Current Inventory Research Articles

Research progress on nanotechnology of traditional Chinese medicine to enhance the therapeutic effect of osteoarthritis.

Osteoarthritis (OA) is a prevalent chronic condition that primarily impacts the articular cartilage and surrounding bone tissue, resulting in joint inflammation and structural deterioration. The etiology of OA is multifaceted and intricately linked to the oxidative stress response of joint tissue. Oxidative stress (OS) in OA leads to the creation of reactive oxygen species (ROS) and other oxidizing agents, resulting in detrimental effects on chondrocytes. This oxidative damage diminishes the flexibility and robustness of cartilage, thereby expediting the progression of joint deterioration. Therefore, the antioxidant effect is crucial in the treatment of OA. Currently, a considerable number of components found in traditional Chinese medicine (TCM) have been scientifically demonstrated to exhibit remarkable antioxidant and anti-inflammatory properties. Nevertheless, the utilization of this program is considerably constrained as a result of intrinsic deficiencies, notably stability concerns. The successful amalgamation of TCM components with nanotechnology has properly tackled these concerns and enhanced the efficacy of therapeutic results. The objective of this study is to delineate the antioxidant characteristics of nano-TCM and assess the current inventory of literature pertaining to the application of nano-TCM in the treatment of OA. In conclusion, this paper will now turn to the constraints and potential avenues for the advancement of nano-TCM within the realm of OA therapy.

A glacial lake outburst floods hazard assessment in the Patagonian Andes combining inventory data and case-studies

We present a glacial-related lake inventory for a region spanning 41.5° - 47° S in Patagonian Andes, where information on past glacier lake outburst floods (GLOF's) has hitherto remained significantly underreported. Analyzing remotely sensed images, we obtained data on 702 glacial-related lakes. Through detailed geomorphic assessments and manual supervision, we revised current inventories and added 35 GLOFs triggered from moraine/bedrock dammed lakes failures. The regional GLOF inventory presented contains information on 71 historical failures of moraine/bedrock dammed glacial lakes. From this database we analyzed outburst timing and managed to constrain 37 events occurrences within a period of 1 year. Around 40 % of them have occurred since the early 2000's, most of them originating from lakes probably formed as a delayed response to the glacial retreat imposed by the end of the Little Ice Age. On the other hand, we analyzed meteorological conditions for a sub-set of 10 events constrained within a 10-days period, finding a strong link between atmospheric rivers, cut-off lows impacting the southern Andes, and GLOFs. Only one case is likely to have been triggered by a Mw 4.9 earthquake. Based on topographic potential for avalanching, we estimated GLOF hazard potential, recognizing at least 3 subregions with high hazard, which moreover can be highly susceptible to climate conditions that regionally affect GLOF occurrence.

Current status of model predictions of volatile organic compounds and impacts on surface ozone predictions during summer in China

Abstract. Volatile organic compounds (VOCs) play a crucial role in the formation of tropospheric ozone (O3) and secondary organic aerosols. VOC emissions are generally considered to have larger uncertainties compared to other pollutants, such as sulfur dioxide and fine particulate matter (PM2.5). Although predictions of O3 and PM2.5 have been extensively evaluated in air quality modeling studies, there has been limited reporting on the evaluation of VOCs, mainly due to a lack of routine VOC measurements at multiple sites. In this study, we utilized VOC measurements from the “Towards an Air Toxic Management System in China” (ATMSYC) project at 28 sites across China and assessed the predicted VOC concentrations using the Community Multiscale Air Quality (CMAQ) model with the widely used Multi-resolution Emission Inventory for China (MEIC). The ratio of predicted to observed total VOCs was found to be 0.74 ± 0.40, with underpredictions ranging from 2.05 to 50.61 ppbv (5.77 % to 85.40 %) at 24 sites. A greater bias in VOC predictions was observed in industrial cities in the north and southwest, such as Jinan, Shijiazhuang, Lanzhou, Chengdu, and Guiyang. In terms of different VOC components, alkanes, alkenes, non-naphthalene aromatics (ARO2MN), alkynes, and formaldehyde (HCHO) had prediction-to-observation ratios of 0.53 ± 0.38, 0.51 ± 0.48, 0.31 ± 0.38, 0.41 ± 0.47, and 1.21 ± 1.61, respectively. Sensitivity experiments were conducted to assess the impact of the VOC prediction bias on O3 predictions. While emission adjustments improved the model performance for VOCs, resulting in a change in the ratio of total VOCs to 0.86 ± 0.47, they also exacerbated O3 overprediction relative to the base case by 0.62 % to 6.27 % across the sites. This study demonstrates that current modeling setups and emission inventories are likely to underpredict VOC concentrations, and this underprediction of VOCs contributes to lower O3 predictions in China.

