The present study is based on the conversion from biomass to biofuels of karanja (Pongamia glabra) seeds via solar thermochemical pyrolysis process. Karanja seeds were pyrolysed at a cavity type reactor temperature of 280-340°C. The pyrolysis process was occurring in the range of 210-550°C. The ultimate and proximate analysis of the pyrolysed bio-oil was performed based on ASTM standards. The FTIR (Fourier transform infrared spectroscopy) analysis of the liquid product indicated the presence of alkenes, alkanes, ketones, carboxylic acids and aromatic rings. GC-MS (gas chromatography-mass spectrometry) demonstrated the presence of hydrocarbons having between 15 and 34 carbon atoms in a chain.

The cell-phone radiation is a potential health hazard not only to the singular user but to the whole population through the environmental pollution. The environmental radiation density may vary from place to place depending upon its absorption or reflection by surroundings, e.g., trees, buildings, human population, water bodies, etc. The present work was taken to study the effect of population density and surroundings on the environmental radiation. The power density values of radiation were measured using a hand-held portable power density meter TES 593, and specific absorption rates (SAR) were estimated from the measured values. The SAR values were compared with the safe limit of 1 mW/kg above which biological system of humans and animals starts getting affected. The studies indicated that the average environmental radiation power density values were higher in unpopulated and open areas than densely populated regions by 300%.

Mango seed kernel, a byproduct of the mango processing industry, is known to be a rich source of phenolic compounds. Phenolic compounds are bioactive in nature and highly valuable due to a number of potential health and therapeutic benefits making it a good component in functional food formulations and for the nutraceutical industry. Through spray drying, the bioactive fraction from an industrial waste mango seed kernel extract was recovered through encapsulation using maltodextrin (MD), gum Arabic (GA), and starch (ST) as encapsulating agents. The encapsulating agent type used alongside inlet drying air temperature was varied and observed to have an influence on encapsulation yield and on the powder qualities measured such as total phenolic content, antioxidant activity, moisture content, bulk density and water solubility index. Among the encapsulating agents used, MD was found to be the most desirable encapsulating material with regards to the desirable properties of spray-dried powders in terms of functionality and applicability.

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.

The major and overriding factors affecting water quality and the aquatic ecosystems in the coastal areas are sewage and nutrient inputs from municipal and industrial wastewater, depletion of seaside contrivances, risks of public health as well as loss of biodiversity. The coastal area of the Karachi harbour is most heavily polluted due to these reasons. In this study, we proposed the artificial neural network (ANN) models to monitor and control the sea surface water quality of the Karachi coastal area along the harbour. Recently, various types of ANN have been successfully applied in hydrological fields. In this study, Nonlinear Auto Regressive eXogenous Neural Network (NARX-NN) shall be applied to predict the concentration of heavy metals in coastal sea surface water of the Karachi harbour area. This method provides significant insight into the comparative study of two different training functions of NARX-NN, namely, Levenberg-Marquardt (LM) and Scale Conjugate Gradient (SCG). The physical parameters like sea surface temperature (SST), salinity, tides and pH are taken as an input and the chemical parameters chromium, copper, lead, nickel and zinc are taken as output individually for all six locations. The performance of the model was evaluated by statistical criteria that include a correlation coefficient (r) and mean square error (MSE). The prediction results indicated that the LM training function is superior to SCG training function. Hope this study is helpful for local authorities and policy makers to develop a new infrastructure and install a water treatment plant to reduce the water pollution of the harbour area.

Civil buildings are among the structures that consume the most energy in society. Reducing the energy consumption of civil buildings has become an important component of China’s energy policy. Identifying the key influencing factors of the energy consumption of civil buildings and formulating effective energy-saving countermeasures are important to enhance the energy efficiency of civil buildings. This study conducted a systematic analysis of the influencing factors of the energy consumption of civil buildings in Hubei Province, China. First, existing studies on the influencing factors of the energy consumption of buildings in foreign developed countries were reviewed. The status of the population, economic life, and social life that influenced the energy consumption of civil buildings in Hubei Province in the past 10 years was summarized. Relevant influencing factors were estimated via ridge regression. Results demonstrated that developed countries generally investigated the influencing factors of the energy consumption of civil buildings from the energy supply-demand relation, family factors, and out-of-family factors. Gross domestic product (GDP), total population, tertiary industry development, per capita floor space, household consumption level, and urbanization facilitated the energy consumption of civil buildings in Hubei Province during the aforementioned period, and the regression coefficients were significant at the 5% level. Lastly, policy countermeasures were proposed to accelerate the energy-saving development of civil buildings. Research conclusions are important to enrich theories regarding the energy consumption reduction of civil buildings, to help relevant government sectors of Hubei Province recognize action points for the energy-saving development of civil buildings, and to accelerate the benign development of energy-saving buildings.

As a strategic emerging industry, environmental protection industry is important in the development of national economy. However, few empirical studies on the performance of environmental protection industry are carried out. In order to explore development performance and influencing factors of environmental protection industry in China, the selection of development data of China’s 31 provincial regions under the environmental protection industry was conducted based on industrial efficiency, economic contribution, industrial scale, and development speed. Development performance of environmental protection industry was qualitatively analysed and influencing factors were explored by using the method of factor analysis. Results show that the factor score of the eastern region is positive in both industry scale and pollution treatment. Factor score of industry scale, industry contribution and pollution treatment in the central region is positive. Development of environmental protection industry in the western region lags far behind other areas, and only factor score of industry contribution are positive and significantly higher than other areas. Factor score of industrial scale, industrial contribution, and pollution treatment in the northeast region is lower than that in the eastern and central region. Suggestions and countermeasures are proposed to promote the development of the environmental protection industry.

Water pollution by heavy metals due to discharge of industrial and anthropogenic waste leads to serious environmental and health problems as most of these heavy metals are carcinogenic in nature. In the present study chromium biosorption capacity of live and dead biomass of bacterial strain HGB1 isolated from Ganga River in Haridwar, which was examined as Bacillus subtilis, following 16S rDNA sequence analysis, was examined for different physical parameters such as pH, time of incubation and temperature. Experimental results indicate that the Bacillius subtilis has maximum tolerance capacity up to 1000 mg.L-1 with highest metal uptake of 95.64%, 97.25% and 97.11% at pH 3, 60 minutes, 2.5 mg/mL biomass respectively in case of dead biomass. In case of living biomass, highest metal uptake was 81.64%, 96.79 % and 95.89% at pH 7, 72hr and 32°C respectively. The surface chemical functional groups of Bacillus subtilis identified by FTIR were amino, carboxyl, hydroxyl and carbonyl groups. The morphological changes were examined by SEM analysis.

The construction industry is among the pillars of China’s economic development. However, it causes high carbon emission and high energy consumption, which should be considered when drafting energy saving and emission reduction policies. The sustainable development of this industry lies in the effective estimation of carbon emission efficiency and implementation of energy-saving and emission reduction measures in accordance with local practical situations. First, investigations on the emission efficiency of the construction industry and relevant emission reduction policies in foreign developed countries were reviewed in this study. Second, the carbon emission efficiency of the construction industry in 13 prefecture-level cities in Hunan Province (China) from 2011 to 2017 were estimated using the SBM (Slack Based Measure) model involving unexpected outputs. Finally, specific suggestions on reducing the carbon emission of the construction industry were proposed. CO2 emissions in the construction industry increase annually as a response to economic development and urbanization. The carbon emission efficiency of Hunan Province’s construction industry maintained a stable growth rate in 2011-2017. The industry achieved an annual growth rate of 2.7% in 2017 from that in 2011. The carbon emission efficiency of Changsha City, Zhangjiajie City, and Yiyang City were relatively higher than those of other cities in the province. Such findings serve as a reference to the quantification of potential of Hunan Province in reducing the carbon emission, the formulation of specific carbon emission reduction goal, the augmentation of the means to evaluate energy saving and emission reduction, and the development of a low-carbon construction industry.

The concentration of chlorophyll-α in the Gorontalo Bay is necessary to be observed since it could describe the condition of water richness. The semi-enclosed Gorontalo Bay morphology causes the status of water fertility to be largely determined by the input of inorganic or organic materials originating from the mainland. This study aimed to figure out the concentration and horizontal distribution pattern of the chlorophyll-α then further to decide the relationship between the concentration of chlorophyll-α and the nutrients in the Gorontalo Bay. There were fifteen sub-sampling sites selected based on coastal and ecological characteristics. Results showed that the distribution pattern of chlorophyll-α in the Gorontalo Bay in June and July 2017 was dissimilar and its concentration ranged from 0.984 to 3.744 mg.m-3. In addition, there was a positive and substantial relationship between chlorophyll-α and phosphate (p<0.01). Nonetheless, there was no significant correlation between chlorophyll-α and nitrate (p>0.01) and ammonia (p>0.01).