Online detection of waterborne bioavailable copper by valve daily rhythms in freshwater clam Corbicula fluminea

Freshwater clam Corbicula fluminea, a surrogate species in metal toxicity testing, is a promising bioindicator of impairment in aquatic ecosystems. Little is known, however, about the relationship between clam valve daily rhythmic response and metal bioavailability related to a metal biological early warning system (BEWS) design. The purpose of this study was to link biotic ligand model (BLM)-based bioavailability and valve daily rhythm in C. fluminea to design a biomonitoring system for online in situ detection of waterborne copper (Cu). We integrated the Hill-based dose-time-response function and the fitted daily rhythm function of valve closure into a constructed programmatic mechanism. The functional presentation of the present dynamic system was completely demonstrated by employing a LabVIEW graphic control program in a personal computer. We used site-specific effect concentration causing 10% of total valve closure response (EC10) as the detection threshold to implement the proposed C. fluminea-based Cu BEWS. Here our results show that the proposed C. fluminea-based BEWS could be deliberately synthesized to online in situ transmit rapidly the information on waterborne bioavailable Cu levels under various aquatic environmental conditions through monitoring the valve daily rhythmic changes. We suggested that the developed C. fluminea-based dynamic biomonitoring system could assist in developing technically defensible site-specific water quality criteria to promote more efficient uses in water resources for protection of species health in aquatic environments.     

Risk assessment and distribution of soil Pb in Guangdong, China

In this study, the spatial distributions of soil lead (Pb) concentration in three horizontal soils in Guangdong, China, were surveyed and analyzed using geostatistics and geography information systems (GIS). Findings indicated that the Pb geometric mean concentration of 23.3 mg/kg in surface soils was found to be higher than those in global soils, which ranged from 2.3–235 mg/kg. In addition, the Pb geometric mean concentrations from A- to C-horizon were found to be 23.3, 27.2, and 28.6 mg/kg, respectively. The classification of a soil Pb environmental risk in an area was likewise presented based on the different levels of environmental quality of Pb and was done by GIS technology. Accordingly, there is a higher local concentration of Pb in the surrounding areas of Guangzhou where there is higher population density and in the north of Guangdong, which is a historic mining area. The results obtained by the environmental risk assessment reveal that about 46% of total surveyed area was above the background value, that is, 2.7% of the total area was at risk of pollution.     

Preliminary air pollution monitoring in San Miguel, Buenos Aires

Passive diffusion samplers were employed in San Miguel(Buenos Aires Metropolitan Area) for a preliminary airpollution monitoring. The highest loads were observedin downtown, compared with an urban background site.Total suspended particulate matter (TSPM) varied from0.257 to 0.033 mg cm^-2 month^-1; dust was examinedfor particle nature and size distribution. A similartrend was observed for nitrogen dioxide (NO₂) andTSPM spatial distribution, suggesting that traffic isthe major pollution source. Sulphur dioxide (SO₂)values were low and rather homogeneous. Levels for theinvestigated pollutants are below EPA's guide linevalues. Geographic (flat area, near to Rio de LaPlata) and climatologic factors (rainfalls andvariable wind directions) contribute to disperse pollutants.     

Seasonal characteristics of haze observed by continuous visibility monitoring in the urban atmosphere of Kwangju, Korea

Continuous visibility monitoring has been carried out inKwangju, Korea since May 1999. The total light extinctioncoefficient b _ext measured by a transmissometer andreveals seasonal trends in urban visual air quality,especially under hazy conditions with a visual range of lessthan 15 km. Seasonal atmospheric visibility under lowrelative humidity during the winter was observed to be betterthan during any other seasons. Summertime visibility wasseverely degraded due to highly increased light scattering byhygroscopic particles under high humidity atmosphericconditions. Visibility during spring and fall was alsomoderate. However, yellow sand in spring caused the lowestvisibility conditions over the measurement area for a fewdays. With continuous monitoring using the transmissometer,the daily average seasonal visual range was measured to be13.1, 9.2, 11.0, and 13.9 km in spring, summer, falland winter, respectively. Under the atmospheric humiditycondition less than 60%, visual range was observed tobe 16.1, 13.9, 15.1, and 16.6 km in spring, summer,fall, and winter, respectively. The mean light extinctionbudget by sulfate and nitrate aerosols was determined to bethe highest value of 63.71% during the summer and thelowest value of 27.08% during spring. During the `yellow sand dust' period, a mean light extinction budget by soil particles was estimated to be at an unusually high value of 44.22%.     

Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

Cultured human-cell-based bioassay for environmental risk management

Among bioassays for evaluating various impacts of chemicalson humans and ecosystems, those based on culturedmammalian-cells can best predict acute lethal toxicity to humans. Weexpect them to be employed in the future in environmentalrisk management alongside mutagenicity tests and endocrine-disrupting activity tests. We recently developed adisposable bioassay device that immobilizes humanhepatocarcinoma cells in a small micropipette tip. Thisenables very quick (within 2 h) evaluation of acute lethaltoxicity to humans. For bioassay-based environmentalmanagement, 2 promising approaches have been demonstrated bythe US-EPA: toxicity identification evaluation (TIE) andtoxicity reduction evaluation (TRE). The Japanese Ministryof Environment has been supporting a multi-center validationproject, aimed at assembling a bioassay database. To makefull use of these resources, we present a numerical modelthat describes contribution of individual chemical toobserved toxicity. This will allow the selection of the mosteffective countermeasure to reduce the toxicity. Bioassay-based environmental risk management works retrospectively,whereas impact assessment using substance flow models andtoxicity databases works prospective. We expect that these 2approaches will exchange information, act complementarily,and work effectively in keeping our environment healthy inthe 21st century.     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

210Po bioaccumulation in coastal sand dune wild legumes--Canavalia spp. of southwest coast of India

In view of considerable natural background radioactivity reported from southwest coast of India, the current study documents bioaccumulation of 210Po in two dominant coastal sand dune perennial mat-forming wild legumes, Canavalia cathartica and C. maritima. Root, stem, leaf, mature beans, dry seeds and rhizosphere sand were analyzed for 210Po concentration. 210Po activity decreased in the order of leaves > roots > seeds > stems > beans. The highest 210Po activity was recorded in rhizosphere sand samples (5.78-5.88 Bq kg(-1)) followed by the leaf samples (3.27-3.07 Bq kg(-1)), while it was lowest in mature beans (0.13-0.20 Bq kg(-1)). 210Po activities or tissue moisture between plant species were not significantly different (p > 0.05; t-test). But 210Po activity vs. moisture differed significantly in all tissues (p = 0.0001), vegetative tissues (root, stem and leaf) (p = 0.0016), seeds (p = 0.0393) and proteins in seeds (p = 2.355 x 10(-6)) indicating the importance of moisture and protein in 210Po accumulation. Although 210Po has affinity for proteins, it did not concentrate too much in seed proteins of Canavalia. Concentration of 210Po in mature beans is at safe levels as fisher folk only consume tender pods occasionally. 210Po activity in Canavalia is compared with other plant materials. As the landraces of C. cathartica and C. maritima are distributed throughout pantropical coastal areas, the current study emphasizes on considering them as bioindicators to monitor 210Po in coastal sand dune biomes and in turn the health of coastal population.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Modelling of Materials Policies

This paper discusses the REAP1 model and its application for the analysis of CO₂ reduction and waste management policies for Japanese petrochemicals. The pros and cons of this modelling approach in comparison to other tools is elaborated. This is followed by a discussion of the model code and the modelling results. The results show that CO₂ policies can have significant impacts on waste flows and waste policies can have significant CO₂ benefits. As a consequence both effects must be considered in policy assessment. Pricing instruments are recommended instead of regulations because of the complex physical relations in the materials life cycle that extend beyond sector boundaries. A taxation approach is superior to a subsidy approach because rebound effects can be avoided.