Porous material based on modified carbon and the effect of pore size distribution on the adsorption of methylene blue dye from an aqueous solution

Environmental Science and Pollution Research - Carbon porous materials obtained through KOH activation of a furfural?+?hydroquinone?+?urotropine mixture were applied as...     

Impact of riverbank filtration on treatment of polluted river water

The impact of riverbank filtration (RBF) on the treatment of water from the River Yamuna at Mathura, which has disagreeable visual properties, has been investigated. The dissolved organic carbon (DOC) and colour of the river water were 4.0–6.8 mg/L and 40–65 colour units (CU), respectively. Pre-chlorination is in practice to improve raw water quality. Chlorine doses as high as 60 mg/L ahead of the water treatment units reduced colour by about 78%. Removal of DOC and UV-absorbance was less than 18%. In comparison to direct pumping of the river water, collection of water through RBF resulted in the reduction of DOC, colour, UV-absorbance and fecal coliforms by around 50%. However, riverbank filtrate did not conform to the drinking water quality standards. Therefore, riverbank-filtered water along with the Yamuna water were ozonated for different durations. To reduce DOC to the desired level, the dose of ozone required for the riverbank filtrate was found to be considerably less than the ozone required for the river water. RBF as compared to direct pumping of Yamuna water appears to be effective in improving the quality of the raw water.     

Utilization of molasses spentwash for production of bioplastics by waste activated sludge

Present study describes the treatment of molasses spentwash and its use as a potential low cost substrate for production of biopolymer polyhydroxybutyrate (PHB) by waste activated sludge. Fluorescence microscopy revealed the presence of PHB granules in sludge biomass which was further confirmed by fourier transform-infra-red spectroscopy (FT-IR) and ¹³C nuclear magnetic resonance (NMR). The processing of molasses spentwash was carried out for attaining different ratios of carbon and nitrogen (C:N). Highest chemical oxygen demand (COD) removal and PHB accumulation of 60% and 31% respectively was achieved with raw molasses spentwash containing inorganic nitrogen (C:N ratio = 28) followed by COD removal of 52% and PHB accumulation of 28% for filtered molasses containing inorganic nitrogen (C:N ratio = 29). PHB production yield (Y_p/s) was highest (0.184 g g^?1 COD consumed) for deproteinized spentwash supplemented with nitrogen. In contrast, the substrate consumption and product formation were higher in case of raw spentwash. Though COD removal was lowest from deproteinized spentwash, evaluation of kinetic parameters suggested higher rates of conversion of available carbon to biomass and PHB. Thus the process provided dual benefit of conversion of two wastes viz. waste activated sludge and molasses spentwash into value-added product-PHB.     

Co-composting of green waste and food waste at low C/N ratio

In this study, co-composting of food waste and green waste at low initial carbon to nitrogen (C/N) ratios was investigated using an in-vessel lab-scale composting reactor. The central composite design (CCD) and response surface method (RSM) were applied to obtain the optimal operating conditions over a range of preselected moisture contents (45–75%) and C/N ratios (13.9–19.6). The results indicate that the optimal moisture content for co-composting of food waste and green waste is 60%, and the substrate at a C/N ratio of 19.6 can be decomposed effectively to reduce 33% of total volatile solids (TVS) in 12 days. The TVS reduction can be modeled by using a second-order equation with a good fit. In addition, the compost passes the standard germination index of white radish seed indicating that it can be used as soil amendment.     

How Should Support for Climate-Friendly Technologies Be Designed?

Stabilizing global greenhouse gas concentrations at levels to avoid significant climate risks will require massive “decarbonization” of all the major economies over the next few decades, in addition to the reduced emissions from other GHGs and carbon sequestration. Achieving the necessary scale of emissions reductions will require a multifaceted policy effort to support a broad array of technological and behavioral changes. Change on this scale will require sound, well-thought-out strategies. In this article, we outline some core principles, drawn from recent social science research, for guiding the design of clean technology policies, with a focus on energy. The market should be encouraged to make good choices: pricing carbon emissions and other environmental damage, removing distorting subsidies and barriers to competition, and supporting RD&D broadly. More specific policies are required to address particular market failures and barriers. For those technologies identified as being particularly desirable, some narrower RD&D policies are available.     

Radon level in dwellings and its correlation with uranium and radium content in some areas of Himachal Pradesh,India

LR- 115 plastic track detectors have been used to measure indoor radon level in some dwellings of Una district, Himachal Pradesh, India. The annual average radon concentration in dwellings in most of the villages falls in the range of the action level recommended by the International Commission on Radiological Protection. The radon values in some of the dwellings exceed the action level and may be unsafe from the health hazard point of view. The indoor radon values are in general higher in winter than in summer. Uranium, radium and radon exhalation studies have also been carried out in soil samples collected from these areas. A good correlation is obtained between uranium concentration in the soil and indoor radon in dwellings. The soil radon exhalation rate also correlates with the uranium concentration in soil.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

Natural gas engine driven heat pump system – a case study of an office building

ABSTRACT

An eQUEST model was developed to conduct a simulation study of a natural gas engine-driven heat pump (GEHP) for an office building in Woodstock, Ontario, Canada. Prior to the installation of the GEHP, the heating and cooling demands of the office building were provided by rooftop units (RTUs), comprising of natural gas heater and electric air conditioner. Energy consumption for both GEHP and RTUs were monitored for operation in alternating months. These recorded energy consumptions along with weather data were used in the regression analysis. The developed eQUEST models were validated and calibrated with the regression analysis results with respect to the ASHRAE Guideline 14–2014. The eventual models were then applied to investigate the potential annual energy consumption, greenhouse gas (GHG) emission and energy cost savings achieved by using the GEHP in Woodstock, and other cities in Canada, particularly in Ontario.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.