Monitoring and modeling of household air quality related to use of different Cookfuels in Paraguay.

In Paraguay, 49% of the population depends on biomass (wood and charcoal) for cooking. Residential biomass burning is a major source of fine particulate matter (PM2.5 ) and carbon monoxide (CO) in and around the household environment. In July 2016, cross-sectional household air pollution sampling was conducted in 80 households in rural Paraguay. Time-integrated samples (24 hours) of PM2.5 and continuous CO concentrations were measured in kitchens that used wood, charcoal, liquefied petroleum gas (LPG), or electricity to cook. Qualitative and quantitative household-level variables were captured using questionnaires. The average PM2.5 concentration (μg/m3 ) was higher in kitchens that burned wood (741.7 ± 546.4) and charcoal (107.0 ± 68.6) than in kitchens where LPG (52.3 ± 18.9) or electricity (52.0 ± 14.8) was used. Likewise, the average CO concentration (ppm) was higher in kitchens that used wood (19.4 ± 12.6) and charcoal (7.6 ± 6.5) than in those that used LPG (0.5 ± 0.6) or electricity (0.4 ± 0.6). Multivariable linear regression was conducted to generate predictive models for indoor PM2.5 and CO concentrations (predicted R2  = 0.837 and 0.822, respectively). This study provides baseline indoor air quality data for Paraguay and presents a multivariate statistical approach that could be used in future research and intervention programs

Quantifying the Direct Radiative Effect of Absorbing Aerosols for Numerical Weather Prediction: A Case Study

We conceptualize aerosol radiative transfer processes arising from the hypothetical coupling of a global aerosol transport model and a global numerical weather prediction model by applying the US Naval Research Laboratory Navy Aerosol Analysis and Prediction System (NAAPS) and the Navy Global Environmental Model (NAVGEM) meteorological and surface reflectance fields. A unique experimental design during the 2013 NASA Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field mission allowed for collocated airborne sampling by the high spectral resolution Lidar (HSRL), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), up/down shortwave (SW) and infrared (IR) broadband radiometers, as well as NASA A-Train support from the Moderate Resolution Imaging Spectroradiometer (MODIS), to attempt direct aerosol forcing closure. The results demonstrate the sensitivity of modeled fields to aerosol radiative fluxes and heating rates, specifically in the SW, as induced in this event from transported smoke and regional urban aerosols. Limitations are identified with respect to aerosol attribution, vertical distribution, and the choice of optical and surface polarimetric properties, which are discussed within the context of their influence on numerical weather prediction output that is particularly important as the community propels forward towards inline aerosol modeling within global forecast systems

Pot-in-pot reactions: a simple and green approach to efficient organic synthesis

Incompatible organic reactions impede efficient green synthesis by making multi-component or cascade reactions a big challenge. This review highlights pot-in-pot reactions (multiple reactions carried out in one pot by separating key reactions with a thin polymeric membrane) as an efficient, green synthetic alternative to conventional synthesis. We discuss the advantages of homogeneous processes to develop new cascade reaction sequences by reviewing the use of polymeric thimbles as selective semi-permeable walls. These thimbles allow small organic molecules to diffuse through while retaining polar reagents, polar solvents, and/or organometallic catalysts. The dynamic and versatile nature of this technique is demonstrated by performing 2- and 3-step cascade reactions in one glass pot. A pot-in-pot reaction approach to synthesis circumvents the need to isolate intermediates, or handling of toxic/unpleasant by-products, therefore enabling synthesis of otherwise challenging molecules, improving the efficiency, or enabling greener approaches to modular synthesis

Sowing density effect on common bean leaf area development

Sowing density is a major management factor that affects growth and development of grain crops by modifying the canopy light environment and interplant competition for water and nutrients. While the effects of sowing density and plant architecture on static vegetative and reproductive growth traits have been explored previously in the common bean, few studies have focused on the impacts of sowing density on the dynamics of node addition and leaf area development. We present the results from two sites of field experiments where the effects of sowing densities (5, 10, 15, 20, 25 and 35 plants m-2) and genotypes with contrasting plant architectures (two each from growth habits I through III) on the dynamics of node addition and leaf area were assessed. Analysis of the phyllochron (°C node-1) indicated genotype and density effects (but no interaction) on the rate of node addition. While significant, these differences amounted to less than two days of growth at either site. In terms of leaf area development, analysis using a power function reflected large differences in the dynamics and final size of individual plant leaf area between the lower density (20 plants m-2) at the growth habit, but not genotype level. These differences in node addition and leaf development dynamics translated to marked differences between growth habits and sowing densities in estimated leaf area indices, and consequently, in the estimated fraction of intercepted light at lower densities

