The construction industry of China is characterized by its huge consumption and carbon emissions, thereby making this industry one of the most important areas that require energy conservation efforts. Identifying those factors that affect carbon emissions in the construction industry carries great significance in reducing building carbon emissions, promoting low-carbon cities, and achieving China’s emission reduction goals. This paper firstly reviews the literature on those factors that affect the carbon emissions in the construction industries of developed countries. Second, by using Henan Province as an example, those factors that influence carbon emissions are measured by using the classical STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model. Third, some measures for reducing carbon emissions in the construction industry are developed. Those factors that influence the carbon emissions of buildings are multi-dimensional and diversified. Resident population, urbanization rate, building carbon emission intensity, per capita GDP (Gross Domestic Product), and per capita added value of the tertiary industry all have significant effects on the carbon emissions of buildings in Henan Province. Some policy suggestions can be derived from the findings of this work, such as encouraging building energy conservation, improving the energy efficiency of the construction industry, adjusting the use of building materials, and improving the extant policies for building emission reduction. The results also provide a theoretical basis for identifying those factors that affect the carbon emissions in the construction industry and for formulating and implementing strategies for the low-carbon development of this industry.

In the present study, an assessment of land suitability potential for agriculture in the Koranahalli subwatershed area has been conducted through a close examination of the different indicators of land characteristics and qualities. The objective of this study is to assess the land resource and generate a potential map of the study area. The database on soil resources and land use/land cover data was generated by using remote sensing satellite data and soil survey to perform an integrated analysis in the GIS environment. Fourteen series were identified after detailed soil survey based on the soil characteristics. About 150 soil mapping units were grouped into good and moderate and fairly good cultivable land. Soil site suitability evaluation for different crops revealed that, about 4.36 percent of area is highly suitable for sorghum, followed by 36.92, 35.20, 34.89, 33.60, 31.75 percent and 31.11 percent of area is moderately suitable for chilli, chickpea, ragi, pomegranate, sorghum and sunflower respectively. About 37.44, 31.33, 30.07, 29.81 and 29.76 percent of area is marginally suitable for cultivating tomato, redgram, ragi, sunflower and sorghum or chickpea. However, 30.94, 25.39, 5.89 and 4.95 percent of the area is not suitable for cultivating castor, sapota, pomegranate and redgram or sunflower due to the limitation of soil depth and gravelliness or stoniness.

Nowadays, water pollution is a part of the major environmental problems. Industrial sewage that does not meet the emission standards will pollute the surface water and groundwater when it is discharged into water bodies, causing serious adverse impacts on human beings and environment. In view of industrial sewage privately discharged without properly monitoring, we present a method for detection of sewage discharge using clustering and differential analysis on image sequences derived from satellite photos taken when focusing on a certain place. The proposed method helps to indicate key images containing sewage, make the sewage area and leave evidence for the retrospective incident. Clustering based on the search of fast density peaks is used for detecting images containing sewage. In addition, two sample’s t-test and Fisher linear discriminant analysis are combined to extract the key pixels representing the area of sewage discharge. Experiments were made on 200 images corresponding to a certain area at different times of the day and 25 key frames with areas labelled to be sewage discharge were extracted, which indicated the effectiveness of this method.

China’s transportation industry holds high energy consumption. The energy consumption of China’s transportation industry climbs up gradually with progress in urbanization and growing volume of passenger and freight traffic, which causes heavy environmental pollution. Improving energy efficiency is an important factor and management goal that influences the sustainable development of the transportation industry. In this study, an energy efficiency evaluation system of transportation industry was initially constructed, and the three-stage data envelopment analysis (DEA) model was adopted to estimate the energy efficiency of China’s transportation industry during 2001-2016. Subsequently, environmental variables were introduced to further perfect the calculation results. Results demonstrate that the technical efficiency (TE) of China’s transportation industry is 1 in 6 years during the study period in the traditional DEA model, reaching the technological frontier level. TE still has a large potential for improvement. The input redundancy of energy efficiency in China’s transportation industry may increase as per capita gross domestic product increases. However, such input can be effectively decreased by increasing the total export-import volume and total retail sales of consumer goods. After eliminating environmental and random factors, the low energy efficiency of China’s transportation industry is mainly caused by scale inefficiency. Conclusions in this study can provide theoretical references to understand and improve the energy efficiency of the transportation industry and thus formulate effective transportation energy and environmental policies.

This study aims at detecting the metallothionein protein that binds cadmium in Gambusia fish using MT ELISA kit and Western Blotting testing. The continuation of the detection is used as a basis for analysing the macrophage and pinocytosis activity on Gambusia fish exposed to cadmium. The methods used to detect metallothionein protein are the MT ELISA kit and Western Blotting test. Meanwhile, to check the fish immunity, macrophage cells and pinocytosis activity were tested. The results indicated that the total proteins detected by the method of MT ELISA kits showed an increasing number with concentrations of exposure to Cd good at acute doses and sub-chronic higher doses (treatment A: 0.066 ± 0.019 ng/mL; B: 0.053 ± 0.022 ng/mL; C: 0,045 ± 0,014 ng/mL; D : 0,021 ± 0,012 ng/mL; E : 0,032 ± 0,019 ng/mL; and control k : 0,018 ± 0,018 ng/mL). Similarly, in the pinocytosis activity, the number of macrophage cells between treatment and control was significantly different (Cd ³ 3x106 treatment; Cd ³ 1x106 no treatment) and the number of pinocytosis activity was significantly different (Cd ³ 24 PA treatment; Cd ³ 10 no PA treatment). Increasing pollutants from cadmium exposure affect the fish health. Pollution causes changes in macrophage’s immune cells and phagocytosis Gambusia affinis, which can change the overall innate immunity system and fish health. The change of immune cells associated with the species and biological conditions is not present. Analysis of the number of immune cells revealed that Gambusia has decreased its macrophage pinocytosis activity, thereby indicating that phagocyte activity is a sensitive biomarker and a good bio-indicator for cadmium pollution.

