Surface ozone concentrations increased in many regions of
China from 2015 to 2019. While the central role of meteorology in modulating
ozone pollution is widely acknowledged, its quantitative ...contribution
remains highly uncertain. Here, we use a data-driven machine learning
approach to assess the impacts of meteorology on surface ozone variations in
China for the period 2015–2019, considering the months of highest ozone pollution
from April to October. To quantify the importance of various meteorological
driver variables, we apply nonlinear random forest regression (RFR) and
linear ridge regression (RR) to learn about the relationship between
meteorological variability and surface ozone in China, and contrast the
results to those obtained with the widely used multiple linear regression
(MLR) and stepwise MLR. We show that RFR outperforms the three linear
methods when predicting ozone using local meteorological predictor
variables, as evident from its higher coefficients of determination
(R2) with observations (0.5–0.6 across China) when compared to the
linear methods (typically R2 = 0.4–0.5). This refers to the importance of
nonlinear relationships between local meteorological factors and ozone,
which are not captured by linear regression algorithms. In addition, we find
that including nonlocal meteorological predictors can further improve the
modelling skill of RR, particularly for southern China where the averaged
R2 increases from 0.47 to 0.6. Moreover, this improved RR shows a
higher averaged meteorological contribution to the increased trend of ozone
pollution in that region, pointing towards an elevated importance of
large-scale meteorological phenomena for ozone pollution in southern China.
Overall, RFR and RR are in close agreement concerning the leading
meteorological drivers behind regional ozone pollution. In line with
expectations, our analysis underlines that hot and dry weather conditions
with high sunlight intensity are strongly related to high ozone pollution
across China, thus further validating our novel approach. In contrast to
previous studies, we also highlight surface solar radiation as a key
meteorological variable to be considered in future analyses. By comparing
our meteorology based predictions with observed ozone values between 2015
and 2019, we estimate that almost half of the 2015–2019 ozone trends across
China might have been caused by meteorological variability. These insights
are of particular importance given possible increases in the frequency and
intensity of weather extremes such as heatwaves under climate change.
Climate policies will affect future surface ozone pollution in China. Here, we simulate changes in summertime ozone across China by 2030 under four emission scenarios reflecting different levels of ...climate action. We also contrast results obtained with two different chemical mechanisms employed in the chemical transport model (WRF‐Chem). With emission reductions in ozone precursors introduced by climate policies, both mechanisms show promising ozone mitigation for most parts of China. However, they disagree starkly in China's three main city clusters, where one mechanism projects worsening ozone pollution by 2030 despite the emission reductions. We analyze possible drivers of this important discrepancy, in particular the role of varying ozone chemical regimes affecting its sensitivity to emission changes. We recommend an intercomparison project to examine this critical modeling uncertainty among other models/mechanisms, which would be invaluable for informing local and regional emission control strategies that are based on single‐model results.
Plain Language Summary
Surface ozone pollution is harmful to both human health and ecosystems. Reducing ozone formation through effective emission control strategies has therefore been identified as a pressing need. Chemical transport models (CTMs) are important tools that can help scientists and policymakers assess how effectively the emission reductions may alleviate ozone pollution. However, we show that the predicted effectiveness of emission control strategies for ozone mitigation in areas within the three city clusters of China are strongly dependent on the choice of chemical mechanism commonly employed in CTMs. For example, given emission reductions driven by ambitious climate action, we find that projected ozone pollution in these regions could be improved or worsened by the year 2030 depending on the model mechanism used. Our work underlines the importance of considering and understanding this disagreement when it comes to projecting even near‐term emission‐control strategies. Furthermore, we highlight the potential benefits of conducting a multi‐model/mechanism intercomparison project to better understand how and why different models/mechanisms disagree on the simulated ozone response to emission changes, as to produce more robust mitigation scenario assessments.
Key Points
Future emission pathways driven by climate actions are projected to alleviate surface ozone pollution in most parts of China by 2030
However, for China's three main city clusters, model projections disagree strongly for two widely used chemical mechanisms
This modeling uncertainty may arise from the inconsistency of categorizing ozone chemical regimes by different chemical mechanisms
Volatile organic compounds (VOCs) play an important role in urban air pollution, both as primary pollutants and through their contribution to the formation of secondary pollutants, such as ...tropospheric ozone and secondary organic aerosols. In this study, more than 30 VOC species were continuously monitored in the two most populous cities in Vietnam, namely Ho Chi Minh City (HCMC, September-October 2018 and March 2019) and Hanoi (March 2019). In parallel with ambient VOC sampling, grab sampling was used to target the most prevalent regional-specific emission sources and estimate their emission factors (EFs).
