scholarly journals Modeling analysis of the seasonal characteristics of haze formation in Beijing

2014 ◽  
Vol 14 (18) ◽  
pp. 10231-10248 ◽  
Author(s):  
X. Han ◽  
M. Zhang ◽  
J. Gao ◽  
S. Wang ◽  
F. Chai
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Formation Mechanism ◽  
Mass Concentration ◽  
Atmospheric Modeling ◽  
Aerosol Optical Property ◽  
The North ◽  
Seasonal Characteristics ◽  
Different Seasons ◽  
Haze Formation

Abstract. The air quality modeling system RAMS-CMAQ (Regional Atmospheric Modeling System–Community Multiscale Air Quality), coupled with an aerosol optical property scheme, was applied to simulate the meteorological field, major aerosol components (sulfate, nitrate, ammonium, black carbon, organic carbon, dust, and sea salt), and surface visibility over the North China Plain (NCP) in 2011. The modeled results in February and July 2011 were selected and analyzed to obtain an in-depth understanding of the haze formation mechanism in Beijing for different seasons. The simulation results showed that the visibility was below 10 km for most regions of the NCP, and dropped to less than 5 km over the megacities of Beijing and Tianjin, the whole of Hebei Province, and the northwest part of Shandong Province during pollution episodes in February and July. The heavy mass concentration of PM2.5 ranged from 120 to 300 μg m−3 and was concentrated in the areas with low visibility. The haze formation mechanism in Beijing in winter was different from that in summer. The mass concentration of PM2.5 was higher, and the components more complicated, in winter. While the mass concentration of PM2.5 in summer was lower than that in winter, the mass concentrations of hygroscopic inorganic salts were comparable with those in winter, and the relative humidity was, as expected, higher. Therefore, the water uptake of hygroscopic aerosols played a key role in summer. Moreover, the analysis showed that the influence of the PM2.5 mass burden on visibility was very weak when its value was larger than 100 μg m−3. Only when the mass burden of PM2.5 decreased to a certain threshold interval did the visibility increase rapidly. This indicates that, when emission reduction measures are taken to control haze occurrence, the mass burden of PM2.5 must be cut to below this threshold interval. The relationship between the threshold of haze occurrence and the relative humidity in Beijing was fitted by an exponential function, and the resulting fitting curves could provide a new theoretical basis to understand and control haze formation in Beijing.

scholarly journals Modeling analysis of the seasonal characteristics of haze formation in Beijing

2013 ◽  
Vol 13 (11) ◽  
pp. 30575-30610 ◽  
Author(s):  
X. Han ◽  
M. Zhang ◽  
J. Gao ◽  
S. Wang ◽  
F. Chai
Keyword(s):  
Relative Humidity ◽  
Urban Areas ◽  
Mass Concentration ◽  
Aerosol Size Distribution ◽  
Observation Data ◽  
Aerosol Optical Property ◽  
The North ◽  
Seasonal Characteristics ◽  
Simulation Results ◽  
Haze Formation

Abstract. The air quality modeling system RAMS-CMAQ coupled with an aerosol optical property scheme was applied to simulate the meteorological field, major aerosol components (sulfate, nitrate, ammonium, black carbon, organic carbon, dust, and sea salt), and surface visibility over the North China Plain (NCP) in 2011. The modeled results in February and July 2011 were selected and analyzed to obtain an in-depth understanding of the haze formation mechanism in Beijing in different seasons. The evaluations suggested that the modeling system provided reliable simulation results of meteorological factors (temperature, relative humidity, and wind field), visibility, mass concentrations of gaseous pollutants (NO2 and O3), and major aerosol components in PM2.5 by compared with various observation data at several measurement stations over NCP. The simulation results showed that the visibility below 10 km covered most regions of NCP and dropped below 5 km over the urban areas of Beijing, Tianjin, and Shijiazhuang during the pollution episodes in February and July. The heavy particulate pollutants were concentrated in the same areas as well. The heavy loading of PM2.5 which could reach 300 μg m−3 in Beijing should be the main reason of haze occurrence in February, and the visibility generally decreased to 3–5 km when the mass concentration of PM2.5 exceeded 200 μg m−3. However, similar values of visibility also appeared in July when the mass concentration of PM2.5 was merely in the range of 120 μg m−3 to 200 μg m−3. Analysis presented that nitrate, sulfate, and ammonium were the three major aerosol components in Beijing and their total mass burden was even higher in July than that in February. Thus, the significantly higher relative humidity and larger mass proportion of soluble aerosol components resulted in more haze days in July. Sensitivity test shows that the mass concentration threshold of PM2.5 to cause haze occurrence was about 80 μg m−3 when the relative humidity was 70% in Beijing. The change of aerosol size distribution can significantly influence the threshold of haze occurrence in Beijing, particularly for particles of smaller size.

