Understanding air pollution reduction from the perspective of synergy with carbon mitigation in China from 2008 to 2017.

In response to the dual challenges of air pollution control and carbon mitigation, China has strategically shifted its focus towards the synergistic reduction of air pollutants and CO emissions. This study identifies the potential areas and specific air pollutant species (including CO, NO, and SO) for co-reduction with carbon mitigation. We also reveal the driving forces behind the emissions of each air pollutant at both the national and regional scales.

Assessing Spatial Representativeness of Global Flux Tower Eddy-Covariance Measurements Using Data from FLUXNET2015.

Large datasets of carbon dioxide, energy, and water fluxes were measured with the eddy-covariance (EC) technique, such as FLUXNET2015. These datasets are widely used to validate remote-sensing products and benchmark models. One of the major challenges in utilizing EC-flux data is determining the spatial extent to which measurements taken at individual EC towers reflect model-grid or remote sensing pixels.

Applications of land surface model to economic and environmental-friendly optimization of nitrogen fertilization and irrigation.

Land surface models (LSMs) have prominent advantages for exploring the best agricultural practices in terms of both economic and environmental benefits with regard to different climate scenarios. However, their applications to optimizing fertilization and irrigation have not been well discussed because of their relatively underdeveloped crop modules. We used a CLM5-Crop LSM to optimize fertilization and irrigation schedules that follow actual agricultural practices for the cultivation of maize and wheat, as well as to explore the most economic and environmental-friendly inputs of nitrogen fertilizer and irrigation (FI), in the North China Plain (NCP), which is a typical intensive farming area.

A meta-analysis highlights globally widespread potassium limitation in terrestrial ecosystems.

Potassium (K ) is the most abundant inorganic cation in plant cells, playing a critical role in various plant functions. However, the impacts of K on natural terrestrial ecosystems have been less studied compared with nitrogen (N) and phosphorus (P). Here, we present a global meta-analysis aimed at quantifying the response of aboveground production to K addition.

High ambient temperatures are associated with urban crime risk in Chicago.

Urban crime (UC) seriously affects the security and stability of the communities and society. However, the effects of external temperatures on the risk of UC are still confusing. We quantitatively estimated the effects of high and low temperatures on UC in Chicago.

Ambient temperatures associated with increased risk of motor vehicle crashes in New York and Chicago.

Motor Vehicle Crashes (MVC) are a major cause of death and disability worldwide. Yet it remains unknown to what extent changes in cold and hot temperatures affect the MVC. Here we quantify the linkage between ambient temperature exposure and the MVC risk of the driver in four cities of the United States.

Spatially explicit and multiscale ecosystem shift probabilities and risk severity assessments in the greater Mekong subregion over three decades.

Ecosystem functioning and related risks could become compromised by climate change and severely affect livestock in different ways. Based on four climate indices (i.e.

Global Revisit Interval Analysis of Landsat-8 -9 and Sentinel-2A -2B Data for Terrestrial Monitoring.

The combination of Landsat-8, Landsat-9, Sentinel-2A and Sentinel-2B data provides a new perspective in remote sensing application for terrestrial monitoring. Jointly, these four sensors together offer global 10-30-m multi-spectral data coverage at a higher temporal revisit frequency. In this study, combinations of four sensors were used to examine the revisit interval by modelled orbit swath information.

A new approach combining a simplified FLEXPART model and a Bayesian-RAT method for forecasting PM and PM.

In this study, we evaluated atmospheric particulate matter (PM) concentration predictions at a regional scale using a simplified Lagrangian particle dispersion modeling system and the Bayesian and multiplicative ratio correction optimization (Bayesian-RAT) method to improve the mixing ratio forecast of PM and PM. We first examined the forecast performance of the LPD (i.e.

A regional data assimilation system for estimating CO surface flux from atmospheric mixing ratio observations-a case study of Xuzhou, China.

Carbon monoxide (CO) emission inventory data are crucial for air quality control. However, the emission inventories are labor-intensive and time-consuming and generally have large uncertainties. In this study, we developed a new regional data assimilation system (TracersTracker) for estimating the surface CO emission flux from continuous mixing ratio observations using the proper orthogonal decomposition (POD)-based four-dimensional variational (4D-VAR) data assimilation method (POD-4DVar) and a coupled regional model (Weather Research and Forecasting model (WRF) with the Models-3 Community Multi-scale Air Quality (CMAQ) model).

Assessing the Spatiotemporal Variation and Impact Factors of Net Primary Productivity in China.

In this study, the net primary productivity (NPP) in China from 2001 to 2012 was estimated based on the Carnegie-Ames-Stanford Approach (CASA) model using Moderate Resolution Imaging Spectroradiometer (MODIS) and meteorological datasets, and the accuracy was verified by a ChinaFLUX dataset. It was found that the spatiotemporal variations in NPP present a downward trend with the increase of latitude and longitude. Moreover, the influence of climate change on the evolution of NPP shows that NPP has had different impact factors in different regions and periods over the 12 years.

A comprehensive estimate of recent carbon sinks in China using both top-down and bottom-up approaches.

Atmospheric inversions use measurements of atmospheric CO2 gradients to constrain regional surface fluxes. Current inversions indicate a net terrestrial CO2 sink in China between 0.16 and 0.

[Review of dynamic global vegetation models (DGVMs)].

Dynamic global vegetation model (DGVM) is an important and efficient tool for study on the terrestrial carbon circle processes and vegetation dynamics. This paper reviewed the development history of DGVMs, introduced the basic structure of DGVMs, and the outlines of several world-widely used DGVMs, including CLM-DGVM, LPJ, IBIS and SEIB. The shortages of the description of dynamic vegetation mechanisms in the current DGVMs were proposed, including plant functional types (PFT) scheme, vegetation competition, disturbance, and phenology.

Understanding of coupled terrestrial carbon, nitrogen and water dynamics-an overview.

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.

Diurnal, seasonal and interannual variability of carbon isotope discrimination at the canopy level in response to environmental factors in a boreal forest ecosystem.

Accurate estimation of temporal and spatial variations in photosynthetic discrimination of 13C is critical to carbon cycle research. In this study, a combined ecosystem-boundary layer isotope model, which was satisfactorily validated against intensive campaign data, was used to explore the temporal variability of carbon discrimination in response to environmental driving factors in a boreal ecosystem in the vicinity of Fraserdale Tower, Ontario, Canada (49 degrees 52'30''N, 81 degrees 34'12''W). A 14 year (1990-1996 and 1998-2004) hourly CO2 concentration and meteorological record measured on this tower was used for this purpose.