This paper is a maiden empirical attempt to analyze the dynamic causal linkages among urban agglomeration, electricity consumption, construction industry, and economic performance, making use of simultaneous structural equations. A national panel of 30 provinces and three sub-national panels of China, for time span 2000 to 2016, have been estimated employing system and difference generalized method of moments (GMM) estimator. A construction industry-augmented model of economic growth has been proposed, incorporating construction industry and urban agglomeration as exogenous shocks to the aggregate production and electricity consumption as the input of production function. The core empirical results are first, the urban agglomeration and construction industry positively cause electricity consumption but are not caused by the same. It revealed the critical role played by urban agglomeration along with construction industry in boosting electricity consumption. Second, the economic performance positively causes electricity consumption, urban agglomeration, and construction industry and is also caused by the same. Third, urban agglomeration causes the construction industry and is caused by the same. It exposed the mutual role of urban agglomeration and urban industry in reinforcing each other in the times of high economic performance. Finally, among the three regions, the eastern zone is found to be strongest in terms of linkages among urban agglomeration, construction industry, electricity consumption, and economic performance. The intermediate zone is moderately strong, while the western zone is found to have the least strong linkages as compared with the two regions. These results are in line with the sub-national level of economic development of China. These findings, in terms of statistical significance, are highly robust across all the panels. Furthermore, depending upon empirical results, the related strategies are proposed.

In this study, the possibility of culturing Dunaliella salina in stickwater (SW) as the main effluent of fishmeal plants was evaluated. D. salina was grown in different media obtained by replacing standard Guillard medium (F/2) with SW at 0% (control), 10%, 25%, 50%, 75%, and 100% ratios. The cell density, pigment contents, proximate composition, saponification value, and fatty acids (FAs) profiles were measured for 14 days. SW was collected from a kilka fishmeal factory in northern Iran, and the characteristics indicated high concentrations of nitrate (242.00 mg L⁻¹) and phosphate (11.13 mg L⁻¹). A significant increase in the cell density was observed in 14 days when 75% SW was used. Moreover, SW significantly affected the pigment contents. The highest contents of chlorophylls, total carotenoids, and β-carotene (3.64 μg mL⁻¹) were calculated in 75% SW. According to the algal proximate composition, the highest and lowest contents of lipid were accumulated in 75% and 100% SW, respectively (p < 0.05). The highest level of saturated FAs was observed in 75% SW compared with the others (p < 0.05). In conclusion, replacing F/2 with SW indicated the capability of D. salina to grow in a treated medium with 75% SW substitution as a bioremediator.

Statistics from the Intergovernmental Panel on Climate Change (IPCC) reveals that energy consumption remains the main root cause of anthropogenic greenhouse pollutant emissions because of economic expansion. Thus, the need to explore the determinants of environmental degradation in South Africa is pertinent for policymakers and stakeholders. The current study is conducted in a multivariate framework using an augmented carbon income function. The present study explores the theme under review with the inclusion of total natural resource rent as an additional variable to circumvent for omitted variable bias. To this end, annual time series data from 1970 to 2017 is employed for econometrics analysis. The study set off with investigation of stationarity properties with conventional unit root test in conjunction with Zivot-Andrews unit root test that accounts for single structural break. The Pesaran’s bounds testing techniques traces long-run equilibrium relationship between energy (coal) consumption, pollutant emission, total natural resources rent, and economic expansion over the sampled period. Empirical test from the modified Wald test detect and validate feedback causality between energy (coal) consumption and economic expansion. This is instructive to energy stakeholders and policymakers that energy is key determinant of economic growth. Furthermore, total natural resources rent shows significant contribution to pollutant emissions in South Africa. Based on the empirical results, policy direction such as adoption of new technologies and cleaner energy sources were suggested rather than fossil fuel driven economy in South Africa.

Dam construction leads to both sediment discontinuities and the creation of internal phosphorus (P) loads in reservoirs capable of supporting eutrophication. Today, majority of large rivers are dammed and numerous of these infrastructures are constructed in cascade. However, few studies focus on the cumulative effect of the presence of dam on sediment P mobility and bioavailability in downstream reservoirs and rivers parts or throughout the continuum. The influence of three cascade dams has been studied herein on the sedimentary P distribution in surface bed sediments along a 17-km fluvial continuum of the Creuse River (Massif Central, France). The sediments (17 samples) were analyzed for their physical (grain size, specific surface area) and chemical (pH, contents of P, Fe, Al, Ca, Mn, organic matter (OM), and P fractionation) characteristics. Results indicated an amount of P 3 to 7 times higher in dam sediments (1.59 ± 0.51 mgP/g DW) than in free-flowing river sections (0.27 ± 0.11 mgP/g DW). Unexpectedly, sedimentary TP content did not decrease from the first to the third reservoir. The spatial variations of sediment characteristics between river and reservoirs were correlated with the retention of particles sized under 200 μm within the reservoirs. In reservoir sediment, P was mainly associated with the ascorbate fraction (P associated with the redox-sensitive Fe/Mn precipitates). Inside each dam reservoir, longitudinal variations of the sedimentary P distribution were mainly due to the increase of amorphous Fe precipitate content accumulated in fine sediments toward the dam, as characterized by a low Fe-Asc/P-Asc molar ratio. In the river sections, P distribution (mainly associated with HCl and ascorbate fractions) was not significantly influenced by cascade dams.

