Atmosphere2015, 6(8), 1119-1128; doi:10.3390/atmos6081119 (registering DOI) - published 31 July 2015 Show/Hide Abstract
Abstract: The contribution of different anthropogenic source-sectors on ozone mixing ratios and PM2.5 concentrations over Europe is assessed for a summer month (July 2006) using the US Environmental Protection Agency’s (EPA’s) Models-3 framework and the Netherlands Organization for Applied Scientific Research (TNO) anthropogenic emissions for 2006. Anthropogenic emission sources have been classified into 10 different Standard Nomenclature for Air Pollution (SNAP) categories. The road transport category, which is mainly responsible for NOX emissions, is estimated to have the major impact on Max8hrO3 mixing ratio suggesting an increase of 6.8% on average over Europe, while locally it is more than 20%. Power generation category is estimated to have the major impact on PM2.5 concentrations since it is the major source of SO2 emissions, suggesting an increase of 22.9% on average over Europe, while locally it is more than 60%. Agriculture category is also contributing significantly on PM2.5 concentrations, since agricultural activities are the major source of NH3 emissions, suggesting an increased by 16.1% on average over Europe, while in regions with elevated NH3 emissions the increase is up to 40%.
Atmosphere2015, 6(8), 1102-1118; doi:10.3390/atmos6081102 (registering DOI) - published 31 July 2015 Show/Hide Abstract
Abstract: The rapid growth and expansion of urbanized landscapes in cities has resulted in an increase in air temperature and has lowered the bioclimatic comfort levels in urban landscapes. Recent studies to estimate the climatic response of urban landscape conversion have mostly examined the relationship between land use/land cover (LULC) change and land surface temperature (LST) data collected using advanced remote sensing (RS) techniques instead of atmospheric temperature. In this respect, four decadal Landsat images from the 1980s were used to investigate the impact of landscape transformation on atmospheric temperature. The mean and average minimum and maximum monthly air temperature datasets were used in the analysis. The CORINE (Coordination of Information on Environment) index was used to determine LULC diversity in an urban development boundary and urban periphery. Consequently, clustered LULC change values for the last three decades were integrated with decadal air temperature anomalies. The findings revealed an important relationship between monthly mean air temperature and land changes over recent decades, which resulted in an increase in urban fabric land use, deforestation land cover changes and conversion of permanent crop fields to artificial green houses for earlier vegetable production; the R-sqr values for these regressions were 97.7%, 88.5% and 90.6% respectively. On the other hand, the most important increasing temperature trends were obtained for the average monthly minimum air temperature, which supports the global warming concerns of the IPCC (Intergovernmental Panel on Climate Change) and related studies, which have concluded that an increased nighttime temperature results in urban heat islands (UHIs). The results should be used to support better urban landscape plans and architectural designs to improve human thermal comfort for sustainable urban life in Mediterranean cities. Street geometry and orientation to wind breeze, the Height/Width H/W ratio of buildings, and sizes of open and green spaces should be examined carefully in urban planning and design for climate adaptation.
Atmosphere2015, 6(8), 1069-1101; doi:10.3390/atmos6081069 (registering DOI) - published 31 July 2015 Show/Hide Abstract
Abstract: We present a framework for calculating the total scattering of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our framework is developed emphasizing the explicit use of chemical composition data for estimating the complex refractive index (RI) of particles, and thus obtaining improved ambient size spectra derived from Optical Particle Counter (OPC) measurements. The feasibility of our framework for improved calculations of total scattering is demonstrated using three types of data collected by the U.S. Department of Energy’s (DOE) aircraft during the Two-Column Aerosol Project (TCAP). Namely, these data types are: (1) size distributions measured by a suite of OPC’s; (2) chemical composition data measured by an Aerosol Mass Spectrometer and a Single Particle Soot Photometer; and (3) the dry total scattering coefficient measured by a integrating nephelometer and scattering enhancement factor measured with a humidification system. We demonstrate that good agreement (~10%) between the observed and calculated scattering can be obtained under ambient conditions (RH < 80%) by applying chemical composition data for the RI-based correction of the OPC-derived size spectra. We also demonstrate that ignoring the RI-based correction or using non-representative RI values can cause a substantial underestimation (~40%) or overestimation (~35%) of the calculated scattering, respectively.
