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

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.

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Technology for Predicting Particulate Matter Emissions at Construction Sites in South Korea

Sustainability ◽

10.3390/su132413792 ◽

2021 ◽

Vol 13 (24) ◽

pp. 13792

Author(s):

Jihwan Yang ◽

Sungho Tae ◽

Hyunsik Kim

Keyword(s):

Particulate Matter ◽

South Korea ◽

Urban Areas ◽

Emission Factor ◽

National Level ◽

Construction Sites ◽

Economic Problems ◽

Particulate Matter Emissions ◽

Surrounding Areas

In recent years, particulate matter (PM) has emerged as a major social issue in various industries, particularly in East Asia. PM not only causes various environmental, social, and economic problems but also has a large impact on public health. Thus, there is an urgent requirement for reducing PM emissions. In South Korea, the PM generated at construction sites in urban areas directly or indirectly causes various environmental problems in surrounding areas. Construction sites are considered a major source of PM that must be managed at the national level. Therefore, this study aims to develop a technology for predicting PM emissions at construction sites. First, the major sources of PM at construction sites are determined. Then, PM emission factors are calculated for each source. Furthermore, an algorithm is developed for calculating PM emissions on the basis of an emission factor database, and a system is built for predicting PM emissions at construction sites. The reliability of the proposed technology is evaluated through a case study. The technology is expected to be used for predicting potential PM emissions at construction sites before the start of construction.

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Calculation Methods of Emission Factors and Emissions of Fugitive Particulate Matter in South Korean Construction Sites

Sustainability ◽

10.3390/su12239802 ◽

2020 ◽

Vol 12 (23) ◽

pp. 9802

Author(s):

Hyunsik Kim ◽

Sungho Tae ◽

Jihwan Yang

Keyword(s):

Particulate Matter ◽

South Korea ◽

The United States ◽

Emission Factors ◽

Construction Workers ◽

Construction Site ◽

Fugitive Dust ◽

Construction Sites ◽

South Korean ◽

Pm10 And Pm2.5

Recently, efforts to effectively reduce particulate matter by identifying its sources and trends have become necessary due to the sustained damage it has caused in East Asia. In the case of South Korea, damage due to fugitive dust generated at construction sites in densely populated downtown areas is significant, and particulate matter in such fugitive dust directly influences the health of nearby residents and construction workers. Accordingly, the purpose of the present study was to develop a method for calculating emission factors for PM10 and PM2.5 emission amounts in the fugitive dust generated in construction sites and to derive emission amount trends for major variables to predict the amounts of generated particulate matter. To this end, South Korean emission factors for PM10 and PM2.5 for different construction equipment and activities that generate fugitive dust were derived and a method for calculating the amount of particulate matter using the derived emission factors was proposed. In addition, the calculated total emissions using these factors were compared to those calculated using construction site fugitive dust equations developed for the United States, Europe, and South Korea, and the trend analysis of total emissions according to the major emission factor variables was conducted.

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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

E3S Web of Conferences ◽

10.1051/e3sconf/20182801027 ◽

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.

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Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke

Sensors ◽

10.3390/s20174796 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4796

Author(s):

Amara L. Holder ◽

Anna K. Mebust ◽

Lauren A. Maghran ◽

Michael R. McGown ◽

Kathleen E. Stewart ◽

...

Keyword(s):

Particulate Matter ◽

Air Quality ◽

Low Cost ◽

Field Evaluation ◽

Eastern United States ◽

Monitoring Networks ◽

Wildfire Smoke ◽

Sensor Package ◽

The Impact ◽

Mean Square Errors

Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although their performance during smoke impacted conditions has not been thoroughly evaluated. We collocated three types of low-cost fine PM (PM2.5) sensors with reference instruments near multiple fires in the western and eastern United States (maximum hourly PM2.5 = 295 µg/m3). Sensors were moderately to strongly correlated with reference instruments (hourly averaged r2 = 0.52–0.95), but overpredicted PM2.5 concentrations (normalized root mean square errors, NRMSE = 80–167%). We developed a correction equation for wildfire smoke that reduced the NRMSE to less than 27%. Correction equations were specific to each sensor package, demonstrating the impact of the physical configuration and the algorithm used to translate the size and count information into PM2.5 concentrations. These results suggest the low-cost sensors can fill in the large spatial gaps in monitoring networks near wildfires with mean absolute errors of less than 10 µg/m3 in the hourly PM2.5 concentrations when using a sensor-specific smoke correction equation.

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

Atmosphere ◽

10.3390/atmos12091112 ◽

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.

