WRF-CMAQ Model Research Articles

Exploring Characteristics and Causes of Summer Ozone Pollution Based on Process Analysis in Wuhai

In recent years, summer O3 pollution has become more severe in Wuhai, where the terrain is complex and industrial parks are densely distributed. However, the characteristics and formation mechanisms of this pollution have not yet been investigated and remain unclear. Analyzing the variation and formation mechanisms of O3 is crucial to the prevention and control of air pollution in this region. By analyzing characteristics and using a WRF-CMAQ model to simulate three O3 pollution periods in Wuhai from June to August 2018, this study explored the causes of O3 pollution based on in-depth process analysis, and the effects of regional transportation and local photochemical reaction on O3 were also discussed. The diurnal variation of ozone exhibited a single-peak distribution, and near-surface O3 was positively correlated with short-wave radiation and temperature, and negatively correlated with relative humidity. The areas of Shizuishan in Ningxia and the Ulanbuhe desert exhibited high O3 values during the day, while the three industrial parks in Wuhai exhibited low values during both the day and night. Process analysis showed that transportation, chemical processes, and their relative magnitudes had a significant impact on O3. Local photochemical reactions and transport during the pollution period in June and July led to an obvious increase in O3, while the impact of chemical processes was about twice as large as that of transport. The increase of O3 in August was mainly caused by transport. Further decomposition of the transportation effect showed that transportation in the south and northwest directions had a remarkable effects on the increase of O3. Together with the emission of O3 precursors, the main sources of transportation were the Yinchuan, Shizuishan, and Bayannaoer regions. Therefore, Wuhai and neighboring cities should strengthen regional joint prevention and control by jointly formulating and implementing control measures for air pollution to reduce the impact of regional transmission on O3.

Computer Simulations of Air Quality and Bio-Climatic Indices for the City of Sofia

Air pollution is responsible for many adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the presented work is to study the behavior of two bio-climatic indices and statistical characteristics of the air quality index for Sofia city—the capital of Bulgaria for the period 2008–2014. The study is based on the WRF-CMAQ model system simulations with a spatial resolution of 1 km. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indices, respectively, for hot and cold weather. It was found that the recurrence of both the heat and cold index categories and of the air quality categories have heterogeneous space distribution and well manifested diurnal and seasonal variability. For all of the situations, only O3 and PM10 are the dominant pollutants—these which determine the AQI category. It was found that AQI1, AQI2, and AQI3, which fall in the “Low” band, have the highest recurrence during the different seasons, up to more than 70% in some places and situations. The recurrence of AQI10 (very high) is rather small—no more than 5% and concentrated in small areas, mostly in the city center. The Heat index of category “Danger” never appears, and the Heat index of category “Extreme caution” appears only in the spring and summer with the highest recurrence of less than 5% in the city center. For the Wind-chill index category, “Very High Risk” never appears, and the category “High Risk” appears with a frequency of about 1–2%. The above leads to the conclusion that both from a point of view of bioclimatic and air quality indices, the human health risks in the city of Sofia are not as high.

GPS-ZTD data assimilation and its impact on wintertime haze prediction over North China Plain using WRF 3DVAR and CMAQ modeling system.

