Aerosol Optical Properties and Direct Radiative Effects over Central China

Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2.5 over Wuhan, China

Large amounts of aerosols remain in the residual layer (RL) after sunset, which may be the source of the next day’s pollutants. However, the characteristics of the nocturnal residual layer height (RLH) and its effect on urban environment pollution are unknown. In this study, the characteristics of the RLH and its effect on fine particles with diameters <2.5 μm (PM2.5) were investigated using lidar data from January 2017 to December 2019. The results show that the RLH is highest in summer (1.55 ± 0.55 km), followed by spring (1.40 ± 0.58 km) and autumn (1.26 ± 0.47 km), and is lowest in winter (1.11 ± 0.44 km). The effect of surface meteorological factors on the RLH were also studied. The correlation coefficients (R) between the RLH and the temperature, relative humidity, wind speed, and pressure were 0.38, −0.18, 0.15, and −0.36, respectively. The results indicate that the surface meteorological parameters exhibit a slight correlation with the RLH, but the high relative humidity was accompanied by a low RLH and high PM2.5 concentrations. Finally, the influence of the RLH on PM2.5 was discussed under different aerosol-loading periods. The aerosol optical depth (AOD) was employed to represent the total amount of pollutants. The results show that the RLH has an effect on PM2.5 when the AOD is small but has almost no effect on PM2.5 when the AOD is high. In addition, the R between the nighttime mean RLH and the following daytime PM2.5 at low AOD is −0.49, suggesting that the RLH may affect the following daytime surface PM2.5. The results of this study have a guiding significance for understanding the interaction between aerosols and the boundary layer.

An Investigation of Vertically Distributed Aerosol Optical Properties over Pakistan Using CALIPSO Satellite Data

The vertically distributed aerosol optical properties are investigated over Pakistan utilizing the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Level 2 products from 2007 to 2014. For a better understanding of the spatiotemporal characteristics of vertical aerosol layers, the interannual and seasonal variations of nine selected aerosol parameters such as the AOD of the lowest aerosol layer (AODL), the base height of the lowest aerosol layer (HL), the top height of the highest aerosol layer (HH), the volume depolarization ratio of the lowest aerosol layer (DRL), the color ratio of the lowest aerosol layer (CRL), total AOD of all the aerosol layers (AODT), the number of aerosol feature layers (N), the thickness of the lowest aerosol layer (TL), the AOD proportion for the lowest aerosol layer (PAODL) for both day and night times are analyzed. The results show AODT increased slightly from 2007 to 2014 over Pakistan, and relatively high AODT exists over the Punjab and Sindh (southern region), which might be owing to the high level of economic development, frequent dust storms, and profound agricultural activities (anthropogenic emissions). AODT increases from north to south. The reason may be that the southern region is rapidly urbanized and is near the desert. The northern region is dominated by agricultural land, and cities are usually semi-urbanized. The highest AODT appears in summer compared to the other seasons, and during daytime compared to nighttime. The HL and HH vary significantly, owing to the topography of Pakistan. The N is relatively large over Punjab and Sindh compared to the other regions, which might be caused by relatively stronger atmospheric convections. The spatial distribution of the TL showed an inverse relationship with the topography as lower values are observed over elevated regions such as Gilgit-Baltistan and Jammu-Kashmir. The value of the PAODL indicates that 77% of the total aerosols are mainly concentrated in the lowest layer of the atmosphere over Pakistan. The higher values of DRL and CRL indicate non-spherical and large particles over Balochistan and Sindh, which might be related to the proximity to the desert. This study provides very useful information about vertically distributed aerosol optical properties which could help researchers and policymakers to regulate and mitigate air pollution issues of Pakistan.

