Monitoring Air Quality in Mountains: Designing an Effective Network

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.     

Cumulative impact assessment in environmental planning: A coastal wetland watershed example

Several theoretical, analytical, and institutional difficulties have impeded the development and application of the assessment of cumulative environmental impacts. Watershed development on coastal wetlands offers an ideal context for evaluating the land disturbance target approach to cumulative impact assessment. A model land use planning system involving a time series approach was developed for Elkhorn Slough in California. The approach included four major components: evaluation of erosion susceptibility, measurement of land disturbance, establishment of a land disturbance target, and a comparison of existing and target land disturbance values. Further research is needed to test the transferability of the approach in a wide range of coastal watersheds and to verify the applicability of the methods to other cumulative impact problems.     

科技论文的写作

本文介绍了科技论文的写作步骤和基本格式,指出科技论文写作中应注意的事项。     

Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada

Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO₄, and NO₃ concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models.     

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.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

The Chemistry of Soils, Rocks and Plant Bioindicators in Three Ecosystems of the Holy Cross Mountains, Poland

In June of 2000, biogeochemical study was carried out in three ecosystems of the Holy Cross Mountains (south-central Poland). This paper presents element concentrations and stable sulfur (and in one site lead) isotope ratios in rocks, detailed soil profiles, and plant bioindicators including epiphytic lichen Hypogymnia physodes (L.) Nyl., mosses (Pleurozium schreberi (Brid.) Mitt., Hypnum cupressiforme Hedw. S. Str., Hylocomium splendens (Hedw.) B.S.G.), Scots pine (Pinus sylvestris L.), common birch (Betula pendula Roth.), aspen (Populus tremula L.) and English oak (Quercus robur L.). Chemical analyses were performed with ICP-AES and AAS methods in the accredited laboratory (Central Chemical Laboratory of the Polish Geological Institute in Warsaw). The principal objective of this study was to compare the chemical composition of rocks, soils and selected plant bioindicators between investigation sites using the same methods of sample collection, preparation and analyses. The results of this study have shown that there is a high variability in concentrations of elements in plant bioindicators from the same sites that can not be explained only by soil properties or anthropogenic influence. This conclusion indicates that for biomonitoring purposes (especially with vascular plants) we cannot neglect individual features of the species examined.     

Application of a systemic approach to the study of pollution of the Tinto and Odiel rivers (Spain)

The province of Huelva in the SW of Spain presents high environmental contrasts: together with the great abundance of natural spaces, it shows the impacts of historical natural resources exploitation processes. In the Ria of Huelva, the effluents of the chemical industries must be added to the contaminating inputs of the Tinto and Odiel rivers, coming from the acid drainage of the mines located in the Iberian Pyrite Belt. This forced the Environmental Agency (AMA) to elaborate in 1987 an Effluent Remediation Plan in order to negate unacceptable environmental impacts. The application of a grey box systemic analysis to the AMD pollution, undergone by the Tinto and Odiel rivers has allowed to set a conclusive explanation of the sampling results observed for a period of 11 years, thus making available an overall view of the polluting process and, above all, an explanation of its partial aspects.     

Selecting Socio-Economic Metrics for Watershed Management

The selection of social and economic metrics to document baseline conditions and analyze the dynamic relationships between ecosystems and human communities are important decisions for scientists, managers, and watershed citizens. A large variety of social and economic data is available but these have limited use without theoretical frameworks. In this paper, several frameworks for reviewing social-ecosystem relations are offered, namely social sanctions, sense of place, civic structure, and cultural differences. Underlying all of these frameworks are attitudes, beliefs, values, and norms that affect which questions are asked and which indicators are chosen. Much work and significant challenges remain in developing a standard set of spatially based socio-economic metrics for watershed management.     

Factors influencing Aerosol Characteristics over Urban Environment

Atmospheric aerosols are an important contributing factor to turbidity in urban areas besides having impact on health. Aerosol characteristics show a high degree of variability in space and time as anthropogenic share of total aerosol loading is quite substantial and is essential to monitor the aerosol features over long time scales. In the present study extensive observations of columnar aerosol optical depth (AOD), total columnar ozone (TCO) and precipitable water content (PWC) have been carried over a tropical urban city of Hyderabad, India. Significant variations of AOD have been observed during course of the day with low values of AOD during morning and evening hours and high values during afternoon hours. Spectral variation of AOD exhibits high AOD at smaller wavelengths and vice versa except a slight enhancement in AOD at 500 nm. Anomalies in AOD, particulate matter and black carbon concentrations have been observed during May, 2003. Back trajectory analysis of air mass during these episodes suggested variation in air mass trajectories. Analysis of the results suggests that air trajectories from land region north of study area cause high loading of atmospheric aerosols. The results are discussed in the paper.