Emission ratios (ERs) obtained from ambient sampling were compared between Vietnamese cities and other cities across the globe. No significant differences were observed between HCMC and Hanoi, suggesting the presence of similar sources. Moreover, a good global agreement was obtained in the spatial comparison within a factor of 2, with greater ER for aromatics and pentanes obtained in the Vietnamese cities.
The detailed analysis of sources included the evaluation of EF from passenger cars, buses, trucks, motorcycles, 3-wheeled motorcycles, waste burning, and coal-burning emissions. Our comparisons between ambient and near-source concentration profiles show that road transport sources are the main contributors to VOC concentrations in Vietnamese cities.
VOC emissions were calculated from measured EF and consumption data available in Hanoi and compared with those estimated by a global emission inventory (EDGAR v4.3.2). The total VOC emissions from the road transport sector estimated by the inventory do not agree with those calculated from our observations which showed higher total emissions by a factor of 3. Furthermore, the inventory misrepresented the VOCs speciation, mainly for isoprene, monoterpenes, aromatics, and oxygenated compounds. Accounting for these differences in regional air quality models would lead to improved predictions of their impacts and help to prioritise pollution reduction strategies in the region.
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•VOC emission ratios do not show substantial seasonal differences in Ho Chi Minh City.•VOCs from road transport emissions are similar to ambient concentration profiles in Hanoi.•Large differences in speciation are observed between observations and inventory estimations.•Observed total VOC road transport emissions are 3 times higher than those estimated by the inventory.
Since 1850 the concentration of atmospheric methane (CH4), a potent
greenhouse gas, has more than doubled. Recent studies suggest that emission
inventories may be missing sources and underestimating ...emissions. To
investigate whether offshore oil and gas platforms leak CH4 during
normal operation, we measured CH4 mole fractions around eight oil and
gas production platforms in the North Sea which were neither flaring gas nor
offloading oil. We use the measurements from summer 2017, along with
meteorological data, in a Gaussian plume model to estimate CH4
emissions from each platform. We find CH4 mole fractions of between 11
and 370 ppb above background concentrations downwind of the platforms
measured, corresponding to a median CH4 emission of 6.8 g CH4 s−1 for each platform, with a range of 2.9 to 22.3 g CH4 s−1.
When matched to production records, during our measurements individual
platforms lost between 0.04 % and 1.4 % of gas produced with a median
loss of 0.23 %. When the measured platforms are considered collectively
(i.e. the sum of platforms' emission fluxes weighted by the sum of the
platforms' production), we estimate the CH4 loss to be 0.19 % of gas
production. These estimates are substantially higher than the emissions most
recently reported to the National Atmospheric Emission Inventory (NAEI) for
total CH4 loss from United Kingdom platforms in the North Sea. The NAEI
reports CH4 losses from the offshore oil and gas platforms we measured
to be 0.13 % of gas production, with most of their emissions coming from
gas flaring and offshore oil loading, neither of which was taking place at
the time of our measurements. All oil and gas platforms we observed were
found to leak CH4 during normal operation, and much of this leakage has
not been included in UK emission inventories. Further research is required
to accurately determine total CH4 leakage from all offshore oil and gas
operations and to properly include the leakage in national and international
emission inventories.
We investigate the use of atmospheric oxygen (O2) and carbon dioxide (CO2) measurements for the estimation of the fossil fuel component of atmospheric CO2 in the UK. Atmospheric potential oxygen ...(APO) – a tracer that combines O2 and CO2, minimizing the influence of terrestrial biosphere fluxes – is simulated at three sites in the UK, two of which make APO measurements. We present a set of model experiments that estimate the sensitivity of APO simulations to key inputs: fluxes from the ocean, fossil fuel flux magnitude and distribution, the APO baseline, and the exchange ratio of O2 to CO2 fluxes from fossil fuel combustion and the terrestrial biosphere. To estimate the influence of uncertainties in ocean fluxes, we compare three ocean O2 flux estimates from the NEMO–ERSEM, the ECCO–Darwin ocean model, and the Jena CarboScope (JC) APO inversion. The sensitivity of APO to fossil fuel emission magnitudes and to terrestrial biosphere and fossil fuel exchange ratios is investigated through Monte Carlo sampling within literature uncertainty ranges and by comparing different inventory estimates. We focus our model–data analysis on the year 2015 as ocean fluxes are not available for later years. As APO measurements are only available for one UK site at this time, our analysis focuses on the Weybourne station. Model–data comparisons for two additional UK sites (Heathfield and Ridge Hill) in 2021, using ocean flux climatologies, are presented in the Supplement. Of the factors that could potentially compromise simulated APO-derived fossil fuel CO2 (ffCO2) estimates, we find that the ocean O2 flux estimate has the largest overall influence at the three sites in the UK. At times, this influence is comparable in magnitude to the contribution of simulated fossil fuel CO2 to simulated APO. We find that simulations using different ocean fluxes differ from each other substantially. No single model estimate, or a model estimate that assumed zero ocean flux, provided a significantly closer fit than any other. Furthermore, the uncertainty in the ocean contribution to APO could lead to uncertainty in defining an appropriate regional background from the data. Our findings suggest that the contribution of non-terrestrial sources needs to be better accounted for in model simulations of APO in the UK to reduce the potential influence on inferred fossil fuel CO2 using APO.
