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For those involved in planning for regional and local scale changes in future climate, there is a requirement for climate information to be available in a context more usually associated with meteorological timescales. Here we combine a tool used in numerical weather prediction, the 30 weather patterns produced by the Met Office, which are already applied operationally to numerical weather prediction models, to assess changes in the UK Climate Projections (UKCP) Global ensemble. Through assessing projected changes in the frequency of the weather patterns at the end of the 21st Century, we determine that future changes in large-scale circulation tend towards an increase in winter of weather patterns associated with cyclonic and westerly wind conditions at the expense of more anticyclonic, settled/blocked weather patterns. In summer, the results indicate a shift towards an increase in dry settled weather types with a corresponding reduction in the wet and windy weather types. Climatologically this suggests a shift towards warmer, wetter winters and warmer, drier summers; which is consistent with the headline findings from the UK Climate Projections 2018. This paper represents the first evaluation of weather patterns analysis within UKCP Global. It provides a detailed assessment of the changes in these weather patterns through the 21st Century and how uncertainty in emissions, structural and perturbed parameters affects these results. We show that the use of these weather patterns in tandem with the UKCP projections is useful for future work investigating changes in a range of weather-related climate features such as extreme precipitation.

Estimating total precipitable water vapour (TPWV) from advanced microwave scanning radiometer 2 (AMSR2) measurements with reasonable accuracy is challenging. Therefore, this study aims to improve t...

The objective of this study is to collect more data on the bio-monitoring of trace element pollution and the distribution of emission sources at the local scale. Accordingly, the concentrations of several trace elements (TEs) were measured in epiphytic lichens and tree bark samples collected from an area of study near Algiers-Algeria, using the instrumental neutron activation analysis (INAA) technique. The results show the existence of more than 20 TEs and the study of the enrichment factors (FEs) indicates pollution of anthropogenic origin: brickyard with emissions of Na, As, Se, Sc, Co, Cr, Tb, Ta, Fe, pollution of vehicles with emission of Se, Sb and Zn and re-suspension of the soil with emission of Zn and Br.

The electric grid’s available capacity to accommodate solar photovoltaic on national scales is currently uncertain. This makes decisions about grid capacity expansion, which can be very costly for local grid operators, difficult to make. Yet, knowledge of national solar photovoltaic grid capacity is central in order to formulate realistic solar PV targets and strategies. We present a methodology based on publicly available data to estimate the grid’s hosting capacity of residential solar photovoltaic at both the national and local scale. The model is applied to Sweden, Germany and the UK and shows that low-voltage grid capacity for residential solar photovoltaic is very large, 33 (+5/-7) GW (Sweden), 248 (+5/-24) GW (Germany) and 63 (+1/-14) GW UK, and similar to current total generation capacity. Based on our estimations, we find that with the capacity of the present grid Sweden can supply 24%, Germany 60% and UK 21% of their current annual net electricity consumption from residential solar photovoltaic. In addition, we find that the grid-supported individual solar PV system sizes increase as population density decreases. Finally, our work highlights the importance of implementing sizing incentives for customers when installing their solar PV systems.

Rain is deemed one of the most important climate elements. It must be given special attention for being the basis without which no kind of life in the world can be there. the aim of the study is to use Statistical models Downscaling (SDSM) where it is a universal model used to converting large scale output into a small scale that can be used to study impact at the local scale (Iraq)' to Forecasting cumulative annual rainfall for the next years where there are a few studies used this model in Iraq. Daily rainfall data from the Iraqi Meteorological Organization and Seismology (IMOS) (2007-2016) for the study areas (Baghdad, Karbala, Al-Hay, Mosul, Kirkuk, Khanaqin, Basra, Nasiriya, Diwaniya, and Rutba) is used to estimate the amount of rainfall by using SDSM. The model was used to estimate the rain values and then the results were compared with the actual values, the results were very close to each other. Also, the model used to predict the cumulative annual rainfall from (2017-2021), The result shows that the bigger amount of rainfall in the north region with (3821) mm and the lowest amount in the west region (665) mm, while middle region (1848) mm and south region (1828) mm.

Since 2010, a severe drought has affected central Chile, resulting in losses that prompt the need to evaluate and improve adaptation responses. The evaluation process requires the engagement of mul...

More than two‐thirds of the world's population reside Eurasia. We comprehensively project the spatial patterns of changes in five selected extreme temperature indices in different periods under future scenarios and at different global warming levels by using 24 CMIP6 model simulations and evaluating their performances. We showed the avoided changes at the local scale and revealed that if global warming can be controlled to within a low warming target, the risk of extreme temperature change will be greatly reduced.

We developed a LOcal-scale High-resolution atmospheric DIspersion Model using Large-Eddy Simulation (LOHDIM-LES) for the safety assessment of nuclear facilities and emergency responses to accidenta...

