Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.     

Is PM10 mass measurement a reliable index for air quality assessment? An environmental study in a geographical area of north-eastern Italy

The aim of this study was to measure the concentration of some metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Ti) in PM(10) samples collected in one urban and one industrial site and to assess that PM(10) total mass measurement may be not sufficient as air quality index due to its complex composition. Metals were determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES) and differential pulsed anodic stripping voltammetry (DPASV). The measured concentrations were used to calculate the content of metals in the PM(10) total mass, and to estimate the enrichment factors and the correlations between PM(10), metal concentrations and meteorological data for the two sites. The mean PM10 concentration during the sampling period in the urban site exceeded the annual European Union (EU) standard (40 microg/m(3)) and, for some sampling days, the daily EU standard (50 microg/m(3)) was also exceeded. In opposite, both EU standards were never exceeded in the industrial site. The overall metal content was nearly double in the industrial site compared to the urban one, and the mean Ni concentration exceeded the EU annual limit value (10 ng/m(3)). The metals with the highest enrichment factor were Cd, Cu, Ni and Pb for both sites, suggesting a dominant anthropogenic source for these metals. Metal concentrations were very low and typical of rural background during Christmas holidays, when factories were closed. PM(10) total mass measurement is not a sufficient air quality index since the metal content of PM(10) is not related to its total mass, especially in sites with industrial activities. This measurement should be associated with the analysis of toxic metals.     

Metal pollution assessment of sediment and water in the Shur River

Intensified industrialization and human activities have resulted in the release of various contaminants into the environment. Among them, heavy metals are often present as a result of mining, milling and industrial manufacturing. In the present investigation, bulk concentrations Pb, Cd, Zn, Cu, Fe, Ca and Al in Shur River (Iran) bed sediments and water around the Sarcheshmeh copper mine were measured from several sample locations. In addition, partitioning was assessed to determine the proportions of metals in different forms. The degree of sediment contamination was evaluated using an Enrichment Factor (EF) and geo-accumulation index (I (geo)) and a newly developed pollution index (I (POLL)). Elevated metals in sediment and water were found to be correlated with areas of the river that were proximal to direct and indirect mining activities. Cadmium and Zn showed the highest pollution index. Cluster analysis was performed in order to assess heavy metal interactions between water and sediment. Chemical partitioning studies revealed that organic metallic bonds were not significantly present in the sediment of the Shur River.     

Emission of isoprene from common Indian plant species and its implications for regional air quality

Isoprene is most dominant volatile organic compounds (VOC) emitted by many plants. In this study 40 common Indian plant species were examined for isoprene emission using dynamic flow through enclosure chamber technique. Isoprene emission rates of plants species were found to vary from undetectable to 69.5 microg g(-1) h(-1) (Madhuca latifolia). Besides, an attempt has been made to evaluate suitability of 80 common Indian plant species for planting programmes. Out of 80 species, 29 species were moderate to high emitters (10 to < or =25 microg g(-1) h(-1)), 12 species were low emitter emitters (1 to < or =10 microg g(-1) h(-1)) and remaining 39 species were found to be negligible or non emitters (<1 microg g(-1) h(-1)) of isoprene. About 50% plant species selected for planting programmes in India were found to be moderate to high emitters of isoprene.     

A Framework for Comprehensive,Integrated, Watershed Monitoring in New York City

The International Life SciencesInstitute (ILSI) Risk Science Institute (RSI) convenedan expert panel of scientists to developrecommendations for a comprehensive monitoring programfor the Croton and Catskill/Delaware watersheds, whichprovide drinking water to New York City's residents. This effort was conducted as part of efforts topreserve and enhance the quality of New York City'sreservoir system through a watershed protectionprogram. The panel developed recommendations for astrategic framework on which to construct a monitoringprogram. As part of this activity, the paneldetermined whether existing monitoring activities weredeficient and, where activities were deficient, thepanel developed recommendations for additionalinformation that should be collected.The panel recommended the development and use of anintegrated approach to watershed monitoring, whichdraws on modeling, risk-based planning and analysis,statistical sampling and design, and basic compliancemonitoring. The approach should be designed toprovide an assessment of natural and anthropogenicsources of stress to the system as well as anassessment of water quality trends in response tostresses acting in concert, both over the long termand over the five-year New York City Memorandum ofAgreement (MOA) assessment time frame. It should alsoprovide an assessment of the human health andenvironmental risks posed by a variety of stressors,and the impact of management actions implemented toameliorate stressors.     

