Spatial distribution,potential risk assessment,and source apportionment of polycyclic aromatic hydrocarbons (PAHs) in sediments of Lake Chaohu,China

Twenty-nine sediment samples were collected from Lake Chaohu, a shallow eutrophic lake in Eastern China, and were analyzed for 15 priority polycyclic aromatic hydrocarbons (PAHs) to determine the spatial distribution and exposure risks of PAHs. Three receptor models, the principal component analysis-multiple linear regression (PCA-MLR) model, the positive matrix factorization (PMF) model, and the Unmix model, were used in combination with the PAHs diagnostic ratios to investigate the potential source apportionment of PAHs. A clear gradient in the spatial distribution and the potential toxicity of PAHs was observed from west to east in the sediments of Lake Chaohu. ∑₁₅PAH concentrations and the TEQ were in the range of 80.82-30 365.01 ng g^?1 d.w. and 40.77-614.03, respectively. The highest values of the aforementioned variables were attributed to urban–industrial pollution sources in the west lake region, and the levels decreased away from the river inlets. The three different models yielded excellent correlation coefficients between the predicted and measured levels of the 15 PAH compounds. Similarly, source apportionment results were derived from the three receptor models and the PAH diagnostic ratios, suggesting that the highest contribution to the PAHs was from coal combustion and wood combustion, followed by vehicular emissions. The PMF model yielded the following contributions to the PAHs from gasoline combustion, diesel combustion, unburned petroleum emissions, and wood combustion: 34.49, 24.61, 16.11, 13.01, and 11.78 %, respectively. The PMF model produced more detailed source apportionment results for the PAHs than the PCA-MLR and Unmix models.     

Environmental and health impacts of geochemical cycles of persistent toxic substances in food productions systems: Editorial to the special issue for the 8th International Conference on Geochemistry in the Topics & Sub-tropics (GeoTrop 2017)

Environmental Geochemistry and Health -     

Oxidative stress in liver of turtle Mauremys reevesii caused by cadmium

Environmental Science and Pollution Research - The research was designed to examine oxidative stress of the liver of turtle Mauremys reevesii caused by cadmium (Cd). Turtles were injected...     

Establishing eutrophication assessment standards for four lake regions, China

The trophic status assessment of lakes in different lake regions may provide important and fundamental information for lake trophic state classification and eutrophication control. In this study, a region-specific lake eutrophication assessment standard was established through a frequency distribution method based on chlorophyll-a concentration. The assessment standards under the oligotrophic state for lakes in the Eastern plain, Yungui Plateau, Northeast Plain and Mountain Mongolia-Xinjiang regions are total phosphorus of 0.068, 0.005, 0.011, 0.005 mg/L; total nitrogen of 1.00, 0.16, 0.37, 0.60 mg/L; Secchi depth of 0.60, 8.00, 1.55, 3.00 m; and CODMn of 2.24, 1.00, 5.1 l, 4.00 mg/L, respectively. Moreover, a region-specific comprehensive trophic level index was developed to provide an understandable assessment method for the public. The results indicated that the frequency distribution analysis based on chlorophyll-a combined with trophic level index provided a useful metric for the assessment of the lake trophic status. In addition, the difference of eutrophication assessment standards in different lake regions was analyzed, which suggested that the sensitivities of algae to nutrients and the assessment standard of trophic status possessed significant regional differences for the four lake ecoregions. Lake eutrophication assessment standards would contribute to maximizing the effectiveness of future management strategies, to control and minimize lake eutrophication problems.     

Air pollution and body burden of persistent organic pollutants at an electronic waste recycling area of China

Environmental Geochemistry and Health - This paper reviews the concentrations of persistent organic pollutants (POPs) in atmosphere of an electronic waste (e-waste) recycling town, Guiyu, in...     

氢氧化钙清液加氯化钙处理酸性高浓度含氟废水

研究了pH值、氯化钙投加量、搅拌时间及沉淀时间等因素对酸性高浓度含氟废水处理效果的影响;提出了采用氢氧化钙清液加氯化钙作为新型沉淀剂处理酸性高浓度含氟废水的工艺参数：pH值在8．5－9．5,按照nCa／F=0．7加入5％CaCl2溶液,搅拌45min、沉降90min;采用此工艺参数处理氟离子浓度为2600mg／L、pH值为2．97的废水,能把废水氟离子的浓度降至20mg／L以下,达到国家二级排放标准;采用本工艺取代传统工艺的好处是：沉渣中氟化钙纯度高,有利于废水中氟的回收利用。     

