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The LES-based PALM model system 6.0 is a state-of-the-art atmospheric numerical model widely used among scientists for urban boundary layer and urban climate studies. Despite being subjected to many validation and sensitivity studies which tested the model’s accuracy and applicability to urban environments, a major step is needed to test its sensitivity to different driving conditions.In this study, we performed a series of PALM model simulations for a given domain and two selected episodes during the year 2019. Each simulation lasts 72 h, and all of them were performed for an 8 km x 8 km domain in 10 m resolution encompassing a real built-up residential area in the southeast part of the city of Prague, Czech Republic. The simulation setups are identical apart from the initial and boundary conditions imposed. For that purpose we utilized the mesoscale WRF model and created an ensemble consisting of several members with different parameterization schemes.This study's findings are serving to better understand how different initial and boundary conditions affect the PALM model simulations. In addition, we present the process, complexity, and challenges one can encounter while trying to find the optimal set of initial and boundary conditions for a given PALM model simulation. Moreover, the performed simulations have shown that most of the variance in the ensemble comes from the driving conditions.

We tried to reproduce results measured in the wind tunnel experiment with a CFD simulation provided by numerical model PALM. A realistic buildings layout from the Prague-Dejvice quarter has been chosen as a testing domain because solid validation campaign for PALM simulation of Atmospheric Boundary Layer (ABL) over this quarter was documented in the past. The question of input data needed for such simulation and capability of the model to capture correctly the inlet profile and its turbulence structure provided by the wind-tunnel is discussed in the study. The PALM dynamical core contains a solver for the Navier-Stokes equations. By default, the model uses the Large Eddy Simulation (LES) approach in which the bulk of the turbulent motions is explicitly resolved. It is well validated tool for simulations of the complex air-flow within the real urban canopy and also within its reduced scale provided by wind tunnel experiments. However the computed flow field between the testing buildings did not correspond well to the measured wind velocity in some points. Different setting of the inlet boundary condition was tested but none of them gave completely developed turbulent flow generated by vortex generators and castellated barrier wall place at the entrance of the aerodynamic section of the wind tunnel.

In recent years, the PALM 6.0 modelling system has been rapidly developing its capability to simulate physical processes within urban environments. Some examples in this regard are energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, a plant-canopy model to consider the effects of plants on flow (thermo)dynamics, and a chemistry transport model to enable simulation of air quality. This study provides a thorough evaluation of modelled meteorological, air chemistry, and ground and wall-surface quantities against dedicated in situ measurements taken in an urban environment in Dejvice, Prague, the Czech Republic. Measurements included monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared cameras, and monitoring of wall heat fluxes. Large-eddy simulations (LES) using the PALM model driven by boundary conditions obtained from a mesoscale model were performed for multiple days within two summer and three winter episodes characterized by different atmospheric conditions. For the simulated episodes, the resulting temperature, wind speed, and chemical compound concentrations within street canyons show a realistic representation of the observed state, except that the LES did not adequately capture night-time cooling near the surface for certain meteorological conditions. In some situations, insufficient turbulent mixing was modelled, resulting in higher near-surface concentrations. At most of the evaluation points, the simulated surface temperature reproduces the observed surface temperature reasonably well for both absolute and daily amplitude values. However, especially for the winter episodes and for modern buildings with multilayer walls, the heat transfer through walls is not well captured in some cases, leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, the study corroborates model dependency on the accuracy of the input data. In particular, the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land surface temperatures at grass surfaces strongly depend on the initial soil moisture, wall-surface temperatures depend on the correct setting of wall material parameters, and concentrations depend on detailed information on spatial distribution of emissions, all of which are often unavailable at sufficient accuracy. The study also points out some current model limitations, particularly the implications of representing topography and complex heterogeneous facades on a discrete Cartesian grid, and glass facades that are not fully represented in terms of radiative processes. Our findings are able to validate the representation of physical processes in PALM while also pointing out specific shortcomings. This will help to build a baseline for future developments of the model and improvements of simulations of physical processes in an urban environment.

