Concentrations of disinfection by-products in swimming pool following modifications of the water treatment process: An exploratory study

The formation and concentration of disinfection by-products (DBPs) in pool water and the ambient air vary according to the type of water treatment process used. This exploratory study was aimed at investigating the short-term impact of modifications of the water treatment process on traditional DBP levels (e.g., trihalomethanes (THMs), chloramines) and emerging DBPs (e.g., Halonitromethanes, Haloketones, NDMA) in swimming pool water and/or air. A sampling program was carried to understand the impact of the following changes made successively to the standard water treatment process: activation of ultraviolet (UV) photoreactor, halt of air stripping with continuation of air extraction from the buffer tank, halt of air stripping and suppression of air extraction from the buffer tank, suppression of the polyaluminium silicate sulfate (PASS) coagulant. UV caused a high increase of Halonitromethanes (8.4 fold), Haloketones (2.1 fold), and THMs in the water (1.7 fold) and, of THMs in the air (1.6 fold) and contributed to reducing the level of chloramines in the air (1.6 fold) and NDMA in the water (2.1 fold). The results highlight the positive impact of air stripping in reducing volatile contaminants. The PASS did not change the presence of DBPs, except for the THMs, which decrease slightly with the use of this coagulant. This study shows that modifications affecting the water treatment process can rapidly produce important and variable impacts on DBP levels in water and air and suggests that implementation of any water treatment process to reduce DBP levels should take into account the specific context of each swimming pool.     

Bioavailability of wastewater derived dissolved organic nitrogen to green microalgae Selenastrum capricornutum, Chlamydomonas reinhardtii, and Chlorella vulgaris with/without presence of bacteria

Effluent dissolved organic nitrogen (DON) is problematic in nutrient sensitive surface waters and needs to be reduced to meet demanding total dissolved nitrogen discharge limits. Bioavailable DON (ABDON) is a portion of DON utilized by algae or algae + bacteria,while biodegradable DON (BDON) is a portion of DON decomposable by bacteria. ABDON and BDON in a two-stage trickling filter (TF) wastewater treatment plant was evaluated using three different microalgal species, Selenastrum capricornutum, Chlamydomonas reinhardtii and Chlorella vulgaris and mixed cultured bacteria. Results showed that up to 80% of DON was bioavailable to algae or algae + bacteria inoculum while up to 60% of DON was biodegradable in all the samples. Results showed that C. reinhardtii and C. vulgaris can be used as a test species the same as S. capricornutum since there were no significant differences among these three algae species based on their ability to remove nitrogen species.     

Asian Urban Environment and Climate Change: Preface

The Asian Network on Climate Science and Technology (www.ancst.org), in collaboration with Tsinghua University, held a conference on environmental and climate science, air pollution, urban planning and transportation in July 2015, with over 40 Asian experts participating and presentation. This was followed by a meeting with local government and community experts on the practical conclusions of the conference. Of the papers presented at the conference a selection are included in this special issue of Journal of Environmental Science, which also reflects the conclusions of the Paris Climate meeting in Dec 2015, when the major nations of the world agreed about the compelling need to reduce the upward trend of adverse impacts associated with global climate change. Now is the time for urban areas to work out the serious consequences for their populations, but also how they should work together to take action to reduce global warming to benefit their own communities and also the whole planet!     

Biodegradation of polycyclic aromatic hydrocarbons (PAHs) by fungal enzymes: A review

Polycyclic aromatic hydrocarbons (PAHs) are a large group of chemicals. They represent an important concern due to their widespread distribution in the environment, their resistance to biodegradation, their potential to bioaccumulate and their harmful effects. Several pilot treatments have been implemented to prevent economic consequences and deterioration of soil and water quality. As a promising option, fungal enzymes are regarded as a powerful choice for degradation of PAHs. Phanerochaete chrysosporium, Pleurotus ostreatus and Bjerkandera adusta are most commonly used for the degradation of such compounds due to their production of ligninolytic enzymes such as lignin peroxidase, manganese peroxidase and laccase. The rate of biodegradation depends on many culture conditions, such as temperature, oxygen, accessibility of nutrients and agitated or shallow culture. Moreover, the addition of biosurfactants can strongly modify the enzyme activity. The removal of PAHs is dependent on the ionization potential. The study of the kinetics is not completely comprehended, and it becomes morem hallenging when fungi are applied for bioremediation. Degradation studies in soil are much more complicated than liquid cultures because of the heterogeneity of soil, thus, many factors should be considered when studying soil bioremediation, such as desorption and bioavailability of PAHs. Different degradation pathways can be suggested. The peroxidases are heme-containing enzymes having common catalytic cycles. One molecule of hydrogen peroxide oxidizes the resting enzyme withdrawing two electrons. Subsequently, the peroxidase is reduced back in two steps of one electron oxidation. Laccases are copper-containing oxidases. They reduce molecular oxygen to water and oxidize phenolic compounds.     

