River ecosystem is one of the most important ecosystems, and it provides many ecosystem services for human beings. However, river health has also been damaged by over-exploitation and water pollution. In the process of reservoir operation, the ecological flow demand of rivers should be fully considered and multi-objective ecological dispatch of reservoirs should be implemented. On basis of the traditional particle swarm optimization (PSO), the improved PSO with adaptive random inertia weights (ARIW) is proposed to deal with the problem of ecological optimal operation of the reservoir in the paper. According to the evolutionary process, based on the probability distribution density function of triangle, the inertia weight can be adjusted randomly and adaptively to meet the global or local optimization requirements. By typical mathematical function, the improved PSO algorithm is compared with traditional PSO and genetic algorithm (GA) and is proved to be more efficient and accurate. Taking Panjiakou Reservoir on the mainstream of Luanhe River in China as an example, the multi-objective ecological optimal dispatch of the reservoir has been analysed and calculated with the improved PSO algorithm under different targets years, considering flood control, water supply, and ecological demand. The research results can provide reference for developing rationally Luanhe River water resources, and making scientifically ecological dispatch plan of the Panjiakou reservoir.

Metal contamination of sediment of Ganges River (Northwestern Bangladesh) and its possible health risk to the local people were evaluated at four different sites during three seasons (summer, monsoon, winter) in the year 2016. Followed by wet digestion, the samples were analysed by Flame Atomic Absorption Spectrophotometer. Mean concentration of Cr, Pb, Ni, Cd, Mn, As, Cu and Zn were 9.31, 6.43, 0.19, 1.90, 61.66, 0.65, 9.33 and 16.14 mg/kg, respectively. According to metal indices (contamination factor, contamination degree and pollution load index), the sediment was low to moderately contaminated with the studied metals, while human health risk assessment indicated unacceptable risk (hazard index (HI) values > 1) for non-carcinogenic adverse health effect. Therefore, the sediment of the river was not contaminated enough to prevail high risk on ecological health of river and to pose health risk on local people, but regular practice of discharging contaminants can somehow worsen the river quality in the coming years.

This study focuses on the removal of organic dyes, such as Malachite Green (MG) and Rhodamine-B (Rh-B) from an aqueous solution with the help of a novel adsorbent (activated carbon) with magnetic property prepared by used disposal paper cups (AC@PC) at 500°C. The synthesized AC@PC adsorbent was characterized by using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), Energy dispersive X-ray spectroscopy (EDS) and point of zero charge (pHZPC). Adsorption of MG and Rh-B onto the AC@PC adsorbent from aqueous solution was investigated systematically. Langmuir, Freundlich and Temkin isotherms were also studied, however, it has been observed that Langmuir isotherm model was best fitted for both the dyes, which describe the adsorption behaviour at equilibrium. Pseudo-first and pseudo-second order kinetic model describe the rate of adsorption. Kinetic study explained that the process of adsorption followed the pseudo-second order model. Thermodynamic parameters such as enthalpy (?H°), entropy (?S°) and Gibb’s free energy (?G°) were also studied and revealed that the adsorption of MG was endothermic, whereas adsorption of Rh-B was exothermic onto the AC@PC. The prepared adsorbent shows potentially high adsorption properties for both the dyes.

Weight loss method was used to assess the inhibition of mild steel corrosion in 1M HCl solution with aqueous extract of Ziziphus jujuba leaves at 303 to 333K temperatures. It was found that Ziziphus jujuba leaves extract retarded the dissolution of mild steel in 1M HCl solution. The inhibition efficiency increases with a rise in the concentration of extract and decreases with increase in temperature. Maximum 88.54% inhibition efficiency was observed at 303 K and 8% (v/v) composition of the extract. Adsorption of extract at mild steel surface follows Langmuir adsorption isotherm. Values of Gibbs free energy, variation in inhibition energy with temperature and with activation energy values trend proposed the physisorption. Negative values of Gibbs energy propose the spontaneous process of inhibition process in the extract at studied temperatures.