The Radiative Transfer Model (RTM) is an explicitly resolved three-dimensional multi-reflection radiation model integrated into the PALM modelling system. It is responsible for modelling complex radiative interactions within the urban canopy. It represents a key component in modelling energy transfer inside the urban layer and consequently PALM's ability to provide explicit simulations of the urban canopy at metre-scale resolution. This paper presents RTM version 3.0, which is integrated into the PALM modelling system version 6.0. This version of RTM has been substantially improved over previous versions. A more realistic representation is enabled by the newly simulated processes, e.g. the interaction of longwave radiation with the plant canopy, evapotranspiration and latent heat flux, calculation of mean radiant temperature, and bidirectional interaction with the radiation forcing model. The new version also features novel discretization schemes and algorithms, namely the angular discretization and the azimuthal ray tracing, which offer significantly improved scalability and computational efficiency, enabling larger parallel simulations. It has been successfully tested on a realistic urban scenario with a horizontal size of over 6 million grid points using 8192 parallel processes.

In recent years, the the Large-eddy simulation (LES) model PALM has been rapidly developed its capability to simulate physical processes within urban environments. For example, this includes energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, a plant-canopy model to consider the effects of plants on flow (thermo-)dynamics, and a chemistry transport model, as well as nesting capabilities that enable “hot-spot” analysis, to name a few. This contribution provides an evaluation of modeled meteorological as well as ground and wall-surface quantities against dedicated in-situ measurements taken in an urban environment in Dejvice, Prague. Measurements included monitoring of surface temperature and wall heat fluxes. Simulations were performed for multiple days during several summer and winter episodes, characterized by different atmospheric conditions. To consider time-evolving synoptic conditions, boundary conditions were obtained from mesoscale WRF simulations. For the simulated episodes, the resulting temperature and wind speed within street canyons show a realistic representation of the observed state, except that the LES did not adequately capture night-time cooling near the surface in some scenarios. At most of the evaluation points, the simulated surface temperature reproduces the observed surface temperature reasonably well, for both, absolute and daily amplitude values. However, especially for the winter episodes and for modern buildings with multi-layer wall structure, the heat transfer through the walls is not well captured in some cases, leading to discrepancies between the modeled and observed wall-surface temperature. Moreover, we also show that the model performance with respect to the observations strongly depends on the accuracy of the input data. To name a few, this includes e.g. the prescribed initial soil moisture, the given leaf-area densities to account for correct shading, or if a facade is insulated or not. Additionally, we will point out current model limitations, particularly implications accompanied by the step-like topography on the Cartesian grid, or wide glass facades that are not fully represented in terms of radiative processes. With our findings we are able to evaluate the representation of physical processes in PALM, while also pointing out specific shortcomings.

Sensitivity of the PALM model 6.0 with respect to land-surface and building properties is tested in a real urban environment in the vicinity of a typical crossroads in a densely built-up residential area in Prague, Czech Republic. The turbulence-resolving PALM is able to simulate the urban boundary layer flow for realistic setups. Besides an accurate representation of the relevant physical processes, the model performance also depends on the input data describing the urban setup, namely the building and land-surface properties. Two types of scenario are employed. The first one is the synthetic scenarios altering mainly surface and material parameters such as albedo, emissivity or wall conductivity, testing sensitivity of the model simulations to potentially erroneous input data. Second, urbanistic-type scenarios are analysed, in which commonly considered urban heat island mitigation measures such as greening of the streets or changing surface materials are applied in order to assess the limits of the effects of a particular type of scenario. For the synthetic scenarios, surface parameters used in radiation balance equations are found to be the most sensitive overall followed by the volumetric heat capacity and thermal conductivity of walls. Other parameters show a limited average effect; however, some can still be significant during some parts of the day, such as surface roughness in the morning hours. The second type, the urbanistic scenarios, shows urban vegetation to be the most effective measure, especially when considering both physical and biophysical temperature indicators. The influence of both types of scenario was also tested for air quality, specifically PM2.5 dispersion, which generally shows opposite behaviour to that of thermal indicators; i.e. improved thermal comfort brings deterioration of PM2.5 concentrations.

Urban population is affected by many processes typical for urban landscapes. Spatial patterns of physical, social, behavioral and environmental elements of urban environments and their interactions with human beings have been therefore gaining interest of scholars as well as politicians and local actors for decades. The combination of climate change, growing urban population and increasing computing capabilities opens up space for new areas of spatial analyses in urban environments—among them analyses of human thermal comfort. Consequently, modeling of thermal exposure as a cardinal factor of thermal comfort in real outdoor urban environments represents a pending and challenging task for urban climate research.

