Efficient View Synthesis with Neural Radiance Distribution Field

Recent work on Neural Radiance Fields (NeRF) has demonstrated significant advances in high-quality view synthesis. A major limitation of NeRF is its low rendering efficiency due to the need for multiple network forwardings to render a single pixel. Existing methods to improve NeRF either reduce the number of required samples or optimize the implementation to accelerate the network forwarding. Despite these efforts, the problem of multiple sampling persists due to the intrinsic representation of radiance fields. In contrast, Neural Light Fields (NeLF) reduce the computation cost of NeRF by querying only one single network forwarding per pixel. To achieve a close visual quality to NeRF, existing NeLF methods require significantly larger network capacities which limits their rendering efficiency in practice. In this work, we propose a new representation called Neural Radiance Distribution Field (NeRDF) that targets efficient view synthesis in real-time. Specifically, we use a small network similar to NeRF while preserving the rendering speed with a single network forwarding per pixel as in NeLF. The key is to model the radiance distribution along each ray with frequency basis and predict frequency weights using the network. Pixel values are then computed via volume rendering on radiance distributions. Experiments show that our proposed method offers a better trade-off among speed, quality, and network size than existing methods: we achieve a ~254x speed-up over NeRF with similar network size, with only a marginal performance decline. Our project page is at yushuang-wu.github.io/NeRDF.Comment: Accepted by ICCV202

Study on the Aral Sea crisis from the risk assessment of polycyclic aromatic hydrocarbons and organochlorine pesticides in surface water of Amu Darya river basin in Uzbekistan

The Amu Darya River, as one of the important flows of the Aral Sea located in the semi-arid area of Central Asia, also performed as the primary water supply for Uzbekistan. Therefore, the residues and risks of anthropogenic-related persistent organic pollutants (POPs) in waters of the Amu Darya River were conducted in the present study to elucidate their possible effects on the water safety in such a specific area as well as on the Aral Sea Crisis from a new perspective. Thirty-nine water samples distributed along the Amu Darya River to the coastal of the Aral Sea were analyzed for both polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) occurrence, showing the total concentrations of ΣOCPs and ΣPAHs in the range of 1.16–22.75 ng/L and 3.18–506.26 ng/L, respectively. Spatial differences showed higher levels for both OCPs and PAHs along the lower reaches of the Amu Darya River due to intense human activities. Source identification performed by isomer ratios indicated that dichlorodiphenyltrichloroethanes (DDTs) probably originated from recent use, while hexachlorocyclohexanes (HCHs), chlordanes, and endosulfans originated mainly from historical usage. Furthermore, the principal component analysis showed PAHs were from coal and petroleum combustion (65.2%), biomass combustion (27.2%), and industrial chemical combustion (7.64%). The human health risk assessment demonstrated no carcinogenic or non-carcinogenic risks at present. However, moderate to high ecological risks to aquatic organisms especially were observed along the lower reaches, especially the delta area. The results obtained would not only provide important basic data for such a semi-arid area but also show us the possible toxic effects induced by such pollutants, which should attract more attention in the shrinking case of the Aral Sea

Tracing the Nitrate Sources of the Yili River in the Taihu Lake Watershed: A Dual Isotope Approach

