Carbonyl sulfide (COS) emissions in two agroecosystems in central France.

Carbonyl sulfide (COS) fluxes simulated by vegetation and soil component models, both implemented in the ORCHIDEE land surface model, were evaluated against field observations at two agroecosystems in central France. The dynamics of a biogenic process not yet accounted for by this model, i.e.

Computational Social Science and Sociology.

The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: () social network analysis and group formation; () collective behavior and political sociology; () the sociology of knowledge; () cultural sociology, social psychology, and emotions; () the production of culture; () economic sociology and organizations; and () demography and population studies.

A top-down approach of sources and non-photosynthetic sinks of carbonyl sulfide from atmospheric measurements over multiple years in the Paris region (France).

Carbonyl sulfide (COS) has been proposed as a proxy for carbon dioxide (CO2) taken up by plants at the leaf and ecosystem scales. However, several additional production and removal processes have been identified which could complicate its use at larger scales, among which are soil uptake, dark uptake by plants, and soil and anthropogenic emissions. This study evaluates the significance of these processes at the regional scale through a top-down approach based on atmospheric COS measurements at Gif-sur-Yvette (GIF), a suburban site near Paris (France).

Land Use Regression Models for Ultrafine Particles and Black Carbon Based on Short-Term Monitoring Predict Past Spatial Variation.

Health effects of long-term exposure to ultrafine particles (UFP) have not been investigated in epidemiological studies because of the lack of spatially resolved UFP exposure data. Short-term monitoring campaigns used to develop land use regression (LUR) models for UFP typically had moderate performance. The aim of this study was to develop and evaluate spatial and spatiotemporal LUR models for UFP and Black Carbon (BC), including their ability to predict past spatial contrasts.

Agreement of central site measurements and land use regression modeled oxidative potential of PM2.5 with personal exposure.

Oxidative potential (OP) of ambient particulate matter (PM) has been suggested as a health-relevant exposure metric. In order to use OP for exposure assessment, information is needed about how well central site OP measurements and modeled average OP at the home address reflect temporal and spatial variation of personal OP. We collected 96-hour personal, home outdoor and indoor PM2.