The rapid increase in demand and consumption of groundwater in the past few decades has imposed colossal pressure on the stakeholders responsible for groundwater management. Assessment of groundwater vulnerability and knowledge about hydrogeological settings are crucial for a particular region, especially at a local scale, to manage groundwater resources effectively. The present study aimed to develop a modified DRASTIC model to demarcate groundwater vulnerability zones based on experimental analysis of field samples to make the model more feasible at local scale. Four techniques were implemented in this study to determine groundwater vulnerability zones: (a) DRASTIC; (b) DRASTIC–AHP (analytic hierarchy process); (c) Modified DRASTIC; (d) Modified DRASTIC–AHP. The best groundwater vulnerability model was determined based on validation results with groundwater nitrate concentration. The comparative assessment showed that the Modified DRASTIC–AHP outperformed the other models. More than 50% of the study area was classified as ‘high’ (33.06%) and ‘very high’ (21.31%) groundwater vulnerability zones. The vulnerability map shows that high vulnerable zones dominate in the northwestern part and in some portions of the floodplain near central part of the study area. The results of this study envision that inclusion of experimentally derived parameters can be used to modify the conventional DRASTIC model and obtain better results at local scale.

A pesar de los demostrados efectos adversos que los metales pesados (MP) provocan en la salud humana, su distribución espacial en España es un fenómeno poco estudiado. Con la finalidad de paliar esta deficiencia, se plantearon los siguientes objetivos: (1) conocer la distribución espacial, a escala municipal, de los vertidos de MP emitidos a las aguas, (2) estimar y cartografiar la peligrosidad de los vertidos según su toxicidad, (3) comparar las emisiones de MP en España con su entorno europeo y (4) estimar la evolución futura de los vertidos de MP. Los datos se han recopilado desde el registro E-PRTR (European Pollutant Release and Transfer Register 2007-2016) y la localización de los puntos de emisión se ha obtenido mediante geocodificación. Tras un análisis exploratorio, los datos fueron normalizados y pondera-dos, facilitando la interpretación de gráficas, tablas y cartografía. Los resultados muestran una mayor concentración de puntos de emisión en los sectores norte (Asturias, Cantabria y País Vasco), nordeste (Cataluña), este-sureste (Valencia) y sur (Andalucía). Tras revisar los efectos de los MP sobre la salud humana, estos han sido ponderados por este orden; mercurio (Hg), plomo (Pb), cadmio (Cd), cromo (Cr), arsénico (As) y zinc (Zn). Se ha constatado que durante el periodo 2007-2016, las cantidades de MP vertidas a las aguas lejos de disminuir, han oscilado adaptándose a las transiciones económicas y persistiendo una mayor concentración de vertidos en los municipios localizados en las provincias del norte, nordeste, este-sureste y sur del país.

HighlightsStabilization structures are only effective at stabilized segments.Erosion increased in two of the six segments in the post-stabilization period.Deposition decreased in all six segments in the post-stabilization period.Jetties are effective at reducing erosion but are also prone to fail.Abstract. The effectiveness of streambank stabilization structures is insufficiently quantified. Although such structures clearly reduce or eliminate streambank erosion at the local scale, little is known about associated effects on unstabilized reaches immediately upstream and downstream. This study measured streambank erosion and deposition in stretches of the Cedar River, 1.5 meander wavelengths upstream and downstream from 24 stabilization structures that included jetties, rock vanes, root wads, and gravel protection. We also measured erosion and deposition on the streambanks directly opposite the stabilized locations. We compared measurements from the pre-stabilization period (1993-2005) with those from the post-stabilization period (2005-2018) using historical imagery in ArcGIS. Upon completion of this analysis, we were able to reject an initial hypothesis that local and adjacent streambank segment erosion rates would be significantly less after stabilization, and that deposition rates would be greater in stabilized locations and adjacent stream segments. Instead, the differences in erosion from pre- to post-stabilization showed little or no statistical significance. Rather, our data indicated that streambank erosion decreased in only four of the six stream segments and was predominantly confined to the stabilized segment. Overall deposition decreased in all six stream segments after bank stabilization. In reaches where wooden jetties were installed, partial or total failure was common, and further increases in erosion and decreases in deposition were more pronounced. We conclude that streambank stabilization on the Cedar River is effective only at the location of installation; there is no measurable effect on adjacent unstabilized reaches. Our results demonstrate the need for improved streambank monitoring practices and better understanding of how streambank stabilization impacts an entire river system. Such advances will enhance stream restoration design and implementation, as well as support future river management efforts. Keywords: Adjacent stream reach, Deposition, Jetty, Erosion, Streambank stabilization.

