Temporal changes in the diet composition and trophic level of walleye pollock (Gadus chalcogrammus) inhabiting the middle-eastern coast of Korea

The influences of oceanographic changes on diet composition and trophic level for pollock (Gadus chalcogrammus) inhabiting the East Sea off the Korean coast were examined based on stomach content and stable isotope analyses during 2016 and 2017. The diets of pollock consisted mainly of benthic crustaceans (particularly carid shrimps and euphausiids) and cephalopods, with a predominance of teleosts in the diets of larger individuals in deeper habitats. In 2016, amphipods, carid shrimps and cephalopods featured strongly in pollock diets, and the contribution of amphipods decreased in the diets of larger individuals and deeper depths. In 2017, euphausiids dominated at shallower depths, whereas the contributions of carid shrimps and teleosts increased in deeper habitats. Body-size-related differences in carbon stable isotope (δ13C) values were present in both 2016 and 2017, but size-related differences in nitrogen stable isotope (δ15N) values were only observed in 2017. The increased contribution of euphausiids during 2017 resulted in a distinct decrease in the trophic level of pollock compared to co-occurring higher trophic level predators, which can be linked to changes in habitat water temperature. Combined stomach contents and isotopic analyses provide a more comprehensive understanding of how fish diets and trophic levels fluctuate with changes in the type and abundance of prey resources in response to environmental changes.

Climate modulation of external forcing factors on air quality change in Eastern China: Implications for PM2.5 seasonal prediction

Meteorological conditions significantly influence the frequency and duration of air pollution events, making the prediction of seasonal variations of PM2.5 concentration crucial for air quality control. This study analyzed the spatiotemporal variations of PM2.5 concentration anomalies over the past 39 years (1980-2018) in winter (November to January) over eastern China based on the empirical orthogonal function (EOF) method. Regression analysis is conducted on external forcing factors such as sea ice, sea temperature, and snow cover in the pre-autumn (September to October) using the time series of the first three modes. Nine key factors were selected, which further led to establishing a model for predicting winter PM2.5 concentration in eastern China using the long short-term memory deep learning algorithm (LSTM). Independent verification revealed that the predicted and observed PM2.5 concentration distributions were consistent, with the absolute value of deviation within 15 μg·m-3 between 2016 and 2018. The correlation coefficients between the predicted and observed values were between 0.42 and 0.93 over eight key cities in the past 10 years (2009-2018). The contribution rates of the nine factors to PM2.5 concentration were calculated to explore their impact on PM2.5 concentration during winter. The Arctic sea ice (ASI) was found to be the key contributor to the winter PM2.5 concentration in eastern China. The predictors can be monitored in real time; hence, the model provides a real-time predictive tool, improving the prospects of predicting seasonal PM2.5 pollution, especially in vulnerable regions such as eastern China.

Weather-Climate Anomalies and Regional Transport Contribute to Air Pollution in Northern China During the COVID-19 Lockdown

Two persistent and heavy haze episodes during the COVID-19 lockdown (from 20 Jan to 22 Feb 2020) still occur in northern China, when anthropogenic emissions, particularly from transportation sources, are greatly reduced. To investigate the underlying cause, this study comprehensively uses in-situ measurements for ambient surface pollutants, reanalysis meteorological data and the WRF-Chem model to calculate the contribution of NO_x emission change and weather-climate change to the "unexpectedly heavy" haze. Results show that a substantial NO_x reduction has slightly decreased PM_2.5 concentration. By contrast, the weakest East Asian winter monsoon (EAWM) in the 2019-2020 winter relative to the past decade is particularly important for haze occurrence. A warmer and moister climate is also favorable. Model results suggest that climate anomalies lead to a 25-50 μg m^-3 increase of PM_2.5 concentration, and atmospheric transport is also an important contributor to two haze episodes. The first haze is closely related to the atmospheric transport of pollutants from NEC to the south, and fireworks emissions in NEC are a possible amplifying factor that warrants future studies. The second one is caused by the convergence of a southerly wind and a mountain wind, resulting in an intra-regional transport within BTH, with a maximal PM_2.5 increment of 50-100 μg m^-3. These results suggest that climate change and regional transport are of great importance to haze occurrence in China, even with significant emission reductions of pollutants.