Risk assessment of pesticide impacts on remote ecosystems makes use of model-estimated degradation in air. Recent studies suggest these degradation rates to be overestimated, questioning current ...pesticide regulation. Here, we investigated the concentrations of 76 pesticides in Europe at 29 rural, coastal, mountain, and polar sites during the agricultural application season. Overall, 58 pesticides were observed in the European atmosphere. Low spatial variation of 7 pesticides suggests continental-scale atmospheric dispersal. Based on concentrations in free tropospheric air and at Arctic sites, 22 pesticides were identified to be prone to long-range atmospheric transport, which included 15 substances approved for agricultural use in Europe and 7 banned ones. Comparison between concentrations at remote sites and those found at pesticide source areas suggests long atmospheric lifetimes of atrazine, cyprodinil, spiroxamine, tebuconazole, terbuthylazine, and thiacloprid. In general, our findings suggest that atmospheric transport and persistence of pesticides have been underestimated and that their risk assessment needs to be improved.
OH, HO2, total and partially speciated RO2, and OH reactivity (kOH′) were measured during the July 2015 ICOZA (Integrated Chemistry of OZone in the Atmosphere) project that took place at a coastal ...site in north Norfolk, UK. Maximum measured daily OH, HO2 and total RO2 radical concentrations were in the range 2.6–17 × 106, 0.75–4.2 × 108 and 2.3–8.0 × 108 molec. cm−3, respectively. kOH′ ranged from 1.7 to 17.6 s−1, with a median value of 4.7 s−1. ICOZA data were split by wind direction to assess differences in the radical chemistry between air that had passed over the North Sea (NW–SE sectors) and that over major urban conurbations such as London (SW sector). A box model using the Master Chemical Mechanism (MCMv3.3.1) was in reasonable agreement with the OH measurements, but it overpredicted HO2 observations in NW–SE air in the afternoon by a factor of ∼ 2–3, although slightly better agreement was found for HO2 in SW air (factor of ∼ 1.4–2.0 underprediction). The box model severely underpredicted total RO2 observations in both NW–SE and SW air by factors of ∼ 8–9 on average. Measured radical and kOH′ levels and measurement–model ratios displayed strong dependences on NO mixing ratios, with the results suggesting that peroxy radical chemistry is not well understood under high-NOx conditions. The simultaneous measurement of OH, HO2, total RO2 and kOH′ was used to derive experimental (i.e. observationally determined) budgets for all radical species as well as total ROx (i.e. OH + HO2 + RO2). In NW–SE air, the ROx budget could be closed during the daytime within experimental uncertainty, but the rate of OH destruction exceeded the rate of OH production, and the rate of HO2 production greatly exceeded the rate of HO2 destruction, while the opposite was true for RO2. In SW air, the ROx budget analysis indicated missing daytime ROx sources, but the OH budget was balanced, and the same imbalances were found with the HO2 and RO2 budgets as in NW–SE air. For HO2 and RO2, the budget imbalances were most severe at high-NO mixing ratios, and the best agreement between HO2 and RO2 rates of production and destruction rates was found when the RO2 + NO rate coefficient was reduced by a factor of 5. A photostationary-steady-state (PSS) calculation underpredicted daytime OH in NW–SE air by ∼ 35 %, whereas agreement (∼ 15 %) was found within instrumental uncertainty (∼ 26 % at 2σ) in SW air. The rate of in situ ozone production (P(Ox)) was calculated from observations of ROx, NO and NO2 and compared to that calculated from MCM-modelled radical concentrations. The MCM-calculated P(Ox) significantly underpredicted the measurement-calculated P(Ox) in the morning, and the degree of underprediction was found to scale with NO.
We present a novel high-resolution inverse modelling system (“FLEXVAR”) based on FLEXPART-COSMO back trajectories driven by COSMO meteorological fields at 7km×7km resolution over the European COSMO-7 ...domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions (“baselines”) consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH4 emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter (“FLExKF”) system and with TM5-4DVAR inversions at 1∘×1∘ resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7km×7km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at 1∘×1∘. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories.
