In this paper we evaluate the global impact of surface ozone on four types of agricultural crop. The study is based on modelled global hourly ozone fields for the year 2000 and 2030, using the global ...1°×1° 2-way nested atmospheric chemical transport model (TM5). Projections for the year 2030 are based on the relatively optimistic “current legislation (CLE) scenario”, i.e. assuming that currently approved air quality legislation will be fully implemented by the year 2030, without a further development of new abatement policies. For both runs, the relative yield loss due to ozone damage is evaluated based on two different indices (accumulated concentration above a 40
ppbV threshold and seasonal mean daytime ozone concentration respectively) on a global, regional and national scale. The cumulative metric appears to be far less robust than the seasonal mean, while the seasonal mean shows satisfactory agreement with measurements in Europe, the US, China and Southern India and South-East Asia.
Present day global relative yield losses are estimated to range between 7% and 12% for wheat, between 6% and 16% for soybean, between 3% and 4% for rice, and between 3% and 5% for maize (range resulting from different metrics used). Taking into account possible biases in our assessment, introduced through the global application of “western” crop exposure–response functions, and through model performance in reproducing ozone-exposure metrics, our estimates may be considered as being conservative.
Under the 2030 CLE scenario, the global situation is expected to deteriorate mainly for wheat (additional 2–6% loss globally) and rice (additional 1–2% loss globally). India, for which no mitigation measures have been assumed by 2030, accounts for 50% of these global increase in crop yield loss. On a regional-scale, significant reductions in crop losses by CLE-2030 are only predicted in Europe (soybean) and China (wheat).
Translating these assumed yield losses into total global economic damage for the four crops considered, using world market prices for the year 2000, we estimate an economic loss in the range $14–$26 billion. About 40% of this damage is occurring in China and India. Considering the recent upward trends in food prices, the ozone-induced damage to crops is expected to offset a significant portion of the GDP growth rate, especially in countries with an economy based on agricultural production.
We present an estimate of net CO₂ exchange between the terrestrial biosphere and the atmosphere across North America for every week in the period 2000 through 2005. This estimate is derived from a ...set of 28,000 CO₂ mole fraction observations in the global atmosphere that are fed into a state-of-the-art data assimilation system for CO₂ called CarbonTracker. By design, the surface fluxes produced in CarbonTracker are consistent with the recent history of CO₂ in the atmosphere and provide constraints on the net carbon flux independent from national inventories derived from accounting efforts. We find the North American terrestrial biosphere to have absorbed -0.65 PgC/yr (1 petagram = 10¹⁵ g; negative signs are used for carbon sinks) averaged over the period studied, partly offsetting the estimated 1.85 PgC/yr release by fossil fuel burning and cement manufacturing. Uncertainty on this estimate is derived from a set of sensitivity experiments and places the sink within a range of -0.4 to -1.0 PgC/yr. The estimated sink is located mainly in the deciduous forests along the East Coast (32%) and the boreal coniferous forests (22%). Terrestrial uptake fell to -0.32 PgC/yr during the large-scale drought of 2002, suggesting sensitivity of the contemporary carbon sinks to climate extremes. CarbonTracker results are in excellent agreement with a wide collection of carbon inventories that form the basis of the first North American State of the Carbon Cycle Report (SOCCR), to be released in 2007. All CarbonTracker results are freely available at http://carbontracker.noaa.gov.
Dry deposition is an important removal mechanism for tropospheric ozone (O.sub.3). Currently, O.sub.3 deposition to oceans in atmospheric chemistry and transport models (ACTMs) is generally ...represented using constant surface uptake resistances. This occurs despite the role of solubility, waterside turbulence and O.sub.3 reacting with ocean water reactants such as iodide resulting in substantial spatiotemporal variability in O.sub.3 deposition and concentrations in marine boundary layers. We hypothesize that O.sub.3 deposition to the Arctic Ocean, having a relatively low reactivity, is overestimated in current models with consequences for the tropospheric concentrations, lifetime and long-range transport of O.sub.3 . We investigate the impact of the representation of oceanic O.sub.3 deposition to the simulated magnitude and spatiotemporal variability in Arctic surface O.sub.3.
