Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

Dynamics of growth and seed production in the Siberian stone pine: The level and pattern of variation in characters

A statistical analysis of interannual variation in a set of vegetative and generative characters over 13 years has been performed to characterize the growth and seed production dynamics of the Siberian stone pine (Pinus sibirica Du Tour) in the southeast of the forest zone in western Siberia. The results have shown that the range of fluctuations in most of vegetative characters is ordinary and their distribution is close to normal. The range of fluctuations in many generative characters is enormous (from 0 to +∞), and the distribution of their values is usually skewed, with low values being recorded several times more frequently than high values. Most variable are the proportion of abortive cones and other characters that are determined mainly in the spring of the pollination year. These characters account for a very high level of variation in the total seed production.     

江汉平原粮食开发必须走优质高产高效的道路

分析江汉平原粮食生产的优势与问题,运用商品经济的观念,提出改革开放新形势下加快江汉平原粮食开发的设想,即依托市场,按照价值规律,科学地调整种植业比例和粮食种类结构,发展优质品种,扩大优化模式及采用高新技术等,通过优质、高产、高效,促进江汉平原粮食生产的发展。     

三峡库区几种林下苔藓的保水功能

通过对三峡库区三种森林类型(松栎混交林、栓皮栎纯林、马尾松纯林)林下苔藓储量调查分析及其持水特性试验，得到不同森林类型林下苔藓储量、最大持水量、吸水速率等水文特征参数。结果表明，马尾松纯林林下苔藓储量最大(12．93t／hm^2)，松栎混交林和栓皮栎纯林林下苔藓储量相同(9．47t／hm^2)。松栎混交林林下苔藓最大持水量为5．36mm，栓皮栎纯林为5．73mm，马尾松纯林为6．26mm。研究结果还表明，三峡库区林下苔藓持水量随时间变化过程与森林类型无关。在只有苔藓覆盖情况下，不同森林类型林内不产生水分下渗和地表径流时的最大降雨量和最大降雨雨强分别为：松栎混交林林地5．36mm，5．820mm／h；马尾松纯林林地6．26mm，7．420mm／h；栓皮栎纯林林地5．73mm，6．060mm／h。     

项目决策阶段清洁生产分析方法的研究

企业在建设项目决策时就应该按照清洁生产的原则，从源头控制污染。提出了在项目决策中，应从产品选择、工艺路线选择、主要设备选型和节能降耗4个方面进行清洁生产的分析方法，通过此分析方法的应用，可以避免项目决策中的环境失误和降低企业的环境风险。     

Geochemical characteristics of surficial sediments in a tropical estuary, south-west India

Geochemical characteristics of surficial sediments in the Panangad region of Cochin estuary, the largest brackish-water humid ecosystem in the south-west coast of India, were analysed. Temporal variations in nutrient stoichiometry, seasonal characteristics of redox elements Fe and S, and the phosphorus geochemistry were employed for the purpose. The stoichiometric analysis pointed towards autochthonous origin of organic matter, possibility of nitrogen limitation, and allochthonous modification of redox conditions. Seasonal variations were not statistically significant for all the geochemical parameters, whereas significant spatial variations were observed with lower values at sandy stations, suggesting that the texture of the sediments is the main factor influencing the sediment geochemistry. Significant inter-relations between the geochemical parameters also suggest a common control mechanism. Based on these geochemical characteristics, the study region can be effectively categorized into two distinct zones, viz. (1) erosion and transportation and (2) deposition zones.     

Deep chlorophyll maximum distribution in the central Tyrrhenian Sea described by a towed undulating vehicle

The towed undulating vehicle (TUV), named SARAGO, was used for two fine-scale surveys between the Italian and the Sardinian coasts during the Astraea 2 cruise (6-7 and 26-27 September 1995), studying the deep chlorophyll maximum distribution. SARAGO sections identify a sub-surface doming with higher chlorophyll a and primary production concentrations in the upwelling area of a cyclonic gyre region, detected by sea-surface temperature images. In the first section, the cyclone presents a double doming, in density and salinity, with shallower and concentrated patches of chlorophyll a for about 2 miles. Twenty days later, the second section shows that the gyre changes shape and extension, showing a single doming with higher primary production and chlorophyll a concentrations, distributed over a large area of about 40 nautical miles. SARAGO allows analysis of this high-variability phenomenon (cyclonic gyre) and allows concentrated patches (2 nm) to be identified, thus proving the importance of TUVs in the study of mesoscale processes.     