In Situ Sampling of NOx Emissions from United States Natural Gas Flares Reveals Heavy-Tail Emission Characteristic.

Natural gas flaring is a common practice employed in many United States (U.S.) oil and gas regions to dispose of gas associated with oil production. Combustion of predominantly hydrocarbon gas results in the production of nitrogen oxides (NOx). Here, we present a large field data set of in situ sampling of real world flares, quantifying flaring NOx production in major U.S. oil production regions: the Bakken, Eagle Ford, and Permian. We find that a single emission factor does not capture the range of the observed NOx emission factors within these regions. For all three regions, the median emission factors fall within the range of four emission factors used by the Texas Commission for Environmental Quality. In the Bakken and Permian, the distribution of emission factors exhibits a heavy tail such that basin-average emission factors are 2-3 times larger than the value employed by the U.S. Environmental Protection Agency. Extrapolation to basin scale emissions using auxiliary satellite assessments of flare volumes indicates that NOx emissions from flares are skewed, with 20%-30% of the flares responsible for 80% of basin-wide flaring NOx emissions. Efforts to reduce flaring volume through alternative gas capture methods would have a larger impact on the NOx oil and gas budget than current inventories indicate.

Digital Twin and Asset Management for Italian highways decision support towards scheduled maintenance, repair and rehab

This paper describes Sina’s current inventory and inspection system (SIOS) development with BIM (Building Information Modelling) applications and BMS (Bridge Management System) strategies towards an Asset Management system implementation. Procedures and data flows using Sina databases SIOS (Sistema Ispettivo Opere Sina inventory and inspection data, seismic vulnerability analysis database, etc.) as inputs supporting BIM modelling are described. Starting from a first project, which is currently being applied to an entire highway agency and which also envisages a later integration of tunnels, a BIM modelling procedure was developed to reach information models for an “inspection” “BIM USE”. Such information models, populated with the information necessary for bridge management system processing, have been connected to Business Intelligence tools to create dashboards supporting decision-making criteria based on management and maintenance approaches (Bridge and Asset Management System). In addition, for Asset Management development, the approach of decision-making tools, integrated with a multi-level approach of Italian Guidelines For The Classification And Management Of Risk, The Assessment Of Safety And The Monitoring Of Existing Bridges, can convey information flows to support criteria planning to choose routine and extraordinary maintenance and restoring interventions. The project illustrated in this paper shows how integrating technologies, methodologies, experience and knowledge must be supported by consistent information management towards companies’ digital transformation and asset management development as a decision-making tool based on enabling technologies.

Potential application of GBIF platform for flora inventory of Karaganda region

The current biodiversity inventory has important scientific and practical implications for the country. In Kazakhstan, data on the flora of spore and vascular plants are outdated; there is a significant gap in assessing the current species composition of certain regions of Kazakhstan, including Central Kazakhstan (Karaganda and Ulytau regions). The problems of formation of a modern flora abstract are determined by the need to use the entire volume of accumulated information, both for individual findings of naturalists and multi-year collections in domestic and international herbarium collections. When carrying out research to analyze the current state of the flora of Karaganda region, the GBIF platform resources containing information on the biological diversity of flora and fauna were used. Data analysis showed that the platform has more than 130 thousand records of vascular plant finds for the territory of Kazakhstan, including 2241 records for Karaganda region with geo-referencing. The main funds containing the largest number of collections made on the territory of our region were determined. The stages of data processing and geo-linking of herbarium collections are defined. In general, a high potential for supplementing field collections with GBIF data to clarify the distribution of individual taxa and make range maps was determined.

