Temporal characteristics and spatial heterogeneity of air quality changes due to the COVID-19 lockdown in China

The Impacts of COVID-19 Lockdowns on Road Transport Air Pollution in London: A State-Space Modelling Approach

The emergence of the COVID-19 pandemic in 2020 led to the implementation of legal restrictions on individual activities, significantly impacting traffic and air pollution levels in urban areas. This study employs a state-space intervention method to investigate the effects of three major COVID-19 lockdowns in March 2020, November 2020, and January 2021 on London's air quality. Data were collected from 20 monitoring stations across London (central, ultra-low emission zone, and greater London), with daily measurements of NOx, PM10, and PM2.5 for four years (January 2019-December 2022). Furthermore, the developed model was adjusted for seasonal effects, ambient temperature, and relative humidity. This study found significant reductions in the NOx levels during the first lockdown: 49% in central London, 33% in the ultra-low emission zone (ULEZ), and 37% in greater London. Although reductions in NOx were also observed during the second and third lockdowns, they were less than the first lockdown. In contrast, PM10 and PM2.5 increased by 12% and 1%, respectively, during the first lockdown, possibly due to higher residential energy consumption. However, during the second lockdown, PM10 and PM2.5 levels decreased by 11% and 13%, respectively, and remained unchanged during the third lockdown. These findings highlight the complex dynamics of urban air quality and underscore the need for targeted interventions to address specific pollution sources, particularly those related to road transport. The study provides valuable insights into the effectiveness of lockdown measures and informs future air quality management strategies.

Spatiotemporal characteristics and co-effects of air quality and carbon dioxide emissions changes during the COVID-19 epidemic lockdown measures in China

The COVID-19 pandemic prompted several nations, including China, to enact unprecedented lockdown measures, leading to significant alterations in environmental conditions. Previous studies have solely analysed the impact of lockdown measures on air pollutants or carbon dioxide (CO2) emissions during the COVID-19 pandemic in China, but few have focused on the spatio-temporal change characteristics and synergistic effects between the two. In this study, we constructed a methodological framework to examine the spatiotemporal characteristics and co-effects of air quality (PM2.5, SO2, and NO2) and CO2 changes in 324 prefecture-level cities in China due to the COVID-19 blockade measures from January 24 to April 30, 2020, using the regression discontinuity in time method and co-effect control coordinate system. The results show that a significant improvement in air quality and CO2 emissions during the lockdown period, with notable north‒south heterogeneity. During the major lockdown period (January 24 to February 29), the measures resulted in respective reductions of 5.6%, 16.6%, and 25.1% in the concentrations of SO2, NO2, and CO2 nationwide. The proportions of cities with negative treatment effects on PM2.5, SO2, NO2, and CO2 were 39.20%, 70.99%, 84.6%, and 99.38%, respectively. Provinces where concentrations of CO2 and NO2 declined by over 30% were primarily concentrated in southern areas of the 'Yangtze River Defense Line'. Starting from March, the improvement effect of air quality and CO2 has weakened, and the concentration of air pollutants has rebounded. This study offers crucial insights into the causal effects of lockdown measures on air quality changes, and reveals the synergy between air quality and CO2, thereby providing a reference for devising effective air quality improvement and energy-saving emission reduction strategies.

How does COVID-19 lockdown affect air quality: Evidence from Lanzhou, a large city in Northwest China

Coronavirus disease (COVID-19) has disrupted health, economy, and society globally. Thus, many countries, including China, have adopted lockdowns to prevent the epidemic, which has limited human activities while affecting air quality. These affects have received attention from academics, but very few studies have focused on western China, with a lack of comparative studies across lockdown periods. Accordingly, this study examines the effects of lockdowns on air quality and pollution, using the hourly and daily air monitoring data collected from Lanzhou, a large city in Northwest China. The results indicate an overall improvement in air quality during the three lockdowns compared to the average air quality in the recent years, as well as reduced PM2.5, PM10, SO2, NO2, and CO concentrations with different rates and increased O3 concentration. During lockdowns, Lanzhou's "morning peak" of air pollution was alleviated, while the spatial characteristics remained unchanged. Further, ordered multi-classification logistic regression models to explore the mechanisms by which socioeconomic backgrounds and epidemic circumstances influence air quality revealed that the increment in population density significantly aggravated air pollution, while the presence of new cases in Lanzhou, and medium- and high-risk areas in the given district or county both increase the likelihood of air quality improvement in different degrees. These findings contribute to the understanding of the impact of lockdown on air quality, and propose policy suggestions to control air pollution and achieve green development in the post-epidemic era.

