Retrievals of ethane from groundbased highresolution FTIR solar observations with updated line parameters: determination of the optimum strategy for the Jungfraujoch station.

Ethane (C2H6) is the most abundant Non-Methane HydroCarbon (NMHC) in the Earth’s atmosphere, with a lifetime of approximately 2 months. Its main sources are biomass burning, natural gas loss and biofuel consumption. Oxidation by the hydroxyl radical is the major C2H6 sink as it controls its strong modulation throug the year. C2H6 is involved in the formation of tropospheric O3 and in the destruction of atmospheric methane through changes in OH. C2H6 is an indirect greenhouse gas with a net-global warming potential of 5.5 (100-yr horizon). Updates of retrieval parameters such as the spectroscopic linelists have been recently published. We will therefore characterize three µ-windows encompassing the strongest C2H6 features after careful selection of these new parameters, accounting at best for all interfering species. The aim is to lessen the fitting residuals while maximizing the information content, the precision and the reliability of the retrieved product. We will present updated C2H6 total and tropospheric column time series, using the SFIT-2 algorithm (v3.91) and high-resolution Fourier Transform Infrared (FTIR) solar absorption spectra recorded with a Bruker 120HR instrument, at the high altitude research station of the Jungfraujoch (46.5°N, 8.0°E, 3580 m asl), within the framework of the Network for the Detection of Atmospheric Composition Change (NDACC, http://www.ndacc.org). Comparisons with synthetic data produced by chemical transport models will also be presented

Development of an atmospheric N2O isotopocule model and optimization procedure, and application to source estimation

This paper presents the development of an atmospheric N2O isotopocule model based on a chemistry-coupled atmospheric general circulation model (ACTM). We also describe a simple method to optimize the model and present its use in estimating the isotopic signatures of surface sources at the hemispheric scale. Data obtained from ground-based observations, measurements of firn air, and balloon and aircraft flights were used to optimize the long-term trends, interhemispheric gradients, and photolytic fractionation, respectively, in the model. This optimization successfully reproduced realistic spatial and temporal variations of atmospheric N2O isotopocules throughout the atmosphere from the surface to the stratosphere. The very small gradients associated with vertical profiles through the troposphere and the latitudinal and vertical distributions within each hemisphere were also reasonably simulated. The results of the isotopic characterization of the global total sources were generally consistent with previous one-box model estimates, indicating that the observed atmospheric trend is the dominant factor controlling the source isotopic signature. However, hemispheric estimates were different from those generated by a previous two-box model study, mainly due to the model accounting for the interhemispheric transport and latitudinal and vertical distributions of tropospheric N2O isotopocules. Comparisons of time series of atmospheric N2O isotopocule ratios between our model and observational data from several laboratories revealed the need for a more systematic and elaborate intercalibration of the standard scales used in N2O isotopic measurements in order to capture a more complete and precise picture of the temporal and spatial variations in atmospheric N2O isotopocule ratios. This study highlights the possibility that inverse estimation of surface N2O fluxes, including the isotopic information as additional constraints, could be realized

Effect of global atmospheric aerosol emission change on PM2.5-related health impacts

Background: Previous research has highlighted the importance of major atmospheric aerosols such as sulfate, through its precursor sulfur dioxide (SO2), black carbon (BC), and organic carbon (OC), and their effect on global climate regimes, specifically on their impact on particulate matter measuring <= 2.5 mu m (PM2.5). Policy regulations have attempted to address the change in these major active aerosols and their impact on PM2.5, which would presumably have a cascading effect toward the change of health risks. Objective: This study aimed to determine how the change in the global emissions of anthropogenic aerosols affects health, particularly through the change in attributable mortality (AN) and years of life lost (YLL). This study also aimed to explore the importance of using AM/YLL in conveying air pollution health impact message. Methods: The Model for Interdisciplinary Research on Climate was used to estimate the gridded atmospheric PM2.5 by changing the emission of SO2, BC, and OC. Next, the emissions were utilized to estimate the associated cause-specific risks via an integrated exposure-response function, and its consequent health indicators, AM and YLL, per country. Results: OC change yielded the greatest benefit for all country income groups, particularly among low-middle-income countries. Utilizing either AM or YLL did not alter the order of benefits among upper-middle and high-income countries (UMIC/HIC); however, using either health indicator to express the order of benefit varied among low- and low-middle-income countries (LIC/LMIC). Conclusions: Global and country-specific mitigation efforts focusing on OC-related activities would yield substantial health benefits. Substantial aerosol emission reduction would greatly benefit high-emitting countries (i.e. China and India). Although no difference is found in the order of health outcome benefits in UMIC/HIC, caution is warranted in using either AM or YLL for health impact assessment in LIC/LMIC

