Jaroslav Resler

Differences Between Magnitudes and Health Impacts of BC Emissions Across the United States Using 12 km Scale Seasonal Source Apportionment

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.

Premature deaths attributed to source-specific BC emissions in six urban US regions

Recent studies have shown that exposure to particulate black carbon (BC) has significant adverse health effects and may be more detrimental to human health than exposure to PM2.5 as a whole. Mobile source BC emission controls, mostly on diesel-burning vehicles, have successfully decreased mobile source BC emissions to less than half of what they were 30 years ago. Quantification of the benefits of previous emissions controls conveys the value of these regulatory actions and provides a method by which future control alternatives could be evaluated. In this study we use the adjoint of the Community Multiscale Air Quality (CMAQ) model to estimate highly-resolved spatial distributions of benefits related to emission reductions for six urban regions within the continental US. Emissions from outside each of the six chosen regions account for between 7% and 27% of the premature deaths attributed to exposure to BC within the region. While we estimate that nonroad mobile and onroad diesel emissions account for the largest number of premature deaths attributable to exposure to BC, onroad gasoline is shown to have more than double the benefit per unit emission relative to that of nonroad mobile and onroad diesel. Within the region encompassing New York City and Philadelphia, reductions in emissions from large industrial combustion sources that are not classified as EGUs (i.e., non-EGU) are estimated to have up to triple the benefits per unit emission relative to reductions to onroad diesel sectors, and provide similar benefits per unit emission to that of onroad gasoline emissions in the region. While onroad mobile emissions have been decreasing in the past 30 years and a majority of vehicle emission controls that regulate PM focus on diesel emissions, our analysis shows the most efficient target for stricter controls is actually onroad gasoline emissions.

Inverse modeling of emissions and their time profiles

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.

High resolution modelling of anthropogenic heat from traffic in urban canopy: A sensitivity study

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.

On the development of urban adaptation strategies using ecosystem-based approaches to adaptation

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. These activities include assessment of energy balance of city, in terms of interactions of solar radiation, atmosphere and urban environment. Urban environment includes not only buildings, street surfaces and vegetation, but also the processes having impact on energy balance such as the traffic, air conditioning and industry that produce anthropogenic heat which can play a role for example in summer heat waves. The ultimate goal is to assess the impact of different adaptation measures on citizens who live in environmental conditions of growing effect of urban heat island. Thus the connection between objective meteorological variables and subjective biological indices has to be investigated. The concept of Physiological Equivalent Temperature (PET) is adopted. In comparison to single values of air temperature, air humidity, global horizontal irradiance, wind speed, and other meteorological indexes, concept of PET has added value in determining the value of important biometeorological index in.

Statistical Modeling for Improvement of Numerical-Model-Based Solar Radiation Forecasts

We first analyze some features of numerical weather predictions (NWP) for global solar radiation and notice that they are undersmooth. This finding opens a way to improvements via various smoothing strategies. Then we introduce a statistical modeling framework based on modern semiparametric regression. We use a numerical weather prediction (NWP) model output as one of the inputs for our statistical model. The statistical model is build on the modern regression formalism, utilizing nonparametric B-splines for nonlinear parts whose exact shape is unknown a priori (apart from physically motivated smoothness). Then we illustrate its abilities for systematic development of strategies for NWP calibration and further development. The results are useful both for practical forecasting and as a source of feedback for NWP modelers.

Attribution of Ozone Pollution Control Benefits to Individual Sources

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

Estimating climatological variability of solar energy production

635K/day in Europe and

PALM-USM v1.0: A new urban surface model integrated into the PALM large-eddy simulation model

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.