Atmosphere2015, 6(8), 1045-1068; doi:10.3390/atmos6081045 (registering DOI) - published 30 July 2015 Show/Hide Abstract
Abstract: This work assessed the impact of aerosol-cloud-radiation (ACR) interactions on U.S. regional ozone and PM2.5 using the NASA Unified Weather Research and Forecasting modeling system. A series of three-month simulations have been carried out for the year 2010, in which the factor separation method has been applied in order to isolate the contributions from aerosol-radiation (AR), aerosol-cloud (AC), and their synergistic effects. The overall ACR effects were to reduce the average cloud liquid water path by 25 g·m−2 (ca. 40% of the baseline) and to increase the downward shortwave radiation by 8 W·m−2 (ca. 3% of the baseline). The spatial difference in response to ACR was large, with ca. 50 W·m−2, 1 K, and 100 m increases in downward shortwave radiation, surface temperature, and planetary boundary layer height (PBLH), respectively, while ca. 60 g·m−2 decrease in cloud liquid water path in central Texas. The AC effect dominated for changes in downward shortwave radiation, cloud liquid water path, wind, and temperature, while both AC and AR effects contributed profoundly to PBLH change. As a result, surface ozone and PM2.5 changed with large temporal-spatial variations. More than a 10 ppbv of surface ozone and a 5 μg·m−3 of PM2.5 difference induced by ACR occurred frequently in the eastern U.S.
Atmosphere2015, 6(8), 1032-1044; doi:10.3390/atmos6081032 - published 24 July 2015 Show/Hide Abstract
Abstract: Sensible heat flux (H) plays an important role in characterizations of land surface water and heat balance. There are various types of H measurement methods that depend on observation scale, from local-area-scale eddy covariance (EC) to regional-scale large aperture scintillometer (LAS) and remote sensing (RS) products. However, methods of converting one H scale to another to validate RS products are still open for question. A previous area-to-area regression kriging-based scaling method performed well in converting EC-scale H to LAS-scale H. However, the method does not consider the path-weighting function in the EC- to LAS-scale kriging with the regression residue, which inevitably brought about a bias estimation. In this study, a weighted area-to-area regression kriging (WATA RK) model is proposed to convert EC-scale H to LAS-scale H. It involves path-weighting functions of EC and LAS source areas in both regression and area kriging stages. Results show that WATA RK outperforms traditional methods in most cases, improving estimation accuracy. The method is considered to provide an efficient validation of RS H flux products.
Atmosphere2015, 6(8), 1006-1031; doi:10.3390/atmos6081006 - published 24 July 2015 Show/Hide Abstract
Abstract: The residents of Mexico City face serious problems of air pollution. Identifying the most representative scenarios for the transport and dispersion of air pollutants requires the knowledge of the main wind circulation patterns. In this paper, a simple method to recognize and characterize the wind circulation patterns in a given region is proposed and applied to the Mexico City winds (2001–2006). This method uses a lattice wind approach to model the local wind events at the meso-β scale, and hierarchical cluster analysis to recognize their agglomerations in their phase space. Data of the meteorological network of Mexico City was used as input for the lattice wind model. The Ward’s clustering algorithm with Euclidean distance was applied to organize the model wind events in seasonal clusters for each year of the period. Comparison of the hourly population trends of these clusters permitted the recognition and detailed description of seven circulation patterns. These patterns resemble the qualitative descriptions of the Mexico City wind circulation modes reported by other authors. Our method, however, permitted also their quantitative characterization in terms of the wind attributes of velocity, divergence and vorticity, and an estimation of their seasonal and annual occurrence probabilities, which never before were quantified.