Using a neural network approach and time series data from an international monitoring station in the Yellow Sea for modeling marine ecosystems

The international marine ecological safety monitoring demonstration station in the Yellow Sea was developed as a collaborative project between China and Russia. It is a nonprofit technical workstation designed as a facility for marine scientific research for public welfare. By undertaking long-term monitoring of the marine environment and automatic data collection, this station will provide valuable information for marine ecological protection and disaster prevention and reduction. The results of some initial research by scientists at the research station into predictive modeling of marine ecological environments and early warning are described in this paper. Marine ecological processes are influenced by many factors including hydrological and meteorological conditions, biological factors, and human activities. Consequently, it is very difficult to incorporate all these influences and their interactions in a deterministic or analysis model. A prediction model integrating a time series prediction approach with neural network nonlinear modeling is proposed for marine ecological parameters. The model explores the natural fluctuations in marine ecological parameters by learning from the latest observed data automatically, and then predicting future values of the parameter. The model is updated in a “rolling” fashion with new observed data from the monitoring station. Prediction experiments results showed that the neural network prediction model based on time series data is effective for marine ecological prediction and can be used for the development of early warning systems.     

Oak decline analyzed using intraannual radial growth indices, δ13C series and climate data from a rural hemiboreal landscape in southwesternmost Finland

Decline of pedunculate oak (Quercus robur L.) was studied in SW Finland. This is a region where the species is growing near its northern distributional limit globally and a recent decline of mature trees has been described regionally. Tree rings of declining oaks were compared to the chronologies of healthy and oaks that died, climate series and stable isotope discrimination of carbon (δ¹³C) of comparable mature trees. The radial growth (earlywood, latewood, and annual ring width) of declining oaks was clearly deteriorated in comparison to healthy oaks, but recuperated, compared to oaks that died, through all index types. Comparison of climate relationships between growth and δ¹³C, expected to reflect oaks’ intrinsic water use efficiency, indicated enhancing resistance to droughts through the growing season. The growth and the climatic growth response was differentiated in declining oaks as compared with the healthy and oaks that died revealing that: (1) declining oaks exhibited decreasing competitive strength as indicated by reduced overall growth relative to healthy oaks, (2) the growth of declining oaks was more sensitive to winter conditions, but less restricted by summer droughts than the growth of other oaks, and (3) healthy oaks were seen having benefitted from the ongoing lengthening of the growing season. Lack of correlativity between growth and δ¹³C became evident as their responses to temperature and precipitation variations deviated drastically during the other but summer months. Our results indicate that several different ecological factors, rather than a single climatic factor (e.g., drought), are controlling the oak decline in the studied environment.     

Estimation of the contributions of long range transported aerosol in East Asia to carbonaceous aerosol and PM concentrations in Seoul, Korea using highly time resolved measurements: a PSCF model approach

The contributions of long range transported aerosol in East Asia to carbonaceous aerosol and particulate matter (PM) concentrations in Seoul, Korea were estimated with potential source contribution function (PSCF) calculations. Carbonaceous aerosol (organic carbon (OC) and elemental carbon (EC)), PM(2.5), and PM(10) concentrations were measured from April 2007 to March 2008 in Seoul, Korea. The PSCF and concentration weighted trajectory (CWT) receptor models were used to identify the spatial source distributions of OC, EC, PM(2.5), and coarse particles. Heavily industrialized areas in Northeast China such as Harbin and Changchun and East China including the Pearl River Delta region, the Yangtze River Delta region, and the Beijing-Tianjin region were identified as high OC, EC and PM(2.5) source areas. The conditional PSCF analysis was introduced so as to distinguish the influence of aerosol transported from heavily polluted source areas on a receptor site from that transported from relatively clean areas. The source contributions estimated using the conditional PSCF analysis account for not only the aerosol concentrations of long range transported aerosols but also the number of transport days effective on the measurement site. Based on the proposed algorithm, the condition of airmass pathways was classified into two types: one condition where airmass passed over the source region (PS) and another condition where airmass did not pass over the source region (NPS). For most of the seasons during the measurement period, 249.5-366.2% higher OC, EC, PM(2.5), and coarse particle concentrations were observed at the measurement site under PS conditions than under NPS conditions. Seasonal variations in the concentrations of OC, EC, PM(2.5), and coarse particles under PS, NPS, and background aerosol conditions were quantified. The contributions of long range transported aerosols on the OC, EC, PM(2.5), and coarse particle concentrations during several Asian dust events were also estimated. We also investigated the performance of the PSCF results obtained from combining highly time resolved measurement data and backward trajectory calculations via comparison with those from data in low resolutions. Reduced tailing effects and the larger coverage over the area of interest were observed in the PSCF results obtained from using the highly time resolved data and trajectories.     

