Nature-based solutions can help reduce the impact of natural hazards: A global analysis of NBS case studies.

The knowledge derived from successful case studies can act as a driver for the implementation and upscaling of nature-based solutions (NBS). This work reviewed 547 case studies to gain an overview of NBS practices and their role in reducing the adverse impact of natural hazards and climate change. The majority (60 %) of case studies are situated in Europe compared with the rest of the world where they are poorly represented. Of 547 case studies, 33 % were green solutions followed by hybrid (31 %), mixed (27 %), and blue (10 %) approaches. Approximately half (48 %) of these NBS interventions were implemented in urban (24 %), and river and lake (24 %) ecosystems. Regarding the scale of intervention, 92 % of the case studies were operationalised at local (50 %) and watershed (46 %) scales while very few (4 %) were implemented at the landscape scale. The results also showed that 63 % of NBS have been used to deal with natural hazards, climate change, and loss of biodiversity, while the remaining 37 % address socio-economic challenges (e.g., economic development, social justice, inequality, and cohesion). Around 88 % of NBS implementations were supported by policies at the national level and the rest 12 % at local and regional levels. Most of the analysed cases contributed to Sustainable Development Goals 15, 13, and 6, and biodiversity strategic goals B and D. Case studies also highlighted the co-benefits of NBS: 64 % of them were environmental co-benefits (e.g., improving biodiversity, air and water qualities, and carbon storage) while 36 % were social (27 %) and economic (9 %) co-benefits. This synthesis of case studies helps to bridge the knowledge gap between scientists, policymakers, and practitioners, which can allow adopting and upscaling of NBS for disaster risk reduction and climate change adaptation and enhance their preference in decision-making processes.

Impacts of town characteristics on the changing urban climate in Vantaa.

In this work, the climatic impacts of modifying urban surface characteristics are examined for the medium-sized city of Vantaa, Finland, in the current climate and in a projected future climate of 2040-2069. In simulations with the SURFEX air-surface interaction model with a horizontal resolution of 500 m, the fraction of green spaces and relatively sparsely built suburban-type land use was increased at the expense of more densely built commercial and industrial areas. The influence of this land use intervention was found to be rather modest but comparable to the effects of the expected climate change under the RCP8.5 greenhouse gas scenario. For temperature, the climate change is the dominating effect, while wind speed is mainly controlled by surface characteristics. For relative humidity, climate change and the imposed intervention are of comparable importance. The results of this sensitivity study are intended to support policy makers by assessing the potential impact of altering the urban layout in order to improve thermal comfort or as a countermeasure to climate warming in a high-latitude city.

How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations.

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30' N, 11°21' E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution.

Towards an operationalisation of nature-based solutions for natural hazards.

Nature-based solutions (NBS) are being promoted as adaptive measures against predicted increasing hydrometeorological hazards (HMHs), such as heatwaves and floods which have already caused significant loss of life and economic damage across the globe. However, the underpinning factors such as policy framework, end-users' interests and participation for NBS design and operationalisation are yet to be established. We discuss the operationalisation and implementation processes of NBS by means of a novel concept of Open-Air Laboratories (OAL) for its wider acceptance. The design and implementation of environmentally, economically, technically and socio-culturally sustainable NBS require inter- and transdisciplinary approaches which could be achieved by fostering co-creation processes by engaging stakeholders across various sectors and levels, inspiring more effective use of skills, diverse knowledge, manpower and resources, and connecting and harmonising the adaptation aims. The OAL serves as a benchmark for NBS upscaling, replication and exploitation in policy-making process through monitoring by field measurement, evaluation by key performance indicators and building solid evidence on their short- and long-term multiple benefits in different climatic, environmental and socio-economic conditions, thereby alleviating the challenges of political resistance, financial barriers and lack of knowledge. We conclude that holistic management of HMHs by effective use of NBS can be achieved with standard compliant data for replicating and monitoring NBS in OALs, knowledge about policy silos and interaction between research communities and end-users. Further research is needed for multi-risk analysis of HMHs and inclusion of NBS into policy frameworks, adaptable at local, regional and national scales leading to modification in the prevalent guidelines related to HMHs. The findings of this work can be used for developing synergies between current policy frameworks, scientific research and practical implementation of NBS in Europe and beyond for its wider acceptance.

Nature-based solutions for hydro-meteorological hazards: Revised concepts, classification schemes and databases.

