Polychlorinated biphenyl (PCB) anaerobic degradation in marine sediments: microcosm study and role of autochthonous microbial communities

Polychlorobiphenyl (PCB) biodegradation was followed for 1 year in microcosms containing marine sediments collected from Mar Piccolo (Taranto, Italy) chronically contaminated by this class of hazardous compounds. The microcosms were performed under strictly anaerobic conditions with or without the addition of Dehalococcoides mccartyi, the main microorganism known to degrade PCBs through the anaerobic reductive dechlorination process. Thirty PCB congeners were monitored during the experiments revealing that the biodegradation occurred in all microcosms with a decrease in hepta-, hexa-, and penta-chlorobiphenyls (CBs) and a parallel increase in low chlorinated PCBs (tri-CBs and tetra-CBs). The concentrations of the most representative congeners detected in the original sediment, such as 245-245-CB and 2345-245-CB, and of the mixture 2356-34-CB+234-245-CB, decreased by 32.5, 23.8, and 46.7 %, respectively, after only 70 days of anaerobic incubation without any bioaugmentation treatment. Additionally, the structure and population dynamics of the microbial key players involved in the biodegradative process and of the entire mixed microbial community were accurately defined by Catalyzed Reporter Deposition Fluorescence In Situ Hybridization (CARD-FISH) in both the original sediment and during the operation of the microcosm. The reductive dehalogenase genes of D. mccartyi, specifically involved in PCB dechlorination, were also quantified using real-time PCR (qPCR). Our results demonstrated that the autochthonous microbial community living in the marine sediment, including D. mccartyi (6.32E+06 16S rRNA gene copy numbers g^?1 sediment), was able to efficiently sustain the biodegradation of PCBs when controlled anaerobic conditions were imposed.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Increasing CACNA1C expression in placenta containing high Cd level: an implication of Cd toxicity

Cadmium (Cd) has known to produce many adverse effects on organs including placenta. Many essential transporters are involved in Cd transport pathways such as DMT-1, ZIP as well as L-VDCC. Fourteen pregnant women participated and were divided into two groups: high and low Cd-exposed (H-Cd, L-Cd) groups on the basis of their residential areas, Cd concentrations in the blood (B-Cd), urine (U-Cd), and placenta (P-Cd). The results showed that the B-Cd and U-Cd were significantly increased in H-Cd group (p < 0.05). Interestingly, the P-Cd in H-Cd group was elevated (p < 0.05) and positively related to their B-Cd and U-Cd values (p < 0.05). However, the mean cord blood Cd (C-Cd) concentration in H-Cd group was not significantly increased about 2.5-fold when comparing to L-Cd group. To determine the Cd accumulation in placental tissues, metallothionein-1A (MT-1A) and metallothionein-2A (MT-2A) expressions were used as biomarkers. The results revealed that mean MT-1A and MT-2A mRNAs and MT-1/2 proteins were up-regulated in H-Cd group (p < 0.05). In addition, the Ca channel alpha 1C (CACNA1C) mRNA and protein expressions were noticeably elevated in H-Cd group (p < 0.05). From these findings, we suggested that CACNA1C might be implicated in Cd transport in human placenta.     

Vietnam’s seafood boom: Economic growth with impoverishment?

By 2050 most seafood will be sourced through aquaculture, with a range of production intensities being required to sustain livelihoods and to meet future needs from seafood. This makes Vietnam a particularly insightful case, since Vietnam is at the forefront of the trend toward greater aquaculture production. Our aim in this paper is to examine the social-ecological sustainability of small producer livelihoods contributing to Vietnam’s seafood boom. This paper uses original survey data to understand the range of fishery-based livelihoods that have contributed to Vietnam being a leading global exporter of seafood. We investigate the kinds of fishery-based livelihood activities that households are engaged in, consider the type and amount (kilograms) of species caught or farmed annually, and examine household perceptions’ of change in species quantity. We find that Vietnam’s seafood sector is facing real sustainability challenges: Nearly 30 % of small producers—fishers and fish farmers—within our sample rest at or below Vietnam’s rural poverty line. Ecological decline and disease in farmed fish is perceived to be a serious issue for all fishers. In this context, policy and management interventions need to better reflect social and ecological variability, adopt an integrated coastal systems perspective across fisheries and aquaculture, and consider the most impact-effective poverty interventions.     