The geo-referenced regional exposure assessment tool for European rivers (GREAT-ER) is designed to support river basin management or the implementation process within the EU Water Framework Directive by predicting spatially resolved exposure concentrations in whole watersheds. The usefulness of the complimentary application of targeted monitoring and GREAT-ER simulations is demonstrated with case studies for three pharmaceuticals in selected German watersheds. Comparison with monitoring data corroborates the capability of the probabilistic model approach to predict the expected range of spatial surface water concentrations. Explicit consideration of local pharmaceutical emissions from hospitals or private doctor’s offices (e.g., for X-ray contrast agents) can improve predictions on the local scale without compromising regional exposure assessment. Pharmaceuticals exhibiting low concentrations hardly detectable with established analytical methods (e.g., EE2) can be evaluated with model simulations. Management scenarios allow for a priori assessment of risk reduction measures. In combination with targeted monitoring approaches, the GREAT-ER model can serve as valuable support tool for exposure and risk assessment of pharmaceuticals in whole watersheds. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-020-12189-7.

A chemical characterization of PM10 collected at hydrofoil exhaust stacks was performed conducting two on-board measuring campaigns, with the aim of assessing the ship emission impact on PM10 collected in the coastal area of Naples (Southern Italy) and providing information about the characteristics of this important PM emission source. Samples were analysed determining the contribution of different chemical parameters to PM10’s mass, which consisted of polycyclic aromatic hydrocarbons (PAHs) (0.10 ± 0.12%), total carbon (61.9% ± 20.0%, with 40.4% of organic carbon, OC, and 21.5% of elemental carbon, EC) and elemental fraction (0.44% ± 1.00%). Differences in terms of composition and chemical parameter profiles were observed between samples collected during offshore navigation (Off) and samples collected during shunting operations (SO), the latter of higher concern on a local scale. For SO samples, lower contributions of OC and EC were observed (39.7% and 19.6% respectively) compared to Off samples (41.5% and 24.2%), and an increase in terms of elements (from 0.32 to 0.51%) and PAHs (from 0.06 to 0.12%) concentrations was observed. In addition, enrichment factors (EFs) for some elements such as V, Zn, Cd, Cu, Ag and Hg as well as PAHs profile varied significantly between SO and Off. Data presented here were compared with data on chemical composition of PM10 sampled in a tunnel, in a background site and in an urban site in the city of Naples. Results indicated that shipping activities contributed significantly to the emission of V and, in some extent, Zn and Cd; in addition, PAH profiles indicated a greater contribution to urban PM10 from vehicular traffic than shipping emissions. These results can significantly contribute to the correct evaluation of the influence of shipping emission on PM10 generation in urban coastal areas and can be a useful reference for similar studies. The coastal area of Naples is an important example of the coexistence of residential, touristic and natural areas with pollutants emission sources including, among the others, shipping emissions. In this and similar contexts, it is important to distinguish the contribution of each emission source to clearly define environmental control policies.

The estimation of forest attributes at the local scale as well as in wall-to-wall approaches benefits from the integration of remote sensing data such as airborne laser scanning (ALS). A poor level...

Heavy snowfall during winter period (November to April) over the north-west Himalaya (NWH) generates many natural hazards. Time critical decisions primarily dependent on precipitation amount such as avalanche forecasting, flood forecasting, management of necessary services and supplies etc. demand real time weather forecasts, specially, quantitative precipitation forecasts (QPFs), at local scale during winter over the NWH. Two analog ensemble systems (AE1 system, AE2 system) for QPFs for varied forecast lead times are developed utilizing surface meteorological observations of 10 stations over the NWH. Performances of developed analog ensemble systems are evaluated and compared with performances of the climatological forecast models (CM1 model, CM2 model) for same forecast lead times for binary weather forecasts (precipitation day/no precipitation day) and QPFs at 10 stations over the NWH. The AE1 (AE2) system is found to perform better as compared to the CM1 (CM2) model for binary weather forecasts and QPFs at local scale over the NWH. Performance of the AE1 system for binary weather forecasts for shorter forecast lead times 0–15 h (0–15 h), 15–24 h, 24–39 h is found comparable to performance of the AE2 system for binary weather forecasts for longer forecast lead times 0–24 h, 24–48 h, 48–72 h. However, the Mean Absolute Errors (MAEs) and Root Mean Square Errors (RMSEs) for QPFs for shorter forecast lead times with the help of the AE1 system are found less as compared to the MAEs (RMSEs) for QPFs with the help of the AE2 system for longer forecast lead times. The AE1 system can provide real time QPFs based on recent surface meteorological observations for shorter lead times which can help in dynamic decision making for weather and avalanche forecasting over the NWH. However, QPFs with the help of the AE2 system can be useful for longer forecast lead times. Performances of the AE2 system and CM2 model are evaluated for binary weather forecasts and QPFs for a week period (7 days). The AE2 system is found to perform better as compared to the CM2 model for binary weather forecasts and QPFs for a week at local scale over the NWH. These results suggest that the AE2 system exhibits better consistency for QPFs as compared to the CM2 model for a week. The MAEs (RMSEs) for QPFs with the help of the AE1(AE2) system comparable to the MAEs (RMSEs) for QPFs with the help of other forecasting methods over the NWH (or elsewhere) suggest that the AE1(AE2) system exhibits good performance for real time QPFs at local scale over the NWH.