Hydro-meteorological hazards (HMHs) have had a strong impact on human societies and ecosystems. Their impact is projected to be exacerbated by future climate scenarios. HMHs cataloguing is an effective tool to evaluate their associated risks and plan appropriate remediation strategies. However, factors linked to HMHs origin and triggers remain uncertain, which pose a challenge for their cataloguing. Focusing on key HMHs (floods, storm surges, landslides, droughts, and heatwaves), the goal of this review paper is to analyse and present a classification scheme, key features, and elements for designing nature-based solutions (NBS) and mitigating the adverse impacts of HMHs in Europe. For this purpose, we systematically examined the literature on NBS classification and assessed the gaps that hinder the widespread uptake of NBS. Furthermore, we critically evaluated the existing literature to give a better understanding of the HMHs drivers and their interrelationship (causing multi-hazards). Further conceptualisation of classification scheme and categories of NBS shows that relatively few studies have been carried out on utilising the broader concepts of NBS in tackling HMHs and that the classification and effectiveness of each NBS are dependent on the location, architecture, typology, green species and environmental conditions, as well as interrelated non-linear systems. NBS are often more cost-effective than hard engineering approaches used within the existing systems, especially when taking into consideration their potential co-benefits. We also evaluated the sources of available data for HMHs and NBS, highlighted gaps in data, and presented strategies to overcome the current shortcomings for the development of the NBS for HMHs. We highlighted specific gaps and barriers that need to be filled since the uptake and upscaling studies of NBS in HMHs reduction is rare. The fundamental concepts and the key technical features of past studies reviewed here could help practitioners to design and implement NBS in a real-world situation.

Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models.

Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offer limited modelling options to evaluate its impact on ambient pollutant concentrations. The scope of this review revolves around the following question: how can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examined the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. We evaluated the limitations of different air pollution dispersion models at two spatial scales - microscale (i.e. 10-500 m) and macroscale (i.e. 5-100 km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that the deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. An appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. The impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The i-Tree tool with the BenMap model has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.

On the interactions between airflow and ice melting in ice caves: A novel methodology based on computational fluid dynamics modeling.

Motivated by progressive climate-change influence on ice degradation in caves, in this paper we present a novel methodology to investigate the link between air dynamics and ice melting. Specifically, we use surveys available for the Leupa ice cave (LIC), located in the Canin-Kanin group in the southeastern Alps and a general purpose computational fluid dynamics model (CFD). Detailed numerical simulations are evaluated on the basis of well-established approaches that consider domain, grid, boundary-conditions, turbulence closure models, buoyancy effects, porous media properties and verification with measured data. External atmospheric conditions are the main trigger for internal circulation but morphology and thermal characteristics of ice and bedrock induce a dynamical process of heat exchange ultimately responsible for ice melting. This process is generally poorly documented in real conditions. Using CFD analyses we show that both in summer and winter, warm and cold air currents within the cave are "disturbed" by several vortices and stagnation zones which locally modify the energy balance. To account for this we introduce a macroscopic physical model based on energy balance between ice surfaces and the inner ice cave airflow to determine the heat exchanged between ice and air. Using this model, a prediction of ice thickness decay over time is obtained. In the case of LIC a reduction of initial 4 cm per year is first obtained with projection of a much faster increase. The methodology is general and easily extendable to other sites, proving to be a powerful method to estimate ice evolution in caves induced by external and internal forcing.

Polycyclic aromatic hydrocarbons in a bakery indoor air: trends, dynamics, and dispersion.

Indoor air pollution assessment in work environments remains challenging due to a combination of logistic reasons and availability of costly instrumentation for data acquisition and post-processing. Existing literature focuses on energy production environments, hospitals, and less so on food production spaces. Studies on indoor air quality in bakeries are scarce or even absent. Motivated by this, the present study investigates indoor air quality in a bakery located in Bari province in South Italy, using a combination of approaches including analytical chemistry analyses and computational fluid dynamics to reconstruct the air ventilation in response to air temperature gradients within the working environment. PM2.5 indoor samplings were collected every 6 h from 7 to 19 April 2013 in the proximity of two bakery ovens powered by gas and wood, respectively. For each sampling day, 4 PM2.5 samples were collected: from 3:00 to 9:00 h (first), from 9:00 to 13:30 h (second), from 14:00 to 21:00 h (third), and from 21:00 to 3:00 h (fourth). In total, 40 samples were collected. On each sample, several polycyclic aromatic hydrocarbons (PAHs) were determined such as benzo[a]anthracene (228), benzo[b]fluoranthene (252), benzo[k]fluoranthene (252), benzo[a]pyrene (252), benzo[g,h,i]perylene (276), indeno[1,2,3-cd]pyrene (276), and dibenzo[a,h]anthracene (278), the main compounds of 16 priority US Environmental Protection Agency (US-EPA) PAHs in particulate phase. The PAH mean concentrations showed higher values during the first (from 3:00 to 9:00 h) and fourth (from 21:00 to 3:00 h) sampling intervals than the other two with benzo[a]pyrene mean values exceeding the Italian law limit of 1 ng/m3. Taking into account benzo[a]pyrene mean concentration for the first interval and the first plus the second one, which are the hours with the largest working activity, we have estimated that the baker and co-workers are exposed to a cancer risk of 4.3 × 10-7 and 5.8 × 10-7, respectively (these values are lower than US-EPA recommended guideline of 10-6). Our study was complemented by numerical analyses using state-of-the-art computational fluid dynamics to reconstruct at high resolution air movement from the various working places, i.e., the bakery and the selling area which were connected via a door. The numerical simulations were possible given that surface temperature using infrared thermography as well as air temperature was continuously recorded throughout the sampling acquisition. The use of this approach allowed us to estimate the transport and diffusion of benzo[a]pyrene from one area to the other thus complementing the point sampling information. Computational fluid dynamic simulation results confirm the presence of benzo[a]pyrene in the laboratory as obtained from the measurements and suggests its presence in the sales' area of the bakery with concentrations similar those found in the laboratory.

