Examining the Experiences and Challenges of Haze-Fog Governance in China

With the rapid development of industrialisation and urbanisation, China is facing the challenge of severe HF (Haze-Fog) pollution. This essay compares the advantages and disadvantages of China’s HF management and summarizes the important lessons China can teach the rest of the world about applying this tactic. China’s capabilities in the digital economy, National Innovation Demonstration Zones, and urban innovation systems are examined in this article, along with its shortcomings in information mechanisms and pollution sources. This essay also summarizes China’s achievements, particularly regarding local autonomy. The essay goes on to say, however, that China is probably going to be under more pressure to manage HF in the future, both in terms of long-term solutions and the economy.

HAZE-TO-FOG TRANSFORMATION DURING A LONG LASTING,LOW VISIBILITY EPISODE IN NANJING

Haze-to-fog transformation during a long lasting,low visibility episode was examined using the observations from a comprehensive field campaign conducted in Nanjing,China during 4-9 December 2013.In this episode,haze was transformed into fog and the fog lasted for dozens of hours.The impacts of meteorological factors such as wind,temperature(T) and relative humidity(RH) on haze,transition and fog during this episode were investigated.Results revealed significant differences between haze and fog days,due to their different formation mechanisms.Comparison was made for boundary-layer conditions during hazy days,haze-to-fog days and foggy days.Distributions of wind speed and wind direction as well as synoptic weather conditions around Nanjing had determinative impacts on the occurrences and characteristics of haze and fog.Weakened southerly wind in southern Nanjing resulted in high concentration of pollutants,and haze events occurred frequently during the study period.The wind speed was less than 1 m s^(-1) in the haze event,which resulted in a stable atmospheric condition and weak dispersion of the pollutants.The height of the temperature inversion was about 400 m during the period.The inversion intensity was weak and the temperature-difference was 4℃ km^(-1) or less in haze,while the inversion was stronger,and temperature-difference was about 6℃ km^(-1),approaching the inversion layer intensity in the fog event.Haze event is strongly influenced by ambient RH.RH values increased,which resulted in haze days evidently increased,suggesting that an increasing fraction of haze events be caused by hygroscopic growth of aerosols,rather than simply by high aerosol loading.When RH was above 90%,haze aerosols started to be transformed from haze to fog.This study calls for more efforts to control emissions to prevent haze events in the region.

A Distinguishing Method and Distribution Characteristics of Fog and Haze Days in Fuzhou

For data of atmospheric composition missing, fog and haze days were distinguished based on the standard of meteorological industry Observation and Forecasting Levels of Haze （QX/T113-2010） and four user-defined standards, and using data of surface meteorological factors in Fuzhou City, China from 2005 to 2011, temporal distributions of fog and haze days were analyzed respectively to provide methods for fog and haze forecast. The results showed that there were 28.9 fog days and 89.7 haze days per year in Fuzhou. Both fog and haze days were variable, and there might be a day difference of twice to thrice among the years. They were the most in 2007, and then decreased in recent years. Both fog and haze days were more in winter and spring, accounted for 94.1% and 70.1% respectively, while in summer and autumn, they only accounted for 5.9% and 29.9% respectively. In a day, fog mainly occurred from night to early morning, while haze occurred mainly at about noon, which demonstrated that fog and haze are different synoptic phenomena. The mass concentration of PM2.5 in fog days was 34 μg/m^3, while it was 61 μg/m^3 in haze days, and in 22% of haze days it was larger than 75 μg/m3, which was above the national second-grade ambient air quality standard.

Cause Analysis on the Extreme Fog-haze Event in East China in January 2013

Characteristics and cause of the fog-haze event in East China in January 2013 were analyzed with the meteorological conventional observation data and atmospheric composition observation data. Results showed that fog or haze days in east area of Southwest China and most areas of central east China were more than 20 days in this month, especially in east of North China, Huanghuai and Jianghuai regions,that were 10 -15 days more than in the same period of normal years. 500 hPa circulation presented zonal type, cold air wasn＇t active, south-branch trough was weaker, and precipitation amounts was small, which was the weather background of the extreme fog and haze. Northwest airflow at upper layer of East Asia mid-high latitude,less cloud,ground temperature reduction at night, and warm dry air coverd at 850 hPa that led to temperature inversion near surface layer,which was the key thermal factor of fog and haze formation. High humidity near the ground ,weak horizontal wind speed, and weak ascending motion ,which were not favorable for horizontal diffusion and vertical exchange of water vapor and pollutant but were the dynamic factors of maintaining fog and haze. Whether there was a water vapor saturated layer performance in relative humidity /〉90% below 925 hPa or not can be looked as a basis of distinguishing between fog and haze.