A current and annotated inventory of the faunal diversity found on the Anna University campus in Tamil Nadu, India

The variety of creatures that are endemic or local to a certain area and that reside there is referred to as faunal diversity. It includes platyhelminths, odonatan, reptiles (predators), hymenopteran, lepidopteran (pollinators), molluscan, avifauna and mammals. An assessment of animal variety explains the food, habitat, ecology, and population of the various species. A survey was carried out to assess the condition of the faunal diversity at Anna University in Chennai. The study's objectives were to list and define the many animal groups belongs to families, genera, and species that inhabit the region, along with information on their habitats and distribution. A total of 85 species, discovered during the course of a year, from May 2023 to November 2023, are included in the study. There were 85 species in 7 phyla. With 55 species, or 64.71% of all species, the Arthropodan has the largest species abundance of any other group. Only one of the 85 species of Platyhelminthes, the hammer-headed worm (Diversibipalium), was found in the vicinity of the university green garden between September and November of 2023 (Vijayan et al., 2023). The observational study found that the area's green spaces, diversity of flora, and water features contributed to its importance as a habitat for a range of animal species. In order to promote biodiversity conservation efforts and offer habitat for animal species, the study highlights the importance of maintaining or growing green spaces at educational institutions.

Using Atmospheric Inverse Modelling of Methane Budgets with Copernicus Land Water and Wetness Data to Detect Land Use-Related Emissions

Climate change mitigation requires countries to report their annual greenhouse gas (GHG) emissions and sinks, including those from land use, land use change, and forestry (LULUCF). In Finland, the LULUCF sector plays a crucial role in achieving net-zero GHG emissions, as the sector is expected to be a net sink. However, accurate estimates of LULUCF-related GHG emissions, such as methane (CH4), remain challenging. We estimated LULUCF-related CH4 emissions in Finland in 2013–2020 by combining national land cover and remote-sensed surface wetness data with CH4 emissions estimated by an inversion model. According to our inversion model, most of Finland’s CH4 emissions were attributed to natural sources such as open pristine peatlands. However, our research indicated that forests with thin tree cover surrounding open peatlands may also be a significant source of CH4. Unlike open pristine peatlands and pristine peatlands with thin tree cover, surrounding transient forests are included in the Finnish GHG inventory if they meet the criteria used for forest land. The current Finnish national GHG inventory may therefore underestimate CH4 emissions from forested organic soils surrounding open peatlands, although more precise methods and data are needed to verify this. Given the potential impact on net GHG emissions, CH4 emissions from transitional forests on organic soils should be further investigated. Furthermore, the results demonstrate the potential of combining atmospheric inversion modelling of GHGs with diverse data sources and highlight the need for methods to more easily combine atmospheric inversions with national GHG inventories.

Financial and health impact of two models of providing prostheses in a public health systemImpacto econômico e sanitário de dois modelos de fornecimento de próteses em um sistema público de saúde

Compare the health outcomes and financial outcomes of two systems for the procurement of prostheses: the traditional system, in which procurement is initiated when a product is requested; and the "Prosthesis Bank" model, based on a current inventory of supplies. Descriptive-analytical study of users of Ministry of Health services in the province of Buenos Aires, Argentina. The patients belonged to two study groups: 1) prostheses were provided through the traditional computerized system for hospital procurement and contracting, known as SIPACH; and 2) prostheses were provided by the Prosthesis Bank. The study was limited to endovascular prostheses (coronary stents) and hip prostheses. Official government databases were used. The study period was from 01/01/2018 to 31/10/2022. The variables analyzed were: age, sex, diagnosis, hospital, type of implant or prosthesis, date of request, date received, unit price, direct and indirect costs, average cost of daily hospitalization, cost-effectiveness, and budgetary impact. A total of 4 106 applications were analyzed. In the traditional system: 13.5% of patients did not get their prostheses; it took 50 days longer than with the Prosthesis Bank; and total costs were higher in SIPACH (coronary stent, +463%; hip prosthesis, +133%). The Prosthesis Bank saved USD 3.2 million annually and prevented 22 deaths through early provision of endovascular prostheses. The Prosthesis Bank proved to be superior to the traditional model for providing prostheses, both in terms of health-by achieving better access, shortening waiting times, and avoiding deaths-and financially-by significantly reducing unit and overall prices, achieving significant savings in allocated budgets.