Seasonal effect of humidity on human comfort in a hot summer/cold winter zone in China

2018 ◽  
Vol 28 (2) ◽  
pp. 264-277 ◽  
Author(s):  
Chao Li ◽  
Hong Liu ◽  
Baizhan Li ◽  
Aihong Sheng
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Effect Of Temperature ◽  
Seasonal Effect ◽  
Thermal Perception ◽  
Cold Winter ◽  
Humidity Ratio ◽  
Subjective Responses ◽  
C 23 ◽  
Different Seasons

Adaptation to different seasonal climates may affect human subjective responses to humidity. In this study, thermal comfort, humidity comfort and perceived air quality were investigated with subjects exposed in a climate chamber during spring, summer and winter. Sixty subjects were recruited in total, divided into groups of 20 subjects for each season. Temperature was set at three levels (cool, moderate and warm) during experiments in ranges of 20–28°C, 23–32°C, 16–28°C for spring, summer and winter, respectively. Likewise, relative humidity was set at three levels: 15% (low), 50% (moderate) and 85% (high). Results showed that seasonal difference had a significant effect on human subjective responses to humidity. The combined effect of temperature and relative humidity on thermal perception, humidity perception and perceived air quality was closely related to standard effective temperature (SET*), humidity ratio and air enthalpy, respectively. Comfort humidity ranges were 7.9–15.1 g/kg, 3.3–18.8 g/kg and 2.9–12.8 g/kg (humidity ratio) in spring, summer and winter, respectively. Overall, our results indicate that different comfort humidity limits should be considered for different seasons in the hot summer/cold winter zones of China.

scholarly journals Numerical analysis of the impact of agricultural emissions on PM<sub>2.5</sub> in China using a high-resolution ammonia emissions inventory

2020 ◽  
Author(s):  
Xiao Han ◽  
Lingyun Zhu ◽  
Mingxu Liu ◽  
Yu Song ◽  
Meigen Zhang
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Source Apportionment ◽  
Mass Concentration ◽  
Atmospheric Modeling ◽  
Central China ◽  
High Mass ◽  
Emissions Inventory ◽  
Aerosol Mass Concentration ◽  
The Impact

Abstract. China is one of the largest agricultural countries in the world. The NH3 emissions from agricultural activities in China significantly affect regional air quality and horizontal visibility. To reliably estimate the influence of NH3 on agriculture, a high-resolution agricultural NH3 emissions inventory, compiled with a 1 km × 1 km horizontal resolution, was applied to calculate the NH3 mass burden in China. The key emission factors of this inventory were enhanced by considering the results of many native experiments, and the activity data of spatial and temporal information were updated using statistical data from 2015. Fertilizer and husbandry, as well as farmland ecosystems, livestock waste, crop residue burning, fuel wood combustion, and other NH3 emission sources were included in the inventory. Furthermore, a source apportionment tool, ISAM (Integrated Source Apportionment Method), coupled with the air quality modeling system RAMS-CMAQ (Regional Atmospheric Modeling System and Community Multiscale Air Quality), was applied to capture the contribution of NH3 emitted from total agriculture (Tagr) in China. The aerosol mass concentration in 2015 was simulated, and the results showed that a high mass concentration of NH3, which exceeded 10 μg m−3, appeared mainly in the North China Plain (NCP), Central China (CNC), the Yangtz River Delta (YRD), and the Sichan Basin (SCB), and the annual average contribution of Tagr NH3 to PM2.5 mass burden in China was 14–18 %. Specific to the PM2.5 components, Tagr NH3 provided a major contribution to ammonium formation (87.6 %) but a tiny contribution to sulfate (2.2 %). In addition, several brute-force sensitivity tests were conducted to estimate the impact of Tagr NH3 emissions reduction on the PM2.5 mass burden. Compared with the results of ISAM, it was found that even though the Tagr NH3 only contributed 10.1 % of nitrate under current emissions scenarios, the reduction of nitrate could reach 98.8 % upon removal of the Tagr NH3 emissions. The main reason for this deviation could be that the NH3 contribution to nitrate is small under rich NH3 conditions and large in poor NH3 environments. Thus, the influence of NH3 on nitrate formation could be enhanced with the decrease of ambient NH3 mass concentration.