Land Surface Temperature (LST) derived from space-borne Thermal-infrared (TIR) sensors is a key parameter of urban climate studies. Current studies are inefficient to capture the spatial and temporal variations of LST for only one snapshot adopted at one time. Focusing on the characterization of the spatial and temporal of LST variations at local scales, the latent patterns, and morphological characteristics are extracted in this study. Technically, sixteen MODerate-resolution Imaging Spectroradiometer (MODIS) eight-day synthesized LST products (MYD11A2) in 2002, 2007, 2012, and 2017 are employed. First, the non-parametric Multi-Task Gaussian Process Model (MTGP) is used to extract the smooth and continuous Latent LST (LLST) patterns using one LST subset and its temporally adjacent images. Second, the Multi-Scale Shape Index (MSSI) is then applied to quantify the morphological characteristics at the optimal scale. Then, the LLST patterns and MSSI maps are clustered into multiple spatial categories. The specific clusters with the highest LLST and MSSI values are considered as local LLST hotspots. The Hotspots Weighted Mean Center (HSWMC) and standard deviation ellipse are adopted to further investigate the spatiotemporal change of hotspots orientation, direction, and trajectories. Results revealed that Impervious Surfaces (IS) composition is the most significant external forcing of local LST anomalies. The configuration factors (e.g., shape index, aggregation index) also have a noticeable local warming effect. This study represents a latent pattern and morphology-based framework for LST hotspots spatial and temporal variations characterization, catering to the zoning and grading strategies in urban planning.

Prediction and accurate digital soil mapping (DSM) of soil organic carbon (SOC) at a local scale is a key factor for any agro-ecological modelling. This study aims to use remote sensing and terrain derivatives to provide a reliable method for SOC prediction. An advanced geostatistical-based empirical Bayesian Kriging regression (EBKR) method was used and performance was compared with the artificial neural network (ANN) and hybrid ANN, i.e. ANN-OK (ordinary kriging) and ANN-CK (cokriging). The result showed that the hybrid ANN model performs better than ANN, whereas the EBKR method outperforms all other methods with the highest R2 of 0.936. The DSM map shows that the highest SOC concentration was found in easternmost part of the study area with grass and agricultural land. This work shows the robustness of the EBKR prediction method over other techniques. The study will also aid the policymakers in adopting sustainable land use management.

Coastal areas are frequently influenced by direct and/or indirect multiple anthropogenic pressures, which impacts marine life. Those perturbations may act in a heterogeneous way with a different intensity and are related to the complexity of coastal ecosystems. To visualize all these interactions at a local scale, a methodology inspired from many researches has been implemented in order to search, identify, and classify coastal ecosystems according to their sensitivity to anthropic pressure exerted by coastal cities. Thus, producing vulnerability maps will be essential tools to local coastal managers. We have applied this methodology on five coastal municipalities in Algiers. Firstly, the environmental sensitivity of coastal ecosystems was assessed by analyzing these four sub-indices: biological sensitivity, geomorphological sensitivity, hydrodynamic characteristics, and pollution intensity. Secondly, an assessment of the anthropogenic pressures presented by each municipality was carried out. Five sub-indexes have been taken into consideration when conducting this assessment: human activities, infrastructures, vectors of pollution, urbanization, and regulatory protection. Then, vulnerability maps were produced by the overlapping of sensitivity and anthropic pressure maps. The results assessed for the environmental vulnerability indicated that most areas are moderately to highly vulnerable, especially in the municipalities of Bab El Oued, Rais Hamidou, and Ain Bénian. The analysis of the obtained results shows the potential applicability of this methodology because they accurately reflect the reality. Therefore, these results can be useful to decision-makers by providing them with a relatively rational decision-making tool to prioritize future management and planning efforts.

Globally, drought constitutes a serious threat to food and water security. The complexity and multivariate nature of drought challenges its assessment, especially at local scales. The study aimed t...

The conservation, management and monitoring of aquatic resources should benefit from understanding their spatial structuring. In this paper, we used the reference condition approach (RCA) to test if the variability in biotic communities, riverine fish assemblages in the present case, is better controlled with a spatial delineation based on ecoregions or by grouping rivers with local catchment characteristics. Electrofishing data from 493 riffles in 99 rivers in Finland were used in the analysis. We completed multivariate analyses (nonmetric multidimensional scaling, multiresponse permutation procedures) to identify differences in fish community composition among groups based on ecoregions or catchment characteristics. We concluded that both regional processes and local environmental characteristics structured fish populations, and bioassessment of freshwaters should be based on regional spatial delineations, supported by local scale characteristics. Spatial delineations like ecoregions should be used to assist the bioassessment to improve the efficiency to detect the human impacts.

A cyclone in July 1572 caused a catastrophic flood in the catchments of the Upper Danube and Vltava rivers. A previously unpublished inventory dating to 1574 enabled local-scale insight into the ef...

