scholarly journals Temporal and Spatial Trends in Particulate Matter and the Responses to Meteorological Conditions and Environmental Management in Xi’an, China

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1112
Author(s):  
Yulu Tian ◽  
Lingnan Zhang ◽  
Yang Wang ◽  
Jinxi Song ◽  
Haotian Sun
Keyword(s):  
Environmental Management ◽  
Particulate Matter ◽  
Environmental Regulation ◽  
Emission Intensity ◽  
Atmospheric Temperature ◽  
Meteorological Conditions ◽  
Pm10 And Pm2.5 ◽  
Haze Pollution ◽  
Temporal And Spatial ◽  
The Impact

Particulate matter contributes much to the haze pollution in China. Meteorological conditions and environmental management significantly influenced the accumulation, deposition, transportation, diffusion, and emission intensity of particulate matter. In this study, temporal and spatial variations of PM10 and PM2.5—and the responses to meteorological factors and environmental regulation intensity—were explored in Xi’an, China. The concentrations of PM10 were higher than those of PM2.5, especially in spring and winter. The mean annual concentrations of PM10 and PM2.5 markedly decreased from 2013 to 2017, but the decreasing trend has plateaued since 2015. The concentrations of PM10 and PM2.5 exhibited seasonal differences, with winter being the highest and summer the lowest. Air quality monitoring stations did not reveal significant spatial variability in PM10 and PM2.5 concentrations. The concentrations of PM10 and PM2.5 were significantly influenced by precipitation, relative humidity, and atmospheric temperature. The impact of wind speed was prominent in autumn and winter, while in spring and summer the impact of wind direction was obvious. Additionally, the emission intensity of SO2, smoke and dust could be effectively decreased with the increasing environmental regulation intensity, but not the concentrations of particulate matter. This study could provide a scientific framework for atmospheric pollution management.

scholarly journals Quantification of Non-Exhaust Particulate Matter Traffic Emissions and the Impact of COVID-19 Lockdown at London Marylebone Road

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 190
Author(s):  
William Hicks ◽  
Sean Beevers ◽  
Anja H. Tremper ◽  
Gregor Stewart ◽  
Max Priestman ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Measurement Data ◽  
Emission Factors ◽  
Meteorological Conditions ◽  
Traffic Emissions ◽  
Atmospheric Particulate Matter ◽  
Exhaust Emission ◽  
Brake Wear ◽  
The Impact ◽  
Exhaust Particulate

This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data were used to determine the traffic increment (roadside–background) and covered a range of meteorological conditions, seasons, and driving styles, as well as the influence of the COVID-19 “lockdown” on non-exhaust concentrations. Non-exhaust particulate matter (PM)10 concentrations were calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc), and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 “dilution approach”. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicate that non-exhaust emission factors were dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds, and meteorological conditions, as well as advanced source apportionment of the PM measurement data, were undertaken to enhance our understanding of these important vehicle sources.

scholarly journals Field Evaluation of the Dust Impacts from Construction Sites on Surrounding Areas: A City Case Study in China

2019 ◽  
Vol 11 (7) ◽  
pp. 1906 ◽  
Author(s):  
Hui Yan ◽  
Guoliang Ding ◽  
Hongyang Li ◽  
Yousong Wang ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Meteorological Data ◽  
Large Diameter ◽  
Field Evaluation ◽  
Building Construction ◽  
Major Constituent ◽  
Construction Sites ◽  
Pm10 And Pm2.5 ◽  
Surrounding Areas ◽  
The Impact