scholarly journals Behavior of the Average Concentrations As Well As Their PM10 and PM2.5 Variability in the Metropolitan Area of Lima, Peru: Case Study February and July 2016

2021 ◽  
Vol 12 (7) ◽  
pp. 204-213
Author(s):  
Reátegui-Romero Warren ◽  
F. Zaldivar-Alvarez Walter ◽  
Pacsi–Valdivia Sergio ◽  
R. Sánchez-Ccoyllo Odón ◽  
E. García-Rivero Alberto ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Relative Humidity ◽  
Metropolitan Area ◽  
Vehicular Traffic ◽  
Northern Area ◽  
The North ◽  
Pm10 And Pm2.5 ◽  
Traffic Behavior

This research focused on analyzing the behavior of the hourly average concentrations of PM10 and PM2.5 in relation to vehicular traffic, as well as the effect of relative humidity on these concentrations. Measurements of hourly particulate matter concentrations were recorded by the National Meteorology and Hydrology Service of Peru (SENAMHI) at five surface air quality stations. The profiles of PM10 concentrations are related to traffic behavior, showing high levels of concentrations at peak hours, while the PM2.5 profiles are flatter and better related to traffic in February (summer). The decrease in relative humidity between 80 to 65% in the mornings has a greater effect on the increase in PM10 and PM2.5 concentrations in February than in July (winter), and the increase in relative humidity between 65 to 80 % in the afternoon, it has a greater effect on the decrease in the concentration of PM2.5 in February than in July. The air quality in the north (PPD and CRB stations) and east (SJL station) of the Metropolitan Area of Lima (MAL) are the most polluted. The factors that relate PM10 concentrations with the Peruvian standard in February at these stations were 2.79, 1.78 and 1.26, and in July 2.74, 1.28 and 1.36 respectively. The highest and lowest variability of PM10 and PM2.5 in February and July occurred in the northern area (PPD and SMP stations).

scholarly journals ESTIMATING PM2.5 IN XI’AN , CHINA USING AEROSOL OPTICAL DEPTH OF NPP VIIRS DATA AND METEOROLOGICAL MEASUREMENTS

2018 ◽  
Vol XLII-3 ◽  
pp. 2267-2271
Author(s):  
K. Zhang ◽  
Z. Yang ◽  
J. Zheng ◽  
J. Jiao ◽  
W. Gao
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Ground Surface ◽  
Shaanxi Province ◽  
The North ◽  
Adverse Weather ◽  
Pm2.5 Concentration

In recent years, the air pollution is becoming more and more serious, which not only causes the decrease of the visibility, but also affects the human health. As the most important pollutant particulate matter, remote sensing satellite measurements have been widely used to estimate PM2.5 concentration on the ground. Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the instruments which is taken in the National Polar-orbiting Partnership (NPP) satellite. In this study, VIIRS was used to retrieve aerosol optical depth (AOD) with the way of dark pixels, and several other major meteorological variables (wind speed, relative humidity, NO<sub>2</sub> concentration, ground surface relative humidity and planetary boundary layer height) were combined with AOD to construct a nonlinear multiple regression mode for establishing the relationship between AOD and PM2.5 concentration. The North Basin of Shaanxi province of China, which includes Xi’an, is located in the north of Qinling Mountains, south of the Loess Plateau, and in the central of Weihe basin, with special structure and other adverse weather conditions (static wind, less rain) to cause the frequent haze weather in Xi'an. Xi’an city was selected as the area of the experiment due to its particularity. This research obtained the AOD results from August 1, 2013 to October 30, 2013. The inversion results were compared with ground-based PM2.5 concentration date from air quality monitoring station of Xi’an. The result showed that there is a significant correlation between the two, and the correlation coefficient is 0.783. The inversion result verified that the model of VIIRS data agreed well AOD, which could be used to estimate the surface PM2.5 concentration and monitor the regional air quality.

scholarly journals Investigating the Transport Mechanism of PM2.5 Pollution during January 2014 in Wuhan, Central China

2019 ◽  
Vol 36 (11) ◽  
pp. 1217-1234 ◽  
Author(s):  
Miaomiao Lu ◽  
Xiao Tang ◽  
Zifa Wang ◽  
Lin Wu ◽  
Xueshun Chen ◽  
...  
Keyword(s):  
Long Range ◽  
Formation Mechanism ◽  
Weather Conditions ◽  
Central China ◽  
Long Range Transport ◽  
The North ◽  
Haze Pollution ◽  
Range Transport ◽  
Haze Formation ◽  
Strong Winds

