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Anthropogenic ammonia (NH₃) emissions have significantly increased in recent decades due to enhanced agricultural activities, contributing to global air pollution. While the effects of NH₃on surface air quality are well documented, its influence on particle dynamics in the upper troposphere-lower stratosphere (UTLS) and related aerosol impacts remain unquantified. NH₃reaches the UTLS through convective transport and can enhance new particle formation (NPF). This modeling study evaluates the global impact of anthropogenic NH₃on UTLS particle formation and quantifies its effects on aerosol loading and cloud condensation nuclei (CCN) abundance. We use the EMAC Earth system model, incorporating multicomponent NPF parameterizations from the CERN CLOUD experiment. Our simulations reveal that convective transport increases NH₃-driven NPF in the UTLS by one to three orders of magnitude compared to a baseline scenario without anthropogenic NH₃, causing a doubling of aerosol numbers over high-emission regions. These aerosol changes induce a 2.5-fold increase in upper tropospheric CCN concentrations. Anthropogenic NH₃emissions increase the relative contribution of water-soluble inorganic ions to the UTLS aerosol optical depth (AOD) by 20% and increase total column AOD by up to 80%. In simulations without anthropogenic NH₃, UTLS aerosol composition is dominated by sulfate and organic species, with a marked reduction in ammonium nitrate and aerosol water content. This results in a decline of aerosol mass concentration by up to 50%. These findings underscore the profound global influence of anthropogenic NH₃emissions on UTLS particle formation, AOD, and CCN production, with important implications for cloud formation and climate. 

Abstract Isoprene (C₅H₈) is the non-methane hydrocarbon with the highest emissions to the atmosphere. It is mainly produced by vegetation, especially broad-leaved trees, and efficiently transported to the upper troposphere in deep convective clouds, where it is mixed with lightning NO_x. Isoprene oxidation products drive rapid formation and growth of new particles in the tropical upper troposphere. However, isoprene oxidation pathways at low temperatures are not well understood. Here, in experiments at the CERN CLOUD chamber at 223 K and 243 K, we find that isoprene oxygenated organic molecules (IP-OOM) all involve two successive$${{{\rm{OH}}}}^{\bullet}$$ ${\mathrm{OH}}^{\bullet }$oxidations. However, depending on the ambient concentrations of the termination radicals ($${{{{\rm{HO}}}}_{2}}^{\bullet},\,{{{\rm{NO}}}}^{\bullet}$$ ${{\mathrm{HO}}_2}^{\bullet },{\mathrm{NO}}^{\bullet }$, and$${{{\rm{NO}}}}_{2}^{\bullet}$$ ${\mathrm{NO}}_2^{\bullet }$), vastly-different IP-OOM emerge, comprising compounds with zero, one or two nitrogen atoms. Our findings indicate high IP-OOM production rates for the tropical upper troposphere, mainly resulting in nitrate IP-OOM but with an increasing non-nitrate fraction around midday, in close agreement with aircraft observations. 

Geo-obfuscation is a location privacy protection mechanism used by mobile users to conceal their precise locations when reporting location data, and it has been widely used to protect the location privacy of workers in spatial crowdsourcing (SC). However, this technique introduces inaccuracies in the reported locations, raising the question of how to control the quality loss that results from obfuscation in SC services. Prior studies have addressed this issue in time-insensitive SC settings, where some degree of quality degradation can be accepted and the locations can be expressed with less precision, which, however, is inadequate for time-sensitive SC. In this paper, we aim to minimize the quality loss caused by geo-obfuscation in time-sensitive SC applications. To this end, we model workers’ mobility on a fine-grained location field and constrain each worker’s obfuscation range to a set of peer locations, which have similar traveling costs to the destination as the actual location. We apply a linear programming (LP) framework to minimize the quality loss while satisfying both peer location constraints and geo-indistinguishability, a location privacy criterion extended from differential privacy. By leveraging the constraint features of the formulated LP, we enhance the time efficiency of solving LP through the geo-indistinguishability constraint reduction and the column generation algorithm. Using both simulation and real-world experiments, we demonstrate that our approach can reduce the quality loss of SC applications while protecting workers’ location privacy. 