Most urgent transport related problems in India are traffic congestion and concomitant air pollutant emissions. During traffic flow, the common causes of congestion in urban centres are pedestrian interruption, unregulated traffic signals, unregulated bus stoppages, and unauthorized roadside parking, which together, particularly during peak hours, create erratic traffic pattern causing higher emissions. In this study, we characterized auto-rickshaw driving dynamics by instantaneous measurements of speed and emission at different times of the day. Traffic speed is an important factor that is perceived by commuters. The speed variables and traffic volume are used as a base variable to examine the traffic flow patterns. The speed variables such as average speed (AS), velocity noise (VN, standard deviation of speed), and the coefficient of variation of speed (CV, the ratio of VN and AS) were examined with respect to traffic volume. The polynomial fit of CV shows three distinct zones of variations with increasing traffic volume, explaining the dynamics of traffic flow. Further, time, speed and mileage variable were investigated for the emission rate analysis in different traffic flow pattern. The analysis depicted that the combined factor of lower speed (speed ?12 km/h) and higher time of travel in correspondence cause higher emission rate. Similarly, vehicle mileage of ?52,000 km has significant impact on emission for pollutants CO, HC and NOx. The results provide real-time information on traffic flow characteristics and impacts of dynamic and age variables on emission rate in on-road driving conditions, which may be useful for the public and transport related agencies.

With the rapid development of urbanization, the Chinese construction industry has generated a large quantity of carbon emission and brought about challenges to sustainable development while making enormous contributions to national economic development. Thus, this industry is the key field of energy conservation and emission reduction. Facilitating sustainable development of the construction industry and scientifically and reasonably evaluating the carbon emission efficiency of the construction industry will be important for effectively controlling carbon emission and boosting the sustainable development of the construction industry. Carbon emission was added into the total-factor productivity model of the traditional construction industry as an environmental factor in this study, and a total-factor evaluation model for the carbon emission efficiency of the construction industry was constructed. Henan Province was taken as an example, and empirical analysis was conducted to determine the differences of Henan construction industry in the period of 2012-2018 in the aspect of carbon emission efficiency. Results showed that the total-factor carbon emission efficiency of Henan construction industry in the period of 2012–2018 was 1.084%, which indicated a certain increase in the total-factor emission efficiency of Henan construction industry over the 7 years. The overall resource utilization efficiency of Henan construction industry was improved by 0.84% due to the joint actions of elevated technological progress (by 0.35%) and improved technical efficiency (by 0.47%). Average pure technical efficiency was slightly reduced by 0.03%, which indicated that building scale was the driving force for improving the total-factor efficiency of the construction industry. The study results can provide systematic and comprehensive carbon emission information in the construction industry for policy making. Therefore, the carbon emission status of the construction industry in one province can be mastered from a provincial level to clarify responsibilities, facilitate coordinated development, and boost the efficiency and equity of emission reduction in the construction industry. This way will be important for finally realizing the goals of energy conservation, emission reduction, and low-carbon development.

In the present study, artificial neural network (ANN) and response surface methodology (RSM) models were used to investigate the heterogeneous photocatalysis performance in removal of chemical oxygen demand (COD) from landfill leachate using compound parabolic collector. Effect of the three parameters, i.e. pH, catalyst dosage, and irradiation time was studied for COD removal efficiency and these parameters are optimized by the RSM. The optimum values of pH 5, the dosage of 0.75 g/L and irradiation time of 100 minutes are capable to remove 32.19% of COD from the leachate. A good agreement is shown by the analysis of variance for the regression coefficient R2 for predicted value (0.92268) and adjusted value (0.9776). The proposed RSM and ANN model R2 values were found to be 0.9882 and 0.9974 respectively, which confirms the ideality of RSM and ANN. The results also confirm that the input and output data from RSM could be appropriate to build the ANN model. Further BOD5/COD ratio is studied for the biodegradability of leachate and it was found that increase of biodegradability value from 0.17 to 0.47 was at pH 3, catalyst dosage of 1 g/L and irradiation time of 150 minutes.