Fog–Haze Transition and Drivers in the Coastal Region of the Yangtze River Delta

Low-visibility events (LVEs) are severe weather phenomena that are closely linked with anthropogenic pollution, which negatively affects traffic, air quality, human health, and the environment. This study conducted a two-month (from October to December 2019) continuous measurement campaign on Chongming Island in Shanghai to characterize the LVEs transition and its drivers. The LVEs accounted for 38% of the time during the campaign, of which mist accounted for 14%, fog–haze for 13%, haze for 6%, and fog for 5%. The fog and mist mainly occurred from midnight to early morning, while haze mostly occurred during the daytime. Different LVEs were interdependent and transitioned from one to another. Fog generally turned into haze after sunrise, while haze turned into fog after sunset. Their formation and evolution were caused by the combined impacts of meteorological conditions and aerosol particles. It was found that temperature difference was the dominant meteorological factor driving the evolution of LVEs. Within the short term, cooling led to a greater increase in relative humidity than humidification. Radiative cooling during the night promoted the formation of fog and mist. During fog and mist events, cloud condensation nuclei (CCN) were mainly internally mixed due to the impact of fog droplet removal and aqueous/heterogeneous aerosol reactions occurring under high humidity. Increased CCN concentration appeared to increase the fog droplet number and liquid water content in fog events. Overall, conditions of high humidity and high particle loading were conducive to LVEs, whereas conditions of sufficient water vapor at a low particle level and sufficient particles at a low humidity level also caused LVEs. This study provided insights into LVEs classification, evolution scheme, and aerosol roles from a micro point of view. The findings could be useful for improving forecasts of local radiative fog and other LVEs.

Climatic–Environmental Effects of Aerosols and Their Sensitivity to Aerosol Mixing States in East Asia in Winter

To establish the direct climatic and environmental effect of anthropogenic aerosols in East Asia in winter under external, internal, and partial internal mixing (EM, IM and PIM) states, a well-developed regional climate–chemical model RegCCMS is used by carrying out sensitive numerical simulations. Different aerosol mixing states yield different aerosol optical and radiative properties. The regional averaged EM aerosol single scattering albedo is approximately 1.4 times that of IM. The average aerosol effective radiative forcing in the atmosphere ranges from −0.35 to +1.40 W/m2 with increasing internal mixed aerosols. Due to the absorption of black carbon aerosol, lower air temperatures are increased, which likely weakens the EAWM circulations and makes the atmospheric boundary more stable. Consequently, substantial accumulations of aerosols further appear in most regions of China. This type of interaction will be intensified when more aerosols are internally mixed. Overall, the aerosol mixing states may be important for regional air pollution and climate change assessments. The different aerosol mixing states in East Asia in winter will result in a variation from 0.04 to 0.11 K for the averaged lower air temperature anomaly and from approximately 0.45 to 2.98 μg/m3 for the aerosol loading anomaly, respectively, due to the different mixing aerosols.

Effects of Meteorology Changes on Inter-Annual Variations of Aerosol Optical Depth and Surface PM2.5 in China—Implications for PM2.5 Remote Sensing

PM2.5 retrieval from satellite-observed aerosol optical depth (AOD) is still challenging due to the strong impact of meteorology. We investigate influences of meteorology changes on the inter-annual variations of AOD and surface PM2.5 in China between 2006 and 2017 using a nested 3D chemical transport model, GEOS-Chem, by fixing emissions at the 2006 level. We then identify major meteorological elements controlling the inter-annual variations of AOD and surface PM2.5 using multiple linear regression. We find larger influences of meteorology changes on trends of AOD than that of surface PM2.5. On the seasonal scale, meteorology changes are beneficial to AOD and surface PM2.5 reduction in spring (1–50%) but show an adverse effect on aerosol reduction in summer. In addition, major meteorological elements influencing variations of AOD and PM2.5 are similar between spring and fall. In winter, meteorology changes are favorable to AOD reduction (−0.007 yr−1, −1.2% yr−1; p < 0.05) but enhanced surface PM2.5 between 2006 and 2017. The difference in winter is mainly attributed to the stable boundary layer that isolates surface PM2.5 from aloft. The significant decrease in AOD over the years is related to the increase in meridional wind speed at 850 hPa in NCP (p < 0.05). The increase of surface PM2.5 in NCP in winter is possibly related to the increased temperature inversion and more stable stratification in the boundary layer. This suggests that previous estimates of wintertime surface PM2.5 using satellite measurements of AOD corrected by meteorological elements should be used with caution. Our findings provide potential meteorological elements that might improve the retrieval of surface PM2.5 from satellite-observed AOD on the seasonal scale.

