scholarly journals Spatial-Temporal Variation of Air PM2.5 and PM10 within Different Types of Vegetation during Winter in an Urban Riparian Zone of Shanghai

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1428
Author(s):  
Jing Wang ◽  
Changkun Xie ◽  
Anze Liang ◽  
Ruiyuan Jiang ◽  
Zihao Man ◽  
...  

Particulate matter (PM) in urban riparian green spaces are undesirable for human participation in outdoor activities, especially PM2.5 and PM10. The PM deposition, dispersion and modification are influenced by various factors including vegetation, water bodies and meteorological conditions. This study aimed to investigate the impact of vegetation structures and the river’s presence on PM in riparian zones. The spatial-temporal variations of PM2.5 and PM10 concentrations in three riparian vegetation communities with different structures (open grassland (G), arbor-grass (AG) and arbor-shrub-grass (ASG) woodlands) were monitored under relatively stable environment. The removal percentages (RP) and ratios of PM2.5 and PM10 were calculated and compared to identify the removal effect of vegetation structures and the river’s presence. It is found that: (1) when the wind was static (hourly wind speed < 0.2 m/s), the RP was ranked as follows: G > AG > ASG. When the wind was mild (0.2 m/s < hourly wind speed < 2 m/s), the RP was ranked as follows: G > ASG > AG. Generally, the G had the best removal effect during the monitoring period; (2) the lowest RP occurred in the middle of the G (–3.4% for PM2.5, 1.8% for PM10) while the highest RP were found in middle of the AG and ASG, respectively (AG: 2.1% for PM2.5, 6.7% for PM10; ASG: 2.4% for PM2.5, 6.3% for PM10). Vegetation cover changed the way of natural deposition and dispersion; (3) compared with static periods, PM removal percentages were significantly reduced under mild wind conditions, and they were positively correlated with wind speed during the mild-wind period. Thus, a piecewise function was inferred between wind speed and PM removal percentage; (4) for all three communities, the 1 m-to-river PM2.5/PM10 ratio was significantly lower than that at 6 m and 11 m, even lower than that in the ambient atmosphere. The river likely promoted the hygroscopic growth of PM2.5 and the generation of larger-sized particles by coagulation effect. Based on these findings, open grassland space is preferred alongside rivers and space for outdoor activities is suggested under canopies in the middle of woodlands.

Author(s):  
S. Harbola ◽  
V. Coors

Abstract. Human and ecosystem health is affected by the risk of air pollution. A comprehensive understanding of the parameters generating pollution and governing their nature in time is essential to devise functional policies focusing on minimising the concentration of the pollutants. The effect of pollution parameters on meteorological data and existing in between relationships, have been the focus of the researcher’s planning of better city future. Thorough study of resources utilisation is required for contributing to framing effective, sustainable development, government policies management, and advance public services convenience. For protecting the environmental quality, renewable resources like solar and wind are more incorporated in techniques supporting better city planning. This paper considers the hourly time series Particular Matter (PM) PM2.5 and PM10, Nitrogen Oxide (NO), and Nitrogen Dioxide (NO2), and Ozone (O3) along with measured wind flow and humidity. This study’s objective is to assess the temporal seasonality patterns of these parameters in Stuttgart, Germany. The temporal variations over the city center in Stuttgart are analysed using unsupervised approach to perform seasonal hierarchical clustering on a series of parameters NO, NO2, O3, PM10, and PM2.5, wind speed and humidity. Furthermore, the correlations between meteorological and pollution parameters are analysed using the Spearman rank correlation method. Moreover, a dashboard is developed to provide the user desired time frame visualisation of these parameters. Proposed work would provide empirical meaning and seasonality comparison among the above mentioned parameters combined with interactive dashboard support. The analyses of the presented results clearly demonstrates the relationship between air pollutants, wind, humidity together in combine temporal activities frame. Thus, it would help city planner and policies maker with advanced knowledge of seasonality for meteorological and pollution parameters conditions.


Author(s):  
Oskar Wiśniewski ◽  
Wiesław Kozak ◽  
Maciej Wiśniewski

AbstractCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work, we analyze the impact of weather factors such as temperature, relative humidity, wind speed, and ground-level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground-level ozone concentration and the daily number of COVID-19 cases.


