Geographical Distribution of Atmospheric Nitrogen Deposition in China and Its Response to Emission Control Policy

Atmospheric nitrogen(N)deposition has experienced significant change because of anthropogenic emissions,thereby exert-ing a pronounced impact on global ecosystem services.With the rapid development of industry and agriculture and the swift expansion of urban areas in China since the 1980s,reactive nitrogen(Nr)emissions and N deposition have substantially increased.In pursuit of im-proving air quality,China has implemented a series of environmental protection policies and undertaken diverse measures to reduce pol-lutant emissions.This paper is a review of multivariate data sources of atmospheric N deposition based on the results of literature from 1980 to 2023,and the original data from 1980 to 2020 are summarized,counted and calculated.The main findings are as follows:1)the annual average atmospheric N deposition ranged from approximately 20-40 kg/(ha·yr),with the variability primarily linked to different assessment methods;2)regional disparities were evident in the spatial distribution of N deposition,with elevated values concentrated in areas with intense Nr emissions;3)atmospheric N deposition significantly declined after 2010,particularly the deposition of oxidized N,while reduced N deposition remained stable.These results reflect the effects of China's serious control policies on nitrogen oxide(NO.)emissions and strengthen the importance of agricultural NH3 emission mitigation.This study contributes to a comprehensive understand-ing of the N dynamics in the emission-deposition process,and provides a scientific foundation for the research of environmental protec-tion,climate change,and sustainable development.

A review and evaluation of nonroad diesel mobile machinery emission control in China

China’s emission control for nonroad diesel mobile machinery(NDMM)must deal with a fast increase in stock as well as regulations that are two decades behind those for on-road vehicles.This study provides the first large-scale review and evaluation of China’s NDMM policies,along with emission measurements and an investigation on diesel fuel quality.The sulfur contents of the investigated diesel declined from 430 ppm(median value)in 2011 to6-8 ppm during the 2017-2018 period.The emission control of NO_(x)and PM greatly improved with the shift from the China II to China IV standards,as demonstrated by engine tests and field NO_(x)measurements.However,the NO_(x)emission factors for non-type-approved engines were approximately twice the limits of the China II standards.Emission compliance based on bench tests was not sufficient to control actual emissions because the field-measured NO_(x)emission factors of all machinery ranged from 24%to 225%greater than the respective emission limits for the engines.These circumstances adversely affected the effectiveness of the regulations and policies for China’s emission control of NDMM.Nevertheless,the policies on new and in-use NDMM,as well as diesel fuel quality,prevented NO_(x)and PM emissions amounting to 4.4 Tg and 297.8 Gg during the period 2008-2017,respectively.The emission management strategy contributed to enhancing the international competitiveness of China’s NDMM industries by promoting advanced technologies.For effective NDMM emission control in the future,portable testing and noncontact remote supervision should be strengthened;also,the issue of noncompliant diesel should be addressed through rigorous control measures and financial penalties.

Recent advances and perspectives towards emission inventories of mobile sources:Compilation approaches,data acquisition methods,and case studies

In recent years,great efforts have been devoted to reducing emissions from mobile sources with the dramatic growth of motor vehicle and nonroad mobile source populations.Compilation of a mobile source emission inventory is conducive to the analysis of pollution emission characteristics and the formulation of emission reduction policies.This study summarizes the latest compilation approaches and data acquisition methods for mobile source emission inventories.For motor vehicles,a high-resolution emission inventory can be developed based on a bottom-up approach with a refined traffic flow model and real-world speed-coupled emission factors.The top-down approach has advantages when dealing with macroscale vehicle emission estimation without substantial traffic flow infrastructure.For nonroad mobile sources,nonroad machinery,inland river ships,locomotives,and civil aviation aircraft,a top-down approach based on fuel consumption or power is adopted.For ocean-going ships,a bottom-up approach based on automatic identification system(AIS)data is adopted.Three typical cases are studied,including emission reduction potential,a cost-benefit model,and marine shipping emission control.Outlooks and suggestions are given on future research directions for emission inventories for mobile sources:building localized emission models and factor databases,improving the dynamic updating capability of emission inventories,establishing a database of emission factors of unconventional pollutants and greenhouse gas from mobile sources,and establishing an urban high temporalspatial resolution volatile organic compound(VOC)evaporation emission inventory.

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling（RSM） methodology and serves as a visualization and analysis tool（VAT） for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S.demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias 〈 2% and assisting in air quality policy making in near real time.