The Radiative Transfer Model (RTM) is an explicitly resolved three-dimensional multi-reflection radiation model integrated into the PALM modelling system. It is responsible for modelling complex radiative interactions within the urban canopy. It represents a key component in modelling energy transfer inside the urban layer and consequently PALM's ability to provide explicit simulations of the urban canopy at metre-scale resolution. This paper presents RTM version 3.0, which is integrated into the PALM modelling system version 6.0. This version of RTM has been substantially improved over previous versions. A more realistic representation is enabled by the newly simulated processes, e.g. the interaction of longwave radiation with the plant canopy, evapotranspiration and latent heat flux, calculation of mean radiant temperature, and bidirectional interaction with the radiation forcing model. The new version also features novel discretization schemes and algorithms, namely the angular discretization and the azimuthal ray tracing, which offer significantly improved scalability and computational efficiency, enabling larger parallel simulations. It has been successfully tested on a realistic urban scenario with a horizontal size of over 6 million grid points using 8192 parallel processes. © 2021 Pavel Krč et al.

The PALM 6.0 model system has been rapidly developed in the recent years with respect to its capability to simulate physical processes within urban environments. In this regard, it includes e.g. energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, as well as a plant-canopy model to consider the effects of plants on the (thermo)dynamics of the flow. This study provides a thorough evaluation of modelled meteorological, air chemistry and wall-surface quantities against dedicated in-situ measurements taken in an urban environment in Prague, Dejvice, Czech Republic. Measurements included e.g. monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared camera and monitoring of wall heat fluxes. Large-eddy simulations (LES) for multiple days within two summer and three winter episodes that are characterized by different atmospheric conditions were performed with the PALM model driven by boundary conditions obtained from a mesoscale model. For the simulated episodes, the resulting temperature, wind speed and concentrations of chemical compounds within street canyons agreed well with the observations, except the LES did not adequately capture nighttime cooling near the surface at certain meteorological conditions. In some situations, less turbulent mixing was modelled resulting in higher near-surface concentrations. At most of the surface evaluation points the simulated wall-surface temperature agreed fairly well with the observed one regarding its absolute value as well as daily amplitude. However, especially for the winter episodes and for modern buildings with multi-layer walls, the heat transfer through the wall is partly not well captured leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, we show that model results depend on the accuracy of the input data, particularly the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land-surface temperatures at grass surfaces strongly depend on the initial soil moisture, or wall-surface temperatures depend on the correct prescription of wall material parameters, though these parameters are often not available with sufficient accuracy. Moreover, we also point out current model limitations, here we particularly focus on implications with respect to the discrete representation of topography on a Cartesian grid, complex heterogeneous facades, as well as glass facades that are not well represented in terms of radiative processes. With these findings presented, we aim to validate the representation of physical processes in PALM as well as to point out specific shortcomings. This will help to build a baseline for future developments of the model and for improvements of simulations of physical processes in an urban environment.

Including radiative transfer processes within the urban canopy layer into microscale urban climate models (UCMs) is essential to obtain realistic model results. These processes include the interaction of buildings and vegetation with shortwave and longwave radiation, thermal emission, and radiation reflections. They contribute differently to the radiation budget of urban surfaces. Each process requires different computational resources and physical data for the urban elements. This study investigates how much detail modellers should include to parameterise radiative transfer in microscale building resolving UCMs. To that end, we introduce a stepwise parameterization method to the the PALM model system 6.0 to quantify individually the effects of the main radiative transfer processes on the radiation budget and on the flow field. We quantify numerical simulations of both simple and realistic urban configurations to identify the radiative transfer processes which have major effects on the radiation budget, such as surface and vegetation interaction with short wave and long wave radiation, and those which have minor effects, such as multiple reflections. The study also shows that radiative transfer processes within the canopy layer implicitly affect the incoming radiation since the radiative transfer model is coupled to the radiation model. The flow field changes considerably in response to the radiative transfer processes included in the model. The study highlights those processes which are essentially needed to assure acceptable quality of the flow field. Omitting any of these processes may lead to high uncertainties in the model results.

