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.

Soil microorganisms play a crucial role in nutrient availability and overall soil health. However, the effects that biochar has on soil microbial communities are not well understood. This study analysed the effects of biochar pyrolysis temperature and application rate on the soil microbial community of loess. Two biochars derived from soybean stover were produced at 300 and 600°C (BC300 and BC600, respectively) and were applied to loess at the rates of 1, 3, and 5% (w/w). After fifteen weeks of incubation, soil microbial analysis was performed using 16S rDNA amplicon sequencing technology. All of the BC300 and BC600 treated soils were shown to have an increase in the relative abundance of Gemmatimonadetes and a decrease in Actinobacteria and Chloroflexi. Proteobacteria also showed a significant increase in the majority of the biochar treated soils. Biochar led to a shift in the soil microbial community and caused a significant increase in the relative abundance of bacteria from the genus Lysobacter. Based on the results of this study, soybean stover-derived biochar should be considered as a potential soil amendment for improving the health of loess or other soils in semi-arid climates.

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.

An investigation of 43 soil samples and their corresponding wheat samples collected from Qinan (QN) and Luling (LL) coal mining areas in Suzhou, China, was conducted to study the accumulation of heavy metals (Cu, Pb, Zn, Cd, Cr and Ni) in the soil-wheat system, and to evaluate the potential human health risk posed by heavy metals from long-term ingestion of local wheat. Results showed that Cu, Zn, Cd and Ni were accumulated in the soils from the two mining areas, higher proportions of all the investigated metals in residual fraction were recorded, while large amounts of Cd, Cu, Zn, Pb were also observed in the bioavailable or potential bioavailable fractions. Metal contents in the different parts of wheat mainly followed the order of Root>Stem>Grain. The trends of Bioaccumulation factor (BF) and Translocation factor (TF) values were Zn>Cd>Cu>Ni>Pb>Cr and Cu>Cd>Zn>Cr>Pb>Ni, respectively. Correlation analysis suggested that the accumulated metals in the grain were mainly supplied from exchangeable and carbonate bound fractions in soil. Since the health risk posed by heavy metals ingestion was very close to the maximum allowable limit, the safety of wheat consumption in the coal mining areas should be continually concerned.

The transportation industry is the fundamental and strategic industry for social and economic development. However, this industry becomes a considerable barrier against green, sound, and sustainable economic and social development due to the rapid increase in energy consumption and greenhouse gas emission. Transportation industry becomes one of weakness of energy saving and emission reduction with its increasing energy consumption and carbon emission. Environmental pollution caused by the transportation industry can be relieved effectively by increasing energy efficiency. A case study based on Jilin Province, China is carried out. First, environmental pollution types caused by regional transportation industry are analysed. Second, energy efficiency of transportation industry in eight prefecture-level cities in Jilin Province from 2011 to 2017 is determined using the DEA-Malmquist index. Finally, measures to control environmental pollution caused by the transportation industry are proposed. Results show that in Jilin Province, environmental pollution caused by the transportation industry manifests through increasing energy consumption, pollution from car exhaust, and degree of traffic jams. In its eight prefecture-level cities, the average energy efficiency change index of transportation industry is 1.054, which is higher than 1. The means of technological efficiency and progress are 0.973 and 1.084, respectively. The mean pure technological efficiency of energy use slightly increases, while the mean scale efficiency decreases significantly. Results can provide beneficial references for full understanding on energy consumption and environmental emission of transportation industry in Jilin Province. This understanding can lead to the exploration of scientific and reasonable energy-saving and emission-reduction ways and countermeasures, aiming to offer decision-making references for energy saving and emission reduction of the transportation industry in Jilin Province.

