我国典型区域二氧化碳和细颗粒物精细化协同减排路径

随着碳达峰、碳中和目标的提出,我国环境保护进入减污降碳协同治理新阶段.目前研究主要探寻空气质量政策或气候政策对二氧化碳和细颗粒物的减排效益.而从二氧化碳和细颗粒物排放终端能源消费重点行业、主要能源以及主导因素等角度出发,来探究我国典型区域协同减排路径精细化方法的研究则鲜见报道.本研究基于2000~2020年我国京津冀、长江三角洲、珠江三角洲典型区域能源消耗数据,首先探明了3个典型区域二氧化碳和细颗粒物终端能源消费的重点排放行业均为工业;并进一步甄别了终端能源消费重点行业中PM_(2.5)排放主要能源为煤类能源,而CO_(2)排放主要能源由煤类能源逐渐转向煤、气类能源,但煤类仍为主导地位;随后使用因素分解模型解析了能源强度、技术进步等主导因素对单位国内生产总值的二氧化碳以及细颗粒物的影响效应;最终利用能源-环境核算预测模型,基于上述研究识别的终端能源消费重点行业、主要能源以及主导因素进行情景分析,旨在判断典型区域不同情景下碳达峰情况,进而寻找协同减排最优路径.结果发现,“技术进步”因素在前期减排效果最好;“能效提升”因素的减排效果在长时期碳污协同减排将起到关键作用,表明未来针对工业排放等终端能源消费重点行业,关注煤、气类等主要能源,采取能效提升、技术进步等手段措施,能够对减污降碳协同增效目标的实现产生最佳收益.希望本研究能为我国典型区域二氧化碳和细颗粒物合理化、精细化协同减排和管控提供科学证据.

Impacts of meteorology and precursor emission change on O_(3) variation in Tianjin, China from 2015 to 2021

Deterioration of surface ozone (O_(3)) pollution in Northern China over the past few years received much attention.For many cities,it is still under debate whether the trend of surface O_(3)variation is driven by meteorology or the change in precursors emissions.In this work,a time series decomposition method (Seasonal-Trend decomposition procedure based on Loess (STL)) and random forest (RF) algorithm were utilized to quantify the meteorological impacts on the recorded O_(3)trend and identify the key meteorological factors affecting O_(3)pollution in Tianjin,the biggest coastal port city in Northern China.After “removing” the meteorological fluctuations from the observed O_(3)time series,we found that variation of O_(3)in Tianjin was largely driven by the changes in precursors emissions.The meteorology was unfavorable for O_(3)pollution in period of 2015-2016,and turned out to be favorable during 2017-2021.Specifically,meteorology contributed 9.3μg/m^(3)O_(3)(13%) in 2019,together with the increase in precursors emissions,making 2019 to be the worst year of O_(3)pollution since 2015.Since then,the favorable effects of meteorology on O_(3)pollution tended to be weaker.Temperature was the most important factor affecting O_(3)level,followed by air humidity in O_(3)pollution season.In the midday of summer days,O_(3)pollution frequently exceeded the standard level (>160μg/m^(3)) at a combined condition with relative humidity in 40%-50%and temperature>31℃.Both the temperature and the dryness of the atmosphere need to be subtly considered for summer O_(3)forecasting.

Quantifying the impacts of emissions and meteorology on the interannual variations of air pollutants in major Chinese cities from 2015 to 2021

Air pollutant concentration is a function of emission rates and meteorology.To accurately evaluate the effect of control measures,the meteorological covariate must be corrected from the observations.This study quantified the impacts of emission abatement and meteorological condition on the interannual variations of SO_(2),NO_(2),CO,O_(3),PM_(10) and PM_(2.5) concentrations in 31 major Chinese cities using an optimized machine learning-based meteorological normalization technique.Overall,the annual average concentrations of SO_(2),NO_(2),CO,PM_(10)and PM_(2.5)were reduced by 86%,51%,99%,86% and 88%from 2015 to 2020,respectively,in the studied cities,attributable to their emission reductions.However,the concentration of O_(3) was found with no significant decrease with the reduction of precursors.Emission abatement notably improved air quality between 2015 and 2018.Such a decline in emissions tended to progressively slow down since 2018.Overall,the meteorological conditions in 2016–2017 and 2018–2019 were unfavorable for a better air quality,while it became favorable in 2020–2021.Specifically,emission abatement in 2021 further lowered the concentrations of SO_(2),NO_(2),CO,and PM_(2.5),while the emission of PM_(10) increased.And changes in precursors emissions worsened O_(3) air quality.To meet the demand of improving air quality,more aggressive abatement measures need to be formulated to synergistically reduce NOx,volatile organic compounds,and coarse particles.

