Heavy metals (Cu, Pb, Cr, Cd and As) contents in surface sediments from western Laizhou Bay were analysed to evaluate the spatial distribution pattern and their contamination level. As was mainly concentrated in the coastal area near the estuaries and the other metals were mainly concentrated in the central part of the study area. The heavy metals were present at unpolluted levels overall evaluated by the sediment quality guidelines and geoaccumulation index. Principal component analysis suggest that Cu, Pb and Cd were mainly sourced from natural processes and As was mainly derived from anthropogenic inputs. Meanwhile, Cr originated from both natural processes and anthropogenic contributions. Tidal currents, sediments and human activities were important factors affecting the distribution of heavy metals. The heavy metal environment was divided into four subareas to provide a reference for understanding the distribution and pollution of heavy metals in the estuary-bay system.

In this work, Erythromycin A(EA)- degrading bacteria was isolated from the contaminated soil obtained from a pharmaceutical factory in China. The isolate designated as strain WX-J1 was identified as Ochrobactrum sp. by sequence analysis of its 16S rDNA gene. It can grow in a medium containing EA as the sole source of carbon and its optimal growth pH and temperature were 6.5 and 32°C, respectively. Under these conditions, when the initial Erythromycin A concentration was 100mg·L−1, 97% of Erythromycin A has been degraded. HPLC–MS analyses indicated that Erythromycin A degradation produced intermediates contained the following three substances: 3-depyranosyloxy erythromycin A, 7,12-dyhydroxy-6-deoxyerythronolide B, 6-deoxyerythronolide B and propionaldehyde. Since Erythromycin A-degrading Ochrobactrum sp. strain rapidly degraded Erythromycin A, this strain might be useful for bioremediation purposes.

Based on the remote sensing retrieval of PM2.5 concentration data in the long-time series, both the linear regression and grey system correlation analysis methods were employed to analyze the spatial and temporal pattern, variation trend and the main influencing factors of PM2.5 concentration in China from 1998 to 2014. The results showed that only 16.21%–24.67% of the land area in China PM2.5 concentrations reached the annual average criterion value of 10 μg/m3 set by the World Health Organization (WHO) in 1998–2014; the PM2.5 concentrations were greater than 95 μg/m3 mainly in Xinjiang Taklimakan Desert, west of Tianjin and the central region of Hebei. PM2.5 concentration was less than 10 μg/m3 mainly in Tibet, western Sichuan, northeastern Yunnan, Taiwan, northern Xinjiang, northern Inner Mongolia and northwest of Heilongjiang. High PM2.5 concentration in the northwest of China was mainly affected by sand and dust, while it was mainly caused by human activities in the eastern region. Except for Taiwan, low PM2.5 concentration areas were mainly located in the economically backward regions. The positive indicators in highly correlation with PM2.5 concentration include the average temperature, the proportion of primary and secondary industry to GDP, industrial consumption, the proportion of fulfilled amount of investment in real estate development to GDP, SO2 emissions and population density. The negative indicators in highly correlation with PM2.5 concentration include the average precipitation, the average wind velocity, the proportion of the tertiary industry to GDP, and the greening coverage rate of the built-up areas.

Road traffic emission factors (EFs) are important parameters in managing air quality. Estimation typically requires data from advanced (and expensive) monitoring systems which remain unavailable in some regions (e.g. in developing countries). In this context, the use of simpler (lower-cost) systems may be more appropriate, but it is essential to guarantee the robustness of EF estimations. This article describes a methodology designed to estimate vehicle EFs from street canyon measurements of traffic fluxes, wind speed and direction, and pollutant concentration levels by using low-cost devices, all samples at a one-minute interval. We use different moving window filters (time periods) to average the raw measurements. Applying standard multiple linear regressions (MRL) and principal component regressions (PCR), we show that there is an optimal smoothing level that best relates traffic episodes and pollutant concentration measurements. An application for PM10's EFs on four vehicle categories of Havana's fleet shows a preference for PCR over MLR techniques since it reduced the collinearity effects that appear when traffic fluxes are naturally correlated between vehicle categories. The best regression fits (R > 0.5 and standard deviation of estimates < 15%) were obtained by averaging data between 40′ and 60’; within the boundaries of 95% confidence interval motorcycles have an EF = 111.1 ± 2.7 mg km−1 veh−1; modern, light vehicles have an EF = 90.6 ± 11.2 mg km−1 veh−1; old, light vehicles have an EF = 125.4 ± 18.5 mg km−1 veh−1 and heavy vehicles have an EF = 415.1 ± 31.2 mg km−1 veh−1. We showed that upgrading old light vehicles is a promising scenario for reducing PM10 air pollution in Havana by between 10 and 17%.

