Moderating effect of corporate financialization on the impact of climate policy on corporate green innovation:Evidence from China

With intensifying global climate change,humanity is confronted with unparalleled environmental challenges and risks.This study employs the staggered difference-in-difference model to examine the relationship between climate policy and green innovation in the corporate financialization context.Using Chinese-listed company data from 2008 to 2020,our analysis reveals a favorable correlation between China’s carbon emission trading policy(CCTP)and advancements in green innovation.Furthermore,we find that the level of corporate financialization moderates this correlation,diminishing the driving effect of CCTP on green innovation.Additionally,results of heterogeneity analysis show that this moderating consequence is more evident in non-state owned and low-digitization enterprises compared with state-owned and high-digitization ones.Our findings contribute to the existing literature by clarifying the interaction between CCTP,green innovation,and corporate financialization.Our research provides valuable insights for policymakers and stakeholders seeking to strengthen climate policies and encourages green innovation in different types of businesses.

Mapping aboveground biomass by integrating geospatial and forest inventory data through a k-nearest neighbor strategy in North Central Mexico

As climate change negotiations progress,monitoring biomass and carbon stocks is becoming an important part of the current forest research.Therefore,national governments are interested in developing forest-monitoring strategies using geospatial technology.Among statistical methods for mapping biomass,there is a nonparametric approach called k-nearest neighbor(kNN).We compared four variations of distance metrics of the kNN for the spatially-explicit estimation of aboveground biomass in a portion of the Mexican north border of the intertropical zone.Satellite derived,climatic,and topographic predictor variables were combined with the Mexican National Forest Inventory(NFI)data to accomplish the purpose.Performance of distance metrics applied into the kNN algorithm was evaluated using a cross validation leave-one-out technique.The results indicate that the Most Similar Neighbor(MSN)approach maximizes the correlation between predictor and response variables(r=0.9).Our results are in agreement with those reported in the literature.These findings confirm the predictive potential of the MSN approach for mapping forest variables at pixel level under the policy of Reducing Emission from Deforestation and Forest Degradation(REDD+).

Investigating the role of emissions trading policy to reduce emissions and improve the efficiency of industrial green innovation

Rapid economic development usually leads to serious environmental pollution problems.In order to solve the problem of pollutant emission in sustainable industrial development,it is urgent to examine the implementation effect of emissions trading policy(ETP)and its impact on green industrial development.This study adopts China's ETP as a case study and selects provincial panel data from 2004 to 2018.We first use a non-radial,non-directed,slack-based measure-directional distance function(SBM-DDF)to measure industrial green innovation efficiency.Then we use a difference in differences(DID)model to empirically test the emissions reduction effect of China's policy and whether it promotes industrial green innovation.Thereafter,results show that:(1)the ETP reduces sulfur dioxide(SO2)emissions indicating the effectiveness of the policy;(2)the policy significantly improves industrial green innovation efficiency,meaning it promotes the sustainable development of the economy;(3)heterogeneity analysis highlights that ETP produces greater benefits for the most polluted regions of China which have more strict environmental regulations.The study examines the effect of emissions trading policy implementation from a new perspective.The study also provides a reference point for China to further refine its policy mechanisms and for other countries to formulate suitable ETP.

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.

Factors influencing polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran (PCDD/F) emissions and control in major industrial sectors: Case evidence from Shandong Province, China

Analyzing determinants that influence polychlorinated dibenzo-p-dioxin and polychlorinated dibenzofuran（PCDD/F） emissions is helpful for decision-makers to find effective and efficient ways to mitigate PCDD/F emissions. The PCDD/F emissions and the contributions of the scale effect, structure effect and technology effect to emissions from eight main industrial sectors in2006, 2008 and 2010 in Shandong Province, were calculated in this article. Total PCDD/F emissions in Shandong increased by 52.8% in 2008（614.1 g I-TEQ） and 49.7% in 2010（601.8 g I-TEQ） based on 2006（401.9 g I-TEQ）. According to the decomposition method, the largest influencing factor on PCDD/F emission changes was the composition effect（contributed 43.4%in 2008 and 120.6% in 2010 based on 2006）, which was also an emission-increasing factor.In this case, the present industrial restructuring policy should be adjusted to control the proportion of production capacities with high emission factors, such as iron ore sintering and steelmaking and the secondary non-ferrous metal sector. The scale effect increased the emissions in 2008（contributed 21.9%） and decreased the emissions in 2010（contributed-28.0%）. However, as a source control measure, the excess capacity control policy indeed had a significant role in emission reduction. The main reason for the technology effect（contributed 34.7% in 2008 and 7.4% in 2010 based on 2006） having an emission-increasing role was the weakness in implementing policies for restricting industries with outdated facilities. Some specific suggestions were proposed on PCDD/F reduction for local administrators at the end.

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.