End-user perspective of low-cost sensors for outdoor air pollution monitoring.

Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network.

Global assessment of heat wave magnitudes from 1901 to 2010 and implications for the river discharge of the Alps.

Heat waves represent one of the most significant climatic stressors for ecosystems, economies and societies. A main topic of debate is whether they have increased or not in intensity and/or their duration due to the observed climate change. Firstly, this is because of the lack of reliable long-term daily temperature data at the global scale; secondly, because of the intermittent nature of such phenomena. Long datasets are required to produce a reliable and meaningful assessment. In this study, we provide a global estimate of heat wave magnitudes based on the three most appropriate datasets currently available, derived from models and observations (i.e. the 20th Century Reanalyses from NOAA and ECMWF), spanning the last century and before. The magnitude of the heat waves is calculated by means of the Heat Wave Magnitude Index daily (HWMId), taking into account both duration and amplitude. We compare the magnitude of the most severe heat waves occurred across different regions of the world and we discuss the decadal variability of the larger events since the 1850s. We concentrate our analysis from 1901 onwards, where all datasets overlap. Our results agree with other studies focusing on heat waves that have occurred in the recent decades, but using different data. In addition, we found that the percentage of global area covered by heat wave exceeding a given magnitude has increased almost three times, in the last decades, with respect to that measured in the early 20th century. Finally, we discuss the specific implications of the heat waves on the river runoff generated in the Alps, for which comparatively long datasets exist, affecting the water quality and availability in a significant portion of the European region in summer.

The rise of low-cost sensing for managing air pollution in cities.

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, while addressing the major challenges for their effective implementation.

On the contribution of mean flow and turbulence to city breathability: the case of long streets with tall buildings.

This paper analyses the contribution of mean flow and turbulence to city breathability within urban canopy layers under the hypothesis that winds from rural/marine areas are sources of clean air (inhale effect) and main contributors to local-scale pollutant dilution (exhale effect). Using Computational Fluid Dynamics (CFD) simulations, several idealized long streets flanked by tall buildings are investigated for wind flow parallel to the street axis. Aspect ratios (building height/street width) ranging from 2 to 4 and street lengths ranging from neighborhood scales (~1km in full scale) to city scales (~10km in full scale) are analyzed. To assess the inhale effect, the age of air concept is applied to quantify the time taken by a parcel of rural/marine air to reach a reference location within the urban canopy layer. To simulate the exhale effect, removal of pollutants released from a ground level source is considered. Numerical results agree with wind tunnel observations showing that a bulk portion of rural/marine air enters the streets through windward entries, a smaller part of it leaves through street roofs and the remaining fraction blows through the street aiding pollutant dilution. Substantial differences between neighborhood-scale and city-scale configurations are found. For neighborhood-scale models, pollutant removal by rural/marine air is mainly associated to mean flow along the streets. Breathability improves in streets flanked by taller buildings since in this case more rural/marine air is captured inside canyons leading to stronger wind along the street. For city-scale models, pollutant removal due to turbulent fluctuations across street roofs competes with that due to mean flows along the street. Breathability improves in streets flanked by lower buildings in which less rural/marine air is driven out and pollutant removal by turbulent fluctuations is more effective. Based on these findings, suggestions for ventilation strategies for urban areas with tall buildings are provided.

Aerodynamic effects of trees on pollutant concentration in street canyons.

This paper deals with aerodynamic effects of avenue-like tree planting on flow and traffic-originated pollutant dispersion in urban street canyons by means of wind tunnel experiments and numerical simulations. Several parameters affecting pedestrian level concentration are investigated, namely plant morphology, positioning and arrangement. We extend our previous work in this novel aspect of research to new configurations which comprise tree planting of different crown porosity and stand density, planted in two rows within a canyon of street width to building height ratio W/H=2 with perpendicular approaching wind. Sulfur hexafluoride was used as tracer gas to model the traffic emissions. Complementary to wind tunnel experiments, 3D numerical simulations were performed with the Computational Fluid Dynamics (CFD) code FLUENT using a Reynolds Stress turbulence closure for flow and the advection-diffusion method for concentration calculations. In the presence of trees, both measurements and simulations showed considerable larger pollutant concentrations near the leeward wall and slightly lower concentrations near the windward wall in comparison with the tree-less case. Tree stand density and crown porosity were found to be of minor importance in affecting pollutant concentration. On the other hand, the analysis indicated that W/H is a more crucial parameter. The larger the value of W/H the smaller is the effect of trees on pedestrian level concentration regardless of tree morphology and arrangement. A preliminary analysis of approaching flow velocities showed that at low wind speed the effect of trees on concentrations is worst than at higher speed. The investigations carried out in this work allowed us to set up an appropriate CFD modelling methodology for the study of the aerodynamic effects of tree planting in street canyons. The results obtained can be used by city planners for the design of tree planting in the urban environment with regard to air quality issues.