Explore the vast range of titles available.

The climate impact of deforestation depends on the relative strength of several biogeochemical and biogeophysical effects. In addition to affecting the exchange of carbon dioxide (CO 2 ) and moisture with the atmosphere and surface albedo, vegetation emits biogenic volatile organic compounds (BVOCs) that alter the formation of short-lived climate forcers (SLCFs), which include aerosol, ozone and methane. Here we show that a scenario of complete global deforestation results in a net positive radiative forcing (RF; 0.12 W m −2 ) from SLCFs, with the negative RF from decreases in ozone and methane concentrations partially offsetting the positive aerosol RF. Combining RFs due to CO 2 , surface albedo and SLCFs suggests that global deforestation could cause 0.8 K warming after 100 years, with SLCFs contributing 8% of the effect. However, deforestation as projected by the RCP8.5 scenario leads to zero net RF from SLCF, primarily due to nonlinearities in the aerosol indirect effect. The climate impacts of deforestation due to changes in biogenic volatile organic compound emissions, which act as short-lived climate forcers (SLCFs), are poorly understood. Here the authors show that including the impact SLCFs increases the projected warming associated with idealised deforestation scenarios.

The terrestrial biosphere is an important source of natural aerosol. Natural aerosol sources alter climate, but are also strongly controlled by climate, leading to the potential for natural aerosol–climate feedbacks. Here we use a global aerosol model to make an assessment of terrestrial natural aerosol–climate feedbacks, constrained by observations of aerosol number. We find that warmer-than-average temperatures are associated with higher-than-average number concentrations of large (>100 nm diameter) particles, particularly during the summer. This relationship is well reproduced by the model and is driven by both meteorological variability and variability in natural aerosol from biogenic and landscape fire sources. We find that the calculated extratropical annual mean aerosol radiative effect (both direct and indirect) is negatively related to the observed global temperature anomaly, and is driven by a positive relationship between temperature and the emission of natural aerosol. The extratropical aerosol–climate feedback is estimated to be −0.14 W m−2 K−1 for landscape fire aerosol, greater than the −0.03 W m−2 K−1 estimated for biogenic secondary organic aerosol. These feedbacks are comparable in magnitude to other biogeochemical feedbacks, highlighting the need for natural aerosol feedbacks to be included in climate simulations.

The Mediterranean troposphere exhibits a marked and localised summertime ozone maximum, which has the potential to strongly impact regional air quality and radiative forcing. The Mediterranean region can be perturbed by long-range pollution import from Northern Europe, North America and Asia, in addition to local emissions, which may all contribute to regional ozone enhancements. We exploit ozone profile observations from the Tropospheric Emission Spectrometer (TES) and the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instruments, and an offline 3-D global chemical transport model (TOMCAT) to investigate the geographical and vertical structure of the summertime tropospheric ozone maximum over the Mediterranean region. We show that both TES and GOME-2 are able to detect enhanced levels of ozone in the lower troposphere over the region during the summer. These observations, together with surface measurements, are used to evaluate the TOMCAT model's ability to capture the observed ozone enhancement. The model is used to quantify sensitivities of the ozone maximum to anthropogenic and natural volatile organic compound (VOC) emissions, anthropogenic NOx emissions, wildfire emissions and long-range import of ozone and precursors. Our results show a dominant sensitivity to natural VOC emissions in the Mediterranean basin over anthropogenic VOC emissions. However, local anthropogenic NOx emissions are result in the overall largest sensitivity in near-surface ozone. We also show that in the lower troposphere, global VOC emissions account for 40% of the ozone sensitivity to VOC emissions in the region, whereas, for NOx the ozone sensitivity to local sources is 9 times greater than that for global emissions at these altitudes. However, in the mid and upper troposphere ozone is most sensitive to non-local emission sources. In terms of radiative effects on regional climate, ozone contributions from non-local emission sources are more important, as these have a larger impact on ozone in the upper troposphere where its radiative effects are larger, with Asian monsoon outflow having the greatest impact. Our results allow improved understanding of the large-scale processes controlling air quality and climate in the region of the Mediterranean basin.