The growing interest in shallow geothermal resources leads to dense installation areas, where interference and decrease in efficiency might occur. To optimize geothermal use in cities which prevents interference between neighbouring and future installations, we present a novel concept relying on the definition of thermal protection perimeters (TPP) around geothermal installations. These perimeters are determined by quantifying the thermal probability of capture around closed- and open-loop geothermal systems. Then, the maximal acceptable power that can be exploited in the vicinity of the installations can be continuously mapped. Existing analytical heat transport models are adapted to calculate these thermal capture probabilities. Two applications are illustrated in Lyon (France). The first application shows that adapted analytical models can help to manage multiple geothermal installations already in place in sectors of few square kilometres. In the second application, a numerical deterministic model is used to determine the TPP of one open-loop system at a local scale. The numerical approach applied for this case allows to account for flow disturbances caused by underground constructions, and thus offers a refined representativeness of the probability of capture. The presented methodology facilitates compatibility assessments between existing and planned new geothermal installations, which is otherwise not feasible by only mapping thermal plumes caused by existing installations, as done in common practice.

In this study, the nutrient regulation ecosystem service (ES) demand was quantified and mapped in an agriculturally-dominated landscape in the federal German state of North Rhine-Westphalia. The demand was assessed in a case study area on an individual field scale. As an indicator for the nutrient regulation ecosystem service demand, nitrogen budgets were calculated. The assessment includes a comparison of an agriculturally calculated nitrogen budget to an ecologically calculated nitrogen budget. The agricultural calculation is based on legal regulations and considers volatile nitrogen losses from fertilizers, whereas the ecological calculation incorporates the total amount of nitrogen and includes also the atmospheric nitrogen deposition. Furthermore, the positive effects of additional agricultural practices on the nutrient regulation ES demand were identified. The spatial distribution of the nutrient regulation ES demand was compared to the distribution of the nitrate leaching and denitrification potential in order to analyse the relative vulnerability of individual fields to nutrient oversupply. The findings of this study, which highlight in particular the suitability of enlarged crop rotation systems, can be used to support sustainable agricultural practices and land management strategies on the local sale.EDITED BY Christine Fürst

This paper reviews the sources of uncertainty in physical climate impact assessments. It draws on examples from related fields such as climate modelling and numerical weather prediction in discussing how to interpret the results of multi-model ensembles and the role of model evaluation. Using large-scale, multi-model simulations of hydrological extremes as an example, we demonstrate how large uncertainty at the local scale does not preclude more robust conclusions at the global scale. Finally, some recommendations are made: climate impact studies should be clear about the questions they want to address, transparent about the uncertainties involved, and honest about the assumptions being made.

This paper describes the process of planning, design, building and first operation tests of a carbonization reactor for the valorization of cashew nutshells, obtained as byproduct from small-scale cashew cultivation and processing in Bobo-Dioulasso, Burkina Faso. The main technical requirements for the reactor were: low cost and ease of construction, robustness, autothermal operation, no need for pre or post-treatments for feedstock and products, and readily useable product fractions in a local scale. Design modifications are discussed and justified. Characterization of the raw material, data from the first successful operational tests, as well as product distribution and characterization, are presented. This carbonization prototype allows for the sustainable valorization of an otherwise problematic biomass residue, creating added-value products that would enhance the economic profitability of local processors. The use of the main charcoal product as a fuel substitute for household cooking is preliminarily assessed, and the recovery of potentially valuable cashew nutshell liquid (CNSL) is accomplished.

Mussel distributions are often described as clumped or patchy. However, few surveys of mussel populations have been designed to quantify these spatial patterns. We used indicators of spatia...

The MOSARH21 project evaluated the future impacts of climate change on streamflows from the French tributaries of the River Rhine based on recent climate projections (CMIP5 experiment). The adopted methodology relies on two hydrological models (GRSD and LARSIM), used jointly with an ensemble of climate projections disaggregated at the local scale. The impacts were quantified with several indicators describing rivers regimes, floods and low flows. The evolutions of mean interannual streamflow indicate a slight increase, which could even become important for the radiative scenario RCP 8.5 (the most pessimistic one in terms of climate warming). Flood could intensify in the near future (2021-2050). In the far future (2071-2100), the evolution of floods indicators is more uncertain, as the hydrological projections diverge. Low flows could be decreasing in the near future. Their evolution in the far future is more uncertain, going from drastic decrease to sensible rise depending on the chosen scenario. The results were compared to those from previous impact studies performed on the basin. Given the methodological differences and the obtained results, we can conclude that the MOSARH21 project is consistent with the conclusions of the previous studies.

Groundwater vulnerability assessment is a basic work for groundwater exploitation and protection. The Chaoyang district of Beijing was selected and investigated in this study. Groundwater vulnerability index system in Chaoyang district was constructed based on hydrogeological settings of local region, the human influence and the DRASTIC model. The comprehensive vulnerability assessment was carried out with weights of 0.4 and 0.6 for the intrinsic vulnerability and the specific vulnerability, respectively. In this study, total 9 hydrogeological parameters were considered, and the diagram of groundwater vulnerability assessment results in Chaoyang District was obtained by using DRASTIC index and overlay weighted method. The groundwater quality is poor in the southwest of Chaoyang District. The correlation analysis between total hardness, total dissolved solids and vulnerability results was carried out, and the correlation results were 06 and 0.7, respectively. The area with high groundwater vulnerability is also the regions with serious groundwater pollution, indicating that the assessment results are objective and reasonable, which can provide prevention and control of groundwater reference for the management department in the future, so as to reduce the risk of pollution.

