With the signature of the free trade agreement, trade ties will develop rapidly between China and South Korea. Based on input–output model, this paper calculates and decomposes the embodied carbon emissions in the trade between China and South Korea from 2000 to 2010, analyses the reasons and gives some future advices. This paper suggests that the embodied carbon emissions surplus is not caused by trade surplus. It further points out that textile and leather industries, chemical manufacturing industries and metal manufacturing industries are three main sectors contributing to imported and exported embodied carbon emissions. In addition, the trade diversion between China and South Korea helps a lot in reducing the global carbon emissions and eases the pressure of carbon emissions in China. This paper also proposes that China should learn advanced technologies from South Korea and reduce carbon-intensive energy consumption in the future.

A total of 141 surface sediments were collected and analyzed for their geochemistry, total organic carbon, and grain size to assess the heavy metal pollution in the Bohai and Yellow Seas. The enrichment factor (EF) and geoaccumulation index (Igeo) of Cu, Pb, Zn, Cr, Cd, Ni, As, and Hg were calculated to assess anthropogenic contamination, and the results suggest that moderate Pb, Cd, and As contamination occurs in the study area. Sediment quality guidelines were applied to assess the adverse biological effects of these metals. The spatial distribution of the mean Effects Range-Median quotient for the vast majority of the study area is between 0.1 and 0.5, indicating low impact and potential negative biological effects. Multivariate analysis indicates that Cu, Pb, Zn, Cr, and Ni resulted primarily from lithogenic sources, whereas As, Cd, and Hg were mainly attributed to anthropogenic sources.

The sources, distribution, surface features, polymer composition and age of microplastic pellets (MPPs) in surface sediments along the Chennai coast during March 2015 (pre-Chennai flood) and November 2015 (post-Chennai flood) were characterised using a Stereoscopic microscope and FTIR-ATR spectroscopy. White MPPs were the most abundant, and specifically polyethylene (PE) and polypropylene (PP) were the dominant polymer types of MPPs found on the coast during both the times. The abundance of MPPs in November 2015 was three-fold higher than those found in March 2015, confirming that huge quantity of fresh MPPs washed through Cooum and Adyar rivers from land during the flood. The winds and surface currents during November were the driving forces for the transportation and deposition of MPPs from the sea to beaches. The results of this study will be useful to formulate beach MPPs litter management policies to effectively create long-term solutions.

With increasing concern over the aquatic environment in marine culture, the integrated multi-trophic aquaculture (IMTA) has received extensive attention in recent years. A three-dimensional numerical ocean model is developed to explore the negative impacts of aquaculture wastes and assess the bio-mitigation effect of IMTA systems on marine environments. Numerical results showed that the concentration of surface phytoplankton could be controlled by planting seaweed (a maximum reduction of 30%), and the percentage change in the improvement of bottom dissolved oxygen concentration increased to 35% at maximum due to the ingestion of organic wastes by sea cucumbers. Numerical simulations indicate that seaweeds need to be harvested in a timely manner for maximal absorption of nutrients, and the initial stocking density of sea cucumbers >3.9 individuals m−2 is preferred to further eliminate the organic wastes sinking down to the sea bottom.

In this study, we developed an atmospheric dispersion model based on the finite difference method (GEARN-FDM) to simulate long-range radiological dispersion. The model includes a mass conservation and monotonic advection scheme and a horizontal diffusion scheme based on the deformation of the resolved horizontal wind. Meteorological fields in calculating dispersion were simulated by the Advanced Research Weather Research and Forecasting (WRF) model. ERA-interim reanalysis was used for the WRF nudging calculation. By using tracer gas concentrations from the European tracer experiment, the GEARN-FDM performance could be tested. The results indicated high performance with factors of 2 and 5 of 37% and 72%, respectively. To investigate the impact of horizontal diffusivity on the concentration distribution, we examined an additional simulation run using GEARN-FDM with a constant value of horizontal diffusivity. In comparison with the additional run, the plume calculated in the original GEARN-FDM run was locally and temporally diluted due to large horizontal diffusivity in a mountainous region. Therefore, geographical heterogeneity of horizontal diffusivity may affect regional-scale atmospheric dispersion simulations.

Exposure to ambient (urban) air pollution consisting of fine particles is linked with the increased risk of respiratory as well as cardiovascular diseases and cancers. Recent studies have, however, suggested the adverse effects of PM₂.₅ and especially ultrafine particulate matter (UFPM or PM₀.₁: size <0.1 μm or 100 nm) in ambient air pollution in the brain and central nervous system (CNS). These particles can travel beyond the pulmonary systems to the CNS and, ultimately, reach the brain that may cause neurological diseases including Alzheimer’s disease, Parkinson’s disease, and other forms of dementia. The polychlorinated biphenyls (PCBs) can also be linked to neurological disorders identically. An attempt has been made in this article to make an assessment on the roles of UFPM and PM₂.₅ as well as PCBs on the neurological disorders from exposure to ambient air pollution. Finally, several recommendations are made for future scope of research followed by regulatory enforcement strategies to reduce the occurrence of neurological disorders from exposures of ambient air pollution to humans.

