Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical ...model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multi-year database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, sea-salt, sulfate, black and organic carbon). We use 9 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS (2 products), TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDER and MSG/SEVIRI, as well as 3 more historical datasets: NIMBUS7/CZCS, TOMS (onboard NIMBUS7 and Earth-Probe) and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, the multi-model mean coming from the ACCMIP exercise, and the reanalyses GEMS and MACC. Ground-based Level-2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatio-temporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain datasets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data, but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences of vertical distribution between dust aerosols showing a large vertical spread, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003-2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology. We extend the 2003-2009 reconstruction to the past up to 1979 using the 2003-2009 average and applying the decreasing trend in sulfate aerosols from LMDz-OR-INCA, whose AOD trends over Europe and the Mediterranean are median among the ACCMIP models. Finally optical properties of the different aerosol types in this region are proposed from Mie calculations so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosol-climate studies.
Climate change can influence fine particulate matter concentrations (PM2.5) through changes in air pollution meteorology. Knowledge of the extent to which climate change can exacerbate or alleviate ...air pollution in the future is needed for robust climate and air pollution policy decision-making. To examine the influence of climate on PM2.5, we use the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 (GFDL CM3), a fully-coupled chemistry-climate model, combined with future emissions and concentrations provided by the four Representative Concentration Pathways (RCPs). For each of the RCPs, we conduct future simulations in which emissions of aerosols and their precursors are held at 2005 levels while other climate forcing agents evolve in time, such that only climate (and thus meteorology) can influence PM2.5 surface concentrations. We find a small increase in global, annual mean PM2.5 of about 0.21 μg m−3 (5%) for RCP8.5, a scenario with maximum warming. Changes in global mean PM2.5 are at a maximum in the fall and are mainly controlled by sulfate followed by organic aerosol with minimal influence of black carbon. RCP2.6 is the only scenario that projects a decrease in global PM2.5 with future climate changes, albeit only by −0.06 μg m−3 (1.5%) by the end of the 21st century. Regional and local changes in PM2.5 are larger, reaching upwards of 2 μg m−3 for polluted (eastern China) and dusty (western Africa) locations on an annually averaged basis in RCP8.5. Using multiple linear regression, we find that future PM2.5 concentrations are most sensitive to local temperature, followed by surface wind and precipitation. PM2.5 concentrations are robustly positively associated with temperature, while negatively related with precipitation and wind speed. Present-day (2006–2015) modeled sensitivities of PM2.5 to meteorological variables are evaluated against observations and found to agree reasonably well with observed sensitivities (within 10–50% over the eastern United States for several variables), although the modeled PM2.5 is less sensitive to precipitation than in the observations due to weaker convective scavenging. We conclude that the hypothesized “climate penalty” of future increases in PM2.5 is relatively minor on a global scale compared to the influence of emissions on PM2.5 concentrations.
•Climate-driven global PM2.5 concentrations increase modestly due to climate change.•Temperature, wind speed, and precipitation exert the largest controls on PM2.5.•Modeled and observed T-PM2.5 and Wind-PM2.5 sensitivities are in excellent agreement.
The ozone (O3) dry depositional sink and its contribution to observed variability in tropospheric O3 are both poorly understood. Distinguishing O3 uptake through plant stomata versus other pathways ...is relevant for quantifying the O3 influence on carbon and water cycles. We use a decade of O3, carbon, and energy eddy covariance (EC) fluxes at Harvard Forest to investigate interannual variability (IAV) in O3 deposition velocities (
vd,O3). In each month, monthly mean
vd,O3 for the highest year is twice that for the lowest. Two independent stomatal conductance estimates, based on either water vapor EC or gross primary productivity, vary little from year to year relative to canopy conductance. We conclude that nonstomatal deposition controls the substantial observed IAV in summertime
vd,O3 during the 1990s over this deciduous forest. The absence of obvious relationships between meteorology and
vd,O3 implies a need for additional long‐term, high‐quality measurements and further investigation of nonstomatal mechanisms.
Key Points
Observed factor of 2 in interannual variability (IAV) of ozone dry deposition velocities, dominated by nonstomatal processes
Stomatal conductance estimates from two observation‐driven independent models show similar but weak IAV
High‐quality, long‐term measurements needed to identify processes driving IAV in ozone dry deposition
Changing emissions can alter the surface O3 seasonal cycle, as detected from northeastern U.S. (NE) observations during recent decades. Under continued regional precursor emission controls (>80% ...decreases in NE NOx by 2100), the NE surface O3 seasonal cycle reverses (to a winter maximum) in 21st century transient chemistry‐climate simulations. Over polluted regions, regional NOx largely controls the shape of surface O3 seasonal cycles. In the absence of regional NOx controls, climate warming contributes to a higher surface O3 summertime peak over the NE. A doubling of the global CH4 abundance by 2100 partially offsets summertime surface O3 decreases attained via NOx reductions and contributes to raising surface O3 during December–March when the O3 lifetime is longer. The similarity between surface O3 seasonal cycles over the NE and the Intermountain West by 2100 indicates a NE transition to a region representative of baseline surface O3 conditions.
Key Points
Changing regional NOx emissions alter peak surface ozone seasonClimate change increases peak summertime surface ozone over NE U.S.Rising global methane enhances surface ozone most strongly during winter
This article is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a ...rate of convergence in probability of n
−r/(2r+1)
when the additive components are r-times continuously differentiable for some r ≥ 2. This result holds regardless of the dimension of the covariates, and thus the new estimator has no curse of dimensionality. In addition, the estimator has an oracle property and is easily extended to a generalized additive quantile regression model with a link function. The numerical performance and usefulness of the estimator are illustrated by Monte Carlo experiments and an empirical example.
In recent years, glycated hemoglobin (HbA1c) has been increasingly accepted as a functional metric of mean blood glucose in the treatment of diabetic patients. Importantly, HbA1c provides an ...alternate measure of total glycemic exposure due to the representation of blood glucose throughout the day, including post-prandially. In this article, we propose and demonstrate the potential of Raman spectroscopy as a novel analytical method for quantitative detection of HbA1c, without using external dyes or reagents. Using the drop coating deposition Raman (DCDR) technique, we observe that the nonenzymatic glycosylation (glycation) of the hemoglobin molecule results in subtle but discernible and highly reproducible changes in the acquired spectra, which enable the accurate determination of glycated and nonglycated hemoglobin using standard chemometric methods. The acquired Raman spectra display excellent reproducibility of spectral characteristics at different locations in the drop and show a linear dependence of the spectral intensity on the analyte concentration. Furthermore, in hemolysate models, the developed multivariate calibration models for HbA1c show a high degree of prediction accuracy and precisionwith a limit of detection that is a factor of ∼15 smaller than the lowest physiological concentrations encountered in clinical practice. The excellent accuracy and reproducibility achieved in this proof-of-concept study opens substantive avenues for characterization and quantification of the glycosylation status of (therapeutic) proteins, which are widely used for biopharmaceutical development. We also envision that the proposed approach can provide a powerful tool for high-throughput HbA1c sensing in multicomponent mixtures and potentially in hemolysate and whole blood lysate samples.
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