Evaluation of the behavior of BTEX at Beijing and Seoul in winter and summer using observations and 3-D modeling

Aromatic volatile organic compounds (VOCs) including benzene, toluene, ethylbenzene, xylene, and trimethylbenzene (BTEX) are known to contribute the most to the formation of ozone and secondary organic aerosols (SOA) in an urban atmosphere and their representation in chemical transport models (CTM) is still uncertain. In this study, we evaluated the model representation of BTEX concentrations and their seasonal difference at Beijing and Seoul using the GEOS-Chem CTM and ground observations from the Fine particle Research Initiative in East Asia considering National Differences (FRIEND) project in winter and summer. The model captured different levels of observed BTEX at Beijing and Seoul, where benzene (BENZ) was comparable and toluene + ethylbenzene (TOLU) and xylenes + trimethylbenzenes (XYLE) were higher at Seoul. The observed seasonal variations of BTEX were similar at both sites, with benzene being higher in winter and TOLU and XYLE being higher in summer. However, the magnitude and seasonal variation of TOLU at Seoul and BENZ at Beijing were not reproduced by the model. TOLU was underestimated in both seasons at Seoul especially in summer due to the underestimation of emission rates and evaporative emission being not included in the current emission inventory. At Beijing, BENZ was underestimated especially in winter and showed no seasonal variation which was different from the observations. Underestimated benzene emission rates or missing sources of it cause discrepancies between observed and modeled benzene concentrations at Beijing.

Four decades of full-scale nitrous oxide emission inventory in China.

China is among the top nitrous oxide (N2O)-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade (1980-2020) of comprehensive quantification of Chinese N2O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N2O emissions peaked at 2287.4 (1774.8-2799.9) Gg N2O yr-1 in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N2O-emitting regions. Agricultural N2O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N2O emissions from agriculture, industry, energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020, respectively, which revealed that it is imperative to prioritize N2O emission mitigation in agriculture, industry, and energy. Natural N2O sources, dominated by forests, have been steadily growing from 317.3 (290.3-344.1) Gg N2O yr-1 in 1980 to 376.2 (335.5-407.2) Gg N2O yr-1 in 2020. Our study produces a Full-scale Annual N2O dataset in China (FAN2020), providing emergent counting to refine the current national N2O inventories.

Emissions of wood pelletization and bioenergy use in the United States

Despite a significant increase in United States biomass energy sector activity, including domestic bioenergy deployment and wood pellet production for overseas exports, the associated criteria pollutant emissions are not well quantified in current regulatory emissions inventories. We present an updated U.S. emissions inventory, with emphasis on wood-based biomass pretreatment (e.g., drying, condensing, storage of wood pellet) and the use of biomass for energy generation. As a significant number of wood pellet production facilities are not included in current inventories, we find that this sector's emissions could be potentially underestimated by a factor of two. Emissions from biomass-based facilities are on average up to 2.8 times higher than their non-biomass counterparts per unit energy. We estimate that 2.3 million people live within 2 km of a biomass facility and who could be subject to adverse health impacts from their emissions. Overall, we find that the bioenergy sector contributes to about 3–17% of total emissions from all energy, i.e., electric and non-electric generating facilities in the U.S. We also review some drivers of bioenergy expansion, such as various feedstocks and technologies deployed with an emphasis on wood-based bioenergy and discuss their implications for future air quality and health impacts.

Emission characteristics of biogenic volatile organic compounds in a subtropical pristine forest of southern China

Emission characteristics of biogenic volatile organic compounds (BVOCs) from dominant tree species in the subtropical pristine forests of China are extremely limited. Here we conducted in situ field measurements of BVOCs emissions from representative mature evergreen trees by using dynamic branch enclosures at four altitude gradients (600–1690 m a.s.l.) in the Nanling Mountains of southern China. Composition characteristics as well as seasonal and altitudinal variations were analyzed. Standardized emission rates and canopy-scale emission factors were then calculated. Results showed that BVOCs emission intensities in the wet season were generally higher than those in the dry season. Monoterpenes were the dominant BVOCs emitted from most broad-leaved trees, accounting for over 70% of the total. Schima superba, Yushania basihirsuta and Altingia chinensis had relatively high emission intensities and secondary pollutant formation potentials. The localized emission factors of isoprene were comparable to the defaults in the Model of Emissions of Gases and Aerosols from Nature (MEGAN), while emission factors of monoterpenes and sesquiterpenes were 2 to 58 times of those in the model. Our results can be used to update the current BVOCs emission inventory in MEGAN, thereby reducing the uncertainties of BVOCs emission estimations in forested regions of southern China.

