New particle formation at a peri-urban agricultural site.

New Particle Formation (NPF) is a major source of ultrafine particles that affect both air quality and climate. Despite emissions from agricultural activities having a strong potential to lead to NPF, little is known about NPF within agricultural environments. The aim of the present study was to investigate the occurrence of NPF events at an agricultural site, and any potential relationship between agricultural emissions and NPF events. A field campaign was conducted for 3 months at the FR-Gri-ICOS site (France), at an experimental farm 25 km west of Paris city centre. 16 NPF events have been identified from the analysis of particle number size distributions; 8 during the daytime, and 8 during the night-time. High solar radiation and ozone mixing ratios were observed during the days NPF occurred, suggesting photochemistry plays a key role in daytime NPF. These events were also associated with higher levels of VOCs such as isoprene, methanol, or toluene compared to non-event days. However, ammonia levels were lower during daytime NPF events, contributing to the hypothesis that daytime NPF events were not related to agricultural activities. On the other hand, temperature and ozone were lower during the nights when NPF events were observed, whereas relative humidity was higher. During these nights, higher concentrations of NO2 and ammonia were observed. As a result, agricultural activities, in particular the spreading of fertiliser on surrounding crops, are suspected to contribute to night-time NPF events. Finally, all the identified NPF events were also observed at SIRTA monitoring station 20 km from the FR-Gri ICOS site, showing that both night-time and daytime NPF events were regional processes. We hypothesise that night-time NPF may be related to fertiliser spreading over a regional scale, as opposed to the local activities at the farm. To our knowledge, this is the first time night-time NPF has been observed in the agricultural context.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Characterization of particulate and gaseous pollutants from a French dairy and sheep farm.

Agricultural activities highly contribute to atmospheric pollution, but the diversity and the magnitude of their emissions are still subject to large uncertainties. A field measurement campaign was conducted to characterize gaseous and particulate emissions from an experimental farm in France containing a sheep pen and a dairy stable. During the campaign, more than four hundred volatile organic compounds (VOCs) were characterized using an original combination of online and off-line measurements. Carbon dioxide (CO2) and ammonia (NH3) were the most concentrated compounds inside the buildings, followed by methanol, acetic acid and acetaldehyde. A CO2 mass balance model was used to estimate NH3 and VOC emission rates. To our knowledge, this study constitutes the first evaluation of emission rates for most of the identified VOCs. The measurements show that the dairy stable emitted more VOCs than the sheep pen. Despite strong VOC and NH3 emissions, the chemical composition of particles indicates that gaseous farm emissions do not affect the loading of fine particles inside the farm and is mainly explained by the low residence time inside the buildings. The experimental dataset obtained in this work will help to improve emissions inventories for agricultural activities.