Input–output analysis in an oil-rich economy: The case of Azerbaijan

This paper aims to provide empirical research to identify the linkages between final demand–total output, final demand–total supply, value-added ratios and prices, and also to analyze total factor productivity growth using input–output framework for 25 sectors. Studying the input–output tables for 2001 and 2006, the research estimates impact and response multipliers of non-oil sectors, as well as non-oil trading sectors. The results are important from the view of development of non-oil trading sectors and diversification of the economy in order to avoid the “resource curse”.     

Can clean biomass energy use lower CO2 emissions in African economies? Empirical evidence from dynamic long-run panel framework

Environmental Science and Pollution Research - This paper seeks to answer an empirical question of whether clean biomass energy consumption lowers CO2 emissions while controlling for technical...     

An environmental forensic investigation at a bio-medical waste treatment and disposal facility in Kerala,India

Indian statutes identify twelve different types of biomedical wastes and give the treatment and disposal options for each. Since it is not possible for every generator of biomedical waste to go for their own treatment and disposal facility, the small-scale generators take the service of centralized treatment and disposal facilities available to them on payment. In the state of Kerala in India, where the basic health indicators match those of many developed countries, the centralized biomedical waste treatment facility is run by Indian Medical Association (IMA), Kerala, under the banner IMAGE (IMA Goes Eco-Friendly) at a place called “Kanjikode” in the Palakkad District. The facility receives biomedical waste from around 4500 hospitals across the State and an equal number of medical laboratories. The plant incinerates the incinerable waste and the other kind of waste are disinfected and decontaminated. The residual ash and dried sludge are then moved to the landfill area. Recently, the facility was in the middle of a controversy due to the alleged health hazards it posed to the surrounding population. An environmental forensic investigation was carried out at the site to establish the merits of the allegation. The reported study is a part of the investigation where groundwater was analysed for the presence of heavy metals. As the biomedical waste contain heavy metals like Zn, Pb, Cd, Cr, and Hg, the presence of these were analysed to establish contamination of groundwater by the facility. The study area is bounded by Malampuzha dam and Korayar river. Groundwater contaminant transport modelling was done for a 3430 m × 3960 m area surrounding the waste treatment facility using Visual MODFLOW and MODPATH. Ground water flow direction and particle pathlines were computed to track the movement of contaminants. Groundwater samples were collected from the area shown to be polluted by the model, if metals were discharged by the facility, and also from outside this area. Water samples were collected conforming to the guidelines in the “Pollution Crime Forensic Investigation Manual” published by INTERPOL. The collected water samples were tested for heavy metal concentration using atomic absorption spectroscopy (AAS). The water sample analysis showed that the groundwater is not contaminated by heavy metal discharge from the biomedical treatment facility.     

Incorporation of sewage sludge in clay brick and its characterization.

This study reports the use of sewage sludge generated from sewage treatment plant (STP) as raw material in a clay brick-making process. The physico-chemical and mineralogical characterization of the sewage sludge and clay were carried out in order to identify the major technological constraints and to define the sludge pretreatment requirements if necessary. Moreover, the effects on processing conditions and/or on changes of typical final characteristics are also evaluated. Bricks were produced with sewage sludge additions ranging from 10 to 40% by dry weight. The texture and finishing of the surface of sludge-amended clay bricks were rather poor. As for the physical and chemical properties, bricks with a sludge content of up to 40 wt.% were capable of meeting the relevant technical standards. However, bricks with more than 30 wt.% sludge addition are not recommended for use since they are brittle and easily broken even when handled gently. A tendency for a general degradation of brick properties with sludge additions was observed due to its refractory nature. Therefore, sludge bricks of this nature are only suitable for use as common bricks, which are normally not exposed to view, because of poor surface finishing.     

The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R² were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R² confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.     

Health risk assessment of drinking arsenic-containing groundwater in Hasilpur,Pakistan: effect of sampling area,depth, and source

Environmental Science and Pollution Research - Currently, several news channels and research publications have highlighted the dilemma of arsenic (As)-contaminated groundwater in Pakistan. However,...     

Numerical investigation of geometrical defect in cold forging of an AUV blade pin head

The precision of cold forging parts becomes critical because the process depends on many factors such as the size and complexity of the parts. Defects negatively affect the assembly accuracy and the performance of the parts. Therefore, defects must be detected and prevented as soon as possible before the manufacturing process begins. The paper intends to investigate the geometrical defect of the cold embossing pin head, which may result in an inaccurate assembly of the blade. In this paper, defect formation was studied using DEFORM-2D based on material flow pattern and stress distribution. The defect was measured in terms of incomplete filling and geometries of the bulging. The effect of the distance to the edge (DTE) is significant to the formation of defects. The size of the bulge is reduced and the filling ability shows better performance as the DTE increases. The FE results are in good agreement with the experimental result.     

Impact of financial development and technological innovation on the volatility of green growth—evidence from China

Environmental Science and Pollution Research - China’s green growth has shown a trend of fluctuation year by year. Simultaneously, Chinese local governments have pursued simple economic...