Apparatus and method for selection of a transport

1 . An apparatus for projected carbon emissions of a transport, the apparatus comprising:

at least a processor; and

a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to:

receive freight data associated with a transport request;

determine one or more transport configurations as a function of the freight data, wherein each transport configuration of the one or more transport configurations comprises a temporal element based on a projected transport journey having one or more transport routes;

retrieve a plurality of previously collected data for the one or more transport routes and a list of drivers corresponding to the one or more transport routes;

generate a carbon projection module, wherein the carbon projection module utilizes the plurality of previously collected data to determine what an increase or decrease in carbon emissions is attributable to;

generate a projected carbon emission for each transport configuration of the one or more transport configurations as a function of the freight data using the carbon projection module, wherein generating the projected carbon emission comprises:

receiving the one or more transport routes associated with a projected transport journey;

determining a projected carbon block for each transport route of the one or more transport routes using historical route data; and

generating the projected carbon emission for each transport configuration of the one or more transport configurations as a function of the projected carbon block for each transport route of the one or more transport routes associated with a projected transport journey;

generate a carbon deviation as a function of the projected carbon emission for each transport configuration of the one or more transport configurations and route obstruction data;

apply the carbon deviation to the projected carbon emission for each transport configuration of the one or more transport configurates; and

output an integrated projected carbon emission for each transport configuration of the one or more transport configurations.

2 . The apparatus of claim 1 , wherein determining a projected carbon block for each transport route of the one or more transport routes comprises:

determining a carbon emission for each of one or more transport carriers associated with a transport route using historic route data;

generating an average of the carbon emissions for each of the one or more transport carriers associated with a transport route; and

generating a projected carbon block as a function of the average of the carbon emissions for each of the one or more transport carriers associated with a transport route.

3 . The apparatus of claim 2 , wherein determining a carbon emission for each of the one or more transport carriers associated with a transport route comprises calculating the carbon emission based on an average energy consumption.

4 . The apparatus of claim 1 , wherein determining the projected carbon block for each transport route comprises:

instantiating a projection machine-learning model;

inputting the one or more transport routes into the projection machine-learning model;

generating, at the projection machine-learning model, a projected carbon block for each of the one or more transport routes; and

outputting the projected carbon blocks for each of the one or more transport routes to a requesting party.

5 . The apparatus of claim 4 , wherein instantiating the projection machine-learning model comprises:

receiving projected carbon training data comprising a plurality of transport routes correlated to a plurality of projected carbon blocks;

training a projection machine learning model as a function of the projected carbon training data; and

determining the projected carbon block as a function of the projection machine learning model, wherein the projection machine learning model is iteratively trained with transport routes correlated to carbon blocks.

6 . The apparatus of claim 5 , wherein the projection machine-learning model is configured to generate a linear regression for each transport route, wherein one or more known variables are input into a linear regression equation to generate a plurality of projected carbon blocks.

7 . The apparatus of claim 6 , wherein the one or more known variables comprises a plurality of historic traffic data.

8 . The apparatus of claim 6 , wherein the one or more known variables comprises a plurality of live map data from one or more data providers.

9 . The apparatus of claim 6 , wherein the one or more known variables comprises transport route variables, wherein transport route variables comprise one or more of elevation data, geographic data, population density data, or road work data.

10 . The apparatus of claim 1 , wherein the at least a processor is further configured to display, at a display device, the projected carbon emission for each transport configuration, wherein the projected carbon emission for each transport configuration is segmented into the one or more transport routes associated with a transport configuration comprising the projected carbon block.

11 . A method for projected carbon emissions of a transport, the method comprising:

receiving freight data associated with a transport request;

determining one or more transport configurations as a function of the freight data, wherein each transport configuration of the one or more transport configurations comprises a temporal element based on a projected transport journey having one or more transport routes;

retrieving a plurality of previously collected data for the one or more transport routes and a list of drivers corresponding to the one or more transport routes;

generating a carbon projection module, wherein the carbon projection module utilizes the plurality of previously collected data to determine what an increase or decrease in carbon emissions is attributable to;

generating a projected carbon emission for each transport configuration of the one or more transport configurations as a function of the freight data using the carbon projection module, wherein generating the projected carbon emission comprises:

receiving the one or more transport routes associated with a projected transport journey;

determining a projected carbon block for each transport route of the one or more transport routes using historical route data; and

generating the projected carbon emission for each transport configuration of the one or more transport configurations as a function of the projected carbon block for each transport route of the one or more transport routes associated with a projected transport journey;

generating a carbon deviation as a function of the projected carbon emission for each transport configuration of the one or more transport configurations and route obstruction data;

applying the carbon deviation to the projected carbon emission for each transport configuration of the one or more transport configurates; and

outputting an integrated projected carbon emission for each transport configuration of the one or more transport configurations.

12 . The method of claim 11 , wherein determining a projected carbon block for each transport route of the one or more transport routes comprises:

determining a carbon emission for each of one or more transport carriers associated with a transport route using historic route data;

generating an average of the carbon emission for each of the one or more transport carriers associated with a transport route; and

generating a projected carbon block as a function of the average of the carbon emissions for each of the one or more transport carriers associated with a transport route.

13 . The method of claim 12 , wherein determining a carbon emission for each of the one or more transport carriers associated with a transport route comprises calculating the carbon emission based on an average energy consumption.

14 . The method of claim 11 , wherein determining the projected carbon block for each transport route comprises:

instantiating a projection machine-learning model

inputting the one or more transport routes into the projection machine-learning model;

generating, at the projection machine-learning model, a projected carbon block for each of the one or more transport routes; and

outputting the projected carbon blocks for each of the one or more transport routes to a requesting party.

15 . The method of claim 14 , wherein instantiating the projection machine-learning model comprises:

receiving projected carbon training data comprising a plurality of transport routes correlated to a plurality of projected carbon blocks;

training a projection machine learning model as a function of the projected carbon training data; and

determining the projected carbon block as a function of the projection machine learning model, wherein the projection machine learning model is iteratively trained with transport routes correlated to carbon blocks.

16 . The method of claim 15 , wherein the projection machine-learning model is configured to generate a linear regression equation for each transport route, wherein one or more known variables are input into the linear regression equation to generate a plurality of projected carbon blocks.

17 . The method of claim 16 , wherein the one or more known variables comprises a plurality of historic traffic data.

18 . The method of claim 16 , wherein the one or more known variables comprises a plurality of live map data from one or more data providers.

19 . The method of claim 16 , wherein the one or more known variables comprises transport route variables, wherein transport route variables comprise one or more of elevation data, geographic data, population density data or road work data.

20 . The method of claim 11 , wherein the method further comprises displaying, at a display device, the projected carbon emission for each transport configuration, wherein the projected carbon emission for each transport configuration is segmented into the one or more transport routes associated with a transport configuration comprising the projected carbon block.