Abstract PM2.5 plays a key role in the solar radiation budget and air quality assessments, but observations and historical data are relatively rare for Beijing. Based on the synchronous monitoring of PM2.5 and broadband solar radiation ( R s ), a logarithmic function was developed to describe the quantitative relationship between these parameters. This empirical parameterization was employed to calculate R sn from PM2.5 with normalized mean bias (NMB) −0.09 and calculate PM2.5 concentration from R sn with NMB −0.12. Our results indicate that this parameterization provides an efficient and straightforward method for estimating PM2.5 from R s or R s from PM2.5.
Abstract. Using the daily records derived from the synoptic weather stations and the NCEP/NCAR and ERA-Interim reanalysis data, the variability of the winter haze pollution (indicated by the mean visibility and number of hazy days) in the Beijing–Tianjin–Hebei (BTH) region during the period 1981 to 2015 and its relationship with the atmospheric circulations at middle–high latitude were analyzed in this study. The winter haze pollution in BTH had distinct inter-annual and inter-decadal variabilities without a significant long-term trend. According to the spatial distribution of correlation coefficients, six atmospheric circulation indices (I1 to I6) were defined from the key areas in sea level pressure (SLP), zonal and meridional winds at 850 hPa (U850, V850), geopotential height field at 500 hPa (H500), zonal wind at 200 hPa (U200), and air temperature at 200 hPa (T200), respectively. All of the six indices have significant and stable correlations with the winter visibility and number of hazy days in BTH. In the raw (unfiltered) correlations, the correlation coefficients between the six indices and the winter visibility (number of hazy days) varied from 0.57 (0.47) to 0.76 (0.6) with an average of 0.65 (0.54); in the high-frequency ( < 10 years) correlations, the coefficients varied from 0.62 (0.58) to 0.8 (0.69) with an average of 0.69 (0.64). The six circulation indices together can explain 77.7 % (78.7 %) and 61.7 % (69.1 %) variances of the winter visibility and the number of hazy days in the year-to-year (inter-annual) variability, respectively. The increase in Ic (a comprehensive index derived from the six individual circulation indices) can cause a shallowing of the East Asian trough at the middle troposphere and a weakening of the Siberian high-pressure field at sea level, and is then accompanied by a reduction (increase) of horizontal advection and vertical convection (relative humidity) in the lowest troposphere and a reduced boundary layer height in BTH and its neighboring areas, which are favorable for the formation of haze pollution in BTH winter, and vice versa. The high level of the prediction statistics and the reasonable mechanism suggested that the winter haze pollution in BTH can be forecasted or estimated credibly based on the optimized atmospheric circulation indices. Thus it is helpful for government decision-making departments to take action in advance in dealing with probably severe haze pollution in BTH indicated by the atmospheric circulation conditions.
Abstract. The mitigation of air pollution in megacities remains a great challenge because of the complex sources and formation mechanisms of aerosol particles. The 2014 Asia- Pacific Economic Cooperation (APEC) summit in Beijing serves as a unique experiment to study the impacts of emission controls on aerosol composition, size distributions, and oxidative properties. Herein, a high-resolution time-of-flight aerosol mass spectrometer was deployed in urban Beijing for real-time measurements of size-resolved non-refractory submicron aerosol (NR-PM1) species from 14 October to 12 November 2014, along with a range of collocated measurements. The average (±σ) PM1 was 41.6 (±38.9) μg m−3 during APEC, which was decreased by 53 % compared with that before APEC. The aerosol composition showed substantial changes owing to emission controls during APEC. Secondary inorganic aerosols (SIA = sulfate + nitrate + ammonium) showed significant reductions of 62–69 %, whereas organics presented much smaller decreases (35 %). The results from the positive matrix factorization of organic aerosols (OA) indicated that highly oxidized secondary OA (SOA) showed decreases similar to those of SIA during APEC. However, primary OA (POA) from cooking, traffic, and biomass burning sources were comparable to those before APEC, indicating the presence of strong local source emissions. The oxidation properties showed corresponding changes in response to OA composition. The average oxygen-to-carbon level during APEC was 0.36 (±0.10), which is lower than the 0.43 (±0.13) measured before APEC, demonstrating a decrease in the OA oxidation degree. The changes in size distributions of primary and secondary species varied during APEC. SIA and SOA showed significant reductions in large accumulation modes with peak diameters shifting from ~ 650 to 400 nm during APEC, whereas those of POA remained relatively unchanged. The changes in aerosol composition, size distributions, and oxidation degrees during the aging processes were further illustrated in a case study of a severe haze episode. Our results elucidated a complex response of aerosol chemistry to emission controls, which has significant implications that emission controls over regional scales can substantially reduce secondary particulates. However, stricter emission controls for local source emissions are needed for further mitigating air pollution in the megacity of Beijing.
