Changes In Particulate Matter Concentrations Research Articles

Air pollution removal with urban greenery – Introducing the Vegetation Impact Dynamic Assessment model (VIDA)

Urban greenery is identified as a potential tool in air pollution mitigation. However, the impact is still debated. This paper introduces the innovative VIDA (Vegetation Impact Dynamic Assessment) model, specifically designed to quantify air pollution removal through deposition on vegetation. The VIDA model offers an advanced representation of vegetation that could be integrated into urban air quality dispersion models in the future. Furthermore, the model serves as a valuable tool for exploring the intricate interactions among deposition, resuspension, and wash-off processes, as well as understanding how meteorological conditions and various leaf traits influence these processes.The current version of the model focuses on particulate matter (PM) and encompasses a range of processes, including deposition on vegetation surfaces, encapsulation within the waxy cuticle, wind-driven resuspension, and wash-off. Additionally, the model takes into consideration dynamic changes in PM concentrations on the leaf surface over time, incorporating factors such as PM size fractions, meteorological conditions, and leaf characteristics. This comprehensive approach allows for the evaluation of various species or species groups based on their distinct traits. The VIDA model effectively reproduces measured data, yet continued evaluation remains crucial as new data emerges. Notably, challenges were encountered due to data scarcity and the absence of standardized methods for characterizing vegetation traits. Addressing these challenges and refining the representation of wash-off process will enhance the VIDA model's utility in predicting the dynamic relationship between vegetation and air quality.The introduction of VIDA provides a significant advancement in modelling air pollution removal by deposition to vegetation at a relevant local scale and enables inclusion of urban greenery as tool in urban planning for air pollution mitigation.

Changes in particulate matter concentration and meteorological variables after changing forest structure in oak-dominated forests nearby highway tollgate

Oak species are the major dominant tree species of deciduous forests, but the little study was conducted to understand the change of particulate matter concentration after changing the forest structure. This study analyzed the effects of changing forest structure (CFS) on the changes in meteorological factors and air particulate matter (PM) concentration after leaf emergence in oak-dominated forests nearby highway pollutants’ sources. In June 2019, 33% of the total trees were removed from the CFS of oak forests in the vicinity of the tollgate of Misiryeong in Goseong-gun, Gangwon-do, Korea. To understand the changes in leaf emergence between the treatment site (TRS is the site changing forest structure) and control site (CS), we investigated the foliage height profile (FHP, %) at each class of tree height in December 2019 and June 2020. The results showed that FHP (%) was lower in TRS than in CS in both months, and the FHP of the middle canopy class increased after TRS while that of the upper canopy class decreased. The correlation was significant with temperature in March (p < 0.01) and with wind speed in June (p < 0.01), indicating that CFS improved the airflow. There was no significant difference in the PM concentration between CS (PM10: 37.7 µg/m3, PM2.5: 21.1 µg/m3) and TRS (PM10: 37.5 µg/m3, PM2.5: 20.8 µg/m3) in March; however, the PM concentration in TRS (PM10: 65.0 µg/m3, PM2.5: 26.2 µg/m3) was lower than that in CS (PM10: 73.9 µg/m3, PM2.5: 29.1 µg/m3) in June. The rate of PM reduction (%) in TRS was higher in June (PM10: 11.3%, PM2.5: 10.0%) than in March (PM10: 2.3%, PM2.5: 4.0%). The low value of PM concentration in June could be related to the leaf emergence. Overall, the results indicated that meteorological factors and PM concentrations had changed in the inner part of the forest after leaf emergence and that the temperature and wind speed were strongly correlated with the PM concentration. These results suggest that CFS can change the forest structure and the airflow in oak-dominated forests, which PM can flow and settle down into the inner forest's nearby pollutants sources of a tollgate. The results provide basic information for understanding the reduction effect of PM by CFS in oak-dominated deciduous forests nearby highway pollutants source.

Seasonal Variation, Chemical Composition, and PMF-Derived Sources Identification of Traffic-Related PM1, PM2.5, and PM2.5-10 in the Air Quality Management Region of Žilina, Slovakia.

