Investigating the Changes in Air Pollutant Emissions over the Beijing-Tianjin-Hebei Region in February from 2014 to 2019 through an Inverse Emission Method

Abstract

In recent years, China has implemented several measures to improve air quality. The Beijing-Tianjin-Hebei (BTH) region is one area that has suffered from the most serious air pollution in China and has undergone huge changes in air quality in the past few years. How to scientifically assess these change processes remain the key issue in further improving the air quality over this region in the future. To evaluate the changes in major air pollutant emissions over this region, this paper employs ensemble Kalman filtering (EnKF) for integrating the national ground monitoring pollutant observation data and the Nested Air Quality Prediction Modeling System (NAQPMS) simulation data to inversely estimate the emission rates of SO₂, NO_X, CO, and primary PM_2.5 over BTH region in February from 2014 to 2019. The results show that SO₂, NO_X, CO, and primary PM_2.5 emissions in the BTH region decreased in February from 2014 to 2019 by 83%, 37%, 41%, and 42%, while decreases in Beijing during this period were 86%, 67%, 59%, and 65%, respectively. Compared with the prior emission inventory, the inversion emission inventory reduces the uncertainty of multi-pollutant simulation in the BTH region, with simulated root mean square errors of the monthly average concentrations of SO₂, NO_X, PM_2.5, and CO reduced by 41%, 30%, 31%, and 22%, respectively. The average uncertainties of SO₂, NO_X, PM_2.5, and CO inversion emissions in 2014–19 are ±14.03% yr⁻¹, ±28.91% yr⁻¹, ±126.15% yr⁻¹, and ±43.58% yr⁻¹. Compared with the uncertainty of MEIC emission, the uncertainties of all species changed by +2% yr⁻¹, −2% yr⁻¹, −26% yr⁻¹, and −4% yr⁻¹, respectively. The spatial distribution results illustrate that air pollutant emissions are mainly distributed over the eastern and southern BTH regions. The spatial gap between the inversion emissions and MEIC emissions was further closed in 2019 compared to 2014. The results of this paper can provide a new reference for assessing changes in air pollution emissions over the BTH region in recent years and validating a bottom-up emission inventory.

摘要

近年来, 中国已经实施了一系列改善空气质量的措施。京津冀地区（BTH）是中国空气污染最严重的地区之一, 在过去几年里空气质量发生了显著变化。如何科学地评价这些变化过程是未来进一步改善该地区空气质量的关键问题。为评估该区域主要大气污染物排放的变化, 本文采用集合卡尔曼滤波（EnKF）方法, 结合全国地面污染物观测数据和嵌套网格空气质量预报系统（NAQPMS）, 反演了2014-19年2月BTH区域SO₂、NO_X、CO和一次PM_2.5的排放速率。结果表明, 2014–19年2月BTH区域SO₂、NO_X、CO和一次PM_2.5排放量分别下降了83%、37%、41%和42%, 同期北京下降了86%、67%、59%和65%。与先验的排放清单相比, 反演排放清单降低了BTH区域多污染物模拟的不确定性, SO₂、NO_X、PM_2.5和CO月平均浓度的模拟均方根误差分别降低了41%、30%、31%和22%。2014-19年SO2、NO_X、PM_2.5和CO反演排放的平均不确定度分别为±14.03%、±28.91%、±126.15%、±43.58%。与MEIC排放的不确定度相比, 所有物种的不确定度分别变化了+2% yr-1、-2% yr-1、-26% yr-1和-4% yr-1。空间分布结果表明, BTH区域大气污染物排放主要分布在东部和南部。与2014年相比, 2019年反演排放与MEIC排放的空间差距进一步缩小。本文的研究结果可为评价近年来京津冀地区大气污染排放变化及自下而上排放清单的验证提供新的参考。