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The dew condensation frequency is high, and the dew amount is heavy in urban ecosystems. During the condensation process, particulate matter acts as a condensation core, playing an important role in purifying the air. At night, dew mainly condenses on plant leaf surfaces, the plant leaves settle the particles in the dew, and some of the particles are resuspended into the atmosphere in the process of dew evaporation after sunrise. This paper monitored the condensation and evaporation processes of dew on four common plants in Changchun city from June to September 2020. By analyzing the mass and size of particles on different leaves after dew condensation and evaporation, the ability of different plants to retain particles in dew was analyzed. The results showed that there was no significant difference in the TSP capture ability during dew condensation between Buxus sinica (Rehd. et Wils.) Cheng subsp. sinica var. parvifolia M. Cheng, Syringa oblata Lindl., Hemiptelea davidii (Hance) Planch., and Pinus tabuliformis Carrière, with a TSP content of 0.21 ± 0.06 μg/cm2. Coarse particulate matter is the main type of deposit in the dew condensation stage. Particulate deposition varied according to species, leaf shape, and microstructure. The proportion of TSP remaining on leaves after dew evaporation from Pinus tabuliformis Carrière, Hemiptelea davidii (Hance) Planch., Buxus sinica (Rehd. et Wils.) Cheng subsp. sinica var. parvifolia M. Cheng, and Syringa oblata Lindl. tree was 89.7 ± 3.9%, 80.6 ± 3.6%, 75.9 ± 4.5%, and 71.4 ± 3.7%, respectively. The ability of the leaves to trap fine particles was significantly higher than that for coarse particles (P < 0.05) after dew evaporation. The highest amount of particle captured by Syringa oblata Lindl. individual was 15.17 g/y during dew condensation, and the amount of remaining particles after dew evaporation was 10.83 g/y. This paper provides a theoretical basis for the selection of tree species for urban greening. [ABSTRACT FROM AUTHOR]

The rational evaluation of tourism resources and the discovery of valuable potential tourism resources are important foundations for promoting the development of tourism industry. This paper systematically reviews the development history of China's ethnic tourism resource evaluation, analyzes the three different stages of tourism resource evaluation changes and their basic characteristics, and conducts research on tourism resource evaluation based on artificial intelligence neural network model to avoid the influence of subjective factors on the evaluation results to the greatest extent. This paper uses the literature comparison method, theoretical analysis method, and expert consultation method to construct an evaluation index system containing 5 primary indicators and 12 secondary indicators on the basis of which an evaluation model is designed focusing on the error values in the evaluation model, and the evaluation model is applied to the evaluation of tourism resources in several major cities, and its evaluation results and error ranges meet the requirements. [ABSTRACT FROM AUTHOR]

Based on 130 climate signal indexes provided by National Climate Center of China, this paper established a decision tree diagnostic prediction model for Spring Kuroshio Sea Surface Temperature (SST) from 1961 to 2015 (65 years) by using Chi-Squared Automatic Interaction Detector (CHAID) algorithm in data mining and obtained five rule sets to determine whether Spring Kuroshio SST is high or not. Considering the data of the 44 years from 1961 to 2004 as the training set of the model and the other years as the test set, the training accuracy of the model can reach to 95.45% and the test accuracy can reach to 81.82%. Three types of Spring Kuroshio SST are different in intensity and distribution. The results show that the prediction model of Spring Kuroshio SST based on CHAID algorithm has a high prediction accuracy, with the reasonable and effective model and the well-thought-out decision rules. Moreover, based on the results of decision classification, the SST anomalies correspond to different distribution characteristics of summer daily precipitation anomalies in eastern China, which can provide a new idea and method for climate prediction of regional summer precipitation. [ABSTRACT FROM AUTHOR]

