[Energy-saving and Emission Reduction Path for Road Traffic in Key Coastal Cities of Guangdong, Fujian and Zhejiang].

The rapid development of society and economy has resulted in a substantial increase in energy consumption, consequently exacerbating pollution issues. Current research predominantly focuses on energy-saving and emission reduction in road transportation within individual cities or the three major economic regions of China:the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei Region. However, there is a dearth of studies addressing the southeastern coastal economic region. Located at the heart of China's southeastern coastal economic development, the provinces of Guangdong, Fujian, and Zhejiang unavoidably face challenges associated with energy consumption and emissions while pursuing economic growth. To address these challenges, this study employed a LEAP model to construct various scenarios for road transportation in the key coastal cities of Guangdong, Fujian, and Zhejiang from 2015 to 2035. These scenarios included a baseline scenario (BAU), an existing policy scenario (EPS), and an improved policy scenario (MPS). The MPS and EPS encompassed vehicle structure optimization (VSO), improved fuel economy (IFE), and reduced annual average mileage (RDM). By simulating and evaluating these scenarios, the energy-saving and emission reduction potentials of road transportation in the key coastal cities were assessed. The results indicated that, in the primary scenario, the MPS exhibited the most significant improvements in energy-saving, carbon reduction, and pollutant reduction effects. By 2035, the MPS achieved a remarkable 75% energy-saving rate compared to that in the baseline scenario, accompanied by reductions of 68%, 59%, 66%, 70%, and 64% in CO2, CO, NOx, PM2.5, and SO2 emissions, respectively. In the secondary scenario, the improved scenario of enhancing fuel economy achieved a notable 30% reduction in energy consumption. Additionally, the scenarios involving vehicle structure adjustment (yielding reductions of 36%, 30%, 36%, 26%, and 40%) and annual average mileage reduction (resulting in reductions of 37%, 37%, 36%, 37%, and 36%) demonstrated significant reductions in CO2, CO, NOx, PM2.5, and SO2 emissions.

Impact of different grade roads on ecological networks: A case study of Fuzhou City, China.

The expansion of roads exacerbates the fragmentation of ecological networks and obstructs landscape connectivity. Scientific analysis of the impacts of different grades of roads on landscape connectivity and ecological networks is crucial for guiding road planning and ecological conservation. Based on the data of 2020 road network, land cover types, and digital elevation models, we used morphological spatial pattern analysis and circuit theory to construct ecological networks within different species dispersal distances (1, 3, 5, 10 km) in Fuzhou. We analyzed the impacts of roads of different grades (motorway, urban expressway, primary and secondary highway) on landscape connectivity at the landscape-patch-corridor scale. The results showed that at the landscape scale, overall landscape connectivity was significantly positively correlated with species dispersal distance. The motorway, urban expressway, primary and secondary highway had the lowest decline rate of overall landscape connectivity within a 10 km species dispersal range, being reduced by 15.6%, 5.3%, 1.5% and 5.2%, respectively. At the patch scale, in the comparison of roads of different grades, motorway led to the highest decline rate of patch connectivity within 1 and 5 km species dispersal range, while primary highway led to the highest decline rate of patch connectivity within 3 and 10 km species dispersal range. At the corridor scale, urban expressway led the highest increase rate of indices. The cost-weighted distance of the overall least-cost path, the ratio of cost-weighted distance to length, ove-rall effective resistance, and total corridor length within 5 km species dispersal range were increased by 43.4%, 33.2%, 57.3%, and 7.3%, respectively. As the distance of species dispersal increased, the patches with high importance were reduced from the northern, central, and northwestern regions to the northern regions, leading to a decrease in the living space of species, and the key corridors were gradually extending from the northwestern and southern regions to the central regions. Our results can guide the construction and optimization of Fuzhou's ecological network from an overall perspective, and provide a scientific basis for biodiversity conservation, ecological restoration, and road network planning under the context of limited land resource utilization.

Spatio-temporal evolution characteristics of carbon emissions from road transportation in the mainland of China from 2006 to 2021.

