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Under the goal of "achieving carbon peak by 2030 and carbon neutrality by 2060", how to select the type of fresh air system has become a key area of energy conservation. The method of outdoor design PM2.5 concentration is one of the important factors affecting the selection of fresh air filtration system. This paper first analyzed the PM2.5 concentration values of 31 cities in China from 2017 to 2020 based on mathematical induction, and next gave the recommended coefficient K under six urban economic regions methods in combination with the actual situation. Finally, the selection of air filters in five typical cities was taken as an example, the differences in recommended coefficient K and selection of outdoor design PM2.5 concentration under different recommended methods were compared and analyzed. The results showed that the recommended coefficient K under the six economic regions could meet the required K value needs of the region. The recommended coefficient K by the six economic regions methods based on per capita GDP is the best. Under that conditions, the recommended coefficient K of the five typical cities under strict and normal conditions differs from the average K values of the six methods by 0.06 and 0.04. This paper will provide a new method for the correct selection of outdoor design PM2.5 concentration in fresh air systems to achieve the dual carbon energy-saving goal. [ABSTRACT FROM AUTHOR]

With the progress of urbanization and industrialization in China, the consumption of fossil fuels blows up. The burning of fossil fuels releases large amounts of particulate matter, leads to smog, and the air quality is gradually getting worsen. Previous studies have shown that vegetation can effectively reduce airborne particles with different size fractions. And large amounts of previous studies pointed to the adsorption ability of urban forest for particles larger than 2.5 μm. The capacity of roadside plants for the capture of fine particles, especially for those smaller than 2.5 μm has been rarely reported. In this study, five external factors including leaf orientation, leaf height, planting location, planting form, and pollution concentration were tested to evaluate their impact on the dust retention capacity of different roadside plants. The results indicate that significant interspecies was found between tested plant species, and with the change of different external factors, the capturing capacity for the same roadside plants varied. The change of leaf orientation has limited effects on the amount of captured fine particles for the tested plants. While, the amount of captured particulate matter by leaves was inversely proportional to its growth height. Plants locating in the central of the road showed significantly higher capturing capacity than they, when they was set alongside the road. The total amount of captured fine particle by Ligustrum japonicum locating in the central green belt of road was about 5 times higher than it when it was planted in the green belt alongside the road. In addition, the correlation between the capturing capacity of roadside plants and its distance to the street curb was found to be negative. Plants have been widely accepted as an environmentally friendly air particulate filter that can effectively remove fine particulate matter which can be harmful to humans. By analyzing the dust retention of plant leaves, this paper discussed the influence of different factors such as traffic pressure, planting position, and leaf orientation on the capture ability of roadside plants, in addition, we investigated particulate matter with a smaller size (PM0.22). The mainly objective of this study is to investigate the factors affecting the dust retention efficiency of roadside plants and roadside plants as phytoremediation to improve city air quality which consists with the purpose of the journal. [ABSTRACT FROM AUTHOR]

PM2.5 is an important global air pollution issue. PM2.5 causes various problems on the environment and human health. Even though PM2.5 of the outdoor air is eliminated by particulate air filters, the chemicals adsorbed on the filtered PM2.5 can be outgassed and introduced into the semiconductor manufacturing facilities and processes, thus causing defects on the semiconductor chips by producing particles and haze as airborne molecular contamination. Therefore, estimating the amount of the outgassing from PM2.5 is a very important factor to control gaseous contaminants in the semiconductor industry. In this paper, the PM2.5 samples at different PM2.5 mass loadings were collected in Xi’an, China and evaluated using the soft X-ray radiolysis method for determining the relation between the outgassing and the PM2.5 mass loading. The PM2.5 samples were also analyzed by several methods for quantifying organic and elemental carbons, water soluble ions, and organic compounds in the PM2.5 samples. The outgassing measured by the soft X-ray method increased linearly with the PM2.5 mass loading, and the chemical analyses explained that the organic carbon (OC) was dominantly detected by the soft X-ray method in the current study. Moreover, the sampling location of the PM2.5 affected on the organic compounds of the PM2.5. [ABSTRACT FROM AUTHOR]

In contrast to a majority of reported damage-cost literature being focused on outdoor pollution, this paper describes the development of a protocol that links population exposure data with reported epidemiological concentration-response coefficients. A change in indoor particulate level is expressed as a change in total exposure levels, which is then linked with a corresponding change in ambient particulate concentrations before evaluating the associated health benefits. In this study, the development of protocol is illustrated by using a typical office building environment and daily time activity patterns of office occupants in Hong Kong. Our results indicate that some benefit gains for the owners-employers and the society would be anticipated if certain filter set configurations had been adopted. However, the amount of benefit gains for the owners-employers is shown to be increased with the average salary level of employees and the duration of their stay in offices. [Copyright &y& Elsevier]