The risk characteristics of heavy metals in urban soil of typical developed cities in China.

With the rapid development of China's industrial economy, heavy metals continue to accumulate in the environment, which has created serious threats for the ecological environment and human health. This study collected 50 surface soil samples in Nanjing, a typical developed city in China, and the contents of Al, Ca, Fe, Mg, Mn, Ni, Ti, Cd, Cr, Cu, Pb, and Zn in the samples were determined. Combined with the ecological risk index and the health risk assessment model, the risk of soil heavy metals in Nanjing was comprehensively evaluated. The results show that the variation coefficients of Pb and Cu are distinctly large, and these elements are all slightly polluting. Children are at a high risk of exposure in various ways, among which Pb and Cu elements have a high risk of causing non-carcinogenic issues. The results of the correlation analysis showed that the content changes of Pb, Zn, and Cu had extremely significant correlations, indicating that they may have the same source. The results of the principal component analysis showed that industrial sources in Nanjing contributed the most heavy metals, reaching 34.4%. The second largest source was from parent material and fertilizer, which contributed 32.3% and 19.6%, respectively. The sources with the lowest contributions were from weathering and deposition, which reached 13.7%. The results of this study will provide guidance and reference for risk-source analysis, early warning, and management of soil heavy metals in developed cities.

Multivariate analysis of roadway multi-fatality crashes using association rules mining and rules graph structures: A case study in China.

Roadway multi-fatality crashes have always been a vital issue for traffic safety. This study aims to explore the contributory factors and interdependent characteristics of multi-fatality crashes using a novel framework combining association rules mining and rules graph structures. A case study is conducted using data from 1068 severe fatal crashes in China from 2015 to 2020, and 1452 interesting rules are generated using an association rule mining approach. Several modular rules graph structures are constructed based on graph theory to reflect the interactions and patterns between different variables. The results indicate that multi-fatality crashes are highly associated with improper operations, passenger overload, fewer lanes, mountainous terrain, and run-off-the-road crashes, representing the key variables of factors concerning driver, vehicle, road, environment, and accident, respectively. Furthermore, crashes involving different severity levels, road categories, and terrain are verified to possess unique association rules and independent crash patterns. Moreover, the proportion of severe crashes caused by a combination of human-vehicle-road-environment factors (43%) is much higher than that of normal crashes (3%). This study reveals that the hidden associations between various factors contribute to the overrepresentation and severity of multi-fatality crashes. It also demonstrates that the crash mechanisms involving multi-fatality crashes and their interactions are more complex at the system level than those for normal crashes. The proposed framework can effectively map the intrinsic link between multiple crash factors and potential risks, providing transportation agencies with helpful insights for targeted safety measures and preventive strategies.

Review of Research on Road Traffic Operation Risk Prevention and Control.

Road traffic safety can be ensured by preventing and controlling the potential risks in road traffic operations. The relevant literature was systematically reviewed to identify the research context and status quo in the road traffic operation risk prevention and control field and identify the key study contents needing further research. As research material, the related English and Chinese literature published between 1996 and 2021 (as of 31st December 2021) was obtained through the Web of Science Core Collection and Chinese Science Citation Database. These research materials include 22,403 English and 7876 Chinese papers. Based on the bibliometrics, this study used CiteSpace software to conduct keyword co-occurrence analysis in the field. The results show that the relevant research topics mainly covered the risks of drivers, vehicles, roads, and the traffic environment. In the aspect of driver risks, the studies focused on driving behavior characteristics. In terms of vehicle risks, the related studies were mainly about the vehicle control system, driving assistance system, hazardous material transportation, automated driving technology, safe driving speed, and vehicle collision prediction. For the road risks, the safe driving guarantee of high-risk road sections, driving risks at intersections, and safe road alignment design were the three study hotspots. In terms of traffic environment risks, identifying traffic risk locations and driving safety guarantees under adverse weather conditions were the two main research highlights. Moreover, mathematical modeling was the main method for studying road traffic operation risk. Furthermore, the impact of environmental factors on drivers, the emergency rescue system for road traffic accidents, the connection between automated driving technology and safe driving theory, and the man-machine hybrid traffic flow characteristics are the subjects needing further research.

Modelling carbon emissions of diesel trucks on longitudinal slope sections in China.

Carbon emissions are the primary reason that contributes to global warming. The gradient has a significant impact on the carbon dioxide (CO2) emissions produced by trucks. The aim of the current paper is to propose a carbon emission quantification model for diesel trucks on longitudinal slope sections and investigate the influence of gradient on the carbon emissions of trucks for use in the low-carbon highway design. The law of conservation of mechanical energy, the first law of thermodynamics, and the vehicle longitudinal dynamics theory were adopted for deriving the carbon emission model of the trucks on the flat, uphill, downhill and round-trip longitudinal slope segments. Three kinds of common trucks were chosen to conduct the field test. Following the test data, the model demonstrates a high accuracy. The minimum gradient which is expected to impact carbon emissions of trucks on the round-trip longitudinal slope sections was the balance gradient as revealed. The gradient of the longitudinal slope is required to be avoided to be greater in comparison with the balance gradient for the achievement of the two-way traffic low carbon operation on a highway. The results of this study are valuable to researchers interested in low carbon road design and low carbon transportation control.

Selectivity control of nitrite and nitrate with the reaction of S0 and achieved nitrite accumulation in the sulfur autotrophic denitrification process.

The characteristics of reaction between S0 and NO2--N or NO3--N in the sulfur autotrophic denitrification (SADN) process were studied using S0 as an electron donor and NO2--N and NO3--N as electron acceptors. The effect of changes in pH and temperature on the processes of NO2--N and NO3--N reduction were also studied to identify the optimum control parameters for strengthening the preference of S0 on NO3--N; thus, achieving the efficient accumulation of NO2--N. The results showed that the affinity of S0 for NO3--N was considerably higher than that for NO2--N. The optimum pH values for the reductions of NO2--N and NO3--N were 7.0 and 8.5, respectively, and both optimum temperatures were 35 °C. By controlling different pH, the NO3--N conversion efficiency reached 90%, at which time the accumulation of NO2--N was more than 95%. Microbial community analysis showed that Thiobacillus, Sulfurimonas, and Thioahalobacter were the main genera in the S0-SADN process.