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Excess reactive nitrogen (Nr), including nitrogen oxides (NO x ) and ammonia (NH 3 ), contributes strongly to fine particulate matter (PM 2.5 ) air pollution in Europe, posing challenges to public health. Designing cost-effective Nr control roadmaps for PM 2.5 mitigation requires considering both mitigation efficiencies and implementation costs. Here we identify optimal Nr control pathways for Europe by integrating emission estimations, air quality modeling, exposure-mortality modeling, Nr control experiments and cost data. We find that phasing out Nr emissions would reduce PM 2.5 by 2.3 ± 1.2 μg·m −3 in Europe, helping many locations achieve the World Health Organization (WHO) guidelines and reducing PM 2.5 -related premature deaths by almost 100 thousand in 2015. Low-ambition NH 3 controls have similar PM 2.5 mitigation efficiencies as NO x in Eastern Europe, but are less effective in Western Europe until reductions exceed 40%. The efficiency for NH 3 controls increases at high-ambition reductions while NO x slightly decreases. When costs are considered, strategies for both regions uniformly shift in favor of NH 3 controls, as NH 3 controls up to 50% remain 5-11 times more cost-effective than NO x per unit PM 2.5 reduction, emphasizing the priority of NH 3 control policies for Europe. Reactive nitrogen (Nr) contributes strongly to PM 2.5 air pollution in Europe. Here, authors identify diverse Nr control pathways for Europe depending on emission and pollution formation and a priority of NH 3 control when costs are considered.

Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue ‘Air quality, past present and future’.

Evidence suggests deep stratospheric intrusions can elevate western US surface ozone to unhealthy levels during spring. These intrusions can be classified as ‘exceptional events’, which are not counted towards non-attainment determinations. Understanding the factors driving the year-to-year variability of these intrusions is thus relevant for effective implementation of the US ozone air quality standard. Here we use observations and model simulations to link these events to modes of climate variability. We show more frequent late spring stratospheric intrusions when the polar jet meanders towards the western United States, such as occurs following strong La Niña winters (Niño3.4<−1.0 °C). While El Niño leads to enhancements of upper tropospheric ozone, we find this influence does not reach surface air. Fewer and weaker intrusion events follow in the two springs after the 1991 volcanic eruption of Mt. Pinatubo. The linkage between La Niña and western US stratospheric intrusions can be exploited to provide a few months of lead time during which preparations could be made to deploy targeted measurements aimed at identifying these exceptional events. Deep stratospheric ozone intrusions can elevate western US ground-level ozone to unhealthy concentrations, but the factors driving interannual variability are poorly understood. Here, the authors combine observations and numerical simulations showing a link between intrusion events and strong La Niña winters.

In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning ∼840 000 km 2 and 5327 tree recruitment dates spanning ∼1.4 million km 2 across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km 2 . Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as \"heavy tailed,\" with most of the years from 1775 to 1780 comprising the heavy-tail portion of the distribution. Historical documents provide no evidence that hurricanes or ice storms triggered the 1775-1780 event. Instead, we identify a significant relationship between prior drought and years with elevated rates of disturbance with an intense drought occurring from 1772 to 1775. We further find that years with high rates of canopy disturbance have a propensity to create larger canopy gaps indicating repeated opportunities for rapid change in species composition beyond the landscape scale. Evidence of elevated, regional-scale disturbance reveals how rare events can potentially alter system trajectory: a substantial portion of old-growth forests examined here originated or were substantially altered more than two centuries ago following events lasting just a few years. Our recruitment data, comprised of at least 21 species and several shade-intolerant species, document a pulse of tree recruitment at the subcontinental scale during the late-1600s suggesting that this event was severe enough to open large canopy gaps. These disturbances and their climatic drivers support the hypothesis that punctuated, episodic, climatic events impart a legacy in broadleaf-dominated forests centuries after their occurrence. Given projections of future drought, these results also reveal the potential for abrupt, meso- to large-scale forest change in broadleaf-dominated forests over future decades.

