scholarly journals Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020

2022 ◽  
Vol 14 (1) ◽  
pp. 511
Author(s):  
Ju Wang ◽  
Yue Zhong ◽  
Zhuoqiong Li ◽  
Chunsheng Fang
Keyword(s):  
Ozone Concentration ◽  
Marine Pollution ◽  
Urban Agglomeration ◽  
Source Zone ◽  
The Yellow Sea ◽  
Potential Contribution ◽  
Heavy Industry ◽  
Pollution Characteristics ◽  
Potential Source ◽  
Temporal And Spatial

The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.

scholarly journals THE USE OF NEUTRON ACTIVATION ANALYSIS IN THE BIOMONITORING OF TRACE ELEMENT DEPOSITION IN THE OPOLE PROVINCE

2013 ◽  
Vol 20 (4) ◽  
pp. 677-687
Author(s):  
Andrzej Kłos ◽  
Yulia A. Aleksiayenak ◽  
Zbigniew Ziembik ◽  
Małgorzata Rajfur ◽  
Dominik Jerz ◽  
...  
Keyword(s):  
Neutron Activation Analysis ◽  
Activation Analysis ◽  
Neutron Activation ◽  
Emission Factor ◽  
Analysis Procedure ◽  
Coal Basin ◽  
Heavy Industry ◽  
Moss Species ◽  
Potential Source ◽  
Agricultural Areas

Abstract The neutron activation analysis procedure was used to determine the concentration of 42 elements: Na, Mg, Al, Cl, K, Ca, Sc, V, Cr, Mn, Fe, Ni, Co, Zn, As, Se, Br, Rb, Sr, Zr, Nb, Mo, I, Ag, Cd, Sb, Ba, Cs, La, Ce, Nd, Sm, Eu, Tb, Yb, Hf, Ta, W, Au, Hg, Th, and U accumulated in mosses sampled for testing in September and October 2011 in the Opole Province (Southern Poland). Samples of different moss species were collected near the intersections of the grid lines marked on the map of the province. The distance between the points was approximately 20 km. The analysis of the results made it possible to identify the places of increased deposition of element-pollutants and to indicate the potential sources of emission. Factor analysis revealed four components, two of which are of definite anthropogenic origin. The possible sources of elements are local industry and farming, and distant heavy industry complexes. The results have demonstrated the increased content of Cr, Cd, Hg, and U in moss samples collected in agricultural areas located in the southern part of the province. It has been concluded that the industrial areas of Rybnik and Ostrava and Karvina Coal Basin may be the potential source of emission of these elements.

scholarly journals Determination of dissolved nitric oxide in coastal waters of the Yellow Sea off Qingdao

2017 ◽  
Author(s):  
Chun-Ying Liu ◽  
Wei-Hua Feng ◽  
Ye Tian ◽  
Gui-Peng Yang ◽  
Pei-Feng Li ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Detection Limit ◽  
Coastal Waters ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
No Production ◽  
Spatial Distributions ◽  
Production Rates ◽  
Temporal And Spatial

Abstract. We developed a new method for the determination of dissolved nitric oxide (NO) in discrete seawater samples based on a combination of a purge-and-trap set-up and fluorometric detection of NO. 2,3-diaminonaphthalene (DAN) reacts with NO in seawater to form the highly fluorescent 2,3-naphthotriazole (NAT). The fluorescence intensity was linear for NO concentrations in the range from 0.14 nmol L−1 to 19 nmol L−1. We determined a detection limit of 0.068 nmol L−1, an average recovery coefficient of 83.8 % (80.2–90.0 %), and a relative standard deviation of ±7.2 %. With our method we determined for the first time the temporal and spatial distributions of NO surface concentrations in coastal waters of the Yellow Sea off Qingdao and in Jiaozhou Bay during a cruise in November 2009. The concentrations of NO varied from below the detection limit to 0.50 nmol L−1 with an average of 0.26 ± 0.14 nmol L−1. NO surface concentrations were generally enhanced significantly during daytime implying that NO formation processes such as NO2− photolysis are much higher during daytime than chemical NO consumption which, in turn, lead to a significant decrease of NO concentrations during nighttime. In general, NO surface concentrations and measured NO production rates were higher compared to previously reported measurements. This might be caused by the high NO2− surface concentrations encountered during the cruise. Moreover, additional measurements of NO production rates implied that the occurrence of particles and a temperature increase can enhance NO production rates. With the method introduced here we have a reliable and comparably easy to use method at hand to measure oceanic NO surface concentrations which can be used to decipher both its temporal and spatial distributions as well as its biogeochemical pathways in the oceans.

