Abstract. In 2013, China's government published the Air Pollution Prevention and Control Action Plan (APPCAP) with a specific target for Beijing, which aims to reduce annual mean PM2.5 concentrations in Beijing to 60 µg m−3 in 2017. During 2013–2017, the air quality in Beijing was significantly improved following the implementation of various emission control measures locally and regionally, with the annual mean PM2.5 concentration decreasing from 89.5 µg m−3 in 2013 to 58 µg m−3 in 2017. As meteorological conditions were more favourable to the reduction of air pollution in 2017 than in 2013 and 2016, the real effectiveness of emission control measures on the improvement of air quality in Beijing has frequently been questioned. In this work, by combining a detailed bottom-up emission inventory over Beijing, the MEIC regional emission inventory and the WRF-CMAQ (Weather Research and Forecasting Model and Community Multiscale Air Quality) model, we attribute the improvement in Beijing's PM2.5 air quality in 2017 (compared to 2013 and 2016) to the following factors: changes in meteorological conditions, reduction of emissions from surrounding regions, and seven specific categories of local emission control measures in Beijing. We collect and summarize data related to 32 detailed control measures implemented during 2013–2017, quantify the emission reductions associated with each measure using the bottom-up local emission inventory in 2013, aggregate the measures into seven categories, and conduct a series of CMAQ simulations to quantify the contribution of different factors to the PM2.5 changes. We found that, although changes in meteorological conditions partly explain the improved PM2.5 air quality in Beijing in 2017 compared to 2013 (3.8 µg m−3, 12.1 % of total), the rapid decrease in PM2.5 concentrations in Beijing during 2013–2017 was dominated by local (20.6 µg m−3, 65.4 %) and regional (7.1 µg m−3, 22.5 %) emission reductions. The seven categories of emission control measures, i.e. coal-fired boiler control, clean fuels in the residential sector, optimize industrial structure, fugitive dust control, vehicle emission control, improved end-of-pipe control, and integrated treatment of VOCs, reduced the PM2.5 concentrations in Beijing by 5.9, 5.3, 3.2, 2.3, 1.9, 1.8, and 0.2 µg m−3, respectively, during 2013–2017. We also found that changes in meteorological conditions could explain roughly 30 % of total reduction in PM2.5 concentration during 2016–2017 with more prominent contribution in winter months (November and December). If the meteorological conditions in 2017 had remained the same as those in 2016, the annual mean PM2.5 concentrations would have increased from 58 to 63 µg m−3, exceeding the target established in the APPCAP. Despite the remarkable impacts from meteorological condition changes, local and regional emission reductions still played major roles in the PM2.5 decrease in Beijing during 2016–2017, and clean fuels in the residential sector, coal-fired boiler control, and optimize industrial structure were the three most effective local measures (contributing reductions of 2.1, 1.9, and 1.5 µg m−3, respectively). Our study confirms the effectiveness of clean air actions in Beijing and its surrounding regions and reveals that a new generation of control measures and strengthened regional joint emission control measures should be implemented for continued air quality improvement in Beijing because the major emitting sources have changed since the implementation of the clean air actions.

Abstract. We describe a new generation of the high-performance GEOS-Chem (GCHP) global model of atmospheric composition developed as part of the GEOS-Chem version 13 series. GEOS-Chem is an open-source grid-independent model that can be used online within a meteorological simulation or offline using archived meteorological data. GCHP is an offline implementation of GEOS-Chem driven by NASA Goddard Earth Observing System (GEOS) meteorological data for massively parallel simulations. Version 13 offers major advances in GCHP for ease of use, computational performance, versatility, resolution, and accuracy. Specific improvements include (i) stretched-grid capability for higher resolution in user-selected regions, (ii) more accurate transport with new native cubed-sphere GEOS meteorological archives including air mass fluxes at hourly temporal resolution with spatial resolution up to C720 (∼ 12 km), (iii) easier build with a build system generator (CMake) and a package manager (Spack), (iv) software containers to enable immediate model download and configuration on local computing clusters, (v) better parallelization to enable simulation on thousands of cores, and (vi) multi-node cloud capability. The C720 data are now part of the operational GEOS forward processing (GEOS-FP) output stream, and a C180 (∼ 50 km) consistent archive for 1998–present is now being generated as part of a new GEOS-IT data stream. Both of these data streams are continuously being archived by the GEOS-Chem Support Team for access by GCHP users. Directly using horizontal air mass fluxes rather than inferring from wind data significantly reduces global mean error in calculated surface pressure and vertical advection. A technical performance demonstration at C720 illustrates an attribute of high resolution with population-weighted tropospheric NO2 columns nearly twice those at a common resolution of 2∘ × 2.5∘.

No abstract

Based on a biodegradable cross-linker, N-maleyl chitosan (N-MACH), a series of Poly(N-isopropylacrylamide) (PNIPAAm) and Poly(N-isopropylacrylamide-co-acrylamide) [P(NIPAAm-co-Am)] hydrogels were prepared, and their lower critical solution temperature (LCST), swelling kinetics, equilibrium swelling ratio in NaCl solution, and enzymatic degradation behavior in simulated gastric fluids (SGF) were discussed. The LCST did not change with different cross-linker contents. By altering the NIPAAm/Am molar ratio of P(NIPAAm-co-Am) hydrogels, the LCST could be increased to 39°C. The LCST of the hydrogel was significantly influenced by the monomer ratio of the NIPAAm/Am but not by the cross-linker content. In the swelling kinetics, all the dry hydrogels exhibited fast swelling behavior, and the swelling ratios were influenced by the cross-linker content and NIPAAm/Am molar ratios. Equilibrium swelling ratio of all the hydrogels decreased with increasing NaCl solution concentration. In enzymatic degradation tests, the weight loss of hydrogels was dependent on the cross-linker contents and the enzyme concentration. © Versita Sp. z o.o.

Emissions in many sources are estimated in municipal district totals and spatially disaggregated onto grid cells using empirically selected spatial proxies such as population density, which might introduce biases, especially in fine spatial scale. Efforts have been made to improve the spatial representation of emission inventory, by incorporating comprehensive point source database (e.g. power plants, industrial facilities) in emission estimates. Satellite-based observations from the TROPOspheric Monitoring Instrument (TROPOMI) with unprecedented pixel sizes (3.5 × 7 km2) and signal-to-noise ratios offer the opportunity to evaluate the spatial accuracy of such highly resolved emissions from space. Here, we compare the city-level NO x emissions from a proxy-based emission inventory named the Multi-resolution Emission Inventory for China (MEIC) with a highly resolved emission inventory named the Multi-resolution Emission Inventory for China - High Resolution (MEIC-HR) that has nearly 100 000 industrial facilities, and evaluate them through NO x emissions derived from the TROPOMI NO2 tropospheric vertical column densities (TVCDs). We find that the discrepancies in city-level NO x emissions between MEIC and MEIC-HR are influenced by the proportions of emissions from point sources and NO x emissions per industrial gross domestic product (IGDP). The use of IGDP as a spatial proxy to disaggregate industrial emissions tends to overestimate NO x emissions in cities with lower industrial emission intensities or less industrial facilities in the MEIC. The NO x emissions of 70 cities are derived from one year TROPOMI NO2 TVCDs using the exponentially modified Gaussian function. Compared to the satellite-derived emissions, the cities with higher industrial point source emission proportions in MEIC-HR agree better with space-constrained results, indicating that integrating more point sources in the inventory would improve the spatial accuracy of emissions on city scale. In the future, we should devote more efforts to incorporating accurate locations of emitting facilities to reduce uncertainties in fine-scale emission estimates and guide future policies.