scholarly journals Time-resolved emission reductions for atmospheric chemistry modelling in Europe during the COVID-19 lockdowns

2020 ◽  
Author(s):  
Marc Guevara ◽  
Oriol Jorba ◽  
Albert Soret ◽  
Hervé Petetin ◽  
Dene Bowdalo ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Emission Reduction ◽  
Power Plants ◽  
Road Traffic ◽  
Urban Background ◽  
Emission Reductions ◽  
Time Resolved ◽  
Wide Range ◽  
Reduction Factors

Abstract. We quantify the reductions in primary emissions due to the COVID-19 lockdowns in Europe. Our estimates are provided in the form of a dataset of reduction factors varying per country and day that will allow modelling and identifying the associated impacts upon air quality. The country- and daily-resolved reduction factors are provided for each of the following source categories: energy industry (power plants), manufacturing industry, road traffic and aviation (landing and take-off cycle). We computed the reduction factors based on open access and near-real time measured activity data from a wide range of information sources. We also trained a machine learning model with meteorological data to derive weather-normalised electricity consumption reductions. The time period covered is from 21 February, when the first European localised lockdown was implemented in the region of Lombardy (Italy), until 26 April 2020. This period includes five weeks (23 March until 26 April) with the most severe and relatively unchanged restrictions upon mobility and socio-economic activities across Europe. The computed reduction factors were combined with the Copernicus Atmosphere Monitoring Service's European emission inventory using adjusted emission temporal profiles in order to derive time-resolved emission reductions per country and pollutant sector. During the most severe lockdown period, we estimate the average emission reductions to be −33 % for NOx, −8 % for NMVOC, −7 % for SOx and −7 % for PM2.5 at the EU-30 level (EU-28 plus Norway and Switzerland). For all pollutants more than 85 % of the total reduction is attributable to road transport, except SOx. The reductions reached −50 % (NOx), −14 % (NMVOC), −12 % (SOx) and −15 % (PM2.5) in countries where the lockdown restrictions were more severe such as Italy, France or Spain. To show the potential for air quality modelling we simulated and evaluated NO2 concentration decreases in rural and urban background regions across Europe (Italy, Spain, France, Germany, United-Kingdom and Sweden). We found the lockdown measures to be responsible for NO2 reductions of up to −58 % at urban background locations (Madrid, Spain) and −44 % at rural background areas (France), with an average contribution of the traffic sector to total reductions of 86 % and 93 %, respectively. A clear improvement of the modelled results was found when considering the emission reduction factors, especially in Madrid, Paris and London where the bias is reduced with more than 90 %. Future updates will include the extension of the COVID-19 lockdown period covered, the addition of other pollutant sectors potentially affected by the restrictions (commercial/residential combustion and shipping) and the evaluation of other air quality pollutants such as O3 and PM2.5. All the emission reduction factors are provided in the supplementary material.

scholarly journals Time-resolved emission reductions for atmospheric chemistry modelling in Europe during the COVID-19 lockdowns

2021 ◽  
Vol 21 (2) ◽  
pp. 773-797
Author(s):  
Marc Guevara ◽  
Oriol Jorba ◽  
Albert Soret ◽  
Hervé Petetin ◽  
Dene Bowdalo ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Emission Reduction ◽  
Power Plants ◽  
Road Traffic ◽  
Urban Background ◽  
Emission Reductions ◽  
Time Resolved ◽  
Wide Range ◽  
Reduction Factors

