Control of rumen methanogenesis

During the last decades, considerable research on methane production in the rumen and its inhibition has been carried out. Initially, as methane production represents a significant loss of gross energy in the feed (2–15%), the ultimate goal of such intervention in rumen fermentation was an increase in feed efficiency. A second reason favouring research on methane inhibition is its role in the global warming phenomenon and in the destruction of the ozone layer. In this review, the authors describe briefly several interventions for reducing methane emission by ruminants. The objective can be reached by intervention at the dietary level by ration manipulation (composition, feeding level) or by the use of additives or supplements. Examples of additives are polyhalogenated compounds, ionophores and other antibiotics. Supplementation of the ration with lipids also lowered methanogenesis. More biotechnological interventions, e.g., defaunation, probiotics and introduction of reductive acetogenesis in the rumen, are also mentioned. It can be concluded that drastic inhibition of methane production is not unequivocally successful as a result of several factors, such as: instantaneous inhibition often followed by restoration of methanogenesis due to adaptation of the microbes or degradation of the additive, toxicity for the host animal, negative effects on overall digestion and productive performance. Therefore, methanogenesis and its inhibition cannot be considered as a separate part of rumen fermentation and its consequences on the animal should be taken into account.     

The analysis of monitoring data with the aid of time-series analysis

Methods derived from time-series analysis are proposed for processing monitoring data. The necessity for the use of these methods is demonstrated. In a case study time-series analysis was applied to assess the impact of the closure of the Grevelingen estuary (S. W. Netherlands) in 1971 on a local wintering population of Oystercatchers (Haematopus ostralegus) in the adjacent Oosterschelde estuary.Communication No. 328 of the Delta Institute for Hydrobiological Research.     

A study on the behaviour of pesticides and their transformation products in the Scheldt estuary using liquid chromatography-electrospray tandem mass spectrometry

Off-line solid-phase extraction (SPE) combined with liquid chromatography-electrospray tandem mass spectrometry (LC-ESI-MS-MS) was used to study the estuarine behaviour of the polar pesticides, atrazine, chloridazon, diuron and metolachlor, and their transformation products (TPs), hydroxyatrazine (HA), desisopropylatrazine (DIA), desethylatrazine (DEA), 3,4-dichlorophenylmethylurea (DPMU) and monuron. The compounds were identified by comparing their LC retention times and product-ion spectra with those of standard solutions. In all but one case the detection limits of the method were sufficient to determine the compounds of interest over the entire salinity range in the estuary. The concentrations of the dissolved pesticides ranged from 70 ng l-1 for chloridazon to 1350 ng l-1 for diuron. The levels of TPs were 3-8% of the levels of their parent pesticide. The mixing plots of polar pesticides and their TPs indicated that TPs, which are present in fresh river water, are conservatively transported to the sea and that no additional amounts of TPs are formed during their transport through the estuary. The one exception was HA, of which approximately 10% of the amount transported to the North Sea is formed in the lower part of the estuary by photochemical oxidation of atrazine. The latter was concluded from the ratios of each analyte over the sum total of the parent pesticide and all TPs along the salinity gradient, which proved to be a useful tool for identifying such estuarine transformations.     

Analysis of BTEX and other substituted benzenes in water using headspace SPME-GC-FID: method validation

The analysis of BTEX and other substituted benzenes in water samples using solid phase microextraction (SPME) and quantification by gas chromatography with flame ionization detection (GC-FID) was validated. The best analytical conditions were obtained using PDMS/DVB/CAR fibre using headspace extraction (HS-SPME) at 50 [degree]C for 20 min without stirring. The linear range for each compound by HS-SPME with GC/FID was defined. The detection limits for these compounds obtained with PDMS/DVB/CAR fibre and GC/FID were: benzene (15 ng L(-1)), toluene (160 ng L(-1)), monochlorobenzene (54 ng L(-1)), ethylbenzene (32 ng L(-1)), m-xylene (56 ng L(-1)), p-xylene (69 ng L(-1)), styrene (35 ng L(-1)), o-xylene (42 ng L(-1)), m-dichlorobenzene (180 ng L(-1)), p-dichlorobenzene (230 ng L(-1)), o-dichlorobenzene (250 ng L(-1)) and trichlorobenzene (260 ng L(-1)). This headspace SPME-GC-FID method was compared with a previously validated method of analysis using closed-loop-stripping analysis (CLSA). The headspace SPME-GC-FID method is suitable for monitoring the production and distribution of potable water and was used, in field trials, for the analysis of samples from main intakes of water (surface or underground) and from the water supply system of a large area (Lisbon and neighbouring municipalities).     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

The organic composition of diesel particulate matter, diesel fuel and engine oil of a non-road diesel generator