Severe haze frequently hits the North China Plain (NCP), especially in winter during recent years. Meteorological factors affect aerosol formation and its optical properties, and accurate meteorological fields are imperative for accurate aerosol simulations. The impacts of Global Positioning System Zenith Total Delay (GPS-ZTD) data assimilation on meteorology and aerosol simulations were evaluated in this study using the WRF-CMAQ (the Weather Research and Forecasting model and Community Multiscale Air Quality) modelling system over the NCP during 01-31 December 2019. After bias correction, GSP-ZTD data were assimilated into the WRF model using the 3DVAR technique. Two sensitivity tests (CTR and ZTD) were conducted. The WRF model had generally acceptable performance for surface and upper air meteorological variables, PM2.5 and visibility. From the aspect of BIAS, STDE, RMSE, and R, the assimilation of ZTD data improved the underestimation of ground relative humidity (RH). The improvement was more pronounced in the first 18 forecast hours. The mean RH BIAS decreased by 8%. Surface pressure was also improved in ZTD. The influence of ZTD data assimilation on ground temperature and wind tended to be neutral. The BIAS of ZTD decreased by 3% after data assimilation while STED or RMSE increased slightly. After ZTD data assimilation, the PM2.5 underestimation decreased by 3.4% over NCP. And station mean BIAS or RMSE of PM2.5 decreased at more than 70% stations. After ZTD data assimilation, the visibility overestimation was reduced by 2.5%. And more than 81% stations over had lower visibility BIAS or RMSE. Station mean PM2.5 mass concentration increased by 1.5% in ZTD. The primary aerosol species increased by approximately 1%, and most secondary aerosol species increased by greater than 2% affected by both aerosol physical and chemical process. Although the improvement of PM2.5 seems marginal from the perspective of regional or temporal average, the contribution of ZTD data assimilation on specific pollution episodes at specific stations can be great. The improvement of PM2.5 troughs was in the range of 1-5 μg/m3, while the overestimation of PM2.5 peaks was reduced by few up to dozens μg/m3. This will contribute to the extreme value prediction during pollution episode.

Impacts of Meteorology and Emission Variations on PM2.5 Concentration Throughout the Country During the 2020 Epidemic Period

This study analyzed the impacts of meteorological conditions and changes in air pollutant emissions on PM2.5 across the country during the first quarter of 2020 based on the WRF-CMAQ model. Results showed that the variations in meteorological conditions led to a national PM2.5 concentration decreased of 1.7% from 2020-01 to 2020-03, whereas it increased by 1.6% in January and decreased by 1.3% and 7.9% in February and March, respectively. The reduction of pollutants emissions led to a decrease of 14.1% in national PM2.5 concentration during the first quarter of 2020 and a decrease of 4.0%, 25.7%, and 15.0% in January, February, and March, respectively. Compared to the same period last year, the PM2.5 concentration measured in Wuhan City decreased more than in the entire country. This was caused by improved meteorological conditions and a higher reduction of pollutant emissions in Wuhan City. PM2.5 in Beijing increased annually before the epidemic outbreak and during the strict control period, mainly due to unfavorable meteorological conditions. However, the decrease in PM2.5 in Beijing compared to March 2019 was closely related to the substantial reduction of emissions. The measured PM2.5 in the "2+26" cities, the Fenwei Plain and the Yangtze River Delta (YRD) decreased during the first quarter of 2020, with the largest drop occurring in the Yangtze River Delta due to higher YRD emissions reductions. The meteorological conditions of "2+26" cities and Fenwei Plain were unfavorable before the epidemic outbreak and greatly improved during the strict control period, whereas the Yangtze River Delta had the most favorable meteorological conditions in March. The decrease in PM2.5 concentration caused by the reduction of pollutant emissions in the three key areas was highest during the strict control period.

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Applying Photochemical Indicators to Analyze Ozone Sensitivity in Handan

Ozone pollution in Handan has become severe in recent years and in the summer of 2018, the average maximum daily 8-hour average ozone concentration in Handan was 175 μg·m-3 with a maximum of 257 μg·m-3. Ozone concentrations exceeded the National Air Quality Grade Ⅱ Standard in 59% of cases. In this study, the H2O2/HNO3 indicator was applied to analyze summertime ozone sensitivity in Handan using the WRF-CMAQ modeling system. The results showed that H2O2/HNO3 was more appropriate than other ozone indicators, both theoretically and based on simulation outputs. The good simulation effect of CMAQ on H2O2 and HNO3 was attributed to fine emission inventory and grid resolution. The H2O2/HNO3 simulation results showed that the relative importance of a VOCs-limited regime decreased month by month; a VOCs-NOx-mixed-limited regime was dominant in June; and a NOx-limited regime was more dominant in July and August than in June. The remarkable spatial difference in VOCs and NOx emission ratios among the counties of Handan led to differences in ozone sensitivity. The VOCs-limited regime was concentrated in counties where VOCs/NOx emission ratios were lower than 1.7. Southern counties had a NOx-limited regime, where VOCs/NOx emission ratios were higher than 6.9. Counties with VOCs/NOx emission ratios varying from 1.7 to 6.9 were more susceptible to both VOCs and NOx. According to these results, the transition range of HCHO/NO2, O3/HNO3, and O3/NOx ratios were adjusted to 0.35-0.6, 20-35, and 10-25 respectively. Adjusting the transition range of H2O2/(O3+NO2) was not effective, indicating that this indicator may not be applicable to Handan.