Aflatoxin contamination in maize (Zea mays), primarily caused by Aspergillus flavus, is strongly influenced by meteorological conditions and remains a major food safety concern. Predictive models have been developed to support contamination risk assessment and management strategies, typically relying on meteorological data from local weather stations. While these inputs offer high accuracy, their limited spatial coverage and lack of forecasting capability reduce their application as early warning systems and in-season decision support. This study evaluates the integration of ERA5-Land reanalysis and seasonal climate forecasts into AFLA-maize, a mechanistic model for predicting aflatoxin B1 contamination, to extend its spatial and temporal applicability. Using historical data from the Emilia-Romagna, Italy (2008–2025), we tested bias-adjusted ERA5-Land inputs and developed a hybrid forecasting approach combining reanalysis data for the early-season with adjusted forecasts for the later crop stages. Results show that simulations driven by ERA5-Land reproduced contamination probability in 91% of years compared to station-based results, supporting its use in regions with low quality observations or missing station networks. Hybrid integrations of bias-adjusted forecasts provided contamination risk assessments 3–8 weeks ahead of harvest, showing the trade-off between lead time and accuracy. Forecast initialized later in the season (August) achieved much higher accuracy (up to 91%) but offer less time for action, whereas earlier initializations (June, July) bear larger uncertainty (accuracy of 88%–93%) but extended the decision windows. Furthermore, the availability of ensemble forecasts allows to quantify the uncertainty, providing probability ranges across members that support risk communication and early warning outputs. In summary, the presented approach extends AFLA-maize into a scalable and transferable tool for anticipatory risk management, supporting climate-resilient agriculture and food safety through publicly available meteorological data.

Rising emissions of anthropogenic greenhouse gases (GHG) have led to tropospheric warming and stratospheric cooling over recent decades. As a thermodynamic consequence, the troposphere has expanded and the rise of the tropopause, the boundary between the troposphere and stratosphere, has been suggested as one of the most robust fingerprints of anthropogenic climate change. Conversely, at altitudes above ∼55 km (in the mesosphere and thermosphere) observational and modeling evidence indicates a downward shift of the height of pressure levels or decreasing density at fixed altitudes. The layer in between, the stratosphere, has not been studied extensively with respect to changes of its global structure. Here we show that this atmospheric layer has contracted substantially over the last decades, and that the main driver for this are increasing concentrations of GHG. Using data from coupled chemistry-climate models we show that this trend will continue and the mean climatological thickness of the stratosphere will decrease by 1.3 km following representative concentration pathway 6.0 by 2080. We also demonstrate that the stratospheric contraction is not only a response to cooling, as changes in both tropopause and stratopause pressure contribute. Moreover, its short emergence time (less than 15 years) makes it a novel and independent indicator of GHG induced climate change.

Radiative and dynamical heating rates control stratospheric temperatures. In this study, radiative temperature trends due to ozone depletion and increasing well-mixed greenhouse gases from 1980 to 2000 in the polar stratosphere are directly evaluated, and the dynamical contributions to temperature trends are estimated as the residual between the observed and radiative trends. The radiative trends are obtained from a seasonally evolving fixed dynamical heating calculation with the Parallel Offline Radiative Transfer model using four different ozone datasets, which provide estimates of observed ozone changes. In the spring and summer seasons, ozone depletion leads to radiative cooling in the lower stratosphere in the Arctic and Antarctic. In Arctic summer there is weak wave driving, and the radiative cooling due to ozone depletion is the dominant driver of observed trends. In late winter and early spring, dynamics dominate the changes in Arctic temperatures. In austral spring and summer in the Antarctic, strong dynamical warming throughout the mid- to lower stratosphere acts to weaken the strong radiative cooling associated with the Antarctic ozone hole and is indicative of a strengthening of the Brewer–Dobson circulation. This dynamical warming is a significant term in the thermal budget overmuch of the Antarctic summer stratosphere, including in regions where strong radiative cooling due to ozone depletion can still lead to net cooling despite dynamical terms. Quantifying the contributions of changes in radiation and dynamics to stratospheric temperature trends is important for understanding how anthropogenic forcings have affected the historical trends and necessary for projecting the future.