A Brief Analysis of the Causes and Countermeasures of Fog-Haze in Beijing-Tianjin-Hebei Region

Since China broke the blockade and opened the country to the outside world, many township enterprises develop quickly. Together with the pollution caused by China’s coal-burning as the main source of national energy, the pollution caused by small and medium-sized enterprises in towns and villages due to their small investment, low technology level and weak environmental awareness, and the pollution caused by a sharp increase in motor vehicle emissions lead to the fact that fog-haze has been rampant in China’s cities and urban agglomerations for nearly two decades, especially in the Beijing-Tianjin-Hebei region. This paper sorted out the current situation of fog-haze and analyzed the causes of fog-haze from the two aspects of natural and man-made causes, discussed the harms of fog-haze to human body, environment and life, and put forward the concrete measures to solve the fog-haze problem.

Economy, Environment and Government: Study on the Path of Supply-Side Reform Forced by the Fog-Haze

Unbalanced development in term as industrial structure and the efficiency use of energy have aggravated environmental pollution to different degrees resulting in the increase of range, time and degree of fog-haze. This, in turn, forced the government to carry out supply-side reforms, to improve energy efficiency and optimize the industrial structure to weaken the environmental pollution. To tackle these problems, this work provides an index system for the issues related to fog-haze, uses a non-linear ST-SVAR model to reflect the effects of industrial structure and energy use efficiency on fog-haze. Results indicated that: First, current industrial structure and energy use efficiency have greater impact on the comprehensive equation of fog-haze risk than itself. With the passage of time, this influence is still gradually expanding. Second, the equations of industrial structure and energy use efficiency are strongly influenced by themselves, and other variables as the current period have less impact on them. Finally, the non-linear or asymmetric relationship is shown among industrial structure, energy use efficiency, and the fog-haze comprehensive risk equation.

Changing Trend and Mutation Analysis of Number of Fog and Haze Days in Baoji City during 1981-2013

Based on data of number of fog and haze days in Baoji City from 1981 to 2013,the changing trends and mutation of number of fog and haze days in Baoji over the past 33 years were analyzed by using trend coefficient,tendency rate,linear regression analysis,anomaly percentage,Mann-Kendall mutation test and sliding t test.The results showed that during the 33 years,the number of fog and haze days in Baoji declined by 16.253d/10 a,and there was a cyclical turbulence every 6,15 or 28years.The frequency of fog and haze weather was the highest in winter,followed by spring and autumn,while it was the lowest in summer.According to the anomaly percentage of the number of fog and haze days in 12 months during 1981-2013,the anomaly percentage changed most greatly in July,followed by September,October,April,May,June,August,February and March,but it fluctuated less greatly in January.The number of fog and haze days from 1981 to 2013had obvious mutation trends in a single year and a single season,and mutation types are different.

基于数值模式与客观方法的辽宁地区空气质量预报检验分析

为检验数值模式和客观方法的空气质量产品预报能力,基于中国气象科学研究院(简称气科院,下同)CUACE模式、中国气象局沈阳大气环境研究所(简称沈阳大气所,下同)CUACE模式和中央气象台(简称中央台,下同)空气质量客观预报方法的产品,利用辽宁地区14个地市大气污染物质量浓度地面观测资料,对2019年1月至2021年4月各家预报产品在辽宁地区的预报效果进行检验。结果表明:中央台的环境空气质量指数(Air Quality Index,AQI)预报偏大,气科院和沈阳大气所偏小;各家的PM_(2.5)和PM_(10)预报均偏小,但中央台的误差最小;各家的O_(3)预报均偏大,气科院的预报误差最小。各家产品对PM_(2.5)和O_(3)浓度变化趋势的预报能力较高,对AQI范围的预报能力是强于AQI等级的。各家产品预报的PM_(2.5)质量浓度离散度和预报偏差最小,TS评分最高;大气污染物浓度和AQI在辽宁东南部的预报可靠性最高、中部地区最差。三家产品相比,中央台在辽宁地区的预报能力最强,对AQI、大气污染物浓度和首要污染物的预报TS评分均为最高,特别是在有(或无明显首要污染物)特定大气污染物对应的季节,预报更具有指导性。沈阳大气所的本地化CUACE模式对于大气污染物浓度和AQI的预报能力显著提高。