A review on factors influencing fog formation, classification, forecasting, detection and impacts

With the changing climate and environment, the nature of fog has also changed and because of its impact on humans and other systems, study of fog becomes essential. Hence, the study of its controlling factors such as the characteristics of condensation nuclei, microphysics, air–surface interaction, moisture, heat fluxes and synoptic conditions also become crucial, along with research in the field of prediction and detection. The current review expands for the period between 1976 to 2021, however, especially focused on the research articles published in the last two decades. It considers 250 research papers/research letters, 24 review papers, four book chapters/manuals, five news articles, 15 reports, six conference papers and five other online readings. This review is a compilation of the pros and cons of the techniques used to determine the factors influencing fog formation, its classification, tools and techniques available for its detection and forecast. Some recent advanced are also discussed in this review: role of soil properties on fogs, application of microwave communication links in the detection of fog, new class of smog, and how the cognitive abilities of humans are affected by fog. Recently India and China are facing an emergence and repetitions of fog haze/smog and thus their policies initiatives are also briefly discussed. It is concluded that the complexity in fog forecasting is high due to multiple factors playing a role at multiple levels. Most of the researchers have worked upon the role of humidity, temperature, wind, and boundary layer to predict fogs. However, the role of global wind circulations, soil properties, and anthropogenic heat requires further investigations. Literature shows that fog is being harnessed to address water insecurity in various countries, however, coastal areas of Angola, Namibia and South Africa, Kenya, Eastern Yemen, Oman, China, India, Sri Lanka, Mexico, along with the mountainous regions of Peru, Chile, and Ecuador, are some of the potential sites that can benefit from the installation of fog water harvesting systems.

Fog collection behavior of bionic surface and large fog collector: A review

Water shortages are currently becoming more and more serious due to complicated factors such as the development of the economy, environmental pollution, and climate deterioration. And it is the best solution to the problems faced by people in today's world to investigate the bionic structure of nature and explore effective methods for fog collection. Herein, we've illustrated the bionic structures of the Namib desert beetle, cactus spines, and spider silk, and we imitate and further modify the respective bionic structures, as well as construct multifunctional bionic structures to improve fog collection. In addition, we also expound the fog collection behavior of a large fog collector, and an excellent fog capture effect was achieved through studying the mesh structure, the surface modification of the mesh, and the construction of the fog collector. The advantages and limitations of fog collection by a harp fog collector were also explored. We hope that through this review, relevant researchers can have a deeper understanding of this field and thus promote the development of fog collection.

Impact of North Atlantic-East Asian teleconnections on extremely high January PM10 cases in Korea

In this study, we investigated the daily variability of PM₁₀ concentrations in January in Korea during the past 19 years (2001-2019), as well as the associated atmospheric circulation patterns. The daily PM₁₀ concentrations were classified into three cases: low (L; < 50 μg/m³), high (H; 50-100 μg/m³), and extremely high (EH; ≥ 100 μg/m³). We found that the strength of the East Asian winter monsoon influenced the PM₁₀ variability in the L and H cases. However, the EH cases were strongly influenced by the rapid growth of barotropic warming (anticyclonic anomaly) over the eastern North Atlantic and Northern Europe (ENE), and the stationary Rossby waves grew rapidly over Eurasia within only four days. Analysis of the quasi-geostrophic geopotential tendency budget revealed that the anticyclonic anomaly over the ENE was enhanced by vorticity advection. Linear baroclinic model experiments confirmed that vorticity forcing over the ENE induces favorable atmospheric conditions for the occurrence of EH PM₁₀ events in East Asia. As a result, the PM₁₀ concentration sharply increased sharply by approximately three times over four days. This study suggests that understanding atmospheric teleconnections between the ENE and East Asia can effectively predict the occurrence of EH PM₁₀ events in Korea, helping to reduce the human health risks from atmospheric pollution.

Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison with observational NWS data acquired in China during a historical period (1975–2014), and projected future changes in NWS under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on an optimal multi-model ensemble. Results showed that most models reproduced the spatial pattern of NWS for all seasons and the annual mean, although the models generally overestimated NWS magnitude. All models tended to underestimate the trends of decline of NWS for all seasons and the annual mean. On the basis of a comprehensive ranking index, the KIOST-ESM, CNRM-ESM2-1, HadGEM3-GC31-LL, CMCC-CM2-SR5, and KACE-1-0-G models were ranked as the five best-performing models. In the projections of future change, nationally averaged NWS for all months was weaker than in the historical period, and the trends decreased markedly under all the different scenarios except the winter time series under SSP2-4.5. Additionally, the projected NWS over most regions of China weakened in both the early period (2021–2060) and the later period (2061–2100).

Fungal Communities on Standing Litter Are Structured by Moisture Type and Constrain Decomposition in a Hyper-Arid Grassland

Non-rainfall moisture (fog, dew, and water vapor; NRM) is an important driver of plant litter decomposition in grasslands, where it can contribute significantly to terrestrial carbon cycling. However, we still do not know whether microbial decomposers respond differently to NRM and rain, nor whether this response affects litter decomposition rates. To determine how local moisture regimes influence decomposer communities and their function, we examined fungal communities on standing grass litter at an NRM-dominated site and a rain-dominated site 75 km apart in the hyper-arid Namib Desert using a reciprocal transplant design. Dominant taxa at both sites consisted of both extremophilic and cosmopolitan species. Fungal communities differed between the two moisture regimes with environment having a considerably stronger effect on community composition than did stage of decomposition. Community composition was influenced by the availability of air-derived spores at each site and by specialization of fungi to their home environment; specifically, fungi from the cooler, moister NRM Site performed worse (measured as fungal biomass and litter mass loss) when moved to the warmer, drier rain-dominated site while Rain Site fungi performed equally well in both environments. Our results contribute to growing literature demonstrating that as climate change alters the frequency, magnitude and type of moisture events in arid ecosystems, litter decomposition rates may be altered and constrained by the composition of existing decomposer communities.

Effects of Early Pollution Control Measures on Secondary Species of PM2.5 in Jiaozuo, China

Various measures for reducing air pollution have been promulgated since 2013 in China. To investigate the synergistic results of emission control and meteorological environment, PM_2.5 samples collected from October 2013 to July 2016 and November 2018 to October 2019 in Jiaozuo city were analyzed for their compositions, secondary species (Ss) variations, and factors changing for Ss formation. The results showed that the concentrations of sulfate, nitrate, ammonium, and secondary organic aerosols (SOAs) generally decreased over the same seasonal period during these years. In addition, the concentrations and proportions of each Ss increased with the increase in the PM_2.5 level in these years, implying that although PM_2.5 levels have been reduced by various control policies, Ss formation would remain the major contributor to PM elevations. The enhanced effects of gas-phase reactions on intensification of sulfate, SOA, and PM were observed in 2018-2019, which was consistent with the elevation of nitrate and SOA at PM levels of >150 μg/m³. Only sulfate in all PM levels sharply decreased after 2015, showing the fine effect of coal-related pollution control and the importance of collaborative control of NO _x , volatile organic compounds, and organic aerosol emissions with SO₂ emissions in the future.

Spatiotemporal variability and evolution of day and night winter fog over the Indo Gangetic Basin using INSAT-3D and comparison with surface visibility and aerosol optical depth

Every year during the peak winter months (December-January), dense and prolonged fog envelops the Indo-Gangetic Basin (IGB) over the Indian sub-continent leading to economic loss. Many efforts are being made to understand its characteristics to improve forecasting skills. In the present work Indian National SATellite (INSAT-3D), a geostationary satellite, retrieved fog data available at every 30 min interval throughout the day and night is used to study its evolution, spatial and temporal variability for the winter months of December 2016 and January 2017 in conjunction with surface measurements. Fog data when compared with ground-based horizontal visibility over different stations in IGB showed good relationship, also depicted similar temporal variability in tune with the favorable meteorological parameters of temperature, relative humidity, and wind speed. It is observed that INSAT-3D captured fog very well for visibility ranging from 0 to 500 m representing very dense, dense, and moderate fog, while, the shallow fog with visibility >600 m is captured occasionally. From the maps of spatial and temporal variability of fog, the regions most affected are identified based on fog duration. The intense fog events covering the entire IGB for long duration are observed mostly in the midnight (00:00-04:00) and early morning (04:00-08:00) hours (local time) of December as compared to January. While in January, moderate intense fog spans the entire IGB during day time also. Due to increase in pollution levels, including biomass burning as inferred from MODIS fire counts, and stable atmosphere, high aerosol optical depths (AOD) are observed across IGB. The high AOD regions (> 0.8) covering central and west IGB, are also the hotspot regions of fog/smog onset and slowly expand over a larger area and intensify.