Historical trends and controlling factors of isoprene emissions in CMIP6 Earth system models

Terrestrial isoprene, a biogenic volatile organic compound emitted by many plants, influences atmospheric chemistry and the Earth’s radiative balance. Elucidating its historical changes is therefore important for predicting climate change and air quality. Isoprene emissions can respond to climate (e.g., temperature, shortwave radiation, precipitation), land use and land cover change (LULCC), and atmospheric CO2 concentrations. However, historical trends of isoprene emissions and the relative influences of the respective drivers of those trends remain highly uncertain. This study addresses uncertainty in historical isoprene emission trends and their influential factors, particularly the roles of climate, LULCC, and atmospheric CO2 (via fertilization and inhibition effects). The findings are expected to reconcile discrepancies among different modelling approaches and to improve predictions of isoprene emissions and their climate change effects. To investigate isoprene emission trends, controlling factors, and discrepancies among models, we analyzed long-term (1850–2014) global isoprene emissions from online simulations of CMIP6 Earth System Models and offline simulations using the VISIT dynamic vegetation model driven by climate reanalysis data. Mean annual global present-day isoprene emissions agree well among models (434–510 TgC yr⁻¹) with a 5 % inter-model spread (24 TgC yr⁻¹), but regional emissions differ greatly (9–212 % spread). All models show an increasing trend in global isoprene emissions in recent decades (1980–2014), but their magnitudes vary (+1.27 ± 0.49 TgC yr⁻², 0.28 ± 0.11 % yr⁻¹). Long-term trends of 1850–2014 show high uncertainty among models (–0.92 to +0.31 TgC yr⁻²). Results of emulated sensitivity experiments indicate meteorological variations as the main factor of year-to-year fluctuations, but the main drivers of long-term isoprene emission trends differ among models. Models without CO2 effects implicate climate change as the driver, but other models with CO2 effects (fertilization only/and inhibition) indicate CO2 and LULCC as the primary drivers. The discrepancies arise from how models account for CO2 and LULCC alongside climate effects on isoprene emissions. Aside from LULCC-induced reductions, differences in CO2 inhibition representation (strength and presence or absence of thresholds) were able to mitigate or reverse increasing trends because of rising temperatures or in combination with CO2 fertilization. Net CO2 effects on global isoprene emissions show the highest inter-model variation (σ = 0.43 TgC yr⁻²), followed by LULCC effects (σ = 0.17 TgC yr⁻²), with climate change effects exhibiting more or less variation (σ = 0.06 TgC yr⁻²). The critical drivers of isoprene emission trends depend on a model’s emission scheme complexity. This dependence emphasizes the need for models with accurate representation of CO2 and LULCC effects alongside climate change influences for robust long-term predictions. Important uncertainties remain in understanding the interplay between CO2, LULCC, and climate effects on isoprene emissions, mainly for CO2. More long-term observations of isoprene emissions across various biomes are necessary, along with improved models with varied CO2 responses. Moreover, instead of reliance on the current models, additional emission schemes can better capture isoprene emissions complexities and their effects on climate