Ozone (O3) is a secondary air pollutant that negatively affects human and ecosystem health. Ozone simulations with regional air quality models suffer from unexplained biases over Europe, and ...uncertainties in the emissions of ozone precursor group nitrogen oxides (NOx=NO+NO2) contribute to these biases. The goal of this study is to use NO2 column observations from the Ozone Monitoring Instrument (OMI) satellite sensor to infer top-down NOx emissions in the regional Weather Research and Forecasting model with coupled chemistry (WRF-Chem) and to evaluate the impact on simulated surface O3 with in situ observations. We first perform a simulation for July 2015 over Europe and evaluate its performance against in situ observations from the AirBase network. The spatial distribution of mean ozone concentrations is reproduced satisfactorily. However, the simulated maximum daily 8 h ozone concentration (MDA8 O3) is underestimated (mean bias error of −14.2 µg m−3), and its spread is too low. We subsequently derive satellite-constrained surface NOx emissions using a mass balance approach based on the relative difference between OMI and WRF-Chem NO2 columns. The method accounts for feedbacks through OH, NO2's dominant daytime oxidant. Our optimized European NOx emissions amount to 0.50 Tg N (for July 2015), which is 0.18 Tg N higher than the bottom-up emissions (which lacked agricultural soil NOx emissions). Much of the increases occur across Europe, in regions where agricultural soil NOx emissions dominate. Our best estimate of soil NOx emissions in July 2015 is 0.1 Tg N, much higher than the bottom-up 0.02 Tg N natural soil NOx emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN). A simulation with satellite-updated NOx emissions reduces the systematic bias between WRF-Chem and OMI NO2 (slope =0.98, r2=0.84) and reduces the low bias against independent surface NO2 measurements by 1.1 µg m−3 (−56 %). Following these NOx emission changes, daytime ozone is strongly affected, since NOx emission changes particularly affect daytime ozone formation. Monthly averaged simulated daytime ozone increases by 6.0 µg m−3, and increases of >10 µg m−3 are seen in regions with large emission increases. With respect to the initial simulation, MDA8 O3 has an improved spatial distribution, expressed by an increase in r2 from 0.40 to 0.53, and a decrease of the mean bias by 7.4 µg m−3 (48 %). Overall, our results highlight the dependence of surface ozone on its precursor NOx and demonstrate that simulations of surface ozone benefit from constraining surface NOx emissions by satellite NO2 column observations.
Variations in the atmospheric oxidative capacity, largely determined by variations in the hydroxyl radical (OH), form a key uncertainty in many greenhouse and other pollutant budgets, such as that of ...methane (CH.sub.4). Methyl chloroform (MCF) is an often-adopted tracer to indirectly put observational constraints on large-scale variations in OH. We investigated the budget of MCF in a 4DVAR inversion using the atmospheric transport model TM5, for the period 1998-2018, with the objective to derive information on large-scale, interannual variations in atmospheric OH concentrations.
This study investigates the use of co-located nitrogen dioxide (NO2) and carbon monoxide (CO) retrievals from the TROPOMI satellite to improve the quantification of burning efficiency and emission ...factors (EFs) over the megacities of Tehran, Mexico City, Cairo, Riyadh, Lahore, and Los Angeles. Efficient combustion is characterized by high NOx (NO+NO2) and low CO emissions, making theNO2/CO ratio a useful proxy for combustion efficiency (CE). The local enhancement of CO and NO2 above megacities is well captured by TROPOMI at short averaging times compared with previous satellite missions. In this study, the upwind background and plume rotation methods are used to investigate the accuracy of satellite-derived ΔNO2/ΔCO ratios. The column enhancement ratios derived using these two methods vary by 5 % to 20 % across the selected megacities. TROPOMI-derived column enhancement ratios are compared with emission ratios from the EDGAR v4.3.2 (Emission Database for Global Atmospheric Research v4.3.2) and the MACCity (Monitoring Atmospheric Chemistry and Climate and CityZen) 2018 emission inventories. TROPOMI correlates strongly (r=0.85 and 0.7) with EDGAR and MACCity, showing the highest emission ratio for Riyadh and lowest emission ratio for Lahore. However, inventory-derived emission ratios are 60 % to 85 % higher than TROPOMI column enhancement ratios across the six megacities. The short lifetime of NO2 and the different vertical sensitivity of TROPOMI NO2 and CO explain most of this difference. We present a method to translate TROPOMI-retrieved column enhancement ratios into corresponding emission ratios, thereby accounting for these influences. Except for Los Angeles and Lahore, TROPOMI-derived emission ratios are close (within 10 % to 25 %) to MACCity values. For EDGAR, however, emission ratios are ∼65 % higher for Cairo and 35 % higher for Riyadh. For Los Angeles, EDGAR and MACCity are a factor of 2 and 3 higher than TROPOMI respectively. The air quality monitoring networks in Los Angeles and Mexico City are used to validate the use of TROPOMI. For Mexico City and Los Angeles, these measurements are consistent with TROPOMI-derived emission ratios, demonstrating the potential of TROPOMI with respect to monitoring burning efficiency.