We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint model provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation, and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosol dynamics and thermodynamics, cloud chemistry and dynamics, diffusion, and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with algorithmic differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or finite-difference method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the complex variable method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM and CVM. In an example application of the full multiphase adjoint model, we provide the first estimates of how emissions of particulate matter (PM2.5) affect public health across the US.

For more than a decade, GNSS-meteorology has been increasingly used operationally in Europe particularly for data assimilation in Numerical Weather Prediction (NWP) models, mainly thanks to the EIG EUMETNET GNSS Water Vapour Program (E-GVAP, 2005-today). As such, GNSS has become a well-established, mature observing technique for data assimilation applications. Over this period however, scientists and specialists in GNSS-meteorology noted the clear potential for enhancements and novelties in the domain. The work carried out by the COST Action ES1206 Working Group 2 members addressed these potential enhancements and novelties from the meteorological point of view, in collaboration with WG1. This included the establishment of discussion channels with forecasters in order to determine which GNSS products would be best suited for their day-to-day operational requirements. Particular areas of interest include engaging more operational forecasters (e.g. use of meteorological case studies), especially for non-numerical nowcasting of severe weather, and getting more meteorological agencies to assimilate GNSS products in regions of Europe where they were not yet/well exploited. It also included the development of the techniques and tools necessary to benefit from the brand new products developed by the Action WG1 and WG2 members, namely real-time GNSS tropospheric products for rapid-cycle NWP and non-numerical nowcasting, data assimilation of horizontal tropospheric gradients and tropospheric slant delays as well as tomographic products. Finally, the work carried out by the WG2 members brought operational improvements through dialog, transfer of knowledge, and standardisation (e.g. the new standardized tropo-SINEX format or the development of assimilation operators). The major WG2 outcomes are discussed in this Chapter.

Over the last decade, near real-time analysis of GPS data has become a well-established atmospheric observing tool, primarily coordinated by the EIG EUMETNET GPS Water Vapour Programme (E-GVAP) in Europe. In the near future, four operational GNSS will be available for commercial and scientific applications with atmospheric science benefiting from new signals from up to 60 satellites observed at any one place and time, however, many challenges remain regarding their optimal combined utilization. Besides raw data streaming, recent availability of precise real-time orbit and clock corrections enable wide utilization of autonomous Precise Point Positioning (PPP), which is particularly efficient for high-rate, real-time and multi-GNSS analyses.

Recently, oil and natural gas (O&NG) production activities in the Denver-Julesburg Basin have expanded rapidly. Associated nonmethane hydrocarbon (NMHC) emissions contribute to photochemical formation of ground-level ozone and include benzene as well as other hazardous air pollutants. Using positive matrix factorization (PMF) and chemical mass balance (CMB) methods, we estimate how much O&NG activities and other sources contribute to morning NMHC mixing ratios measured from 2013 to mid-2016 at a site in Platteville, CO, in the Denver-Julesburg Basin, and at a contrasting site in downtown Denver. A novel adjoint sensitivity analysis method is then used to estimate corresponding contributions to ozone and ozone-linked mortality in the Denver region. Average 6-9 am NMHC mixing ratios in Platteville were seven times higher than those in Denver in 2013 but four times higher in 2016. CMB estimates that O&NG activities contributed to the Platteville (Denver) site an average of 96% (56%) of NMHC on a carbon basis while PMF indicated 92% (33%). Average vehicle-related contributions of NMHC are estimated as 41% by CMB and 53% by PMF in Denver. Estimates of the fractional contribution to potential ozone and ozone-linked mortality from O&NG activities are smaller while those from vehicles are larger than the NMHC contributions. CMB (PMF) indicate that greater than 78% (40%) of annual average benzene in Denver is attributable to vehicle emissions while greater than 75% (67%) of benzene in Platteville is attributable to O&NG activities. AirWaterGas Sustainability Research Network - National Science Foundation [CBET-1240584] This research was supported in part by the AirWaterGas Sustainability Research Network funded by the National Science Foundation under Grant No. CBET-1240584. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the author and do not necessarily reflect the views of the National Science Foundation. The authors have declared that no competing interests exist. The CDPHE North Front Range Ozone Precursor Monitoring data are available at https://www.colorado.gov/airquality/tech_doc_repository.aspx.The CMAQ adjoint model and inputs are available upon request from the corresponding author.