Seasonal and long-term trends of sulfate, nitrate, and ammonium in PM2.5 in Beijing: implication for air pollution control

Particulate matter pollution in Beijing is a serious environmental problem. In response to this, the Beijing government has implemented comprehensive emission reduction measures in recent years. To assess the effectiveness of these measures, the seasonal and long-term trends in chemical compositions of PM_2.5 in Beijing have been studied based on daily samples collected from July 2015 to April 2016 and literature investigation (2000-2014). Results show that the concentrations of sulfate, nitrate, and ammonium in PM_2.5 have significant seasonal variations, which are related to the changes in meteorological conditions and emission intensities. In addition, the long-term data display that the concentrations of sulfate, nitrate, and ammonium have significantly decreased between 2013 and 2016, which are consistent with the reduction in PM_2.5 levels (~ 11.2 μg/m³ per year). The declines could not be interpreted by the meteorological factors. It suggests that the air pollution control measures in Beijing (2013-2016), especially the decreasing consumption of coal, can effectively decrease the mass concentration of fine particles. To further improve the air quality, similar measures should be adopted in the areas around Beijing. These air pollution control measures taken in Beijing can provide invaluable guidance for mega-cities in China and other developing countries to decrease their PM_2.5 concentration and reduce health risk from particulate pollution.

Evaluation and Projections of Wind Power Resources over China for the Energy Industry Using CMIP5 Models

The energy industry is faced with important investment and optimization choices especially for wind power as a fuel of the future, especially for China which boasts the largest installed wind power capacity. This study therefore assessed the potential status of future wind power over China using Coupled Model Intercomparison Project phase 5 (CMIP5) models. Changes in wind power density relative to the current time period 1981–2005 were then analyzed using near-surface wind speeds extrapolated to hub-height of 90 m above ground level. The results showed relatively modest differences between the models and reanalysis. The majority of the models showed any two of location, shape, and size agreement for peak areas albeit models BCC-CSM-1-1-M, BNU-ESM, and CanESM2 tended to overestimate wind speed by up to 2.5 m/s. The multi-model ensemble mean performed better than most individual models in representing the wind characteristics over the study area. Future changes in wind power density showed an increase (decrease) over the coastal areas of the South China Sea and Bay of Bengal (areas along the 30°–40° N belt). In all, the changes were not significant enough to neither warrant a move away from wind energy nor threaten considerably the marketability and profitability under the present warming scenario rate.

Quantifying the Influences of PM2.5 and Relative Humidity on Change of Atmospheric Visibility over Recent Winters in an Urban Area of East China

Fine particulate matters (PM2.5) and relative humidity (RH) in the ambient atmosphere are the leading anthropogenic and natural factors changing atmospheric horizontal visibility. Based on the analysis of environmental and meteorological data observed over 2013–2019 in Nanjing, an urban area in East China, this study investigated the influences of PM2.5 and RH on atmospheric visibility changes over recent years. The visibility had significantly negative correlations with the PM2.5 concentrations and RH changes. The nonlinear relationships existed between PM2.5 concentrations and visibility, as well as between RH and visibility, with the inflection points in the atmospheric visibility changes. The PM2.5 inflection concentrations were 81.0 μg m−3, 76.0 μg m−3, 49.0 μg m−3, and 33.0 μg m−3, respectively, for the RH ranges of RH < 60%, 60% ≤ RH < 80%, 80% ≤ RH < 90%, and RH ≥ 90%, indicating that the improvement of visibility with reducing PM2.5 concentrations could be more difficult under the humid meteorological condition. The visibility changes were most sensitive to PM2.5 concentrations in the RH range of 60–80% in this urban area of East China. The relative contributions of natural factor RH and anthropogenic factor PM2.5 to variations of wintertime atmospheric visibility were quantified with 54.3% and 45.7%, respectively, revealing an important role of natural factor RH in the change of atmospheric visibility in the urban area of East Asian monsoon region.