Climate variability and changes in the major cities of Bangladesh: observations,possible impacts and adaptation

High population density, inadequate infrastructure and low adaptive capacity have made the urban population of Bangladesh highly vulnerable to climate change. Trends in climate and climate-related extreme events in five major cities have been analyzed in this paper to decipher the variability and ongoing changes in urban Bangladesh. An analysis of 55 years (1958–2012) of daily rainfall and temperature data using nonparametric statistical methods shows a significant increase in annual and seasonal mean daily maximum and minimum temperatures in all five cities. A significant increase in climate-related extreme events, such as heavy rainfall events (>20 mm), hot days (>32 °C) and hot nights (>25 °C), is also observed. Climate model results suggest that these trends will continue through the twenty-first century. Vulnerability of urban livelihoods and physical structures to climate change is estimated by considering certainty and timing of impacts. It has been predicted that public health and urban infrastructures, viz. water and power supply, would be the imminent affected sectors in the urban areas of Bangladesh. Adaptation measures that can be adopted to mitigate the negative impacts of climate change are also discussed.     

Expression of copper-resistance genes in microbial communities under copper stress and oxic/anoxic conditions

Microorganisms have developed copper-resistance mechanisms in order to survive in contaminated environments. The abundance and expression of the copper-resistance genes cusA and copA, encoding respectively for a Resistance Cell Nodulation protein and for a P-type ATP-ase pump, was assessed along a gradient of copper concentration in microcosms prepared from Seine estuary mudflat sediment. We demonstrated that the abundance of copA and cusA genes decreased with the increase of copper concentration and that cusA gene was up to ten times higher than the copA gene. Only the copA gene was expressed in both oxic and anoxic conditions. The abundance and activity of the microbial community remained constant whatever the concentrations of copper along the gradient. The molecular phylogeny of the two copper-resistance genes was studied and revealed that the increase of copper increased the diversity of copA and cusA gene sequences.     

Climate change adaptation strategies for transportation infrastructure in Prince George,Canada

Transport infrastructure is particularly vulnerable to climate impacts as it is designed for long operational lives, and both episodic and seasonal conditions contribute to deterioration, disruption and unsafe incidents. There are some examples of adaptation in transportation design, but many communities do not have the capacity to incorporate climate change considerations into infrastructure planning and management. Researchers worked closely with the City of Prince George, in Central British Columbia, Canada, to build on existing work and explore how the City could plan, design, and maintain roads and other structures to account for climate change. A local steering committee was formed, and created and evaluated 23 potential research topics. Two focus areas were selected for further investigation and explored during a workshop with practitioners, researchers, consultants and other representatives. The workshop precipitated an investigation of projected impacts of climate change on road maintenance and road safety, and plans to explore alternative paving techniques. Outcomes of the case study provide insights regarding climate change and local transportation infrastructure, including: how researchers can engage with local experts to explore adaptation; issues local governments perceive as important; and barriers communities face as they attempt to address vulnerabilities.     

Utilizing international networks for accelerating research and learning in transformational sustainability science

A promising approach for addressing sustainability problems is to recognize the unique conditions of a particular place, such as problem features and solution capabilities, and adopt and adapt solutions developed at other places around the world. Therefore, research and teaching in international networks becomes critical, as it allows for accelerating learning by sharing problem understandings, successful solutions, and important contextual considerations. This article identifies eight distinct types of research and teaching collaborations in international networks that can support such accelerated learning. The four research types are, with increasing intensity of collaboration: (1) solution adoption; (2) solution consultation; (3) joint research on different problems; and (4) joint research on similar problems. The four teaching types are, with increasing intensity of collaboration: (1) adopted course; (2) course with visiting faculty; (3) joint course with traveling faculty; and (4) joint course with traveling students. The typology is illustrated by extending existing research and teaching projects on urban sustainability in the International Network of Programs in Sustainability, with partner universities from Europe, North America, Asia, and Africa. The article concludes with challenges and strategies for extending individual projects into collaborations in international networks.