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Dispersion of Nitrogen Dioxide and Particulate Matter Concentrations in Street Canyons and Open Landscape in Urban Mysore

Shanlax International Journal of Arts, Science and Humanities ◽

10.34293/sijash.v7i3.1352 ◽

2020 ◽

Vol 7 (3) ◽

pp. 36-43

Author(s):

Prabhakaran Nataraj ◽

Azis Kemal Fauzie ◽

P N Sandhya Rani ◽

G V Venkataramana

Keyword(s):

Particulate Matter ◽

Wind Speed ◽

Nitrogen Dioxide ◽

Meteorological Data ◽

Tall Buildings ◽

Urban Spaces ◽

Street Canyons ◽

Factors Affecting ◽

Pm10 And Pm2.5 ◽

Different Types

The variation in nitrogen dioxide (NO2), particulate matter (PM10 and PM2.5) concentrations and meteorological data were analyzed at different types of urban spaces in Mysore consisting of four street canyons and one open landscape sites. The NO2 and PM levels were measured using portable monitoring device and respirable dust sampler, respectively. The maximum NO2 concentration was found at the intersection of both street canyons and open landscape, either in the morning (70-160 µg/m3) or evening (20-60 µg/m3). Result found that concentration of NO2 in street canyons was significantly higher than in open landscape sites (p < 0.001). The ambient NO2 levels were also found lower in the cross roads compared to such in the main roads. The high number of vehicles passing through the roads accounts for the higher NO2 concentration as we found significant positive correlation between traffic volume and NO2, SPM, PM10 and PM2.5 concentrations, either in the street canyon and open landscape sites. Furthermore, a negative association has been observed between both SPM and NO2 levels and the wind speed (p = 0.002 and p < 0.05 respectively). The factors affecting the different dispersion characteristics of air pollutants were found to be the wind speed, vehicular traffic, and site landscape where congested with high number of tall buildings.

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

Frontiers in Sustainability ◽

10.3389/frsus.2021.649715 ◽

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 < 1.5, suspiciously non-confident when 1.5 ≤ t < 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.

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Study on Particulate Matter Concentration in the Indoor Air of Classrooms in a Beijing Primary School

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.113-116.1419 ◽

2010 ◽

Vol 113-116 ◽

pp. 1419-1423

Author(s):

Yu Shu Xie ◽

Bing Xue Song ◽

Tong Wang ◽

Pei Yi Wang

Keyword(s):

Particulate Matter ◽

Primary School ◽

Indoor Air ◽

Pm10 And Pm2.5 ◽

Portable Monitors ◽

Room Volume ◽

Autumn And Winter ◽

The Impact ◽

Measurement Period ◽

Mass Concentrations

Five classrooms in a Primary School in Xuanwu District of Beijing were chosen for investigation of indoor air quality. In the autumn measurement period and in the winter measurement period, various dust particle fractions (PM10 and PM2.5) were monitored indoors and outdoors continuously by portable monitors and samplers. Applying statistical software, the impact of different parameters on particulate matter (PM10 and PM2.5) mass concentration was then quantitatively analyzed. The main conclusions were included as follows: (1) Exposure to PM10 and PM2.5 in the indoor air of classrooms in autumn and in winter was high, especially that of PM2.5 in autumn. (2) The indoor PM10 and PM2.5 mass concentrations were related to different parameters including relative humidity, temperature, carbon dioxide, area of opened windows or louver windows, number of students and room volume/student and so on. (3) No marked differences in indoor PM10 and PM2.5 mass concentrations were observed between autumn and winter (p>0.05). However, a statistically significant influence of class level on the indoor PM10 and PM2.5 mass concentrations was apparent in both measurement periods (p<0.05).

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Evaluation and Prediction of PM10 and PM2.5 from Road Source Emissions in Kuala Lumpur City Centre

Sustainability ◽

10.3390/su13105402 ◽

2021 ◽

Vol 13 (10) ◽

pp. 5402

Author(s):

Azliyana Azhari ◽

Nor Diana Abdul Halim ◽

Anis Asma Ahmad Mohtar ◽

Kadaruddin Aiyub ◽

Mohd Talib Latif ◽

...

Keyword(s):

Particulate Matter ◽

Traffic Management ◽

Average Concentration ◽

Monitoring Station ◽

City Centre ◽

Kuala Lumpur ◽

Pm10 And Pm2.5 ◽

Traffic Reduction ◽

Annual Average Concentration ◽

The Impact

Particulate matter (PM) is one of the major pollutants emitted by vehicles that adversely affect human health and the environment. This study evaluates and predicts concentrations and dispersion patterns of PM10 and PM2.5 in Kuala Lumpur city centre. The OML-Highway model calculates hourly time series of PM10 and PM2.5 concentrations and distribution caused by traffic emissions under different scenarios; business as usual (BAU) and 30% traffic reduction to see the impact of traffic reduction for sustainable traffic management. Continuous PM10 and PM2.5 data from a nearby monitoring station were analysed for the year 2019 and compared with modelled concentrations. Annual average concentration at various locations of interest for PM10 and PM2.5 during BAU runs were in the ranges 41.4–65.9 µg/m3 and 30.4–43.7 µg/m3 respectively, compared to during the 30% traffic reduction run ranging at 40.5–59.5 µg/m3 and 29.9–40.3 µg/m3 respectively. The average concentration of PM10 and PM2.5 at the Continuous Air Quality Monitoring Station (CAQMS) was 36.4 µg/m3 and 28.2 µg/m3 respectively. Strong correlations were observed between the predicted and observed data for PM10 and PM2.5 in both scenarios (p < 0.05). This research demonstrated that the reduction of traffic volume in the city contributes to reducing the concentration of particulate matter pollution.

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