Ecosystem services are present everywhere, green vegetation coverage (or green areas) is one of the primary sources of ecosystem services considering urban areas sustainability and peoples urban life quality. Urban vegetation cover loss decreases the capacity of nature to provision ecosystem services; the loss of urban vegetation is also observed within the Amazon. This study aims at identifying urban vegetation loss and relate it to the provision of ecosystem services of reduction of air quality, reduction of air pollution, and climate regulation. Urban vegetation coverage loss was calculated using NDVI on LANDSAT 5 imagery over a 23-year period from 1986 to 2009. NDVI thresholds were arbitrarily selected, and complemented by in locus observation, to establish guidelines for quantitative (area) and qualitative (density) evolution of green cover, divided in six different categories, named as water, bare soil, poor vegetation, moderate vegetation, dense vegetation and very dense vegetation. Data on air pollution, noise pollution and temperature were outsourced from previous works. Measurement show a significant loss of very dense, dense and moderate vegetation coverage and an increase in poor vegetation and bare soil areas, in accordance to increase in air and noise pollution, and local temperature, and provides positive refashions between the loss of urban green coverage and decrease in ecosystem services.

Aluminum dialkyl phosphinates (ADPs) are a class of promising phosphorus-containing flame retardants, but their environmental fate is not well understood. Sorption and transport behaviors of ADPs, and their hydrolysates dialkyl phosphinic acids (DPAs) were studied by batch and column experiments. ADPs are less mobile in soil columns with more than half (>52.6%) of ADPs retained in the soil and residues in the topmost 2-cm layer account for more than 57% of total residues. Dissolution and dispersion of fine grain ADPs were responsible for the transport of ADPs. Sorption DPAs (logKₒc) was significantly related to the lipophilicity of DPAs (logD) (p < 0.05). Soil pH and clay content were the dominant factors governing the sorption and transport of DPAs in soils, indicating the importance of electrostatic interactions. The retardation factors (R) of DPAs derived from leaching experiments were pH-dependent with larger R values in the acidic soil (pH = 4.0) where anionic and neutral species of DPAs coexisted. Both physical and chemical non-equilibrium convection-dispersion equations (CDE) yield appropriate modeling for DPAs transport. In most cases, R values estimated from column tests differed from those derived from the batch experiments, which might be attributed to non-equilibrium sorption processes in dynamic conditions.

Organic pollutants in the Arctic seas have been of concern to many researchers; however, the vast dynamic marine water poses challenges to their comprehensive monitoring within appropriate spatial and temporal scales in the Arctic. In this study, on-board passive sampling of organic pollutants using a self-developed device coupled with triolein-embedded cellulose acetate membranes (TECAMs) was performed during an Arctic cruise. The TECAM extracts were used for target analysis of organophosphorus flame retardants (PFRs), and non-target screening of persistent, bioaccumulative, and toxic (PBT) contaminants using two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS). Sixteen chemicals were screened out as PBT contaminants from the 1500 features in the non-target analysis and further identified. Consequently, two chlorinated PFRs (tris(chloroisopropyl)phosphate and tris(1,3-dichloroisopropyl)phosphate) and four PBT contaminants (4-tert-butylphenol, 2-isopropylnaphthalene, 1,1,3-trimethyl-3-phenylindane, and 1-phenylnonan-1-one) were accurately quantified, with the temporally and spatially integrated concentrations ranging from 0.83 ng L⁻¹ to 20.82 ng L⁻¹ in the seawaters. Sources and transport of the contaminants were studied, and ocean current transport (West Spitsbergen Current, WSC) and local sources (human settlement, Arctic oil exploitation, and petroleum fuel emissions) were found to contribute to the presence of the different contaminants. Finally, annual transport fluxes of the contaminants from the North Atlantic to the Arctic Ocean by WSC were estimated, and the results indicate that their hazard to the Arctic should be concerned.