COVID-19 pandemic, port congestion, and air quality: Evidence from China

The emergency of COVID-19 leads to almost all unnecessary activities being banned because of city lockdowns, which results in the economy and human mobility being strictly restricted. While affecting economic development, it has brought some environmental benefits. As a critical link to collection and distribution, ports have been deeply impacted by COVID-19, including quarantine time and operational efficiency, and even cause unexpected port congestion. This study empirically examines the relationship between the COVID-19 pandemic, port congestion and air quality in Chinese port cities using classical and system panel models. We find that the COVID-19 pandemic and port congestion significantly influence air quality in port cities. Managerial implications include the ensuring of port workers' shifts, the unblocking of port logistics, and the cooperation between transportation, customs, and quarantine departments, which can reduce the time of ships at berths and improve the air quality in port cities.

Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016-2020: The impact of air pollution controls and the COVID-19 pandemic

Air pollution is a threat to public health in China, and several actions and plans have been implemented by Chinese authorities in recent years to mitigate it. This study examined the spatial distribution of changes in urban air pollutants (UAP) in 336 Chinese cities from 2016 to 2020 and their responses to air pollution controls and the COVID-19 pandemic. Based on the harmonic model, decreases in fine particles (PM_2.5), inhalable particles (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO) levels were found in 90.7%, 91.9%, 75.2%, 94.3%, and 88.7% of cities, respectively, while an increase in ozone (O₃) was found in 87.2% of cities. Notable spatial heterogeneity was observed in the air pollution trends. The greatest improvement in air quality occurred mainly in areas with poor air quality, such as Hebei province and its surrounding cities. However, some areas (i.e., Yunnan and Hainan provinces) with good air quality showed a worsening trend. During the 13th Five-Year Plan period (2016-2020), the remarkable effects of PM_2.5 and SO₂ pollution control plans were confirmed. Additionally, economic growth in 74.2% of the Chinese provinces decoupled from air quality after implementing pollution control measures. In 2020, several Chinese cities were locked down to reduce the spread of COVID-19. Except for SO₂, the national air pollution in 2020 improved to a greater extent than that in 2016-2019; In particularly, the contribution of simulated COVID-19 pandemic to NO₂ reduction was 66.7%. Overall, air pollution control actions improved urban PM_2.5, PM₁₀, SO₂, and CO, whereas NO₂ was reduced primarily because of the COVID-19 pandemic.

The Long-Term Impact of COVID-19 Lockdowns in Istanbul

The World Health Organization (WHO) have set sustainability development goals to reduce diseases, deaths, and the environmental impact of cities due to air pollution. In Istanbul, although average pollutant concentrations have been on a downward trend in recent years, extreme values and their annual exceedance numbers are high based on the air quality standards of WHO and the EU. Due to COVID-19 lockdowns, statistically significant reductions in emissions were observed for short periods. However, how long the effect of the lockdowns will last is unknown. For this reason, this study aims to investigate the impact of long-term lockdowns on Istanbul's air quality. The restriction period is approximated to the same periods of the previous years to eliminate seasonal effects. A series of paired t-tests (p-value < 0.05) were applied to hourly data from 12 March 2016, until 1 July 2021, when quarantines were completed at 36 air quality monitoring stations in Istanbul. The findings reveal that the average air quality of Istanbul was approximately 17% improved during the long-term lockdowns. Therefore, the restriction-related changes in emission distributions continued in the long-term period of 476 days. However, it is unknown how long this effect will continue, which will be the subject of future studies. Moreover, it was observed that the emission probability density functions changed considerably during the lockdowns compared to the years before. Accordingly, notable decreases were detected in air quality limit exceedances in terms of both excessive pollutant concentrations and frequency of occurrence, respectively, for PM10 (-13% and -13%), PM2.5 (-16% and -30%), and NO2 (-3% and -8%), but not for O3 (+200% and +540%) and SO2 (-10% and +2.5%).