Abstract. We quantify the reductions in primary emissions due to the COVID-19 lockdowns in Europe. Our estimates are provided in the form of a dataset of reduction factors varying per country and day that will allow the modelling and identification of the associated impacts upon air quality. The country- and daily-resolved reduction factors are provided for each of the following source categories: energy industry (power plants), manufacturing industry, road traffic and aviation (landing and take-off cycle). We computed the reduction factors based on open-access and near-real-time measured activity data from a wide range of information sources. We also trained a machine learning model with meteorological data to derive weather-normalized electricity consumption reductions. The time period covered is from 21 February, when the first European localized lockdown was implemented in the region of Lombardy (Italy), until 26 April 2020. This period includes 5 weeks (23 March until 26 April) with the most severe and relatively unchanged restrictions upon mobility and socio-economic activities across Europe. The computed reduction factors were combined with the Copernicus Atmosphere Monitoring Service's European emission inventory using adjusted temporal emission profiles in order to derive time-resolved emission reductions per country and pollutant sector. During the most severe lockdown period, we estimate the average emission reductions to be −33 % for NOx, −8 % for non-methane volatile organic compounds (NMVOCs), −7 % for SOx and −7 % for PM2.5 at the EU-30 level (EU-28 plus Norway and Switzerland). For all pollutants more than 85 % of the total reduction is attributable to road transport, except SOx. The reductions reached −50 % (NOx), −14 % (NMVOCs), −12 % (SOx) and −15 % (PM2.5) in countries where the lockdown restrictions were more severe such as Italy, France or Spain. To show the potential for air quality modelling, we simulated and evaluated NO2 concentration decreases in rural and urban background regions across Europe (Italy, Spain, France, Germany, United-Kingdom and Sweden). We found the lockdown measures to be responsible for NO2 reductions of up to −58 % at urban background locations (Madrid, Spain) and −44 % at rural background areas (France), with an average contribution of the traffic sector to total reductions of 86 % and 93 %, respectively. A clear improvement of the modelled results was found when considering the emission reduction factors, especially in Madrid, Paris and London where the bias is reduced by more than 90 %. Future updates will include the extension of the COVID-19 lockdown period covered, the addition of other pollutant sectors potentially affected by the restrictions (commercial and residential combustion and shipping) and the evaluation of other air quality pollutants such as O3 and PM2.5. All the emission reduction factors are provided in the Supplement.

Quantification of the Emission Changes in Europe During 2020 Due to the COVID-19 Mobility Restrictions

2021 ◽  
Author(s):  
Marc Guevara ◽  
Oriol Jorba ◽  
Hervé Petetin ◽  
Hugo Denier Van Der Gon ◽  
Jeroen Kuenen ◽  
...  
Keyword(s):  
Emission Reduction ◽  
Manufacturing Industry ◽  
Meteorological Data ◽  
Road Transport ◽  
Machine Learning Techniques ◽  
Activity Data ◽  
Time Resolved ◽  
Wide Range ◽  
Emission Changes ◽  
Reduction Factors

<p>To hinder the circulation of the COVID-19 virus, European governments implemented emergency measures going from light social distancing to strict lockdowns, depending on the country. As a consequence, many industries, businesses and transport networks were forced to either close down or drastically reduce their activity, which resulted in an unprecedented drop of anthropogenic emissions. This work presents the Copernicus Atmosphere Monitoring Service (CAMS) European regional emission reduction factors associated to the COVID-19 mobility restrictions (CAMS-REG_ERF-COVID19), an open source dataset of daily-, sector-, pollutant- and country-dependent emission reduction factors for Europe linked to the COVID-19 pandemic. The resulting dataset covers a total of six emission sectors, including: road transport, energy industry, manufacturing industry, residential and commercial combustion, aviation and shipping. The time period covered by the dataset includes the first and second waves of the disease ocurred during 2020, starting from 21 February, when the first European localised lockdown was implemented in the region of Lombardy (Italy), until 31 December, when COVID-19 transmission remained widespread and several countries had nationwide restrictions still in place. The CAMS-REG_ERF-COVID19 dataset is based on a wide range of information sources and approaches, including open access and measured activity data and meteorological data, as well as the use of machine learning techniques. We combined the computed emission reduction factors with the Copernicus CAMS European gridded emission inventory to spatially (0.1x0.05 degrees) and temporally (daily) quantify reductions in 2020 primary emissions from both criteria pollutants (NO<sub>x</sub>, SO<sub>2</sub>, NMVOC, NH<sub>3</sub>, CO, PM<sub>10</sub> and PM<sub>2.5</sub>) and greenhouse gases (CO<sub>2</sub> fossil fuel, CO<sub>2</sub> biofuel and CH<sub>4</sub>), as well as to assess the contribution of each pollutant sector and country to the overall reductions. The resulting gridded and time-resolved emission reductions suggest an heterogeneous impact of the COVID-19 across pollutants, sectors and countries.</p>

scholarly journals The role of emission reductions and the meteorological situation for air quality improvements during the COVID-19 lockdown period in central Europe

