A study of meteorological effects on PM2.5 concentration in mining area

Asif, Zunaira; Chen, Zhi; Guo, Jianbo

doi:10.1016/j.apr.2018.01.004

Cited by 19 publications

(5 citation statements)

References 15 publications

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“…The relationship between PM 2.5 concentrations and traffic volume of roadways was consistently significant during the overall study period when adopting 100M to estimate the impact of PM 2.5 from roadways. Although the exponential distance-decay of PM 2.5 concentrations from roadways has been reported in previous studies [25,26], the detailed distance parameters of decay models would not be very consistent because numerous meteorological factors, such as precipitation and wind, strongly affect PM 2.5 dispersion [25,36,37]. The contribution of traffic to PM 2.5 concentrations became inconspicuous 150 m away from roadways where the turbulence caused by vehicles, road and atmospheric boundary layer was small [26].…”

Section: Contributions Of Road Traffic To Pm 25 Concentrations By Season and Modelmentioning

confidence: 87%

A Network-Based Approach for Reducing Pedestrian Exposure to PM2.5 Induced by Road Traffic in Seoul

Yoon

Youngjoo

Jeong

et al. 2021

Land

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Urban plans for pedestrian-friendly environments by reducing exposure to air pollutants and enhancing movement are crucial for public health and accessibility of social infrastructure. Here, we develop a novel network analysis-based approach, which identifies pivotal local walkways that lower exposure risk to fine particulate matter (PM2.5) while improving the urban landscape connectivity. We employ an exponential distance-decay model and partial correlation analysis to estimate traffic-induced PM2.5 and to test the relationship between the proxies and actual PM2.5 concentrations, respectively. We use a proxy for pedestrians’ PM2.5 exposure as a movement cost when conducting network analyses to compute pedestrian network centrality, reflecting both low PM2.5 exposure risk and landscape connectivity. As a result, we found a significant contribution of traffic to the estimated PM2.5 exposure and PM2.5 concentrations. We also found that walkways make a large contribution to regional connectivity regardless of the estimated PM2.5 exposure risk owing to the composition and configuration of urban landscape elements. Regarding the spatial features and planning context, this study suggests four types of pedestrian networks to provide urban authorities with useful practical information in city-wide urban plans for enhancing walkability: PM2.5 reduction required; PM2.5 reduction recommended; optimal areas; and alternatives of optimal areas.

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Section: Contributions Of Road Traffic To Pm 25 Concentrations By Season and Modelmentioning

confidence: 87%

A Network-Based Approach for Reducing Pedestrian Exposure to PM2.5 Induced by Road Traffic in Seoul

Yoon

Youngjoo

Jeong

et al. 2021

Land

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“…Xu et al [8] find out that meteorological conditions (such as low wind speed, high humidity, low boundary layer height, and low rainfall) may contribute to PM2.5 concentration worsening by 29.7%, 42.6% and 7.9% in the Beijing-Tianjin-Hebei region. Essential meteorological parameters play a vital role in either dilution of the pollutant into the atmosphere or deposition of the particles tending to concentrate on to the ground [9]. Based on the relationship between meteorological factors and PM2.5, various mathematical modeling methods have been further used to establish monitoring and predicting models for improving accuracy and prediction duration.…”

Section: Introductionmentioning

confidence: 99%

Short-Term PM2.5 Concentration Prediction by Combining GNSS and Meteorological Factors

