scholarly journals Changes in China's anthropogenic emissions during the COVID-19 pandemic

2020 ◽  
Author(s):  
Bo Zheng ◽  
Qiang Zhang ◽  
Guannan Geng ◽  
Qinren Shi ◽  
Yu Lei ◽  
...  
Keyword(s):  
Air Quality ◽  
Mainland China ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Anthropogenic Emissions ◽  
Economic Activities ◽  
Time Data ◽  
Sharp Drop ◽  
Traffic Volumes ◽  
First Time

Abstract. The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. The short-term impacts of lockdowns on China's air quality have been measured and reported, however, the changes in anthropogenic emissions have not yet been assessed quantitatively, which hinders our understanding of the causes of the air quality changes during COVID-19. Here, for the first time, we report the anthropogenic air pollutant emissions from mainland China during the first eight months of 2020 by using a bottom-up approach based on the near real-time data. The COVID-19 lockdown was estimated to have reduced China's anthropogenic emissions substantially between January and March in 2020, with the largest reductions in February. Emissions of SO2, NOx, CO, NMVOCs, and primary PM2.5 were estimated to have decreased by 29 %, 31 %, 27 %, 26 %, and 21 %, respectively, in February 2020 compared to the same month in 2019. The reductions in anthropogenic emissions were dominated by the industry sector for SO2 and PM2.5 and were contributed approximately equally by the industry and transportation sectors for NOx, CO, and NMVOCs. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to the comparable levels of 2019 in August 2020. The provinces in China have presented nearly synchronous decline and rebound in anthropogenic emissions, while Hubei and the provinces surrounding Beijing recovered slower due to the extension of lockdown measures. The reduction ratios of anthropogenic emissions from 2019 to 2020 can be accessed from https://doi.org/10.6084/m9.figshare.c.5214920.v1 (Zheng et al., 2020) by species, month, sector, and province.

scholarly journals Comparison of emissions inventories of anthropogenic air pollutants and greenhouse gases in China

2017 ◽  
Vol 17 (10) ◽  
pp. 6393-6421 ◽  
Author(s):  
Eri Saikawa ◽  
Hankyul Kim ◽  
Min Zhong ◽  
Alexander Avramov ◽  
Yu Zhao ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Central China ◽  
Pollutant Emissions ◽  
Mitigation Measures ◽  
Economic Activities ◽  
Temporal And Spatial Distribution ◽  
Emissions Inventories

Abstract. Anthropogenic air pollutant emissions have been increasing rapidly in China, leading to worsening air quality. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates. Thus, assessing differences in these inventories is essential for the better understanding of air pollution over China. We compare five different emissions inventories estimating emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter of 10 µm or less (PM10) from China. The emissions inventories analyzed in this paper include the Regional Emission inventory in ASia v2.1 (REAS), the Multi-resolution Emission Inventory for China (MEIC), the Emission Database for Global Atmospheric Research v4.2 (EDGAR), the inventory by Yu Zhao (ZHAO), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008, during which Chinese economic activities more than doubled. In addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements exist among the five inventories at disaggregated levels. These disagreements lead to differences of 67 µg m−3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modeled regional concentrations in China. We also find that all the inventory emissions estimates create a volatile organic compound (VOC)-limited environment and MEIC emissions lead to much lower O3 mixing ratio in East and Central China compared to the simulations using REAS and EDGAR estimates, due to their low VOC emissions. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding effective mitigation measures for reducing national and regional air pollution in China.

scholarly journals Changes in China's anthropogenic emissions and air quality during the COVID-19 pandemic in 2020

2021 ◽  
Vol 13 (6) ◽  
pp. 2895-2907
Author(s):  
Bo Zheng ◽  
Qiang Zhang ◽  
Guannan Geng ◽  
Cuihong Chen ◽  
Qinren Shi ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Model Simulation ◽  
Ambient Air ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Ambient Air Pollution ◽  
Anthropogenic Emissions ◽  
Quality Changes ◽  
Air Quality Model

