Hammingh P; Jimmink BA(Rijksinstituut voor Volksgezondheid en Milieu RIVM, 2002-01-24)
This national report on air quality resolutions is based on reports from provinces and municipalities for the year 2000. The reports describe the local air quality by exceedances of air quality standards for the compounds sulphur dioxide, suspended particles (black smoke), nitrogen dioxide, carbon monoxide, lead and benzene. No exceedances of air quality standards were reported for industrial areas. The provinces of Utrecht, Noord-Holland and Zuid-Holland report exceedances for nitrogen dioxide near a number of motorways. The province of Noord-Brabant reports two exceedances for nitrogen dioxide near national motorways. Twelve municipalities reported a joint total of 50 cases of exceedance: 22 times for nitrogen dioxide, 23 times for benzene, twice for suspended particles and three times for carbonmonoxide.<br>
Groot MSM; Bronswijk JJB; Leeuwen TC van(LEI-DLO, 2003-07-04)
This report contains the results of the National Soil Monitoring Network of the Netherlands in 1997, the fifth year of sampling. The network represents the cooperative effort of the National Institute of Public Health and the Environment (RIVM), the Agricultural Economic Research Institute (LEI) and the Research Institute for Agrobiology and Soil Fertility (Alterra). The first sampling, of soil and upper groundwater, took place in 1993 on 35 dairy-cattle farms in the sandy regions of the Netherlands. In 1994, 20 intensive cattle farms (high phosphate production) and 20 forest sites (deciduous, pine and mixed) on sandy soils were sampled, in 1995, sampling was carried out on 19 arable farms on sandy soils and 18 cattle farms on peaty soils, in 1996, 20 arable farms on sea clay and 20 cattle farms on river clay were sampled and finally, in 1997, 20 cattle farms on sea clay, 10 vegetable farms and 7 bulb farms on sandy clay soils were sampled. The objectives of the network are to establish changes in soil quality over time, and to establish the actual quality of soil and upper groundwater. Attention is focused primarily on the rural part of the country. The monitoring programme is divided into even time units and samples 40 locations yearly. Sampling has yielded information on concentrations of heavy metals, polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides and triazines, both in the topsoil (0-10 cm) and at a depth of 30-50 cm. Information on concentrations of macroparameters, nutrients and heavy metals in the upper groundwater is also presented. The measured concentrations are compared with the Dutch objectives for soil and groundwater quality (target values). On dairy-cattle farms, target values for lead were exceeded in a few samples of the topsoil, while on vegetable farms, targets for zinc and copper were exceeded in samples of the topsoil. On bulb farms targets for copper were exceeded in a few topsoil-samples. Target values for a number of individual PAHs and organochlorine pesticides were exceeded in soil for all categories. Atrazine was shown to greatly exceed the target value, especially on cattle farms. On cattle farms, target values for a number of heavy metals were exceeded in groundwater. The same holds for zinc, cadmium, chrome, copper, nickel and arsene on vegetable farms. On bulb farms targets for chrome, nickel and arsene were exceeded. For both categories, target values for total phosphate, ortho phosphate, ammonium (mostly on bulb farms) chloride, nitrate, sulphate and potassium were exceeded in groundwater. Heavy metal balances have been computed at farm level for cadmium, copper, lead and zinc. There is a balance surplus for all metals involved, caused by the net result of input through atmospheric deposition and farming practice and output through leaching to the groundwater. Therefore accumulation of heavy metals has been concluded to occur in both categories.
Stolk AP; Boschloo DJ(Rijksinstituut voor Volksgezondheid en Milieu RIVM, 2002-10-16)
This report documents the tabulated results of the regional stations of the National Air Quality Monitoring Network in the regions 4 (Zuid-Holland) and 5 (Noord-Holland) for the calendar year 1998, summer 1998, winter 1997-1998 and 1 April 1997 - 31 March 1998 (tropical year: EU reference period). The components measured were: NH3, fine dust (PM10), CO, oxidant (Ox , which is NO2+O3), O3, NO2, NO, NOx (=NO2+NO), black smoke (which is suspended matter measured by the black smoke method) and SO2. The fine dust (PM10) measurement data are multiplied by a factor 1.33 to correct the systematic underestimation when compared to the EU reference method for PM10.<br>
Picavet HSJ; van Gils HWV; Schouten JSAG(Rijksinstituut voor Volksgezondheid en Milieu RIVM, 2000-03-31)
Musculoskeletal complaints represent a big public health problem however data on the total population are scarce.Using cross-sectional data from a national population-based study on persons of 25 years and olderw we give estimates on prevalences of different musculoskeletal complaints, their consequences and risk groups in the Dutch population.The period prevalence (12 months) and point prevalence (Pp) of pain complaints of ten different anatomical sites were assessed in five groups: 1. neck, shoulder or higher part of the back, 2. elbow or wrist/hand, 3. lower part of the back, 4. hip or knee, 5. ankle and foot. Additional data included demographics, characteristics of the complaints (duration, severity, course) and consequences (perceived health, (work) disability, use of health care services). Data were weighted to present data on the Dutch population aged 25 years and over.The top 3 of self-reported musculoskeletal complaints was: 1. low back pain, Pp=26.9%, 2. shoulder pain, Pp=20.9% 3. neck pain, Pp=20.6%. In most cases the pain was described as continuous or repetitive, non-severe pain. In every 3 out of 10 cases the pain complaints were accompanied with limitation in daily life. Between 33% and 42% of those with complaints consulted their general physician for their pain. With exception of those who are work disabled, general socio-demographic characteristics cannot be used to identify high risk groups. Musculoskeletal pain is common among every subgroup in the population and varies from a non-severe pain complaint to a severe health problem with consequences for work and use of health care.<br>