Abstract Severe haze pollution that occurred in January 2014 in Wuhan was investigated. The factors leading to Wuhan’s PM2.5 pollution and the characteristics and formation mechanism were found to be significantly different from other megacities, like Beijing. Both the growth rates and decline rates of PM2.5 concentrations in Wuhan were lower than those in Beijing, but the monthly PM2.5 value was approximately twice that in Beijing. Furthermore, the sharp increases of PM2.5 concentrations were often accompanied by strong winds. A high-precision modeling system with an online source-tagged method was established to explore the formation mechanism of five haze episodes. The long-range transport of the polluted air masses from the North China Plain (NCP) was the main factor leading to the sharp increases of PM2.5 concentrations in Wuhan, which contributed 53.4% of the monthly PM2.5 concentrations and 38.5% of polluted days. Furthermore, the change in meteorological conditions such as weakened winds and stable weather conditions led to the accumulation of air pollutants in Wuhan after the long-range transport. The contribution from Wuhan and surrounding cities to the PM2.5 concentrations was determined to be 67.4% during this period. Under the complex regional transport of pollutants from surrounding cities, the NCP, East China, and South China, the five episodes resulted in 30 haze days in Wuhan. The findings reveal important roles played by transregional and intercity transport in haze formation in Wuhan.

scholarly journals Numerical analysis of agricultural emissions impacts on PM<sub>2.5</sub> in China using a high-resolution ammonia emission inventory

2020 ◽  
Vol 20 (16) ◽  
pp. 9979-9996
Author(s):  
Xiao Han ◽  
Lingyun Zhu ◽  
Mingxu Liu ◽  
Yu Song ◽  
Meigen Zhang
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Source Apportionment ◽  
Mass Concentration ◽  
Emission Inventory ◽  
Atmospheric Modeling ◽  
Central China ◽  
High Mass ◽  
Nh3 Emission ◽  
The Impact

Abstract. China is one of the largest agricultural countries in the world. Thus, NH3 emission from agricultural activities in China considerably affects the country's regional air quality and visibility. In this study, a high-resolution agricultural NH3 emission inventory compiled on 1 km × 1 km horizontal resolution was applied to calculate the NH3 mass burden in China and reliably estimate the influence of NH3 on agriculture. The key parameter emission factors of this inventory were enhanced by considering many experiment results, and the dynamic data of spatial and temporal information were updated using statistical data of 2015. In addition to fertilizers and husbandry, farmland ecosystems, livestock waste, crop residue burning, wood-based fuel combustion, and other NH3 emission sources were included in this inventory. Furthermore, a source apportionment tool, namely, the Integrated Source Apportionment Method (ISAM) coupled with the air quality modeling system Regional Atmospheric Modeling System and Community Multiscale Air Quality, was applied to capture the contribution of NH3 emitted from total agriculture (Tagr) in China. The aerosol mass concentration in 2015 was simulated, and results showed that the high mass concentration of NH3 exceeded 10 µg m−3 and mainly appeared in the North China Plain, Central China, the Yangtze River Delta, and the Sichuan Basin. Moreover, the annual average contribution of Tagr NH3 to PM2.5 mass burden was 14 %–22 % in China. Specific to the PM2.5 components, Tagr NH3 contributed dominantly to ammonium formation (87.6 %) but trivially to sulfate formation (2.2 %). In addition, several brute-force sensitivity tests were conducted to estimate the impact of Tagr NH3 emission reduction on PM2.5 mass burden. In contrast to the result of ISAM, even though the Tagr NH3 only provided 10.1 % contribution to nitrate under the current emission scenario, the reduction of nitrate could reach 95.8 % upon removal of the Tagr NH3 emission. This deviation occurred because the contribution of NH3 to nitrate should be small under a “rich NH3”environment and large under a “poor NH3” environment. Thus, the influence of NH3 on nitrate formation would be enhanced with the decrease in ambient NH3 mass concentration.

