Integrated catalytic wet air oxidation and aerobic biological treatment in a municipal WWTP of a high-strength o-cresol wastewater

This study examines the feasibility of coupling a Catalytic Wet Air Oxidation (CWAO), with activated carbon (AC) as catalyst, and an aerobic biological treatment to treat a high-strength o-cresol wastewater. Two goals are pursued: (a) To determine the effect of the main AC/CWAO intermediates on the activated sludge of a municipal WasteWater Treatment Plant (WWTP) and (b) To demonstrate the feasibility of coupling the AC/CWAO effluent as a part of the influent of a municipal WWTP. In a previous study, a high-strength o-cresol wastewater was treated by AC/CWAO aiming to establish the distribution of intermediates and the biodegradability enhancement. In this work, the biodegradability, toxicity and inhibition of the most relevant intermediates detected in the AC/CWAO effluent were determined by respirometry. Also, the results of a pilot scale municipal WWTP study for an integrated AC/CWAO-aerobic biological treatment of this effluent are presented. The biodegradation parameters (i.e. maximum oxygen uptake rate and oxygen consumption) of main AC/CWAO intermediates allowed the classification of the intermediates into readily biodegradable, inert or toxic/inhibitory compounds. This detailed study, allowed to understand the biodegradability enhancement exhibited by an AC/CWAO effluent and to achieve a successful strategy for coupling the AC/CWAO step with an aerobic biological treatment for a high-strength o-cresol wastewater. Using 30%, as COD, of AC/CWAO effluent in the inlet to the pilot scale WWTP, the integrated AC/CWAO-biological treatment achieved a 98% of total COD removal and, particularly, a 91% of AC/CWAO effluent COD removal without any undesirable effect on the biomass.     

Heavy metals in untreated/treated urban effluent and sludge from a biological wastewater treatment plant

Background, Aim and Scope

The presence of heavy metals in wastewater is one of the main causes of water and soil pollution. The aim of the present study was to investigate the removal of Cd, Cu, Pb, Hg, Mn, Cr and Zn in urban effluent by a biological wastewater treatment, as well as to quantify the levels of As, Be, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sn, Tl, V and Zn in dewatering sludge from the Biological Wastewater Treatment Plant to Ribeirão Preto (RP-BWTP), Brazil.

Materials and Methods

Concentrations of Cd, Cr, Cu, Mn and Pb in wastewater and those of Ni in sludge were determined by atomic absorption spectrophotometry with graphite furnace atomization. Mercury concentrations in wastewater were measured by hydride generation atomic spectrophotometry, and Zn levels were determined by atomic absorption spectrophotometry using acetylene flame. In sludge, the levels of As, Be, Cd, Cr, Cu, Fe, Hg, Mn, Pb, Sn, Tl, V and Zn were determined by inductively coupled plasma-mass spectrometry.

Results

The percentages of removal efficiency (RE) were the following: Hg 61.5%, Cd 60.0%, Zn 44.9%, Cu 44.2%, PB 39.7%, Cr 16,5% and Mn 10.4%. In turn, the mean concentrations (mg/kg) of metals in dewatering sludge followed this increasing order: Tl (<0.03), Hg (0.31), Be (0.43), As (1.14), Cd (1.34), V (59.2), Pb (132.1), Sn (166.1), Cr (195.0), Mn (208.1), Ni (239.4), Cu (391.7), Zn (864.4) and Fe (20537).

Discussion

The relationship between metal levels in untreated wastewater, as well as the removal efficiency are in agreement with previous data from various investigators, It is important to note that metal removal efficiency is not only affected by metal ion species and concentration, but also by other conditions such as operating parameters, physical, chemical, and biological factors.

Conclusions

Metal values recorded for treated wastewater and sludge were within the maximum permitted levels established by the Environmental Sanitation Company (CETESB), São Paulo, Brazil.

Recommendations

There is an urgent need for the authorities who are responsible for legislation on sludge uses in agriculture of establishing safety levels for As, Be, Hg, Sn, Tl and V.

Perspectives

According to the current metal levels, RP-BWTP sludge might be used for agriculture purposes. However, for an environmentally safe use of sewage sludge, further studies including systematic monitoring are recommended. Annual metal concentrations and predicted variations of those elements in the sludge should be monitored.