Abstract. The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. The short-term impacts of lockdowns on China's air quality have been measured and reported, however, the changes in anthropogenic emissions have not yet been assessed quantitatively, which hinders our understanding of the causes of the air quality changes during COVID-19. Here, for the first time, we report the anthropogenic air pollutant emissions from mainland China by using a bottom-up approach based on the near-real-time data in 2020 and use the estimated emissions to simulate air quality changes with a chemical transport model. The COVID-19 lockdown was estimated to have reduced China's anthropogenic emissions substantially between January and March in 2020, with the largest reductions in February. Emissions of SO2, NOx, CO, non-methane volatile organic compounds (NMVOCs), and primary PM2.5 were estimated to have decreased by 27 %, 36 %, 28 %, 31 %, and 24 %, respectively, in February 2020 compared to the same month in 2019. The reductions in anthropogenic emissions were dominated by the industry sector for SO2 and PM2.5 and were contributed to approximately equally by the industry and transportation sectors for NOx, CO, and NMVOCs. With the spread of coronavirus controlled, China's anthropogenic emissions rebounded in April and since then returned to the comparable levels of 2019 in the second half of 2020. The provinces in China have presented nearly synchronous decline and rebound in anthropogenic emissions, while Hubei and the provinces surrounding Beijing recovered more slowly due to the extension of lockdown measures. The ambient air pollution presented much lower concentrations during the first 3 months in 2020 than in 2019 while rapidly returning to comparable levels afterward, which have been reproduced by the air quality model simulation driven by our estimated emissions. China's monthly anthropogenic emissions in 2020 can be accessed from https://doi.org/10.6084/m9.figshare.c.5214920.v2 (Zheng et al., 2021) by species, month, sector, and province.

scholarly journals Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns

2021 ◽  
Vol 7 (3) ◽  
pp. eabd6696
Author(s):  
Zongbo Shi ◽  
Congbo Song ◽  
Bowen Liu ◽  
Gongda Lu ◽  
Jingsha Xu ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Quality Improvements ◽  
Learning Technique ◽  
Emission Changes ◽  
Almost All ◽  
Gaseous Oxidant ◽  
Sophisticated Analysis ◽  
Limited Change

The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (Ox = NO2 + O3) showed limited change, and PM2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.

scholarly journals Renewable Energy Sources vs. an Air Quality Improvement in Urbanized Areas - the Metropolitan Area of Kraków Case

2021 ◽  
Vol 9 ◽  
Author(s):  
Rafał Blazy ◽  
Jakub Błachut ◽  
Agnieszka Ciepiela ◽  
Rita Łabuz ◽  
Renata Papież
Keyword(s):  
Air Quality ◽  
Metropolitan Area ◽  
Renewable Energy Sources ◽  
Well Being ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Single Family ◽  
Air Quality Improvement ◽  
The Government ◽  
Selection Of

The premise for the selection of the topic discussed in this article is the lack of research on the level of reduction of air pollutant emissions by the use of photovoltaic micro-installations in single-family buildings, both in Poland and other countries of Central and Eastern Europe. Therefore, the Authors made an attempt to estimate the scale of air pollution reduction (in particular CO2) in the area of the urbanized Metropolitan area of Krakow, which is one of the most polluted regions in Poland. The installation of photovoltaic panels on single-family buildings, co-financed by the government My Electricity Program, is the investment cost in improving the air quality in this region, and thus increasing the well-being of its inhabitants.

scholarly journals EURODELTA-Trends, a multi-model experiment of air quality hindcast in Europe over 1990–2010

2017 ◽  
Vol 10 (9) ◽  
pp. 3255-3276 ◽  
Author(s):  
Augustin Colette ◽  
Camilla Andersson ◽  
Astrid Manders ◽  
Kathleen Mar ◽  
Mihaela Mircea ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Boundary Conditions ◽  
Radiative Forcing ◽  
Regional Scale ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Mitigation Measures ◽  
Modelling Experiment ◽  
Technical Features

Abstract. The EURODELTA-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990–2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional-scale air quality. The present paper formulates the main scientific questions and policy issues being addressed by the EURODELTA-Trends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions. The experiment is designed in three tiers, with increasing degrees of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000, and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions, and (iii) meteorology complements it. The most demanding tier consists of two complete time series from 1990 to 2010, simulated using either time-varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and five models have – to date – completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community. The main expected outcomes are (i) an evaluation of the models' performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990–2010 time period, (iii) attribution analyses of the respective role of driving factors (e.g. emissions, boundary conditions, meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem, and radiative forcing.

scholarly journals Enhanced atmospheric oxidizing capacity in simulating air quality with updated emission inventories for power plants especially for haze periods over East China

2017 ◽  
Author(s):  
Lei Zhang ◽  
Tianliang Zhao ◽  
Sunling Gong ◽  
Shaofei Kong ◽  
Lili Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Power Plants ◽  
Emission Inventory ◽  
Environmental Changes ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Atmospheric Environment ◽  
Pollutant Emission ◽  
East China ◽  
Emission Inventories

