Changes in aerosol loading before, during and after the COVID-19 pandemic outbreak in China: Effects of anthropogenic and natural aerosol

Human activity's impact on urban vegetation in China during the COVID-19 lockdown: An atypical anthropogenic disturbance

The COVID-19 lockdown led to reduced industrial and transportation emissions in Chinese cities, improving air quality and affecting large-scale vegetation. This study examines changes in net primary productivity (NPP) across 283 prefecture-level cities in China (PCC) during the lockdown, focusing on aerosol optical depth (AOD), nighttime light (NTL), temperature, and precipitation. Results from spring 2020 show that 53.5% of cities experienced increased NPP, with greater gains in cities with high industrial and traffic activity due to reduced AOD. Structural equation modeling revealed that urban characteristics, particularly industrial levels, influenced NPP primarily through changes in AOD, with human activity shifts playing a larger role than climate factors. In cities with substantial NPP changes, human activity effects were especially pronounced. These findings highlight the complex interactions among urban characteristics, environmental changes, and vegetation responses, offering insights for ecological management and urban planning in the face of future disruptions.

Impact of improved air quality during complete and partial lockdowns on surface energetics and atmospheric boundary layer

Long-term measurements of meteorological, radiation, and aerosol profiles at a rural location have been used to study (i) the differences in spatial and vertical variation of aerosols during complete and partial lockdowns (LDs), (ii) the impact of these LDs on surface energetics and atmospheric boundary layer (ABL) height, and (iii) underlying processes that explain the variations in the above-measured parameters during LDs from the climatology. Large reduction in aerosol optical depth (AOD) and lidar (aerosol) backscatter up to the ABL height during complete and partial LD periods relative to climatology is observed, indicating improved air-quality during these periods. The reduction, in fact, is more during the partial LD imposed in 2021 (46 % in AOD) than during the complete LD (40 %) in 2020 over most part of peninsular India, partly due to higher rainfall during LD period of 2021. The reduction in aerosols during the LD periods increased the shortwave radiation by 59.8 W m-2 and 76.9 W m-2 in 2020 and 2021, respectively, relative to climatology. Contrary to the expected increase in temperature and ABL height due to higher insolation, both decreased during the LD. On the other hand, the absolute humidity increased during the above period. To shed more light on the above observations, rainfall and turbulent heat fluxes during the above periods were examined. More rain events and higher rain amount are observed during the LD periods of both years, which increased the soil moisture and modified the portioning of net radiation into turbulent fluxes. It increased the latent heat flux considerably and thereby the absolute humidity. On the other hand, the sensible heat flux has decreased, which in turn reduced the temperature and also the ABL height. The present study highlights the complex interplay of natural and anthropogenic processes in modifying land-atmospheric interaction and ABL dynamics.

Source-specific light absorption and radiative effects decreases and indications due to the lockdown

The 'extreme' emission abatement during the lockdown (from the end of 2019 to the early 2020) provided an experimental period to investigate the corresponding source-specific effects of aerosol. In this study, the variations of source-specific light absorption (babs) and direct radiative effect (DRE) were obtained during and after the lockdown period by using the artificial neural network (ANN) and source apportionment environmental receptor model. The results showed that the babs decreased for all sources during the two periods. The most reductions were observed with ∼90% for traffic-related emissions (during the lockdown) and ∼85% for coal combustion (after the lockdown), respectively. Heightened babs (370 nm) values were obtained for coal and biomass burning during the lockdown, which was attributed to the enhanced atmospheric oxidization capacity. Nevertheless, the variations of babs (880 nm) after the lockdown was mainly due to the weakening of oxidation and reduced emissions of secondary precursors. The present study indicated that the large-scale emission reduction can promote both reductions of babs (370 nm) and DRE (34-68%) during the lockdown. The primary emissions decrease (e.g., Traffic emission) may enhance atmosphere oxidation, increase the ultraviolet wavelength light absorption and DRE efficiencies. The source-specific emission reduction may be contributed to various radiation effects, which is beneficial for the adopting of control strategies.

