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27 results for “North China Plain”
NAQPMS simulation results for analysis the effects of regional transport on haze in the North China Plain
<p>This directory contains data generated and used for paper "Effects of regional transport on haze in the North China Plain: transport of precursors or secondary inorganic aerosols".</p> <p>This dataset contains the observed and simulated aerosols components of Beijing and surrounding cities; regional sources of secondary inrganic aerosols in Beijing; sources of secondary inorganic aerosols under relative clean and polluted conditions; and average differences of regional contribution to secondary inorganic aerosols between clean and polluted conditions; and data for supporting figures.</p>
A 500m-Resolution Agricultural Drought Area Dataset for the period 2006–2019 in the North China Plain
<p>Agricultural drought has caused huge loss in crop production in the recent decades and will continue to occur with increased frequency and severity in the upcoming future period. However, lack of reliable historic agricultural drought information at finer spatiotemporal resolutions constrains the effective formulation strategy for prevention and mitigation of agricultural drought, especially for monitoring and early/warming. Hence, we generated a 500 m-resolution agricultural drought area dataset with three degrees (drought covered, drought damaged, and crop failure) for summer-harvest crops and autumn-harvest crops encompassing the whole NCP.</p>
Dataset for ozone imacts on NPP in the North China Plain
<p>Ozone pollution led to an average 25% decrease in NPP in the North China Plain (NCP). This decline is consistent with previous estimates that ranged from 10% to 25%. Productivity of forest trees, crops, and grasses declined significantly, ranging from 36.7% to 47.1%. These results have implications for Chinese crops, as lower crop productivity can negatively affect crop yields. Our study highlights the urgent need for action to mitigate the detrimental effects of ozone pollution on ecosystem health and productivity.</p>
Dataset for ozone imacts on NPP in the North China Plain
<p>Ozone pollution led to an average 25% decrease in NPP in the North China Plain (NCP). This decline is consistent with previous estimates that ranged from 10% to 25%. Productivity of forest trees, crops, and grasses declined significantly, ranging from 36.7% to 47.1%. These results have implications for Chinese crops, as lower crop productivity can negatively affect crop yields. Our study highlights the urgent need for action to mitigate the detrimental effects of ozone pollution on ecosystem health and productivity.</p>
Wintertime new particle formation in the rural area of North China Plain: influencing factors and possible formation mechanism
<p><strong>data for <em>Wintertime new particle formation in the rural area of North China Plain: influencing factors and possible formation mechanism</em></strong></p>
GPS and hydraulic head measurement utilized in North China Plain research
<p>This dataset contains the raw data of the GPS and hydraulic head measurement <br> utilized in North China Plain research.</p> <p>## Included files</p> <p>The `gps_cmonoc.dat` file contains the horizontal and vertical velocities of <br> the 35 continuous GPS stations from the Crustal Movement Observation Network of <br> China (CMONOC) project.</p> <p>The `gps_bjcors.dat` file contains the horizontal and vertical velocities of <br> the 14 continuous GPS stations from the Beijing Continuously Operating Reference <br> Station (BJCORS) network.</p> <p>The `gps_campaign.dat` file contains the horizontal and vertical velocities of <br> the 432 campaign GPS stations from the Crustal Movement Observation Network of <br> China (CMONOC) project.</p> <p>The `hydraulic_datacenter.xlsx` file contains the 559 measurements from confined <br> well accessed from the National Earth System Science Data Center, National Science <br> & Technology Infrastructure of China (http://www.geodata.cn), recording during 2005-2018.</p> <p>The `hydraulic_yearbook.xlsx` file contains the 130 measurements from both confined<br> and unconfined well compiled from the yearbook 'the China Groundwater Level Yearbook <br> for Geo-environmental Monitoring', recoding during 2005-2016.</p>