Knowledge, data and interests: Challenges in participation of diverse stakeholders in HIA

Stakeholder participation is considered an integral part of HIA. However, the challenges that participation implies in a multi-disciplinary and multi-ethnic society are less studied. This paper presents the manifestations of the multiplicity of sectors and population groups in HIA and discusses the challenges that such diversity imposes. Specifically, there is no common ground between participants, as their positions entail contradictory knowledge regarding the current situation, reliance on distinct data and conflicting interests. This entails usage of multiple professional and ethnic languages, disagreements regarding the definition of health and prioritizing health issues in HIA, and divergent perceptions of risk. These differences between participants are embedded culturally, socially, individually and, maybe most importantly, professionally. This complex picture of diverse stakeholder attributes is grounded in a case study of stakeholder participation in HIA, regarding zoning of a hazardous industry site in Israel. The implication is that participatory HIAs should address the multiplicity of stakeholders and types of knowledge, data and interests in a more comprehensive way.     

Monitoring, assessment and modelling using water quality data in the Saale River Basin, Germany

The European Water Framework Directive (WFD) is the overall driver for this environmental study and currently requires the identification of patterns and sources of pollution (monitoring) to support objective ecological sound decision making and specific measures to enhance river water quality (modelling). The purpose of this paper is to demonstrate in a case study the interrelationship between (1) hydrologic and water quality monitoring data for river basin characterization and (2) modelling applications to assess resources management alternatives. The study deals with monitoring assessment and modelling of river water quality data of the main stem Saale River and its principal tributaries. For a period of 6 years the data, which was sampled by Environmental Agencies of the German states of Thuringia, Saxony and Saxony-Anhalt, was investigated to assess sources and indicators of pollution. In addition to the assessment a modelling exercise of the routing of different pollutants was carried out in the lower part of the test basin. The modelling is a tool to facilitate the evaluation of alternative measures to reduce contaminant loadings and improve ecological status of a water body as required by WFD. The transport of suspended solids, salts and heavy metals was modelled along a selected Saale reach under strong anthropogenic influence in terms of contaminants and river morphology between the city of Halle and the confluence with the Elbe River. The simulations were carried out with the model WASP5 which is a dynamic flood-routing and water quality model package developed by the US Environmental Protection Agency.     

Air Quality in Norwich, UK Multi-Scale Modelling to Assess the Significance of City, County and Regional Pollution Sources

Norwich is the eastern most city in the United Kingdom. Despite a population of only 100,000 and very little local industry, studies have shown that the city experiences levels of nitrogen dioxide, ozone, particulates and sulphur dioxide exceeding the UK Air Quality Standards. Because of Norwich's situation within a large, predominantly rural area a large non-resident workforce is one factor that contributes to large, often very congested traffic flows. The city's location close to the European mainland also exposes it to polluted airmasses transported from the continent, especially in the case of particulates and ozone. In order to assess the relative contributions of local and regional sources, data from rural and urban monitoring sites are to be used in conjunction with ADMS-Urban and the UK Meteorological Office's NAME model.     

基于网格空间数据的晋陕蒙接壤区生态环境综合评价

晋陕蒙接壤区是典型的生态过渡带、生态脆弱带。文章在调查研究的基础上 ,选取了 1 3个评价指标 ,应用层次分析法确定其权重 ,并将各个因子分级标准化和定量赋值 ,再用加权求和法得到每个评价单元的环境质量综合评价指数。根据环境综合评价指数将环境质量分为较好 (≥ 8)、一般 (≥ 6～ <8)、较差 (≥ 4～ <6)、恶劣 (<4) 4级。结果表明 :晋陕蒙接壤区的环境质量大多处于较差等级 ,较好、一般、较差、恶劣等级的面积比例分别为 2 .2 % ,2 8% ,5 7.4%和1 2 .4%     

Testing the validity of a critical sulfur and nitrogen load model in southern Ontario, Canada, using soil chemistry data from MARYP

The validity of a steady-state massbalance model (Arp et al., 1996; referred to asARP) was tested using physicochemical soil data fromthe Monitoring Acid Rain Youth Program (MARYP). FourARP sites were matched with ten MARYP sites accordingto proximity, bedrock type and subsoil pH to test thevalidity of the ARP model for critical loadexceedances. Soil solution pH, base concentration andAl concentration from MARYP sites, which were wellmatched to ARP sites, validated the modelled criticalload exceedances. Higher exceedance areas wereassociated with more acidic pH and lower base andhigher Al concentrations from matched MARYP sites andvice versa. One ARP site was inappropriately matchedwith MARYP sites and could not be validated using baseand Al concentrations. This study also confirmed thesouthern limit of the zero critical load exceedanceisopleth from the model. However, variability of theother exceedance isopleths was noted due to thelimited number of sites used in the model. Thevalidation of these sites in the ARP model and thezero critical load exceedance isopleth nonethelessallows greater confidence in using this model as amanagement tool for acidic deposition.