Mechanical Engineering

Black carbon (BC) emissions play an important role in regional climate change in the Arctic. It is necessary to pay attention to the impact of long-range transport from regions outside the Arctic as BC emissions from local sources in the Arctic were relatively small. The task force Hemispheric Transport of Air Pollution Phase 2 (HTAP2) set up a series of simulation scenarios to investigate the response of BC in a given region to different source regions. This study investigated the responses of Arctic BC concentrations and surface temperature to 20&thinsp;% anthropogenic emission reductions from six regions in 2010 within the framework of HTAP2 based on ensemble modeling results. Emission reductions from East Asia (EAS) had the most (monthly contributions: 0.2&ndash;1.5&thinsp;ng&thinsp;m&minus;3) significant impact on the Arctic near-surface BC concentrations, while the monthly contributions from Europe (EUR), Middle East (MDE), North America (NAM), Russia&ndash;Belarus&ndash;Ukraine (RBU), and South Asia (SAS) were 0.2&ndash;1.0, 0.001&ndash;0.01, 0.1&ndash;0.3, 0.1&ndash;0.7, and 0.0&ndash;0.2&thinsp;ng&thinsp;m&minus;3, respectively. The responses of the vertical profiles of the Arctic BC to the six regions were found to be different due to multiple transport pathways. Emission reductions from NAM, RBU, EUR, and EAS mainly influenced the BC concentrations in the low troposphere of the Arctic, while most of the BC in the upper troposphere of the Arctic derived from SAS. The response of the Arctic BC to emission reductions in six source regions became less significant with the increase in the latitude. The benefit of BC emission reductions in terms of slowing down surface warming in the Arctic was evaluated by using absolute regional temperature change potential (ARTP). Compared to the response of global temperature to BC emission reductions, the response of Arctic temperature was substantially more sensitive, highlighting the need for curbing global BC emissions. &nbsp;</p

Future global mortality from changes in air pollution attributable to climate change

Ground-level ozone and fine particulate matter (PM2.5) are associated with premature human mortality1-4; their future concentrations depend on changes in emissions, which dominate the near-term5, and on climate change6,7. Previous global studies of the air quality-related health effects of future climate change8,9 used single atmospheric models. However, in related studies, mortality results differ among models10-12. Here we use an ensemble of global chemistry-climate models13 to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.514, is likely positive. We estimate 3,340 (-30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (-195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM2.5, we estimate 55,600 (-34,300 to 164,000) deaths in 2030 and 215,000 (-76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation will likely reduce air pollution-related mortality

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models

Estimates of the global burden of ambient PM2.5, ozone, and NO2 on asthma incidence and emergency room visits

Abstract Background: Asthma is the most prevalent chronic respiratory disease worldwide, affecting 358 million people in 2015. Ambient air pollution exacerbates asthma among populations around the world and may also contribute to new-onset asthma. Objectives: We aimed to estimate the number of asthma emergency room visits and new onset asthma cases globally attributable to fine particulate matter (PM2.5), ozone, and nitrogen dioxide (NO2) concentrations. Methods: We used epidemiological health impact functions combined with data describing population, baseline asthma incidence and prevalence, and pollutant concentrations. We constructed a new dataset of national and regional emergency room visit rates among people with asthma using published survey data. Results: We estimated that 9–23 million and 5–10 million annual asthma emergency room visits globally in 2015 could be attributable to ozone and PM2.5, respectively, representing 8–20% and 4–9% of the annual number of global visits, respectively. The range reflects the application of central risk estimates from different epidemiological meta-analyses. Anthropogenic emissions were responsible for ∼37% and 73% of ozone and PM2.5 impacts, respectively. Remaining impacts were attributable to naturally occurring ozone precursor emissions (e.g., from vegetation, lightning) and PM2.5 (e.g., dust, sea salt), though several of these sources are also influenced by humans. The largest impacts were estimated in China and India. Conclusions: These findings estimate the magnitude of the global asthma burden that could be avoided by reducing ambient air pollution. We also identified key uncertainties and data limitations to be addressed to enable refined estimation. https://doi.org/10.1289/EHP376