Online UV-Vis spectrophotometer technology as accurate, convenient and fast monitoring method was used to detect instantaneous dye concentration in aqueous medium. Ferrous ion coupling with Persulphate to degrade methylene blue (MB) exhibited a very high degradation rate, and therefore online UV-Vis spectrophotometer showed great advantage in this study. The effects of ferrous ion concentration, sodium Persulphate concentration, pH value and initial MB concentration on MB degradation were investigated. The online spectrophotometer could minimize the systematic error caused by the termination of adding chemicals and manual operation. At room temperature, the optimal condition was acquired with 73.6% MB removal after 100s at neutral medium when initial ferrous dosage and sodium Persulphate were 1.25 mmol/L and 0.2 mmol/L, respectively. Fe2+/S2O8 2- system exhibited a great degradation efficiency in acidic or neutral environment.

Mycoremediation, involving the use of fungus for bioremediation, is one of the promising cost-effective methods for cleaning up the carcinogenic and mutagenic polycyclic aromatic hydrocarbons present in the environment. The present study deals with the isolation of white rot fungus from Chhattisgarh forest, India followed by identification based on ITS sequencing. Identification revealed MP 5 closely related to Pleurotus ostreatus isolate 6689 with 99% sequence similarity. Comparative primary screening assay of both the wild isolate and reference strain of Pleurotus ostreatus MTCC 1804 was performed by measuring the growth diameter of mycelia on minimal salt media enriched with 2% used engine oil (v/v). The fungal isolate MP 5 showed highest average growth rate. Confirmatory test was conducted via orbital shaking method and spectroscopic study was carried out at 600 nm which displayed degradation within 7 days and percentage of degradation was calculated. Level of degradation was 69.7 ± 0.351% and 64.7 ± 1.153% respectively for Pleurotus ostreatus MP 5 and Pleurotus ostreatus MTCC 1804. Degradation potential of both the isolates was evaluated in terms of chemical characterization via Fourier transform infrared spectroscopy (FTIR) which revealed bands formation based on the presence of different functional groups indicating oxidative degradation of hydrocarbons.

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.

To study the variations in microorganisms and enzyme activity during sewage sludge composting, the dynamic changes in temperature, enzyme activity and microorganism composition were studied by co-composting municipal sludge and corn straw. The results show that the pile underwent mesophilic, thermophilic, and cooling phases and that the high-temperature duration (³ 50 °C) had reached 5 days, which meets harmlessness requirements. During the composting process, the protease, arylsulfatase (ARS) and cellulase content increased gradually; urease content first decreased and then increased rapidly; and peroxidase (POD) content first increased and then decreased. Ureibacillus, Bacillus, Pseudomonas, Flavobacterium and Sporosarcina were the dominant bacteria during sludge composting. Microorganisms played different roles at different stages of the composting. Ureibacillus and Bacillus were the dominant strains in the mesophilic and thermophilic phases, respectively, and Pseudomonas and Flavobacterium were the dominant strains in the cooling phase. Sporosarcina mainly played a role later in the thermophilic and cooling phases. The effect of different bacteria on enzyme activity varied; Pseudomonas played a clear role in promoting the production of urease while Bacillus had a clear inhibitory effect on the production of urease. Ureibacillus inhibited the production of ARS, POD, protease and cellulase. By studying the changes in microbial and enzymatic activities at different stages of sludge composting, it is possible to thoroughly explore the nature of the latter and provide a reference for optimizing composting processes.

The rapid development of information technology has promoted the transformation of the manufacturing industry and the upgrading of Chinese intelligent manufacturing enterprises. Environmental protection and enterprise benefits have become the pursuit target. To explore the impact of environmental investment on the performance of intelligent manufacturing enterprises, an evaluation index system from the four dimensions of debt paying, operation, profitability, and growth ability was constructed. Then, factor analysis method was used to analyse the index data of 33 intelligent manufacturing enterprises in the Yangtze River Delta in 2018, and a multiple regression model was constructed to analyse the impact of environmental investment on enterprise performance. Results show a significant difference in the performance of intelligent manufacturing enterprises in the Yangtze River Delta and a positive correlation between environmental investment and enterprise performance. Finally, specific optimization measures are given to help the managers of intelligent manufacturing enterprises make scientific and reasonable decisions.