炼化企业低温余热利用技术探讨＊

目前炼化企业有大量的低温余热需要回收,了解低温余热的来源、回收途径和技术,对提高低温余热利用效率十分重要。文章对炼厂低温余热的主要来源、利用途径和技术进行综合分析,提出炼厂低温余热回收利用的一些建议。     

Acidic and basic properties and buffer capacity of airborne particulate matter in an urban area of Beijing

Particles with aerodynamic diameters <10  $\upmu $ m (PM₁₀) and particles with aerodynamic diameters <2.5  $\upmu $ m (PM_2.5) were sampled during summer 2006 in Beijing and mass concentrations, water-soluble ionic compounds concentrations, and acidic buffer capacity were analyzed. Results show that the mass concentration ranges of PM₁₀ and PM_2.5 were from 56.4 to 226.6  $\upmu $ g/m³ and from 31.3 to 200.7  $\upmu $ g/m³ during sampling days, respectively. Concentrations of F^???, Cl^???, NO $_{3}^{\,\,-}$ , NO $_{2}^{\,\,-}$ , SO $_{4}^{\,\,2-}$ , Ac^???, Ca^2?+?, Na^?+?, K^?+?, Mg^2?+?, and NH $_{4}^{\,\,+}$ in particles were analyzed by ion chromatography. Microtitration was adapted to determine the acidic?Cbasic property and the change of the buffering systems in different pH of the aqueous solution in which the PM is suspended. The major alkalinity and buffer capacity of particles were analyzed and calculated. The average carbonate buffer capacity was 0.3 mmol/g in PM_2.5 and 0.7 mmol/g in PM₁₀. The average acetic acid buffer capacity was 0.1 mmol/g in PM_2.5 and 0.3 mmol/g in PM₁₀. Carbonate and acetic acid are the main species for the buffer capacity in the particle phase. The average mass of carbonate was 71.0 mg/g in PM₁₀ and 46.7 mg/g in PM_2.5. The average mass of acetic acid was 11.2 mg/g in PM_2.5 and 20.0 mg/g in PM₁₀.     

The abundance,characteristics and diversity of microplastics in the South China Sea: Observation around three remote islands

• A high abundance of floating MPs was found in the southern South China Sea. • Transparent film and fiber were predominant in water and organisms, respectively. • 84.7% of floating MPs and 54.5% of MPs in vivo belonged to PP and PE. • Characteristics of MP in organisms were different from those of inshore ones. Surrounded by emerging markets with considerable plastic consumption, the South China Sea has been a focus area of microplastic research. A survey on the floating microplastics (>0.3 mm) and microplastics ingested by fish and mollusks was conducted around three remote islands here. Compared with the results from several previous studies, a high abundance of floating microplastics (with a median of 1.9 × 10⁵ items/km² or 0.7 items/m³) was observed, revealing another “hot spot” for microplastics. Polyolefin, especially polypropylene, was the main component. The diversity index and evenness index were calculated and evaluated based on the composition of microplastics. The characteristic peaks of Raman spectra concerning pigmented microplastics were provided. Transparent sheets/films were predominant in the water sample, which was quite different from a similar study in this sea area (8.9% for film), and only 16.4% of floating microplastics (>0.3 mm) were fibers/lines, implying that the main sources of floating microplastics (>0.3 mm) might be household/agricultural consumption activities. The transparent fiber/line was also dominant in organisms. It is suggested that the main sources of microplastics ingested by organisms might be both fabric fibers and fishing/aquaculture.     

Development of machine learning multi-city model for municipal solid waste generation prediction

● A database of municipal solid waste (MSW) generation in China was established. ● An accurate MSW generation prediction model (WGMod) was constructed. ● Key factors affecting MSW generation were identified. ● MSW trends generation in Beijing and Shenzhen in the near future are projected. Integrated management of municipal solid waste (MSW) is a major environmental challenge encountered by many countries. To support waste treatment/management and national macroeconomic policy development, it is essential to develop a prediction model. With this motivation, a database of MSW generation and feature variables covering 130 cities across China is constructed. Based on the database, advanced machine learning (gradient boost regression tree) algorithm is adopted to build the waste generation prediction model, i.e., WGMod. In the model development process, the main influencing factors on MSW generation are identified by weight analysis. The selected key influencing factors are annual precipitation, population density and annual mean temperature with the weights of 13%, 11% and 10%, respectively. The WGMod shows good performance with R² = 0.939. Model prediction on MSW generation in Beijing and Shenzhen indicates that waste generation in Beijing would increase gradually in the next 3–5 years, while that in Shenzhen would grow rapidly in the next 3 years. The difference between the two is predominately driven by the different trends of population growth.