Bakkenes MD; de Zwart D; Alkemade JRM(Rijksinstituut voor Volksgezondheid en Milieu RIVM, 2002-09-30)
This report describes the process to produce optimal regression equations for vegetation response models in MOVE 3.2. MOVE is a Dutch national model for MOdelling VEgetation responses using regression models. The research consists of two parts, in part I the available data are analysed and in the second part the optimal regression equations are derived. The study shows that values of all variables are present for the complete data range and that the samples show a good spatial distribution. Comparing a random sample of thirteen species with records in the Dutch standard reference book 'Heukel's Flora van Nederland' shows that the values and dispersion of these species are similar. The construction of optimal regression equations for each species is done in two ways. The first method compares up to eleven different regression models, starting with a simple model and creating new and more complex models by adding variables. This resulted in the calculation of eleven enforced regression equations. The second method is a stepwise regression analysis. The only control on the stepwise procedure is the variation of start and end models of the stepwise regression. In the second method we have experimented with six different variants of which three are used in the final selection procedure. This totals the total number of calculated results to fourteen different models for each species. Of the original 914 species only those species (models) are selected that meet two criteria. First the measure of goodness of fit must lie within the 5 (alpha = 0.05) percent confidence interval (meaning that there is a possibility of 5% that a model will be wrongly rejected). When more than one model meets this criteria the model with the largest predictor will be selected. The second criterium is that at least one of the variables in the model must be a variable that can change over time. These criteria resulted in models for 690 species. The goodness of fit criteria resulted in poor models for fifteen models. Poor models are models with a relatively low predictor compared with the highest predictor in the set of the fourteen different models. For these fifteen models a better model is selected, i.e. a model with a much higher predictor and a goodness of fit value with p greater than 0.01. In the final set all fourteen different model runs are included. The variables with the fewest occurrences are the variable describing the impact of heavy metal, the variable salt en vegetation type. Apparently , these variables are for many plant species less important distinguishing variables.<br>
Berdowski JJM; Draaijers GPJ; Janssen LHJM; Hollander JCTh; Loon M van; Roemer MGM; Vermeulen AT; Vosbeek M; Visser H(TNO, 2001-11-19)
The agreed emission reductions in the Kyoto Protocol require methods to establish the quality and accuracy of the inventory data and to monitor compliance with the Protocol. The IPCC Expert Meeting in November 1997 in the Netherlands concluded that an assessment of inventory data quality was strongly supported by independent checks and additional analysis of uncertainties in the emissions inventories. In this study, carried out in the frame of the Dutch National Research Programme on Global Air Pollution and Climate Change three connected validation procedures have been applied for a methane emission inventory, namely (i) the comparison of emission inventories, (ii) the comparison of modelled with observed methane concentrations, and (iii) the comparison of bottom-up emission estimates with inversely modelled emission estimates. There is a good overall correspondence between the consistent bottom-up METDAT emission inventory and the National Communication data. However, on a country level and on a source category level large discrepancies could been found. The analysis of concentration measurements gives a clear indication of the contribution from the different areas. Time series analysis as such appeared not to be suitable for verification purposes in this study. The technique of emission verification by modelling methane concentrations with the bottom-up estimated emission data as input for the model and comparing the results with measured concentrations has been proven quite successful, at least on a regional scale. The technique applied so far is however not able to indicate whether the individual sources are estimated realistically as well. At present, the technique of inverse modelling has not proven to be robust enough to produce stable results of satisfactory accuracy on a regional scale. At least, there is a lack of sufficient measurement data, e.g. from neighbouring countries and a need for the improvement of background concentration data (by global models).
Boschloo DJ; Stolk AP(Rijksinstituut voor Volksgezondheid en Milieu RIVM, 2002-10-16)
This report presents the tabulated results of the city and street stations of the National Air Quality Monitoring Network in the whole of the Netherlands for the calendar year 1997, summer 1997, winter 1996-1997 and 1 April 1996 - 31 March 1997 (tropical year: EU reference period). The components measured were: fine dust (PM10), CO, oxidant (Ox , which is NO2+O3), O3, NO2, NO, NOx (=NO2+NO), black smoke (which is suspended matter measured by the black smoke method) and SO2. The fine dust (PM10) measurement data are multiplied by a factor 1.33 to correct the systematic underestimation when compared to the EU reference method for PM10.<br>
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