scholarly journals Regional Air Pollutant Characteristics and Health Risk Assessment of Large Cities in Northeast China

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1519
Author(s):  
Chunsheng Fang ◽  
Hanbo Gao ◽  
Zhuoqiong Li ◽  
Ju Wang
Keyword(s):  
Clustering Analysis ◽  
Northeast China ◽  
Carcinogenic Risk ◽  
Air Pollutant ◽  
The Yellow Sea ◽  
Trajectory Clustering ◽  
High Concentration ◽  
Backward Trajectory ◽  
Average Value ◽  
Potential Source

This study systematically investigated the pollution characteristics of atmospheric O3 and PM2.5, regional transport, and their health risks in three provincial capitals in northeast China during 2016–2020. The results show that O3 concentrations showed a trend of high summer and low winter, while PM2.5 concentrations showed a trend of high winter and low summer during these five years. The results of the correlation analysis indicate that external sources contribute more O3, while PM2.5 is more from local sources. The backward trajectory clustering analysis results showed that Changchun had the highest share of northwest trajectory with a five-year average value of 67.89%, and the city with the highest percentage of southwest trajectory was Shenyang with a five-year average value of 23.95%. The backward trajectory clustering analysis results showed that the share of the northwest trajectory decreased and the share of the southwest trajectory increased for all three cities in 2020 compared to 2016. The results of the potential source contribution function (PSCF) and concentration weighting trajectory (CWT) analysis showed that the main potential source areas and high concentration contribution areas for PM2.5 in the northeast were concentrated in Mongolia, Inner Mongolia, Shandong Province, and the northeast, and for O3 were mainly located in Shandong, Anhui, and Jiangsu Provinces, and the Yellow Sea and Bohai Sea. The non-carcinogenic risk of PM2.5 in Harbin was high with a HQ of 2.04, while the other cities were at acceptable levels (HQ < 0.69) and the non-carcinogenic risk of O3 was acceptable in all three cities (HQ < 0.22). However, PM2.5 had a high carcinogenic risk (4 × 10−4 < CR < 0.44) and further treatment is needed to reduce the risk.

Temporal and spatial evolution of human landscape development in the Fujian delta urban agglomeration in the 21st Century: Based on emergy-GIS approach

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
王亚楠 WANG Ya' ◽  
税伟 SHUI Wei ◽  
杨海峰 YANG Haifeng ◽  
祁新华 QI Xinhua ◽  
范冰雄 FAN Bingxiong ◽  
...  
Keyword(s):  
21St Century ◽  
Urban Agglomeration ◽  
Spatial Evolution ◽  
Landscape Development ◽  
Temporal And Spatial Evolution ◽  
Temporal And Spatial ◽  
Human Landscape

scholarly journals The Use of Remote Sensing Analysis for Evaluating the Impact of Development Projects in the Yellow Sea Large Marine Ecosystem

2020 ◽  
Vol 12 (9) ◽  
pp. 3628
Author(s):  
Gabriel Sidman ◽  
Sydney Fuhrig ◽  
Geeta Batra
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Yellow Sea ◽  
Marine Pollution ◽  
Marine Ecosystem ◽  
Environmental Indicators ◽  
The Yellow Sea ◽  
Series Data ◽  
Large Marine Ecosystem ◽  
The Impact

Remote sensing has long been valued as a data source for monitoring environmental indicators and detecting trends in ecosystem stress from anthropogenic causes such as deforestation, river dams and air and water pollution. More recently, remote sensing analyses have been applied to evaluate the impacts of environmental projects and programs on reducing environmental stresses. Such evaluation has focused primarily on the change in above-surface vegetation such as forests. This study uses remote sensing ocean color products to evaluate the impact on reducing marine pollution of the Global Environment Facility’s (GEF) portfolio of projects in the Yellow Sea Large Marine Ecosystem. Chlorophyll concentration was derived from satellite images over a time series from the 1990s, when GEF projects began, until the present. Results show a 50% increase in chlorophyll until 2011 followed by a 34% decrease until 2019, showing a potential delayed effect of pollution control efforts. The rich time series data is a major advantage to using geospatial analysis for evaluating the impacts of environmental interventions on marine pollution. However, one drawback to the method is that it provides insights into correlations but cannot attribute the results to any particular cause, such as GEF interventions.

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