The Vegetation of Wet Meadows in Relation to Their Land-use

Wetland biomonitoring approaches are needed to determine when changes in response to stressors are occurring and to predict the consequences of proposed land-use changes. These approaches require an understanding of shifts in biota that occur in response to land-use, data that are lacking for most kinds of wetlands. Changes in floristic composition corresponding to land-use differences at multiple scales (site to 2500 m radius) were characterized for 40 wet meadows associated with prairie glacial marshes in Minnesota (U.S.A.). In general, guild was more useful than species composition for indicating land-use impacts. Site impacts (stormwater, cultivation) and landscape disturbance (agriculture and urbanization, combined), coincide with a reduction in native graminoid and herbaceous perennial abundance (e.g., Carex lasiocarpa, Calamagrostis canadensis, Spartina pectinata). This vegetation is replaced with annuals (e.g, Bidens cernua, Polygonum pensylvanicum) in recently cultivated sites or introduced perennials (e.g., Phalaris arundinacea, Typha angustifolia) and floating aquatics (lemnids) in stormwater impacted wetlands. Ditches also reduce native perennial importance and increase perennials, but only when they are in highly impacted landscapes.     

Step-up multiple regression model to compute Chlorophyll a in the coastal waters off Cochin, southwest coast of India

The interaction effects of abiotic processes in the production of phytoplankton in a coastal marine region off Cochin are evaluated using multiple regression models. The study shows that chlorophyll production is not limited by nutrients, but their physiological regulations (responses to nutrients, pH, temperature and salinity) are mainly responsible for the increased biological production. The model explaining 77% of variability for chlorophyll a production is indicative of preconditioning of the coastal waters. The phytoplankton production is found to be sensitive to the environment, which varies seasonally. Further, the study suggests that supply of organic matter and grazing of zooplankton (not included) would improve the model efficiency. Despite this, the good agreement in the computed and measured chlorophyll a values shows that step-up multiple regression model is a useful tool to understand the influence of environmental variables on the production of phytoplankton in these coastal waters.     

Migratory crustaceans as biomonitors of metal pollution in their nursery areas. The Lesina lagoon (SE Italy) as a case study

Lichens collected in an unpolluted forest (background) in November 2004, transplanted at 41 sampling sites along the Madina-Tetteh Quarshie road, retrieved in February 2005 and analysed were found to contain higher concentrations of Manganese (Mn), Vanadium (V), lead, Cadmium (Cd), Chromium (Cr) and Nickel (Ni) than in the background area. Observations showed that of all the heavy metals studied, Manganese concentrations were highest at all sampling points with maximum values around a traffic light, an intersection and car fitting/mechanic workshops. Significant correlations were found between Ni and Mn, Mn and Cr and Mn and V. Statistical analysis also revealed a relatively even dispersion of the studied elements on the eastern side of the road than on the western side.     

Small mammals as indicators of short-term and long-term disturbance in mixed prairie

Disturbance by military maneuvers over short and long time scales may have differential effects on grassland communities. We assessed small mammals as indicators of disturbance by military maneuvers in a mixed prairie in southern Oklahoma USA. We examined sites on two soil series, Foard and Lawton, across a gradient of disturbance intensity. A MANOVA showed that abundance of small mammals was associated (p = 0.03) with short-term (cover of vehicle tracks) disturbance but was not associated (p = 0.12) with long-term (loss of soil organic carbon, SOC) disturbance intensity. At the individual species level, Sigmodon hispidus (cotton rat) and Peromyscus maniculatus (deer mouse) occurred across all levels of disturbance and in both soil types. Only P. maniculatus abundance changed (p < 0.01) with short-term disturbance and increased by about one individual per 5% of additional track-cover. Abundance of P. maniculatus also increased (p = 0.04) by about three individuals per 1% increase in soil carbon. Chaetodipus hispidus (hispid pocket mouse) and Reithrodontomys fulvescens (fulvous harvest mouse) only occurred in single soil types limiting their potential as more general indicators. Abundance of P. maniculatus was positively related to shifts in plant species composition and likely reflected changes in vegetation structure (i.e. litter depth) and forage availability resulting from disturbance. Peromyscus maniculatus may be a useful biological indicator of ecosystem change because it responded predictably to both long-term and short-term disturbance and, when coupled with soil, plant, and disturbance history variables, can reveal land condition trends.