This study evaluates the relationship between both commercial and scientific spatial fisheries data and a new satellite-based estimate of potential fish production (Ocean Productivity available to Fish, OPFish) in the European Seas. To construct OPFish, we used productivity frontal features derived from chlorophyll-a horizontal gradients, which characterize 10%–20% of the global phytoplankton production that effectively fuels higher trophic levels. OPFish is relatively consistent with the spatial distribution of both pelagic and demersal fish landings and catches per unit of effort (LPUEs and CPUEs, respectively). An index of harvest relative to ocean productivity (HP index) is calculated by dividing these LPUEs or CPUEs with OPFish. The HP index reflects the intensity of fishing by gear type with regard to local fish production. Low HP levels indicate lower LPUEs or CPUEs than expected from oceanic production, suggesting over-exploitation, while high HP levels imply more sustainable fishing. HP allows comparing the production-dependent suitability of local fishing intensities. Our results from bottom trawl data highlight that over-exploitation of demersal species from the shelves is twice as high in the Mediterranean Sea than in the North-East Atlantic. The estimate of HP index by dominant pelagic and demersal gears suggests that midwater and bottom otter trawls are associated with the lowest and highest overfishing, respectively. The contrasts of fishing intensity at local scales captured by the HP index suggest that accounting for the local potential fish production can promote fisheries sustainability in the context of ecosystem-based fisheries management as required by international marine policies., With the institutional support of the ‘Severo OchoaCentre of Excellence’ accreditation (CEX2019-000928-S).

Airflows over complex geometrical surfaces such as complex terrain and densely built urban districts are highly turbulent and sometimes become a threat under disturbed weather conditions. Among the...

Since the seagrass Posidonia oceanica is highly sensitive to environmental changes, a monitoring of the physiognomy, phenology and lepidochronology of the meadows was conducted during 2015-2020 at Tremiti Islands Marine Protected Area (Adriatic Sea). The meadow resulted stressed where anthropogenic disturbances occurred, while the implementation of proper management measures proved to trigger the recovery of the habitat. Our results underlined the importance of P. oceanica as a biological indicator to monitor human activities at local scale.

The environmental effects of drought appear to be substantial. At local scales, even small areas can have diverse climates due to their geographical location. This study compares the cumulative effect of daily droughts from 1989 to 2019 using daily precipitation data from nine synoptic stations in the Tehran Province, Iran. The Effective Drought Index (EDI), the Standardized Precipitation Index (SPI), and the China Z-Index (CZI) have been applied to calculate droughts. Initially, we have determined drought characteristics (severity, frequency, and duration) using the run theory. Later, the copula models (Frank, Gaussian, and Gumbel) have been used to find dependence between drought characteristics at different time scales as a cumulative effect. The results show that a pattern of the number and order of temporal distribution variables of precipitation play a major role in intensifying droughts. Also, the findings indicate that the frequency-duration of daily droughts in semi-arid and mountainous stations located in the north of the province has a cumulative effect on monthly and annual droughts. The severity frequency of daily droughts affects long-term droughts in the stations located in the middle and south of the province characterized by a drier climate. The variability in the intensity and shift of daily droughts in the mountainous stations is higher compared to other areas but it decreases on monthly and annual scales. This study found that the copula model is an ideal tool to demonstrate regional differences of drought in the regions with climatic and geographical diversity.

The small-scale variability of fog over Paris-CdG airport was explored by using the twelve visibility measurements installed on runways. The variability inside this sub-kilometre area is significant for fog, whatever the studied fog characteristics. These results confirm that about 50% of fog is thin and heterogeneous at the airport scale. This study indicated that one point of measurement may be far from the representativeness of sub-kilometre scale area and can create problems when used for verifying numerical models. The fog characteristics cannot be captured by a local measurement of visibility, and it is not possible to deduce fog extension at the local scale from a local measurement, even for low visibility such as for LVP cases (Low Visibility Procedures). This work demonstrated with a perfect forecast framework that a large dispersion of forecast scores could be obtained when using one observation at the local-scale due to representativeness errors of visibility measurements. This dispersion has the same order of magnitude as the current NWP forecast quality of fog. An attempt to quantify the scale heterogeneity of fog was made using the Gini index. This index has allowed highlighting the appearance of waves during the dissipation phase of fog.

