New technology has led to new opportunities for a holistic environmental monitoring approach adjusted to purpose and object of interest. The proposed integrated environmental mapping and monitoring (IEMM) concept, presented in this paper, describes the different steps in such a system from mission of survey to selection of parameters, sensors, sensor platforms, data collection, data storage, analysis and to data interpretation for reliable decision making. The system is generic; it can be used by authorities, industry and academia and is useful for planning- and operational phases. In the planning process the systematic approach is also ideal to identify areas with gap of knowledge. The critical stages of the concept is discussed and exemplified by two case studies, one environmental mapping and one monitoring case. As an operational system, the IEMM concept can contribute to an optimised integrated environmental mapping and monitoring for knowledge generation as basis for decision making.

A nitrous oxide (N2O) emission database was compiled for arable land (284 measurements from 62 studies) to establish predictive models for building a greenhouse gas emission inventory in China. Arable lands were grouped into dry land and rice paddy based on the IPCC 2006 guidelines. The results of the meta analysis show that the annual mean N2O fluxes from dry land and rice paddy were 4.69±4.62 (SD) and 5.89±3.23kg N2O–N ha–1 yr–1. Fertilizer–induced N2O emission factors were 0.68±0.41% for dry land, and 0.49±0.43% for rice paddy. The relationship between N2O flux from arable lands and various environmental variables were analyzed, and the magnitude of N2O emissions from zero mineral N addition control plots (background emission) was determined based on precipitation. Based on the above background emissions and correlation coefficients, two new predictive models were established to estimate N2O emissions from arable lands in China. Comparison showed that the precipitation–rectified background emissions could largely improve the model predictions, and the two new models had better performance than the 1996 IPCC guideline method. Therefore, it is strongly recommended that the important local environmental variables be included in the estimates when compiling a national N2O emission inventory.

There has been growing concern about potential health risks from exposure to PM2.5 (fine particulate matter). The importance of conducting simultaneous indoor and outdoor measurements emerged because people, especially in developed countries, spend more than 90% of their time indoors. Great spatial and temporal variations in human exposure to PM2.5 have recently been reported. This review aims to identify the main research areas that have attracted recent attention, any possible gaps in the measurements of PM2.5 in various microenvironments, and the relationships between indoor and outdoor concentrations. This study also provides recommendations for further studies on PM2.5 measurement methods and exposure levels. To achieve these goals, this review included articles published online from 2003 to 2013 in the Science Direct and Web of Science databases. In the initial screening stage, 113 abstracts selected while 61 articles were remained for full review. The reviewed studies consistently showed positive correlations between indoor and outdoor PM2.5. Sulfate/sulfur concentrations were used intensively for calculating the infiltration factor (FINF). The higher FINF indicated high infiltration of outdoor PM2.5 into indoor areas. Great percentage (42%) of the reviewed filter–based studies was conducted in Europe, followed by a similar amount (38%) in the USA, and 20% in Asia, indicating a lack in PM2.5 research in other parts of the world. It was difficult to conclude that ambient fixed–site monitoring provided accurate estimations of actual exposure to PM2.5– Studies shown trends of higher personal concentrations compared to indoor and outdoor ones. Higher indoor levels of OC (organic carbon), compared to outdoor levels, were consistently reported. The opposite trend was true for EC (elemental carbon), and there were higher indoor OC/EC ratios than outdoor OC/EC ratios. There was a consistent general trend of a high (r>0.70) correlation between indoor and outdoor EC, while the correlation between indoor and outdoor OC was much weaker (r=022–0.75). The higher indoor OC/EC ratios, compared to the outdoor OC/EC ratios, reflects multiple sources of indoor OC. Sulfate (SO42–), nitrate (NO3–), and ammonium (NH4+) were primary contributors to PM2.5 mass.

PCBs and PBDEs were determined in two dolphin species, Sotalia guianensis and Steno bredanensis, from an upwelling system off the Central-northern coast of Rio de Janeiro, Brazil. PCB levels varied from 0.040 to 0.75μgg−1lw in muscles and from 0.022 to 1.32μgg−1lw in liver samples from S. guianensis. In S. bredanensis, values varied from 0.085 to 11.3μgg−1lw in muscles and from 0.024 to 18.6μgg−1lw in livers. PCB-138, -153 and -180 were the major PCB congeners detected in both species, while BDE-47 was the predominant PBDE congener found in both species. Higher concentrations in S. bredanensis were possibly related to the different feeding habits for both delphinid species. These results contribute to extend the database on organic contamination in cetaceans from the southern hemisphere, understanding their distribution and environmental fate in Southeastern Brazil.

Groundwater is the main source of drinking water for more than half of the residents of Hanoi (HN). It also provides about one third of the total water demand for residents of Ho Chi Minh City (HCM). However, due to rapid urbanization and frequent discharges of untreated urban wastewater to surface water, freshwater is widely contaminated by man-made chemicals, which may result in groundwater pollution. As part of an ongoing campaign to collect baseline information on the occurrence of organic micro-pollutants (OMPs) in the aquatic environment in Vietnam, 43 water samples were collected from 26 groundwater wells in HN (22) and HCM (4) in September 2013 and August 2014. Samples were analyzed by gas chromatography-mass spectrometry (GC-MS) and the resulting chromatograms were screened for 940 OMPs by an automated identification and quantification system (AIQS) within a GC-MS database. A total of 74 compounds were detected, with between 4 and 43 (median 18) compounds found at each site. Overall, contamination levels were low, with over 89 % of the detected concentrations that were less than 0.5 μg L⁻¹. Results suggest that most of the sampled aquifers have been impacted by non-point source pollution. Most of the contaminants detected are either currently not regulated in drinking water or are present at low levels. A health risk assessment for detected contaminants implied that there were no risks to humans. Since this study was based on a limited number of samples, especially in HCM, further, more detailed studies on the occurrence of OMPs in groundwater in HCM and a full risk assessment of detected contaminants should be prioritized.