The leaping forward of the economy has promoted the rapid growth of road traffic demand, resulting in the carbon emissions of road traffic increasing significantly. It is well known that a one-size-fits-all emission reduction policy is not feasible. Therefore, conducting an investigation on the carbon emissions of all provincial-level regions within a country can assist the government in formulating carbon emission policies at a macro level tailored to different regions. In this study, the whole provincial-level administrative regions in the mainland of China were selected to quantify the carbon emissions of road traffic, and the carbon emissions from 2006 to 2021 were obtained by employing the top-down model. What's more, spatiotemporal characteristics of road transportation carbon emissions in those regions were explored based on Moran's I spatial autocorrelation method. In addition, the LMDI model was constructed based on five driving factors, namely energy intensity, energy consumption intensity, industrial scale, economic development, and population size, and the decomposition analysis of driving factors is carried out. The results show that carbon emissions from road traffic in all provincial regions showed an overall rising trend in the research period, with an average annual growth rate of 11.83 %. The distribution of road transportation carbon emissions exhibited an east-high, west-low distribution, with significantly higher emissions in the eastern and coastal regions compared to inland areas, additionally, China's seven geographical regions showed an initial rapid increase in carbon emissions followed by a stable growth trend. Secondly, five types of spatial clustering were identified of carbon emissions within provincial regions. Thirdly, the impacts of energy intensity and industrial scale were detrimental to road transportation carbon emissions, whereas economic development, energy consumption intensity, and population size had contrasting effects. Implications according to the above conclusions were put forward, aiming to provide guidance for the sustainable development of road transportation and expediting the achievement of the "carbon peaking and carbon neutrality" objective.

Characterizing nighttime vertical profiles of atmospheric particulate matter and ozone in a megacity of south China using unmanned aerial vehicle measurements.

Daytime atmospheric pollution has received wide attention, while the vertical structures of atmospheric pollutants at night play a crucial role in the photochemical process on the following day, which is still less reported. Focusing on Guangzhou, a megacity of South China, we established an unmanned aerial vehicle (UAV) equipped with micro detectors to collect consecutive high-resolution samples of fine particle (PM2.5), submicron particle (PM1.0), black carbon (BC) and ozone (O3) concentrations in the atmosphere, as well as the air temperature (AT) and relative humidity (RH) within a 500 m altitude during nighttime from Oct. 24th to Nov. 6th, 2018. The measurements showed that PM2.5, PM1.0, and BC decreased with altitude and were influenced by the nighttime shallow planetary boundary layer (PBL) where BC was more accumulated and fluctuated. In contrast, O3 was positively correlated with altitude. Backward trajectory clustering and Pasquill stability classification showed that advection and convection significantly influenced the vertical distribution of all pollutants, particularly particulate matter. External air masses carrying high concentrations of pollutants increased PM1.0 and PM2.5 levels by 145% and 455%, respectively, compared to unaffected periods. The ratio of BC to PM2.5 indicated that local emissions had a minor role in nighttime particulate matter. Vertical transport caused by atmospheric instability reduced the differences in pollutant concentrations at various heights. Geodetector and generalized additive model showed that RH and BC accumulation in the PBL were significant factors influencing vertical changes of the secondary aerosol intensity as indicated by the ratio of PM1.0 to PM2.5. The joint explanation of RH and atmospheric stability with other variables such as BC is essential to understand the generation of secondary aerosols. These findings provide insights into regional and local measures to prevent and control night-time particulate matter pollution.

Lockdown effects of the COVID-19 on the spatio-temporal distribution of air pollution in Beijing, China.

To prevent the spread of COVID-19, China enacted a series of strict policies, which reduced anthropogenic activities to a near standstill. This provided a precious window to explore its effects on the spatio-temporal distribution of air pollution in Beijing, China. In this study, continuous wavelet transforms and spatial interpolation methods were used to explore the spatiotemporal variations in air pollutants and their lockdown effects. The results indicate that except O3, the annual average concentration of NO2, PM2.5 and SO2 showed a decreasing trend during 2016 and 2019; NO2, PM2.5 and SO2 show a trend of "low in summer and high in winter"; the diurnal variation of NO2 concentration was mainly related to the rush hours of traffic volume, with the first peak at the morning peak (7:00), and then accumulating gradually to second peak (22:00). The continuous wavelet analysis shows that PM2.5, SO2 and NO2 had four primary periods, while O3 only had two primary periods. The high NO2 concentration areas were mainly in Dongcheng, Xicheng, Chaoyang and Fengtai, while the low concentration areas were located in the northern areas, such as Miyun and Huairou; the PM2.5 concentration decreased from south to north; this characteristic presented more obviously in winter. Compared to the pre-lockdown, NO2 and SO2 decreased considerably during lockdown, whereas PM2.5 and O3 increased dramatically. The contribution rates of transportation activities to the NO2, O3, PM2.5 and SO2 were estimated be 9.4 % ∼ 17.2 %, -76.4 % ∼ -42.9 %, -39.5 % ∼ -22.8 % and 5.7 % ∼ 43.7 %, respectively; the contribution rates of industrial activities were 19.9 % ∼ 26.7 %, 7.8 % ∼ 30.9 %, 1.6 % ∼ 36.2 % and -10.5 % ∼ 15.9 %, respectively. Considering meteorological factors, we inferred that pauses in anthropogenic activities indeed help improving air pollution, but it is difficult to offset the impact of extreme weather. These findings can enhance our understanding on the sources of air pollution, and can therefore provide insights on urban air pollution mitigation.

Does leakage exist in China's typical protected areas? Evidence from 13 national nature reserves.