Non-alcoholic fatty liver disease (NAFLD), the most common form of liver disease, affects over 30% of the US population. Our group and others have previously demonstrated that low-level environmental pollutant exposures were associated with increased odds ratios for unexplained alanine aminotransferase (ALT) elevation, a surrogate biomarker for NAFLD, in the adult National Health and Nutrition Examination Survey (NHANES). However, recently, more sensitive and lower ALT cutoffs have been proposed. The objective of this observational study is to utilize these ALT cutoffs to determine new associations between environmental chemicals and the surrogate NAFLD biomarker. Adult NHANES 2003–2004 participants without viral hepatitis, hemochromatosis, or alcoholic liver disease were analyzed in this cross-sectional study. ALT elevation was defined as > 30 IU/L in men and > 19 IU/L in women. Odds ratios adjusted for potential confounders for ALT elevation were determined across exposure quartiles for 17 pollutant subclasses comprised of 111 individual pollutants. The overall prevalence of ALT elevation was 37.6%. Heavy metal and organochlorine insecticide subclasses were associated with dose-dependent increased adjusted odds ratios for ALT elevation of 1.6 (95% CI 1.2–2.3) and 3.5 (95% CI 2.3–5.5) respectively, for the highest vs. lowest exposure quartiles (pₜᵣₑₙd < 0.01). Within these subclasses, increasing whole blood levels of lead and mercury, and lipid-adjusted serum levels of dieldrin, and the chlordane metabolites, heptachlor epoxide, and trans-nonachlor, were associated with increased odds ratios for ALT elevation. In conclusion, organochlorine insecticide, lead, and mercury exposures were associated with ALT elevation and suspected NAFLD in adult NHANES 2003–2004.

Hydrogeochemical understanding of groundwater is essential for the effective management of groundwater. This study has been carried out to have concrete data for the seasonal variations in hydrogeochemistry of groundwater in central Tamilnadu forming a complex geological terrain with a varied lithology. A total of 244 groundwater samples were collected during four different seasons, viz, southwest monsoon (SWM), summer (SUM), postmonsoon (POM), and northeast monsoon (NEM) from bore wells. The physical parameters such as pH, temperature, TDS, ORP, humidity, and electrical conductivity (EC) were measured insitu, whereas major ions were analyzed in the lab adopting standard procedures. Overall, higher EC and NO₃ values were observed and exceeded the WHO permissible limit irrespective of seasons, except for NO₃ in SWM. Na and HCO₃ are the dominant cation and anion in the groundwater irrespective of seasons. The highest average values of Na (65.06 mg L⁻¹) and HCO₃ (350.75 mg L⁻¹) were noted during SWM. Statistical analysis was carried out to elucidate the hydrogeochemistry of the region. Initially, to understand the ionic relationship, correlation matrix was used followed by factor analysis for determination of major geochemical control and later factor scores were derived to understand the regional representations. An attempt has also been made to identify the samples influenced by multiple geochemical processes and to understand their spatial variation in the study period. Correlation of geochemical parameters reveals a excellent positive correlation between Ca and NO₃ in SUM, SWM, and NEM due to the dominant of anthropogenic sources and minor influence of weathering process. Strongly loaded factor scores are found to be mostly in the following order POM > NEM > SWM > SUM. Principal component analysis of different seasons indicates the interplay of natural weathering and anthropogenic factors. Overall, the predominant geochemical processes in this region, irrespective of seasons are weathering and, ion exchange and anthropogenic activities.

Coal mining causes serious ecological and environmental damage. The crushed gangue is backfilled into underground goaf, which not only inhibits mining-induced subsidence but also reduces accumulation of waste on the ground: however, the effects of backfilling with gangue backfill materials in goaf are affected by a combination of multiple factors. To predict compression-induced deformation (CID) of gangue backfill materials, key factors influencing compression and deformation characteristics of gangue backfill materials in an underground confined space (lithology, particle size distribution, lateral stress and lateral loading times) were determined. Moreover, two key factors, namely, lithology and particle size distribution of gangue backfill materials, were quantified. Based on orthogonal test design, the compression characteristics of gangue backfill materials were measured under different stress levels and coupling effects of the four key factors by utilising a self-made bidirectional loading test system for bulk materials. Furthermore, through regression, the relationships of the four key factors and axial strain were determined as well as undetermined parameters in axial stress-axial strain equations and axial stress. Based on this, an equation for predicting stress-strain relationship during compression-induced deformation of gangue backfill materials under multi-factor coupling effects was established. Comparison with the orthogonal test results shows that this equation can predict compression-induced deformation of gangue backfill materials in goaf. This is beneficial to providing a basis for predicting strata movement and surface subsidence and guidance for designing backfilling process, thus protecting the surface environment.

