The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.     

Climate change effect on outdoor ambiences in Iranian cities

In present research work the effect of climate change over the humidex in Iran is analyzed. From this research, we can conclude that the PD_IAQ index showed a special sensibility to changes in temperature and relative humidity, hence, it can be an interesting tool, may be even better than the humidex to show the expected effect of climate change in perception of air quality. Thus, it was found that the humidex expected in the future will be more elevated than that in the preceding period and, on the other hand, the PD_WRC has clearly reached a lower value than in the preceding period. The same effects, other than those using the earlier indexes in a more detailed manner, were observed with the PD_IAQ. This index showed a higher sensitivity to variations in temperature and relative humidity, than the humidex. Finally, the main results obtained must be considered at the time of design and during construction of future buildings, since buildings that are being constructed today will be occupied in the future years of the 2100s.     

Seasonal baseline of nutrients and stable isotopes in a saline lake of Argentina: biogeochemical processes and river runoff effects

The seasonal variability of inorganic and organic nutrients and stable isotopes and their relations with plankton and environmental conditions were monitored in Lake Chasicó. Principal component analysis evidenced the strong influence of the river runoff on several biogeochemical variables. Silicate concentrations were controlled by diatom biomass and river discharge. Higher values of nitrate and soluble reactive phosphorus (SRP) indicated agricultural uses in the river basin. Elevated pH values (～9) inhibiting nitrification in the lake explained partially the dominance of ammonium: ～83 % of dissolved inorganic nitrogen (DIN). The low DIN/SRP ratio inferred nitrogen limitation, although the hypotheses of iron and CO₂ limitation are relevant in alkaline lakes. Particulate organic matter (POM) and dissolved organic matter (DOM) were mainly of autochthonous origin. The main allochthonous input was imported by the river as POM owning to the arid conditions. Dissolved organic carbon was likely top-down regulated by the bacterioplankton grazer Brachionus plicatilis. The δ¹³C signature was a good indicator of primary production and its values were influenced probably by CO₂ limitation. The δ¹⁵N did not evidence nitrogen fixation and suggested the effects of anthropogenic activities. The preservation of a good water quality in the lake is crucial for resource management.     

Attribution of Carbon Dioxide Fluxes to Crop Types in a Heterogeneous Agricultural Landscape of Argentina

The increasing proportion of agricultural lands worldwide makes it necessary to intensify the research concerning the carbon exchange at agricultural sites. In order to determine the Net Ecosystem Exchange (NEE) in an agricultural landscape in the province of Buenos Aires, Argentina, we carried out eddy covariance measurements with a flux tower, which was placed between two agricultural fields. Therefore, the measured CO₂ flux represents the accumulated flux from both areas, i.e., from different crop types. We here present an analysis method which attributes the flux to the two crop types. For this analysis, we applied the Hsieh footprint model to identify the contributing source area to the flux measurement. We then applied a multiple regression analysis to calculate the NEE in the growing season 2011/2012 for each field separately. The pronounced differences in the time courses of the CO₂ fluxes in the two fields can be explained by the different sowing times and different growth stages of both cultivations. The time courses furthermore show that the CO₂ uptake of the plants was strongly affected by the drought which lasted from December 2011 to January 2012. For the growth cycle of maize (216 days), the NEE was ?240 g C m^?2 and for the growth cycle of soybean (154 days) ?231 g C m^?2. In order to obtain the NEE of a complete agricultural cycle (from harvest to harvest), we also considered the NEE of autumn and winter 2011. Uncertainties of the spatially partitioned NEE are quantified and discussed.     

A methodology to identify representative configurations of sensors for monitoring soil moisture

Soil moisture is the key link among hydroecological compartments, responding dynamically to sequences of atmospheric processes and management conditions and modulating physical, chemical, and biological processes in the soil. Currently, there are a variety of monitoring techniques to measure, directly or indirectly, the soil moisture. However, some practical issues remain open like the definition a priori of the number, location and depth of the monitoring points, and the impact of failing or poor performance soil moisture sensors. Here, we present a set of techniques, namely Δθ time series, wavelet filtering, and time stability, to identify representative points and monitoring depths through an analysis of hourly soil moisture time series for different configuration of the monitoring network. We used real data from a monitoring network consisting of seven monitoring points, each one with four EC-5 probes (Decagon Devices Inc., Pullman, WA) at 20, 40, 60, and 100?cm. The use of simple time series of Δθ allowed us to assess the spatiotemporal influence of the monitoring points, while the wavelet periodograms allowed us to get insight about the response of the monitoring points at different time scales. Both methods are easy to implement or adapt to specific conditions, being coherent to the results derived from time stability analysis. For our case study, we concluded that we could reallocate 16 sensors (out of 28) without a significant loss of information. However, the final decision strongly relies on a deep knowledge of the site features and the objectives of the monitoring network.     

Assessment of potential health risk for inhabitants living near a former lead smelter. Part 1: metal concentrations in soils, agricultural crops, and homegrown vegetables

Soil contamination by metals engenders important environmental and health problems in northern France where a smelter (Metaleurop Nord) was in activity for more than a century. This study aims to look at the long-term effects of the smelter after its closedown by combining data on the degree of soil contamination and the quality of the crops grown (agricultural crops and homegrown vegetables) in these soils for a better assessment of the local population’s exposure to Cd, Pb, and Zn. Seven years after the Metaleurop Nord closedown, (1) the agricultural and urban topsoils were strongly contaminated by Cd, Pb, and Zn; (2) the kitchen garden topsoils were even more polluted than the agricultural soils, with great variability in metal concentrations within the gardens studied; (3) a high proportion of the agricultural crops for foodstuffs did not conform with the European legislation; (4) for feedstuffs, most samples did not exceed the Cd and Pb legislation limits, indicating that feedstuffs may be an opportunity for most agricultural produce; and (5) a high proportion of the vegetables produced in the kitchen gardens did not conform with the European foodstuff legislation. The high contamination level of the soils studied continues to be a risk for the environment and the population’s health. A further investigation (part 2) assesses the associated potential health risk for local inhabitants through consumption of homegrown vegetables and ingestion of soil particles by estimating the site-specific human health assessment criteria for Cd and Pb.