Abstract. Air pollutant emissions play a determinant role in deteriorating air quality. However, an uncertainty in emission inventories is still the key problem for modeling air pollution. In this study, an updated emission inventory of coal-fired power plants (UEIPP) based on online monitoring data in Jiangsu province of East China for the year of 2012 was implemented in the widely used Multi-resolution Emission Inventory for China (MEIC). By employing the Weather Research and Forecasting Model with Chemistry (WRF-Chem), two simulations were executed to assess the atmospheric environmental change by using the original MEIC emission inventory and the MEIC inventory with the UEIPP. A synthetic analysis shows that (1) compared to the power emissions of MEIC, PM2.5, PM10, SO2 and NOx were lower, and CO, black carbon (BC), organic carbon (OC) and NMVOCs were higher in the UEIPP, reflecting a large discrepancy in the power emissions over East China; (2) In accordance with the changes of UEIPP, the modeled concentrations were reduced for SO2 and NO2, and increased for most areas of primary OC, BC and CO, whose concentrations in atmosphere are highly dependent on emission changes. (3) Interestingly, when the UEIPP was used, the atmospheric oxidizing capacity significantly reinforced, reflecting by increased oxidizing agents, e.g. O3 and OH, thus directly strengthened the chemical production from SO2 and NOx to sulfate and nitrate, which offset the reduction of primary PM2.5 emissions especially in the haze days. This study indicated the importance of updating air pollutant emission inventories in simulating the complex atmospheric environment changes with the implications on air quality and environmental changes.

Comparison of Modeled-to-Monitored PM2.5 Exposure Concentrations Resulting from Transportation Emissions in a Near-Road Community

2020 ◽  
Vol 2674 (12) ◽  
pp. 130-143
Author(s):  
Mayra Chavez ◽  
Wen-Whai Li
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Temporal Variations ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Spatial And Temporal Variations ◽  
Quality Data ◽  
Background Concentrations ◽  
Regional Background ◽  
Transportation Emissions

Residents living in near-road communities are exposed to traffic-related air pollutants, which can adversely affect their health. Near-road communities are expected to observe significant spatial and temporal variations in pollutant concentrations. Determining these variations in the surrounding areas can help raise awareness among government agencies of these underserved communities living near highways. This study conducted traffic and air quality measurements along with emission and dispersion modeling of the exposure to transportation emissions of a near-road urban community adjacent to the US 54 highway (US 54), with annual average daily traffic (AADT) of 107,237. The objectives of this study were (i) to develop spatial and temporal patterns of pollutant concentration variation and (ii) to apportion the differences in exposure concentrations to background concentrations and those that are contributed from major highways. It was observed that: (a) particulate matter (PM2.5) in near-road communities is dominated by the regional background concentrations which account for more than 85% of the pollution; and (b) only near-road receptors are affected by the traffic-related air pollutant emissions from major highways while spatial and temporal variations of PM2.5 concentrations in near-road communities are less influenced by local traffic, subsiding rapidly to negligible concentrations at 300 m from the road. Modeled PM2.5 concentrations were compared with monitored data. For better air quality impact assessments, higher quality data such as time-specific traffic volume and fleet information as well as site-specific meteorological data could help yield more accurate concentration predictions. Modeled-to-monitored comparison shows that air quality in near-road communities is dominated by regional background concentrations.

scholarly journals Air pollutant emissions from Chinese households: A major and underappreciated ambient pollution source

2016 ◽  
Vol 113 (28) ◽  
pp. 7756-7761 ◽  
Author(s):  
Jun Liu ◽  
Denise L. Mauzerall ◽  
Qi Chen ◽  
Qiang Zhang ◽  
Yu Song ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Eastern China ◽  
Pollution Prevention ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Base Case ◽  
Chinese Government ◽  
Industrial Sectors ◽  
Bth Region

As part of the 12th Five-Year Plan, the Chinese government has developed air pollution prevention and control plans for key regions with a focus on the power, transport, and industrial sectors. Here, we investigate the contribution of residential emissions to regional air pollution in highly polluted eastern China during the heating season, and find that dramatic improvements in air quality would also result from reduction in residential emissions. We use the Weather Research and Forecasting model coupled with Chemistry to evaluate potential residential emission controls in Beijing and in the Beijing, Tianjin, and Hebei (BTH) region. In January and February 2010, relative to the base case, eliminating residential emissions in Beijing reduced daily average surface PM2.5 (particulate mater with aerodynamic diameter equal or smaller than 2.5 micrometer) concentrations by 14 ± 7 μg⋅m−3 (22 ± 6% of a baseline concentration of 67 ± 41 μg⋅m−3; mean ± SD). Eliminating residential emissions in the BTH region reduced concentrations by 28 ± 19 μg⋅m−3 (40 ± 9% of 67 ± 41 μg⋅m−3), 44 ± 27 μg⋅m−3 (43 ± 10% of 99 ± 54 μg⋅m−3), and 25 ± 14 μg⋅m−3 (35 ± 8% of 70 ± 35 μg⋅m−3) in Beijing, Tianjin, and Hebei provinces, respectively. Annually, elimination of residential sources in the BTH region reduced emissions of primary PM2.5 by 32%, compared with 5%, 6%, and 58% achieved by eliminating emissions from the transportation, power, and industry sectors, respectively. We also find air quality in Beijing would benefit substantially from reductions in residential emissions from regional controls in Tianjin and Hebei, indicating the value of policies at the regional level.