National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations

Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a−1 for oil-gas and 32.7 ± 5.2 Tg a−1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a−1 or 18%.

An exploratory approach to estimate point emission sources

The current atmospheric emission inventories do not fully meet the spatial and temporal resolution requirements of air quality modelling applications. Considering Portugal as a case study and focusing on combustion point emission sources (i.e., public power, refineries, manufacturers, and construction activities), this work proposes a methodological approach and dataset to estimate anthropogenic emissions suitable for different spatial scales (from regional to local). The obtained results were similar to the annual values reported by the Portuguese Environment Agency with the maximum emissions being estimated for manufacturing and construction activities. No significant differences were recorded between the temporal profiles developed in this and previous studies. However, the country-specific proxies from the developed database allowed us to better represent the temporal and spatial patterns of the Portuguese atmospheric emissions. The combination of the BigAir database with a comprehensive and standardized approach could help policymakers define mitigation and/or plan measures to reduce emissions from point sources, support countries worldwide (with a lack of data) to develop high-resolution emission inventories, and improve the current global and European inventories.

Estimation of natural methane emissions from the largest oil sand deposits on earth.

Worldwide methane emission by various industrial sources is one of the important human concerns due to its serious climate and air-quality implications. This study investigates less-considered diffusive natural methane emissions from the world's largest oil sand deposits. An analytical model, considering the first-order methane degradation, in combination with Monte Carlo simulations, is used to quantitatively characterize diffusive methane emissions from Alberta's oil sands formations. The results show that the average diffusive methane emissions from Alberta's oil sands formations is 1.56 × 10-4 kg/m2/year at the 90th percentile of cumulative probability. The results also indicate an annual diffusive methane emissions rate of 0.857 ± 0.013 Million tons of CO2e/year (MtCO2e/year) from Alberta's oil sands formations. This finding suggests that natural diffusive leakages from the oil sands contribute an additional 1.659 ± 0.025 and 5.194 ± 0.079% to recent Canada's 2019 and Alberta's 2020 methane emission estimates from the upstream oil and gas sector, respectively. The developed model combined with Monte Carlo simulations can be used as a tool for assessing methane emissions and current inventories.

Synopsis of the family Convolvulaceae in Mexico

The Convolvulaceae is a diverse family and it is particularly well represented in Mexico. The current inventory confirms the presence of 313 species within Mexico, and this quantity represents nearly 20% of the family’s global diversity. Convolvulaceae species are found in all states of our country but are most frequent at elevations below 1500 m. The preferred habitat is tropical deciduous forest and secondary communities derived from it. Whereas most species are herbaceous to woody climbers, it is noteworthy that some species are arborescent, and the distribution of this growth form is essentially Mexican, with a few species in the Andes.

An improved hourly-resolved atmospheric NOx emission inventory of industrial sources based on Continuous Emission Monitoring System data: Case of Jiangsu Province, China