Satellite-derived spatiotemporal PM2.5 concentrations and variations from 2006 to 2017 in China

The PM_2.5 concentration is an important evaluation index for the global Sustainable Development Goals (SDGs) for its negative impacts on human health. Last decade, several fine particulate pollution episodes occurred in the vast area of China. In response to this, the Chinese government has stepped up efforts to tackle air pollution. In this paper, the temporal trends of PM_2.5 and the quantitative potential impact of environmental governance on PM_2.5 are analyzed for China. Due to the lack of historical records, a two-stage model was used to estimate the historical PM_2.5 concentrations, combined with the newly released satellite-based aerosol optical depth (AOD) product (MODIS Collection 6.1) and other data. The estimated PM_2.5 concentrations showed strong consistency with the surface observations. Furthermore, significant seasonal variations existed in the PM_2.5 concentrations and the temporal trends were captured, especially in city clusters. Then eight major city clusters were selected as typical samples. All the city clusters showed decrease trends in recent years, with PM_2.5 concentrations in these regions decreased by 0.269-1.604 μg m^-3 year^-1. From 2006 to 2017, the annual PM_2.5 concentrations decreased by 7.83%-26.35% in the major city clusters among China. Technological innovation and environmental governance play an important role in the decrease of PM_2.5. In order to quantify the influence of governance, environmental regulation intensity and synergy were applied as the indicators of the internal governance and co-governance in each city cluster. In most city clusters, PM_2.5 concentrations were significantly negatively correlated with regional internal governance and co-governance (R = -0.596 to -0.930, p < 0.05), and the effect on PM_2.5 lasted for several years. However, 1- to 2-year lagged effect was found for governance, which means that the regulatory measures should be enhanced to decrease PM_2.5 in the future to achieve the SDGs in China.

Contrasting changes in snow cover and its sensitivity to aerosol optical properties in Hindukush-Karakoram-Himalaya region

Snow cover plays a major role in the earth's climate system. The stability of the snow mass over Hindukush-Karakoram-Himalaya (HKH) in contrast to the worldwide retreat of mountainous glaciers and its relation to aerosol concentration remains poorly understood. The proposed study focused on the understanding of this relationship between various snow parameters and the optical properties of atmospheric aerosols over the HKH region of Northern Pakistan between March and June for a prolonged study period from 2005 to 2015. The aerosol's optical properties were retrieved from snow covered pixels in the study area to avoid the contamination of snow albedo (SA) by other features of land surfaces. The results revealed an increasing trend in the snow cover area (SCA) at the rate of 577.3, 1090.6 and 652.3 km²/year in March, May and June, respectively, with a decrease in April due to the uneven distribution of SCA during 2005-2015. The results revealed a strong positive correlation (R = 0.77) between SCA and SA, whereas SCA and SST were negatively correlated (R = -0.82) during the study period. The Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) indicated the presence of scattering and absorbing aerosols (e.g., dust, polluted dust, and smoke) both at high and low altitudes. However, the diminution of aerosol concentration was caused by their short time span in atmosphere and the occurrence of snowfall that washed them out from the snow at high altitudes. The findings indicated an increased SCA, with contrasting behavior in the ablation period. However, the presence of aerosols demands proper attention, to monitor any future threat to the high-altitude cryosphere.

Evaluation of the Aqua-MODIS C6 and C6.1 Aerosol Optical Depth Products in the Yellow River Basin, China

In this study, Aqua-Moderate Resolution Imaging Spectroradiometer (MODIS) Collection (C6) and C6.1 Dark Target aerosol optical depth (AOD) retrievals at 3 km (DT3K) and 10 km (DT10K), Deep Blue AOD retrievals at 10 km (DB10K), and combined DT and DB (DTB) AOD retrievals at 10 km resolutions were validated from 2002 to 2014 against ground-based sunphotometer AOD measurements obtained from the Chinese aerosol remote sensing network (CARSNET). The CARSNET AOD data were obtained for sites at Mt. Waliguan (MW), Lanzhou (LZ), Ulate (UL), and Zhengzhou (ZZ) located in the Yellow River basin (YERB) region, China. Errors and agreement between satellite and ground data were reported using Pearson’s correlation (R) and relative mean bias (RMB). Results showed that the DT3K C6.1 highest quality flag (QF = 3) AOD retrievals were well correlated with the sunphotometer AOD data, with an R of 0.82 and an RMB of 1.01. Overestimation and underestimation in DT AOD retrievals were observed for AOD > 1.1 and AOD < 1.1, respectively. A significant underestimation of 37% in DB10K AOD retrievals was observed across all the sites except ZZ, which was indicated by a low-value RMB (0.63). Spatial distribution maps showed high AOD values (>0.8) over the lower part of the YERB and low AOD values (<0.4) across the upstream part of the YERB. This might be due to a large number of aerosol emissions over the lower developed areas and a scarcity of aerosols over the upstream mountain areas. Overall, this study supports the use of DT10K C6.1 AOD retrievals over the western semi-arid and arid regions of the YERB and DTB10K AOD retrievals over the north-central water system and eastern plain regions of the YERB.

