Chinese blue days: a novel index and spatio-temporal variations

Wang, Su; Huang, Gang; Lin, Jian; Hu, Kaiming; Wang, Lin; Gong, Hainan

doi:10.1088/1748-9326/ab29bb

Cited by 10 publications

(4 citation statements)

References 51 publications

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“…However, cloud contamination still existed. In addition, the trend of Chinese Blue Days in Yangtze River Delta was decreasing as well [45]. Besides, the accuracy of MODIS LST product depended on the land cover classification [1], so there were uncertainties in the product.…”

Section: Issues About the Modis Lst Productmentioning

confidence: 99%

Effects of Different Urbanization Levels on Land Surface Temperature Change: Taking Tokyo and Shanghai for Example

et al. 2020

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The influence of different urbanization levels on land surface temperature (LST) has attracted extensive attention. Though both are world megacities, Shanghai and Tokyo have gone through different urbanization processes that urban sprawl characterized by impervious surfaces was more notable in Shanghai than in Tokyo over the past years. Here, annual and seasonal mean LST in daytime (LSTday), in nighttime (LSTnight), and LSTdiff (annual and seasonal mean difference of LST in daytime and nighttime) were extracted from the MODIS LST product, MYD11A2 006, for 9 typical sites in Shanghai and Tokyo from 2003 to 2018, respectively. Then the effects of the urbanization levels were analyzed through Mann-Kendall statistics and Sen’s slope estimator. The trends of change in LSTday and LSTdiff for most sites in Shanghai, an urbanizing region, rose. In addition, there was no obvious regularity when considering seasonal factors, which could be due to the increasing fragmentized landscapes and scattered water bodies produced by urbanization. By comparison, the change in LST in Tokyo, a post-urbanizing region, was regular, especially in the spring. In other seasons, there was no obvious trend in temperature change regardless of whether the land cover was impervious surface or mountain forest. On the whole, vegetation cover and water bodies can mitigate the urban heat island (UHI) effect in urban regions. For more scientific urban planning, further analysis about the effect of urbanization on LST should focus on the compound stress from climate change and urbanization.

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Section: Issues About the Modis Lst Productmentioning

confidence: 99%

Effects of Different Urbanization Levels on Land Surface Temperature Change: Taking Tokyo and Shanghai for Example

et al. 2020

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“…Zhao et al [21] analyzed the characteristics of six criteria air pollutants in the Sichuan Basin of Southwest China from 2015 to 2017 and pointed out that all air pollutants except O 3 showed U-shaped annual changes; motor vehicle emissions was the main contributor to O 3 in the basin, while industrial emission was the main contributor to O 3 in the Western Sichuan Plateau area. Air quality in many large and medium-sized cities has improved significantly as a result of various environmental policies implemented by the Chinese government [22,23]. The changes of air pollutants in the sparsely populated western plateau in the past decade remain in question.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Long-Term Variation Characteristics of SO2, NO2, and O3 in the Ecological and Economic Zones of the Western Sichuan Plateau, Southwest China

Zhao

Liu²,

Luo³

et al. 2019

IJERPH

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Sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) are important atmospheric pollutants that affect air quality. The long-term variations of SO2 and NO2 in 2008–2018 and O3 in 2015–2018 in the relatively less populated ecological and economic zones of Western Sichuan Plateau, Southwest China were analyzed. In 2008–2018, the variations in SO2 and NO2 in the ecological zone were not significant, but Ganzi showed a slight upward trend. SO2 decreased significantly in the economic zone, especially in Panzhihua, where NO2 changes were not obvious. From 2015 to 2018, the concentration of O3 in the ecological zone increased significantly, while the economic zone showed a downward trend. The rising trend of the concentration ratio of SO2 to NO2 in the ecological zone and the declining trend in the economic zone indicate that the energy consumption structure of these two zones is quite different. The lower correlation coefficients between NO2 and O3 in the Western Sichuan Plateau imply that the variations of O3 are mainly affected by the regional background. The effects of meteorological factors on SO2, NO2, and O3 were more obvious in the economic zone where there are high anthropometric emissions.

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“…To ensure the accuracy and continuity of data used, a series of strict quality controls have been implemented following earlier work (Wang et al 2019 ). In particular, as manual visibility measurement is broadly replaced by automated detection techniques around 2013–2015, special treatment is required for visibility records to keep data consistency.…”

Section: Methodsmentioning

confidence: 99%

“…Previous studies show that good air quality can be represented by high atmospheric visibility in the long term (Wu 2004 ; Ma et al 2014 ; Zhang et al 2014 ; Liu et al 2017 ). Thus, our previous study (Wang et al 2019 ) defined a blue sky day via the following criteria: the days with no rain, low cloud cover ≤75th percentile,, and the dry visibility in 14:00 ≥15 km.…”

Section: Introductionmentioning

confidence: 99%

The deep blue day is decreasing in China

Wang

Huang

et al. 2022

Theor Appl Climatol

Self Cite

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The deep blue sky is an indicator of a lower concentration of aerosols and a cloudless sky. With increasing human emissions, a trend towards days with fewer deep blue skies might indicate a decline in a good living environment for humans. This study investigates the long-term changes of the deep blue sky in China from 1980 to 2018. Due to a lack of direct measurements, we use atmospheric visibility and low cloud cover to classify blue sky days into three grades: light blue day, medium blue day, and deep blue day. Climatologically, annual deep blue days increase from southeast China to northwest China, with the maximum number in Xinjiang and eastern Inner Mongolia and the minimum number in western Qinghai and southern Hebei. From 1980 to 2018, annual deep blue days show a prominent decreasing trend in most of China, with area-mean annual deep blue days decreasing by −0.48 days per year (d/y) in China, and the variation becomes more obvious after 2013. The maximum decreasing trend is observed in eastern China. The most prominent decreases of deep blue days are seen in winter. Both air pollution and the change in meteorological conditions contribute to the decrease of wintertime deep blue days in China. Specifically, the decrease in surface wind speed hinders the cleaning of air by winds, the increase in surface air temperature, and decrease in relative humidity is favorable for low cloud increase, and the increasing emission of pollution reduces atmospheric visibility. Supplementary Information The online version contains supplementary material available at 10.1007/s00704-021-03898-1.

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Chinese blue days: a novel index and spatio-temporal variations

Cited by 10 publications

References 51 publications

Effects of Different Urbanization Levels on Land Surface Temperature Change: Taking Tokyo and Shanghai for Example

Effects of Different Urbanization Levels on Land Surface Temperature Change: Taking Tokyo and Shanghai for Example

Comparative Analysis of Long-Term Variation Characteristics of SO2, NO2, and O3 in the Ecological and Economic Zones of the Western Sichuan Plateau, Southwest China

The deep blue day is decreasing in China

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