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In 2021, the World Health Organization (WHO) ranked Nigeria among the most polluted nations in the world, an indication of a deteriorating air quality, especially in the major urban areas of the country, which might pose adverse human health impacts. In this study, the Integrated Source Apportionment Method (ISAM) tool in the Community Multiscale Air Quality (CMAQ) model (CMAQ-ISAM) was employed to quantify the contributions of eight emissions sectors to fine particulate matter (PM2.5) and its major components in Lagos during a prolonged severe atmospheric pollution episode (APE) in January 2021. The influence of meteorological conditions on the formation and dispersion of PM2.5 during the APE was also elucidated. Spatially, elevated PM2.5 concentrations were found in the northwestern region of Lagos, an urban area with larger anthropogenic emissions. Residential and industry were the two major sources of PM2.5. Residential contributed the most to total PM2.5 (~40 μg/m3), followed by industry (~20 μg/m3). High concentrations of secondary inorganic aerosols (SIA) at the northwest and upper northern areas of Lagos were majorly attributed to residential and industry sectors. In addition, sulfate accounted for the largest fraction of PM2.5, with residential, industry, and energy being its major sources. Residential, industry, and on-road sectors dominated the contributions to nitrate, while residential and industry were the major contributors to ammonium. Furthermore, the elevated PM2.5 concentrations during the APE were greatly enhanced by unfavorable meteorological conditions. This study provides insights for designing effective emissions control strategies to mitigate future severe PM2.5 pollution episode in Lagos.

Ozone (O3) has become a significant air pollutant in China in recent years. O3 abatement is challenging due to the nonlinear response of O3 to precursors nitrogen oxides (NOx) and volatile organic compounds (VOCs). Photochemical indicators are widely used to estimate the O3–NOx–VOC sensitivity, and this has important policy implications. However, the effectiveness of the indicators has seldom been evaluated. This study examined the applications of four indicators that include the ratio of the production rates of H2O2 and HNO3 (PH2O2/PHNO3), HCHO/NO2, HCHO/NOy, and reactive nitrogen (NOy) in the Yangtze River Delta (YRD) with localized thresholds. The overall accuracy was high (>92 %) for all indicators and not significantly reduced with different simulation periods or in different locations of the region. By comparing with the O3 isopleths, it was found that HCHO/NO2 and HCHO/NOy showed the most consistency, whereas PH2O2/PHNO3 (NOy) tended to underestimate (overestimate) the positive response of O3 to NOx. Additionally, PH2O2/PHNO3 was less likely to attribute the O3 formation to mixed sensitivity than the other indicators, and this demonstrated a preference for a single-pollutant control strategy. This study also revealed that the details in the methodology used to derive the threshold values impacted the results, and this may produce uncertainties in the application of photochemical indicators.

Surface ozone (O

Ozone (O3) has become a significant air pollutant in China in recent years. O3 abatement is challenging due to the nonlinear response of O3 to precursors nitrogen oxides (NOx) and volatile organic compounds (VOCs). Photochemical indicators are widely used to estimate the O3-NOx-VOC sensitivity, and this has important policy implications. However, the effectiveness of the indicators has seldom been evaluated. This study examines the applications of four indicators that include the ratio of the production rates of H2O2 and HNO3 (PH2O2 / PHNO3), HCHO / NO2, HCHO / NOy, and reactive nitrogen (NOy) in the Yangtze River Delta (YRD) with localized thresholds. The overall accuracy was high (> 92 %) for all indicators and not significantly reduced with different simulation periods or in different locations of the region. By comparing with the O3 isopleths, it was found that HCHO/NO2 and HCHO / NOy showed the most consistency, whereas PH2O2 / PHNO3 (NOy) tended to underestimate (overestimate) the positive response of O3 to NOx. Additionally, PH2O2 / PHNO3 was less likely to attribute the O3 formation to mixed sensitivity than the other indicators, and this demonstrated a preference for a single-pollutant control strategy. This study also revealed that the details in the methodology used to derive the threshold values impacted the results, and this may produce uncertainties in the application of photochemical indicators.