We have evaluated tropospheric ozone enhancement in air dominated by biomass burning emissions at high latitudes (> 50° N) in July 2008, using 10 global chemical transport model simulations from the POLMIP multi-model comparison exercise. In model air masses dominated by fire emissions, ΔO3/ΔCO values ranged between 0.039 and 0.196 ppbv ppbv−1 (mean: 0.113 ppbv ppbv−1) in freshly fire-influenced air, and between 0.140 and 0.261 ppbv ppbv−1 (mean: 0.193 ppbv) in more aged fire-influenced air. These values are in broad agreement with the range of observational estimates from the literature. Model ΔPAN/ΔCO enhancement ratios show distinct groupings according to the meteorological data used to drive the models. ECMWF-forced models produce larger ΔPAN/ΔCO values (4.47 to 7.00 pptv ppbv−1) than GEOS5-forced models (1.87 to 3.28 pptv ppbv−1), which we show is likely linked to differences in efficiency of vertical transport during poleward export from mid-latitude source regions. Simulations of a large plume of biomass burning and anthropogenic emissions exported from towards the Arctic using a Lagrangian chemical transport model show that 4-day net ozone change in the plume is sensitive to differences in plume chemical composition and plume vertical position among the POLMIP models. In particular, Arctic ozone evolution in the plume is highly sensitive to initial concentrations of PAN, as well as oxygenated VOCs (acetone, acetaldehyde), due to their role in producing the peroxyacetyl radical PAN precursor. Vertical displacement is also important due to its effects on the stability of PAN, and subsequent effect on NOx abundance. In plumes where net ozone production is limited, we find that the lifetime of ozone in the plume is sensitive to hydrogen peroxide loading, due to the production of HOx from peroxide photolysis, and the key role of HO2 + O3 in controlling ozone loss. Overall, our results suggest that emissions from biomass burning lead to large-scale photochemical enhancement in high-latitude tropospheric ozone during summer.

A global chemical transport model is used in conjunction with measurements from surface stations to study the importance of biomass burning and meteorology in driving Arctic carbon monoxide (CO) interannual variability (IAV). Simulations with yearly varying fire emissions capture 66%–93% of CO IAV and a simulation with yearly varying meteorology but fixed fire emissions captures 0–25%, showing that biomass burning variability is the dominant driver of surface CO IAV. Observed CO anomalies are found to be significantly correlated with El Niño (0.58 < r < 0.64, 99% confidence level (CL)) and results indicate that this is due to ENSO's influence on fire emissions. Boreal Alaska, Canada and north‐east Siberia are found to contribute 59% to total Arctic fire CO and 67% to Arctic fire CO IAV. Analysis of meteorological fire drivers in these regions suggests that ENSO affects winter/spring precipitation, driving the Arctic/ENSO relationship. Key Points Fire emissions are the dominant driver of Arctic CO interannual variability ENSO influences Arctic CO interannual variability through its effect on fires The Arctic is most sensitive to fire emissions from the boreal regions

During the POLARCAT summer campaign in 2008, two episodes (2–5 July and 7–10 July 2008) occurred where low-pressure systems traveled from Siberia across the Arctic Ocean towards the North Pole. The two cyclones had extensive smoke plumes from Siberian forest fires and anthropogenic sources in East Asia embedded in their associated air masses, creating an excellent opportunity to use satellite and aircraft observations to validate the performance of atmospheric transport models in the Arctic, which is a challenging model domain due to numerical and other complications. Here we compare transport simulations of carbon monoxide (CO) from the Lagrangian transport model FLEXPART and the Eulerian chemical transport model TOMCAT with retrievals of total column CO from the IASI passive infrared sensor onboard the MetOp-A satellite. The main aspect of the comparison is how realistic horizontal and vertical structures are represented in the model simulations. Analysis of CALIPSO lidar curtains and in situ aircraft measurements provide further independent reference points to assess how reliable the model simulations are and what the main limitations are. The horizontal structure of mid-latitude pollution plumes agrees well between the IASI total column CO and the model simulations. However, finer-scale structures are too quickly diffused in the Eulerian model. Applying the IASI averaging kernels to the model data is essential for a meaningful comparison. Using aircraft data as a reference suggests that the satellite data are biased high, while TOMCAT is biased low. FLEXPART fits the aircraft data rather well, but due to added background concentrations the simulation is not independent from observations. The multi-data, multi-model approach allows separating the influences of meteorological fields, model realisation, and grid type on the plume structure. In addition to the very good agreement between simulated and observed total column CO fields, the results also highlight the difficulty to identify a data set that most realistically represents the actual pollution state of the Arctic atmosphere.

Using observations from aircraft, surface stations and a satellite instrument, we comprehensively evaluate multi-model simulations of carbon monoxide (CO) and ozone (O3) in the Arctic and over lower latitude emission regions, as part of the POLARCAT Model Inter-comparison Project (POLMIP). Evaluation of 11- atmospheric models with chemistry shows that they generally underestimate CO throughout the Arctic troposphere, with the largest biases found during winter and spring. Negative CO biases are also found throughout the Northern Hemisphere, with multi-model mean gross errors (9–12%) suggesting models perform similarly over Asia, North America and Europe. A multi-model annual mean tropospheric OH (10.8 ± 0.6 × 105 molec cm−3) is found to be slightly higher than previous estimates of OH constrained by methyl chloroform, suggesting negative CO biases in models may be improved through better constraints on OH. Models that have lower Arctic OH do not always show a substantial improvement in their negative CO biases, suggesting that Arctic OH is not the dominant factor controlling the Arctic CO burden in these models. In addition to these general biases, models do not capture the magnitude of CO enhancements observed in the Arctic free troposphere in summer, suggesting model errors in the simulation of plumes that are transported from anthropogenic and biomass burning sources at lower latitudes. O3 in the Arctic is also generally underestimated, particularly at the surface and in the upper troposphere. Summer O3 comparisons over lower latitudes show several models overestimate upper tropospheric concentrations. Simulated CO, O3 and OH all demonstrate a substantial degree of inter-model variability. Idealised CO-like tracers are used to quantitatively compare the impact of inter-model differences in transport and OH on CO in the Arctic troposphere. The tracers show that model differences in transport from Europe in winter and from Asia throughout the year are important sources of model variability at Barrow. Unlike transport, inter-model variability in OH similarly affects all regional tracers at Barrow. Comparisons of fixed-lifetime and OH-loss idealised CO-like tracers throughout the Arctic troposphere show that OH differences are a much larger source of inter-model variability than transport differences. Model OH concentrations are correlated with H2O concentrations, suggesting water vapour concentrations are linked to differences in simulated concentrations of CO and OH at high latitudes in these simulations. Despite inter-model differences in transport and OH, the relative contributions from the different source regions (North America, Europe and Asia) and different source types (anthropogenic and biomass burning) are comparable across the models. Fire emissions from the boreal regions in 2008 contribute 33, 43 and 19% to the total Arctic CO-like tracer in spring, summer and autumn, respectively, highlighting the importance of boreal fire emissions in controlling pollutant burdens in the Arctic.