Spatiotemporal patterns of gross ecosystem product across China's cropland ecosystems over the past two decades

As the largest artificial ecosystem on Earth, croplands not only secure the basic living materials for people but also provide ecological service values for human society. For croplands, ecosystem services have proven to be of great value and are closely linked to human activities and climate change. However, spatiotemporal patterns of cropland ecosystem services and their drivers still need to be further assessed quantitatively. In this study, we provided a comprehensive evaluation of ecosystem services across China's cropland ecosystems over the past two decades using gross ecosystem product (GEP) as a single metric of the monetary evaluation of final ecosystem services. The values of material services, regulating services, and cultural services were calculated to summarize the GEP value of cropland ecosystems in China. Our results showed that the multiyear mean value of GEP was 4.35 × 107 million CNY. The value of regulating services reached 3.86 × 107 million CNY, followed by material services of 4.76 × 106 million CNY and cultural services of 1.16 × 105 million CNY. GEP value was different among provinces, leading to a heterogeneous spatial pattern associated with population and cultivated area. Moreover, we analyzed the trends in the GEP value at the provincial and national scales. The results showed that the GEP value of China's cropland ecosystems has increased over the period. The values of the material, regulating, and cultural services have increased at a rate of (0.35 ± 0.01) × 106 million CNY a−1, (1.12 ± 0.10) × 106 million CNY a−1, and (0.002 ± 0.0002) × 106 million CNY a−1, respectively (P &lt; 0.05). The majority of provinces had an increasing trend in GEP, yet some developed provinces, e.g., Beijing and Shanghai, showed a decreasing trend. Furthermore, we evaluated the impacts of social-economic and natural factors on changes in GEP. We found that rising prices for agricultural products and services boosted an increase in GEP. Meanwhile, the spatiotemporal patterns of GEP were also associated with the adjustments of planting area in each province. Overall, our findings highlight the importance of assessing spatiotemporal patterns of cropland ecosystem services for decision-makers.

COVID-19 Pandemic, Air Quality, and PM2.5 Reduction-Induced Health Benefits: A Comparative Study for Three Significant Periods in Beijing

Previous studies have estimated the influence of control measures on air quality in the ecological environment during the COVID-19 pandemic. However, few have attached importance to the comparative study of several different periods and evaluated the health benefits of PM2.5 decrease caused by COVID-19. Therefore, we aimed to estimate the control measures' impact on air pollutants in 16 urban areas in Beijing and conducted a comparative study across three different periods by establishing the least squares dummy variable model and difference-in-differences model. We discovered that restriction measures did have an apparent impact on most air pollutants, but there were discrepancies in the three periods. The Air Quality Index (AQI) decreased by 7.8%, and SO2, NO2, PM10, PM2.5, and CO concentrations were lowered by 37.32, 46.76, 53.22, 34.07, and 19.97%, respectively, in the first period, while O3 increased by 36.27%. In addition, the air pollutant concentrations in the ecological environment, including O3, reduced significantly, of which O3 decreased by 7.26% in the second period. Furthermore, AQI and O3 concentrations slightly increased compared to the same period in 2019, while other pollutants dropped, with NO2 being the most apparent decrease in the third period. Lastly, we employed health effects and environmental value assessment methods to evaluate the additional public health benefits of PM2.5 reduction owing to the restriction measures in three periods. This research not only provides a natural experimental basis for governance actions of air pollution in the ecological environment, but also points out a significant direction for future control strategies.