Time-Determination and Contribution Analysis of Transport, Retention, and Offshore Backflow to Long-Term Sand-Dust Coupling

Continuous on-line observation of particulate matter and PM2.5 chemical composition was conducted from October 15th to November 7th 2019 in East China. During the observation period, a wide range of dust-related processes took place. According to supplementary urban air quality assessment affected by dust (hereafter referred to as supplementary provisions), the observations were divided into four stages including pre-dust event, dust Ⅰ, dust Ⅱ, and post-dust event. The dust Ⅰ stage represented the processes of transportation and retention, while the dust Ⅱ stage represented processes of backflow from the sea and scavenging. The start time of the studied dust event was October 29th 08:00-09:00 based on the supplementary provisions, dust tracers, and air quality models; however, disagreements existed between these data sources with respect to the finishing time. The supplementary provisions could not effectively distinguish backflow dust from sea, and results from different dust tracers were variable. The WRF-CMAQ model simulated dust variation trends well but overestimated short-term suspended dust and backflow dust. PM10, PM2.5, and trace element concentrations were much higher during dust events than during non-dust periods, with highest daily concentrations of (234.8±125.5), (76.8±22.5), and (17.54±10.5) μg·m-3, respectively, which occurred on October 29th. During the dust event, concentration of crustal elements were remarkably high in PM2.5. At the same time, secondary ions (SO42-, NO3-, and NH4+) contributed less to PM2.5 mass concentrations. Four major crustal elements (Al, Si, Ca, and Fe) accounted for 23.5% and 13.7% of the mass concentration of PM2.5 and secondary ions accounted for 24.3% and 41.9% during dust Ⅰ and dust Ⅱ stages, respectively. Based on PMF source apportionment, Ca abundance, PM2.5/PM10 in dust sources, and the reconstruction of crustal material, dust particulates accounted for 43.4%-50.0% of PM2.5 and backflow dust accounted for 19.2%-24.7% of PM2.5.

Measure-specific environmental benefits of air pollution control for coal-fired industrial boilers in China from 2015 to 2017.

From 2015 to 2017, China took strong air pollution control measures (APCMs) for coal-fired industrial boilers (CFIBs), including eliminating CFIBs, promoting clean fuels, and updating air pollution control devices (APCDs). Based on the industrial boiler's emission inventory of air pollutants, measure-specific emission reductions from 2015 to 2017 was estimated in this study. Besides, the measure-specific environmental benefits of unit emission reduction on concentration and deposition flux were systematically evaluated by WRF-CMAQ model. The total emission reductions for CFIBs of PM10, PM2.5, SO2, NOx, Hg, As, Cd, Cr and Pb from 2015 to 2017 were 1.2Tg, 0.53Tg, 2.06Tg, 0.65Tg, 37.6 tons, 179.5 tons, 17.9 tons, 1029.3 tons and 676.0 tons, respectively. Based on meteorological fields in 2017, their corresponding national population-weighted mitigated concentration was 1.8μgm-3, 1.3μgm-3, 3.6μgm-3, 0.6μgm-3 (NO2), 0.076ngm-3, 0.37ngm-3, 0.04ngm-3, 1.83ngm-3 and 2.3ngm-3, respectively. Updating APCDs was identified as the major measure to reduce air pollutants (except NOx), accounting for more than 35% of emission reductions and mitigated concentration. Moreover, elimination was the major NOx reduction method, contributing to 55% of NOx emission reductions. The promoting of fuels, including replacement of CFIBs with gas-fired and biomass-fired industrial boilers, had higher environmental benefits for unit emission reductions. Furthermore, there were still more than 43,000 CFIBs with the capacity <10th-1, accounting for 14%, 21%, and 11% of total PM2.5, SO2, and NOX emissions for CFIBs in 2017; meanwhile, 20% and 59% of CFIBs did not install flue gas desulfurization and denitrification devices, respectively. Therefore, it is recommended to give priority to phase out CFIBs with capacity <10th-1 and APCDs updating for larger capacity CFIBs in the future.