2021 ◽  
Vol 21 (18) ◽  
pp. 13931-13971
Author(s):  
Volker Matthias ◽  
Markus Quante ◽  
Jan A. Arndt ◽  
Ronny Badeke ◽  
Lea Fink ◽  
...  
Keyword(s):  
Air Quality ◽  
Central Europe ◽  
Urban Areas ◽  
Road Traffic ◽  
Quality Improvements ◽  
Emission Data ◽  
Emission Reductions ◽  
Meteorological Situation ◽  
Weather Situation

Abstract. The lockdown measures taken to prevent a rapid spreading of the coronavirus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years; however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 were extrapolated from most recent reported emission data, and lockdown adjustment factors were computed from reported activity data changes, e.g. Google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with 2-week-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to ±15 %) and showed both increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx / VOC emission ratio. PM2.5 revealed 2 %–12 % reductions of 2-week-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in northern central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

Air quality modelling, simulation, and computational methods: a review

2013 ◽  
Vol 21 (3) ◽  
pp. 149-179 ◽  
Author(s):  
Mohanad El-Harbawi
Keyword(s):  
Air Quality ◽  
Computational Methods ◽  
Atmospheric Chemistry ◽  
Web Sites ◽  
Remote Sensing Data ◽  
Reference Source ◽  
Air Quality Modelling ◽  
Quality Models ◽  
Wide Range ◽  
Recent Developments

The objective of this paper is to provide a comprehensive theoretical review with regard to history, existing approaches, recent developments, major research, associated computational methods, and applications of air quality models. A wide range of topics is covered, focusing on sources of air pollution, primary and secondary pollutants, atmospheric chemistry, atmospheric chemical transport models, computer programs for dispersion modelling, online and offline air quality modelling, data assimilation, parallel computing, applications of geographic information system in air quality modelling, air quality index, as well as the use of satellite and remote sensing data in air quality modelling. Each of these elements is comprehensively discussed, covered, and reviewed with respect to various literature and methods related to air quality modelling and applications. Several major commercial and noncommercial dispersion packages are extensively reviewed and detailed advantages and limitations of their applications are highlighted. The paper includes several comparison summaries among various models used in air quality study. Furthermore, the paper provides useful web sites, where readers can obtain further information regarding air quality models and (or) software. Lastly, current generation of air quality models and future directions are also discussed. This paper may serve as a compendium for scientists who work in air quality modelling field. Some topics are generally treated; therefore, the paper may also be used as a reference source by many scientists working with air quality modelling.

scholarly journals Non-linear response of PM2.5 to changes in NO<sub>x</sub> and NH<sub>3</sub> emissions in the Po basin (Italy): consequences for air quality plans

2021 ◽  
Author(s):  
Philippe Thunis ◽  
Alain Clappier ◽  
Matthias Beekmann ◽  
Jean Philippe Putaud ◽  
Cornelis Cuvelier ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Reduction ◽  
Oxidative Capacity ◽  
Nox Emission ◽  
Aerosol Formation ◽  
Linear Processes ◽  
Emission Reductions ◽  
Nh3 Emission ◽  
Non Linear ◽  
Pm2.5 Concentration

