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Based on remote sensing images and measurements of soil organic carbon content (including 28 sample sites, 112 soil samples from forests, grasslands, croplands, and construction lands), methods including Sen's trend analysis, Hurst exponent, partial correlation analysis, and the InVEST model were employed to investigate the spatiotemporal variations in vegetation and carbon storage of the mountainous ecosystem in northeastern Guangdong province. The results show that; (1) The research area exhibits relatively high vegetation coverage, with a Normalized Difference Vegetation Index (NDVI) ranging from 0.14 to 0.95 and an average value of 0.79. From 2000 to 2021, the vegetation coverage of the study region increased. Apart from the city area of Meizhou, the rest showed varying degrees of NDVI increase, especially in mountainous areas, where it showed a trend of rising and subsequently declining with elevation. The Hurst exponent (<0.5) implies a potential declining trend in vegetation changes in the study area. (2) From 2000 to 2020, the carbon storage in the study area displayed a decreasing trend, amounting to a total reduction of 1.33 teragrams (Tg). Land use changes, particularly the conversion of forests and grasslands into agricultural and urban areas, are the primary reasons for the decrease in carbon storage in the study area. The conclusions can serve as fundamental data for investigating the changes in carbon sequestration functionality within subtropical ecosystems in China. [ABSTRACT FROM AUTHOR]

The reductions in aerosols often exacerbate climate warming. It remains unclear how to effectively alleviate PM2.5 pollution while minimizing the penalty on climate warming. Here we identify the clean air measures in China that are associated with low aerosol climate penalty efficiency (ACPE), which is defined as aerosol radiative forcing per unit PM2.5 concentration reduction. The measures in transportation, residential combustion, and open burning sectors generally caused lower ACPE [0.07, 0.24, and 0.10 (W m−2)/(μg m−3)] than those from other sectors [0.34–0.46 (W m−2)/(μg m−3)]. This is ascribed to relatively small decreases in cloud concentration nuclei per unit PM2.5 reduction in these sectors, which is further attributed to either relatively low aerosol hygroscopicity or relatively small decrease in aerosol number. Most measures in the former three sectors have low ACPE of <0.15 [(W m−2)/(μg m−3)] and thus may be prioritized for synergistically controlling PM2.5 pollution and climate warming. Plain Language Summary: Aerosols not only cause serious air pollution but also alter the Earth's climate. Previous studies reported that PM2.5 improvement since 2013 has led to considerable positive aerosol radiative forcing over China, exacerbating climate warming. However, it remains unclear how to effectively alleviate PM2.5 pollution while minimizing the penalty on climate warming. Here we identify clean air measures in China that are associated with low aerosol climate penalty efficiency (ACPE), which is defined as aerosol radiative forcing per unit PM2.5 concentration reduction. The measures taken in transportation, residential combustion, and open burning sectors generally caused lower ACPE [0.07, 0.24, and 0.10 (W m−2)/(μg m−3)] than those from other sectors [0.34–0.46 (W m−2)/(μg m−3)]. This is ascribed to relatively small decreases in cloud concentration nuclei per unit PM2.5 reduction in these sectors, which is further attributed to either relatively low aerosol hygroscopicity or relatively small decreases in aerosol number. Furthermore, we found that most clean air measures in the former three sectors have low ACPE [<0.15 (W m−2)/(μg m−3)] and possess high emission reduction potential. These measures may be prioritized for promotion to reduce PM2.5 concentrations and minimize climate penalties. Key Points: The emission reductions in transportation, residential and open burning caused relatively small radiative forcing per unit PM2.5 reductionThe smaller radiative forcing is primarily ascribed to weaker decreases in cloud condensation nuclei per unit PM2.5 reductionThe measures with the smallest radiative forcing per unit PM2.5 reduction are identified and may be implemented in priority [ABSTRACT FROM AUTHOR]