Particulate matter (PM) air pollution in the urban environment is mainly related to the presence of potential sources throughout the year. Road transport is one of the most important sources of PM in the urban environment, because it directly affects pedestrians. PM measurements were performed in the city of Žilina, Slovakia, at various road-traffic-related measurement stations over the course of several years. This paper evaluates changes in the concentration of the fine fraction (PM2.5), the ultrafine fraction (PM1), and the coarse fraction (PM2.5–10) over time. PM concentrations were measured by reference gravimetric method. Significant changes in PM concentrations over time due to the diversification of pollution sources and other, secondary factors can be observed from the analysis of the measured data. PM samples were subjected to chemical analysis inductively coupled plasma mass spectrometry (ICP-MS) to determine the concentrations of elements (Mg, Al, Ca, Cr, Cu, Fe, Cd, Sb, Ba, Pb, Ni, and Zn). The seasonal variation of elements was evaluated, and the sources of PM2.5, PM1, and PM2.5–10 were estimated using principal component analysis (PCA) and positive matrix factorization (PMF). PM2.5 (maximum concentration of 148.95 µg/m3 over 24 h) and PM1 (maximum concentration of 110.51 µg/m3 over 24 h) showed the highest concentrations during the heating season, together with the elements Cd, Pb, and Zn, which showed a significant presence in these fractions. On the other hand, PM2.5–10 (maximum concentration of 38.17 µg/m3 over 24 h) was significantly related to the elements Cu, Sb, Ba, Ca, Cr, Fe, Mg, and Al. High correlation coefficients (r ≥ 0.8) were found for the elements Mg, Ca, Fe, Al, Cd, Pb, and Zn in the PM1 fraction, Cd, Pb, and Zn in PM2.5, and Ba, Sb, Fe, Cu, Cr, Mg, Al, and Ca in PM2.5–10. Using PMF analysis, three major sources of PM (abrasion from tires and brakes, road dust resuspension/winter salting, and combustion processes) were identified for the PM2.5 and PM1 fractions, as well as for the coarse PM2.5–10 fraction. This study reveals the importance of non-exhaust PM emissions in the urban environment.

In situ ozone production is highly sensitive to volatile organic compounds in Delhi, India

Abstract. The Indian megacity of Delhi suffers from some of the poorest air quality in the world. While ambient NO2 and particulate matter (PM) concentrations have received considerable attention in the city, high ground-level ozone (O3) concentrations are an often overlooked component of pollution. O3 can lead to significant ecosystem damage and agricultural crop losses, and adversely affect human health. During October 2018, concentrations of speciated non-methane hydrocarbon volatile organic compounds (C2–C13), oxygenated volatile organic compounds (o-VOCs), NO, NO2, HONO, CO, SO2, O3, and photolysis rates, were continuously measured at an urban site in Old Delhi. These observations were used to constrain a detailed chemical box model utilising the Master Chemical Mechanism v3.3.1. VOCs and NOx (NO + NO2) were varied in the model to test their impact on local O3 production rates, P(O3), which revealed a VOC-limited chemical regime. When only NOx concentrations were reduced, a significant increase in P(O3) was observed; thus, VOC co-reduction approaches must also be considered in pollution abatement strategies. Of the VOCs examined in this work, mean morning P(O3) rates were most sensitive to monoaromatic compounds, followed by monoterpenes and alkenes, where halving their concentrations in the model led to a 15.6 %, 13.1 %, and 12.9 % reduction in P(O3), respectively. P(O3) was not sensitive to direct changes in aerosol surface area but was very sensitive to changes in photolysis rates, which may be influenced by future changes in PM concentrations. VOC and NOx concentrations were divided into emission source sectors, as described by the Emissions Database for Global Atmospheric Research (EDGAR) v5.0 Global Air Pollutant Emissions and EDGAR v4.3.2_VOC_spec inventories, allowing for the impact of individual emission sources on P(O3) to be investigated. Reducing road transport emissions only, a common strategy in air pollution abatement strategies worldwide, was found to increase P(O3), even when the source was removed in its entirety. Effective reduction in P(O3) was achieved by reducing road transport along with emissions from combustion for manufacturing and process emissions. Modelled P(O3) reduced by ∼ 20 ppb h−1 when these combined sources were halved. This study highlights the importance of reducing VOCs in parallel with NOx and PM in future pollution abatement strategies in Delhi.

Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea.

This study analyzed the changes in particulate matter concentrations according to land-use over time and the spatial characteristics of the distribution of particulate matter concentrations using big data of particulate matter in Daejeon, Korea, measured by Private Air Quality Monitoring Smart Sensors (PAQMSSs). Land-uses were classified into residential, commercial, industrial, and green groups according to the primary land-use around the 650-m sensor radius. Data on particulate matter with an aerodynamic diameter <10 µm (PM10) and <2.5 µm (PM2.5) were captured by PAQMSSs from September‒October (i.e., fall) in 2019. Differences and variation characteristics of particulate matter concentrations between time periods and land-uses were analyzed and spatial mobility characteristics of the particulate matter concentrations over time were analyzed. The results indicate that the particulate matter concentrations in Daejeon decreased in the order of industrial, housing, commercial and green groups overall; however, the concentrations of the commercial group were higher than those of the residential group during 21:00–23:00, which reflected the vital nighttime lifestyle in the commercial group in Korea. Second, the green group showed the lowest particulate matter concentration and the industrial group showed the highest concentration. Third, the highest particulate matter concentrations were in urban areas where commercial and business functions were centered and in the vicinity of industrial complexes. Finally, over time, the PM10 concentrations were clearly high at noon and low at night, whereas the PM2.5 concentrations were similar at certain areas.