Meteorological disasters have brought a great negative impact on people's lives. With the rapid development of modern science and technology, the detection technology of meteorological disasters has been continuously improved. At present, satellite remote sensing detection technology has made gratifying achievements, and it has a good application in meteorological disaster prediction. In this paper, the application of satellite remote sensing technology in the process of meteorological disaster monitoring is discussed in depth. In traditional work, the accuracy and timeliness of meteorological disaster monitoring is the key and difficult point of meteorological disaster prevention. Using satellite telemetry to monitor meteorological disasters can effectively improve the accuracy and timeliness of meteorological disaster monitoring, provide reasonable solutions and decision-making basis for meteorological disaster prevention, and achieve the purpose of disaster prevention and mitigation. This paper introduces the basic principle, technical system, and important role of satellite remote sensing technology, expounds on the application of satellite remote sensing technology in the monitoring of agricultural meteorological disasters such as water, drought, freezing, and hail, and provides a scientific reference for farmers, agricultural sustainability, and agricultural decision-making. The continuous development of our country's modern social economy has put forward higher requirements for agricultural production. Traditional monitoring technology can no longer meet the needs of agricultural meteorological disaster monitoring. The scientific application of remote sensing monitoring technology has important value, which can effectively improve the detection level and make it have higher accuracy and real-time performance, thereby promoting modern agricultural production in China. Based on the analysis of the application value of remote sensing monitoring technology, this paper comprehensively discusses the specific conditions of different disasters monitored by remote sensing monitoring technology in agricultural production. [ABSTRACT FROM AUTHOR]

The higher contribution of traffic delay to environmental impacts is urging the highway agencies to take work zone management into the maintenance schemes decision-making. Aiming to understand the role of work zone management in user CO2 emissions reduction, this paper firstly developed a practical methodological framework of traffic delay-related CO2 emissions caused by highway maintenance based on a popular life cycle user cost analysis approach in regard of the microscopic vehicle operation analysis. The method was applied in an actual freeway flexible pavement with 15-year design life in Shaanxi Province, China, covering three types of preventive maintenance, correction maintenance, and rehabilitation. In addition, the impacts of key inputs of proposed method on work zone user CO2 emissions results were checked. The results show that traffic delay attributes to 29.4% of total CO2 emissions of the life cycle of highway pavement maintenance, and 51.8% of work zone user CO2 emissions result from preventive maintenance, especially from micro vehicle operations including speed change and queue near work zone (62% of total work zone user CO2 emissions). The work zone management alternative strategies related to less traffic volume or higher highway capacity including vehicle type limitation and the limited work zone speed have an advantage in reducing the work zone CO2 emissions over changing work zone length or work zone timing. The findings in this paper may present a useful tool and reference for robustly supporting the decision-making on highway maintenance carbon mitigation in work zone traffic. [ABSTRACT FROM AUTHOR]

Sichuan is a high-incidence area of thunderstorm activity in China. Based on the data of the total lightning location system from 2018 to 2022, the total lightning, cloud-to-ground (CG) lightning, and intracloud (IC) lightning activity regularity for the Sichuan province (SC) and its three climate subregions: Sichuan Basin (SB), Panxi district (PD), and West Sichuan Plateau (WSP) are analyzed, and the influences of different climate and topography conditions on lightning activities are also discussed. The results show that (1) for the whole province, the annual mean value of total lightning is about 850 thousand. The SB has the most lightning occurrences, and the WSP has the largest IC and +CG proportion. The southwest of PD, the north-center of PD, and the southeast of SB are the three high-value centers of lightning density. (2) For SB, the better thermodynamic and moisture conditions account for the most lightning occurrences. For PD, the lightning distribution is attributed to the joint effect of specific meteorological conditions and mountainous topography. For WSP, the convections are weak and shallow, which lead to high IC and +CG proportion. (3) The IC lightning mainly occurs below 12 km, and the IC height is much lower on WSP. The spatial and seasonal variation of IC height corresponds well to the cloud base height (CBH) and cloud top height (CTH). (4) The seasonal lightning frequency distribution in the three regions is similar, but the diurnal variation is quite different. The lightning activity mainly occurs between 1400 and 2200 LT on WSP but shows obvious nocturnal in SB. (5) Most CG intensity concentrates in the range below 50 kA, and IC concentrates in the range below 75 kA. [ABSTRACT FROM AUTHOR]