A WRF-CMAQ modeling of atmospheric PAH cycling and health risks in the heavy petrochemical industrialized Lanzhou valley, Northwest China

Polycyclic aromatic hydrocarbons (PAHs) are omnipresent air pollutants with mutagenic and carcinogenic characteristics. Lanzhou city in Northwest China, where the first photochemical smog incident occurred in China, is located in an area characterized by mountain-valley topography. The city has been known as a heavy and petrochemical industry base and heavily contaminated by PAHs. There are large knowledge gaps in the understanding of atmospheric environmental fate of PAHs in Lanzhou city due to sparse observation data. We performed extensive numerical investigations of PAHs for August (summertime) and December (wintertime) of 2014 in Lanzhou city, using the Community Multiscale Air Quality (CMAQ) model, aiming to fill knowledge gaps in the spatial-temporal distribution and health consequences across the city. Strong seasonality in the atmospheric concentrations of PAHs was found, with high concentrations in winter and low concentrations in summer. The modeling results show high days in which daily air concentrations of BaP exceeding the level Ⅱ of Chinese National Standard (CNS) (2.5 ng/m3) in several August days in industrial suburb and urban area. In December, 77% and 80% of simulated BaP daily air concentrations were well above this national standard in the two areas. The modeled NAP and PHE in the atmosphere were predominantly in gas phase, whereas BaP was mainly in particulate phase. It was also found that the dry deposition dominated total PAHs deposition in Lanzhou. The incremental lifetime cancer risk (ILCR) ranged from 4.0 × 10−6 to 16.0 × 10−6, which were higher than the satisfactory risk level of 1.0 × 10−6, suggesting that local residents in Lanzhou city have a potential carcinogenic risk through exposure to ambient BaP. Especially, children had a higher exposure risk than adults. We suggest that the different actions in different regions of the city should be taken by the local government and those industries with high PAH emission, so as to reduce PAH contamination and risk.

Long-range transport of ozone across the eastern China seas: A case study in coastal cities in southeastern China

Tropospheric ozone (O3) can be transported influenced by large-scale circulation. In this study, an ozone pollution episode in 6 cities of southeastern coastal area of China (SCA) in autumn 2017 was investigated. Compared with the typical local ozone pollution, there was no significant diurnal variations in this pollution episode, the O3 concentrations maintained a stable level of about 47 ppb continuously. The WRF-CMAQ model as well as the coupled process analysis (PA) and source apportionment modules were used to simulate the formation and transport and quantify the contributions to O3. Besides, the HYSPLIT model was used to calculate the backward trajectories arriving in the cities. We find that this pollution was mainly caused by O3 transport from the eastern China seas (ECS). Under the movement of the Mongolian high-pressure, the O3 precursors emitted from Beijing-Tianjin-Hebei (BTH), Northeast China (NEC) and Japan-Korea (JK) were transported to ECS then generated O3 through photochemical reactions. Due to the weak nitrogen oxide titration and the extremely weak ozone deposition on the water surface, O3 concentrations maintained high during the movement of air masses over ECS and finally affected SCA after long-range transport. The contributions of horizontal advections were significant basically all the day with hourly contribution about 10 ppb hr−1 and extended from surface to 500 m above the ground level. JK contributed the most, with multi-days averaged contribution about 5 ppb and peak up to 30 ppb. The contributions of BTH and NEC were comparable, with average about 2 ppb and hourly peak of 19 and 10 ppb, respectively. For the first time, this study clearly shows that the O3 precursors emitted from northern China and Japan-Korea contribute to the O3 pollution in SCA under certain weather conditions, which will help to better understand and predict the O3 pollution in that area.