Wen

Dang

Li³

2020

IEEE Access

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With the development of industrialization, fine particulate matter (PM2.5) severely chills the health of people. Studies have shown that the variation of PM2.5 concentration is related to the Global Navigation Satellite System (GNSS) tropospheric delay. Therefore, it is possible to use the widely distributed continuous operation reference station (CORS) to monitor and predict PM2.5 concentrations with high time resolution. In this paper, the zenith wet delay (ZWD) of five CORS located in Baoding, Hebei Province, China, from Sep 2014 to Feb 2015, is calculated firstly. Then, the correlation between PM2.5 and ZWD is investigated. Finally, the experimental data including PM2.5, ZWD, temperature, air pressure, and relative humidity data sampled in one hour are used to establish PM2.5 concentrations online prediction model based on support vector machine regression (SVMR) model with metabolic method. The experimental results show that in autumn and winter, the correlation coefficient between daily-mean PM2.5 and ZWD is mainly larger than 0.4, and the correlation coefficient between hourly mean PM2.5 and ZWD is mainly larger than 0.3. Meanwhile, in daily cycle analysis, air temperature, air pressure and relative humidity are related to PM2.5 concentration. Finally, Using SVMR model with metabolic method, by combining GNSS and meteorological factors, ideal short-term prediction accuracy is achieved, which shows that the use of GNSS and meteorological factors is potential in predicting PM2.5 concentration.

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“…Solar radiation could impact the APTI through its effects on the total chlorophyll values and relative water content of plants. Increased exposure to solar radiation can stimulate chlorophyll production, enhancing a plant's ability to photosynthesize and synthesize protective compounds against air pollutants [40][41][42]. Solar radiation contributes to the regulation of plant water balance, influencing the relative water content, which is crucial for maintaining physiological functions and resilience to environmental stressors, including air pollution.…”

Section: Discussionmentioning

confidence: 99%

Assessing the Air Pollution Tolerance Index of Urban Plantation: A Case Study Conducted along High-Traffic Roadways

Asif,

2024

Atmosphere

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Road transport and traffic congestion significantly contribute to dust pollution, which negatively impacts the growth of roadside plants in urban areas. This study aims to quantify the air pollution tolerance index (APTI) and analyze the impacts of dust deposition on different plant species and trees planted along a busy urban roadside in Lahore, Pakistan by considering seasonal variations. The APTI of each species is determined based on inputs of various biochemical parameters (leaf extract pH, ascorbic acid content, relative water content, and total chlorophyll levels), including dust deposition. In this study, laboratory analysis techniques are employed to assess these factors in selected plant species such as Mangifera indica, Saraca asoca, Cassia fistula, and Syzygium cumini. A statistical analysis is conducted to understand the pairwise correlation between various parameters and the APTI at significant and non-significant levels. Additionally, uncertainties in the inputs and APTI are addressed through a probabilistic analysis using the Monte Carlo simulation method. This study unveils seasonal variations in key parameters among selected plant species. Almost all biochemical parameters exhibit higher averages during the rainy season, followed by the summer and winter. Conversely, dust deposition on plants follows an inverse trend, with values ranging from 0.19 to 4.8 g/cm2, peaking during winter, notably in Mangifera indica. APTI values, ranging from 9.39 to 14.75, indicate varying sensitivity levels across species, from sensitive (Syzygium cumini) to intermediate tolerance (Mangifera indica). Interestingly, plants display increased tolerance during regular traffic hours, reflecting a 0.9 to 5% difference between the APTI at peak and regular traffic hours. Moreover, a significant negative correlation (−0.86 at p < 0.05 level) between APTI values and dust deposition suggests a heightened sensitivity to pollutants during the winter. These insights into the relationship between dust pollution and plant susceptibility will help decision makers in the selection of resilient plants for urban areas and improve air quality.

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A study of meteorological effects on PM2.5 concentration in mining area

Cited by 19 publications

References 15 publications

A Network-Based Approach for Reducing Pedestrian Exposure to PM2.5 Induced by Road Traffic in Seoul

A Network-Based Approach for Reducing Pedestrian Exposure to PM2.5 Induced by Road Traffic in Seoul

Short-Term PM2.5 Concentration Prediction by Combining GNSS and Meteorological Factors

Assessing the Air Pollution Tolerance Index of Urban Plantation: A Case Study Conducted along High-Traffic Roadways

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