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Air pollution is an important factor threatening human health. Inhalation of pollutants can cause damage to the cardiovascular system, leading to increased morbidity and mortality of cardiovascular diseases. This paper selects six pollution factors stipulated by the national air quality standards, collects the air quality index data of Shanghai from 2014 to 2017 and the emergency data of cardiovascular disease in a tertiary hospital in the city during the same period, and conducts relevant analysis to explore different air quality conditions, characteristics, and the relationship between pollutants and cardiovascular disease visits. The results show that the seasonal changes of major air pollutants are related to the incidence of cardiovascular disease. [ABSTRACT FROM AUTHOR]

Optimal strategy, one of the main transit assignment models, can better demonstrate the flexibility for passengers using routes in a transit network. According to the basic optimal strategy model, passengers can board trains based on their frequency without any capacity limitation. In the metropolitan cities such as Beijing, Shanghai, and Hong Kong, morning commuters face huge transit problems. Especially for the metro system, there is heavy rush in metro stations. Owing to the limited train capacity, some passengers cannot board the first coming train and need to wait for the next one. To better demonstrate the behavior of passengers pertaining to the limited train capacity, we consider capacity constraints for the basic optimal strategy model to represent the real situation. We have proposed a simulation-based algorithm to solve the model and apply it to the Beijing Subway to demonstrate the feasibility of the model. The application of the proposed approach has been demonstrated using the computational results for transit networks originating from practice. [ABSTRACT FROM AUTHOR]

Traffic restriction policy (TRP) is common practice to alleviate urban congestion and air pollution. However, effects of TRP for non-local vehicles and elevated expressways on local and regional air quality are understudied. Using air pollutant data collected by ground-based national and roadside environmental monitoring stations and field measurements, comparative research design and regression discontinuity analysis were performed to investigate the local and regional variations in air pollutant concentrations with and without the TRP. Results indicate that traffic restriction significantly decreased the local and regional concentration levels of primary gaseous pollutants (e.g., NOX and CO), particularly under more stringent TRP during China International Import Expo, which also brought an ozone increase due to the reduced effect of NOX titration. However, the TRP only exhibited limited impacts on mitigating regional particulate pollution. These findings suggest that the air quality improvements due to the non-local TRP highly depend on the types of pollutants and the spatial locations. [Display omitted] • Pollutant data from Shanghai monitoring networks are used for policy evaluation. • Comparative research design and regression discontinuity analysis are performed. • Restriction brings a sharper decline in primary gaseous pollutants than particles. • Restriction hardly improves urban air quality of Shanghai where particles dominate. • Air quality impacts highly depend on the types of pollutants and spatial locations. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic provides an opportunity to study the effects of urban lockdown policies on the variation in pollutant concentrations and to characterize the recovery patterns of urban air pollution under the interruption of COVID-19 lockdown policies. In this paper, interruption-recovery models and regression discontinuity design were developed to characterize air pollution interruption-recovery patterns and analyze environmental impacts of the COVID-19 lockdown, using air pollution data from four Chinese metropolises (i.e., Shanghai, Wuhan, Tianjin, and Guangzhou). The results revealed the air pollutant interruption-recovery curve represented by the three lockdown response periods (Level I, Level II and Level III) during COVID-19. The curve decreased during Level I (A 25.3%–48.8% drop in the concentration of NO 2 has been observed in the four metropolises compared with the same period in 2018–2019.), then recovered around reopening, but decreased again during Level III. Moreover, the interruption-recovery curve of the year-on-year air pollution difference suggests a process of first decreasing during Level I and gradually recovering to a new equilibrium during Level III (e.g., the unit cumulative difference of NO 2 mass concentrations in Shanghai was 21.7, 22.5, 11.3 (μg/m3) during Level I, II, and III and other metropolises shared similar results). Our findings reveal general trends in the air quality externality of different lockdown policies, hence could provide valuable insights into air pollutant interruption-recovery patterns and clear scientific guides for policymakers to estimate the effect of different lockdown policies on urban air quality. • The interruption and recovery of air pollution during the COVID-19 was evaluated. • Regression Discontinuity Design (RDD) has been used for statistical analysis. • Data of four major Chinese cites were utilized for characterizing and modelling. • The year-on-year NO 2 and PM 2.5 showed 25.3%–48.8% and 23.1%–46.2% drop separately. [ABSTRACT FROM AUTHOR]

Elevated expressways have been built in many cities worldwide to improve the accessibility and capability of urban road network. Meanwhile, intensive emissions from ground- and elevated-road traffic would significantly elevate personal exposure levels to air pollutants, such as fine particles (PM 1), carbon monoxide (CO) and black carbon (BC). However, their transport and dispersion mechanisms in urban residential areas have not been clearly recognized. In this study, we characterized temporal and vertical distribution patterns of traffic-emitted pollutants near an elevated expressway in near-road buildings. Vertically-resolved measurements of traffic emissions were made at different floors of a roadside building alongside the Inner Ring Viaduct in downtown Shanghai, China from January to June 2019. Results show that higher pollutant concentrations were observed during the morning (Local Time, UTC+8, LT 08–09) in winter and during the late afternoon (LT 17–18) in summer, the result of seasonal variations in vehicular activities and meteorological factors. Additionally, the vertical profiles of traffic-emitted pollutants all exhibited bimodal distribution patterns, which was more obvious for PM 1 than for CO and BC. The upper peak appeared slightly above noise barriers, attributable to the extra vehicular emissions on the elevated expressway. The lower peak occurred at ground level mainly due to on-road congested traffic flow, and the presence of the elevated road, which inhibited the dilution of ground-level vehicular exhausts. These findings reveal the general trends of the dispersion patterns of traffic emissions surrounding urban elevated expressways, and could provide implications in making control measures to mitigate air pollution exposure. Image 1 • Spatiotemporal distributions were analyzed for traffic emissions via field study. • The hourly variations of traffic-emitted pollutants changed greatly with season. • The vertical profiles of traffic-emitted pollutants exhibited bimodal patterns. • Two peaks appeared at ground level and slightly above noise barriers, respectively. • Traffic-emitted pollutants highly correlated to relative humidity and traffic flow. [ABSTRACT FROM AUTHOR]

Following the outbreak of the COVID-19 pandemic, various lockdown strategies restrained global economic growth bringing a significant decline in maritime transportation. However, the previous studies have not adequately recognized the specific impacts of COVID-19 on maritime transportation. In this study, a series of analyses of the Baltic Dry Index (BDI), the China Coastal Bulk Freight Index (CCBFI) and of container throughputs with and without the impact of COVID-19 were carried out to assess changing trends in dry bulk and container transportation. The results show that global dry bulk transportation was largely affected by lockdown policies in the second month during COVID-19, and BDI presented a year-on-year decrease of approximately 35.5% from 2019 to 2020. The CCBFI showed an upward trend in the second month during COVID-19, one month ahead of the BDI. The container throughputs at Shanghai Port, the Ports of Hong Kong, the Ports of Singapore and the Ports of Los Angeles from 2019 to 2020 presented the largest year-on-year drops of approximately 19.6%, 7.1%, 10.6% and 30.9%, respectively. In addition, the authors developed exponential smoothing models of BDI, CCBFI, and container transportation, and calculated the percentage prediction error between the observed and predicted values to examine the impact of exogenous effects on the shipping industry due to the outbreak of COVID-19. The results are consistent with the conclusions obtained from the comparison of BDI, CCBFI, and container transportation during the same period in 2020 and 2019. Finally, on the basis of the findings, smart shipping and special support policies are proposed to reduce the negative impacts of COVID-19. [ABSTRACT FROM AUTHOR]