A mathematical model to predict the composition and generation of hospital wastes in Iran

The aim of this study is to investigate the quality and quantity of hospital wastes in Iran. The generated hospital wastes have been estimated by the number of hospitals and the number of active beds in each province of Iran in 2001. All data and information have been gathered from: (i) Iran Statistics Center, (ii) literature review, and (iii) hospital waste investigations for an average hospital. Physical analyses have been conducted in terms of various materials (plastic, textile, paper, metal, and others) and components (biological, infectious, medical, and regular wastes). Based on the above-mentioned investigation and information, a mathematical model has been developed to calculate the generation of (infectious) hospital wastes for any desired year. Utilizing the model, generated infectious hospital wastes has been estimated as 698,937 tones for 2008 (short-term) and 3,494,387 tones for 2028 (long-term period). If the real infectious wastes are collected separately, then the generated infectious wastes will be reduced by 15.1% of the above-mentioned amount (139,787 tones for 2008, and 698,877 tones for 2028). Results of physical analysis show the components of the hospital waste as: (a) infectious, 67.3%; (b) medical, 8.8%; (c) biological, 1.8%; and (d) common municipal wastes, 22.1%. An appropriate collection method requires training the staff at hospitals along with preparation of the required facilities. Of course, both of these requirements are cost intensive.     

Performance of Cow Dung Reinforced Biodegradable Poly(Lactic Acid) Biocomposites for Structural Applications

In this work, performance of cow dung (CD) reinforced poly(lactic acid) (PLA) biocomposites was investigated for the potential use in load bearing application. CD of average 4 mm size was blended with PLA at different CD ratios (0–50 wt%) and their effects on the biocomposite properties were studied. The results showed an improvement in the flexural properties, while the tensile and impact strength dropped by 20 and 28% with the addition of 50% CD. The decline in the tensile and impact strength was due to micro-cracking and voids formation at higher CD content. Also, the incorporation of CD slightly decreased the thermal stability of the biocomposite. However, dynamic mechanical properties of the biocomposites generally improved. SEM analysis of tensile and impact fractured surfaces indicated that the CD had a reasonable adhesion with matrix. Moreover, the SEM micrographs of soil burial studies showed an accelerated degradation of higher CD wt% biocomposites.     

Application of polyamide thin-film composite layered on polysulfone-GO/TiO2 mixed matrix membranes for removal of nitrotoluene derivatives from petrochemical wastewaters

Release of harmful organic intermediates or byproducts during the manufacture of petrochemical compounds is a serious problem in petrochemical plants. In this work, polysulfone membranes blended with GO/TiO₂ nanocomposite were synthesized by phase inversion method and coated with a polyamide layer formed by interfacial polymerization to prepare a thin-film composite (TFC) sample. Analysis and characterization of the sample were carried out by XRD, FE-SEM, BET, FTIR/ATR, AFM, TGA, and zeta potential. Results indicated that incorporation of GO/TiO₂ into the membrane structure enhanced porosity, surface roughness, and macrovoid formation along the cross-section of the sublayer and permeability of the membrane. The TFC membranes were applied to remove mononitrotoluene (MNT) and dinitrotoluene (DNT) as the basic intermediates of toluene diisocyanate (TDI). The membranes demonstrated high efficiency (>?90%) for the removal of MNT and DNT according to the charge exclusion mechanism and Donnan effect. Application of the TFC membrane for treatment of wastewater in the TDI plant showed that the removal of pollutants is variable in the range of 45–65% and 53–69% for the membrane with the highest flux and highest rejection in different transmembrane pressure, respectively.

     

Field effectiveness evaluation of advanced driver assistance systems

Abstract

Objective: Advanced driver assistance systems (ADAS) are a class of vehicle technologies designed to increase safety by providing drivers with timely warnings and autonomously intervening to avoid hazardous situations. Though laboratory testing suggests that ADAS technologies will greatly impact crash involvement rates, real-world evidence that characterizes their effectiveness is still limited. This study evaluates and quantifies the association of ADAS technologies with the likelihood of a moderate or severe crash for new-model BMWs in the United States.

Methods: Vehicle ADAS option information for the cohort of model year 2014 and later BMW passenger vehicles sold after January 1, 2014 (n?=?1,063,503), was coded using VIN-identified options data. ADAS technologies of interest include frontal collision warning with autonomous emergency braking, lane departure warning, and blind spot detection. BMW Automated Crash Notification system data (from January 2014 to November 2017) were merged with vehicle data by VIN to identify crashed vehicles (n?=?15,507), including date, crash severity (delta V), and area of impact. Using Cox proportional hazards regression modeling, the study calculates the adjusted hazard ratio for crashing among BMW passenger vehicles with versus without ADAS technologies. The adjusted percentage reduction in moderate and severe crashes associated with ADAS is interpreted as one minus the hazard ratio.