Treating messenger RNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been pursued in gene-specific ways. Transcript abundances often serve as a surrogate for classical quantitative traits in that the levels of expression are significantly correlated with the classical traits across members of a segregating population. The correlation structure between transcript abundances and classical traits has been used to identify susceptibility loci for complex diseases such as diabetes 1 and allergic asthma 2 . One study recently completed the first comprehensive dissection of transcriptional regulation in budding yeast 3 , giving a detailed glimpse of a genome-wide survey of the genetics of gene expression. Unlike classical quantitative traits, which often represent gross clinical measurements that may be far removed from the biological processes giving rise to them, the genetic linkages associated with transcript abundance affords a closer look at cellular biochemical processes. Here we describe comprehensive genetic screens of mouse, plant and human transcriptomes by considering gene expression values as quantitative traits. We identify a gene expression pattern strongly associated with obesity in a murine cross, and observe two distinct obesity subtypes. Furthermore, we find that these obesity subtypes are under the control of different loci.

We use a global inverse model, satellite data and flask measurements to estimate methane (CH4) emissions from South America, Brazil and the basin of the Amazon River for the period 2010–2018. We find that emissions from Brazil have risen during this period, most quickly in the eastern Amazon basin, and that this is concurrent with increasing surface temperatures in this region. Brazilian CH4 emissions rose from 49.8 ± 5.4 Tg yr−1 in 2010–2013 to 55.6 ± 5.2 Tg yr−1 in 2014–2017, with the wet season of December–March having the largest positive trend in emissions. Amazon basin emissions grew from 41.7 ± 5.3 to 49.3 ± 5.1 Tg yr−1 during the same period. We derive no significant trend in regional emissions from fossil fuels during this period. We find that our posterior distribution of emissions within South America is significantly and consistently changed from our prior estimates, with the strongest emission sources being in the far north of the continent and to the south and south-east of the Amazon basin, at the mouth of the Amazon River and nearby marsh, swamp and mangrove regions. We derive particularly large emissions during the wet season of 2013/14, when flooding was prevalent over larger regions than normal within the Amazon basin. We compare our posterior CH4 mole fractions, derived from posterior fluxes, to independent observations of CH4 mole fraction taken at five lower- to mid-tropospheric vertical profiling sites over the Amazon and find that our posterior fluxes outperform prior fluxes at all locations. In particular the large emissions from the eastern Amazon basin are shown to be in good agreement with independent observations made at Santarém, a location which has long displayed higher mole fractions of atmospheric CH4 in contrast with other basin locations. We show that a bottom-up wetland flux model can match neither the variation in annual fluxes nor the positive trend in emissions produced by the inversion. Our results show that the Amazon alone was responsible for 24 ± 18 % of the total global increase in CH4 flux during the study period, and it may contribute further in future due to its sensitivity to temperature changes.

Pyrimethamine (PM) plus sulfadoxine (SD) is the last remaining affordable drug for treating uncomplicated malaria in Africa. The selective pressure exerted by the slowly eliminated combination PM/SD was compared with that exerted by the more rapidly eliminated combination chlorproguanil/dapsone (CPG/Dap) on Kenyan Plasmodium falciparum. Point mutations were analyzed in dihydrofolate reductase and dihydropteroate synthase and in the genetic diversity of 3 genes in isolates collected before and after CPG/Dap and PM/SD treatments. PM/SD was associated strongly with the disappearance of fully drug-sensitive parasites and with a significant increase in the prevalence of resistant parasites in subsequent parasitemias. However, this was not a characteristic of treatment with CPG/Dap. Moreover, most of the patients who returned with recrudescent infections were in the PM/SD-treated group. The data predict a longer useful therapeutic life for CPG/Dap than for PM/SD, and, thus, CPG/Dap is a preferable alternative for treatment of chloroquine-resistant falciparum malaria in sub-Saharan Africa.