During the COVID-19 lockdown period (from January 23 to February 29, 2020), ambient PM2.5 concentrations in the Yangtze River Delta (YRD) region were observed to be much lower, while the maximum daily 8 h average (MDA8) O3 concentrations became much higher compared to those before the lockdown (from January 1 to 22, 2020). Here, we show that emission reduction is the major driving force for the PM2.5 change, contributing to a PM2.5 decrease by 37% to 55% in the four YRD major cities (i.e., Shanghai, Hangzhou, Nanjing, and Hefei), but the MDA8 O3 increase is driven by both emission reduction (29%–52%) and variation in meteorological conditions (17%– 49%). Among all pollutants, reduction in emissions mainly of primary PM contributes to a PM2.5 decrease by 28% to 46%, and NOx emission reduction contributes 7% to 10%. Although NOx emission reduction dominates the MDA8 O3 increase (38%–59%), volatile organic compounds (VOCs) emission reduction lead to a 5% to 9% MDA8 O3 decrease. Increased O3 promotes secondary aerosol formation and partially offsets the decrease of PM2.5 caused by the primary PM emission reductions. The results demonstrate that more coordinated air pollution control strategies are needed in YRD.

We investigated the spatial distribution and trend of double high pollution (DHP), in which the daily average concentration of fine particulate matter (PM2.5) was above 75 μg/m3 and the daily maximum 8-hour average ozone (MDA8 O3) concentration was above 160 μg/m3, in the Yangtze River Delta (YRD) region during 2015-2019, along with the meteorological and chemical characteristics during DHP and differences compared to high O3 pollution (HOP) and high PM2.5 pollution (HPP). In the YRD, Shanghai had the highest frequency of DHP at 7.6%, while Anhui had the least (2.1%). DHP mostly occurred in the northwest and along the Yangtze River in the east of the YRD, especially in spring (April) and autumn (October). MDA8 O3 level was relatively higher during DHP than HOP, while PM2.5 level was relatively higher during HPP than DHP. In 2015-2019, the total number of DHP events decreased in the YRD, but the changes in PM2.5 and O3 concentrations showed great spatial variations. DHP was often associated with a weak pressure field, under meteorological conditions with east winds, temperatures of 18.7-26.1 °C, relative humidity of 65.7-77.1%, sea level pressure of 1008.2-1019 hPa, wind speed of 1.4-2.4 m/s, and visibility of 3.1-7.5 km. Water-soluble ions (NO3-, NH4+, and SO42-) were the dominant components of PM2.5 during DHP at Nanjing and Changzhou City in 2019. Although the fraction of those ions during DHP and HPP were similar, the secondary conversion of NO2 and SO2 was stronger in HPP. The concentrations of those ions were lowest in HOP, with a higher fraction of sulfate than the other two types of pollution. The conversion of SO2 to sulfate was easier to occur than that of NO2 to nitrate under all the polluted conditions in the two cities.

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM

The Yangtze River Delta (YRD) urban agglomeration is one of the most developed regions in China. During recent decades, this region has experienced severe regional haze and photochemical smog pollution problems. In this study, we used a source-oriented chemical transport model to quantitatively estimate the effects of inter-city transport on fine particulate matter (PM

Lockdown measures to curtail the COVID-19 pandemic in China halted most non-essential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. Employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM

Although the air quality in China has been improved by collaborative efforts dedicating to mitigate the haze pollution, PM2.5 concentrations still remain high levels and the issue of increasing O3 concentration has attracted more attention of the public. The YRD region has been suffering from both the PM2.5 and O3 pollution problems. To investigate the formation mechanisms and sources of PM2.5 and O3 in this region, a comprehensive EXPLORE-YRD campaign (EXPeriment on the eLucidation of theatmospheric Oxidation capacity and aerosol foRmation, and their Effects inYangtze River Delta) was carried out in May - June 2018. In this study, we investigate the contributions of different source categories to PM2.5 and O3. A source-oriented 3-D air quality model (CMAQ) was applied to analyze contributions of different emission sources to PM2.5 and O3 in the YRD region. Emissions were divided into eight source categories: industry, power, transportation, residential, agriculture, biogenic, wildfire, and other countries. Contribution from individual source category was quantified. The importance of anthropogenic and natural sources to PM2.5 and O3 was discussed.

