Aerosol properties over Southeastern China from multi-wavelength Raman and depolarization lidar measurements

A dataset of particle optical properties of highly polluted urban aerosol over the Pearl River Delta, Guangzhou, China is presented. The data were derived from multi-wavelengths Raman and depolarization lidar PollyXT and AERONET sun photometer measurements. The measurement campaign was conducted from Nov 2011 to June 2012. High aerosol optical depth was observed in the polluted atmosphere over this megacity, with a mean value of 0.54 ± 0.33 and a peak value of even 1.9. For the particle characterization the lidar ratio and the linear particle depolarization ratio, both at 532 nm, were used. The mean values of these properties are 48.0 sr ± 10.7 sr for the lidar ratio and 4%+-4% for the particle depolarization ratio, which means most depolarization measurements stayed below 10%. So far, most of these results indicate urban pollution particles mixed with particles arisen from biomass and industrial burning

An overview of the first decade of PollyNET: An emerging network of automated Raman-polarization lidars for continuous aerosol profiling

A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere

Ship detection and classification based on cascaded detection of hull and wake from optical satellite remote sensing imagery

Satellite remote-sensing provides a cost- and time-effective tool for ship monitoring at sea. Most existing approaches focused on extraction of ship locations using either hull or wake. In this paper, a method of cascaded detection of ship hull and wake was proposed to locate and classify ships using high-resolution satellite imagery. Candidate hulls were fast located through phase spectrum of Fourier transform. A hull refining module was then executed to acquire accurate shapes of candidate hull. False alarms were removed through the shape features and textures of candidate hulls. The probability that a candidate hull is determined as a real one increased with the presence of wakes. After true ships were determined, ship classification was conducted using a fuzzy classifier combining both hull and wake information. The proposed method was implemented to Gaofen-1 panchromatic and multispectral (PMS) imagery and showed good performance for ship detection with recall, precision, overall accuracy, and specificity of 90.1%, 88.1%, 98.8%, and 99.3%, respectively, better than other state-of-the-art coarse-to-fine ship detection methods. Ship classification was successfully achieved for ships with detected wakes. The accuracy of correct classification was 83.8% while the proportion of false classification was 1.0%. Factors influencing the accuracy of the developed method, including texture features and classifiers combination and key parameters of the method, were also discussed

Aerosol Properties over Southeastern China from Multi-Wavelength Raman and Depolarization Lidar Measurements

A dataset of particle optical properties of highly polluted urban aerosol over the Pearl River Delta, Guangzhou, China is presented. The data were derived from multi-wavelengths Raman and depolarization lidar PollyXT and AERONET sun photometer measurements. The measurement campaign was conducted from Nov 2011 to June 2012. High aerosol optical depth was observed in the polluted atmosphere over this megacity, with a mean value of 0.54 ± 0.33 and a peak value of even 1.9. For the particle characterization the lidar ratio and the linear particle depolarization ratio, both at 532 nm, were used. The mean values of these properties are 48.0 sr ± 10.7 sr for the lidar ratio and 4%+-4% for the particle depolarization ratio, which means most depolarization measurements stayed below 10%. So far, most of these results indicate urban pollution particles mixed with particles arisen from biomass and industrial burning

Remote Sensing Retrieval of Total Phosphorus in the Pearl River Channels Based on the GF-1 Remote Sensing Data

Total phosphorus (TP) concentration is one of the indicators for surface water quality evaluation. In this study, an indirect algorithm was proposed to retrieve TP concentration. This algorithm retrieves the TP concentration in urban waters based on Gaofen-1 (GF-1) remote sensing data. The algorithm uses the correlation between remote-sensing reflectance, optically significant constituents of water (chlorophyll, suspended sediment, and organic matter (excluding algae)), and TP to establish a retrieval model. First, the concentrations of optically active components are retrieved using a semi-analytical model. Second, the correlation between TP and optically active components is used to retrieve the TP concentration in waters. The GF-1 remote sensing data for 7 August 2015 were used to perform remote sensing retrieval of TP concentration in the Pearl River channels in Guangzhou, China. The results show that the TP concentration in most areas of the Front Channel, Western Channel, Guangzhou Channel, and the western part of the Back Channel was higher than 0.2 mg/L, while the TP concentration in the middle and eastern parts of the Back Channel was generally lower than 0.2 mg/L. The mean absolute percentage error of the retrieval is 24.18%. The experimental results show that the model is suitable for remote sensing retrieval of TP in urban waters in Guangzhou

Comparative Analysis of the Factors Influencing Land Use Change for Emerging Industry and Traditional Industry: A Case Study of Shenzhen City, China