We present a characterization of the chemical composition of the atmosphere
of the Brazilian Amazon rainforest based on trace gas measurements carried
out during the South AMerican Biomass Burning ...Analysis (SAMBBA) airborne
experiment in September 2012. We analyzed the observations of primary biomass
burning emission tracers, i.e., carbon monoxide (CO), nitrogen oxides
(NOx), ozone (O3), isoprene, and its main oxidation
products, methyl vinyl ketone (MVK), methacrolein (MACR), and isoprene
hydroxy hydroperoxide (ISOPOOH). The focus of SAMBBA was primarily on biomass
burning emissions, but there were also several flights in areas of the Amazon
forest not directly affected by biomass burning, revealing a background with
a signature of biomass burning in the chemical composition due to long-range
transport of biomass burning tracers from both Africa and the eastern part of
Amazonia. We used the MVK + MACR + ISOPOOH ∕ isoprene ratio
and the hydroxyl radical (OH) indirect calculation to assess the oxidative
capacity of the Amazon forest atmosphere. We compared the background regions
(CO < 150 ppbv), fresh and aged smoke plumes classified according
to their photochemical age (O3 ∕ CO), to evaluate the impact
of biomass burning emissions on the oxidative capacity of the Amazon forest
atmosphere. We observed that biomass burning emissions disturb the isoprene
oxidation reactions, especially for fresh plumes
(MVK + MACR + ISOPOOH ∕ isoprene = 7) downwind. The
oxidation of isoprene is higher in fresh smoke plumes at lower altitudes
(∼ 500 m) than in aged smoke plumes, anticipating near the surface a
complex chain of oxidation reactions which may be related to secondary organic aerosol (SOA) formation.
We proposed a refinement of the OH calculation based on the
sequential reaction model, which considers vertical and horizontal transport
for both biomass burning regimes and background environment. Our approach for
the OH estimation resulted in values on the same order of magnitude of a
recent observation in the Amazon rainforest OH ≅ 106
(molecules cm−3). During the fresh plume regime, the vertical profile
of OH and the MVK + MACR + ISOPOOH ∕ isoprene ratio showed
evidence of an increase in the oxidizing power in the transition from
planetary boundary layer to cloud layer (1000–1500 m). These high values of
OH (1.5 × 106 molecules cm−3) and
MVK + MACR + ISOPOOH ∕ isoprene (7.5) indicate a significant
change above and inside the cloud decks due to cloud edge effects on
photolysis rates, which have a major impact on OH production rates.
Fluxes of oxygen (O2) and carbon dioxide (CO2) in and out of the atmosphere are strongly coupled for terrestrial biospheric exchange processes and fossil fuel combustion but are uncoupled for oceanic ...air–sea gas exchange. High-precision measurements of both species can therefore provide constraints on the carbon cycle and can be used to quantify fossil fuel CO2 (ffCO2) emission estimates. In the case of O2, however, due to its large atmospheric mole fraction (∼20.9 %) it is very challenging to measure small variations to the degree of precision and accuracy required for these applications. We have tested an atmospheric O2 analyser based on the principle of cavity ring-down spectroscopy (Picarro Inc., model G2207-i), both in the laboratory and at the Weybourne Atmospheric Observatory (WAO) field station in the UK, in comparison to well-established, pre-existing atmospheric O2 and CO2 measurement systems.In laboratory tests analysing dry air in high-pressure cylinders, we found that the best precision was achieved with 30 min averaging and was±0.5 ppm (∼±2.4 per meg). Also from continuous measurements from a cylinder of dry air, we found the 24 h peak-to-peak range of hourly averaged values to be 1.2 ppm (∼5.8 per meg). These results are close to atmospheric O2 compatibility goals as set by the UN World Meteorological Organization. However, from measurements of ambient air conducted at WAO we found that the built-in water correction of the G2207-i does not sufficiently correct for the influence of water vapour on the O2 mole fraction. When sample air was dried and a 5-hourly baseline correction with a reference gas cylinder was employed, the G2207-i's results showed an average difference from the established O2 analyser of 13.6±7.5 per meg (over 2 weeks of continuous measurements). Over the same period, based on measurements of a so-called “target tank”, analysed for 12 min every 7 h, we calculated a repeatability of ±5.7±5.6 per meg and a compatibility of ±10.0±6.7 per meg for the G2207-i. To further examine the G2207-i's performance in real-world applications we used ambient air measurements of O2 together with concurrent CO2 measurements to calculate ffCO2. Due to the imprecision of the G2207-i, the ffCO2 calculated showed large differences from that calculated from the established measurement system and had a large uncertainty of ±13.0 ppm, which was roughly double that from the established system (±5.8 ppm).
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