Current Status of Anserinae Wintering in Azov-Black Sea Region of Ukraine

2019 ◽  
Vol 53 (4) ◽  
pp. 297-312
Author(s):  
Yu. O. Andryushchenko ◽  
V. S. Gavrilenko ◽  
V. A. Kostiushyn ◽  
V. N. Kucherenko ◽  
A. S. Mezinov ◽  
...  
Keyword(s):  
Black Sea ◽  
Current Status ◽  
Anser Anser ◽  
Scientific Publications ◽  
Climate Conditions ◽  
Black Sea Region ◽  
Chen Caerulescens ◽  
Branta Bernicla ◽  
The North ◽  
Different Seasons

Abstract In the article is analyzed own field data of the authors and scientific publications on the wintering of Anserinae in the Azov-Black Sea region of Ukraine in 1900–2017, but the main data was obtained in frame of international mid-winter counts (IWC) in 2005–2017. It was found that 9 species of Anserinae occur in this region during the different seasons of the year: Anser anser — nesting, wintering and migrating; Rufibrenta ruficollis, A. albifrons, A. erythropus, A. fabalis — migrating and wintering; Branta canadensis, Branta leucopsis, Branta bernicla, Chen caerulescens — vagrant or birds which flew away from captivity (zoo etc.). Eulabeia indica — is possible vagrant species. The most numerous wintering species is A. albifrons, common — Rufibrenta ruficollis, not numerous — Anser anser, the other species are not met annually and registered in a very small number. There was almost tenfold drop in number of wintering geese in the Azov-Black Sea region of Ukraine during the period of counts. The main reasons of such reducing of geese amount are the followwing: weather and climate conditions, changes in the forage acessibility, hunting and poaching pressure, poisoning as a result of deratization of agricultural lands, and from 2014 — the militarization of the Syvash area and stop of water supplying of Crimea through the North Crimean channell. It is likely that the factors mentioned above led to relocating of wintering areas of Anserinae, and resulted in decreasing of their amount in this region.

scholarly journals Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3338
Author(s):  
Ivan Vajs ◽  
Dejan Drajic ◽  
Nenad Gligoric ◽  
Ilija Radovanovic ◽  
Ivan Popovic
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Relative Humidity ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Lower Accuracy ◽  
Wide Range ◽  
The Impact ◽  
Monitoring Stations

Existing government air quality monitoring networks consist of static measurement stations, which are highly reliable and accurately measure a wide range of air pollutants, but they are very large, expensive and require significant amounts of maintenance. As a promising solution, low-cost sensors are being introduced as complementary, air quality monitoring stations. These sensors are, however, not reliable due to the lower accuracy, short life cycle and corresponding calibration issues. Recent studies have shown that low-cost sensors are affected by relative humidity and temperature. In this paper, we explore methods to additionally improve the calibration algorithms with the aim to increase the measurement accuracy considering the impact of temperature and humidity on the readings, by using machine learning. A detailed comparative analysis of linear regression, artificial neural network and random forest algorithms are presented, analyzing their performance on the measurements of CO, NO2 and PM10 particles, with promising results and an achieved R2 of 0.93–0.97, 0.82–0.94 and 0.73–0.89 dependent on the observed period of the year, respectively, for each pollutant. A comprehensive analysis and recommendations on how low-cost sensors could be used as complementary monitoring stations to the reference ones, to increase spatial and temporal measurement resolution, is provided.

scholarly journals Potential Evapotranspiration Reduction and Its Influence on Crop Yield in the North China Plain in 1961–2014

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Wanlin Dong ◽  
Chao Li ◽  
Qi Hu ◽  
Feifei Pan ◽  
Jyoti Bhandari ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Crop Yield ◽  
North China Plain ◽  
North China ◽  
Potential Evapotranspiration ◽  
The North ◽  
The North China Plain ◽  
Sunshine Hours ◽  
Humidity Index

Climate change has caused uneven changes in hydrological processes (precipitation and evapotranspiration) on a space-temporal scale, which would influence climate types, eventually impact agricultural production. Based on data from 61 meteorological stations from 1961 to 2014 in the North China Plain (NCP), the spatiotemporal characteristics of climate variables, such as humidity index, precipitation, and potential evapotranspiration (ET0), were analyzed. The sensitivity coefficients and contribution rates were applied to ET0. The NCP has experienced a semiarid to humid climate from north to south due to the significant decline of ET0 (−13.8 mm decade−1). In the study region, 71.0% of the sites showed a “pan evaporation paradox” phenomenon. Relative humidity had the most negative influence on ET0, while wind speed, sunshine hours, and air temperature had a positive effect on ET0. Wind speed and sunshine hours contributed the most to the spatiotemporal variation of ET0, followed by relative humidity and air temperature. Overall, the key climate factor impacting ET0 was wind speed decline in the NCP, particularly in Beijing and Tianjin. The crop yield in Shandong and Henan provinces was higher than that in the other regions with a higher humidity index. The lower the humidity index in Hebei province, the lower the crop yield. Therefore, potential water shortages and water conflict should be considered in the future because of spatiotemporal humidity variations in the NCP.

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