Effect of organic amendments on the mobility of trace elements in phytoremediated techno-soils: role of the humic substances

The efficiency of aided phytostabilization using organic amendments such as ramial chipped wood (RCW) and composted sewage sludge (CSS) was studied on contaminated techno-soils, on nine experimental plots. The objective was to characterize the role of fulvic (FA) and humic acids (HA) on the mobilization of trace elements, specifically As, Cu, Mo, Pb and Zn. Results showed that the addition of CSS increased the total organic carbon and nitrogen content more than with RCW and as a result, the C/N ratio in the CSS soil was higher than in the RCW and non-amended (NE) soil, reflecting the high decomposition of soil organic matter in the CSS soil compared with the other soils. The RCW and CSS amendments increased the hydrogen index (HI) values and the oxygen index (OI) values compared with the NE soil, especially for the soil treated with CSS which contained more aliphatic than aromatic compounds. The addition of CSS to the techno-soil significantly increased the percentage of C _org associated with the HA fractions compared with the RCW and NE soils. The soil amended with CSS showed the highest E ₄/E ₆ ratio and the lowest E ₂/E ₃ ratio of FA. Zn and As were more abundant in the FA fraction than in the HA fraction, whereas Pb, Cu and Mo were more associated to HA than to FA in the treated and untreated soils, which may explain the difference in their mobility and availability.     

Carbon mitigation potential and costs of forestry options in Brazil,China, India,Indonesia, Mexico,the Philippines and Tanzania

This paper summarizes studies of carbon (C) mitigation potential and costs of about 40 forestry options in seven developing countries. Each study uses the same methodological approach – Comprehensive Mitigation Assessment Process (COMAP) – to estimate the above parameters between 2000 and 2030. The approach requires the projection of baseline and mitigation land-use scenarios. Coupled with data on a per ha basis on C sequestration or avoidance, and costs and benefits, it allows the estimation of monetary benefit per Mg C, and the total costs and carbon potential. The results show that about half (3.0 Pg C) the cumulative mitigation potential of 6.2 Petagram (Pg) C between 2000 and 2030 in the seven countries (about 200× 10⁶ Mg C yr^-1) could be achieved at a negative cost and the remainder at costs ranging up to $100 Mg C^-1. About 5 Pg C could be achieved, at a cost less than $20 per Mg C. Negative cost potential indicates that non-carbon revenue is sufficient to offset direct costs of these options. The achievable potential is likely to be smaller, however, due to market, institutional, and sociocultural barriers that can delay or prevent the implementation of the analyzed options.     

Effect of long-term fertilization on soil nitrate distribution

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Distribution of atrazine in a crop-soil-groundwater system at Baiyangdian Lake area in China

ＩｎｔｒｏｄｕｃｔｉｏｎＡｔｒａｚｉｎｅ(2ｃｈｌｏｒｏ4ｅｔｈｙｌａｍｉｎｏ6ｉｓｏｐｒｏｐｙｌａｍｉｎｏｓｔｒｉａｚｉｎｅ)ｉｓｏｎｅｏｆｔｈｅｍｏｓｔｗｉｄｅｌｙｕｓｅｄｓｅｌｅｃｔｉｖｅｐｒｅａｎｄｐｏｓｔｅｍｅｒｇｅｎｃｅｈｅｒｂｉｃｉｄｅｓｆｏｒｔｈｅｃｏｎｔｒｏｌｏｆｂｒｏａｄｌｅａｆａｎｄｇｒａｓｓｙｗｅｅｄｓ.ＴｈｉｓｈｅｒｂｉｃｉｄｅｉｓｐｒｉｍａｒｉｌｙｕｓｅｄｉｎｃｏｒｎｃｒｏｐｐｉｎｇｓｙｓｔｅｍｉｎＮｏｒｔｈｅａｓｔａｎｄＮｏｒｔｈｏｆＣｈｉｎａ,ａｎｄａｓｏｆｔｅｎｔｉｍ…     

Effects of cultivation on N2O emission and seasonal quantitative variations of related microbes in a temperate grassland soil

