Large measurement networks of Black Carbon (BC) aerosol are important for understanding its impacts on climate and health. PM2.5 filter samples were collected at three urban US locations and one India urban location and were analyzed for Elemental Carbon (EC) and Organic Carbon (OC) concentrations using thermo-optical analysis (TO) following the IMPROVE protocol for US samples and NIOSH protocol for India samples. Site and season-specific calibrations of an inexpensive photo-reference (PR) method were created with TO EC measurements of the US filter samples whereas method-specific calibration was prepared using India filter samples. Piece-wise calibration based on filter loading was also explored. Calibrations were applied across different sites, seasons and methods to determine Root Mean Square Error (RMSE) and average absolute error in each calibration by comparing with reference EC measurements. This paper investigates various calibrations of PR method to improve the agreement between PR method and TO EC measurements. Difference in BC estimated error remained within ±10% among three urban US site-specific calibrations, which suggests that site-specific calibrations are not necessary. Season based calibrations were found to perform best (least RMSE/Mean EC), when applied to same season test samples but resulted in large errors of up to 60% RMSE/Mean EC when applied to different seasons, thus warranting the use of season-specific calibrations of the PR method. RMSE relative to mean EC was 50% when calibration prepared from US samples (IMPROVE protocol) was used to test India samples (NIOSH protocol). However, method-specific calibration prepared from India samples reduced the error to 24%, showing the large dependency of PR method on reference BC measurement method. Calibration based on filter loading reduced the RMSE slightly for both US urban and India samples and indicated that filters with loadings higher than 20 μg cm−2 are not suitable for estimating BC by PR method.

Beijing and Kanpur are two cities identified as high aerosol optical thickness (AOT) and complex composition of aerosols in Asian monsoon regions. Detail knowledge of key aerosol types in these two countries would be helpful for clarifying the mechanisms of aerosol radiative forcing and improving the accuracy of satellite remote sensing in these two countries. This study examines the characteristics of aerosol types over Beijing and Kanpur derived from a 12-year dataset from Aerosol Robotic Network (AERONET) stations and compares them via cluster analysis of optical and microphysical properties. Aerosols in Beijing are more complex than in Kanpur. Four fine-size dominated aerosol types (including two types of moderately absorbing aerosols, one highly absorbing aerosol type and one non-absorbing aerosol type) and one coarse-size dominated aerosol type are identified over Beijing. In Kanpur, two fine-sized dominated aerosol types (one high absorbing aerosol type and one non-absorbing aerosol type) and one coarse-sized dominated aerosol type are obtained. Compared to Beijing, the average SSAs of non-absorbing and high-absorbing aerosols are lower for the four wavelengths (440 nm, 676 nm, 869 nm, 1020 nm) in Kanpur. High absorbing aerosols usually occur in the months December to February (DJF) for both sites. The proportion in Kanpur (14%) is about twice that in Beijing (7%). Non-absorbing aerosols are usually observed in the months June to August (JJA) for both sites. Their proportion in Kanpur (31%) is ∼3 times larger than that in Beijing (11%). Coarse aerosols are frequently observed in the months March to May (MAM) for both sites. Their proportion in Kanpur (54%) is two times larger than in Beijing (21%).

This study aimed to assess the impact of trace element concentrations in fish assemblages of a recovering coastal lagoon. Fish, water and sediment were sampled in winter and summer in the Ria de Aveiro (Portugal). Multivariate analyses were used to examine the relationship between fish assemblages and environmental variables (physical-chemical parameters, contaminants and sediment grain size). In winter, fish density and biomass were mainly affected by the water turbidity, while Li concentration in the water column was found to be significant for fish biomass. During summer, a significant relationship was found between fish density and temperature, Hg, Li and Zn concentration in the sediment. These contaminants were mainly associated with the historically contaminated area, were Liza spp. and Dicentrarchus labrax appeared as dominant species. Environmental variables were not significant for fish biomass. The historical contamination in the Ria de Aveiro still seems to exert some influence on fish community structure.

Surface sediments were collected near potential contamination sources impacting Ribeira Bay (Brazil), a system considered as a ‘reference site’ for trace metals. Physicochemical properties (pH and Eh), grain size and concentrations of total organic carbon (TOC), total phosphorus (TP), acid-volatile sulfides (AVS) and simultaneously-extracted metals (Fe, Mn, Cd, Cu, Ni, Pb and Zn) were analyzed. Although relatively low metal concentrations were found, correlations of Zn and Ni with high TP levels suggested an association with sewage inputs, while other metals presented associations with specific geochemical carriers (TOC, Fe and Mn compounds). AVS levels exceeding those of the sums of Cd, Cu, Ni, Pb and Zn (ΣSEM) by at least one order of magnitude and TOC-normalized differences between ΣSEM and AVS ((ΣSEM–AVS)/fOC) near to or below than −200μmolgOC−1 indicated that there were sufficient AVS and TOC levels to control trace metal bioavailability in sediment pore water.