Comprehensive study of a long-lasting severe haze in Seoul megacity and its impacts on fine particulate matter and health

A long-lasting severe haze event was observed over the Seoul metropolitan region (SMR: Seoul, Incheon, and Gyeonggi-do), South Korea, in the winter of 2013 (January 12–16). We comprehensively investigated the atmospheric processes affecting particulate matter (PM) distributions during the haze event, as well as its impact on human health in the study area. These analyses were performed based on meteorological and PM observations and numerical modeling, which included the WRF-CMAQ modeling system and the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE). High PM10 concentrations during the haze event were mostly observed in the western and southern parts of the SMR. Significant differences (60–70 μg m−3) in the mean PM2.5 concentrations for haze and non-haze days were predicted mainly in the west-northwest areas of SMR. This might be primarily due to the pollutant transport (horizontal and vertical) from large emission sources (e.g., Chinese emissions) and, in part, their local accumulation (by local emissions) under high-pressure conditions and slow-moving air flows (i.e., blocking effect) around SMR. In addition, the enhanced PM2.5 concentrations in the study area during the haze event led to an increase in the number of premature deaths.

Air Quality and COVID-19 mortality in the Chicago area

Background:In the United States, deaths caused by COVID-19 have occurred disproportionately in racial and ethnic minority populations. As no medical cure or natural immunity exists, understanding the factors that place people at higher risk of dying of COVID-19 is crucial to reducing mortality. Prelminary ecological analyses suggest that poor air quality may increase the risk of COVID-19 mortality, but thus far, this association has not been evaluated in with fine-scale spatial exposure resolution in a homogenously urban area. We aimed to interrogate the relationship between air quality and COVID-19 mortality in residents of Cook County, an area with high levels of racial and ethnic residential seggregation.Methods: High-resolution estimates of three air pollutants were developed for Cook County, Illinois (the Chicagoland area): particulate matter smaller than 2.5 microns (PM2.5), ozone (O3), and nitrogen dioxide (NO2) utilizing a WRF-CMAQ model. The association of these air pollutants were associated with overall and race-specific COVID-19 death rates within each census tract controlling for tract-level confounders.Results: Race and ethnicity were highly correlated with the air pollutants (p&lt;0.00001). An increased risk of COVID-19 mortality was found in tracts with higher PM2.5 (RR=1.26; p=1.19·10-5) and NO2 (RR=1.04; p=1.13·10-2) when controlling for tract-level gender, age, and proxies for exposure to the virus (public transit use, population density, and occupants per residential room). This effect persisted when controlling for congregate living such as nursing homes and jails. This effect was attenuated when controlling for other tract-level measures of socioeconomic status, and such measures were often highly correlated with air pollution.Conclusions: This analysis supports the hypothesis that air pollution may be associated with COVID-19 mortality. While individual-level analyses are needed, these findings support mitigation strategies that may reduce death rates in vulnerable population such as filtration and pollutant regulations.

Evaluation of real-time PM2.5 forecasts with the WRF-CMAQ modeling system and weather-pattern-dependent bias-adjusted PM2.5 forecasts in Taiwan

