Traffic-related air pollutant emissions have become a global environmental problem, especially in urban areas. The estimation of pollutant emissions is based on complex models that require the use of detailed travel-activity data, which is often unavailable and in particular, in developing countries. In order to overcome this issue, an alternative multiple-input–multiple-output general regression neural network model, based on basic socioeconomic and transport related indicators, is proposed for the simultaneous prediction of sulphur oxides (SOx), nitrogen oxides (NOx), ammonia (NH3), non-methane volatile organic compounds (NMVOC) and particulate matter emissions at the national level. The best model, created using only six inputs, has MAPE (mean absolute percentage error) values on testing in the range of 12–15% for all studied pollutants, except NMVOC (MAPE = 21%). The obtained predictions for SOx, NH3 and PM10 emissions were in good agreement with the reported emissions (R2 ≥ 0.93), while the predictions for NOx and NMVOC are somewhat less accurate (R2 ≈ 0.85). It can be concluded that the presented ANN approach can offer a simple and relatively accurate alternative method for the estimation of traffic-related air pollutant emissions.

To determine sources of organic material in semi-enclosed Bohai Sea, samples of marine surface sediments, suspended particulates in adjacent rivers and atmospheric deposition were collected and analyzed for grain size composition, total organic carbon(TOC and POC), total nitrogen (TN and PN), and stable isotopic composition (δ13C and δ15N). Measured bulk C/N ratio (5.50–12.28), δ13C (−23.59~−19.54‰), and δ15N (2.80–8.07‰) values of surface sediment organic materials indicated a mixed source of marine and terrestrial contributions. Spatial distribution of organic C, N and their stable isotope composition indicated a land-sea gradient of organic material content and source combination. Using MixMIR model with dual isotopes, it was estimated that relative contributions of marine, riverine, and atmospheric sources to sediment mixture were 69.0%, 9.6%, and 21.4%, respectively. Our results demonstrated the advantage of Bayesian isotope mixing models over the conventional end-member mixing models for source apportionment in coastal seas with complex source origins.

A glasshouse experiment was designed to investigate the role of bacterial consortia isolated from the endosphere (CE) and rhizosphere (CR) of Arthrocnemum macrostachyum on its metal uptake capacity and tolerance in plants grown in metal polluted sediments. A. macrostachyum plants were randomly assigned to three bioaugmentation treatments (CE, CR and without inoculation) during 120days. Bioaugmentation with both bacterial consortia enhanced A. macrostachyum capacity to accumulate ions in its roots, while shoot ions concentration only increased with CE treatment. Furthermore bioaugmentation ameliorated the phytotoxicity levels, which was reflected in an increment of plant growth of 59 and 113% for shoots and 52 and 98% for roots with CE and CR treatments, respectively. This effect was supported by bacteria beneficial effect on photochemical apparatus and the modulation of its oxidative stress machinery. These findings indicated that bacteria selected from the microbiome can be claimed to improve A. macrostachyum metal remediation efficiency.

This study examined the influence of environmental concentrations of Aroclor 1254 (10, 100, and 1000ng/L) on metamorphosis of Paralichthys olivaceus, and analyzed the mechanisms in relation to thyroid disruption. Results showed that 100 and 1000ng/L Aroclor 1254 delayed metamorphosis and that 1000ng/L Aroclor 1254 caused abnormal morphology. Thyroxine and triiodothyronine levels in the control group were significantly elevated at metamorphic climax, but treatment with 100 and 1000ng/L delayed the increase in thyroid hormones (THs) and retarded metamorphic processes. In larvae exposed to 1000ng/L Aroclor 1254, TH levels at metamorphic climax were significantly lower than those of the control group at the same metamorphic stage. We suggest that the effects of Aroclor 1254 on larval metamorphosis can be explained by disruption of thyroid homeostasis. These findings provide a new perspective and biological model for thyroid-disrupting chemicals (TDCs) screening and investigating interference of thyroid function by TDCs.

PURPOSE OF THE REVIEW: The paper is focused on the prioritization process in noise action plans. The available indicators (noise scores) and methodologies for defining hotspots are analysed and discussed. Indicators and methodologies are classified in order to highlight their suitability for different specific aims. RECENT FINDINGS: The revised annex II of the European Directive 2002/49/EC fixed population exposure and modelling issues leading to different approaches in the prioritization process. Unfortunately, the indicators for rating areas are not commonly defined and a validated procedure is still not recognized at EU level. Furthermore, the importance of considering annoyance in the mitigation process arose, and this paper summarizes the pros and cons of their use for the purpose of prioritization process. A recent attempt to combine annoyance evaluations with limits compliance in noise score for the priority definition is presented. The paper classifies various priority indicators basing on their inclusion of compliance limits compliance, annoyance or both. Then, the methods for merging index values at dwelling for hotspot identification are classified according to their approaches, particularly between those using geometrical approaches, or needing reference administrative areas. The paper highlights the suitability of each method to specific sources, contexts and aims of the prioritization process. Merging methods resulted necessary whenever the epidemiological study is not the aim of the calculation; indeed, the mitigation measures could be planned for delimited and prioritized areas and not directly derived from building noise scores.