Analyzing the factors influencing emerging industry land use change is important for promoting industrial transformation and for upgrading and improving the level of intensive use of emerging industry land. In recent years, to solve the problem of land resource shortage and expansion space, Shenzhen has implemented a strategy of promoting urban development through technological innovation and has actively promoted the transformation of inefficient industrial land to emerging industry. This article introduces the development, land use types, and spatial distribution of Shenzhen’s emerging industries. Based on the logistic regression model, we analyze the differences between the factors influencing changes in land use for both emerging and traditional industry. The research results show that the distance from public roads, the distance from highways, the distance from railway freight stations, the proportion of secondary industry, and the proportion of tertiary industry are important explanatory variables for the two types of land use change. Traditional industrial land use is also affected by the land slope, the distance from ports, the population, and fixed asset investment. Emerging industry land use is also affected by the distance from the airport, the number of railway stations, the quality of the population, and innovation-driving forces. These results provide a reference for government to rationally plan emerging industry land and differentiated management of this, in order to fill the current research gap in the field of land use change, and to contribute to research revealing the mechanisms driving changes in emerging industrial land

Genome characterization based on the Spike-614 and NS8-84 loci of SARS-CoV-2 reveals two major possible onsets of the COVID-19 pandemic.

The global COVID-19 pandemic has lasted for 3 years since its outbreak, however its origin is still unknown. Here, we analyzed the genotypes of 3.14 million SARS-CoV-2 genomes based on the amino acid 614 of the Spike (S) and the amino acid 84 of NS8 (nonstructural protein 8), and identified 16 linkage haplotypes. The GL haplotype (S_614G and NS8_84L) was the major haplotype driving the global pandemic and accounted for 99.2% of the sequenced genomes, while the DL haplotype (S_614D and NS8_84L) caused the pandemic in China in the spring of 2020 and accounted for approximately 60% of the genomes in China and 0.45% of the global genomes. The GS (S_614G and NS8_84S), DS (S_614D and NS8_84S), and NS (S_614N and NS8_84S) haplotypes accounted for 0.26%, 0.06%, and 0.0067% of the genomes, respectively. The main evolutionary trajectory of SARS-CoV-2 is DS→DL→GL, whereas the other haplotypes are minor byproducts in the evolution. Surprisingly, the newest haplotype GL had the oldest time of most recent common ancestor (tMRCA), which was May 1 2019 by mean, while the oldest haplotype DS had the newest tMRCA with a mean of October 17, indicating that the ancestral strains that gave birth to GL had been extinct and replaced by the more adapted newcomer at the place of its origin, just like the sequential rise and fall of the delta and omicron variants. However, the haplotype DL arrived and evolved into toxic strains and ignited a pandemic in China where the GL strains had not arrived in by the end of 2019. The GL strains had spread all over the world before they were discovered, and ignited the global pandemic, which had not been noticed until the virus was declared in China. However, the GL haplotype had little influence in China during the early phase of the pandemic due to its late arrival as well as the strict transmission controls in China. Therefore, we propose two major onsets of the COVID-19 pandemic, one was mainly driven by the haplotype DL in China, the other was driven by the haplotype GL globally

Effect of Perforation Dyeing Technique on Color Difference, Colorfastness, and Basic Density of Living Red-Heart Chinese Fir

Red-heart Chinese fir is an excellent geographic provenance of Cunninghamia lanceolata, with high-value red heartwood. However, the formation of red heartwood is usually slow. To quickly cultivate red-heart Chinese fir, we studied perforation dyeing technology on living trees that were 7 years old and efficient in high-value red heartwood formation. Reactive dye (%), penetrant (%), KH2PO4 (%), and pH were selected as influencing factors, and an orthogonal test (L9(3)4) was used. The results showed that the total color difference between the experimental and CK groups ranged from 13.74 to 26.86 NBS, which was a significant visual perception (above 12 NBS). The total color difference before and after soaking in water for 6 h ranged from 2.30 to 5.12 NBS, which belonged to the detectable and identifiable value of the human eye (2~5 NBS). After the injection of the dye liquid, the wood basic density (WBD) was significantly affected after one year. After a comprehensive analysis of wood color difference, colorfastness, and WBD of the orthogonal test, the best dyeing process of juvenile red-heart Chinese fir was reactive dye: 0.8%, penetrant: 0.05%, KH2PO4: 0.3%, and pH: 3.5. The results of this study can provide a reference to improve the value of red-heart Chinese fir, a fast-cultivated, high-value decorative wood material

250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ)