Crown profile models are key components of growth and yield models and are crucial for estimating the crown volume and constructing 3D visualization of trees. We used a total of 431 trees collected from 98 pure even-aged temporary sample plots established in Fujian Province to develop crown profile models of Chinese fir (Cunninghamia lanceolata).To describe the shape of tree crowns more accurately, significance tests of the effects of different stand conditions (stand age, site index, and stand density) on crown shape were conducted with one-way analysis of variance (ANOVA). Multiple comparisons based on the ANOVA results were used to classify the crown data into three groups according to stand age: Group I (young forest), Group II (medium forest), and Group III (nearly mature and mature forest). We analysed the relationships between the crown variables and stand variables and used the reparameterization approach to develop three optimal crown profile models for different age groups. Stand variables (such as stand density) further improved the prediction efficacy of the models. Considering the correlation between repeated measurement data for the same tree crown, the non-linear mixed-effects modelling (NLME) method was used to account for autocorrelation. The determination coefficients (R2) of the above three optimal models fitted by the non-linear mixed-effects approach were 0.9214, 0.9398 and 0.9129, and their Root Mean Squared Errors (RMSEs) were 0.1246, 0.1409 and 0.1786, respectively. The determinant coefficients (R2) of the three models fitted by the nonlinear least squares (NLS) approach were 0.9015, 0.8794 and 0.8930, and their RMSEs were 0.1395, 0.2102 and 0.1878, respectively. The results indicated that the predicted accuracy was significantly increased by using non-linear mixed effects modelling compared with the NLS method.

With the accelerating industrialization and urbanization in China, the energy consumption of the transportation industry in the country is increasing quickly, and its proportion to the total social energy consumption is significantly growing. The transportation industry is a main source of carbon emission in urban areas. The unreasonable structure of energy consumption, the low proportion of new-energy use, and low energy utilization influence the energy-saving and emission reduction in the transportation industry. Thus, in this work, the influencing factors of transportation-induced carbon emission were estimated to analyze the environmental pollution caused by the transportation industry further. Regression analysis was performed on the environmental pollution caused by the transportation industry and the influencing factors of carbon emission in Jiangxi Province, China. Subsequently, a random STIRPAT model was constructed, and the influencing factors of carbon emission from the transportation industry in Jiangxi Province from 2007 to 2017 were analyzed through the partial least squares (PLS) method. Regression results based on the PLS method were relatively ideal. Increases in gross domestic product per capita, population size, passenger person kilometers, rotation freight transport kilometers, and the number of car ownerships can intensify transportation-induced carbon emission. This emission is increased when transportation energy intensity declines, but can be significantly inhibited by increased energy prices. The conclusions of this study can provide references for the continuous optimization of the energy use structure in the transportation industry, saving of energy resources, reduction of greenhouse gas and pollutant emission, and acceleration of low carbonization in the transportation industry.

The Legon Bajak port is a strategic port in Indonesia, because it is located in a busy and potential shipping lane. The port is adjacent to the Karimunjawa Marine National Park which is protected by the Indonesian government; therefore, this study aims to provide an overview of the ecological status of the Legon Bajak sea and the prediction of the impact of port activities on the ecological status of the Marine National Park. This research is a descriptive study by analysing seawater quality using atomic absorption spectroscopic methods, the status of biodiversity of seaweed and coral reefs with the transect method at 6 observed sample points and photos of underwater marine supporters. The results of the analysis of seawater quality indicate that it is in good condition, but when viewed from the analysis of seaweed conditions and coral cover <10%, this indicates that the ecological status is in a damaged condition and a category with a low functional value. An in-depth study is needed for the analysis of the environmental impact of the Legon Bajak port on the Karimunjawa National Marine Park Conservation Area.

Anthropogenic activities are most likely to alter the natural composition of waters. Extensive phosphate mining in Huangbaihe River Basin (HRB), China, has resulted in the reduction of the self-purification capacity of freshwater reservoirs in the basin. Based on a three-year (2014-2016) water quality monitored data and the application of three pollution index assessment (PIA) methods: Single Factor Pollution Index (SFPI), Nemerow’ Pollution Index (NPI), and Water Quality Index (WQI), the main objective of this study was to determine the water quality standards of surface water in the river basin. Research findings indicated that a holistic approach, a combination of a single factor and multi factor pollution indexes (MFPIs) method was able to distinguish pollutant characteristics and used to classify water quality of the river system. Comparison of the results showed that the SFPI classification is more conservative and highly influenced by the worst evaluated index. On the other hand, the MFPIs: the NPI and the WQI methods classified the water quality into a more reasonable grade because they integrate the effects of different impacting factors. The most impaired pollutants affected the water quality classification were total phosphorus (TP) and total nitrogen (TN). Application of the PIA result for the water quality management purpose in the basin showed that there is a direct causal relationship between the TP concentration and water quality of reservoir water; low water quality reservoirs were correlated with high TP. On the other hand, the reservoir water quality did not show any significant dependence on TN. A linear regression equation was proposed to determine WQI of reservoirs’ water using measured TP. The equation may be used to characterize the pollution level of reservoir water for prioritizing water quality management measures in HRB.