Possible Link Between Arctic Sea Ice and January PM10 Concentrations in South Korea

In this study, we investigated the possible teleconnection between PM10 concentrations in South Korea and Arctic Sea ice concentrations at inter-annual time scales using observed PM10 data from South Korea, NCEP R2 data, and NOAA Sea Ice Concentration (SIC) data from 2001 to 2018. From the empirical orthogonal function (EOF) analysis, we found that the first mode (TC1) was a large-scale mode for PM10 in South Korea and explained about 27.4% of the total variability. Interestingly, the TC1 is more dominantly influenced by the horizontal ventilation effect than the vertical atmospheric stability effect. The pollution potential index (PPI), which is defined by the weighted average of the two ventilation effects, is highly correlated with the TC1 of PM10 at a correlation coefficient of 0.75, indicating that the PPI is a good measure for PM10 in South Korea at inter-annual time scales. Regression maps show that the decrease of SIC over the Barents Sea is significantly correlated with weakening of high pressure over the Ural mountain range region, the anomalous high pressure at 500 hPa over the Korean peninsula, and the weakening of the Siberian High and Aleutian low. Moreover, these patterns are similar to the correlation pattern with the PPI, suggesting that the variability of SIC over the Barents Sea may play an important role in modulating the variability of PM10 in South Korea through teleconnection from the Barents Sea to the Korean peninsula via Eurasia.

Changes in the Relationship between Particulate Matter and Surface Temperature in Seoul from 2002–2017

This study focuses on the changes over time in the relationship between surface temperature and particulate matter (PM) concentration over Seoul using long-term observational data. Correlation coefficients between the daily mean PM10 concentration and surface temperature were calculated to investigate the relationship between the two. The PM10 and temperature displayed a strong positive correlation, suggesting the increase in PM was driven by large-scale synoptic patterns accompanying such high temperatures. It was found that the correlation coefficient in 2002–2009 was significantly higher than that of 2010–2017, indicating that the relationship between PM10 concentration and temperature has weakened over time in recent decades. Correlation coefficients between daily averaged temperature and the PM10 of each year were calculated to account for the decreased correlation in the most recent decade. We found that the correlation coefficients between surface temperature and PM of each year exhibited a clear negative correlation with the longitudinal position of the Siberian High, suggesting that the position of the Siberian High might affect the strength of the relationship between PM concentration and temperature over Seoul. We also found that the eastward shift of the Siberian High reduces the standard deviation of pressure over Seoul, indicating reduction of synoptic perturbation. These results imply that the eastward shift of the Siberian High in recent decades might weaken the relationship between the PM and surface temperature over Seoul. This study suggests that the relationship between PM and meteorological variables is changing over time through changes in large climate variability.

Long-term variations in PM2.5 concentrations under changing meteorological conditions in Taiwan

With emission control efforts, the PM_2.5 concentrations and PM_2.5 exceedance days (daily mean PM_2.5 concentrations >35 µg m⁻³) show an apparent declining trend from 2006–2017. The PM_2.5 concentrations increase from the northern to southern part of western Taiwan, and reductions in the PM_2.5 concentration generally decrease from northern to southern part of western Taiwan. Thus, mitigation of the PM_2.5 problem is less effective in southwestern Taiwan than in other regions in Taiwan. Analysis of a 39-year ERA-interim reanalysis dataset (1979–2017) reveals a weakening of the East Asian winter monsoon, a reduction in northeasterly (NE) monsoonal flow, and a tendency of enhanced stably stratified atmospheric structures in Taiwan and the surrounding area. The observed surface wind speed also presents a long-term decline. We can conclude that the long-term PM_2.5 variations in Taiwan are mainly associated with changes in local anthropogenic emissions and modulated by short-term yearly variations due to strong haze events in China. In southwestern Taiwan, the long-term trend of PM_2.5 reductions is possibly offset by worsening weather conditions, as this region is situated on the leeside of the mountains and often subject to stagnant wind when under the influence of NE monsoonal flow.