Abstract. Air pollution is one of the main causes of damages to human health in Europe with an estimate of about 380 000 premature deaths per year in the EU28, as the result of exposure to fine particulate matter (PM2.5) only. In this work, we focus on one specific region in Europe, the Po basin, a region where chemical regimes are the most complex, showing important non-linear processes, especially those related to interactions between NOx and NH3. We analyse the sensitivities of PM2.5 to NOx and NH3 emissions by means of a set of EMEP simulations performed with different levels of emission reductions, from 25 % up to a total switch-off of those emissions. Both single and combined precursor reduction scenarios are applied to determine the most efficient emission reduction strategies and quantify the interactions between NOx and NH3 emission reductions. The results confirmed the peculiarity of secondary PM2.5 formation in the Po basin, characterised by contrasting chemical regimes within distances of few (hundreds of) kilometres, as well as strong non-linear responses to emission reductions during wintertime. One of the striking results is the increase of the PM2.5 concentration levels when NOx emission reductions are applied in NOx-rich areas, such as the surroundings of Bergamo. The increased oxidative capacity of the atmosphere is the cause of the increase of PM2.5 induced by a reduction in NOx emission. This process can have contributed to the absence of significant PM2.5 concentration decrease during the COVID-19 lockdowns in many European cities. It is important to account for this process when designing air quality plans, since it could well lead to transitionary increases in PM2.5 at some locations in winter as NOx emission reduction measures are gradually implemented. While PM2.5 responses to NOx and NH3 emission reduction show large variations seasonally and spatially, these responses remain close to linear, i.e. proportional to the emission reduction levels, at least up to −50 % because secondary aerosol formation chemical regimes are not modified by those relatively moderate ranges.

scholarly journals The role of emission reductions and the meteorological situation for air quality improvements during the COVID-19 lockdown period in Central Europe

2021 ◽  
Author(s):  
Volker Matthias ◽  
Markus Quante ◽  
Jan A. Arndt ◽  
Ronny Badeke ◽  
Lea Fink ◽  
...  
Keyword(s):  
Air Quality ◽  
Central Europe ◽  
Urban Areas ◽  
Road Traffic ◽  
Quality Improvements ◽  
Emission Data ◽  
Emission Reductions ◽  
Meteorological Situation ◽  
Weather Situation

Abstract. The lockdown measures taken to prevent a rapid spreading of the Corona virus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years, however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in Central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 was extrapolated from most recent reported emission data and lockdown adjustment factors were computed from reported activity data changes, e.g. google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with two-weeks-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to +/−15 %) and showed both, increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx/VOC emission ratio. PM2.5 revealed 2–12 % reductions of two-weeks-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in Northern Central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

scholarly journals Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling

2021 ◽  
Vol 13 (2) ◽  
pp. 367-404 ◽  
Author(s):  
Marc Guevara ◽  
Oriol Jorba ◽  
Carles Tena ◽  
Hugo Denier van der Gon ◽  
Jeroen Kuenen ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Power Plants ◽  
Manufacturing Industry ◽  
Road Traffic ◽  
Sociodemographic Factors ◽  
Electricity Production ◽  
Anthropogenic Source ◽  
Ancillary Data ◽  
Monitoring Service ◽  
Temporal Profiles

Abstract. We present the Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO), a dataset of global and European emission temporal profiles that provides gridded monthly, daily, weekly and hourly weight factors for atmospheric chemistry modelling. CAMS-TEMPO includes temporal profiles for the priority air pollutants (NOx; SOx; NMVOC, non-methane volatile organic compound; NH3; CO; PM10; and PM2.5) and the greenhouse gases (CO2 and CH4) for each of the following anthropogenic source categories: energy industry (power plants), residential combustion, manufacturing industry, transport (road traffic and air traffic in airports) and agricultural activities (fertilizer use and livestock). The profiles are computed on a global 0.1 × 0.1∘ and regional European 0.1 × 0.05∘ grid following the domain and sector classification descriptions of the global and regional emission inventories developed under the CAMS programme. The profiles account for the variability of the main emission drivers of each sector. Statistical information linked to emission variability (e.g. electricity production and traffic counts) at national and local levels were collected and combined with existing meteorology-dependent parametrizations to account for the influences of sociodemographic factors and climatological conditions. Depending on the sector and the temporal resolution (i.e. monthly, weekly, daily and hourly) the resulting profiles are pollutant-dependent, year-dependent (i.e. time series from 2010 to 2017) and/or spatially dependent (i.e. the temporal weights vary per country or region). We provide a complete description of the data and methods used to build the CAMS-TEMPO profiles, and whenever possible, we evaluate the representativeness of the proxies used to compute the temporal weights against existing observational data. We find important discrepancies when comparing the obtained temporal weights with other currently used datasets. The CAMS-TEMPO data product including the global (CAMS-GLOB-TEMPOv2.1, https://doi.org/10.24380/ks45-9147, Guevara et al., 2020a) and regional European (CAMS-REG-TEMPOv2.1, https://doi.org/10.24380/1cx4-zy68, Guevara et al., 2020b) temporal profiles are distributed from the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: February 2021).