There is profound interest in knowing the degree to which the effectiveness of China's nature reserves, and whether leakage is common around the reserves, in the face of the most drastic conflicts between conservation and development in the world. To answer these questions, we employed the Landsat-derived Global Forest Change Dataset with 30-m resolution to examine forest change patterns during 2001 and 2017 both inside and outside of 13 typically national nature reserves in China. The average forest loss rates inside the reserves were significantly lower than those of outside the reserves (i.e., both in buffer and landscape zones), suggesting the success in protecting forest of these reserves in China. We found that the protection practice reduced approximately 10% of deforestation. Protection efficiency may be substantially overestimated (about 13-43%) if failing to control the related variables, such as altitude, climate, and human interference. The forest loss rates in the buffer zones were not significantly higher than those in the broader landscape zones, suggesting that leakage is not a frequent occurrence in the buffer zones of the reserves. However, the forest loss rates showed a slightly increasing tendency from 2001 to 2017, the loss rates increased gradually from inside to their outside buffer zones, and leakage was observed in certain zones of some years for most of the reserves. The conversions of forest to grassland and cultivated land were the primary trajectories of forest loss both inside and outside of the reserves. Though the leakage is not universal in the reserves across the country, forest loss rates are much higher in the buffer zones than those inside the reserves, resulting in increased insulation of the reserves that could undermine the provisioning of ecosystem services and the biodiversity conservation efficiency.

Quantifying public health benefits of PM2.5 reduction and spatial distribution analysis in China.

In recent years, particulate matter (PM) air pollution has become a significant and growing public health problem in China. In this study, the daily PM2.5 exposure level at a spatial resolution of 100 km2 was simulated based on the data of 1328 monitoring sites and the Voronoi Neighborhood Averaging (VNA) interpolation method. The results reveal that the daily mean PM2.5 concentration reduced from 47.82 µg/m3 (2016) to 40.87 µg/m3 (2018), a reduction of 14.53%. We first calculated the heath impacts and economic benefits of this reduction (Scenario 1) by using Environmental Benefits Mapping and Analysis Program (BenMAP). The estimated avoided premature mortalities for all-cause, cardiovascular diseases, respiratory diseases, and lung cancer were in the range of 7214 to 81,681 cases (total of 154,176 cases). The estimated economic benefits based on willingness to pay (WTP) ranged from 3.96 to 44.85 billion RMB (total of 84.66 billion RMB). Moreover, the PM2.5 concentration in the control scenario was rolled back to the Grade I standards (35 µg/m3, Scenario 2). The avoided deaths are in the range of 58,820 to 590,464 cases (total of 1,217,671 cases). The estimated monetary value of the avoided cases of all health endpoints range from 36.63 to 367.66 billion RMB based on WTP (total of 758.21 billion RMB). In addition, the spatial autocorrelation analysis reveals that the distribution of both avoided premature mortality and economic benefits exhibit a certain spatial aggregation.

Spatial variability of urban climate in response to quantitative trait of land cover based on GWR model.

Land surface temperature and moisture are central components of the Earth's surface heat budget. China has experienced substantial land use/cover change that has led to deterioration of the urban microclimate, thus affecting global climate change. Understanding the spatial non-stationarity in the relationships between climate and land cover across a highly heterogeneous surface of urban landscapes is important for improving urban planning and management. This study used Landsat-8 OLI/TIRS data to explore the relationship of the three components (index-based built-up index (IBI); bare soil index (SI); and normalized difference vegetation index (NDVI)) with the urban climate (land surface temperature (LST) and land surface moisture (LSM)) using both a global model (ordinary least squares (OLS)) and a local model (geographically weighted regression (GWR)) for a megacity in Southeast China. The global regression results showed that there were significant positive correlations between the LST and the IBI and SI, while significant negative correlations were observed between the LST and the NDVI; opposite results were observed for the LSM. The IBI is the factor having the greatest impact on the LST, while the SI is among the most important factors for the LSM. The local regression results showed that the response of urban climate to land surface is affected greatly by water areas, but the role of the water areas is impacted by their size and surrounding landscape patterns. Moreover, the effects of vegetation and built-up land on the urban climate vary across locations with different wind patterns.

A new remote sensing index based on the pressure-state-response framework to assess regional ecological change.