A real-time air quality forecasting (AQF) system was developed in Taiwan using the Weather Research and Forecasting meteorological model and Community Multiscale Air Quality model framework. This study evaluated the performance of the one-year archived AQF PM2.5 forecasts (October 2018 to September 2019) and developed a bias-correction method to improve the accuracy of the PM2.5 forecasts.The bias-correction method incorporates a cluster-analysis-based synoptic weather pattern (WP) classification (one type of analog method). In principle, the historical model errors are categorized according to the synoptic WP and used to adjust the PM2.5 forecast. First, the synoptic WPs are determined using K-means cluster analysis (six WPs were identified). Second, the historical AQF PM2.5 bias at each surface station is estimated for each classified WP. Third, a linear-regression relationship between the AQF PM2.5 bias and PM2.5 forecasts for the six WPs is developed to postprocess the PM2.5 forecasts.The AQF PM2.5 bias is found to have a strong dependency on the synoptic WP. A performance assessment of the AQF PM2.5 forecasts reveals systematic PM2.5 underprediction, with the most pronounced underprediction occurring on days associated with weak synoptic weather conditions. Under these conditions, a severe PM2.5 event is likely to occur in Taiwan. The bias-correction method is able to reduce the PM2.5 forecast error and improve the root mean square error (RMSE) and mean bias (MB) calculations. The improvement is most significant on days associated with a weak synoptic WP and in regions where high PM2.5 concentrations are likely to occur. The method is shown to be effective at reducing the AQF PM2.5 bias.

Regional and Urban-Scale Environmental Influences of Oceanic DMS Emissions over Coastal China Seas.

Marine biogenic dimethyl sulfide (DMS) is an important natural source of sulfur in the atmosphere, which may play an important role in air quality. In this study, the WRF-CMAQ model is employed to assess the impact of DMS on the atmospheric environment at the regional scale of eastern coastal China and urban scale of Shanghai in 2017. A national scale database of DMS concentration in seawater is established based on the historical DMS measurements in the Yellow Sea, the Bohai Sea and the East China Sea in different seasons during 2009~2017. Results indicate that the sea-to-air emission flux of DMS varies greatly in different seasons, with the highest in summer, followed by spring and autumn, and the lowest in winter. The annual DMS emissions from the Yellow Sea, the Bohai Sea and the East China Sea are 0.008, 0.059, and 0.15 Tg S a−1, respectively. At the regional scale, DMS emissions increase atmospheric sulfur dioxide (SO2) and sulfate concentrations over the East China seas by a maximum of 8% in summer and a minimum of 2% in winter, respectively. At the urban scale, the addition of DMS emissions increase the SO2 and levels by 2% and 5%, respectively, and reduce ozone (O3) in the air of Shanghai by 1.5%~2.5%. DMS emissions increase fine-mode ammonium particle concentration distribution by 4% and 5%, and fine-mode nss- concentration distributions by 4% and 9% in the urban and marine air, respectively. Our results indicate that although anthropogenic sources are still the dominant contributor of atmospheric sulfur burden in China, biogenic DMS emissions source cannot be ignored.

Atmospheric outflow of anthropogenic iron and its deposition to China adjacent seas

Atmospheric deposition of iron (Fe) can increase marine primary productivity, consequently affect ocean biogeochemical cycles and climate change. In this study, we develop an adaptor to generate anthropogenic Fe emission inventories for China in 2012 and 2016 via anthropogenic PM2.5 emissions from Multi-resolution Emission Inventory for China (MEIC) using local source-specific mass fractions of Fe in PM2.5. Using the generated emission inventories, we simulated Fe concentrations as well as dry deposition fluxes to China marginal seas using a WRF-CMAQ model during four campaign periods. The simulated Fe concentrations are in good agreement with observations except for those in presence of severe dust-intrusion events (NMB −13% ~ −27%), indicating a reasonably good performance of the generated Fe emissions and leaving the large underestimation of Fe concentrations mainly due to nature dust emissions. Simulated Fe concentrations over China marginal seas are in the range of 62–6.5 × 102 ng m−3, providing 2.0–12.5 μg m−2 d−1 to the seas during the study periods. We also found that inputs of total Fe in PM2.5 to the seas in presence of dust-intrusion events are 3 and 13 times larger than those in presence of haze events or on less polluted days. Due to lower Fe solubility in nature mineral aerosols than in anthropogenic aerosols, dry deposition fluxes of bioavailable Fe on haze days almost double that in dust days. The total anthropogenic emissions of Fe over China in 2012 and 2016 are estimated as 5.5 × 102 Gg and 3.3 × 102 Gg, respectively. Iron and steel industry are the dominant sources of Fe, accounting for 59–63% of the total anthropogenic Fe emissions. Geotropically, stronger emissions per area were distributed in eastern China, e.g., 2.3 to 15.4 ng m−2 s−1 in eastern China versus <0.4 ng m−2 s−1 in western China.