This study performed an observational analysis to examine the interdecadal variation in the frequency of extreme high-temperature events (EHEs) during spring over the western Tianshan mountain, China, which were characterized by relatively fewer (more) EHEs during 1983–1996 (2000–2015). A composite analysis indicated that the interdecadal increase in EHEs is closely related to a deep dynamic anomalous Iranian high. Under the control of this high system, the water vapor content decreased over the western Tianshan mountains, and atmospheric circulation was dominated by a descending motion. Both were attributed to the decreased cloud cover, inducing a cloud-forced net solar radiation increase. The short-wave radiation flux and sensible heat flux reaching the surface increased, and the net surface heat flux increased cumulatively, which was conducive to the surface temperature increase and EHE occurrence. The anomalous Iranian high responsible for ECEs occurrence was related to the air-sea interaction over the Atlantic and Indo-Pacific. The latitudinal sea surface temperature (SST) difference between the tropical western Pacific and the western Indian Ocean directly strengthens the Walker circulation and thus enhances the Iranian high. In addition, the anomalous Iranian high was affected by the atmospheric wave trains at middle latitude, which was triggered by the warm anomaly of the Atlantic SST. [ABSTRACT FROM AUTHOR]

Climate reanalysis products have been widely used to overcome the absence of high-quality and long-term observational records for wind energy users. In this study, the applicability of two popular reanalysis datasets (ERA5 and MERRA2) in estimating wind characteristics for four tall tower observatories (TTOs) in South China was assessed. For each TTO, linear and nonlinear downscaling techniques, namely, multiple linear regression (MLR) and an artificial neural network (ANN), respectively, were adopted for the downscaling of the scalar wind speed and the corresponding U/V components. The downscaled wind speed and U/V components were subsequently compared with the TTO observations by correlation coefficient (Pearson's r), the root mean square error (RMSE), the uncertainty analysis (U95), and the reliability analysis (RE). According to the results, ERA5 had a better applicability (higher Pearson's r and RE, but lower RMSE and U95) in estimating TTO wind speed than MERRA2 when using both the MLR and ANN downscaling method. The average Pearson's r, RE, RMSE, and U95 of the downscaled wind from ERA5 by the MLR (ANN) method were 0.66 (0.69), 40.8% (41.8%), 2.20 m/s (2.11 m/s), 0.181 m/s (0.179 m/s), respectively, and 0.60 (0.63), 38.0% (39.7%), 2.32 m/s (2.25 m/s), 0.189 m/s (0.187 m/s), respectively, for MERRA2. The wind components analysis showed that the better performance of ERA5 was attributed to its smaller error in estimating V component than MERRA2. For the wind direction, the two reanalysis datasets did not display distinct differences. Additionally, the misalignment of the wind direction between the reanalysis products and the TTOs was higher for the secondary predominant wind direction (SPWD) than for the predominant wind direction (PWD). Furthermore, we found that the reanalysis U wind had a higher RMSE but a lower RE and Pearson's r than the V wind, which indicates that the misalignment in the wind direction was mainly associated with the deviation in the U component. [ABSTRACT FROM AUTHOR]

As a regulator of ecological environment, Baiyangdian Wetland is in a pivotal position in constructing the blue-green space (BGS) of Xiong'an New Area in China. This study aims to reveal the spatiotemporal changes of the BGS in Baiyangdian Wetland from 2016 to 2021. It uses Google Earth Engine (GEE) to calculate NDVI and NDWI based on Sentinel-2 Satellite remote sensing data and extracts the blue-green space by a classification model driven by NDVI and NDWI. Moreover, the land-use transfer matrix and landscape pattern indices are applied for evaluating the BGS changes in the wetland. According to the results, vegetation in the wetland shows no obvious spatial transfer. From 2016 to 2020, the BGS proportion in the wetland showed a stable increase, with the blue space getting larger by 10.8%. The indicators of the Number of Patches (NP), Patch Density (PD), Largest Patch Index (LPI), Contagion, and Landscape Shape Index (LSI) of the wetland decreased, suggesting a better ecological environment since the establishment of Xiong'an New Area in 2017. Based on the results, the author makes the following conclusion: the construction of BGS in Baiyangdian Wetland results in a well-organized ecological environment. The study provides a reference for building Xiong'an New Area and monitoring BGS changes in other regions. [ABSTRACT FROM AUTHOR]