Winter haze over North China Plain from 2009 to 2016: Influence of emission and meteorology

Analysis of observed PM_2.5 in Beijing since 2009 reveals that winter haze over North China Plain (NCP) peaked in 2012 and 2013 and there was an improvement in air quality until 2016. The variation of wintertime PM_2.5 from 2009 to 2016 is influenced by both emission changes and meteorology conditions, and we quantified the relative contributions from these two aspects. Sensitivity simulation by GEOS-Chem suggested that emission reductions over NCP in 2013-2017 caused 10% decrease of regional mean PM_2.5 concentration in 2016 winter compared to 2012 winter level. We removed emission influence on PM_2.5 to get PM_2.5 that influenced by meteorology (met-influenced PM_2.5). For met-influenced PM_2.5, compared to original-observed PM_2.5(the US Embassy data), percentage of clean days (daily PM_2.5 ≤ 75 μg m^-3) decreases while that of polluted (75 μg m^-3 < daily PM_2.5 ≤150 μg m^-3) and heavily polluted (150 μg m^-3 < daily PM_2.5 ≤ 250 μg m^-3) days increases. However, proportion of extremely polluted (daily PM_2.5 > 250 μg m^-3) days stays unchanged, even if emission reduction is doubled, indicating that the extremely polluted situation over NCP is dominated by meteorological conditions, and emission control from 2013 to 2017 has little effects on the extremely polluted days. We developed an effective haze day index (HDI) to represent the weather conditions conducive to haze days. HDI is constructed based on the normalized near surface meridional wind (V850), temperature difference (δT) between near surface (850 hPa) and upper atmosphere (250 hPa), and the relative humidity at 1000 hPa (RH1000). HDI is skillful to detect 72% of the severe haze days (daily PM_2.5 > 150 μg m^-3). On average, the anomalously high V850 is the main cause of severe haze, while in 2012 winter, RH1000 favorable for secondary aerosols' formation is the largest contributor to haze.

Variations of Haze Pollution in China Modulated by Thermal Forcing of the Western Pacific Warm Pool

In addition to the impact of pollutant emissions, haze pollution is connected with meteorology and climate change. Based on the interannual change analyses of meteorological and environmental observation data from 1981 to 2010, we studied the relationship between the winter haze frequency in central-eastern China (CEC) and the interannual variations of sea surface temperature (SST) over Western Pacific Warm Pool (WPWP) and its underlying mechanism to explore the thermal effect of WPWP on haze pollution variation in China. The results show a significant positive correlation coefficient reaching up to 0.61 between the interannual variations of SST in WPWP and haze pollution frequency in the CEC region over 1981–2010, reflecting the WPWP’s thermal forcing exerting an important impact on haze variation in China. The anomalies of thermal forcing of WPWP could induce to the changes of East Asian winter monsoonal winds and the vertical thermal structures in the troposphere over the CEC region. In the winter with anomalously warm SST over the WPWP, the near-surface winds were declined, and vertical thermal structure in the lower troposphere tended to be stable over the CEC-region, which could be conducive to air pollutant accumulation leading to the more frequent haze occurrences especially the heavy haze regions of Yangtze River Delta (YRD) and Pearl River Delta (PRD); In the winter with the anomalously cold WPWP, it is only the reverse of warm WPWP with the stronger East Asian winter monsoonal winds and the unstable thermal structure in the lower troposphere, which could attribute to the less frequent haze pollution over the CEC region. Our study revealed that the thermal forcing of the WPWP could have a modulation on air environment change in China.

Numerical simulations of the effects of regional topography on haze pollution in Beijing

In addition to weather conditions and pollutant emissions, the degree to which topography influences the occurrence and development of haze pollution in downtown Beijing and the mechanisms that may be involved remain open questions. A series of atmospheric chemistry simulations are executed by using the online-coupled Weather Research and Forecasting with Chemistry (WRF-Chem) model for November-December 2015 with different hypothetical topographic height scenarios. The simulation results show that topography exerts an important influence on haze pollution in downtown Beijing, particularly the typical development of haze pollution. A possible mechanism that underlies the response of haze pollution to topography is that the mountains that surround Beijing tend to produce anomalous southerly winds, high relative humidity, low boundary layer heights, and sinking motion over most of Beijing. These conditions favor the formation and development of haze pollution in downtown Beijing. Furthermore, the reduction percentage in PM_2.5 concentrations due to reduced terrain height in the southerly wind (S) mode is almost three times larger than that in the northerly wind (N) mode. In the context of the regional topography, the simple S and N modes represent useful indicators for haze prediction in Beijing to some extent, especially over medium to long time scales.

