Similarities and Differences in the Temporal Variability of PM2.5 and AOD Between Urban and Rural Stations in Beijing

Abstract

Surface particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) and column-integrated aerosol optical depth (AOD) exhibits substantial diurnal, daily, and yearly variabilities that are regionally dependent. The diversity of these temporal variabilities in urban and rural areas may imply the inherent mechanisms. A novel time-series analysis tool developed by Facebook, Prophet, is used to investigate the holiday, seasonal, and inter-annual patterns of PM2.5 and AOD at a rural station (RU) and an urban station (UR) in Beijing. PM2.5 shows a coherent decreasing tendency at both stations during 2014–2018, consistent with the implementation of the air pollution action plan at the end of 2013. RU is characterized by similar seasonal variations of AOD and PM2.5, with the lowest values in winter and the highest in summer, which is opposite that at UR with maximum AOD, but minimum PM2.5 in summer and minimum AOD, but maximum PM2.5 in winter. During the National Day holiday (1–7 October), both AOD and PM2.5 holiday components regularly shift from negative to positive departures, and the turning point generally occurs on October 4. AODs at both stations steadily increase throughout the daytime, which is most striking in winter. A morning rush hour peak of PM2.5 (7:00–9:00 local standard time (LST)) and a second peak at night (23:00 LST) are observed at UR. PM2.5 at RU often reaches minima (maxima) at around 12:00 LST (19:00 LST), about four hours later (earlier) than UR. The ratio of PM2.5 to AOD (η) shows a decreasing tendency at both stations in the last four years, indicating a profound impact of the air quality control program. η at RU always begins to increase about 1–2 h earlier than that at UR during the daytime. Large spatial and temporal variations of η suggest that caution should be observed in the estimation of PM2.5 from AOD.

Mapping Carbon Monoxide Pollution of Residential Areas in a Polish City

“…When analyzing the scientific works [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60] as well as legal provisions [14], it can be stated that there is currently incomplete information regarding the air quality when it comes to carbon monoxide, which results from a few reasons:…”

“…This level was over 30 mg/m 3 /year; • mathematical modeling of transport and the changes of substances in the air do not account for all air pollutants that were indicated in the European Union directive [14]. Advanced research methods are applied for the assessment of other air pollutants [50][51][52][53] and often the level of carbon monoxide derived from motor vehicle traffic is often overlooked, though a model based on the maximum concentration of CO for the given terrain accounting for dispersion in the vertical and horizontal direction was developed in a publication [55]. The Hadipour team also accounted for the distance of residential areas from the urban transportation network and based the modeling of carbon monoxide pollution on road traffic data.…”

Variation of Aerosol Optical Depth Measured by Sun Photometer at a Rural Site near Beijing during the 2017–2019 Period

“…As shown in Figure 8a, The CE-318 AOD in Gucheng is almost constant from 8:00 a.m. to 2:00 p.m., with a mean value of 0.530, and rises slowly after 2:00 p.m., finally reaching 0.732. Elevated AOD in the afternoon may be associated with secondary aerosol formation [73]. The PM 2.5 concentrations in Baoding (Huadian II) were high in the morning and evening (above 0.9 µg/m 3 ) and low in the noon period (below 0.4 µg/m 3 ), as shown in Figure S6.…”

Case-Crossover Spatial Lag Grid Differences Between Aerosol Optical Depth-PM2.5 and Respiratory-Cardiovascular Emergency Department Visits and Inpatient Hospitalizations in Baltimore, Maryland, USA: Identification of Homogeneous Spatial Areas

“…The majority of these PM2.5 filter-based monitors measure PM2.5 concentration levels every three or six days in urban areas with higher population density [3,32,38]. Few studies have evaluated differences between urban-rural areas [16,[43][44][45][46][47][48]. Increasing the number of stationary PM2.5 air monitors in rural areas would provide accurate readings of fine PM concentration levels and decrease spatial heterogeneity.…”

“…An alternative would be to utilize remote sensing methodology. Increased emphasis on using remote sensing would result in obtaining cost-effective readings of PM2.5 concentration levels in urban and rural areas [3,6,9,13,16,20,22,24,30,32,[46][47][48]. Different investigators have combined satellite AOD readings with PM2.5 air monitor measurements by utilizing Hierarchical Bayesian Model (HBM) or other statistical procedures to attain continuous (homogeneous) temporal-spatial aerosol concentration level fused surfaces that represent ambient PM2.5 concentration levels in urban areas that have air monitors and in rural areas that do not have air monitors [3, 6, 9, 13-16, 20, 22, 30, 32, 48, 51, 52, 55, 59-61, 64-66, 68-74, 77, 79-82].…”