Nutrients in soil solution following selective logging of a humid tropical ‘terra firme’ forest north of Manaus,Brazil

Sustainable use of the Amazon forest for timber production is conditioned by the effect of logging on the system's nutrient cycling. This paper reports the results of a soil moisture and soil water chemistry monitoring campaign before and immediately after a selective logging which removed 35 m³ wood/ha. Soil moisture was measured using tensiometers, and soil water chemistry using suction samplers in five disturbance classes: tractor tracks, clearing centres, clearing edges, forest edges and untouched forest. The results show that the soil under the tractor tracks and clearings contained more moisture than under the untouched forest. The suction samplers extracted substantially more nitrate, ammonium, calcium, magnesium and potassium from the clearing centres, the tractor tracks and the clearing edges than from the forest sites. The results are explained in terms of altered microbial activity, changes in crown interception and uptake by roots.     

巴西戈亚斯州阿拉瓜亚河中亚马孙河巨龟(Podocnemis expansa)的巢穴布局

在旱季,亚马孙河巨龟(Podocnemis expansa)将巢穴修筑在河槽边缘和内部的广阔沙洲上.这些巢穴在某些沙滩上的某些具体地点的大量聚集表明巢穴位置的选择不是随机的,而是与一些地质状况有关,如沙洲边缘的倾斜度和砂质高台的存在.通向高台顶端的通道或斜坡结构的存在是巢穴位置选择的决定性因素.被侵蚀的以及陡峭的沙滩边缘阻碍了亚马孙河龟到达最理想的筑巢位置.随着时间的推移,沙滩形态的变化会改变巢穴的分布.     

Effects of tertiary treatment by fungi on organic compounds in a kraft pulp mill effluent

Background, aim and scope  

Pulp and paper mills generate a plethora of pollutants depending upon the type of pulping process. Efforts to mitigate the environmental impact of such effluents have been made by developing more effective biological treatment systems in terms of biochemical oxygen demand, chemical oxygen demand, colour and lignin content. This study is the first that reports an evaluation of the effects of a tertiary treatment by fungi (Pleurotus sajor caju, Trametes versicolor and Phanerochaete chrysosporium and Rhizopus oryzae) on individual organic compounds of a Eucalyptus globulus bleached kraft pulp and paper mill final effluent after secondary treatment (final effluent).     

The problem of using fixed-area subsampling methods to estimate macroinvertebrate richness: a case study with Neotropical stream data

Subsampling has been widely applied in the laboratory to process freshwater macroinvertebrate samples. Currently, many governmental agencies and research groups apply the fixed-count approach, targeting a number of individuals per sample, and at the same time keeping track of the number of quadrats (fraction of the sample) processed. However, fixed-area methods are still in use. The objective of this paper was to evaluate the reliability of macroinvertebrate taxonomic richness estimates developed from processing a standard number of subsampling quadrats (i.e., fixed-area approaches). We used a dataset from 18 tropical stream sites experiencing three different levels of human disturbance (most-, intermediate-, and least-disturbed). With 12 quadrats processed (half the sample), the collection curves started to stabilize, and for more than half of the sites studied, it was possible to sample at least 80 % of the total taxonomic richness of the sample. However, we observed that the minimum number of quadrats to achieve 80 % of taxonomic richness was strongly negatively correlated with the number of individuals collected in each site: the fewer the individuals in a sample, the greater the processed proportion of that sample needed to represent it properly. Thus our results indicate that for any given areal subsampling effort (any fixed fraction of the sample), samples with different numbers of individuals will be represented differently in terms of the proportion of the total number of taxa of the whole samples, those with greater numbers being overestimated and those with fewer numbers being underestimated. Therefore, we do not recommend the use of fixed-area subsampling methods alone if the main purpose is to measure and analyze taxonomic richness; instead, we encourage researchers to use fixed-count approaches for this purpose.     

Forecasting human exposure to atmospheric pollutants in Portugal – A modelling approach

Air pollution has become one main environmental concern because of its known impact on human health. Aiming to inform the population about the air they are breathing, several air quality modelling systems have been developed and tested allowing the assessment and forecast of air pollution ambient levels in many countries. However, every day, an individual is exposed to different concentrations of atmospheric pollutants as he/she moves from and to different outdoor and indoor places (the so-called microenvironments). Therefore, a more efficient way to prevent the population from the health risks caused by air pollution should be based on exposure rather than air concentrations estimations. The objective of the present study is to develop a methodology to forecast the human exposure of the Portuguese population based on the air quality forecasting system available and validated for Portugal since 2005. Besides that, a long-term evaluation of human exposure estimates aims to be obtained using one-year of this forecasting system application. Additionally, a hypothetical 50% emission reduction scenario has been designed and studied as a contribution to study emission reduction strategies impact on human exposure.To estimate the population exposure the forecasting results of the air quality modelling system MM5-CHIMERE have been combined with the population spatial distribution over Portugal and their time-activity patterns, i.e. the fraction of the day time spent in specific indoor and outdoor places. The population characterization concerning age, work, type of occupation and related time spent was obtained from national census and available enquiries performed by the National Institute of Statistics. A daily exposure estimation module has been developed gathering all these data and considering empirical indoor/outdoor relations from literature to calculate the indoor concentrations in each one of the microenvironments considered, namely home, office/school, and other indoors (leisure activities like shopping areas, gym, theatre/cinema and restaurants). The results show how this developed modelling system can be useful to anticipate air pollution episodes and to estimate their effects on human health on a long-term basis. The two metropolitan areas of Porto and Lisbon are identified as the most critical ones in terms of air pollution effects on human health over Portugal in a long-term as well as in a short-term perspective. The coexistence of high concentration values and high population density is the key factor for these stressed areas. Regarding the 50% emission reduction scenario, the model results are significantly different for both pollutants: there is a small overall reduction in the individual exposure values of PM₁₀ (<10 μg m^?3 h), but for O₃, in contrast, there is an extended area where exposure values increase with emission reduction. This detailed knowledge is a prerequisite for the development of effective policies to reduce the foreseen adverse impact of air pollution on human health and to act on time.     

