Search

Tropospheric nitrogen dioxide (NO2) measured from satellites has been widely used to track anthropogenic NOx emissions, but its retrieval and interpretation can be complicated by the free tropospheric NO2 background to which satellite measurements are particularly sensitive. Tropospheric NO2 vertical column densities (VCDs) from the spaceborne Ozone Monitoring Instrument (OMI) averaged over the contiguous US (CONUS) show no trend after 2009, despite sustained decreases in anthropogenic NOx emissions, implying an important and rising contribution from the free tropospheric background. Here, we use the GEOS-Chem chemical transport model applied to the simulation of OMI NO2 to better understand the sources and trends of background NO2 over CONUS. The previous model underestimate of the background is largely corrected by the consideration of aerosol nitrate photolysis, which increases the model NO2 VCDs by 13 % on an annual basis (25 % in spring) and also increases the air mass factor (AMF) to convert the tropospheric slant column densities (SCDs) inferred from the OMI spectra into VCDs by 7 % on an annual basis (11 % in spring). The increase in the AMF decreases the retrieved NO2 VCDs in the satellite observations, contributing to the improved agreement with the model. Accounting for the 2009–2017 increase in aircraft NOx emissions drives only a 1.4 % mean increase in NO2 VCDs over CONUS and a 2 % increase in the AMF, but the combination of decreasing surface NOx emissions and increasing aircraft emissions is expected to drive a 14 % increase in the AMF over the next decade that will be necessary to account for in the interpretation of satellite NO2 trends. Fire smoke identification with the National Oceanic and Atmospheric Administration (NOAA) Hazard Mapping System (HMS) indicates that wildfires contribute 1 %–8 % of OMI NO2 VCDs over the western US in June–September and that this contribution has been increasing since 2009, contributing to the flattening of OMI NO2 trends. Future analyses of NO2 trends from satellite data to infer trends in surface NOx emissions must critically consider the effects of a rising free tropospheric background due to increasing emissions from aircraft, fires, and possibly lightning.

A large population in China has been exposed to both severe ozone (O3) pollution and extreme heat under global warming. Here, the spatiotemporal characteristics of coupled extremes in surface O3 and heat (OPCs) over China are investigated using surface observations, a process-based chemical transport model (GEOS-Chem), and multi-model simulations from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). North China Plain (NCP; 37–41∘ N; 114–120∘ E) is identified as a hot spot of OPCs, where more than half of the O3 pollution days are accompanied by high temperature extremes. OPCs over NCP exceeded 40 d during 2014–2019, exhibiting an increasing trend. Both O3 concentrations and temperatures are elevated during OPCs compared with O3 pollution days occurring individually (OPIs). Therefore, OPCs impose more severe health impacts to humans than OPIs, but the stronger health effects are mainly driven by the higher temperatures. GEOS-Chem simulations further reveal that enhanced chemical production resulting from hot and stable atmospheric conditions under anomalous weather patterns primarily contributes to the exacerbated O3 levels during OPCs. In the future, CMIP6 projections suggest increased occurrences of OPCs over NCP in the middle of this century, but by the end of this century, OPCs may decrease or increase depending on the pollutant emission scenarios. However, for all future scenarios, extreme high temperatures will play an increasingly important role in modulating O3 pollution in a warming climate.

We applied the global 3-D chemical transport model GEOS-Chem to examine the anthropogenic and meteorological contributions in driving summertime (JJA) surface ozone (O3) trend in China during the Clean Air Action period 2012–2017. The model captures the observed spatial distribution of summertime O3 concentrations in China (R = 0.78) and reproduces the observed increasing trends in two most populated city clusters: North China Plain (NCP) and Yangtze River Delta (YRD). Trend of simulated maximum daily 8-h average (MDA8) O3 concentration is 0.58 ppbv yr−1 in NCP and 1.74 ppbv yr−1 in YRD in JJA 2012–2017. Sensitivity studies show that both changes in anthropogenic emissions and meteorology favored the MDA8 O3 increases in these two regions with respective contributions of 39% and 49% in NCP, and 13% and 84% in YRD. In NCP, the 49% meteorology impact includes a considerable contribution from natural emissions (19%). Changes in biogenic VOCs, soil NOx, and lightning NOx emissions are estimated to enhance MDA8 O3 in NCP with a rate of 0.14, 0.10, and 0.14 ppbv yr−1, respectively. In YRD, natural emissions made small contributions to the MDA8 O3 trend. Statistical analysis shows that higher temperatures and anomalous southerlies at 850 hPa in 2017 relative to 2012 are the two major meteorological drivers in NCP that favored the O3 increases, while weaker wind speed and lower relative humidity are those for YRD. We further examined the trend of fourth highest daily maximum 8-h average (4MDA8) O3 among a specific month that linked with extreme pollution episodes. Trends of simulated 4MDA8 O3 in NCP and YRD are 34–46% higher than those of MDA8 O3 and are found more meteorology-induced. Our results suggest an important role of meteorology in driving summertime O3 increases in China in recent years.