A risk based approach to assessing compliance with EU limit values is described, using the advanced chemical transport model CMAQ to determine the regional component of NO2 and particulate matter under various conditions over the UK. A new air quality data analysis retrieval tool AirDART is used to extract concentrations for selected areas of the country. Roadside concentrations in a street canyon are then calculated using a dispersion model. The two model calculations need to be combined to obtain concentrations in future years assuming appropriate changes in emission. To merge the local and regional contributions exactly requires assumptions regarding parameterisations and is computationally expensive. From a risk based viewpoint not every possible condition need be considered in order to make policy decisions. Instead future trends under typical conditions are estimated, allowing the direct effect of local action plans and of national measures to be assessed. The approach is applied to London, this being a worst case UK example, to demonstrate the procedure.

Several statistical methods are performed in this study to evaluate the effect of emission control measures on particulate matter (PM) concentrations during the 2014 Asia–Pacific Economic Cooperation (APEC) Summit held in Beijing. The concentration of PM2.5 is reduced by 30%, 38% on a year-on-year and month-on-month basis during the APEC emission control period while PM10 reducing by 41% and 26% respectively. Considering from the impacts of the weather circulation types, PM2.5 and PM10 are both reduced by 34%.ANN model is considered to be appropriate with the ability of characterising non-linear phenomena. In this work an ANN model is built to predict the daily averaged PM concentrations. Comparing the observed PM concentrations and the predicted value which are forecasted by ANN model on condition that no emission control measures were carried out during the APEC, the reductions for PM2.5 and PM10 are 24%, 28% respectively. All these results suggest that strict emission control measures push down the pollution level effectively, and more observed data with long time could improve the accuracy of evaluation results. More stringent controls of regional emissions should be lasted for the continuous improvements of air quality in Beijing-Tianjin-Hebei region.

Sediment characteristics and benthic communities on a finer sampling scale in four contrasting environments in subtropical Hong Kong were analyzed in summer and winter 2012. In two harbour habitats which suffered from historic sewage pollution or hypoxic events, organic carbon, nutrient and trace metal content in the sediment were significantly higher than that in an offshore area and a marine reserve. The relatively low organic and nutrient content in the offshore habitat could be resulted from enhanced resuspension of such materials from the seabed owing to intense water mixing and disturbance caused by bottom trawling. The biotic indices AMBI and M-AMBI were shown to be useful in assessing the benthic ecological status of these habitats. Such indices can also be more sensitive than sediment physico-chemical parameters in differentiating the response of macrofauna to seasonal changes in the benthic environment.

Waste bioremediation is a key regulating ecosystem service, removing wastes from ecosystems through storage, burial and recycling. The bivalve Mytilus edulis is an important contributor to this service, and is used in managing eutrophic waters. Studies show that they are affected by changes in pH due to ocean acidification, reducing their growth. This is forecasted to lead to reductions in M. edulis biomass of up to 50% by 2100. Growth reduction will negatively affect the filtering capacity of each individual, potentially leading to a decrease in bioremediation of waste. This paper critically reviews the current state of knowledge of bioremediation of waste carried out by M. edulis, and the current knowledge of the resultant effect of ocean acidification on this key service. We show that the effects of ocean acidification on waste bioremediation could be a major issue and pave the way for empirical studies of the topic.

Extended use of GC–FID and GC–MS in oil spill fingerprinting and matching is significantly important for oil classification from the oil spill sources collected from various areas of Peninsular Malaysia and Sabah (East Malaysia). Oil spill fingerprinting from GC–FID and GC–MS coupled with chemometric techniques (discriminant analysis and principal component analysis) is used as a diagnostic tool to classify the types of oil polluting the water. Clustering and discrimination of oil spill compounds in the water from the actual site of oil spill events are divided into four groups viz. diesel, Heavy Fuel Oil (HFO), Mixture Oil containing Light Fuel Oil (MOLFO) and Waste Oil (WO) according to the similarity of their intrinsic chemical properties. Principal component analysis (PCA) demonstrates that diesel, HFO, MOLFO and WO are types of oil or oil products from complex oil mixtures with a total variance of 85.34% and are identified with various anthropogenic activities related to either intentional releasing of oil or accidental discharge of oil into the environment. Our results show that the use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution in Malaysia. This, in consequence would result in cost and time saving in identification of the oil spill sources.

A multidisciplinary survey was carried out on the quality of water and sediments of a coastal protected marine area, embedded between the inputs from Bagnoli steel plant to the south and a sewage plant, Volturno River and Regi Lagni channel to the north. The study integrated chemical-sedimentological data with biological and ecotoxicological analyses to assess anthropogenic pressures and natural variability. Data reveal marked differences in anthropogenic pollution between southeastern and northwestern zone, with the north affected by both inorganic and organic flows and the south influenced by levels of As, Pb and Zn in the sediments above law limits, deriving from inputs of the Bagnoli brownfield site. Meiobenthic data revealed at south higher relative abundance of sensitive species to pollution and environmental stress to the south, i.e. Lobatula lobatula and Rosalina bradyi, whereas to the north relative abundance of stress tolerant Quinqueloculina lata, Quinqueloculina pygmaea and Cribroelphidium cuvilleri were determined.