Current emission inventories with low spatial and temporal resolutions, slow updates, and great uncertainty can no longer meet the new demands for the precise prevention and control of air pollution. This study considered industrial sources of Jiangsu province in 2018 as the research object and divided key industrial sources into 16 processes. Based on the continuous emission monitoring system (CEMS) data of key enterprises, millions of hourly scale monitoring data from 17842-point source enterprises at 169289 emission outlets were collected. An hourly scale high-resolution industrial source NOx emission inventory was constructed and compared with existing inventories. The total NOx emissions of power plants, industrial boilers, ferrous metal manufacturing, non-metallic mineral manufacturing, and chemical manufacturing industries in Jiangsu Province in 2018 were 55, 27, 64, 28, and 3 Gg, respectively. The total emissions from industrial sources were high in summer, reaching a peak of 17 Gg in July, and low in winter, reaching 11 Gg in February. The emission factors of the power plants, coking, and cement industries decreased by 15.95%, 29.03%, and 51.61%, respectively. Hourly scales showed that the power plants had the most considerable fluctuation in 24 h emissions at 5.94%, with high emissions occurring in the afternoon and at night. However, the 24 h emissions of ferrous metal manufacturing fluctuated slightly, at only 3.22%, and the high emissions mostly occurred at night. The WRF-Chem model was used for simulation validation. The NO2 simulation results based on this study's inventory were significantly better than those based on the Multi-resolution Emission Inventory for China (MEIC), with normalized mean biases (NMBs) of −7.1% and −10.7% for January and July, respectively, as opposed to 30.8% and 14.4% in the MEIC. The hourly scale high-precision emission inventory established in this study is significant for formulating real-time differentiated precise prevention and control policies and improving the accuracy of air quality models.

Real world emission characteristics of Chinese fleet and the current situation of underestimated ship emissions

Ships are considered important contributors to air pollution and have seriously health impact globally. Although many researchers have carried out studies on emission factors (EFs) in recent years, studies covering various types of ships are rare and the chemical characteristics of particulate matter (PM) emitted by them are unclear. Due to the diversity of different national fleets, the current emission inventory in China established by citing foreign EFs will lead to inaccurate calculation results and generate large uncertainty. In this study, the EFs for ocean-going, harbour, offshore and inland vessels were measured by the portable emission measurement system (PEMS). The specific compositions of PM were analyzed, including carbonaceous components, water-soluble ions (WSI), elements, and polycyclic aromatic hydrocarbons (PAHs). Combined with localized EFs, the ship emission inventory of Qingdao Port was established based on Automatic Identification System (AIS) data. The results show nitrogen oxide (NOx) is the primary pollutant discharged by all ships, followed by sulfur dioxide (SO2). The emissions of SO2 and PM from inland and offshore vessels fueled with high sulfur fuel (HSF) are significantly higher than other ships. Carbonaceous components accounted for 43.4%–53.9% of the total mass of PM, WSI accounted for 9.8%–14.3%, and elements accounted for 16.5%–28.6%. Although the use of low sulfur fuel (LSF) has reduced the emission of V and Ni from ships, it could still be treated as tracer elements of ship emissions. The annual emissions of SO2, NOX, PM2.5, THC and CO from ships in Qingdao port in 2020 were 9728.5, 38503.9, 1424.9, 1331.5 and 2440.4 tons, respectively. The ship emission inventory established based on EPA-recommended EFs resulted in underestimating approximately 16.8% of ship pollutants, especially for SO2 and PM. Ocean-going ships and offshore vessels are major emitters in the study waters. This study is hoped to provide a valuable reference for the further regulation and policy formulation of ship emissions in China.

Uncovering the CO2 emissions of vehicles: A well-to-wheel approach

Carbon dioxide (CO2) from road traffic is a non-negligible part of global greenhouse gas (GHG) emissions, and it is a challenge for the world today to accurately estimate road traffic CO2 emissions and formulate effective emission reduction policies. Current emission inventories for vehicles have either low-resolution, or limited coverage, and they have not adequately focused on the CO2 emission produced by new energy vehicles (NEV) considering fuel life cycle. To fill the research gap, this paper proposed a framework of a high-resolution well-to-wheel (WTW) CO2 emission estimation for a full sample of vehicles and revealed the unique CO2 emission characteristics of different categories of vehicles combined with vehicle behavior. Based on this, the spatiotemporal characteristics and influencing factors of CO2 emissions were analyzed with the geographical and temporal weighted regression (GTWR) model. Finally, the CO2 emissions of vehicles under different scenarios are simulated to support the formulation of emission reduction policies. The results show that the distribution of vehicle CO2 emissions shows obvious heterogeneity in time, space, and vehicle category. By simply adjusting the existing NEV promotion policy, the emission reduction effect can be improved by 6.5%–13.5% under the same NEV penetration. If combined with changes in power generation structure, it can further release the emission reduction potential of NEVs, which can reduce the current CO2 emissions by 78.1% in the optimal scenario.