Abstract The identification of Chiral molecules is essential in pharmaceutical and food science. However, conventional methods are complex and cost‐prohibitive. This study introduces a sustainable method using hydroxypropyl cellulose (HPC) gel to identify amino acids enantiomers, such as phenylalanine and alanine, through visible light. By integrating the structural color properties of HPC, this research demonstrates the HPC gel's capability to distinguish L (Levo)‐phenylalanine (L‐Phe), D (Dextro)‐phenylalanine (D‐Phe), and DL (racemic mixture)‐phenylalanine (DL‐Phe) supplemented with visible circular dichroism (CD) spectra or hydrochloric acid (HCl) as visual indicators. Similar chiral sensing results are observed with D‐alanine, L‐alanine, and DL‐alanine. Unlike traditional UV‐based detection requiring expensive equipment, this approach simplifies the process while maintaining sensitivity. Varying phenylalanine concentrations altered the CD response without disrupting the gel's helical structure, and color changes in response to HCl addition facilitated visual identification of enantiomers. Furthermore, adding various salts generates colorful HPC/Phe gels, demonstrating their suitability for 3D printing. Meanwhile, the HPC gels remained functional for three months, indicating long‐term stability. These advancements are significant for pharmaceutical and biotechnological industries, facilitating efficient low‐concentration chirality detection (0.2 wt.%). Continued development and refinement of this technology are expected to expand its applications and improve analytical capabilities for future chirality‐related studies and photonic gel 3D printing. 

Abstract During summer, ammonia emissions in Southeast Asia influence air pollution and cloud formation. Convective transport by the South Asian monsoon carries these pollutant air masses into the upper troposphere and lower stratosphere (UTLS), where they accumulate under anticyclonic flow conditions. This air mass accumulation is thought to contribute to particle formation and the development of the Asian Tropopause Aerosol Layer (ATAL). Despite the known influence of ammonia and particulate ammonium on air pollution, a comprehensive understanding of the ATAL is lacking. In this modelling study, the influence of ammonia on particle formation is assessed with emphasis on the ATAL. We use the EMAC chemistry-climate model, incorporating new particle formation parameterisations derived from experiments at the CERN CLOUD chamber. Our diurnal cycle analysis confirms that new particle formation mainly occurs during daylight, with a 10-fold enhancement in rate. This increase is prominent in the South Asian monsoon UTLS, where deep convection introduces high ammonia levels from the boundary layer, compared to a baseline scenario without ammonia. Our model simulations reveal that this ammonia-driven particle formation and growth contributes to an increase of up to 80% in cloud condensation nuclei (CCN) concentrations at cloud-forming heights in the South Asian monsoon region. We find that ammonia profoundly influences the aerosol mass and composition in the ATAL through particle growth, as indicated by an order of magnitude increase in nitrate levels linked to ammonia emissions. However, the effect of ammonia-driven new particle formation on aerosol mass in the ATAL is relatively small. Ammonia emissions enhance the regional aerosol optical depth (AOD) for shortwave solar radiation by up to 70%. We conclude that ammonia has a pronounced effect on the ATAL development, composition, the regional AOD, and CCN concentrations. 

Abstract Exposure to anthropogenic atmospheric aerosol is a major health issue, causing several million deaths per year worldwide. The oxidation of aromatic hydrocarbons from traffic and wood combustion is an important anthropogenic source of low-volatility species in secondary organic aerosol, especially in heavily polluted environments. It is not yet established whether the formation of anthropogenic secondary organic aerosol involves mainly rapid autoxidation, slower sequential oxidation steps or a combination of the two. Here we reproduced a typical urban haze in the ‘Cosmics Leaving Outdoor Droplets’ chamber at the European Organization for Nuclear Research and observed the dynamics of aromatic oxidation products during secondary organic aerosol growth on a molecular level to determine mechanisms underlying their production and removal. We demonstrate that sequential oxidation is required for substantial secondary organic aerosol formation. Second-generation oxidation decreases the products’ saturation vapour pressure by several orders of magnitude and increases the aromatic secondary organic aerosol yields from a few percent to a few tens of percent at typical atmospheric concentrations. Through regional modelling, we show that more than 70% of the exposure to anthropogenic organic aerosol in Europe arises from second-generation oxidation. 

Isoprene affects new particle formation rates in environments and experiments also containing monoterpenes. 

We present a “diagonal” Volatility Basis Set (dVBS) comparing gas-phase concentrations of oxygenated organic molecules (OOM) to their condensed-phase mass fractions.