     

Critical environmental indicators: performance indices and assessment models for sustainable rural development planning

Sustainable development planning must be based on environmental and biophysical baseline indices that effectively define comparative development potential and environmental constraints. As such, indices must define the comparative advantage of the natural resource base and measure the fundamental capacity to sustain production rates of natural resource goods and services used to create societal well being. Complex biophysical and socioeconomic characteristics affect the identification and selection of sustainable development strategies. When derived from effective baseline indicators, indices may be used to define the spatial and temporal distribution of economically viable production opportunities and may be expressed in derived indices that realistically describe basic production opportunities and guide the selection of feasible, long-term development strategies. Specifically, representative indices are critical in the identification of development goals and realistic objectives and can be used to evaluate, select and implement sustainable development strategies and plans. It is stressed that the relevancy and effectiveness of public policies depend on the identification of representative evaluation models and baseline indices to define development strategies that are both environmentally sustainable and economically viable. In this context, the role of baseline indicators that define natural resource production capacities is discussed. This includes potential resource uses, derived benefits and their economic and environmental impacts. Key thematic indicators are suggested that may be especially useful in identifying development alternatives and impacts. This suggested that clearly defined environmental pollution limits or impact standards be used to define public risk tolerance limits and carrying capacity constraints. It is argued that these measures may be more effective in directing policy choices than economic valuation of non market goods and services that represent environmental externalities associated with resource exploitation options and economic development strategies. To this end, examples of thematic indicators and derived indices are introduced that may prove effective in resource assessment, economic evaluation and strategic development planning.     

固硫生物型煤

研究出生物型煤的生产工艺流程,对型煤和生物型煤的固硫技术进行了研究,成功试验生产出固硫性能优良的生物型煤,为中国煤能源可持续发展利用开辟了新途径。     

关于我国21世纪农业清洁生产的思考

现代工业的出现和工业化进程的不断发展,使生态环境受到污染和破坏。清洁生产因突破了传统的终端污染控制的被动局面,在工业领域得到推广应用。然而,以高度集约化和大量化学物质投入为重要特征的现代农业,所导致的环境污染问题也日益严峻。因此,为达到农业生产与生态环境协调发展的目的,农业清洁生产应成为２１世纪农业发展模式和农业环保策略,其关键是开发绿色农用品,改进农业生产技术。     

武汉市实施清洁生产的方案构想

分析了武汉市工业特点。认为武汉市仍处于工业化加速发展时期,偏重型的工业结构和落后的总体技术水平造成武汉市工业污染严重,布局不合理则加剧了这一状况。为此,结合矿产资源缺管而水资源丰富的资源特点,提出了武汉市实施可持续发展、推行清洁生产的初步方案。（１）调整工业结构的大力发展轻工业,由偏重型结构向轻重工业协调发展转变;（２）对现有产品生产进行深加工,提高含量及其附加值;（３）积极发展高新技术,以此作为     

微波强化CWPO工艺CuO_x-CeO_2/GAC催化剂的制备及其对二甲亚砜的降解

以颗粒活性炭(GAC)为载体、铜为活性组分、铈为助剂组分、草酸钠为沉淀剂,采用浸渍焙烧法制得CuO_x-CeO_2/GAC催化剂。以H_2O_2为氧化剂,微波强化催化湿式过氧化氢氧化(CWPO)处理二甲亚砜(DMSO)初始质量浓度为1 000 mg/L的废水,处理3 min后DMSO去除率达93.8%。催化剂第7次使用时DMSO去除率仍保持在75%以上。初始废水pH在3~9范围内,DMSO去除率均在85%以上。助剂Ce的加入提高了催化剂表面活性组分的分散性和稳定性,使催化剂的活性稳定性和使用寿命显著提高。     

A panel study on the relationship between biofuels production and sustainable development

Biomass is one of the renewable energy sources on which policy makers are greatly dependent on since it is a flexible feedstock capable of conversion into electricity, transport liquid fuels and heat by chemical and biological processes on demand. Though numerous publications have examined the relationship of economic growth with renewable energy and other parameters, biomass energy has never been included in these studies. Then, this study examines the causal relationship within a multivariate panel cointegration/error correction framework which combines the cross-section and time series data while allowing for heterogeneity across different provinces. After employing panel data regression model ranging from 2003 through 2012 to examine the relationships of biofuels production with sustainable development in China, the paper concludes that the development of biofuel energy production integrated with the consideration of the improvement of income per capita, and the attraction of more capital investment, does make a significant contribution to economic growth. However, some negative side effects including the increase of greenhouse emissions and the decrease of marginal land still coexist with the economic development. Of course, the importance of these findings lies on their implications and their adoption on strategic policies.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.