The health impact of changes in particulate matter with an aerodynamic diameter, Graphical abstract Image 1

The height of the atmospheric boundary layer (ABLH) or the mixing layer height (MLH) is a key parameter characterizing the planetary boundary layer, and the accurate estimation of that is critically important for boundary layer related studies, which include air quality forecasts and numerical weather prediction. Aerosol lidar is a powerful remote sensing instrument frequently used to retrieve the ABLH through detecting the vertical distributions of aerosol concentration. Presently available methods for ABLH determination from aerosol lidar are summarized in this review, including a lot of classical methodologies as well as some improved versions of them. Some new recently developed methods applying advanced techniques such as image edge detection, as well as some new methods based on multi-wavelength lidar systems, are also summarized. Although a lot of techniques have been proposed and have already given reasonable results in several studies, it is impossible to recommend a technique which is suitable in all atmospheric scenarios. More accurate instantaneous ABLH from robust techniques is required, which can be used to estimate or improve the boundary layer parameterization in the numerical model, or maybe possible to be assimilated into the weather and environment models to improve the simulation or forecast of weather and air quality in the future.

We applied a global 3-D chemical transport model (GEOS-Chem) to examine the variations in the frequency and intensity in severe winter haze days (SWHDs) in BTH from 1985–2017 and quantified the roles of changes in anthropogenic emissions and/or meteorological parameters. Comparisons between the simulated SWHDs and those obtained from the observed PM2.5 concentrations and atmospheric visibility showed that the model can capture the spatial and temporal variations of SWHDs in China; the correlation coefficient between the simulated and observed SWHDs is 0.98 at 161 grids in China. From 1985–2017, with changes in both anthropogenic emissions and meteorological parameters, the simulated frequency (total severe haze days in winter) and intensity (PM2.5 concentration averaged over severe haze days in winter) of SWHDs in BTH showed increasing trends of 4.5 days decade−1 and 13.7 μg m−3 decade−1, respectively. The simulated frequency exhibited fluctuations from 1985–2017, with a sudden decrease from 1992–2001 (29 days to 10 days) and a rapid growth from 2003–2012 (16 days to 47 days). The sensitivity simulations indicated that variations in meteorological parameters played a dominant role during 1992–2001, while variations in both emissions and meteorological parameters were important for the simulated frequency trend during 2003–2012 (simulated trends were 27.3 days decade−1 and 12.5 days decade−1 owing to changes in emissions alone and changes in meteorology alone, respectively). The simulated intensity showed a steady increase from 1985–2017, which was driven by changes in both emissions and meteorology. The results of this study have important implications for the control of SWHDs in BTH.

Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently used to retrieve ABLH through the detection of the vertical distribution of aerosol concentration. A challenge is that cloud, residual layer (RL), and local signal structure seriously interfere with the lidar measurement of ABLH. A new objective technique presenting as giving a top limiter altitude is introduced to reduce the interference of RL and cloud layer on ABLH determination. Cloud layers are identified by looking for the rapid increase and sharp attenuation of the signal combined with the relative increase in the signal. The cloud layers whether they overlay the ABL are classified or are decoupled from the ABL are classified by analyzing the continuity of the signal below the cloud base. For cloud layer capping of the ABL, the limiter is determined to be the altitude where a positive signal gradient first occurs above the cloud upper edge. For a cloud that is decoupled from the ABL, the cloud base is considered to be the altitude limiter. For RL in the morning, the altitude limiter is the greatest positive gradient altitude below the RL top. The ABLH will be determined below the top limiter altitude using Haar wavelet (HM) and the curve fitting method (CFM). Besides, the interference of local signal noise is eliminated through consideration of the temporal continuity. While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences with respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations, respectively. The diurnal variations in the ABLH determined from HM and CFM on four selected cases show good agreement with a mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km. Also, the determined diurnal ABLH are consistent with surface turbulent kinetic energy (TKE) combined with the time-height distribution of the equivalent potential temperature.

Summertime ozone (O3) concentrations over China continue to increase although the governmental Clear Air Actions have been carried out since 2013. The worst O3 pollution is confronted over North China Plain. Ozone polluted days (with observed regionally-averaged maximum daily 8-h average (MDA8) O3 concentrations exceeding 80 ppbv) in May–July in North China increased from 35 days in year 2014 to 56 days in year 2018, and persistent O3 pollution episodes that lasted for 5 days or longer (OPEs5) contributed 14.3% and 66.1% to those O3 polluted days in 2014 and 2018, respectively. Model simulations suggest that O3 transport from central eastern China (including Shandong, Henan, Jiangsu and Anhui Provinces) contributes 36% of the enhanced O3 concentrations in North China during OPEs5 relative to the seasonal mean. We find that emission control of volatile organic compounds in central eastern China is most effective to alleviate intensity of OPEs5 in North China.

