scholarly journals Relationship between the Formation of PM2.5 and Meteorological Factors in Northern China: The Periodic Characteristics of Wavelet Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yuanyuan Meng ◽  
Wanlong Sun
Keyword(s):  
Meteorological Factors ◽  
Surface Wind ◽  
Northern China ◽  
Surface Wind Speed ◽  
Photochemical Reactions ◽  
Pollutant Emissions ◽  
Near Surface ◽  
Multiple Cycles ◽  
Haze Formation ◽  
The Government

China’s rapid urbanisation and industrialisation have led to frequent haze in China in recent years. Although many measures to control haze have been implemented, no significant improvement has been observed, and haze still exists. In this study, we used wavelet transform to investigate the changes in PM2.5 on the time scale, the relationship amongst meteorological factors, and the causes and changes in haze formation and take measures to prevent haze. Results indicated the following: (1) The peak of PM2.5 changes in winter in the past three years primarily occurred in the range from 11:00 to 13:00 and 20:00 to 22:00. (2) Multiple cycles of daily average PM2.5 concentrations existed in 3–5 d, 6–14 d, 6–21 d, and 16–27 d, with a significant oscillation in 6–14 d and stable cycle characteristics. (3) The meteorological factors promoted the formation of haze to a certain extent. When haze occurred, the near-surface wind speed was only 1 m/s, which was not conducive to the spread of pollutants. (4) The formation of haze was affected by the interaction of various factors; the photochemical reactions of NO2 and O3 also exacerbated the formation of pollutants. This study provided a clear direction for the prevention and prediction of haze. Furthermore, the government must take relevant measures to reduce pollutant emissions and ensure the air quality of cities in winter.

scholarly journals A Reliability Assessment of the NCEP/FNL Reanalysis Data in Depicting Key Meteorological Factors on Clean Days and Polluted Days in Beijing

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 481
Author(s):  
Chao Liu ◽  
Jianping Guo ◽  
Bihui Zhang ◽  
Hengde Zhang ◽  
Panbo Guan ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Meteorological Factors ◽  
Surface Wind ◽  
Lower Boundary ◽  
Temperature Inversion ◽  
Surface Wind Speed ◽  
Reanalysis Data ◽  
Near Surface ◽  
The Difference

In this study, based on the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data, the reliability and performances of their application on clean days and polluted days (based on the PM2.5 mass concentrations) in Beijing were assessed. Conventional meteorological factors and diagnostic physical quantities from the NCEP/FNL data were compared with the L-band radar observations in Beijing in the autumns and winters of 2017–2019. The results indicate that the prediction reliability of the temperature was the best compared with those of the relative humidity and wind speed. It is worth noting that the relative humidity was lower and the near-surface wind speed was higher on polluted days from the NCEP/FNL data than from the observations. As far as diagnostic physical quantity is concerned, it was revealed that the temperature inversion intensity depicted by the NCEP/FNL data was significantly lower than that from the observations, especially on polluted days. For example, the difference in the temperature inversion intensity between the NCEP/FNL data and the observation ranged from −0.56 to −0.77 °C on polluted days. In addition, the difference in the wind shears between the NCEP/FNL reanalysis data and the observations increased to 0.40 m/s in the lower boundary layer on polluted days compared with that on clean days. Therefore, it is suggested that the underestimation of the relative humidity and temperature inversion intensity, and the overestimation of the near-surface wind speed should be seriously considered in simulating the air quality in the model, particularly on polluted days, which should be focused on more in future model developments.

scholarly journals Changes in Haze Trends in the Sichuan-Chongqing Region, China, 1980 to 2016

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 277 ◽  
Author(s):  
Hongke Cai ◽  
Ke Gui ◽  
Quanliang Chen
Keyword(s):  
Meteorological Factors ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Joint Effect ◽  
Near Surface ◽  
Annual Variations ◽  
Boundary Layer Height ◽  
Haze Pollution ◽  
Increasing Trend