测风激光雷达在青岛低能见度天气下的适用性

利用2021年4月—2022年12月青岛国家基本气象站多普勒测风激光雷达和L波段探空系统低空风场观测数据,对比非降水时低能见度天气下测风激光雷达的探测高度和精度。结果表明:测风激光雷达在青岛地区具有良好的适用性,在能见度大于10000 m的非降水天气,其平均最大探测高度稳定在约1200 m,水平风速均方根误差约为1.2 m·s^(-1),水平风向均方根误差约为25°。在能见度小于10000 m的低能见度天气下,测风激光雷达在不同能见度和相对湿度范围内的探测高度和精度受干扰程度存在差异。在能见度为1000~10000 m、相对湿度小于90%的霾天,此时大气能见度降低主要是气溶胶粒子含量增加所致,测风激光雷达的探测能力与高能见度天气下相当。当相对湿度高于95%时,此时大气能见度降低是空气中水汽含量的增加所致,严重干扰了激光在大气中的传输,测风激光雷达的探测高度和精度均有所降低,尤其在能见度小于1000 m的雾天,需谨慎使用其风速和风向数据。

2024年1月大气环流和天气分析

2024年1月大气环流的主要特征是:北半球极涡呈偶极型分布,欧亚中高纬环流呈纬向“两槽一脊”型,东亚大槽偏东。1月,全国平均降水量为16.3 mm,较常年同期(14.1 mm)偏多15.6%;全国平均气温-3.8℃,较常年同期(-4.8℃)偏高1.0℃。月内气温起伏较大,出现了1次全国型寒潮过程和2次大范围持续性雾-霾天气过程。其中20—22日的寒潮天气过程具有影响范围广、降温幅度大、大风持续时间长、暴雪极端性强等特点。

2023年12月大气环流和天气分析

2023年12月大气环流的主要特征是:北半球极涡呈多极型分布,欧亚中高纬环流经向度大,东亚大槽偏强,西太平洋副热带高压异常强盛。12月,全国平均降水量为12.2 mm,较常年同期(11.9 mm)偏多2.5%;全国平均气温为-2.6℃,比常年同期(-3.0℃)偏高0.4℃。月内共出现6次冷空气过程、1次沙尘天气过程和1次大范围持续性雾-霾天气过程。其中13—16日,我国大部地区遭遇的强寒潮过程具有影响范围广、降温幅度大和低温极端性显著等特点。

基于无人机垂直观测的连云港地区一次污染天气分析

2020年12月11—13日连云港地区出现了一次大范围重污染天气过程,利用搭载在无人机上的粒子计数器和气溶胶采样装置对连云港地区近地面大气颗粒物进行垂直探测,结合风廓线雷达、地基微波辐射计以及地面气象观测和再分析资料,分析了大气颗粒物浓度廓线和气象要素垂直分布特征,并通过后向轨迹追踪模式分析了污染物来源及扩散情况,探究了此次污染天气的成因。结果表明:风廓线雷达观测的高空风场和微波辐射计测量的温湿变化特征与颗粒物垂直特征具有较好的对应关系,从污染物的垂直分布看,污染严重时段,污染物主要集中在200 m以下高度,污染层浅薄,呈现明显的双峰结构,在污染扩散阶段,随着逆温层减弱抬升,污染物向上扩散,地面污染物浓度明显下降,污染层较为深厚。污染物外源输送和污染物在连云港地区有利气象条件下的吸湿增长是本轮污染天气的主要原因。其中上游污染物传输主要来源于徐州和山东半岛中部地区,污染物离开连云港后主要沿东南到东方向向海上扩散,风向的转变可能是预报污染开始消散的关键气象条件,而风速的大小则是污染物消散快慢的关键。

融合雾线先验与对比度增强的图像去雾研究

经传统大气散射模型及雾线先验算法处理后的图像出现浓雾区域边缘模糊、物体边缘有光晕及颜色失真等现象,由此提出一种融合雾线先验与对比度增强技术的去雾算法。该算法首先基于雾线先验模型粗略估计有雾图像的透射率系数;然后采用软抠图技术对粗略估计的结果进行校准,得到相对准确的透射率,并选取区域的亮点作为大气环境光值,通过大气散射模型获得初步图像;再结合边缘信息,通过高斯滤波器对初步结果进行优化;最后用Frankle-McCann Retinex算法调节图像的对比度,获得优化后的去雾图像。实验结果表明:在客观评价结果中,与雾线先验算法相比,PSNR值平均提升了1.63左右,SSIM值平均提升了3%左右。由此可知,该算法与传统去雾算法相比,图像去雾效果显著,在改善图像细节的同时,也减小了图像色彩失真的影响。

