Spatio-Temporal Characteristics and Variation Pattern of the Atmospheric Particulate Matter Concentration: A Case Study of the Beijing–Tianjin–Hebei Region, China

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM2.5 and PM10, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 were analysed at yearly, seasonal, monthly, daily and hourly scales. The results indicated that (1) from 2015 to 2018, the annual average values of PM2.5 and PM10 concentrations and the PM2.5/PM10 ratio in the study area decreased each year; (2) the particulate matter (PM) concentration in winter was significantly higher than that in summer, and the PM2.5/PM10 ratio was highest in winter and lowest in spring; (3) the PM2.5 and PM10 concentrations exhibited a pattern of double peaks and valleys throughout the day, reaching peak values at night and in the morning and valleys in the morning and afternoon; and (4) with the use of an improved sine function to simulate the change trend of the monthly mean PM concentration, the fitting R2 values for PM2.5 and PM10 in the whole study area were 0.74 and 0.58, respectively. Moreover, the high-value duration was shorter, the low-value duration was longer, and the concentration decrease rate was slower than the increase rate.

COVID-19 and Air Pollution: A Spatial Analysis of Particulate Matter Concentration and Pandemic-Associated Mortality in the US

In 2019, a novel coronavirus, SARS-CoV-2, was first reported in Wuhan, China. The virus causes the disease commonly known as COVID-19, and, since its emergence, it has infected over 252 million individuals globally and taken the lives of over 5 million in the same time span. Primary research on SARS-CoV-2 and COVID-19 focused on understanding the biomolecular composition of the virus. This research has led to the development of multiple vaccines with great efficacy and antiviral treatments for the disease. The development of biomedical interventions has been crucial to combating this pandemic; additionally, environmental confounding variables that could have exacerbated the pandemic need further assessment. In this research study, we conducted a spatial analysis of particulate matter (PM) concentration and its association with COVID-19 mortality in the United States. Results of this study demonstrate a significant positive correlation between PM concentration levels and COVID-19 mortality; however, this does not necessarily imply a causal relationship. These results are consistent with similar studies in Italy and China, where significant COVID-19 cases and corresponding deaths were exhibited. Furthermore, maps of the data demonstrate clustering of COVID-19 mortality which suggest further investigation into the social determinants of health impacting the pandemic.

Air quality analysis for a metropolitan area in Romania during the first half of 2021

This paper aims to interpret and to use within a statistical analysis the concentration profiles of the main air pollutants – i.e., nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO) and suspended particulate matter (PM10) – results recorded during the first half of 2021 by two air quality monitoring stations in Craiova, which is an important metropolitan area in Southern Romania. Another goal of the paper is finding the best numerical diffusion model to fit the recorded values for PM10, as this pollutant seems to be the major problem, because its daily average is often higher than the European Union threshold, meaning that imperative measures have to be taken for reducing particulate matter concentration in Craiova (like in other major Romanian metropolitan areas), in order for Romania to get the exoneration regarding air pollution from the European Union and, of course, for its citizens to improve the quality of their lives.

UAVC: A New Method for Correcting Lidar Overlap Factors Based on Unmanned Aerial Vehicle Vertical Detection

A method to calibrate the overlap factor of Lidar is proposed, named unmanned aerial vehicle correction (UAVC), which uses unmanned aerial vehicles (UAVs) to detect the vertical distribution of particle concentrations. The conversion relationship between the particulate matter concentration and the aerosol extinction coefficient is inverted by the high-altitude coincidence of the vertical detection profiles of the UAV and Lidar. Using this conversion relationship, the Lidar signal without the influence of the overlap factor can be inverted. Then, the overlap factor profile is obtained by comparing the signal with the original Lidar signal. A 355 nm Raman-Mie Lidar and UAV were used to measure overlap factors under different weather conditions. After comparison with the Raman method, it is found that the overlap factors calculated by the two methods are in good agreement. The changing trend of the extinction coefficient at each height is relatively consistent, after comparing the inversion result of the corrected Lidar signal with the ground data. The results show that after the continuously measured Lidar signal is corrected by the overlap factor measured by this method, low-altitude aerosol information can be effectively obtained.