This work reports on the current status of the global modeling of iron (Fe)
deposition fluxes and atmospheric concentrations and the analyses of the
differences between models, as well as between ...models and observations. A
total of four global 3-D chemistry transport (CTMs) and general circulation
(GCMs) models participated in this intercomparison, in the framework of
the United Nations Joint Group of Experts on the Scientific Aspects of Marine
Environmental Protection (GESAMP) Working Group 38, “The Atmospheric Input
of Chemicals to the Ocean”. The global total Fe (TFe) emission strength in
the models is equal to ∼72 Tg Fe yr−1 (38–134 Tg Fe yr−1)
from mineral dust sources and around 2.1 Tg Fe yr−1 (1.8–2.7 Tg Fe yr−1)
from combustion processes (the sum of anthropogenic
combustion/biomass burning and wildfires). The mean global labile Fe (LFe)
source strength in the models, considering both the primary emissions and the
atmospheric processing, is calculated to be 0.7 (±0.3) Tg Fe yr−1,
accounting for both mineral dust and combustion aerosols. The
mean global deposition fluxes into the global ocean are estimated to be in the range
of 10–30 and 0.2–0.4 Tg Fe yr−1 for TFe and LFe, respectively,
which roughly corresponds to a respective 15 and 0.3 Tg Fe yr−1 for the multi-model ensemble model mean. The model intercomparison analysis indicates that the representation of the
atmospheric Fe cycle varies among models, in terms of both the magnitude of
natural and combustion Fe emissions as well as the complexity of atmospheric
processing parameterizations of Fe-containing aerosols. The model comparison
with aerosol Fe observations over oceanic regions indicates that most models
overestimate surface level TFe mass concentrations near dust source
regions and tend to underestimate the low concentrations observed in remote
ocean regions. All models are able to simulate the tendency of higher Fe
concentrations near and downwind from the dust source regions, with the mean
normalized bias for the Northern Hemisphere (∼14), larger
than that of the Southern Hemisphere (∼2.4) for the ensemble model
mean. This model intercomparison and model–observation comparison study
reveals two critical issues in LFe simulations that require further
exploration: (1) the Fe-containing aerosol size distribution and (2) the
relative contribution of dust and combustion sources of Fe to labile Fe in
atmospheric aerosols over the remote oceanic regions.
Carbonyl sulfide (COS) has the potential to be used as a climate diagnostic due to its close coupling to the biospheric uptake of CO2 and its role in the formation of stratospheric aerosol. The ...current understanding of the COS budget, however, lacks COS sources, which have previously been allocated to the tropical ocean. This paper presents a first attempt at global inverse modelling of COS within the 4-dimensional variational data-assimilation system of the TM5 chemistry transport model (TM5-4DVAR) and a comparison of the results with various COS observations. We focus on the global COS budget, including COS production from its precursors carbon disulfide (CS2) and dimethyl sulfide (DMS). To this end, we implemented COS uptake by soil and vegetation from an updated biosphere model (Simple Biosphere Model – SiB4). In the calculation of these fluxes, a fixed atmospheric mole fraction of 500 pmol mol−1 was assumed. We also used new inventories for anthropogenic and biomass burning emissions. The model framework is capable of closing the COS budget by optimizing for missing emissions using NOAA observations in the period 2000–2012. The addition of 432 Gg a−1 (as S equivalents) of COS is required to obtain a good fit with NOAA observations. This missing source shows few year-to-year variations but considerable seasonal variations. We found that the missing sources are likely located in the tropical regions, and an overestimated biospheric sink in the tropics cannot be ruled out due to missing observations in the tropical continental boundary layer. Moreover, high latitudes in the Northern Hemisphere require extra COS uptake or reduced emissions. HIPPO (HIAPER Pole-to-Pole Observations) aircraft observations, NOAA airborne profiles from an ongoing monitoring programme and several satellite data sources are used to evaluate the optimized model results. This evaluation indicates that COS mole fractions in the free troposphere remain underestimated after optimization. Assimilation of HIPPO observations slightly improves this model bias, which implies that additional observations are urgently required to constrain sources and sinks of COS. We finally find that the biosphere flux dependency on the surface COS mole fraction (which was not accounted for in this study) may substantially lower the fluxes of the SiB4 biosphere model over strong-uptake regions. Using COS mole fractions from our inversion, the prior biosphere flux reduces from 1053 to 851 Gg a−1, which is closer to 738 Gg a−1 as was found by Berry et al. (2013). In planned further studies we will implement this biosphere dependency and additionally assimilate satellite data with the aim of better separating the role of the oceans and the biosphere in the global COS budget.