In the present research work, batch adsorption study was carried out to optimize the fluoride removal capacity of guar gum hydrogel beads from aqueous solution. The adsorption capacity was found to be 71.2 mg/g. The FTIR spectrum revealed the presence of functional groups that might be involved in fluoride adsorption. Adsorption of fluoride onto bio-sorbent was investigated as a function of pH, adsorbent dosage and time. The experimental equilibrium sorption data well fitted to the Langmuir mo del and the sorption kinetics for the bio-sorbent was found to follow second order rate expression. The negative values of ΔG° suggest that the sorption of fluoride onto the bio-sorbent was spontaneous and exothermic due to the negative value of ΔH°. The negative ΔS° value for the guar gum was found to be decreasing in randomness at the solid-liquid intersection.

In this study, the structural characteristics of the attached microbial community during biofilm formation and the metabolic requirements under anaerobic conditions were evaluated. In particular, 16S rDNA sequencing technology was used to study the structural changes of the attached microbial community during biofilm formation (day 0, 10, 20, and 30) in an aquaculture system, and Biolog microplate technology was used to study metabolic characteristics under anaerobic conditions during biofilm formation. The AWCD (average well colour development), an indicator of carbon metabolism, of attached microorganisms during biofilm formation under anaerobic conditions differed significantly among time points (P < 0.05), and the carbon source utilization capacity was enhanced. Under anaerobic conditions during biofilm formation, the utilization of amines in six major carbon sources was the highest, followed by polymers, carbohydrates, amino acids, and carboxylic acids, and the utilization of phenols was the lowest. Under anaerobic conditions, the utilization rate by the attached microorganisms during biofilm formation was highest for Tween 40, followed by Tween 80, D-xylose, 4-hydroxybenzoic acid, α-D-glucose-1-phosphate, L-phenylalanine, and phenylethylamine. The 16s rDNA sequencing results showed that the dominant phyla of attached microorganisms during biofilm formation were mainly Proteobacteria, Bacteroidetes, Firmicutes, and Cyanobacteria. On the 10th and 20th days of biofilm formation, attached microorganisms were enriched for Rhodobacter of α-Proteobacteria and Janthinobacterium of β-Proteobacteria, which play important roles in biofilm denitrification. However, on the 30th day, enriched bacteria included the Burkholderiales of β-Proteobacteria, the Xanthomonadaceae and Thermomonas of γ- Proteobacteria, which function in cyanide decomposition.

The Tha Chin River is a branch river of the Chaophraya River, which is one of the four main rivers in the central area of Thailand. Currently, the Tha Chin River is experiencing serious problems regarding water quality. Our study was carried out to analyse the river quality status, classify the health of the river according to Water Quality Index (WQI) and assess the riverbank community’s understanding of the Tha Chin River water quality. The results indicated that the water quality in the estuary of the Tha Chin River has been seriously polluted. In addition, the results also found that the WQI of the wet period was significantly lower than that of the dry period at p-value < 0.05. While the results from the riverbank community’s understanding assessment revealed that they feel the water quality in this river is still good, especially in the upstream and the midstream. Therefore, the assessed water quality according to WQI method showed that the riverbank community had a misunderstanding of the water quality of the Tha Chin River.

A composite adsorbent was prepared by montmorillonite and biochar from peanut shell. The adsorption experiment of the Cu2+ ions from aqueous solution by the montmorillonite-biochar composite was carried out in detail. The effects of initial concentration of Cu2+ ions in aqueous solution and contact time on adsorption efficiency were studied. FTIR spectroscopy, SEM and TEM analyses, standard N2 adsorption-desorption techniques, EDS and XPS were used to evaluate the physico-chemical, textural and crystalline properties of the montmorillonite-biochar composite. Results showed that the montmorillonite-biochar composite was mesoporous material. The surface of montmorillonite-biochar composite was rough with irregular layer structure. According to the experimental data, pseudo first order kinetics model and pseudo second order kinetics model were applied. The adsorption process fits well with the pseudo second order kinetics model. The predominant process is chemisorption, which involves a sharing of electrons between the adsorbate and the surface of the adsorbent. Adsorption data were correlated well by Freundlich isotherm models and adsorption process was chemical. It is concluded that the montmorillonite-biochar composite can be used as an effective adsorbent for the removal of Cu2+ ions from aqueous solutions.

The assessment of forest site quality at early stages of stand development is very essential for scientific afforestation and forest management. In order to enhance the accuracy of the existing models, a new site quality assessment model based on Genetic Algorithm-Radial Basis Function (GA-RBF) was proposed to predict site index (stand dominant height). Data used in this study came from 980 permanent sample plots for Chinese fir (Cunninghamia lanceolata) plantations in Fujian Province, China, which were randomly divided into the training dataset (786 plots) and the testing dataset (194 plots) with a ratio of 8:2. In this paper, the GA-RBF was compared with the radial basis function (RBF) and the traditional Quantitative Theory I (QT-I) method. The results indicated that the predicted accuracy was significantly increased by using the GA-RBF model. Furthermore, we used the existing site-specific site index table of Chinese fir to test the results of the GA-RBF and the agreement was 73.2%. Therefore, we recommend the GA-RBF for assessing site quality of afforestation land.