Diesel-powered equipment is known to emit significant quantities of fine particulate matter to the atmosphere. Numerous organic compounds can be adsorbed onto the surfaces of these inhalable particles, among which polycyclic aromatic hydrocarbons (PAHs) are considered potential occupational carcinogens. Guidelines have been established by various agencies regarding diesel emissions and various control technologies are under development. The purpose of this study is to identify, quantify and compare the organic compounds in diesel particulate matter (DPM) with the diesel fuel and engine oil used in a non-road diesel generator. Approximately 90 organic compounds were quantified (with molecular weight ranging from 120 to 350), which include alkanes, PAHs, alkylated PAHs, alkylbenzenes and alkanoic acids. The low sulfur diesel fuel contains 61% alkanes and 7.1% of PAHs. The identifiable portion of the engine oil contains mainly the alkanoic and benzoic acids. The composition of DPM suggests that they may be originated from unburned diesel fuel, engine oil evaporation and combustion generated products. Compared with diesel fuel, DPM contains fewer fractions of alkanes and more PAH compounds, with the shift toward higher molecular weight ones. The enrichment of compounds with higher molecular weight in DPM may be combustion related (pyrogenic).     

Exposure and inhalation risk assessment in an aluminium cast-house

To date the exposure, absorption and respiratory health effects of cast-house workers have not been described since most studies performed in the aluminium industry are focused on exposure and health effects of potroom personnel. In the present study, we assessed the external exposure and the absorbed dose of metals in personnel from the aluminium cast house. This was combined with an evaluation of respiratory complaints and the lung function of the personnel. 30 workers from an aluminium casting plant participated and 17 individuals of the packaging and distribution departments were selected as controls. The exposure was assessed by the quantification of total inhalable fume with metal fraction and by the determination of urinary aluminium, chromium, beryllium, manganese and lead concentration. Carbon monoxide (CO), carbon dioxide (CO2), aldehydes and polyaromatic hydrocarbons and man-made mineral fibres concentration were assessed as well. In order to evaluate their respiratory status each participant filled out a questionnaire and their lung function was tested by forced spirometry. Total inhalable fume exposure was maximum 4.37 mg m(-3). Exposure to the combustion gases, man-made mineral fibres and metal fume was well below the exposure limits. Beryllium could not be detected in the urine. The values of aluminium, manganese and lead in the urine were all under the respective reference value. One individual had a urinary chromium excretion above the ACGIH defined biological exposure index (BEI) of 30 microg g(-1) creatinine. There was no significant difference in any of the categories of the respiratory questionnaire and in the results of the spirometry between cast house personnel and referents (Chi-square, all p > 0.05). Exposure in cast houses seem to be acceptable under these conditions. However, peak exposure to fumes cannot be excluded and the potential risk of chromium and beryllium exposure due to the recycling of aluminium requires further attention.     

Seasonal variations in nickel and vanadium in Mont Blanc snow and ice dated from the 1960s and 1990s

Ni and V have been determined in snow and ice collected at a high altitude location (Col du D?me) near the summit of Mont Blanc on the French-Italian border; dated from the 1960s and 1990s. Ni and V were simultaneously determined by inductively coupled plasma sector field mass spectrometry. Measured concentrations range from 6 to 700 pg g(-1) and 4 to 1,100 pg g(-1) for Ni and V, respectively. The results show pronounced seasonal variations in the concentrations of both metals, with high concentration values in summer layers and much lower values for winter layers. These seasonal variations are linked especially with the existence of inversion layers during winter months. Ni and V concentrations in excess of the contributions from rock and soil dust (Ni(excess), V(excess)) appear to be mainly associated with anthropogenic inputs, with pronounced seasonal variations. Large variations in the V(excess)/Ni(excess) ratio are observed, with a higher ratio in summer than in winter. This shows differences in anthropogenic inputs at Col du D?me during the different parts of the year. The above ratio was compared with the corresponding ratios for oil combustion from stationary sources and the exhaust from gasoline and diesel engines. It appears that Ni and V concentrations at Col du D?me are probably the result of changing combinations of contributions from oil combustion for power generation, industrial and residential uses, on one side, and automobile and truck traffic, on the other side, with possibly a significant contribution from Ni smelters in Russia during winter months.     

上海汽车制造业涂装废气VOCs排放特征

于2015年10月对上海市嘉定区4家(A、B、C、D)汽车制造企业涂装废气ρ(VOCs)和组成特征进行了调查分析。结果表明,A、B、C、D厂涂装废气排放口ρ(VOCs)总为0. 743～6. 11 mg/m~3,主要检出物和最高检出值分别为:A厂二甲苯2. 06 mg/m~3、B厂二甲苯0. 578 mg/m~3、C厂甲苯2. 59 mg/m~3、D厂庚烷0. 274 mg/m~3;芳香烃类是A、B、C厂排放比例最高的VOCs组分,烷烃类是D厂排放比例最高的VOCs组分。指出,原、辅料种类影响排放物的主要成分,废气处理工艺类型影响排放物主要成分和浓度。