Results: Vehicles equipped with both autonomous emergency braking and lane departure warning were 23% less likely to crash than those not equipped (hazard ratio [HR]?=?0.77; 95% confidence interval [CI], 0.73–0.81), controlling for model year, vehicle size and body type. Autonomous emergency braking and lane departure warning generally occur together, making it difficult to tease apart their individual effects. Blind spot detection was associated with a 14% reduction in crashes after controlling for the presence of autonomous emergency braking and lane departure warning (HR =0.86; 95% CI, 0.744–0.99). Differences were observed by vehicle type and crash type. The combined effect of autonomous emergency braking and lane departure warning was greater in newer model vehicles: Equipped vehicles were 13% less likely to crash (HR =0.87; 95% CI, 0.79–0.95) among 2014 model year vehicles versus 34% less likely to crash (HR =0.66; 95% CI, 0.57–0.77) among 2017 model year vehicles.

Conclusion: This robust cohort study contributes to the growing evidence on the effectiveness of ADAS technologies.     

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.     

Simultaneous Removal of Nitrate and Natural Organic Matter from Drinking Water Using a Hybrid Heterotrophic/Autotrophic/Biological Activated Carbon Bioreactor

Simultaneous removal of nitrate ([Formula: see text]) and natural organic matter (NOM) from drinking water using a hybrid heterotrophic/autotrophic/BAC bioreactor (HHABB) was studied in continuous mode. The HHABB consisted of three compartments: ethanol heterotrophic part, sulfur autotrophic part, and biological activated carbon (BAC)-part (including anoxic and aerobic sections). Experiments were performed with [Formula: see text] concentration 30?mg N/L, [Formula: see text] loading rate 0.72?kg N/m(3)/d, C?:?N ratio 0.53, and three concentrations of NOM (0.6, 2.6, and 5.7?mg C/L). Overall denitrification rate and efficiency of the HHABB were not affected by NOM concentration and were in the suitable ranges of 0.69-0.70?kg N/m(3)/d and 96.0%-97.7%, respectively. NOM removal at concentration 0.6?mg C/L was not efficient because of organic carbon replacement as soluble microbial products. At higher NOM concentrations, total NOM removal efficiencies were 55%-65%, 55%-70%, and 55%-65% for dissolved organic carbon, trihalomethane formation potential, and UV absorbance at 254?nm (UV(254)), respectively. The more efficient compartments of the HHABB for the removal of NOM were the ethanol heterotrophic phase and aerobic BAC-phase. The efficiency of the HHABB in the removal of NOM was considerable, and the effluent dissolved organic carbon and trihalomethane formation potential concentrations were relatively low. This study indicated that the HHABB without the anoxic BAC-phase could be a feasible alternative for simultaneous removal of [Formula: see text] and NOM from drinking water at full scale.     

High CO2 adsorption on improved ZSM-5 zeolite porous structure modified with ethylenediamine and desorption characteristics with microwave

Journal of Material Cycles and Waste Management - Synthesized zeolite Socony Mobil-5 (ZSM-5) with large pore surface structures and modified with ethylenediamine were used to achieve high CO2...     

Sustainable development conflict over freeway construction

Environmental disputes arise due to opposing views of various groups about their environmental concerns and their economic or developmental interests. Development and protection of the environment constitute two main contradictory objectives within the sustainable development paradigm, which are often in conflict. The decision support system, GMCR II, which implements the graph model for conflict resolution, is employed to model and analyze an environmental dispute arising over the construction of a new freeway between the Iranian capital, Tehran, and the city of Chalous located in the north of the country. This study demonstrates that the graph model for conflict resolution can be used as a methodology to promote a reasonable balance between economic development and environmental protection from a strategic viewpoint. In addition to systematically modelling the conflict by putting the existing information into proper perspective, it is shown how conflict analysis can be used for comparing alternative scenarios and predicting possible future outcomes. Readers should send their comments on this paper to: BhaskarNath@aol.com within 3 months of publication of this issue.     

Optimization of membrane-based CO2-removal from natural gas using simple models considering both pressure and temperature effects

Simple models for permeability and selectivity variations of the CO₂/CH₄ system in 6FDA-2,6-DAT membrane have been derived that include both temperature and pressure effects simultaneously in a single equation. The proposed models were used in MATLAB, for a membrane-based CO₂-removal process design for natural gas sweetening. The effects of the following factors on design parameters were examined: feed temperature, feed pressure and permeate pressure. The effect of permeate pressure was found to be very significant in the optimization process. In order to reduce hydrocarbon losses to below 2%, a two-stage membrane process was modeled and simulated in MATLAB, and the extent of desired hydrocarbon recovery was shown to be crucial in the optimization process. It has also been shown that there exist minima for the total required area of the two-stage membrane-based process, and as the CO₂ load increases in the feed, the position of these minima shift to higher values of methane loss.     

Convergence in carbon dioxide emissions and the role of growth and institutions: a parametric and non-parametric analysis

Environmental Economics and Policy Studies - This paper examines convergence of per capita carbon dioxide (CO2) emission for a panel of 124 countries taking into account the impact of economic...