Surface fine particulate matter (PM 2.5) pollution can be enhanced by feedback processes induced by aerosol–radiation interactions (ARIs) and aerosol–cloud interactions (ACIs). Many previous studies have reported enhanced PM 2.5 concentrations induced by ARIs and ACIs for episodic events in China. However, few studies have examined the changes in the ARI- and ACI-induced PM 2.5 enhancements over a long period, though the anthropogenic emissions have changed substantially in the last decade. In this study, we quantify the ARI- and ACI-induced PM 2.5 changes for 2013–2021 under different meteorology and emission scenarios using the Weather Research and Forecasting model with Chemistry (WRF-Chem), and we investigate the driving factors behind the changes. Our results show that, in January 2013, when China suffered from the worst PM 2.5 pollution, the PM 2.5 enhancement induced by ARIs in eastern China (5.59 µg m -3) was larger than that induced by ACIs (3.96 µg m -3). However, the ACI-induced PM 2.5 enhancement showed a significantly smaller decrease ratio (51 %) than the ARI-induced enhancement (75 %) for 2013–2021, making ACIs more important for enhancing PM 2.5 concentrations in January 2021. Our analyses suggest that the anthropogenic emission reductions played a key role in this shift. Owing to only anthropogenic emission reductions, the ACI-induced PM 2.5 enhancement decreased by 43 % in January, which was lower than the decrease ratio of the ARI-induced enhancement (57 %). The relative change in ARI- and ACI-induced PM 2.5 enhancement in July was similar to the pattern observed in January, caused by anthropogenic emission reductions. The primary reason for this phenomenon is that the decrease in ambient PM 2.5 for 2013–2021 caused a disproportionately small decrease in the liquid water path (LWP) and an increase in the cloud effective radius (Re) under the condition of high PM 2.5 concentrations. Therefore, the surface solar radiation attenuation (and, hence, the boundary layer height reduction) caused by ACIs decreased slower than that caused by ARIs. Moreover, the lower decrease ratio of the ACI-induced PM 2.5 enhancement was dominated by the lower decrease ratio of ACI-induced secondary PM 2.5 component enhancement, which was additionally caused by the smaller decrease ratio of the air temperature reduction and the relative humidity (RH) increase. Our findings indicate that, with the decrease in ambient PM 2.5 , the ACI-induced PM 2.5 enhancement inevitably becomes more important. This needs to be considered in the formulation of control policies to meet the national PM 2.5 air quality standard. [ABSTRACT FROM AUTHOR]

The processes of new particle formation (NPF) and growth are important contributors to cloud condensation nuclei (CCN) concentrations, and CCN are important for climate from their impact on planetary radiative forcing. While the general ubiquity and importance of NPF is understood, the vertical extent and governing mechanisms of NPF and growth in the lower troposphere are uncertain. We present an analysis of four NPF events and two non‐NPF events during the HI‐SCALE field campaign at the Southern Great Plains observatory in Oklahoma, USA. First, we analyzed airborne and ground‐based observations of aerosol and gas‐phase properties. Second, we used a column aerosol chemistry and microphysics model to probe factors that influence the vertical profile of NPF. During HI‐SCALE, we found several instances of enhanced NPF occurring several hundred meters above the surface; however, the spatio‐temporal characteristics of the observed NPF made comparisons between airborne‐ and ground‐based observations difficult. The model represented the observed NPF (or lack of NPF) and particle growth at the surface to final diameters within 10 nm. The model predicted enhanced NPF rates in the upper mixed layer, and this enhancement is primarily due to the temperature dependence in the NPF schemes, but this was also dependent on the vertical profile of gas‐phase precursors measured during HI‐SCALE. We found vertical mixing in the model either enhanced or suppressed NPF rates, aerosol number concentrations, and particle growth rates at the surface. Finally, our analysis provides insights for future field campaigns and modeling efforts investigating the vertical profile of NPF. Plain Language Summary: Aerosol particles in the atmosphere are important for climate, weather, and human health. In our work, we are trying to understand some of the processes that create new aerosol particles in the atmosphere. To accomplish this, we looked at measurements of these aerosol particles taken from a measurement site located on the ground and in an airplane. We also looked at some of the different gases in the atmosphere that might contribute to creating, and growing, these new particles. Finally, we took the measurements and put them into a complex aerosol‐chemistry model in order to understand some of the processes "under the hood" that measurements alone cannot tell us. We had to make some educated guesses and assumptions about certain processes in the model; however, we found that the new particles often form several hundred to thousands of meters above Earth's surface over central Oklahoma, USA. Unfortunately, many of the assumptions we had to make limit the robustness of our findings. Key Points: New particle formation (NPF) was observed at the surface on many days of the HI‐SCALE field campaignAirborne observations provide evidence of NPF initiating aloft on one of these daysModel results suggest that the vertical profiles of temperature and precursor gases are strong predictors of the vertical profile of NPF [ABSTRACT FROM AUTHOR]

In this paper, we present a multi-view stereo reconstruction approach which fuses scaled-neighborhood information. PMVS proposed by Furukawa is one of the most excellent algorithms, and it has a good performance on many datasets both the accuracy and the completeness. However, there are still further improvements on this algorithm. PMVS cannot perform well in the presence of slanted surfaces, which are usually imaged at oblique angles. According to these aspects, on the one hand we propose to estimate the initial normal of every seed patch via fitting quadrics with scaled-neighborhood patches, which greatly improves the accuracy of the normal. On the other hand, we present to compute scaled-window for the further optimization based on texture. And it has been tested that employing the scaled-window will dramatically smooth the surfaces and enhance the reconstruction precision.