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The annual mean PM 2.5 mass concentration has decreased because of the stringent emission controls implemented in Beijing, China in recent years, whereas the nitrate NO 3 – mass fraction in PM 2.5 increases gradually. Low-visibility events occur frequently even though PM 2.5 pollution has been mitigated significantly, with the daily mean PM 2.5 mass concentration mostly less than 75 μg/m3. In this study, the non-linear relationship was analyzed between atmospheric visibility and PM 2.5 based on chemical composition from a two-year field observation. Our results showed that NO 3 – became the main constituent of PM 2.5 , especially during the haze pollution episodes. A localized parameterization scheme was proposed between the atmospheric extinction coefficient (σ ext) and major chemical constituents of PM 2.5 by multiple linear regression (MLR). The contribution of NO 3 – to σ ext increased with increasing air pollution, and NO 3 – became the most important contributor for PM 2.5 above 75 μg/m3. The visibility decreased with increasing NO 3 – mass fraction for the same PM 2.5 mass concentration when PM 2.5 was above 20 μg/m3. The hygroscopicity of PM 2.5 increased with increasing mass fraction of hygroscopic NO 3 –. These results stressed the importance of reducing particulate NO 3 – and its precursors (for instance, NH 3) through effective emission control measures as well as the tightening of PM 2.5 standards to further improve air quality and visibility in Beijing. [Display omitted] • Nitrate accounted for the largest mass fraction in PM 2.5 during pollution episodes. • Nitrate contributed mostly to visibility impairment during the haze days. • Visibility degraded significantly with increasing nitrate fraction in PM 2.5. [ABSTRACT FROM AUTHOR]

Urban functional zones are important space carriers for urban economic and social function. The accurate and rapid identification of urban functional zones is of great significance to urban planning and resource allocation. However, the factors considered in the existing functional zone identification methods are not comprehensive enough, and the recognition of functional zones stops at their categories. This paper proposes a framework that combines multisource heterogeneous data to identify the categories of functional zones and draw the portraits of functional zones. The framework comprehensively describes the features of functional zones from four aspects: building-level metrics, landscape metrics, semantic metrics, and human activity metrics, and uses a combination of ensemble learning and active learning to balance the identification accuracy of functional zones and the labeling cost during large-scale generalization. Furthermore, sentiment analysis, word cloud analysis, and land cover proportion maps are added to the portraits of typical functional zones to make the image of functional zones vivid. The experiment carried out within the Fifth Ring Road, Haidian District, Beijing, shows that the overall accuracy of the method reached 82.37% and the portraits of the four typical functional zones are clear. The method in this paper has good repeatability and generalization, which is helpful to carry out quantitative and objective research on urban functional zones. [ABSTRACT FROM AUTHOR]

Abstract To investigate aerosol optical properties relevant to pollutant level controls in place in Beijing, particulate matters with diameter <2.5 μm (PM 2.5) mass concentration, aerosol absorption ( σ a p ) and scattering ( σ s p ) coefficients were continuously measured from January 2014 to March 2017 at an urban site Peking University Atmosphere Environment MonitoRing Station (PKUERS). Our results showed that PM 2.5 , σ a p , and σ s p all decreased, especially from 2014 to 2015. Note that, a significant decrease of σ a p in autumn and σ s p in winter was responsible for the decrease of the year by year average. PM 2.5 , σ a p and σ s p exhibited a pronounced bi-peak diurnal variation, which was attributed to the traffic emissions. The wind dependence analysis revealed that σ a p was mainly influenced by local emissions but σ s p was influenced by both local emissions and regional transport. The potential spatial source origins of σ s p in Beijing were investigated using the potential source contribution function (PSCF). The results indicated that the potential source regions that influence σ s p of Beijing were mainly from south and west of Beijing but slightly varied with different years and seasons. Highlights • 3-year aerosol optical property data of Beijing were analyzed to investigate aerosol optical properties relevant to pollutant level controls in place in Beijing. • Influencing factors of aerosol optical properties were explored. • PSCF was applied to identify the potential source origins of the aerosol optical properties. [ABSTRACT FROM AUTHOR]