Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

FIA-coupled spectrophotometric method for determination of Cr (VI) traces in natural waters: application of in-line dissolution of 1,5-diphenylcarbazide after heat treatment and activated alumina as adsorbent for preconcentration

This work proposes the quantification of Cr (VI) ions in natural waters in trace level, using activated alumina (Al₂O₃) as preconcentration support, controlled in-line dissolution of the solidified chromophore diphenylcarbazide after heat treatment and spectrophotometric detection. The manifold ensures high sensitivity of analytical response, good repeatability, and stability. In this work, optimization of experimental conditions of a flow injection system was chosen as the parameters for greater sensitivity and better selectivity. The selected optimized conditions were 0.30 mol L^?1 for H₂SO₄ concentration, system flow rate as 0.40 mL min^?1, sample injection volume of 192.50 μL, 2 min for preconcentration time, and 0.10 mol L^?1 for eluent concentration. The analytical curves obtained for real sample analysis show linear range from 0.192 to 0.961 μM, linear correlation coefficient R?=?0.9997 and LOD?=?0.024 μM. The preconcentration factor of about four times was obtained through the passage of 800 μL of a standard solution containing 0.961 μM of Cr (VI) through mini-column of preconcentration followed by elution at 192.5 μL of NH₄OH 0.1 mol L^?1 solution. The solid chromogenic reagent presented high durability (weeks in daily use with mass of 0.0993 g) and good reproducibility in analytical signal. The reactivation of the mini-column of alumina should be executed after ten injections of eluent, using 800 μL of HCl 0.02 mol L^?1 solution in flow through the same. Each cycle of injection and elution of the sample takes about 5 min on the proposed terms. Despite the length of each cycle still be high, low concentrations can be detected using a technique of relatively low cost. This is due in part, the association dissolution of the chromogenic reagent directly in the line and the preconcentration step. Another important factor is the economy of reagent chromogenic, low generation of reject contributing to better quality of the environment, and the high potential for applications to work in field.     

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.     

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.     

Bioremediation of tannery effluent by Cr- and salt-tolerant bacterial strains

Microorganisms have great potential to control environmental pollution, particularly industrial sources of water pollution. Currently, leather industry is regarded as the most polluting and suffering from negative impacts due to the pollution it adds to the environment. Chromium, one of the hazardous pollutants discharged from tanneries, is highly toxic and carcinogenic in nature. Effective treatment of tannery effluent is a dire need of the era as a part of environmental management. Among all the wastewater treatment technologies, bioremediation is the most effective and environment-friendly tool to manage the water pollution. The present study evaluated the potential of 11 previously isolated bacterial strains, tolerant to high concentrations of salts and Cr for the bioremediation of tannery effluent. Among all the tested strains, Enterobacter sp. HU38, Microbacterium arborescens HU33, and Pantoea stewartii ASI11 were found most effective in reducing biological oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solids (TDS), total suspended solids (TSS), and chromium (Cr) 70, 63, 57, 87, and 54%, respectively, of tannery effluent and proliferated well under highly toxic conditions, at 9 days of incubation. The pollutant removal efficacy of these bacterial strains can be improved by extending the incubation period or by increasing the amount of inoculum.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Comprehensive analysis of the carbon impacts of vehicle intelligent speed control

In recent years sophisticated technologies have been developed to control vehicle speed based on the type of road the vehicle is driven on using Global Positioning Systems and in-car technology that can alter the speed of the vehicle. While reducing the speed of road vehicles is primarily of interest from a safety perspective, vehicle speed is also an important determinant of vehicle emissions and thus these technologies can be expected to have impacts on a range of exhaust emissions. This work analyses the results from a very large, comprehensive field trial that used 20 instrumented vehicles with and without speed control driven almost 500,000 km measuring vehicle speed at 10 Hz. We develop individual vehicle modal emissions models for CO₂ for 30 Euro III and Euro IV cars at a 1-Hz time resolution. Generalized Additive Models were used to describe how emissions from individual vehicles vary depending on their driving conditions, taking account of variable interactions and time-lag effects. We quantify the impact that vehicle speed control has on-vehicle emissions of CO₂ by road type, fuel type and driver behaviour. Savings in CO₂ of ≈6% were found on average for motorway-type roads when mandatory speed control was used compared with base case conditions. For most other types of road, speed control has very little effect on emissions of CO₂ and in some cases can result in increased emissions for low-speed limit urban roads. We also find that there is on average a 20% difference in CO₂ emission between the lowest and highest emitting driver, which highlights the importance of driver behaviour in general as a means of reducing emissions of CO₂.     