Increased water pollution due to toxic heavy metals is becoming a serious threat that has been faced by the entire world in the last few decades. To overcome this problem a suitable complex ligand was designed for removal of Fe3+, Cd2+, Pb2+ and Zn2+ from the effluents. The work incorporated the synthesis of (4Z)-4-((2Z)-2-(2,5-dihydro-2,3-dimethyl-5-oxo-1-phenyl-1H-pyrazol-4-ylimino) ethylidene amino)-1,2- dihydro-1,5-dimethyl-2-phenylpyrazol-3-one (Supramolecular Ligand) by the condensation method and confirmed by FTIR and 1HNMR spectroscopic methods. The batch extraction experiments designed to examine the effect of various experimental parameters on the extraction efficiency of heavy metals. The experimental results depicted that up to 30 min time for supramolecular ligand is enough for the significant extraction of all the metals under study. The pH level, slightly acidic to the neutral condition is favourable for maximum extraction of metals. The percent extraction at optimized conditions of time and pH were found to be 98.29, 96.63, 96.95 and 95.64% for Fe3+, Cd2+, Pb2+ and Zn2+ respectively. The extraction efficiency was governed by chloroform as a solvent. Simple to synthesize, faster extraction of metals, slightly acidic to neutral pH conditions for extraction are the characteristic features of the compound which governs its applicability.

In the present global scenario, fossil fuels are facing challenges due to escalating costs, increasing demand and impact on environmental pollution. In internal combustion engines, the emission characteristics and economy of the fuel are controlled by the chemical and physical properties of the fuel. Various additives are being used to act like catalysts with the fuels to improve quality of fuel, to obtain better combustion and to reduce exhaust emissions. At the time of combustion process, fuel instability reactions get accelerated by the catalysts which improve the performance of the engine. In this study, the B10, B15 and B20 fuel blends of cotton seed oil and diesel were mixed with the carbon nanotubes (CNTs) as an additive to analyse the performance and exhaust emissions of a CI engine. The carbon nanotubes were mixed with each fuel blend with the concentration of 50 ppm. All the tests were carried out for different engine loads. Tested characteristics were power, brake thermal efficiency (BTE), specific fuel consumption (SFC), and analysis of exhaust gases like hydrocarbons (HC), CO2, CO, and smoke. The experimental results showed that there was significant reduction of SFC and improved combustion by addition of CNTs. It was also observed that the exhaust emissions, CO, HC, and smoke percentage got decreased by the influence of CNTs.

The contradiction between supply and demand of resource environment has become increasingly severe because of population expansion and the rapid development of industrial economy. Spatial quantitative evaluation of coupling strength and mutual promotion between industrialization and resource environmental bearing capacity based on panel data can facilitate industrialization and promote sustainable and healthy development of regional economy objectively, scientifically, and rationally. This study proposed a three-level comprehensive evaluation matrix for clustering and comparative analysis of 31 provinces in China to analyse the characteristics of spatial heterogeneity in the coordinated development of industrialization and resource environmental bearing capacity. First, a comprehensive evaluation index system for resource environmental bearing capacity was established based on the differences in resource environmental bearing capacities in various regions of China. Combined with the coordination degree for the evaluation model, the coordination between the resource environmental bearing capacity and the industrialization of the 31 provinces in 2018 was evaluated and compared based on their comprehensive evaluation index. Finally, a cluster comparison analysis was performed in the 31 provinces using the three-level comprehensive evaluation matrix of coupling development of regional economy and resource environmental bearing capacity. Moreover, the accuracy of the coordination degree model was verified according to the clustering results. Results show that the regions with good ordination between industrialization and resource environmental bearing capacity include East and North China. Meanwhile, the provinces with poor coordination mainly include Southwest and Northwest China. The resource environment still restricts the coordination between resource environmental bearing capacity and industrialization development. This study provides a reference for developing differentiated resource environment management measures and countermeasures in various regions in China.