Analysis of a Haze Weather Process in Eastern China from November 11th to 17th, 2020

This study mainly introduces a large-scale heavy haze weather process in northern China from November 11 to 17, 2020, and analyzes the weather process. Methods such as comparative analysis and data analysis were used in this study. The main reasons for the formation of smog are as follows. First, the relative humidity is high and the water vapor content is relatively high. Second, the atmosphere is in a static and stable state, and suspended particulate matter in the atmosphere is not easy to diffuse and dilute, so it will gradually accumulate in urban areas and suburban areas. Third, there is a temperature inversion in the vertical direction, and the suspended particles in the air are difficult to drift to high altitudes and are blocked at low altitudes and near the ground. Fourth, there must be cooling conditions. Meteorological factors are the external causes for the formation of smog. And inversion intensity has a negative correlation with visibility, which has some indicating importance in fog and haze predictions. Large-scale haze weather mainly occurs in the large-scale atmospheric circulation with weak cold air and good water vapor conditions, and wind near the ground is small. Due to the high humidity in haze weather, fog droplets provide adsorption and reaction sites, accelerating the conversion of gaseous pollutants to liquid particles. At the same time, particles are also easy to act as condensation nucleus to accelerate the generation of haze. When the two interact, the pollutants are not easy to diffuse outward, resulting in agglomeration effect, and the pollution is getting heavier.

基于旋翼无人机观测的雾天和霾天VOCs垂直分布特征研究

为研究雾和霾天气下VOCs时空变化特征,于2020年11月19日—2021年1月15日在江苏省东海国家气象观测站进行为期58 d的外场观测试验。利用自主研发的多旋翼无人机捕获2次辐射雾和2次霾天气过程,获得气温、气压、相对湿度、风向、风速、VOCs、O_(3)等7种要素100多条垂直廓线。结果表明:时间上,霾过程夜间VOCs体积浓度(0.225~0.253 ppm(parts per million,1 ppm=10-6))明显高于白天(0.191~0.205 ppm),雾形成前体积浓度(0.121~0.239 ppm)显著高于雾过程(0.056~0.209 ppm)。雾过程中VOCs体积浓度与雾强度变化相反,雾层高度与VOCs体积浓度剧烈变化高度一致,雾层(<200 m)中VOCs体积浓度(0.172~0.178 ppm)明显减小,显著低于雾形成前(0.195~0.240 ppm),雾层以上浓度变化大,雾结束后1 h内保持雾过程中分布特点。雾对逆温层中的水溶性污染物有清除作用,VOCs体积浓度和O_(3)质量浓度均下降。

CLDAS陆面融合实况数据对天津雾和霾判识的准确性分析

雾和霾是危害人类健康和影响社会经济发展的灾害天气,精细化的实况资料能够在雾和霾的防治中发挥重要作用。利用2017年12月1日至2020年11月30日天津及其周边地区国家气象观测站资料、Himawari-8卫星L1级全圆盘观测数据和L3级气溶胶光学厚度产品,分析了中国气象局陆面数据同化系统(CMA Land Data Assimilation System,CLDAS)能见度和相对湿度融合实况分析产品判识天津地区雾、轻雾和霾的准确性。结果表明:与台站资料相比,CLDAS产品对轻雾、雾和霾的平均检出率分别为90.4%、84.2%和78.8%;CLDAS产品对轻雾的逐月检出率为81.1%~96.4%,雾和霾出现较多的月份,其检出率均在80.0%左右。个例分析表明CLDAS产品判识的雾、轻雾和霾与台站观测结果以及Himawari-8卫星反演检测结果基本一致。CLDAS产品未正确判识雾、轻雾和霾的情况主要表现为雾误判为轻雾(各站为3.8%~21.4%)和霾漏判(各站为8.6%~25.0%)。当台站水平能见度在区间[0,0.75 km)时,CLDAS能见度的误差主要导致雾误判为轻雾;在区间[0.75,7.5 km)时,CLDAS能见度的误差主要导致霾漏判;在区间[7.5,15 km)时,CLDAS能见度的误差主要导致轻雾和霾空报。当台站相对湿度大于40%且小于等于60%时,CLDAS相对湿度的误差主要导致霾误判为轻雾。总体而言,CLDAS产品对天津地区雾、轻雾和霾的判识准确性较好,能够为雾、轻雾和霾的精细化监测提供参考,改善雾和霾监测中能见度观测站点稀少、空间覆盖不足的现状。