Urban areas are an important part of the climate system and many aspects of urban climate have direct effects on human health and living conditions. This implies that reliable tools for local urban climate studies supporting sustainable urban planning are needed. However, a realistic implementation of urban canopy processes still poses a serious challenge for weather and climate modelling for the current generation of numerical models. To address this demand, a new urban surface model (USM), describing the surface energy processes for urban environments, was developed and integrated as a module into the PALM large-eddy simulation model. The development of the presented first version of the USM originated from modelling the urban heat island during summer heat wave episodes and thus implements primarily processes important in such conditions. The USM contains a multi-reflection radiation model for shortwave and longwave radiation with an integrated model of absorption of radiation by resolved plant canopy (i.e. trees, shrubs). Furthermore, it consists of an energy balance solver for horizontal and vertical impervious surfaces, and thermal diffusion in ground, wall, and roof materials, and it includes a simple model for the consideration of anthropogenic heat sources. The USM was parallelized using the standard Message Passing Interface and performance testing demonstrates that the computational costs of the USM are reasonable on typical clusters for the tested configurations. The module was fully integrated into PALM and is available via its online repository under the GNU General Public License (GPL). The USM was tested on a summer heat-wave episode for a selected Prague crossroads. The general representation of the urban boundary layer and patterns of surface temperatures of various surface types (walls, pavement) are in good agreement with in situ observations made in Prague. Additional simulations were performed in order to assess the sensitivity of the results to uncertainties in the material parameters, the domain size, and the general effect of the USM itself. The first version of the USM is limited to the processes most relevant to the study of summer heat waves and serves as a basis for ongoing development which will address additional processes of the urban environment and lead to improvements to extend the utilization of the USM to other environments and conditions.

Objective: We assess the societal benefits of reducing air pollutant emissions that contribute to ambient fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) exposure and public...

We estimate monetized health benefits of phasing out the coal-fired power plants in Ontario and Alberta as well as in the US. We quantify these health impacts by accounting for reduced mortality du...

Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, which provides source-receptor relationships at highly resolved sectoral, spatial, and temporal scales. While damage resulting from anthropogenic emissions of BC is strongly correlated with population and premature death, we found little correlation between damage and emission magnitude, suggesting that controls on the largest emissions may not be the most efficient means of reducing damage resulting from anthropogenic BC emissions. Rather, the best proxy for locations with damaging BC emissions is locations where premature deaths occur. Onroad diesel and nonroad vehicle emissions are the largest contributors to premature deaths attributed to exposure to BC, while onroad gasoline emissions cause the highest deaths per amount emitted. Emissions in fall and winter contribute to more premature deaths (and more per amount emitted) than emissions in spring and summer. Overall, these results show the value of the high-resolution source attribution for determining the locations, seasons, and sectors for which BC emission controls have the most effective health benefits.

Urban areas are an important part of the climate system and many aspects of urban climate have a direct effect on human health and living conditions. This implies the need for a reliable tool for climatology studies that supports urban planning and development strategies. However, a realistic implementation of urban canopy processes still poses a serious challenge for weather and climate modelling for the current generation of numerical models. To address this demand, a new model of energy processes for urban environments was developed as an Urban Surface Model (USM) and integrated as a module into the large-eddy simulation (LES) model PALM. The USM contains a multi-reflection radiation model for short and long wave radiation, calculation of the energy balance on horizontal and vertical impervious surfaces, thermal diffusion in ground, wall and roof materials and anthropogenic heat from transportation. The module also models absorption of radiation by resolved plant canopy (i.e. trees, shrubs). The USM was parallelized using MPI and performance testing demonstrates that the computational costs of the USM are reasonable and the model scales well on typical cluster configurations. The module was fully integrated into PALM and is available via its online repository under GNU General Public License (GPL). The implementation was tested on a summer heat wave episode in the real conditions of a selected Prague crossroad. General patterns of temperature of various surface types (walls, pavement) are in good agreement with observations. The coupled LES-USM system appears to correct the bias found between observations and mesoscale model predictions for the near-surface air temperature. The results, however, show a strong dependence on the prescribed surface and wall material properties. Their exact knowledge is thus essential for the correct prediction of the flow in the urban canopy layer.

