Integrated Spatial Simulation of Population and Urban Land Use: a Pan-European Model Validation.

Spatial models jointly simulating population and land-use change provide support for policy-making, by allowing to explore territorial developments under alternative scenarios and resulting impacts in the environment, economy and society. However, their ability to reproduce observed spatial patterns is rarely evaluated through model validation. This lack of insight prevents researchers and policy-makers of fully grasping the ability of existing models to provide sensible projections of future land use and population density. In this article, we address this gap by performing a model validation of the LUISA Territorial Modelling Platform, a spatial model jointly simulating population and land use at a fine resolution (100 m) in the European Union and United Kingdom. In particular, we compare observed and simulated patterns of population and urban residential land-use change for the period of 1990-2015, and evaluate the model performance according to different degrees of urbanisation. The results show that model performance can vary depending on the context, even when the same data and methods are uniformly applied. The model performed consistently well in urban areas characterized by compact urban growth, but poorly where residential development occurred predominantly in scattered patterns across rural areas. Overall, the model tends to favour the formation of densely populated, highly accessible urban conglomerations, which often do not entirely correspond to the observed patterns. Based on the validation results, we propose directions for further model improvement and development. Model validation should be regarded as a critical step, and an integral part, in the process of developing models for policy support. Supplementary Information: The online version contains supplementary material available at 10.1007/s12061-023-09518-x.

Higher proportion of agricultural land use around the residence is associated with higher urinary concentrations of AMPA, a glyphosate metabolite.

INTRODUCTION: Pesticides, including herbicides, are widely used for agricultural and sanitary reasons and concerns have been raised about their various health effects. Little research has been done into the extent to which agricultural land use in the residential surroundings contributes to (internal) exposure of pesticides. OBJECTIVES: We investigated the associations between the proportion of agricultural land use around the residence and the exposure to pesticides in adolescents in Flanders (Belgium). MATERIAL AND METHODS: We included 424 adolescents participating in the fourth Flemish Environment and Health Study (FLEHS IV) between 2016 and 2020. The residential address of all participants was geocoded and the proportion of agricultural land use around the residence was estimated in several buffers (300 m, 500 m, 1000 m and 2000 m). The concentrations of the following biomarkers of pesticides were measured in urine and adjusted for the specific gravity: glyphosate and its metabolite, aminomethyl-phosphonic acid (AMPA); 3-phenoxybenzoic acid (3-PBA); 3,5,6-trichloro-2-pyridinol (TCPy) and 2,4-dichlophenoxy-acetic acid (2,4-D). We categorized the pesticide biomarkers in three categories according to the exposure levels and used ordinal logistic regression models adjusted for sex, season and household education to estimate the odds ratio for an increase in an interquartile range (IQR) of proportion of agricultural land use. We also used binary logistic regression models in which the category of highest exposure was compared to the category of lowest exposure. In addition, we explored potential effect modification by sex and season. RESULTS: We found a significant association between the proportion of agricultural land use in a buffer of 2000 m around the residence and the levels of urinary AMPA divided into three categories (OR = 1.35 for an IQR increase in the proportion of agricultural land use around residence; 95% CI: 1.00-1.83). This association was less pronounced and not statistically significant for the other studied pesticides (OR ranging between 0.95 and 1.16). Stratified analysis showed the strongest association of the proportion of agricultural land use within 2000 m buffers for AMPA among boys (OR = 1.89; 95% CI: 1.19-3.04). Results using smaller buffers were comparable, but did not reach statistical significance. CONCLUSION: Our findings suggest that a higher proportion of agricultural land use around the residence might increase exposure to AMPA.

Event mean concentration and first flush from residential catchments in different climate zones.

Most studies on EMC (Event mean concentration) and first flush are reported as local studies; however variations of EMC and first flush across catchments in different climate zones has not been studied. This research collected continuous flow and discrete water quality data and rainfall measurements from 17 catchments, EMC and rainfall data from 14 catchments, and an additional dataset where only average EMC values are reported (19 catchments). The data are from residential sites across temperate, tropical, dry, and continental climate zones and include water quality parameters in particulate (total suspended solids), mixed (total nitrogen and total phosphorus) and dissolved (orthophosphate and ammonium nitrogen) forms. Our study shows that EMC differs significantly between climate zones. The average EMC is highest in dry followed by continental and temperate, with lowest in the tropical zone. Pearson's correlation analysis revealed that the rainfall depth is negatively correlated with EMC for particulate and mixed form parameters for the tropical, temperate and dry zones, but positively correlated for the continental zone. The discrete time-series data from the 17 catchments were used to evaluate first flush and it was found that catchments in the tropics exhibit stronger first flush than temperate zone catchments, for all the water quality parameters with particulate showing a stronger first flush compared to dissolved forms. Based on the distribution of the data, new limits for very strong, strong, moderate, and very weak to no first flush are suggested for TSS for different climate zones. The new limits were quantified by fitting the function L^=V^bwhere L^and V^are the normalized cumulative runoff load and volume, respectively. For catchments in the tropics, this corresponds to b < 0.47, 0.6 > b > 0.47, 0.76 > b > 0.6 and b > 0.76, respectively. For the temperate zone, b < 0.5, 0.67 > b > 0.5, 0.85 > b > 0.67 and b > 0.85, are appropriate. From a design perspective, the FF20 concept defined as the load corresponding to 20% runoff volume, is often used. The ranges FF20 < 0.27, 0.36 > FF20 > 0.27, 0.45 > FF20 > 0.36 and FF20 > 0.45 and FF20 < 0.24, 0.31 > FF20 > 0.24, 0.31 > FF20 > 0.39 and FF20 > 0.39 are proposed for tropical and temperate catchments, respectively. Other limits for TP, TN, OP and NH4-N are also suggested. This is the first study of its kind and an expended dataset especially for continental and dry regions is needed to further validate the findings.