Air temperature (Ta) is an essential parameter for science research and engineering practice. While the traditional site-based approach is only able to obtain observations in limited and discrete locations, satellite remote sensing is promising to retrieve some environmental variables with spatially continuous coverage. Nowadays, land surface temperature (Ts) measurements can be obtained from some satellite sensors (e.g., MODIS), further enabling us to estimate Ta in view of the relationship between Ta and Ts. In this article, we proposed a two-phase integrated framework to estimate daily mean Ta nationwide. In the first phase, multivariate linear regression models were fitted between site-based observations of daily mean air temperature (Ta-mean) and MODIS land surface temperature products (including Terra day: TMOD-day, Terra night: TMOD-night, Aqua day: TMYD-day, and Aqua night: TMYD-night) conditional on some covariates of environmental factors. The fitted models were then used to predict Ta-mean from those covariates at unobserved locations. The predicted Ta-mean were looked on as stochastic variables, and their distributions were also obtained. In the second phase, Bayesian maximum entropy (BME) methods were used to produce spatially continuous maps of Ta-mean taking the meteorological station observations as hard data and the predicted Ta-mean in the first phase as soft data. It is shown that the proposed approach is promising to improve the interpolation accuracy significantly, comprehensively considering the prior knowledge and the context of space variability and correlation, which will enable it to compile spatially continuous air temperature products with higher accuracy. [ABSTRACT FROM AUTHOR]

The Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) V06 product has been widely studied, but the errors and the source of the errors within IMERG over diverse climate regions still need to be quantified. To this end, the final run gauge-calibrated IMERG V06 (V06C) and uncalibrated IMERG V06 (V06UC) products are comprehensively evaluated here against 2088 precipitation gauges acquired between March 2014 and June 2018 over China. Moreover, V06C and V06UC rainfall estimates are compared against the Precipitation Estimation from Remotely Sensed Imagery using Artificial Neural Networks (PERSIANN)-Climate Data Record (CDR) and the Climate Prediction Center morphing technique (CMORPH) gauge-satellite blended (BLD) products. Continuous statistical indices and two error decomposition schemes are used to quantify their performance. Key results are as follows. (1) Except for V06UC's relatively high underestimation over the Tibetan Plateau (TP) and high overestimation over Xinjiang (XJ), Northeastern China (DB), and Northern China (HB) and CDR's severe overestimation over TP, all four satellite-based precipitation products can generally capture the spatial pattern of precipitation over China. Moreover, the satellite-based precipitation estimates agree better with gauge observations over humid regions than over semi-humid, semi-arid, and arid regions. (2) All the statistical indicators show that CDR has the worst performance, whereas BLD is the best precipitation product. As for the two IMERG products, V06C has improved V06UC's precipitation estimate. Results show that the gauge calibration algorithm (GCA) used in IMERG has active effect in terms of r, POD, and CSI. (3) Within all subregions, all four satellite-based precipitation products demonstrate their worst performance over the arid XJ region which exhibits the highest FAR and lowest POD and CSI values among all regions. (4) In terms of intensity distribution, for summer over China, the four satellite-based precipitation products generally overestimate the frequency of moderate precipitation and light precipitation events (<25 mm/day) and underestimate heavy precipitation events (>42 mm/day). (5) The relative bias ratio (RBR) analysis shows that the contribution of missed precipitation tends to be lower over wetter regions. In addition, for the same climate region, the contribution of missed precipitation is clearly lower in summer than in winter. In summer, false precipitation dominates the total error, whereas missed and false precipitation are the two leading error sources in winter. Future algorithm refinement efforts should focus on decreasing FAR in summer and winter and improving missed snow events during the winter. [ABSTRACT FROM AUTHOR]

Heavy pollution in North China has attracted extensive attention in recent decades, and numerous studies have been conducted in developed regions, while studies on the heavily polluted Fenwei Plain in Northwest China are still scarce. In this study, we analyzed the continuous air pollution records of Weinan city on the Fenwei Plain from 2016 to 2020 to provide specific prevention and control strategies for the region. From 2016 to 2020, pollutant concentrations showed an overall decreasing trend, with a slight increase in O3 concentration. The study found that during the COVID-19 lockdown period, O3 was also significantly affected by the lockdown policy. During the prevailing COVID-19 pandemic in 2020, anthropogenic emissions were reduced due to restraints on commercial and social activities. NO2 responds sensitively during COVID-19, and PM2.5 has a delayed response. We applied pathway analysis to investigate the contribution of different pollutants and meteorology to PM2.5. The results show that CO and NO2 have the largest positive comprehensive effect, while wind speed and temperature have the largest negative comprehensive effect. Spearman's correlation analysis shows that NO2 contributes significantly to O3 production in different AQI ranges. We advocate that the NOx should be given more attention and become the new focus of air control. [ABSTRACT FROM AUTHOR]