As the third largest freshwater lake in China, Taihu Lake has experienced severe cyanobacterial blooms and associated water quality degradation in recent decades, threatening the human health and sustainable development of cities in the watershed. The Yili River is a main river of Taihu Lake, contributing about 30% of the total nitrogen load entering the lake. Tracing the nitrate sources of Yili River can inform the origin of eutrophication in Taihu Lake and provide hints for effective control measures. This paper explored the nitrate sources and cycling of the Yili River based on dual nitrogen (δ15N) and oxygen (δ18O) isotopic compositions. Water samples collected during both the wet and dry seasons from different parts of the Yili River permitted the analysis of the seasonal and spatial variations of nitrate concentrations and sources. Results indicated that the wet season has higher nitrate concentrations than the dry season despite the stronger dilution effects, suggesting a greater potential of cyanobacterial blooms in summer. The δ15N-NO3− values were in the range of 4.0‰–14.0‰ in the wet season and 4.8‰–16.9‰ in dry, while the equivalent values of δ18O were 0.5‰–17.8‰ and 3.5‰–15.6‰, respectively. The distribution of δ15N-NO3− and δ18O-NO3− indicated that sewage and manure as well as fertilizer and soil organic matter were the major nitrate sources of the Yili River. Atmospheric deposition was an important nitrate source in the upper part of Yili River but less so in the middle and lower reaches due to increasing anthropogenic contamination. Moreover, there was a positive relationship between δ18O-NO3− and δ15N-NO3− in the wet season, indicating a certain extent of denitrification. In contrast, the δ18O-δ15N relationship in the dry season was significantly negative, suggesting that the δ15N and δ18O values were determined by a mixing of different nitrate sources

Heavy Metal Pollution of Lakes along the Mid-Lower Reaches of the Yangtze River in China: Intensity, Sources and Spatial Patterns

Lakes in the middle and lower reaches of the Yangtze River form a shallow lake group unique in the World that is becoming increasingly polluted by heavy metals. Previous studies have largely focused on individual lakes, with limited exploration of the regional pattern of heavy metal pollution of the lake group in this area. This paper explores the sources, intensity and spatial patterns of heavy metal pollution of lake sediments. A total of 45 sample lakes were selected and the concentrations of key metal elements in the sediments of each lake were measured. The cluster analysis (CA), principal component analysis (PCA) and Geo-accumulation index (Ig) analysis permitted analysis of the source and pollution intensity of the target lakes. Results suggested a notable spatial variation amongst the sample lakes. Lakes in the upper part of the lower reach of the Yangtze River surrounded by typical urban landscapes were strongly or extremely polluted, with high concentrations of Pb, Zn, Cu and Cd in their sediments. This was attributed to large amount of untreated industrial discharges and municipal sewage produced within the lake catchments. In contrast, the heavy-metal pollution of lakes in the Taihu Delta area was notably lower due to industrial restructuring and implementation of effective environmental protection measures. Lakes along the middle reach of Yangtze River surrounded by agricultural areas were unpolluted to moderately polluted by heavy metals overall. Our results suggested that lakes in the central part of China require immediate attention and efforts should be made to implement management plans to prevent further degradation of water quality in these lakes

Spatial variations of hydrochemistry and stable isotopes in mountainous river water from the Central Asian headwaters of the Tajikistan Pamirs

Water resources in Central Asia from the mountainous headwater catchments is changing due to the shrinkage of glaciers in the Tian Shan and Pamir mountain systems. In order to predict future changes in water quality, it is crucial to understand what factors are governing the spatial variations of water chemistry and hydrological processes in mountainous headwater catchments. In this study, water chemistry including major ions and stable isotopes in the headwaters of major Tajikistan rivers was studied. Results showed that Tajikistan river water had an alkaline pH value (mean: 8.2) and total dissolved solids (mean: 368.5mg/L) were higher than the global average value. Ca2+, Na+, HCO3-, and SO42- in the rivers were the most abundant cations and anions, controlled by the rock weathering process and evaporation-crystallization processes. The hydrochemical facies of river water was dominated by Ca-HCO3 (71.7%) and exhibited spatial heterogeneity, which was related to the lithologic compositions and water source across Tajikistan. A significant negative correlation of river water delta O-18 with elevation was observed with a vertical lapse rate of 0.17%/100 m. The more negative delta O-18 values in rivers from eastern Tajikistan were scattered in the lower left corner of the delta O-18-delta H-2 plot, implying that the rivers were primarily supplied by snow/glacier meltwater because of the substantial number of glaciers and high elevation mountain in eastern regions. The drinking and irrigation suitability from ionic compositions revealed that the water quality of Tajikistan rivers was naturally good, though some sites posed a safety concern. These findings can provide new insights into sustainable management of water quality in the climatically and lithologically distinct segments of headwater regions in the Tajikistan Pamirs