Vegetation net primary productivity in urban areas of China responded positively to the COVID-19 lockdown in spring 2020

To prevent the spread of COVID-19, China implemented large-scale lockdown measures in early 2020, resulting in a marked reduction in human activities over a short period. Studies have explored environmental changes during lockdowns, lacking analysis of response of net primary productivity (NPP) to lockdowns, especially for diverse vegetation types. Correlation between NPP and impact factors during lockdowns remains unclear. Through Google Earth Engine, we evaluated spatial-temporal changes in spring NPP at multiple scales during lockdown period (LD, 2020) compared with unlocked period (UL, 2017-2019) by remote sensing data in urban areas of China. Changes in four impact factors, aerosol optical depth (AOD) and photosynthetically active radiation (PAR) (via remote sensing data), alongside temperature (TEM) and precipitation (PRE) (via meteorological data) were explored. Additionally, geodetector, a valuable statistical tool for detecting the driving ability of various elements, was employed to explore the underlying causes of vegetation changes during LD. In the spring of LD: 1) National urban NPP generally increased (+6.50 %), notably in Northeast China (NE), North China (N) and East China (E). Besides, overall urban AOD decreased (-3.64 %), notably in N and Central China (C). National urban PAR increased (+2.7 %), particularly in C and Northwest China (NW). However, overall urban TEM (-0.06 %) and PRE (-1.21 %) changed negatively. 2) NPP in all three vegetation types in urban areas enhanced, with change rates: croplands > forests > grasslands. Evident enhancements occurred in the forests and croplands in N, and the grasslands in NE. 3) Through geodetector, during LD, AOD (q = 0.223) and TEM (q = 0.272) emerged as the dominant factors for NPP. Compared with UL, the explanatory power of AOD and PAR on NPP increased during LD. This study provides valuable insights into understanding the effects of short-term human activities on vegetation productivity, offering reference for the formulation of ecological and environmental policies.

Columnar optical-radiative properties and components of aerosols in the Arctic summer from long-term AERONET measurements

Aerosols as an external factor have an important role in the amplification of Arctic warming, yet the geography of this harsh region has led to a paucity of observations, which has limited our understanding of the Arctic climate. We synthesized the latest decade (2010-2021) of data on the microphysical-optical-radiative properties of aerosols and their multi-component evolution during the Arctic summer, taking into consideration the important role of wildfire burning. Our results are based on continuous observations from eight AERONET sites across the Arctic region, together with a meteorological reanalysis dataset and satellite observations of fires, and utilize a back-trajectory model to track the source of the aerosols. The summer climatological characteristics within the Arctic Circle showed that the aerosols are mainly fine-mode aerosols (fraction >0.95) with a radius of 0.15-0.20 μm, a slight extinction ability (aerosol optical depth ∼ 0.11) with strong scattering (single scattering albedo ∼0.95) and dominant forward scattering (asymmetry factor ∼ 0.68). These optical properties result in significant cooling at the Earth's surface (∼-13 W m-2) and a weak cooling effect at the top of the atmosphere (∼-5 W m-2). Further, we found that Arctic region is severely impacted by wildfire burning events in July and August, which primarily occur in central and eastern Siberia and followed in subpolar North America. The plumes from wildfire transport aerosols to the Arctic atmosphere with the westerly circulation, leading to an increase in fine-mode aerosols containing large amounts of organic carbon, with fraction as high as 97-98 %. Absorptive carbonaceous aerosols also increase synergistically, which could convert the instantaneous direct aerosol radiative effect into a heating effect on the Earth-atmosphere system. This study provides insights into the complex sources of aerosol loading in the Arctic atmosphere in summer and emphasizes the important impacts of the increasingly frequent occurrence of wildfire burning events in recent years.

The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m-3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m-3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020-2021. Despite a 22~62% decline in NOx levels in 2020-2021, the increased O3 caused a similar NO3- concentration (20.69~23.00 μg m-3) in 2020-2021 to that (22.93 μg m-3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019-2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future.

Detection of atmospheric aerosols and terrestrial nanoparticles collected in a populous city in southern Brazil

The main objective of this study is to analyze hazardous elements in nanoparticles (NPs) (smaller than 100 nm) and ultrafine particles (smaller than 1 µm) in Porto Alegre City, southern Brazil using a self-made passive sampler and Sentinel-3B SYN satellite images in 32 collection points. The Aerosol Optical Thickness proportion (T550) identification was conducted using images of the Sentinel-3B SYN satellite at 634 points sampled in 2019, 2020, 2021, and 2022. Focused ion beam scanning electron microscopy analyses were performed to identify chemical elements present in NPs and ultrafine particles, followed by single-stage cascade impactor to be processed by high-resolution transmission electron microscopy. This process was coupled with energy-dispersive X-ray spectroscopy and later analysis via secondary ion mass spectrometry. Data was acquired from Sentinel-3B SYN images, normalized to a standard mean of 0.83 µg/mg, at moderate spatial resolution (260 m), and modeled in the Sentinel Application Platform (SNAP) software v.8.0. Statistical matrix data was generated in the JASP software (Jeffreys's Amazing Statistics Program) v.0.14.1.0 followed by a K-means cluster analysis. The results demonstrate the presence of between 1 and 100 nm particles of the following chemical elements: Si, Al, K, Mg, P, and Ti. Many people go through these areas daily and may inhale or absorb these elements that can harm human health. In the Sentinel-3B SYN satellite images, the sum of squares in cluster 6 is 168,265 and in cluster 7 a total of 21,583. The use of images from the Sentinel-3B SYN satellite to obtain T550 levels is of great importance as it reveals that atmospheric pollution can move through air currents contaminating large areas on a global scale.