On the initial-state assimilation for limited-area air-quality forecasts

2020 ◽  
Author(s):  
Rostislav Kouznetsov ◽  
Mikhail Sofiev
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Air Pollutant ◽  
Optimal Interpolation ◽  
Limited Area ◽  
Time Data ◽  
Initial State ◽  
Skill Scores ◽  
Forecast Lead Time ◽  
Set Up

<p>An ensemble of 9 regional Air Quality models is being run operationally within CAMS-50 project providing the 3D fields of air-pollutant distribution over Europe. The models are initialized from their previous-day's forecasts for 00Z and run for 4 days forward. The same models are used for near-real-time reanalysis of the previous day involving the air-quality observations to adjust the modelled  fields via data assimilation methods, such as 3D-var or optimal-interpolation procedures.  In this set-up the observed near-real-time data do not affect the forecasts.  Development of a method to improve the forecast quality by using the assimilated fields from the previous-day analysis is one of the goals for the CAMS-61 project.</p><p>As a prototype evaluation for this study, we made several tests with SILAM model (http://silam.fmi.fi) initializing the simulations from the assimilated or non-assimilated states and evaluated the evolution of the model skill scores along the forecast lead time. The tests were made for summer and winter seasons and for initialization time of 00Z vs 12Z.  In order to generalize the results, and make them independent on particular implementation of 3D-VAR in SILAM, the tests were made also with initialization from the analyses made with other CAMS-50 models.  That experiment utilized the list of species and vertical available in the CAMS-50 product catalog. </p><p>The results of the simulation corroborated with our earlier studies that showed a quite quick relaxation of the scores for runs initialized from analyses to the free-run state: with certain variability between the species, the runs converged to the free-run trajectory generally within several hours.  We also investigated the issues connected with initialization from the incomplete set of species and sparse vertical, which might make the scores of the forecast initialized from the incomplete assimilated model state being worse than the ones from the free-run model.</p><p> </p>

scholarly journals Mapping the drivers of formaldehyde (HCHO) variability from 2015–2019 over eastern China: insights from FTIR observation and GEOS-Chem model simulation

2020 ◽  
Author(s):  
Youwen Sun ◽  
Hao Yin ◽  
Cheng Liu ◽  
Lin Zhang ◽  
Yuan Cheng ◽  
...  
Keyword(s):  
Air Quality ◽  
Model Simulation ◽  
Eastern China ◽  
Mean Value ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Mitigation Measures ◽  
Positive Trend ◽  
Oh Radical ◽  
Clean Air

Abstract. The major air pollutant emissions have decreased and the overall air quality has substantially improved across China in recent years as a consequence of active clean air policies for mitigating severe air pollution problems. As key precursors of formaldehyde (HCHO) and ozone (O3), the volatile organic compounds (VOCs) in China are still increasing because current clean air policies lack mitigation measures for VOCs. In this study, we mapped the drivers of HCHO variability over eastern China using ground-based high-resolution Fourier transform infrared (FTIR) spectrometry and GEOS-Chem model simulation. Diurnal, seasonal, and interannual variability of HCHO over eastern China was investigated and hydroxyl (OH) radical production from HCHO was evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO were analysed by using ground level carbon monoxide (CO) and Ox (O3 + nitrogen oxide (NO2)) as tracers for emitted and photochemical HCHO, respectively. Contributions of various emission sectors and geographical transport to the observed HCHO summertime enhancements were determined by using a GEOS-Chem tagged-tracer simulation. The tropospheric HCHO volume mixing ratio (VMR) reached a maximum monthly mean value of (1.1 ± 0.27) ppbv in July and a minimum monthly mean value of (0.4 ± 0.11) ppbv in January. The tropospheric HCHO VMR time series from 2015–2019 shows a positive trend of (1.43 ± 0.14) % per yr. The photochemical HCHO is the dominant source of atmospheric HCHO over eastern China for most of the year (68.1 %). In the studied years, the HCHO photolysis was an important source of OH radical over eastern China during all sunlight hours of both summer and winter days. The anthropogenic emissions (fossil fuel + biofuel emissions) accounted for 31.96 % and the natural emissions (biomass burning + biogenic) accounted for 48.75 % of HCHO summertime enhancements. The observed HCHO summertime enhancements were largely attributed to the emissions within China (76.92 %), where eastern China dominated the contribution (46.24 %). The increased trend in HCHO in recent years was largely attributed to the increase in the HCHO precursors such as CH4 and nonmethane VOCs (NMVOCs). This study can provide an evaluation of recent VOC emissions and regional photochemical capacity in China. In addition, this study is also important for regulatory and control purposes and will help to improve urban air quality and contribute to the formation of new Chinese clean air policies in the future.

Sign in / Sign up

Export Citation Format

Share Document