Luca Pozzoli

Simultaneously Mitigating Near-Term Climate Change and Improving Human Health and Food Security

Why Wait? Tropospheric ozone can be dangerous to human health, can be harmful to vegetation, and is a major contributor to climate warming. Black carbon also has significant negative effects on health and air quality and causes warming of the atmosphere. Shindell et al. (p. 183) present results of an analysis of emissions, atmospheric processes, and impacts for each of these pollutants. Seven measures were identified that, if rapidly implemented, would significantly reduce global warming over the next 50 years, with the potential to prevent millions of deaths worldwide from outdoor air pollution. Furthermore, some crop yields could be improved by decreasing agricultural damage. Most of the measures thus appear to have economic benefits well above the cost of their implementation. Reducing anthropogenic emissions of methane and black carbon would have multiple climate and health benefits. Tropospheric ozone and black carbon (BC) contribute to both degraded air quality and global warming. We considered ~400 emission control measures to reduce these pollutants by using current technology and experience. We identified 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050. This strategy avoids 0.7 to 4.7 million annual premature deaths from outdoor air pollution and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond. Benefits of methane emissions reductions are valued at

Global Air Quality and Health Co-benefits of Mitigating Near-Term Climate Change through Methane and Black Carbon Emission Controls

700 to

Sources, sinks, and transatlantic transport of North African dust aerosol: A multimodel analysis and comparison with remote sensing data

5000 per metric ton, which is well above typical marginal abatement costs (less than

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems : Multivariable temporal and spatial breakdown

250). The selected controls target different sources and influence climate on shorter time scales than those of carbon dioxide–reduction measures. Implementing both substantially reduces the risks of crossing the 2°C threshold.

Spatial and temporal analysis of black carbon aerosols in Istanbul megacity.

Background: Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM2.5), are associated with premature mortality and they disrupt global and regional climate. Objectives: We examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20–40 years. Methods: We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5- and ozone-related deaths using epidemiologically derived concentration–response functions. Results: We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23–34% and 7–17% and avoid 0.6–4.4 and 0.04–0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration–response function. Conclusions: In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

Quantifying the impacts of an updated global dimethyl sulfide climatology on cloud microphysics and aerosol radiative forcing

This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes.

The contribution of Saharan dust in PM10 concentration levels in Anatolian Peninsula of Turkey

Through the comparison of several regional-scale chemistry transport modeling systems that simulate meteorology and air quality over the European and North American continents, this study aims at (i) apportioning error to the responsible processes using timescale analysis, (ii) helping to detect causes of model error, and (iii) identifying the processes and temporal scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overallsense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance, and covariance) can help assess the nature and quality of the error. Each of the error components is analyzed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intraday) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emission and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high interdependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. This will require evaluaion methods that are able to frame the impact on error of processes, conditions, and fluxes at the surface. For example, error due to emission and boundary conditions is dominant for primary species (CO, particulate matter (PM)), while errors due to meteorology and chemistry are most relevant to secondary species, such as ozone. Some further aspects emerged whose interpretation requires additional consideration, such as the uniformity of the synoptic error being region- and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3

Black carbon (BC) is an important component of particulate matter due to its effects on human health and climate. In this study, we present the first BC concentrations measured in the Istanbul megacity (~15 million inhabitants). Two measurement campaigns have been conducted to measure BC and fine particulate matter (PM2.5) concentrations at four locations, characterized by different traffic densities. In the first campaign, BC daily mean concentrations have been found to be between 4 μg/m(3) and 10 μg/m(3). In the second campaign, BC and PM2.5 have been measured at the site with the highest traffic density for an entire year. Annually averaged BC contributes by 38 ± 14% to the PM2.5 levels (annual average BC: 13 μg/m(3) and PM2.5: 36 μg/m(3)). Diurnal variations of BC concentrations followed those of traffic density (correlation coefficient of 0.87). These measurements are essential to identify the sources of BC and PM2.5 concentrations in Istanbul and develop mitigation measures.

Simulated air quality and pollutant budgets over Europe in 2008

One of the critical parameters in assessing the global impacts of dimethyl sulfide (DMS) on cloud properties and the radiation budget is the estimation of phytoplankton-induced ocean emissions, which are derived from prescribed, climatological surface seawater DMS concentrations. The most widely used global ocean DMS climatology was published 15 years ago and has recently been updated using a much larger database of observations. The updated climatology displays significant differences in terms of the global distribution and regional monthly averages of sea surface DMS. In this study, we use the ECHAM5-HAMMOZ aerosol-chemistry-climate general circulation model to quantify the influence of the updated DMS climatology in computed atmospheric properties, namely, the spatial and temporal distributions of atmospheric DMS concentration, sulfuric acid concentration, sulfate aerosols, number of activated aerosols, cloud droplet number concentration, and the aerosol radiative forcing at the top of the atmosphere. Significant differences are observed for all the modeled variables. Comparison with observations of atmospheric DMS and total sulfate also shows that in places with large DMS emissions, the updated climatology shows a better match with the observations. This highlights the importance of using the updated climatology for projecting future impacts of oceanic DMS emissions, especially considering that the relative importance of the natural sulfur fluxes is likely to increase due to legislation to “clean up” anthropogenic emissions. The largest estimated differences are in the Southern Ocean, Indian Ocean, and parts of the Pacific Ocean, where the climatologies differ in seasonal concentrations over large geographical areas. The model results also indicate that the former DMS climatology underestimated the effect of DMS on the globally averaged annual aerosol radiative forcing at the top of the atmosphere by about 20%.

Modeled deposition of nitrogen and sulfur in Europe estimated by 14 air quality model systems: evaluation, effects of changes in emissions and implications for habitat protection

Sahara-originated dust is the most significant natural source of particulate matter; however, this contribution is still unclear in the Eastern Mediterranean especially in Western Turkey, where significant industrial sources and metropolitan areas are located. The Real-time Air Quality Modeling System (RAQMS) is utilized to explore the possible effects of Saharan dust on high levels of PM10 measured in Turkey. RAQMS model is compared with 118-air quality stations distributed throughout Turkey (81 cities) for April 2008. MODIS aerosol product (MOD04 for Terra and MYD04 for Aqua) is used to see columnar aerosol loading of the atmosphere at 550 nm (Aerosol optical depth (AOD) values found to be between 0.6 and 0.8 during the episode). High-resolution vertical profiles of clouds and aerosols are provided from CALIOP, on board of CALISPO satellite. The results suggest a significant contribution of Sahara dust to high levels of PM10 in Turkey with RAQMS and in situ time series showing similar patterns. The two data sets are found to be in agreement with a correlation of 0.87.