The sources of PM10 in the Tahunanui airshed of Nelson, New Zealand were investigated using positive matrix factorization (PMF) on elemental data obtained from filters collected from September 2008-September 2009. Also, the source(s) of peak, non-winter PM10 concentrations that exceeded the National Environmental Standard for PM10 were investigated using PM10 and meteorological data from 2007–2012 and the PMF results. Seven PM10 sources were identified: biomass burning, motor vehicles, secondary sulfate, marine aerosol, crustal matter, protective coating activities and fertilizer. Overall, biomass burning was the dominant source contributor (35% of PM10). Analyses of PM10 concentration dependences on meteorological variables showed that peak, non-winter PM10 concentrations that occurred under moderate-to-high wind speeds from the southwest were the result of vehicular movements on unsealed roads in an industrial area. From this information, it is possible for Nelson City Council, who manages air quality at Tahunanui, to formulate mitigation strategies to reduce the impact of biomass burning and industrial vehicles on local air quality.

The size distribution of water-soluble inorganic components of urban aerosols in Shanghai was studied. The size-resolved aerosol samples collected by an 8-stage cascade sampler between April and May of 2012 were analyzed by ion chromatography. The ion mass concentrations followed the sequence of SO42−>NO3−~NH4+>Ca2+>Na+ ~Cl−>K+>Mg2+>F− for each size fraction below 2.1μm, while the sequence was NO3−>SO4−2>Ca2+>NH4+>Na+>Cl−>K+>Mg2+>F− for coarse mode particles larger than 3.3μm. The size distribution in 5 fractions showed that SO42−, NO3−, and NH4+ were generally in the fine mode peaking below 1μm while Ca2+, Mg2+, Na+, and Cl− were bimodally distributed with a second peak larger than 2.1μm. Back trajectory analyses revealed that the air masses could be classified into three main groups. The total ion concentrations were comparable between the terrestrial and mixing regimes. In the terrestrial regime, fine mode sulfate and nitrate were predominantly associated with ammonium. The excessive sulfate and nitrate over the whole size range might exist in the forms of Ca(NO3)2 and CaSO4. In the maritime regime, the decrease in SO42−, NO3−, and NH4+ contributed to the improvement in air quality. Besides marine aerosols, local emissions from soil dust and coal combustion were also important sources of sea-salt type ions (i.e., Na+ and Cl−).

Continuous operational monitoring by means of remote sensing contributes significantly towards less occurrence of oil spills over European waters however, operational activities show regular occurrence of accidental and deliberate oil spills over the North Sea, particularly from offshore platform installations. Since the areas covered by oil spills are usually large and scattered over the North Sea, satellite remote sensing particularly Synthetic Aperture Radar (SAR) represents an effective tool for operational oil spill detection. This paper describes the development of a semi-automated approach for oil spill detection, optimized for near real time offshore platform sourced pollution monitoring context. Eight feature parameters are extracted from each segmented dark spot. The classification algorithm is based on artificial neural network. An initial evaluation of this methodology has been carried out on 156 TerraSAR-X images. Wind and current history information also have been analyzed for particular cases in order to evaluate their influences on spill trajectory.

Medium Resolution Imaging Spectrometer (MERIS) data, Moderate Resolution Imaging Spectroradiometer (MODIS) data, and hydro-biological measurements were used to detect two very severe blooms in the southern Caspian Sea in 2005 and 2010. The MERIS Cyanobacteria Index (CIMERIS) was more reliable for detecting cyanobacterial blooms. The CIMERIS and MODIS cyanobacteria indices (CIMODIS) were compared in an effort to find a reliable method for detecting future blooms, as MERIS data were not available after April 2012. The CIMODIS had a linear relationship with and similar spatial patterns to the CIMERIS. On the CIMODIS images, extremely high biomass cyanobacteria patches were masked. A comparison of classified in situ data with the CIMODIS and Floating Algal Index (FAI) from four images of a severe bloom event in 2005 showed that the FAI is a reliable index for bloom detection over extremely dense patches. The corrected CIMODIS, the MODIS FAI and in situ data are adequate tools for cyanobacterial bloom monitoring in the southern Caspian Sea.