A 500m-Resolution Dataset of Agricultural Drought Areas in the North China Plain During 2006–2019
<p>Agricultural drought stands as a dominant natural hazard in the North China Plain, showing increasing frequency and severity over recent decades. However, limitations posed by the coarser spatiotemporal resolution of accessible agricultural drought data archives impede the practical application of regional-scale agricultural drought simulation and monitoring studies. Hence, we generated a 500 m-resolution agricultural drought areas dataset of summer-harvest crops and autumn-harvest crops spanning across the North China Plain (NCP) from 2006 to 2019, encompassing three degrees of agricultural drought area: drought-covered area, drought-damaged area, and crop failure area. The generated dataset holds the potential for effective application in generating synthetic regional drought information, support impact-based agricultural drought monitoring and prediction, and subsequently could greatly assist in optimizing agricultural water management and ensuring global food security.</p>
The mean annual groundwater-level trends observed by 452 monitoring wells in the North China Plain during 2003-2016
<p>The mean annual groundwater-level (GWL) trends observed by 452 monitoring wells (341 unconfined and 111 confined) in the North China Plain (NCP) during 2003-2016. The monthly GWL data were obtained from the Chinese groundwater management authority and the groundwater yearbooks. The wells were relatively evenly distributed in NCP region and each well follows a quality control with at least 60% of temporal coverage of the study period having GWL data records.</p>
The groundwater-level anomalies observed by 446 monitoring wells in the North China Plain during 2003-2017
<p>The groundwater level anomalies observed by 446 monitoring wells in the North China Plain (NCP) during 2003-2017. The monthly GWL data were obtained from the Ministry of Water Resources of China and the groundwater yearbooks. The wells were relatively evenly distributed in NCP region . The GWL anomalies were calculated by subtracting the mean GWL values during 2003-2017 from the monthly time series values of each well. Unit: meter</p>
Data for "North China Plain as a hot spot of ozone pollution exacerbated by extreme high temperature"
<p>Data for "North China Plain as a hot spot of ozone pollution exacerbated by extreme high temperature"</p>
Process-level quantification on opposite PM2.5 changes during COVID-19 lockdown over North China Plain
<p>Observations and WRF-Chem simulation results for manuscript (Process-level quantification on opposite PM<sub>2.5</sub> changes during COVID-19 lockdown over North China Plain) submitted to GRL</p>
A Daily High-Resolution (1 km) Human Thermal Index Collection over the North China Plain from 2003 to 2020
<p>The daily <strong>Hi</strong>gh spatial resolution human <strong>T</strong>hermal <strong>I</strong>ndex <strong>C</strong>ollection over the <strong>North China Plain </strong>(<strong>HiTIC-NCP</strong>) includes <em><strong>near-surface air temperature</strong></em><strong> </strong>(SAT) and 11 commonly used<strong> </strong><em><strong>human-perceived temperature</strong></em><strong> </strong>indices: indoor Apparent Temperature (AT<sub>in</sub>), outdoor shaded Apparent Temperature (AT<sub>out</sub>), Discomfort Index (DI), Effective Temperature (ET), Heat Index (HI), Humidex (HMI), Modified Discomfort Index (MDI), Net Effective Temperature (NET), Wet-Bulb Temperature (WBT), simplified Wet-Bulb Globe Temperature (sWBGT), and Wind Chill Temperature (WCT). This daily dataset has a high spatial resolution of 1 km × 1 km and covers the North China Plain<strong> </strong>from January 2003 to December 2020. It has high accuracy with averaged determination coefficient, mean absolute error, and root mean squared error of 0.987, 0.970 °C, and 1.292 °C, respectively. The dataset is stacked by year and each stack consists of 365 daily images in NetCDF format by day of the year. The unit of the dataset is 0.01 degree Celsius (°C), and the values are stored in an integer type (Int16) to save storage space, and thus need to be divided by 100 to get the values in degree Celcius when in use. The geographic coordinate system of the dataset is World Geodetic System (WGS) 1984 Coordinate System. Naming rules and other details can be found in "README.pdf".