The Effects of Different Planetary Boundary Layer Schemes on the Meteorological and Environmental Elements in winter stable weather of Shenyang

Two planetary boundary layer schemes (YUS and MYJ) in the WRF-CMAQ model, are selected for sensitivity simulation, and the simulation capabilities of different planetary boundary layer schemes to meteorological elements and PM2.5 concentration distribution are analyzed from December 17th to December 20th in 2016. The results show that using the YSU and MYJ schemes can well simulate the spatial distribution and diurnal variation characteristics of temperature, wind speed and PM2.5 concentration on the ground under the background of stable weather in winter. It is sensitive to temperature, wind speed and PM2.5 concentration on the ground using different planetary boundary layer parameterization schemes. The simulated wind speed is relatively large, and the maximum deviation can reach about 2m/s. The deviation of wind speed using the MYJ scheme is relatively small than YSU, which is closer to the real value. There has a lower PM2.5 concentration value using YSU than MYJ at night, however the daytime (mainly from 11:00 to 18: 00) YSU scheme is relatively higher than MYJ. The deviation of PM2.5 concentration on the ground using the MYJ scheme is relatively smaller than YSU, and the characteristics of daily variation is closer to the real situation. Overall, the MYJ scheme is better than YSU in air pollution simulation.

Simulating the effects of land urbanization on regional meteorology and air quality in Yangtze River Delta, China

Land urbanization caused by human activities is increasingly converting natural land surfaces to artificial ones and modifying land surface parameters. This can lead to changes in weather conditions and further effects on air pollutants. This study examines the influence of land urbanization on meteorology and air quality in the Yangtze River Delta (YRD) by simulating the impacts of land-use/land cover (LULC) changes on meteorology and air quality. Our results show that the temperature at 2m increases by 0.2–0.7 °C, and the planetary boundary layer height exhibits a maximum growth during the daytime of 116.74 m after updating LULC. The average reduction of 10-m wind speed is 0.29 m/s, and the maximum decrease is 0.52 m/s, which occurs in the daytime due to increased surface resistance. Furthermore, PM2.5, NO2, SO2, and ozone are sensitive to these meteorological changes in the WRF-CMAQ model. Additionally, land urbanization results in a decrease in the PM2.5 concentration in most urban areas for the same emission source. However, land urbanization aggravates photochemical smog pollution, which is dominated by O3. The findings of the study can be used as a reference for policymakers and urban planners to help implement effective air pollution prevention and control measures and ensure the rational use of land resources.

Port-Related Emissions, Environmental Impacts and Their Implication on Green Traffic Policy in Shanghai

The port of Shanghai, as the world’s largest container port, has been experiencing rapid development in recent years, with increasing cargo throughput capacity. The combustion of diesel fuels used by internal and external port-related container trucks and in-port machineries can release various pollutants, causing air pollution. The terminals are close to the residential area, and the emissions are concentrated, which is worth paying attention to. This study aims to synthetically assess the port-related emissions and their environmental impacts. We firstly constructed an emission inventory of air pollutants in the port of Shanghai and then used the WRF-CMAQ model to estimate the influence of port-related source emissions on air quality. The results show that the annual emissions of SO2, NOX, CO, VOCS, PM, PM10, PM2.5, CO2, BC and OC caused by cargo-handling equipment were 21.88 t, 1811.22 t, 1741.72 t, 222.76 t, 61.52 t, 61.42 t, 58.41 t, 141,805.40 t, 26.80 t and 10.07 t in 2015. The emissions of NOX, CO, VOCS, PM10 and PM2.5 caused by external port-related container trucks were 18,002.92 t, 5308.0 t, 1134.57 t, 711.12 t and 640.58 t. The exhaust of external port-related container trucks was much larger than that of cargo-handling equipment, so the impact on air quality was also higher than that of the machinery. The peak annual average concentrations of PM2.5 and NOX contributed by the port-related sources were 1.75 μg/m3 and 49.21 μg/m3, respectively, which accounted for 3.08% and 36.7%, respectively, of the simulated ambient concentrations by all the anthropogenic emissions in Shanghai. Our results imply that the emission control policy to reduce the combined port-related emissions, especially for the cargo-delivery transportation phase from port to city, is key for large coastal port cities such as Shanghai.