Ecological indicators have widespread appeal to scientists, environmental managers, and the general public. Remote sensing is unique in its capability to record variety of spatio-temporal information on land surface with complete coverage, especially with regard to larger spatial scales, which has been proven to be an effective data source to create indicators to rapidly identify regional eco-environment. In this paper, a new index, remote sensing based ecological index (RSEI) based on the pressure-state-response (PSR) framework, was applied to assess regional ecological changes in Fuzhou City of Fujian Province, southeastern China, using Landsat ETM+/OLI/TIRS images. Taking the advantages of being totally free of artificial interference in the calculation using principal components analysis (PCA) to assign weights of each variable, the RSEI can assess the regional ecological status more objectively and easily. The effectivity of the new index was validated by four approaches, including point-based, classification-based, correlation-based, and urban-rural-gradient-based comparisons. The case study showed that Fuzhou has witnessed ecological improvement during the study period, with the value of RSEI increasing from 0.663 in 2000 to 0.675 in 2016. Spatial variation analysis showed that the poor level of RSEI distributed mostly in the central urban areas, and the ecological degradation was attributed to the fast expansion of the built-up area, characterized by increasing greatly in the value of the normalized differential built up and soil index (NDBSI) in such areas.

Effects of road network on diversiform forest cover changes in the highest coverage region in China: An analysis of sampling strategies.

Forest cover changes are of global concern due to their roles in global warming and biodiversity. However, many previous studies have ignored the fact that forest loss and forest gain are different processes that may respond to distinct factors by stressing forest loss more than gain or viewing forest cover change as a whole. It behooves us to carefully examine the patterns and drivers of the change by subdividing it into several categories. Our study includes areas of forest loss (4.8% of the study area), forest gain (1.3% of the study area) and forest loss and gain (2.0% of the study area) from 2000 to 2012 in Fujian Province, China. In the study area, approximately 65% and 90% of these changes occurred within 2000m of the nearest road and under road densities of 0.6km/km(2), respectively. We compared two sampling techniques (systematic sampling and random sampling) and four intensities for each technique to investigate the driving patterns underlying the changes using multinomial logistic regression. The results indicated the lack of pronounced differences in the regressions between the two sampling designs, although the sample size had a great impact on the regression outcome. The application of multi-model inference indicated that the low level road density had a negative significant association with forest loss and forest loss and gain, the expressway density had a positive significant impact on forest loss, and the road network was insignificantly related to forest gain. The model including socioeconomic and biophysical variables illuminated potentially different predictors of the different forest change categories. Moreover, the multiple comparisons tested by Fisher's least significant difference (LSD) were a good compensation for the multinomial logistic model to enrich the interpretation of the regression results.

The pollutants from livestock and poultry farming in China-geographic distribution and drivers.

Livestock and poultry farming is a major source of agricultural pollution. However, our knowledge of the constraining factors of the geographic distribution of pollutants from livestock and poultry farming is still limited. In this study, using the optimized pollutant generation coefficients, we estimated the annual pollutant productions of eight livestock and poultry species at the provincial level in 2005 and 2013 and their growth rates during the study period in China; using canonical correlation analysis, we also explored the association between the eight pollutant measurements as dependent variables and 14 factors (including resource endowment, developmental level, and economic structure factors) as independent variables. Results indicate that there exist spatial disparity in the distribution of pollutants from livestock and poultry farming across regions, with provinces in the Huang-Huai-Hai region and the southwestern region accounting for approximately 50 % of the total productions in the nation. Cattle, pig, and poultry constitute the primary pollution sources in terms of livestock and poultry farming not only at the national level but also at the province level. While the species constitute and their respective growth rates of the pollutants can be also characterized by spatial disparity across regions, canonical correlation analysis shows that the observed regional patterns of the pollutants can be largely explained by the resource endowment factors (positive effects) and the developmental level factors (negative effects). In addition, we found that the development of livestock and poultry farming is negatively associated with the growing rate of both the resource endowment and the socioeconomic factors. This indicates that there exist different driving patterns in the gross and increment of the pollutant productions. Our research has significant implications for the appropriate environmental protection policy formulation and implementation in livestock sector.

Geographic variations of ecosystem service intensity in Fuzhou City, China.

Ecosystem services are strongly influenced by the landscape configuration of natural and human systems. So they are heterogeneous across landscapes. However lack of the knowledge of spatial variations of ecosystem services constrains the effective management and conservation of ecosystems. We presented a spatially explicit and quantitative assessment of the geographic variations in ecosystem services for the Fuzhou City in 2009 using exploratory spatial data analysis (ESDA) and semivariance analysis. Results confirmed a significant and positive spatial autocorrelation, and revealed several hot-spots and cold-spots for the spatial distribution of ecosystem service intensity (ESI) in the study area. Also the trend surface analysis indicated that the level of ESI tended to be reduced gradually from north to south and from west to east, with a trough in the urban central area, which was quite in accordance with land-use structure. A more precise cluster map was then developed using the range of lag distance, deriving from semivariance analysis, as neighborhood size instead of default value in the software of ESRI ArcGIS 10.0, and geographical clusters where population growth and land-use pressure varied significantly and positively with ESI across the city were also created by geographically weighted regression (GWR). This study has good policy implications applicable to prioritize areas for conservation or construction, and design ecological corridor to improve ecosystem service delivery to benefiting areas.