ALBERT

Description: In many cities around the world people are exposed to elevated levels of air pollution. Often local air quality is not well known due to the sparseness of official monitoring networks or unrealistic assumptions being made in urban-air-quality models. Low-cost sensor technology, which has become available in recent years, has the potential to provide complementary information. Unfortunately, an integrated interpretation of urban air pollution based on different sources is not straightforward because of the localized nature of air pollution and the large uncertainties associated with measurements of low-cost sensors. This study presents a practical approach to producing high-spatiotemporal-resolution maps of urban air pollution capable of assimilating air quality data from heterogeneous data streams. It offers a two-step solution: (1) building a versatile air quality model, driven by an open-source atmospheric-dispersion model and emission proxies from open-data sources, and (2) a practical spatial-interpolation scheme, capable of assimilating observations with different accuracies. The methodology, called Retina, has been applied and evaluated for nitrogen dioxide (NO2) in Amsterdam, the Netherlands, during the summer of 2016. The assimilation of reference measurements results in hourly maps with a typical accuracy (defined as the ratio between the root mean square error and the mean of the observations) of 39 % within 2 km of an observation location and 53 % at larger distances. When low-cost measurements of the Urban AirQ campaign are included, the maps reveal more detailed concentration patterns in areas which are undersampled by the official network. It is shown that during the summer holiday period, NO2 concentrations drop about 10 %. The reduction is less in the historic city centre, while strongest reductions are found around the access ways to the tunnel connecting the northern and the southern part of the city, which was closed for maintenance. The changing concentration patterns indicate how traffic flow is redirected to other main roads. Overall, it is shown that Retina can be applied for an enhanced understanding of reference measurements and as a framework to integrate low-cost measurements next to reference measurements in order to get better localized information in urban areas.

Description: We improve the emission estimate algorithm DECSO (Daily Emission estimates Constrained by Satellite Observations) to better detect NOx emissions over remote areas. The new version is referred to as DECSO v5. The error covariance of the sensitivity of NO2 column observations to gridded NOx emissions has been better characterized. This reduces the background noise of emission estimates by a factor of 10. An emission update constraint has been added to avoid unrealistic day-to-day fluctuations of emissions. We estimate total NOx emissions, which include biogenic emissions that often drive the seasonal cycle of the NOx emissions. We demonstrate the improvements implemented in DECSO v5 for the domain of East Asia in the year 2012 and 2013. The emissions derived by DECSO v5 are in good agreement with other inventories like MIX. In addition, the improved algorithm is able to better capture the seasonality of NOx emissions and for the first time it reveals ship tracks near the Chinese coasts that are otherwise hidden by the outflow of NO2 from the Chinese mainland. The precision of monthly emissions derived by DECSO v5 for each grid cell is about 20 %.

Description: We compare nine emission inventories of nitrogen oxides including four satellite-derived NOx inventories and the following bottom-up inventories for East Asia: REAS (Regional Emission inventory in ASia), MEIC (Multi-resolution Emission Inventory for China), CAPSS (Clean Air Policy Support System) and EDGAR (Emissions Database for Global Atmospheric Research). Two of the satellite-derived inventories are estimated by using the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm, which is based on an extended Kalman filter applied to observations from OMI or from GOME-2. The other two are derived with the EnKF algorithm, which is based on an ensemble Kalman filter applied to observations of multiple species using either the chemical transport model CHASER and MIROC-chem. The temporal behaviour and spatial distribution of the inventories are compared on a national and regional scale. A distinction is also made between urban and rural areas. The intercomparison of all inventories shows good agreement in total NOx emissions over mainland China, especially for trends, with an average bias of about 20 % for yearly emissions. All the inventories show the typical emission reduction of 10 % during the Chinese New Year and a peak in December. Satellite-derived approaches using OMI show a summer peak due to strong emissions from soil and biomass burning in this season. Biases in NOx emissions and uncertainties in temporal variability increase quickly when the spatial scale decreases. The analyses of the differences show the importance of using observations from multiple instruments and a high spatial resolution model for the satellite-derived inventories, while for bottom-up inventories, accurate emission factors and activity information are required. The advantage of the satellite-derived approach is that the emissions are soon available after observation, while the strength of the bottom-up inventories is that they include detailed information of emissions for each source category.

Description: Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope  =  0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope  =  1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10–40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of −30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15 % in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

Description: In many urban areas the population is exposed to elevated levels of air pollution. However, real-time air quality is usually only measured at few locations. These measurements provide a general picture of the state of the air, but they are unable to monitor local differences. New low-cost sensor technology is available for several years now, and has the potential to extend official monitoring networks significantly even though the current generation of sensors suffer from various technical issues. Citizen science experiments based on these sensors must be designed carefully to avoid generation of data which is of poor or even useless quality. This study explores the added value of the 2016 Urban AirQ campaign, which focused on measuring nitrogen dioxide (NO2) in Amsterdam, the Netherlands. Sixteen low-cost air quality sensor devices were built and distributed among volunteers living close to roads with high traffic volume for a 2-month measurement period. Each electrochemical sensor was calibrated in-field next to an air monitoring station during an 8-day period, resulting in R2 ranging from 0.3 to 0.7. When temperature and relative humidity are included in a multilinear regression approach, the NO2 accuracy is improved significantly, with R2 ranging from 0.6 to 0.9. Recalibration after the campaign is crucial, as all sensors show a significant signal drift in the 2-month measurement period. The measurement series between the calibration periods can be corrected for after the measurement period by taking a weighted average of the calibration coefficients. Validation against an independent air monitoring station shows good agreement. Using our approach, the standard deviation of a typical sensor device for NO2 measurements was found to be 7 µg m−3, provided that temperatures are below 30 ∘C. Stronger ozone titration on street sides causes an underestimation of NO2 concentrations, which 75 % of the time is less than 2.3 µg m−3. Our findings show that citizen science campaigns using low-cost sensors based on the current generations of electrochemical NO2 sensors may provide useful complementary data on local air quality in an urban setting, provided that experiments are properly set up and the data are carefully analysed.