Impact of climate change is often amplified in urban areas — particularly during the heat waves, the extreme temperatures are even more pronounced in cities due to the effect urban heat island (UHI). It is therefore important to improve our understanding of heat fluxes and energy balance in urbanized areas. We investigate the possibility of high resolution urban canopy modelling using PALM model. To account for the realistic implementation of urban canopy processes in complex urban geometry we enhanced PALM model including some of the most important urban canopy mechanisms including detailed description of physical properties of urban surfaces, calculation of shape view factors and plant canopy sink factor to model accurately both shortwave and longwave radiation budgets, and heat transfer within urban surfaces and on the interfaces of surfaces and atmosphere or ground. Such approach allows for very detailed modelling in high spatial and temporal scale. The simulation of the impact of anthropogenic heat from transportation has been conducted as one of the pilot experiments to test feasibility of this approach and also sensitivity of highly unstable turbulent flow heat exchange to a relatively small perturbation of input parameters.

The paper presents a version of the 4DVar method, capable of optimizing diurnal time profiles of emissions. It is a generalization of existing inverse methods that optimize emission daily totals. The core of the method is formed by the CMAQ adjoint model with SAPRC99 mechanism. Measurements from both ground–level stations (NO2 and O3), and satellites (retrieved columns of NO2 from GOME2 and OMI and the lowest layer of O3 retrieved from IASI) have been used as a data source for the inverse modeling procedure. The method can be used for detection of bias or errors in the emission model. It also can assist in development of data–driven emission model with location–specific time profiles of emissions. Different aspects of the method are illustrated on simulation experiments. Forecasting performance of the optimized model is evaluated for O3 and NO2 concentrations.

Selected aspects of currently running project UrbanAdapt are described. The project deals with the adaptation of cities on changing climatic conditions. The main project objective is to start the process of preparation of cities adaptation strategies, developing adaptation scenarios and testing the effects and benefits of particular measures. Previously developed models of adaptation impacts are used with available real data and according to several prepared scenarios to provide necessary decision making tools. The final policies have to take into account climatic conditions, available means, and devices to propose necessary amendments and solutions. Project team involves groups from different fields that cover various aspects of adaptation measures including economic analyses, policy making processes, education and dissemination to the public. The presented paper deals with the part of activities which are focused on modelling of adaptation measures and climatic impacts for the city of Prague.

An air-quality forecasting system based on the pair ‘NWP model MM5–chemistry transport model CAMx’ is proposed. A version of the ensemble Kalman Filter has been developed. The model-error covariance matrix is parametrized with the help of a covariance function and represented by an ensemble formed as a random selection from leading eigenvectors. The performance of the system is tested on the case of an ozone episode in June 2001. As a source of observations, the AirBase database has been used. Starting the forecast from analysed concentration fields improves the quality of forecast of the next day's ozone concentration maxima. Copyright © 2005 Royal Meteorological Society

Adjoint sensitivity analysis of numerical models provides a platform for directly linking public health effects with air quality for evaluating emission control policies in a more straightforward manner. We link epidemiological and valuation statistics to the adjoint of CMAQ and calculate sensitivities of short-term mortality-related benefits in Canada, the U.S. and Europe to anthropogenic NOx and VOC emissions across two continental domains. Our results show significant spatial variability in impacts of NOx and VOC emissions reduction on short-term mortality. We estimate that sensitivities of mortality-related benefits to 10 % NOx emissions reductions in major cities reach monetary values in excess of $635K/day in Europe and $355K/day in North America. We find that when the cumulative effects of anthropogenic emissions on O3 and NO2 population exposure are considered, NOx emissions reductions generally yield higher mortality-related benefits than the same relative reductions in VOC emissions.

This paper presents a simple and robust wind power forecasting approach using inputs from a state-of-the-art numerical weather prediction models (NWP) with mesoscale resolution. The model can be used for short-term and longer term forecasting horizon up to 72 hours ahead. The forecasting ability of the presented approach is demonstrated using real power production data from the Czech Republic.