Abstract Atmospheric chemistry transport models have been extensively applied in aerosol forecasts over recent decades, whereas they are facing challenges from uncertainties in emission rates, meteorological data, and over-simplified chemical parameterizations. Here, we developed a spatial-temporal deep learning framework, named PPN (Pollution-Predicting Net for PM 2.5 ), to accurately and efficiently predict regional PM 2.5 concentrations. It has an encoder-decoder architecture and combines the preceding PM 2.5 observations and numerical weather prediction. Besides, the model proposes a weighted loss function to promote the forecasting performance in extreme events. We applied the proposed model to forecast 3-day PM 2.5 concentrations over the Beijing-Tianjin-Hebei region in China on a three-hour-by-three-hour basis. Overall, the model showed good performance with R 2 and RMSE values of 0.7 and 17.7 μg m −3 , respectively. It could capture the high PM 2.5 concentration in the south and relatively low concentration in the north and exhibit better performance within the next 24 h. The use of the weighted loss function decreased the level of “high values underestimation, low values overestimation”, while incorporating the preceding PM 2.5 observations into the encoder phase improved the predictive accuracy within 24 h. We also compared the model result with that from a state-of-the-art numerical model (WRF-Chem with pollutant data assimilation). The temporal R 2 and RMSE from the WRF-Chem were 0.30−0.77 and 19−45 μg m −3 while those from the PPN model were 0.42−0.84 and 15−42 μg m −3 . The proposed model shows powerful capacity in aerosol forecasts and provides an efficient and accurate tool for early warning and management of regional pollution events.
This study investigates the vertical thermal and dynamic structure of the atmosphere on synoptic and local scales from a three-dimensional perspective and its contribution to haze formation in Beijing during autumn. On a synoptic scale, the occurrence of heavy haze corresponds either to significant horizontal pollutant transport by southerly winds or to strong atmospheric vertical stability with downward air motion at altitudes below ~1500–3000 m; hence, meteorological parameters measured below ~1500 m serve as better indicators of pollutant transport and dispersion than surface observations. When accompanied by increased southerly winds, the upward air motion between the ground and altitudes above ~1500 m can transport pollutants from surrounding areas to Beijing, resulting in a rapid increase in PM2.5 (within several hours) despite weak winds on the surface, which confirms the possibility of regional transport during stagnant surface conditions and its potential role in haze formation. Additionally, the mountain-plain breeze in the Beijing-Tianjin-Hebei (BTH) region during autumn drives strong local wind circulation, influencing the cumulative stage of haze episodes in this season. During the daytime, this breeze pushes pollutants to areas along the mountains and then to Beijing, resulting in a day-by-day increase in pollution. (By contrast, winter haze episodes arise from the accumulation of local pollution under stable meteorological conditions.) The combination of easterly winds and local topography can induce the formation and dissipation of haze, with the orographic effect propelling the haze into higher layers that host the transport of PM2.5 to the southeast. Afterward, southerly winds carry this pollution plume back along the mountain front, where it merges with surface pollutants through vertical mixing, finally this mixed plume arrived Beijing and contributes to the development of the next haze episode.
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