Abstract. Ozone pollution in eastern China has become one of the top environmental issues. Quantifying the temporal trend of surface ozone helps to assess the impacts of the anthropogenic precursor reductions and the likely effects of emission control strategies implemented. In this paper, ozone data collected at the Shangdianzi (SDZ) regional atmospheric background station from 2003 to 2015 are presented and analyzed to obtain the variation in the trend of surface ozone in the most polluted region of China, north of eastern China or the North China Plain. A modified Kolmogorov–Zurbenko (KZ) filter method was performed on the maximum daily average 8 h (MDA8) concentrations of ozone to separate the contributions of different factors from the variation of surface ozone and remove the influence of meteorological fluctuations on surface ozone. Results reveal that the short-term, seasonal and long-term components of ozone account for 36.4, 57.6 and 2.2 % of the total variance, respectively. The long-term trend indicates that the MDA8 has undergone a significant increase in the period of 2003–2015, with an average rate of 1.13 ± 0.01 ppb year−1 (R2 = 0.92). It is found that meteorological factors did not significantly influence the long-term variation of ozone and the increase may be completely attributed to changes in emissions. Furthermore, there is no significant correlation between the long-term O3 and NO2 trends. This study suggests that emission changes in VOCs might have played a more important role in the observed increase of surface ozone at SDZ.
The contributions of meteorology and emissions to air pollutant trends are critical for air quality management, but they have not been fully analyzed, especially in the background area of northern China.
Peroxyacetyl nitrate (PAN) is an important indicator for photochemical pollution, formed similar to ozone in the photochemistry of certain volatile organic compounds (VOCs) in the presence of nitrogen oxides, and has displayed surprisingly high concentrations during wintertime that were better correlated to particulate rather than ozone concentrations, for which the reasons remained unknown. In this study, wintertime observations of PAN, VOCs, PM2.5, HONO, and various trace gases were investigated to find the relationship between aerosols and wintertime PAN formation. Wintertime photochemical pollution was affirmed by the high PAN concentrations (average: 1.2 ± 1.1 ppb, maximum: 7.1 ppb), despite low ozone concentrations. PAN concentrations were determined by its oxygenated VOC (OVOC) precursor concentrations and the NO/NO2 ratios and can be well parameterized based on the understanding of their chemical relationship. Data analysis and box modeling results suggest that PAN formation was mostly contributed by VOC aging processes involving OH oxidation or photolysis rather than ozonolysis pathways. Heterogeneous reactions on aerosols have supplied key photochemical oxidants such as HONO, which produced OH radicals upon photolysis, promoting OVOC formation and thereby enhancing PAN production, explaining the observed PM2.5-OVOC-PAN intercorrelation. In turn, parts of these OVOCs might participate in the formation of secondary organic aerosol, further aggravating haze pollution as a feedback. Low wintertime temperatures enable the long-range transport of PAN to downwind regions, and how that will impact their oxidation capacity and photochemical pollution requires further assessment in future studies.
Ammonia (NH3) is critical to the nitrogen cycle and PM2.5 formation, yet a great deal of uncertainty exists in its urban emission quantifications. Model-underestimated NH3 concentrations have been reported for cities, yet few studies have provided an explanation. Here, we explore reasons for severe WRF-Chem model underestimations of NH3 concentrations in Beijing in August 2018, including simulated gas-particle partitioning, meteorology, regional transport, and emissions, using spatially refined (3 km resolution) NH3 emission estimates in the agricultural sector for Beijing-Tianjin-Hebei and in the traffic sector for Beijing. We find that simulated NH3 concentrations are significantly lower than ground-based and satellite observations during August in Beijing, while wintertime underestimations are much more moderate. Further analyses and sensitivity experiments show that such discrepancies cannot be attributed to factors other than biases in NH3 emissions. Using site measurements as constraints, we estimate that both agricultural and non-agricultural NH3 emission totals in Beijing shall increase by ∼5 times to match the observations. Future research should be performed to allocate underestimations to urban fertilizer, power, traffic, or residential sources. Dense and regular urban NH3 observations are necessary to constrain and validate bottom-up inventories and NHx simulation.