Dam construction and reservoir formation alters hydro-morphology of rivers, thereby restructuring microbial communities and biogenic element cycles in river ecosystems. The ecological responses and mechanisms of planktonic communities showed notable changes upstream and downstream of dams. Yet, less is reported about how the ecological mechanisms structuring planktonic communities at the closest area upstream and downstream of dams. In this study, we hypothesized that planktonic communities remained the connectivity or similarities but show distinctive ecological responses to changing environment at the closes area upstream and downstream of dams. Three large dams in the upper Yangtze River were chosen in the study. Field data revealed that the alpha diversity indexes slightly increased downstream of the dams. In addition, more eukaryotic ASVs solely occurred downstream of the dams, indicating that a large proportion of eukaryotes was formed downstream of the dams. Co-occurrence network analysis demonstrated that the keystone species of planktonic bacteria and eukaryotes decreased downstream of the dams, and the modularity increased. The robustness of the co-occurrence relationships among the eukaryotic communities was more strongly influenced by these dams than that among the planktonic bacteria. The variance partitioning analysis results indicated that dam-related variables and local environmental variables mainly shape the assembly of the planktonic microbial communities closest to the dams. In conclusion, dams exert a greater impact on planktonic eukaryotes than on bacteria in near-dam areas, and planktonic bacteria can better adapt to changing environments. Our study provides a better understanding of the ecological effects of river damming.

This study aims to investigate local-scale meteorological conditions associated with large fires in Brazil during recent decades. We assess whether there are large fire types with preceding predictors. Our results show that large fires, defined with a threshold of a daily burned area >95th percentile of the historical record, mainly occur in August and September in Brazil, and Amazônia and Cerrado experience much higher numbers of large fires than the other biomes. There are two large fire types that have robust meteorological signatures: (1) a wind driven type, characterized by peak wind speed on the day of the fire, and anomalously high wind speed a few (∼3) days before and after the fire; and (2) a Hot-Drought driven type, characterized by anomalously high temperature, low relative humidity, and consistent drought conditions indicated by anomalously high fuel aridity starting as far back as 5 months prior to the fires. A third one is characterized by no anomalous meteorological conditions. The wind driven type most frequently occurs in southern and southeastern Amazônia, Pantanal, and western and northern-to-central Cerrado, with some occurrences over the western Caatinga region bordering Cerrado, southern Cerrado, and southern Mata Atlântica; whereas the Hot-Drought driven type most frequently occurs in southern and southeastern Amazônia, Pantanal and western and northern-to-central Cerrado, with some occurrences over the western Caatinga region bordering Cerrado, southern Cerrado, central-to-southern Mata Atlântica, and a few occurrences over Northern Brazil where the Amazônia meets Roraima. Southern and southeastern Amazônia, Pantanal and western and northern-to-central Cerrado are the major large fire prone regions. Our results highlight that understanding the temporal and spatial variability of the meteorological conditions associated with large fires is essential for developing spatially explicit forecasting, and future projections of large fire hazards under climate change in Brazil, in particular the Hot-Drought driven type.

Identifying the driving factors of urban land surface temperatures (U-LSTs) is critical in improving urban thermal environments and in supporting the sustainable development of cities. Previous studies have demonstrated that two- and three-dimensional (2D and 3D) urban structure parameters (USPs) largely influence seasonal U-LSTs. However, the effects of 2D and 3D USPs on seasonal U-LSTs at different spatial scales still await a general explanation. In this study, we used very-high-resolution remotely sensed data to investigate how 2D and 3D USPs impact seasonal U-LSTs at different spatial scales (including pixel and city block scales). In addition, the influences of various functional zones on U-LSTs were analyzed. The results show that, (1) generally, the links between USPs and U-LSTs at the city block scale were more obvious than those at the pixel scale, e.g., the Pearson correlation coefficient (r) between U-LST and the mean building height at the city block scale (summer: r = −0.156) was higher than that at the pixel scale (summer: r = −0.081). Tree percentage yielded a considerable cooling effect on summer U-LSTs on both the pixel (r = −0.199) and city block (r = −0.369) scales, and the effect was more obvious in regions with tall trees. (2) The independently total explained variances (R2) of 3D USPs on seasonal U-LSTs were considerably higher than those of 2D USPs in most urban functional zones (UFZs), suggesting the distinctive roles of 3D USPs in U-LST regulation at the local scale. Three-dimensional USPs (R2 value = 0.66) yielded more decisive influences on summer U-LSTs than 2D USPs did (R2 value = 0.48). (3) Manufacturing zones yielded the highest U-LST, followed by residential and commercial zones. Notably, it is found that the explained variances of the total study area for seasonal U-LSTs were significantly lower than those of each UFZ, suggesting the different roles of 2D and 3D USPs played in various UFZs and that it is critical to explain U-LST variations by using UFZs.