Several methods of treatment have been suggested for the removal of chromium from raw water, which include chemical precipitation, reverse osmosis, ion exchange, foam formation, etc. The main disadvantages of the above processes are that they produce a large amount of sludge and there are no possibilities of metal recovery as they are very costly. The use of plants and other plant materials for the removal of the heavy metals has already been reported in the literature as the non-conventional adsorbents. In the present work, an attempt has been made to check the suitability of Terminalia chebula powder for removing chromium from raw water by adsorption and for suggesting an environmental friendly as well as economically feasible solution to overcome the problems due to the presence of toxic pollutants like chromium in drinking water. Batch experiments were conducted using aqueous solution of chromium to determine the chromium removal. Terminalia chebula powder (commonly known as karakkaya locally) has been collected locally and used as an adsorbent for all the batch experiments. Variation of chromium removal with dosage of adsorbent and initial pollution concentration is studied.

Monsoon is a typical wind system, which influences a quarter of continental area on the earth and is closely bound up with the life of one half of the earth’s population. Therefore, it is important to explore the information on monsoon activities. In the present study, samples of precipitation and surface water collected in the summer of 2018 were analysed to reveal the variation of stable isotopes influenced by summer monsoon and its relationship with the sources of water vapour. The temporal variation of stable isotopes in precipitation is great during the monsoon period, which is primarily the result of the varying proportions of water vapour from continental and oceanic sources. The heavy isotopes in precipitation grew gradually as the proportion of ocean-source water vapour increased from May to August. The meteorological parameters of temperature and precipitation amount are not the main factors that influence the isotopic composition in precipitation, for the determination coefficient (R2 value) is low. The isotopic characteristics of river water are similar to those of precipitation, indicating that the rivers are mainly recharged by precipitation. The temporal-spatial variations of isotopes surface water are complex for the joint influence of the distribution of isotopes in precipitation, isotopic compositions of the river source, rainfall amount and evaporation, which can be considered as the indirect effects of monsoon activities.

Petroleum fuels have served mankind successfully for more than a century mainly for mobility in the form of vehicles, power generation and industrial activities. As crude oil is a fossil fuel, we cannot rely upon it forever. Transportation is the backbone for the mobility for which fuel is the basic necessity. As the petroleum products are at the verge of their extinction, finding alternative fuels is the need of the time. Alternative fuels are obtained from seeds of many edible and non-edible oil plants. Edible oils due to their consumption for cooking purposes, may not be advisable to use for commercial activity, however, non-edible oils can be attempted as a source to serve the purpose as engine fuels. Nonedible oils can be blended with the petroleum products and can be used mainly in the diesel engine with slight or no modifications. The performance studies are being carried out by various researchers all over the world using many such refined oils as engine fuels. This review paper attempts to collate the published research literature. The focus in this review paper is on analysis of availability, engine performance and pollution characteristics when oils such as Jatropha curcas, Calophyllum inophyllum, Mahua and Pongamia pinnata are used.

The low coverage of drinking water in the West Kalimantan-Indonesia region because of the limited availability of decent water as a source of drinking water is the main trigger for the community to use rainwater as a source of drinking water. The way of storing rainwater through zinc roofs and environmental pollution conditions results in rainwater being a health concern for the community because of the content of Plumbum (Pb). In this study, the characteristics of rainwater in the West Kalimantan region were investigated from rainwater collected by people from homes with zinc roofs. Rainwater samples from the collection results were analysed for the presence of Plumbum (Pb). The impact of consuming rainwater is carried out by blood Pb examination. The main problem can analyse the existence of Plumbum (Pb) in rainwater against the content of Plumbum (Pb) in the blood. The results showed that there was a correlation of Pb content in rainwater with Pb content in the blood of people who consumed rainwater as water drink (p≤0.001).

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.