Wutaishan (WTS) Station on Wutai Mountain (2208 m a.s.l.), which is also known as the "North China Roof," in Shanxi Province, is surrounded by lush forest vegetation and situated far (30 km) from industrial emission sources. This study filtered online observation data of the atmospheric CO2 (G2301; Picarro) at WTS Station from March 2017 till February 2018 using both robust extraction of the baseline signal (REBS), and meteorological data (MET) in order to obtain the average background concentration, which is representative of the region (Shanxi Province and the surrounding areas). The background concentration of CO2 averaged (410.9 ± 6.4) × 10–6 (mole ratio, the same below), and the daily variation ranged from 2.4 × 10–6 to 4.8 × 10–6, which is relatively low, across the four seasons. The concentration and the surface wind speed displayed negative correlations during spring and winter, with R being –0.44 and –0.46, respectively. Analyzing the backward trajectories, we concluded that wind from the SE–S–SW sector noticeably increased the local CO2 concentration by transporting from high altitudes (i.e., high air masses) or along the surface.
Abstract. Tropospheric ozone (O3) and peroxyacetyl nitrate (PAN) are both photochemical pollutants harmful to the ecological environment and human health. In this study, measurements of O3 and PAN as well as their precursors were conducted from May to July 2019 at Nam Co station (NMC), a highly pristine high-altitude site in the southern Tibetan Plateau (TP), to investigate how distinct transport processes and photochemistry contributed to their variations. Results revealed that, despite highly similar diurnal variations with steep morning rises and flat daytime plateaus that were caused by boundary layer development and downmixing of free-tropospheric air, day-to-day variations in O3 and PAN were in fact controlled by distinct physicochemical processes. During the dry spring season, air masses rich in O3 were associated with high-altitude westerly air masses that entered the TP from the west or the south, which frequently carried high loadings of stratospheric O3 to NMC. During the summer monsoon season, a northward shift of the subtropical jet stream shifted the stratospheric downward entrainment pathway also to the north, leading to direct stratospheric O3 entrainment into the troposphere of the northern TP, which traveled southwards to NMC within low altitudes via northerly winds in front of ridges or closed high pressures over the TP. Westerly and southerly air masses, however, revealed low O3 levels due to the overall less stratospheric O3 within the troposphere of low-latitude regions. PAN, however, was only rich in westerly or southerly air masses that crossed over polluted regions such as northern India, Nepal or Bangladesh before entering the TP and arriving at NMC from the south during both spring and summer. Overall, the O3 level at NMC was mostly determined by stratosphere–troposphere exchange (STE), which explained 77 % and 88 % of the observed O3 concentration in spring and summer, respectively. However, only 0.1 % of the springtime day-to-day O3 variability could be explained by STE processes, while 22 % was explained during summertime. Positive net photochemical formation was estimated for both O3 and PAN based on observation-constrained box modeling. Near-surface photochemical formation was unable to account for the high O3 level observed at NMC, nor was it the determining factor for the day-to-day variability of O3. However, it was able to capture events with elevated PAN concentrations and explain its day-to-day variations. O3 and PAN formation were both highly sensitive to NOx levels, with PAN being also quite sensitive to volatile organic compound (VOC) concentrations. The rapid development of transportation networks and urbanization within the TP may lead to increased emissions and loadings in NOx and VOCs, resulting in strongly enhanced O3 and PAN formation in downwind pristine regions, which should be given greater attention in future studies.
The volume concentration of peroxyacetyl nitrate (PAN) and O3 in the atmosphere were measured at the Tianjin Meteorological Tower in summer 2017 by using the online instrument with meteorological parameters and back trajectory analysis to analyze the delivery characteristics of PAN and O3. The average volume concentrations of PAN and O3 during the observational period are (0.73±0.56)×10-9 and (53±25)×10-9, respectively. The hourly maximum concentrations of PAN and O3 are 3.49×10-9 and 137×10-9. The volume concentrations of PAN and O3 show pronounced diurnal profiles, which are both characterized by much higher values at daytime than at nighttime. In addition, the correlation coefficient between PAN and O3 at daytime (R2=0.52) is notably higher than that at nighttime (R2=0.21). The air masses originating from the south show the highest volume concentration of PAN and O3, with the lowest volume concentration originating from the east. The wind rose plot and cluster analysis of the back trajectories show that the highest concentration of pollutants mainly originates in the southwest. The air massess originating from the east and circulating through the Bohai Sea and coastal areas of the Hebei and Liaoning provinces show the lowest volume concentrations of PAN and O3. The transportation within the boundary layer plays an important role in the concentration distribution of PAN and O3.
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