This review evaluates the three dynamic models (biokinetic model: BK, physiologically based pharmacokinetic model: PBPK, and toxicokinetic-toxicodynamic model: TKTD) in our understanding of the key questions in metal ecotoxicology in aquatic systems, i.e., bioaccumulation, transport and toxicity. All the models rely on the first-order kinetics principle of metal uptake and elimination. The BK model basically treats organisms as a single compartment, and is both physiologically and geochemically based. With a good understanding of each kinetic parameter, bioaccumulation of metals in any aquatic organisms can be studied holistically and mechanistically. Modeling efforts are not merely restrained from the prediction of metal accumulation in the tissues, but instead provide the direction of the key processes that need to be addressed. PBPK is more physiologically based since it mainly addresses the transportation, transformation and distribution of metals in the organisms. It can be treated conceptually as a multi-compartmental kinetic model, whereas the physiology is driving the development of any good PBPK model which is no generic for aquatic animals and contaminants. There are now increasingly applications of the PBPK modeling specifically in metal studies, which reveal many important processes that are impossible to be teased out by direct experimental measurements without adequate modeling. TKTD models further focus on metal toxicity in addition to metal bioaccumulation. The TK part links exposure and bioaccumulation, while the TD part links bioaccumulation and toxic effects. The separation of TK and TD makes it possible to model processes, e.g., toxicity modification by environmental factors, interaction between different metals, at both the toxicokinetic and toxicodynamic levels. TKTD models provide a framework for making full use of metal toxicity data, and thus provide more information for environmental risk assessments. Overall, the three models reviewed here will continue to provide guiding principles in our further studies of metal bioaccumulation and toxicity in aquatic organisms.

Enormous research interest is devoted to fabricating three-dimensional graphene-based gels (3D GBGs) toward improved conversion of solar energy by virtue of the intrinsic properties of single graphene and 3D porous structure characteristics. Here, this concise minireview is primarily focused on the recent progress on applications of 3D GBGs, including aerogels and hydrogels, in photocatalytic degradation of pollutants from water and air, such as organic pollutants, heavy metal ions, bacteria and gaseous pollutants. In particular, the preponderances of 3D GBG photocatalysts for environmental pollutants degradation have been elaborated. Furthermore, in addition to discussing opportunities offered by 3D GBG composite photocatalysts, we also describe the existing problems and the future direction of 3D GBG materials in this burgeoning research area. It is hoped that this review could spur multidisciplinary research interest for advancing the rational utilization of 3D GBGs for practical applications in environmental remediation.

Dibenzofuran (DBF) derivatives have caused serious environmental problems, especially those produced by paper pulp bleaching and incineration processes. Prominent for its resilient mutagenicity and toxicity, DBF poses a major challenge to human health. In the present study, a new strain of Pseudomonas aeruginosa, FA-HZ1, with high DBF-degrading activity was isolated and identified. The determined optimum conditions for cell growth of strain FA-HZ1 were a temperature of 30 °C, pH 5.0, rotation rate of 200 rpm and 0.1 mM DBF as a carbon source. The biochemical and physiological features as well as usage of different carbon sources by FA-HZ1 were studied. The new strain was positive for arginine double hydrolase, gelatinase and citric acid, while it was negative for urease and lysine decarboxylase. It could utilize citric acid as its sole carbon source, but was negative for indole and H2S production. Intermediates of DBF 1,2-dihydroxy-1,2-dihydrodibenzofuran, 1,2-dihydroxydibenzofuran, 2-hydroxy-4-(3′-oxo-3′H-benzofuran-2′-yliden)but-2-enoic acid, 2,3-dihydroxybenzofuran, 2-oxo-2-(2′-hydrophenyl)lactic acid, and 2-hydroxy-2-(2′-hydroxyphenyl)acetic acid were detected and identified through liquid chromatography-mass analyses. FA-HZ1 metabolizes DBF by both the angular and lateral dioxygenation pathways. The genomic study identified 158 genes that were involved in the catabolism of aromatic compounds. To identify the key genes responsible for DBF degradation, a proteomic study was performed. A total of 1459 proteins were identified in strain FA-HZ1, of which 100 were up-regulated and 104 were down-regulated. A novel enzyme “HZ6359 dioxygenase”, was amplified and expressed in pET-28a in E. coli BL21(DE3). The recombinant plasmid was successfully constructed, and was used for further experiments to verify its function. In addition, the strain FA-HZ1 can also degrade halogenated analogues such as 2, 8-dibromo dibenzofuran and 4-(4-bromophenyl) dibenzofuran. Undoubtedly, the isolation and characterization of new strain and the designed pathways is significant, as it could lead to the development of cost-effective and alternative remediation strategies. The degradation pathway of DBF by P. aeruginosa FA-HZ1 is a promising tool of biotechnological and environmental significance.

