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.

Dispersion modeling is an important decision tool for estimating the impact of human activities on the environment and its populations. However, it was proved by researchers that AERMOD and CALPUFF, the current regulatory models, do not account for the effect of averaging time. In consequence, these models do not have the ability to predict short-term time peak concentrations. This inability arises from the errors in the lateral and vertical dispersion estimates, which are reliable only to predict 10 min or longer average concentrations. In this paper, a novel evaluation based on Irwin (1983) was conducted to investigate the effect of averaging time on the lateral dispersion and maximum concentration estimates. The Pasquill-Gifford, Högström, Draxler (embedded in CALPUFF) and AERMOD lateral dispersion schemes were tested using the Round Hill II experiment, developed to investigate the effects of averaging time on atmospheric transport and diffusion. The observed lateral dispersion was derived from the lateral concentration profiles along 3 sampling arcs (50, 100 and 200 m), measured on 3 different averaging times (0.5; 3 and 10 min). The observed lateral dispersion was compared to those estimates. The results of the comparison show that AERMOD and Draxler correlate better with measured data than the PG and Högström methods. However, their estimates are biased and the magnitude of systematic errors tends to grow as the averaging time decreases. Moreover, AERMOD and Draxler, with Peak-to-Mean (P-M) adjustment, tend to overestimate the lateral dispersion farther from the source and underestimate at downwind distances less than 200 m. The analysis also highlights some concerns on the P-M ratio application due its subjectivity. The present investigation on the effect of short-term averaging times on atmospheric transport and diffusion may help to understand some issues related to the use of dispersion models in the case of flammability, malodor nuisance and toxicity

Stormwater is a challenging source of coastal pollution to abate because stormwater also involves complex natural processes, and differentiating these processes from anthropogenic excesses is difficult. The goal of this study was to identify the natural concentrations of stormwater constituents along the 1377km coastline of California, USA. Twenty-eight ocean reference sites, a priori defined by lack of human disturbance in its adjacent watershed, were collected following 78 site-events and measured for 57 constituents and toxicity. Results indicated a complete lack of toxicity and undetectable levels of anthropogenic constituents (i.e., pesticides). The range of concentrations in ocean receiving waters for naturally-occurring constituents (i.e., total suspended solids, nutrients, trace metals) typically ranged three orders of magnitude. Regional differences and storm characteristics did not explain much of the variations in concentration. The reference site information is now being used to establish targets for marine protected areas subject to runoff from developed watersheds.

The objective of this study was to evaluate the burden of environmental pollution by Polychlorinated Biphenyls (PCBs) and Organochlorine Pesticides (OCs) in two localities of Rio de Janeiro coast, through the determination of these levels in specimens of mullets and croakers collected from May to August 2008, at Guanabara Bay (GB) and from Araújo Island (AI), at Paraty Bay. Twenty three organochlorine pollutants were detected in croakers at GB and twenty in mullets and all PCBs congeners investigated in the study were present in the two species. Ratio ∑DDT/∑PCB of 1.4 shows an important contribution of agricultural residues in GB and p,p′-DDE/∑DDT of 0.1 demonstrates a reintroduction of DDT. Consumption of mullet may represent a risk to the health of fishermen families from GB, with average and maximum estimated daily intake of ∑DDT of 9.012μg/kg p.c. and 26,174μg/kg p.c., representing 45% and 131% of ADI established by WHO.

We evaluated the influence of storm waves on the intertidal community structure of urbanized and non-urbanized areas of a sandy beach on the northern coast of Rio de Janeiro, Brazil. The macrofauna was sampled before (PREV) and after two storm wave events (POEV I; POEV II) in 2013 and 2014. Significant differences in community structure between PREV and POEV I in the urbanized sector demonstrate higher macrofauna vulnerability, and the community recovery within 41days on this scenario of less frequent events in 2013. On the other hand, significant differences in the macrofauna only in the urbanized sector between PREV and POEV II also highlight macrofauna vulnerability and community recovery failure within 42days on this scenario of more frequent storm in 2014. Urbanization and wave height were the variables that most influenced species, indicating that high storm wave events and increasing urbanization synergism are a threat to the macrofauna.

Tokyo Bay, Ise Bay, and the Seto Inland Sea are the total pollutant load control target areas in Japan. A significant correlation between the incidence of red tides and water quality has been observed in the Seto Inland Sea (Honjo, 1991). However, while red tides also occur in Ise Bay and Tokyo Bay, similar correlations have not been observed. Hence, it is necessary to understand what factors cause red tides to effectively manage these semi-closed systems. This study aims to investigate the relationship between the dynamics of the Red Tide Index and nitrogen regulation as well as phosphorus regulation, even in Ise Bay where, unlike Tokyo Bay, there are few observation items, by selecting a suitable objective variable. The introduction of a new technique that uses the Red Tide Index has revealed a possibility that the total pollution load control has influenced the dynamics of red tide blooms in Ise Bay.

The Biguglia lagoon is a shallow Mediterranean coastal ecosystem where eutrophication is increasing for years. A channel supplying freshwater was cleared in 2009 to enhance lagoon water circulation and alleviate dystrophic crises. Monthly monitoring was started in 2010 to document the impacts of this action on abiotic characteristics and phytoplankton communities. Three stations were surveyed (by microscopy and HPLC). Evidence suggests that this operation had an unexpected outcome. Salinity footprints indicated the succession of three main hydrological sequences that depended on rainfall and circulation pattern. Diatoms and dinoflagellates dominated the first sequence, characterized by heavy rainfall, while Prorocentrum minimum became progressively the dominant species in the second period (increasing salinities) with extensive bloom over the whole lagoon (5.93×10-5cells·L−1) during the third period. These phytoplankton successions and community structures underline the risk of pernicious effects arising from remediation efforts, in the present case based on increasing freshwater inputs.