Isotopes as tracers of sources of lead and strontium in aerosols (TSP & PM2.5) in Beijing

Even after its being phased out in gasoline in the late 90s, lead (Pb) is still present at relatively high levels in the atmosphere of Beijing, China (0.10–0.18 μg m^?3). Its origin is subject to debate as several distinct sources may contribute to the observed pollution levels. This study proposes to constrain the origin(s) of Pb and strontium (Sr) in aerosols, by coupling both Pb and Sr isotope systematics. The characterisation of the main pollution sources (road traffic, smelters, metal refining plants, coal combustion, cement factories, and soil erosion) shows that they can unambiguously be discriminated by the multi-isotope approach (²⁰⁶Pb/²⁰⁴Pb and ⁸⁷Sr/⁸⁶Sr). The study of total suspended particulates (TSP) and fine particles (PM_2.5) from Beijing and its vicinity indicates that both size fractions are controlled by the same sources. Lead isotopes indicate that metal refining plants are the major source of atmospheric lead, followed by thermal power stations and other coal combustion processes. The role of this latter source is confirmed by the study of strontium isotopes. Occasionally, emissions from cement plants and/or input from soil alteration are isotopically detectable.     

Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks

The Minnesota Particulate Matter 2.5 (PM_2.5) Source Apportionment Study was undertaken to explore the utility of PM_2.5 mass, element, ion, and carbon measurements from long-term speciation networks for pollution source attribution. Ambient monitoring data at eight sites across the state were retrieved from the archives of the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and analyzed by an Effective Variance – Chemical Mass Balance (EV-CMB) receptor model with region-specific geological source profiles developed in this study. PM_2.5 was apportioned into contributions of fugitive soil dust, calcium-rich dust, taconite (low grade iron ore) dust, road salt, motor vehicle exhaust, biomass burning, coal-fired utility, and secondary aerosol. Secondary sulfate and nitrate contributed strongly (49–71% of PM_2.5) across all sites and was dominant (≥60%) at IMPROVE sites. Vehicle exhausts accounted for 20–70% of the primary PM_2.5 contribution, largely exceeding the proportion in the primary PM_2.5 emission inventory. The diesel exhaust contribution was separable from the gasoline engine exhaust contribution at the STN sites. Higher detection limits for several marker elements in the STN resulted in non-detectable coal-fired boiler contributions which were detected in the IMPROVE data. Despite the different measured variables, analytical methods, and detection limits, EV-CMB results from a nearby IMPROVE-STN non-urban/urban sites showed similar contributions from regional sources – including fugitive dust and secondary aerosol. Seasonal variations of source contributions were examined and extreme PM_2.5 episodes were explained by both local and regional pollution events.     

Climate Change and Mitigation

Planet Earth has experienced repeated changes of its climate throughout time. Periods warmer than today as well as much colder, during glacial episodes, have alternated. In our time, rapid population growth with increased demand for natural resources and energy, has made society increasingly vulnerable to environmental changes, both natural and those caused by man; human activity is clearly affecting the radiation balance of the Earth. In the session “Climate Change and Mitigation” the speakers offered four different views on coal and CO₂: the basis for life, but also a major hazard with impact on Earth’s climate. A common denominator in the presentations was that more than ever science and technology is required. We need not only understand the mechanisms for climate change and climate variability, we also need to identify means to remedy the anthropogenic influence on Earth’s climate.