Long term changes in atmospheric N and S throughfall deposition and effects on soil solution chemistry in a Scots pine forest in the Netherlands

In a Scots pine forest the throughfall deposition and the chemical composition of the soil solution was monitored since 1984. (Inter)national legislation measures led to a reduction of the deposition of nitrogen and sulphur. The deposition of sulphur has decreased by approximately 65%. The total mineral-nitrogen deposition has decreased by ca. 25%, which is mainly due to a reduction in ammonium-N deposition (−40%), since nitrate-N deposition has increased (+50%). The nitrogen concentration in the upper mineral soil solution at 10 cm depth has decreased, leading to an improved nutritional balance, which may result in improved tree vitality. In the drainage water at 90 cm depth the fluxes of NO₃⁻ and SO₄²⁻ have decreased, resulting in a reduced leeching of accompanying base cations, thus preserving nutrients in the ecosystem. It may take still several years, however, before this will meet the prerequisite of a sustainable ecosystem.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.     

A Sensitivity Analysis of an Integrated Modelling Approach to Assess the Risk of Wind-borne Spread of Foot-and-mouth Disease Virus from Infected Premises

The sensitivity of an integrated model to assess the potential for wind-borne spread of foot-and-mouth disease (FMD) to variations in key parameters controlling different physical and biological processes was evaluated. The estimated number of farms at risk is sensitive to the virus strain used and the accompanying effective contact rate. The C Noville strain increased the estimated number of exposed farms ranked as high and medium risk of being infected by a factor of 5, compared to the baseline, based on the O UKG 2001 strain. The inclusion of a model for biological ageing of the virus can also have a significant effect on the concentration patterns arising from transport and dispersion of the virus. Its inclusion has the practical advantage of markedly reducing the time required for the calculations. The estimated number of farms affected by exposure to high and medium virus concentrations is not grossly sensitive to attenuation caused by temperature or relative humidity effects. Changes in susceptibility to infection, as determined by the parameter θ in the exposure-risk model, does not change the configuration of the virus plumes, but it does change the distribution of farms at risk by risk category. These findings suggest that a good understanding of characteristics (excretion rates from infected animals, susceptibility of different species to infection, virus survival, etc.) of the virus strain involved in an FMD outbreak is necessary to provide a reliable assessment of the risk of wind-borne spread. In the event of an incursion of FMD, provision for laboratory studies on the virus will be an essential component of the disease response and should be factored into contingency plans.

Role of glycine on sulfuric acid-ammonia clusters formation: Transporter or participator

Glycine(Gly) is ubiquitous in the atmosphere and plays a vital role in new particle formation(NPF).However,the potential mechanism of its on sulfuric acid(SA)-ammonia(A)clusters formation under various atmospheric conditions is still ambiguous.Herein,a(Gly)_x·(SA)_y·(A)_z(z≤x+y≤3) multicomponent system was investigated by using density functional theory(DFT) combined with Atmospheric Cluster Dynamics Code(ACDC) at different temperatures and precursor concentrations.The results show that Gly,with one carboxyl(-COOH) and one amine(-NH_2) group,can interact strongly with SA and A in two directions through hydrogen bonds or proton transfer.Within the relevant range of atmospheric concentrations,Gly can enhance the formation rate of SA-A-based clusters,especially at low temperature,low [SA],and median [A].The enhancement(R) of Gly on NPF can be up to 340 at T=218.15 K,[SA]=10~4,[A]=10~9,and [Gly]=10~7 molecules/cm~3.In addition,the main growth paths of clusters show that Gly molecules participate into cluster formation in the initial stage and eventually leave the cluster by evaporation in subsequent cluster growth at low [Gly],it acts as an important "transporter" to connect the smaller and larger cluster.With the increase of [Gly],it acts as a "participator" directly participating in NPF.     

基于SVR的长江经济带水环境承载力评价

基于DPSIRM模型构建区域水环境承载力评价指标体系,并基于SVR模型构建了区域水环境承载力评价模型,利用交叉验证法对SVR模型参数进行优化选择,进一步提高模型预测精度.运用该模型研究了长江经济带2009~2018年的水环境承载力演变趋势及空间差异,结果表明：长江经济带水环境承载力等级整体呈现升高趋势,其中上游城市群承载等级由II级（超载）提升到了IV级（弱可承载）;中游城市群承载等级由II级（超载）提升到了IV级（弱可承载）;下游长三角区域承载等级由I级（重超载）提升到了IV级（弱可承载）.将评价结果与熵权-TOPSIS法的评价结果相比较,相同率达到91.7%,说明SVR模型评价区域水环境承载力可行,评价结果可靠.以下游区域为例,分别对其6个子系统的承载力进行剖析,并运用单因素轮换OAT法对各子系统内的评价指标进行敏感性分析,便于决策者识别指标敏感性.     

气体中毒窒息事故的环境应急监测

以株洲市攸县某矿业公司"5·7"重大中毒窒息事故的环境应急监测为例，详细阐述了该事故开展应急监测的全过程。针对锁定污染因子、查找污染源、判断污染团的扩散趋势以及监控敏感点的安全等监测目的设计监测方案。通过监测数据分析确定事故特征因子为CO，其周边环境空气中浓度随着与抽风口距离的增加而快速下降，监测到附近居民区环境空气质量未受事故影响。     

龙岩市区大气颗粒物中多环芳烃的种类和时空分布特征及来源

采用恒能量同步荧光法检测了龙岩市大气颗粒物样品中的多环芳烃(PAHs),比较了龙岩市区大气颗粒物中多环芳烃含量的差异以及不同季节对多环芳烃含量的影响,讨论了其分布规律及污染源。     

大气污染物影响因素的灰色关联分析

运用灰色系统理论，对产生和影响城市大气主要污染物的相关因素，利用灰色关联分析方法进行了量化分析研究，根据研究结果，提出了控制大气污染的防治对策．     

化工区环境突发事件的数学预测及应对措施

通过对某市化工区环境污染物概况的调查,建立了污染风险模型,并且根据模型获得的结果确定了区域内的主要污染物。在此基础上提出了化工区环境突发事件的应对措施,为今后的应急监测提供的理论保证。