Da Zhang

Dr. Da Zhang

College of Geography and Ocean Sciences, Yanbian University, Yanji 133000, China
orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 March 2024 in Nature Communications
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Journal Article
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HYHuanbi Yue
Huanbi Yue
CHChunyang He
Chunyang He
QHQingxu Huang
Qingxu Huang
Da ZhangDa Zhang
Da Zhang
PSPeijun Shi
Peijun Shi
Brett BryanBrett Bryan
Brett Bryan
The United Nations’ Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP.

24 November 2020 in Sustainability
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YZYanan Zhang
Yanan Zhang
RJRi Jin
Ri Jin
WZWeihong Zhu
Weihong Zhu
Da ZhangDa Zhang
Da Zhang
XZXiaoxue Zhang
Xiaoxue Zhang
Climate change and global rapid agricultural expansion have drastically reduced the area of wetlands globally recently, so that the ecosystem functions of wetlands have been impacted severely. Therefore, this study integrated the land use data and the integrated valuation of ecosystem services and tradeoffs (InVEST) model to evaluate the impacts of the land-use change (LUC) on wetland ecosystem services (ES) from 1976 to 2016 in the Tumen River Basin (TRB). Results reveal that the area of wetlands in TRB had decreased by 22.39% since 1976, mainly due to the rapid conversion of wetlands to dry fields and construction lands, and the LUC had induced notable geospatial changes in wetland ES consequently. A marked decrease in carbon storage and water yield was observed, while the habitat quality was enhanced slightly. Specifically, the conversion of rivers and paddy fields to ponds and reservoirs were the main reasons for the increase in habitat quality and caused the habitat quality to increase by 0.09. The conversion of marshes to lakes, paddy fields, grasslands, dry fields, and artificial surfaces were the key points for the decline in carbon storage; the conversion of marshes to lakes (5.38 km2) and reservoir ponds (1.69 km2) were the dominant factors driving the losses of water yield. According to our results, we should center on the conservation of wetlands and rethink the construction of the land use. The findings are expected to provide a theoretical reference and basis for promoting environmental protection in TRB and the construction of ecological civilization in border areas.

25 March 2023 in Applied Sciences
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HFHengdong Feng
Hengdong Feng
Xiaoguang ZhangXiaoguang Zhang
Xiaoguang Zhang
YNYing Nan
Ying Nan
Da ZhangDa Zhang
Da Zhang
YSYan Sun
Yan Sun
Ecological sensitivity is one of the important indicators of regional ecological fragility, which can represent the sensitivity of ecosystems to natural environmental conditions and human activity disturbances in the region. In this study, the ecological sensitivity of land resources in the Tumen River Basin of China was quantitatively evaluated by taking 3 ecologically sensitive impact types, including the natural environment, human disturbance, and soil erosion, as evaluation criteria, and 11 ecologically sensitive factors were selected to build an evaluation system using the analytic hierarchy process (AHP) method, to determine the weights of the evaluation factors, combined with geographic information system (GIS) technology. The results show that: (1) Among the three types of ecological sensitivity factors, the influence of human disturbance is the most obvious, and the two factors of land use type and distance from construction land have the highest weights in the comprehensive ecological sensitivity evaluation. (2) There are no extremely sensitive areas or insensitive areas in the Tumen River Basin in China. Highly sensitive areas account for only 0.59% of the total area and are mainly concentrated in the lakes, rivers, and reservoirs in the study area. Moderately sensitive areas account for 54.12%, which are concentrated in the central part of the Tumen River Basin Slightly sensitive areas are mainly located in the mountainous areas in the north and south of the study area. (3) Among the various land resource types, the proportion of slightly sensitive areas and moderately sensitive areas of woodland is close (about 50%), while cultivated land, grassland, construction land, and bare land are mainly moderately sensitive areas (73.95%, 82.07%, 96.59%, and 78.78%), and water bodies are mostly distributed within highly sensitive areas (60.97%), and all wetlands with the smallest area are moderately sensitive. The results of the study can provide data support and a scientific basis for regional ecological protection and development planning.

5 March 2023 in Land Degradation & Development
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Da ZhangDa Zhang
Da Zhang
YNYing Nan
Ying Nan
WZWeihong Zhu
Weihong Zhu
CHChunyang He
Chunyang He
Zhifeng LiuZhifeng Liu
Zhifeng Liu
YYYanmin Yang
Yanmin Yang

31 August 2019 in Frontiers of Earth Science
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JWJianwen Wang
Jianwen Wang
Da ZhangDa Zhang
Da Zhang
YNYing Nan
Ying Nan
Zhifeng LiuZhifeng Liu
Zhifeng Liu
DQDekang Qi
Dekang Qi

14 July 2020 in Chinese Geographical Science
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YNYing Nan
Ying Nan
BWBingbing Wang
Bingbing Wang
Da ZhangDa Zhang
Da Zhang
Zhifeng LiuZhifeng Liu
Zhifeng Liu
DQDekang Qi
Dekang Qi
HZHaohao Zhou
Haohao Zhou