Construction activities generate a large amount of dust and cause significant impacts on air quality of surrounding areas. Thus, revealing the characteristics of construction dust is crucial for finding the way of reducing its effects. To fully uncover the characteristics of construction dust affecting surrounding areas, this study selected seven representative construction sites in Qingyuan city, China as empirical cases for field evaluation. In the experiment, the up-downwind method was adopted to monitor and collect TSP (total suspended particulate), PM10 and PM2.5 (particulate matter ≤10 µm and 2.5 µm in aerodynamic diameter, respectively) concentrations, meteorological data and construction activities of each site for 2 to 3 days and 18 h in a day. The results show that the average daily construction site makes the surrounding areas’ concentration of TSP, PM10 and PM2.5 increase by 42.24%, 19.76% and 16.27%, respectively. The proportion of TSP, PM10 and PM2.5 in building construction dust is 1, 0.239 and 0.116, respectively. The large diameter particulate matter was the major constituent and the distance of its influence was limited. In addition, construction vehicles were one of the main influencing factors for building construction dust. However, building construction dust was not significantly correlated with any single meteorological factor when it did not change too much. Findings of this research can provide a valuable basis for reducing the impact of building construction dust on surrounding areas.

scholarly journals Evident PM<sub>2.5</sub> Drops in the East of China due to the COVID-19 Quarantines in February

2020 ◽  
Author(s):  
Zhicong Yin ◽  
Yijia Zhang ◽  
Huijun Wang ◽  
Yuyan Li
Keyword(s):  
Emergency Response ◽  
Yangtze River ◽  
North China ◽  
Fine Particulate Matter ◽  
Yangtze River Delta ◽  
Meteorological Conditions ◽  
Pollution Regulation ◽  
Fine Particulate ◽  
Haze Pollution ◽  
The Impact

Abstract. The top-level emergency response to the COVID-19 pandemic involved an exhaustive quarantine in China. The impacts of COVID-19 quarantine on the decline in fine particulate matter (PM2.5) were quantitatively assessed based on numerical simulations and observations in February. The stable meteorological conditions in February 2020 caused considerable PM2.5 anomalies that were eliminated in advance. The contributions of routine emission reductions were also quantitatively extrapolated. The top-level emergency response substantially alleviated the level of haze pollution in the east of China. Although climate variability elevated the PM2.5 by 29 % (relative to 2020 observations), 59 % decline related to COVID-19 pandemic and 20 % decline from the expected pollution regulation dramatically exceeded the former in North China. The COVID-19 quarantine measures decreased the PM2.5 in Yangtze River Delta by 72 %. In Hubei Province where most pneumonia cases were confirmed, the impact of total emission reduction (72 %) evidently exceeded the rising percentage of PM2.5 driven by meteorology (13 %).

scholarly journals The Impact of Haze Pollution on Regional Eco-Economic Treatment Efficiency in China: An Environmental Regulation Perspective

2019 ◽  
Vol 16 (21) ◽  
pp. 4059 ◽  
Author(s):  
Jian Hou ◽  
Yifang An ◽  
Hongfeng Song ◽  
Jiancheng Chen
Keyword(s):  
Environmental Regulation ◽  
Local Governments ◽  
Critical Mass ◽  
Heterogeneous Structure ◽  
Treatment Efficiency ◽  
Regional Heterogeneity ◽  
Haze Pollution ◽  
The Impact ◽  
Province Level ◽  
Great Wall

“The Gray Great Wall” formed by haze pollution is an increasingly serious issue in China, and the resulting air pollution has brought severe challenges to human health, the socio-economy and the world ecosystem. Based on the facts above, this paper uses China’s province-level panel data from 2009 to 2016, systematically measures the heterogeneous structure of regional ecological economic (eco-economic) treatment efficiency through a Super Slacks-Based Measure (SBM) model and dynamic threshold models, and analyzes the forcing mechanism of haze pollution pressure on regional eco-economic treatment efficiency from an environmental regulation perspective. Results indicated that China’s eco-economic treatment has been vigorously promoted, which is significantly conducive to green growth upgrading. However, the process has a large developmental scope due to regional heterogeneity. Interestingly, the forcing impact of haze pollution on regional eco-economic treatment efficiency is limited by the “critical mass” of environmental regulations: a weak degree of regulation will facilitate an increase in regional eco-economic treatment efficiency through the forcing effect of haze pollution pressure. Once environmental regulation reaches a critical level, a stronger degree of regulation will suppress the forcing effect of haze pollution in turn and it will decrease the regional eco-economic treatment efficiency. This paper endeavors to clarify the differences, suitability and dependency in the process of ecological transformation for Chinese local governments in different regions and provide policy references for a regional ecological transformation matching system.

