Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

Honeybees (<Emphasis Type="Italic">Apis mellifera</Emphasis>) as a biological barrier for contamination of honey by environmental toxic metals

The aim of the study was to investigate the transfer of toxic metals from honeybee workers (Apis mellifera L.) to bee honey in relation to the ecological state of the environment. The materials of the study consisted of samples of honeybee bodies and varietal honeys taken from the same apiary located in three areas: R1—urbanized (16), R2—ecologically clean (16) and R3—industrialized (15) of south-eastern Poland. The contents of 14 elements in all tested samples, including toxic metals (Cd, Pb, Hg, Al, Ni, Tl) as well as bioelements (K, Mg, Ca, Mn, Fe, Zn, Cu, Se), were analysed by the ICP-OES method with prior microwave mineralization. The concentrations of the majority of the studied elements, excluding aluminum and lead, were significantly higher in bee bodies than in honey samples (P?<?0.05). The pollution of bee bodies by toxic metals was dependent on the environmental cleanliness, and the most pollution was observed in the industrialized area. The bee body was the most effective barrier for Cd and Tl transfer to the honey, while the level of Ni was similar in both tested materials. The Al concentration was significantly higher in honey than bee bodies (14.81?±?24.69 and 6.51?±?5.83 mg kg^?1, respectively), which suggests the possibility of secondary contamination of honey. The greatest sensitivity to heavy metal pollution was observed in honeydew honey compared to nectar honeys (P?<?0.05). It was proved for the first time that bees work as biofilters for toxic metals and prevent honey contamination.     

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.     

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.     

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.     

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.     

The Impact of Succession Stage on Share and Traits of Clonal Plants in Abandoned <Emphasis Type="Italic">Molinion caeruleae</Emphasis> Meadows

The impact of succession stage on the share of clonal plants in the plant cover, seed rain and seedling pool has been studied in the years 2014 and 2015. The investigations were carried out in abandoned Molinion caeruleae meadows dominated by small-statured species (Patch I), tall growing large-tussock grasses (Patch II) and shrub-willows (Patch III). Although the clonal taxa dominated in the plant cover, seed rain and seedling pool, their share in subsequent study sites was quite different. The spectra of life-history traits relevant to clonality in the plant cover and seed rain were similar and did not vary significantly among subsequent locations, while they mostly differed as observed in the seedling pool. The various spectra observed in seedling pool in subsequent study sites might be due to fact that the seed germination and recruitment of offspring are strongly influenced by habitat conditions which varied remarkably in the successive Patches.     

Investigating the oil curse in OECD and Non-OECD oil-exporting economies using green measures of income

Empirical studies investigating the natural resource curse theory mostly employ cross-country and panel regression techniques subject to endogeneity bias. Also, most of these studies employ GDP in its aggregate or per-capita terms as the outcome variable in their analyses. However, the use of GDP measures of income for resource curse investigations may not portray the true incomes of resource-intensive economies. Standard national accounts treat natural resource rents as a positive contribution to income without adjusting for the value of depleted natural resource stock. This treatment often leads to a positive bias in the national income computations of resource-rich economies. Unlike previous studies, we test the robustness of the curse in the predominantly used measures of national income, GDP, by investigating the theme in genuine income measures of economic output as well. Also, the paper deviates from most empirical studies in the literature by using the Arellano–Bond difference GMM method in investigating the oil curse in OECD and Non-OECD oil-exporting economies. Additionally, we employ two alternative measures of resource intensity in our explorations; the share of oil rents in GDP and per-capita oil reserves. Our results provide evidence of the curse in Non-OECD countries employing aggregate and per-capita measures of genuine income.     

Sustainability indicators in the swine industry of the Brazilian State of Santa Catarina

In recent decades, there has been a growing concern about measuring and evaluating the results of intensive production practices, such as the mode of integration practiced on a large scale by agro-industries. The present study discusses the application and the results of a Sustainability Indicators System in the context of the swine industry in the Brazilian State of Santa Catarina. These indicators, focused on the level of sustainability maturity, can be used as a way to diagnose and compare the efficiency of the industry from a broader perspective. The research findings indicate that most of the pig farms that have been studied can be classified as “in search of sustainability or sustainable.” Nevertheless, there are differences among the dimensions and between the most ranked farms and the others which must be considered for a better design and application of public policies and company strategies toward an effective and balanced social, economic and environmental sustainability.