Multivariate statistical techniques and geostatistical methods are among the important tools used in surface water quality management. They are widely used in interpreting data, identifying the pollution sources, understanding the spatial variation of parameters, and determining the places of monitoring stations. Therefore, in this study, spatial variation of water quality and pollutants in the Anzali Wetland water (Iran) was evaluated using multivariate statistical and Kriging methods. The values of different water quality parameters measured in six stations in the wetland water were subjected to cluster analysis (CA) and principal component analysis (PCA). Cluster analysis reduced the number of stations from six to four. The results of PCA showed that industrial and agricultural pollution sources could be responsible for the Anzali Wetland water quality. Then, the spatial variation maps of the PCA scores were generated using Kriging geostatistical method in the geographical information system (GIS) to investigate the pollution sources affecting the wetland parts. These maps illustrated that a great part of the wetland body was under the effect of agricultural sources, while the industrial sources affected the outlet and central parts. Finally, a comparison between two models (multiple linear regression (MLR) and Kriging) was made to assess their ability in predicting water quality parameters in the study area. The results showed the improvement of prediction using MLR, which was by 25%–97%, compared with Kriging. The results of the present study can be effectively used in the planning and implementation of future monitoring networks in the Anzali Wetland and other similar aquatic systems.

Dynamic oil release from oil-contaminated sediment to seawater was investigated in kinetic and factor experiments. Oil-release kinetic was described using a two-compartment first-order equation with rapid- and slow-release steps. The rapid-desorption-fraction rate (kᵣ) was not affected by the ratio of solid-liquid, but significantly affected by sediment pollution level and salinity. The slow-desorption-fraction rate constant (kₛ) was affected by sediment pollution level, the ratio of solid-liquid, and salinity. Desorption efficiencies were 1.09–4.04%, increasing as the sediment pollution level and salinity increased and the ratio of solid-liquid decreased. Oil desorption was critically affected by sediment suspension (or lack of). The desorption kinetics curves were unaffected with the shear force for unsuspended sediment, and the desorption efficiency and kᵣ were increasing with the shear force for suspended sediment, and no significant correlations were found between kₛ and hydrodynamic conditions. The results provide a theoretical basis for evaluating ecological risks posed by oil in sediment.

Climate change has become a threatening issue for major field crops of Pakistan, especially rice. A 2 years’ (2014 and 2015) field trial was conducted on fine, coarse, and hybrid rice at Research Area, Department of Agronomy, University of Agriculture, Faisalabad following the split-plot design. Data of growth, yield, and yield components were collected to calibrate and evaluate the CERES-Rice model under Decision Support System for Agro-technology Transfer (DSSAT). Two cultivars of each type of fine, coarse, and hybrid rice were transplanted with interval of fortnight from May to September during 2014 and 2015. The model was calibrated with non-stressed sowing data during the year 2014 and evaluated with the data of 2015. Climate change scenarios were generated for mid-century (2040–2069) under representative concentration pathway (RCP8.5) using different general circulation models (GCMs) (baseline, cool dry, hot dry, cool wet, hot wet, and middle) were using different General Circulation Models (GCMs). CERES-Rice calibration and evaluation results were quite good to simulate impacts of climate change and to formulate adaptations during 2040–2069 (mid-century). Simulations of all GCMs showed an average increase of 3 °C in average temperature as compared to baseline (1980–2010). Likewise, there would be an average increase of 107.6 mm in rainfall than baseline. The future rise in temperature will reduced the paddy yield by 10.33% in fine, 18–54% in coarse and 24–64% in hybrid rice for mid-century under RCP8.5. To nullified deleterious effects of climate change, some agronomic and genetics adaptation strategies were evaluated with CERES-rice during mid-century. Paddy yield of fine rice was increased by 15% in cool dry and 5% in hot dry GCM. Paddy yield of coarse rice was improved by 15% and 9% under cool dry and hot dry climatic conditions, respectively, with adaptations. For hybrid rice, paddy yield was enhanced by 15% and 0.3% with cool wet and hot dry climatic conditions, respectively. Hot dry climatic conditions were the most threatening for rice crop in rice producing areas of Punjab, Pakistan.