Worldwide, crude palm oil industries generate an overwhelming amount of palm oil mill effluent (POME). Since the past few decades, environmental issues associated with POME disposal have challenged the palm oil-producing nations which led them to reevaluate and develop their waste management strategies by using advanced biotreatment technologies. With the help of these technological advances, POME has emerged as a valuable biomass resource with great potential to produce sustainable renewable resources like biogas. This review entails various POME treatment methods in vogue and offers an insight into their improved applicability potential and pollution mitigation strategies by using proposed improved configurations like ponding system, open digesting tanks, anaerobic digestion based-bioreactors, aerobic anaerobic hybrid bioreactors, and membrane bioreactors. This review paper also gives an overview about the recent advancements in POME treatment bioreactor configurations and emphasizing their scope in large-scale applications on an industrial level. This review also critically analyzes their performance level to achieve the standard POME discharge limit by efficiently removing high COD (chemical oxygen demand), BOD (biological oxygen demand), and TSS (total suspended solid).

In this paper three well known Gaussian dispersion models have been evaluated for a case study of a steel plant using complete and incomplete upper air meteorological data.In developing countries, the availability of surface and upper air meteorological data is limited. AMS/EPA Regulatory Model (AERMOD), Advanced Dispersion Modeling System (ADMS) and Industrial Source Complex Model (ISC3) have been evaluated for both real and estimated upper meteorological data and the results have been compared with field measurements both in the horizontal and vertical directions.The results show significant differences in predicted concentrations when modeling with real (actual) and estimated upper meteorological data. The differences ranged from 100% to 450%. Comparison of model performance suggests that AERMOD and ADMS with real meteorological data produce consistent results in the horizontal direction while ISC3 output over-predicts in general. In AERMOD and ISC3 the predicted concentrations have a similar trend of variation in the vertical direction but in ADMS the concentration variation in the vertical direction exhibited different trends. In general, the ADMS predicted concentrations under-estimated field observations.The paper suggests that upper data must be used for modeling and the default values must be used with care. In absence of upper meteorological data, users could estimate upper meteorological data by different available algorithm rather than only default option of models.

Canadian Arctic and Subarctic regions experience a rapid decrease of sea ice accompanied with increasing shipping traffic. The resulting time-space changes in shipping noise are studied for four key regions of this pristine environment, for 2013 traffic conditions and a hypothetical tenfold traffic increase. A probabilistic modeling and mapping framework, called Ramdam, which integrates the intrinsic variability and uncertainties of shipping noise and its effects on marine habitats, is developed and applied. A substantial transformation of soundscapes is observed in areas where shipping noise changes from present occasional-transient contributor to a dominant noise source. Examination of impacts on low-frequency mammals within ecologically and biologically significant areas reveals that shipping noise has the potential to trigger behavioral responses and masking in the future, although no risk of temporary or permanent hearing threshold shifts is noted. Such probabilistic modeling and mapping is strategic in marine spatial planning of this emerging noise issues.

Phthalates are an emerging class of environmental pollutants whose distribution and effects in aquatic environments are not well characterized. We analyzed intertidal and emerged beach sediments from the Abruzzo coastline, along the Adriatic Sea, finding significant phthalate concentrations in marine sediments. Phthalate baseline levels in the intertidal environment, marked by substantial interplay of sediment, water and air, were determined. We used statistical rank methods to select representative phthalate compositions, for which we derived risk levels for ingestion, dermal absorption and inhalation. Our study shows that phthalates are a major cause of pollution along the Abruzzo coast, with river transport of sediments a continuous source of replenishment. Phthalate concentrations in two specific sites were determined to be of the same order of magnitude as the safety, remediation-warranting, threshold set by Italian law. Phthalates, heavy metals, PAHs appear to be correlated. We discuss possible intervention and mitigation strategies.

The south-eastern Black Sea coast in Turkey was evaluated for marine litter composition and density covering nine beaches during four seasons. The marine litter (>2cm in size), was collected from the coast and categorized into material and usage categories. The data analysis showed that plastic was the most abundant litter (≥61.65%) by count and weight followed by styrofoam and fabric. The marine litter density ranged from 0.03 to 0.58 with a mean (±SD) of 0.16±0.02 items/m2 by count. Based on weight, it varied between 0.44 and 14.74g/m2 with 3.35±1.63. The east side had a higher marine litter density than the west side with significant differences between beaches. The variations due to different seasons were not significant for any beach. The results of this study should provide baseline information about the coastal marine pollution and will assist the mitigation strategies.