Groundwater plays a critical role in the water- food-energy nexus and extensively supports global drinking water and food production. Despite the pressing demands for groundwater resources, groundwater withdrawals are not actively monitored in most regions. Thus, reliable methods are required to estimate withdrawals at local scales suitable for implementing sustainable groundwater management practices. Here, we combine publicly available remote sensing datasets into a deep learning framework for estimating groundwater withdrawals at high resolution (5 km) over the states of Arizona and Kansas in the USA. We compare ensemble machine learning and deep learning algorithms using groundwater pumping data from 2002–2019. Our research shows promising results in sub-humid and semi-arid (Kansas) and arid (Arizona) regions, which demonstrates the robustness and extensibility of this integrated approach. The success of this method indicates that we can effectively and accurately estimate local-scale groundwater withdrawals under different climatic conditions and aquifer properties.

In this study we present the first findings of the potential utility of miniaturized Light and Detection Ranging (LiDAR) scanners mounted on Unmanned Aerial Vehicles (UAVs) for improving urban flood assessment at the local scale. This is done by generating high spatial resolution Digital Terrain Models (DTM) featuring buildings and urban microtopographic structures that can affect floodwater pathways (DTMbs). The accuracy and level of detail of the flooded areas simulated by a hydrologic screening model (Arc-Malstrøm), were vastly improved when DTMbs of 0.3 m resolution representing three urban sites surveyed by a UAV-LiDAR in Accra, Ghana, supplemented a commercially available 10 m resolution DTM covering the full catchment area of the region. The generation of DTMbs necessitated the effective classification of UAV-LiDAR point clouds using a morphological and a triangulated irregular network method for hilly and flat landscapes, respectively. The UAV-LiDAR enabled the identification of archways, boundary walls and bridges that were critical when predicting precise runoff courses that could not be projected using the DTM only. Variations in a stream’s geometry due to a one-year time gap between the satellite-based and UAV-LiDAR datasets were also observed. The application of the coarser DTM produced an overestimation of water flows equal to 15% for sloping terrain and up to 62.5% for flat areas when compared to the respective runoff simulated using the DTMbs. The application of UAV-LiDAR may enhance the effectiveness of urban planning by projecting precisely the location, extent and runoff of flooded areas in dynamic urban settings.

Critical groundwater overdraft is one of the greatest water issues of our time. In California, decades of overdraft have resulted in the passage of the 2014 Sustainable Groundwater Management Act, which requires critically overdrafted groundwater basins to create groundwater sustainability plans for future groundwater management. Many managers are using managed aquifer recharge (MAR) in their overall sustainability portfolio, in an attempt to balance groundwater use. Soil maps have been used in the past to determine viability of managed aquifer recharge sites. However, soil maps do not account for the high permeability pathways that exist in the subsurface, which have the potential to provide high efficiency recharge to the water table. This paper emphasizes the utility of creating data dense fine resolution geostatistical models and generating many realizations of the subsurface, which can then be used for analysis to understand the variability in recharge potential for specific recharge sites. These geostatistical realizations were investigated using connectivity metrics to evaluate the spread of highly conductive pathways throughout the subsurface. Connectivity analyses of high conductivity pathways show confidence that the study site- three vineyards located in the floodplain between the Cosumnes River and Deer Creek in Elk Grove, CA - has the potential to provide efficient recharge to the water table. These connectivity analyses can be completed prior to running computationally expensive and time intensive groundwater models and can be used as a way to understand variance between realizations of these geostatistical models.

Natural variability of regional climatic conditions poses certain difficulties in detecting global climate change at a local scale. The question about the ratio between the contribution of human forcing, induced by the increase in atmospheric carbon dioxide concentration, and the contribution of natural variability in atmospheric and oceanic circulation arises in each particular case. The purpose of the study reported in this article was to evaluate the contribution of the North Atlantic Oscillation to decrease in Moscows climate continentality during the period of 1951-2000. The results of this study show that a significant part of the decrease in continentality could be attributed to increase in the North Atlantic Oscillation index observed during this period.

Open-cast lignite mines are sources of PM- emissions, caused by mining activities and wind erosion on the large bare deposition areas. PM10- and PM2.5-emissions of these technogenic materials have not been determined in detail so far, but are needed for emission cadastres or in dispersion models at the local scale In wind tunnel experiments substrates from the four active mines in Lower Lusatia in eastern Germany were investigated to estimate PM10- and PM2.5-emissions. The substrates include the cover layers and the lignite seams. Two experimental approaches were compared to relate the PM- emissions of the substrates to the main releasing mechanisms and substrate characteristics. The results show that lignite and lignite containing substrates emit distinctly higher amounts of PM10 and PM2.5 than mineral substrates, regardless of the releasing process. The estimated PM-emission potentials (PM-EP) ranged between 5 and 650 µg g−1 for PM10 and between 2 and 44 µg g−1 for PM2.5 and are correlated to the dry sieving fraction The highest PM- emissions per m2 occur together with the highest transport rates, although the materials themselves have low PM-EP. A distinct higher rate is emitted from lignite samples and substrates permeated with lignite. Wind erosion increases the PM10- emissions to 360 per cent and the PM2.5-emissions to 270 per cent of the PM-EP. The PM10- emissions of the mineral substrates are close to the potentials and heterogeneity of the materials has also an increasing effect.