Effective measures for protecting and preserving the marine environment require an understanding of the potential impact of anthropogenic sound on marine life. A crucial component is a proper assessment of the anthropogenic soundscape: which sounds are present where, when and how strong? We provide an extensive case study modelling the spatial, temporal and spectral distribution of sound radiated by several anthropogenic sources (ships, seismic airguns, explosives) and a naturally occurring one (wind) in the Dutch North Sea. We present the results as a series of sound maps covering the whole of the Dutch North Sea, showing the spatial and temporal distribution of the energy from these sources. Averaged over a two year period, shipping is responsible for the largest amount of acoustic energy (∼1800 J), followed by seismic surveys (∼300 J), explosions (∼20 J) and wind (∼20 J) in the frequency band between 100 Hz and 100 kHz. Our study shows that anthropogenic sources are responsible for 100 times more acoustic energy (averaged over 2 years) in the Dutch North Sea than naturally occurring sound from wind. The potential impact of these sounds on aquatic animals depends not only on these temporally averaged and spatially integrated broadband energies, but also on the source-specific spatial, spectral and temporal variation. Shipping is dominant in the southern part and along the coast in the north, throughout the years and across the spectrum. Seismic surveys are relatively local and spatially and temporally dependent on exploration activities in any particular year, and spectrally shifted to low frequencies relative to the other sources. Explosions in the southern part contribute wide-extent high energy bursts across the spectrum. Relating modelled sound fields to the temporal and spatial distribution of animal species may provide a powerful tool for understanding the potential impact of anthropogenic sound on marine life.

Air pollutants accumulated in confined livestock barns could impact the health of animals and staff. Particulate matter (PM) and ammonia (NH3) concentrations are typically high in enclosed livestock houses with weak ventilation. The objective of this study was to investigate the distribution of PM in different size fractions and the levels of NH3 in a high-rise nursery (HN) barn and a high-rise fattening (HF) barn on a swine farm and to analyse the physicochemical properties of fine PM (PM2.5, PM with aerodynamic diameter ≤ 2.5 μm). The concentrations of total suspended particles (TSP, PM with aerodynamic diameter ≤ 100 μm), inhalable PM (PM10, PM with aerodynamic diameter ≤ 10 μm), PM2.5 and NH3 were monitored continuously for 6 d in each barn. The results showed that the concentrations of PM and NH3 varied with position, they were significantly higher inside the barns than outside (P < 0.01) and significantly higher in the forepart than at the rear of the two barns (P < 0.05). In the HF barn, the values of the two parameters were 0.777 ± 0.2 mg m−3 and 26.7 ± 7 mg m−3, respectively, significantly higher than the values observed in the HN barn at all monitored sites (P < 0.05). The PM concentrations increased markedly during feeding time in the two barns. Chemical characteristics analysis revealed that the main sources of PM2.5 in the two barns may have consisted of blowing dust, feed, mineral particles and smoke. In conclusion, the air quality at the forepart was worse than that at the rear of the barns. Activities such as feeding could increase the PM concentrations. The components of PM2.5 in the two barns were probably blowing dust, feed, mineral particles and smoke from outside.

An accurate estimation of PM2.5 (fine particulate matters with diameters ≤ 2.5 μm) concentration is critical for health risk assessment and generating air pollution control strategies. In this study, a hybrid remote sensing and machine learning approach, named RSRF model is proposed to estimate daily ground-level PM2.5 concentrations, which integrates Random Forest (RF), one of machine learning (ML) models, and aerosol optical depth (AOD), one of remote sensing (RS) products. The proposed RSRF model provides an opportunity for an adequate characterization of real-time spatiotemporal PM2.5 distributions at uninhabited places and complex surfaces. It also offers advantages in handling complicated non-linear relationships among a large number of meteorological, environmental and air pollutant factors, as well as ever-increasing environmental data sets. The applicability of the proposed RSRF model is tested in the Beijing-Tianjin-Hebei region (BTH region) during 2015–2017. Deep Blue (DB) AOD from Aqua-retrieved Collection 6.1 (C_61) aerosol products of Moderate Resolution Imaging Spectroradiometer (MODIS) is validated with Aerosol Robotic Network. The validation results indicate C_61 DB AOD has a high correlation with ground based AOD in the BTH region. The proposed RSRF model performed well in characterizing spatiotemporal variations of annual and seasonal PM2.5 concentrations. It not only is useful to quantify the relationships between PM2.5 and relevant factors such as DB AOD, meteorological and air pollutant variables, but also can provide decision support for air pollution control at a regional environment during haze periods.