The possible sources of forecast errors associated with rainstorms in the South China monsoon region were investigated based on Weather Research and Forecasting (WRF) model forecasts for 19 rainstorm cases that occurred in the past 13 years. Two datasets were separately selected as the initial fields of WRF with the same physical parameterization schemes. By investigating the improvement rate of the forecast when using one set of data rather than the other, the important degree of the initial conditions with respect to the forecasts for each case has been obtained. For those initial errors are the important sources of forecast errors, we further explored the source of the initial errors by comparing the two initial conditions. It was found that, interestingly, the significant differences between two initial conditions are all located upstream the rainfall area, with a distance of 5° of longitude away and an area of about 4° × 4°. Based on this, we developed a new method (which we refer to as the "guide flow method") to identify the sensitive area for rainstorm forecasts in the South China monsoon region and then examined the efficiency of the sensitive areas. It was found that reducing the initial errors in the sensitive areas leads to better forecast results than doing the same in other areas. Thus, the sensitive areas are the source areas of forecast errors for rainstorms in the South China monsoon region. [ABSTRACT FROM AUTHOR]

In order to analyze the primary sources of air pollutants in Chang-Zhu-Tan region, this article selected the environmental monitoring data and meteorological data in the winter of 2019 to calculate the backward airflow trajectories with the Chang-Zhu-Tan region as the starting point by using the backward trajectory model. Combined with the ground concentration monitoring data, cluster analysis, potential source contribution factor (PSCF) analysis, and concentration weighted trajectory (CWT) analysis were carried out to determine the pollutant transportation paths and sources of the potential source area. The results show that air mass transportation mainly comes from three directions: northwest, northeast, and southwest China. The airflow in northwest China moves faster and cleaner, while the airflow from the northeast and southwest moves slowly and carries a high concentration of pollutants. PSCF and CWT analyses show that the critical potential sources are mainly located in this area and some cities next to the study area. This study has important practical significance for the environmental research of Chang-Zhu-Tan region and can provide theoretical reference for regional joint prevention and control of air pollution. [ABSTRACT FROM AUTHOR]

Over nearly three rainy seasons of lightning activity in North China, numerical prediction experiments were carried out using the Weather Research and Forecasting model coupled with electrification and discharge schemes (WRF-Electric). The numerical forecast results were evaluated using the neighborhood-based equitable threat score (ETS) and fraction skill score (FSS) verification methods based on nationwide observational lightning data. An algorithm was used to generate the coverage of the total flash (intracloud and cloud-to-ground flashes) by fitting the cloud-to-ground flash data. The numerical results showed that the region of lightning activity could be well predicted by the mesoscale WRF-Electric model, particularly during a 6–12-hour forecasting period. The average ETS score of the 6–12-hour forecasting period was 0.34 for a 20 km neighborhood radius. The predictive skill of the model varied not only monthly but also diurnally. The model showed better forecasting skills during the main rainy season (June–July–August) and at 14 : 00–20 : 00 local time. The predictability of the model was enhanced with increasing thunderstorm scale. On the other hand, the coverage of predicted lightning activity was relatively concentrated, and the lightning flash density was higher than the observations. The main discrepancies in the model prediction were related to the design of the discharge parameterization. Thus, in discharge parameterization, the initial threshold for lightning should be modified according to the model resolution, while the magnitude of the neutralization charge in a single discharge should be referenced to the observational results. [ABSTRACT FROM AUTHOR]