A regional ozone (O3) pollution event occurred in the Yangtze River Delta region during August 17–23, 2020 (except on August 21). This study aims to understand the causes of O3 pollution during the event using an emission-based model (i.e., the Community Multiscale Air Quality (CMAQ) model) and an observation-based model (OBM). The OBM was used to investigate O3 sensitivity to its precursors during the O3 pollution, concluding that O3 formation was limited by volatile organic compounds (VOCs) on August 19, but was co-limited by VOCs and nitrogen oxides (NOx) on other polluted days. Aromatics and alkenes were the two main VOC groups contributing to the O3 formation, with trans-2-butene and m/p-xylene as the key species among the VOCs measured at the Nanjing urban site. The source apportionment results estimated using the source-oriented CMAQ model suggest that the transportation and industry sources dominated the non-background O3 production in Nanjing, which were responsible for 52% and 24.7%, respectively. The O3 concentration attributed to NOx (~70%) was significantly higher than that attributed to VOCs (approximately 30%). The process analysis revealed that vertical mixing increased the O3 concentrations in the early morning, and photochemical reactions promoted O3 formation and accumulation during the daytime within the planetary boundary layer. At night, outflow from horizontal transport and nocturnal chemistry jointly resulted the O3 depletion. The contributions of inter-city transport during the O3 pollution period in Nanjing were also estimated. The predicted O3 concentration was largely recorded from long-distance regions, reaching 46%, followed by local sources (38%) and surrounding cities (16%). The results indicate that both NOx and VOCs contributed significantly to O3 pollution during this event, and the emissions controls of NOx and the key VOC species of aromatics and alkenes from a cooperative regional perspective should be considered to mitigate O3 pollution.

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM2.5) and ozone (O3) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM2.5 and O3 in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM2.5 and O3 using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM2.5-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142-159) to 308 (CI95: 213-241) thousands from 2014 to 2018 by using different concentration data, while O3-related premature mortality increases by 67 (CI95: 26-104) to 103 (CI95: 40-163) thousands. The estimated mean changes are up to 40% different for the PM2.5-related mortality, and up to 30% for the O3-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 103 people/km2, mostly located in Central China, for both PM2.5 and O3. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.

Lockdown measures to curtail the COVID-19 pandemic in China halted most non-essential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. Employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM2.5 concentrations change in this region. The model using the scenario (C3) with greater traffic reductions performed better compared to the observed PM2.5. Compared with the no reductions base-case (scenario C1), PM2.5 reductions with scenario C3 were 2.70, 2.53, 2.90, 2.98, 3.30, 2.81, 2.82, 2.98, 2.68, and 2.83 μg/m3 in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai, respectively. During high-pollution days in scenario C3, the percentage reductions in PM2.5 concentrations in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai were 3.76, 3.54, 3.28, 3.22, 3.57, 3.56, 3.47, 6.10, 3.61, and 3.67%, respectively. However, significant increases caused by unfavorable meteorological conditions counteracted the emissions reduction effects resulting in high air pollution in BTH region during the lockdown period. This study shows that effective air pollution control strategies incorporating these results are urgently required in BTH to avoid severe pollution.

The Yangtze River Delta (YRD) urban agglomeration is one of the most developed regions in China. During recent decades, this region has experienced severe regional haze and photochemical smog pollution problems. In this study, we used a source-oriented chemical transport model to quantitatively estimate the effects of inter-city transport on fine particulate matter (PM2.5) and ozone (O3) among the 41 cities in the YRD urban agglomeration during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (May 17 to June 17, 2018). The results show that inter-city transport is very significant in the YRD region. On average, the emissions from the local city, the other YRD cities, and the regions outside of the YRD contribute 25.3%, 49.9%, and 24.8% to the PM2.5, respectively, and they contribute 33.7%, 46.8%, and 19.5% of the non-background O3, respectively. On PM2.5 or O3 pollution days, the transport contribution from the non-local YRD cities becomes much more important, while the local emissions and the transport from non-YRD emissions become less important. The results also suggest that the cities within a distance of 184 km and 94 km contribute 60% of the PM2.5 and O3, respectively. Therefore, we recommend that regional cooperative control programs in the YRD consider emission controls over cities within these ranges. The range for primary PM2.5 (92 km) is very different from that for secondary PM2.5 (515 km). Cooperative emission controls of SO2 and NOx on a much larger regional scale are required to reduce the secondary PM2.5 in the YRD.

The EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta (EXPLORE-YRD) campaign was carried out between May and June 2018 at a regional site in Taizhou, China. The EXPLORE-YRD campaign helped construct a detailed air quality model to understand the formation of O3 and PM2.5 further, identify the key sources of elevated air pollution events, and design efficient emission control strategies to reduce O3 and PM2.5 pollution in YRD. In this study, we predicted the air quality during the EXPLORE-YRD campaign using the Weather Research and Forecasting/Community Multiscale Air Quality modelling system (WRF/CMAQ) and evaluated model performance on O3 and PM2.5 concentrations and compositions. Air quality was predicted using two sets of reanalysis data—NCEP Final (FNL) Operational Global Analysis and ECMWF Reanalysis v5.0 (ERA5)—and three horizontal resolutions of 36, 12, and 4 km. The results showed that PM2.5 concentration was generally under-predicted using both the FNL and ERA5 data. ERA5 yielded slightly higher PM2.5 predictions during the EXPLORE-YRD campaign. Both reanalysis data sets under-predicted the high PM2.5 pollution processes on 29–30 May 2018, indicating that reanalysis data is not essential for under-predicting extreme PM2.5 pollution processes. The performance of O3 was similar in both the reanalysis data sets, because O3 is mostly sensitive to temperature predictions and FNL and ERA5 yielded similar temperature results. Although the average performance of PM2.5 and O3 predictions yielded by FNL and ERA5 was similar, large differences were observed in certain locations on specific days (e.g. in Hangzhou between 29 May and June 6, 2018 and in Hefei on 1–3 June 2018). Therefore, the choice of reanalysis data could be an important factor affecting the predictions of PM2.5 and O3, depending on locations and episodes. Comparable results were obtained using predictions with different horizontal resolutions, indicating that grid resolution was not crucial for determining the model performance of both PM2.5 and O3 during the campaign.

A source-oriented Community Multiscale Air Quality model was used to quantify the contributions of different sources to ground-level fine particulate matter (PM2.5) and ozone (O3) over the Yangtze River Delta (YRD) region during the EXPLORE-YRD (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation, and their Effects in the Yangtze River Delta) campaign (17 May to June 17, 2018). O3 formation in most urban areas of YRD is attributed to volatile organic compounds (VOCs) (81.1%, 78.5%, 60.2%, and 55.1% in Shanghai, Nanjing, Hefei, and Hangzhou, respectively), but is affected more by nitrogen oxides (NOx) in suburban and rural areas. Industry and transportation are the two major sources of O3 and PM2.5. In addition to the two sources, NOx produced owing to power generation, and VOC emissions from biogenic sources are important source of O3. Industry contributes the most to the total mass of PM2.5 in the YRD during the study period (9–25 μg/m3), followed by transportation (2–7 μg/m3). Industry, residential emissions, and transportation are the major sources of primary organic carbon and elemental carbon, whereas industry, transportation, and power generation account for most of the sulphate (SO2− 4) and nitrate (NO− 3) in the YRD. Agriculture is the most dominant source of ammonium emissions (NH+ 4). In Shanghai, Nanjing, Hefei, and Taizhou, secondary organic aerosol (SOA) are mainly contributed by industrial emissions. However, in Hangzhou, biogenic emissions contribute more than 40% of SOA. During all types of pollution episodes, industry and transportation are generally the two greatest sources of O3 and PM2.5 in YRD. The contribution of industry is higher during high PM2.5 pollution episodes, whereas biogenic and open burning contributions are more important during high O3 episodes. Overall, anthropogenic sources dominate the formation of O3 and PM2.5 pollution in the YRD, whereas biogenic emissions contribute significantly to O3 attributable to VOC emissions (O3_VOCs) accounting for 9–20% in urban areas of the YRD.