Effect of infectious disease outbreak on air quality: Impact of COVID-19 on changes in particulate matter concentrations in Taiwan

Backgrounds: Abundant research has shed light on how climate change instigates and propels the spread of infectious diseases. Recently published literature reported that global epidemic of COVID-19 has reduced air pollutant emissions in several metropolises due to lockdown measures. This study aims to compare the ambient particulate matter concentrations in Taiwan in the past year during the same time frame. Methods: We examined air quality in 17 counties from Taiwan; concentrations of PM1.0, PM2.5, and PM10 detected by low-cost air quality sensors (LCS) from January to March of 2019 and 2020, were analyzed to demonstrate the spatiotemporal pattern air pollution prior to and during the COVID-19 outbreak. We examined monitoring data from 674 LCS and calculated monthly and seasonal mean levels, as well as Wilcoxon signed-rank test to assess whether changes in concentrations were statistically significant. Particulate matter concentrations detected by another type of LCS, hereafter denoted as microsensors, were also analyzed. Results: Ambient concentrations of PM1.0, PM2.5, and PM10 in January of 2019 did not differ significantly from those detected in 2020. However, decreases in PM2.5 levels in February of 2020 reached statistical significance when we compared to levels detected in February of the previous year (30.35 10.38 and 28.13 8.22 μg/m3, p =0.027). Differences in monthly mean PM2.5 concentrations detected by microsensors were also statistically significant (22.57 7.05 and 21.61 7.13 μg/m3, p =0.035). As the pandemic progressed and social distancing encouraged, decreases in levels of PM1.0, PM2.5, and PM10 in March of 2020 were statistically significant (p=0.004, p=0.0002, p&lt;0.001). Similar decreases were detected by microsensors across Taiwan, with levels of PM2.5 decreased from 24.40 to 21.39 μg/m3, p&lt;0.001). Conclusion: Initial analysis showed even though Taiwan did not enforce full nationwide lockdown amidst COVID-19 pandemic, reductions in anthropogenic activities have lowered air pollution levels.

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides, volatile organic compounds, and ammonia emissions

ABSTRACTAn ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NOx) emissions by the year 2030. Two high PM2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NOx and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM2.5 concentrations. However, the targeted NOx reductions for ozone were not found to be optimal for reducing PM2.5 concentrations. Ammonia emission reductions reduced PM2.5 and this might be considered as part of a PM2.5 control strategy.Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NOx emission reductions. Their strategy will affect both ozone and PM2.5. Two episodes that occurred during September and November 2008 with high PM2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM2.5 concentrations but its effect on PM2.5 concentrations is not optimal.

Comparison of Source Apportionment and Sensitivity Analysis in a Particulate Matter Air Quality Model

Two efficient methods to study relationships between particulate matter (PM) concentrations and emission sources are compared in the three-dimensional comprehensive air quality model with extensions (CAMx). Particulate source apportionment technology (PSAT) is a tagged species method that apportions concentrations of PM components to their respective primary precursors, e.g., sulfate is apportioned to SOx, nitrate to NOx, etc. The decoupled direct method (DDM) calculates first-order sensitivities of PM concentrations to model inputs. Both tools were applied to two month long (February and July) PM modeling episodes and evaluated against changes in PM concentrations due to various emission reductions. The results show that source contributions calculated by PSAT start to deviate from the actual model responses as indirect effects from limiting reactants or nonprimary precursor emissions become important The DDM first-order sensitivity is useful for determining source contributions only if the model response to input changes is reasonably linear. For secondary inorganic PM, the response is linear for emission reductions of 20% in all cases considered and reasonably linear for reductions of 100% inthe case of on-road mobile sources. The model response for secondary organic aerosols and primary PM remains nearly linear to 100% reductions in anthropogenic emissions.

Particulate matter grain‐size characteristics and flocculation in a partially mixed estuary

ABSTRACTThe concentration and grain size of the natural and deflocculated inorganic suspended particulate matter were measured along the length of the Miramichi Estuary and interpreted with respect to flocculation and transport properties. Changes in particulate matter concentration are associated with regular changes in grain‐size characteristics. In the turbidity maximum region of the estuary the suspended matter occurs mostly as large flocculated particles whereas, in the waters with lower particle concentrations, a larger proportion of the material occurs as fine material. At higher concentrations natural floc modes and inorganic grain modes vary simultaneously but at low concentrations the two modes vary inversely. This modal relationship and the variation in organic matter within the estuary is proposed to result from variation in inorganic—organic composition of flocs. Increase in settling rates due to flocculation is believed to increase the trapping effect of the estuarine circulation that produces the turbidity maximum.