suggested no effect of the WWTP for most variables, with continued impacts at sites downstream, but non-parametric multivariate analysis indicated that these sites were recovering to chemical characteristics similar to upstream sites, apparently due to autodepuration. Therefore, multivariate methods that allow rigorous tests of multifactor hypotheses can greatly contribute to determine effects of both point and non-point sources in river systems, thus contributing to freshwater monitoring and management.