Biomass burning sources and their contributions to PM10 concentrations over countries in mainland Southeast Asia during a smog episode

Abstract Severe particulate matter problems are known to occur frequently in mainland Southeast Asia (MSEA) during times of intensified biomass burning (BB). Therefore, the objectives of this study are to investigate BB characteristics and their impacts on PM10 concentrations in MSEA during a smog episode that took place in March 2012. According to the analysis of our study, PM10 was emitted from BB and accounted for 72% of all sources. Using the WRF-CMAQ modeling system, the current study showed that severe PM10 levels in MSEA exceeded the World Health Organization (WHO) ambient air quality standard (AAQS) recommended safe level of air quality by 51%. Subsequently, based on aggregated monthly data, the area average PM10 concentration was found to be 80 μg/m3 over MSEA. In addition, the model showed that the major source of particulate matter was from BB and contributed to 49% of ambient PM10 concentrations in MSEA while it specifically contributed 73%, 69%, 59%, 45%, 33%, and 31% in Laos, Myanmar, Cambodia, Thailand, China, and Vietnam, respectively. Based on a sensitivity analysis, we found that every 1 Tg of PM10 increased in MSEA would result in a 27.8 μg/m3 increase in PM10 concentrations in MSEA. However, these research findings tend to vary from one country to another, where for every 1 Tg of PM10 increased, it would result in a 60.6, 50.8, 17.6, 14.1, 13.0, and 9.9 μg/m3 increase in PM10 concentrations in Laos, Myanmar, Thailand, China, Cambodia, and Vietnam, respectively. These findings assume great significance those who wish to establish PM10 control strategies at both regional and national levels, given that BB needs to be recognized as the primary genesis of PM10 problems.

Estimation of biogenic VOC emissions and their corresponding impact on ozone and secondary organic aerosol formation in China

Abstract Biogenic volatile organic compounds (BVOC) play an important role in global environmental chemistry and climate. In the present work, biogenic emissions from China in 2017 were estimated based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN). The effects of BVOC emissions on ozone and secondary organic aerosol (SOA) formation were investigated using the WRF-CMAQ modeling system. Three parallel scenarios were developed to assess the impact of BVOC emissions on China's ozone and SOA formation in July 2017. Biogenic emissions were estimated at 23.54 Tg/yr, with a peak in the summer and decreasing from southern to northern China. The high BVOC emissions across eastern and southwestern China increased the surface ozone levels, particularly in the BTH (Beijing-Tianjin-Hebei), SCB (Sichuan Basin), YRD (Yangtze River Delta) and central PRD (Pearl River Delta) regions, with increases of up to 47 μg m−3 due to the sensitivity of VOC-limited urban areas. In summer, most SOA concentrations formed over China are from biogenic sources (national average of 70%). And SOA concentrations in YRD and SCB regions are generally higher than other regions. Excluding anthropogenic emissions while keeping biogenic emissions unchanged results that SOA concentrations reduce by 60% over China, which indicates that anthropogenic emissions can interact with biogenic emissions then facilitate biogenic SOA formation. It is suggested that controlling anthropogenic emissions would result in reduction of both anthropogenic and biogenic SOA.