Rising greenhouse gases (GHG) and decreasing anthropogenic ozone-depleting substances (ODS) are the main drivers of the stratospheric climate evolution in the 21st century. However, the coupling between stratospheric composition, radiation and dynamics is subject to many uncertainties, which is partly because of the simplistic representation of ozone (O3) in many current climate models. Changes in ozone due to heterogeneous chemistry are known to be the largest during springtime in the Arctic, which is also a season with very active stratosphere–troposphere coupling. The focus of this study is to investigate the role of varying ozone levels driven by changing GHG and ODS for the Arctic polar cap stratosphere. We use two state-of-the-art chemistry-climate models with ocean coupling in two configurations (prescribed ozone fields vs. interactive ozone chemistry) for three different scenarios: preindustrial conditions—1 × CO2, year 2000 conditions (peak anthropogenic ODS levels) and extreme future conditions—4 × CO2. Our results show that in the upper and middle stratosphere CO2 thermal cooling is the dominant effect determining the temperature response under 4 × CO2, and outweighs warming effects of ozone by about a factor of ten. In contrast, in the lower stratosphere, the effects of O3 warming and CO2 cooling under 4 × CO2 are largely offsetting each other. ODS driven variations in O3 affect both the temperature mean and variability, and are responsible for the tight springtime coupling between composition and dynamics under year 2000 conditions in comparison to simulations under 1 × CO2 or 4 × CO2.

Considering the representation of the atmosphere, the current generation of Earth-System Models (ESMs) differs mainly in the representation of the stratospheric ozone layer and its variability and changes. So-called high-top models have a well resolved stratosphere and typically calculate ozone chemistry interactively, low-top models on the other hand rely on parameterized ozone chemistry or prescribed climatological ozone fields and have a model top below the stratopause. Here we investigate whether interactive ozone chemistry is important for representing temperature variability and extremes in the Arctic polar stratosphere. To this end we analyze a suite of two 200 year sensitivity simulations, one with interactive ozone chemistry and one without, performed with the Whole Atmosphere Community Climate Model version 4 (WACCM4), a stratosphere-resolving version of the National Center for Atmospheric Research Community Earth-System Model. We find a tight coupling between ozone and temperatures over the Arctic polar cap, manifesting in increased variability in stratospheric spring-time temperatures in simulations with interactive chemistry compared to simulations imposing climatological mean ozone abundances. Our results indicate that stratospheric temperature extremes regularly occurring in simulations with interactive chemistry are absent in uncoupled model simulations.

A simple statistical model to predict the number of aerosols which activate to form cloud droplets in warm clouds has been established, based on regression analysis of data from four summertime Cloud and Aerosol Characterisation Experiments (CLACE) at the high-altitude site Jungfraujoch (JFJ). It is shown that 79 % of the observed variance in droplet numbers can be represented by a model accounting only for the number of potential cloud condensation nuclei (defined as number of particles larger than 80 nm in diameter), while the mean errors in the model representation may be reduced by the addition of further explanatory variables, such as the mixing ratios of O3, CO, and the height of the measurements above cloud base. The statistical model has a similar ability to represent the observed droplet numbers in each of the individual years, as well as for the two predominant local wind directions at the JFJ (northwest and southeast). Given the central European location of the JFJ, with air masses in summer being representative of the free troposphere with regular boundary layer in-mixing via convection, we expect that this statistical model is generally applicable to warm clouds under conditions where droplet formation is aerosol limited (i.e. at relatively high updraught velocities and/or relatively low aerosol number concentrations). A comparison between the statistical model and an established microphysical parametrization shows good agreement between the two and supports the conclusion that cloud droplet formation at the JFJ is predominantly controlled by the number concentration of aerosol particles.