北京南部城区PM2.5中碳质组分特征

为了解《大气污染防治行动计划》实施后北京市大气PM_2.5中碳质组分特征,于2017年12月至2018年12月在北京污染较重的南部城区进行了PM_2.5连续采样,对其中的有机碳（OC）和元素碳（EC）进行了全面研究.结果表明,北京大气PM_2.5、OC和EC浓度变化范围分别为4.2~366.3、0.9~74.5和0.0~5.5 μg ·m^-3,平均浓度分别为（77.1±52.1）、（11.2±7.8）和（1.2±0.8）μg ·m^-3,碳质组分（OC和EC）整体占PM_2.5的16.1%.OC质量浓度季节特征表现为：冬季[（13.8±8.7）μg ·m^-3] > 春季[（12.7±9.6）μg ·m^-3] > 秋季[（11.8±6.2）μg ·m^-3] > 夏季[（6.5±2.1）μg ·m^-3],EC四季质量浓度水平均较低,范围为0.8~1.5 μg ·m^-3.二次有机碳（SOC）年均质量浓度为（5.4±5.8）μg ·m^-3,四季贡献比例范围为45.7%~52.3%,年均贡献为48.2%,凸显了二次形成的重要贡献.随污染加重,尽管OC和EC贡献比例均降低,但浓度水平却成倍升高,OC和EC浓度在严重污染天分别是空气质量为优天的6.3和3.2倍.与非供暖时段相比,供暖时段PM_2.5、OC和SOC浓度分别增加了14.4%、47.9%和72.1%,体现了OC对供暖季PM_2.5污染的重要贡献.PSCF分析表明,位于北京西南的山西省和河南省部分区域是PM_2.5和OC的主要潜在源区,且PM_2.5潜在源区更为集中;EC的PSCF高值（>0.7）区域较少,主要位于北京南部,如山东省和河南省部分地区,且北京市及周边地区贡献明显.     

废塑料再生过程废水中微塑料去除模拟试验

微塑料是一种存在于不同环境介质中的新兴污染物,主要来源于废弃塑料制品,其存在污染范围广、潜在环境污染大的问题.废塑料再生企业生产废水中微塑料浓度远高于其他类型废水,对其生产废水中的微塑料进行处理具有重要的环境意义.模拟废塑料再生过程的生产废水并进行微塑料去除的絮凝沉淀试验,研究絮凝剂投加量、pH、水力快速搅拌条件的单因素和正交试验对废水中微塑料去除率及其各因素作用的影响.结果表明:①当PAC (聚合氯化铝)投加量为10 mL,PAM (聚丙烯酰胺)投加量为7 mL,pH为9,水力快速搅拌条件为100 r/min下维持40 s再200 r/min下维持40 s时,微塑料的总去除率最高,达91%.②PAC投加量是影响微塑料去除效果的主要因素,其次是pH.③微塑料的去除率与其本身的密度有关,密度大的ABS (acrylonitrile butadiene styrene,丙烯腈-丁二烯-苯乙烯)去除率最高,密度小的PE (polyethylene,聚乙烯)去除率最低.④不同粒径区间的微塑料去除率区别较大,粒径小(0.1~0.25 mm)的微塑料去除效果最好.研究显示,通过控制PAC和PAM的投加量、pH和水力搅拌速率等条件,能够有效将废水中的微塑料通过絮凝沉淀的方法去除,从而达到净化含微塑料生产废水的目的.      

典型西南工业城市春冬季PM2.5来源与潜在源区分析——以柳州市为例

为了揭示柳州城区春冬季PM_2.5的来源及其潜在源区分布和贡献,利用2018年24h自动监测数据和气象数据对柳州市大气污染物浓度变化特征进行了分析,并且使用后向轨迹模型（HYSPLIT）对春冬季柳州市PM_2.5逐日72h气流后向轨迹和前向轨迹进行聚类分析,同时结合潜在源贡献因子分析法（WPSCF）和轨迹浓度权重法（WCWT）对其潜在源区和浓度贡献进行了分析.结果显示,（1）在研究期内,不利的主导风向和工业区布局导致研究区PM_2.5在春冬季污染较严重,且工业源和交通源是其主要本地来源;（2）春冬季PM_2.5高值主要来源于西北和东南方向,其中,西北向PM_2.5主要来源于本地排放,且浓度在空间上呈现西高东低的趋势;（3）春季后向轨迹PM_2.5浓度整体大于冬季,春冬季中对柳州市PM_2.5影响最大轨迹均来自东部的短距离输送,而来自西北的气流轨迹输对PM_2.5贡献最低.春冬季柳州市大气PM_2.5通过气流传输对贵州地区大气环境有较大影响;（4）春季,柳州市PM_2.5的主要潜在源区分布在广西东南部、广东中西部、南海沿岸海域、湖南中部、江西西北部、湖北东部及安徽西北部;冬季,主要分布在广西东南部、广东西南部和南海沿岸海域.