scholarly journals A spatial econometric empirical research on the impact of industrial agglomeration on haze pollution in China

2020 ◽  
Vol 13 (11) ◽  
pp. 1305-1312 ◽  
Author(s):  
Hong Zhao ◽  
Xiaoxi Cao ◽  
Tao Ma
Keyword(s):  
Environmental Regulation ◽  
Carbon Dioxide Emissions ◽  
Industrial Agglomeration ◽  
Spatial Error ◽  
Spatial Lag Model ◽  
Haze Pollution ◽  
The Government ◽  
Obvious Manner ◽  
And Control ◽  
The Impact

Abstract Based on statistical data on 30 provincial administrative regions in China from 2000 to 2016, this paper conducts an empirical study of the impact of industrial agglomeration on haze pollution using the spatial Dubin model (SDM), spatial lag model (SLM), and spatial error model (SEM). The findings are as follows: (1) Industrial agglomeration can effectively reduce the degree of haze pollution. (2) Haze pollution has an inverted U-shaped relationship with economic development and population agglomeration. (3) The secondary industry has a positive correlation with haze pollution, while the tertiary industry can reduce haze pollution but not in an obvious manner. (4) The level of innovation and urbanization can help to reduce haze pollution, and the level of economic opening up and carbon dioxide emissions can exacerbate haze pollution. (5) Due to the insufficient commercialization of scientific and technological achievements, investment in science and technology is not obviously effective in preventing and controlling haze pollution. The relationship between environmental regulation and haze pollution is still unclear due to regional differences and the varied effectiveness of law enforcement. The study suggests that the government should guide industrial agglomeration in a reasonable manner, improve joint prevention and control across regions, and strengthen environmental regulation to prevent and control haze pollution.

scholarly journals Application of the Data Mining Methods to Assess the Impact of Meteorological Conditions on the Episodes of High Concentrations of PM10 along the Polish – Czech Border

2018 ◽  
Vol 28 ◽  
pp. 01027
Author(s):  
Leszek Ośródka ◽  
Ewa Krajny ◽  
Marek Wojtylak
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Particulate Matter ◽  
Concentration Level ◽  
Meteorological Data ◽  
Meteorological Conditions ◽  
Mining Methods ◽  
High Concentrations ◽  
The Impact ◽  
Derivatives Of

The paper presents an attempt to use selected data mining methods to determine the influence of a complex of meteorological conditions on the concentrations of PM10 (PM2.5) proffering the example of the regions of Silesia and Northern Moravia. The collection of standard meteorological data has been supplemented by increments and derivatives of measurable weather elements such as vertical pseudo-gradient of air temperature. The main objective was to develop a universal methodology for the assessment of these impacts, i.e. one that would be independent of the analysed pollution. The probability of occurrence (at a given location) of the assumed concentration level as exceeding the value of the specified distributional quintile was adopted as the discriminant of the incidence. As a result of the analyses conducted, incidences of elevated concentrations of air pollution particulate matter PM10 have been identified and the types of weather responsible for the emergence of such situations have also been determined.

scholarly journals The Impact of COVID-19 Lockdowns on Particulate Matter Emissions in Lombardy and Italian Citizens' Consumption Habits

2021 ◽  
Vol 2 ◽  
Author(s):  
Alessandro Rovetta
Keyword(s):  
Particulate Matter ◽  
First Nations ◽  
Home Delivery ◽  
Particulate Emissions ◽  
Lombardy Region ◽  
Pm10 And Pm2.5 ◽  
Wide Range ◽  
Delivery Services ◽  
The Impact ◽  
Consumption Habits