</p> <p>If you have any questions when using the HiTIC-NCP dataset, please feel free to contact Mr. Xiang Li via <a href="mailto:lixiang97@mail2.sysu.edu.cn">lixiang97@mail2.sysu.edu.cn</a>, Dr. Ming Luo via <a href="mailto:luom38@mail.sysu.edu.cn">luom38@mail.sysu.edu.cn</a>, or Dr. Yongquan Zhao via <a href="mailto:zhaoyq66@mail.sysu.edu.cn">yqzhao@link.cuhk.edu.hk</a>. More details on the procedure of producing the HiTIC-NCP dataset and its accuracy assessment can be found in:</p> <p>Li, X., Luo, M*., Zhao, Y*., Zhang, H., Ge, E., Huang, Z., Wu, S., Wang, P., Wang X., Tang Y. (2023). A daily high-resolution (1 km) human thermal index collection over the North China Plain from 2003 to 2020. <em>Scientific Data</em>, 10, 634. https://doi.org/10.1038/s41597-023-02535-y</p>
Measurement Report: Exchange Fluxes of HONO over Agricultural Fields in the North China Plain
<p>Raw data for Song et al. submitted to ACP.</p>
Secondary formation of aerosols under typical high-humidity conditions in wintertime Sichuan Basin, China: A contrast to the North China Plain
<p>The Sichuan Basin is one of the regions suffering from severe haze pollution in southwest China. However, the secondary aerosol formation in this region is poorly understood. In this study, the chemical compositions of PM<sub>2.5</sub> and molecular compositions of water-soluble organics in wintertime Sichuan were measured to investigate the aerosol sources and formation under typical high relative humidity (RH) conditions. Strong correlations between PM<sub>2.5</sub>, carbonaceous aerosols and K<sup>+</sup> suggested obvious influence of biomass burning. The impacts of biomass burning were also supported by the dominance of primarily emitted reduced/less oxidized nitrogen-containing organics as well as the high peak intensities of secondarily formed nitrocatechols and methyl-nitrocatechols. High humidity (average RH=80%) and aerosol liquid water (ALW) in Sichuan obviously facilitated the secondary formation of sulfate, nitrate and secondary organic aerosols (SOA). The average sulfate oxidation ratio and nitrogen oxidation ratio in Sichuan were 2.5 and 3.1 times of those in winter Beijing (average RH= 27%). This suggested higher potentials of SO<sub>2</sub> and NO<sub>x</sub> to form sulfate and nitrate under high-RH conditions.<sub> </sub>The abundant aqueous-SOA formation in Sichuan was supported by the dominance of organosulfates (OSs) and nitrooxy-OSs in mass spectra of water-soluble organics, while the OSs in winter Beijing were quite limited. The more abundant OS formation in Sichuan was attributed to the much higher RH, ALW, aerosol acidity and sulfate, which favored the acidic sulfate-catalyzed aqueous-phase reactions for OS formation. Higher concentrations of biogenic volatile organic compounds were additional reasons for the more abundant OSs in Sichuan than in Beijing.</p>
Subspecies and Distribution. M. n. nivalis Linnaeus, 1766 — China, North and South Korea, Mongolia, Russia, Taiwan, and Scandinavia. M. n. allegheniensis Rhoads, 1900 — NE USA (Allegheny Mts W to Wisconsin). M. n. boccamela Bechstein, 1800 — Corsica, Italy, Portugal, Sardinia, Sicily, and Spain. M. n. campestris Jackson, 1913 — C Great Plains, USA. M. n. eskimo Stone, 1900 — Alaska and NW Canada (Yukon). M. n. namiyer Kuroda, 1921 — Japan and the Kurile Is. M. n. numidica Pucheran, 1855 — N Africa. M. n. rnixosa Bangs, 1896 — Canada and N Great Plains of USA. M. n. vulgaris Erxleben, 1777 = W & C Europe and most of C Eurasia. Introduced to New Zealand, Malta, Crete, the Azores Is, and apparently also Sao Tome I. in Mustelidae
Subspecies and Distribution. M. n. nivalis Linnaeus, 1766 — China, North and South Korea, Mongolia, Russia, Taiwan, and Scandinavia. M. n. allegheniensis Rhoads, 1900 — NE USA (Allegheny Mts W to Wisconsin). M. n. boccamela Bechstein, 1800 — Corsica, Italy, Portugal, Sardinia, Sicily, and Spain. M. n. campestris Jackson, 1913 — C Great Plains, USA. M. n. eskimo Stone, 1900 — Alaska and NW Canada (Yukon). M. n. namiyer Kuroda, 1921 — Japan and the Kurile Is. M. n. numidica Pucheran, 1855 — N Africa. M. n. rnixosa Bangs, 1896 — Canada and N Great Plains of USA. M. n. vulgaris Erxleben, 1777 = W & C Europe and most of C Eurasia. Introduced to New Zealand, Malta, Crete, the Azores Is, and apparently also Sao Tome I.