A new method is presented for estimating urban hydroxyl radical (OH) concentrations using the downwind decay of the ratio of nitrogen dioxide over carbon monoxide column-mixing ratios (XNO2/XCO) ...retrieved from the Tropospheric Monitoring Instrument (TROPOMI). The method makes use of plumes simulated by the Weather Research and Forecast model (WRF-Chem) using passive-tracer transport, instead of the encoded chemistry, in combination with auxiliary input variables such as Copernicus Atmospheric Monitoring Service (CAMS) OH, Emission Database for Global Atmospheric Research v4.3.2 (EDGAR) NOx and CO emissions, and National Center for Environmental Protection (NCEP)-based meteorological data. NO2 and CO mixing ratios from the CAMS reanalysis are used as initial and lateral boundary conditions. WRF overestimates NO2 plumes close to the center of the city by 15 % to 30 % in summer and 40 % to 50 % in winter compared to TROPOMI observations over Riyadh. WRF-simulated CO plumes differ by 10 % with TROPOMI in both seasons. The differences between WRF and TROPOMI are used to optimize the OH concentration, NOx, CO emissions and their backgrounds using an iterative least-squares method. To estimate OH, WRF is optimized using (a) TROPOMI XNO2/XCO and (b) TROPOMI-derived XNO2 only.For summer, both the NO2/CO ratio optimization and the XNO2 optimization increase the prior OH from CAMS by 32 ± 5.3 % and 28.3 ± 3.9 %, respectively. EDGAR NOx and CO emissions over Riyadh are increased by 42.1 ± 8.4 % and 101 ± 21 %, respectively, in summer. In winter, the optimization method doubles the CO emissions while increasing OH by ∼ 52 ± 14 % and reducing NOx emissions by 15.5 ± 4.1 %. TROPOMI-derived OH concentrations and the pre-existing exponentially modified Gaussian function fit (EMG) method differ by 10 % in summer and winter, confirming that urban OH concentrations can be reliably estimated using the TROPOMI-observed NO2/CO ratio. Additionally, our method can be applied to a single TROPOMI overpass, allowing one to analyze day-to-day variability in OH, NOx and CO emission.
Carbonyl sulfide (COS), a trace gas in our atmosphere that leads to the formation of aerosols in the stratosphere, is largely taken up by terrestrial ecosystems. Quantifying the biosphere uptake of ...COS could provide a useful quantity to estimate gross primary productivity (GPP). Some COS sources and sinks still contain large uncertainties, and several top-down estimates of the COS budget point to an underestimation of sources, especially in the tropics. We extended the inverse model TM5-4DVAR to assimilate Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite data, in addition to National Oceanic and Atmospheric Administration (NOAA) surface data as used in a previous study. To resolve possible discrepancies among the two observational data sets, a bias correction scheme is necessary and implemented. A set of inversions is presented that explores the influence of the different measurement streams and the settings of the prior fluxes. To evaluate the performance of the inverse system, the HIAPER Pole-to-Pole Observations (HIPPO) aircraft observations and NOAA airborne profiles are used. All inversions reduce the COS biosphere uptake from a prior value of 1053 GgS a−1 to much smaller values, depending on the inversion settings. These large adjustments of the biosphere uptake often turn parts of Amazonia into a COS source. Only inversions that exclusively use MIPAS observations, or strongly reduce the prior errors on the biosphere flux, maintain the Amazon as a COS sink. Inclusion of MIPAS data in the inversion leads to a better separation of land and ocean fluxes. Over the Amazon, these inversions reduce the biosphere uptake from roughly 300 to 100 GgS a−1, indicating a strongly overestimated prior uptake in this region. Although a recent study also reported reduced COS uptake over the Amazon, we emphasise that a careful construction of prior fluxes and their associated errors remains important. For instance, an inversion that gives large freedom to adjust the anthropogenic and ocean fluxes of CS2, an important COS precursor, also closes the budget satisfactorily with much smaller adjustments to the biosphere. We achieved better characterisation of biosphere prior and uncertainty, better characterisation of combined ocean and land fluxes, and better constraint of both by combining surface and satellite observations. We recommend more COS observations to characterise biosphere and ocean fluxes, especially over the data-poor tropics.
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