An extensive and year-round survey was conducted to assess metal pollution in vast watershed areas of the Selenga River Basin (2007–2009), which provided baseline heavy metal database for the future management. Sources and environmental hazard and risk indices associated with metal pollution were evidenced across the countries of Mongolia and Russia (Buryatia Republic). In general, the concentrations of heavy metals in river water of Mongolia were greater than those of Russia, expect for the upstream of the Dzhida River in Russia. The spatial distribution generally indicated that metal pollution in the Selenga River was mainly associated with the activities in the Mongolian upstream regions. Similar pollution sources of metals between river water and wastewater associated with surrounding activities were found across the industrial and mining areas. Compositional patterns of metals suggested their sources were independent of each other, with hot spots in certain sites. Our measurements indicated that about 63 % of the locations surveyed (48 of 76) exceeded the critical heavy metal pollution index of 100, identifying possible harmful effects on aquatic ecosystems through metal pollution. Zinc was found to be the chemical of priority concern, as more than half of the locations exceeded the corresponding water quality guideline. Other metals including Mn, Fe, Cr, Cu, and As might be problematic in the Selenga River Basin considering the occurrence and their concentrations. Results of our extensive survey during the period of 3 years indicated that urgent action would be necessary in timely manner to improve water quality and mitigate the impact of heavy metals on aquatic environment of the Selenga River Basin.

As the dielectric constant and conductivity of petroleum products are different from those of the pore water in soil, the electrical resistivity characteristics of oil-contaminated soil will be changed by the corresponding oil type and content. The contaminated soil specimens were manually prepared by static compaction method in the laboratory with commercial kaolin clay and diesel oil. The water content and dry density of the first group of soil specimens were controlled at 10 % and 1.58 g/cm³. Corresponding electrical resistivities of the contaminated specimens were measured at the curing periods of 7, 14, and 28 and 90, 120, and 210 days on a modified oedometer cell with an LCR meter. Then, the electrical resistivity characteristics of diesel oil-contaminated kaolin clay were discussed. In order to realize a resistivity-based oil detection method, the other group of oil-contaminated kaolin clay specimens was also made and tested, but the initial water content, oil content, and dry density were controlled at 0~18 %, 0~18 %, 1.30~1.95 g/cm³, respectively. Based on the test data, a resistivity-based artificial neural network (ANN) was developed. It was found that the electrical resistivity of kaolin clay decreased with the increase of oil content. Moreover, there was a good nonlinear relationship between electrical resistivity and corresponding oil content when the water content and dry density were kept constant. The decreasing velocity of the electrical resistivity of oil-contaminated kaolin clay was higher before the oil content of 12 % than after 12 %, which indicated a transition of the soil from pore water-controlled into oil-controlled electrical resistivity characteristics. Through microstructural analysis, the decrease of electrical resistivity could be explained by the increase of saturation degree together with the collapse of the electrical double layer. Environmental scanning electron microscopy (ESEM) photos indicated that the diesel oil in kaolin clay normally had three kinds of effects including oil filling, coating, and bridging. Finally, a resistivity-based ANN model was established based on the database collected from the experiment data. The performance of the model was proved to be reasonably accepted, which puts forward a possible simple, economic, and effective tool to detect the oil content in contaminated clayey soils just with four basic parameters: wet density, dry density, measured moisture content, and electrical resistivity.

The main aim of the study was to test for the presence of Legionnaires’ disease-causing microorganisms in air-conditioned buildings in Kuwait using molecular technologies. For this purpose, 547 samples were collected from 38 cooling towers for the analysis of Legionella pneumophila. These samples included those from water (n = 178), air (n = 231), and swabs (n = 138). Out of the 547 samples, 226 (41 %) samples were presumptive positive for L. pneumophila, with L. pneumophila viable counts in the positive water samples ranging from 1 to 88 CFU/ml. Of the Legionella culture-positive samples, 204 isolates were examined by latex agglutination. These isolates were predominately identified as L. pneumophila serogroup (sg) 2–14. Using the Dresden panel of monoclonal antibodies, 74 representatives isolates were further serogrouped. Results showed that 51 % of the isolates belonged to serogroup 7 followed by 1 (18 %) and 3 (18 %). Serogroups 4 (4 %) and 10 (7 %) were isolated at a lower frequency, and two isolates could not be assigned to a serogroup. These results indicate the wide prevalence of L. pneumophila serogroup 7 as the predominant serogroup at the selected sampling sites. Furthermore, the 74 L. pneumophila (sg1 = 13; sg3 = 13; sg4 = 3; sg7 = 38; sg10 = 5; sgX = 2) isolates were genotyped using the seven gene protocol sequence-based typing (SBT) scheme developed by the European Working Group for Legionella Infections (EWGLI). The results show that Legionella isolates were discriminated into nine distinct sequence typing (ST) profiles, five of which were new to the SBT database of EWGLI. Additionally, all of the ST1 serogroup 1 isolates were of the OLDA/Oxford subgroup. These baseline data will form the basis for the development of a Legionella environmental surveillance program and used for future epidemiological investigations.