Differences in Airborne Particulate Matter Concentration in Urban Green Spaces with Different Spatial Structures in Xi’an, China

With the acceleration of urbanization and industrialization, air pollution is becoming one of the most serious problems in cities. Urban green spaces, as “green infrastructure”, are an important part of urban ecosystems for air purification. Therefore, 10 typical green spaces of urban parks in the city of Xi’an, China, were selected as study areas according to vegetation structure and species composition. Considering meteorological factors and time changes, the effects of the selected green spaces with different vegetation structures of different heights on the reduction in airborne particulate matter concentration were explored. The results showed that the following: (1) Temperature, relative humidity, wind speed, and air pressure had significant correlation with the concentration of airborne particulate matter at the different heights, and the correlations were the same at 1.5 and 5 m. (2) After heating in winter, the concentration of airborne particulate matter with different particle sizes increased significantly. The concentration of airborne particulate matter showed different trends throughout the day, and the small particles (PM1 and PM2.5) had a trend of “lower in the morning and evening, and higher at noon”, while the large particles (PM10 and TSP) gradually decreased over time. (3) In the selected green spaces with different vegetation structure types, the concentration of airborne particulate matter below the canopy (1.5 m) was generally higher than that in the middle of the canopy (5 m), but the effects of reducing the concentration of airborne particulate matter were consistent at the different heights. (4) The adsorption capacity of PM1 and PM2.5 concentration was strong in the partially closed broad-leaved one-layered forest (PBO), and poor in the partially closed broad-leaved multi-layered forest (PBM). Partially closed broad-leaved multi-layered forest (PBM) and partially closed coniferous and broad-leaved mixed multi-layered forest (PMM) also had strong dust-retention effect on PM10 and TSP, while closed broad-leaved one-layered forest (CBO) had a poor dust-retention effect. The results showed that the reduction effects of urban green spaces with different spatial structures on air particles were different, and were restricted by various environmental factors, which could provide a theoretical basis for the optimization of urban green space structure and the improvement of urban air quality.

APPLICATION OF LOW-COST PARTICULATE MATTER SENSORS FOR MEASUREMENT OF POLLUTANTS GENERATED DURING 3D PRINTING

This work presents measurement results of pollutants generated during 3D printing. The measure of pollutants is the concentration of particulate matter with a diameter of up to 2.5 μm (PM2,5). Materials acrylonitrile-butadiene-styrene (ABS), polyactide (PLA) for a 3D printer and low-cost particulate matter concentration sensors PMS3003, PMS7003 were used in the research. Research results show that low-cost sensors can be useful for monitoring pollution during 3D printing in offices, laboratories or private homes.

Environmental Factors Related to Non-compliant Health Behaviors in Urban-Dwelling Elderly

Purpose: The purpose of this study was to explore non-compliant health behaviors among urban-dwelling elderly and identify related environmental factors.Methods: This study analyzed integrated data from the 2017 Korean National Survey on the elderly and 2017 Annual Report of Air Quality in Korea (N=3,198). In this study, health behaviors included seven recommendations for promoting health. Social and physical environmental factors were selected based on Bronfenbrenner’s ecosystem theory, including air quality as an environmental factor. Hierarchical multiple regression analysis was used to analyze the data while controlling for general characteristics of the elderly.Results: The average score for non-compliant health behaviors was 3.05±1.03 among seven health behaviors. Hierarchical multiple regression showed the environmental factors related to non-compliant health behaviors were social activity participation (β=.15, p＜.001); interactions with friends, neighbors, and acquaintances (β=.06, p=.002); access to institutions and facilities (β=.06, p=.001); and particulate matter concentration (β=-.10, p＜.001).Conclusion: Our study findings emphasized that social activity participation, interactions with significant others, access to institutions and facilities, and particulate matter concentration should be considered when developing ecological interventions to improve health behaviors among the urban-dwelling elderly.

Methods for calculating the average particulate matter concentrations in the Krasnoyarsk city ground layer

The paper considers a method based on the Voronoi diagram for calculating the average particulate matter concentration in the surface layer of the Krasnoyarsk city air environment. We have used two methods to achieve this goal. The first method relied on buffer zones built in the immediate vicinity around monitoring posts. The second one uses the boundaries of the city of Krasnoyarsk.