Compound climate-pollution extremes in Santiago de Chile

Cities in the global south face dire climate impacts. It is in socioeconomically marginalized urban communities of the global south that the effects of climate change are felt most deeply. Santiago de Chile, a major mid-latitude Andean city of 7.7 million inhabitants, is already undergoing the so-called “climate penalty” as rising temperatures worsen the effects of endemic ground-level ozone pollution. As many cities in the global south, Santiago is highly segregated along socioeconomic lines, which offers an opportunity for studying the effects of concurrent heatwaves and ozone episodes on distinct zones of affluence and deprivation. Here, we combine existing datasets of social indicators and climate-sensitive health risks with weather and air quality observations to study the response to compound heat-ozone extremes of different socioeconomic strata. Attributable to spatial variations in the ground-level ozone burden (heavier for wealthy communities), we found that the mortality response to extreme heat (and the associated further ozone pollution) is stronger in affluent dwellers, regardless of comorbidities and lack of access to health care affecting disadvantaged population. These unexpected findings underline the need of a site-specific hazard assessment and a community-based risk management.</p

Characterization of submicron aerosol chemical composition and sources in the coastal area of Central Chile

Chemical characteristics and the sources of submicron particles (<1 mu m in diameter) were investigated in Valle Alegre, the coastal area of Central Chile. The chemical composition of particles was studied by using a Soot particle Aerosol Mass Spectrometer and Multi-Angle Absorption Photometer. Submicron particles were dominated by organics (42% of mass) and sulfate (39% of mass) while the mass fractions of ammonium, nitrate and black carbon were much smaller (13, 2 and 4% of mass, respectively). Additionally, several metals (V, Zn, Fe, Cd, Cu, K, Na and Mg) were detected in submicron particles and also some of their inorganic salts (e.g. NaCl+, MgCl2+, CaCl2+, KCl+ and KNO3+). The sources of particles were examined by using Positive Matrix Factorization (PMF). Organic aerosol (OA) was divided into five factors by using PMF; hydrocarbon-like OA (HOA), biomass burning OA (BBOA), low-volatility oxygenated OA (LV-OOA), semi-volatile OA (SV-OOA) and marine oxygenated OOA (MOOA), Oxygenated factors (LV-OOA; SV-OOA and MOOA) comprised 75% of total OA with LV-OOA being the dominant factor (38% of OA). Sulfate had two major sources in Valle Alegre; similar to 70% of sulfate was related to anthropogenic sources through the oxidation of gas phase SO2 whereas similar to 24% of sulfate was associated with biogenic origin related to the oxidation of dimethyl sulfide in the marine environment. Regarding total submicron particle mass (campaign-average 9.5 mu g m(-3)), the contribution of anthropogenic sources was at least as large as that of biogenic origin.Peer reviewe

Progress towards a quiescent, high confinement regime for the all-metal ASDEX Upgrade tokamak

EUROfusion Consortium 633053European Union’s Horizon 2020 80516

Conceptualizing the impact of dust-contaminated infrared radiances on data assimilation for numerical weather prediction

Numerical weather prediction systems depend on Hyperspectral Infrared Sounder (HIS) data, yet the impacts of dust-contaminated HIS radiances on weather forecasts has not been quantified. To determine the impact of dust aerosol on HIS radiance assimilation, we use a modified radiance assimilation system employing a one-dimensional variational assimilation system (1DVAR) developed under the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Numerical Weather Prediction–Satellite Application Facility (NWP-SAF) project, which uses the Radiative Transfer for TOVS (RTTOV). Dust aerosol impacts on analyzed temperature and moisture fields are quantified using synthetic HIS observations from rawinsonde, Micropulse Lidar Network (MPLNET), and Aerosol Robotic Network (AERONET). Specifically, a unit dust aerosol optical depth (AOD) contamination at 550 nm can introduce larger than 2.4 and 8.6 K peak biases in analyzed temperature and dewpoint, respectively, over our test domain. We hypothesize that aerosol observations, or even possibly forecasts from aerosol predication models, may be used operationally to mitigate dust induced temperature and moisture analysis biases through forward radiative transfer modeling.This study is supported by the NASA ROSES Science of Terra and Aqua program (T. Lee; 80HQTR18T0085). The MPLNET project is funded by the NASA Radiation Sciences Program and Earth Observing System. MPLNET observations at the Santa Cruz de Tenerife site are supported by the INTA Grant IGE03004