Size distribution and chemical characteristics of particles from crop residue open burning in North China

Crop residue open burning is an important emission source of ambient particles in China.This study analyzed the particle emission characteristics of crop residue open burning through combustion experiments with a novel open combustion simulation device using three typical crop straws in north China(corn,wheat,and rice).Particle samples size ranging from 0.006–9.890μm were collected by an Electrical Low Pressure Impactor plus,a high size-resolution instrument capable of dividing particles into 14 size stages.The size distributions of organic carbon(OC),elemental carbon(EC),water-soluble ions,and elements were analyzed,and source chemical profiles were constructed for PM0.1,PM1,PM2.5,and PM10.The number concentration of particles was concentrated in the Aiken nuclei mode(0.006–0.054μm),accounting for 75%of the total number,whereas the mass concentration was concentrated in the accumulation mode(0.054–0.949μm),accounting for 85.43%of the mass loading.OC,EC,Cl−,and K(include total K and water-soluble K)were the major chemical components of the particles,whose mass percentage distributions differed from those of other components.These fivemain components exhibited a bell-shaped size distribution in the 0.006–9.890μm range,whereas the other components exhibited a U-shaped distribution.Among the chemical profiles for PM0.1–PM10,OC was the most important component at 10–30%,followed by EC at 2%–8%.The proportions of K^(+),Cl^(−),and K varied substantially in different experimental groups,ranging from 0–15%,and K+and Cl−were significantly correlated(r=0.878,α=0.000).

Impact of meteorological condition changes on air quality and particulate chemical composition during the COVID-19 lockdown

Stringent quarantine measures during the Coronavirus Disease 2019(COVID-19)lockdown period(January 23,2020 to March 15,2020)have resulted in a distinct decrease in anthropogenic source emissions in North China Plain compared to the paralleled period of 2019.Particularly,22.7%decrease in NO_(2)and 3.0%increase of O_(3)was observed in Tianjin,nonlinear relationship between O_(3)generation and NO_(2)implied that synergetic control of NOx and VOCs is needed.Deteriorating meteorological condition during the COVID-19 lockdown obscured the actual PM2.5 reduction.Fireworks transport in 2020 Spring Festival(SF)triggered regional haze pollution.PM2.5 during the COVID-19 lockdown only reduced by 5.6%in Tianjin.Here we used the dispersion coefficient to normalize the measured PM2.5(DN-PM2.5),aiming to eliminate the adverse meteorological impact and roughly estimate the actual PM2.5 reduction,which reduced by 17.7%during the COVID-19 lockdown.In terms of PM2.5 chemical composition,significant NO_(3)−increase was observed during the COVID-19 lockdown.However,as a tracer of atmospheric oxidation capacity,odd oxygen(Ox=NO_(2)+O_(3))was observed to reduce during the COVID-19 lockdown,whereas relative humidity(RH),specific humidity and aerosol liquid water content(ALWC)were observed with noticeable enhancement.Nitrogen oxidation rate(NOR)was observed to increase at higher specific humidity and ALWC,especially in the haze episode occurred during 2020SF,high air humidity and obvious nitrate generation was observed.Anomalously enhanced air humidity may response for the nitrate increase during the COVID-19 lockdown period.

Insight into the critical factors determining the particle number concentrations during summer at a megacity in China

To identify the critical factors impacting the number concentration of particles with the aerodynamic diameters less than 2.5 μm(PNC_(2.5)), the continuous measurement of PNC_(2.5),chemical components in PM_(2.5), gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC_(2.5) was 2839 ± 2430 d N/dlog Dp 1/cm^3 during the campaign. Compared to other meteorological parameters, the relative humidity(RH) had the strongest relationship with PNC_(2.5), with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC_(2.5).The important influence of secondary reactions on PNC_(2.5) was inferred due to higher correlation coefficients between PNC_(2.5) and SO_4^(2-), NO_3^-, NH_4^+(r = 0.78–0.89; p < 0.01) and between PNC_(2.5) and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter(r = 0.42–0.49; p < 0.01). Under specific RH conditions, there were even stronger correlations between PNC_(2.5) and NO_3^-, SO_4^(2-), NH_4^+, while those between PNC_(2.5) and EC, OC were relatively weak, especially when RH exceeded 50%. Principal component analysis(PCA) and Pearson's correlation analysis indicated that secondary sources, vehicle emission and coal combustion might be major contributors to PNC_(2.5). Backward trajectory and potential source contribution function(PSCF) analysis suggested that the transport of air masses originated from these regions around Tianjin(Liaoning, Hebei, Shandong and Jiangsu) influenced critically PNC_(2.5). The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC_(2.5) by PSCF model.