scholarly journals Evaluation of the effect of regional joint-control measures on changing photochemical transformation: a comprehensive study of the optimization scenario analysis

2019 ◽  
Vol 19 (14) ◽  
pp. 9037-9060 ◽  
Author(s):  
Li Li ◽  
Shuhui Zhu ◽  
Jingyu An ◽  
Min Zhou ◽  
Hongli Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Emission Reduction ◽  
Meteorological Conditions ◽  
Air Pollutant ◽  
Control Measures ◽  
Joint Control ◽  
Emission Reductions ◽  
The Yrd ◽  
Comprehensive Study

Abstract. Heavy haze usually occurs in winter in eastern China. To control the severe air pollution during the season, comprehensive regional joint-control strategies were implemented throughout a campaign. To evaluate the effectiveness of these strategies and to provide some insights into strengthening the regional joint-control mechanism, the influence of control measures on levels of air pollution was estimated with an integrated measurement-emission-modeling method. To determine the influence of meteorological conditions, and the control measures on the air quality, in a comprehensive study, the 2nd World Internet Conference was held during 16–18 December 2015 in Jiaxing City, Zhejiang province, in the Yangtze River Delta (YRD) region. We first analyzed the air quality changes during four meteorological regimes and then compared the air pollutant concentrations before, during, and after the regulation under static meteorological conditions. Next, we conducted modeling scenarios to quantify the effects caused due to the air pollution control measures. We found that total emissions of SO2, NOx, PM2.5, and volatile organic compounds (VOCs) in Jiaxing were reduced by 56 %, 58 %, 64 %, and 80 %, respectively, while total emission reductions of SO2, NOx, PM2.5, and VOCs over the YRD region are estimated to be 10 %, 9 %, 10 %, and 11 %, respectively. Modeling results suggest that during the campaign from 8 to 18 December, PM2.5 daily average concentrations decreased by 10 µg m−3 with an average decrease of 14.6 %. Our implemented optimization analysis compared with previous studies also reveals that local emission reductions play a key role in air quality improvement, although it shall be supplemented by regional linkage. In terms of regional joint control, implementing pollution channel control 48 h before the event is of most benefit in getting similar results. Therefore, it is recommended that a synergistic emission reduction plan between adjacent areas with local pollution emission reductions as the core part should be established and strengthened, and emission reduction plans for different types of pollution through a stronger regional linkage should be reserved.

scholarly journals Variability of levels of PM, black carbon and particle number concentration in selected European cities

2011 ◽  
Vol 11 (3) ◽  
pp. 8665-8717 ◽  
Author(s):  
C. Reche ◽  
X. Querol ◽  
A. Alastuey ◽  
M. Viana ◽  
J. Pey ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Emissions ◽  
Northern Europe ◽  
Gaseous Pollutants ◽  
Emission Sources ◽  
Urban Background ◽  
Road Traffic Emissions ◽  
The Impact

