Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.     

Assessing agricultural land-use change in the Midlands region of KwaZulu-Natal,South Africa: application of mixed multinomial logit

On-farm tree cultivation is considered an important strategy to mitigate detrimental environmental impacts of agricultural land-use change (ALUC). In South Africa, however, little is known about farm-level incentives and constraints that govern ALUC decisions among small-scale farmers. To address this knowledge gap, this study employs a mixed multinomial logit model by using a combination of revealed and stated preference data. After correcting for endogeneity, the estimated results show that decisions about ALUC are rationally derived and driven by clear but heterogeneous preferences and trade-offs between crop productivity, food security and labour saving. The results further show that the decision to plant sugarcane is constrained by landholding, whilst farmland afforestation is negatively influenced by household size. Decisions to convert land use are also driven by the behaviour of peer groups and agro-ecological conditions. Based on these findings, important policy implications for sustainable land use are outlined.     

Saharan dust particles in snow samples of Alps and Apennines during an exceptional event of transboundary air pollution

Southern European countries are often affected in summer by transboundary air pollution from Saharan dust. However, very few studies deal with Saharan dust pollution at high altitudes in winter. In Italy, the exceptional event occurred on February 19, 2014, colored in red the entire mountain range (Alps and Apennines) and allowed to characterize the particulate matter deposited on snow from a morphological and chemical point of view. Snow samples were collected after this event in four areas in the Alps and one in the Apennines. The particulate matter of the melted snow samples was analyzed by scanning electron microscopy with energy dispersive X-ray spectrometry (SEM-EDS) and by inductively coupled plasma mass spectrometry (ICP-MS). These analyses confirmed the presence of Saharan dust particle components in all areas with similar percentages, supported also by the positive correlations between Mg-Ca, Al-Ca, Al-Mg, and Al-K in all samples.     

Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: a case study Coruh River Basin

In this study, the water quality of the Coruh River Basin, which is located in the Eastern Black Sea Region of Turkey, was evaluated. The water quality data measurement results obtained by the State Hydraulic Works 26th Regional Directorate from four different sites over a course of 4 years between the years 2011 and 2014 in the Coruh River Basin were used as the data. In this study, the water quality was evaluated by using the Canadian Council of Ministers of the Environmental Water Quality Index (CCME WQI) method and discriminant analysis (DA). The water quality of the Coruh River Basin was calculated as 30.4 and 71.35 by using the CCME WQI and classified as “poor,” “marginal,” and “fair”. These values show that the water of the Coruh River Basin is degraded and under threat and its overall quality is not close to natural or desired levels. The monitoring sites were divided into two groups by the cluster analysis (CA). DA is a multivariate analysis technique used to divide individuals or objects into different groups and assign them into predetermined groups. As a result of DA, calcium (Ca) and sulfate (SO₄) were determined to be significant parameters in the determination of the water quality of the Coruh River Basin. The success of DA depends on the percentage of correct classification. As a result of the analysis, 23% of the parameters in the first measurement point, 69.2% of the parameters in the second and third measurement points, and 76.9% of the parameters in the fourth measurement point were classified correctly. Since the second measurement point is the discharge point of a copper mine, it can be said that the water quality parameters measured may provide accurate results in detecting pollution at this point.     

Hunting Selectivity and Its Influence on the Structure of Sable Populations in the Cis-Ural Region

The structure of commercial sable samples from the Cis-Ural region was studied taking into account hunting method (shooting or trapping). The proportion of adult animals was found to be significantly lower in samples taken during the first half of the hunting season, compared to the second half, indicating predominant harvesting of young animals. To estimate the degree of hunting selectivity (I), the ratios of demographic groups among shot and trapped animals were calculated. The results confirmed the fact of selective hunting for underyearlings both by shooting (I = 1.49–1.60 for the Cis-Ural region and I = 2.46–3.37 for the Western Sayan Mountains) and by trapping (I = 2.80–4.37), especially during the first half of winter. Samples taken during the second half of the season were characterized by prevalence of adult animals making up the reproductive core of the population (I = 1.43–2.07). It is considered that the process of reproduction in Cis-Ural sable populations in the 1960s to 1980s was stimulated by intensive commercial hunting. To maintain reproduction of sable populations at a safe level, it is necessary to reduce the period of hunting in the first quarter of the year. It is proposed to use the phenomenon of hunting selectivity for managing sable populations, regulating their exploitation, and improving the economic productivity of habitats. Commercial hunting in terms of its impact on the population can act as a factor of conscious or unconscious artificial selection.     

The impact of global change on economic values of water for Public Irrigation Schemes at the São Francisco River Basin in Brazil

Economic values of water for the main Public Irrigation Schemes in the sub-middle region of the São Francisco River Basin, in northeastern Brazil, are determined in this study using an integration of a global agro-economic land and water use (MAgPIE) with a local economic model (Positive Mathematical Programming). As in the latter, the water values depend on the crops grown, and as Brazilian agriculture is strongly influenced by the global market, we used a regionalized version of the global model adapted to the region in order to simulate the crop land use, which is in turn determined by changes in global demand, trade barriers, and climate. The allocation of sugarcane and fruit crops projected with climate change by the global model, showed an impact on the average yields and on the water costs in the main schemes resulting in changes in the water values locally. The economic values for all schemes in the baseline year were higher than the water prices established for agricultural use in the basin. In the future, these water values will be higher in all the schemes. The highest water values currently and in the future were identified in municipalities with a significant proportion of area growing irrigated sugarcane. Being aware of current water values of each user in a baseline year and in a projected future under global climate and socioeconomic changes, decision makers should improve water allocation policies at local scale, in order to avoid conflicts and unsustainable development in the future.     

Water quality index for agricultural systems in Northwest Uruguay

Agricultural systems have experienced rapid expansion and intensification in the last several decades. In Uruguay, since the beginning of 2000, the most common cropping systems have included soybeans. Currently, this crop is expanding towards lowlands traditionally occupied by rice in rotation with pastures. However, the environmental effects of agricultural intensification and diversification are not well known. Thus, some indices have been proposed to quantify the changes in agricultural production systems and assess water quality. The main goal of this study was to develop a water quality index (WQI) to assess the impacts of the diversification of rice production systems in northwest Uruguay. The study was carried out in an agricultural basin where other summer crops have been incorporated in the rice-pasture sequence. Agriculture intensification and crop diversification indices were calculated using information provided by farmers. Water samples were collected downstream of the production area before crop sowing and after crop harvest (2008–2009 to 2010–2011 and 2016–2017 to 2017–2018). Biochemical oxygen demand, nitrates, total phosphorus, fecal coliforms, and total suspended solids were the variables that mainly explained the effects of the agricultural activities on water quality. The proposed water quality index included these unweighted variables, which allowed for the pre-sowing and post-harvest to be differentiated, as well as the degree of diversification. Therefore, the proposed WQI constitutes a tool that can be used to evaluate the water quality in an agricultural basin. Likewise, it can be used to select agricultural sequences that generate the least possible impacts on the associated water resources.     

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.