Aerobic respiration and nitrification are important processes for dissolved inorganic nitrogen (DIN) composition change and CO2 production in human-perturbed coastal waters. On-site incubations and field investigations were conducted in the eastern Jiaozhou Bay, a high-urbanization region, from May to August 2014. Results show that aerobic respiration rates reached 15.58μmolO2L−1d−1, and NH4+ and NO2− oxidation rates were 0.53 and 0.13μmolNL−1d−1, respectively, in the human-perturbed northeastern area. The intense aerobic respiration there contributed to high-concentration NH4+, and meanwhile caused a pH decrease of 0.042units and a pCO2 increase of 166μatm per day. Moreover, the linear relationship between excess CO2 and apparent oxygen utilization suggested that the excess CO2 in the entire eastern Jiaozhou Bay was mainly from the aerobic respiration. This study may help us better understand the role of aerobic respiration in DIN composition and CO2 sink/source pattern in coastal waters.

In this study, we measured the concentrations of trace metals (Cr, Cu, Zn, As, Cd, Pb and Hg) in typical cultured animals (crabs, clams, and shrimps) and sediments from aquaculture ponds nearby mangrove wetlands in Zhangjiang estuary, China. The contents of Cr, Cu, Cd, and Pb in mangrove sediments were significantly higher than those in pond sediments, while an inverse distribution was observed for Zn, As, and Hg. Significantly higher concentrations of trace metals were found in clams from the mangrove mudflats compared to those from the aquaculture ponds. The sources of trace metals in the clams were primarily from organic fertilizer, whereas those in the shrimp were from contaminated sediment. The results of geo-accumulation index and the ecological risk assessment indicated that the aquaculture ponds near the mangrove wetlands in this subtropical estuary posed a special risk of endogenous and exogenous trace metal pollution to nearby systems.

Although anthropogenic oil spills vary in size, duration and severity, their broad impacts on complex social, economic and ecological systems can be significant. Questions pertaining to the operational challenges associated with the tactical allocation of human resources, cleanup equipment and supplies to areas impacted by a large spill are particularly salient when developing mitigation strategies for extreme oiling events. The purpose of this paper is to illustrate the application of advanced oil spill modeling techniques in combination with a developed mathematical model to spatially optimize the allocation of response crews and equipment for cleaning up an offshore oil spill. The results suggest that the detailed simulations and optimization model are a good first step in allowing both communities and emergency responders to proactively plan for extreme oiling events and develop response strategies that minimize the impacts of spills.

Effective emulsification plays an important role in the treatment of marine oil spills. The negative effects of chemical surfactants have necessitated a search for alternative dispersant that are sustainable and environmentally-friendly. To identify alternate dispersants, oil-in-seawater emulsions stabilized by hydrocarbon-degrading bacteria were investigated. After individual immobilization and surface-modification, the hydrocarbon-degrading bacteria, Bacillus cereus S-1, was found to produce a stable oil-in-seawater Pickering emulsion, which was similar to particle emulsifiers. The individual immobilization and surface-modification process improved the surface hydrophobicity and wettability of the bacterial cells, which was responsible for their effective adsorption at the oil–water interface. Through effective emulsification, the biodegradation of oil was remarkably facilitated by these treated bacteria, because of the increased interfacial area. By combining the emulsification and biodegradation, the results of this reported work demonstrated a novel approach for developing environmentally-friendly bioremediation technology in the field of oil treatment.

Microplastics (MPs) are observed to be present on the seafloor ranging from coastal areas to deep seas. Because bioturbation alters the distribution of natural particles on inhabited soft bottoms, a mesocosm experiment with common benthic invertebrates was conducted to study their effect on the distribution of secondary MPs (different-sized pieces of fishing line<1mm). During the study period of three weeks, the benthic community increased MP concentration in the depth of 1.7–5.1cm in the sediment. The experiment revealed a clear vertical gradient in MP distribution with their abundance being highest in the uppermost parts of the sediment and decreasing with depth. The Baltic clam Macoma balthica was the only study animal that ingested MPs. This study highlights the need to further examine the vertical distribution of MPs in natural sediments to reliably assess their abundance on the seafloor as well as their potential impacts on benthic communities.

Mangrove forests play an important role in biogeochemical cycle of C, storing large amounts of organic carbon. However, these functions can be controlled by the high spatial heterogeneity of these intertidal environments. In this study were performed an intensive sampling characterizing mangrove soils under different type of vegetation (Rhizophora/Avicennia/dead mangrove) in the Venezuelan coast. The soils were anoxic, with a pH~7; however other soil parameters varied widely (e.g., clay, organic carbon). Dead mangrove area showed a significant lower amounts of total organic carbon (TOC) (6.8±2.2%), in comparison to the well-preserved mangrove of Avicennia or Rhizophora (TOC=17–20%). Our results indicate that 56% of the TOC was lost within a period of 10years and we estimate that 11,219kgm−2 of CO2 was emitted as a result of the mangrove death. These results represent an average emission rate of 11.2±19.17tCO2ha−1y−1.