Abstract. In many large cities of Europe standard air quality limit values of particulate matter (PM) are exceeded. Emissions from road traffic and biomass burning are frequently reported to be the major causes. As a consequence of these exceedances a large number of air quality plans, most of them focusing on traffic emissions reductions, have been implemented in the last decade. In spite of this implementation, a number of cities did not record a decrease of PM levels. Thus, is the efficiency of air quality plans overestimated? Or do we need a more specific metric to evaluate the impact of the above emissions on the levels of urban aerosols? This study shows the results of the interpretation of the 2009 variability of levels of PM, black carbon (BC), aerosol number concentration (N) and a number of gaseous pollutants in seven selected urban areas covering road traffic, urban background, urban-industrial, and urban-shipping environments from southern, central and northern Europe. The results showed that variations of PM and N levels do not always reflect the variation of the impact of road traffic emissions on urban aerosols. However, BC levels vary proportionally with those of traffic related gaseous pollutants, such as CO, NO2 and NO. Due to this high correlation, one may suppose that monitoring the levels of these gaseous pollutants would be enough to extrapolate exposure to traffic-derived BC levels. However, the BC/CO, BC/NO2 and BC/NO ratios vary widely among the cities studied, as a function of distance to traffic emissions, vehicle fleet composition and the influence of other emission sources such as biomass burning. Thus, levels of BC should be measured at air quality monitoring sites. During traffic rush hours, a narrow variation in the N/BC ratio was evidenced, but a wide variation of this ratio was determined for the noon period. Although in central and northern Europe N and BC levels tend to vary simultaneously, not only during the traffic rush hours but also during the whole day, in urban background stations in southern Europe maximum N levels coinciding with minimum BC levels are recorded at midday in all seasons. These N maxima recorded in southern European urban background environments are attributed to midday nucleation episodes occurring when gaseous pollutants are diluted and maximum insolation and O3 levels occur. The occurrence of SO2 peaks may also contribute to the occurrence of midday nucleation bursts in specific industrial or shipping-influenced areas, although at several central European sites similar levels of SO2 are recorded without yielding nucleation episodes. Accordingly, it is clearly evidenced that N variability in different European urban environments is not equally influenced by the same emission sources and atmospheric processes. We conclude that N variability does not always reflect the impact of road traffic on air quality, whereas BC is a more consistent tracer of such an influence. The combination of PM10 and BC monitoring in urban areas potentially constitutes a useful approach to evaluate the impact of road traffic emissions on air quality.

scholarly journals NO<sub>x</sub> emissions in China: historical trends and future perspectives

2013 ◽  
Vol 13 (6) ◽  
pp. 16047-16112 ◽  
Author(s):  
B. Zhao ◽  
S. X. Wang ◽  
J. Y. Xu ◽  
K. Fu ◽  
Z. Klimont ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Emission Reduction ◽  
Power Plants ◽  
Ambient Air ◽  
Control Measures ◽  
Nox Emission ◽  
Nox Emissions ◽  
Emission Scenarios ◽  
Emission Reductions ◽  
Stringent Control

Abstract. Nitrogen oxides (NOx) are key pollutants for the improvement of ambient air quality. Within this study we estimated the historical NOx emissions in China for the period 1995–2010, and calculated future NOx emissions every five years until 2030 under six emission scenarios. Driven by the fast growth of energy consumption, we estimate the NOx emissions in China increased rapidly from 11.0 Mt in 1995 to 26.1 Mt in 2010. Power plants, industry and transportation were major sources of NOx emissions, accounting for 28.4, 34.0, and 25.4% of the total NOx emissions in 2010, respectively. Two energy scenarios, a business as usual scenario (BAU) and an alternative policy scenario (PC), were developed to project future energy consumption. In 2030, total energy consumption is projected to increase by 64 and 27% from 2010 level respectively. Three sets of end-of-pipe pollution control measures, including baseline, progressive, and stringent control case, were developed for each energy scenario, thereby constituting six emission scenarios. By 2030, the total NOx emissions are projected to increase (compared to 2010) by 36% in the baseline while policy cases result in reduction up to 61% in the most ambitious case with stringent control measures. More than a third of the reduction achieved by 2030 between least and most ambitious scenario comes from power sector and more than half is distributed equally between industry and transportation sectors. Selective Catalytic Reduction dominates the NOx emission reductions in power plants, while life style changes, control measures for industrial boilers and cement production are major contributors to reductions in industry. Timely enforcement of legislation on heavy duty vehicles would contribute significantly to NOx emission reductions. About 30% of the NOx emission reduction in 2020, and 40% of the NOx emission reduction in 2030 could be treated as the ancillary benefit of energy conservation. Sensitivity analysis was conducted to explore the impact of key factors on future emissions.

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