We modeled the transport of oil, source-fingerprinted 44 tarball samples from Galveston Island (GV) and Mustang Island (MT), and determined the hydrocarbon and bacterial community composition of these tarballs following the 2014 Texas City “Y” Oil Spill (TCY). Transport modeling indicated that the tarballs arrived in MT before the samples were collected. Source-fingerprinting confirmed that the tarballs collected from GV and MT, 6d and 11d after the TCY, respectively, originated from the spill. Tarballs from GV showed 21% depletion of alkanes, mainly C9–C17, and 55% depletion of PAHs mainly naphthalenes, and dominated by alkane-degrading Alcanivorax and Psychrobacter. Samples from MT were depleted of 24% alkanes and 63% PAHs, and contained mainly of PAH-degrading Pseudoalteromonas. To the best of our knowledge, this is the first study to relate oil transport, tarball source-fingerprinting, chemistry, and microbiology, which provides insights on the fate of oil in the northern Gulf of Mexico.

In order to take actions against the annual flooding in Jakarta, the construction of a Giant Seawall has been proposed in the Master Plan for National Capital Integrated Coastal Development. The seawall provides a combination of technical solutions against flooding, but these will heavily modify the mass transports in the near-coastal area of Jakarta Bay. This study presents numerical simulations of river flux of total nitrogen and N,N-diethyl-m-toluamide, a molecular tracer for municipal waste water for similar scenarios as described in the Master Plan. Model results demonstrate a strong accumulation of municipal wastes and nutrients in the planned reservoirs to extremely high levels which will result in drastic adverse eutrophication effects if the treatment of municipal waste water is not dealt with in the same priority as the construction of the Giant Seawall.

Concentrations of CO2 and CH4 measured over 3 years at a rural site in the Spanish northern plateau were investigated together with vegetation and meteorological variables. Two procedures were implemented to study the annual evolution. Kernel estimation provided a detailed time description, and the harmonic model may be fitted easily. The site was characterised by grass from autumn to spring. However, vigorous growth was observed during the latter season due to the biological cycle of plants under favourable meteorological conditions. A CO2 peak was observed a fortnight before the time of maximum NDVI, and was attributed to the prevalence of respiration over photosynthesis. A pronounced trough was apparent in summer and was explained by the death of vegetation and active dispersion in a highly developed boundary layer. CH4 evolution was characterised by a deficit period from May to October, indicating that meteorological evolution played a key role. The harmonic model showed that annual and half-annual cycles evidenced a similar contribution for CO2, whereas said weight for the half-annual cycle was considerably smaller for CH4.

The concentrations of organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSIC), and major & trace elements of PM10 were studied in Delhi, an urban site of the Indo Gangetic Plain (IGP), India during January 2013 to June 2014. The average mass concentration of PM10 recorded as 249.7 ± 103.9 μg m−3 (average ± standard deviation) with a range of 61.4–584.8 μg m−3. The strong seasonal variation was noticed in the mass concentration of PM10 and its chemical composition with maxima during winter (PM10: 293.9 ± 95.6 μg m−3; OC: 30.5 ± 13.7 μg m−3; EC: 15.2 ± 7.4 μg m−3) and minima during monsoon (PM10: 143.9 ± 36.3 μg m−3; OC: 19.9 ± 16.2 μg m−3; EC: 7.4 ± 5.4 μg m−3). The average concentration of major and trace elements (Na, Mg, Al, P, S, Cl, K, Ca, Si, Cr, Ti, As, Br, Pb, Fe, Zn and Mn) was accounted for ∼18.5% of PM10 mass. Results of Positive Matrix Factorization (PMF) model, HYSPLIT4 trajectory model, PSCF analysis and cluster analysis provide region of sources and its strength and types of sources of PM10 over Delhi. Positive PMF provides that the major source of PM10 are soil dust (22.7%) followed by secondary aerosols (20.5%), vehicle emissions (17.0%), fossil fuel burning (15.5%), biomass burning (12.2%), industrial emissions (7.3%) and sea salts (4.8%) at the observational site of Delhi. The cluster analysis of air mass trajectories calculated by HYSPLIT model indicates that the air mass approaches to the observational site mainly from 4 sides (north-western IGP, Pakistan (10%); north-western IGP, Northwest Asia (45%); eastern IGP (38%); Pakistan and Arabian Sea (6%)) during study. Potential Source Contribution Function (PSCF) analysis also supports the cluster analysis indicating that the concentration of PM10 mass contributed, is mainly from IGP region (Uttar Pradesh, Haryana and Punjab etc.), Afghanistan, Pakistan and surrounding areas.