The emergence of various high-resolution satellite precipitation products (SPPs) solves the problem of precipitation data sources for areas with a lack of precipitation data and is recognized as a reliable supplement to rain gauge observations in hydrometeorological applications. However, there still exists a shortcoming of coarse spatial resolution when applying these products to small and microscale river basins. In this study, a typical karst watershed in Southwest China—the Pingtang River Basin (PTRB)—was selected, and based on the relationship between precipitation and normalized difference vegetation index (NDVI), aspect, slope, and elevation, we used the geographically weighted regression (GWR) to downscale three SPPs, namely, global precipitation measurement (GPM), global satellite mapping of precipitation (GSMAP), and multisource weighted-ensemble precipitation (MSWEP), to 1 km × 1 km, respectively. Combined with rain gauge stations, the geographical differential analysis (GDA) was used to carry out error corrections to obtain three downscaling correction satellite precipitation products (DC-SPPs) with a 1 km spatial resolution, including DC-GPM, DC -GSMAP, and DC-MSWEP. Several statistical indices were used to perform error evaluation and precipitation capture ability analysis on SPPs and DC-SPPs, and the Grid-Xin'anjiang (the Grid-XAJ) model was used to compare their hydrological utility. The results show the following: (1) The downscaling correction method is effective. GWR can effectively improve the spatial resolution of SPPs, while GDA can reduce errors and further improve the accuracy of precipitation estimation. In addition, (2) the precipitation event characterization capabilities of GPM and GSMAP have been improved after downscaling correction, while the ability to capture precipitation events before and after the MSWEP correction is poor, showing a high hit rate and a high false alarm rate, which is unreliable to monitor precipitation events in the PTRB. Finally, (3) compared with SPPs, the hydrological performances of the three kinds of DC-SPPs have been significantly improved, and the NSE are all above 0.75 with low error. In general, the overall performance of DC-GSMAP is satisfactory. The accuracy of different SPPs after downscaling correction is different, but the applicability has been improved to different degrees. [ABSTRACT FROM AUTHOR]

Large-scale flooding causes widespread disaster, and harmful pollutant concentration in water following flood affects public safety and the environment. In this study, a numerical model for solving the 2D shallow water equations and the solute transport equation is proposed to simulate overland flood and pollutant transport caused by floods. The present model is verified by comparing the predictions with the analytical solutions and simulation results; sufficiently high computational accuracy is achieved. The model is also used to simulate flood inundation and pollution spread in the area of Hun and Taizi Lane (HTL) in China due to river dike breaches; the results show that the coupling model has excellent performance for simulating the flooding process and the temporal and spatial distribution of pollutants in urban or rural areas. We use remote sensing techniques to acquire the land coverage in the area of HTL based on Landsat TM satellites. The impacts of changed land use on mitigation of flooding waves and pollutant spread are investigated; the results indicate that the land cover changes have an obvious influence on the evolution process of flood waves and pollutant transport in the study areas, where the transport of pollutants is very dynamic during flood inundation in HTL area. Furthermore, the motion of pollutants considering anisotropic diffusion is more reasonable than that due to isotropic dispersion in simulating pollutant transport associated with the flood in urban or farmland environments. [ABSTRACT FROM AUTHOR]

China's rapid urbanisation and industrialisation have led to frequent haze in China in recent years. Although many measures to control haze have been implemented, no significant improvement has been observed, and haze still exists. In this study, we used wavelet transform to investigate the changes in PM2.5 on the time scale, the relationship amongst meteorological factors, and the causes and changes in haze formation and take measures to prevent haze. Results indicated the following: (1) The peak of PM2.5 changes in winter in the past three years primarily occurred in the range from 11:00 to 13:00 and 20:00 to 22:00. (2) Multiple cycles of daily average PM2.5 concentrations existed in 3–5 d, 6–14 d, 6–21 d, and 16–27 d, with a significant oscillation in 6–14 d and stable cycle characteristics. (3) The meteorological factors promoted the formation of haze to a certain extent. When haze occurred, the near-surface wind speed was only 1 m/s, which was not conducive to the spread of pollutants. (4) The formation of haze was affected by the interaction of various factors; the photochemical reactions of NO2 and O3 also exacerbated the formation of pollutants. This study provided a clear direction for the prevention and prediction of haze. Furthermore, the government must take relevant measures to reduce pollutant emissions and ensure the air quality of cities in winter. [ABSTRACT FROM AUTHOR]