Italy has been one of the first nations in the world to be heavily affected by COVID-19. A wide range of containment measures has been adopted from February to December 2020 to mitigate the pandemic. In this regard, the present research sets out to evaluate two aspects: (i) the impact of lockdowns on the concentrations of particulate matter (PM) 10 and 2.5 in the Lombardy region, and (ii) how anti-COVID-19 restrictions influenced Italian citizens' consumption habits. To do this, the average daily concentrations of PM10 and PM2.5 during 2020 in all the provinces of Lombardy were compared with those of the previous years through Welch's t-test. The same procedure was adopted to estimate the change in Google relative search volumes of home delivery services and smart working on a national scale. Two mean values were considered statistically confident when t &lt; 1.5, suspiciously non-confident when 1.5 ≤ t &lt; 1.9, and non-confident when t ≥ 1.9. Seasonalities and trends were assessed both graphically and with Augmented Dickey-Fuller, Phillips-Perron, and Kwiatkowski-Phillips-Schmidt-Shin tests. Finally, Pearson and Spearman correlations between changes in citizens' behavior and specific key events related to COVID-19 have been dealt with. The P-value threshold was indicatively set at 0.05. Microsoft Excel 2020 and Google Sheets were used as data analysis software. This paper showed: (i) the limited or insufficient effectiveness of lockdowns in reducing PM10 and PM2.5 concentrations in Lombardy, and (ii) a significant change in the consumption habits of Italian citizens, thus leading to both positive and negative results in terms of sustainability. Therefore, it is high time that both Italian and international environmental protection authorities thoroughly investigated the role of non-mobility-related sources of particulate emissions to impose effective rules on home delivery services. Moreover, further research is required for the understanding of anthropogenic, environmental, and atmospheric phenomena that influence the concentrations of PM10 and PM2.5.

scholarly journals Impact of Varying Wind Patterns on PM10 Concentrations in the Seoul Metropolitan Area in South Korea from 2012 to 2016

2019 ◽  
Vol 58 (12) ◽  
pp. 2743-2754 ◽  
Author(s):  
Wonbae Jeon ◽  
Hwa Woon Lee ◽  
Tae-Jin Lee ◽  
Jung-Woo Yoo ◽  
Jeonghyeok Mun ◽  
...  
Keyword(s):  
Particulate Matter ◽  
South Korea ◽  
Metropolitan Area ◽  
Clustering Analysis ◽  
Meteorological Conditions ◽  
Wind Pattern ◽  
Seoul Metropolitan Area ◽  
L1 And L2 ◽  
The Impact ◽  
Wind Patterns

AbstractIn this study, we classify wind patterns that impacted PM10 concentrations in the Seoul Metropolitan Area (SMA), South Korea, from 2012 to 2016 and analyze their contributions to annual variability in particulate matter smaller than 10 μm in diameter (PM10). Using a k-means clustering analysis, we identify major wind patterns affecting PM10 concentrations from 2002 to 2016. We confirm that the impact of wind pattern changes on PM10 variability in the SMA from 2012 to 2016 was relatively greater than the impact from 2002 to 2011. We find that PM10 from 2012 to 2016 was mainly affected by wind patterns that were 1) associated with the transport of foreign emissions (our clusters H2, H4, and H5) and 2) favorable for ventilation (our clusters L1 and L2). This finding shows that PM10 variability was determined by overall variations in the respective wind patterns particularly associated with high (over 80 μg m−3) and low (below 30 μg m−3) PM10 concentrations. The results from 2012 to 2016 CMAQ simulations indicate that the effects of meteorological conditions (e.g., wind, temperature, humidity, and so on) on PM10 vary from year to year. The calculated PM10 anomalies from 2012 to 2016 were −4.97, 3.55, 1.73, 0.15, and −0.46 μg m−3, suggesting that the wind patterns in 2012 produced the least PM10 and those in 2013 produced the most.

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