Fine-particle pollution associated with winter haze threatens the health of more than 400 million people in the North China Plain. Sulfate is a major component of fine haze particles. Record sulfate concentrations of up to ~300 μg m −3 were observed during the January 2013 winter haze event in Beijing. State-of-the-art air quality models that rely on sulfate production mechanisms requiring photochemical oxidants cannot predict these high levels because of the weak photochemistry activity during haze events. We find that the missing source of sulfate and particulate matter can be explained by reactive nitrogen chemistry in aerosol water. The aerosol water serves as a reactor, where the alkaline aerosol components trap SO 2 , which is oxidized by NO 2 to form sulfate, whereby high reaction rates are sustained by the high neutralizing capacity of the atmosphere in northern China. This mechanism is self-amplifying because higher aerosol mass concentration corresponds to higher aerosol water content, leading to faster sulfate production and more severe haze pollution.

Reactive nitrogen chemistry in aerosol water as a source of sulfate during haze events in China

Formation, features and controlling strategies of severe haze-fog pollutions in China

Thick haze plagued northeastern China in January 2013, strongly affecting both regional climate and human respiratory health. Here, we present dual carbon isotope constrained (Δ14C and δ13C) source apportionment for combustion-derived black carbon aerosol (BC) for three key hotspot regions (megacities): North China Plain (NCP, Beijing), the Yangtze River Delta (YRD, Shanghai), and the Pearl River Delta (PRD, Guangzhou) for January 2013. BC, here quantified as elemental carbon (EC), is one of the most health-detrimental components of PM2.5 and a strong climate warming agent. The results show that these severe haze events were equally affected (∼30%) by biomass combustion in all three regions, whereas the sources of the dominant fossil fuel component was dramatically different between north and south. In the NCP region, coal combustion accounted for 66% (46–74%, 95% C.I.) of the EC, whereas, in the YRD and PRD regions, liquid fossil fuel combustion (e.g., traffic) stood for 46% (18–66%) and 58% (38–68%), re...

Regionally-Varying Combustion Sources of the January 2013 Severe Haze Events over Eastern China

Long-range transport and regional sources of PM2.5 in Beijing based on long-term observations from 2005 to 2010

Formation process of the widespread extreme haze pollution over northern China in January 2013: Implications for regional air quality and climate

A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013

A Hybrid Conjugate Gradient Algorithm for Nonconvex Functions and Its Applications in Image Restoration Problems

Optimization problem, which is aimed at ﬁnding the global minimal value of a given cost function, is one of the central problem in science and engineering. Various numerical methods have been proposed to solve this problem, among which the Gradient Descent (GD) method is the most popular one due to its simplicity and eﬃciency. However, the GD method suﬀers from two main issues: the local minima and the slow convergence especially near the minima point. The Natural Gradient Descent(NGD), which has been proved as one of the most powerful method for various optimization problems in machine learning, tensor network, variational quantum algorithms and so on, supplies an eﬃcient way to accelerate the convergence. Here, we give a uniﬁed method to extend the NGD method to a more general situation which keeps the fast convergence by looking for a more suitable metric through introducing a ’proper’ reference Riemannian manifold. Our method generalizes the NDG, and may give more insight of the optimization methods.

Meng-Xiang Zhang

Papers

A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013

A Hybrid Conjugate Gradient Algorithm for Nonconvex Functions and Its Applications in Image Restoration Problems

Generalization to the Natural Gradient Descent