the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Natural sea-salt emissions moderate the climate forcing of anthropogenic nitrate
Nan Ma
Chao Wei
Liang Ran
Ralf Wolke
Johannes Größ
Qiaoqiao Wang
Andrea Pozzer
Hugo A. C. Denier van der Gon
Gerald Spindler
Jos Lelieveld
Ina Tegen
Alfred Wiedensohler
Related authors
Accurate national methane (CH4) emission estimates are essential for tracking progress towards climate goals. This study compares estimates from Finland, which use different methods and scales, and shows how well a global model estimates emissions within a country. The bottom-up estimates vary a lot but constraining them with atmospheric CH4 measurements brought the estimates closer together. We also highlight the importance of quantifying natural emissions alongside anthropogenic emissions.
real-world laboratoryconditions was conducted. We found that measured black carbon (eBC) and particulate matter (PM) in rural shallow terrain depressions with residential wood burning could be much greater than predicted by models. The exceeding levels are a cause for concern since similar conditions can be expected in numerous hilly and mountainous regions across Europe, where approximately 20 % of the total population lives.
direct effect of dust agingas an increase in the AOD as a result of hygroscopic growth. We define the
indirect effectas a reduction in the dust AOD due to the higher removal of the aged dust particles.
Related subject area
A state-of-the-art thermodynamic model has been coupled with the city-scale chemistry transport model EPISODE–CityChem to investigate the equilibrium between the inorganic gas and aerosol phases over the greater Athens area, Greece. The simulations indicate that the formation of nitrates in an urban environment is significantly affected by local nitrogen oxide emissions, as well as ambient temperature, relative humidity, photochemical activity, and the presence of non-volatile cations.
hiddensource of inter-model variability and may be leading to bias in some climate model results.