Temporal characteristics of aerosol optical properties over the glacier region of northern Pakistan

Glacier melting due to light-absorbing aerosol has become a growing issue in recent decades. The emphasis of this study is to examine aerosol loadings over the high mountain glacier region of northern Pakistan between 2004 and 2016, with sources including local emissions and long-range transported pollution. Optical properties of aerosols were seasonally analyzed over the glacier region (35-36.5°N; 74.5-77.5°E) along with three selected sites (Gilgit, Skardu, and Diamar) based on the Ozone Monitoring Instrument (OMI). The aerosol sub-type profile was analyzed with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to understand the origin of air masses arriving in the study region. The highest values of aerosol optical depth (AOD) and single scattering albedo (SSA) occurred during spring, whereas aerosol index (AI) and absorption AOD (AAOD) exhibited maximum values in winter and summer, respectively. The minimum values of AOD, AI, AAOD, and SSA occurred in winter, autumn, winter, and autumn, respectively. The results revealed that in spring and summer the prominent aerosols were dust, whereas, in autumn and winter, anthropogenic aerosols were prominent. Trend analysis showed that AI, AOD, and AAOD increased at the rate of 0.005, 0.006, and 0.0001 yr^-1, respectively, while SSA decreased at the rate of 0.0002 yr^-1. This is suggestive of the enhancement in aerosol types over the region with time that accelerates melting of ice. CALIPSO data indicate that the regional aerosol was mostly comprised of sub-types categorized as dust, polluted dust, smoke, and clean continental. The types of aerosols defined by OMI were in good agreement with CALIPSO retrievals. Analysis of the National Oceanic and Atmospheric Administration Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model revealed that air parcels arriving at the glacier region stemmed from different source sites.

Assessment of MERRA-2 Surface PM2.5 over the Yangtze River Basin: Ground-based Verification, Spatiotemporal Distribution and Meteorological Dependence

A good understanding of how meteorological conditions exacerbate or mitigate air pollution is critical for developing robust emission reduction policies. Thus, based on a multiple linear regression (MLR) model in this study, the quantified impacts of six meteorological variables on PM2.5 (i.e., particle matter with diameter of 2.5 µm or less) and its major components were estimated over the Yangtze River Basin (YRB). The 38-year (1980–2017) daily PM2.5 and meteorological data were derived from the newly-released Modern-Era Retrospective Analysis and Research and Application, version 2 (MERRA-2) products. The MERRA-2 PM2.5 was underestimated compared with ground measurements, partly due to the bias in the MERRA-2 Aerosol Optical Depth (AOD) assimilation. An over-increasing trend in each PM2.5 component occurred for the whole study period; however, this has been curbed since 2007. The MLR model suggested that meteorological variability could explain up to 67% of the PM2.5 changes. PM2.5 was robustly anti-correlated with surface wind speed, precipitation and boundary layer height (BLH), but was positively correlated with temperature throughout the YRB. The relationship of relative humidity (RH) and total cloud cover with PM2.5 showed regional dependencies, with negative correlation in the Yangtze River Delta (YRD) and positive correlation in the other areas. In particular, PM2.5 was most sensitive to surface wind speed, and the sensitivity was approximately −2.42 µg m−3 m−1 s. This study highlighted the impact of meteorological conditions on PM2.5 growth, although it was much smaller than the anthropogenic emissions impact.