Data for "On the difference of aerosol hygroscopicity between high and low RH conditions in the North China Plain"
<p>Data for "Measurement Report: On the difference of aerosol hygroscopicity between high and low RH conditions in the North China PlainMeasurement Report: On the difference of aerosol hygroscopicity between high and low RH conditions in the North China Plain"</p>
Source Parameters and Ground Motion Simulation of the 2023 MW 5.5 Pingyuan Earthquake in the North China Plain
<p>Broadband seismic waveform data used for determining the focal mechanism and depth of the 2023 <em>M</em><sub>W</sub> 5.5 Pingyuan earthquake</p>
Data associated with the manuscript"Improvement of Stable Atmospheric Boundary Simulation with High-Spatiotemporal-Resolution Nudging over the North China Plain"
<p>The data includes sounding data and ground observation data, mainly used for reconstructing vertical high-resolution nudge modules</p>
Data from: Spatial variation of soil respiration in a cropland under winter wheat and summer maize rotation in the North China Plain
Spatial variation of soil respiration (Rs) in cropland ecosystems must be assessed to evaluate the global terrestrial carbon budget. This study aims to explore the spatial characteristics and controlling factors of Rs in a cropland under winter wheat and summer maize rotation in the North China Plain. We collected Rs data from 23 sample plots in the cropland. At the late jointing stage, the daily mean Rs of summer maize (4.74 μmol CO2 m-2 s-1) was significantly higher than that of winter wheat (3.77μmol CO2 m-2 s-1). However, the spatial variation of Rs in summer maize (coefficient of variation, CV = 12.2%) was lower than that in winter wheat (CV = 18.5%). A similar trend in CV was also observed for environmental factors but not for biotic factors, such as leaf area index, aboveground biomass, and canopy chlorophyll content. Pearson's correlation analyses based on the sampling data revealed that the spatial variation of Rs was poorly explained by the spatial variations of biotic factors, environmental factors, or soil properties alone for winter wheat and summer maize. The similarly non-significant relationship was observed between Rs and the enhanced vegetation index (EVI), which was used as surrogate for plant photosynthesis. EVI was better correlated with field-measured leaf area index than the normalized difference vegetation index and red edge chlorophyll index. All the data from the 23 sample plots were categorized into three clusters based on the cluster analysis of soil carbon/nitrogen and soil organic carbon content. An apparent improvement was observed in the relationship between Rs and EVI in each cluster for both winter wheat and summer maize. The spatial variation of Rs in the cropland under winter wheat and summer maize rotation could be attributed to the differences in spatial variations of soil properties and biotic factors. The results indicate that applying cluster analysis to minimize differences in soil properties among different clusters can improve the role of remote sensing data as a proxy of plant photosynthesis in semi-empirical Rs models and benefit the acquisition of Rs in cropland ecosystems at large scales.
Low hygroscopicity of newly-formed particles on the North China Plain and its implications for nanoparticle growth
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