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.     

Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

Sulphate, Nitrogen and Base Cation Budgets at 21 Forested Catchments in Canada, the United States and Europe

To assess the concern over declining base cation levels in forest soils caused by acid deposition, input-output budgets (1990s average) for sulphate (SO₄), inorganic nitrogen (NO₃-N; NH₄-N), calcium (Ca), magnesium (Mg) and potassium (K) were synthesised for 21 forested catchments from 17 regions in Canada, the United States and Europe. Trend analysis was conducted on monthly ion concentrations in deposition and runoff when more than 9 years of data were available (14 regions, 17 sites). Annual average SO₄ deposition during the 1990s ranged between 7.3 and 28.4 kg ha⁻¹ per year, and inorganic nitrogen (N) deposition was between 2.8 and 13.8 kg ha⁻¹ per year, of which 41–67% was nitrate (NO₃-N). Over the period of record, SO₄ concentration in deposition decreased in 13/14 (13 out of 14 total) regions and SO₄ in runoff decreased at 14/17 catchments. In contrast, NO₃-N concentrations in deposition decreased in only 1/14 regions, while NH₄-N concentration patterns varied; increasing at 3/14 regions and decreasing at 2/14 regions. Nitrate concentrations in runoff decreased at 4/17 catchments and increased at only 1 site, whereas runoff levels of NH₄-N increased at 5/17 catchments. Decreasing trends in deposition were also recorded for Ca, Mg, and K at many of the catchments and on an equivalent basis, accounted for up to 131% (median 22%) of the decrease in acid anion deposition. Base cation concentrations in streams generally declined over time, with significant decreases in Ca, Mg and K occurring at 8, 9 and 7 of 17 sites respectively, which accounted for up to 133% (median 48%) of the decrease in acid anion concentration. Sulphate export exceeded input at 18/21 catchments, likely due to dry deposition and/or internal sources. The majority of N in deposition (31–100%; median 94%) was retained in the catchments, although there was a tendency for greater NO₃-N leaching at sites receiving higher (<7 kg ha^-1 per year) bulk inorganic N deposition. Mass balance calculations show that export of Ca and Mg in runoff exceeds input at all 21 catchments, but K export only exceeds input at 16/21 sites. Estimates of base cation weathering were available for 18 sites. When included in the mass balance calculation, Ca, Mg and K exports exceeded inputs at 14, 10 and 2 sites respectively. Annual Ca and Mg losses represent appreciable proportions of the current exchangeable soil Ca and Mg pools, although losses at some of the sites likely occur from weathering reactions beneath the rooting zone and there is considerable uncertainty associated with mineral weathering estimates. Critical loads for sulphur (S) and N, using a critical base cation to aluminium ratio of 10 in soil solution, are currently exceeded at 7 of the 18 sites with base cation weathering estimates. Despite reductions in SO₄ and H⁺ deposition, mass balance estimates indicate that acid deposition continues to acidify soils in many regions with losses of Ca and Mg of primary concern. The U.S. Government's right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged. The Canadian Crown reserves the right to retain a non-exclusive, royalty free licence in and to any copyright.     

An integrated assessment model for cross-country pipelines

The cross-country petroleum pipelines are environmentally sensitive because they traverse through varied terrain covering crop fields, forests, rivers, populated areas, desert, hills and offshore. Any malfunction of these pipelines may cause devastating effect on the environment. Hence, the pipeline operators plan and design pipelines projects with sufficient consideration of environment and social aspects along with the technological alternatives. Traditionally, in project appraisal, optimum technical alternative is selected using financial analysis. Impact assessments (IA) are then carried out to justify the selection and subsequent statutory approval. However, the IAs often suggest alternative sites and/or alternate technology and implementation methodology, resulting in revision of entire technical and financial analysis. This study addresses the above issues by developing an integrated framework for project feasibility analysis with the application of analytic hierarchy process (AHP), a multiple attribute decision-making technique. The model considers technical analysis (TA), socioeconomic IA (SEIA) and environmental IA (EIA) in an integrated framework to select the best project from a few alternative feasible projects. Subsequent financial analysis then justifies the selection. The entire methodology has been explained here through a case application on cross-country petroleum pipeline project in India.     