This study analyzed the long-term variations and trends of haze pollution and its relationships with emission and meteorological factors using the haze days (HDs) data derived from surface observation stations in Sichuan-Chongqing (SCC) region during 1980–2016. The results showed that the multi-year mean number of HDs were 68.7 and 4.9 days for the Sichuan-Basin (SCB) and the rest of SCC region, respectively. The seasonally averaged HDs over SCB reached its maximum in winter (34.7 days), followed by autumn (17.0 days) and spring (11.6 days), and with the minimum observed in summer (5.5 days). The inter-annual variations of HDs in 18 main cities revealed that Zigong, Neijiang, and Yibin, which are located in the southern of SCB, have been the most polluted areas over the SCC region in the past decades. A notable increasing trend in annual HDs over the majority of SCC region was found during 1980–1995, then the trend sharply reversed during 1996–2005, while it increased, fluctuating at some cities after 2006. Seasonally, the increased trend in spring and autumn seems to be the strongest during 1980–1995, whereas the decreased trend in spring and winter was stronger than other seasons during 1996–2005. In addition, a remarkable increasing trend was found in winter since 2006. Using correlation analysis between HDs and emission and meteorological factors during different periods, we found that the variability of local precipitation days (PDs), planetary boundary layer height (PBLH), near-surface wind speed (WS), and relatively humidity (RH) play different roles in influencing the haze pollution change during different historical periods. The joint effect of sharp increase of anthropogenic emissions, reduced PDs and WS intensified the haze pollution in SCB during 1980–1995. In contrast, decreased HDs during 1996–2005 are mainly attributable to the reduction of PM2.5 emission and the increase of PDs (especially in winter). In addition, the decrease of PDs is likely to be responsible for the unexpected increase in winter HDs over SCB in the last decade.

scholarly journals Impact of near-surface wind speed variability on wind erosion in the eastern agro-pastoral transitional zone of Northern China, 1982–2016

2019 ◽  
Vol 271 ◽  
pp. 102-115 ◽  
Author(s):  
Gangfeng Zhang ◽  
Cesar Azorin-Molina ◽  
Peijun Shi ◽  
Degen Lin ◽  
Jose A. Guijarro ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Erosion ◽  
Surface Wind ◽  
Northern China ◽  
Surface Wind Speed ◽  
Transitional Zone ◽  
Near Surface

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

A preliminary study on the influence of Beijing urban spatial morphology on near-surface wind speed

Urban Climate ◽  
2020 ◽  
Vol 34 ◽  
pp. 100703
Author(s):  
Yonghong Liu ◽  
Yongming Xu ◽  
Fangmin Zhang ◽  
Wenjun Shu
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Spatial Morphology ◽  
Preliminary Study

scholarly journals Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 738 ◽  
Author(s):  
Wenqing Xu ◽  
Like Ning ◽  
Yong Luo
Keyword(s):  
Wind Speed ◽  
Decision Tree ◽  
Wind Power ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Gradient Boosting ◽  
Post Processing ◽  
Near Surface ◽  
Wind Power Forecasting ◽  
Numerical Weather

With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.

scholarly journals Uncertainty in recent near-surface wind speed trends: a global reanalysis intercomparison

2017 ◽  
Vol 12 (11) ◽  
pp. 114019 ◽  
Author(s):  
Verónica Torralba ◽  
Francisco J Doblas-Reyes ◽  
Nube Gonzalez-Reviriego
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Global Reanalysis ◽  
Reanalysis Intercomparison

Comparing Polar Lows in Atmospheric Reanalyses: Arctic System Reanalysis versus ERA-Interim

2017 ◽  
Vol 145 (6) ◽  
pp. 2375-2383 ◽  
Author(s):  
Julia Smirnova ◽  
Pavel Golubkin
Keyword(s):  
Strong Dependence ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Static Stability ◽  
Relative Vorticity ◽  
Reference List ◽  
Near Surface ◽  
Polar Lows ◽  
Polar Low ◽  
Definition Of

Abstract Representation of polar lows in the new high-resolution Arctic System Reanalysis (ASR) was for the first time assessed and compared to that in the ERA-Interim. Substantial improvements were found in the 850-hPa relative vorticity and near-surface wind speed information. The latter was found to be in close agreement with satellite-derived estimates. Representation of polar lows from a widely used selective list in ERA-Interim and ASR was estimated as 48% and 89%, respectively. The proportion of polar lows represented in ASR is substantially higher than reported for other reanalyses in previous studies. Verifications were found to be sensitive to the polar low reference list used, and to the definition of a polar low. As found, when a more complete polar low list from a recent satellite-derived climatology was used, the proportion of represented events decreased to 26% and 66% for ERA-Interim and ASR, respectively. Variations in polar low representation in reanalyses were also observed in different regions, with the highest proportion resolved in the Norwegian Sea. Strong dependence between polar low sizes and their representation in ERA-Interim was found. In the case of ASR, polar low representation remains constant in the size range of 200–500 km and slightly decreases only for the smallest systems with diameters less than 200 km. Usage of the strict threshold of 43 K for the atmospheric static stability criterion was found to exclude a considerable number of otherwise well-represented polar lows.

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