The microbial community and the nirS- and nirK-encoding denitrifiers in the intertidal sediments along Laizhou Bay in China were studied using pyrosequencing and real-time quantitative PCR (qPCR), respectively. There were three primary intertidal zones: Laizhou (La), Weifang Harbor (We), and Dongying (Do). Significant differences in composition and abundances at the different taxonomic levels were observed among the three bacterial communities. The qPCR results indicated that the nirS gene abundance varied from 8.67×105 to 5.68×106copies/gwet weight (ww), whereas the nirK gene abundance varied from 1.26×105 to 1.89×106copies/gww. The canonical correlation analysis (CCA) indicated that the sand percentage was the most important factor in shaping the bacterial community followed by silt percentage, NO2−, TOC, DO, pH, and clay percentage, whereas the clay percentage, pH, NO3−, DO, NO2−, TOC, silt percentage, and sand percentage were the most important factors associated with regulating the abundance of nirS- and nirK-encoding denitrifiers.

Baseline records are crucial in understanding how chemicals of concern impact on the receiving environment. We analysed terrestrial and marine resources from a pristine site on Isabel Island, Solomon Islands, to provide environmental baseline levels for total arsenic and arsenic species composition for commonly consumed marine resources. Our data show that levels of the more toxic inorganic arsenic species were very low or below detectable limits, with the exception of the seaweed Sargassum sp. that contained pentavalent inorganic arsenic levels of 4.63μgg−1. Total arsenic concentrations in the majority of marine and terrestrial samples collected were below 2μgg−1. The less toxic arsenobetaine was the predominant arsenic species present in all marine fauna samples analysed. This work highlights the need for arsenic speciation analysis to accurately assess potential toxicity of marine resources and provides a crucial baseline to assess the impact of future development within this region.

We examined if there is truth to the preconceptions that non-resident workers (including FIFO/DIDO’s) detract from communities. We used marine debris to test this, specifically focussing on littering behaviour and evidence of awareness of local environmental programs that focus on marine debris. Littering was most common at recreational areas, then beaches and whilst boating. Twenty-five percent of respondents that admit to littering, reported no associated guilt with their actions. Younger respondents litter more frequently. Thus, non-resident workers litter at the same rate as permanent residents, visitors and tourists in this region, within this study. Few respondents are aware of the environmental programs that operate in their local region. Awareness was influenced by a respondent’s residency (non-residents are less aware), age, and level of education. To address this failure we recommend that industries, that use non-resident workers, should develop inductions that expose new workers to the environmental programs in their region.

Surface sediments from the coastal area of the Leizhou Peninsula in the South China Sea were collected and analyzed and the potential ecological risks in the area were assessed based on acid-volatile sulfide (AVS) model. The AVS levels are between 0.109 and 55.6μmolg−1, with the average at 4.45μmolg−1. The high AVS-concentration zones include the aquaculture areas of Liusha Bay and the densely populated areas of Zhanjiang Bay. The simultaneously extracted metals (SEM) range from 0.026μmolg−1 to 8.61μmolg–1, with the average at 0.843μmolg–1. Most of high SEM-concentration stations were located in ports or aquaculture zones. Most of the coastal surface sediments of the Leizhou Peninsula (90%) had no adverse biological effects according to the criterion proposed by USEPA (2005); while adverse effects were uncertain in some stations (8%); even in 2 stations (2%) adverse biological effects may be expected.

Global warming effects on seaweed beds are already perceptible. Their geographical distributions greatly depend on water temperatures. To predict future geographical distributions of brown alga, Sargassum horneri, forming large beds in the northwestern Pacific, we referred to future monthly surface water temperatures at about 1.1° of longitude and 0.6° of latitude in February and August in 2050 and 2100 simulated by 12 organizations under an A2 scenario of global warming. The southern limit of S. horneri distribution is expected to keep moving northward such that it may broadly disappear from Honshu Island, the Chinese coast, and Korean Peninsula in 2100, when tropical Sargassum species such as Sargassum tenuifolium may not completely replace S. horneri. Thus, their forests in 2100 do not substitute those of S. horneri in 2000. Fishes using the beds and seaweed rafts consisting of S. horneri in East China Sea suffer these disappearances.

Preliminary impact assessment of two large oil spill incidents at Bodo Creek, in the Niger Delta, was undertaken, focusing on intertidal macrozoobenthos. Post-spill number of species and abundance were measured against recent pre-spill baseline data from the same study area. Results show that surface and infauna communities suffered severe reduction in abundance and number of species reduced by 81% after the spills, with two of the resampled sites having no taxa at all. Capitella capitata populations increased several-fold over pre-spill numbers. The impact of the oil spills is discussed in relation to local livelihoods and ecosystem integrity. The Niger Delta endemic lucinid, Keletistes rhizoecus, is proposed as a potential bioindicator for monitoring hydrocarbon contamination in Niger Delta estuaries.