ＩｎｔｒｏｄｕｃｔｉｏｎＡｔｍｏｓｐｈｅｒｉｃｎｉｔｒｏｕｓｏｘｉｄｅ (Ｎ2 Ｏ)ｉｓａｖｅｒｙｒａｄｉｏａｃｔｉｖｅｌｙａｃｔｉｖｅｇｒｅｅｎｈｏｕｓｅｇａｓ,ａｌｓｏｃｏｎｔｒｉｂｕｔｉｎｇｔｏｔｈｅｄｅｐｌｅｔｉｏｎｏｆｏｚｏｎｅｌａｙｅｒｏｆｓｔｒａｔｏｓｐｈｅｒｅ .ＡｔｍｏｓｐｈｅｒｉｃＮ2 Ｏｍａｉｎｌｙｏｒｉｇｉｎａｔｅｄｆｒｏｍｎｉｔｒｉｆｉｃａｔｉｏｎａｎｄｄｅｎｉｔｒｉｆｉｃａｔｉｏｎｉｎｔｅｒｒｅｓｔｒｉａｌｅｃｏｓｙｓｔｅｍｓ.Ｇｒａｓｓｌａｎｄｅｃｏｓｙｓｔｅｍ ,ａｃｃｏｕｎ…     

Atrazine contamination in agricultural soils from the Yangtze River Delta of China and associated health risks

Atrazine is one of the most widely applied and persistent herbicides in the world. In view of limited information on the regional contamination of atrazine in soils in China, this study investigated the spatial distribution and environmental impacts of atrazine in agricultural soils collected from the Yangtze River Delta (YRD) as an illustrative analysis of rapidly developing regions in the country. The results showed that the concentrations of atrazine in the YRD agricultural soils ranged from <1.0 to 113 ng/g dry weight, with a mean of 5.7 ng/g, and a detection rate of 57.7 % in soils. Pesticide factory might be a major source for the elevated levels of atrazine in Zhejiang Province. The contamination of atrazine was closely associated with land use types. The concentrations and detection rates of atrazine were higher in corn fields and mulberry fields than in rice paddy fields. There was no significant difference in compositions of soil microbial phospholipids fatty acids among the areas with different atrazine levels. Positive relationship (R = 0.417, p < 0.05, n = 30) was observed between atrazine and total microbial biomass. However, other factors, such as soil type and land management practice, might have stronger influences on soil microbial communities. Human health risks via exposure to atrazine in soils were estimated according to the methods recommended by the US EPA. Atrazine by itself in all the soil samples imposed very low carcinogenic risks (<10^?6) and minimal non-cancer risks (hazard index <1) to adults and children.     

Spatiotemporal changes and fragmentation of mangroves and its effects on fish diversity in Ca Mau Province (Vietnam)

Mangroves are important economically and ecologically, however mangrove cover has declined dramatically leading to habitat fragmentation and biodiversity loss. Information on mangrove cover change, fragmentation and impacts on fish diversity is poorly understood. The aims of this study are to detect spatiotemporal changes and mangrove status, examine fragmentation changes and associated effects on fish diversity. Landsat images in1989, 2000, and 2013 were used to classify mangrove cover in Ca Mau Province (Vietnam) and validated against high resolution Pleiades imagery. Fragmentation changes in mangrove cover were examined using series of landscape metrics evaluated against fish diversity indices (Simpson’s index, Jaccard’s coefficient and relative abundance). Results show that mangrove cover has declined 24.6% in the province. Currently, high and moderately dense mangroves distribute in southern half of the region while the low density mangroves occurs in the northern half. Over the 24 year study periods, the number of patches and edge density has increased 58% and 53.9%, respectively, while the mean patch size and mean patch edge has decreased 52.3% and 26.6%. Fish diversity in the more highly fragmented mangrove area was 1.78 times lower than the less fragmented mangrove. The study illustrates the applicability of using Landsat satellite imagery for use in mangrove fragmentation studies as well as the impact of fragmentation.     

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.     

Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.     

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.