Attributions of meteorological and emission factors to the 2015 winter severe haze pollution episodes in China's Jing-Jin-Ji area

Abstract

Abstract. In the 2015 winter month of December, northern China witnessed the most severe air pollution phenomena since the 2013 winter haze events occurred. This triggered the first-ever red alert in the air pollution control history of Beijing, with an instantaneous fine particulate matter (PM2. 5) concentration over 1 mg m−3. Air quality observations reveal large temporal–spatial variations in PM2. 5 concentrations over the Beijing–Tianjin–Hebei (Jing-Jin-Ji) area between 2014 and 2015. Compared to 2014, the PM2. 5 concentrations over the area decreased significantly in all months except November and December of 2015, with an increase of 36 % in December. Analysis shows that the PM2. 5 concentrations are significantly correlated with the local meteorological parameters in the Jing-Jin-Ji area such as the stable conditions, relative humidity (RH), and wind field. A comparison of two month simulations (December 2014 and 2015) with the same emission data was performed to explore and quantify the meteorological impacts on the PM2. 5 over the Jing-Jin-Ji area. Observation and modeling results show that the worsening meteorological conditions are the main reasons behind this unusual increase of air pollutant concentrations and that the emission control measures taken during this period of time have contributed to mitigate the air pollution ( ∼ 9 %) in the region. This work provides a scientific insight into the emission control measures vs. the meteorology impacts for the period.

Severe air pollution events not avoided by reduced anthropogenic activities during COVID-19 outbreak

“…To better understand the role of emissions changes and meteorological conditions, a rough method is proposed with similar idea of a previous study (Wang et al, 2019b;Liu et al, 2017;WEI et al 2017;Li et al, 2015). The changes due to emission changes are calculated by subtracting the concentrations in Case 3 from that in Case 1, while the changes due to meteorology are calculated using concentrations in high-pollution days minus concentrations in low-pollution days, assuming that meteorology is the reason for severe pollution as the emissions are not changing day by day.…”

“…Compared with December 2015, the PM 2.5 concentration increased by 36% in BTH region. Liu et al (2017) attributed the increase to unfavorable meteorology of PBL, RH and wind.…”

Exploring the relationship between surface PM<sub>2.5</sub> and meteorology in Northern India

“…However, these values are not flagged and are also considered in the daily averages that CPCB provides. Most of these fill values are well over 1000 µg m −3 and so we exclude any PM 2.5 abundance ≥ 985 µg m −3 , although such high levels have occasionally been observed in similarly polluted environments (e.g., Liu et al, 2017). This process filters 812 observations, or ∼ 1 % of the total hourly data.…”

Impacts of meteorological uncertainties on the haze formation in Beijing–Tianjin–Hebei (BTH) during wintertime: a case study

“…Numerous studies have been performed in China to explore the role of meteorological conditions in the air pollution formation (e.g., Gao et al, 2011;Zhang et al, 2012Zhang et al, , 2015Wu et al, 2013;Wang et al, 2014;Bei et al, 2016a, b). Most recently, Liu et al (2017) have investigated the meteorological impacts on the PM 2.5 concentrations over Beijing-TianjinHebei (BTH) in December 2015. Their results have demon-strated that the unfavorable meteorological conditions are the main reason for deterioration of the air quality in BTH, while the undertaken emission control measures have only mitigated the air pollution slightly.…”