Description: The main aim of this paper is to update existing sulfur dioxide (SO2) emission inventories over China using modern inversion techniques, state-of-the-art chemistry transport modelling (CTM) and satellite observations of SO2. Within the framework of the EU Seventh Framework Programme (FP7) MarcoPolo (Monitoring and Assessment of Regional air quality in China using space Observations) project, a new SO2 emission inventory over China was calculated using the CHIMERE v2013b CTM simulations, 10 years of Ozone Monitoring Instrument (OMI)/Aura total SO2 columns and the pre-existing Multi-resolution Emission Inventory for China (MEIC v1.2). It is shown that including satellite observations in the calculations increases the current bottom-up MEIC inventory emissions for the entire domain studied (15–55° N, 102–132° E) from 26.30 to 32.60 Tg annum−1, with positive updates which are stronger in winter ( ∼  36 % increase). New source areas were identified in the southwest (25–35° N, 100–110° E) as well as in the northeast (40–50° N, 120–130° E) of the domain studied as high SO2 levels were observed by OMI, resulting in increased emissions in the a posteriori inventory that do not appear in the original MEIC v1.2 dataset. Comparisons with the independent Emissions Database for Global Atmospheric Research, EDGAR v4.3.1, show a satisfying agreement since the EDGAR 2010 bottom-up database provides 33.30 Tg annum−1 of SO2 emissions. When studying the entire OMI/Aura time period (2005 to 2015), it was shown that the SO2 emissions remain nearly constant before the year 2010, with a drift of −0.51 ± 0.38 Tg annum−1, and show a statistically significant decline after the year 2010 of −1.64 ± 0.37 Tg annum−1 for the entire domain. Similar findings were obtained when focusing on the greater Beijing area (30–40° N, 110–120° E) with pre-2010 drifts of −0.17 ± 0.14 and post-2010 drifts of −0.47 ± 0.12 Tg annum−1. The new SO2 emission inventory is publicly available and forms part of the official EU MarcoPolo emission inventory over China, which also includes updated NOx, volatile organic compounds and particulate matter emissions.

Description: Air quality observations by satellite instruments are global and have a regular temporal resolution, which makes them very useful in studying long-term trends in atmospheric species. To monitor air quality trends in China for the period 2005–2015, we derive SO2 columns and NOx emissions on a provincial level with improved accuracy. To put these trends into perspective they are compared with public data on energy consumption and the environmental policies of China. We distinguish the effect of air quality regulations from economic growth by comparing them relatively to fossil fuel consumption. Pollutant levels, per unit of fossil fuel, are used to assess the effectiveness of air quality regulations. We note that the desulfurization regulations enforced in 2005–2006 only had a significant effect in the years 2008–2009, when a much stricter control of the actual use of the installations began. For national NOx emissions a distinct decreasing trend is only visible from 2012 onwards, but the emission peak year differs from province to province. Unlike SO2, emissions of NOx are highly related to traffic. Furthermore, regulations for NOx emissions are partly decided on a provincial level. The last 3 years show a reduction both in SO2 and NOx emissions per fossil fuel unit, since the authorities have implemented several new environmental regulations. Despite an increasing fossil fuel consumption and a growing transport sector, the effects of air quality policy in China are clearly visible. Without the air quality regulations the concentration of SO2 would be about 2.5 times higher and the NO2 concentrations would be at least 25 % higher than they are today in China.

Description: Air quality observations by satellite instruments are spatially consistent, and have a regular temporal resolution, which make them very useful in studying long-term trends in atmospheric species. To monitor air quality trends in China for the period 2005–2015 we derive SO2 columns and NOx emissions on a provincial level with an unprecedented accuracy. To put these trends into perspective they are compared with public data on energy consumption and the environmental policies of China. We distinguish the effect of air quality regulations from economic growth by comparing them relatively to fossil fuel consumption. Pollutant levels, per unit of fossil fuel, are used to assess the effectiveness of air quality regulations. We note that the desulphurisation regulations enforced in 2005–2006 only had a significant effect in the years 2008–2009 when a much stricter control of the actual use of the installations began. For national NOx emissions a distinct decreasing trend is only visible since 2012, but the emission peak year differs from province to province. Unlike SO2, emissions of NOx are highly related to traffic. Furthermore, regulations for NOx emissions are partly decided on a provincial level. The last three years show both a reduction in SO2 and NOx emissions per fossil fuel unit, since the authorities have implemented several new environmental regulations. Despite an increasing fossil fuel consumption and a growing transport sector, the effects of air quality policy in China are clearly visible. Without the air quality regulations the concentration of SO2 would be almost 3 times higher and the NO2 concentrations would be at least 30 % higher than they are today in China.