Bias Correction Techniques to Improve Air Quality Ensemble Predictions: Focus on O3 and PM Over Portugal

Five air quality models were applied over Portugal for July 2006 and used as ensemble members. Each model was used, with its original set up in terms of meteorology, parameterizations, boundary conditions and chemical mechanisms, but with the same emission data. The validation of the individual models and the ensemble of ozone (O₃) and particulate matter (PM) is performed using monitoring data from 22 background sites. The ensemble approach, based on the mean and median of the five models, did not improve significantly the skill scores due to large deviations in each ensemble member. Different bias correction techniques, including a subtraction of the mean bias and a multiplicative ratio adjustment, were implemented and analysed. The obtained datasets were compared against the individual modelled outputs using the bias, the root mean square error (RMSE) and the correlation coefficient. The applied bias correction techniques also improved the skill of the individual models and work equally well over the entire range of observed O₃ and PM values. The obtained results revealed that the best bias correction technique was the ratio adjustment with a 4-day training period, demonstrating significant improvements for both analysed pollutants. The increase in the ensemble skill found comprehends a bias reduction of 88 % for O₃, and 92 % for PM10, and also a decrease in 23 % for O₃ and 43 % for PM10 in what concerns the RMSE. In addition, a spatial bias correction approach was also examined with successful skills comparing to the uncorrected ensemble for both pollutants.     

Monitoring of firefighters exposure to smoke during fire experiments in Portugal

Forest fires represent a serious threat to public security in Europe due to the large burned area. Moreover, smoke pollution due to forest fire events is an important public health issue for the communities directly affected, and particularly for the personnel involved in firefighting operations. Aiming to contribute to the scientific knowledge concerning firefighters exposure to forest fires smoke, data of individual exposure to carbon monoxide, nitrogen dioxide, volatile organic compounds, and particulate matter were obtained during experimental field fires for a group of 10 firefighters equipped with portable “in continuum” measuring devices. Measured values are very high exceeding the Occupational Exposure Standard limits, in particular for peak limit thresholds. These are the first measurements and analysis of firefighter's individual exposure to toxic gases and particles in fire smoke experiments in Europe. However, they already indicate that urgent measures to avoid these levels of exposure are needed.     

Use of neural networks for monitoring surface water quality changes in a neotropical urban stream

This paper reports the using of neural networks for water quality analysis in a tropical urban stream before (2002) and after sewerage building and the completion of point-source control-based sanitation program (2003). Mathematical modeling divided water quality data in two categories: (a) input of some in situ water quality variables (temperature, pH, O2 concentration, O2 saturation and electrical conductivity) and (b) water chemical composition (N-NO2(-); N-NO3(-); N-NH4(+) Total-N; P-PO4(3-); K+; Ca2+; Mg+2; Cu2+; Zn2+ and Fe+3) as the output from tested models. Stream water data come from fortnightly sampling in five points along the Ipanema stream (Southeast Brazil, Minas Gerais state) plus two points downstream and upstream Ipanema discharge into Doce River. Once the best models are consistent with variables behavior we suggest that neural networking shows potential as a methodology to enhance guidelines for urban streams restoration, conservation and management.     

A net water production model for ultrafiltration including flow direction reversal and chemically assisted backwashing.

Flow direction reversal (FDR) was proposed as a novel method to increase net water production (NWP) during cross-flow ultrafiltration. The design of the pilot-plant study allowed measurement of specific flux recovery after each chemically assisted backwash (BW) combined with FDR and after each FDR at the midpoint of each BW/FDR cycle. The percent recovery of specific flux was higher following FDR (55%) than combined BW and FDR (53%) at lower chemical dosages; however, the percent increase in specific flux recovery by FDR was much lower (20%) when the chemical dose was doubled. A mathematical model was developed to predict the NWP achieved by any combination ofBW/ FDR and FDR frequency. For example, the advantage of introducing FDR was demonstrated at the lower chlorine dose, whereby the percent increase in NWP by alternating 15-minute intervals of BW/FDR with FDR over BW/ FDR alone was 10% for 30-minute BW/FDR intervals and 2% for 15-minute BW/FDR intervals.     

Sustainability assessment in the Brazilian Amazon: the municipalities of the state of Amapá

Environment, Development and Sustainability - Although sustainability assessment is widely discussed at Brazil, in Brazilian Amazon its use is still little applied, considering this territory is...