Quantifying the contributions of natural and anthropogenic dust sources in Shanxi Province, northern China

Dust storms have direct or indirect impacts on climate change and human health. Identifying and quantifying natural/anthropogenic dust sources can facilitate effective prevention and control of dust events. Based on surface real-time PM10 monitoring data, satellite remote sensing and the HYSPLIT model, this study determined the specific timing, coverage and sources of dust events in Shanxi Province, Northern China. Thus, a composite fingerprinting technique was established to quantify potential dust sources and dust contributions of single dust events. The dust oxidation model was validated, indicating that the composite fingerprinting technique was well suited to the study region. The results show that natural dust sources (67%) contributed more to the study region than anthropogenic dust sources. They were mainly from the northwest and north of the study region. Particularly, the contributions of Taiyuan (TY) and Linfen (LF) accounted for the largest (82%) and smallest (55%) proportions, respectively, both exceeding 50%. Anthropogenic dust sources contributed 33%, mainly from the east and south of the study region. The contribution of anthropogenic dust sources increased in the study region from north to south. In terms of potential dust sources, the Tengger Desert and Badain Jaran Desert (TDBD) contributed the most (26%), followed by the Otindag Sandy Land (OL) (22%). The Taklimakan Desert (TD) contributed the least (2%). The Middle Farmland region of the Hexi Corridor (HMF) in the west (15%) had the largest proportion of anthropogenic dust sources. Differences in the regional contribution of potential dust sources mainly resulted from winter winds, surface drought severity and particle size. At an insignificant distance from the study region, the contribution of potential dust sources was larger in the west than in the east and increased from south to north overall. These methods and findings can contribute to improving the ecological environment in Northern China.

Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal

Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.

A multi-objective framework to select numerical options in air quality prediction models: A case study on dust storm modeling

Numerical weather prediction models are very important tools in predicting severe weather phenomena such as dust storms. However, the prediction accuracy in these models depends on the options considered in the modeling. In this study, a multi-objective framework is presented to determine the optimal options of the weather research forecasting with chemistry (WRF-Chem) model. For this purpose, a severe dust storm that occurred in the center of Iran is considered and the effect of 10 options including grid (computational domain size, modeling start time, horizontal, vertical and temporal resolution), physical (initial conditions, boundary layer and land surface schemes) and chemical options (dust emission schemes and dust source functions) are investigated. In general, the results showed that the WRF-Chem model has a high ability to model dust storms, but its results depend on the options considered in the modeling. Evaluation of grid options showed that inappropriate selection of domain size and modeling start time can lead to the failure in dust storm forecasting. Also, the land surface scheme has the greatest impact on dust concentration among the physical options. In addition, chemical options have the greatest impact on the dust storm forecasting as well. Based on the proposed multi-objective framework, the optimal options for dust storm modeling were determined. The proposed approach is comprehensive and can be used for other atmospheric/air quality modeling.

Analysis of Factors Influencing Air Quality in Different Periods during COVID-19: A Case Study of Tangshan, China

This study aimed to analyze the main factors influencing air quality in Tangshan during COVID-19, covering three different periods: the COVID-19 period, the Level I response period, and the Spring Festival period. Comparative analysis and the difference-in-differences (DID) method were used to explore differences in air quality between different stages of the epidemic and different years. During the COVID-19 period, the air quality index (AQI) and the concentrations of six conventional air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃-8h) decreased significantly compared to 2017-2019. For the Level I response period, the reduction in AQI caused by COVID-19 control measures were 29.07%, 31.43%, and 20.04% in February, March, and April of 2020, respectively. During the Spring Festival, the concentrations of the six pollutants were significantly higher than those in 2019 and 2021, which may be related to heavy pollution events caused by unfavorable meteorological conditions and regional transport. As for the further improvement in air quality, it is necessary to take strict measures to prevent and control air pollution while paying attention to meteorological factors.