Solar‐induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite‐observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory‐2 (OCO‐2) provides the first opportunity to examine the SIF–GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO‐2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO‐2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R² = 0.72,p < 0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R² = 0.57–0.79,p < 0.0001) except evergreen broadleaf forests (R² = 0.16,p < 0.05) at the daily timescale. A higher slope was found for C₄grasslands and croplands than for C₃ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome‐specific SIF–GPP relationship, and this finding is an important distinction and simplification compared to previous results. SIF was mainly driven by absorbed photosynthetically active radiation and was also influenced by environmental stresses (temperature and water stresses) that determine photosynthetic light use efficiency. OCO‐2 SIF generally had a better performance for predicting GPP than satellite‐derived vegetation indices and a light use efficiency model. The universal SIF–GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer resolution SIF observations from OCO‐2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies.

In recent years evidence has emerged that the amount of isoprene emitted from a leaf is affected by the CO₂ growth environment. Many – though not all – laboratory experiments indicate that emissions increase significantly at below-ambient CO₂ concentrations and decrease when concentrations are raised to above-ambient. A small number of process-based leaf isoprene emission models can reproduce this CO₂ stimulation and inhibition. These models are briefly reviewed, and their performance in standard conditions compared with each other and to an empirical algorithm. One of the models was judged particularly useful for incorporation into a dynamic vegetation model framework, LPJ-GUESS, yielding a tool that allows the interactive effects of climate and increasing CO₂ concentration on vegetation distribution, productivity, and leaf and ecosystem isoprene emissions to be explored. The coupled vegetation dynamics-isoprene model is described and used here in a mode particularly suited for the ecosystem scale, but it can be employed at the global level as well. Annual and/or daily isoprene emissions simulated by the model were evaluated against flux measurements (or model estimates that had previously been evaluated with flux data) from a wide range of environments, and agreement between modelled and simulated values was generally good. By using a dynamic vegetation model, effects of canopy composition, disturbance history, or trends in CO₂ concentration can be assessed. We show here for five model test sites that the suggested CO₂-inhibition of leaf-isoprene metabolism can be large enough to offset increases in emissions due to CO₂-stimulation of vegetation productivity and leaf area growth. When effects of climate change are considered atop the effects of atmospheric composition the interactions between the relevant processes will become even more complex. The CO₂-isoprene inhibition may have the potential to significantly dampen the expected steep increase of ecosystem isoprene emission in a future, warmer atmosphere with higher CO₂ levels; this effect raises important questions for projections of future atmospheric chemistry, and its connection to the terrestrial vegetation and carbon cycle.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM_2.5, PM₁₀, PMC (coarse fraction of PM), NO₂, SO₂, NOx, CO, O₃ and the total gaseous oxidant (OX = NO₂ + O₃) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO₂ and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO₂ and between 30% and 40% in mean PM_2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM_2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO₂/CO ratio). Some Chinese cities showed similar increases in PM_2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O₃ concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO₂ anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO₂/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO₂ decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO₂ + O₃) showed that primary NO₂ emissions at urban locations were greater than the O₃ production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO₂ and O₃ concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM_2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

In models of plant volatile isoprenoid emissions, the instantaneous compound emission rate typically scales with the plant's emission potential under specified environmental conditions, also called as the emission factor, E_S. In the most widely employed plant isoprenoid emission models, the algorithms developed by Guenther and colleagues (1991, 1993), instantaneous variation of the steady-state emission rate is described as the product of E_S and light and temperature response functions. When these models are employed in the atmospheric chemistry modeling community, species-specific E_S values and parameter values defining the instantaneous response curves are often taken as initially defined. In the current review, we argue that E_S as a characteristic used in the models importantly depends on our understanding of which environmental factors affect isoprenoid emissions, and consequently need standardization during experimental E_S determinations. In particular, there is now increasing consensus that in addition to variations in light and temperature, alterations in atmospheric and/or within-leaf CO₂ concentrations may need to be included in the emission models. Furthermore, we demonstrate that for less volatile isoprenoids, mono- and sesquiterpenes, the emissions are often jointly controlled by the compound synthesis and volatility. Because of these combined biochemical and physico-chemical drivers, specification of E_S as a constant value is incapable of describing instantaneous emissions within the sole assumptions of fluctuating light and temperature as used in the standard algorithms. The definition of E_S also varies depending on the degree of aggregation of E_S values in different parameterization schemes (leaf- vs. canopy- or region-scale, species vs. plant functional type levels) and various aggregated E_S schemes are not compatible for different integration models. The summarized information collectively emphasizes the need to update model algorithms by including missing environmental and physico-chemical controls, and always to define E_S within the proper context of model structure and spatial and temporal resolution.

The effect of aerosol loading on solar radiation and the subsequent effect on photosynthesis is a relevant question for estimating climate feedback mechanisms. This effect is quantified in the present study using ground-based measurements from five remote sites in boreal and hemiboreal (coniferous and mixed) forests of Eurasia. The diffuse fraction of global radiation associated with the direct effect of aerosols, i.e. excluding the effect of clouds, increases with an increase in the aerosol loading. The increase in the diffuse fraction of global radiation from approximately 0.11 on days characterized by low aerosol loading to 0.2–0.27 on days with relatively high aerosol loading leads to an increase in gross primary production (GPP) between 6 % and 14 % at all sites. The largest increase in GPP (relative to days with low aerosol loading) is observed for two types of ecosystems: a coniferous forest at high latitudes and a mixed forest at the middle latitudes. For the former ecosystem the change in GPP due to the relatively large increase in the diffuse radiation is compensated for by the moderate increase in the light use efficiency. For the latter ecosystem, the increase in the diffuse radiation is smaller for the same aerosol loading, but the smaller change in GPP due to this relationship between radiation and aerosol loading is compensated for by the higher increase in the light use efficiency. The dependence of GPP on the diffuse fraction of solar radiation has a weakly pronounced maximum related to clouds.