The impacts of regional transport and meteorological factors on aerosol optical depth over Beijing, 1980-2014

Understanding the role of different sources that contribute to the aerosol extinction coefficient is an important aspect toward analyzing climate change and regional air quality. In Beijing specifically, the region has suffered severe air quality deterioration over the past three decades, but the magnitude of extraneous contributions to aerosol variation has remained uncertain. Therefore, we estimated trends of contributions to aerosol optical depth (AOD) for Beijing from 1980 to 2014 and built a seasonal regression model to decouple the extraneous contribution from the total emitted using ground-based aerosol and meteorological measurements, extended to the emissions of man-made and natural contribution. The variation of AOD over Beijing was significantly affected by the anthropogenic aerosol emissions, which experienced slight augmentation by 15.3% from 1980 to 2000, rapid inflation by 36.9% from 2000 to 2006, and a gradual decrease by 10.0% from 2006 to 2014. The extraneous contribution from wind and its associated languishing patterns explain the historical increase of regional AOD, which experienced about a 10% enhancement over the three stages. Other meteorological contributions show no significant trends over 35 years, except for the temperature inversion, which despite the weakened hygroscopic growth after 2006, still experiences a significant enhancement.

Recent intensification of winter haze in China linked to foreign emissions and meteorology

Wintertime aerosol pollution in the North China Plain has increased over the past several decades as anthropogenic emissions in China have increased, and has dramatically escalated since the beginning of the 21^st century, but the causes and their quantitative attributions remain unclear. Here we use an aerosol source tagging capability implemented in a global aerosol-climate model to assess long-term trends of PM_2.5 (particulate matter less than 2.5 μm in diameter) in the North China Plain. Our analysis suggests that the impact of China’s increasing domestic emissions on PM_2.5 concentrations over the last two decades of 20^th century was partially offset (13%) by decreasing foreign emission over this period. As foreign emissions stabilized after 2000, their counteracting effect almost disappeared, uncovering the impact of China’s increasing domestic emissions that had been partially offset in previous years by reductions in foreign emissions. A slowdown in the impact from foreign emission reductions together with weakening winds explain 25% of the increased PM_2.5 trend over 2000–2014 as compared to 1980–2000. Further reductions in foreign emissions are not expected to relieve China’s pollution in the future. Reducing local emissions is the most certain way to improve future air quality in the North China Plain.

Aerosol and boundary-layer interactions and impact on air quality

Air quality is concerned with pollutants in both the gas phase and solid or liquid phases. The latter are referred to as aerosols, which are multifaceted agents affecting air quality, weather and climate through many mechanisms. Unlike gas pollutants, aerosols interact strongly with meteorological variables with the strongest interactions taking place in the planetary boundary layer (PBL). The PBL hosting the bulk of aerosols in the lower atmosphere is affected by aerosol radiative effects. Both aerosol scattering and absorption reduce the amount of solar radiation reaching the ground and thus reduce the sensible heat fluxes that drive the diurnal evolution of the PBL. Moreover, aerosols can increase atmospheric stability by inducing a temperature inversion as a result of both scattering and absorption of solar radiation, which suppresses dispersion of pollutants and leads to further increases in aerosol concentration in the lower PBL. Such positive feedback is especially strong during severe pollution events. Knowledge of the PBL is thus crucial for understanding the interactions between air pollution and meteorology. A key question is how the diurnal evolution of the PBL interacts with aerosols, especially in vertical directions, and affects air quality. We review the major advances in aerosol measurements, PBL processes and their interactions with each other through complex feedback mechanisms, and highlight the priorities for future studies.

Humidity plays an important role in the PM₂.₅ pollution in Beijing

Heavily-polluted PM₂.₅ (fine particulate matter) episodes frequently impacting Beijing, especially during winter, have become a substantial concern. We found that during winter, the daily variation of PM2.5 in Beijing tracked the pattern of relative humidity (RH). With the increase of PM₂.₅ (or RH), water-soluble components (especially inorganic ions) became more abundant, and the water-soluble organic carbon to organic carbon ratios increased. The nitrate to sulfate ratios also exhibited dependence on RH, and were higher than those measured about a decade ago, consistent with the increasing trend of nitrogen oxides emissions. Surprisingly, the ratios of water-insoluble organic carbon to elemental carbon showed significant increase at high RH levels, presumably indicating the formation of secondary organic aerosol that is not soluble in water. In addition, humid winters were occasionally identified during 1996-2013 which are expected to be favorable for the formation of air pollution episodes with high PM₂.₅ concentrations.