2021 ◽  
Vol 13 (14) ◽  
pp. 7637
Author(s):  
Taekyoung Lee ◽  
Jieun Cha ◽  
Sohyun Sung

Trees’ ability to capture atmospheric Particular Matter (PM) is related to morphological traits (shape, size, and micro-morphology) of the leaves. The objectives of this study were (1) to find out whether cluster pattern of the leaves is also a parameter that affects trees’ PM capturing performance and (2) to apply the cluster patterns of the leaves on architectural surfaces to confirm its impact on PM capturing performance. Two series of chamber experiments were designed to observe the impact of cluster patterns on PM capturing performance whilst other influential variables were controlled. First, we exposed synthetic leaf structures of different cluster patterns (a large and sparsely arranged cluster pattern and a small and densely arranged cluster pattern) to artificially generated PM in a chamber for 60 min and recorded the changing levels of PM2.5 and PM10 every minute. The results confirmed that the small and densely arranged cluster pattern has more significant effect on reducing PM2.5 and PM10 than the large and sparsely arranged cluster pattern. Secondly, we created three different types of architectural surfaces mimicking the cluster patterns of the leaves: a base surface, a folded surface, and a folded and porous surface. The surfaces were also exposed to artificially generated PM in the chamber and the levels of PM2.5 and PM10 were recorded. The results confirmed that the folded and porous surface has a more significant effect on reducing PM2.5 and PM10 than other surfaces. The study has confirmed that the PM capturing performance of architectural surfaces can be improved by mimicking cluster pattern of the leaves.


2021 ◽  
Vol 13 (15) ◽  
pp. 3014
Author(s):  
Feng Wang ◽  
Dongkai Yang ◽  
Guodong Zhang ◽  
Jin Xing ◽  
Bo Zhang ◽  
...  

Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.


Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 793
Author(s):  
Abdul Razzaq Ghumman ◽  
Mohammed Jamaan ◽  
Afaq Ahmad ◽  
Md. Shafiquzzaman ◽  
Husnain Haider ◽  
...  

The evaporation losses are very high in warm-arid regions and their accurate evaluation is vital for the sustainable management of water resources. The assessment of such losses involves extremely difficult and original tasks because of the scarcity of data in countries with an arid climate. The main objective of this paper is to develop models for the simulation of pan-evaporation with the help of Penman and Hamon’s equations, Artificial Neural Networks (ANNs), and the Artificial Neuro Fuzzy Inference System (ANFIS). The results from five types of ANN models with different training functions were compared to find the best possible training function. The impact of using various input variables was investigated as an original contribution of this research. The average temperature and mean wind speed were found to be the most influential parameters. The estimation of parameters for Penman and Hamon’s equations was quite a daunting task. These parameters were estimated using a state of the art optimization algorithm, namely General Reduced Gradient Technique. The results of the Penman and Hamon’s equations, ANN, and ANFIS were compared. Thirty-eight years (from 1980 to 2018) of manually recorded pan-evaporation data regarding mean daily values of a month, including the relative humidity, wind speed, sunshine duration, and temperature, were collected from three gauging stations situated in Al Qassim, Saudi Arabia. The Nash and Sutcliffe Efficiency (NSE) and Mean Square Error (MSE) evaluated the performance of pan-evaporation modeling techniques. The study shows that the ANFIS simulation results were better than those of ANN and Penman and Hamon’s equations. The findings of the present research will help managers, engineers, and decision makers to sustainability manage natural water resources in warm-arid regions.


2021 ◽  
Vol 13 (10) ◽  
pp. 5688
Author(s):  
Jangyoul You ◽  
Kipyo You ◽  
Minwoo Park ◽  
Changhee Lee

In this paper, the air flow characteristics and the impact of wind power generators were analyzed according to the porosity and height of the parapet installed in the rooftop layer. The wind speed at the top was decreasing as the parapet was installed. However, the wind speed reduction effect was decreasing as the porosity rate increased. In addition, the increase in porosity significantly reduced turbulence intensity and reduced it by up to 40% compared to no railing. In the case of parapets with sufficient porosity, the effect of reducing turbulence intensity was also increased as the height increased. Therefore, it was confirmed that sufficient parapet height and high porosity reduce the effect of reducing wind speed by parapets and significantly reducing the turbulence intensity, which can provide homogeneous wind speed during installation of wind power generators.


Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 843
Author(s):  
Jiaqi Tian ◽  
Chunsheng Fang ◽  
Jiaxin Qiu ◽  
Ju Wang

The increase in tropospheric ozone (O3) concentration has become one of the factors restricting urban development. This paper selected the important economic cooperation areas in Northeast China as the research object and collected the hourly monitoring data of pollutants and meteorological data in 11 cities from 1 January 2015 to 31 December 2019. The temporal and spatial variation trend of O3 concentration and the effects of meteorological factors and other pollutants, including CO (carbon monoxide), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and PM2.5 and PM10 (PM particles with aerodynamic diameters less than 2.5 μm and 10 μm) on ozone concentration were analyzed. At the same time, the variation period of O3 concentration was further analyzed by Morlet wavelet analysis. The results showed that the O3 pollution in the study area had a significant spatial correlation. The spatial distribution showed that the O3 concentration was relatively high in the south and low in the northeast. Seasonally, the O3 concentration was the highest in spring, followed by summer, and the lowest in winter. The diurnal variation of O3 concentration presented a “single peak” pattern. O3 concentration had a significant positive correlation with temperature, sunshine duration, and wind speed and a significant anticorrelation with CO, NO2, SO2, and PM2.5 concentration. Under the time scale of a = 9, 23, O3 had significant periodic fluctuation, which was similar to those of wind speed and temperature.


2021 ◽  
Vol 9 (3) ◽  
pp. 246
Author(s):  
Difu Sun ◽  
Junqiang Song ◽  
Xiaoyong Li ◽  
Kaijun Ren ◽  
Hongze Leng

A wave state related sea surface roughness parameterization scheme that takes into account the impact of sea foam is proposed in this study. Using eight observational datasets, the performances of two most widely used wave state related parameterizations are examined under various wave conditions. Based on the different performances of two wave state related parameterizations under different wave state, and by introducing the effect of sea foam, a new sea surface roughness parameterization suitable for low to extreme wind conditions is proposed. The behaviors of drag coefficient predicted by the proposed parameterization match the field and laboratory measurements well. It is shown that the drag coefficient increases with the increasing wind speed under low and moderate wind speed conditions, and then decreases with increasing wind speed, due to the effect of sea foam under high wind speed conditions. The maximum values of the drag coefficient are reached when the 10 m wind speeds are in the range of 30–35 m/s.


2017 ◽  
Vol 130 (3) ◽  
pp. 311-324 ◽  
Author(s):  
Junkai Liu ◽  
Zhiqiu Gao ◽  
Linlin Wang ◽  
Yubin Li ◽  
Chloe Y. Gao

2015 ◽  
Vol 15 (23) ◽  
pp. 13633-13646 ◽  
Author(s):  
B. L. Zhuang ◽  
T. J. Wang ◽  
J. Liu ◽  
Y. Ma ◽  
C. Q. Yin ◽  
...  

Abstract. Absorbing aerosols can significantly modulate short-wave solar radiation in the atmosphere, affecting regional and global climate. The aerosol absorption coefficient (AAC) is an indicator that assesses the impact of absorbing aerosols on radiative forcing. In this study, the near-surface AAC and absorption Ångström exponent (AAE) in the urban area of Nanjing, China, are characterized on the basis of measurements in 2012 and 2013 using the seven-channel Aethalometer (model AE-31, Magee Scientific, USA). The AAC is estimated with direct and indirect corrections, which result in consistent temporal variations and magnitudes of AAC at 532 nm. The mean AAC at 532 nm is about 43.23 ± 28.13 M m−1 in the urban area of Nanjing, which is much lower than that in Pearl River Delta and the same as in rural areas (Lin'an) in Yangtze River Delta. The AAC in the urban area of Nanjing shows strong seasonality (diurnal variations); it is high in cold seasons (at rush hour) and low in summer (in the afternoon). It also shows synoptic and quasi-2-week cycles in response to weather systems. Its frequency distribution follows a typical log-normal pattern. The 532 nm AAC ranging from 15 to 65 M m−1 dominates, accounting for more than 72 % of the total data samples in the entire study period. Frequent high pollution episodes, such as those observed in June 2012 and in winter 2013, greatly enhanced AAC and altered its temporal variations and frequency distributions. These episodes are mostly due to local emissions and regional pollution. Air masses flowing from northern China to Nanjing can sometimes be highly polluted and lead to high AAC at the site. AAE at 660/470 nm from the Schmid correction (Schmid et al., 2006) is about 1.56, which might be more reasonable than from the Weingartner correction (Weingartner et al., 2003). Low AAEs mainly occur in summer, likely due to high relative humidity (RH) in the season. AAC increases with increasing AAE at a fixed aerosol loading. The RH–AAC relationship is more complex. Overall, AAC peaks at RH values of around 40 % (1.3 < AAE < 1.6), 65 % (AAE < 1.3 and AAE > 1.6), and 80 % (1.3 < AAE < 1.6).


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