We investigated the spatial-temporal characteristics of the correlations between observed PM2.5 and O3 over China at a national-scale level, and examined the underlying reasons for the varying PM2.5&ndash, O3 correlations by using a chemical transport model. The PM2.5 concentrations were positively correlated with O3 concentrations for most regions and seasons over China, while negative correlations were mainly observed in northern China during winter. The strongest positive PM2.5&ndash, O3 correlations with correlation coefficients (r) larger than +0.7 existed in southern China during July, and the strongest negative correlations (r &lt, &minus, 0.5) were observed in northern China during January. It was a very interesting phenomenon that the positive PM2.5&ndash, O3 correlations prevailed for high air temperature samples, while the negative correlations were generally found in cold environments. Together, the effective inhibitory effect of PM2.5 on O3 generation by reducing photolysis rates and the strong titration effect of freshly emitted NO with O3 contributed to the strongest negative PM2.5&ndash, O3 correlations in northern China during January (i.e., in cold environments). The strongest positive correlations in southern China during July (i.e., at high temperature), however, were mainly attributed to the promoting effect of high O3 concentration and active photochemical activity on secondary particle formation.

Accurate identification of key parameters for data assimilation is important in simulating the planetary boundary layer height (PBLH) and structure evolution in numerical weather prediction models. In this study, surface observational data and lidar-derived PBLH on 42 cloudless days from June 2007 to May 2008 are used to quantify the statistical relationships between surface parameters and the PBLH at a semiarid climate observational site in Northwest China. The results indicate that surface upward long wave radiation, surface temperature, and surface sensible heat fluxes show strong correlations with the PBLH with correlation coefficients at a range of 0.63–0.72. But these parameters show varying correlation response time to the different stages of PBL development. Furthermore, the air temperature shows the highest correlation with the PBLH near the surface and the correlation decreases with increasing height.

Satellite-based retrievals of tropospheric NO(2)columns are widely used to infer NOx (equivalent to NO + NO2) emissions. These retrievals rely on model information for the vertical distribution of NO2. The free tropospheric background above 2 km is particularly important because the sensitivity of the retrievals increases with altitude. Free tropospheric NOx also has a strong effect on tropospheric OH and ozone concentrations. Here we use observations from three aircraft campaigns (SEAC(4)RS, DC3, and ATom) and four atmospheric chemistry models (GEOS-Chem, GMI, TM5, and CAMS) to evaluate the model capabilities for simulating NOx in the free troposphere and attribute it to sources. NO2 measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry (DC3) campaigns over the southeastern U.S. in summer show increasing concentrations in the upper troposphere above 10 km, which are not replicated by the GEOS-Chem, although the model is consistent with the NO measurements. Using concurrent NO, NO2, and ozone observations from a DC3 flight in a thunderstorm outflow, we show that the NO2 measurements in the upper troposphere are biased high, plausibly due to interference from thermally labile NO(2)reservoirs such as peroxynitric acid (HNO4) and methyl peroxy nitrate (MPN). We find that NO2 concentrations calculated from the NO measurements and NO-NO2 photochemical steady state (PSS) are more reliable to evaluate the vertical profiles of NO2 in models. GEOS-Chem reproduces the shape of the PSS-inferred NO2 profiles throughout the troposphere for SEAC(4)RS and DC3 but overestimates NO2 concentrations by about a factor of 2. The model underestimates MPN and alkyl nitrate concentrations, suggesting missing organic NOx chemistry. On the other hand, the standard GEOS-Chem model underestimates NO observations from the Atmospheric Tomography Mission (ATom) campaigns over the Pacific and Atlantic oceans, indicating a missing NOx source over the oceans. We find that we can account for this missing source by including in the model the photolysis of particulate nitrate on sea salt aerosols at rates inferred from laboratory studies and field observations of nitrous acid (HONO) over the Atlantic. The median PSS-inferred tropospheric NO2 column density for the ATom campaign is 1.7 +/- 0.44 x 10(14) molec. cm(-2), and the NO2 column density simulated by the four models is in the range of 1.4-2.4 x 10(14) molec. cm(-2), implying that the uncertainty from using modeled NO2 tropospheric columns over clean areas in the retrievals for stratosphere-troposphere separation is about 1 x 10(14 )molec. cm(-2). We find from GEOS-Chem that lightning is the main primary NOx source in the free troposphere over the tropics and southern midlatitudes, but aircraft emissions dominate at northern midlatitudes in winter and in summer over the oceans. Particulate nitrate photolysis increases ozone concentrations by up to 5 ppbv (parts per billion by volume) in the free troposphere in the northern extratropics in the model, which would largely correct the low model bias relative to ozonesonde observations. Global tropospheric OH concentrations increase by 19 %., The contribution of the free tropospheric background to the tropospheric NO2 columns observed by satellites over the contiguous U.S. increases from 25 +/- 11 % in winter to 65 +/- 9 % in summer, according to the GEOS-Chem vertical profiles. This needs to be accounted for when deriving NOx emissions from satellite NO2 column measurements.