青岛地区一次雾—霾过程能见度特征及影响因素分析

利用2021年11月16—20日青岛、平度、黄岛、胶州站的能见度等气象数据和邻近环境监测站PM 2.5浓度及水溶性离子浓度等观测数据,分析了雾—霾过程中能见度的动态变化特征及其影响因素。结果表明:2021年11月16—20日青岛整个雾霾过程大致经历了轻雾→干霾→湿霾→干霾→湿霾→干霾→湿霾→轻雾的转换,地理位置差异导致内陆站点未经历轻雾阶段且霾阶段开始时间较沿海站提前8 h。雾、霾过程大气层结稳定且有一定的湿度条件,地面风速≤2 m·s^(-1),垂直运动速度0.0~0.5 Pa·s^(-1)。偏东风携带的大量水汽、>80%的湿度层变化是干霾、湿霾转化的重要因素。能见度随PM 2.5浓度、相对湿度的增加而逐渐下降,相对湿度增大时能见度与PM 2.5浓度的相关性减小,湿霾较干霾阶段PM 2.5浓度升高14.1%,能见度下降47.4%,霾转化为雾后能见度降低7.6%。在干霾阶段能见度的变化主要受PM 2.5浓度的影响;在湿霾阶段能见度受PM 2.5浓度和相对湿度的共同影响;在雾阶段能见度主要受相对湿度的影响。霾阶段SNA(SO_(4) ^(2- )、NO_(3)^(-)、NH_(4)^(+))浓度、SOR(硫氧化率)、颗粒物中液态水含量随污染等级升高逐渐增加而能见度逐渐降低。从后向轨迹分析可以看出,霾期间气团从内陆起源经江苏、河南等地到达青岛污染程度深,雾期间气团经沿海地区到达青岛湿度大、污染程度小。

2023年1月大气环流和天气分析

2023年1月大气环流的主要特征是:北半球极涡呈偶极型分布,东北亚低涡偏强。东亚大槽偏东,南支槽偏弱。1月全国平均降水量为8.8 mm,较常年同期(14.3 mm)偏少38%;全国平均气温为-4.4℃,较常年同期(-4.8℃)偏高0.4℃。月内气温冷暖起伏较大,中下旬出现3次冷空气过程,气温由上旬异常偏暖逆转为下旬普遍偏冷的格局,黑龙江出现极寒天气,漠河最低气温达-53℃,刷新我国最低气温纪录。13—16日出现年度首次大范围寒潮天气,具有降温剧烈、风力大、雨雪范围广等特点,新疆、陕西、山西、河南等地出现大雪或暴雪,北方地区出现首次沙尘天气过程。此外,上旬大气扩散和湿清除条件较为不利,出现持续性雾-霾天气。

基于多波长激光雷达探测雾和霾的应用研究

该文利用355 nm&532 nm的双波长大气颗粒物监测激光雷达和910 nm的激光云高仪3个不同波长的激光雷达来探测雾、霾过程,并结合地面气象要素,分析雾、霾过程中气溶胶的光学特性和吸湿性质。结果表明,雾后向散射强度较大,后向散射系数在垂直方向上变化率大,出现高度较低;霾后向散射强度较小,空间分布均匀,后向散射系数垂直变化率小,出现高度较高。对雾、霾天气中气溶胶吸湿性质进行分析,得出随着气溶胶粒子的吸湿增长,较长的波长对大粒子更为敏感,且相对湿度越大,气溶胶粒子的吸湿增长速度越快。吸湿增长因子和Angstrom指数呈负相关,气溶胶粒子增长的越快,Angstrom指数减小的速度也越快。在近地面处,雾、霾天气的Angstrom(910 nm/532 nm)指数小于Angstrom(532 nm/355 nm)指数,而晴天与之相反,表明雾、霾天气时,大气中有较多的粗粒子存在,而晴天则以细粒子为主。

2022年11月大气环流和天气分析

2022年11月大气环流的主要特征是:北半球极涡呈偶极型,东亚大槽偏弱,南支槽偏弱,副热带高压偏强。11月,全国平均降水为26.9 mm,比常年同期(20.2 mm)偏多33.2%;全国平均气温为4.8℃,较常年同期(3.3℃)偏高1.5℃。月内气温冷暖起伏较大,前中期冷空气活动偏弱,大部地区气温偏高,降水偏少;后期受强冷空气、活跃南支槽影响,气温大幅降低,降水显著增多。月内出现了1次全国型寒潮过程,影响范围广、降温幅度大,以及2次大范围持续性雾-霾天气过程。