Distribution of Chlorinated Organic Pollutants in Harbor Sediments of Livorno (Italy): A Multivariate Approach to Evaluate Dredging Sediments

Dredging is a very important procedure for harbor management. InItaly the guidelines for the offshore dumping of dredged materials are issued by the Ministry of Environment. Theydescribed a few steps of dredging activities, such as thesampling strategy, but do not deal with limits or guide-valuesfor the chemical, physical and biological composition of theresulting sediments. The quality of dredged materials is mainlydependent on the presence of inorganic and organic pollutants.In particular, polychlorinated biphenyls (PCBs) and organo-chlorinated pesticides are seen as a high priority inmarine environment by international organizations because oftheir persistence, toxicity and bioaccumulation capacity.In this article the presence of some PCBs and organo-chlorinatedpesticides in sediment samples collected from the harbor ofLivorno (Northern Tyrrhenian Sea) was investigated. Theconcentration of HCHs, Aldrin, Chlordanes, DDEs, DDTs, and PCBsin 12 representative sites ranged between <1 g kg^–1and 95, 19, 32, 35, 107, and 111 g kg^–1, respectively.The application of univariate and multivariate statisticaltechniques, such as linear regression analysis and principalcomponent analysis, to the experimental data showed a differentdistribution of PCBs in the two sediment layers. On thecontrary, the vertical distribution of the other investigatedpollutants was more homogeneous and affected by randomvariability. The multivariate approach was an important tool to establish more rational criteria for the management of dredged materials.     

Climate impact on social systems: the risk assessment approach

A novel approach to the problem of estimating climate impact on social systems is suggested. This approach is based on a risk concept, where the notion of critical events is introduced and the probability of such events is estimated. The estimation considers both the inherent stochasticity of climatic processes and the artificial stochasticity of climate predictions due to scientific uncertainties. The method is worked out in some detail for the regional problem of crop production and the risks associated with global climate change, and illustrated by a case study (Kursk region of the FSU). In order to get local climatic characteristics (weather), a so-called statistical weather generator is used. One interesting finding is that the 3% risk level remains constant up to 1.0–1.1°C rise of mean seasonal temperature, if the variance does not change. On the other hand, the risk grows rapidly with increasing variance (even if the mean temperature rises very slowly). The risk approach is able to separate two problems: (i) assessment of global change impact, and (ii) decision making. The main task for the scientific community is to provide the politicians with different options; the choice of admissible (from the social point of view) critical events and the corresponding risk levels is the business of decision makers.     

用工业废水排放量预测地面水CODMn灰色方法研究

ＧＰＭ（１）灰色生长曲线常被用于等距时序环境系统的分析建模、非等距摆动空间序列方面的应用尚未报道。本文研究提出了将非等距摆动空间序列经过等距化处理的ＧＰＭ（１）线性回归优化建模方法采用该方法所建的非等距ＧＰＭ（１）模型用于工业废水量预测地面水ＣＯＤＭｎ的实例表明，该方法简捷，方便、精度高于回归分析，有较大实用价值。     

A study on the orbit of air temperature movement

In this paper, we describe an air temperature movement by mapping its time series to the polar coordinates: the value of the time series is plotted on the radial coordinate and the time on the angular coordinate. In this way, both the yearly and daily air temperature movements from five different locations of China are used to demonstrate that, in an intuitionistic view, air temperature movement is neither random nor chaotic, but has its own orbit. We then propose an elliptic orbit model for the air temperature movement. Our proposed model provides quite good results when it is applied to the evaluation of yearly air temperature movements in eight locations in various parts of the world, and the evaluation of daily air temperature movements in five locations in Hunan Province of China on December 17, 2005. Results show that our approach provides a concise and helpful model for air temperature analysis.     

南通市冬季PM2.5中水溶性离子污染特征

根据南通市2016和2017年冬季大气多参数站自动监测PM2.5数据和在线离子色谱分析仪Marga监测的PM2.5中水溶性离子数据,分析了南通市冬季PM2.5中水溶性离子污染特征。结果表明,南通市2016和2017年冬季,ρ(PM2.5)分别为58和54μg/m 3,均高出其年均值(14μg/m^3);ρ(水溶性离子)总占ρ(PM2.5)百分比分别为74.5%和74.3%;二次离子ρ(NO3^-、SO4^2-和NH4^+)占ρ(PM2.5)百分比分别为66.8%和66.6%;各水溶性离子占比大小依次为:NO3^-、SO4^2-、NH4^+、Cl^-、K^+、Na^+、Ca^2+、Mg^2+。对ρ(NO3^-)/ρ(SO 4^2-)分析表明,移动源已经成为南通市冬季的主要污染源,且呈逐年增强趋势。对氯氧化率和硫氧化率的分析表明,南通市冬季存在较明显的二次污染,SO2的转化程度大于NO2。除Na^+和Mg^2+外,其他离子与PM2.5均呈显著相关性,NO3^-、SO4^2-与NH4^+之间的相关系数最高,Cl^-与除Na^+外的所有阳离子均呈显著相关性。