A metal-free composite photocatalyst of graphene quantum dots deposited on red phosphorus

A simple approach to enhance the photocatalytic activity of red phosphorus(P) was developed.A mechanical ball milling method was applied to reduce the size of red P and to deposit graphene quantum dots onto red P. The product was characterized by scanning electron microscopy, transmission electron microscopy, contact angle measurements, zeta-potential measurements, X-ray diffraction and UV–vis absorption spectroscopy. The product exhibited high visible-light-driven photocatalytic performance in the photodegradation of rhodamine B.     

Construction of vesicle CdSe nano-semiconductors photocatalysts with improved photocatalytic activity: Enhanced photo induced carriers separation efficiency and mechanism insight

Visible-light-driven photocatalysis as a green technology has attracted a lot of attention due to its potential applications in environmental remediation. Vesicle Cd Se nano-semiconductor photocatalyst are successfully prepared by a gas template method and characterized by a variety of methods. The vesicle Cd Se nano-semiconductors display enhanced photocatalytic performance for the degradation of tetracycline hydrochloride, the photodegradation rate of78.824% was achieved by vesicle Cd Se, which exhibited an increase of 31.779% compared to granular Cd Se. Such an exceptional photocatalytic capability can be attributed to the unique structure of the vesicle Cd Se nano-semiconductor with enhanced light absorption ability and excellent carrier transport capability. Meanwhile, the large surface area of the vesicle Cd Se nano-semiconductor can increase the contact probability between catalyst and target and provide more surface-active centers. The photocatalytic mechanisms are analyzed by active species quenching. It indicates that h+and UO_2~-are the main active species which play a major role in catalyzing environmental toxic pollutants. Simultaneously, the vesicle Cd Se nano-semiconductor had high efficiency and stability.     

Amoxicillin effects on functional microbial community and spread of antibiotic resistance genes in amoxicillin manufacture wastewater treatment system

This study aimed to reveal how amoxicillin(AMX) affected the microbial community and the spread mechanism of antibiotic resistance genes(ARGs) in the AMX manufacture wastewater treatment system. For this purpose, a 1.47 L expanded granular sludge bed(EGSB) reactor was designed and run for 241 days treating artificial AMX manufacture wastewater. 454 pyrosequencing was applied to analyze functional microorganisms in the system. The antibiotic genes OXA_(-1), OXA_(-2), OXA_(-10), TEM_(-1), CTX-M_(-1), class I integrons(intI1) and 16 SrRNA genes were also examined in sludge samples. The results showed that the genera Ignavibacterium, Phocoenobacter,Spirochaeta, Aminobacterium and Cloacibacillus contributed to the degradation of different organic compounds(such as various sugars and amines). And the relative quantification of eachβ-lactam resistance gene in the study was changed with the increasing of AMX concentration.Furthermore the vertical gene transfer was the main driver for the spread of ARGs rather than horizontal transfer pathways in the system.     

Arsenic biotransformation and an arsenite S-adenosylmethionine methyltransferase in plankton

<正>Arsenic(As)is a well-recognized toxicant and carcinogen.Chronic exposure to inorganic arsenic causes a range of human cancers(e.g.,skin,bladder,and lung)and increases the risk of developing diabetes,hypertension,and cardiovascular and neurological diseases.The prevalence of arsenic species and the severity of their health effects continue to drive and demand for extensive research(Carlin et al.,2016).     

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing–Tianjin–Hebei region, China

In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km~2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m~3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively.     

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers'' information and vehicles'' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.